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.

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.

Gross primary production dynamics assessment of a mediterranean holm oak forest by remote sensing time series analysis

NASA Astrophysics Data System (ADS)

Cicuéndez, Víctor; Huesca, Margarita; Rodriguez-Rastrero, Manuel; Litago, Javier; Recuero, Laura; Merino de Miguel, Silvia; Palacios Orueta, Alicia

2014-05-01

Agroforestry ecosystems have a significant social, economic and environmental impact on the development of many regions of the world. In the Iberian Peninsula the agroforestry oak forest called "Dehesa" or "Montado" is considered as the extreme case of transformation of a Mediterranean forest by the management of human to provide a wide range of natural resources. The high variability of the Mediterranean climate and the different extensive management practices which human realized on the Dehesa result in a high spatial and temporal dynamics of the ecosystem. This leads to a complex pattern in CO2 exchange between the atmosphere and the ecosystem, i.e. in ecosystem's production. Thus, it is essential to assess Dehesa's carbon cycle to reach maximum economic benefits ensuring environmental sustainability. In this sense, the availability of high frequency Remote Sensing (RS) time series allows the assessment of ecosystem evolution at different temporal and spatial scales. Extensive research has been conducted to estimate production from RS data in different ecosystems. However, there are few studies on the Dehesa type ecosystems, probably due to their complexity in terms of spatial arrangement and temporal dynamics. In this study our overall objective is to assess the Gross Primary Production (GPP) dynamics of a Dehesa ecosystem situated in Central Spain by analyzing time series (2004-2008) of two models: (1) GPP provided by Remote Sensing Images of sensor MODIS (MOD17A2 product) and (2) GPP estimated by the implementation of a Site Specific Light Use Efficiency model based as MODIS model on Monteith equation (1972), but taking into account local ecological and meteorological parameters. Both models have been compared with the Production provided by an Eddy Covariance (EC) flux Tower that is located in our study area. In addition, dynamic relationships between models of GPP with Precipitation and Soil Water Content have been investigated by means of cross-correlations and Granger causality tests. Results have indicated that both models of GPP have shown a typical dynamic of the Dehesa in a Mediterranean climate in which there are primarily two layers, the arboreal and the herbaceous strata. However, MODIS underestimates the production of the Dehesa while our Site specific model has given more similar values and dynamics to those from the EC tower. Additionally, the analysis of the dynamic relationships has corroborated the strong dynamic link between GPP and available water for plant growth. In conclusion, we have managed to avoid the main sources of underestimation that has MODIS model with the implementation of a Site specific model. Thus, it seems that the different ecological and meteorological parameters used in MODIS model are the principally responsible for this underestimation. Finally, the Granger causality tests indicate that the prediction of GPP can improve if Precipitation or Soil Water is included in the models. References Monteith, J.L., 1972. Solar Radiation and Productivity in Tropical Ecosystems. J. Appl. Ecol. 9, 747-766.

The spatial dynamics of ecosystem engineers.

PubMed

Franco, Caroline; Fontanari, José F

2017-10-01

The changes on abiotic features of ecosystems have rarely been taken into account by population dynamics models, which typically focus on trophic and competitive interactions between species. However, understanding the population dynamics of organisms that must modify their habitats in order to survive, the so-called ecosystem engineers, requires the explicit incorporation of abiotic interactions in the models. Here we study a model of ecosystem engineers that is discrete both in space and time, and where the engineers and their habitats are arranged in patches fixed to the sites of regular lattices. The growth of the engineer population is modeled by Ricker equation with a density-dependent carrying capacity that is given by the number of modified habitats. A diffusive dispersal stage ensures that a fraction of the engineers move from their birth patches to neighboring patches. We find that dispersal influences the metapopulation dynamics only in the case that the local or single-patch dynamics exhibit chaotic behavior. In that case, it can suppress the chaotic behavior and avoid extinctions in the regime of large intrinsic growth rate of the population. Copyright © 2017 Elsevier Inc. All rights reserved.

Climate-based models for pulsed resources improve predictability of consumer population dynamics: outbreaks of house mice in forest ecosystems.

PubMed

Holland, E Penelope; James, Alex; Ruscoe, Wendy A; Pech, Roger P; Byrom, Andrea E

2015-01-01

Accurate predictions of the timing and magnitude of consumer responses to episodic seeding events (masts) are important for understanding ecosystem dynamics and for managing outbreaks of invasive species generated by masts. While models relating consumer populations to resource fluctuations have been developed successfully for a range of natural and modified ecosystems, a critical gap that needs addressing is better prediction of resource pulses. A recent model used change in summer temperature from one year to the next (ΔT) for predicting masts for forest and grassland plants in New Zealand. We extend this climate-based method in the framework of a model for consumer-resource dynamics to predict invasive house mouse (Mus musculus) outbreaks in forest ecosystems. Compared with previous mast models based on absolute temperature, the ΔT method for predicting masts resulted in an improved model for mouse population dynamics. There was also a threshold effect of ΔT on the likelihood of an outbreak occurring. The improved climate-based method for predicting resource pulses and consumer responses provides a straightforward rule of thumb for determining, with one year's advance warning, whether management intervention might be required in invaded ecosystems. The approach could be applied to consumer-resource systems worldwide where climatic variables are used to model the size and duration of resource pulses, and may have particular relevance for ecosystems where global change scenarios predict increased variability in climatic events.

Dynamical implications of bi-directional resource exchange within a meta-ecosystem.

PubMed

Messan, Marisabel Rodriguez; Kopp, Darin; Allen, Daniel C; Kang, Yun

2018-05-05

The exchange of resources across ecosystem boundaries can have large impacts on ecosystem structures and functions at local and regional scales. In this article, we develop a simple model to investigate dynamical implications of bi-directional resource exchanges between two local ecosystems in a meta-ecosystem framework. In our model, we assume that (1) Each local ecosystem acts as both a resource donor and recipient, such that one ecosystem donating resources to another results in a cost to the donating system and a benefit to the recipient; and (2) The costs and benefits of the bi-directional resource exchange between two ecosystems are correlated in a nonlinear fashion. Our model could apply to the resource interactions between terrestrial and aquatic ecosystems that are supported by the literature. Our theoretical results show that bi-directional resource exchange between two ecosystems can indeed generate complicated dynamical outcomes, including the coupled ecosystems having amensalistic, antagonistic, competitive, or mutualistic interactions, with multiple alternative stable states depending on the relative costs and benefits. In addition, if the relative cost for resource exchange for an ecosystem is decreased or the relative benefit for resource exchange for an ecosystem is increased, the production of that ecosystem would increase; however, depending on the local environment, the production of the other ecosystem may increase or decrease. We expect that our work, by evaluating the potential outcomes of resource exchange theoretically, can facilitate empirical evaluations and advance the understanding of spatial ecosystem ecology where resource exchanges occur in varied ecosystems through a complicated network. Copyright © 2018 Elsevier Inc. All rights reserved.

Meta-ecosystem dynamics and functioning on finite spatial networks

PubMed Central

Marleau, Justin N.; Guichard, Frédéric; Loreau, Michel

2014-01-01

The addition of spatial structure to ecological concepts and theories has spurred integration between sub-disciplines within ecology, including community and ecosystem ecology. However, the complexity of spatial models limits their implementation to idealized, regular landscapes. We present a model meta-ecosystem with finite and irregular spatial structure consisting of local nutrient–autotrophs–herbivores ecosystems connected through spatial flows of materials and organisms. We study the effect of spatial flows on stability and ecosystem functions, and provide simple metrics of connectivity that can predict these effects. Our results show that high rates of nutrient and herbivore movement can destabilize local ecosystem dynamics, leading to spatially heterogeneous equilibria or oscillations across the meta-ecosystem, with generally increased meta-ecosystem primary and secondary production. However, the onset and the spatial scale of these emergent dynamics depend heavily on the spatial structure of the meta-ecosystem and on the relative movement rate of the autotrophs. We show how this strong dependence on finite spatial structure eludes commonly used metrics of connectivity, but can be predicted by the eigenvalues and eigenvectors of the connectivity matrix that describe the spatial structure and scale. Our study indicates the need to consider finite-size ecosystems in meta-ecosystem theory. PMID:24403323

Linkage of a Physically Based Distributed Watershed Model and a Dynamic Plant Growth Model

DTIC Science & Technology

2006-12-01

i.e., Universal Soil Loss Equation ( USLE ) factors, K, C, and P). The K, C, and P factors are empiri- cal coefficients with the same conceptual...with general ecosystem models designed to make long-term projections of ecosystem dynamics. This development effort investigated the linkage of soil ...20 EDYS soil module

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

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.

Multistate modeling of habitat dynamics: Factors affecting Florida scrub transition probabilities

USGS Publications Warehouse

Breininger, D.R.; Nichols, J.D.; Duncan, B.W.; Stolen, Eric D.; Carter, G.M.; Hunt, D.K.; Drese, J.H.

2010-01-01

Many ecosystems are influenced by disturbances that create specific successional states and habitat structures that species need to persist. Estimating transition probabilities between habitat states and modeling the factors that influence such transitions have many applications for investigating and managing disturbance-prone ecosystems. We identify the correspondence between multistate capture-recapture models and Markov models of habitat dynamics. We exploit this correspondence by fitting and comparing competing models of different ecological covariates affecting habitat transition probabilities in Florida scrub and flatwoods, a habitat important to many unique plants and animals. We subdivided a large scrub and flatwoods ecosystem along central Florida's Atlantic coast into 10-ha grid cells, which approximated average territory size of the threatened Florida Scrub-Jay (Aphelocoma coerulescens), a management indicator species. We used 1.0-m resolution aerial imagery for 1994, 1999, and 2004 to classify grid cells into four habitat quality states that were directly related to Florida Scrub-Jay source-sink dynamics and management decision making. Results showed that static site features related to fire propagation (vegetation type, edges) and temporally varying disturbances (fires, mechanical cutting) best explained transition probabilities. Results indicated that much of the scrub and flatwoods ecosystem was resistant to moving from a degraded state to a desired state without mechanical cutting, an expensive restoration tool. We used habitat models parameterized with the estimated transition probabilities to investigate the consequences of alternative management scenarios on future habitat dynamics. We recommend this multistate modeling approach as being broadly applicable for studying ecosystem, land cover, or habitat dynamics. The approach provides maximum-likelihood estimates of transition parameters, including precision measures, and can be used to assess evidence among competing ecological models that describe system dynamics. ?? 2010 by the Ecological Society of America.

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape.

PubMed

Gilpin, William; Feldman, Marcus W

2017-07-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the "edge of chaos" while creating a wide distribution of opportunities for speciation during epochs of disruptive selection-a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies.

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

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.

Modelling carbon responses of tundra ecosystems to historical and projected climate: A comparison of a plot- and a global-scale ecosystem model to identify process-based uncertainties

USGS Publications Warehouse

Clein, Joy S.; Kwiatkowski, B.L.; McGuire, A.D.; Hobbie, J.E.; Rastetter, E.B.; Melillo, J.M.; Kicklighter, D.W.

2000-01-01

We are developing a process-based modelling approach to investigate how carbon (C) storage of tundra across the entire Arctic will respond to projected climate change. To implement the approach, the processes that are least understood, and thus have the most uncertainty, need to be identified and studied. In this paper, we identified a key uncertainty by comparing the responses of C storage in tussock tundra at one site between the simulations of two models - one a global-scale ecosystem model (Terrestrial Ecosystem Model, TEM) and one a plot-scale ecosystem model (General Ecosystem Model, GEM). The simulations spanned the historical period (1921-94) and the projected period (1995-2100). In the historical period, the model simulations of net primary production (NPP) differed in their sensitivity to variability in climate. However, the long-term changes in C storage were similar in both simulations, because the dynamics of heterotrophic respiration (RH) were similar in both models. In contrast, the responses of C storage in the two model simulations diverged during the projected period. In the GEM simulation for this period, increases in RH tracked increases in NPP, whereas in the TEM simulation increases in RH lagged increases in NPP. We were able to make the long-term C dynamics of the two simulations agree by parameterizing TEM to the fast soil C pools of GEM. We concluded that the differences between the long-term C dynamics of the two simulations lay in modelling the role of the recalcitrant soil C. These differences, which reflect an incomplete understanding of soil processes, lead to quite different projections of the response of pan-Arctic C storage to global change. For example, the reference parameterization of TEM resulted in an estimate of cumulative C storage of 2032 g C m-2 for moist tundra north of 50??N, which was substantially higher than the 463 g C m-2 estimated for a parameterization of fast soil C dynamics. This uncertainty in the depiction of the role of recalcitrant soil C in long-term ecosystem C dynamics resulted from our incomplete understanding of controls over C and N transformations in Arctic soils. Mechanistic studies of these issues are needed to improve our ability to model the response of Arctic ecosystems to global change.

Pattern formation--A missing link in the study of ecosystem response to environmental changes.

PubMed

Meron, Ehud

2016-01-01

Environmental changes can affect the functioning of an ecosystem directly, through the response of individual life forms, or indirectly, through interspecific interactions and community dynamics. The feasibility of a community-level response has motivated numerous studies aimed at understanding the mutual relationships between three elements of ecosystem dynamics: the abiotic environment, biodiversity and ecosystem function. Since ecosystems are inherently nonlinear and spatially extended, environmental changes can also induce pattern-forming instabilities that result in spatial self-organization of life forms and resources. This, in turn, can affect the relationships between these three elements, and make the response of ecosystems to environmental changes far more complex. Responses of this kind can be expected in dryland ecosystems, which show a variety of self-organizing vegetation patterns along the rainfall gradient. This paper describes the progress that has been made in understanding vegetation patterning in dryland ecosystems, and the roles it plays in ecosystem response to environmental variability. The progress has been achieved by modeling pattern-forming feedbacks at small spatial scales and up-scaling their effects to large scales through model studies. This approach sets the basis for integrating pattern formation theory into the study of ecosystem dynamics and addressing ecologically significant questions such as the dynamics of desertification, restoration of degraded landscapes, biodiversity changes along environmental gradients, and shrubland-grassland transitions. Copyright © 2015 Elsevier Inc. All rights reserved.

Application of a Lower Food Web Ecosystem Productivity Model to Investigate Population Dynamics of Invasive Species in Lake Michigan

EPA Science Inventory

A Lake Michigan Ecosystem Model (LM-Eco) that includes a detailed description of trophic levels and their interactions was developed for Lake Michigan. The LM-Eco model constitutes a first step toward a comprehensive Lake Michigan ecosystem productivity model to investigate ecosy...

Application of a Lower Food Web Ecosystem Productivity Model for Investigating Dynamics of the Invasive Species Bythortrephes longimanus in Lake Michigan

EPA Science Inventory

A Lake Michigan Ecosystem Model (LM-Eco) that includes a detailed description of trophic levels and their interactions was developed for Lake Michigan. The LM-Eco model constitutes a first step toward a comprehensive Lake Michigan ecosystem productivity model to investigate ecos...

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.

The unseen iceberg: Plant roots in arctic tundra

USGS Publications Warehouse

Iverson, Colleen M.; Sloan, Victoria L.; Sullivan, Patrick F.; Euskirchen, E.S.; McGuire, A. David; Norby, Richard J.; Walker, Anthony P.; Warren, Jeffrey M.; Wullschleger, Stan D.

2015-01-01

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits – including distribution, chemistry, anatomy and resource partitioning – play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions.

Can market-based policies accomplish the optimal floodplain management? A gap between static and dynamic models.

PubMed

Mori, Koichiro

2009-02-01

The purpose of this short article is to set static and dynamic models for optimal floodplain management and to compare policy implications from the models. River floodplains are important multiple resources in that they provide various ecosystem services. It is fundamentally significant to consider environmental externalities that accrue from ecosystem services of natural floodplains. There is an interesting gap between static and dynamic models about policy implications for floodplain management, although they are based on the same assumptions. Essentially, we can derive the same optimal conditions, which imply that the marginal benefits must equal the sum of the marginal costs and the social external costs related to ecosystem services. Thus, we have to internalise the external costs by market-based policies. In this respect, market-based policies seem to be effective in a static model. However, they are not sufficient in the context of a dynamic model because the optimal steady state turns out to be unstable. Based on a dynamic model, we need more coercive regulation policies.

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...

The Dependencies of Ecosystem Pattern, Structure, and Dynamics on Climate, Climate Variability, and Climate Change

NASA Astrophysics Data System (ADS)

Flanagan, S.; Hurtt, G. C.; Fisk, J. P.; Rourke, O.

2012-12-01

A robust understanding of the sensitivity of the pattern, structure, and dynamics of ecosystems to climate, climate variability, and climate change is needed to predict ecosystem responses to current and projected climate change. We present results of a study designed to first quantify the sensitivity of ecosystems to climate through the use of climate and ecosystem data, and then use the results to test the sensitivity of the climate data in a state-of the art ecosystem model. A database of available ecosystem characteristics such as mean canopy height, above ground biomass, and basal area was constructed from sources like the National Biomass and Carbon Dataset (NBCD). The ecosystem characteristics were then paired by latitude and longitude with the corresponding climate characteristics temperature, precipitation, photosynthetically active radiation (PAR) and dew point that were retrieved from the North American Regional Reanalysis (NARR). The average yearly and seasonal means of the climate data, and their associated maximum and minimum values, over the 1979-2010 time frame provided by NARR were constructed and paired with the ecosystem data. The compiled results provide natural patterns of vegetation structure and distribution with regard to climate data. An advanced ecosystem model, the Ecosystem Demography model (ED), was then modified to allow yearly alterations to its mechanistic climate lookup table and used to predict the sensitivities of ecosystem pattern, structure, and dynamics to climate data. The combined ecosystem structure and climate data results were compared to ED's output to check the validity of the model. After verification, climate change scenarios such as those used in the last IPCC were run and future forest structure changes due to climate sensitivities were identified. The results of this study can be used to both quantify and test key relationships for next generation models. The sensitivity of ecosystem characteristics to climate data shown in the database construction and by the model reinforces the need for high-resolution datasets and stresses the importance of understanding and incorporating climate change scenarios into earth system models.

Ecosystem Restoration: Fact or Fancy?

Treesearch

John A. Stanturf; Callie J. Schweitzer; Stephen H. Schoenholtz; James P. Barnett; Charles K. McMahon; Donald J. Tomszak

1998-01-01

Ecological restoration is generally accepted as the reestablishment of natural ecological processes that produce certain dynamic ecosystem properties of structure, function, and processes. But restore to what? The most frequently used conceptual model for the restoration process is the shift of conditions from some current (degraded) dynamic state to some past dynamic...

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Spatially cascading effect of perturbations in experimental meta-ecosystems.

PubMed

Harvey, Eric; Gounand, Isabelle; Ganesanandamoorthy, Pravin; Altermatt, Florian

2016-09-14

Ecosystems are linked to neighbouring ecosystems not only by dispersal, but also by the movement of subsidy. Such subsidy couplings between ecosystems have important landscape-scale implications because perturbations in one ecosystem may affect community structure and functioning in neighbouring ecosystems via increased/decreased subsidies. Here, we combine a general theoretical approach based on harvesting theory and a two-patch protist meta-ecosystem experiment to test the effect of regional perturbations on local community dynamics. We first characterized the relationship between the perturbation regime and local population demography on detritus production using a mathematical model. We then experimentally simulated a perturbation gradient affecting connected ecosystems simultaneously, thus altering cross-ecosystem subsidy exchanges. We demonstrate that the perturbation regime can interact with local population dynamics to trigger unexpected temporal variations in subsidy pulses from one ecosystem to another. High perturbation intensity initially led to the highest level of subsidy flows; however, the level of perturbation interacted with population dynamics to generate a crash in subsidy exchange over time. Both theoretical and experimental results show that a perturbation regime interacting with local community dynamics can induce a collapse in population levels for recipient ecosystems. These results call for integrative management of human-altered landscapes that takes into account regional dynamics of both species and resource flows. © 2016 The Author(s).

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

Treesearch

Shanlei Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter V. Caldwell; Kai Duan; Yang Zhang

2016-01-01

Quantifying the potential impacts of climatechange on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, andecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and StressIndex, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled...

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...

A phase transition induces chaos in a predator-prey ecosystem with a dynamic fitness landscape

PubMed Central

2017-01-01

In many ecosystems, natural selection can occur quickly enough to influence the population dynamics and thus future selection. This suggests the importance of extending classical population dynamics models to include such eco-evolutionary processes. Here, we describe a predator-prey model in which the prey population growth depends on a prey density-dependent fitness landscape. We show that this two-species ecosystem is capable of exhibiting chaos even in the absence of external environmental variation or noise, and that the onset of chaotic dynamics is the result of the fitness landscape reversibly alternating between epochs of stabilizing and disruptive selection. We draw an analogy between the fitness function and the free energy in statistical mechanics, allowing us to use the physical theory of first-order phase transitions to understand the onset of rapid cycling in the chaotic predator-prey dynamics. We use quantitative techniques to study the relevance of our model to observational studies of complex ecosystems, finding that the evolution-driven chaotic dynamics confer community stability at the “edge of chaos” while creating a wide distribution of opportunities for speciation during epochs of disruptive selection—a potential observable signature of chaotic eco-evolutionary dynamics in experimental studies. PMID:28678792

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

USDA-ARS?s Scientific Manuscript database

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynami...

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...

The unseen iceberg: plant roots in arctic tundra.

PubMed

Iversen, Colleen M; Sloan, Victoria L; Sullivan, Patrick F; Euskirchen, Eugenie S; McGuire, A David; Norby, Richard J; Walker, Anthony P; Warren, Jeffrey M; Wullschleger, Stan D

2015-01-01

Plant roots play a critical role in ecosystem function in arctic tundra, but root dynamics in these ecosystems are poorly understood. To address this knowledge gap, we synthesized available literature on tundra roots, including their distribution, dynamics and contribution to ecosystem carbon and nutrient fluxes, and highlighted key aspects of their representation in terrestrial biosphere models. Across all tundra ecosystems, belowground plant biomass exceeded aboveground biomass, with the exception of polar desert tundra. Roots were shallowly distributed in the thin layer of soil that thaws annually, and were often found in surface organic soil horizons. Root traits - including distribution, chemistry, anatomy and resource partitioning - play an important role in controlling plant species competition, and therefore ecosystem carbon and nutrient fluxes, under changing climatic conditions, but have only been quantified for a small fraction of tundra plants. Further, the annual production and mortality of fine roots are key components of ecosystem processes in tundra, but extant data are sparse. Tundra root traits and dynamics should be the focus of future research efforts. Better representation of the dynamics and characteristics of tundra roots will improve the utility of models for the evaluation of the responses of tundra ecosystems to changing environmental conditions. No claim to original US Government works New Phytologist © 2014 New Phytologist Trust.

The Importance of Uncertainty and Sensitivity Analysis in Process-based Models of Carbon and Nitrogen Cycling in Terrestrial Ecosystems with Particular Emphasis on Forest Ecosystems — Selected Papers from a Workshop Organized by the International Society for Ecological Modelling (ISEM) at the Third Biennal Meeting of the International Environmental Modelling and Software Society (IEMSS) in Burlington, Vermont, USA, August 9-13, 2006

USGS Publications Warehouse

Larocque, Guy R.; Bhatti, Jagtar S.; Liu, Jinxun; Ascough, James C.; Gordon, Andrew M.

2008-01-01

Many process-based models of carbon (C) and nitrogen (N) cycles have been developed for terrestrial ecosystems, including forest ecosystems. They address many basic issues of ecosystems structure and functioning, such as the role of internal feedback in ecosystem dynamics. The critical factor in these phenomena is scale, as these processes operate at scales from the minute (e.g. particulate pollution impacts on trees and other organisms) to the global (e.g. climate change). Research efforts remain important to improve the capability of such models to better represent the dynamics of terrestrial ecosystems, including the C, nutrient, (e.g. N) and water cycles. Existing models are sufficiently well advanced to help decision makers develop sustainable management policies and planning of terrestrial ecosystems, as they make realistic predictions when used appropriately. However, decision makers must be aware of their limitations by having the opportunity to evaluate the uncertainty associated with process-based models (Smith and Heath, 2001 and Allen et al., 2004). The variation in scale of issues currently being addressed by modelling efforts makes the evaluation of uncertainty a daunting task.

The distribution of persistent organic pollutants in a trophically complex Antarctic ecosystem model

NASA Astrophysics Data System (ADS)

Bates, Michael L.; Bengtson Nash, Susan M.; Hawker, Darryl W.; Shaw, Emily C.; Cropp, Roger A.

2017-06-01

Despite Antarctica's isolation from human population centres, persistent organic pollutants (POPs) are transported there via long range atmospheric transport and subsequently cold-trapped. The challenging nature of working in the Antarctic environment greatly limits our ability to monitor POP concentrations and understand the processes that govern the distribution of POPs in Antarctic ecosystems. Here we couple a dynamic, trophically complex biological model with a fugacity model to investigate the distribution of hexachlorobenzene (HCB) in a near-shore Antarctic ecosystem. Using this model we examine the steady-state, and annual cycle of HCB concentration in the atmosphere, ocean, sediment, detritus, and 21 classes of biota that span from primary producers to apex predators. The scope and trophic resolution of our model allows us to examine POP pathways through the ecosystem. In our model the main pathway of HCB to upper trophic species is via pelagic communities, with relatively little via benthic communities. Using a dynamic ecosystem model also allows us to examine the seasonal and potential climate change induced changes in POP distribution. We show that there is a large annual cycle in concentration in the planktonic communities, which may have implications for biomagnification factors calculated from observations. We also examine the direct effects of increasing temperature on the redistribution of HCB in a changing climate and find that it is likely minor compared to other indirect effects, such as changes in atmospheric circulation, sea ice dynamics, and changes to the ecosystem itself.

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

USGS Publications Warehouse

He, Yujie; Zhuang, Qianlai; McGuire, David; Liu, Yaling; Chen, Min

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 in modeling regional carbon dynamics and explore the implications of those options. We calibrated the Terrestrial Ecosystem Model on a hierarchy of three vegetation classification levels for the Alaskan boreal forest: species level, plant-functional-type level (PFT level), and biome level, and we examined the differences in simulated carbon dynamics. Species-specific field-based estimates were directly used to parameterize the model for species-level simulations, while weighted averages based on species percent cover were used to generate estimates for PFT- and biome-level model parameterization. We found that calibrated key ecosystem process parameters differed substantially among species and overlapped for species that are categorized into different PFTs. Our analysis of parameter sets suggests that the PFT-level parameterizations primarily reflected the dominant species and that functional information of some species were lost from the PFT-level parameterizations. The biome-level parameterization was primarily representative of the needleleaf PFT and lost information on broadleaf species or PFT function. Our results indicate that PFT-level simulations may be potentially representative of the performance of species-level simulations while biome-level simulations may result in biased estimates. Improved theoretical and empirical justifications for grouping species into PFTs or biomes are needed to adequately represent the dynamics of ecosystem functioning and structure.

Wasp waist or beer belly? Modeling food web structure and energetic control in Alaskan marine ecosystems, with implications for fishing and environmental forcing

NASA Astrophysics Data System (ADS)

Gaichas, Sarah; Aydin, Kerim; Francis, Robert C.

2015-11-01

The Eastern Bering Sea (EBS) and Gulf of Alaska (GOA) continental shelf ecosystems show some similar and some distinctive groundfish biomass dynamics. Given that similar species occupy these regions and fisheries management is also comparable, similarities might be expected, but to what can we attribute the differences? Different types of ecosystem structure and control (e.g. top-down, bottom-up, mixed) can imply different ecosystem dynamics and climate interactions. Further, the structural type identified for a given ecosystem may suggest optimal management for sustainable fishing. Here, we use information on the current system state derived from food web models of both the EBS and the GOA combined with dynamic ecosystem models incorporating uncertainty to classify each ecosystem by its structural type. We then suggest how this structure might be generally related to dynamics and predictability. We find that the EBS and GOA have fundamentally different food web structures both overall, and when viewed from the perspective of the same commercially and ecologically important species in each system, walleye pollock (Gadus chalcogrammus). EBS food web structure centers on a large mass of pollock, which appears to contribute to relative system stability and predictability. In contrast, GOA food web structure features high predator biomass, which contributes to a more dynamic, less predictable ecosystem. Mechanisms for climate influence on pollock production in the EBS are increasingly understood, while climate forcing mechanisms contributing to the potentially destabilizing high predator biomass in the GOA remain enigmatic. We present results of identical pollock fishing and climate-driven pollock recruitment simulations in the EBS and GOA which show different system responses, again with less predictable response in the GOA. Overall, our results suggest that identifying structural properties of fished food webs is as important for sustainable fisheries management as attempting to predict climate and fisheries effects within each ecosystem.

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...

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...

Disentangling the effects of climate variability and functional change on ecosystem carbon dynamics using semi-empirical modelling

NASA Astrophysics Data System (ADS)

Wu, J.; van der Linden, L.; Lasslop, G.; Carvalhais, N.; Pilegaard, K.; Beier, C.; Ibrom, A.

2012-04-01

The ecosystem carbon balance is affected by both external climatic forcing (e.g. solar radiation, air temperature and humidity) and internal dynamics in the ecosystem functional properties (e.g. canopy structure, leaf photosynthetic capacity and carbohydrate reserve). In order to understand to what extent and at which temporal scale, climatic variability and functional changes regulated the interannual variation (IAV) in the net ecosystem exchange of CO2 (NEE), data-driven analysis and semi-empirical modelling (Lasslop et al. 2010) were performed based on a 13 year NEE record in a temperate deciduous forest (Pilegaard et al 2011, Wu et al. 2012). We found that the sensitivity of carbon fluxes to climatic variability was significantly higher at shorter than at longer time scales and changed seasonally. This implied that the changing distribution of climate anomalies during the vegetation period could have stronger impacts on future ecosystem carbon balances than changes in average climate. At the annual time scale, approximately 80% of the interannual variability in NEE was attributed to the variation in the model parameters, indicating the observed IAV in the carbon dynamics at the investigated site was dominated by changes in ecosystem functioning. In general this study showed the need for understanding the mechanisms of ecosystem functional change. The method can be applied at other sites to explore ecosystem behavior across different plant functional types and climate gradients. Incorporating ecosystem functional change into process based models will reduce the uncertainties in long-term predictions of ecosystem carbon balances in global climate change projections. Acknowledgements. This work was supported by the EU FP7 project CARBO-Extreme, the DTU Climate Centre and the Danish national project ECOCLIM (Danish Council for Strategic Research).

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.

Indicators of ecosystem function identify alternate states in the sagebrush steppe.

PubMed

Kachergis, Emily; Rocca, Monique E; Fernandez-Gimenez, Maria E

2011-10-01

Models of ecosystem change that incorporate nonlinear dynamics and thresholds, such as state-and-transition models (STMs), are increasingly popular tools for land management decision-making. However, few models are based on systematic collection and documentation of ecological data, and of these, most rely solely on structural indicators (species composition) to identify states and transitions. As STMs are adopted as an assessment framework throughout the United States, finding effective and efficient ways to create data-driven models that integrate ecosystem function and structure is vital. This study aims to (1) evaluate the utility of functional indicators (indicators of rangeland health, IRH) as proxies for more difficult ecosystem function measurements and (2) create a data-driven STM for the sagebrush steppe of Colorado, USA, that incorporates both ecosystem structure and function. We sampled soils, plant communities, and IRH at 41 plots with similar clayey soils but different site histories to identify potential states and infer the effects of management practices and disturbances on transitions. We found that many IRH were correlated with quantitative measures of functional indicators, suggesting that the IRH can be used to approximate ecosystem function. In addition to a reference state that functions as expected for this soil type, we identified four biotically and functionally distinct potential states, consistent with the theoretical concept of alternate states. Three potential states were related to management practices (chemical and mechanical shrub treatments and seeding history) while one was related only to ecosystem processes (erosion). IRH and potential states were also related to environmental variation (slope, soil texture), suggesting that there are environmental factors within areas with similar soils that affect ecosystem dynamics and should be noted within STMs. Our approach generated an objective, data-driven model of ecosystem dynamics for rangeland management. Our findings suggest that the IRH approximate ecosystem processes and can distinguish between alternate states and communities and identify transitions when building data-driven STMs. Functional indicators are a simple, efficient way to create data-driven models that are consistent with alternate state theory. Managers can use them to improve current model-building methods and thus apply state-and-transition models more broadly for land management decision-making.

Estimating Rates of Permafrost Degradation and their Impact on Ecosystems across Alaska and Northwest Canada using the Process-based Permafrost Dynamics Model GIPL as a Component of the Integrated Ecosystem Model (IEM)

NASA Astrophysics Data System (ADS)

Marchenko, S. S.; Genet, H.; Euskirchen, E. S.; Breen, A. L.; McGuire, A. D.; Rupp, S. T.; Romanovsky, V. E.; Bolton, W. R.; Walsh, J. E.

2016-12-01

The impact of climate warming on permafrost and the potential of climate feedbacks resulting from permafrost thawing have recently received a great deal of attention. Permafrost temperature has increased in most locations in the Arctic and Sub-Arctic during the past 30-40 years. The typical increase in permafrost temperature is 1-3°C. The process-based permafrost dynamics model GIPL developed in the Geophysical Institute Permafrost Lab, and which is the permafrost module of the Integrated Ecosystem Model (IEM) has been using to quantify the nature and rate of permafrost degradation and its impact on ecosystems, infrastructure, CO2 and CH4fluxes and net C storage following permafrost thaw across Alaska and Northwest Canada. The IEM project is a multi-institutional and multi-disciplinary effort aimed at understanding potential landscape, habitat and ecosystem change across the IEM domain. The IEM project also aims to tie three scientific models together Terrestrial Ecosystem Model (TEM), the ALFRESCO (ALaska FRame-based EcoSystem Code) and GIPL so that they exchange data at run-time. The models produce forecasts of future fire, vegetation, organic matter, permafrost and hydrology regimes. The climate forcing data are based on the historical CRU3.1 data set for the retrospective analysis period (1901-2009) and the CMIP3 CCCMA-CGCM3.1 and MPI-ECHAM5/MPI-OM climate models for the future period (2009-2100). All data sets were downscaled to a 1 km resolution, using a differencing methodology (i.e., a delta method) and the Parameter-elevation Regressions on Independent Slopes Model (PRISM) climatology. We estimated the dynamics of permafrost temperature, active layer thickness, area occupied by permafrost, and volume of thawed soils across the IEM domain. The modeling results indicate how different types of ecosystems affect the thermal state of permafrost and its stability. Although the rate of soil warming and permafrost degradation in peatland areas are slower than other areas, a considerable volume of peat will be thawed by the end of the current century. 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.

A methodology for evaluation of parent-mutant competition using a generalized non-linear ecosystem model

Treesearch

Raymond L. Czaplewski

1973-01-01

A generalized, non-linear population dynamics model of an ecosystem is used to investigate the direction of selective pressures upon a mutant by studying the competition between parent and mutant populations. The model has the advantages of considering selection as operating on the phenotype, of retaining the interaction of the mutant population with the ecosystem as a...

Transport and fate of radionuclides in aquatic environments--the use of ecosystem modelling for exposure assessments of nuclear facilities.

PubMed

Kumblad, L; Kautsky, U; Naeslund, B

2006-01-01

In safety assessments of nuclear facilities, a wide range of radioactive isotopes and their potential hazard to a large assortment of organisms and ecosystem types over long time scales need to be considered. Models used for these purposes have typically employed approaches based on generic reference organisms, stylised environments and transfer functions for biological uptake exclusively based on bioconcentration factors (BCFs). These models are of non-mechanistic nature and involve no understanding of uptake and transport processes in the environment, which is a severe limitation when assessing real ecosystems. In this paper, ecosystem models are suggested as a method to include site-specific data and to facilitate the modelling of dynamic systems. An aquatic ecosystem model for the environmental transport of radionuclides is presented and discussed. With this model, driven and constrained by site-specific carbon dynamics and three radionuclide specific mechanisms: (i) radionuclide uptake by plants, (ii) excretion by animals, and (iii) adsorption to organic surfaces, it was possible to estimate the radionuclide concentrations in all components of the modelled ecosystem with only two radionuclide specific input parameters (BCF for plants and Kd). The importance of radionuclide specific mechanisms for the exposure to organisms was examined, and probabilistic and sensitivity analyses to assess the uncertainties related to ecosystem input parameters were performed. Verification of the model suggests that this model produces analogous results to empirically derived data for more than 20 different radionuclides.

Dynamically Coupled Food-web and Hydrodynamic Modeling with ADH-CASM

NASA Astrophysics Data System (ADS)

Piercy, C.; Swannack, T. M.

2012-12-01

Oysters and freshwater mussels are "ecological engineers," modifying the local water quality by filtering zooplankton and other suspended particulate matter from the water column and flow hydraulics by impinging on the near-bed flow environment. The success of sessile, benthic invertebrates such as oysters depends on environmental factors including but not limited to temperature, salinity, and flow regime. Typically food-web and other types of ecological models use flow and water quality data as direct input without regard to the feedback between the ecosystem and the physical environment. The USACE-ERDC has developed a coupled hydrodynamic-ecological modeling approach that dynamically couples a 2-D hydrodynamic and constituent transport model, Adaptive Hydraulics (ADH), with a bioenergetics food-web model, the Comprehensive Aquatics Systems Model (CASM), which captures the dynamic feedback between aquatic ecological systems and the environment. We present modeling results from restored oyster reefs in the Great Wicomico River on the western shore of the Chesapeake Bay, which quantify ecosystem services such as the influence of the benthic ecosystem on water quality. Preliminary results indicate that while the influence of oyster reefs on bulk flow dynamics is limited due to the localized influence of oyster reefs, large reefs and the associated benthic ecosystem can create measurable changes in the concentrations of nitrogen, phosphorus, and carbon in the areas around reefs. We also present a sensitivity analysis to quantify the relative sensitivity of the coupled ADH-CASM model to both hydrodynamic and ecological parameter choice.

Modelled effects of precipitation on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Dieter Gerten; Yiqi Luo; Guerric Le Maire; William J. Parton; Cindy Keough; Ensheng Weng; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Paul J. Hanson; Alan A. K. Knapp; Sune Linder; Dan Nepstad; Lindsey Rustad; Alwyn. Sowerby

2008-01-01

The ongoing changes in the global climate expose the world’s ecosystems not only to increasing CO2 concentrations and temperatures but also to altered precipitation (P) regimes. Using four well-established process-based ecosystem models (LPJ, DayCent, ORCHIDEE, TECO), we explored effects of potential P...

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.

[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.

Understanding variation in ecosystem pulse responses to wetting: Benefits of data-model coupling

NASA Astrophysics Data System (ADS)

Jenerette, D.

2011-12-01

Metabolic pulses of activity are a common ecological response to intermittently available resources and in water-limited ecosystems these pulses often occur in response to wetting. Net ecosystem CO2 exchange (NEE) in response to episodic wetting events is hypothesized to have a complex trajectory reflecting the distinct responses, or "pulses", of respiration and photosynthesis. To help direct research activities a physiological-based model of whole ecosystem metabolic activity up- and down-regulation was developed to investigate ecosystem energy balance and gas exchange pulse responses following precipitation events. This model was to investigate pulse dynamics from a local network of sites in southern Arizona, a global network of eddy-covariance ecosystem monitoring sites, laboratory incubation studies, and field manipulations. Pulse responses were found to be ubiquitous across ecosystem types. These pulses had a highly variable influence on NEE following wetting, ranging from large net sinks to sources of CO2 to the atmosphere. Much of the variability in pulse responses of NEE could be described through a coupled up- and down-regulation pulse response model. Respiration pulses were hypothesized to occur through a reduction in whole ecosystem activation energy; this model was both useful and corroborated through laboratory incubation studies of soil respiration. Using the Fluxnet eddy-covariance measurement database event specific responses were combined with the pulse model into an event specific twenty-five day net flux calculation. Across all events observed a general net accumulation of CO2 following a precipitation event, with the largest net uptake within deciduous broadleaf forests and smallest within grasslands. NEE pulses favored greater uptake when pre-event ecosystem respiration rates and total precipitation were higher. While the latter was expected, the former adds to previous theory by suggesting a larger net uptake of CO2 when pre-event metabolic activity is higher. Scenario analyses of precipitation regimes suggested increased uptake with increasing total precipitation while more complex NEE responses to increasing number of events and interval between events. Pulse dynamics provides a general framework for understanding ecosystem responses to intermittent wetting projected to occur more frequently in future climates. Pulse dynamics also provides an opportunity to evaluate processes spanning cellular upregulation to global change.

A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China

NASA Astrophysics Data System (ADS)

Wu, Meng; Ren, Xiangyu; Che, Yue; Yang, Kai

2015-08-01

Most of the cities in developing countries are experiencing rapid urbanization. Land use change driven by urban sprawl, population growth, and intensified socio-economic activities have led to a steep decline of ecosystem service value (ESV) in rapid urbanization areas, and decision-makers often ignore some valuable ecosystem service functions and values in land use planning. In this paper, we attempt to build a modeling framework which integrated System Dynamics model with Conversion of Land Use and its Effects at Small Extent model to simulate the dynamics of ESV of landscape and explore the potential impacts of land use change on ESV. We take Baoshan district of Shanghai as an example which is a fast urbanization area of metropolitan in China. The results of the study indicate that: (1) The integrated methodology can improve the characterization and presentation of the dynamics of ESV, which may give insight into understanding the possible impacts of land use change on ESV and provide information for land use planning. (2) Land use polices can affect the magnitude and location of ESV both directly and indirectly. Land use changes tend to weaken and simplify ecosystem service functions and values of landscape at urban rural fringe where land use change is more intensive. (3) The application of the methodology has proved that the integration of currently existing models within a single modeling framework could be a beneficial exploration, and should be encouraged and enhanced in the future research on the changing dynamics of ESV due to the complexity of ecosystem services and land use system.

A Coupled SD and CLUE-S Model for Exploring the Impact of Land Use Change on Ecosystem Service Value: A Case Study in Baoshan District, Shanghai, China.

PubMed

Wu, Meng; Ren, Xiangyu; Che, Yue; Yang, Kai

2015-08-01

Most of the cities in developing countries are experiencing rapid urbanization. Land use change driven by urban sprawl, population growth, and intensified socio-economic activities have led to a steep decline of ecosystem service value (ESV) in rapid urbanization areas, and decision-makers often ignore some valuable ecosystem service functions and values in land use planning. In this paper, we attempt to build a modeling framework which integrated System Dynamics model with Conversion of Land Use and its Effects at Small Extent model to simulate the dynamics of ESV of landscape and explore the potential impacts of land use change on ESV. We take Baoshan district of Shanghai as an example which is a fast urbanization area of metropolitan in China. The results of the study indicate that: (1) The integrated methodology can improve the characterization and presentation of the dynamics of ESV, which may give insight into understanding the possible impacts of land use change on ESV and provide information for land use planning. (2) Land use polices can affect the magnitude and location of ESV both directly and indirectly. Land use changes tend to weaken and simplify ecosystem service functions and values of landscape at urban rural fringe where land use change is more intensive. (3) The application of the methodology has proved that the integration of currently existing models within a single modeling framework could be a beneficial exploration, and should be encouraged and enhanced in the future research on the changing dynamics of ESV due to the complexity of ecosystem services and land use system.

The impact of human-environment interactions on the stability of forest-grassland mosaic ecosystems

PubMed Central

Innes, Clinton; Anand, Madhur; Bauch, Chris T.

2013-01-01

Forest-grassland mosaic ecosystems can exhibit alternative stables states, whereby under the same environmental conditions, the ecosystem could equally well reside either in one state or another, depending on the initial conditions. We develop a mathematical model that couples a simplified forest-grassland mosaic model to a dynamic model of opinions about conservation priorities in a population, based on perceptions of ecosystem rarity. Weak human influence increases the region of parameter space where alternative stable states are possible. However, strong human influence precludes bistability, such that forest and grassland either co-exist at a single, stable equilibrium, or their relative abundance oscillates. Moreover, a perturbation can shift the system from a stable state to an oscillatory state. We conclude that human-environment interactions can qualitatively alter the composition of forest-grassland mosaic ecosystems. The human role in such systems should be viewed as dynamic, responsive element rather than as a fixed, unchanging entity. PMID:24048359

Nutrient Dynamics In Flooded Wetlands. I: Model Development

EPA Science Inventory

Wetlands are rich ecosystems recognized for ameliorating floods, improving water quality and providing other ecosystem benefits. In this part of a two-paper sequel, we present a relatively detailed process-based model for nitrogen and phosphorus retention, cycling and removal in...

Modeled effect of warming on ecosystem carbon and water dynamics within grassland/old-field ecosystems along a moisture gradient

USDA-ARS?s Scientific Manuscript database

As a consequence of steadily increasing concentrations of greenhouse gases in Earth’s atmosphere, average world-wide surface temperature is expected to increase 1.5-6.4°C by the end of the 21st Century. Results from manipulative field experiments and ecosystem modeling indicate that plants and soil...

Using ground- and satellite-based measurements and models to quantify response to multiple disturbances and climate change in South African semi-arid ecosystems

NASA Astrophysics Data System (ADS)

Falge, Eva; Brümmer, Christian; Schmullius, Christiane; Scholes, Robert; Twine, Wayne; Mudau, Azwitamisi; Midgley, Guy; Hickler, Thomas; Bradshaw, Karen; Lück, Wolfgang; Thiel-Clemen, Thomas; du Toit, Justin; Sankaran, Vaith; Kutsch, Werner

2016-04-01

Sub-Saharan Africa currently experiences significant changes in shrubland, savanna and mixed woodland ecosystems driving degradation, affecting fire frequency and water availability, and eventually fueling climate change. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. For a network of research clusters along an aridity gradient in South Africa, we measure greenhouse gas exchange, ecosystem structure and eco-physiological properties as affected by land use change at paired sites with natural and altered vegetation. We set up dynamic vegetation models and individual-based models to predict ecosystem dynamics under (post) disturbance managements. We monitor vegetation amount and heterogeneity using remotely sensed images and aerial photography over several decades to examine time series of land cover change. Finally, we investigate livelihood strategies with focus on carbon balance components to develop sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation of estimates obtained from eddy covariance, model approaches and satellite derivations. We envision our methodological approach on a network of research clusters a valuable means to investigate potential linkages to concepts of adaptive resilience.

CLIMATIC EFFECTS ON TUNDRA CARBON STORAGE INFERRED FROM EXPERIMENTAL DATA AND A MODEL

EPA Science Inventory

We used a process-based model of ecosystem carbon (C) and nitrogen (N)dynamics, MBL-GEM (Marine Biological Laboratory General Ecosystem Model), to integrated and analyze the results of several experiments that examined the response of arctic tussock tundra to manipulations of CO2...

The synergistic use of models and observations: understanding the mechanisms behind observed biomass dynamics at 14 Amazonian field sites and the implications for future biomass change

NASA Astrophysics Data System (ADS)

Levine, N. M.; Galbraith, D.; Christoffersen, B. J.; Imbuzeiro, H. A.; Restrepo-Coupe, N.; Malhi, Y.; Saleska, S. R.; Costa, M. H.; Phillips, O.; Andrade, A.; Moorcroft, P. R.

2011-12-01

The Amazonian rainforests play a vital role in global water, energy and carbon cycling. The sensitivity of this system to natural and anthropogenic disturbances therefore has important implications for the global climate. Some global models have predicted large-scale forest dieback and the savannization of Amazonia over the next century [Meehl et al., 2007]. While several studies have demonstrated the sensitivity of dynamic global vegetation models to changes in temperature, precipitation, and dry season length [e.g. Galbraith et al., 2010; Good et al., 2011], the ability of these models to accurately reproduce ecosystem dynamics of present-day transitional or low biomass tropical forests has not been demonstrated. A model-data intercomparison was conducted with four state-of-the-art terrestrial ecosystem models to evaluate the ability of these models to accurately represent structure, function, and long-term biomass dynamics over a range of Amazonian ecosystems. Each modeling group conducted a series of simulations for 14 sites including mature forest, transitional forest, savannah, and agricultural/pasture sites. All models were run using standard physical parameters and the same initialization procedure. Model results were compared against forest inventory and dendrometer data in addition to flux tower measurements. While the models compared well against field observations for the mature forest sites, significant differences were observed between predicted and measured ecosystem structure and dynamics for the transitional forest and savannah sites. The length of the dry season and soil sand content were good predictors of model performance. In addition, for the big leaf models, model performance was highest for sites dominated by late successional trees and lowest for sites with predominantly early and mid-successional trees. This study provides insight into tropical forest function and sensitivity to environmental conditions that will aid in predictions of the response of the Amazonian rainforest to future anthropogenically induced changes.

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.

The Resilience of Coral Reefs Across a Hierarchy of Spatial and Temporal scales

NASA Astrophysics Data System (ADS)

Mumby, P. J.

2016-02-01

Resilience is a dynamical property of ecosystems that integrates processes of recovery, disturbance and internal dynamics, including reinforcing feedbacks. As such, resilience is a useful framework to consider how ecosystems respond to multiple drivers occurring over multiple scales. Many insights have emerged recently including the way in which stressors can combine synergistically to deplete resilience. However, while recent advances have mapped resilience across seascapes, most studies have not captured emergent spatial dependencies and dynamics across the seascape (e.g., independent box models are run across the seascape in isolation). Here, we explore the dynamics that emerge when the seascape is `wired up' using data on larval dispersal, thereby giving a fully spatially-realistic model. We then consider how dynamics change across even larger, biogeographic scales, posing the question, `are there robust and global "rules of thumb" for the resilience of a single ecosystem?'. Answers to this question will help managers tailor their interventions and research needs for their own jurisdiction.

Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America.

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

Terrestrial biosphere models are important tools for diagnosing both the current state of the terrestrial carbon cycle and forecasting terrestrial ecosystem responses to global change. While there are a number of ongoing assessments of the short-term predictive capabilities of terrestrial biosphere models using flux-tower measurements, to date there have been relatively few assessments of their ability to predict longer term, decadal-scale biomass dynamics. Here, we present the results of a regional-scale evaluation of the Ecosystem Demography version 2 (ED2)-structured terrestrial biosphere model, evaluating the model's predictions against forest inventory measurements for the northeast USA and Quebec from 1985 to 1995. Simulations were conducted using a default parametrization, which used parameter values from the literature, and a constrained model parametrization, which had been developed by constraining the model's predictions against 2 years of measurements from a single site, Harvard Forest (42.5° N, 72.1° W). The analysis shows that the constrained model parametrization offered marked improvements over the default model formulation, capturing large-scale variation in patterns of biomass dynamics despite marked differences in climate forcing, land-use history and species-composition across the region. These results imply that data-constrained parametrizations of structured biosphere models such as ED2 can be successfully used for regional-scale ecosystem prediction and forecasting. We also assess the model's ability to capture sub-grid scale heterogeneity in the dynamics of biomass growth and mortality of different sizes and types of trees, and then discuss the implications of these analyses for further reducing the remaining biases in the model's predictions.

A coarse wood dynamics model for the Western Cascades.

Treesearch

K. Mellen; A. Ager

2002-01-01

The Coarse Wood Dynamics Model (CWDM) analyzes the dynamics (fall, fragmentation, and decomposition) of Douglas-fir (Pseudotsuga menziesii) and western hemlock (Tsuga heterophylla) snags and down logs in forested ecosystems of the western Cascades of Oregon and Washington. The model predicts snag fall, height loss and decay,...

Transient traceability analysis of land carbon storage dynamics: procedures and its application to two forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, L.; Shi, Z.; Xia, J.; Liang, J.; Lu, X.; Wang, Y.; Luo, Y.

2017-12-01

Uptake of anthropogenically emitted carbon (C) dioxide by terrestrial ecosystem is critical for determining future climate. However, Earth system models project large uncertainties in future C storage. To help identify sources of uncertainties in model predictions, this study develops a transient traceability framework to trace components of C storage dynamics. Transient C storage (X) can be decomposed into two components, C storage capacity (Xc) and C storage potential (Xp). Xc is the maximum C amount that an ecosystem can potentially store and Xp represents the internal capacity of an ecosystem to equilibrate C input and output for a network of pools. Xc is co-determined by net primary production (NPP) and residence time (𝜏N), with the latter being determined by allocation coefficients, transfer coefficients, environmental scalar, and exit rate. Xp is the product of redistribution matrix (𝜏ch) and net ecosystem exchange. We applied this framework to two contrasting ecosystems, Duke Forest and Harvard Forest with an ecosystem model. This framework helps identify the mechanisms underlying the responses of carbon cycling in the two forests to climate change. The temporal trajectories of X are similar between the two ecosystems. Using this framework, we found that two different mechanisms leading to the similar trajectory. This framework has potential to reveal mechanisms behind transient C storage in response to various global change factors. It can also identify sources of uncertainties in predicted transient C storage across models and can therefore be useful for model intercomparison.

Nutrient supply and mercury dynamics in marine ecosystems: A conceptual model

PubMed Central

Chen, Celia Y.; Hammerschmidt, Chad R.; Mason, Robert P.; Gilmour, Cynthia C.; Sunderland, Elsie M.; Greenfield, Ben K.; Buckman, Kate L.; Lamborg, Carl H.

2013-01-01

There is increasing interest and concern over the impacts of mercury (Hg) inputs to marine ecosystems. One of the challenges in assessing these effects is that the cycling and trophic transfer of Hg are strongly linked to other contaminants and disturbances. In addition to Hg, a major problem facing coastal waters is the impacts of elevated nutrient, particularly nitrogen (N), inputs. Increases in nutrient loading alter coastal ecosystems in ways that should change the transport, transformations and fate of Hg, including increases in fixation of organic carbon and deposition to sediments, decreases in the redox status of sediments and changes in fish habitat. In this paper we present a conceptual model which suggests that increases in loading of reactive N to marine ecosystems might alter Hg dynamics, decreasing bioavailabilty and trophic transfer. This conceptual model is most applicable to coastal waters, but may also be relevant to the pelagic ocean. We present information from case studies that both support and challenge this conceptual model, including marine observations across a nutrient gradient; results of a nutrient-trophic transfer Hg model for pelagic and coastal ecosystems; observations of Hg species, and nutrients from coastal sediments in the northeastern U.S.; and an analysis of fish Hg concentrations in estuaries under different nutrient loadings. These case studies suggest that changes in nutrient loading can impact Hg dynamics in coastal and open ocean ecosystems. Unfortunately none of the case studies is comprehensive; each only addresses a portion of the conceptual model and has limitations. Nevertheless, our conceptual model has important management implications. Many estuaries near developed areas are impaired due to elevated nutrient inputs. Widespread efforts are underway to control N loading and restore coastal ecosystem function. An unintended consequence of nutrient control measures could be to exacerbate problems associated with Hg contamination. Additional focused research and monitoring are needed to critically examine the link between nutrient supply and Hg contamination of marine waters. PMID:22749872

Nutrient supply and mercury dynamics in marine ecosystems: a conceptual model.

PubMed

Driscoll, Charles T; Chen, Celia Y; Hammerschmidt, Chad R; Mason, Robert P; Gilmour, Cynthia C; Sunderland, Elsie M; Greenfield, Ben K; Buckman, Kate L; Lamborg, Carl H

2012-11-01

There is increasing interest and concern over the impacts of mercury (Hg) inputs to marine ecosystems. One of the challenges in assessing these effects is that the cycling and trophic transfer of Hg are strongly linked to other contaminants and disturbances. In addition to Hg, a major problem facing coastal waters is the impacts of elevated nutrient, particularly nitrogen (N), inputs. Increases in nutrient loading alter coastal ecosystems in ways that should change the transport, transformations and fate of Hg, including increases in fixation of organic carbon and deposition to sediments, decreases in the redox status of sediments and changes in fish habitat. In this paper we present a conceptual model which suggests that increases in loading of reactive N to marine ecosystems might alter Hg dynamics, decreasing bioavailabilty and trophic transfer. This conceptual model is most applicable to coastal waters, but may also be relevant to the pelagic ocean. We present information from case studies that both support and challenge this conceptual model, including marine observations across a nutrient gradient; results of a nutrient-trophic transfer Hg model for pelagic and coastal ecosystems; observations of Hg species, and nutrients from coastal sediments in the northeastern U.S.; and an analysis of fish Hg concentrations in estuaries under different nutrient loadings. These case studies suggest that changes in nutrient loading can impact Hg dynamics in coastal and open ocean ecosystems. Unfortunately none of the case studies is comprehensive; each only addresses a portion of the conceptual model and has limitations. Nevertheless, our conceptual model has important management implications. Many estuaries near developed areas are impaired due to elevated nutrient inputs. Widespread efforts are underway to control N loading and restore coastal ecosystem function. An unintended consequence of nutrient control measures could be to exacerbate problems associated with Hg contamination. Additional focused research and monitoring are needed to critically examine the link between nutrient supply and Hg contamination of marine waters. Copyright © 2012 Elsevier Inc. All rights reserved.

Priming effect and microbial diversity in ecosystem functioning and response to global change: a modeling approach using the SYMPHONY model.

PubMed

Perveen, Nazia; Barot, Sébastien; Alvarez, Gaël; Klumpp, Katja; Martin, Raphael; Rapaport, Alain; Herfurth, Damien; Louault, Frédérique; Fontaine, Sébastien

2014-04-01

Integration of the priming effect (PE) in ecosystem models is crucial to better predict the consequences of global change on ecosystem carbon (C) dynamics and its feedbacks on climate. Over the last decade, many attempts have been made to model PE in soil. However, PE has not yet been incorporated into any ecosystem models. Here, we build plant/soil models to explore how PE and microbial diversity influence soil/plant interactions and ecosystem C and nitrogen (N) dynamics in response to global change (elevated CO2 and atmospheric N depositions). Our results show that plant persistence, soil organic matter (SOM) accumulation, and low N leaching in undisturbed ecosystems relies on a fine adjustment of microbial N mineralization to plant N uptake. This adjustment can be modeled in the SYMPHONY model by considering the destruction of SOM through PE, and the interactions between two microbial functional groups: SOM decomposers and SOM builders. After estimation of parameters, SYMPHONY provided realistic predictions on forage production, soil C storage and N leaching for a permanent grassland. Consistent with recent observations, SYMPHONY predicted a CO2 -induced modification of soil microbial communities leading to an intensification of SOM mineralization and a decrease in the soil C stock. SYMPHONY also indicated that atmospheric N deposition may promote SOM accumulation via changes in the structure and metabolic activities of microbial communities. Collectively, these results suggest that the PE and functional role of microbial diversity may be incorporated in ecosystem models with a few additional parameters, improving accuracy of predictions. © 2013 John Wiley & Sons Ltd.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

Hurtt, G. C.; Fisk, J.; Thomas, R. Q.; Dubayah, R.; Moorcroft, P. R.; Shugart, H. H.

2010-06-01

For more than a century, scientists have recognized the importance of vegetation structure in understanding forest dynamics. Now future satellite missions such as Deformation, Ecosystem Structure, and Dynamics of Ice (DESDynI) hold the potential to provide unprecedented global data on vegetation structure needed to reduce uncertainties in terrestrial carbon dynamics. Here, we briefly review the uses of data on vegetation structure in ecosystem models, develop and analyze theoretical models to quantify model-data requirements, and describe recent progress using a mechanistic modeling approach utilizing a formal scaling method and data on vegetation structure to improve model predictions. Generally, both limited sampling and coarse resolution averaging lead to model initialization error, which in turn is propagated in subsequent model prediction uncertainty and error. In cases with representative sampling, sufficient resolution, and linear dynamics, errors in initialization tend to compensate at larger spatial scales. However, with inadequate sampling, overly coarse resolution data or models, and nonlinear dynamics, errors in initialization lead to prediction error. A robust model-data framework will require both models and data on vegetation structure sufficient to resolve important environmental gradients and tree-level heterogeneity in forest structure globally.

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.

How models can support ecosystem-based management of coral reefs

NASA Astrophysics Data System (ADS)

Weijerman, Mariska; Fulton, Elizabeth A.; Janssen, Annette B. G.; Kuiper, Jan J.; Leemans, Rik; Robson, Barbara J.; van de Leemput, Ingrid A.; Mooij, Wolf M.

2015-11-01

Despite the importance of coral reef ecosystems to the social and economic welfare of coastal communities, the condition of these marine ecosystems have generally degraded over the past decades. With an increased knowledge of coral reef ecosystem processes and a rise in computer power, dynamic models are useful tools in assessing the synergistic effects of local and global stressors on ecosystem functions. We review representative approaches for dynamically modeling coral reef ecosystems and categorize them as minimal, intermediate and complex models. The categorization was based on the leading principle for model development and their level of realism and process detail. This review aims to improve the knowledge of concurrent approaches in coral reef ecosystem modeling and highlights the importance of choosing an appropriate approach based on the type of question(s) to be answered. We contend that minimal and intermediate models are generally valuable tools to assess the response of key states to main stressors and, hence, contribute to understanding ecological surprises. As has been shown in freshwater resources management, insight into these conceptual relations profoundly influences how natural resource managers perceive their systems and how they manage ecosystem recovery. We argue that adaptive resource management requires integrated thinking and decision support, which demands a diversity of modeling approaches. Integration can be achieved through complimentary use of models or through integrated models that systemically combine all relevant aspects in one model. Such whole-of-system models can be useful tools for quantitatively evaluating scenarios. These models allow an assessment of the interactive effects of multiple stressors on various, potentially conflicting, management objectives. All models simplify reality and, as such, have their weaknesses. While minimal models lack multidimensionality, system models are likely difficult to interpret as they require many efforts to decipher the numerous interactions and feedback loops. Given the breadth of questions to be tackled when dealing with coral reefs, the best practice approach uses multiple model types and thus benefits from the strength of different models types.

Challenges and opportunities for integrating lake ecosystem modelling approaches

USGS Publications Warehouse

Mooij, Wolf M.; Trolle, Dennis; Jeppesen, Erik; Arhonditsis, George; Belolipetsky, Pavel V.; Chitamwebwa, Deonatus B.R.; Degermendzhy, Andrey G.; DeAngelis, Donald L.; Domis, Lisette N. De Senerpont; Downing, Andrea S.; Elliott, J. Alex; Ruberto, Carlos Ruberto; Gaedke, Ursula; Genova, Svetlana N.; Gulati, Ramesh D.; Hakanson, Lars; Hamilton, David P.; Hipsey, Matthew R.; Hoen, Jochem 't; Hulsmann, Stephan; Los, F. Hans; Makler-Pick, Vardit; Petzoldt, Thomas; Prokopkin, Igor G.; Rinke, Karsten; Schep, Sebastiaan A.; Tominaga, Koji; Van Dam, Anne A.; Van Nes, Egbert H.; Wells, Scott A.; Janse, Jan H.

2010-01-01

A large number and wide variety of lake ecosystem models have been developed and published during the past four decades. We identify two challenges for making further progress in this field. One such challenge is to avoid developing more models largely following the concept of others ('reinventing the wheel'). The other challenge is to avoid focusing on only one type of model, while ignoring new and diverse approaches that have become available ('having tunnel vision'). In this paper, we aim at improving the awareness of existing models and knowledge of concurrent approaches in lake ecosystem modelling, without covering all possible model tools and avenues. First, we present a broad variety of modelling approaches. To illustrate these approaches, we give brief descriptions of rather arbitrarily selected sets of specific models. We deal with static models (steady state and regression models), complex dynamic models (CAEDYM, CE-QUAL-W2, Delft 3D-ECO, LakeMab, LakeWeb, MyLake, PCLake, PROTECH, SALMO), structurally dynamic models and minimal dynamic models. We also discuss a group of approaches that could all be classified as individual based: super-individual models (Piscator, Charisma), physiologically structured models, stage-structured models and trait-based models. We briefly mention genetic algorithms, neural networks, Kalman filters and fuzzy logic. Thereafter, we zoom in, as an in-depth example, on the multi-decadal development and application of the lake ecosystem model PCLake and related models (PCLake Metamodel, Lake Shira Model, IPH-TRIM3D-PCLake). In the discussion, we argue that while the historical development of each approach and model is understandable given its 'leading principle', there are many opportunities for combining approaches. We take the point of view that a single 'right' approach does not exist and should not be strived for. Instead, multiple modelling approaches, applied concurrently to a given problem, can help develop an integrative view on the functioning of lake ecosystems. We end with a set of specific recommendations that may be of help in the further development of lake ecosystem models.

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.

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.

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,...

Phytoplankton competition and coexistence: Intrinsic ecosystem dynamics and impact of vertical mixing

NASA Astrophysics Data System (ADS)

Perruche, Coralie; Rivière, Pascal; Pondaven, Philippe; Carton, Xavier

2010-04-01

This paper aims at studying analytically the functioning of a very simple ecosystem model with two phytoplankton species. First, using the dynamical system theory, we determine its nonlinear equilibria, their stability and characteristic timescales with a focus on phytoplankton competition. Particular attention is paid to the model sensitivity to parameter change. Then, the influence of vertical mixing and sinking of detritus on the vertically-distributed ecosystem model is investigated. The analytical results reveal a high diversity of ecosystem structures with fixed points and limit cycles that are mainly sensitive to variations of light intensity and total amount of nitrogen matter. The sensitivity to other parameters such as re-mineralisation, growth and grazing rates is also specified. Besides, the equilibrium analysis shows a complete segregation of the two phytoplankton species in the whole parameter space. The embedding of our ecosystem model into a one-dimensional numerical model with diffusion turns out to allow coexistence between phytoplankton species, providing a possible solution to the 'paradox of plankton' in the sense that it prevents the competitive exclusion of one phytoplankton species. These results improve our knowledge of the factors that control the structure and functioning of plankton communities.

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...

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.

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.

Modeling leaf phenology variation by groupings of species within and across ecosystems in northern Alaska

NASA Astrophysics Data System (ADS)

Euskirchen, E. S.; Carman, T. B.; McGuire, A. D.

2012-12-01

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 and 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 a regional to global scale typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observational data 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 ecotonal 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. This implementation improves the timing of the onset of carbon uptake in the spring, permitting a more accurate assessment of the contribution of each grouping of species to ecosystem performance. Furthermore, this implementation provides a more nuanced perspective on light competition among species and across ecosystems. For example, in the shrub tundra, the sedges and grasses leaf-out before the shade-inducing willow and dwarf birch, thereby providing the sedges and grasses time to accumulate biomass before shading effects arise. Also in the shrub tundra, the forbs leaf-out last, and are therefore, more prone to shading impacts by the taller willow and dwarf birch shrubs. However, in the wet sedge and heath tundra ecosystems, the forbs leaf-out before the shrubs, and are therefore less prone to shading impacts early in the growing season. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape. These findings also demonstrate that high-latitude dynamic vegetation models should consider variation in leaf-out by groupings of species within and across ecosystems in order to provide more accurate projections of future plant distributions in Arctic regions.

Temporal dynamics of phosphorus during aquatic and terrestrial litter decomposition in an alpine forest.

PubMed

Peng, Yan; Yang, Wanqin; Yue, Kai; Tan, Bo; Huang, Chunping; Xu, Zhenfeng; Ni, Xiangyin; Zhang, Li; Wu, Fuzhong

2018-06-17

Plant litter decomposition in forested soil and watershed is an important source of phosphorus (P) for plants in forest ecosystems. Understanding P dynamics during litter decomposition in forested aquatic and terrestrial ecosystems will be of great importance for better understanding nutrient cycling across forest landscape. However, despite massive studies addressing litter decomposition have been carried out, generalizations across aquatic and terrestrial ecosystems regarding the temporal dynamics of P loss during litter decomposition remain elusive. We conducted a two-year field experiment using litterbag method in both aquatic (streams and riparian zones) and terrestrial (forest floors) ecosystems in an alpine forest on the eastern Tibetan Plateau. By using multigroup comparisons of structural equation modeling (SEM) method with different litter mass-loss intervals, we explicitly assessed the direct and indirect effects of several biotic and abiotic drivers on P loss across different decomposition stages. The results suggested that (1) P concentration in decomposing litter showed similar patterns of early increase and later decrease across different species and ecosystems types; (2) P loss shared a common hierarchy of drivers across different ecosystems types, with litter chemical dynamics mainly having direct effects but environment and initial litter quality having both direct and indirect effects; (3) when assessing at the temporal scale, the effects of initial litter quality appeared to increase in late decomposition stages, while litter chemical dynamics showed consistent significant effects almost in all decomposition stages across aquatic and terrestrial ecosystems; (4) microbial diversity showed significant effects on P loss, but its effects were lower compared with other drivers. Our results highlight the importance of including spatiotemporal variations and indicate the possibility of integrating aquatic and terrestrial decomposition into a common framework for future construction of models that account for the temporal dynamics of P in decomposing litter. Copyright © 2018 Elsevier B.V. All rights reserved.

Using landscape limnology to classify freshwater ecosystems for multi-ecosystem management and conservation

USGS Publications Warehouse

Soranno, Patricia A.; Cheruvelil, Kendra Spence; Webster, Katherine E.; Bremigan, Mary T.; Wagner, Tyler; Stow, Craig A.

2010-01-01

Governmental entities are responsible for managing and conserving large numbers of lake, river, and wetland ecosystems that can be addressed only rarely on a case-by-case basis. We present a system for predictive classification modeling, grounded in the theoretical foundation of landscape limnology, that creates a tractable number of ecosystem classes to which management actions may be tailored. We demonstrate our system by applying two types of predictive classification modeling approaches to develop nutrient criteria for eutrophication management in 1998 north temperate lakes. Our predictive classification system promotes the effective management of multiple ecosystems across broad geographic scales by explicitly connecting management and conservation goals to the classification modeling approach, considering multiple spatial scales as drivers of ecosystem dynamics, and acknowledging the hierarchical structure of freshwater ecosystems. Such a system is critical for adaptive management of complex mosaics of freshwater ecosystems and for balancing competing needs for ecosystem services in a changing world.

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.

Data Synthesis and Data Assimilation at Global Change Experiments and Fluxnet Toward Improving Land Process Models

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

Luo, Yiqi

The project was conducted during the period from 7/1/2012 to 6/30/2017 with three major tasks: (1) data synthesis and development of data assimilation (DA) techniques to constrain modeled ecosystem feedback to climate change; (2) applications of DA techniques to improve process models at different scales from ecosystem to regions and the globe; and 3) improvements of modeling soil carbon (C) dynamics by land surface models. During this period, we have synthesized published data from soil incubation experiments (e.g., Chen et al., 2016; Xu et al., 2016; Feng et al., 2016), global change experiments (e.g., Li et al., 2013; Shi etmore » al., 2015, 2016; Liang et al., 2016) and fluxnet (e.g., Niu et al., 2012., Xia et al., 2015; Li et al., 2016). These data have been organized into multiple data products and have been used to identify general mechanisms and estimate parameters for model improvement. We used the data sets that we collected and the DA techniques to improve model performance of both ecosystem models and global land models. The objectives are: 1) to improve model simulations of litter and soil carbon storage (e.g., Schädel et al., 2013; Hararuk and Luo, 2014; Hararuk et al., 2014; Liang et al., 2015); 2) to explore the effects of CO 2, warming and precipitation on ecosystem processes (e.g., van Groenigen et al., 2014; Shi et al., 2015, 2016; Feng et al., 2017); and 3) to estimate parameters variability in different ecosystems (e.g., Li et al., 2016). We developed a traceability framework, which was based on matrix approaches and decomposed the modeled steady-state terrestrial ecosystem carbon storage capacity into four can trace the difference in ecosystem carbon storage capacity among different biomes to four traceable components: net primary productivity (NPP), baseline C residence times, environmental scalars and climate forcing (Xia et al., 2013). With this framework, we can diagnose the differences in modeled carbon storage across ecosystems, biomes, and models. This framework has been successfully implemented by several global land models, such as CABLE (Xia et al., 2013), LPJ-GUESS (Ahlström et al., 2015), CLM (Hararuk et al., 2014; Huang et al., 2017, submitted; Shi et al., 2017, submitted), and ORCHIDEE (Huang et al., 2017, unpublished). Moreover, we have identified the theoretical foundation of the determinants of transient C storage dynamics by adding another term, C storage potential, to the steady-state traceability framework (Luo et al., 2017). The theoretical foundation of transient C storage dynamics has been applied to develop a transient traceability framework to explore the traceable components of transient C storage dynamics responded to the rising CO 2 and climate change in the two contrasting ecosystem types Duke needleleaved forest and Harvard deciduous broadleaved forest (Jiang et al., 2017, in revision). Overall, with the data synthesis, data assimilation techniques, and the steady-state and transient traceability frameworks, we have greatly improved land process models for predicting responses and feedback of terrestrial C dynamics to global change. The matrix approaches has the potential to be applied in theoretical research on nitrogen and phosphorus cycle, and therefore, the coupling of carbon-nitrogen-phosphorus.« less

EXPOSURE OF RIPARIAN ECOSYSTEMS TO NON-INDIGENOUS PLANT SPECIES: A CONCEPTUAL RISK ASSESSMENT MODEL

EPA Science Inventory

Biological invasions are one of the foremost threats to the integrity of riparian

ecosystems worldwide, but little is known regarding the long-term invasion dynamics of

non-indigenous plant species (NIPS) along rivers. Riparian ecosystems are of great

importa...

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.

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.

Insights into resource consumption, cross-feeding, system collapse, stability and biodiversity from an artificial ecosystem

PubMed Central

Sumpter, David

2017-01-01

Community ecosystems at very different levels of biological organization often have similar properties. Coexistence of multiple species, cross-feeding, biodiversity and fluctuating population dynamics are just a few of the properties that arise in a range of ecological settings. Here we develop a bottom-up model of consumer–resource interactions, in the form of an artificial ecosystem ‘number soup’, which reflects basic properties of many bacterial and other community ecologies. We demonstrate four key properties of the number soup model: (i) communities self-organize so that all available resources are fully consumed; (ii) reciprocal cross-feeding is a common evolutionary outcome, which evolves in a number of stages, and many transitional species are involved; (iii) the evolved ecosystems are often ‘robust yet fragile’, with keystone species required to prevent the whole system from collapsing; (iv) non-equilibrium dynamics and chaotic patterns are general properties, readily generating rich biodiversity. These properties have been observed in empirical ecosystems, ranging from bacteria to rainforests. Establishing similar properties in an evolutionary model as simple as the number soup suggests that these four properties are ubiquitous features of all community ecosystems, and raises questions about how we interpret ecosystem structure in the context of natural selection. PMID:28100827

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo

2010-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon budgets. Here we use the General Ensemble biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China’s upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to a lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sink/source patterns showed a high degree of spatial heterogeneity. Carbon sinks were associated with forest areas without disturbances, whereas carbon sources were primarily caused by stand-replacing disturbances. It is critical to adequately represent the detailed fast-changing dynamics of land use activities in regional biogeochemical models to determine the spatial and temporal evolution of regional carbon sink/source patterns.

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

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

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

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

Quantifying spatially and temporally explicit CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics

DOE PAGES

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min; ...

2016-07-25

Current terrestrial ecosystem models are usually driven with global average annual atmospheric carbon dioxide (CO 2) concentration data at the global scale. However, high-precision CO 2 measurement from eddy flux towers showed that seasonal, spatial surface atmospheric CO 2 concentration differences were as large as 35 ppmv and the site-level tests indicated that the CO 2 variation exhibited different effects on plant photosynthesis. Here we used a process-based ecosystem model driven with two spatially and temporally explicit CO 2 data sets to analyze the atmospheric CO 2 fertilization effects on the global carbon dynamics of terrestrial ecosystems from 2003 tomore » 2010. Our results demonstrated that CO 2 seasonal variation had a negative effect on plant carbon assimilation, while CO2 spatial variation exhibited a positive impact. When both CO 2 seasonal and spatial effects were considered, global gross primary production and net ecosystem production were 1.7 Pg C•yr –1 and 0.08 Pg C•yr –1 higher than the simulation using uniformly distributed CO 2 data set and the difference was significant in tropical and temperate evergreen broadleaf forest regions. Moreover, this study suggests that the CO 2 observation network should be expanded so that the realistic CO 2 variation can be incorporated into the land surface models to adequately account for CO 2 fertilization effects on global terrestrial ecosystem carbon dynamics.« less

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.

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong, since: (i) No given ecosystem ever is at steady state! (ii) Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

Adressing optimality principles in DGVMs: Dynamics of Carbon allocation changes.

NASA Astrophysics Data System (ADS)

Pietsch, S.

2016-12-01

DGVMs are designed to reproduce and quantify ecosystem processes. Based on plant functions or species specific parameter sets, the energy, carbon, nitrogen and water cycles of different ecosystems are assessed. These models have been proven to be important tools to investigate ecosystem fluxes as they are derived by plant, site and environmental factors. The general model approach assumes steady state conditions and constant model parameters. Both assumptions, however, are wrong. Any given ecosystem never is at steady state! Ecosystems have the capability to adapt to changes in growth conditions, e.g. via changes in allocation patterns! This presentation will give examples how these general failures within current DGVMs may be addressed.

Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

NASA Astrophysics Data System (ADS)

Maslov, Sergei; Sneppen, Kim

2017-01-01

Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity.

Population cycles and species diversity in dynamic Kill-the-Winner model of microbial ecosystems

PubMed Central

Maslov, Sergei; Sneppen, Kim

2017-01-01

Determinants of species diversity in microbial ecosystems remain poorly understood. Bacteriophages are believed to increase the diversity by the virtue of Kill-the-Winner infection bias preventing the fastest growing organism from taking over the community. Phage-bacterial ecosystems are traditionally described in terms of the static equilibrium state of Lotka-Volterra equations in which bacterial growth is exactly balanced by losses due to phage predation. Here we consider a more dynamic scenario in which phage infections give rise to abrupt and severe collapses of bacterial populations whenever they become sufficiently large. As a consequence, each bacterial population in our model follows cyclic dynamics of exponential growth interrupted by sudden declines. The total population of all species fluctuates around the carrying capacity of the environment, making these cycles cryptic. While a subset of the slowest growing species in our model is always driven towards extinction, in general the overall ecosystem diversity remains high. The number of surviving species is inversely proportional to the variation in their growth rates but increases with the frequency and severity of phage-induced collapses. Thus counter-intuitively we predict that microbial communities exposed to more violent perturbations should have higher diversity. PMID:28051127

Modeled interactive effects of precipitation, temperature, and [CO2] on ecosystem carbon and water dynamics in different climatic zones

Treesearch

Yiqi Luo; Dieter Gerten; Guerric Le Maire; William J. Parton; Ensheng Weng; Xuhui Zhou; Cindy Keough; Claus Beier; Philippe Ciais; Wolfgang Cramer; Jeffrey S. Dukes; Bridget Emmett; Paul J. Hanson; Alan Knapp; Sune Linder; Dan Nepstad; Lindsey. Rustad

2008-01-01

Interactive effects of multiple global change factors on ecosystem processes are complex. It is relatively expensive to explore those interactions in manipulative experiments. We conducted a modeling analysis to identify potentially important interactions and to stimulate hypothesis formulation for experimental research. Four models were used to quantify interactive...

Effects of ecological interactions and environmental conditions on community dynamics in an estuarine ecosystem

NASA Astrophysics Data System (ADS)

Liu, H.; Minello, T.; Sutton, G.

2016-02-01

Coastal marine ecosystems are both productive and vulnerable to human and natural stressors. Examining the relative importance of fishing, environmental variability, and habitat alteration on ecosystem dynamics is challenging. Intensive harvest and habitat loss have resulted in widespread concerns related to declines in fisheries production, but causal mechanisms are rarely clear. In this study, we modeled trophic dynamics in Galveston Bay, Texas, using fishery-independent catch data for blue crab, shrimp, red drum, Atlantic croaker and spotted seatrout along with habitat information collected by the Texas Parks and Wildlife Department during 1984 - 2014. We developed a multispecies state-space model to examine ecological interactions and partition the relative effects of trophic interactions and environmental conditions on the community dynamics. Preliminary results showed the importance of salinity, density-dependence, and trophic interactions. We are continuing to explore these results from a perspective of fish community compensatory responses to exploitation, reflecting both direct and indirect effects of harvesting under the influence of climate variability.

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.

Society and Ecosystem Carbon Budget through Life Cycle Assessment: Results from Asian Drylands

NASA Astrophysics Data System (ADS)

Chen, J.

2017-12-01

Land use, land cover changes, and ecosystem-specific management practices are recognized for their roles in mediating the climatic effects on ecosystem structure and function. A major challenge is that our understanding and forecasting of ecosystem functions, such as C fluxes, cannot rely solely on conventional biophysical regulations from the local ecosystem to the global scale. A second challenge lies in quantifying the magnitude of the C fluxes from managed ecosystems and landscapes over the lifetime of the C cycle, and to deduct the various energy inputs during management. Our specific challenge here is to quantify the landscape-scale C footprint of both managed agricultural-forest landscapes and people - the societal input and engagement in ecosystem studies. Using the East Asia Drylands (Chen et al., 2013) and an agricultural watershed in southwestern Michigan as a test bed, the mechanisms (carbon as an example) from both human activities and biophysical changes on ecosystem C dynamics at different temporal and spatial scales are proposed to be explored by modeling total net ecosystem C production (physical and social C fluxes), performing a spatially-explicit life cycle assessment (LCA) on the total C production. Remote sensing technology, available geospatial data, records of management practices, surveys of historical practices, a land surface model, and in situ measurements of C fluxes are all needed to achieve our objectives. Our case study calls for direct involvement of society as both the driver and beneficiary of ecosystem dynamics. Reference Chen, J., Wan, S., Henebry, G., Qi, J., Gutman, G., Sun, G., and Kappas, M. (Eds.) 2013. Dryland East Asia (DEA): Land Dynamics Amid Social And Climate Change. HEP and De Gruyter, 470 pp.

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.

Managing for resilience: an information theory-based ...

EPA Pesticide Factsheets

Ecosystems are complex and multivariate; hence, methods to assess the dynamics of ecosystems should have the capacity to evaluate multiple indicators simultaneously. Most research on identifying leading indicators of regime shifts has focused on univariate methods and simple models which have limited utility when evaluating real ecosystems, particularly because drivers are often unknown. We discuss some common univariate and multivariate approaches for detecting critical transitions in ecosystems and demonstrate their capabilities via case studies. Synthesis and applications. We illustrate the utility of an information theory-based index for assessing ecosystem dynamics. Trends in this index also provide a sentinel of both abrupt and gradual transitions in ecosystems. In response to the need to identify leading indicators of regime shifts in ecosystems, our research compares traditional indicators and Fisher information, an information theory based method, by examining four case study systems. Results demonstrate the utility of methods and offers great promise for quantifying and managing for resilience.

Identifying habitats at risk: simple models can reveal complex ecosystem dynamics.

PubMed

Maxwell, Paul S; Pitt, Kylie A; Olds, Andrew D; Rissik, David; Connolly, Rod M

2015-03-01

The relationship between ecological impact and ecosystem structure is often strongly nonlinear, so that small increases in impact levels can cause a disproportionately large response in ecosystem structure. Nonlinear ecosystem responses can be difficult to predict because locally relevant data sets can be difficult or impossible to obtain. Bayesian networks (BN) are an emerging tool that can help managers to define ecosystem relationships using a range of data types from comprehensive quantitative data sets to expert opinion. We show how a simple BN can reveal nonlinear dynamics in seagrass ecosystems using ecological relationships sourced from the literature. We first developed a conceptual diagram by cataloguing the ecological responses of seagrasses to a range of drivers and impacts. We used the conceptual diagram to develop a BN populated with values sourced from published studies. We then applied the BN to show that the amount of initial seagrass biomass has a mitigating effect on the level of impact a meadow can withstand without loss, and that meadow recovery can often require disproportionately large improvements in impact levels. This mitigating effect resulted in the middle ranges of impact levels having a wide likelihood of seagrass presence, a situation known as bistability. Finally, we applied the model in a case study to identify the risk of loss and the likelihood of recovery for the conservation and management of seagrass meadows in Moreton Bay, Queensland, Australia. We used the model to predict the likelihood of bistability in 23 locations in the Bay. The model predicted bistability in seven locations, most of which have experienced seagrass loss at some stage in the past 25 years providing essential information for potential future restoration efforts. Our results demonstrate the capacity of simple, flexible modeling tools to facilitate collation and synthesis of disparate information. This approach can be adopted in the initial stages of conservation programs as a low-cost and relatively straightforward way to provide preliminary assessments of.nonlinear dynamics in ecosystems.

DRAINMOD-FOREST: Integrated modeling of hydrology, soil carbon and nitrogen dynamics, and plant growth for drained forests

Treesearch

Shiying Tian; Mohamed A. Youssef; R. Wayne Skaggs; Devendra M. Amatya; G.M. Chescheir

2012-01-01

We present a hybrid and stand-level forest ecosystem model, DRAINMOD-FOREST, for simulating the hydrology, carbon (C) and nitrogen (N) dynamics, and tree growth for drained forest lands under common silvicultural practices. The model was developed by linking DRAINMOD, the hydrological model, and DRAINMOD-N II, the soil C and N dynamics model, to a forest growth model,...

Implementing seasonal carbon allocation into a dynamic vegetation model

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Assessing ecosystem response to multiple disturbances and climate change in South Africa using ground- and satellite-based measurements and model

NASA Astrophysics Data System (ADS)

Kutsch, W. L.; Falge, E. M.; Brümmer, C.; Mukwashi, K.; Schmullius, C.; Hüttich, C.; Odipo, V.; Scholes, R. J.; Mudau, A.; Midgley, G.; Stevens, N.; Hickler, T.; Scheiter, S.; Martens, C.; Twine, W.; Iiyambo, T.; Bradshaw, K.; Lück, W.; Lenfers, U.; Thiel-Clemen, T.; du Toit, J.

2015-12-01

Sub-Saharan Africa currently experiences rapidly growing human population, intrinsically tied to substantial changes in land use on shrubland, savanna and mixed woodland ecosystems due to over-exploitation. Significant conversions driving degradation, affecting fire frequency and water availability, and fueling climate change are expected to increase in the immediate future. However, measured data of greenhouse gas emissions as affected by land use change are scarce to entirely lacking from this region. The project 'Adaptive Resilience of Southern African Ecosystems' (ARS AfricaE) conducts research and develops scenarios of ecosystem development under climate change, for management support in conservation or for planning rural area development. This will be achieved by (1) creation of a network of research clusters (paired sites with natural and altered vegetation) along an aridity gradient in South Africa for ground-based micrometeorological in-situ measurements of energy and matter fluxes, (2) linking biogeochemical functions with ecosystem structure, and eco-physiological properties, (3) description of ecosystem disturbance (and recovery) in terms of ecosystem function such as carbon balance components and water use efficiency, (4) set-up of individual-based models to predict ecosystem dynamics under (post) disturbance managements, (5) combination with long-term landscape dynamic information derived from remote sensing and aerial photography, and (6) development of sustainable management strategies for disturbed ecosystems and land use change. Emphasis is given on validation (by a suite of field measurements) of estimates obtained from eddy covariance, model approaches and satellite derivations.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Evaluation of atmospheric aerosol and tropospheric ozone effects on global terrestrial ecosystem carbon dynamics

NASA Astrophysics Data System (ADS)

Chen, Min

The increasing human activities have produced large amounts of air pollutants ejected into the atmosphere, in which atmospheric aerosols and tropospheric ozone are considered to be especially important because of their negative impacts on human health and their impacts on global climate through either their direct radiative effect or indirect effect on land-atmosphere CO2 exchange. This dissertation dedicates to quantifying and evaluating the aerosol and tropospheric ozone effects on global terrestrial ecosystem dynamics using a modeling approach. An ecosystem model, the integrated Terrestrial Ecosystem Model (iTem), is developed to simulate biophysical and biogeochemical processes in terrestrial ecosystems. A two-broad-band atmospheric radiative transfer model together with the Moderate-Resolution Imaging Spectroradiometer (MODIS) measured atmospheric parameters are used to well estimate global downward solar radiation and the direct and diffuse components in comparison with observations. The atmospheric radiative transfer modeling framework were used to quantify the aerosol direct radiative effect, showing that aerosol loadings cause 18.7 and 12.8 W m -2 decrease of direct-beam Photosynthetic Active Radiation (PAR) and Near Infrared Radiation (NIR) respectively, and 5.2 and 4.4 W m -2 increase of diffuse PAR and NIR, respectively, leading to a total 21.9 W m-2 decrease of total downward solar radiation over the global land surface during the period of 2003-2010. The results also suggested that the aerosol effect may be overwhelmed by clouds because of the stronger extinction and scattering ability of clouds. Applications of the iTem with solar radiation data and with or without considering the aerosol loadings shows that aerosol loading enhances the terrestrial productions [Gross Primary Production (GPP), Net Primary Production (NPP) and Net Ecosystem Production (NEP)] and carbon emissions through plant respiration (RA) in global terrestrial ecosystems over the period of 2003-2010. Ecosystem heterotrophic respiration (RH) was negatively affected by the aerosol loading. These results support previous conclusions of the advantage of aerosol light scattering effect on plant productions in other studies but suggest there is strong spatial variation. This study finds indirect aerosol effects on terrestrial ecosystem carbon dynamics through affecting plant phenology, thermal and hydrological environments. All these evidences suggested that the aerosol direct radiative effect on global terrestrial ecosystem carbon dynamics should be considered to better understand the global carbon cycle and climate change. An ozone sub-model is developed in this dissertation and fully coupled with iTem. The coupled model, named iTemO3 considers the processes of ozone stomatal deposition, plant defense to ozone influx, ozone damage and plant repairing mechanism. By using a global atmospheric chemical transport model (GACTM) estimated ground-level ozone concentration data, the model estimated global annual stomatal ozone deposition is 234.0 Tg O3 yr-1 and indicates which regions have high ozone damage risk. Different plant functional types, sunlit and shaded leaves are shown to have different responses to ozone. The model predictions suggest that ozone has caused considerable change on global terrestrial ecosystem carbon storage and carbon exchanges over the study period 2004-2008. The study suggests that uncertainty of the key parameters in iTemO3 could result in large errors in model predictions. Thus more experimental data for better model parameterization is highly needed.

Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

DOE PAGES

Zhu, Qing; Zhuang, Qianlai

2015-12-21

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less

Ecosystem biogeochemistry model parameterization: Do more flux data result in a better model in predicting carbon flux?

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

Zhu, Qing; Zhuang, Qianlai

Reliability of terrestrial ecosystem models highly depends on the quantity and quality of thedata that have been used to calibrate the models. Nowadays, in situ observations of carbon fluxes areabundant. However, the knowledge of how much data (data length) and which subset of the time seriesdata (data period) should be used to effectively calibrate the model is still lacking. This study uses theAmeriFlux carbon flux data to parameterize the Terrestrial Ecosystem Model (TEM) with an adjoint-baseddata assimilation technique for various ecosystem types. Parameterization experiments are thus conductedto explore the impact of both data length and data period on the uncertaintymore » reduction of the posteriormodel parameters and the quantification of site and regional carbon dynamics. We find that: the modelis better constrained when it uses two-year data comparing to using one-year data. Further, two-year datais sufficient in calibrating TEM’s carbon dynamics, since using three-year data could only marginallyimprove the model performance at our study sites; the model is better constrained with the data thathave a higher‘‘climate variability’’than that having a lower one. The climate variability is used to measurethe overall possibility of the ecosystem to experience all climatic conditions including drought and extremeair temperatures and radiation; the U.S. regional simulations indicate that the effect of calibration datalength on carbon dynamics is amplified at regional and temporal scales, leading to large discrepanciesamong different parameterization experiments, especially in July and August. Our findings areconditioned on the specific model we used and the calibration sites we selected. The optimal calibrationdata length may not be suitable for other models. However, this study demonstrates that there may exist athreshold for calibration data length and simply using more data would not guarantee a better modelparameterization and prediction. More importantly, climate variability might be an effective indicator ofinformation within the data, which could help data selection for model parameterization. As a result, we believe ourfindings will benefit the ecosystem modeling community in using multiple-year data to improve modelpredictability.« less

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.

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...

A coupled metabolic-hydraulic model and calibration scheme for estimating of whole-river metabolism during dynamic flow conditions

USGS Publications Warehouse

Payn, Robert A.; Hall, Robert O Jr.; Kennedy, Theodore A.; Poole, Geoff C; Marshall, Lucy A.

2017-01-01

Conventional methods for estimating whole-stream metabolic rates from measured dissolved oxygen dynamics do not account for the variation in solute transport times created by dynamic flow conditions. Changes in flow at hourly time scales are common downstream of hydroelectric dams (i.e. hydropeaking), and hydrologic limitations of conventional metabolic models have resulted in a poor understanding of the controls on biological production in these highly managed river ecosystems. To overcome these limitations, we coupled a two-station metabolic model of dissolved oxygen dynamics with a hydrologic river routing model. We designed calibration and parameter estimation tools to infer values for hydrologic and metabolic parameters based on time series of water quality data, achieving the ultimate goal of estimating whole-river gross primary production and ecosystem respiration during dynamic flow conditions. Our case study data for model design and calibration were collected in the tailwater of Glen Canyon Dam (Arizona, USA), a large hydropower facility where the mean discharge was 325 m3 s 1 and the average daily coefficient of variation of flow was 0.17 (i.e. the hydropeaking index averaged from 2006 to 2016). We demonstrate the coupled model’s conceptual consistency with conventional models during steady flow conditions, and illustrate the potential bias in metabolism estimates with conventional models during unsteady flow conditions. This effort contributes an approach to solute transport modeling and parameter estimation that allows study of whole-ecosystem metabolic regimes across a more diverse range of hydrologic conditions commonly encountered in streams and rivers.

Top-down constraints on disturbance dynamics in the terrestrial carbon cycle: effects at global and regional scales

NASA Astrophysics Data System (ADS)

Bloom, A. A.; Exbrayat, J. F.; van der Velde, I.; Peters, W.; Williams, M.

2014-12-01

Large uncertainties preside over terrestrial carbon flux estimates on a global scale. In particular, the strongly coupled dynamics between net ecosystem productivity and disturbance C losses are poorly constrained. To gain an improved understanding of ecosystem C dynamics from regional to global scale, we apply a Markov Chain Monte Carlo based model-data-fusion approach into the CArbon DAta-MOdel fraMework (CARDAMOM). We assimilate MODIS LAI and burned area, plant-trait data, and use the Harmonized World Soil Database (HWSD) and maps of above ground biomass as prior knowledge for initial conditions. We optimize model parameters based on (a) globally spanning observations and (b) ecological and dynamic constraints that force single parameter values and parameter inter-dependencies to be representative of real world processes. We determine the spatial and temporal dynamics of major terrestrial C fluxes and model parameter values on a global scale (GPP = 123 +/- 8 Pg C yr-1 & NEE = -1.8 +/- 2.7 Pg C yr-1). We further show that the incorporation of disturbance fluxes, and accounting for their instantaneous or delayed effect, is of critical importance in constraining global C cycle dynamics, particularly in the tropics. In a higher resolution case study centred on the Amazon Basin we show how fires not only trigger large instantaneous emissions of burned matter, but also how they are responsible for a sustained reduction of up to 50% in plant uptake following the depletion of biomass stocks. The combination of these two fire-induced effects leads to a 1 g C m-2 d-1reduction in the strength of the net terrestrial carbon sink. Through our simulations at regional and global scale, we advocate the need to assimilate disturbance metrics in global terrestrial carbon cycle models to bridge the gap between globally spanning terrestrial carbon cycle data and the full dynamics of the ecosystem C cycle. Disturbances are especially important because their quick occurrence may have long-term effects on ecosystems. Our synthetic simulations show that while tropical ecosystems uptake may reach pre-disturbance level after a decade, biomass stocks would most likely need more than a century to recover from a single extreme disturbance event.

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...

A landscape based, systems dynamic model for assessing impacts of urban development on water quality for sustainable seagrass growth in Tampa Bay, Florida

EPA Science Inventory

We present an integrated assessment model to predict potential unintended consequences of urban development on the sustainability of seagrasses and preservation of ecosystem services, such as catchable fish, in Tampa Bay. Ecosystem services are those ecological functions and pro...

Ecosystem dynamics and disturbance in mountain wildernesses: assessing vulnerability of natural resources to change

Treesearch

Daniel B. Fagre; David L. Peterson

2000-01-01

An integrated program of ecosystem modeling and extensive field studies at Glacier and Olympic National Parks has quantified many of the ecological processes affected by climatic variability and disturbance. Models have successfully estimated snow distribution, annual watershed discharge, and stream temperature variation based on seven years of monitoring. Various...

Fort Collins Science Center Ecosystem Dynamics branch--interdisciplinary research for addressing complex natural resource issues across landscapes and time

USGS Publications Warehouse

Bowen, Zachary H.; Melcher, Cynthia P.; Wilson, Juliette T.

2013-01-01

The Ecosystem Dynamics Branch of the Fort Collins Science Center offers an interdisciplinary team of talented and creative scientists with expertise in biology, botany, ecology, geology, biogeochemistry, physical sciences, geographic information systems, and remote-sensing, for tackling complex questions about natural resources. As demand for natural resources increases, the issues facing natural resource managers, planners, policy makers, industry, and private landowners are increasing in spatial and temporal scope, often involving entire regions, multiple jurisdictions, and long timeframes. Needs for addressing these issues include (1) a better understanding of biotic and abiotic ecosystem components and their complex interactions; (2) the ability to easily monitor, assess, and visualize the spatially complex movements of animals, plants, water, and elements across highly variable landscapes; and (3) the techniques for accurately predicting both immediate and long-term responses of system components to natural and human-caused change. The overall objectives of our research are to provide the knowledge, tools, and techniques needed by the U.S. Department of the Interior, state agencies, and other stakeholders in their endeavors to meet the demand for natural resources while conserving biodiversity and ecosystem services. Ecosystem Dynamics scientists use field and laboratory research, data assimilation, and ecological modeling to understand ecosystem patterns, trends, and mechanistic processes. This information is used to predict the outcomes of changes imposed on species, habitats, landscapes, and climate across spatiotemporal scales. The products we develop include conceptual models to illustrate system structure and processes; regional baseline and integrated assessments; predictive spatial and mathematical models; literature syntheses; and frameworks or protocols for improved ecosystem monitoring, adaptive management, and program evaluation. The descriptions in this fact sheet provide snapshots of our three research emphases, followed by descriptions of select current projects.

Benchmarking Terrestrial Ecosystem Models in the South Central US

NASA Astrophysics Data System (ADS)

Kc, M.; Winton, K.; Langston, M. A.; Luo, Y.

2016-12-01

Ecosystem services and products are the foundation of sustainability for regional and global economy since we are directly or indirectly dependent on the ecosystem services like food, livestock, water, air, wildlife etc. It has been increasingly recognized that for sustainability concerns, the conservation problems need to be addressed in the context of entire ecosystems. This approach is even more vital in the 21st century with formidable increasing human population and rapid changes in global environment. This study was conducted to find the state of the science of ecosystem models in the South-Central region of US. The ecosystem models were benchmarked using ILAMB diagnostic package developed as a result of International Land Model Benchmarking (ILAMB) project on four main categories; viz, Ecosystem and Carbon Cycle, Hydrology Cycle, Radiation and Energy Cycle and Climate forcings. A cumulative assessment was generated with weighted seven different skill assessment metrics for the ecosystem models. This synthesis on the current state of the science of ecosystem modeling in the South-Central region of US will be highly useful towards coupling these models with climate, agronomic, hydrologic, economic or management models to better represent ecosystem dynamics as affected by climate change and human activities; and hence gain more reliable predictions of future ecosystem functions and service in the region. Better understandings of such processes will increase our ability to predict the ecosystem responses and feedbacks to environmental and human induced change in the region so that decision makers can make an informed management decisions of the ecosystem.

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.

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

Treesearch

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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.

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.

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...

Devil's in the details: Using archaeological and historical data to refine ecosystem models at the local level

Treesearch

Don Hann

2006-01-01

The United States Forest Service is charged with managing extensive and varied ecosystems throughout the country. Under the rubric of “ecosystem management” the goal has been to provide goods and services from Forest Service lands while maintaining ecological integrity. Recognizing that ecosystems are dynamic in nature, the concept of Historical Range of Variability (...

Probabilistic model predicts dynamics of vegetation biomass in a desert ecosystem in NW China

PubMed Central

Wang, Xin-ping; Schaffer, Benjamin Eli; Yang, Zhenlei; Rodriguez-Iturbe, Ignacio

2017-01-01

The temporal dynamics of vegetation biomass are of key importance for evaluating the sustainability of arid and semiarid ecosystems. In these ecosystems, biomass and soil moisture are coupled stochastic variables externally driven, mainly, by the rainfall dynamics. Based on long-term field observations in northwestern (NW) China, we test a recently developed analytical scheme for the description of the leaf biomass dynamics undergoing seasonal cycles with different rainfall characteristics. The probabilistic characterization of such dynamics agrees remarkably well with the field measurements, providing a tool to forecast the changes to be expected in biomass for arid and semiarid ecosystems under climate change conditions. These changes will depend—for each season—on the forecasted rate of rainy days, mean depth of rain in a rainy day, and duration of the season. For the site in NW China, the current scenario of an increase of 10% in rate of rainy days, 10% in mean rain depth in a rainy day, and no change in the season duration leads to forecasted increases in mean leaf biomass near 25% in both seasons. PMID:28584097

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.

Alternative stable states and the sustainability of forests, grasslands, and agriculture

PubMed Central

Henderson, Kirsten A.; Bauch, Chris T.; Anand, Madhur

2016-01-01

Endangered forest–grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human–environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations—especially for forests—due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human–environment mosaic ecosystems. PMID:27956605

Alternative stable states and the sustainability of forests, grasslands, and agriculture.

PubMed

Henderson, Kirsten A; Bauch, Chris T; Anand, Madhur

2016-12-20

Endangered forest-grassland mosaics interspersed with expanding agriculture and silviculture occur across many parts of the world, including the southern Brazilian highlands. This natural mosaic ecosystem is thought to reflect alternative stable states driven by threshold responses of recruitment to fire and moisture regimes. The role of adaptive human behavior in such systems remains understudied, despite its pervasiveness and the fact that such ecosystems can exhibit complex dynamics. We develop a nonlinear mathematical model of coupled human-environment dynamics in mosaic systems and social processes regarding conservation and economic land valuation. Our objective is to better understand how the coupled dynamics respond to changes in ecological and social conditions. The model is parameterized with southern Brazilian data on mosaic ecology, land-use profits, and questionnaire results concerning landowner preferences and conservation values. We find that the mosaic presently resides at a crucial juncture where relatively small changes in social conditions can generate a wide variety of possible outcomes, including complete loss of mosaics; large-amplitude, long-term oscillations between land states that preclude ecosystem stability; and conservation of the mosaic even to the exclusion of agriculture/silviculture. In general, increasing the time horizon used for conservation decision making is more likely to maintain mosaic stability. In contrast, increasing the inherent conservation value of either forests or grasslands is more likely to induce large oscillations-especially for forests-due to feedback from rarity-based conservation decisions. Given the potential for complex dynamics, empirically grounded nonlinear dynamical models should play a larger role in policy formulation for human-environment mosaic ecosystems.

Modelling the pelagic nitrogen cycle and vertical particle flux in the Norwegian sea

NASA Astrophysics Data System (ADS)

Haupt, Olaf J.; Wolf, Uli; v. Bodungen, Bodo

1999-02-01

A 1D Eulerian ecosystem model (BIological Ocean Model) for the Norwegian Sea was developed to investigate the dynamics of pelagic ecosystems. The BIOM combines six biochemical compartments and simulates the annual nitrogen cycle with specific focus on production, modification and sedimentation of particles in the water column. The external forcing and physical framework is based on a simulated annual cycle of global radiation and an annual mixed-layer cycle derived from field data. The vertical resolution of the model is given by an exponential grid with 200 depth layers, allowing specific parameterization of various sinking velocities, breakdown of particles and the remineralization processes. The aim of the numerical experiments is the simulation of ecosystem dynamics considering the specific biogeochemical properties of the Norwegian Sea, for example the life cycle of the dominant copepod Calanus finmarchicus. The results of the simulations were validated with field data. Model results are in good agreement with field data for the lower trophic levels of the food web. With increasing complexity of the organisms the differences increase between simulated processes and field data. Results of the numerical simulations suggest that BIOM is well adapted to investigate a physically controlled ecosystem. The simulation of grazing controlled pelagic ecosystems, like the Norwegian Sea, requires adaptations of parameterization to the specific ecosystem features. By using seasonally adaptation of the most sensible processes like utilization of light by phytoplankton and grazing by zooplankton results were greatly improved.

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.

Effects of disturbance and climate change on ecosystem performance in the Yukon River Basin boreal forest

USGS Publications Warehouse

Wylie, Bruce K.; Rigge, Matthew B.; Brisco, Brian; Mrnaghan, Kevin; Rover, Jennifer R.; Long, Jordan

2014-01-01

A warming climate influences boreal forest productivity, dynamics, and disturbance regimes. We used ecosystem models and 250 m satellite Normalized Difference Vegetation Index (NDVI) data averaged over the growing season (GSN) to model current, and estimate future, ecosystem performance. We modeled Expected Ecosystem Performance (EEP), or anticipated productivity, in undisturbed stands over the 2000–2008 period from a variety of abiotic data sources, using a rule-based piecewise regression tree. The EEP model was applied to a future climate ensemble A1B projection to quantify expected changes to mature boreal forest performance. Ecosystem Performance Anomalies (EPA), were identified as the residuals of the EEP and GSN relationship and represent performance departures from expected performance conditions. These performance data were used to monitor successional events following fire. Results suggested that maximum EPA occurs 30–40 years following fire, and deciduous stands generally have higher EPA than coniferous stands. Mean undisturbed EEP is projected to increase 5.6% by 2040 and 8.7% by 2070, suggesting an increased deciduous component in boreal forests. Our results contribute to the understanding of boreal forest successional dynamics and its response to climate change. This information enables informed decisions to prepare for, and adapt to, climate change in the Yukon River Basin forest.

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

USGS Publications Warehouse

Bestelmeyer, Brandon T.; Williamson, Jeb C.; Talbot, Curtis J.; Cates, Greg W.; Duniway, Michael C.; Brown, Joel R.

2016-01-01

State-and-transition models (STMs) are useful tools for management, but they can be difficult to use and have limited content.STMs created for groups of related ecological sites could simplify and improve their utility. The amount of information linked to models can be increased using tables that communicate management interpretations and important within-group variability.We created a new web-based information system (the Ecosystem Dynamics Interpretive Tool) to house STMs, associated tabular information, and other ecological site data and descriptors.Fewer, more informative, better organized, and easily accessible STMs should increase the accessibility of science information.

A sensor fusion field experiment in forest ecosystem dynamics

NASA Technical Reports Server (NTRS)

Smith, James A.; Ranson, K. Jon; Williams, Darrel L.; Levine, Elissa R.; Goltz, Stewart M.

1990-01-01

The background of the Forest Ecosystem Dynamics field campaign is presented, a progress report on the analysis of the collected data and related modeling activities is provided, and plans for future experiments at different points in the phenological cycle are outlined. The ecological overview of the study site is presented, and attention is focused on forest stands, needles, and atmospheric measurements. Sensor deployment and thermal and microwave observations are discussed, along with two examples of the optical radiation measurements obtained during the experiment in support of radiative transfer modeling. Future activities pertaining to an archival system, synthetic aperture radar, carbon acquisition modeling, and upcoming field experiments are considered.

Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change

Treesearch

Eric J. Gustafson; Arjan M.G. De Bruijn; Robert E. Pangle; Jean-Marc Limousin; Nate G. McDowell; William T. Pockman; Brian R. Sturtevant; Jordan D. Muss; Mark E. Kubiske

2015-01-01

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and...

Improving the effectiveness of ecological site descriptions: General state-and-transition models and the Ecosystem Dynamics Interpretive Tool (EDIT)

USDA-ARS?s Scientific Manuscript database

State-and-transition models (STMs) were conceived as a means to organize and communicate information about ecosystem changes and how to manage them. Information within STMs applies to ecological land classes, such as ecological sites, that possess similar vegetation states. The value of STMs for ran...

Comparing simple respiration models for eddy flux and dynamic chamber data

Treesearch

Andrew D. Richardson; Bobby H. Braswell; David Y. Hollinger; Prabir Burman; Eric A. Davidson; Robert S. Evans; Lawrence B. Flanagan; J. William Munger; Kathleen Savage; Shawn P. Urbanski; Steven C. Wofsy

2006-01-01

Selection of an appropriate model for respiration (R) is important for accurate gap-filling of CO2 flux data, and for partitioning measurements of net ecosystem exchange (NEE) to respiration and gross ecosystem exchange (GEE). Using cross-validation methods and a version of Akaike's Information Criterion (AIC), we evaluate a wide range of...

Spiraling down the river continuum: stream ecology and the U-shaped curve

Treesearch

Jackson R. Webster

2007-01-01

The spiraling concept provides an explicit approach to modeling the longitudinal linkages within a river continuum. I developed a spiraling-based model for particulate organic C dynamics in the Little Tennessee River to synthesize existing data and to illustrate our current understanding of ecosystem processes in river ecosystems. The Little Tennessee River is a medium...

Modelling multi-species interactions in the Barents Sea ecosystem with special emphasis on minke whales and their interactions with cod, herring and capelin

NASA Astrophysics Data System (ADS)

Lindstrøm, Ulf; Smout, Sophie; Howell, Daniel; Bogstad, Bjarte

2009-10-01

The Barents Sea ecosystem, one of the most productive and commercially important ecosystems in the world, has experienced major fluctuations in species abundance the past five decades. Likely causes are natural variability, climate change, overfishing and predator-prey interactions. In this study, we use an age-length structured multi-species model (Gadget, Globally applicable Area-Disaggregated General Ecosystem Toolbox) to analyse the historic population dynamics of major fish and marine mammal species in the Barents Sea. The model was used to examine possible effects of a number of plausible biological and fisheries scenarios. The results suggest that changes in cod mortality from fishing or cod cannibalism levels have the largest effect on the ecosystem, while changes to the capelin fishery have had only minor effects. Alternate whale migration scenarios had only a moderate impact on the modelled ecosystem. Indirect effects are seen to be important, with cod fishing pressure, cod cannibalism and whale predation on cod having an indirect impact on capelin, emphasising the importance of multi-species modelling in understanding and managing ecosystems. Models such as the one presented here provide one step towards an ecosystem-based approach to fisheries management.

Treating powerless minorities through an ecosystem approach.

PubMed

Chung, W S; Pardeck, J T

1997-01-01

An ecological approach to social work practice for a minority based on an ecosystem-oriented assessment-intervention model is presented. Strengths and limitations of the ecological perspective for practice are emphasized (in the context of power dynamics). A case study is presented.

Conceptualizing Stakeholders' Perceptions of Ecosystem Services: A Participatory Systems Mapping Approach

NASA Astrophysics Data System (ADS)

Lopes, Rita; Videira, Nuno

2015-12-01

A participatory system dynamics modelling approach is advanced to support conceptualization of feedback processes underlying ecosystem services and to foster a shared understanding of leverage intervention points. The process includes systems mapping workshop and follow-up tasks aiming at the collaborative construction of causal loop diagrams. A case study developed in a natural area in Portugal illustrates how a stakeholder group was actively engaged in the development of a conceptual model depicting policies for sustaining the climate regulation ecosystem service.

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.

Ecosystem performance monitoring of rangelands by integrating modeling and remote sensing

USGS Publications Warehouse

Wylie, Bruce K.; Boyte, Stephen P.; Major, Donald J.

2012-01-01

Monitoring rangeland ecosystem dynamics, production, and performance is valuable for researchers and land managers. However, ecosystem monitoring studies can be difficult to interpret and apply appropriately if management decisions and disturbances are inseparable from the ecosystem's climate signal. This study separates seasonal weather influences from influences caused by disturbances and management decisions, making interannual time-series analysis more consistent and interpretable. We compared the actual ecosystem performance (AEP) of five rangeland vegetation types in the Owyhee Uplands for 9 yr to their expected ecosystem performance (EEP). Integrated growing season Normalized Difference Vegetation Index data for each of the nine growing seasons served as a proxy for annual AEP. Regression-tree models used long-term site potential, seasonal weather, and land cover data sets to generate annual EEP, an estimate of ecosystem performance incorporating annual weather variations. The difference between AEP and EEP provided a performance measure for each pixel in the study area. Ecosystem performance anomalies occurred when the ecosystem performed significantly better or worse than the model predicted. About 14% of the Owyhee Uplands showed a trend of significant underperformance or overperformance (P<0.10). Land managers can use results from weather-based rangeland ecosystem performance models to help support adaptive management strategies.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Dynamics of Active Layer Depth across Alaskan Tundra Ecosystems

NASA Astrophysics Data System (ADS)

Ma, C.; Zhang, X.; Song, X.; Xu, X.

2016-12-01

The thickness of the active layer, near-surface layer of Earth material above permafrost undergoing seasonal freezing and thawing, is of considerable importance in high-latitude environments because most physical, chemical, and biological processes in the permafrost region take place within it. The dynamics of active layer thickness (ALT) result from a combination of various factors including heat transfer, soil water content, soil texture, root density, stem density, moss layer thickness, organic layer thickness, etc. However, the magnitude and controls of ALT in the permafrost region remain uncertain. The purpose of this study is to improve our understanding of the dynamics of ALT across Alaskan tundra ecosystems and their controls at multiple scales, ranging from plots to entire Alaska. This study compiled a comprehensive dataset of ALT at site and regional scales across the Alaskan tundra ecosystems, and further analyzed ALT dynamics and their hierarchical controls. We found that air temperature played a predominant role on the seasonality of ALT, regulated by other physical and chemical factors including soil texture, moisture, and root density. The structural equation modeling (SEM) analysis confirmed the predominant role of physical controls (dominated by heat and soil properties), followed by chemical and biological factors. Then a simple empirical model was developed to reconstruct the ALT across the Alaska. The comparisons against field observational data show that the method used in this study is robust; the reconstructed time-series ALT across Alaska provides a valuable dataset source for understanding ALT and validating large-scale ecosystem models.

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

Global variation of carbon use efficiency in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Tang, Xiaolu; Carvalhais, Nuno; Moura, Catarina; Reichstein, Markus

2017-04-01

Carbon use efficiency (CUE), defined as the ratio between net primary production (NPP) and gross primary production (GPP), is an emergent property of vegetation that describes its effectiveness in storing carbon (C) and is of significance for understanding C biosphere-atmosphere exchange dynamics. A constant CUE value of 0.5 has been widely used in terrestrial C-cycle models, such as the Carnegie-Ames-Stanford-Approach model, or the Marine Biological Laboratory/Soil Plant-Atmosphere Canopy Model, for regional or global modeling purposes. However, increasing evidence argues that CUE is not constant, but varies with ecosystem types, site fertility, climate, site management and forest age. Hence, the assumption of a constant CUE of 0.5 can produce great uncertainty in estimating global carbon dynamics between terrestrial ecosystems and the atmosphere. Here, in order to analyze the global variations in CUE and understand how CUE varies with environmental variables, a global database was constructed based on published data for crops, forests, grasslands, wetlands and tundra ecosystems. In addition to CUE data, were also collected: GPP and NPP; site variables (e.g. climate zone, site management and plant function type); climate variables (e.g. temperature and precipitation); additional carbon fluxes (e.g. soil respiration, autotrophic respiration and heterotrophic respiration); and carbon pools (e.g. stem, leaf and root biomass). Different climate metrics were derived to diagnose seasonal temperature (mean annual temperature, MAT, and maximum temperature, Tmax) and water availability proxies (mean annual precipitation, MAP, and Palmer Drought Severity Index), in order to improve the local representation of environmental variables. Additionally were also included vegetation phenology dynamics as observed by different vegetation indices from the MODIS satellite. The mean CUE of all terrestrial ecosystems was 0.45, 10% lower than the previous assumed constant CUE of 0.50. CUE varied significantly between sites - from 0.13 to 0.93 - and between ecosystem types, ranging between 0.41 and 0.60, decreasing from wetlands, to tundra, to croplands, to grasslands until the lower CUE found on average for forested ecosystems. Our analysis shows that ecosystem type was the most important predictor of CUE in terrestrial ecosystems, immediately followed by Tmax; MAT and management practices. For crop, forest and wetland ecosystems CUE varied with climate zones and a strong linear negative correlation was found between CUE and MAT and MAP for grassland ecosystems. Overall, the interaction between different environmental variables showed significant effects on CUE for all ecosystem types. Our results challenge the consideration of a constant value of 0.5 for modeling global purposes, and argue for a deeper understanding of environmental controls on CUE for different ecosystem types.

Integrating ecophysiology and forest landscape models to improve projections of drought effects under climate change.

PubMed

Gustafson, Eric J; De Bruijn, Arjan M G; Pangle, Robert E; Limousin, Jean-Marc; McDowell, Nate G; Pockman, William T; Sturtevant, Brian R; Muss, Jordan D; Kubiske, Mark E

2015-02-01

Fundamental drivers of ecosystem processes such as temperature and precipitation are rapidly changing and creating novel environmental conditions. Forest landscape models (FLM) are used by managers and policy-makers to make projections of future ecosystem dynamics under alternative management or policy options, but the links between the fundamental drivers and projected responses are weak and indirect, limiting their reliability for projecting the impacts of climate change. We developed and tested a relatively mechanistic method to simulate the effects of changing precipitation on species competition within the LANDIS-II FLM. Using data from a field precipitation manipulation experiment in a piñon pine (Pinus edulis) and juniper (Juniperus monosperma) ecosystem in New Mexico (USA), we calibrated our model to measurements from ambient control plots and tested predictions under the drought and irrigation treatments against empirical measurements. The model successfully predicted behavior of physiological variables under the treatments. Discrepancies between model output and empirical data occurred when the monthly time step of the model failed to capture the short-term dynamics of the ecosystem as recorded by instantaneous field measurements. We applied the model to heuristically assess the effect of alternative climate scenarios on the piñon-juniper ecosystem and found that warmer and drier climate reduced productivity and increased the risk of drought-induced mortality, especially for piñon. We concluded that the direct links between fundamental drivers and growth rates in our model hold great promise to improve our understanding of ecosystem processes under climate change and improve management decisions because of its greater reliance on first principles. Published 2014. This article is a U.S. Government work and is in the public domain in the USA.

Effects of nitrogen deposition on carbon cycle in terrestrial ecosystems of China: A meta-analysis.

PubMed

Chen, Hao; Li, Dejun; Gurmesa, Geshere A; Yu, Guirui; Li, Linghao; Zhang, Wei; Fang, Huajun; Mo, Jiangming

2015-11-01

Nitrogen (N) deposition in China has increased greatly, but the general impact of elevated N deposition on carbon (C) dynamics in Chinese terrestrial ecosystems is not well documented. In this study we used a meta-analysis method to compile 88 studies on the effects of N deposition C cycling on Chinese terrestrial ecosystems. Our results showed that N addition did not change soil C pools but increased above-ground plant C pool. A large decrease in below-ground plant C pool was observed. Our result also showed that the impacts of N addition on ecosystem C dynamics depend on ecosystem type and rate of N addition. Overall, our findings suggest that 1) decreased below-ground plant C pool may limit long-term soil C sequestration; and 2) it is better to treat N-rich and N-limited ecosystems differently in modeling effects of N deposition on ecosystem C cycle. Copyright © 2015 Elsevier Ltd. All rights reserved.

The changing global carbon cycle: Linking plant-soil carbon dynamics to global consequences

USGS Publications Warehouse

Chapin, F. S.; McFarland, J.; McGuire, David A.; Euskirchen, E.S.; Ruess, Roger W.; Kielland, K.

2009-01-01

Synthesis. Current climate systems models that include only NPP and HR are inadequate under conditions of rapid change. Many of the recent advances in biogeochemical understanding are sufficiently mature to substantially improve representation of ecosystem C dynamics in these models.

Understanding ecohydrological connectivity in savannas: A system dynamics modeling approach

USDA-ARS?s Scientific Manuscript database

Ecohydrological connectivity is a system-level property that results from the linkages in the networks of water transport through ecosystems, by which feedback effects and other emergent system behaviors may be generated. We created a systems dynamic model that represents primary ecohydrological net...

Hydrological regulation drives regime shifts: evidence from paleolimnology and ecosystem modeling of a large shallow Chinese lake.

PubMed

Kong, Xiangzhen; He, Qishuang; Yang, Bin; He, Wei; Xu, Fuliu; Janssen, Annette B G; Kuiper, Jan J; van Gerven, Luuk P A; Qin, Ning; Jiang, Yujiao; Liu, Wenxiu; Yang, Chen; Bai, Zelin; Zhang, Min; Kong, Fanxiang; Janse, Jan H; Mooij, Wolf M

2017-02-01

Quantitative evidence of sudden shifts in ecological structure and function in large shallow lakes is rare, even though they provide essential benefits to society. Such 'regime shifts' can be driven by human activities which degrade ecological stability including water level control (WLC) and nutrient loading. Interactions between WLC and nutrient loading on the long-term dynamics of shallow lake ecosystems are, however, often overlooked and largely underestimated, which has hampered the effectiveness of lake management. Here, we focus on a large shallow lake (Lake Chaohu) located in one of the most densely populated areas in China, the lower Yangtze River floodplain, which has undergone both WLC and increasing nutrient loading over the last several decades. We applied a novel methodology that combines consistent evidence from both paleolimnological records and ecosystem modeling to overcome the hurdle of data insufficiency and to unravel the drivers and underlying mechanisms in ecosystem dynamics. We identified the occurrence of two regime shifts: one in 1963, characterized by the abrupt disappearance of submerged vegetation, and another around 1980, with strong algal blooms being observed thereafter. Using model scenarios, we further disentangled the roles of WLC and nutrient loading, showing that the 1963 shift was predominantly triggered by WLC, whereas the shift ca. 1980 was attributed to aggravated nutrient loading. Our analysis also shows interactions between these two stressors. Compared to the dynamics driven by nutrient loading alone, WLC reduced the critical P loading and resulted in earlier disappearance of submerged vegetation and emergence of algal blooms by approximately 26 and 10 years, respectively. Overall, our study reveals the significant role of hydrological regulation in driving shallow lake ecosystem dynamics, and it highlights the urgency of using multi-objective management criteria that includes ecological sustainability perspectives when implementing hydrological regulation for aquatic ecosystems around the globe. © 2016 John Wiley & Sons Ltd.

Forest forming process and dynamic vegetation models under global change

Treesearch

A. Shvidenko; E. Gustafson

2009-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Global changes in biogeochemical cycles in response to human activities

NASA Technical Reports Server (NTRS)

Moore, Berrien, III; Melillo, Jerry

1994-01-01

The main objective of our research was to characterize biogeochemical cycles at continental and global scales in both terrestrial and aquatic ecosystems. This characterization applied to both natural ecosystems and those disturbed by human activity. The primary elements of interest were carbon and nitrogen and the analysis sought to quantify standing stocks and dynamic cycling processes. The translocation of major nutrients from the terrestrial landscape to the atmosphere (via trace gases) and to fluvial systems (via leaching, erosional losses, and point source pollution) were of particular importance to this study. Our aim was to develop the first generation of Earth System Models. Our research was organized around the construction and testing of component biogeochemical models which treated terrestrial ecosystem processes, aquatic nutrient transport through drainage basins, and trace gas exchanges at the continental and global scale. A suite of three complementary models were defined within this construct. The models were organized to operate at a 1/2 degree latitude by longitude level of spatial resolution and to execute at a monthly time step. This discretization afforded us the opportunity to understand the dynamics of the biosphere down to subregional scales, while simultaneously placing these dynamics into a global context.

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.

A coordinated set of ecosystem research platforms open to international research in ecotoxicology, AnaEE-France.

PubMed

Mougin, Christian; Azam, Didier; Caquet, Thierry; Cheviron, Nathalie; Dequiedt, Samuel; Le Galliard, Jean-François; Guillaume, Olivier; Houot, Sabine; Lacroix, Gérard; Lafolie, François; Maron, Pierre-Alain; Michniewicz, Radika; Pichot, Christian; Ranjard, Lionel; Roy, Jacques; Zeller, Bernd; Clobert, Jean; Chanzy, André

2015-10-01

The infrastructure for Analysis and Experimentation on Ecosystems (AnaEE-France) is an integrated network of the major French experimental, analytical, and modeling platforms dedicated to the biological study of continental ecosystems (aquatic and terrestrial). This infrastructure aims at understanding and predicting ecosystem dynamics under global change. AnaEE-France comprises complementary nodes offering access to the best experimental facilities and associated biological resources and data: Ecotrons, seminatural experimental platforms to manipulate terrestrial and aquatic ecosystems, in natura sites equipped for large-scale and long-term experiments. AnaEE-France also provides shared instruments and analytical platforms dedicated to environmental (micro) biology. Finally, AnaEE-France provides users with data bases and modeling tools designed to represent ecosystem dynamics and to go further in coupling ecological, agronomical, and evolutionary approaches. In particular, AnaEE-France offers adequate services to tackle the new challenges of research in ecotoxicology, positioning its various types of platforms in an ecologically advanced ecotoxicology approach. AnaEE-France is a leading international infrastructure, and it is pioneering the construction of AnaEE (Europe) infrastructure in the field of ecosystem research. AnaEE-France infrastructure is already open to the international community of scientists in the field of continental ecotoxicology.

Phosphorus Dynamics in Flooded Wetlands: I. Model Development and Sensitivity Analysis

EPA Science Inventory

Wetlands are unique ecosystems that are recognized as a transition between terrestrial and aquatic ecosystems. Wetlands provide habitats that support wildlife and biodiversity and act as natural purifiers for sediment and nutrient laden runoff from upland regions. They receive,...

Exploring tropical forest vegetation dynamics using the FATES model

NASA Astrophysics Data System (ADS)

Koven, C. D.; Fisher, R.; Knox, R. G.; Chambers, J.; Kueppers, L. M.; Christoffersen, B. O.; Davies, S. J.; Dietze, M.; Holm, J.; Massoud, E. C.; Muller-Landau, H. C.; Powell, T.; Serbin, S.; Shuman, J. K.; Walker, A. P.; Wright, S. J.; Xu, C.

2017-12-01

Tropical forest vegetation dynamics represent a critical climate feedback in the Earth system, which is poorly represented in current global modeling approaches. We discuss recent progress on exploring these dynamics using the Functionally Assembled Terrestrial Ecosystem Simulator (FATES), a demographic vegetation model for the CESM and ACME ESMs. We will discuss benchmarks of FATES predictions for forest structure against inventory sites, sensitivity of FATES predictions of size and age structure to model parameter uncertainty, and experiments using the FATES model to explore PFT competitive dynamics and the dynamics of size and age distributions in responses to changing climate and CO2.

Predicting future US water yield and ecosystem productivity by linking an ecohydrological model to WRF dynamically downscaled climate projections

Treesearch

S. Sun; Ge Sun; Erika Cohen Mack; Steve McNulty; Peter Caldwell; K. Duan; Y. Zhang

2015-01-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity (i.e., carbon balances) is essential to developing sound watershed restoration plans, and climate change adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model)...

Linking degradation status with ecosystem vulnerability to environmental change

USGS Publications Warehouse

Angeler, David G.; Baho, Didier L.; Allen, Craig R.; Johnson, Richard K.

2015-01-01

Environmental change can cause regime shifts in ecosystems, potentially threatening ecosystem services. It is unclear if the degradation status of ecosystems correlates with their vulnerability to environmental change, and thus the risk of future regime shifts. We assessed resilience in acidified (degraded) and circumneutral (undegraded) lakes with long-term data (1988–2012), using time series modeling. We identified temporal frequencies in invertebrate assemblages, which identifies groups of species whose population dynamics vary at particular temporal scales. We also assessed species with stochastic dynamics, those whose population dynamics vary irregularly and unpredictably over time. We determined the distribution of functional feeding groups of invertebrates within and across the temporal scales identified, and in those species with stochastic dynamics, and assessed attributes hypothesized to contribute to resilience. Three patterns of temporal dynamics, consistent across study lakes, were identified in the invertebrates. The first pattern was one of monotonic change associated with changing abiotic lake conditions. The second and third patterns appeared unrelated to the environmental changes we monitored. Acidified and the circumneutral lakes shared similar levels and patterns of functional richness, evenness, diversity, and redundancy for species within and across the observed temporal scales and for stochastic species groups. These similar resilience characteristics suggest that both lake types did not differ in vulnerability to the environmental changes observed here. Although both lake types appeared equally vulnerable in this study, our approach demonstrates how assessing systemic vulnerability by quantifying ecological resilience can help address uncertainty in predicting ecosystem responses to environmental change across ecosystems.

Sustainable exploitation and management of autogenic ecosystem engineers: application to oysters in Chesapeake Bay.

PubMed

Wilberg, Michael J; Wiedenmann, John R; Robinson, Jason M

2013-06-01

Autogenic ecosystem engineers are critically important parts of many marine and estuarine systems because of their substantial effect on ecosystem services. Oysters are of particular importance because of their capacity to modify coastal and estuarine habitats and the highly degraded status of their habitats worldwide. However, models to predict dynamics of ecosystem engineers have not previously included the effects of exploitation. We developed a linked population and habitat model for autogenic ecosystem engineers undergoing exploitation. We parameterized the model to represent eastern oyster (Crassostrea virginica) in upper Chesapeake Bay by selecting sets of parameter values that matched observed rates of change in abundance and habitat. We used the model to evaluate the effects of a range of management and restoration options including sustainability of historical fishing pressure, effectiveness of a newly enacted sanctuary program, and relative performance of two restoration approaches. In general, autogenic ecosystem engineers are expected to be substantially less resilient to fishing than an equivalent species that does not rely on itself for habitat. Historical fishing mortality rates in upper Chesapeake Bay for oysters were above the levels that would lead to extirpation. Reductions in fishing or closure of the fishery were projected to lead to long-term increases in abundance and habitat. For fisheries to become sustainable outside of sanctuaries, a substantial larval subsidy would be required from oysters within sanctuaries. Restoration efforts using high-relief reefs were predicted to allow recovery within a shorter period of time than low-relief reefs. Models such as ours, that allow for feedbacks between population and habitat dynamics, can be effective tools for guiding management and restoration of autogenic ecosystem engineers.

Inter-annual variability of carbon fluxes in temperate forest ecosystems: effects of biotic and abiotic factors

NASA Astrophysics Data System (ADS)

Chen, M.; Keenan, T. F.; Hufkens, K.; Munger, J. W.; Bohrer, G.; Brzostek, E. R.; Richardson, A. D.

2014-12-01

Carbon dynamics in terrestrial ecosystems are influenced by both abiotic and biotic factors. Abiotic factors, such as variation in meteorological conditions, directly drive biophysical and biogeochemical processes; biotic factors, referring to the inherent properties of the ecosystem components, reflect the internal regulating effects including temporal dynamics and memory. The magnitude of the effect of abiotic and biotic factors on forest ecosystem carbon exchange has been suggested to vary at different time scales. In this study, we design and conduct a model-data fusion experiment to investigate the role and relative importance of the biotic and abiotic factors for inter-annual variability of the net ecosystem CO2 exchange (NEE) of temperate deciduous forest ecosystems in the Northeastern US. A process-based model (FöBAAR) is parameterized at four eddy-covariance sites using all available flux and biometric measurements. We conducted a "transplant" modeling experiment, that is, cross- site and parameter simulations with different combinations of site meteorology and parameters. Using wavelet analysis and variance partitioning techniques, analysis of model predictions identifies both spatial variant and spatially invariant parameters. Variability of NEE was primarily modulated by gross primary productivity (GPP), with relative contributions varying from hourly to yearly time scales. The inter-annual variability of GPP and NEE is more regulated by meteorological forcing, but spatial variability in certain model parameters (biotic response) has more substantial effects on the inter-annual variability of ecosystem respiration (Reco) through the effects on carbon pools. Both the biotic and abiotic factors play significant roles in modulating the spatial and temporal variability in terrestrial carbon cycling in the region. Together, our study quantifies the relative importance of both, and calls for better understanding of them to better predict regional CO2 exchanges.

Towards end-to-end models for investigating the effects of climate and fishing in marine ecosystems

NASA Astrophysics Data System (ADS)

Travers, M.; Shin, Y.-J.; Jennings, S.; Cury, P.

2007-12-01

End-to-end models that represent ecosystem components from primary producers to top predators, linked through trophic interactions and affected by the abiotic environment, are expected to provide valuable tools for assessing the effects of climate change and fishing on ecosystem dynamics. Here, we review the main process-based approaches used for marine ecosystem modelling, focusing on the extent of the food web modelled, the forcing factors considered, the trophic processes represented, as well as the potential use and further development of the models. We consider models of a subset of the food web, models which represent the first attempts to couple low and high trophic levels, integrated models of the whole ecosystem, and size spectrum models. Comparisons within and among these groups of models highlight the preferential use of functional groups at low trophic levels and species at higher trophic levels and the different ways in which the models account for abiotic processes. The model comparisons also highlight the importance of choosing an appropriate spatial dimension for representing organism dynamics. Many of the reviewed models could be extended by adding components and by ensuring that the full life cycles of species components are represented, but end-to-end models should provide full coverage of ecosystem components, the integration of physical and biological processes at different scales and two-way interactions between ecosystem components. We suggest that this is best achieved by coupling models, but there are very few existing cases where the coupling supports true two-way interaction. The advantages of coupling models are that the extent of discretization and representation can be targeted to the part of the food web being considered, making their development time- and cost-effective. Processes such as predation can be coupled to allow the propagation of forcing factors effects up and down the food web. However, there needs to be a stronger focus on enabling two-way interaction, carefully selecting the key functional groups and species, reconciling different time and space scales and the methods of converting between energy, nutrients and mass.

Application of the Rangeland Hydrology and Erosion Model to Ecological Site Descriptions and Management

USDA-ARS?s Scientific Manuscript database

The utility of Ecological Site Descriptions (ESDs) and State-and-Transition Models (STMs) concepts in guiding rangeland management hinges on their ability to accurately describe and predict community dynamics and the associated consequences. For many rangeland ecosystems, plant community dynamics ar...

Constraining Centennial-Scale Ecosystem-Climate Interactions with a Pre-colonial Forest Reconstruction across the Upper Midwest and Northeastern United States

NASA Astrophysics Data System (ADS)

Matthes, J. H.; Dietze, M.; Fox, A. M.; Goring, S. J.; McLachlan, J. S.; Moore, D. J.; Poulter, B.; Quaife, T. L.; Schaefer, K. M.; Steinkamp, J.; Williams, J. W.

2014-12-01

Interactions between ecological systems and the atmosphere are the result of dynamic processes with system memories that persist from seconds to centuries. Adequately capturing long-term biosphere-atmosphere exchange within earth system models (ESMs) requires an accurate representation of changes in plant functional types (PFTs) through time and space, particularly at timescales associated with ecological succession. However, most model parameterization and development has occurred using datasets than span less than a decade. We tested the ability of ESMs to capture the ecological dynamics observed in paleoecological and historical data spanning the last millennium. Focusing on an area from the Upper Midwest to New England, we examined differences in the magnitude and spatial pattern of PFT distributions and ecotones between historic datasets and the CMIP5 inter-comparison project's large-scale ESMs. We then conducted a 1000-year model inter-comparison using six state-of-the-art biosphere models at sites that bridged regional temperature and precipitation gradients. The distribution of ecosystem characteristics in modeled climate space reveals widely disparate relationships between modeled climate and vegetation that led to large differences in long-term biosphere-atmosphere fluxes for this region. Model simulations revealed that both the interaction between climate and vegetation and the representation of ecosystem dynamics within models were important controls on biosphere-atmosphere exchange.

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.

Exploring the sensitivity of soil carbon dynamics to climate change, fire disturbance and permafrost thaw in a black spruce ecosystem

Treesearch

J.A. O' Donnell; J.W. Harden; A.D. McGuire; V.E. Romanovsky

2011-01-01

In the boreal region, soil organic carbon (OC) dynamics are strongly governed by the interaction between wildfire and permafrost. Using a combination of field measurements, numerical modeling of soil thermal dynamics, and mass-balance modeling of OC dynamics, we tested the sensitivity of soil OC storage to a suite of individual climate factors (air temperature, soil...

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.

Changes in Landscape-level Carbon Balance of an Arctic Coastal Plain Tundra Ecosystem Between 1970-2100, in Response to Projected Climate Change

NASA Astrophysics Data System (ADS)

Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Genet, H.; Sloan, V. L.; Iversen, C. M.; Norby, R. J.; Zhang, Y.; Yuan, F.

2014-12-01

Northern permafrost regions are estimated to cover 16% of the global soil area and account for approximately 50% of the global belowground organic carbon pool. However, there are considerable uncertainties regarding the fate of this soil carbon pool with projected climate warming over the next century. In northern Alaska, nearly 65% of the terrestrial surface is composed of polygonal tundra, where geomorphic land cover types such as high-, flat-, and low-center polygons influence local surface hydrology, plant community composition, nutrient and biogeochemical cycling, over small spatial scales. Due to the lack of representation of these fine-scale geomorphic types and ecosystem processes, in large-scale terrestrial ecosystem models, future uncertainties are large for this tundra region. In this study, we use a new version of the terrestrial ecosystem model (TEM), that couples a dynamic vegetation model (in which plant functional types compete for water, nitrogen, and light) with a dynamic soil organic model (in which temperature, moisture, and associated organic/inorganic carbon and nitrogen pools/fluxes vary together in vertically resolved layers) to simulate ecosystem carbon balance. We parameterized and calibrated this model using data specific to the local climate, vegetation, and soil associated with tundra geomorphic types. We extrapolate model results at a 1km2 resolution across the ~1800 km2 Barrow Peninsula using a tundra geomorphology map, describing ten dominant geomorphic tundra types (Lara et al. submitted), to estimate the likely change in landscape-level carbon balance between 1970 and 2100 in response to projected climate change. Preliminary model runs for this region indicated temporal variability in carbon and active layer dynamics, specific to tundra geomorphic type over time. Overall, results suggest that it is important to consider small-scale discrete polygonal tundra geomorphic types that control local structure and function in regional estimates of carbon balance in northern Alaska.

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

Treesearch

Crystal L. Raymond; Donald McKenzie

2014-01-01

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

A Conceptual Model of Natural and Anthropogenic Drivers and Their Influence on the Prince William Sound, Alaska, Ecosystem

PubMed Central

Harwell, Mark A.; Gentile, John H.; Cummins, Kenneth W.; Highsmith, Raymond C.; Hilborn, Ray; McRoy, C. Peter; Parrish, Julia; Weingartner, Thomas

2010-01-01

Prince William Sound (PWS) is a semi-enclosed fjord estuary on the coast of Alaska adjoining the northern Gulf of Alaska (GOA). PWS is highly productive and diverse, with primary productivity strongly coupled to nutrient dynamics driven by variability in the climate and oceanography of the GOA and North Pacific Ocean. The pelagic and nearshore primary productivity supports a complex and diverse trophic structure, including large populations of forage and large fish that support many species of marine birds and mammals. High intra-annual, inter-annual, and interdecadal variability in climatic and oceanographic processes as drives high variability in the biological populations. A risk-based conceptual ecosystem model (CEM) is presented describing the natural processes, anthropogenic drivers, and resultant stressors that affect PWS, including stressors caused by the Great Alaska Earthquake of 1964 and the Exxon Valdez oil spill of 1989. A trophodynamic model incorporating PWS valued ecosystem components is integrated into the CEM. By representing the relative strengths of driver/stressors/effects, the CEM graphically demonstrates the fundamental dynamics of the PWS ecosystem, the natural forces that control the ecological condition of the Sound, and the relative contribution of natural processes and human activities to the health of the ecosystem. The CEM illustrates the dominance of natural processes in shaping the structure and functioning of the GOA and PWS ecosystems. PMID:20862192

A Conceptual Model of Natural and Anthropogenic Drivers and Their Influence on the Prince William Sound, Alaska, Ecosystem.

PubMed

Harwell, Mark A; Gentile, John H; Cummins, Kenneth W; Highsmith, Raymond C; Hilborn, Ray; McRoy, C Peter; Parrish, Julia; Weingartner, Thomas

2010-07-01

Prince William Sound (PWS) is a semi-enclosed fjord estuary on the coast of Alaska adjoining the northern Gulf of Alaska (GOA). PWS is highly productive and diverse, with primary productivity strongly coupled to nutrient dynamics driven by variability in the climate and oceanography of the GOA and North Pacific Ocean. The pelagic and nearshore primary productivity supports a complex and diverse trophic structure, including large populations of forage and large fish that support many species of marine birds and mammals. High intra-annual, inter-annual, and interdecadal variability in climatic and oceanographic processes as drives high variability in the biological populations. A risk-based conceptual ecosystem model (CEM) is presented describing the natural processes, anthropogenic drivers, and resultant stressors that affect PWS, including stressors caused by the Great Alaska Earthquake of 1964 and the Exxon Valdez oil spill of 1989. A trophodynamic model incorporating PWS valued ecosystem components is integrated into the CEM. By representing the relative strengths of driver/stressors/effects, the CEM graphically demonstrates the fundamental dynamics of the PWS ecosystem, the natural forces that control the ecological condition of the Sound, and the relative contribution of natural processes and human activities to the health of the ecosystem. The CEM illustrates the dominance of natural processes in shaping the structure and functioning of the GOA and PWS ecosystems.

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

USGS Publications Warehouse

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

2014-01-01

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

AQUATOX coupled foodweb model for ecosystem risk assessment of Polybrominated diphenyl ethers (PBDEs) in lake ecosystems.

PubMed

Zhang, Lulu; Liu, Jingling

2014-08-01

The AQUATOX model considers the direct toxic effects of chemicals and their indirect effects through foodwebs. For this study, the AQUATOX model was applied to evaluating the ecological risk of Polybrominated diphenyl ethers (PBDEs) in a highly anthropogenically disturbed lake-Baiyangdian Lake. Calibration and validation results indicated that the model can adequately describe the dynamics of 18 biological populations. Sensitivity analysis results suggested that the model is highly sensitive to temperature limitation. PBDEs risk estimate results demonstrate that estimated risk for natural ecosystems cannot be fully explained by single species toxicity data alone. The AQUATOX model could provide a good basis in ascertaining ecological protection levels of "chemicals of concern" for aquatic ecosystems. Therefore, AQUATOX can potentially be used to provide necessary information corresponding to early warning and rapid forecasting of pollutant transport and fate in the management of chemicals that put aquatic ecosystems at risk. Copyright © 2014 Elsevier Ltd. All rights reserved.

Catchment hydrological responses to forest harvest amount and spatial pattern - 2011

EPA Science Inventory

We used an ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest location and amount on ecosystem carbon (C) and nitrogen (N) dynamics in an intensively studied headwater catchment (WS10) in western Oregon,...

Hydrocentric view of Agro-ecosystem Resiliency to Extreme Hydrometeorological and Climate Events in the High Plains, US.

NASA Astrophysics Data System (ADS)

Munoz-Arriola, Francisco; Sharma, Ashutosh; Werner, Katherine; Chacon, Juan-Carlos; Corzo, Gerald; Goyal, Manish-Kumar

2017-04-01

An increasing incidence of Hydrometeorological and Climate Extreme Events (EHCEs) is challenging food, water, and ecosystem services security at local to global contexts. This study aims to understand how a large-scale representation of agroecosystems and ecosystems respond to EHCE in the Northern Highplains, US. To track such responses the Variable Infiltration Capacity model (VIC) Land Surface Hydrology model was used and two experiments were implemented. The first experiment uses the LAI MODIS15A2 product to capture dynamic responses of vegetation with a time span from 2000 to 2013. The second experiment used a climatological fixed seasonal cycle calculated as the average from the 2000-2013 dynamic MODIS15A2 product to isolate vegetation from soil physical responses. Based on the analyses of multiple hydrological variables and state variables and high-level organization of agroecosystems and ecosystems, we evidence how the influence of droughts and anomalously wet conditions affect hydrological resilience at large scale.

Carbon dioxide dynamics in an artificial ecosystem

NASA Astrophysics Data System (ADS)

Hu, Enzhu; Hu, Dawei; Tong, Ling; Li, Ming; Fu, Yuming; He, Wenting; Liu, Hong

An experimental artificial ecosystem was established as a tool to understand the behavior of closed ecosystem and to develop the technology for a future bioregenerative life support system for lunar or planetary exploration. Total effective volume of the system is 0.7 m3 . It consists of a higher plant chamber, an animal chamber and a photo-bioreactor which cultivated lettuce (Lactuca sativa L.), silkworm (Bombyx Mori L.) and microalgae (Chlorella), respectively. For uniform and sustained observations, lettuce and silkworms was cultivated using sequential cultivation method, and microalgae using continuous culture. Four researchers took turns breathing the system air through a tube for brief periods every few hours. A mathematic model, simulating the carbon dioxide dynamics was developed. The main biological parameters concerning photosynthesis of lettuce and microalgae, respiration of silkworms and human were validated by the experimental data. The model described the respiratory relationship between autotrophic and heterotrophic compartments. A control strategy was proposed as a tool for the atmosphere management of the artificial ecosystem.

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.

From terrestrial to aquatic fluxes: Integrating stream dynamics within a dynamic global vegetation modeling framework

NASA Astrophysics Data System (ADS)

Hoy, Jerad; Poulter, Benjamin; Emmett, Kristen; Cross, Molly; Al-Chokhachy, Robert; Maneta, Marco

2016-04-01

Integrated terrestrial ecosystem models simulate the dynamics and feedbacks between climate, vegetation, disturbance, and hydrology and are used to better understand biogeography and biogeochemical cycles. Extending dynamic vegetation models to the aquatic interface requires coupling surface and sub-surface runoff to catchment routing schemes and has the potential to enhance how researchers and managers investigate how changes in the environment might impact the availability of water resources for human and natural systems. In an effort towards creating such a coupled model, we developed catchment-based hydrologic routing and stream temperature model to pair with LPJ-GUESS, a dynamic global vegetation model. LPJ-GUESS simulates detailed stand-level vegetation dynamics such as growth, carbon allocation, and mortality, as well as various physical and hydrologic processes such as canopy interception and through-fall, and can be applied at small spatial scales, i.e., 1 km. We demonstrate how the coupled model can be used to investigate the effects of transient vegetation dynamics and CO2 on seasonal and annual stream discharge and temperature regimes. As a direct management application, we extend the modeling framework to predict habitat suitability for fish habitat within the Greater Yellowstone Ecosystem, a 200,000 km2 region that provides critical habitat for a range of aquatic species. The model is used to evaluate, quantitatively, the effects of management practices aimed to enhance hydrologic resilience to climate change, and benefits for water storage and fish habitat in the coming century.

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...

Management Strategy Evaluation Applied to Coral Reef Ecosystems in Support of Ecosystem-Based Management.

PubMed

Weijerman, Mariska; Fulton, Elizabeth A; Brainard, Russell E

2016-01-01

Ecosystem modelling is increasingly used to explore ecosystem-level effects of changing environmental conditions and management actions. For coral reefs there has been increasing interest in recent decades in the use of ecosystem models for evaluating the effects of fishing and the efficacy of marine protected areas. However, ecosystem models that integrate physical forcings, biogeochemical and ecological dynamics, and human induced perturbations are still underdeveloped. We applied an ecosystem model (Atlantis) to the coral reef ecosystem of Guam using a suite of management scenarios prioritized in consultation with local resource managers to review the effects of each scenario on performance measures related to the ecosystem, the reef-fish fishery (e.g., fish landings) and coral habitat. Comparing tradeoffs across the selected scenarios showed that each scenario performed best for at least one of the selected performance indicators. The integrated 'full regulation' scenario outperformed other scenarios with four out of the six performance metrics at the cost of reef-fish landings. This model application quantifies the socio-ecological costs and benefits of alternative management scenarios. When the effects of climate change were taken into account, several scenarios performed equally well, but none prevented a collapse in coral biomass over the next few decades assuming a business-as-usual greenhouse gas emissions scenario.

Management Strategy Evaluation Applied to Coral Reef Ecosystems in Support of Ecosystem-Based Management

PubMed Central

Weijerman, Mariska; Fulton, Elizabeth A.; Brainard, Russell E.

2016-01-01

Ecosystem modelling is increasingly used to explore ecosystem-level effects of changing environmental conditions and management actions. For coral reefs there has been increasing interest in recent decades in the use of ecosystem models for evaluating the effects of fishing and the efficacy of marine protected areas. However, ecosystem models that integrate physical forcings, biogeochemical and ecological dynamics, and human induced perturbations are still underdeveloped. We applied an ecosystem model (Atlantis) to the coral reef ecosystem of Guam using a suite of management scenarios prioritized in consultation with local resource managers to review the effects of each scenario on performance measures related to the ecosystem, the reef-fish fishery (e.g., fish landings) and coral habitat. Comparing tradeoffs across the selected scenarios showed that each scenario performed best for at least one of the selected performance indicators. The integrated ‘full regulation’ scenario outperformed other scenarios with four out of the six performance metrics at the cost of reef-fish landings. This model application quantifies the socio-ecological costs and benefits of alternative management scenarios. When the effects of climate change were taken into account, several scenarios performed equally well, but none prevented a collapse in coral biomass over the next few decades assuming a business-as-usual greenhouse gas emissions scenario. PMID:27023183

Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment

EPA Science Inventory

We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where t...

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

NASA Astrophysics Data System (ADS)

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

2014-01-01

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

Unravelling the Impacts of Climate and People on Vegetation Dynamics in the Sahel 1982- 2002

NASA Astrophysics Data System (ADS)

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

2009-05-01

Satellite sensors have recently shown that much of the Sahel belt of north Africa has experienced significant increases in photosynthetic activity since the early 1980s. This has reignited old debates about the role that people play in shaping land surface status at broad geographical extents. If the human 'footprint' on Sahel vegetation dynamics is measurable, then such impacts may be significant enough alter broad-scale both carbon budgets and climate via land surface atmosphere feedbacks. We test the hypothesis that people have had a measurable impact on vegetation dynamics in the Sahel for the period 1982-2002. We accomplish this by mapping the agreement between potential natural vegetation dynamics predicted by a process-based ecosystem model (Lund Potsdam Jena-Dynamic Global Vegetation Model) and satellite-derived greenness observations (Global Inventory Modelling and Mapping Studies data set) across a geographic grid at a spatial resolution of 0.5 degrees. We then relate this agreement metric to state-of-the-art data sets on demographics, pasture, and cropping. Demographic and agricultural pressures in the Sahel are unable to account for differences between simulated and observed vegetation dynamics, even for the most densely populated areas. But we do identify a weak, positive correlation between data-model agreement and pasture intensity at the Sahel-wide level. This indicates that herding or grazing does not appreciably affect vegetation dynamics in the region. Either people have not had a significant impact on vegetation dynamics in the Sahel or the identification of a human 'footprint' is precluded by inconsistent or subtle vegetation response to complex socio-environmental interactions, and/or limitations in the data used for this study. This research showcases untapped potential for combining ecosystem process models with remote sensing at broad spatial extents for examining the underlying causes of ecosystem change.

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.

Food-web stability signals critical transitions in temperate shallow lakes

PubMed Central

Kuiper, Jan J.; van Altena, Cassandra; de Ruiter, Peter C.; van Gerven, Luuk P. A.; Janse, Jan H.; Mooij, Wolf M.

2015-01-01

A principal aim of ecologists is to identify critical levels of environmental change beyond which ecosystems undergo radical shifts in their functioning. Both food-web theory and alternative stable states theory provide fundamental clues to mechanisms conferring stability to natural systems. Yet, it is unclear how the concept of food-web stability is associated with the resilience of ecosystems susceptible to regime change. Here, we use a combination of food web and ecosystem modelling to show that impending catastrophic shifts in shallow lakes are preceded by a destabilizing reorganization of interaction strengths in the aquatic food web. Analysis of the intricate web of trophic interactions reveals that only few key interactions, involving zooplankton, diatoms and detritus, dictate the deterioration of food-web stability. Our study exposes a tight link between food-web dynamics and the dynamics of the whole ecosystem, implying that trophic organization may serve as an empirical indicator of ecosystem resilience. PMID:26173798

Comparing two tools for ecosystem service assessments regarding water resources decisions.

PubMed

Dennedy-Frank, P James; Muenich, Rebecca Logsdon; Chaubey, Indrajeet; Ziv, Guy

2016-07-15

We present a comparison of two ecohydrologic models commonly used for planning land management to assess the production of hydrologic ecosystem services: the Soil and Water Assessment Tool (SWAT) and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) annual water yield model. We compare these two models at two distinct sites in the US: the Wildcat Creek Watershed in Indiana and the Upper Upatoi Creek Watershed in Georgia. The InVEST and SWAT models provide similar estimates of the spatial distribution of water yield in Wildcat Creek, but very different estimates of the spatial distribution of water yield in Upper Upatoi Creek. The InVEST model may do a poor job estimating the spatial distribution of water yield in the Upper Upatoi Creek Watershed because baseflow provides a significant portion of the site's total water yield, which means that storage dynamics which are not modeled by InVEST may be important. We also compare the ability of these two models, as well as one newly developed set of ecosystem service indices, to deliver useful guidance for land management decisions focused on providing hydrologic ecosystem services in three particular decision contexts: environmental flow ecosystem services, ecosystem services for potable water supply, and ecosystem services for rainfed irrigation. We present a simple framework for selecting models or indices to evaluate hydrologic ecosystem services as a way to formalize where models deliver useful guidance. Copyright © 2016 Elsevier Ltd. All rights reserved.

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).

Observations and Models of Highly Intermittent Phytoplankton Distributions

PubMed Central

Mandal, Sandip; Locke, Christopher; Tanaka, Mamoru; Yamazaki, Hidekatsu

2014-01-01

The measurement of phytoplankton distributions in ocean ecosystems provides the basis for elucidating the influences of physical processes on plankton dynamics. Technological advances allow for measurement of phytoplankton data to greater resolution, displaying high spatial variability. In conventional mathematical models, the mean value of the measured variable is approximated to compare with the model output, which may misinterpret the reality of planktonic ecosystems, especially at the microscale level. To consider intermittency of variables, in this work, a new modelling approach to the planktonic ecosystem is applied, called the closure approach. Using this approach for a simple nutrient-phytoplankton model, we have shown how consideration of the fluctuating parts of model variables can affect system dynamics. Also, we have found a critical value of variance of overall fluctuating terms below which the conventional non-closure model and the mean value from the closure model exhibit the same result. This analysis gives an idea about the importance of the fluctuating parts of model variables and about when to use the closure approach. Comparisons of plot of mean versus standard deviation of phytoplankton at different depths, obtained using this new approach with real observations, give this approach good conformity. PMID:24787740

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

Spatial dynamics of ecosystem service flows: a comprehensive approach to quantifying actual services

USGS Publications Warehouse

Bagstad, Kenneth J.; Johnson, Gary W.; Voigt, Brian; Villa, Ferdinando

2013-01-01

Recent ecosystem services research has highlighted the importance of spatial connectivity between ecosystems and their beneficiaries. Despite this need, a systematic approach to ecosystem service flow quantification has not yet emerged. In this article, we present such an approach, which we formalize as a class of agent-based models termed “Service Path Attribution Networks” (SPANs). These models, developed as part of the Artificial Intelligence for Ecosystem Services (ARIES) project, expand on ecosystem services classification terminology introduced by other authors. Conceptual elements needed to support flow modeling include a service's rivalness, its flow routing type (e.g., through hydrologic or transportation networks, lines of sight, or other approaches), and whether the benefit is supplied by an ecosystem's provision of a beneficial flow to people or by absorption of a detrimental flow before it reaches them. We describe our implementation of the SPAN framework for five ecosystem services and discuss how to generalize the approach to additional services. SPAN model outputs include maps of ecosystem service provision, use, depletion, and flows under theoretical, possible, actual, inaccessible, and blocked conditions. We highlight how these different ecosystem service flow maps could be used to support various types of decision making for conservation and resource management planning.

Tropical forest response to elevated CO2: Model-experiment integration at the AmazonFACE site.

NASA Astrophysics Data System (ADS)

Frankenberg, C.; Berry, J. A.; Guanter, L.; Joiner, J.

2014-12-01

The terrestrial biosphere's response to current and future elevated atmospheric carbon dioxide (eCO2) is a large source of uncertainty in future projections of the C cycle, climate and ecosystem functioning. In particular, the sensitivity of tropical rainforest ecosystems to eCO­2 is largely unknown even though the importance of tropical forests for biodiversity, carbon storage and regional and global climate feedbacks is unambiguously recognized. The AmazonFACE (Free-Air Carbon Enrichment) project will be the first ecosystem scale eCO2 experiment undertaken in the tropics, as well as the first to be undertaken in a mature forest. AmazonFACE provides the opportunity to integrate ecosystem modeling with experimental observations right from the beginning of the experiment, harboring a two-way exchange, i.e. models provide hypotheses to be tested, and observations deliver the crucial data to test and improve ecosystem models. We present preliminary exploration of observed and expected process responses to eCO2 at the AmazonFACE site from the dynamic global vegetation model LPJ-GUESS, highlighting opportunities and pitfalls for model integration of tropical FACE experiments. The preliminary analysis provides baseline hypotheses, which are to be further developed with a follow-up multiple model inter-comparison. The analysis builds on the recently undertaken FACE-MDS (Model-Data Synthesis) project, which was applied to two temperate FACE experiments and exceeds the traditional focus on comparing modeled end-target output. The approach has proven successful in identifying well (and less well) represented processes in models, which are separated for six clusters also here; (1) Carbon fluxes, (2) Carbon pools, (3) Energy balance, (4) Hydrology, (5) Nutrient cycling, and (6) Population dynamics. Simulation performance of observed conditions at the AmazonFACE site (a.o. from Manaus K34 eddy flux tower) will highlight process-based model deficiencies, and aid the separation of uncertainties arising from general ecosystem responses and those responses related to eCO2.

Tropical forest response to elevated CO2: Model-experiment integration at the AmazonFACE site.

NASA Astrophysics Data System (ADS)

Fleischer, K.

2015-12-01

The terrestrial biosphere's response to current and future elevated atmospheric carbon dioxide (eCO2) is a large source of uncertainty in future projections of the C cycle, climate and ecosystem functioning. In particular, the sensitivity of tropical rainforest ecosystems to eCO­2 is largely unknown even though the importance of tropical forests for biodiversity, carbon storage and regional and global climate feedbacks is unambiguously recognized. The AmazonFACE (Free-Air Carbon Enrichment) project will be the first ecosystem scale eCO2 experiment undertaken in the tropics, as well as the first to be undertaken in a mature forest. AmazonFACE provides the opportunity to integrate ecosystem modeling with experimental observations right from the beginning of the experiment, harboring a two-way exchange, i.e. models provide hypotheses to be tested, and observations deliver the crucial data to test and improve ecosystem models. We present preliminary exploration of observed and expected process responses to eCO2 at the AmazonFACE site from the dynamic global vegetation model LPJ-GUESS, highlighting opportunities and pitfalls for model integration of tropical FACE experiments. The preliminary analysis provides baseline hypotheses, which are to be further developed with a follow-up multiple model inter-comparison. The analysis builds on the recently undertaken FACE-MDS (Model-Data Synthesis) project, which was applied to two temperate FACE experiments and exceeds the traditional focus on comparing modeled end-target output. The approach has proven successful in identifying well (and less well) represented processes in models, which are separated for six clusters also here; (1) Carbon fluxes, (2) Carbon pools, (3) Energy balance, (4) Hydrology, (5) Nutrient cycling, and (6) Population dynamics. Simulation performance of observed conditions at the AmazonFACE site (a.o. from Manaus K34 eddy flux tower) will highlight process-based model deficiencies, and aid the separation of uncertainties arising from general ecosystem responses and those responses related to eCO2.

Quantifying long-term trajectories of plant community change with movement models: implication for ecological resilience

USDA-ARS?s Scientific Manuscript database

Quantification of rates and patterns of community dynamics is central for understanding the organization and function of ecosystems. These insights may support a greater empirical understanding of ecological resilience, and the application of resilience concepts toward ecosystem management. Distinct...

Disturbance Distance: Using a process based ecosystem model to estimate and map potential thresholds in disturbance rates that would give rise to fundamentally altered ecosystems

NASA Astrophysics Data System (ADS)

Dolan, K. A.; Hurtt, G. C.; Fisk, J.; Flanagan, S.; LePage, Y.; Sahajpal, R.

2014-12-01

Disturbance plays a critical role in shaping the structure and function of forested ecosystems as well as the ecosystem services they provide, including but not limited to: carbon storage, biodiversity habitat, water quality and flow, and land atmosphere exchanges of energy and water. As recent studies highlight novel disturbance regimes resulting from pollution, invasive pests and climate change, there is a need to include these alterations in predictions of future forest function and structure. The Ecosystem Demography (ED) model is a mechanistic model of forest ecosystem dynamics in which individual-based forest dynamics can be efficiently implemented over regional to global scales due to advanced scaling methods. We utilize ED to characterize the sensitivity of potential vegetation structure and function to changes in rates of density independent mortality. Disturbance rate within ED can either be altered directly or through the development of sub-models. Disturbance sub-models in ED currently include fire, land use and hurricanes. We use a tiered approach to understand the sensitivity of North American ecosystems to changes in background density independent mortality. Our first analyses were conducted at half-degree spatial resolution with a constant rate of disturbance in space and time, which was altered between runs. Annual climate was held constant at the site level and the land use and fire sub-models were turned off. Results showed an ~ 30% increase in non-forest area across the US when disturbance rates were changed from 0.6% a year to 1.2% a year and a more than 3.5 fold increase in non-forest area when disturbance rates doubled again from 1.2% to 2.4%. Continued runs altered natural background disturbance rates with the existing fire and hurricane sub models turned on as well as historic and future land use. By quantify differences between model outputs that characterize ecosystem structure and function related to the carbon cycle across the US, we are identifying areas and characteristics that display higher sensitivities to change in disturbance rates.

Multiple ecosystem services in a working landscape

PubMed Central

Eastburn, Danny J.; O’Geen, Anthony T.; Tate, Kenneth W.; Roche, Leslie M.

2017-01-01

Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services—specifically agricultural production, biodiversity and habitat, and soil health—across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments. PMID:28301475

Multiple ecosystem services in a working landscape.

PubMed

Eastburn, Danny J; O'Geen, Anthony T; Tate, Kenneth W; Roche, Leslie M

2017-01-01

Policy makers and practitioners are in need of useful tools and models for assessing ecosystem service outcomes and the potential risks and opportunities of ecosystem management options. We utilize a state-and-transition model framework integrating dynamic soil and vegetation properties to examine multiple ecosystem services-specifically agricultural production, biodiversity and habitat, and soil health-across human created vegetation states in a managed oak woodland landscape in a Mediterranean climate. We found clear tradeoffs and synergies in management outcomes. Grassland states maximized agricultural productivity at a loss of soil health, biodiversity, and other ecosystem services. Synergies existed among multiple ecosystem services in savanna and woodland states with significantly larger nutrient pools, more diversity and native plant richness, and less invasive species. This integrative approach can be adapted to a diversity of working landscapes to provide useful information for science-based ecosystem service valuations, conservation decision making, and management effectiveness assessments.

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

Climate and land use controls over terrestrial water use efficiency in monsoon Asia.

Treesearch

Hanqin Tian; Chaoqun Lu; Guangsheng Chen; Xiaofeng Xu; Mingliang Liu; et al

2011-01-01

Much concern has been raised regarding how and to what extent climate change and intensive human activities have altered water use efficiency (WUE, amount of carbon uptake per unit of water use) in monsoon Asia. By using a process-based ecosystem model [dynamic land ecosystem model (DLEM)], we examined effects of climate change, land use/cover change, and land...

Competition favors elk over beaver in a riparian willow ecosystem

USGS Publications Warehouse

Baker, B.W.; Peinetti, H.R.; Coughenour, M.C.; Johnson, T.L.

2012-01-01

Beaver (Castor spp.) conservation requires an understanding of their complex interactions with competing herbivores. Simulation modeling offers a controlled environment to examine long-term dynamics in ecosystems driven by uncontrollable variables. We used a new version of the SAVANNA ecosystem model to investigate beaver (C. Canadensis) and elk (Cervus elapses) competition for willow (Salix spp.). We initialized the model with field data from Rocky Mountain National Park, Colorado, USA, to simulate a 4-ha riparian ecosystem containing beaver, elk, and willow. We found beaver persisted indefinitely when elk density was or = 30 elk km_2. The loss of tall willow preceded rapid beaver declines, thus willow condition may predict beaver population trajectory in natural environments. Beaver were able to persist with slightly higher elk densities if beaver alternated their use of foraging sites in a rest-rotation pattern rather than maintained continuous use. Thus, we found asymmetrical competition for willow strongly favored elk over beaver in a simulated montane ecosystem. Finally, we discuss application of the SAVANNA model and mechanisms of competition relative to beaver persistence as metapopulations, ecological resistance and alternative state models, and ecosystem regulation.

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.

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

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

Chen, Min; Zhuang, Qianlai; Cook, D.

2011-08-31

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000-2005 at a 0.05-0.05 spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr{sup -1} and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr{sup -1} and net ecosystem production (NEP) varies within 0.08- 0.73 PgC yr{sup -1} over the period 2000-2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr{sup -1} for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less

Impacts of urbanization on carbon balance in terrestrial ecosystems of the Southern United States.

PubMed

Zhang, Chi; Tian, Hanqin; Chen, Guangsheng; Chappelka, Arthur; Xu, Xiaofeng; Ren, Wei; Hui, Dafeng; Liu, Mingliang; Lu, Chaoqun; Pan, Shufen; Lockaby, Graeme

2012-05-01

Using a process-based Dynamic Land Ecosystem Model, we assessed carbon dynamics of urbanized/developed lands in the Southern United States during 1945-2007. The results indicated that approximately 1.72 (1.69-1.77) Pg (1P = 10(15)) carbon was stored in urban/developed lands, comparable to the storage of shrubland or cropland in the region. Urbanization resulted in a release of 0.21 Pg carbon to the atmosphere during 1945-2007. Pre-urbanization vegetation type and time since land conversion were two primary factors determining the extent of urbanization impacts on carbon dynamics. After a rapid decline of carbon storage during land conversion, an urban ecosystem gradually accumulates carbon and may compensate for the initial carbon loss in 70-100 years. The carbon sequestration rate of urban ecosystem diminishes with time, nearly disappearing in two centuries after land conversion. This study implied that it is important to take urbanization effect into account for assessing regional carbon balance. Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

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.

Influence of crop type specification and spatial resolution on empirical modeling of field-scale Maize and Soybean carbon fluxes in the US Great Plains

NASA Astrophysics Data System (ADS)

McCombs, A. G.; Hiscox, A.; Wang, C.; Desai, A. R.

2016-12-01

A challenge in satellite land surface remote-sensing models of ecosystem carbon dynamics in agricultural systems is the lack of differentiation by crop type and management. This generalization can lead to large discrepancies between model predictions and eddy covariance flux tower observations of net ecosystem exchange of CO2 (NEE). Literature confirms that NEE varies remarkably among different crop types making the generalization of agriculture in remote sensing based models inaccurate. Here, we address this inaccuracy by identifying and mapping net ecosystem exchange (NEE) in agricultural fields by comparing bulk modeling and modeling by crop type, and using this information to develop empirical models for future use. We focus on mapping NEE in maize and soybean fields in the US Great Plains at higher spatial resolution using the fusion of MODIS and LandSAT surface reflectance. MODIS observed reflectance was downscaled using the ESTARFM downscaling methodology to match spatial scales to those found in LandSAT and that are more appropriate for carbon dynamics in agriculture fields. A multiple regression model was developed from surface reflectance of the downscaled MODIS and LandSAT remote sensing values calibrated against five FLUXNET/AMERIFLUX flux towers located on soybean and/or maize agricultural fields in the US Great Plains with multi-year NEE observations. Our new methodology improves upon bulk approximates to map and model carbon dynamics in maize and soybean fields, which have significantly different photosynthetic capacities.

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.

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.

Impacts of tropospheric ozone and climate change on net primary productivity and net carbon exchange of China’s forest ecosystems

Treesearch

Wei Ren; Hanqin Tian; Bo Tao; Art Chappelka; Ge Sun; et al

2011-01-01

Aim We investigated how ozone pollution and climate change/variability have interactively affected net primary productivity (NPP) and net carbon exchange (NCE) across China’s forest ecosystem in the past half century. Location Continental China. Methods Using the dynamic land ecosystem model (DLEM) in conjunction with 10-km-resolution gridded historical data sets (...

The costs of climate change: ecosystem services and wildland fires

EPA Science Inventory

In this paper we use Habitat Equivalency Analysis (HEA) to monetize the avoided ecosystem services losses due to climate change-induced wildland fires in the U.S. Specifically, we use the U.S. Forest Service’s MC1 dynamic global vegetation model to forecast changes in wildland fi...

Discussion of skill improvement in marine ecosystem dynamic models based on parameter optimization and skill assessment

NASA Astrophysics Data System (ADS)

Shen, Chengcheng; Shi, Honghua; Liu, Yongzhi; Li, Fen; Ding, Dewen

2016-07-01

Marine ecosystem dynamic models (MEDMs) are important tools for the simulation and prediction of marine ecosystems. This article summarizes the methods and strategies used for the improvement and assessment of MEDM skill, and it attempts to establish a technical framework to inspire further ideas concerning MEDM skill improvement. The skill of MEDMs can be improved by parameter optimization (PO), which is an important step in model calibration. An efficient approach to solve the problem of PO constrained by MEDMs is the global treatment of both sensitivity analysis and PO. Model validation is an essential step following PO, which validates the efficiency of model calibration by analyzing and estimating the goodness-of-fit of the optimized model. Additionally, by focusing on the degree of impact of various factors on model skill, model uncertainty analysis can supply model users with a quantitative assessment of model confidence. Research on MEDMs is ongoing; however, improvement in model skill still lacks global treatments and its assessment is not integrated. Thus, the predictive performance of MEDMs is not strong and model uncertainties lack quantitative descriptions, limiting their application. Therefore, a large number of case studies concerning model skill should be performed to promote the development of a scientific and normative technical framework for the improvement of MEDM skill.

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

USGS Publications Warehouse

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

2018-01-01

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

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.

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond.

NASA Astrophysics Data System (ADS)

Pietsch, S.

2016-12-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

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.

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.

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

Ecosystem Model Skill Assessment. Yes We Can!

PubMed

Olsen, Erik; Fay, Gavin; Gaichas, Sarah; Gamble, Robert; Lucey, Sean; Link, Jason S

2016-01-01

Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted. We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes. We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment).

Ecosystem Model Skill Assessment. Yes We Can!

PubMed Central

Olsen, Erik; Fay, Gavin; Gaichas, Sarah; Gamble, Robert; Lucey, Sean; Link, Jason S.

2016-01-01

Need to Assess the Skill of Ecosystem Models Accelerated changes to global ecosystems call for holistic and integrated analyses of past, present and future states under various pressures to adequately understand current and projected future system states. Ecosystem models can inform management of human activities in a complex and changing environment, but are these models reliable? Ensuring that models are reliable for addressing management questions requires evaluating their skill in representing real-world processes and dynamics. Skill has been evaluated for just a limited set of some biophysical models. A range of skill assessment methods have been reviewed but skill assessment of full marine ecosystem models has not yet been attempted. Northeast US Atlantis Marine Ecosystem Model We assessed the skill of the Northeast U.S. (NEUS) Atlantis marine ecosystem model by comparing 10-year model forecasts with observed data. Model forecast performance was compared to that obtained from a 40-year hindcast. Multiple metrics (average absolute error, root mean squared error, modeling efficiency, and Spearman rank correlation), and a suite of time-series (species biomass, fisheries landings, and ecosystem indicators) were used to adequately measure model skill. Overall, the NEUS model performed above average and thus better than expected for the key species that had been the focus of the model tuning. Model forecast skill was comparable to the hindcast skill, showing that model performance does not degenerate in a 10-year forecast mode, an important characteristic for an end-to-end ecosystem model to be useful for strategic management purposes. Skill Assessment Is Both Possible and Advisable We identify best-practice approaches for end-to-end ecosystem model skill assessment that would improve both operational use of other ecosystem models and future model development. We show that it is possible to not only assess the skill of a complicated marine ecosystem model, but that it is necessary do so to instill confidence in model results and encourage their use for strategic management. Our methods are applicable to any type of predictive model, and should be considered for use in fields outside ecology (e.g. economics, climate change, and risk assessment). PMID:26731540

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.

'Trophic whales' as biotic buffers: weak interactions stabilize ecosystems against nutrient enrichment.

PubMed

Schwarzmüller, Florian; Eisenhauer, Nico; Brose, Ulrich

2015-05-01

Human activities may compromise biodiversity if external stressors such as nutrient enrichment endanger overall network stability by inducing unstable dynamics. However, some ecosystems maintain relatively high diversity levels despite experiencing continuing disturbances. This indicates that some intrinsic properties prevent unstable dynamics and resulting extinctions. Identifying these 'ecosystem buffers' is crucial for our understanding of the stability of ecosystems and an important tool for environmental and conservation biologists. In this vein, weak interactions have been suggested as stabilizing elements of complex systems, but their relevance has rarely been tested experimentally. Here, using network and allometric theory, we present a novel concept for a priori identification of species that buffer against externally induced instability of increased population oscillations via weak interactions. We tested our model in a microcosm experiment using a soil food-web motif. Our results show that large-bodied species feeding at the food web's base, so called 'trophic whales', can buffer ecosystems against unstable dynamics induced by nutrient enrichment. Similar to the functionality of chemical or mechanical buffers, they serve as 'biotic buffers' that take up stressor effects and thus protect fragile systems from instability. We discuss trophic whales as common functional building blocks across ecosystems. Considering increasing stressor effects under anthropogenic global change, conservation of these network-intrinsic biotic buffers may help maintain the stability and diversity of natural ecosystems. © 2014 The Authors. Journal of Animal Ecology © 2014 British Ecological Society.

Preventing the collapse of the Baltic cod stock through an ecosystem-based management approach

PubMed Central

Lindegren, Martin; Möllmann, Christian; Nielsen, Anders; Stenseth, Nils C.

2009-01-01

Worldwide a number of fish stocks have collapsed because of overfishing and climate-induced ecosystem changes. Developing ecosystem-based fisheries management (EBFM) to prevent these catastrophic events in the future requires ecological models incorporating both internal food-web dynamics and external drivers such as fishing and climate. Using a stochastic food-web model for a large marine ecosystem (i.e., the Baltic Sea) hosting a commercially important cod stock, we were able to reconstruct the history of the stock. Moreover we demonstrate that in hindsight the collapse could only have been avoidable by adapting fishing pressure to environmental conditions and food-web interactions. The modeling approach presented here represents a significant advance for EBFM, the application of which is important for sustainable resource management in the future. PMID:19706557

Linking water quality and quantity in environmental flow assessment in deteriorated ecosystems: a food web view.

PubMed

Chen, He; Ma, Lekuan; Guo, Wei; Yang, Ying; Guo, Tong; Feng, Cheng

2013-01-01

Most rivers worldwide are highly regulated by anthropogenic activities through flow regulation and water pollution. Environmental flow regulation is used to reduce the effects of anthropogenic activities on aquatic ecosystems. Formulating flow alteration-ecological response relationships is a key factor in environmental flow assessment. Traditional environmental flow models are characterized by natural relationships between flow regimes and ecosystem factors. However, food webs are often altered from natural states, which disturb environmental flow assessment in such ecosystems. In ecosystems deteriorated by heavy anthropogenic activities, the effects of environmental flow regulation on species are difficult to assess with current modeling approaches. Environmental flow management compels the development of tools that link flow regimes and food webs in an ecosystem. Food web approaches are more suitable for the task because they are more adaptive for disordered multiple species in a food web deteriorated by anthropogenic activities. This paper presents a global method of environmental flow assessment in deteriorated aquatic ecosystems. Linkages between flow regimes and food web dynamics are modeled by incorporating multiple species into an ecosystem to explore ecosystem-based environmental flow management. The approach allows scientists and water resources managers to analyze environmental flows in deteriorated ecosystems in an ecosystem-based way.

Characteristics of organic soil in black spruce forests: implications for the application of land surface and ecosystem models in cold regions

Treesearch

Shuhua Yi; Kristen Manies; Jennifer Harden; David McGuire

2009-01-01

Soil organic layers (OL) play an important role in land-atmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that...

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...

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.

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.

Water resources management in a homogenizing world: Averting the Growth and Underinvestment trajectory

NASA Astrophysics Data System (ADS)

Mirchi, Ali; Watkins, David W.; Huckins, Casey J.; Madani, Kaveh; Hjorth, Peder

2014-09-01

Biotic homogenization, a de facto symptom of a global biodiversity crisis, underscores the urgency of reforming water resources management to focus on the health and viability of ecosystems. Global population and economic growth, coupled with inadequate investment in maintenance of ecological systems, threaten to degrade environmental integrity and ecosystem services that support the global socioeconomic system, indicative of a system governed by the Growth and Underinvestment (G&U) archetype. Water resources management is linked to biotic homogenization and degradation of system integrity through alteration of water systems, ecosystem dynamics, and composition of the biota. Consistent with the G&U archetype, water resources planning primarily treats ecological considerations as exogenous constraints rather than integral, dynamic, and responsive parts of the system. It is essential that the ecological considerations be made objectives of water resources development plans to facilitate the analysis of feedbacks and potential trade-offs between socioeconomic gains and ecological losses. We call for expediting a shift to ecosystem-based management of water resources, which requires a better understanding of the dynamics and links between water resources management actions, ecological side-effects, and associated long-term ramifications for sustainability. To address existing knowledge gaps, models that include dynamics and estimated thresholds for regime shifts or ecosystem degradation need to be developed. Policy levers for implementation of ecosystem-based water resources management include shifting away from growth-oriented supply management, better demand management, increased public awareness, and institutional reform that promotes adaptive and transdisciplinary management approaches.

Project Summary (2012-2015) – Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change

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

Hinkle, Ross; Benscoter, Brian; Comas, Xavier

2015-04-07

Carbon Dynamics of the Greater Everglades Watershed and Implications of Climate Change The objectives of this project are to: 1) quantify above- and below-ground carbon stocks of terrestrial ecosystems along a seasonal hydrologic gradient in the headwaters region of the Greater Everglades watershed; 2) develop budgets of ecosystem gaseous carbon exchange (carbon dioxide and methane) across the seasonal hydrologic gradient; 3) assess the impact of climate drivers on ecosystem carbon exchange in the Greater Everglades headwater region; and 4) integrate research findings with climate-driven terrestrial ecosystem carbon models to examine the potential influence of projected future climate change on regionalmore » carbon cycling. Note: this project receives a one-year extension past the original performance period - David Sumner (USGS) is not included in this extension.« less

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.

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

PubMed Central

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

2014-01-01

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

Global change and terrestrial plant community dynamics

DOE PAGES

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

2016-02-29

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

Global change and terrestrial plant community dynamics

PubMed Central

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

2016-01-01

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

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health

PubMed Central

Ortiz, Marco

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an “ecological” tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics. PMID:28453548

Self-feedbacks determine the sustainability of human interventions in eco-social complex systems: Impacts on biodiversity and ecosystem health.

PubMed

Ortiz, Marco; Levins, Richard

2017-01-01

Several administrative polices have been implemented in order to reduce the negative impacts of fishing on natural ecosystems. Four eco-social models with different levels of complexity were constructed, which represent the seaweed harvest in central-northern Chile under two different regimes, Management and Exploitation Areas for Benthic Resources (MAEBRs) and Open Access Areas (OAAs). The dynamics of both regimes were analyzed using the following theoretical frameworks: (1) Loop Analysis, which allows the local stability or sustainability of the models and scenarios to be assessed; and (2) Hessian´s optimization procedure of a global fishery function (GFF) that represents each dynamics of each harvest. The results suggest that the current fishing dynamics in MAEBRs are not sustainable unless the market demand presents some type of control (i.e. taxes). Further, the results indicated that if the demand changes to a self-negative feedback (self-control) in MAEBRs, the stability is increased and, simultaneously, a relative maximum for the GFF is reached. Contrarily, the sustainability of the model/system representing the harvest (principally by cutting plants) in OAAs is not reached. The implementation of an "ecological" tax for intensive artisanal fisheries with low operational cost is proposed. The network analysis developed here is proposed as a general strategy for studying the effects of human interventions in marine coastal ecosystems under transient (short-term) dynamics.

Understanding the Dynamics of Socio-Hydrological Environment: a Conceptual Framework

NASA Astrophysics Data System (ADS)

Woyessa, Y.; Welderufael, W.; Edossa, D.

2011-12-01

Human actions affect ecological systems and the services they provide through various activities, such as land use, water use, pollution and climate change. Climate change is perhaps one of the most important sustainable development challenges that threaten to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the change of ecosystems under different scenarios of climate and biophysical conditions could assist in bringing the issue of ecosystem services into decision making process. Similarly, the impacts of land use change on ecosystems and biodiversity have received considerable attention from ecologists and hydrologists alike. Land use change in a catchment can impact on water supply by altering hydrological processes, such as infiltration, groundwater recharge, base flow and direct runoff. In the past a variety of models were used for predicting land-use changes. Recently the focus has shifted away from using mathematically oriented models to agent-based modelling (ABM) approach to simulate land use scenarios. A conceptual framework is being developed which integrates climate change scenarios and the human dimension of land use decision into a hydrological model in order to assess its impacts on the socio-hydrological dynamics of a river basin. The following figures present the framework for the analysis and modelling of the socio-hydrological dynamics. Keywords: climate change, land use, river basin

Early Successional Microhabitats Allow the Persistence of Endangered Plants in Coastal Sand Dunes

PubMed Central

2015-01-01

Many species are adapted to disturbance and occur within dynamic, mosaic landscapes that contain early and late successional microhabitats. Human modification of disturbance regimes alters the availability of microhabitats and may affect the viability of species in these ecosystems. Because restoring historical disturbance regimes is typically expensive and requires action at large spatial scales, such restoration projects must be justified by linking the persistence of species with successional microhabitats. Coastal sand dune ecosystems worldwide are characterized by their endemic biodiversity and frequent disturbance. Dune-stabilizing invasive plants alter successional dynamics and may threaten species in these ecosystems. We examined the distribution and population dynamics of two federally endangered plant species, the annual Layia carnosa and the perennial Lupinus tidestromii, within a dune ecosystem in northern California, USA. We parameterized a matrix population model for L. tidestromii and examined the magnitude by which the successional stage of the habitat (early or late) influenced population dynamics. Both species had higher frequencies and L. tidestromii had higher frequency of seedlings in early successional habitats. Lupinus tidestromii plants in early successional microhabitats had higher projected rates of population growth than those associated with stabilized, late successional habitats, due primarily to higher rates of recruitment in early successional microhabitats. These results support the idea that restoration of disturbance is critical in historically dynamic landscapes. Our results suggest that large-scale restorations are necessary to allow persistence of the endemic plant species that characterize these ecosystems. PMID:25835390

Characteristics of organic soil in black spruce forests: Implications for the application of land surface and ecosystem models in cold regions

USGS Publications Warehouse

Yi, S.; Manies, K.; Harden, J.; McGuire, A.D.

2009-01-01

Soil organic layers (OL) play an important role in landatmosphere exchanges of water, energy and carbon in cold environments. The proper implementation of OL in land surface and ecosystem models is important for predicting dynamic responses to climate warming. Based on the analysis of OL samples of black spruce (Picea mariana), we recommend that implementation of OL for cold regions modeling: (1) use three general organic horizon types (live, fibrous, and amorphous) to represent vertical soil heterogeneity; (2) implement dynamics of OL over the course of disturbance, as there are significant differences of OL thickness between young and mature stands; and (3) use two broad drainage classes to characterize spatial heterogeneity, as there are significant differences in OL thickness between dry and wet sites. Implementation of these suggestions into models has the potential to substantially improve how OL dynamics influence variability in surface temperature and soil moisture in cold regions. Copyright 2009 by the American Geophys.ical Union.

Assessing tropical rainforest growth traits: Data - Model fusion in the Congo basin and beyond

NASA Astrophysics Data System (ADS)

Pietsch, Stephan

2017-04-01

Virgin forest ecosystems resemble the key reference level for natural tree growth dynamics. The mosaic cycle concept describes such dynamics as local disequilibria driven by patch level succession cycles of breakdown, regeneration, juvenescence and old growth. These cycles, however, may involve different traits of light demanding and shade tolerant species assemblies. In this work a data model fusion concept will be introduced to assess the differences in growth dynamics of the mosaic cycle of the Western Congolian Lowland Rainforest ecosystem. Field data from 34 forest patches located in an ice age forest refuge, recently pinpointed to the ground and still devoid of direct human impact up to today - resemble the data base. A 3D error assessment procedure versus BGC model simulations for the 34 patches revealed two different growth dynamics, consistent with observed growth traits of pioneer and late succession species assemblies of the Western Congolian Lowland rainforest. An application of the same procedure to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to Central American Pacific rainforests confirms the strength of the 3D error field data model fusion concept to assess different growth traits of the mosaic cycle of natural forest dynamics.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Integrated Inquiry.

ERIC Educational Resources Information Center

Trautmann, Nancy M.; Carlsen, William S.; Krasny, Marianne E.; Cunningham, Christine M.

2000-01-01

Introduces the Environmental Inquiry (EI) program which focuses on five topics: watershed dynamics, environmental toxicology, ecology of invasive species, biodegradations, and urban ecosystem modeling. (YDS)

Near Real-time Ecological Forecasting of Peatland Responses to Warming and CO2 Treatment through EcoPAD-SPRUCE

NASA Astrophysics Data System (ADS)

Huang, Y.; Jiang, J.; Stacy, M.; Ricciuto, D. M.; Hanson, P. J.; Sundi, N.; Luo, Y.

2016-12-01

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 Ecological Platform for Assimilation of Data (EcoPAD) facilitates the integration of current best knowledge from models, manipulative experimentations, observations and other modern techniques and provides both near real-time and long-term forecasting of ecosystem dynamics. As a case study, the web-based EcoPAD platform synchronizes real- or near real-time field measurements from the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment experiment, assimilates multiple data streams into process based models, enhances timely feedback between modelers and experimenters, and ultimately improves ecosystem forecasting and makes best utilization of current knowledge. In addition to enable 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, and (v) conduct ecological forecasting, EcoPAD-SPRUCE automated the workflow from real-time data acquisition, model simulation to result visualization. EcoPAD-SPRUCE promotes seamless feedback between modelers and experimenters, hand in hand to make better forecasting of future changes. The framework of EcoPAD-SPRUCE (with flexible API, Application Programming Interface) is easily portable and will benefit scientific communities, policy makers as well as the general public.

Assessing resilience and state-transition models with historical records of cheatgrass Bromus tectorum invasion in North American sagebrush-steppe

USDA-ARS?s Scientific Manuscript database

1. Resilience-based approaches are increasingly being called upon to inform ecosystem management, particularly in arid and semi-arid regions. This requires management frameworks that can assess ecosystem dynamics, both within and between alternative states, at relevant time scales. 2. We analysed l...

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...

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.

Optimal control of soybean aphid in the presence of natural enemies and the implied value of their ecosystem services.

PubMed

Zhang, Wei; Swinton, Scott M

2012-04-15

By suppressing pest populations, natural enemies provide an important ecosystem service that maintains the stability of agricultural ecosystems systems and potentially mitigates producers' pest control costs. Integrating natural control services into decisions about pesticide-based control has the potential to significantly improve the economic efficiency of pesticide use, with socially desirable outcomes. Two gaps have hindered the incorporation of natural enemies into pest management decision rules: (1) insufficient knowledge of pest and predator population dynamics and (2) lack of a decision framework for the economic tradeoffs among pest control options. Using a new intra-seasonal, dynamic bioeconomic optimization model, this study assesses how predation by natural enemies contributes to profit-maximizing pest management strategies. The model is applied to the management of the invasive soybean aphid, the most significant serious insect threat to soybean production in North America. The resulting lower bound estimate of the value of natural pest control ecosystem services was estimated at $84 million for the states of Illinois, Indiana, Iowa, Michigan and Minnesota in 2005. Copyright © 2011 Elsevier Ltd. All rights reserved.

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.

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

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...

Introducing mixotrophy into a biogeochemical model describing an eutrophied coastal ecosystem: The Southern North Sea

NASA Astrophysics Data System (ADS)

Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie

2017-09-01

Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mol N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3-32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. Under high irradiance, non-constitutive mixotrophy appreciably increases annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. In this ecosystem, non-constitutive mixotrophy is also observed to have an indirect stimulating effect on diatoms. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that contrasting forms of mixotrophy have different impacts on system dynamics and, due to the complex interactions in the ecosystem, their combined effect is not exactly the addition of the effects individually observed. It is thus important to describe such contrasting forms in an appropriate fashion.

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 the responses of forest ecosystems to climate change and CO2 using dynamic global vegetation models.

PubMed

Song, Xiang; Zeng, Xiaodong

2017-02-01

The climate has important influences on the distribution and structure of forest ecosystems, which may lead to vital feedback to climate change. However, much of the existing work focuses on the changes in carbon fluxes or water cycles due to climate change and/or atmospheric CO 2 , and few studies have considered how and to what extent climate change and CO 2 influence the ecosystem structure (e.g., fractional coverage change) and the changes in the responses of ecosystems with different characteristics. In this work, two dynamic global vegetation models (DGVMs): IAP-DGVM coupled with CLM3 and CLM4-CNDV, were used to investigate the response of the forest ecosystem structure to changes in climate (temperature and precipitation) and CO 2 concentration. In the temperature sensitivity tests, warming reduced the global area-averaged ecosystem gross primary production in the two models, which decreased global forest area. Furthermore, the changes in tree fractional coverage (Δ F tree ; %) from the two models were sensitive to the regional temperature and ecosystem structure, i.e., the mean annual temperature (MAT; °C) largely determined whether Δ F tree was positive or negative, while the tree fractional coverage ( F tree ; %) played a decisive role in the amplitude of Δ F tree around the globe, and the dependence was more remarkable in IAP-DGVM. In cases with precipitation change, F tree had a uniformly positive relationship with precipitation, especially in the transition zones of forests (30% <  F tree  < 60%) for IAP-DGVM and in semiarid and arid regions for CLM4-CNDV. Moreover, Δ F tree had a stronger dependence on F tree than on the mean annual precipitation (MAP; mm/year). It was also demonstrated that both models captured the fertilization effects of the CO 2 concentration.

Quantifying terrestrial ecosystem carbon dynamics in the Jinsha watershed, Upper Yangtze, China from 1975 to 2000

USGS Publications Warehouse

Zhao, Shuqing; Liu, Shuguang; Yin, Runsheng; Li, Zhengpeng; Deng, Yulin; Tan, Kun; Deng, Xiangzheng; Rothstein, David; Qi, Jiaguo; Yin, Runsheng

2009-01-01

Quantifying the spatial and temporal dynamics of carbon stocks in terrestrial ecosystems and carbon fluxes between the terrestrial biosphere and the atmosphere is critical to our understanding of regional patterns of carbon storage and loss. Here we use the General Ensemble Biogeochemical Modeling System to simulate the terrestrial ecosystem carbon dynamics in the Jinsha watershed of China's upper Yangtze basin from 1975 to 2000, based on unique combinations of spatial and temporal dynamics of major driving forces, such as climate, soil properties, nitrogen deposition, and land use and land cover changes. Our analysis demonstrates that the Jinsha watershed ecosystems acted as a carbon sink during the period of 1975–2000, with an average rate of 0.36 Mg/ha/yr, primarily resulting from regional climate variation and local land use and land cover change. Vegetation biomass accumulation accounted for 90.6% of the sink, while soil organic carbon loss before 1992 led to lower net gain of carbon in the watershed, and after that soils became a small sink. Ecosystem carbon sinks/source pattern showed a high degree of spatial heterogeneity, Carbon sinks were associated with forest areas without disturbances, whereas carbon Sources were primarily caused by stand-replacing disturbances. This highlights the importance of land-use history in determining the regional carbon sinks/source pattern.

A multiscale, hierarchical model of pulse dynamics in arid-land ecosystems

USGS Publications Warehouse

Collins, Scott L.; Belnap, Jayne; Grimm, N. B.; Rudgers, J. A.; Dahm, Clifford N.; D'Odorico, P.; Litvak, M.; Natvig, D. O.; Peters, Douglas C.; Pockman, W. T.; Sinsabaugh, R. L.; Wolf, B. O.

2014-01-01

Ecological processes in arid lands are often described by the pulse-reserve paradigm, in which rain events drive biological activity until moisture is depleted, leaving a reserve. This paradigm is frequently applied to processes stimulated by one or a few precipitation events within a growing season. Here we expand the original framework in time and space and include other pulses that interact with rainfall. This new hierarchical pulse-dynamics framework integrates space and time through pulse-driven exchanges, interactions, transitions, and transfers that occur across individual to multiple pulses extending from micro to watershed scales. Climate change will likely alter the size, frequency, and intensity of precipitation pulses in the future, and arid-land ecosystems are known to be highly sensitive to climate variability. Thus, a more comprehensive understanding of arid-land pulse dynamics is needed to determine how these ecosystems will respond to, and be shaped by, increased climate variability.

GLOBEC (Global Ocean Ecosystems Dynamics: Northwest Atlantic program

NASA Technical Reports Server (NTRS)

1991-01-01

The specific objective of the meeting was to plan an experiment in the Northwestern Atlantic to study the marine ecosystem and its role, together with that of climate and physical dynamics, in determining fisheries recruitment. The underlying focus of the GLOBEC initiative is to understand the marine ecosystem as it related to marine living resources and to understand how fluctuation in these resources are driven by climate change and exploitation. In this sense the goal is a solid scientific program to provide basic information concerning major fisheries stocks and the environment that sustains them. The plan is to attempt to reach this understanding through a multidisciplinary program that brings to bear new techniques as disparate as numerical fluid dynamic models of ocean circulation, molecular biology and modern acoustic imaging. The effort will also make use of the massive historical data sets on fisheries and the state of the climate in a coordinated manner.

Advances in Estimating Current and Future Effects of Climate and Management on Forest Ecosystem Carbon and Water Dynamics at Multiple Scales

NASA Astrophysics Data System (ADS)

Law, B. E.; Still, C. J.; Hudiburg, T. W.; Buotte, P.; Hanson, C. V.

2017-12-01

As we examine the integrated effects of climate variability, atmospheric CO2, and land management actions on terrestrial carbon and water processes within regions, and evaluate mitigation and adaptation options, we want our analysis to be as accurate as possible to reduce the risk of negative impacts from management decisions. The use of global land models at regional scales requires modifications for realistic projections. Model evaluation reveals knowledge and data gaps in species sensitivities to climate extremes and responses to land use change and management actions such as restoration. For example, a combination of sapflux and AmeriFlux tower measurements identifies seasonal shifts in the proportion of water vapor exchange that is due to tree transpiration, as well as changes in tree water-use efficiency associated with climate variation. Thermal measurements from an unmanned aerial system quantify canopy temperatures reached during extreme heat events, as well as tree-to-tree thermal variations, which can be related to transpiration dynamics. Diagnosis of land model performance across climate/vegetation gradients includes the combination of atmospheric CO2/CO/H2O observations from aircraft, a tall tower network, and a mobile platform, combined with inverse modeling. This approach identified an ecoregion where the Community Land Model (CLM4.5) underestimated net ecosystem production by 28%, suggesting model challenges in high productivity forests with high soil nitrogen and deep organic soils. We use land-model output of net ecosystem production, harvest and fire emissions to estimate net ecosystem carbon balance, which is input to a Life-Cycle Assessment of wood product use to estimate net carbon emissions to the atmosphere for harvest scenarios and bioenergy production. Such robust and interdisciplinary approaches are needed to more accurately quantify impacts on ecosystems and "what the atmosphere sees" in terms of greenhouse gas sources and impacts on ecosystems across landscapes and regions.

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.

A framework for predicting impacts on ecosystem services from (sub)organismal responses to chemicals.

PubMed

Forbes, Valery E; Salice, Chris J; Birnir, Bjorn; Bruins, Randy J F; Calow, Peter; Ducrot, Virginie; Galic, Nika; Garber, Kristina; Harvey, Bret C; Jager, Henriette; Kanarek, Andrew; Pastorok, Robert; Railsback, Steve F; Rebarber, Richard; Thorbek, Pernille

2017-04-01

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. Environ Toxicol Chem 2017;36:845-859. © 2017 SETAC. © 2017 SETAC.

Role of lake-wide prey fish survey in understanding ecosystem dynamics and managing fisheries of Lake Michigan

USGS Publications Warehouse

Madenjian, Charles P.; Edsall, T.; Munawar, M.

2005-01-01

With this study, the role of this lake-wide prey fish survey in both understanding the dynamics of the Lake Michigan ecosystem and managing Lake Michigan fisheries was documented. The complexity of ecosystems is such that long-term study is required before the dynamics of the ecosystem can be understoond. Furthermore, long-term observation is needed before important or meaningful questions about ecosystem dynamics can be asked. My approach is to first illustrate, by example, the usefulness of the survey results in providing insights into the dynamics of the Lake Michigan ecosystem. Then, examples of direct application of the survey results toward Lake Michigan fisheries management are presented.

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.

Modeling forest development after fire disturbance: Climate, soil organic layer, and nitrogen jointly affect forest canopy species and long-term ecosystem carbon accumulation in the North American boreal forest

NASA Astrophysics Data System (ADS)

Trugman, A. T.; Fenton, N.; Bergeron, Y.; Xu, X.; Welp, L.; Medvigy, D.

2015-12-01

Soil organic layer dynamics strongly affect boreal forest development after fire. Field studies show that soil organic layer thickness exerts a species-specific control on propagule establishment in the North American boreal forest. On organic soils thicker than a few centimeters, all propagules are less able to recruit, but broadleaf trees recruit less effectively than needleleaf trees. In turn, forest growth controls organic layer accumulation through modulating litter input and litter quality. These dynamics have not been fully incorporated into models, but may be essential for accurate projections of ecosystem carbon storage. Here, we develop a data-constrained model for understanding boreal forest development after fire. We update the ED2 model to include new aspen and black spruce species-types, species-specific propagule survivorship dependent on soil organic layer depth, species-specific litter decay rates, dynamically accumulating moss and soil organic layers, and nitrogen fixation by cyanobacteria associated with moss. The model is validated against diverse observations ranging from monthly to centennial timescales and spanning a climate gradient in Alaska, central Canada, and Quebec. We then quantify differences in forest development that result from changes in organic layer accumulation, temperature, and nitrogen. We find that (1) the model accurately reproduces a range of observations throughout the North American boreal forest; (2) the presence of a thick organic layer results in decreased decomposition and decreased aboveground productivity, effects that can increase or decrease ecosystem carbon uptake depending on location-specific attributes; (3) with a mean warming of 4°C, some forests switch from undergoing succession to needleleaf forests to recruiting multiple cohorts of broadleaf trees, decreasing ecosystem accumulation by ~30% after 300 years; (4) the availability of nitrogen regulates successional dynamics such than broadleaf species are less able to compete with needleleaf trees under low nitrogen regimes. We conclude that a joint regulation between the soil organic layer, temperature, and nitrogen will likely play an important role in influencing boreal forests development after fire in future climates, and should be represented in models.

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.

Montane ecosystem productivity responds more to global circulation patterns than climatic trends.

PubMed

Desai, A R; Wohlfahrt, G; Zeeman, M J; Katata, G; Eugster, W; Montagnani, L; Gianelle, D; Mauder, M; Schmid, H-P

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

Montane ecosystem productivity responds more to global circulation patterns than climatic trends

NASA Astrophysics Data System (ADS)

Desai, A. R.; Wohlfahrt, G.; Zeeman, M. J.; Katata, G.; Eugster, W.; Montagnani, L.; Gianelle, D.; Mauder, M.; Schmid, H.-P.

2016-02-01

Regional ecosystem productivity is highly sensitive to inter-annual climate variability, both within and outside the primary carbon uptake period. However, Earth system models lack sufficient spatial scales and ecosystem processes to resolve how these processes may change in a warming climate. Here, we show, how for the European Alps, mid-latitude Atlantic ocean winter circulation anomalies drive high-altitude summer forest and grassland productivity, through feedbacks among orographic wind circulation patterns, snowfall, winter and spring temperatures, and vegetation activity. Therefore, to understand future global climate change influence to regional ecosystem productivity, Earth systems models need to focus on improvements towards topographic downscaling of changes in regional atmospheric circulation patterns and to lagged responses in vegetation dynamics to non-growing season climate anomalies.

Consistent nutrient storage and supply mediated by diverse fish communities in coral reef ecosystems.

PubMed

Allgeier, Jacob E; Layman, Craig A; Mumby, Peter J; Rosemond, Amy D

2014-08-01

Corals thrive in low nutrient environments and the conservation of these globally imperiled ecosystems is largely dependent on mitigating the effects of anthropogenic nutrient enrichment. However, to better understand the implications of anthropogenic nutrients requires a heightened understanding of baseline nutrient dynamics within these ecosystems. Here, we provide a novel perspective on coral reef nutrient dynamics by examining the role of fish communities in the supply and storage of nitrogen (N) and phosphorus (P). We quantified fish-mediated nutrient storage and supply for 144 species and modeled these data onto 172 fish communities (71 729 individual fish), in four types of coral reefs, as well as seagrass and mangrove ecosystems, throughout the Northern Antilles. Fish communities supplied and stored large quantities of nutrients, with rates varying among ecosystem types. The size structure and diversity of the fish communities best predicted N and P supply and storage and N : P supply, suggesting that alterations to fish communities (e.g., overfishing) will have important implications for nutrient dynamics in these systems. The stoichiometric ratio (N : P) for storage in fish mass (~8 : 1) and supply (~20 : 1) was notably consistent across the four coral reef types (but not seagrass or mangrove ecosystems). Published nutrient enrichment studies on corals show that deviations from this N : P supply ratio may be associated with poor coral fitness, providing qualitative support for the hypothesis that corals and their symbionts may be adapted to specific ratios of nutrient supply. Consumer nutrient stoichiometry provides a baseline from which to better understand nutrient dynamics in coral reef and other coastal ecosystems, information that is greatly needed if we are to implement more effective measures to ensure the future health of the world's oceans. © 2014 John Wiley & Sons Ltd.

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.

Successional dynamics drive tropical forest nutrient limitation

NASA Astrophysics Data System (ADS)

Chou, C.; Hedin, L. O. O.

2017-12-01

It is increasingly recognized that nutrients such as N and P may significantly constrain the land carbon sink. However, we currently lack a complete understanding of these nutrient cycles in forest ecosystems and how to incorporate them into Earth System Models. We have developed a framework of dynamic forest nutrient limitation, focusing on the role of secondary forest succession and canopy gap disturbances as bottlenecks of high plant nutrient demand and limitation. We used succession biomass data to parameterize a simple ecosystem model and examined the dynamics of nutrient limitation throughout tropical secondary forest succession. Due to the patterns of biomass recovery in secondary tropical forests, we found high nutrient demand from rapid biomass accumulation in the earliest years of succession. Depending on previous land use scenarios, soil nutrient availability may also be low in this time period. Coupled together, this is evidence that there may be high biomass nutrient limitation early in succession, which is partially met by abundant symbiotic nitrogen fixation from certain tree species. We predict a switch from nitrogen limitation in early succession to one of three conditions: (i) phosphorus only, (ii) phosphorus plus nitrogen, or (iii) phosphorus, nitrogen, plus light co-limitation. We will discuss the mechanisms that govern the exact trajectory of limitation as forests build biomass. In addition, we used our model to explore scenarios of tropical secondary forest impermanence and the impacts of these dynamics on ecosystem nutrient limitation. We found that secondary forest impermanence exacerbates nutrient limitation and the need for nitrogen fixation early in succession. Together, these results indicate that biomass recovery dynamics early in succession as well as their connection to nutrient demand and limitation are fundamental for understanding and modeling nutrient limitation of the tropical forest carbon sink.

From Rivers to Oceans and Back: Linking Models to Encompass the Full Salmon Life Cycle

NASA Astrophysics Data System (ADS)

Danner, E.; Hendrix, N.; Martin, B.; Lindley, S. T.

2016-02-01

Pacific salmon are a promising study subject for investigating the linkages between freshwater and coastal ocean ecosystems. Salmon use a wide range of habitats throughout their life cycle as they move with water from mountain streams, mainstem rivers, estuaries, bays, and coastal oceans, with adult fish swimming back through the same migration route they took as juveniles. Conditions in one habitat can have growth and survival consequences that manifest in the following habitat, so is key that full life cycle models are used to further our understanding salmon population dynamics. Given the wide range of habitats and potential stressors, this approach requires the coordination of a multidisciplinary suite of physical and biological models, including climate, hydrologic, hydraulic, food web, circulation, bioenergetic, and ecosystem models. Here we present current approaches to linking physical and biological models that capture the foundational drivers for salmon in complex and dynamic systems.

Calibration and analysis of genome-based models for microbial ecology.

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

Microbial ecosystem modeling is complicated by the large number of unknown parameters and the lack of appropriate calibration tools. Here we present a novel computational framework for modeling microbial ecosystems, which combines genome-based model construction with statistical analysis and calibration to experimental data. Using this framework, we examined the dynamics of a community of Escherichia coli strains that emerged in laboratory evolution experiments, during which an ancestral strain diversified into two coexisting ecotypes. We constructed a microbial community model comprising the ancestral and the evolved strains, which we calibrated using separate monoculture experiments. Simulations reproduced the successional dynamics in the evolution experiments, and pathway activation patterns observed in microarray transcript profiles. Our approach yielded detailed insights into the metabolic processes that drove bacterial diversification, involving acetate cross-feeding and competition for organic carbon and oxygen. Our framework provides a missing link towards a data-driven mechanistic microbial ecology.

Diversity, Adaptability and Ecosystem Resilience

NASA Astrophysics Data System (ADS)

Keribin, Rozenn; Friend, Andrew

2013-04-01

Our ability to predict climate change and anticipate its impacts depends on Earth System Models (ESMs) and their ability to account for the high number of interacting components of the Earth System and to gauge both their influence on the climate and the feedbacks they induce. The land carbon cycle is a component of ESMs that is still poorly constrained. Since the 1990s dynamic global vegetation models (DGVMs) have become the main tool through which we understand the interactions between plant ecosystems and the climate. While DGVMs have made it clear the impacts of climate change on vegetation could be dramatic, predicting the dieback of rainforests and massive carbon losses from various ecosystems, they are highly variable both in their composition and their predictions. Their treatment of plant diversity and competition in particular vary widely and are based on highly-simplified relationships that do not account for the multiple levels of diversity and adaptability found in real plant ecosystems. The aim of this GREENCYCLES II project is to extend an individual-based DGVM to treat the diversity of physiologies found in plant communities and evaluate their effect if any on the ecosystem's transient dynamics and resilience. In the context of the InterSectoral Impacts Model Intercomparison Project (ISI-MIP), an initiative coordinated by a team at the Potsdam Institute for Climate Impact Research (PIK) that aims to provide fast-track global impact assessments for the IPCC's Fifth Assessment Report, we compare 6 vegetation models including 4 DGVMs under different climate change scenarios and analyse how the very different treatments of plant diversity and interactions from one model to the next affect the models' results. We then investigate a new, more mechanistic method of incorporating plant diversity into the DGVM "Hybrid" based on ecological tradeoffs mediated by plant traits and individual-based competition for light.

Application of ecosystem-scale fate and bioaccumulation models to predict fish mercury response times to changes in atmospheric deposition.

PubMed

Knightes, Christopher D; Sunderland, Elsie M; Craig Barber, M; Johnston, John M; Ambrose, Robert B

2009-04-01

Management strategies for controlling anthropogenic mercury emissions require understanding how ecosystems will respond to changes in atmospheric mercury deposition. Process-based mathematical models are valuable tools for informing such decisions, because measurement data often are sparse and cannot be extrapolated to investigate the environmental impacts of different policy options. Here, we bring together previously developed and evaluated modeling frameworks for watersheds, water bodies, and food web bioaccumulation of mercury. We use these models to investigate the timescales required for mercury levels in predatory fish to change in response to altered mercury inputs. We model declines in water, sediment, and fish mercury concentrations across five ecosystems spanning a range of physical and biological conditions, including a farm pond, a seepage lake, a stratified lake, a drainage lake, and a coastal plain river. Results illustrate that temporal lags are longest for watershed-dominated systems (like the coastal plain river) and shortest for shallow water bodies (like the seepage lake) that receive most of their mercury from deposition directly to the water surface. All ecosystems showed responses in two phases: A relatively rapid initial decline in mercury concentrations (20-60% of steady-state values) over one to three decades, followed by a slower descent lasting for decades to centuries. Response times are variable across ecosystem types and are highly affected by sediment burial rates and active layer depths in systems not dominated by watershed inputs. Additional research concerning watershed processes driving mercury dynamics and empirical data regarding sediment dynamics in freshwater bodies are critical for improving the predictive capability of process-based mercury models used to inform regulatory decisions.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Carbon fluxes in tropical forest ecosystems: the value of Eddy-covariance data for individual-based dynamic forest gap models

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

The effects of climatic inter-annual fluctuations and human activities on the global carbon cycle are uncertain and currently a major issue in global vegetation models. Individual-based forest gap models, on the other hand, model vegetation structure and dynamics on a small spatial (<100 ha) and large temporal scale (>1000 years). They are well-established tools to reproduce successions of highly-diverse forest ecosystems and investigate disturbances as logging or fire events. However, the parameterizations of the relationships between short-term climate variability and forest model processes are often uncertain in these models (e.g. daily variable temperature and gross primary production (GPP)) and cannot be constrained from forest inventories. We addressed this uncertainty and linked high-resolution Eddy-covariance (EC) data with an individual-based forest gap model. The forest model FORMIND was applied to three diverse tropical forest sites in the Amazonian rainforest. Species diversity was categorized into three plant functional types. The parametrizations for the steady-state of biomass and forest structure were calibrated and validated with different forest inventories. The parameterizations of relationships between short-term climate variability and forest model processes were evaluated with EC-data on a daily time step. The validations of the steady-state showed that the forest model could reproduce biomass and forest structures from forest inventories. The daily estimations of carbon fluxes showed that the forest model reproduces GPP as observed by the EC-method. Daily fluctuations of GPP were clearly reflected as a response to daily climate variability. Ecosystem respiration remains a challenge on a daily time step due to a simplified soil respiration approach. In the long-term, however, the dynamic forest model is expected to estimate carbon budgets for highly-diverse tropical forests where EC-measurements are rare.

Stochastic simulations of a synthetic bacteria-yeast ecosystem

PubMed Central

2012-01-01

Background The field of synthetic biology has greatly evolved and numerous functions can now be implemented by artificially engineered cells carrying the appropriate genetic information. However, in order for the cells to robustly perform complex or multiple tasks, co-operation between them may be necessary. Therefore, various synthetic biological systems whose functionality requires cell-cell communication are being designed. These systems, microbial consortia, are composed of engineered cells and exhibit a wide range of behaviors. These include yeast cells whose growth is dependent on one another, or bacteria that kill or rescue each other, synchronize, behave as predator-prey ecosystems or invade cancer cells. Results In this paper, we study a synthetic ecosystem comprising of bacteria and yeast that communicate with and benefit from each other using small diffusible molecules. We explore the behavior of this heterogeneous microbial consortium, composed of Saccharomyces cerevisiae and Escherichia coli cells, using stochastic modeling. The stochastic model captures the relevant intra-cellular and inter-cellular interactions taking place in and between the eukaryotic and prokaryotic cells. Integration of well-characterized molecular regulatory elements into these two microbes allows for communication through quorum sensing. A gene controlling growth in yeast is induced by bacteria via chemical signals and vice versa. Interesting dynamics that are common in natural ecosystems, such as obligatory and facultative mutualism, extinction, commensalism and predator-prey like dynamics are observed. We investigate and report on the conditions under which the two species can successfully communicate and rescue each other. Conclusions This study explores the various behaviors exhibited by the cohabitation of engineered yeast and bacterial cells. The way that the model is built allows for studying the dynamics of any system consisting of two species communicating with one another via chemical signals. Therefore, key information acquired by our model may potentially drive the experimental design of various synthetic heterogeneous ecosystems. PMID:22672814

Identifying grasslands suitable for cellulosic feedstock crops in the Greater Platte River Basin: dynamic modeling of ecosystem performance with 250 m eMODIS

USGS Publications Warehouse

Gu, Yingxin; Boyte, Stephen P.; Wylie, Bruce K.; Tieszen, Larry L.

2012-01-01

This study dynamically monitors ecosystem performance (EP) to identify grasslands potentially suitable for cellulosic feedstock crops (e.g., switchgrass) within the Greater Platte River Basin (GPRB). We computed grassland site potential and EP anomalies using 9-year (2000–2008) time series of 250 m expedited moderate resolution imaging spectroradiometer Normalized Difference Vegetation Index data, geophysical and biophysical data, weather and climate data, and EP models. We hypothesize that areas with fairly consistent high grassland productivity (i.e., high grassland site potential) in fair to good range condition (i.e., persistent ecosystem overperformance or normal performance, indicating a lack of severe ecological disturbance) are potentially suitable for cellulosic feedstock crop development. Unproductive (i.e., low grassland site potential) or degraded grasslands (i.e., persistent ecosystem underperformance with poor range condition) are not appropriate for cellulosic feedstock development. Grassland pixels with high or moderate ecosystem site potential and with more than 7 years ecosystem normal performance or overperformance during 2000–2008 are identified as possible regions for future cellulosic feedstock crop development (ca. 68 000 km2 within the GPRB, mostly in the eastern areas). Long-term climate conditions, elevation, soil organic carbon, and yearly seasonal precipitation and temperature are important performance variables to determine the suitable areas in this study. The final map delineating the suitable areas within the GPRB provides a new monitoring and modeling approach that can contribute to decision support tools to help land managers and decision makers make optimal land use decisions regarding cellulosic feedstock crop development and sustainability.

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.

Modeling landscape net ecosystem productivity (LandNEP) under alternative management regimes

Treesearch

Eugenie S. Euskirchen; Jiquan Chen; Harbin Li; Eric J. Gustafson; Thomas R. Crow

2002-01-01

Forests have been considered as a major carbon sink within the global carbon budget. However, a fragmented forest landscape varies significantly in its composition and age structure, and the amount of carbon sequestered at this level remains generally unknown to the scientific community. More precisely, the temporal dynamics and spatial distribution of net ecosystem...

Prediction of harmful water quality parameters combining weather, air quality and ecosystem models with in situ measurement

EPA Science Inventory

The ability to predict water quality in lakes is important since lakes are sources of water for agriculture, drinking, and recreational uses. Lakes are also home to a dynamic ecosystem of lacustrine wetlands and deep waters. They are sensitive to pH changes and are dependent on d...

Integrating a process-based ecosystem model with Landsat imagery to assess impacts of forest disturbance on terrestrial carbon dynamics: Case studies in Alabama and Mississippi

USDA-ARS?s Scientific Manuscript database

Forest ecosystems in the southern United States are dramatically altered by three major 26 disturbances: timber harvesting, hurricane, and permanent land conversion. Understanding and quantifying effects of disturbance on forest carbon, nitrogen, and water cycles is critical for sustainable forest m...

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...

Quantifying characteristic growth dynamics in a semiarid grassland ecosystem by predicting short-term NDVI phenology from daily rainfall: a simple 4 parameter coupled-reservoir model

USDA-ARS?s Scientific Manuscript database

Predicting impacts of the magnitude and seasonal timing of rainfall pulses in water-limited grassland ecosystems concerns ecologists, climate scientists, hydrologists, and a variety of stakeholders. This report describes a simple, effective procedure to emulate the seasonal response of grassland bio...

Future changes in coastal upwelling ecosystems with global warming: The case of the California Current System.

PubMed

Xiu, Peng; Chai, Fei; Curchitser, Enrique N; Castruccio, Frederic S

2018-02-12

Coastal upwelling ecosystems are among the most productive ecosystems in the world, meaning that their response to climate change is of critical importance. Our understanding of climate change impacts on marine ecosystems is largely limited to the open ocean, mainly because coastal upwelling is poorly reproduced by current earth system models. Here, a high-resolution model is used to examine the response of nutrients and plankton dynamics to future climate change in the California Current System (CCS). The results show increased upwelling intensity associated with stronger alongshore winds in the coastal region, and enhanced upper-ocean stratification in both the CCS and open ocean. Warming of the open ocean forces isotherms downwards, where they make contact with water masses with higher nutrient concentrations, thereby enhancing the nutrient flux to the deep source waters of the CCS. Increased winds and eddy activity further facilitate upward nutrient transport to the euphotic zone. However, the plankton community exhibits a complex and nonlinear response to increased nutrient input, as the food web dynamics tend to interact differently. This analysis highlights the difficulty in understanding how the marine ecosystem responds to a future warming climate, given to range of relevant processes operating at different scales.

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.

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.

A STELLA model to estimate water and nitrogen dynamics in a short-rotation woody crop plantation

Treesearch

Ying Ouyang; Jiaen Zhang; Theodor D. Leininger; Brent R. Frey

2015-01-01

Although short-rotation woody crop biomass production technology has demonstrated a promising potential to supply feedstocks for bioenergy production, the water and nutrient processes in the woody crop planation ecosystem are poorly understood. In this study, a computer model was developed to estimate the dynamics of water and nitrogen (N) species (e.g., NH4...

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

DOE PAGES

Chen, M.; Zhuang, Q.; Cook, D. R.; ...

2011-09-21

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. First we modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000–2005 at a 0.05° × 0.05° spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr -1 and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr -1 and net ecosystem production (NEP) varies within 0.08– 0.73 PgC yr -1 over the period 2000–2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr -1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Lastly, our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less

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.

Quantification of Terrestrial Ecosystem Carbon Dynamics in the Conterminous United States Combining a Process-Based Biogeochemical Model and MODIS and AmeriFlux data

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

Chen, Min; Zhuang, Qianlai; Cook, David R.

2011-09-21

Satellite remote sensing provides continuous temporal and spatial information of terrestrial 24 ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical 25 models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate 26 quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution 27 Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index 28 (LSWI) and carbon flux data of AmeriFlux to conduct such a study. We first modify the gross primary 29 production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of themore » 30 changes of canopy photosynthetic capacity, phenology and water stress. Second, we parameterize and 31 verify the new version of TEM with eddy flux data. We then apply the model to the conterminous 32 United States over the period 2000-2005 at a 0.05o ×0.05o spatial resolution. We find that the new 33 version of TEM generally captured the expected temporal and spatial patterns of regional carbon 34 dynamics. We estimate that regional GPP is between 7.02 and 7.78 Pg C yr-1 and net primary 35 production (NPP) ranges from 3.81 to 4.38 Pg C yr-1 and net ecosystem production (NEP) varies 36 within 0.08-0.73 Pg C yr-1 over the period 2000-2005 for the conterminous United States. The 37 uncertainty due to parameterization is 0.34, 0.65 and 0.18 Pg C yr-1 for the regional estimates of GPP, 38 NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 39 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Our study provides a 40 new independent and more adequate measure of carbon fluxes for the conterminous United States, 41 which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon 42 management and climate.« less

Quantification of terrestrial ecosystem carbon dynamics in the conterminous United States combining a process-based biogeochemical model and MODIS and AmeriFlux data

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

Chen, M.; Zhuang, Q.; Cook, D. R.

Satellite remote sensing provides continuous temporal and spatial information of terrestrial ecosystems. Using these remote sensing data and eddy flux measurements and biogeochemical models, such as the Terrestrial Ecosystem Model (TEM), should provide a more adequate quantification of carbon dynamics of terrestrial ecosystems. Here we use Moderate Resolution Imaging Spectroradiometer (MODIS) Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI) and carbon flux data of AmeriFlux to conduct such a study. First we modify the gross primary production (GPP) modeling in TEM by incorporating EVI and LSWI to account for the effects of the changes of canopy photosynthetic capacity, phenologymore » and water stress. Second, we parameterize and verify the new version of TEM with eddy flux data. We then apply the model to the conterminous United States over the period 2000–2005 at a 0.05° × 0.05° spatial resolution. We find that the new version of TEM made improvement over the previous version and generally captured the expected temporal and spatial patterns of regional carbon dynamics. We estimate that regional GPP is between 7.02 and 7.78 PgC yr -1 and net primary production (NPP) ranges from 3.81 to 4.38 Pg Cyr -1 and net ecosystem production (NEP) varies within 0.08– 0.73 PgC yr -1 over the period 2000–2005 for the conterminous United States. The uncertainty due to parameterization is 0.34, 0.65 and 0.18 PgC yr -1 for the regional estimates of GPP, NPP and NEP, respectively. The effects of extreme climate and disturbances such as severe drought in 2002 and destructive Hurricane Katrina in 2005 were captured by the model. Lastly, our study provides a new independent and more adequate measure of carbon fluxes for the conterminous United States, which will benefit studies of carbon-climate feedback and facilitate policy-making of carbon management and climate.« less

Drivers of dissolved organic carbon export in a subarctic catchment: Importance of microbial decomposition, sorption-desorption, peatland and lateral flow.

PubMed

Tang, Jing; Yurova, Alla Y; Schurgers, Guy; Miller, Paul A; Olin, Stefan; Smith, Benjamin; Siewert, Matthias B; Olefeldt, David; Pilesjö, Petter; Poska, Anneli

2018-05-01

Tundra soils account for 50% of global stocks of soil organic carbon (SOC), and it is expected that the amplified climate warming in high latitude could cause loss of this SOC through decomposition. Decomposed SOC could become hydrologically accessible, which increase downstream dissolved organic carbon (DOC) export and subsequent carbon release to the atmosphere, constituting a positive feedback to climate warming. However, DOC export is often neglected in ecosystem models. In this paper, we incorporate processes related to DOC production, mineralization, diffusion, sorption-desorption, and leaching into a customized arctic version of the dynamic ecosystem model LPJ-GUESS in order to mechanistically model catchment DOC export, and to link this flux to other ecosystem processes. The extended LPJ-GUESS is compared to observed DOC export at Stordalen catchment in northern Sweden. Vegetation communities include flood-tolerant graminoids (Eriophorum) and Sphagnum moss, birch forest and dwarf shrub communities. The processes, sorption-desorption and microbial decomposition (DOC production and mineralization) are found to contribute most to the variance in DOC export based on a detailed variance-based Sobol sensitivity analysis (SA) at grid cell-level. Catchment-level SA shows that the highest mean DOC exports come from the Eriophorum peatland (fen). A comparison with observations shows that the model captures the seasonality of DOC fluxes. Two catchment simulations, one without water lateral routing and one without peatland processes, were compared with the catchment simulations with all processes. The comparison showed that the current implementation of catchment lateral flow and peatland processes in LPJ-GUESS are essential to capture catchment-level DOC dynamics and indicate the model is at an appropriate level of complexity to represent the main mechanism of DOC dynamics in soils. The extended model provides a new tool to investigate potential interactions among climate change, vegetation dynamics, soil hydrology and DOC dynamics at both stand-alone to catchment scales. Copyright © 2017 Elsevier B.V. All rights reserved.

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.

Implications of tristability in pattern-forming ecosystems

NASA Astrophysics Data System (ADS)

Zelnik, Yuval R.; Gandhi, Punit; Knobloch, Edgar; Meron, Ehud

2018-03-01

Many ecosystems show both self-organized spatial patterns and multistability of possible states. The combination of these two phenomena in different forms has a significant impact on the behavior of ecosystems in changing environments. One notable case is connected to tristability of two distinct uniform states together with patterned states, which has recently been found in model studies of dryland ecosystems. Using a simple model, we determine the extent of tristability in parameter space, explore its effects on the system dynamics, and consider its implications for state transitions or regime shifts. We analyze the bifurcation structure of model solutions that describe uniform states, periodic patterns, and hybrid states between the former two. We map out the parameter space where these states exist, and note how the different states interact with each other. We further focus on two special implications with ecological significance, breakdown of the snaking range and complex fronts. We find that the organization of the hybrid states within a homoclinic snaking structure breaks down as it meets a Maxwell point where simple fronts are stationary. We also discover a new series of complex fronts between the uniform states, each with its own velocity. We conclude with a brief discussion of the significance of these findings for the dynamics of regime shifts and their potential control.

Changes in future fire regimes under climate change

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Temporal and spatial constraints on community assembly during microbial colonization of wood in seawater.

PubMed

Kalenitchenko, Dimitri; Fagervold, Sonja K; Pruski, Audrey M; Vétion, Gilles; Yücel, Mustafa; Le Bris, Nadine; Galand, Pierre E

2015-12-01

Wood falls on the ocean floor form chemosynthetic ecosystems that remain poorly studied compared with features such as hydrothermal vents or whale falls. In particular, the microbes forming the base of this unique ecosystem are not well characterized and the ecology of communities is not known. Here we use wood as a model to study microorganisms that establish and maintain a chemosynthetic ecosystem. We conducted both aquaria and in situ deep-sea experiments to test how different environmental constraints structure the assembly of bacterial, archaeal and fungal communities. We also measured changes in wood lipid concentrations and monitored sulfide production as a way to detect potential microbial activity. We show that wood falls are dynamic ecosystems with high spatial and temporal community turnover, and that the patterns of microbial colonization change depending on the scale of observation. The most illustrative example was the difference observed between pine and oak wood community dynamics. In pine, communities changed spatially, with strong differences in community composition between wood microhabitats, whereas in oak, communities changed more significantly with time of incubation. Changes in community assembly were reflected by changes in phylogenetic diversity that could be interpreted as shifts between assemblies ruled by species sorting to assemblies structured by competitive exclusion. These ecological interactions followed the dynamics of the potential microbial metabolisms accompanying wood degradation in the sea. Our work showed that wood is a good model for creating and manipulating chemosynthetic ecosystems in the laboratory, and attracting not only typical chemosynthetic microbes but also emblematic macrofaunal species.

A spatial ecosystem and populations dynamics model (SEAPODYM) Modeling of tuna and tuna-like populations

NASA Astrophysics Data System (ADS)

Lehodey, Patrick; Senina, Inna; Murtugudde, Raghu

2008-09-01

An enhanced version of the spatial ecosystem and population dynamics model SEAPODYM is presented to describe spatial dynamics of tuna and tuna-like species in the Pacific Ocean at monthly resolution over 1° grid-boxes. The simulations are driven by a bio-physical environment predicted from a coupled ocean physical-biogeochemical model. This new version of SEAPODYM includes expanded definitions of habitat indices, movements, and natural mortality based on empirical evidences. A thermal habitat of tuna species is derived from an individual heat budget model. The feeding habitat is computed according to the accessibility of tuna predator cohorts to different vertically migrating and non-migrating micronekton (mid-trophic) functional groups. The spawning habitat is based on temperature and the coincidence of spawning fish with presence or absence of predators and food for larvae. The successful larval recruitment is linked to spawning stock biomass. Larvae drift with currents, while immature and adult tuna can move of their own volition, in addition to being advected by currents. A food requirement index is computed to adjust locally the natural mortality of cohorts based on food demand and accessibility to available forage components. Together these mechanisms induce bottom-up and top-down effects, and intra- (i.e. between cohorts) and inter-species interactions. The model is now fully operational for running multi-species, multi-fisheries simulations, and the structure of the model allows a validation from multiple data sources. An application with two tuna species showing different biological characteristics, skipjack ( Katsuwonus pelamis) and bigeye ( Thunnus obesus), is presented to illustrate the capacity of the model to capture many important features of spatial dynamics of these two different tuna species in the Pacific Ocean. The actual validation is presented in a companion paper describing the approach to have a rigorous mathematical parameter optimization [Senina, I., Sibert, J., Lehodey, P., 2008. Parameter estimation for basin-scale ecosystem-linked population models of large pelagic predators: application to skipjack tuna. Progress in Oceanography]. Once this evaluation and parameterization is complete, it may be possible to use the model for management of tuna stocks in the context of climate and ecosystem variability, and to investigate potential changes due to anthropogenic activities including global warming and fisheries pressures and management scenarios.

Bridging the gap between marine biogeochemical and fisheries sciences; configuring the zooplankton link

NASA Astrophysics Data System (ADS)

Mitra, Aditee; Castellani, Claudia; Gentleman, Wendy C.; Jónasdóttir, Sigrún H.; Flynn, Kevin J.; Bode, Antonio; Halsband, Claudia; Kuhn, Penelope; Licandro, Priscilla; Agersted, Mette D.; Calbet, Albert; Lindeque, Penelope K.; Koppelmann, Rolf; Møller, Eva F.; Gislason, Astthor; Nielsen, Torkel Gissel; St. John, Michael

2014-12-01

Exploring climate and anthropogenic impacts on marine ecosystems requires an understanding of how trophic components interact. However, integrative end-to-end ecosystem studies (experimental and/or modelling) are rare. Experimental investigations often concentrate on a particular group or individual species within a trophic level, while tropho-dynamic field studies typically employ either a bottom-up approach concentrating on the phytoplankton community or a top-down approach concentrating on the fish community. Likewise the emphasis within modelling studies is usually placed upon phytoplankton-dominated biogeochemistry or on aspects of fisheries regulation. In consequence the roles of zooplankton communities (protists and metazoans) linking phytoplankton and fish communities are typically under-represented if not (especially in fisheries models) ignored. Where represented in ecosystem models, zooplankton are usually incorporated in an extremely simplistic fashion, using empirical descriptions merging various interacting physiological functions governing zooplankton growth and development, and thence ignoring physiological feedback mechanisms. Here we demonstrate, within a modelled plankton food-web system, how trophic dynamics are sensitive to small changes in parameter values describing zooplankton vital rates and thus the importance of using appropriate zooplankton descriptors. Through a comprehensive review, we reveal the mismatch between empirical understanding and modelling activities identifying important issues that warrant further experimental and modelling investigation. These include: food selectivity, kinetics of prey consumption and interactions with assimilation and growth, form of voided material, mortality rates at different age-stages relative to prior nutrient history. In particular there is a need for dynamic data series in which predator and prey of known nutrient history are studied interacting under varied pH and temperature regimes.

A Sense of Place: Integrating Environmental Psychology into Marine Socio-Ecological Models

NASA Astrophysics Data System (ADS)

van Putten, I. E.; Fleming, A.; Fulton, E.; Plaganyi-Lloyd, E.

2016-02-01

Sense of place is a concept that is increasingly applied in different social research contexts where it can act as a bridge between disciplines that might otherwise work in parallel. A sense of place is a well established and flexible concept that has been empirically measured using different survey methods. The psychological principals and theories that underpin sense of place have been inextricably linked to the quality of ecological systems and the impact on development of the system, and vice versa. Ecological models and scenario analyses play an important role in characterising, assessing and predicting the potential impacts of alternative developments and other changes affecting ecological systems. To improve the predictive accuracy of ecological models, human drivers, interactions, and uses have been dynamically incorporated, for instance, through management strategy evaluation applied to marine ecosystem models. However, to date no socio-ecological models (whether terrestrial or marine) have been developed that incorporate a dynamic feedback between ecosystem characteristics and peoples' sense of place. These models thus essentially ignore the influence of environmental psychology on the way people use and interact with ecosystems. We develop a proof of concept and provide a mathematical basis for a Sense of Place Index (SoPI) that allows the quantitative integration of environmental psychology into socio-ecological models. Incorporating dynamic feedback between the SoPI for different resource user groups and the ecological system improves the accuracy and precision of predictions regarding future resource use as well as, ultimately, the potential state of the resource to be developed.

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).

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.

Lytic to temperate switching of viral communities

NASA Astrophysics Data System (ADS)

Knowles, B.; Silveira, C. B.; Bailey, B. A.; Barott, K.; Cantu, V. A.; Cobián-Güemes, A. G.; Coutinho, F. H.; Dinsdale, E. A.; Felts, B.; Furby, K. A.; George, E. E.; Green, K. T.; Gregoracci, G. B.; Haas, A. F.; Haggerty, J. M.; Hester, E. R.; Hisakawa, N.; Kelly, L. W.; Lim, Y. W.; Little, M.; Luque, A.; McDole-Somera, T.; McNair, K.; de Oliveira, L. S.; Quistad, S. D.; Robinett, N. L.; Sala, E.; Salamon, P.; Sanchez, S. E.; Sandin, S.; Silva, G. G. Z.; Smith, J.; Sullivan, C.; Thompson, C.; Vermeij, M. J. A.; Youle, M.; Young, C.; Zgliczynski, B.; Brainard, R.; Edwards, R. A.; Nulton, J.; Thompson, F.; Rohwer, F.

2016-03-01

Microbial viruses can control host abundances via density-dependent lytic predator-prey dynamics. Less clear is how temperate viruses, which coexist and replicate with their host, influence microbial communities. Here we show that virus-like particles are relatively less abundant at high host densities. This suggests suppressed lysis where established models predict lytic dynamics are favoured. Meta-analysis of published viral and microbial densities showed that this trend was widespread in diverse ecosystems ranging from soil to freshwater to human lungs. Experimental manipulations showed viral densities more consistent with temperate than lytic life cycles at increasing microbial abundance. An analysis of 24 coral reef viromes showed a relative increase in the abundance of hallmark genes encoded by temperate viruses with increased microbial abundance. Based on these four lines of evidence, we propose the Piggyback-the-Winner model wherein temperate dynamics become increasingly important in ecosystems with high microbial densities; thus ‘more microbes, fewer viruses’.

The Influence of Individual Variability on Zooplankton Population Dynamics under Different Environmental Conditions

NASA Astrophysics Data System (ADS)

Bi, R.; Liu, H.

2016-02-01

Understanding how biological components respond to environmental changes could be insightful to predict ecosystem trajectories under different climate scenarios. Zooplankton are key components of marine ecosystems and changes in their dynamics could have major impact on ecosystem structure. We developed an individual-based model of a common coastal calanoid copepod Acartia tonsa to examine how environmental factors affect zooplankton population dynamics and explore the role of individual variability in sustaining population under various environmental conditions consisting of temperature, food concentration and salinity. Total abundance, egg production and proportion of survival were used to measure population success. Results suggested population benefits from high level of individual variability under extreme environmental conditions including unfavorable temperature, salinity, as well as low food concentration, and selection on fast-growers becomes stronger with increasing individual variability and increasing environmental stress. Multiple regression analysis showed that temperature, food concentration, salinity and individual variability have significant effects on survival of A. tonsa population. These results suggest that environmental factors have great influence on zooplankton population, and individual variability has important implications for population survivability under unfavorable conditions. Given that marine ecosystems are at risk from drastic environmental changes, understanding how individual variability sustains populations could increase our capability to predict population dynamics in a changing environment.

Priming effects in boreal black spruce forest soils: quantitative evaluation and sensitivity analysis.

PubMed

Fan, Zhaosheng; Jastrow, Julie D; Liang, Chao; Matamala, Roser; Miller, Raymond Michael

2013-01-01

Laboratory studies show that introduction of fresh and easily decomposable organic carbon (OC) into soil-water systems can stimulate the decomposition of soil OC (SOC) via priming effects in temperate forests, shrublands, grasslands, and agro-ecosystems. However, priming effects are still not well understood in the field setting for temperate ecosystems and virtually nothing is known about priming effects (e.g., existence, frequency, and magnitude) in boreal ecosystems. In this study, a coupled dissolved OC (DOC) transport and microbial biomass dynamics model was developed to simultaneously simulate co-occurring hydrological, physical, and biological processes and their interactions in soil pore-water systems. The developed model was then used to examine the importance of priming effects in two black spruce forest soils, with and without underlying permafrost. Our simulations showed that priming effects were strongly controlled by the frequency and intensity of DOC input, with greater priming effects associated with greater DOC inputs. Sensitivity analyses indicated that priming effects were most sensitive to variations in the quality of SOC, followed by variations in microbial biomass dynamics (i.e., microbial death and maintenance respiration), highlighting the urgent need to better discern these key parameters in future experiments and to consider these dynamics in existing ecosystem models. Water movement carries DOC to deep soil layers that have high SOC stocks in boreal soils. Thus, greater priming effects were predicted for the site with favorable water movement than for the site with limited water flow, suggesting that priming effects might be accelerated for sites where permafrost degradation leads to the formation of dry thermokarst.

Modeling forest C and N allocation responses to free-air CO2 enrichment

NASA Astrophysics Data System (ADS)

Luus, Kristina; De Kauwe, Martin; Walker, Anthony; Werner, Christian; Iversen, Colleen; McCarthy, Heather; Medlyn, Belinda; Norby, Richard; Oren, Ram; Zak, Donald; Zaehle, Sönke

2015-04-01

Vegetation allocation patterns and soil-vegetation partitioning of C and N are predicted to change in response to rising atmospheric concentrations of CO2. These allocation responses to rising CO2 have been examined at the ecosystem level through through free-air CO2 enrichment (FACE) experiments, and their global implications for the timing of progressive N limitation (PNL) and C sequestration have been predicted for ~100 years using a variety of ecosystem models. However, recent FACE model-data syntheses studies [1,2,3] have indicated that ecosystem models do not capture the 5-10 year site-level ecosystem allocation responses to elevated CO2. This may be due in part to the missing representation of the rhizosphere interactions between plants and soil biota in models. Ecosystem allocation of C and N is altered by interactions between soil and vegetation through the priming effect: as plant N availability diminishes, plants respond physiologically by altering their tissue allocation strategies so as to increase rates of root growth and rhizodeposition. In response, either soil organic material begins to accumulate, which hastens the onset of PNL, or soil microbes start to decompose C more rapidly, resulting in increased N availability for plant uptake, which delays PNL. In this study, a straightforward approach for representing rhizosphere interactions in ecosystem models was developed through which C and N allocation to roots and rhizodeposition responds dynamically to elevated CO2 conditions, modifying soil decomposition rates without pre-specification of the direction in which soil C and N accumulation should shift in response to elevated CO2. This approach was implemented in a variety of ecosystem models ranging from stand (G'DAY), to land surface (CLM 4.5, O-CN), to dynamic global vegetation (LPJ-GUESS) models. Comparisons against data from three forest FACE sites (Duke, Oak Ridge & Rhinelander) indicated that representing rhizosphere interactions allowed models to more reliably capture responses of ecosystem C and N allocation to free-air CO2 enrichment because they were able to simulate the priming effect. Insights were therefore gained into between-site differences observed in forest FACE experiments, and the underlying physiological and biogeochemical mechanisms determining ecosystem C and N allocation responses to elevated CO2. References 1. De Kauwe, M. G., et al. (2014), Where does the carbon go? A model-data intercomparison of vegetation carbon allocation and turnover processes at two temperate forest free-air CO2 enrichment sites, New Phytologist, 203, 883-899. 2. Walker, A. P., et al. (2014), Comprehensive ecosystem model-data synthesis using multiple data sets at two temperate forest free-air CO2 enrichment experiments: Model performance at ambient CO2 concentration, Journal of Geophysical Research: Biogeosciences, 119, 937-964. 3. Zaehle, S., et al. (2014), Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies, New Phytologist, 202 (3), 803-822.

Driving terrestrial ecosystem models from space

NASA Technical Reports Server (NTRS)

Waring, R. H.

1993-01-01

Regional air pollution, land-use conversion, and projected climate change all affect ecosystem processes at large scales. Changes in vegetation cover and growth dynamics can impact the functioning of ecosystems, carbon fluxes, and climate. As a result, there is a need to assess and monitor vegetation structure and function comprehensively at regional to global scales. To provide a test of our present understanding of how ecosystems operate at large scales we can compare model predictions of CO2, O2, and methane exchange with the atmosphere against regional measurements of interannual variation in the atmospheric concentration of these gases. Recent advances in remote sensing of the Earth's surface are beginning to provide methods for estimating important ecosystem variables at large scales. Ecologists attempting to generalize across landscapes have made extensive use of models and remote sensing technology. The success of such ventures is dependent on merging insights and expertise from two distinct fields. Ecologists must provide the understanding of how well models emulate important biological variables and their interactions; experts in remote sensing must provide the biophysical interpretation of complex optical reflectance and radar backscatter data.

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.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

A dynamical model for bark beetle outbreaks

Treesearch

Vlastimil Krivan; Mark Lewis; Barbara J. Bentz; Sharon Bewick; Suzanne M. Lenhart; Andrew Liebhold

2016-01-01

Tree-killing bark beetles are major disturbance agents affecting coniferous forest ecosystems. The role of environmental conditions on driving beetle outbreaks is becoming increasingly important as global climatic change alters environmental factors, such as drought stress, that, in turn, govern tree resistance. Furthermore, dynamics between beetles and trees...

Modeling Diel Oxygen Dynamics and Ecosystem Metabolism in Weeks Bay, Alabama.

EPA Science Inventory

Weeks Bay is a shallow eutrophic estuary that exhibits frequent summertime diel-cycling hypoxia and periods of dissolved oxygen (DO) oversaturation during the day. Diel DO dynamics in shallow estuaries like Weeks Bay are complex, and may be influenced by wind forcing, vertical an...

DCMIP2016: a review of non-hydrostatic dynamical core design and intercomparison of participating models

NASA Astrophysics Data System (ADS)

Ullrich, Paul A.; Jablonowski, Christiane; Kent, James; Lauritzen, Peter H.; Nair, Ramachandran; Reed, Kevin A.; Zarzycki, Colin M.; Hall, David M.; Dazlich, Don; Heikes, Ross; Konor, Celal; Randall, David; Dubos, Thomas; Meurdesoif, Yann; Chen, Xi; Harris, Lucas; Kühnlein, Christian; Lee, Vivian; Qaddouri, Abdessamad; Girard, Claude; Giorgetta, Marco; Reinert, Daniel; Klemp, Joseph; Park, Sang-Hun; Skamarock, William; Miura, Hiroaki; Ohno, Tomoki; Yoshida, Ryuji; Walko, Robert; Reinecke, Alex; Viner, Kevin

2017-12-01

Atmospheric dynamical cores are a fundamental component of global atmospheric modeling systems and are responsible for capturing the dynamical behavior of the Earth's atmosphere via numerical integration of the Navier-Stokes equations. These systems have existed in one form or another for over half of a century, with the earliest discretizations having now evolved into a complex ecosystem of algorithms and computational strategies. In essence, no two dynamical cores are alike, and their individual successes suggest that no perfect model exists. To better understand modern dynamical cores, this paper aims to provide a comprehensive review of 11 non-hydrostatic dynamical cores, drawn from modeling centers and groups that participated in the 2016 Dynamical Core Model Intercomparison Project (DCMIP) workshop and summer school. This review includes a choice of model grid, variable placement, vertical coordinate, prognostic equations, temporal discretization, and the diffusion, stabilization, filters, and fixers employed by each system.

On the spatial dynamics and oscillatory behavior of a predator-prey model based on cellular automata and local particle swarm optimization.

PubMed

Molina, Mario Martínez; Moreno-Armendáriz, Marco A; Carlos Seck Tuoh Mora, Juan

2013-11-07

A two-dimensional lattice model based on Cellular Automata theory and swarm intelligence is used to study the spatial and population dynamics of a theoretical ecosystem. It is found that the social interactions among predators provoke the formation of clusters, and that by increasing the mobility of predators the model enters into an oscillatory behavior. © 2013 Elsevier Ltd. All rights reserved.

A framework for predicting impacts on ecosystem services ...

EPA Pesticide Factsheets

Protection of ecosystem services is increasingly emphasized as a risk-assessment goal, but there are wide gaps between current ecological risk-assessment endpoints and potential effects on services provided by ecosystems. The authors present a framework that links common ecotoxicological endpoints to chemical impacts on populations and communities and the ecosystem services that they provide. This framework builds on considerable advances in mechanistic effects models designed to span multiple levels of biological organization and account for various types of biological interactions and feedbacks. For illustration, the authors introduce 2 case studies that employ well-developed and validated mechanistic effects models: the inSTREAM individual-based model for fish populations and the AQUATOX ecosystem model. They also show how dynamic energy budget theory can provide a common currency for interpreting organism-level toxicity. They suggest that a framework based on mechanistic models that predict impacts on ecosystem services resulting from chemical exposure, combined with economic valuation, can provide a useful approach for informing environmental management. The authors highlight the potential benefits of using this framework as well as the challenges that will need to be addressed in future work. The framework introduced here represents an ongoing initiative supported by the National Institute of Mathematical and Biological Synthesis (NIMBioS; http://www.nimbi

LAI is the major cause of divergence in CO2 fertilization effect in land surface models

NASA Astrophysics Data System (ADS)

Li, Q.; Luo, Y.; Lu, X.; Wang, Y.; Huang, X.; Lin, G., Sr.

2017-12-01

Concentration-carbon feedback (β), also called CO2 fertilization effect, is an important feedback between terrestrial ecosystems and atmosphere to alleviate global climate change. However, models participating in C4MIP and CMIP5 predicted diverse CO2 fertilization effects under future CO2 inceasing scenarios. Hence identifing the key processes dominating the divergence of β in land surface models is of significance. We calculated CO2 fertilization effects from leaf level, canopy gross productivity level, net ecosystem productivity level and ecosystem carbon stock level in Community Atmosphere Biosphere Land Exchange (CABLE) model. Our results identified LAI is the key factor dominating the divergence of β among C3 plants in CABLE model. Saturation of the ecosystem productivity to increasing CO2 is not only regulated by leaf-level response, but also the response of LAI to increasing CO2. The greatest variation among C3 plants at ecosystem level suggests that other processes such as different allocation patterns and soil carbon dynamics of various vegetation types are also responsible for the divergence. Our results indicate that processes regarding to LAI need to be better calibrated according to experiments and observations in order to better represent the response of ecosystem productivity to increasing CO2.

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.

Strong spatial variability in trace gas dynamics following experimental drought in a humid tropical forest

Treesearch

Tana Wood; W. L. Silver

2012-01-01

[1] Soil moisture is a key driver of biogeochemical processes in terrestrial ecosystems, strongly affecting carbon (C) and nutrient availability as well as trace gas production and consumption in soils. Models predict increasing drought frequency in tropical forest ecosystems, which could feed back on future climate change directly via effects on trace gasdynamics and...

Fir sawyer beetle-Siberian fir interaction modeling: resistance of fir stands to insect outbreaks

Treesearch

Tamara M. Ovtchinnikova; Victor V. Kiselev

1991-01-01

Entomological monitoring is part of a total ecological monitoring system. Its purpose is the identification, prognosis, and estimation of forest ecosystem impacts induced by insects. The entomological monitoring of a forest is based on a clear understanding of the role played by insects in forest ecosystems. The patterns of insect population dynamics in space and time...

Introducing mixotrophy into a biogeochemical model describing an eutrophied coastal ecosystem: The Southern North Sea

NASA Astrophysics Data System (ADS)

Ghyoot, Caroline; Lancelot, Christiane; Flynn, Kevin J.; Mitra, Aditee; Gypens, Nathalie

2017-04-01

Most biogeochemical/ecological models divide planktonic protists between phototrophs (phytoplankton) and heterotrophs (zooplankton). However, a large number of planktonic protists are able to combine several mechanisms of carbon and nutrient acquisition. Not representing these multiple mechanisms in biogeochemical/ecological models describing eutrophied coastal ecosystems can potentially lead to different conclusions regarding ecosystem functioning, especially regarding the success of harmful algae, which are often reported as mixotrophic. This modelling study investigates, for the first time, the implications for trophic dynamics of including 3 contrasting forms of mixotrophy, namely osmotrophy (using alkaline phosphatase activity, APA), non-constitutive mixotrophy (acquired phototrophy by microzooplankton) and also constitutive mixotrophy. The application is in the Southern North Sea, an ecosystem that faced, between 1985 and 2005, a significant increase in the nutrient supply N:P ratio (from 31 to 81 mole N:P). The comparison with a traditional model shows that, when the winter N:P ratio in the Southern North Sea is above 22 molN molP-1 (as occurred from mid-1990s), APA allows a 3 to 32% increase of annual gross primary production (GPP). In result of the higher GPP, the annual sedimentation increases as well as the bacterial production. By contrast, APA does not affect the export of matter to higher trophic levels because the increased GPP is mainly due to Phaeocystis colonies, which are not grazed by copepods. The effect of non-constitutive mixotrophy depends on light and affects the ecosystem functioning in terms of annual GPP, transfer to higher trophic levels, sedimentation, and nutrient remineralisation. Constitutive mixotrophy in nanoflagellates appears to have little influence on this ecosystem functioning. An important conclusion from this work is that different forms of mixotrophy have different impacts on system dynamics and it is thus important to describe such differences in an appropriate fashion.

Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment

Treesearch

Alex Abdelnour; Robert B. McKane; Marc Stieglitz; Feifei Pan; Yiwei Cheng

2013-01-01

We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where two major disturbance events have occurred during the past 500 years: a stand-replacing fire...

THE DYNAMIC REGIME CONCEPT FOR ECOSYSTEM MANAGEMENT AND RESTORATION

EPA Science Inventory

Dynamic regimes of ecosystems are multidimensional basis of attraction, characterized by particular species communities and ecosystems processes. Ecosystem patterns and processes rarely respond linerarly to disturbances, and the nonlinear cynamic regime concept offers a more real...

The response of vegetation distribution, ecosystem productivity, and fire in California to future climate scenarios simulated by the MC1 dynamic vegetation dynamic.

Treesearch

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

2006-01-01

The objective of this study was to dynamically simulate the response of vegetation distribution, carbon, and fire to three scenarios of future climate change for California using the MAPSS-CENTURY (MCI) dynamic general vegetation model. Under all three scenarios, Alpine/Subalpine Forest cover declined with increased growing season length and warmth, and increases in...

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.

Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management

NASA Astrophysics Data System (ADS)

Müller, Felix; Burkhard, Benjamin; Kroll, Franziska

In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the "adaptive cycle". Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.

Wetland fire remote sensing research--The Greater Everglades example

USGS Publications Warehouse

Jones, John W.

2012-01-01

Fire is a major factor in the Everglades ecosystem. For thousands of years, lightning-strike fires from summer thunderstorms have helped create and maintain a dynamic landscape suited both to withstand fire and recover quickly in the wake of frequent fires. Today, managers in the Everglades National Park are implementing controlled burns to promote healthy, sustainable vegetation patterns and ecosystem functions. The U.S. Geological Survey (USGS) is using remote sensing to improve fire-management databases in the Everglades, gain insights into post-fire land-cover dynamics, and develop spatially and temporally explicit fire-scar data for habitat and hydrologic modeling.

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

NASA Astrophysics Data System (ADS)

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differed from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.

Meta-analysis of high-latitude nitrogen-addition and warming studies imply ecological mechanisms overlooked by land models

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

Bouskill, N. J.; Riley, W. J.; Tang, J.

2014-08-18

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the atmosphere. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the above and belowground high-latitude ecosystem responses to warming and nitrogen addition, and identified mechanisms absent, or poorly parameterized in CLM4.5. While the two model versions predicted similar trajectories for soil carbon stocks following both types of perturbation, other variables (e.g., belowground respiration) differedmore » from the observations in both magnitude and direction, indicating the underlying mechanisms are inadequate for representing high-latitude ecosystems. The observational synthesis attribute these differences to missing representations of microbial dynamics, characterization of above and belowground functional processes, and nutrient competition. We use the observational meta-analyses to discuss potential approaches to improving the current models (e.g., the inclusion of dynamic vegetation or different microbial functional guilds), however, we also raise a cautionary note on the selection of data sets and experiments to be included in a meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average =72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which preclude a rigorous evaluation of the model responses to nitrogen perturbation. Overall, we demonstrate here that elucidating ecological mechanisms via meta-analysis can identify deficiencies in both ecosystem models and empirical experiments.« less

Nitrogen dynamics post-harvest: the role of woody residues

Treesearch

Kathryn Piatek

2007-01-01

The role of woody residues in N dynamics in harvested forests has not been fully elucidated. Woody residues have been found to be an N sink, N source, and N neutral in different studies. To understand the implications of each of these scenarios, post-harvest N dynamics in high- and no- woody residue treatments were modeled for a Douglas-fir ecosystem. Nitrogen...

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

PubMed

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

2014-07-01

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

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

NASA Astrophysics Data System (ADS)

Scheiter, Simon; Savadogo, Patrice

2017-04-01

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

Habitat structure mediates biodiversity effects on ecosystem properties

PubMed Central

Godbold, J. A.; Bulling, M. T.; Solan, M.

2011-01-01

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised. PMID:21227969

Habitat structure mediates biodiversity effects on ecosystem properties.

PubMed

Godbold, J A; Bulling, M T; Solan, M

2011-08-22

Much of what we know about the role of biodiversity in mediating ecosystem processes and function stems from manipulative experiments, which have largely been performed in isolated, homogeneous environments that do not incorporate habitat structure or allow natural community dynamics to develop. Here, we use a range of habitat configurations in a model marine benthic system to investigate the effects of species composition, resource heterogeneity and patch connectivity on ecosystem properties at both the patch (bioturbation intensity) and multi-patch (nutrient concentration) scale. We show that allowing fauna to move and preferentially select patches alters local species composition and density distributions, which has negative effects on ecosystem processes (bioturbation intensity) at the patch scale, but overall positive effects on ecosystem functioning (nutrient concentration) at the multi-patch scale. Our findings provide important evidence that community dynamics alter in response to localized resource heterogeneity and that these small-scale variations in habitat structure influence species contributions to ecosystem properties at larger scales. We conclude that habitat complexity forms an important buffer against disturbance and that contemporary estimates of the level of biodiversity required for maintaining future multi-functional systems may need to be revised.

Assimilating satellite-based canopy height within an ecosystem model to estimate aboveground forest biomass

NASA Astrophysics Data System (ADS)

Joetzjer, E.; Pillet, M.; Ciais, P.; Barbier, N.; Chave, J.; Schlund, M.; Maignan, F.; Barichivich, J.; Luyssaert, S.; Hérault, B.; von Poncet, F.; Poulter, B.

2017-07-01

Despite advances in Earth observation and modeling, estimating tropical biomass remains a challenge. Recent work suggests that integrating satellite measurements of canopy height within ecosystem models is a promising approach to infer biomass. We tested the feasibility of this approach to retrieve aboveground biomass (AGB) at three tropical forest sites by assimilating remotely sensed canopy height derived from a texture analysis algorithm applied to the high-resolution Pleiades imager in the Organizing Carbon and Hydrology in Dynamic Ecosystems Canopy (ORCHIDEE-CAN) ecosystem model. While mean AGB could be estimated within 10% of AGB derived from census data in average across sites, canopy height derived from Pleiades product was spatially too smooth, thus unable to accurately resolve large height (and biomass) variations within the site considered. The error budget was evaluated in details, and systematic errors related to the ORCHIDEE-CAN structure contribute as a secondary source of error and could be overcome by using improved allometric equations.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

NASA Astrophysics Data System (ADS)

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, Anthony D.; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-12-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr-1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil RH with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

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

He, Yujie; Yang, Jinyan; Zhuang, Qianlai

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here in this study we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbialmore » dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO 2 efflux (R H) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil R H (7.5 ± 2.4 PgCyr -1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4-0.6) in the simulated spatial pattern of soil R H with both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = -0.43 to -0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.« less

Incorporating microbial dormancy dynamics into soil decomposition models to improve quantification of soil carbon dynamics of northern temperate forests

USGS Publications Warehouse

He, Yujie; Yang, Jinyan; Zhuang, Qianlai; Harden, Jennifer W.; McGuire, A. David; Liu, Yaling; Wang, Gangsheng; Gu, Lianhong

2015-01-01

Soil carbon dynamics of terrestrial ecosystems play a significant role in the global carbon cycle. Microbial-based decomposition models have seen much growth recently for quantifying this role, yet dormancy as a common strategy used by microorganisms has not usually been represented and tested in these models against field observations. Here we developed an explicit microbial-enzyme decomposition model and examined model performance with and without representation of microbial dormancy at six temperate forest sites of different forest types. We then extrapolated the model to global temperate forest ecosystems to investigate biogeochemical controls on soil heterotrophic respiration and microbial dormancy dynamics at different temporal-spatial scales. The dormancy model consistently produced better match with field-observed heterotrophic soil CO2 efflux (RH) than the no dormancy model. Our regional modeling results further indicated that models with dormancy were able to produce more realistic magnitude of microbial biomass (<2% of soil organic carbon) and soil RH (7.5 ± 2.4 Pg C yr−1). Spatial correlation analysis showed that soil organic carbon content was the dominating factor (correlation coefficient = 0.4–0.6) in the simulated spatial pattern of soil RHwith both models. In contrast to strong temporal and local controls of soil temperature and moisture on microbial dormancy, our modeling results showed that soil carbon-to-nitrogen ratio (C:N) was a major regulating factor at regional scales (correlation coefficient = −0.43 to −0.58), indicating scale-dependent biogeochemical controls on microbial dynamics. Our findings suggest that incorporating microbial dormancy could improve the realism of microbial-based decomposition models and enhance the integration of soil experiments and mechanistically based modeling.

Understory plant biomass dynamics of prescribed burned Pinus palustris stands

Treesearch

C.A. Gonzalez-Benecke; L.J. Samuelson; T.A. Stokes; W.P. Cropper Jr; T.A. Martin; K.H. Johnsen

2015-01-01

Longleaf pine (Pinus palustris Mill.) forests are characterized by unusually high understory plant species diversity, but models describing understory ground cover biomass, and hence fuel load dynamics, are scarce for this fire-dependent ecosystem. Only coarse scale estimates, being restricted on accuracy and geographical extrapolation,...

Modeling Diel Oxygen Dynamics and Ecosystem Metabolism in a Shallow, Eutrophic Estuary

EPA Science Inventory

Weeks Bay is a shallow eutrophic estuary that exhibits frequent summertime diel-cycling hypoxia and periods of dissolved oxygen (DO) oversaturation during the day. Diel DO dynamics in shallow estuaries like Weeks Bay are complex, and may be influenced by wind forcing, vertical an...

Importance of Nitrogen Availability on Land Carbon Sequestration in Northern Eurasia during the 21st Century

NASA Astrophysics Data System (ADS)

Kicklighter, D. W.; Melillo, J. M.; Monier, E.; Sokolov, A. P.; Lu, X.; Zhuang, Q.

2015-12-01

Atmospheric nitrogen deposition, nitrogen fixation, and the application of nitrogen fertilizers provide subsidies to land ecosystems that can increase nitrogen availability for vegetation production and thereby influence land carbon dynamics. In addition, enhanced decomposition of soil organic matter (SOM) from warming soils and permafrost degradation may also increase nitrogen availability in Northern Eurasia. Here, we examine how changes in nitrogen availability may influence land carbon dynamics in Northern Eurasia during the 21st century by comparing results for a "business as usual" scenario (the IPCC Representative Concentration Pathways or RCP 8.5) and a stabilization scenario (RCP 4.5) between a version of the Terrestrial Ecosystem Model that does not consider the effects of atmospheric nitrogen deposition, nitrogen fixation and soil thermal dynamics on land carbon dynamics (TEM 4.4) and a version that does consider these dynamics (TEM 6.0). In these simulations, atmospheric nitrogen deposition, nitrogen fixation, and fertilizer applications provide an additional 3.3 Pg N (RCP 4.5) to 3.9 Pg N (RCP 8.5) to Northern Eurasian ecosystems over the 21st century. Land ecosystems retain about 38% (RCP4.5) to 48% (RCP 8.5) of this nitrogen subsidy. Net nitrogen mineralization estimated by TEM 6.0 provide an additional 1.0 Pg N to vegetation than estimated by TEM 4.4 over the 21st century from enhanced decomposition of SOM including SOM formerly protected by permafrost. The enhanced nitrogen availability in TEM 6.0 allows Northern Eurasian ecosystems to sequester 1.8x (RCP 8.5) to 2.4x (RCP 4.5) more carbon over the 21st century than estimated by TEM 4.4. Our results indicate that consideration of nitrogen subsidies and soil thermal dynamics have a large influence on how simulated land carbon dynamics in Northern Eurasia will respond to future changes in climate, atmospheric chemistry, and disturbances.

Improving Marine Ecosystem Models with Biochemical Tracers

NASA Astrophysics Data System (ADS)

Pethybridge, Heidi R.; Choy, C. Anela; Polovina, Jeffrey J.; Fulton, Elizabeth A.

2018-01-01

Empirical data on food web dynamics and predator-prey interactions underpin ecosystem models, which are increasingly used to support strategic management of marine resources. These data have traditionally derived from stomach content analysis, but new and complementary forms of ecological data are increasingly available from biochemical tracer techniques. Extensive opportunities exist to improve the empirical robustness of ecosystem models through the incorporation of biochemical tracer data and derived indices, an area that is rapidly expanding because of advances in analytical developments and sophisticated statistical techniques. Here, we explore the trophic information required by ecosystem model frameworks (species, individual, and size based) and match them to the most commonly used biochemical tracers (bulk tissue and compound-specific stable isotopes, fatty acids, and trace elements). Key quantitative parameters derived from biochemical tracers include estimates of diet composition, niche width, and trophic position. Biochemical tracers also provide powerful insight into the spatial and temporal variability of food web structure and the characterization of dominant basal and microbial food web groups. A major challenge in incorporating biochemical tracer data into ecosystem models is scale and data type mismatches, which can be overcome with greater knowledge exchange and numerical approaches that transform, integrate, and visualize data.

A hybrid regional approach to model discharge at multiple sub-basins within the Calapooia Watershed, Oregon, USA

EPA Science Inventory

Modeling is a useful tool for quantifying ecosystem services and understanding their temporal dynamics. Here we describe a hybrid regional modeling approach for sub-basins of the Calapooia watershed that incorporates both a precipitation-runoff model and an indexed regression mo...

SHIMMER (1.0): a novel mathematical model for microbial and biogeochemical dynamics in glacier forefield ecosystems

NASA Astrophysics Data System (ADS)

Bradley, J. A.; Anesio, A. M.; Singarayer, J. S.; Heath, M. R.; Arndt, S.

2015-10-01

SHIMMER (Soil biogeocHemIcal Model for Microbial Ecosystem Response) is a new numerical modelling framework designed to simulate microbial dynamics and biogeochemical cycling during initial ecosystem development in glacier forefield soils. However, it is also transferable to other extreme ecosystem types (such as desert soils or the surface of glaciers). The rationale for model development arises from decades of empirical observations in glacier forefields, and enables a quantitative and process focussed approach. Here, we provide a detailed description of SHIMMER, test its performance in two case study forefields: the Damma Glacier (Switzerland) and the Athabasca Glacier (Canada) and analyse sensitivity to identify the most sensitive and unconstrained model parameters. Results show that the accumulation of microbial biomass is highly dependent on variation in microbial growth and death rate constants, Q10 values, the active fraction of microbial biomass and the reactivity of organic matter. The model correctly predicts the rapid accumulation of microbial biomass observed during the initial stages of succession in the forefields of both the case study systems. Primary production is responsible for the initial build-up of labile substrate that subsequently supports heterotrophic growth. However, allochthonous contributions of organic matter, and nitrogen fixation, are important in sustaining this productivity. The development and application of SHIMMER also highlights aspects of these systems that require further empirical research: quantifying nutrient budgets and biogeochemical rates, exploring seasonality and microbial growth and cell death. This will lead to increased understanding of how glacier forefields contribute to global biogeochemical cycling and climate under future ice retreat.

An online database for informing ecological network models: http://kelpforest.ucsc.edu.

PubMed

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H; Tinker, Martin T; Black, August; Caselle, Jennifer E; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui).

An Online Database for Informing Ecological Network Models: http://kelpforest.ucsc.edu

PubMed Central

Beas-Luna, Rodrigo; Novak, Mark; Carr, Mark H.; Tinker, Martin T.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/databaseui). PMID:25343723

An online database for informing ecological network models: http://kelpforest.ucsc.edu

USGS Publications Warehouse

Beas-Luna, Rodrigo; Tinker, M. Tim; Novak, Mark; Carr, Mark H.; Black, August; Caselle, Jennifer E.; Hoban, Michael; Malone, Dan; Iles, Alison C.

2014-01-01

Ecological network models and analyses are recognized as valuable tools for understanding the dynamics and resiliency of ecosystems, and for informing ecosystem-based approaches to management. However, few databases exist that can provide the life history, demographic and species interaction information necessary to parameterize ecological network models. Faced with the difficulty of synthesizing the information required to construct models for kelp forest ecosystems along the West Coast of North America, we developed an online database (http://kelpforest.ucsc.edu/) to facilitate the collation and dissemination of such information. Many of the database's attributes are novel yet the structure is applicable and adaptable to other ecosystem modeling efforts. Information for each taxonomic unit includes stage-specific life history, demography, and body-size allometries. Species interactions include trophic, competitive, facilitative, and parasitic forms. Each data entry is temporally and spatially explicit. The online data entry interface allows researchers anywhere to contribute and access information. Quality control is facilitated by attributing each entry to unique contributor identities and source citations. The database has proven useful as an archive of species and ecosystem-specific information in the development of several ecological network models, for informing management actions, and for education purposes (e.g., undergraduate and graduate training). To facilitate adaptation of the database by other researches for other ecosystems, the code and technical details on how to customize this database and apply it to other ecosystems are freely available and located at the following link (https://github.com/kelpforest-cameo/data​baseui).

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.

Distribution of phytoplankton functional types in high-nitrate, low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-11-01

Modeling and monitoring plankton functional types (PFTs) is challenged by the insufficient amount of field measurements of ground truths in both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs and focus on resolving the question of diatom-coccolithophore coexistence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high-latitude areas and indicate seasonal coexistence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, has so far not been captured by state-of-the-art dynamic models, which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Distribution of phytoplankton functional types in high-nitrate low-chlorophyll waters in a new diagnostic ecological indicator model

NASA Astrophysics Data System (ADS)

Palacz, A. P.; St. John, M. A.; Brewin, R. J. W.; Hirata, T.; Gregg, W. W.

2013-05-01

Modeling and monitoring plankton functional types (PFTs) is challenged by insufficient amount of field measurements to ground-truth both plankton models and bio-optical algorithms. In this study, we combine remote sensing data and a dynamic plankton model to simulate an ecologically-sound spatial and temporal distribution of phyto-PFTs. We apply an innovative ecological indicator approach to modeling PFTs, and focus on resolving the question of diatom-coccolithophore co-existence in the subpolar high-nitrate and low-chlorophyll regions. We choose an artificial neural network as our modeling framework because it has the potential to interpret complex nonlinear interactions governing complex adaptive systems, of which marine ecosystems are a prime example. Using ecological indicators that fulfill the criteria of measurability, sensitivity and specificity, we demonstrate that our diagnostic model correctly interprets some basic ecological rules similar to ones emerging from dynamic models. Our time series highlight a dynamic phyto-PFT community composition in all high latitude areas, and indicate seasonal co-existence of diatoms and coccolithophores. This observation, though consistent with in situ and remote sensing measurements, was so far not captured by state-of-the-art dynamic models which struggle to resolve this "paradox of the plankton". We conclude that an ecological indicator approach is useful for ecological modeling of phytoplankton and potentially higher trophic levels. Finally, we speculate that it could serve as a powerful tool in advancing ecosystem-based management of marine resources.

Equation-free mechanistic ecosystem forecasting using empirical dynamic modeling

PubMed Central

Ye, Hao; Beamish, Richard J.; Glaser, Sarah M.; Grant, Sue C. H.; Hsieh, Chih-hao; Richards, Laura J.; Schnute, Jon T.; Sugihara, George

2015-01-01

It is well known that current equilibrium-based models fall short as predictive descriptions of natural ecosystems, and particularly of fisheries systems that exhibit nonlinear dynamics. For example, model parameters assumed to be fixed constants may actually vary in time, models may fit well to existing data but lack out-of-sample predictive skill, and key driving variables may be misidentified due to transient (mirage) correlations that are common in nonlinear systems. With these frailties, it is somewhat surprising that static equilibrium models continue to be widely used. Here, we examine empirical dynamic modeling (EDM) as an alternative to imposed model equations and that accommodates both nonequilibrium dynamics and nonlinearity. Using time series from nine stocks of sockeye salmon (Oncorhynchus nerka) from the Fraser River system in British Columbia, Canada, we perform, for the the first time to our knowledge, real-data comparison of contemporary fisheries models with equivalent EDM formulations that explicitly use spawning stock and environmental variables to forecast recruitment. We find that EDM models produce more accurate and precise forecasts, and unlike extensions of the classic Ricker spawner–recruit equation, they show significant improvements when environmental factors are included. Our analysis demonstrates the strategic utility of EDM for incorporating environmental influences into fisheries forecasts and, more generally, for providing insight into how environmental factors can operate in forecast models, thus paving the way for equation-free mechanistic forecasting to be applied in management contexts. PMID:25733874

Maximum entropy models of ecosystem functioning

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

Bertram, Jason, E-mail: jason.bertram@anu.edu.au

2014-12-05

Using organism-level traits to deduce community-level relationships is a fundamental problem in theoretical ecology. This problem parallels the physical one of using particle properties to deduce macroscopic thermodynamic laws, which was successfully achieved with the development of statistical physics. Drawing on this parallel, theoretical ecologists from Lotka onwards have attempted to construct statistical mechanistic theories of ecosystem functioning. Jaynes’ broader interpretation of statistical mechanics, which hinges on the entropy maximisation algorithm (MaxEnt), is of central importance here because the classical foundations of statistical physics do not have clear ecological analogues (e.g. phase space, dynamical invariants). However, models based on themore » information theoretic interpretation of MaxEnt are difficult to interpret ecologically. Here I give a broad discussion of statistical mechanical models of ecosystem functioning and the application of MaxEnt in these models. Emphasising the sample frequency interpretation of MaxEnt, I show that MaxEnt can be used to construct models of ecosystem functioning which are statistical mechanical in the traditional sense using a savanna plant ecology model as an example.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

DOE PAGES

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.; ...

2015-08-07

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Cross-scale impact of climate temporal variability on ecosystem water and carbon fluxes

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

Paschalis, Athanasios; Fatichi, Simone; Katul, Gabriel G.

While the importance of ecosystem functioning is undisputed in the context of climate change and Earth system modeling, the role of short-scale temporal variability of hydrometeorological forcing (~1 h) on the related ecosystem processes remains to be fully understood. Additionally, various impacts of meteorological forcing variability on water and carbon fluxes across a range of scales are explored here using numerical simulations. Synthetic meteorological drivers that highlight dynamic features of the short temporal scale in series of precipitation, temperature, and radiation are constructed. These drivers force a mechanistic ecohydrological model that propagates information content into the dynamics of water andmore » carbon fluxes for an ensemble of representative ecosystems. The focus of the analysis is on a cross-scale effect of the short-scale forcing variability on the modeled evapotranspiration and ecosystem carbon assimilation. Interannual variability of water and carbon fluxes is emphasized in the analysis. The main study inferences are summarized as follows: (a) short-scale variability of meteorological input does affect water and carbon fluxes across a wide range of time scales, spanning from the hourly to the annual and longer scales; (b) different ecosystems respond to the various characteristics of the short-scale variability of the climate forcing in various ways, depending on dominant factors limiting system productivity; (c) whenever short-scale variability of meteorological forcing influences primarily fast processes such as photosynthesis, its impact on the slow-scale variability of water and carbon fluxes is small; and (d) whenever short-scale variability of the meteorological forcing impacts slow processes such as movement and storage of water in the soil, the effects of the variability can propagate to annual and longer time scales.« less

Consequences of biodiversity loss diverge from expectation due to post-extinction compensatory responses

NASA Astrophysics Data System (ADS)

Thomsen, Matthias S.; Garcia, Clement; Bolam, Stefan G.; Parker, Ruth; Godbold, Jasmin A.; Solan, Martin

2017-03-01

Consensus has been reached that global biodiversity loss impairs ecosystem functioning and the sustainability of services beneficial to humanity. However, the ecosystem consequences of extinction in natural communities are moderated by compensatory species dynamics, yet these processes are rarely accounted for in impact assessments and seldom considered in conservation programmes. Here, we use marine invertebrate communities to parameterise numerical models of sediment bioturbation - a key mediator of biogeochemical cycling - to determine whether post-extinction compensatory mechanisms alter biodiversity-ecosystem function relations following non-random extinctions. We find that compensatory dynamics lead to trajectories of sediment mixing that diverge from those without compensation, and that the form, magnitude and variance of each probabilistic distribution is highly influenced by the type of compensation and the functional composition of surviving species. Our findings indicate that the generalized biodiversity-function relation curve, as derived from multiple empirical investigations of random species loss, is unlikely to yield representative predictions for ecosystem properties in natural systems because the influence of post-extinction community dynamics are under-represented. Recognition of this problem is fundamental to management and conservation efforts, and will be necessary to ensure future plans and adaptation strategies minimize the adverse impacts of the biodiversity crisis.

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.

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

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

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

Importance of vegetation distribution for future carbon balance

NASA Astrophysics Data System (ADS)

Ahlström, A.; Xia, J.; Arneth, A.; Luo, Y.; Smith, B.

2015-12-01

Projections of future terrestrial carbon uptake vary greatly between simulations. Net primary production (NPP), wild fires, vegetation dynamics (including biome shifts) and soil decomposition constitute the main processes governing the response of the terrestrial carbon cycle in a changing climate. While primary production and soil respiration are relatively well studied and implemented in all global ecosystem models used to project the future land sink of CO2, vegetation dynamics are less studied and not always represented in global models. Here we used a detailed second generation dynamic global vegetation model with advanced representation of vegetation growth and mortality and the associated turnover and proven skill in predicting vegetation distribution and succession. 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 CMIP5 ensemble under RCP8.5 radiative forcing at year 2085. We exchanged carbon cycle processes between these 13 simulations and investigate the changes predicted by the emulator. This method allowed us to partition the entire ensemble carbon uptake uncertainty into individual processes. We found that NPP, vegetation dynamics (including biome shifts, wild fires and mortality) and soil decomposition rates explained 49%, 17% and 33% respectively of uncertainties in modeled global C-uptake. Uncertainty due to vegetation dynamics 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 shifts in vegetation distribution, represent a significant fraction globally and regionally (tropical forests: 40%), strongly motivating their representation and analysis in future C-cycle studies.

AN INDEX TO DETECT EXTERNALLY-FORCED DYNAMIC REGIME SHIFTS IN ECOSYSTEMS

EPA Science Inventory

The concept of dynamic regimes, and nonlinear shifts between regimes, has gained acceptance and importance in ecosystem research. Regimes in ecosystems are identified as states with characteristic species abundances and abiotic conditions. Ecosystems are maintained in particular ...

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

Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe

NASA Astrophysics Data System (ADS)

Churkina, G.; Zaehle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Heumann, B. W.; Ramankutty, N.; Heimann, M.; Jones, C.

2010-09-01

European ecosystems are thought to take up large amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more that 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C yr-1. The extents of forest and grasslands have increased with the respective rates of 5800 km2 yr-1 and 1100 km2 yr-1 as agricultural land has been abandoned at a rate of 7000 km2 yr-1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. The models suggest that European ecosystems sequester carbon at a rate of 56 TgC yr-1 (mean of four models for 1951-2000) with strong interannual variability (±88 TgC yr-1, average across models) and substantial inter-model uncertainty (±39 TgC yr-1). Decadal budgets suggest that there has been a continuous increase in the mean net carbon storage of ecosystems from 85 TgC yr-1 in 1980s to 108 TgC yr-1 in 1990s, and to 114 TgC yr-1 in 2000-2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are suggested as an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.

The ecohydrology of water limited landscapes

NASA Astrophysics Data System (ADS)

Huxman, T. E.

2011-12-01

Developing a mechanistic understanding of the coupling of ecological and hydrological systems is crucial for understanding the land-surface response of large areas of the globe to changes in climate. The distribution of biodiversity, the quantity and quality of streamflow, the biogeochemistry that constrains vegetation cover and production, and the stability of soil systems in watersheds are all functions of water-life coupling. Many key ecosystem services are governed by the dynamics of near-surface hydrology and biological feedbacks on the landscape occur through plant influence over available soil moisture. Thus, ecohydrology has tremendous potential to contribute to a predictive framework for understanding earth system dynamics. Despite the importance of such couplings and water as a major limiting resource in ecosystems throughout the globe, ecology still struggles with a mechanistic understanding of how changes in rainfall affect the biology of plants and microbes, or how changes in plant communities affect hydrological dynamics in watersheds. Part of the problem comes from our lack of understanding of how plants effectively partition available water among individuals in communities and how that modifies the physical environment, affecting additional resource availability and the passage of water along other hydrological pathways. The partitioning of evapotranspiration between transpiration by plants and evaporation from the soil surface is key to interrelated ecological, hydrological, and atmospheric processes and likely varies with vegetation structure and atmospheric dynamics. In addition, the vertical stratification of autotrophic and heterotrophic components in the soil profile, and the speed at which each respond to increased water, exert strong control over the carbon cycle. The magnitude of biosphere-atmosphere carbon exchange depends on the time-depth-distribution of soil moisture, a fundamental consequence of local precipitation pulse characteristics, soil texture and plant functional type. The transport of metabolic products within plants and their differential activation result in non-intuitive patterns of exchange associated with the major drivers creating problems with the scaling of physiological processes of individual plants to ecosystems. Such dynamics, along with hysteretic behavior creates challenges for measurement, evaluation, modeling and predicting ecosystem behavior. New frameworks and conceptual approaches to modeling ecosystem metabolism and the role of water are helping to describe the consequences of precipitation variability and change.

Modeled change in carbon balance between 1970-2100 of a polygonal arctic tundra ecosystem near Barrow, Alaska

NASA Astrophysics Data System (ADS)

Lara, M. J.; McGuire, A. D.; Euskirchen, E. S.; Sloan, V. L.; Iversen, C. M.; Norby, R. J.; Genet, H.; Zhang, Y.; Yuan, F.

2013-12-01

Northern permafrost regions are estimated to cover 16% of the global soil area and account for approximately 50% of the global belowground organic carbon pool. However, there are considerable uncertainties regarding the fate of this soil carbon pool with projected climate warming over the next century. In northern Alaska, nearly 65% of the terrestrial surface is composed of polygonal tundra, where microtopographic position (i.e. high center, low center, trough) varies surface hydrology, plant community composition, and biogeochemical cycling, over small (<5m) spatial scales. Due to large spatial heterogeneity and other non-linear responses of soil carbon to altered thermal regime, it is difficult to accurately estimate the fate of terrestrial carbon balance over decadal time-scales without explicitly considering the dynamically coupled processes driving permafrost dynamics, community structure, and ecosystem function. We use a new version of the terrestrial ecosystem model (TEM), which couples a dynamic vegetation and dynamic organic soil model (DVM-DOS-TEM). This large-scale ecosystem model is designed to study interactions among carbon and nitrogen cycling, vegetation composition, and soil physical properties, including permafrost and active layer dynamics. The model is parameterized and calibrated using data specific to the local climate, vegetation, and soils within various polygon land cover types (i.e. high center & rim, low center, trough) collected from sites (71.28°N 156.60° W) on the arctic coastal plain near Barrow, Alaska to estimate the likely change in carbon balance between 1970 and 2100 in this landscape. Model outputs are scaled across the Barrow Peninsula using the distribution of polygonal tundra land cover types, described by a land cover classification of 26.9 km2, using a 2008 multi-spectral QuickBird satellite image. The polygonal tundra land cover classification found high center & rims to represent 37.5% of the study area, low centers 19.7%, troughs 9.9%, water bodies (i.e. lakes, ponds, rivers) 17.8%, and non-polygonal tundra (i.e. drainage terraces & graminoid meadows) 15.1%, respectively. The overall accuracy of the map was 86%, based on 250 ground control points, and the Kappa coefficient was 0.77. Preliminary model runs for this region indicated variability in response to specific polygonal tundra land cover type through time. Overall, results suggest that it is important to consider discrete polygonal tundra features in regional estimates of carbon balance in northern Alaska.

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

Treesearch

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

2007-01-01

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

Recovery after mass extinction: evolutionary assembly in large-scale biosphere dynamics.

PubMed Central

Solé, Ricard V; Montoya, José M; Erwin, Douglas H

2002-01-01

Biotic recoveries following mass extinctions are characterized by a process in which whole ecologies are reconstructed from low-diversity systems, often characterized by opportunistic groups. The recovery process provides an unexpected window to ecosystem dynamics. In many aspects, recovery is very similar to ecological succession, but important differences are also apparently linked to the innovative patterns of niche construction observed in the fossil record. In this paper, we analyse the similarities and differences between ecological succession and evolutionary recovery to provide a preliminary ecological theory of recoveries. A simple evolutionary model with three trophic levels is presented, and its properties (closely resembling those observed in the fossil record) are compared with characteristic patterns of ecological response to disturbances in continuous models of three-level ecosystems. PMID:12079530

Impacts of insect disturbance on the structure, composition, and functioning of oak-pine forests

NASA Astrophysics Data System (ADS)

Medvigy, D.; Schafer, K. V.; Clark, K. L.

2011-12-01

Episodic disturbance is an essential feature of terrestrial ecosystems, and strongly modulates their structure, composition, and functioning. However, dynamic global vegetation models that are commonly used to make ecosystem and terrestrial carbon budget predictions rarely have an explicit representation of disturbance. One reason why disturbance is seldom included is that disturbance tends to operate on spatial scales that are much smaller than typical model resolutions. In response to this problem, the Ecosystem Demography model 2 (ED2) was developed as a way of tracking the fine-scale heterogeneity arising from disturbances. In this study, we used ED2 to simulate an oak-pine forest that experiences episodic defoliation by gypsy moth (Lymantria dispar L). The model was carefully calibrated against site-level data, and then used to simulate changes in ecosystem composition, structure, and functioning on century time scales. Compared to simulations that include gypsy moth defoliation, we show that simulations that ignore defoliation events lead to much larger ecosystem carbon stores and a larger fraction of deciduous trees relative to evergreen trees. Furthermore, we find that it is essential to preserve the fine-scale nature of the disturbance. Attempts to "smooth out" the defoliation event over an entire grid cells led to large biases in ecosystem structure and functioning.

Modeling climate change, urbanization, and fire effects on Pinus palustris ecosystems of the southeastern U.S.

USGS Publications Warehouse

Costanza, Jennifer; Terando, Adam J.; McKerrow, Alexa; Collazo, Jaime A.

2015-01-01

Managing ecosystems for resilience and sustainability requires understanding how they will respond to future anthropogenic drivers such as climate change and urbanization. In fire-dependent ecosystems, predicting this response requires a focus on how these drivers will impact fire regimes. Here, we use scenarios of climate change, urbanization and management to simulate the future dynamics of the critically endangered and fire-dependent longleaf pine (Pinus palustris) ecosystem. We investigated how climate change and urbanization will affect the ecosystem, and whether the two conservation goals of a 135% increase in total longleaf area and a doubling of fire-maintained open-canopy habitat can be achieved in the face of these drivers. Our results show that while climatic warming had little effect on the wildfire regime, and thus on longleaf pine dynamics, urban growth led to an 8% reduction in annual wildfire area. The management scenarios we tested increase the ecosystem's total extent by up to 62% and result in expansion of open-canopy longleaf by as much as 216%, meeting one of the two conservation goals for the ecosystem. We find that both conservation goals for this ecosystem, which is climate-resilient but vulnerable to urbanization, are only attainable if a greater focus is placed on restoration of non-longleaf areas as opposed to maintaining existing longleaf stands. Our approach demonstrates the importance of accounting for multiple relevant anthropogenic threats in an ecosystem-specific context in order to facilitate more effective management actions.

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.

A multi-omics and imaging approach to understand soil organic matter composition and its interaction with microbes.

NASA Astrophysics Data System (ADS)

Tfaily, M. M.; Walker, L. R.; Kyle, J. E.; Chu, R. K.; Dohnalkova, A.; Tolic, N.; Orton, D.; Robinson, E. R.; Paša-Tolić, L.; Hess, N. J.

2015-12-01

The focus on soil C dynamics is currently relevant as researchers and policymakers strive to understand the feedbacks between ecosystem stress and climate change. Successful development of molecular profiles that link soil microbiology with soil carbon (C) dynamics to ascertain soil vulnerability and resilience to climate change would have great impact on assessments of soil ecosystems in response to climate change. Additionally, a better understanding of the soil C dynamics would improve climate modeling, and fate and transport of carbon across terrestrial, subsurface and atmospheric interfaces. Unravelling the wide range of possible interactions between and within the microbial communities, with minerals and organic compounds in the terrestrial ecosystem requires a multimodal, molecular approach. Here we report on the use of a combination of several molecular 'omics' approaches: metabolomics, metallomics, lipidomics, and proteomics coupled with a suite of high resolution imaging, and X-ray diffraction crystallographic techniques, as a novel methodology to understand SOM composition, and its interaction with microbial communities in different ecosystems, including C associated with mineral surfaces. The findings of these studies provide insights into the SOM persistence and microbial stabilization of carbon in ecosystems and reveal the powerful coupling of a multi-scale of techniques. Examples of this approach will be presented from field studies of simulated climate change, and laboratory column-grown Pinus resinosa mesocosms.

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

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.

Resilience, Integrity and Ecosystem Dynamics: Bridging Ecosystem Theory and Management

NASA Astrophysics Data System (ADS)

Müller, Felix; Burkhard, Benjamin; Kroll, Franziska

In this paper different approaches to elucidate ecosystem dynamics are described, illustrated and interrelated. Ecosystem development is distinguished into two separate sequences, a complexifying phase which is characterized by orientor optimization and a destruction based phase which follows disturbances. The two developmental pathways are integrated in a modified illustration of the “adaptive cycle”. Based on these fundamentals, the recent definitions of resilience, adaptability and vulnerability are discussed and a modified comprehension is proposed. Thereafter, two case studies about wetland dynamics are presented to demonstrate both, the consequences of disturbance and the potential of ecosystem recovery. In both examples ecosystem integrity is used as a key indicator variable. Based on the presented results the relativity and the normative loading of resilience quantification is worked out. The paper ends with the suggestion that the features of adaptability could be used as an integrative guideline for the analysis of ecosystem dynamics and as a well-suited concept for ecosystem management.

Nitrogen and phosphorus limitation over long-term ecosystem development in terrestrial ecosystems.

PubMed

Menge, Duncan N L; Hedin, Lars O; Pacala, Stephen W

2012-01-01

Nutrient limitation to net primary production (NPP) displays a diversity of patterns as ecosystems develop over a range of timescales. For example, some ecosystems transition from N limitation on young soils to P limitation on geologically old soils, whereas others appear to remain N limited. Under what conditions should N limitation and P limitation prevail? When do transitions between N and P limitation occur? We analyzed transient dynamics of multiple timescales in an ecosystem model to investigate these questions. Post-disturbance dynamics in our model are controlled by a cascade of rates, from plant uptake (very fast) to litter turnover (fast) to plant mortality (intermediate) to plant-unavailable nutrient loss (slow) to weathering (very slow). Young ecosystems are N limited when symbiotic N fixation (SNF) is constrained and P weathering inputs are high relative to atmospheric N deposition and plant N:P demand, but P limited under opposite conditions. In the absence of SNF, N limitation is likely to worsen through succession (decades to centuries) because P is mineralized faster than N. Over long timescales (centuries and longer) this preferential P mineralization increases the N:P ratio of soil organic matter, leading to greater losses of plant-unavailable N versus P relative to plant N:P demand. These loss dynamics favor N limitation on older soils despite the rising organic matter N:P ratio. However, weathering depletion favors P limitation on older soils when continual P inputs (e.g., dust deposition) are low, so nutrient limitation at the terminal equilibrium depends on the balance of these input and loss effects. If NPP switches from N to P limitation over long time periods, the transition time depends most strongly on the P weathering rate. At all timescales SNF has the capacity to overcome N limitation, so nutrient limitation depends critically on limits to SNF.

Do we have to choose between feeding the human population and conserving nature? Modelling the global dependence of people on ecosystem services.

PubMed

Cazalis, Victor; Loreau, Michel; Henderson, Kirsten

2018-09-01

The ability of the human population to continue growing depends strongly on the ecosystem services provided by nature. Nature, however, is becoming more and more degraded as the number of individuals increases, which could potentially threaten the future well-being of the human population. We use a dynamic model to conceptualise links between the global proportion of natural habitats and human demography, through four categories of ecosystem services (provisioning, regulating, cultural recreational and informational) to investigate the common future of nature and humanity in terms of size and well-being. Our model shows that there is generally a trade-off between the quality of life and human population size and identifies four short-term scenarios, corresponding to three long-term steady states of the model. First, human population could experience declines if nature becomes too degraded and regulating services diminish; second the majority of the population could be in a famine state, where the population continues to grow with minimal food provision. Between these scenarios, a desirable future scenario emerges from the model. It occurs if humans convert enough land to feed all the population, while maintaining biodiversity and ecosystem services. Finally, we find a fourth scenario, which combines famine and a decline in the population because of an overexploitation of land leading to a decrease in food production. Human demography is embedded in natural dynamics; the two factors should be considered together if we are to identify a desirable future for both nature and humans. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

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...

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...

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.

2015-06-01

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. 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. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. 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 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature 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.

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

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.

Modeling temperature and humidity profiles within forest canopies

USDA-ARS?s Scientific Manuscript database

Physically-based models are a powerful tool to help understand interactions of vegetation, atmospheric dynamics, and hydrology, and to test hypotheses regarding the effects of land cover, management, hydrometeorology, and climate variability on ecosystem processes. The purpose of this paper is to f...

Scaling up of Carbon Exchange Dynamics from AmeriFlux Sites to a Super-Region in the Eastern United States

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

Hans Peter Schmid; Craig Wayson

The primary objective of this project was to evaluate carbon exchange dynamics across a region of North America between the Great Plains and the East Coast. This region contains about 40 active carbon cycle research (AmeriFlux) sites in a variety of climatic and landuse settings, from upland forest to urban development. The core research involved a scaling strategy that uses measured fluxes of CO{sub 2}, energy, water, and other biophysical and biometric parameters to train and calibrate surface-vegetation-atmosphere models, in conjunction with satellite (MODIS) derived drivers. To achieve matching of measured and modeled fluxes, the ecosystem parameters of the modelsmore » will be adjusted to the dynamically variable flux-tower footprints following Schmid (1997). High-resolution vegetation index variations around the flux sites have been derived from Landsat data for this purpose. The calibrated models are being used in conjunction with MODIS data, atmospheric re-analysis data, and digital land-cover databases to derive ecosystem exchange fluxes over the study domain.« less

Global dynamics in a stoichiometric food chain model with two limiting nutrients.

PubMed

Chen, Ming; Fan, Meng; Kuang, Yang

2017-07-01

Ecological stoichiometry studies the balance of energy and multiple chemical elements in ecological interactions to establish how the nutrient content affect food-web dynamics and nutrient cycling in ecosystems. In this study, we formulate a food chain with two limiting nutrients in the form of a stoichiometric population model. A comprehensive global analysis of the rich dynamics of the targeted model is explored both analytically and numerically. Chaotic dynamic is observed in this simple stoichiometric food chain model and is compared with traditional model without stoichiometry. The detailed comparison reveals that stoichiometry can reduce the parameter space for chaotic dynamics. Our findings also show that decreasing producer production efficiency may have only a small effect on the consumer growth but a more profound impact on the top predator growth. Copyright © 2017 Elsevier Inc. All rights reserved.

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.

A Hierarchical and Dynamic Seascape Framework for Scaling and Comparing Ocean Biodiversity Observations

NASA Astrophysics Data System (ADS)

Kavanaugh, M.; Muller-Karger, F. E.; Montes, E.; Santora, J. A.; Chavez, F.; Messié, M.; Doney, S. C.

2016-02-01

The pelagic ocean is a complex system in which physical, chemical and biological processes interact to shape patterns on multiple spatial and temporal scales and levels of ecological organization. Monitoring and management of marine seascapes must consider a hierarchical and dynamic mosaic, where the boundaries, extent, and location of features change with time. As part of a Marine Biodiversity Observing Network demonstration project, we conducted a multiscale classification of dynamic coastal seascapes in the northeastern Pacific and Gulf of Mexico using multivariate satellite and modeled data. Synoptic patterns were validated using mooring and ship-based observations that spanned multiple trophic levels and were collected as part of several long-term monitoring programs, including the Monterey Bay and Florida Keys National Marine Sanctuaries. Seascape extent and habitat diversity varied as a function of both seasonal and interannual forcing. We discuss the patterns of in situ observations in the context of seascape dynamics and the effect on rarefaction, spatial patchiness, and tracking and comparing ecosystems through time. A seascape framework presents an effective means to translate local biodiversity measurements to broader spatiotemporal scales, scales relevant for modeling the effects of global change and enabling whole-ecosystem management in the dynamic ocean.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

The role of satellite remote sensing in structured ecosystem risk assessments.

PubMed

Murray, Nicholas J; Keith, David A; Bland, Lucie M; Ferrari, Renata; Lyons, Mitchell B; Lucas, Richard; Pettorelli, Nathalie; Nicholson, Emily

2018-04-01

The current set of global conservation targets requires methods for monitoring the changing status of ecosystems. Protocols for ecosystem risk assessment are uniquely suited to this task, providing objective syntheses of a wide range of data to estimate the likelihood of ecosystem collapse. Satellite remote sensing can deliver ecologically relevant, long-term datasets suitable for analysing changes in ecosystem area, structure and function at temporal and spatial scales relevant to risk assessment protocols. However, there is considerable uncertainty about how to select and effectively utilise remotely sensed variables for risk assessment. Here, we review the use of satellite remote sensing for assessing spatial and functional changes of ecosystems, with the aim of providing guidance on the use of these data in ecosystem risk assessment. We suggest that decisions on the use of satellite remote sensing should be made a priori and deductively with the assistance of conceptual ecosystem models that identify the primary indicators representing the dynamics of a focal ecosystem. Copyright © 2017 Elsevier B.V. All rights reserved.

Attributing Asymmetric Productivity Responses to Internal Ecosystem Dynamics and External Drivers Using Probabilistic Models

NASA Astrophysics Data System (ADS)

Parolari, A.; Goulden, M.

2017-12-01

A major challenge to interpreting asymmetric changes in ecosystem productivity is the attribution of these changes to external climate forcing or to internal ecophysiological processes that respond to these drivers (e.g., photosynthesis response to drying soil). For example, positive asymmetry in productivity can result from either positive skewness in the distribution of annual rainfall amount or from negative curvature in the productivity response to annual rainfall. To analyze the relative influences of climate and ecosystem dynamics on both positive and negative asymmetry in multi-year ANPP experiments, we use a multi-scale coupled ecosystem water-carbon model to interpret field experimental results that span gradients of rainfall skewness and ANPP response curvature. The model integrates rainfall variability, soil moisture dynamics, and net carbon assimilation from the daily to inter-annual scales. From the underlying physical basis of the model, we compute the joint probability distribution of the minimum and maximum ANPP for an annual ANPP experiment of N years. The distribution is used to estimate the likelihood that either positive or negative asymmetry will be observed in an experiment, given the annual rainfall distribution and the ANPP response curve. We estimate the total asymmetry as the mode of this joint distribution and the relative contribution attributable to rainfall skewness as the mode for a linear ANPP response curve. Applied to data from several long-term ANPP experiments, we find that there is a wide range of observed ANPP asymmetry (positive and negative) and a spectrum of contributions from internal and external factors. We identify the soil water holding capacity relative to the mean rain event depth as a critical ecosystem characteristic that controls the non-linearity of the ANPP response and positive curvature at high rainfall. Further, the seasonal distribution of rainfall is shown to control the presence or absence of negative curvature at low rainfall. Therefore, a combination of rooting depth, soil texture, and climate seasonality contribute to ANPP response curvature and its contribution to overall observed asymmetry.

Using stable isotopes to resolve eco-hydrological dynamics of soil-plant-atmosphere feedbacks

NASA Astrophysics Data System (ADS)

Dubbert, M.; Piayda, A.; Kübert, A.; Cuntz, M.; Werner, C.

2016-12-01

Water is the main driver of ecosystem productivity in most terrestrial ecosystems worldwide. Extreme events are predicted to increase in frequency in many regions and dynamic responses in soil-vegetation-atmosphere feedbacks play a privotal role in understanding the ecosystem water balance and functioning. In this regard, more interdisciplinary approaches, bridging hydrology, ecophysiology and atmospheric sciences are needed and particularly water stable isotopes are a powerful tracer of water transfer in soils and at the soil-plant interface (Werner and Dubbert 2016). Here, we present observations 2 different ecosystems. Water fluxes, atmospheric concentrations and their isotopic compositions were measured using laser spectroscopy. Soil moisture and its isotopic composition in several depths as well as further water sources in the ecosystem were monitored throughout the year. Using these isotopic approaches we disentangled soil-plant-atmosphere feedback processes controlling the ecosystem water cycle including vegetation effects on soil water infiltration and distribution, event water use of vegetation and soil fluxes, vegetational soil water uptake depths plasticity and partitioning of ecosystem water fluxes. In this regard, we review current strategies of ET partitioning and highlight pitfalls in the presented strategies (Dubbert et al. 2013, Dubbert et al.2014a). We demonstrate that vegetation strongly influenced water cycling, altering infiltration and distribution of precipitation. In conclusion, application of stable water isotope tracers delivers a process based understanding of interactions between soil, understorey and trees governing ecosystem water cycling necessary for prediction of climate change impact on ecosystem productivity and vulnerability. ReferencesDubbert, M. et al. (2013): Partitioning evapotranspiration - Testing the Craig and Gordon model with field measurements of oxygen isotope ratios of evaporative fluxes. Journal of Hydrology Dubbert, M. et al. (2014a): Oxygen isotope signatures of transpired water vapor: the role of isotopic non-steady-state transpiration under natural conditions. New Phytologist. Werner, C. and Dubbert, M. (2016): Resolving rapid dynamics of soil-plant-atmosphere interactions. New Phytologist.

Stochastic hybrid delay population dynamics: well-posed models and extinction.

PubMed

Yuan, Chenggui; Mao, Xuerong; Lygeros, John

2009-01-01

Nonlinear differential equations have been used for decades for studying fluctuations in the populations of species, interactions of species with the environment, and competition and symbiosis between species. Over the years, the original non-linear models have been embellished with delay terms, stochastic terms and more recently discrete dynamics. In this paper, we investigate stochastic hybrid delay population dynamics (SHDPD), a very general class of population dynamics that comprises all of these phenomena. For this class of systems, we provide sufficient conditions to ensure that SHDPD have global positive, ultimately bounded solutions, a minimum requirement for a realistic, well-posed model. We then study the question of extinction and establish conditions under which an ecosystem modelled by SHDPD is doomed.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Diagnosis of Processes Controlling Dissolved Organic Carbon (DOC) Export in a Subarctic Region by a Dynamic Ecosystem Model

NASA Astrophysics Data System (ADS)

Tang, J.

2015-12-01

Permafrost thawing in high latitudes allows more soil organic carbon (SOC) to become hydrologically accessible. This can increase dissolved organic carbon (DOC) exports and carbon release to the atmosphere as CO2 and CH4, with a positive feedback to regional and global climate warming. However, this portion of carbon loss through DOC export is often neglected in ecosystem models. In this paper, we incorporate a set of DOC-related processes (DOC production, mineralization, diffusion, sorption-desorption and leaching) into an Arctic-enabled version of the dynamic ecosystem model LPJ-GUESS (LPJ-GUESS WHyMe) to mechanistically model the DOC export, and to link this flux to other ecosystem processes. The extended LPJ-GUESS WHyMe with these DOC processes is applied to the Stordalen catchment in northern Sweden. The relative importance of different DOC-related processes for mineral and peatland soils for this region have been explored at both monthly and annual scales based on a detailed variance-based Sobol sensitivity analysis. For mineral soils, the annual DOC export is dominated by DOC fluxes in snowmelt seasons and the peak in spring is related to the runoff passing through top organic rich layers. Two processes, DOC sorption-desorption and production, are found to contribute most to the annual variance in DOC export. For peatland soils, the DOC export during snowmelt seasons is constrained by frozen soils and the processes of DOC production and mineralization, determining the magnitudes of DOC desorption in snowmelt seasons as well as DOC sorption in the rest of months, play the most important role in annual variances of DOC export. Generally, the seasonality of DOC fluxes is closely correlated with runoff seasonality in this region. The current implementation has demonstrated that DOC-related processes in the framework of LPJ-GUESS WHyMe are at an appropriate level of complexity to represent the main mechanism of DOC dynamics in soils. The quantified contributions from different processes on DOC export dynamics could be further linked to the climate change, vegetation composition change and permafrost thawing in this region.

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes

PubMed Central

Weitz, Joshua S; Stock, Charles A; Wilhelm, Steven W; Bourouiba, Lydia; Coleman, Maureen L; Buchan, Alison; Follows, Michael J; Fuhrman, Jed A; Jover, Luis F; Lennon, Jay T; Middelboe, Mathias; Sonderegger, Derek L; Suttle, Curtis A; Taylor, Bradford P; Frede Thingstad, T; Wilson, William H; Eric Wommack, K

2015-01-01

Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles. PMID:25635642

A multitrophic model to quantify the effects of marine viruses on microbial food webs and ecosystem processes.

PubMed

Weitz, Joshua S; Stock, Charles A; Wilhelm, Steven W; Bourouiba, Lydia; Coleman, Maureen L; Buchan, Alison; Follows, Michael J; Fuhrman, Jed A; Jover, Luis F; Lennon, Jay T; Middelboe, Mathias; Sonderegger, Derek L; Suttle, Curtis A; Taylor, Bradford P; Frede Thingstad, T; Wilson, William H; Eric Wommack, K

2015-06-01

Viral lysis of microbial hosts releases organic matter that can then be assimilated by nontargeted microorganisms. Quantitative estimates of virus-mediated recycling of carbon in marine waters, first established in the late 1990s, were originally extrapolated from marine host and virus densities, host carbon content and inferred viral lysis rates. Yet, these estimates did not explicitly incorporate the cascade of complex feedbacks associated with virus-mediated lysis. To evaluate the role of viruses in shaping community structure and ecosystem functioning, we extend dynamic multitrophic ecosystem models to include a virus component, specifically parameterized for processes taking place in the ocean euphotic zone. Crucially, we are able to solve this model analytically, facilitating evaluation of model behavior under many alternative parameterizations. Analyses reveal that the addition of a virus component promotes the emergence of complex communities. In addition, biomass partitioning of the emergent multitrophic community is consistent with well-established empirical norms in the surface oceans. At steady state, ecosystem fluxes can be probed to characterize the effects that viruses have when compared with putative marine surface ecosystems without viruses. The model suggests that ecosystems with viruses will have (1) increased organic matter recycling, (2) reduced transfer to higher trophic levels and (3) increased net primary productivity. These model findings support hypotheses that viruses can have significant stimulatory effects across whole-ecosystem scales. We suggest that existing efforts to predict carbon and nutrient cycling without considering virus effects are likely to miss essential features of marine food webs that regulate global biogeochemical cycles.

Modelling algae-duckweed interaction under chemical pressure within a laboratory microcosm.

PubMed

Lamonica, Dominique; Clément, Bernard; Charles, Sandrine; Lopes, Christelle

2016-06-01

Contaminant effects on species are generally assessed with single-species bioassays. As a consequence, interactions between species that occur in ecosystems are not taken into account. To investigate the effects of contaminants on interacting species dynamics, our study describes the functioning of a 2-L laboratory microcosm with two species, the duckweed Lemna minor and the microalgae Pseudokirchneriella subcapitata, exposed to cadmium contamination. We modelled the dynamics of both species and their interactions using a mechanistic model based on coupled ordinary differential equations. The main processes occurring in this two-species microcosm were thus formalised, including growth and settling of algae, growth of duckweeds, interspecific competition between the two species and cadmium effects. We estimated model parameters by Bayesian inference, using simultaneously all the data issued from multiple laboratory experiments specifically conducted for this study. Cadmium concentrations ranged between 0 and 50 μg·L(-1). For all parameters of our model, we obtained biologically realistic values and reasonable uncertainties. Only duckweed dynamics was affected by interspecific competition, while algal dynamics was not impaired. Growth rate of both species decreased with cadmium concentration, as well as competition intensity showing that the interspecific competition pressure on duckweed decreased with cadmium concentration. This innovative combination of mechanistic modelling and model-guided experiments was successful to understand the algae-duckweed microcosm functioning without and with contaminant. This approach appears promising to include interactions between species when studying contaminant effects on ecosystem functioning. Copyright © 2016 Elsevier Inc. All rights reserved.

Trophic signatures of seabirds suggest shifts in oceanic ecosystems

PubMed Central

Gagne, Tyler O.; Hyrenbach, K. David; Hagemann, Molly E.; Van Houtan, Kyle S.

2018-01-01

Pelagic ecosystems are dynamic ocean regions whose immense natural capital is affected by climate change, pollution, and commercial fisheries. Trophic level–based indicators derived from fishery catch data may reveal the food web status of these systems, but the utility of these metrics has been debated because of targeting bias in fisheries catch. We analyze a unique, fishery-independent data set of North Pacific seabird tissues to inform ecosystem trends over 13 decades (1890s to 2010s). Trophic position declined broadly in five of eight species sampled, indicating a long-term shift from higher–trophic level to lower–trophic level prey. No species increased their trophic position. Given species prey preferences, Bayesian diet reconstructions suggest a shift from fishes to squids, a result consistent with both catch reports and ecosystem models. Machine learning models further reveal that trophic position trends have a complex set of drivers including climate, commercial fisheries, and ecomorphology. Our results show that multiple species of fish-consuming seabirds may track the complex changes occurring in marine ecosystems. PMID:29457134

Trophic signatures of seabirds suggest shifts in oceanic ecosystems.

PubMed

Gagne, Tyler O; Hyrenbach, K David; Hagemann, Molly E; Van Houtan, Kyle S

2018-02-01

Pelagic ecosystems are dynamic ocean regions whose immense natural capital is affected by climate change, pollution, and commercial fisheries. Trophic level-based indicators derived from fishery catch data may reveal the food web status of these systems, but the utility of these metrics has been debated because of targeting bias in fisheries catch. We analyze a unique, fishery-independent data set of North Pacific seabird tissues to inform ecosystem trends over 13 decades (1890s to 2010s). Trophic position declined broadly in five of eight species sampled, indicating a long-term shift from higher-trophic level to lower-trophic level prey. No species increased their trophic position. Given species prey preferences, Bayesian diet reconstructions suggest a shift from fishes to squids, a result consistent with both catch reports and ecosystem models. Machine learning models further reveal that trophic position trends have a complex set of drivers including climate, commercial fisheries, and ecomorphology. Our results show that multiple species of fish-consuming seabirds may track the complex changes occurring in marine ecosystems.

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.

Marine ecosystem modeling beyond the box: using GIS to study carbon fluxes in a coastal ecosystem.

PubMed

Wijnbladh, Erik; Jönsson, Bror Fredrik; Kumblad, Linda

2006-12-01

Studies of carbon fluxes in marine ecosystems are often done by using box model approaches with basin size boxes, or highly resolved 3D models, and an emphasis on the pelagic component of the ecosystem. Those approaches work well in the ocean proper, but can give rise to considerable problems when applied to coastal systems, because of the scale of certain ecological niches and the fact that benthic organisms are the dominant functional group of the ecosystem. In addition, 3D models require an extensive modeling effort. In this project, an intermediate approach based on a high resolution (20x20 m) GIS data-grid has been developed for the coastal ecosystem in the Laxemar area (Baltic Sea, Sweden) based on a number of different site investigations. The model has been developed in the context of a safety assessment project for a proposed nuclear waste repository, in which the fate of hypothetically released radionuclides from the planned repository is estimated. The assessment project requires not only a good understanding of the ecosystem dynamics at the site, but also quantification of stocks and flows of matter in the system. The data-grid was then used to set up a carbon budget describing the spatial distribution of biomass, primary production, net ecosystem production and thus where carbon sinks and sources are located in the area. From these results, it was clear that there was a large variation in ecosystem characteristics within the basins and, on a larger scale, that the inner areas are net producing and the outer areas net respiring, even in shallow phytobenthic communities. Benthic processes had a similar or larger influence on carbon fluxes as advective processes in inner areas, whereas the opposite appears to be true in the outer basins. As many radionuclides are expected to follow the pathways of organic matter in the environment, these findings enhance our abilities to realistically describe and predict their fate in the ecosystem.

Screening variability and change of soil moisture under wide-ranging climate conditions: Snow dynamics effects.

PubMed

Verrot, Lucile; Destouni, Georgia

2015-01-01

Soil moisture influences and is influenced by water, climate, and ecosystem conditions, affecting associated ecosystem services in the landscape. This paper couples snow storage-melting dynamics with an analytical modeling approach to screening basin-scale, long-term soil moisture variability and change in a changing climate. This coupling enables assessment of both spatial differences and temporal changes across a wide range of hydro-climatic conditions. Model application is exemplified for two major Swedish hydrological basins, Norrström and Piteälven. These are located along a steep temperature gradient and have experienced different hydro-climatic changes over the time period of study, 1950-2009. Spatially, average intra-annual variability of soil moisture differs considerably between the basins due to their temperature-related differences in snow dynamics. With regard to temporal change, the long-term average state and intra-annual variability of soil moisture have not changed much, while inter-annual variability has changed considerably in response to hydro-climatic changes experienced so far in each basin.

Metabolic resource allocation in individual microbes determines ecosystem interactions and spatial dynamics

PubMed Central

Harcombe, William R.; Riehl, William J.; Dukovski, Ilija; Granger, Brian R.; Betts, Alex; Lang, Alex H.; Bonilla, Gracia; Kar, Amrita; Leiby, Nicholas; Mehta, Pankaj; Marx, Christopher J.; Segrè, Daniel

2014-01-01

Summary The inter-species exchange of metabolites plays a key role in the spatio-temporal dynamics of microbial communities. This raises the question whether ecosystem-level behavior of structured communities can be predicted using genome-scale models of metabolism for multiple organisms. We developed a modeling framework that integrates dynamic flux balance analysis with diffusion on a lattice, and applied it to engineered consortia. First, we predicted, and experimentally confirmed, the species-ratio to which a 2-species mutualistic consortium converges, and the equilibrium composition of a newly engineered 3-member community. We next identified a specific spatial arrangement of colonies, which gives rise to what we term the “eclipse dilemma”: does a competitor placed between a colony and its cross-feeding partner benefit or hurt growth of the original colony? Our experimentally validated finding, that the net outcome is beneficial, highlights the complex nature of metabolic interactions in microbial communities, while at the same time demonstrating their predictability. PMID:24794435

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

DOE PAGES

Drewniak, Beth; Gonzalez-Meler, Miquel

2017-07-27

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

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

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

Drewniak, Beth; Gonzalez-Meler, Miquel

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

Emergence of a complex and stable network in a model ecosystem with extinction and mutation.

PubMed

Tokita, Kei; Yasutomi, Ayumu

2003-03-01

We propose a minimal model of the dynamics of diversity-replicator equations with extinction, invasion and mutation. We numerically study the behavior of this simple model and show that it displays completely different behavior from the conventional replicator equation and the generalized Lotka-Volterra equation. We reach several significant conclusions as follows: (1) a complex ecosystem can emerge when mutants with respect to species-specific interaction are introduced; (2) such an ecosystem possesses strong resistance to invasion; (3) a typical fixation process of mutants is realized through the rapid growth of a group of mutualistic mutants with higher fitness than majority species; (4) a hierarchical taxonomic structure (like family-genus-species) emerges; and (5) the relative abundance of species exhibits a typical pattern widely observed in nature. Several implications of these results are discussed in connection with the relationship of the present model to the generalized Lotka-Volterra equation.

Final report for DOE Award # DE- SC0010039*: Carbon dynamics of forest recovery under a changing climate: Forcings, feedbacks, and implications for earth system modeling

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

Anderson-Teixeira, Kristina J.; DeLucia, Evan H.; Duval, Benjamin D.

2015-10-29

To advance understanding of C dynamics of forests globally, we compiled a new database, the Forest C database (ForC-db), which contains data on ground-based measurements of ecosystem-level C stocks and annual fluxes along with disturbance history. This database currently contains 18,791 records from 2009 sites, making it the largest and most comprehensive database of C stocks and flows in forest ecosystems globally. The tropical component of the database will be published in conjunction with a manuscript that is currently under review (Anderson-Teixeira et al., in review). Database development continues, and we hope to maintain a dynamic instance of the entiremore » (global) database.« less

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...

Modeling whole-tree carbon assimilation rate using observed transpiration rates and needle sugar carbon isotope ratios.

PubMed

Hu, Jia; Moore, David J P; Riveros-Iregui, Diego A; Burns, Sean P; Monson, Russell K

2010-03-01

*Understanding controls over plant-atmosphere CO(2) exchange is important for quantifying carbon budgets across a range of spatial and temporal scales. In this study, we used a simple approach to estimate whole-tree CO(2) assimilation rate (A(Tree)) in a subalpine forest ecosystem. *We analysed the carbon isotope ratio (delta(13)C) of extracted needle sugars and combined it with the daytime leaf-to-air vapor pressure deficit to estimate tree water-use efficiency (WUE). The estimated WUE was then combined with observations of tree transpiration rate (E) using sap flow techniques to estimate A(Tree). Estimates of A(Tree) for the three dominant tree species in the forest were combined with species distribution and tree size to estimate and gross primary productivity (GPP) using an ecosystem process model. *A sensitivity analysis showed that estimates of A(Tree) were more sensitive to dynamics in E than delta(13)C. At the ecosystem scale, the abundance of lodgepole pine trees influenced seasonal dynamics in GPP considerably more than Engelmann spruce and subalpine fir because of its greater sensitivity of E to seasonal climate variation. *The results provide the framework for a nondestructive method for estimating whole-tree carbon assimilation rate and ecosystem GPP over daily-to weekly time scales.

Do ecohydrology and community dynamics feed back to banded-ecosystem structure and productivity?

NASA Astrophysics Data System (ADS)

Callegaro, Chiara; Ursino, Nadia

2016-04-01

Mixed communities including grass, shrubs and trees are often reported to populate self-organized vegetation patterns. Patterns of survey data suggest that species diversity and complementarity strengthen the dynamics of banded environments. Resource scarcity and local facilitation trigger self organization, whereas coexistence of multiple species in vegetated self-organizing patches, implying competition for water and nutrients and favorable reproduction sites, is made possible by differing adaptation strategies. Mixed community spatial self-organization has so far received relatively little attention, compared with local net facilitation of isolated species. We assumed that soil moisture availability is a proxy for the environmental niche of plant species according to Ursino and Callegaro (2016). Our modelling effort was focused on niche differentiation of coexisting species within a tiger bush type ecosystem. By minimal numerical modelling and stability analysis we try to answer a few open scientific questions: Is there an adaptation strategy that increases biodiversity and ecosystem functioning? Does specific adaptation to environmental niches influence the structure of self-organizing vegetation pattern? What specific niche distribution along the environmental gradient gives the highest global productivity?

The Potential and Flux Landscape Theory of Ecology

PubMed Central

Zhang, Kun; Wang, Erkang; Wang, Jin

2014-01-01

The species in ecosystems are mutually interacting and self sustainable stable for a certain period. Stability and dynamics are crucial for understanding the structure and the function of ecosystems. We developed a potential and flux landscape theory of ecosystems to address these issues. We show that the driving force of the ecological dynamics can be decomposed to the gradient of the potential landscape and the curl probability flux measuring the degree of the breaking down of the detailed balance (due to in or out flow of the energy to the ecosystems). We found that the underlying intrinsic potential landscape is a global Lyapunov function monotonically going down in time and the topology of the landscape provides a quantitative measure for the global stability of the ecosystems. We also quantified the intrinsic energy, the entropy, the free energy and constructed the non-equilibrium thermodynamics for the ecosystems. We studied several typical and important ecological systems: the predation, competition, mutualism and a realistic lynx-snowshoe hare model. Single attractor, multiple attractors and limit cycle attractors emerge from these studies. We studied the stability and robustness of the ecosystems against the perturbations in parameters and the environmental fluctuations. We also found that the kinetic paths between the multiple attractors do not follow the gradient paths of the underlying landscape and are irreversible because of the non-zero flux. This theory provides a novel way for exploring the global stability, function and the robustness of ecosystems. PMID:24497975

Leaf and stem economics spectra drive diversity of functional plant traits in a dynamic global vegetation model.

PubMed

Sakschewski, Boris; von Bloh, Werner; Boit, Alice; Rammig, Anja; Kattge, Jens; Poorter, Lourens; Peñuelas, Josep; Thonicke, Kirsten

2015-01-22

Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to plant functional types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the DGVM LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL- flexible individual traits (LPJmL-FIT) with flexible individual traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area (SLA), leaf longevity (LL), leaf nitrogen content (N area ), the maximum carboxylation rate of Rubisco per leaf area (vcmaxarea), and wood density (WD). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No preselection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, while lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, that is, deforestation and climate change effects. © 2015 John Wiley & Sons Ltd.

Advancing the use of minirhizotrons in wetlands

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

Iversen, Colleen M; Murphy, Meaghan T.; Allen, Michael F.

Background: Wetlands store a substantial amount of carbon (C) in deep soil organic matter deposits, and play an important role in global fluxes of carbon dioxide and methane. Fine roots (i.e., ephemeral roots that are active in water and nutrient uptake) are recognized as important components of biogeochemical cycles in nutrient-limited wetland ecosystems. However, quantification of fine-root dynamics in wetlands has generally been limited to destructive approaches, possibly because of methodological difficulties associated with the unique environmental, soil, and plant community characteristics of these systems. Non-destructive minirhizotron technology has rarely been used in wetland ecosystems. Scope: Our goal was tomore » develop a consensus on, and a methodological framework for, the appropriate installation and use of minirhizotron technology in wetland ecosystems. Here, we discuss a number of potential solutions for the challenges associated with the deployment of minirhizotron technology in wetlands, including minirhizotron installation and anchorage, capture and analysis of minirhizotron images, and upscaling of minirhizotron data for analysis of biogeochemical pools and parameterization of land surface models. Conclusions: The appropriate use of minirhizotron technology to examine relatively understudied fine-root dynamics in wetlands will advance our knowledge of ecosystem C and nutrient cycling in these globally important ecosystems.« less

The Flora Mission for Ecosystem Composition, Disturbance and Productivity

NASA Technical Reports Server (NTRS)

Asner, Gregory P.; Knox, Robert G.; Green, Robert O.; Ungar, Stephen G.

2005-01-01

Global land use and climate variability alter ecosystem conditions - including structure, function, and biological diversity - at a pace that requires unambiguous observations from satellite vantage points. Current global measurements are limited to general land cover, some disturbances, vegetation leaf area index, and canopy energy absorption. Flora is a pathfinding mission that provides new measurements of ecosystem structure, function, and diversity to understand the spatial and temporal dynamics of human and natural disturbances, and the biogeochemical and physiological responses of ecosystems to disturbance. The mission relies upon high-fidelity imaging spectroscopy to deliver full optical spectrum measurements (400-2500 nm) of the global land surface on a monthly time step at 45 meter spatial resolution for three years. The Flora measurement objectives are: (i) fractional cover of biological materials, (ii) canopy water content, (iii) vegetation pigments and light-use efficiency, (iv) plant functional types, (v) fire fuel load and fuel moisture content, and (vi) disturbance occurrence, type and intensity. These measurements are made using a multi-parameter, spectroscopic analysis approach afforded by observation of the full optical spectrum. Combining these measurements, along with additional observations from multispectral sensors, Flora will far advance global studies and models of ecosystem dynamics and change.

Dependence of spectral characteristics on parameters describing CO2 exchange between crop species and the atmosphere

NASA Astrophysics Data System (ADS)

Uździcka, Bogna; Stróżecki, Marcin; Urbaniak, Marek; Juszczak, Radosław

2017-07-01

The aim of this paper is to demonstrate that spectral vegetation indices are good indicators of parameters describing the intensity of CO2 exchange between crops and the atmosphere. Measurements were conducted over 2011-2013 on plots of an experimental arable station on winter wheat, winter rye, spring barley, and potatoes. CO2 fluxes were measured using the dynamic closed chamber system, while spectral vegetation indices were determined using SKYE multispectral sensors. Based on spectral data collected in 2011 and 2013, various models to estimate net ecosystem productivity and gross ecosystem productivity were developed. These models were then verified based on data collected in 2012. The R2 for the best model based on spectral data ranged from 0.71 to 0.83 and from 0.78 to 0.92, for net ecosystem productivity and gross ecosystem productivity, respectively. Such high R2 values indicate the utility of spectral vegetation indices in estimating CO2 fluxes of crops. The effects of the soil background turned out to be an important factor decreasing the accuracy of the tested models.

Universality of human microbial dynamics

NASA Astrophysics Data System (ADS)

Bashan, Amir; Gibson, Travis E.; Friedman, Jonathan; Carey, Vincent J.; Weiss, Scott T.; Hohmann, Elizabeth L.; Liu, Yang-Yu

2016-06-01

Human-associated microbial communities have a crucial role in determining our health and well-being, and this has led to the continuing development of microbiome-based therapies such as faecal microbiota transplantation. These microbial communities are very complex, dynamic and highly personalized ecosystems, exhibiting a high degree of inter-individual variability in both species assemblages and abundance profiles. It is not known whether the underlying ecological dynamics of these communities, which can be parameterized by growth rates, and intra- and inter-species interactions in population dynamics models, are largely host-independent (that is, universal) or host-specific. If the inter-individual variability reflects host-specific dynamics due to differences in host lifestyle, physiology or genetics, then generic microbiome manipulations may have unintended consequences, rendering them ineffective or even detrimental. Alternatively, microbial ecosystems of different subjects may exhibit universal dynamics, with the inter-individual variability mainly originating from differences in the sets of colonizing species. Here we develop a new computational method to characterize human microbial dynamics. By applying this method to cross-sectional data from two large-scale metagenomic studies—the Human Microbiome Project and the Student Microbiome Project—we show that gut and mouth microbiomes display pronounced universal dynamics, whereas communities associated with certain skin sites are probably shaped by differences in the host environment. Notably, the universality of gut microbial dynamics is not observed in subjects with recurrent Clostridium difficile infection but is observed in the same set of subjects after faecal microbiota transplantation. These results fundamentally improve our understanding of the processes that shape human microbial ecosystems, and pave the way to designing general microbiome-based therapies.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert.

PubMed

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F; Li, Lin; Seely, Mary K

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months' continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert.

The Impact of Rainfall on Soil Moisture Dynamics in a Foggy Desert

PubMed Central

Li, Bonan; Wang, Lixin; Kaseke, Kudzai F.; Li, Lin; Seely, Mary K.

2016-01-01

Soil moisture is a key variable in dryland ecosystems since it determines the occurrence and duration of vegetation water stress and affects the development of weather patterns including rainfall. However, the lack of ground observations of soil moisture and rainfall dynamics in many drylands has long been a major obstacle in understanding ecohydrological processes in these ecosystems. It is also uncertain to what extent rainfall controls soil moisture dynamics in fog dominated dryland systems. To this end, in this study, twelve to nineteen months’ continuous daily records of rainfall and soil moisture (from January 2014 to August 2015) obtained from three sites (one sand dune site and two gravel plain sites) in the Namib Desert are reported. A process-based model simulating the stochastic soil moisture dynamics in water-limited systems was used to study the relationships between soil moisture and rainfall dynamics. Model sensitivity in response to different soil and vegetation parameters under diverse soil textures was also investigated. Our field observations showed that surface soil moisture dynamics generally follow rainfall patterns at the two gravel plain sites, whereas soil moisture dynamics in the sand dune site did not show a significant relationship with rainfall pattern. The modeling results suggested that most of the soil moisture dynamics can be simulated except the daily fluctuations, which may require a modification of the model structure to include non-rainfall components. Sensitivity analyses suggested that soil hygroscopic point (sh) and field capacity (sfc) were two main parameters controlling soil moisture output, though permanent wilting point (sw) was also very sensitive under the parameter setting of sand dune (Gobabeb) and gravel plain (Kleinberg). Overall, the modeling results were not sensitive to the parameters in non-bounded group (e.g., soil hydraulic conductivity (Ks) and soil porosity (n)). Field observations, stochastic modeling results as well as sensitivity analyses provide soil moisture baseline information for future monitoring and the prediction of soil moisture patterns in the Namib Desert. PMID:27764203

From individuals to populations to communities: a dynamic energy budget model of marine ecosystem size-spectrum including life history diversity.

PubMed

Maury, Olivier; Poggiale, Jean-Christophe

2013-05-07

Individual metabolism, predator-prey relationships, and the role of biodiversity are major factors underlying the dynamics of food webs and their response to environmental variability. Despite their crucial, complementary and interacting influences, they are usually not considered simultaneously in current marine ecosystem models. In an attempt to fill this gap and determine if these factors and their interaction are sufficient to allow realistic community structure and dynamics to emerge, we formulate a mathematical model of the size-structured dynamics of marine communities which integrates mechanistically individual, population and community levels. The model represents the transfer of energy generated in both time and size by an infinite number of interacting fish species spanning from very small to very large species. It is based on standard individual level assumptions of the Dynamic Energy Budget theory (DEB) as well as important ecological processes such as opportunistic size-based predation and competition for food. Resting on the inter-specific body-size scaling relationships of the DEB theory, the diversity of life-history traits (i.e. biodiversity) is explicitly integrated. The stationary solutions of the model as well as the transient solutions arising when environmental signals (e.g. variability of primary production and temperature) propagate through the ecosystem are studied using numerical simulations. It is shown that in the absence of density-dependent feedback processes, the model exhibits unstable oscillations. Density-dependent schooling probability and schooling-dependent predatory and disease mortalities are proposed to be important stabilizing factors allowing stationary solutions to be reached. At the community level, the shape and slope of the obtained quasi-linear stationary spectrum matches well with empirical studies. When oscillations of primary production are simulated, the model predicts that the variability propagates along the spectrum in a given frequency-dependent size range before decreasing for larger sizes. At the species level, the simulations show that small and large species dominate the community successively (small species being more abundant at small sizes and large species being more abundant at large sizes) and that the total biomass of a species decreases with its maximal size which again corroborates empirical studies. Our results indicate that the simultaneous consideration of individual growth and reproduction, size-structured trophic interactions, the diversity of life-history traits and a density-dependent stabilizing process allow realistic community structure and dynamics to emerge without any arbitrary prescription. As a logical consequence of our model construction and a basis for future studies, we define the function Φ as the relative contribution of each species to the total biomass of the ecosystem, for any given size. We argue that this function is a measure of the functional role of biodiversity characterizing the impact of the structure of the community (its species composition) on its function (the relative proportions of losses, dissipation and biological work). Copyright © 2013 Elsevier Ltd. All rights reserved.

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.

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.

Improving Estimates and Forecasts of Lake Carbon Pools and Fluxes Using Data Assimilation

NASA Astrophysics Data System (ADS)

Zwart, J. A.; Hararuk, O.; Prairie, Y.; Solomon, C.; Jones, S.

2017-12-01

Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite significant use of this technique in other fields with great success. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill information gaps. In this analysis, we highlight the utility of data assimilation in lake carbon cycling research by using the Ensemble Kalman Filter to combine simple lake carbon models with observations of lake carbon pools. We demonstrate the use of data assimilation to improve a model's representation of lake carbon dynamics, to reduce uncertainty in estimates of lake carbon pools and fluxes, and to improve the accuracy of carbon pool size estimates relative to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.

Animal diversity and ecosystem functioning in dynamic food webs

NASA Astrophysics Data System (ADS)

Schneider, Florian D.; Brose, Ulrich; Rall, Björn C.; Guill, Christian

2016-10-01

Species diversity is changing globally and locally, but the complexity of ecological communities hampers a general understanding of the consequences of animal species loss on ecosystem functioning. High animal diversity increases complementarity of herbivores but also increases feeding rates within the consumer guild. Depending on the balance of these counteracting mechanisms, species-rich animal communities may put plants under top-down control or may release them from grazing pressure. Using a dynamic food-web model with body-mass constraints, we simulate ecosystem functions of 20,000 communities of varying animal diversity. We show that diverse animal communities accumulate more biomass and are more exploitative on plants, despite their higher rates of intra-guild predation. However, they do not reduce plant biomass because the communities are composed of larger, and thus energetically more efficient, plant and animal species. This plasticity of community body-size structure reconciles the debate on the consequences of animal species loss for primary productivity.

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.

A toy terrestrial carbon flow model

NASA Technical Reports Server (NTRS)

Parton, William J.; Running, Steven W.; Walker, Brian

1992-01-01

A generalized carbon flow model for the major terrestrial ecosystems of the world is reported. The model is a simplification of the Century model and the Forest-Biogeochemical model. Topics covered include plant production, decomposition and nutrient cycling, biomes, the utility of the carbon flow model for predicting carbon dynamics under global change, and possible applications to state-and-transition models and environmentally driven global vegetation models.

Interactions between nitrogen deposition, land cover conversion, and climate change determine the contemporary carbon balance of Europe

NASA Astrophysics Data System (ADS)

Churkina, G.; Zaehle, S.; Hughes, J.; Viovy, N.; Chen, Y.; Jung, M.; Heumann, B. W.; Ramankutty, N.; Rödenbeck, C.; Heimann, M.; Jones, C.

2010-03-01

European ecosystems are thought to uptake significant amounts of carbon, but neither the rate nor the contributions of the underlying processes are well known. In the second half of the 20th century, carbon dioxide concentrations have risen by more than 100 ppm, atmospheric nitrogen deposition has more than doubled, and European mean temperatures were increasing by 0.02 °C per year. The extents of forest and grasslands have increase with the respective rates of 5800 km2 yr-1 and 1100 km2 yr-1 as agricultural land has been abandoned at a rate of 7000 km2 yr-1. In this study, we analyze the responses of European land ecosystems to the aforementioned environmental changes using results from four process-based ecosystem models: BIOME-BGC, JULES, ORCHIDEE, and O-CN. All four models suggest that European terrestrial ecosystems sequester carbon at a rate of 100 TgC yr-1 (1980-2007 mean) with strong interannual variability (± 85 TgC yr-1) and a substantial inter-model uncertainty (± 45 TgC yr-1). Decadal budgets suggest that there has been a slight increase in terrestrial net carbon storage from 85 TgC yr-1 in 1980-1989 to 114 TgC yr-1 in 2000-2007. The physiological effect of rising CO2 in combination with nitrogen deposition and forest re-growth have been identified as the important explanatory factors for this net carbon storage. Changes in the growth of woody vegetation are an important contributor to the European carbon sink. Simulated ecosystem responses were more consistent for the two models accounting for terrestrial carbon-nitrogen dynamics than for the two models which only accounted for carbon cycling and the effects of land cover change. Studies of the interactions of carbon-nitrogen dynamics with land use changes are needed to further improve the quantitative understanding of the driving forces of the European land carbon balance.

Impact of fire disturbance on soil thermal and carbon dynamics in Alaskan Tundra and Boreal forest ecosystems

NASA Astrophysics Data System (ADS)

Jiang, Y.; Rastetter, E.; Shaver, G. R.; Rocha, A. V.

2012-12-01

In Alaska, fire disturbance is a major component influencing the soil water and energy balance in both tundra and boreal forest ecosystems. Fire-caused changes in soil environment further affect both above- and below-ground carbon cycles depending on different fire severities. Understanding the effects of fire disturbance on soil thermal change requires implicit modeling work on the post-fire soil thawing and freezing processes. In this study, we model the soil temperature profiles in multiple burned and non-burned sites using a well-developed soil thermal model which fully couples soil water and heat transport. The subsequent change in carbon dynamics is analyzed based on site level observations and simulations from the Multiple Element Limitation (MEL) model. With comparison between burned and non-burned sites, we compare and contrast fire effects on soil thermal and carbon dynamics in continuous permafrost (Anaktuvik fire in north slope), discontinuous permafrost (Erickson Creek fire at Hess Creek) and non-permafrost zone (Delta Junction fire in interior Alaska). Then we check the post-fire recovery of soil temperature profiles at sites with different fire severities in both tundra and boreal forest fire areas. We further project the future changes in soil thermal and carbon dynamics using projected climate data from Scenarios Network for Alaska & Arctic Planning (SNAP). This study provides information to improve the understanding of fire disturbance on soil thermal and carbon dynamics and the consequent response under a warming climate.

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.

Detecting Subtle Shifts in Ecosystem Functioning in a Dynamic Estuarine Environment

PubMed Central

Pratt, Daniel R.; Lohrer, Andrew M.; Thrush, Simon F.; Hewitt, Judi E.; Townsend, Michael; Cartner, Katie; Pilditch, Conrad A.; Harris, Rachel J.; van Colen, Carl; Rodil, Iván F.

2015-01-01

Identifying the effects of stressors before they impact ecosystem functioning can be challenging in dynamic, heterogeneous ‘real-world’ ecosystems. In aquatic systems, for example, reductions in water clarity can limit the light available for photosynthesis, with knock-on consequences for secondary consumers, though in naturally turbid wave-swept estuaries, detecting the effects of elevated turbidity can be difficult. The objective of this study was to investigate the effects of shading on ecosystem functions mediated by sandflat primary producers (microphytobenthos) and deep-dwelling surface-feeding macrofauna (Macomona liliana; Bivalvia, Veneroida, Tellinidae). Shade cloths (which reduced incident light intensity by ~80%) were deployed on an exposed, intertidal sandflat to experimentally stress the microphytobenthic community associated with the sediment surface. After 13 weeks, sediment properties, macrofauna and fluxes of oxygen and inorganic nutrients across the sediment-water interface were measured. A multivariate metric of ecosystem function (MF) was generated by combining flux-based response variables, and distance-based linear models were used to determine shifts in the drivers of ecosystem function between non-shaded and shaded plots. No significant differences in MF or in the constituent ecosystem function variables were detected between the shaded and non-shaded plots. However, shading reduced the total explained variation in MF (from 64% in non-shaded plots to 15% in shaded plots) and affected the relative influence of M. liliana and other explanatory variables on MF. This suggests that although shade stress may shift the drivers of ecosystem functioning (consistent with earlier investigations of shading effects on sandflat interaction networks), ecosystem functions appear to have a degree of resilience to those changes. PMID:26214854

SIMPPLLE, version 2.5 user's guide

Treesearch

Jimmie D. Chew; Kirk Moeller; Christine Stalling

2012-01-01

SIMPPLLE is a spatially-interactive, dynamic landscape modeling system for projecting temporal changes in the spatial distribution of vegetation in response to insects, disease, wildland fire, and other natural and management-caused disturbances. SIMPPLLE is designed to provide a balance between incorporating enough complexity and interactions in modeling ecosystem...

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.

Evaluation of eco-physiological indicators in Northeast Asia dryland regions based on MODIS products and ecological models

NASA Astrophysics Data System (ADS)

Kang, W.

2017-12-01

Ecosystem carbon-energy-water circles have significant effect on function and structure and vice verse. Based on these circles mechanism, some eco-physiological indicators, like Transpiration (T), gross primary productivity (GPP), light use efficiency (LUE) and water use efficiency (WUE), are commonly applied to assess terrestrial ecosystem function and structure dynamics. The ecosystem weakened function and simple structure in Northeast dryland regions resulted from land degradation or desertification, which could be demonstrated by above-mentioned indicators. In this study, based on MODIS atmosphere (MYD07, MYD04, MYD06 data) and land products (MYD13A2 NDVI, MYD11A1 LST, MYD15A2 LAI and land cover data), we first retrieved transpiration and LUE via Penman-Monteith Model and modified Vegetation Photosynthesis Model (VPM), respectively; and then evaluated dynamics of these eco-physiological indicators (Tair, VPD, T, LUE, GPP and WUE) and some hotspots were found for next land degradation assessment. The results showed: (1) LUE and WUE are lower in barren or sparsely vegetated area and grasslands than in forest and croplands. (2) Whereas, all indicators presented higher variability in grassland area, particularly in east Mongolia. (3) GPP and transpiration have larger variability than other indicators due to fraction of absorbed Photosynthetically active radiation (FPAR). These eco-physiological indicators are expected to continue to change under future climate change and to help to assess land degradation from ecosystem energy-water-carbon perspectives.

Improving Future Ecosystem Benefits through Earth Observations: the H2020 Project ECOPOTENTIAL

NASA Astrophysics Data System (ADS)

Provenzale, Antonello; Beierkuhnlein, Carl; Ziv, Guy

2016-04-01

Terrestrial and marine ecosystems provide essential goods and services to human societies. In the last decades, however, anthropogenic pressures caused serious threats to ecosystem integrity, functions and processes, potentially leading to the loss of essential ecosystem services. ECOPOTENTIAL is a large European-funded H2020 project which focuses its activities on a targeted set of internationally recognised protected areas in Europe, European Territories and beyond, blending Earth Observations from remote sensing and field measurements, data analysis and modelling of current and future ecosystem conditions and services. The definition of future scenarios is based on climate and land-use change projections, addressing the issue of uncertainties and uncertainty propagation across the modelling chain. The ECOPOTENTIAL project addresses cross-scale geosphere-biosphere interactions and landscape-ecosystem dynamics at regional to continental scales, using geostatistical methods and the emerging approaches in Macrosystem Ecology and Earth Critical Zone studies, addressing long-term and large-scale environmental and ecological challenges. The project started its activities in 2015, by defining a set of storylines which allow to tackle some of the most crucial issues in the assessment of present conditions and the estimate of the future state of selected ecosystem services. In this contribution, we focus on some of the main storylines of the project and discuss the general approach, focusing on the interplay of data and models and on the estimate of projection uncertainties.

Modelling marine community responses to climate-driven species redistribution to guide monitoring and adaptive ecosystem-based management.

PubMed

Marzloff, Martin Pierre; Melbourne-Thomas, Jessica; Hamon, Katell G; Hoshino, Eriko; Jennings, Sarah; van Putten, Ingrid E; Pecl, Gretta T

2016-07-01

As a consequence of global climate-driven changes, marine ecosystems are experiencing polewards redistributions of species - or range shifts - across taxa and throughout latitudes worldwide. Research on these range shifts largely focuses on understanding and predicting changes in the distribution of individual species. The ecological effects of marine range shifts on ecosystem structure and functioning, as well as human coastal communities, can be large, yet remain difficult to anticipate and manage. Here, we use qualitative modelling of system feedback to understand the cumulative impacts of multiple species shifts in south-eastern Australia, a global hotspot for ocean warming. We identify range-shifting species that can induce trophic cascades and affect ecosystem dynamics and productivity, and evaluate the potential effectiveness of alternative management interventions to mitigate these impacts. Our results suggest that the negative ecological impacts of multiple simultaneous range shifts generally add up. Thus, implementing whole-of-ecosystem management strategies and regular monitoring of range-shifting species of ecological concern are necessary to effectively intervene against undesirable consequences of marine range shifts at the regional scale. Our study illustrates how modelling system feedback with only limited qualitative information about ecosystem structure and range-shifting species can predict ecological consequences of multiple co-occurring range shifts, guide ecosystem-based adaptation to climate change and help prioritise future research and monitoring. © 2016 John Wiley & Sons Ltd.

Integrating a process-based ecosystem model with Landsat imagery to assess impacts of forest disturbance on terrestrial carbon dynamics: Case studies in Alabama and Mississippi

DOE PAGES

Chen, Guangsheng; Tian, Hanqin; Huang, Chengquan; ...

2013-07-01

Forest ecosystems in the southern United States are dramatically altered by three major disturbances: timber harvesting, hurricane, and permanent land conversion. Understanding and quantifying effects of disturbance on forest carbon, nitrogen, and water cycles is critical for sustainable forest management in this region. In this study, we introduced a process-based ecosystem model for simulating forest disturbance impacts on ecosystem carbon, nitrogen, and water cycles. Based on forest mortality data classified from Landsat TM/ETM + images, this model was then applied to estimate changes in carbon storage using Mississippi and Alabama as a case study. Mean annual forest mortality rate formore » these states was 2.37%. Due to frequent disturbance, over 50% of the forest land in the study region was less than 30 years old. Forest disturbance events caused a large carbon source (138.92 Tg C, 6.04 Tg C yr -1; 1 Tg = 10 12 g) for both states during 1984–2007, accounting for 2.89% (4.81% if disregard carbon storage changes in wood products) of the total forest carbon storage in this region. Large decreases and slow recovery of forest biomass were the main causes for carbon release. Forest disturbance could result in a carbon sink in few areas if wood product carbon was considered as a local carbon pool, indicating the importance of accounting for wood product carbon when assessing forest disturbance effects. The legacy effects of forest disturbance on ecosystem carbon storage could last over 50 years. Lastly, this study implies that understanding forest disturbance impacts on carbon dynamics is of critical importance for assessing regional carbon budgets.« less

Intraguild Predation Dynamics in a Lake Ecosystem Based on a Coupled Hydrodynamic-Ecological Model: The Example of Lake Kinneret (Israel).

PubMed

Makler-Pick, Vardit; Hipsey, Matthew R; Zohary, Tamar; Carmel, Yohay; Gal, Gideon

2017-03-29

The food web of Lake Kinneret contains intraguild predation (IGP). Predatory invertebrates and planktivorous fish both feed on herbivorous zooplankton, while the planktivorous fish also feed on the predatory invertebrates. In this study, a complex mechanistic hydrodynamic-ecological model, coupled to a bioenergetics-based fish population model (DYCD-FISH), was employed with the aim of revealing IGP dynamics. The results indicate that the predation pressure of predatory zooplankton on herbivorous zooplankton varies widely, depending on the season. At the time of its annual peak, it is 10-20 times higher than the fish predation pressure. When the number of fish was significantly higher, as occurs in the lake after atypical meteorological years, the effect was a shift from a bottom-up controlled ecosystem, to the top-down control of planktivorous fish and a significant reduction of predatory and herbivorous zooplankton biomass. Yet, seasonally, the decrease in predatory-zooplankton biomass was followed by a decrease in their predation pressure on herbivorous zooplankton, leading to an increase of herbivorous zooplankton biomass to an extent similar to the base level. The analysis demonstrates the emergence of non-equilibrium IGP dynamics due to intra-annual and inter-annual changes in the physico-chemical characteristics of the lake, and suggests that IGP dynamics should be considered in food web models in order to more accurately capture mass transfer and trophic interactions.

Partitioning sources of uncertainty in projecting the impact of future climate extremes on site to regional ecosystem carbon cycling

NASA Astrophysics Data System (ADS)

Simkins, J.; Desai, A. R.; Cowdery, E.; Dietze, M.; Rollinson, C.

2016-12-01

The terrestrial biosphere assimilates nearly one fourth of anthropogenic carbon dioxide emissions, providing a significant ecosystem service. Anthropogenic climate changes that influence the distribution and frequency of weather extremes and can have a momentous impact on this useful function that ecosystems provide. However, most analyses of the impact of extreme events on ecosystem carbon uptake do not integrate across the wide range of structural, parametric, and driver uncertainty that needs to be taken into account to estimate probability of changes to ecosystem function under shifts in climate patterns. In order to improve ecosystem model forecasts, we integrated and estimated these sources of uncertainty using an open-sourced informatics workflow, the Predictive ECosystem Analyzer (PEcAn, http://pecanproject.org). PEcAn allows any researcher to parameterize and run multiple ecosystem models and automate extraction of meteorological forcing and estimation of its uncertainty. Trait databases and a uniform protocol for parameterizing and driving models were used to test parametric and structural uncertainty. In order to sample the uncertainty in future projected meteorological drivers, we developed automated extraction routines to acquire site-level three-hourly Coupled Model Intercomparison Project 5 (CMIP5) forcing data from the Geophysical Fluid Dynamics Laboratory general circulation models (CM3, ESM2M, and ESM2G) across the r1i1p1, r3i1p1 and r5i1p1 ensembles and AR5 emission scenarios. We also implemented a site-level high temporal resolution downscaling technique for these forcings calibrated against half-hourly eddy covariance flux tower observations. Our hypothesis claims that parametric and driver uncertainty dominate over the model structural uncertainty. In order to test this, we partition the uncertainty budget on the ChEAS regional network of towers in Northern Wisconsin, USA where each tower is located in forest and wetland ecosystems.

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

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

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

1995-10-01

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

Impacts of atmospheric variability on a coupled upper-ocean/ecosystem model of the subarctic Northeast Pacific

NASA Astrophysics Data System (ADS)

Monahan, Adam Hugh; Denman, Kenneth L.

2004-06-01

The biologically-mediated flux of carbon from the upper ocean to below the permanent thermocline (the biological pump) is estimated to be ˜10 PgC/yr [, 2001], and plays an important role in the global carbon cycle. A detailed quantitative understanding of the dynamics of the biological pump is therefore important, particularly in terms of its potential sensitivity to climate change and its role in this change via feedback processes. Previous studies of coupled upper-ocean/planktonic ecosystem dynamics have considered models forced by observed atmospheric variability or by smooth annual and diurnal cycles. The second approach has the drawback that environmental variability is ubiquitous in the climate system, and may have a nontrivial impact on the (nonlinear) dynamics of the system, while the first approach is limited by the fact that observed time series are generally too short to obtain statistically robust characterizations of variability in the system. In the present study, an empirical stochastic model of high-frequency atmospheric variability (with a decorrelation timescale of less than a week) is estimated from long-term observations at Ocean Station Papa in the northeast subarctic Pacific. This empirical model, the second-order statistics of which resemble those of the observations to a good approximation, is used to produce very long (1000-year) realizations of atmospheric variability which are used to drive a coupled upper-ocean/ecosystem model. It is found that fluctuations in atmospheric forcing do not have an essential qualitative impact on most aspects of the dynamics of the ecosystem when primary production is limited by the availability of iron, although pronounced interannual variability in diatom abundance is simulated (even in the absence of episodic iron fertilization). In contrast, the impacts of atmospheric variability are considerably more significant when phytoplankton growth is limited in the summer by nitrogen availability, as observed closer to the North American coast. Furthermore, the high-frequency variability in atmospheric forcing is associated with regions in parameter space in which the system alternates between iron and nitrogen limitation on interannual to interdecadal timescales. Both the mean and variability of export production are found to be significantly larger in the nitrogen-limited regime than in the iron-limited regime.

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.

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.

Modelling southern elephant seals Mirounga leonina using an individual-based model coupled with a dynamic energy budget

PubMed Central

Melbourne-Thomas, Jessica; Corney, Stuart P.; McMahon, Clive R.; Hindell, Mark A.

2018-01-01

Higher trophic-level species are an integral component of any marine ecosystem. Despite their importance, methods for representing these species in end-to-end ecosystem models often have limited representation of life histories, energetics and behaviour. We built an individual-based model coupled with a dynamic energy budget for female southern elephant seals Mirounga leonina to demonstrate a method for detailed representation of marine mammals. We aimed to develop a model which could i) simulate energy use and life histories, as well as breeding traits of southern elephant seals in an emergent manner, ii) project a stable population over time, and iii) have realistic population dynamics and structure based on emergent life history features (such as age at first breeding, lifespan, fecundity and (yearling) survival). We evaluated the model’s ability to represent a stable population over long time periods (>10 generations), including the sensitivity of the emergent properties to variations in key parameters. Analyses indicated that the model is sensitive to changes in resource availability and energy requirements for the transition from pup to juvenile, and juvenile to adult stage. This was particularly the case for breeding success and yearling survival. This model is suitable for use as a standalone tool for investigating the impacts of changes to behaviour and population responses of southern elephant seals. PMID:29596456

Ecosystem shifts under climate change - a multi-model analysis from ISI-MIP

NASA Astrophysics Data System (ADS)

Warszawski, Lila; Beerling, David; Clark, Douglas; Friend, Andrew; Ito, Akihito; Kahana, Ron; Keribin, Rozenn; Kleidon, Axel; Lomas, Mark; Lucht, Wolfgang; Nishina, Kazuya; Ostberg, Sebastian; Pavlick, Ryan; Tito Rademacher, Tim; Schaphoff, Sibyll

2013-04-01

Dramatic ecosystem shifts, relating to vegetation composition and water and carbon stocks and fluxes, are potential consequences of climate change in the twenty-first century. Shifting climatic conditions, resulting in changes in biogeochemical properties of the ecosystem, will render it difficult for endemic plant and animal species to continue to survive in their current habitat. The potential for major shifts in biomes globally will also have severe consequences for the humans who rely on vital ecosystem services. Here we employ a novel metric of ecosystem shift to quantify the magnitude and uncertainty in these shifts at different levels of global warming, based on the response of seven biogeochemical Earth models to different future climate scenarios, in the context of the Intersectoral Impact Model Intercomparison Project (ISI-MIP). Based on this ensemble, 15% of the Earth's land surface will experience severe ecosystem shifts at 2°C degrees of global warming above 1980-2010 levels. This figure rises monotonically with global mean temperature for all models included in this study, reaching a median value of 60% of the land surface in a 4°C warmer world. At both 2°C and 4°C of warming, the most pronounced shifts occur in south-eastern India and south-western China, large swathes of the northern lattitudes above 60°N, the Amazon region and sub-Saharan Africa. Where dynamic vegetation composition is modelled, these shifts correspond to significant reductions in the land surface of vunerable vegetation types. We show that global mean temperature is a robust predictor of ecosystem shifts, whilst the spread across impact models is the greatest contributor to uncertainty.

Diversification versus specialization in complex ecosystems.

PubMed

Di Clemente, Riccardo; Chiarotti, Guido L; Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2014-01-01

By analyzing the distribution of revenues across the production sectors of quoted firms we suggest a novel dimension that drives the firms diversification process at country level. Data show a non trivial macro regional clustering of the diversification process, which underlines the relevance of geopolitical environments in determining the microscopic dynamics of economic entities. These findings demonstrate the possibility of singling out in complex ecosystems those micro-features that emerge at macro-levels, which could be of particular relevance for decision-makers in selecting the appropriate parameters to be acted upon in order to achieve desirable results. The understanding of this micro-macro information exchange is further deepened through the introduction of a simplified dynamic model.

Diversification versus Specialization in Complex Ecosystems

PubMed Central

Di Clemente, Riccardo; Chiarotti, Guido L.; Cristelli, Matthieu; Tacchella, Andrea; Pietronero, Luciano

2014-01-01

By analyzing the distribution of revenues across the production sectors of quoted firms we suggest a novel dimension that drives the firms diversification process at country level. Data show a non trivial macro regional clustering of the diversification process, which underlines the relevance of geopolitical environments in determining the microscopic dynamics of economic entities. These findings demonstrate the possibility of singling out in complex ecosystems those micro-features that emerge at macro-levels, which could be of particular relevance for decision-makers in selecting the appropriate parameters to be acted upon in order to achieve desirable results. The understanding of this micro-macro information exchange is further deepened through the introduction of a simplified dynamic model. PMID:25384059

Large-Scale Operations Management Test of Use of the White Amur for Control of Problem Aquatic Plants. Report 2. First Year Poststocking Results. Volume IV. Nitrogen and Phosphorus Dynamics of the Lake Conway Ecosystem: Loading Budgets and a Dynamic Hydrologic Phosphorus Model.

DTIC Science & Technology

1982-08-01

AD-AIA 700 FLORIDA UN1V GAINESVILLE DEPT OF ENVIRONMENTAL ENGIN -ETC F/G 6/6 LARGE-SCALE OPERATIONS MANAGEMENT TEST OF USE OF THE WHITE AMOR--ENL...Conway ecosystem and is part of the Large- Scale Operations Management Test (LSOMT) of the Aquatic Plant Control Research Program (APCRP) at the WES...should be cited as follows: Blancher, E. C., II, and Fellows, C. R. 1982. "Large-Scale Operations Management Test of Use of the White Amur for Control

Modeling the effects of free-living marine bacterial community composition on heterotrophic remineralization rates and biogeochemical carbon cycling

NASA Astrophysics Data System (ADS)

Teel, E.; Liu, X.; Cram, J. A.; Sachdeva, R.; Fuhrman, J. A.; Levine, N. M.

2016-12-01

Global oceanic ecosystem models either disregard fluctuations in heterotrophic bacterial remineralization or vary remineralization as a simple function of temperature, available carbon, and nutrient limitation. Most of these models were developed before molecular techniques allowed for the description of microbial community composition and functional diversity. Here we investigate the impact of a dynamic heterotrophic community and variable remineralization rates on biogeochemical cycling. Specifically, we integrated variable microbial remineralization into an ecosystem model by utilizing molecular community composition data, association network analysis, and biogeochemical rate data from the San Pedro Ocean Time-series (SPOT) station. Fluctuations in free-living bacterial community function and composition were examined using monthly environmental and biological data collected at SPOT between 2000 and 2011. On average, the bacterial community showed predictable seasonal changes in community composition and peaked in abundance in the spring with a one-month lag from peak chlorophyll concentrations. Bacterial growth efficiency (BGE), estimated from bacterial production, was found to vary widely at the site (5% to 40%). In a multivariate analysis, 47.6% of BGE variability was predicted using primary production, bacterial community composition, and temperature. A classic Nutrient-Phytoplankton-Zooplankton-Detritus model was expanded to include a heterotroph module that captured the observed relationships at the SPOT site. Results show that the inclusion of dynamic bacterial remineralization into larger oceanic ecosystem models can significantly impact microzooplankton grazing, the duration of surface phytoplankton blooms, and picophytoplankton primary production rates.

Towards reconstructing herbaceous biome dynamics and associated precipitation in Africa: insights from the classification of grass morphological traits

NASA Astrophysics Data System (ADS)

Pasturel, Marine; Alexandre, Anne; Novello, Alice; Moctar Dieye, Amadou; Wele, Abdoulaye; Paradis, Laure; Hely, Christelle

2014-05-01

Inter-tropical herbaceous ecosystems occupy a 1/5th of terrestrial surface, a half of the African continent, and are expected to extend in the next decades. Dynamic of these ecosystems is simulated with poor accuracy by Dynamic Global Vegetation Models (DGVMs). One of the bias results from the fact that the diversity of the grass layer dominating these herbaceous ecosystems is poorly taken into account. Mean annual precipitation and the length of the dry season are the main constrains of the dynamics of these ecosystems. Conversely, changes in vegetation affect the water cycle. Inaccuracy in herbaceous ecosystem simulation thus impacts simulations of the water cycle (including precipitation) and vice versa. In order to increase our knowledge of the relationships between grass morphological traits, taxonomy, biomes and climatic niches in Western and South Africa, a 3-step methodology was followed: i) values of culm height, leaf length and width of dominant grass species from Senegal were gathered from flora and clustered using the Partition Around Medoids (PAM) method; ii) trait group ability to sign climatic domains and biomes was assessed using Kruskal-Wallis tests; iii) genericity and robustness of the trait groups were evaluated through their application to Chadian and South African botanical datasets. Results show that 8 grass trait groups are present either in Senegal, Chad or South Africa. These 8 trait groups are distributed along mean annual precipitation and dry season length gradients. The combination of three of them allow to discriminate mean annual precipitation domains (<250, 250-600, 600-1000 and >1000 mm) and herbaceous biomes (steppes, savannas, South African grasslands and Nama-Karoo). With these results in hand, grass Plant Functional Types (PFTs) of the DGMV LPJ-GUESS will be re-parameterized and particular attention will be given to the herbaceous biomass assigned to each grass trait group. Simultaneously, relationships between grass trait groups and phytolith vegetation proxies will be quantified in order to reconstruct the past dynamics of herbaceous ecosystems and associated mean annual precipitation domains.

Mycobacterium ulcerans Ecological Dynamics and Its Association with Freshwater Ecosystems and Aquatic Communities: Results from a 12-Month Environmental Survey in Cameroon

PubMed Central

Garchitorena, Andrés; Roche, Benjamin; Kamgang, Roger; Ossomba, Joachim; Babonneau, Jérémie; Landier, Jordi; Fontanet, Arnaud; Flahault, Antoine

2014-01-01

Background Mycobacterium ulcerans (MU) is the agent responsible for Buruli Ulcer (BU), an emerging skin disease with dramatic socioeconomic and health outcomes, especially in rural settings. BU emergence and distribution is linked to aquatic ecosystems in tropical and subtropical countries, especially to swampy and flooded areas. Aquatic animal organisms are likely to play a role either as host reservoirs or vectors of the bacilli. However, information on MU ecological dynamics, both in space and time, is dramatically lacking. As a result, the ecology of the disease agent, and consequently its mode of transmission, remains largely unknown, which jeopardizes public health attempts for its control. The objective of this study was to gain insight on MU environmental distribution and colonization of aquatic organisms through time. Methodology/Principal Findings Longitudinal sampling of 32 communities of aquatic macro-invertebrates and vertebrates was conducted from different environments in two BU endemic regions in Cameroon during 12 months. As a result, 238,496 individuals were classified and MU presence was assessed by qPCR in 3,084 sample-pools containing these aquatic organisms. Our study showed a broad distribution of MU in all ecosystems and taxonomic groups, with important regional differences in its occurrence. Colonization dynamics fluctuated along the year, with the highest peaks in August and October. The large variations observed in the colonization dynamics of different taxonomic groups and aquatic ecosystems suggest that the trends shown here are the result of complex ecological processes that need further investigation. Conclusion/Perspectives This is the largest field study on MU ecology to date, providing the first detailed description of its spatio-temporal dynamics in different aquatic ecosystems within BU endemic regions. We argue that coupling this data with fine-scale epidemiological data through statistical and mathematical models will provide a major step forward in the understanding of MU ecology and mode of transmission. PMID:24831924

Methodology to assess and map the potential development of forest ecosystems exposed to climate change and atmospheric nitrogen deposition: A pilot study in Germany.

PubMed

Schröder, Winfried; Nickel, Stefan; Jenssen, Martin; Riediger, Jan

2015-07-15

A methodology for mapping ecosystems and their potential development under climate change and atmospheric nitrogen deposition was developed using examples from Germany. The methodology integrated data on vegetation, soil, climate change and atmospheric nitrogen deposition. These data were used to classify ecosystem types regarding six ecological functions and interrelated structures. Respective data covering 1961-1990 were used for reference. The assessment of functional and structural integrity relies on comparing a current or future state with an ecosystem type-specific reference. While current functions and structures of ecosystems were quantified by measurements, potential future developments were projected by geochemical soil modelling and data from a regional climate change model. The ecosystem types referenced the potential natural vegetation and were mapped using data on current tree species coverage and land use. In this manner, current ecosystem types were derived, which were related to data on elevation, soil texture, and climate for the years 1961-1990. These relations were quantified by Classification and Regression Trees, which were used to map the spatial patterns of ecosystem type clusters for 1961-1990. The climate data for these years were subsequently replaced by the results of a regional climate model for 1991-2010, 2011-2040, and 2041-2070. For each of these periods, one map of ecosystem type clusters was produced and evaluated with regard to the development of areal coverage of ecosystem type clusters over time. This evaluation of the structural aspects of ecological integrity at the national level was added by projecting potential future values of indicators for ecological functions at the site level by using the Very Simple Dynamic soil modelling technique based on climate data and two scenarios of nitrogen deposition as input. The results were compared to the reference and enabled an evaluation of site-specific ecosystem changes over time which proved to be both, positive and negative. Copyright © 2015 Elsevier B.V. All rights reserved.

Taking a closer look: disentangling effects of functional diversity on ecosystem functions with a trait-based model across hierarchy and time.

PubMed

Holzwarth, Frédéric; Rüger, Nadja; Wirth, Christian

2015-03-01

Biodiversity and ecosystem functioning (BEF) research has progressed from the detection of relationships to elucidating their drivers and underlying mechanisms. In this context, replacing taxonomic predictors by trait-based measures of functional composition (FC)-bridging functions of species and of ecosystems-is a widely used approach. The inherent challenge of trait-based approaches is the multi-faceted, dynamic and hierarchical nature of trait influence: (i) traits may act via different facets of their distribution in a community, (ii) their influence may change over time and (iii) traits may influence processes at different levels of the natural hierarchy of organization. Here, we made use of the forest ecosystem model 'LPJ-GUESS' parametrized with empirical trait data, which creates output of individual performance, community assembly, stand-level states and processes. To address the three challenges, we resolved the dynamics of the top-level ecosystem function 'annual biomass change' hierarchically into its various component processes (growth, leaf and root turnover, recruitment and mortality) and states (stand structures, water stress) and traced the influence of different facets of FC along this hierarchy in a path analysis. We found an independent influence of functional richness, dissimilarity and identity on ecosystem states and processes and hence biomass change. Biodiversity effects were only positive during early succession and later turned negative. Unexpectedly, resource acquisition (growth, recruitment) and conservation (mortality, turnover) played an equally important role throughout the succession. These results add to a mechanistic understanding of biodiversity effects and place a caveat on simplistic approaches omitting hierarchical levels when analysing BEF relationships. They support the view that BEF relationships experience dramatic shifts over successional time that should be acknowledged in mechanistic theories.

Increased topsoil carbon stock across China's forests.

PubMed

Yang, Yuanhe; Li, Pin; Ding, Jinzhi; Zhao, Xia; Ma, Wenhong; Ji, Chengjun; Fang, Jingyun

2014-08-01

Biomass carbon accumulation in forest ecosystems is a widespread phenomenon at both regional and global scales. However, as coupled carbon-climate models predicted, a positive feedback could be triggered if accelerated soil carbon decomposition offsets enhanced vegetation growth under a warming climate. It is thus crucial to reveal whether and how soil carbon stock in forest ecosystems has changed over recent decades. However, large-scale changes in soil carbon stock across forest ecosystems have not yet been carefully examined at both regional and global scales, which have been widely perceived as a big bottleneck in untangling carbon-climate feedback. Using newly developed database and sophisticated data mining approach, here we evaluated temporal changes in topsoil carbon stock across major forest ecosystem in China and analysed potential drivers in soil carbon dynamics over broad geographical scale. Our results indicated that topsoil carbon stock increased significantly within all of five major forest types during the period of 1980s-2000s, with an overall rate of 20.0 g C m(-2) yr(-1) (95% confidence interval, 14.1-25.5). The magnitude of soil carbon accumulation across coniferous forests and coniferous/broadleaved mixed forests exhibited meaningful increases with both mean annual temperature and precipitation. Moreover, soil carbon dynamics across these forest ecosystems were positively associated with clay content, with a larger amount of SOC accumulation occurring in fine-textured soils. In contrast, changes in soil carbon stock across broadleaved forests were insensitive to either climatic or edaphic variables. Overall, these results suggest that soil carbon accumulation does not counteract vegetation carbon sequestration across China's forest ecosystems. The combination of soil carbon accumulation and vegetation carbon sequestration triggers a negative feedback to climate warming, rather than a positive feedback predicted by coupled carbon-climate models. © 2014 John Wiley & Sons Ltd.

Empirical Succession Mapping and Data Assimilation to Constrain Demographic Processes in an Ecosystem Model

NASA Astrophysics Data System (ADS)

Kelly, R.; Andrews, T.; Dietze, M.

2015-12-01

Shifts in ecological communities in response to environmental change have implications for biodiversity, ecosystem function, and feedbacks to global climate change. Community composition is fundamentally the product of demography, but demographic processes are simplified or missing altogether in many ecosystem, Earth system, and species distribution models. This limitation arises in part because demographic data are noisy and difficult to synthesize. As a consequence, demographic processes are challenging to formulate in models in the first place, and to verify and constrain with data thereafter. Here, we used a novel analysis of the USFS Forest Inventory Analysis to improve the representation of demography in an ecosystem model. First, we created an Empirical Succession Mapping (ESM) based on ~1 million individual tree observations from the eastern U.S. to identify broad demographic patterns related to forest succession and disturbance. We used results from this analysis to guide reformulation of the Ecosystem Demography model (ED), an existing forest simulator with explicit tree demography. Results from the ESM reveal a coherent, cyclic pattern of change in temperate forest tree size and density over the eastern U.S. The ESM captures key ecological processes including succession, self-thinning, and gap-filling, and quantifies the typical trajectory of these processes as a function of tree size and stand density. Recruitment is most rapid in early-successional stands with low density and mean diameter, but slows as stand density increases; mean diameter increases until thinning promotes recruitment of small-diameter trees. Strikingly, the upper bound of size-density space that emerges in the ESM conforms closely to the self-thinning power law often observed in ecology. The ED model obeys this same overall size-density boundary, but overestimates plot-level growth, mortality, and fecundity rates, leading to unrealistic emergent demographic patterns. In particular, the current ED formulation cannot capture steady state dynamics evident in the ESM. Ongoing efforts are aimed at reformulating ED to more closely approach overall forest dynamics evident in the ESM, and then assimilating inventory data to constrain model parameters and initial conditions.

Integrated earth system dynamic modeling for life cycle impact assessment of ecosystem services.

PubMed

Arbault, Damien; Rivière, Mylène; Rugani, Benedetto; Benetto, Enrico; Tiruta-Barna, Ligia

2014-02-15

Despite the increasing awareness of our dependence on Ecosystem Services (ES), Life Cycle Impact Assessment (LCIA) does not explicitly and fully assess the damages caused by human activities on ES generation. Recent improvements in LCIA focus on specific cause-effect chains, mainly related to land use changes, leading to Characterization Factors (CFs) at the midpoint assessment level. However, despite the complexity and temporal dynamics of ES, current LCIA approaches consider the environmental mechanisms underneath ES to be independent from each other and devoid of dynamic character, leading to constant CFs whose representativeness is debatable. This paper takes a step forward and is aimed at demonstrating the feasibility of using an integrated earth system dynamic modeling perspective to retrieve time- and scenario-dependent CFs that consider the complex interlinkages between natural processes delivering ES. The GUMBO (Global Unified Metamodel of the Biosphere) model is used to quantify changes in ES production in physical terms - leading to midpoint CFs - and changes in human welfare indicators, which are considered here as endpoint CFs. The interpretation of the obtained results highlights the key methodological challenges to be solved to consider this approach as a robust alternative to the mainstream rationale currently adopted in LCIA. Further research should focus on increasing the granularity of environmental interventions in the modeling tools to match current standards in LCA and on adapting the conceptual approach to a spatially-explicit integrated model. Copyright © 2013 Elsevier B.V. All rights reserved.

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.

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.

Model for multi-stand management based on structural attributes of individual stands

Treesearch

G.W. Miller; J. Sullivan

1997-01-01

A growing interest in managing forest ecosystems calls for decision models that take into account attribute goals for large forest areas while continuing to recognize the individual stand as a basic unit of forest management. A dynamic, nonlinear forest management model is described that schedules silvicultural treatments for individual stands that are linked by multi-...

Description and Initial Simulation of a Dynamic Bidirectional Air-Surface Exchange Model for Mercury in Community Multiscale Air Quality Model

EPA Science Inventory

Emissions of elemental mercury (Hg⁰) from natural processes are believed to be as large as anthropogenic mercury emissions and are a critical source required to model the transport and fate of mercury. Recent ecosystem scale measurements indicate that a fraction of rec...

Local disease-ecosystem-livelihood dynamics: reflections from comparative case studies in Africa.

PubMed

Leach, Melissa; Bett, Bernard; Said, M; Bukachi, Salome; Sang, Rosemary; Anderson, Neil; Machila, Noreen; Kuleszo, Joanna; Schaten, Kathryn; Dzingirai, Vupenyu; Mangwanya, Lindiwe; Ntiamoa-Baidu, Yaa; Lawson, Elaine; Amponsah-Mensah, Kofi; Moses, Lina M; Wilkinson, Annie; Grant, Donald S; Koninga, James

2017-07-19

This article explores the implications for human health of local interactions between disease, ecosystems and livelihoods. Five interdisciplinary case studies addressed zoonotic diseases in African settings: Rift Valley fever (RVF) in Kenya, human African trypanosomiasis in Zambia and Zimbabwe, Lassa fever in Sierra Leone and henipaviruses in Ghana. Each explored how ecological changes and human-ecosystem interactions affect pathogen dynamics and hence the likelihood of zoonotic spillover and transmission, and how socially differentiated peoples' interactions with ecosystems and animals affect their exposure to disease. Cross-case analysis highlights how these dynamics vary by ecosystem type, across a range from humid forest to semi-arid savannah; the significance of interacting temporal and spatial scales; and the importance of mosaic and patch dynamics. Ecosystem interactions and services central to different people's livelihoods and well-being include pastoralism and agro-pastoralism, commercial and subsistence crop farming, hunting, collecting food, fuelwood and medicines, and cultural practices. There are synergies, but also tensions and trade-offs, between ecosystem changes that benefit livelihoods and affect disease. Understanding these can inform 'One Health' approaches towards managing ecosystems in ways that reduce disease risks and burdens.This article is part of the themed issue 'One Health for a changing world: zoonoses, ecosystems and human well-being'. © 2017 The Authors.

Climate change's impact on key ecosystem services and the human well-being they support in the US

USGS Publications Warehouse

Nelson, Erik J.; Kareiva, Peter; Ruckelshaus, Mary; Arkema, Katie; Geller, Gary; Girvetz, Evan; Goodrich, Dave; Matzek, Virginia; Pinsky, Malin; Reid, Walt; Saunders, Martin; Semmens, Darius J.; Tallis, Heather

2013-01-01

Climate change alters the functions of ecological systems. As a result, the provision of ecosystem services and the well-being of people that rely on these services are being modified. Climate models portend continued warming and more frequent extreme weather events across the US. Such weather-related disturbances will place a premium on the ecosystem services that people rely on. We discuss some of the observed and anticipated impacts of climate change on ecosystem service provision and livelihoods in the US. We also highlight promising adaptive measures. The challenge will be choosing which adaptive strategies to implement, given limited resources and time. We suggest using dynamic balance sheets or accounts of natural capital and natural assets to prioritize and evaluate national and regional adaptation strategies that involve ecosystem services.

Ages and transit times as important diagnostics of model performance for predicting C allocation in ecosystem models

NASA Astrophysics Data System (ADS)

Ceballos-Núñez, Verónika; Richardson, Andrew; Sierra, Carlos

2017-04-01

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. However, it is uncertain how some vegetation dynamics such as the allocation of carbon to different ecosystem compartments should be represented in models. The assumptions behind model structures may result in highly divergent model predictions. Here, we asses model performance by calculating the age of the carbon in the system and in each compartment, and the overall transit time of C in the system. We used these diagnostics to assess the influence of three different carbon allocation schemes on the rates of C cycling in vegetation. First, we used published measurements of ecosystem C compartments from the Harvard Forest Environmental Measurement Site to find the best set of parameters for the different model structures. Second, we calculated C stocks, respiration fluxes, radiocarbon values, ages, and transit times. We found a good fit of the three model structures to 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. Differences in model structures had a small impact on predicting ecosystem C compartments, but overall they resulted in very different predictions of age and transit time distributions. In particular, the inclusion of a storage compartment had an important impact on predicting system ages and transit times. In the case of the models with 1 or 2 storage compartments, the age of carbon in the system and in each of the compartments was distributed more towards younger ages than in the model that had no storage; the mean system age of these two models with storage was 80 years younger than in the model without storage. As expected from these age distributions, the mean transit time for the two models with storage compartments was 50 years faster than for the model without storage. 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 on 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.

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.

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.

High-resolution modeling of a marine ecosystem using the FRESCO hydroecological model

NASA Astrophysics Data System (ADS)

Zalesny, V. B.; Tamsalu, R.

2009-02-01

The FRESCO (Finnish Russian Estonian Cooperation) mathematical model describing a marine hydroecosystem is presented. The methodology of the numerical solution is based on the method of multicomponent splitting into physical and biological processes, spatial coordinates, etc. The model is used for the reproduction of physical and biological processes proceeding in the Baltic Sea. Numerical experiments are performed with different spatial resolutions for four marine basins that are enclosed into one another: the Baltic Sea, the Gulf of Finland, the Tallinn-Helsinki water area, and Tallinn Bay. Physical processes are described by the equations of nonhydrostatic dynamics, including the k-ω parametrization of turbulence. Biological processes are described by the three-dimensional equations of an aquatic ecosystem with the use of a size-dependent parametrization of biochemical reactions. The main goal of this study is to illustrate the efficiency of the developed numerical technique and to demonstrate the importance of a high spatial resolution for water basins that have complex bottom topography, such as the Baltic Sea. Detailed information about the atmospheric forcing, bottom topography, and coastline is very important for the description of coastal dynamics and specific features of a marine ecosystem. Experiments show that the spatial inhomogeneity of hydroecosystem fields is caused by the combined effect of upwelling, turbulent mixing, surface-wave breaking, and temperature variations, which affect biochemical reactions.

Interannual variation of carbon fluxes from three contrasting evergreen forests: the role of forest dynamics and climate.

PubMed

Sierra, Carlos A; Loescher, Henry W; Harmon, Mark E; Richardson, Andrew D; Hollinger, David Y; Perakis, Steven S

2009-10-01

Interannual variation of carbon fluxes can be attributed to a number of biotic and abiotic controls that operate at different spatial and temporal scales. Type and frequency of disturbance, forest dynamics, and climate regimes are important sources of variability. Assessing the variability of carbon fluxes from these specific sources can enhance the interpretation of past and current observations. Being able to separate the variability caused by forest dynamics from that induced by climate will also give us the ability to determine if the current observed carbon fluxes are within an expected range or whether the ecosystem is undergoing unexpected change. Sources of interannual variation in ecosystem carbon fluxes from three evergreen ecosystems, a tropical, a temperate coniferous, and a boreal forest, were explored using the simulation model STANDCARB. We identified key processes that introduced variation in annual fluxes, but their relative importance differed among the ecosystems studied. In the tropical site, intrinsic forest dynamics contributed approximately 30% of the total variation in annual carbon fluxes. In the temperate and boreal sites, where many forest processes occur over longer temporal scales than those at the tropical site, climate controlled more of the variation among annual fluxes. These results suggest that climate-related variability affects the rates of carbon exchange differently among sites. Simulations in which temperature, precipitation, and radiation varied from year to year (based on historical records of climate variation) had less net carbon stores than simulations in which these variables were held constant (based on historical records of monthly average climate), a result caused by the functional relationship between temperature and respiration. This suggests that, under a more variable temperature regime, large respiratory pulses may become more frequent and high enough to cause a reduction in ecosystem carbon stores. Our results also show that the variation of annual carbon fluxes poses an important challenge in our ability to determine whether an ecosystem is a source, a sink, or is neutral in regard to CO2 at longer timescales. In simulations where climate change negatively affected ecosystem carbon stores, there was a 20% chance of committing Type II error, even with 20 years of sequential data.

Multimodel inference to quantify the relative importance of abiotic factors in the population dynamics of marine zooplankton

NASA Astrophysics Data System (ADS)

Everaert, Gert; Deschutter, Yana; De Troch, Marleen; Janssen, Colin R.; De Schamphelaere, Karel

2018-05-01

The effect of multiple stressors on marine ecosystems remains poorly understood and most of the knowledge available is related to phytoplankton. To partly address this knowledge gap, we tested if combining multimodel inference with generalized additive modelling could quantify the relative contribution of environmental variables on the population dynamics of a zooplankton species in the Belgian part of the North Sea. Hence, we have quantified the relative contribution of oceanographic variables (e.g. water temperature, salinity, nutrient concentrations, and chlorophyll a concentrations) and anthropogenic chemicals (i.e. polychlorinated biphenyls) to the density of Acartia clausi. We found that models with water temperature and chlorophyll a concentration explained ca. 73% of the population density of the marine copepod. Multimodel inference in combination with regression-based models are a generic way to disentangle and quantify multiple stressor-induced changes in marine ecosystems. Future-oriented simulations of copepod densities suggested increased copepod densities under predicted environmental changes.

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.

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.

Potential effects of climate change on aquatic ecosystems of the Great Plains of North America

USGS Publications Warehouse

Covich, A.P.; Fritz, S.C.; Lamb, P.J.; Marzolf, R.D.; Matthews, W.J.; Poiani, K.A.; Prepas, E.E.; Richman, M.B.; Winter, T.C.

1997-01-01

The Great Plains landscape is less topographically complex than most other regions within North America, but diverse aquatic ecosystems, such as playas, pothole lakes, ox-bow lakes, springs, groundwater aquifers, intermittent and ephemeral streams, as well as large rivers and wetlands, are highly dynamic and responsive to extreme climatic fluctuations. We review the evidence for climatic change that demonstrates the historical importance of extremes in north-south differences in summer temperatures and east-west differences in aridity across four large subregions. These physical driving forces alter density stratification, deoxygenation, decomposition and salinity. Biotic community composition and associated ecosystem processes of productivity and nutrient cycling respond rapidly to these climatically driven dynamics. Ecosystem processes also respond to cultural effects such as dams and diversions of water for irrigation, waste dilution and urban demands for drinking water and industrial uses. Distinguishing climatic from cultural effects in future models of aquatic ecosystem functioning will require more refinement in both climatic and economic forecasting. There is a need, for example, to predict how long-term climatic forecasts (based on both ENSO and global warming simulations) relate to the permanence and productivity of shallow water ecosystems. Aquatic ecologists, hydrologists, climatologists and geographers have much to discuss regarding the synthesis of available data and the design of future interdisciplinary research. ?? 1997 by John Wiley & Sons, Ltd.

Ecosystem properties of semiarid savanna grassland in West Africa and its relationship with environmental variability.

PubMed

Tagesson, Torbern; Fensholt, Rasmus; Guiro, Idrissa; Rasmussen, Mads Olander; Huber, Silvia; Mbow, Cheikh; Garcia, Monica; Horion, Stéphanie; Sandholt, Inge; Holm-Rasmussen, Bo; Göttsche, Frank M; Ridler, Marc-Etienne; Olén, Niklas; Lundegard Olsen, Jørgen; Ehammer, Andrea; Madsen, Mathias; Olesen, Folke S; Ardö, Jonas

2015-01-01

The Dahra field site in Senegal, West Africa, was established in 2002 to monitor ecosystem properties of semiarid savanna grassland and their responses to climatic and environmental change. This article describes the environment and the ecosystem properties of the site using a unique set of in situ data. The studied variables include hydroclimatic variables, species composition, albedo, normalized difference vegetation index (NDVI), hyperspectral characteristics (350-1800 nm), surface reflectance anisotropy, brightness temperature, fraction of absorbed photosynthetic active radiation (FAPAR), biomass, vegetation water content, and land-atmosphere exchanges of carbon (NEE) and energy. The Dahra field site experiences a typical Sahelian climate and is covered by coexisting trees (~3% canopy cover) and grass species, characterizing large parts of the Sahel. This makes the site suitable for investigating relationships between ecosystem properties and hydroclimatic variables for semiarid savanna ecosystems of the region. There were strong interannual, seasonal and diurnal dynamics in NEE, with high values of ~-7.5 g C m(-2)  day(-1) during the peak of the growing season. We found neither browning nor greening NDVI trends from 2002 to 2012. Interannual variation in species composition was strongly related to rainfall distribution. NDVI and FAPAR were strongly related to species composition, especially for years dominated by the species Zornia glochidiata. This influence was not observed in interannual variation in biomass and vegetation productivity, thus challenging dryland productivity models based on remote sensing. Surface reflectance anisotropy (350-1800 nm) at the peak of the growing season varied strongly depending on wavelength and viewing angle thereby having implications for the design of remotely sensed spectral vegetation indices covering different wavelength regions. The presented time series of in situ data have great potential for dryland dynamics studies, global climate change related research and evaluation and parameterization of remote sensing products and dynamic vegetation models. © 2014 John Wiley & Sons Ltd.

Long-term stream discharge and chemistry observations reveal unexpected ecosystem dynamics: Coweeta Watershed 7 clearcut manipulation

NASA Astrophysics Data System (ADS)

Jackson, C. R.; Webster, J. R.; Knoepp, J. D.; Elliott, K.; Emanuel, R. E.; Miniat, C.

2017-12-01

In the 1970s, the Coweeta Hydrologic Laboratory Watershed 7 was clearcut from ridge to ridge to observe how far the perturbation would move the ecosystem and how quickly the ecosystem would return to its pre-disturbance state. Nearly 40 years of observations of streamflow and DIN export demonstrate that this view of ecosystem resistance and resilience was too simplistic. Forest disturbance triggered a chain of ecological dynamics that are still evolving. For the first 12 years following watershed road building, forest harvest, and forest regeneration, streamflows and DIN concentrations temporarily increased and then appeared to return to pre-harvest behavior. Thereupon the ecosystem trajectory diverged from expectations. Unexpected successional changes in forest composition interacted with drought cycles, climate change effects, and forest changes due to pests and diseases to push the biogeochemical system into an alternate state featuring persistently high DIN concentrations and hydrological rather than biological control of DIN exports. Thirty years after harvest, these forest changes also increased evapotranspiration and reduced water yields. These ecosystem dynamics were only revealed because of long-term monitoring, and they inspired new research to elucidate mechanisms behind these dynamics. We conclude that long-term approaches are critical for understanding ecosystem dynamics and responses to disturbances.

AggModel: A soil organic matter model with measurable pools for use in incubation studies

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

Segoli, Moran; De Gryze, S.; Dou, Fugen

2013-01-01

Current soil organic matter (SOM) models are empirical in nature by employing few conceptual SOM pools that have a specific turnover time, but that are not measurable and have no direct relationship with soil structural properties. Most soil particles are held together in aggregates and the number, size and stability of these aggregates significantly affect the size and amount of organic matter contained in these aggregates, and its susceptibility to decomposition. While it has been shown that soil aggregates and their dynamics can be measured directly in the laboratory and in the field, the impact of soil aggregate dynamics onmore » SOM decomposition has not been explicitly incorporated in ecosystem models. Here, we present AggModel, a conceptual and simulation model that integrates soil aggregate and SOM dynamics. In AggModel, we consider unaggregated and microaggregated soil that can exist within or external to macroaggregated soil. Each of the four aggregate size classes contains particulate organic matter and mineral-associated organic matter fractions. We used published data from laboratory incubations to calibrate and validate the biological and environmental effects on the rate of formation and breakdown of macroaggregates and microaggregates, and the organic matter dynamics within these different aggregate fractions. After calibration, AggModel explained more than 70% of the variation in aggregate masses and over 90% of the variation in aggregate-associated carbon. The model estimated the turnover time of macroaggregates as 32 days and 166 days for microaggregates. Sensitivity analysis of AggModel parameterization supported the notion that macroaggregate turnover rate has a strong control over microaggregate masses and, hence, carbon sequestration. In addition to AggModel being a proof-of-concept, the advantage of a model that is based on measurable SOM fractions is that its internal structure and dynamics can be directly calibrated and validated by using experimental data. In conclusion, AggModel successfully incorporates the explicit representation for the turnover of soil aggregates and their influence on SOM dynamics and can form the basis for new SOM modules within existing ecosystem models.« less

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya

PubMed Central

Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively. PMID:29664961

Understanding the dynamics in distribution of invasive alien plant species under predicted climate change in Western Himalaya.

PubMed

Thapa, Sunil; Chitale, Vishwas; Rijal, Srijana Joshi; Bisht, Neha; Shrestha, Bharat Babu

2018-01-01

Invasive alien plant species (IAPS) can pose severe threats to biodiversity and stability of native ecosystems, therefore, predicting the distribution of the IAPS plays a crucial role in effective planning and management of ecosystems. In the present study, we use Maximum Entropy (MaxEnt) modelling approach to predict the potential of distribution of eleven IAPS under future climatic conditions under RCP 2.6 and RCP 8.5 in part of Kailash sacred landscape region in Western Himalaya. Based on the model predictions, distribution of most of these invasive plants is expected to expand under future climatic scenarios, which might pose a serious threat to the native ecosystems through competition for resources in the study area. Native scrublands and subtropical needle-leaved forests will be the most affected ecosystems by the expansion of these IAPS. The present study is first of its kind in the Kailash Sacred Landscape in the field of invasive plants and the predictions of potential distribution under future climatic conditions from our study could help decision makers in planning and managing these forest ecosystems effectively.

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.

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Projecting water yield and ecosystem productivity across the United States by linking an ecohydrological model to WRF dynamically downscaled climate data

NASA Astrophysics Data System (ADS)

Sun, Shanlei; Sun, Ge; Cohen, Erika; McNulty, Steven G.; Caldwell, Peter V.; Duan, Kai; Zhang, Yang

2016-03-01

Quantifying the potential impacts of climate change on water yield and ecosystem productivity is essential to developing sound watershed restoration plans, and ecosystem adaptation and mitigation strategies. This study links an ecohydrological model (Water Supply and Stress Index, WaSSI) with WRF (Weather Research and Forecasting Model) using dynamically downscaled climate data of the HadCM3 model under the IPCC SRES A2 emission scenario. We evaluated the future (2031-2060) changes in evapotranspiration (ET), water yield (Q) and gross primary productivity (GPP) from the baseline period of 1979-2007 across the 82 773 watersheds (12-digit Hydrologic Unit Code level) in the coterminous US (CONUS). Across the CONUS, the future multi-year means show increases in annual precipitation (P) of 45 mm yr-1 (6 %), 1.8° C increase in temperature (T), 37 mm yr-1 (7 %) increase in ET, 9 mm yr-1 (3 %) increase in Q, and 106 gC m-2 yr-1 (9 %) increase in GPP. We found a large spatial variability in response to climate change across the CONUS 12-digit HUC watersheds, but in general, the majority would see consistent increases all variables evaluated. Over half of the watersheds, mostly found in the northeast and the southern part of the southwest, would see an increase in annual Q (> 100 mm yr-1 or 20 %). In addition, we also evaluated the future annual and monthly changes of hydrology and ecosystem productivity for the 18 Water Resource Regions (WRRs) or two-digit HUCs. The study provides an integrated method and example for comprehensive assessment of the potential impacts of climate change on watershed water balances and ecosystem productivity at high spatial and temporal resolutions. Results may be useful for policy-makers and land managers to formulate appropriate watershed-specific strategies for sustaining water and carbon sources in the face of climate change.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Dynamics of Ecosystem Services during Forest Transitions in Reventazón, Costa Rica.

PubMed

Vallet, Améline; Locatelli, Bruno; Levrel, Harold; Brenes Pérez, Christian; Imbach, Pablo; Estrada Carmona, Natalia; Manlay, Raphaël; Oszwald, Johan

2016-01-01

The forest transition framework describes the temporal changes of forest areas with economic development. A first phase of forest contraction is followed by a second phase of expansion once a turning point is reached. This framework does not differentiate forest types or ecosystem services, and describes forests regardless of their contribution to human well-being. For several decades, deforestation in many tropical regions has degraded ecosystem services, such as watershed regulation, while increasing provisioning services from agriculture, for example, food. Forest transitions and expansion have been observed in some countries, but their consequences for ecosystem services are often unclear. We analyzed the implications of forest cover change on ecosystem services in Costa Rica, where a forest transition has been suggested. A review of literature and secondary data on forest and ecosystem services in Costa Rica indicated that forest transition might have led to an ecosystem services transition. We modeled and mapped the changes of selected ecosystem services in the upper part of the Reventazón watershed and analyzed how supply changed over time in order to identify possible transitions in ecosystem services. The modeled changes of ecosystem services is similar to the second phase of a forest transition but no turning point was identified, probably because of the limited temporal scope of the analysis. Trends of provisioning and regulating services and their tradeoffs were opposite in different spatial subunits of our study area, which highlights the importance of scale in the analysis of ecosystem services and forest transitions. The ecosystem services transition framework proposed in this study is useful for analyzing the temporal changes of ecosystem services and linking socio-economic drivers to ecosystem services demand at different scales.