Comparative Model Evaluation Studies of Biogenic Trace Gas Fluxes in Tropical Forests

NASA Technical Reports Server (NTRS)

Potter, C. S.; Peterson, David L. (Technical Monitor)

1997-01-01

Simulation modeling can play a number of important roles in large-scale ecosystem studies, including synthesis of patterns and changes in carbon and nutrient cycling dynamics, scaling up to regional estimates, and formulation of testable hypotheses for process studies. Recent comparative studies have shown that ecosystem models of soil trace gas exchange with the atmosphere are evolving into several distinct simulation approaches. Different levels of detail exist among process models in the treatment of physical controls on ecosystem nutrient fluxes and organic substrate transformations leading to gas emissions. These differences are is in part from distinct objectives of scaling and extrapolation. Parameter requirements for initialization scalings, boundary conditions, and time-series driven therefore vary among ecosystem simulation models, such that the design of field experiments for integration with modeling should consider a consolidated series of measurements that will satisfy most of the various model requirements. For example, variables that provide information on soil moisture holding capacity, moisture retention characteristics, potential evapotranspiration and drainage rates, and rooting depth appear to be of the first order in model evaluation trials for tropical moist forest ecosystems. The amount and nutrient content of labile organic matter in the soil, based on accurate plant production estimates, are also key parameters that determine emission model response. Based on comparative model results, it is possible to construct a preliminary evaluation matrix along categories of key diagnostic parameters and temporal domains. Nevertheless, as large-scale studied are planned, it is notable that few existing models age designed to simulate transient states of ecosystem change, a feature which will be essential for assessment of anthropogenic disturbance on regional gas budgets, and effects of long-term climate variability on biosphere-atmosphere exchange.

Assimilation of Ocean-Color Plankton Functional Types to Improve Marine Ecosystem Simulations

NASA Astrophysics Data System (ADS)

Ciavatta, S.; Brewin, R. J. W.; Skákala, J.; Polimene, L.; de Mora, L.; Artioli, Y.; Allen, J. I.

2018-02-01

We assimilated phytoplankton functional types (PFTs) derived from ocean color into a marine ecosystem model, to improve the simulation of biogeochemical indicators and emerging properties in a shelf sea. Error-characterized chlorophyll concentrations of four PFTs (diatoms, dinoflagellates, nanoplankton, and picoplankton), as well as total chlorophyll for comparison, were assimilated into a physical-biogeochemical model of the North East Atlantic, applying a localized Ensemble Kalman filter. The reanalysis simulations spanned the years 1998-2003. The skill of the reference and reanalysis simulations in estimating ocean color and in situ biogeochemical data were compared by using robust statistics. The reanalysis outperformed both the reference and the assimilation of total chlorophyll in estimating the ocean-color PFTs (except nanoplankton), as well as the not-assimilated total chlorophyll, leading the model to simulate better the plankton community structure. Crucially, the reanalysis improved the estimates of not-assimilated in situ data of PFTs, as well as of phosphate and pCO2, impacting the simulation of the air-sea carbon flux. However, the reanalysis increased further the model overestimation of nitrate, in spite of increases in plankton nitrate uptake. The method proposed here is easily adaptable for use with other ecosystem models that simulate PFTs, for, e.g., reanalysis of carbon fluxes in the global ocean and for operational forecasts of biogeochemical indicators in shelf-sea ecosystems.

Evaluation of model predictions of the ecological effects of 4-nonylphenol -- before and after model refinement

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

Hanratty, M.P.; Liber, K.

1994-12-31

The Littoral Ecosystem Risk Assessment Model (LERAM) is a bioenergetic ecosystem effects model. It links single species toxicity data to a bioenergetic model of the trophic structure of an ecosystem in order to simulate community and ecosystem level effects of chemical stressors. LERAM was used in 1992 to simulate the ecological effects of diflubenzuron. When compared to the results from a littoral enclosure study, the model exaggerated the cascading of effects through the trophic levels of the littoral ecosystem. It was hypothesized that this could be corrected by making minor changes in the representation of the littoral food web. Twomore » refinements of the model were therefore performed: (1) the plankton and macroinvertebrate model populations [eg., predatory Copepoda, herbivorous Insecta, green phytoplankton, etc.] were changed to better represent the habitat and feeding preferences of the endemic taxa; and (2) the method for modeling the microbial degradation of detritus (and the resulting nutrient remineralization) was changed from simulating bacterial populations to simulating bacterial function. Model predictions of the ecological effects of 4-nonylphenol were made before and after these refinements. Both sets of predictions were then compared to the results from a littoral enclosure study of the ecological effects of 4-nonylphenol. The changes in the LERAM predictions were then used to determine the success of the refinements, to guide. future research, and to further define LERAM`s domain of application.« less

Current and future carbon budget at Takayama site, Japan, evaluated by a regional climate model and a process-based terrestrial ecosystem model.

PubMed

Kuribayashi, Masatoshi; Noh, Nam-Jin; Saitoh, Taku M; Ito, Akihiko; Wakazuki, Yasutaka; Muraoka, Hiroyuki

2017-06-01

Accurate projection of carbon budget in forest ecosystems under future climate and atmospheric carbon dioxide (CO 2 ) concentration is important to evaluate the function of terrestrial ecosystems, which serve as a major sink of atmospheric CO 2 . In this study, we examined the effects of spatial resolution of meteorological data on the accuracies of ecosystem model simulation for canopy phenology and carbon budget such as gross primary production (GPP), ecosystem respiration (ER), and net ecosystem production (NEP) of a deciduous forest in Japan. Then, we simulated the future (around 2085) changes in canopy phenology and carbon budget of the forest by incorporating high-resolution meteorological data downscaled by a regional climate model. The ecosystem model overestimated GPP and ER when we inputted low-resolution data, which have warming biases over mountainous landscape. But, it reproduced canopy phenology and carbon budget well, when we inputted high-resolution data. Under the future climate, earlier leaf expansion and delayed leaf fall by about 10 days compared with the present state was simulated, and also, GPP, ER and NEP were estimated to increase by 25.2%, 23.7% and 35.4%, respectively. Sensitivity analysis showed that the increase of NEP in June and October would be mainly caused by rising temperature, whereas that in July and August would be largely attributable to CO 2 fertilization. This study suggests that the downscaling of future climate data enable us to project more reliable carbon budget of forest ecosystem in mountainous landscape than the low-resolution simulation due to the better predictions of leaf expansion and shedding.

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.

Parameterisation of Biome BGC to assess forest ecosystems in Africa

NASA Astrophysics Data System (ADS)

Gautam, Sishir; Pietsch, Stephan A.

2010-05-01

African forest ecosystems are an important environmental and economic resource. Several studies show that tropical forests are critical to society as economic, environmental and societal resources. Tropical forests are carbon dense and thus play a key role in climate change mitigation. Unfortunately, the response of tropical forests to environmental change is largely unknown owing to insufficient spatially extensive observations. Developing regions like Africa where records of forest management for long periods are unavailable the process-based ecosystem simulation model - BIOME BGC could be a suitable tool to explain forest ecosystem dynamics. This ecosystem simulation model uses descriptive input parameters to establish the physiology, biochemistry, structure, and allocation patterns within vegetation functional types, or biomes. Undocumented parameters for larger-resolution simulations are currently the major limitations to regional modelling in African forest ecosystems. This study was conducted to document input parameters for BIOME-BGC for major natural tropical forests in the Congo basin. Based on available literature and field measurements updated values for turnover and mortality, allometry, carbon to nitrogen ratios, allocation of plant material to labile, cellulose, and lignin pools, tree morphology and other relevant factors were assigned. Daily climate input data for the model applications were generated using the statistical weather generator MarkSim. The forest was inventoried at various sites and soil samples of corresponding stands across Gabon were collected. Carbon and nitrogen in the collected soil samples were determined from soil analysis. The observed tree volume, soil carbon and soil nitrogen were then compared with the simulated model outputs to evaluate the model performance. Furthermore, the simulation using Congo Basin specific parameters and generalised BIOME BGC parameters for tropical evergreen broadleaved tree species were also executed and the simulated results compared. Once the model was optimised for forests in the Congo basin it was validated against observed tree volume, soil carbon and soil nitrogen from a set of independent plots.

Simulation of hydrologic influences on wetland ecosystem succession. Master's thesis

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

Pompilio, R.A.

1994-09-01

This research focuses on the development of a simulation model to determine the affects of hydrological influences on a wetland ecosystem. The model allows perturbations to the inputs of various wetland data which in turn, influences the successional development of the ecosystem. This research consisted of converting a grassland ecosystem model to one which simulates wetland conditions. The critical factor in determining the success of wetland creation is the hydrology of the system. There are four of the areas of the original model which are affected by the hydrology. The model measures the health or success of the ecosystem throughmore » the measurement of the systems gross plant production, the respiration and the net primary production of biomass. Altering the auxiliary variables of water level and the rate of flow through the system explicitly details the affects hydrologic influences on those production rates. Ten case tests depicting exogenous perturbations of the hydrology were run to identify these affects. Although the tests dealt with the fluctuation of water through the system, any one of the auxiliary variables in the model could be changed to reflect site specific data. Productivity, Hazardous material management, Hazardous material pharmacy.« less

Available fuel dynamics in nine contrasting forest ecosystems in North America

Treesearch

Soung-Ryoul Ryu; Jiquan Chen; Thomas R. Crow; Sari C. Saunders

2004-01-01

Available fuel and its dynamics, both of which affect fire behavior in forest ecosystems, are direct products of ecosystem production, decomposition, and disturbances. Using published ecosystem models and equations, we developed a simulation model to evaluate the effects of dynamics of aboveground net primary production (ANPP), carbon allocation, residual slash,...

Simulating the biogeochemical cycles in cypress wetland-pine upland ecosystems at a landscape scale with the wetland-DNDC model

Treesearch

G. Sun; C. Li; C. Tretting; J. Lu; S.G. McNulty

2005-01-01

A modeling framework (Wetland-DNDC) that described forested wetland ecosystem processes has been developed and validated with data from North America and Europe. The model simulates forest photosynthesis, respiration, carbon allocation, and liter production, soil organic matter (SOM) turnover, trace gas emissions, and N leaching. Inputs required by Wetland-DNDC...

Processes influencing model-data mismatch in drought-stressed, fire-disturbed eddy flux sites

NASA Astrophysics Data System (ADS)

Mitchell, Stephen; Beven, Keith; Freer, Jim; Law, Beverly

2011-06-01

Semiarid forests are very sensitive to climatic change and among the most difficult ecosystems to accurately model. We tested the performance of the Biome-BGC model against eddy flux data taken from young (years 2004-2008), mature (years 2002-2008), and old-growth (year 2000) ponderosa pine stands at Metolius, Oregon, and subsequently examined several potential causes for model-data mismatch. We used the Generalized Likelihood Uncertainty Estimation methodology, which involved 500,000 model runs for each stand (1,500,000 total). Each simulation was run with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in modeled estimates of net ecosystem CO2 exchange (NEE) that were compared to measured eddy flux data. Simulations for the young stand exhibited the highest level of performance, though they overestimated ecosystem C accumulation (-NEE) 99% of the time. Among the simulations for the mature and old-growth stands, 100% and 99% of the simulations underestimated ecosystem C accumulation. One obvious area of model-data mismatch is soil moisture, which was overestimated by the model in the young and old-growth stands yet underestimated in the mature stand. However, modeled estimates of soil water content and associated water deficits did not appear to be the primary cause of model-data mismatch; our analysis indicated that gross primary production can be accurately modeled even if soil moisture content is not. Instead, difficulties in adequately modeling ecosystem respiration, mainly autotrophic respiration, appeared to be the fundamental cause of model-data mismatch.

Processes influencing model-data mismatch in drought-stressed, fire-disturbed eddy flux sites

NASA Astrophysics Data System (ADS)

Mitchell, S. R.; Beven, K.; Freer, J. E.; Law, B. E.

2010-12-01

Semi-arid forests are very sensitive to climatic change and among the most difficult ecosystems to accurately model. We tested the performance of the Biome-BGC model against eddy flux data taken from young (years 2004-2008), mature (years 2002-2008), and old-growth (year 2000) Ponderosa pine stands at Metolius, Oregon, and subsequently examined several potential causes for model-data mismatch. We used the generalized likelihood uncertainty estimation (GLUE) methodology, which involved 500,000 model runs for each stand (1,500,000 total). Each simulation was run with randomly generated parameter values from a uniform distribution based on published parameter ranges, resulting in modeled estimates of net ecosystem CO2 exchange (NEE) that were compared to measured eddy flux data. Simulations for the young stand exhibited the highest level of performance, though they over-estimated ecosystem C accumulation (-NEE) 99% of the time. Among the simulations for the mature and old-growth stands, 100% and 99% of the simulations under-estimated ecosystem C accumulation. One obvious area of model-data mismatch is soil moisture, which was overestimated by the model in the young and old-growth stands yet underestimated in the mature stand. However, modeled estimates of soil water content and associated water deficits did not appear to be the primary cause of model-data mismatch; our analysis indicated that gross primary production can be accurately modeled even if soil moisture content is not. Instead, difficulties in adequately modeling ecosystem respiration, both autotrophic and heterotrophic, appeared to be fundamental causes of model-data mismatch.

A dynamic organic soil biogeochemical model for simulating the effects of wildfire on soil environmental conditions and carbon dynamics of black spruce forests

Treesearch

Shuhua Yi; A. David McGuire; Eric Kasischke; Jennifer Harden; Kristen Manies; Michelle Mack; Merritt Turetsky

2010-01-01

Ecosystem models have not comprehensively considered how interactions among fire disturbance, soil environmental conditions, and biogeochemical processes affect ecosystem dynamics in boreal forest ecosystems. In this study, we implemented a dynamic organic soil structure in the Terrestrial Ecosystem Model (DOS-TEM) to investigate the effects of fire on soil temperature...

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

Development of the BIOME-BGC model for the simulation of managed Moso bamboo forest ecosystems.

PubMed

Mao, Fangjie; Li, Pingheng; Zhou, Guomo; Du, Huaqiang; Xu, Xiaojun; Shi, Yongjun; Mo, Lufeng; Zhou, Yufeng; Tu, Guoqing

2016-05-01

Numerical models are the most appropriate instrument for the analysis of the carbon balance of terrestrial ecosystems and their interactions with changing environmental conditions. The process-based model BIOME-BGC is widely used in simulation of carbon balance within vegetation, litter and soil of unmanaged ecosystems. For Moso bamboo forests, however, simulations with BIOME-BGC are inaccurate in terms of the growing season and the carbon allocation, due to the oversimplified representation of phenology. Our aim was to improve the applicability of BIOME-BGC for managed Moso bamboo forest ecosystem by implementing several new modules, including phenology, carbon allocation, and management. Instead of the simple phenology and carbon allocation representations in the original version, a periodic Moso bamboo phenology and carbon allocation module was implemented, which can handle the processes of Moso bamboo shooting and high growth during "on-year" and "off-year". Four management modules (digging bamboo shoots, selective cutting, obtruncation, fertilization) were integrated in order to quantify the functioning of managed ecosystems. The improved model was calibrated and validated using eddy covariance measurement data collected at a managed Moso bamboo forest site (Anji) during 2011-2013 years. As a result of these developments and calibrations, the performance of the model was substantially improved. Regarding the measured and modeled fluxes (gross primary production, total ecosystem respiration, net ecosystem exchange), relative errors were decreased by 42.23%, 103.02% and 18.67%, respectively. Copyright © 2015 Elsevier Ltd. All rights reserved.

Upscaling key ecosystem functions across the conterminous United States by a water‐centric ecosystem model

Treesearch

Ge Sun; Peter Caldwell; Asko Noormets; Steven G. McNulty; Erika Cohen; al. et.

2011-01-01

We developed a water‐centric monthly scale simulation model (WaSSI‐C) by integrating empirical water and carbon flux measurements from the FLUXNET network and an existing water supply and demand accounting model (WaSSI). The WaSSI‐C model was evaluated with basin‐scale evapotranspiration (ET), gross ecosystem productivity (GEP), and net ecosystem exchange (NEE)...

Microbial processes in marine ecosystem models: state of the art and future prospective

NASA Astrophysics Data System (ADS)

Polimene, L.; Butenschon, M.; Blackford, J.; Allen, I.

2012-12-01

Heterotrophic bacteria play a key role in the marine biogeochemistry being the main consumer of dissolved organic matter (DOM) and the main producer of carbon dioxide (CO2) by respiration. Quantifying the carbon and energy fluxes within bacteria (i.e. production, respiration, overflow metabolism etc.) is therefore crucial for the assessment of the global ocean carbon and nutrient cycles. Consequently, the description of bacteria dynamic in ecosystem models is a key (although challenging) issue which cannot be overlooked if we want to properly simulate the marine environment. We present an overview of the microbial processes described in the European Sea Regional Ecosystem Model (ERSEM), a state of the art biogeochemical model resolving carbon and nutrient cycles (N, P, Si and Fe) within the low trophic levels (up to mesozooplankton) of the marine ecosystem. The description of the theoretical assumptions and philosophy underpinning the ERSEM bacteria sub-model will be followed by the presentation of some case studies highlighting the relevance of resolving microbial processes in the simulation of ecosystem dynamics at a local scale. Recent results concerning the implementation of ERSEM on a global ocean domain will be also presented. This latter exercise includes a comparison between simulations carried out with the full bacteria sub-model and simulations carried out with an implicit parameterization of bacterial activity. The results strongly underline the importance of explicitly resolved bacteria in the simulation of global carbon fluxes. Finally, a summary of the future developments along with issues still open on the topic will be presented and discussed.

Application of a coupled ecosystem-chemical equilibrium model, DayCent-Chem, to stream and soil chemistry in a Rocky Mountain watershed

USGS Publications Warehouse

Hartman, M.D.; Baron, Jill S.; Ojima, D.S.

2007-01-01

Atmospheric deposition of sulfur and nitrogen species have the potential to acidify terrestrial and aquatic ecosystems, but nitrate and ammonium are also critical nutrients for plant and microbial productivity. Both the ecological response and the hydrochemical response to atmospheric deposition are of interest to regulatory and land management agencies. We developed a non-spatial biogeochemical model to simulate soil and surface water chemistry by linking the daily version of the CENTURY ecosystem model (DayCent) with a low temperature aqueous geochemical model, PHREEQC. The coupled model, DayCent-Chem, simulates the daily dynamics of plant production, soil organic matter, cation exchange, mineral weathering, elution, stream discharge, and solute concentrations in soil water and stream flow. By aerially weighting the contributions of separate bedrock/talus and tundra simulations, the model was able to replicate the measured seasonal and annual stream chemistry for most solutes for Andrews Creek in Loch Vale watershed, Rocky Mountain National Park. Simulated soil chemistry, net primary production, live biomass, and soil organic matter for forest and tundra matched well with measurements. This model is appropriate for accurately describing ecosystem and surface water chemical response to atmospheric deposition and climate change. ?? 2006 Elsevier B.V. All rights reserved.

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.

SIMULATION MODEL FOR WATERSHED MANAGEMENT PLANNING. VOLUME 1. MODEL THEORY AND FORMULATION

EPA Science Inventory

Evaluation of nonpoint source pollution problems requires an understanding of the behavioral response to an ecosystem to the impacts of land use activities on individual components of that ecosystem. By analyzing basic ecosystem processes and impacts of land use activities on spe...

Food web modeling of a river ecosystem for risk assessment of down-the-drain chemicals: a case study with AQUATOX.

PubMed

Lombardo, Andrea; Franco, Antonio; Pivato, Alberto; Barausse, Alberto

2015-03-01

Conventional approaches to estimating protective ecotoxicological thresholds of chemicals, i.e. predicted no-effect concentrations (PNEC), for an entire ecosystem are based on the use of assessment factors to extrapolate from single-species toxicity data derived in the laboratory to community-level effects on ecosystems. Aquatic food web models may be a useful tool to improve the ecological realism of chemical risk assessment because they enable a more insightful evaluation of the fate and effects of chemicals in dynamic trophic networks. A case study was developed in AQUATOX to simulate the effects of the anionic surfactant linear alkylbenzene sulfonate and the antimicrobial triclosan on a lowland riverine ecosystem. The model was built for a section of the River Thames (UK), for which detailed ecological surveys were available, allowing for a quantification of energy flows through the whole ecosystem. A control scenario was successfully calibrated for a simulation period of one year, and tested for stability over six years. Then, the model ecosystem was perturbed with varying inputs of the two chemicals. Simulations showed that both chemicals rapidly approach steady-state, with internal concentrations in line with the input bioconcentration factors throughout the year. At realistic environmental concentrations, both chemicals have insignificant effects on biomass trends. At hypothetical higher concentrations, direct and indirect effects of chemicals on the ecosystem dynamics emerged from the simulations. Indirect effects due to competition for food sources and predation can lead to responses in biomass density of the same magnitude as those caused by direct toxicity. Indirect effects can both exacerbate or compensate for direct toxicity. Uncertainties in key model assumptions are high as the validation of perturbed simulations remains extremely challenging. Nevertheless, the study is a step towards the development of realistic ecological scenarios and their potential use in prospective risk assessment of down-the-drain chemicals. Copyright © 2014 Elsevier B.V. All rights reserved.

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.

Use of Combined Biogeochemical Model Approaches and Empirical Data to Assess Critical Loads of Nitrogen

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

Fenn, Mark E.; Driscoll, Charles; Zhou, Qingtao

2015-01-01

Empirical and dynamic biogeochemical modelling are complementary approaches for determining the critical load (CL) of atmospheric nitrogen (N) or other constituent deposition that an ecosystem can tolerate without causing ecological harm. The greatest benefits are obtained when these approaches are used in combination. Confounding environmental factors can complicate the determination of empirical CLs across depositional gradients, while the experimental application of N amendments for estimating the CL does not realistically mimic the effects of chronic atmospheric N deposition. Biogeochemical and vegetation simulation models can provide CL estimates and valuable ecosystem response information, allowing for past and future scenario testing withmore » various combinations of environmental factors, pollutants, pollutant control options, land management, and ecosystem response parameters. Even so, models are fundamentally gross simplifications of the real ecosystems they attempt to simulate. Empirical approaches are vital as a check on simulations and CL estimates, to parameterize models, and to elucidate mechanisms and responses under real world conditions. In this chapter, we provide examples of empirical and modelled N CL approaches in ecosystems from three regions of the United States: mixed conifer forest, desert scrub and pinyon- juniper woodland in California; alpine catchments in the Rocky Mountains; and lakes in the Adirondack region of New York state.« less

Carbon cycling in extratropical terrestrial ecosystems of the Northern Hemisphere during the 20th century: a modeling analysis of the influences of soil thermal dynamics

USGS Publications Warehouse

Zhuang, Q.; McGuire, A.D.; Melillo, J.M.; Clein, Joy S.; Dargaville, R.J.; Kicklighter, D.W.; Myneni, Ranga B.; Dong, J.; Romanovsky, V.E.; Harden, J.; Hobbie, J.E.

2003-01-01

There is substantial evidence that soil thermal dynamics are changing in terrestrial ecosystems of the Northern Hemisphere and that these dynamics have implications for the exchange of carbon between terrestrial ecosystems and the atmosphere. To date, large-scale biogeochemical models have been slow to incorporate the effects of soil thermal dynamics on processes that affect carbon exchange with the atmosphere. In this study we incorporated a soil thermal module (STM), appropriate to both permafrost and non-permafrost soils, into a large-scale ecosystem model, version 5.0 of the Terrestrial Ecosystem Model (TEM). We then compared observed regional and seasonal patterns of atmospheric CO2 to simulations of carbon dynamics for terrestrial ecosystems north of 30°N between TEM 5.0 and an earlier version of TEM (version 4.2) that lacked a STM. The timing of the draw-down of atmospheric CO2 at the start of the growing season and the degree of draw-down during the growing season were substantially improved by the consideration of soil thermal dynamics. Both versions of TEM indicate that climate variability and change promoted the loss of carbon from temperate ecosystems during the first half of the 20th century, and promoted carbon storage during the second half of the century. The results of the simulations by TEM suggest that land-use change in temperate latitudes (30–60°N) plays a stronger role than climate change in driving trends for increased uptake of carbon in extratropical terrestrial ecosystems (30–90°N) during recent decades. In the 1980s the TEM 5.0 simulation estimated that extratropical terrestrial ecosystems stored 0.55 Pg C yr−1, with 0.24 Pg C yr−1 in North America and 0.31 Pg C yr−1 in northern Eurasia. From 1990 through 1995 the model simulated that these ecosystems stored 0.90 Pg C yr−1, with 0.27 Pg C yr−1 stored in North America and 0.63 Pg C yr−1 stored in northern Eurasia. Thus, in comparison to the 1980s, simulated net carbon storage in the 1990s was enhanced by an additional 0.35 Pg C yr−1 in extratropical terrestrial ecosystems, with most of the additional storage in northern Eurasia. The carbon storage simulated by TEM 5.0 in the 1980s and 1990s was lower than estimates based on other methodologies, including estimates by atmospheric inversion models and remote sensing and inventory analyses. This suggests that other issues besides the role of soil thermal dynamics may be responsible, in part, for the temporal and spatial dynamics of carbon storage of extratropical terrestrial ecosystems. In conclusion, the consideration of soil thermal dynamics and terrestrial cryospheric processes in modeling the global carbon cycle has helped to reduce biases in the simulation of the seasonality of carbon dynamics of extratropical terrestrial ecosystems. This progress should lead to an enhanced ability to clarify the role of other issues that influence carbon dynamics in terrestrial regions that experience seasonal freezing and thawing of soil.

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...

Assessment of coastal management options by means of multilayered ecosystem models

NASA Astrophysics Data System (ADS)

Nobre, Ana M.; Ferreira, João G.; Nunes, João P.; Yan, Xiaojun; Bricker, Suzanne; Corner, Richard; Groom, Steve; Gu, Haifeng; Hawkins, Anthony J. S.; Hutson, Rory; Lan, Dongzhao; Silva, João D. Lencart e.; Pascoe, Philip; Telfer, Trevor; Zhang, Xuelei; Zhu, Mingyuan

2010-03-01

This paper presents a multilayered ecosystem modelling approach that combines the simulation of the biogeochemistry of a coastal ecosystem with the simulation of the main forcing functions, such as catchment loading and aquaculture activities. This approach was developed as a tool for sustainable management of coastal ecosystems. A key feature is to simulate management scenarios that account for changes in multiple uses and enable assessment of cumulative impacts of coastal activities. The model was applied to a coastal zone in China with large aquaculture production and multiple catchment uses, and where management efforts to improve water quality are under way. Development scenarios designed in conjunction with local managers and aquaculture producers include the reduction of fish cages and treatment of wastewater. Despite the reduction in nutrient loading simulated in three different scenarios, inorganic nutrient concentrations in the bay were predicted to exceed the thresholds for poor quality defined by Chinese seawater quality legislation. For all scenarios there is still a Moderate High to High nutrient loading from the catchment, so further reductions might be enacted, together with additional decreases in fish cage culture. The model predicts that overall, shellfish production decreases by 10%-28% using any of these development scenarios, principally because shellfish growth is being sustained by the substances to be reduced for improvement of water quality. The model outcomes indicate that this may be counteracted by zoning of shellfish aquaculture at the ecosystem level in order to optimize trade-offs between productivity and environmental effects. The present case study exemplifies the value of multilayered ecosystem modelling as a tool for Integrated Coastal Zone Management and for the adoption of ecosystem approaches for marine resource management. This modelling approach can be applied worldwide, and may be particularly useful for the application of coastal management regulation, for instance in the implementation of the European Marine Strategy Framework Directive.

Response to droughts and heat waves of the productivity of natural and agricultural ecosystems in Europe within ISI-MIP2 historical simulations

NASA Astrophysics Data System (ADS)

François, Louis; Henrot, Alexandra-Jane; Dury, Marie; Jacquemin, Ingrid; Munhoven, Guy; Friend, Andrew; Rademacher, Tim T.; Hacket Pain, Andrew J.; Hickler, Thomas; Tian, Hanqin; Morfopoulos, Catherine; Ostberg, Sebastian; Chang, Jinfeng; Rafique, Rashid; Nishina, Kazuya

2016-04-01

According to the projections of climate models, extreme events such as droughts and heat waves are expected to become more frequent and more severe in the future. Such events are known to severely impact the productivity of both natural and agricultural ecosystems, and hence to affect ecosystem services such as crop yield and ecosystem carbon sequestration potential. Dynamic vegetation models are conventional tools to evaluate the productivity and carbon sequestration of ecosystems and their response to climate change. However, how far are these models able to correctly represent the sensitivity of ecosystems to droughts and heat waves? How do the responses of natural and agricultural ecosystems compare to each other, in terms of drought-induced changes in productivity and carbon sequestration? In this contribution, we use ISI-MIP2 model historical simulations from the biome sector to tentatively answer these questions. Nine dynamic vegetation models have participated in the biome sector intercomparison of ISI-MIP2: CARAIB, DLEM, HYBRID, JULES, LPJ-GUESS, LPJml, ORCHIDEE, VEGAS and VISIT. We focus the analysis on well-marked droughts or heat waves that occured in Europe after 1970, such as the 1976, 2003 and 2010 events. For most recent studied events, the model results are compared to the response observed at several eddy covariance sites in Europe, and, at a larger scale, to the changes in crop productivities reported in national statistics or to the drought impacts on gross primary productivity derived from satellite data (Terra MODIS instrument). The sensitivity of the models to the climatological dataset used in the simulations, as well as to the inclusion or not of anthropogenic land use, is also analysed within the studied events. Indeed, the ISI-MIP simulations have been run with four different historical climatic forcings, as well as for several land use/land cover configurations (natural vegetation, fixed land use and variable land use).

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

USGS Publications Warehouse

Lokupitiya, E.; Denning, A. Scott; Schaefer, K.; Ricciuto, D.; Anderson, R.; Arain, M. A.; Baker, I.; Barr, A. G.; Chen, G.; Chen, J.M.; Ciais, P.; Cook, D.R.; Dietze, M.C.; El Maayar, M.; Fischer, M.; Grant, R.; Hollinger, D.; Izaurralde, C.; Jain, A.; Kucharik, C.J.; Li, Z.; Liu, S.; Li, L.; Matamala, R.; Peylin, P.; Price, D.; Running, S. W.; Sahoo, A.; Sprintsin, M.; Suyker, A.E.; Tian, H.; Tonitto, Christina; Torn, M.S.; Verbeeck, Hans; Verma, S.B.; Xue, Y.

2016-01-01

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fed sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO2 seasonal uptake over agricultural regions.

Carbon and energy fluxes in cropland ecosystems: a model-data comparison

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

Lokupitiya, E.; Denning, A. S.; Schaefer, K.

2016-06-03

Croplands are highly productive ecosystems that contribute to land–atmosphere exchange of carbon, energy, and water during their short growing seasons. We evaluated and compared net ecosystem exchange (NEE), latent heat flux (LE), and sensible heat flux (H) simulated by a suite of ecosystem models at five agricultural eddy covariance flux tower sites in the central United States as part of the North American Carbon Program Site Synthesis project. Most of the models overestimated H and underestimated LE during the growing season, leading to overall higher Bowen ratios compared to the observations. Most models systematically under predicted NEE, especially at rain-fedmore » sites. Certain crop-specific models that were developed considering the high productivity and associated physiological changes in specific crops better predicted the NEE and LE at both rain-fed and irrigated sites. Models with specific parameterization for different crops better simulated the inter-annual variability of NEE for maize-soybean rotation compared to those models with a single generic crop type. Stratification according to basic model formulation and phenological methodology did not explain significant variation in model performance across these sites and crops. The under prediction of NEE and LE and over prediction of H by most of the models suggests that models developed and parameterized for natural ecosystems cannot accurately predict the more robust physiology of highly bred and intensively managed crop ecosystems. When coupled in Earth System Models, it is likely that the excessive physiological stress simulated in many land surface component models leads to overestimation of temperature and atmospheric boundary layer depth, and underestimation of humidity and CO 2 seasonal uptake over agricultural regions.« less

Non-Deterministic Modelling of Food-Web Dynamics

PubMed Central

Planque, Benjamin; Lindstrøm, Ulf; Subbey, Sam

2014-01-01

A novel approach to model food-web dynamics, based on a combination of chance (randomness) and necessity (system constraints), was presented by Mullon et al. in 2009. Based on simulations for the Benguela ecosystem, they concluded that observed patterns of ecosystem variability may simply result from basic structural constraints within which the ecosystem functions. To date, and despite the importance of these conclusions, this work has received little attention. The objective of the present paper is to replicate this original model and evaluate the conclusions that were derived from its simulations. For this purpose, we revisit the equations and input parameters that form the structure of the original model and implement a comparable simulation model. We restate the model principles and provide a detailed account of the model structure, equations, and parameters. Our model can reproduce several ecosystem dynamic patterns: pseudo-cycles, variation and volatility, diet, stock-recruitment relationships, and correlations between species biomass series. The original conclusions are supported to a large extent by the current replication of the model. Model parameterisation and computational aspects remain difficult and these need to be investigated further. Hopefully, the present contribution will make this approach available to a larger research community and will promote the use of non-deterministic-network-dynamics models as ‘null models of food-webs’ as originally advocated. PMID:25299245

Nitrogen controls on ecosystem carbon sequestration: a model implementation and application to Saskatchewan, Canada

USGS Publications Warehouse

Liu, J.; Price, D.T.; Chen, J.M.

2005-01-01

A plant–soil nitrogen (N) cycling model was developed and incorporated into the Integrated BIosphere Simulator (IBIS) of Foley et al. [Foley, J.A., Prentice, I.C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., Haxeltine, A., 1996. An integrated biosphere model of land surface process, terrestrial carbon balance and vegetation dynamics. Global Biogeochem. Cycles 10, 603–628]. In the N-model, soil mineral N regulates ecosystem carbon (C) fluxes and ecosystem C:N ratios. Net primary productivity (NPP) is controlled by feedbacks from both leaf C:N and soil mineral N. Leaf C:N determines the foliar and canopy photosynthesis rates, while soil mineral N determines the N availability for plant growth and the efficiency of biomass construction. Nitrogen controls on the decomposition of soil organic matter (SOM) are implemented through N immobilization and mineralization separately. The model allows greater SOM mineralization at lower mineral N, and conversely, allows greater N immobilization at higher mineral N. The model's seasonal and inter-annual behaviours are demonstrated. A regional simulation for Saskatchewan, Canada, was performed for the period 1851–2000 at a 10 km × 10 km resolution. Simulated NPP was compared with high-resolution (1 km × 1 km) NPP estimated from remote sensing data using the boreal ecosystem productivity simulator (BEPS) [Liu, J., Chen, J.M., Cihlar, J., Park, W.M., 1997. A process-based boreal ecosystem productivity simulator using remote sensing inputs. Remote Sens. Environ. 44, 81–87]. The agreement between IBIS and BEPS, particularly in NPP spatial variation, was considerably improved when the N controls were introduced into IBIS.

Impacts of weather versus climate and driver uncertainty on multi-centennial ecosystem model simulations

NASA Astrophysics Data System (ADS)

Rollinson, C.; Simkins, J.; Fer, I.; Desai, A. R.; Dietze, M.

2017-12-01

Simulations of ecosystem dynamics and comparisons with empirical data require accurate, continuous, and often sub-daily meteorology records that are spatially aligned to the scale of the empirical data. A wealth of meteorology data for the past, present, and future is available through site-specific observations, modern reanalysis products, and gridded GCM simulations. However, these products are mismatched in spatial and temporal resolution, often with both different means and seasonal patterns. We have designed and implemented a two-step meteorological downscaling and ensemble generation method that combines multiple meteorology data products through debiasing and temporal downscaling protocols. Our methodology is designed to preserve the covariance among seven meteorological variables for use as drivers in ecosystem model simulations: temperature, precipitation, short- and longwave radiation, surface pressure, humidity, and wind. Furthermore, our method propagates uncertainty through the downscaling process and results in ensembles of meteorology that can be compared to paleoclimate reconstructions and used to analyze the effects of both high- and low-frequency climate anomalies on ecosystem dynamics. Using a multiple linear regression approach, we have combined hourly, 0.125-degree gridded data from the NLDAS (1980-present) with CRUNCEP (1901-2010) and CMIP5 historical (1850-2005), past millennium (850-1849), and future (1950-2100) GCM simulations. This has resulted in an ensemble of continuous, hourly-resolved meteorology from from the paleo era into the future with variability in weather events as well as low-frequency climatic changes. We investigate the influence of extreme sub-daily weather phenomena versus long-term climatic changes in an ensemble of ecosystem models that range in atmospheric and biological complexity. Through data assimilation with paleoclimate reconstructions of past climate, we can improve data-model comparisons using observations of vegetation change from the past 1200 years. Accounting for driver uncertainty in model evaluation can help determine the relative influence of structural versus parameterization errors in ecosystem modelings.

Improving SWAT for simulating water and carbon fluxes of forest ecosystems

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

Yang, Qichun; Zhang, Xuesong

2016-11-01

As a widely used watershed model for assessing impacts of anthropogenic and natural disturbances on water quantity and quality, the Soil and Water Assessment Tool (SWAT) has not been extensively tested in simulating water and carbon fluxes of forest ecosystems. Here, we examine SWAT simulations of evapotranspiration (ET), net primary productivity (NPP), net ecosystem exchange (NEE), and plant biomass at ten AmeriFlux forest sites across the U.S. We identify unrealistic radiation use efficiency (Bio_E), large leaf to biomass fraction (Bio_LEAF), and missing phosphorus supply from parent material weathering as the primary causes for the inadequate performance of the default SWATmore » model in simulating forest dynamics. By further revising the relevant parameters and processes, SWAT’s performance is substantially improved. Based on the comparison between the improved SWAT simulations and flux tower observations, we discuss future research directions for further enhancing model parameterization and representation of water and carbon cycling for forests.« less

A Proposal for Modeling Real Hardware, Weather and Marine Conditions for Underwater Sensor Networks

PubMed Central

Climent, Salvador; Capella, Juan Vicente; Blanc, Sara; Perles, Angel; Serrano, Juan José

2013-01-01

Network simulators are useful for researching protocol performance, appraising new hardware capabilities and evaluating real application scenarios. However, these tasks can only be achieved when using accurate models and real parameters that enable the extraction of trustworthy results and conclusions. This paper presents an underwater wireless sensor network ecosystem for the ns-3 simulator. This ecosystem is composed of a new energy-harvesting model and a low-cost, low-power underwater wake-up modem model that, alongside existing models, enables the performance of accurate simulations by providing real weather and marine conditions from the location where the real application is to be deployed. PMID:23748171

Application of the Ecosystem Assessment Model to Lake Norman: A cooling lake in North Carolina: Final report

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

Porcella, D.B.; Bowie, G.L.; Campbell, C.L.

The Ecosystem Assessment Model (EAM) of the Cooling Lake Assessment Methodology was applied to the extensive ecological field data collected at Lake Norman, North Carolina by Duke Power Company to evaluate its capability to simulate lake ecosystems and the ecological effects of steam electric power plants. The EAM provided simulations over a five-year verification period that behaved as expected based on a one-year calibration. Major state variables of interest to utilities and regulatory agencies are: temperature, dissolved oxygen, and fish community variables. In qualitative terms, temperature simulation was very accurate, dissolved oxygen simulation was accurate, and fish prediction was reasonablymore » accurate. The need for more accurate fisheries data collected at monthly intervals and non-destructive sampling techniques was identified.« less

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...

Terrestrial ecosystem process model Biome-BGCMuSo v4.0: summary of improvements and new modeling possibilities

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Barcza, Zoltán; Marjanović, Hrvoje; Zorana Ostrogović Sever, Maša; Dobor, Laura; Gelybó, Györgyi; Fodor, Nándor; Pintér, Krisztina; Churkina, Galina; Running, Steven; Thornton, Peter; Bellocchi, Gianni; Haszpra, László; Horváth, Ferenc; Suyker, Andrew; Nagy, Zoltán

2016-12-01

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented). Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance.

The Lagrangian Ensemble metamodel for simulating plankton ecosystems

NASA Astrophysics Data System (ADS)

Woods, J. D.

2005-10-01

This paper presents a detailed account of the Lagrangian Ensemble (LE) metamodel for simulating plankton ecosystems. It uses agent-based modelling to describe the life histories of many thousands of individual plankters. The demography of each plankton population is computed from those life histories. So too is bio-optical and biochemical feedback to the environment. The resulting “virtual ecosystem” is a comprehensive simulation of the plankton ecosystem. It is based on phenotypic equations for individual micro-organisms. LE modelling differs significantly from population-based modelling. The latter uses prognostic equations to compute demography and biofeedback directly. LE modelling diagnoses them from the properties of individual micro-organisms, whose behaviour is computed from prognostic equations. That indirect approach permits the ecosystem to adjust gracefully to changes in exogenous forcing. The paper starts with theory: it defines the Lagrangian Ensemble metamodel and explains how LE code performs a number of computations “behind the curtain”. They include budgeting chemicals, and deriving biofeedback and demography from individuals. The next section describes the practice of LE modelling. It starts with designing a model that complies with the LE metamodel. Then it describes the scenario for exogenous properties that provide the computation with initial and boundary conditions. These procedures differ significantly from those used in population-based modelling. The next section shows how LE modelling is used in research, teaching and planning. The practice depends largely on hindcasting to overcome the limits to predictability of weather forecasting. The scientific method explains observable ecosystem phenomena in terms of finer-grained processes that cannot be observed, but which are controlled by the basic laws of physics, chemistry and biology. What-If? Prediction ( WIP), used for planning, extends hindcasting by adding events that describe natural or man-made hazards and remedial actions. Verification is based on the Ecological Turing Test, which takes account of uncertainties in the observed and simulated versions of a target ecological phenomenon. The rest of the paper is devoted to a case study designed to show what LE modelling offers the biological oceanographer. The case study is presented in two parts. The first documents the WB model (Woods & Barkmann, 1994) and scenario used to simulate the ecosystem in a mesocosm moored in deep water off the Azores. The second part illustrates the emergent properties of that virtual ecosystem. The behaviour and development of an individual plankton lineage are revealed by an audit trail of the agent used in the computation. The fields of environmental properties reveal the impact of biofeedback. The fields of demographic properties show how changes in individuals cumulatively affect the birth and death rates of their population. This case study documents the virtual ecosystem used by Woods, Perilli and Barkmann (2005; hereafter WPB); to investigate the stability of simulations created by the Lagrangian Ensemble metamodel. The Azores virtual ecosystem was created and analysed on the Virtual Ecology Workbench (VEW) which is described briefly in the Appendix.

An eco-hydrological modeling framework for assessing trade-offs among ecosystem services in response to alternative land use scenarios

NASA Astrophysics Data System (ADS)

Mckane, R.; Abdelnour, A. G.; Brookes, A.; Djang, K.; Stieglitz, M.; Pan, F.; Bolte, J.; Papenfus, M.; Burdick, C.

2012-12-01

Scientists, policymakers, community planners and others have discussed ecosystem services for decades, however, society is still in the early stages of developing methodologies to quantify and value the services that ecosystems provide. For example, the U.S. Environmental Protection Agency recently established the Sustainable and Healthy Communities Research Program to develop such methodologies, so that natural capital can be better accounted for in decisions that affect the supply of the ecosystem goods and services upon which human well-being depends. Essential to this goal are highly integrated models that can be used to define policy and management strategies for entire ecosystems, not simply individual components of the ecosystem. We developed the VELMA (Visualizing Ecosystems for Land Management Assessments) eco-hydrologic modeling framework to help address this emerging risk assessment objective. Here we describe a proof-of-concept application of VELMA to the H.J. Andrews Experimental Forest, a forested 64 km2 basin and Long Term Ecological Research site in the western Cascade Range of Oregon, USA. VELMA is a spatially-distributed eco-hydrologic model that links a land surface hydrologic model with a terrestrial biogeochemistry model for simulating the integrated responses of vegetation, soil, and water resources to interacting stressors. We used the model to simulate the effects of three different land use scenarios (100% old-growth, 100% clearcut harvest, and present-day land cover consisting of 45% old-growth and 55% harvested) on trade-offs among five ecosystem services: timber production, carbon sequestration, greenhouse gas regulation, water quantity, and water quality. Compared to the old-growth simulation, over a 60-yr period the clearcut simulation reduced total ecosystem carbon stocks (-40%), and initially increased total stream discharge (+28%), stream nitrogen export (>300%), and total CO2 and N2O radiative forcing (>200%). The simulation for present-day land cover resulted in intermediate values, albeit substantially closer to old growth than to clearcut values. Ongoing work is focused on incorporating VELMA within a flexible decision support platform (Envision) that integrates a wide variety of models, decision tools, and datasets for evaluating economic, social and environmental trade-offs associated with alternative decision scenarios. This framework will be used to address questions about the sustainability of natural capital vital to local and regional economies, initially in the PNW and Great Plains. For example, can those factors that have the greatest potential to improve future trajectories of ecosystem services and human well-being be identified? What green and grey infrastructure improvements, carbon and nitrogen management practices, and growth and development policies can most effectively be managed to attain a sustainable and desirable future?

An integrated approach to modeling changes in land use, land cover, and disturbance and their impact on ecosystem carbon dynamics: a case study in the Sierra Nevada Mountains of California

USGS Publications Warehouse

Sleeter, Benjamin M.; Liu, Jinxun; Daniel, Colin; Frid, Leonardo; Zhu, Zhiliang

2015-01-01

Increased land-use intensity (e.g. clearing of forests for cultivation, urbanization), often results in the loss of ecosystem carbon storage, while changes in productivity resulting from climate change may either help offset or exacerbate losses. However, there are large uncertainties in how land and climate systems will evolve and interact to shape future ecosystem carbon dynamics. To address this we developed the Land Use and Carbon Scenario Simulator (LUCAS) to track changes in land use, land cover, land management, and disturbance, and their impact on ecosystem carbon storage and flux within a scenario-based framework. We have combined a state-and-transition simulation model (STSM) of land change with a stock and flow model of carbon dynamics. Land-change projections downscaled from the Intergovernmental Panel on Climate Change’s (IPCC) Special Report on Emission Scenarios (SRES) were used to drive changes within the STSM, while the Integrated Biosphere Simulator (IBIS) ecosystem model was used to derive input parameters for the carbon stock and flow model. The model was applied to the Sierra Nevada Mountains ecoregion in California, USA, a region prone to large wildfires and a forestry sector projected to intensify over the next century. Three scenario simulations were conducted, including a calibration scenario, a climate-change scenario, and an integrated climate- and land-change scenario. Based on results from the calibration scenario, the LUCAS age-structured carbon accounting model was able to accurately reproduce results obtained from the process-based biogeochemical model. Under the climate-only scenario, the ecoregion was projected to be a reliable net sink of carbon, however, when land use and disturbance were introduced, the ecoregion switched to become a net source. This research demonstrates how an integrated approach to carbon accounting can be used to evaluate various drivers of ecosystem carbon change in a robust, yet transparent modeling environment.

THE AQUATOX MODEL

EPA Science Inventory

This lecture will present AQUATOX, an aquatic ecosystem simulation model developed by Dr. Dick Park and supported by the U.S. EPA. The AQUATOX model predicts the fate of various pollutants, such as nutrients and organic chemicals, and their effects on the ecosystem, including fi...

Simulations of ecosystem hydrological processes using a unified multi-scale model

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

Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin

2015-01-01

This paper presents a unified multi-scale model (UMSM) that we developed to simulate hydrological processes in an ecosystem containing both surface water and groundwater. The UMSM approach modifies the Navier–Stokes equation by adding a Darcy force term to formulate a single set of equations to describe fluid momentum and uses a generalized equation to describe fluid mass balance. The advantage of the approach is that the single set of the equations can describe hydrological processes in both surface water and groundwater where different models are traditionally required to simulate fluid flow. This feature of the UMSM significantly facilitates modelling ofmore » hydrological processes in ecosystems, especially at locations where soil/sediment may be frequently inundated and drained in response to precipitation, regional hydrological and climate changes. In this paper, the UMSM was benchmarked using WASH123D, a model commonly used for simulating coupled surface water and groundwater flow. Disney Wilderness Preserve (DWP) site at the Kissimmee, Florida, where active field monitoring and measurements are ongoing to understand hydrological and biogeochemical processes, was then used as an example to illustrate the UMSM modelling approach. The simulations results demonstrated that the DWP site is subject to the frequent changes in soil saturation, the geometry and volume of surface water bodies, and groundwater and surface water exchange. All the hydrological phenomena in surface water and groundwater components including inundation and draining, river bank flow, groundwater table change, soil saturation, hydrological interactions between groundwater and surface water, and the migration of surface water and groundwater interfaces can be simultaneously simulated using the UMSM. Overall, the UMSM offers a cross-scale approach that is particularly suitable to simulate coupled surface and ground water flow in ecosystems with strong surface water and groundwater interactions.« less

[Simulation of water and carbon fluxes in harvard forest area based on data assimilation method].

PubMed

Zhang, Ting-Long; Sun, Rui; Zhang, Rong-Hua; Zhang, Lei

2013-10-01

Model simulation and in situ observation are the two most important means in studying the water and carbon cycles of terrestrial ecosystems, but have their own advantages and shortcomings. To combine these two means would help to reflect the dynamic changes of ecosystem water and carbon fluxes more accurately. Data assimilation provides an effective way to integrate the model simulation and in situ observation. Based on the observation data from the Harvard Forest Environmental Monitoring Site (EMS), and by using ensemble Kalman Filter algorithm, this paper assimilated the field measured LAI and remote sensing LAI into the Biome-BGC model to simulate the water and carbon fluxes in Harvard forest area. As compared with the original model simulated without data assimilation, the improved Biome-BGC model with the assimilation of the field measured LAI in 1998, 1999, and 2006 increased the coefficient of determination R2 between model simulation and flux observation for the net ecosystem exchange (NEE) and evapotranspiration by 8.4% and 10.6%, decreased the sum of absolute error (SAE) and root mean square error (RMSE) of NEE by 17.7% and 21.2%, and decreased the SAE and RMSE of the evapotranspiration by 26. 8% and 28.3%, respectively. After assimilated the MODIS LAI products of 2000-2004 into the improved Biome-BGC model, the R2 between simulated and observed results of NEE and evapotranspiration was increased by 7.8% and 4.7%, the SAE and RMSE of NEE were decreased by 21.9% and 26.3%, and the SAE and RMSE of evapotranspiration were decreased by 24.5% and 25.5%, respectively. It was suggested that the simulation accuracy of ecosystem water and carbon fluxes could be effectively improved if the field measured LAI or remote sensing LAI was integrated into the model.

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.

An analytical framework to assist decision makers in the use of forest ecosystem model predictions

USDA-ARS?s Scientific Manuscript database

The predictions of most terrestrial ecosystem models originate from deterministic simulations. Relatively few uncertainty evaluation exercises in model outputs are performed by either model developers or users. This issue has important consequences for decision makers who rely on models to develop n...

Alternative ways of using field-based estimates to calibrate ecosystem models and their implications for ecosystem carbon cycle studies

Treesearch

Y. He; Q. Zhuang; A.D. McGuire; Y. Liu; M. Chen

2013-01-01

Model-data fusion is a process in which field observations are used to constrain model parameters. How observations are used to constrain parameters has a direct impact on the carbon cycle dynamics simulated by ecosystem models. In this study, we present an evaluation of several options for the use of observations inmodeling regional carbon dynamics and explore the...

NON-SPATIAL CALIBRATIONS OF A GENERAL UNIT MODEL FOR ECOSYSTEM SIMULATIONS. (R825792)

EPA Science Inventory

General Unit Models simulate system interactions aggregated within one spatial unit of resolution. For unit models to be applicable to spatial computer simulations, they must be formulated generally enough to simulate all habitat elements within the landscape. We present the d...

NON-SPATIAL CALIBRATIONS OF A GENERAL UNIT MODEL FOR ECOSYSTEM SIMULATIONS. (R827169)

EPA Science Inventory

General Unit Models simulate system interactions aggregated within one spatial unit of resolution. For unit models to be applicable to spatial computer simulations, they must be formulated generally enough to simulate all habitat elements within the landscape. We present the d...

Mechanisms controlling primary and new production in a global ecosystem model - Part I: Validation of the biological simulation

NASA Astrophysics Data System (ADS)

Popova, E. E.; Coward, A. C.; Nurser, G. A.; de Cuevas, B.; Fasham, M. J. R.; Anderson, T. R.

2006-12-01

A global general circulation model coupled to a simple six-compartment ecosystem model is used to study the extent to which global variability in primary and export production can be realistically predicted on the basis of advanced parameterizations of upper mixed layer physics, without recourse to introducing extra complexity in model biology. The "K profile parameterization" (KPP) scheme employed, combined with 6-hourly external forcing, is able to capture short-term periodic and episodic events such as diurnal cycling and storm-induced deepening. The model realistically reproduces various features of global ecosystem dynamics that have been problematic in previous global modelling studies, using a single generic parameter set. The realistic simulation of deep convection in the North Atlantic, and lack of it in the North Pacific and Southern Oceans, leads to good predictions of chlorophyll and primary production in these contrasting areas. Realistic levels of primary production are predicted in the oligotrophic gyres due to high frequency external forcing of the upper mixed layer (accompanying paper Popova et al., 2006) and novel parameterizations of zooplankton excretion. Good agreement is shown between model and observations at various JGOFS time series sites: BATS, KERFIX, Papa and HOT. One exception is the northern North Atlantic where lower grazing rates are needed, perhaps related to the dominance of mesozooplankton there. The model is therefore not globally robust in the sense that additional parameterizations are needed to realistically simulate ecosystem dynamics in the North Atlantic. Nevertheless, the work emphasises the need to pay particular attention to the parameterization of mixed layer physics in global ocean ecosystem modelling as a prerequisite to increasing the complexity of ecosystem models.

A first-order analysis of the potential role of CO2 fertilization to affect the global carbon budget: A comparison of four terrestrial biosphere models

USGS Publications Warehouse

Kicklighter, D.W.; Bruno, M.; Donges, S.; Esser, G.; Heimann, Martin; Helfrich, J.; Ift, F.; Joos, F.; Kaduk, J.; Kohlmaier, G.H.; McGuire, A.D.; Melillo, J.M.; Meyer, R.; Moore, B.; Nadler, A.; Prentice, I.C.; Sauf, W.; Schloss, A.L.; Sitch, S.; Wittenberg, U.; Wurth, G.

1999-01-01

We compared the simulated responses of net primary production, heterotrophic respiration, net ecosystem production and carbon storage in natural terrestrial ecosystems to historical (1765 to 1990) and projected (1990 to 2300) changes of atmospheric CO2 concentration of four terrestrial biosphere models: the Bern model, the Frankfurt Biosphere Model (FBM), the High-Resolution Biosphere Model (HRBM) and the Terrestrial Ecosystem Model (TEM). The results of the model intercomparison suggest that CO2 fertilization of natural terrestrial vegetation has the potential to account for a large fraction of the so-called 'missing carbon sink' of 2.0 Pg C in 1990. Estimates of this potential are reduced when the models incorporate the concept that CO2 fertilization can be limited by nutrient availability. Although the model estimates differ on the potential size (126 to 461 Pg C) of the future terrestrial sink caused by CO2 fertilization, the results of the four models suggest that natural terrestrial ecosystems will have a limited capacity to act as a sink of atmospheric CO2 in the future as a result of physiological constraints and nutrient constraints on NPP. All the spatially explicit models estimate a carbon sink in both tropical and northern temperate regions, but the strength of these sinks varies over time. Differences in the simulated response of terrestrial ecosystems to CO2 fertilization among the models in this intercomparison study reflect the fact that the models have highlighted different aspects of the effect of CO2 fertilization on carbon dynamics of natural terrestrial ecosystems including feedback mechanisms. As interactions with nitrogen fertilization, climate change and forest regrowth may play an important role in simulating the response of terrestrial ecosystems to CO2 fertilization, these factors should be included in future analyses. Improvements in spatially explicit data sets, whole-ecosystems experiments and the availability of net carbon exchange measurements across the globe will also help to improve future evaluations of the role of CO2 fertilization on terrestrial carbon storage.

Structural development and web service based sensitivity analysis of the Biome-BGC MuSo model

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Balogh, János; Churkina, Galina; Haszpra, László; Horváth, Ferenc; Ittzés, Péter; Ittzés, Dóra; Ma, Shaoxiu; Nagy, Zoltán; Pintér, Krisztina; Barcza, Zoltán

2014-05-01

Studying the greenhouse gas exchange, mainly the carbon dioxide sink and source character of ecosystems is still a highly relevant research topic in biogeochemistry. During the past few years research focused on managed ecosystems, because human intervention has an important role in the formation of the land surface through agricultural management, land use change, and other practices. In spite of considerable developments current biogeochemical models still have uncertainties to adequately quantify greenhouse gas exchange processes of managed ecosystem. Therefore, it is an important task to develop and test process-based biogeochemical models. Biome-BGC is a widely used, popular biogeochemical model that simulates the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems. Biome-BGC was originally developed by the Numerical Terradynamic Simulation Group (NTSG) of University of Montana (http://www.ntsg.umt.edu/project/biome-bgc), and several other researchers used and modified it in the past. Our research group developed Biome-BGC version 4.1.1 to improve essentially the ability of the model to simulate carbon and water cycle in real managed ecosystems. The modifications included structural improvements of the model (e.g., implementation of multilayer soil module and drought related plant senescence; improved model phenology). Beside these improvements management modules and annually varying options were introduced and implemented (simulate mowing, grazing, planting, harvest, ploughing, application of fertilizers, forest thinning). Dynamic (annually varying) whole plant mortality was also enabled in the model to support more realistic simulation of forest stand development and natural disturbances. In the most recent model version separate pools have been defined for fruit. The model version which contains every former and new development is referred as Biome-BGC MuSo (Biome-BGC with multi-soil layer). Within the frame of the BioVeL project (http://www.biovel.eu) an open source and domain independent scientific workflow management system (http://www.taverna.org.uk) are used to support 'in silico' experimentation and easy applicability of different models including Biome-BGC MuSo. Workflows can be built upon functionally linked sets of web services like retrieval of meteorological dataset and other parameters; preparation of single run or spatial run model simulation; desk top grid technology based Monte Carlo experiment with parallel processing; model sensitivity analysis, etc. The newly developed, Monte Carlo experiment based sensitivity analysis is described in this study and results are presented about differences in the sensitivity of the original and the developed Biome-BGC model.

DayCent-Chem Simulations of Ecological and Biogeochemical Processes of Eight Mountain Ecosystems in the United States

USGS Publications Warehouse

Hartman, Melannie D.; Baron, Jill S.; Clow, David W.; Creed, Irena F.; Driscoll, Charles T.; Ewing, Holly A.; Haines, Bruce D.; Knoepp, Jennifer; Lajtha, Kate; Ojima, Dennis S.; Parton, William J.; Renfro, Jim; Robinson, R. Bruce; Van Miegroet, Helga; Weathers, Kathleen C.; Williams, Mark W.

2009-01-01

Atmospheric deposition of nitrogen (N) and sulfur (S) cause complex responses in ecosystems, from fertilization to forest ecosystem decline, freshwater eutrophication to acidification, loss of soil base cations, and alterations of disturbance regimes. DayCent-Chem, an ecosystem simulation model that combines ecosystem nutrient cycling and plant dynamics with aqueous geochemical equilibrium calculations, was developed to address ecosystem responses to combined atmospheric N and S deposition. It is unique among geochemically-based models in its dynamic biological cycling of N and its daily timestep for investigating ecosystem and surface water chemical response to episodic events. The model was applied to eight mountainous watersheds in the United States. The sites represent a gradient of N deposition across locales, from relatively pristine to N-saturated, and a variety of ecosystem types and climates. Overall, the model performed best in predicting stream chemistry for snowmelt-dominated sites. It was more difficult to predict daily stream chemistry for watersheds with deep soils, high amounts of atmospheric deposition, and a large degree of spatial heterogeneity. DayCent-Chem did well in representing plant and soil carbon and nitrogen pools and fluxes. Modeled stream nitrate (NO3-) and ammonium (NH4+) concentrations compared well with measurements at all sites, with few exceptions. Simulated daily stream sulfate (SO42-) concentrations compared well to measured values for sites where SO42- deposition has been low and where SO42- adsorption/desorption reactions did not seem to be important. The concentrations of base cations and silica in streams are highly dependent on the geochemistry and weathering rates of minerals in each catchment, yet these were rarely, if ever, known. Thus, DayCent-Chem could not accurately predict weathering products for some catchments. Additionally, few data were available for exchangeable soil cations or the magnitude of base cation deposition as a result of dry and fog inputs. The uncertainties related to weathering reactions, deposition, soil cation exchange capacity, and groundwater contributions influenced how well the simulated acid neutralizing capacity (ANC) and pH estimates compared to observed values. Daily discharge was well represented by the model for most sites. The chapters of this report describe the parameterization for each site and summarize model results for ecosystem variables, stream discharge, and stream chemistry. This intersite comparison exercise provided insight about important and possibly not well understood processes.

Integrating remotely sensed land cover observations and a biogeochemical model for estimating forest ecosystem carbon dynamics

USGS Publications Warehouse

Liu, J.; Liu, S.; Loveland, Thomas R.; Tieszen, L.L.

2008-01-01

Land cover change is one of the key driving forces for ecosystem carbon (C) dynamics. We present an approach for using sequential remotely sensed land cover observations and a biogeochemical model to estimate contemporary and future ecosystem carbon trends. We applied the General Ensemble Biogeochemical Modelling System (GEMS) for the Laurentian Plains and Hills ecoregion in the northeastern United States for the period of 1975-2025. The land cover changes, especially forest stand-replacing events, were detected on 30 randomly located 10-km by 10-km sample blocks, and were assimilated by GEMS for biogeochemical simulations. In GEMS, each unique combination of major controlling variables (including land cover change history) forms a geo-referenced simulation unit. For a forest simulation unit, a Monte Carlo process is used to determine forest type, forest age, forest biomass, and soil C, based on the Forest Inventory and Analysis (FIA) data and the U.S. General Soil Map (STATSGO) data. Ensemble simulations are performed for each simulation unit to incorporate input data uncertainty. Results show that on average forests of the Laurentian Plains and Hills ecoregion have been sequestrating 4.2 Tg C (1 teragram = 1012 gram) per year, including 1.9 Tg C removed from the ecosystem as the consequences of land cover change. ?? 2008 Elsevier B.V.

Integrating peatlands into the coupled Canadian Land Surface Scheme (CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0

NASA Astrophysics Data System (ADS)

Wu, Yuanqiao; Verseghy, Diana L.; Melton, Joe R.

2016-08-01

Peatlands, which contain large carbon stocks that must be accounted for in the global carbon budget, are poorly represented in many earth system models. We integrated peatlands into the coupled Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM), which together simulate the fluxes of water, energy, and CO2 at the land surface-atmosphere boundary in the family of Canadian Earth system models (CanESMs). New components and algorithms were added to represent the unique features of peatlands, such as their characteristic ground floor vegetation (mosses), the slow decomposition of carbon in the water-logged soils and the interaction between the water, energy, and carbon cycles. This paper presents the modifications introduced into the CLASS-CTEM modelling framework together with site-level evaluations of the model performance for simulated water, energy and carbon fluxes at eight different peatland sites. The simulated daily gross primary production (GPP) and ecosystem respiration are well correlated with observations, with values of the Pearson correlation coefficient higher than 0.8 and 0.75 respectively. The simulated mean annual net ecosystem production at the eight test sites is 87 g C m-2 yr-1, which is 22 g C m-2 yr-1 higher than the observed annual mean. The general peatland model compares well with other site-level and regional-level models for peatlands, and is able to represent bogs and fens under a range of climatic and geographical conditions.

Integrating peatlands into the coupled Canadian Land Surface Scheme (CLASS) v3.6 and the Canadian Terrestrial Ecosystem Model (CTEM) v2.0

NASA Astrophysics Data System (ADS)

Wu, Y.; Verseghy, D. L.; Melton, J. R.

2015-11-01

Peatlands, which contain large carbon stocks that must be accounted for in the global carbon budget, are poorly represented in many earth system models. We integrated peatlands into the coupled Canadian Land Surface Scheme (CLASS) and the Canadian Terrestrial Ecosystem Model (CTEM), which together simulate the fluxes of water, energy and CO2 at the land surface-atmosphere boundary in the family of Canadian Earth System Models (CanESMs). New components and algorithms were added to represent the unique features of peatlands, such as their characteristic ground floor vegetation (mosses), the slow decomposition of carbon in the water-logged soils and the interaction between the water, energy and carbon cycles. This paper presents the modifications introduced into the CLASS-CTEM modelling framework together with site-level evaluations of the model performance for simulated water, energy and carbon fluxes at eight different peatland sites. The simulated daily gross primary production and ecosystem respiration are well correlated with observations, with values of the Pearson correlation coefficient higher than 0.8 and 0.75 respectively. The simulated mean annual net ecosystem production at the eight test sites is 87 g C m-2 yr-1, which is 22 g C m-2 yr-1 higher than the observed annual mean. The general peatland model compares well with other site-level and regional-level models for peatlands, and is able to represent bogs and fens under a range of climatic and geographical conditions.

An ecosystem model for tropical forest disturbance and selective logging

Treesearch

Maoyi Huang; Gregory P. Asner; Michael Keller; Joseph A. Berry

2008-01-01

[1] A new three-dimensional version of the Carnegie-Ames-Stanford Approach (CASA) ecosystem model (CASA-3D) was developed to simulate regional carbon cycling in tropical forest ecosystems after disturbances such as logging. CASA-3D has the following new features: (1) an alternative approach for calculating absorbed photosynthetically active radiation (APAR) using new...

A Simulation Model for Studying Effects of Pollution and Freshwater Inflow on Secondary Productivity in an Ecosystem. Ph.D. Thesis - North Carolina State Univ.

NASA Technical Reports Server (NTRS)

Johnson, R. W.

1974-01-01

A mathematical model of an ecosystem is developed. Secondary productivity is evaluated in terms of man related and controllable factors. Information from an existing physical parameters model is used as well as pertinent biological measurements. Predictive information of value to estuarine management is presented. Biological, chemical, and physical parameters measured in order to develop models of ecosystems are identified.

Comparing simulated carbon budget of a Lei bamboo forest with flux tower data

USGS Publications Warehouse

Li, Xuehe; Jiang, Hong; Liu, Jinxun; Sun, Cheng; Wang, Ying; Jin, Jiaxin

2014-01-01

Bamboo forest ecosystem is the part of the forest ecosystem. The distribution area of bamboo forest is limited, but in somewhere, like south China, it has been cultivate for a long time with human management. As the climate change has been take great effect on forest carbon budget, many researchers pay attention to the carbon budget in bamboo forest. Moreover cultivative management had a significant impact on the bamboo forest carbon budget. In this study, we modified a terrestrial ecosystem model named Integrated Biosphere Simulator (IBIS) according the management of Lei bamboo forest. Some management, like fertilization, shoots harvesting and organic mulching in winter, had been incorporated into model. Then we had compared model results with the observation data from a Lei bamboo flux tower. The simulated and observed results had achieved good consistency. Our simulated Lei bamboo forest yearly net ecosystem productivity (NEP) was 0.41 kgC a-1 of carbon, which is very close to the observation data 0.45 kgC a-1 of carbon. And the monthly simulated results can take the change of carbon budget in each month, similar to the data we got from flux tower. It reflects that the modified IBIS model can characterize the growth of bamboo forest and perform the simulation well. And then two groups of simulations were set to evaluate effects of cultivative managements on Lei bamboo forests carbon budget. And results showed that both fertilization and organic mulching had taken positive effects on Lei bamboo forests carbon sequestration.

THE DOWNSLOPE PROPAGATION OF A DISTURBANCE IN A FORESTED CATCHMENT: AN ECO-HYDROLOGIC SIMULATION STUDY

EPA Science Inventory

We developed and applied a spatially-explicit, eco-hydrologic model to examine how a landscape disturbance affects hydrologic processes, ecosystem cycling of C and N, and ecosystem structure. We simulated how the pattern and magnitude of tree removal in a catchment influences fo...

Simulated response of conterminous United States ecosystems to climate change at different levels of fire suppression, CO2 emission rate, and growth response to CO2

Treesearch

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

2008-01-01

A modeling experiment was designed to investigate the impact of fire management, CO2 emission rate, and the growth response to CO2 on the response of ecosystems in the conterminous United States to climate scenarios produced by three different general circulation models (GCMs) as simulated by the MCl Dynamic General...

A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

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

Thornton, Peter E; Wang, Weile; Law, Beverly E.

2009-01-01

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically supportmore » the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.« less

[Simulating of carbon fluxes in bamboo forest ecosystem using BEPS model based on the LAI assimilated with Dual Ensemble Kalman Filter].

PubMed

Li, Xue Jian; Mao, Fang Jie; Du, Hua Qiang; Zhou, Guo Mo; Xu, Xiao Jun; Li, Ping Heng; Liu, Yu Li; Cui, Lu

2016-12-01

LAI is one of the most important observation data in the research of carbon cycle of forest ecosystem, and it is also an important parameter to drive process-based ecosystem model. The Moso bamboo forest (MBF) and Lei bamboo forest (LBF) were selected as the study targets. Firstly, the MODIS LAI time series data during 2014-2015 was assimilated with Dual Ensemble Kalman Filter method. Secondly, the high quality assimilated MBF LAI and LBF LAI were used as input dataset to drive BEPS model for simulating the gross primary productivity (GPP), net ecosystem exchange (NEE) and total ecosystem respiration (TER) of the two types of bamboo forest ecosystem, respectively. The modeled carbon fluxes were evaluated by the observed carbon fluxes data, and the effects of different quality LAI inputs on carbon cycle simulation were also studied. The LAI assimilated using Dual Ensemble Kalman Filter of MBF and LBF were significantly correlated with the observed LAI, with high R 2 of 0.81 and 0.91 respectively, and lower RMSE and absolute bias, which represented the great improvement of the accuracy of MODIS LAI products. With the driving of assimilated LAI, the modeled GPP, NEE, and TER were also highly correlated with the flux observation data, with the R 2 of 0.66, 0.47, and 0.64 for MBF, respectively, and 0.66, 0.45, and 0.73 for LBF, respectively. The accuracy of carbon fluxes modeled with assimilated LAI was higher than that acquired by the locally adjusted cubic-spline capping method, in which, the accuracy of mo-deled NEE for MBF and LBF increased by 11.2% and 11.8% at the most degrees, respectively.

Global sensitivity analysis of DRAINMOD-FOREST, an integrated forest ecosystem model

Treesearch

Shiying Tian; Mohamed A. Youssef; Devendra M. Amatya; Eric D. Vance

2014-01-01

Global sensitivity analysis is a useful tool to understand process-based ecosystem models by identifying key parameters and processes controlling model predictions. This study reported a comprehensive global sensitivity analysis for DRAINMOD-FOREST, an integrated model for simulating water, carbon (C), and nitrogen (N) cycles and plant growth in lowland forests. The...

Nitrous oxide emissions from cropland: A procedure for calibrating the DayCent biogeochemical model using inverse modelling

USDA-ARS?s Scientific Manuscript database

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon (SOC) and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameter...

Landscape modeling for Everglades ecosystem restoration

USGS Publications Warehouse

DeAngelis, D.L.; Gross, L.J.; Huston, M.A.; Wolff, W.F.; Fleming, D.M.; Comiskey, E.J.; Sylvester, S.M.

1998-01-01

A major environmental restoration effort is under way that will affect the Everglades and its neighboring ecosystems in southern Florida. Ecosystem and population-level modeling is being used to help in the planning and evaluation of this restoration. The specific objective of one of these modeling approaches, the Across Trophic Level System Simulation (ATLSS), is to predict the responses of a suite of higher trophic level species to several proposed alterations in Everglades hydrology. These include several species of wading birds, the snail kite, Cape Sable seaside sparrow, Florida panther, white-tailed deer, American alligator, and American crocodile. ATLSS is an ecosystem landscape-modeling approach and uses Geographic Information System (GIS) vegetation data and existing hydrology models for South Florida to provide the basic landscape for these species. A method of pseudotopography provides estimates of water depths through time at 28 ?? 28-m resolution across the landscape of southern Florida. Hydrologic model output drives models of habitat and prey availability for the higher trophic level species. Spatially explicit, individual-based computer models simulate these species. ATLSS simulations can compare the landscape dynamic spatial pattern of the species resulting from different proposed water management strategies. Here we compare the predicted effects of one possible change in water management in South Florida with the base case of no change. Preliminary model results predict substantial differences between these alternatives in some biotic spatial patterns. ?? 1998 Springer-Verlag.

Simulated grazing responses on the proposed prairies National Park

NASA Astrophysics Data System (ADS)

Parton, William J.; Wright, R. Gerald; Risser, Paul G.

1980-03-01

The tallgrass prairie version of the ELM Grassland Model was used to evaluate the potential impact of establishing a tallgrass prairie National Park in the Flint Hills region of Kansas. This total ecosystem model simulates ( a) the flow of water, heat, nitrogen, and phosphorus through the ecosystem and( b) the biomass dynamics of plants and consumers. It was specifically developed to study the effects of levels and types of herbivory, climatic variation, and fertilization upon grassland ecosystems. The model was used to simulate the impact of building up herds of bison, elk, antelope, and wolves on a tallgrass prairie. The results show that the grazing levels in the park should not be decreased below the prepark grazing levels (moderate grazing with cattle) and that the final grazing levels in the park could be maintained at a slightly higher level than the prepark grazing levels.

Flux frequency analysis of seasonally dry ecosystem fluxes in two unique biomes of Sonora Mexico

NASA Astrophysics Data System (ADS)

Verduzco, V. S.; Yepez, E. A.; Robles-Morua, A.; Garatuza, J.; Rodriguez, J. C.; Watts, C.

2013-05-01

Complex dynamics from the interactions of ecosystems processes makes difficult to model the behavior of ecosystems fluxes of carbon and water in response to the variation of environmental and biological drivers. Although process oriented ecosystem models are critical tools for studying land-atmosphere fluxes, its validity depends on the appropriate parameterization of equations describing temporal and spatial changes of model state variables and their interactions. This constraint often leads to discrepancies between model simulations and observed data that reduce models reliability especially in arid and semiarid ecosystems. In the semiarid north western Mexico, ecosystem processes are fundamentally controlled by the seasonality of water and the intermittence of rain pulses which are conditions that require calibration of specific fitting functions to describe the response of ecosystem variables (i.e. NEE, GPP, ET, respiration) to these wetting and drying periods. The goal is to find functions that describe the magnitude of ecosystem fluxes during individual rain pulses and the seasonality of the ecosystem. Relaying on five years of eddy covariance flux data of a tropical dry forest and a subtropical shrubland we present a flux frequency analysis that describe the variation of net ecosystem exchange (NEE) of CO2 to highlight the relevance of pulse driven dynamics controlling this flux. Preliminary results of flux frequency analysis of NEE indicate that these ecosystems are strongly controlled by the frequency distribution of rain. Also, the output of fitting functions for NEE, GPP, ET and respiration using semi-empirical functions applied at specific rain pulses compared with season-long statistically generated simulations do not agree. Seasonality and the intrinsic nature of individual pulses have different effects on ecosystem flux responses. This suggests that relationships between the nature of seasonality and individual pulses can help improve the parameterization of process oriented ecosystem models.

Lake Michigan offshore ecosystem structure and food web changes from 1987 to 2008

USGS Publications Warehouse

Rogers, Mark W.; Bunnell, David B.; Madenjian, Charles P.; Warner, David M.

2014-01-01

Ecosystems undergo dynamic changes owing to species invasions, fisheries management decisions, landscape modifications, and nutrient inputs. At Lake Michigan, new invaders (e.g., dreissenid mussels (Dreissena spp.), spiny water flea (Bythotrephes longimanus), round goby (Neogobius melanostomus)) have proliferated and altered energy transfer pathways, while nutrient concentrations and stocking rates to support fisheries have changed. We developed an ecosystem model to describe food web structure in 1987 and ran simulations through 2008 to evaluate changes in biomass of functional groups, predator consumption, and effects of recently invading species. Keystone functional groups from 1987 were identified as Mysis, burbot (Lota lota), phytoplankton, alewife (Alosa pseudoharengus), nonpredatory cladocerans, and Chinook salmon (Oncorhynchus tshawytscha). Simulations predicted biomass reductions across all trophic levels and predicted biomasses fit observed trends for most functional groups. The effects of invasive species (e.g., dreissenid grazing) increased across simulation years, but were difficult to disentangle from other changes (e.g., declining offshore nutrient concentrations). In total, our model effectively represented recent changes to the Lake Michigan ecosystem and provides an ecosystem-based tool for exploring future resource management scenarios.

δ15N constraints on long-term nitrogen balances in temperate forests

USGS Publications Warehouse

Perakis, S.S.; Sinkhorn, E.R.; Compton, J.E.

2011-01-01

Biogeochemical theory emphasizes nitrogen (N) limitation and the many factors that can restrict N accumulation in temperate forests, yet lacks a working model of conditions that can promote naturally high N accumulation. We used a dynamic simulation model of ecosystem N and δ15N to evaluate which combination of N input and loss pathways could produce a range of high ecosystem N contents characteristic of forests in the Oregon Coast Range. Total ecosystem N at nine study sites ranged from 8,788 to 22,667 kg ha−1 and carbon (C) ranged from 188 to 460 Mg ha−1, with highest values near the coast. Ecosystem δ15N displayed a curvilinear relationship with ecosystem N content, and largely reflected mineral soil, which accounted for 96–98% of total ecosystem N. Model simulations of ecosystem N balances parameterized with field rates of N leaching required long-term average N inputs that exceed atmospheric deposition and asymbiotic and epiphytic N2-fixation, and that were consistent with cycles of post-fire N2-fixation by early-successional red alder. Soil water δ15NO3 − patterns suggested a shift in relative N losses from denitrification to nitrate leaching as N accumulated, and simulations identified nitrate leaching as the primary N loss pathway that constrains maximum N accumulation. Whereas current theory emphasizes constraints on biological N2-fixation and disturbance-mediated N losses as factors that limit N accumulation in temperate forests, our results suggest that wildfire can foster substantial long-term N accumulation in ecosystems that are colonized by symbiotic N2-fixing vegetation.

A framework for simulating map error in ecosystem models

Treesearch

Sean P. Healey; Shawn P. Urbanski; Paul L. Patterson; Chris Garrard

2014-01-01

The temporal depth and spatial breadth of observations from platforms such as Landsat provide unique perspective on ecosystem dynamics, but the integration of these observations into formal decision support will rely upon improved uncertainty accounting. Monte Carlo (MC) simulations offer a practical, empirical method of accounting for potential map errors in broader...

Testing the sensitivity of terrestrial carbon models using remotely sensed biomass estimates

NASA Astrophysics Data System (ADS)

Hashimoto, H.; Saatchi, S. S.; Meyer, V.; Milesi, C.; Wang, W.; Ganguly, S.; Zhang, G.; Nemani, R. R.

2010-12-01

There is a large uncertainty in carbon allocation and biomass accumulation in forest ecosystems. With the recent availability of remotely sensed biomass estimates, we now can test some of the hypotheses commonly implemented in various ecosystem models. We used biomass estimates derived by integrating MODIS, GLAS and PALSAR data to verify above-ground biomass estimates simulated by a number of ecosystem models (CASA, BIOME-BGC, BEAMS, LPJ). This study extends the hierarchical framework (Wang et al., 2010) for diagnosing ecosystem models by incorporating independent estimates of biomass for testing and calibrating respiration, carbon allocation, turn-over algorithms or parameters.

Simulating effects of fire on northern Rocky Mountain landscapes with the ecological process model FIRE-BGC.

PubMed

Keane, R E; Ryan, K C; Running, S W

1996-03-01

A mechanistic, biogeochemical succession model, FIRE-BGC, was used to investigate the role of fire on long-term landscape dynamics in northern Rocky Mountain coniferous forests of Glacier National Park, Montana, USA. FIRE-BGC is an individual-tree model-created by merging the gap-phase process-based model FIRESUM with the mechanistic ecosystem biogeochemical model FOREST-BGC-that has mixed spatial and temporal resolution in its simulation architecture. Ecological processes that act at a landscape level, such as fire and seed dispersal, are simulated annually from stand and topographic information. Stand-level processes, such as tree establishment, growth and mortality, organic matter accumulation and decomposition, and undergrowth plant dynamics are simulated both daily and annually. Tree growth is mechanistically modeled based on the ecosystem process approach of FOREST-BGC where carbon is fixed daily by forest canopy photosynthesis at the stand level. Carbon allocated to the tree stem at the end of the year generates the corresponding diameter and height growth. The model also explicitly simulates fire behavior and effects on landscape characteristics. We simulated the effects of fire on ecosystem characteristics of net primary productivity, evapotranspiration, standing crop biomass, nitrogen cycling and leaf area index over 200 years for the 50,000-ha McDonald Drainage in Glacier National Park. Results show increases in net primary productivity and available nitrogen when fires are included in the simulation. Standing crop biomass and evapotranspiration decrease under a fire regime. Shade-intolerant species dominate the landscape when fires are excluded. Model tree increment predictions compared well with field data.

Ecosystem function in complex mountain terrain: Combining models and long-term observations to advance process-based understanding

NASA Astrophysics Data System (ADS)

Wieder, William R.; Knowles, John F.; Blanken, Peter D.; Swenson, Sean C.; Suding, Katharine N.

2017-04-01

Abiotic factors structure plant community composition and ecosystem function across many different spatial scales. Often, such variation is considered at regional or global scales, but here we ask whether ecosystem-scale simulations can be used to better understand landscape-level variation that might be particularly important in complex terrain, such as high-elevation mountains. We performed ecosystem-scale simulations by using the Community Land Model (CLM) version 4.5 to better understand how the increased length of growing seasons may impact carbon, water, and energy fluxes in an alpine tundra landscape. The model was forced with meteorological data and validated with observations from the Niwot Ridge Long Term Ecological Research Program site. Our results demonstrate that CLM is capable of reproducing the observed carbon, water, and energy fluxes for discrete vegetation patches across this heterogeneous ecosystem. We subsequently accelerated snowmelt and increased spring and summer air temperatures in order to simulate potential effects of climate change in this region. We found that vegetation communities that were characterized by different snow accumulation dynamics showed divergent biogeochemical responses to a longer growing season. Contrary to expectations, wet meadow ecosystems showed the strongest decreases in plant productivity under extended summer scenarios because of disruptions in hydrologic connectivity. These findings illustrate how Earth system models such as CLM can be used to generate testable hypotheses about the shifting nature of energy, water, and nutrient limitations across space and through time in heterogeneous landscapes; these hypotheses may ultimately guide further experimental work and model development.

Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests and its implication for simulated climate sensitivities

NASA Astrophysics Data System (ADS)

Li, Yue; Yang, Hui; Wang, Tao; MacBean, Natasha; Bacour, Cédric; Ciais, Philippe; Zhang, Yiping; Zhou, Guangsheng; Piao, Shilong

2017-08-01

Reducing parameter uncertainty of process-based terrestrial ecosystem models (TEMs) is one of the primary targets for accurately estimating carbon budgets and predicting ecosystem responses to climate change. However, parameters in TEMs are rarely constrained by observations from Chinese forest ecosystems, which are important carbon sink over the northern hemispheric land. In this study, eddy covariance data from six forest sites in China are used to optimize parameters of the ORganizing Carbon and Hydrology In Dynamics EcosystEms TEM. The model-data assimilation through parameter optimization largely reduces the prior model errors and improves the simulated seasonal cycle and summer diurnal cycle of net ecosystem exchange, latent heat fluxes, and gross primary production and ecosystem respiration. Climate change experiments based on the optimized model are deployed to indicate that forest net primary production (NPP) is suppressed in response to warming in the southern China but stimulated in the northeastern China. Altered precipitation has an asymmetric impact on forest NPP at sites in water-limited regions, with the optimization-induced reduction in response of NPP to precipitation decline being as large as 61% at a deciduous broadleaf forest site. We find that seasonal optimization alters forest carbon cycle responses to environmental change, with the parameter optimization consistently reducing the simulated positive response of heterotrophic respiration to warming. Evaluations from independent observations suggest that improving model structure still matters most for long-term carbon stock and its changes, in particular, nutrient- and age-related changes of photosynthetic rates, carbon allocation, and tree mortality.

A model-data comparison of gross primary productivity: Results from the North American Carbon Program site synthesis

Treesearch

Kevin Schaefer; Christopher R. Schwalm; Chris Williams; M. Altaf Arain; Alan Barr; Jing M. Chen; Kenneth J. Davis; Dimitre Dimitrov; Timothy W. Hilton; David Y. Hollinger; Elyn Humphreys; Benjamin Poulter; Brett M. Raczka; Andrew D. Richardson; Alok Sahoo; Peter Thornton; Rodrigo Vargas; Hans Verbeeck; Ryan Anderson; Ian Baker; T. Andrew Black; Paul Bolstad; Jiquan Chen; Peter S. Curtis; Ankur R. Desai; Michael Dietze; Danilo Dragoni; Christopher Gough; Robert F. Grant; Lianhong Gu; Atul Jain; Chris Kucharik; Beverly Law; Shuguang Liu; Erandathie Lokipitiya; Hank A. Margolis; Roser Matamala; J. Harry McCaughey; Russ Monson; J. William Munger; Walter Oechel; Changhui Peng; David T. Price; Dan Ricciuto; William J. Riley; Nigel Roulet; Hanqin Tian; Christina Tonitto; Margaret Torn; Ensheng Weng; Xiaolu Zhou

2012-01-01

Accurately simulating gross primary productivity (GPP) in terrestrial ecosystem models is critical because errors in simulated GPP propagate through the model to introduce additional errors in simulated biomass and other fluxes. We evaluated simulated, daily average GPP from 26 models against estimated GPP at 39 eddy covariance flux tower sites across the United States...

Simulating the response of natural ecosystems and their fire regimes to climatic variability in Alaska.

Treesearch

D. Bachelet; J. Lenihan; R. Neilson; R. Drapek; T. Kittel

2005-01-01

The dynamic global vegetation model MC1 was used to examine climate, fire, and ecosystems interactions in Alaska under historical (1922-1996) and future (1997-2100) climate conditions. Projections show that by the end of the 21st century, 75%-90% of the area simulated as tundra in 1922 is replaced by boreal and temperate forest. From 1922 to 1996, simulation results...

AQUATOX Basic Information

EPA Pesticide Factsheets

AQUATOX is an ecosystem simulation model that predicts the fate of various pollutants, such as excess nutrients and organic chemicals, and their effects on aquatic ecosystems, including fish, invertebrates, and aquatic plants.

APPLYING THE PATUXENT LANDSCAPE UNIT MODEL TO HUMAN DOMINATED ECOSYSTEMS: THE CASE OF AGRICULTURE. (R827169)

EPA Science Inventory

Non-spatial dynamics are core to landscape simulations. Unit models simulate system interactions aggregated within one space unit of resolution used within a spatial model. For unit models to be applicable to spatial simulations they have to be formulated in a general enough w...

Modelling the diurnal and seasonal dynamics of soil CO2 exchange in a semiarid ecosystem with high plant-interspace heterogeneity

NASA Astrophysics Data System (ADS)

Gong, Jinnan; Wang, Ben; Jia, Xin; Feng, Wei; Zha, Tianshan; Kellomäki, Seppo; Peltola, Heli

2018-01-01

We used process-based modelling to investigate the roles of carbon-flux (C-flux) components and plant-interspace heterogeneities in regulating soil CO2 exchanges (FS) in a dryland ecosystem with sparse vegetation. To simulate the diurnal and seasonal dynamics of FS, the modelling considered simultaneously the CO2 production, transport and surface exchanges (e.g. biocrust photosynthesis, respiration and photodegradation). The model was parameterized and validated with multivariate data measured during the years 2013-2014 in a semiarid shrubland ecosystem in Yanchi, northwestern China. The model simulation showed that soil rewetting could enhance CO2 dissolution and delay the emission of CO2 produced from rooting zone. In addition, an ineligible fraction of respired CO2 might be removed from soil volumes under respiration chambers by lateral water flows and root uptakes. During rewetting, the lichen-crusted soil could shift temporally from net CO2 source to sink due to the activated photosynthesis of biocrust but the restricted CO2 emissions from subsoil. The presence of plant cover could decrease the root-zone CO2 production and biocrust C sequestration but increase the temperature sensitivities of these fluxes. On the other hand, the sensitivities of root-zone emissions to water content were lower under canopy, which may be due to the advection of water flows from the interspace to canopy. To conclude, the complexity and plant-interspace heterogeneities of soil C processes should be carefully considered to extrapolate findings from chamber to ecosystem scales and to predict the ecosystem responses to climate change and extreme climatic events. Our model can serve as a useful tool to simulate the soil CO2 efflux dynamics in dryland ecosystems.

A 3-D ecosystem model in the Pacific Ocean and its simulations

NASA Astrophysics Data System (ADS)

Xu, Y.; Ba, Q.

2011-12-01

A simple 3-D ecosystem model with nutrient, phytoplankton, zooplankton and detritus is coupled into the basinwide ocean general circulation (OGCM) of the Pacific Ocean that has been examined by the passive tracer such as tritium. The model was integrated for 500 years under the forcing of climatological monthly mean fields. The model generates similar distribution patterns of ecosystem variables to the estimates based on satellite-derived chlorophyll maps by vertically generalized production model with low water-column NPP values in the subtropical region and high values in the subarctic region and equatorial upwelling region. But the area and strength of oligotrophic gyre is much larger than that indicated in the observations. Compared with the observations, seasonal variations of surface chlorophyll concentrations and top 200-m average zooplankton biomass in the mid-high latitude regions are well simulated in the model. Because of the restoring term near the northern boundary used in the model, a false phytoplankton bloom can occur nearby 50N during winter time. An unrealistic maximum value in the vertical profile of chlorophyll near ocean weather station Papa is generated by our model. In terms of modification of model structure and sensitivity test of the associated parameters, the simulated results can be well improved. Although the division of nutrient into nitrate and ammonium and inclusion of DON in the model can alleviate the low-NPP problem in the subtropical region, modification of the sinking rate and decomposition rate of detritus in the model can be more effective. Introduction of the influence of mixed layer on the ecosystem process and modification of restraint of nutrients near the northern boundary can overcome the shortcomings of simulation of both spring bloom near 50N and vertical profile of chlorophyll at Papa to some extent.

Trait-based Modeling Reveals How Plankton Biodiversity-Ecosystem Function (BEF) Relationships Depend on Environmental Variability

NASA Astrophysics Data System (ADS)

Smith, S. L.; Chen, B.; Vallina, S. M.

2017-12-01

Biodiversity-Ecosystem Function (BEF) relationships, which are most commonly quantified in terms of productivity or total biomass yield, are known to depend on the timescale of the experiment or field study, both for terrestrial plants and phytoplankton, which have each been widely studied as model ecosystems. Although many BEF relationships are positive (i.e., increasing biodiversity enhances function), in some cases there is an optimal intermediate diversity level (i.e., a uni-modal relationship), and in other cases productivity decreases with certain measures of biodiversity. These differences in BEF relationships cannot be reconciled merely by differences in the timescale of experiments. We will present results from simulation experiments applying recently developed trait-based models of phytoplankton communities and ecosystems, using the `adaptive dynamics' framework to represent continuous distributions of size and other key functional traits. Controlled simulation experiments were conducted with different levels of phytoplankton size-diversity, which through trait-size correlations implicitly represents functional-diversity. One recent study applied a theoretical box model for idealized simulations at different frequencies of disturbance. This revealed how the shapes of BEF relationships depend systematically on the frequency of disturbance and associated nutrient supply. We will also present more recent results obtained using a trait-based plankton ecosystem model embedded in a three-dimensional ocean model applied to the North Pacific. This reveals essentially the same pattern in a spatially explicit model with more realistic environmental forcing. In the relatively more variable subarctic, productivity tends to increase with the size (and hence functional) diversity of phytoplankton, whereas productivity tends to decrease slightly with increasing size-diversity in the relatively calm subtropics. Continuous trait-based models can capture essential features of BEF relationships, while requiring far fewer calculations compared to typical plankton diversity models that explicitly simulate a great many idealized species.

Analyzing the ecosystem carbon and hydrologic characteristics of forested wetland using a biogeochemical process model

Treesearch

Jianbo Cui; Changsheng Li; Carl Trettin

2005-01-01

A comprehensive biogeochemical model, Wetland-DNDC, was applied to analyze the carbon and hydrologic characteristics of forested wetland ecosystem at Minnesota (MN) and Florida (FL) sites. The model simulates the flows of carbon, energy, and water in forested wetlands. Modeled carbon dynamics depends on physiological plant factors, the size of plant pools,...

The Regional Healthcare Ecosystem Analyst (RHEA): a simulation modeling tool to assist infectious disease control in a health system.

PubMed

Lee, Bruce Y; Wong, Kim F; Bartsch, Sarah M; Yilmaz, S Levent; Avery, Taliser R; Brown, Shawn T; Song, Yeohan; Singh, Ashima; Kim, Diane S; Huang, Susan S

2013-06-01

As healthcare systems continue to expand and interconnect with each other through patient sharing, administrators, policy makers, infection control specialists, and other decision makers may have to take account of the entire healthcare 'ecosystem' in infection control. We developed a software tool, the Regional Healthcare Ecosystem Analyst (RHEA), that can accept user-inputted data to rapidly create a detailed agent-based simulation model (ABM) of the healthcare ecosystem (ie, all healthcare facilities, their adjoining community, and patient flow among the facilities) of any region to better understand the spread and control of infectious diseases. To demonstrate RHEA's capabilities, we fed extensive data from Orange County, California, USA, into RHEA to create an ABM of a healthcare ecosystem and simulate the spread and control of methicillin-resistant Staphylococcus aureus. Various experiments explored the effects of changing different parameters (eg, degree of transmission, length of stay, and bed capacity). Our model emphasizes how individual healthcare facilities are components of integrated and dynamic networks connected via patient movement and how occurrences in one healthcare facility may affect many other healthcare facilities. A decision maker can utilize RHEA to generate a detailed ABM of any healthcare system of interest, which in turn can serve as a virtual laboratory to test different policies and interventions.

From bottles to stream reaches and networks: Consequences of scale in how we interpret the function of freshwaters in the carbon cycle

NASA Astrophysics Data System (ADS)

Hotchkiss, E. R.

2017-12-01

Freshwater biological processes can alter the quantity and quality of organic carbon (OC) inputs from land before they are transported downstream, but the relative role of hydrologic transport and in-stream processing is still not well quantified at the scale of fluvial networks. Despite much research on the role of biology and hydrology in governing the form and fate of C in inland waters, conclusions about the function of freshwater ecosystems in modifying OC still largely depend on where we draw our ecosystem boundaries, i.e., the spatial scale of measurements used to assess OC transformations. Here I review freshwater OC uptake rates derived from bioassay incubations, synoptic modeling, reach-scale experiments, and ecosystem OC spiraling estimates. Median OC uptake velocities from standard bioassay incubations (0.02 m/d) and synoptic modeling (0.04 m/d) are 1-2 orders of magnitude lower than reach-scale experimental DOC additions and ecosystem OC spiraling estimates (2.2 and 0.27 m/d, respectively) in streams and rivers. Together, ecosystem metabolism and OC fluxes can be used to estimate the distance OC travels before being consumed and respired as CO2 through biological processes (i.e., OC spiraling), allowing for a more mechanistic understanding of the role of ecosystem processes and hydrologic fluxes in modifying downstream OC transport. Beyond the reach scale, data from stream network and stream-lake-river modeling simulations show how we may use linked sampling sites within networks to better understand the integrated sources and fate of OC in freshwaters. We currently underestimate the role of upstream processes in contributing to downstream fluxes: moving from single-ecosystem comparisons to linked-ecosystem simulations increases the contribution of in situ OC processing to CO2 emissions from 30% to >40%. Insights from literature reviews, ecosystem process measurements, and model simulations provide a framework for future considerations of integrated C transport, transformations, and fate when scaling patterns and processes in inland waters.

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

Kremer, R.G.

Three papers are presented that focus on remote sensing and ecosystem simulation modeling of the Intermountain Northwest sagebrush-steppe ecosystem. The first utilizes Advanced Very High Resolution Radiometer data to derive seasonal greenness indices of three pre-dominant vegetation communities in south-central WashingtoN. Temporal signatures were statistically separated, and used to create a classification for the three communities by integrating Normalized Difference Vegetation Indices over the growing season. The classification accuracy was 75% when compared to 53 ground-truthed sites, but was less accurate (62%) in a more topographically variable region. The second paper develops a logic for treating the intermountain sagebrush-steepe asmore » a mosaic of distinct, hydrologically partitioned vegetation communities, and identifies critical ecophysiological considerations for process modeling of arid ecosystems. Soil water and nutrient dynamics of an ecosystem process model were modified to simulate productivity and seasonal water use patterns in Artemisia, Agropyron, and Bromus communities for the same study site. 60 year simulations maintained steady state vegetation productivity while predicting soil moisture content for 65 dates in 1992 with R[sup 2] values ranging from 0.93 to 0.98. In the third paper, the model was used to derive projections of the response of the ecosystem to natural and general circulation model (GCM)-predicted climate variability. Simulations predicted the adaptability of a less productive, invasive grass community (Bromus) to climate change, while a native sagebrush (Artemisia) community does not survive the increased temperatures of the GCM climates. High humidity deficits and greater maintenance respiration costs associated with increased temperatures limit the ability of the sagebrush community to support a relatively high biomass, and substantial increases in soil water storage and subsurface outflow occur was the vegetation senesces.« less

The resilience and functional role of moss in boreal and arctic ecosystems.

PubMed

Turetsky, M R; Bond-Lamberty, B; Euskirchen, E; Talbot, J; Frolking, S; McGuire, A D; Tuittila, E-S

2012-10-01

Mosses in northern ecosystems are ubiquitous components of plant communities, and strongly influence nutrient, carbon and water cycling. We use literature review, synthesis and model simulations to explore the role of mosses in ecological stability and resilience. Moss community responses to disturbance showed all possible responses (increases, decreases, no change) within most disturbance categories. Simulations from two process-based models suggest that northern ecosystems would need to experience extreme perturbation before mosses were eliminated. But simulations with two other models suggest that loss of moss will reduce soil carbon accumulation primarily by influencing decomposition rates and soil nitrogen availability. It seems clear that mosses need to be incorporated into models as one or more plant functional types, but more empirical work is needed to determine how to best aggregate species. We highlight several issues that have not been adequately explored in moss communities, such as functional redundancy and singularity, relationships between response and effect traits, and parameter vs conceptual uncertainty in models. Mosses play an important role in several ecosystem processes that play out over centuries - permafrost formation and thaw, peat accumulation, development of microtopography - and there is a need for studies that increase our understanding of slow, long-term dynamical processes. © 2012 The Authors. New Phytologist © 2012 New Phytologist Trust.

The resilience and functional role of moss in boreal and arctic ecosystems

USGS Publications Warehouse

Turetsky, M.; Bond-Lamberty, B.; Euskirchen, E.S.; Talbot, J. J.; Frolking, S.; McGuire, A.D.; Tuittila, E.S.

2012-01-01

Mosses in northern ecosystems are ubiquitous components of plant communities, and strongly influence nutrient, carbon and water cycling. We use literature review, synthesis and model simulations to explore the role of mosses in ecological stability and resilience. Moss community responses to disturbance showed all possible responses (increases, decreases, no change) within most disturbance categories. Simulations from two process-based models suggest that northern ecosystems would need to experience extreme perturbation before mosses were eliminated. But simulations with two other models suggest that loss of moss will reduce soil carbon accumulation primarily by influencing decomposition rates and soil nitrogen availability. It seems clear that mosses need to be incorporated into models as one or more plant functional types, but more empirical work is needed to determine how to best aggregate species. We highlight several issues that have not been adequately explored in moss communities, such as functional redundancy and singularity, relationships between response and effect traits, and parameter vs conceptual uncertainty in models. Mosses play an important role in several ecosystem processes that play out over centuries – permafrost formation and thaw, peat accumulation, development of microtopography – and there is a need for studies that increase our understanding of slow, long-term dynamical processes.

FOREST ECOLOGY. Pervasive drought legacies in forest ecosystems and their implications for carbon cycle models.

PubMed

Anderegg, W R L; Schwalm, C; Biondi, F; Camarero, J J; Koch, G; Litvak, M; Ogle, K; Shaw, J D; Shevliakova, E; Williams, A P; Wolf, A; Ziaco, E; Pacala, S

2015-07-31

The impacts of climate extremes on terrestrial ecosystems are poorly understood but important for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with the understanding of basic plant physiology. We examined the recovery of stem growth in trees after severe drought at 1338 forest sites across the globe, comprising 49,339 site-years, and compared the results with simulated recovery in climate-vegetation models. We found pervasive and substantial "legacy effects" of reduced growth and incomplete recovery for 1 to 4 years after severe drought. Legacy effects were most prevalent in dry ecosystems, among Pinaceae, and among species with low hydraulic safety margins. In contrast, limited or no legacy effects after drought were simulated by current climate-vegetation models. Our results highlight hysteresis in ecosystem-level carbon cycling and delayed recovery from climate extremes. Copyright © 2015, American Association for the Advancement of Science.

Evaluating the ecological benefits of wildfire by integrating fire and ecosystem simulation models

Treesearch

Robert E. Keane; Eva Karau

2010-01-01

Fire managers are now realizing that wildfires can be beneficial because they can reduce hazardous fuels and restore fire-dominated ecosystems. A software tool that assesses potential beneficial and detrimental ecological effects from wildfire would be helpful to fire management. This paper presents a simulation platform called FLEAT (Fire and Landscape Ecology...

The western arctic linkage experiment (WALE): overview and synthesis

Treesearch

A.D. McGuire; J. Walsh; J.S. Kimball; J.S. Clein; S.E. Euskirdhen; S. Drobot; U.C. Herzfeld; J. Maslanik; R.B. Lammers; M.A. Rawlins; C.J. Vorosmarty; T.S. Rupp; W. Wu; M. Calef

2008-01-01

The primary goal of the Western Arctic Linkage Experiment (WALE) was to better understand uncertainties of simulated hydrologic and ecosystem dynamics of the western Arctic in the context of 1) uncertainties in the data available to drive the models and 2) different approaches to simulating regional hydrology and ecosystem dynamics. Analyses of datasets on climate...

Carbon balance of the terrestrial biosphere in the twentieth century: analyses of CO2, climate and land use effects with four process-based ecosystem models

USGS Publications Warehouse

McGuire, A.D.; Sitch, S.; Clein, Joy S.; Dargaville, R.; Esser, G.; Foley, J.; Heimann, Martin; Joos, F.; Kaplan, J.; Kicklighter, D.W.; Meier, R.A.; Melillo, J.M.; Moore, B.; Prentice, I.C.; Ramankutty, N.; Reichenau, T.; Schloss, A.; Tian, H.; Williams, L.J.; Wittenberg, U.

2001-01-01

The concurrent effects of increasing atmospheric CO2 concentration, climate variability, and cropland establishment and abandonment on terrestrial carbon storage between 1920 and 1992 were assessed using a standard simulation protocol with four process-based terrestrial biosphere models. Over the long-term(1920–1992), the simulations yielded a time history of terrestrial uptake that is consistent (within the uncertainty) with a long-term analysis based on ice core and atmospheric CO2 data. Up to 1958, three of four analyses indicated a net release of carbon from terrestrial ecosystems to the atmosphere caused by cropland establishment. After 1958, all analyses indicate a net uptake of carbon by terrestrial ecosystems, primarily because of the physiological effects of rapidly rising atmospheric CO2. During the 1980s the simulations indicate that terrestrial ecosystems stored between 0.3 and 1.5 Pg C yr−1, which is within the uncertainty of analysis based on CO2 and O2 budgets. Three of the four models indicated (in accordance with O2 evidence) that the tropics were approximately neutral while a net sink existed in ecosystems north of the tropics. Although all of the models agree that the long-term effect of climate on carbon storage has been small relative to the effects of increasing atmospheric CO2 and land use, the models disagree as to whether climate variability and change in the twentieth century has promoted carbon storage or release. Simulated interannual variability from 1958 generally reproduced the El Niño/Southern Oscillation (ENSO)-scale variability in the atmospheric CO2 increase, but there were substantial differences in the magnitude of interannual variability simulated by the models. The analysis of the ability of the models to simulate the changing amplitude of the seasonal cycle of atmospheric CO2 suggested that the observed trend may be a consequence of CO2 effects, climate variability, land use changes, or a combination of these effects. The next steps for improving the process-based simulation of historical terrestrial carbon include (1) the transfer of insight gained from stand-level process studies to improve the sensitivity of simulated carbon storage responses to changes in CO2 and climate, (2) improvements in the data sets used to drive the models so that they incorporate the timing, extent, and types of major disturbances, (3) the enhancement of the models so that they consider major crop types and management schemes, (4) development of data sets that identify the spatial extent of major crop types and management schemes through time, and (5) the consideration of the effects of anthropogenic nitrogen deposition. The evaluation of the performance of the models in the context of a more complete consideration of the factors influencing historical terrestrial carbon dynamics is important for reducing uncertainties in representing the role of terrestrial ecosystems in future projections of the Earth system.

Ecosystem Model Performance at Wetlands: Results from the North American Carbon Program Site Synthesis

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Desai, A. R.; Schroeder, N. M.; NACP Site Synthesis Participants

2011-12-01

Northern peatlands contain a significant fraction of the global carbon pool, and their responses to hydrological change are likely to be important factors in future carbon cycle-climate feedbacks. Global-scale carbon cycle modeling studies typically use general ecosystem models with coarse spatial resolution, often without peatland-specific processes. Here, seven ecosystem models were used to simulate CO2 fluxes at three field sites in Canada and the northern United States, including two nutrient-rich fens and one nutrient-poor, sphagnum-dominated bog, from 2002-2006. Flux residuals (simulated - observed) were positively correlated with measured water table for both gross ecosystem productivity (GEP) and ecosystem respiration (ER) at the two fen sites for all models, and were positively correlated with water table at the bog site for the majority of models. Modeled diurnal cycles at fen sites agreed well with eddy covariance measurements overall. Eddy covariance GEP and ER were higher during dry periods than during wet periods, while model results predicted either the opposite relationship or no significant difference. At the bog site, eddy covariance GEP had no significant dependence on water table, while models predicted higher GEP during wet periods. All models significantly over-estimated GEP at the bog site, and all but one over-estimated ER at the bog site. Carbon cycle models in peatland-rich regions could be improved by incorporating better models or measurements of hydrology and by inhibiting GEP and ER rates under saturated conditions. Bogs and fens likely require distinct treatments in ecosystem models due to differences in nutrients, peat properties, and plant communities.

Detection and Attribution of Simulated Climatic Extreme Events and Impacts: High Sensitivity to Bias Correction

NASA Astrophysics Data System (ADS)

Sippel, S.; Otto, F. E. L.; Forkel, M.; Allen, M. R.; Guillod, B. P.; Heimann, M.; Reichstein, M.; Seneviratne, S. I.; Kirsten, T.; Mahecha, M. D.

2015-12-01

Understanding, quantifying and attributing the impacts of climatic extreme events and variability is crucial for societal adaptation in a changing climate. However, climate model simulations generated for this purpose typically exhibit pronounced biases in their output that hinders any straightforward assessment of impacts. To overcome this issue, various bias correction strategies are routinely used to alleviate climate model deficiencies most of which have been criticized for physical inconsistency and the non-preservation of the multivariate correlation structure. We assess how biases and their correction affect the quantification and attribution of simulated extremes and variability in i) climatological variables and ii) impacts on ecosystem functioning as simulated by a terrestrial biosphere model. Our study demonstrates that assessments of simulated climatic extreme events and impacts in the terrestrial biosphere are highly sensitive to bias correction schemes with major implications for the detection and attribution of these events. We introduce a novel ensemble-based resampling scheme based on a large regional climate model ensemble generated by the distributed weather@home setup[1], which fully preserves the physical consistency and multivariate correlation structure of the model output. We use extreme value statistics to show that this procedure considerably improves the representation of climatic extremes and variability. Subsequently, biosphere-atmosphere carbon fluxes are simulated using a terrestrial ecosystem model (LPJ-GSI) to further demonstrate the sensitivity of ecosystem impacts to the methodology of bias correcting climate model output. We find that uncertainties arising from bias correction schemes are comparable in magnitude to model structural and parameter uncertainties. The present study consists of a first attempt to alleviate climate model biases in a physically consistent way and demonstrates that this yields improved simulations of climate extremes and associated impacts. [1] http://www.climateprediction.net/weatherathome/

Calibration of two complex ecosystem models with different likelihood functions

NASA Astrophysics Data System (ADS)

Hidy, Dóra; Haszpra, László; Pintér, Krisztina; Nagy, Zoltán; Barcza, Zoltán

2014-05-01

The biosphere is a sensitive carbon reservoir. Terrestrial ecosystems were approximately carbon neutral during the past centuries, but they became net carbon sinks due to climate change induced environmental change and associated CO2 fertilization effect of the atmosphere. Model studies and measurements indicate that the biospheric carbon sink can saturate in the future due to ongoing climate change which can act as a positive feedback. Robustness of carbon cycle models is a key issue when trying to choose the appropriate model for decision support. The input parameters of the process-based models are decisive regarding the model output. At the same time there are several input parameters for which accurate values are hard to obtain directly from experiments or no local measurements are available. Due to the uncertainty associated with the unknown model parameters significant bias can be experienced if the model is used to simulate the carbon and nitrogen cycle components of different ecosystems. In order to improve model performance the unknown model parameters has to be estimated. We developed a multi-objective, two-step calibration method based on Bayesian approach in order to estimate the unknown parameters of PaSim and Biome-BGC models. Biome-BGC and PaSim are a widely used biogeochemical models that simulate the storage and flux of water, carbon, and nitrogen between the ecosystem and the atmosphere, and within the components of the terrestrial ecosystems (in this research the developed version of Biome-BGC is used which is referred as BBGC MuSo). Both models were calibrated regardless the simulated processes and type of model parameters. The calibration procedure is based on the comparison of measured data with simulated results via calculating a likelihood function (degree of goodness-of-fit between simulated and measured data). In our research different likelihood function formulations were used in order to examine the effect of the different model goodness metric on calibration. The different likelihoods are different functions of RMSE (root mean squared error) weighted by measurement uncertainty: exponential / linear / quadratic / linear normalized by correlation. As a first calibration step sensitivity analysis was performed in order to select the influential parameters which have strong effect on the output data. In the second calibration step only the sensitive parameters were calibrated (optimal values and confidence intervals were calculated). In case of PaSim more parameters were found responsible for the 95% of the output data variance than is case of BBGC MuSo. Analysis of the results of the optimized models revealed that the exponential likelihood estimation proved to be the most robust (best model simulation with optimized parameter, highest confidence interval increase). The cross-validation of the model simulations can help in constraining the highly uncertain greenhouse gas budget of grasslands.

The Role of Environmental Driving Factors in Historical and Projected Carbon Dynamics of Wetland Ecosystems in Alaska.

PubMed

Lyu, Zhou; Genet, Hélène; He, Yujie; Zhuang, Qianlai; McGuire, A David; Bennett, Alec; Breen, Amy; Clein, Joy; Euskirchen, Eugénie S; Johnson, Kristofer; Kurkowski, Tom; Pastick, Neal J; Rupp, T Scott; Wylie, Bruce K; Zhu, Zhiliang

2018-05-29

Wetlands are critical terrestrial ecosystems in Alaska, covering ~177,000 km 2 , an area greater than all the wetlands in the remainder of the United States. To assess the relative influence of changing climate, atmospheric carbon dioxide (CO 2 ) concentration, and fire regime on carbon balance in wetland ecosystems of Alaska, a modeling framework that incorporates a fire disturbance model and two biogeochemical models was used. Spatially explicit simulations were conducted at 1 km-resolution for the historical period (1950-2009) and future projection period (2010-2099). Simulations estimated that wetland ecosystems of Alaska lost 175 Tg carbon (C) in the historical period. Ecosystem C storage in 2009 was 5556 Tg, with 89% of the C stored in soils. The estimated loss of C as CO 2 and biogenic methane (CH 4 ) emissions resulted in wetlands of Alaska increasing the greenhouse gas forcing of climate warming. Simulations for the projection period were conducted for six climate change scenarios constructed from two climate models forced under three CO 2 emission scenarios. Ecosystem C storage averaged among climate scenarios increased 3.94 TgC/yr by 2099, with variability among the simulations ranging from 2.02 to 4.42 TgC/yr. These increases were driven primarily by increases in net primary production (NPP) that were greater than losses from increased decomposition and fire. The NPP increase was driven by CO 2 fertilization (~5% per 100 ppmv increase) and by increases in air temperature (~1% per °C increase). Increases in air temperature were estimated to be the primary cause for a projected 47.7% mean increase in biogenic CH 4 emissions among the simulations (~15% per °C increase). Ecosystem CO 2 sequestration offset the increase in CH 4 emissions during the 21 st century to decrease the greenhouse gas forcing of climate warming. However, beyond 2100, we expect that this forcing will ultimately increase as wetland ecosystems transition from being a sink to a source of atmospheric CO 2 because of (1) decreasing sensitivity of NPP to increasing atmospheric CO 2 , (2) increasing availability of soil C for decomposition as permafrost thaws, and (3) continued positive sensitivity of biogenic CH 4 emissions to increases in soil temperature. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Development of simplified ecosystem models for applications in Earth system studies: The Century experience

NASA Technical Reports Server (NTRS)

Parton, William J.; Ojima, Dennis S.; Schimel, David S.; Kittel, Timothy G. F.

1992-01-01

During the past decade, a growing need to conduct regional assessments of long-term trends of ecosystem behavior and the technology to meet this need have converged. The Century model is the product of research efforts initially intended to develop a general model of plant-soil ecosystem dynamics for the North American central grasslands. This model is now being used to simulate plant production, nutrient cycling, and soil organic matter dynamics for grassland, crop, forest, and shrub ecosystems in various regions of the world, including temperate and tropical ecosystems. This paper will focus on the philosophical approach used to develop the structure of Century. The steps included were model simplification, parameterization, and testing. In addition, the importance of acquiring regional data bases for model testing and the present regional application of Century in the Great Plains, which focus on regional ecosystem dynamics and the effect of altering environmental conditions, are discussed.

A model using marginal efficiency of investment to analyse carbon and nitrogen interactions in forested ecosystems

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-12-01

Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System modelling community. Here we explore the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants using a new, simple model of ecosystem C-N cycling and interactions (ACONITE). ACONITE builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C:N, N fixation, and plant C use efficiency) based on the optimization of the marginal change in net C or N uptake associated with a change in allocation of C or N to plant tissues. We simulated and evaluated steady-state and transient ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C:N differed among the three ecosystem types (temperate deciduous < tropical evergreen < temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C:N. Also, a widely used linear leaf N-respiration relationship did not yield a realistic leaf C:N, while a more recently reported non-linear relationship simulated leaf C:N that compared better to the global trait database than the linear relationship. Overall, our ability to constrain leaf area index and allow spatially and temporally variable leaf C:N can help address challenges simulating these properties in ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C-N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

Effects of climate and lifeform on dry matter yield (epsilon) from simulations using BIOME BGC. [ecosystem process model for vegetation biomass production using daily absorbed photosynthetically active radiation

NASA Technical Reports Server (NTRS)

Hunt, E. R., Jr.; Running, Steven W.

1992-01-01

An ecosystem process simulation model, BIOME-BGC, is used in a sensitivity analysis to determine the factors that may cause the dry matter yield (epsilon) and annual net primary production to vary for different ecosystems. At continental scales, epsilon is strongly correlated with annual precipitation. At a single location, year-to-year variation in net primary production (NPP) and epsilon is correlated with either annual precipitation or minimum air temperatures. Simulations indicate that forests have lower epsilon than grasslands. The most sensitive parameter affecting forest epsilon is the total amount of living woody biomass, which affects NPP by increasing carbon loss by maintenance respiration. A global map of woody biomass should significantly improve estimates of global NPP using remote sensing.

Modeling the effects of hydrology on gross primary productivity and net ecosystem productivity at Mer Bleue bog

NASA Astrophysics Data System (ADS)

Dimitrov, Dimitre D.; Grant, Robert F.; Lafleur, Peter M.; Humphreys, Elyn R.

2011-12-01

The ecosys model was applied to investigate the effects of water table and subsurface hydrology changes on carbon dioxide exchange at the ombrotrophic Mer Bleue peatland, Ontario, Canada. It was hypothesized that (1) water table drawdown would not affect vascular canopy water potential, hence vascular productivity, because roots would penetrate deeper to compensate for near-surface dryness, (2) moss canopy water potential and productivity would be severely reduced because rhizoids occupy the uppermost peat that is subject to desiccation with water table decline, and (3) given that in a previous study of Mer Bleue, ecosystem respiration showed little sensitivity to water table drawdown, gross primary productivity would mainly determine the net ecosystem productivity through these vegetation-subsurface hydrology linkages. Model output was compared with literature reports and hourly eddy-covariance measurements during 2000-2004. Our findings suggest that late-summer water table drawdown in 2001 had only a minor impact on vascular canopy water potential but greatly impacted hummock moss water potential, where midday values declined to -250 MPa on average in the model. As a result, simulated moss productivity was reduced by half, which largely explained a reduction of 2-3 μmol CO2 m-2 s-1 in midday simulated and measurement-derived gross primary productivity and an equivalent reduction in simulated and measured net ecosystem productivity. The water content of the near-surface peat (top 5-10 cm) was found to be the most important driver of interannual variability of annual net ecosystem productivity through its effects on hummock moss productivity and on ecosystem respiration.

A Simulation Model of Carbon Cycling and Methane Emissions in Amazon Wetlands

NASA Technical Reports Server (NTRS)

Potter, Christopher; Melack, John; Hess, Laura; Forsberg, Bruce; Novo, Evlyn Moraes; Klooster, Steven

2004-01-01

An integrative carbon study is investigating the hypothesis that measured fluxes of methane from wetlands in the Amazon region can be predicted accurately using a combination of process modeling of ecosystem carbon cycles and remote sensing of regional floodplain dynamics. A new simulation model has been build using the NASA- CASA concept for predicting methane production and emission fluxes in Amazon river and floodplain ecosystems. Numerous innovations area being made to model Amazon wetland ecosystems, including: (1) prediction of wetland net primary production (NPP) as the source for plant litter decomposition and accumulation of sediment organic matter in two major vegetation classes - flooded forests (varzea or igapo) and floating macrophytes, (2) representation of controls on carbon processing and methane evasion at the diffusive boundary layer, through the lake water column, and in wetland sediments as a function of changes in floodplain water level, (3) inclusion of surface emissions controls on wetland methane fluxes, including variations in daily surface temperature and of hydrostatic pressure linked to water level fluctuations. A model design overview and early simulation results are presented.

Back-to-the-future: a fresh policy initiative for fisheries and a restoration ecology for ocean ecosystems

PubMed Central

Pitcher, Tony J.

2005-01-01

‘Back-to-the-future’ (BTF) is an integrative approach to a restoration ecology of the oceans that attempts to solve the fisheries crisis. To this end, it harnesses the latest understanding of ecosystem processes, developments in whole ecosystem simulation modelling, and insight into the human dimension of fisheries management. BTF includes new methods for describing past ecosystems, designing fisheries that meet criteria for sustainability and responsibility, and evaluating the costs and benefits of fisheries in restored ecosystems. Evaluation of alternative policy choices, involving trade-offs between conservation and economic values, employs a range of economic, social and ecological measures. Automated searches maximize values of objective functions, and the methodology includes analyses of model parameter uncertainty. Participatory workshops attempt to maximize compliance by fostering a sense of ownership among all stakeholders. Some challenges that have still to be met include improving methods for quantitatively describing the past, reducing uncertainty in ecosystem simulation techniques and in making policy choices robust against climate change. Critical issues include whether past ecosystems make viable policy goals, and whether desirable goals may be reached from today’s ecosystem. Examples from case studies in British Columbia, Newfoundland and elsewhere are presented. PMID:15713591

An individual-based process model to simulate landscape-scale forest ecosystem dynamics

Treesearch

Rupert Seidl; Werner Rammer; Robert M. Scheller; Thomas Spies

2012-01-01

Forest ecosystem dynamics emerges from nonlinear interactions between adaptive biotic agents (i.e., individual trees) and their relationship with a spatially and temporally heterogeneous abiotic environment. Understanding and predicting the dynamics resulting from these complex interactions is crucial for the sustainable stewardship of ecosystems, particularly in the...

Landscape Level Carbon and Water Balances and Agricultural Production in Mountainous Terrain of the Haean Basin, South Korea

NASA Astrophysics Data System (ADS)

Lee, B.; Geyer, R.; Seo, B.; Lindner, S.; Walther, G.; Tenhunen, J. D.

2009-12-01

The process-based spatial simulation model PIXGRO was used to estimate gross primary production, ecosystem respiration, net ecosystem CO2 exchange and water use by forest and crop fields of Haean Basin, South Korea at landscape scale. Simulations are run for individual years from early spring to late fall, providing estimates for dry land crops and rice paddies with respect to carbon gain, biomass and leaf area development, allocation of photoproducts to the belowground ecosystem compartment, and harvest yields. In the case of deciduous oak forests, gas exchange is estimated, but spatial simulation of growth over the single annual cycles is not included. Spatial parameterization of the model is derived for forest LAI based on remote sensing, for forest and cropland fluxes via eddy covariance and chamber studies, for soil characteristics by generalization from spatial surveys, for climate drivers by generalizing observations at ca. 20 monitoring stations distributed throughout the basin and along the elevation gradient from 500 to 1000 m, and for incident radiation via modelling of the radiation components in complex terrain. Validation of the model is being carried out at point scale based on comparison of model output at selected locations with observations as well as with known trends in ecosystem response documented in the literature. The resulting modelling tool is useful for estimation of ecosystem services at landscape scale, first expressed as kg ha-1 crop yield, but via future cooperative studies also in terms of monetary gain to individual farms and farming cooperatives applying particular management strategies.

Northern Forest Ecosystem Dynamics Using Coupled Models and Remote Sensing

NASA Technical Reports Server (NTRS)

Ranson, K. J.; Sun, G.; Knox, R. G.; Levine, E. R.; Weishampel, J. F.; Fifer, S. T.

1999-01-01

Forest ecosystem dynamics modeling, remote sensing data analysis, and a geographical information system (GIS) were used together to determine the possible growth and development of a northern forest in Maine, USA. Field measurements and airborne synthetic aperture radar (SAR) data were used to produce maps of forest cover type and above ground biomass. These forest attribute maps, along with a conventional soils map, were used to identify the initial conditions for forest ecosystem model simulations. Using this information along with ecosystem model results enabled the development of predictive maps of forest development. The results obtained were consistent with observed forest conditions and expected successional trajectories. The study demonstrated that ecosystem models might be used in a spatial context when parameterized and used with georeferenced data sets.

Accounting for age Structure in Ponderosa Pine Ecosystem Analyses: Integrating Management, Disturbance Histories and Observations with the BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Hibbard, K. A.; Law, B.; Thornton, P.

2003-12-01

Disturbance and management regimes in forested ecosystems have been recently highlighted as important factors contributing to quantification of carbon stocks and fluxes. Disturbance events, such as stand-replacing fires and current management regimes that emphasize understory and tree thinning are primary suspects influencing ecosystem processes, including net ecosystem productivity (NEP) in forests of the Pacific Northwest. Several recent analyses have compared simulated to measured component stocks and fluxes of carbon in Ponderosa Pine (Pinus ponderosa var. Laws) at 12 sites ranging from 9 to 300 years in central Oregon (Law et al. 2001, Law et al. 2003) using the BIOME-BGC model. Major emphases on ecosystem model developments include improving allocation logic, integrating ecosystem processes with disturbance such as fire and including nitrogen in biogeochemical cycling. In Law et al. (2001, 2003), field observations prompted BIOME-BGC improvements including dynamic allocation of carbon to fine root mass through the life of a stand. A sequence of simulations was also designed to represent both management and disturbance histories for each site, however, current age structure of each sites wasn't addressed. Age structure, or cohort management has largely been ignored by ecosystem models, however, some studies have sought to incorporate stand age with disturbance and management (e.g. Hibbard et al. 2003). In this analyses, we regressed tree ages against height (R2 = 0.67) to develop a proportional distribution of age structure for each site. To preserve the integrity of the comparison between Law et al. (2003) and this study, we maintained the same timing of harvest, however, based on the distribution of age structures, we manipulated the amount of removal. Harvest by Law et al. (2003) was set at stand-replacement (99%) levels to simulate clear-cutting and reflecting the average top 10% of the age in each plot. For the young sites, we set removal at 73%, 51% and 61% for sites averaging 9,16 and 23 years, respectively. It was assumed that changes in long-term pools (e.g. soil C) were negligible within these timeframes. In Law et al. (2003), the model performed well for old and mature sites, however, model simulations of the younger sites (9-50Y) were weak compared to NEP estimates from observations. Error for the young plots in Law et al. (2003) ranged from 150 - >400% of observed NEP. By accounting for the observed age structure through harvest removal, model error from this study ranged from 20-90% in young plots. This study is one of a few that have sought to account for age structure in simulating ecosystem dynamics and processes.

BOREAS RSS-8 BIOME-BGC Model Simulations at Tower Flux Sites in 1994

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Nickeson, Jaime (Editor); Kimball, John

2000-01-01

BIOME-BGC is a general ecosystem process model designed to simulate biogeochemical and hydrologic processes across multiple scales (Running and Hunt, 1993). In this investigation, BIOME-BGC was used to estimate daily water and carbon budgets for the BOREAS tower flux sites for 1994. Carbon variables estimated by the model include gross primary production (i.e., net photosynthesis), maintenance and heterotrophic respiration, net primary production, and net ecosystem carbon exchange. Hydrologic variables estimated by the model include snowcover, evaporation, transpiration, evapotranspiration, soil moisture, and outflow. The information provided by the investigation includes input initialization and model output files for various sites in tabular ASCII format.

The Integrated Landscape Modeling partnership - Current status and future directions

USGS Publications Warehouse

Mushet, David M.; Scherff, Eric J.

2016-01-28

The Integrated Landscape Modeling (ILM) partnership is an effort by the U.S. Geological Survey (USGS) and U.S. Department of Agriculture (USDA) to identify, evaluate, and develop models to quantify services derived from ecosystems, with a focus on wetland ecosystems and conservation effects. The ILM partnership uses the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling platform to facilitate regional quantifications of ecosystem services under various scenarios of land-cover change that are representative of differing conservation program and practice implementation scenarios. To date, the ILM InVEST partnership has resulted in capabilities to quantify carbon stores, amphibian habitat, plant-community diversity, and pollination services. Work to include waterfowl and grassland bird habitat quality is in progress. Initial InVEST modeling has been focused on the Prairie Pothole Region (PPR) of the United States; future efforts might encompass other regions as data availability and knowledge increase as to how functions affecting ecosystem services differ among regions.The ILM partnership is also developing the capability for field-scale process-based modeling of depressional wetland ecosystems using the Agricultural Policy/Environmental Extender (APEX) model. Progress was made towards the development of techniques to use the APEX model for closed-basin depressional wetlands of the PPR, in addition to the open systems that the model was originally designed to simulate. The ILM partnership has matured to the stage where effects of conservation programs and practices on multiple ecosystem services can now be simulated in selected areas. Future work might include the continued development of modeling capabilities, as well as development and evaluation of differing conservation program and practice scenarios of interest to partner agencies including the USDA’s Farm Service Agency (FSA) and Natural Resources Conservation Service (NRCS). When combined, the ecosystem services modeling capabilities of InVEST and the process-based abilities of the APEX model should provide complementary information needed to meet USDA and the Department of the Interior information needs.

Simulating ectomycorrhiza in boreal forests: implementing ectomycorrhizal fungi model MYCOFON in CoupModel (v5)

NASA Astrophysics Data System (ADS)

He, Hongxing; Meyer, Astrid; Jansson, Per-Erik; Svensson, Magnus; Rütting, Tobias; Klemedtsson, Leif

2018-02-01

The symbiosis between plants and Ectomycorrhizal fungi (ECM) is shown to considerably influence the carbon (C) and nitrogen (N) fluxes between the soil, rhizosphere, and plants in boreal forest ecosystems. However, ECM are either neglected or presented as an implicit, undynamic term in most ecosystem models, which can potentially reduce the predictive power of models.

In order to investigate the necessity of an explicit consideration of ECM in ecosystem models, we implement the previously developed MYCOFON model into a detailed process-based, soil-plant-atmosphere model, Coup-MYCOFON, which explicitly describes the C and N fluxes between ECM and roots. This new Coup-MYCOFON model approach (ECM explicit) is compared with two simpler model approaches: one containing ECM implicitly as a dynamic uptake of organic N considering the plant roots to represent the ECM (ECM implicit), and the other a static N approach in which plant growth is limited to a fixed N level (nonlim). Parameter uncertainties are quantified using Bayesian calibration in which the model outputs are constrained to current forest growth and soil C / N ratio for four forest sites along a climate and N deposition gradient in Sweden and simulated over a 100-year period.

The nonlim approach could not describe the soil C / N ratio due to large overestimation of soil N sequestration but simulate the forest growth reasonably well. The ECM implicit and explicit approaches both describe the soil C / N ratio well but slightly underestimate the forest growth. The implicit approach simulated lower litter production and soil respiration than the explicit approach. The ECM explicit Coup-MYCOFON model provides a more detailed description of internal ecosystem fluxes and feedbacks of C and N between plants, soil, and ECM. Our modeling highlights the need to incorporate ECM and organic N uptake into ecosystem models, and the nonlim approach is not recommended for future long-term soil C and N predictions. We also provide a key set of posterior fungal parameters that can be further investigated and evaluated in future ECM studies.

Complex Dynamics of Wetland Ecosystem with Nonlinear Harvesting: Application to Chilika Lake in Odisha, India

NASA Astrophysics Data System (ADS)

Upadhyay, Ranjit Kumar; Tiwari, S. K.; Roy, Parimita

2015-06-01

In this paper, an attempt has been made to study the spatial and temporal dynamical interactions among the species of wetland ecosystem through a mathematical model. The model represents the population dynamics of phytoplankton, zooplankton and fish species found in Chilika lake, Odisha, India. Nonlinear stability analysis of both the temporal and spatial models has been carried out. Maximum sustainable yield and optimal harvesting policy have been studied for a nonspatial model system. Numerical simulation has been performed to figure out the parameters responsible for the complex dynamics of the wetland system. Significant outcomes of our numerical findings and their interpretations from an ecological point of view are provided in this paper. Numerical simulation of spatial model exhibits some interesting and beautiful patterns. We have also pointed out the parameters that are responsible for the good health of wetland ecosystem.

Characterizing Vegetation Model Skill and Uncertainty in Simulated Ecosystem Response to Climate Change in the United States

NASA Astrophysics Data System (ADS)

Drapek, R. J.; Kim, J. B.

2013-12-01

We simulated ecosystem response to climate change in the USA and Canada at a 5 arc-minute grid resolution using the MC1 dynamic global vegetation model and nine CMIP3 future climate projections as input. The climate projections were produced by 3 GCMs simulating 3 SRES emissions scenarios. We examined MC1 outputs for the conterminous USA by summarizing them by EPA level II and III ecoregions to characterize model skill and evaluate the magnitude and uncertainties of simulated ecosystem response to climate change. First, we evaluated model skill by comparing outputs from the recent historical period with benchmark datasets. Distribution of potential natural vegetation simulated by MC1 was compared with Kuchler's map. Above ground live carbon simulated by MC1 was compared with the National Biomass and Carbon Dataset. Fire return intervals calculated by MC1 were compared with maximum and minimum values compiled for the United States. Each EPA Level III Ecoregion was scored for average agreement with corresponding benchmark data and an average score was calculated for all three types of output. Greatest agreement with benchmark data happened in the Western Cordillera, the Ozark / Ouachita-Appalachian Forests, and the Southeastern USA Plains (EPA Level II Ecoregions). The lowest agreement happened in the Everglades and the Tamaulipas-Texas Semiarid Plain. For simulated ecosystem response to future climate projections we examined MC1 output for shifts in vegetation type, vegetation carbon, runoff, and biomass consumed by fire. Each ecoregion was scored for the amount of change from historical conditions for each variable and an average score was calculated. Smallest changes were forecast for Western Cordillera and Marine West Coast Forest ecosystems. Largest changes were forecast for the Cold Deserts, the Mixed Wood Plains, and the Central USA Plains. By combining scores of model skill for the historical period for each EPA Level 3 Ecoregion with scores representing the magnitude of ecosystem changes in the future, we identified high and low uncertainty ecoregions. The largest anticipated changes and the lowest measures of model skill coincide in the Central USA Plains and the Mixed Wood Plains. The combination of low model skill and high degree of ecosystem change elevate the importance of our uncertainty in this ecoregion. The highest projected changes coincide with relatively high model skill in the Cold Deserts. Climate adaptation efforts are the most likely to pay off in these regions. Finally, highest model skill and lowest anticipated changes coincide in the Western Cordillera and the Marine West Coast Forests. These regions may be relatively low-risk for climate change impacts when compared to the other ecoregions. These results represent only the first step in this type of analysis; there exist many ways to strengthen it. One, MC1 calibrations can be optimized using a structured optimization technique. Two, a larger set of climate projections can be used to capture a fuller range of GCMs and emissions scenarios. And three, employing an ensemble of vegetation models would make the analysis more robust.

Depression of belowground respiration is more pronounced than enhancement of photosynthesis during the first year after nitrogen fertilization of a mature Pacific Northwest Douglas-fir forest

NASA Astrophysics Data System (ADS)

Chen, B.; Black, T. A.; Jassal, R.; Nesic, Z.; Bruemmer, C.

2008-05-01

Nitrogen (N) additions to forest have shown variable effects on both respiration and photosynthesis. With increasing rates of anthropogenic N deposition, there is a strong need to understand the ecosystem response to N inputs. We investigated how N fertilization affects the ecosystem carbon (C) balance of a 57-year-old coast Douglas-fir stand in British Columbia, Canada, based on eddy-covariance (EC) and soil-chamber (fertilized and control plots) measurements and process-based modeling. The stand was fertilized by helicopter with urea at 200 kg N ha-1 in January 2007. A land surface model (Ecosystem Atmosphere Simulation Scheme, EASS) was combined with an ecosystem model (Boreal Ecosystem Productivity Simulator, BEPS) and a coupled C and N subroutine was incorporated into the integrated EASS-BEPS model in this study. This half-hourly time step model was run continuously for the period from 2001 to 2007 in two scenarios: with and without fertilization. Modeled C fluxes without fertilization [net ecosystem productivity (NEP), gross primary productivity (GPP), ecosystem respiration (Re) and belowground respiration (Rs)] agreed well with EC and soil chamber measurements over diurnal, seasonal and annual time scales for 2001 to 2006; while simulated NEP, GPP, Re and Rs with fertilization reasonably followed EC and chamber measurements in 2007 (545 vs. 520, 2163 vs. 2155, 1618 vs. 1635, and 920 vs. 906 g C m-2 yr-1, respectively). Comparison of EC-determined C fluxes in 2007 with model simulations without fertilization suggests that annual Re decreased by 6.7% (1635 vs. 1752 g C m-2), gross primary productivity (GPP) increased by 6.8% (2155 vs. 2017 g C m-2), and annual NEP increased by 96.2% (520 vs. 265 g C m-2) due to fertilization. The modeled reduction in Rs (9.6%, comparing modeled values without and with fertilization: 1008 vs. 920 g C m-2 yr-1) is consistent with that measured using the soil chambers (~11.5%, comparing CO2 effluxes from control and fertilized plots measured from late summer to fall). The model also indicated that the effect of fertilization on aboveground (leaf and stem) respiration was very small. These experimental and modeling results suggest N fertilization significantly increased NEP mainly as a result of strongly reduced Rs (~10-12%) and moderately enhanced GPP (~6.8%) in the first year after fertilization.

Evaluation of simulated biospheric carbon dioxide fluxes and atmospheric concentrations using global in situ observations

NASA Astrophysics Data System (ADS)

Philip, S.; Johnson, M. S.; Potter, C. S.; Genovese, V. B.

2016-12-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

B33C-0612: Evaluation of Simulated Biospheric Carbon Dioxide Fluxes and Atmospheric Concentrations Using Global in Situ Observations

NASA Technical Reports Server (NTRS)

Philip, Sajeev; Johnson, Matthew S.; Potter, Christopher S.; Genovese, Vanessa

2016-01-01

Atmospheric mixing ratios of carbon dioxide (CO2) are largely controlled by anthropogenic emission sources and biospheric sources/sinks. Global biospheric fluxes of CO2 are controlled by complex processes facilitating the exchange of carbon between terrestrial ecosystems and the atmosphere. These processes which play a key role in these terrestrial ecosystem-atmosphere carbon exchanges are currently not fully understood, resulting in large uncertainties in the quantification of biospheric CO2 fluxes. Current models with these inherent deficiencies have difficulties simulating the global carbon cycle with high accuracy. We are developing a new modeling platform, GEOS-Chem-CASA by integrating the year-specific NASA-CASA (National Aeronautics and Space Administration - Carnegie Ames Stanford Approach) biosphere model with the GEOS-Chem (Goddard Earth Observation System-Chemistry) chemical transport model to improve the simulation of atmosphere-terrestrial ecosystem carbon exchange. We use NASA-CASA to explicitly represent the exchange of CO2 between terrestrial ecosystem and atmosphere by replacing the baseline GEOS-Chem land net CO2 flux and forest biomass burning CO2 emissions. We will present the estimation and evaluation of these "bottom-up" land CO2 fluxes, simulated atmospheric mixing ratios, and forest disturbance changes over the last decade. In addition, we will present our initial comparison of atmospheric column-mean dry air mole fraction of CO2 predicted by the model and those retrieved from NASA's OCO-2 (Orbiting Carbon Observatory-2) satellite instrument and model-predicted surface CO2 mixing ratios with global in situ observations. This evaluation is the first step necessary for our future work planned to constrain the estimates of biospheric carbon fluxes through "top-down" inverse modeling, which will improve our understanding of the processes controlling atmosphere-terrestrial ecosystem greenhouse gas exchanges, especially over regions which lack in situ observations.

The southern megalopolis: using the past to predict the future of urban sprawl in the Southeast U.S.

USGS Publications Warehouse

Terando, Adam; Costanza, Jennifer; Belyea, Curtis; Dunn, Robert R.; McKerrow, Alexa; Collazo, Jaime

2014-01-01

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires.

The Southern Megalopolis: Using the Past to Predict the Future of Urban Sprawl in the Southeast U.S

PubMed Central

Terando, Adam J.; Costanza, Jennifer; Belyea, Curtis; Dunn, Robert R.; McKerrow, Alexa; Collazo, Jaime A.

2014-01-01

The future health of ecosystems is arguably as dependent on urban sprawl as it is on human-caused climatic warming. Urban sprawl strongly impacts the urban ecosystems it creates and the natural and agro-ecosystems that it displaces and fragments. Here, we project urban sprawl changes for the next 50 years for the fast-growing Southeast U.S. Previous studies have focused on modeling population density, but the urban extent is arguably as important as population density per se in terms of its ecological and conservation impacts. We develop simulations using the SLEUTH urban growth model that complement population-driven models but focus on spatial pattern and extent. To better capture the reach of low-density suburban development, we extend the capabilities of SLEUTH by incorporating street-network information. Our simulations point to a future in which the extent of urbanization in the Southeast is projected to increase by 101% to 192%. Our results highlight areas where ecosystem fragmentation is likely, and serve as a benchmark to explore the challenging tradeoffs between ecosystem health, economic growth and cultural desires. PMID:25054329

Modelling Pseudocalanus elongatus stage-structured population dynamics embedded in a water column ecosystem model for the northern North Sea

NASA Astrophysics Data System (ADS)

Moll, Andreas; Stegert, Christoph

2007-01-01

This paper outlines an approach to couple a structured zooplankton population model with state variables for eggs, nauplii, two copepodites stages and adults adapted to Pseudocalanus elongatus into the complex marine ecosystem model ECOHAM2 with 13 state variables resolving the carbon and nitrogen cycle. Different temperature and food scenarios derived from laboratory culture studies were examined to improve the process parameterisation for copepod stage dependent development processes. To study annual cycles under realistic weather and hydrographic conditions, the coupled ecosystem-zooplankton model is applied to a water column in the northern North Sea. The main ecosystem state variables were validated against observed monthly mean values. Then vertical profiles of selected state variables were compared to the physical forcing to study differences between zooplankton as one biomass state variable or partitioned into five population state variables. Simulated generation times are more affected by temperature than food conditions except during the spring phytoplankton bloom. Up to six generations within the annual cycle can be discerned in the simulation.

Effects of optimized root water uptake parameterization schemes on water and heat flux simulation in a maize agroecosystem

NASA Astrophysics Data System (ADS)

Cai, Fu; Ming, Huiqing; Mi, Na; Xie, Yanbing; Zhang, Yushu; Li, Rongping

2017-04-01

As root water uptake (RWU) is an important link in the water and heat exchange between plants and ambient air, improving its parameterization is key to enhancing the performance of land surface model simulations. Although different types of RWU functions have been adopted in land surface models, there is no evidence as to which scheme most applicable to maize farmland ecosystems. Based on the 2007-09 data collected at the farmland ecosystem field station in Jinzhou, the RWU function in the Common Land Model (CoLM) was optimized with scheme options in light of factors determining whether roots absorb water from a certain soil layer ( W x ) and whether the baseline cumulative root efficiency required for maximum plant transpiration ( W c ) is reached. The sensibility of the parameters of the optimization scheme was investigated, and then the effects of the optimized RWU function on water and heat flux simulation were evaluated. The results indicate that the model simulation was not sensitive to W x but was significantly impacted by W c . With the original model, soil humidity was somewhat underestimated for precipitation-free days; soil temperature was simulated with obvious interannual and seasonal differences and remarkable underestimations for the maize late-growth stage; and sensible and latent heat fluxes were overestimated and underestimated, respectively, for years with relatively less precipitation, and both were simulated with high accuracy for years with relatively more precipitation. The optimized RWU process resulted in a significant improvement of CoLM's performance in simulating soil humidity, temperature, sensible heat, and latent heat, for dry years. In conclusion, the optimized RWU scheme available for the CoLM model is applicable to the simulation of water and heat flux for maize farmland ecosystems in arid areas.

Simulation of the effect of air pollution on forest ecosystems in a region

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

Tarko, A.M.; Bykadorov, A.V.; Kryuchkov, V.V.

1995-03-01

This article describes a model of air pollution effects on spruce in forests of the northern taiga regions which have been exposed to air pollution from a large metallurgical industrial complex. Both the predictions the model makes about forest ecosystem degradation zones and the limitations of the model are discussed. 5 refs., 1 fig.

Response of North American ecosystem models to multi-annual periodicities in temperature and precipitation

Treesearch

J. Alan Yeakley; Ron A. Moen; David D. Breshears; Martha K. Nungesser

1994-01-01

Ecosystem models typically use input temperature and precipitation data generated stochastically from weather station means and variances. Although the weather station data are based on measurements taken over a few decades, model simulations are usually on the order of centuries. Consequently, observed periodicities in temperature and precipitation at the continental...

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

EPA Science Inventory

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Pr...

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.

Historical and projected carbon balance of mature black spruce ecosystems across north america: The role of carbon-nitrogen interactions

USGS Publications Warehouse

Clein, Joy S.; McGuire, A.D.; Zhang, X.; Kicklighter, D.W.; Melillo, J.M.; Wofsy, S.C.; Jarvis, P.G.; Massheder, J.M.

2002-01-01

The role of carbon (C) and nitrogen (N) interactions on sequestration of atmospheric CO2 in black spruce ecosystems across North America was evaluated with the Terrestrial Ecosystem Model (TEM) by applying parameterizations of the model in which C-N dynamics were either coupled or uncoupled. First, the performance of the parameterizations, which were developed for the dynamics of black spruce ecosystems at the Bonanza Creek Long-Term Ecological Research site in Alaska, were evaluated by simulating C dynamics at eddy correlation tower sites in the Boreal Ecosystem Atmosphere Study (BOREAS) for black spruce ecosystems in the northern study area (northern site) and the southern study area (southern site) with local climate data. We compared simulated monthly growing season (May to September) estimates of gross primary production (GPP), total ecosystem respiration (RESP), and net ecosystem production (NEP) from 1994 to 1997 to available field-based estimates at both sites. At the northern site, monthly growing season estimates of GPP and RESP for the coupled and uncoupled simulations were highly correlated with the field-based estimates (coupled: R2= 0.77, 0.88 for GPP and RESP; uncoupled: R2 = 0.67, 0.92 for GPP and RESP). Although the simulated seasonal pattern of NEP generally matched the field-based data, the correlations between field-based and simulated monthly growing season NEP were lower (R2 = 0.40, 0.00 for coupled and uncoupled simulations, respectively) in comparison to the correlations between field-based and simulated GPP and RESP. The annual NEP simulated by the coupled parameterization fell within the uncertainty of field-based estimates in two of three years. On the other hand, annual NEP simulated by the uncoupled parameterization only fell within the field-based uncertainty in one of three years. At the southern site, simulated NEP generally matched field-based NEP estimates, and the correlation between monthly growing season field-based and simulated NEP (R2 = 0.36, 0.20 for coupled and uncoupled simulations, respectively) was similar to the correlations at the northern site. To evaluate the role of N dynamics in C balance of black spruce ecosystems across North America, we simulated historical and projected C dynamics from 1900 to 2100 with a global-based climatology at 0.5?? resolution (latitude ?? longitude) with both the coupled and uncoupled parameterizations of TEM. From analyses at the northern site, several consistent patterns emerge. There was greater inter-annual variability in net primary production (NPP) simulated by the uncoupled parameterization as compared to the coupled parameterization, which led to substantial differences in inter-annual variability in NEP between the parameterizations. The divergence between NPP and heterotrophic respiration was greater in the uncoupled simulation, resulting in more C sequestration during the projected period. These responses were the result of fundamentally different responses of the coupled and uncoupled parameterizations to changes in CO2 and climate. Across North American black spruce ecosystems, the range of simulated decadal changes in C storage was substantially greater for the uncoupled parameterization than for the coupled parameterization. Analysis of the spatial variability in decadal responses of C dynamics revealed that C fluxes simulated by the coupled and uncoupled parameterizations have different sensitivities to climate and that the climate sensitivities of the fluxes change over the temporal scope of the simulations. The results of this study suggest that uncertainties can be reduced through (1) factorial studies focused on elucidating the role of C and N interactions in the response of mature black spruce ecosystems to manipulations of atmospheric CO2 and climate, (2) establishment of a network of continuous, long-term measurements of C dynamics across the range of mature black spruce ecosystems in North America, and (3) ancillary measureme

Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

NASA Astrophysics Data System (ADS)

Yue, C.; Ciais, P.; Luyssaert, S.; Cadule, P.; Harden, J.; Randerson, J.; Bellassen, V.; Wang, T.; Piao, S. L.; Poulter, B.; Viovy, N.

2013-04-01

Stand-replacing fires are the dominant fire type in North American boreal forest and leave a historical legacy of a mosaic landscape of different aged forest cohorts. To accurately quantify the role of fire in historical and current regional forest carbon balance using models, one needs to explicitly simulate the new forest cohort that is established after fire. The present study adapted the global process-based vegetation model ORCHIDEE to simulate boreal forest fire CO2 emissions and follow-up recovery after a stand-replacing fire, with representation of postfire new cohort establishment, forest stand structure and the following self-thinning process. Simulation results are evaluated against three clusters of postfire forest chronosequence observations in Canada and Alaska. Evaluation variables for simulated postfire carbon dynamics include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index (LAI), and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). The model simulation results, when forced by local climate and the atmospheric CO2 history on each chronosequence site, generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with measurement accuracy (for CO2 flux ~100 g C m-2 yr-1, for biomass carbon ~1000 g C m-2 and for soil carbon ~2000 g C m-2). We find that current postfire forest carbon sink on evaluation sites observed by chronosequence methods is mainly driven by historical atmospheric CO2 increase when forests recover from fire disturbance. Historical climate generally exerts a negative effect, probably due to increasing water stress caused by significant temperature increase without sufficient increase in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon stocks evolution after fire, making it suitable for regional simulations in boreal regions where fire regimes play a key role on ecosystem carbon balance.

Assessing Ecosystem Model Performance in Semiarid Systems

NASA Astrophysics Data System (ADS)

Thomas, A.; Dietze, M.; Scott, R. L.; Biederman, J. A.

2017-12-01

In ecosystem process modelling, comparing outputs to benchmark datasets observed in the field is an important way to validate models, allowing the modelling community to track model performance over time and compare models at specific sites. Multi-model comparison projects as well as models themselves have largely been focused on temperate forests and similar biomes. Semiarid regions, on the other hand, are underrepresented in land surface and ecosystem modelling efforts, and yet will be disproportionately impacted by disturbances such as climate change due to their sensitivity to changes in the water balance. Benchmarking models at semiarid sites is an important step in assessing and improving models' suitability for predicting the impact of disturbance on semiarid ecosystems. In this study, several ecosystem models were compared at a semiarid grassland in southwestern Arizona using PEcAn, or the Predictive Ecosystem Analyzer, an open-source eco-informatics toolbox ideal for creating the repeatable model workflows necessary for benchmarking. Models included SIPNET, DALEC, JULES, ED2, GDAY, LPJ-GUESS, MAESPA, CLM, CABLE, and FATES. Comparison between model output and benchmarks such as net ecosystem exchange (NEE) tended to produce high root mean square error and low correlation coefficients, reflecting poor simulation of seasonality and the tendency for models to create much higher carbon sources than observed. These results indicate that ecosystem models do not currently adequately represent semiarid ecosystem processes.

A multi-objective constraint-based approach for modeling genome-scale microbial ecosystems.

PubMed

Budinich, Marko; Bourdon, Jérémie; Larhlimi, Abdelhalim; Eveillard, Damien

2017-01-01

Interplay within microbial communities impacts ecosystems on several scales, and elucidation of the consequent effects is a difficult task in ecology. In particular, the integration of genome-scale data within quantitative models of microbial ecosystems remains elusive. This study advocates the use of constraint-based modeling to build predictive models from recent high-resolution -omics datasets. Following recent studies that have demonstrated the accuracy of constraint-based models (CBMs) for simulating single-strain metabolic networks, we sought to study microbial ecosystems as a combination of single-strain metabolic networks that exchange nutrients. This study presents two multi-objective extensions of CBMs for modeling communities: multi-objective flux balance analysis (MO-FBA) and multi-objective flux variability analysis (MO-FVA). Both methods were applied to a hot spring mat model ecosystem. As a result, multiple trade-offs between nutrients and growth rates, as well as thermodynamically favorable relative abundances at community level, were emphasized. We expect this approach to be used for integrating genomic information in microbial ecosystems. Following models will provide insights about behaviors (including diversity) that take place at the ecosystem scale.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J.; Holm, J. A.; Bailey, V.; Gough, C. M.

2014-07-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

Responses of alpine grassland on Qinghai-Tibetan plateau to climate warming and permafrost degradation: a modeling perspective

NASA Astrophysics Data System (ADS)

Yi, Shuhua; Wang, Xiaoyun; Qin, Yu; Xiang, Bo; Ding, Yongjian

2014-07-01

Permafrost plays a critical role in soil hydrology. Thus, the degradation of permafrost under warming climate conditions may affect the alpine grassland ecosystem on the Qinghai-Tibetan Plateau. Previous space-for-time studies using plot and basin scales have reached contradictory conclusions. In this study, we applied a process-based ecosystem model (DOS-TEM) with a state-of-the-art permafrost hydrology scheme to examine this issue. Our results showed that 1) the DOS-TEM model could properly simulate the responses of soil thermal and hydrological dynamics and of ecosystem dynamics to climate warming and spatial differences in precipitation; 2) the simulated results were consistent with plot-scale studies showing that warming caused an increase in maximum unfrozen thickness, a reduction in vegetation and soil carbon pools as a whole, and decreases in soil water content, net primary production, and heterotrophic respiration; and 3) the simulated results were also consistent with basin-scale studies showing that the ecosystem responses to warming were different in regions with different combinations of water and energy constraints. Permafrost prevents water from draining into water reservoirs. However, the degradation of permafrost in response to warming is a long-term process that also enhances evapotranspiration. Thus, the degradation of the alpine grassland ecosystem on the Qinghai-Tibetan Plateau (releasing carbon) cannot be mainly attributed to the disappearing waterproofing function of permafrost.

Multi-Agent-Based Simulation of a Complex Ecosystem of Mental Health Care.

PubMed

Kalton, Alan; Falconer, Erin; Docherty, John; Alevras, Dimitris; Brann, David; Johnson, Kyle

2016-02-01

This paper discusses the creation of an Agent-Based Simulation that modeled the introduction of care coordination capabilities into a complex system of care for patients with Serious and Persistent Mental Illness. The model describes the engagement between patients and the medical, social and criminal justice services they interact with in a complex ecosystem of care. We outline the challenges involved in developing the model, including process mapping and the collection and synthesis of data to support parametric estimates, and describe the controls built into the model to support analysis of potential changes to the system. We also describe the approach taken to calibrate the model to an observable level of system performance. Preliminary results from application of the simulation are provided to demonstrate how it can provide insights into potential improvements deriving from introduction of care coordination technology.

Multi-model comparison on the effects of climate change on tree species in the eastern U.S.: results from an enhanced niche model and process-based ecosystem and landscape models

Treesearch

Louis R. Iverson; Frank R. Thompson; Stephen Matthews; Matthew Peters; Anantha Prasad; William D. Dijak; Jacob Fraser; Wen J. Wang; Brice Hanberry; Hong He; Maria Janowiak; Patricia Butler; Leslie Brandt; Chris Swanston

2016-01-01

Context. Species distribution models (SDM) establish statistical relationships between the current distribution of species and key attributes whereas process-based models simulate ecosystem and tree species dynamics based on representations of physical and biological processes. TreeAtlas, which uses DISTRIB SDM, and Linkages and LANDIS PRO, process...

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

NASA Technical Reports Server (NTRS)

Armstrong, Amanda; Fischer, Rico; Huth, Andreas; Shugart, Herman; Fatoyinbo, Temilola

2018-01-01

Ecological modeling and forecasting are essential tools for the understanding of complex vegetation dynamics. The parametric demands of some of these models are often lacking or scant for threatened ecosystems, particularly in diverse tropical ecosystems. One such ecosystem and also one of the world's biodiversity hotspots, Madagascar's lowland rainforests, have disappeared at an alarming rate. The processes that drive tree species growth and distribution remain as poorly understood as the species themselves. We investigated the application of the process-based individual-based FORMIND model to successfully simulate a Madagascar lowland rainforest using previously collected multi-year forest inventory plot data. We inspected the model's ability to characterize growth and species abundance distributions over the study site, and then validated the model with an independently collected forest-inventory dataset from another lowland rainforest in eastern Madagascar. Following a comparative analysis using inventory data from the two study sites, we found that FORMIND accurately captures the structure and biomass of the study forest, with r(squared) values of 0.976, 0.895, and 0.995 for 1:1 lines comparing observed and simulated values across all plant functional types for aboveground biomass (tonnes/ha), stem numbers, and basal area (m(squared)/ha), respectively. Further, in validation with a second study forest site, FORMIND also compared well, only slightly over-estimating shade-intermediate species as compared to the study site, and slightly under-representing shade-tolerant species in percentage of total aboveground biomass. As an important application of the FORMIND model, we measured the net ecosystem exchange (NEE, in tons of carbon per hectare per year) for 50 ha of simulated forest over a 1000-year run from bare ground. We found that NEE values ranged between 1 and -1 t Cha(exp -1)year(exp -1), consequently the study forest can be considered as a net neutral or a very slight carbon sink ecosystem, after the initial 130 years of growth. Our study found that FORMIND represents a valuable tool toward simulating forest dynamics in the immensely diverse Madagascar rainforests.

The Role of Driving Factors in Historical and Projected Carbon Dynamics in Wetland Ecosystems of Alaska

NASA Astrophysics Data System (ADS)

Lyu, Z.; Helene, G.; He, Y.; Zhuang, Q.; McGuire, A. D.; Bennett, A.; Breen, A. L.; Clein, J.; Euskirchen, E. S.; Johnson, K. D.; Kurkowski, T. A.; Pastick, N. J.; Rupp, S. T.; Wylie, B. K.; Zhu, Z.

2017-12-01

Wetlands are important terrestrial ecosystems in Alaska. It is important to understand and assess their role in the regional carbon dynamics in response to historical and projected environmental conditions. A coupled modeling framework that incorporates a fire disturbance model and two biogeochemical models was used to assess the relative influence of changing climate, atmospheric carbon dioxide (CO2) concentration, and fire regime on the historical and future carbon balance in wetland ecosystems of the four main Landscape Conservation Cooperatives (LCCs) of Alaska. Simulations were conducted for the historical period (1950-2009) and future projection period (2010-2099). These simulations estimate that the total carbon (C) storage in wetland ecosystems of Alaska is 5556 Tg C in 2009, with 89% of the C stored in soils. An estimated 175 Tg C was lost during the historical period, which is attributed to greater C lost from the Northwest Boreal LCC than C gained from the other three LCCs. The simulations for the projection period were conducted for six different scenarios driven by climate forcings from two different climate models for each of three CO2 emission scenarios. The mean total carbon storage increased 3.94 Tg C/yr by 2099, with variability among the simulations ranging from 2.02 Tg C/yr to 4.42 Tg C/yr. Across the four LCCs, the largest relative C storage increase occurred in the Arctic and North Pacific LCCs. These increases were primarily driven by increases in net primary production (NPP) that were greater than increases in heterotrophic respiration and fire emissions. Our analysis further indicates that NPP increase was primarily driven by CO2 fertilization ( 5% per 100 ppmv increase) as well as by increases in air temperature ( 1% per ° increase). Increases air temperature were estimated to be the primary cause for a projected 47.7% mean increase in wetlands biogenic CH4 emissions among the simulations ( 15% per ° increase). The combined effects of ecosystem CO2 sequestration and increased CH4 emissions result in a weaker global warming potential (GWP) for wetlands ecosystems in Alaska. Overall, this study estimates that wetland ecosystems of Alaska will transition into a C sink with less contribution to the global warming enhancement.

Application of a water/ecosystem model, VELMA, to inform environmental management decision-making in the watersheds of Keene and Kingsbury Creeks

EPA Science Inventory

VELMA (Visualizing Ecosystem Land Management Assessments) is an eco-hydrological model that produces visual simulations of many hydrologic and ecological processes over time periods from hours to days to years. The purpose thus far has been used for predicting effectiveness of g...

Landscape-level terrestrial methane flux observed from a very tall tower

Treesearch

Ankur R. Desai; Ke Xu; Hanqin Tian; Peter Weishampel; Jonathan Thom; Dan Baumann; Arlyn E. Andrews; Druce D. Cook; Jennifer Y. King; Randall Kolka

2015-01-01

Simulating the magnitude and variability of terrestrial methane sources and sinks poses a challenge to ecosystem models because the biophysical and biogeochemical processes that lead to methane emissions from terrestrial and freshwater ecosystems are, by their nature, episodic and spatially disjunct. As a consequence, model predictions of regional methane emissions...

Classifying and comparing spatial models of fire dynamics

Treesearch

Geoffrey J. Cary; Robert E. Keane; Mike D. Flannigan

2007-01-01

Wildland fire is a significant disturbance in many ecosystems worldwide and the interaction of fire with climate and vegetation over long time spans has major effects on vegetation dynamics, ecosystem carbon budgets, and patterns of biodiversity. Landscape-Fire-Succession Models (LFSMs) that simulate the linked processes of fire and vegetation development in a spatial...

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...

Model-data fusion across ecosystems: from multisite optimizations to global simulations

NASA Astrophysics Data System (ADS)

Kuppel, S.; Peylin, P.; Maignan, F.; Chevallier, F.; Kiely, G.; Montagnani, L.; Cescatti, A.

2014-11-01

This study uses a variational data assimilation framework to simultaneously constrain a global ecosystem model with eddy covariance measurements of daily net ecosystem exchange (NEE) and latent heat (LE) fluxes from a large number of sites grouped in seven plant functional types (PFTs). It is an attempt to bridge the gap between the numerous site-specific parameter optimization works found in the literature and the generic parameterization used by most land surface models within each PFT. The present multisite approach allows deriving PFT-generic sets of optimized parameters enhancing the agreement between measured and simulated fluxes at most of the sites considered, with performances often comparable to those of the corresponding site-specific optimizations. Besides reducing the PFT-averaged model-data root-mean-square difference (RMSD) and the associated daily output uncertainty, the optimization improves the simulated CO2 balance at tropical and temperate forests sites. The major site-level NEE adjustments at the seasonal scale are reduced amplitude in C3 grasslands and boreal forests, increased seasonality in temperate evergreen forests, and better model-data phasing in temperate deciduous broadleaf forests. Conversely, the poorer performances in tropical evergreen broadleaf forests points to deficiencies regarding the modelling of phenology and soil water stress for this PFT. An evaluation with data-oriented estimates of photosynthesis (GPP - gross primary productivity) and ecosystem respiration (Reco) rates indicates distinctively improved simulations of both gross fluxes. The multisite parameter sets are then tested against CO2 concentrations measured at 53 locations around the globe, showing significant adjustments of the modelled seasonality of atmospheric CO2 concentration, whose relevance seems PFT-dependent, along with an improved interannual variability. Lastly, a global-scale evaluation with remote sensing NDVI (normalized difference vegetation index) measurements indicates an improvement of the simulated seasonal variations of the foliar cover for all considered PFTs.

Ecosystem functioning is enveloped by hydrometeorological variability.

PubMed

Pappas, Christoforos; Mahecha, Miguel D; Frank, David C; Babst, Flurin; Koutsoyiannis, Demetris

2017-09-01

Terrestrial ecosystem processes, and the associated vegetation carbon dynamics, respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Long-term variability of the terrestrial carbon cycle is not yet well constrained and the resulting climate-biosphere feedbacks are highly uncertain. Here we present a comprehensive overview of hydrometeorological and ecosystem variability from hourly to decadal timescales integrating multiple in situ and remote-sensing datasets characterizing extra-tropical forest sites. We find that ecosystem variability at all sites is confined within a hydrometeorological envelope across sites and timescales. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. However, simulation results with state-of-the-art process-based models do not reflect this long-term persistent behaviour in ecosystem functioning. Accordingly, we develop a cross-time-scale stochastic framework that captures hydrometeorological and ecosystem variability. Our analysis offers a perspective for terrestrial ecosystem modelling and paves the way for new model-data integration opportunities in Earth system sciences.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Fisk, J.; Holm, J. A.; Bailey, V. L.; Gough, C. M.

2014-12-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. In particular, it is unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging U.S. forests. We tested whether three forest ecosystem models—Biome-BGC, a classic big-leaf model, and the ED and ZELIG gap-oriented models—could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols, and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ED and ZELIG correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes. Biome-BGC net primary production (NPP) was correctly resilient, but for the wrong reasons, while ED and ZELIG exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. As a result we expect that most ecosystem models, developed to simulate processes following stand-replacing disturbances, will not simulate well the gradual and less extensive tree mortality characteristic of moderate disturbances.

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.

The economics of fuel management: Wildfire, invasive plants, and the dynamics of sagebrush rangelands in the western United States

Treesearch

Michael H. Taylor; Kimberly Rollins; Mimako Kobayashi; Robin J. Tausch

2013-01-01

In this article we develop a simulation model to evaluate the economic efficiency of fuel treatments and apply it to two sagebrush ecosystems in the Great Basin of the western United States: the Wyoming Sagebrush Steppe and Mountain Big Sagebrush ecosystems. These ecosystems face the two most prominent concerns in sagebrush ecosystems relative to wildfire: annual grass...

Resilience, rapid transitions and regime shifts: fingerprinting the responses of Lake Żabińskie (NE Poland) to climate variability and human disturbance since 1000 AD

NASA Astrophysics Data System (ADS)

Tylmann, Wojciech; Hernández-Almeida, Iván; Grosjean, Martin; José Gómez Navarro, Juan; Larocque-Tobler, Isabelle; Bonk, Alicja; Enters, Dirk; Ustrzycka, Alicja; Piotrowska, Natalia; Przybylak, Rajmund; Wacnik, Agnieszka; Witak, Małgorzata

2016-04-01

Rapid ecosystem transitions and adverse effects on ecosystem services as responses to combined climate and human impacts are of major concern. Yet few quantitative observational data exist, particularly for ecosystems that have a long history of human intervention. Here, we combine quantitative summer and winter climate reconstructions, climate model simulations and proxies for three major environmental pressures (land use, nutrients and erosion) to explore the system dynamics, resilience, and the role of disturbance regimes in varved eutrophic Lake Żabińskie since AD 1000. Comparison between regional and global climate simulations and quantitative climate reconstructions indicate that proxy data capture noticeably natural forced climate variability, while internal variability appears as the dominant source of climate variability in the climate model simulations during most parts of the last millennium. Using different multivariate analyses and change point detection techniques, we identify ecosystem changes through time and shifts between rather stable states and highly variable ones, as expressed by the proxies for land-use, erosion and productivity in the lake. Prior to AD 1600, the lake ecosystem was characterized by a high stability and resilience against considerable observed natural climate variability. In contrast, lake-ecosystem conditions started to fluctuate at high frequency across a broad range of states after AD 1600. The period AD 1748-1868 represents the phase with the strongest human disturbance of the ecosystem. Analyses of the frequency of change points in the multi-proxy dataset suggests that the last 400 years were highly variable and flickering with increasing vulnerability of the ecosystem to the combined effects of climate variability and anthropogenic disturbances. This led to significant rapid ecosystem transformations.

Simulation modeling of forest landscape disturbances: Where do we go from here?

Treesearch

Ajith H. Perera; Brian R. Sturtevant; Lisa J. Buse

2015-01-01

It was nearly a quarter-century ago when Turner and Gardner (1991) drew attention to methods of quantifying landscape patterns and processes, including simulation modeling. The many authors who contributed to that seminal text collectively signaled the emergence of a new field—spatially explicit simulation modeling of broad-scale ecosystem dynamics. Of particular note...

Modeling winter wheat phenological responses to water deficits in the Unified Plant Growth Model (UPGM) component of the spatially distributed Agricultural Ecosystem Services (AgES) model

USDA-ARS?s Scientific Manuscript database

Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...

Interannual Variability In the Atmospheric CO2 Rectification Over Boreal Forests Based On A Coupled Ecosystem-Atmosphere Model

NASA Astrophysics Data System (ADS)

Chen, B.; Chen, J. M.; Worthy, D.

2004-05-01

Ecosystem CO2 exchange and the planetary boundary layer (PBL) are correlated diurnally and seasonally. The simulation of this atmospheric rectifier effect is important in understanding the global CO2 distribution pattern. A 12-year (1990-1996, 1999-2003), continuous CO2 measurement record from Fraserdale, Ontario (located ~150 km north of Timmons), along with a coupled Vertical Diffusion Scheme (VDS) and ecosystem model (Boreal Ecosystem Productivity Simulator, BEPS), is used to investigate the interannual variability in this effect over a boreal forest region. The coupled model performed well in simulating CO2 vertical diffusion processes. Simulated annual atmospheric rectifier effects, (including seasonal and diurnal), quantified as the variation in the mean CO2 concentration from the surface to the top of the PBL, varied from 2.8 to 4.1 ppm, even though the modeled seasonal variations in the PBL depth were similar throughout the 12-year period. The differences in the interannual rectifier effect primarily resulted from changes in the biospheric CO2 uptake and heterotrophic respiration. Correlations in the year-to year variations of the CO2 rectification were found with mean annual air temperatures, simulated gross primary productivity (GPP) and heterotrophic respiration (Rh) (r2=0.5, 0.46, 0.42, respectively). A small increasing trend in the CO2 rectification was also observed. The year-to-year variation in the vertical distribution of the monthly mean CO2 mixing ratios (reflecting differences in the diurnal rectifier effect) was related to interannual climate variability, however, the seasonal rectifier effects were found to be more sensitive to climate variability than the diurnal rectifier effects.

Convergence and Divergence in a Multi-Model Ensemble of Terrestrial Ecosystem Models in North America

NASA Astrophysics Data System (ADS)

Dungan, J. L.; Wang, W.; Hashimoto, H.; Michaelis, A.; Milesi, C.; Ichii, K.; Nemani, R. R.

2009-12-01

In support of NACP, we are conducting an ensemble modeling exercise using the Terrestrial Observation and Prediction System (TOPS) to evaluate uncertainties among ecosystem models, satellite datasets, and in-situ measurements. The models used in the experiment include public-domain versions of Biome-BGC, LPJ, TOPS-BGC, and CASA, driven by a consistent set of climate fields for North America at 8km resolution and daily/monthly time steps over the period of 1982-2006. The reference datasets include MODIS Gross Primary Production (GPP) and Net Primary Production (NPP) products, Fluxnet measurements, and other observational data. The simulation results and the reference datasets are consistently processed and systematically compared in the climate (temperature-precipitation) space; in particular, an alternative to the Taylor diagram is developed to facilitate model-data intercomparisons in multi-dimensional space. The key findings of this study indicate that: the simulated GPP/NPP fluxes are in general agreement with observations over forests, but are biased low (underestimated) over non-forest types; large uncertainties of biomass and soil carbon stocks are found among the models (and reference datasets), often induced by seemingly “small” differences in model parameters and implementation details; the simulated Net Ecosystem Production (NEP) mainly responds to non-respiratory disturbances (e.g. fire) in the models and therefore is difficult to compare with flux data; and the seasonality and interannual variability of NEP varies significantly among models and reference datasets. These findings highlight the problem inherent in relying on only one modeling approach to map surface carbon fluxes and emphasize the pressing necessity of expanded and enhanced monitoring systems to narrow critical structural and parametrical uncertainties among ecosystem models.

Model parameters for representative wetland plant functional groups

USDA-ARS?s Scientific Manuscript database

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and...

Study on the ecosystem construction of using ecopath model in inland waterway

NASA Astrophysics Data System (ADS)

Zhao, Junjie; Bai, Jing; Zhang, Lu; Wang, Ning; Shou, Youping

2018-04-01

In this paper, Ecopath with Ecosim 5.1 software is used to simulate the constructed water ecosystem of inland waterway. According to the characteristics of feeding relationship, the ecopath model of water ecosystem is divided into seven functional groups: phytoplankton, hydrophyte, zooplankton, herbivorous, omnivorous, polychaetes and detritus. By analyzing the important ecological parameters of the ecosystem, such as biomass, biomass / biomass, consumption / biomass, trophic level and ecological nutrient conversion efficiency, the software integrates the energy flow process of the ecosystem, the ratio of the total net primary production and the sum of all respiratory flows is 1.314, it’s indicating that the ecosystem is equilibrium. The research method of this paper can be widely used to evaluate the stability of the ecosystem of the domestic river.

Comprehensive ecosystem model-experiment synthesis using multiple datasets at two temperate forest free-air CO2 enrichment experiments: model performance and compensating biases

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

Walker, Anthony P; Hanson, Paul J; DeKauwe, Martin G

2014-01-01

Free Air CO2 Enrichment (FACE) experiments provide a remarkable wealth of data to test the sensitivities of terrestrial ecosystem models (TEMs). In this study, a broad set of 11 TEMs were compared to 22 years of data from two contrasting FACE experiments in temperate forests of the south eastern US the evergreen Duke Forest and the deciduous Oak Ridge forest. We evaluated the models' ability to reproduce observed net primary productivity (NPP), transpiration and Leaf Area index (LAI) in ambient CO2 treatments. Encouragingly, many models simulated annual NPP and transpiration within observed uncertainty. Daily transpiration model errors were often relatedmore » to errors in leaf area phenology and peak LAI. Our analysis demonstrates that the simulation of LAI often drives the simulation of transpiration and hence there is a need to adopt the most appropriate of hypothesis driven methods to simulate and predict LAI. Of the three competing hypotheses determining peak LAI (1) optimisation to maximise carbon export, (2) increasing SLA with canopy depth and (3) the pipe model the pipe model produced LAI closest to the observations. Modelled phenology was either prescribed or based on broader empirical calibrations to climate. In some cases, simulation accuracy was achieved through compensating biases in component variables. For example, NPP accuracy was sometimes achieved with counter-balancing biases in nitrogen use efficiency and nitrogen uptake. Combined analysis of parallel measurements aides the identification of offsetting biases; without which over-confidence in model abilities to predict ecosystem function may emerge, potentially leading to erroneous predictions of change under future climates.« less

Reduction of net primary productivity in southern China caused by abnormal low-temperature freezing in winter of 2008 detected by a remote sensing-driven ecosystem model

NASA Astrophysics Data System (ADS)

Ju, W.; Liu, Y.; Zhou, Y.; Zhu, G.

2011-12-01

Terrestrial carbon cycle is an important determinant of global climate change and affected by various factors, including climate, CO2 concentration, atmospheric nitrogen deposition and human activities. Extreme weather events can significantly regulate short-term even long-term carbon exchanges between terrestrial ecosystems and the atmosphere. During the period from the middle January to the middle February 2008, Southern China was seriously hit by abnormal low-temperature freezing, which caused serous damages to forests and crops. However, the reduction of net primary productivity (NPP) of terrestrial ecosystems caused by this extremely abnormal weather event has not been quantitatively investigated. In this study, the Boreal Ecosystem Productivity Simulator (BEPS) model was employed to assess the reduction of NPP in Southern China caused by the abnormal low-temperature freezing. Prior to the regional simulation, the BEPS model was validated using measured NPP in different ecosystems, demonstrating the ability of this model to simulate NPP reliably in China. Then, it was forced using meteorological data interpolated from observations of weather stations and leaf area index inversed from MODIS reflectance data to simulate national wide NPP at a 500 m resolution for the period from 2003 to 2008. The departures of NPP in 2008 from the means during 2003-2007 were used as the indicator of NPP reduction caused by the low-temperature freezing. It was found out that NPP in 2008 decreased significantly in forests of Southern China, especially in Guangdong, Fujian, Zhejiang, Guangxi, Jiangxi, and Hunan Provinces, in which the low-temperature freeing was more serious. The annul reduction of NPP was above 150 g C/m^2/yr in these areas. Key words: Net Primary Productivity, low-temperature freezing, BEPS model, MODIS Correspondence author: Weimin Ju Email:juweimin@nju.edu.cn

SimilarityExplorer: A visual inter-comparison tool for multifaceted climate data

Treesearch

J. Poco; A. Dasgupta; Y. Wei; W. Hargrove; C. Schwalm; R. Cook; E. Bertini; C. Silva

2014-01-01

Inter-comparison and similarity analysis to gauge consensus among multiple simulation models is a critical visualization problem for understanding climate change patterns. Climate models, specifically, Terrestrial Biosphere Models (TBM) represent time and space variable ecosystem processes, for example, simulations of photosynthesis and respiration, using algorithms...

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...

Thinking outside the channel: modeling nitrogen cycling in networked river ecosystems

Treesearch

Ashley M. Helton; Geoffrey C. Poole; Judy L. Meyer; Wilfred M. Wollheim; Bruce J. Peterson; Patrick J. Mulholland; Emily S. Bernhardt; Jack A. Stanford; Clay Arango; Linda R. Ashkenas; Lee W. Cooper; Walter K. Dodds; Stanley V. Gregory; Robert O. Hall; Stephen K. Hamilton; Sherri L. Johnson; William H. McDowell; Jody D. Potter; Jennifer L. Tank; Suzanne M. Thomas; H. Maurice Valett; Jackson R. Webster; Lydia Zeglin

2011-01-01

Agricultural and urban development alters nitrogen and other biogeochemical cycles in rivers worldwide. Because such biogeochemical processes cannot be measured empirically across whole river networks, simulation models are critical tools for understanding river-network biogeochemistry. However, limitations inherent in current models restrict our ability to simulate...

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.

MC1: a dynamic vegetation model for estimating the distribution of vegetation and associated carbon, nutrients, and water—technical documentation. Version 1.0.

Treesearch

Dominique Bachelet; James M. Lenihan; Christopher Daly; Ronald P. Neilson; Dennis S. Ojima; William J. Parton

2001-01-01

Assessments of vegetation response to climate change have generally been made only by equilibrium vegetation models that predict vegetation composition under steady-state conditions. These models do not simulate either ecosystem biogeochemical processes or changes in ecosystem structure that may, in turn, act as feedbacks in determining the dynamics of vegetation...

Impact of hydrological variations on modeling of peatland CO2 fluxes: Results from the North American Carbon Program site synthesis

NASA Astrophysics Data System (ADS)

Sulman, Benjamin N.; Desai, Ankur R.; Schroeder, Nicole M.; Ricciuto, Dan; Barr, Alan; Richardson, Andrew D.; Flanagan, Lawrence B.; Lafleur, Peter M.; Tian, Hanqin; Chen, Guangsheng; Grant, Robert F.; Poulter, Benjamin; Verbeeck, Hans; Ciais, Philippe; Ringeval, Bruno; Baker, Ian T.; Schaefer, Kevin; Luo, Yiqi; Weng, Ensheng

2012-03-01

Northern peatlands are likely to be important in future carbon cycle-climate feedbacks due to their large carbon pools and vulnerability to hydrological change. Use of non-peatland-specific models could lead to bias in modeling studies of peatland-rich regions. Here, seven ecosystem models were used to simulate CO2fluxes at three wetland sites in Canada and the northern United States, including two nutrient-rich fens and one nutrient-poor,sphagnum-dominated bog, over periods between 1999 and 2007. Models consistently overestimated mean annual gross ecosystem production (GEP) and ecosystem respiration (ER) at all three sites. Monthly flux residuals (simulated - observed) were correlated with measured water table for GEP and ER at the two fen sites, but were not consistently correlated with water table at the bog site. Models that inhibited soil respiration under saturated conditions had less mean bias than models that did not. Modeled diurnal cycles agreed well with eddy covariance measurements at fen sites, but overestimated fluxes at the bog site. Eddy covariance GEP and ER at fens were higher during dry periods than during wet periods, while models predicted either the opposite relationship or no significant difference. At the bog site, eddy covariance GEP did not depend on water table, while simulated GEP was higher during wet periods. Carbon cycle modeling in peatland-rich regions could be improved by incorporating wetland-specific hydrology and by inhibiting GEP and ER under saturated conditions. Bogs and fens likely require distinct plant and soil parameterizations in ecosystem models due to differences in nutrients, peat properties, and plant communities.

Detecting a Terrestrial Biosphere Sink for Carbon Dioxide: Interannual Ecosystem Modeling for the Mid-1980s

NASA Technical Reports Server (NTRS)

Potter, Christopher S.; Klooster, Steven A.; Brooks, Vanessa; Gore, Warren J. (Technical Monitor)

1998-01-01

There is considerable uncertainty as to whether interannual variability in climate and terrestrial ecosystem production is sufficient to explain observed variation in atmospheric carbon content over the past 20-30 years. In this paper, we investigated the response of net CO2 exchange in terrestrial ecosystems to interannual climate variability (1983 to 1988) using global satellite observations as drivers for the NASA-CASA (Carnegie-Ames-Stanford Approach) simulation model. This computer model of net ecosystem production (NEP) is calibrated for interannual simulations driven by monthly satellite vegetation index data (NDVI) from the NOAA Advanced Very High Resolution Radiometer (AVHRR) at 1 degree spatial resolution. Major results from NASA-CASA simulations suggest that from 1985 to 1988, the northern middle-latitude zone (between 30 and 60 degrees N) was the principal region driving progressive annual increases in global net primary production (NPP; i.e., the terrestrial biosphere sink for carbon). The average annual increase in NPP over this predominantly northern forest zone was on the order of +0.4 Pg (10 (exp 15) g) C per year. This increase resulted mainly from notable expansion of the growing season for plant carbon fixation toward the zonal latitude extremes, a pattern uniquely demonstrated in our regional visualization results. A net biosphere source flux of CO2 in 1983-1984, coinciding with an El Nino event, was followed by a major recovery of global NEP in 1985 which lasted through 1987 as a net carbon sink of between 0.4 and 2.6 Avg C per year. Analysis of model controls on NPP and soil heterotrophic CO2 fluxes (Rh) suggests that regional warming in northern forests can enhance ecosystem production significantly. In seasonally dry tropical zones, periodic drought and temperature drying effects may carry over with at least a two-year lag time to adversely impact ecosystem production. These yearly patterns in our model-predicted NEP are consistent in magnitude with the estimated exchange of CO2 by the terrestrial biosphere with the atmosphere, as determined by previous isotopic (delta (sup 13 C) convolution analysis. Ecosystem simulation results can help further target locations where net carbon sink fluxes have occurred in the past or may be verified in subsequent field studies.

Modeling ecohydrological impacts of land management and water use in the Silver Creek basin, Idaho

NASA Astrophysics Data System (ADS)

Loinaz, Maria C.; Gross, Dayna; Unnasch, Robert; Butts, Michael; Bauer-Gottwein, Peter

2014-03-01

A number of anthropogenic stressors, including land use change and intensive water use, have caused stream habitat deterioration in arid and semiarid climates throughout the western U.S. These often contribute to high stream temperatures, a widespread water quality problem. Stream temperature is an important indicator of stream ecosystem health and is affected by catchment-scale climate and hydrological processes, morphology, and riparian vegetation. To properly manage affected systems and achieve ecosystem sustainability, it is important to understand the relative impact of these factors. In this study, we predict relative impacts of different stressors using an integrated catchment-scale ecohydrological model that simulates hydrological processes, stream temperature, and fish growth. This type of model offers a suitable measure of ecosystem services because it provides information about the reproductive capability of fish under different conditions. We applied the model to Silver Creek, Idaho, a stream highly valued for its world-renowned trout fishery. The simulations indicated that intensive water use by agriculture and climate change are both major contributors to habitat degradation in the study area. Agricultural practices that increase water use efficiency and mitigate drainage runoff are feasible and can have positive impacts on the ecosystem. All of the mitigation strategies simulated reduced stream temperatures to varying degrees; however, not all resulted in increases in fish growth. The results indicate that temperature dynamics, rather than point statistics, determine optimal growth conditions for fish. Temperature dynamics are influenced by surface water-groundwater interactions. Combined restoration strategies that can achieve ecosystem stability under climate change should be further explored.

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.

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.

A biologically-based individual tree model for managing the longleaf pine ecosystem

Treesearch

Rick Smith; Greg Somers

1998-01-01

Duration: 1995-present Objective: Develop a longleaf pine dynamics model and simulation system to define desirable ecosystem management practices in existing and future longleaf pine stands. Methods: Naturally-regenerated longleaf pine trees are being destructively sampled to measure their recent growth and dynamics. Soils and climate data will be combined with the...

MODELING THE DYNAMICS OF THE INTEGRATED EARTH SYSTEM AND THE VALUE OF GLOBAL ECOSYSTEM SERVICES USING THE GUMBO MODEL. (R827169)

EPA Science Inventory

A global unified metamodel of the biosphere (GUMBO) was developed to simulate the integrated earth system and assess the dynamics and values of ecosystem services. It is a `metamodel' in that it represents a synthesis and a simplification of several existing dynamic gl...

Trade-offs between maintenance of ecosystem services and socio-economic development in rural mountainous communities in southern Spain: a dynamic simulation approach.

PubMed

Vidal-Legaz, Beatriz; Martínez-Fernández, Julia; Picón, Andrés Sánchez; Pugnaire, Francisco I

2013-12-15

Mountainous rural communities have traditionally managed their land extensively, resulting in land uses that provide important ecosystem services for both rural and urban areas. Over recent decades, these communities have undergone drastic changes in economic structure, population size and land use. Our understanding of the exact mechanisms that drive these changes is limited, and there is also a lack of integrative approaches to enable decision makers to steer rural development towards a more sustainable path. In this study, we build a dynamic simulation model to calculate the trade-offs between the provisions of two ecosystem services - landscape aesthetic value and water supply for human use - and the economic development associated with different land use changes. The study area for the simulation comprises two rural communities located in southern Spain. Our results show trade-offs between economic development and the provision of the selected ecosystem services in the selected study area. Land use intensification results in economic development but is not enough to prevent population loss and has a negative impact on both the water supply and on aesthetic services. We conclude that more proactive management policies are needed to mitigate a loss in ecosystem services. Simulation models like ours may facilitate the choice of these policies, as they could test the result of land use planning policies contributing therefore, to a more integrative and sustainable management of rural communities. Copyright © 2013 Elsevier Ltd. All rights reserved.

Simulating the effects of fire disturbance and vegetation recovery on boreal ecosystem carbon fluxes

NASA Astrophysics Data System (ADS)

Yi, Y.; Kimball, J. S.; Jones, L. A.; Zhao, M.

2011-12-01

Fire related disturbance and subsequent vegetation recovery has a major influence on carbon storage and land-atmosphere CO2 fluxes in boreal ecosystems. We applied a synthetic approach combining tower eddy covariance flux measurements, satellite remote sensing and model reanalysis surface meteorology within a terrestrial carbon model framework to estimate fire disturbance and recovery effects on boreal ecosystem carbon fluxes including gross primary production (GPP), ecosystem respiration and net CO2 exchange (NEE). A disturbance index based on MODIS land surface temperature and NDVI was found to coincide with vegetation recovery status inferred from tower chronosequence sites. An empirical algorithm was developed to track ecosystem recovery status based on the disturbance index and used to nudge modeled net primary production (NPP) and surface soil organic carbon stocks from baseline steady-state conditions. The simulations were conducted using a satellite based terrestrial carbon flux model driven by MODIS NDVI and MERRA reanalysis daily surface meteorology inputs. The MODIS (MCD45) burned area product was then applied for mapping recent (post 2000) regional disturbance history, and used with the disturbance index to define vegetation disturbance and recovery status. The model was then applied to estimate regional patterns and temporal changes in terrestrial carbon fluxes across the entire northern boreal forest and tundra domain. A sensitivity analysis was conducted to assess the relative importance of fire disturbance and recovery on regional carbon fluxes relative to assumed steady-state conditions. The explicit representation of disturbance and recovery effects produces more accurate NEE predictions than the baseline steady-state simulations and reduces uncertainty regarding the purported missing carbon sink in the high latitudes.

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.

Comparative study of modeling the impacts of air pollution on carbon and water cycles in terrestrial ecosystems of China during 1980-2005

NASA Astrophysics Data System (ADS)

Ren, W.; Tian, H.; Liu, M.; Chen, G.; Lu, C.; Xu, X.; Zhang, C.; Pan, S.; Felzer, B. S.; Kicklighter, D. W.; Melillo, J. M.; Mu, Q.; Running, S.; Zhao, M.

2008-12-01

China has experienced one of the most rapid changes in the past three decades, which has resulted in and will raise lots of environment problems as undergoing further rapid development in the coming years. Severe air pollution combined with other changing environment factors such as climate variability, increasing CO2 and nitrogen deposition, land use cover and change including agronomic management, significantly have been the most serious environmental problems that have threatened the sustainability of China's ecosystems as well as its economy. We investigated the potential effects of elevated ozone (O3) along with other multiple stresses on net primary productivity (NPP) and evapotransporatioin (ET) in China's terrestrial ecosystems for the period 1980-2005, by using three process-based models including the Biom-BGC, Dynamic Land Ecosystem Model (DLEM) and Terrestrial Ecosystem Model (TEM) forced by the gridded data of historical tropospheric O3, climate and other environmental factors. The comparative study of the model simulations showed that elevated O3 could result in a reduction of decadal mean NPP up to 390 TgC, and a small temporal change in total ET nationwide from 1980 to 2005. However, changes in annual NPP and ET across China's terrestrial ecosystems show substantial spatial variation and the reduction rate of NPP up to 32% indicate varied sensitivity and vulnerability to elevated ozone pollution among different plant functional types. The comparative study indicates that there is an important need to test the simulated results and models' behavior against field experiments.

Interactions between soil thermal and hydrological dynamics in the response of Alaska ecosystems to fire disturbance

USGS Publications Warehouse

Yi, Shuhua; McGuire, A. David; Harden, Jennifer; Kasischke, Eric; Manies, Kristen L.; Hinzman, Larry; Liljedahl, Anna K.; Randerson, J.; Liu, Heping; Romanovsky, Vladimir E.; Marchenko, Sergey S.; Kim, Yongwon

2009-01-01

Soil temperature and moisture are important factors that control many ecosystem processes. However, interactions between soil thermal and hydrological processes are not adequately understood in cold regions, where the frozen soil, fire disturbance, and soil drainage play important roles in controlling interactions among these processes. These interactions were investigated with a new ecosystem model framework, the dynamic organic soil version of the Terrestrial Ecosystem Model, that incorporates an efficient and stable numerical scheme for simulating soil thermal and hydrological dynamics within soil profiles that contain a live moss horizon, fibrous and amorphous organic horizons, and mineral soil horizons. The performance of the model was evaluated for a tundra burn site that had both preburn and postburn measurements, two black spruce fire chronosequences (representing space-for-time substitutions in well and intermediately drained conditions), and a poorly drained black spruce site. Although space-for-time substitutions present challenges in model-data comparison, the model demonstrates substantial ability in simulating the dynamics of evapotranspiration, soil temperature, active layer depth, soil moisture, and water table depth in response to both climate variability and fire disturbance. Several differences between model simulations and field measurements identified key challenges for evaluating/improving model performance that include (1) proper representation of discrepancies between air temperature and ground surface temperature; (2) minimization of precipitation biases in the driving data sets; (3) improvement of the measurement accuracy of soil moisture in surface organic horizons; and (4) proper specification of organic horizon depth/properties, and soil thermal conductivity.

Improving ecosystem-scale modeling of evapotranspiration using ecological mechanisms that account for compensatory responses following disturbance

NASA Astrophysics Data System (ADS)

Millar, David J.; Ewers, Brent E.; Mackay, D. Scott; Peckham, Scott; Reed, David E.; Sekoni, Adewale

2017-09-01

Mountain pine beetle outbreaks in western North America have led to extensive forest mortality, justifiably generating interest in improving our understanding of how this type of ecological disturbance affects hydrological cycles. While observational studies and simulations have been used to elucidate the effects of mountain beetle mortality on hydrological fluxes, an ecologically mechanistic model of forest evapotranspiration (ET) evaluated against field data has yet to be developed. In this work, we use the Terrestrial Regional Ecosystem Exchange Simulator (TREES) to incorporate the ecohydrological impacts of mountain pine beetle disturbance on ET for a lodgepole pine-dominated forest equipped with an eddy covariance tower. An existing degree-day model was incorporated that predicted the life cycle of mountain pine beetles, along with an empirically derived submodel that allowed sap flux to decline as a function of temperature-dependent blue stain fungal growth. The eddy covariance footprint was divided into multiple cohorts for multiple growing seasons, including representations of recently attacked trees and the compensatory effects of regenerating understory, using two different spatial scaling methods. Our results showed that using a multiple cohort approach matched eddy covariance-measured ecosystem-scale ET fluxes well, and showed improved performance compared to model simulations assuming a binary framework of only areas of live and dead overstory. Cumulative growing season ecosystem-scale ET fluxes were 8 - 29% greater using the multicohort approach during years in which beetle attacks occurred, highlighting the importance of including compensatory ecological mechanism in ET models.

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

NASA Astrophysics Data System (ADS)

Wu, S. H.; Jansson, P.-E.

2012-05-01

Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

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.

Land Use Management in the Panama Canal Watershed to Maximize Hydrologic Ecosystem Services Benefits: Explicit Simulation of Preferential Flow Paths in an HPC Environment

NASA Astrophysics Data System (ADS)

Regina, J. A.; Ogden, F. L.; Steinke, R. C.; Frazier, N.; Cheng, Y.; Zhu, J.

2017-12-01

Preferential flow paths (PFP) resulting from biotic and abiotic factors contribute significantly to the generation of runoff in moist lowland tropical watersheds. Flow through PFPs represents the dominant mechanism by which land use choices affect hydrological behavior. The relative influence of PFP varies depending upon land-use management practices. Assessing the possible effects of land-use and landcover change on flows, and other ecosystem services, in the humid tropics partially depends on adequate simulation of PFP across different land-uses. Currently, 5% of global trade passes through the Panama Canal, which is supplied with fresh water from the Panama Canal Watershed. A third set of locks, recently constructed, are expected to double the capacity of the Canal. We incorporated explicit simulation of PFPs in to the ADHydro HPC distributed hydrological model to simulate the effects of land-use and landcover change due to land management incentives on water resources availability in the Panama Canal Watershed. These simulations help to test hypotheses related to the effectiveness of various proposed payments for ecosystem services schemes. This presentation will focus on hydrological model formulation and performance in an HPC environment.

Modelling climate change responses in tropical forests: similar productivity estimates across five models, but different mechanisms and responses

NASA Astrophysics Data System (ADS)

Rowland, L.; Harper, A.; Christoffersen, B. O.; Galbraith, D. R.; Imbuzeiro, H. M. A.; Powell, T. L.; Doughty, C.; Levine, N. M.; Malhi, Y.; Saleska, S. R.; Moorcroft, P. R.; Meir, P.; Williams, M.

2015-04-01

Accurately predicting the response of Amazonia to climate change is important for predicting climate change across the globe. Changes in multiple climatic factors simultaneously result in complex non-linear ecosystem responses, which are difficult to predict using vegetation models. Using leaf- and canopy-scale observations, this study evaluated the capability of five vegetation models (Community Land Model version 3.5 coupled to the Dynamic Global Vegetation model - CLM3.5-DGVM; Ecosystem Demography model version 2 - ED2; the Joint UK Land Environment Simulator version 2.1 - JULES; Simple Biosphere model version 3 - SiB3; and the soil-plant-atmosphere model - SPA) to simulate the responses of leaf- and canopy-scale productivity to changes in temperature and drought in an Amazonian forest. The models did not agree as to whether gross primary productivity (GPP) was more sensitive to changes in temperature or precipitation, but all the models were consistent with the prediction that GPP would be higher if tropical forests were 5 °C cooler than current ambient temperatures. There was greater model-data consistency in the response of net ecosystem exchange (NEE) to changes in temperature than in the response to temperature by net photosynthesis (An), stomatal conductance (gs) and leaf area index (LAI). Modelled canopy-scale fluxes are calculated by scaling leaf-scale fluxes using LAI. At the leaf-scale, the models did not agree on the temperature or magnitude of the optimum points of An, Vcmax or gs, and model variation in these parameters was compensated for by variations in the absolute magnitude of simulated LAI and how it altered with temperature. Across the models, there was, however, consistency in two leaf-scale responses: (1) change in An with temperature was more closely linked to stomatal behaviour than biochemical processes; and (2) intrinsic water use efficiency (IWUE) increased with temperature, especially when combined with drought. These results suggest that even up to fairly extreme temperature increases from ambient levels (+6 °C), simulated photosynthesis becomes increasingly sensitive to gs and remains less sensitive to biochemical changes. To improve the reliability of simulations of the response of Amazonian rainforest to climate change, the mechanistic underpinnings of vegetation models need to be validated at both leaf- and canopy-scales to improve accuracy and consistency in the quantification of processes within and across an ecosystem.

Marine Biogeochemistry Under The Influence of Fish And Fisheries: An Ecosystem Modeling Study

NASA Astrophysics Data System (ADS)

Disa, Deniz; Akoglu, Ekin; Salihoglu, Baris

2017-04-01

The ocean and the marine ecosystems are important controllers of the global carbon cycle. They play a pivotal role in capturing atmospheric carbon into the ocean body, transforming it into organic carbon through photosynthesis and transporting it to the depths of the ocean. Fish, which has a significant role in the marine food webs, is thought to have a considerable impact on carbon export. More specifically, fish has a control on plankton dynamics as a predator, it provides nutrient to the ecosystem by its metabolic activities and it has the ability of moving actively and transporting materials. Fishing is also expected to impact carbon cycle because it directly changes the fish biomasses. However, how fish impacts the biogeochemistry of marine ecosystems is not studied extensively. The aim of this study is to analyze the impact of fish and fisheries on marine biogeochemical processes by setting up an end-to-end model, which simulates lower and higher tropic levels of marine ecosystems simultaneously. For this purpose, a one dimensional biogeochemical model simulating lower tropic level dynamics (e.g. carbon export, nutrient cycles) and an food web model simulating fisheries exploitation and higher tropic level dynamics were online and two-way coupled. Representing the marine ecosystem from one end to the other, the coupled model served as a tool for the analysis of fishing impacts on marine biogeochemical dynamics. Results obtained after incorporation of higher trophic level model changed the plankton compositions and enhanced detritus pools and increased carbon export. Additionally, our model showed that active movement of fish contributed to transport of carbon from surface to the deeper parts of the ocean. Moreover, results after applying different fishing intensities indicated that changes in fisheries exploitation levels directly influence the marine nutrient cycles and hence, the carbon export. Depending on the target and the intensity of fisheries, considerable changes in the biogeochemical responses observed. In conclusion, unlike the models that do not represent the fish explicitly, we demonstrate how marine biogeochemical processes are impacted by the activity of fish assemblages and fisheries exploitation.

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.

Statistical modeling of ecosystem respiration using eddy covariance data: Maximum likelihood parameter estimation, and Monte Carlo simulation of model and parameter uncertainty, applied to three simple models

Treesearch

Andrew D. Richardson; David Y. Hollinger; David Y. Hollinger

2005-01-01

Whether the goal is to fill gaps in the flux record, or to extract physiological parameters from eddy covariance data, researchers are frequently interested in fitting simple models of ecosystem physiology to measured data. Presently, there is no consensus on the best models to use, or the ideal optimization criteria. We demonstrate that, given our estimates of the...

[Responses of Pinus tabulaeformis forest ecosystem in North China to climate change and elevated CO2: a simulation based on BIOME-BGC model and tree-ring data].

PubMed

He, Jun-Jie; Peng, Xing-Yuan; Chen, Zhen-Ju; Cui, Ming-Xing; Zhang, Xian-Liang; Zhou, Chang-Hong

2012-07-01

Based on BIOME-BGC model and tree-ring data, a modeling study was conducted to estimate the dynamic changes of the net primary productivity (NPP) of Pinus tabulaeformis forest ecosystem in North China in 1952-2008, and explore the responses of the radial growth and NPP to regional climate warming as well as the dynamics of the NPP in the future climate change scenarios. The simulation results indicated the annual NPP of the P. tabulaeformis ecosystem in 1952-2008 fluctuated from 244.12 to 645.31 g C x m(-2) x a(-1), with a mean value of 418.6 g C x m(-2) x a(-1) The mean air temperature in May-June and the precipitation from previous August to current July were the main factors limiting the radial growth of P. tabulaeformis and the NPP of P. tabulaeformis ecosystem. In the study period, both the radial growth and the NPP presented a decreasing trend due to the regional warming and drying climate condition. In the future climate scenarios, the NPP would have positive responses to the increase of air temperature, precipitation, and their combination. The elevated CO2 would benefit the increase of the NPP, and the increment would be about 16.1% due to the CO2 fertilization. At both ecosystem and regional scales, the tree-ring data would be an ideal proxy to predict the ecosystem dynamic change, and could be used to validate and calibrate the process-based ecosystem models including BIOME-BGC.

An Integrated Modeling Framework Forecasting Ecosystem Exposure-- A Systems Approach to the Cumulative Impacts of Multiple Stressors

NASA Astrophysics Data System (ADS)

Johnston, J. M.

2013-12-01

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework 'iemWatersheds' has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water Assessment Tool (SWAT) predicts surface water and sediment runoff and associated contaminants; the Watershed Mercury Model (WMM) predicts mercury runoff and loading to streams; the Water quality Analysis and Simulation Program (WASP) predicts water quality within the stream channel; the Habitat Suitability Index (HSI) model scores physicochemical habitat quality for individual fish species; and the Bioaccumulation and Aquatic System Simulator (BASS) predicts fish growth, population dynamics and bioaccumulation of toxic substances. The capability of the Framework to address cumulative impacts will be demonstrated for freshwater ecosystem services and mountaintop mining.

BOREAS TE-19 Ecosystem Carbon Balance Model

NASA Technical Reports Server (NTRS)

Hall, Forrest G. (Editor); Papagno, Andrea (Editor); Frolking, Steve

2000-01-01

The BOREAS TE-19 team developed a model called the Spruce and Moss Model (SPAM) designed to simulate the daily carbon balance of a black spruce/moss boreal forest ecosystem. It is driven by daily weather conditions, and consists of four components: (1) soil climate, (2) tree photosynthesis and respiration, (3) moss photosynthesis and respiration, and (4) litter decomposition and associated heterotrophic respiration. The model simulates tree gross and net photosynthesis, wood respiration, live root respiration, moss gross and net photosynthesis, and heterotrophic respiration (decomposition of root litter, young needle and moss litter, and humus). These values can be combined to generate predictions of total site net ecosystem exchange of carbon (NEE), total soil dark respiration (live roots + heterotrophs + live moss), spruce and moss net productivity, and net carbon accumulation in the soil. To date, simulations have been of the BOREAS NSA-OBS and SSA-OBS tower sites, from 1968-95 (except 1990-93). The files include source code and sample input and output files in ASCII format. The data files are available on a CD-ROM (see document number 20010000884), or from the Oak Ridge National Laboratory (ORNL) Distributed Activity Archive Center (DAAC).

Terrestrial biogeochemical cycles: global interactions with the atmosphere and hydrology

NASA Astrophysics Data System (ADS)

Schimel, David S.; Kittel, Timothy G. F.; Parton, William J.

1991-08-01

Ecosystem scientists have developed a body of theory to predict the behaviour of biogeochemical cycles when exchanges with other ecosystems are small or prescribed. Recent environmental changes make it clear that linkages between ecosystems via atmospheric and hydrological transport have large effects on ecosystem dynamics when considered over time periods of a decade to a century, time scales relevant to contemporary humankind. Our ability to predict behaviour of ecosystems coupled by transport is limited by our ability (1) to extrapolate biotic function to large spatial scales and (2) to measure and model transport. We review developments in ecosystem theory, remote sensing, and geographical information systems (GIS) that support new efforts in spatial modeling. A paradigm has emerged to predict behaviour of ecosystems based on understanding responses to multiple resources (e.g., water, nutrients, light). Several ecosystem models couple primary production to decomposition and nutrient availability using the above paradigm. These models require a fairly small set of environmental variables to simulate spatial and temporal variation in rates of biogeochemical cycling. Simultaneously, techniques for inferring ecosystem behaviour from remotely measured canopy light interception are improving our ability to infer plant activity from satellite observations. Efforts have begun to couple models of transport in air and water to models of ecosystem function. Preliminary work indicates that coupling of transport and ecosystem processes alters the behaviour of earth system components (hydrology, terrestrial ecosystems, and the atmosphere) from that of an uncoupled mode.

Dynamic Shade and Irradiance Simulation of Aquatic Landscapes and Watersheds

EPA Science Inventory

Penumbra is a landscape shade and irradiance simulation model that simulates how solar energy spatially and temporally interacts within dynamic ecosystems such as riparian zones, forests, and other terrain that cast topological shadows. Direct and indirect solar energy accumulate...

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.

Simulation of Boreal Ecosystem Carbon and Water Budgets: Scaling from Local to Regional Extents

NASA Technical Reports Server (NTRS)

Wood, Eric F.

1997-01-01

A coupled water and energy balance model is developed. This model can predict the partitioning of water and energy between major source, sink and storage elements within the Boreal-Ecosystem-Atmospheric Study (BOREAS) areas. The results of testing the model against data collected at BOREAS tower sites during Intensive Field Campaigns and remotely sensed data collected across the BOREAS region are presented.

Predictors of Drought Recovery across Forest Ecosystems

NASA Astrophysics Data System (ADS)

Anderegg, W.

2016-12-01

The impacts of climate extremes on terrestrial ecosystems are poorly understood but central for predicting carbon cycle feedbacks to climate change. Coupled climate-carbon cycle models typically assume that vegetation recovery from extreme drought is immediate and complete, which conflicts with basic plant physiological understanding. Here, we discuss what we have learned about forest ecosystem recovery from extreme drought across spatial and temporal scales, drawing on inference from tree rings, eddy covariance data, large scale gross primary productivity products, and ecosystem models. In tree rings, we find pervasive and substantial "legacy effects" of reduced growth and incomplete recovery for 1-4 years after severe drought, and that legacy effects are most prevalent in dry ecosystems, Pinaceae, and species with low hydraulic safety margins. At larger scales, we see relatively rapid recovery of ecosystem fluxes, with strong influences of ecosystem productivity and diversity and longer recovery periods in high latidue forests. In contrast, no or limited legacy effects are simulated in current climate-vegetation models after drought, and we highlight some of the key missing mechanisms in dynamic vegetation models. Our results reveal hysteresis in forest ecosystem carbon cycling and delayed recovery from climate extremes and help advance a predictive understanding of ecosystem recovery.

Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska

Treesearch

Q. Zhuang; A. D. McGuire; K. P. O' Neill; J. W. Harden; V. E. Romanovsky; J. Yarie

2003-01-01

In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce...

Contribution of Increasing CO2 and Climate to Carbon Storage by Ecosystems in the United States

Treesearch

David Schimel; Jerry Melillo; Hanqin Tian; A. David McGuire; David Kicklighter; Timothy Kittel; Nan Rosenbloom; Steven Running; Peter Thorton; Dennis Ojima; William Parton; Robin Kelly; Martin Sykes; Ron Neilson; Brian Rizzo

2000-01-01

The effects of increasing carbon dioxide (CO2) and climate on net carbon storage in terrestrial ecosystems of the conterminous United States for the period 1895-1993 were modeled with new, detailed historical climate information. For the period 1980-1993, results from an ensemble of three models agree within 25%, simulating a land carbon sink...

Assessing the Impacts of forest degradation on water, energy, and carbon budgets in Amazon forest using the Functionally Assembled Terrestrial Ecosystem Simulator

NASA Astrophysics Data System (ADS)

Huang, M.; Xu, Y.; Longo, M.; Keller, M.; Knox, R. G.; Koven, C.; Fisher, R.

2017-12-01

Tropical forest degradation from logging, fire, and fragmentation not only alters carbon stocks and carbon fluxes, but also impacts physical land-surface properties such as albedo and roughness length. Such impacts are poorly quantified to date due to difficulties in accessing and maintaining observational infrastructures, and the lack of proper modeling tools for capturing the interactions among biophysical properties, ecosystem demography, and biogeochemical cycling in tropical forests. As a first step to address these limitations, we implemented a selective logging module into the Functional Assembled Terrestrial Ecosystem Simulator (FATES) and parameterized the model to reproduce the selective logging experiment at the Tapajos National Forest in Brazil. The model was spun up until it reached the steady state, and simulations with and without logging were compared with the eddy covariance flux towers located at the logged and intact sites. The sensitivity of simulated water, energy, and carbon fluxes to key plant functional traits (e.g. Vcmax and leaf longevity) were quantified by perturbing their values within their documented ranges. Our results suggest that the model can reproduce water and carbon fluxes in intact forests, although sensible heat fluxes were overestimated. The effects of logging intensity and techniques on fluxes were assessed by specifying different disturbance parameters in the models (e.g., size-dependent mortality rates associated with timber harvest, collateral damage, and mechanical damage for infrastructure construction). The model projections suggest that even though the degraded forests rapidly recover water and energy fluxes compared with old-growth forests, the recovery times for carbon stocks, forest structure and composition are much longer. In addition, the simulated recovery trajectories are highly dependent on choices of values for functional traits. Our study highlights the advantages of an Earth system modeling approach, constrained by observations, to quantify the complex interactions among forest degradation, ecosystem recovery, climate, and environmental factors. Our results also show the urgent need to improve the representations of key mechanisms and traits to better capture forest degradation dynamics in Earth System Models.

A spatially explicit hydro-ecological modeling framework (BEPS-TerrainLab V2.0): Model description and test in a boreal ecosystem in Eastern North America

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Margolis, Hank; Ju, Weimin; Sonnentag, Oliver; Giasson, Marc-André

2009-04-01

SummaryA spatially explicit, process-based hydro-ecological model, BEPS-TerrainLab V2.0, was developed to improve the representation of ecophysiological, hydro-ecological and biogeochemical processes of boreal ecosystems in a tightly coupled manner. Several processes unique to boreal ecosystems were implemented including the sub-surface lateral water fluxes, stratification of vegetation into distinct layers for explicit ecophysiological representation, inclusion of novel spatial upscaling strategies and biogeochemical processes. To account for preferential water fluxes common in humid boreal ecosystems, a novel scheme was introduced based on laboratory analyses. Leaf-scale ecophysiological processes were upscaled to canopy-scale by explicitly considering leaf physiological conditions as affected by light and water stress. The modified model was tested with 2 years of continuous measurements taken at the Eastern Old Black Spruce Site of the Fluxnet-Canada Research Network located in a humid boreal watershed in eastern Canada. Comparison of the simulated and measured ET, water-table depth (WTD), volumetric soil water content (VSWC) and gross primary productivity (GPP) revealed that BEPS-TerrainLab V2.0 simulates hydro-ecological processes with reasonable accuracy. The model was able to explain 83% of the ET, 92% of the GPP variability and 72% of the WTD dynamics. The model suggests that in humid ecosystems such as eastern North American boreal watersheds, topographically driven sub-surface baseflow is the main mechanism of soil water partitioning which significantly affects the local-scale hydrological conditions.

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.

Climate change and Arctic ecosystems: 2. Modeling, paleodata-model comparisons, and future projections

USGS Publications Warehouse

Kaplan, J.O.; Bigelow, N.H.; Prentice, I.C.; Harrison, S.P.; Bartlein, P.J.; Christensen, T.R.; Cramer, W.; Matveyeva, N.V.; McGuire, A.D.; Murray, D.F.; Razzhivin, V.Y.; Smith, B.; Walker, D.A.; Anderson, P.M.; Andreev, A.A.; Brubaker, L.B.; Edwards, M.E.; Lozhkin, A.V.

2003-01-01

Large variations in the composition, structure, and function of Arctic ecosystems are determined by climatic gradients, especially of growing-season warmth, soil moisture, and snow cover. A unified circumpolar classification recognizing five types of tundra was developed. The geographic distributions of vegetation types north of 55??N, including the position of the forest limit and the distributions of the tundra types, could be predicted from climatology using a small set of plant functional types embedded in the biogeochemistry-biogeography model BIOME4. Several palaeoclimate simulations for the last glacial maximum (LGM) and mid-Holocene were used to explore the possibility of simulating past vegetation patterns, which are independently known based on pollen data. The broad outlines of observed changes in vegetation were captured. LGM simulations showed the major reduction of forest, the great extension of graminoid and forb tundra, and the restriction of low- and high-shrub tundra (although not all models produced sufficiently dry conditions to mimic the full observed change). Mid-Holocene simulations reproduced the contrast between northward forest extension in western and central Siberia and stability of the forest limit in Beringia. Projection of the effect of a continued exponential increase in atmospheric CO2 concentration, based on a transient ocean-atmosphere simulation including sulfate aerosol effects, suggests a potential for larger changes in Arctic ecosystems during the 21st century than have occurred between mid-Holocene and present. Simulated physiological effects of the CO2 increase (to > 700 ppm) at high latitudes were slight compared with the effects of the change in climate.

Changes in the ecosystem structure of the Black Sea under predicted climatological and anthropogenic variations

NASA Astrophysics Data System (ADS)

Akoglu, Ekin; Salihoglu, Baris; Fach Salihoglu, Bettina; Libralato, Simone; Cannaby, Heather; Oguz, Temel; Solidoro, Cosimo

2014-05-01

A dynamic Ecopath with Ecosim higher-trophic-level (HTL) model representation of the Black Sea ecosystem was coupled to the physical (BIMS-CIR) and biogeochemical (BIMS-ECO) models of the Black Sea in order to investigate historical anthropogenic and climatological interactions and feedbacks in the ecosystem. Further, the coupled models were used to assess the likely consequences of these interactions on the ecosystem's structure and functioning under predicted future climate (IPCC A1B) and fishing variability. Therefore, two model scenarios were used; i) a hindcast scenario (1980-1999) to evaluate and understand the impacts of the short-term climate and physical variability and the introduction of invasive species on the Black Sea ecosystem, and ii) a forecast scenario (2080-2099) to investigate the potential implications of climate change and anthropogenic exploitation on living resources of the Black Sea ecosystem by the end of the 21st century. According to the outcomes of the hindcast simulation, fisheries were found to be the main driver in determining the structure and functioning of the Black Sea ecosystem under changing environmental conditions. The coupled physical-biogeochemical forecast simulations predicted a slight but statistically significant basin-wide increase in the Black Sea's primary productivity by the end of the century due to increased stratification induced by basin-wide temperature increase and reduced Cold Intermediate Layer (CIL) formation which increased the residence time of riverine nutrients within the euphotic zone. Despite this increased primary productivity, the HTL model forecast simulation predicted a significant decrease in the commercial fish stocks primarily due to fisheries exploitation if current catch rates are maintained into the future. Results further suggested that some economically important small pelagic fish species are likely to disappear from the ecosystem making the recovery of the already-collapsed piscivorous fish stocks increasingly unlikely. In addition, a further reduction in the proportion of piscivorous fish in the fish community was found to be consequent. From a management perspective, the results of the study suggested that along with managing fishing exploitation levels of the target stocks, monitoring and management of other species in the ecosystem that are tightly coupled with the fish species in terms of food web interactions were found to be the most effective way of applying an ecosystem-based management strategy in the Black Sea. Such an approach will ensure the sustainable utilisation of the fish stocks of the Black Sea by maintaining the ecological integrity of the Black Sea marine food web.

Effects of experimental nitrogen deposition on peatland carbon pools and fluxes: a modeling analysis

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.; Moore, T. R.; Bubier, J. L.; Juutinen, S.; Larmola, T.

2014-07-01

Nitrogen (N) pollution of peatlands alters their carbon (C) balances, yet long-term effects and controls are poorly understood. We applied the model PEATBOG to analyze impacts of long-term nitrogen (N) fertilization on C cycling in an ombrotrophic bog. Simulations of summer gross ecosystem production (GEP), ecosystem respiration (ER) and net ecosystem exchange (NEE) were evaluated against 8 years of observations and extrapolated for 80 years to identify potential effects of N fertilization and factors influencing model behavior. The model successfully simulated moss decline and raised GEP, ER and NEE on fertilized plots. GEP was systematically overestimated in the model compared to the field data due to high tolerance of Sphagnum to N deposition in the model. Model performance regarding the 8 year response of GEP and NEE to N was improved by introducing an N content threshold shifting the response of photosynthesis capacity to N content in shrubs and graminoids from positive to negative at high N contents. Such changes also eliminated the competitive advantages of vascular species and led to resilience of mosses in the long-term. Regardless of the large changes of C fluxes over the short-term, the simulated GEP, ER and NEE after 80 years depended on whether a graminoid- or shrub-dominated system evolved. When the peatland remained shrub-Sphagnum dominated, it shifted to a C source after only 10 years of fertilization at 6.4 g N m-2 yr-1, whereas this was not the case when it became graminoid-dominated. The modeling results thus highlight the importance of ecosystem adaptation and reaction of plant functional types to N deposition, when predicting the future C balance of N-polluted cool temperate bogs.

A stream temperature model for the Peace-Athabasca River basin

NASA Astrophysics Data System (ADS)

Morales-Marin, L. A.; Rokaya, P.; Wheater, H. S.; Lindenschmidt, K. E.

2017-12-01

Water temperature plays a fundamental role in water ecosystem functioning. Because it regulates flow energy and metabolic rates in organism productivity over a broad spectrum of space and time scales, water temperature constitutes an important indicator of aquatic ecosystems health. In cold region basins, stream water temperature modelling is also fundamental to predict ice freeze-up and break-up events in order to improve flood management. Multiple model approaches such as linear and multivariable regression methods, neural network and thermal energy budged models have been developed and implemented to simulate stream water temperature. Most of these models have been applied to specific stream reaches and trained using observed data, but very little has been done to simulate water temperature in large catchment river networks. We present the coupling of RBM model, a semi-Lagrangian water temperature model for advection-dominated river system, and MESH, a semi-distributed hydrological model, to simulate stream water temperature in river catchments. The coupled models are implemented in the Peace-Athabasca River basin in order to analyze the variation in stream temperature regimes under changing hydrological and meteorological conditions. Uncertainty of stream temperature simulations is also assessed in order to determine the degree of reliability of the estimates.

Evaluation of CH4 and N2O Budget of Natural Ecosystems and Croplands in Asia with a Process-based Model

NASA Astrophysics Data System (ADS)

Ito, A.

2017-12-01

Terrestrial ecosystems are important sink of carbon dioxide (CO2) but significant sources of other greenhouse gases such as methane (CH4) and nitrous oxide (N2O). To resolve the role of terrestrial biosphere in the climate system, we need to quantify total greenhouse gas budget with an adequate accuracy. In addition to top-down evaluation on the basis of atmospheric measurements, model-based approach is required for integration and up-scaling of filed data and for prediction under changing environment and different management practices. Since the early 2000s, we have developed a process-based model of terrestrial biogeochemical cycles focusing on atmosphere-ecosystem exchange of trace gases: Vegetation Integrated SImulator for Trace gases (VISIT). The model includes simple and comprehensive schemes of carbon and nitrogen cycles in terrestrial ecosystems, allowing us to capture dynamic nature of greenhouse gas budget. Beginning from natural ecosystems such as temperate and tropical forests, the models is now applicable to croplands by including agricultural practices such as planting, harvest, and fertilizer input. Global simulation results have been published from several papers, but model validation and benchmarking using up-to-date observations are remained for works. The model is now applied to several practical issues such as evaluation of N2O emission from bio-fuel croplands, which are expected to accomplish the mitigation target of the Paris Agreement. We also show several topics about basic model development such as revised CH4 emission affected by dynamic water-table and refined N2O emission from nitrification.

Three Dimensional Thermal Pollution Models. Volume 2; Rigid-Lid Models

NASA Technical Reports Server (NTRS)

Lee, S. S.; Sengupta, S.

1978-01-01

Three versions of rigid lid programs are presented: one for near field simulation; the second for far field unstratified situations; and the third for stratified basins, far field simulation. The near field simulates thermal plume areas, and the far field version simulates larger receiving aquatic ecosystems. Since these versions have many common subroutines, a unified testing is provided, with main programs for the three possible conditions listed.

Past and future effects of atmospheric deposition on the forest ecosystem at the Hubbard Brook Experimental Forest: simulations with the dynamic model ForSAFE

Treesearch

Salim Belyazid; Scott Bailey; Harald Sverdrup

2010-01-01

The Hubbard Brook Ecosystem Study presents a unique opportunity for studying long-term ecosystem responses to changes in anthropogenic factors. Following industrialisation and the intensification of agriculture, the Hubbard Brook Experimental Forest (HBEF) has been subject to increased loads of atmospheric deposition, particularly sulfur and nitrogen. The deposition of...

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process-based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

Estimation of Carbon Flux of Forest Ecosystem over Qilian Mountains by BIOME-BGC Model

NASA Astrophysics Data System (ADS)

Yan, Min; Tian, Xin; Li, Zengyuan; Chen, Erxue; Li, Chunmei

2014-11-01

The gross primary production (GPP) and net ecosystem exchange (NEE) are important indicators for carbon fluxes. This study aims at evaluating the forest GPP and NEE over the Qilian Mountains using meteorological, remotely sensed and other ancillary data at large scale. To realize this, the widely used ecological-process- based model, Biome-BGC, and remote-sensing-based model, MODIS GPP algorithm, were selected for the simulation of the forest carbon fluxes. The combination of these two models was based on calibrating the Biome-BGC by the optimized MODIS GPP algorithm. The simulated GPP and NEE values were evaluated against the eddy covariance observed GPPs and NEEs, and the well agreements have been reached, with R2=0.76, 0.67 respectively.

New tendencies in wildland fire simulation for understanding fire phenomena: An overview of the WFDS system capabilities in Mediterranean ecosystems

NASA Astrophysics Data System (ADS)

Pastor, E.; Tarragó, D.; Planas, E.

2012-04-01

Wildfire theoretical modeling endeavors predicting fire behavior characteristics, such as the rate of spread, the flames geometry and the energy released by the fire front by applying the physics and the chemistry laws that govern fire phenomena. Its ultimate aim is to help fire managers to improve fire prevention and suppression and hence reducing damage to population and protecting ecosystems. WFDS is a 3D computational fluid dynamics (CFD) model of a fire-driven flow. It is particularly appropriate for predicting the fire behaviour burning through the wildland-urban interface, since it is able to predict the fire behaviour in the intermix of vegetative and structural fuels that comprise the wildland urban interface. This model is not suitable for operational fire management yet due to computational costs constrains, but given the fact that it is open-source and that it has a detailed description of the fuels and of the combustion and heat transfer mechanisms it is currently a suitable system for research purposes. In this paper we present the most important characteristics of the WFDS simulation tool in terms of the models implemented, the input information required and the outputs that the simulator gives useful for understanding fire phenomena. We briefly discuss its advantages and opportunities through some simulation exercises of Mediterranean ecosystems.

Moderate forest disturbance as a stringent test for gap and big-leaf models

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B.; Fisk, J. P.; Holm, J. A.; Bailey, V.; Bohrer, G.; Gough, C. M.

2015-01-01

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models - Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models - could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experiment in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.

Moderate forest disturbance as a stringent test for gap and big-leaf models

DOE PAGES

Bond-Lamberty, Benjamin; Fisk, Justin P.; Holm, Jennifer; ...

2015-01-27

Disturbance-induced tree mortality is a key factor regulating the carbon balance of a forest, but tree mortality and its subsequent effects are poorly represented processes in terrestrial ecosystem models. It is thus unclear whether models can robustly simulate moderate (non-catastrophic) disturbances, which tend to increase biological and structural complexity and are increasingly common in aging US forests. We tested whether three forest ecosystem models – Biome-BGC (BioGeochemical Cycles), a classic big-leaf model, and the ZELIG and ED (Ecosystem Demography) gap-oriented models – could reproduce the resilience to moderate disturbance observed in an experimentally manipulated forest (the Forest Accelerated Succession Experimentmore » in northern Michigan, USA, in which 38% of canopy dominants were stem girdled and compared to control plots). Each model was parameterized, spun up, and disturbed following similar protocols and run for 5 years post-disturbance. The models replicated observed declines in aboveground biomass well. Biome-BGC captured the timing and rebound of observed leaf area index (LAI), while ZELIG and ED correctly estimated the magnitude of LAI decline. None of the models fully captured the observed post-disturbance C fluxes, in particular gross primary production or net primary production (NPP). Biome-BGC NPP was correctly resilient but for the wrong reasons, and could not match the absolute observational values. ZELIG and ED, in contrast, exhibited large, unobserved drops in NPP and net ecosystem production. The biological mechanisms proposed to explain the observed rapid resilience of the C cycle are typically not incorporated by these or other models. It is thus an open question whether most ecosystem models will simulate correctly the gradual and less extensive tree mortality characteristic of moderate disturbances.« less

Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

USGS Publications Warehouse

Yue, C.; Ciais, P.; Luyssaert, S.; Cadule, P.; Harden, J.; Randerson, J.; Bellassen, V.; Wang, T.; Piao, S.L.; Poulter, B.; Viovy, N.

2013-01-01

Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO2 history at each chronosequence site, the model simulations generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO2 flux ~100 g C m−2 yr−1, for biomass carbon ~1000 g C m−2 and for soil carbon ~2000 g C m−2). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.

Simulating boreal forest carbon dynamics after stand-replacing fire disturbance: insights from a global process-based vegetation model

NASA Astrophysics Data System (ADS)

Yue, C.; Ciais, P.; Luyssaert, S.; Cadule, P.; Harden, J.; Randerson, J.; Bellassen, V.; Wang, T.; Piao, S. L.; Poulter, B.; Viovy, N.

2013-12-01

Stand-replacing fires are the dominant fire type in North American boreal forests. They leave a historical legacy of a mosaic landscape of different aged forest cohorts. This forest age dynamics must be included in vegetation models to accurately quantify the role of fire in the historical and current regional forest carbon balance. The present study adapted the global process-based vegetation model ORCHIDEE to simulate the CO2 emissions from boreal forest fire and the subsequent recovery after a stand-replacing fire; the model represents postfire new cohort establishment, forest stand structure and the self-thinning process. Simulation results are evaluated against observations of three clusters of postfire forest chronosequences in Canada and Alaska. The variables evaluated include: fire carbon emissions, CO2 fluxes (gross primary production, total ecosystem respiration and net ecosystem exchange), leaf area index, and biometric measurements (aboveground biomass carbon, forest floor carbon, woody debris carbon, stand individual density, stand basal area, and mean diameter at breast height). When forced by local climate and the atmospheric CO2 history at each chronosequence site, the model simulations generally match the observed CO2 fluxes and carbon stock data well, with model-measurement mean square root of deviation comparable with the measurement accuracy (for CO2 flux ~100 g C m-2 yr-1, for biomass carbon ~1000 g C m-2 and for soil carbon ~2000 g C m-2). We find that the current postfire forest carbon sink at the evaluation sites, as observed by chronosequence methods, is mainly due to a combination of historical CO2 increase and forest succession. Climate change and variability during this period offsets some of these expected carbon gains. The negative impacts of climate were a likely consequence of increasing water stress caused by significant temperature increases that were not matched by concurrent increases in precipitation. Our simulation results demonstrate that a global vegetation model such as ORCHIDEE is able to capture the essential ecosystem processes in fire-disturbed boreal forests and produces satisfactory results in terms of both carbon fluxes and carbon-stock evolution after fire. This makes the model suitable for regional simulations in boreal regions where fire regimes play a key role in the ecosystem carbon balance.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

Antecedent soil conditions create an ecosystem's "memory" of past rainfall events. Such soil moisture memory effects may be observed over a range of timescales, from daily to yearly, and lead to feedbacks between hydrological and ecosystem processes. In this study, we modeled the soil moisture memory effect on savanna ecosystems in California, Arizona, and Africa, using a system dynamics model created to simulate the ecohydrological processes at the plot-scale. The model was carefully calibrated using soil moisture and evapotranspiration data collected at three study sites. The model was then used to simulate scenarios with various initial soil moisture conditions and antecedent precipitation regimes, in order to study the soil moisture memory effects on the evapotranspiration of understory and overstory species. Based on the model results, soil texture and antecedent precipitation regime impact the redistribution of water within soil layers, potentially causing deeper soil layers to influence the ecosystem for a longer time. Of all the study areas modeled, soil moisture memory of California savanna ecosystem site is replenished and dries out most rapidly. Thus soil moisture memory could not maintain the high rate evapotranspiration for more than a few days without incoming rainfall event. On the contrary, soil moisture memory of Arizona savanna ecosystem site lasts the longest time. The plants with different root depths respond to different memory effects; shallow-rooted species mainly respond to the soil moisture memory in the shallow soil. The growing season of grass is largely depended on the soil moisture memory of the top 25cm soil layer. Grass transpiration is sensitive to the antecedent precipitation events within daily to weekly timescale. Deep-rooted plants have different responses since these species can access to the deeper soil moisture memory with longer time duration Soil moisture memory does not have obvious impacts on the phenology of woody plants, as these can maintain transpiration for a longer time even through the top soil layer dries out.

Simulation Modeling of Lakes in Undergraduate and Graduate Classrooms Increases Comprehension of Climate Change Concepts and Experience with Computational Tools

ERIC Educational Resources Information Center

Carey, Cayelan C.; Gougis, Rebekka Darner

2017-01-01

Ecosystem modeling is a critically important tool for environmental scientists, yet is rarely taught in undergraduate and graduate classrooms. To address this gap, we developed a teaching module that exposes students to a suite of modeling skills and tools (including computer programming, numerical simulation modeling, and distributed computing)…

Historical and Possible Future Changes in Permafrost and Active Layer Thickness in Alaska: Implications to Landscape Changes and Permafrost Carbon Pool.

NASA Astrophysics Data System (ADS)

Marchenko, S. S.; Helene, G.; Euskirchen, E. S.; Breen, A. L.; McGuire, D.; Rupp, S. T.; Romanovsky, V. E.; Walsh, J. E.

2017-12-01

The Soil Temperature and Active Layer Thickness (ALT) Gridded Data was developed to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4 fluxes and net C storage following permafrost thaw across Alaska. To develop this database, we used the process-based permafrost dynamics model GIPL2 developed in the Geophysical Institute Permafrost Lab, UAF and which is the permafrost module of the Integrated Ecosystem Model (IEM) for Alaska and Northwest Canada. The climate forcing data for simulations were developed by the Scenarios Network for Alaska and Arctic Planning (SNAP, http://www.snap.uaf.edu/). These data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the five model averaged data were derived from the five CMIP5/AR5 IPCC Global Circulation Models that performed the best in Alaska and other northern regions: NCAR-CCSM4, GFDL-CM3, GISS-E2-R, IPSL-CM5A-LR, MRI-CGCM3. A composite of all five-model outputs for the RCP4.5 and RCP8.5 were used in these particular permafrost dynamics simulations. Data sets were downscaled to a 771 m resolution, using the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. Additional input data (snow characteristics, soil thermal properties, soil water content, organic matter accumulation or its loss due to fire, etc.) came from the Terrestrial Ecosystem Model (TEM) and the ALFRESCO (ALaska FRame-based EcoSystem COde) model simulations. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of seasonally thawed soils within the 4.75 upper meters (original TEM soil column) across the Alaska domain. Simulations of future changes in permafrost indicate that, by the end of the 21st century, late-Holocene permafrost in Alaska will be actively thawing at all locations and that some Late Pleistocene carbon-rich peatlands underlain by permafrost will start to thaw at some locations. The modeling results also indicate how different types of ecosystems affect the thermal state of permafrost and its stability. The release of carbon and the net effect of this thawing depends on the balance between increased productivity and respiration, which depend, in part, on soil moisture dynamics.

Analysing the response of European ecosystems to droughts and heat waves within ISI-MIP2 simulations.

NASA Astrophysics Data System (ADS)

Dury, M.; Henrot, A. J.; Francois, L. M.; Munhoven, G.; Jacquemin, I.; Friend, A. D.; Rademacher, T. T.; Hacket Pain, A. J.; Hickler, T.

2015-12-01

With unprecedented speed and extent, the future climate change can be expected to severely impact terrestrial ecosystems due to more frequent extreme events, such as droughts or heat waves. What will be the impacts of these extreme events on ecosystem functioning and structure? How far will net primary production be reduced by such events? What will be the impact on plant mortality? Could such events trigger changes in the abundance of plant species, thus leading to biome shifts? In this contribution, we propose to use ISI-MIP2 model historical simulations from the biome sector to analyse the response of ecosystems to droughts or heat waves, trying to understand the differences between several vegetation models (e.g. CARAIB, HYBRID, LPJ). The analysis will focus on Europe. It will compare and assess the model responses for a series of well-marked drought or heat wave events in the simulated historical period, such as those that occurred in 1976, 2003 or 2010. This analysis will be performed in terms of several important environmental variables, like soil water and hydric stress, runoff, PFT abundance, net primary productivity and biomass, fire frequency, turnover of soil organic matter, etc. Whenever possible, the response of the model will be compared to available data for the most recent well-marked events. Examples of data to be used are eddy covariance, satellite data (including leaf area and fire occurrence) or tree rings.

Modeling Root Exudation, Priming and Protection in Soil Carbon Responses to Elevated CO2 from Ecosystem to Global Scales

NASA Astrophysics Data System (ADS)

Sulman, B. N.; Phillips, R.; Shevliakova, E.; Oishi, A. C.; Pacala, S. W.

2014-12-01

The sensitivity of soil organic carbon (SOC) to changing environmental conditions represents a critical uncertainty in coupled carbon cycle-climate models. Much of this uncertainty arises from our limited understanding of the extent to which plants induce SOC losses (through accelerated decomposition or "priming") or promote SOC gains (via stabilization through physico-chemical protection). We developed a new SOC model, "Carbon, Organisms, Rhizosphere and Protection in the Soil Environment" (CORPSE), to examine the net effect of priming and protection in response to rising atmospheric CO2, and conducted simulations of rhizosphere priming effects at both ecosystem and global scales. At the ecosystem scale, the model successfully captured and explained disparate SOC responses at the Duke and Oak Ridge free-air CO2 enrichment (FACE) experiments. We show that stabilization of "new" carbon in protected SOC pools may equal or exceed microbial priming of "old" SOC in ecosystems with readily decomposable litter (e.g. Oak Ridge). In contrast, carbon losses owing to priming dominate the net SOC response in ecosystems with more resistant litters (e.g. Duke). For global simulations, the model was fully integrated into the Geophysical Fluid Dynamics Laboratory (GFDL) land model LM3. Globally, priming effects driven by enhanced root exudation and expansion of the rhizosphere reduced SOC storage in the majority of terrestrial areas, partially counterbalancing SOC gains from the enhanced ecosystem productivity driven by CO2 fertilization. Collectively, our results suggest that SOC stocks globally depend not only on temperature and moisture, but also on vegetation responses to environmental changes, and that protected C may provide an important constraint on priming effects.

An Ecosystem Model for the Simulation of Physical and Biological Oceanic Processes-IDAPAK User's Guide and Applications

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Arrigo, Kevin; Murtugudde, Ragu; Signorini, Sergio R.; Tai, King-Sheng

1998-01-01

This TM describes the development, testing, and application of a 4-component (phytoplankton, zooplankton, nitrate, and ammonium) ecosystem model capable of simulating oceanic biological processes. It also reports and documents an in-house software package (Interactive Data Analysis Package - IDAPAK) for interactive data analysis of geophysical fields, including those related to the forcing, verification, and analysis of the ecosystem model. Two regions were studied in the Pacific: the Warm Pool (WP) in the Equatorial Pacific (165 deg. E at the equator) and at Ocean Weather Station P (OWS P) in the Northeast Pacific (50 deg. N, 145 deg. W). The WP results clearly indicate that the upwelling at 100 meters correlates well with surface blooms. The upwelling events in late 1987 and 1990 produced dramatic increases in the surface layer values of all 4 ecosystem components, whereas the spring-summer deep mixing events, do not seem to incur a significant response in any of the ecosystem quantities. The OWS P results show that the monthly profiles of temperature, the annual cycles of solar irradiance, and 0- to 50-m integrated nitrate accurately reproduce observed values. Annual primary production is 190 gC/m(exp 2)/yr, which is consistent with recent observations but is much greater than earlier estimates.

Harnessing Big Data to Represent 30-meter Spatial Heterogeneity in Earth System Models

NASA Astrophysics Data System (ADS)

Chaney, N.; Shevliakova, E.; Malyshev, S.; Van Huijgevoort, M.; Milly, C.; Sulman, B. N.

2016-12-01

Terrestrial land surface processes play a critical role in the Earth system; they have a profound impact on the global climate, food and energy production, freshwater resources, and biodiversity. One of the most fascinating yet challenging aspects of characterizing terrestrial ecosystems is their field-scale (˜30 m) spatial heterogeneity. It has been observed repeatedly that the water, energy, and biogeochemical cycles at multiple temporal and spatial scales have deep ties to an ecosystem's spatial structure. Current Earth system models largely disregard this important relationship leading to an inadequate representation of ecosystem dynamics. In this presentation, we will show how existing global environmental datasets can be harnessed to explicitly represent field-scale spatial heterogeneity in Earth system models. For each macroscale grid cell, these environmental data are clustered according to their field-scale soil and topographic attributes to define unique sub-grid tiles. The state-of-the-art Geophysical Fluid Dynamics Laboratory (GFDL) land model is then used to simulate these tiles and their spatial interactions via the exchange of water, energy, and nutrients along explicit topographic gradients. Using historical simulations over the contiguous United States, we will show how a robust representation of field-scale spatial heterogeneity impacts modeled ecosystem dynamics including the water, energy, and biogeochemical cycles as well as vegetation composition and distribution.

Winter Simulation Conference, Miami Beach, Fla., December 4-6, 1978, Proceedings. Volumes 1 & 2

NASA Technical Reports Server (NTRS)

Highland, H. J. (Editor); Nielsen, N. R.; Hull, L. G.

1978-01-01

The papers report on the various aspects of simulation such as random variate generation, simulation optimization, ranking and selection of alternatives, model management, documentation, data bases, and instructional methods. Simulation studies in a wide variety of fields are described, including system design and scheduling, government and social systems, agriculture, computer systems, the military, transportation, corporate planning, ecosystems, health care, manufacturing and industrial systems, computer networks, education, energy, production planning and control, financial models, behavioral models, information systems, and inventory control.

Improved simulation of river water and groundwater exchange in an alluvial plain using the SWAT model

USDA-ARS?s Scientific Manuscript database

Hydrological interaction between surface and subsurface water systems has a significant impact on water quality, ecosystems and biogeochemistry cycling of both systems. Distributed models have been developed to simulate this function, but they require detailed spatial inputs and extensive computati...

Evaluating the accuracy of VEMAP daily weather data for application in crop simulations on a regional scale

USDA-ARS?s Scientific Manuscript database

Weather plays a critical role in eco-environmental and agricultural systems. Limited availability of meteorological records often constrains the applications of simulation models and related decision support tools. The Vegetation/Ecosystem Modeling and Analysis Project (VEMAP) provides daily weather...

How well does your model capture the terrestrial ecosystem dynamics of the Arctic-Boreal Region?

NASA Astrophysics Data System (ADS)

Stofferahn, E.; Fisher, J. B.; Hayes, D. J.; Huntzinger, D. N.; Schwalm, C.

2016-12-01

The Arctic-Boreal Region (ABR) is a major source of uncertainties for terrestrial biosphere model (TBM) simulations. These uncertainties are precipitated by a lack of observational data from the region, affecting the parameterizations of cold environment processes in the models. Addressing these uncertainties requires a coordinated effort of data collection and integration of the following key indicators of the ABR ecosystem: disturbance, flora / fauna and related ecosystem function, carbon pools and biogeochemistry, permafrost, and hydrology. We are developing a model-data integration framework for NASA's Arctic Boreal Vulnerability Experiment (ABoVE), wherein data collection for the key ABoVE indicators is driven by matching observations and model outputs to the ABoVE indicators. The data are used as reference datasets for a benchmarking system which evaluates TBM performance with respect to ABR processes. The benchmarking system utilizes performance metrics to identify intra-model and inter-model strengths and weaknesses, which in turn provides guidance to model development teams for reducing uncertainties in TBM simulations of the ABR. The system is directly connected to the International Land Model Benchmarking (ILaMB) system, as an ABR-focused application.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2014-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

Effects of land cover change on evapotranspiration and streamflow of small catchments in the Upper Xingu River Basin, Central Brazi

NASA Astrophysics Data System (ADS)

Costa, M. H.; Dias, L. C. P.; Macedo, M.; Coe, M. T.; Neill, C.

2015-12-01

This study assess the influence of land cover changes on evapotranspiration and streamflow in small catchments in the Upper Xingu River Basin (Mato Grosso state, Brazil). Streamflow was measured in catchments with uniform land use for September 1, 2008 to August 31, 2010. We used models to simulate evapotranspiration and streamflow for the four most common land cover types found in the Upper Xingu: tropical forest, cerrado (savanna), pasture, and soybean croplands. We used INLAND to perform single point simulations considering tropical rainforest, cerrado and pasturelands, and AgroIBIS for croplands. Converting natural vegetation to agriculture substantially modifies evapotranspiration and streamflow in small catchments. Measured mean streamflow in soy catchments was about three times greater than that of forest catchments, while the mean annual amplitude of flow in soy catchments was more than twice that of forest catchments. Simulated mean annual evapotranspiration was 39% lower in agricultural ecosystems (pasture and soybean cropland) than in natural ecosystems (tropical rainforest and cerrado). Observed and simulated mean annual streamflows in agricultural ecosystems were more than 100% higher than in natural ecosystems. The accuracy of the simulations is improved by using field-measured soil hydraulic properties. The inclusion of local measurements of key soil parameters is likely to improve hydrological simulations in other tropical regions.

A Global Carbon Assimilation System using a modified EnKF assimilation method

NASA Astrophysics Data System (ADS)

Zhang, S.; Zheng, X.; Chen, Z.; Dan, B.; Chen, J. M.; Yi, X.; Wang, L.; Wu, G.

2014-10-01

A Global Carbon Assimilation System based on Ensemble Kalman filter (GCAS-EK) is developed for assimilating atmospheric CO2 abundance data into an ecosystem model to simultaneously estimate the surface carbon fluxes and atmospheric CO2 distribution. This assimilation approach is based on the ensemble Kalman filter (EnKF), but with several new developments, including using analysis states to iteratively estimate ensemble forecast errors, and a maximum likelihood estimation of the inflation factors of the forecast and observation errors. The proposed assimilation approach is tested in observing system simulation experiments and then used to estimate the terrestrial ecosystem carbon fluxes and atmospheric CO2 distributions from 2002 to 2008. The results showed that this assimilation approach can effectively reduce the biases and uncertainties of the carbon fluxes simulated by the ecosystem model.

[Characteristics of terrestrial ecosystem primary productivity in East Asia based on remote sensing and process-based model].

PubMed

Zhang, Fang-Min; Ju, Wei-Min; Chen, Jing-Ming; Wang, Shao-Qiang; Yu, Gui-Rui; Han, Shi-Jie

2012-02-01

Based on the bi-linearly interpolated meteorological reanalysis data from National Centers for Environmental Prediction, USA and by using the leaf area index data derived from the GIMMS NDVI to run the process-based Boreal Ecosystems Productivity Simulator (BEPS) model, this paper simulated and analyzed the spatiotemporal characteristics of the terrestrial ecosystem gross primary productivity (GPP) and net primary productivity (NPP) in East Asia in 2000-2005. Before regional simulating and calculating, the observation GPP data of different terrestrial ecosystem in 15 experimental stations of AsiaFlux network and the inventory measurements of NPP at 1300 sampling sites were applied to validate the BEPS GPP and NPP. The results showed that BEPS could well simulate the changes in GPP and NPP of different terrestrial ecosystems, with the R2 ranging from 0.86 to 0.99 and the root mean square error (RMSE) from 0.2 to 1.2 g C x m(-2) x d(-1). The simulated values by BEPS could explain 78% of the changes in annual NPP, and the RMSE was 118 g C x m(-2) x a(-1). In 2000-2005, the averaged total GPP and total NPP of the terrestrial ecosystems in East Asia were 21.7 and 10.5 Pg C x a(-1), respectively, and the GPP and NPP exhibited similar spatial and temporal variation patterns. During the six years, the total NPP of the terrestrial ecosystems varied from 10.2 to 10.7 Pg C x a(-1), with a coefficient of variation being 2. 2%. High NPP (above 1000 g C x m(-2) x a(-1)) occurred in the southeast island countries, while low NPP (below 30 g C x m(-2) x a(-1)) occurred in the desert area of Northwest China. The spatial patterns of NPP were mainly attributed to the differences in the climatic variables across East Asia. The NPP per capita also varied greatly among different countries, which was the highest (70217 kg C x a(-1)) in Mongolia, far higher than that (1921 kg C x a(-1)) in China, and the lowest (757 kg C x a(-1)) in India.

Biodiversity and ecosystem stability across scales in metacommunities

PubMed Central

Wang, Shaopeng; Loreau, Michel

2016-01-01

Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilizing effects for regional ecosystems, through local and spatial insurance effects, respectively. We further show that at the regional scale, the stabilizing effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenization) and biodiversity loss on ecosystem sustainability at large scales. PMID:26918536

A Model Supported Interactive Virtual Environment for Natural Resource Sharing in Environmental Education

ERIC Educational Resources Information Center

Barbalios, N.; Ioannidou, I.; Tzionas, P.; Paraskeuopoulos, S.

2013-01-01

This paper introduces a realistic 3D model supported virtual environment for environmental education, that highlights the importance of water resource sharing by focusing on the tragedy of the commons dilemma. The proposed virtual environment entails simulations that are controlled by a multi-agent simulation model of a real ecosystem consisting…

Critical Watersheds: Climate Change, Tipping Points, and Energy-Water Impacts

NASA Astrophysics Data System (ADS)

Middleton, R. S.; Brown, M.; Coon, E.; Linn, R.; McDowell, N. G.; Painter, S. L.; Xu, C.

2014-12-01

Climate change, extreme climate events, and climate-induced disturbances will have a substantial and detrimental impact on terrestrial ecosystems. How ecosystems respond to these impacts will, in turn, have a significant effect on the quantity, quality, and timing of water supply for energy security, agriculture, industry, and municipal use. As a community, we lack sufficient quantitative and mechanistic understanding of the complex interplay between climate extremes (e.g., drought, floods), ecosystem dynamics (e.g., vegetation succession), and disruptive events (e.g., wildfire) to assess ecosystem vulnerabilities and to design mitigation strategies that minimize or prevent catastrophic ecosystem impacts. Through a combination of experimental and observational science and modeling, we are developing a unique multi-physics ecohydrologic framework for understanding and quantifying feedbacks between novel climate and extremes, surface and subsurface hydrology, ecosystem dynamics, and disruptive events in critical watersheds. The simulation capability integrates and advances coupled surface-subsurface hydrology from the Advanced Terrestrial Simulator (ATS), dynamic vegetation succession from the Ecosystem Demography (ED) model, and QUICFIRE, a novel wildfire behavior model developed from the FIRETEC platform. These advances are expected to make extensive contributions to the literature and to earth system modeling. The framework is designed to predict, quantify, and mitigate the impacts of climate change on vulnerable watersheds, with a focus on the US Mountain West and the energy-water nexus. This emerging capability is used to identify tipping points in watershed ecosystems, quantify impacts on downstream users, and formally evaluate mitigation efforts including forest (e.g., thinning, prescribed burns) and watershed (e.g., slope stabilization). The framework is being trained, validated, and demonstrated using field observations and remote data collections in the Valles Caldera National Preserve, including pre- and post-wildfire and infestation observations. Ultimately, the framework will be applied to the upper Colorado River basin. Here, we present an overview of the framework development strategy and latest field and modeling results.

Use of hydrologic and hydrodynamic modeling for ecosystem restoration

USGS Publications Warehouse

Obeysekera, J.; Kuebler, L.; Ahmed, S.; Chang, M.-L.; Engel, V.; Langevin, C.; Swain, E.; Wan, Y.

2011-01-01

Planning and implementation of unprecedented projects for restoring the greater Everglades ecosystem are underway and the hydrologic and hydrodynamic modeling of restoration alternatives has become essential for success of restoration efforts. In view of the complex nature of the South Florida water resources system, regional-scale (system-wide) hydrologic models have been developed and used extensively for the development of the Comprehensive Everglades Restoration Plan. In addition, numerous subregional-scale hydrologic and hydrodynamic models have been developed and are being used for evaluating project-scale water management plans associated with urban, agricultural, and inland costal ecosystems. The authors provide a comprehensive summary of models of all scales, as well as the next generation models under development to meet the future needs of ecosystem restoration efforts in South Florida. The multiagency efforts to develop and apply models have allowed the agencies to understand the complex hydrologic interactions, quantify appropriate performance measures, and use new technologies in simulation algorithms, software development, and GIS/database techniques to meet the future modeling needs of the ecosystem restoration programs. Copyright ?? 2011 Taylor & Francis Group, LLC.

A model using marginal efficiency of investment to analyze carbon and nitrogen interactions in terrestrial ecosystems (ACONITE Version 1)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-09-01

Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System Modeling community. However, there is little understanding of the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants. Here we describe a new, simple model of ecosystem C-N cycling and interactions (ACONITE), that builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C : N, N fixation, and plant C use efficiency) based on the outcome of assessments of the marginal change in net C or N uptake associated with a change in allocation of C or N to plant tissues. We simulated and evaluated steady-state ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C : N differed among the three ecosystem types (temperate deciduous < tropical evergreen < temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. Simulated N fixation at steady-state, calculated based on relative demand for N and the marginal return on C investment to acquire N, was an order of magnitude higher in the tropical forest than in the temperate forest, consistent with observations. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C : N. A parameter governing how photosynthesis scales with day length had the largest influence on total vegetation C, GPP, and NPP. Multiple parameters associated with photosynthesis, respiration, and N uptake influenced the rate of N fixation. Overall, our ability to constrain leaf area index and allow spatially and temporally variable leaf C : N can help address challenges simulating these properties in ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C-N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

Evapotranspiration estimates from eddy covariance towers and hydrologic modeling in managed forests in Northern Wisconsin, USA

Treesearch

Ge Sun; A. Noormets; J. Chen; S.G. McNulty

2008-01-01

Direct measurement of ecosystem evapotranspiration by the eddy covariance method and simulation modeling were employed to quantify the growing season (May–October) evapotranspiration (ET) of eight forest ecosystems representing a management gradient in dominant forest types and age classes in the Upper Great Lakes Region from 2002 to 2003. We measured net exchange of...

Modelling soil temperature and moisture and corresponding seasonality of photosynthesis and transpiration in a boreal spruce ecosystem

NASA Astrophysics Data System (ADS)

Wu, S. H.; Jansson, P.-E.

2013-02-01

Recovery of photosynthesis and transpiration is strongly restricted by low temperatures in air and/or soil during the transition period from winter to spring in boreal zones. The extent to which air temperature (Ta) and soil temperature (Ts) influence the seasonality of photosynthesis and transpiration of a boreal spruce ecosystem was investigated using a process-based ecosystem model (CoupModel) together with eddy covariance (EC) data from one eddy flux tower and nearby soil measurements at Knottåsen, Sweden. A Monte Carlo-based uncertainty method (GLUE) provided prior and posterior distributions of simulations representing a wide range of soil conditions and performance indicators. The simulated results showed sufficient flexibility to predict the measured cold and warm Ts in the moist and dry plots around the eddy flux tower. Moreover, the model presented a general ability to describe both biotic and abiotic processes for the Norway spruce stand. The dynamics of sensible heat fluxes were well described by the corresponding latent heat fluxes and net ecosystem exchange of CO2. The parameter ranges obtained are probably valid to represent regional characteristics of boreal conifer forests, but were not easy to constrain to a smaller range than that produced by the assumed prior distributions. Finally, neglecting the soil temperature response function resulted in fewer behavioural models and probably more compensatory errors in other response functions for regulating the seasonality of ecosystem fluxes.

Estimating ecosystem carbon change in the Conterminous United States based on 40 years of land-use change and disturbance

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Rayfield, B.; Liu, J.; Sherba, J.; Daniel, C.; Frid, L.; Wilson, T. S.; Zhu, Z.

2016-12-01

Since 1970, the combined changes in land use, land management, climate, and natural disturbances have dramatically altered land cover in the United States, resulting in the potential for significant changes in terrestrial carbon storage and flux between ecosystems and the atmosphere. Processes including urbanization, agricultural expansion and contraction, and forest management have had impacts - both positive and negative - on the amount of natural vegetation, the age structure of forests, and the amount of impervious cover. Anthropogenic change coupled with climate-driven changes in natural disturbance regimes, particularly the frequency and severity of wildfire, together determine the spatio-temporal patterns of land change and contribute to changing ecosystem carbon dynamics. Quantifying this effect and its associated uncertainties is fundamental to developing a rigorous and transparent carbon monitoring and assessment programs. However, large-scale systematic inventories of historical land change and their associated uncertainties are sparse. To address this need, we present a newly developed modeling framework, the Land Use and Carbon Scenario Simulator (LUCAS). The LUCAS model integrates readily available high quality, empirical land-change data into a stochastic space-time simulation model representing land change feedbacks on carbon cycling in terrestrial ecosystems. We applied the LUCAS model to estimate regional scale changes in carbon storage, atmospheric flux, and net biome production in 84 ecological regions of the conterminous United States for the period 1970-2015. The model was parameterized using a newly available set of high resolution (30 m) land-change data, compiled from Landsat remote sensing imagery, including estimates of uncertainty. Carbon flux parameters for each ecological region were derived from the IBIS dynamic global vegetation model with full carbon cycle accounting. This paper presents our initial findings describing regional and temporal changes and variability in carbon storage and flux resulting from land use change and disturbance between 1973 and 2015. Additionally, based on stochastic simulations we quantify and present key sources of uncertainty in the estimation of terrestrial ecosystem carbon dynamics.

Towards a Stochastic Predictive Understanding of Ecosystem Functioning and Resilience to Environmental Changes

NASA Astrophysics Data System (ADS)

Pappas, C.

2017-12-01

Terrestrial ecosystem processes respond differently to hydrometeorological variability across timescales, and so does our scientific understanding of the underlying mechanisms. Process-based modeling of ecosystem functioning is therefore challenging, especially when long-term predictions are envisioned. Here we analyze the statistical properties of hydrometeorological and ecosystem variability, i.e., the variability of ecosystem process related to vegetation carbon dynamics, from hourly to decadal timescales. 23 extra-tropical forest sites, covering different climatic zones and vegetation characteristics, are examined. Micrometeorological and reanalysis data of precipitation, air temperature, shortwave radiation and vapor pressure deficit are used to describe hydrometeorological variability. Ecosystem variability is quantified using long-term eddy covariance flux data of hourly net ecosystem exchange of CO2 between land surface and atmosphere, monthly remote sensing vegetation indices, annual tree-ring widths and above-ground biomass increment estimates. We find that across sites and timescales ecosystem variability is confined within a hydrometeorological envelope that describes the range of variability of the available resources, i.e., water and energy. Furthermore, ecosystem variability demonstrates long-term persistence, highlighting ecological memory and slow ecosystem recovery rates after disturbances. We derive an analytical model, combining deterministic harmonics and stochastic processes, that represents major mechanisms and uncertainties and mimics the observed pattern of hydrometeorological and ecosystem variability. This stochastic framework offers a parsimonious and mathematically tractable approach for modelling ecosystem functioning and for understanding its response and resilience to environmental changes. Furthermore, this framework reflects well the observed ecological memory, an inherent property of ecosystem functioning that is currently not captured by simulation results with process-based models. Our analysis offers a perspective for terrestrial ecosystem modelling, combining current process understanding with stochastic methods, and paves the way for new model-data integration opportunities in Earth system sciences.

Modeling Global Biogenic Emission of Isoprene: Exploration of Model Drivers

NASA Technical Reports Server (NTRS)

Alexander, Susan E.; Potter, Christopher S.; Coughlan, Joseph C.; Klooster, Steven A.; Lerdau, Manuel T.; Chatfield, Robert B.; Peterson, David L. (Technical Monitor)

1996-01-01

Vegetation provides the major source of isoprene emission to the atmosphere. We present a modeling approach to estimate global biogenic isoprene emission. The isoprene flux model is linked to a process-based computer simulation model of biogenic trace-gas fluxes that operates on scales that link regional and global data sets and ecosystem nutrient transformations Isoprene emission estimates are determined from estimates of ecosystem specific biomass, emission factors, and algorithms based on light and temperature. Our approach differs from an existing modeling framework by including the process-based global model for terrestrial ecosystem production, satellite derived ecosystem classification, and isoprene emission measurements from a tropical deciduous forest. We explore the sensitivity of model estimates to input parameters. The resulting emission products from the global 1 degree x 1 degree coverage provided by the satellite datasets and the process model allow flux estimations across large spatial scales and enable direct linkage to atmospheric models of trace-gas transport and transformation.

Understanding the Effect of Land Cover Classification on Model Estimates of Regional Carbon Cycling in the Boreal Forest Biome

NASA Technical Reports Server (NTRS)

Kimball, John; Kang, Sinkyu

2003-01-01

The original objectives of this proposed 3-year project were to: 1) quantify the respective contributions of land cover and disturbance (i.e., wild fire) to uncertainty associated with regional carbon source/sink estimates produced by a variety of boreal ecosystem models; 2) identify the model processes responsible for differences in simulated carbon source/sink patterns for the boreal forest; 3) validate model outputs using tower and field- based estimates of NEP and NPP; and 4) recommend/prioritize improvements to boreal ecosystem carbon models, which will better constrain regional source/sink estimates for atmospheric C02. These original objectives were subsequently distilled to fit within the constraints of a 1 -year study. This revised study involved a regional model intercomparison over the BOREAS study region involving Biome-BGC, and TEM (A.D. McGuire, UAF) ecosystem models. The major focus of these revised activities involved quantifying the sensitivity of regional model predictions associated with land cover classification uncertainties. We also evaluated the individual and combined effects of historical fire activity, historical atmospheric CO2 concentrations, and climate change on carbon and water flux simulations within the BOREAS study region.

Effects of ice storm on forest ecosystem of southern China in 2008 Shaoqiang Wang1, Lei Zhou1, Weimin Ju2, Kun Huang1 1Key Lab of Ecosystem Network Observation and Modeling, Institute of Geographical Sciences and Natural Resources Research, Beijing, 10010

NASA Astrophysics Data System (ADS)

Wang, Shaoqiang

2014-05-01

Evidence is mounting that an increase in extreme climate events has begun to occur worldwide during the recent decades, which affect biosphere function and biodiversity. Ecosystems returned to its original structures and functions to maintain its sustainability, which was closely dependent on ecosystem resilience. Understanding the resilience and recovery capacity of ecosystem to extreme climate events is essential to predicting future ecosystem responses to climate change. Given the overwhelming importance of this region in the overall carbon cycle of forest ecosystems in China, south China suffered a destructive ice storm in 2008. In this study, we used the number of freezing day and a process-based model (Boreal Ecosystem Productivity Simulator, BEPS) to characterize the spatial distribution of ice storm region in southeastern China and explore the impacts on carbon cycle of forest ecosystem over the past decade. The ecosystem variables, i.e. Net primary productivity (NPP), Evapotranspiration (ET), and Water use efficiency (WUE, the ratio of NPP to ET) from the outputs of BEPS models were used to detect the resistance and resilience of forest ecosystem in southern China. The pattern of ice storm-induced forest productivity widespread decline was closely related to the number of freezing day during the ice storm period. The NPP of forest area suffered heavy ice storm returned to normal status after five months with high temperature and ample moisture, indicated a high resilience of subtropical forest in China. The long-term changes of forest WUE remain stable, behaving an inherent sensitivity of ecosystem to extreme climate events. In addition, ground visits suggested that the recovery of forest productivity was attributed to rapid growth of understory. Understanding the variability and recovery threshold of ecosystem following extreme climate events help us to better simulate and predict the variability of ecosystem structure and function under current and future climate change.

Exploration of an urban lake management model to simulate chlorine interference based on the ecological relationships among aquatic species.

PubMed

Yan, Zhiqiang; Wang, Yafei; Wu, Di; Xia, Beicheng

2018-05-29

In eutrophic lakes, algae are known to be sensitive to chlorine, but the impact of chlorine on the wider ecosystem has not been investigated. To quantitatively investigate the effects of chlorine on the urban lake ecosystem and analyze the changes in the aquatic ecosystem structure, a dynamic response model of aquatic species to chlorine was constructed based on the biomass density dynamics of aquatic species of submerged macrophytes, phytoplankton, zooplankton, periphyton, and benthos. The parameters were calibrated using data from the literature and two simulative experiments. The model was then validated using field data from an urban lake with a surface area of approximately 8000 m 2 located in the downtown area of Guangzhou, South China. The correlation coefficient (R), root mean square error-observations standard deviation ratio (RSR) and index of agreement (IOA) were used to evaluate the accuracy and reliability of the model and the results were consistent with the observations (0.446 R < 0.985, RSR < 0.7, IOA > 0.6). Comparisons between the simulated and observed trends confirmed the feasibility of using this model to investigate the dynamics of aquatic species under chlorine interference. The model can help managers apply a modest amount of chlorine to control eutrophication and provides scientific support for the management of urban lakes.

Responses of ecosystem carbon cycling to climate change treatments along an elevation gradient

USGS Publications Warehouse

Wu, Zhuoting; Koch, George W.; Dijkstra, Paul; Bowker, Matthew A.; Hungate, Bruce A.

2011-01-01

Global temperature increases and precipitation changes are both expected to alter ecosystem carbon (C) cycling. We tested responses of ecosystem C cycling to simulated climate change using field manipulations of temperature and precipitation across a range of grass-dominated ecosystems along an elevation gradient in northern Arizona. In 2002, we transplanted intact plant–soil mesocosms to simulate warming and used passive interceptors and collectors to manipulate precipitation. We measured daytime ecosystem respiration (ER) and net ecosystem C exchange throughout the growing season in 2008 and 2009. Warming generally stimulated ER and photosynthesis, but had variable effects on daytime net C exchange. Increased precipitation stimulated ecosystem C cycling only in the driest ecosystem at the lowest elevation, whereas decreased precipitation showed no effects on ecosystem C cycling across all ecosystems. No significant interaction between temperature and precipitation treatments was observed. Structural equation modeling revealed that in the wetter-than-average year of 2008, changes in ecosystem C cycling were more strongly affected by warming-induced reduction in soil moisture than by altered precipitation. In contrast, during the drier year of 2009, warming induced increase in soil temperature rather than changes in soil moisture determined ecosystem C cycling. Our findings suggest that warming exerted the strongest influence on ecosystem C cycling in both years, by modulating soil moisture in the wet year and soil temperature in the dry year.

Mathematical modeling relevant to closed artificial ecosystems

USGS Publications Warehouse

DeAngelis, D.L.

2003-01-01

The mathematical modeling of ecosystems has contributed much to the understanding of the dynamics of such systems. Ecosystems can include not only the natural variety, but also artificial systems designed and controlled by humans. These can range from agricultural systems and activated sludge plants, down to mesocosms, microcosms, and aquaria, which may have practical or research applications. Some purposes may require the design of systems that are completely closed, as far as material cycling is concerned. In all cases, mathematical modeling can help not only to understand the dynamics of the system, but also to design methods of control to keep the system operating in desired ranges. This paper reviews mathematical modeling relevant to the simulation and control of closed or semi-closed artificial ecosystems designed for biological production and recycling in applications in space. Published by Elsevier Science Ltd on behalf of COSPAR.

Grassland Smoke Emission Measurement Supporting Multi-Modeling Framework Simulation of Rangeland Burning Practices for the Kansas Flint Hills Fire Experiment

EPA Science Inventory

Historically, frequent wildfires were essential for the maintenance of native prairie fire adapted ecosystems. Today prescribed fires are used to control invasive woody species and potentially improve forage production in these same prairie ecosystems for the beef-cattle industry...

An Ecosystem Simulation Model for Methane Production and Emission from Wetlands

NASA Technical Reports Server (NTRS)

Potter, C. S.; Peterson, David L. (Technical Monitor)

1997-01-01

Previous experimental studies suggest that methane emission from wetland is influenced by multiple interactive pathways of gas production and transport through soil and sediment layers to the atmosphere. The objective of this study is to evaluate a new simulation model of methane production and emission in wetland soils that was developed initially to help identify key processes that regulate methanogenesis and net flux of CH4 to the air, but which is designed ultimately for regional simulation using remotely sensed inputs for land cover characteristics. The foundation for these computer simulations is based on a well-documented model (CASA) of ecosystem production and carbon cycling in the terrestrial blaspheme. Modifications to represent flooded wetland soils and anaerobic decomposition include three new sub-models for: (1) layered soil temperature and water table depth (WTD) as a function of daily climate drivers, (2) CH4 production within the anoxic soil layer as a function of WTD and CO2 production under poorly drained conditions, and (3) CH4 gaseous transport pathways (molecular diffusion, ebullition, and plant vascular transport) as a function of WTD and ecosystem type. The model was applied and tested using climate and ecological data to characterize tundra wetland sites near Fairbanks, Alaska studied previously by Whalen and Reeburgh. Comparison of model predictions to measurements of soil temperature and thaw depth, water-table depth, and CH4 emissions over a two year period suggest that inter-site differences in soil physical conditions and methane fluxes could be reproduced accurately for selected periods. Day-to-day comparison of predicted emissions to measured CH4 flux rates reveals good agreement during the early part of the thaw season, but the model tends to underestimate production of CH4 during the months of July and August in both test years. Important seasonal effects, including that of falling WTD during these periods, are apparently overlooked in the model formulation. Nevertheless, reasonably close agreement was achieved between the model's mean daily and seasonal estimates of CH4 flux and observed emission rates for northern wetland ecosystems. Several features of the model are identified as crucial to more accurate prediction of wetland methane emission, including the capacity to incorporate influences of localized topographic and hydrologic features on site-specific soil temperature and WTD dynamics, and mechanistic simulation of methane emission transport pathways from within the soil profile.

Ecological Assimilation of Land and Climate Observations - the EALCO model

NASA Astrophysics Data System (ADS)

Wang, S.; Zhang, Y.; Trishchenko, A.

2004-05-01

Ecosystems are intrinsically dynamic and interact with climate at a highly integrated level. Climate variables are the main driving factors in controlling the ecosystem physical, physiological, and biogeochemical processes including energy balance, water balance, photosynthesis, respiration, and nutrient cycling. On the other hand, ecosystems function as an integrity and feedback on the climate system through their control on surface radiation balance, energy partitioning, and greenhouse gases exchange. To improve our capability in climate change impact assessment, a comprehensive ecosystem model is required to address the many interactions between climate change and ecosystems. In addition, different ecosystems can have very different responses to the climate change and its variation. To provide more scientific support for ecosystem impact assessment at national scale, it is imperative that ecosystem models have the capability of assimilating the large scale geospatial information including satellite observations, GIS datasets, and climate model outputs or reanalysis. The EALCO model (Ecological Assimilation of Land and Climate Observations) is developed for such purposes. EALCO includes the comprehensive interactions among ecosystem processes and climate, and assimilates a variety of remote sensing products and GIS database. It provides both national and local scale model outputs for ecosystem responses to climate change including radiation and energy balances, water conditions and hydrological cycles, carbon sequestration and greenhouse gas exchange, and nutrient (N) cycling. These results form the foundation for the assessment of climate change impact on ecosystems, their services, and adaptation options. In this poster, the main algorithms for the radiation, energy, water, carbon, and nitrogen simulations were diagrammed. Sample input data layers at Canada national scale were illustrated. Model outputs including the Canada wide spatial distributions of net radiation, evapotranspiration, gross primary production, net primary production, and net ecosystem production were discussed.

Simulated effects of nitrogen saturation the global carbon budget using the IBIS model

USGS Publications Warehouse

Lu, Xuehe; Jiang, Hong; Liu, Jinxun; Zhang, Xiuying; Jin, Jiaxin; Zhu, Qiuan; Zhang, Zhen; Peng, Changhui

2016-01-01

Over the past 100 years, human activity has greatly changed the rate of atmospheric N (nitrogen) deposition in terrestrial ecosystems, resulting in N saturation in some regions of the world. The contribution of N saturation to the global carbon budget remains uncertain due to the complicated nature of C-N (carbon-nitrogen) interactions and diverse geography. Although N deposition is included in most terrestrial ecosystem models, the effect of N saturation is frequently overlooked. In this study, the IBIS (Integrated BIosphere Simulator) was used to simulate the global-scale effects of N saturation during the period 1961–2009. The results of this model indicate that N saturation reduced global NPP (Net Primary Productivity) and NEP (Net Ecosystem Productivity) by 0.26 and 0.03 Pg C yr−1, respectively. The negative effects of N saturation on carbon sequestration occurred primarily in temperate forests and grasslands. In response to elevated CO2 levels, global N turnover slowed due to increased biomass growth, resulting in a decline in soil mineral N. These changes in N cycling reduced the impact of N saturation on the global carbon budget. However, elevated N deposition in certain regions may further alter N saturation and C-N coupling.

Model-experiment synthesis at two FACE sites in the southeastern US. Forest ecosystem responses to elevated CO[2]. (Invited)

NASA Astrophysics Data System (ADS)

Walker, A. P.; Zaehle, S.; De Kauwe, M. G.; Medlyn, B. E.; Dietze, M.; Hickler, T.; Iversen, C. M.; Jain, A. K.; Luo, Y.; McCarthy, H. R.; Parton, W. J.; Prentice, C.; Thornton, P. E.; Wang, S.; Wang, Y.; Warlind, D.; Warren, J.; Weng, E.; Hanson, P. J.; Oren, R.; Norby, R. J.

2013-12-01

Ecosystem observations from two long-term Free-Air CO[2] Enrichment (FACE) experiments (Duke forest and Oak Ridge forest) were used to evaluate the assumptions of 11 terrestrial ecosystem models and the consequences of those assumptions for the responses of ecosystem water, carbon (C) and nitrogen (N) fluxes to elevated CO[2] (eCO[2]). Nitrogen dynamics were the main constraint on simulated productivity responses to eCO[2]. At Oak Ridge some models reproduced the declining response of C and N fluxes, while at Duke none of the models were able to maintain the observed sustained responses. C and N cycles are coupled through a number of complex interactions, which causes uncertainty in model simulations in multiple ways. Nonetheless, the major difference between models and experiments was a larger than observed increase in N-use efficiency and lower than observed response of N uptake. The results indicate that at Duke there were mechanisms by which trees accessed additional N in response to eCO[2] that were not represented in the ecosystem models, and which did not operate with the same efficiency at Oak Ridge. Sequestration of the additional productivity under eCO[2] into forest biomass depended largely on C allocation. Allocation assumptions were classified into three main categories--fixed partitioning coefficients, functional relationships and a partial (leaf allocation only) optimisation. The assumption which best constrained model results was a functional relationship between leaf area and sapwood area (pipe-model) and increased root allocation when nitrogen or water were limiting. Both, productivity and allocation responses to eCO[2] determined the ecosystem-level response of LAI, which together with the response of stomatal conductance (and hence water-use efficiency; WUE) determined the ecosystem response of transpiration. Differences in the WUE response across models were related to the representation of the relationship of stomatal conductance to CO[2] and the relative importance of the combined boundary and aerodynamic resistances in the total resistance to leaf-atmosphere water transport.

A 3D radiative transfer model based on lidar data and its application on hydrological and ecosystem modeling

NASA Astrophysics Data System (ADS)

Li, W.; Su, Y.; Harmon, T. C.; Guo, Q.

2013-12-01

Light Detection and Ranging (lidar) is an optical remote sensing technology that measures properties of scattered light to find range and/or other information of a distant object. Due to its ability to generate 3-dimensional data with high spatial resolution and accuracy, lidar technology is being increasingly used in ecology, geography, geology, geomorphology, seismology, remote sensing, and atmospheric physics. In this study we construct a 3-dimentional (3D) radiative transfer model (RTM) using lidar data to simulate the spatial distribution of solar radiation (direct and diffuse) on the surface of water and mountain forests. The model includes three sub-models: a light model simulating the light source, a sensor model simulating the camera, and a scene model simulating the landscape. We use ground-based and airborne lidar data to characterize the 3D structure of the study area, and generate a detailed 3D scene model. The interactions between light and object are simulated using the Monte Carlo Ray Tracing (MCRT) method. A large number of rays are generated from the light source. For each individual ray, the full traveling path is traced until it is absorbed or escapes from the scene boundary. By locating the sensor at different positions and directions, we can simulate the spatial distribution of solar energy at the ground, vegetation and water surfaces. These outputs can then be incorporated into meteorological drivers for hydrologic and energy balance models to improve our understanding of hydrologic processes and ecosystem functions.

Soil carbon management in large-scale Earth system modelling: implications for crop yields and nitrogen leaching

NASA Astrophysics Data System (ADS)

Olin, S.; Lindeskog, M.; Pugh, T. A. M.; Schurgers, G.; Wårlind, D.; Mishurov, M.; Zaehle, S.; Stocker, B. D.; Smith, B.; Arneth, A.

2015-11-01

Croplands are vital ecosystems for human well-being and provide important ecosystem services such as crop yields, retention of nitrogen and carbon storage. On large (regional to global)-scale levels, assessment of how these different services will vary in space and time, especially in response to cropland management, are scarce. We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land-use-enabled dynamic vegetation model LPJ-GUESS (Lund-Potsdam-Jena General Ecosystem Simulator). Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land-use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. Our model experiments allow us to investigate trade-offs between these ecosystem services that can be provided from agricultural fields. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP (Representative Concentration Pathway) 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till management and cover crops proposed in previous studies is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change and the effects these have on terrestrial biogeochemical cycles.

[Structure and function of Fenshuijiang Reservoir ecosystem based on the analysis with Ecopath model].

PubMed

Wu, Zhen; Jia, Pei-Qiao; Hu, Zhong-Jun; Chen, Li-Qiao; Gu, Zhi-Min; Liu, Qi-Gen

2012-03-01

Based on the 2008-2009 survey data of fishery resources and eco-environment of Fenshuijiang Reservoir, a mass balance model for the Reservoir ecosystem was constructed by Ecopath with Ecosim software. The model was composed of 14 functional groups, including silver carp, bighead carp, Hemibarbus maculates, Cutler alburnus, Microlepis and other fishes, Oligochaeta, aquatic insect, zooplankton, phytoplankton, and organic detritus, etc. , being able to better simulate Fenshuijiang Reservoir ecosystem. In this ecosystem, there were five trophic levels (TLs), and the nutrient flow mainly occurred in the first three TLs. Grazing and detritus food chains were the main energy flows in the ecosystem, but the food web was simpler and susceptible to be disturbed by outer environment. The transfer efficiency at lower TLs was relatively low, indicating that the ecosystem had a lower capability in energy utilization, and the excessive stock of nutrients in the ecosystem could lead to eutrophication. The lower connectance index, system omnivory index, Finn' s cycled index, and Finn's mean path length demonstrated that the ecosystem was unstable, while the high ecosystem property indices such as Pp/R and Pp/B showed that the ecosystem was immature and highly productive. It was suggested that Fenshuijiang Reservoir was still a developing new reservoir ecosystem, with a very short history and comparatively high primary productivity.

Ecological Network Indicators of Ecosystem Status and Change in the Baltic Sea

PubMed Central

Tomczak, Maciej T.; Heymans, Johanna J.; Yletyinen, Johanna; Niiranen, Susa; Otto, Saskia A.; Blenckner, Thorsten

2013-01-01

Several marine ecosystems under anthropogenic pressure have experienced shifts from one ecological state to another. In the central Baltic Sea, the regime shift of the 1980s has been associated with food-web reorganization and redirection of energy flow pathways. These long-term dynamics from 1974 to 2006 have been simulated here using a food-web model forced by climate and fishing. Ecological network analysis was performed to calculate indices of ecosystem change. The model replicated the regime shift. The analyses of indicators suggested that the system’s resilience was higher prior to 1988 and lower thereafter. The ecosystem topology also changed from a web-like structure to a linearized food-web. PMID:24116045

Simulation of Regionally Ecological Land Based on a Cellular Automation Model: A Case Study of Beijing, China

PubMed Central

Xie, Hualin; Kung, Chih-Chun; Zhang, Yanting; Li, Xiubin

2012-01-01

Ecological land is like the “liver” of a city and is very useful to public health. Ecological land change is a spatially dynamic non-linear process under the interaction between natural and anthropogenic factors at different scales. In this study, by setting up natural development scenario, object orientation scenario and ecosystem priority scenario, a Cellular Automation (CA) model has been established to simulate the evolution pattern of ecological land in Beijing in the year 2020. Under the natural development scenario, most of ecological land will be replaced by construction land and crop land. But under the scenarios of object orientation and ecosystem priority, the ecological land area will increase, especially under the scenario of ecosystem priority. When considering the factors such as total area of ecological land, loss of key ecological land and spatial patterns of land use, the scenarios from priority to inferiority are ecosystem priority, object orientation and natural development, so future land management policies in Beijing should be focused on conversion of cropland to forest, wetland protection and prohibition of exploitation of natural protection zones, water source areas and forest parks to maintain the safety of the regional ecosystem. PMID:23066410

Simulation of regionally ecological land based on a cellular automation model: a case study of Beijing, China.

PubMed

Xie, Hualin; Kung, Chih-Chun; Zhang, Yanting; Li, Xiubin

2012-08-01

Ecological land is like the "liver" of a city and is very useful to public health. Ecological land change is a spatially dynamic non-linear process under the interaction between natural and anthropogenic factors at different scales. In this study, by setting up natural development scenario, object orientation scenario and ecosystem priority scenario, a Cellular Automation (CA) model has been established to simulate the evolution pattern of ecological land in Beijing in the year 2020. Under the natural development scenario, most of ecological land will be replaced by construction land and crop land. But under the scenarios of object orientation and ecosystem priority, the ecological land area will increase, especially under the scenario of ecosystem priority. When considering the factors such as total area of ecological land, loss of key ecological land and spatial patterns of land use, the scenarios from priority to inferiority are ecosystem priority, object orientation and natural development, so future land management policies in Beijing should be focused on conversion of cropland to forest, wetland protection and prohibition of exploitation of natural protection zones, water source areas and forest parks to maintain the safety of the regional ecosystem.

Modeling soil thermal and carbon dynamics of a fire chronosequence in interior Alaska

USGS Publications Warehouse

Zhuang, Q.; McGuire, A.D.; O'Neill, K. P.; Harden, J.W.; Romanovsky, V.E.; Yarie, J.

2003-01-01

In this study, the dynamics of soil thermal, hydrologic, and ecosystem processes were coupled to project how the carbon budgets of boreal forests will respond to changes in atmospheric CO2, climate, and fire disturbance. The ability of the model to simulate gross primary production and ecosystem respiration was verified for a mature black spruce ecosystem in Canada, the age-dependent pattern of the simulated vegetation carbon was verified with inventory data on aboveground growth of Alaskan black spruce forests, and the model was applied to a postfire chronosequence in interior Alaska. The comparison between the simulated soil temperature and field-based estimates during the growing season (May to September) of 1997 revealed that the model was able to accurately simulate monthly temperatures at 10 cm (R > 0.93) for control and burned stands of the fire chronosequence. Similarly, the simulated and field-based estimates of soil respiration for control and burned stands were correlated (R = 0.84 and 0.74 for control and burned stands, respectively). The simulated and observed decadal to century-scale dynamics of soil temperature and carbon dynamics, which are represented by mean monthly values of these variables during the growing season, were correlated among stands (R = 0.93 and 0.71 for soil temperature at 20- and 10-cm depths, R = 0.95 and 0.91 for soil respiration and soil carbon, respectively). Sensitivity analyses indicate that along with differences in fire and climate history a number of other factors influence the response of carbon dynamics to fire disturbance. These factors include nitrogen fixation, the growth of moss, changes in the depth of the organic layer, soil drainage, and fire severity.

Simulations of forest mortality in Colorado River basin

NASA Astrophysics Data System (ADS)

Wei, L.; Xu, C.; Johnson, D. J.; Zhou, H.; McDowell, N.

2017-12-01

The Colorado River Basin (CRB) had experienced multiple severe forest mortality events under the recent changing climate. Such forest mortality events may have great impacts on ecosystem services and water budget of the watershed. It is hence important to estimate and predict the forest mortality in the CRB with climate change. We simulated forest mortality in the CRB with a model of plant hydraulics within the FATES (the Functionally Assembled Terrestrial Ecosystem Simulator) coupled to the DOE Earth System model (ACME: Accelerated Climate Model of Energy) at a 0.5 x 0.5 degree resolution. Moreover, we incorporated a stable carbon isotope (δ13C) module to ACME(FATE) and used it as a new predictor of forest mortality. The δ13C values of plants with C3 photosynthetic pathway (almost all trees are C3 plants) can indicate the water stress plants experiencing (the more intensive stress, the less negative δ13C value). We set a δ13C threshold in model simulation, above which forest mortality initiates. We validate the mortality simulations with field data based on Forest Inventory and Analysis (FIA) data, which were aggregated into the same spatial resolution as the model simulations. Different mortality schemes in the model (carbon starvation, hydraulic failure, and δ13C) were tested and compared. Each scheme demonstrated its strength and the plant hydraulics module provided more reliable simulations of forest mortality than the earlier ACME(FATE) version. Further testing is required for better forest mortality modelling.

Simulating forest productivity and surface-atmosphere carbon exchange in the BOREAS study region.

PubMed

Kimball, John S.; Thornton, Peter E.; White, Mike A.; Running, Steven W.

1997-01-01

A process-based, general ecosystem model (BIOME-BGC) was used to simulate daily gross primary production, maintenance and heterotrophic respiration, net primary production and net ecosystem carbon exchange of boreal aspen, jack pine and black spruce stands. Model simulations of daily net carbon exchange of the ecosystem (NEE) explained 51.7% (SE = 1.32 g C m(-2) day(-1)) of the variance in daily NEE derived from stand eddy flux measurements of CO(2) during 1994. Differences between measured and simulated results were attributed to several factors including difficulties associated with measuring nighttime CO(2) fluxes and model assumptions of site homogeneity. However, comparisons between simulations and field data improved markedly at coarser time-scales. Model simulations explained 66.1% (SE = 0.97 g C m(-2) day(-1)) of the variance in measured NEE when 5-day means of daily results were compared. Annual simulations of aboveground net primary production ranged from 0.6-2.4 Mg C ha(-1) year(-1) and were concurrent with results derived from tree increment core measurements and allometric equations. Model simulations showed that all of the sites were net sinks (0.1-4.1 Mg C ha(-1) year(-1)) of atmospheric carbon for 1994. Older conifer stands showed narrow margins between uptake of carbon by net photosynthesis and carbon release through respiration. Younger stands were more productive than older stands, primarily because of lower maintenance respiration costs. However, all sites appeared to be less productive than temperate forests. Productivity simulations were strongly linked to stand morphology and site conditions. Old jack pine and aspen stands showed decreased productivity in response to simulated low soil water contents near the end of the 1994 growing season. Compared with the aspen stand, the jack pine stand appeared better adapted to conserve soil water through lower daily evapotranspiration losses but also exhibited a narrower margin between daily net photosynthesis and respiration. Stands subjected to water stress during the growing season may exist on the edge between being annual sources or sinks for atmospheric carbon.

On the additional information content of hyperspectral remote sensing data for estimating ecosystem carbon dioxde and energy exchange

NASA Astrophysics Data System (ADS)

Wohlfahrt, Georg; Hammerle, Albin; Tomelleri, Enrico

2015-04-01

Radiation reflected back from an ecosystem carries a spectral signature resulting from the interaction of radiation with the vegetation canopy and the underlying soil and thus allows drawing conclusions about the structure and functioning of an ecosystem. When this information is linked to a model of the leaf CO2 exchange, the ecosystem-scale CO2 exchange can be simulated. A well-known and very simplistic example for this approach is the light-use efficiency (LUE) model proposed by Monteith which links the flux of absorbed photosynthetically active radiation times a LUE parameter, both of which may be estimated based on remote sensing data, to predict the ecosystem gross photosynthesis. Here we explore the ability of a more elaborate approach by using near-surface remote sensing of hyperspectral reflected radiation, eddy covariance CO2 and energy flux measurements and a coupled radiative transfer and soil-vegetation-atmosphere-transfer (SVAT) model. Our main objective is to understand to what degree the joint assimilation of hyperspectral reflected radiation and eddy covariance flux measurements into the model helps to better constrain model parameters. To this end we use the SCOPE model, a combination of the well-known PROSAIL model and a SVAT model, and the Bayesian inversion algorithm DREAM. In order to explicitly link reflectance in the visible light and the leaf CO2 exchange, a novel parameterisation of the maximum carboxylation capacity parameter (Vcmax) on the leaf a+b chlorophyll content parameter of PROSAIL is introduced. Results are discussed with respect to the additional information content the hyperspectral data yield for simulating canopy photosynthesis.

Chapter 8: Simulating mortality from forest insects and diseases

Treesearch

Alan A. Ager; Jane L. Hayes; Craig L. Schmitt

2004-01-01

We describe methods for incorporating the effects of insects and diseases on coniferous forests into forest simulation models and discuss options for including this capability in the modeling work of the Interior Northwest Landscape Analysis System (INLAS) project. Insects and diseases are major disturbance agents in forested ecosystems in the Western United States,...

One-Dimensional Coupled Ecosystem-Carbon Flux Model for the Simulation of Biogeochemical Parameters at Ocean Weather Station P

NASA Technical Reports Server (NTRS)

Signorini, S.; McClain, C.; Christian, J.; Wong, C. S.

2000-01-01

In this Technical Publication, we describe the model functionality and analyze its application to the seasonal and interannual variations of phytoplankton, nutrients, pCO2 and CO2 concentrations in the eastern subarctic Pacific at Ocean Weather Station P (OWSP, 50 deg. N 145 deg. W). We use a verified one-dimensional ecosystem model, coupled with newly incorporated carbon flux and carbon chemistry components, to simulate 22 years (1958-1980) of pCO2 and CO2 variability at Ocean Weather Station P (OWS P). This relatively long period of simulation verifies and extends the findings of previous studies using an explicit approach for the biological component and realistic coupling with the carbon flux dynamics. The slow currents and the horizontally homogeneous ocean in the subarctic Pacific make OWS P one of the best available candidates for modeling the chemistry of the upper ocean in one dimension. The chlorophyll and ocean currents composite for 1998 illustrates this premise. The chlorophyll concentration map was derived from SeaWiFS data and the currents are from an OGCM simulation (from R. Murtugudde).

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Anderson, C.; Bond-Lamberty, B. P.; Huang, M.; Xu, Y.; Stegen, J.

2016-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

Using Imaging Spectrometry measurements of Ecosystem Composition to constrain Regional Predictions of Carbon, Water and Energy Fluxes

NASA Astrophysics Data System (ADS)

Antonarakis, A. S.; Bogan, S.; Moorcroft, P. R.

2017-12-01

Ecosystem composition is a key attribute of terrestrial ecosystems, influencing the fluxes of carbon, water, and energy between the land surface and the atmosphere. The description of current ecosystem composition has traditionally come from relatively few ground-based inventories of the plant canopy, but are spatially limited and do not provide a comprehensive picture of ecosystem composition at regional or global scales. In this analysis, imaging spectrometry measurements, collected as part of the HyspIRI Preparatory Mission, are used to provide spatially-resolved estimates of plant functional type composition providing an important constraint on terrestrial biosphere model predictions of carbon, water and energy fluxes across the heterogeneous landscapes of the Californian Sierras. These landscapes include oak savannas, mid-elevation mixed pines, fir-cedar forests, and high elevation pines. Our results show that imaging spectrometry measurements can be successfully used to estimate regional-scale variation in ecosystem composition and resulting spatial heterogeneity in patterns of carbon, water and energy fluxes and ecosystem dynamics. Simulations at four flux tower sites within the study region yield patterns of seasonal and inter-annual variation in carbon and water fluxes that have comparable accuracy to simulations initialized from ground-based inventory measurements. Finally, results indicate that during the 2012-2015 Californian drought, regional net carbon fluxes fell by 84%, evaporation and transpiration fluxes fell by 53% and 33% respectively, and sensible heat increase by 51%. This study provides a framework for assimilating near-future global satellite imagery estimates of ecosystem composition with terrestrial biosphere models, constraining and improving their predictions of large-scale ecosystem dynamics and functioning.

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.

Modeling the impact of watershed management policies on marine ecosystem services with application to Hood Canal, WA, USA

NASA Astrophysics Data System (ADS)

Sutherland, D. A.; Kim, C.; Marsik, M.; Spiridonov, G.; Toft, J.; Ruckelshaus, M.; Guerry, A.; Plummer, M.

2011-12-01

Humans obtain numerous benefits from marine ecosystems, including fish to eat; mitigation of storm damage; nutrient and water cycling and primary production; and cultural, aesthetic and recreational values. However, managing these benefits, or ecosystem services, in the marine world relies on an integrated approach that accounts for both marine and watershed activities. Here we present the results of a set of simple, physically-based, and spatially-explicit models that quantify the effects of terrestrial activities on marine ecosystem services. Specifically, we model the circulation and water quality of Hood Canal, WA, USA, a fjord system in Puget Sound where multiple human uses of the nearshore ecosystem (e.g., shellfish aquaculture, recreational Dungeness crab and shellfish harvest) can be compromised when water quality is poor (e.g., hypoxia, excessive non-point source pollution). Linked to the estuarine water quality model is a terrestrial hydrology model that simulates streamflow and nutrient loading, so land cover and climate changes in watersheds can be reflected in the marine environment. In addition, a shellfish aquaculture model is linked to the water quality model to test the sensitivity of the ecosystem service and its value to both terrestrial and marine activities. The modeling framework is general and will be publicly available, allowing easy comparisons of watershed impacts on marine ecosystem services across multiple scales and regions.

A generic framework for individual-based modelling and physical-biological interaction

PubMed Central

2018-01-01

The increased availability of high-resolution ocean data globally has enabled more detailed analyses of physical-biological interactions and their consequences to the ecosystem. We present IBMlib, which is a versatile, portable and computationally effective framework for conducting Lagrangian simulations in the marine environment. The purpose of the framework is to handle complex individual-level biological models of organisms, combined with realistic 3D oceanographic model of physics and biogeochemistry describing the environment of the organisms without assumptions about spatial or temporal scales. The open-source framework features a minimal robust interface to facilitate the coupling between individual-level biological models and oceanographic models, and we provide application examples including forward/backward simulations, habitat connectivity calculations, assessing ocean conditions, comparison of physical circulation models, model ensemble runs and recently posterior Eulerian simulations using the IBMlib framework. We present the code design ideas behind the longevity of the code, our implementation experiences, as well as code performance benchmarking. The framework may contribute substantially to progresses in representing, understanding, predicting and eventually managing marine ecosystems. PMID:29351280

Emergent Global Patterns of Ecosystem Structure and Function from a Mechanistic General Ecosystem Model

PubMed Central

Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J.; Scharlemann, Jörn P. W.; Purves, Drew W.

2014-01-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures. PMID:24756001

Emergent global patterns of ecosystem structure and function from a mechanistic general ecosystem model.

PubMed

Harfoot, Michael B J; Newbold, Tim; Tittensor, Derek P; Emmott, Stephen; Hutton, Jon; Lyutsarev, Vassily; Smith, Matthew J; Scharlemann, Jörn P W; Purves, Drew W

2014-04-01

Anthropogenic activities are causing widespread degradation of ecosystems worldwide, threatening the ecosystem services upon which all human life depends. Improved understanding of this degradation is urgently needed to improve avoidance and mitigation measures. One tool to assist these efforts is predictive models of ecosystem structure and function that are mechanistic: based on fundamental ecological principles. Here we present the first mechanistic General Ecosystem Model (GEM) of ecosystem structure and function that is both global and applies in all terrestrial and marine environments. Functional forms and parameter values were derived from the theoretical and empirical literature where possible. Simulations of the fate of all organisms with body masses between 10 µg and 150,000 kg (a range of 14 orders of magnitude) across the globe led to emergent properties at individual (e.g., growth rate), community (e.g., biomass turnover rates), ecosystem (e.g., trophic pyramids), and macroecological scales (e.g., global patterns of trophic structure) that are in general agreement with current data and theory. These properties emerged from our encoding of the biology of, and interactions among, individual organisms without any direct constraints on the properties themselves. Our results indicate that ecologists have gathered sufficient information to begin to build realistic, global, and mechanistic models of ecosystems, capable of predicting a diverse range of ecosystem properties and their response to human pressures.

Ecosystem service impacts of future changes in CO2, climate, and land use as simulated by a coupled vegetation/land-use model system

NASA Astrophysics Data System (ADS)

Rabin, S. S.; Alexander, P.; Henry, R.; Anthoni, P.; Pugh, T.; Rounsevell, M.; Arneth, A.

2017-12-01

In a future of increasing atmospheric carbon dioxide (CO2) concentrations, changing climate, increasing human populations, and changing socioeconomic dynamics, the global agricultural system will need to adapt in order to feed the world. Global modeling can help to explore what these adaptations will look like, and their potential impacts on ecosystem services. To do so, however, the complex interconnections among the atmosphere, terrestrial ecosystems, and society mean that these various parts of the Earth system must be examined as an interconnected whole. With the goal of answering these questions, a model system has been developed that couples a biologically-representative global vegetation model, LPJ-GUESS, with the PLUMv2 land use model. LPJ-GUESS first simulates—at 0.5º resolution across the world—the potential yield of various crops and pasture under a range of management intensities for a time step given its atmospheric CO2 level and climatic forcings. These potential yield simulations are fed into PLUMv2, which uses them in conjunction with endogenous agricultural commodity demand and prices to produce land use and management inputs (fertilizer and irrigation water) at a sub-national level for the next time step. This process is performed through 2100 for a range of future climate and societal scenarios—the Representative Concentration Pathways (RCPs) and the Shared Socioeconomic Pathways (SSPs), respectively—providing a thorough exploration of possible trajectories of land use and land cover change. The land use projections produced by PLUMv2 are fed back into LPJ-GUESS to simulate the future impacts of land use change, along with increasing CO2 and climate change, on terrestrial ecosystems. This integrated analysis examines the resulting impacts on regulating and provisioning ecosystem services affecting biophysics (albedo); carbon, nitrogen, and water cycling; and the emission of biogenic volatile organic compounds (BVOCs).

Simulating Carbon cycle and phenology in complex forests using a multi-layer process based ecosystem model; evaluation and use of 3D-CMCC-Forest Ecosystem Model in a deciduous and an evergreen neighboring forests, within the area of Brasschaat (Be)

NASA Astrophysics Data System (ADS)

Marconi, S.; Collalti, A.; Santini, M.; Valentini, R.

2013-12-01

3D-CMCC-Forest Ecosystem Model is a process based model formerly developed for complex forest ecosystems to estimate growth, water and carbon cycles, phenology and competition processes on a daily/monthly time scale. The Model integrates some characteristics of the functional-structural tree models with the robustness of the light use efficiency approach. It treats different heights, ages and species as discrete classes, in competition for light (vertical structure) and space (horizontal structure). The present work evaluates the results of the recently developed daily version of 3D-CMCC-FEM for two neighboring different even aged and mono specific study cases. The former is a heterogeneous Pedunculate oak forest (Quercus robur L. ), the latter a more homogeneous Scot pine forest (Pinus sylvestris L.). The multi-layer approach has been evaluated against a series of simplified versions to determine whether the improved model complexity in canopy structure definition increases its predictive ability. Results show that a more complex structure (three height layers) should be preferable to simulate heterogeneous scenarios (Pedunculate oak stand), where heights distribution within the canopy justify the distinction in dominant, dominated and sub-dominated layers. On the contrary, it seems that using a multi-layer approach for more homogeneous stands (Scot pine stand) may be disadvantageous. Forcing the structure of an homogeneous stand to a multi-layer approach may in fact increase sources of uncertainty. On the other hand forcing complex forests to a mono layer simplified model, may cause an increase in mortality and a reduction in average DBH and Height. Compared with measured CO2 flux data, model results show good ability in estimating carbon sequestration trends, on both a monthly/seasonal and daily time scales. Moreover the model simulates quite well leaf phenology and the combined effects of the two different forest stands on CO2 fluxes.

A New High Resolution Climate Dataset for Climate Change Impacts Assessments in New England

NASA Astrophysics Data System (ADS)

Komurcu, M.; Huber, M.

2016-12-01

Assessing regional impacts of climate change (such as changes in extreme events, land surface hydrology, water resources, energy, ecosystems and economy) requires much higher resolution climate variables than those available from global model projections. While it is possible to run global models in higher resolution, the high computational cost associated with these simulations prevent their use in such manner. To alleviate this problem, dynamical downscaling offers a method to deliver higher resolution climate variables. As part of an NSF EPSCoR funded interdisciplinary effort to assess climate change impacts on New Hampshire ecosystems, hydrology and economy (the New Hampshire Ecosystems and Society project), we create a unique high-resolution climate dataset for New England. We dynamically downscale global model projections under a high impact emissions scenario using the Weather Research and Forecasting model (WRF) with three nested grids of 27, 9 and 3 km horizontal resolution with the highest resolution innermost grid focusing over New England. We prefer dynamical downscaling over other methods such as statistical downscaling because it employs physical equations to progressively simulate climate variables as atmospheric processes interact with surface processes, emissions, radiation, clouds, precipitation and other model components, hence eliminates fix relationships between variables. In addition to simulating mean changes in regional climate, dynamical downscaling also allows for the simulation of climate extremes that significantly alter climate change impacts. We simulate three time slices: 2006-2015, 2040-2060 and 2080-2100. This new high-resolution climate dataset (with more than 200 variables saved in hourly (six hourly) intervals for the highest resolution domain (outer two domains)) along with model input and restart files used in our WRF simulations will be publicly available for use to the broader scientific community to support in-depth climate change impacts assessments for New England. We present results focusing on future changes in New England extreme events.

Carbon budget of tropical forests in Southeast Asia and the effects of deforestation: an approach using a process-based model and field measurements

NASA Astrophysics Data System (ADS)

Adachi, M.; Ito, A.; Ishida, A.; Kadir, W. R.; Ladpala, P.; Yamagata, Y.

2011-09-01

More reliable estimates of the carbon (C) stock within forest ecosystems and C emission induced by deforestation are urgently needed to mitigate the effects of emissions on climate change. A process-based terrestrial biogeochemical model (VISIT) was applied to tropical primary forests of two types (a seasonal dry forest in Thailand and a rainforest in Malaysia) and one agro-forest (an oil palm plantation in Malaysia) to estimate the C budget of tropical ecosystems in Southeast Asia, including the impacts of land-use conversion. The observed aboveground biomass in the seasonal dry tropical forest in Thailand (226.3 t C ha-1) and the rainforest in Malaysia (201.5 t C ha-1) indicate that tropical forests of Southeast Asia are among the most C-abundant ecosystems in the world. The model simulation results in rainforests were consistent with field data, except for the NEP, however, the VISIT model tended to underestimate C budget and stock in the seasonal dry tropical forest. The gross primary production (GPP) based on field observations ranged from 32.0 to 39.6 t C ha-1 yr-1 in the two primary forests, whereas the model slightly underestimated GPP (26.5-34.5 t C ha-1 yr-1). The VISIT model appropriately captured the impacts of disturbances such as deforestation and land-use conversions on the C budget. Results of sensitivity analysis showed that the proportion of remaining residual debris was a key parameter determining the soil C budget after the deforestation event. According to the model simulation, the total C stock (total biomass and soil C) of the oil palm plantation was about 35% of the rainforest's C stock at 30 yr following initiation of the plantation. However, there were few field data of C budget and stock, especially in oil palm plantation. The C budget of each ecosystem must be evaluated over the long term using both the model simulations and observations to understand the effects of climate and land-use conversion on C budgets in tropical forest ecosystems.

Model estimates of net primary productivity, evaportranspiration, and water use efficiency in the terrestrial ecosystems of the southern United States

Treesearch

Hanqin Tian; Guangsheng Chen; Mingliang Liu; Chi Zhang; Ge Sun; Chaoqun Lu; Xiaofeng Xu; Wei Ren; Shufen Pan; Arthur Chappelka

2010-01-01

The effects of global change on ecosystem productivity and water resources in the southern United States (SUS), a traditionally ‘water-rich’ region and the ‘timber basket’ of the country, are not well quantified. We carried out several simulation experiments to quantify ecosystem net primary productivity (NPP), evapotranspiration (ET)...

Coupled isotopic and simulation modeling of gaseous nitrogen losses from tropical rainforests

NASA Astrophysics Data System (ADS)

Bai, E.; Houlton, B.

2008-12-01

Gaseous nitrogen (N) losses remove fixed N from the biosphere and play an important role in regulating Earth's climate system. Current techniques for directly measuring gaseous N fluxes are still limited, however, and many uncertainties remain. We combined natural isotopic and simulation modeling (DAYCENT; daily version of CENTURY) to examine the extent to which N isotopes offer meaningful constraint to estimates of large-scale gaseous N emissions from terrestrial ecosystems. The isotope model considers two scenarios: in the first, soil δ15N is a linear function of fraction of gaseous N losses; in the second, underexpression of the isotope effect of denitrification is considered and soil 15N/14N is determined by both the fraction of gaseous losses and the proportion of nitrate consumed locally by denitrification. We examined the coupled simulation and isotope-based model along two Hawaiian rainforest gradients which span a range of tropical rainfall climates, soil biogeochemical ages and ecosystem 15N/14N. Under most conditions (MAP < 4050 mm and age > 2100 yr), modeled soil 15N/14N ratios agreed reasonably well with measurements (r2 = 0.53), consistent with full expression of a field-calibrated isotope effect (scenario 1). In very wet sites (MAP > 4050 mm), locally complete consumption of nitrate appears to lower the effective isotope effect of denitrification at ecosystem levels, resulting in soil 15N/14N ratios that approach those of the N inputs (i.e., scenario 2). Replacing DAYCENT simulation results with field-based measures of N gas fluxes (NOx + N2O) yielded consistently lower estimates of soil 15N/14N ratios across the forests, pointing to a missing gas N loss term (i.e., N2), inadequate coverage of spatial and temporal heterogeneity by empirical measures or both. These results demonstrate the potential for soil N isotopes to constrain N gas fluxes at large geographic scales, implying a quantitative tracer for gaseous N losses from terrestrial ecosystems.

Toward Improved Parameterization of a Meso-Scale Hydrologic Model in a Discontinuous Permafrost, Boreal Forest Ecosystem

NASA Astrophysics Data System (ADS)

Endalamaw, A. M.; Bolton, W. R.; Young, J. M.; Morton, D.; Hinzman, L. D.

2013-12-01

The sub-arctic environment can be characterized as being located in the zone of discontinuous permafrost. Although the distribution of permafrost is site specific, it dominates many of the hydrologic and ecologic responses and functions including vegetation distribution, stream flow, soil moisture, and storage processes. In this region, the boundaries that separate the major ecosystem types (deciduous dominated and coniferous dominated ecosystems) as well as permafrost (permafrost verses non-permafrost) occur over very short spatial scales. One of the goals of this research project is to improve parameterizations of meso-scale hydrologic models in this environment. Using the Caribou-Poker Creeks Research Watershed (CPCRW) as the test area, simulations of the headwater catchments of varying permafrost and vegetation distributions were performed. CPCRW, located approximately 50 km northeast of Fairbanks, Alaska, is located within the zone of discontinuous permafrost and the boreal forest ecosystem. The Variable Infiltration Capacity (VIC) model was selected as the hydrologic model. In CPCRW, permafrost and coniferous vegetation is generally found on north facing slopes and valley bottoms. Permafrost free soils and deciduous vegetation is generally found on south facing slopes. In this study, hydrologic simulations using fine scale vegetation and soil parameterizations - based upon slope and aspect analysis at a 50 meter resolution - were conducted. Simulations were also conducted using downscaled vegetation from the Scenarios Network for Alaska and Arctic Planning (SNAP) (1 km resolution) and soil data sets from the Food and Agriculture Organization (FAO) (approximately 9 km resolution). Preliminary simulation results show that soil and vegetation parameterizations based upon fine scale slope/aspect analysis increases the R2 values (0.5 to 0.65 in the high permafrost (53%) basin; 0.43 to 0.56 in the low permafrost (2%) basin) relative to parameterization based on coarse scale data. These results suggest that using fine resolution parameterizations can be used to improve meso-scale hydrological modeling in this region.

Land-Use Impacts on the Terrestrial Carbon Cycle: An Integrative Tool for Resource Assessment and Planning

NASA Astrophysics Data System (ADS)

Sleeter, B. M.; Liu, J.; Zhu, Z.; Hawbaker, T. J.

2014-12-01

Human land use and natural processes contribute to the ability of ecosystems to store and sequester carbon and offset greenhouse gas emissions. Changes in land use (e.g. agricultural cultivation, timber harvest, urban development, and other land management strategies) and natural processes (e.g. climate, wildfire, disease, storm, and insect outbreak) drive the dynamics of ecosystem carbon pools. These carbon dynamics operate at different spatial and temporal scales, making it challenging to track the changes in a single integrative framework. Landowners, managers, and policy makers require data, information, and tools on the relative contributions of these drivers of ecosystem carbon stocks and fluxes in order to evaluate alternative policies and management strategies designed to increase carbon storage and sequestration. In this paper we explore preliminary results from efforts to simulate changes in ecosystem carbon at ecoregional scales, resulting from anthropogenic land use, wildfire, natural vegetation change, and climate variability under a range of future conditions coherent with a range of global change scenarios. Simulations track the fate of carbon across several pools, including living biomass, deadwood, litter, soil, and wood products. Carbon fluxes are estimated based on simulations from the Integrated Biosphere Simulator model (IBIS). Downscaled land-use projections from the Special Report on Emission Scenarios and Representative Concentration Pathways drive changes in land use, along with extrapolations based on local-scale data. We discuss the sensitivity of the model to individual drivers, and the overall uncertainty associated with the wide range of scenario projections, as well as explore alternative policy and management outcomes and their ability to increase carbon storage in terrestrial ecosystems.

Response of South American Ecosystems to Precipitation Variability

NASA Astrophysics Data System (ADS)

Knox, R. G.; Kim, Y.; Longo, M.; Medvigy, D.; Wang, J.; Moorcroft, P. R.; Bras, R. L.

2009-12-01

The Ecosystem Demography Model 2 is a dynamic ecosystem model and land surface energy balance model. ED2 discretizes landscapes of particular terrain and meteorology into fractional areas of unique disturbance history. Each fraction, defined by a shared vertical soil column and canopy air space, contains a stratum of plant groups unique in functional type, size and number density. The result is a vertically distributed representation of energy transfer and plant dynamics (mortality, productivity, recruitment, disturbance, resource competition, etc) that successfully approximates the behaviour of individual-based vegetation models. In previous exercises simulating Amazonian land surface dynamics with ED 2, it was observed that when using grid averaged precipitation as an external forcing the resulting water balance typically over-estimated leaf interception and leaf evaporation while under estimating through-fall and transpiration. To investigate this result, two scenario were conducted in which land surface biophysics and ecosystem demography over the Northern portion of South America are simulated over ~200 years: (1) ED2 is forced with grid averaged values taken from the ERA40 reanalysis meteorological dataset; (2) ED2 is forced with ERA40 reanalysis, but with its precipitation re-sampled to reflect statistical qualities of point precipitation found at rain gauge stations in the region. The findings in this study suggest that the equilibrium moisture states and vegetation demography are co-dependent and show sensitivity to temporal variability in precipitation. These sensitivities will need to be accounted for in future projections of coupled climate-ecosystem changes in South America.

Simulating the impacts of land use in northwest Europe on Net Ecosystem Exchange (NEE): the role of arable ecosystems, grasslands and forest plantations in climate change mitigation.

PubMed

Abdalla, Mohamed; Saunders, Matthew; Hastings, Astley; Williams, Mike; Smith, Pete; Osborne, Bruce; Lanigan, Gary; Jones, Mike B

2013-11-01

In this study, we compared measured and simulated Net Ecosystem Exchange (NEE) values from three wide spread ecosystems in the southeast of Ireland (forest, arable and grassland), and investigated the suitability of the DNDC (the DeNitrification-DeComposition) model to estimate present and future NEE. Although, the field-DNDC version overestimated NEE at temperatures >5 °C, forest-DNDC under-estimated NEE at temperatures >5 °C. The results suggest that the field/forest DNDC models can successfully estimate changes in seasonal and annual NEE from these ecosystems. Differences in NEE were found to be primarily land cover specific. The annual NEE was similar for the grassland and arable sites, but due to the contribution of exported carbon, the soil carbon increased at the grassland site and decreased at the arable site. The NEE of the forest site was an order of magnitude larger than that of the grassland or arable ecosystems, with large amounts of carbon stored in woody biomass and the soil. The average annual NEE, GPP and Reco values over the measurement period were -904, 2379 and 1475 g C m(-2) (forest plantations), -189, 906 and 715 g C m(-2) (arable systems) and -212, 1653 and 1444 g C m(-2) (grasslands), respectively. The average RMSE values were 3.8 g C m(-2) (forest plantations), 0.12 g C m(-2) (arable systems) and 0.21 g C m(-2) (grasslands). When these models were run with climate change scenarios to 2060, predictions show that all three ecosystems will continue to operate as carbon sinks. Further, climate change may decrease the carbon sink strength in the forest plantations by up to 50%. This study supports the use of the DNDC model as a valid tool to predict the consequences of climate change on NEE from different ecosystems. Copyright © 2012 Elsevier B.V. All rights reserved.

Latent heat exchange in the boreal and arctic biomes.

PubMed

Kasurinen, Ville; Alfredsen, Knut; Kolari, Pasi; Mammarella, Ivan; Alekseychik, Pavel; Rinne, Janne; Vesala, Timo; Bernier, Pierre; Boike, Julia; Langer, Moritz; Belelli Marchesini, Luca; van Huissteden, Ko; Dolman, Han; Sachs, Torsten; Ohta, Takeshi; Varlagin, Andrej; Rocha, Adrian; Arain, Altaf; Oechel, Walter; Lund, Magnus; Grelle, Achim; Lindroth, Anders; Black, Andy; Aurela, Mika; Laurila, Tuomas; Lohila, Annalea; Berninger, Frank

2014-11-01

In this study latent heat flux (λE) measurements made at 65 boreal and arctic eddy-covariance (EC) sites were analyses by using the Penman-Monteith equation. Sites were stratified into nine different ecosystem types: harvested and burnt forest areas, pine forests, spruce or fir forests, Douglas-fir forests, broadleaf deciduous forests, larch forests, wetlands, tundra and natural grasslands. The Penman-Monteith equation was calibrated with variable surface resistances against half-hourly eddy-covariance data and clear differences between ecosystem types were observed. Based on the modeled behavior of surface and aerodynamic resistances, surface resistance tightly control λE in most mature forests, while it had less importance in ecosystems having shorter vegetation like young or recently harvested forests, grasslands, wetlands and tundra. The parameters of the Penman-Monteith equation were clearly different for winter and summer conditions, indicating that phenological effects on surface resistance are important. We also compared the simulated λE of different ecosystem types under meteorological conditions at one site. Values of λE varied between 15% and 38% of the net radiation in the simulations with mean ecosystem parameters. In general, the simulations suggest that λE is higher from forested ecosystems than from grasslands, wetlands or tundra-type ecosystems. Forests showed usually a tighter stomatal control of λE as indicated by a pronounced sensitivity of surface resistance to atmospheric vapor pressure deficit. Nevertheless, the surface resistance of forests was lower than for open vegetation types including wetlands. Tundra and wetlands had higher surface resistances, which were less sensitive to vapor pressure deficits. The results indicate that the variation in surface resistance within and between different vegetation types might play a significant role in energy exchange between terrestrial ecosystems and atmosphere. These results suggest the need to take into account vegetation type and phenology in energy exchange modeling. © 2014 John Wiley & Sons Ltd.

Scaling approach of terrestrial carbon cycle over Alaska's black spruce forests: a synthesis of field observation, remote sensing, and ecosystem modeling

NASA Astrophysics Data System (ADS)

Ueyama, M.; Date, T.; Harazono, Y.; Ichii, K.

2007-12-01

Spatio-temporal scale up of the eddy covariance data is an important challenge especially in the northern high latitude ecosystems, since continuous ground observations are rarely conducted. In this study, we measured the carbon fluxes at a black spruce forest in interior Alaska, and then scale up the eddy covariance data to spatio- temporal variations in regional carbon budget by using satellite remote sensing data and a process based ecosystem model, Biome-BGC. At point scale, both satellite-based empirical model and Biome-BGC could reproduce seasonal and interannual variations in GPP/RE/NEE. The magnitude of GPP/RE is also consistent among the models. However, spatial patterns in GPP/RE are something different among the models; high productivity in low elevation area is estimated by the satellite-based model whereas insignificant relationship is simulated by Biome-BGC. Long- term satellite records, AVHRR and MODIS, show the gradual decline of NDVI in Alaska's black spruce forests between 1981 and 2006, resulting in a general trend of decreasing GPP/RE for Alaska's black spruce forests. These trends are consistent with the Biome-BGC simulation. The trend of carbon budget is also consistent among the models, where the carbon budget of black spruce forests did not significantly change in the period. The simulated results suggest that the carbon fluxes in black spruce forests could be more sensitive to water availability than air temperature.

A carbon balance model for the great dismal swamp ecosystem

USGS Publications Warehouse

Sleeter, Rachel; Sleeter, Benjamin M.; Williams, Brianna; Hogan, Dianna; Hawbaker, Todd J.; Zhu, Zhiliang

2017-01-01

BackgroundCarbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting.ResultsWe modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985–2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus.ConclusionsNatural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha−1/year−1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.

A carbon balance model for the great dismal swamp ecosystem.

PubMed

Sleeter, Rachel; Sleeter, Benjamin M; Williams, Brianna; Hogan, Dianna; Hawbaker, Todd; Zhu, Zhiliang

2017-12-01

Carbon storage potential has become an important consideration for land management and planning in the United States. The ability to assess ecosystem carbon balance can help land managers understand the benefits and tradeoffs between different management strategies. This paper demonstrates an application of the Land Use and Carbon Scenario Simulator (LUCAS) model developed for local-scale land management at the Great Dismal Swamp National Wildlife Refuge. We estimate the net ecosystem carbon balance by considering past ecosystem disturbances resulting from storm damage, fire, and land management actions including hydrologic inundation, vegetation clearing, and replanting. We modeled the annual ecosystem carbon stock and flow rates for the 30-year historic time period of 1985-2015, using age-structured forest growth curves and known data for disturbance events and management activities. The 30-year total net ecosystem production was estimated to be a net sink of 0.97 Tg C. When a hurricane and six historic fire events were considered in the simulation, the Great Dismal Swamp became a net source of 0.89 Tg C. The cumulative above and below-ground carbon loss estimated from the South One and Lateral West fire events totaled 1.70 Tg C, while management activities removed an additional 0.01 Tg C. The carbon loss in below-ground biomass alone totaled 1.38 Tg C, with the balance (0.31 Tg C) coming from above-ground biomass and detritus. Natural disturbances substantially impact net ecosystem carbon balance in the Great Dismal Swamp. Through alternative management actions such as re-wetting, below-ground biomass loss may have been avoided, resulting in the added carbon storage capacity of 1.38 Tg. Based on two model assumptions used to simulate the peat system, (a burn scar totaling 70 cm in depth, and the soil carbon accumulation rate of 0.36 t C/ha -1 /year -1 for Atlantic white cedar), the total soil carbon loss from the South One and Lateral West fires would take approximately 1740 years to re-amass. Due to the impractical time horizon this presents for land managers, this particular loss is considered permanent. Going forward, the baseline carbon stock and flow parameters presented here will be used as reference conditions to model future scenarios of land management and disturbance.

Simulating Canopy-Level Solar Induced Fluorescence with CLM-SIF 4.5 at a Sub-Alpine Conifer Forest in the Colorado Rockies

NASA Astrophysics Data System (ADS)

Raczka, B. M.; Bowling, D. R.; Lin, J. C.; Lee, J. E.; Yang, X.; Duarte, H.; Zuromski, L.

2017-12-01

Forests of the Western United States are prone to drought, temperature extremes, forest fires and insect infestation. These disturbance render carbon stocks and land-atmosphere carbon exchanges highly variable and vulnerable to change. Regional estimates of carbon exchange from terrestrial ecosystem models are challenged, in part, by a lack of net ecosystem exchange observations (e.g. flux towers) due to the complex mountainous terrain. Alternatively, carbon estimates based on light use efficiency models that depend upon remotely-sensed greenness indices are challenged due to a weak relationship with GPP during the winter season. Recent advances in the retrieval of remotely sensed solar induced fluorescence (SIF) have demonstrated a strong seasonal relationship between GPP and SIF for deciduous, grass and, to a lesser extent, conifer species. This provides an important opportunity to use remotely-sensed SIF to calibrate terrestrial ecosystem models providing a more accurate regional representation of biomass and carbon exchange across mountainous terrain. Here we incorporate both leaf-level fluorescence and leaf-to-canopy radiative transfer represented by the SCOPE model into CLM 4.5 (CLM-SIF). We simulate canopy level fluorescence at a sub-alpine forest site (Niwot Ridge, Colorado) and test whether these simulations reproduce remotely-sensed SIF from a satellite (GOME2). We found that the average peak SIF during the growing season (yrs 2007-2013) was similar between the model and satellite observations (within 15%); however, simulated SIF during the winter season was significantly greater than the satellite observations (5x higher). This implies that the fluorescence yield is overestimated by the model during the winter season. It is important that the modeled representation of seasonal fluorescence yield is improved to provide an accurate seasonal representation of SIF across the Western United States.

A physiologically-based plant hydraulics scheme for ESMs: impacts of hydraulic trait variability for tropical forests under drought

NASA Astrophysics Data System (ADS)

Christoffersen, B. O.; Xu, C.; Fisher, R.; Fyllas, N.; Gloor, M.; Fauset, S.; Galbraith, D.; Koven, C.; Knox, R. G.; Kueppers, L. M.; Chambers, J. Q.; Meir, P.; McDowell, N. G.

2016-12-01

A major challenge of Earth System Models (ESMs) is to capture the diversity of individual-level responses to changes in water availability. Yet, decades of research in plant physiological ecology have given us a means to quantify central tendencies and variances of plant hydraulic traits. If ESMs possessed the relevant hydrodynamic process structure, these traits could be incorporated into improved predictions of community- and ecosystem-level processes such as tree mortality. We present a model of plant hydraulics in which all parameters are biologically-interpretable and measurable traits, such as turgor loss point πtlp, bulk elastic modulus ɛ, hydraulic capacitance Cft, xylem hydraulic conductivity ks,max, water potential at 50 % loss of conductivity for both xylem (P50,x) and stomata (P50,gs). We applied this scheme to tropical forests by incorporating it into both an individual-based model `Trait Forest Simulator' (TFS) and the `Functionally Assembled Terrestrial Ecosystem Simulator' (FATES; derived from CLM(ED)), and explore the consequences of variability in plant hydraulic traits on simulated leaf water potential, a potentially powerful predictor of tree mortality. We show that, independent of the difference between P50,gs and P50,x, or the hydraulic safety margin (HSM), diversity in hydraulic traits can increase or decrease whole-ecosystem resistance to hydraulic failure, and thus ecosystem-level responses to drought. Key uncertainties remaining concern how coordination and trade-offs in hydraulic traits are parameterized. We conclude that inclusion of such a physiologically-based plant hydraulics scheme in ESMs will greatly improve the capability of ESMs to predict functional trait filtering within ecosystems in responding to environmental change.

GRL-FLUXNET: A network of eddy covariance systems in the southern great plains

USDA-ARS?s Scientific Manuscript database

Information on exchange of energy, carbon dioxide (CO2), and water vapor (H2O) for major terrestrial ecosystems is vital to quantify carbon and water budgets to develop, evaluate, and enhance hydrologic and crop simulation models and to better understand the potential of terrestrial ecosystems to mi...

Plant hydraulic diversity buffers forest ecosystem responses to drought

NASA Astrophysics Data System (ADS)

Anderegg, W.; Konings, A. G.; Trugman, A. T.; Pacala, S. W.; Yu, K.; Sulman, B. N.; Sperry, J.; Bowling, D. R.

2017-12-01

Drought impacts carbon, water, and energy cycles in forests and may pose a fundamental threat to forests in future climates. Plant hydraulic transport of water is central to tree drought responses, including curtailing of water loss and the risk of mortality during drought. The effect of biodiversity on ecosystem function has typically been examined in grasslands, yet the diversity of plant hydraulic strategies may influence forests' response to drought. In a combined analysis of eddy covariance measurements, remote-sensing data of plant water content variation, model simulations, and plant hydraulic trait data, we test the degree to which plant water stress schemes influence the carbon cycle and how hydraulic diversity within and across ecosystems affects large-scale drought responses. We find that current plant functional types are not well-suited to capture hydraulic variation and that higher hydraulic diversity buffers ecosystem variation during drought. Our results demonstrate that tree functional diversity, particularly hydraulic diversity, may be critical to simulate in plant functional types in current land surface model projections of future vegetation's response to climate extremes.

Multimodeling Framework for Predicting Water Quality in Fragmented Agriculture-Forest Ecosystems

NASA Astrophysics Data System (ADS)

Rose, J. B.; Guber, A.; Porter, W. F.; Williams, D.; Tamrakar, S.; Dechen Quinn, A.

2012-12-01

Both livestock and wildlife are major contributors of nonpoint pollution of surface water bodies. The interactions among them can substantially increase the chance of contamination especially in fragmented agriculture-forest landscapes, where wildlife (e.g. white tailed deer) can transmit diseases between remote farms. Unfortunately, models currently available for predicting fate and transport of microorganisms in these ecosystems do not account for such interactions. The objectives of this study are to develop and test a multimodeling framework that assesses the risk of microbial contamination of surface water caused by wildlife-livestock interactions in fragmented agriculture-forest ecosystems. The framework consists of a modified Soil Water Assessment Tool (SWAT), KINematic Runoff and EROSion model (KINEROS2) with the add-on module STWIR (Microorganism Transport with Infiltration and Runoff), RAMAS GIS, SIR compartmental model and Quantitative Microbial Risk Assessment model (QMRA). The watershed-scale model SWAT simulates plant biomass growth, wash-off of microorganisms from foliage and soil, overland and in-stream microbial transport, microbial growth, and die-off in foliage and soil. RAMAS GIS model predicts the most probable habitat and subsequent population of white-tailed deer based on land use and crop biomass. KINEROS-STWIR simulates overland transport of microorganisms released from soil, surface applied manure, and fecal deposits during runoff events at high temporal and special resolutions. KINEROS-STWIR and RAMAS GIS provide input for an SIR compartmental model which simulates disease transmission within and between deer groups. This information is used in SWAT model to account for transmission and deposition of pathogens by white tailed deer in stream water, foliage and soil. The QMRA approach extends to microorganisms inactivated in forage and water consumed by deer. Probabilities of deer infections and numbers of infected animals are computed based on a dose-response approach, including Beta Poisson and Maximum Risk models, which take into account pathogen variation in infectivity. An example of the Multimodeling framework performance for a fragmented agriculture-forest ecosystem will be shown in the presentation.

Carbon balance of South Asia constrained by passenger aircraft CO2 measurements

NASA Astrophysics Data System (ADS)

Patra, P. K.; Niwa, Y.; Schuck, T. J.; Brenninkmeijer, C. A.; Machida, T.; Matsueda, H.; Sawa, Y.

2011-12-01

Quantifying the fluxes of carbon dioxide (CO2) between the atmosphere and terrestrial ecosystems in all their diversity, across the continents, is important and urgent for implementing effective mitigating policies. Whereas much is known for Europe and North America for instance, in comparison, South Asia, with 1.6 billion inhabitants and considerable CO2 fluxes, remained terra incognita in this respect. The sole measurement site at Cape Rama does not constrain CO2 fluxes during the summer monsoon season. We use regional measurements of atmospheric CO2 aboard a Lufthansa passenger aircraft between Frankfurt (Germany) and Chennai (India) at cruise altitude, in addition to the existing network sites for 2008, to estimate monthly fluxes for 64-regions using Bayesian inversion and ACTM transport model simulations. The applicability of the model's transport parameterization is confirmed using multi-tracer (SF6, CH4, N2O) simulations for the CARIBIC datasets. The annual carbon flux obtained by including the aircraft data is twice as large as the fluxes simulated by a terrestrial ecosystem model that was applied to prescribe the fluxes used in the inversions. It is shown that South Asia sequestered carbon at a rate of 0.37±0.20 Pg C yr-1 for the years 2007 and 2008, primarily during the summer monsoon season when the water limitation for this tropical ecosystem is relaxed. The seasonality and the strength of the calculated monthly fluxes are successfully validated using independent measurements of vertical CO2 profiles over Delhi and spatial variations at cruising altitude by the CONTRAIL program over Asia aboard Japan Airlines passenger aircraft (Patra et al., 2011). Major challenges remain the verification of the inverse model flux seasonality and annual totals by bottom-up estimations using field measurements and terrestrial ecosystem models.

Multiple dimensions of biodiversity and ecosystem processes: Exploring the joint influence of intraspecific, specific and interspecific diversity.

PubMed

Eduardo, Anderson A

2016-09-07

The positive influence of biodiversity on ecosystem processes was the focus of intense debate in ecology throughout the recent decades, becoming accepted and treated as a new paradigm in contemporary ecology. However, the available literature in this research field extensively explores species richness as an unidimensional measure for biodiversity. The present study explores how different components of biological diversity (number of genotypes, species, and functional groups) can influence an ecosystem process (biomass fixation). A mathematical model was employed and the simulation results showed that species richness per se does not affect the ecosystem productivity. Genotypic richness affected positively the ecosystem, but only if the genotypes are functionally complementary. The functional groups richness always affected positively the simulated ecosystem process. When together, richness at the different components of biological diversity showed stronger effect on ecosystem, and the scenarios with high species, genotypes and functional groups richness were the most productive ones. The results also allowed to observe that the ecosystems which are diverse in terms of functional groups and genotypes can be less susceptible to species loss. Finally, it is argued that a multiple dimension approach to biodiversity is relevant to advance the current knowledge on the relation between biodiversity and ecosystem functioning. Copyright © 2016 Elsevier Ltd. All rights reserved.

Simulated Carbon Cycling in a Model Microbial Mat.

NASA Astrophysics Data System (ADS)

Decker, K. L.; Potter, C. S.

2006-12-01

We present here the novel addition of detailed organic carbon cycling to our model of a hypersaline microbial mat ecosystem. This ecosystem model, MBGC (Microbial BioGeoChemistry), simulates carbon fixation through oxygenic and anoxygenic photosynthesis, and the release of C and electrons for microbial heterotrophs via cyanobacterial exudates and also via a pool of dead cells. Previously in MBGC, the organic portion of the carbon cycle was simplified into a black-box rate of accumulation of simple and complex organic compounds based on photosynthesis and mortality rates. We will discuss the novel inclusion of fermentation as a source of carbon and electrons for use in methanogenesis and sulfate reduction, and the influence of photorespiration on labile carbon exudation rates in cyanobacteria. We will also discuss the modeling of decomposition of dead cells and the ultimate release of inorganic carbon. The detailed modeling of organic carbon cycling is important to the accurate representation of inorganic carbon flux through the mat, as well as to accurate representation of growth models of the heterotrophs under different environmental conditions. Because the model ecosystem is an analog of ancient microbial mats that had huge impacts on the atmosphere of early earth, this MBGC can be useful as a biological component to either early earth models or models of other planets that potentially harbor life.

Dynamics of a prey-predator system under Poisson white noise excitation

NASA Astrophysics Data System (ADS)

Pan, Shan-Shan; Zhu, Wei-Qiu

2014-10-01

The classical Lotka-Volterra (LV) model is a well-known mathematical model for prey-predator ecosystems. In the present paper, the pulse-type version of stochastic LV model, in which the effect of a random natural environment has been modeled as Poisson white noise, is investigated by using the stochastic averaging method. The averaged generalized Itô stochastic differential equation and Fokker-Planck-Kolmogorov (FPK) equation are derived for prey-predator ecosystem driven by Poisson white noise. Approximate stationary solution for the averaged generalized FPK equation is obtained by using the perturbation method. The effect of prey self-competition parameter ɛ2 s on ecosystem behavior is evaluated. The analytical result is confirmed by corresponding Monte Carlo (MC) simulation.

Biological data assimilation for parameter estimation of a phytoplankton functional type model for the western North Pacific

NASA Astrophysics Data System (ADS)

Hoshiba, Yasuhiro; Hirata, Takafumi; Shigemitsu, Masahito; Nakano, Hideyuki; Hashioka, Taketo; Masuda, Yoshio; Yamanaka, Yasuhiro

2018-06-01

Ecosystem models are used to understand ecosystem dynamics and ocean biogeochemical cycles and require optimum physiological parameters to best represent biological behaviours. These physiological parameters are often tuned up empirically, while ecosystem models have evolved to increase the number of physiological parameters. We developed a three-dimensional (3-D) lower-trophic-level marine ecosystem model known as the Nitrogen, Silicon and Iron regulated Marine Ecosystem Model (NSI-MEM) and employed biological data assimilation using a micro-genetic algorithm to estimate 23 physiological parameters for two phytoplankton functional types in the western North Pacific. The estimation of the parameters was based on a one-dimensional simulation that referenced satellite data for constraining the physiological parameters. The 3-D NSI-MEM optimized by the data assimilation improved the timing of a modelled plankton bloom in the subarctic and subtropical regions compared to the model without data assimilation. Furthermore, the model was able to improve not only surface concentrations of phytoplankton but also their subsurface maximum concentrations. Our results showed that surface data assimilation of physiological parameters from two contrasting observatory stations benefits the representation of vertical plankton distribution in the western North Pacific.

Gap models and their individual-based relatives in the assessment of the consequences of global change

NASA Astrophysics Data System (ADS)

Shugart, Herman H.; Wang, Bin; Fischer, Rico; Ma, Jianyong; Fang, Jing; Yan, Xiaodong; Huth, Andreas; Armstrong, Amanda H.

2018-03-01

Individual-based models (IBMs) of complex systems emerged in the 1960s and early 1970s, across diverse disciplines from astronomy to zoology. Ecological IBMs arose with seemingly independent origins out of the tradition of understanding the ecosystems dynamics of ecosystems from a ‘bottom-up’ accounting of the interactions of the parts. Individual trees are principal among the parts of forests. Because these models are computationally demanding, they have prospered as the power of digital computers has increased exponentially over the decades following the 1970s. This review will focus on a class of forest IBMs called gap models. Gap models simulate the changes in forests by simulating the birth, growth and death of each individual tree on a small plot of land. The summation of these plots comprise a forest (or set of sample plots on a forested landscape or region). Other, more aggregated forest IBMs have been used in global applications including cohort-based models, ecosystem demography models, etc. Gap models have been used to provide the parameters for these bulk models. Currently, gap models have grown from local-scale to continental-scale and even global-scale applications to assess the potential consequences of climate change on natural forests. Modifications to the models have enabled simulation of disturbances including fire, insect outbreak and harvest. Our objective in this review is to provide the reader with an overview of the history, motivation and applications, including theoretical applications, of these models. In a time of concern over global changes, gap models are essential tools to understand forest responses to climate change, modified disturbance regimes and other change agents. Development of forest surveys to provide the starting points for simulations and better estimates of the behavior of the diversity of tree species in response to the environment are continuing needs for improvement for these and other IBMs.

Simulating and mapping the spatial and seasonal effects of future climate and land -use changes on ecosystem services in the Yanhe watershed, China.

PubMed

Chen, Dengshuai; Li, Jing; Zhou, Zixiang; Liu, Yan; Li, Ting; Liu, Jingya

2018-01-01

Effective information about ecosystem services is essential to help optimize and prioritize activities that support conservation planning in the face of land use and climate changes. This study shows an approach that integrates several dissimilar models for assessing water-related ecosystem services to predict values in 2050 under three land use scenarios in the Yanhe watershed. The simulated output variables pertaining to water yield and sediment yield were used as indicators for two ecosystem-regulating services, i.e., water flow regulation and erosion regulation, which were quantified using the soil and water assessment tool (SWAT) model. The model results were translated into a relative ecosystem service valuation scale, which facilitated the analysis of spatial and seasonal changes and served as the basis for the applied mapping approach. The simulated results indicate that higher water-related regulation services were concentrated in the middle and lower reaches of rivers with high water yield and low sediment erosion. The highest water flow regulation services occurred in summer; nevertheless, this was when erosion regulation services were the lowest compared to other periods in 2050. A comparison of the three land use scenarios showed differences in the water-related regulation services. Scenario 1, with high forest coverage, had the highest erosion regulation services, but the water flow regulation services were the lowest. Scenario 3 showed the reverse pattern. Scenario 2 had intermediate water flow regulation and erosion regulation. Increasing vegetation cover in the watershed is conducive to controlling water and soil erosion but could lead to a decline in available water resources. Spatial mapping is a powerful tool for displaying the spatiotemporal differences in the water-related regulation services delivered by ecosystems and can help decision makers optimize land use in the future, with the goal of maximizing the benefits offered by ecological services in the Yanhe watershed.

Biodiversity and ecosystem stability across scales in metacommunities.

PubMed

Wang, Shaopeng; Loreau, Michel

2016-05-01

Although diversity-stability relationships have been extensively studied in local ecosystems, the global biodiversity crisis calls for an improved understanding of these relationships in a spatial context. Here, we use a dynamical model of competitive metacommunities to study the relationships between species diversity and ecosystem variability across scales. We derive analytic relationships under a limiting case; these results are extended to more general cases with numerical simulations. Our model shows that, while alpha diversity decreases local ecosystem variability, beta diversity generally contributes to increasing spatial asynchrony among local ecosystems. Consequently, both alpha and beta diversity provide stabilising effects for regional ecosystems, through local and spatial insurance effects respectively. We further show that at the regional scale, the stabilising effect of biodiversity increases as spatial environmental correlation increases. Our findings have important implications for understanding the interactive effects of global environmental changes (e.g. environmental homogenisation) and biodiversity loss on ecosystem sustainability at large scales. © 2016 John Wiley & Sons Ltd/CNRS.

Evaluating carbon fluxes of global forest ecosystems by using an individual tree-based model FORCCHN.

PubMed

Ma, Jianyong; Shugart, Herman H; Yan, Xiaodong; Cao, Cougui; Wu, Shuang; Fang, Jing

2017-05-15

The carbon budget of forest ecosystems, an important component of the terrestrial carbon cycle, needs to be accurately quantified and predicted by ecological models. As a preamble to apply the model to estimate global carbon uptake by forest ecosystems, we used the CO 2 flux measurements from 37 forest eddy-covariance sites to examine the individual tree-based FORCCHN model's performance globally. In these initial tests, the FORCCHN model simulated gross primary production (GPP), ecosystem respiration (ER) and net ecosystem production (NEP) with correlations of 0.72, 0.70 and 0.53, respectively, across all forest biomes. The model underestimated GPP and slightly overestimated ER across most of the eddy-covariance sites. An underestimation of NEP arose primarily from the lower GPP estimates. Model performance was better in capturing both the temporal changes and magnitude of carbon fluxes in deciduous broadleaf forest than in evergreen broadleaf forest, and it performed less well for sites in Mediterranean climate. We then applied the model to estimate the carbon fluxes of forest ecosystems on global scale over 1982-2011. This application of FORCCHN gave a total GPP of 59.41±5.67 and an ER of 57.21±5.32PgCyr -1 for global forest ecosystems during 1982-2011. The forest ecosystems over this same period contributed a large carbon storage, with total NEP being 2.20±0.64PgCyr -1 . These values are comparable to and reinforce estimates reported in other studies. This analysis highlights individual tree-based model FORCCHN could be used to evaluate carbon fluxes of forest ecosystems on global scale. Copyright © 2017 Elsevier B.V. All rights reserved.

Global sensitivity analysis, probabilistic calibration, and predictive assessment for the data assimilation linked ecosystem carbon model

DOE PAGES

Safta, C.; Ricciuto, Daniel M.; Sargsyan, Khachik; ...

2015-07-01

In this paper we propose a probabilistic framework for an uncertainty quantification (UQ) study of a carbon cycle model and focus on the comparison between steady-state and transient simulation setups. A global sensitivity analysis (GSA) study indicates the parameters and parameter couplings that are important at different times of the year for quantities of interest (QoIs) obtained with the data assimilation linked ecosystem carbon (DALEC) model. We then employ a Bayesian approach and a statistical model error term to calibrate the parameters of DALEC using net ecosystem exchange (NEE) observations at the Harvard Forest site. The calibration results are employedmore » in the second part of the paper to assess the predictive skill of the model via posterior predictive checks.« less

Changes in land-uses and ecosystem services under multi-scenarios simulation.

PubMed

Liu, Jingya; Li, Jing; Qin, Keyu; Zhou, Zixiang; Yang, Xiaonan; Li, Ting

2017-05-15

Social economy of China has been rapidly developing for more than 30years with efficient reforms and policies being issued. Societal developments have resulted in a greater use of many natural resources to the extent that the ecosystem can no longer self-regulate, thus severely damaging the balance of the ecosystem itself. This in turn has led to a deterioration in people's living environments. Our research is based on a combination of climate scenarios presented in the fifth report of the Intergovernmental Panel on Climate Change (IPCC) and policy scenarios, including the one-child policy and carbon tax policy. We adopted Land Change Modeler of IDRISI software to simulate and analyze land-use change under 16 future scenarios in 2050. Carbon sequestration, soil conservation and water yields were quantified, based on those land-use maps and different ecosystem models. We also analyzed trade-offs and synergy among each ecosystem service and discussed why those interactions happened. The results show that: (1) Global climate change has a strong influence on future changes in land-use. (2) Carbon sequestration, water yield and soil conservation have a mutual relationship in the Guanzhong-Tianshui economic region. (3) Climate change and implementation of policy have a conspicuous impact on the changes in ecosystem services in the Guanzhong-Tianshui economic region. This paper can be used as a reference for further related research, and provide a reliable basis for achieving the sustainable development of the ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

Amazon rainforest responses to elevated CO2: Deriving model-based hypotheses for the AmazonFACE experiment

NASA Astrophysics Data System (ADS)

Rammig, A.; Fleischer, K.; Lapola, D.; Holm, J.; Hoosbeek, M.

2017-12-01

Increasing atmospheric CO2 concentration is assumed to have a stimulating effect ("CO2 fertilization effect") on forest growth and resilience. Empirical evidence, however, for the existence and strength of such a tropical CO2 fertilization effect is scarce and thus a major impediment for constraining the uncertainties in Earth System Model projections. The implications of the tropical CO2 effect are far-reaching, as it strongly influences the global carbon and water cycle, and hence future global climate. In the scope of the Amazon Free Air CO2 Enrichment (FACE) experiment, we addressed these uncertainties by assessing the CO2 fertilization effect at ecosystem scale. AmazonFACE is the first FACE experiment in an old-growth, highly diverse tropical rainforest. Here, we present a priori model-based hypotheses for the experiment derived from a set of 12 ecosystem models. Model simulations identified key uncertainties in our understanding of limiting processes and derived model-based hypotheses of expected ecosystem responses to elevated CO2 that can directly be tested during the experiment. Ambient model simulations compared satisfactorily with in-situ measurements of ecosystem carbon fluxes, as well as carbon, nitrogen, and phosphorus stocks. Models consistently predicted an increase in photosynthesis with elevated CO2, which declined over time due to developing limitations. The conversion of enhanced photosynthesis into biomass, and hence ecosystem carbon sequestration, varied strongly among the models due to different assumptions on nutrient limitation. Models with flexible allocation schemes consistently predicted an increased investment in belowground structures to alleviate nutrient limitation, in turn accelerating turnover rates of soil organic matter. The models diverged on the prediction for carbon accumulation after 10 years of elevated CO2, mainly due to contrasting assumptions in their phosphorus cycle representation. These differences define the expected response ratio to elevated CO2 at the AmazonFACE site and identify priorities for experimental work and model development.

Evaluating the effects of future climate change and elevated CO2 on the water use efficiency in terrestrial ecosystems of China

USGS Publications Warehouse

Zhu, Q.; Jiang, H.; Peng, C.; Liu, J.; Wei, X.; Fang, X.; Liu, S.; Zhou, G.; Yu, S.

2011-01-01

Water use efficiency (WUE) is an important variable used in climate change and hydrological studies in relation to how it links ecosystem carbon cycles and hydrological cycles together. However, obtaining reliable WUE results based on site-level flux data remains a great challenge when scaling up to larger regional zones. Biophysical, process-based ecosystem models are powerful tools to study WUE at large spatial and temporal scales. The Integrated BIosphere Simulator (IBIS) was used to evaluate the effects of climate change and elevated CO2 concentrations on ecosystem-level WUE (defined as the ratio of gross primary production (GPP) to evapotranspiration (ET)) in relation to terrestrial ecosystems in China for 2009–2099. Climate scenario data (IPCC SRES A2 and SRES B1) generated from the Third Generation Coupled Global Climate Model (CGCM3) was used in the simulations. Seven simulations were implemented according to the assemblage of different elevated CO2 concentrations scenarios and different climate change scenarios. Analysis suggests that (1) further elevated CO2concentrations will significantly enhance the WUE over China by the end of the twenty-first century, especially in forest areas; (2) effects of climate change on WUE will vary for different geographical regions in China with negative effects occurring primarily in southern regions and positive effects occurring primarily in high latitude and altitude regions (Tibetan Plateau); (3) WUE will maintain the current levels for 2009–2099 under the constant climate scenario (i.e. using mean climate condition of 1951–2006 and CO2concentrations of the 2008 level); and (4) WUE will decrease with the increase of water resource restriction (expressed as evaporation ratio) among different ecosystems.

Effects of experimental nitrogen deposition on peatland carbon pools and fluxes: a modelling analysis

NASA Astrophysics Data System (ADS)

Wu, Y.; Blodau, C.; Moore, T. R.; Bubier, J.; Juutinen, S.; Larmola, T.

2015-01-01

Nitrogen (N) pollution of peatlands alters their carbon (C) balances, yet long-term effects and controls are poorly understood. We applied the model PEATBOG to explore impacts of long-term nitrogen (N) fertilization on C cycling in an ombrotrophic bog. Simulations of summer gross ecosystem production (GEP), ecosystem respiration (ER) and net ecosystem exchange (NEE) were evaluated against 8 years of observations and extrapolated for 80 years to identify potential effects of N fertilization and factors influencing model behaviour. The model successfully simulated moss decline and raised GEP, ER and NEE on fertilized plots. GEP was systematically overestimated in the model compared to the field data due to factors that can be related to differences in vegetation distribution (e.g. shrubs vs. graminoid vegetation) and to high tolerance of vascular plants to N deposition in the model. Model performance regarding the 8-year response of GEP and NEE to N input was improved by introducing an N content threshold shifting the response of photosynthetic capacity (GEPmax) to N content in shrubs and graminoids from positive to negative at high N contents. Such changes also eliminated the competitive advantages of vascular species and led to resilience of mosses in the long-term. Regardless of the large changes of C fluxes over the short-term, the simulated GEP, ER and NEE after 80 years depended on whether a graminoid- or shrub-dominated system evolved. When the peatland remained shrub-Sphagnum-dominated, it shifted to a C source after only 10 years of fertilization at 6.4 g N m-2 yr-1, whereas this was not the case when it became graminoid-dominated. The modelling results thus highlight the importance of ecosystem adaptation and reaction of plant functional types to N deposition, when predicting the future C balance of N-polluted cool temperate bogs.

An Ecohydrological Approach to the Resiliency and Stability of Ecosystems

NASA Astrophysics Data System (ADS)

Peña Alzate, S.; Canon Barriga, J. E.

2013-12-01

We introduce a simplified ecohydrological model to quantitatively assess the resiliency and stability of ecosystems. The proposed model couples a hydrological soil moisture balance with a set of spatiotemporal dynamics of systems and agent-based algorithms to represent the interactions among several plant populations in a gridded area under different water, soil and temperature constraints. The model also allows disturbances, representing mostly the effects of deforestation practices. The simulated ecosystem, composed by a set of plant populations, includes allometric rules (i.e., power laws for generational and reproductive times, linear approximations for water and temperature gains, losses and optimal values and a set of intra and interspecific interaction rules based on high, optimal and low competition responses among the populations). Disturbances are determined by a clearance of populations in a defined area within the model's domain. The effects of climate variability can be also incorporated through precipitation and temperature time series that exhibit trends and heteroskedasticity. Resiliency and stability are calculated with modified indices that are used in hydrology, in this case to determine the ability of the ecosystem to recover from a disturbance. The model represents different types of plant phenotypes showing exponential growth in the first steps of the simulations. The indices, evaluated on each population and over the structure of the entire ecosystem, show how different populations respond differently to disturbances, following behaviors similar to those expected in nature, like high reproduction rates on gregarious plants with short generation times, and low densities in plants with high generations times. The selection of plant populations was mainly focused on the concept of biodiversity with emphasis on tropical regions. The model can represent the spatial and temporal succession of the ecosystem after being disturbed. The model also shows the differences between a disturbed and undisturbed ecosystem in a temporal scale, and how the differences in the phenotypical characteristics of plant populations can be advantageous or disadvantageous when they are disturbed. This ecohydrological model is intended to be used as an aid for making decisions about restoration and conservation practices, and also to help understanding resilience and stability of ecosystems, especially in tropical forests under climate change scenarios. Acknowledgements: authors thank the financial support of COLCIENCIAS (program Jovenes Investigadores e innovadores 2012), GAIA group and Universidad de Antioquia through its Sustainability Program 2011-2012.

Simulated Long-term Effects of the MOFEP Cutting Treatments

Treesearch

David R. Larsen

1997-01-01

Changes in average basal area and volume per acre were simulated for a 35-year pertod using the treatments designated for sites 4, 5, and 6 of the Missouri Ozark Forest Ecosystem Project. A traditional growth and yield model (Central States TWIGS variant of the Forest Vegetation Simulator) was used with Landscape Management System Software to simulate and display...

Evaluation of the ORCHIDEE ecosystem model over Africa against 25 years of satellite-based water and carbon measurements

NASA Astrophysics Data System (ADS)

Traore, Abdoul Khadre; Ciais, Philippe; Vuichard, Nicolas; Poulter, Benjamin; Viovy, Nicolas; Guimberteau, Matthieu; Jung, Martin; Myneni, Ranga; Fisher, Joshua B.

2014-08-01

Few studies have evaluated land surface models for African ecosystems. Here we evaluate the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based model for the interannual variability (IAV) of the fraction of absorbed active radiation, the gross primary productivity (GPP), soil moisture, and evapotranspiration (ET). Two ORCHIDEE versions are tested, which differ by their soil hydrology parameterization, one with a two-layer simple bucket and the other a more complex 11-layer soil-water diffusion. In addition, we evaluate the sensitivity of climate forcing data, atmospheric CO2, and soil depth. Beside a very generic vegetation parameterization, ORCHIDEE simulates rather well the IAV of GPP and ET (0.5 < r < 0.9 interannual correlation) over Africa except in forestlands. The ORCHIDEE 11-layer version outperforms the two-layer version for simulating IAV of soil moisture, whereas both versions have similar performance of GPP and ET. Effects of CO2 trends, and of variable soil depth on the IAV of GPP, ET, and soil moisture are small, although these drivers influence the trends of these variables. The meteorological forcing data appear to be quite important for faithfully reproducing the IAV of simulated variables, suggesting that in regions with sparse weather station data, the model uncertainty is strongly related to uncertain meteorological forcing. Simulated variables are positively and strongly correlated with precipitation but negatively and weakly correlated with temperature and solar radiation. Model-derived and observation-based sensitivities are in agreement for the driving role of precipitation. However, the modeled GPP is too sensitive to precipitation, suggesting that processes such as increased water use efficiency during drought need to be incorporated in ORCHIDEE.

Changes of global terrestrial carbon budget and major drivers in recent 30 years simulated using the remote sensing driven BEPS model

NASA Astrophysics Data System (ADS)

Ju, W.; Chen, J.; Liu, R.; Liu, Y.

2013-12-01

The process-based Boreal Ecosystem Productivity Simulator (BEPS) model was employed in conjunction with spatially distributed leaf area index (LAI), land cover, soil, and climate data to simulate the carbon budget of global terrestrial ecosystems during the period from 1981 to 2008. The BEPS model was first calibrated and validated using gross primary productivity (GPP), net primary productivity (NPP), and net ecosystem productivity (NEP) measured in different ecosystems across the word. Then, four global simulations were conducted at daily time steps and a spatial resolution of 8 km to quantify the global terrestrial carbon budget and to identify the relative contributions of changes in climate, atmospheric CO2 concentration, and LAI to the global terrestrial carbon sink. The long term LAI data used to drive the model was generated through fusing Moderate Resolution Imaging Spectroradiometer (MODIS) and historical Advanced Very High Resolution Radiometer (AVHRR) data pixel by pixel. The meteorological fields were interpolated from the 0.5° global daily meteorological dataset produced by the land surface hydrological research group at Princeton University. The results show that the BEPS model was able to simulate carbon fluxes in different ecosystems. Simulated GPP, NPP, and NEP values and their temporal trends exhibited distinguishable spatial patterns. During the period from 1981 to 2008, global terrestrial ecosystems acted as a carbon sink. The averaged global totals of GPP NPP, and NEP were 122.70 Pg C yr-1, 56.89 Pg C yr-1, and 2.76 Pg C yr-1, respectively. The global totals of GPP and NPP increased greatly, at rates of 0.43 Pg C yr-2 (R2=0.728) and 0.26 Pg C yr-2 (R2=0.709), respectively. Global total NEP did not show an apparent increasing trend (R2= 0.036), averaged 2.26 Pg C yr-1, 3.21 Pg C yr-1, and 2.72 Pg C yr-1 for the periods from 1981 to 1989, from 1990 to 1999, and from 2000 to 2008, respectively. The magnitude and temporal trend of global terrestrial carbon budget were similar to the values recently reported by the Global Carbon Project. The obvious increases in global GPP and NPP were mainly driven by the enhancement of atmospheric CO2 fertilization. The change of LAI played the secondary role. Climate had a small negative impact on global terrestrial carbon sequestration. The relative importance of changes in climate, atmospheric CO2 concentration, and LAI in altering the temporal trend of carbon sequestration differed spatially. During the period from 2000 to 2008, terrestrial carbon sinks mainly existed in the northern region of South America, the western region of middle Africa, Southeast Asia, Southeast China, Southeast United States, and some regions of Eurasia.

Sensitivity of Global Terrestrial Gross Primary Production to Hydrologic States Simulated by the Community Land Model Using Two Runoff Parameterizations

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

Lei, Huimin; Huang, Maoyi; Leung, Lai-Yung R.

2014-09-01

The terrestrial water and carbon cycles interact strongly at various spatio-temporal scales. To elucidate how hydrologic processes may influence carbon cycle processes, differences in terrestrial carbon cycle simulations induced by structural differences in two runoff generation schemes were investigated using the Community Land Model 4 (CLM4). Simulations were performed with runoff generation using the default TOPMODEL-based and the Variable Infiltration Capacity (VIC) model approaches under the same experimental protocol. The comparisons showed that differences in the simulated gross primary production (GPP) are mainly attributed to differences in the simulated leaf area index (LAI) rather than soil moisture availability. More specifically,more » differences in runoff simulations can influence LAI through changes in soil moisture, soil temperature, and their seasonality that affect the onset of the growing season and the subsequent dynamic feedbacks between terrestrial water, energy, and carbon cycles. As a result of a relative difference of 36% in global mean total runoff between the two models and subsequent changes in soil moisture, soil temperature, and LAI, the simulated global mean GPP differs by 20.4%. However, the relative difference in the global mean net ecosystem exchange between the two models is small (2.1%) due to competing effects on total mean ecosystem respiration and other fluxes, although large regional differences can still be found. Our study highlights the significant interactions among the water, energy, and carbon cycles and the need for reducing uncertainty in the hydrologic parameterization of land surface models to better constrain carbon cycle modeling.« less

A dynamic ecosystem growth model for forests at high complexity structure

NASA Astrophysics Data System (ADS)

Collalti, A.; Perugini, L.; Chiti, T.; Matteucci, G.; Oriani, A.; Santini, M.; Papale, D.; Valentini, R.

2012-04-01

Forests ecosystem play an important role in carbon cycle, biodiversity conservation and for other ecosystem services and changes in their structure and status perturb a delicate equilibrium that involves not only vegetation components but also biogeochemical cycles and global climate. The approaches to determine the magnitude of these effects are nowadays various and one of those include the use of models able to simulate structural changes and the variations in forests yield The present work shows the development of a forest dynamic model, on ecosystem spatial scale using the well known light use efficiency to determine Gross Primary Production. The model is predictive and permits to simulate processes that determine forest growth, its dynamic and the effects of forest management using eco-physiological parameters easy to be assessed and to be measured. The model has been designed to consider a tri-dimensional cell structure composed by different vertical layers depending on the forest type that has to be simulated. These features enable the model to work on multi-layer and multi-species forest types, typical of Mediterranean environment, at the resolution of one hectare and at monthly time-step. The model simulates, for each layer, a value of available Photosynthetic Active Radiation (PAR) through Leaf Area Index, Light Extinction Coefficient and cell coverage, the transpiration rate that is closely linked to the intercepted light and the evaporation from soil. Using this model it is possible to evaluate the possible impacts of climate change on forests that may result in decrease or increase of productivity as well as the feedback of one or more dominated layers in terms of CO2 uptake in a forest stand and the effects of forest management activities during the forest harvesting cycle. The model has been parameterised, validated and applied in a multi-layer, multi-age and multi-species Italian turkey oak forest (Q. cerris L., C. betulus L. and C. avellana L.) where the medium-term (10 years) development of forest parameters were simulated. The results obtained for net primary production and for stem, root and foliage compartments as well as for forest structure i.e. Diameter at Breast Height, height and canopy cover are in good accordance with field data (R2>0.95). These results show how the model is able to predict forest yield as well as forest dynamic with good accuracy and encourage testing the model capability on other sites with a more complex forest structure and for long-time period with an higher spatial resolution.

An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate

PubMed Central

Weijerman, Mariska; Fulton, Elizabeth A.; Kaplan, Isaac C.; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M.; Brainard, Russell E.

2015-01-01

Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5–8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors. PMID:26672983

An Integrated Coral Reef Ecosystem Model to Support Resource Management under a Changing Climate.

PubMed

Weijerman, Mariska; Fulton, Elizabeth A; Kaplan, Isaac C; Gorton, Rebecca; Leemans, Rik; Mooij, Wolf M; Brainard, Russell E

2015-01-01

Millions of people rely on the ecosystem services provided by coral reefs, but sustaining these benefits requires an understanding of how reefs and their biotic communities are affected by local human-induced disturbances and global climate change. Ecosystem-based management that explicitly considers the indirect and cumulative effects of multiple disturbances has been recommended and adopted in policies in many places around the globe. Ecosystem models give insight into complex reef dynamics and their responses to multiple disturbances and are useful tools to support planning and implementation of ecosystem-based management. We adapted the Atlantis Ecosystem Model to incorporate key dynamics for a coral reef ecosystem around Guam in the tropical western Pacific. We used this model to quantify the effects of predicted climate and ocean changes and current levels of current land-based sources of pollution (LBSP) and fishing. We used the following six ecosystem metrics as indicators of ecosystem state, resilience and harvest potential: 1) ratio of calcifying to non-calcifying benthic groups, 2) trophic level of the community, 3) biomass of apex predators, 4) biomass of herbivorous fishes, 5) total biomass of living groups and 6) the end-to-start ratio of exploited fish groups. Simulation tests of the effects of each of the three drivers separately suggest that by mid-century climate change will have the largest overall effect on this suite of ecosystem metrics due to substantial negative effects on coral cover. The effects of fishing were also important, negatively influencing five out of the six metrics. Moreover, LBSP exacerbates this effect for all metrics but not quite as badly as would be expected under additive assumptions, although the magnitude of the effects of LBSP are sensitive to uncertainty associated with primary productivity. Over longer time spans (i.e., 65 year simulations), climate change impacts have a slight positive interaction with other drivers, generally meaning that declines in ecosystem metrics are not as steep as the sum of individual effects of the drivers. These analyses offer one way to quantify impacts and interactions of particular stressors in an ecosystem context and so provide guidance to managers. For example, the model showed that improving water quality, rather than prohibiting fishing, extended the timescales over which corals can maintain high abundance by at least 5-8 years. This result, in turn, provides more scope for corals to adapt or for resilient species to become established and for local and global management efforts to reduce or reverse stressors.

The global distribution of ecosystems in a world without fire.

PubMed

Bond, W J; Woodward, F I; Midgley, G F

2005-02-01

This paper is the first global study of the extent to which fire determines global vegetation patterns by preventing ecosystems from achieving the potential height, biomass and dominant functional types expected under the ambient climate (climate potential). To determine climate potential, we simulated vegetation without fire using a dynamic global-vegetation model. Model results were tested against fire exclusion studies from different parts of the world. Simulated dominant growth forms and tree cover were compared with satellite-derived land- and tree-cover maps. Simulations were generally consistent with results of fire exclusion studies in southern Africa and elsewhere. Comparison of global 'fire off' simulations with landcover and treecover maps show that vast areas of humid C(4) grasslands and savannas, especially in South America and Africa, have the climate potential to form forests. These are the most frequently burnt ecosystems in the world. Without fire, closed forests would double from 27% to 56% of vegetated grid cells, mostly at the expense of C(4) plants but also of C(3) shrubs and grasses in cooler climates. C(4) grasses began spreading 6-8 Ma, long before human influence on fire regimes. Our results suggest that fire was a major factor in their spread into forested regions, splitting biotas into fire tolerant and intolerant taxa.

Testing simulations of intra- and inter-annual variation in the plant production response to elevated CO(2) against measurements from an 11-year FACE experiment on grazed pasture.

PubMed

Li, Frank Yonghong; Newton, Paul C D; Lieffering, Mark

2014-01-01

Ecosystem models play a crucial role in understanding and evaluating the combined impacts of rising atmospheric CO2 concentration and changing climate on terrestrial ecosystems. However, we are not aware of any studies where the capacity of models to simulate intra- and inter-annual variation in responses to elevated CO2 has been tested against long-term experimental data. Here we tested how well the ecosystem model APSIM/AgPasture was able to simulate the results from a free air carbon dioxide enrichment (FACE) experiment on grazed pasture. At this FACE site, during 11 years of CO2 enrichment, a wide range in annual plant production response to CO2 (-6 to +28%) was observed. As well as running the full model, which includes three plant CO2 response functions (plant photosynthesis, nitrogen (N) demand and stomatal conductance), we also tested the influence of these three functions on model predictions. Model/data comparisons showed that: (i) overall the model over-predicted the mean annual plant production response to CO2 (18.5% cf 13.1%) largely because years with small or negative responses to CO2 were not well simulated; (ii) in general seasonal and inter-annual variation in plant production responses to elevated CO2 were well represented by the model; (iii) the observed CO2 enhancement in overall mean legume content was well simulated but year-to-year variation in legume content was poorly captured by the model; (iv) the best fit of the model to the data required all three CO2 response functions to be invoked; (v) using actual legume content and reduced N fixation rate under elevated CO2 in the model provided the best fit to the experimental data. We conclude that in temperate grasslands the N dynamics (particularly the legume content and N fixation activity) play a critical role in pasture production responses to elevated CO2 , and are processes for model improvement. © 2013 John Wiley & Sons Ltd.

Simulating Population Dynamics in an Ecosystem Context Using Coupled Eulerian-Lagrangian Hybrid Models (CEL HYBRID Models)

DTIC Science & Technology

2000-04-01

natural systems (King 1993). Population modelers have used certain difference equations, sometimes called the Lotka - Volterra system of equations...environment 28 Step 5 - Simulate the hydraulic and/or water quality field 29 Step 6 - Generate biota response data for decision support 29 Step 7...Quality and Contaminant Modeling Branch (WQCMB), and Mr. R. Andrew Goodwin, contract student, WQCMB, under the general supervision of Dr. Mark S. Dortch

A generic biogeochemical module for Earth system models: Next Generation BioGeoChemical Module (NGBGC), version 1.0

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.; Leung, L. R.

2013-11-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into Earth system models (e.g., community land models (CLMs)), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module, Next Generation BioGeoChemical Module (NGBGC), version 1.0, with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter, and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into CLM. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems. The method presented here could in theory be applied to simulate biogeochemical cycles in other Earth system models.

Simulations of the north sea circulation, its variability, and its implementation as hydrodynamical forcing in ERSEM

NASA Astrophysics Data System (ADS)

Lenhart, Hermann J.; Radach, Günther; Backhaus, Jan O.; Pohlmann, Thomas

The rationale is given of how the gross physical features of the circulation and the stratification of the North Sea have been aggregated for inclusion in the ecosystem box model ERSEM. As the ecosystem dynamics are to a large extent determined by small-scale physical events, the ecosystem model is forced with the circulation of a specific year rather than using the long-term mean circulation field. Especially the vertical exchange processes have been explicitly included, because the primary production strongly depends on them. Simulations with a general circulation model (GCM), forced by three-hourly meteorological fields, have been utilized to derive daily horizontal transport values driving ERSEM on boxes of sizes of a few 100 km. The daily vertical transports across a fixed 30-m interface provide the necessary short-term event character of the vertical exchange. For the years 1988 and 1989 the properties of the hydrodynamic flow fields are presented in terms of trajectories of the flow, thermocline depths, of water budgets, flushing times and diffusion rates. The results of the standard simulation with ERSEM show that the daily variability of the circulation, being smoothed by the box integration procedure, is transferred to the chemical and biological state variables to a very limited degree only.

Simulated effects of nitrogen saturation on the global carbon budget using the IBIS model

PubMed Central

Lu, Xuehe; Jiang, Hong; Liu, Jinxun; Zhang, Xiuying; Jin, Jiaxin; Zhu, Qiuan; Zhang, Zhen; Peng, Changhui

2016-01-01

Over the past 100 years, human activity has greatly changed the rate of atmospheric N (nitrogen) deposition in terrestrial ecosystems, resulting in N saturation in some regions of the world. The contribution of N saturation to the global carbon budget remains uncertain due to the complicated nature of C-N (carbon-nitrogen) interactions and diverse geography. Although N deposition is included in most terrestrial ecosystem models, the effect of N saturation is frequently overlooked. In this study, the IBIS (Integrated BIosphere Simulator) was used to simulate the global-scale effects of N saturation during the period 1961–2009. The results of this model indicate that N saturation reduced global NPP (Net Primary Productivity) and NEP (Net Ecosystem Productivity) by 0.26 and 0.03 Pg C yr−1, respectively. The negative effects of N saturation on carbon sequestration occurred primarily in temperate forests and grasslands. In response to elevated CO2 levels, global N turnover slowed due to increased biomass growth, resulting in a decline in soil mineral N. These changes in N cycling reduced the impact of N saturation on the global carbon budget. However, elevated N deposition in certain regions may further alter N saturation and C-N coupling. PMID:27966643

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.

Modelling Temporal Variability in the Carbon Balance of a Spruce/Moss Boreal Forest

NASA Technical Reports Server (NTRS)

Frolking, S.; Goulden, M. L.; Wofsy, S. C.; Fan, S.-M.; Sutton, D. J.; Munger, J. W.; Bazzaz, A. M.; Daube, B. C.; Crill, P. M.; Aber, J. D.;

Integrating research on ecohydrology and land use change with land use management

NASA Astrophysics Data System (ADS)

Bass, Brad; Byers, Ralph E.; Lister, Nina-Marie

1998-10-01

One objective of the International Geosphere-Biosphere Programme is to provide a scientific basis for sustainable development policies. Land use change and ecohydrology are important components of this scientific basis, but predicting change is difficult because of the scale and complexity of the interactions between non-linear ecohydrological and socio-economic processes at different spatial and temporal scales. A systems framework, the Ecosystem Approach, has been developed to conceptualize these interactions for the purpose of providing information for sustainable development policy. The Ecosystem Approach combines the dynamics of the Holling figure-eight model - a conceptual model of dynamics that stresses discontinuous change and destruction as an internal property of the system - and the properties of self-organizing systems with the socio political aspects of decision making.The Ecosystem Approach highlights the problems of managing change in complex systems when that change may involve unpredictable shifts to a different attractor. Although there are methods available to detect the occurrence of such shifts, both detection and modelling are complicated by the presence of semi-stable attractors. When a model or an ecosystem is on a semi-stable attractor, it may appear to remain stable for an extended period prior to changing as a consequence of inherent instabilities. When the shift to a new attractor occurs, it is quite sudden and unpredictable. A technical discussion on prediction under conditions of semi-stability and chaos is included because it enhances our understanding of the role of surprise in ecosystems, as well as the utility of simulation models.The principles of the Ecosystem Approach are derived from the theoretical discussion and an example of a land use policy in the Huron Natural Area in south-western Ontario. These principles provide a clear role for scientific research, and particularly simulation modelling, within the larger context of policy and land use management.

Danish heathland manipulation experiment data in Model-Data-Fusion

NASA Astrophysics Data System (ADS)

Thum, Tea; Peylin, Philippe; Ibrom, Andreas; Van Der Linden, Leon; Beier, Claus; Bacour, Cédric; Santaren, Diego; Ciais, Philippe

2013-04-01

In ecosystem manipulation experiments (EMEs) the ecosystem is artificially exposed to different environmental conditions that aim to simulate circumstances in future climate. At Danish EME site Brandbjerg the responses of a heathland to drought, warming and increased atmospheric CO2 concentration are studied. The warming manipulation is realized by passive nighttime warming. The measurements include control plots as well as replicates for each three treatment separately and in combination. The Brandbjerg heathland ecosystem is dominated by heather and wavy hairgrass. These experiments provide excellent data for validation and development of ecosystem models. In this work we used a generic vegetation model ORCHIDEE with Model-Data-Fusion (MDF) approach. ORCHIDEE model is a process-based model that describes the exchanges of carbon, water and energy between the atmosphere and the vegetation. It can be run at different spatial scales from global to site level. Different vegetation types are described in ORCHIDEE as plant functional types. In MDF we are using observations from the site to optimize the model parameters. This enables us to assess the modelling errors and the performance of the model for different manipulation treatments. This insight will inform us whether the different processes are adequately modelled or if the model is missing some important processes. We used a genetic algorithm in the MDF. The data available from the site included measurements of aboveground biomass, heterotrophic soil respiration and total ecosystem respiration from years 2006-2008. The biomass was measured six times doing this period. The respiration measurements were done with manual chamber measurements. For the soil respiration we used results from an empirical model that has been developed for the site. This enabled us to have more data for the MDF. Before the MDF we performed a sensitivity analysis of the model parameters to different data streams. Fifteen most influential parameters were chosen to be optimized. These included parameters connected to photosynthesis, phenology, allocation of biomass and respiration. All three data streams were used simultaneously in the MDF. Before the MDF, the model had the tendency to overestimate the respiration and the aboveground biomass. After MDF the model simulations were closer to the observations, but its estimations for those variables that were not used in the MDF, such as, e.g., fine root biomass growth, did not improve greatly. In these runs the vegetation of Brandbjerg site was described in ORCHIDEE as C3 grass, which had some characteristics that do not apply to a Danish heathland very well. The results suggest that a new plant functional type needs to be developed to ORCHIDEE in order to successfully simulate such ecosystem as Brandbjerg.

Model-data assimilation of multiple phenological observations to constrain and predict leaf area index.

PubMed

Viskari, Toni; Hardiman, Brady; Desai, Ankur R; Dietze, Michael C

2015-03-01

Our limited ability to accurately simulate leaf phenology is a leading source of uncertainty in models of ecosystem carbon cycling. We evaluate if continuously updating canopy state variables with observations is beneficial for predicting phenological events. We employed ensemble adjustment Kalman filter (EAKF) to update predictions of leaf area index (LAI) and leaf extension using tower-based photosynthetically active radiation (PAR) and moderate resolution imaging spectrometer (MODIS) data for 2002-2005 at Willow Creek, Wisconsin, USA, a mature, even-aged, northern hardwood, deciduous forest. The ecosystem demography model version 2 (ED2) was used as the prediction model, forced by offline climate data. EAKF successfully incorporated information from both the observations and model predictions weighted by their respective uncertainties. The resulting. estimate reproduced the observed leaf phenological cycle in the spring and the fall better than a parametric model prediction. These results indicate that during spring the observations contribute most in determining the correct bud-burst date, after which the model performs well, but accurately modeling fall leaf senesce requires continuous model updating from observations. While the predicted net ecosystem exchange (NEE) of CO2 precedes tower observations and unassimilated model predictions in the spring, overall the prediction follows observed NEE better than the model alone. Our results show state data assimilation successfully simulates the evolution of plant leaf phenology and improves model predictions of forest NEE.

Chapter 4: Overview of the vegetation management treatment economic analysis module in the integrated landscape assessment project

Treesearch

Xiaoping Zhou; Miles A. Hemstrom

2014-01-01

Forest land provides various ecosystem services, including timber, biomass, and carbon sequestration. Estimating trends in these ecosystem services is essential for assessing potential outcomes of landscape management scenarios. However, the state-and transition models used in the Integrated Landscape Assessment Project for simulating landscape changes over time do not...

DAYCENT AND ITS LAND SURFACE SUBMODEL: DESCRIPTION AND TESTING. (R824993)

EPA Science Inventory

Abstract

A land surface submodel was developed for the daily version of the CENTURY ecosystem model (DAYCENT). The goal of DAYCENT to simulate soil N₂O, NO_x, and CH₄ fluxes for terrestrial ecosystems determined the structure and ...

Evaluating the ecological sustainability of a pinyon-juniper grassland ecosystem in northern Arizona

Treesearch

Reuben Weisz; Jack Triepke; Don Vandendriesche; Mike Manthei; Jim Youtz; Jerry Simon; Wayne Robbie

2010-01-01

In order to develop strategic land management plans, managers must assess current and future ecological conditions. Climate change has expanded the need to assess the sustainability of ecosystems and predict their conditions under different climate change and management scenarios using landscape dynamics simulation models. We present a methodology for developing a...

Influence of forest planning alternatives on landscape pattern and ecosystem processes in northern Wisconsin, USA

Treesearch

Patrick A. Zollner; L. Jay Roberts; Eric J. Gustafson; Hong S. He; Volker Radeloff

2008-01-01

Incorporating an ecosystem management perspective into forest planning requires consideration of the impacts of timber management on a suite of landscape characteristics at broad spatial and long temporal scales. We used the LANDIS forest landscape simulation model to predict forest composition and landscape pattern under seven alternative forest management plans...

Simulated sensitivity of African terrestrial ecosystem photosynthesis to rainfall frequency, intensity, and rainy season length

NASA Astrophysics Data System (ADS)

Guan, Kaiyu; Good, Stephen P.; Caylor, Kelly K.; Medvigy, David; Pan, Ming; Wood, Eric F.; Sato, Hisashi; Biasutti, Michela; Chen, Min; Ahlström, Anders; Xu, Xiangtao

2018-02-01

There is growing evidence of ongoing changes in the statistics of intra-seasonal rainfall variability over large parts of the world. Changes in annual total rainfall may arise from shifts, either singly or in a combination, of distinctive intra-seasonal characteristics -i.e. rainfall frequency, rainfall intensity, and rainfall seasonality. Understanding how various ecosystems respond to the changes in intra-seasonal rainfall characteristics is critical for predictions of future biome shifts and ecosystem services under climate change, especially for arid and semi-arid ecosystems. Here, we use an advanced dynamic vegetation model (SEIB-DGVM) coupled with a stochastic rainfall/weather simulator to answer the following question: how does the productivity of ecosystems respond to a given percentage change in the total seasonal rainfall that is realized by varying only one of the three rainfall characteristics (rainfall frequency, intensity, and rainy season length)? We conducted ensemble simulations for continental Africa for a realistic range of changes (-20% ~ +20%) in total rainfall amount. We find that the simulated ecosystem productivity (measured by gross primary production, GPP) shows distinctive responses to the intra-seasonal rainfall characteristics. Specifically, increase in rainfall frequency can lead to 28% more GPP increase than the same percentage increase in rainfall intensity; in tropical woodlands, GPP sensitivity to changes in rainy season length is ~4 times larger than to the same percentage changes in rainfall frequency or intensity. In contrast, shifts in the simulated biome distribution are much less sensitive to intra-seasonal rainfall characteristics than they are to total rainfall amount. Our results reveal three major distinctive productivity responses to seasonal rainfall variability—‘chronic water stress’, ‘acute water stress’ and ‘minimum water stress’ - which are respectively associated with three broad spatial patterns of African ecosystem physiognomy, i.e. savannas, woodlands, and tropical forests.

Competition for light between individual trees lowers reference canopy stomatal conductance: Results from a model

NASA Astrophysics Data System (ADS)

Loranty, Michael M.; Mackay, D. Scott; Ewers, Brent E.; Traver, Elizabeth; Kruger, Eric L.

2010-12-01

We have used an ecosystem model, TREES (Terrestrial Regional Ecosystem Exchange Simulator), to test the hypothesis that competition for light limits reference canopy stomatal conductance (GSref; conductance at 1 kPa vapor pressure deficit) for individual tree crowns. Sap flux (JS) data was collected at an aspen-dominated unmanaged early successional site, and at a sugar maple dominated midsuccessional site managed for timber production. Using a Monte Carlo approach, JS scaled canopy transpiration (EC) estimates were used to parameterize two versions of the model for each tree individually; a control model treated trees as isolated individuals, and a modified version incorporated the shading effects of neighboring individuals on incident radiation. Agreement between simulated and observed EC was better for maple than for aspen using the control model. Accounting for canopy heterogeneity using a three-dimensional canopy representation had minimal effects on estimates of GSref or model performance for individual maples. At the Aspen site the modified model resulted in improved EC estimates, particularly for trees with lower GSref and more shading by neighboring individuals. Our results imply a link between photosynthetic capacity, as mediated by competitive light environment, and GSref. We conclude that accounting for the effects of canopy heterogeneity on incident radiation improves modeled estimates of canopy carbon and water fluxes, especially for shade intolerant species. Furthermore our results imply a link between ecosystem structure and function that may be exploited to elucidate the impacts of forest structural heterogeneity on ecosystem fluxes of carbon and water via LiDAR remote sensing.

Redefinition and global estimation of basal ecosystem respiration rate

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

Yuan, Wenping; Luo, Yiqi; Li, Xianglan

2011-10-13

Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located atmore » latitudes ranging from ~3°S to ~70°N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual« less

Carbon storage, timber production, and biodiversity: comparing ecosystem services with multi-criteria decision analysis

USGS Publications Warehouse

Schwenk, W. Scott; Donovan, Therese; Keeton, William S.; Nunery, Jared S.

2012-01-01

Increasingly, land managers seek ways to manage forests for multiple ecosystem services and functions, yet considerable challenges exist in comparing disparate services and balancing trade-offs among them. We applied multi-criteria decision analysis (MCDA) and forest simulation models to simultaneously consider three objectives: (1) storing carbon, (2) producing timber and wood products, and (3) sustaining biodiversity. We used the Forest Vegetation Simulator (FVS) applied to 42 northern hardwood sites to simulate forest development over 100 years and to estimate carbon storage and timber production. We estimated biodiversity implications with occupancy models for 51 terrestrial bird species that were linked to FVS outputs. We simulated four alternative management prescriptions that spanned a range of harvesting intensities and forest structure retention. We found that silvicultural approaches emphasizing less frequent harvesting and greater structural retention could be expected to achieve the greatest net carbon storage but also produce less timber. More intensive prescriptions would enhance biodiversity because positive responses of early successional species exceeded negative responses of late successional species within the heavily forested study area. The combinations of weights assigned to objectives had a large influence on which prescriptions were scored as optimal. Overall, we found that a diversity of silvicultural approaches is likely to be preferable to any single approach, emphasizing the need for landscape-scale management to provide a full range of ecosystem goods and services. Our analytical framework that combined MCDA with forest simulation modeling was a powerful tool in understanding trade-offs among management objectives and how they can be simultaneously accommodated.

Model analysis of grazing effect on above-ground biomass and above-ground net primary production of a Mongolian grassland ecosystem

NASA Astrophysics Data System (ADS)

Chen, Yuxiang; Lee, Gilzae; Lee, Pilzae; Oikawa, Takehisa

2007-01-01

In this study, we have analyzed the productivity of a grassland ecosystem in Kherlenbayan-Ulaan (KBU), Mongolia under non-grazing and grazing conditions using a new simulation model, Sim-CYCLE grazing. The model was obtained by integrating the Sim-CYCLE [Ito, A., Oikawa, T., 2002. A simulation model of carbon cycle in land ecosystems (Sim-CYCLE): a description based on dry-matter production theory and plot-scale validation. Ecological Modeling, 151, pp. 143-176] and a defoliation formulation [Seligman, N.G., Cavagnaro, J.B., Horno, M.E., 1992. Simulation of defoliation effects on primary production of warm-season, semiarid perennial- species grassland. Ecological Modelling, 60, pp. 45-61]. The results from the model have been validated against a set of field data obtained at KBU showing that both above-ground biomass (AB) and above-ground net primary production ( Np,a) decrease with increasing grazing intensity. The simulated maximum AB for a year maintains a nearly constant value of 1.15 Mg DM ha -1 under non-grazing conditions. The AB decreases and then reaches equilibrium under a stocking rate ( Sr) of 0.4 sheep ha -1 and 0.7 sheep ha -1. The AB decreases all the time if Sr is greater than 0.7 sheep ha -1. These results suggest that the maximum sustainable Sr is 0.7 sheep ha -1. A similar trend is also observed for the simulated Np,a. The annual Np,a is about 1.25 Mg DM ha -1 year -1 and this value is also constant under non-grazing conditions. The annual Np,a decreases and then reaches equilibrium under an Sr of 0.4 sheep ha -1 and 0.7 sheep ha -1, but the Np,a decreases all the time when Sr is greater than 0.7 sheep ha -1. It also indicates that the maximum sustainable Sr is 0.7 sheep ha -1. Transpiration ( ET) and evaporation ( EE) rates were determined by the Penman-Monteith method. Simulated results show that ET decreases with increasing Sr, while EE increases with increasing Sr. At equilibrium, the annual mean evapotranspiration ( E) is 189.11 mm year -1 under non-grazing conditions and 187.46 mm year -1 under an Sr of 0.7 sheep ha -1. This indicates that the water budget of the KBU grassland ecosystem is not significantly affected by grazing.

Integrated evaluation of the vulnerability to thermokarst disturbance and its implications for the regional carbon balance in boreal Alaska

NASA Astrophysics Data System (ADS)

Helene, G.; Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Bolton, W. R.; Romanovsky, V. E.

2017-12-01

Our capacity to project future ecosystem trajectories in northern permafrost regions depends on our ability to characterize complex interactions between climatic and ecological processes at play in the soil, the vegetation, and the atmosphere. We present a study that uses remote sensing analyses, field observations, and data synthesis to inform models for the prediction of ecosystem responses to climate change in the boreal zone of Alaska. Recent warming, altered precipitation and fire regimes are driving permafrost degradation, threatening to mobilize vast reservoirs of ancient carbon previously protected from decomposition. Although large scale, progressive, top-down permafrost thaw have been well studied and represented in high-latitude ecosystem models, the consequences of abrupt and local thermokarst disturbances (TK) are less well understood. To fill this gap, we conducted a detection analysis characterizing 60 years of land cover change in the Tanana Flats, a wetland complex subjected to TK disturbance in Interior Alaska, using aerial and satellite images. We observed a nonlinear loss of permafrost plateau forest associated with TK and driven by precipitation and forest fragmentation. The results of this analysis were integrated into the Alaska Thermokarst Model (ATM), a state-and-transition model that simulates land cover change associated with TK disturbance. Thermokarst-related land cover change was simulated from 2000 to 2100 across the Tanana Flats. By 2100, the model predicts a mean decrease of 7.4% (sd 1.8%) in permafrost plateau forests associated with an increase in TK fens and bogs. Transitions from permafrost plateau forests to TK wetlands are accompanied with changes in physical and biogeochemical processes affecting ecosystem carbon balance. We evaluated the consequences of TK disturbances on the regional carbon balance by coupling outputs from the ATM and from a process-based biogeochemical model. We used long-term field observations of vegetation and soil physical and biogeochemical attributes to develop new parameterizations for TK wetlands and permafrost plateau forest land cover types. Preliminary simulations from 2000 to 2100 estimate that the conversion of permafrost plateau forest to young TK wetlands would result in a 7.5% (sd 3.5%) decrease in Net Ecosystem Exchange.

Growing C4 perennial grass for bioenergy using a new Agro-BGC ecosystem model

NASA Astrophysics Data System (ADS)

di Vittorio, A. V.; Anderson, R. S.; Miller, N. L.; Running, S. W.

2009-12-01

Accurate, spatially gridded estimates of bioenergy crop yields require 1) biophysically accurate crop growth models and 2) careful parameterization of unavailable inputs to these models. To meet the first requirement we have added the capacity to simulate C4 perennial grass as a bioenergy crop to the Biome-BGC ecosystem model. This new model, hereafter referred to as Agro-BGC, includes enzyme driven C4 photosynthesis, individual live and dead leaf, stem, and root carbon/nitrogen pools, separate senescence and litter fall processes, fruit growth, optional annual seeding, flood irrigation, a growing degree day phenology with a killing frost option, and a disturbance handler that effectively simulates fertilization, harvest, fire, and incremental irrigation. There are four Agro-BGC vegetation parameters that are unavailable for Panicum virgatum (switchgrass), and to meet the second requirement we have optimized the model across multiple calibration sites to obtain representative values for these parameters. We have verified simulated switchgrass yields against observations at three non-calibration sites in IL. Agro-BGC simulates switchgrass growth and yield at harvest very well at a single site. Our results suggest that a multi-site optimization scheme would be adequate for producing regional-scale estimates of bioenergy crop yields on high spatial resolution grids.

A generic biogeochemical module for earth system models

NASA Astrophysics Data System (ADS)

Fang, Y.; Huang, M.; Liu, C.; Li, H.-Y.; Leung, L. R.

2013-06-01

Physical and biogeochemical processes regulate soil carbon dynamics and CO2 flux to and from the atmosphere, influencing global climate changes. Integration of these processes into earth system models (e.g. community land models - CLM), however, currently faces three major challenges: (1) extensive efforts are required to modify modeling structures and to rewrite computer programs to incorporate new or updated processes as new knowledge is being generated, (2) computational cost is prohibitively expensive to simulate biogeochemical processes in land models due to large variations in the rates of biogeochemical processes, and (3) various mathematical representations of biogeochemical processes exist to incorporate different aspects of fundamental mechanisms, but systematic evaluation of the different mathematical representations is difficult, if not impossible. To address these challenges, we propose a new computational framework to easily incorporate physical and biogeochemical processes into land models. The new framework consists of a new biogeochemical module with a generic algorithm and reaction database so that new and updated processes can be incorporated into land models without the need to manually set up the ordinary differential equations to be solved numerically. The reaction database consists of processes of nutrient flow through the terrestrial ecosystems in plants, litter and soil. This framework facilitates effective comparison studies of biogeochemical cycles in an ecosystem using different conceptual models under the same land modeling framework. The approach was first implemented in CLM and benchmarked against simulations from the original CLM-CN code. A case study was then provided to demonstrate the advantages of using the new approach to incorporate a phosphorus cycle into the CLM model. To our knowledge, the phosphorus-incorporated CLM is a new model that can be used to simulate phosphorus limitation on the productivity of terrestrial ecosystems.

Uncertainty analysis of a coupled ecosystem response model simulating greenhouse gas fluxes from a temperate grassland

NASA Astrophysics Data System (ADS)

Liebermann, Ralf; Kraft, Philipp; Houska, Tobias; Breuer, Lutz; Müller, Christoph; Kraus, David; Haas, Edwin; Klatt, Steffen

2015-04-01

Among anthropogenic greenhouse gas emissions, CO2 is the dominant driver of global climate change. Next to its direct impact on the radiation budget, it also affects the climate system by triggering feedback mechanisms in terrestrial ecosystems. Such mechanisms - like stimulated photosynthesis, increased root exudations and reduced stomatal transpiration - influence both the input and the turnover of carbon and nitrogen compounds in the soil. The stabilization and decomposition of these compounds determines how increasing CO2 concentrations change the terrestrial trace gas emissions, especially CO2, N2O and CH4. To assess the potential reaction of terrestrial greenhouse gas emissions to rising tropospheric CO2 concentration, we make use of a comprehensive ecosystem model integrating known processes and fluxes of the carbon-nitrogen cycle in soil, vegetation and water. We apply a state-of-the-art ecosystem model with measurements from a long term field experiment of CO2 enrichment. The model - a grassland realization of LandscapeDNDC - simulates soil chemistry coupled with plant physiology, microclimate and hydrology. The data - comprising biomass, greenhouse gas emissions, management practices and soil properties - has been attained from a FACE (Free Air Carbon dioxide Enrichment) experiment running since 1997 on a temperate grassland in Giessen, Germany. Management and soil data, together with weather records, are used to drive the model, while cut biomass as well as CO2 and N2O emissions are used for calibration and validation. Starting with control data from installations without CO2 enhancement, we begin with a GLUE (General Likelihood Uncertainty Estimation) assessment using Latin Hypercube to reduce the range of the model parameters. This is followed by a detailed sensitivity analysis, the application of DREAM-ZS for model calibration, and an estimation of the effect of input uncertainty on the simulation results. Since first results indicate problems with the correct representation of the seasonal cycle of soil moisture and N2O emissions, our model is soon to be augmented with a more elaborate sub model for hydrology. Subsequent steps include the comparison of simulations and measurements under 20% elevated atmospheric CO2 concentrations, and the integration of a Farquhar-type sub model for photosynthesis.

Monitoring and Simulating Water, Carbon and Nitrogen Dynamics over Catchments in Eastern Asia

NASA Astrophysics Data System (ADS)

Wang, Q.; Xiao, Q.; Liu, C.; Watanabe, M.

2006-05-01

There is an emergency need to support decision-making in water environment management in Eastern Asia. For sound management and decision making of sustainable water use, the catchment ecosystem assessment, emphasizing biophysical and biogeochemical processes and human interactions, is a key task. For this task, an integrated ecosystem model has been developed to estimate the spatial and temporal distributions of the water, carbon and nutrient cycles over catchment scales. The model integrated both a distributed hydrologic model (Nakayama and Watanabe, 2004) and an ecosystem model, BIOME-BGC (Running and Coughlan, 1988), which has been modified and validated for various ecosystems by using the APEIS-FLUX datasets in China (Wang and Watanabe, 2005). The model has been applied to catchments in China, such as the Changjiang River and the Yellow River. The MODIS satellite data products, such as leaf area index (LAI), vegetation index (VI) and land surface temperature (LST) were used as the input parameters. By using the integrated model, the future changes in water, carbon and nitrogen cycle can be predicted based on scenarios, such as the decrease in crop production due to water shortage, and the increase in temperature and CO2 concentration, as well as the land use/cover changes. The model was validated by the measured values of soil moisture, and river flow discharge throughout the year, showing that this model achieves a fairly high accuracy. As an example, we applied the integrated model to simulate the daily water vapor, carbon and nitrogen fluxes over the Changjiang River Basin. The Changjiang River is ranked third in length and is the largest river in terms of water discharge over the Euro-Asian continent. The drainage basin of the Changjiang supplies 5-10% of the total world population with water resources and nutrition and irrigates 40% of China's national crop production. Moreover, the materials carried by the Changjiang River have a significant influence on the coastal environment. Simulation results showed that enhanced atmospheric CO2 concentrations and especially increased nitrogen application had a marked effect on the simulated water and carbon sequestration capacity and played a prominent role in increasing this capacity. Finally, the model has been applied to evaluate the impact of land cover change from 1980 to 2000 on water, carbon and nitrogen fluxes over larger river basins in China.

Simulating changes in ecosystem structure and composition in response to climate change: a case study focused on tropical nitrogen-fixing trees (Invited)

NASA Astrophysics Data System (ADS)

Medvigy, D.; Levy, J.; Xu, X.; Batterman, S. A.; Hedin, L.

2013-12-01

Ecosystems, by definition, involve a community of organisms. These communities generally exhibit heterogeneity in their structure and composition as a result of local variations in climate, soil, topography, disturbance history, and other factors. Climate-driven shifts in ecosystems will likely include an internal re-organization of community structure and composition and as well as the introduction of novel species. In terms of vegetation, this ecosystem heterogeneity can occur at relatively small scales, sometimes of the order of tens of meters or even less. Because this heterogeneous landscape generally has a variable and nonlinear response to environmental perturbations, it is necessary to carefully aggregate the local competitive dynamics between individual plants to the large scales of tens or hundreds of kilometers represented in climate models. Accomplishing this aggregation in a computationally efficient way has proven to be an extremely challenging task. To meet this challenge, the Ecosystem Demography 2 (ED2) model statistically characterizes a distribution of local resource environments, and then simulates the competition between individuals of different sizes and species (or functional groupings). Within this framework, it is possible to explicitly simulate the impacts of climate change on ecosystem structure and composition, including both internal re-organization and the introduction of novel species or functional groups. This presentation will include several illustrative applications of the evolution of ecosystem structure and composition under climate change. One application pertains to the role of nitrogen-fixing species in tropical forests. Will increasing CO2 concentrations increase the demand for nutrients and perhaps give a competitive edge to nitrogen-fixing species? Will potentially warmer and drier conditions make some tropical forests more water-limited, reducing the demand for nitrogen, thereby giving a competitive advantage to non-nitrogen-fixing species? Will the response of nitrogen-fixing species to climate change be sensitive to local disturbance histories?

Decline of the marine ecosystem caused by a reduction in the Atlantic overturning circulation.

PubMed

Schmittner, Andreas

2005-03-31

Reorganizations of the Atlantic meridional overturning circulation were associated with large and abrupt climatic changes in the North Atlantic region during the last glacial period. Projections with climate models suggest that similar reorganizations may also occur in response to anthropogenic global warming. Here I use ensemble simulations with a coupled climate-ecosystem model of intermediate complexity to investigate the possible consequences of such disturbances to the marine ecosystem. In the simulations, a disruption of the Atlantic meridional overturning circulation leads to a collapse of the North Atlantic plankton stocks to less than half of their initial biomass, owing to rapid shoaling of winter mixed layers and their associated separation from the deep ocean nutrient reservoir. Globally integrated export production declines by more than 20 per cent owing to reduced upwelling of nutrient-rich deep water and gradual depletion of upper ocean nutrient concentrations. These model results are consistent with the available high-resolution palaeorecord, and suggest that global ocean productivity is sensitive to changes in the Atlantic meridional overturning circulation.

National Geospatial-Intelligence Agency (NGA) Calibration Target Placements during HI-SCALE (Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems)

DOE Data Explorer

Kalukin, Andrew; Endo, Satashi

2016-08-30

Test the feasibility of incorporating atmospheric models to improve simulation algorithms of image collection, developed at NGA. Various calibration objects will be used to compare simulated image products with real image products.

Simulating forest productivity along a neotropical elevational transect: temperature variation and carbon use efficiency

NASA Astrophysics Data System (ADS)

Marthews, T.; Malhi, Y.; Girardin, C.; Silva-Espejo, J.; Aragão, L.; Metcalfe, D.; Rapp, J.; Mercado, L.; Fisher, R.; Galbraith, D.; Fisher, J.; Salinas-Revilla, N.; Friend, A.; Restrepo-Coupe, N.; Williams, R.

2012-04-01

A better understanding of the mechanisms controlling the magnitude and sign of carbon components in tropical forest ecosystems is important for reliable estimation of this important regional component of the global carbon cycle. We used the JULES vegetation model to simulate all components of the carbon balance at six sites along an Andes-Amazon transect across Peru and Brazil and compared the results to published field measurements. In the upper montane zone the model predicted a vegetation dieback, indicating a need for better parameterisation of cloud forest vegetation. In the lower montane and lowland zones simulated ecosystem productivity and respiration were predicted with reasonable accuracy, although not always within the error bounds of the observations. Model-predicted carbon use efficiency in this transect surprisingly did not increase with elevation, but remained close to the 'temperate' value 0.5. This may be explained by elevational changes in the balance between growth and maintenance respiration within the forest canopy, as controlled by both temperature- and pressure-mediated processes.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-11-01

In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

A Comparison of Simulated and Field-Derived Leaf Area Index (LAI) and Canopy Height Values from Four Forest Complexes in the Southeastern USA

EPA Science Inventory

Vegetative leaf area is a critical input to models that simulate human and ecosystem exposure to atmospheric pollutants. Leaf area index (LAI) can be measured in the field or numerically simulated, but all contain some inherent uncertainty that is passed to the exposure assessmen...

Incorporating an enzymatic model of effects of temperature, moisture, and substrate supply on soil respiration into an ecosystem model for two forests of northeastern USA

NASA Astrophysics Data System (ADS)

Sihi, Debjani; Davidson, Eric; Chen, Min; Savage, Kathleen; Richardson, Andrew; Keenan, Trevor; Hollinger, David

2017-04-01

Soils represent the largest terrestrial carbon (C) pool, and microbial decomposition of soil organic matter (SOM) to carbon dioxide, also called heterotrophic respiration (Rh), is an important component of the global C cycle. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed to disentangle the confounding factors of apparent temperature sensitivity of SOM decomposition and improve performance of ecosystem models and ESMs. The objective of this work was to incorporate into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen and soluble carbon substrates to the enzymatic reaction site. However, in its current configuration, DAMM depends on assumptions or inputs from other models regarding soil C inputs. Here we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration) by replacing FöBAAR's algorithms for Rh with those of DAMM. Classical root trenching experiments provided data to partition soil CO2 efflux into Rh (trenched plot) and root respiration (untrenched minus trenched plots). We used three years of high-frequency soil flux data from automated soil chambers (trenched and untrenched plots) and landscape-scale ecosystem fluxes from eddy covariance towers from two mid-latitude forests (Harvard Forest, MA and Howland Forest, ME) of northeastern USA to develop and validate the merged model and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal dynamics of Rh compared to the FöBAAR-only model for the Harvard Forest, as indicated by lower cost functions (model-data mismatch). However, DAMM-FöBAAR showed less improvement over FöBAAR-only for the boreal transition forest at Howland. The frequency of droughts is lower at Howland, due to a shallow water table, resulting in only brief water limitation affecting Rh in some years. At both sites, the declining trend of soil respiration during drought episodes was captured by the DAMM-FöBAAR model, but not the FöBAAR-only model, which simulates Rh using only a Q10 type function. Greater confidence in model prediction resulting from the inclusion of mechanistic simulation of moisture limitation on substrate availability, an emergent property of DAMM, depends on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the cost function. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than other commonly used empirical functions.

Exploring the co-evolution of marine ecology and environment in silico

NASA Astrophysics Data System (ADS)

Ridgwell, A.

2015-12-01

Species do not live in isolation, but adapt and ultimately, evolve, in relationship with other species as well as with their chemical and physical environment. In the marine environment, this interaction is intimately two-way - the surface biogeochemical environment modulates the makeup of the pelagic ecosystem, yet at the same time, the ecosystem assemblage, by setting the strength of the biological pump and ultimately, in regulating the carbon and nutrient inventory of the ocean and atmospheric pCO2, influences the surface geochemical environment. Feedbacks, both negative and positive, must therefore exist between plankton ecology and global biogeochemical cycles. This has implications for understanding the geological record and particularly the response and recovery of marine ecosystems following major environmental perturbation, but also complicates making projections of future ocean changes. To address a coupled system such as this, new numerical tools are needed as traditional 'functional type' marine ecosystem models are generally incapable of accounting for short-term adaptation, let alone long-term evolution. What is needed is the combination of a plankton model able to simulate a highly diverse ecology plus 'genetic' mutation (changes in trait value(s)) and extinction, *and* an Earth system model capable of simulating long-term evolution of the climatology and geochemistry of the ocean. The Earth system model 'cGENIE' - http://mycgenie.seao2.org generally fills the second criteria, so for this presentation I will focus on the structure of the ecosystem model, the associated methodology, and numerical techniques for dealing with what will turn out to be an exceptionally large number of ocean tracers. If you are really lucky, there may even be some preliminary results :)

Partitioning net ecosystem exchange of CO2 into gross primary production and ecosystem respiration in northern high-latitude ecosystems

NASA Astrophysics Data System (ADS)

Lund, M.; Zona, D.; Jackowicz-Korczynski, M.; Xu, X.

2017-12-01

The eddy covariance methodology is the primary tool for studying landscape-scale land-atmosphere exchange of greenhouse gases. Since the choice of instrumental setup and processing algorithms may influence the results, efforts within the international flux community have been made towards methodological harmonization and standardization. Performing eddy covariance measurements in high-latitude, Arctic tundra sites involves several challenges, related not only to remoteness and harsh climate conditions but also to the choice of processing algorithms. Partitioning of net ecosystem exchange (NEE) of CO2 into gross primary production (GPP) and ecosystem respiration (Reco) in the FLUXNET2015 dataset is made using either Nighttime or Daytime methods. These variables, GPP and Reco, are essential for calibration and validation of Earth system models. North of the Arctic Circle, sun remains visible at local midnight for a period of time, the number of days per year with midnight sun being dependent on latitude. The absence of nighttime conditions during Arctic summers renders the Nighttime method uncertain, however, no extensive assessment on the implications for flux partitioning has yet been made. In this study, we will assess the performance and validity of both partitioning methods along a latitudinal transect of northern sites included in the FLUXNET2015 dataset. We will evaluate the partitioned flux components against model simulations using the Community Land Model (CLM). Our results will be valuable for users interested in simulating Arctic and global carbon cycling.

Modeling compensatory responses of ecosystem-scale water fluxes in forests affected by pine and spruce beetle mortality

NASA Astrophysics Data System (ADS)

Millar, D.; Ewers, B. E.; Peckham, S. D.; Mackay, D. S.; Frank, J. M.; Massman, W. J.; Reed, D. E.

2015-12-01

Mountain pine beetle (Dendroctonus ponderosae) and spruce beetle (Dendroctonus rufipennis) epidemics have led to extensive mortality in lodgepole pine (Pinus contorta) and Engelmann spruce (Picea engelmannii) forests in the Rocky Mountains of the western US. In both of these tree species, mortality results from hydraulic failure within the xylem, due to blue stain fungal infection associated with beetle attack. However, the impacts of these disturbances on ecosystem-scale water fluxes can be complex, owing to their variable and transient nature. In this work, xylem scaling factors that reduced whole-tree conductance were initially incorporated into a forest ecohydrological model (TREES) to simulate the impact of beetle mortality on evapotranspiration (ET) in both pine and spruce forests. For both forests, simulated ET was compared to observed ET fluxes recorded using eddy covariance techniques. Using xylem scaling factors, the model overestimated the impact of beetle mortality, and observed ET fluxes were approximately two-fold higher than model predictions in both forests. The discrepancy between simulated and observed ET following the onset of beetle mortality may be the result of spatial and temporal heterogeneity of plant communities within the foot prints of the eddy covariance towers. Since simulated ET fluxes following beetle mortality in both forests only accounted for approximately 50% of those observed in the field, it is possible that newly established understory vegetation in recently killed tree stands may play a role in stabilizing ecosystem ET fluxes. Here, we further investigate the unaccounted for ET fluxes in the model by breaking it down into multiple cohorts that represent live trees, dying trees, and understory vegetation that establishes following tree mortality.

Simulation's Ensemble is Better Than Ensemble Simulation

NASA Astrophysics Data System (ADS)

Yan, X.

2017-12-01

Simulation's ensemble is better than ensemble simulation Yan Xiaodong State Key Laboratory of Earth Surface Processes and Resource Ecology (ESPRE) Beijing Normal University,19 Xinjiekouwai Street, Haidian District, Beijing 100875, China Email: yxd@bnu.edu.cnDynamical system is simulated from initial state. However initial state data is of great uncertainty, which leads to uncertainty of simulation. Therefore, multiple possible initial states based simulation has been used widely in atmospheric science, which has indeed been proved to be able to lower the uncertainty, that was named simulation's ensemble because multiple simulation results would be fused . In ecological field, individual based model simulation (forest gap models for example) can be regarded as simulation's ensemble compared with community based simulation (most ecosystem models). In this talk, we will address the advantage of individual based simulation and even their ensembles.

Soil Carbon Residence Time in the Arctic - Potential Drivers of Past and Future Change

NASA Astrophysics Data System (ADS)

Huntzinger, D. N.; Fisher, J.; Schwalm, C. R.; Hayes, D. J.; Stofferahn, E.; Hantson, W.; Schaefer, K. M.; Fang, Y.; Michalak, A. M.; Wei, Y.

2017-12-01

Carbon residence time is one of the most important factors controlling carbon cycling in ecosystems. Residence time depends on carbon allocation and conversion among various carbon pools and the rate of organic matter decomposition; all of which rely on environmental conditions, primarily temperature and soil moisture. As a result, residence time is an emergent property of models and a strong determinant of terrestrial carbon storage capacity. However, residence time is poorly constrained in process-based models due, in part, to the lack of data with which to benchmark global-scale models in order to guide model improvements and, ultimately, reduce uncertainty in model projections. Here we focus on improving the understanding of the drivers to observed and simulated carbon residence time in the Arctic-Boreal region (ABR). Carbon-cycling in the ABR represents one of the largest sources of uncertainty in historical and future projections of land-atmosphere carbon dynamics. This uncertainty is depicted in the large spread of terrestrial biospheric model (TBM) estimates of carbon flux and ecosystem carbon pool size in this region. Recent efforts, such as the Arctic-Boreal Vulnerability Experiment (ABoVE), have increased the availability of spatially explicit in-situ and remotely sensed carbon and ecosystem focused data products in the ABR. Together with simulations from Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we use these observations to evaluate the ability of models to capture soil carbon stocks and changes in the ABR. Specifically, we compare simulated versus observed soil carbon residence times in order to evaluate the functional response and sensitivity of modeled soil carbon stocks to changes in key environmental drivers. Understanding how simulated carbon residence time compares with observations and what drives these differences is critical for improving projections of changing carbon dynamics in the ABR and globally.

Implications of Uncertainty in Fossil Fuel Emissions for Terrestrial Ecosystem Modeling

NASA Astrophysics Data System (ADS)

King, A. W.; Ricciuto, D. M.; Mao, J.; Andres, R. J.

2017-12-01

Given observations of the increase in atmospheric CO2, estimates of anthropogenic emissions and models of oceanic CO2 uptake, one can estimate net global CO2 exchange between the atmosphere and terrestrial ecosystems as the residual of the balanced global carbon budget. Estimates from the Global Carbon Project 2016 show that terrestrial ecosystems are a growing sink for atmospheric CO2 (averaging 2.12 Gt C y-1 for the period 1959-2015 with a growth rate of 0.03 Gt C y-1 per year) but with considerable year-to-year variability (standard deviation of 1.07 Gt C y-1). Within the uncertainty of the observations, emissions estimates and ocean modeling, this residual calculation is a robust estimate of a global terrestrial sink for CO2. A task of terrestrial ecosystem science is to explain the trend and variability in this estimate. However, "within the uncertainty" is an important caveat. The uncertainty (2σ; 95% confidence interval) in fossil fuel emissions is 8.4% (±0.8 Gt C in 2015). Combined with uncertainty in other carbon budget components, the 2σ uncertainty surrounding the global net terrestrial ecosystem CO2 exchange is ±1.6 Gt C y-1. Ignoring the uncertainty, the estimate of a general terrestrial sink includes 2 years (1987 and 1998) in which terrestrial ecosystems are a small source of CO2 to the atmosphere. However, with 2σ uncertainty, terrestrial ecosystems may have been a source in as many as 18 years. We examine how well global terrestrial biosphere models simulate the trend and interannual variability of the global-budget estimate of the terrestrial sink within the context of this uncertainty (e.g., which models fall outside the 2σ uncertainty and in what years). Models are generally capable of reproducing the trend in net terrestrial exchange, but are less able to capture interannual variability and often fall outside the 2σ uncertainty. The trend in the residual carbon budget estimate is primarily associated with the increase in atmospheric CO2, while interannual variation is related to variations in global land-surface temperature with weaker sinks in warmer years. We examine whether these relationships are reproduced in models. Their absence might explain weaknesses in model simulations or in the reconstruction of historical climate used as drivers in model intercomparison projects (MIPs).

Simulating modern-day cropland and pasture burning in an Earth system model

NASA Astrophysics Data System (ADS)

Rabin, Sam; Malyshev, Sergey; Shevliakova, Elena; Magi, Brian; Pacala, Steve

2015-04-01

Throughout the Holocene, humans have extended our influence across a larger and larger fraction of ecosystems, even creating some new ones in the process. Herds of livestock grazing either native vegetation (rangeland) or specially planted species (pasture) have modified huge areas of land. We have even developed new plant species and cultivated them as crops. The extent of our ecosystem modification intensified dramatically with the advent of industrialized agriculture, to the point where cropland and pasture (which will henceforth encompass rangeland as well) now cover over a third of the Earth's land area. One way we have altered the terrestrial biosphere is by intentionally and unintentionally altering fire's frequency, intensity, and seasonal timing. This is especially true for agricultural ecosystems. Because their maintenance and use require a level of human control, cropland and pasture often experience fire regimes substantially different from those of the ecosystems they replaced or what would occur in the absence of active fire management. For example, farmers might burn to prepare land for planting or to dispose of crop residues, and pastoralists often use fire to prevent encroachment of unpalatable woody plants. Due to the vast global extent of agriculture, and considering the myriad ways fire affects the Earth system, it is critical that we understand (a) the ways people manage fire on cropland and pasture and (b) the effects of this management on the Earth system. Earth system models are an ideal tool for examining this kind of question. By simulating the processes within and interactions among the atmosphere, oceans, land, and terrestrial ecosystems, Earth system models allow phenomena such as fire to be examined in their global context. However, while the past fifteen years have seen great progress in the simulation of vegetation fire within Earth system models, the direct human influence via cropland and pasture management burning has been mostly ignored. Instead, indirect functions are usually used to incorporate human influence based on population density and economic factors. This paper describes a global fire model that incorporates knowledge from new estimates of cropland and pasture burning to explicitly simulate fire on those lands across the world. After briefly describing some of the agricultural fire patterns observed in Eurasia, we detail the structure of the model and context in which it was developed. We then use the model to investigate the contribution of cropland and pasture fire to emissions of greenhouse gases and aerosols, as well as net carbon cycling across the globe.

Baseline and Projected Future Carbon Stocks and Fluxes in the Hawaiian Islands

NASA Astrophysics Data System (ADS)

Selmants, P. C.; Sleeter, B. M.; Giardina, C. P.; Zhu, Z.; Asner, G. P.

2016-12-01

Hawaii is characterized by steep climatic gradients and heterogeneous land cover within a small geographic area, presenting a model tropical system to capture ecosystem carbon dynamics across a wide range of climate, soil, and land use conditions. However, ecosystem carbon balance is poorly understood on a statewide level, and the potential for climate and land use change to affect carbon dynamics in Hawaii has not been formally assessed. We estimated current baseline and projected future ecosystem carbon stocks and fluxes on the seven main Hawaiian Islands using a combination of remote sensing, published plot-level data, and simulation modeling. Total ecosystem carbon storage during the baseline period was estimated at 258 TgC, with 70% stored as soil organic carbon, 25% as live biomass and 5% as surface detritus, and gross primary production was estimated at 20 TgC y-1. Net ecosystem carbon balance, which incorporated carbon losses from freshwater aquatic fluxes to nearshore waters and wildland fire emissions, was estimated as 0.34 TgC y-1 during the baseline period, offsetting 7% of anthropogenic emissions. We used a state and transition simulation model to estimate the response of ecosystem carbon stocks and fluxes to potential changes in climate, land use, and wildfire over a 50-year projection period (2012-2061). Total ecosystem carbon storage was projected to increase by 5% by the year 2061, but net ecosystem carbon balance was projected to decline by 35% due to climate change induced reductions in statewide net primary production and increased carbon losses from land use and land cover change. Our analysis indicates that the State of Hawaii would remain a net carbon sink overall, primarily because of ecosystem carbon sequestration on Hawaii Island, but predicted changes in climate and land use on Kauai and Oahu would convert these islands to net carbon sources. The Hawaii carbon assessment is part of a larger effort by the U.S. Geological Survey to assess the carbon sequestration potential of ecosystems across the United States and should provide valuable information for setting research and policy priorities for sustainable carbon management strategies aimed at offsetting anthropogenic carbon emissions.

A model using marginal efficiency of investment to analyse carbon and nitrogen interactions in terrestrial ecosystems (ACONITE Version 1)

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-04-01

Carbon (C) and nitrogen (N) cycles are coupled in terrestrial ecosystems through multiple processes including photosynthesis, tissue allocation, respiration, N fixation, N uptake, and decomposition of litter and soil organic matter. Capturing the constraint of N on terrestrial C uptake and storage has been a focus of the Earth System modelling community. However there is little understanding of the trade-offs and sensitivities of allocating C and N to different tissues in order to optimize the productivity of plants. Here we describe a new, simple model of ecosystem C-N cycling and interactions (ACONITE), that builds on theory related to plant economics in order to predict key ecosystem properties (leaf area index, leaf C : N, N fixation, and plant C use efficiency) using emergent constraints provided by marginal returns on investment for C and/or N allocation. We simulated and evaluated steady-state ecosystem stocks and fluxes in three different forest ecosystems types (tropical evergreen, temperate deciduous, and temperate evergreen). Leaf C : N differed among the three ecosystem types (temperate deciduous < tropical evergreen < temperature evergreen), a result that compared well to observations from a global database describing plant traits. Gross primary productivity (GPP) and net primary productivity (NPP) estimates compared well to observed fluxes at the simulation sites. Simulated N fixation at steady-state, calculated based on relative demand for N and the marginal return on C investment to acquire N, was an order of magnitude higher in the tropical forest than in the temperate forest, consistent with observations. A sensitivity analysis revealed that parameterization of the relationship between leaf N and leaf respiration had the largest influence on leaf area index and leaf C : N. Also, a widely used linear leaf N-respiration relationship did not yield a realistic leaf C : N, while a more recently reported non-linear relationship performed better. A parameter governing how photosynthesis scales with day length had the largest influence on total vegetation C, GPP, and NPP. Multiple parameters associated with photosynthesis, respiration, and N uptake influenced the rate of N fixation. Overall, our ability to constrain leaf area index and have spatially and temporally variable leaf C : N helps address challenges for ecosystem and Earth System models. Furthermore, the simple approach with emergent properties based on coupled C-N dynamics has potential for use in research that uses data-assimilation methods to integrate data on both the C and N cycles to improve C flux forecasts.

The Apollo Structured Vocabulary: an OWL2 ontology of phenomena in infectious disease epidemiology and population biology for use in epidemic simulation.

PubMed

Hogan, William R; Wagner, Michael M; Brochhausen, Mathias; Levander, John; Brown, Shawn T; Millett, Nicholas; DePasse, Jay; Hanna, Josh

2016-08-18

We developed the Apollo Structured Vocabulary (Apollo-SV)-an OWL2 ontology of phenomena in infectious disease epidemiology and population biology-as part of a project whose goal is to increase the use of epidemic simulators in public health practice. Apollo-SV defines a terminology for use in simulator configuration. Apollo-SV is the product of an ontological analysis of the domain of infectious disease epidemiology, with particular attention to the inputs and outputs of nine simulators. Apollo-SV contains 802 classes for representing the inputs and outputs of simulators, of which approximately half are new and half are imported from existing ontologies. The most important Apollo-SV class for users of simulators is infectious disease scenario, which is a representation of an ecosystem at simulator time zero that has at least one infection process (a class) affecting at least one population (also a class). Other important classes represent ecosystem elements (e.g., households), ecosystem processes (e.g., infection acquisition and infectious disease), censuses of ecosystem elements (e.g., censuses of populations), and infectious disease control measures. In the larger project, which created an end-user application that can send the same infectious disease scenario to multiple simulators, Apollo-SV serves as the controlled terminology and strongly influences the design of the message syntax used to represent an infectious disease scenario. As we added simulators for different pathogens (e.g., malaria and dengue), the core classes of Apollo-SV have remained stable, suggesting that our conceptualization of the information required by simulators is sound. Despite adhering to the OBO Foundry principle of orthogonality, we could not reuse Infectious Disease Ontology classes as the basis for infectious disease scenarios. We thus defined new classes in Apollo-SV for host, pathogen, infection, infectious disease, colonization, and infection acquisition. Unlike IDO, our ontological analysis extended to existing mathematical models of key biological phenomena studied by infectious disease epidemiology and population biology. Our ontological analysis as expressed in Apollo-SV was instrumental in developing a simulator-independent representation of infectious disease scenarios that can be run on multiple epidemic simulators. Our experience suggests the importance of extending ontological analysis of a domain to include existing mathematical models of the phenomena studied by the domain. Apollo-SV is freely available at: http://purl.obolibrary.org/obo/apollo_sv.owl .

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad Z.; Estes, Maurice G., Jr.; Judd, Chaeli; Thom, Ron; Woodruff, Dana; Ellis, Jean T.; Quattrochi, Dale; Watson, Brian; Rodriquez, Hugo; Johnson, Hoyt

2012-01-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA s EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

Using Remotely Sensed Data and Watershed and Hydrodynamic Models to Evaluate the Effects of Land Cover Land Use Change on Aquatic Ecosystems in Mobile Bay, AL

NASA Astrophysics Data System (ADS)

Al-Hamdan, M. Z.; Estes, M. G.; Judd, C.; Thom, R.; Woodruff, D.; Ellis, J. T.; Quattrochi, D.; Watson, B.; Rodriguez, H.; Johnson, H.

2012-12-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land cover land use (LCLU) change in the two counties surrounding Mobile Bay (Mobile and Baldwin) on SAV stressors and controlling factors (temperature, salinity, and sediment) in the Mobile Bay estuary. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for LCLU scenarios in 1948, 1992, 2001, and 2030. Remotely sensed Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 LCLU scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the estuary. These results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid throughout Mobile Bay and adjacent estuaries. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to LCLU driven flow changes with the restoration potential of SAVs. Data products and results are being integrated into NOAA's EcoWatch and Gulf of Mexico Data Atlas online systems for dissemination to coastal resource managers and stakeholders.

From precipitation to groundwater baseflow in a native prairie ecosystem: a regional study of the Konza LTER in the Flint Hills of Kansas, USA

USDA-ARS?s Scientific Manuscript database

Methods are developed to study hydrologic interactions across the surficial/groundwater interface in a native prairie ecosystem. Surficial ecohydrologic processes are simulated with the USDA’s EPIC model using daily climate data from the Kansas Weather Data Library, vegetation and soil data from the...

An original model of the northern Gulf of Mexico using Ecopath with Ecosim and its implications for the effects of fishing on ecosystem structure and maturity

NASA Astrophysics Data System (ADS)

Geers, T. M.; Pikitch, E. K.; Frisk, M. G.

2016-07-01

The Gulf of Mexico (GoM) is a valuable ecosystem both socially and economically, and fisheries contribute substantially to this value. Gulf menhaden, Brevoortia patronus, support the largest fishery in the Gulf (by weight) and provide forage for marine mammals, seabirds and commercially and recreationally important fish species. Understanding the complex interactions among multiple fisheries and myriad unfished species requires tools different from those used in traditional single-species management. One such tool, Ecopath with Ecosim (EwE) is increasingly being used to construct food web models of aquatic ecosystems and to evaluate fisheries management options within a broader, ecosystem context. Here, an EwE model was developed to examine the impact of Gulf fisheries on ecosystem structure and maturity. This model builds on previously published EwE models of the GoM, and is tailored to the range and habitat of Gulf menhaden. The model presented here consists of 47 functional groups, including 4 seabird groups, 1 marine mammal group, 3 elasmobranch groups, 26 bony fish groups, 9 invertebrate groups, 3 primary producer groups and 1 detritus group. A number of different management scenarios for Gulf fisheries were modeled and the results were evaluated in terms of impacts on ecosystem maturity and development. The results of the model simulations indicated that the northern Gulf of Mexico is in an immature state (sensuOdum, 1969). Management scenarios that increased fishing pressure over time consistently resulted in a decrease in the maturity indices. In particular, we found that Gulf menhaden, as a key forage fish in the ecosystem, plays a substantial role in the structure and functioning of the ecosystem.

Modelling hydrological processes and analysing water-related ecosystem services of Western Siberian lowland basins

NASA Astrophysics Data System (ADS)

Schmalz, Britta; Kiesel, Jens; Kruse, Marion; Pfannerstill, Matthias; Sheludkov, Artyom; Khoroshavin, Vitaliy; Veshkurseva, Tatyana; Müller, Felix; Fohrer, Nicola

2015-04-01

For discussing and planning sustainable land management of river basins, stakeholders need suitable information on spatio-temporal patterns of hydrological components and ecosystem services. The ecosystem services concept, i.e., services provided by ecosystems that contribute to human welfare benefits, contributes comprehensive information for sustainable river management. This study shows an approach to use ecohydrological modelling results for quantifying and assessing water-related ecosystem services in three lowland river basins in Western Siberia, a region which is of global significance in terms of carbon sequestration, agricultural production and biodiversity preservation. Using the ecohydrological model SWAT, the three basins Pyschma (16762 km²), Vagai (3348 km²) and Loktinka (373 km²) were modelled following a gradient from the landscape units taiga, pre-taiga to forest steppe. For a correct representation of the Siberian lowland hydrology, the consideration of snow melt and retention of surface runoff as well as the implementation of a second groundwater aquifer was of great importance. Good to satisfying model performances were obtained for the extreme hydrological conditions. The simulated SWAT output variables of different hydrological processes were used as indicators for the two regulating services water flow and erosion regulation. The model results were translated into a relative ecosystem service valuation scale. The resulting ecosystem service maps show different spatial and seasonal patterns. Although the high resolution modelling results are averaged out within the aggregated relative valuation scale, seasonal differences can be depicted: during snowmelt, low relevant regulation can be determined, especially for water flow regulation, but a very high relevant regulation was calculated for the vegetation period during summer and for the winter period. The SWAT model serves as a suitable quantification method for the assessment of water-related ecosystem services on different spatial scales and ecoregions of the Western Siberian lowlands.

Modeling of larch forest dynamics under a changing climate in eastern Siberia

NASA Astrophysics Data System (ADS)

Nakai, T.; Kumagai, T.; Iijima, Y.; Ohta, T.; Kotani, A.; Maximov, T. C.; Hiyama, T.

2017-12-01

According to the projection by an earth system model under RCP8.5 scenario, boreal forest in eastern Siberia (near Yakutsk) is predicted to experience significant changes in climate, in which the mean annual air temperature is projected to be positive and the annual precipitation will be doubled by the end of 21st century. Since the forest in this region is underlain by continuous permafrost, both increasing temperature and precipitation can affect the dynamics of forest through the soil water processes. To investigate such effects, we adopted a newly developed terrestrial ecosystem dynamics model named S-TEDy (SEIB-DGVM-originated Terrestrial Ecosystem Dynamics model), which mechanistically simulates "the way of life" of each individual tree and resulting tree mortality under the future climate conditions. This model was first developed for the simulation of the dynamics of a tropical rainforest in the Borneo Island, and successfully reproduced higher mortality of large trees due to a prolonged drought induced by ENSO event of 1997-1998. To apply this model to a larch forest in eastern Siberia, we are developing a soil submodel to consider the effect of thawing-freezing processes. We will present a simulation results using the future climate projection.

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.

Trophic models: What do we learn about Celtic Sea and Bay of Biscay ecosystems?

NASA Astrophysics Data System (ADS)

Moullec, Fabien; Gascuel, Didier; Bentorcha, Karim; Guénette, Sylvie; Robert, Marianne

2017-08-01

Trophic models are key tools to go beyond the single-species approaches used in stock assessments to adopt a more holistic view and implement the Ecosystem Approach to Fisheries Management (EAFM). This study aims to: (i) analyse the trophic functioning of the Celtic Sea and the Bay of Biscay, (ii) investigate ecosystem changes over the 1980-2013 period and, (iii) explore the response to management measures at the food web scale. Ecopath models were built for each ecosystem for years 1980 and 2013, and Ecosim models were fitted to time series data of biomass and catches. EcoTroph diagnosis showed that in both ecosystems, fishing pressure focuses on high trophic levels (TLs) and, to a lesser extent, on intermediate TLs. However, the interplay between local environmental conditions, species composition and ecosystem functioning could explain the different responses to fisheries management observed between these two contiguous ecosystems. Indeed, over the study period, the ecosystem's exploitation status has improved in the Bay of Biscay but not in the Celtic Sea. This improvement does not seem to be sufficient to achieve the objectives of an EAFM, as high trophic levels were still overexploited in 2013 and simulations conducted with Ecosim in the Bay of Biscay indicate that at current fishing effort the biomass will not be rebuilt by 2030. The ecosystem's response to a reduction in fishing mortality depends on which trophic levels receive protection. Reducing fishing mortality on pelagic fish, instead of on demersal fish, appears more efficient at maximising catch and total biomass and at conserving both top-predator and intermediate TLs. Such advice-oriented trophic models should be used on a regular basis to monitor the health status of marine food webs and analyse the trade-offs between multiple objectives in an ecosystem-based fisheries management context.

Simulating soybean productivity under rainfed conditions for major soil types using APEX model in East Central Mississippi

Treesearch

Bangbang Zhang; Gary Feng; John J. Read; Xiangbin Kong; Ying Ouyang; Ardeshir Adeli; Johnie N. Jenkins

2016-01-01

Knowledge of soybean yield constraints under rainfed conditions on major soil types in East CentralMississippi would assist growers in the region to effectively utilize the benefits of water/irrigation man-agement. The objectives of this study were to use the Agricultural Policy/Environmental eXtender (APEX)agro-ecosystem model to simulate rainfed soybean grain yield (...

Modelling the process-based controls of long term CO2 exchange in High Arctic heath ecosystems

NASA Astrophysics Data System (ADS)

Zhang, W.; Jansson, P. E.; Elberling, B.

2016-12-01

Frozen organic carbon (C) stored in northern permafrost soils may become vulnerable due to the rapid warming of the Arctic. The loss of C as greenhouse gases may imply a critical warming potential, resulting in positive feedbacks to global climate change. However, how permafrost ecosystems C dynamics is associated with changes in hydrothermal conditions (e.g. extent and duration of snow, soil water content and active layer depth) and changes in the responses of ecosystem biogeochemistry to climate (e.g. carbon assimilation of the entire growing season, falling rates of plants' litter, and turnover rates of different soil carbon pools) is still unclear and needs to be distinguished from site to site. Here, we use a process-oriented model (CoupModel) that couples heat and mass transfer within the high resolution soil-plant-atmosphere profile to simulate the high Arctic Cassiope tetragona Heath ecosystems in Northeast Greenland. The 15 years of net ecosystem exchange (NEE) flux (2000-2014) measured during the growing season indicate that the ecosystems may be at a transition from a C sink to a C source. We calibrated the model with the NEE flux transformed from hourly data to daily, yearly and total cumulative data to identify ensembles of parameters that best described the various patterns in the observed C fluxes. Only the ensembles of yearly and total cumulative transformation described reasonably well for seasonal variability, inter-annual variability and long term trends of measurements. The correlations between parameters and simulation performance described the relative importance of physical or biological parameters that contributes to the short- and long-term variation of C flux from biogeochemical processes of such ecosystems. The estimated C budget including internal fluxes and redistribution between various pools showed that the ecosystem functioned as a C source in the first-half period and a week C sink in the second-half period. The respiration outside the growing season was mainly from the autotropic respiration of plants, occupying a considerable portion of the total yearly respiration. The dynamics of soil C fluxes were associated with the variations of air temperature, snow fall and soil moisture of the shoulder seasons.

KABAM Version 1.0 User's Guide and Technical Documentation - Appendix A - Description of Bioaccumulation Model

EPA Pesticide Factsheets

The purpose of this model is to estimate chemical concentrations (CB) and BCF and BAF values for aquatic ecosystems. KABAM is a simulation model used to predict pesticide concentrations in aquatic regions for use in exposure assessments.

Assimilation of ocean colour to improve the simulation and understanding of the North West European shelf-sea ecosystem

NASA Astrophysics Data System (ADS)

Ciavatta, Stefano; Brewin, Robert; Skakala, Jozef; Sursham, David; Ford, David

2017-04-01

Shelf-seas and coastal zones provide essential goods and services to humankind, such as fisheries, aquaculture, tourism and climate regulation. The understanding and management of these regions can be enhanced by merging ocean-colour observations and marine ecosystem simulations through data assimilation, which provides (sub)optimal estimates of key biogeochemical variables. Here we present a range of applications of ocean-colour data assimilation in the North West European shelf-sea. A reanalysis application illustrates that assimilation of error-characterized chlorophyll concentrations could provide a map of the shelf sea vulnerability to oxygen deficiency, as well as estimates of the shelf sea uptake of atmospheric carbon dioxide (CO2) in the last decade. The interannual variability of CO2 uptake and its uncertainty were related significantly to interannual fluctuations of the simulated primary production. However, the reanalysis also indicates that assimilation of total chlorophyll did not improve significantly the simulation of some other variables, e.g. nutrients. We show that the assimilation of alternative products derived from ocean colour (i.e. spectral diffuse attenuation coefficient and phytoplankton size classes) can overcome this limitation. In fact, these products can constrain a larger number of model variables, which define either the underwater light field or the structure of the lower trophic levels. Therefore, the assimilation of such ocean-colour products into marine ecosystem models is an advantageous novel approach to improve the understanding and simulation of shelf-sea environments.

Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J. F.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-12-01

This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m-2 yr-1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Resilience of the Eastern Chukchi Sea Food Web to Mortality Based Perturbations and Identification of Ecologically Important Species

NASA Astrophysics Data System (ADS)

Whitehouse, G. A.; Aydin, K.

2016-02-01

Evidence of climate impacts on Arctic marine ecosystems is accumulating and Arctic marine ecosystems face additional pressures that may accompany increasing human activities due to improved access following reductions in sea ice cover. Thus, there is growing demand for information on how Arctic ecosystems may respond to potential disturbance. We explore the response of the eastern Chukchi Sea food web to mortality based perturbations using the dynamic food web modeling framework, Ecopath with Ecosim. We generated thousands of ecosystems by drawing random sets of model parameters from informative prior distributions and only retained those ecosystems that resulted in plausible, numerically stable configurations (no extinctions or population growth without limit). To perturb the systems, we increased mortality rates for selected functional groups then ran the retained models forward 50 years to examine how the biomass of other functional groups responded, and evaluated the resilience of the food web as the time for all functional groups to return to within 10 percent of their starting biomass. Ecologically important species were identified as those species (or functional groups of species) for whom changes in mortality had the greatest effect on the remainder of the food web. We also report on how a selection of ecosystem scale properties were affected by selected perturbations, including mean biomass longevity, the distribution of biomass across trophic levels, and a selection of dimensionless biomass ratios. These perturbations simulate a range of potential impacts that mortality events may have on the food web of the eastern Chukchi Sea, and indicate the directional response of other species and functional groups to these simulated events. This information will be of value to decision makers and resource managers developing guidelines for commercial and industrial development in the eastern Chukchi Sea.

Global covariation of carbon turnover times with climate in terrestrial ecosystems.

PubMed

Carvalhais, Nuno; Forkel, Matthias; Khomik, Myroslava; Bellarby, Jessica; Jung, Martin; Migliavacca, Mirco; Mu, Mingquan; Saatchi, Sassan; Santoro, Maurizio; Thurner, Martin; Weber, Ulrich; Ahrens, Bernhard; Beer, Christian; Cescatti, Alessandro; Randerson, James T; Reichstein, Markus

2014-10-09

The response of the terrestrial carbon cycle to climate change is among the largest uncertainties affecting future climate change projections. The feedback between the terrestrial carbon cycle and climate is partly determined by changes in the turnover time of carbon in land ecosystems, which in turn is an ecosystem property that emerges from the interplay between climate, soil and vegetation type. Here we present a global, spatially explicit and observation-based assessment of whole-ecosystem carbon turnover times that combines new estimates of vegetation and soil organic carbon stocks and fluxes. We find that the overall mean global carbon turnover time is 23(+7)(-4) years (95 per cent confidence interval). On average, carbon resides in the vegetation and soil near the Equator for a shorter time than at latitudes north of 75° north (mean turnover times of 15 and 255 years, respectively). We identify a clear dependence of the turnover time on temperature, as expected from our present understanding of temperature controls on ecosystem dynamics. Surprisingly, our analysis also reveals a similarly strong association between turnover time and precipitation. Moreover, we find that the ecosystem carbon turnover times simulated by state-of-the-art coupled climate/carbon-cycle models vary widely and that numerical simulations, on average, tend to underestimate the global carbon turnover time by 36 per cent. The models show stronger spatial relationships with temperature than do observation-based estimates, but generally do not reproduce the strong relationships with precipitation and predict faster carbon turnover in many semi-arid regions. Our findings suggest that future climate/carbon-cycle feedbacks may depend more strongly on changes in the hydrological cycle than is expected at present and is considered in Earth system models.

N2O Source Strength of Tropical Rain Forests: From the Site to the Global Scale

NASA Astrophysics Data System (ADS)

Kiese, R.; Werner, C.; Butterbach-Bahl, K.

2006-12-01

In contrast to the significant importance of tropical rain forest ecosystems as one of the major single sources within the global atmospheric N2O budget (2.2 3.7 Tg N y-1, regional and global estimates of their N2O source strength are still limited and highly uncertain. However, accurate quantification of sources and sinks of greenhouse gases like CO2, N2O and CH4 for natural, agricultural and forest ecosystems is crucial to our understanding of land use change effects on global climate change. At present, up-scaling approaches which link detailed geographic information systems (GIS) to mechanistic biochemical models are seen as a promising tool to contribute towards more reliable estimates of biogenic sources of N2O, e.g. tropical rain forest ecosystems. In our study we further developed and tested the PnET-N-DNDC model using Bayesian calibration techniques based on detailed N2O emission data of two recently conducted field campaigns in African (Kenya) and Asian (SE-China) tropical forest ecosystems and additional datasets from earlier own field campaigns or the literature. For global upscaling of N2O emissions an extensive GIS database was constructed holding all necessary parameters (climate ECWMF ERA 40; soil: FAO, vegetation: LPJ-DGVM simulation) in spatial and temporal resolution for initializing and driving the further developed biogeochemical model at a grid size of 0.25°x0.25°. We calculated global N2O emissions inventories for the years 1991 to 2001, and found a general agreement of the simulated flux ranges with reported N2O emissions from tropical forest ecosystems worldwide. According to our simulations, tropical rainforest soils are indeed a significant source of atmospheric N2O ranging from 1.1 2.2 Tg in dependence from the simulated year. Notably, related to differences in environmental conditions, N2O emissions varied considerably within the tropical belt. Furthermore, our simulations revealed a pronounced inter-annual variability of N2O emissions mainly driven by differences in weather conditions (e.g. distribution and total amount of rainfall) across years, which may be mirrored in atmospheric N2O concentrations.

Qualitative modelling for the Caeté Mangrove Estuary (North Brazil): a preliminary approach to an integrated eco-social analysis

NASA Astrophysics Data System (ADS)

Ortiz, Marco; Wolff, Matthias

2004-10-01

The sustainability of different integrated management regimes for the mangrove ecosystem of the Caeté Estuary (North Brazil) were assessed using a holistic theoretical framework. As a way to demonstrate that the behaviour and trajectory of complex whole systems are not epiphenomenal to the properties of the small parts, a set of conceptual models from more reductionistic to more holistic were enunciated. These models integrate the scientific information published until present for this mangrove ecosystem. The sustainability of different management scenarios (forestry and fishery) was assessed. Since the exploitation of mangrove trees is not allowed according Brazilian laws, the forestry was only included for simulation purposes. The model simulations revealed that sustainability predictions of reductionistic models should not be extrapolated into holistic approaches. Forestry and fishery activities seem to be sustainable only if they are self-damped. The exploitation of the two mangrove species Rhizophora mangle and Avicenia germinans does not appear to be sustainable, thus a rotation harvest is recommended. A similar conclusion holds for the exploitation of invertebrate species. Our results suggest that more studies should be focused on the estimation of maximum sustainable yield based on a multispecies approach. Any reference to holistic sustainability based on reductionistic approaches may distort our understanding of the natural complex ecosystems.

The resilience and functional role of moss in boreal and arctic ecosystems

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

Turetsky, Merritt; Bond-Lamberty, Benjamin; Euskirchen, Eugenie S.

2012-08-24

Mosses in boreal and arctic ecosystems are ubiquitous components of plant communities, represent an important component of plant diversity, and strongly influence the cycling of water, nutrients, energy and carbon. Here we use a literature review and synthesis as well as model simulations to explore the role of moss in ecological stability and resilience. Our literature review of moss community responses to disturbance showed all possible responses (increases, decreases, no change) within most disturbance categories in boreal and arctic regions. Our modeling simulations suggest that loss of moss within northern plant communities will reduce soil carbon accumulation primarily by influencingmore » decomposition rates and soil nitrogen availability. While two models (HPM and STM-TEM) showed a significant effect of moss removal, results from the Biome-BGC and DVM-TEM models suggest that northern, moss-rich ecosystems would need to experience extreme perturbation before mosses were eliminated. We highlight a number of issues that have not been adequately explored in moss communities, such as functional redundancy and singularity, relationships between response and effect traits, phenotypical plasticity in traits, and whether the effects of moss on ecosystem processes scale with local abundance. We also suggest that as more models explore issues related to ecological resilience, issues related to both parameter and conceptual uncertainty should be addressed: are the models more limited by uncertainty in the parameterization of the processes included or by what is not represented in the model at all? It seems clear from our review that mosses need to be incorporated into models as one or more plant functional types, but more empirical work is needed to determine how to best aggregate species.« less

Divergent predictions of carbon storage between two global land models: attribution of the causes through traceability analysis

NASA Astrophysics Data System (ADS)

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; Asrar, Ghassem R.; Leng, Guoyong; Wang, Yingping; Luo, Yiqi

2016-07-01

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted ˜ 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivity (NPP) and ecosystem residence time (τE), the predicted difference in the storage capacity between the two models results from differences in either NPP or τE or both. Our analysis showed that CLM-CASA' simulated 37 % higher NPP than CABLE. On the other hand, τE, which was a function of the baseline carbon residence time (τ'E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τE was mainly caused by longer τ'E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ'E. Overall, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

DOE PAGES

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra; ...

2016-07-29

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Divergent predictions of carbon storage between two global land models: Attribution of the causes through traceability analysis

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

Rafique, Rashid; Xia, Jianyang; Hararuk, Oleksandra

Representations of the terrestrial carbon cycle in land models are becoming increasingly complex. It is crucial to develop approaches for critical assessment of the complex model properties in order to understand key factors contributing to models' performance. In this study, we applied a traceability analysis which decomposes carbon cycle models into traceable components, for two global land models (CABLE and CLM-CASA') to diagnose the causes of their differences in simulating ecosystem carbon storage capacity. Driven with similar forcing data, CLM-CASA' predicted – 31 % larger carbon storage capacity than CABLE. Since ecosystem carbon storage capacity is a product of net primary productivitymore » (NPP) and ecosystem residence time ( τ E), the predicted difference in the storage capacity between the two models results from differences in either NPP or τ E or both. Our analysis showed that CLM-CASA'simulated 37 % higher NPP than CABLE. On the other hand, τ E, which was a function of the baseline carbon residence time ( τ' E) and environmental effect on carbon residence time, was on average 11 years longer in CABLE than CLM-CASA'. This difference in τ E was mainly caused by longer τ' E of woody biomass (23 vs. 14 years in CLM-CASA'), and higher proportion of NPP allocated to woody biomass (23 vs. 16 %). Differences in environmental effects on carbon residence times had smaller influences on differences in ecosystem carbon storage capacities compared to differences in NPP and τ' E. Altogether, the traceability analysis showed that the major causes of different carbon storage estimations were found to be parameters setting related to carbon input and baseline carbon residence times between two models.« less

Modeling carbon dynamics in mangrove ecosystems in North America and Eastern Africa

NASA Astrophysics Data System (ADS)

Trettin, C.; Dai, Z.; Birdsey, R.; Frolking, S. E.

2016-12-01

Assessing carbon (C) dynamics in mangroves is fundamental to understand their role in mitigating climate change as well as the myriad of ecosystems derived the wetland forest. A spatially-explicit process model, MCAT (Mangrove-Carbon-Assessment-Tool), was developed to estimate (1) C dynamics in mangrove ecosystems, including biomass, burial C, dissolved inorganic and organic C (DIC and DOC), particulate organic C (POC), and CH4 and soil CO2 fluxes, and (2) impacts of disturbances, including storms, fire, insects and harvesting, on C sequestration in mangrove ecosystems. MCAT was tested using observations from eight plots in Everglades National Park (ENP) in Florida of USA and the World Heritage site in Mexican Caribbean in Quintana Roo (QR). The model was applied for assessing C dynamics in mangrove forests with different eco-environmental conditions in Northern America and Eastern Africa. The metrics from the four model evaluation statistics, determination coefficient (R2=0.99), model performance efficiency (E=0.98), percent bias (PBIAS=1.06%), and the ratio of the root mean squared error to standard deviation (RRS=0.11) showed that the model performed well for assessing mangrove C at these plots with a high model performance efficiency. The simulated biomass for ENP and QR was in good agreement with observations although there are large differences in canopy stature among those plots, ranging from tall to dwarf mangroves. The simulated aboveground net primary productivity, burial C, DIC, DOC, POC and CH4 for the plot at ENP approximated the reported values. There are substantial differences in C sequestration and fluxes in mangroves to atmosphere and water place-to-place due to differences in ecological drivers. Climate and soils are key factors that impact C dynamics in mangrove ecosystems, including temperature and salinity, such that there are differences in C sequestration rates among these mangrove sites in southeastern USA, Mexican Caribbean and Zambezi River Delta of Mozambique.

Coral–algal phase shifts alter fish communities and reduce fisheries production

PubMed Central

Ainsworth, Cameron H; Mumby, Peter J

2015-01-01

Anthropogenic stress has been shown to reduce coral coverage in ecosystems all over the world. A phase shift towards an algae-dominated system may accompany coral loss. In this case, the composition of the reef-associated fish assemblage will change and human communities relying on reef fisheries for income and food security may be negatively impacted. We present a case study based on the Raja Ampat Archipelago in Eastern Indonesia. Using a dynamic food web model, we simulate the loss of coral reefs with accompanied transition towards an algae-dominated state and quantify the likely change in fish populations and fisheries productivity. One set of simulations represents extreme scenarios, including 100% loss of coral. In this experiment, ecosystem changes are driven by coral loss itself and a degree of habitat dependency by reef fish is assumed. An alternative simulation is presented without assumed habitat dependency, where changes to the ecosystem are driven by historical observations of reef fish communities when coral is lost. The coral–algal phase shift results in reduced biodiversity and ecosystem maturity. Relative increases in the biomass of small-bodied fish species mean higher productivity on reefs overall, but much reduced landings of traditionally targeted species. PMID:24953835

Impact of the Gulf of California SST on simulating precipitation and crop productivity in the Southwestern United States

NASA Astrophysics Data System (ADS)

Kim, S.; Kim, J.; Prasad, A. K.; Stack, D. H.; El-Askary, H. M.; Kafatos, M.

2012-12-01

Like other ecosystems, agricultural productivity is substantially affected by climate factors. Therefore, accurate climatic data (i.e. precipitation, temperature, and radiation) is crucial to simulating crop yields. In order to understand and anticipate climate change and its impacts on agricultural productivity in the Southwestern United States, the WRF regional climate model (RCM) and the Agricultural Production Systems sIMulator (APSIM) were employed for simulating crop production. 19 years of WRF RCM output show that there is a strong dry bias during the warm season, especially in Arizona. Consequently, the APSIM crop model indicates very low crop yields in this region. We suspect that the coarse resolution of reanalysis data could not resolve the relatively warm Sea Surface Temperature (SST) in the Gulf of California (GC), causing the SST to be up to 10 degrees lower than the climatology. In the Southwestern United States, a significant amount of precipitation is associated with North American Monsoon (NAM). During the monsoon season, the low-level moisture is advected to the Southwestern United States via the GC, which is known to be the dominant moisture source. Thus, high-resolution SST data in the GC is required for RCM simulations to accurately represent a reasonable amount of precipitation in the region, allowing reliable evaluation of the impacts on regional ecosystems.and evaluate impacts on regional ecosystems. To evaluate the influence of SST on agriculture in the Southwestern U.S., two sets of numerical simulations were constructed: a control, using unresolved SST of GC, and daily updated SST data from the MODIS satellite sensor. The meteorological drivers from each of the 6 year RCM runs were provided as input to the APSIM model to determine the crop yield. Analyses of the simulated crop production, and the interannual variation of the meteorological drivers, demonstrate the influence of SST on crop yields in the Southwestern United States.

The role of organic soil layer on the fate of Siberian larch forest and near-surface permafrost under changing climate: A simulation study

NASA Astrophysics Data System (ADS)

SATO, H.; Iwahana, G.; Ohta, T.

2013-12-01

Siberian larch forest is the largest coniferous forest region in the world. In this vast region, larch often forms nearly pure stands, regenerated by recurrent fire. This region is characterized by a short and dry growing season; the annual mean precipitation for Yakutsk was only about 240 mm. To maintain forest ecosystem under such small precipitation, underlying permafrost and seasonal soil freezing-thawing-cycle have been supposed to play important roles; (1) frozen ground inhibits percolation of soil water into deep soil layers, and (2) excess soil water at the end of growing season can be carried over until the next growing season as ice, and larch trees can use the melt water. As a proof for this explanation, geographical distribution of Siberian larch region highly coincides with continuous and discontinuous permafrost zone. Recent observations and simulation studies suggests that existences of larch forest and permafrost in subsurface layer are co-dependent; permafrost maintains the larch forest by enhancing water use efficiency of trees, while larch forest maintains permafrost by inhibiting solar radiation and preventing heat exchanges between soil and atmosphere. Owing to such complexity and absence of enough ecosystem data available, current-generation Earth System Models significantly diverse in their prediction of structure and key ecosystem functions in Siberian larch forest under changing climate. Such uncertainty should in turn expand uncertainty over predictions of climate, because Siberian larch forest should have major role in the global carbon balance with its huge area and vast potential carbon pool within the biomass and soil, and changes in boreal forest albedo can have a considerable effect on Northern Hemisphere climate. In this study, we developed an integrated ecosystem model, which treats interactions between plant-dynamics and freeze-thaw cycles. This integrated model contains a dynamic global vegetation model SEIB-DGVM, which simulates plant and carbon dynamics. It also contains a one-dimensional land surface model NOAH 2.7.1, which simulates soil moisture (both liquid and frozen), soil temperature, snowpack depth and density, canopy water content, and the energy and water fluxes. This integrated model quantitatively reconstructs post-fire development of forest structure (i.e. LAI and biomass) and organic soil layer, which dampens heat exchanges between soil and atmosphere. With the post-fire development of LAI and the soil organic layer, the integrated model also quantitatively reconstructs changes in seasonal maximum of active layer depth. The integrated model is then driven by the IPCC A1B scenario of rising atmospheric CO2, and by climate changes during the twenty-first century resulting from the change in CO2. This simulation suggests that forecasted global warming would causes decay of Siberian larch ecosystem, but such responses could be delayed by "memory effect" of the soil organic layer for hundreds of years.

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.

CMIP5 land surface models systematically underestimate inter-annual variability of net ecosystem exchange in semi-arid southwestern North America.

NASA Astrophysics Data System (ADS)

MacBean, N.; Scott, R. L.; Biederman, J. A.; Vuichard, N.; Hudson, A.; Barnes, M.; Fox, A. M.; Smith, W. K.; Peylin, P. P.; Maignan, F.; Moore, D. J.

2017-12-01

Recent studies based on analysis of atmospheric CO2 inversions, satellite data and terrestrial biosphere model simulations have suggested that semi-arid ecosystems play a dominant role in the interannual variability and long-term trend in the global carbon sink. These studies have largely cited the response of vegetation activity to changing moisture availability as the primary mechanism of variability. However, some land surface models (LSMs) used in these studies have performed poorly in comparison to satellite-based observations of vegetation dynamics in semi-arid regions. Further analysis is therefore needed to ensure semi-arid carbon cycle processes are well represented in global scale LSMs before we can fully establish their contribution to the global carbon cycle. In this study, we evaluated annual net ecosystem exchange (NEE) simulated by CMIP5 land surface models using observations from 20 Ameriflux sites across semi-arid southwestern North America. We found that CMIP5 models systematically underestimate the magnitude and sign of NEE inter-annual variability; therefore, the true role of semi-arid regions in the global carbon cycle may be even more important than previously thought. To diagnose the factors responsible for this bias, we used the ORCHIDEE LSM to test different climate forcing data, prescribed vegetation fractions and model structures. Climate and prescribed vegetation do contribute to uncertainty in annual NEE simulations, but the bias is primarily caused by incorrect timing and magnitude of peak gross carbon fluxes. Modifications to the hydrology scheme improved simulations of soil moisture in comparison to data. This in turn improved the seasonal cycle of carbon uptake due to a more realistic limitation on photosynthesis during water stress. However, the peak fluxes are still too low, and phenology is poorly represented for desert shrubs and grasses. We provide suggestions on model developments needed to tackle these issues in the future.

EcoPAD, an interactive platform for near real-time ecological forecasting by assimilating data into model

NASA Astrophysics Data System (ADS)

MA, S.; Huang, Y.; Stacy, M.; Jiang, J.; Sundi, N.; Ricciuto, D. M.; Hanson, P. J.; Luo, Y.; Saruta, V.

2017-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our study presents a smart system - Ecological Platform for Assimilation of Data (EcoPAD) - which streamlines web request-response, data management, model execution, result storage and visualization. EcoPAD allows users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, (v) conduct ecological forecasting, and (vi) detect ecosystem acclimation to climate change. One of the key innovations of the web-based EcoPAD is the automated near- or real-time forecasting of ecosystem dynamics with uncertainty fully quantified. The user friendly webpage enables non-modelers to explore their data for simulation and data assimilation. As a case study, we applied EcoPAD to the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment project in the northern peatland, assimilated multiple data streams into a process based ecosystem model, enhanced timely feedback between modelers and experimenters, ultimately improved ecosystem forecasting and made better use of current knowledge. Built in a framework with flexible API, EcoPAD is easily portable and will benefit scientific communities, policy makers as well as the general public.

Model-data integration to improve the LPJmL dynamic global vegetation model

NASA Astrophysics Data System (ADS)

Forkel, Matthias; Thonicke, Kirsten; Schaphoff, Sibyll; Thurner, Martin; von Bloh, Werner; Dorigo, Wouter; Carvalhais, Nuno

2017-04-01

Dynamic global vegetation models show large uncertainties regarding the development of the land carbon balance under future climate change conditions. This uncertainty is partly caused by differences in how vegetation carbon turnover is represented in global vegetation models. Model-data integration approaches might help to systematically assess and improve model performances and thus to potentially reduce the uncertainty in terrestrial vegetation responses under future climate change. Here we present several applications of model-data integration with the LPJmL (Lund-Potsdam-Jena managed Lands) dynamic global vegetation model to systematically improve the representation of processes or to estimate model parameters. In a first application, we used global satellite-derived datasets of FAPAR (fraction of absorbed photosynthetic activity), albedo and gross primary production to estimate phenology- and productivity-related model parameters using a genetic optimization algorithm. Thereby we identified major limitations of the phenology module and implemented an alternative empirical phenology model. The new phenology module and optimized model parameters resulted in a better performance of LPJmL in representing global spatial patterns of biomass, tree cover, and the temporal dynamic of atmospheric CO2. Therefore, we used in a second application additionally global datasets of biomass and land cover to estimate model parameters that control vegetation establishment and mortality. The results demonstrate the ability to improve simulations of vegetation dynamics but also highlight the need to improve the representation of mortality processes in dynamic global vegetation models. In a third application, we used multiple site-level observations of ecosystem carbon and water exchange, biomass and soil organic carbon to jointly estimate various model parameters that control ecosystem dynamics. This exercise demonstrates the strong role of individual data streams on the simulated ecosystem dynamics which consequently changed the development of ecosystem carbon stocks and fluxes under future climate and CO2 change. In summary, our results demonstrate challenges and the potential of using model-data integration approaches to improve a dynamic global vegetation model.

Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-05-01

This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Distributed hydrological models to quantify ecosystem services and inform land use decisions in Europe

NASA Astrophysics Data System (ADS)

Wilebore, Beccy; Willis, Kathy

2016-04-01

Landcover conversion is one of the largest anthropogenic threats to ecological services globally; in the EU around 1500 ha of biodiverse land are lost every day to changes in infrastructure and urbanisation. This land conversion directly affects key ecosystem services that support natural infrastructure, including water flow regulation and the mitigation of flood risks. We assess the sensitivity of runoff production to landcover in the UK at a high spatial resolution, using a distributed hydrologic model in the regional land-surface model JULES (Joint UK Land Environment Simulator). This work, as part of the wider initiative 'NaturEtrade', will create a novel suite of easy-to-use tools and mechanisms to allow EU landowners to quickly map and assess the value of their land in providing key ecosystem services.

PICUS v1.6 - enhancing the water cycle within a hybrid ecosystem model to assess the provision of drinking water in a changing climate

NASA Astrophysics Data System (ADS)

Schimmel, A.; Rammer, W.; Lexer, M. J.

2012-04-01

The PICUS model is a hybrid ecosystem model which is based on a 3D patch model and a physiological stand level production model. The model includes, among others, a submodel of bark beetle disturbances in Norway spruce and a management module allowing any silvicultural treatment to be mimicked realistically. It has been tested intensively for its ability to realistically reproduce tree growth and stand dynamics in complex structured mixed and mono-species temperate forest ecosystems. In several applications the models capacity to generate relevant forest related attributes which were subsequently fed into indicator systems to assess sustainable forest management under current and future climatic conditions has been proven. However, the relatively coarse monthly temporal resolution of the driving climate data as well as the process resolution of the major water relations within the simulated ecosystem hampered the inclusion of more detailed physiologically based assessments of drought conditions and water provisioning ecosystem services. In this contribution we present the improved model version PICUS v1.6 focusing on the newly implemented logic for the water cycle calculations. Transpiration, evaporation from leave surfaces and the forest floor, snow cover and snow melt as well as soil water dynamics in several soil horizons are covered. In enhancing the model overarching goal was to retain the large-scale applicability by keeping the input requirements to a minimum while improving the physiological foundation of water related ecosystem processes. The new model version is tested against empirical time series data. Future model applications are outlined.

Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.

PubMed

Bonan, Gordon B; Doney, Scott C

2018-02-02

Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.

SIGMA: A Knowledge-Based Simulation Tool Applied to Ecosystem Modeling

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Keller, Richard; Lawless, James G. (Technical Monitor)

1994-01-01

The need for better technology to facilitate building, sharing and reusing models is generally recognized within the ecosystem modeling community. The Scientists' Intelligent Graphical Modelling Assistant (SIGMA) creates an environment for model building, sharing and reuse which provides an alternative to more conventional approaches which too often yield poorly documented, awkwardly structured model code. The SIGMA interface presents the user a list of model quantities which can be selected for computation. Equations to calculate the model quantities may be chosen from an existing library of ecosystem modeling equations, or built using a specialized equation editor. Inputs for dim equations may be supplied by data or by calculation from other equations. Each variable and equation is expressed using ecological terminology and scientific units, and is documented with explanatory descriptions and optional literature citations. Automatic scientific unit conversion is supported and only physically-consistent equations are accepted by the system. The system uses knowledge-based semantic conditions to decide which equations in its library make sense to apply in a given situation, and supplies these to the user for selection. "Me equations and variables are graphically represented as a flow diagram which provides a complete summary of the model. Forest-BGC, a stand-level model that simulates photosynthesis and evapo-transpiration for conifer canopies, was originally implemented in Fortran and subsequenty re-implemented using SIGMA. The SIGMA version reproduces daily results and also provides a knowledge base which greatly facilitates inspection, modification and extension of Forest-BGC.

Evaluating the role of large jellyfish and forage fishes as energy pathways, and their interplay with fisheries, in the Northern Humboldt Current System

NASA Astrophysics Data System (ADS)

Chiaverano, Luciano M.; Robinson, Kelly L.; Tam, Jorge; Ruzicka, James J.; Quiñones, Javier; Aleksa, Katrina T.; Hernandez, Frank J.; Brodeur, Richard D.; Leaf, Robert; Uye, Shin-ichi; Decker, Mary Beth; Acha, Marcelo; Mianzan, Hermes W.; Graham, William M.

2018-05-01

Large jellyfish are important consumers of plankton, fish eggs and fish larvae in heavily fished ecosystems worldwide; yet they are seldom included in fisheries production models. Here we developed a trophic network model with 41 functional groups using ECOPATH re-expressed in a donor-driven, end-to-end format to directly evaluate the efficiency of large jellyfish and forage fish at transferring energy to higher trophic levels, as well as the ecosystem-wide effects of varying jellyfish and forage fish consumption rates and fishing rates, in the Northern Humboldt Current system (NHCS) off of Peru. Large jellyfish were an energy-loss pathway for high trophic-level consumers, while forage fish channelized the production of lower trophic levels directly into production of top-level consumers. A simulated jellyfish bloom resulted in a decline in productivity of all functional groups, including forage fish (12%), with the exception of sea turtles. A modeled increase in forage fish consumption rate by 50% resulted in a decrease in large jellyfish productivity (29%). A simulated increase of 40% in forage fish harvest enhanced jellyfish productivity (24%), while closure of all fisheries caused a decline in large jellyfish productivity (26%) and productivity increases in upper level consumers. These outcomes not only suggest that jellyfish blooms and fisheries have important effects on the structure of the NHCS, but they also support the hypothesis that forage fishing provides a competitive release for large jellyfish. We recommend including jellyfish as a functional group in future ecosystem modeling efforts, including ecosystem-based approaches to fishery management of coastal ecosystems worldwide.

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling

PubMed Central

2011-01-01

Background A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Results Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Conclusions Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape. PMID:21835025

Carbon fluxes in ecosystems of Yellowstone National Park predicted from remote sensing data and simulation modeling.

PubMed

Potter, Christopher; Klooster, Steven; Crabtree, Robert; Huang, Shengli; Gross, Peggy; Genovese, Vanessa

2011-08-11

A simulation model based on remote sensing data for spatial vegetation properties has been used to estimate ecosystem carbon fluxes across Yellowstone National Park (YNP). The CASA (Carnegie Ames Stanford Approach) model was applied at a regional scale to estimate seasonal and annual carbon fluxes as net primary production (NPP) and soil respiration components. Predicted net ecosystem production (NEP) flux of CO2 is estimated from the model for carbon sinks and sources over multi-year periods that varied in climate and (wildfire) disturbance histories. Monthly Enhanced Vegetation Index (EVI) image coverages from the NASA Moderate Resolution Imaging Spectroradiometer (MODIS) instrument (from 2000 to 2006) were direct inputs to the model. New map products have been added to CASA from airborne remote sensing of coarse woody debris (CWD) in areas burned by wildfires over the past two decades. Model results indicated that relatively cooler and wetter summer growing seasons were the most favorable for annual plant production and net ecosystem carbon gains in representative landscapes of YNP. When summed across vegetation class areas, the predominance of evergreen forest and shrubland (sagebrush) cover was evident, with these two classes together accounting for 88% of the total annual NPP flux of 2.5 Tg C yr-1 (1 Tg = 1012 g) for the entire Yellowstone study area from 2000-2006. Most vegetation classes were estimated as net ecosystem sinks of atmospheric CO2 on annual basis, making the entire study area a moderate net sink of about +0.13 Tg C yr-1. This average sink value for forested lands nonetheless masks the contribution of areas burned during the 1988 wildfires, which were estimated as net sources of CO2 to the atmosphere, totaling to a NEP flux of -0.04 Tg C yr-1 for the entire burned area. Several areas burned in the 1988 wildfires were estimated to be among the lowest in overall yearly NPP, namely the Hellroaring Fire, Mink Fire, and Falls Fire areas. Rates of recovery for burned forest areas to pre-1988 biomass levels were estimated from a unique combination of remote sensing and CASA model predictions. Ecosystem production and carbon fluxes in the Greater Yellowstone Ecosystem (GYE) result from complex interactions between climate, forest age structure, and disturbance-recovery patterns of the landscape.

Accounting for Forest Harvest and Wildfire in a Spatially-distributed Carbon Cycle Process Model

NASA Astrophysics Data System (ADS)

Turner, D. P.; Ritts, W.; Kennedy, R. E.; Yang, Z.; Law, B. E.

2009-12-01

Forests are subject to natural disturbances in the form of wildfire, as well as management-related disturbances in the form of timber harvest. These disturbance events have strong impacts on local and regional carbon budgets, but quantifying the associated carbon fluxes remains challenging. The ORCA Project aims to quantify regional net ecosystem production (NEP) and net biome production (NBP) in Oregon, California, and Washington, and we have adopted an integrated approach based on Landsat imagery and ecosystem modeling. To account for stand-level carbon fluxes, the Biome-BGC model has been adapted to simulate multiple severities of fire and harvest. New variables include snags, direct fire emissions, and harvest removals. New parameters include fire-intensity-specific combustion factors for each carbon pool (based on field measurements) and proportional removal rates for harvest events. To quantify regional fluxes, the model is applied in a spatially-distributed mode over the domain of interest, with disturbance history derived from a time series of Landsat images. In stand-level simulations, the post disturbance transition from negative (source) to positive (sink) NEP is delayed approximately a decade in the case of high severity fire compared to harvest. Simulated direct pyrogenic emissions range from 11 to 25 % of total non-soil ecosystem carbon. In spatial mode application over Oregon and California, the sum of annual pyrogenic emissions and harvest removals was generally less that half of total NEP, resulting in significant carbon sequestration on the land base. Spatially and temporally explicit simulation of disturbance-related carbon fluxes will contribute to our ability to evaluate effects of management on regional carbon flux, and in our ability to assess potential biospheric feedbacks to climate change mediated by changing disturbance regimes.

Effects of future land use on biogeography of aquatic ecosystems of Amazonia

NASA Astrophysics Data System (ADS)

Howard, E. A.; Coe, M. T.; Foley, J. A.; Costa, M. H.

2006-12-01

Amazonian ecosystems provide key ecosystem services, such as regulating the amount and timing of water and carbon flows through the Amazon Basin. Land use in these ecosystems affects regional water balance, which in turn affects biogeography of aquatic ecosystems, including wetlands and floodplains. We combined a hydrological model (Terrestrial Hydrology Model with Biogeochemistry, THMB), remote sensing observations (Hess et al. 2003), and empirical data to identify the distribution of aquatic biogeographic types throughout the central Amazon basin over time. We explored how future land-use scenarios for the Amazon Basin through 2030 (Soares-Filho et al. 2004) would modify the spatial and temporal patterns of aquatic ecosystems as compared to a baseline of natural potential vegetation cover under historical climate variability for the 20th century. We calibrated monthly simulation results with remotely sensed observations of flooded area and extent of different wetland categories for high and low water periods over a 1.7 million sq. km region of the central Amazon. Two additional dimensions of floodplain biogeography (river size and color) were added to provide insight into the geographic distribution of key ecosystem types and their flooding seasonality. For historical conditions, the model results reproduced regional differences in seasonal flood extent and timing north and south of the Amazon mainstem, reflecting the dominant climatic regimes. Black-water streams and medium-sized rivers, followed by large white-water rivers, were the most extensive types across the study region. However much of the black water was in areas likely to be influenced by white-water rivers while flooded. The monthly extent of flooded areas dominated by woody vegetation was consistently more strongly seasonal than non-woody areas. Also, the extent of flooding in muddy and semi-muddy rivers and floodplains tended to be more highly seasonal than in black- and clear-water areas. We discuss our efforts to use our simulation results to extrapolate and bound estimates and patterns of aquatic ecosystem extent in the Amazon River system under future land-use scenarios. Regional flooding variability has disproportionate effects on different ecosystem types, suggesting that persistent, long-term changes to flooding regimes may have long-lasting consequences for floodplain vegetation, wildlife, and human residents.

Puget Sound Applications of the VELMA Ecohydrological Model

EPA Science Inventory

This seminar will present an overview of EPA’s Visualizing Ecosystem Land Management Assessments (VELMA) model and its applications in the Puget Sound Basin. Topics will include a description of how VELMA simulates the interaction of hydrological and biogeochemical processe...

Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates

NASA Astrophysics Data System (ADS)

Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje

2017-04-01

Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak

Divergent patterns of experimental and model derived variables of tundra ecosystem carbon exchange in response to arctic warming

NASA Astrophysics Data System (ADS)

Schaedel, C.; Koven, C.; Celis, G.; Hutchings, J.; Lawrence, D. M.; Mauritz, M.; Pegoraro, E.; Salmon, V. G.; Taylor, M.; Wieder, W. R.; Schuur, E.

2017-12-01

Warming over the Arctic in the last decades has been twice as high as for the rest of the globe and has exposed large amounts of organic carbon to microbial decomposition in permafrost ecosystems. Continued warming and associated changes in soil moisture conditions not only lead to enhanced microbial decomposition from permafrost soil but also enhanced plant carbon uptake. Both processes impact the overall contribution of permafrost carbon dynamics to the global carbon cycle, yet field and modeling studies show large uncertainties in regard to both uptake and release mechanisms. Here, we compare variables associated with ecosystem carbon exchange (GPP: gross primary production; Reco: ecosystem respiration; and NEE: net ecosystem exchange) from eight years of experimental soil warming in moist acidic tundra with the same variables derived from an experimental model (Community Land Model version 4.5: CLM4.5) that simulates the same degree of arctic warming. While soil temperatures and thaw depths exhibited comparable increases with warming between field and model variables, carbon exchange related parameters showed divergent patterns. In the field non-linear responses to experimentally induced permafrost thaw were observed in GPP, Reco, and NEE. Indirect effects of continued soil warming and thaw created changes in soil moisture conditions causing ground surface subsidence and suppressing ecosystem carbon exchange over time. In contrast, the model predicted linear increases in GPP, Reco, and NEE with every year of warming turning the ecosystem into a net annual carbon sink. The field experiment revealed the importance of hydrology in carbon flux responses to permafrost thaw, a complexity that the model may fail to predict. Further parameterization of variables that drive GPP, Reco, and NEE in the model will help to inform and refine future model development.

Climate Change Impacts for Conterminous USA: An Integrated Assessment Part 2. Models and Validation

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

Thomson, Allison M.; Rosenberg, Norman J.; Izaurralde, R Cesar C.

As CO{sub 2} and other greenhouse gases accumulate in the atmosphere and contribute to rising global temperatures, it is important to examine how a changing climate may affect natural and managed ecosystems. In this series of papers, we study the impacts of climate change on agriculture, water resources and natural ecosystems in the conterminous United States using a suite of climate change predictions from General Circulation Models (GCMs) as described in Part 1. Here we describe the agriculture model EPIC and the HUMUS water model and validate them with historical crop yields and streamflow data. We compare EPIC simulated grainmore » and forage crop yields with historical crop yields from the US Department of Agriculture and find an acceptable level of agreement for this study. The validation of HUMUS simulated streamflow with estimates of natural streamflow from the US Geological Survey shows that the model is able to reproduce significant relationships and capture major trends.« less

Modeling the effects of snowpack on heterotrophic respiration across northern temperate and high latitude regions: Comparison with measurements of atmospheric carbon dioxide in high latitudes

USGS Publications Warehouse

McGuire, A.D.; Melillo, J.M.; Randerson, J.T.; Parton, W.J.; Heimann, Martin; Meier, R.A.; Clein, Joy S.; Kicklighter, D.W.; Sauf, W.

2000-01-01

Simulations by global terrestrial biogeochemical models (TBMs) consistently underestimate the concentration of atmospheric carbon dioxide (CO2) at high latitude monitoring stations during the nongrowing season. We hypothesized that heterotrophic respiration is underestimated during the nongrowing season primarily because TBMs do not generally consider the insulative effects of snowpack on soil temperature. To evaluate this hypothesis, we compared the performance of baseline and modified versions of three TBMs in simulating the seasonal cycle of atmospheric CO2 at high latitude CO2 monitoring stations; the modified version maintained soil temperature at 0 ??C when modeled snowpack was present. The three TBMs include the Carnegie-Ames-Stanford Approach (CASA), Century, and the Terrestrial Ecosystem Model (TEM). In comparison with the baseline simulation of each model, the snowpack simulations caused higher releases of CO2 between November and March and greater uptake of CO2 between June and August for latitudes north of 30??N. We coupled the monthly estimates of CO2 exchange, the seasonal carbon dioxide flux fields generated by the HAMOCC3 seasonal ocean carbon cycle model, and fossil fuel source fields derived from standard sources to the three-dimensional atmospheric transport model TM2 forced by observed winds to simulate the seasonal cycle of atmospheric CO2 at each of seven high latitude monitoring stations, in comparison to the CO2 concentrations simulated with the baseline fluxes of each TBM, concentrations simulated using the snowpack fluxes are generally in better agreement with observed concentrations between August and March at each of the monitoring stations. Thus, representation of the insulative effects of snowpack in TBMs generally improves simulation of atmospheric CO2 concentrations in high latitudes during both the late growing season and nongrowing season. These simulations highlight the global importance of biogeochemical processes during the nongrowing season in estimating carbon balance of ecosystems in northern high and temperate latitudes.

Evaluating Energy Flows Through Jellyfish and Forage Fish and the Effects of Fishing on the Northern Humboldt Current Ecosystem

NASA Astrophysics Data System (ADS)

Chiaverano, L.; Robinson, K. L.; Ruzicka, J.; Quiñones, J.; Tam, J.; Acha, M.; Graham, W. M.; Brodeur, R.; Decker, M. B.; Hernandez, F., Jr.; Leaf, R.; Mianzan, H.; Uye, S. I.

2016-02-01

Increases in the frequency of jellyfish mass occurrences in a number of coastal areas around the globe have intensified concerns that some ecosystems are becoming "jellyfish-dominated". Gelatinous planktivores not only compete with forage fish for food, but also feed on fish eggs and larvae. When jellyfish abundance is high, the fraction of the energy and the efficiency at which it is transferred upwards in the food web are reduced compared with times when fish are dominant. Hence, ecosystems supporting major forage fish fisheries are the most likely to experience fish-to-jellyfish shifts due to the harvest pressure on mid-trophic planktivores. Although forage fish-jellyfish replacement cycles have been detected in recent decades in some productive, coastal ecosystems (e.g. Gulf of Mexico, Northern California Current), jellyfish are typically not included in ecosystem-based fisheries management (EBFM) production models. Here we explored the roles of jellyfish and forage fish as trophic energy transfer pathways to higher trophic levels in the Northern Humboldt Current (NHC) ecosystem, one of the most productive ecosystems in the world. A trophic network model with 33 functional groups was developed using ECOPATH and transformed to an end-to-end model using ECOTRAN techniques to map food web energy flows. Predicted, relative changes in functional group productivity were analyzed in simulations with varying forage fish consumption rates, jellyfish consumption rates, and forage fish harvest rates in a suite of static, alternative-energy-demand scenarios. Our modeling efforts will not only improve EBFM of forage fish and their predators in the NHC ecosystem, but also increase our understanding of trophic interactions between forage fish and large jellyfish, an important, but overlooked component in most ecosystem models to date.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-06-01

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

Evaluation of the effects of climate and man intervention on ground waters and their dependent ecosystems using time series analysis

NASA Astrophysics Data System (ADS)

Gemitzi, Alexandra; Stefanopoulos, Kyriakos

2011-06-01

SummaryGroundwaters and their dependent ecosystems are affected both by the meteorological conditions as well as from human interventions, mainly in the form of groundwater abstractions for irrigation needs. This work aims at investigating the quantitative effects of meteorological conditions and man intervention on groundwater resources and their dependent ecosystems. Various seasonal Auto-Regressive Integrated Moving Average (ARIMA) models with external predictor variables were used in order to model the influence of meteorological conditions and man intervention on the groundwater level time series. Initially, a seasonal ARIMA model that simulates the abstraction time series using as external predictor variable temperature ( T) was prepared. Thereafter, seasonal ARIMA models were developed in order to simulate groundwater level time series in 8 monitoring locations, using the appropriate predictor variables determined for each individual case. The spatial component was introduced through the use of Geographical Information Systems (GIS). Application of the proposed methodology took place in the Neon Sidirochorion alluvial aquifer (Northern Greece), for which a 7-year long time series (i.e., 2003-2010) of piezometric and groundwater abstraction data exists. According to the developed ARIMA models, three distinct groups of groundwater level time series exist; the first one proves to be dependent only on the meteorological parameters, the second group demonstrates a mixed dependence both on meteorological conditions and on human intervention, whereas the third group shows a clear influence from man intervention. Moreover, there is evidence that groundwater abstraction has affected an important protected ecosystem.

Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem

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

Laufkotter, Charlotte; Vogt, Meike; Gruber, Nicolas

Here, accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralisation of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projectionsmore » in EP over the 21st century, generated by four marine ecosystem models under the high emission scenario Representative Concentration Pathways (RCP) 8.5 of the Intergovernmental Panel on Climate Change (IPCC), and determine the processes driving these changes. The models simulate small to modest decreases in global EP between -1 and -12%. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralisation is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralisation or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralisation. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94% in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.« less

Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem

DOE PAGES

Laufkotter, Charlotte; Vogt, Meike; Gruber, Nicolas; ...

2016-07-14

Here, accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralisation of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projectionsmore » in EP over the 21st century, generated by four marine ecosystem models under the high emission scenario Representative Concentration Pathways (RCP) 8.5 of the Intergovernmental Panel on Climate Change (IPCC), and determine the processes driving these changes. The models simulate small to modest decreases in global EP between -1 and -12%. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralisation is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralisation or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralisation. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94% in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.« less

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,...

Simulating forest landscape disturbances as coupled human and natural systems

USGS Publications Warehouse

Wimberly, Michael; Sohl, Terry L.; Liu, Zhihua; Lamsal, Aashis

2015-01-01

Anthropogenic disturbances resulting from human land use affect forest landscapes over a range of spatial and temporal scales, with diverse influences on vegetation patterns and dynamics. These processes fall within the scope of the coupled human and natural systems (CHANS) concept, which has emerged as an important framework for understanding the reciprocal interactions and feedbacks that connect human activities and ecosystem responses. Spatial simulation modeling of forest landscape change is an important technique for exploring the dynamics of CHANS over large areas and long time periods. Landscape models for simulating interactions between human activities and forest landscape dynamics can be grouped into two main categories. Forest landscape models (FLMs) focus on landscapes where forests are the dominant land cover and simulate succession and natural disturbances along with forest management activities. In contrast, land change models (LCMs) simulate mosaics of different land cover and land use classes that include forests in addition to other land uses such as developed areas and agricultural lands. There are also several examples of coupled models that combine elements of FLMs and LCMs. These integrated models are particularly useful for simulating human–natural interactions in landscapes where human settlement and agriculture are expanding into forested areas. Despite important differences in spatial scale and disciplinary scope, FLMs and LCMs have many commonalities in conceptual design and technical implementation that can facilitate continued integration. The ultimate goal will be to implement forest landscape disturbance modeling in a CHANS framework that recognizes the contextual effects of regional land use and other human activities on the forest ecosystem while capturing the reciprocal influences of forests and their disturbances on the broader land use mosaic.

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

Ecosystem Modeling Applied to Nutrient Criteria Development in Rivers

NASA Astrophysics Data System (ADS)

Carleton, James N.; Park, Richard A.; Clough, Jonathan S.

2009-09-01

Threshold concentrations for biological impairment by nutrients are difficult to quantify in lotic systems, yet States and Tribes in the United States are charged with developing water quality criteria to protect these ecosystems from excessive enrichment. The analysis described in this article explores the use of the ecosystem model AQUATOX to investigate impairment thresholds keyed to biological indexes that can be simulated. The indexes selected for this exercise include percentage cyanobacterial biomass of sestonic algae, and benthic chlorophyll a. The calibrated model was used to analyze responses of these indexes to concurrent reductions in phosphorus, nitrogen, and suspended sediment in an enriched upper Midwestern river. Results suggest that the indexes would respond strongly to changes in phosphorus and suspended sediment, and less strongly to changes in nitrogen concentration. Using simulated concurrent reductions in all three water quality constituents, a total phosphorus concentration of 0.1 mg/l was identified as a threshold concentration, and therefore a hypothetical water quality criterion, for prevention of both excessive periphyton growth and sestonic cyanobacterial blooms. This kind of analysis is suggested as a way to evaluate multiple contrasting impacts of hypothetical nutrient and sediment reductions and to define nutrient criteria or target concentrations that balance multiple management objectives concurrently.

Changing ecophysiological processes and carbon budget in East Asian ecosystems under near-future changes in climate: implications for long-term monitoring from a process-based model.

PubMed

Ito, Akihiko

2010-07-01

Using a process-based model, I assessed how ecophysiological processes would respond to near-future global changes predicted by coupled atmosphere-ocean climate models. An ecosystem model, Vegetation Integrative SImulator for Trace gases (VISIT), was applied to four sites in East Asia (different types of forest in Takayama, Tomakomai, and Fujiyoshida, Japan, and an Alpine grassland in Qinghai, China) where observational flux data are available for model calibration. The climate models predicted +1-3 degrees C warming and slight change in annual precipitation by 2050 as a result of an increase in atmospheric CO2. Gross primary production (GPP) was estimated to increase substantially at each site because of improved efficiency in the use of water and radiation. Although increased respiration partly offset the GPP increase, the simulation showed that these ecosystems would act as net carbon sinks independent of disturbance-induced uptake for recovery. However, the carbon budget response relied strongly on nitrogen availability, such that photosynthetic down-regulation resulting from leaf nitrogen dilution largely decreased GPP. In relation to long-term monitoring, these results indicate that the impacts of global warming may be more evident in gross fluxes (e.g., photosynthesis and respiration) than in the net CO2 budget, because changes in these fluxes offset each other.

A linear regression model for predicting PNW estuarine temperatures in a changing climate

EPA Science Inventory

Pacific Northwest coastal regions, estuaries, and associated ecosystems are vulnerable to the potential effects of climate change, especially to changes in nearshore water temperature. While predictive climate models simulate future air temperatures, no such projections exist for...

Comparative Biogeochemical Cycles of Bioenergy Crops Reveal Nitrogen-Fixation and Low GHG Emissions in a Miscanthus x giganteus Agro-ecosystem

USDA-ARS?s Scientific Manuscript database

We evaluated the relative greenhouse gas mitigation potential of plant species considered as biofuel feedstock crops by simulating the biogeochemical processes associated with Miscanthus x giganteus, Panicum virgatum, Zea mays, and a mixed prairie community. DayCent model simulations for Miscanthus ...

Business analysis for a sustainable, multi-stakeholder ecosystem for leveraging the Electronic Health Records for Clinical Research (EHR4CR) platform in Europe.

PubMed

Dupont, Danielle; Beresniak, Ariel; Sundgren, Mats; Schmidt, Andreas; Ainsworth, John; Coorevits, Pascal; Kalra, Dipak; Dewispelaere, Marc; De Moor, Georges

2017-01-01

The Electronic Health Records for Clinical Research (EHR4CR) technological platform has been developed to enable the trustworthy reuse of hospital electronic health records data for clinical research. The EHR4CR platform can enhance and speed up clinical research scenarios: protocol feasibility assessment, patient identification for recruitment in clinical trials, and clinical data exchange, including for reporting serious adverse events. Our objective was to seed a multi-stakeholder ecosystem to enable the scalable exploitation of the EHR4CR platform in Europe, and to assess its economic sustainability. Market analyses were conducted by a multidisciplinary task force to define an EHR4CR emerging ecosystem and multi-stakeholder value chain. This involved mapping stakeholder groups and defining their unmet needs, incentives, potential barriers for adopting innovative solutions, roles and interdependencies. A comprehensive business model, value propositions, and sustainability strategies were developed accordingly. Using simulation modelling (including Monte Carlo simulations) and a 5-year horizon, the potential financial outcomes of the business model were forecasted from the perspective of an EHR4CR service provider. A business ecosystem was defined to leverage the EHR4CR multi-stakeholder value chain. Value propositions were developed describing the expected benefits of EHR4CR solutions for all stakeholders. From an EHR4CR service provider's viewpoint, the business model simulation estimated that a profitability ratio of up to 1.8 could be achieved at year 1, with potential for growth in subsequent years depending on projected market uptake. By enhancing and speeding up existing processes, EHR4CR solutions promise to transform the clinical research landscape. The ecosystem defined provides the organisational framework for optimising the value and benefits for all stakeholders involved, in a sustainable manner. Our study suggests that the exploitation of EHR4CR solutions appears profitable and sustainable in Europe, with a growth potential depending on the rates of market and hospital adoption. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Predicting trends of invasive plants richness using local socio-economic data: An application in North Portugal

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

Santos, Mario, E-mail: mgsantoss@gmail.com; Freitas, Raul, E-mail: raulfreitas@portugalmail.com; Crespi, Antonio L., E-mail: aluis.crespi@gmail.com

2011-10-15

This study assesses the potential of an integrated methodology for predicting local trends in invasive exotic plant species (invasive richness) using indirect, regional information on human disturbance. The distribution of invasive plants was assessed in North Portugal using herbarium collections and local environmental, geophysical and socio-economic characteristics. Invasive richness response to anthropogenic disturbance was predicted using a dynamic model based on a sequential modeling process (stochastic dynamic methodology-StDM). Derived scenarios showed that invasive richness trends were clearly associated with ongoing socio-economic change. Simulations including scenarios of growing urbanization showed an increase in invasive richness while simulations in municipalities with decreasingmore » populations showed stable or decreasing levels of invasive richness. The model simulations demonstrate the interest and feasibility of using this methodology in disturbance ecology. - Highlights: {yields} Socio-economic data indicate human induced disturbances. {yields} Socio-economic development increase disturbance in ecosystems. {yields} Disturbance promotes opportunities for invasive plants.{yields} Increased opportunities promote richness of invasive plants.{yields} Increase in richness of invasive plants change natural ecosystems.« less

A Comparison of Landsat TM and ASTER for Equivalent Water Thickness Derivation in a Ponderosa Pine Ecosystem

NASA Astrophysics Data System (ADS)

Toomey, M.; Vierling, L.

2004-12-01

Landsat TM and ASTER satellite data can be used to make physically-based estimates of equivalent water thickness (EWT) in a Pinus ponderosa ecosystem. EWT is a measure of ecosystem water status and is an important parameter for studying ecosystem dynamics, fire potential, and biological responses to climate change. Near infrared (NIR) and shortwave infrared (SWIR) reflectances were simulated using the LIBERTY and GeoSAIL leaf and canopy reflectance models; the results were used to calculate a NIR/SWIR ratio and a normalized NIR/SWIR index. Index-EWT relationships were modeled and inverted for EWT derivation. Landsat and ASTER were used to make reasonably accurate estimates of EWT (± 17.3% and 19.4% mean error, respectively); TM band 5 and ASTER band 4 produced the best results. Exclusion of plots with dense understory vegetation reduced point scatter substantially, especially with Landsat (r2 = 0.847, ±13%), indicating that this method can provide robust EWT quantification in homogeneous conifer ecosystems.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

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

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Environmental fate and biodegradability of benzene derivatives as studied in a model aquatic ecosystem.

PubMed Central

Lu, P Y; Metcalf, R L

1975-01-01

A model aquatic ecosystem is devised for studying relatively volatile organic compounds and simulating direct discharge of chemical wastes into aquatic ecosystems. Six simple benzene derivatives (aniline, anisole, benzoic acid, chlorobenzene, nitrobenzene, and phthalic anhydride) and other important specialty chemicals: hexachlorobenzene, pentachlorophenol, 2,6-diethylaniline, and 3,5,6-trichloro-2-pyridinol were also chosen for study of environmental behavior and fate in the model aquatic ecosystem. Quantitative relationships of the intrinsic molecular properties of the environmental micropollutants with biological responses are established, e.g., water solubility, partition coefficient, pi constant, sigma constant, ecological magnification, biodegradability index, and comparative detoxication mechanisms, respectively. Water solubility, pi constant, and sigma constant are the most significant factors and control the biological responses of the food chain members. Water solubility and pi constant control the degree of bioaccumulation, and sigma constant limits the metabolism of the xenobiotics via microsomal detoxication enzymes. These highly significant correlations should be useful for predicting environmental fate of organic chemicals. PMID:1157796

The impact of exploiting grazers (Scaridae) on the dynamics of Caribbean coral reefs.

PubMed

Mumby, Peter J

2006-04-01

Coral reefs provide a number of ecosystem services including coastal defense from storms, the generation of building materials, and fisheries. It is increasingly clear that the management of reef resources requires an ecosystem approach in which extractive activities are weighed against the needs of the ecosystem and its functions rather than solely those of the fishery. Here, I use a spatially explicit simulation model of a Caribbean coral reef to examine the ecosystem requirements for grazing which is primarily conducted by parrotfishes (Scaridae). The model allows the impact of fishing grazers to be assessed in the wider context of other ecosystem processes including coral-algal competition, hurricanes, and mass extinction of the herbivorous urchin Diadema antillarum. Using a new analytical model of scarid grazing, it is estimated that parrotfishes can only maintain between 10% and 30% of a structurally complex forereef in a grazed state. Predictions from this grazing model were then incorporated into a broader simulation model of the ecosystem. Simulations predict that scarid grazing is unable to maintain high levels of coral cover (> or = 30%) when severe hurricanes occur on a decadal basis, such as occurs in parts of the northern Caribbean. However, reefs can withstand such intense disturbance when grazing is undertaken by both scarids and the urchin Diadema. Scarid grazing is predicted to allow recovery from hurricanes when their incidence falls to 20 years or less (e.g., most of Central and South America). Sensitivity analyses revealed that scarid grazing had the most acute impact on model behavior, and depletion led to the emergence of a stable, algal-dominated community state. Under conditions of heavy grazer depletion, coral cover was predicted to decline rapidly from an initial level of 30% to less than 1% within 40 years, even when hurricane frequency was low at 60 years. Depleted grazers caused a population bottleneck in juvenile corals in which algal overgrowth caused elevated levels of postsettlement mortality and resulted in a bimodal distribution of coral sizes. Several new hypotheses were generated including a region-wide change in the spatial heterogeneity of coral reefs following extinction of Diadema. The management of parrotfishes on Caribbean reefs is usually approached implicitly through no-take marine reserves. The model predicts that depletion of grazers in nonreserve areas can severely limit coral accretion. Other studies have shown that low coral accretion can reduce the structural complexity and therefore quality of the reef habitat for many organisms. A speculative yet rational inference from the model is that failure to manage scarid populations outside reserves will have a profoundly negative impact on the functioning of the reserve system and status of non-reserve reefs.

Carbon budget of tropical forests in Southeast Asia and the effects of deforestation: an approach using a process-based model and field measurements

NASA Astrophysics Data System (ADS)

Adachi, M.; Ito, A.; Ishida, A.; Kadir, W. R.; Ladpala, P.; Yamagata, Y.

2011-03-01

More reliable estimates of carbon (C) stock within forest ecosystems and C emission induced by deforestation are urgently needed to mitigate the effects of emissions on climate change. A process-based terrestrial biogeochemical model (VISIT) was applied to tropical primary forests of two types (a seasonal dry forest in Thailand and a rainforest in Malaysia) and one agro-forest (an oil palm plantation in Malaysia) to estimate the C budget of tropical ecosystems, including the impacts of land-use conversion, in Southeast Asia. Observations and VISIT model simulations indicated that the primary forests had high photosynthetic uptake: gross primary production was estimated at 31.5-35.5 t C ha-1 yr-1. In the VISIT model simulation, the rainforest had a higher total C stock (plant biomass and soil organic matter, 301.5 t C ha-1) than that in the seasonal dry forest (266.5 t C ha-1) in 2008. The VISIT model appropriately captured the impacts of disturbances such as deforestation and land-use conversions on the C budget. Results of sensitivity analysis implied that the ratio of remaining residual debris was a key parameter determining the soil C budget after deforestation events. The C stock of the oil palm plantation was about 46% of the rainforest's C at 30 yr following initiation of the plantation, when the ratio of remaining residual debris was assumed to be about 33%. These results show that adequate forest management is important for reducing C emission from soil and C budget of each ecosystem must be evaluated over a long term using both the model simulations and observations.

Process Model for Studying Regional 13C Stable Isotope Exchange between Vegetation and Atmosphere

NASA Astrophysics Data System (ADS)

Chen, J. M.; Chen, B.; Huang, L.; Tans, P.; Worthy, D.; Ishizawa, M.; Chan, D.

2007-12-01

The variation of the stable isotope 13CO2 in the air in exchange with land ecosystems results from fractionation processes in both plants and soil during photosynthesis and respiration. Its diurnal and seasonal variations therefore contain information on the carbon cycle. We developed a model (BEPS-iso) to simulate its exchange between vegetation and the atmosphere. To be useful for regional carbon cycle studies, the model has the following characteristics: (i) it considers the turbulent mixing in the vertical profile from the soil surface to the top of the planetary boundary layer (PBL); (ii) it scales individual leaf photosynthetic discrimination to the whole canopy through the separation of sunlit and shaded leaf groups; (iii) through simulating leaf-level photosynthetic processes, it has the capacity to mechanistically examine isotope discrimination resulting from meteorological forcings, such as radiation, precipitation and humidity; and (iv) through complete modeling of radiation, energy and water fluxes, it also simulates soil moisture and temperature needed for estimating ecosystem respiration and the 13C signal from the soil. After validation using flask data acquired at 20 m level on a tower near Fraserdale, Ontario, Canada, during intensive campaigns (1998-2000), the model has been used for several purposes: (i) to investigate the diurnal and seasonal variations in the disequilibrium in 13C fractionation between ecosystem respiration and photosynthesis, which is an important step in using 13C measurements to separate these carbon cycle components; (ii) to quantify the 13C rectification in the PBL, which differs significantly from CO2 rectification because of the diurnal and seasonal disequilibriums; and (iii) to model the 13C spatial and temporal variations over the global land surface for the purpose of CO2 inversion using 13C as an additional constraint.

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

A Simulation of Biological Prosesses in the Equatorial Pacific Warm Pool at 165 deg E

NASA Technical Reports Server (NTRS)

McClain, Charles R.; Murtugudde, Ragu; Signorini, Sergio

1998-01-01

A nine-year simulation (1984-1992) of biological processes in the equatorial Pacific Warm Pool is presented. A modified version of the 4-component (phytoplankton, zooplankton, nitrate and ammonium) ecosystem model by McClain et al. (1996) is used. Modifications include use of a spectral model for computation of PAR and inclusion of fecal pellet remineralization and ammonium nitrification. The physical parameters (horizontal and vertical velocities and temperature) required by the ecosystem model were derived from an improved version of the Gent and Cane (1990) ocean general circulation model (Murtugudde and Busalacchi, 1997). Surface downwelling spectral irradiance was estimated using the clear-sky models of Frouin et al. (1989) and Gregg and Carder (1990) and cloud cover information from the International Satellite Cloud Climatology Project (ISCCP). The simulations indicate considerable variability on interannual time scales in all four ecosystem components. In particular, surface chlorophyll concentrations varied by an order of magnitude with maximum values exceeding 0.30 mg/cu m in 1988, 1989, and 1990, and pronounced minimums during 1987 and 1992. The deep chlorophyll maximum ranged between 75 and 125 meters with values occasionally exceeding 0.40 mg/cu m. With the exception of the last half of 1988, surface nitrate was always near depletion. Ammonium exhibited a subsurface maximum just below the DCM with concentrations as high as 0.5 mg-atN/cu m . Total integrated annual primary production varied between 40 and 250 gC/sq m/yr with an annual average of 140 gC/sq m/yr. Finally, the model is used to estimate the mean irradiance at the base of the mixed layer, i.e., the penetration irradiance, which was 18 Watts/sq m over the nine year period. The average mixed layer depth was 42 m.

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.

Invasive species: an increasing threat to marine ecosystems under climate change?

NASA Astrophysics Data System (ADS)

Artioli, Yuri; Galienne, Chris; Holt, Jason; Wakelin, Sarah; Butenschön, Momme; Schrum, Corinna; Daewel, Ute; Pushpadas, Dhania; Cannaby, Heather; Salihoglu, Baris; Zavatarelli, Marco; Clementi, Emanuela; Olenin, Sergej; Allen, Icarus

2013-04-01

Planktonic Non-Indigenous Species (NIS) are a potential threat to marine ecosystems: a successful invasion of such organisms can alter significantly the ecosystem structure with shift in species composition that can affect different levels of the trophic network and also with local extinction of native species in the more extreme cases. Such changes will also impact some ecosystem functions like primary and secondary production or nutrient cycling, and services, like fishery, aquaculture or carbon sequestration. Understanding how climate change influences the susceptibility of a marine ecosystem to invasion is challenging as the success and the impact of an invasion depend on many different factors all tightly interconnected (e.g. time of the invasion, location, state of the ecosystem…). Here we present DivERSEM, a new version of the biogeochemical model ERSEM modified in order to account for phytoplankton diversity. With such a model, we are able to simulate invasion from phytoplankton NIS, to assess the likelihood of success of such an invasion and to estimate the potential impact on ecosystem structure, using indicator like the Biopollution index. In the MEECE project (www.meece.eu), the model has been coupled to a 1D water column model (GOTM) in two different climate scenarios (present day and the IPCC SRES A1B scenario for 2100) in 4 different European shelf seas (North Sea, Baltic Sea, Black Sea and Adriatic Sea). The model has been forced with atmospheric data coming from the IPSL climate model, and nutrient concentration extracted from a set of 3D biogeochemical models running under the same climate scenario. The response of the ecosystem susceptibility to invasion to climate change has been analysed comparing the successfulness of invasions in the two time slices and its impact on community structure and ecosystem functions. At the same time, the comparison among the different basins allowed to highlight some of the characteristics that make the ecosystems more vulnerable to NIS.

Freshwater Ecosystem Service Flow Model To Evaluate Regional Water Security: A Case Study In Beijing-Tianjin-Hebei Region, China

NASA Astrophysics Data System (ADS)

Li, D.; Li, S.

2016-12-01

Freshwater service, as the most important support ecosystem service, is essential to human survival and development. Many studies have evidenced the spatial differences in the supply and demand of ecosystem services and raised the concept of ecosystem service flow. However, rather few studies quantitatively characterize the freshwater service flow. This paper aims to quantify the effect of freshwater ecosystem service flow on downstream areas in Beijing-Tianjin-Hebei (BTH) region, China over 2000, 2005 and 2010. We computed the freshwater ecosystem service provision with InVEST model. We calculated freshwater ecosystem service consumption with water quota method. We simulated the freshwater ecosystem service flow using our simplified flow model and assessed the regional water security with the improved freshwater security index. The freshwater provision service mainly depends on climatic factors that cannot be influenced by management, while the freshwater consumption service is constrained by human activities. Furthermore, the decrease of water quota for agricultural, domestic and industrial water counteracts the impact of increasing freshwater demand. The analysis of freshwater ecosystem service flow reveals that the majority area of the BTH (69.2%) is affected by upstream freshwater. If freshwater ecosystem service flow is considered, the water safety areas of the whole BTH account for 66.9%, 66.1%, 71.3%, which increase 6.4%, 6.8% and 5.7% in 2000, 2005 and 2010, respectively. These results highlight the need to understand the teleconnections between distant freshwater ecosystem service provision and local freshwater ecosystem service use. This approach therefore helps managers choose specific management and investment strategies for critical upstream freshwater provisions across different regions.

Simulating dynamics of δ13C of CO2 in the planetary boundary layer over a boreal forest region: covariation between surface fluxes and atmospheric mixing

NASA Astrophysics Data System (ADS)

Chen, Baozhang; Chen, Jing M.; Tans, Pieter P.; Huang, Lin

2006-11-01

Stable isotopes of CO2 contain unique information on the biological and physical processes that exchange CO2 between terrestrial ecosystems and the atmosphere. Ecosystem exchange of carbon isotopes with the atmosphere is correlated diurnally and seasonally with the planetary boundary layer (PBL) dynamics. The strength of this kind of covariation affects the vertical gradient of δ13C and thus the global δ13C distribution pattern. We need to understand the various processes involved in transport/diffusion of carbon isotope ratio in the PBL and between the PBL and the biosphere and the troposphere. In this study, we employ a one-dimensional vertical diffusion/transport atmospheric model (VDS), coupled to an ecosystem isotope model (BEPS-EASS) to simulate dynamics of 13CO2 in the PBL over a boreal forest region in the vicinity of the Fraserdale (FRD) tower (49°52'29.9''N, 81°34'12.3''W) in northern Ontario, Canada. The data from intensive campaigns during the growing season in 1999 at this site are used for model validation in the surface layer. The model performance, overall, is satisfactory in simulating the measured data over the whole course of the growing season. We examine the interaction of the biosphere and the atmosphere through the PBL with respect to δ13C on diurnal and seasonal scales. The simulated annual mean vertical gradient of δ13C in the PBL in the vicinity of the FRD tower was about 0.25‰ in 1999. The δ13C vertical gradient exhibited strong diurnal (29%) and seasonal (71%) variations that do not exactly mimic those of CO2. Most of the vertical gradient (96.5% +/-) resulted from covariation between ecosystem exchange of carbon isotopes and the PBL dynamics, while the rest (3.5%+/-) was contributed by isotopic disequilibrium between respiration and photosynthesis. This disequilibrium effect on δ13C of CO2 dynamics in PBL, moreover, was confined to the near surface layers (less than 350 m).

Understanding hydrologic budgets, dynamics in an arid basin and explore spatial scaling properties using Process-based Adaptive Watershed Simulator (PAWS)

NASA Astrophysics Data System (ADS)

Fang, K.; Shen, C.; Salve, R.

2013-12-01

The Southern California hot desert hosts a fragile ecosystem as well as a range of human economic activities, primarily mining, energy production and recreation. This inland arid landscape is characterized by occasional intensive precipitation events and year-round strong potential evapotranspiration. In this landscape, water and especially groundwater is vital for ecosystem functions and human use. However, the impact of recent development on the sustainability of groundwater resources in the area has not been thoroughly investigated. We apply an integrated, physically-based hydrologic-land surface model, the Process-based Adaptive Watershed Simulator + Community Land Model (PAWS+CLM) to evaluate the sustainability of the groundwater resources in the area. We elucidate the spatio-temporal patterns of hydrologic fluxes and budgets. The modeling results indicate that mountain front recharge is the essential recharging mechanism for the alluvial aquifer. Although pumping activities do not exceed annual-average recharge values, they are still expected to contribute significantly to groundwater drawdown in business-as-usual scenario. The impact of groundwater withdrawals is significant on the desert ecosystem. The relative importance of groundwater flow on NPP rises significantly as compared to other ecosystems. We further evaluate the fractal scaling properties of soil moisture in this very arid system and found the relationship to be much more static in time than that found in a humid continental climate system. The scaling exponents can be predicted using simple functions of the mean. Therefore, multi-scale model based on coarse-resolution surrogate model is expected to perform well in this system. The modeling result is also important for assessing the groundwater sustainability and impact of human activities in the desert environment.

Modelling short-term variability in carbon and water exchange in a temperate Scots pine forest

NASA Astrophysics Data System (ADS)

Vermeulen, M. H.; Kruijt, B. J.; Hickler, T.; Kabat, P.

2015-07-01

The vegetation-atmosphere carbon and water exchange at one particular site can strongly vary from year to year, and understanding this interannual variability in carbon and water exchange (IAVcw) is a critical factor in projecting future ecosystem changes. However, the mechanisms driving this IAVcw are not well understood. We used data on carbon and water fluxes from a multi-year eddy covariance study (1997-2009) in a Dutch Scots pine forest and forced a process-based ecosystem model (Lund-Potsdam-Jena General Ecosystem Simulator; LPJ-GUESS) with local data to, firstly, test whether the model can explain IAVcw and seasonal carbon and water exchange from direct environmental factors only. Initial model runs showed low correlations with estimated annual gross primary productivity (GPP) and annual actual evapotranspiration (AET), while monthly and daily fluxes showed high correlations. The model underestimated GPP and AET during winter and drought events. Secondly, we adapted the temperature inhibition function of photosynthesis to account for the observation that at this particular site, trees continue to assimilate at very low atmospheric temperatures (up to daily averages of -10 °C), resulting in a net carbon sink in winter. While we were able to improve daily and monthly simulations during winter by lowering the modelled minimum temperature threshold for photosynthesis, this did not increase explained IAVcw at the site. Thirdly, we implemented three alternative hypotheses concerning water uptake by plants in order to test which one best corresponds with the data. In particular, we analyse the effects during the 2003 heatwave. These simulations revealed a strong sensitivity of the modelled fluxes during dry and warm conditions, but no single formulation was consistently superior in reproducing the data for all timescales and the overall model-data match for IAVcw could not be improved. Most probably access to deep soil water leads to higher AET and GPP simulated during the heatwave of 2003. We conclude that photosynthesis at lower temperatures than assumed in most models can be important for winter carbon and water fluxes in pine forests. Furthermore, details of the model representations of water uptake, which are often overlooked, need further attention, and deep water access should be treated explicitly.

The Role of Temporal Evolution in Modeling Atmospheric Emissions from Tropical Fires

NASA Technical Reports Server (NTRS)

Marlier, Miriam E.; Voulgarakis, Apostolos; Shindell, Drew T.; Faluvegi, Gregory S.; Henry, Candise L.; Randerson, James T.

2014-01-01

Fire emissions associated with tropical land use change and maintenance influence atmospheric composition, air quality, and climate. In this study, we explore the effects of representing fire emissions at daily versus monthly resolution in a global composition-climate model. We find that simulations of aerosols are impacted more by the temporal resolution of fire emissions than trace gases such as carbon monoxide or ozone. Daily-resolved datasets concentrate emissions from fire events over shorter time periods and allow them to more realistically interact with model meteorology, reducing how often emissions are concurrently released with precipitation events and in turn increasing peak aerosol concentrations. The magnitude of this effect varies across tropical ecosystem types, ranging from smaller changes in modeling the low intensity, frequent burning typical of savanna ecosystems to larger differences when modeling the short-term, intense fires that characterize deforestation events. The utility of modeling fire emissions at a daily resolution also depends on the application, such as modeling exceedances of particulate matter concentrations over air quality guidelines or simulating regional atmospheric heating patterns.

Simulation modeling to understand how selective foraging by beaver can drive the structure and function of a willow community

USGS Publications Warehouse

Peinetti, H.R.; Baker, B.W.; Coughenour, M.B.

2009-01-01

Beaver-willow (Castor-Salix) communities are a unique and vital component of healthy wetlands throughout the Holarctic region. Beaver selectively forage willow to provide fresh food, stored winter food, and construction material. The effects of this complex foraging behavior on the structure and function of willow communities is poorly understood. Simulation modeling may help ecologists understand these complex interactions. In this study, a modified version of the SAVANNA ecosystem model was developed to better understand how beaver foraging affects the structure and function of a willow community in a simulated riparian ecosystem in Rocky Mountain National Park, Colorado (RMNP). The model represents willow in terms of plant and stem dynamics and beaver foraging in terms of the quantity and quality of stems cut to meet the energetic and life history requirements of beaver. Given a site where all stems were equally available, the model suggested a simulated beaver family of 2 adults, 2 yearlings, and 2 kits required a minimum of 4 ha of willow (containing about10 stems m-2) to persist in a steady-state condition. Beaver created a willow community where the annual net primary productivity (ANPP) was 2 times higher and plant architecture was more diverse than the willow community without beaver. Beaver foraging created a plant architecture dominated by medium size willow plants, which likely explains how beaver can increase ANPP. Long-term simulations suggested that woody biomass stabilized at similar values even though availability differed greatly at initial condition. Simulations also suggested that willow ANPP increased across a range of beaver densities until beaver became food limited. Thus, selective foraging by beaver increased productivity, decreased biomass, and increased structural heterogeneity in a simulated willow community.

Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem in Eastern Canada.

NASA Astrophysics Data System (ADS)

Govind, A.; Chen, J. M.; Margolis, H.

2007-12-01

Current estimates of terrestrial carbon overlook the effects of topographically-driven lateral flow of soil water. We hypothesize that this component, which occur at a landscape or watershed scale have significant influences on the spatial distribution of carbon, due to its large contribution to the local water balance. To this end, we further developed a spatially explicit ecohydrological model, BEPS-TerrainLab V2.0. We simulated the coupled hydrological and carbon cycle processes in a black spruce-moss ecosystem in central Quebec, Canada. The carbon stocks were initialized using a long term carbon cycling model, InTEC, under a climate change and disturbance scenario, the accuracy of which was determined with inventory plot measurements. Further, we simulated and validated several ecosystem indicators such as ET, GPP, NEP, water table, snow depth and soil temperature, using the measurements for two years, 2004 and 2005. After gaining confidence in the model's ability to simulate ecohydrological processes, we tested the influence of lateral water flow on the carbon cycle. We made three hydrological modeling scenarios 1) Explicit, were realistic lateral water routing was considered 2) Implicit where calculations were based on a bucket modeling approach 3) NoFlow, where the lateral water flow was turned off in the model. The results showed that pronounced anomalies exist among the scenarios for the simulated GPP, ET and NEP. In general, Implicit calculation overestimated GPP and underestimated NEP, as opposed to Explicit simulation. NoFlow underestimated GPP and overestimated NEP. The key processes controlling GPP were manifested through stomatal conductance which reduces under conditions of rapid soil saturation ( NoFlow ) or increases in the Implicit case, and, nitrogen availability which affects Vcmax, the maximum carboxylation rate. However, for NEP, the anomalies were attributed to differences in soil carbon pool decomposition, which determine the heterotrophic respiration and the resultant nitrogen mineralization which affects GPP and several other feedback mechanisms. These results suggest that lateral water flow does play a significant role in the terrestrial carbon distribution. Therefore, regional or global scale terrestrial carbon estimates could have significant errors if proper hydrological constrains are not considered for modeling ecological processes due to large topographic variations on the Earth's surface. For more info please visit: http://ajit.govind.googlepages.com/agu2007

Hurricane frequency and landfall distribution for coastal wetlands of the Gulf coast, USA

USGS Publications Warehouse

Doyle, T.W.

2009-01-01

The regularity and severity of tropical storms are major determinants controlling ecosystem structure and succession for coastal ecosystems. Hurricane landfall rates vary greatly with high and low frequency for given coastal stretches of the southeastern United States. Site-specific meteorological data of hurricane wind speeds and direction, however, are only available for select populated cities of relatively sparse distribution and inland from the coast. A spatial simulation model of hurricane circulation, HURASIM, was applied to reconstruct chronologies of hurricane wind speeds and vectors for northern Gulf coast locations derived from historical tracking data of North Atlantic tropical storms dating back to 1851. Contrasts of storm frequencies showed that tropical storm incidence is nearly double for Florida coastal ecosystems than the westernmost stretches of Texas coastline. Finer-scale spatial simulations for the north-central Gulf coast exhibited sub-regional differences in storm strength and frequency with coastal position and latitude. The overall pattern of storm incidence in the Gulf basin indicates that the disturbance regime of coastal areas varies greatly along the coast, inland from the coast, and temporally over the period of record. Field and modeling studies of coastal ecosystems will benefit from this retrospective analysis of hurricane incidence and intensity both on a local or regional basis. ?? 2009 The Society of Wetland Scientists.

Evaluation of the DayCent model to predict carbon fluxes in French crop sites

NASA Astrophysics Data System (ADS)

Fujisaki, Kenji; Martin, Manuel P.; Zhang, Yao; Bernoux, Martial; Chapuis-Lardy, Lydie

2017-04-01

Croplands in temperate regions are an important component of the carbon balance and can act as a sink or a source of carbon, depending on pedoclimatic conditions and management practices. Therefore the evaluation of carbon fluxes in croplands by modelling approach is relevant in the context of global change. This study was part of the Comete-Global project funded by the multi-Partner call FACCE JPI. Carbon fluxes, net ecosystem exchange (NEE), leaf area index (LAI), biomass, and grain production were simulated at the site level in three French crop experiments from the CarboEurope project. Several crops were studied, like winter wheat, rapeseed, barley, maize, and sunflower. Daily NEE was measured with eddy covariance and could be partitioned between gross primary production (GPP) and total ecosystem respiration (TER). Measurements were compared to DayCent simulations, a process-based model predicting plant production and soil organic matter turnover at daily time step. We compared two versions of the model: the original one with a simplified plant module and a newer version that simulates LAI. Input data for modelling were soil properties, climate, and management practices. Simulations of grain yields and biomass production were acceptable when using optimized crop parameters. Simulation of NEE was also acceptable. GPP predictions were improved with the newer version of the model, eliminating temporal shifts that could be observed with the original model. TER was underestimated by the model. Predicted NEE was more sensitive to soil tillage and nitrogen applications than measured NEE. DayCent was therefore a relevant tool to predict carbon fluxes in French crops at the site level. The introduction of LAI in the model improved its performance.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

Development of mpi_EPIC model for global agroecosystem modeling

DOE PAGES

Kang, Shujiang; Wang, Dali; Jeff A. Nichols; ...

2014-12-31

Models that address policy-maker concerns about multi-scale effects of food and bioenergy production systems are computationally demanding. We integrated the message passing interface algorithm into the process-based EPIC model to accelerate computation of ecosystem effects. Simulation performance was further enhanced by applying the Vampir framework. When this enhanced mpi_EPIC model was tested, total execution time for a global 30-year simulation of a switchgrass cropping system was shortened to less than 0.5 hours on a supercomputer. The results illustrate that mpi_EPIC using parallel design can balance simulation workloads and facilitate large-scale, high-resolution analysis of agricultural production systems, management alternatives and environmentalmore » effects.« less

Asymmetric responses of primary productivity to altered precipitation simulated by ecosystem models across three long-term grassland sites

NASA Astrophysics Data System (ADS)

Wu, Donghai; Ciais, Philippe; Viovy, Nicolas; Knapp, Alan K.; Wilcox, Kevin; Bahn, Michael; Smith, Melinda D.; Vicca, Sara; Fatichi, Simone; Zscheischler, Jakob; He, Yue; Li, Xiangyi; Ito, Akihiko; Arneth, Almut; Harper, Anna; Ukkola, Anna; Paschalis, Athanasios; Poulter, Benjamin; Peng, Changhui; Ricciuto, Daniel; Reinthaler, David; Chen, Guangsheng; Tian, Hanqin; Genet, Hélène; Mao, Jiafu; Ingrisch, Johannes; Nabel, Julia E. S. M.; Pongratz, Julia; Boysen, Lena R.; Kautz, Markus; Schmitt, Michael; Meir, Patrick; Zhu, Qiuan; Hasibeder, Roland; Sippel, Sebastian; Dangal, Shree R. S.; Sitch, Stephen; Shi, Xiaoying; Wang, Yingping; Luo, Yiqi; Liu, Yongwen; Piao, Shilong

2018-06-01

Field measurements of aboveground net primary productivity (ANPP) in temperate grasslands suggest that both positive and negative asymmetric responses to changes in precipitation (P) may occur. Under normal range of precipitation variability, wet years typically result in ANPP gains being larger than ANPP declines in dry years (positive asymmetry), whereas increases in ANPP are lower in magnitude in extreme wet years compared to reductions during extreme drought (negative asymmetry). Whether the current generation of ecosystem models with a coupled carbon-water system in grasslands are capable of simulating these asymmetric ANPP responses is an unresolved question. In this study, we evaluated the simulated responses of temperate grassland primary productivity to scenarios of altered precipitation with 14 ecosystem models at three sites: Shortgrass steppe (SGS), Konza Prairie (KNZ) and Stubai Valley meadow (STU), spanning a rainfall gradient from dry to moist. We found that (1) the spatial slopes derived from modeled primary productivity and precipitation across sites were steeper than the temporal slopes obtained from inter-annual variations, which was consistent with empirical data; (2) the asymmetry of the responses of modeled primary productivity under normal inter-annual precipitation variability differed among models, and the mean of the model ensemble suggested a negative asymmetry across the three sites, which was contrary to empirical evidence based on filed observations; (3) the mean sensitivity of modeled productivity to rainfall suggested greater negative response with reduced precipitation than positive response to an increased precipitation under extreme conditions at the three sites; and (4) gross primary productivity (GPP), net primary productivity (NPP), aboveground NPP (ANPP) and belowground NPP (BNPP) all showed concave-down nonlinear responses to altered precipitation in all the models, but with different curvatures and mean values. Our results indicated that most models overestimate the negative drought effects and/or underestimate the positive effects of increased precipitation on primary productivity under normal climate conditions, highlighting the need for improving eco-hydrological processes in those models in the future.

When 1+1 can be >2: Uncertainties compound when simulating climate, fisheries and marine ecosystems

NASA Astrophysics Data System (ADS)

Evans, Karen; Brown, Jaclyn N.; Sen Gupta, Alex; Nicol, Simon J.; Hoyle, Simon; Matear, Richard; Arrizabalaga, Haritz

2015-03-01

Multi-disciplinary approaches that combine oceanographic, biogeochemical, ecosystem, fisheries population and socio-economic models are vital tools for modelling whole ecosystems. Interpreting the outputs from such complex models requires an appreciation of the many different types of modelling frameworks being used and their associated limitations and uncertainties. Both users and developers of particular model components will often have little involvement or understanding of other components within such modelling frameworks. Failure to recognise limitations and uncertainties associated with components and how these uncertainties might propagate throughout modelling frameworks can potentially result in poor advice for resource management. Unfortunately, many of the current integrative frameworks do not propagate the uncertainties of their constituent parts. In this review, we outline the major components of a generic whole of ecosystem modelling framework incorporating the external pressures of climate and fishing. We discuss the limitations and uncertainties associated with each component of such a modelling system, along with key research gaps. Major uncertainties in modelling frameworks are broadly categorised into those associated with (i) deficient knowledge in the interactions of climate and ocean dynamics with marine organisms and ecosystems; (ii) lack of observations to assess and advance modelling efforts and (iii) an inability to predict with confidence natural ecosystem variability and longer term changes as a result of external drivers (e.g. greenhouse gases, fishing effort) and the consequences for marine ecosystems. As a result of these uncertainties and intrinsic differences in the structure and parameterisation of models, users are faced with considerable challenges associated with making appropriate choices on which models to use. We suggest research directions required to address these uncertainties, and caution against overconfident predictions. Understanding the full impact of uncertainty makes it clear that full comprehension and robust certainty about the systems themselves are not feasible. A key research direction is the development of management systems that are robust to this unavoidable uncertainty.

Water ecosystem service function assessment based on eco-hydrological process in Luanhe Basin,China

NASA Astrophysics Data System (ADS)

Zhang, C.; Hao, C.; Qin, T.; Wang, G.; Weng, B.

2012-12-01

At present, ecological water are mainly occupied by a rapid development of social economic and population explosion, which seriously threat the ecological security and water security in watershed and regional scale. Due to the lack of a unified standard of measuring the benefit of water resource, social economic and ecosystem, the water allocation can't take place in social economic and ecosystem. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. Throughout the researches of water ecosystem service, a clear identification of the connection of water ecosystem service function has not been established, and eco-economic approach can't meet the practical requirement of water allocation. Based on "nature-artificiality" dual water cycle theory and eco-hydrological process, this paper proposes a connection and indicator system of water ecosystem service function. In approach, this paper establishes an integrated assessment approach through prototype observation technology, numerical simulation, physical simulation and modern geographic information technology. The core content is to couple an eco-hydrological model, which involves the key processes of distributed hydrological model (WEP), ecological model (CLM-DGVM), in terms of eco-hydrological process. This paper systematically evaluates the eco-hydrological process and evolution of Luanhe Basin in terms of precipitation, ET, runoff, groundwater, ecosystem's scale, form and distribution. According to the results of eco-hydrological process, this paper assesses the direct and derived service function. The result indicates that the general service function of 2010 has minor increase than 2007, however the general function of two years are in common level; Compare with different region, the upstream, middle stream and downstream indicates "worse", "common" and "good" level respectively. The first three derived functions are leisure, offer products and industrial water use. In the end, this paper investigates the evolution of water ecosystem service function under rising temperatures and elevated CO2 concentration scenarios in Luanhe Basin through eco-hydrological model. The results elaborate that the water ecosystem service functions would decline when temperature rising, and warming to 1.5 degree is the mutation point of sharp drop; Increased CO2 concentration scenario will improve the direct service function in the whole Basin; under the overlying scenario, different region shows different results, the direct service function will increased in upstream and middle stream, direct service function will drop in downstream. A comprehensive analysis indicates that the rising temperature is the major driven of water ecosystem service function in Luanhe Basin.

Tundra biome research in Alaska: the structure and function of cold-dominated ecosystems

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

Brown, J.; West, G.C.

1970-11-01

The objective of the Tundra Biome Program is to acquire a basic understanding of tundra, both alpine and arctic, and taiga. Collectively these are referred to as the cold-dominated ecosystems. The program's broad objectives are threefold: To develop a predictive understanding of how the wet arctic tundra ecosystem operates, particularly as exemplified in the Barrow, Alaska, area; to obtain the necessary data base from the variety of cold-dominated ecosystem types represented in the United States, so that their behavior can be modeled and simulated, and the results compared with similar studies underway in other circumpolar countries; to bring basic environmentalmore » knowledge to bear on problems of degradation, maintenance, and restoration of the temperature-sensitive and cold-dominated tundra/taiga ecosystems. (GRA)« less

Seasonality of Overstory and Understory Fluxes in a Semi-Arid Oak Savanna: What can be Learned from Comparing Measured and Modeled Fluxes?

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Chen, J. M.; Verfaillie, J. G.; Ma, S.; Baldocchi, D. D.

2011-12-01

Semi-arid climates experience large seasonal and inter-annual variability in radiation and precipitation, creating natural conditions adequate to study how year-to-year changes affect atmosphere-biosphere fluxes. Especially, savanna ecosystems, that combine tree and below-canopy components, create a unique environment in which phenology dramatically changes between seasons. We used a 10-year flux database in order to define seasonal and interannual variability of climatic inputs and fluxes, and evaluate model capability to reproduce observed variability. This is based on the perception that model capability to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site is a low density and low LAI (0.8) semi-arid savanna, located at Tonzi Ranch, Northern California. In this system, trees are active during the warm season (Mar - Oct), and grasses are active during the wet season (Dec - May). Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Fluxes were simulated using bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Models were partly capable of reproducing fluxes on daily scales (R2=0.66). We then compared model outputs for different ecosystem components and seasons, and found distinct seasons with high correlations while other seasons were purely represented. Comparison was much higher for ET than for GPP. The understory was better simulated than the overstory. CANOAK overestimated spring understory fluxes, probably due to the capability to directly calculated 3D radiative transfer. BEPS underestimated spring understory fluxes, following the pre-description of grass die-off. Both models underestimated peak spring overstory fluxes. During winter tree dormant, modeled fluxes were null, but occasional high fluxes of both ET and GPP were measured following precipitation events, likely produced by an adverse measurement effect. This analysis enabled to pinpoint specific areas where models break, and stress that model capability to reproduce fluxes vary among seasons and ecosystem components. The combined response was such, that comparison decreases when ecosystem fluxes were partitioned between overstory and understory fluxes. Model performance decreases with time scale; while performance was high for some seasons, models were less capable of reproducing the high variability in understory fluxes vs. the conservative overstory fluxes on annual scales. Discrepancies were not always a result of models' faults; comparison largely improved when measurements of overstory fluxes during precipitation events were excluded. Conclusions raised from this research enable to answer the critical question of the level and type of details needed in order to correctly predict ecosystem respond to environmental and climatic change.

Eddy-resolving simulation of plankton ecosystem dynamics in the California Current System

NASA Astrophysics Data System (ADS)

Gruber, Nicolas; Frenzel, Hartmut; Doney, Scott C.; Marchesiello, Patrick; McWilliams, James C.; Moisan, John R.; Oram, John J.; Plattner, Gian-Kasper; Stolzenbach, Keith D.

2006-09-01

We study the dynamics of the planktonic ecosystem in the coastal upwelling zone within the California Current System using a three-dimensional (3-D), eddy-resolving circulation model coupled to an ecosystem/biogeochemistry model. The physical model is based on the Regional Oceanic Modeling System (ROMS), configured at a resolution of 15 km for a domain covering the entire US West Coast, with an embedded child grid covering the central California upwelling region at a resolution of 5 km. The model is forced with monthly mean boundary conditions at the open lateral boundaries as well as at the surface. The ecological/biogeochemical model is nitrogen based, includes single classes for phytoplankton and zooplankton, and considers two detrital pools with different sinking speeds. The model also explicitly simulates a variable chlorophyll-to-carbon ratio. Comparisons of model results with either remote sensing observations (AVHRR, SeaWiFS) or in-situ measurements from the CalCOFI program indicate that our model is capable of replicating many of the large-scale, time-averaged features of the coastal upwelling system. An exception is the underestimation of the chlorophyll levels in the northern part of the domain, perhaps because of the lack of short-term variations in the atmospheric forcing. Another shortcoming is that the modeled thermocline is too diffuse, and that the upward slope of the isolines toward the coast is too small. Detailed time-series comparisons with observations from Monterey Bay reveal similar agreements and discrepancies. We attribute the good agreement between the modeled and observed ecological properties in large part to the accuracy of the physical fields. In turn, many of the discrepancies can be traced back to our use of monthly mean forcing. Analysis of the ecosystem structure and dynamics reveal that the magnitude and pattern of phytoplankton biomass in the nearshore region are determined largely by the balance of growth and zooplankton grazing, while in the offshore region, growth is balanced by mortality. The latter appears to be inconsistent with in situ observations and is a result of our consideration of only one zooplankton size class (mesozooplankton), neglecting the importance of microzooplankton grazing in the offshore region. A comparison of the allocation of nitrogen into the different pools of the ecosystem in the 3-D results with those obtained from a box model configuration of the same ecosystem model reveals that only a few components of the ecosystem reach a local steady-state, i.e. where biological sources and sinks balance each other. The balances for the majority of the components are achieved by local biological source and sink terms balancing the net physical divergence, confirming the importance of the 3-D nature of circulation and mixing in a coastal upwelling system.

Spatially Explicit Simulation of Mesotopographic Controls on Peatland Hydrology and Carbon Fluxes

NASA Astrophysics Data System (ADS)

Sonnentag, O.; Chen, J. M.; Roulet, N. T.

2006-12-01

A number of field carbon flux measurements, paleoecological records, and model simulations have acknowledged the importance of northern peatlands in terrestrial carbon cycling and methane emissions. An important parameter in peatlands that influences both net primary productivity, the net gain of carbon through photosynthesis, and decomposition under aerobic and anaerobic conditions, is the position of the water table. Biological and physical processes involved in peatland carbon dynamics and their hydrological controls operate at different spatial scales. The highly variable hydraulic characteristics of the peat profile and the overall shape of the peat body as defined by its surface topography at the mesoscale (104 m2) are of major importance for peatland water table dynamics. Common types of peatlands include bogs with a slightly domed centre. As a result of the convex profile, their water supply is restricted to atmospheric inputs, and water is mainly shed by shallow subsurface flow. From a modelling perspective the influence of mesotopographic controls on peatland hydrology and thus carbon balance requires that process-oriented models that examine the links between peatland hydrology, ecosystem functioning, and climate must incorporate some form of lateral subsurface flow consideration. Most hydrological and ecological modelling studies in complex terrain explicitly account for the topographic controls on lateral subsurface flow through digital elevation models. However, modelling studies in peatlands often employ simple empirical parameterizations of lateral subsurface flow, neglecting the influence of peatlands low relief mesoscale topography. Our objective is to explicitly simulate the mesotopographic controls on peatland hydrology and carbon fluxes using the Boreal Ecosystem Productivity Simulator (BEPS) adapted to northern peatlands. BEPS is a process-oriented ecosystem model in a remote sensing framework that takes into account peatlands multi-layer canopy through vertically stratified mapped leaf area index. Model outputs are validated against multi-year measurements taken at an eddy-covariance flux tower located within Mer Bleue bog, a typical raised bog near Ottawa, Ontario, Canada. Model results for seasonal water table dynamics and evapotranspiration at daily time steps in 2003 are in good agreement with measurements with R2=0.74 and R2=0.79, respectively, and indicate the suitability of our pursued approach.

Exploring eco-hydrological consequences of the Amazonian ecosystems under climate and land-use changes in the 21st century

NASA Astrophysics Data System (ADS)

Zhang, K.; Castanho, A. D.; Moghim, S.; Bras, R. L.; Coe, M. T.; Costa, M. H.; Levine, N. M.; Longo, M.; McKnight, S.; Wang, J.; Moorcroft, P. R.

2012-12-01

Deforestation and drought have imposed regional-scale perturbations onto Amazonian ecosystems and are predicted to cause larger negative impacts on the Amazonian ecosystems and associated regional carbon dynamics in the 21st century. However, global climate models (GCMs) vary greatly in their projections of future climate change in Amazonia, giving rise to uncertainty in the expected fate of the Amazon over the coming century. In this study, we explore the possible eco-hydrological consequences of the Amazonian ecosystems under projected climate and land-use changes in the 21st century using two state-of-the-art terrestrial ecosystem models—Ecosystem Demography Model 2.1(ED2.1) and Integrated Biosphere Simulator model (IBIS)—driven by three representative, bias-corrected climate projections from three IPCC GCMs (NCARPCM1, NCARCCSM3 and HadCM3), coupled with two land-use change scenarios (a business-as-usual and a strict governance scenario). We also analyze the relative roles of climate change, CO2 fertilization, land-use change and fire in driving the projected composition and structure of the Amazonian ecosystems. Our results show that CO2 fertilization enhances vegetation productivity and above-ground biomass (AGB) in the region, while land-use change and fire cause AGB loss and the replacement of forests by the savanna-like vegetation. The impacts of climate change depend strongly on the direction and severity of projected precipitation changes in the region. In particular, when intensified water stress is superimposed on unregulated deforestation, both ecosystem models predict large-scale dieback of Amazonian rainforests.

Ensemble ecosystem modeling for predicting ecosystem response to predator reintroduction.

PubMed

Baker, Christopher M; Gordon, Ascelin; Bode, Michael

2017-04-01

Introducing a new or extirpated species to an ecosystem is risky, and managers need quantitative methods that can predict the consequences for the recipient ecosystem. Proponents of keystone predator reintroductions commonly argue that the presence of the predator will restore ecosystem function, but this has not always been the case, and mathematical modeling has an important role to play in predicting how reintroductions will likely play out. We devised an ensemble modeling method that integrates species interaction networks and dynamic community simulations and used it to describe the range of plausible consequences of 2 keystone-predator reintroductions: wolves (Canis lupus) to Yellowstone National Park and dingoes (Canis dingo) to a national park in Australia. Although previous methods for predicting ecosystem responses to such interventions focused on predicting changes around a given equilibrium, we used Lotka-Volterra equations to predict changing abundances through time. We applied our method to interaction networks for wolves in Yellowstone National Park and for dingoes in Australia. Our model replicated the observed dynamics in Yellowstone National Park and produced a larger range of potential outcomes for the dingo network. However, we also found that changes in small vertebrates or invertebrates gave a good indication about the potential future state of the system. Our method allowed us to predict when the systems were far from equilibrium. Our results showed that the method can also be used to predict which species may increase or decrease following a reintroduction and can identify species that are important to monitor (i.e., species whose changes in abundance give extra insight into broad changes in the system). Ensemble ecosystem modeling can also be applied to assess the ecosystem-wide implications of other types of interventions including assisted migration, biocontrol, and invasive species eradication. © 2016 Society for Conservation Biology.

Net primary productivity of China's terrestrial ecosystems from a process model driven by remote sensing.

PubMed

Feng, X; Liu, G; Chen, J M; Chen, M; Liu, J; Ju, W M; Sun, R; Zhou, W

2007-11-01

The terrestrial carbon cycle is one of the foci in global climate change research. Simulating net primary productivity (NPP) of terrestrial ecosystems is important for carbon cycle research. In this study, China's terrestrial NPP was simulated using the Boreal Ecosystem Productivity Simulator (BEPS), a carbon-water coupled process model based on remote sensing inputs. For these purposes, a national-wide database (including leaf area index, land cover, meteorology, vegetation and soil) at a 1 km resolution and a validation database were established. Using these databases and BEPS, daily maps of NPP for the entire China's landmass in 2001 were produced, and gross primary productivity (GPP) and autotrophic respiration (RA) were estimated. Using the simulated results, we explore temporal-spatial patterns of China's terrestrial NPP and the mechanisms of its responses to various environmental factors. The total NPP and mean NPP of China's landmass were 2.235 GtC and 235.2 gCm(-2)yr(-1), respectively; the total GPP and mean GPP were 4.418 GtC and 465 gCm(-2)yr(-1); and the total RA and mean RA were 2.227 GtC and 234 gCm(-2)yr(-1), respectively. On average, NPP was 50.6% of GPP. In addition, statistical analysis of NPP of different land cover types was conducted, and spatiotemporal patterns of NPP were investigated. The response of NPP to changes in some key factors such as LAI, precipitation, temperature, solar radiation, VPD and AWC are evaluated and discussed.

[Response of water yield function of ecosystem to land use change in Nansi Lake Basin based on CLUE-S model and InVEST model .

PubMed

Guo, Hong Wei; Sun, Xiao Yin; Lian, Li Shu; Zhang, Da Zhi; Xu, Yan

2016-09-01

Land use change has an important role in hydrological processes and utilization of water resources, and is the main driving force of water yield function of ecosystem. This paper analyzed the change of land use from 1990 to 2013 in Nansi Lake Basin, Shandong Province. The future land use in 2030 was also predicted and simulated by CLUE-S model. Based on land use scenarios, we analyzed the influence of land use change on ecosystem function of water yield in nearly 25 years through InVEST water yield model and spatial mapping. The results showed that the area of construction land increased by 3.5% in 2013 because of burgeoning urbanization process, but farmland area decreased by 2.4% which was conversed to construction land mostly. The simulated result of InVEST model suggested that water yield level of whole basin decreased firstly and increased subsequently during last 25 years and peaked at 232.1 mm in 2013. The construction land area would increase by 6.7% in 2030 based on the land use scenarios of fast urbanization, which would lead to a remarkable growth for water yield and risk of flowing flooding. However, the water yield level of whole basin would decrease by 1.2 % in 2013 if 300 meter-wide forest buffer strips around Nansi Lake were built up.

Seasonal and inter-annual dynamics in the stable oxygen isotope compositions of water pools in a temperate humid grassland ecosystem: results from MIBA sampling and MuSICA modelling

NASA Astrophysics Data System (ADS)

Hirl, Regina; Schnyder, Hans; Auerswald, Karl; Vetter, Sylvia; Ostler, Ulrike; Schleip, Inga; Wingate, Lisa; Ogée, Jérôme

2015-04-01

The oxygen isotope composition (δ18O) of water in terrestrial ecosystems usually shows strong and dynamic variations within and between the various compartments. These variations originate from changes in the δ18O of water inputs (e.g. rain or water vapour) and from 18O fractionation phenomena in the soil-plant-atmosphere continuum. Investigations of δ18O in ecosystem water pools and of their main drivers can help us understand water relations at plant, canopy or ecosystem scale and interpret δ18O signals in plant and animal tissues as paleo-climate proxies. During the vegetation periods of 2006 to 2012, soil, leaf and stem water as well as atmospheric humidity, rain water and groundwater were sampled at bi-weekly intervals in a temperate humid pasture of the Grünschwaige Grassland Research Station near Munich (Germany). The sampling was performed following standardised MIBA (Moisture Isotopes in the Biosphere and Atmosphere) protocols. Leaf water samples were prepared from a mixture of co-dominant species in the plant community in order to obtain a canopy-scale leaf water δ18O signal. All samples were then analysed for their δ18O compositions. The measured δ18O of leaf, stem and soil water were then compared with the δ18O signatures simulated by the process-based isotope-enabled ecosystem model MuSICA (Multi-layer Simulator of the Interactions between a vegetation Canopy and the Atmosphere). MuSICA integrates current mechanistic understanding of processes in the soil-plant-atmosphere continuum. Hence, the comparison of modelled and measured data allows the identification of gaps in current knowledge and of questions to be tackled in the future. Soil and plant characteristics for model parameterisation were derived from investigations at the experimental site and supplemented by values from the literature. Eddy-covariance measurements of ecosystem CO2 (GPP, NEE) and energy (H, LE) fluxes and soil temperature data were used for model evaluation. The comparison of measured and predicted ecosystem fluxes showed that the model captured the main features of the diurnal cycles of GPP, NEE, LE and H, as well as the soil temperature dynamics. In this presentation I will present the main results of this model-data comparison, as well as results from a model sensitivity analysis performed over a range of soil, plant and meteorological parameters to evaluate the relative importance of each parameter on the δ18O signatures of the various water pools.

Assessing the trophic position and ecological role of squids in marine ecosystems by means of food-web models

NASA Astrophysics Data System (ADS)

Coll, Marta; Navarro, Joan; Olson, Robert J.; Christensen, Villy

2013-10-01

We synthesized available information from ecological models at local and regional scales to obtain a global picture of the trophic position and ecological role of squids in marine ecosystems. First, static food-web models were used to analyze basic ecological parameters and indicators of squids: biomass, production, consumption, trophic level, omnivory index, predation mortality diet, and the ecological role. In addition, we developed various dynamic temporal simulations using two food-web models that included squids in their parameterization, and we investigated potential impacts of fishing pressure and environmental conditions for squid populations and, consequently, for marine food webs. Our results showed that squids occupy a large range of trophic levels in marine food webs and show a large trophic width, reflecting the versatility in their feeding behaviors and dietary habits. Models illustrated that squids are abundant organisms in marine ecosystems, and have high growth and consumption rates, but these parameters are highly variable because squids are adapted to a large variety of environmental conditions. Results also show that squids can have a large trophic impact on other elements of the food web, and top-down control from squids to their prey can be high. In addition, some squid species are important prey of apical predators and may be keystone species in marine food webs. In fact, we found strong interrelationships between neritic squids and the populations of their prey and predators in coastal and shelf areas, while the role of squids in open ocean and upwelling ecosystems appeared more constrained to a bottom-up impact on their predators. Therefore, large removals of squids will likely have large-scale effects on marine ecosystems. In addition, simulations confirm that squids are able to benefit from a general increase in fishing pressure, mainly due to predation release, and quickly respond to changes triggered by the environment. Squids may thus be very sensitive to the effects of fishing and climate change.

APEX sensitivity to atrazine dissipation rate on surface runoff loss within a coastal zone in Southeastern Puerto Rico

USDA-ARS?s Scientific Manuscript database

Simulation models are increasingly used to predict effects of conservation practices on transport of pesticides to water bodies. We used two models - the Agricultural Policy/Environmental eXtender (APEX) and the Riparian Ecosystem Management Model (REMM) to predict the movement of the herbicide, at...

Special features of the dayCent modeling package and additional procedures for parameterization, calibration, validation, and applications

USDA-ARS?s Scientific Manuscript database

DayCent (Daily Century) is a biogeochemical model of intermediate complexity used to simulate flows of carbon and nutrients for crop, grassland, forest, and savanna ecosystems. Required model inputs are: soil texture, current and historical land use, vegetation cover, and daily maximum/minimum tempe...

Empirical methods for modeling landscape change, ecosystem services, and biodiversity

Treesearch

David Lewis; Ralph Alig

2009-01-01

The purpose of this paper is to synthesize recent economics research aimed at integrating discrete-choice econometric models of land-use change with spatially-explicit landscape simulations and quantitative ecology. This research explicitly models changes in the spatial pattern of landscapes in two steps: 1) econometric estimation of parcel-scale transition...

Global carbon assimilation system using a local ensemble Kalman filter with multiple ecosystem models

NASA Astrophysics Data System (ADS)

Zhang, Shupeng; Yi, Xue; Zheng, Xiaogu; Chen, Zhuoqi; Dan, Bo; Zhang, Xuanze

2014-11-01

In this paper, a global carbon assimilation system (GCAS) is developed for optimizing the global land surface carbon flux at 1° resolution using multiple ecosystem models. In GCAS, three ecosystem models, Boreal Ecosystem Productivity Simulator, Carnegie-Ames-Stanford Approach, and Community Atmosphere Biosphere Land Exchange, produce the prior fluxes, and an atmospheric transport model, Model for OZone And Related chemical Tracers, is used to calculate atmospheric CO2 concentrations resulting from these prior fluxes. A local ensemble Kalman filter is developed to assimilate atmospheric CO2 data observed at 92 stations to optimize the carbon flux for six land regions, and the Bayesian model averaging method is implemented in GCAS to calculate the weighted average of the optimized fluxes based on individual ecosystem models. The weights for the models are found according to the closeness of their forecasted CO2 concentration to observation. Results of this study show that the model weights vary in time and space, allowing for an optimum utilization of different strengths of different ecosystem models. It is also demonstrated that spatial localization is an effective technique to avoid spurious optimization results for regions that are not well constrained by the atmospheric data. Based on the multimodel optimized flux from GCAS, we found that the average global terrestrial carbon sink over the 2002-2008 period is 2.97 ± 1.1 PgC yr-1, and the sinks are 0.88 ± 0.52, 0.27 ± 0.33, 0.67 ± 0.39, 0.90 ± 0.68, 0.21 ± 0.31, and 0.04 ± 0.08 PgC yr-1 for the North America, South America, Africa, Eurasia, Tropical Asia, and Australia, respectively. This multimodel GCAS can be used to improve global carbon cycle estimation.

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.

Using the CARDAMOM framework to retrieve global terrestrial ecosystem functioning properties

NASA Astrophysics Data System (ADS)

Exbrayat, Jean-François; Bloom, A. Anthony; Smallman, T. Luke; van der Velde, Ivar R.; Feng, Liang; Williams, Mathew

2016-04-01

Terrestrial ecosystems act as a sink for anthropogenic emissions of fossil-fuel and thereby partially offset the ongoing global warming. However, recent model benchmarking and intercomparison studies have highlighted the non-trivial uncertainties that exist in our understanding of key ecosystem properties like plant carbon allocation and residence times. It leads to worrisome differences in terrestrial carbon stocks simulated by Earth system models, and their evolution in a warming future. In this presentation we attempt to provide global insights on these properties by merging an ecosystem model with remotely-sensed global observations of leaf area and biomass through a data-assimilation system: the CARbon Data MOdel fraMework (CARDAMOM). CARDAMOM relies on a Markov Chain Monte Carlo algorithm to retrieve confidence intervals of model parameters that regulate ecosystem properties independently of any prior land-cover information. The MCMC method thereby enables an explicit representation of the uncertainty in land-atmosphere fluxes and the evolution of terrestrial carbon stocks through time. Global experiments are performed for the first decade of the 21st century using a 1°×1° spatial resolution. Relationships emerge globally between key ecosystem properties. For example, our analyses indicate that leaf lifespan and leaf mass per area are highly correlated. Furthermore, there exists a latitudinal gradient in allocation patterns: high latitude ecosystems allocate more carbon to photosynthetic carbon (leaves) while plants invest more carbon in their structural parts (wood and root) in the wet tropics. Overall, the spatial distribution of these ecosystem properties does not correspond to usual land-cover maps and are also partially correlated with disturbance regimes. For example, fire-prone ecosystems present statistically significant higher values of carbon use efficiency than less disturbed ecosystems experiencing similar climatic conditions. These results raise concerns on the suitability of the plant functional type paradigm for terrestrial carbon cycling.

Response of a subalpine grassland to simulated grazing: Aboveground productivity along soil phosphorus gradients

Treesearch

C. Thiel-Egenter; A. C. Risch; M. F. Jurgensen; D. S. Page-Dumroese; B. O. Krusi; M. Schutz

2007-01-01

Interactions between grassland ecosystems and vertebrate herbivores are critical for a better understanding of ecosystem processes, but diverge widely in different ecosystems. In this study, we examined plant responses to simulated red deer (Cervus elaphus L.) grazing using clip-plot experiments in a subalpine grassland ecosystem of the Central...

Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to fish and coasts to ocean

NASA Astrophysics Data System (ADS)

Holt, Jason; Icarus Allen, J.; Anderson, Thomas R.; Brewin, Robert; Butenschön, Momme; Harle, James; Huse, Geir; Lehodey, Patrick; Lindemann, Christian; Memery, Laurent; Salihoglu, Baris; Senina, Inna; Yool, Andrew

2014-12-01

It has long been recognised that there are strong interactions and feedbacks between climate, upper ocean biogeochemistry and marine food webs, and also that food web structure and phytoplankton community distribution are important determinants of variability in carbon production and export from the euphotic zone. Numerical models provide a vital tool to explore these interactions, given their capability to investigate multiple connected components of the system and the sensitivity to multiple drivers, including potential future conditions. A major driver for ecosystem model development is the demand for quantitative tools to support ecosystem-based management initiatives. The purpose of this paper is to review approaches to the modelling of marine ecosystems with a focus on the North Atlantic Ocean and its adjacent shelf seas, and to highlight the challenges they face and suggest ways forward. We consider the state of the art in simulating oceans and shelf sea physics, planktonic and higher trophic level ecosystems, and look towards building an integrative approach with these existing tools. We note how the different approaches have evolved historically and that many of the previous obstacles to harmonisation may no longer be present. We illustrate this with examples from the on-going and planned modelling effort in the Integrative Modelling Work Package of the EURO-BASIN programme.

Sensitivity of productivity and respiration to water availability determines the net ecosystem exchange of carbon terrestrial ecosystems of the United States

NASA Astrophysics Data System (ADS)

Liu, Z.; Ballantyne, A.; Poulter, B.; Anderegg, W.; Jacobson, A. R.; Miller, J. B.

2017-12-01

Interannual variability (IAV) of atmospheric CO2 is primarily driven by fluctuations in net carbon exchange (NEE) by terrestrial ecosystems. Recent analyses suggested that global terrestrial carbon uptake is dominated by the sensitivity of productivity to precipitation in semi-arid ecosystems, or sensitivity of respiration to temperature in tropical ecosystems. There is a need to better understand factors that control the carbon balance of land ecosystems across spatial and temporal scales. Here we used multiple observational dataset to assess: (1) What are the dominant processes controlling the IAV of NEE in terrestrial ecosystem? What are the climatic controls on the variability gross primary productivity (GPP) and total ecosystem respiration (TER) in the contiguous United States (CONUS). Our analysis revealed that there is a strong positive correlation between IAV of GPP and IAV of NEE in drier (mean annual precipitation: MAP < 750mm) western ecosystem, while there is no correlation between IAV of GPP and IAV of NEE in moist (MAP > 750mm) eastern ecosystem using observational dataset. Both βspatial and βtemporal of GPP and TER to precipitation exhibit an emergent threshold where GPP is more sensitive than TER to precipitation in semi-arid western ecosystems and TER is more sensitive than GPP to precipitation in more humid eastern ecosystems. This emergent ecosystem threshold was evident in several independent observations. However, analyses from 10 TRENDY models indicate current Dynamic Global Vegetation Models (DGVMs) tend to overestimate the sensitivity of NEE to GPP and underestimate the sensitivity of NEE to TER to precipitation across CONUS ecosystems. TER experiments showed that commonly used TER models failed to capture the IAV of TER in the moist region in CONUS. This is because heterotrophic respiration (Rh) was relatively independent of GPP in moist regions of CONUS, but was too tightly coupled to GPP in the DGVMs. The emergent thresholds at the ecosystem and continental scale may help reconcile model simulations and observations of terrestrial carbon processes.

Simulated effects of reduced sulfur, nitrogen, and base cation deposition on soils and solutions in Southern Appalachian forests

Treesearch

D.W. Johnson; R.B. Susfalk; P.F. Brewer; W.T. Swank

1999-01-01

Effects of reduced deposition of N, S, and CB on nutrient pools, fluxes, soil, and soil solution chemistry were simulated for two Appalachian forest ecosystems using the nutrient cycling model. In the extremely acidic, N- and S-saturated red spruce (Picea rubens (Sarg.)) forest (Nolan Divide), reducing

Climate change effects on historical range and variability of two large landscapes in western Montana, USA

Treesearch

Robert E. Keane; Lisa M. Holsinger; Russell A. Parsons; Kathy Gray

2008-01-01

Quantifying the historical range and variability of landscape composition and structure using simulation modeling is becoming an important means of assessing current landscape condition and prioritizing landscapes for ecosystem restoration. However, most simulated time series are generated using static climate conditions which fail to account for the predicted major...

Representing winter wheat in the Community Land Model (version 4.5)

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

Lu, Yaqiong; Williams, Ian N.; Bagley, Justin E.

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land–atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange ofmore » CO 2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.« less

Representing winter wheat in the Community Land Model (version 4.5)

NASA Astrophysics Data System (ADS)

Lu, Yaqiong; Williams, Ian N.; Bagley, Justin E.; Torn, Margaret S.; Kueppers, Lara M.

2017-05-01

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land-atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange of CO2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.

Representing winter wheat in the Community Land Model (version 4.5)

DOE PAGES

Lu, Yaqiong; Williams, Ian N.; Bagley, Justin E.; ...

2017-05-05

Winter wheat is a staple crop for global food security, and is the dominant vegetation cover for a significant fraction of Earth's croplands. As such, it plays an important role in carbon cycling and land–atmosphere interactions in these key regions. Accurate simulation of winter wheat growth is not only crucial for future yield prediction under a changing climate, but also for accurately predicting the energy and water cycles for winter wheat dominated regions. We modified the winter wheat model in the Community Land Model (CLM) to better simulate winter wheat leaf area index, latent heat flux, net ecosystem exchange ofmore » CO 2, and grain yield. These included schemes to represent vernalization as well as frost tolerance and damage. We calibrated three key parameters (minimum planting temperature, maximum crop growth days, and initial value of leaf carbon allocation coefficient) and modified the grain carbon allocation algorithm for simulations at the US Southern Great Plains ARM site (US-ARM), and validated the model performance at eight additional sites across North America. We found that the new winter wheat model improved the prediction of monthly variation in leaf area index, reduced latent heat flux, and net ecosystem exchange root mean square error (RMSE) by 41 and 35 % during the spring growing season. The model accurately simulated the interannual variation in yield at the US-ARM site, but underestimated yield at sites and in regions (northwestern and southeastern US) with historically greater yields by 35 %.« less

Modelling wetland-groundwater interactions in the boreal Kälväsvaara esker, Northern Finland

NASA Astrophysics Data System (ADS)

Jaros, Anna; Rossi, Pekka; Ronkanen, Anna-Kaisa; Kløve, Bjørn

2016-04-01

Many types of boreal peatland ecosystems such as alkaline fens, aapa mires and Fennoscandia spring fens rely on the presence of groundwater. In these ecosystems groundwater creates unique conditions for flora and fauna by providing water, nutrients and constant water temperature enriching local biodiversity. The groundwater-peatland interactions and their dynamics are not, however, in many cases fully understood and their measurement and quantification is difficult due to highly heterogeneous structure of peatlands and large spatial extend of these ecosystems. Understanding of these interactions and their changes due to anthropogenic impact on groundwater resources would benefit the protection of the groundwater dependent peatlands. The groundwater-peatland interactions were investigated using the fully-integrated physically-based groundwater-surface water code HydroGeoSphere in a case study of the Kälväsvaara esker aquifer, Northern Finland. The Kälväsvaara is a geologically complex esker and it is surrounded by vast aapa mire system including alkaline and springs fens. In addition, numerous small springs occur in the discharge zone of the esker. In order to quantify groundwater-peatland interactions a simple steady-state model was built and results were evaluated using expected trends and field measurements. The employed model reproduced relatively well spatially distributed hydrological variables such as soil water content, water depths and groundwater-surface water exchange fluxes within the wetland and esker areas. The wetlands emerged in simulations as a result of geological and topographical conditions. They could be identified by high saturation levels at ground surface and by presence of shallow ponded water over some areas. The model outputs exhibited also strong surface water-groundwater interactions in some parts of the aapa system. These areas were noted to be regions of substantial diffusive groundwater discharge by the earlier studies. In contrast, the simulations were not able to capture small scale point groundwater discharge i.e. springs. This reflects that modelling small scale groundwater input to wetland ecosystems can be challenging without detailed information on the aquifer and wetland geology. Overall, the good consistency between simulations and observations demonstrated that wetland-groundwater interactions can be studied using fully-integrated physically-based groundwater-surface water models.

Development of a Systematic Stakeholder Identification System for 3VS Modeling in the Snohomish Basin, Washington, USA

EPA Science Inventory

In the Environmental Protection Agency’s Triple Value Simulation (3VS) models, social, economic and environmental indicators are utilized to understand the interrelated impacts of programs and regulations on ecosystems and human communities. Critical to identifying the app...

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska.

PubMed

Genet, Hélène; He, Yujie; Lyu, Zhou; McGuire, A David; Zhuang, Qianlai; Clein, Joy; D'Amore, David; Bennett, Alec; Breen, Amy; Biles, Frances; Euskirchen, Eugénie S; Johnson, Kristofer; Kurkowski, Tom; Kushch Schroder, Svetlana; Pastick, Neal; Rupp, T Scott; Wylie, Bruce; Zhang, Yujin; Zhou, Xiaoping; Zhu, Zhiliang

2018-01-01

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km 2 ), are influencing and will influence state-wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO 2 ), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950-2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (-6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010-2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO 2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO 2 , we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO 2 increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO 2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO 2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional. © 2017 by the Ecological Society of America.

The role of driving factors in historical and projected carbon dynamics of upland ecosystems in Alaska

USGS Publications Warehouse

Genet, Hélène; He, Yujie; Lyu, Zhou; McGuire, A. David; Zhuang, Qianlai; Clein, Joy S.; D'Amore, David; Bennett, Alec; Breen, Amy; Biles, Frances; Euskirchen, Eugénie S.; Johnson, Kristofer; Kurkowski, Tom; Schroder, Svetlana (Kushch); Pastick, Neal J.; Rupp, T. Scott; Wylie, Bruce K.; Zhang, Yujin; Zhou, Xiaoping; Zhu, Zhiliang

2018-01-01

It is important to understand how upland ecosystems of Alaska, which are estimated to occupy 84% of the state (i.e., 1,237,774 km2), are influencing and will influence state‐wide carbon (C) dynamics in the face of ongoing climate change. We coupled fire disturbance and biogeochemical models to assess the relative effects of changing atmospheric carbon dioxide (CO2), climate, logging and fire regimes on the historical and future C balance of upland ecosystems for the four main Landscape Conservation Cooperatives (LCCs) of Alaska. At the end of the historical period (1950–2009) of our analysis, we estimate that upland ecosystems of Alaska store ~50 Pg C (with ~90% of the C in soils), and gained 3.26 Tg C/yr. Three of the LCCs had gains in total ecosystem C storage, while the Northwest Boreal LCC lost C (−6.01 Tg C/yr) because of increases in fire activity. Carbon exports from logging affected only the North Pacific LCC and represented less than 1% of the state's net primary production (NPP). The analysis for the future time period (2010–2099) consisted of six simulations driven by climate outputs from two climate models for three emission scenarios. Across the climate scenarios, total ecosystem C storage increased between 19.5 and 66.3 Tg C/yr, which represents 3.4% to 11.7% increase in Alaska upland's storage. We conducted additional simulations to attribute these responses to environmental changes. This analysis showed that atmospheric CO2 fertilization was the main driver of ecosystem C balance. By comparing future simulations with constant and with increasing atmospheric CO2, we estimated that the sensitivity of NPP was 4.8% per 100 ppmv, but NPP becomes less sensitive to CO2increase throughout the 21st century. Overall, our analyses suggest that the decreasing CO2 sensitivity of NPP and the increasing sensitivity of heterotrophic respiration to air temperature, in addition to the increase in C loss from wildfires weakens the C sink from upland ecosystems of Alaska and will ultimately lead to a source of CO2 to the atmosphere beyond 2100. Therefore, we conclude that the increasing regional C sink we estimate for the 21st century will most likely be transitional.

Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change

PubMed Central

Lawrence, David M.; Koven, Charles; Clein, Joy S.; Burke, Eleanor; Chen, Guangsheng; Jafarov, Elchin; MacDougall, Andrew H.; Marchenko, Sergey; Nicolsky, Dmitry; Peng, Shushi; Rinke, Annette; Ciais, Philippe; Gouttevin, Isabelle; Krinner, Gerhard; Moore, John C.; Romanovsky, Vladimir; Schädel, Christina; Schaefer, Kevin; Zhuang, Qianlai

2018-01-01

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback. PMID:29581283

Soil type and texture impacts on soil organic carbon accumulation in a sub-tropical agro-ecosystem

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

Gonçalves, Daniel Ruiz Potma; Sa, Joao Carlos de Moraes; Mishra, Umakant

Soil organic carbon (C) plays a fundamental role in tropical and subtropical soil fertility, agronomic productivity, and soil health. As a tool for understand ecosystems dynamics, mathematical models such as Century have been used to assess soil's capacity to store C in different environments. However, as Century was initially developed for temperate ecosystems, several authors have hypothesized that C storage may be underestimated by Century in Oxisols. We tested the hypothesis that Century model can be parameterized for tropical soils and used to reliably estimate soil organic carbon (SOC) storage. The aim of this study was to investigate SOC storagemore » under two soil types and three textural classes and quantify the sources and magnitude of uncertainty using the Century model. The simulation for SOC storage was efficient and the mean residue was 10 Mg C ha -1 (13%) for n = 91. However, a different simulation bias was observed for soil with <600 g kg -1 of clay was 16.3 Mg C ha -1 (18%) for n = 30, and at >600 g kg -1 of clay, was 4 Mg C ha -1 (5%) for n = 50, respectively. The results suggest a non-linear effect of clay and silt contents on C storage in Oxisols. All types of soil contain nearly 70% of Fe and Al oxides in the clay fraction and a regression analysis showed an increase in model bias with increase in oxides content. Consequently, inclusion of mineralogical control of SOC stabilization by Fe and Al (hydro) oxides may improve results of Century model simulations in soils with high oxides contents« less

Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change

DOE PAGES

McGuire, A. David; Lawrence, David M.; Koven, Charles; ...

2018-03-26

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km 2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbonmore » varied between 66-Pg C (10 15-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. In conclusion, this assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.« less

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)

Evaluating the Impact of Land Use Change on Submerged Aquatic Vegetation Stressors in Mobile Bay

NASA Technical Reports Server (NTRS)

Al-Hamdan, Mohammad; Estes, Maurice G., Jr.; Quattrochi, Dale; Thom, Ronald; Woodruff, Dana; Judd, Chaeli; Ellis, Jean; Watson, Brian; Rodriquez, Hugo; Johnson, Hoyt

2009-01-01

Alabama coastal systems have been subjected to increasing pressure from a variety of activities including urban and rural development, shoreline modifications, industrial activities, and dredging of shipping and navigation channels. The impacts on coastal ecosystems are often observed through the use of indicator species. One such indicator species for aquatic ecosystem health is submerged aquatic vegetation (SAV). Watershed and hydrodynamic modeling has been performed to evaluate the impact of land use change in Mobile and Baldwin counties on SAV stressors and controlling factors (temperature, salinity, and sediment) in Mobile Bay. Watershed modeling using the Loading Simulation Package in C++ (LSPC) was performed for all watersheds contiguous to Mobile Bay for land use scenarios in 1948, 1992, 2001, and 2030. Landsat-derived National Land Cover Data (NLCD) were used in the 1992 and 2001 simulations after having been reclassified to a common classification scheme. The Prescott Spatial Growth Model was used to project the 2030 land use scenario based on current trends. The LSPC model simulations provided output on changes in flow, temperature, and sediment for 22 discharge points into the Bay. Theses results were inputted in the Environmental Fluid Dynamics Computer Code (EFDC) hydrodynamic model to generate data on changes in temperature, salinity, and sediment on a grid with four vertical profiles throughout Mobile Bay. The changes in the aquatic ecosystem were used to perform an ecological analysis to evaluate the impact on SAV habitat suitability. This is the key product benefiting the Mobile Bay coastal environmental managers that integrates the influences of temperature, salinity, and sediment due to land use driven flow changes with the restoration potential of SAVs.

Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change

USGS Publications Warehouse

McGuire, A. David; Lawrence, David M.; Koven, Charles; Clein, Joy S.; Burke, Eleanor J.; Chen, Guangsheng; Jafarov, Elchin; MacDougall, Andrew H.; Marchenko, Sergey S.; Nicolsky, Dmitry J.; Peng, Shushi; Rinke, Annette; Ciais, Philippe; Gouttevin, Isabelle; Hayes, Daniel J.; Ji, Duoying; Krinner, Gerhard; Moore, John C.; Romanovsky, Vladimir; Schadel, Christina; Schaefer, Kevin; Schuur, Edward A.G.; Zhuang, Qianlai

2018-01-01

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (1015-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.

Tropical Carbon Response to Seasonal Phasing and Intensity of Precipitation in CMIP5 Earth System Models

NASA Astrophysics Data System (ADS)

Basile, S.; Keppel-Aleks, G.

2016-12-01

Carbon cycling and water fluxes are connected over land. Understanding the current sensitivity of tropical ecosystems to climate drivers, such as precipitation, at short timescales is important for projecting future trends in the land sink of anthropogenic CO2. Several recent studies have shown that interannual droughts in 2005 and 2010 reduced net carbon uptake in the Amazon rainforest. In 2011 Southern Hemisphere semi-arid regions, especially Australian ecosystems, were found to largely contribute to the above average increase in the land carbon sink following consecutive wet seasons under La Nina conditions. Earth system models (ESMs) are able to simulate these sensitivities with varying degrees of fidelity, and ESMs also show a wide range of changes in precipitation phasing and intensity by 2100. Unsurprisingly, model projections of the land carbon sink also vary widely, with some simulations showing land becoming a CO2 source to the atmosphere. To constrain projections of the tropical land carbon balance among an ensemble of ESMs, we analyzed seasonal and interannual precipitation-carbon relationships in Coupled Model Intercomparison Project Phase 5 (CMIP5) ESMs for the period from 1982-2006. The sensitivity of net biospheric production on land (NBP) to precipitation was quantified on seasonal and annual timescales, and NBP was spatially correlated to precipitation across tropical and subtropical regions (+/- 30 degrees) within humid and semi-arid ecosystems. This analysis was expanded to soil moisture and drought metrics were used to distinguish between wet and dry seasons. Large scale precipitation was used to resolve Intertropical Convergence Zone (ITCZ) movement and convective precipitation was used to diagnose the short-term NBP response within the wet season. Results revealed a spread in NBP sensitivity to precipitation intensity as well as how individual models simulated precipitation phasing across different tropical regions.

Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change.

PubMed

McGuire, A David; Lawrence, David M; Koven, Charles; Clein, Joy S; Burke, Eleanor; Chen, Guangsheng; Jafarov, Elchin; MacDougall, Andrew H; Marchenko, Sergey; Nicolsky, Dmitry; Peng, Shushi; Rinke, Annette; Ciais, Philippe; Gouttevin, Isabelle; Hayes, Daniel J; Ji, Duoying; Krinner, Gerhard; Moore, John C; Romanovsky, Vladimir; Schädel, Christina; Schaefer, Kevin; Schuur, Edward A G; Zhuang, Qianlai

2018-04-10

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon-climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km 2 for the RCP4.5 climate and between 6 and 16 million km 2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbon varied between 66-Pg C (10 15 -g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. This assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon-climate feedback. Copyright © 2018 the Author(s). Published by PNAS.

Year-round simulated methane emissions from a permafrost ecosystem in Northeast Siberia

NASA Astrophysics Data System (ADS)

Castro-Morales, Karel; Kleinen, Thomas; Kaiser, Sonja; Zaehle, Sönke; Kittler, Fanny; Kwon, Min Jung; Beer, Christian; Göckede, Mathias

2018-05-01

Wetlands of northern high latitudes are ecosystems highly vulnerable to climate change. Some degradation effects include soil hydrologic changes due to permafrost thaw, formation of deeper active layers, and rising topsoil temperatures that accelerate the degradation of permafrost carbon and increase in CO2 and CH4 emissions. In this work we present 2 years of modeled year-round CH4 emissions into the atmosphere from a Northeast Siberian region in the Russian Far East. We use a revisited version of the process-based JSBACH-methane model that includes four CH4 transport pathways: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. The gas is emitted through wetlands represented by grid cell inundated areas simulated with a TOPMODEL approach. The magnitude of the summertime modeled CH4 emissions is comparable to ground-based CH4 fluxes measured with the eddy covariance technique and flux chambers in the same area of study, whereas wintertime modeled values are underestimated by 1 order of magnitude. In an annual balance, the most important mechanism for transport of methane into the atmosphere is through plants (61 %). This is followed by ebullition ( ˜ 35 %), while summertime molecular diffusion is negligible (0.02 %) compared to the diffusion through the snow during winter ( ˜ 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model will facilitate a more process-oriented land surface scheme and better simulate CH4 emissions under climate change. This is especially necessary at regional scales in Arctic ecosystems influenced by permafrost thaw.

Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change

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

McGuire, A. David; Lawrence, David M.; Koven, Charles

We conducted a model-based assessment of changes in permafrost area and carbon storage for simulations driven by RCP4.5 and RCP8.5 projections between 2010 and 2299 for the northern permafrost region. All models simulating carbon represented soil with depth, a critical structural feature needed to represent the permafrost carbon–climate feedback, but that is not a universal feature of all climate models. Between 2010 and 2299, simulations indicated losses of permafrost between 3 and 5 million km2 for the RCP4.5 climate and between 6 and 16 million km 2 for the RCP8.5 climate. For the RCP4.5 projection, cumulative change in soil carbonmore » varied between 66-Pg C (10 15-g carbon) loss to 70-Pg C gain. For the RCP8.5 projection, losses in soil carbon varied between 74 and 652 Pg C (mean loss, 341 Pg C). For the RCP4.5 projection, gains in vegetation carbon were largely responsible for the overall projected net gains in ecosystem carbon by 2299 (8- to 244-Pg C gains). In contrast, for the RCP8.5 projection, gains in vegetation carbon were not great enough to compensate for the losses of carbon projected by four of the five models; changes in ecosystem carbon ranged from a 641-Pg C loss to a 167-Pg C gain (mean, 208-Pg C loss). The models indicate that substantial net losses of ecosystem carbon would not occur until after 2100. In conclusion, this assessment suggests that effective mitigation efforts during the remainder of this century could attenuate the negative consequences of the permafrost carbon–climate feedback.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

DOE PAGES

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.; ...

2016-10-20

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

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

Sippel, Sebastian; Lange, Holger; Mahecha, Miguel D.

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observedmore » and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. Here we demonstrate that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics.« less

Diagnosing the Dynamics of Observed and Simulated Ecosystem Gross Primary Productivity with Time Causal Information Theory Quantifiers

PubMed Central

Sippel, Sebastian; Mahecha, Miguel D.; Hauhs, Michael; Bodesheim, Paul; Kaminski, Thomas; Gans, Fabian; Rosso, Osvaldo A.

2016-01-01

Data analysis and model-data comparisons in the environmental sciences require diagnostic measures that quantify time series dynamics and structure, and are robust to noise in observational data. This paper investigates the temporal dynamics of environmental time series using measures quantifying their information content and complexity. The measures are used to classify natural processes on one hand, and to compare models with observations on the other. The present analysis focuses on the global carbon cycle as an area of research in which model-data integration and comparisons are key to improving our understanding of natural phenomena. We investigate the dynamics of observed and simulated time series of Gross Primary Productivity (GPP), a key variable in terrestrial ecosystems that quantifies ecosystem carbon uptake. However, the dynamics, patterns and magnitudes of GPP time series, both observed and simulated, vary substantially on different temporal and spatial scales. We demonstrate here that information content and complexity, or Information Theory Quantifiers (ITQ) for short, serve as robust and efficient data-analytical and model benchmarking tools for evaluating the temporal structure and dynamical properties of simulated or observed time series at various spatial scales. At continental scale, we compare GPP time series simulated with two models and an observations-based product. This analysis reveals qualitative differences between model evaluation based on ITQ compared to traditional model performance metrics, indicating that good model performance in terms of absolute or relative error does not imply that the dynamics of the observations is captured well. Furthermore, we show, using an ensemble of site-scale measurements obtained from the FLUXNET archive in the Mediterranean, that model-data or model-model mismatches as indicated by ITQ can be attributed to and interpreted as differences in the temporal structure of the respective ecological time series. At global scale, our understanding of C fluxes relies on the use of consistently applied land models. Here, we use ITQ to evaluate model structure: The measures are largely insensitive to climatic scenarios, land use and atmospheric gas concentrations used to drive them, but clearly separate the structure of 13 different land models taken from the CMIP5 archive and an observations-based product. In conclusion, diagnostic measures of this kind provide data-analytical tools that distinguish different types of natural processes based solely on their dynamics, and are thus highly suitable for environmental science applications such as model structural diagnostics. PMID:27764187

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; Wullschleger, Stan D.; Thornton, Peter E.; Riley, William J.; Song, Xia; Graham, David E.; Song, Changchun; Tian, Hanqin

2016-06-01

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

Role of carbon and climate in forming the Páramo, an Andean evolutionary hotspot

NASA Astrophysics Data System (ADS)

Hill, Daniel

2015-04-01

According to a number of genetic diversification measures the Páramo grasslands of the high equatorial Andes show the greatest rates of speciation on the planet. This is probably driven by contrasting ranges of the ecosystem between glacial and interglacial periods of the Pleistocene. During the warm interglacial periods the treeline is high in the Andes restricting the Páramos to the highest regions of the Andean mountain chain, while in the cool glacial periods the Páramo areas expand and probably coalesce, bringing isolated populations into contact with each other. The origin of the Páramo ecosystem is placed close to the end of the Pliocene and has been related to the finale of regional Andean mountain building. However, this formation date is also coincident with the global cooling at the end of the Pliocene, as Northern Hemisphere glaciation and the bipolar Pleistocene ice ages begin. Furthermore, it is estimated that atmospheric CO2 concentrations dropped from the 400 ppmv typical of the Pliocene to values more typical of the Pleistocene at around this time. Global climate model simulations, coupled with a high resolution biome model, give us the opportunity to test these competing hypotheses for the formation of the Páramo ecosystem. A series of HadCM3 climate model simulations are presented here varying the height of the highest altitude Andes and the global climate from its pre-industrial state to the Pliocene. The climate are topographic changes are varied both independently and together. These climatologies are then used to drive a high-resolution biome model, BIOME4, and simulate the impact on Andean vegetation. These models seem to reproduce the observed changes in high altitude grassland biomes during the Pliocene. The climate and biome modelling presented here show that the climate changes associated with the Plio-Pleistocene boundary are the primary cause of the initial formation of this unique and important ecosystem. Although the reduction of the highest altitude Andean regions reduces the available area for grassland biomes, the effect is significantly smaller than the impact of Plio-Pleistocene climate change. By individually introducing the Pliocene changes (atmospheric carbon dioxide levels, mean temperature, minimum temperatures, precipitation and direct sunlight) to the BIOME4 simulations, it is shown that the primary driver of these changes is atmospheric carbon dioxide levels. The higher Pliocene levels favour the expansion of the forest biomes, increasing the altitude of the treeline and replacing grassland biomes. This suggests that in such areas prediction of future changes and plans to preserve these important ecosystems must consider the impact of both climate change and CO2 fertilization.

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

NASA Astrophysics Data System (ADS)

Wu, M.; Smith, B.; Samuelsson, P.; Rummukainen, M.; Schurgers, G.

2012-12-01

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 feed back 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 feed back 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. Our study, the first application of a coupled Earth system model at regional scale and resolution over Africa, reveals that 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.

Detecting Emergence of Acidification and Warming as Stressors for Coral Reef Regions using Earth System Models

NASA Astrophysics Data System (ADS)

Menendez, A. T.

2015-12-01

Coral reef ecosystems rely on complex interactions between biological, biogeochemical, and physical processes to ensure their survival and resilience. However, both human interaction and anthropogenic climate change have negatively impacted the prosperity of these regions, resulting in a crucial need to understand and predict the future of important biogeochemical and physical stressors. Contemporary changes to these relationships and environmental conditions in coral reef ecosystems are a mixture of anthropogenic contributions and natural variability (e.g. ENSO) of the climate system. To better quantify the uncertainty in future projections, it is exceedingly necessary to differentiate between these two contributors. In this study we look at acidification and warming stressors in the Galapagos, Coral Triangle, and Hawaiian islands regions. We use a suite of hindcast simulations (a 30-member large initial condition ensemble) done with an Earth Systems Model (GFDL-ESM2M) in order quantify the degree to which natural variability alters the emergence time-scales of anthropogenically-induced changes to ecosystem drivers such as pH, ΩArag, and SST. A comparison of output from a suit of CMIP5 models will be used to evaluate model uncertainty for the same regions. Simulated trends and variability in these ecosystem drivers were then compared to observed trends over the three Pacific regions. Evidently the models and observed trends proved invaluable for testing the hypothesis addressing the presence of a temporal hierarchy between emergence, defined by a signal-to-noise ratio, of acidification stressors and temperature as a stressor. Furthermore, challenges in deconvolving anthropogenic and natural contributions to stressor trends will be discussed for each of the three sites.

Importance of soil thermal regime in terrestrial ecosystem carbon dynamics in the circumpolar north

NASA Astrophysics Data System (ADS)

Jiang, Yueyang; Zhuang, Qianlai; Sitch, Stephen; O'Donnell, Jonathan A.; Kicklighter, David; Sokolov, Andrei; Melillo, Jerry

2016-07-01

In the circumpolar north (45-90°N), permafrost plays an important role in vegetation and carbon (C) dynamics. Permafrost thawing has been accelerated by the warming climate and exerts a positive feedback to climate through increasing soil C release to the atmosphere. To evaluate the influence of permafrost on C dynamics, changes in soil temperature profiles should be considered in global C models. This study incorporates a sophisticated soil thermal model (STM) into a dynamic global vegetation model (LPJ-DGVM) to improve simulations of changes in soil temperature profiles from the ground surface to 3 m depth, and its impacts on C pools and fluxes during the 20th and 21st centuries. With cooler simulated soil temperatures during the summer, LPJ-STM estimates 0.4 Pg C yr- 1 lower present-day heterotrophic respiration but 0.5 Pg C yr- 1 higher net primary production than the original LPJ model resulting in an additional 0.8 to 1.0 Pg C yr- 1 being sequestered in circumpolar ecosystems. Under a suite of projected warming scenarios, we show that the increasing active layer thickness results in the mobilization of permafrost C, which contributes to a more rapid increase in heterotrophic respiration in LPJ-STM compared to the stand-alone LPJ model. Except under the extreme warming conditions, increases in plant production due to warming and rising CO2, overwhelm the e nhanced ecosystem respiration so that both boreal forest and arctic tundra ecosystems remain a net C sink over the 21st century. This study highlights the importance of considering changes in the soil thermal regime when quantifying the C budget in the circumpolar north.

Simulating fire-induced ecological succession with the dynamically coupled fire-vegetation model, ED-SPIFTIRE

NASA Astrophysics Data System (ADS)

Spessa, A.; Fisher, R.

2009-04-01

The simulation of fire-vegetation feedbacks is crucial for determining fire-induced changes to ecosystem structure and function, and emissions of trace gases and aerosols under future climate change. A new global fire model SPITFIRE (SPread and InTensity of FIRE) has been designed to overcome many of the limitations in existing fire models set within DGVM frameworks (Thonicke et al. 2008). SPITFIRE has been applied in coupled mode globally (Thonicke et al. 2008) and northern Australia (Spessa et al. unpubl.) as part of the LPJ DGVM. It has also been driven with MODIS burnt area data applied to sub-Saharan Africa (Lehsten et al. 2008) as part of the LPJ-GUESS vegetation model (Smith et al. 2001). Recently, Spessa & Fisher (unpubl.) completed the coupling of SPIFTIRE to the Ecosystem Demography (ED) model (Moorecroft et al. 2001), which has been globalised by Dr R. Fisher as part of the development of the new land surface scheme JULES (Joint UK Environment Simulator) within the QUEST Earth System Model (http://www.quest-esm.ac.uk/). In contrast to the LPJ DGVM, ED is a ‘size and age structured' approximation of an individual based gap model. The major innovation of the ED-SPITFIRE model compared with LPJ-SPITFIRE is the categorisation of each climatic grid cell into a series of non-spatially contiguous patches which are defined by a common ‘age since last disturbance'. In theory, the age-class structure of ED facilitates ecologically realistic processes of succession and re-growth to be represented. By contrast, LPJ DGVM adopts an ‘area-based approach' that implicitly averages individual and patch differences across a wider area and across ‘populations' of PFTs. This presentation provides an overview of SPITFIRE, and provides preliminary results from ED-SPITFIRE applied to northern Australian savanna ecosystems which, due to spatio-temporal variation in fire disturbance, comprise a patchwork of grasses and trees at different stages of post-fire succession. Comparisons with similar simulations undertaken with LPJ-SPITFIRE are also presented.

Decomposition by ectomycorrhizal fungi alters soil carbon storage in a simulation model

DOE PAGES

Moore, J. A. M.; Jiang, J.; Post, W. M.; ...

2015-03-06

Carbon cycle models often lack explicit belowground organism activity, yet belowground organisms regulate carbon storage and release in soil. Ectomycorrhizal fungi are important players in the carbon cycle because they are a conduit into soil for carbon assimilated by the plant. It is hypothesized that ectomycorrhizal fungi can also be active decomposers when plant carbon allocation to fungi is low. Here, we reviewed the literature on ectomycorrhizal decomposition and we developed a simulation model of the plant-mycorrhizae interaction where a reduction in plant productivity stimulates ectomycorrhizal fungi to decompose soil organic matter. Our review highlights evidence demonstrating the potential formore » ectomycorrhizal fungi to decompose soil organic matter. Our model output suggests that ectomycorrhizal activity accounts for a portion of carbon decomposed in soil, but this portion varied with plant productivity and the mycorrhizal carbon uptake strategy simulated. Lower organic matter inputs to soil were largely responsible for reduced soil carbon storage. Using mathematical theory, we demonstrated that biotic interactions affect predictions of ecosystem functions. Specifically, we developed a simple function to model the mycorrhizal switch in function from plant symbiont to decomposer. In conclusion, we show that including mycorrhizal fungi with the flexibility of mutualistic and saprotrophic lifestyles alters predictions of ecosystem function.« less

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

[Global climate change and carbon balance in forest ecosystems of boreal zones: imitating modeling as a forecast tool].

PubMed

Shanin, V N; Mikhaĭlov, A V; Bykhovets, S S; Komarov, A S

2010-01-01

The individually oriented system of the EFIMOD models simulating carbon and nitrogen flows in forest ecosystems has been used for forecasting the response of forest ecosystems to various forest exploitation regimes with climate change. As input data the forest management materials for the Manturovskii forestry of the Kostroma region were used. It has been shown that increase of mid-annual temperatures and rainfall influence the redistribution of carbon and nitrogen supply in organic form: supply increase of these elements in phytomass simultaneously with depletion of them in soil occurred. The most carbon and nitrogen accumulation in forest ecosystems occurs in the scenario without felling. In addition, in this scenario only the ecosystems of the modeling territory function as a carbon drain; in the other two scenarios (with selective and total felling) they function as a source of carbon. Climate changes greatly influence the decomposition rate of organic matter in soil, which leads to increased emission of carbonic acid. The second consequence of the increase in the destruction rate is nitrogen increase in the soil in a form available for plants that entails production increase of plantations.

Carbon Cycle Model Linkage Project (CCMLP): Evaluating Biogeochemical Process Models with Atmospheric Measurements and Field Experiments

NASA Astrophysics Data System (ADS)

Heimann, M.; Prentice, I. C.; Foley, J.; Hickler, T.; Kicklighter, D. W.; McGuire, A. D.; Melillo, J. M.; Ramankutty, N.; Sitch, S.

2001-12-01

Models of biophysical and biogeochemical proceses are being used -either offline or in coupled climate-carbon cycle (C4) models-to assess climate- and CO2-induced feedbacks on atmospheric CO2. Observations of atmospheric CO2 concentration, and supplementary tracers including O2 concentrations and isotopes, offer unique opportunities to evaluate the large-scale behaviour of models. Global patterns, temporal trends, and interannual variability of the atmospheric CO2 concentration and its seasonal cycle provide crucial benchmarks for simulations of regionally-integrated net ecosystem exchange; flux measurements by eddy correlation allow a far more demanding model test at the ecosystem scale than conventional indicators, such as measurements of annual net primary production; and large-scale manipulations, such as the Duke Forest Free Air Carbon Enrichment (FACE) experiment, give a standard to evaluate modelled phenomena such as ecosystem-level CO2 fertilization. Model runs including historical changes of CO2, climate and land use allow comparison with regional-scale monthly CO2 balances as inferred from atmospheric measurements. Such comparisons are providing grounds for some confidence in current models, while pointing to processes that may still be inadequately treated. Current plans focus on (1) continued benchmarking of land process models against flux measurements across ecosystems and experimental findings on the ecosystem-level effects of enhanced CO2, reactive N inputs and temperature; (2) improved representation of land use, forest management and crop metabolism in models; and (3) a strategy for the evaluation of C4 models in a historical observational context.

Relationships between net primary productivity and stand age for several forest types and their influence on China's carbon balance.

PubMed

Wang, Shaoqiang; Zhou, Lei; Chen, Jingming; Ju, Weimin; Feng, Xianfeng; Wu, Weixing

2011-06-01

Affected by natural and anthropogenic disturbances such as forest fires, insect-induced mortality and harvesting, forest stand age plays an important role in determining the distribution of carbon pools and fluxes in a variety of forest ecosystems. An improved understanding of the relationship between net primary productivity (NPP) and stand age (i.e., age-related increase and decline in forest productivity) is essential for the simulation and prediction of the global carbon cycle at annual, decadal, centurial, or even longer temporal scales. In this paper, we developed functions describing the relationship between national mean NPP and stand age using stand age information derived from forest inventory data and NPP simulated by the BEPS (Boreal Ecosystem Productivity Simulator) model in 2001. Due to differences in ecobiophysical characteristics of different forest types, NPP-age equations were developed for five typical forest ecosystems in China (deciduous needleleaf forest (DNF), evergreen needleleaf forest in tropic and subtropical zones (ENF-S), deciduous broadleaf forest (DBF), evergreen broadleaf forest (EBF), and mixed broadleaf forest (MBF)). For DNF, ENF-S, EBF, and MBF, changes in NPP with age were well fitted with a common non-linear function, with R(2) values equal to 0.90, 0.75, 0.66, and 0.67, respectively. In contrast, a second order polynomial was best suitable for simulating the change of NPP for DBF, with an R(2) value of 0.79. The timing and magnitude of the maximum NPP varied with forest types. DNF, EBF, and MBF reached the peak NPP at the age of 54, 40, and 32 years, respectively, while the NPP of ENF-S maximizes at the age of 13 years. The highest NPP of DBF appeared at 122 years. NPP was generally lower in older stands with the exception of DBF, and this particular finding runs counter to the paradigm of age-related decline in forest growth. Evaluation based on measurements of NPP and stand age at the plot-level demonstrates the reliability and applicability of the fitted NPP-age relationships. These relationships were used to replace the normalized NPP-age relationship used in the original InTEC (Integrated Terrestrial Ecosystem Carbon) model, to improve the accuracy of estimated carbon balance for China's forest ecosystems. With the revised NPP-age relationship, the InTEC model simulated a larger carbon source from 1950-1980 and a larger carbon sink from 1985-2001 for China's forests than the original InTEC model did because of the modification to the age-related carbon dynamics in forests. This finding confirms the importance of considering the dynamics of NPP related to forest age in estimating regional and global terrestrial carbon budgets. Copyright © 2011 Elsevier Ltd. All rights reserved.

Terrestrial Carbon Sinks in the Brazilian Amazon and Cerrado Region Predicted from MODIS Satellite Data and Ecosystem Modeling

NASA Technical Reports Server (NTRS)

Potter, C.; Klooster, S.; Huete, A.; Genovese, V.; Bustamante, M.; Ferreira, L. Guimaraes; deOliveira, R. C., Jr.; Zepp, R.

2009-01-01

A simulation model based on satellite observations of monthly vegetation cover from the Moderate Resolution Imaging Spectroradiometer (MODIS) was used to estimate monthly carbon fluxes in terrestrial ecosystems of Brazilian Amazon and Cerrado regions over the period 2000-2004. Net ecosystem production (NEP) flux for atmospheric CO2 in the region for these years was estimated. Consistently high carbon sink fluxes in terrestrial ecosystems on a yearly basis were found in the western portions of the states of Acre and Rondonia and the northern portions of the state of Par a. These areas were not significantly impacted by the 2002-2003 El Nino event in terms of net annual carbon gains. Areas of the region that show periodically high carbon source fluxes from terrestrial ecosystems to the atmosphere on yearly basis were found throughout the state of Maranhao and the southern portions of the state of Amazonas. As demonstrated though tower site comparisons, NEP modeled with monthly MODIS Enhanced Vegetation Index (EVI) inputs closely resembles the measured seasonal carbon fluxes at the LBA Tapajos tower site. Modeling results suggest that the capacity for use of MODIS Enhanced Vegetation Index (EVI) data to predict seasonal uptake rates of CO2 in Amazon forests and Cerrado woodlands is strong.

Estimating daily forest carbon fluxes using a combination of ground and remotely sensed data

NASA Astrophysics Data System (ADS)

Chirici, Gherardo; Chiesi, Marta; Corona, Piermaria; Salvati, Riccardo; Papale, Dario; Fibbi, Luca; Sirca, Costantino; Spano, Donatella; Duce, Pierpaolo; Marras, Serena; Matteucci, Giorgio; Cescatti, Alessandro; Maselli, Fabio

2016-02-01

Several studies have demonstrated that Monteith's approach can efficiently predict forest gross primary production (GPP), while the modeling of net ecosystem production (NEP) is more critical, requiring the additional simulation of forest respirations. The NEP of different forest ecosystems in Italy was currently simulated by the use of a remote sensing driven parametric model (modified C-Fix) and a biogeochemical model (BIOME-BGC). The outputs of the two models, which simulate forests in quasi-equilibrium conditions, are combined to estimate the carbon fluxes of actual conditions using information regarding the existing woody biomass. The estimates derived from the methodology have been tested against daily reference GPP and NEP data collected through the eddy correlation technique at five study sites in Italy. The first test concerned the theoretical validity of the simulation approach at both annual and daily time scales and was performed using optimal model drivers (i.e., collected or calibrated over the site measurements). Next, the test was repeated to assess the operational applicability of the methodology, which was driven by spatially extended data sets (i.e., data derived from existing wall-to-wall digital maps). A good estimation accuracy was generally obtained for GPP and NEP when using optimal model drivers. The use of spatially extended data sets worsens the accuracy to a varying degree, which is properly characterized. The model drivers with the most influence on the flux modeling strategy are, in increasing order of importance, forest type, soil features, meteorology, and forest woody biomass (growing stock volume).

Production and export in a global ocean ecosystem model

NASA Astrophysics Data System (ADS)

Palmer, J. R.; Totterdell, I. J.

2001-05-01

The Hadley Centre Ocean Carbon Cycle (HadOCC) model is a coupled physical-biogeochemical model of the ocean carbon cycle. It features an explicit representation of the marine ecosystem, which is assumed to be limited by nitrogen availability. The biogeochemical compartments are dissolved nutrient, total CO 2, total alkalinity, phytoplankton, zooplankton and detritus. The results of the standard simulation are presented. The annual primary production predicted by the model ( 47.7 Gt C yr -1) compares well to the estimates made by Longhurst et al. (1995, J. Plankton Res., 17, 1245) and Antoine et al. (1996, Global Biogeochem. Cycles, 10, 57). The HadOCC model finds high production in the sub-polar North Pacific and North Atlantic Oceans, and around the Antarctic convergence, and low production in the sub-tropical gyres. However in disagreement with the observations of Longhurst et al. and Antoine et al., the model predicts very high production in the eastern equatorial Pacific Ocean. The export flux of carbon in the model agrees well with data from deep-water sediment traps. In order to examine the factors controlling production in the ocean, additional simulations have been run. A nutrient-restoring simulation confirms that the areas with the highest primary production are those with the greatest nutrient supply. A reduced wind-stress experiment demonstrates that the high production found in the equatorial Pacific is driven by excessive upwelling of nutrient-rich water. Three further simulations show that nutrient supply at high latitudes, and hence production there, is sensitive to the parameters and climatological forcings of the mixed layer sub-model.