A SIMPLE CELLULAR AUTOMATON MODEL FOR HIGH-LEVEL VEGETATION DYNAMICS

EPA Science Inventory

We have produced a simple two-dimensional (ground-plan) cellular automata model of vegetation dynamics specifically to investigate high-level community processes. The model is probabilistic, with individual plant behavior determined by physiologically-based rules derived from a w...

Woody-Herbaceous Species Coexistence in Mulga Hillslopes: Modelling Structure and Function

NASA Astrophysics Data System (ADS)

Soltanjalili, M. J.; Saco, P. M.; Willgoose, G. R.

2016-12-01

The fundamental processes underlying the coexistence of woody and herbaceous species in arid and semi-arid areas have been a topic of intense research during the last few decades. Experimental and modelling studies have both supported and disputed alternative hypotheses explaining this phenomenon. Vegetation models including the key processes that drive coexistence can be used to understand vegetation pattern dynamics and structure under current climate conditions, and to predict changes under future conditions. Here we present work done towards linking the observations to modelling. The model captures woody-herbaceous coexistence along a rainfall gradient characteristic of typical conditions on Mulga ecosystems in Australia. The dynamic vegetation model simulates the spatial dynamics of overland flow, soil moisture and vegetation growth of two species. It incorporates key mechanisms for coexistence and pattern formation, including facilitation by evaporation reduction through shading, and infiltration feedbacks, local and non-local seed dispersal, competition for water uptake. Model outcomes, obtained including diflerent mechanisms, are qualitatively compared to typical vegetation cover patterns in the Australian Mulga bioregion where bush fire is very infrequent and the fate of vegetation cover is mostly determined by intra- and interspecies interactions. Through these comparisons, and by drawing on the large number of recent studies that have delivered new insights into the dynamics of such ecosystems, we identify main mechanisms that need an improved representation in the dynamic vegetation models. We show that a realistic parameterization of the model leads to results which are aligned with the observations reported in the literature. At the lower end of the rainfall gradient woody species coexist with herbaceous species within a sparse banded pattern, while at higher rainfall woody species tend to dominate the landscape.

Dynamics of riparian plant communities, a new integrative ecohydrological modelling approach

NASA Astrophysics Data System (ADS)

García-Arias, Alicia; Francés, Félix

2015-04-01

The Riparian Vegetation Dynamic Model (RVDM) integrates the impacts of the hydrological extremes on the vegetation, the vegetation evolution and the competition between different vegetation classes. Considering a daily time step and a detailed spatial resolution, RVDM allows the analysis of the dynamic vegetation distribution in riverine areas during a simulated period. The riparian vegetation wellbeing and distribution are considered to be conditioned by the river hydrodynamics in RVDM. Using biomass loss functions, the stress caused by hydrological extreme events is translated into changes on the distribution of the vegetation. These extreme events are considered as removal and asphyxia associated to floods, and wilt related to droughts. The variables considered to determine the impacts are water shear stress, water table elevation and the soil moisture, respectively. RVDM includes the modelling of the natural evolution of the vegetation. The potential recruitment in bared areas, the plant growth and the succession/retrogression between plant categories are included in the model conceptualization. The recruitment takes place when seeds presence, germination and seedlings establishment overcome, so it depends on the plant reproductive period and the environmental conditions. Light use efficiency determines the vegetation growth in terms of biomass production while the soil moisture limits this biomass production and the successional evolution. Finally, the competition modelling considers the advantages between successional patterns under the specific soil moisture conditions of each unit area. Several meteorological, morphological, hydrological and hydraulic inputs are required. In addition, an initial vegetation condition is required for RVDM to start the simulation period. The model results on new vegetation maps that are considered as new inputs in the next model step. Following this approach the model simulates iteratively al the processes day by day. This model represents an improvement respect to previous models in the way of understanding the riparian dynamics. Currently, RVDM has been already implemented in a Mediterranean semi-arid river reach and a sensitivity analysis to analyze the influence of the different vegetation parameters has been performed. The good results obtained indicate that the model is suitable for scenarios analysis and for environmental flows establishment.

Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2016-04-01

Dynamic global vegetation models (DGVMs) are an important platform to study past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks (e.g. Sitch et al. 2008, Smith et al. 2001). However, very few attempts have been made to simulate peatlands using DGVMs (Kleinen et al. 2012, Tang et al. 2015, Wania et al. 2009a). In the present study, we have improved the peatland dynamics in the state-of-the-art dynamic vegetation model (LPJ-GUESS) in order to understand the long-term evolution of northern peatland ecosystems and to assess the effect of changing climate on peatland carbon balance. We combined a dynamic multi-layer approach (Frolking et al. 2010, Hilbert et al. 2000) with soil freezing-thawing functionality (Ekici et al. 2015, Wania et al. 2009a) in LPJ-GUESS. The new model is named LPJ-GUESS Peatland (LPJ-GUESS-P) (Chaudhary et al. in prep). The model was calibrated and tested at the sub-arctic mire in Stordalen, Sweden, and the model was able to capture the reported long-term vegetation dynamics and peat accumulation patterns in the mire (Kokfelt et al. 2010). For evaluation, the model was run at 13 grid points across a north to south transect in Europe. The modelled peat accumulation values were found to be consistent with the published data for each grid point (Loisel et al. 2014). Finally, a series of additional experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We find that the Stordalen mire will sequester more carbon in the future due to milder and wetter climate conditions, longer growing seasons, and the carbon fertilization effect. References: - Chaudhary et al. (in prep.). Modelling Holocene peatland and permafrost dynamics with the LPJ-GUESS dynamic vegetation model - Ekici A, et al. 2015. Site-level model intercomparison of high latitude and high altitude soil thermal dynamics in tundra and barren landscapes. The Cryosphere 9: 1343-1361. - Frolking S, Roulet NT, Tuittila E, Bubier JL, Quillet A, Talbot J, Richard PJH. 2010. A new model of Holocene peatland net primary production, decomposition, water balance, and peat accumulation. Earth Syst. Dynam., 1, 1-21, doi:10.5194/esd-1-1-2010, 2010. - Hilbert DW, Roulet N, Moore T. 2000. Modelling and analysis of peatlands as dynamical systems. Journal of Ecology 88: 230-242. - Kleinen T, Brovkin V, Schuldt RJ. 2012. A dynamic model of wetland extent and peat accumulation: results for the Holocene. Biogeosciences 9: 235-248. - Kokfelt U, Reuss N, Struyf E, Sonesson M, Rundgren M, Skog G, Rosen P, Hammarlund D. 2010. Wetland development, permafrost history and nutrient cycling inferred from late Holocene peat and lake sediment records in subarctic Sweden. Journal of Paleolimnology 44: 327-342. - Loisel J, et al. 2014. A database and synthesis of northern peatland soil properties and Holocene carbon and nitrogen accumulation. Holocene 24: 1028-1042. - Sitch S, et al. 2008. Evaluation of the terrestrial carbon cycle, future plant geography and climate-carbon cycle feedbacks using five Dynamic Global Vegetation Models (DGVMs). Global Change Biology 14: 2015-2039. - Smith B, Prentice IC, Sykes MT. 2001. Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecology and Biogeography 10: 621-637. - Tang J, et al. 2015. Carbon budget estimation of a subarctic catchment using a dynamic ecosystem model at high spatial resolution. Biogeosciences 12: 2791-2808. - Wania R, Ross I, Prentice IC. 2009a. Integrating peatlands and permafrost into a dynamic global vegetation model: 1. Evaluation and sensitivity of physical land surface processes. Global Biogeochemical Cycles 23.

Hydrological Validation of The Lpj Dynamic Global Vegetation Model - First Results and Required Actions

NASA Astrophysics Data System (ADS)

Haberlandt, U.; Gerten, D.; Schaphoff, S.; Lucht, W.

Dynamic global vegetation models are developed with the main purpose to describe the spatio-temporal dynamics of vegetation at the global scale. Increasing concern about climate change impacts has put the focus of recent applications on the sim- ulation of the global carbon cycle. Water is a prime driver of biogeochemical and biophysical processes, thus an appropriate representation of the water cycle is crucial for their proper simulation. However, these models usually lack thorough validation of the water balance they produce. Here we present a hydrological validation of the current version of the LPJ (Lund- Potsdam-Jena) model, a dynamic global vegetation model operating at daily time steps. Long-term simulated runoff and evapotranspiration are compared to literature values, results from three global hydrological models, and discharge observations from various macroscale river basins. It was found that the seasonal and spatial patterns of the LPJ-simulated average values correspond well both with the measurements and the results from the stand-alone hy- drological models. However, a general underestimation of runoff occurs, which may be attributable to the low input dynamics of precipitation (equal distribution within a month), to the simulated vegetation pattern (potential vegetation without anthro- pogenic influence), and to some generalizations of the hydrological components in LPJ. Future research will focus on a better representation of the temporal variability of climate forcing, improved description of hydrological processes, and on the consider- ation of anthropogenic land use.

Exploring the role of fire, succession, climate, and weather on landscape dynamics using comparative modeling

Treesearch

Robert E. Keane; Geoffrey J. Cary; Mike D. Flannigan; Russell A. Parsons; Ian D. Davies; Karen J. King; Chao Li; Ross A. Bradstock; Malcolm Gill

2013-01-01

An assessment of the relative importance of vegetation change and disturbance as agents of landscape change under current and future climates would (1) provide insight into the controls of landscape dynamics, (2) help inform the design and development of coarse scale spatially explicit ecosystem models such as Dynamic Global Vegetation Models (DGVMs), and (3) guide...

Soil Water Balance and Vegetation Dynamics in two Water-limited Mediterranean Ecosystem on Sardinia under past and future climate change

NASA Astrophysics Data System (ADS)

Corona, R.; Montaldo, N.; Albertson, J. D.

2016-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Historical human influences (e.g., deforestation, urbanization) further altered these ecosystems. Sardinia island is a representative region of Mediterranean ecosystems. It is low urbanized except some plan areas close to the main cities where main agricultural activities are concentrated. Two contrasting case study sites are within the Flumendosa river basin (1700 km2). The first site is a typical grassland on an alluvial plan valley (soil depth > 2m) while the second is a patchy mixture of Mediterranean vegetation species (mainly wild olive trees and C3 herbaceous) that grow in a soil bounded from below by a rocky layer of basalt, partially fractured (soil depth 15 - 40 cm). In both sites land-surface fluxes and CO2 fluxes are estimated by the eddy correlation technique while soil moisture was continuously estimated with water content reflectometers, and periodically leaf area index (LAI) was estimated. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics; 3) evaluate the impact of past and future climate change scenarios on the two contrasting ecosystems. For reaching the objectives an ecohydrologic model that couples a vegetation dynamic model (VDM), and a 3-component (bare soil, grass and woody vegetation) land surface model (LSM) has been used. Historical meteorological data are available from 1922 and hydro-meteorological scenarios are then generated using a weather generator. The VDM-LSM model predict soil water balance and vegetation dynamics for the generated hydrometeorological scenarios in the two contrasting ecosystems. Results demonstrate that vegetation dynamics are influenced by the inter-annual variability of atmospheric forcing, with vegetation density changing significantly according to seasonal rainfall amount. At the same time the vegetation dynamics affect the soil water balance.

Predicting Changes in Arctic Tundra Vegetation: Towards an Understanding of Plant Trait Uncertainty

NASA Astrophysics Data System (ADS)

Euskirchen, E. S.; Serbin, S.; Carman, T.; Iversen, C. M.; Salmon, V.; Helene, G.; McGuire, A. D.

2017-12-01

Arctic tundra plant communities are currently undergoing unprecedented changes in both composition and distribution under a warming climate. Predicting how these dynamics may play out in the future is important since these vegetation shifts impact both biogeochemical and biogeophysical processes. More precise estimates of these future vegetation shifts is a key challenge due to both a scarcity of data with which to parameterize vegetation models, particularly in the Arctic, as well as a limited understanding of the importance of each of the model parameters and how they may vary over space and time. Here, we incorporate newly available field data from arctic Alaska into a dynamic vegetation model specifically developed to take into account a particularly wide array of plant species as well as the permafrost soils of the arctic tundra (the Terrestrial Ecosystem Model with Dynamic Vegetation and Dynamic Organic Soil, Terrestrial Ecosystem Model; DVM-DOS-TEM). We integrate the model within the Predicative Ecosystem Analyzer (PEcAn), an open-source integrated ecological bioinformatics toolbox that facilitates the flows of information into and out of process models and model-data integration. We use PEcAn to evaluate the plant functional traits that contribute most to model variability based on a sensitivity analysis. We perform this analysis for the dominant types of tundra in arctic Alaska, including heath, shrub, tussock and wet sedge tundra. The results from this analysis will help inform future data collection in arctic tundra and reduce model uncertainty, thereby improving our ability to simulate Arctic vegetation structure and function in response to global change.

Next generation dynamic global vegetation models: learning from community ecology (Invited)

NASA Astrophysics Data System (ADS)

Scheiter, S.; Higgins, S.; Langan, L.

2013-12-01

Dynamic global vegetation models are a powerful tool to project past, current and future vegetation patterns and the associated biogeochemical cycles. However, most models are limited by their representation of vegetation by using static and pre-defined plant functional types and by their simplistic representation of competition. We discuss how concepts from community assembly theory and coexistence theory can help to improve dynamic vegetation models. We present a trait- and individual-based dynamic vegetation model, the aDGVM2, that allows individual plants to adopt a unique combination of trait values. These traits define how individual plants grow, compete and reproduce under the given biotic and abiotic conditions. A genetic optimization algorithm is used to simulate trait inheritance and reproductive isolation between individuals. These model properties allow the assembly of plant communities that are adapted to biotic and abiotic conditions. We show (1) that the aDGVM2 can simulate coarse vegetation patterns in Africa, (2) that changes in the environmental conditions and disturbances strongly influence trait diversity and the assembled plant communities by influencing traits such as leaf phenology and carbon allocation patterns of individual plants and (3) that communities do not necessarily return to the initial state when environmental conditions return to the initial state. The aDGVM2 deals with functional diversity and competition fundamentally differently from current models and allows novel insights as to how vegetation may respond to climate change. We believe that the aDGVM2 approach could foster collaborations between research communities that focus on functional plant ecology, plant competition, plant physiology and Earth system science.

Implementing seasonal carbon allocation into a dynamic vegetation model

NASA Astrophysics Data System (ADS)

Vermeulen, Marleen; Kruijt, Bart; Hickler, Thomas; Forrest, Matthew; Kabat, Pavel

2014-05-01

Long-term measurements of terrestrial fluxes through the FLUXNET Eddy Covariance network have revealed that carbon and water fluxes can be highly variable from year-to-year. This so-called interannual variability (IAV) of ecosystems is not fully understood because a direct relation with environmental drivers cannot always be found. Many dynamic vegetation models allocate NPP to leaves, stems, and root compartments on an annual basis, and thus do not account for seasonal changes in productivity in response to changes in environmental stressors. We introduce this vegetation seasonality into dynamic vegetation model LPJ-GUESS by implementing a new carbon allocation scheme on a daily basis. We focus in particular on modelling the observed flux seasonality of the Amazon basin, and validate our new model against fluxdata and MODIS GPP products. We expect that introducing seasonal variability into the model improves estimates of annual productivity and IAV, and therefore the model's representation of ecosystem carbon budgets as a whole.

Vegetation-hydrology dynamics in complex terrain of semiarid areas: 1. A mechanistic approach to modeling dynamic feedbacks

NASA Astrophysics Data System (ADS)

Ivanov, Valeriy Y.; Bras, Rafael L.; Vivoni, Enrique R.

2008-03-01

Vegetation, particularly its dynamics, is the often-ignored linchpin of the land-surface hydrology. This work emphasizes the coupled nature of vegetation-water-energy dynamics by considering linkages at timescales that vary from hourly to interannual. A series of two papers is presented. A dynamic ecohydrological model [tRIBS + VEGGIE] is described in this paper. It reproduces essential water and energy processes over the complex topography of a river basin and links them to the basic plant life regulatory processes. The framework focuses on ecohydrology of semiarid environments exhibiting abundant input of solar energy but limiting soil water that correspondingly affects vegetation structure and organization. The mechanisms through which water limitation influences plant dynamics are related to carbon assimilation via the control of photosynthesis and stomatal behavior, carbon allocation, stress-induced foliage loss, as well as recruitment and phenology patterns. This first introductory paper demonstrates model performance using observations for a site located in a semiarid environment of central New Mexico.

On modeling the organization of landscapes and vegetation patterns controlled by solar radiation

NASA Astrophysics Data System (ADS)

Istanbulluoglu, E.; Yetemen, O.

2014-12-01

Solar radiation is a critical driver of ecohydrologic processes and vegetation dynamics. Patterns of runoff generation and vegetation dictate landscape geomorphic response. Distinct patterns in the organization of soil moisture, vegetation type, and landscape morphology have been documented in close relation to aspect in a range of climates. Within catchments, from north to south facing slopes, studies have shown ecotone shifts from forest to shrub species, and steep diffusion-dominated landforms to fluvial landforms. Over the long term differential evolution of ecohydrology and geomorphology leads to observed asymmetric structure in the planform of channel network and valley morphology. In this talk we present examples of coupled modeling of ecohydrology and geomorphology driven by solar radiation. In a cellular automata model of vegetation dynamics we will first show how plants organize in north and south facing slopes and how biodiversity changes with elevation. When vegetation-erosion feedbacks are coupled emergent properties of the coupled system are observed in the modeled elevation and vegetation fields. Integrating processes at a range of temporal and spatial scales, coupled models of ecohydrologic and geomorphic dynamics enable examination of global change impacts on landscapes and ecosystems.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

NASA Astrophysics Data System (ADS)

Jiao, Yang; Lei, Huimin; Yang, Dawen; Huang, Maoyi; Liu, Dengfeng; Yuan, Xing

2017-08-01

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of eco-hydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of the Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965-1969) from -0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010-2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.

Impact of vegetation dynamics on hydrological processes in a semi-arid basin by using a land surface-hydrology coupled model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jiao, Yang; Lei, Huimin; Yang, Dawen

Land surface models (LSMs) are widely used to understand the interactions between hydrological processes and vegetation dynamics, which is important for the attribution and prediction of regional hydrological variations. However, most LSMs have large uncertainties in their representations of ecohydrological processes due to deficiencies in hydrological parameterizations. In this study, the Community Land Model version 4 (CLM4) LSM was modified with an advanced runoff generation and flow routing scheme, resulting in a new land surface-hydrology coupled model, CLM-GBHM. Both models were implemented in the Wudinghe River Basin (WRB), which is a semi-arid basin located in the middle reaches of themore » Yellow River, China. Compared with CLM, CLM-GBHM increased the Nash Sutcliffe efficiency for daily river discharge simulation (1965–1969) from 0.03 to 0.23 and reduced the relative bias in water table depth simulations (2010–2012) from 32.4% to 13.4%. The CLM-GBHM simulations with static, remotely sensed and model-predicted vegetation conditions showed that the vegetation in the WRB began to recover in the 2000s due to the Grain for Green Program but had not reached the same level of vegetation cover as regions in natural eco-hydrological equilibrium. Compared with a simulation using remotely sensed vegetation cover, the simulation with a dynamic vegetation model that considers only climate-induced change showed a 10.3% increase in evapotranspiration, a 47.8% decrease in runoff, and a 62.7% and 71.3% deceleration in changing trend of the outlet river discharge before and after the year 2000, respectively. This result suggests that both natural and anthropogenic factors should be incorporated in dynamic vegetation models to better simulate the eco-hydrological cycle.« less

Co-evolution of Riparian Vegetation and Channel Dynamics in an Aggrading Braided River System, Mount Pinatubo, Philippines

NASA Astrophysics Data System (ADS)

Gran, K. B.; Michal, T.

2014-12-01

Increased bank stability by riparian vegetation in braided rivers can decrease bed reworking rates and focus the flow. The magnitude of influence and resulting channel morphology are functions of vegetation strength vs. channel dynamics, a concept encapsulated in a dimensionless ratio between timescales for vegetation growth and channel reworking known as T*. We investigate this relationship in an aggrading braided river at Mount Pinatubo, Philippines, and compare results to numerical and physical models. Gradual reductions in post-eruption sediment loads have reduced bed reworking rates, allowing vegetation to persist year-round and impact channel dynamics on the Pasig-Potrero and Sacobia Rivers. From 2009-2011, we collected data detailing vegetation extent, type, density, and root strength. Incorporating these data into RipRoot and BSTEM models shows cohesion due to roots increased from zero in unvegetated conditions to >10.2 kPa in densely-growing grasses. Field-based parameters were incorporated into a cellular model comparing vegetation growth and sediment mobility effects on braided channel dynamics. The model shows that both low sediment mobility and high vegetation strength lead to less active systems, reflecting trends observed in the field. An estimated T* between 0.8 - 2.3 for the Pasig-Potrero River suggests channels were mobile enough to maintain the braidplain width clear of vegetation and even experience slight gains in area through annual removal of existing vegetation. However, persistent vegetation focused flow and thus aggradation over the unvegetated fraction of braidplain, leading to an aggradational imbalance and transition to a more avulsive state. While physical models predict continued narrowing of the active braidplain as T* declines, the future trajectory of channel-vegetation interactions at Pinatubo as sedimentation rates decline appears more complicated due to strong seasonal variability in precipitation and sediment loads. By 2011, seasonal incision in the dry season had started to occur, lowering the water-table, and impeding vegetation growth.

Assessing global climate-terrestrial vegetation feedbacks on carbon and nitrogen cycling in the earth system model EC-Earth

NASA Astrophysics Data System (ADS)

Wårlind, David; Miller, Paul; Nieradzik, Lars; Söderberg, Fredrik; Anthoni, Peter; Arneth, Almut; Smith, Ben

2017-04-01

There has been great progress in developing an improved European Consortium Earth System Model (EC-Earth) in preparation for the Coupled Model Intercomparison Project Phase 6 (CMIP6) and the next Assessment Report of the IPCC. The new model version has been complemented with ocean biogeochemistry, atmospheric composition (aerosols and chemistry) and dynamic land vegetation components, and has been configured to use the recommended CMIP6 forcing data sets. These new components will give us fresh insights into climate change. This study focuses on the terrestrial biosphere component Lund-Potsdam-Jena General Ecosystem Simulator (LPJ-GUESS) that simulates vegetation dynamics and compound exchange between the terrestrial biosphere and the atmosphere in EC-Earth. LPJ-GUESS allows for vegetation to dynamically evolve, depending on climate input, and in return provides the climate system and land surface scheme with vegetation-dependent fields such as vegetation types and leaf area index. We present the results of a study to examine the feedbacks between the dynamic terrestrial vegetation and the climate and their impact on the terrestrial ecosystem carbon and nitrogen cycles. Our results are based on a set of global, atmosphere-only historical simulations (1870 to 2014) with and without feedback between climate and vegetation and including or ignoring the effect of nitrogen limitation on plant productivity. These simulations show to what extent the addition degree of freedom in EC-Earth, introduced with the coupling of interactive dynamic vegetation to the atmosphere, has on terrestrial carbon and nitrogen cycling, and represent contributions to CMIP6 (C4MIP and LUMIP) and the EU Horizon 2020 project CRESCENDO.

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-11-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use LPJ-GUESS, a dynamic vegetation model employing a detailed individual- and patch-based representation of vegetation dynamics, to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one representative "business-as-usual" climate scenario). Single-factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model as documented in previous studies using other global models. Under an RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics up to the present. However, during the 21st century, nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contrasts with previous results with other global models that have shown an 8 to 37% decrease in carbon uptake relative to modern baseline conditions. Implications for the plausibility of earlier projections of future terrestrial C dynamics based on C-only models are discussed.

Inter-species competition-facilitation in stochastic riparian vegetation dynamics.

PubMed

Tealdi, Stefano; Camporeale, Carlo; Ridolfi, Luca

2013-02-07

Riparian vegetation is a highly dynamic community that lives on river banks and which depends to a great extent on the fluvial hydrology. The stochasticity of the discharge and erosion/deposition processes in fact play a key role in determining the distribution of vegetation along a riparian transect. These abiotic processes interact with biotic competition/facilitation mechanisms, such as plant competition for light, water, and nutrients. In this work, we focus on the dynamics of plants characterized by three components: (1) stochastic forcing due to river discharges, (2) competition for resources, and (3) inter-species facilitation due to the interplay between vegetation and fluid dynamics processes. A minimalist stochastic bio-hydrological model is proposed for the dynamics of the biomass of two vegetation species: one species is assumed dominant and slow-growing, the other is subdominant, but fast-growing. The stochastic model is solved analytically and the probability density function of the plant biomasses is obtained as a function of both the hydrologic and biologic parameters. The impact of the competition/facilitation processes on the distribution of vegetation species along the riparian transect is investigated and remarkable effects are observed. Finally, a good qualitative agreement is found between the model results and field data. Copyright © 2012 Elsevier Ltd. All rights reserved.

Noise-induced transitions and shifts in a climate-vegetation feedback model.

PubMed

Alexandrov, Dmitri V; Bashkirtseva, Irina A; Ryashko, Lev B

2018-04-01

Motivated by the extremely important role of the Earth's vegetation dynamics in climate changes, we study the stochastic variability of a simple climate-vegetation system. In the case of deterministic dynamics, the system has one stable equilibrium and limit cycle or two stable equilibria corresponding to two opposite (cold and warm) climate-vegetation states. These states are divided by a separatrix going across a point of unstable equilibrium. Some possible stochastic scenarios caused by different externally induced natural and anthropogenic processes inherit properties of deterministic behaviour and drastically change the system dynamics. We demonstrate that the system transitions across its separatrix occur with increasing noise intensity. The climate-vegetation system therewith fluctuates, transits and localizes in the vicinity of its attractor. We show that this phenomenon occurs within some critical range of noise intensities. A noise-induced shift into the range of smaller global average temperatures corresponding to substantial oscillations of the Earth's vegetation cover is revealed. Our analysis demonstrates that the climate-vegetation interactions essentially contribute to climate dynamics and should be taken into account in more precise and complex models of climate variability.

Detecting changes in water limitation in the West using integrated ecosystem modeling approaches

NASA Astrophysics Data System (ADS)

Poulter, B.; Hoy, J.; Emmett, K.; Cross, M.; Maneta, M. P.; Al-Chokhachy, R.

2016-12-01

Water in the western United States is the critical currency for determining a range of ecosystem services, such as wildlife habitat, carbon sequestration, and timber and water resources for an expanding human population. The current generation of catchment models trades a detailed representation of hydrologic processes for a generalization of vegetation processes and thus ignores many land-surface feedbacks that are driven by physiological responses to atmospheric CO2 and changes in vegetation structure following disturbance and climate change. Here we demonstrate how catchment scale modeling can better couple vegetation dynamics and disturbance processes to reconstruct historic streamflow, stream temperature and vegetation greening for the Greater Yellowstone Ecosystem. Using a new catchment routing model coupled to the LPJ-GUESS dynamic global vegetation model, simulations are made at 1 km spatial resolution using two different climate products. Decreased winter snowpack has led to increasing spring runoff and declines in summertime slow, and increasing the likelihood that stream temperature exceeds thresholds for cold-water fish growth. Since the mid-1980s, vegetation greening is projected by both the model and detected from space-borne normalized difference vegetation index observations. These greening trends are superimposed on a landscape matrix defined by frequent disturbance and intensive land management, making the climate and CO2 fingerprint difficult to discern. Integrating dynamical vegetation models with in-situ and spaceborne measurements to understand and interpret catchment-scale trends in water availability has potential to better disentangle historical climate, CO2, and human drivers and their ecosystem consequences.

Integrating SPOT-VEGETATION 13-yr time series and land-surface modelling to forecast the terrestrial carbon dynamics in a changing climate - The VEGECLIM project: achievements and lessons learned

NASA Astrophysics Data System (ADS)

Defourny, Pierre; Verbeeck, Hans; Moreau, Inès; De Weirdt, Marjolein; Verhegghen, Astrid; Kibambe-Lubamba, Jean-Paul; Jungers, Quentin; Maignan, Fabienne; Najdovski, Nicolas; Poulter, Benjamin; MacBean, Natasha; Peylin, Philippe

2014-05-01

Vegetation is a major carbon sink and is as such a key component of the international response to climate change caused by the build-up of greenhouse gases in the atmosphere. However, anthropogenic disturbances like deforestation are the primary mechanism that changes ecosystems from carbon sinks to sources, and are hardly included in the current carbon modelling approaches. Moreover, in tropical regions, the seasonal/interannual variability of carbon fluxes is still uncertain and a weak or even no seasonality is taken into account in global vegetation models. In the context of climate change and mitigation policies like "Reducing Emissions from Deforestation and Forest Degradation in Developing Countries" (REDD), it is particularly important to be able to quantify and forecast the vegetation dynamics and carbon fluxes in these regions. The overall objective of the VEGECLIM project is to increase our knowledge on the terrestrial carbon cycle in tropical regions and to improve the forecast of the vegetation dynamics and carbon stocks and fluxes under different climate-change and deforestation scenarios. Such an approach aims to determine whether the African terrestrial carbon balance will remain a net sink or could become a carbon source by the end of the century, according to different climate-change and deforestation scenarios. The research strategy is to integrate the information of the land surface characterizations obtained from 13 years of consistent SPOT-VEGETATION time series (land cover, vegetation phenology through vegetation indices such as the Enhanced Vegetation Index (EVI)) as well as in-situ carbon flux data into the process based ORCHIDEE global vegetation model, capable of simulating vegetation dynamics and carbon balance. Key challenge of this project was to bridge the gap between the land cover and the land surface model teams. Several improvements of the ORCHIDEE model have been realized such as a new seasonal leaf dynamics for tropical evergreen forests, the introduction of spatial soil phosphorus to improve the spatial distribution of simulated woody biomass and an assimilation of smoothed seasonal pattern of satellite-based EVI used as a proxy to vegetation productivity. The outputs of the ORCHIDEE simulations over both Amazon and Congo Basins are discussed with regards to the observed phenology by remote sensing.

Dynamical stabilization of grazing systems: An interplay among plant-water interaction, overgrazing and a threshold management policy.

PubMed

Costa, Michel Iskin da Silveira; Meza, Magno Enrique Mendoza

2006-12-01

In a plant-herbivore system, a management strategy called threshold policy is proposed to control grazing intensity where the vegetation dynamics is described by a plant-water interaction model. It is shown that this policy can lead the vegetation density to a previously chosen level under an overgrazing regime. This result is obtained despite both the potential occurrence of vegetation collapse due to overgrazing and the possibility of complex dynamics sensitive to vegetation initial densities and parameter uncertainties.

Importance of vegetation dynamics for future terrestrial carbon cycling

NASA Astrophysics Data System (ADS)

Ahlström, Anders; Xia, Jianyang; Arneth, Almut; Luo, Yiqi; Smith, Benjamin

2015-05-01

Terrestrial ecosystems currently sequester about one third of anthropogenic CO2 emissions each year, an important ecosystem service that dampens climate change. The future fate of this net uptake of CO2 by land based ecosystems is highly uncertain. Most ecosystem models used to predict the future terrestrial carbon cycle share a common architecture, whereby carbon that enters the system as net primary production (NPP) is distributed to plant compartments, transferred to litter and soil through vegetation turnover and then re-emitted to the atmosphere in conjunction with soil decomposition. However, while all models represent the processes of NPP and soil decomposition, they vary greatly in their representations of vegetation turnover and the associated processes governing mortality, disturbance and biome shifts. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality, and the associated turnover. We apply an emulator that describes the carbon flows and pools exactly as in simulations with the full model. The emulator simulates ecosystem dynamics in response to 13 different climate or Earth system model simulations from the Coupled Model Intercomparison Project Phase 5 ensemble under RCP8.5 radiative forcing. By exchanging carbon cycle processes between these 13 simulations we quantified the relative roles of three main driving processes of the carbon cycle; (I) NPP, (II) vegetation dynamics and turnover and (III) soil decomposition, in terms of their contribution to future carbon (C) uptake uncertainties among the ensemble of climate change scenarios. We found that NPP, vegetation turnover (including structural shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33%, respectively, of uncertainties in modelled global C-uptake. Uncertainty due to vegetation turnover was further partitioned into stand-clearing disturbances (16%), wild fires (0%), stand dynamics (7%), reproduction (10%) and biome shifts (67%) globally. We conclude that while NPP and soil decomposition rates jointly account for 83% of future climate induced C-uptake uncertainties, vegetation turnover and structure, dominated by biome shifts, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

Global simulation of interactions between groundwater and terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Braakhekke, M. C.; Rebel, K.; Dekker, S. C.; Smith, B.; Van Beek, L. P.; Sutanudjaja, E.; van Kampenhout, L.; Wassen, M. J.

2016-12-01

In many places in the world ecosystems are influenced by the presence of a shallow groundwater table. In these regions upward water flux due to capillary rise increases soil moisture availability in the root zone, which has strong positive effect on evapotranspiration. Additionally it has important consequences for vegetation dynamics and fluxes of carbon and nitrogen. Under water limited conditions shallow groundwater stimulates vegetation productivity, and soil organic matter decomposition while under saturated conditions groundwater may have a negative effect on these processes due to lack of oxygen. Furthermore, since plant species differ with respect to their root distribution, preference for moisture conditions, and resistance to oxygen stress, shallow groundwater also influences vegetation type. Finally, processes such as denitrification and methane production occur under strictly anaerobic conditions and are thus strongly influenced by moisture availability. Most global hydrological models and several land surface models simulate groundwater table dynamics and their effects on land surface processes. However, these models typically have relatively simplistic representation of vegetation and do not consider changes in vegetation type and structure and are therefore less suitable to represent effects of groundwater on biogeochemical fluxes. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure and biogeochemical processes. These models are thus more appropriate to simulate the ecological and biogeochemical effects of groundwater interactions. However, currently virtually all DGVMs ignore these effects, assuming that water tables are too deep to affect soil moisture in the root zone. We have implemented a tight coupling between the dynamic global ecosystem model LPJ-GUESS and the global hydrological model PCR-GLOBWB. Using this coupled model we aim to study the influence of shallow groundwater on terrestrial ecosystem processes. We will present results of global simulations to demonstrate the effects on C, N, and water fluxes.

A Model-Based Study of Ecohydrological Controls in the Mojave Desert

NASA Astrophysics Data System (ADS)

Ng, G. C.; Bedford, D.; Miller, D. M.

2010-12-01

Desert ecosystems represent extreme conditions near the limits of viability for vegetation. Their dependence on scarce resources make them vulnerable to climate and land use change. Understanding how ecohydrological conditions impact plants in such regions is critical for ecological sustainability. Various relationships have been observed in the field between vegetation growth and meteorology, terrain, and plant physiology. Quantifying the complex interactions of those influences on vegetation dynamics can be facilitated with a physically-based ecohydrological model. To assess ecohydrological controls in the Mojave Desert, we employ the CLM4.0 land-surface model with the Carbon-Nitrogen model component to simulate vegetation dynamics [Olesen et al., 2010]. Using an ecohydrological model with fully prognostic vegetation variables is essential for representing the coupled dynamics between plants and soil moisture. We apply the CLM4.0-CN model to a study basin in the Mojave National Preserve that covers a variety of conditions. Soils range from coarse-textured wash sediments to low-permeability desert pavements. Higher elevations in the basin experience cooler and moister conditions than the lower wash areas. The dominant vegetation types in the basin include the evergreen shrub Larrea tridentata (creosote) and the drought-deciduous shrub Ambrosia dumosa. Simulations are conducted over a 50 year period to investigate both seasonal and interannual dynamics. Sensitivity tests indicate that high temporal resolution rainfall inputs (at least hourly) are important for properly resolving ecohydrological dynamics at the study site. As expected, preliminary results show that both coarser soils and milder climate facilitate vegetation growth in this moisture-limited region. However, results indicate that effects of soil texture variations become subordinate with milder climate. The model also reveals how drought-deciduous and evergreen shrub types respond differently to various conditions. Due to its quick response to sporadic wet episodes, the drought-deciduous Ambrosia thrives under harsher (hotter and drier) climates in simulations. The evergreen Larrea shrub becomes more competitive with more consistent moisture of the relatively milder climates in the basin. Multi-decadal simulations indicate that anomalously wet years can yield a sustained boost in vegetation in following years, especially for Larrea. These model results coincide with many observed vegetation patterns in the field, and they serve to elucidate and quantify the contributing factors that impact desert vegetation.

Understanding climate impacts on vegetation using a spatiotemporal non-linear Granger causality framework

NASA Astrophysics Data System (ADS)

Papagiannopoulou, Christina; Decubber, Stijn; Miralles, Diego; Demuzere, Matthias; Dorigo, Wouter; Verhoest, Niko; Waegeman, Willem

2017-04-01

Satellite data provide an abundance of information about crucial climatic and environmental variables. These data - consisting of global records, spanning up to 35 years and having the form of multivariate time series with different spatial and temporal resolutions - enable the study of key climate-vegetation interactions. Although methods which are based on correlations and linear models are typically used for this purpose, their assumptions for linearity about the climate-vegetation relationships are too simplistic. Therefore, we adopt a recently proposed non-linear Granger causality analysis [1], in which we incorporate spatial information, concatenating data from neighboring pixels and training a joint model on the combined data. Experimental results based on global data sets show that considering non-linear relationships leads to a higher explained variance of past vegetation dynamics, compared to simple linear models. Our approach consists of several steps. First, we compile an extensive database [1], which includes multiple data sets for land surface temperature, near-surface air temperature, surface radiation, precipitation, snow water equivalents and surface soil moisture. Based on this database, high-level features are constructed and considered as predictors in our machine-learning framework. These high-level features include (de-trended) seasonal anomalies, lagged variables, past cumulative variables, and extreme indices, all calculated based on the raw climatic data. Second, we apply a spatiotemporal non-linear Granger causality framework - in which the linear predictive model is substituted for a non-linear machine learning algorithm - in order to assess which of these predictor variables Granger-cause vegetation dynamics at each 1° pixel. We use the de-trended anomalies of Normalized Difference Vegetation Index (NDVI) to characterize vegetation, being the target variable of our framework. Experimental results indicate that climate strongly (Granger-)causes vegetation dynamics in most regions globally. More specifically, water availability is the most dominant vegetation driver, being the dominant vegetation driver in 54% of the vegetated surface. Furthermore, our results show that precipitation and soil moisture have prolonged impacts on vegetation in semiarid regions, with up to 10% of additional explained variance on the vegetation dynamics occurring three months later. Finally, hydro-climatic extremes seem to have a remarkable impact on vegetation, since they also explain up to 10% of additional variance of vegetation in certain regions despite their infrequent occurrence. References [1] Papagiannopoulou, C., Miralles, D. G., Verhoest, N. E. C., Dorigo, W. A., and Waegeman, W.: A non-linear Granger causality framework to investigate climate-vegetation dynamics, Geosci. Model Dev. Discuss., doi:10.5194/gmd-2016-266, in review, 2016.

Simulating vegetation dynamics in Chile from 21ka BP to present: Effects of climate change on vegetation functions and cover

NASA Astrophysics Data System (ADS)

Werner, Christian; Liakka, Johan; Schmid, Manuel; Fuentes, Juan-Pablo; Ehlers, Todd A.; Hickler, Thomas

2017-04-01

Vegetation composition and establishment is strongly dependent on climate conditions but also a result of vegetation dynamics (competition for light, water and nutrients). In addition, vegetation exerts control over the development of landscapes as it mediates the climatic and hydrological forces shaping the terrain via hillslope and fluvial processes. At the same time, topography as well as soil texture and soil depth affect the microclimate, soil water storage and rooting space that is defining the environmental envelope for vegetation development. Within the EarthShape research program (www.earthshape.net) we evaluate these interactions by simulating the co-evolution of landscape and vegetation with a dynamic vegetation model (LPJ-GUESS) and a landscape evolution model (LandLab). LPJ-GUESS is a mechanistic model driven by daily or monthly weather data and explicitly simulates vegetation physiology, succession, competition and water and nutrient cycling. Here we present the results of first transient vegetation simulations from 21kyr BP to present-day using the TraCE-21ka climate dataset for four focus sites along the coastal cordillera of Chile that are exposed to a substantial meridional climate gradient (ranging from hyper-arid to humid-temperate conditions). We show that the warming occurring in the region from LGM to present, in addition to the increase of atmospheric CO2 concentrations, led to a shift in vegetation composition and surface cover. Future work will show how these changes resonate in the dynamics of hillslope and fluvial erosion and ultimately bi-directional feedback mechanisms of vegetation development and landscape evolution/ soil formation (see also companion presentation by Schmid et al., this session).

Modelling Holocene peatland dynamics with an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Chaudhary, Nitin; Miller, Paul A.; Smith, Benjamin

2017-05-01

Dynamic global vegetation models (DGVMs) are designed for the study of past, present and future vegetation patterns together with associated biogeochemical cycles and climate feedbacks. However, most DGVMs do not yet have detailed representations of permafrost and non-permafrost peatlands, which are an important store of carbon, particularly at high latitudes. We demonstrate a new implementation of peatland dynamics in a customized Arctic version of the LPJ-GUESS DGVM, simulating the long-term evolution of selected northern peatland ecosystems and assessing the effect of changing climate on peatland carbon balance. Our approach employs a dynamic multi-layer soil with representation of freeze-thaw processes and litter inputs from a dynamically varying mixture of the main peatland plant functional types: mosses, shrubs and graminoids. The model was calibrated and tested for a sub-Arctic mire in Stordalen, Sweden, and validated at a temperate bog site in Mer Bleue, Canada. A regional evaluation of simulated carbon fluxes, hydrology and vegetation dynamics encompassed additional locations spread across Scandinavia. Simulated peat accumulation was found to be generally consistent with published data and the model was able to capture reported long-term vegetation dynamics, water table position and carbon fluxes. A series of sensitivity experiments were carried out to investigate the vulnerability of high-latitude peatlands to climate change. We found that the Stordalen mire may be expected to sequester more carbon in the first half of the 21st century due to milder and wetter climate conditions, a longer growing season, and the CO2 fertilization effect, turning into a carbon source after mid-century because of higher decomposition rates in response to warming soils.

Dynamic modeling of the cesium, strontium, and ruthenium transfer to grass and vegetables

DOE Office of Scientific and Technical Information (OSTI.GOV)

Renaud, P.; Real, J.; Maubert, H.

1999-05-01

From 1988 to 1993, the Nuclear Safety and Protection Institute (Institut de Protection et de Surete Nucleaire -- IPSN) conducted experimental programs focused on transfers to vegetation following accidental localized deposits of radioactive aerosols. In relation to vegetable crops (fruit, leaves, and root vegetables) and meadow grass these experiments have enabled a determination of the factors involved in the transfer of cesium, strontium, and ruthenium at successive harvests, or cuttings, in respect of various time lags after contamination. The dynamic modeling given by these results allows an evaluation of changes in the mass activity of vegetables and grass during themore » months following deposit. It constitutes part of the ASTRAL post-accident radioecology model.« less

MODELING DYNAMIC VEGETATION RESPONSE TO RAPID CLIMATE CHANGE USING BIOCLIMATIC CLASSIFICATION

EPA Science Inventory

Modeling potential global redistribution of terrestrial vegetation frequently is based on bioclimatic classifications which relate static regional vegetation zones (biomes) to a set of static climate parameters. The equilibrium character of the relationships limits our confidence...

An integrated model of soil, hydrology, and vegetation for carbon dynamics in wetland ecosystems

Treesearch

Yu Zhang; Changsheng Li; Carl C. Trettin; Harbin Li; Ge Sun

2002-01-01

Wetland ecosystems are an important component in global carbon (C) cycles and may exert a large influence on global clinlate change. Predictions of C dynamics require us to consider interactions among many critical factors of soil, hydrology, and vegetation. However, few such integrated C models exist for wetland ecosystems. In this paper, we report a simulation model...

Disentangling the effects of climate and people on Sahel vegetation dynamics

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2009-03-01

The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. We do not exclude the possibility of a greater human influence on vegetation dynamics over the coming decades with changing land use.

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

DOE PAGES

Sakaguchi, K.; Zeng, X.; Leung, L. R.; ...

2016-12-21

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Influence of dynamic vegetation on carbon-nitrogen cycle feedback in the Community Land Model (CLM4)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sakaguchi, K.; Zeng, X.; Leung, L. R.

Land carbon sensitivity to atmospheric CO 2 concentration (β L) and climate warming (γ L) is a crucial part of carbon-climate feedbacks in the earth system. Using the Community Land Model version 4 with a coupled carbon-nitrogen cycle, we examine whether the inclusion of a dynamic global vegetation model (CNDV) significantly changes the land carbon sensitivity from that obtained with prescribed vegetation cover (CN). For decadal timescale in the late twentieth century, β L is not substantially different between the two models but γ L of CNDV is stronger (more negative) than that of CN. The main reason for themore » difference in γL is not the concurrent change in vegetation cover driving the carbon dynamics, but rather the smaller nitrogen constraint on plant growth in CNDV compared with CN, which arises from the deviation of CNDV's near-equilibrium vegetation distribution from CN’s prescribed, historical land cover. The smaller nitrogen constraint makes the enhanced nitrogen mineralization with warming less effective in stimulating plant productivity to counter moisture stress in a warmer climate, leading to a more negative γ L. This represents a new indirect pathway that has not been identified for dynamic vegetation in the coupled carbon-nitrogen cycle to affect the terrestrial carbon-climate feedbacks in the earth system.« less

Future vegetation ecosystem response to warming climate over the Tibetan Plateau

NASA Astrophysics Data System (ADS)

Bao, Y.; Gao, Y.; Wang, Y.

2017-12-01

The amplified vegetation response to climate variability has been found over the Tibetan Plateau (TP) in recent decades. In this study, the potential impacts of 21st century climate change on the vegetation ecosystem over the TP are assessed based on the dynamic vegetation outputs of models from Coupled Model Intercomparison Project Phase 5 (CMIP5), and the sensitivity of the TP vegetation in response to warming climate was investigated. Models project a continuous and accelerating greening in future, especially in the eastern TP, which closely associates with the plant type upgrade due to the pronouncing warming in growing season.Vegetation leaf area index (LAI) increase well follows the global warming, suggesting the warming climate instead of co2 fertilization controlls the future TP plant growth. The warming spring may advance the start of green-up day and extend the growing season length. More carbon accumulation in vegetation and soil will intensify the TP carbon cycle and will keep it as a carbon sink in future. Keywords: Leaf Area Index (LAI), Climate Change, Global Dynamic Vegetation Models (DGVMs), CMIP5, Tibetan Plateau (TP)

Dynamic root distributions in ecohydrological modeling: A case study at Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, Gajan; Bras, Rafael L.

2013-06-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. However, land surface models currently prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. Additionally, these models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings or competition from other plant species and therefore tend to underestimate the resilience of these ecosystems. To address the simplicity of the current representation of roots in land surface models, a new dynamic rooting scheme was incorporated into the framework of the distributed ecohydrological model tRIBS+VEGGIE. The new scheme optimizes the allocation of carbon to the root zone to reduce the perceived stress of the vegetation, so that root profiles evolve based upon local climate and soil conditions. The ability of the new scheme to capture the complex dynamics of natural systems was evaluated by comparisons to hourly timescale energy flux, soil moisture, and vegetation growth observations from the Walnut Gulch Experimental Watershed, Arizona. Robust agreement was found between the model and observations, providing confidence that the improved model is able to capture the multidirectional interactions between climate, soil, and vegetation at this site.

Elevation Control on Vegetation Organization in a Semiarid Ecosystem in Central New Mexico

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2015-12-01

Many semiarid and desert ecosystems are characterized by patchy and dynamic vegetation. Topography plays a commanding role on vegetation patterns. It is observed that plant biomes and biodiversity vary systematically with slope and aspect, from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations. In this study, we investigate the role of elevation dependent climatology on vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. An ecohydrologic cellular automaton model developed within Landlab (component based modeling framework) is used. The model couples local vegetation dynamics (that simulate biomass production based on local soil moisture and potential evapotranspiration) and plant establishment and mortality based on competition for resources and space. This model is driven by elevation dependent rainfall pulses and solar radiation. The domain is initialized with randomly assigned plant types and the model parameters that couple plant response with soil moisture are systematically changed. Climate perturbation experiments are conducted to examine spatial vegetation organization and associated timescales. Model results reproduce elevation and aspect controls on observed vegetation patterns indicating that this model captures necessary and sufficient conditions that explain these observed ecohydrological patterns.

Disentangling the effects of climate and people on Sahel vegetation dynamics

NASA Astrophysics Data System (ADS)

Seaquist, J. W.; Hickler, T.; Eklundh, L.; Ardö, J.; Heumann, B. W.

2008-08-01

The Sahel belt of Africa has been the focus of intensive scientific research since the 1960s, spurred on by the chronic vulnerability of its population to recurring drought and the threat of long-term land degradation. But satellite sensors have recently shown that much of the region has experienced significant increases in photosynthetic activity since the early 1980s, thus re-energizing long-standing debates about the role that people play in shaping land surface status, and thus climate at regional scales. In this paper, we test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982 2002. We compare potential natural vegetation dynamics predicted by a process-based ecosystem model with satellite-derived greenness observations, and map the agreement between the two across a geographic grid at a spatial resolution of 0.5°. As aggregated data-model agreement is very good, any local differences between the two could be due to human impact. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Our findings suggest that demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human "footprint" is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study.

Can Dynamic Global Vegetation Models Reproduce Satellite Observed Extreme Browning and Greening Events in Vegetation Productivity?

NASA Astrophysics Data System (ADS)

van Eck, C. M.; Morfopoulos, C.; Betts, R. A.; Chang, J.; Ciais, P.; Friedlingstein, P.; Regnier, P. A. G.

2016-12-01

The frequency and severity of extreme climate events such as droughts, extreme precipitation and heatwaves are expected to increase in our changing climate. These extreme climate events will have an effect on vegetation either by enhanced or reduced productivity. Subsequently, this can have a substantial impact on the terrestrial carbon sink and thus the global carbon cycle, especially as extreme climate events are expected to increase in frequency and severity. Connecting observational datasets with modelling studies provides new insights into these climate-vegetation interactions. This study aims to compare extremes in vegetation productivity as derived from observations with that of Dynamic Global Vegetation Models (DGVMs). In this case GIMMS-NDVI 3g is selected as the observational dataset and both JULES (Joint UK Land Environment Simulator) and ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) as the DGVMs. Both models are forced with PGFv2 Global Meteorological Forcing Dataset according to the ISI-MIP2 protocol for historical runs. Extremes in vegetation productivity are the focal point, which are identified as NDVI anomalies below the 10th percentile or above the 90th percentile during the growing season, referred to as browning or greening events respectively. The monthly NDVI dataset GIMMS-NDVI 3g is used to obtain the location in time and space of the vegetation extremes. The global GIMMS-NDVI 3g dataset has been subdivided into IPCC's SREX-regions for which the NDVI anomalies are calculated and the extreme thresholds are determined. With this information we can identify the location in time and space of the browning and greening events in remotely-sensed vegetation productivity. The same procedure is applied to the modelled Gross Primary Productivity (GPP) allowing a comparison between the spatial and temporal occurrence of the browning and greening events in the observational dataset and the models' output. The capacity of the models to catch observed extremes in vegetation productivity is assessed and compared. Factors contributing to observed and modelled vegetation browning/greening extremes are analysed. The results of this study provide a stepping stone to modelling future extremes in vegetation productivity.

Multi-centennial ecosystem modelling in northeastern America at the species level

NASA Astrophysics Data System (ADS)

Steinkamp, J.; Biskupovic, A.; Rollinson, C.; Dawson, A.; Goring, S. J.; McLachlan, J. S.; Mladenoff, D. J.; Williams, J.; Hickler, T.

2016-12-01

Most dynamic global vegetation models (DGVM) are based on a small set of plant functional types (PFTs) to simulate biome distribution, vegetation dynamics, and carbon and nutrient cycles, which is of limited use for more regional studies and stakeholders. We tested a tree-species-based parameterization approach of the LPJ-GUESS DGVM in the northeastern USA, which previously has been successful in simulating the main potential natural vegetation zones in Europe. A transient model run was carried out from 850 A.D. to today, and the model results have been evaluated against pre-settlement vegetation maps and reconstructed vegetation from pollen within the PalEON project and hypothesized potential natural vegetation zones. We will analyze the simulation with respect to long term carbon cycling and the driving forces. Main reconstructed vegetation features were reproduced by the model, which implies that the general processes shaping the forested vegetation in parts of Europe and the northeastern USA are similar. However, so far the decrease in biomass towards the prairie in the west could not fully be captured by the model, which is currently analyzed with additional simulations. Moisture and fire are the important driver at the prairie forest transition zone, which we need to better constrain for this model domain.

Simulations of moving effect of coastal vegetation on tsunami damping

NASA Astrophysics Data System (ADS)

Tsai, Ching-Piao; Chen, Ying-Chi; Octaviani Sihombing, Tri; Lin, Chang

2017-05-01

A coupled wave-vegetation simulation is presented for the moving effect of the coastal vegetation on tsunami wave height damping. The problem is idealized by solitary wave propagation on a group of emergent cylinders. The numerical model is based on general Reynolds-averaged Navier-Stokes equations with renormalization group turbulent closure model by using volume of fluid technique. The general moving object (GMO) model developed in computational fluid dynamics (CFD) code Flow-3D is applied to simulate the coupled motion of vegetation with wave dynamically. The damping of wave height and the turbulent kinetic energy along moving and stationary cylinders are discussed. The simulated results show that the damping of wave height and the turbulent kinetic energy by the moving cylinders are clearly less than by the stationary cylinders. The result implies that the wave decay by the coastal vegetation may be overestimated if the vegetation was represented as stationary state.

Predicting landscape vegetation dynamics using state-and-transition simulation models

Treesearch

Colin J. Daniel; Leonardo Frid

2012-01-01

This paper outlines how state-and-transition simulation models (STSMs) can be used to project changes in vegetation over time across a landscape. STSMs are stochastic, empirical simulation models that use an adapted Markov chain approach to predict how vegetation will transition between states over time, typically in response to interactions between succession,...

Semisupervised GDTW kernel-based fuzzy c-means algorithm for mapping vegetation dynamics in mining region using normalized difference vegetation index time series

NASA Astrophysics Data System (ADS)

Jia, Duo; Wang, Cangjiao; Lei, Shaogang

2018-01-01

Mapping vegetation dynamic types in mining areas is significant for revealing the mechanisms of environmental damage and for guiding ecological construction. Dynamic types of vegetation can be identified by applying interannual normalized difference vegetation index (NDVI) time series. However, phase differences and time shifts in interannual time series decrease mapping accuracy in mining regions. To overcome these problems and to increase the accuracy of mapping vegetation dynamics, an interannual Landsat time series for optimum vegetation growing status was constructed first by using the enhanced spatial and temporal adaptive reflectance fusion model algorithm. We then proposed a Markov random field optimized semisupervised Gaussian dynamic time warping kernel-based fuzzy c-means (FCM) cluster algorithm for interannual NDVI time series to map dynamic vegetation types in mining regions. The proposed algorithm has been tested in the Shengli mining region and Shendong mining region, which are typical representatives of China's open-pit and underground mining regions, respectively. Experiments show that the proposed algorithm can solve the problems of phase differences and time shifts to achieve better performance when mapping vegetation dynamic types. The overall accuracies for the Shengli and Shendong mining regions were 93.32% and 89.60%, respectively, with improvements of 7.32% and 25.84% when compared with the original semisupervised FCM algorithm.

Stereophotogrammetry in studies of riparian vegetation dynamics

NASA Astrophysics Data System (ADS)

Hortobagyi, Borbala; Vautier, Franck; Corenblit, Dov; Steiger, Johannes

2014-05-01

Riparian vegetation responds to hydrogeomorphic disturbances and also controls sediment deposition and erosion. Spatio-temporal riparian vegetation dynamics within fluvial corridors have been quantified in many studies using aerial photographs and GIS. However, this approach does not allow the consideration of woody vegetation growth rates (i.e. vertical dimension) which are fundamental when studying feedbacks between the processes of fluvial landform construction and vegetation establishment and succession. We built 3D photogrammetric models of vegetation height based on aerial argentic and digital photographs from sites of the Allier and Garonne Rivers (France). The models were realized at two different spatial scales and with two different methods. The "large" scale corresponds to the reach of the river corridor on the Allier river (photograph taken in 2009) and the "small" scale to river bars of the Allier (photographs taken in 2002, 2009) and Garonne Rivers (photographs taken in 2000, 2002, 2006 and 2010). At the corridor scale, we generated vegetation height models using an automatic procedure. This method is fast but can only be used with digital photographs. At the bar scale, we constructed the models manually using a 3D visualization on the screen. This technique showed good results for digital and also argentic photographs but is very time-consuming. A diachronic study was performed in order to investigate vegetation succession by distinguishing three different classes according to the vegetation height: herbs (<1 m), shrubs (1-4 m) or trees (>4 m). Both methods, i.e. automatic and manual, were employed to study the evolution of the three vegetation classes and the recruitment of new vegetation patches. A comparison was conducted between the vegetation height given by models (automatic and manual) and the vegetation height measured in the field. The manually produced models (small scale) were of a precision of 0.5-1 m, allowing the quantification of woody vegetation growth rates. Thus, our results show that the manual method we developed is accurate to quantify vegetation growth rates at small scales, whereas the less accurate automatic method is appropriate to study vegetation succession at the corridor scale. Both methods are complementary and will contribute to a further exploration of the mutual relationships between hydrogeomorphic processes, topography and vegetation dynamics within alluvial systems, adding the quantification of the vertical dimension of riparian vegetation to their spatio-temporal characteristics.

Assessing the Influence of Precipitation Variability on the Vegetation Dynamics of the Mediterranean Rangelands using NDVI and Machine Learning

NASA Astrophysics Data System (ADS)

Daliakopoulos, Ioannis; Tsanis, Ioannis

2017-04-01

Mitigating the vulnerability of Mediterranean rangelands against degradation is limited by our ability to understand and accurately characterize those impacts in space and time. The Normalized Difference Vegetation Index (NDVI) is a radiometric measure of the photosynthetically active radiation absorbed by green vegetation canopy chlorophyll and is therefore a good surrogate measure of vegetation dynamics. On the other hand, meteorological indices such as the drought assessing Standardised Precipitation Index (SPI) are can be easily estimated from historical and projected datasets at the global scale. This work investigates the potential of driving Random Forest (RF) models with meteorological indices to approximate NDVI-based vegetation dynamics. A sufficiently large number of RF models are trained using random subsets of the dataset as predictors, in a bootstrapping approach to account for the uncertainty introduced by the subset selection. The updated E-OBS-v13.1 dataset of the ENSEMBLES EU FP6 program provides observed monthly meteorological input to estimate SPI over the Mediterranean rangelands. RF models are trained to depict vegetation dynamics using the latest version (3g.v1) of the third generation GIMMS NDVI generated from NOAA's Advanced Very High Resolution Radiometer (AVHRR) sensors. Analysis is conducted for the period 1981-2015 at a gridded spatial resolution of 25 km. Preliminary results demonstrate the potential of machine learning algorithms to effectively mimic the underlying physical relationship of drought and Earth Observation vegetation indices to provide estimates based on precipitation variability.

Application of a coupled vegetation competition and groundwater simulation model to study effects of sea level rise and storm surges on coastal vegetation

USGS Publications Warehouse

Teh, Su Yean; Turtora, Michael; DeAngelis, Donald L.; Jiang Jiang,; Pearlstine, Leonard G.; Smith, Thomas; Koh, Hock Lye

2015-01-01

Global climate change poses challenges to areas such as low-lying coastal zones, where sea level rise (SLR) and storm-surge overwash events can have long-term effects on vegetation and on soil and groundwater salinities, posing risks of habitat loss critical to native species. An early warning system is urgently needed to predict and prepare for the consequences of these climate-related impacts on both the short-term dynamics of salinity in the soil and groundwater and the long-term effects on vegetation. For this purpose, the U.S. Geological Survey’s spatially explicit model of vegetation community dynamics along coastal salinity gradients (MANHAM) is integrated into the USGS groundwater model (SUTRA) to create a coupled hydrology–salinity–vegetation model, MANTRA. In MANTRA, the uptake of water by plants is modeled as a fluid mass sink term. Groundwater salinity, water saturation and vegetation biomass determine the water available for plant transpiration. Formulations and assumptions used in the coupled model are presented. MANTRA is calibrated with salinity data and vegetation pattern for a coastal area of Florida Everglades vulnerable to storm surges. A possible regime shift at that site is investigated by simulating the vegetation responses to climate variability and disturbances, including SLR and storm surges based on empirical information.

Potential role of vegetation dynamics on recent extreme droughts over tropical South America

NASA Astrophysics Data System (ADS)

Wang, G.; Erfanian, A.; Fomenko, L.

2017-12-01

Tropical South America is a drought hot spot. In slightly over a decade (2005-2016), the region encountered three extreme droughts (2005, 2010, and 2016). Recurrent extreme droughts not only impact the region's eco-hydrology and socio-economy, but are also globally important as they can transform the planet's largest rainforest, the Amazon, from a carbon sink to a carbon source. Understanding drought drivers and mechanisms underlying extreme droughts in tropical South America can help better project the fate of the Amazon rainforest in a changing climate. In this study we use a regional climate model (RegCM4.3.4) coupled with a comprehensive land-surface model (CLM4.5) to study the present-day hydroclimate of the region, focusing specifically on what might have caused the frequent recurrence of extreme droughts. In the context of observation natural variability of the global oceanic forcing, we tackle the role of land-atmosphere interactions and ran the model with and without dynamic vegetation to study how vegetation dynamics and carbon-nitrogen cycles may have influenced the drought characteristics. Our results demonstrate skillful simulation of the South American climate in the model, and indicate substantial sensitivity of the region's hydroclimatology to vegetation dynamics. This presentation will compare the role of global oceanic forcing versus regional land surface feedback in the recent recurrent droughts, and will characterize the effects of vegetation dynamics in enhancing the drought severity. Preliminary results on future projections of the regional ecosystem and droughts perspective will be also presented.

Consistent response of vegetation dynamics to recent climate change in tropical mountain regions.

PubMed

Krishnaswamy, Jagdish; John, Robert; Joseph, Shijo

2014-01-01

Global climate change has emerged as a major driver of ecosystem change. Here, we present evidence for globally consistent responses in vegetation dynamics to recent climate change in the world's mountain ecosystems located in the pan-tropical belt (30°N-30°S). We analyzed decadal-scale trends and seasonal cycles of vegetation greenness using monthly time series of satellite greenness (Normalized Difference Vegetation Index) and climate data for the period 1982-2006 for 47 mountain protected areas in five biodiversity hotspots. The time series of annual maximum NDVI for each of five continental regions shows mild greening trends followed by reversal to stronger browning trends around the mid-1990s. During the same period we found increasing trends in temperature but only marginal change in precipitation. The amplitude of the annual greenness cycle increased with time, and was strongly associated with the observed increase in temperature amplitude. We applied dynamic models with time-dependent regression parameters to study the time evolution of NDVI-climate relationships. We found that the relationship between vegetation greenness and temperature weakened over time or was negative. Such loss of positive temperature sensitivity has been documented in other regions as a response to temperature-induced moisture stress. We also used dynamic models to extract the trends in vegetation greenness that remain after accounting for the effects of temperature and precipitation. We found residual browning and greening trends in all regions, which indicate that factors other than temperature and precipitation also influence vegetation dynamics. Browning rates became progressively weaker with increase in elevation as indicated by quantile regression models. Tropical mountain vegetation is considered sensitive to climatic changes, so these consistent vegetation responses across widespread regions indicate persistent global-scale effects of climate warming and associated moisture stresses. © 2013 John Wiley & Sons Ltd.

Climate change and northern prairie wetlands: Simulations of long-term dynamics

USGS Publications Warehouse

Poiani, Karen A.; Johnson, W. Carter; Swanson, George A.; Winter, Thomas C.

1996-01-01

A mathematical model (WETSIM 2.0) was used to simulate wetland hydrology and vegetation dynamics over a 32-yr period (1961–1992) in a North Dakota prairie wetland. A hydrology component of the model calculated changes in water storage based on precipitation, evapotranspiration, snowpack, surface runoff, and subsurface inflow. A spatially explicit vegetation component in the model calculated changes in distribution of vegetative cover and open water, depending on water depth, seasonality, and existing type of vegetation.The model reproduced four known dry periods and one extremely wet period during the three decades. One simulated dry period in the early 1980s did not actually occur. Simulated water levels compared favorably with continuous observed water levels outside the calibration period (1990–1992). Changes in vegetative cover were realistic except for years when simulated water levels were significantly different than actual levels. These generally positive results support the use of the model for exploring the effects of possible climate changes on wetland resources.

Modeling dynamics of western juniper under climate change in a semiarid ecosystem

NASA Astrophysics Data System (ADS)

Shrestha, R.; Glenn, N. F.; Flores, A. N.

2013-12-01

Modeling future vegetation dynamics in response to climate change and disturbances such as fire relies heavily on model parameterization. Fine-scale field-based measurements can provide the necessary parameters for constraining models at a larger scale. But the time- and labor-intensive nature of field-based data collection leads to sparse sampling and significant spatial uncertainties in retrieved parameters. In this study we quantify the fine-scale carbon dynamics and uncertainty of juniper woodland in the Reynolds Creek Experimental Watershed (RCEW) in southern Idaho, which is a proposed critical zone observatory (CZO) site for soil carbon processes. We leverage field-measured vegetation data along with airborne lidar and timeseries Landsat imagery to initialize a state-and-transition model (VDDT) and a process-based fire-model (FlamMap) to examine the vegetation dynamics in response to stochastic fire events and climate change. We utilize recently developed and novel techniques to measure biomass and canopy characteristics of western juniper at the individual tree scale using terrestrial and airborne laser scanning techniques in RCEW. These fine-scale data are upscaled across the watershed for the VDDT and FlamMap models. The results will immediately improve our understanding of fine-scale dynamics and carbon stocks and fluxes of woody vegetation in a semi-arid ecosystem. Moreover, quantification of uncertainty will also provide a basis for generating ensembles of spatially-explicit alternative scenarios to guide future land management decisions in the region.

Modeling long-term changes in forested landscapes and their relation to the Earth's energy balance

NASA Technical Reports Server (NTRS)

Shugart, H. H.; Emanuel, W. R.; Solomon, A. M.

1984-01-01

The dynamics of the forested parts of the Earth's surface on time scales from decades to centuries are discussed. A set of computer models developed at Oak Ridge National Laboratory and elsewhere are applied as tools. These models simulate a landscape by duplicating the dynamics of growth, death and birth of each tree living on a 0.10 ha element of the landscape. This spatial unit is generally referred to as a gap in the case of the forest models. The models were tested against and applied to a diverse array of forests and appear to provide a reasonable representation for investigating forest-cover dynamics. Because of the climate linkage, one important test is the reconstruction of paleo-landscapes. Detailed reconstructions of changes in vegetation in response to changes in climate are crucial to understanding the association of the Earth's vegetation and climate and the response of the vegetation to climate change.

Modeling Vegetation Growth Impact on Groundwater Recharge

NASA Astrophysics Data System (ADS)

Anurag, H.; Ng, G. H. C.; Tipping, R.

2017-12-01

Vegetation growth is affected by variability in climate and land-cover / land-use over a range of temporal and spatial scales. Vegetation also modifies water budget through interception and evapotranspiration and thus has a significant impact on groundwater recharge. Most groundwater recharge assessments represent vegetation using specified, static parameter, such as for leaf-area-index, but this neglects the effect of vegetation dynamics on recharge estimates. Our study addresses this gap by including vegetation growth in model simulations of recharge. We use NCAR's Community Land Model v4.5 with its BGC module (BGC is the new CLM4.5 biogeochemistry). It integrates prognostic vegetation growth with land-surface and subsurface hydrological processes and can thus capture the effect of vegetation on groundwater. A challenge, however, is the need to resolve uncertainties in model inputs ranging from vegetation growth parameters all the way down to the water table. We have compiled diverse data spanning meteorological inputs to subsurface geology and use these to implement ensemble model simulations to evaluate the possible effects of dynamic vegetation growth (versus specified, static vegetation parameterizations) on estimating groundwater recharge. We present preliminary results for select data-intensive test locations throughout the state of Minnesota (USA), which has a sharp east-west precipitation gradient that makes it an apt testbed for examining ecohydrologic relationships across different temperate climatic settings and ecosystems. Using the ensemble simulations, we examine the effect of seasonal to interannual variability of vegetation growth on recharge and water table depths, which has implications for predicting the combined impact of climate, vegetation, and geology on groundwater resources. Future work will include distributed model simulations over the entire state, as well as conditioning uncertain vegetation and subsurface parameters on remote sensing data and statewide water table records using data assimilation.

Paleoclimate reconstruction through Bayesian data assimilation

NASA Astrophysics Data System (ADS)

Fer, I.; Raiho, A.; Rollinson, C.; Dietze, M.

2017-12-01

Methods of paleoclimate reconstruction from plant-based proxy data rely on assumptions of static vegetation-climate link which is often established between modern climate and vegetation. This approach might result in biased climate constructions as it does not account for vegetation dynamics. Predictive tools such as process-based dynamic vegetation models (DVM) and their Bayesian inversion could be used to construct the link between plant-based proxy data and palaeoclimate more realistically. In other words, given the proxy data, it is possible to infer the climate that could result in that particular vegetation composition, by comparing the DVM outputs to the proxy data within a Bayesian state data assimilation framework. In this study, using fossil pollen data from five sites across the northern hardwood region of the US, we assimilate fractional composition and aboveground biomass into dynamic vegetation models, LINKAGES, LPJ-GUESS and ED2. To do this, starting from 4 Global Climate Model outputs, we generate an ensemble of downscaled meteorological drivers for the period 850-2015. Then, as a first pass, we weigh these ensembles based on their fidelity with independent paleoclimate proxies. Next, we run the models with this ensemble of drivers, and comparing the ensemble model output to the vegetation data, adjust the model state estimates towards the data. At each iteration, we also reweight the climate values that make the model and data consistent, producing a reconstructed climate time-series dataset. We validated the method using present-day datasets, as well as a synthetic dataset, and then assessed the consistency of results across ecosystem models. Our method allows the combination of multiple data types to reconstruct the paleoclimate, with associated uncertainty estimates, based on ecophysiological and ecological processes rather than phenomenological correlations with proxy data.

Modeling forest dynamics along climate gradients in Bolivia

NASA Astrophysics Data System (ADS)

Seiler, C.; Hutjes, R. W. A.; Kruijt, B.; Quispe, J.; Añez, S.; Arora, V. K.; Melton, J. R.; Hickler, T.; Kabat, P.

2014-05-01

Dynamic vegetation models have been used to assess the resilience of tropical forests to climate change, but the global application of these modeling experiments often misrepresents carbon dynamics at a regional level, limiting the validity of future projections. Here a dynamic vegetation model (Lund Potsdam Jena General Ecosystem Simulator) was adapted to simulate present-day potential vegetation as a baseline for climate change impact assessments in the evergreen and deciduous forests of Bolivia. Results were compared to biomass measurements (819 plots) and remote sensing data. Using regional parameter values for allometric relations, specific leaf area, wood density, and disturbance interval, a realistic transition from the evergreen Amazon to the deciduous dry forest was simulated. This transition coincided with threshold values for precipitation (1400 mm yr-1) and water deficit (i.e., potential evapotranspiration minus precipitation) (-830 mm yr-1), beyond which leaf abscission became a competitive advantage. Significant correlations were found between modeled and observed values of seasonal leaf abscission (R2 = 0.6, p <0.001) and vegetation carbon (R2 = 0.31, p <0.01). Modeled Gross Primary Productivity (GPP) and remotely sensed normalized difference vegetation index showed that dry forests were more sensitive to rainfall anomalies than wet forests. GPP was positively correlated to the El Niño-Southern Oscillation index in the Amazon and negatively correlated to consecutive dry days. Decreasing rainfall trends were simulated to reduce GPP in the Amazon. The current model setup provides a baseline for assessing the potential impacts of climate change in the transition zone from wet to dry tropical forests in Bolivia.

Soil dynamics and accelerated erosion: a sensitivity analysis of the LPJ Dynamic vegetation model

NASA Astrophysics Data System (ADS)

Bouchoms, Samuel; Van Oost, Kristof; Vanacker, Veerle; Kaplan, Jed O.; Vanwalleghem, Tom

2013-04-01

It is widely accepted that humans have become a major geomorphic force by disturbing natural vegetation patterns. Land conversion for agriculture purposes removes the protection of soils by the natural vegetation and leads to increased soil erosion by one to two orders of magnitude, breaking the balance that exists between the loss of soils and its production. Accelerated erosion and deposition have a strong influence on evolution and heterogeneity of basic soil characteristics (soil thickness, hydrology, horizon development,…) as well as on organic matter storage and cycling. Yet, since they are operating at a long time scale, those processes are not represented in state-of-art Dynamic Global Vegetation Models, which is a clear lack when exploring vegetation dynamics over past centuries. The main objectives of this paper are (i) to test the sensitivity of a Dynamic Global Vegetation Model, in terms of NPP and organic matter turnover, variations in state variables in response to accelerated erosion and (ii) to assess the performance of the model under the impact of erosion for a case-study in Central Spain. We evaluated the Lund-Postdam-Jena Dynamic Vegetation Model (LPJ DVGM) (Sitch et al, 2003) which simulates vegetation growth and carbon pools at the surface and in the soil based on climatic, pedologic and topographic variables. We assessed its reactions to changes in key soil properties that are affected by erosion such as texture and soil depth. We present the results of where we manipulated soil texture and bulk density while keeping the environmental drivers of climate, slope and altitude constant. For parameters exhibiting a strong control on NPP or SOM, a factorial analysis was conducted to test for interaction effects. The simulations show an important dependence on the clay content, especially for the slow cycling carbon pools and the biomass production, though the underground litter seems to be mostly influenced by the silt content. The fast cycling C pools and/or the surface pools vary with sand and silt richness, the highest values being reached with a combination of 50% silt and 25% sand while the lowest are for a 100% clay soil. Finally, LPJ is run for three cases corresponding to a stable, erosive and depositional soil profile. These simulations show how the model reacts and performs under erosion/deposition conditions which are recreated by changing the soil's texture and soil depth over time. We discuss the performance of the LPJ model in the context of accelerated erosion and conclusions drawn from the sensitivity analysis.

FATE-HD: A spatially and temporally explicit integrated model for predicting vegetation structure and diversity at regional scale

PubMed Central

Isabelle, Boulangeat; Damien, Georges; Wilfried, Thuiller

2014-01-01

During the last decade, despite strenuous efforts to develop new models and compare different approaches, few conclusions have been drawn on their ability to provide robust biodiversity projections in an environmental change context. The recurring suggestions are that models should explicitly (i) include spatiotemporal dynamics; (ii) consider multiple species in interactions; and (iii) account for the processes shaping biodiversity distribution. This paper presents a biodiversity model (FATE-HD) that meets this challenge at regional scale by combining phenomenological and process-based approaches and using well-defined plant functional groups. FATE-HD has been tested and validated in a French National Park, demonstrating its ability to simulate vegetation dynamics, structure and diversity in response to disturbances and climate change. The analysis demonstrated the importance of considering biotic interactions, spatio-temporal dynamics, and disturbances in addition to abiotic drivers to simulate vegetation dynamics. The distribution of pioneer trees was particularly improved, as were all undergrowth functional groups. PMID:24214499

Effect of river flow fluctuations on riparian vegetation dynamics: Processes and models

NASA Astrophysics Data System (ADS)

Vesipa, Riccardo; Camporeale, Carlo; Ridolfi, Luca

2017-12-01

Several decades of field observations, laboratory experiments and mathematical modelings have demonstrated that the riparian environment is a disturbance-driven ecosystem, and that the main source of disturbance is river flow fluctuations. The focus of the present work has been on the key role that flow fluctuations play in determining the abundance, zonation and species composition of patches of riparian vegetation. To this aim, the scientific literature on the subject, over the last 20 years, has been reviewed. First, the most relevant ecological, morphological and chemical mechanisms induced by river flow fluctuations are described from a process-based perspective. The role of flow variability is discussed for the processes that affect the recruitment of vegetation, the vegetation during its adult life, and the morphological and nutrient dynamics occurring in the riparian habitat. Particular emphasis has been given to studies that were aimed at quantifying the effect of these processes on vegetation, and at linking them to the statistical characteristics of the river hydrology. Second, the advances made, from a modeling point of view, have been considered and discussed. The main models that have been developed to describe the dynamics of riparian vegetation have been presented. Different modeling approaches have been compared, and the corresponding advantages and drawbacks have been pointed out. Finally, attention has been paid to identifying the processes considered by the models, and these processes have been compared with those that have actually been observed or measured in field/laboratory studies.

A spatial simulation model of hydrology and vegetation dynamics in semi-permanent prairie wetlands

USGS Publications Warehouse

Poiani, Karen A.; Johnson, W. Carter

1993-01-01

The objective of this study was to construct a spatial simulation model of the vegetation dynamics in semi-permanent prairie wetlands. A hydrologic submodel estimated water levels based on precipitation, runoff, and potential evapotranspiration. A vegetation submodel calculated the amount and distribution of emergent cover and open water using a geographic information system. The response of vegetation to water-level changes was based on seed bank composition, seedling recruitment and establishment, and plant survivorship. The model was developed and tested using data from the Cottonwood Lake study site in North Dakota. Data from semi-permanent wetland P1 were used to calibrate the model. Data from a second wetland, P4, were used to evaluate model performance. Simulation results were compared with actual water data from 1797 through 1989. Test results showed that differences between calculated and observed water levels were within 10 cm 75% of the time. Open water over the past decade ranged from 0 to 7% in wetland P4 and from 0 to 8% in submodel simulations. Several model parameters including evapotranspiration and timing of seedling germination could be improved with more complex techniques or relatively minor adjustments. Despite these differences the model adequately represented vegetation dynamics of prairie wetlands and can be used to examine wetland response to natural or human-induced climate change.

Improving plant functional groups for dynamic models of biodiversity: at the crossroads between functional and community ecology

PubMed Central

Isabelle, Boulangeat; Pauline, Philippe; Sylvain, Abdulhak; Roland, Douzet; Luc, Garraud; Sébastien, Lavergne; Sandra, Lavorel; Jérémie, Van Es; Pascal, Vittoz; Wilfried, Thuiller

2013-01-01

The pace of on-going climate change calls for reliable plant biodiversity scenarios. Traditional dynamic vegetation models use plant functional types that are summarized to such an extent that they become meaningless for biodiversity scenarios. Hybrid dynamic vegetation models of intermediate complexity (hybrid-DVMs) have recently been developed to address this issue. These models, at the crossroads between phenomenological and process-based models, are able to involve an intermediate number of well-chosen plant functional groups (PFGs). The challenge is to build meaningful PFGs that are representative of plant biodiversity, and consistent with the parameters and processes of hybrid-DVMs. Here, we propose and test a framework based on few selected traits to define a limited number of PFGs, which are both representative of the diversity (functional and taxonomic) of the flora in the Ecrins National Park, and adapted to hybrid-DVMs. This new classification scheme, together with recent advances in vegetation modeling, constitutes a step forward for mechanistic biodiversity modeling. PMID:24403847

Nitrogen feedbacks increase future terrestrial ecosystem carbon uptake in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Wårlind, D.; Smith, B.; Hickler, T.; Arneth, A.

2014-01-01

Recently a considerable amount of effort has been put into quantifying how interactions of the carbon and nitrogen cycle affect future terrestrial carbon sinks. Dynamic vegetation models, representing the nitrogen cycle with varying degree of complexity, have shown diverging constraints of nitrogen dynamics on future carbon sequestration. In this study, we use the dynamic vegetation model LPJ-GUESS to evaluate how population dynamics and resource competition between plant functional types, combined with nitrogen dynamics, have influenced the terrestrial carbon storage in the past and to investigate how terrestrial carbon and nitrogen dynamics might change in the future (1850 to 2100; one exemplary "business-as-usual" climate scenario). Single factor model experiments of CO2 fertilisation and climate change show generally similar directions of the responses of C-N interactions, compared to the C-only version of the model, as documented in previous studies. Under a RCP 8.5 scenario, nitrogen limitation suppresses potential CO2 fertilisation, reducing the cumulative net ecosystem carbon uptake between 1850 and 2100 by 61%, and soil warming-induced increase in nitrogen mineralisation reduces terrestrial carbon loss by 31%. When environmental changes are considered conjointly, carbon sequestration is limited by nitrogen dynamics until present. However, during the 21st century nitrogen dynamics induce a net increase in carbon sequestration, resulting in an overall larger carbon uptake of 17% over the full period. This contradicts earlier model results that showed an 8 to 37% decrease in carbon uptake, questioning the often stated assumption that projections of future terrestrial C dynamics from C-only models are too optimistic.

Chapter 7: Developing climate-informed state-and-transition models

Treesearch

Miles A. Hemstrom; Jessica E. Halofsky; David R. Conklin; Joshua S. Halofsky; Dominique Bachelet; Becky K. Kerns

2014-01-01

Land managers and others need ways to understand the potential effects of climate change on local vegetation types and how management activities might be impacted by climate change. To date, climate change impact models have not included localized vegetation communities or the integrated effects of vegetation development dynamics, natural disturbances, and management...

Incorporating geometrically complex vegetation in a computational fluid dynamic framework

NASA Astrophysics Data System (ADS)

Boothroyd, Richard; Hardy, Richard; Warburton, Jeff; Rosser, Nick

2015-04-01

Vegetation is known to have a significant influence on the hydraulic, geomorphological, and ecological functioning of river systems. Vegetation acts as a blockage to flow, thereby causing additional flow resistance and influencing flow dynamics, in particular flow conveyance. These processes need to be incorporated into flood models to improve predictions used in river management. However, the current practice in representing vegetation in hydraulic models is either through roughness parameterisation or process understanding derived experimentally from flow through highly simplified configurations of fixed, rigid cylinders. It is suggested that such simplifications inadequately describe the geometric complexity that characterises vegetation, and therefore the modelled flow dynamics may be oversimplified. This paper addresses this issue by using an approach combining field and numerical modelling techniques. Terrestrial Laser Scanning (TLS) with waveform processing has been applied to collect a sub-mm, 3-dimensional representation of Prunus laurocerasus, an invasive species to the UK that has been increasingly recorded in riparian zones. Multiple scan perspectives produce a highly detailed point cloud (>5,000,000 individual data points) which is reduced in post processing using an octree-based voxelisation technique. The method retains the geometric complexity of the vegetation by subdividing the point cloud into 0.01 m3 cubic voxels. The voxelised representation is subsequently read into a computational fluid dynamic (CFD) model using a Mass Flux Scaling Algorithm, allowing the vegetation to be directly represented in the modelling framework. Results demonstrate the development of a complex flow field around the vegetation. The downstream velocity profile is characterised by two distinct inflection points. A high velocity zone in the near-bed (plant-stem) region is apparent due to the lack of significant near-bed foliage. Above this, a zone of reduced velocity is found where the bulk of the vegetation blockage is more evenly distributed. Finally, flow rapidly recovers towards the free-stream region. Analysis of the pressure field demonstrates that drag force is non-linearly distributed over the vegetation. In the downstream direction, the drag force decreases through the vegetation. The experiment is extended to emulate vegetation reconfiguration in the flow, and is achieved through rotation of the vegetation about a fixed position (roots) on the bed. The experiment demonstrates a reduction in the total drag force and a shift in the contribution of different drag mechanisms as the degree of rotation increases. In the upright state, form drag dominates, but with additional rotation, the contribution of viscous drag increases. Consequently, the total drag force is found to decrease by approximately one third between the upright and fully rotated states of reconfiguration. Explicit representation of vegetation geometry therefore enables a re-evaluation of vegetative flow resistance. This presents an opportunity to move away from the conventional methods of representing vegetation in hydraulic models, i.e. roughness parameterisation, in favour of a more physically determined approach.

The salt marsh vegetation spread dynamics simulation and prediction based on conditions optimized CA

NASA Astrophysics Data System (ADS)

Guan, Yujuan; Zhang, Liquan

2006-10-01

The biodiversity conservation and management of the salt marsh vegetation relies on processing their spatial information. Nowadays, more attentions are focused on their classification surveying and describing qualitatively dynamics based on RS images interpreted, rather than on simulating and predicting their dynamics quantitatively, which is of greater importance for managing and planning the salt marsh vegetation. In this paper, our notion is to make a dynamic model on large-scale and to provide a virtual laboratory in which researchers can run it according requirements. Firstly, the characteristic of the cellular automata was analyzed and a conclusion indicated that it was necessary for a CA model to be extended geographically under varying conditions of space-time circumstance in order to make results matched the facts accurately. Based on the conventional cellular automata model, the author introduced several new conditions to optimize it for simulating the vegetation objectively, such as elevation, growth speed, invading ability, variation and inheriting and so on. Hence the CA cells and remote sensing image pixels, cell neighbors and pixel neighbors, cell rules and nature of the plants were unified respectively. Taking JiuDuanSha as the test site, where holds mainly Phragmites australis (P.australis) community, Scirpus mariqueter (S.mariqueter) community and Spartina alterniflora (S.alterniflora) community. The paper explored the process of making simulation and predictions about these salt marsh vegetable changing with the conditions optimized CA (COCA) model, and examined the links among data, statistical models, and ecological predictions. This study exploited the potential of applying Conditioned Optimized CA model technique to solve this problem.

Lifting the Green Veil: A Fresh Look at Synoptic Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Henebry, G. M.; Vina, A.; Gitelson, A. A.

2003-12-01

Observing the dynamics of the vegetated land surface synoptically from spaceborne sensors plays a key role in understanding the global water, carbon, and nitrogen cycles, land cover and land use change, and biodiversity mapping. For the past three decades the study of global and regional vegetation dynamics has relied on satellite observations of the distinctive spectral contrast between red and near infrared reflectance exhibited by photosynthetically active green vegetation. It has long been recognized, however, that the spectral vegetation index with the widest currency-the Normalized Difference Vegetation Index (NDVI)-suffers a rapid decrease of sensitivity even at moderate Leaf Area Index (LAI) values of 2 to 4, as are commonly encountered in croplands and woodlands. This decrease in NDVI sensitivity casts a green veil over the land surface that obscures vegetation dynamics across vast areas during much of the growing season. This veil has important consequences for monitoring vegetation dynamics, developing land surface climatologies, and detecting significant changes. A straightforward modification of the NDVI, developed to increase its sensitivity under higher green biomass conditions, was applied to a standard, widely available AVHRR NDVI dataset for the conterminous US. The new Wide Dynamic Range Vegetation Index (WDRVI) exhibited increases in sensitivity between 30%-50% for Omernik Level III ecoregions dominated by woodlands, croplands, and grasslands. Ecoregions with lower aboveground net primary production, such as aridlands and semi-arid grasslands, showed no increase in sensitivity of the WDRVI over the NDVI. This powerful, new but simple approach creates an opportunity for a fresh look at the satellite data record. Further, it offers the possibility for significant improvements in the retrievals of canopy variables for carbon and nitrogen models, more accurate land surface characterizations for numerical weather prediction models, more sensitive analyses of land cover / land use change, and improvements in habitat mapping for biodiversity management.

Climate change and long-term fire management impacts on Australian savannas.

PubMed

Scheiter, Simon; Higgins, Steven I; Beringer, Jason; Hutley, Lindsay B

2015-02-01

Tropical savannas cover a large proportion of the Earth's land surface and many people are dependent on the ecosystem services that savannas supply. Their sustainable management is crucial. Owing to the complexity of savanna vegetation dynamics, climate change and land use impacts on savannas are highly uncertain. We used a dynamic vegetation model, the adaptive dynamic global vegetation model (aDGVM), to project how climate change and fire management might influence future vegetation in northern Australian savannas. Under future climate conditions, vegetation can store more carbon than under ambient conditions. Changes in rainfall seasonality influence future carbon storage but do not turn vegetation into a carbon source, suggesting that CO₂ fertilization is the main driver of vegetation change. The application of prescribed fires with varying return intervals and burning season influences vegetation and fire impacts. Carbon sequestration is maximized with early dry season fires and long fire return intervals, while grass productivity is maximized with late dry season fires and intermediate fire return intervals. The study has implications for management policy across Australian savannas because it identifies how fire management strategies may influence grazing yield, carbon sequestration and greenhouse gas emissions. This knowledge is crucial to maintaining important ecosystem services of Australian savannas. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Estimating drought induced tree mortality in the Amazon rainforest: A simulation study with a focus on plant hydraulic processes

NASA Astrophysics Data System (ADS)

Papastefanou, P.; Fleischer, K.; Hickler, T.; Grams, T.; Lapola, D.; Quesada, C. A.; Zang, C.; Rammig, A.

2017-12-01

The Amazon basin was recently hit by severe drought events that were unprecedented in their severity and spatial extent, e.g. during 2005, 2010 and 2015/2016. Significant amounts of biomass were lost, turning large parts of the rainforest from a carbon sink into a carbon source. It is assumed that drought-induced tree mortality from hydraulic failure played an important role during these events and may become more frequent in the Amazon region in the future. Many state-of-the-art dynamic vegetation models do not include plant hydraulic processes and fail to reproduce observed rainforest responses to drought events, such as e.g. increased tree mortality. We address this research gap by developing a simple plant-hydraulic module for the dynamic vegetation model LPJ-GUESS. This plant-hydraulic module uses leaf water potential and cavitation as baseline processes to simulate tree mortality under drought stress. Furthermore, we introduce different plant strategies in the model, which describe e.g. differences in the stomatal regulation under drought stress. To parameterize and evaluate our hydraulic module, we use a set of available observational data from the Amazon region. We apply our model to the Amazon Basin and highlight similarities and differences across other measured and predicted drought responses, e.g. extrapolated observations and data derived from satellite measurements. Our results highlight the importance of including plant hydraulic processes in dynamic vegetation models to correctly predict vegetation dynamics under drought stress and show major differences on the vegetation dynamics depending on the selected plant strategies. We also identify gaps in process understanding of the triggering factors, the extent and the consequences of drought responses that hampers our ability to predict potential impact of future drought events on the Amazon rainforest.

Monitoring vegetation phenology using MODIS

USGS Publications Warehouse

Zhang, Xiayong; Friedl, Mark A.; Schaaf, Crystal B.; Strahler, Alan H.; Hodges, John C.F.; Gao, Feng; Reed, Bradley C.; Huete, Alfredo

2003-01-01

Accurate measurements of regional to global scale vegetation dynamics (phenology) are required to improve models and understanding of inter-annual variability in terrestrial ecosystem carbon exchange and climate–biosphere interactions. Since the mid-1980s, satellite data have been used to study these processes. In this paper, a new methodology to monitor global vegetation phenology from time series of satellite data is presented. The method uses series of piecewise logistic functions, which are fit to remotely sensed vegetation index (VI) data, to represent intra-annual vegetation dynamics. Using this approach, transition dates for vegetation activity within annual time series of VI data can be determined from satellite data. The method allows vegetation dynamics to be monitored at large scales in a fashion that it is ecologically meaningful and does not require pre-smoothing of data or the use of user-defined thresholds. Preliminary results based on an annual time series of Moderate Resolution Imaging Spectroradiometer (MODIS) data for the northeastern United States demonstrate that the method is able to monitor vegetation phenology with good success.

Tropical Tree Trait Diversity Enhances Forest Biomass Resilience in a Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Sakschewski, B.; Kirsten, T.; von Bloh, W.; Poorter, L.; Pena-Claros, M.; Boit, A.

2016-12-01

Functional diversity of ecosystems has been found to increase ecosystem functions and therefore enhance ecosystem resilience against environmental stressors. However, global carbon-cycle and biosphere models still classify the global vegetation into a relatively small number of distinct plant functional types (PFT) with constant features over space and time. Therefore, those models might underestimate the resilience and adaptive capacity of natural vegetation under climate change by ignoring positive effects that functional diversity might bring about. We diversified a set a of selected tree traits in a dynamic global vegetation model (LPJmL). In the new subversion, called LPJmL-FIT, Amazon region biomass stocks and forest structure appear significantly more resilient against climate change. Enhanced tree trait diversity enables the simulated rainforests to adjust to new environmental conditions via ecological sorting. These results may stimulate a new debate on the value of biodiversity for climate change mitigation.

Modelling carbon fluxes of forest and grassland ecosystems in Western Europe using the CARAIB dynamic vegetation model: evaluation against eddy covariance data.

NASA Astrophysics Data System (ADS)

Henrot, Alexandra-Jane; François, Louis; Dury, Marie; Hambuckers, Alain; Jacquemin, Ingrid; Minet, Julien; Tychon, Bernard; Heinesch, Bernard; Horemans, Joanna; Deckmyn, Gaby

2015-04-01

Eddy covariance measurements are an essential resource to understand how ecosystem carbon fluxes react in response to climate change, and to help to evaluate and validate the performance of land surface and vegetation models at regional and global scale. In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), vegetation dynamics and carbon fluxes of forest and grassland ecosystems simulated by the CARAIB dynamic vegetation model (Dury et al., iForest - Biogeosciences and Forestry, 4:82-99, 2011) are evaluated and validated by comparison of the model predictions with eddy covariance data. Here carbon fluxes (e.g. net ecosystem exchange (NEE), gross primary productivity (GPP), and ecosystem respiration (RECO)) and evapotranspiration (ET) simulated with the CARAIB model are compared with the fluxes measured at several eddy covariance flux tower sites in Belgium and Western Europe, chosen from the FLUXNET global network (http://fluxnet.ornl.gov/). CARAIB is forced either with surface atmospheric variables derived from the global CRU climatology, or with in situ meteorological data. Several tree (e.g. Pinus sylvestris, Fagus sylvatica, Picea abies) and grass species (e.g. Poaceae, Asteraceae) are simulated, depending on the species encountered on the studied sites. The aim of our work is to assess the model ability to reproduce the daily, seasonal and interannual variablility of carbon fluxes and the carbon dynamics of forest and grassland ecosystems in Belgium and Western Europe.

Chapter 6 - Developing the LANDFIRE Vegetation and Biophysical Settings Map Unit Classifications for the LANDFIRE Prototype Project

Treesearch

Jennifer L. Long; Melanie Miller; James P. Menakis; Robert E. Keane

2006-01-01

The Landscape Fire and Resource Management Planning Tools Prototype Project, or LANDFIRE Prototype Project, required a system for classifying vegetation composition, biophysical settings, and vegetation structure to facilitate the mapping of vegetation and wildland fuel characteristics and the simulation of vegetation dynamics using landscape modeling. We developed...

Stochastic simulation of ecohydrological interactions between vegetation and groundwater

NASA Astrophysics Data System (ADS)

Dwelle, M. C.; Ivanov, V. Y.; Sargsyan, K.

2017-12-01

The complex interactions between groundwater and vegetation in the Amazon rainforest may yield vital ecophysiological interactions in specific landscape niches such as buffering plant water stress during dry season or suppression of water uptake due to anoxic conditions. Representation of such processes is greatly impacted by both external and internal sources of uncertainty: inaccurate data and subjective choice of model representation. The models that can simulate these processes are complex and computationally expensive, and therefore make it difficult to address uncertainty using traditional methods. We use the ecohydrologic model tRIBS+VEGGIE and a novel uncertainty quantification framework applied to the ZF2 watershed near Manaus, Brazil. We showcase the capability of this framework for stochastic simulation of vegetation-hydrology dynamics. This framework is useful for simulation with internal and external stochasticity, but this work will focus on internal variability of groundwater depth distribution and model parameterizations. We demonstrate the capability of this framework to make inferences on uncertain states of groundwater depth from limited in situ data, and how the realizations of these inferences affect the ecohydrological interactions between groundwater dynamics and vegetation function. We place an emphasis on the probabilistic representation of quantities of interest and how this impacts the understanding and interpretation of the dynamics at the groundwater-vegetation interface.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model.

PubMed

Shafer, Sarah L; Bartlein, Patrick J; Gray, Elizabeth M; Pelltier, Richard T

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0-58.0°N latitude by 136.6-103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070-2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected vegetation changes for the American Southwest: combined dynamic modeling and bioclimatic-envelope approach.

PubMed

Notaro, Michael; Mauss, Adrien; Williams, John W

2012-06-01

This study focuses on potential impacts of 21st century climate change on vegetation in the Southwest United States, based on debiased and interpolated climate projections from 17 global climate models used in the Fourth Assessment Report of the Intergovernmental Panel on Climate Change. Among these models a warming trend is universal, but projected changes in precipitation vary in sign and magnitude. Two independent methods are applied: a dynamic global vegetation model to assess changes in plant functional types and bioclimatic envelope modeling to assess changes in individual tree and shrub species and biodiversity. The former approach investigates broad responses of plant functional types to climate change, while considering competition, disturbances, and carbon fertilization, while the latter approach focuses on the response of individual plant species, and net biodiversity, to climate change. The dynamic model simulates a region-wide reduction in vegetation cover during the 21st century, with a partial replacement of evergreen trees with grasses in the mountains of Colorado and Utah, except at the highest elevations, where tree cover increases. Across southern Arizona, central New Mexico, and eastern Colorado, grass cover declines, in some cases abruptly. Due to the prevalent warming trend among all 17 climate models, vegetation cover declines in the 21st century, with the greatest vegetation losses associated with models that project a drying trend. The inclusion of the carbon fertilization effect largely ameliorates the projected vegetation loss. Based on bioclimatic envelope modeling for the 21st century, the number of tree and shrub species that are expected to experience robust declines in range likely outweighs the number of species that are expected to expand in range. Dramatic shifts in plant species richness are projected, with declines in the high-elevation evergreen forests, increases in the eastern New Mexico prairies, and a northward shift of the Sonoran Desert biodiversity maximum.

A review on vegetation models and applicability to climate simulations at regional scale

NASA Astrophysics Data System (ADS)

Myoung, Boksoon; Choi, Yong-Sang; Park, Seon Ki

2011-11-01

The lack of accurate representations of biospheric components and their biophysical and biogeochemical processes is a great source of uncertainty in current climate models. The interactions between terrestrial ecosystems and the climate include exchanges not only of energy, water and momentum, but also of carbon and nitrogen. Reliable simulations of these interactions are crucial for predicting the potential impacts of future climate change and anthropogenic intervention on terrestrial ecosystems. In this paper, two biogeographical (Neilson's rule-based model and BIOME), two biogeochemical (BIOME-BGC and PnET-BGC), and three dynamic global vegetation models (Hybrid, LPJ, and MC1) were reviewed and compared in terms of their biophysical and physiological processes. The advantages and limitations of the models were also addressed. Lastly, the applications of the dynamic global vegetation models to regional climate simulations have been discussed.

Who's driving?: Separating Fire, CO2, and Climate Change Influences on Vegetation and Carbon Dynamics on MC2 Results for Western Oregon and Washington, United States

NASA Astrophysics Data System (ADS)

Sheehan, T.; Bachelet, D. M.; Ferschweiler, K.

2016-12-01

For Oregon and Washington west of the Cascade Mountain crest, results from the MC2 global dynamic vegetation model have projected a shift in potential vegetation type from predominantly conifer to predominantly mixed forest over the 21st century, with a shift from mixed to conifer in some areas. Carbon stocks have been projected to fall over this period. We ran MC2 using the CCSM4 RCP 8.5 climate future downscaled to 2.5 arc minute resolution with 5 different configurations: no fire; assumed ignitions without fire suppression; assumed ignitions with fire suppression; assumed ignitions with fire suppression and with CO2 concentration held at the preindustrial level; and stochastic ignitions without fire suppression. Results show that vegetation change is the result of climate change alone, while carbon is influenced by both fire occurrence and CO2-induced increased water use efficiency. While model results do not indicate a large change in carbon dynamics concomitant with the shift in vegetation, it is reasonable to expect that a change in conditions resulting in such a change in vegetation type would stress the existing vegetation resulting in some mortality and loss of live carbon.

Simulation Based Exploration of Critical Zone Dynamics in Intensively Managed Landscapes

NASA Astrophysics Data System (ADS)

Kumar, P.

2017-12-01

The advent of high-resolution measurements of topographic and (vertical) vegetation features using areal LiDAR are enabling us to resolve micro-scale ( 1m) landscape structural characteristics over large areas. Availability of hyperspectral measurements is further augmenting these LiDAR data by enabling the biogeochemical characterization of vegetation and soils at unprecedented spatial resolutions ( 1-10m). Such data have opened up novel opportunities for modeling Critical Zone processes and exploring questions that were not possible before. We show how an integrated 3-D model at 1m grid resolution can enable us to resolve micro-topographic and ecological dynamics and their control on hydrologic and biogeochemical processes over large areas. We address the computational challenge of such detailed modeling by exploiting hybrid CPU and GPU computing technologies. We show results of moisture, biogeochemical, and vegetation dynamics from studies in the Critical Zone Observatory for Intensively managed Landscapes (IMLCZO) in the Midwestern United States.

Competition between hardwood hammocks and mangroves

USGS Publications Warehouse

Sternberg, L.D.S.L.; Teh, S.Y.; Ewe, S.M.L.; Miralles-Wilhelm, F.; DeAngelis, D.L.

2007-01-01

The boundaries between mangroves and freshwater hammocks in coastal ecotones of South Florida are sharp. Further, previous studies indicate that there is a discontinuity in plant predawn water potentials, with woody plants either showing predawn water potentials reflecting exposure to saline water or exposure to freshwater. This abrupt concurrent change in community type and plant water status suggests that there might be feedback dynamics between vegetation and salinity. A model examining the salinity of the aerated zone of soil overlying a saline body of water, known as the vadose layer, as a function of precipitation, evaporation and plant water uptake is presented here. The model predicts that mixtures of saline and freshwater vegetative species represent unstable states. Depending on the initial vegetation composition, subsequent vegetative change will lead either to patches of mangrove coverage having a high salinity vadose zone or to freshwater hammock coverage having a low salinity vadose zone. Complete or nearly complete coverage by either freshwater or saltwater vegetation represents two stable steady-state points. This model can explain many of the previous observations of vegetation patterns in coastal South Florida as well as observations on the dynamics of vegetation shifts caused by sea level rise and climate change. ?? 2007 Springer Science+Business Media, LLC.

Vegetation in drylands: Effects on wind flow and aeolian sediment transport

USDA-ARS?s Scientific Manuscript database

Drylands are characterised by patchy vegetation, erodible surfaces and erosive aeolian processes. Empirical and modelling studies have shown that vegetation elements provide drag on the overlying airflow, thus affecting wind velocity profiles and altering erosive dynamics on desert surfaces. However...

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Miao; Wang, Guiling; Chen, Haishan

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Quantifying the impacts of land surface schemes and dynamic vegetation on the model dependency of projected changes in surface energy and water budgets

DOE PAGES

Yu, Miao; Wang, Guiling; Chen, Haishan

2016-03-01

Assessing and quantifying the uncertainties in projected future changes of energy and water budgets over land surface are important steps toward improving our confidence in climate change projections. In our study, the contribution of land surface models to the inter-GCM variation of projected future changes in land surface energy and water fluxes are assessed based on output from 19 global climate models (GCMs) and offline Community Land Model version 4 (CLM4) simulations driven by meteorological forcing from the 19 GCMs. Similar offline simulations using CLM4 with its dynamic vegetation submodel are also conducted to investigate how dynamic vegetation feedback, amore » process that is being added to more earth system models, may amplify or moderate the intermodel variations of projected future changes. Projected changes are quantified as the difference between the 2081–2100 period from the Representative Concentration Pathway 8.5 (RCP8.5) future experiment and the 1981–2000 period from the historical simulation. Under RCP8.5, projected changes in surface water and heat fluxes show a high degree of model dependency across the globe. Although precipitation is very likely to increase in the high latitudes of the Northern Hemisphere, a high degree of model-related uncertainty exists for evapotranspiration, soil water content, and surface runoff, suggesting discrepancy among land surface models (LSMs) in simulating the surface hydrological processes and snow-related processes. Large model-related uncertainties for the surface water budget also exist in the Tropics including southeastern South America and Central Africa. Moreover, these uncertainties would be reduced in the hypothetical scenario of a single near-perfect land surface model being used across all GCMs, suggesting the potential to reduce uncertainties through the use of more consistent approaches toward land surface model development. Under such a scenario, the most significant reduction is likely to be seen in the Northern Hemisphere high latitudes. Including representation of vegetation dynamics is expected to further amplify the model-related uncertainties in projected future changes in surface water and heat fluxes as well as soil moisture content. This is especially the case in the high latitudes of the Northern Hemisphere (e.g., northwestern North America and central North Asia) where the projected vegetation changes are uncertain and in the Tropics (e.g., the Amazon and Congo Basins) where dense vegetation exists. Finally, findings from this study highlight the importance of improving land surface model parameterizations related to soil and snow processes, as well as the importance of improving the accuracy of dynamic vegetation models.« less

Climate-vegetation modelling and fossil plant data suggest low atmospheric CO2 in the late Miocene

NASA Astrophysics Data System (ADS)

Forrest, M.; Eronen, J. T.; Utescher, T.; Knorr, G.; Stepanek, C.; Lohmann, G.; Hickler, T.

2015-12-01

There is an increasing need to understand the pre-Quaternary warm climates, how climate-vegetation interactions functioned in the past, and how we can use this information to understand the present. Here we report vegetation modelling results for the Late Miocene (11-7 Ma) to study the mechanisms of vegetation dynamics and the role of different forcing factors that influence the spatial patterns of vegetation coverage. One of the key uncertainties is the atmospheric concentration of CO2 during past climates. Estimates for the last 20 million years range from 280 to 500 ppm. We simulated Late Miocene vegetation using two plausible CO2 concentrations, 280 ppm CO2 and 450 ppm CO2, with a dynamic global vegetation model (LPJ-GUESS) driven by climate input from a coupled AOGCM (Atmosphere-Ocean General Circulation Model). The simulated vegetation was compared to existing plant fossil data for the whole Northern Hemisphere. For the comparison we developed a novel approach that uses information of the relative dominance of different plant functional types (PFTs) in the palaeobotanical data to provide a quantitative estimate of the agreement between the simulated and reconstructed vegetation. Based on this quantitative assessment we find that pre-industrial CO2 levels are largely consistent with the presence of seasonal temperate forests in Europe (suggested by fossil data) and open vegetation in North America (suggested by multiple lines of evidence). This suggests that during the Late Miocene the CO2 levels have been relatively low, or that other factors that are not included in the models maintained the seasonal temperate forests and open vegetation.

A nonlinear coupled soil moisture-vegetation model

NASA Astrophysics Data System (ADS)

Liu, Shikuo; Liu, Shida; Fu, Zuntao; Sun, Lan

2005-06-01

Based on the physical analysis that the soil moisture and vegetation depend mainly on the precipitation and evaporation as well as the growth, decay and consumption of vegetation a nonlinear dynamic coupled system of soil moisture-vegetation is established. Using this model, the stabilities of the steady states of vegetation are analyzed. This paper focuses on the research of the vegetation catastrophe point which represents the transition between aridness and wetness to a great extent. It is shown that the catastrophe point of steady states of vegetation depends mainly on the rainfall P and saturation value v0, which is selected to balance the growth and decay of vegetation. In addition, when the consumption of vegetation remains constant, the analytic solution of the vegetation equation is obtained.

Modeling Elevation and Aspect Controls on Emerging Ecohydrologic Processes and Ecosystem Patterns Using the Component-based Landlab Framework

NASA Astrophysics Data System (ADS)

Nudurupati, S. S.; Istanbulluoglu, E.; Adams, J. M.; Hobley, D. E. J.; Gasparini, N. M.; Tucker, G. E.; Hutton, E. W. H.

2014-12-01

Topography plays a commanding role on the organization of ecohydrologic processes and resulting vegetation patterns. In southwestern United States, climate conditions lead to terrain aspect- and elevation-controlled ecosystems, with mesic north-facing and xeric south-facing vegetation types; and changes in biodiversity as a function of elevation from shrublands in low desert elevations, to mixed grass/shrublands in mid elevations, and forests at high elevations and ridge tops. These observed patterns have been attributed to differences in topography-mediated local soil moisture availability, micro-climatology, and life history processes of plants that control chances of plant establishment and survival. While ecohydrologic models represent local vegetation dynamics in sufficient detail up to sub-hourly time scales, plant life history and competition for space and resources has not been adequately represented in models. In this study we develop an ecohydrologic cellular automata model within the Landlab component-based modeling framework. This model couples local vegetation dynamics (biomass production, death) and plant establishment and competition processes for resources and space. This model is used to study the vegetation organization in a semiarid New Mexico catchment where elevation and hillslope aspect play a defining role on plant types. Processes that lead to observed plant types across the landscape are examined by initializing the domain with randomly assigned plant types and systematically changing model parameters that couple plant response with soil moisture dynamics. Climate perturbation experiments are conducted to examine the plant response in space and time. Understanding the inherently transient ecohydrologic systems is critical to improve predictions of climate change impacts on ecosystems.

The role of deep nitrogen and dynamic rooting profiles on vegetation dynamics and productivity in response to permafrost thaw and climate change in Arctic tundra

NASA Astrophysics Data System (ADS)

Hewitt, R. E.; Helene, G.; Taylor, D. L.; McGuire, A. D.; Mack, M. C.

2017-12-01

The release of permafrost-derived nitrogen (N) has the potential to fertilize tundra vegetation, modulating plant competition, stimulating productivity, and offsetting carbon losses from thawing permafrost. Dynamic rooting, mycorrhizal interactions, and coupling of N availability and root N uptake have been identified as gaps in ecosystem models. As a first step towards understanding whether Arctic plants can access deep permafrost-derived N, we characterized rooting profiles and quantified acquisition of 15N tracer applied at the permafrost boundary by moist acidic tundra plants subjected to almost three decades of warming at Toolik Lake, Alaska. In the ambient control plots the vegetation biomass is distributed between five plant functional types (PFTs): sedges, evergreen and deciduous shrubs, mosses and in lower abundance, forbs. The warming treatment has resulted in the increase of deciduous shrub biomass and the loss of sedges, evergreen shrubs, and mosses. We harvested roots by depth increment down to the top of the permafrost. Roots were classified by size class and PFT. The average thaw depth in the warmed plots was 58.3 cm ± 6.4 S.E., close to 18 cm deeper than the average thaw depth in the ambient plots (40.8 cm ± 1.8 S.E.). Across treatments the deepest rooting species was Rubus chamaemorus (ambient 40.8 cm ± 1.8 S.E., warmed 50.3 cm ± 9.8 S.E.), a non-mycorrhizal forb, followed by Eriophorum vaginatum, a non-mycorrhizal sedge. Ectomycorrhizal deciduous and ericoid mycorrhizal evergreen shrubs were rooted at more shallow depths. Deeply rooted non-mycorrhizal species had the greatest uptake of 15N tracer within 24 hours across treatments. Tracer uptake was greatest for roots of E. vaginatum in ambient plots and R. chamaemorus in warmed plots. Root profiles were integrated into a process-based ecosystem model coupled with a dynamic vegetation model. Functions modeling dynamic rooting profile relative to thaw depth were implemented for each PFT. The goal of the model simulations is to evaluate the relative effect of deep N acquisition and dynamic rooting profile on site level vegetation productivity. This modeling exercise will contribute to more accurate predictions of vegetation change in the Arctic modulated by belowground plant traits and changing soil resources with warming.

Projected climate and vegetation changes and potential biotic effects for Fort Benning, Georgia; Fort Hood, Texas; and Fort Irwin, California

USGS Publications Warehouse

Shafer, S.L.; Atkins, J.; Bancroft, B.A.; Bartlein, P.J.; Lawler, J.J.; Smith, B.; Wilsey, C.B.

2012-01-01

The responses of species and ecosystems to future climate changes will present challenges for conservation and natural resource managers attempting to maintain both species populations and essential habitat. This report describes projected future changes in climate and vegetation for three study areas surrounding the military installations of Fort Benning, Georgia, Fort Hood, Texas, and Fort Irwin, California. Projected climate changes are described for the time period 2070–2099 (30-year mean) as compared to 1961–1990 (30-year mean) for each study area using data simulated by the coupled atmosphere-ocean general circulation models CCSM3, CGCM3.1(T47), and UKMO-HadCM3, run under the B1, A1B, and A2 future greenhouse gas emissions scenarios. These climate data are used to simulate potential changes in important components of the vegetation for each study area using LPJ, a dynamic global vegetation model, and LPJ-GUESS, a dynamic vegetation model optimized for regional studies. The simulated vegetation results are compared with observed vegetation data for the study areas. Potential effects of the simulated future climate and vegetation changes for species and habitats of management concern are discussed in each study area, with a particular focus on federally listed threatened and endangered species.

Impact of dynamic vegetation phenology on the simulated pan-Arctic land surface state

NASA Astrophysics Data System (ADS)

Teufel, Bernardo; Sushama, Laxmi; Arora, Vivek K.; Verseghy, Diana

2018-03-01

The pan-Arctic land surface is undergoing rapid changes in a warming climate, with near-surface permafrost projected to degrade significantly during the twenty-first century. Vegetation-related feedbacks have the potential to influence the rate of degradation of permafrost. In this study, the impact of dynamic phenology on the pan-Arctic land surface state, particularly near-surface permafrost, for the 1961-2100 period, is assessed by comparing two simulations of the Canadian Land Surface Scheme (CLASS)—one with dynamic phenology, modelled using the Canadian Terrestrial Ecosystem Model (CTEM), and the other with prescribed phenology. These simulations are forced by atmospheric data from a transient climate change simulation of the 5th generation Canadian Regional Climate Model (CRCM5) for the Representative Concentration Pathway 8.5 (RCP8.5). Comparison of the CLASS coupled to CTEM simulation to available observational estimates of plant area index, spatial distribution of permafrost and active layer thickness suggests that the model captures reasonably well the overall distribution of vegetation and permafrost. It is shown that the most important impact of dynamic phenology on the land surface occurs through albedo and it is demonstrated for the first time that vegetation control on albedo during late spring and early summer has the highest potential to impact the degradation of permafrost. While both simulations show extensive near-surface permafrost degradation by the end of the twenty-first century, the strong projected response of vegetation to climate warming and increasing CO2 concentrations in the coupled simulation results in accelerated permafrost degradation in the northernmost continuous permafrost regions.

Model estimation of land-use effects on water levels of northern Prairie wetlands

USGS Publications Warehouse

Voldseth, R.A.; Johnson, W.C.; Gilmanov, T.; Guntenspergen, G.R.; Millett, B.V.

2007-01-01

Wetlands of the Prairie Pothole Region exist in a matrix of grassland dominated by intensive pastoral and cultivation agriculture. Recent conservation management has emphasized the conversion of cultivated farmland and degraded pastures to intact grassland to improve upland nesting habitat. The consequences of changes in land-use cover that alter watershed processes have not been evaluated relative to their effect on the water budgets and vegetation dynamics of associated wetlands. We simulated the effect of upland agricultural practices on the water budget and vegetation of a semipermanent prairie wetland by modifying a previously published mathematical model (WETSIM). Watershed cover/land-use practices were categorized as unmanaged grassland (native grass, smooth brome), managed grassland (moderately heavily grazed, prescribed burned), cultivated crops (row crop, small grain), and alfalfa hayland. Model simulations showed that differing rates of evapotranspiration and runoff associated with different upland plant-cover categories in the surrounding catchment produced differences in wetland water budgets and linked ecological dynamics. Wetland water levels were highest and vegetation the most dynamic under the managed-grassland simulations, while water levels were the lowest and vegetation the least dynamic under the unmanaged-grassland simulations. The modeling results suggest that unmanaged grassland, often planted for waterfowl nesting, may produce the least favorable wetland conditions for birds, especially in drier regions of the Prairie Pothole Region. These results stand as hypotheses that urgently need to be verified with empirical data.

Vegetation of Upper Coastal Plain Depression Wetlands: Environmental Templates and Wetland Dynamics Within A Landscape Framework

Treesearch

Diane De Steven; Maureen M. Toner

2004-01-01

Reference wetlands play an important role in efforts to protect wetlands and assess wetland condition. Because wetland vegetation integrates the influence of many ecological factors, a useful reference system would identify natural vegetation types and include models relating vegetation to important regional geomorphic, hydrologic, and geochemical properties. Across...

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model.

PubMed

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-03-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45(o)N and polewards) for the period 1900-2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue.

Simulating dynamic and mixed-severity fire regimes: a process-based fire extension for LANDIS-II

Treesearch

Brian R. Sturtevant; Robert M. Scheller; Brian R. Miranda; Douglas Shinneman; Alexandra Syphard

2009-01-01

Fire regimes result from reciprocal interactions between vegetation and fire that may be further affected by other disturbances, including climate, landform, and terrain. In this paper, we describe fire and fuel extensions for the forest landscape simulation model, LANDIS-II, that allow dynamic interactions among fire, vegetation, climate, and landscape structure, and...

Effect of climate fluctuation on long-term vegetation dynamics in Carolina bay wetlands

Treesearch

Chrissa Stroh; Diane De Steven; Glenn Guntenspergen

2008-01-01

Carolina bays and similar depression wetlands of the U. S. Southeastern Coastal Plain have hydrologic regimes that are driven primarily by rainfall. Therefore, climate fluctuations such as drought cycles have the potential to shape long-term vegetation dynamics. Models suggest two potential long-term responses to hydrologic fluctuations, either cyclic change...

Influence of climate variability, fire and phosphorus limitation on vegetation structure and dynamics of the Amazon-Cerrado border

NASA Astrophysics Data System (ADS)

Ane Dionizio, Emily; Heil Costa, Marcos; de Almeida Castanho, Andrea D.; Ferreira Pires, Gabrielle; Schwantes Marimon, Beatriz; Hur Marimon-Junior, Ben; Lenza, Eddie; Martins Pimenta, Fernando; Yang, Xiaojuan; Jain, Atul K.

2018-02-01

Climate, fire and soil nutrient limitation are important elements that affect vegetation dynamics in areas of the forest-savanna transition. In this paper, we use the dynamic vegetation model INLAND to evaluate the influence of interannual climate variability, fire and phosphorus (P) limitation on Amazon-Cerrado transitional vegetation structure and dynamics. We assess how each environmental factor affects net primary production, leaf area index and aboveground biomass (AGB), and compare the AGB simulations to an observed AGB map. We used two climate data sets (monthly average climate for 1961-1990 and interannual climate variability for 1948-2008), two data sets of total soil P content (one based on regional field measurements and one based on global data), and the INLAND fire module. Our results show that the inclusion of interannual climate variability, P limitation and fire occurrence each contribute to simulating vegetation types that more closely match observations. These effects are spatially heterogeneous and synergistic. In terms of magnitude, the effect of fire is strongest and is the main driver of vegetation changes along the transition. Phosphorus limitation, in turn, has a stronger effect on transitional ecosystem dynamics than interannual climate variability does. Overall, INLAND typically simulates more than 80 % of the AGB variability in the transition zone. However, the AGB in many places is clearly not well simulated, indicating that important soil and physiological factors in the Amazon-Cerrado border region, such as lithology, water table depth, carbon allocation strategies and mortality rates, still need to be included in the model.

An ecohydrological model for studying groundwater-vegetation interactions in wetlands

NASA Astrophysics Data System (ADS)

Chui, Ting Fong May; Low, Swee Yang; Liong, Shie-Yui

2011-10-01

SummaryDespite their importance to the natural environment, wetlands worldwide face drastic degradation from changes in land use and climatic patterns. To help preservation efforts and guide conservation strategies, a clear understanding of the dynamic relationship between coupled hydrology and vegetation systems in wetlands, and their responses to engineering works and climate change, is needed. An ecohydrological model was developed in this study to address this issue. The model combines a hydrology component based on the Richards' equation for characterizing variably saturated groundwater flow, with a vegetation component described by Lotka-Volterra equations tailored for plant growth. Vegetation is represented by two characteristic wetland herbaceous plant types which differ in their flood and drought resistances. Validation of the model on a study site in the Everglades demonstrated the capability of the model in capturing field-measured water table and transpiration dynamics. The model was next applied on a section of the Nee Soon swamp forest, a tropical wetland in Singapore, for studying the impact of possible drainage works on the groundwater hydrology and native vegetation. Drainage of 10 m downstream of the wetland resulted in a localized zone of influence within half a kilometer from the drainage site with significant adverse impacts on groundwater and biomass levels, indicating a strong need for conservation. Simulated water table-plant biomass relationships demonstrated the capability of the model in capturing the time-lag in biomass response to water table changes. To test the significance of taking plant growth into consideration, the performance of the model was compared to one that substituted the vegetation component with a pre-specified evapotranspiration rate. Unlike its revised counterpart, the original ecohydrological model explicitly accounted for the drainage-induced plant biomass decrease and translated the resulting reduced transpiration toll back to the groundwater hydrology for a more accurate soil water balance. This study represents, to our knowledge, the first development of an ecohydrological model for wetland ecosystems that characterizes the coupled relationship between variably-saturated groundwater flow and plant growth dynamics.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems

PubMed Central

Wullschleger, Stan D.; Epstein, Howard E.; Box, Elgene O.; Euskirchen, Eugénie S.; Goswami, Santonu; Iversen, Colleen M.; Kattge, Jens; Norby, Richard J.; van Bodegom, Peter M.; Xu, Xiaofeng

2014-01-01

Background Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Scope Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. Conclusions Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait–environment relationships. Surprisingly, despite being important to land–atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings. PMID:24793697

Integrated modeling of long-term vegetation and hydrologic dynamics in Rocky Mountain watersheds

Treesearch

Robert Steven Ahl

2007-01-01

Changes in forest structure resulting from natural disturbances, or managed treatments, can have negative and long lasting impacts on water resources. To facilitate integrated management of forest and water resources, a System for Long-Term Integrated Management Modeling (SLIMM) was developed. By combining two spatially explicit, continuous time models, vegetation...

Feedback of observed interannual vegetation change: a regional climate model analysis for the West African monsoon

NASA Astrophysics Data System (ADS)

Klein, Cornelia; Bliefernicht, Jan; Heinzeller, Dominikus; Gessner, Ursula; Klein, Igor; Kunstmann, Harald

2017-05-01

West Africa is a hot spot region for land-atmosphere coupling where atmospheric conditions and convective rainfall can strongly depend on surface characteristics. To investigate the effect of natural interannual vegetation changes on the West African monsoon precipitation, we implement satellite-derived dynamical datasets for vegetation fraction (VF), albedo and leaf area index into the Weather Research and Forecasting model. Two sets of 4-member ensembles with dynamic and static land surface description are used to extract vegetation-related changes in the interannual difference between August-September 2009 and 2010. The observed vegetation patterns retain a significant long-term memory of preceding rainfall patterns of at least 2 months. The interannual vegetation changes exhibit the strongest effect on latent heat fluxes and associated surface temperatures. We find a decrease (increase) of rainy hours over regions with higher (lower) VF during the day and the opposite during the night. The probability that maximum precipitation is shifted to nighttime (daytime) over higher (lower) VF is 12 % higher than by chance. We attribute this behaviour to horizontal circulations driven by differential heating. Over more vegetated regions, the divergence of moist air together with lower sensible heat fluxes hinders the initiation of deep convection during the day. During the night, mature convective systems cause an increase in the number of rainy hours over these regions. We identify this feedback in both water- and energy-limited regions of West Africa. The inclusion of observed dynamical surface information improved the spatial distribution of modelled rainfall in the Sahel with respect to observations, illustrating the potential of satellite data as a boundary constraint for atmospheric models.

Vegetation cover dynamics of the Mongolian semiarid zone according to multi-temporal LANDSAT imagery (the case of Darkhan test range)

NASA Astrophysics Data System (ADS)

Zharnikova, M. A.; Alymbaeva, ZH B.; Ayurzhanaev, A. A.; Garmaev, E. ZH

2016-11-01

At present much attention is given to the spatio-temporal dynamics of plant communities of steppes to assess their response to the current climate changes. In this study, a mapping of a selected modeling polygon was carried out on the basis of data decoding and field surveys of vegetation cover in the semi-arid zone. The resulting large-scale map of actual vegetation reflects the current state of the vegetation cover and its horizontal structure. It is a valuable material for monitoring of changes in the chosen area. With multi-temporal satellite Landsat imagery we consider the vegetation cover dynamics of the test range. To analyze the transformation of the environment by the climatic factors, we compared series of NDVI versus the precipitation and of NDVI versus the temperatures. Then we calculated the degree of correlation between them.

An eleven-year validation of a physically-based distributed dynamic ecohydorological model tRIBS+VEGGIE: Walnut Gulch Experimental Watershed

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bisht, G.; Ivanov, V. Y.; Bras, R. L.

2008-12-01

A coupled, dynamic vegetation and hydrologic model, tRIBS+VEGGIE, was applied to the semiarid Walnut Gulch Experimental Watershed in Arizona. The physically-based, distributed nature of the coupled model allows for parameterization and simulation of watershed vegetation-water-energy dynamics on timescales varying from hourly to interannual. The model also allows for explicit spatial representation of processes that vary due to complex topography, such as lateral redistribution of moisture and partitioning of radiation with respect to aspect and slope. Model parameterization and forcing was conducted using readily available databases for topography, soil types, and land use cover as well as the data from network of meteorological stations located within the Walnut Gulch watershed. In order to test the performance of the model, three sets of simulations were conducted over an 11 year period from 1997 to 2007. Two simulations focus on heavily instrumented nested watersheds within the Walnut Gulch basin; (i) Kendall watershed, which is dominated by annual grasses; and (ii) Lucky Hills watershed, which is dominated by a mixture of deciduous and evergreen shrubs. The third set of simulations cover the entire Walnut Gulch Watershed. Model validation and performance were evaluated in relation to three broad categories; (i) energy balance components: the network of meteorological stations were used to validate the key energy fluxes; (ii) water balance components: the network of flumes, rain gauges and soil moisture stations installed within the watershed were utilized to validate the manner in which the model partitions moisture; and (iii) vegetation dynamics: remote sensing products from MODIS were used to validate spatial and temporal vegetation dynamics. Model results demonstrate satisfactory spatial and temporal agreement with observed data, giving confidence that key ecohydrological processes can be adequately represented for future applications of tRIBS+VEGGIE in regional modeling of land-atmosphere interactions.

Empirical analysis of vegetation dynamics and the possibility of a catastrophic desertification transition

PubMed Central

Kent, Rafi; Michael, Yaron; Shnerb, Nadav M.

2017-01-01

The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states. Some support to this idea comes from the analysis of static patterns, where peaks of the vegetation density histogram were associated with these alternative states. Here we present a large-scale empirical study of vegetation dynamics, aimed at identifying and quantifying directly the effects of positive feedback. To do that, we have analyzed vegetation density across 2.5 × 106 km2 of the African Sahel region, with spatial resolution of 30 × 30 meters, using three consecutive snapshots. The results are mixed. The local vegetation density (measured at a single pixel) moves towards the average of the corresponding rainfall line, indicating a purely negative feedback. On the other hand, the chance of spatial clusters (of many “green” pixels) to expand in the next census is growing with their size, suggesting some positive feedback. We show that these apparently contradicting results emerge naturally in a model with positive feedback and strong demographic stochasticity, a model that allows for a catastrophic shift only in a certain range of parameters. Static patterns, like the double peak in the histogram of vegetation density, are shown to vary between censuses, with no apparent correlation with the actual dynamical features. Our work emphasizes the importance of dynamic response patterns as indicators of the state of the system, while the usefulness of static modality features appears to be quite limited. PMID:29261678

Empirical analysis of vegetation dynamics and the possibility of a catastrophic desertification transition.

PubMed

Weissmann, Haim; Kent, Rafi; Michael, Yaron; Shnerb, Nadav M

2017-01-01

The process of desertification in the semi-arid climatic zone is considered by many as a catastrophic regime shift, since the positive feedback of vegetation density on growth rates yields a system that admits alternative steady states. Some support to this idea comes from the analysis of static patterns, where peaks of the vegetation density histogram were associated with these alternative states. Here we present a large-scale empirical study of vegetation dynamics, aimed at identifying and quantifying directly the effects of positive feedback. To do that, we have analyzed vegetation density across 2.5 × 106 km2 of the African Sahel region, with spatial resolution of 30 × 30 meters, using three consecutive snapshots. The results are mixed. The local vegetation density (measured at a single pixel) moves towards the average of the corresponding rainfall line, indicating a purely negative feedback. On the other hand, the chance of spatial clusters (of many "green" pixels) to expand in the next census is growing with their size, suggesting some positive feedback. We show that these apparently contradicting results emerge naturally in a model with positive feedback and strong demographic stochasticity, a model that allows for a catastrophic shift only in a certain range of parameters. Static patterns, like the double peak in the histogram of vegetation density, are shown to vary between censuses, with no apparent correlation with the actual dynamical features. Our work emphasizes the importance of dynamic response patterns as indicators of the state of the system, while the usefulness of static modality features appears to be quite limited.

Simulation of Dynamic Soil Crusting Processes and Vegetative Feedbacks in Semi-Arid Regions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bras, R. L.

2009-12-01

Many soils, especially those in arid and semi-arid regions, develop compacted surface layers with hydrologic properties different to those of the underlying layers. These layers, referred to as soil crusts when dry and soil seals when wet, may be only a few millimeters thick but can have a significant impact by altering the partitioning of rainfall, increasing surface runoff and reducing infiltration. This reduces the quantity of water entering the root zone, limiting the amount of water available for primary productivity, while increasing erosion and negatively impacting seedling establishment and growth. Vegetation significantly alters soil hydraulic properties in the immediate vicinity of a vegetation patch. Root action has been shown to create macropores, increasing infiltration capacity around the base of vegetation. Shading protects the soil from evaporation and the formation of soil seals/crusts. Experiments have confirmed large variations in infiltration rates in below canopy and bare soil patches. It is believed that a positive feedback may occur between seals/crusts and vegetation patches resulting in systems that exhibit ‘islands of fertility’. The bare soil patches act to increase the micro-catchment area of the vegetation patch, thereby collecting moisture from a far greater area than the immediate footprint of its rooting system. Vegetation then alters the soil conditions directly beneath it, allowing for increased infiltration of this extra moisture. A coupled, dynamic vegetation and hydrologic model, tRIBS+VEGGIE, was used to explore the role of dynamic soil properties on hydrologic and energy fluxes. Rather than assigning the hydraulic properties of the surface soils a priori, soil seals/crusts were allowed to develop in the model depending on vegetation cover, soil type and rainfall intensity. The effects of plant shading and root action on infiltration in the immediate vicinity of vegetation patches were also included. These changes introduced both spatial and temporal heterogeneity into soil hydraulic properties and allowed for simulation of plant-soil feedbacks. The semi-arid Lucky Hills basin in the Walnut Gulch Experimental Watershed in Arizona was used as a case study to investigate the role of dynamic soil properties, which occur at patch scales, on the larger basin scale hydrologic and energy fluxes (sensible and latent heats, net radiation and rainfall partitioning). The model was used to test the contribution of dynamic soil properties to the establishment of a positive feedback between vegetation and soils that leads to the ‘islands of fertility’ that have been observed in many semi-arid systems. The model was also used to investigate the role that plant-soil interactions play in providing both stability to the larger system during periods of consistent climate forcing and some resilience to disturbance during climate perturbations.

Projected future vegetation changes for the northwest United States and southwest Canada at a fine spatial resolution using a dynamic global vegetation model.

USGS Publications Warehouse

Shafer, Sarah; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas.

Projected Future Vegetation Changes for the Northwest United States and Southwest Canada at a Fine Spatial Resolution Using a Dynamic Global Vegetation Model

PubMed Central

Shafer, Sarah L.; Bartlein, Patrick J.; Gray, Elizabeth M.; Pelltier, Richard T.

2015-01-01

Future climate change may significantly alter the distributions of many plant taxa. The effects of climate change may be particularly large in mountainous regions where climate can vary significantly with elevation. Understanding potential future vegetation changes in these regions requires methods that can resolve vegetation responses to climate change at fine spatial resolutions. We used LPJ, a dynamic global vegetation model, to assess potential future vegetation changes for a large topographically complex area of the northwest United States and southwest Canada (38.0–58.0°N latitude by 136.6–103.0°W longitude). LPJ is a process-based vegetation model that mechanistically simulates the effect of changing climate and atmospheric CO2 concentrations on vegetation. It was developed and has been mostly applied at spatial resolutions of 10-minutes or coarser. In this study, we used LPJ at a 30-second (~1-km) spatial resolution to simulate potential vegetation changes for 2070–2099. LPJ was run using downscaled future climate simulations from five coupled atmosphere-ocean general circulation models (CCSM3, CGCM3.1(T47), GISS-ER, MIROC3.2(medres), UKMO-HadCM3) produced using the A2 greenhouse gases emissions scenario. Under projected future climate and atmospheric CO2 concentrations, the simulated vegetation changes result in the contraction of alpine, shrub-steppe, and xeric shrub vegetation across the study area and the expansion of woodland and forest vegetation. Large areas of maritime cool forest and cold forest are simulated to persist under projected future conditions. The fine spatial-scale vegetation simulations resolve patterns of vegetation change that are not visible at coarser resolutions and these fine-scale patterns are particularly important for understanding potential future vegetation changes in topographically complex areas. PMID:26488750

The hydrological effects of varying vegetation characteristics in a temperate water-limited basin: Development of the dynamic Budyko-Choudhury-Porporato (dBCP) model

NASA Astrophysics Data System (ADS)

Liu, Qiang; McVicar, Tim R.; Yang, Zhifeng; Donohue, Randall J.; Liang, Liqiao; Yang, Yuting

2016-12-01

Vegetation patterns are affected by water availability, which, in turn, influences the hydrological partitioning and regional water balance, especially in water-limited regions. Considering the important role of vegetation in partitioning the catchment water yield, the recently developed Budyko-Choudhury-Porporato (or BCP) model incorporated Porporato's model of key ecohydrological processes into Choudury's form of the Budyko hydroclimatic framework. Here we extend the steady state BCP model by incorporating dynamic ecohydrological processes into it and combining it with a typical bucket soil water balance model (resulting in the dynamic BCP, or dBCP, model). The dBCP model is used here to assess the impacts of vegetation on the water balance in a temperate water-limited basin (i.e., the Yellow River Basin (YRB) in north China), where growing season phenology is primarily constrained by low temperatures. The results show that: (i) the incorporation of dynamic growing season (fs) and dynamic effective rooting depth (Ze) conditions into the dBCP model improves results when compared to the original BCP model; (ii) dBCP model's results vary depending on time-step used (i.e., we tested mean-annual to monthly), which reflected the influence of catchment variables, e.g., catchment area, catchment-average air temperature, dryness index and Ze; and (iii) actual evapotranspiration (E) is more sensitive to changes in mean storm depth (α), followed by P, Ze, and Ep. When taking into account observed variability of each of four ecohydrological variables, changes in Ze cause the greatest variability in E, generally followed by variability in P and α, and then Ep. The dBCP results indicate that incorporating dynamic ecohydrological processes into the Budyko framework can improve the estimation of inter-annual variability of the regional water balance. This can help to understand the water requirement and to establish suitable water management strategies to adapt to climate change in the YRB. The dBCP model has modest forcing data requirements and can be applied to other basins globally.

Understanding coupled natural and human systems on fire prone landscapes: integrating wildfire simulation into an agent based planning system.

NASA Astrophysics Data System (ADS)

Barros, Ana; Ager, Alan; Preisler, Haiganoush; Day, Michelle; Spies, Tom; Bolte, John

2015-04-01

Agent-based models (ABM) allow users to examine the long-term effects of agent decisions in complex systems where multiple agents and processes interact. This framework has potential application to study the dynamics of coupled natural and human systems where multiple stimuli determine trajectories over both space and time. We used Envision, a landscape based ABM, to analyze long-term wildfire dynamics in a heterogeneous, multi-owner landscape in Oregon, USA. Landscape dynamics are affected by land management policies, actors decisions, and autonomous processes such as vegetation succession, wildfire, or at a broader scale, climate change. Key questions include: 1) How are landscape dynamics influenced by policies and institutions, and 2) How do land management policies and actor decisions interact to produce intended and unintended consequences with respect to wildfire on fire-prone landscapes. Applying Envision to address these questions required the development of a wildfire module that could accurately simulate wildfires on the heterogeneous landscapes within the study area in terms of replicating historical fire size distribution, spatial distribution and fire intensity. In this paper we describe the development and testing of a mechanistic fire simulation system within Envision and application of the model on a 3.2 million fire prone landscape in central Oregon USA. The core fire spread equations use the Minimum Travel Time algorithm developed by M Finney. The model operates on a daily time step and uses a fire prediction system based on the relationship between energy release component and historical fires. Specifically, daily wildfire probabilities and sizes are generated from statistical analyses of historical fires in relation to daily ERC values. The MTT was coupled with the vegetation dynamics module in Envision to allow communication between the respective subsystem and effectively model fire effects and vegetation dynamics after a wildfire. Canopy and surface fuels are modeled in a state and transition framework that accounts for succession, fire effects, and fuels management. Fire effects are modeled using simulated fire intensity (flame length) to calculate expected vegetation impacts for each vegetation state. This talk will describe the mechanics of the simulation system along with initial results of Envision simulations for the Central Oregon study area that explore the dynamics of wildfire, fuel management, and succession over time.

The Fire and Fuels Extension to the Forest Vegetation Simulator

Treesearch

Elizabeth Reinhardt; Nicholas L. Crookston

2003-01-01

The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) simulates fuel dynamics and potential fire behaviour over time, in the context of stand development and management. Existing models of fire behavior and fire effects were added to FVS to form this extension. New submodels representing snag and fuel dynamics were created to complete the linkages...

Reimplementation of the Biome-BGC model to simulate successional change.

PubMed

Bond-Lamberty, Ben; Gower, Stith T; Ahl, Douglas E; Thornton, Peter E

2005-04-01

Biogeochemical process models are increasingly employed to simulate current and future forest dynamics, but most simulate only a single canopy type. This limitation means that mixed stands, canopy succession and understory dynamics cannot be modeled, severe handicaps in many forests. The goals of this study were to develop a version of Biome-BGC that supported multiple, interacting vegetation types, and to assess its performance and limitations by comparing modeled results to published data from a 150-year boreal black spruce (Picea mariana (Mill.) BSP) chronosequence in northern Manitoba, Canada. Model data structures and logic were modified to support an arbitrary number of interacting vegetation types; an explicit height calculation was necessary to prioritize radiation and precipitation interception. Two vegetation types, evergreen needle-leaf and deciduous broadleaf, were modeled based on site-specific meteorological and physiological data. The new version of Biome-BGC reliably simulated observed changes in leaf area, net primary production and carbon stocks, and should be useful for modeling the dynamics of mixed-species stands and ecological succession. We discuss the strengths and limitations of Biome-BGC for this application, and note areas in which further work is necessary for reliable simulation of boreal biogeochemical cycling at a landscape scale.

An Idealized Model of Plant and Soil Dynamics

NASA Astrophysics Data System (ADS)

Burg, David; Malkinson, Dan; Wittenberg, Lea

2014-05-01

Following wildfire events the landscape commonly becomes denuded of vegetation cover, resulting in systems prone to soil loss and degradation. In this context soil dynamics are an intricate process balanced between pedogenesis, which is a relatively slow process and erosion which depends on many inert (e.g. soil texture, slope, precipitation and wind) and biological factors such as vegetation properties, grazing intensity, and human disturbance. We develop a simple homogenous, spatially implicit, theoretical model of the global dynamics of the interactions between vegetation and soil using a system of two nonlinear differential equations describing this interdependence, assuming a double feedback between them - plants control erosion and soil availability facilitates plants growth: ( ) dV- -K-- dt = rV K - 1+ aS - V (1) dS-= σ - ɛSe-cT dt (2) where V and S represent vegetation cover and soil availability, respectively. Vegetation growth is similar to the classical logistic model with a growth rate of r(yr1), however, the "carrying capacity" (K) is dependent on soil availability (a1 is the amount of soil where V is reduced by half). Soil influxes at a constant rate σ(mm×yr1) and is eroded at a constant rategɛ (yr-1), while vegetation abates this process modeled as a decreasing exponent as the effectiveness of vegetation in reducing soil erosion (c). Parameter values were chosen from a variable range found in the literature: r=0.01 yr1, K=75%, a1=1, σ=1 mm×yr1, ɛ=0.1 yr1, c=0.08. Complex properties emerge from this model. At certain parameter values (cK≤4) the model predicts one of two steady states - full recovery of vegetation cover or a degraded barren system. However, at certain boundary conditions (cK>4 and Λ1 ≤ σ/ɛ ≤ Λ2, see Article for terms of Λ1 and Λ2) bistability may be observed. We also show that erosion seems to be the determining factor in this system, and we identify the threshold values from which beyond the systems become unstable. The model predicts that certain ecosystems will be highly stable in one of two states, while others might be bistable transitioning between these two states through perturbations. This is an indicator of hysteresis, possibly indicating the ability of the system to shift leading to sudden and dramatic changes; formalizing the conceptual model shown by Davenport et al. (1998) and others. Following the establishment of these interrelationships, the role of repeated disturbances, such as wildfires, was assessed with numerical analysis in determining the long term dynamics of coupled soil-vegetation systems.

Chapter 2: Fire and Fuels Extension: Model description

Treesearch

Sarah J. Beukema; Elizabeth D. Reinhardt; Julee A. Greenough; Donald C. E. Robinson; Werner A. Kurz

2003-01-01

The Fire and Fuels Extension to the Forest Vegetation Simulator is a model that simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. Existing models are used to represent forest stand development (the Forest Vegetation Simulator, Wykoff and others 1982), fire behavior (Rothermel 1972, Van Wagner 1977, and...

Approaches to incorporating climate change effects in state and transition simulation models of vegetation

Treesearch

Becky K. Kerns; Miles A. Hemstrom; David Conklin; Gabriel I. Yospin; Bart Johnson; Dominique Bachelet; Scott Bridgham

2012-01-01

Understanding landscape vegetation dynamics often involves the use of scientifically-based modeling tools that are capable of testing alternative management scenarios given complex ecological, management, and social conditions. State-and-transition simulation model (STSM) frameworks and software such as PATH and VDDT are commonly used tools that simulate how landscapes...

Forest canopy growth dynamic modeling based on remote sensing prodcuts and meteorological data in Daxing'anling of Northeast China

NASA Astrophysics Data System (ADS)

Wu, Qiaoli; Song, Jinling; Wang, Jindi; Xiao, Zhiqiang

2014-11-01

Leaf Area Index (LAI) is an important biophysical variable for vegetation. Compared with vegetation indexes like NDVI and EVI, LAI is more capable of monitoring forest canopy growth quantitatively. GLASS LAI is a spatially complete and temporally continuous product derived from AVHRR and MODIS reflectance data. In this paper, we present the approach to build dynamic LAI growth models for young and mature Larix gmelinii forest in north Daxing'anling in Inner Mongolia of China using the Dynamic Harmonic Regression (DHR) model and Double Logistic (D-L) model respectively, based on the time series extracted from multi-temporal GLASS LAI data. Meanwhile we used the dynamic threshold method to attract the key phenological phases of Larix gmelinii forest from the simulated time series. Then, through the relationship analysis between phenological phases and the meteorological factors, we found that the annual peak LAI and the annual maximum temperature have a good correlation coefficient. The results indicate this forest canopy growth dynamic model to be very effective in predicting forest canopy LAI growth and extracting forest canopy LAI growth dynamic.

Sensitivity of burned area in Europe to climate change, atmospheric CO2 levels, and demography: A comparison of two fire-vegetation models

NASA Astrophysics Data System (ADS)

Wu, Minchao; Knorr, Wolfgang; Thonicke, Kirsten; Schurgers, Guy; Camia, Andrea; Arneth, Almut

2015-11-01

Global environmental changes and human activity influence wildland fires worldwide, but the relative importance of the individual factors varies regionally and their interplay can be difficult to disentangle. Here we evaluate projected future changes in burned area at the European and sub-European scale, and we investigate uncertainties in the relative importance of the determining factors. We simulated future burned area with LPJ-GUESS-SIMFIRE, a patch-dynamic global vegetation model with a semiempirical fire model, and LPJmL-SPITFIRE, a dynamic global vegetation model with a process-based fire model. Applying a range of future projections that combine different scenarios for climate changes, enhanced CO2 concentrations, and population growth, we investigated the individual and combined effects of these drivers on the total area and regions affected by fire in the 21st century. The two models differed notably with respect to the dominating drivers and underlying processes. Fire-vegetation interactions and socioeconomic effects emerged as important uncertainties for future burned area in some European regions. Burned area of eastern Europe increased in both models, pointing at an emerging new fire-prone region that should gain further attention for future fire management.

The effects of vegetation and climate change on catchment erosion over millennial time scales: Insights from coupled dynamic vegetation and landscape evolution models

NASA Astrophysics Data System (ADS)

Schmid, Manuel; Ehlers, Todd; Werner, Christian; Hickler, Thomas

2017-04-01

Recent studies hypothesize that vegetation and the morphology of landscapes are strongly coupled. On a small scale, plants influence the erosivity of soil and sediments and therefore systematically impact catchment erosion and topography. Previous landscape evolution modeling studies primarily focus on changes in fluvial and hillslope erosion due to variations in climate and tectonics, without explicit consideration of vegetation effects. In this study, we complement previous work by investigating the effects of vegetation and vegetation change on hillslope and fluvial processes by combining LPJ-GUESS, a dynamic global vegetation model, with a modified version of the Landlab surface process model. The LandLab model was extended to account for vegetation-dependent sediment fluxes for both hillslope and detachment-limited fluvial erosion. The models are coupled by using predicted changes in surface vegetation from LPJ-GUESS for different climate scenarios as input for vegetation dependent erosional coefficients in Landlab. Simulations were conducted with the general climate and vegetation conditions representative between 25° and 40°S along the Coastal Cordillera of Chile. This region is the focus of the EarthShape research program (www.earthshape.net). These areas present a natural climatic and associated vegetation gradient that ranges from hyper-arid (Atacama desert) to humid-temperate conditions without a dry season and pristine temperate Araucaria forest. All study areas considered have a similar and uniform granite substrate, which minimizes lithologic variations and their effect on catchment erosion. Simulations are in progress that were designed to independently determine the climatic or vegetation controls on topography and erosion histories over the last 21 kyr. Our preliminary findings suggest that an increase in the surface vegetation results in a modulation of the mean hillslope angle and the average drainage density. In addition, we find that a decrease in surface vegetation density within a landscape can act as a trigger for sudden pulses of erosion, leading towards a new equilibrium topography. Our study suggests that vegetation changes (e.g. from the Last Glacial Maximum to present) act as a main agent of perturbing topographic equilibria. Reducing surface vegetation increases erosional efficiency and therefore sediment transport until a new stable state is reached.

Modeling the hydrological and mechanical effect of roots on shallow landslides

NASA Astrophysics Data System (ADS)

Arnone, E.; Caracciolo, D.; Noto, L. V.; Preti, F.; Bras, R. L.

2016-11-01

This study proposes a new methodology for estimating the additional shear strength (or cohesion) exerted by vegetation roots on slope stability analysis within a coupled hydrological-stability model. The mechanical root cohesion is estimated within a Fiber Bundle Model framework that allows for the evaluation of the root strength as a function of stress-strain relationships of populations of fibers. The use of such model requires the knowledge of the root architecture. A branching topology model based on Leonardo's rule is developed, providing an estimation of the amount of roots and the distribution of diameters with depth. The proposed methodology has been implemented into an existing distributed hydrological-stability model able to simulate the dynamics of factor of safety as a function of soil moisture dynamics. The model also accounts for the hydrological effects of vegetation, which reduces soil water content via root water uptake, thus increasing the stability. The entire methodology has been tested in a synthetic hillslope with two configurations of vegetation type, i.e., trees and shrubs, which have been compared to a configuration without vegetation. The vegetation has been characterized using roots data of two mediterranean plant species. The results demonstrate the capabilities of the topological model in accurately reproducing the observed root structure of the analyzed species. For the environmental setting modeled, the effects of root uptake might be more significant than the mechanical reinforcement; the additional resistance depends strictly on the vegetation root depth. Finally, for the simulated climatic environment, landslides are seasonal, in agreement with past observations.

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

2013-11-01

The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well-reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness-of-fit for broadleaved forests. N limitation associated with low N mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N-limitation associated with low N mineralisation rates of colder soils reduces CO2-enhancement of NPP for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by c. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions not only in studies of global terrestrial C cycling, but to understand underlying mechanisms on local scales and in different regional contexts.

Implications of incorporating N cycling and N limitations on primary production in an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Smith, B.; Wårlind, D.; Arneth, A.; Hickler, T.; Leadley, P.; Siltberg, J.; Zaehle, S.

2014-04-01

The LPJ-GUESS dynamic vegetation model uniquely combines an individual- and patch-based representation of vegetation dynamics with ecosystem biogeochemical cycling from regional to global scales. We present an updated version that includes plant and soil N dynamics, analysing the implications of accounting for C-N interactions on predictions and performance of the model. Stand structural dynamics and allometric scaling of tree growth suggested by global databases of forest stand structure and development were well reproduced by the model in comparison to an earlier multi-model study. Accounting for N cycle dynamics improved the goodness of fit for broadleaved forests. N limitation associated with low N-mineralisation rates reduces productivity of cold-climate and dry-climate ecosystems relative to mesic temperate and tropical ecosystems. In a model experiment emulating free-air CO2 enrichment (FACE) treatment for forests globally, N limitation associated with low N-mineralisation rates of colder soils reduces CO2 enhancement of net primary production (NPP) for boreal forests, while some temperate and tropical forests exhibit increased NPP enhancement. Under a business-as-usual future climate and emissions scenario, ecosystem C storage globally was projected to increase by ca. 10%; additional N requirements to match this increasing ecosystem C were within the high N supply limit estimated on stoichiometric grounds in an earlier study. Our results highlight the importance of accounting for C-N interactions in studies of global terrestrial N cycling, and as a basis for understanding mechanisms on local scales and in different regional contexts.

Tundra shrubification and tree-line advance amplify arctic climate warming: results from an individual-based dynamic vegetation model

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Miller, Paul A.; Smith, Benjamin; Wania, Rita; Koenigk, Torben; Döscher, Ralf

2013-09-01

One major challenge to the improvement of regional climate scenarios for the northern high latitudes is to understand land surface feedbacks associated with vegetation shifts and ecosystem biogeochemical cycling. We employed a customized, Arctic version of the individual-based dynamic vegetation model LPJ-GUESS to simulate the dynamics of upland and wetland ecosystems under a regional climate model-downscaled future climate projection for the Arctic and Subarctic. The simulated vegetation distribution (1961-1990) agreed well with a composite map of actual arctic vegetation. In the future (2051-2080), a poleward advance of the forest-tundra boundary, an expansion of tall shrub tundra, and a dominance shift from deciduous to evergreen boreal conifer forest over northern Eurasia were simulated. Ecosystems continued to sink carbon for the next few decades, although the size of these sinks diminished by the late 21st century. Hot spots of increased CH4 emission were identified in the peatlands near Hudson Bay and western Siberia. In terms of their net impact on regional climate forcing, positive feedbacks associated with the negative effects of tree-line, shrub cover and forest phenology changes on snow-season albedo, as well as the larger sources of CH4, may potentially dominate over negative feedbacks due to increased carbon sequestration and increased latent heat flux.

Combining Mechanistic Approaches for Studying Eco-Hydro-Geomorphic Coupling

NASA Astrophysics Data System (ADS)

Francipane, A.; Ivanov, V.; Akutina, Y.; Noto, V.; Istanbullouglu, E.

2008-12-01

Vegetation interacts with hydrology and geomorphic form and processes of a river basin in profound ways. Despite recent advances in hydrological modeling, the dynamic coupling between these processes is yet to be adequately captured at the basin scale to elucidate key features of process interaction and their role in the organization of vegetation and landscape morphology. In this study, we present a blueprint for integrating a geomorphic component into the physically-based, spatially distributed ecohydrological model, tRIBS- VEGGIE, which reproduces essential water and energy processes over the complex topography of a river basin and links them to the basic plant life regulatory processes. We present a preliminary design of the integrated modeling framework in which hillslope and channel erosion processes at the catchment scale, will be coupled with vegetation-hydrology dynamics. We evaluate the developed framework by applying the integrated model to Lucky Hills basin, a sub-catchment of the Walnut Gulch Experimental Watershed (Arizona). The evaluation is carried out by comparing sediment yields at the basin outlet, that follows a detailed verification of simulated land-surface energy partition, biomass dynamics, and soil moisture states.

How much rainfall sustained a Green Sahara during the mid-Holocene?

NASA Astrophysics Data System (ADS)

Hopcroft, Peter; Valdes, Paul; Harper, Anna

2016-04-01

The present-day Sahara desert has periodically transformed to an area of lakes and vegetation during the Quaternary in response to orbitally-induced changes in the monsoon circulation. Coupled atmosphere-ocean general circulation model simulations of the mid-Holocene generally underestimate the required monsoon shift, casting doubt on the fidelity of these models. However, the climatic regime that characterised this period remains unclear. To address this, we applied an ensemble of dynamic vegetation model simulations using two different models: JULES (Joint UK Land Environment Simulator) a comprehensive land surface model, and LPJ (Lund-Potsdam-Jena model) a widely used dynamic vegetation model. The simulations are forced with a number of idealized climate scenarios, in which an observational climatology is progressively altered with imposed anomalies of precipitation and other related variables, including cloud cover and humidity. The applied anomalies are based on an ensemble of general circulation model simulations, and include seasonal variations but are spatially uniform across the region. When perturbing precipitation alone, a significant increase of at least 700mm/year is required to produce model simulations with non-negligible vegetation coverage in the Sahara region. Changes in related variables including cloud cover, surface radiation fluxes and humidity are found to be important in the models, as they modify the water balance and so affect plant growth. Including anomalies in all of these variables together reduces the precipitation change required for a Green Sahara compared to the case of increasing precipitation alone. We assess whether the precipitation changes implied by these vegetation model simulations are consistent with reconstructions for the mid-Holocene from pollen samples. Further, Earth System models predict precipitation increases that are significantly smaller than that inferred from these vegetation model simulations. Understanding this difference presents an ongoing challenge.

Global change and terrestrial plant community dynamics

DOE PAGES

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; ...

2016-02-29

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Global change and terrestrial plant community dynamics

PubMed Central

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.; Regan, Helen M.

2016-01-01

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this paper, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on a literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change. PMID:26929338

Soil Water Balance and Vegetation Dynamics in two Contrasting Water-limited Mediterranean Ecosystems on Sardinia, Italy

NASA Astrophysics Data System (ADS)

Montaldo, N.; Albertson, J. D.; Corona, R.

2011-12-01

Water limited conditions strongly impacts soil and vegetation dynamics in Mediterranean regions, which are commonly heterogeneous ecosystems, characterized by inter-annual rainfall variability, topography variability and contrasting plant functional types (PFTs) competing for water use. Mediterranean regions are characterized by two main ecosystems, grassland and woodland, which for both natural and anthropogenic causes can grow in soils with different characteristics, highly impacting water resources. Water resources and forestal planning need a deep understanding of the dynamics between PFTs, soil and atmosphere and their impacts on water and CO2 distributions of these two main ecosystems. The first step is the monitoring of land surface fluxes, soil moisture, and vegetation dynamics of the two contrasting ecosystems. Moreover, due to the large percentage of soils with low depth (< 50 cm), and due to the quick hydrologic answer to atmospheric forcing in these soils, there is also the need to understand the impact of the soil depth in the vegetation dynamics, and make measurements in these types of soils. Sardinia island is a very interesting and representative region of Mediterranean ecosystems. It is low urbanized, and is not irrigated, except some plan areas close to the main cities where main agricultural activities are concentrated. The case study sites are within the Flumendosa river basin on Sardinia. Two sites, both in the Flumendosa river and with similar height a.s.l., are investigated. The distance between the sites is around 4 km but the first is a typically grass site located on an alluvial plan valley with a soil depth more than 2m, while the second site is a patchy mixture of Mediterranean vegetation types Oaks, creepers of the wild olive trees and C3 herbaceous species and the soil thickness varies from 15-40 cm, bounded from below by a rocky layer of basalt, partially fractured. In both sites land-surface fluxes and CO2 fluxes are estimated by eddy correlation technique based micrometeorological towers. Soil moisture profiles were also continuously estimated using water content reflectometers and gravimetric method, and periodically leaf area index PFTs are estimated during the Spring-Summer 2005. The following objectives are addressed:1) pointing out the dynamics of land surface fluxes, soil moisture, CO2 and vegetation cover for two contrasting water-limited ecosystems; 2) assess the impact of the soil depth and type on the CO2 and water balance dynamics. For reaching the objectives an ecohydrologic model is also successfully used and applied to the case studies. It couples a vegetation dynamic model, which computes the change in biomass over time for the PFTs, and a 3-component (bare soil, grass and woody vegetation) land surface model.

A novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China

PubMed Central

Yang, Yanzheng; Zhu, Qiuan; Peng, Changhui; Wang, Han; Xue, Wei; Lin, Guanghui; Wen, Zhongming; Chang, Jie; Wang, Meng; Liu, Guobin; Li, Shiqing

2016-01-01

Increasing evidence indicates that current dynamic global vegetation models (DGVMs) have suffered from insufficient realism and are difficult to improve, particularly because they are built on plant functional type (PFT) schemes. Therefore, new approaches, such as plant trait-based methods, are urgently needed to replace PFT schemes when predicting the distribution of vegetation and investigating vegetation sensitivity. As an important direction towards constructing next-generation DGVMs based on plant functional traits, we propose a novel approach for modelling vegetation distributions and analysing vegetation sensitivity through trait-climate relationships in China. The results demonstrated that a Gaussian mixture model (GMM) trained with a LMA-Nmass-LAI data combination yielded an accuracy of 72.82% in simulating vegetation distribution, providing more detailed parameter information regarding community structures and ecosystem functions. The new approach also performed well in analyses of vegetation sensitivity to different climatic scenarios. Although the trait-climate relationship is not the only candidate useful for predicting vegetation distributions and analysing climatic sensitivity, it sheds new light on the development of next-generation trait-based DGVMs. PMID:27052108

Advances in Remote Sensing for Vegetation Dynamics and Agricultural Management

NASA Technical Reports Server (NTRS)

Tucker, Compton; Puma, Michael

2015-01-01

Spaceborne remote sensing has led to great advances in the global monitoring of vegetation. For example, the NASA Global Inventory Modeling and Mapping Studies (GIMMS) group has developed widely used datasets from the Advanced Very High Resolution Radiometer (AVHRR) sensors as well as the Moderate Resolution Imaging Spectroradiometer (MODIS) map imagery and normalized difference vegetation index datasets. These data are valuable for analyzing vegetation trends and variability at the regional and global levels. Numerous studies have investigated such trends and variability for both natural vegetation (e.g., re-greening of the Sahel, shifts in the Eurasian boreal forest, Amazonian drought sensitivity) and crops (e.g., impacts of extremes on agricultural production). Here, a critical overview is presented on recent developments and opportunities in the use of remote sensing for monitoring vegetation and crop dynamics.

Aboveground Biomass and Dynamics of Forest Attributes using LiDAR Data and Vegetation Model

NASA Astrophysics Data System (ADS)

V V L, P. A.

2015-12-01

In recent years, biomass estimation for tropical forests has received much attention because of the fact that regional biomass is considered to be a critical input to climate change. Biomass almost determines the potential carbon emission that could be released to the atmosphere due to deforestation or conservation to non-forest land use. Thus, accurate biomass estimation is necessary for better understating of deforestation impacts on global warming and environmental degradation. In this context, forest stand height inclusion in biomass estimation plays a major role in reducing the uncertainty in the estimation of biomass. The improvement in the accuracy in biomass shall also help in meeting the MRV objectives of REDD+. Along with the precise estimate of biomass, it is also important to emphasize the role of vegetation models that will most likely become an important tool for assessing the effects of climate change on potential vegetation dynamics and terrestrial carbon storage and for managing terrestrial ecosystem sustainability. Remote sensing is an efficient way to estimate forest parameters in large area, especially at regional scale where field data is limited. LIDAR (Light Detection And Ranging) provides accurate information on the vertical structure of forests. We estimated average tree canopy heights and AGB from GLAS waveform parameters by using a multi-regression linear model in forested area of Madhya Pradesh (area-3,08,245 km2), India. The derived heights from ICESat-GLAS were correlated with field measured tree canopy heights for 60 plots. Results have shown a significant correlation of R2= 74% for top canopy heights and R2= 57% for stand biomass. The total biomass estimation 320.17 Mt and canopy heights are generated by using random forest algorithm. These canopy heights and biomass maps were used in vegetation models to predict the changes biophysical/physiological characteristics of forest according to the changing climate. In our study we have used Dynamic Global Vegetation Model to understand the possible vegetation dynamics in the event of climate change. The vegetation represents a biogeographic regime. Simulations were carried out for 70 years time period. The model produced leaf area index and biomass for each plant functional type and biome for each grid in that region.

Spatial Self-Organization of Vegetation Subject to Climatic Stress-Insights from a System Dynamics-Individual-Based Hybrid Model.

PubMed

Vincenot, Christian E; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)-Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed.

An overview of the fire and fuels extension to the forest vegetation simulator

Treesearch

Sarah J. Beukema; Elizabeth D. Reinhardt; Werner A. Kurz; Nicholas L. Crookston

2000-01-01

The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) has been developed to assess the risk, behavior, and impact of fire in forest ecosystems. This extension to the widely-used stand-dynamics model FVS simulates the dynamics of snags and surface fuels as they are affected by stand management (of trees or fuels), live tree growth and mortality,...

Modeling the Atmospheric Dynamics within and Above Vegetation Layers

Treesearch

Warren E. Heilman; John Zasada

2000-01-01

A critical component of any silvicultural treatment is the creation of suitable microclimatic conditions for desired plant and animal species. One of the most useful tools for examining the microclimatic implications of different vegetation treatments is the use of atmospheric boundary-layer models that can simulate resulting micrometeorological conditions within and...

MCFire model technical description

Treesearch

David R. Conklin; James M. Lenihan; Dominique Bachelet; Ronald P. Neilson; John B. Kim

2016-01-01

MCFire is a computer program that simulates the occurrence and effects of wildfire on natural vegetation, as a submodel within the MC1 dynamic global vegetation model. This report is a technical description of the algorithms and parameter values used in MCFire, intended to encapsulate its design and features a higher level that is more conceptual than the level...

Development of a Dynamic Web Mapping Service for Vegetation Productivity Using Earth Observation and in situ Sensors in a Sensor Web Based Approach

PubMed Central

Kooistra, Lammert; Bergsma, Aldo; Chuma, Beatus; de Bruin, Sytze

2009-01-01

This paper describes the development of a sensor web based approach which combines earth observation and in situ sensor data to derive typical information offered by a dynamic web mapping service (WMS). A prototype has been developed which provides daily maps of vegetation productivity for the Netherlands with a spatial resolution of 250 m. Daily available MODIS surface reflectance products and meteorological parameters obtained through a Sensor Observation Service (SOS) were used as input for a vegetation productivity model. This paper presents the vegetation productivity model, the sensor data sources and the implementation of the automated processing facility. Finally, an evaluation is made of the opportunities and limitations of sensor web based approaches for the development of web services which combine both satellite and in situ sensor sources. PMID:22574019

Uncertainty analysis of vegetation distribution in the northern high latitudes during the 21st century with a dynamic vegetation model

PubMed Central

Jiang, Yueyang; Zhuang, Qianlai; Schaphoff, Sibyll; Sitch, Stephen; Sokolov, Andrei; Kicklighter, David; Melillo, Jerry

2012-01-01

This study aims to assess how high-latitude vegetation may respond under various climate scenarios during the 21st century with a focus on analyzing model parameters induced uncertainty and how this uncertainty compares to the uncertainty induced by various climates. The analysis was based on a set of 10,000 Monte Carlo ensemble Lund-Potsdam-Jena (LPJ) simulations for the northern high latitudes (45oN and polewards) for the period 1900–2100. The LPJ Dynamic Global Vegetation Model (LPJ-DGVM) was run under contemporary and future climates from four Special Report Emission Scenarios (SRES), A1FI, A2, B1, and B2, based on the Hadley Centre General Circulation Model (GCM), and six climate scenarios, X901M, X902L, X903H, X904M, X905L, and X906H from the Integrated Global System Model (IGSM) at the Massachusetts Institute of Technology (MIT). In the current dynamic vegetation model, some parameters are more important than others in determining the vegetation distribution. Parameters that control plant carbon uptake and light-use efficiency have the predominant influence on the vegetation distribution of both woody and herbaceous plant functional types. The relative importance of different parameters varies temporally and spatially and is influenced by climate inputs. In addition to climate, these parameters play an important role in determining the vegetation distribution in the region. The parameter-based uncertainties contribute most to the total uncertainty. The current warming conditions lead to a complexity of vegetation responses in the region. Temperate trees will be more sensitive to climate variability, compared with boreal forest trees and C3 perennial grasses. This sensitivity would result in a unanimous northward greenness migration due to anomalous warming in the northern high latitudes. Temporally, boreal needleleaved evergreen plants are projected to decline considerably, and a large portion of C3 perennial grass is projected to disappear by the end of the 21st century. In contrast, the area of temperate trees would increase, especially under the most extreme A1FI scenario. As the warming continues, the northward greenness expansion in the Arctic region could continue. PMID:22822437

Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests.

PubMed

Xu, Xiangtao; Medvigy, David; Powers, Jennifer S; Becknell, Justin M; Guan, Kaiyu

2016-10-01

We assessed whether diversity in plant hydraulic traits can explain the observed diversity in plant responses to water stress in seasonally dry tropical forests (SDTFs). The Ecosystem Demography model 2 (ED2) was updated with a trait-driven mechanistic plant hydraulic module, as well as novel drought-phenology and plant water stress schemes. Four plant functional types were parameterized on the basis of meta-analysis of plant hydraulic traits. Simulations from both the original and the updated ED2 were evaluated against 5 yr of field data from a Costa Rican SDTF site and remote-sensing data over Central America. The updated model generated realistic plant hydraulic dynamics, such as leaf water potential and stem sap flow. Compared with the original ED2, predictions from our novel trait-driven model matched better with observed growth, phenology and their variations among functional groups. Most notably, the original ED2 produced unrealistically small leaf area index (LAI) and underestimated cumulative leaf litter. Both of these biases were corrected by the updated model. The updated model was also better able to simulate spatial patterns of LAI dynamics in Central America. Plant hydraulic traits are intercorrelated in SDTFs. Mechanistic incorporation of plant hydraulic traits is necessary for the simulation of spatiotemporal patterns of vegetation dynamics in SDTFs in vegetation models. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Vegetation function and non-uniqueness of the hydrological response

NASA Astrophysics Data System (ADS)

Ivanov, V. Y.; Fatichi, S.; Kampf, S. K.; Caporali, E.

2012-04-01

Through local moisture uptake vegetation exerts seasonal and longer-term impacts on the watershed hydrological response. However, the role of vegetation may go beyond the conventionally implied and well-understood "sink" function in the basin soil moisture storage equation. We argue that vegetation function imposes a "homogenizing" effect on pre-event soil moisture spatial storage, decreasing the likelihood that a rainfall event will result in a topographically-driven redistribution of soil water and the consequent formation of variable source areas. In combination with vegetation temporal dynamics, this may lead to the non-uniqueness of the hydrological response with respect to the mean basin wetness. This study designs a set of relevant numerical experiments carried out with two physically-based models; one of the models, HYDRUS, resolves variably saturated subsurface flow using a fully three-dimensional formulation, while the other model, tRIBS+VEGGIE, uses a one-dimensional formulation applied in a quasi-three-dimensional framework in combination with the model of vegetation dynamics. We demonstrate that (1) vegetation function modifies spatial heterogeneity in moisture spatial storage by imposing different degrees of subsurface flow connectivity; explore mechanistically (2) how and why a basin with the same mean soil moisture can have distinctly different spatial soil moisture distributions; and demonstrate (2) how these distinct moisture distributions result in a hysteretic runoff response to precipitation. Furthermore, the study argues that near-surface soil moisture is an insufficient indicator of the initial moisture state of a catchment with the implication of its limited effect on hydrological predictability.

Formation of banded vegetation patterns resulted from interactions between sediment deposition and vegetation growth.

PubMed

Huang, Tousheng; Zhang, Huayong; Dai, Liming; Cong, Xuebing; Ma, Shengnan

2018-03-01

This research investigates the formation of banded vegetation patterns on hillslopes affected by interactions between sediment deposition and vegetation growth. The following two perspectives in the formation of these patterns are taken into consideration: (a) increased sediment deposition from plant interception, and (b) reduced plant biomass caused by sediment accumulation. A spatial model is proposed to describe how the interactions between sediment deposition and vegetation growth promote self-organization of banded vegetation patterns. Based on theoretical and numerical analyses of the proposed spatial model, vegetation bands can result from a Turing instability mechanism. The banded vegetation patterns obtained in this research resemble patterns reported in the literature. Moreover, measured by sediment dynamics, the variation of hillslope landform can be described. The model predicts how treads on hillslopes evolve with the banded patterns. Thus, we provide a quantitative interpretation for coevolution of vegetation patterns and landforms under effects of sediment redistribution. Copyright © 2018. Published by Elsevier Masson SAS.

The combined effects of topography and vegetation on catchment connectivity

NASA Astrophysics Data System (ADS)

Nippgen, F.; McGlynn, B. L.; Emanuel, R. E.

2012-12-01

The deconvolution of whole catchment runoff response into its temporally dynamic source areas is a grand challenge in hydrology. The extent to which the intersection of static and dynamic catchment characteristics (e.g. topography and vegetation) influences water redistribution within a catchment and the hydrologic connectivity of hillslopes to the riparian and stream system is largely unknown. Over time, patterns of catchment storage shift and, because of threshold connectivity behavior, catchment areas become disconnected from the stream network. We developed a simple but spatially distributed modeling framework that explicitly incorporates static (topography) and dynamic (vegetation) catchment structure to document the evolution of catchment connectivity over the course of a water year. We employed directly measured eddy-covariance evapotranspiration data co-located within a highly instrumented (>150 recording groundwater wells) and gauged catchment to parse the effect of current and zero vegetation scenarios on the temporal evolution of hydrologic connectivity. In the absence of vegetation, and thus in the absence of evapotranspiration, modeled absolute connectivity was 4.5% greater during peak flow and 3.9% greater during late summer baseflow when compared to the actual vegetation scenario. The most significant differences in connected catchment area between current and zero vegetation (14.9%) occurred during the recession period in early July, when water and energy availability were at an optimum. However, the greatest relative difference in connected area occurs during the late summer baseflow period when the absence of evapotranspiration results in a connected area approximately 500% greater than when vegetation is present, while the relative increase during peak flow is just 6%. Changes in connected areas ultimately lead to propose a biologically modified geomorphic width function. This biogeomorphic width function is the result of lateral water redistribution driven by topography and water uptake by vegetation.

Coevolution of hydraulic, soil and vegetation processes in estuarine wetlands

NASA Astrophysics Data System (ADS)

Trivisonno, Franco; Rodriguez, Jose F.; Riccardi, Gerardo; Saco, Patricia; Stenta, Hernan

2014-05-01

Estuarine wetlands of south eastern Australia, typically display a vegetation zonation with a sequence mudflats - mangrove forest - saltmarsh plains from the seaward margin and up the topographic gradient. Estuarine wetlands are among the most productive ecosystems in the world, providing unique habitats for fish and many terrestrial species. They also have a carbon sequestration capacity that surpasess terrestrial forest. Estuarine wetlands respond to sea-level rise by vertical accretion and horizontal landward migration, in order to maintain their position in the tidal frame. In situations in which buffer areas for landward migration are not available, saltmarsh can be lost due to mangrove encroachment. As a result of mangrove invasion associated in part with raising estuary water levels and urbanisation, coastal saltmarsh in parts of south-eastern Australia has been declared an endangered ecological community. Predicting estuarine wetlands response to sea-level rise requires modelling the coevolving dynamics of water flow, soil and vegetation. This paper presents preliminary results of our recently developed numerical model for wetland dynamics in wetlands of the Hunter estuary of NSW. The model simulates continuous tidal inflow into the wetland, and accounts for the effect of varying vegetation types on flow resistance. Coevolution effects appear as vegetation types are updated based on their preference to prevailing hydrodynamic conditions. The model also considers that accretion values vary with vegetation type. Simulations are driven using local information collected over several years, which includes estuary water levels, accretion rates, soil carbon content, flow resistance and vegetation preference to hydraulic conditions. Model results predict further saltmarsh loss under current conditions of moderate increase of estuary water levels.

Plant functional types in Earth system models: past experiences and future directions for application of dynamic vegetation models in high-latitude ecosystems.

PubMed

Wullschleger, Stan D; Epstein, Howard E; Box, Elgene O; Euskirchen, Eugénie S; Goswami, Santonu; Iversen, Colleen M; Kattge, Jens; Norby, Richard J; van Bodegom, Peter M; Xu, Xiaofeng

2014-07-01

Earth system models describe the physical, chemical and biological processes that govern our global climate. While it is difficult to single out one component as being more important than another in these sophisticated models, terrestrial vegetation is a critical player in the biogeochemical and biophysical dynamics of the Earth system. There is much debate, however, as to how plant diversity and function should be represented in these models. Plant functional types (PFTs) have been adopted by modellers to represent broad groupings of plant species that share similar characteristics (e.g. growth form) and roles (e.g. photosynthetic pathway) in ecosystem function. In this review, the PFT concept is traced from its origin in the early 1800s to its current use in regional and global dynamic vegetation models (DVMs). Special attention is given to the representation and parameterization of PFTs and to validation and benchmarking of predicted patterns of vegetation distribution in high-latitude ecosystems. These ecosystems are sensitive to changing climate and thus provide a useful test case for model-based simulations of past, current and future distribution of vegetation. Models that incorporate the PFT concept predict many of the emerging patterns of vegetation change in tundra and boreal forests, given known processes of tree mortality, treeline migration and shrub expansion. However, representation of above- and especially below-ground traits for specific PFTs continues to be problematic. Potential solutions include developing trait databases and replacing fixed parameters for PFTs with formulations based on trait co-variance and empirical trait-environment relationships. Surprisingly, despite being important to land-atmosphere interactions of carbon, water and energy, PFTs such as moss and lichen are largely absent from DVMs. Close collaboration among those involved in modelling with the disciplines of taxonomy, biogeography, ecology and remote sensing will be required if we are to overcome these and other shortcomings. Published by Oxford University Press on behalf of the Annals of Botany Company 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

Changes in future fire regimes under climate change

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; von Bloh, Werner; Lutz, Julia; Knorr, Wolfgang; Wu, Minchao; Arneth, Almut

2013-04-01

Fires are expected to change under future climate change, climatic fire is is increasing due to increase in droughts and heat waves affecting vegetation productivity and ecosystem function. Vegetation productivity influences fuel production, but can also limit fire spread. Vegetation-fire models allow investigating the interaction between wildfires and vegetation dynamics, thus non-linear effects between changes in fuel composition and production on fire as well as changes in fire regimes on fire-related plant mortality and fuel combustion. Here we present results from simulation experiments, where the vegetation-fire models LPJmL-SPITFIRE and LPJ-GUESS are applied to future climate change scenarios from regional climate models in Europe and Northern Africa. Climate change impacts on fire regimes, vegetation dynamics and carbon fluxes are quantified and presented. New fire-prone regions are mapped and changes in fire regimes of ecosystems with a long-fire history are analyzed. Fuel limitation is likely to increase in Mediterranean-type ecosystems, indicating non-linear connection between increasing fire risk and fuel production. Increased warming in temperate ecosystems in Eastern Europe and continued fuel production leads to increases not only in climatic fire risk, but also area burnt and biomass burnt. This has implications for fire management, where adaptive capacity to this new vulnerability might be limited.

Fluvial processes and vegetation - Glimpses of the past, the present, and perhaps the future

USGS Publications Warehouse

Osterkamp, W.R.; Hupp, C.R.

2010-01-01

Most research before 1960 into interactions among fluvial processes, resulting landforms, and vegetation was descriptive. Since then, however, research has become more detailed and quantitative permitting numerical modeling and applications including agricultural-erosion abatement and rehabilitation of altered bottomlands. Although progress was largely observational, the empiricism increasingly yielded to objective recognition of how vegetation interacts with and influences geomorphic process. A review of advances relating fluvial processes and vegetation during the last 50 years centers on hydrologic reconstructions from tree rings, plant indicators of flow- and flood-frequency parameters, hydrologic controls on plant species, regulation of sediment movement by vegetation, vegetative controls on mass movement, and relations between plant cover and sediment movement. Extension of present studies of vegetation as a regulator of bottomland hydrologic and geomorphic processes may become markedly more sophisticated and widespread than at present. Research emphases that are likely to continue include vegetative considerations for erosion modeling, response of riparian-zone forests to disturbance such as dams and water diversion, the effect of vegetation on channel and bottomland dynamics, and rehabilitation of stream corridors. Research topics that presently are receiving attention are the effect of woody vegetation on the roughness of stream corridors and, hence, processes of flood conveyance and flood-plain sedimentation, the development of a theoretical basis for rehabilitation projects as opposed to fully empirical approaches, the effect of invasive plant species on the dynamics of bottomland vegetation, the quantification of below-surface biomass and related soil-stability factors for use in erosion-prediction models, and the effect of impoundments on downstream narrowing of channels and accompanying encroachment of vegetation. Bottomland vegetation partially controls and is controlled by fluvial-geomorphic processes. The purposes of this paper are to identify and review investigations that have related vegetation to bottomland features and processes, to distinguish the present status of these investigations, and to anticipate future research into how hydrologic and fluvial-geomorphic processes of bottomlands interact with vegetation.

Developing a Dynamic SPARROW Water Quality Decision Support System Using NASA Remotely-Sensed Products

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Smith, R. A.; Hoos, A.; Schwarz, G. E.; Alexander, R. B.; Crosson, W. L.; Srikishen, J.; Estes, M., Jr.; Cruise, J.; Al-Hamdan, A.; Ellenburg, W. L., II; Flores, A.; Sanford, W. E.; Zell, W.; Reitz, M.; Miller, M. P.; Journey, C. A.; Befus, K. M.; Swann, R.; Herder, T.; Sherwood, E.; Leverone, J.; Shelton, M.; Smith, E. T.; Anastasiou, C. J.; Seachrist, J.; Hughes, A.; Graves, D.

2017-12-01

The USGS Spatially Referenced Regression on Watershed Attributes (SPARROW) surface water quality modeling system has been widely used for long term, steady state water quality analysis. However, users have increasingly requested a dynamic version of SPARROW that can provide seasonal estimates of nutrients and suspended sediment to receiving waters. The goal of this NASA-funded project is to develop a dynamic decision support system to enhance the southeast SPARROW water quality model and finer-scale dynamic models for selected coastal watersheds through the use of remotely-sensed data and other NASA Land Information System (LIS) products. The spatial and temporal scale of satellite remote sensing products and LIS modeling data make these sources ideal for the purposes of development and operation of the dynamic SPARROW model. Remote sensing products including MODIS vegetation indices, SMAP surface soil moisture, and OMI atmospheric chemistry along with LIS-derived evapotranspiration (ET) and soil temperature and moisture products will be included in model development and operation. MODIS data will also be used to map annual land cover/land use in the study areas and in conjunction with Landsat and Sentinel to identify disturbed areas that might be sources of sediment and increased phosphorus loading through exposure of the bare soil. These data and others constitute the independent variables in a regression analysis whose dependent variables are the water quality constituents total nitrogen, total phosphorus, and suspended sediment. Remotely-sensed variables such as vegetation indices and ET can be proxies for nutrient uptake by vegetation; MODIS Leaf Area Index can indicate sources of phosphorus from vegetation; soil moisture and temperature are known to control rates of denitrification; and bare soil areas serve as sources of enhanced nutrient and sediment production. The enhanced SPARROW dynamic models will provide improved tools for end users to manage water quality in near real time and for the formulation of future scenarios to inform strategic planning. Time-varying SPARROW outputs will aid water managers in decision making regarding allocation of resources in protecting aquatic habitats, planning for harmful algal blooms, and restoration of degraded habitats, stream segments, or lakes.

Effects of Seasonal Land Surface Conditions on Hydrometeorological Dynamics in South-western North America

DTIC Science & Technology

2015-09-21

vehicles, environmental sensor networks, distributed hydrologic modeling, vegetation dynamics, soil moisture, evapotranspiration , remote sensing, North...Received Paper 1.00 5.00 3.00 8.00 9.00 E. Vivoni, J. Rodriguez, C. Watts. On the spatiotemporal variability of soil moisture and evapotranspiration ...Vegetation Impacts on Evapotranspiration and Its Partitioning at the Catchment Scale during SMEX04–NAME, Journal of Hydrometeorology, (10 2012

Belowground Controls on the Dynamics of Plant Communities

NASA Astrophysics Data System (ADS)

Sivandran, G.

2013-12-01

Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. In particular, the rooting strategies employed by vegetation can be critical to their survival. These rooting strategies also dictate the competitive outcomes within plant communities. A dynamic rooting scheme was incorporated into tRIBS+VEGGIE (a physically-based, distributed ecohydrologic model). The dynamic rooting scheme allows vegetation the freedom to alter its rooting profile in response to changes in rainfall and soil conditions, in a way that more closely mimics observed phenotypic plasticity. A simple competition-colonization model was combined with the new dynamic root scheme to explore the role of root adaptability in plant competition and landscape evolution in semi-arid environments. The influence of model representation of rooting strategy on the long term plant community composition

Simulating vegetation cover dynamics with regards to long-term climatic variations in sub-arctic landscapes

NASA Astrophysics Data System (ADS)

Haraldsson, Hörður V.; Ólafsdóttir, Rannveig

2003-09-01

Iceland is facing severe land degradation in many parts of the country. This study aims to increase the understanding of the complex interactions and interconnectivity between the critical factors that help maintain the land degradation processes in sub-arctic environments. A holistic approach in the form of a causal loop diagram (CLD) is applied for diagnosing the influencing factors. To further study the relationship between vegetation cover and its degradation, a dynamic model that uses a long-term temperature data as the main indicator function is constructed to simulate potential vegetation cover during the Holocene. The results depict an oscillating vegetation cover. Gradual degradation in potential vegetation cover begins ca. 3000 BP and accelerates greatly after ca. 2500 BP. From the time of the Norse settlement in the latter halve of the 9th century to present time, the simulated vegetation cover retreats ca. 25% in relation to climatic cooling.

Satellite remote sensing assessment of climate impact on forest vegetation dynamics

NASA Astrophysics Data System (ADS)

Zoran, M.

2009-04-01

Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modelling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2007 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Oscillations in a simple climate-vegetation model

NASA Astrophysics Data System (ADS)

Rombouts, J.; Ghil, M.

2015-05-01

We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various timescales is discussed.

Oscillations in a simple climate-vegetation model

NASA Astrophysics Data System (ADS)

Rombouts, J.; Ghil, M.

2015-02-01

We formulate and analyze a simple dynamical systems model for climate-vegetation interaction. The planet we consider consists of a large ocean and a land surface on which vegetation can grow. The temperature affects vegetation growth on land and the amount of sea ice on the ocean. Conversely, vegetation and sea ice change the albedo of the planet, which in turn changes its energy balance and hence the temperature evolution. Our highly idealized, conceptual model is governed by two nonlinear, coupled ordinary differential equations, one for global temperature, the other for vegetation cover. The model exhibits either bistability between a vegetated and a desert state or oscillatory behavior. The oscillations arise through a Hopf bifurcation off the vegetated state, when the death rate of vegetation is low enough. These oscillations are anharmonic and exhibit a sawtooth shape that is characteristic of relaxation oscillations, as well as suggestive of the sharp deglaciations of the Quaternary. Our model's behavior can be compared, on the one hand, with the bistability of even simpler, Daisyworld-style climate-vegetation models. On the other hand, it can be integrated into the hierarchy of models trying to simulate and explain oscillatory behavior in the climate system. Rigorous mathematical results are obtained that link the nature of the feedbacks with the nature and the stability of the solutions. The relevance of model results to climate variability on various time scales is discussed.

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) Dynamic Vegetation-Land Surface Model

NASA Astrophysics Data System (ADS)

Landry, J.-S.; Price, D. T.; Ramankutty, N.; Parrott, L.; Matthews, H. D.

2015-12-01

Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from broadleaf defoliators, needleleaf defoliators, and bark beetles, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water following a simulated outbreak of the mountain pine beetle. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.

Assessment of Climate Driven Dynamics of Active Layer, Hydrological and Vegetation Status at the Qinghai-Tibet Plateau Using Dynamic Global Vegetation Model

NASA Astrophysics Data System (ADS)

Yang, Y.

2014-12-01

Extensive permafrost degradation starting from 1970s is observed at the Qinghai-Tibet Plateau , China. Degradation is attributed to an increase in mean annual ground temperature 0.1◦-0.5◦ C with mainly winter warming. The construction of Qinghai-Tibet Railway also influenced a state of permafrost in the area Permafrost degradation caused negative environmental consequences in the area. The areas covered by sand are expanding steadily making large concern of accelerating desertification. The general pathway of future joint dynamics of permafrost, vegetation and hydrological status at the Qinghai-Tibet Plateau is still poorly understood and foreseeable. Hydrology in the area is determined by heat-moisture dynamics of active layer. This dynamics is highly non-linear and depends as on external climatic variables temperature and precipitation, so on soil and rock properties (amount of sand against aeolian deposits in the Plateau) as well as vegetation cover, which determine thaw and freeze processes in the active layer and evaporation and run-off. SEVER DGVM was modified to include heat-moisture dynamics of active layer in the Qinghai-Tibet Plateau. SEVER DGVM imitates processes in 10 plant functional types at coarse resolution of 0.5 degrees. This model imitates behavior of average individual of each plant type in each grid cell through simulation years. Each of those grid cells processed independently. First, this model starts from "bare soil", placing a bit of each plant type and giving them some time to grow and achieve equilibrium. Then, including active layer thickness and soil moisture dynamics into this layer, it allows assessment of potential environmental dynamics in this area. Simulations demonstrate further degradation of pastureland and accelerating desertification processes in this vitally important water feed area for many Asian rivers. Negative environmental problems related to operation of Qinghai-Tibet are also assessed.

Severity of climate change dictates the direction of biophysical feedbacks of vegetation change to Arctic climate

NASA Astrophysics Data System (ADS)

Zhang, Wenxin; Jansson, Christer; Miller, Paul; Smith, Ben; Samuelsson, Patrick

2014-05-01

Vegetation-climate feedbacks induced by vegetation dynamics under climate change alter biophysical properties of the land surface that regulate energy and water exchange with the atmosphere. Simulations with Earth System Models applied at global scale suggest that the current warming in the Arctic has been amplified, with large contributions from positive feedbacks, dominated by the effect of reduced surface albedo as an increased distribution, cover and taller stature of trees and shrubs mask underlying snow, darkening the surface. However, these models generally employ simplified representation of vegetation dynamics and structure and a coarse grid resolution, overlooking local or regional scale details determined by diverse vegetation composition and landscape heterogeneity. In this study, we perform simulations using an advanced regional coupled vegetation-climate model (RCA-GUESS) applied at high resolution (0.44×0.44° ) over the Arctic Coordinated Regional Climate Downscaling Experiment (CORDEX-Arctic) domain. The climate component (RCA4) is forced with lateral boundary conditions from EC-EARTH CMIP5 simulations for three representative concentration pathways (RCP 2.6, 4.5, 8.5). Vegetation-climate response is simulated by the individual-based dynamic vegetation model (LPJ-GUESS), accounting for phenology, physiology, demography and resource competition of individual-based vegetation, and feeding variations of leaf area index and vegetative cover fraction back to the climate component, thereby adjusting surface properties and surface energy fluxes. The simulated 2m air temperature, precipitation, vegetation distribution and carbon budget for the present period has been evaluated in another paper. The purpose of this study is to elucidate the spatial and temporal characteristics of the biophysical feedbacks arising from vegetation shifts in response to different CO2 concentration pathways and their associated climate change. Our results indicate that the albedo feedback dominates simulated warming in spring in all three scenarios, while in summer, evapotranspiration feedback, governing the partitioning of the return energy flux from the surface to the atmosphere into latent and sensible heat, exerts evaporative cooling effects, the magnitude of which depends on the severity of climate change, in turn driven by the underlying GHG emissions pathway, resulting in shift in the sign of net biophysical at higher levels of warming. Spatially, western Siberia is identified as the most susceptible location, experiencing the potential to reverse biophysical feedbacks in all seasons. We further analyze how the pattern of vegetation shifts triggers different signs of net effects of biophysical feedbacks.

Human impact on wildfires varies between regions and with vegetation productivity

NASA Astrophysics Data System (ADS)

Lasslop, Gitta; Kloster, Silvia

2017-11-01

We assess the influence of humans on burned area simulated with a dynamic global vegetation model. The human impact in the model is based on population density and cropland fraction, which were identified as important drivers of burned area in analyses of global datasets, and are commonly used in global models. After an evaluation of the sensitivity to these two variables we extend the model by including an additional effect of the cropland fraction on the fire duration. The general pattern of human influence is similar in both model versions: the strongest human impact is found in regions with intermediate productivity, where fire occurrence is not limited by fuel load or climatic conditions. Human effects in the model increases burned area in the tropics, while in temperate regions burned area is reduced. While the population density is similar on average for the tropical and temperate regions, the cropland fraction is higher in temperate regions, and leads to a strong suppression of fire. The model shows a low human impact in the boreal region, where both population density and cropland fraction is very low and the climatic conditions, as well as the vegetation productivity limit fire. Previous studies attributed a decrease in fire activity found in global charcoal datasets to human activity. This is confirmed by our simulations, which only show a decrease in burned area when the human influence on fire is accounted for, and not with only natural effects on fires. We assess how the vegetation-fire feedback influences the results, by comparing simulations with dynamic vegetation biogeography to simulations with prescribed vegetation. The vegetation-fire feedback increases the human impact on burned area by 10% for present day conditions. These results emphasize that projections of burned area need to account for the interactions between fire, climate, vegetation and humans.

Interaction Between Ecohydrologic Dynamics and Microtopographic Variability Under Climate Change

NASA Astrophysics Data System (ADS)

Le, Phong V. V.; Kumar, Praveen

2017-10-01

Vegetation acclimation resulting from elevated atmospheric CO2 concentration, along with response to increased temperature and altered rainfall pattern, is expected to result in emergent behavior in ecologic and hydrologic functions. We hypothesize that microtopographic variability, which are landscape features typically of the length scale of the order of meters, such as topographic depressions, will play an important role in determining this dynamics by altering the persistence and variability of moisture. To investigate these emergent ecohydrologic dynamics, we develop a modeling framework, Dhara, which explicitly incorporates the control of microtopographic variability on vegetation, moisture, and energy dynamics. The intensive computational demand from such a modeling framework that allows coupling of multilayer modeling of the soil-vegetation continuum with 3-D surface-subsurface flow processes is addressed using hybrid CPU-GPU parallel computing framework. The study is performed for different climate change scenarios for an intensively managed agricultural landscape in central Illinois, USA, which is dominated by row-crop agriculture, primarily soybean (Glycine max) and maize (Zea mays). We show that rising CO2 concentration will decrease evapotranspiration, thus increasing soil moisture and surface water ponding in topographic depressions. However, increased atmospheric demand from higher air temperature overcomes this conservative behavior resulting in a net increase of evapotranspiration, leading to reduction in both soil moisture storage and persistence of ponding. These results shed light on the linkage between vegetation acclimation under climate change and microtopography variability controls on ecohydrologic processes.

Vegetation projections for Wind Cave National Park with three future climate scenarios: Final report in completion of Task Agreement J8W07100052

USGS Publications Warehouse

King, David A.; Bachelet, Dominique M.; Symstad, Amy J.

2013-01-01

Since the initial application of MC1 to a small portion of WICA (Bachelet et al. 2000), the model has been altered to improve model performance with the inclusion of dynamic fire. Applying this improved version to WICA required substantial recalibration, during which we have made a number of improvements to MC1 that will be incorporated as permanent changes. In this report we document these changes and our calibration procedure following a brief overview of the model. We compare the projections of current vegetation to the current state of the park and present projections of vegetation dynamics under future climates downscaled from three GCMs selected to represent the existing range in available GCM projections. In doing so, we examine the consequences of different management options regarding fire and grazing, major aspects of biotic management at Wind Cave.

Modeling complex flow structures and drag around a submerged plant of varied posture

NASA Astrophysics Data System (ADS)

Boothroyd, Richard J.; Hardy, Richard J.; Warburton, Jeff; Marjoribanks, Timothy I.

2017-04-01

Although vegetation is present in many rivers, the bulk of past work concerned with modeling the influence of vegetation on flow has considered vegetation to be morphologically simple and has generally neglected the complexity of natural plants. Here we report on a combined flume and numerical model experiment which incorporates time-averaged plant posture, collected through terrestrial laser scanning, into a computational fluid dynamics model to predict flow around a submerged riparian plant. For three depth-limited flow conditions (Reynolds number = 65,000-110,000), plant dynamics were recorded through high-definition video imagery, and the numerical model was validated against flow velocities collected with an acoustic Doppler velocimeter. The plant morphology shows an 18% reduction in plant height and a 14% increase in plant length, compressing and reducing the volumetric canopy morphology as the Reynolds number increases. Plant shear layer turbulence is dominated by Kelvin-Helmholtz type vortices generated through shear instability, the frequency of which is estimated to be between 0.20 and 0.30 Hz, increasing with Reynolds number. These results demonstrate the significant effect that the complex morphology of natural plants has on in-stream drag, and allow a physically determined, species-dependent drag coefficient to be calculated. Given the importance of vegetation in river corridor management, the approach developed here demonstrates the necessity to account for plant motion when calculating vegetative resistance.

Earth System Model Needs for Including the Interactive Representation of Nitrogen Deposition and Drought Effects on Forested Ecosystems

DOE PAGES

Drewniak, Beth; Gonzalez-Meler, Miquel

2017-07-27

One of the biggest uncertainties of climate change is determining the response of vegetation to many co-occurring stressors. In particular, many forests are experiencing increased nitrogen deposition and are expected to suffer in the future from increased drought frequency and intensity. Interactions between drought and nitrogen deposition are antagonistic and non-additive, which makes predictions of vegetation response dependent on multiple factors. The tools we use (Earth system models) to evaluate the impact of climate change on the carbon cycle are ill equipped to capture the physiological feedbacks and dynamic responses of ecosystems to these types of stressors. In this manuscript,more » we review the observed effects of nitrogen deposition and drought on vegetation as they relate to productivity, particularly focusing on carbon uptake and partitioning. We conclude there are several areas of model development that can improve the predicted carbon uptake under increasing nitrogen deposition and drought. This includes a more flexible framework for carbon and nitrogen partitioning, dynamic carbon allocation, better representation of root form and function, age and succession dynamics, competition, and plant modeling using trait-based approaches. These areas of model development have the potential to improve the forecasting ability and reduce the uncertainty of climate models.« less

Earth System Model Needs for Including the Interactive Representation of Nitrogen Deposition and Drought Effects on Forested Ecosystems

DOE Office of Scientific and Technical Information (OSTI.GOV)

Drewniak, Beth; Gonzalez-Meler, Miquel

One of the biggest uncertainties of climate change is determining the response of vegetation to many co-occurring stressors. In particular, many forests are experiencing increased nitrogen deposition and are expected to suffer in the future from increased drought frequency and intensity. Interactions between drought and nitrogen deposition are antagonistic and non-additive, which makes predictions of vegetation response dependent on multiple factors. The tools we use (Earth system models) to evaluate the impact of climate change on the carbon cycle are ill equipped to capture the physiological feedbacks and dynamic responses of ecosystems to these types of stressors. In this manuscript,more » we review the observed effects of nitrogen deposition and drought on vegetation as they relate to productivity, particularly focusing on carbon uptake and partitioning. We conclude there are several areas of model development that can improve the predicted carbon uptake under increasing nitrogen deposition and drought. This includes a more flexible framework for carbon and nitrogen partitioning, dynamic carbon allocation, better representation of root form and function, age and succession dynamics, competition, and plant modeling using trait-based approaches. These areas of model development have the potential to improve the forecasting ability and reduce the uncertainty of climate models.« less

Forest forming process and dynamic vegetation models under global change

Treesearch

A. Shvidenko; E. Gustafson

2009-01-01

The paper analyzes mathematical models that are used to project the dynamics of forest ecosystems on different spatial and temporal scales. Landscape disturbance and succession models (LDSMs) are of a particular interest for studying the forest forming process in Northern Eurasia. They have a solid empirical background and are able to model ecological processes under...

Impact of Multiple Environmental Stresses on Wetland Vegetation Dynamics

NASA Astrophysics Data System (ADS)

Muneepeerakul, C. P.; Tamea, S.; Muneepeerakul, R.; Miralles-Wilhelm, F. R.; Rinaldo, A.; Rodriguez-Iturbe, I.

2009-12-01

This research quantifies the impacts of climate change on the dynamics of wetland vegetation under the effect of multiple stresses, such as drought, water-logging, shade and nutrients. The effects of these stresses are investigated through a mechanistic model that captures the co-evolving nature between marsh emergent plant species and their resources (water, nitrogen, light, and oxygen). The model explicitly considers the feedback mechanisms between vegetation, light and nitrogen dynamics as well as the specific dynamics of plant leaves, rhizomes, and roots. Each plant species is characterized by three independent traits, namely leaf nitrogen (N) content, specific leaf area, and allometric carbon (C) allocation to rhizome storage, which govern the ability to gain and maintain resources as well as to survive in a particular multi-stressed environment. The modeling of plant growth incorporates C and N into the construction of leaves and roots, whose amount of new biomass is determined by the dynamic plant allocation scheme. Nitrogen is internally recycled between pools of plants, litter, humus, microbes, and mineral N. The N dynamics are modeled using a parallel scheme, with the major modifications being the calculation of the aerobic and anoxic periods and the incorporation of the anaerobic processes. A simple hydrologic model with stochastic rainfall is used to describe the water level dynamics and the soil moisture profile. Soil water balance is evaluated at the daily time scale and includes rainfall, evapotranspiration and lateral flow to/from an external water body, with evapotranspiration loss equal to the potential value, governed by the daily average condition of atmospheric water demand. The resulting feedback dynamics arising from the coupled system of plant-soil-microbe are studied in details and species’ fitnesses in the 3-D trait space are compared across various rainfall patterns with different mean and fluctuations. The model results are then compared with those from experiments and field studies reported in the literature, providing insights about the physiological features that enable plants to thrive in different wetland environments and climate regimes.

Response of spatial vegetation distribution in China to climate changes since the Last Glacial Maximum (LGM)

PubMed Central

Wang, Siyang; Xu, Xiaoting; Shrestha, Nawal; Zimmermann, Niklaus E.; Tang, Zhiyao; Wang, Zhiheng

2017-01-01

Analyzing how climate change affects vegetation distribution is one of the central issues of global change ecology as this has important implications for the carbon budget of terrestrial vegetation. Mapping vegetation distribution under historical climate scenarios is essential for understanding the response of vegetation distribution to future climatic changes. The reconstructions of palaeovegetation based on pollen data provide a useful method to understand the relationship between climate and vegetation distribution. However, this method is limited in time and space. Here, using species distribution model (SDM) approaches, we explored the climatic determinants of contemporary vegetation distribution and reconstructed the distribution of Chinese vegetation during the Last Glacial Maximum (LGM, 18,000 14C yr BP) and Middle-Holocene (MH, 6000 14C yr BP). The dynamics of vegetation distribution since the LGM reconstructed by SDMs were largely consistent with those based on pollen data, suggesting that the SDM approach is a useful tool for studying historical vegetation dynamics and its response to climate change across time and space. Comparison between the modeled contemporary potential natural vegetation distribution and the observed contemporary distribution suggests that temperate deciduous forests, subtropical evergreen broadleaf forests, temperate deciduous shrublands and temperate steppe have low range fillings and are strongly influenced by human activities. In general, the Tibetan Plateau, North and Northeast China, and the areas near the 30°N in Central and Southeast China appeared to have experienced the highest turnover in vegetation due to climate change from the LGM to the present. PMID:28426780

Response of vegetation distribution, ecosystem productivity, and fire to climate change scenarios for California

Treesearch

James M. Lenihan; Dominique Bachelet; Ronald P. Neilson; Raymond Drapeck

2008-01-01

The response of vegetation distribution, carbon, and fire to three scenarios of future climate change was simulated for California using the MC1 Dynamic General Vegetation Model. Under all three scenarios, Alpine/Subalpine Forest cover declined, and increases in the productivity of evergreen hardwoods led to the displacement of Evergreen Conifer Forest by Mixed...

Carbon stock and carbon turnover in boreal and temperate forests - Integration of remote sensing data and global vegetation models

NASA Astrophysics Data System (ADS)

Thurner, Martin; Beer, Christian; Carvalhais, Nuno; Forkel, Matthias; Tito Rademacher, Tim; Santoro, Maurizio; Tum, Markus; Schmullius, Christiane

2016-04-01

Long-term vegetation dynamics are one of the key uncertainties of the carbon cycle. There are large differences in simulated vegetation carbon stocks and fluxes including productivity, respiration and carbon turnover between global vegetation models. Especially the implementation of climate-related mortality processes, for instance drought, fire, frost or insect effects, is often lacking or insufficient in current models and their importance at global scale is highly uncertain. These shortcomings have been due to the lack of spatially extensive information on vegetation carbon stocks, which cannot be provided by inventory data alone. Instead, we recently have been able to estimate northern boreal and temperate forest carbon stocks based on radar remote sensing data. Our spatially explicit product (0.01° resolution) shows strong agreement to inventory-based estimates at a regional scale and allows for a spatial evaluation of carbon stocks and dynamics simulated by global vegetation models. By combining this state-of-the-art biomass product and NPP datasets originating from remote sensing, we are able to study the relation between carbon turnover rate and a set of climate indices in northern boreal and temperate forests along spatial gradients. We observe an increasing turnover rate with colder winter temperatures and longer winters in boreal forests, suggesting frost damage and the trade-off between frost adaptation and growth being important mortality processes in this ecosystem. In contrast, turnover rate increases with climatic conditions favouring drought and insect outbreaks in temperate forests. Investigated global vegetation models from the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), including HYBRID4, JeDi, JULES, LPJml, ORCHIDEE, SDGVM, and VISIT, are able to reproduce observation-based spatial climate - turnover rate relationships only to a limited extent. While most of the models compare relatively well in terms of NPP, simulated vegetation carbon stocks are severely biased compared to our biomass dataset. Current limitations lead to considerable uncertainties in the estimated vegetation carbon turnover, contributing substantially to the forest feedback to climate change. Our results are the basis for improving mortality concepts in models and estimating their impact on the land carbon balance.

Ecosystem composition changes over the past millennium: model simulations and comparison with paleoecological observations

NASA Astrophysics Data System (ADS)

Liu, Y.; Rollinson, C.; Dietze, M.; McLachlan, J. S.; Poulter, B.; Quaife, T. L.; Raiho, A.; Ricciuto, D. M.; Schaefer, K. M.; Steinkamp, J.; Moore, D. J.

2015-12-01

Over multi-decadal to multi-centennial timescales, ecosystem function and carbon storage is largely influenced by vegetation composition. The predictability of ecosystem responses to climate change thus depends on the understanding of long-term community dynamics. Our study aims to quantify the influence of the most relevant ecological factors that control plant distribution and abundance, in contemporary terrestrial biosphere models and in paleo-records, and constrain the model processes and parameters with paleoecological data. We simulated vegetation changes at 6 sites in the northeastern United States over the past 1160 years using 7 terrestrial biosphere models and variations (CLM4.5-CN, ED2, ED2-LU, JULES-TRIFFID, LINKAGES, LPJ-GUESS, LPJ-wsl) driven by common paleoclimatic drivers. We examined plant growth, recruitment, and mortality (including other carbon turnover) of the plant functional types (PFTs) in the models, attributed the responses to three major factors (climate, competition, and disturbance), and estimated the relative effect of each factor. We assessed the model responses against plant-community theories (bioclimatic limits, niche difference, temporal variation and storage effect, and disturbance). We found that vegetation composition were sensitive to realized niche differences (e.g. differential growth response) among PFTs. Because many models assume unlimited dispersal and sometimes recruitment, the "storage effect" constantly affects community composition. Fire was important in determining the ecosystem composition, yet the vegetation to fire feedback was weak in the models. We also found that vegetation-composition changes in the simulations were driven to a much greater degree by growth as opposed to by turnover/mortality, when compared with those in paleoecological records. Our work suggest that 1) for forecasting slow changes in vegetation composition, we can use paleo-data to better quantify the realized niches of PFTs and associated uncertainties, and 2) for predicting abrupt changes in vegetation composition, we need to better implement processes of dynamic turnover and fire in current ecosystem models.

Improving the Projections of Vegetation Biogeography by Integrating Climate Envelope Models and Dynamic Global Vegetation Models

NASA Astrophysics Data System (ADS)

Case, M. J.; Kim, J. B.

2015-12-01

Assessing changes in vegetation is increasingly important for conservation planning in the face of climate change. Dynamic global vegetation models (DGVMs) are important tools for assessing such changes. DGVMs have been applied at regional scales to create projections of range expansions and contractions of plant functional types. Many DGVMs use a number of algorithms to determine the biogeography of plant functional types. One such DGVM, MC2, uses a series of decision trees based on bioclimatic thresholds while others, such as LPJ, use constraining emergent properties with a limited set of bioclimatic threshold-based rules. Although both approaches have been used widely, we demonstrate that these biogeography outputs perform poorly at continental scales when compared to existing potential vegetation maps. Specifically, we found that with MC2, the algorithm for determining leaf physiognomy is too simplistic to capture arid and semi-arid vegetation in much of the western U.S., as well as is the algorithm for determining the broadleaf and needleleaf mix in the Southeast. With LPJ, we found that the bioclimatic thresholds used to allow seedling establishment are too broad and fail to capture regional-scale biogeography of the plant functional types. In response, we demonstrate a new approach to determining the biogeography of plant functional types by integrating the climatic thresholds produced for individual tree species by a series of climate envelope models with the biogeography algorithms of MC2 and LPJ. Using this approach, we find that MC2 and LPJ perform considerably better when compared to potential vegetation maps.

Land Conversion in Amazonia and Northern South America; Influences on Regional Hydrology and Ecosystem Response

NASA Astrophysics Data System (ADS)

Knox, Ryan Gary

A numerical model of the terrestrial biosphere (Ecosystem Demography Model) is compbined with an atmospheric model (Brazilian Regional Atmospheric Modeling System) to investigate how land conversion in the Amazon and Northern South America have changed the hydrology of the region, and to see if those changes are significant enough to produce an ecological response. Two numerical realizations of the structure and composition of terrestrial vegetation are used as boundary conditions in a simulation of the regional land surface and atmosphere. One realization seeks to capture the present day vegetation condition that includes human deforestation and land-conversion, the other is an estimate of the potential structure and composition of the region without human influence. Model output is assessed for consistent and significant differences in hydrometeorology. Locations that show compelling differences are taken as case studies. The seasonal biases in precipitation at these locations are then used to create perturbations to long-term climate datasets. These perturbations then drive long-term simulations of dynamic vegetation to see if the climate consistent with a potential regional vegetation could elicit a change in the vegetation equilibrium at the site. Results show that South American land conversion has had consistent impacts on the regional patterning of precipitation. At some locations, changes in precipitation are persistent and constitute a significant fraction of total precipitation. Land-conversion has decreased mean continental evaporation and increased mean moisture convergence. Case study simulations of long term vegetation dynamic indicate that a hydrologic climate consistent with regional potential vegetation can indeed have significant influence on ecosystem structure and composition, particularly in water limited growth conditions. (Copies available exclusively from MIT Libraries, libraries.mit.edu/docs - docs@mit.edu)

Description, calibration and sensitivity analysis of the local ecosystem submodel of a global model of carbon and nitrogen cycling and the water balance in the terrestrial biosphere

DOE Office of Scientific and Technical Information (OSTI.GOV)

Kercher, J.R.; Chambers, J.Q.

1995-10-01

We have developed a geographically-distributed ecosystem model for the carbon, nitrogen, and water dynamics of the terrestrial biosphere TERRA. The local ecosystem model of TERRA consists of coupled, modified versions of TEM and DAYTRANS. The ecosystem model in each grid cell calculates water fluxes of evaporation, transpiration, and runoff; carbon fluxes of gross primary productivity, litterfall, and plant and soil respiration; and nitrogen fluxes of vegetation uptake, litterfall, mineralization, immobilization, and system loss. The state variables are soil water content; carbon in live vegetation; carbon in soil; nitrogen in live vegetation; organic nitrogen in soil and fitter; available inorganic nitrogenmore » aggregating nitrites, nitrates, and ammonia; and a variable for allocation. Carbon and nitrogen dynamics are calibrated to specific sites in 17 vegetation types. Eight parameters are determined during calibration for each of the 17 vegetation types. At calibration, the annual average values of carbon in vegetation C, show site differences that derive from the vegetation-type specific parameters and intersite variation in climate and soils. From calibration, we recover the average C{sub v} of forests, woodlands, savannas, grasslands, shrublands, and tundra that were used to develop the model initially. The timing of the phases of the annual variation is driven by temperature and light in the high latitude and moist temperate zones. The dry temperate zones are driven by temperature, precipitation, and light. In the tropics, precipitation is the key variable in annual variation. The seasonal responses are even more clearly demonstrated in net primary production and show the same controlling factors.« less

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zhang, T.

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover,more » soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations. 46 refs., 10 figs., 6 tabs.« less

Sensitivity properties of a biosphere model based on BATS and a statistical-dynamical climate model

NASA Technical Reports Server (NTRS)

Zhang, Taiping

1994-01-01

A biosphere model based on the Biosphere-Atmosphere Transfer Scheme (BATS) and the Saltzman-Vernekar (SV) statistical-dynamical climate model is developed. Some equations of BATS are adopted either intact or with modifications, some are conceptually modified, and still others are replaced with equations of the SV model. The model is designed so that it can be run independently as long as the parameters related to the physiology and physiognomy of the vegetation, the atmospheric conditions, solar radiation, and soil conditions are given. With this stand-alone biosphere model, a series of sensitivity investigations, particularly the model sensitivity to fractional area of vegetation cover, soil surface water availability, and solar radiation for different types of vegetation, were conducted as a first step. These numerical experiments indicate that the presence of a vegetation cover greatly enhances the exchanges of momentum, water vapor, and energy between the atmosphere and the surface of the earth. An interesting result is that a dense and thick vegetation cover tends to serve as an environment conditioner or, more specifically, a thermostat and a humidistat, since the soil surface temperature, foliage temperature, and temperature and vapor pressure of air within the foliage are practically insensitive to variation of soil surface water availability and even solar radiation within a wide range. An attempt is also made to simulate the gradual deterioration of environment accompanying gradual degradation of a tropical forest to grasslands. Comparison with field data shows that this model can realistically simulate the land surface processes involving biospheric variations.

Addressing spatial scales and new mechanisms in climate impact ecosystem modeling

NASA Astrophysics Data System (ADS)

Poulter, B.; Joetzjer, E.; Renwick, K.; Ogunkoya, G.; Emmett, K.

2015-12-01

Climate change impacts on vegetation distributions are typically addressed using either an empirical approach, such as a species distribution model (SDM), or with process-based methods, for example, dynamic global vegetation models (DGVMs). Each approach has its own benefits and disadvantages. For example, an SDM is constrained by data and few parameters, but does not include adaptation or acclimation processes or other ecosystem feedbacks that may act to mitigate or enhance climate effects. Alternatively, a DGVM model includes many mechanisms relating plant growth and disturbance to climate, but simulations are costly to perform at high-spatial resolution and there remains large uncertainty on a variety of fundamental physical processes. To address these issues, here, we present two DGVM-based case studies where i) high-resolution (1 km) simulations are being performed for vegetation in the Greater Yellowstone Ecosystem using a biogeochemical, forest gap model, LPJ-GUESS, and ii) where new mechanisms for simulating tropical tree-mortality are being introduced. High-resolution DGVM model simulations require not only computing and reorganizing code but also a consideration of scaling issues on vegetation dynamics and stochasticity and also on disturbance and migration. New mechanisms for simulating forest mortality must consider hydraulic limitations and carbon reserves and their interactions on source-sink dynamics and in controlling water potentials. Improving DGVM approaches by addressing spatial scale challenges and integrating new approaches for estimating forest mortality will provide new insights more relevant for land management and possibly reduce uncertainty by physical processes more directly comparable to experimental and observational evidence.

From Dynamic Global Vegetation Modelling to Real-World regional and local Application

NASA Astrophysics Data System (ADS)

Steinkamp, J.; Forrest, M.; Kamm, K.; Leiblein-Wild, M.; Pachzelt, A.; Werner, C.; Hickler, T.

2015-12-01

Dynamic (global) vegetation models (DGVM) can be applied to any spatial resolution on the local, national, continental and global scale given suitable climatic and geographic input forcing data. LPJ-GUESS, the main DGVM applied in our research group, uses the plant functional type (PFT) concept in the global setup with typically about 10-20 tree PFTs (subdivided into tropical, temperate and boreal) and two herbaceous PFTs by default. When modelling smaller spatial extents, such as continental (e.g. Europe/North America) national domains, or individual sites (e.g. Frankfurt, Germany), i.e. the scale of decision making, it becomes necessary to refine the PFT representation, the model initialization and validation and, in some case, to include additional processes. I will present examples of LPJ-GUESS applications at the continental to local scale performed by our working group including i.) a European simulation representing the main tree species and Mediterranean shrubs, ii.) a climate impact study for Turkey, iii.) coupled dynamic large grazer-vegetation modelling across Africa and, iv.) modelling an allergenic and in Europe invasive shrub (Ambrosia artemisiifolia), iv.) simulating water usage by an oak-pine forest stand near Frankfurt, and v.) stand specific differences in modelling at the FACE sites. Finally, I will present some thoughts on how to advance the models in terms of more detailed and realistic PFT or species parameterizations accounting for adaptive functional trait responses also within species.

A Modeling Approach for Evaluating the Coupled Riparian Vegetation-Geomorphic Response to Altered Flow Regimes

NASA Astrophysics Data System (ADS)

Manners, R.; Wilcox, A. C.; Merritt, D. M.

2016-12-01

The ecogeomorphic response of riparian ecosystems to a change in hydrologic properties is difficult to predict because of the interactions and feedbacks among plants, water, and sediment. Most riparian models of community dynamics assume a static channel, yet geomorphic processes strongly control the establishment and survival of riparian vegetation. Using a combination of approaches that includes empirical relationships and hydrodynamic models, we model the coupled vegetation-topographic response of three cross-sections on the Yampa and Green Rivers in Dinosaur National Monument, to a shift in the flow regime. The locations represent the variable geomorphology and vegetation composition of these canyon-bound rivers. We account for the inundation and hydraulic properties of vegetation plots surveyed over three years within International River Interface Cooperative (iRIC) Fastmech, equipped with a vegetation module that accounts for flexible stems and plant reconfiguration. The presence of functional groupings of plants, or those plants that respond similarly to environmental factors such as water availability and disturbance are determined from flow response curves developed for the Yampa River. Using field measurements of vegetation morphology, distance from the channel centerline, and dominant particle size and modeled inundation properties we develop an empirical relationship between these variables and topographic change. We evaluate vegetation and channel form changes over decadal timescales, allowing for the integration of processes over time. From our analyses, we identify thresholds in the flow regime that alter the distribution of plants and reduce geomorphic complexity, predominately through side-channel and backwater infilling. Simplification of some processes (e.g., empirically-derived sedimentation) and detailed treatment of others (e.g., plant-flow interactions) allows us to model the coupled dynamics of riparian ecosystems and evaluate the impact of small to large shifts in the flow regime. This approach will be useful to river managers and scientists, as they try to understand the potential changes to riparian ecosystems with uncertain changes to hydrologic regimes as a result of a changing climate and human demands.

Proceeding of the 2017 Forest vegetation simulator (FVS) e-Conference

Treesearch

Chad E. Keyser; Tara L. Keyser

2017-01-01

The Forest Vegetation Simulator (FVS) is a forest dynamics modeling system with geographic variants covering forested areas of the contiguous United States. As a direct descendant of the Prognosis model of the 1970/80s, FVS has seen continuous development and use for over 40 years. The 2017 FVS e-Conference, the fifth in a series of quinquennial conferences, was a...

Evapotranspiration trends over the eastern United States during the 20th century

USGS Publications Warehouse

Kramer, Ryan J.; Bounoua, Lahouari; Zhang, Ping; Wolfe, Robert E.; Huntington, Thomas G.; Imhoff, Marc L.; Thome, Kurtis; Noyce, Genevieve L.

2015-01-01

Most models evaluated by the Intergovernmental Panel for Climate change estimate projected increases in temperature and precipitation with rising atmospheric CO2 levels. Researchers have suggested that increases in CO2 and associated increases in temperature and precipitation may stimulate vegetation growth and increase evapotranspiration (ET), which acts as a cooling mechanism, and on a global scale, may slow the climate-warming trend. This hypothesis has been modeled under increased CO2 conditions with models of different vegetation-climate dynamics. The significance of this vegetation negative feedback, however, has varied between models. Here we conduct a century-scale observational analysis of the Eastern US water balance to determine historical evapotranspiration trends and whether vegetation greening has affected these trends. We show that precipitation has increased significantly over the twentieth century while runoff has not. We also show that ET has increased and vegetation growth is partially responsible.

The Role of Different Plant Soil-Water Feedbacks in Models of Dryland Vegetation Patterns

NASA Astrophysics Data System (ADS)

Silber, M.; Bonetti, S.; Gandhi, P.; Gowda, K.; Iams, S.; Porporato, A. M.

2017-12-01

Understanding the processes underlying the formation of regular vegetation patterns in arid and semi-arid regions is important to assessing desertification risk under increasing anthropogenic pressure. Various modeling frameworks have been proposed, which are all capable of generating similar patterns through self-organizing mechanisms that stem from assumptions about plant feedbacks on surface/subsurface water transport. We critically discuss a hierarchy of hydrology-vegetation models for the coupled dynamics of surface water, soil moisture, and vegetation biomass on a hillslope. We identify distinguishing features and trends for the periodic traveling wave solutions when there is an imposed idealized topography and make some comparisons to satellite images of large-scale banded vegetation patterns in drylands of Africa, Australia and North America. This work highlights the potential for constraining models by considerations of where the patterns may lie on a landscape, such as whether on a ridge or in a valley.

Temporal carbon dynamics of forests in Washington, US: implications for ecological theory and carbon management

Treesearch

Crystal L. Raymond; Donald McKenzie

2014-01-01

We quantified carbon (C) dynamics of forests in Washington, US using theoretical models of C dynamics as a function of forest age. We fit empirical models to chronosequences of forest inventory data at two scales: a coarse-scale ecosystem classification (ecosections) and forest types (potential vegetation) within ecosections. We hypothesized that analysis at the finer...

The role of root distribution in eco-hydrological modeling in semi-arid regions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Bras, R. L.

2010-12-01

In semi arid regions, the rooting strategies employed by vegetation can be critical to its survival. Arid regions are characterized by high variability in the arrival of rainfall, and species found in these areas have adapted mechanisms to ensure the capture of this scarce resource. Niche separation, through rooting strategies, is one manner in which different species coexist. At present, land surface models prescribe rooting profiles as a function of only the plant functional type of interest with no consideration for the soil texture or rainfall regime of the region being modeled. These models do not incorporate the ability of vegetation to dynamically alter their rooting strategies in response to transient changes in environmental forcings and therefore tend to underestimate the resilience of many of these ecosystems. A coupled, dynamic vegetation and hydrologic model, tRIBS+VEGGIE, was used to explore the role of vertical root distribution on hydrologic fluxes. Point scale simulations were carried out using two vertical root distribution schemes: (i) Static - a temporally invariant root distribution; and (ii) Dynamic - a temporally variable allocation of assimilated carbon at any depth within the root zone in order to minimize the soil moisture-induced stress on the vegetation. The simulations were forced with a stochastic climate generator calibrated to weather stations and rain gauges in the semi-arid Walnut Gulch Experimental Watershed in Arizona. For the static root distribution scheme, a series of simulations were carried out varying the shape of the rooting profile. The optimal distribution for the simulation was defined as the root distribution with the maximum mean transpiration over a 200 year period. This optimal distribution was determined for 5 soil textures and using 2 plant functional types, and the results varied from case to case. The dynamic rooting simulations allow vegetation the freedom to adjust the allocation of assimilated carbon to different rooting depths in response to changes in stress caused by the redistribution and uptake of soil moisture. The results obtained from these experiments elucidate the strong link between plant functional type, soil texture and climate and highlight the potential errors in the modeling of hydrologic fluxes from imposing a static root profile.

The Ecohydrologic Role of Coexistence and Competition in Semiarid Hillslopes

NASA Astrophysics Data System (ADS)

Soltanjalili, M. J.; Saco, P. M.; Willgoose, G. R.

2015-12-01

Through its influence on runoff and erosion-deposition processes, vegetation remarkably regulates different aspects of landscape dynamics. Here, the influence of different plant functional traits on the coexistence of different species in arid and semi-arid regions with patchy vegetation is investigated using an ecohydrology model. The model simulates coevolving changes in biomass patterns for two species, as well as overland flow and soil moisture dynamics. Vegetation patterns emerge as a result of facilitation (shading and infiltration) and competition mechanisms as well as varying seed dispersal strategies. The results show that the survival of only one species or the coexistence of both species not only strongly depends on environmental stresses, but also on differences in hillslope micro and macro topography. These vegetation patterns have very different hydrologic signatures and the potential to trigger remarkably different geomorphic responses. Based on these results we establish new hypothesis that will be used to further investigate the role of plant interspecific and intraspecific feedbacks on landscape coevolution processes.

Understanding global fire dynamics by classifying and comparing spatial models of vegetation and fire

Treesearch

Robert E. Keane; Geoffrey J. Cary; Ian D. Davies; Michael D. Flannigan; Robert H. Gardner; Sandra Lavorel; James M. Lenihan; Chao Li; T. Scott Rupp

2007-01-01

Wildland fire is a major disturbance in most ecosystems worldwide (Crutzen and Goldammer 1993). The interaction of fire with climate and vegetation over long time spans, often referred to as the fire regime (Agee 1993; Clark 1993; Swetnam and Baisan 1996; Swetnam 1997), has major effects on dominant vegetation, ecosystem carbon budget, and biodiversity (Gardner et aL...

Climatic and topographical factors affecting the vegetative carbon stock of rangelands in arid and semiarid regions of China

USGS Publications Warehouse

Zhengchao, Ren; Huazhong, Zhu; Shi, Hua; Xiaoni, Liu

2016-01-01

Rangeland systems play an important role in ecological stabilization and the terrestrial carbon cycle in arid and semiarid regions. However, little is known about the vegetative carbon dynamics and climatic and topographical factors that affect vegetative carbon stock in these rangelands. Our goal was to assess vegetative carbon stock by examining meteorological data in conjunction with NDVI (normalized difference vegetation index) time series datasets from 2001–2012. An improved CASA (Carnegie Ames Stanford Approach) model was then applied to simulate the spatiotemporal dynamic variation of vegetative carbon stock, and analyze its response to climatic and topographical factors. We estimated the vegetative carbon stock of rangeland in Gansu province, China to be 4.4× 1014 gC, increasing linearly at an annual rate of 9.8×1011 gC. The mean vegetative carbon density of the whole rangeland was 136.5 gC m-2. Vegetative carbon density and total carbon varied temporally and spatially and were highly associated with temperature, precipitation and solar radiation. Vegetative carbon density reached the maximal value on elevation at 2500–3500 m, a slope of >30°and easterly aspect. The effect of precipitation, temperature and solar radiation on the vegetative carbon density of five rangeland types (desert and salinized meadow, steppe, alpine meadow, shrub and tussock, and marginal grassland in the forest) depends on the acquired quantity of water and heat for rangeland plants at all spatial scales. The results of this study provide new evidence for explaining spatiotemporal heterogeneity in vegetative carbon dynamics and responses to global change for rangeland vegetative carbon stock, and offer a theoretical and practical basis for grassland agriculture management in arid and semiarid regions.

Plant toxicity, adaptive herbivory, and plant community dynamics

Treesearch

Zhilan Feng; Rongsong Liu; Donald L. DeAngelis; John P. Bryant; Knut Kielland; F. Stuart Chapin; Robert K. Swihart

2009-01-01

We model effects of interspecific plant competition, herbivory, and a plant's toxic defenses against herbivores on vegetation dynamics. The model predicts that, when a generalist herbivore feeds in the absence of plant toxins, adaptive foraging generally increases the probability of coexistence of plant species populations, because the herbivore switches more of...

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

USGS Publications Warehouse

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A.D.

2013-01-01

Soil surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Representing the effects of alpine grassland vegetation cover on the simulation of soil thermal dynamics by ecosystem models applied to the Qinghai-Tibetan Plateau

NASA Astrophysics Data System (ADS)

Yi, S.; Li, N.; Xiang, B.; Wang, X.; Ye, B.; McGuire, A. D.

2013-07-01

surface temperature is a critical boundary condition for the simulation of soil temperature by environmental models. It is influenced by atmospheric and soil conditions and by vegetation cover. In sophisticated land surface models, it is simulated iteratively by solving surface energy budget equations. In ecosystem, permafrost, and hydrology models, the consideration of soil surface temperature is generally simple. In this study, we developed a methodology for representing the effects of vegetation cover and atmospheric factors on the estimation of soil surface temperature for alpine grassland ecosystems on the Qinghai-Tibetan Plateau. Our approach integrated measurements from meteorological stations with simulations from a sophisticated land surface model to develop an equation set for estimating soil surface temperature. After implementing this equation set into an ecosystem model and evaluating the performance of the ecosystem model in simulating soil temperature at different depths in the soil profile, we applied the model to simulate interactions among vegetation cover, freeze-thaw cycles, and soil erosion to demonstrate potential applications made possible through the implementation of the methodology developed in this study. Results showed that (1) to properly estimate daily soil surface temperature, algorithms should use air temperature, downward solar radiation, and vegetation cover as independent variables; (2) the equation set developed in this study performed better than soil surface temperature algorithms used in other models; and (3) the ecosystem model performed well in simulating soil temperature throughout the soil profile using the equation set developed in this study. Our application of the model indicates that the representation in ecosystem models of the effects of vegetation cover on the simulation of soil thermal dynamics has the potential to substantially improve our understanding of the vulnerability of alpine grassland ecosystems to changes in climate and grazing regimes.

Implementation of a Marauding Insect Module (MIM, version 1.0) in the Integrated BIosphere Simulator (IBIS, version 2.6b4) dynamic vegetation-land surface model

NASA Astrophysics Data System (ADS)

Landry, Jean-Sébastien; Price, David T.; Ramankutty, Navin; Parrott, Lael; Damon Matthews, H.

2016-04-01

Insects defoliate and kill plants in many ecosystems worldwide. The consequences of these natural processes on terrestrial ecology and nutrient cycling are well established, and their potential climatic effects resulting from modified land-atmosphere exchanges of carbon, energy, and water are increasingly being recognized. We developed a Marauding Insect Module (MIM) to quantify, in the Integrated BIosphere Simulator (IBIS), the consequences of insect activity on biogeochemical and biogeophysical fluxes, also accounting for the effects of altered vegetation dynamics. MIM can simulate damage from three different insect functional types: (1) defoliators on broadleaf deciduous trees, (2) defoliators on needleleaf evergreen trees, and (3) bark beetles on needleleaf evergreen trees, with the resulting impacts being estimated by IBIS based on the new, insect-modified state of the vegetation. MIM further accounts for the physical presence and gradual fall of insect-killed dead standing trees. The design of MIM should facilitate the addition of other insect types besides the ones already included and could guide the development of similar modules for other process-based vegetation models. After describing IBIS-MIM, we illustrate the usefulness of the model by presenting results spanning daily to centennial timescales for vegetation dynamics and cycling of carbon, energy, and water in a simplified setting and for bark beetles only. More precisely, we simulated 100 % mortality events from the mountain pine beetle for three locations in western Canada. We then show that these simulated impacts agree with many previous studies based on field measurements, satellite data, or modelling. MIM and similar tools should therefore be of great value in assessing the wide array of impacts resulting from insect-induced plant damage in the Earth system.

On the relative role of fire and rainfall in determining vegetation patterns in tropical savannas: a simulation study

NASA Astrophysics Data System (ADS)

Spessa, Allan; Fisher, Rosie

2010-05-01

Tropical savannas cover 18% of the world's land surface and are amongst the most productive terrestrial systems in the world. They comprise 15% of the total terrestrial carbon stock, with an estimated mean net primary productivity (NPP) of 7.2 tCha-1yr-1 or two thirds of NPP in tropical forests. Tropical savannas are the most frequently burnt biome, with fire return intervals in highly productive areas being typically 1-2 years. Fires shape vegetation species composition, tree to grass ratios and nutrient redistribution, as well as the biosphere-atmosphere exchange of trace gases, momentum and radiative energy. Tropical savannas are a major source of emissions, contributing 38 % of total annual CO2 from biomass burning, 30% CO, 19 % CH4 and 59 % NOx. Climatically, they occur in regions subject to a strongly seasonal ‘wet-dry' regime, usually under monsoonal control from the movement of the inter-tropical convergence zone. In general, rainfall during the prior wet season(s) determines the amount of grass fuel available for burning while the length of the dry season influences fuel moisture content. Rainfall in tropical savannas exhibits high inter-annual variability, and under future climate change, is projected to change significantly in much of Africa, South America and northern Australia. Process-based simulation models of fire-vegetation dynamics and feedbacks are critical for determining the impacts of wildfires under projected future climate change on i) ecosystem structure and function, and ii) emissions of trace gases and aerosols from biomass burning. A new mechanistic global fire model SPITFIRE (SPread and InTensity of FIRE) has been designed to overcome many of the limitations in existing fire models set within Dynamic Global Vegetation Models (DGVMs). SPITFIRE has been applied in coupled mode globally and southern Africa, both as part of the LPJ DGVM. It has also been driven with MODIS burnt area data applied to sub-Saharan Africa, while coupled to the LPJ-GUESS vegetation model. Recently, SPIFTIRE has been coupled to the Ecosystem Demography (ED) model, which simulates global vegetation dynamics as part of the new land surface scheme JULES (Joint UK Environment Simulator) within the QUEST Earth System Model (http://www.quest-esm.ac.uk/). This study forms part of on-going work to further improve and test the ability of JULES to accurately simulate the terrestrial carbon cycle and land-atmosphere exchanges under different climates. Using the JULES (ED-SPITFIRE) model driven by observed climate (1901-2002), and focusing on large-scale rainfall gradients in the tropical savannas of west Africa, the Northern Territory (Australia) and central-southern Brazil, this study assesses: i) simulated versus observed vegetation dynamics and distributions, and ii) the relative importance of fire versus rainfall in determining vegetation patterns. A sensitivity analysis approach was used.

Relations between Vegetation and Geologic Framework in Barrier Island

NASA Astrophysics Data System (ADS)

Smart, N. H.; Ferguson, J. B.; Lehner, J. D.; Taylor, D.; Tuttle, L. F., II; Wernette, P. A.

2017-12-01

Barrier islands provide valuable ecosystems and protective services to coastal communities. The longevity of barrier islands is threatened by sea-level rise, human impacts, and extreme storms. The purpose of this research is to evaluate how vegetation dynamics interact with the subsurface and offshore framework geology to influence the beach and dune morphology. Beach and dune morphology can be viewed as free and/or forced behavior, where free systems are stochastic and the morphology is dependent on variations in the storm surge run-up, aeolian sediment supply and transport potential, and vegetation dynamics and persistence. Forced systems are those where patterns in the coastal morphology are determined by some other structural control, such as the underlying and offshore framework geology. Previous studies have documented the effects of geologic framework or vegetation dynamics on the beach and dunes, although none have examined possible control by vegetation dynamics in context of the geologic framework (i.e. combined free and forced behavior). Padre Island National Seashore (PAIS) was used to examine the interaction of free and forced morphology because the subsurface framework geology and surface beach and dune morphology are variable along the island. Vegetation dynamics were assessed by classifying geographically referenced historical aerial imagery into areas with vegetation and areas without vegetation, as well as LiDAR data to verify this imagery. The subsurface geologic structure was assessed using a combination of geophysical surveys (i.e. electromagnetic induction, ground-penetrating radar, and offshore seismic surveys). Comparison of the observed vegetation patterns and geologic framework leads to a series of questions surrounding how mechanistically these two drivers of coastal morphology are related. Upcoming coring and geophysical surveys will enable us to validate new and existing geophysical data. Results of this paper will help us better understand how barrier islands have responded to environmental change in the past should be integrated into current models of barrier island evolution in order to more accurately predict how the island will change over time in response to continued climatic variability.

ALM-FATES: Using dynamic vegetation and demography to capture changes in forest carbon cycling and competition at the global scale

NASA Astrophysics Data System (ADS)

Holm, J. A.; Knox, R. G.; Koven, C.; Riley, W. J.; Bisht, G.; Fisher, R.; Christoffersen, B. O.; Dietze, M.; Chambers, J. Q.

2017-12-01

The inclusion of dynamic vegetation demography in Earth System Models (ESMs) has been identified as a critical step in moving ESMs towards more realistic representations of plant ecology and the processes that govern climatically important fluxes of carbon, energy, and water. Successful application of dynamic vegetation models, and process-based approaches to simulate plant demography, succession, and response to disturbances without climate envelopes at the global scale is a challenging endeavor. We integrated demographic processes using the Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) in the newly developed ACME Land Model (ALM). We then use an ALM-FATES globally gridded simulation for the first time to investigate plant functional type (PFT) distributions and dynamic turnover rates. Initial global simulations successfully include six interacting and competing PFTs (ranging from tropical to boreal, evergreen, deciduous, needleleaf and broadleaf); including more PFTs is planned. Global maps of net primary productivity, leaf area index, and total vegetation biomass by ALM-FATES matched patterns and values when compared to CLM4.5-BGC and MODIS estimates. We also present techniques for PFT parameterization based on the Predictive Ecosystem Analyzer (PEcAn), field based turnover rates, improved PFT groupings based on trait-tradeoffs, and improved representation of multiple canopy positions. Finally, we applied the improved ALM-FATES model at a central Amazon tropical and western U.S. temperate sites and demonstrate improvements in predicted PFT size- and age-structure and regional distribution. Results from the Amazon tropical site investigate the ability and magnitude of a tropical forest to act as a carbon sink by 2100 with a doubling of CO2, while results from the temperate sites investigate the response of forest mortality with increasing droughts.

Global climate change impacts on forests and markets

Treesearch

Xiaohui Tian; Brent Sohngen; John B Kim; Sara Ohrel; Jefferson Cole

2016-01-01

This paper develops an economic analysis of climate change impacts in the global forest sector. It illustrates how potential future climate change impacts can be integrated into a dynamic forestry economics model using data from a global dynamic vegetation model, theMC2model. The results suggest that climate change will cause forest outputs (such as timber) to increase...

DOE Office of Scientific and Technical Information (OSTI.GOV)

Franklin, Janet; Serra-Diaz, Josep M.; Syphard, Alexandra D.

Anthropogenic drivers of global change include rising atmospheric concentrations of carbon dioxide and other greenhouse gasses and resulting changes in the climate, as well as nitrogen deposition, biotic invasions, altered disturbance regimes, and land-use change. Predicting the effects of global change on terrestrial plant communities is crucial because of the ecosystem services vegetation provides, from climate regulation to forest products. In this article, we present a framework for detecting vegetation changes and attributing them to global change drivers that incorporates multiple lines of evidence from spatially extensive monitoring networks, distributed experiments, remotely sensed data, and historical records. Based on amore » literature review, we summarize observed changes and then describe modeling tools that can forecast the impacts of multiple drivers on plant communities in an era of rapid change. Observed responses to changes in temperature, water, nutrients, land use, and disturbance show strong sensitivity of ecosystem productivity and plant population dynamics to water balance and long-lasting effects of disturbance on plant community dynamics. Persistent effects of land-use change and human-altered fire regimes on vegetation can overshadow or interact with climate change impacts. Models forecasting plant community responses to global change incorporate shifting ecological niches, population dynamics, species interactions, spatially explicit disturbance, ecosystem processes, and plant functional responses. Lastly, monitoring, experiments, and models evaluating multiple change drivers are needed to detect and predict vegetation changes in response to 21st century global change.« less

Assessment of Climate Impact Changes on Forest Vegetation Dynamics by Satellite Remote Sensing

NASA Astrophysics Data System (ADS)

Zoran, Maria

Climate variability represents the ensemble of net radiation, precipitation, wind and temper-ature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Forest vegetation phenology constitutes an efficient bio-indicator of climate and anthropogenic changes impacts and a key parameter for understanding and modelling vegetation-climate in-teractions. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vege-tation Index (NDVIs), which requires NDVI time-series with good time resolution, over homo-geneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images with the Harmonic ANalysis of Time Series algorithm. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. The aim of this paper was to quantify this impact over a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, with Normalized Difference Vegetation Index (NDVI) parameter extracted from IKONOS and LANDSAT TM and ETM satellite images and meteorological data over l995-2007 period. For investigated test area, considerable NDVI decline was observed between 1995 and 2008 due to the drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and to-pography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation . The paper aims to describe observed trends and potential impacts based on scenarios from simulations with regional climate models and other downscaling procedures.

Monitoring height and greenness of non-woody floodplain vegetation with UAV time series

NASA Astrophysics Data System (ADS)

van Iersel, Wimala; Straatsma, Menno; Addink, Elisabeth; Middelkoop, Hans

2018-07-01

Vegetation in river floodplains has important functions for biodiversity, but can also have a negative influence on flood safety. Floodplain vegetation is becoming increasingly heterogeneous in space and time as a result of river restoration projects. To document the spatio-temporal patterns of the floodplain vegetation, the need arises for efficient monitoring techniques. Monitoring is commonly performed by mapping floodplains based on single-epoch remote sensing data, thereby not considering seasonal dynamics of vegetation. The rising availability of unmanned airborne vehicles (UAV) increases monitoring frequency potential. Therefore, we aimed to evaluate the performance of multi-temporal high-spatial-resolution imagery, collected with a UAV, to record the dynamics in floodplain vegetation height and greenness over a growing season. Since the classification accuracy of current airborne surveys remains insufficient for low vegetation types, we focussed on seasonal variation of herbaceous and grassy vegetation with a height up to 3 m. Field reference data on vegetation height were collected six times during one year in 28 field plots within a single floodplain along the Waal River, the main distributary of the Rhine River in the Netherlands. Simultaneously with each field survey, we recorded UAV true-colour and false-colour imagery from which normalized digital surface models (nDSMs) and a consumer-grade camera vegetation index (CGCVI) were calculated. We observed that: (1) the accuracy of a UAV-derived digital terrain model (DTM) varies over the growing season and is most accurate during winter when the vegetation is dormant, (2) vegetation height can be determined from the nDSMs in leaf-on conditions via linear regression (RSME = 0.17-0.33 m), (3) the multitemporal nDSMs yielded meaningful temporal profiles of greenness and vegetation height and (4) herbaceous vegetation shows hysteresis for greenness and vegetation height, but no clear hysteresis was observed for grassland vegetation. These results show the high potential of using UAV-borne sensors for increasing the classification accuracy of low floodplain vegetation within the framework of floodplain monitoring.

Vegetation ecogeomorphology, dynamic equilibrium, and disturbance: chapter 7

USGS Publications Warehouse

Hupp, Cliff R.

2013-01-01

Early ecologists understood the need to document geomorphic form and process to explain plant species distributions. Although this relationship has been acknowledged for over a century, with the exception of a few landmark papers, only the past few decades have experienced intensive research on this interdisciplinary topic. Here the authors provide a summary of the intimate relations between vegetation and geomorphic/process on hillslopes and fluvial systems. These relations are separated into systems (primarily fluvial) in dynamic equilibrium and those that are in nonequilibrium conditions including the impacts of various human disturbances affecting landforms, geomorphic processes, and interrelated, attendant vegetation patterns and processes. The authors conclude with a conceptual model of stream regime focusing on sediment deposition, erosion, and equilibrium that can be expanded to organize and predict vegetation patterns and life history strategies.

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

DOE Office of Scientific and Technical Information (OSTI.GOV)

Yu, Yan; Notaro, Michael; Wang, Fuyao

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Validation of a Statistical Methodology for Extracting Vegetation Feedbacks: Focus on North African Ecosystems in the Community Earth System Model

DOE PAGES

Yu, Yan; Notaro, Michael; Wang, Fuyao; ...

2018-02-05

Generalized equilibrium feedback assessment (GEFA) is a potentially valuable multivariate statistical tool for extracting vegetation feedbacks to the atmosphere in either observations or coupled Earth system models. The reliability of GEFA at capturing the terrestrial impacts on regional climate is demonstrated in this paper using the National Center for Atmospheric Research Community Earth System Model (CESM), with focus on North Africa. The feedback is assessed statistically by applying GEFA to output from a fully coupled control run. To reduce the sampling error caused by short data records, the traditional or full GEFA is refined through stepwise GEFA by dropping unimportantmore » forcings. Two ensembles of dynamical experiments are developed for the Sahel or West African monsoon region against which GEFA-based vegetation feedbacks are evaluated. In these dynamical experiments, regional leaf area index (LAI) is modified either alone or in conjunction with soil moisture, with the latter runs motivated by strong regional soil moisture–LAI coupling. Stepwise GEFA boasts higher consistency between statistically and dynamically assessed atmospheric responses to land surface anomalies than full GEFA, especially with short data records. GEFA-based atmospheric responses are more consistent with the coupled soil moisture–LAI experiments, indicating that GEFA is assessing the combined impacts of coupled vegetation and soil moisture. Finally, both the statistical and dynamical assessments reveal a negative vegetation–rainfall feedback in the Sahel associated with an atmospheric stability mechanism in CESM versus a weaker positive feedback in the West African monsoon region associated with a moisture recycling mechanism in CESM.« less

Model-based prediction of nephropathia epidemica outbreaks based on climatological and vegetation data and bank vole population dynamics.

PubMed

Haredasht, S Amirpour; Taylor, C J; Maes, P; Verstraeten, W W; Clement, J; Barrios, M; Lagrou, K; Van Ranst, M; Coppin, P; Berckmans, D; Aerts, J-M

2013-11-01

Wildlife-originated zoonotic diseases in general are a major contributor to emerging infectious diseases. Hantaviruses more specifically cause thousands of human disease cases annually worldwide, while understanding and predicting human hantavirus epidemics pose numerous unsolved challenges. Nephropathia epidemica (NE) is a human infection caused by Puumala virus, which is naturally carried and shed by bank voles (Myodes glareolus). The objective of this study was to develop a method that allows model-based predicting 3 months ahead of the occurrence of NE epidemics. Two data sets were utilized to develop and test the models. These data sets were concerned with NE cases in Finland and Belgium. In this study, we selected the most relevant inputs from all the available data for use in a dynamic linear regression (DLR) model. The number of NE cases in Finland were modelled using data from 1996 to 2008. The NE cases were predicted based on the time series data of average monthly air temperature (°C) and bank voles' trapping index using a DLR model. The bank voles' trapping index data were interpolated using a related dynamic harmonic regression model (DHR). Here, the DLR and DHR models used time-varying parameters. Both the DHR and DLR models were based on a unified state-space estimation framework. For the Belgium case, no time series of the bank voles' population dynamics were available. Several studies, however, have suggested that the population of bank voles is related to the variation in seed production of beech and oak trees in Northern Europe. Therefore, the NE occurrence pattern in Belgium was predicted based on a DLR model by using remotely sensed phenology parameters of broad-leaved forests, together with the oak and beech seed categories and average monthly air temperature (°C) using data from 2001 to 2009. Our results suggest that even without any knowledge about hantavirus dynamics in the host population, the time variation in NE outbreaks in Finland could be predicted 3 months ahead with a 34% mean relative prediction error (MRPE). This took into account solely the population dynamics of the carrier species (bank voles). The time series analysis also revealed that climate change, as represented by the vegetation index, changes in forest phenology derived from satellite images and directly measured air temperature, may affect the mechanics of NE transmission. NE outbreaks in Belgium were predicted 3 months ahead with a 40% MRPE, based only on the climatological and vegetation data, in this case, without any knowledge of the bank vole's population dynamics. In this research, we demonstrated that NE outbreaks can be predicted using climate and vegetation data or the bank vole's population dynamics, by using dynamic data-based models with time-varying parameters. Such a predictive modelling approach might be used as a step towards the development of new tools for the prevention of future NE outbreaks. © 2012 Blackwell Verlag GmbH.

A model inter-comparison study to examine limiting factors in modelling Australian tropical savannas

NASA Astrophysics Data System (ADS)

Whitley, Rhys; Beringer, Jason; Hutley, Lindsay B.; Abramowitz, Gab; De Kauwe, Martin G.; Duursma, Remko; Evans, Bradley; Haverd, Vanessa; Li, Longhui; Ryu, Youngryel; Smith, Benjamin; Wang, Ying-Ping; Williams, Mathew; Yu, Qiang

2016-06-01

The savanna ecosystem is one of the most dominant and complex terrestrial biomes, deriving from a distinct vegetative surface comprised of co-dominant tree and grass populations. While these two vegetation types co-exist functionally, demographically they are not static but are dynamically changing in response to environmental forces such as annual fire events and rainfall variability. Modelling savanna environments with the current generation of terrestrial biosphere models (TBMs) has presented many problems, particularly describing fire frequency and intensity, phenology, leaf biochemistry of C3 and C4 photosynthesis vegetation, and root-water uptake. In order to better understand why TBMs perform so poorly in savannas, we conducted a model inter-comparison of six TBMs and assessed their performance at simulating latent energy (LE) and gross primary productivity (GPP) for five savanna sites along a rainfall gradient in northern Australia. Performance in predicting LE and GPP was measured using an empirical benchmarking system, which ranks models by their ability to utilise meteorological driving information to predict the fluxes. On average, the TBMs performed as well as a multi-linear regression of the fluxes against solar radiation, temperature and vapour pressure deficit but were outperformed by a more complicated nonlinear response model that also included the leaf area index (LAI). This identified that the TBMs are not fully utilising their input information effectively in determining savanna LE and GPP and highlights that savanna dynamics cannot be calibrated into models and that there are problems in underlying model processes. We identified key weaknesses in a model's ability to simulate savanna fluxes and their seasonal variation, related to the representation of vegetation by the models and root-water uptake. We underline these weaknesses in terms of three critical areas for development. First, prescribed tree-rooting depths must be deep enough, enabling the extraction of deep soil-water stores to maintain photosynthesis and transpiration during the dry season. Second, models must treat grasses as a co-dominant interface for water and carbon exchange rather than a secondary one to trees. Third, models need a dynamic representation of LAI that encompasses the dynamic phenology of savanna vegetation and its response to rainfall interannual variability. We believe that this study is the first to assess how well TBMs simulate savanna ecosystems and that these results will be used to improve the representation of savannas ecosystems in future global climate model studies.

Potential Arctic tundra vegetation shifts in response to changing temperature, precipitation and permafrost thaw

NASA Astrophysics Data System (ADS)

van der Kolk, Henk-Jan; Heijmans, Monique M. P. D.; van Huissteden, Jacobus; Pullens, Jeroen W. M.; Berendse, Frank

2016-11-01

Over the past decades, vegetation and climate have changed significantly in the Arctic. Deciduous shrub cover is often assumed to expand in tundra landscapes, but more frequent abrupt permafrost thaw resulting in formation of thaw ponds could lead to vegetation shifts towards graminoid-dominated wetland. Which factors drive vegetation changes in the tundra ecosystem are still not sufficiently clear. In this study, the dynamic tundra vegetation model, NUCOM-tundra (NUtrient and COMpetition), was used to evaluate the consequences of climate change scenarios of warming and increasing precipitation for future tundra vegetation change. The model includes three plant functional types (moss, graminoids and shrubs), carbon and nitrogen cycling, water and permafrost dynamics and a simple thaw pond module. Climate scenario simulations were performed for 16 combinations of temperature and precipitation increases in five vegetation types representing a gradient from dry shrub-dominated to moist mixed and wet graminoid-dominated sites. Vegetation composition dynamics in currently mixed vegetation sites were dependent on both temperature and precipitation changes, with warming favouring shrub dominance and increased precipitation favouring graminoid abundance. Climate change simulations based on greenhouse gas emission scenarios in which temperature and precipitation increases were combined showed increases in biomass of both graminoids and shrubs, with graminoids increasing in abundance. The simulations suggest that shrub growth can be limited by very wet soil conditions and low nutrient supply, whereas graminoids have the advantage of being able to grow in a wide range of soil moisture conditions and have access to nutrients in deeper soil layers. Abrupt permafrost thaw initiating thaw pond formation led to complete domination of graminoids. However, due to increased drainage, shrubs could profit from such changes in adjacent areas. Both climate and thaw pond formation simulations suggest that a wetter tundra can be responsible for local shrub decline instead of shrub expansion.

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf-out times across groupings of species in a dynamic vegetation model

USGS Publications Warehouse

Euskirchen, E.S.; Carman, T.B.; McGuire, Anthony David

2013-01-01

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970 -2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared to simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf-out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf-out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions.

Changes in the structure and function of northern Alaskan ecosystems when considering variable leaf-out times across groupings of species in a dynamic vegetation model.

PubMed

Euskirchen, Eugénie S; Carman, Tobey B; McGuire, A David

2014-03-01

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over regional to global scales typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observations of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest, and perform model simulations for the years 1970-2100. Over the course of the model simulations, we found changes in ecosystem composition under this new phenology algorithm compared with simulations with the previous phenology algorithm. These changes were the result of the differential timing of leaf-out, as well as the ability for the groupings of species to compete for nitrogen and light availability. Regionally, there were differences in the trends of the carbon pools and fluxes between the new phenology algorithm and the previous phenology algorithm, although these differences depended on the future climate scenario. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape, and that dynamic vegetation models should consider variation in leaf-out by groupings of species within these ecosystems to make more accurate projections of future plant distributions and carbon cycling in Arctic regions. © 2013 John Wiley & Sons Ltd.

A mechanistic soil biogeochemistry model with explicit representation of microbial and macrofaunal activities and nutrient cycles

NASA Astrophysics Data System (ADS)

Fatichi, Simone; Manzoni, Stefano; Or, Dani; Paschalis, Athanasios

2016-04-01

The potential of a given ecosystem to store and release carbon is inherently linked to soil biogeochemical processes. These processes are deeply connected to the water, energy, and vegetation dynamics above and belowground. Recently, it has been advocated that a mechanistic representation of soil biogeochemistry require: (i) partitioning of soil organic carbon (SOC) pools according to their functional role; (ii) an explicit representation of microbial dynamics; (iii) coupling of carbon and nutrient cycles. While some of these components have been introduced in specialized models, they have been rarely implemented in terrestrial biosphere models and tested in real cases. In this study, we combine a new soil biogeochemistry model with an existing model of land-surface hydrology and vegetation dynamics (T&C). Specifically the soil biogeochemistry component explicitly separates different litter pools and distinguishes SOC in particulate, dissolved and mineral associated fractions. Extracellular enzymes and microbial pools are explicitly represented differentiating the functional roles of bacteria, saprotrophic and mycorrhizal fungi. Microbial activity depends on temperature, soil moisture and litter or SOC stoichiometry. The activity of macrofauna is also modeled. Nutrient dynamics include the cycles of nitrogen, phosphorous and potassium. The model accounts for feedbacks between nutrient limitations and plant growth as well as for plant stoichiometric flexibility. In turn, litter input is a function of the simulated vegetation dynamics. Root exudation and export to mycorrhiza are computed based on a nutrient uptake cost function. The combined model is tested to reproduce respiration dynamics and nitrogen cycle in few sites where data were available to test plausibility of results across a range of different metrics. For instance in a Swiss grassland ecosystem, fine root, bacteria, fungal and macrofaunal respiration account for 40%, 23%, 33% and 4% of total belowground respiration, respectively. Root exudation and carbon export to mycorrhizal represent about 7% of plant Net Primary Production. The model allows exploring the temporal dynamics of respiration fluxes from the different ecosystem components and designing virtual experiments on the controls exerted by environmental variables and/or soil microbes and mycorrhizal associations on soil carbon storage, plant growth, and nutrient leaching.

Palaeodistribution modelling of European vegetation types at the Last Glacial Maximum using modern analogues from Siberia: Prospects and limitations

NASA Astrophysics Data System (ADS)

Janská, Veronika; Jiménez-Alfaro, Borja; Chytrý, Milan; Divíšek, Jan; Anenkhonov, Oleg; Korolyuk, Andrey; Lashchinskyi, Nikolai; Culek, Martin

2017-03-01

We modelled the European distribution of vegetation types at the Last Glacial Maximum (LGM) using present-day data from Siberia, a region hypothesized to be a modern analogue of European glacial climate. Distribution models were calibrated with current climate using 6274 vegetation-plot records surveyed in Siberia. Out of 22 initially used vegetation types, good or moderately good models in terms of statistical validation and expert-based evaluation were computed for 18 types, which were then projected to European climate at the LGM. The resulting distributions were generally consistent with reconstructions based on pollen records and dynamic vegetation models. Spatial predictions were most reliable for steppe, forest-steppe, taiga, tundra, fens and bogs in eastern and central Europe, which had LGM climate more similar to present-day Siberia. The models for western and southern Europe, regions with a lower degree of climatic analogy, were only reliable for mires and steppe vegetation, respectively. Modelling LGM vegetation types for the wetter and warmer regions of Europe would therefore require gathering calibration data from outside Siberia. Our approach adds value to the reconstruction of vegetation at the LGM, which is limited by scarcity of pollen and macrofossil data, suggesting where specific habitats could have occurred. Despite the uncertainties of climatic extrapolations and the difficulty of validating the projections for vegetation types, the integration of palaeodistribution modelling with other approaches has a great potential for improving our understanding of biodiversity patterns during the LGM.

Biodiversity of Terrestrial Vegetation during Past Warm Periods

NASA Astrophysics Data System (ADS)

Davies-Barnard, T.; Valdes, P. J.; Ridgwell, A.

2016-12-01

Previous modelling studies of vegetation have generally used a small number of plant functional types to understand how the terrestrial biosphere responds to climate changes. Whilst being useful for understanding first order climate feedbacks, this climate-envelope approach makes a lot of assumptions about past vegetation being very similar to modern. A trait-based method has the advantage for paleo modelling in that there are substantially less assumptions made. In a novel use of the trait-based dynamic vegetation model JeDi, forced with output from climate model HadCM3, we explore past biodiversity and vegetation carbon changes. We use JeDi to model an optimal 2000 combinations of fifteen different traits to enable assessment of the overall level of biodiversity as well as individual growth strategies. We assess the vegetation shifts and biodiversity changes in past greenhouse periods to better understand the impact on the terrestrial biosphere. This work provides original insights into the response of vegetation and terrestrial carbon to climate and hydrological changes in high carbon dioxide climates over time, including during the Late Permian and Cretaceous. We evaluate how the location of biodiversity hotspots and species richness in past greenhouse climates is different to the present day.

Spatial Self-Organization of Vegetation Subject to Climatic Stress—Insights from a System Dynamics—Individual-Based Hybrid Model

PubMed Central

Vincenot, Christian E.; Carteni, Fabrizio; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2016-01-01

In simulation models of populations or communities, individual plants have often been obfuscated in favor of aggregated vegetation. This simplification comes with a loss of biological detail and a smoothing out of the demographic noise engendered by stochastic individual-scale processes and heterogeneities, which is significant among others when studying the viability of small populations facing challenging fluctuating environmental conditions. This consideration has motivated the development of precise plant-centered models. The accuracy gained in the representation of plant biology has then, however, often been balanced by the disappearance in models of important plant-soil interactions (esp. water dynamics) due to the inability of most individual-based frameworks to simulate complex continuous processes. In this study, we used a hybrid modeling approach, namely integrated System Dynamics (SD)—Individual-based (IB), to illustrate the importance of individual plant dynamics to explain spatial self-organization of vegetation in arid environments. We analyzed the behavior of this model under different parameter sets either related to individual plant properties (such as seed dispersal distance and reproductive age) or the environment (such as intensity and yearly distribution of precipitation events). While the results of this work confirmed the prevailing theory on vegetation patterning, they also revealed the importance therein of plant-level processes that cannot be rendered by reaction-diffusion models. Initial spatial distribution of plants, reproductive age, and average seed dispersal distance, by impacting patch size and vegetation aggregation, affected pattern formation and population survival under climatic variations. Besides, changes in precipitation regime altered the demographic structure and spatial organization of vegetation patches by affecting plants differentially depending on their age and biomass. Water availability influenced non-linearly total biomass density. Remarkably, lower precipitation resulted in lower mean plant age yet higher mean individual biomass. Moreover, seasonal variations in rainfall greater than a threshold (here, ±0.45 mm from the 1.3 mm baseline) decreased mean total biomass and generated limit cycles, which, in the case of large variations, were preceded by chaotic demographic and spatial behavior. In some cases, peculiar spatial patterns (e.g., rings) were also engendered. On a technical note, the shortcomings of the present model and the benefit of hybrid modeling for virtual investigations in plant science are discussed. PMID:27252707

Using a Dynamic Global Vegetation Model to Simulate the Response of Vegetation to Warming at the Paleocene-Eocene Boundary

NASA Astrophysics Data System (ADS)

Shellito, C. J.; Sloan, L. C.

2004-12-01

A major turnover in benthic marine and terrestrial fauna marks the Initial Eocene Thermal Maximum (IETM) (~55Ma), a period of ~150 ky in which there was a rapid rise in deep sea and high latitude sea surface temperatures by 5-8C. Curiously, no major responses to this warming in the terrestrial floral record have been detected to date. Here, we present results from experiments examining the response of the global distribution of vegetation to changes in climate at the IETM using the NCAR Land Surface Model (LSM1.2) integrated with a dynamic global vegetation model (DGVM). DGVMs allow vegetation to respond to and interact with climate, and thus, provide a unique new method for addressing questions regarding feedbacks between the ecosystem and climate in Earth's past. However, there are a number of drawbacks to using these models that can affect interpretation of results. More specifically, these drawbacks involve uncertainties in the application of modern plant functional types to paleo-flora simulations, inaccuracies in the model climatology used to drive the DGVM, and lack of available detail regarding paleo-geography and paleo-soil type for use in model boundary conditions. For a better understanding of these drawbacks, we present results from a series of tests in the NCAR LSM-DGVM which examine (1) the effect of removing C4 grasses from the available plant functional types in the model; (2) model sensitivity to a change in soil texture; and (3), model sensitivity to a change in the value of pCO2 used in the photosynthetic rate equations. We consider our DGVM results for the IETM in light of output from these sensitivity experiments.

Short- and Long-Term Feedbacks on Vegetation Water Use: Unifying Evidence from Observations and Modeling

NASA Astrophysics Data System (ADS)

Mackay, D. S.

2001-05-01

Recent efforts to measure and model the interacting influences of climate, soil, and vegetation on soil water and nutrient dynamics have identified numerous important feedbacks that produce nonlinear responses. In particular, plant physiological factors that control rates of transpiration respond to soil water deficits and vapor pressure deficits (VPD) in the short-term, and to climate, nutrient cycling and disturbance in the long-term. The starting point of this presentation is the observation that in many systems, in particular forest ecosystems, conservative water use emerges as a result of short-term closure of stomata in response to high evaporative demand, and long-term vegetative canopy development under nutrient limiting conditions. Evidence for important short-term controls is presented from sap flux measurements of stand transpiration, remote sensing, and modeling of transpiration through a combination of physically-based modeling and Monte Carlo analysis. A common result is a strong association between stomatal conductance (gs) and the negative evaporative gain (∂ gs/∂ VPD) associated with the sensitivity of stomatal closure to rates of water loss. The importance of this association from the standpoint of modeling transpiration depends on the degree of canopy-atmosphere coupling. This suggests possible simplifications to future canopy component models for use in watershed and larger-scale hydrologic models for short-term processes. However, further results are presented from theoretical modeling, which suggest that feedbacks between hydrology and vegetation in current long-term (inter-annual to century) models may be too simple, as they do not capture the spatially variable nature of slow nutrient cycling in response to soil water dynamics and site history. Memory effects in the soil nutrient pools can leave lasting effects on more rapid processes associated with soil, vegetation, atmosphere coupling.

Understanding Broadscale Wildfire Risks in a Human-Dominated Landscape

Treesearch

Jeffrey P. Prestemon; John M. Pye; David T. Butry; Thomas P. Holmes; D. Evan Mercer

2002-01-01

Broadscale statistical evaluations of wildfire incidence can answer policy relevant questions about the effectiveness of microlevel vegetation management and can identify subjects needing further study. A dynamic time series cross-sectional model was used to evaluate the statistical links between forest wildfire and vegetation management, human land use, and climatic...

Incorporating historical ecosystem diversity into conservation planning efforts in grass and shrub ecosystems

Treesearch

Amy C. Ganguli; Johathan B. Haufler; Carolyn A. Mehl; Jimmie D. Chew

2011-01-01

Understanding historical ecosystem diversity and wildlife habitat quality can provide a useful reference for managing and restoring rangeland ecosystems. We characterized historical ecosystem diversity using available empirical data, expert opinion, and the spatially explicit vegetation dynamics model SIMPPLLE (SIMulating Vegetative Patterns and Processes at Landscape...

Estimating carbon and showing impacts of drought using satellite data in regression-tree models

USGS Publications Warehouse

Boyte, Stephen; Wylie, Bruce K.; Howard, Danny; Dahal, Devendra; Gilmanov, Tagir G.

2018-01-01

Integrating spatially explicit biogeophysical and remotely sensed data into regression-tree models enables the spatial extrapolation of training data over large geographic spaces, allowing a better understanding of broad-scale ecosystem processes. The current study presents annual gross primary production (GPP) and annual ecosystem respiration (RE) for 2000–2013 in several short-statured vegetation types using carbon flux data from towers that are located strategically across the conterminous United States (CONUS). We calculate carbon fluxes (annual net ecosystem production [NEP]) for each year in our study period, which includes 2012 when drought and higher-than-normal temperatures influence vegetation productivity in large parts of the study area. We present and analyse carbon flux dynamics in the CONUS to better understand how drought affects GPP, RE, and NEP. Model accuracy metrics show strong correlation coefficients (r) (r ≥ 94%) between training and estimated data for both GPP and RE. Overall, average annual GPP, RE, and NEP are relatively constant throughout the study period except during 2012 when almost 60% less carbon is sequestered than normal. These results allow us to conclude that this modelling method effectively estimates carbon dynamics through time and allows the exploration of impacts of meteorological anomalies and vegetation types on carbon dynamics.

Ecosystem management can mitigate vegetation shifts induced by climate change in African savannas

NASA Astrophysics Data System (ADS)

Scheiter, Simon; Savadogo, Patrice

2017-04-01

The welfare of people in the tropics and sub-tropics strongly depends on goods and services that ecosystems supply. Flows of these ecosystem services are strongly influenced by interactions between climate change and land use. A prominent example are savannas, covering approximately 20% of the Earth's land surface. Key ecosystem services in these areas are fuel wood for cooking and heating, food production and livestock. Changes in the structure and dynamics of savanna vegetation may strongly influence local people's living conditions, as well as the climate system and biogeochemical cycles. We used a dynamic vegetation model to explore interactive effects of climate and land use on the vegetation structure, distribution and carbon cycling of African savannas under current and future conditions. More specifically, we simulate long term impacts of fire management, grazing and fuel wood harvesting. The model projects that under future climate without human land use impacts, large savanna areas would shift towards more wood dominated vegetation due to CO2 fertilization effects and changes in water use efficiency. However, land use activities can mitigate climate change impacts on vegetation to maintain desired ecosystem states that ensure fluxes of important ecosystem services. We then use optimization algorithms to identify sustainable land use strategies that maximize the utility of people managing savannas while preserving a stable vegetation state. Our results highlight that the development of land use policy for tropical and sub-tropical areas needs to account for climate change impacts on vegetation.

Monitoring vegetation dynamics with medium resolution MODIS-EVI time series at sub-regional scale in southern Africa

NASA Astrophysics Data System (ADS)

Dubovyk, Olena; Landmann, Tobias; Erasmus, Barend F. N.; Tewes, Andreas; Schellberg, Jürgen

2015-06-01

Currently there is a lack of knowledge on spatio-temporal patterns of land surface dynamics at medium spatial scale in southern Africa, even though this information is essential for better understanding of ecosystem response to climatic variability and human-induced land transformations. In this study, we analysed vegetation dynamics across a large area in southern Africa using the 14-years (2000-2013) of medium spatial resolution (250 m) MODIS-EVI time-series data. Specifically, we investigated temporal changes in the time series of key phenometrics including overall greenness, peak and timing of annual greenness over the monitoring period and study region. In order to specifically capture spatial and per pixel vegetation changes over time, we calculated trends in these phenometrics using a robust trend analysis method. The results showed that interannual vegetation dynamics followed precipitation patterns with clearly differentiated seasonality. The earliest peak greenness during 2000-2013 occurred at the end of January in the year 2000 and the latest peak greenness was observed at the mid of March in 2012. Specifically spatial patterns of long-term vegetation trends allowed mapping areas of (i) decrease or increase in overall greenness, (ii) decrease or increase of peak greenness, and (iii) shifts in timing of occurrence of peak greenness over the 14-year monitoring period. The observed vegetation decline in the study area was mainly attributed to human-induced factors. The obtained information is useful to guide selection of field sites for detailed vegetation studies and land rehabilitation interventions and serve as an input for a range of land surface models.

Systems modeling to improve the hydro-ecological performance of diked wetlands

NASA Astrophysics Data System (ADS)

Alminagorta, Omar; Rosenberg, David E.; Kettenring, Karin M.

2016-09-01

Water scarcity and invasive vegetation threaten arid-region wetlands and wetland managers seek ways to enhance wetland ecosystem services with limited water, labor, and financial resources. While prior systems modeling efforts have focused on water management to improve flow-based ecosystem and habitat objectives, here we consider water allocation and invasive vegetation management that jointly target the concurrent hydrologic and vegetation habitat needs of priority wetland bird species. We formulate a composite weighted usable area for wetlands (WU) objective function that represents the wetland surface area that provides suitable water level and vegetation cover conditions for priority bird species. Maximizing the WU is subject to constraints such as water balance, hydraulic infrastructure capacity, invasive vegetation growth and control, and a limited financial budget to control vegetation. We apply the model at the Bear River Migratory Bird Refuge on the Great Salt Lake, Utah, compare model-recommended management actions to past Refuge water and vegetation control activities, and find that managers can almost double the area of suitable habitat by more dynamically managing water levels and managing invasive vegetation in August at the beginning of the window for control operations. Scenario and sensitivity analyses show the importance to jointly consider hydrology and vegetation system components rather than only the hydrological component.

Ecological investigations: vegetation studies, preliminary findings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Olgeirson, E.R.; Martin, R.B.

1978-09-01

The objective of the vegetation studies conducted on the research site is to produce a descriptive data base that can be applied to determinations of carrying capacity of the site and surrounding area. Additional information obtained about parameters that influence vegetation growth and maintenance of soil nutrients, and moisture and temperature regimes help define dynamic relationships that must be understood to effect successful revegetation and habitat rehabilitation. The descriptive vegetation baseline also provides a point of departure for design of future monitoring programs, and predictive models and strategies to be used in dealing with impact mitigation; in turn, monitoring programsmore » and predictive modeling form the bases for making distinctions between natural trends and man-induced perturbations.« less

Modelling the interactions between vegetation and climate from the Cretaceous to the Eocene

NASA Astrophysics Data System (ADS)

Loptson, Claire; Lunt, Dan; Francis, Jane

2013-04-01

The climates during the Cretaceous (~144 to 66 Ma) and the early Eocene (~56 to 48 Ma) were much warmer than the present day. Atmospheric CO2 levels for these past climates have a large uncertainty associated with them, but were possibly as high as 2000 to 3000 ppm for the early Eocene (Beerling and Royer, 2011; Lowenstein and Demicco, 2006) and maximum values are thought to range from 800 to 1800 ppm during the Cretaceous (Royer et al., 2012). Current modelling efforts have had great difficulty in replicating the shallow latitudinal temperature gradient indicated by proxy data for these time periods (e.g. Heinemann et al., 2009; Winguth et al., 2010; Shellito et al., 2009). Mechanisms that can result in such a low temperature gradient have not been found (Winguth et al., 2010; Beerling et al., 2011; Sloan and Morrill, 1998), but a contributing factor could be that not all climate feedbacks are included in these models. Vegetation feedbacks have been shown to be especially important (e.g. Otto-Bliesner and Upchurch, 1997; Bonan, 2008) so by including a more accurate representation of vegetation in the climate model, the model-data discrepancies may be reduced. A fully coupled atmosphere-ocean GCM, HadCM3L, coupled to a dynamic global vegetation model (TRIFFID), was used to simulate the climate and the predicted vegetation distributions for and the early Eocene and 12 different time slices representing different ages throughout the Cretaceous at 4x pre-industrial CO2. The only difference in the way these simulations were set up are different boundary conditions that are specific to that time period, e.g. different solar constants and paleogeographies. This allows a direct comparison between the time slices. We present the changes in climate, and therefore vegetation, during the Cretaceous due to changes in these boundary conditions alone, with a focus on Antarctica. Additional Eocene simulations were also carried out with a) fixed globally-uniform vegetation and b) a prescribed vegetation distribution as predicted by the TRIFFID model, but with TRIFFID turned off i.e. the vegetation distribution was fixed, not dynamic. All three Eocene simulations were also run for 2x pre-industrial CO2, allowing the effects of changing CO2 on climate and vegetation to be analysed. We present the effects of different vegetation representations included in a GCM on the early Eocene climate. In addition, climate sensitivity and sensitivity of vegetation to atmospheric CO2 concentration during the early Eocene are investigated. Modelled vegetation types are compared to fossil data to evaluate the performance of TRIFFID for these paleoclimate simulations.

Hydroclimatic Controls on the Means and Variability of Vegetation Phenology and Carbon Uptake

NASA Technical Reports Server (NTRS)

Koster, Randal Dean; Walker, Gregory K.; Collatz, George J.; Thornton, Peter E.

2013-01-01

Long-term, global offline (land-only) simulations with a dynamic vegetation phenology model are used to examine the control of hydroclimate over vegetation-related quantities. First, with a control simulation, the model is shown to capture successfully (though with some bias) key observed relationships between hydroclimate and the spatial and temporal variations of phenological expression. In subsequent simulations, the model shows that: (i) the global spatial variation of seasonal phenological maxima is controlled mostly by hydroclimate, irrespective of distributions in vegetation type, (ii) the occurrence of high interannual moisture-related phenological variability in grassland areas is determined by hydroclimate rather than by the specific properties of grassland, and (iii) hydroclimatic means and variability have a corresponding impact on the spatial and temporal distributions of gross primary productivity (GPP).

An improved SWAT vegetation growth module and its evaluation for four tropical ecosystems

NASA Astrophysics Data System (ADS)

Alemayehu, Tadesse; van Griensven, Ann; Taddesse Woldegiorgis, Befekadu; Bauwens, Willy

2017-09-01

The Soil and Water Assessment Tool (SWAT) is a globally applied river basin ecohydrological model used in a wide spectrum of studies, ranging from land use change and climate change impacts studies to research for the development of the best water management practices. However, SWAT has limitations in simulating the seasonal growth cycles for trees and perennial vegetation in the tropics, where rainfall rather than temperature is the dominant plant growth controlling factor. Our goal is to improve the vegetation growth module of SWAT for simulating the vegetation variables - such as the leaf area index (LAI) - for tropical ecosystems. Therefore, we present a modified SWAT version for the tropics (SWAT-T) that uses a straightforward but robust soil moisture index (SMI) - a quotient of rainfall (P) and reference evapotranspiration (ETr) - to dynamically initiate a new growth cycle within a predefined period. Our results for the Mara Basin (Kenya/Tanzania) show that the SWAT-T-simulated LAI corresponds well with the Moderate Resolution Imaging Spectroradiometer (MODIS) LAI for evergreen forest, savanna grassland and shrubland. This indicates that the SMI is reliable for triggering a new annual growth cycle. The water balance components (evapotranspiration and streamflow) simulated by the SWAT-T exhibit a good agreement with remote-sensing-based evapotranspiration (ET-RS) and observed streamflow. The SWAT-T model, with the proposed vegetation growth module for tropical ecosystems, can be a robust tool for simulating the vegetation growth dynamics in hydrologic models in tropical regions.

Predictive models of forest dynamics.

PubMed

Purves, Drew; Pacala, Stephen

2008-06-13

Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter the response of the global climate system to increased atmospheric carbon dioxide over the next century. But there is little agreement between different DGVMs, making forest dynamics one of the greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by integrating the ecological realities of biodiversity and height-structured competition for light, facilitated by recent advances in the mathematics of forest modeling, ecological understanding of diverse forest communities, and the availability of forest inventory data.

The SMAP Level-4 ECO Project: Linking the Terrestrial Water and Carbon Cycles

NASA Technical Reports Server (NTRS)

Kolassa, J.; Reichle, R. H.; Liu, Qing; Koster, Randal D.

2017-01-01

The SMAP (Soil Moisture Active Passive) Level-4 projects aims to develop a fully coupled hydrology-vegetation data assimilation algorithm to generate improved estimates of modeled hydrological fields and carbon fluxes. This includes using the new NASA Catchment-CN (Catchment-Carbon-Nitrogen) model, which combines the Catchment land surface hydrology model with dynamic vegetation components from the Community Land Model version 4 (CLM4). As such, Catchment-CN allows a more realistic, fully coupled feedback between the land hydrology and the biosphere. The L4 ECO project further aims to inform the model through the assimilation of Soil Moisture Active Passive (SMAP) brightness temperature observations as well as observations of Moderate Resolution Imaging Spectroradiometer (MODIS) fraction of absorbed photosynthetically active radiation (FPAR). Preliminary results show that the assimilation of SMAP observations leads to consistent improvements in the model soil moisture skill. An evaluation of the Catchment-CN modeled vegetation characteristics showed that a calibration of the model's vegetation parameters is required before an assimilation of MODIS FPAR observations is feasible.

Reconstructing a lost Eocene Paradise, Part II: On the utility of dynamic global vegetation models in pre-Quaternary climate studies

NASA Astrophysics Data System (ADS)

Shellito, Cindy J.; Sloan, Lisa C.

2006-02-01

Models that allow vegetation to respond to and interact with climate provide a unique method for addressing questions regarding feedbacks between the ecosystem and climate in pre-Quaternary time periods. In this paper, we consider how Dynamic Global Vegetation Models (DGVMs), which have been developed for simulations with present day climate, can be used for paleoclimate studies. We begin with a series of tests in the NCAR Land Surface Model (LSM)-DGVM with Eocene geography to examine (1) the effect of removing C 4 grasses from the available plant functional types in the model; (2) model sensitivity to a change in soil texture; and (3), model sensitivity to a change in the value of pCO 2 used in the photosynthetic rate equations. The tests were designed to highlight some of the challenges of using these models and prompt discussion of possible improvements. We discuss how lack of detail in model boundary conditions, uncertainties in the application of modern plant functional types to paleo-flora simulations, and inaccuracies in the model climatology used to drive the DGVM can affect interpretation of model results. However, we also review a number of DGVM features that can facilitate understanding of past climates and offer suggestions for improving paleo-DGVM studies.

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data

NASA Astrophysics Data System (ADS)

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.; Yin, Yunhe; Kumar, Jitendra; Ma, Chun; Xu, Xiaofeng

2017-09-01

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. We compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62). However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S-10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1-0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.

Modeling global vegetation in the late Quaternary: What progress have we made and what are the priorities for the future?

NASA Astrophysics Data System (ADS)

Kaplan, Jed

2017-04-01

More than two decades ago, the development of the first global biogeography models led to an interest in simulating global land cover in the past. These models promised the possibility of creating a coherent picture of the Earth's vegetation that went beyond qualitative extrapolation of site-based observations, e.g., from paleoecological archives, and was not limited to areas with a high density of sites. Then as now, the goal of much work simulating past vegetation was to explore and understand the role of biogeophysical and biogeochemical feedbacks between the Earth's land surface and the climate system. Paleovegetation modeling for the late Quaternary has also influenced debates on the character of natural vegetation, conservation and ecological restoration goals, and the co-evolution of humans, civilizations, and the landscapes in which they live. The first simulations of global land cover in the past used equilibrium vegetation models, e.g., BIOME1, BIOME3, and BIOME4, and focused on well-known timeslices of interest in paleoclimate research, including the Last Glacial Maximum (21,000 BP) and the mid-Holocene (6,000 BP). Questions addressed included: quantification of the importance of terrestrial vegetation in the glacial carbon cycle, the role of changing vegetation cover on glacial inception, and the influence of biogeophysical feedbacks on the amplitude and spatial pattern of the mid-Holocene African Monsoon. In the intervening years, as both vegetation and climate models evolved and improved, the spatial resolution, number of periods studied, and the type of research questions addressed expanded greatly. Studies covered the dynamics of Arctic vegetation, wetland area, wetland methane emissions, and paleo-atmospheric chemistry, dust emissions and effects on paleoclimate, among others. A major recent advance in paleovegetation modeling for the late Quaternary has come with the development of Dynamic Global Vegetation Models (DGVMs) that are capable of simulating changing vegetation cover over time, continuously. Several DGVMs have been directly incorporated into the land surface scheme of modern Earth System Models (ESMs), further allowing the exploration of land-atmosphere feedbacks, e.g., during abrupt climate change events, such as those that occurred during the last deglaciation. Recent increases in computer power have also allowed offline simulations, i.e., not directly coupled to an ESM, with DGVMs to simulate vegetation change over long time periods, e.g., continuously for the entire Holocene. Realizing that climate change alone was not the only driver of land cover change over the late Quaternary, the most recent developments in paleovegetation modeling for this period have incorporated human agency as an influence on vegetation. Incorporation of scenarios of Anthropogenic Land Cover Change into DGVMs has allowed a quantitative contribution to the ongoing, lively debate regarding the role of humans in influencing Holocene atmospheric greenhouse gas concentrations. With the further advances in ESMs and the availability of very long climate model simulations, e.g., TraCE-21ka, improvements to DGVMs such as the explicit representation of age structure and plant traits, and the increasing awareness of the importance of human-environment interactions, the future of paleovegetation modeling for the late Quaternary presents a variety of opportunities. One important focus for future modeling should be on simulating the dynamics of ecotones, e.g., forest-grassland boundaries, over time, particularly during abrupt transient climate change events. Accurate simulation of ecotone boundaries is traditionally a weakness in DGVMs, yet these environments are highly valued by humans for their ecosystem services both at present and in the past, paleoecological evidence suggests that ecotone boundaries were very sensitive to past climate change, and they are critical locations where land-atmosphere feedbacks could have amplified or attenuated ongoing, externally-forced climate change. Lessons drawn from paleovegetation simulations may shed new light on the behavior of the earth system that will be valuable for understanding the future.

Combining surface reanalysis and remote sensing data for monitoring evapotranspiration

USGS Publications Warehouse

Marshall, M.; Tu, K.; Funk, C.; Michaelsen, J.; Williams, Pat; Williams, C.; Ardö, J.; Marie, B.; Cappelaere, B.; Grandcourt, A.; Nickless, A.; Noubellon, Y.; Scholes, R.; Kutsch, W.

2012-01-01

Climate change is expected to have the greatest impact on the world's poor. In the Sahel, a climatically sensitive region where rain-fed agriculture is the primary livelihood, expected decreases in water supply will increase food insecurity. Studies on climate change and the intensification of the water cycle in sub-Saharan Africa are few. This is due in part to poor calibration of modeled actual evapotranspiration (AET), a key input in continental-scale hydrologic models. In this study, a model driven by dynamic canopy AET was combined with the Global Land Data Assimilation System realization of the NOAH Land Surface Model (GNOAH) wet canopy and soil AET for monitoring purposes in sub-Saharan Africa. The performance of the hybrid model was compared against AET from the GNOAH model and dynamic model using eight eddy flux towers representing major biomes of sub-Saharan Africa. The greatest improvements in model performance are at humid sites with dense vegetation, while performance at semi-arid sites is poor, but better than individual models. The reduction in errors using the hybrid model can be attributed to the integration of a dynamic vegetation component with land surface model estimates, improved model parameterization, and reduction of multiplicative effects of uncertain data.

Modeling invasive alien plant species in river systems: Interaction with native ecosystem engineers and effects on hydro-morphodynamic processes

NASA Astrophysics Data System (ADS)

van Oorschot, M.; Kleinhans, M. G.; Geerling, G. W.; Egger, G.; Leuven, R. S. E. W.; Middelkoop, H.

2017-08-01

Invasive alien plant species negatively impact native plant communities by out-competing species or changing abiotic and biotic conditions in their introduced range. River systems are especially vulnerable to biological invasions, because waterways can function as invasion corridors. Understanding interactions of invasive and native species and their combined effects on river dynamics is essential for developing cost-effective management strategies. However, numerical models for simulating long-term effects of these processes are lacking. This paper investigates how an invasive alien plant species affects native riparian vegetation and hydro-morphodynamics. A morphodynamic model has been coupled to a dynamic vegetation model that predicts establishment, growth and mortality of riparian trees. We introduced an invasive alien species with life-history traits based on Japanese Knotweed (Fallopia japonica), and investigated effects of low- and high propagule pressure on invasion speed, native vegetation and hydro-morphodynamic processes. Results show that high propagule pressure leads to a decline in native species cover due to competition and the creation of unfavorable native colonization sites. With low propagule pressure the invader facilitates native seedling survival by creating favorable hydro-morphodynamic conditions at colonization sites. With high invader abundance, water levels are raised and sediment transport is reduced during the growing season. In winter, when the above-ground invader biomass is gone, results are reversed and the floodplain is more prone to erosion. Invasion effects thus depend on seasonal above- and below ground dynamic vegetation properties and persistence of the invader, on the characteristics of native species it replaces, and the combined interactions with hydro-morphodynamics.

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method

USGS Publications Warehouse

Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis

2017-01-01

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled-Ocean-Atmosphere-Wave-Sediment Transport (COAWST) Modeling System. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant density, height, and to a certain degree, diameter. Wave dissipation is mostly dependent on the variation in plant density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance for future observational and modeling work to optimize efforts and reduce exploration of parameter space.

Obtaining a Pragmatic Representation of Fire Disturbance in Dynamic Vegetation Models by Assimilating Earth Observation Data

NASA Astrophysics Data System (ADS)

Kantzas, Euripides; Quegan, Shaun

2015-04-01

Fire constitutes a violent and unpredictable pathway of carbon from the terrestrial biosphere into the atmosphere. Despite fire emissions being in many biomes of similar magnitude to that of Net Ecosystem Exchange, even the most complex Dynamic Vegetation Models (DVMs) embedded in IPCC General Circulation Models poorly represent fire behavior and dynamics, a fact which still remains understated. As DVMs operate on a deterministic, grid cell-by-grid cell basis they are unable to describe a host of important fire characteristics such as its propagation, magnitude of area burned and stochastic nature. Here we address these issues by describing a model-independent methodology which assimilates Earth Observation (EO) data by employing image analysis techniques and algorithms to offer a realistic fire disturbance regime in a DVM. This novel approach, with minimum model restructuring, manages to retain the Fire Return Interval produced by the model whilst assigning pragmatic characteristics to its fire outputs thus allowing realistic simulations of fire-related processes such as carbon injection into the atmosphere and permafrost degradation. We focus our simulations in the Arctic and specifically Canada and Russia and we offer a snippet of how this approach permits models to engage in post-fire dynamics hitherto absent from any other model regardless of complexity.

Using a dynamic vegetation model for future projections of crop yields: application to Belgium in the framework of the VOTES and MASC projects

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Fontaine, Corentin M.; Dendoncker, Nicolas; Beckers, Veronique; Debusscher, Bos; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

Dynamic vegetation models (DVM) were initially designed to describe the dynamics of natural ecosystems as a function of climate and soil, to study the role of the vegetation in the carbon cycle. These models are now directly coupled with climate models in order to evaluate feedbacks between vegetation and climate. But DVM characteristics allow numerous other applications, leading to amelioration of some of their modules (e.g., evaluating sensitivity of the hydrological module to land surface changes) and developments (e.g., coupling with other models like agent-based models), to be used in ecosystem management and land use planning studies. It is in this dynamic context about DVMs that we have adapted the CARAIB (CARbon Assimilation In the Biosphere) model. One of the main improvements is the implementation of a crop module, allowing the assessment of climate change impacts on crop yields. We try to validate this module at different scales: - from the plot level, with the use of eddy-covariance data from agricultural sites in the FLUXNET network, such as Lonzée (Belgium) or other Western European sites (Grignon, Dijkgraaf,…), - to the country level, for which we compare the crop yield calculated by CARAIB to the crop yield statistics for Belgium and for different agricultural regions of the country. Another challenge for the CARAIB DVM was to deal with the landscape dynamics, which is not directly possible due to the lack of consideration of anthropogenic factors in the system. In the framework of the VOTES and the MASC projects, CARAIB is coupled with an agent-based model (ABM), representing the societal component of the system. This coupled module allows the use of climate and socio-economic scenarios, particularly interesting for studies which aim at ensuring a sustainable approach. This module has particularly been exploited in the VOTES project, where the objective was to provide a social, biophysical and economic assessment of the ecosystem services in four municipalities under urban pressure in the center of Belgium. The biophysical valuation was carried out with the coupled module, allowing a quantitative evaluation of key ecosystem services as a function of three climatic and socio-economic scenarios.

Riparian Vegetation: Controls on Channel Planform in Noncohesive Beds

NASA Astrophysics Data System (ADS)

Tal, M.; Paola, C.; Gran, K.

2001-12-01

Riparian vegetation has strong consequences for the channel planform and dynamics. An understanding of this role is key to accurate modeling of river systems, and may provide answers to fundamental questions concerning stream dynamics as well as bridge the various approaches to modeling channel evolution. Vegetation on the flood plain works to constrain the flow of the river to a single channel by stabilizing banks and offering resistance to overbank flow. These controls were recently established through a set of controlled experiments at the St. Anthony Falls Laboratory. The runs were designed to determine how addition of vegetation affects channel form and flow dynamics. This was achieved by holding water discharge, sediment discharge, grain size, and slope constant, while making vegetation density the only variable between runs. Plants were grown while water discharge was half its channel-forming value. This work showed that as vegetation density increased there was a decrease in braiding intensity, lateral mobility, and width to depth ratios, and an increase in maximum scour hole depth, and channel relief. While producing braiding experimentally has proven simple, no one has yet produced true dynamic meanders (i.e. high-amplitude bends that grow, cut off, and grow again). Present experimental studies at St. Anthony Falls Laboratory aim to investigate the role of vegetation in the development of a meandering river in otherwise insufficiently cohesive sand that would favor a more stable braided river system. The experiments begin with an unseeded bed into which a straight channel has been carved. Each cycle comprises a period of low discharge during which the bed is seeded with alfalfa seeds. The discharge is raised to a higher discharge only after the plants have grown to a height of about 20 mm (approximately 7 days). The duration of the high-flow stage is such that not more than 10-20% of the channel width is eroded. In addition to offering insight as to the several possible states that a river might be in, the experimental studies are intended to provide an understanding of how vegetation stabilizes single-thread channels, identify the nondimensional parameters that measure the stabilizing effects of vegetation, and realize the role of discharge variation in allowing plant colonization.

Sensitivity of vegetation indices and gross primary production of tallgrass prairie to severe drought

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wagle, Pradeep; Xiao, Xiangming; Torn, Margaret S.

2014-09-01

Drought affects vegetation photosynthesis and growth.Many studies have used the normalized difference vegetation index (NDVI), which is calculated as the normalized ratio between near infrared and red spectral bands in satellite images, to evaluate the response of vegetation to drought. In this study, we examined the impacts of drought on three vegetation indices (NDVI, enhanced vegetation index, EVI, and land surface water index, LSWI) and CO2 flux from three tallgrass prairie eddy flux tower sites in the U.S. Gross primary production (GPP) was also modeled using a satellite-based Vegetation Photosynthesis Model (VPM), and the modeled GPP (GPPVPM) was compared withmore » the GPP (GPPEC) derived from eddy covariance measurements. Precipitation at two sites in Oklahoma was 30% below the historical mean in both years of the study period (2005–2006), while the site in Illinois did not experience drought in the 2005–2007 study period. The EVI explained the seasonal dynamics of GPP better than did NDVI. The LSWI dropped below zero during severe droughts in the growing season, showing its potential to track drought. The result shows that GPP was more sensitive to drought than were vegetation indices, and EVI and LSWI were more sensitive than NDVI. We developed a modified function (Wscalar), calculated as a function of LSWI, to account for the effect of severe droughts on GPP in VPM. The GPPVPM from the modified VPM accounted for the rapid reduction in GPP during severe droughts and the seasonal dynamics of GPPVPM agreed reasonably well with GPPEC. Our analysis shows that 8-day averaged values (temperature, vapor-pressure deficit) do not reflect the short-term extreme climate events well, suggesting that satellite based models may need to be run at daily or hourly scales, especially under unfavorable climatic conditions.« less

High-resolution climate and land surface interactions modeling over Belgium: current state and decennial scale projections

NASA Astrophysics Data System (ADS)

Jacquemin, Ingrid; Henrot, Alexandra-Jane; Beckers, Veronique; Berckmans, Julie; Debusscher, Bos; Dury, Marie; Minet, Julien; Hamdi, Rafiq; Dendoncker, Nicolas; Tychon, Bernard; Hambuckers, Alain; François, Louis

2016-04-01

The interactions between land surface and climate are complex. Climate changes can affect ecosystem structure and functions, by altering photosynthesis and productivity or inducing thermal and hydric stresses on plant species. These changes then impact socio-economic systems, through e.g., lower farming or forestry incomes. Ultimately, it can lead to permanent changes in land use structure, especially when associated with other non-climatic factors, such as urbanization pressure. These interactions and changes have feedbacks on the climate systems, in terms of changing: (1) surface properties (albedo, roughness, evapotranspiration, etc.) and (2) greenhouse gas emissions (mainly CO2, CH4, N2O). In the framework of the MASC project (« Modelling and Assessing Surface Change impacts on Belgian and Western European climate »), we aim at improving regional climate model projections at the decennial scale over Belgium and Western Europe by combining high-resolution models of climate, land surface dynamics and socio-economic processes. The land surface dynamics (LSD) module is composed of a dynamic vegetation model (CARAIB) calculating the productivity and growth of natural and managed vegetation, and an agent-based model (CRAFTY), determining the shifts in land use and land cover. This up-scaled LSD module is made consistent with the surface scheme of the regional climate model (RCM: ALARO) to allow simulations of the RCM with a fully dynamic land surface for the recent past and the period 2000-2030. In this contribution, we analyze the results of the first simulations performed with the CARAIB dynamic vegetation model over Belgium at a resolution of 1km. This analysis is performed at the species level, using a set of 17 species for natural vegetation (trees and grasses) and 10 crops, especially designed to represent the Belgian vegetation. The CARAIB model is forced with surface atmospheric variables derived from the monthly global CRU climatology or ALARO outputs (from a 4 km resolution simulation) for the recent past and the decennial projections. Evidently, these simulations lead to a first analysis of the impact of climate change on carbon stocks (e.g., biomass, soil carbon) and fluxes (e.g., gross and net primary productivities (GPP and NPP) and net ecosystem production (NEP)). The surface scheme is based on two land use/land cover databases, ECOPLAN for the Flemish region and, for the Walloon region, the COS-Wallonia database and the Belgian agricultural statistics for agricultural land. Land use and land cover are fixed through time (reference year: 2007) in these simulations, but a first attempt of coupling between CARAIB and CRAFTY will be made to establish dynamic land use change scenarios for the next decades. A simulation with variable land use would allow an analysis of land use change impacts not only on crop yields and the land carbon budget, but also on climate relevant parameters, such as surface albedo, roughness length and evapotranspiration towards a coupling with the RCM.

Quantifying and Monetizing Potential Climate Change Policy Impacts on Terrestrial Ecosystem Carbon Storage and Wildfires in the United States

EPA Science Inventory

This paper quantifies and monetizes climate change impacts on carbon stored in terrestrial vegetation and wildfire incidence in the contiguous United States to assess the benefits of alternative mitigation policies. The MC-1 dynamic global vegetation model was used to develop int...

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data: Vegetation Carbon Density in ESMs

DOE Office of Scientific and Technical Information (OSTI.GOV)

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. Here we have compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62).more » However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S–10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1–0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.« less

Significant inconsistency of vegetation carbon density in CMIP5 Earth system models against observational data: Vegetation Carbon Density in ESMs

DOE PAGES

Song, Xia; Hoffman, Forrest M.; Iversen, Colleen M.; ...

2017-09-09

Earth system models (ESMs) have been widely used for projecting global vegetation carbon dynamics, yet how well ESMs performed for simulating vegetation carbon density remains untested. Here we have compiled observational data of vegetation carbon density from literature and existing data sets to evaluate nine ESMs at site, biome, latitude, and global scales. Three variables—root (including fine and coarse roots), total vegetation carbon density, and the root:total vegetation carbon ratios (R/T ratios), were chosen for ESM evaluation. ESM models performed well in simulating the spatial distribution of carbon densities in root (r = 0.71) and total vegetation (r = 0.62).more » However, ESM models had significant biases in simulating absolute carbon densities in root and total vegetation biomass across the majority of land ecosystems, especially in tropical and arctic ecosystems. Particularly, ESMs significantly overestimated carbon density in root (183%) and total vegetation biomass (167%) in climate zones of 10°S–10°N. Substantial discrepancies between modeled and observed R/T ratios were found: the R/T ratios from ESMs were relatively constant, approximately 0.2 across all ecosystems, along latitudinal gradients, and in tropic, temperate, and arctic climatic zones, which was significantly different from the observed large variations in the R/T ratios (0.1–0.8). There were substantial inconsistencies between ESM-derived carbon density in root and total vegetation biomass and the R/T ratio at multiple scales, indicating urgent needs for model improvements on carbon allocation algorithms and more intensive field campaigns targeting carbon density in all key vegetation components.« less

Evaluating the coupled vegetation-fire model, LPJ-GUESS-SPITFIRE, against observed tropical forest biomass

NASA Astrophysics Data System (ADS)

Spessa, Allan; Forrest, Matthew; Werner, Christian; Steinkamp, Joerg; Hickler, Thomas

2013-04-01

Wildfire is a fundamental Earth System process. It is the most important disturbance worldwide in terms of area and variety of biomes affected; a major mechanism by which carbon is transferred from the land to the atmosphere (2-4 Pg per annum, equiv. 20-30% of global fossil fuel emissions over the last decade); and globally a significant source of particulate aerosols and trace greenhouse gases. Fire is also potentially important as a feedback in the climate system. If climate change favours more intense fire regimes, this would result in a net transfer of carbon from ecosystems to the atmosphere, as well as higher emissions, and under certain circumstances, increased troposphere ozone production- all contributing to positive climate-land surface feedbacks. Quantitative analysis of fire-vegetation-climate interactions has been held back until recently by a lack of consistent global data sets on fire, and by the underdeveloped state of dynamic vegetation-fire modelling. Dynamic vegetation-fire modelling is an essential part of our forecasting armory for examining the possible impacts of climate, fire regimes and land-use on ecosystems and emissions from biomass burning beyond the observation period, as part of future climate or paleo-climate studies. LPJ-GUESS is a process-based model of vegetation dynamics designed for regional to global applications. It combines features of the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) with those of the General Ecosystem Simulator (GUESS) in a single, flexible modelling framework. The models have identical representations of eco-physiological and biogeochemical processes, including the hydrological cycle. However, they differ in the detail with which vegetation dynamics and canopy structure are simulated. Simplified, computationally efficient representations are used in the LPJ-DGVM, while LPJ-GUESS employs a gap-model approach, which better captures ecological succession and hence ecosystem changes due to disturbance such as fire. SPITFIRE (SPread and InTensity of FIRe and Emissions) mechanistically simulates the number of fires, area burnt, fire intensity, crown fires, fire-induced plant mortality, and emissions of carbon, trace gases and aerosols from biomass burning. Originally developed as an embedded model within LPJ-DGVM, SPITFIRE has since been coupled to LPJ-GUESS. However, neither LPJ-DGVM-SPITFIRE nor LPJ-GUESS-SPITFIRE has been fully benchmarked, especially in terms of how well each model simulates vegetation patterns and biomass in areas where fire is known to be important. This information is crucial if we are to have confidence in the models in forecasting fire, emissions from biomass burning and fire-climate impacts on ecosystems. Here we report on the benchmarking of the LPJ-GUESS-SPITFIRE model. We benchmarked LPJ-GUESS-SPITFIRE driven by a combination of daily reanalysis climate data (Sheffield 2012), monthly GFEDv3 burnt area data (1997-2009) (van der Werf et al. 2010) and long-term annual fire statistics (1901 to 2000) (Mouillot and Field 2005) against new Lidar-based biomass data for tropical forests and savannas (Saatchi et al. 2011; Baccini et al., 2012). Our new work has focused on revising the way GUESS simulates tree allometry, light penetration through the tree canopy and sapling recruitment, and how GUESS-SPITFIRE simulates fire-induced mortality, all based on recent literature, as well as a more explicit accounting of land cover change (JRC's GLC 2009). We present how these combined changes result in a much improved simulation of tree carbon across the tropics, including the Americas, Africa, Asia and Australia. Our results are compared with respect to more empirical-based approaches to calculating emissions from biomass burning. We discuss our findings in terms of improved forecasting of fire, emissions from biomass burning and fire-climate impacts on ecosystems.

The Change in the area of various land covers on the Tibetan Plateau during 1957-2015

NASA Astrophysics Data System (ADS)

Cuo, Lan; Zhang, Yongxin

2017-04-01

With average elevation of 4000 m and area of 2.5×106 km2, Tibetan Plateau hosts various fragile ecosystems such as perennial alpine meadow, perennial alpine steppe, temperate evergreen needleleaf trees, temperate deciduous trees, temperate shrub grassland, and barely vegetated desert. Perennial alpine meadow and steppe are the two dominant vegetation types on the heartland of the plateau. MODIS Leaf Area Index (LAI) ranges from 0 to 2 in most part of the plateau. With climate change, these ecosystems are expected to undergo alteration. This study uses a dynamic vegetation model - Lund-Potsdam-Jena (LPJ) to investigate the change of the barely vegetated area and other vegetation types caused by climate change during 1957-2015 on the Tibetan Plateau. Model simulated foliage projective coverage (FPC) and plant functional types (PFTs) are selected for the investigation. The model is evaluated first using both field surveyed land cover map and MODIS LAI images. Long term trends of vegetation FPC is examined. Decadal variations of vegetated and barely vegetated land are compared. The impacts of extreme precipitation, air temperature and CO2 on the expansion and contraction of barely vegetated and vegetated areas are shown. The study will identify the dominant climate factors in affecting the desert area in the region.

Estimating Vegetation Rainfall Interception Using Remote Sensing Observations at Very High Resolution

NASA Astrophysics Data System (ADS)

Cui, Y.; Zhao, P.; Hong, Y.; Fan, W.; Yan, B.; Xie, H.

2017-12-01

Abstract: As an important compont of evapotranspiration, vegetation rainfall interception is the proportion of gross rainfall that is intercepted, stored and subsequently evaporated from all parts of vegetation during or following rainfall. Accurately quantifying the vegetation rainfall interception at a high resolution is critical for rainfall-runoff modeling and flood forecasting, and is also essential for understanding its further impact on local, regional, and even global water cycle dynamics. In this study, the Remote Sensing-based Gash model (RS-Gash model) is developed based on a modified Gash model for interception loss estimation using remote sensing observations at the regional scale, and has been applied and validated in the upper reach of the Heihe River Basin of China for different types of vegetation. To eliminate the scale error and the effect of mixed pixels, the RS-Gash model is applied at a fine scale of 30 m with the high resolution vegetation area index retrieved by using the unified model of bidirectional reflectance distribution function (BRDF-U) for the vegetation canopy. Field validation shows that the RMSE and R2 of the interception ratio are 3.7% and 0.9, respectively, indicating the model's strong stability and reliability at fine scale. The temporal variation of vegetation rainfall interception loss and its relationship with precipitation are further investigated. In summary, the RS-Gash model has demonstrated its effectiveness and reliability in estimating vegetation rainfall interception. When compared to the coarse resolution results, the application of this model at 30-m fine resolution is necessary to resolve the scaling issues as shown in this study. Keywords: rainfall interception; remote sensing; RS-Gash analytical model; high resolution

Cyberpark 2000: Protected Areas Management Pilot Project. Satellite time series vegetation monitoring

NASA Astrophysics Data System (ADS)

Monteleone, M.; Lanorte, A.; Lasaponara, R.

2009-04-01

Cyberpark 2000 is a project funded by the UE Regional Operating Program of the Apulia Region (2000-2006). The main objective of the Cyberpark 2000 project is to develop a new assessment model for the management and monitoring of protected areas in Foggia Province (Apulia Region) based on Information and Communication Technologies. The results herein described are placed inside the research activities finalized to develop an environmental monitoring system knowledge based on the use of satellite time series. This study include: - A- satellite time series of high spatial resolution data for supporting the analysis of fire static risk factors through land use mapping and spectral/quantitative characterization of vegetation fuels; - B- satellite time series of MODIS for supporting fire dynamic risk evaluation of study area - Integrated fire detection by using thermal imaging cameras placed on panoramic view-points; - C - integrated high spatial and high temporal satellite time series for supporting studies in change detection factors or anomalies in vegetation covers; - D - satellite time-series for monitoring: (i) post fire vegetation recovery and (ii) spatio/temporal vegetation dynamics in unburned and burned vegetation covers.

Interactions and Feedbacks Between Land Surface Processes and Water Cycle Dynamics in Africa

NASA Astrophysics Data System (ADS)

Prince, S. D.; Xue, Y.; Song, G.; Cox, P. M.

2012-12-01

In the past three decades, numerous modeling sensitivity studies have established the importance of detailed vegetation and atmosphere interactions in West African water cycle dynamics. Recently, new evidence has emerged from satellite data analyses that indicate a fully coupled process is needed to explain the relationships discovered in these analyses. In order to elucidate the processes, we have applied the off-line Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID). SSiB4 is a biophysical model based on surface water and energy balance which interacts with TRIFFID by providing the carbon assimilation. TRIFFID is a dynamic vegetation model based on carbon balance. The offline SSiB4/TRIFFID was integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2006 over West Africa. West Africa has diverse climate and ecosystem regions. It suffered the most severe and longest drought in the world during the 20th century, and has the most pronounced decadal water cycle variability in the planet. The simulation results indicate that the water cycle variability has significant effects on the spatial distributions and temporal variations of plant functional types and leaf area index (LAI), which are generally consistent with those observed from satellites since the 1980s. The simulated vegetation conditions over Sahel region exhibited seasonal, inter-annual variations, consistent with West Africa monsoon variability, and the simulated inter-decadal variability in vegetation was consistent with the Sahel drought in the 1970s and 1980s and partial recovery in the 1990s and 2000s. To further understand the cause of decadal variability of climate, water cycle and vegetation dynamics, experiments were conducted to investigate the relationship between the LAI, atmospheric carbon dioxide increase and global warming. In one experiment, the 1948 atmospheric carbon dioxide was used (310 ppmv) and in another it was increased as observed. The LAI increased linearly between the fixed and elevated carbon dioxide, suggesting carbon dioxide fertilization. This increase was related to an increase in shrubs and decrease in C4 grasses. The greatest increases in LAI in the Sahel occurred during the winter. To understand how the warming trend affected decadal variability, we compared an experiment with observed temperature (with warming trend) and another in which the warming trend was removed. The simulations showed a reduction in LAI due to the warming after 1980, although it was not as strong as the carbon fertilization effects. High temperature created stress on vegetation over the Sahel, and especially over its transition zone. However, the fertilization effect dominated the global warming effect.

Calibration of a parsimonious distributed ecohydrological daily model in a data-scarce basin by exclusively using the spatio-temporal variation of NDVI

NASA Astrophysics Data System (ADS)

Ruiz-Pérez, Guiomar; Koch, Julian; Manfreda, Salvatore; Caylor, Kelly; Francés, Félix

2017-12-01

Ecohydrological modeling studies in developing countries, such as sub-Saharan Africa, often face the problem of extensive parametrical requirements and limited available data. Satellite remote sensing data may be able to fill this gap, but require novel methodologies to exploit their spatio-temporal information that could potentially be incorporated into model calibration and validation frameworks. The present study tackles this problem by suggesting an automatic calibration procedure, based on the empirical orthogonal function, for distributed ecohydrological daily models. The procedure is tested with the support of remote sensing data in a data-scarce environment - the upper Ewaso Ngiro river basin in Kenya. In the present application, the TETIS-VEG model is calibrated using only NDVI (Normalized Difference Vegetation Index) data derived from MODIS. The results demonstrate that (1) satellite data of vegetation dynamics can be used to calibrate and validate ecohydrological models in water-controlled and data-scarce regions, (2) the model calibrated using only satellite data is able to reproduce both the spatio-temporal vegetation dynamics and the observed discharge at the outlet and (3) the proposed automatic calibration methodology works satisfactorily and it allows for a straightforward incorporation of spatio-temporal data into the calibration and validation framework of a model.

Responses of the terrestrial carbon cycle to drought: modeling sensitivities of the interactive nitrogen and dynamic vegetation

NASA Astrophysics Data System (ADS)

Jia, B.; Wang, Y.; Xie, Z.

2016-12-01

Drought can trigger both immediate and time-lagged responses of terrestrial ecosystems and even cause sizeable positive feedbacks to climate warming. In this study, the influences of interactive nitrogen (N) and dynamic vegetation (DV) on the response of the carbon cycle in terrestrial ecosystems of China to drought were investigated using the Community Land Model version 4.5 (CLM4.5). Model simulations from three configurations of CLM4.5 (C, carbon cycle only; CN, dynamic carbon and nitrogen cycle; CNDV, dynamic carbon and nitrogen cycle as well as dynamic vegetation) between 1961 and 2010 showed that the incorporation of a prognostic N cycle and DV into CLM4.5 reduce the predicted annual means and inter-annual variability of predicted gross primary production (GPP) and net ecosystem production (NEP), except for a slight increase in NEP for CNDV compared to CN. These model improvements resulted in better agreement with observations (7.0 PgC yr-1) of annual GPP over the terrestrial ecosystems in China for CLM45-CN (7.5 PgC yr-1) and CLM45-CNDV (7.3 PgC yr-1) than for CLM45-C (10.9 PgC yr-1). Compared to the CLM45-C, the carbon-nitrogen coupling strengthened the predicted response of GPP to drought, resulting in a higher correlation with the standardized precipitation index (SPI; rC = 0.62, rCN = 0.67), but led to a weaker sensitivity of NEP to SPI (rC = 0.51, rCN = 0.45). The CLM45-CNDV had the longest lagged responses of GPP to drought among the three configurations. These results enhance our understanding of the response of the terrestrial carbon cycle to drought.

Incorporating Plant Phenology Dynamics in a Biophysical Canopy Model

NASA Technical Reports Server (NTRS)

Barata, Raquel A.; Drewry, Darren

2012-01-01

The Multi-Layer Canopy Model (MLCan) is a vegetation model created to capture plant responses to environmental change. Themodel vertically resolves carbon uptake, water vapor and energy exchange at each canopy level by coupling photosynthesis, stomatal conductance and leaf energy balance. The model is forced by incoming shortwave and longwave radiation, as well as near-surface meteorological conditions. The original formulation of MLCan utilized canopy structural traits derived from observations. This project aims to incorporate a plant phenology scheme within MLCan allowing these structural traits to vary dynamically. In the plant phenology scheme implemented here, plant growth is dependent on environmental conditions such as air temperature and soil moisture. The scheme includes functionality that models plant germination, growth, and senescence. These growth stages dictate the variation in six different vegetative carbon pools: storage, leaves, stem, coarse roots, fine roots, and reproductive. The magnitudes of these carbon pools determine land surface parameters such as leaf area index, canopy height, rooting depth and root water uptake capacity. Coupling this phenology scheme with MLCan allows for a more flexible representation of the structure and function of vegetation as it responds to changing environmental conditions.

Arctic shrubification mediates the impacts of warming climate on changes to tundra vegetation

NASA Astrophysics Data System (ADS)

Mod, Heidi K.; Luoto, Miska

2016-12-01

Climate change has been observed to expand distributions of woody plants in many areas of arctic and alpine environments—a phenomenon called shrubification. New spatial arrangements of shrubs cause further changes in vegetation via changing dynamics of biotic interactions. However, the mediating influence of shrubification is rarely acknowledged in predictions of tundra vegetation change. Here, we examine possible warming-induced landscape-level vegetation changes in a high-latitude environment using species distribution modelling (SDM), specifically concentrating on the impacts of shrubification on ambient vegetation. First, we produced estimates of current shrub and tree cover and forecasts of their expansion under climate change scenarios to be incorporated to SDMs of 116 vascular plants. Second, the predictions of vegetation change based on the models including only abiotic predictors and the models including abiotic, shrub and tree predictors were compared in a representative test area. Based on our model predictions, abundance of woody plants will expand, thus decreasing predicted species richness, amplifying species turnover and increasing the local extinction risk for ambient vegetation. However, the spatial variation demonstrated in our predictions highlights that tundra vegetation can be expected to show a wide variety of different responses to the combined effects of warming and shrubification, depending on the original plant species pool and environmental conditions. We conclude that realistic forecasts of the future require acknowledging the role of shrubification in warming-induced tundra vegetation change.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2.

PubMed

Friend, Andrew D; Lucht, Wolfgang; Rademacher, Tim T; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B; Dankers, Rutger; Falloon, Pete D; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F Ian

2014-03-04

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510-758 ppm of CO2), vegetation carbon increases by 52-477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended.

Carbon residence time dominates uncertainty in terrestrial vegetation responses to future climate and atmospheric CO2

PubMed Central

Friend, Andrew D.; Lucht, Wolfgang; Rademacher, Tim T.; Keribin, Rozenn; Betts, Richard; Cadule, Patricia; Ciais, Philippe; Clark, Douglas B.; Dankers, Rutger; Falloon, Pete D.; Ito, Akihiko; Kahana, Ron; Kleidon, Axel; Lomas, Mark R.; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Peylin, Philippe; Schaphoff, Sibyll; Vuichard, Nicolas; Warszawski, Lila; Wiltshire, Andy; Woodward, F. Ian

2014-01-01

Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models. For example, at 4 °C of global land surface warming (510–758 ppm of CO2), vegetation carbon increases by 52–477 Pg C (224 Pg C mean), mainly due to CO2 fertilization of photosynthesis. Simulations agree on large regional increases across much of the boreal forest, western Amazonia, central Africa, western China, and southeast Asia, with reductions across southwestern North America, central South America, southern Mediterranean areas, southwestern Africa, and southwestern Australia. Four vegetation models display discontinuities across 4 °C of warming, indicating global thresholds in the balance of positive and negative influences on productivity and biomass. In contrast to previous global vegetation model studies, we emphasize the importance of uncertainties in projected changes in carbon residence times. We find, when all seven models are considered for one representative concentration pathway × general circulation model combination, such uncertainties explain 30% more variation in modeled vegetation carbon change than responses of net primary productivity alone, increasing to 151% for non-HYBRID4 models. A change in research priorities away from production and toward structural dynamics and demographic processes is recommended. PMID:24344265

Quantifying Grassland-to-Woodland Transitions and the Implications for Carbon and Nitrogen Dynamics in the Southwest United States

NASA Technical Reports Server (NTRS)

Wessman, Carol A.; Archer, Steven R.; Asner, Gregory P.; Bateson, C. Ann

2004-01-01

Replacement of grasslands and savannas by shrublands and woodlands has been widely reported in tropical, temperate and high-latitude rangelands worldwide (Archer 1994). These changes in vegetation structure may reflect historical shifts in climate and land use; and are likely to influence biodiversity, productivity, above- and below ground carbon and nitrogen sequestration and biophysical aspects of land surface-atmosphere interactions. The goal of our proposed research is to investigate how changes in the relative abundance of herbaceous and woody vegetation affect carbon and nitrogen dynamics across heterogeneous savannas and shrub/woodlands. By linking actual land-cover composition (derived through spectral mixture analysis of AVIRIS, TM, and AVHRR imagery) with a process-based ecosystem model, we will generate explicit predictions of the C and N storage in plants and soils resulting from changes in vegetation structure. Our specific objectives will be to (1) continue development and test applications of spectral mixture analysis across grassland-to-woodland transitions; (2) quantify temporal changes in plant and soil C and N storage and turnover for remote sensing and process model parameterization and verification; and (3) couple landscape fraction maps to an ecosystem simulation model to observe biogeochemical dynamics under changing landscape structure and climatological forcings.

Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?

USGS Publications Warehouse

McKenzie, Donald; Littell, Jeremy

2017-01-01

Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong, such as mesic and arid forests and shrublands with substantial biomass such as chaparral. We examine the drought–fire relationship, specifically the correlations between water-balance deficit and annual area burned, across the full gradient of deficit in the western USA, from temperate rainforest to desert. In the middle of this gradient, conditional on vegetation (fuels), correlations are strong, but outside this range the equivalence hotter and drier equals more fire either breaks down or is contingent on other factors such as previous-year climate. This suggests that the regional drought–fire dynamic will not be stationary in future climate, nor will other more complex contingencies associated with the variation in fire extent. Predictions of future wildfire area therefore need to consider not only vegetation changes, as some dynamic vegetation models now do, but also potential changes in the drought–fire dynamic that will ensue in a warming climate.

Climate change and the eco-hydrology of fire: Will area burned increase in a warming western USA?

PubMed

McKenzie, Donald; Littell, Jeremy S

2017-01-01

Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong, such as mesic and arid forests and shrublands with substantial biomass such as chaparral. We examine the drought-fire relationship, specifically the correlations between water-balance deficit and annual area burned, across the full gradient of deficit in the western USA, from temperate rainforest to desert. In the middle of this gradient, conditional on vegetation (fuels), correlations are strong, but outside this range the equivalence hotter and drier equals more fire either breaks down or is contingent on other factors such as previous-year climate. This suggests that the regional drought-fire dynamic will not be stationary in future climate, nor will other more complex contingencies associated with the variation in fire extent. Predictions of future wildfire area therefore need to consider not only vegetation changes, as some dynamic vegetation models now do, but also potential changes in the drought-fire dynamic that will ensue in a warming climate. © 2016 by the Ecological Society of America.

The contribution of brown vegetation to vegetation dynamics

USDA-ARS?s Scientific Manuscript database

Indices of vegetation dynamics that include both green vegetation (GV) and non-photosynthetic vegetation (NPV), that is, brown vegetation, were applied to MODIS surface reflectance data from 2000 to 2006 for the southwestern United States. These indices reveal that the cover of NPV, a measure of veg...

Comparison of water-use efficiency estimates based on tree-ring carbon isotopes with simulations of a dynamic vegetation model

NASA Astrophysics Data System (ADS)

Saurer, Matthias; Renato, Spahni; Fortunat, Joos; David, Frank; Kerstin, Treydte; Rolf, Siegwolf

2015-04-01

Tree-ring d13C-based estimates of intrinsic water-use efficiency (iWUE, reflecting the ratio of assimilation A to stomatal conductance gs) generally show a strong increase during the industrial period, likely associated with the increase in atmospheric CO2. However, it is not clear, first, if tree-ring d13C-derived iWUE-values indeed reflect actual plant and ecosystem-scale variability in fluxes and, second, what physiological changes were the drivers of the observed iWUE increase, changes in A or gs or both. To address these questions, we used a complex dynamic vegetation model (LPX) that combines process-based vegetation dynamics with land-atmosphere carbon and water exchange. The analysis was conducted for three functional types, representing conifers, oaks, larch, and various sites in Europe, where tree-ring isotope data are available. The increase in iWUE over the 20th century was comparable in LPX-simulations as in tree-ring-estimates, strengthening confidence in these results. Furthermore, the results from the LPX model suggest that the cause of the iWUE increase was reduced stomatal conductance during recent decades rather than increased assimilation. High-frequency variation reflects the influence of climate, like for example the 1976 summer drought, resulting in strongly reduced A and g in the model, particularly for oak.

Towards a physically-based multi-scale ecohydrological simulator for semi-arid regions

NASA Astrophysics Data System (ADS)

Caviedes-Voullième, Daniel; Josefik, Zoltan; Hinz, Christoph

2017-04-01

The use of numerical models as tools for describing and understanding complex ecohydrological systems has enabled to test hypothesis and propose fundamental, process-based explanations of the system system behaviour as a whole as well as its internal dynamics. Reaction-diffusion equations have been used to describe and generate organized pattern such as bands, spots, and labyrinths using simple feedback mechanisms and boundary conditions. Alternatively, pattern-matching cellular automaton models have been used to generate vegetation self-organization in arid and semi-arid regions also using simple description of surface hydrological processes. A key question is: How much physical realism is needed in order to adequately capture the pattern formation processes in semi-arid regions while reliably representing the water balance dynamics at the relevant time scales? In fact, redistribution of water by surface runoff at the hillslope scale occurs at temporal resolution of minutes while the vegetation development requires much lower temporal resolution and longer times spans. This generates a fundamental spatio-temporal multi-scale problem to be solved, for which high resolution rainfall and surface topography are required. Accordingly, the objective of this contribution is to provide proof-of-concept that governing processes can be described numerically at those multiple scales. The requirements for a simulating ecohydrological processes and pattern formation with increased physical realism are, amongst others: i. high resolution rainfall that adequately captures the triggers of growth as vegetation dynamics of arid regions respond as pulsed systems. ii. complex, natural topography in order to accurately model drainage patterns, as surface water redistribution is highly sensitive to topographic features. iii. microtopography and hydraulic roughness, as small scale variations do impact on large scale hillslope behaviour iv. moisture dependent infiltration as temporal dynamics of infiltration affects water storage under vegetation and in bare soil Despite the volume of research in this field, fundamental limitations still exist in the models regarding the aforementioned issues. Topography and hydrodynamics have been strongly simplified. Infiltration has been modelled as dependent on depth but independent of soil moisture. Temporal rainfall variability has only been addressed for seasonal rain. Spatial heterogenity of the topography as well as roughness and infiltration properties, has not been fully and explicitly represented. We hypothesize that physical processes must be robustly modelled and the drivers of complexity must be present with as much resolution as possible in order to provide the necessary realism to improve transient simulations, perhaps leading the way to virtual laboratories and, arguably, predictive tools. This work provides a first approach into a model with explicit hydrological processes represented by physically-based hydrodynamic models, coupled with well-accepted vegetation models. The model aims to enable new possibilities relating to spatiotemporal variability, arbitrary topography and representation of spatial heterogeneity, including sub-daily (in fact, arbitrary) temporal variability of rain as the main forcing of the model, explicit representation of infiltration processes, and various feedback mechanisms between the hydrodynamics and the vegetation. Preliminary testing strongly suggests that the model is viable, has the potential of producing new information of internal dynamics of the system, and allows to successfully aggregate many of the sources of complexity. Initial benchmarking of the model also reveals strengths to be exploited, thus providing an interesting research outlook, as well as weaknesses to be addressed in the immediate future.

PREDICTION OF PEROMYSCUS MANICULATUS (DEER MOUSE) POPULATION DYNAMICS IN MONTANA, USA, USING SATELLITE-DRIVEN VEGETATION PRODUCTIVITY AND WEATHER DATA

PubMed Central

Loehman, Rachel A.; Elias, Joran; Douglass, Richard J.; Kuenzi, Amy J.; Mills, James N.; Wagoner, Kent

2013-01-01

Deer mice (Peromyscus maniculatus) are the main reservoir host for Sin Nombre virus, the primary etiologic agent of hantavirus pulmonary syndrome in North America. Sequential changes in weather and plant productivity (trophic cascades) have been noted as likely catalysts of deer mouse population irruptions, and monitoring and modeling of these phenomena may allow for development of early-warning systems for disease risk. Relationships among weather variables, satellite-derived vegetation productivity, and deer mouse populations were examined for a grassland site east of the Continental Divide and a sage-steppe site west of the Continental Divide in Montana, USA. We acquired monthly deer mouse population data for mid-1994 through 2007 from long-term study sites maintained for monitoring changes in hantavirus reservoir populations, and we compared these with monthly bioclimatology data from the same period and gross primary productivity data from the Moderate Resolution Imaging Spectroradiometer sensor for 2000–06. We used the Random Forests statistical learning technique to fit a series of predictive models based on temperature, precipitation, and vegetation productivity variables. Although we attempted several iterations of models, including incorporating lag effects and classifying rodent density by seasonal thresholds, our results showed no ability to predict rodent populations using vegetation productivity or weather data. We concluded that trophic cascade connections to rodent population levels may be weaker than originally supposed, may be specific to only certain climatic regions, or may not be detectable using remotely sensed vegetation productivity measures, although weather patterns and vegetation dynamics were positively correlated. PMID:22493110

Utility of an image-based canopy reflectance modeling tool for remote estimation and LAI and leaf chlorophyll content at regional scales

USDA-ARS?s Scientific Manuscript database

Radiance data recorded by remote sensors function as a unique source for monitoring the terrestrial biosphere and vegetation dynamics at a range of spatial and temporal scales. A key challenge is to relate the remote sensing signal to critical variables describing land surface vegetation canopies su...

Vegetation-climate feedback causes reduced precipitation in CMIP5 regional Earth system model simulation over Africa

NASA Astrophysics Data System (ADS)

Wu, Minchao; Smith, Benjamin; Schurgers, Guy; Lindström, Joe; Rummukainen, Markku; Samuelsson, Patrick

2013-04-01

Terrestrial ecosystems have been demonstrated to play a significant role within the climate system, amplifying or dampening climate change via biogeophysical and biogeochemical exchange with the atmosphere and vice versa (Cox et al. 2000; Betts et al. 2004). Africa is particularly vulnerable to climate change and studies of vegetation-climate feedback mechanisms on Africa are still limited. Our study is the first application of A coupled Earth system model at regional scale and resolution over Africa. We applied a coupled regional climate-vegetation model, RCA-GUESS (Smith et al. 2011), over the CORDEX Africa domain, forced by boundary conditions from a CanESM2 CMIP5 simulation under the RCP8.5 future climate scenario. The simulations were from 1961 to 2100 and covered the African continent at a horizontal grid spacing of 0.44°. RCA-GUESS simulates changes in the phenology, productivity, relative cover and population structure of up to eight plant function types (PFTs) in response to forcing from the climate part of the model. These vegetation changes feedback to simulated climate through dynamic adjustments in surface energy fluxes and surface properties. Changes in the net ecosystem-atmosphere carbon flux and its components net primary production (NPP), heterotrophic respiration and emissions from biomass burning were also simulated but do not feedback to climate in our model. Constant land cover was assumed. We compared simulations with and without vegetation feedback switched "on" to assess the influence of vegetation-climate feedback on simulated climate, vegetation and ecosystem carbon cycling. Both positive and negative warming feedbacks were identified in different parts of Africa. In the Sahel savannah zone near 15°N, reduced vegetation cover and productivity, and mortality caused by a deterioration of soil water conditions led to a positive warming feedback mediated by decreased evapotranspiration and increased sensible heat flux between vegetation and the atmosphere. In the equatorial rainforest stronghold region of central Africa, a feedback syndrome characterised by reduced plant production and LAI, a dominance shift from tropical trees to grasses, reduced soil water and reduced rainfall was identified. The likely underlying mechanism was a decline in evaporative water recycling associated with sparser vegetation cover, reminiscent of Earth system model studies in which a similar feedback mechanism was simulated to force dieback of tropical rainforest and reduced precipitation over the Amazon Basin (Cox et al. 2000; Betts et al. 2004; Malhi et al. 2009). Opposite effects are seen in southern Senegal, southern Mali, northern Guinea and Guinea-Bissau, positive evapotranspiration feedback enhancing the cover of trees in forest and savannah, mitigating warming and promoting local moisture recycling as rainfall. We reveal that LAI-driven evapotranspiration feedback may reduced rainfall in parts of Africa, vegetation-climate feedbacks may significantly impact the magnitude and character of simulated changes in climate as well as vegetation and ecosystems in future scenario studies of this region. They should be accounted for in future studies of climate change and its impacts on Africa. Keywords: vegetation-climate feedback, regional climate model, evapotranspiration, CORDEX. References: Betts, R.A., Cox, P.M., Collins, M., Harris, P.P., Huntingford, C. & Jones, C.D. 2004. The role of ecosystem-atmosphere interactions in simulated Amazonian precipitation decrease and forest dieback under global climate warming. Theoretical and Applied Climatology 78: 157-175. Cox, P.M., Betts, R.A., Jones, C.D., Spall, S.A. & Totterdell, I.J. 2000. Acceleration of global warming due to carbon-cycle feedbacks in a coupled climate model. Nature 408: 184-187. Samuelsson, P., Jones, C., Wilĺen, U., Gollvik, S., Hansson, U. and coauthors. 2011. The Rossby Centre Regional Climate Model RCA3:Model description and performance. Tellus 63A, 4-23. Smith, B., Prentice, I. C. and Sykes, M. T. 2001. Representation of vegetation dynamics in modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space. Global Ecol. Biogeog. 10, 621-637 Smith, B., Samuelsson, P., Wramneby, A. & Rummukainen, M. 2011. A model of the coupled dynamics of climate, vegetation and terrestrial ecosystem biogeochemistry for regional applications. Tellus 63A: 87-106.

Riparian vegetation controls on the hydraulic geometry of streams

NASA Astrophysics Data System (ADS)

McBride, M.

2010-12-01

A synthesis of field measurements, remote observations, and numerical modeling techniques highlights the significance of riparian vegetation in determining the geometry of streams and impacting sediment transport dynamics in temperate, Piedmont regions. Specifically, forested and grassy riparian vegetation establish streams with significantly different widths and with different timescales for attaining a state of dynamic equilibrium. The interactions between riparian vegetation, channel form, and channel dynamics are scale dependent. Scale dependency arises because of variations in ratios of vegetation length scales and geomorphic scales (e.g., channel width and depth). Stream reaches with grassy vegetation experience more frequent overbank discharges, migrate more quickly, and exhibit a more classic dynamic equilibrium than forested reaches. These phenomena are relevant to current watershed management efforts that aim to reduce sediment and nutrient loads to receiving water bodies, such as the Chesapeake Bay. The reforestation of riparian buffers is a common restoration technique that intends to improve water quality, temperature regimes, and in-stream physical habitat. Passive reforestation of riparian areas along a tributary to Sleepers River in Danville, VT, USA caused an increase in channel width and cross-sectional area over a 40-year period. From a comparison of historical records and current cross-sectional dimensions, the channel widening resulted in the mobilization of approximately 85 kg/ha/yr of floodplain sediments. Long-term monitoring of suspended sediments in an adjacent watershed indicates that this sediment source may account for roughly 40 percent of the total suspended sediment load. In some instances, increased sediment loads associated with channel widening may be an unforeseen consequence that compromises riparian restoration efforts.

[Study on the nutrition of alpine meadow based on hyperspectral data].

PubMed

Wang, Xun; Liu, Shu-Jie; Jia, Hai-Feng; Chai, Sha-Tuo; Dang, An-Rong; Liu, Xue-Hua; Hao, Li-Zhuang; Cui, Zhan-Hong

2012-10-01

Remote sensing monitoring of alpine grassland nutritional status is a key factor of grassland reasonable utilization, also a difficulty for dynamic vegetation monitoring. The present paper studies the correlations between vegetation nutrition and hyperspectral data. The results showed that two band ratio models have a significant correlation with biomass, air-DM, P, CF, and CP. MAXR models have a significant correlation with most of nutrition index when selected wavebands equaled five. On the whole, the MAXR model precedes two band ratio models. Using MAXR models to estimate air-DM, P and CF can obtain higher accuracy.

A field study on the dynamic uptake and transfer of heavy metals in Chinese cabbage and radish in weak alkaline soils.

PubMed

Ai, Shiwei; Guo, Rui; Liu, Bailin; Ren, Liang; Naeem, Sajid; Zhang, Wenya; Zhang, Yingmei

2016-10-01

Vegetables and crops can take up heavy metals when grown on polluted lands. The concentrations and dynamic uptake of heavy metals vary at different growth points for different vegetables. In order to assess the safe consumption of vegetables in weak alkaline farmlands, Chinese cabbage and radish were planted on the farmlands of Baiyin (polluted site) and Liujiaxia (relatively unpolluted site). Firstly, the growth processes of two vegetables were recorded. The growth curves of the two vegetables observed a slow growth at the beginning, an exponential growth period, and a plateau towards the end. Maximum concentrations of copper (Cu), zinc (Zn), lead (Pb), and cadmium (Cd) were presented at the slow growth period and showed a downtrend except the radish shoot. The concentrations of heavy metals (Cu, Zn, and Cd) in vegetables of Baiyin were higher than those of Liujiaxia. In the meanwhile, the uptake contents continued to increase during the growth or halted at maximum at a certain stage. The maximum uptake rates were found on the maturity except for the shoot of radish which took place at the exponential growth stages of root. The sigmoid model could simulate the dynamic processes of growth and heavy metals uptake of Chinese cabbage and radish. Conclusively, heavy metals have higher bioaccumulation tendency for roots in Chinese cabbage and for shoots in radish.

Plant functional coexistence and influence on the eco-hydrologic response of semiarid hillslopes

NASA Astrophysics Data System (ADS)

Soltanjalili, Mohammadjafar; Saco, Patricia M.; Willgoose, Garry

2016-04-01

Through its influence on rainfall-runoff and erosion-deposition processes, vegetation remarkably regulates different aspects of landscape processes. Here, the influence of different plant functional dynamics on the coexistence of different species in arid and semi-arid regions with banded vegetation patterns is investigated. Simulations capture the coevolution and coexistence of two different species interacting with hydrology in hillslopes with gentle slopes. The dynamic vegetation model simulates the dynamics of overland runoff, soil moisture, facilitation mechanisms (evaporation reduction through shading and enhanced infiltration by vegetation), local and non-local seed dispersal, competition through water uptake and changes in the biomass of the two species. Here for simplicity the two species are assumed to use water from the same soil depth. Results of the coexistence of the two species capture differences in facilitation-competition interactions caused by specific types of vegetation with varying hydrologic traits. The results illustrate that the dominance of facilitation or competition feedbacks which determine either the coexistence of the two species or survival of only one of them strongly depends on the characteristics and hydrologic traits of the coexisting species and the severity of water stresses. We therefore argue that our results should stimulate further research into the role of interspecific and intraspecific feedbacks between different plant species and specifically the influence of the resulting vegetation community on landform evolution processes.

Multiple mechanisms of Amazonian forest biomass losses in three dynamic global vegetation models under climate change.

PubMed

Galbraith, David; Levy, Peter E; Sitch, Stephen; Huntingford, Chris; Cox, Peter; Williams, Mathew; Meir, Patrick

2010-08-01

*The large-scale loss of Amazonian rainforest under some future climate scenarios has generally been considered to be driven by increased drying over Amazonia predicted by some general circulation models (GCMs). However, the importance of rainfall relative to other drivers has never been formally examined. *Here, we conducted factorial simulations to ascertain the contributions of four environmental drivers (precipitation, temperature, humidity and CO(2)) to simulated changes in Amazonian vegetation carbon (C(veg)), in three dynamic global vegetation models (DGVMs) forced with climate data based on HadCM3 for four SRES scenarios. *Increased temperature was found to be more important than precipitation reduction in causing losses of Amazonian C(veg) in two DGVMs (Hyland and TRIFFID), and as important as precipitation reduction in a third DGVM (LPJ). Increases in plant respiration, direct declines in photosynthesis and increases in vapour pressure deficit (VPD) all contributed to reduce C(veg) under high temperature, but the contribution of each mechanism varied greatly across models. Rising CO(2) mitigated much of the climate-driven biomass losses in the models. *Additional work is required to constrain model behaviour with experimental data under conditions of high temperature and drought. Current models may be overly sensitive to long-term elevated temperatures as they do not account for physiological acclimation.

Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland

NASA Astrophysics Data System (ADS)

Cerasoli, Sofia; Costa e Silva, Filipe; Silva, João M. N.

2016-06-01

The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus ( Cistus salviifolius) and ulex ( Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence ( ΔF/ Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

Temporal dynamics of spectral bioindicators evidence biological and ecological differences among functional types in a cork oak open woodland.

PubMed

Cerasoli, Sofia; Costa E Silva, Filipe; Silva, João M N

2016-06-01

The application of spectral vegetation indices for the purpose of vegetation monitoring and modeling increased largely in recent years. Nonetheless, the interpretation of biophysical properties of vegetation through their spectral signature is still a challenging task. This is particularly true in Mediterranean oak forest characterized by a high spatial and temporal heterogeneity. In this study, the temporal dynamics of vegetation indices expected to be related with green biomass and photosynthetic efficiency were compared for the canopy of trees, the herbaceous layer, and two shrub species: cistus (Cistus salviifolius) and ulex (Ulex airensis). coexisting in a cork oak woodland. All indices were calculated from in situ measurements with a FieldSpec3 spectroradiometer (ASD Inc., Boulder, USA). Large differences emerged in the temporal trends and in the correlation between climate and vegetation indices. The relationship between spectral indices and temperature, radiation, and vapor pressure deficit for cork oak was opposite to that observed for the herbaceous layer and cistus. No correlation was observed between rainfall and vegetation indices in cork oak and ulex, but in the herbaceous layer and in the cistus, significant correlations were found. The analysis of spectral vegetation indices with fraction of absorbed PAR (fPAR) and quantum yield of chlorophyll fluorescence (ΔF/Fm') evidenced strongest relationships with the indices Normalized Difference Water Index (NDWI) and Photochemical Reflectance Index (PRI)512, respectively. Our results, while confirms the ability of spectral vegetation indices to represent temporal dynamics of biophysical properties of vegetation, evidence the importance to consider ecosystem composition for a correct ecological interpretation of results when the spatial resolution of observations includes different plant functional types.

Effects of Emergent Vegetation on Sediment Dynamics within a Retreating Coastal Marshland

NASA Astrophysics Data System (ADS)

Stellern, C.; Grossman, E.; Fuller, R.; Wallin, D.; Linneman, S. R.

2015-12-01

Coastal emergent vegetation in estuaries physically interrupts flow within the water column, reduces wave energy and increases sediment deposition. Previous workers conclude that wave attenuation rates decrease exponentially with distance from the marsh edge and are dependent on site and species-specific plant characteristics (Yang et al., 2011). Sediment deposition may exhibit similar patterns; however, sediment, geomorphic and habitat models seldom integrate site-specific biophysical plant parameters into change analyses. We paired vegetation and sediment dynamic studies to: (1) characterize vegetation structure, (2) estimate sediment available for deposition, (3) estimate rate, distribution and composition of sediment deposits, (4) determine sediment accumulation on vegetation, (5) compare sediment deposition within dense tidal wetland relative to non-vegetated tidal flat. These studies integrate a variety of monitoring methods, including the use of sediment traps, turbidity sensors, side-on photographs of vegetation and remote sensing image analysis. We compared sedimentation data with vegetation characteristics and spatial distribution data to examine the relative role of vegetation morphologic traits (species, stem density, biomass, distribution, tidal channels, etc.) on sediment dynamics. Our study is focused on Port Susan Bay of Washington State; a protected delta that has experienced up to 1 kilometer of marsh retreat (loss) over the past fifty years. Preliminary results show that the highest winter deposition occurred in the high marsh/mid-marsh boundary, up to 300m inland of the marsh edge, where bulrush species are most dense. These results will inform restoration efforts aimed at reestablishing sediment supply to the retreating marshland. This research is necessary to understand the vulnerability and adaptability of coastal marshlands to climate change related stressors such as, increased water levels (sea-level rise) and wave energy.

Ecohydrological implications of aeolian sediment trapping by sparse vegetation in drylands

USGS Publications Warehouse

Gonzales, Howell B.; Ravi, Sujith; Li, Junran; Sankey, Joel B.

2018-01-01

Aeolian processes are important drivers of ecosystem dynamics in drylands, and important feedbacks exist among aeolian – hydrological processes and vegetation. The trapping of wind-borne sediments by vegetation may result in changes in soil properties beneath the vegetation, which, in turn, can alter hydrological and biogeochemical processes. Despite the relevance of aeolian transport to ecosystem dynamics, the interactions between aeolian transport and vegetation in shaping dryland landscapes where sediment distribution is altered by relatively rapid changes in vegetation composition such as shrub encroachment, is not well understood. Here, we used a computational fluid dynamics (CFD) modeling framework to investigate the sediment trapping efficiencies of vegetation canopies commonly found in a shrub-grass ecotone in the Chihuahuan Desert (New Mexico, USA) and related the results to spatial heterogeneity in soil texture and infiltration measured in the field. A CFD open-source software package was used to simulate aeolian sediment movement through three-dimensional architectural depictions of Creosote shrub (Larrea tridentata) and Black Grama grass (Bouteloua eriopoda) vegetation types. The vegetation structures were created using a computer-aided design software (Blender), with inherent canopy porosities, which were derived using LIDAR (Light Detection and Ranging) measurements of plant canopies. Results show that considerable heterogeneity in infiltration and soil grain size distribution exist between the microsites, with higher infiltration and coarser soil texture under shrubs. Numerical simulations also indicate that the differential trapping of canopies might contribute to the observed heterogeneity in soil texture. In the early stages of encroachment, the shrub canopies, by trapping coarser particles more efficiently, might maintain higher infiltration rates leading to faster development of the microsites (among other factors) with enhanced ecological productivity, which might provide positive feedbacks to shrub encroachment.

Incorporating food web dynamics into ecological restoration: A modeling approach for river ecosystems

USGS Publications Warehouse

Bellmore, J. Ryan; Benjamin, Joseph R.; Newsom, Michael; Bountry, Jennifer A.; Dombroski, Daniel

2017-01-01

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration planning we constructed a model that links river food web dynamics to in-stream physical habitat and riparian vegetation conditions. We present an application of the model to the Methow River, Washington (USA), a location of on-going restoration aimed at recovering salmon. Three restoration strategies were simulated: riparian vegetation restoration, nutrient augmentation via salmon carcass addition, and side-channel reconnection. We also added populations of nonnative aquatic snails and fish to the modeled food web to explore how changes in food web structure mediate responses to restoration. Simulations suggest that side-channel reconnection may be a better strategy than carcass addition and vegetation planting for improving conditions for salmon in this river segment. However, modeled responses were strongly sensitive to changes in the structure of the food web. The addition of nonnative snails and fish modified pathways of energy through the food web, which negated restoration improvements. This finding illustrates that forecasting responses to restoration may require accounting for the structure of food webs, and that changes in this structure—as might be expected with the spread of invasive species—could compromise restoration outcomes. Unlike habitat-based approaches to restoration assessment that focus on the direct effects of physical habitat conditions on single species of interest, our approach dynamically links the success of target organisms to the success of competitors, predators, and prey. By elucidating the direct and indirect pathways by which restoration affects target species, dynamic food web models can improve restoration planning by fostering a deeper understanding of system connectedness and dynamics.

Floodplain Vegetation Dynamics Modeling Using Coupled RiPCAS-DFLOW (CoRD): Jemez Canyon, Jemez River, New Mexico

NASA Astrophysics Data System (ADS)

Miller, S. J.; Gregory, A. E.; Turner, M. A.; Chaulagain, S.; Cadol, D.; Stone, M. C.; Sheneman, L.

2017-12-01

Interactions among precipitation, vegetation, soil moisture, runoff and other landscape properties set the stage for complex streamflow regimes and cascading riparian habitat impacts, particularly in semi-arid regions. A consortium of New Mexico, Nevada, and Idaho, funded through NSF-EPSCoR, has promulgated the Western Consortium for Watershed Analysis, Visualization, and Exploration (WC-WAVE). Two WC-WAVE objectives are to advance understanding of hydrologic interactions and ecosystem services, and to develop a virtual watershed platform (VWP) cyber-infrastructure to unite and streamline coordination among teams, databases and modeling tools. To provide proof of concept for the VWP and to study coevolution of riparian habitat mosaics and flood dynamics, the study team selected two models and developed a model coupling system for the Jemez River Canyon, Jemez River, NM. DFLOW is a 2-D hydrodynamic model for steady and unsteady flow conditions; the Riparian Community Alteration and Succession (RipCAS) model, developed using concepts from a vegetation disturbance and succession model (CASiMiR), uses shear stresses and flood depths from DFLOW to evolve riparian vegetation maps with associated roughness. The Coupled RipCAS-DFLOW (CoRD) model allows serial annual time step feedback of changes in peak-flow-derived depth and shear stress and vegetation-derived roughness values. An intuitive command-line interface on a computing cluster is used to call CoRD, which provides commands to calculate boundary conditions, perform multiple file and data format conversions and archive and compress decades of data. Four thirty-year synthetic annual maximum flood scenarios were selected for CoRD simulations, representing a historical wet period (1957-1986) a historical dry period (1986-2015), and flows doubling the historical wet period and halving the historical dry period. Event-driven coupled modeling simulates the spatial distribution of floodplain vegetation community evolution over decades of flood record. Implications for riparian habitat distribution patterns under changing streamflow regimes due to increased fire and climate change, shifting landuse and livestock access patterns, and management of invasive exotic species are considered in interpreting experimental model scenarios.

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China)

PubMed Central

Liu, Xiaojun; Ferguson, Richard B.; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-01-01

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI=(1+e−15.2829×(RAGDDi−0.1944))−1−(1+e−11.6517×(RAGDDi−1.0267))−1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status. PMID:28338637

Using an Active-Optical Sensor to Develop an Optimal NDVI Dynamic Model for High-Yield Rice Production (Yangtze, China).

PubMed

Liu, Xiaojun; Ferguson, Richard B; Zheng, Hengbiao; Cao, Qiang; Tian, Yongchao; Cao, Weixing; Zhu, Yan

2017-03-24

The successful development of an optimal canopy vegetation index dynamic model for obtaining higher yield can offer a technical approach for real-time and nondestructive diagnosis of rice (Oryza sativa L) growth and nitrogen (N) nutrition status. In this study, multiple rice cultivars and N treatments of experimental plots were carried out to obtain: normalized difference vegetation index (NDVI), leaf area index (LAI), above-ground dry matter (DM), and grain yield (GY) data. The quantitative relationships between NDVI and these growth indices (e.g., LAI, DM and GY) were analyzed, showing positive correlations. Using the normalized modeling method, an appropriate NDVI simulation model of rice was established based on the normalized NDVI (RNDVI) and relative accumulative growing degree days (RAGDD). The NDVI dynamic model for high-yield production in rice can be expressed by a double logistic model: RNDVI = ( 1 + e - 15.2829 × ( R A G D D i - 0.1944 ) ) - 1 - ( 1 + e - 11.6517 × ( R A G D D i - 1.0267 ) ) - 1 (R2 = 0.8577**), which can be used to accurately predict canopy NDVI dynamic changes during the entire growth period. Considering variation among rice cultivars, we constructed two relative NDVI (RNDVI) dynamic models for Japonica and Indica rice types, with R2 reaching 0.8764** and 0.8874**, respectively. Furthermore, independent experimental data were used to validate the RNDVI dynamic models. The results showed that during the entire growth period, the accuracy (k), precision (R2), and standard deviation of RNDVI dynamic models for the Japonica and Indica cultivars were 0.9991, 1.0170; 0.9084**, 0.8030**; and 0.0232, 0.0170, respectively. These results indicated that RNDVI dynamic models could accurately reflect crop growth and predict dynamic changes in high-yield crop populations, providing a rapid approach for monitoring rice growth status.

Landscape matrix mediates occupancy dynamics of Neotropical avian insectivores

USGS Publications Warehouse

Kennedy, Christina M.; Campbell Grant, Evan H.; Neel, Maile C.; Fagan, William F.; Marpa, Peter P.

2011-01-01

In addition to patch-level attributes (i.e., area and isolation), the nature of land cover between habitat patches (the matrix) may drive colonization and extinction dynamics in fragmented landscapes. Despite a long-standing recognition of matrix effects in fragmented systems, an understanding of the relative impacts of different types of land cover on patterns and dynamics of species occurrence remains limited. We employed multi-season occupancy models to determine the relative influence of patch area, patch isolation, within-patch vegetation structure, and landscape matrix on occupancy dynamics of nine Neotropical nsectivorous birds in 99 forest patches embedded in four matrix types (agriculture, suburban evelopment, bauxite mining, and forest) in central Jamaica. We found that within-patch vegetation structure and the matrix type between patches were more important than patch area and patch isolation in determining local colonization and local extinction probabilities, and that the effects of patch area, isolation, and vegetation structure on occupancy dynamics tended to be matrix and species dependent. Across the avian community, the landscape matrix influenced local extinction more than local colonization, indicating that extinction processes, rather than movement, likely drive interspecific differences in occupancy dynamics. These findings lend crucial empirical support to the hypothesis that species occupancy dynamics in fragmented systems may depend greatly upon the landscape context.

Spectral wave dissipation by submerged aquatic vegetation in a back-barrier estuary

USGS Publications Warehouse

Nowacki, Daniel J.; Beudin, Alexis; Ganju, Neil K.

2017-01-01

Submerged aquatic vegetation is generally thought to attenuate waves, but this interaction remains poorly characterized in shallow-water field settings with locally generated wind waves. Better quantification of wave–vegetation interaction can provide insight to morphodynamic changes in a variety of environments and also is relevant to the planning of nature-based coastal protection measures. Toward that end, an instrumented transect was deployed across a Zostera marina (common eelgrass) meadow in Chincoteague Bay, Maryland/Virginia, U.S.A., to characterize wind-wave transformation within the vegetated region. Field observations revealed wave-height reduction, wave-period transformation, and wave-energy dissipation with distance into the meadow, and the data informed and calibrated a spectral wave model of the study area. The field observations and model results agreed well when local wind forcing and vegetation-induced drag were included in the model, either explicitly as rigid vegetation elements or implicitly as large bed-roughness values. Mean modeled parameters were similar for both the explicit and implicit approaches, but the spectral performance of the explicit approach was poor compared to the implicit approach. The explicit approach over-predicted low-frequency energy within the meadow because the vegetation scheme determines dissipation using mean wavenumber and frequency, in contrast to the bed-friction formulations, which dissipate energy in a variable fashion across frequency bands. Regardless of the vegetation scheme used, vegetation was the most important component of wave dissipation within much of the study area. These results help to quantify the influence of submerged aquatic vegetation on wave dynamics in future model parameterizations, field efforts, and coastal-protection measures.

Analysis of terrestrial conditions and dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N. (Principal Investigator)

1984-01-01

Land spectral reflectance properties for selected locations, including the Goddard Space Flight Center, the Wallops Flight Facility, a MLA test site in Cambridge, Maryland, and an acid test site in Burlington, Vermont, were measured. Methods to simulate the bidirectional reflectance properties of vegetated landscapes and a data base for spatial resolution were developed. North American vegetation patterns observed with the Advanced Very High Resolution Radiometer were assessed. Data and methods needed to model large-scale vegetation activity with remotely sensed observations and climate data were compiled.

Quantifying the effects of land use and climate on Holocene vegetation in Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph M.; Jönsson, Anna Maria; Smith, Benjamin; Kaplan, Jed O.; Alenius, Teija; Birks, H. John B.; Bjune, Anne E.; Christiansen, Jörg; Dodson, John; Edwards, Kevin J.; Giesecke, Thomas; Herzschuh, Ulrike; Kangur, Mihkel; Koff, Tiiu; Latałowa, Małgorzata; Lechterbeck, Jutta; Olofsson, Jörgen; Seppä, Heikki

2017-09-01

Early agriculture can be detected in palaeovegetation records, but quantification of the relative importance of climate and land use in influencing regional vegetation composition since the onset of agriculture is a topic that is rarely addressed. We present a novel approach that combines pollen-based REVEALS estimates of plant cover with climate, anthropogenic land-cover and dynamic vegetation modelling results. This is used to quantify the relative impacts of land use and climate on Holocene vegetation at a sub-continental scale, i.e. northern and western Europe north of the Alps. We use redundancy analysis and variation partitioning to quantify the percentage of variation in vegetation composition explained by the climate and land-use variables, and Monte Carlo permutation tests to assess the statistical significance of each variable. We further use a similarity index to combine pollen-based REVEALS estimates with climate-driven dynamic vegetation modelling results. The overall results indicate that climate is the major driver of vegetation when the Holocene is considered as a whole and at the sub-continental scale, although land use is important regionally. Four critical phases of land-use effects on vegetation are identified. The first phase (from 7000 to 6500 BP) corresponds to the early impacts on vegetation of farming and Neolithic forest clearance and to the dominance of climate as a driver of vegetation change. During the second phase (from 4500 to 4000 BP), land use becomes a major control of vegetation. Climate is still the principal driver, although its influence decreases gradually. The third phase (from 2000 to 1500 BP) is characterised by the continued role of climate on vegetation as a consequence of late-Holocene climate shifts and specific climate events that influence vegetation as well as land use. The last phase (from 500 to 350 BP) shows an acceleration of vegetation changes, in particular during the last century, caused by new farming practices and forestry in response to population growth and industrialization. This is a unique signature of anthropogenic impact within the Holocene but European vegetation remains climatically sensitive and thus may continue to respond to ongoing climate change.

The impact of flood variables on riparian vegetation

NASA Astrophysics Data System (ADS)

Dzubakova, Katarina; Molnar, Peter

2016-04-01

The riparian vegetation of Alpine rivers often grows in temporally dynamic riverine environments which are characterized by pronounced meteorological and hydrological fluctuations and high resource competition. Within these relatively rough conditions, riparian vegetation fulfils essential ecosystem functions such as water retention, biomass production and habitat to endangered species. The identification of relevant flood attributes impacting riparian vegetation is crucial for a better understanding of the vegetation dynamics in the riverine ecosystem. Hence, in this contribution we aim to quantify the ecological effects of flood attributes on riparian vegetation and to analyze the spatial coherence of flood-vegetation interaction patterns. We analyzed a 500 m long and 300-400 m wide study reach located on the Maggia River in southern Switzerland. Altogether five floods between 2008 and 2011 with return periods ranging from 1.4 to 20.1 years were studied. To assess the significance of the flood attributes, we compared post-flood to pre-flood vegetation vigour to flood intensity. Pre- and post-flood vegetation vigour was represented by the Normalized Difference Vegetation Index (NDVI) which was computed from images recorded by high resolution ground-based cameras. Flood intensity was expressed in space in the study reach by six flood attributes (inundation duration, maximum depth, maximum and total velocity, maximum and total shear stress) which were simulated by the 2D hydrodynamic model BASEMENT (VAW, ETH Zurich). We considered three floodplain units separately (main bar, secondary bar, transitional zone). Based on our results, pre-flood vegetation vigour largely determined vegetation reaction to the less intense floods (R = 0.59-0.96). However for larger floods with a strong erosive effect, its contribution was significantly lower (R = 0.59-0.68). Using multivariate regression analysis we show that pre-flood vegetation vigour and maximum velocity proved to be the most significant variables impacting vegetation response. Generally, maximal flood attributes had more significant impacts than integrated attributes over the flood duration. Additional explanatory variables in the model should account for vegetation heterogeneity, groundwater conditions and different effects of lateral and surface erosion.

Effects of soil freezing and thawing on vegetation carbon density in Siberia: A modeling analysis with the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM)

NASA Astrophysics Data System (ADS)

Beer, C.; Lucht, W.; Gerten, D.; Thonicke, K.; Schmullius, C.

2007-03-01

The current latitudinal gradient in biomass suggests a climate-driven limitation of biomass in high latitudes. Understanding of the underlying processes, and quantification of their relative importance, is required to assess the potential carbon uptake of the biosphere in response to anticipated warming and related changes in tree growth and forest extent in these regions. We analyze the hydrological effects of thawing and freezing of soil on vegetation carbon density (VCD) in permafrost-dominated regions of Siberia using a process-based biogeochemistry-biogeography model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM). The analysis is based on spatially explicit simulations of coupled daily thaw depth, site hydrology, vegetation distribution, and carbon fluxes influencing VCD subject to climate, soil texture, and atmospheric CO2 concentration. LPJ represents the observed high spring peak of runoff of large Arctic rivers, and simulates a realistic fire return interval of 100 to 200 years in Siberia. The simulated VCD changeover from taiga to tundra is comparable to inventory-based information. Without the consideration of freeze-thaw processes VCD would be overestimated by a factor of 2 in southern taiga to a factor of 5 in northern forest tundra, mainly because available soil water would be overestimated with major effects on fire occurrence and net primary productivity. This suggests that forest growth in high latitudes is not only limited by temperature, radiation, and nutrient availability but also by the availability of liquid soil water.

Sensitivity analysis of a coupled hydrodynamic-vegetation model using the effectively subsampled quadratures method (ESQM v5.2)

NASA Astrophysics Data System (ADS)

Kalra, Tarandeep S.; Aretxabaleta, Alfredo; Seshadri, Pranay; Ganju, Neil K.; Beudin, Alexis

2017-12-01

Coastal hydrodynamics can be greatly affected by the presence of submerged aquatic vegetation. The effect of vegetation has been incorporated into the Coupled Ocean-Atmosphere-Wave-Sediment Transport (COAWST) modeling system. The vegetation implementation includes the plant-induced three-dimensional drag, in-canopy wave-induced streaming, and the production of turbulent kinetic energy by the presence of vegetation. In this study, we evaluate the sensitivity of the flow and wave dynamics to vegetation parameters using Sobol' indices and a least squares polynomial approach referred to as the Effective Quadratures method. This method reduces the number of simulations needed for evaluating Sobol' indices and provides a robust, practical, and efficient approach for the parameter sensitivity analysis. The evaluation of Sobol' indices shows that kinetic energy, turbulent kinetic energy, and water level changes are affected by plant stem density, height, and, to a lesser degree, diameter. Wave dissipation is mostly dependent on the variation in plant stem density. Performing sensitivity analyses for the vegetation module in COAWST provides guidance to optimize efforts and reduce exploration of parameter space for future observational and modeling work.

A vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel tests and its application in pollutant dispersion studies.

PubMed

Gromke, Christof

2011-01-01

A new vegetation modeling concept for Building and Environmental Aerodynamics wind tunnel investigations was developed. The modeling concept is based on fluid dynamical similarity aspects and allows the small-scale modeling of various kinds of vegetation, e.g. field crops, shrubs, hedges, single trees and forest stands. The applicability of the modeling concept was validated in wind tunnel pollutant dispersion studies. Avenue trees in urban street canyons were modeled and their implications on traffic pollutant dispersion were investigated. The dispersion experiments proved the modeling concept to be practicable for wind tunnel studies and suggested to provide reliable concentration results. Unfavorable effects of trees on pollutant dispersion and natural ventilation in street canyons were revealed. Increased traffic pollutant concentrations were found in comparison to the tree-free reference case. Copyright © 2010 Elsevier Ltd. All rights reserved.

Arctic Tundra Greening and Browning at Circumpolar and Regional Scales

NASA Astrophysics Data System (ADS)

Epstein, H. E.; Bhatt, U. S.; Walker, D. A.; Raynolds, M. K.; Yang, X.

2017-12-01

Remote sensing data have historically been used to assess the dynamics of arctic tundra vegetation. Until recently the scientific literature has largely described the "greening" of the Arctic; from a remote sensing perspective, an increase in the Normalized Difference Vegetation Index (NDVI), or a similar satellite-based vegetation index. Vegetation increases have been heterogeneous throughout the Arctic, and were reported to be up to 25% in certain areas over a 30-year timespan. However, more recently, arctic tundra vegetation dynamics have gotten more complex, with observations of more widespread tundra "browning" being reported. We used a combination of remote sensing data, including the Global Inventory Monitoring and Modeling System (GIMMS), as well as higher spatial resolution Landsat data, to evaluate the spatio-temporal patterns of arctic tundra vegetation dynamics (greening and browning) at circumpolar and regional scales over the past 3-4 decades. At the circumpolar scale, we focus on the spatial heterogeneity (by tundra subzone and continent) of tundra browning over the past 5-15 years, followed by a more recent recovery (greening since 2015). Landsat time series allow us to evaluate the landscape-scale heterogeneity of tundra greening and browning for northern Alaska and the Yamal Peninsula in northwestern Siberia, Russia. Multi-dataset analyses reveal that tundra greening and browning (i.e. increases or decreases in the NDVI respectively) are generated by different sets of processes. Tundra greening is largely a result of either climate warming, lengthening of the growing season, or responses to disturbances, such as fires, landslides, and freeze-thaw processes. Browning on the other hand tends to be more event-driven, such as the shorter-term decline in vegetation due to fire, insect defoliation, consumption by larger herbivores, or extreme weather events (e.g. winter warming or early summer frost damage). Browning can also be caused by local or regional cooling, or changes in the snow regime (e.g. depth, timing of melt). The spatio-temporal dynamics of tundra vegetation are only now beginning to get serious attention from the scientific community and the continual use of remote sensing data across spatial scales allows us to monitor these dynamics and elucidate their controls.

Influence of dynamic vegetation on climate change and terrestrial carbon storage in the Last Glacial Maximum

NASA Astrophysics Data System (ADS)

O'ishi, R.; Abe-Ouchi, A.

2013-07-01

When the climate is reconstructed from paleoevidence, it shows that the Last Glacial Maximum (LGM, ca. 21 000 yr ago) is cold and dry compared to the present-day. Reconstruction also shows that compared to today, the vegetation of the LGM is less active and the distribution of vegetation was drastically different, due to cold temperature, dryness, and a lower level of atmospheric CO2 concentration (185 ppm compared to a preindustrial level of 285 ppm). In the present paper, we investigate the influence of vegetation change on the climate of the LGM by using a coupled atmosphere-ocean-vegetation general circulation model (AOVGCM, the MIROC-LPJ). The MIROC-LPJ is different from earlier studies in the introduction of a bias correction method in individual running GCM experiments. We examined four GCM experiments (LGM and preindustrial, with and without vegetation feedback) and quantified the strength of the vegetation feedback during the LGM. The result shows that global-averaged cooling during the LGM is amplified by +13.5 % due to the introduction of vegetation feedback. This is mainly caused by the increase of land surface albedo due to the expansion of tundra in northern high latitudes and the desertification in northern middle latitudes around 30° N to 60° N. We also investigated how this change in climate affected the total terrestrial carbon storage by using offline Lund-Potsdam-Jena dynamic global vegetation model (LPJ-DGVM). Our result shows that the total terrestrial carbon storage was reduced by 597 PgC during the LGM, which corresponds to the emission of 282 ppm atmospheric CO2. In the LGM experiments, the global carbon distribution is generally the same whether the vegetation feedback to the atmosphere is included or not. However, the inclusion of vegetation feedback causes substantial terrestrial carbon storage change, especially in explaining the lowering of atmospheric CO2 during the LGM.

Terrestrial Feedbacks Incorporated in Global Vegetation Models through Observed Trait-Environment Responses

NASA Astrophysics Data System (ADS)

Bodegom, P. V.

2015-12-01

Most global vegetation models used to evaluate climate change impacts rely on plant functional types to describe vegetation responses to environmental stresses. In a traditional set-up in which vegetation characteristics are considered constant within a vegetation type, the possibility to implement and infer feedback mechanisms are limited as feedback mechanisms will likely involve a changing expression of community trait values. Based on community assembly concepts, we implemented functional trait-environment relationships into a global dynamic vegetation model to quantitatively assess this feature. For the current climate, a different global vegetation distribution was calculated with and without the inclusion of trait variation, emphasizing the importance of feedbacks -in interaction with competitive processes- for the prevailing global patterns. These trait-environmental responses do, however, not necessarily imply adaptive responses of vegetation to changing conditions and may locally lead to a faster turnover in vegetation upon climate change. Indeed, when running climate projections, simulations with trait variation did not yield a more stable or resilient vegetation than those without. Through the different feedback expressions, global and regional carbon and water fluxes were -however- strongly altered. At a global scale, model projections suggest an increased productivity and hence an increased carbon sink in the next decades to come, when including trait variation. However, by the end of the century, a reduced carbon sink is projected. This effect is due to a downregulation of photosynthesis rates, particularly in the tropical regions, even when accounting for CO2-fertilization effects. Altogether, the various global model simulations suggest the critical importance of including vegetation functional responses to changing environmental conditions to grasp terrestrial feedback mechanisms at global scales in the light of climate change.

Assessing and monitoring of urban vegetation using multiple endmember spectral mixture analysis

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Savastru, R. S.; Savastru, D. M.

2013-08-01

During last years urban vegetation with significant health, biological and economical values had experienced dramatic changes due to urbanization and human activities in the metropolitan area of Bucharest in Romania. We investigated the utility of remote sensing approaches of multiple endmember spectral mixture analysis (MESMA) applied to IKONOS and Landsat TM/ETM satellite data for estimating fractional cover of urban/periurban forest, parks, agricultural vegetation areas. Because of the spectral heterogeneity of same physical features of urban vegetation increases with the increase of image resolution, the traditional spectral information-based statistical method may not be useful to classify land cover dynamics from high resolution imageries like IKONOS. So we used hierarchy tree classification method in classification and MESMA for vegetation land cover dynamics assessment based on available IKONOS high-resolution imagery of Bucharest town. This study employs thirty two endmembers and six hundred and sixty spectral models to identify all Earth's features (vegetation, water, soil, impervious) and shade in the Bucharest area. The mean RMS error for the selected vegetation land cover classes range from 0.0027 to 0.018. The Pearson correlation between the fraction outputs from MESMA and reference data from all IKONOS images 1m panchromatic resolution data for urban/periurban vegetation were ranging in the domain 0.7048 - 0.8287. The framework in this study can be applied to other urban vegetation areas in Romania.

Use of a stochastic approach for description of water balance and runoff production dynamics

NASA Astrophysics Data System (ADS)

Gioia, A.; Manfreda, S.; Iacobellis, V.; Fiorentino, M.

2009-04-01

The present study exploits an analytical model (Manfreda, NHESS [2008]) for the description of the probability density function of soil water balance and runoff generation over a set of river basins belonging to Southern Italy. The model is based on a stochastic differential equation where the rainfall forcing is interpreted as an additive noise in the soil water balance; the watershed heterogeneity is described exploiting the conceptual lumped watershed Xinanjiang model (widely used in China) that uses a parabolic curve for the distribution of the soil water storage capacity (Zhao et al. [1980]). The model, characterized by parameters that depend on soil, vegetation and basin morphology, allowed to derive the probability density function of the relative saturation and the surface runoff of a basin accounting for the spatial heterogeneity in soil water storage. Its application on some river basins belonging to regions of Southern Italy, gives interesting insights for the investigation of the role played by the dynamical interaction between climate, soil, and vegetation in soil moisture and runoff production dynamics. Manfreda, S., Runoff Generation Dynamics within a Humid River Basin, Natural Hazard and Earth System Sciences, 8, 1349-1357, 2008. Zhao, R. -J., Zhang, Y. L., and Fang, L. R.: The Xinanjiang model, Hydrological Forecasting Proceedings Oxford Symposium, IAHS Pub. 129, 351-356, 1980.

Mechanistic ecohydrological modeling with Tethys-Chloris: an attempt to unravel complexity

NASA Astrophysics Data System (ADS)

Fatichi, S.; Ivanov, V. Y.; Caporali, E.

2010-12-01

The role of vegetation in controlling and mediating hydrological states and fluxes at the level of individual processes has been largely explored, which has lead to the improvement of our understanding of mechanisms and patterns in ecohydrological systems. Nonetheless, relatively few efforts have been directed toward the development of continuous, complex, mechanistic ecohydrological models operating at the watershed-scale. This study presents a novel ecohydrological model Tethys-Chloris (T&C) and aims to discuss current limitations and perspectives of the mechanistic approach in ecohydrology. The model attempts to synthesize the state-of-the-art knowledge on individual processes and mechanisms drawn from various disciplines such as hydrology, plant physiology, ecology, and biogeochemistry. The model reproduces all essential components of hydrological cycle resolving the mass and energy budgets at the hourly scale; it includes energy and mass exchanges in the atmospheric boundary layer; a module of saturated and unsaturated soil water dynamics; two layers of vegetation, and a module of snowpack evolution. The vegetation component parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, tissues turnover, and soil biogeochemistry. Quantitative metrics of model performance are discussed and highlight the capabilities of T&C in reproducing ecohydrological dynamics. The simulated patterns mimic the outcome of hydrological dynamics with high realism, given the uncertainty of imposed boundary conditions and limited data availability. Furthermore, highly satisfactory results are obtained without significant (e.g., automated) calibration efforts despite the large phase-space dimensionality of the model. A significant investment into model design and development leads to such desirable behavior. This suggests that while using the presented tool for high-precision predictions can be still problematic, the mechanistic nature of the model can be extremely valuable for designing virtual experiments, testing hypotheses. and focusing questions of scientific inquiry.

A blueprint for using climate change predictions in an eco-hydrological study

NASA Astrophysics Data System (ADS)

Caporali, E.; Fatichi, S.; Ivanov, V. Y.

2009-12-01

There is a growing interest to extend climate change predictions to smaller, catchment-size scales and identify their implications on hydrological and ecological processes. Small scale processes are, in fact, expected to mediate climate changes, producing local effects and feedbacks that can interact with the principal consequences of the change. This is particularly applicable, when a complex interaction, such as the inter-relationship between the hydrological cycle and vegetation dynamics, is considered. This study presents a blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the catchment scale. Climate conditions, present or future, are imposed through input hydrometeorological variables for hydrological and eco-hydrological models. These variables are simulated with an hourly weather generator as an outcome of a stochastic downscaling technique. The generator is parameterized to reproduce the climate of southwestern Arizona for present (1961-2000) and future (2081-2100) conditions. The methodology provides the capability to generate ensemble realizations for the future that take into account the heterogeneous nature of climate predictions from different models. The generated time series of meteorological variables for the two scenarios corresponding to the current and mean expected future serve as input to a coupled hydrological and vegetation dynamics model, “Tethys-Chloris”. The hydrological model reproduces essential components of the land-surface hydrological cycle, solving the mass and energy budget equations. The vegetation model parsimoniously parameterizes essential plant life-cycle processes, including photosynthesis, phenology, carbon allocation, and tissue turnover. The results for the two mean scenarios are compared and discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity The need to account for uncertainties in projections of future climate is discussed and a methodology for propagating these uncertainties into the probability density functions of changes in eco-hydrological variables is presented.

Ecological optimality in water-limited natural soil-vegetation systems. I - Theory and hypothesis

NASA Technical Reports Server (NTRS)

Eagleson, P. S.

1982-01-01

The solution space of an approximate statistical-dynamic model of the average annual water balance is explored with respect to the hydrologic parameters of both soil and vegetation. Within the accuracy of this model it is shown that water-limited natural vegetation systems are in stable equilibrium with their climatic and pedologic environments when the canopy density and species act to minimize average water demand stress. Theory shows a climatic limit to this equilibrium above which it is hypothesized that ecological pressure is toward maximization of biomass productivity. It is further hypothesized that natural soil-vegetation systems will develop gradually and synergistically, through vegetation-induced changes in soil structure, toward a set of hydraulic soil properties for which the minimum stress canopy density of a given species is maximum in a given climate. Using these hypotheses, only the soil effective porosity need be known to determine the optimum soil and vegetation parameters in a given climate.

Potential management of young-growth stands for understory vegetation and wildlife habitat in southeastern Alaska.

Treesearch

Thomas A. Hanley

2005-01-01

I review the current state of knowledge about dynamics of understory vegetation in postlogging succession and responses to silviculture treatments in southeastern Alaska, and I derive implications for future research and development. The classic Alaback [Ecology 63 (1982) 1932] model of postlogging succession has dominated ecological thinking in the region for the past...

Eco-hydrological Modeling in the Framework of Climate Change

NASA Astrophysics Data System (ADS)

Fatichi, Simone; Ivanov, Valeriy Y.; Caporali, Enrica

2010-05-01

A blueprint methodology for studying climate change impacts, as inferred from climate models, on eco-hydrological dynamics at the plot and small catchment scale is presented. Input hydro-meteorological variables for hydrological and eco-hydrological models for present and future climates are reproduced using a stochastic downscaling technique and a weather generator, "AWE-GEN". The generated time series of meteorological variables for the present climate and an ensemble of possible future climates serve as input to a newly developed physically-based eco-hydrological model "Tethys-Chloris". An application of the proposed methodology is realized reproducing the current (1961-2000) and multiple future (2081-2100) climates for the location of Tucson (Arizona). A general reduction of precipitation and a significant increase of air temperature are inferred. The eco-hydrological model is successively applied to detect changes in water recharge and vegetation dynamics for a desert shrub ecosystem, typical of the semi-arid climate of south Arizona. Results for the future climate account for uncertainties in the downscaling and are produced in terms of probability density functions. A comparison of control and future scenarios is discussed in terms of changes in the hydrological balance components, energy fluxes, and indices of vegetation productivity. An appreciable effect of climate change can be observed in metrics of vegetation performance. The negative impact on vegetation due to amplification of water stress in a warmer and dryer climate is offset by a positive effect of carbon dioxide augment. This implies a positive shift in plant capabilities to exploit water. Consequently, the plant water use efficiency and rain use efficiency are expected to increase. Interesting differences in the long-term vegetation productivity are also observed for the ensemble of future climates. The reduction of precipitation and the substantial maintenance of vegetation cover ultimately leads to the depletion of soil moisture and recharge to deeper layers. Such an outcome can affect the long-tem water availability in semi-arid systems and expose plants to more severe and frequent periods of stress.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2015-06-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition, and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverages of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverages of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, J. R.; Arora, V. K.

2016-01-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the Earth system model of the Canadian Centre for Climate Modelling and Analysis. CTEM models land-atmosphere exchange of CO2 through the response of carbon in living vegetation, and dead litter and soil pools, to changes in weather and climate at timescales of days to centuries. Version 1.0 of CTEM uses prescribed fractional coverage of plant functional types (PFTs) although, in reality, vegetation cover continually adapts to changes in climate, atmospheric composition and anthropogenic forcing. Changes in the spatial distribution of vegetation occur on timescales of years to centuries as vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM, which includes a representation of competition between PFTs based on a modified version of the Lotka-Volterra (L-V) predator-prey equations. Our approach is used to dynamically simulate the fractional coverage of CTEM's seven natural, non-crop PFTs, which are then compared with available observation-based estimates. Results from CTEM v. 2.0 show the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. However, differences remain between modelled and observation-based fractional coverage of PFTs since representing the multitude of plant species globally, with just seven non-crop PFTs, only captures the large-scale climatic controls on PFT distributions. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model, and the corresponding driving climate, or the limited number of PFTs used. We also simulate the fractional coverage of PFTs using unmodified L-V equations to illustrate its limitations. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably well with each other and observation-based estimates. The parametrization of competition between PFTs in CTEM v. 2.0 based on the modified L-V equations behaves in a reasonably realistic manner and yields a tool with which to investigate the changes in spatial distribution of vegetation in response to future changes in climate.

Post Fire Vegetation Recovery in Greece after the large Drought event of 2007

NASA Astrophysics Data System (ADS)

Gouveia, Célia M.; Bastos, Ana; DaCamara, Carlos; Trigo, Ricardo

2013-04-01

Fire is a natural factor of Mediterranean ecosystems. However, fire regimes in the European Mediterranean areas have been changing in the last decades, mainly due to land-use changes and climate driven factors possibly associated with climatic warming (e.g. decline of precipitation, increasing temperatures but also higher frequency of heatwaves). In Greece, the fire season of 2007 was particularly devastating, achieving the new all-time record of estimated burnt area (225 734 ha), since 1980. Additionally, we must stress that prior to the summer fire season in 2007, Greece suffered an exceptional drought event. This severe drought had a strong negative impact in vegetation dynamics. Since water availability is a crucial factor in post-fire vegetation recovery, it is desirable to assess the impact that such water-stress conditions had on fire sensitivity and post-fire vegetation recovery. Based on monthly values of NDVI, at the 1km×1km spatial scale, as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2010, large burnt scars are identified in Greece, during 2007 fire season. Vegetation recovery is then assessed based on a mono parametric regression model originally developed by Gouveia et al. (2010) to identify large burnt scars in Portugal during the 2003 fire season and after applied to 2005 fire season (Bastos et al., 2012). Some large burnt areas are selected and the respective NDVI behaviour is monitored throughout the pre and the post fire period. The vegetation dynamics during the pre-fire period is analysed and related to the extreme climatic events that characterised the considered period. An analysis is made of the dependence of recovery rates on land cover types and fire damage. Finally results are compared to results already obtained for Portugal (Gouveia et al. 2010). This work emphasises the use of a simple methodology, when applied to low resolution satellite imagery in order to monitor vegetation recovery after large fires events over distinct regions of Mediterranean Europe. Gouveia C., DaCamara C.C, Trigo R.M. (2010). "Post-fire vegetation dynamics in Portugal". Natural Hazards and Earth System Sciences, 10, 4, 673-684. Bastos A., Gouveia C., DaCamara C.C., and Trigo R.M.: Modelling post-fire vegetation recovery in Portugal.Biogeosciences, 8, 4559-4601, 2011.

Dynamics of global vegetation biomass simulated by the integrated Earth System Model

NASA Astrophysics Data System (ADS)

Mao, J.; Shi, X.; Di Vittorio, A. V.; Thornton, P. E.; Piao, S.; Yang, X.; Truesdale, J. E.; Bond-Lamberty, B. P.; Chini, L. P.; Thomson, A. M.; Hurtt, G. C.; Collins, W.; Edmonds, J.

2014-12-01

The global vegetation biomass stores huge amounts of carbon and is thus important to the global carbon budget (Pan et al., 2010). For the past few decades, different observation-based estimates and modeling of biomass in the above- and below-ground vegetation compartments have been comprehensively conducted (Saatchi et al., 2011; Baccini et al., 2012). However, uncertainties still exist, in particular for the simulation of biomass magnitude, tendency, and the response of biomass to climatic conditions and natural and human disturbances. The recently successful coupling of the integrated Earth System Model (iESM) (Di Vittorio et al., 2014; Bond-Lamberty et al., 2014), which links the Global Change Assessment Model (GCAM), Global Land-use Model (GLM), and Community Earth System Model (CESM), offers a great opportunity to understand the biomass-related dynamics in a fully-coupled natural and human modeling system. In this study, we focus on the systematic analysis and evaluation of the iESM simulated historical (1850-2005) and future (2006-2100) biomass changes and the response of the biomass dynamics to various impact factors, in particular the human-induced Land Use/Land Cover Change (LULCC). By analyzing the iESM simulations with and without the interactive LULCC feedbacks, we further study how and where the climate feedbacks affect socioeconomic decisions and LULCC, such as to alter vegetation carbon storage. References Pan Y et. al: A large and persistent carbon sink in the World's forests. Science 2011, 333:988-993. Saatchi SS et al: Benchmark map of forest carbon stocks in tropical regions across three continents. Proc Natl Acad Sci 2011, 108:9899-9904. Baccini A et al: Estimated carbon dioxide emissions from tropical deforestation improved by carbon-density maps. Nature Clim Change 2012, 2:182-185. Di Vittorio AV et al: From land use to land cover: restoring the afforestation signal in a coupled integrated assessment-earth system model and the implications for CMIP5 RCP simulations. Biogeosciences Discuss 2014, 11:7151-7188. Bond-Lamberty, B et al: Coupling earth system and integrated assessment models: The problem of steady state. Geosci. Model Dev. Discuss 2014, 7: 1499-1524, doi:10.5194/gmdd-7-1499-2014.

Climate-driven reduction in soil loss due to the dynamic role of vegetation

NASA Astrophysics Data System (ADS)

Constantine, J. A.; Ciampalini, R.; Walker-Springett, K.; Hales, T. C.; Ormerod, S.; Gabet, E. J.; Hall, I. R.

2016-12-01

Simulations of 21st century climate change predict increases in seasonal precipitation that may lead to widespread soil loss and reduced soil carbon stores by increasing the likelihood of surface runoff. Vegetation may counteract this increase through its dynamic response to climate change, possibly mitigating any impact on soil erosion. Here, we document for the first time the potential for vegetation to prevent widespread soil loss by surface-runoff mechanisms (i.e., rill and inter-rill erosion) by implementing a process-based soil erosion model across catchments of Great Britain with varying land-cover, topographic, and soil characteristics. Our model results reveal that, even under a significantly wetter climate, warmer air temperatures can limit soil erosion across areas with permanent vegetation cover because of its role in enhancing primary productivity, which improves leaf interception, soil infiltration-capacity, and the erosive resistance of soil. Consequently, any increase in air temperature associated with climate change will increase the threshold change in rainfall required to accelerate soil loss, and rates of soil erosion could therefore decline by up to 50% from 2070-2099 compared to baseline values under the IPCC-defined medium-emissions scenario SRES A1B. We conclude that enhanced primary productivity due to climate change can introduce a negative-feedback mechanism that limits soil loss by surface runoff as vegetation-induced impacts on soil hydrology and erodibility offset precipitation increases, highlighting the need to expand areas of permanent vegetation cover to reduce the potential for climate-driven soil loss.

Millennial Climatic Fluctuations Are Key to the Structure of Last Glacial Ecosystems

PubMed Central

Huntley, Brian; Allen, Judy R. M.; Collingham, Yvonne C.; Hickler, Thomas; Lister, Adrian M.; Singarayer, Joy; Stuart, Anthony J.; Sykes, Martin T.; Valdes, Paul J.

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in “normal” and “hosing” experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The “hosing” experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the “normal” experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems. PMID:23613985

Millennial climatic fluctuations are key to the structure of last glacial ecosystems.

PubMed

Huntley, Brian; Allen, Judy R M; Collingham, Yvonne C; Hickler, Thomas; Lister, Adrian M; Singarayer, Joy; Stuart, Anthony J; Sykes, Martin T; Valdes, Paul J

2013-01-01

Whereas fossil evidence indicates extensive treeless vegetation and diverse grazing megafauna in Europe and northern Asia during the last glacial, experiments combining vegetation models and climate models have to-date simulated widespread persistence of trees. Resolving this conflict is key to understanding both last glacial ecosystems and extinction of most of the mega-herbivores. Using a dynamic vegetation model (DVM) we explored the implications of the differing climatic conditions generated by a general circulation model (GCM) in "normal" and "hosing" experiments. Whilst the former approximate interstadial conditions, the latter, designed to mimic Heinrich Events, approximate stadial conditions. The "hosing" experiments gave simulated European vegetation much closer in composition to that inferred from fossil evidence than did the "normal" experiments. Given the short duration of interstadials, and the rate at which forest cover expanded during the late-glacial and early Holocene, our results demonstrate the importance of millennial variability in determining the character of last glacial ecosystems.

A vital link: water and vegetation in the Anthropocene

NASA Astrophysics Data System (ADS)

Gerten, D.

2013-10-01

This paper argues that the interplay of water, carbon and vegetation dynamics fundamentally links some global trends in the current and conceivable future Anthropocene, such as cropland expansion, freshwater use, and climate change and its impacts. Based on a review of recent literature including geographically explicit simulation studies with the process-based LPJmL global biosphere model, it demonstrates that the connectivity of water and vegetation dynamics is vital for water security, food security and (terrestrial) ecosystem dynamics alike. The water limitation of net primary production of both natural and agricultural plants - already pronounced in many regions - is shown to increase in many places under projected climate change, though this development is partially offset by water-saving direct CO2 effects. Natural vegetation can to some degree adapt dynamically to higher water limitation, but agricultural crops usually require some form of active management to overcome it - among them irrigation, soil conservation and eventually shifts of cropland to areas that are less water-limited due to more favourable climatic conditions. While crucial to secure food production for a growing world population, such human interventions in water-vegetation systems have, as also shown, repercussions on the water cycle. Indeed, land use changes are shown to be the second-most important influence on the terrestrial water balance in recent times. Furthermore, climate change (warming and precipitation changes) will in many regions increase irrigation demand and decrease water availability, impeding rainfed and irrigated food production (if not CO2 effects counterbalance this impact - which is unlikely at least in poorly managed systems). Drawing from these exemplary investigations, some research perspectives on how to further improve our knowledge of human-water-vegetation interactions in the Anthropocene are outlined.

Evaluating CO2 and CH4 dynamics of Alaskan ecosystems during the Holocene Thermal Maximum

USGS Publications Warehouse

He, Yujie; Jones, Miriam C.; Zhuang, Qianlai; Bochicchio, Christopher; Felzer, B. S.; Mason, Erik; Yu, Zicheng

2014-01-01

The Arctic has experienced much greater warming than the global average in recent decades due to polar amplification. Warming has induced ecological changes that have impacted climate carbon-cycle feedbacks, making it important to understand the climate and vegetation controls on carbon (C) dynamics. Here we used the Holocene Thermal Maximum (HTM, 11–9 ka BP, 1 ka BP = 1000 cal yr before present) in Alaska as a case study to examine how ecosystem Cdynamics responded to the past warming climate using an integrated approach of combining paleoecological reconstructions and ecosystem modeling. Our paleoecological synthesis showed expansion of deciduous broadleaf forest (dominated by Populus) into tundra and the establishment of boreal evergreen needleleaf and mixed forest during the second half of the HTM under a warmer- and wetter-than-before climate, coincident with the occurrence of the highest net primary productivity, cumulative net ecosystem productivity, soil C accumulation and CH4 emissions. These series of ecological and biogeochemical shifts mirrored the solar insolation and subsequent temperature and precipitation patterns during HTM, indicating the importance of climate controls on C dynamics. Our simulated regional estimate of CH4 emission rates from Alaska during the HTM ranged from 3.5 to 6.4 Tg CH4 yr−1 and highest annual NPP of 470 Tg C yr−1, significantly higher than previously reported modern estimates. Our results show that the differences in static vegetation distribution maps used in simulations of different time slices have greater influence on modeled C dynamics than climatic fields within each time slice, highlighting the importance of incorporating vegetation community dynamics and their responses to climatic conditions in long-term biogeochemical modeling.

Constraining the Late Miocene paleo-CO2 estimates through GCM model-data comparisons

NASA Astrophysics Data System (ADS)

Bradshaw, Catherine; Pound, Matthew; Lunt, Daniel; Flecker, Rachel; Salzmann, Ulrich; Haywood, Alan; Riding, James; Francis, Jane

2010-05-01

The period following the Mid-Miocene Climatic Optimum experienced a continued downward trend in the δ18O record - a record acknowledged as a proxy indicator of both ice volume and temperature (Zachos et al., 2001). Given the link between atmospheric CO2 and temperature (IPCC, 2007), it could be thought that the timeline throughout the Late Miocene would show a general decline in CO2 in accordance with the δ18O record. However, examination of the palaeo-CO2 record shows a relatively flat profile across this time, or perhaps even a slight increase, but there is a wide variation in the palaeo-CO2 estimate for the differing approximation methods. We use the fully coupled atmosphere-ocean-vegetation model of the Hadley Centre, HadCM3L, which has a low resolution ocean (Hadley Centre Coupled Model, Version 3 - low resolution ocean) with TRIFFID (Top-down Representation of Interactive Foliage and Flora Including Dynamics: Cox, 2001) to generate CO2 sensitivity scenarios for the Late Miocene: 180ppmv, 280ppmv and 400ppmv, as well as a preindustrial control simulation: 280 ppmv. We also run the BIOME4 model offline to produce predicted biome distributions for each of our scenarios. We compare both marine and terrestrial modelled temperatures, and the predicted vegetation distributions for these scenarios against available palaeodata As we simulate with a coupled dynamic ocean model, we use planktonic and benthic foraminiferal-based proxy palaeotemperature estimates to compare to the modelled marine temperatures at the depths consistent with the reconstructed palaeoecology of the foraminifera. We compare our modelled terrestrial temperatures to vegetation-based proxy palaeotemperatures, and we use a newly compiled vegetation reconstruction for the Late Miocene to compare to our modelled vegetation distributions. The new Late Miocene vegetation reconstruction is based on a 200+ point database of palaeobotanical sites. Each location is classified into a biome consistent with the BIOME4 model, to allow for easy data - model comparison. We use all these data - model comparisons to constrain the best-fit scenario and the overall most likely Late Miocene CO2 estimate according to the model simulations. Preliminary results suggest that the 400ppmv simulation provides the best fit to the proxy data.

Time-lag effects of global vegetation responses to climate change.

PubMed

Wu, Donghai; Zhao, Xiang; Liang, Shunlin; Zhou, Tao; Huang, Kaicheng; Tang, Bijian; Zhao, Wenqian

2015-09-01

Climate conditions significantly affect vegetation growth in terrestrial ecosystems. Due to the spatial heterogeneity of ecosystems, the vegetation responses to climate vary considerably with the diverse spatial patterns and the time-lag effects, which are the most important mechanism of climate-vegetation interactive effects. Extensive studies focused on large-scale vegetation-climate interactions use the simultaneous meteorological and vegetation indicators to develop models; however, the time-lag effects are less considered, which tends to increase uncertainty. In this study, we aim to quantitatively determine the time-lag effects of global vegetation responses to different climatic factors using the GIMMS3g NDVI time series and the CRU temperature, precipitation, and solar radiation datasets. First, this study analyzed the time-lag effects of global vegetation responses to different climatic factors. Then, a multiple linear regression model and partial correlation model were established to statistically analyze the roles of different climatic factors on vegetation responses, from which the primary climate-driving factors for different vegetation types were determined. The results showed that (i) both the time-lag effects of the vegetation responses and the major climate-driving factors that significantly affect vegetation growth varied significantly at the global scale, which was related to the diverse vegetation and climate characteristics; (ii) regarding the time-lag effects, the climatic factors explained 64% variation of the global vegetation growth, which was 11% relatively higher than the model ignoring the time-lag effects; (iii) for the area with a significant change trend (for the period 1982-2008) in the global GIMMS3g NDVI (P < 0.05), the primary driving factor was temperature; and (iv) at the regional scale, the variation in vegetation growth was also related to human activities and natural disturbances. Considering the time-lag effects is quite important for better predicting and evaluating the vegetation dynamics under the background of global climate change. © 2015 John Wiley & Sons Ltd.

Uprooting of flexible riparian vegetation: field and laboratory observations

NASA Astrophysics Data System (ADS)

Solari, L.; Calvani, G.; Francalanci, S.

2017-12-01

Vegetation is a key element in fluvial systems, controlling river corridor form and dynamics. Plants actively interact with fluvial processes; their aboveground biomass can affect the flow field and sediment transport and therefore river morphological evolution, whereas their belowground biomass modifies the hydraulic and mechanical properties of the substrate, and consequently the moisture regime and erodibility of the soil (Gurnell, 2014; Solari et al., 2015). Vegetation biomass can either increase over time or can die through the mechanism of uprooting. Despite its important implications in river morphodynamics, vegetation uprooting due to sediment transport during flood events have been poorly investigated (Edmaier et al., 2011). Most of previous research focused on the mechanism of root breakage and on measuring the vegetation resistance to uprooting in the vertical direction (Bywater-Reyes et al., 2015, among others). In this work, we focus on the uprooting of flexible juvenile seedlings vegetation due to flow and to bed erosion. First, we derive a physics-based model for the prediction of vegetation uprooting for given root geometry, soil strength characteristics, flow bed shear stress and bed erosion. The model is then tested in a laboratory flume using two different species of vegetation: Avena sativa and Salix purpurea. Various experiments were run considering increasing flow discharges and a quasi- parallel bed erosion. The vegetation model is then applied to a sediment bar in the Ombrone Pistoiese river where we observed the removal of Salix Purpurea during the flood of November 2016. We implemented a 2D hydraulic model to reconstruct the pattern of bed shear stresses on the bar and we compared the prediction of the vegetation model with the field surveys of Salix purpurea before and after the flood. Results suggest that juvenile seedlings can be easily removed by the flow provided sediment transport takes place.

Sentinel-1 backscatter sensitivity to vegetation dynamics at the field scale.

NASA Astrophysics Data System (ADS)

Vreugdenhil, Mariette; Eder, Alexander; Bauer-Marschallinger, Bernhard; Cao, Senmao; Naeimi, Vahid; Oismueller, Markus; Strauss, Peter; Wagner, Wolfgang

2017-04-01

Vegetation monitoring is pivotal to improve our understanding of the role vegetation dynamics play in the global carbon-, energy- and hydrological cycle. And with the increasing stress on food supply due to the growing world populating and changing climate, vegetation monitoring is of great importance in agricultural areas. By closely tracking crop conditions, droughts and subsequent crop losses could be mitigated. Sensors operating in the microwave domain are sensitive to several surface characteristics, including soil moisture and vegetation. Hence, spaceborne microwave remote sensing provides the means to monitor vegetation and soil conditions on different scales, ranging from field scale to global scale. However, it also presents a challenge since multiple combinations of soil and vegetation characteristics can lead to a similar measurement. Copernicus Sentinel-1 (S-1) is a series of two satellites, developed by the European Space Agency (ESA) , which carry C-band Synthetic Aperture Radars. The C-SAR sensors provide VV, HH, VH and HV backscatter at a 5 m by 20 m spatial resolution. The temporal revisit time of the two satellites is 3-6 days. With their unique capacity for temporally dense and spatially detailed data, the S-1 satellite series provides for the first time the chance to investigate vegetation dynamics at high temporal and spatial resolution. The aim of this study is to assess the sensitivity of Sentinel-1 backscatter to vegetation dynamics. The study is performed in the Hydrological Open Air Laboratory (HOAL), which is a 66 hectare large catchment located in Petzenkirchen, Austria. In the HOAL several vegetation parameters were measured during the course of the growing season (2016) at the overpass time of S-1a. Vegetation height was obtained ten times for the whole catchment, using georeferenced photos made by a motorized paraglider and a Land Surface Model. In addition, vegetation water content, Leaf Area Index and soil moisture were measured in four different cropfields. An in situ soil moisture network provides continuous soil moisture measurements at 31 locations within the catchment. Different polarizations and ratios thereof were calculated and compared, both spatially and temporally, to the in situ measurements of vegetation height, LAI, vegetation water content and soil moisture. Preliminary results show a clear spatial pattern in cross-polarized backscatter, which is related to different crop types. Time series analysis suggests that a ratio between cross- and co-polarized backscatter is affected by both vegetation water content and vegetation structure. This presentation will provide a comprehensive assessment of Sentinel-1's capability for monitoring of vegetation over croplands, using in situ reference data obtained over a full growing season.

A coupled vegetation/sediment transport model for dryland environments

NASA Astrophysics Data System (ADS)

Mayaud, Jerome R.; Bailey, Richard M.; Wiggs, Giles F. S.

2017-04-01

Dryland regions are characterized by patchy vegetation, erodible surfaces, and erosive aeolian processes. Understanding how these constituent factors interact and shape landscape evolution is critical for managing potential environmental and anthropogenic impacts in drylands. However, modeling wind erosion on partially vegetated surfaces is a complex problem that has remained challenging for researchers. We present the new, coupled cellular automaton Vegetation and Sediment TrAnsport (ViSTA) model, which is designed to address fundamental questions about the development of arid and semiarid landscapes in a spatially explicit way. The technical aspects of the ViSTA model are described, including a new method for directly imposing oblique wind and transport directions onto a cell-based domain. Verification tests for the model are reported, including stable state solutions, the impact of drought and fire stress, wake flow dynamics, temporal scaling issues, and the impact of feedbacks between sediment movement and vegetation growth on landscape morphology. The model is then used to simulate an equilibrium nebkha dune field, and the resultant bed forms are shown to have very similar size and spacing characteristics to nebkhas observed in the Skeleton Coast, Namibia. The ViSTA model is a versatile geomorphological tool that could be used to predict threshold-related transitions in a range of dryland ecogeomorphic systems.

Ecological controls on water-cycle response to climate variability in deserts.

PubMed

Scanlon, B R; Levitt, D G; Reedy, R C; Keese, K E; Sully, M J

2005-04-26

The impact of climate variability on the water cycle in desert ecosystems is controlled by biospheric feedback at interannual to millennial timescales. This paper describes a unique field dataset from weighing lysimeters beneath nonvegetated and vegetated systems that unequivocally demonstrates the role of vegetation dynamics in controlling water cycle response to interannual climate variability related to El Nino southern oscillation in the Mojave Desert. Extreme El Nino winter precipitation (2.3-2.5 times normal) typical of the U.S. Southwest would be expected to increase groundwater recharge, which is critical for water resources in semiarid and arid regions. However, lysimeter data indicate that rapid increases in vegetation productivity in response to elevated winter precipitation reduced soil water storage to half of that in a nonvegetated lysimeter, thereby precluding deep drainage below the root zone that would otherwise result in groundwater recharge. Vegetation dynamics have been controlling the water cycle in interdrainage desert areas throughout the U.S. Southwest, maintaining dry soil conditions and upward soil water flow since the last glacial period (10,000-15,000 yr ago), as shown by soil water chloride accumulations. Although measurements are specific to the U.S. Southwest, correlations between satellite-based vegetation productivity and elevated precipitation related to El Nino southern oscillation indicate this model may be applicable to desert basins globally. Understanding the two-way coupling between vegetation dynamics and the water cycle is critical for predicting how climate variability influences hydrology and water resources in water-limited landscapes.

A vital link: water and vegetation in the Anthropocene

NASA Astrophysics Data System (ADS)

Gerten, D.

2013-04-01

This paper argues that the interplay of water, carbon and vegetation dynamics is fundamental to some global trends in the current and conceivable future Anthropocene. Supported by simulations with a process-based biosphere model and a literature review, it demonstrates that the connectivity of freshwater and vegetation dynamics is vital for water security, food security and (terrestrial) ecosystem integrity alike. The water limitation of net primary production of both natural and agricultural plants - already pronounced in many regions - is shown to increase in many places under projected climate change, though this development is partially offset by water-saving direct CO2 effects. Natural vegetation can to some degree adapt dynamically to higher water limitation, but agricultural crops require some form of active management to overcome it - among them irrigation, soil conservation and expansion into still uncultivated areas. While crucial to secure food production for a growing world population, such human interventions in water-vegetation systems have, as also shown, repercussions to the water cycle. Indeed, land use changes have been shown to be the second-most important influence on the terrestrial water balance in recent times. Furthermore, climate change regionally increases irrigation demand and decreases freshwater availability, impeding on rainfed and irrigated food production (if not CO2 effects counterbalance this impact - which is unlikely at least in poorly managed systems). Drawing from these exemplary investigations, some research perspectives on how to further improve our quantitative knowledge of human-water-vegetation interactions in the Anthropocene are outlined.

Dynamics of Aboveground Phytomass of the Circumpolar Arctic Tundra During the Past Three Decades

NASA Technical Reports Server (NTRS)

Epstein, Howard E.; Raynolds, Martha K.; Walker, Donald A.; Bhatt, Uma S.; Tucker, Compton J.; Pinzon, Jorge E.

2012-01-01

Numerous studies have evaluated the dynamics of Arctic tundra vegetation throughout the past few decades, using remotely sensed proxies of vegetation, such as the normalized difference vegetation index (NDVI). While extremely useful, these coarse-scale satellite-derived measurements give us minimal information with regard to how these changes are being expressed on the ground, in terms of tundra structure and function. In this analysis, we used a strong regression model between NDVI and aboveground tundra phytomass, developed from extensive field-harvested measurements of vegetation biomass, to estimate the biomass dynamics of the circumpolar Arctic tundra over the period of continuous satellite records (1982-2010). We found that the southernmost tundra subzones (C-E) dominate the increases in biomass, ranging from 20 to 26%, although there was a high degree of heterogeneity across regions, floristic provinces, and vegetation types. The estimated increase in carbon of the aboveground live vegetation of 0.40 Pg C over the past three decades is substantial, although quite small relative to anthropogenic C emissions. However, a 19.8% average increase in aboveground biomass has major implications for nearly all aspects of tundra ecosystems including hydrology, active layer depths, permafrost regimes, wildlife and human use of Arctic landscapes. While spatially extensive on-the-ground measurements of tundra biomass were conducted in the development of this analysis, validation is still impossible without more repeated, long-term monitoring of Arctic tundra biomass in the field.

Climatic and anthropogenic forcing of prehistorical vegetation succession and fire dynamics in the Lago di Como area (N-Italy, Insubria)

NASA Astrophysics Data System (ADS)

Martinelli, Elisa; Michetti, Alessandro Maria; Colombaroli, Daniele; Mazzola, Eleonora; Motella De Carlo, Sila; Livio, Franz; Gilli, Adrian; Ferrario, Maria Francesca; Höbig, Nicole; Brunamonte, Fabio; Castelletti, Lanfredo; Tinner, Willy

2017-04-01

Combined pollen, charcoal and modeling evidence from the Insubria Region suggests that fire was a major driver of late Holocene vegetation change. However, the extent and timing of fire response dynamics are not clear yet. We use lacustrine sediments from Lago di Como (N-Italy, S-Alps) to assess if the reconstructed vegetation and fire dynamics were relevant at large scales and if they coincided in time with those observed at smaller sites. The lake, due to its size (142 km2) and economic potential, was very attractive for early land use and human presence in this area is well documented since ca. 10,000 yrs ago (Mesolithic). We used pollen, plant macrofossils and charcoal to reconstruct the vegetation composition and fire activity. During the Younger Dryas and the Early Holocene until ca. 8000 cal BP natural dynamics prevailed. Subsequently, land use and slash-and-burn activities increased at the Mesolithic-Neolithic transition and became widespread around ca. 6500 cal BP. Microscopic charcoal and numerical analyses demonstrate that anthropogenic fires had a determinant influence on long-term vegetation dynamics at regional scales in Insubria. Microscopic charcoal and pollen and spores indicative of land use show that human pressure intensified after ca. 5300 cal yr BP and even more since ca. 4300 cal yr BP. Our results suggest that important species which disappeared or were strongly reduced by land use and fire (e.g. Abies alba, Tilia, Ulmus) will potentially reestablish in the Lago di Como area and elsewhere in Insubria, if land abandonment initiated in the 1950s will continue.

Analysing spatio-temporal land degradation dynamics in dry rangelands using landscape metrics and satellite time series data

NASA Astrophysics Data System (ADS)

von Keyserlingk, Jennifer; Paton, Eva Nora; Förster, Saskia; Bronstert, Axel

2017-04-01

Many of the dry rangelands of Southern Europe are threatened by land degradation. This process not only reduces the land's ecological functioning, but also its capacity to provide ecosystem goods and services for local land users. In rangelands, one important aspect is vegetation degradation, which reduces the land's capacity to support livestock. Thus, there is an urgent need to understand the complex dynamics and drivers of land degradation. In the past, both have been difficult to study due to the extensive spatial and temporal scales involved. In the last decade, a large number of remotely sensed imageries has become available for free, which enables a new approach to this topic. The aim of this research is to study land degradation as a multidimensional process incorporating its spatial and temporal components. We developed a methodological approach that makes use of long-term satellite Landsat data. Here, we use imagery of a typical degraded Mediterranean rangeland in Southern Cyprus (Randi Forest) for the years 1998-2015. We have chosen the NDVI as a proxy for vegetation greenness and applied different spatial landscape metrics to calculate changes in vegetation patterns over time. Further, we applied a time-series based approach (BFAST) on selected pixels, to look for sudden changes and trends in the vegetation dynamics. The results promoted our knowledge on how land degradation dynamics in Mediterranean rangelands can be captured through spatio-temporal vegetation dynamics and allowed us to select the most suitable metrics for further analysis. In the long-term, we aim at using Landsat satellite data covering 30 years. To gain a functional understanding of land degradation, we want to overlay our results from the remotely sensed data with results of an eco-hydrological model (SWAT).

Analysis of vegetation dynamics and climatic variability impacts on greenness across Canada using remotely sensed data from 2000 to 2009

NASA Astrophysics Data System (ADS)

Fang, Xiuqin; Zhu, Qiuan; Chen, Huai; Ma, Zhihai; Wang, Weifeng; Song, Xinzhang; Zhao, Pengxiang; Peng, Changhui

2014-01-01

Using time series of moderate-resolution imaging spectroradiometer (MODIS) normalized difference vegetation index (NDVI) data from 2000 to 2009, we assessed decadal vegetation dynamics across Canada and examined the relationship between NDVI and climatic variables (precipitation and temperature). The Palmer drought severity index and vapor pressure difference (VPD) were used to relate the vegetation changes to the climate, especially in cases of drought. Results indicated that MODIS NDVI measurements provided a dynamic picture of interannual variation in Canadian vegetation patterns. Greenness declined in 2000, 2002, and 2009 and increased in 2005, 2006, and 2008. Vegetation dynamics varied across regions during the period. Most forest land shows little change, while vegetation in the ecozone of Pacific Maritime, Prairies, and Taiga Shield shows more dynamics than in the others. Significant correlations were found between NDVI and the climatic variables. The variation of NDVI resulting from climatic variability was more highly correlated to temperature than to precipitation in most ecozones. Vegetation grows better with higher precipitation and temperature in almost all ecozones. However, vegetation grows worse under higher temperature in the Prairies ecozone. The annual changes in NDVI corresponded well with the change in VPD in most ecozones.

Impacts of Climate Change and Vegetation Dynamics on Runoff in the Mountainous Region of the Haihe River Basin in the Past Five Decades

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lei, Huimin; Yang, Dawen; Huang, Maoyi

2014-04-16

Climate and atmospheric CO2 concentration have changed significantly in the mountainous region of the Haihe River basin over the past five decades. In the study, a process-based terrestrial model, version 4 of the Community Land Model (CLM4), was used to quantify the spatiotemporal changes in runoff over the region, driven by the varying climate factors and CO2 concentration. Overall, our simulations suggest that climate-induced change in runoff in this region show a decreasing trend since 1960. Changes in precipitation, solar radiation, air temperature, and wind speed accounts for 56%, -14%, 13%, -5% of the overall decrease in annual runoff, respectively,more » but their relative contributions vary across the study area. Rising atmospheric CO2 concentration was found to have limited impacts on runoff. Significant decrease in runoff over the southern and northeastern portion of the region is primarily attributed to decreasing precipitation, while decreasing solar radiation and increasing air temperature are the main causes of slight runoff increase in the northern portion. Our results also suggest that the magnitude of decreasing trend could be greatly underestimated if the dynamical interactions of vegetation phenology with the environmental factors are not considered in the modeling, highlighting the importance of including dynamic vegetation phenology in the prediction of runoff in this region.« less

Braided river flow and invasive vegetation dynamics in the Southern Alps, New Zealand.

PubMed

Caruso, Brian S; Edmondson, Laura; Pithie, Callum

2013-07-01

In mountain braided rivers, extreme flow variability, floods and high flow pulses are fundamental elements of natural flow regimes and drivers of floodplain processes, understanding of which is essential for management and restoration. This study evaluated flow dynamics and invasive vegetation characteristics and changes in the Ahuriri River, a free-flowing braided, gravel-bed river in the Southern Alps of New Zealand's South Island. Sixty-seven flow metrics based on indicators of hydrologic alteration and environmental flow components (extreme low flows, low flows, high flow pulses, small floods and large floods) were analyzed using a 48-year flow record. Changes in the areal cover of floodplain and invasive vegetation classes and patch characteristics over 20 years (1991-2011) were quantified using five sets of aerial photographs, and the correlation between flow metrics and cover changes were evaluated. The river exhibits considerable hydrologic variability characteristic of mountain braided rivers, with large variation in floods and other flow regime metrics. The flow regime, including flood and high flow pulses, has variable effects on floodplain invasive vegetation, and creates dynamic patch mosaics that demonstrate the concepts of a shifting mosaic steady state and biogeomorphic succession. As much as 25 % of the vegetation cover was removed by the largest flood on record (570 m(3)/s, ~50-year return period), with preferential removal of lupin and less removal of willow. However, most of the vegetation regenerated and spread relatively quickly after floods. Some flow metrics analyzed were highly correlated with vegetation cover, and key metrics included the peak magnitude of the largest flood, flood frequency, and time since the last flood in the interval between photos. These metrics provided a simple multiple regression model of invasive vegetation cover in the aerial photos evaluated. Our analysis of relationships among flow regimes and invasive vegetation cover has implications for braided rivers impacted by hydroelectric power production, where increases in invasive vegetation cover are typically greater than in unimpacted rivers.

Short-term bryoid and vascular vegetation response to reforestation alternatives following wildfire in conifer plantations

Treesearch

Lori J. Kayes; Klaus J. Puettmann; Paul D. Anderson

2011-01-01

How are dynamics of early-seral post-fire vascular plant and bryoid (terrestrial mosses, lichens, and fungi) vegetation impacted by reforestation activities, particularly manual vegetation removal and planting density? Does the relationship between vegetation dynamics and vegetation removal differ between harsh (west-facing) and moderate (east-facing) aspects?...

The Functionally-Assembled Terrestrial Ecosystem Simulator Version 1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Xu, Chonggang; Christoffersen, Bradley

The Functionally-Assembled Terrestrial Ecosystem Simulator (FATES) is a vegetation model for use in Earth system models (ESMs). The model includes a size- and age-structured representation of tree dynamics, competition between functionally diverse plant functional types, and the biophysics underpinning plant growth, competition, mortality, as well as the carbon, water, and energy exchange with the atmosphere. The FATES model is designed as a modular vegetation model that can be integrated within a host land model for inclusion in ESMs. The model is designed for use in global change studies to understand and project the responses and feedbacks between terrestrial ecosystems andmore » the Earth system under changing climate and other forcings.« less

Towards an understanding of coupled physical and biological processes in the cultivated Sahel - 2. Vegetation and carbon dynamics

NASA Astrophysics Data System (ADS)

Boulain, N.; Cappelaere, B.; Ramier, D.; Issoufou, H. B. A.; Halilou, O.; Seghieri, J.; Guillemin, F.; Oï, M.; Gignoux, J.; Timouk, F.

2009-08-01

SummaryThis paper analyses the dynamics of vegetation and carbon during the West African monsoon season, for millet crop and fallow vegetation covers in the cultivated area of the Sahel. Comparing these two dominant land cover types informs on the impact of cultivation on productivity and carbon fluxes. Biomass, leaf area index (LAI) and carbon fluxes were monitored over a 2-year period for these two vegetation systems in the Wankama catchment of the AMMA (African monsoon multidisciplinary analyses) experimental super-site in West Niger. Carbon fluxes and water use efficiency observed at the field scale are confronted with ecophysiological measurements (photosynthetic response to light, and relation of water use efficiency to air humidity) made at the leaf scale for the dominant plant species in the two vegetation systems. The two rainy seasons monitored were dissimilar with respect to rain patterns, reflecting some of the interannual variability. Distinct responses in vegetation development and in carbon dynamics were observed between the two vegetation systems. Vegetation development in the fallow was found to depend more on rainfall distribution along the season than on its starting date. A quite opposite behaviour was observed for the crop vegetation: the date of first rain appears as a principal factor of millet growth. Carbon flux exchanges were well correlated to vegetation development. High responses of photosynthesis to light were observed for the dominant herbaceous and shrub species of the fallow at the leaf and field scales. Millet showed high response at the leaf scale, but a much lesser response at the field scale. This pattern, also observed for water use efficiency, is to be related to the low density of the millet cover. A simple LAI-based model for scaling up the photosynthetic response from leaf to field scale was found quite successful for the fallow, but was less conclusive for the crop, due to spatial variability of LAI. Time/space variations in leaf distribution for the dominant species are key to scale transition of carbon dynamics. Results obtained for the two vegetation covers are important in light of the major land use/cover change experienced in the Sahel region due to extensive savanna clearing for food production.

The role of riparian vegetation density, channel orientation and water velocity in determining river temperature dynamics

NASA Astrophysics Data System (ADS)

Garner, Grace; Malcolm, Iain A.; Sadler, Jonathan P.; Hannah, David M.

2017-10-01

A simulation experiment was used to understand the importance of riparian vegetation density, channel orientation and flow velocity for stream energy budgets and river temperature dynamics. Water temperature and meteorological observations were obtained in addition to hemispherical photographs along a ∼1 km reach of the Girnock Burn, a tributary of the Aberdeenshire Dee, Scotland. Data from nine hemispherical images (representing different uniform canopy density scenarios) were used to parameterise a deterministic net radiation model and simulate radiative fluxes. For each vegetation scenario, the effects of eight channel orientations were investigated by changing the position of north at 45° intervals in each hemispheric image. Simulated radiative fluxes and observed turbulent fluxes drove a high-resolution water temperature model of the reach. Simulations were performed under low and high water velocity scenarios. Both velocity scenarios yielded decreases in mean (≥1.6 °C) and maximum (≥3.0 °C) temperature as canopy density increased. Slow-flowing water resided longer within the reach, which enhanced heat accumulation and dissipation, and drove higher maximum and lower minimum temperatures. Intermediate levels of shade produced highly variable energy flux and water temperature dynamics depending on the channel orientation and thus the time of day when the channel was shaded. We demonstrate that in many reaches relatively sparse but strategically located vegetation could produce substantial reductions in maximum temperature and suggest that these criteria are used to inform future river management.

Improving dynamic global vegetation model (DGVM) simulation of western U.S. rangelands vegetation seasonal phenology and productivity

NASA Astrophysics Data System (ADS)

Kerns, B. K.; Kim, J. B.; Day, M. A.; Pitts, B.; Drapek, R. J.

2017-12-01

Ecosystem process models are increasingly being used in regional assessments to explore potential changes in future vegetation and NPP due to climate change. We use the dynamic global vegetation model MAPSS-Century 2 (MC2) as one line of evidence for regional climate change vulnerability assessments for the US Forest Service, focusing our fine tuning model calibration from observational sources related to forest vegetation. However, there is much interest in understanding projected changes for arid rangelands in the western US such as grasslands, shrublands, and woodlands. Rangelands provide many ecosystem service benefits and local rural human community sustainability, habitat for threatened and endangered species, and are threatened by annual grass invasion. Past work suggested MC2 performance related to arid rangeland plant functional types (PFT's) was poor, and the model has difficulty distinguishing annual versus perennial grasslands. Our objectives are to increase the model performance for rangeland simulations and explore the potential for splitting the grass plant functional type into annual and perennial. We used the tri-state Blue Mountain Ecoregion as our study area and maps of potential vegetation from interpolated ground data, the National Land Cover Data Database, and ancillary NPP data derived from the MODIS satellite. MC2 historical simulations for the area overestimated woodland occurrence and underestimated shrubland and grassland PFT's. The spatial location of the rangeland PFT's also often did not align well with observational data. While some disagreement may be due to differences in the respective classification rules, the errors are largely linked to MC2's tree and grass biogeography and physiology algorithms. Presently, only grass and forest productivity measures and carbon stocks are used to distinguish PFT's. MC2 grass and tree productivity simulation is problematic, in particular grass seasonal phenology in relation to seasonal patterns of temperature and precipitation. The algorithm also does not accurately translate simulated carbon stocks into the canopy allometry of woodland tree species that dominate the BME, thereby inaccurately shading out the grasses in the understory. We are devising improvements to these shortcomings in the model architecture.

PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.

2013-08-01

Elevated nitrogen deposition and climate change alter the vegetation communities and carbon (C) and nitrogen (N) cycling in peatlands. To address this issue we developed a new process-oriented biogeochemical model (PEATBOG) for analyzing coupled carbon and nitrogen dynamics in northern peatlands. The model consists of four submodels, which simulate: (1) daily water table depth and depth profiles of soil moisture, temperature and oxygen levels; (2) competition among three plants functional types (PFTs), production and litter production of plants; (3) decomposition of peat; and (4) production, consumption, diffusion and export of dissolved C and N species in soil water. The model is novel in the integration of the C and N cycles, the explicit spatial resolution belowground, the consistent conceptualization of movement of water and solutes, the incorporation of stoichiometric controls on elemental fluxes and a consistent conceptualization of C and N reactivity in vegetation and soil organic matter. The model was evaluated for the Mer Bleue Bog, near Ottawa, Ontario, with regards to simulation of soil moisture and temperature and the most important processes in the C and N cycles. Model sensitivity was tested for nitrogen input, precipitation, and temperature, and the choices of the most uncertain parameters were justified. A simulation of nitrogen deposition over 40 yr demonstrates the advantages of the PEATBOG model in tracking biogeochemical effects and vegetation change in the ecosystem.

PEATBOG: a biogeochemical model for analyzing coupled carbon and nitrogen dynamics in northern peatlands

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.

2013-03-01

Elevated nitrogen deposition and climate change alter the vegetation communities and carbon (C) and nitrogen (N) cycling in peatlands. To address this issue we developed a new process-oriented biogeochemical model (PEATBOG) for analyzing coupled carbon and nitrogen dynamics in northern peatlands. The model consists of four submodels, which simulate: (1) daily water table depth and depth profiles of soil moisture, temperature and oxygen levels; (2) competition among three plants functional types (PFTs), production and litter production of plants; (3) decomposition of peat; and (4) production, consumption, diffusion and export of dissolved C and N species in soil water. The model is novel in the integration of the C and N cycles, the explicit spatial resolution belowground, the consistent conceptualization of movement of water and solutes, the incorporation of stoichiometric controls on elemental fluxes and a consistent conceptualization of C and N reactivity in vegetation and soil organic matter. The model was evaluated for the Mer Bleue Bog, near Ottawa, Ontario, with regards to simulation of soil moisture and temperature and the most important processes in the C and N cycles. Model sensitivity was tested for nitrogen input, precipitation, and temperature, and the choices of the most uncertain parameters were justified. A simulation of nitrogen deposition over 40 yr demonstrates the advantages of the PEATBOG model in tracking biogeochemical effects and vegetation change in the ecosystem.

Floods and Fluvial Wood

NASA Astrophysics Data System (ADS)

Comiti, F.

2014-12-01

Several studies have recently addressed the complex interactions existing at various spatial scales among riparian vegetation, channel morphology and wood storage. The majority of these investigations has been carried out in relatively natural river systems, focusing mostly on the long-term vegetation-morphology dynamics under "equilibrium" conditions. Little is still known about the role of flood events - of different frequency/magnitude - on several aspects of such dynamics, e.g. entrainment conditions of in-channel wood, erosion rates of vegetation from channel margins and from islands, transport distances of wood elements of different size along the channel network. Even less understood is how the river's evolutionary trajectory may affect these processes, and thus the degree to which conceptual models derivable from near-natural systems could be applicable to human-disturbed channels. Indeed, the different human pressures - present on most river basins worldwide - have greatly impaired the morphological and ecological functions of fluvial wood, and the attempts to "restore" in-channel wood storage are currently carried out without a sufficient understanding of wood transport processes occurring during floods. On the other hand, the capability to correctly predict the magnitude of large wood transport during large floods is now seen as crucial - especially in mountain basins - for flood hazard mapping, as is the identification of the potential wood sources (e.g. landslides, floodplains, islands) for the implementation of sound and effective hazard mitigation measures. The presentation will first summarize the current knowledge on fluvial wood dynamics and modelling at different spatial and temporal scales, with a particular focus on mountain rivers. The effects of floods of different characteristics on vegetation erosion and wood transport will be then addressed presenting some study cases from rivers in the European Alps and in the Italian Apennines featuring different degrees of human alteration. Finally, several conclusions about the applicability of wood transport modelling and on rationale vegetation/wood management strategies will be drawn.

The Development in modeling Tibetan Plateau Land/Climate Interaction

NASA Astrophysics Data System (ADS)

Xue, Yongkang; Liu, Ye; li, qian; Maheswor Shrestha, Maheswor; Ma, Hsi-Yen; Cox, Peter; Sun, shufen; Koike, Toshio

2015-04-01

Tibetan Plateau (TP) plays an important role in influencing the continental and planetary scale climate, including East Asian and South Asian monsoon, circulation and precipitation over West Pacific and Indian Oceans. The numerical study has identified TP as the area with strongest land/atmosphere interactions over the midlatitude land. The land degradation there has also affected the monsoon precipitation in TP along the monsoon pathway. The water cycle there affects water sources for major Asian river systems, which include the Tarim, Amu Darya, Indus, Ganges, Brahmaputra, Irrawaddy, Salween, Mekong, Yellow, and Yangtze Rivers. Despite the importance of TP land process in the climate system, the TP land surface processes are poorly modeled due to lack of data available for model validation. To better understand, simulate, and project the role of Tibetan Plateau land surface processes, better parameterization of the Tibetan Land surface processes have been developed and evaluated. The recently available field measurement there and satellite observation have greatly helped this development. This paper presents these new developments and preliminary results using the newly developed biophysical/dynamic vegetation model, frozen soil model, and glacier model. In recent CMIP5 simulation, the CMIP5 models with dynamic vegetation model show poor performance in simulating the TP vegetation and climate. To better simulate the TP vegetation condition and its interaction with climate, we have developed biophysical/dynamic vegetation model, the Simplified Simple Biosphere Model version 4/Top-down Representation of Interactive Foliage and Flora Including Dynamics Model (SSiB4/TRIFFID), based on water, carbon, and energy balance. The simulated vegetation variables are updates, driven by carbon assimilation, allocation, and accumulation, as well as competition between plant functional types. The model has been validated with the station data, including those measured over the TP. The offline SSiB4/TRIFFID is integrated using the observed precipitation and reanalysis-based meteorological forcing from 1948 to 2008 with 1 degree horizontal resolution. The simulated vegetation conditions and surface hydrology are compared well with observational data with some bias, and shows strong decadal and interannual variabilities with a linear trend associated with the global warming. The TP region is covered by both discontinuous and sporadic permafrost with irregular snow layers above. A frozen soil model is developed to take the coupling effect of mass and heat transport into consideration and includes a detailed description of mass balances of volumetric liquid water, ice, as well as vapor content. It also considers contributions' of heat conduction to the energy balance. The model has been extensively tested using a number of TP station data, which included soil temperature and soil water measurements. The results suggest that it is important to include the frozen sol process to adequately simulate the surface energy balance during the freezing and thawing periods and surface temperature variability, including its diurnal variation. Issues in simulating permafrost process will also be addressed. To better understand the glacier variations under climate change scenarios, an integrated modeling system with an energy budget-based multilayer scheme for clean glaciers, a single-layer scheme for debris-covered glaciers and multilayer scheme for seasonal snow over glacier, soil and forest are developed within a distributed biosphere hydrological modeling framework (WEB-DHM-S model). Discharge simulations using this model show good agreement with observations for Hunza River Basin (13,733 km2) in the Karakoram region of Pakistan for three hydrologic years (2002-2004). Flow composition analysis reveals that the runoff regime is strongly controlled by the snow and glacier melt runoff (50% snowmelt and 33% glacier melt) and suggests that both topography and glacier hypsometry play key roles in glacier mass balance. This study provides a basis for potential application of such an integrated model to the entire Hindu-Kush-Karakoram-Himalaya region.

Assessing the Three-North Shelter Forest Program in China by a novel framework for characterizing vegetation changes

NASA Astrophysics Data System (ADS)

Qiu, Bingwen; Chen, Gong; Tang, Zhenghong; Lu, Difei; Wang, Zhuangzhuang; Chen, Chongchen

2017-11-01

The Three-North Shelter Forest Program (TNSFP) in China has been intensely invested for approximately 40 years. However, the efficacy of the TNSFP has been debatable due to the spatiotemporal complexity of vegetation changes. A novel framework was proposed for characterizing vegetation changes in the TNSFP region through Combining Trend and Temporal Similarity trajectory (COTTS). This framework could automatically and continuously address the fundamental questions on where, what, how and when vegetation changes have occurred. Vegetation trend was measured by a non-parametric method. The temporal similarity trajectory was tracked by the Jeffries-Matusita (JM) distance of the inter-annual vegetation indices temporal profiles and modeled using the logistic function. The COTTS approach was applied to examine the afforestation efforts of the TNSFP using 500 m 8-day composites MODIS datasets from 2001 to 2015. Accuracy assessment from the 1109 reference sites reveals that the COTTS is capable of automatically determining vegetation dynamic patterns, with an overall accuracy of 90.08% and a kappa coefficient of 0.8688. The efficacy of the TNSFP was evaluated through comprehensive considerations of vegetation, soil and wetness. Around 45.78% areas obtained increasing vegetation trend, 2.96% areas achieved bare soil decline and 4.50% areas exhibited increasing surface wetness. There were 4.49% areas under vegetation degradation & desertification. Spatiotemporal heterogeneity of efficacy of the TNSFP was revealed: great vegetation gain through the abrupt dynamic pattern in the semi-humid and humid regions, bare soil decline & potential efficacy in the semi-arid region and remarkable efficacy in functional region of Eastern Ordos.

Negative plant soil feedback explaining ring formation in clonal plants.

PubMed

Cartenì, Fabrizio; Marasco, Addolorata; Bonanomi, Giuliano; Mazzoleni, Stefano; Rietkerk, Max; Giannino, Francesco

2012-11-21

Ring shaped patches of clonal plants have been reported in different environments, but the mechanisms underlying such pattern formation are still poorly explained. Water depletion in the inner tussocks zone has been proposed as a possible cause, although ring patterns have been also observed in ecosystems without limiting water conditions. In this work, a spatially explicit model is presented in order to investigate the role of negative plant-soil feedback as an additional explanation for ring formation. The model describes the dynamics of the plant biomass in the presence of toxicity produced by the decomposition of accumulated litter in the soil. Our model qualitatively reproduces the emergence of ring patterns of a single clonal plant species during colonisation of a bare substrate. The model admits two homogeneous stationary solutions representing bare soil and uniform vegetation cover which depend only on the ratio between the biomass death and growth rates. Moreover, differently from other plant spatial patterns models, but in agreement with real field observations of vegetation dynamics, we demonstrated that the pattern dynamics always lead to spatially homogeneous vegetation covers without creation of stable Turing patterns. Analytical results show that ring formation is a function of two main components, the plant specific susceptibility to toxic compounds released in the soil by the accumulated litter and the decay rate of these same compounds, depending on environmental conditions. These components act at the same time and their respective intensities can give rise to the different ring structures observed in nature, ranging from slight reductions of biomass in patch centres, to the appearance of marked rings with bare inner zones, as well as the occurrence of ephemeral waves of plant cover. Our results highlight the potential role of plant-soil negative feedback depending on decomposition processes for the development of transient vegetation patterns. Copyright © 2012 Elsevier Ltd. All rights reserved.

The role of reproductive plant traits and biotic interactions in the dynamics of semi-arid plant communities.

PubMed

Pueyo, Y; Kéfi, S; Díaz-Sierra, R; Alados, C L; Rietkerk, M

2010-12-01

The dynamics of semi-arid plant communities are determined by the interplay between competition and facilitation among plants. The sign and strength of these biotic interactions depend on plant traits. However, the relationships between plant traits and biotic interactions, and the consequences for plant communities are still poorly understood. Our objective here was to investigate, with a modelling approach, the role of plant reproductive traits on biotic interactions, and the consequences for processes such as plant succession and invasion. The dynamics of two plant types were modelled with a spatially-explicit integrodifferential model: (1) a plant with seed dispersal (colonizer of bare soil) and (2) a plant with local vegetative propagation (local competitor). Both plant types were involved in facilitation due to a local positive feedback between vegetation biomass and soil water availability, which promoted establishment and growth. Plants in the system also competed for limited water. The efficiency in water acquisition (dependent on reproductive and growth plant traits) determined which plant type dominated the community at the steady state. Facilitative interactions between plant types also played an important role in the community dynamics, promoting establishment in the driest conditions and recovery from low biomass. Plants with vegetative propagation took advantage of the ability of seed dispersers to establish on bare soil from a low initial biomass. Seed dispersers were good invaders, maintained high biomass at intermediate and high rainfall and showed a high ability in taking profit from the positive feedback originated by plants with vegetative propagation under the driest conditions. However, seed dispersers lost competitiveness with an increasing investment in fecundity. All together, our results showed that reproductive plant traits can affect the balance between facilitative and competitive interactions. Understanding this effect of plant traits on biotic interactions provides insights in processes such as plant succession and shrub encroachment. Copyright © 2010 Elsevier Inc. All rights reserved.

Chapter 2: Dynamic vegetation modeling of forest, woodland, shrubland, and grassland vegetation communities in the Pacific Northwest and Southwest Regions of the United States

Treesearch

Theresa K. Burcsu; Joshua S. Halofsky; Simon A. Bisrat; Treg A. Christopher; Megan K. Creutzburg; Emilie B. Henderson; Miles A. Hemstrom; F. Jack Triepke; Melissa Whitman

2014-01-01

Land management planning at broad scales requires integrative techniques to understand and synthesize the effects of different land management activities and address socioeconomic and conservation concerns. The Integrated Landscape Assessment Project was developed to support the vital but complex task of broadscale integration of information to assess ecological...

Gradient Analysis and Classification of Carolina Bay Vegetation: A Framework for Bay Wetlands Conservation and Restoration

DOE Office of Scientific and Technical Information (OSTI.GOV)

Diane De Steven,Ph.D.; Maureen Tone,PhD.

1997-10-01

This report address four project objectives: (1) Gradient model of Carolina bay vegetation on the SRS--The authors use ordination analyses to identify environmental and landscape factors that are correlated with vegetation composition. Significant factors can provide a framework for site-based conservation of existing diversity, and they may also be useful site predictors for potential vegetation in bay restorations. (2) Regional analysis of Carolina bay vegetation diversity--They expand the ordination analyses to assess the degree to which SRS bays encompass the range of vegetation diversity found in the regional landscape of South Carolina's western Upper Coastal Plain. Such comparisons can indicatemore » floristic status relative to regional potentials and identify missing species or community elements that might be re-introduced or restored. (3) Classification of vegetation communities in Upper Coastal Plain bays--They use cluster analysis to identify plant community-types at the regional scale, and explore how this classification may be functional with respect to significant environmental and landscape factors. An environmentally-based classification at the whole-bay level can provide a system of templates for managing bays as individual units and for restoring bays to desired plant communities. (4) Qualitative model for bay vegetation dynamics--They analyze present-day vegetation in relation to historic land uses and disturbances. The distinctive history of SRS bays provides the possibility of assessing pathways of post-disturbance succession. They attempt to develop a coarse-scale model of vegetation shifts in response to changing site factors; such qualitative models can provide a basis for suggesting management interventions that may be needed to maintain desired vegetation in protected or restored bays.« less

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

Modeling aeolian transport in response to succession, disturbance and future climate: Dynamic long-term risk assessment for contaminant redistribution

USGS Publications Warehouse

Breshears, D.D.; Kirchner, T.B.; Whicker, J.J.; Field, J.P.; Allen, Craig D.

2012-01-01

Aeolian sediment transport is a fundamental process redistributing sediment, nutrients, and contaminants in dryland ecosystems. Over time frames of centuries or longer, horizontal sediment fluxes and associated rates of contaminant transport are likely to be influenced by succession, disturbances, and changes in climate, yet models of horizontal sediment transport that account for these fundamental factors are lacking, precluding in large part accurate assessment of human health risks associated with persistent soil-bound contaminants. We present a simple model based on empirical measurements of horizontal sediment transport (predominantly saltation) to predict potential contaminant transport rates for recently disturbed sites such as a landfill cover. Omnidirectional transport is estimated within vegetation that changes using a simple Markov model that simulates successional trajectory and considers three types of short-term disturbances (surface fire, crown fire, and drought-induced plant mortality) under current and projected climates. The model results highlight that movement of contaminated soil is sensitive to vegetation dynamics and increases substantially (e.g., > fivefold) when disturbance and/or future climate are considered. The time-dependent responses in horizontal sediment fluxes and associated contaminant fluxes were sensitive to variability in the timing of disturbance, with longer intervals between disturbance allowing woody plants to become dominant and crown fire and drought abruptly reducing woody plant cover. Our results, which have direct implications for contaminant transport and landfill management in the specific context of our assessment, also have general relevance because they highlight the need to more fully account for vegetation dynamics, disturbance, and changing climate in aeolian process studies.

Climate and anthropogenic impacts on forest vegetation derived from satellite data

NASA Astrophysics Data System (ADS)

Zoran, M.; Savastru, R.; Savastru, D.; Tautan, M.; Miclos, S.; Baschir, L.

2010-09-01

Vegetation and climate interact through a series of complex feedbacks, which are not very well understood. The patterns of forest vegetation are largely determined by temperature, precipitation, solar irradiance, soil conditions and CO2 concentration. Vegetation impacts climate directly through moisture, energy, and momentum exchanges with the atmosphere and indirectly through biogeochemical processes that alter atmospheric CO2 concentration. Changes in forest vegetation land cover/use alter the surface albedo and radiation fluxes, leading to a local temperature change and eventually a vegetation response. This albedo (energy) feedback is particularly important when forests mask snow cover. Forest vegetation-climate feedback regimes are designated based on the temporal correlations between the vegetation and the surface temperature and precipitation. The different feedback regimes are linked to the relative importance of vegetation and soil moisture in determining land-atmosphere interactions. Forest vegetation phenology constitutes an efficient bio-indicator of impacts of climate and anthropogenic changes and a key parameter for understanding and modeling vegetation-climate interactions. Climate variability represents the ensemble of net radiation, precipitation, wind and temperature characteristic for a region in a certain time scale (e.g.monthly, seasonal annual). The temporal and/or spatial sensitivity of forest vegetation dynamics to climate variability is used to characterize the quantitative relationship between these two quantities in temporal and/or spatial scales. So, climate variability has a great impact on the forest vegetation dynamics. Satellite remote sensing is a very useful tool to assess the main phenological events based on tracking significant changes on temporal trajectories of Normalized Difference Vegetation Index (NDVIs), which requires NDVI time-series with good time resolution, over homogeneous area, cloud-free and not affected by atmospheric and geometric effects and variations in sensor characteristics (calibration, spectral responses). Spatio-temporal forest vegetation dynamics have been quantified as the total amount of vegetation (mean NDVI) and the seasonal difference (annual NDVI amplitude) by a time series analysis of NDVI satellite images over 1989 - 2009 period for a forest ecosystem placed in the North-Eastern part of Bucharest town, Romania, from IKONOS and LANDSAT TM and ETM satellite images and meteorological data. A climate indicator (CI) was created from meteorological data (precipitation over net radiation). The relationships between the vegetation dynamics and the CI have been determined spatially and temporally. The driest test regions prove to be the most sensitive to climate impact. The spatial and temporal patterns of the mean NDVI are the same, while they are partially different for the seasonal difference. For investigated test area, considerable NDVI decline was observed for drought events during 2003 and 2007 years. Under stress conditions, it is evident that environmental factors such as soil type, parent material, and topography are not correlated with NDVI dynamics. Specific aim of this paper was to assess, forecast, and mitigate the risks of climatic changes on forest systems and its biodiversity as well as on adjacent environment areas and to provide early warning strategies on the basis of spectral information derived from satellite data regarding atmospheric effects of forest biome degradation .

Transition from Connected to Fragmented Vegetation across an Environmental Gradient: Scaling Laws in Ecotone Geometry.

PubMed

Gastner, Michael T; Oborny, Beata; Zimmermann, D K; Pruessner, Gunnar

2009-07-01

A change in the environmental conditions across space-for example, altitude or latitude-can cause significant changes in the density of a vegetation type and, consequently, in spatial connectivity. We use spatially explicit simulations to study the transition from connected to fragmented vegetation. A static (gradient percolation) model is compared to dynamic (gradient contact process) models. Connectivity is characterized from the perspective of various species that use this vegetation type for habitat and differ in dispersal or migration range, that is, "step length" across the landscape. The boundary of connected vegetation delineated by a particular step length is termed the " hull edge." We found that for every step length and for every gradient, the hull edge is a fractal with dimension 7/4. The result is the same for different spatial models, suggesting that there are universal laws in ecotone geometry. To demonstrate that the model is applicable to real data, a hull edge of fractal dimension 7/4 is shown on a satellite image of a piñon-juniper woodland on a hillside. We propose to use the hull edge to define the boundary of a vegetation type unambiguously. This offers a new tool for detecting a shift of the boundary due to a climate change.

Improving the prediction of African savanna vegetation variables using time series of MODIS products

NASA Astrophysics Data System (ADS)

Tsalyuk, Miriam; Kelly, Maggi; Getz, Wayne M.

2017-09-01

African savanna vegetation is subject to extensive degradation as a result of rapid climate and land use change. To better understand these changes detailed assessment of vegetation structure is needed across an extensive spatial scale and at a fine temporal resolution. Applying remote sensing techniques to savanna vegetation is challenging due to sparse cover, high background soil signal, and difficulty to differentiate between spectral signals of bare soil and dry vegetation. In this paper, we attempt to resolve these challenges by analyzing time series of four MODIS Vegetation Products (VPs): Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Leaf Area Index (LAI), and Fraction of Photosynthetically Active Radiation (FPAR) for Etosha National Park, a semiarid savanna in north-central Namibia. We create models to predict the density, cover, and biomass of the main savanna vegetation forms: grass, shrubs, and trees. To calibrate remote sensing data we developed an extensive and relatively rapid field methodology and measured herbaceous and woody vegetation during both the dry and wet seasons. We compared the efficacy of the four MODIS-derived VPs in predicting vegetation field measured variables. We then compared the optimal time span of VP time series to predict ground-measured vegetation. We found that Multiyear Partial Least Square Regression (PLSR) models were superior to single year or single date models. Our results show that NDVI-based PLSR models yield robust prediction of tree density (R2 = 0.79, relative Root Mean Square Error, rRMSE = 1.9%) and tree cover (R2 = 0.78, rRMSE = 0.3%). EVI provided the best model for shrub density (R2 = 0.82) and shrub cover (R2 = 0.83), but was only marginally superior over models based on other VPs. FPAR was the best predictor of vegetation biomass of trees (R2 = 0.76), shrubs (R2 = 0.83), and grass (R2 = 0.91). Finally, we addressed an enduring challenge in the remote sensing of semiarid vegetation by examining the transferability of predictive models through space and time. Our results show that models created in the wetter part of Etosha could accurately predict trees' and shrubs' variables in the drier part of the reserve and vice versa. Moreover, our results demonstrate that models created for vegetation variables in the dry season of 2011 could be successfully applied to predict vegetation in the wet season of 2012. We conclude that extensive field data combined with multiyear time series of MODIS vegetation products can produce robust predictive models for multiple vegetation forms in the African savanna. These methods advance the monitoring of savanna vegetation dynamics and contribute to improved management and conservation of these valuable ecosystems.

Vegetation dynamics under fire exclusion and logging in a Rocky Mountain watershed, 1856-1996

USGS Publications Warehouse

Gallant, Alisa L.; Hansen, A.J.; Councilman, J.S.; Monte, D.K.; Betz, D.W.

2003-01-01

How have changes in land management practices affected vegetation patterns in the greater Yellowstone ecosystem? This question led us to develop a deterministic, successional, vegetation model to “turn back the clock” on a study area and assess how patterns in vegetation cover type and structure have changed through different periods of management. Our modeling spanned the closing decades of use by Native Americans, subsequent Euro-American settlement, and associated indirect methods of fire suppression, and more recent practices of fire exclusion and timber harvest. Model results were striking, indicating that the primary forest dynamic in the study area is not fragmentation of conifer forest by logging, but the transition from a fire-driven mosaic of grassland, shrubland, broadleaf forest, and mixed forest communities to a conifer-dominated landscape. Projections for conifer-dominated stands showed an increase in areal coverage from 15% of the study area in the mid-1800s to ∼50% by the mid-1990s. During the same period, projections for aspen-dominated stands showed a decline in coverage from 37% to 8%. Substantial acreage previously occupied by a variety of age classes has given way to extensive tracts of mature forest. Only 4% of the study area is currently covered by young stands, all of which are coniferous. While logging has replaced wildfire as a mechanism for cycling younger stands into the landscape, the locations, species constituents, patch sizes, and ecosystem dynamics associated with logging do not mimic those associated with fire. It is also apparent that the nature of these differences varies among biophysical settings, and that land managers might consider a biophysical class strategy for tailoring management goals and restoration efforts.

Ages and transit times as important diagnostics of model performance for predicting carbon dynamics in terrestrial vegetation models

NASA Astrophysics Data System (ADS)

Ceballos-Núñez, Verónika; Richardson, Andrew D.; Sierra, Carlos A.

2018-03-01

The global carbon cycle is strongly controlled by the source/sink strength of vegetation as well as the capacity of terrestrial ecosystems to retain this carbon. These dynamics, as well as processes such as the mixing of old and newly fixed carbon, have been studied using ecosystem models, but different assumptions regarding the carbon allocation strategies and other model structures may result in highly divergent model predictions. We assessed the influence of three different carbon allocation schemes on the C cycling in vegetation. First, we described each model with a set of ordinary differential equations. Second, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find suitable parameters for the different model structures. And third, we calculated C stocks, release fluxes, radiocarbon values (based on the bomb spike), ages, and transit times. We obtained model simulations in accordance with the available data, but the time series of C in foliage and wood need to be complemented with other ecosystem compartments in order to reduce the high parameter collinearity that we observed, and reduce model equifinality. Although the simulated C stocks in ecosystem compartments were similar, the different model structures resulted in very different predictions of age and transit time distributions. In particular, the inclusion of two storage compartments resulted in the prediction of a system mean age that was 12-20 years older than in the models with one or no storage compartments. The age of carbon in the wood compartment of this model was also distributed towards older ages, whereas fast cycling compartments had an age distribution that did not exceed 5 years. As expected, models with C distributed towards older ages also had longer transit times. These results suggest that ages and transit times, which can be indirectly measured using isotope tracers, serve as important diagnostics of model structure and could largely help to reduce uncertainties in model predictions. Furthermore, by considering age and transit times of C in vegetation compartments as distributions, not only their mean values, we obtain additional insights into the temporal dynamics of carbon use, storage, and allocation to plant parts, which not only depends on the rate at which this C is transferred in and out of the compartments but also on the stochastic nature of the process itself.

Vegetation/Ecosystem Modeling and Analysis Project:Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling

NASA Astrophysics Data System (ADS)

1995-12-01

We compare the simulations of three biogeography models (BIOME2, Dynamic Global Phytogeography Model (DOLY), and Mapped Atmosphere-Plant Soil System (MAPSS)) and three biogeochemistry models (BIOME-BGC (BioGeochemistry Cycles), CENTURY, and Terrestrial Ecosystem Model (TEM)) for the conterminous United States under contemporary conditions of atmospheric CO2 and climate. We also compare the simulations of these models under doubled CO2 and a range of climate scenarios. For contemporary conditions, the biogeography models successfully simulate the geographic distribution of major vegetation types and have similar estimates of area for forests (42 to 46% of the conterminous United States), grasslands (17 to 27%), savannas (15 to 25%), and shrublands (14 to 18%). The biogeochemistry models estimate similar continental-scale net primary production (NPP; 3125 to 3772 × 1012 gC yr-1) and total carbon storage (108 to 118 × 1015 gC) for contemporary conditions. Among the scenarios of doubled CO2 and associated equilibrium climates produced by the three general circulation models (Oregon State University (OSU), Geophysical Fluid Dynamics Laboratory (GFDL), and United Kingdom Meteorological Office (UKMO)), all three biogeography models show both gains and losses of total forest area depending on the scenario (between 38 and 53% of conterminous United States area). The only consistent gains in forest area with all three models (BIOME2, DOLY, and MAPSS) were under the GFDL scenario due to large increases in precipitation. MAPSS lost forest area under UKMO, DOLY under OSU, and BIOME2 under both UKMO and OSU. The variability in forest area estimates occurs because the hydrologic cycles of the biogeography models have different sensitivities to increases in temperature and CO2. However, in general, the biogeography models produced broadly similar results when incorporating both climate change and elevated CO2 concentrations. For these scenarios, the NPP estimated by the biogeochemistry models increases between 2% (BIOME-BGC with UKMO climate) and 35% (TEM with UKMO climate). Changes in total carbon storage range from losses of 33% (BIOME-BGC with UKMO climate) to gains of 16% (TEM with OSU climate). The CENTURY responses of NPP and carbon storage are positive and intermediate to the responses of BIOME-BGC and TEM. The variability in carbon cycle responses occurs because the hydrologic and nitrogen cycles of the biogeochemistry models have different sensitivities to increases in temperature and CO2. When the biogeochemistry models are run with the vegetation distributions of the biogeography models, NPP ranges from no response (BIOME-BGC with all three biogeography model vegetations for UKMO climate) to increases of 40% (TEM with MAPSS vegetation for OSU climate). The total carbon storage response ranges from a decrease of 39% (BIOME-BGC with MAPSS vegetation for UKMO climate) to an increase of 32% (TEM with MAPSS vegetation for OSU and GFDL climates). The UKMO responses of BIOME-BGC with MAPSS vegetation are primarily caused by decreases in forested area and temperature-induced water stress. The OSU and GFDL responses of TEM with MAPSS vegetations are primarily caused by forest expansion and temperature-enhanced nitrogen cycling.

Vegetation/ecosystem modeling and analysis project: Comparing biogeography and biogeochemistry models in a continental-scale study of terrestrial ecosystem responses to climate change and CO2 doubling

NASA Astrophysics Data System (ADS)

Melillo, J. M.; Borchers, J.; Chaney, J.; Fisher, H.; Fox, S.; Haxeltine, A.; Janetos, A.; Kicklighter, D. W.; Kittel, T. G. F.; McGuire, A. D.; McKeown, R.; Neilson, R.; Nemani, R.; Ojima, D. S.; Painter, T.

1995-12-01

We compare the simulations of three biogeography models (BIOME2, Dynamic Global Phytogeography Model (DOLY), and Mapped Atmosphere-Plant Soil System (MAPSS)) and three biogeochemistry models (BIOME-BGC (BioGeochemistry Cycles), CENTURY, and Terrestrial Ecosystem Model (TEM)) for the conterminous United States under contemporary conditions of atmospheric CO2 and climate. We also compare the simulations of these models under doubled CO2 and a range of climate scenarios. For contemporary conditions, the biogeography models successfully simulate the geographic distribution of major vegetation types and have similar estimates of area for forests (42 to 46% of the conterminous United States), grasslands (17 to 27%), savannas (15 to 25%), and shrublands (14 to 18%). The biogeochemistry models estimate similar continental-scale net primary production (NPP; 3125 to 3772×1012 gCyr-1) and total carbon storage (108 to 118×1015 gC) for contemporary conditions. Among the scenarios of doubled CO2 and associated equilibrium climates produced by the three general circulation models (Oregon State University (OSU), Geophysical Fluid Dynamics Laboratory (GFDL), and United Kingdom Meteorological Office (UKMO)), all three biogeography models show both gains and losses of total forest area depending on the scenario (between 38 and 53% of conterminous United States area). The only consistent gains in forest area with all three models (BIOME2, DOLY, and MAPSS) were under the GFDL scenario due to large increases in precipitation. MAPSS lost forest area under UKMO, DOLY under OSU, and BIOME2 under both UKMO and OSU. The variability in forest area estimates occurs because the hydrologic cycles of the biogeography models have different sensitivities to increases in temperature and CO2. However, in general, the biogeography models produced broadly similar results when incorporating both climate change and elevated CO2 concentrations. For these scenarios, the NPP estimated by the biogeochemistry models increases between 2% (BIOME-BGC with UKMO climate) and 35% (TEM with UKMO climate). Changes in total carbon storage range from losses of 33% (BIOME-BGC with UKMO climate) to gains of 16% (TEM with OSU climate). The CENTURY responses of NPP and carbon storage are positive and intermediate to the responses of BIOME-BGC and TEM. The variability in carbon cycle responses occurs because the hydrologic and nitrogen cycles of the biogeochemistry models have different sensitivities to increases in temperature and CO2. When the biogeochemistry models are run with the vegetation distributions of the biogeography models, NPP ranges from no response (BIOME-BGC with all three biogeography model vegetations for UKMO climate) to increases of 40% (TEM with MAPSS vegetation for OSU climate). The total carbon storage response ranges from a decrease of 39% (BIOME-BGC with MAPSS vegetation for UKMO climate) to an increase of 32% (TEM with MAPSS vegetation for OSU and GFDL climates). The UKMO responses of BIOME-BGC with MAPSS vegetation are primarily caused by decreases in forested area and temperature-induced water stress. The OSU and GFDL responses of TEM with MAPSS vegetations are primarily caused by forest expansion and temperature-enhanced nitrogen cycling.

A further assessment of vegetation feedback on decadal Sahel rainfall variability

NASA Astrophysics Data System (ADS)

Kucharski, Fred; Zeng, Ning; Kalnay, Eugenia

2013-03-01

The effect of vegetation feedback on decadal-scale Sahel rainfall variability is analyzed using an ensemble of climate model simulations in which the atmospheric general circulation model ICTPAGCM ("SPEEDY") is coupled to the dynamic vegetation model VEGAS to represent feedbacks from surface albedo change and evapotranspiration, forced externally by observed sea surface temperature (SST) changes. In the control experiment, where the full vegetation feedback is included, the ensemble is consistent with the observed decadal rainfall variability, with a forced component 60 % of the observed variability. In a sensitivity experiment where climatological vegetation cover and albedo are prescribed from the control experiment, the ensemble of simulations is not consistent with the observations because of strongly reduced amplitude of decadal rainfall variability, and the forced component drops to 35 % of the observed variability. The decadal rainfall variability is driven by SST forcing, but significantly enhanced by land-surface feedbacks. Both, local evaporation and moisture flux convergence changes are important for the total rainfall response. Also the internal decadal variability across the ensemble members (not SST-forced) is much stronger in the control experiment compared with the one where vegetation cover and albedo are prescribed. It is further shown that this positive vegetation feedback is physically related to the albedo feedback, supporting the Charney hypothesis.

Impacts of peatland and permafrost changes on the terrestrial carbon storage over the last 21 ka

NASA Astrophysics Data System (ADS)

Spahni, Renato; Stocker, Benjamin D.; Joos, Fortunat

2014-05-01

Paleoclimate records and global climate-carbon cycle models suggest a net increase in land carbon (C) storage between 300 and 700 Pg C (1 Pg C = 1015 g C) during the transition from the last glacial maximum (LGM), the Holocene up to the preindustrial period. Peat accumulation rate records imply an increase in peatland C of ~600 Pg C over the course of the Holocene. In high northern latitudes mineral and organic soils are subject to permafrost formation, which is believed to have been more extensive during glacial compared to interglacial periods. Soil C in permafrost regions represents the largest inert C pool on land at present. The spatio-temporal evolution, however, of C stocks in soils and vegetation remains poorly quantified and is uncertain. Here, the Land surface Processes and eXchanges (LPX-Bern) Dynamic Global Vegetation Model is applied in transient simulations to explore the evolution of permafrost, peatland and vegetation C over the last 21'000 years. The model is forced with temperature and precipitation output from the Trace-21ka climate simulation, and dynamically simulates the formation and disappearance of peatlands and permafrost soils, vegetation distribution and C stocks. Results indicate that peatlands and permfrost areas existed further south in the LGM, in agreement with available proxy information, and that their associated C was lost during the transition into the Holocene. The simulated loss of inert C is over-compensated by vegetation regrowth. The timing of the C relocation on land is compared to observational evidence from paleoclimate archives and estimates from ocean C inventory changes.

Shifts in wind energy potential following land-use driven vegetation dynamics in complex terrain.

PubMed

Fang, Jiannong; Peringer, Alexander; Stupariu, Mihai-Sorin; Pǎtru-Stupariu, Ileana; Buttler, Alexandre; Golay, Francois; Porté-Agel, Fernando

2018-10-15

Many mountainous regions with high wind energy potential are characterized by multi-scale variabilities of vegetation in both spatial and time dimensions, which strongly affect the spatial distribution of wind resource and its time evolution. To this end, we developed a coupled interdisciplinary modeling framework capable of assessing the shifts in wind energy potential following land-use driven vegetation dynamics in complex mountain terrain. It was applied to a case study area in the Romanian Carpathians. The results show that the overall shifts in wind energy potential following the changes of vegetation pattern due to different land-use policies can be dramatic. This suggests that the planning of wind energy project should be integrated with the land-use planning at a specific site to ensure that the expected energy production of the planned wind farm can be reached over its entire lifetime. Moreover, the changes in the spatial distribution of wind and turbulence under different scenarios of land-use are complex, and they must be taken into account in the micro-siting of wind turbines to maximize wind energy production and minimize fatigue loads (and associated maintenance costs). The proposed new modeling framework offers, for the first time, a powerful tool for assessing long-term variability in local wind energy potential that emerges from land-use change driven vegetation dynamics over complex terrain. Following a previously unexplored pathway of cause-effect relationships, it demonstrates a new linkage of agro- and forest policies in landscape development with an ultimate trade-off between renewable energy production and biodiversity targets. Moreover, it can be extended to study the potential effects of micro-climatic changes associated with wind farms on vegetation development (growth and patterning), which could in turn have a long-term feedback effect on wind resource distribution in mountainous regions. Copyright © 2018 Elsevier B.V. All rights reserved.

Evaluation of the New Dynamic Global Vegetation Model in CAS-ESM

NASA Astrophysics Data System (ADS)

Zhu, Jiawen; Zeng, Xiaodong; Zhang, Minghua; Dai, Yongjiu; Ji, Duoying; Li, Fang; Zhang, Qian; Zhang, He; Song, Xiang

2018-06-01

In the past several decades, dynamic global vegetation models (DGVMs) have been the most widely used and appropriate tool at the global scale to investigate vegetation-climate interactions. At the Institute of Atmospheric Physics, a new version of DGVM (IAP-DGVM) has been developed and coupled to the Common Land Model (CoLM) within the framework of the Chinese Academy of Sciences' Earth System Model (CAS-ESM). This work reports the performance of IAP-DGVM through comparisons with that of the default DGVM of CoLM (CoLM-DGVM) and observations. With respect to CoLMDGVM, IAP-DGVM simulated fewer tropical trees, more "needleleaf evergreen boreal tree" and "broadleaf deciduous boreal shrub", and a better representation of grasses. These contributed to a more realistic vegetation distribution in IAP-DGVM, including spatial patterns, total areas, and compositions. Moreover, IAP-DGVM also produced more accurate carbon fluxes than CoLM-DGVM when compared with observational estimates. Gross primary productivity and net primary production in IAP-DGVM were in better agreement with observations than those of CoLM-DGVM, and the tropical pattern of fire carbon emissions in IAP-DGVM was much more consistent with the observation than that in CoLM-DGVM. The leaf area index simulated by IAP-DGVM was closer to the observation than that of CoLM-DGVM; however, both simulated values about twice as large as in the observation. This evaluation provides valuable information for the application of CAS-ESM, as well as for other model communities in terms of a comparative benchmark.

Ecohydrologic role of solar radiation on landscape evolution

NASA Astrophysics Data System (ADS)

Yetemen, Omer; Istanbulluoglu, Erkan; Flores-Cervantes, J. Homero; Vivoni, Enrique R.; Bras, Rafael L.

2015-02-01

Solar radiation has a clear signature on the spatial organization of ecohydrologic fluxes, vegetation patterns and dynamics, and landscape morphology in semiarid ecosystems. Existing landscape evolution models (LEMs) do not explicitly consider spatially explicit solar radiation as model forcing. Here, we improve an existing LEM to represent coupled processes of energy, water, and sediment balance for semiarid fluvial catchments. To ground model predictions, a study site is selected in central New Mexico where hillslope aspect has a marked influence on vegetation patterns and landscape morphology. Model predictions are corroborated using limited field observations in central NM and other locations with similar conditions. We design a set of comparative LEM simulations to investigate the role of spatially explicit solar radiation on landscape ecohydro-geomorphic development under different uplift scenarios. Aspect-control and network-control are identified as the two main drivers of soil moisture and vegetation organization on the landscape. Landscape-scale and long-term implications of these short-term ecohdrologic patterns emerged in modeled landscapes. As north facing slopes (NFS) get steeper by continuing uplift they support erosion-resistant denser vegetation cover which leads to further slope steepening until erosion and uplift attains a dynamic equilibrium. Conversely, on south facing slopes (SFS), as slopes grow with uplift, increased solar radiation exposure with slope supports sparser biomass and shallower slopes. At the landscape scale, these differential erosion processes lead to asymmetric development of catchment forms, consistent with regional observations. Understanding of ecohydrogeomorphic evolution will improve to assess the impacts of past and future climates on landscape response and morphology.

Co-evolution of landforms and vegetation under the influence of orographic precipitation

NASA Astrophysics Data System (ADS)

Yetemen, Omer; Srivastava, Ankur; Saco, Patricia M.

2017-04-01

Landforms are controlled by the interaction between tectonics, climate, and vegetation. Orography induced precipitation not only has implications on erosion resistance through vegetation dynamics but also affects erosive forces through modifying runoff production. The implications of elevated precipitation due to orography on landscape morphology requires a numerical framework that integrates a range of ecohydrologic and geomorphic processes to explore the competition between erosive and resisting forces in catchments where pronounced orographic precipitation prevails. In this study, our aim was to realistically represent ecohydrology driven by orographic precipitation and explore its implications on landscape evolution through a numerical model. The model was used to investigate how ecohydro-geomorphic differences caused by differential precipitation patterns as a result of orographic influence and rain-shadow effect lead to differences in the organization of modelled topography, soil moisture, and plant biomass. We use the CHILD landscape evolution model equipped with a vegetation dynamics component that explicitly tracks above- and below-ground biomass, and a precipitation forcing component that simulates rainfall as a function of elevation and orientation. The preliminary results of the model have shown how the competition between an increased shear stress through runoff production and an enhanced resistance force due to denser canopy cover, shape the landscape. Hillslope asymmetry between polar- and equator-facing hillslopes are enhanced (diminished) when they coincide with windward (leeward) side of the mountain series. The mountain divide accommodates itself by migrating toward the windward direction to increase (decrease) hillslope gradients on windward (leeward) slopes. These results clearly demonstrate the strong coupling between landform evolution and climate processes.

Projected future changes in vegetation in western North America in the 21st century

USGS Publications Warehouse

Xiaoyan, Jiang; Rauscher, Sara A.; Ringler, Todd D.; Lawrence, David M.; Williams, A. Park; Allen, Craig D.; Steiner, Allison L.; Cai, D. Michael; McDowell, Nate G.

2013-01-01

Rapid and broad-scale forest mortality associated with recent droughts, rising temperature, and insect outbreaks has been observed over western North America (NA). Climate models project additional future warming and increasing drought and water stress for this region. To assess future potential changes in vegetation distributions in western NA, the Community Earth System Model (CESM) coupled with its Dynamic Global Vegetation Model (DGVM) was used under the future A2 emissions scenario. To better span uncertainties in future climate, eight sea surface temperature (SST) projections provided by phase 3 of the Coupled Model Intercomparison Project (CMIP3) were employed as boundary conditions. There is a broad consensus among the simulations, despite differences in the simulated climate trajectories across the ensemble, that about half of the needleleaf evergreen tree coverage (from 24% to 11%) will disappear, coincident with a 14% (from 11% to 25%) increase in shrubs and grasses by the end of the twenty-first century in western NA, with most of the change occurring over the latter half of the twenty-first century. The net impact is a ~6 GtC or about 50% decrease in projected ecosystem carbon storage in this region. The findings suggest a potential for a widespread shift from tree-dominated landscapes to shrub and grass-dominated landscapes in western NA because of future warming and consequent increases in water deficits. These results highlight the need for improved process-based understanding of vegetation dynamics, particularly including mortality and the subsequent incorporation of these mechanisms into earth system models to better quantify the vulnerability of western NA forests under climate change.

DayCent model simulations for estimating soil carbon dynamics and greenhouse gas fluxes from agricultural production systems

USDA-ARS?s Scientific Manuscript database

DayCent is a biogeochemical model of intermediate complexity used to simulate carbon, nutrient, and greenhouse gas fluxes for crop, grassland, forest, and savanna ecosystems. Model inputs include: soil texture and hydraulic properties, current and historical land use, vegetation cover, daily maximum...

Seasonally-Dynamic SPARROW Modeling of Nitrogen Flux Using Earth Observation Data

NASA Astrophysics Data System (ADS)

Smith, R. A.; Schwarz, G. E.; Brakebill, J. W.; Hoos, A. B.; Moore, R. B.; Shih, J.; Nolin, A. W.; Macauley, M.; Alexander, R. B.

2013-12-01

SPARROW models are widely used to identify and quantify the sources of contaminants in watersheds and to predict their flux and concentration at specified locations downstream. Conventional SPARROW models describe the average relationship between sources and stream conditions based on long-term water quality monitoring data and spatially-referenced explanatory information. But many watershed management issues stem from intra- and inter-annual changes in contaminant sources, hydrologic forcing, or other environmental conditions which cause a temporary imbalance between inputs and stream water quality. Dynamic behavior of the system relating to changes in watershed storage and processing then becomes important. In this study, we describe dynamically calibrated SPARROW models of total nitrogen flux in three sub-regional watersheds: the Potomac River Basin, Long Island Sound drainage, and coastal South Carolina drainage. The models are based on seasonal water quality and watershed input data for a total 170 monitoring stations for the period 2001 to 2008. Frequently-reported, spatially-detailed input data on the phenology of agricultural production, terrestrial vegetation growth, and snow melt are often challenging requirements of seasonal modeling of reactive nitrogen. In this NASA-funded research, we use Enhanced Vegetation Index (EVI), gross primary production and snow/ice cover data from MODIS to parameterize seasonal uptake and release of nitrogen from vegetation and snowpack. The spatial reference frames of the models are 1:100,000-scale stream networks, and the computational time steps are 0.25-year seasons. Precipitation and temperature data are from PRISM. The model formulation accounts for storage of nitrogen from nonpoint sources including fertilized cropland, pasture, urban land, and atmospheric deposition. Model calibration is by non-linear regression. Once calibrated, model source terms based on previous season export allow for recursive dynamic simulation of stream flux: gradual increases or decreases in export occur as source supply rates and hydrologic forcing change. Based on an assumption that removal of nitrogen from watershed storage to stream channels and to 'permanent' sinks (e.g. the atmosphere and deep groundwater) occur as parallel first-order processes, the models can be used to estimate the approximate residence times of nonpoint source nitrogen in the watersheds.

Climate variability and human impact in South America during the last 2000 years: synthesis and perspectives from pollen records

NASA Astrophysics Data System (ADS)

Flantua, S. G. A.; Hooghiemstra, H.; Vuille, M.; Behling, H.; Carson, J. F.; Gosling, W. D.; Hoyos, I.; Ledru, M. P.; Montoya, E.; Mayle, F.; Maldonado, A.; Rull, V.; Tonello, M. S.; Whitney, B. S.; González-Arango, C.

2016-02-01

An improved understanding of present-day climate variability and change relies on high-quality data sets from the past 2 millennia. Global efforts to model regional climate modes are in the process of being validated against, and integrated with, records of past vegetation change. For South America, however, the full potential of vegetation records for evaluating and improving climate models has hitherto not been sufficiently acknowledged due to an absence of information on the spatial and temporal coverage of study sites. This paper therefore serves as a guide to high-quality pollen records that capture environmental variability during the last 2 millennia. We identify 60 vegetation (pollen) records from across South America which satisfy geochronological requirements set out for climate modelling, and we discuss their sensitivity to the spatial signature of climate modes throughout the continent. Diverse patterns of vegetation response to climate change are observed, with more similar patterns of change in the lowlands and varying intensity and direction of responses in the highlands. Pollen records display local-scale responses to climate modes; thus, it is necessary to understand how vegetation-climate interactions might diverge under variable settings. We provide a qualitative translation from pollen metrics to climate variables. Additionally, pollen is an excellent indicator of human impact through time. We discuss evidence for human land use in pollen records and provide an overview considered useful for archaeological hypothesis testing and important in distinguishing natural from anthropogenically driven vegetation change. We stress the need for the palynological community to be more familiar with climate variability patterns to correctly attribute the potential causes of observed vegetation dynamics. This manuscript forms part of the wider LOng-Term multi-proxy climate REconstructions and Dynamics in South America - 2k initiative that provides the ideal framework for the integration of the various palaeoclimatic subdisciplines and palaeo-science, thereby jump-starting and fostering multidisciplinary research into environmental change on centennial and millennial timescales.

Carbon cycling under 300 years of land use change: importance of the secondary vegetation sink

USGS Publications Warehouse

Shevliakova, Elena; Pacala, Stephen W.; Malyshev, Sergey; Hurtt, George C.; Milly, P.C.D.; Caspersen, John P.; Sentman, Lori T.; Fisk, Justin P.; Wirth, Christian; Crevoisier, Cyril

2009-01-01

We have developed a dynamic land model (LM3V) able to simulate ecosystem dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V is specifically designed to address the consequences of land use and land management changes including cropland and pasture dynamics, shifting cultivation, logging, fire, and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V, forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL) atmospheric model AM2, observed precipitation data, and four historic scenarios of land use change for 1700-2000. Our analysis suggests a net terrestrial carbon source due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due to the difference in the historic cropland distribution. This magnitude is substantially smaller than previous estimates from other models, largely due to our estimates of a secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural land clearing since the 1960s. For the 1990s, our estimates for the pastures' carbon flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller net deforestation source than earlier bookkeeping models because it accounts for decelerated net conversion of primary forest to agriculture and for stronger secondary vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher than the range reported here because of uncertainty in the biomass recovery under changing ambient conditions, including atmospheric CO2 concentration, nutrients availability, and climate. Copyright 2009 by the American Geophysical Union.

Responses of Terrestrial Ecosystems’ Net Primary Productivity to Future Regional Climate Change in China

PubMed Central

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems’ response to global climate change. China’s ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund–Potsdam–Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China’s terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change. PMID:23593325

Responses of terrestrial ecosystems' net primary productivity to future regional climate change in China.

PubMed

Zhao, Dongsheng; Wu, Shaohong; Yin, Yunhe

2013-01-01

The impact of regional climate change on net primary productivity (NPP) is an important aspect in the study of ecosystems' response to global climate change. China's ecosystems are very sensitive to climate change owing to the influence of the East Asian monsoon. The Lund-Potsdam-Jena Dynamic Global Vegetation Model for China (LPJ-CN), a global dynamical vegetation model developed for China's terrestrial ecosystems, was applied in this study to simulate the NPP changes affected by future climate change. As the LPJ-CN model is based on natural vegetation, the simulation in this study did not consider the influence of anthropogenic activities. Results suggest that future climate change would have adverse effects on natural ecosystems, with NPP tending to decrease in eastern China, particularly in the temperate and warm temperate regions. NPP would increase in western China, with a concentration in the Tibetan Plateau and the northwest arid regions. The increasing trend in NPP in western China and the decreasing trend in eastern China would be further enhanced by the warming climate. The spatial distribution of NPP, which declines from the southeast coast to the northwest inland, would have minimal variation under scenarios of climate change.

Modeling temperature and humidity profiles within forest canopies

USDA-ARS?s Scientific Manuscript database

Physically-based models are a powerful tool to help understand interactions of vegetation, atmospheric dynamics, and hydrology, and to test hypotheses regarding the effects of land cover, management, hydrometeorology, and climate variability on ecosystem processes. The purpose of this paper is to f...

A simple, dynamic, hydrological model of a mesotidal salt marsh

EPA Science Inventory

Salt marsh hydrology presents many difficulties from a modeling standpoint: the bi-directional flows of tidal waters, variable water densities due to mixing of fresh and salt water, significant influences from vegetation, and complex stream morphologies. Because of these difficu...

Scaling up of Carbon Exchange Dynamics from AmeriFlux Sites to a Super-Region in the Eastern United States

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hans Peter Schmid; Craig Wayson

The primary objective of this project was to evaluate carbon exchange dynamics across a region of North America between the Great Plains and the East Coast. This region contains about 40 active carbon cycle research (AmeriFlux) sites in a variety of climatic and landuse settings, from upland forest to urban development. The core research involved a scaling strategy that uses measured fluxes of CO{sub 2}, energy, water, and other biophysical and biometric parameters to train and calibrate surface-vegetation-atmosphere models, in conjunction with satellite (MODIS) derived drivers. To achieve matching of measured and modeled fluxes, the ecosystem parameters of the modelsmore » will be adjusted to the dynamically variable flux-tower footprints following Schmid (1997). High-resolution vegetation index variations around the flux sites have been derived from Landsat data for this purpose. The calibrated models are being used in conjunction with MODIS data, atmospheric re-analysis data, and digital land-cover databases to derive ecosystem exchange fluxes over the study domain.« less

A new model of the global biogeochemical cycle of carbonyl sulfide - Part 2: Use of carbonyl sulfide to constrain gross primary productivity in current vegetation models

NASA Astrophysics Data System (ADS)

Launois, T.; Peylin, P.; Belviso, S.; Poulter, B.

2015-08-01

Clear analogies between carbonyl sulfide (OCS) and carbon dioxide (CO2) diffusion pathways through leaves have been revealed by experimental studies, with plant uptake playing an important role for the atmospheric budget of both species. Here we use atmospheric OCS to evaluate the gross primary production (GPP) of three dynamic global vegetation models (Lund-Potsdam-Jena, LPJ; National Center for Atmospheric Research - Community Land Model 4, NCAR-CLM4; and Organising Carbon and Hydrology In Dynamic Ecosystems, ORCHIDEE). Vegetation uptake of OCS is modeled as a linear function of GPP and leaf relative uptake (LRU), the ratio of OCS to CO2 deposition velocities of plants. New parameterizations for the non-photosynthetic sinks (oxic soils, atmospheric oxidation) and biogenic sources (oceans and anoxic soils) of OCS are also provided. Despite new large oceanic emissions, global OCS budgets created with each vegetation model show exceeding sinks by several hundred Gg S yr-1. An inversion of the surface fluxes (optimization of a global scalar which accounts for flux uncertainties) led to balanced OCS global budgets, as atmospheric measurements suggest, mainly by drastic reduction (up to -50 %) in soil and vegetation uptakes. The amplitude of variations in atmospheric OCS mixing ratios is mainly dictated by the vegetation sink over the Northern Hemisphere. This allows for bias recognition in the GPP representations of the three selected models. The main bias patterns are (i) the terrestrial GPP of ORCHIDEE at high northern latitudes is currently overestimated, (ii) the seasonal variations of the GPP are out of phase in the NCAR-CLM4 model, showing a maximum carbon uptake too early in spring in the northernmost ecosystems, (iii) the overall amplitude of the seasonal variations of GPP in NCAR-CLM4 is too small, and (iv) for the LPJ model, the GPP is slightly out of phase for the northernmost ecosystems and the respiration fluxes might be too large in summer in the Northern Hemisphere. These results rely on the robustness of the OCS modeling framework and, in particular, the choice of the LRU values (assumed constant in time) and the parameterization of soil OCS uptake with small seasonal variations. Refined optimization with regional-scale and seasonally varying coefficients might help to test some of these hypothesis.

Past and future effects of climate change on spatially heterogeneous vegetation activity in China

NASA Astrophysics Data System (ADS)

Gao, Jiangbo; Jiao, Kewei; Wu, Shaohong; Ma, Danyang; Zhao, Dongsheng; Yin, Yunhe; Dai, Erfu

2017-07-01

Climate change is a major driver of vegetation activity but its complex ecological relationships impede research efforts. In this study, the spatial distribution and dynamic characteristics of climate change effects on vegetation activity in China from the 1980s to the 2010s and from 2021 to 2050 were investigated using a geographically weighted regression (GWR) model. The GWR model was based on combined datasets of satellite vegetation index, climate observation and projection, and future vegetation productivity simulation. Our results revealed that the significantly positive precipitation-vegetation relationship was and will be mostly distributed in North China. However, the regions with temperature-dominated distribution of vegetation activity were and will be mainly located in South China. Due to the varying climate features and vegetation cover, the spatial correlation between vegetation activity and climate change may be altered. There will be different dominant climatic factors for vegetation activity distribution in some regions such as Northwest China, and even opposite correlations in Northeast China. Additionally, the response of vegetation activity to precipitation will move southward in the next three decades. In contrast, although the high warming rate will restrain the vegetation activity, precipitation variability could modify hydrothermal conditions for vegetation activity. This observation is exemplified in the projected future enhancement of vegetation activity in the Tibetan Plateau and weakened vegetation activity in East and Middle China. Furthermore, the vegetation in most parts of North China may adapt to an arid environment, whereas in many southern areas, vegetation will be repressed by water shortage in the future.

Modeling Pacific Northwest carbon and water cycling using CARAIB Dynamic Vegetation Model

NASA Astrophysics Data System (ADS)

Dury, M.; Kim, J. B.; Still, C. J.; Francois, L. M.; Jiang, Y.

2015-12-01

While uncertainties remain regarding projected temperature and precipitation changes, climate warming is already affecting ecosystems in the Pacific Northwest (PNW). Decrease in ecosystem productivity as well as increase in mortality of some plant species induced by drought and disturbance have been reported. Here, we applied the process-based dynamic vegetation model CARAIB to PNW to simulate the response of water and carbon cycling to current and future climate change projections. The vegetation model has already been successfully applied to Europe to simulate plant physiological response to climate change. We calibrated CARAIB to PNW using global Plant Functional Types. For calibration, the model is driven with the gridded surface meteorological dataset UIdaho MACA METDATA with 1/24-degree (~4-km) resolution at a daily time step for the period 1979-2014. The model ability to reproduce the current spatial and temporal variations of carbon stocks and fluxes was evaluated using a variety of available datasets, including eddy covariance and satellite observations. We focused particularly on past severe drought and fire episodes. Then, we simulated future conditions using the UIdaho MACAv2-METDATA dataset, which includes downscaled CMIP5 projections from 28 GCMs for RCP4.5 and RCP8.5. We evaluated the future ecosystem carbon balance resulting from changes in drought frequency as well as in fire risk. We also simulated future productivity and drought-induced mortality of several key PNW tree species.

Measuring urban tree loss dynamics across residential landscapes.

PubMed

Ossola, Alessandro; Hopton, Matthew E

2018-01-15

The spatial arrangement of urban vegetation depends on urban morphology and socio-economic settings. Urban vegetation changes over time because of human management. Urban trees are removed due to hazard prevention or aesthetic preferences. Previous research attributed tree loss to decreases in canopy cover. However, this provides little information about location and structural characteristics of trees lost, as well as environmental and social factors affecting tree loss dynamics. This is particularly relevant in residential landscapes where access to residential parcels for field surveys is limited. We tested whether multi-temporal airborne LiDAR and multi-spectral imagery collected at a 5-year interval can be used to investigate urban tree loss dynamics across residential landscapes in Denver, CO and Milwaukee, WI, covering 400,705 residential parcels in 444 census tracts. Position and stem height of trees lost were extracted from canopy height models calculated as the difference between final (year 5) and initial (year 0) vegetation height derived from LiDAR. Multivariate regression models were used to predict number and height of tree stems lost in residential parcels in each census tract based on urban morphological and socio-economic variables. A total of 28,427 stems were lost from residential parcels in Denver and Milwaukee over 5years. Overall, 7% of residential parcels lost one stem, averaging 90.87 stems per km 2 . Average stem height was 10.16m, though trees lost in Denver were taller compared to Milwaukee. The number of stems lost was higher in neighborhoods with higher canopy cover and developed before the 1970s. However, socio-economic characteristics had little effect on tree loss dynamics. The study provides a simple method for measuring urban tree loss dynamics within and across entire cities, and represents a further step toward high resolution assessments of the three-dimensional change of urban vegetation at large spatial scales. Published by Elsevier B.V.

PALADYN v1.0, a comprehensive land surface-vegetation-carbon cycle model of intermediate complexity

NASA Astrophysics Data System (ADS)

Willeit, Matteo; Ganopolski, Andrey

2016-10-01

PALADYN is presented; it is a new comprehensive and computationally efficient land surface-vegetation-carbon cycle model designed to be used in Earth system models of intermediate complexity for long-term simulations and paleoclimate studies. The model treats in a consistent manner the interaction between atmosphere, terrestrial vegetation and soil through the fluxes of energy, water and carbon. Energy, water and carbon are conserved. PALADYN explicitly treats permafrost, both in physical processes and as an important carbon pool. It distinguishes nine surface types: five different vegetation types, bare soil, land ice, lake and ocean shelf. Including the ocean shelf allows the treatment of continuous changes in sea level and shelf area associated with glacial cycles. Over each surface type, the model solves the surface energy balance and computes the fluxes of sensible, latent and ground heat and upward shortwave and longwave radiation. The model includes a single snow layer. Vegetation and bare soil share a single soil column. The soil is vertically discretized into five layers where prognostic equations for temperature, water and carbon are consistently solved. Phase changes of water in the soil are explicitly considered. A surface hydrology module computes precipitation interception by vegetation, surface runoff and soil infiltration. The soil water equation is based on Darcy's law. Given soil water content, the wetland fraction is computed based on a topographic index. The temperature profile is also computed in the upper part of ice sheets and in the ocean shelf soil. Photosynthesis is computed using a light use efficiency model. Carbon assimilation by vegetation is coupled to the transpiration of water through stomatal conductance. PALADYN includes a dynamic vegetation module with five plant functional types competing for the grid cell share with their respective net primary productivity. PALADYN distinguishes between mineral soil carbon, peat carbon, buried carbon and shelf carbon. Each soil carbon type has its own soil carbon pools generally represented by a litter, a fast and a slow carbon pool in each soil layer. Carbon can be redistributed between the layers by vertical diffusion and advection. For the vegetated macro surface type, decomposition is a function of soil temperature and soil moisture. Carbon in permanently frozen layers is assigned a long turnover time which effectively locks carbon in permafrost. Carbon buried below ice sheets and on flooded ocean shelves is treated differently. The model also includes a dynamic peat module. PALADYN includes carbon isotopes 13C and 14C, which are tracked through all carbon pools. Isotopic discrimination is modelled only during photosynthesis. A simple methane module is implemented to represent methane emissions from anaerobic carbon decomposition in wetlands (including peatlands) and flooded ocean shelf. The model description is accompanied by a thorough model evaluation in offline mode for the present day and the historical period.

Regional impacts of Atlantic Forest deforestation on climate and vegetation dynamics

NASA Astrophysics Data System (ADS)

Holm, J. A.; Chambers, J. Q.

2012-12-01

The Brazilian Atlantic Forest was a large and important forest due to its high biodiversity, endemism, range in climate, and complex geography. The original Atlantic Forest was estimated to cover 150 million hectares, spanning large latitudinal, longitudinal, and elevation gradients. This unique environment helped contribute to a diverse assemblage of plants, mammals, birds, and reptiles. Unfortunately, due to land conversion into agriculture, pasture, urban areas, and increased forest fragmentation, only ~8-10% of the original Atlantic Forest remains. Tropical deforestation in the Americas can have considerable effects on local to global climates, and surrounding vegetation growth and survival. This study uses a fully coupled, global climate model (Community Earth System Model, CESM v.1.0.1) to simulate the full removal of the historical Atlantic Forest, and evaluate the regional climatic and vegetation responses due to deforestation. We used the fully coupled atmosphere and land surface components in CESM, and a partially interacting ocean component. The vegetated grid cell portion of the land surface component, the Community Landscape Model (CLM), is divided into 4 of 16 plant functional types (PFTs) with vertical layers of canopy, leaf area index, soil physical properties, and interacting hydrological features all tracking energy, water, and carbon state and flux variables, making CLM highly capable in predicting the complex nature and outcomes of large-scale deforestation. The Atlantic Forest removal (i.e. deforestation) was conducted my converting all woody stem PFTs to grasses in CLM, creating a land-use change from forest to pasture. By comparing the simulated historical Atlantic Forest (pre human alteration) to a deforested Atlantic Forest (close to current conditions) in CLM and CESM we found that live stem carbon, NPP (gC m-2 yr-1), and other vegetation dynamics inside and outside the Atlantic Forest region were largely altered. In addition to vegetation effects, regional surface air temperature (C°), precipitation (mm day-1), and emitted longwave radiation (W m-2) were highly affected in the location of the removed forest, and throughout surrounding areas of South America. For example climate patterns of increased temperature and decreased precipitation were affected as far as the Amazon Forest region. The use of fully coupled global climate and terrestrial models to study the effects of large-scale forest removal have been rarely applied. This study successfully showed the valuation of an important tropical forest, and the consequences of large deforestation through the reporting of complex earth-atmosphere interactions between vegetation dynamics and climate.

The implementation of biofiltration systems, rainwater tanks and urban irrigation in a single-layer urban canopy model

NASA Astrophysics Data System (ADS)

Demuzere, Matthias; Coutts, Andrew; Goehler, Maren; Broadbent, Ashley; Wouters, Hendrik; van Lipzig, Nicole; Gebert, Luke

2015-04-01

Urban vegetation is generally considered as a key tool to modify the urban energy balance through enhanced evapotranspiration (ET). Given that vegetation is most effective when it is healthy, stormwater harvesting and retention strategies (such as water sensitive urban design) could be used to support vegetation and promote ET. This study presents the implementation of a vegetated lined bio-filtration system (BFS) combined with a rainwater tank (RWT) and urban irrigation system in the single-layer urban canopy model Community Land Model-Urban. Runoff from roof and impervious road surface fractions is harvested and used to support an adequate soil moisture level for vegetation in the BFS. In a first stage, modelled soil moisture dynamics are evaluated and found reliable compared to observed soil moisture levels from biofiltration pits in Smith Street, Melbourne (Australia). Secondly, the impact of BFS, RWT and urban irrigation on ET is illustrated for a two-month period in 2012 using varying characteristics for all components. Results indicate that (i) a large amount of stormwater is potentially available for indoor and outdoor water demands, including irrigation of urban vegetation, (ii) ET from the BFS is an order of magnitude larger compared to the contributions from the impervious surfaces, even though the former only covers 10% of the surface fraction and (iii) attention should be paid to the cover fraction and soil texture of the BFS, size of the RWT and the surface fractions contributing to the collection of water in the RWT. Overall, this study reveals that this model development can effectuate future research with state-of-the-art urban climate models to further explore the benefits of vegetated biofiltration systems as a water sensitive urban design tool optimised with an urban irrigation system to maintain healthy vegetation.

Using ground- and satellite-based measurements and models to quantify response to multiple disturbances and climate change in South African semi-arid ecosystems

NASA Astrophysics Data System (ADS)

Falge, Eva; Brümmer, Christian; Schmullius, Christiane; Scholes, Robert; Twine, Wayne; Mudau, Azwitamisi; Midgley, Guy; Hickler, Thomas; Bradshaw, Karen; Lück, Wolfgang; Thiel-Clemen, Thomas; du Toit, Justin; Sankaran, Vaith; Kutsch, Werner

2016-04-01

Sub-Saharan Africa currently experiences significant changes in shrubland, savanna and mixed woodland ecosystems driving degradation, affecting fire frequency and water availability, and eventually fueling climate change. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. For a network of research clusters along an aridity gradient in South Africa, we measure greenhouse gas exchange, ecosystem structure and eco-physiological properties as affected by land use change at paired sites with natural and altered vegetation. We set up dynamic vegetation models and individual-based models to predict ecosystem dynamics under (post) disturbance managements. We monitor vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change. Finally, we investigate livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation of estimates obtained from eddy covariance, model approaches and satellite derivations. We envision our methodological approach on a network of research clusters a valuable means to investigate potential linkages to concepts of adaptive resilience.

Calibration of the maximum carboxylation velocity (Vcmax) using data mining techniques and ecophysiological data from the Brazilian semiarid region, for use in Dynamic Global Vegetation Models.

PubMed

Rezende, L F C; Arenque-Musa, B C; Moura, M S B; Aidar, S T; Von Randow, C; Menezes, R S C; Ometto, J P B H

2016-06-01

The semiarid region of northeastern Brazil, the Caatinga, is extremely important due to its biodiversity and endemism. Measurements of plant physiology are crucial to the calibration of Dynamic Global Vegetation Models (DGVMs) that are currently used to simulate the responses of vegetation in face of global changes. In a field work realized in an area of preserved Caatinga forest located in Petrolina, Pernambuco, measurements of carbon assimilation (in response to light and CO2) were performed on 11 individuals of Poincianella microphylla, a native species that is abundant in this region. These data were used to calibrate the maximum carboxylation velocity (Vcmax) used in the INLAND model. The calibration techniques used were Multiple Linear Regression (MLR), and data mining techniques as the Classification And Regression Tree (CART) and K-MEANS. The results were compared to the UNCALIBRATED model. It was found that simulated Gross Primary Productivity (GPP) reached 72% of observed GPP when using the calibrated Vcmax values, whereas the UNCALIBRATED approach accounted for 42% of observed GPP. Thus, this work shows the benefits of calibrating DGVMs using field ecophysiological measurements, especially in areas where field data is scarce or non-existent, such as in the Caatinga.

GAPPARD: a computationally efficient method of approximating gap-scale disturbance in vegetation models

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Thürig, E.; Lischke, H.

2013-09-01

Models of vegetation dynamics that are designed for application at spatial scales larger than individual forest gaps suffer from several limitations. Typically, either a population average approximation is used that results in unrealistic tree allometry and forest stand structure, or models have a high computational demand because they need to simulate both a series of age-based cohorts and a number of replicate patches to account for stochastic gap-scale disturbances. The detail required by the latter method increases the number of calculations by two to three orders of magnitude compared to the less realistic population average approach. In an effort to increase the efficiency of dynamic vegetation models without sacrificing realism, we developed a new method for simulating stand-replacing disturbances that is both accurate and faster than approaches that use replicate patches. The GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) method works by postprocessing the output of deterministic, undisturbed simulations of a cohort-based vegetation model by deriving the distribution of patch ages at any point in time on the basis of a disturbance probability. With this distribution, the expected value of any output variable can be calculated from the output values of the deterministic undisturbed run at the time corresponding to the patch age. To account for temporal changes in model forcing (e.g., as a result of climate change), GAPPARD performs a series of deterministic simulations and interpolates between the results in the postprocessing step. We integrated the GAPPARD method in the vegetation model LPJ-GUESS, and evaluated it in a series of simulations along an altitudinal transect of an inner-Alpine valley. We obtained results very similar to the output of the original LPJ-GUESS model that uses 100 replicate patches, but simulation time was reduced by approximately the factor 10. Our new method is therefore highly suited for rapidly approximating LPJ-GUESS results, and provides the opportunity for future studies over large spatial domains, allows easier parameterization of tree species, faster identification of areas of interesting simulation results, and comparisons with large-scale datasets and results of other forest models.

Estimation of the stand ages of tropical secondary forests after shifting cultivation based on the combination of WorldView-2 and time-series Landsat images

NASA Astrophysics Data System (ADS)

Fujiki, Shogoro; Okada, Kei-ichi; Nishio, Shogo; Kitayama, Kanehiro

2016-09-01

We developed a new method to estimate stand ages of secondary vegetation in the Bornean montane zone, where local people conduct traditional shifting cultivation and protected areas are surrounded by patches of recovering secondary vegetation of various ages. Identifying stand ages at the landscape level is critical to improve conservation policies. We combined a high-resolution satellite image (WorldView-2) with time-series Landsat images. We extracted stand ages (the time elapsed since the most recent slash and burn) from a change-detection analysis with Landsat time-series images and superimposed the derived stand ages on the segments classified by object-based image analysis using WorldView-2. We regarded stand ages as a response variable, and object-based metrics as independent variables, to develop regression models that explain stand ages. Subsequently, we classified the vegetation of the target area into six age units and one rubber plantation unit (1-3 yr, 3-5 yr, 5-7 yr, 7-30 yr, 30-50 yr, >50 yr and 'rubber plantation') using regression models and linear discriminant analyses. Validation demonstrated an accuracy of 84.3%. Our approach is particularly effective in classifying highly dynamic pioneer vegetation younger than 7 years into 2-yr intervals, suggesting that rapid changes in vegetation canopies can be detected with high accuracy. The combination of a spectral time-series analysis and object-based metrics based on high-resolution imagery enabled the classification of dynamic vegetation under intensive shifting cultivation and yielded an informative land cover map based on stand ages.

Representing Northern Peatland Hydrology and Biogeochemistry with ALM Land Surface Model

NASA Astrophysics Data System (ADS)

Shi, X.; Ricciuto, D. M.; Thornton, P. E.; Hanson, P. J.; Xu, X.; Mao, J.; Warren, J.; Yuan, F.; Norby, R. J.; Sebestyen, S.; Griffiths, N.; Weston, D. J.; Walker, A.

2017-12-01

Northern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pool and vulnerability to hydrological change. Predictive understanding of northern peatland hydrology is a necessary precursor to understanding the fate of massive carbon stores in these systems under the influence of present and future climate change. Current models have begun to address microtopographic controls on peatland hydrology, but none have included a prognostic calculation of peatland water table depth for a vegetated wetland, independent of prescribed regional water tables. Firstly, we introduce a new configuration of the land model (ALM) of Accelerated Climate model for Energy (ACME), which includes a fully prognostic water table calculation for a vegetated peatland. Secondly, we couple our new hydrology treatment with vertically structured soil organic matter pool, and the addition of components from methane biogeochemistry. Thirdly, we introduce a new PFT for mosses and implement the water content dynamics and physiology of mosses. We inform and test our model based on SPRUCE experiment to get the reasonable results for the seasonal dynamics water table depths, water content dynamics and physiology of mosses, and correct soil carbon profiles. Then, we use our new model structure to test the how the water table depth and CH4 emission will respond to elevated CO2 and different warming scenarios.

Evolution of wave and tide over vegetation region in nearshore waters

NASA Astrophysics Data System (ADS)

Zhang, Mingliang; Zhang, Hongxing; Zhao, Kaibin; Tang, Jun; Qin, Huifa

2017-08-01

Coastal wetlands are an important ecosystem in nearshore regions, where complex flow characteristics occur because of the interactions among tides, waves, and plants, especially in the discontinuous flow of the intertidal zone. In order to simulate the wave and wave-induced current in coastal waters, in this study, an explicit depth-averaged hydrodynamic (HD) model has been dynamically coupled with a wave spectral model (CMS-Wave) by sharing the tide and wave data. The hydrodynamic model is based on the finite volume method; the intercell flux is computed using the Harten-Lax-van Leer (HLL) approximate Riemann solver for computing the dry-to-wet interface; the drag force of vegetation is modeled as the sink terms in the momentum equations. An empirical wave energy dissipation term with plant effect has been derived from the wave action balance equation to account for the resistance induced by aquatic vegetation in the CMS-Wave model. The results of the coupling model have been verified using the measured data for the case with wave-tide-vegetation interactions. The results show that the wave height decreases significantly along the wave propagation direction in the presence of vegetation. In the rip channel system, the oblique waves drive a meandering longshore current; it moves from left to right past the cusps with oscillations. In the vegetated region, the wave height is greatly attenuated due to the presence of vegetation, and the radiation stresses are noticeably changed as compared to the region without vegetation. Further, vegetation can affect the spatial distribution of mean velocity in a rip channel system. In the co-exiting environment of tides, waves, and vegetation, the locations of wave breaking and wave-induced radiation stress also vary with the water level of flooding or ebb tide in wetland water, which can also affect the development and evolution of wave-induced current.

Micro-topographic hydrologic variability due to vegetation acclimation under climate change

NASA Astrophysics Data System (ADS)

Le, P. V.; Kumar, P.

2012-12-01

Land surface micro-topography and vegetation cover have fundamental effects on the land-atmosphere interactions. The altered temperature and precipitation variability associated with climate change will affect the water and energy processes both directly and that mediated through vegetation. Since climate change induces vegetation acclimation that leads to shifts in evapotranspiration and heat fluxes, it further modifies microclimate and near-surface hydrological processes. In this study, we investigate the impacts of vegetation acclimation to climate change on micro-topographic hydrologic variability. The ability to accurately predict these impacts requires the simultaneous considerations of biochemical, ecophysiological and hydrological processes. A multilayer canopy-root-soil system model coupled with a conjunctive surface-subsurface flow model is used to capture the acclimatory responses and analyze the changes in dynamics of structure and connectivity of micro-topographic storage and in magnitudes of runoff. The study is performed using Light Detection and Ranging (LiDAR) topographic data in the Birds Point-New Madrid floodway in Missouri, U.S.A. The result indicates that both climate change and its associated vegetation acclimation play critical roles in altering the micro-topographic hydrological responses.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2012-01-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2 > 0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

A new concept for simulation of vegetated land surface dynamics - Part 1: The event driven phenology model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2011-05-01

Phenologies of the vegetated land surface are being used increasingly for diagnosis and prognosis of climate change consequences. Current prospective and retrospective phenological models stand far apart in their approaches to the subject. We report on an exploratory attempt to implement a phenological model based on a new event driven concept which has both diagnostic and prognostic capabilities in the same modeling framework. This Event Driven Phenological Model (EDPM) is shown to simulate land surface phenologies and phenophase transition dates in agricultural landscapes based on assimilation of weather data and land surface observations from spaceborne sensors. The model enables growing season phenologies to develop in response to changing environmental conditions and disturbance events. It also has the ability to ingest remotely sensed data to adjust its output to improve representation of the modeled variable. We describe the model and report results of initial testing of the EDPM using Level 2 flux tower records from the Ameriflux sites at Mead, Nebraska, USA, and at Bondville, Illinois, USA. Simulating the dynamics of normalized difference vegetation index based on flux tower data, the predictions by the EDPM show good agreement (RMSE < 0.08; r2>0.8) for maize and soybean during several growing seasons at different locations. This study presents the EDPM used in the companion paper (Kovalskyy and Henebry, 2011) in a coupling scheme to estimate daily actual evapotranspiration over multiple growing seasons.

Interactive Vegetation Phenology, Soil Moisture, and Monthly Temperature Forecasts

NASA Technical Reports Server (NTRS)

Koster, R. D.; Walker, G. K.

2015-01-01

The time scales that characterize the variations of vegetation phenology are generally much longer than those that characterize atmospheric processes. The explicit modeling of phenological processes in an atmospheric forecast system thus has the potential to provide skill to subseasonal or seasonal forecasts. We examine this possibility here using a forecast system fitted with a dynamic vegetation phenology model. We perform three experiments, each consisting of 128 independent warm-season monthly forecasts: 1) an experiment in which both soil moisture states and carbon states (e.g., those determining leaf area index) are initialized realistically, 2) an experiment in which the carbon states are prescribed to climatology throughout the forecasts, and 3) an experiment in which both the carbon and soil moisture states are prescribed to climatology throughout the forecasts. Evaluating the monthly forecasts of air temperature in each ensemble against observations, as well as quantifying the inherent predictability of temperature within each ensemble, shows that dynamic phenology can indeed contribute positively to subseasonal forecasts, though only to a small extent, with an impact dwarfed by that of soil moisture.

Implementation of system dynamic simulation method to optimize profit in supply chain network of vegetable product

NASA Astrophysics Data System (ADS)

Tama, I. P.; Akbar, Z.; Eunike, A.

2018-04-01

Vegetables are categorized as a perishable product, which is a product with short lifespan thus requires proper handling and planning to reduce losses caused by the short lifespan. In order to reduce the losses, coordination among the players in the supply chain is required. On the other hand, the decision in the supply chain of vegetables and other farming products in the traditional market of developing country is independent among the players. This research is conducted by using System Dynamic Simulation method to develop model and scenario by coordinating the supply quantity amongst players in the supply chain. The scenarios are developed based on newsboy inventory model. This study aims to compare scenarios combining tiers involved in coordination program. The result shows that coordination in supply chain increases total supply chain profit, although there will always be players who experienced decrements in profit. The scenario of coordination among the farmer, the distributor, and the wholesaler resulted in the highest increase in total supply chain profit compared to other coordination scenarios, with an increased value of 10.49%.

Do ecohydrology and community dynamics feed back to banded-ecosystem structure and productivity?

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Mixed communities including grass, shrubs and trees are often reported to populate self-organized vegetation patterns. Patterns of survey data suggest that species diversity and complementarity strengthen the dynamics of banded environments. Resource scarcity and local facilitation trigger self organization, whereas coexistence of multiple species in vegetated self-organizing patches, implying competition for water and nutrients and favorable reproduction sites, is made possible by differing adaptation strategies. Mixed community spatial self-organization has so far received relatively little attention, compared with local net facilitation of isolated species. We assumed that soil moisture availability is a proxy for the environmental niche of plant species according to Ursino and Callegaro (2016). Our modelling effort was focused on niche differentiation of coexisting species within a tiger bush type ecosystem. By minimal numerical modelling and stability analysis we try to answer a few open scientific questions: Is there an adaptation strategy that increases biodiversity and ecosystem functioning? Does specific adaptation to environmental niches influence the structure of self-organizing vegetation pattern? What specific niche distribution along the environmental gradient gives the highest global productivity?

Ecological controls on water-cycle response to climate variability in deserts

PubMed Central

Scanlon, B. R.; Levitt, D. G.; Reedy, R. C.; Keese, K. E.; Sully, M. J.

2005-01-01

The impact of climate variability on the water cycle in desert ecosystems is controlled by biospheric feedback at interannual to millennial timescales. This paper describes a unique field dataset from weighing lysimeters beneath nonvegetated and vegetated systems that unequivocally demonstrates the role of vegetation dynamics in controlling water cycle response to interannual climate variability related to El Niño southern oscillation in the Mojave Desert. Extreme El Niño winter precipitation (2.3-2.5 times normal) typical of the U.S. Southwest would be expected to increase groundwater recharge, which is critical for water resources in semiarid and arid regions. However, lysimeter data indicate that rapid increases in vegetation productivity in response to elevated winter precipitation reduced soil water storage to half of that in a nonvegetated lysimeter, thereby precluding deep drainage below the root zone that would otherwise result in groundwater recharge. Vegetation dynamics have been controlling the water cycle in interdrainage desert areas throughout the U.S. Southwest, maintaining dry soil conditions and upward soil water flow since the last glacial period (10,000-15,000 yr ago), as shown by soil water chloride accumulations. Although measurements are specific to the U.S. Southwest, correlations between satellite-based vegetation productivity and elevated precipitation related to El Niño southern oscillation indicate this model may be applicable to desert basins globally. Understanding the two-way coupling between vegetation dynamics and the water cycle is critical for predicting how climate variability influences hydrology and water resources in water-limited landscapes. PMID:15837922

The status and challenge of global fire modelling

DOE PAGES

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; ...

2016-06-09

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

The status and challenge of global fire modelling

NASA Astrophysics Data System (ADS)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.; Kelley, Douglas I.; Prentice, I. Colin; Rabin, Sam S.; Archibald, Sally; Mouillot, Florent; Arnold, Steve R.; Artaxo, Paulo; Bachelet, Dominique; Ciais, Philippe; Forrest, Matthew; Friedlingstein, Pierre; Hickler, Thomas; Kaplan, Jed O.; Kloster, Silvia; Knorr, Wolfgang; Lasslop, Gitta; Li, Fang; Mangeon, Stephane; Melton, Joe R.; Meyn, Andrea; Sitch, Stephen; Spessa, Allan; van der Werf, Guido R.; Voulgarakis, Apostolos; Yue, Chao

2016-06-01

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central question underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. We indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.

The status and challenge of global fire modelling

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hantson, Stijn; Arneth, Almut; Harrison, Sandy P.

Biomass burning impacts vegetation dynamics, biogeochemical cycling, atmospheric chemistry, and climate, with sometimes deleterious socio-economic impacts. Under future climate projections it is often expected that the risk of wildfires will increase. Our ability to predict the magnitude and geographic pattern of future fire impacts rests on our ability to model fire regimes, using either well-founded empirical relationships or process-based models with good predictive skill. While a large variety of models exist today, it is still unclear which type of model or degree of complexity is required to model fire adequately at regional to global scales. This is the central questionmore » underpinning the creation of the Fire Model Intercomparison Project (FireMIP), an international initiative to compare and evaluate existing global fire models against benchmark data sets for present-day and historical conditions. In this paper we review how fires have been represented in fire-enabled dynamic global vegetation models (DGVMs) and give an overview of the current state of the art in fire-regime modelling. In conclusion, we indicate which challenges still remain in global fire modelling and stress the need for a comprehensive model evaluation and outline what lessons may be learned from FireMIP.« less

Combining remote sensing and watershed modeling for regional-scale carbon cycling studies in disturbance-prone systems

NASA Astrophysics Data System (ADS)

Hanan, E. J.; Tague, C.; Choate, J.; Liu, M.; Adam, J. C.

2016-12-01

Disturbance is a major force regulating C dynamics in terrestrial ecosystems. Evaluating future C balance in disturbance-prone systems requires understanding the underlying mechanisms that drive ecosystem processes over multiple scales of space and time. Simulation modeling is a powerful tool for bridging these scales, however, model projections are limited by large uncertainties in the initial state of vegetation C and N stores. Watershed models typically use one of two methods to initialize these stores. Spin up involves running a model until vegetation reaches steady state based on climate. This "potential" state however assumes the vegetation across the entire watershed has reached maturity and has a homogeneous age distribution. Yet to reliably represent C and N dynamics in disturbance-prone systems, models should be initialized to reflect their non-equilibrium conditions. Alternatively, remote sensing of a single vegetation parameter (typically leaf area index; LAI) can be combined with allometric relationships to allocate C and N to model stores and can reflect non-steady-state conditions. However, allometric relationships are species and region specific and do not account for environmental variation, thus resulting in C and N stores that may be unstable. To address this problem, we developed a new approach for initializing C and N pools using the watershed-scale ecohydrologic model RHESSys. The new approach merges the mechanistic stability of spinup with the spatial fidelity of remote sensing. Unlike traditional spin up, this approach supports non-homogeneous stand ages. We tested our approach in a pine-dominated watershed in central Idaho, which partially burned in July of 2000. We used LANDSAT and MODIS data to calculate LAI across the watershed following the 2000 fire. We then ran three sets of simulations using spin up, direct measurements, and the combined approach to initialize vegetation C and N stores, and compared our results to remotely sensed LAI following the simulation period. Model estimates of C, N, and water fluxes varied depending on which approach was used. The combined approach provided the best LAI estimates after 10 years of simulation. This method shows promise for improving projections of C, N, and water fluxes in disturbance-prone watersheds.

Bird-vegetation associations in thinned and unthinned young Douglas-fir forests 10 years after thinning

USGS Publications Warehouse

Yegorova, Svetlana; Betts, Matthew G.; Hagar, Joan; Puettmann, Klaus J.

2013-01-01

Quantitative associations between animals and vegetation have long been used as a basis for conservation and management, as well as in formulating predictions about the influence of resource management and climate change on populations. A fundamental assumption embedded in the use of such correlations is that they remain relatively consistent over time. However, this assumption of stationarity has been rarely tested – even for forest birds, which are frequently considered to be 'indicator species' in management operations. We investigated the temporal dynamics of bird-vegetation relationships in young Douglas-fir (Pseudotsuga menziesii) forests over more than a decade following initial anthropogenic disturbance (commercial thinning). We modeled bird occurrence or abundance as a function of vegetation characteristics for eight common bird species for each of six breeding seasons following forest thinning. Generally, vegetation relationships were highly inconsistent in magnitude across years, but remained positive or negative within species. For 3 species, relationships that were initially strong dampened over time. For other species, strength of vegetation association was apparently stochastic. These findings indicate that caution should be used when interpreting weak bird-vegetation relationships found in short-term studies and parameterizing predictive models with data collected over the short term.

Ecological restoration and recovery in the wind-blown sand hazard areas of northern China: relationship between soil water and carrying capacity for vegetation in the Tengger Desert.

PubMed

Li, XingRong; Zhang, ZhiShan; Tan, HuiJuan; Gao, YanHong; Liu, LiChao; Wang, XingPing

2014-05-01

The main prevention and control area for wind-blown sand hazards in northern China is about 320000 km(2) in size and includes sandlands to the east of the Helan Mountain and sandy deserts and desert-steppe transitional regions to the west of the Helan Mountain. Vegetation recovery and restoration is an important and effective approach for constraining wind-blown sand hazards in these areas. After more than 50 years of long-term ecological studies in the Shapotou region of the Tengger Desert, we found that revegetation changed the hydrological processes of the original sand dune system through the utilization and space-time redistribution of soil water. The spatiotemporal dynamics of soil water was significantly related to the dynamics of the replanted vegetation for a given regional precipitation condition. The long-term changes in hydrological processes in desert areas also drive replanted vegetation succession. The soil water carrying capacity of vegetation and the model for sand fixation by revegetation in aeolian desert areas where precipitation levels are less than 200 mm are also discussed.

Mechanical Analyses for coupled Vegetation-Flow System

NASA Astrophysics Data System (ADS)

Chen, L.; Acharya, K.; Stone, M.

2010-12-01

Vegetation in riparian areas plays important roles in hydrology, geomorphology and ecology in local environment. Mechanical response of the aquatic vegetation to hydraulic forces and its impact on flow hydraulics have received considerable attention due to implications for flood control, habitat restoration, and water resources management. This study aims to advance understanding of the mechanical properties of in-stream vegetation including drag force, moment and stress. Dynamic changes of these properties under various flow conditions largely determine vegetation affected flow field and dynamic resistance with progressive bending, and hydraulic conditions for vegetation failure (rupture or wash-out) thus are critical for understanding the coupled vegetation-flow system. A new approach combining fluid and material mechanics is developed in this study to examine the behavior of both rigid and flexible vegetation. The major advantage of this approach is its capability to treat large deflection (bending) of plants and associated changes of mechanical properties in both vegetation and flow. Starting from simple emergent vegetation, both static and dynamic formulations of the problem are presented and the solutions are compared. Results show the dynamic behavior of a simplified system mimicking complex and real systems, implying the approach is able to disclose the physical essence of the coupled system. The approach is extended to complex vegetation under both submerged and emergent conditions using more realistic representation of biomechanical properties for vegetation.

Developing a global mixed-canopy, height-variable vegetation structure dataset for estimating global vegetation albedo and biomass in the NASA Ent Terrestrial Biosphere Model and GISS GCM

NASA Astrophysics Data System (ADS)

Montes, C.; Kiang, N. Y.; Yang, W.; Ni-Meister, W.; Schaaf, C.; Aleinov, I. D.; Jonas, J.; Zhao, F. A.; Yao, T.; Wang, Z.; Sun, Q.

2015-12-01

Processes determining biosphere-atmosphere coupling are strongly influenced by vegetation structure. Thus, ecosystem carbon sequestration and evapotranspiration affecting global carbon and water balances will depend upon the spatial extent of vegetation, its vertical structure, and its physiological variability. To represent this globally, Dynamic Global Vegetation Models (DGVMs) coupled to General Circulation Models (GCMs) make use of satellite and/or model-based vegetation classifications often composed by homogeneous communities. This work aims at developing a new Global Vegetation Structure Dataset (GVSD) by incorporating varying vegetation heights for mixed plant communities to be used as input to the Ent Terrestrial Biosphere Model (TBM), the DGVM coupled to the NASA Goddard Institute for Space Studies (GISS) GCM. Information sources include the Moderate Resolution Imaging Spectroradiometer (MODIS) land cover and plant functional types (PFTs) (Friedl et al., 2010), vegetation height from the Geoscience Laser Altimeter System (GLAS) on board ICESat (Ice, Cloud, and land Elevation Satellite) (Simard et al., 2011; Tang et al., 2014) along with the Global Data Sets of Vegetation Leaf Area Index (LAI)3g (Zhu et al. 2013). Further PFT partitioning is performed according to a climate classification utilizing the Climate Research Unit (CRU) and the NOAA Global Precipitation Climatology Centre (GPCC) data. Final products are a GVSD consisting of mixed plant communities (e.g. mixed forests, savannas, mixed PFTs) following the Ecosystem Demography model (Moorcroft et al., 2001) approach represented by multi-cohort community patches at the sub-grid level of the GCM, which are ensembles of identical individuals whose differences are represented by PFTs, canopy height, density and vegetation structure sensitivity to allometric parameters. To assess the sensitivity of the GISS GCM to vegetation structure, we produce a range of estimates of Ent TBM biomass and plant densities by varying allometric specifications. Ultimately, this GVSD will serve as a template for community data sets, and be used as boundary conditions to the Ent TBM for prediction of canopy albedo in the Analytical Clumped Two-Stream canopy radiative transfer scheme, biomass, primary productivity, respiration, and GISS GCM climate.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

Variation in herbaceous vegetation and soil moisture under treated and untreated oneseed juniper trees

Treesearch

Hector Ramirez; Alexander Fernald; Andres Cibils; Michelle Morris; Shad Cox; Michael Rubio

2008-01-01

Clearing oneseed juniper (Juniperus monosperma) may make more water available for aquifer recharge or herbaceous vegetation growth, but the effects of tree treatment on soil moisture dynamics are not fully understood. This study investigated juniper treatment effects on understory herbaceous vegetation concurrently with soil moisture dynamics using vegetation sampling...

Incorporating dynamic root growth enhances the performance of Noah-MP at two contrasting winter wheat field sites

NASA Astrophysics Data System (ADS)

Gayler, Sebastian; Wöhling, Thomas; Ingwersen, Joachim; Wizemann, Hans-Dieter; Warrach-Sagi, Kirsten; Attinger, Sabine; Streck, Thilo; Wulmeyer, Volker

2014-05-01

Interactions between the soil, the vegetation, and the atmospheric boundary layer require close attention when predicting water fluxes in the hydrogeosystem, agricultural systems, weather and climate. However, land-surface schemes used in large scale models continue to show deficits in consistently simulating fluxes of water and energy from the subsurface through vegetation layers to the atmosphere. In this study, the multi-physics version of the Noah land-surface model (Noah-MP) was used to identify the processes, which are most crucial for a simultaneous simulation of water and heat fluxes between land-surface and the lower atmosphere. Comprehensive field data sets of latent and sensible heat fluxes, ground heat flux, soil moisture, and leaf area index from two contrasting field sites in South-West Germany are used to assess the accuracy of simulations. It is shown that an adequate representation of vegetation-related processes is the most important control for a consistent simulation of energy and water fluxes in the soil-plant-atmosphere system. In particular, using a newly implemented sub-module to simulate root growth dynamics has enhanced the performance of Noah-MP at both field sites. We conclude that further advances in the representation of leaf area dynamics and root/soil moisture interactions are the most promising starting points for improving the simulation of feedbacks between the sub-soil, land-surface and atmosphere in fully-coupled hydrological and atmospheric models.

Seed Dispersal Near and Far: Patterns Across Temperate and Tropical Forests

Treesearch

James S. Clark; Miles Silman; Ruth Kern; Eric Macklin; Janneke HilleRisLambers

1999-01-01

Dispersal affects community dynamics and vegetation response to global change. Understanding these effects requires descriptions of dispersal at local and regional scales and statistical models that permit estimation. Classical models of dispersal describe local or long-distance dispersal, but not both. The lack of statistical methods means that models have rarely been...

A toy terrestrial carbon flow model

NASA Technical Reports Server (NTRS)

Parton, William J.; Running, Steven W.; Walker, Brian

1992-01-01

A generalized carbon flow model for the major terrestrial ecosystems of the world is reported. The model is a simplification of the Century model and the Forest-Biogeochemical model. Topics covered include plant production, decomposition and nutrient cycling, biomes, the utility of the carbon flow model for predicting carbon dynamics under global change, and possible applications to state-and-transition models and environmentally driven global vegetation models.

Vegetation greenness modelling in response to interannual precipitation and temperature changes between 2001 and 2012 in Liao River Basin in Jilin Province, China.

PubMed

Lin, Xiao-Sheng; Tang, Jie; Li, Zhao-Yang; Li, Hai-Yi

2016-01-01

Liao River basin in Jilin Province is the place of origin of the Dongliao River. This study gives a comprehensive analysis of the vegetation coverage in the region and provides a potential theoretical basis for ecological restoration. The seasonal variation of vegetation greenness and dynamics based on the Normalized Difference Vegetation Index (NDVI) in major land cover types in the region was studied. Analyzing the relationship NDVI, temperature and rainfall, we derived a set of predictor variables from 2001 to 2012 using the MODIS Terra level 1 Product (MOD02QKM). The results showed a general increasing trend in NDVI value in the region, while 34.63 % of the region showed degradation. NDVI values begin to rise from April when plants are regreening and they drop in September when temperature are decreasing and the leaves are falling in the study area and temperature was found decreasing during the period of 2001-2012 while rainfall showed an increasing trend. This model could be used to observe the change in vegetation greenness and the dynamic effects of temperature and rainfall. This study provided important data for the environmental protection of the basin area. And we hope to provide scientific analysis for controlling water and soil erosion, maintaining the sustainable productivity of land resources, enhancing the treatment of water pollution and stimulating the virtuous cycle of the ecological system.

Projected effects of vegetation feedbacks on drought characteristics with SPEI over West Africa using the RegCM-CLM-CN-DV

NASA Astrophysics Data System (ADS)

Jaehyeong, L.; Kim, Y.; Erfanian, A.; Wang, G.; Um, M. J.

2017-12-01

This study utilizes the Standardized Precipitation-Evapotranspiration Index (SPEI) to investigate the projected effect of vegetation feedbacks on drought in West Africa using the Regional Climate Model coupled to the NCAR Community Land Model with both the Carbon and Nitrogen module (CN) and Dynamic Vegetation module (DV) activated (RegCM-CLM-CN-DV). The role of vegetation feedbacks is examined based on simulations with and without dynamic vegetation. The four different future climate scenarios from CCSM, GFDL, MIROC and MPI are used as the boundary conditions of RegCM for two historical and future periods, i.e., for 1981 to 2000 and for 2081 to 2100, respectively. Using SPEI, the duration, frequency, severity and spatial extents are quantified over West Africa and analyzed for two regions of the Sahel and the Gulf of Guinea. In this study, we find that the estimated annual SPEIs clearly indicate that the projected future droughts over the Sahel are enhanced and prolonged when DV is activated. The opposite is shown over the Gulf of Guinea in general. AcknowledgementsThis work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT & Future Planning (2015R1C1A2A01054800), by the Korea Meteorological Administration R&D Program under Grant KMIPA 2015-6180 and by the Yonsei University Future-leading Research Initiative of 2015(2016-22-0061).

The Plant Foliage Projective Coverage Change over the Northern Tibetan Plateau during 1957-2009

NASA Astrophysics Data System (ADS)

Cuo, L.

2015-12-01

Northern Tibetan Plateau is the headwater of the Yellow River, the Yangtze River and the Mekong River that support billions of the population. Vegetation change will affect the regional ecosystem and water balances through the changes in biomass and evapotranspiration. Dynamic vegetation growth is determined by physiological, morphological, bioclimatic and phenological properties. These properties are affected by climate variables such as air temperature, precipitation, soil temperature and concentration of CO2, etc. Due to climate change, some parts of the northern Tibetan Plateau are under the threat of desertification. Identifying the places of vegetation degradation and the dominant driven climatic factors will help mitigate the climate change impacts on ecosystem and water resources in this region. In this study, the changes of foliage projective coverages (FPCs) of various plant functional types (PFTs) existed in the northern Tibetan Plateau and the responses of FPCs to the four climate variables over 1957-2009 are examined. The dominant factors among the four climate variables are also identified. The Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM) is modified and used for the investigation. The modified LPJ-DGVM can better account for soil temperature in the top 0.4-m depth where vegetation root concentrates over the northern Tibetan Plateau. The modified model is evaluated by using monthly and annual soil temperature observed at stations across the region, and the eco-geographic maps that describe plant types and spatial distributions developed from field surveys and satellite images for this region.

Modelling the impacts of reoccurring fires in tropical savannahs using Biome-BGC.

NASA Astrophysics Data System (ADS)

Fletcher, Charlotte; Petritsch, Richard; Pietsch, Stephan

2010-05-01

Fires are a dominant feature of tropical savannahs and have occurred throughout history by natural as well as human-induced means. These fires have a profound influence on the landscape in terms of flux dynamics and vegetative species composition. This study attempts to understand the impacts of fire regimes on flux dynamics and vegetation composition in savannahs using the Biome-BGC model. The Batéké Plateau, Gabon - an area of savannah grasslands in the Congo basin, serves as a case-study. To achieve model validation for savannahs, data sets from stands with differing levels of past burning are used. It is hypothesised that the field measurements from those stands with lower-levels of past burning will correlate with the Biome-BGC model output, meaning that the model is validated for the savannah excluding fire regimes. However, in reality, fire is frequent in the savannah. Data on past fire events are available from the Moderate Resolution Imaging Spectroradiometer (MODIS) to provide the fire regimes of the model. As the field data-driven measurements of the burnt stands are influenced by fire in the savannah, this will therefore result in a Biome-BGC model validated for the impacts of fire on savannah ecology. The validated model can then be used to predict the savannah's flux dynamics under the fire scenarios expected with climate and/or human impact change.

Constraining Centennial-Scale Ecosystem-Climate Interactions with a Pre-colonial Forest Reconstruction across the Upper Midwest and Northeastern United States

NASA Astrophysics Data System (ADS)

Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.

2014-12-01

Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.

Multi-Scale Modeling of Boreal Forest Vegetation Growth Under the Influence of Permafrost and Wildfire Interactions

NASA Astrophysics Data System (ADS)

Foster, A.; Armstrong, A. H.; Shuman, J. K.; Ranson, K.; Shugart, H. H., Jr.; Rogers, B. M.; Goetz, S. J.

2017-12-01

Global temperatures have increased about 0.2°C per decade since 1979, and the high latitudes are warming faster than the rest of the globe. Climate change within Alaska is likely to bring about increased drought and longer fire seasons, as well as increases in the severity and frequency of fires. These changes in disturbance regimes and their associated effects on ecosystem C stocks, including permafrost, may lead to a positive feedback to further climate warming. As of now, it is uncertain how vegetation will respond to ongoing climate change, and the addition of disturbance effects leads to even more complicated and varied scenarios. Through ecological modeling, we have the capacity to examine forest processes at multiple temporal and spatial scales, allowing for the testing of complex interactions between vegetation, climate, and disturbances. The University of Virginia Forest Model Enhanced (UVAFME) is an individual tree-based forest model that has been updated for use in interior boreal Alaska, with a new permafrost model and updated fire simulation. These updated submodels allow for feedback between soils, vegetation, and fire severity through fuels tracking and impact of depth of burn on permafrost dynamics. We present these updated submodels as well as calibration and validation of UVAFME to the Yukon River Basin in Alaska, with comparisons to inventory data. We also present initial findings from simulations of potential future forest biomass, structure, and species composition across the Yukon River Basin under expected changes in precipitation, temperature, and disturbances. We predict changing climate and the associated impacts on wildfire and permafrost dynamics will result in shifts in biomass and species composition across the region, with potential for further feedback to the climate-vegetation-disturbance system. These simulations advance our understanding of the possible futures for the Alaskan boreal forest, which is a valuable part of the global carbon budget.

Leaf Phenology of Amazonian Canopy Trees as Revealed by Spectral and Physiochemical Measurements

NASA Astrophysics Data System (ADS)

Chavana-Bryant, C.; Gerard, F. F.; Malhi, Y.; Enquist, B. J.; Asner, G. P.

2013-12-01

The phenological dynamics of terrestrial ecosystems reflect the response of the Earth's biosphere to inter- and intra-annual dynamics of climatic and hydrological regimes. Some Dynamic Global Vegetation Models (GDVMs) have predicted that by 2050 the Amazon rainforest will begin to dieback (Cox et al. 2000, Nature) or that the ecosystem will become unsustainable (Salazar et al. 2007, GRL). One major component in DGVMs is the simulation of vegetation phenology, however, modelers are challenged with the estimation of tropical phenology which is highly complex. Current modeled phenology is based on observations of temperate vegetation and accurate representation of tropical phenology is long overdue. Remote sensing (RS) data are a key tool in monitoring vegetation dynamics at regional and global scales. Of the many RS techniques available, time-series analysis of vegetation indices (VIs) has become the most common approach in monitoring vegetation phenology (Samanta et al. 2010, GRL; Bradley et al. 2011, GCB). Our research focuses on investigating the influence that age related variation in the spectral reflectance and physiochemical properties of leaves may have on VIs of tropical canopies. In order to do this, we collected a unique leaf and canopy phenological dataset at two different Amazonian sites: Inselberg, French Guyana (FG) and Tambopata, Peru (PE). Hyperspectral reflectance measurements were collected from 4,102 individual leaves sampled to represent different leaf ages and vertical canopy positions (top, mid and low canopy) from 20 different canopy tree species (8 in FG and 12 in PE). These leaf spectra were complemented with 1) leaf physical measurements: fresh and dry weight, area and thickness, LMA and LWC and 2) leaf chemical measurements: %N, %C, %P, C:N and d13C. Canopy level observations included top-of-canopy reflectance measurements obtained using a multispectral 16-band radiometer, leaf demography (tot. number and age distribution) and branch structural measurements (space between leaves, min. and max. season's growth and diameter) of two 1m branches harvested from each canopy level. Both leaf and canopy-level observations where collected monthly when trees where not in flush and weekly during the period of leaf flushing. Here, we present our leaf spectral and physiochemical results. Results show 1) changes in leaf spectral and physiochemical properties related to leaf age, 2) the most significant changes in the leaves' spectrum during different stages in their life cycle, and 3) how leaf spectral changes are related to changes in the chemical and physical properties of the leaves as they progress through their life cycle. Future work will involve the incorporation of leaf and canopy observations into a light canopy interaction model to investigate the possibility that seasonal variation in VIs may be driven by leaf aging as well as by the shedding or appearance of new leaves.

Co-producing simulation models to inform resource management: a case study from southwest South Dakota

USGS Publications Warehouse

Miller, Brian W.; Symstad, Amy J.; Frid, Leonardo; Fisichelli, Nicholas A.; Schuurman, Gregor W.

2017-01-01

Simulation models can represent complexities of the real world and serve as virtual laboratories for asking “what if…?” questions about how systems might respond to different scenarios. However, simulation models have limited relevance to real-world applications when designed without input from people who could use the simulated scenarios to inform their decisions. Here, we report on a state-and-transition simulation model of vegetation dynamics that was coupled to a scenario planning process and co-produced by researchers, resource managers, local subject-matter experts, and climate change adaptation specialists to explore potential effects of climate scenarios and management alternatives on key resources in southwest South Dakota. Input from management partners and local experts was critical for representing key vegetation types, bison and cattle grazing, exotic plants, fire, and the effects of climate change and management on rangeland productivity and composition given the paucity of published data on many of these topics. By simulating multiple land management jurisdictions, climate scenarios, and management alternatives, the model highlighted important tradeoffs between grazer density and vegetation composition, as well as between the short- and long-term costs of invasive species management. It also pointed to impactful uncertainties related to the effects of fire and grazing on vegetation. More broadly, a scenario-based approach to model co-production bracketed the uncertainty associated with climate change and ensured that the most important (and impactful) uncertainties related to resource management were addressed. This cooperative study demonstrates six opportunities for scientists to engage users throughout the modeling process to improve model utility and relevance: (1) identifying focal dynamics and variables, (2) developing conceptual model(s), (3) parameterizing the simulation, (4) identifying relevant climate scenarios and management alternatives, (5) evaluating and refining the simulation, and (6) interpreting the results. We also reflect on lessons learned and offer several recommendations for future co-production efforts, with the aim of advancing the pursuit of usable science.

SIMPPLLE, version 2.5 user's guide

Treesearch

Jimmie D. Chew; Kirk Moeller; Christine Stalling

2012-01-01

SIMPPLLE is a spatially-interactive, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire, and other natural and management-caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem...

Improving root-zone soil moisture estimations using dynamic root growth and crop phenology

USDA-ARS?s Scientific Manuscript database

Water Energy Balance (WEB) Soil Vegetation Atmosphere Transfer (SVAT) modelling can be used to estimate soil moisture by forcing the model with observed data such as precipitation and solar radiation. Recently, an innovative approach that assimilates remotely sensed thermal infrared (TIR) observatio...

User's guide [Chapter 3

Treesearch

Nicholas L. Crookston; Donald C. E. Robinson; Sarah J. Beukema

2003-01-01

The Fire and Fuels Extension (FFE) to the Forest Vegetation Simulator (FVS) simulates fuel dynamics and potential fire behavior over time, in the context of stand development and management. This chapter presents the model's options, provides annotated examples, describes the outputs, and describes how to use and apply the model.

Floodplain Hydrodynamics and Ecosystem Function in a Dryland Wetland

NASA Astrophysics Data System (ADS)

Rodriguez, J. F.; Sandi, S. G.; Saco, P. M.; Wen, L.; Saintilan, N.; Kuczera, G. A.

2017-12-01

The Macquarie Marshes is a floodplain wetland system located in the semiarid region of south-east Australia, regularly flooded by small channels and creeks that get their water from a regulated river system. Flood-dependent vegetation in the wetland includes semi-permanent wetland areas (reed beds, lagoons, and mixed marsh), and floodplain forests and woodlands mainly dominated by River Red Gum (Eucalyptus Camaldulensis). These plant communities support a rich ecosystem and provide sanctuary for birds, frogs and fish and their ecological importance has been recognized under the Ramsar convention. During droughts, wetland vegetation can deteriorate or transition to terrestrial vegetation. Most recently, during the Millennium drought (2001-2009) large areas of water couch and common reeds transitioned to terrestrial vegetation and many patches of River Red Gum reported up to an 80% mortality. Since then, a significant recovery has occurred after a few years of record or near record rainfall. In order to support management decisions regarding watering of the wetland from the upstream reservoir, we have developed an eco-hydraulic model that relates vegetation distribution to the inundation regime (present and past) determined by floodplain hydrodynamics. The model couples hydrodynamic simulations with a rules-based vegetation module that considers water requirements for different plant associations and transition rules accounting for patch dynamics and vegetation resilience. The model has been setup and calibrated with satellite-derived inundation and vegetation maps as well as fractional cover products during the period from 1991 to 2013. We use the model to predict short-term wetland evolution under dry and wet future conditions.

Emergence of nutrient limitation in tropical dry forests: hypotheses from simulation models

NASA Astrophysics Data System (ADS)

Medvigy, D.; Waring, B. G.; Xu, X.; Trierweiler, A.; Werden, L. K.; Wang, G.; Zhu, Q.; Powers, J. S.

2017-12-01

It is unclear to what extent tropical dry forest productivity may be limited by nutrients. Direct assessment of nutrient limitation through fertilization experiments has been rare, and paradigms pertaining to other ecosystems may not extend to tropical dry forests. For example, because dry tropical forests have a lower water supply than moist tropical forests, dry forests can have lower decomposition rates, higher soil carbon and nitrogen concentrations, and a more open nitrogen cycle than moist forests. We used a mechanistic, numerical model to generate hypotheses about nutrient limitation in tropical dry forests. The model dynamically couples ED2 (vegetation dynamics), MEND (biogeochemistry), and N-COM (plant-microbe competition for nutrients). Here, the MEND-component of the model has been extended to include nitrogen (N) and phosphorus (P) cycles. We focus on simulation of sixteen 25m x 25m plots in Costa Rica where a fertilization experiment has been underway since 2015. Baseline simulations are characterized by both nitrogen and phosphorus limitation of vegetation. Fertilization with N and P increased vegetation biomass, with N fertilization having a somewhat stronger effect. Nutrient limitation was also sensitive to climate and was more pronounced during drought periods. Overflow respiration was identified as a key process that mitigated nutrient limitation. These results suggest that, despite often having richer soils than tropical moist forests, tropical dry forests can also become nutrient-limited. If the climate becomes drier in the next century, as is expected for Central America, drier soils may decrease microbial activity and exacerbate nutrient limitation. The importance of overflow respiration underscores the need for appropriate treatment of microbial dynamics in ecosystem models. Ongoing and new nutrient fertilization experiments will present opportunities for testing whether, and how, nutrient limitation may indeed be emerging in tropical dry forests.

The importance of nature's invisible fabric: food web structure mediates modeled responses to river restoration

NASA Astrophysics Data System (ADS)

Bellmore, R.; Benjamin, J.; Newsom, M.; Bountry, J.; Dombroski, D.

2016-12-01

Restoration is frequently aimed at the recovery of target species, but also influences the larger food web in which these species participate. Effects of restoration on this broader network of organisms can influence target species both directly and indirectly via changes in energy flow through food webs. To help incorporate these complexities into river restoration planning we constructed a food web model that links river food web dynamics to in-stream physical habitat and riparian vegetation conditions. We present an application of this model to the Methow River, Washington (USA), a location of on-going restoration aimed at recovering salmon. Three restoration strategies were simulated: riparian vegetation restoration, nutrient augmentation via salmon carcass addition, and floodplain reconnection. To explore how food web structure mediates responses to these actions, we modified the food web by adding populations of invasive aquatic snails and nonnative fish. Simulations suggest that floodplain reconnection may be a better strategy than carcass addition and vegetation planting for improving conditions for salmon in this river segment. However, modeled responses were strongly sensitive to changes in the structure of the food web. The addition of invasive snails and nonnative fishes modified pathways of energy through the food web, which negated restoration improvements. This finding illustrates that forecasting responses to restoration may require accounting for the structure of food webs, and that changes in this structure—as might be expected with the spread of invasive species—could compromise restoration outcomes. By elucidating the direct and indirect pathways by which restoration affects target species, dynamic food web models can improve restoration planning by fostering a deeper understanding of system connectedness and dynamics.

Global vegetation-fire pattern under different land use and climate conditions

NASA Astrophysics Data System (ADS)

Thonicke, K.; Poulter, B.; Heyder, U.; Gumpenberger, M.; Cramer, W.

2008-12-01

Fire is a process of global significance in the Earth System influencing vegetation dynamics, biogeochemical cycling and biophysical feedbacks. Naturally ignited wildfires have long history in the Earth System. Humans have been using fire to shape the landscape for their purposes for many millenia, sometimes influencing the status of the vegetation remarkably as for example in Mediterranean-type ecosystems. Processes and drivers describing fire danger, ignitions, fire spread and effects are relatively well-known for many fire-prone ecosystems. Modeling these has a long tradition in fire-affected regions to predict fire risk and behavior for fire-fighting purposes. On the other hand, the global vegetation community realized the importance of disturbances to be recognized in their global vegetation models with fire being globally most important and so-far best studied. First attempts to simulate fire globally considered a minimal set of drivers, whereas recent developments attempt to consider each fire process separately. The process-based fire model SPITFIRE (SPread and InTensity of FIRE) simulates these processes embedded in the LPJ DGVM. Uncertainties still arise from missing measurements for some parameters in less-studied fire regimes, or from broad PFT classifications which subsume different fire-ecological adaptations and tolerances. Some earth observation data sets as well as fire emission models help to evaluate seasonality and spatial distribution of simulated fire ignitions, area burnt and fire emissions within SPITFIRE. Deforestation fires are a major source of carbon released to the atmosphere in the tropics; in the Amazon basin it is the second-largest contributor to Brazils GHG emissions. How ongoing deforestation affects fire regimes, forest stability and biogeochemical cycling in the Amazon basin under present climate conditions will be presented. Relative importance of fire vs. climate and land use change is analyzed. Emissions resulting from wildfires, agricultural and woodfuel burning will be quantified and drivers identified. Future projections of climate and land use change are applied to the model to investigate joint effects on future changes in fire, deforestation and vegetation dynamics in the Amazon basin.

Groundwater Controls on Vegetation Composition and Patterning in Mountain Meadows

NASA Astrophysics Data System (ADS)

Loheide, S. P.; Lowry, C.; Moore, C. E.; Lundquist, J. D.

2010-12-01

Mountain meadows are groundwater dependent ecosystems that are hotspots of biodiversity and productivity in the Sierra Nevada of California. Meadow vegetation relies on shallow groundwater during the region’s dry summer growing season. Vegetation composition in this environment is influenced both by 1) oxygen stress that occurs when portions of the root zone are saturated and anaerobic conditions are created that limit root respiration and 2) water stress that occurs when the water table drops and water-limited conditions are created in the root zone. A watershed model that explicitly accounts for snowmelt processes was linked to a fine resolution groundwater flow model of Tuolumne Meadows in Yosemite National Park, CA to simulated spatially distributed water table dynamics. This linked hydrologic model was calibrated to observations from a well observation network for 2006-2008, and validated using data from 2009. A vegetation survey was also conducted at the site in which the three dominant species were identified at more than 200 plots distributed across the meadow. Nonparametric multiplicative regression was performed to create and select the best models for predicting vegetation dominance based on simulated hydrologic regime. The hydrologic niche of three vegetation types representing wet, moist, and dry meadow vegetation communities was best described using both 1) a sum exceedance value calculated as the integral of water table position above a threshold of oxygen stress and 2) a sum deceedance value calculated as the integral of water table position below a threshold of water stress. This linked hydrologic and vegetative modeling framework advances our ability to predict the propagation of human-induced climatic and land-use/-cover changes through the hydrologic system to the ecosystem.

Impacts of phenology on estimation of actual evapotranspiration with VegET model

NASA Astrophysics Data System (ADS)

Kovalskyy, V.; Henebry, G. M.

2009-12-01

The VegET model provides spatially explicit estimation of actual evapotranspiration (AET). Currently, it uses a climatology based on AVHRR NDVI image time series to modulate fluxes during growing seasons (Senay 2008). This step simplifies the model formulation, but it also introduces errors by ignoring the interannual variation in phenology. We report on a study to evaluate the effects of using an NDVI climatology in VegET rather than current season values. Using flux tower data from three sites across the US Corn Belt, we found that currently the model overestimates the duration of season. With the standard deviation of more than one week, the model results in an additional 50 to 70 mm of AET per season, which can account for about 10% of seasonal AET in drier western sites. The model showed only modest sensitivity to variation in growing season weather. This lack of sensitivity greatly decreased model accuracy during drought years: Pearson correlation coefficients between model estimates and observed values dropped from about 0.7 to 0.5, depending on vegetation type. We also evaluated an alternative approach to drive the canopy component of evapotranspiration, the Event Driven Phenology Model (EDPM). The parameterization of VegET with EDPM-simulated canopy dynamics improved the correlation by 0.1 or more and reduced the RMSE on daily AET estimates by 0.3 mm. By accounting for the progress of phenology during a particular growing season, the EDPM improves AET estimation over an NDVI climatology.

State-and-transition prototype model of riparian vegetation downstream of Glen Canyon Dam, Arizona

USGS Publications Warehouse

Ralston, Barbara E.; Starfield, Anthony M.; Black, Ronald S.; Van Lonkhuyzen, Robert A.

2014-01-01

Facing an altered riparian plant community dominated by nonnative species, resource managers are increasingly interested in understanding how to manage and promote healthy riparian habitats in which native species dominate. For regulated rivers, managing flows is one tool resource managers consider to achieve these goals. Among many factors that can influence riparian community composition, hydrology is a primary forcing variable. Frame-based models, used successfully in grassland systems, provide an opportunity for stakeholders concerned with riparian systems to evaluate potential riparian vegetation responses to alternative flows. Frame-based, state-and-transition models of riparian vegetation for reattachment bars, separation bars, and the channel margin found on the Colorado River downstream of Glen Canyon Dam were constructed using information from the literature. Frame-based models can be simple spreadsheet models (created in Microsoft® Excel) or developed further with programming languages (for example, C-sharp). The models described here include seven community states and five dam operations that cause transitions between states. Each model divides operations into growing (April–September) and non-growing seasons (October–March) and incorporates upper and lower bar models, using stage elevation as a division. The inputs (operations) can be used by stakeholders to evaluate flows that may promote dynamic riparian vegetation states, or identify those flow options that may promote less desirable states (for example, Tamarisk [Tamarix sp.] temporarily flooded shrubland). This prototype model, although simple, can still elicit discussion about operational options and vegetation response.

Ecohydro-geomorphic implications of orographic precipitation on landform evolution using a landscape evolution model

NASA Astrophysics Data System (ADS)

Yetemen, O.; Saco, P. M.

2016-12-01

Orography induced precipitation and its implications on vegetation dynamics and landscape morphology have long been documented in the literature. However a numerical framework that integrates a range of ecohydrologic and geomorphic processes to explore the coupled ecohydro-geomorphic landscape response of catchments where pronounced orographic precipitation prevails has been missing. In this study, our aim is to realistically represent orographic-precipitation-driven ecohydrologic dynamics in a landscape evolution model (LEM). The model is used to investigate how ecohydro-geomorphic differences caused by differential precipitation patterns on the leeward and windward sides of low-relief landscapes lead to differences in the organization of modelled topography, soil moisture and plant biomass. We use the CHILD LEM equipped with a vegetation dynamics component that explicitly tracks above- and below-ground biomass, and a precipitation forcing component that simulates rainfall as a function of elevation and orientation. The preliminary results of the model show how the competition between an increased shear stress through runoff production and an enhanced resistance force due to denser canopy cover shape the landscape. Moreover, orographic precipitation leads to not only the migration of the divide between leeward and windward slopes but also a change in the concavity of streams. These results clearly demonstrate the strong coupling between landform evolution and climate processes.

Use of MODIS Vegetation Data in Dynamic SPARROW Modeling of Reactive Nitrogen Flux

NASA Astrophysics Data System (ADS)

Smith, R. A.; Brakebill, J.; Schwarz, G. E.; Nolin, A. W.; Shih, J.; Blomquist, J.; Alexander, R. B.; Macauley, M.

2012-12-01

SPARROW models are widely used to identify and quantify the sources of contaminants in watersheds and to predict their flux and concentration at specified locations downstream. Conventional SPARROW models are steady-state in form, and describe the average relationship between sources and stream conditions based on non-linear regression of long-term water quality monitoring data on spatially-referenced explanatory information. But many watershed management issues involve intra- and inter-annual changes in contaminant sources, hydrologic forcing, or other environmental conditions which cause a temporary imbalance between watershed inputs and outputs. Dynamic behavior of the system relating to changes in watershed storage and processing then becomes important. We describe the results of dynamic statistical calibration of a SPARROW model of total reactive nitrogen flux in the Potomac River Basin based on seasonal water quality and watershed explanatory data for 80 monitoring stations over the period 2000 to 2008. One challenge in dynamic modeling of reactive nitrogen is obtaining frequently-reported, spatially-detailed input data on the phenology of agricultural production and growth of other terrestrial vegetation. In this NASA-funded research, we use the Enhanced Vegetation Index (EVI) and gross primary productivity (GPP) data from the Terra Satellite-borne MODIS sensor to parameterize seasonal uptake and release of nitrogen. The spatial reference frame of the model is a 16,000-reach, 1:100,000-scale stream network, and the computational time step is seasonal. Precipitation and temperature data are from PRISM. The model describes transient storage and transport of nitrogen from multiple nonpoint sources including fertilized cropland, pasture, urban/suburban land, and atmospheric deposition. Removal of nitrogen from watershed storage to stream channels and to "permanent" sinks (deep groundwater and the atmosphere) occurs as parallel first-order processes. Point sources of nitrogen bypass storage and flow directly to stream channels. Model results indicate that, on average, a little more than half of the reactive nitrogen flux comes from transient storage; but in some sub-watersheds a large majority of the flux comes from stored nitrogen input to the watershed in previous seasons and years.

Simulating Pacific Northwest Forest Response to Climate Change: How We Made Model Results Useful for Vulnerability Assessments

NASA Astrophysics Data System (ADS)

Kim, J. B.; Kerns, B. K.; Halofsky, J.

2014-12-01

GCM-based climate projections and downscaled climate data proliferate, and there are many climate-aware vegetation models in use by researchers. Yet application of fine-scale DGVM based simulation output in national forest vulnerability assessments is not common, because there are technical, administrative and social barriers for their use by managers and policy makers. As part of a science-management climate change adaptation partnership, we performed simulations of vegetation response to climate change for four national forests in the Blue Mountains of Oregon using the MC2 dynamic global vegetation model (DGVM) for use in vulnerability assessments. Our simulation results under business-as-usual scenarios suggest a starkly different future forest conditions for three out of the four national forests in the study area, making their adoption by forest managers a potential challenge. However, using DGVM output to structure discussion of potential vegetation changes provides a suitable framework to discuss the dynamic nature of vegetation change compared to using more commonly available model output (e.g. species distribution models). From the onset, we planned and coordinated our work with national forest managers to maximize the utility and the consideration of the simulation results in planning. Key lessons from this collaboration were: (1) structured and strategic selection of a small number climate change scenarios that capture the range of variability in future conditions simplified results; (2) collecting and integrating data from managers for use in simulations increased support and interest in applying output; (3) a structured, regionally focused, and hierarchical calibration of the DGVM produced well-validated results; (4) simple approaches to quantifying uncertainty in simulation results facilitated communication; and (5) interpretation of model results in a holistic context in relation to multiple lines of evidence produced balanced guidance. This latest point demonstrates the importance of using model out as a forum for discussion along with other information, rather than using model output in an inappropriately predictive sense. These lessons are being applied currently to other national forests in the Pacific Northwest to contribute in vulnerability assessments.

Spatial pattern formation of coastal vegetation in response to external gradients and positive feedbacks affecting soil porewater salinity: A model study

USGS Publications Warehouse

Jiang, J.; DeAngelis, D.L.; Smith, T. J.; Teh, S.Y.; Koh, H. L.

2012-01-01

Coastal vegetation of South Florida typically comprises salinity-tolerant mangroves bordering salinity-intolerant hardwood hammocks and fresh water marshes. Two primary ecological factors appear to influence the maintenance of mangrove/hammock ecotones against changes that might occur due to disturbances. One of these is a gradient in one or more environmental factors. The other is the action of positive feedback mechanisms, in which each vegetation community influences its local environment to favor itself, reinforcing the boundary between communities. The relative contributions of these two factors, however, can be hard to discern. A spatially explicit individual-based model of vegetation, coupled with a model of soil hydrology and salinity dynamics is presented here to simulate mangrove/hammock ecotones in the coastal margin habitats of South Florida. The model simulation results indicate that an environmental gradient of salinity, caused by tidal flux, is the key factor separating vegetation communities, while positive feedback involving the different interaction of each vegetation type with the vadose zone salinity increases the sharpness of boundaries, and maintains the ecological resilience of mangrove/hammock ecotones against small disturbances. Investigation of effects of precipitation on positive feedback indicates that the dry season, with its low precipitation, is the period of strongest positive feedback. ?? 2011 Springer Science+Business Media B.V. (outside the USA).

Post-fire vegetation dynamics in Portugal

NASA Astrophysics Data System (ADS)

Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2009-04-01

The number of fires and the extent of the burned surface in Mediterranean Europe have increased significantly during the last three decades. This may be due either to modifications in land-use (e.g. land abandonment and fuel accumulation) or to climatic changes (e.g. reduction of fuel humidity), both factors leading to an increase of fire risk and fire spread. As in the Mediterranean ecosystems, fires in Portugal have an intricate effect on vegetation regeneration due to the complexity of landscape structures as well as to the different responses of vegetation to the variety of fire regimes. A thorough evaluation of vegetation recovery after fire events becomes therefore crucial in land management. In the above mentioned context remote sensing plays an important role because of its ability to monitor and characterise post-fire vegetation dynamics. A number of fire recovery studies, based on remote sensing, have been conducted in regions characterised by Mediterranean climates and the use of NDVI to monitor plant regeneration after fire events was successfully tested (Díaz-Delgado et al., 1998). In particular, several studies have shown that rapid regeneration occurs within the first 2 years after the fire occurrences, with distinct recovery rates according to the geographical facing of the slopes (Pausas and Vallejo, 1999). In 2003 Portugal was hit by the most devastating sequence of large fires, responsible by a total burnt area of 450 000 ha (including 280 000 ha of forest), representing about 5% of the Portuguese mainland (Trigo et al., 2006). The aim of the present work is to assess and monitor the vegetation behaviour over Portugal following the 2003 fire episodes. For this purpose we have used the regional fields of the Normalized Difference Vegetation Index (NDVI) as obtained from the VEGETATION-SPOT5 instrument, from 1999 to 2008. We developed a methodology to identify large burnt scars in Portugal for the 2003 fire season. The vegetation dynamics was then analysed for some selected areas and a regression model of post-fire recovery was fitted to the recorded values of NDVI. The model allowed characterising the dynamics of the regeneration process. It was found that recovery rates depend on geographical location, fire intensity/severity and type of vegetation cover. Díaz-Delgado, R., Salvador, R. and Pons, X., 1998: Monitoring of plant community regeneration after fire by remote sensing. In L. Traboud (Ed.), Fire management and landscape ecology (pp. 315-324). International Association of Wildland Fire, Fairfield, WA. Pausas, G.J. and Vallejo, V.R., 1999: The role of fire in European Mediterranean Ecosystems. In: E. Chuvieco (Ed.), Remote sensing of large wildfires in the European Mediterranean basin (pp. 3-16). Springer-Verlag. Trigo R.M., Pereira J.M.C., Pereira M.G., Mota B., Calado M.T., DaCamara C.C., Santo F.E., 2006: Atmospheric conditions associated with the exceptional fire season of 2003 in Portugal. International Journal of Climatology 26 (13): 1741-1757 NOV 15 2006.

Using natural selection and optimization for smarter vegetation models - challenges and opportunities

NASA Astrophysics Data System (ADS)

Franklin, Oskar; Han, Wang; Dieckmann, Ulf; Cramer, Wolfgang; Brännström, Åke; Pietsch, Stephan; Rovenskaya, Elena; Prentice, Iain Colin

2017-04-01

Dynamic global vegetation models (DGVMs) are now indispensable for understanding the biosphere and for estimating the capacity of ecosystems to provide services. The models are continuously developed to include an increasing number of processes and to utilize the growing amounts of observed data becoming available. However, while the versatility of the models is increasing as new processes and variables are added, their accuracy suffers from the accumulation of uncertainty, especially in the absence of overarching principles controlling their concerted behaviour. We have initiated a collaborative working group to address this problem based on a 'missing law' - adaptation and optimization principles rooted in natural selection. Even though this 'missing law' constrains relationships between traits, and therefore can vastly reduce the number of uncertain parameters in ecosystem models, it has rarely been applied to DGVMs. Our recent research have shown that optimization- and trait-based models of gross primary production can be both much simpler and more accurate than current models based on fixed functional types, and that observed plant carbon allocations and distributions of plant functional traits are predictable with eco-evolutionary models. While there are also many other examples of the usefulness of these and other theoretical principles, it is not always straight-forward to make them operational in predictive models. In particular on longer time scales, the representation of functional diversity and the dynamical interactions among individuals and species presents a formidable challenge. Here we will present recent ideas on the use of adaptation and optimization principles in vegetation models, including examples of promising developments, but also limitations of the principles and some key challenges.

Study on the vegetation dynamic change using long time series of remote sensing data

NASA Astrophysics Data System (ADS)

Fan, Jinlong; Zhang, Xiaoyu

2010-10-01

The vegetation covering land surface is main component of biosphere which is one of five significant spheres on the earth. The vegetation plays a very important role on the natural environment conservation and improvement to keep human being's living environment evergreen while the vegetation supplies many natural resources to human living and development continuously. Under the background of global warming, vegetation is changing as climate changes. It is not doubt that human activities have great effects on the vegetation dynamic. In general, there are two aspects of the interaction between vegetation and climate, the climatic adaptation of vegetation and the vegetation feedback on climate. On the base of the research on the long term vegetation growth dynamics, it can be found out the vegetation adaptation to climate change. The dynamic change of vegetation is the direct indicator of the ecological environment changes. Therefore, study on the dynamic change of vegetation will be very interest and useful. In this paper, the vegetation change in special region of China will be described in detail. In addition to the methods of the long term in-situ observation of vegetation, remote sensing technologies can also be used to study the long time series vegetation dynamic. The widely used NDVI was often employed to monitor the status of vegetation growth. Actually, NDVI can indicate the vigor and the fractional cover of vegetation effectively. So the long time series of NDVI datasets are a very valuable data source supporting the study on the long term vegetation dynamics. Since 1980, a series of NOAA satellites have been launched successfully, which have already supplied more than 20 years NOAA/AVHRR satellites data. In this paper, we selected Ningxia Hui autonomic region of China as the case study area and used 20 years pathfinder AVHRR NDVI data to carry out the case study on the vegetation dynamics in order to further understand the phenomena of 20 years vegetation dynamics of the whole Ningxia region. Ningxia Hui autonomic region is one of provinces in west china. Ningxia is a small region with square area of about 66, 4000 km2. Ningxia has special land cover with irrigated crop land in north and natural grass land in central and south. In addition to NDVI data, we also collected land cover and land use data and administrative border vector data with the scale of 1:4,000,000 and other data. The results show that (1)vegetation dynamic of Ningxia presents the characters of one season per year with the length of the growth season from the first decade May to the middle decade October and the range of NDVI value 0.05-0.25; the season characters vary with the local area; the max value of NDVI in the central dry area is only 0.2 and the date of reaching the peak of time series NDVI in the irrigation area is the latest while that in the south mountain area is the earliest; the Helan mountain area presents the characters of forest and the range of NDVI is narrower than those in the irrigation area and the south mountain area and higher in winter than those in two area above; in recent 18 years, the length of growth season in whole Ningxia has prolonged one decade, mainly in spring one decade in advance.(2) from 1982 to 1999, the trend of the whole Ningxia mean NDVI is increasing and presents the stable or better of vegetation growth; compared to NDVI in 1980's, NDVI in 1990's has increased already and the anomaly of growth season mean NDVI is mainly negative in 1980's while mainly positive in 1990's; NDVI in the central dry area is the lowest while NDVI in the Helan mountain is the highest; the values of NDVI in the irrigation area, the Helan mountain area and the south mountain area are higher than that of the whole Ningxia; the increasing trend of vegetation dynamic in the irrigation area, the south mountain area and the central dry area is similar with the whole Ningxia while the trend in the Helan mountain area is increasing from 1982-1988 but decreasing after 1988.

Combining super-ensembles and statistical emulation to improve a regional climate and vegetation model

NASA Astrophysics Data System (ADS)

Hawkins, L. R.; Rupp, D. E.; Li, S.; Sarah, S.; McNeall, D. J.; Mote, P.; Betts, R. A.; Wallom, D.

2017-12-01

Changing regional patterns of surface temperature, precipitation, and humidity may cause ecosystem-scale changes in vegetation, altering the distribution of trees, shrubs, and grasses. A changing vegetation distribution, in turn, alters the albedo, latent heat flux, and carbon exchanged with the atmosphere with resulting feedbacks onto the regional climate. However, a wide range of earth-system processes that affect the carbon, energy, and hydrologic cycles occur at sub grid scales in climate models and must be parameterized. The appropriate parameter values in such parameterizations are often poorly constrained, leading to uncertainty in predictions of how the ecosystem will respond to changes in forcing. To better understand the sensitivity of regional climate to parameter selection and to improve regional climate and vegetation simulations, we used a large perturbed physics ensemble and a suite of statistical emulators. We dynamically downscaled a super-ensemble (multiple parameter sets and multiple initial conditions) of global climate simulations using a 25-km resolution regional climate model HadRM3p with the land-surface scheme MOSES2 and dynamic vegetation module TRIFFID. We simultaneously perturbed land surface parameters relating to the exchange of carbon, water, and energy between the land surface and atmosphere in a large super-ensemble of regional climate simulations over the western US. Statistical emulation was used as a computationally cost-effective tool to explore uncertainties in interactions. Regions of parameter space that did not satisfy observational constraints were eliminated and an ensemble of parameter sets that reduce regional biases and span a range of plausible interactions among earth system processes were selected. This study demonstrated that by combining super-ensemble simulations with statistical emulation, simulations of regional climate could be improved while simultaneously accounting for a range of plausible land-atmosphere feedback strengths.

The effects of anthropogenic land cover change on pollen-vegetation relationships in the American Midwest

USGS Publications Warehouse

Kujawa, Ellen Ruth; Goring, Simon; Dawson, Andria; Calcote, Randy; Grimm, Eric; Hotchkiss, Sara C.; Jackson, Stephen T.; Lynch, Elizabeth A.; McLachlan, Jason S.; St-Jacques, Jeannine-Marie; Umbanhowar, Charles; Williams, John W.

2016-01-01

Fossil pollen assemblages provide information about vegetation dynamics at time scales ranging from centuries to millennia. Pollen-vegetation models and process-based models of dispersal typically assume stable relationships between source vegetation and corresponding pollen in surface sediments, as well as stable parameterizations of dispersal and productivity. These assumptions, however, are largely unevaluated. This paper reports a test of the stability of pollen-vegetation relationships using vegetation and pollen data from the Midwestern region of the United States, during a period of large changes in land use and vegetation driven by Euro-American settlement. We compared a dataset of pollen records for the early settlement-era with three other datasets of pollen and forest composition for two time periods: before Euro-American settlement, and the late 20th century. Results from generalized linear models for thirteen genera indicate that pollen-vegetation relationships significantly differ (p < 0.05) between pre-settlement and the modern era for several genera: Fagus, Betula, Tsuga, Quercus, Pinus, and Picea. The estimated pollen source radius for the 8 km gridded vegetation data and associated pollen data is 25–85 km, consistent with prior studies using similar methods and spatial resolutions.Hence, the rapid changes in land cover associated with the Anthropocene affect the accuracy of ecological predictions for both the future and the past. In the Anthropocene, paleoecology should move beyond the assumption that pollen-vegetation relationships are stable over time. Multi-temporal calibration datasets are increasingly possible and enable paleoecologists to better understand the complex processes governing pollen-vegetation relationships through space and time.

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

NASA Astrophysics Data System (ADS)

Choler, P.; Sea, W.; Briggs, P.; Raupach, M.; Leuning, R.

2009-09-01

Modelling leaf phenology in water-controlled ecosystems remains a difficult task because of high spatial and temporal variability in the interaction of plant growth and soil moisture. Here, we move beyond widely used linear models to examine the performance of low-dimensional, nonlinear ecohydrological models that couple the dynamics of plant cover and soil moisture. The study area encompasses 400 000 km2 of semi-arid perennial tropical grasslands, dominated by C4 grasses, in the Northern Territory and Queensland (Australia). We prepared 8 yr time series (2001-2008) of climatic variables and estimates of fractional vegetation cover derived from MODIS Normalized Difference Vegetation Index (NDVI) for 400 randomly chosen sites, of which 25% were used for model calibration and 75% for model validation. We found that the mean absolute error of linear and nonlinear models did not markedly differ. However, nonlinear models presented key advantages: (1) they exhibited far less systematic error than their linear counterparts; (2) their error magnitude was consistent throughout a precipitation gradient while the performance of linear models deteriorated at the driest sites, and (3) they better captured the sharp transitions in leaf cover that are observed under high seasonality of precipitation. Our results showed that low-dimensional models including feedbacks between soil water balance and plant growth adequately predict leaf dynamics in semi-arid perennial grasslands. Because these models attempt to capture fundamental ecohydrological processes, they should be the favoured approach for prognostic models of phenology.

A simple ecohydrological model captures essentials of seasonal leaf dynamics in semi-arid tropical grasslands

NASA Astrophysics Data System (ADS)

Choler, P.; Sea, W.; Briggs, P.; Raupach, M.; Leuning, R.

2010-03-01

Modelling leaf phenology in water-controlled ecosystems remains a difficult task because of high spatial and temporal variability in the interaction of plant growth and soil moisture. Here, we move beyond widely used linear models to examine the performance of low-dimensional, nonlinear ecohydrological models that couple the dynamics of plant cover and soil moisture. The study area encompasses 400 000 km2 of semi-arid perennial tropical grasslands, dominated by C4 grasses, in the Northern Territory and Queensland (Australia). We prepared 8-year time series (2001-2008) of climatic variables and estimates of fractional vegetation cover derived from MODIS Normalized Difference Vegetation Index (NDVI) for 400 randomly chosen sites, of which 25% were used for model calibration and 75% for model validation. We found that the mean absolute error of linear and nonlinear models did not markedly differ. However, nonlinear models presented key advantages: (1) they exhibited far less systematic error than their linear counterparts; (2) their error magnitude was consistent throughout a precipitation gradient while the performance of linear models deteriorated at the driest sites, and (3) they better captured the sharp transitions in leaf cover that are observed under high seasonality of precipitation. Our results showed that low-dimensional models including feedbacks between soil water balance and plant growth adequately predict leaf dynamics in semi-arid perennial grasslands. Because these models attempt to capture fundamental ecohydrological processes, they should be the favoured approach for prognostic models of phenology.

Spatiotemporal variability and predictability of Normalized Difference Vegetation Index (NDVI) in Alberta, Canada.

PubMed

Jiang, Rengui; Xie, Jiancang; He, Hailong; Kuo, Chun-Chao; Zhu, Jiwei; Yang, Mingxiang

2016-09-01

As one of the most popular vegetation indices to monitor terrestrial vegetation productivity, Normalized Difference Vegetation Index (NDVI) has been widely used to study the plant growth and vegetation productivity around the world, especially the dynamic response of vegetation to climate change in terms of precipitation and temperature. Alberta is the most important agricultural and forestry province and with the best climatic observation systems in Canada. However, few studies pertaining to climate change and vegetation productivity are found. The objectives of this paper therefore were to better understand impacts of climate change on vegetation productivity in Alberta using the NDVI and provide reference for policy makers and stakeholders. We investigated the following: (1) the variations of Alberta's smoothed NDVI (sNDVI, eliminated noise compared to NDVI) and two climatic variables (precipitation and temperature) using non-parametric Mann-Kendall monotonic test and Thiel-Sen's slope; (2) the relationships between sNDVI and climatic variables, and the potential predictability of sNDVI using climatic variables as predictors based on two predicted models; and (3) the use of a linear regression model and an artificial neural network calibrated by the genetic algorithm (ANN-GA) to estimate Alberta's sNDVI using precipitation and temperature as predictors. The results showed that (1) the monthly sNDVI has increased during the past 30 years and a lengthened growing season was detected; (2) vegetation productivity in northern Alberta was mainly temperature driven and the vegetation in southern Alberta was predominantly precipitation driven for the period of 1982-2011; and (3) better performances of the sNDVI-climate relationships were obtained by nonlinear model (ANN-GA) than using linear (regression) model. Similar results detected in both monthly and summer sNDVI prediction using climatic variables as predictors revealed the applicability of two models for different period of year ecologists might focus on.

Circumpolar arctic tundra biomass and productivity dynamics in response to projected climate change and herbivory.

PubMed

Yu, Qin; Epstein, Howard; Engstrom, Ryan; Walker, Donald

2017-09-01

Satellite remote sensing data have indicated a general 'greening' trend in the arctic tundra biome. However, the observed changes based on remote sensing are the result of multiple environmental drivers, and the effects of individual controls such as warming, herbivory, and other disturbances on changes in vegetation biomass, community structure, and ecosystem function remain unclear. We apply ArcVeg, an arctic tundra vegetation dynamics model, to estimate potential changes in vegetation biomass and net primary production (NPP) at the plant community and functional type levels. ArcVeg is driven by soil nitrogen output from the Terrestrial Ecosystem Model, existing densities of Rangifer populations, and projected summer temperature changes by the NCAR CCSM4.0 general circulation model across the Arctic. We quantified the changes in aboveground biomass and NPP resulting from (i) observed herbivory only; (ii) projected climate change only; and (iii) coupled effects of projected climate change and herbivory. We evaluated model outputs of the absolute and relative differences in biomass and NPP by country, bioclimate subzone, and floristic province. Estimated potential biomass increases resulting from temperature increase only are approximately 5% greater than the biomass modeled due to coupled warming and herbivory. Such potential increases are greater in areas currently occupied by large or dense Rangifer herds such as the Nenets-occupied regions in Russia (27% greater vegetation increase without herbivores). In addition, herbivory modulates shifts in plant community structure caused by warming. Plant functional types such as shrubs and mosses were affected to a greater degree than other functional types by either warming or herbivory or coupled effects of the two. © 2017 John Wiley & Sons Ltd.

Soil-geomorphic heterogeneity governs patchy vegetation dynamics at an arid ecotone.

PubMed

Bestelmeyer, Brandon T; Ward, Judy P; Havstad, Kris M

2006-04-01

Soil properties are well known to affect vegetation, but the role of soil heterogeneity in the patterning of vegetation dynamics is poorly documented. We asked whether the location of an ecotone separating grass-dominated and sparsely vegetated areas reflected only historical variation in degradation or was related to variation in inherent soil properties. We then asked whether changes in the cover and spatial organization of vegetated and bare patches assessed using repeat aerial photography reflected self-organizing dynamics unrelated to soil variation or the stable patterning of soil variation. We found that the present-day ecotone was related to a shift from more weakly to more strongly developed soils. Parts of the ecotone were stable over a 60-year period, but shifts between bare and vegetated states, as well as persistently vegetated and bare states, occurred largely in small (<40 m2) patches throughout the study area. The probability that patches were presently vegetated or bare, as well as the probability that vegetation persisted and/or established over the 60-year period, was negatively related to surface calcium carbonate and positively related to subsurface clay content. Thus, only a fraction of the landscape was susceptible to vegetation change, and the sparsely vegetated area probably featured a higher frequency of susceptible soil patches. Patch dynamics and self-organizing processes can be constrained by subtle (and often unrecognized) soil heterogeneity.

Ecogeomorphology of Sand Dunes Shaped by Vegetation

NASA Astrophysics Data System (ADS)

Tsoar, H.

2014-12-01

Two dune types associated with vegetation are known: Parabolic and Vegetated Linear Dunes (VLDs), the latters are the dominant dune type in the world deserts. Parabolic dunes are formed in humid, sub-humid and semi-arid environments (rather than arid) where vegetation is nearby. VLDs are known today in semiarid and arid lands where the average yearly rainfall is ≥100 mm, enough to support sparse cover of vegetation. These two dune types are formed by unidirectional winds although they demonstrate a different form and have a distinct dynamics. Conceptual and mathematical models of dunes mobility and stability, based on three control parameters: wind power (DP), average annual precipitation (p), and the human impact parameter (μ) show that where human impact is negligible the effect of wind power (DP) on vegetative cover is substantial. The average yearly rainfall of 60-80 mm is the threshold of annual average rainfall for vegetation growth on dune sand. The model is shown to follow a hysteresis path, which explains the bistability of active and stabilized dunes under the same climatic conditions with respect to wind power. We have discerned formation of parabolic dunes from barchans and transverse dunes in the coastal plain of Israel where a decrease in human activity during the second half of the 20th century caused establishment of vegetation on the crest of the dunes, a process that changed the dynamics of these barchans and transverse dunes and led to a change in the shape of the windward slope from convex to concave. These dunes gradually became parabolic. It seems that VLDs in Australia or the Kalahari have always been vegetated to some degree, though the shrubs were sparser in colder periods when the aeolian erosion was sizeable. Those ancient conditions are characterized by higher wind power and lower rainfall that can reduce, but not completely destroy, the vegetation cover, leading to the formation of lee (shadow) dunes behind each shrub. Formation of such VLDs can occur today in some coasts where the wind is quite strong and the rain can support some shrubs.

LPJ-GUESS Simulated Western North America Mid-latitude Vegetation Changes for 15-10 ka Using the CCSM3 TraCE Climate Simulation

NASA Astrophysics Data System (ADS)

Shafer, S. L.; Bartlein, P. J.

2017-12-01

The period from 15-10 ka was a time of rapid vegetation changes in North America. Continental ice sheets in northern North America were receding, exposing new habitat for vegetation, and regions distant from the ice sheets experienced equally large environmental changes. Northern hemisphere temperatures during this period were increasing, promoting transitions from cold-adapted to temperate plant taxa at mid-latitudes. Long, transient paleovegetation simulations can provide important information on vegetation responses to climate changes, including both the spatial dynamics and rates of species distribution changes over time. Paleovegetation simulations also can fill the spatial and temporal gaps in observed paleovegetation records (e.g., pollen data from lake sediments), allowing us to test hypotheses about past vegetation changes (e.g., the location of past refugia). We used the CCSM3 TraCE transient climate simulation as input for LPJ-GUESS, a general ecosystem model, to simulate vegetation changes from 15-10 ka for parts of western North America at mid-latitudes ( 35-55° N). For these simulations, LPJ-GUESS was parameterized to simulate key tree taxa for western North America (e.g., Pseudotsuga, Tsuga, Quercus, etc.). The CCSM3 TraCE transient climate simulation data were regridded onto a 10-minute grid of the study area. We analyzed the simulated spatial and temporal dynamics of these taxa and compared the simulated changes with observed paleovegetation changes recorded in pollen and plant macrofossil data (e.g., data from the Neotoma Paleoecology Database). In general, the LPJ-GUESS simulations reproduce the general patterns of paleovegetation responses to climate change, although the timing of some simulated vegetation changes do not match the observed paleovegetation record. We describe the areas and time periods with the greatest data-model agreement and disagreement, and discuss some of the strengths and weaknesses of the simulated climate and vegetation data. The magnitude and rate of the simulated past vegetation changes are compared with projected future vegetation changes for the region.

A fully traits-based approach to modeling global vegetation distribution.

PubMed

van Bodegom, Peter M; Douma, Jacob C; Verheijen, Lieneke M

2014-09-23

Dynamic Global Vegetation Models (DGVMs) are indispensable for our understanding of climate change impacts. The application of traits in DGVMs is increasingly refined. However, a comprehensive analysis of the direct impacts of trait variation on global vegetation distribution does not yet exist. Here, we present such analysis as proof of principle. We run regressions of trait observations for leaf mass per area, stem-specific density, and seed mass from a global database against multiple environmental drivers, making use of findings of global trait convergence. This analysis explained up to 52% of the global variation of traits. Global trait maps, generated by coupling the regression equations to gridded soil and climate maps, showed up to orders of magnitude variation in trait values. Subsequently, nine vegetation types were characterized by the trait combinations that they possess using Gaussian mixture density functions. The trait maps were input to these functions to determine global occurrence probabilities for each vegetation type. We prepared vegetation maps, assuming that the most probable (and thus, most suited) vegetation type at each location will be realized. This fully traits-based vegetation map predicted 42% of the observed vegetation distribution correctly. Our results indicate that a major proportion of the predictive ability of DGVMs with respect to vegetation distribution can be attained by three traits alone if traits like stem-specific density and seed mass are included. We envision that our traits-based approach, our observation-driven trait maps, and our vegetation maps may inspire a new generation of powerful traits-based DGVMs.

Infrastructure effects on estuarine wetlands increase their vulnerability to sea level rise

NASA Astrophysics Data System (ADS)

Rodriguez, Jose; Saco, Patricia; Sandi, Steven; Saintilan, Neil; Riccardi, Gerardo

2017-04-01

At the regional and global scales, coastal management and planning for future sea level rise scenarios is typically supported by modelling tools that predict the expected inundation extent. These tools rely on a number of simplifying assumptions that, in some cases, may result in important miscalculation of the inundation effects. One of such cases is estuarine wetlands, where vegetation strongly depends on both the magnitude and the timing of inundation. Many coastal wetlands display flow restrictions due to infrastructure or drainage works, which produce alterations to the inundation patterns that can not be captured by conventional models. In this contribution we explore the effects of flow restrictions on inundation patterns under sea level rise conditions in estuarine wetlands. We use a spatially-distributed dynamic wetland ecogeomorphological model that not only incorporates the effects of flow restrictions due to culverts, bridges and weirs as well as vegetation, but also considers that vegetation changes as a consequence of increasing inundation. We also consider the ability of vegetation to capture sediment and produce accretion. We apply our model to an estuarine wetland in Australia and show that our model predicts a much faster wetland loss due to sea level rise than conventional approaches.

Bayesian inference of the groundwater depth threshold in a vegetation dynamic model: a case study, lower reach, Tarim River

USDA-ARS?s Scientific Manuscript database

The responses of eco-hydrological systems to anthropogenic and natural disturbances have attracted much attention in recent years. The coupling and simulating feedback between hydrological and ecological components have been realized in several recently developed eco-hydrological models. However, li...

Vegetation and Carbon Cycle Dynamics in the High-Resolution Transient Holocene Simulations Using the MPI Earth System Model

NASA Astrophysics Data System (ADS)

Brovkin, V.; Lorenz, S.; Raddatz, T.; Claussen, M.; Dallmeyer, A.

2017-12-01

One of the interesting periods to investigate a climatic role of terrestrial biosphere is the Holocene, when, despite of the relatively steady global climate, the atmospheric CO2 grew by about 20 ppm from 7 kyr BP to pre-industrial. We use a new setup of the Max Planck Institute Earth System Model MPI-ESM1 consisting of the latest version of the atmospheric model ECHAM6, including the land surface model JSBACH3 with carbon cycle and vegetation dynamics, coupled to the ocean circulation model MPI-OM, which includes the HAMOCC model of ocean biogeochemistry. The model has been run for several simulations over the Holocene period of the last 8000 years under the forcing data sets of orbital insolation, atmospheric greenhouse gases, volcanic aerosols, solar irradiance and stratospheric ozone, as well as land-use changes. In response to this forcing, the land carbon storage increased by about 60 PgC between 8 and 4 kyr BP, stayed relatively constant until 2 kyr BP, and decreased by about 90 PgC by 1850 AD due to land use changes. At 8 kyr BP, vegetation cover was much denser in Africa, mainly due to increased rainfall in response to the orbital forcing. Boreal forests moved northward in both, North America and Eurasia. The boreal forest expansion in North America is much less pronounced than in Eurasia. Simulated physical ocean fields, including surface temperatures and meridional overturning, do not change substantially in the Holocene. Carbonate ion concentration in deep ocean decreases in both, prescribed and interactive CO2simulations. Comparison with available proxies for terrestrial vegetation and for the ocean carbonate chemistry will be presented. Vegetation and soil carbon changes significantly affected atmospheric CO2 during the periods of strong volcanic eruptions. In response to the eruption-caused cooling, the land initially stores more carbon as respiration decreases, but then it releases even more carbon die to productivity decrease. This decadal-scale variability helps to quantify the vegetation and land carbon feedbacks during the past periods when the temporal resolution of the ice-core CO2 record is not sufficient to capture fast CO2 variations. From a set of Holocene simulations with prescribed or interactive atmospheric CO2, we get estimates of climate-carbon feedback useful for future climate studies.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Technical Reports Server (NTRS)

Koster, Randal; Walker, G.; Thornton, Patti; Collatz, G. J.

2012-01-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

Hydroclimatic Controls over Global Variations in Phenology and Carbon Flux

NASA Astrophysics Data System (ADS)

Koster, R. D.; Walker, G.; Thornton, P. E.; Collatz, G. J.

2012-12-01

The connection between phenological and hydroclimatological variations are quantified through joint analyses of global NDVI, LAI, and precipitation datasets. The global distributions of both NDVI and LAI in the warm season are strongly controlled by three quantities: mean annual precipitation, the standard deviation of annual precipitation, and Budyko's index of dryness. Upon demonstrating that these same basic (if somewhat biased) relationships are produced by a dynamic vegetation model (the dynamic vegetation and carbon storage components of the NCAR Community Land Model version 4 combined with the water and energy balance framework of the Catchment Land Surface Model of the NASA Global Modeling and Assimilation Office), we use the model to perform a sensitivity study focusing on how phenology and carbon flux might respond to climatic change. The offline (decoupled from the atmosphere) simulations show us, for example, where on the globe a given small increment in precipitation mean or variability would have the greatest impact on carbon uptake. The analysis framework allows us in addition to quantify the degree to which climatic biases in a free-running GCM are manifested as biases in simulated phenology.

The role of evapotranspiration fluxes in summertime precipitation in Central Europe: coupled groundwater-atmosphere simulations with the WRF-LEAFHYDRO system.

NASA Astrophysics Data System (ADS)

Regueiro Sanfiz, Sabela; Gómez, Breo; Miguez Macho, Gonzalo

2017-04-01

Because of its continental position, Central Europe summertime rainfall is largely dependent on local or regional dynamics, with precipitation water possibly also significantly dependent on local sources. We investigate here land-atmosphere feedbacks over inland Europe focusing in particular on evapotranspiration-soil moisture connections and precipitation recycling ratios. For this purpose, a set of simulations were performed with the Weather Research and Forecasting (WRF) model coupled to LEAFHYDRO soil-vegetation-hydrology model. The LEAFHYDRO Land Surface Model includes a groundwater parameterization with a dynamic water table fully coupling groundwater to the soil-vegetation and surface waters via two-way fluxes. A water tagging capability in the WRF model is used to quantify evapotranspiration contribution to precipitation over the region. Several years are considered, including summertime 2002, during which severe flooding occurred. Preliminary results from our simulations highlight the link of large areas with shallow water with high air moisture values through the summer season; and the importance of the contribution of evapotranspiration to summertime precipitation. Consequently, results show the advantages of using a fully coupled hydrology-atmospheric modeling system.

Topography and vegetation alter soil nitrogen availability and loss in tropical and temperate ecosystems

NASA Astrophysics Data System (ADS)

Weintraub, S. R.

2016-12-01

A dominant paradigm in ecosystem ecology holds that nitrogen (N) cycles as an excess nutrient in old tropical landscapes but is a scarce, limiting resource in young, temperate ecosystems. However, recent work suggests that both biotic and abiotic state factors can promote unexpected patterns of N cycling across complex landscapes. Here, I present two case studies demonstrating how topography and vegetation shape patterns of N cycling and loss in heterogeneous terrain. In a geomorphically dynamic, high-diversity tropical rainforest, flat ridge tops display open N cycling, yet eroding hillslopes are surprisingly N-poor with multiple indicators implying conservative N cycling. Soil mineralogy indicates slope soils are less developed than adjacent flat ridge counterparts, and the accumulation of cosmogenic 10Be in surface soil suggests residence times are only half as long. Together, these observations suggest erosion resets soil development, with constant N-removal promoting tight N-cycling. Further, soil δ15N is negatively correlated with slope angle across the landscape, and mass balance modeling supports an increasing role for erosive N loss in steep regions. In a temperate montane landscape with lower physical erosion rates, vegetation interacts with hydro-topographic position to mediate local N dynamics. Upslope, forests display conservative N-cycling, yet in adjacent herbaceous areas, multiple indicators point toward an open N cycle. Downslope, both vegetation types show an increase in N-richness. In downslope forests, this is confined to the near-surface, stemming from higher foliar N content due to lateral N transport and uptake. In herbaceous sites, deeper vadose-zone N transport occurs but with no change in foliar N, implying differences in the degree of N limitation between vegetation types. In this landscape, soil nitrate leaching rates track N availability, though δ15N-NO3- does not suggest a similar pattern for gaseous losses, instead reflecting nitrification and/or transport dynamics. Pervasive human alteration of the N cycle underscores the need to unravel these state-factor controls on N availability and loss in order to predict and model ecosystem biogeochemical dynamics in the face of global change.

Dynamics of skimming flow in the wake of a vegetation patch

NASA Astrophysics Data System (ADS)

Mayaud, Jerome R.; Wiggs, Giles F. S.; Bailey, Richard M.

2016-09-01

Dryland vegetation is often spatially patchy, and so affects wind flow in complex ways. Theoretical models and wind tunnel testing have shown that skimming flow develops above vegetation patches at high plant densities, resulting in little or no wind erosion in these zones. Understanding the dynamics of skimming flow is therefore important for predicting sediment transport and bedform development in dryland areas. However, no field-based data are available describing turbulent airflow dynamics in the wake of vegetation patches. In this study, turbulent wind flow was examined using high-frequency (10 Hz) sonic anemometry at four measurement heights (0.30 m, 0.55 m, 1.10 m and 1.65 m) along a transect in the lee of an extensive patch of shrubs (z = 1.10 m height) in Namibia. Spatial variations in mean wind velocity, horizontal Reynolds stresses and coherent turbulent structures were analysed. We found that wind velocity in the wake of the patch effectively recovered over ∼12 patch heights (h) downwind, which is 2-5 h longer than previously reported recovery lengths for individual vegetation elements and two-dimensional wind fences. This longer recovery can be attributed to a lack of flow moving around the obstacle in the patch case. The step-change in roughness between the patch canopy and the bare surface in its wake resulted in an initial peak in resultant horizontal shear stress (τr) followed by significant decrease downwind. In contrast to τr , horizontal normal Reynolds stress (u‧2 ‾) progressively increased along the patch wake. A separation of the upper shear layer at the leeside edge of the patch was observed, and a convergence of τr curves implies the formation of a constant stress layer by ∼20 h downwind. The use of τr at multiple heights is found to be a useful tool for identifying flow equilibration in complex aerodynamic regimes. Quadrant analysis revealed elevated frequencies of Q2 (ejection) and Q4 (sweep) events in the immediate lee of the patch, which contributed to the observed high levels of shear stress. The increasing downwind contribution of Q1 (outward interaction) events, which coincides with greater u‧2 ‾ and wind velocity, suggests that sediment transport potential increases with greater distance from the patch edge. Determining realistic, field-derived constraints on turbulent airflow dynamics in the wakes of vegetation patches is crucial for accurately parameterising sediment transport potential in larger-scale dryland landscape models. This will help to improve our understanding of how semi-vegetated desert surfaces might react to future environmental and anthropogenic stresses.

Dynamic coupling of regional atmosphere to biosphere in the new generation regional climate system model REMO-iMOVE

NASA Astrophysics Data System (ADS)

Wilhelm, C.; Rechid, D.; Jacob, D.

2013-05-01

The main objective of this study is the coupling of the regional climate model REMO to a 3rd generation land surface scheme and the evaluation of the new model version of REMO, called REMO with interactive MOsaic-based VEgetation: REMO-iMOVE. Attention is paid to the documentation of the technical aspects of the new model constituents and the coupling mechanism. We compare simulation results of REMO-iMOVE and of the reference version REMO2009, to investigate the sensitivity of the regional model to the new land surface scheme. An 11 yr climate model run (1995-2005), forced with ECMWF ERA-Interim lateral boundary conditions, over Europe in 0.44° resolution of both model versions was carried out, to represent present day European climate. The result of these experiments are compared to multiple temperature, precipitation, heat flux and leaf area index observation data, to determine the differences in the model versions. The new model version has further the ability to model net primary productivity for the given plant functional types. This new feature is thoroughly evaluated by literature values of net primary productivity of different plant species in European climatic regions. The new model version REMO-iMOVE is able to model the European climate in the same quality as the parent model version REMO2009 does. The differences in the results of the two model versions stem from the differences in the dynamics of vegetation cover and density and can be distinct in some regions, due to the influences of these parameters to the surface heat and moisture fluxes. The modeled inter-annual variability in the phenology as well as the net primary productivity lays in the range of observations and literature values for most European regions. This study also reveals the need for a more sophisticated soil moisture representation in the newly developed model version REMO-iMOVE to be able to treat the differences in plant functional types. This gets especially important if the model will be used in dynamic vegetation studies.

Multifractal Model of Soil Water Erosion

NASA Astrophysics Data System (ADS)

Oleshko, Klaudia

2017-04-01

Breaking of solid surface symmetry during the interaction between the rainfall of high erosivity index and internally unstable volcanic soil/vegetation systems, results in roughness increasing as well as fertile horizon loosing. In these areas, the sustainability of management practices depends on the ability to select and implement the precise indicators of soil erodibility and vegetation capacity to protect the system against the extreme damaging precipitation events. Notwithstanding, the complex, non-linear and scaling nature of the phenomena involved in the interaction among the soil, vegetation and precipitation is still not taken into account by the numerous commonly used empirical, mathematical and computer simulation models: for instance, by the universal soil loss equation (USLE). The soil erodibility factor (K-factor) is still measuring by a set of empirical, dimensionless parameters and indexes, without taking into account the scaling (frequently multifractal) origin of a broad range of heterogeneous, anisotropic and dynamical phenomena involved in hydric erosion. Their mapping is not representative of this complex system spatial variability. In our research, we propose to use the toolbox of fractals and multifractals techniques in vista of its ability to measure the scale invariance and type/degree of soil, vegetation and precipitation symmetry breaking. The hydraulic units are chosen as the precise measure of soil/vegetation stability. These units are measured and modeled for soils with contrasting architecture, based on their porosity/permeability (Poroperm) as well as retention capacity relations. The simple Catalog of the most common Poroperm relations is proposed and the main power law relations among the elements of studied system are established and compared for some representative agricultural and natural Biogeosystems of Mexico. All resulted are related with the Mandelbrot' Baby Theorem in order to construct the universal Phase Diagram which graphically represents the critical points of the dynamics of soil erodibility as function of the vegetation cover and precipitation parameters.

Assessing vegetation structure and ANPP dynamics in a grassland-shrubland Chihuahuan ecotone using NDVI-rainfall relationships

NASA Astrophysics Data System (ADS)

Moreno-de las Heras, M.; Diaz-Sierra, R.; Turnbull, L.; Wainwright, J.

2015-01-01

Climate change and the widespread alteration of natural habitats are major drivers of vegetation change in drylands. A classic case of vegetation change is the shrub-encroachment process that has been taking place over the last 150 years in the Chihuahuan Desert, where large areas of grasslands dominated by perennial grass species (black grama, Bouteloua eriopoda, and blue grama, B. gracilis) have transitioned to shrublands dominated by woody species (creosotebush, Larrea tridentata, and mesquite, Prosopis glandulosa), accompanied by accelerated water and wind erosion. Multiple mechanisms drive the shrub-encroachment process, including exogenous triggering factors such as precipitation variations and land-use change, and endogenous amplifying mechanisms brought about by soil erosion-vegetation feedbacks. In this study, simulations of plant biomass dynamics with a simple modelling framework indicate that herbaceous (grasses and forbs) and shrub vegetation in drylands have different responses to antecedent precipitation due to functional differences in plant growth and water-use patterns, and therefore shrub encroachment may be reflected in the analysis of landscape-scale vegetation-rainfall relationships. We analyze the structure and dynamics of vegetation at an 18 km2 grassland-shrubland ecotone in the northern edge of the Chihuahuan Desert (McKenzie Flats, Sevilleta National Wildlife Refuge, NM, USA) by investigating the relationship between decade-scale (2000-2013) records of medium-resolution remote sensing of vegetation greenness (MODIS NDVI) and precipitation. Spatial evaluation of NDVI-rainfall relationship at the studied ecotone indicates that herbaceous vegetation shows quick growth pulses associated with short-term (previous 2 months) precipitation, while shrubs show a slow response to medium-term (previous 5 months) precipitation. We use these relationships to (a) classify landscape types as a function of the spatial distribution of dominant vegetation, and to (b) decompose the NDVI signal into partial primary production components for herbaceous vegetation and shrubs across the study site. We further apply remote-sensed annual net primary production (ANPP) estimations and landscape type classification to explore the influence of inter-annual variations in seasonal precipitation on the production of herbaceous and shrub vegetation. Our results suggest that changes in the amount and temporal pattern of precipitation comprising reductions in monsoonal summer rainfall and/or increases in winter precipitation may enhance the shrub-encroachment process in desert grasslands of the American Southwest.

Time series evaluation of landscape dynamics using annual Landsat imagery and spatial statistical modeling: Evidence from the Phoenix metropolitan region

NASA Astrophysics Data System (ADS)

Fan, Chao; Myint, Soe W.; Rey, Sergio J.; Li, Wenwen

2017-06-01

Urbanization is a natural and social process involving simultaneous changes to the Earth's land systems, energy flow, demographics, and the economy. Understanding the spatiotemporal pattern of urbanization is increasingly important for policy formulation, decision making, and natural resource management. A combination of satellite remote sensing and patch-based models has been widely adopted to characterize landscape changes at various spatial and temporal scales. Nevertheless, the validity of this type of framework in identifying long-term changes, especially subtle or gradual land modifications is seriously challenged. In this paper, we integrate annual image time series, continuous spatial indices, and non-parametric trend analysis into a spatiotemporal study of landscape dynamics over the Phoenix metropolitan area from 1991 to 2010. We harness local indicators of spatial dependence and modified Mann-Kendall test to describe the monotonic trends in the quantity and spatial arrangement of two important land use land cover types: vegetation and built-up areas. Results suggest that declines in vegetation and increases in built-up areas are the two prevalent types of changes across the region. Vegetation increases mostly occur at the outskirts where new residential areas are developed from natural desert. A sizable proportion of vegetation declines and built-up increases are seen in the central and southeast part. Extensive land conversion from agricultural fields into urban land use is one important driver of vegetation declines. The xeriscaping practice also contributes to part of vegetation loss and an increasingly heterogeneous landscape. The quantitative framework proposed in this study provides a pathway to effective landscape mapping and change monitoring from a spatial statistical perspective.

Monitoring Urban Greenness Dynamics Using Multiple Endmember Spectral Mixture Analysis

PubMed Central

Gan, Muye; Deng, Jinsong; Zheng, Xinyu; Hong, Yang; Wang, Ke

2014-01-01

Urban greenness is increasingly recognized as an essential constituent of the urban environment and can provide a range of services and enhance residents’ quality of life. Understanding the pattern of urban greenness and exploring its spatiotemporal dynamics would contribute valuable information for urban planning. In this paper, we investigated the pattern of urban greenness in Hangzhou, China, over the past two decades using time series Landsat-5 TM data obtained in 1990, 2002, and 2010. Multiple endmember spectral mixture analysis was used to derive vegetation cover fractions at the subpixel level. An RGB-vegetation fraction model, change intensity analysis and the concentric technique were integrated to reveal the detailed, spatial characteristics and the overall pattern of change in the vegetation cover fraction. Our results demonstrated the ability of multiple endmember spectral mixture analysis to accurately model the vegetation cover fraction in pixels despite the complex spectral confusion of different land cover types. The integration of multiple techniques revealed various changing patterns in urban greenness in this region. The overall vegetation cover has exhibited a drastic decrease over the past two decades, while no significant change occurred in the scenic spots that were studied. Meanwhile, a remarkable recovery of greenness was observed in the existing urban area. The increasing coverage of small green patches has played a vital role in the recovery of urban greenness. These changing patterns were more obvious during the period from 2002 to 2010 than from 1990 to 2002, and they revealed the combined effects of rapid urbanization and greening policies. This work demonstrates the usefulness of time series of vegetation cover fractions for conducting accurate and in-depth studies of the long-term trajectories of urban greenness to obtain meaningful information for sustainable urban development. PMID:25375176

Use of MODIS Data in Dynamic SPARROW Analysis of Watershed Loading Reductions

NASA Astrophysics Data System (ADS)

Smith, R. A.; Schwarz, G. E.; Brakebill, J. W.; Hoos, A.; Moore, R. B.; Nolin, A. W.; Shih, J. S.; Journey, C. A.; Macauley, M.

2014-12-01

Predicting the temporal response of stream water quality to a proposed reduction in contaminant loading is a major watershed management problem due to temporary storage of contaminants in groundwater, vegetation, snowpack, etc. We describe the response of dynamically calibrated SPARROW models of total nitrogen (TN) flux to hypothetical reductions in reactive nitrogen inputs in three sub-regional watersheds: Potomac River Basin (Chesapeake Bay drainage), Long Island Sound drainage, and South Carolina coastal drainage. The models are based on seasonal water quality and watershed input data from 170 monitoring stations for the period 2002 to 2008.The spatial reference frames of the three models are stream networks containing an average 38,000 catchments and the time step is seasonal. We use MODIS Enhanced Vegetation Index (EVI) and snow/ice cover data to parameterize seasonal uptake and release of nitrogen from vegetation and snowpack. The model accounts for storage of total nitrogen inputs from fertilized cropland, pasture, urban land, and atmospheric deposition. Model calibration is by non-linear regression. Model source terms based on previous season export allow for recursive simulation of stream flux and can be used to estimate the approximate residence times of TN in the watersheds. Catchment residence times in the Long Island Sound Basin are shorter (typically < 1 year) than in the Potomac or South Carolina Basins (typically > 1 year), in part, because a significant fraction of nitrogen flux derives from snowmelt and occurs within one season of snowfall. We use the calibrated models to examine the response of TN flux to hypothetical step reductions in source inputs at the beginning of the 2002-2008 period and the influence of observed fluctuations in precipitation, temperature, vegetation growth and snow melt over the period. Following non-point source reductions of up to 100%, stream flux was found to continue to vary greatly for several years as a function of seasonal conditions, with high values in both winter (January, February, March) and spring due to high precipitation and snow melt, but much lower summer yields due to low precipitation and nitrogen retention in growing vegetation (EVI). Temporal variations in stream flux are large enough to potentially mask water quality improvements for several years.

A dynamic growth model of vegetative soya bean plants: model structure and behaviour under varying root temperature and nitrogen concentration

NASA Technical Reports Server (NTRS)

Lim, J. T.; Wilkerson, G. G.; Raper, C. D. Jr; Gold, H. J.

1990-01-01

A differential equation model of vegetative growth of the soya bean plant (Glycine max (L.) Merrill cv. Ransom') was developed to account for plant growth in a phytotron system under variation of root temperature and nitrogen concentration in nutrient solution. The model was tested by comparing model outputs with data from four different experiments. Model predictions agreed fairly well with measured plant performance over a wide range of root temperatures and over a range of nitrogen concentrations in nutrient solution between 0.5 and 10.0 mmol NO3- in the phytotron environment. Sensitivity analyses revealed that the model was most sensitive to changes in parameters relating to carbohydrate concentration in the plant and nitrogen uptake rate.

Modelling the impact of vegetation on marly catchments in the Southern Alps of France

NASA Astrophysics Data System (ADS)

Carriere, Alexandra; Le Bouteiller, Caroline; Tucker, Greg; Naaim, Mohamed

2017-04-01

The Southern Alps of France have been identified as a hot-spot in a global climate change context where the rainfall intensity increase may exacerbate the erosion of already badly erodible lands: Badlands. Vegetalization methods are a promising area of research for erosion control and slope and riverbed stabilization. Nevertheless the impact of vegetation on erosive dynamics is still poorly understood. We own data collected over the last thirty years on marly catchments in the Southern Alps of France from the Draix-Bléone Observatory, part of the Network of Drainage Basins RBV. These are temporal data of sedimentary flux at the scale of the precipitation event but also more recent topographic data on watersheds with areas ranging from 10-3 square kilometers to twenty square kilometers. Erosion rates in this landscape reach 1 cm per year. We simulate the topographic evolution of the catchments over a few decades to centuries with the landscape evolution model Landlab, using our data to calibrate and explicitly validate the model. This model, in comparison with other landscape evolution models, incorporates a more advanced vegetation module in terms of ecology. Nevertheless the erosion-vegetation coupling is not present in Landlab and we are working on its construction. To this end we use an erosion module and a vegetation module that we seek to couple. We want to see how the erosion laws parameters depend on the vegetation cover. We have implemented the calibration of parameters of a non-linear diffusion module coupled with a transport-limited law by comparing the simulated annual sediment flux with the one of the data of the observatory as a function of the percentage of vegetation cover of the ground. We obtained average values of parameters adjusted according to vegetation cover. We observe that the values of the erosion laws parameters are strongly affected by the percentage of vegetation cover. We will then spatialize these parameters on our vegetation maps in order to obtain different parameter values for different types of vegetation.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Li, Xuecao; Zhou, Yuyu; Asrar, Ghassem R.

Seasonal phenology of vegetation plays an important role in global carbon cycle and ecosystem productivity. In urban environments, vegetation phenology is also important because of its influence on public health (e.g., allergies), and energy demand (e.g. cooling effects). In this study, we studied the potential use of remotely sensed observations (i.e. Landsat data) to derive some phenology indicators for vegetation embedded within the urban core domains in four distinctly different U.S. regions (Washington, D.C., King County in Washington, Polk County in Iowa, and Baltimore City and County in Maryland) during the past three decades. We used all available Landsat observationsmore » (circa 3000 scenes) from 1982 to 2015 and a self-adjusting double logistic model to detect and quantify the annual change of vegetation phenophases, i.e. indicators of seasonal changes in vegetation. The proposed model can capture and quantify not only phenophases of dense vegetation in rural areas, but also those of mixed vegetation in urban core domains. The derived phenology indicators show a good agreement with similar indicators derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in situ observations, suggesting that the phenology dynamic depicted by the proposed model is reliable. The vegetation phenology and its seasonal and interannual dynamics demonstrate a distinct spatial pattern in urban domains with an earlier (9–14 days) start-of season (SOS) and a later (13–20 days) end-of season (EOS), resulting in an extended (5–30 days) growing season length (GSL) when compared to the surrounding suburban and rural areas in the four study regions. There is a general long-term trend of decreasing SOS (-0.30 day per year), and increasing EOS and GSL (0.50 and 0.90 day per year, respectively) over past three decades for these study regions. The magnitude of these trends varies among the four urban systems due to their diverse local climate conditions, vegetation types, and different urban-rural settings. The Landsat derived phenology information for urban domains provides more details when compared to the coarse-resolution datasets such as MODIS, thus improves our understanding of human-natural systems interactions (or feedbacks) in urban domains. Such information is very valuable for urban planning in light of rapid urbanization and expansion of major metropolitans at the national and global levels.« less

Analysis of Terrestrial Conditions and Dynamics

NASA Technical Reports Server (NTRS)

Goward, S. N.

1985-01-01

An ecological model is developed to estimate annual net primary productivity of vegetation in twelve major North American biomes. Three models are adapted and combined, each addressing a different factor known to govern primary productivity, i.e., photosynthesis, respiration, and moisture availability. Measures of intercepted photosynthetically active radiation (1PAR) for input to the photosynthesis model are derived from spectral vegetation index data. Normalized Difference Vegetation Index (NDVI) data are produced from NOAA-7 Advanced Very High Resolution Radiometer (AVHRR) observations for April 1982 through March 1983. NDVI values are sampled from within the biomes at locations for which climatological data are available. Monthly estimates of Net Primary Productivity (NPP) for each sample location are generated and summed over the twelve month period. These monthly estimates are averaged to produce a single annual estimated NPP value for each biomes. Comparison of estimated NPP values with figures reported in the literature produces a correlation coefficient of 85.

From Patterns to Function in Living Systems: Dryland Ecosystems as a Case Study

NASA Astrophysics Data System (ADS)

Meron, Ehud

2018-03-01

Spatial patterns are ubiquitous in animate matter. Besides their intricate structure and beauty they generally play functional roles. The capacity of living systems to remain functional in changing environments is a question of utmost importance, but its intimate relationship to pattern formation is largely unexplored. Here, we address this relationship using dryland vegetation as a case study. Following a brief introduction to pattern-formation theory, we describe a mathematical model that captures several mechanisms of vegetation pattern formation and discuss ecological contexts that showcase different mechanisms. Using this model, we unravel the different vegetation patterns that keep dryland ecosystems viable along the rainfall gradient, identify multistability ranges where fronts separating domains of alternative stable states exist, and highlight the roles of front dynamics in mitigating or reversing desertification. The utility of satellite images in testing model predictions is discussed. An outlook on outstanding open problems concludes this paper.

Metastability for discontinuous dynamical systems under Lévy noise: Case study on Amazonian Vegetation.

PubMed

Serdukova, Larissa; Zheng, Yayun; Duan, Jinqiao; Kurths, Jürgen

2017-08-24

For the tipping elements in the Earth's climate system, the most important issue to address is how stable is the desirable state against random perturbations. Extreme biotic and climatic events pose severe hazards to tropical rainforests. Their local effects are extremely stochastic and difficult to measure. Moreover, the direction and intensity of the response of forest trees to such perturbations are unknown, especially given the lack of efficient dynamical vegetation models to evaluate forest tree cover changes over time. In this study, we consider randomness in the mathematical modelling of forest trees by incorporating uncertainty through a stochastic differential equation. According to field-based evidence, the interactions between fires and droughts are a more direct mechanism that may describe sudden forest degradation in the south-eastern Amazon. In modeling the Amazonian vegetation system, we include symmetric α-stable Lévy perturbations. We report results of stability analysis of the metastable fertile forest state. We conclude that even a very slight threat to the forest state stability represents L´evy noise with large jumps of low intensity, that can be interpreted as a fire occurring in a non-drought year. During years of severe drought, high-intensity fires significantly accelerate the transition between a forest and savanna state.

User's Guide to the Western Root Disease Model, Version 3.0

Treesearch

Susan J. Frankel

1998-01-01

Effects of Armillaria spp., Phellinus weirii, Heterobasidion annosum, or bark beetles on stand dynamics are represented by the Western Root Disease Model,Version 3.0. This model, which operates in conjunction with the Forest Vegetation Simulator, can be used to evaluate the effects of many silvicultural practices. This guide contains instructions for use, detailed...

Towards quantifying uncertainty in predictions of Amazon 'dieback'.

PubMed

Huntingford, Chris; Fisher, Rosie A; Mercado, Lina; Booth, Ben B B; Sitch, Stephen; Harris, Phil P; Cox, Peter M; Jones, Chris D; Betts, Richard A; Malhi, Yadvinder; Harris, Glen R; Collins, Mat; Moorcroft, Paul

2008-05-27

Simulations with the Hadley Centre general circulation model (HadCM3), including carbon cycle model and forced by a 'business-as-usual' emissions scenario, predict a rapid loss of Amazonian rainforest from the middle of this century onwards. The robustness of this projection to both uncertainty in physical climate drivers and the formulation of the land surface scheme is investigated. We analyse how the modelled vegetation cover in Amazonia responds to (i) uncertainty in the parameters specified in the atmosphere component of HadCM3 and their associated influence on predicted surface climate. We then enhance the land surface description and (ii) implement a multilayer canopy light interception model and compare with the simple 'big-leaf' approach used in the original simulations. Finally, (iii) we investigate the effect of changing the method of simulating vegetation dynamics from an area-based model (TRIFFID) to a more complex size- and age-structured approximation of an individual-based model (ecosystem demography). We find that the loss of Amazonian rainforest is robust across the climate uncertainty explored by perturbed physics simulations covering a wide range of global climate sensitivity. The introduction of the refined light interception model leads to an increase in simulated gross plant carbon uptake for the present day, but, with altered respiration, the net effect is a decrease in net primary productivity. However, this does not significantly affect the carbon loss from vegetation and soil as a consequence of future simulated depletion in soil moisture; the Amazon forest is still lost. The introduction of the more sophisticated dynamic vegetation model reduces but does not halt the rate of forest dieback. The potential for human-induced climate change to trigger the loss of Amazon rainforest appears robust within the context of the uncertainties explored in this paper. Some further uncertainties should be explored, particularly with respect to the representation of rooting depth.

Effects of land-use and climate on Holocene vegetation composition in northern Europe

NASA Astrophysics Data System (ADS)

Marquer, Laurent; Gaillard, Marie-José; Sugita, Shinya; Poska, Anneli; Trondman, Anna-Kari; Mazier, Florence; Nielsen, Anne Birgitte; Fyfe, Ralph; Jönsson, Anna Maria

2016-04-01

Prior to the advent of agriculture, broad-scale vegetation patterns in Europe were controlled primarily by climate. Early agriculture can be detected in palaeovegetation records, but the relative extent to which past regional vegetation was climatically or anthropogenically-forced is of current scientific interest. Using comparisons of transformed pollen data, climate-model data, dynamic vegetation model simulations and anthropogenic land-cover change data, this study aims to estimate the relative impacts of human activities and climate on the Holocene vegetation composition of northern Europe at a subcontinental scale. The REVEALS model was used for pollen-based quantitative reconstruction of vegetation (RV). Climate variables from ECHAM and the extent of human deforestation from KK10 were used as explanatory variables to evaluate their respective impacts on RV. Indices of vegetation-composition changes based on RV and climate-induced vegetation simulated by the LPJ-GUESS model (LPJG) were used to assess the relative importance of climate and anthropogenic impacts. The results show that climate is the major predictor of Holocene vegetation changes until 5000 years ago. The similarity in rate of change and turnover between RV and LPJG decreases after this time. Changes in RV explained by climate and KK10 vary for the last 2000 years; the similarity in rate of change, turnover, and evenness between RV and LPJG decreases to the present. The main conclusions provide important insights on Neolithic forest clearances that affected regional vegetation from 6700 years ago, although climate (temperature and precipitation) still was a major driver of vegetation change (explains 37% of the variation) at the subcontinental scale. Land use became more important around 5000-4000 years ago, while the influence of climate decreased (explains 28% of the variation). Land-use affects all indices of vegetation compositional change during the last 2000 years; the influence of climate on vegetation, although reduced, remains at 16% until modern time while land-use explains 7%, which underlines that North-European vegetation is still climatically sensitive and, therefore, responds strongly to ongoing climate change.

Multi-Frequency Investigation into Scattering from Vegetation over the Growth Cycle

NASA Technical Reports Server (NTRS)

Lang, R. H.; Kurum, M.; O'Neill, P. E.; Joseph, A. T.; Deshpande, M. D.; Cosh, M. H.

2016-01-01

In this investigation, we aim to collect and use time-series multi-frequency microwave data over winter wheat during entire growth cycle to characterize vegetation dynamics and to quantify its effects on soil moisture retrievals. We plan to incorporate C-band radar and VHF receiver within the existing L-band radarradiometer system called ComRAD (SMAPs ground based simulator). With C-bands ability to sense vegetation details and VHFs root-zone soil moisture within ComRADs footprint, we will be able to test our discrete scatterer vegetation models and parameters at various surface conditions. The purpose of this study is to determine optical depth and effective scattering albedo of vegetation of a given type (i.e. winter wheat) at various stages of growth that are need to refine soil moisture retrieval algorithms being developed for the SMAP mission.

Erosion and vegetation restoration impacts on ecosystem carbon dynamics in South China

USGS Publications Warehouse

Tang, X.; Liu, Shuguang; Zhou, G.

2010-01-01

To quantify the consequences of erosion and vegetation restoration on ecosystem C dynamics (a key element in understanding the terrestrial C cycle), field measurements were collected since 1959 at two experimental sites set up on highly disturbed barren land in South China. One site had received vegetation restoration (the restored site) while the other received no planting and remained barren (the barren site). The Erosion-Deposition Carbon Model (EDCM) was used to simulate the ecosystem C dynamics at both sites. The on-site observations in 2007 showed that soil organic C (SOC) storage in the top 80-cm soil layer at the barren site was 50.3 ± 3.5 Mg C ha−1, half that of the restored site. The SOC and surface soil loss by erosion at the restored site from 1959 to 2007 was 3.7 Mg C ha−1 and 2.2 cm, respectively—one-third and one-eighth that of the barren site. The on-site C sequestration in SOC and vegetation at the restored site was 0.67 and 2.5 Mg C ha−1 yr−1, respectively, from 1959 to 2007, driven largely by tree growth and high atmospheric N deposition in the study area. Simulated findings suggested that higher N deposition resulted in higher on-site SOC storage in the soil profile (with SOC in the top 20-cm layer increasing more significantly), and higher on-site ecosystem C sequestration as long as N saturation was not reached. Lacking human-induced vegetation recovery, the barren site remained as barren land from 1959 to 2007 and the on-site C decrease was 0.28 Mg C ha−1 yr−1 Our study clearly indicated that vegetation restoration and burial by soil erosion provide a large potential C sink in terrestrial ecosystems.

Comprehensive Understanding for Vegetated Scene Radiance Relationships

NASA Technical Reports Server (NTRS)

Kimes, D. S.; Deering, D. W.

1984-01-01

The improvement of our fundamental understanding of the dynamics of directional scattering properties of vegetation canopies through analysis of field data and model simulation data is discussed. Directional reflectance distributions spanning the entire existance hemisphere were measured in two field studies; one using a Mark III 3-band radiometer and one using rapid scanning bidirectional field instrument called PARABOLA. Surfaces measured included corn, soybeans, bare soils, grass lawn, orchard grass, alfalfa, cotton row crops, plowed field, annual grassland, stipa grass, hard wheat, salt plain shrubland, and irrigated wheat. Some structural and optical measurements were taken. Field data show unique reflectance distributions ranging from bare soil to complete vegetation canopies. Physical mechanisms causing these trends are proposed based on scattering properties of soil and vegetation. Soil exhibited a strong backscattering peak toward the Sun. Complete vegetation exhibited a bowl distribution with the minimum reflectance near nadir. Incomplete vegetation canopies show shifting of the minimum reflectance off of nadir in the forward scattering direction because both the scattering properties or the vegetation and soil are observed.

Evaluating simulated functional trait patterns and quantifying modelled trait diversity effects on simulated ecosystem fluxes

NASA Astrophysics Data System (ADS)

Pavlick, R.; Schimel, D.

2014-12-01

Dynamic Global Vegetation Models (DGVMs) typically employ only a small set of Plant Functional Types (PFTs) to represent the vast diversity of observed vegetation forms and functioning. There is growing evidence, however, that this abstraction may not adequately represent the observed variation in plant functional traits, which is thought to play an important role for many ecosystem functions and for ecosystem resilience to environmental change. The geographic distribution of PFTs in these models is also often based on empirical relationships between present-day climate and vegetation patterns. Projections of future climate change, however, point toward the possibility of novel regional climates, which could lead to no-analog vegetation compositions incompatible with the PFT paradigm. Here, we present results from the Jena Diversity-DGVM (JeDi-DGVM), a novel traits-based vegetation model, which simulates a large number of hypothetical plant growth strategies constrained by functional tradeoffs, thereby allowing for a more flexible temporal and spatial representation of the terrestrial biosphere. First, we compare simulated present-day geographical patterns of functional traits with empirical trait observations (in-situ and from airborne imaging spectroscopy). The observed trait patterns are then used to improve the tradeoff parameterizations of JeDi-DGVM. Finally, focusing primarily on the simulated leaf traits, we run the model with various amounts of trait diversity. We quantify the effects of these modeled biodiversity manipulations on simulated ecosystem fluxes and stocks for both present-day conditions and transient climate change scenarios. The simulation results reveal that the coarse treatment of plant functional traits by current PFT-based vegetation models may contribute substantial uncertainty regarding carbon-climate feedbacks. Further development of trait-based models and further investment in global in-situ and spectroscopic plant trait observations are needed.

Seasonality of vegetation types of South America depicted by moderate resolution imaging spectroradiometer (MODIS) time series

NASA Astrophysics Data System (ADS)

Adami, Marcos; Bernardes, Sérgio; Arai, Egidio; Freitas, Ramon M.; Shimabukuro, Yosio E.; Espírito-Santo, Fernando D. B.; Rudorff, Bernardo F. T.; Anderson, Liana O.

2018-07-01

The development, implementation and enforcement of policies involving the rational use of the land and the conservation of natural resources depend on an adequate characterization and understanding of the land cover, including its dynamics. This paper presents an approach for monitoring vegetation dynamics using high-quality time series of MODIS surface reflectance data by generating fraction images using Linear Spectral Mixing Model (LSMM) over South America continent. The approach uses physically-based fraction images, which highlight target information and reduce data dimensionality. Further dimensionality was also reduced by using the vegetation fraction images as input to a Principal Component Analysis (PCA). The RGB composite of the first three PCA components, accounting for 92.9% of the dataset variability, showed good agreement with the main ecological regions of South America continent. The analysis of 21 temporal profiles of vegetation fraction values and precipitation data over South America showed the ability of vegetation fractions to represent phenological cycles over a variety of environments. Comparisons between vegetation fractions and precipitation data indicated the close relationship between water availability and leaf mass/chlorophyll content for several vegetation types. In addition, phenological changes and disturbance resulting from anthropogenic pressure were identified, particularly those associated with agricultural practices and forest removal. Therefore the proposed method supports the management of natural and non-natural ecosystems, and can contribute to the understanding of key conservation issues in South America, including deforestation, disturbance and fire occurrence and management.

Probabilistic calibration of the SPITFIRE fire spread model using Earth observation data

NASA Astrophysics Data System (ADS)

Gomez-Dans, Jose; Wooster, Martin; Lewis, Philip; Spessa, Allan

2010-05-01

There is a great interest in understanding how fire affects vegetation distribution and dynamics in the context of global vegetation modelling. A way to include these effects is through the development of embedded fire spread models. However, fire is a complex phenomenon, thus difficult to model. Statistical models based on fire return intervals, or fire danger indices need large amounts of data for calibration, and are often prisoner to the epoch they were calibrated to. Mechanistic models, such as SPITFIRE, try to model the complete fire phenomenon based on simple physical rules, making these models mostly independent of calibration data. However, the processes expressed in models such as SPITFIRE require many parameters. These parametrisations are often reliant on site-specific experiments, or in some other cases, paremeters might not be measured directly. Additionally, in many cases, changes in temporal and/or spatial resolution result in parameters becoming effective. To address the difficulties with parametrisation and the often-used fitting methodologies, we propose using a probabilistic framework to calibrate some areas of the SPITFIRE fire spread model. We calibrate the model against Earth Observation (EO) data, a global and ever-expanding source of relevant data. We develop a methodology that tries to incorporate the limitations of the EO data, reasonable prior values for parameters and that results in distributions of parameters, which can be used to infer uncertainty due to parameter estimates. Additionally, the covariance structure of parameters and observations is also derived, whcih can help inform data gathering efforts and model development, respectively. For this work, we focus on Southern African savannas, an important ecosystem for fire studies, and one with a good amount of EO data relevnt to fire studies. As calibration datasets, we use burned area data, estimated number of fires and vegetation moisture dynamics.

A Data-Driven Assessment of the Sensitivity of Global Ecosystems to Climate Anomalies

NASA Astrophysics Data System (ADS)

Miralles, D. G.; Papagiannopoulou, C.; Demuzere, M.; Decubber, S.; Waegeman, W.; Verhoest, N.; Dorigo, W.

2017-12-01

Vegetation is a central player in the climate system, constraining atmospheric conditions through a series of feedbacks. This fundamental role highlights the importance of understanding regional drivers of ecological sensitivity and the response of vegetation to climatic changes. While nutrient availability and short-term disturbances can be crucial for vegetation at various spatiotemporal scales, natural vegetation dynamics are overall driven by climate. At monthly scales, the interactions between vegetation and climate become complex: some vegetation types react preferentially to specific climatic changes, with different levels of intensity, resilience and lagged response. For our current Earth System Models (ESMs) being able to capture this complexity is crucial but extremely challenging. This adds uncertainty to our projections of future climate and the fate of global ecosystems. Here, following a Granger causality framework based on a non-linear random forest predictive model, we exploit the current wealth of satellite data records to uncover the main climatic drivers of monthly vegetation variability globally. Results based on three decades of satellite data indicate that water availability is the most dominant factor driving vegetation in over 60% of the vegetated land. This overall dependency of ecosystems on water availability is larger than previously reported, partly owed to the ability of our machine-learning framework to disentangle the co-linearites between climatic drivers, and to quantify non-linear impacts of climate on vegetation. Our observation-based results are then used to benchmark ESMs on their representation of vegetation sensitivity to climate and climatic extremes. Our findings indicate that the sensitivity of vegetation to climatic anomalies is ill-reproduced by some widely-used ESMs.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

PubMed

Tagesson, Torbern; Fensholt, Rasmus; Guiro, Idrissa; Rasmussen, Mads Olander; Huber, Silvia; Mbow, Cheikh; Garcia, Monica; Horion, Stéphanie; Sandholt, Inge; Holm-Rasmussen, Bo; Göttsche, Frank M; Ridler, Marc-Etienne; Olén, Niklas; Lundegard Olsen, Jørgen; Ehammer, Andrea; Madsen, Mathias; Olesen, Folke S; Ardö, Jonas

2015-01-01

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models. © 2014 John Wiley & Sons Ltd.

Spatial and temporal dynamic of surface water and vegetation dynamic using remotely sensed data in the Murray -Darling Basin, Australia

NASA Astrophysics Data System (ADS)

Tulbure, M. G.; Kingsford, R.; Broich, M.

2012-12-01

Australia is the driest inhabited continent and river systems have highly variable flows in space and time. The Murray-Darling Basin (MDB), a catchment covering 14% of the continent contains the nation's largest rivers and important groundwater systems. The basin has highly variable rainfall patterns in space and time and the vast majority of rainfall is lost to evapotranspiration with only 4% becoming runoff. The basin is home to several wetlands of high hydrological and ecological value with a number of them being recognised as wetlands of international importance. The basin produces more than a third of Australia's food supply, making it the most important agricultural area in the country. However, variation in surface and ground water availability exacerbated by a long period of drought, combined with high water demands for irrigation and in several major cities, and the need for water to maintain ecosystem health in the floodplains have led to the need of managing water resources in an integrated fashion. Several dams have been constructed in the basin, which store water during wet periods which is released during dry periods as environmental flows. Assessment of water resources and understanding of the effectiveness of environmental flows requires knowledge of 1) long term trends in occurrence and extent of surface water, 2) what is the vegetation response to flooding and 3) whether water reached target vegetation communities. However, such information does not exist at the basin level. Satellite remote sensing is the only viable way for synoptically mapping and monitoring the extent and dynamic of flooding and vegetation response to flooding. Moreover, recent La Nina -induced, extreme flooding broke a decade long of drought and made 2010 the wettest calendar year on record in the MDB and across vast areas of Australia. This represents a unique opportunity to develop predictive models relating flow regime to vegetation response and identify trends over long term and across a large space in a drying yet variable climate. Using an internally consistent method, Landsat TM and ETM+ data were used to synoptically map the extent and dynamic of surface water bodies and track the response of vegetation communities to flooding in space and time at selected sites. Per pixel trajectory of surface water and vegetation index time series were used. Results show high interannual variability in number and size of flooded areas and a positive relationship with rainfall. Response of vegetation communities to flooding varied in space and time and with vegetation types and densities. Knowledge of the spatial and temporal dynamic of flooding and the response of vegetation communities to flooding is important for management of floodplain wetlands and vegetation communities and for investigating effectiveness of environmental flows and flow regimes in the MDB. The approach presented here can be transferred to other river systems around the world where high demand for water requires informed management decisions.

Quantifying Subsurface Water and Heat Distribution and its Linkage with Landscape Properties in Terrestrial Environment using Hydro-Thermal-Geophysical Monitoring and Coupled Inverse Modeling

NASA Astrophysics Data System (ADS)

Dafflon, B.; Tran, A. P.; Wainwright, H. M.; Hubbard, S. S.; Peterson, J.; Ulrich, C.; Williams, K. H.

2015-12-01

Quantifying water and heat fluxes in the subsurface is crucial for managing water resources and for understanding the terrestrial ecosystem where hydrological properties drive a variety of biogeochemical processes across a large range of spatial and temporal scales. Here, we present the development of an advanced monitoring strategy where hydro-thermal-geophysical datasets are continuously acquired and further involved in a novel inverse modeling framework to estimate the hydraulic and thermal parameter that control heat and water dynamics in the subsurface and further influence surface processes such as evapotranspiration and vegetation growth. The measured and estimated soil properties are also used to investigate co-interaction between subsurface and surface dynamics by using above-ground aerial imaging. The value of this approach is demonstrated at two different sites, one in the polygonal shaped Arctic tundra where water and heat dynamics have a strong impact on freeze-thaw processes, vegetation and biogeochemical processes, and one in a floodplain along the Colorado River where hydrological fluxes between compartments of the system (surface, vadose zone and groundwater) drive biogeochemical transformations. Results show that the developed strategy using geophysical, point-scale and aerial measurements is successful to delineate the spatial distribution of hydrostratigraphic units having distinct physicochemical properties, to monitor and quantify in high resolution water and heat distribution and its linkage with vegetation, geomorphology and weather conditions, and to estimate hydraulic and thermal parameters for enhanced predictions of water and heat fluxes as well as evapotranspiration. Further, in the Colorado floodplain, results document the potential presence of only periodic infiltration pulses as a key hot moment controlling soil hydro and biogeochemical functioning. In the arctic, results show the strong linkage between soil water content, thermal parameters, thaw layer thickness and vegetation distribution. Overall, results of these efforts demonstrate the value of coupling various datasets at high spatial and temporal resolution to improve predictive understanding of subsurface and surface dynamics.

A Dynamic Simulation Model of Land-Use, Population, and Rural Livelihoods in the Central Rift Valley of Ethiopia

NASA Astrophysics Data System (ADS)

Garedew, Efrem; Sandewall, Mats; Soderberg, Ulf

2012-01-01

The dynamic interactions between society and land resources have to be taken into account when planning and managing natural resources. A computer model, using STELLA software, was developed through active participation of purposively selected farm households from different wealth groups, age groups and gender within a rural community and some members of Kebelle council. The aim of the modeling was to study the perceived changes in land-use, population and livelihoods over the next 30 years and to improve our understanding of the interactions among them. The modeling output is characterized by rapid population growth, declining farm size and household incomes, deteriorating woody vegetation cover and worsening land degradation if current conditions remain. However, through integrated intervention strategies (including forest increase, micro-finance, family planning, health and education) the woody vegetation cover is likely to increase in the landscape, population growth is likely to slow down and households' income is likely to improve. A validation assessment of the simulation model based on historical data on land-use and population from 1973 to 2006 showed that the model is relatively robust. We conclude that as a supporting tool, the simulation model can contribute to the decision making process.

Lidar and Hyperspectral Remote Sensing for the Analysis of Coniferous Biomass Stocks and Fluxes

NASA Astrophysics Data System (ADS)

Halligan, K. Q.; Roberts, D. A.

2006-12-01

Airborne lidar and hyperspectral data can improve estimates of aboveground carbon stocks and fluxes through their complimentary responses to vegetation structure and biochemistry. While strong relationships have been demonstrated between lidar-estimated vegetation structural parameters and field data, research is needed to explore the portability of these methods across a range of topographic conditions, disturbance histories, vegetation type and climate. Additionally, research is needed to evaluate contributions of hyperspectral data in refining biomass estimates and determination of fluxes. To address these questions we are a conducting study of lidar and hyperspectral remote sensing data across sites including coniferous forests, broadleaf deciduous forests and a tropical rainforest. Here we focus on a single study site, Yellowstone National Park, where tree heights, stem locations, above ground biomass and basal area were mapped using first-return small-footprint lidar data. A new method using lidar intensity data was developed for separating the terrain and vegetation components in lidar data using a two-scale iterative local minima filter. Resulting Digital Terrain Models (DTM) and Digital Canopy Models (DCM) were then processed to retrieve a diversity of vertical and horizontal structure metrics. Univariate linear models were used to estimate individual tree heights while stepwise linear regression was used to estimate aboveground biomass and basal area. Three small-area field datasets were compared for their utility in model building and validation of vegetation structure parameters. All structural parameters were linearly correlated with lidar-derived metrics, with higher accuracies obtained where field and imagery data were precisely collocated . Initial analysis of hyperspectral data suggests that vegetation health metrics including measures of live and dead vegetation and stress indices may provide good indicators of carbon flux by mapping vegetation vigor or senescence. Additionally, the strength of hyperspectral data for vegetation classification suggests these data have additional utility for modeling carbon flux dynamics by allowing more accurate plant functional type mapping.

Groundwater controls on vegetation composition and patterning in mountain meadows

NASA Astrophysics Data System (ADS)

Lowry, Christopher S.; Loheide, Steven P., II; Moore, Courtney E.; Lundquist, Jessica D.

2011-10-01

Mountain meadows are groundwater-dependent ecosystems that are hot spots of biodiversity and productivity. In the Sierra Nevada mountains of California, these ecosystems rely on shallow groundwater to support their vegetation communities during the dry summer growing season in the region's Mediterranean montane climate. Vegetation composition in this environment is influenced by both (1) oxygen stress that occurs when portions of the root zone are saturated and anaerobic conditions limit root respiration and (2) water stress that occurs when the water table drops and the root zone becomes water limited. A spatially distributed watershed model that explicitly accounts for snowmelt processes was linked to a fine-resolution groundwater flow model of Tuolumne Meadows in Yosemite National Park, California, to simulate water table dynamics. This linked hydrologic model was calibrated to observations from a well observation network for 2006-2009. A vegetation survey was also conducted at the site in which the three dominant species were identified at more than 200 plots distributed across the meadow. Nonparametric multiplicative regression was performed to create and select the best models for predicting vegetation dominance on the basis of the simulated hydrologic regime. The hydrologic niches of three vegetation types representing wet, moist, and dry meadow vegetation communities were found to be best described using both (1) a sum exceedance value calculated as the integral of water table position above a depth threshold of oxygen stress and (2) a sum exceedance value calculated as the integral of water table position below a depth threshold of water stress. This linked hydrologic and vegetative modeling framework advances our ability to predict the propagation of human-induced climatic and land use or land cover changes through the hydrologic system to the ecosystem. The hydroecologic functioning of meadows provides an example of the extent to which cascading hydrologic processes at watershed, hillslope, and riparian zones and within channels are reflected in the composition and distribution of riparian vegetation.

Role of model structure on the response of soil biogeochemistry to hydro-climatic fluctuations

NASA Astrophysics Data System (ADS)

Manzoni, S.; Porporato, A.

2005-05-01

Soil carbon and nutrient cycles are strongly affected by hydro-climatic variability, which interacts with the internal ecosystem structure. Here we test the implications of biogeochemical model structure on such dynamics by extending an existing model by the authors and coworkers. When forced by hydro-climatic fluctuations, the different model structures induce specific preferential nutrient paths among the soil pools, which in turn affect nutrient distribution and availability to microbes and plants. In particular, if it is assumed that microbes can directly assimilate organic nitrogen, plants tend to be inferior competitors for nutrients even in well-watered conditions, while if a certain amount of organic nitrogen is assumed to be mineralized without being first incorporated into microbial cells, vegetation can be advantaged over a wide range of soil moisture values. We also investigate the intensification of competition for nutrients (e.g., nitrogen) between plant and soil microbial communities under extreme hydrologic conditions, such as droughts and intense storms. Frequent rainfall events may determine ideal soil moisture conditions for plant uptake, enhancing nitrogen leaching while lowering oxygen concentration and inhibiting microbial activity. During droughts, the soil water potential often drops to the point of hampering the plant nutrient uptake while still remaining high enough for microbial decomposition and nitrogen immobilization. The interplay of microbe and vegetation water stress is investigated in depth as it controls the ability of one community (e.g., plants or soil microbes) to establish competitive advantage on the other. The long-term effects of these dynamics of competition and nutrient allocation are explored under steady-state and stochastic soil moisture conditions to analyze the feedbacks between soil organic matter and vegetation dynamics.

Predicting vegetation type through physiological and environmental interactions with leaf traits: evergreen and deciduous forests in an earth system modeling framework.

PubMed

Weng, Ensheng; Farrior, Caroline E; Dybzinski, Ray; Pacala, Stephen W

2017-06-01

Earth system models are incorporating plant trait diversity into their land components to better predict vegetation dynamics in a changing climate. However, extant plant trait distributions will not allow extrapolations to novel community assemblages in future climates, which will require a mechanistic understanding of the trade-offs that determine trait diversity. In this study, we show how physiological trade-offs involving leaf mass per unit area (LMA), leaf lifespan, leaf nitrogen, and leaf respiration may explain the distribution patterns of evergreen and deciduous trees in the temperate and boreal zones based on (1) an evolutionary analysis of a simple mathematical model and (2) simulation experiments of an individual-based dynamic vegetation model (i.e., LM3-PPA). The evolutionary analysis shows that these leaf traits set up a trade-off between carbon- and nitrogen-use efficiency at the scale of individual trees and therefore determine competitively dominant leaf strategies. As soil nitrogen availability increases, the dominant leaf strategy switches from one that is high in nitrogen-use efficiency to one that is high in carbon-use efficiency or, equivalently, from high-LMA/long-lived leaves (i.e., evergreen) to low-LMA/short-lived leaves (i.e., deciduous). In a region of intermediate soil nitrogen availability, the dominant leaf strategy may be either deciduous or evergreen depending on the initial conditions of plant trait abundance (i.e., founder controlled) due to feedbacks of leaf traits on soil nitrogen mineralization through litter quality. Simulated successional patterns by LM3-PPA from the leaf physiological trade-offs are consistent with observed successional dynamics of evergreen and deciduous forests at three sites spanning the temperate to boreal zones. © 2016 John Wiley & Sons Ltd.

Using a conceptual model to assess the role of flow regulation in the hydromorphological evolution of riparian corridors

NASA Astrophysics Data System (ADS)

Martínez-Fernández, Vanesa; Gonzalez del Tánago, Marta; García de Jalón, diego

2017-04-01

Riparian corridors result from active vegetation-fluvial interactions, which are highly dependent on flow regime conditions and sediment dynamics. Colonization, establishment and survival of species are constrained by fluvial processes which vary according to topographic and sedimentological complexity of the corridor. In order to manage these dynamic and complex riparian systems there is a need for practical tools based on conceptual models. The objective of this study was to apply the conceptual model of riparian corridors lateral zonation in response to the dominant fluvial processes established by Gurnell et al. (2015) and verify its usefulness as a tool for assessing the effect of flow regulation. Two gravel rivers have been selected for this purpose from the north of Spain, the Porma River regulated by Boñar large dam and the unregulated Curueño River. The historical series of flows and the aerial photographs of 1956 and 2011 on which the river corridor has been delimited have been analyzed and identified the permanent inundated zone (1) and four areas of riparian vegetation dominated respectively by fluvial disturbance with coarse sediment erosion and deposition (zone 2), fluvial disturbance with finer sediment deposition (zone 3), inundation (zone 4) and soil moisture regime (zone 5). Likewise, a two-dimensional hydraulic simulation was performed with avenues of different return periods and calculated the prevailing hydraulic conditions (depths, velocities and drag forces) to characterize each of the vegetation zones mentioned in both rivers. The results show that the most active zone 2 (fluvial disturbance dominated showing coarse sediment erosion and deposition) disappears due to the regulation of flows and vegetation encroachment, while the riparian corridor is dominated by the less active zone where the vegetation is maintained by the humidity of sporadic floods and underground runoff. Moreover, by means of the hydraulic simulation we have found a close relationship between the different areas of fluvial processes recognized through its vegetation and hydraulic conditions, which predicts the expected evolution of vegetation at different scenarios of regulation.

Incorporating NDVI in a gravity model setting to describe spatio-temporal patterns of Lyme borreliosis incidence

NASA Astrophysics Data System (ADS)

Barrios, J. M.; Verstraeten, W. W.; Farifteh, J.; Maes, P.; Aerts, J. M.; Coppin, P.

2012-04-01

Lyme borreliosis (LB) is the most common tick-borne disease in Europe and incidence growth has been reported in several European countries during the last decade. LB is caused by the bacterium Borrelia burgdorferi and the main vector of this pathogen in Europe is the tick Ixodes ricinus. LB incidence and spatial spread is greatly dependent on environmental conditions impacting habitat, demography and trophic interactions of ticks and the wide range of organisms ticks parasite. The landscape configuration is also a major determinant of tick habitat conditions and -very important- of the fashion and intensity of human interaction with vegetated areas, i.e. human exposure to the pathogen. Hence, spatial notions as distance and adjacency between urban and vegetated environments are related to human exposure to tick bites and, thus, to risk. This work tested the adequacy of a gravity model setting to model the observed spatio-temporal pattern of LB as a function of location and size of urban and vegetated areas and the seasonal and annual change in the vegetation dynamics as expressed by MODIS NDVI. Opting for this approach implies an analogy with Newton's law of universal gravitation in which the attraction forces between two bodies are directly proportional to the bodies mass and inversely proportional to distance. Similar implementations have proven useful in fields like trade modeling, health care service planning, disease mapping among other. In our implementation, the size of human settlements and vegetated systems and the distance separating these landscape elements are considered the 'bodies'; and the 'attraction' between them is an indicator of exposure to pathogen. A novel element of this implementation is the incorporation of NDVI to account for the seasonal and annual variation in risk. The importance of incorporating this indicator of vegetation activity resides in the fact that alterations of LB incidence pattern observed the last decade have been ascribed to changes in vector habitat induced by a changing climate. Hence, the incorporation of dynamic covariates in epidemiologic modelling schemes is necessary. Preliminary results of this on-going analysis reveal the great potential of this modeling approach to base the incorporation of remotely sensed information of the environment in monitoring shrinkages and expansions of risk zones in this - and probably other - vector-borne disease.

IN11B-1621: Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Technical Reports Server (NTRS)

Das, Kamalika; Kodali, Anuradha; Szubert, Marcin; Ganguly, Sangram; Bongard, Joshua

2016-01-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

Quantifying How Climate Affects Vegetation in the Amazon Rainforest

NASA Astrophysics Data System (ADS)

Das, K.; Kodali, A.; Szubert, M.; Ganguly, S.; Bongard, J.

2016-12-01

Amazon droughts in 2005 and 2010 have raised serious concern about the future of the rainforest. Amazon forests are crucial because of their role as the largest carbon sink in the world which would effect the global warming phenomena with decreased photosynthesis activity. Especially, after a decline in plant growth in 1.68 million km2 forest area during the once-in-a-century severe drought in 2010, it is of primary importance to understand the relationship between different climatic variables and vegetation. In an earlier study, we have shown that non-linear models are better at capturing the relation dynamics of vegetation and climate variables such as temperature and precipitation, compared to linear models. In this research, we learn precise models between vegetation and climatic variables (temperature, precipitation) for normal conditions in the Amazon region using genetic programming based symbolic regression. This is done by removing high elevation and drought affected areas and also considering the slope of the region as one of the important factors while building the model. The model learned reveals new and interesting ways historical and current climate variables affect the vegetation at any location. MAIAC data has been used as a vegetation surrogate in our study. For temperature and precipitation, we have used TRMM and MODIS Land Surface Temperature data sets while learning the non-linear regression model. However, to generalize the model to make it independent of the data source, we perform transfer learning where we regress a regularized least squares to learn the parameters of the non-linear model using other data sources such as the precipitation and temperature from the Climatic Research Center (CRU). This new model is very similar in structure and performance compared to the original learned model and verifies the same claims about the nature of dependency between these climate variables and the vegetation in the Amazon region. As a result of this study, we are able to learn, for the very first time how exactly different climate factors influence vegetation at any location in the Amazon rainforests, independent of the specific sources from which the data has been obtained.

LPJmL4 - a dynamic global vegetation model with managed land - Part 1: Model description

NASA Astrophysics Data System (ADS)

Schaphoff, Sibyll; von Bloh, Werner; Rammig, Anja; Thonicke, Kirsten; Biemans, Hester; Forkel, Matthias; Gerten, Dieter; Heinke, Jens; Jägermeyr, Jonas; Knauer, Jürgen; Langerwisch, Fanny; Lucht, Wolfgang; Müller, Christoph; Rolinski, Susanne; Waha, Katharina

2018-04-01

This paper provides a comprehensive description of the newest version of the Dynamic Global Vegetation Model with managed Land, LPJmL4. This model simulates - internally consistently - the growth and productivity of both natural and agricultural vegetation as coherently linked through their water, carbon, and energy fluxes. These features render LPJmL4 suitable for assessing a broad range of feedbacks within and impacts upon the terrestrial biosphere as increasingly shaped by human activities such as climate change and land use change. Here we describe the core model structure, including recently developed modules now unified in LPJmL4. Thereby, we also review LPJmL model developments and evaluations in the field of permafrost, human and ecological water demand, and improved representation of crop types. We summarize and discuss LPJmL model applications dealing with the impacts of historical and future environmental change on the terrestrial biosphere at regional and global scale and provide a comprehensive overview of LPJmL publications since the first model description in 2007. To demonstrate the main features of the LPJmL4 model, we display reference simulation results for key processes such as the current global distribution of natural and managed ecosystems, their productivities, and associated water fluxes. A thorough evaluation of the model is provided in a companion paper. By making the model source code freely available at https://gitlab.pik-potsdam.de/lpjml/LPJmL, we hope to stimulate the application and further development of LPJmL4 across scientific communities in support of major activities such as the IPCC and SDG process.

Comparison of the New LEAF Area INDEX (LAI 3G) with the Kazahstan-Wide LEAF Area INDEX DATA SET (GGRS-LAI) over Central ASIA

NASA Astrophysics Data System (ADS)

Kappas, M.; Propastin, P.; Degener, J.; Renchin, T.

2014-12-01

Long-term global data sets of Leaf Area Index (LAI) are important for monitoring global vegetation dynamics. LAI indicating phenological development of vegetation is an important state variable for modeling land surface processes. The comparison of long-term data sets is based on two recently available data sets both derived from AVHRR time series. The LAI 3g data set introduced by Zaichun Zhu et al. (2013) is developed from the new improved third generation Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) and best-quality MODIS LAI data. The second long-term data set is based on the 8 km spatial resolution GIMMS-AVHRR data (GGRS-data set by Propastin et al. 2012). The GGRS-LAI product uses a three-dimensional physical radiative transfer model which establishes relationship between LAI, vegetation fractional cover and given patterns of surface reflectance, view-illumination conditions and optical properties of vegetation. The model incorporates a number of site/region specific parameters, including the vegetation architecture variables such as leaf angle distribution, clumping index, and light extinction coefficient. For the application of the model to Kazakhstan, the vegetation architecture variables were computed at the local (pixel) level based on extensive field surveys of the biophysical properties of vegetation in representative grassland areas of Kazakhstan. The comparison of both long-term data sets will be used to interpret their quality for scientific research in other disciplines. References:Propastin, P., Kappas, M. (2012). Retrieval of coarse-resolution leaf area index over the Republic of Kazakhstan using NOAA AVHRR satellite data and ground measurements," Remote Sensing, vol. 4, no. 1, pp. 220-246. Zaichun Zhu, Jian Bi, Yaozhong Pan, Sangram Ganguly, Alessandro Anav, Liang Xu, Arindam Samanta, Shilong Piao, Ramakrishna R. Nemani and Ranga B. Myneni (2013). Global Data Sets of Vegetation Leaf Area Index (LAI)3g and Fraction of photosynthetically Active Radiation (FPAR)3g Derived from Global Inventory Modeling and Mapping Studies (GIMMS) Normalized Difference Vegetation Index (NDVI3g) for the Period 1981 to 2011. Remote Sens. 2013, 5, 927-948; doi:10.3390/rs5020927

El Niño Southern Oscillation and vegetation dynamics as predictors of dengue fever cases in Costa Rica

NASA Astrophysics Data System (ADS)

Fuller, D. O.; Troyo, A.; Beier, J. C.

2009-01-01

Dengue fever (DF) and dengue hemorrhagic fever (DHF) are growing health concerns throughout Latin America and the Caribbean. This study focuses on Costa Rica, which experienced over 100 000 cases of DF/DHF from 2003 to 2007. We utilized data on sea-surface temperature anomalies related to the El Niño Southern Oscillation (ENSO) and two vegetation indices derived from the Moderate Resolution Imaging Spectrometer (MODIS) from the Terra satellite to model the influence of climate and vegetation dynamics on DF/DHF cases in Costa Rica. Cross-correlations were calculated to evaluate both positive and negative lag effects on the relationships between independent variables and DF/DHF cases. The model, which utilizes a sinusoid and non-linear least squares to fit case data, was able to explain 83% of the variance in weekly DF/DHF cases when independent variables were shifted backwards in time. When the independent variables were shifted forward in time, consistently with a forecasting approach, the model explained 64% of the variance. Importantly, when five ENSO and two vegetation indices were included, the model reproduced a major DF/DHF epidemic of 2005. The unexplained variance in the model may be due to herd immunity and vector control measures, although information regarding these aspects of the disease system are generally lacking. Our analysis suggests that the model may be used to predict DF/DHF outbreaks as early as 40 weeks in advance and may also provide valuable information on the magnitude of future epidemics. In its current form it may be used to inform national vector control programs and policies regarding control measures; it is the first climate-based dengue model developed for this country and is potentially scalable to the broader region of Latin America and the Caribbean where dramatic increases in DF/DHF incidence and spread have been observed.

A Multi-Scale Integrated Approach to Representing Watershed Systems: Significance and Challenges

NASA Astrophysics Data System (ADS)

Kim, J.; Ivanov, V. Y.; Katopodes, N.

2013-12-01

A range of processes associated with supplying services and goods to human society originate at the watershed level. Predicting watershed response to forcing conditions has been of high interest to many practical societal problems, however, remains challenging due to two significant properties of the watershed systems, i.e., connectivity and non-linearity. Connectivity implies that disturbances arising at any larger scale will necessarily propagate and affect local-scale processes; their local effects consequently influence other processes, and often convey nonlinear relationships. Physically-based, process-scale modeling is needed to approach the understanding and proper assessment of non-linear effects between the watershed processes. We have developed an integrated model simulating hydrological processes, flow dynamics, erosion and sediment transport, tRIBS-OFM-HRM (Triangulated irregular network - based Real time Integrated Basin Simulator-Overland Flow Model-Hairsine and Rose Model). This coupled model offers the advantage of exploring the hydrological effects of watershed physical factors such as topography, vegetation, and soil, as well as their feedback mechanisms. Several examples investigating the effects of vegetation on flow movement, the role of soil's substrate on sediment dynamics, and the driving role of topography on morphological processes are illustrated. We show how this comprehensive modeling tool can help understand interconnections and nonlinearities of the physical system, e.g., how vegetation affects hydraulic resistance depending on slope, vegetation cover fraction, discharge, and bed roughness condition; how the soil's substrate condition impacts erosion processes with an non-unique characteristic at the scale of a zero-order catchment; and how topographic changes affect spatial variations of morphologic variables. Due to feedback and compensatory nature of mechanisms operating in different watershed compartments, our conclusion is that a key to representing watershed systems lies in an integrated, interdisciplinary approach, whereby a physically-based model is used for assessments/evaluations associated with future changes in landuse, climate, and ecosystems.

Interacting Effects of Leaf Water Potential and Biomass on Vegetation Optical Depth

NASA Astrophysics Data System (ADS)

Momen, Mostafa; Wood, Jeffrey D.; Novick, Kimberly A.; Pangle, Robert; Pockman, William T.; McDowell, Nate G.; Konings, Alexandra G.

2017-11-01

Remotely sensed microwave observations of vegetation optical depth (VOD) have been widely used for examining vegetation responses to climate. Nevertheless, the relative impacts of phenological changes in leaf biomass and water stress on VOD have not been explicitly disentangled. In particular, determining whether leaf water potential (ψL) affects VOD may allow these data sets as a constraint for plant hydraulic models. Here we test the sensitivity of VOD to variations in ψL and present a conceptual framework that relates VOD to ψL and total biomass including leaves, whose dynamics are measured through leaf area index, and woody components. We used measurements of ψL from three sites across the US—a mixed deciduous forests in Indiana and Missouri and a piñon-juniper woodland in New Mexico—to validate the conceptual model. The temporal dynamics of X-band VOD were similar to those of the VOD signal estimated from the new conceptual model with observed ψL (R2 = 0.6-0.8). At the global scale, accounting for a combination of biomass and estimated ψL (based on satellite surface soil moisture data) increased correlations with VOD by 15% and 30% compared to biomass and water potential, respectively. In wetter regions with denser and taller canopy heights, VOD has a higher correlation with leaf area index than with water stress and vice versa in drier regions. Our results demonstrate that variations in both phenology and ψL must be considered to accurately interpret the dynamics of VOD observations for ecological applications.

Belowground adaptation and resilience to drought conditions

NASA Astrophysics Data System (ADS)

Sivandran, G.; Gentine, P.; Bras, R. L.

2012-12-01

The most expansive drought in 50 years stretched across the Midwest in 2012. In light of predicted increases in the variability of climate, this type of event can no longer be considered extreme. Understanding the resilience of both managed and natural vegetation and how these systems may adapt to this new climate reality is critical in predicting changes to the global carbon, energy and water balance. An eco-hydrological model (tRIBS+VEGGIE) was employed to model the sensitivity of vegetation to varying drought intensities. Point scale simulations were carried out using two vertical root distribution schemes: (i) Static - a temporally invariant root distribution; and (ii) Dynamic - a temporally variable root carbon allocation scheme. A stochastic climate generator was used to create a series of synthetic climate realizations varying the drought characteristics - in particular the interstorm period. This change in the seasonal distribution of precipitation impacts the spatial (soil layers) and temporal distribution of soil moisture which directly impacts the water resource niche for vegetation. This change in resource niche is reflected in a shift in the optimal static rooting strategy further highlighting the need for the incorporation of a dynamic scheme that responds to local conditions.

Quantifying Potential Groundwater Recharge In South Texas

NASA Astrophysics Data System (ADS)

Basant, S.; Zhou, Y.; Leite, P. A.; Wilcox, B. P.

2015-12-01

Groundwater in South Texas is heavily relied on for human consumption and irrigation for food crops. Like most of the south west US, woody encroachment has altered the grassland ecosystems here too. While brush removal has been widely implemented in Texas with the objective of increasing groundwater recharge, the linkage between vegetation and groundwater recharge in South Texas is still unclear. Studies have been conducted to understand plant-root-water dynamics at the scale of plants. However, little work has been done to quantify the changes in soil water and deep percolation at the landscape scale. Modeling water flow through soil profiles can provide an estimate of the total water flowing into deep percolation. These models are especially powerful with parameterized and calibrated with long term soil water data. In this study we parameterize the HYDRUS soil water model using long term soil water data collected in Jim Wells County in South Texas. Soil water was measured at every 20 cm intervals up to a depth of 200 cm. The parameterized model will be used to simulate soil water dynamics under a variety of precipitation regimes ranging from well above normal to severe drought conditions. The results from the model will be compared with the changes in soil moisture profile observed in response to vegetation cover and treatments from a study in a similar. Comparative studies like this can be used to build new and strengthen existing hypotheses regarding deep percolation and the role of soil texture and vegetation in groundwater recharge.

Predicting Phenologic Response to Water Stress and Implications for Carbon Uptake across the Southeast U.S.

NASA Astrophysics Data System (ADS)

Lowman, L.; Barros, A. P.

2016-12-01

Representation of plant photosynthesis in modeling studies requires phenologic indicators to scale carbon assimilation by plants. These indicators are typically the fraction of photosynthetically active radiation (FPAR) and leaf area index (LAI) which represent plant responses to light and water availability, as well as temperature constraints. In this study, a prognostic phenology model based on the growing season index is adapted to determine the phenologic indicators of LAI and FPAR at the sub-daily scale based on meteorological and soil conditions. Specifically, we directly model vegetation green-up and die-off responses to temperature, vapor pressure deficit, soil water potential, and incoming solar radiation. The indices are based on the properties of individual plant functional types, driven by observational data and prior modeling applications. First, we describe and test the sensitivity of the carbon uptake response to predicted phenology for different vegetation types. Second, the prognostic phenology model is incorporated into a land-surface hydrology model, the Duke Coupled Hydrology Model with Prognostic Vegetation (DCHM-PV), to demonstrate the impact of dynamic phenology on modeled carbon assimilation rates and hydrologic feedbacks. Preliminary results show reduced carbon uptake rates when incorporating a prognostic phenology model that match well against the eddy-covariance flux tower observations. Additionally, grassland vegetation shows the most variability in LAI and FPAR tied to meteorological and soil conditions. These results highlight the need to incorporate vegetation-specific responses to water limitation in order to accurately estimate the terrestrial carbon storage component of the global carbon budget.

Beyond scenario planning: projecting the future using models at Wind Cave National Park (USA)

NASA Astrophysics Data System (ADS)

King, D. A.; Bachelet, D. M.; Symstad, A. J.

2011-12-01

Scenario planning has been used by the National Park Service as a tool for natural resource management planning in the face of climate change. Sets of plausible but divergent future scenarios are constructed from available information and expert opinion and serve as starting point to derive climate-smart management strategies. However, qualitative hypotheses about how systems would react to a particular set of conditions assumed from coarse scale climate projections may lack the scientific rigor expected from a federal agency. In an effort to better assess the range of likely futures at Wind Cave National Park, a project was conceived to 1) generate high resolution historic and future climate time series to identify local weather patterns that may or may not persist, 2) simulate the hydrological cycle in this geologically varied landscape and its response to future climate, 3) project vegetation dynamics and ensuing changes in the biogeochemical cycles given grazing and fire disturbances under new climate conditions, and 4) synthesize and compare results with those from the scenario planning exercise. In this framework, we tested a dynamic global vegetation model against local information on vegetation cover, disturbance history and stream flow to better understand the potential resilience of these ecosystems to climate change. We discuss the tradeoffs between a coarse scale application of the model showing regional trends with limited ability to project the fine scale mosaic of vegetation at Wind Cave, and a finer scale approach that can account for local slope effects on water balance and better assess the vulnerability of landscape facets, but requires more intensive data acquisition. We elaborate on the potential for sharing information between models to mitigate the often-limited treatment of biological feedbacks in the physical representations of soil and atmospheric processes.

Modelling post-fire vegetation recovery in Portugal

NASA Astrophysics Data System (ADS)

Bastos, A.; Gouveia, C.; Dacamara, C. C.; Trigo, R. M.

2011-05-01

Wildfires in Mediterranean Europe have been increasing in number and extension over the last decades and constitute one of the major disturbances of these ecosystems. Portugal is the country with more burnt area in the last decade and the years of 2003 and 2005 were particularly devastating, the total burned areas of 425 000 and 338 000 ha being several times higher than the corresponding average. The year of 2005 further coincided with one of the most severe droughts since early 20th century. Due to different responses of vegetation to diverse fire regimes and to the complexity of landscape structures, fires have complex effects on vegetation recovery. Remote sensing has revealed to be a powerful tool in studying vegetation dynamics and in monitoring post-fire vegetation recovery, which is crucial to land-management and to prevent erosion. The main goals of the present work are (i) to assess the accuracy of a vegetation recovery model previously developed by the authors; (ii) to assess the model's performance, namely its sensitivity to initial conditions, to the temporal length of the input dataset and to missing data; (iii) to study vegetation recovery over two selected areas that were affected by two large wildfire events in the fire seasons of 2003 and 2005, respectively. The study relies on monthly values of NDVI over 11 yr (1998-2009), at 1 × 1 km spatial resolution, as obtained by the VEGETATION instrument. According to results from sensitivity analysis, the model is robust and able to provide good estimations of recovery times of vegetation when the regeneration process is regular, even when missing data is present. In what respect to the two selected burnt scars, results indicate that fire damage is a determinant factor of regeneration, as less damaged vegetation recovers more rapidly, which is mainly justified by the high coverage of Pinus Pinaster over the area, and by the fact that coniferous forests tend to recover slower than transitional woodland-shrub, which tend to dominate the areas following the fire event.

Modelling post-fire vegetation recovery in Portugal

NASA Astrophysics Data System (ADS)

Bastos, A.; Gouveia, C. M.; Dacamara, C. C.; Trigo, R. M.

2011-12-01

Wildfires in Mediterranean Europe have been increasing in number and extension over the last decades and constitute one of the major disturbances of these ecosystems. Portugal is the country with more burnt area in the last decade and the years of 2003 and 2005 were particularly devastating, the total burned areas of 425 000 and 338 000 ha being several times higher than the corresponding average. The year of 2005 further coincided with one of the most severe droughts since early 20th century. Due to different responses of vegetation to diverse fire regimes and to the complexity of landscape structures, fires have complex effects on vegetation recovery. Remote sensing has revealed to be a powerful tool in studying vegetation dynamics and in monitoring post-fire vegetation recovery, which is crucial to land-management and to prevent erosion. The main goals of the present work are (i) to assess the accuracy of a vegetation recovery model previously developed by the authors; (ii) to assess the model's performance, namely its sensitivity to initial conditions, to the temporal length of the input dataset and to missing data; (iii) to study vegetation recovery over two selected areas that were affected by two large wildfire events in the fire seasons of 2003 and 2005, respectively. The study relies on monthly values of NDVI over 11 years (1998-2009), at 1 km × 1 km spatial resolution, as obtained by the VEGETATION instrument. According to results from sensitivity analysis, the model is robust and able to provide good estimations of recovery times of vegetation when the regeneration process is regular, even when missing data is present. In respect to the two selected burnt scars, results indicate that fire damage is a determinant factor of regeneration, as less damaged vegetation recovers more rapidly, which is mainly justified by the high coverage of Pinus pinaster over the area, and by the fact that coniferous forests tend to recover slower than transitional woodland-shrub, which tend to dominate the areas following the fire event.

Extracting temporal and spatial information from remotely sensed data for mapping wildlife habitat: Tucson

USGS Publications Warehouse

Wallace, Cynthia S.A.; Advised by Marsh, Stuart E.

2002-01-01

The research accomplished in this dissertation used both mathematical and statistical techniques to extract and evaluate measures of landscape temporal dynamics and spatial structure from remotely sensed data for the purpose of mapping wildlife habitat. By coupling the landscape measures gleaned from the remotely sensed data with various sets of animal sightings and population data, effective models of habitat preference were created.Measures of temporal dynamics of vegetation greenness as measured by National Oceanographic and Atmospheric Administration’s Advanced Very High Resolution Radiometer (AVHRR) satellite were used to effectively characterize and map season specific habitat of the Sonoran pronghorn antelope, as well as produce preliminary models of potential yellow-billed cuckoo habitat in Arizona. Various measures that capture different aspects of the temporal dynamics of the landscape were derived from AVHRR Normalized Difference Vegetation Index composite data using three main classes of calculations: basic statistics, standardized principal components analysis, and Fourier analysis. Pronghorn habitat models based on the AVHRR measures correspond visually and statistically to GIS-based models produced using data that represent detailed knowledge of ground-condition.Measures of temporal dynamics also revealed statistically significant correlations with annual estimates of elk population in selected Arizona Game Management Units, suggesting elk respond to regional environmental changes that can be measured using satellite data. Such relationships, once verified and established, can be used to help indirectly monitor the population.Measures of landscape spatial structure derived from IKONOS high spatial resolution (1-m) satellite data using geostatistics effectively map details of Sonoran pronghorn antelope habitat. Local estimates of the nugget, sill, and range variogram parameters calculated within 25 x 25-meter image windows describe the spatial autocorrelation of the image, permitting classification of all pixels into coherent units whose signature graphs exhibit a classic variogram shape. The variogram parameters captured in these signatures have been shown in previous studies to discriminate between different species-specific vegetation associations.The synoptic view of the landscape provided by satellite data can inform resource management efforts. The ability to characterize the spatial structure and temporal dynamics of habitat using repeatable remote sensing data allows closer monitoring of the relationship between a species and its landscape.

FVS out of the box - assembly required

Treesearch

Don Vandendriesche

2010-01-01

The Forest Vegetation Simulator (FVS) is a prominent growth and yield model used for forecasting stand dynamics. However, users need to be aware of model behavior regarding stocking density, tree senescence, and understory recruitment; otherwise over long projections, FVS tends to concentrate substantial growth on few survivor trees. If the intent is to forecast...

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

Modeling mechanisms of vegetation change due to fire in a semi-arid ecosystem

USGS Publications Warehouse

White, J.D.; Gutzwiller, K.J.; Barrow, W.C.; Randall, L.J.; Swint, P.

2008-01-01

Vegetation growth and community composition in semi-arid environments is determined by water availability and carbon assimilation mechanisms specific to different plant types. Disturbance also impacts vegetation productivity and composition dependent on area affected, intensity, and frequency factors. In this study, a new spatially explicit ecosystem model is presented for the purpose of simulating vegetation cover type changes associated with fire disturbance in the northern Chihuahuan Desert region. The model is called the Landscape and Fire Simulator (LAFS) and represents physiological activity of six functional plant types incorporating site climate, fire, and seed dispersal routines for individual grid cells. We applied this model for Big Bend National Park, Texas, by assessing the impact of wildfire on the trajectory of vegetation communities over time. The model was initialized and calibrated based on landcover maps derived from Landsat-5 Thematic Mapper data acquired in 1986 and 1999 coupled with plant biomass measurements collected in the field during 2000. Initial vegetation cover change analysis from satellite data showed shrub encroachment during this time period that was captured in the simulated results. A synthetic 50-year climate record was derived from historical meteorological data to assess system response based on initial landcover conditions. This simulation showed that shrublands increased to the detriment of grass and yucca-ocotillo vegetation cover types indicating an ecosystem-level trajectory for shrub encroachment. Our analysis of simulated fires also showed that fires significantly reduced site biomass components including leaf area, stem, and seed biomass in this semi-arid ecosystem. In contrast to other landscape simulation models, this new model incorporates detailed physiological responses of functional plant types that will allow us to simulated the impact of increased atmospheric CO2 occurring with climate change coupled with fire disturbance. Simulations generated from this model are expected to be the subject of subsequent studies on landscape dynamics with specific regard to prediction of wildlife distributions associated with fire management and climate change.

Application of a computationally efficient method to approximate gap model results with a probabilistic approach

NASA Astrophysics Data System (ADS)

Scherstjanoi, M.; Kaplan, J. O.; Lischke, H.

2014-07-01

To be able to simulate climate change effects on forest dynamics over the whole of Switzerland, we adapted the second-generation DGVM (dynamic global vegetation model) LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator) to the Alpine environment. We modified model functions, tuned model parameters, and implemented new tree species to represent the potential natural vegetation of Alpine landscapes. Furthermore, we increased the computational efficiency of the model to enable area-covering simulations in a fine resolution (1 km) sufficient for the complex topography of the Alps, which resulted in more than 32 000 simulation grid cells. To this aim, we applied the recently developed method GAPPARD (approximating GAP model results with a Probabilistic Approach to account for stand Replacing Disturbances) (Scherstjanoi et al., 2013) to LPJ-GUESS. GAPPARD derives mean output values from a combination of simulation runs without disturbances and a patch age distribution defined by the disturbance frequency. With this computationally efficient method, which increased the model's speed by approximately the factor 8, we were able to faster detect the shortcomings of LPJ-GUESS functions and parameters. We used the adapted LPJ-GUESS together with GAPPARD to assess the influence of one climate change scenario on dynamics of tree species composition and biomass throughout the 21st century in Switzerland. To allow for comparison with the original model, we additionally simulated forest dynamics along a north-south transect through Switzerland. The results from this transect confirmed the high value of the GAPPARD method despite some limitations towards extreme climatic events. It allowed for the first time to obtain area-wide, detailed high-resolution LPJ-GUESS simulation results for a large part of the Alpine region.

Radiative transfer in shrub savanna sites in Niger: Preliminary results from HAPEX-Sahel. Part 3: Optical dynamics and vegetation index sensitivity to biomass and plant cover

NASA Technical Reports Server (NTRS)

vanLeeuwen, W. J. D.; Huete, A. R.; Duncan, J.; Franklin, J.

1994-01-01

A shrub savannah landscape in Niger was optically characterized utilizing blue, green, red and near-infrared wavelengths. Selected vegetation indices were evaluated for their performance and sensitivity to describe the complex Sahelian soil/vegetation canopies. Bidirectional reflectance factors (BRF) of plants and soils were measured at several view angles, and used as input to various vegetation indices. Both soil and vegetation targets had strong anisotropic reflectance properties, rendering all vegetation index (6) responses to be a direct function of sun and view geometry. Soil background influences were shown to alter the response of most vegetation indices. N-space greenness had the smallest dynamic range in VI response, but the n-space brightness index provided additional useful information. The global environmental monitoring index (GEMI) showed a large 6 dynamic range for bare soils, which was undesirable for a vegetation index. The view angle response of the normalized difference vegetation index (NDVI), atmosphere resistant vegetation index (ARVI) and soil atmosphere resistant vegetation index (SARVI) were asymmetric about nadir for multiple view angles, and were, except for the SARVI, altered seriously by soil moisture and/or soil brightness effects. The soil adjusted vegetation index (SAVI) was least affected by surface soil moisture and was symmetric about nadir for grass vegetation covers. Overall the SAVI, SARVI and the n-space vegetation index performed best under all adverse conditions and were recommended to monitor vegetation growth in the sparsely vegetated Sahelian zone.

Predicting Ecologically Important Vegetation Variables from Remotely Sensed Optical/Radar Data Using Neural Networks

NASA Technical Reports Server (NTRS)

Kimes, Daniel S.; Nelson, Ross F.

1998-01-01

A number of satellite sensor systems will collect large data sets of the Earth's surface during NASA's Earth Observing System (EOS) era. Efforts are being made to develop efficient algorithms that can incorporate a wide variety of spectral data and ancillary data in order to extract vegetation variables required for global and regional studies of ecosystem processes, biosphere-atmosphere interactions, and carbon dynamics. These variables are, for the most part, continuous (e.g. biomass, leaf area index, fraction of vegetation cover, vegetation height, vegetation age, spectral albedo, absorbed photosynthetic active radiation, photosynthetic efficiency, etc.) and estimates may be made using remotely sensed data (e.g. nadir and directional optical wavelengths, multifrequency radar backscatter) and any other readily available ancillary data (e.g., topography, sun angle, ground data, etc.). Using these types of data, neural networks can: 1) provide accurate initial models for extracting vegetation variables when an adequate amount of data is available; 2) provide a performance standard for evaluating existing physically-based models; 3) invert multivariate, physically based models; 4) in a variable selection process, identify those independent variables which best infer the vegetation variable(s) of interest; and 5) incorporate new data sources that would be difficult or impossible to use with conventional techniques. In addition, neural networks employ a more powerful and adaptive nonlinear equation form as compared to traditional linear, index transformations, and simple nonlinear analyses. These neural networks attributes are discussed in the context of the authors' investigations of extracting vegetation variables of ecological interest.

30-year Dynamics of Terrestrial Vegetation Activity and the Relationship with Climatologies

NASA Astrophysics Data System (ADS)

de Jong, R.; Schaepman, M. E.; Furrer, R.; de Bruin, S.; Verburg, P. H.

2013-12-01

The climate governs the seasonal activity of terrestrial vegetation while humankind influences it. The relative role of these drivers in changing vegetation activity is crucial information for accurate modeling of vegetation and climate dynamics and for adaptation and mitigation strategies. Disentangling the two, however, is an ongoing scientific challenge, because of limited data availability, mainly regarding non-climatic drivers, and complex biosphere-atmosphere feedback mechanisms. Here, we contribute to this quest by modeling the spatial relationship between climatologies and changes in global vegetation activity (de Jong et al., 2013a). Vegetation activity is commonly quantified using remotely sensed vegetation indices (VI). Extensive reports on temporal trends over the past decades in time series of such indices can be found in literature, including the detection of shifts (de Jong et al., 2013b), which may be related to climate (e.g. Zhao & Running, 2010). However, little remains known about the exact processes underlying vegetation change at large spatial scales. Depending on eco-region, three climatologies potentially constrain plant growth (Churkina and Running, 1998). In the humid mid-latitudes, for example, temperature is the largest influencing factor; in (semi) arid regions it is the availability of water and in the tropics incident solar radiation. Based on this logic, we developed a mixed-effect model to relate changes in these climatologies to changes in vegetation activity and to quantify the spatial process underlying the other drivers, including human land use. Little over 50% of the spatial variation in vegetation change could be attributed to changes in climatologies; conspicuously, many of the global ';greening' trends and the ';browning' hotspots in Argentina and Australia. Browning hotspots in the non-climatic component were especially located in subequatorial Africa (e.g. parts of Zimbabwe and Tanzania), where human drivers may be responsible. Indications for browning under warming conditions were found in some boreal regions. These results are examples of relationships we can find within readily available datasets, without a-priori information, and may be used as indicator for drivers of biospheric change. Churkina G, Running SW (1998) Contrasting climatic controls on the estimated productivity of global terrestrial biomes. Ecosystems, 1, 206-215 de Jong R, Schaepman ME, Furrer R, De Bruin S, Verburg PH (2013a) Spatial relationship between climatologies and changes in global vegetation activity. Global Change Biology, 19, 1953-1964 de Jong, R, Verbesselt, J, Zeileis, A, & Schaepman, ME (2013b) Shifts in Global Vegetation Activity Trends. Remote Sensing, 5, 1117-1133 Zhao M, Running SW (2010) Drought-Induced Reduction in Global Terrestrial Net Primary Production from 2000 Through 2009. Science, 329, 940-943

Analysis of regional-scale vegetation dynamics of Mexico using stratified AVHRR NDVI data. [Normalized Difference Vegetaion Index

NASA Technical Reports Server (NTRS)

Turcotte, Kevin M.; Kramber, William J.; Venugopal, Gopalan; Lulla, Kamlesh

1989-01-01

Previous studies have shown that a good relationship exists between AVHRR Normalized Difference Vegetation Index (NDVI) measurements, and both regional-scale patterns of vegetation seasonality and productivity. Most of these studies used known samples of vegetation types. An alternative approach, and the objective was to examine the above relationships by analyzing one year of AVHRR NDVI data that was stratified using a small-scale vegetation map of Mexico. The results show that there is a good relationship between AVHRR NDVI measurements and regional-scale vegetation dynamics of Mexico.

What determines area burned in large landscapes? Insights from a decade of comparative landscape-fire modelling

Treesearch

Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan; Ian D. Davies; Russ A. Parsons

2015-01-01

Understanding what determines area burned in large landscapes is critical for informing wildland fire management in fire-prone environments and for representing fire activity in Dynamic Global Vegetation Models. For the past ten years, a group of landscape-fire modellers have been exploring the relative influence of key determinants of area burned in temperate and...

Simulation and sensitivity analysis of carbon storage and fluxes in the New Jersey Pinelands

Treesearch

Zewei Miao; Richard G. Lathrop; Ming Xu; Inga P. La Puma; Kenneth L. Clark; John Hom; Nicholas Skowronski; Steve Van Tuyl

2011-01-01

A major challenge in modeling the carbon dynamics of vegetation communities is the proper parameterization and calibration of eco-physiological variables that are critical determinants of the ecosystem process-based model behavior. In this study, we improved and calibrated a biochemical process-based WxBGC model by using in situ AmeriFlux eddy covariance tower...

Evaluating the impact of a wide range of vegetation densities on river channel pattern

NASA Astrophysics Data System (ADS)

Pattison, Ian; Roucou, Ron

2016-04-01

Braided rivers are very dynamic systems which have complex controls over their planform and flow dynamics. Vegetation is one variable which influences channel geometry and pattern, through its effect on local flow hydraulics and the process continuum of sediment erosion-transport-deposition. Furthermore, where in the braided floodplain stable vegetation develops depends on the temporal sequencing of the river discharge i.e. floods. Understanding the effect of vegetation in these highly dynamic systems has multiple consequences for human activity and floodplain management. This paper focusses on the specific role of vegetation density in controlling braided river form and processes. Previous research in this field has been contradictory; with Gran and Paola (2001) finding that increasing vegetation density decreased the number of active channels. In contrast, Coulthard (2005] observed that as vegetation become denser there was an increase in the number of channels. This was hypothesized to be caused by flow separation around vegetation and the development of bars immediately downstream of the plant. This paper reports the results from a set of experiments in a 4m by 1m flume, where discharge, slope and sediment size were kept constant. Artificial grass was used to represent vegetation with a density ranging from 50 plants/m2 to 400 plants/m2. Digital photographs, using a GoPro camera with a fish eye lens, were taken from ~1m above the flume at an interval of 30 seconds during the 3 hour experiment. The experiments showed that as the vegetation density increased from 50 to 150 plants/m2, the number of channel bars developing doubled from 12 to 24. At vegetation densities greater than 150 plants/m2 there was a decline in the number of bars created to a minimum of 8 bars for a density of 400 plants/m2. We attribute these patterns to the effect that the vegetation has on flow hydraulics, sediment transport processes and the spatial patterns of erosion and deposition. We develop a simple conceptual model to explain the observations along the wide range of vegetation densities investigated. At low plant densities, each plant acted independently and caused flow separation and convergence around each plant, similar to in the Coulthard (2005] experiment. At medium densities, individual plants start to interact together with narrow channels developing longitudinally between vegetative bars. Finally at very high densities, there was both lateral and longitudinal interaction between plants meaning that flow was diverted around them forming wandering, meandering channels. In summary, the relationship between vegetation density and channel braiding is more complex than previous thought, taking a parabolic shape, with maximum braiding occurring at medium vegetation densities.

Simulating carbon flows in Amazonian rainforests: how intensive C-cycle data can help to reduce vegetation model uncertainty

NASA Astrophysics Data System (ADS)

Galbraith, D.; Levine, N. M.; Christoffersen, B. O.; Imbuzeiro, H. A.; Powell, T.; Costa, M. H.; Saleska, S. R.; Moorcroft, P. R.; Malhi, Y.

2014-12-01

The mathematical codes embedded within different vegetation models ultimately represent alternative hypotheses of biosphere functioning. While formulations for some processes (e.g. leaf-level photosynthesis) are often shared across vegetation models, other processes (e.g. carbon allocation) are much more variable in their representation across models. This creates the opportunity for equifinality - models can simulate similar values of key metrics such as NPP or biomass through very different underlying causal pathways. Intensive carbon cycle measurements allow for quantification of a comprehensive suite of carbon fluxes such as the productivity and respiration of leaves, roots and wood, allowing for in-depth assessment of carbon flows within ecosystems. Thus, they provide important information on poorly-constrained C-cycle processes such as allocation. We conducted an in-depth evaluation of the ability of four commonly used dynamic global vegetation models (CLM, ED2, IBIS, JULES) to simulate carbon cycle processes at ten lowland Amazonian rainforest sites where individual C-cycle components have been measured. The rigorous model-data comparison procedure allowed identification of biases which were specific to different models, providing clear avenues for model improvement and allowing determination of internal C-cycling pathways that were better supported by data. Furthermore, the intensive C-cycle data allowed for explicit testing of the validity of a number of assumptions made by specific models in the simulation of carbon allocation and plant respiration. For example, the ED2 model assumes that maintenance respiration of stems is negligible while JULES assumes equivalent allocation of NPP to fine roots and leaves. We argue that field studies focusing on simultaneous measurement of a large number of component fluxes are fundamentally important for reducing uncertainty in vegetation model simulations.

Utilizing multisource remotely sensed data to dynamically monitor drought in China

NASA Astrophysics Data System (ADS)

Liu, Sanchao; Li, Wenbo

2011-12-01

Drought is one of major nature disaster in the world and China. China has a vast territory and very different spatio-temporal distribution weather condition. Therefore, drought disasters occur frequently throughout China, which may affect large areas and cause great economic loss every year. In this paper, geostationary meteorological remote sensing data, FY-2C/D/E VISSR and three quantitative remotely sensed models including Cloud Parameters Method (CPM), Vegetation Supply Water Index (VSWI), and Temperature Vegetation Dryness Index (TVDI) have been used to dynamically monitor severe drought in southwest China from 2009 to 2010. The results have effectively revealed the occurrence, development and disappearance of this drought event. The monitoring results can be used for the relevant disaster management departments' decision-making works.

Probabilistic model predicts dynamics of vegetation biomass in a desert ecosystem in NW China

PubMed Central

Wang, Xin-ping; Schaffer, Benjamin Eli; Yang, Zhenlei; Rodriguez-Iturbe, Ignacio

2017-01-01

The temporal dynamics of vegetation biomass are of key importance for evaluating the sustainability of arid and semiarid ecosystems. In these ecosystems, biomass and soil moisture are coupled stochastic variables externally driven, mainly, by the rainfall dynamics. Based on long-term field observations in northwestern (NW) China, we test a recently developed analytical scheme for the description of the leaf biomass dynamics undergoing seasonal cycles with different rainfall characteristics. The probabilistic characterization of such dynamics agrees remarkably well with the field measurements, providing a tool to forecast the changes to be expected in biomass for arid and semiarid ecosystems under climate change conditions. These changes will depend—for each season—on the forecasted rate of rainy days, mean depth of rain in a rainy day, and duration of the season. For the site in NW China, the current scenario of an increase of 10% in rate of rainy days, 10% in mean rain depth in a rainy day, and no change in the season duration leads to forecasted increases in mean leaf biomass near 25% in both seasons. PMID:28584097

Influence of feedbacks from simulated crop growth on integrated regional hydrologic simulations under climate scenarios

NASA Astrophysics Data System (ADS)

van Walsum, P. E. V.

2011-11-01

Climate change impact modelling of hydrologic responses is hampered by climate-dependent model parameterizations. Reducing this dependency was one of the goals of extending the regional hydrologic modelling system SIMGRO with a two-way coupling to the crop growth simulation model WOFOST. The coupling includes feedbacks to the hydrologic model in terms of the root zone depth, soil cover, leaf area index, interception storage capacity, crop height and crop factor. For investigating whether such feedbacks lead to significantly different simulation results, two versions of the model coupling were set up for a test region: one with exogenous vegetation parameters, the "static" model, and one with endogenous simulation of the crop growth, the "dynamic" model WOFOST. The used parameterization methods of the static/dynamic vegetation models ensure that for the current climate the simulated long-term average of the actual evapotranspiration is the same for both models. Simulations were made for two climate scenarios. Owing to the higher temperatures in combination with a higher CO2-concentration of the atmosphere, a forward time shift of the crop development is simulated in the dynamic model; the used arable land crop, potatoes, also shows a shortening of the growing season. For this crop, a significant reduction of the potential transpiration is simulated compared to the static model, in the example by 15% in a warm, dry year. In consequence, the simulated crop water stress (the unit minus the relative transpiration) is lower when the dynamic model is used; also the simulated increase of crop water stress due to climate change is lower; in the example, the simulated increase is 15 percentage points less (of 55) than when a static model is used. The static/dynamic models also simulate different absolute values of the transpiration. The difference is most pronounced for potatoes at locations with ample moisture supply; this supply can either come from storage release of a good soil or from capillary rise. With good supply of moisture, the dynamic model simulates up to 10% less actual evapotranspiration than the static one in the example. This can lead to cases where the dynamic model predicts a slight increase of the recharge in a climate scenario, where the static model predicts a decrease. The use of a dynamic model also affects the simulated demand for surface water from external sources; especially the timing is affected. The proposed modelling approach uses postulated relationships that require validation with controlled field trials. In the Netherlands there is a lack of experimental facilities for performing such validations.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China.

PubMed

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-10-07

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide.

A probabilistic assessment of the likelihood of vegetation drought under varying climate conditions across China

PubMed Central

Liu, Zhiyong; Li, Chao; Zhou, Ping; Chen, Xiuzhi

2016-01-01

Climate change significantly impacts the vegetation growth and terrestrial ecosystems. Using satellite remote sensing observations, here we focus on investigating vegetation dynamics and the likelihood of vegetation-related drought under varying climate conditions across China. We first compare temporal trends of Normalized Difference Vegetation Index (NDVI) and climatic variables over China. We find that in fact there is no significant change in vegetation over the cold regions where warming is significant. Then, we propose a joint probability model to estimate the likelihood of vegetation-related drought conditioned on different precipitation/temperature scenarios in growing season across China. To the best of our knowledge, this study is the first to examine the vegetation-related drought risk over China from a perspective based on joint probability. Our results demonstrate risk patterns of vegetation-related drought under both low and high precipitation/temperature conditions. We further identify the variations in vegetation-related drought risk under different climate conditions and the sensitivity of drought risk to climate variability. These findings provide insights for decision makers to evaluate drought risk and vegetation-related develop drought mitigation strategies over China in a warming world. The proposed methodology also has a great potential to be applied for vegetation-related drought risk assessment in other regions worldwide. PMID:27713530