Biogeochemical cycling in terrestrial ecosystems - Modeling, measurement, and remote sensing

NASA Technical Reports Server (NTRS)

Peterson, D. L.; Matson, P. A.; Lawless, J. G.; Aber, J. D.; Vitousek, P. M.

1985-01-01

The use of modeling, remote sensing, and measurements to characterize the pathways and to measure the rate of biogeochemical cycling in forest ecosystems is described. The application of the process-level model to predict processes in intact forests and ecosystems response to disturbance is examined. The selection of research areas from contrasting climate regimes and sites having a fertility gradient in that regime is discussed, and the sites studied are listed. The use of remote sensing in determining leaf area index and canopy biochemistry is analyzed. Nitrous oxide emission is investigated by using a gas measurement instrument. Future research projects, which include studying the influence of changes on nutrient cycling in ecosystems and the effect of pollutants on the ecosystems, are discussed.

Adventures in holistic ecosystem modelling: the cumberland basin ecosystem model

NASA Astrophysics Data System (ADS)

Gordon, D. C.; Keizer, P. D.; Daborn, G. R.; Schwinghamer, P.; Silvert, W. L.

A holistic ecosystem model has been developed for the Cumberland Basin, a turbid macrotidal estuary at the head of Canada's Bay of Fundy. The model was constructed as a group exercise involving several dozen scientists. Philosophy of approach and methods were patterned after the BOEDE Ems-Dollard modelling project. The model is one-dimensional, has 3 compartments and 3 boundaries, and is composed of 3 separate submodels (physical, pelagic and benthic). The 28 biological state variables cover the complete estuarine ecosystem and represent broad functional groups of organisms based on trophic relationships. Although still under development and not yet validated, the model has been verified and has reached the stage where most state variables provide reasonable output. The modelling process has stimulated interdisciplinary discussion, identified important data gaps and produced a quantitative tool which can be used to examine ecological hypotheses and determine critical environmental processes. As a result, Canadian scientists have a much better understanding of the Cumberland Basin ecosystem and are better able to provide competent advice on environmental management.

Linking an ecosystem model and a landscape model to study forest species response to climate warming

Treesearch

Hong S. He; David J. Mladenoff; Thomas R. Crow

1999-01-01

No single model can address forest change from single tree to regional scales. We discuss a framework linking an ecosystem process model {LINKAGES) with a spatial landscape model (LANDIS) to examine forest species responses to climate warming for a large, heterogeneous landscape in northern Wisconsin, USA. Individual species response at the ecosystem scale was...

Terrestrial biogeochemical cycles - Global interactions with the atmosphere and hydrology

NASA Technical Reports Server (NTRS)

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

1991-01-01

A review is presented of developments in ecosystem theory, remote sensing, and geographic information systems that support new endeavors in spatial modeling. A paradigm has emerged to predict ecosystem behavior based on understanding responses to multiple resources. Ecosystem models couple primary production to decomposition and nutrient availability utilizing this paradigm. It is indicated that coupling of transport and ecosystem processes alters the behavior of earth system components (terrestrial ecosystems, hydrology, and the atmosphere) from that of an uncoupled model.

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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.

Spatially explicit simulation of hydrologically controlled carbon and nitrogen cycles and associated feedback mechanisms in a boreal ecosystem

NASA Astrophysics Data System (ADS)

Govind, Ajit; Chen, Jing Ming; Ju, Weimin

2009-06-01

Ecosystem models that simulate biogeochemical processes usually ignore hydrological controls that govern them. It is quite possible that topographically driven water fluxes significantly influence the spatial distribution of C sources and sinks because of their large contribution to the local water balance. To investigate this, we simulated biogeochemical processes along with the associated feedback mechanisms in a boreal ecosystem using a spatially explicit hydroecological model, boreal ecosystem productivity simulator (BEPS)-TerrainLab V2.0, that has a tight coupling of ecophysiological, hydrological, and biogeochemical processes. First, the simulated dynamics of snowpack, soil temperature, net ecosystem productivity (NEP), and total ecosystem respiration (TER) were validated with high-frequency measurements for 2 years. The model was able to explain 80% of the variability in NEP and 84% of the variability in TER. Further, we investigated the influence of topographically driven subsurface base flow on soil C and N cycling and on the spatiotemporal patterns of C sources and sinks using three hydrological modeling scenarios that differed in hydrological conceptualizations. In general, the scenarios that had nonexplicit hydrological representation overestimated NEP, as opposed to the scenario that had an explicit (realistic) representation. The key processes controlling the NEP differences were attributed to the combined effects of variations in photosynthesis (due to changes in stomatal conductance and nitrogen (N) availability), heterotrophic respiration, and autotrophic respiration, all of which occur simultaneously affecting NEP. Feedback relationships were also found to exacerbate the differences. We identified six types of NEP differences (biases), of which the most commonly found was due to an underestimation of the existing C sources, highlighting the vulnerability of regional-scale ecosystem models that ignore hydrological processes.

Spatially-explicit modeling of multi-scale drivers of aboveground forest biomass and water yield in watersheds of the Southeastern United States.

PubMed

Ajaz Ahmed, Mukhtar Ahmed; Abd-Elrahman, Amr; Escobedo, Francisco J; Cropper, Wendell P; Martin, Timothy A; Timilsina, Nilesh

2017-09-01

Understanding ecosystem processes and the influence of regional scale drivers can provide useful information for managing forest ecosystems. Examining more local scale drivers of forest biomass and water yield can also provide insights for identifying and better understanding the effects of climate change and management on forests. We used diverse multi-scale datasets, functional models and Geographically Weighted Regression (GWR) to model ecosystem processes at the watershed scale and to interpret the influence of ecological drivers across the Southeastern United States (SE US). Aboveground forest biomass (AGB) was determined from available geospatial datasets and water yield was estimated using the Water Supply and Stress Index (WaSSI) model at the watershed level. Our geostatistical model examined the spatial variation in these relationships between ecosystem processes, climate, biophysical, and forest management variables at the watershed level across the SE US. Ecological and management drivers at the watershed level were analyzed locally to identify whether drivers contribute positively or negatively to aboveground forest biomass and water yield ecosystem processes and thus identifying potential synergies and tradeoffs across the SE US region. Although AGB and water yield drivers varied geographically across the study area, they were generally significantly influenced by climate (rainfall and temperature), land-cover factor1 (Water and barren), land-cover factor2 (wetland and forest), organic matter content high, rock depth, available water content, stand age, elevation, and LAI drivers. These drivers were positively or negatively associated with biomass or water yield which significantly contributes to ecosystem interactions or tradeoff/synergies. Our study introduced a spatially-explicit modelling framework to analyze the effect of ecosystem drivers on forest ecosystem structure, function and provision of services. This integrated model approach facilitates multi-scale analyses of drivers and interactions at the local to regional scale. Copyright © 2017 Elsevier Ltd. All rights reserved.

Climate Change Vulnerability of Agro-Ecosystems: Does socio-economic factors matters?

NASA Astrophysics Data System (ADS)

Surendran Nair, S.; Preston, B. L.; King, A. W.; Mei, R.; Post, W. M.

2013-12-01

Climate variability and change has direct impacts on agriculture. Despite continual adaptation to climate as well as gains in technology innovation and adoption, agriculture is still vulnerable to changes in temperature and precipitation expected in coming decades. Generally, researchers use two major methodologies to understand the vulnerability of agro-ecosystems to climate change: process-based crop models and empirical models. However, these models are not yet designed to capture the influence of socioeconomic systems on agro-ecosystem processes and outcomes.. However, socioeconomic processes are an important factor driving agro-ecological responses to biophysical processes (climate, topography and soil), because of the role of human agency in mediating the response of agro-ecosystems to climate. We have developed a framework that integrates socioeconomic and biophysical characteristics of agro-ecosystems using cluster analysis and GIS tools. This framework has been applied to the U.S. Southeast to define unique socio-ecological domains for agriculture. The results demonstrate that socioeconomic characteristics are an important factor influencing agriculture production. These results suggest that the lack of attention to socioeconomic conditions and human agency in agro-ecological modeling creates a potential bias with respect to the representation of climate change impacts.

Simulating carbon and water fluxes at Arctic and boreal ecosystems in Alaska by optimizing the modified BIOME-BGC with eddy covariance data

NASA Astrophysics Data System (ADS)

Ueyama, M.; Kondo, M.; Ichii, K.; Iwata, H.; Euskirchen, E. S.; Zona, D.; Rocha, A. V.; Harazono, Y.; Nakai, T.; Oechel, W. C.

2013-12-01

To better predict carbon and water cycles in Arctic ecosystems, we modified a process-based ecosystem model, BIOME-BGC, by introducing new processes: change in active layer depth on permafrost and phenology of tundra vegetation. The modified BIOME-BGC was optimized using an optimization method. The model was constrained using gross primary productivity (GPP) and net ecosystem exchange (NEE) at 23 eddy covariance sites in Alaska, and vegetation/soil carbon from a literature survey. The model was used to simulate regional carbon and water fluxes of Alaska from 1900 to 2011. Simulated regional fluxes were validated with upscaled GPP, ecosystem respiration (RE), and NEE based on two methods: (1) a machine learning technique and (2) a top-down model. Our initial simulation suggests that the original BIOME-BGC with default ecophysiological parameters substantially underestimated GPP and RE for tundra and overestimated those fluxes for boreal forests. We will discuss how optimization using the eddy covariance data impacts the historical simulation by comparing the new version of the model with simulated results from the original BIOME-BGC with default ecophysiological parameters. This suggests that the incorporation of the active layer depth and plant phenology processes is important to include when simulating carbon and water fluxes in Arctic ecosystems.

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.

Modeling coupled interactions of carbon, water, and ozone exchange between terrestrial ecosystems and the atmosphere

Treesearch

Ned Nikolova; Karl F. Zeller

2003-01-01

A new biophysical model (FORFLUX) is presented to study the simultaneous exchange of ozone, carbon dioxide, and water vapor between terrestrial ecosystems and the atmosphere. The model mechanistically couples all major processes controlling ecosystem flows trace gases and water implementing recent concepts in plant eco-physiology, micrometeorology, and soil hydrology....

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

EPA Science Inventory

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

Spatial perspectives in state-and-transition models: A missing link to land management?

USDA-ARS?s Scientific Manuscript database

Conceptual models of alternative states and thresholds are based largely on observations of ecosystem processes at a few points in space. Because the distribution of alternative states in spatially-structured ecosystems is the result of variations in pattern-process interactions at different scales,...

Revisiting the Holy Grail: using plant functional traits to understand ecological processes.

PubMed

Funk, Jennifer L; Larson, Julie E; Ames, Gregory M; Butterfield, Bradley J; Cavender-Bares, Jeannine; Firn, Jennifer; Laughlin, Daniel C; Sutton-Grier, Ariana E; Williams, Laura; Wright, Justin

2017-05-01

One of ecology's grand challenges is developing general rules to explain and predict highly complex systems. Understanding and predicting ecological processes from species' traits has been considered a 'Holy Grail' in ecology. Plant functional traits are increasingly being used to develop mechanistic models that can predict how ecological communities will respond to abiotic and biotic perturbations and how species will affect ecosystem function and services in a rapidly changing world; however, significant challenges remain. In this review, we highlight recent work and outstanding questions in three areas: (i) selecting relevant traits; (ii) describing intraspecific trait variation and incorporating this variation into models; and (iii) scaling trait data to community- and ecosystem-level processes. Over the past decade, there have been significant advances in the characterization of plant strategies based on traits and trait relationships, and the integration of traits into multivariate indices and models of community and ecosystem function. However, the utility of trait-based approaches in ecology will benefit from efforts that demonstrate how these traits and indices influence organismal, community, and ecosystem processes across vegetation types, which may be achieved through meta-analysis and enhancement of trait databases. Additionally, intraspecific trait variation and species interactions need to be incorporated into predictive models using tools such as Bayesian hierarchical modelling. Finally, existing models linking traits to community and ecosystem processes need to be empirically tested for their applicability to be realized. © 2016 Cambridge Philosophical Society.

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...

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.

Improved global simulation of groundwater-ecosystem interactions via tight coupling of a dynamic global ecosystem model and a global hydrological model

NASA Astrophysics Data System (ADS)

Braakhekke, Maarten; Rebel, Karin; Dekker, Stefan; Smith, Benjamin; Sutanudjaja, Edwin; van Beek, Rens; van Kampenhout, Leo; Wassen, Martin

2017-04-01

In up to 30% of the global land surface ecosystems are potentially influenced by the presence of a shallow groundwater table. In these regions upward water flux by capillary rise increases soil moisture availability in the root zone, which has a strong effect on evapotranspiration, vegetation dynamics, and fluxes of carbon and nitrogen. 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. Dynamic global vegetation models (DGVMs), describe land surface from an ecological perspective, combining detailed description of vegetation dynamics and structure, and biogeochemical processes and 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, which explicitly simulates groundwater dynamics. This coupled model allows us to explicitly account for groundwater effects on terrestrial ecosystem processes at global scale. Results of global simulations indicate that groundwater strongly influences fluxes of water, carbon and nitrogen, in many regions, adding up to a considerable effect at the global scale.

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

Treesearch

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

2013-01-01

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

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.

Conceptualizing and Communicating River Restoration

NASA Astrophysics Data System (ADS)

Jacobosn, R. B.

2007-12-01

River restoration increasingly involves collaboration with stakeholders having diverse values and varying technical understanding. In cases where river restoration proceeds through collaborative processes, scientists are required to communicate complex understanding about riverine ecosystem processes to broad audiences. Of particular importance is communication of uncertainties in predictions of ecosystem responses to restoration actions, and how those uncertainties affect monitoring and evaluation strategies. I present a relatively simple conceptual model of how riverine ecosystems operate. The model, which has been used to conceptualize and communicate various river-restoration and management processes in the Lower Missouri River, emphasizes a) the interdependencies of driving regimes (for example, flow, sediment, and water quality), b) the filtering effect of management history, c) the typical hierarchical nature of information about how ecosystems operate, and d) how scientific understanding interacts with decision making. I provide an example of how the conceptual model has been used to illustrate the effects of extensive channel re-engineering of the Lower Missouri River which is intended to mitigate the effects of channelization and flow regulation on aquatic and flood-plain ecosystems. The conceptual model illustrates the logic for prioritizing investments in monitoring and evaluation, interactions among ecosystem components, tradeoffs between ecological and social-commercial benefits, and the feedback loop necessary for successful adaptive management.

Understanding the Day Cent model: Calibration, sensitivity, and identifiability through inverse modeling

USGS Publications Warehouse

Necpálová, Magdalena; Anex, Robert P.; Fienen, Michael N.; Del Grosso, Stephen J.; Castellano, Michael J.; Sawyer, John E.; Iqbal, Javed; Pantoja, Jose L.; Barker, Daniel W.

2015-01-01

The ability of biogeochemical ecosystem models to represent agro-ecosystems depends on their correct integration with field observations. We report simultaneous calibration of 67 DayCent model parameters using multiple observation types through inverse modeling using the PEST parameter estimation software. Parameter estimation reduced the total sum of weighted squared residuals by 56% and improved model fit to crop productivity, soil carbon, volumetric soil water content, soil temperature, N2O, and soil3NO− compared to the default simulation. Inverse modeling substantially reduced predictive model error relative to the default model for all model predictions, except for soil 3NO− and 4NH+. Post-processing analyses provided insights into parameter–observation relationships based on parameter correlations, sensitivity and identifiability. Inverse modeling tools are shown to be a powerful way to systematize and accelerate the process of biogeochemical model interrogation, improving our understanding of model function and the underlying ecosystem biogeochemical processes that they represent.

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China

PubMed Central

Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO2, and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone. PMID:28286690

A Carbon Cycle Model for the Social-Ecological Process in Coastal Wetland: A Case Study on Gouqi Island, East China.

PubMed

Li, Yanxia; Xiong, Lihu; Zhu, Wenjia

2017-01-01

Coastal wetlands offer many important ecosystem services both in natural and in social systems. How to simultaneously decrease the destructive effects flowing from human activities and maintaining the sustainability of regional wetland ecosystems are an important issue for coastal wetlands zones. We use carbon credits as the basis for regional sustainable developing policy-making. With the case of Gouqi Island, a typical coastal wetlands zone that locates in the East China Sea, a carbon cycle model was developed to illustrate the complex social-ecological processes. Carbon-related processes in natural ecosystem, primary industry, secondary industry, tertiary industry, and residents on the island were identified in the model. The model showed that 36780 tons of carbon is released to atmosphere with the form of CO 2 , and 51240 tons of carbon is captured by the ecosystem in 2014 and the three major resources of carbon emission are transportation and tourism development and seawater desalination. Based on the carbon-related processes and carbon balance, we proposed suggestions on the sustainable development strategy of Gouqi Island as coastal wetlands zone.

Knowledge Management in Preserving Ecosystems: The Case of Seoul

ERIC Educational Resources Information Center

Lee, Jeongseok

2009-01-01

This study explores the utility of employing knowledge management as a framework for understanding how public managers perform ecosystem management. It applies the grounded theory method to build a model. The model is generated by applying the concept of knowledge process to an investigation of how the urban ecosystem is publicly managed by civil…

Impaired ecosystem process despite little effects on populations: modeling combined effects of warming and toxicants.

PubMed

Galic, Nika; Grimm, Volker; Forbes, Valery E

2017-08-01

Freshwater ecosystems are exposed to many stressors, including toxic chemicals and global warming, which can impair, separately or in combination, important processes in organisms and hence higher levels of organization. Investigating combined effects of warming and toxicants has been a topic of little research, but neglecting their combined effects may seriously misguide management efforts. To explore how toxic chemicals and warming, alone and in combination, propagate across levels of biological organization, including a key ecosystem process, we developed an individual-based model (IBM) of a freshwater amphipod detritivore, Gammarus pseudolimnaeus, feeding on leaf litter. In this IBM, life history emerges from the individuals' energy budgets. We quantified, in different warming scenarios (+1-+4 °C), the effects of hypothetical toxicants on suborganismal processes, including feeding, somatic and maturity maintenance, growth, and reproduction. Warming reduced mean adult body sizes and population abundance and biomass, but only in the warmest scenarios. Leaf litter processing, a key contributor to ecosystem functioning and service delivery in streams, was consistently enhanced by warming, through strengthened interaction between the detritivorous consumer and its resource. Toxicant effects on feeding and maintenance resulted in initially small adverse effects on consumers, but ultimately led to population extinction and loss of ecosystem process. Warming in combination with toxicants had little effect at the individual and population levels, but ecosystem process was impaired in the warmer scenarios. Our results suggest that exposure to the same amount of toxicants can disproportionately compromise ecosystem processing depending on global warming scenarios; for example, reducing organismal feeding rates by 50% will reduce resource processing by 50% in current temperature conditions, but by up to 200% with warming of 4 °C. Our study has implications for assessing and monitoring impacts of chemicals on ecosystems facing global warming. We advise complementing existing monitoring approaches with directly quantifying ecosystem processes and services. © 2017 John Wiley & Sons Ltd.

The 1990 forest ecosystem dynamics multisensor aircraft campaign

NASA Technical Reports Server (NTRS)

Williams, Darrel L.; Ranson, K. Jon

1991-01-01

The overall objective of the Forest Ecosystem Dynamics (FED) research activity is to develop a better understanding of the dynamics of forest ecosystem evolution over a variety of temporal and spatial scales. Primary emphasis is being placed on assessing the ecosystem dynamics associated with the transition zone between northern hardwood forests in eastern North America and the predominantly coniferous forests of the more northerly boreal biome. The approach is to combine ground-based, airborne, and satellite observations with an integrated forest pattern and process model which is being developed to link together existing models of forest growth and development, soil processes, and radiative transfer.

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.

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed Central

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J. M.; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C.; Glanville, Helen C.; Jones, Davey L.; Angel, Roey; Salminen, Janne; Newton, Ryan J.; Bürgmann, Helmut; Ingram, Lachlan J.; Hamer, Ute; Siljanen, Henri M. P.; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C.; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C.; Lopes, Ana R.; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S.; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S.; Basiliko, Nathan; Nemergut, Diana R.

2016-01-01

Microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology. PMID:26941732

Microbes as Engines of Ecosystem Function: When Does Community Structure Enhance Predictions of Ecosystem Processes?

PubMed

Graham, Emily B; Knelman, Joseph E; Schindlbacher, Andreas; Siciliano, Steven; Breulmann, Marc; Yannarell, Anthony; Beman, J M; Abell, Guy; Philippot, Laurent; Prosser, James; Foulquier, Arnaud; Yuste, Jorge C; Glanville, Helen C; Jones, Davey L; Angel, Roey; Salminen, Janne; Newton, Ryan J; Bürgmann, Helmut; Ingram, Lachlan J; Hamer, Ute; Siljanen, Henri M P; Peltoniemi, Krista; Potthast, Karin; Bañeras, Lluís; Hartmann, Martin; Banerjee, Samiran; Yu, Ri-Qing; Nogaro, Geraldine; Richter, Andreas; Koranda, Marianne; Castle, Sarah C; Goberna, Marta; Song, Bongkeun; Chatterjee, Amitava; Nunes, Olga C; Lopes, Ana R; Cao, Yiping; Kaisermann, Aurore; Hallin, Sara; Strickland, Michael S; Garcia-Pausas, Jordi; Barba, Josep; Kang, Hojeong; Isobe, Kazuo; Papaspyrou, Sokratis; Pastorelli, Roberta; Lagomarsino, Alessandra; Lindström, Eva S; Basiliko, Nathan; Nemergut, Diana R

2016-01-01

Microorganisms are vital in mediating the earth's biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: 'When do we need to understand microbial community structure to accurately predict function?' We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of process rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.

The evolution of ecosystem ascendency in a complex systems based model.

PubMed

Brinck, Katharina; Jensen, Henrik Jeldtoft

2017-09-07

General patterns in ecosystem development can shed light on driving forces behind ecosystem formation and recovery and have been of long interest. In recent years, the need for integrative and process oriented approaches to capture ecosystem growth, development and organisation, as well as the scope of information theory as a descriptive tool has been addressed from various sides. However data collection of ecological network flows is difficult and tedious and comprehensive models are lacking. We use a hierarchical version of the Tangled Nature Model of evolutionary ecology to study the relationship between structure, flow and organisation in model ecosystems, their development over evolutionary time scales and their relation to ecosystem stability. Our findings support the validity of ecosystem ascendency as a meaningful measure of ecosystem organisation, which increases over evolutionary time scales and significantly drops during periods of disturbance. The results suggest a general trend towards both higher integrity and increased stability driven by functional and structural ecosystem coadaptation. Copyright © 2017 Elsevier Ltd. All rights reserved.

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...

A quantitative assessment of a terrestrial biosphere model's data needs across North American biomes

NASA Astrophysics Data System (ADS)

Dietze, Michael C.; Serbin, Shawn P.; Davidson, Carl; Desai, Ankur R.; Feng, Xiaohui; Kelly, Ryan; Kooper, Rob; LeBauer, David; Mantooth, Joshua; McHenry, Kenton; Wang, Dan

2014-03-01

Terrestrial biosphere models are designed to synthesize our current understanding of how ecosystems function, test competing hypotheses of ecosystem function against observations, and predict responses to novel conditions such as those expected under climate change. Reducing uncertainties in such models can improve both basic scientific understanding and our predictive capacity, but rarely are ecosystem models employed in the design of field campaigns. We provide a synthesis of carbon cycle uncertainty analyses conducted using the Predictive Ecosystem Analyzer ecoinformatics workflow with the Ecosystem Demography model v2. This work is a synthesis of multiple projects, using Bayesian data assimilation techniques to incorporate field data and trait databases across temperate forests, grasslands, agriculture, short rotation forestry, boreal forests, and tundra. We report on a number of data needs that span a wide array of diverse biomes, such as the need for better constraint on growth respiration, mortality, stomatal conductance, and water uptake. We also identify data needs that are biome specific, such as photosynthetic quantum efficiency at high latitudes. We recommend that future data collection efforts balance the bias of past measurements toward aboveground processes in temperate biomes with the sensitivities of different processes as represented by ecosystem models. ©2014. American Geophysical Union. All Rights Reserved.

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.

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.

Potential for real-time understanding of coupled hydrologic and biogeochemical processes in stream ecosystems: Future integration of telemetered data with process models for glacial meltwater streams

NASA Astrophysics Data System (ADS)

McKnight, Diane M.; Cozzetto, Karen; Cullis, James D. S.; Gooseff, Michael N.; Jaros, Christopher; Koch, Joshua C.; Lyons, W. Berry; Neupauer, Roseanna; Wlostowski, Adam

2015-08-01

While continuous monitoring of streamflow and temperature has been common for some time, there is great potential to expand continuous monitoring to include water quality parameters such as nutrients, turbidity, oxygen, and dissolved organic material. In many systems, distinguishing between watershed and stream ecosystem controls can be challenging. The usefulness of such monitoring can be enhanced by the application of quantitative models to interpret observed patterns in real time. Examples are discussed primarily from the glacial meltwater streams of the McMurdo Dry Valleys, Antarctica. Although the Dry Valley landscape is barren of plants, many streams harbor thriving cyanobacterial mats. Whereas a daily cycle of streamflow is controlled by the surface energy balance on the glaciers and the temporal pattern of solar exposure, the daily signal for biogeochemical processes controlling water quality is generated along the stream. These features result in an excellent outdoor laboratory for investigating fundamental ecosystem process and the development and validation of process-based models. As part of the McMurdo Dry Valleys Long-Term Ecological Research project, we have conducted field experiments and developed coupled biogeochemical transport models for the role of hyporheic exchange in controlling weathering reactions, microbial nitrogen cycling, and stream temperature regulation. We have adapted modeling approaches from sediment transport to understand mobilization of stream biomass with increasing flows. These models help to elucidate the role of in-stream processes in systems where watershed processes also contribute to observed patterns, and may serve as a test case for applying real-time stream ecosystem models.

Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition.

PubMed

Bradford, Mark A; Wood, Stephen A; Bardgett, Richard D; Black, Helaina I J; Bonkowski, Michael; Eggers, Till; Grayston, Susan J; Kandeler, Ellen; Manning, Peter; Setälä, Heikki; Jones, T Hefin

2014-10-07

Ecosystem management policies increasingly emphasize provision of multiple, as opposed to single, ecosystem services. Management for such "multifunctionality" has stimulated research into the role that biodiversity plays in providing desired rates of multiple ecosystem processes. Positive effects of biodiversity on indices of multifunctionality are consistently found, primarily because species that are redundant for one ecosystem process under a given set of environmental conditions play a distinct role under different conditions or in the provision of another ecosystem process. Here we show that the positive effects of diversity (specifically community composition) on multifunctionality indices can also arise from a statistical fallacy analogous to Simpson's paradox (where aggregating data obscures causal relationships). We manipulated soil faunal community composition in combination with nitrogen fertilization of model grassland ecosystems and repeatedly measured five ecosystem processes related to plant productivity, carbon storage, and nutrient turnover. We calculated three common multifunctionality indices based on these processes and found that the functional complexity of the soil communities had a consistent positive effect on the indices. However, only two of the five ecosystem processes also responded positively to increasing complexity, whereas the other three responded neutrally or negatively. Furthermore, none of the individual processes responded to both the complexity and the nitrogen manipulations in a manner consistent with the indices. Our data show that multifunctionality indices can obscure relationships that exist between communities and key ecosystem processes, leading us to question their use in advancing theoretical understanding--and in management decisions--about how biodiversity is related to the provision of multiple ecosystem services.

Discontinuity in the responses of ecosystem processes and multifunctionality to altered soil community composition

PubMed Central

Bradford, Mark A.; Wood, Stephen A.; Bardgett, Richard D.; Black, Helaina I. J.; Bonkowski, Michael; Eggers, Till; Grayston, Susan J.; Kandeler, Ellen; Manning, Peter; Setälä, Heikki; Jones, T. Hefin

2014-01-01

Ecosystem management policies increasingly emphasize provision of multiple, as opposed to single, ecosystem services. Management for such “multifunctionality” has stimulated research into the role that biodiversity plays in providing desired rates of multiple ecosystem processes. Positive effects of biodiversity on indices of multifunctionality are consistently found, primarily because species that are redundant for one ecosystem process under a given set of environmental conditions play a distinct role under different conditions or in the provision of another ecosystem process. Here we show that the positive effects of diversity (specifically community composition) on multifunctionality indices can also arise from a statistical fallacy analogous to Simpson’s paradox (where aggregating data obscures causal relationships). We manipulated soil faunal community composition in combination with nitrogen fertilization of model grassland ecosystems and repeatedly measured five ecosystem processes related to plant productivity, carbon storage, and nutrient turnover. We calculated three common multifunctionality indices based on these processes and found that the functional complexity of the soil communities had a consistent positive effect on the indices. However, only two of the five ecosystem processes also responded positively to increasing complexity, whereas the other three responded neutrally or negatively. Furthermore, none of the individual processes responded to both the complexity and the nitrogen manipulations in a manner consistent with the indices. Our data show that multifunctionality indices can obscure relationships that exist between communities and key ecosystem processes, leading us to question their use in advancing theoretical understanding—and in management decisions—about how biodiversity is related to the provision of multiple ecosystem services. PMID:25246582

Carbon Cycle Model Linkage Project (CCMLP): Evaluating Biogeochemical Process Models with Atmospheric Measurements and Field Experiments

NASA Astrophysics Data System (ADS)

Heimann, M.; Prentice, I. C.; Foley, J.; Hickler, T.; Kicklighter, D. W.; McGuire, A. D.; Melillo, J. M.; Ramankutty, N.; Sitch, S.

2001-12-01

Models of biophysical and biogeochemical proceses are being used -either offline or in coupled climate-carbon cycle (C4) models-to assess climate- and CO2-induced feedbacks on atmospheric CO2. Observations of atmospheric CO2 concentration, and supplementary tracers including O2 concentrations and isotopes, offer unique opportunities to evaluate the large-scale behaviour of models. Global patterns, temporal trends, and interannual variability of the atmospheric CO2 concentration and its seasonal cycle provide crucial benchmarks for simulations of regionally-integrated net ecosystem exchange; flux measurements by eddy correlation allow a far more demanding model test at the ecosystem scale than conventional indicators, such as measurements of annual net primary production; and large-scale manipulations, such as the Duke Forest Free Air Carbon Enrichment (FACE) experiment, give a standard to evaluate modelled phenomena such as ecosystem-level CO2 fertilization. Model runs including historical changes of CO2, climate and land use allow comparison with regional-scale monthly CO2 balances as inferred from atmospheric measurements. Such comparisons are providing grounds for some confidence in current models, while pointing to processes that may still be inadequately treated. Current plans focus on (1) continued benchmarking of land process models against flux measurements across ecosystems and experimental findings on the ecosystem-level effects of enhanced CO2, reactive N inputs and temperature; (2) improved representation of land use, forest management and crop metabolism in models; and (3) a strategy for the evaluation of C4 models in a historical observational context.

A probabilistic process model for pelagic marine ecosystems informed by Bayesian inverse analysis

EPA Science Inventory

Marine ecosystems are complex systems with multiple pathways that produce feedback cycles, which may lead to unanticipated effects. Models abstract this complexity and allow us to predict, understand, and hypothesize. In ecological models, however, the paucity of empirical data...

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.

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...

Modelling hydrological processes and analysing water-related ecosystem services of Western Siberian lowland basins

NASA Astrophysics Data System (ADS)

Schmalz, Britta; Kiesel, Jens; Kruse, Marion; Pfannerstill, Matthias; Sheludkov, Artyom; Khoroshavin, Vitaliy; Veshkurseva, Tatyana; Müller, Felix; Fohrer, Nicola

2015-04-01

For discussing and planning sustainable land management of river basins, stakeholders need suitable information on spatio-temporal patterns of hydrological components and ecosystem services. The ecosystem services concept, i.e., services provided by ecosystems that contribute to human welfare benefits, contributes comprehensive information for sustainable river management. This study shows an approach to use ecohydrological modelling results for quantifying and assessing water-related ecosystem services in three lowland river basins in Western Siberia, a region which is of global significance in terms of carbon sequestration, agricultural production and biodiversity preservation. Using the ecohydrological model SWAT, the three basins Pyschma (16762 km²), Vagai (3348 km²) and Loktinka (373 km²) were modelled following a gradient from the landscape units taiga, pre-taiga to forest steppe. For a correct representation of the Siberian lowland hydrology, the consideration of snow melt and retention of surface runoff as well as the implementation of a second groundwater aquifer was of great importance. Good to satisfying model performances were obtained for the extreme hydrological conditions. The simulated SWAT output variables of different hydrological processes were used as indicators for the two regulating services water flow and erosion regulation. The model results were translated into a relative ecosystem service valuation scale. The resulting ecosystem service maps show different spatial and seasonal patterns. Although the high resolution modelling results are averaged out within the aggregated relative valuation scale, seasonal differences can be depicted: during snowmelt, low relevant regulation can be determined, especially for water flow regulation, but a very high relevant regulation was calculated for the vegetation period during summer and for the winter period. The SWAT model serves as a suitable quantification method for the assessment of water-related ecosystem services on different spatial scales and ecoregions of the Western Siberian lowlands.

Perturbations and gradients as fundamental tests for modeling the soil carbon cycle

NASA Astrophysics Data System (ADS)

Bond-Lamberty, B. P.; Bailey, V. L.; Becker, K.; Fansler, S.; Hinkle, C.; Liu, C.

2013-12-01

An important step in matching process-level knowledge to larger-scale measurements and model results is to challenge those models with site-specific perturbations and/or changing environmental conditions. Here we subject modified versions of an ecosystem process model to two stringent tests: replicating a long-term climate change dryland experiment (Rattlesnake Mountain) and partitioning the carbon fluxes of a soil drainage gradient in the northern Everglades (Disney Wilderness Preserve). For both sites, on-site measurements were supplemented by laboratory incubations of soil columns. We used a parameter-space search algorithm to optimize, within observational limits, the model's influential inputs, so that the spun-up carbon stocks and fluxes matched observed values. Modeled carbon fluxes (net primary production and net ecosystem exchange) agreed with measured values, within observational error limits, but the model's partitioning of soil fluxes (autotrophic versus heterotrophic), did not match laboratory measurements from either site. Accounting for site heterogeneity at DWP, modeled carbon exchange was reasonably consistent with values from eddy covariance. We discuss the implications of this work for ecosystem- to global scale modeling of ecosystems in a changing climate.

A protocol for the intercomparison of marine fishery and ecosystem models: Fish-MIP v1.0

NASA Astrophysics Data System (ADS)

Tittensor, Derek P.; Eddy, Tyler D.; Lotze, Heike K.; Galbraith, Eric D.; Cheung, William; Barange, Manuel; Blanchard, Julia L.; Bopp, Laurent; Bryndum-Buchholz, Andrea; Büchner, Matthias; Bulman, Catherine; Carozza, David A.; Christensen, Villy; Coll, Marta; Dunne, John P.; Fernandes, Jose A.; Fulton, Elizabeth A.; Hobday, Alistair J.; Huber, Veronika; Jennings, Simon; Jones, Miranda; Lehodey, Patrick; Link, Jason S.; Mackinson, Steve; Maury, Olivier; Niiranen, Susa; Oliveros-Ramos, Ricardo; Roy, Tilla; Schewe, Jacob; Shin, Yunne-Jai; Silva, Tiago; Stock, Charles A.; Steenbeek, Jeroen; Underwood, Philip J.; Volkholz, Jan; Watson, James R.; Walker, Nicola D.

2018-04-01

Model intercomparison studies in the climate and Earth sciences communities have been crucial to building credibility and coherence for future projections. They have quantified variability among models, spurred model development, contrasted within- and among-model uncertainty, assessed model fits to historical data, and provided ensemble projections of future change under specified scenarios. Given the speed and magnitude of anthropogenic change in the marine environment and the consequent effects on food security, biodiversity, marine industries, and society, the time is ripe for similar comparisons among models of fisheries and marine ecosystems. Here, we describe the Fisheries and Marine Ecosystem Model Intercomparison Project protocol version 1.0 (Fish-MIP v1.0), part of the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP), which is a cross-sectoral network of climate impact modellers. Given the complexity of the marine ecosystem, this class of models has substantial heterogeneity of purpose, scope, theoretical underpinning, processes considered, parameterizations, resolution (grain size), and spatial extent. This heterogeneity reflects the lack of a unified understanding of the marine ecosystem and implies that the assemblage of all models is more likely to include a greater number of relevant processes than any single model. The current Fish-MIP protocol is designed to allow these heterogeneous models to be forced with common Earth System Model (ESM) Coupled Model Intercomparison Project Phase 5 (CMIP5) outputs under prescribed scenarios for historic (from the 1950s) and future (to 2100) time periods; it will be adapted to CMIP phase 6 (CMIP6) in future iterations. It also describes a standardized set of outputs for each participating Fish-MIP model to produce. This enables the broad characterization of differences between and uncertainties within models and projections when assessing climate and fisheries impacts on marine ecosystems and the services they provide. The systematic generation, collation, and comparison of results from Fish-MIP will inform an understanding of the range of plausible changes in marine ecosystems and improve our capacity to define and convey the strengths and weaknesses of model-based advice on future states of marine ecosystems and fisheries. Ultimately, Fish-MIP represents a step towards bringing together the marine ecosystem modelling community to produce consistent ensemble medium- and long-term projections of marine ecosystems.

A new theoretical approach to terrestrial ecosystem science based on multiscale observations and eco-evolutionary optimality principles

NASA Astrophysics Data System (ADS)

Prentice, Iain Colin; Wang, Han; Cornwell, William; Davis, Tyler; Dong, Ning; Evans, Bradley; Keenan, Trevor; Peng, Changhui; Stocker, Benjamin; Togashi, Henrique; Wright, Ian

2016-04-01

Ecosystem science focuses on biophysical interactions of organisms and their abiotic environment, and comprises vital aspects of Earth system function such as the controls of carbon, water and energy exchanges between ecosystems and the atmosphere. Global numerical models of these processes have proliferated, and have been incorporated as standard components of Earth system models whose ambitious goal is to predict the coupled behaviour of the oceans, atmosphere and land on time scales from minutes to millennia. Unfortunately, however, the performance of most current terrestrial ecosystem models is highly unsatisfactory. Models typically fail the most basic observational benchmarks, and diverge greatly from one another when called upon to predict the response of ecosystem function and composition to environmental changes beyond the narrow range for which they were developed. This situation seems to have arisen for two inter-related reasons. First, general principles underlying many basic terrestrial biogeochemical processes have been neither clearly formulated nor adequately tested. Second, extensive observational data sets that could be used to test process formulations have become available only quite recently, long postdating the emergence of the current modelling paradigm. But the situation has changed now and ecosystem science needs to change too, to reflect both recent theoretical advances and the vast increase in the availability of relevant data sets at scales from the leaf to the globe. This presentation will outline an emerging mathematical theory that links biophysical plant and ecosystem processes through testable hypotheses derived from the principle of optimization by natural selection. The development and testing of this theory has depended on the availability of extensive data sets on climate, leaf traits (including δ13C measurements), and ecosystem properties including green vegetation cover and land-atmosphere CO2 fluxes. Achievements to date include unified explanations for observed climate and elevation effects on leaf CO2 drawdown (ci:c¬a¬ ratio) and photosynthetic capacity (Vcmax), growth temperature effects on the Jmax:Vcmax ratio, the adaptive nature of acclimation to enhanced CO2 concentration, the controls of leaf versus sapwood respiration, the controls of leaf N content (Narea), the relative constancy of the light use efficiency of gross primary production, and the relative conservatism of leaf dark respiration with climate. These findings call into question many assumptions in supposed "state-of-the-art" terrestrial ecosystem models, and provide a foundation for next-generation global ecosystem models that will rest on a greatly strengthened theoretical and empirical basis.

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

DOE PAGES

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas; ...

2016-02-24

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Microbes as engines of ecosystem function: When does community structure enhance predictions of ecosystem processes?

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

Graham, Emily B.; Knelman, Joseph E.; Schindlbacher, Andreas

In this study, microorganisms are vital in mediating the earth’s biogeochemical cycles; yet, despite our rapidly increasing ability to explore complex environmental microbial communities, the relationship between microbial community structure and ecosystem processes remains poorly understood. Here, we address a fundamental and unanswered question in microbial ecology: ‘When do we need to understand microbial community structure to accurately predict function?’ We present a statistical analysis investigating the value of environmental data and microbial community structure independently and in combination for explaining rates of carbon and nitrogen cycling processes within 82 global datasets. Environmental variables were the strongest predictors of processmore » rates but left 44% of variation unexplained on average, suggesting the potential for microbial data to increase model accuracy. Although only 29% of our datasets were significantly improved by adding information on microbial community structure, we observed improvement in models of processes mediated by narrow phylogenetic guilds via functional gene data, and conversely, improvement in models of facultative microbial processes via community diversity metrics. Our results also suggest that microbial diversity can strengthen predictions of respiration rates beyond microbial biomass parameters, as 53% of models were improved by incorporating both sets of predictors compared to 35% by microbial biomass alone. Our analysis represents the first comprehensive analysis of research examining links between microbial community structure and ecosystem function. Taken together, our results indicate that a greater understanding of microbial communities informed by ecological principles may enhance our ability to predict ecosystem process rates relative to assessments based on environmental variables and microbial physiology.« less

Water ecosystem service function assessment based on eco-hydrological process in Luanhe Basin,China

NASA Astrophysics Data System (ADS)

Zhang, C.; Hao, C.; Qin, T.; Wang, G.; Weng, B.

2012-12-01

At present, ecological water are mainly occupied by a rapid development of social economic and population explosion, which seriously threat the ecological security and water security in watershed and regional scale. Due to the lack of a unified standard of measuring the benefit of water resource, social economic and ecosystem, the water allocation can't take place in social economic and ecosystem. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. The function which provided by water in terrestrial, aquatic and social economic system can be addressed through water ecosystem service function research, and it can guide the water allocation in water resource management. Throughout the researches of water ecosystem service, a clear identification of the connection of water ecosystem service function has not been established, and eco-economic approach can't meet the practical requirement of water allocation. Based on "nature-artificiality" dual water cycle theory and eco-hydrological process, this paper proposes a connection and indicator system of water ecosystem service function. In approach, this paper establishes an integrated assessment approach through prototype observation technology, numerical simulation, physical simulation and modern geographic information technology. The core content is to couple an eco-hydrological model, which involves the key processes of distributed hydrological model (WEP), ecological model (CLM-DGVM), in terms of eco-hydrological process. This paper systematically evaluates the eco-hydrological process and evolution of Luanhe Basin in terms of precipitation, ET, runoff, groundwater, ecosystem's scale, form and distribution. According to the results of eco-hydrological process, this paper assesses the direct and derived service function. The result indicates that the general service function of 2010 has minor increase than 2007, however the general function of two years are in common level; Compare with different region, the upstream, middle stream and downstream indicates "worse", "common" and "good" level respectively. The first three derived functions are leisure, offer products and industrial water use. In the end, this paper investigates the evolution of water ecosystem service function under rising temperatures and elevated CO2 concentration scenarios in Luanhe Basin through eco-hydrological model. The results elaborate that the water ecosystem service functions would decline when temperature rising, and warming to 1.5 degree is the mutation point of sharp drop; Increased CO2 concentration scenario will improve the direct service function in the whole Basin; under the overlying scenario, different region shows different results, the direct service function will increased in upstream and middle stream, direct service function will drop in downstream. A comprehensive analysis indicates that the rising temperature is the major driven of water ecosystem service function in Luanhe Basin.

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

PubMed

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

2016-05-01

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

Forest fragmentation and selective logging have inconsistent effects on multiple animal-mediated ecosystem processes in a tropical forest.

PubMed

Schleuning, Matthias; Farwig, Nina; Peters, Marcell K; Bergsdorf, Thomas; Bleher, Bärbel; Brandl, Roland; Dalitz, Helmut; Fischer, Georg; Freund, Wolfram; Gikungu, Mary W; Hagen, Melanie; Garcia, Francisco Hita; Kagezi, Godfrey H; Kaib, Manfred; Kraemer, Manfred; Lung, Tobias; Naumann, Clas M; Schaab, Gertrud; Templin, Mathias; Uster, Dana; Wägele, J Wolfgang; Böhning-Gaese, Katrin

2011-01-01

Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants.

Forest Fragmentation and Selective Logging Have Inconsistent Effects on Multiple Animal-Mediated Ecosystem Processes in a Tropical Forest

PubMed Central

Schleuning, Matthias; Farwig, Nina; Peters, Marcell K.; Bergsdorf, Thomas; Bleher, Bärbel; Brandl, Roland; Dalitz, Helmut; Fischer, Georg; Freund, Wolfram; Gikungu, Mary W.; Hagen, Melanie; Garcia, Francisco Hita; Kagezi, Godfrey H.; Kaib, Manfred; Kraemer, Manfred; Lung, Tobias; Schaab, Gertrud; Templin, Mathias; Uster, Dana; Wägele, J. Wolfgang; Böhning-Gaese, Katrin

2011-01-01

Forest fragmentation and selective logging are two main drivers of global environmental change and modify biodiversity and environmental conditions in many tropical forests. The consequences of these changes for the functioning of tropical forest ecosystems have rarely been explored in a comprehensive approach. In a Kenyan rainforest, we studied six animal-mediated ecosystem processes and recorded species richness and community composition of all animal taxa involved in these processes. We used linear models and a formal meta-analysis to test whether forest fragmentation and selective logging affected ecosystem processes and biodiversity and used structural equation models to disentangle direct from biodiversity-related indirect effects of human disturbance on multiple ecosystem processes. Fragmentation increased decomposition and reduced antbird predation, while selective logging consistently increased pollination, seed dispersal and army-ant raiding. Fragmentation modified species richness or community composition of five taxa, whereas selective logging did not affect any component of biodiversity. Changes in the abundance of functionally important species were related to lower predation by antbirds and higher decomposition rates in small forest fragments. The positive effects of selective logging on bee pollination, bird seed dispersal and army-ant raiding were direct, i.e. not related to changes in biodiversity, and were probably due to behavioural changes of these highly mobile animal taxa. We conclude that animal-mediated ecosystem processes respond in distinct ways to different types of human disturbance in Kakamega Forest. Our findings suggest that forest fragmentation affects ecosystem processes indirectly by changes in biodiversity, whereas selective logging influences processes directly by modifying local environmental conditions and resource distributions. The positive to neutral effects of selective logging on ecosystem processes show that the functionality of tropical forests can be maintained in moderately disturbed forest fragments. Conservation concepts for tropical forests should thus include not only remaining pristine forests but also functionally viable forest remnants. PMID:22114695

The Integrated Landscape Modeling partnership - Current status and future directions

USGS Publications Warehouse

Mushet, David M.; Scherff, Eric J.

2016-01-28

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

Hydrologically driven ecosystem processes determine the distribution and persistence of ecosystem-specialist predators under climate change.

PubMed

Carroll, Matthew J; Heinemeyer, Andreas; Pearce-Higgins, James W; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E; Thomas, Chris D

2015-07-31

Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56-81% declines in cranefly abundance and, hence, 15-51% reductions in the abundances of these birds by 2051-2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators.

Hydrologically driven ecosystem processes determine the distribution and persistence of ecosystem-specialist predators under climate change

PubMed Central

Carroll, Matthew J.; Heinemeyer, Andreas; Pearce-Higgins, James W.; Dennis, Peter; West, Chris; Holden, Joseph; Wallage, Zoe E.; Thomas, Chris D.

2015-01-01

Climate change has the capacity to alter physical and biological ecosystem processes, jeopardizing the survival of associated species. This is a particular concern in cool, wet northern peatlands that could experience warmer, drier conditions. Here we show that climate, ecosystem processes and food chains combine to influence the population performance of species in British blanket bogs. Our peatland process model accurately predicts water-table depth, which predicts abundance of craneflies (keystone invertebrates), which in turn predicts observed abundances and population persistence of three ecosystem-specialist bird species that feed on craneflies during the breeding season. Climate change projections suggest that falling water tables could cause 56–81% declines in cranefly abundance and, hence, 15–51% reductions in the abundances of these birds by 2051–2080. We conclude that physical (precipitation, temperature and topography), biophysical (evapotranspiration and desiccation of invertebrates) and ecological (food chains) processes combine to determine the distributions and survival of ecosystem-specialist predators. PMID:26227623

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...

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.

Are more complex physiological models of forest ecosystems better choices for plot and regional predictions?

Treesearch

Wenchi Jin; Hong S. He; Frank R. Thompson

2016-01-01

Process-based forest ecosystem models vary from simple physiological, complex physiological, to hybrid empirical-physiological models. Previous studies indicate that complex models provide the best prediction at plot scale with a temporal extent of less than 10 years, however, it is largely untested as to whether complex models outperform the other two types of models...

Secondary Students' Dynamic Modeling Processes: Analyzing, Reasoning About, Synthesizing, and Testing Models of Stream Ecosystems.

ERIC Educational Resources Information Center

Stratford, Steven J.; Krajeik, Joseph; Soloway, Elliot

This paper presents the results of a study of the cognitive strategies in which ninth-grade science students engaged as they used a learner-centered dynamic modeling tool (called Model-It) to make original models based upon stream ecosystem scenarios. The research questions were: (1) In what Cognitive Strategies for Modeling (analyzing, reasoning,…

Integrated Modeling for Watershed Ecosystem Services Assessment and Forecasting

EPA Science Inventory

Regional scale watershed management decisions must be informed by the science-based relationship between anthropogenic activities on the landscape and the change in ecosystem structure, function, and services that occur as a result. We applied process-based models that represent...

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...

The PEcAn Project: Accessible Tools for On-demand Ecosystem Modeling

NASA Astrophysics Data System (ADS)

Cowdery, E.; Kooper, R.; LeBauer, D.; Desai, A. R.; Mantooth, J.; Dietze, M.

2014-12-01

Ecosystem models play a critical role in understanding the terrestrial biosphere and forecasting changes in the carbon cycle, however current forecasts have considerable uncertainty. The amount of data being collected and produced is increasing on daily basis as we enter the "big data" era, but only a fraction of this data is being used to constrain models. Until we can improve the problems of model accessibility and model-data communication, none of these resources can be used to their full potential. The Predictive Ecosystem Analyzer (PEcAn) is an ecoinformatics toolbox and a set of workflows that wrap around an ecosystem model and manage the flow of information in and out of regional-scale TBMs. Here we present new modules developed in PEcAn to manage the processing of meteorological data, one of the primary driver dependencies for ecosystem models. The module downloads, reads, extracts, and converts meteorological observations to Unidata Climate Forecast (CF) NetCDF community standard, a convention used for most climate forecast and weather models. The module also automates the conversion from NetCDF to model specific formats, including basic merging, gap-filling, and downscaling procedures. PEcAn currently supports tower-based micrometeorological observations at Ameriflux and FluxNET sites, site-level CSV-formatted data, and regional and global reanalysis products such as the North American Regional Reanalysis and CRU-NCEP. The workflow is easily extensible to additional products and processing algorithms.These meteorological workflows have been coupled with the PEcAn web interface and now allow anyone to run multiple ecosystem models for any location on the Earth by simply clicking on an intuitive Google-map based interface. This will allow users to more readily compare models to observations at those sites, leading to better calibration and validation. Current work is extending these workflows to also process field, remotely-sensed, and historical observations of vegetation composition and structure. The processing of heterogeneous met and veg data within PEcAn is made possible using the Brown Dog cyberinfrastructure tools for unstructured data.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism

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

Graham, Emily B.; Crump, Alex R.; Resch, Charles T.

Community assembly processes govern shifts in species abundances in response to environmental change, yet our understanding of assembly remains largely decoupled from ecosystem function. Here, we test hypotheses regarding assembly and function across space and time using hyporheic microbial communities as a model system. We pair sampling of two habitat types through hydrologic fluctuation with null modeling and multivariate statistics. We demonstrate that dual selective pressures assimilate to generate compositional changes at distinct timescales among habitat types, resulting in contrasting associations of Betaproteobacteria and Thaumarchaeota with selection and with seasonal changes in aerobic metabolism. Our results culminate in a conceptualmore » model in which selection from contrasting environments regulates taxon abundance and ecosystem function through time, with increases in function when oscillating selection opposes stable selective pressures. Our model is applicable within both macrobial and microbial ecology and presents an avenue for assimilating community assembly processes into predictions of ecosystem function.« less

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.

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.

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.

Biomass is the main driver of changes in ecosystem process rates during tropical forest succession.

PubMed

Lohbeck, Madelon; Poorter, Lourens; Martínez-Ramos, Miguel; Bongers, Frans

2015-05-01

Over half of the world's forests are disturbed, and the rate at which ecosystem processes recover after disturbance is important for the services these forests can provide. We analyze the drivers' underlying changes in rates of key ecosystem processes (biomass productivity, litter productivity, actual litter decomposition, and potential litter decomposition) during secondary succession after shifting cultivation in wet tropical forest of Mexico. We test the importance of three alternative drivers of ecosystem processes: vegetation biomass (vegetation quantity hypothesis), community-weighted trait mean (mass ratio hypothesis), and functional diversity (niche complementarity hypothesis) using structural equation modeling. This allows us to infer the relative importance of different mechanisms underlying ecosystem process recovery. Ecosystem process rates changed during succession, and the strongest driver was aboveground biomass for each of the processes. Productivity of aboveground stem biomass and leaf litter as well as actual litter decomposition increased with initial standing vegetation biomass, whereas potential litter decomposition decreased with standing biomass. Additionally, biomass productivity was positively affected by community-weighted mean of specific leaf area, and potential decomposition was positively affected by functional divergence, and negatively by community-weighted mean of leaf dry matter content. Our empirical results show that functional diversity and community-weighted means are of secondary importance for explaining changes in ecosystem process rates during tropical forest succession. Instead, simply, the amount of vegetation in a site is the major driver of changes, perhaps because there is a steep biomass buildup during succession that overrides more subtle effects of community functional properties on ecosystem processes. We recommend future studies in the field of biodiversity and ecosystem functioning to separate the effects of vegetation quality (community-weighted mean trait values and functional diversity) from those of vegetation quantity (biomass) on ecosystem processes and services.

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

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

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

Testing a land model in ecosystem functional space via a comparison of observed and modeled ecosystem flux responses to precipitation regimes and associated stresses in a Central U.S. forest: Test Model in Ecosystem Functional Space

DOE PAGES

Gu, Lianhong; Pallardy, Stephen G.; Yang, Bai; ...

2016-07-14

Testing complex land surface models has often proceeded by asking the question: does the model prediction agree with the observation? This approach has yet led to high-performance terrestrial models that meet the challenges of climate and ecological studies. Here we test the Community Land Model (CLM) by asking the question: does the model behave like an ecosystem? We pursue its answer by testing CLM in the ecosystem functional space (EFS) at the Missouri Ozark AmeriFlux (MOFLUX) forest site in the Central U.S., focusing on carbon and water flux responses to precipitation regimes and associated stresses. In the observed EFS, precipitationmore » regimes and associated water and heat stresses controlled seasonal and interannual variations of net ecosystem exchange (NEE) of CO 2 and evapotranspiration in this deciduous forest ecosystem. Such controls were exerted more strongly by precipitation variability than by the total precipitation amount per se. A few simply constructed climate variability indices captured these controls, suggesting a high degree of potential predictability. While the interannual fluctuation in NEE was large, a net carbon sink was maintained even during an extreme drought year. Although CLM predicted seasonal and interanual variations in evapotranspiration reasonably well, its predictions of net carbon uptake were too small across the observed range of climate variability. Also, the model systematically underestimated the sensitivities of NEE and evapotranspiration to climate variability and overestimated the coupling strength between carbon and water fluxes. Its suspected that the modeled and observed trajectories of ecosystem fluxes did not overlap in the EFS and the model did not behave like the ecosystem it attempted to simulate. A definitive conclusion will require comprehensive parameter and structural sensitivity tests in a rigorous mathematical framework. We also suggest that future model improvements should focus on better representation and parameterization of process responses to environmental stresses and on more complete and robust representations of carbon-specific processes so that adequate responses to climate variability and a proper degree of coupling between carbon and water exchanges are captured.« less

From Bacteria to Whales: Using Functional Size Spectra to Model Marine Ecosystems.

PubMed

Blanchard, Julia L; Heneghan, Ryan F; Everett, Jason D; Trebilco, Rowan; Richardson, Anthony J

2017-03-01

Size-based ecosystem modeling is emerging as a powerful way to assess ecosystem-level impacts of human- and environment-driven changes from individual-level processes. These models have evolved as mechanistic explanations for observed regular patterns of abundance across the marine size spectrum hypothesized to hold from bacteria to whales. Fifty years since the first size spectrum measurements, we ask how far have we come? Although recent modeling studies capture an impressive range of sizes, complexity, and real-world applications, ecosystem coverage is still only partial. We describe how this can be overcome by unifying functional traits with size spectra (which we call functional size spectra) and highlight the key knowledge gaps that need to be filled to model ecosystems from bacteria to whales. Copyright © 2017 Elsevier Ltd. All rights reserved.

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,...

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.

Introduction to a special section on ecohydrology of semiarid environments: Confronting mathematical models with ecosystem complexity

NASA Astrophysics Data System (ADS)

Svoray, Tal; Assouline, Shmuel; Katul, Gabriel

2015-11-01

Current literature provides large number of publications about ecohydrological processes and their effect on the biota in drylands. Given the limited laboratory and field experiments in such systems, many of these publications are based on mathematical models of varying complexity. The underlying implicit assumption is that the data set used to evaluate these models covers the parameter space of conditions that characterize drylands and that the models represent the actual processes with acceptable certainty. However, a question raised is to what extent these mathematical models are valid when confronted with observed ecosystem complexity? This Introduction reviews the 16 papers that comprise the Special Section on Eco-hydrology of Semiarid Environments: Confronting Mathematical Models with Ecosystem Complexity. The subjects studied in these papers include rainfall regime, infiltration and preferential flow, evaporation and evapotranspiration, annual net primary production, dispersal and invasion, and vegetation greening. The findings in the papers published in this Special Section show that innovative mathematical modeling approaches can represent actual field measurements. Hence, there are strong grounds for suggesting that mathematical models can contribute to greater understanding of ecosystem complexity through characterization of space-time dynamics of biomass and water storage as well as their multiscale interactions. However, the generality of the models and their low-dimensional representation of many processes may also be a "curse" that results in failures when particulars of an ecosystem are required. It is envisaged that the search for a unifying "general" model, while seductive, may remain elusive in the foreseeable future. It is for this reason that improving the merger between experiments and models of various degrees of complexity continues to shape the future research agenda.

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.

Dominance, biomass and extinction resistance determine the consequences of biodiversity loss for multiple coastal ecosystem processes.

PubMed

Davies, Thomas W; Jenkins, Stuart R; Kingham, Rachel; Kenworthy, Joseph; Hawkins, Stephen J; Hiddink, Jan G

2011-01-01

Key ecosystem processes such as carbon and nutrient cycling could be deteriorating as a result of biodiversity loss. However, currently we lack the ability to predict the consequences of realistic species loss on ecosystem processes. The aim of this study was to test whether species contributions to community biomass can be used as surrogate measures of their contribution to ecosystem processes. These were gross community productivity in a salt marsh plant assemblage and an intertidal macroalgae assemblage; community clearance of microalgae in sessile suspension feeding invertebrate assemblage; and nutrient uptake in an intertidal macroalgae assemblage. We conducted a series of biodiversity manipulations that represented realistic species extinction sequences in each of the three contrasting assemblages. Species were removed in a subtractive fashion so that biomass was allowed to vary with each species removal, and key ecosystem processes were measured at each stage of community disassembly. The functional contribution of species was directly proportional to their contribution to community biomass in a 1:1 ratio, a relationship that was consistent across three contrasting marine ecosystems and three ecosystem processes. This suggests that the biomass contributed by a species to an assemblage can be used to approximately predict the proportional decline in an ecosystem process when that species is lost. Such predictions represent "worst case scenarios" because, over time, extinction resilient species can offset the loss of biomass associated with the extinction of competitors. We also modelled a "best case scenario" that accounts for compensatory responses by the extant species with the highest per capita contribution to ecosystem processes. These worst and best case scenarios could be used to predict the minimum and maximum species required to sustain threshold values of ecosystem processes in the future.

Dominance, Biomass and Extinction Resistance Determine the Consequences of Biodiversity Loss for Multiple Coastal Ecosystem Processes

PubMed Central

Davies, Thomas W.; Jenkins, Stuart R.; Kingham, Rachel; Kenworthy, Joseph; Hawkins, Stephen J.; Hiddink, Jan G.

2011-01-01

Key ecosystem processes such as carbon and nutrient cycling could be deteriorating as a result of biodiversity loss. However, currently we lack the ability to predict the consequences of realistic species loss on ecosystem processes. The aim of this study was to test whether species contributions to community biomass can be used as surrogate measures of their contribution to ecosystem processes. These were gross community productivity in a salt marsh plant assemblage and an intertidal macroalgae assemblage; community clearance of microalgae in sessile suspension feeding invertebrate assemblage; and nutrient uptake in an intertidal macroalgae assemblage. We conducted a series of biodiversity manipulations that represented realistic species extinction sequences in each of the three contrasting assemblages. Species were removed in a subtractive fashion so that biomass was allowed to vary with each species removal, and key ecosystem processes were measured at each stage of community disassembly. The functional contribution of species was directly proportional to their contribution to community biomass in a 1∶1 ratio, a relationship that was consistent across three contrasting marine ecosystems and three ecosystem processes. This suggests that the biomass contributed by a species to an assemblage can be used to approximately predict the proportional decline in an ecosystem process when that species is lost. Such predictions represent “worst case scenarios” because, over time, extinction resilient species can offset the loss of biomass associated with the extinction of competitors. We also modelled a “best case scenario” that accounts for compensatory responses by the extant species with the highest per capita contribution to ecosystem processes. These worst and best case scenarios could be used to predict the minimum and maximum species required to sustain threshold values of ecosystem processes in the future. PMID:22163297

Integration of Process Models and Remote Sensing for Estimating Productivity, Soil Moisture, and Energy Fluxes in a Tallgrass Prairie Ecosystem

EPA Science Inventory

We describe a research program aimed at integrating remotely sensed data with an ecosystem model (VELMA) and a soil-vegetation-atmosphere transfer (SVAT) model (SEBS) for generating spatially explicit, regional scale estimates of productivity (biomass) and energy\\mass exchanges i...

Transpiration and Leaf Temperature. Physical Processes in Terrestrial and Aquatic Ecosystems, Transport Processes.

ERIC Educational Resources Information Center

Gates, David M.

These materials were designed to be used by life science students for instruction in the application of physical theory to ecosystem operation. Most modules contain computer programs which are built around a particular application of a physical process. This report introduces two models of the thermal energy budget of a leaf. Typical values for…

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

EPA Science Inventory

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change enco...

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.

Developing a Modeling Framework for Ecosystem Forecasting: The Lake Michigan Pilot

EPA Science Inventory

Recent multi-party efforts to coordinate modeling activities that support ecosystem management decision-making in the Great Lakes have resulted in the recommendation to convene an interagency working group that will develop a pilot approach for Lake Michigan. The process will br...

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.

Space-time modeling in EPA's Ecosystem Services Research Program

EPA Science Inventory

The US EPA is conducting a long-term research program on the effects of human actions on ecosystem services. Ecosystem services are defined in this program as “the products of ecological functions or processes that directly or indirectly contribute to human well-being.” Modelin...

Using the concept of Shannon's Entropy to evaluate impacts of climate extremes on interannual variability in ecosystem CO2 fluxes

NASA Astrophysics Data System (ADS)

Ma, S.; Baldocchi, D. D.

2016-12-01

Although interannual variability in ecosystem CO2 fluxes have been observed in the field and described with empirical or process-based models, we still lack tools for evaluating and comparing impacts of climate extremes or unusual biogeophysical events on the variability. We examined a 15-year-long dataset of net ecosystem exchange of CO2 (NEE) measured at a woody savanna and a grassland site in California from 2000 to 2015. We proposed a conceptual framework to quantify season contributions by computing relatively contributions of each season to annual anomalies of gross ecosystem productivity (GPP) and ecosystem respiration (Reco). According to the framework, we calculated the Shannon's Entropy for each year. The values of Shannon Entropy were higher in the year that variations in GPP and Reco were beyond predictions of empirical models established for the study site. We specifically examined the outliers compared to model predictions and concluded that the outliers were related to occurrences of unexpected biogeophysical events in those years. This study offers a new application of Shannon's Entropy in understanding complicated biophysical and ecological processes involved in ecosystem carbon cycling.

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

Sources of Uncertainty in Predicting Land Surface Fluxes Using Diverse Data and Models

NASA Technical Reports Server (NTRS)

Dungan, Jennifer L.; Wang, Weile; Michaelis, Andrew; Votava, Petr; Nemani, Ramakrishma

2010-01-01

In the domain of predicting land surface fluxes, models are used to bring data from large observation networks and satellite remote sensing together to make predictions about present and future states of the Earth. Characterizing the uncertainty about such predictions is a complex process and one that is not yet fully understood. Uncertainty exists about initialization, measurement and interpolation of input variables; model parameters; model structure; and mixed spatial and temporal supports. Multiple models or structures often exist to describe the same processes. Uncertainty about structure is currently addressed by running an ensemble of different models and examining the distribution of model outputs. To illustrate structural uncertainty, a multi-model ensemble experiment we have been conducting using the Terrestrial Observation and Prediction System (TOPS) will be discussed. TOPS uses public versions of process-based ecosystem models that use satellite-derived inputs along with surface climate data and land surface characterization to produce predictions of ecosystem fluxes including gross and net primary production and net ecosystem exchange. Using the TOPS framework, we have explored the uncertainty arising from the application of models with different assumptions, structures, parameters, and variable definitions. With a small number of models, this only begins to capture the range of possible spatial fields of ecosystem fluxes. Few attempts have been made to systematically address the components of uncertainty in such a framework. We discuss the characterization of uncertainty for this approach including both quantifiable and poorly known aspects.

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.

Process-based upscaling of surface-atmosphere exchange

NASA Astrophysics Data System (ADS)

Keenan, T. F.; Prentice, I. C.; Canadell, J.; Williams, C. A.; Wang, H.; Raupach, M. R.; Collatz, G. J.; Davis, T.; Stocker, B.; Evans, B. J.

2015-12-01

Empirical upscaling techniques such as machine learning and data-mining have proven invaluable tools for the global scaling of disparate observations of surface-atmosphere exchange, but are not based on a theoretical understanding of the key processes involved. This makes spatial and temporal extrapolation outside of the training domain difficult at best. There is therefore a clear need for the incorporation of knowledge of ecosystem function, in combination with the strength of data mining. Here, we present such an approach. We describe a novel diagnostic process-based model of global photosynthesis and ecosystem respiration, which is directly informed by a variety of global datasets relevant to ecosystem state and function. We use the model framework to estimate global carbon cycling both spatially and temporally, with a specific focus on the mechanisms responsible for long-term change. Our results show the importance of incorporating process knowledge into upscaling approaches, and highlight the effect of key processes on the terrestrial carbon cycle.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

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.

Modelling C3 photosynthesis from the chloroplast to the ecosystem

USDA-ARS?s Scientific Manuscript database

Globally, photosynthesis accounts for the largest flux of CO2 from the atmosphere into ecosystems and is the driving process for terrestrial ecosystem function. The importance of accurate predictions of photosynthesis over a range of plant growth conditions led to the development of a C3 photosynthe...

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

Treesearch

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

2012-01-01

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

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...

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.

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).

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

PubMed

Eduardo, Anderson A

2016-09-07

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

Ecosystem Services and Climate Change Considerations for ...

EPA Pesticide Factsheets

Freshwater habitats provide fishable, swimmable and drinkable resources and are a nexus of geophysical and biological processes. These processes in turn influence the persistence and sustainability of populations, communities and ecosystems. Climate change and landuse change encompass numerous stressors of potential exposure, including the introduction of toxic contaminants, invasive species, and disease in addition to physical drivers such as temperature and hydrologic regime. A systems approach that includes the scientific and technologic basis of assessing the health of ecosystems is needed to effectively protect human health and the environment. The Integrated Environmental Modeling Framework “iemWatersheds” has been developed as a consistent and coherent means of forecasting the cumulative impact of co-occurring stressors. The Framework consists of three facilitating technologies: Data for Environmental Modeling (D4EM) that automates the collection and standardization of input data; the Framework for Risk Assessment of Multimedia Environmental Systems (FRAMES) that manages the flow of information between linked models; and the Supercomputer for Model Uncertainty and Sensitivity Evaluation (SuperMUSE) that provides post-processing and analysis of model outputs, including uncertainty and sensitivity analysis. Five models are linked within the Framework to provide multimedia simulation capabilities for hydrology and water quality processes: the Soil Water

Climate Change and Socio-Hydrological Dynamics: Adaptations and Feedbacks

NASA Astrophysics Data System (ADS)

Woyessa, Yali E.; Welderufael, Worku A.

2012-10-01

A functioning ecological system results in ecosystem goods and services which are of direct value to human beings. Ecosystem services are the conditions and processes which sustain and fulfil human life, and maintain biodiversity and the production of ecosystem goods. However, 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 threatens to undo many of the development efforts being made to reach the targets set for the Millennium Development Goals. Understanding the provision of ecosystem services and how they change 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 landuse changes. Recently, the focus has shifted away from using mathematically oriented models to agent-based modeling (ABM) approach to simulate land use scenarios. The agent-based perspective, with regard to land-use cover change, is centered on the general nature and rules of land-use decision making by individuals. A conceptual framework is developed to investigate the possibility of incorporating the human dimension of land use decision and climate change model into a hydrological model in order to assess the impact of future land use scenario and climate change on the ecological system in general and water resources in particular.

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

PubMed

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

2012-10-01

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

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

USGS Publications Warehouse

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

2012-01-01

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

Including hydrological self-regulating processes in peatland models: Effects on peatmoss drought projections.

PubMed

Nijp, Jelmer J; Metselaar, Klaas; Limpens, Juul; Teutschbein, Claudia; Peichl, Matthias; Nilsson, Mats B; Berendse, Frank; van der Zee, Sjoerd E A T M

2017-02-15

The water content of the topsoil is one of the key factors controlling biogeochemical processes, greenhouse gas emissions and biosphere - atmosphere interactions in many ecosystems, particularly in northern peatlands. In these wetland ecosystems, the water content of the photosynthetic active peatmoss layer is crucial for ecosystem functioning and carbon sequestration, and is sensitive to future shifts in rainfall and drought characteristics. Current peatland models differ in the degree in which hydrological feedbacks are included, but how this affects peatmoss drought projections is unknown. The aim of this paper was to systematically test whether the level of hydrological detail in models could bias projections of water content and drought stress for peatmoss in northern peatlands using downscaled projections for rainfall and potential evapotranspiration in the current (1991-2020) and future climate (2061-2090). We considered four model variants that either include or exclude moss (rain)water storage and peat volume change, as these are two central processes in the hydrological self-regulation of peatmoss carpets. Model performance was validated using field data of a peatland in northern Sweden. Including moss water storage as well as peat volume change resulted in a significant improvement of model performance, despite the extra parameters added. The best performance was achieved if both processes were included. Including moss water storage and peat volume change consistently reduced projected peatmoss drought frequency with >50%, relative to the model excluding both processes. Projected peatmoss drought frequency in the growing season was 17% smaller under future climate than current climate, but was unaffected by including the hydrological self-regulating processes. Our results suggest that ignoring these two fine-scale processes important in hydrological self-regulation of northern peatlands will have large consequences for projected climate change impact on ecosystem processes related to topsoil water content, such as greenhouse gas emissions. Copyright © 2016 Elsevier B.V. All rights reserved.

Scientific Foundations for an IUCN Red List of Ecosystems

PubMed Central

Keith, David A.; Rodríguez, Jon Paul; Rodríguez-Clark, Kathryn M.; Nicholson, Emily; Aapala, Kaisu; Alonso, Alfonso; Asmussen, Marianne; Bachman, Steven; Basset, Alberto; Barrow, Edmund G.; Benson, John S.; Bishop, Melanie J.; Bonifacio, Ronald; Brooks, Thomas M.; Burgman, Mark A.; Comer, Patrick; Comín, Francisco A.; Essl, Franz; Faber-Langendoen, Don; Fairweather, Peter G.; Holdaway, Robert J.; Jennings, Michael; Kingsford, Richard T.; Lester, Rebecca E.; Nally, Ralph Mac; McCarthy, Michael A.; Moat, Justin; Oliveira-Miranda, María A.; Pisanu, Phil; Poulin, Brigitte; Regan, Tracey J.; Riecken, Uwe; Spalding, Mark D.; Zambrano-Martínez, Sergio

2013-01-01

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world’s ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity PMID:23667454

Scientific foundations for an IUCN Red List of ecosystems.

PubMed

Keith, David A; Rodríguez, Jon Paul; Rodríguez-Clark, Kathryn M; Nicholson, Emily; Aapala, Kaisu; Alonso, Alfonso; Asmussen, Marianne; Bachman, Steven; Basset, Alberto; Barrow, Edmund G; Benson, John S; Bishop, Melanie J; Bonifacio, Ronald; Brooks, Thomas M; Burgman, Mark A; Comer, Patrick; Comín, Francisco A; Essl, Franz; Faber-Langendoen, Don; Fairweather, Peter G; Holdaway, Robert J; Jennings, Michael; Kingsford, Richard T; Lester, Rebecca E; Mac Nally, Ralph; McCarthy, Michael A; Moat, Justin; Oliveira-Miranda, María A; Pisanu, Phil; Poulin, Brigitte; Regan, Tracey J; Riecken, Uwe; Spalding, Mark D; Zambrano-Martínez, Sergio

2013-01-01

An understanding of risks to biodiversity is needed for planning action to slow current rates of decline and secure ecosystem services for future human use. Although the IUCN Red List criteria provide an effective assessment protocol for species, a standard global assessment of risks to higher levels of biodiversity is currently limited. In 2008, IUCN initiated development of risk assessment criteria to support a global Red List of ecosystems. We present a new conceptual model for ecosystem risk assessment founded on a synthesis of relevant ecological theories. To support the model, we review key elements of ecosystem definition and introduce the concept of ecosystem collapse, an analogue of species extinction. The model identifies four distributional and functional symptoms of ecosystem risk as a basis for assessment criteria: A) rates of decline in ecosystem distribution; B) restricted distributions with continuing declines or threats; C) rates of environmental (abiotic) degradation; and D) rates of disruption to biotic processes. A fifth criterion, E) quantitative estimates of the risk of ecosystem collapse, enables integrated assessment of multiple processes and provides a conceptual anchor for the other criteria. We present the theoretical rationale for the construction and interpretation of each criterion. The assessment protocol and threat categories mirror those of the IUCN Red List of species. A trial of the protocol on terrestrial, subterranean, freshwater and marine ecosystems from around the world shows that its concepts are workable and its outcomes are robust, that required data are available, and that results are consistent with assessments carried out by local experts and authorities. The new protocol provides a consistent, practical and theoretically grounded framework for establishing a systematic Red List of the world's ecosystems. This will complement the Red List of species and strengthen global capacity to report on and monitor the status of biodiversity.

A generic biogeochemical module for earth system models

NASA Astrophysics Data System (ADS)

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

2013-06-01

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

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.

Inferring Aggregated Functional Traits from Metagenomic Data Using Constrained Non-negative Matrix Factorization: Application to Fiber Degradation in the Human Gut Microbiota.

PubMed

Raguideau, Sébastien; Plancade, Sandra; Pons, Nicolas; Leclerc, Marion; Laroche, Béatrice

2016-12-01

Whole Genome Shotgun (WGS) metagenomics is increasingly used to study the structure and functions of complex microbial ecosystems, both from the taxonomic and functional point of view. Gene inventories of otherwise uncultured microbial communities make the direct functional profiling of microbial communities possible. The concept of community aggregated trait has been adapted from environmental and plant functional ecology to the framework of microbial ecology. Community aggregated traits are quantified from WGS data by computing the abundance of relevant marker genes. They can be used to study key processes at the ecosystem level and correlate environmental factors and ecosystem functions. In this paper we propose a novel model based approach to infer combinations of aggregated traits characterizing specific ecosystemic metabolic processes. We formulate a model of these Combined Aggregated Functional Traits (CAFTs) accounting for a hierarchical structure of genes, which are associated on microbial genomes, further linked at the ecosystem level by complex co-occurrences or interactions. The model is completed with constraints specifically designed to exploit available genomic information, in order to favor biologically relevant CAFTs. The CAFTs structure, as well as their intensity in the ecosystem, is obtained by solving a constrained Non-negative Matrix Factorization (NMF) problem. We developed a multicriteria selection procedure for the number of CAFTs. We illustrated our method on the modelling of ecosystemic functional traits of fiber degradation by the human gut microbiota. We used 1408 samples of gene abundances from several high-throughput sequencing projects and found that four CAFTs only were needed to represent the fiber degradation potential. This data reduction highlighted biologically consistent functional patterns while providing a high quality preservation of the original data. Our method is generic and can be applied to other metabolic processes in the gut or in other ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Asymmetric warming significantly affects net primary production, but not ecosystem carbon balances of forest and grassland ecosystems in northern China

NASA Astrophysics Data System (ADS)

Su, Hongxin; Feng, Jinchao; Axmacher, Jan C.; Sang, Weiguo

2015-03-01

We combine the process-based ecosystem model (Biome-BGC) with climate change-scenarios based on both RegCM3 model outputs and historic observed trends to quantify differential effects of symmetric and asymmetric warming on ecosystem net primary productivity (NPP), heterotrophic respiration (Rh) and net ecosystem productivity (NEP) of six ecosystem types representing different climatic zones of northern China. Analysis of covariance shows that NPP is significant greater at most ecosystems under the various environmental change scenarios once temperature asymmetries are taken into consideration. However, these differences do not lead to significant differences in NEP, which indicates that asymmetry in climate change does not result in significant alterations of the overall carbon balance in the dominating forest or grassland ecosystems. Overall, NPP, Rh and NEP are regulated by highly interrelated effects of increases in temperature and atmospheric CO2 concentrations and precipitation changes, while the magnitude of these effects strongly varies across the six sites. Further studies underpinned by suitable experiments are nonetheless required to further improve the performance of ecosystem models and confirm the validity of these model predictions. This is crucial for a sound understanding of the mechanisms controlling the variability in asymmetric warming effects on ecosystem structure and functioning.

Asymmetric warming significantly affects net primary production, but not ecosystem carbon balances of forest and grassland ecosystems in northern China.

PubMed

Su, Hongxin; Feng, Jinchao; Axmacher, Jan C; Sang, Weiguo

2015-03-13

We combine the process-based ecosystem model (Biome-BGC) with climate change-scenarios based on both RegCM3 model outputs and historic observed trends to quantify differential effects of symmetric and asymmetric warming on ecosystem net primary productivity (NPP), heterotrophic respiration (Rh) and net ecosystem productivity (NEP) of six ecosystem types representing different climatic zones of northern China. Analysis of covariance shows that NPP is significant greater at most ecosystems under the various environmental change scenarios once temperature asymmetries are taken into consideration. However, these differences do not lead to significant differences in NEP, which indicates that asymmetry in climate change does not result in significant alterations of the overall carbon balance in the dominating forest or grassland ecosystems. Overall, NPP, Rh and NEP are regulated by highly interrelated effects of increases in temperature and atmospheric CO2 concentrations and precipitation changes, while the magnitude of these effects strongly varies across the six sites. Further studies underpinned by suitable experiments are nonetheless required to further improve the performance of ecosystem models and confirm the validity of these model predictions. This is crucial for a sound understanding of the mechanisms controlling the variability in asymmetric warming effects on ecosystem structure and functioning.

Asymmetric warming significantly affects net primary production, but not ecosystem carbon balances of forest and grassland ecosystems in northern China

PubMed Central

Su, Hongxin; Feng, Jinchao; Axmacher, Jan C.; Sang, Weiguo

2015-01-01

We combine the process-based ecosystem model (Biome-BGC) with climate change-scenarios based on both RegCM3 model outputs and historic observed trends to quantify differential effects of symmetric and asymmetric warming on ecosystem net primary productivity (NPP), heterotrophic respiration (Rh) and net ecosystem productivity (NEP) of six ecosystem types representing different climatic zones of northern China. Analysis of covariance shows that NPP is significant greater at most ecosystems under the various environmental change scenarios once temperature asymmetries are taken into consideration. However, these differences do not lead to significant differences in NEP, which indicates that asymmetry in climate change does not result in significant alterations of the overall carbon balance in the dominating forest or grassland ecosystems. Overall, NPP, Rh and NEP are regulated by highly interrelated effects of increases in temperature and atmospheric CO2 concentrations and precipitation changes, while the magnitude of these effects strongly varies across the six sites. Further studies underpinned by suitable experiments are nonetheless required to further improve the performance of ecosystem models and confirm the validity of these model predictions. This is crucial for a sound understanding of the mechanisms controlling the variability in asymmetric warming effects on ecosystem structure and functioning. PMID:25766381

Linking big models to big data: efficient ecosystem model calibration through Bayesian model emulation

NASA Astrophysics Data System (ADS)

Fer, I.; Kelly, R.; Andrews, T.; Dietze, M.; Richardson, A. D.

2016-12-01

Our ability to forecast ecosystems is limited by how well we parameterize ecosystem models. Direct measurements for all model parameters are not always possible and inverse estimation of these parameters through Bayesian methods is computationally costly. A solution to computational challenges of Bayesian calibration is to approximate the posterior probability surface using a Gaussian Process that emulates the complex process-based model. Here we report the integration of this method within an ecoinformatics toolbox, Predictive Ecosystem Analyzer (PEcAn), and its application with two ecosystem models: SIPNET and ED2.1. SIPNET is a simple model, allowing application of MCMC methods both to the model itself and to its emulator. We used both approaches to assimilate flux (CO2 and latent heat), soil respiration, and soil carbon data from Bartlett Experimental Forest. This comparison showed that emulator is reliable in terms of convergence to the posterior distribution. A 10000-iteration MCMC analysis with SIPNET itself required more than two orders of magnitude greater computation time than an MCMC run of same length with its emulator. This difference would be greater for a more computationally demanding model. Validation of the emulator-calibrated SIPNET against both the assimilated data and out-of-sample data showed improved fit and reduced uncertainty around model predictions. We next applied the validated emulator method to the ED2, whose complexity precludes standard Bayesian data assimilation. We used the ED2 emulator to assimilate demographic data from a network of inventory plots. For validation of the calibrated ED2, we compared the model to results from Empirical Succession Mapping (ESM), a novel synthesis of successional patterns in Forest Inventory and Analysis data. Our results revealed that while the pre-assimilation ED2 formulation cannot capture the emergent demographic patterns from ESM analysis, constrained model parameters controlling demographic processes increased their agreement considerably.

Unraveling the intricate dynamics of planktonic Arctic marine food webs. A sensitivity analysis of a well-documented food web model

NASA Astrophysics Data System (ADS)

Saint-Béat, Blanche; Maps, Frédéric; Babin, Marcel

2018-01-01

The extreme and variable environment shapes the functioning of Arctic ecosystems and the life cycles of its species. This delicate balance is now threatened by the unprecedented pace and magnitude of global climate change and anthropogenic pressure. Understanding the long-term consequences of these changes remains an elusive, yet pressing, goal. Our work was specifically aimed at identifying which biological processes impact Arctic planktonic ecosystem functioning, and how. Ecological Network Analysis (ENA) indices reveal emergent ecosystem properties that are not accessible through simple in situ observation. These indices are based on the architecture of carbon flows within food webs. But, despite the recent increase in in situ measurements from Arctic seas, many flow values remain unknown. Linear inverse modeling (LIM) allows missing flow values to be estimated from existing flow observations and, subsequent reconstruction of ecosystem food webs. Through a sensitivity analysis on a LIM model of the Amundsen Gulf in the Canadian Arctic, we were able to determine which processes affected the emergent properties of the planktonic ecosystem. The analysis highlighted the importance of an accurate knowledge of the various processes controlling bacterial production (e.g. bacterial growth efficiency and viral lysis). More importantly, a change in the fate of the microzooplankton within the food web can be monitored through the trophic level of mesozooplankton. It can be used as a "canary in the coal mine" signal, a forewarner of larger ecosystem change.

Ecosystem processes at the watershed scale: mapping and modeling ecohydrological controls

Treesearch

Lawrence E. Band; T. Hwang; T.C. Hales; James Vose; Chelcy Ford

2012-01-01

Mountain watersheds are sources of a set of valuable ecosystem services as well as potential hazards. The former include high quality freshwater, carbon sequestration, nutrient retention, and biodiversity, whereas the latter include flash floods, landslides and forest fires. Each of these ecosystem services and hazards represents different elements of the integrated...

Remote sensing of the energetic status of plants and ecosystems: optical and odorous signals

NASA Astrophysics Data System (ADS)

Penuelas, J.; Bartrons, M.; Llusia, J.; Filella, I.

2016-12-01

The optical and odorous signals emitted by plants and ecosystems present consistent relationships. They offer promising prospects for continuous local and global monitoring of the energetic status of plants and ecosystems, and therefore of their processing of energy and matter. We will discuss how the energetic status of plants (and ecosystems) resulting from the balance between the supply and demand of reducing power can be assessed biochemically, by the cellular NADPH/NADP ratio, optically, by using the photochemical reflectance index and sun-induced fluorescence as indicators of the dissipation of excess energy and associated physiological processes, and "odorously", by the emission of volatile organic compounds such as isoprenoids, as indicators of an excess of reducing equivalents and also of enhancement of protective converging physiological processes. These signals thus provide information on the energetic status, associated health status, and the functioning of plants and ecosystems. We will present the links among the three signals and will especially discuss the possibility of remotely sense the optical signals linked to carbon uptake and VOCs exchange by plants and ecosystems. These signals and their integration may have multiple applications for environmental and agricultural monitoring, for example, by extending the spatial coverage of carbon-flux and VOCs emission observations to most places and times, and/or for improving the process-based modeling of carbon fixation and isoprenoid emissions from terrestrial vegetation on plant, ecosystemic and global scales. Considerable challenges remain for a wide-scale and routine implementation of these biochemical, optical, and odorous signals for ecosystemic and/or agronomic monitoring and modeling, but its interest for making further steps forward in global ecology, agricultural applications, global carbon cycle, atmospheric science, and earth science warrants further research efforts in this line.

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

Treesearch

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

2005-01-01

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

A general equilibrium model of ecosystem services in a river basin

Treesearch

Travis Warziniack

2014-01-01

This study builds a general equilibrium model of ecosystem services, with sectors of the economy competing for use of the environment. The model recognizes that production processes in the real world require a combination of natural and human inputs, and understanding the value of these inputs and their competing uses is necessary when considering policies of resource...

Quantifying Process-Based Mitigation Strategies in Historical Context: Separating Multiple Cumulative Effects on River Meander Migration

PubMed Central

Fremier, Alexander K.; Girvetz, Evan H.; Greco, Steven E.; Larsen, Eric W.

2014-01-01

Environmental legislation in the US (i.e. NEPA) requires defining baseline conditions on current rather than historical ecosystem conditions. For ecosystems with long histories of multiple environmental impacts, this baseline method can subsequently lead to a significantly altered environment; this has been termed a ‘sliding baseline’. In river systems, cumulative effects caused by flow regulation, channel revetment and riparian vegetation removal significantly impact floodplain ecosystems by altering channel dynamics and precluding subsequent ecosystem processes, such as primary succession. To quantify these impacts on floodplain development processes, we used a model of river channel meander migration to illustrate the degree to which flow regulation and riprap impact migration rates, independently and synergistically, on the Sacramento River in California, USA. From pre-dam conditions, the cumulative effect of flow regulation alone on channel migration is a reduction by 38%, and 42–44% with four proposed water diversion project scenarios. In terms of depositional area, the proposed water project would reduce channel migration 51–71 ha in 130 years without current riprap in place, and 17–25 ha with riprap. Our results illustrate the utility of a modeling approach for quantifying cumulative impacts. Model-based quantification of environmental impacts allow scientists to separate cumulative and synergistic effects to analytically define mitigation measures. Additionally, by selecting an ecosystem process that is affected by multiple impacts, it is possible to consider process-based mitigation scenarios, such as the removal of riprap, to allow meander migration and create new floodplains and allow for riparian vegetation recruitment. PMID:24964145

Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem

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

Laufkotter, Charlotte; Vogt, Meike; Gruber, Nicolas

Here, accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralisation of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projectionsmore » in EP over the 21st century, generated by four marine ecosystem models under the high emission scenario Representative Concentration Pathways (RCP) 8.5 of the Intergovernmental Panel on Climate Change (IPCC), and determine the processes driving these changes. The models simulate small to modest decreases in global EP between -1 and -12%. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralisation is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralisation or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralisation. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94% in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.« less

Projected decreases in future marine export production: the role of the carbon flux through the upper ocean ecosystem

DOE PAGES

Laufkotter, Charlotte; Vogt, Meike; Gruber, Nicolas; ...

2016-07-14

Here, accurate projections of marine particle export production (EP) are crucial for predicting the response of the marine carbon cycle to climate change, yet models show a wide range in both global EP and their responses to climate change. This is, in part, due to EP being the net result of a series of processes, starting with net primary production (NPP) in the sunlit upper ocean, followed by the formation of particulate organic matter and the subsequent sinking and remineralisation of these particles, with each of these processes responding differently to changes in environmental conditions. Here, we compare future projectionsmore » in EP over the 21st century, generated by four marine ecosystem models under the high emission scenario Representative Concentration Pathways (RCP) 8.5 of the Intergovernmental Panel on Climate Change (IPCC), and determine the processes driving these changes. The models simulate small to modest decreases in global EP between -1 and -12%. Models differ greatly with regard to the drivers causing these changes. Among them, the formation of particles is the most uncertain process with models not agreeing on either magnitude or the direction of change. The removal of the sinking particles by remineralisation is simulated to increase in the low and intermediate latitudes in three models, driven by either warming-induced increases in remineralisation or slower particle sinking, and show insignificant changes in the remaining model. Changes in ecosystem structure, particularly the relative role of diatoms matters as well, as diatoms produce larger and denser particles that sink faster and are partly protected from remineralisation. Also this controlling factor is afflicted with high uncertainties, particularly since the models differ already substantially with regard to both the initial (present-day) distribution of diatoms (between 11–94% in the Southern Ocean) and the diatom contribution to particle formation (0.6–3.8 times higher than their contribution to biomass). As a consequence, changes in diatom concentration are a strong driver for EP changes in some models but of low significance in others. Observational and experimental constraints on ecosystem structure and how the fixed carbon is routed through the ecosystem to produce export production are urgently needed in order to improve current generation ecosystem models and their ability to project future changes.« less

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

NASA Astrophysics Data System (ADS)

Johnston, J. M.

2013-12-01

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

Marine mammals' influence on ecosystem processes affecting fisheries in the Barents Sea is trivial.

PubMed

Corkeron, Peter J

2009-04-23

Some interpretations of ecosystem-based fishery management include culling marine mammals as an integral component. The current Norwegian policy on marine mammal management is one example. Scientific support for this policy includes the Scenario Barents Sea (SBS) models. These modelled interactions between cod, Gadus morhua, herring, Clupea harengus, capelin, Mallotus villosus and northern minke whales, Balaenoptera acutorostrata. Adding harp seals Phoca groenlandica into this top-down modelling approach resulted in unrealistic model outputs. Another set of models of the Barents Sea fish-fisheries system focused on interactions within and between the three fish populations, fisheries and climate. These model key processes of the system successfully. Continuing calls to support the SBS models despite their failure suggest a belief that marine mammal predation must be a problem for fisheries. The best available scientific evidence provides no justification for marine mammal culls as a primary component of an ecosystem-based approach to managing the fisheries of the Barents Sea.

Using Ecosystem Experiments to Improve Vegetation Models

DOE PAGES

Medlyn, Belinda; Zaehle, S; DeKauwe, Martin G.; ...

2015-05-21

Ecosystem responses to rising CO2 concentrations are a major source of uncertainty in climate change projections. Data from ecosystem-scale Free-Air CO2 Enrichment (FACE) experiments provide a unique opportunity to reduce this uncertainty. The recent FACE Model–Data Synthesis project aimed to use the information gathered in two forest FACE experiments to assess and improve land ecosystem models. A new 'assumption-centred' model intercomparison approach was used, in which participating models were evaluated against experimental data based on the ways in which they represent key ecological processes. Identifying and evaluating the main assumptions caused differences among models, and the assumption-centered approach produced amore » clear roadmap for reducing model uncertainty. We explain this approach and summarize the resulting research agenda. We encourage the application of this approach in other model intercomparison projects to fundamentally improve predictive understanding of the Earth system.« less

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.

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

NASA Technical Reports Server (NTRS)

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

2000-01-01

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

Linking Local Scale Ecosystem Science to Regional Scale Management

NASA Astrophysics Data System (ADS)

Shope, C. L.; Tenhunen, J.; Peiffer, S.

2012-04-01

Ecosystem management with respect to sufficient water yield, a quality water supply, habitat and biodiversity conservation, and climate change effects requires substantial observational data at a range of scales. Complex interactions of local physical processes oftentimes vary over space and time, particularly in locations with extreme meteorological conditions. Modifications to local conditions (ie: agricultural land use changes, nutrient additions, landscape management, water usage) can further affect regional ecosystem services. The international, inter-disciplinary TERRECO research group is intensively investigating a variety of local processes, parameters, and conditions to link complex physical, economic, and social interactions at the regional scale. Field-based meteorology, hydrology, soil physics, plant production, solute and sediment transport, economic, and social behavior data were measured in a South Korean catchment. The data are used to parameterize suite of models describing local to landscape level water, sediment, nutrient, and monetary relationships. We focus on using the agricultural and hydrological SWAT model to synthesize the experimental field data and local-scale models throughout the catchment. The approach of our study was to describe local scientific processes, link potential interrelationships between different processes, and predict environmentally efficient management efforts. The Haean catchment case study shows how research can be structured to provide cross-disciplinary scientific linkages describing complex ecosystems and landscapes that can be used for regional management evaluations and predictions.

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

EPA Science Inventory

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

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

Treesearch

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

2015-01-01

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

State and transition models: Theory, applications, and challenges. In: Briske, D.D. Rangeland Systems: Processes, Management and Challenges

USDA-ARS?s Scientific Manuscript database

State and transition models (STMs) are used for communicating about ecosystem change in rangelands and other ecosystems, especially the implications for management. The fundamental premise that rangelands can exhibit multiple states is now widely accepted. The current application of STMs for managem...

Classifying and comparing spatial models of fire dynamics

Treesearch

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

2007-01-01

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

Representing climate, disturbance, and vegetation interactions in landscape models

Treesearch

Robert E. Keane; Donald McKenzie; Donald A. Falk; Erica A.H. Smithwick; Carol Miller; Lara-Karena B. Kellogg

2015-01-01

The prospect of rapidly changing climates over the next century calls for methods to predict their effects on myriad, interactive ecosystem processes. Spatially explicit models that simulate ecosystem dynamics at fine (plant, stand) to coarse (regional, global) scales are indispensable tools for meeting this challenge under a variety of possible futures. A special...

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...

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

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

Yang, Xiaofan; Liu, Chongxuan; Fang, Yilin

2015-01-01

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

Forest ecosystems in the Alaskan taiga

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

Van Cleve, K.; Chapin, F.S. III; Flanagan, P.W.

1986-01-01

This volume in the series ''Ecological Studies'' provides an overview and synthesis of research on the structure and function of taiga forest ecosystems of interior Alaska. The first section discusses the nature of the taiga environment and covers climate, forest ecosystem distribution, natural regeneration of vegetation, and the role of fire. The second edition focuses on environmental controls over organism activity with discussions on growth and nutrient use, nitrogen fixation, physiological ecology of mosses, and microbial activity and element availability. The final section considers environmental controls over ecosystem processes with discussions of processes, plant-animal interactions, and a model of forestmore » growth and yield.« less

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

Fagre, Daniel B.; Peterson, David L.; Hessl, Amy E.

2003-01-01

An integrated program of ecosystem modeling and field studies in the mountains of the Pacific Northwest (U.S.A.) has quantified many of the ecological processes affected by climatic variability. Paleoecological and contemporary ecological data in forest ecosystems provided model parameterization and validation at broad spatial and temporal scales for tree growth, tree regeneration and treeline movement. For subalpine tree species, winter precipitation has a strong negative correlation with growth; this relationship is stronger at higher elevations and west-side sites (which have more precipitation). Temperature affects tree growth at some locations with respect to length of growing season (spring) and severity of drought at drier sites (summer). Furthermore, variable but predictable climate-growth relationships across elevation gradients suggest that tree species respond differently to climate at different locations, making a uniform response of these species to future climatic change unlikely. Multi-decadal variability in climate also affects ecosystem processes. Mountain hemlock growth at high-elevation sites is negatively correlated with winter snow depth and positively correlated with the winter Pacific Decadal Oscillation (PDO) index. At low elevations, the reverse is true. Glacier mass balance and fire severity are also linked to PDO. Rapid establishment of trees in subalpine ecosystems during this century is increasing forest cover and reducing meadow cover at many subalpine locations in the western U.S.A. and precipitation (snow depth) is a critical variable regulating conifer expansion. Lastly, modeling potential future ecosystem conditions suggests that increased climatic variability will result in increasing forest fire size and frequency, and reduced net primary productivity in drier, east-side forest ecosystems. As additional empirical data and modeling output become available, we will improve our ability to predict the effects of climatic change across a broad range of climates and mountain ecosystems in the northwestern U.S.A.

Coupled ocean-shelf ecosystem modelling of northern North Atlantic

NASA Astrophysics Data System (ADS)

Harle, J.; Holt, J. T.; Butenschön, M.; Allen, J. I.

2016-02-01

The biogeochemistry and ecosystems of the open-ocean and shelf seas are intimately connected. For example Northwest European continental shelf receives a substantial fraction of its nutrients from the wider North Atlantic and exports carbon at depth, sequestering it from atmospheric exchange. In the EC FP7 EuroBasin project (Holt et al 2014) we have developed a 1/12 degree basin-scale NEMO-ERSEM model with specific features relevant to shelf seas (e.g. tides and advanced vertical mixing schemes). This model is eddy resolving in the open-ocean, and resolves barotropic scales on-shelf. We use this model to explore the interaction between finely resolved physical processes and the ecosystem. Here we focus on shelf-sea processes and the connection between the shelf seas and open-ocean, and compare results with a 1/4 degree (eddy permitting) model that does not include shelf sea processes. We find tidal mixing fronts and river plume are well represented in the 1/12 degree model. Using approaches developed for the NW Shelf (Holt et al 2012), we provide estimates of across-shelf break nutrient fluxes to the seas surrounding this basin, and relate these fluxes and their interannual variability to the physical processes driving ocean-shelf exchange. Holt, J., et al, 2012. Oceanic controls on the primary production of the northwest European continental shelf: model experiments under recent past conditions and a potential future scenario. Biogeosciences 9, 97-117. Holt, J., et al, 2014. Challenges in integrative approaches to modelling the marine ecosystems of the North Atlantic: Physics to Fish and Coasts to Ocean. Progress in Oceanography doi:10.1016/j.pocean.2014.04.024.

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.

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.

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.

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...

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

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.

CHEMICAL PROCESSES AND MODELING IN ECOSYSTEMS

EPA Science Inventory

Trends in regulatory strategies require EPA to understand better chemical behavior in natural and impacted ecosystems and in biological systems to carry out the increasingly complex array of exposure and risk assessments needed to develop scientifically defensible regulations (GP...

Biogeochemical Responses and Feedbacks to Climate Change: Synthetic Meta-Analyses Relevant to Earth System Models

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

van Gestel, Natasja; Jan van Groenigen, Kees; Osenberg, Craig

This project examined the sensitivity of carbon in land ecosystems to environmental change, focusing on carbon contained in soil, and the role of carbon-nitrogen interactions in regulating ecosystem carbon storage. The project used a combination of empirical measurements, mathematical models, and statistics to partition effects of climate change on soil into processes enhancing soil carbon and processes through which it decomposes. By synthesizing results from experiments around the world, the work provided novel insight on ecological controls and responses across broad spatial and temporal scales. The project developed new approaches in meta-analysis using principles of element mass balance and largemore » datasets to derive metrics of ecosystem responses to environmental change. The project used meta-analysis to test how nutrients regulate responses of ecosystems to elevated CO2 and warming, in particular responses of nitrogen fixation, critical for regulating long-term C balance.« less

Net ecosystem productivity of temperate and boreal forests after clearcutting - a Fluxnet-Canada measurement and modelling synthesis

NASA Astrophysics Data System (ADS)

Grant, R. F.; Barr, A.; Black, T. A.; Margolis, H. A.; McCaughey, J. H.; Trofymow, J. A.

2010-05-01

Clearcutting strongly affects subsequent forest net ecosystem productivity (NEP). Hypotheses for ecological controls on NEP in the ecosystem model ecosys were tested with CO2 fluxes measured by eddy covariance (EC) in three post-clearcut conifer chronosequences. An algorithm for microbial colonization of fine and woody debris allowed the model to reproduce sigmoidal declines in debris observed after clearcutting. In the model, Rh drove debris decomposition that drove microbial growth, N mineralization and asymbiotic N2 fixation. These processes controlled root N uptake, and thereby CO2 fixation in regrowing vegetation. Interactions among soil and plant processes allowed the model to simulate hourly CO2 fluxes and annual NEP within the uncertainty of EC measurements from 2003 through 2007 over forest stands from 1 to 80 years of age in all three chronosequences without site- or species-specific parameterization. The model was then used to study the impacts of increasing harvest removals on subsequent C stocks at one of the chronosequence sites. Model results indicated that increasing harvest removals would hasten recovery of NEP during the first 30 years after clearcutting, but would reduce ecosystem C stocks by about 15% of the increased removals at the end of an 80 year harvest cycle.

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.

Uncovering stability mechanisms in microbial ecosystems - combining microcosm experiments, computational modelling and ecological theory in a multidisciplinary approach

NASA Astrophysics Data System (ADS)

Worrich, Anja; König, Sara; Banitz, Thomas; Centler, Florian; Frank, Karin; Kästner, Matthias; Miltner, Anja; Thullner, Martin; Wick, Lukas

2015-04-01

Although bacterial degraders in soil are commonly exposed to fluctuating environmental conditions, the functional performance of the biodegradation processes can often be maintained by resistance and resilience mechanisms. However, there is still a gap in the mechanistic understanding of key factors contributing to the stability of such an ecosystem service. Therefore we developed an integrated approach combining microcosm experiments, simulation models and ecological theory to directly make use of the strengths of these disciplines. In a continuous interplay process, data, hypotheses, and central questions are exchanged between disciplines to initiate new experiments and models to ultimately identify buffer mechanisms and factors providing functional stability. We focus on drying and rewetting-cycles in soil ecosystems, which are a major abiotic driver for bacterial activity. Functional recovery of the system was found to depend on different spatial processes in the computational model. In particular, bacterial motility is a prerequisite for biodegradation if either bacteria or substrate are heterogeneously distributed. Hence, laboratory experiments focussing on bacterial dispersal processes were conducted and confirmed this finding also for functional resistance. Obtained results will be incorporated into the model in the next step. Overall, the combination of computational modelling and laboratory experiments identified spatial processes as the main driving force for functional stability in the considered system, and has proved a powerful methodological approach.

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.

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...

Lynx conservation in an ecosystem management context [Chapter 15

Treesearch

Kevin S. McKelvey; Keith B. Aubry; James K. Agee; Steven W. Buskirk; Leonard F. Ruggiero; Gary M. Koehler

2000-01-01

In an ecosystem management context, management for lynx must occur in the context of the needs of other species, watershed health, and a variety of products, outputs, and uses. This chapter presents a management model based on the restoration of historical patterns and processes. We argue that this model is sustainable in a formal sense, practical, and likely...

Modeling impacts of management on carbon sequestration and trace gas emissions in forested wetland ecosystems

Treesearch

Changsheng Li; Jianbo Cui

2004-01-01

A process- based model, Wetland-DNDC, was modified to enhance its capacity to predict the impacts of management practices on carbon sequestration in and trace gas emissions from forested wetland ecosystems. The modifications included parameterization of management practices fe.g., forest harvest, chopping, burning, water management, fertilization, and tree planting),...

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...

Assessing model sensitivity and uncertainty across multiple Free-Air CO2 Enrichment experiments.

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2015-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentrations are highly variable and contain a considerable amount of uncertainty. It is necessary that we understand which factors are driving this uncertainty. The Free-Air CO2 Enrichment (FACE) experiments have equipped us with a rich data source that can be used to calibrate and validate these model predictions. To identify and evaluate the assumptions causing inter-model differences we performed model sensitivity and uncertainty analysis across ambient and elevated CO2 treatments using the Data Assimilation Linked Ecosystem Carbon (DALEC) model and the Ecosystem Demography Model (ED2), two process-based models ranging from low to high complexity respectively. These modeled process responses were compared to experimental data from the Kennedy Space Center Open Top Chamber Experiment, the Nevada Desert Free Air CO2 Enrichment Facility, the Rhinelander FACE experiment, the Wyoming Prairie Heating and CO2 Enrichment Experiment, the Duke Forest Face experiment and the Oak Ridge Experiment on CO2 Enrichment. By leveraging data access proxy and data tilling services provided by the BrownDog data curation project alongside analysis modules available in the Predictive Ecosystem Analyzer (PEcAn), we produced automated, repeatable benchmarking workflows that are generalized to incorporate different sites and ecological models. Combining the observed patterns of uncertainty between the two models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Prototyping an online wetland ecosystem services model using open model sharing standards

USGS Publications Warehouse

Feng, M.; Liu, S.; Euliss, N.H.; Young, Caitlin; Mushet, D.M.

2011-01-01

Great interest currently exists for developing ecosystem models to forecast how ecosystem services may change under alternative land use and climate futures. Ecosystem services are diverse and include supporting services or functions (e.g., primary production, nutrient cycling), provisioning services (e.g., wildlife, groundwater), regulating services (e.g., water purification, floodwater retention), and even cultural services (e.g., ecotourism, cultural heritage). Hence, the knowledge base necessary to quantify ecosystem services is broad and derived from many diverse scientific disciplines. Building the required interdisciplinary models is especially challenging as modelers from different locations and times may develop the disciplinary models needed for ecosystem simulations, and these models must be identified and made accessible to the interdisciplinary simulation. Additional difficulties include inconsistent data structures, formats, and metadata required by geospatial models as well as limitations on computing, storage, and connectivity. Traditional standalone and closed network systems cannot fully support sharing and integrating interdisciplinary geospatial models from variant sources. To address this need, we developed an approach to openly share and access geospatial computational models using distributed Geographic Information System (GIS) techniques and open geospatial standards. We included a means to share computational models compliant with Open Geospatial Consortium (OGC) Web Processing Services (WPS) standard to ensure modelers have an efficient and simplified means to publish new models. To demonstrate our approach, we developed five disciplinary models that can be integrated and shared to simulate a few of the ecosystem services (e.g., water storage, waterfowl breeding) that are provided by wetlands in the Prairie Pothole Region (PPR) of North America.

Lake and wetland ecosystem services measuring water storage and local climate regulation

NASA Astrophysics Data System (ADS)

Wong, Christina P.; Jiang, Bo; Bohn, Theodore J.; Lee, Kai N.; Lettenmaier, Dennis P.; Ma, Dongchun; Ouyang, Zhiyun

2017-04-01

Developing interdisciplinary methods to measure ecosystem services is a scientific priority, however, progress remains slow in part because we lack ecological production functions (EPFs) to quantitatively link ecohydrological processes to human benefits. In this study, we tested a new approach, combining a process-based model with regression models, to create EPFs to evaluate water storage and local climate regulation from a green infrastructure project on the Yongding River in Beijing, China. Seven artificial lakes and wetlands were established to improve local water storage and human comfort; evapotranspiration (ET) regulates both services. Managers want to minimize the trade-off between water losses and cooling to sustain water supplies while lowering the heat index (HI) to improve human comfort. We selected human benefit indicators using water storage targets and Beijing's HI, and the Variable Infiltration Capacity model to determine the change in ET from the new ecosystems. We created EPFs to quantify the ecosystem services as marginal values [Δfinal ecosystem service/Δecohydrological process]: (1) Δwater loss (lake evaporation/volume)/Δdepth and (2) Δsummer HI/ΔET. We estimate the new ecosystems increased local ET by 0.7 mm/d (20.3 W/m2) on the Yongding River. However, ET rates are causing water storage shortfalls while producing no improvements in human comfort. The shallow lakes/wetlands are vulnerable to drying when inflow rates fluctuate, low depths lead to higher evaporative losses, causing water storage shortfalls with minimal cooling effects. We recommend managers make the lakes deeper to increase water storage, and plant shade trees to improve human comfort in the parks.

Modeling soil moisture memory in savanna ecosystems

NASA Astrophysics Data System (ADS)

Gou, S.; Miller, G. R.

2011-12-01

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

Assessing The Ecosystem Service Freshwater Production From An Integrated Water Resources Management Perspective. Case Study: The Tormes Water Resources System (Spain)

NASA Astrophysics Data System (ADS)

Momblanch, Andrea; Paredes-Arquiola, Javier; Andreu, Joaquín; Solera, Abel

2014-05-01

The Ecosystem Services are defined as the conditions and processes through which natural ecosystems, and the species that make them up, sustain and fulfil human life. A strongly related concept is the Integrated Water Resources Management. It is a process which promotes the coordinated development and management of water, land and related resources in order to maximise the resultant economic and social welfare in an equitable manner without compromising the sustainability of vital ecosystems. From these definitions, it is clear that in order to cover so many water management and ecosystems related aspects the use of integrative models is increasingly necessary. In this study, we propose to link a hydrologic model and a water allocation model in order to assess the Freshwater Production as an Ecosystem Service in anthropised river basins. First, the hydrological model allows determining the volume of water generated by each sub-catchment; that is, the biophysical quantification of the service. This result shows the relevance of each sub-catchment as a source of freshwater and how this could change if the land uses are modified. On the other hand, the water management model allocates the available water resources among the different water uses. Then, it is possible to provide an economic value to the water resources through the use of demand curves, or other economic concepts. With this second model, we are able to obtain the economical quantification of the Ecosystem Service. Besides, the influence of water management and infrastructures on the service provision can be analysed. The methodology is applied to the Tormes Water Resources System, in Spain. The software used are EVALHID and SIMGES, for hydrological and management aspects, respectively. Both models are included in the Decision Support System Shell AQUATOOL for water resources planning and management. A scenario approach is presented to illustrate the potential of the methodology, including the current state and some intervention scenarios.

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

DOE PAGES

Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.; ...

2017-11-22

Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

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

Griffiths, Natalie A.; Hanson, Paul J.; Ricciuto, Daniel M.

Here, we are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO 2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial vs. temporal variation in measured C cycle processes and their environmental drivers. We also conducted a sensitivity analysis of a peatland C model to identify how variation in ecosystem parameters contributes to model prediction uncertainty. High spatial variability in C cycle processes resulted in the inability to determinemore » if the bog was a C source or sink, as the 95% confidence interval ranged from a source of 50 g C m –2 yr –1 to a sink of 67 g C m –2 yr –1. Model sensitivity analysis also identified that spatial variation in tree and shrub photosynthesis, allocation characteristics, and maintenance respiration all contributed to large variations in the pretreatment estimates of net C balance. Variation in ecosystem processes can be more thoroughly characterized if more measurements are collected for parameters that are highly variable over space and time, and especially if those measurements encompass environmental gradients that may be driving the spatial and temporal variation (e.g., hummock vs. hollow microtopographies, and wet vs. dry years). Together, the coupled modeling and empirical approaches indicate that variability in C cycle processes and their drivers must be taken into account when interpreting the significance of experimental warming and elevated CO 2 treatments.« less

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.

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.

Uncertainties in ecosystem service maps: a comparison on the European scale.

PubMed

Schulp, Catharina J E; Burkhard, Benjamin; Maes, Joachim; Van Vliet, Jasper; Verburg, Peter H

2014-01-01

Safeguarding the benefits that ecosystems provide to society is increasingly included as a target in international policies. To support such policies, ecosystem service maps are made. However, there is little attention for the accuracy of these maps. We made a systematic review and quantitative comparison of ecosystem service maps on the European scale to generate insights in the uncertainty of ecosystem service maps and discuss the possibilities for quantitative validation. Maps of climate regulation and recreation were reasonably similar while large uncertainties among maps of erosion protection and flood regulation were observed. Pollination maps had a moderate similarity. Differences among the maps were caused by differences in indicator definition, level of process understanding, mapping aim, data sources and methodology. Absence of suitable observed data on ecosystem services provisioning hampers independent validation of the maps. Consequently, there are, so far, no accurate measures for ecosystem service map quality. Policy makers and other users need to be cautious when applying ecosystem service maps for decision-making. The results illustrate the need for better process understanding and data acquisition to advance ecosystem service mapping, modelling and validation.

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.

Incorporating Ecosystem Experiments and Observations into Process Models of Forest Carbon and Water Cycles: Challenges and Solutions

NASA Astrophysics Data System (ADS)

Ward, E. J.; Thomas, R. Q.; Sun, G.; McNulty, S. G.; Domec, J. C.; Noormets, A.; King, J. S.

2015-12-01

Numerous studies, both experimental and observational, have been conducted over the past two decades in an attempt to understand how water and carbon cycling in terrestrial ecosystems may respond to changes in climatic conditions. These studies have produced a wealth of detailed data on key processes driving these cycles. In parallel, sophisticated models of these processes have been formulated to answer a variety of questions relevant to natural resource management. Recent advances in data assimilation techniques offer exciting new possibilities to combine this wealth of ecosystem data with process models of ecosystem function to improve prediction and quantify associated uncertainty. Using forests of the southeastern United States as our focus, we will specify how fine-scale physiological (e.g. half-hourly sap flux) can be scaled up with quantified error for use in models of stand growth and hydrology. This approach represents an opportunity to leverage current and past research from experiments including throughfall displacement × fertilization (PINEMAP), irrigation × fertilization (SETRES), elevated CO­2­ (Duke and ORNL FACE) and a variety of observational studies in both conifer and hardwood forests throughout the region, using a common platform for data assimilation and prediction. As part of this discussion, we will address variation in dominant species, stand structure, site age, management practices, soils and climate that represent both challenges to the development of a common analytical approach and opportunities to address questions of interest to policy makers and natural resource managers.

Ecosystem services sustainability in the Mediterranean Sea: assessment of status and trends using multiple modelling approaches

NASA Astrophysics Data System (ADS)

Liquete, Camino; Piroddi, Chiara; Macías, Diego; Druon, Jean-Noël; Zulian, Grazia

2016-09-01

Mediterranean ecosystems support important processes and functions that bring direct benefits to human society. Yet, marine ecosystem services are usually overlooked due to the challenges in identifying and quantifying them. This paper proposes the application of several biophysical and ecosystem modelling approaches to assess spatially and temporally the sustainable use and supply of selected marine ecosystem services. Such services include food provision, water purification, coastal protection, lifecycle maintenance and recreation, focusing on the Mediterranean region. Overall, our study found a higher number of decreasing than increasing trends in the natural capacity of the ecosystems to provide marine and coastal services, while in contrast the opposite was observed to be true for the realised flow of services to humans. Such a study paves the way towards an effective support for Blue Growth and the European maritime policies, although little attention is paid to the quantification of marine ecosystem services in this context. We identify a key challenge of integrating biophysical and socio-economic models as a necessary step to further this research.

Ecosystem services sustainability in the Mediterranean Sea: assessment of status and trends using multiple modelling approaches

PubMed Central

Liquete, Camino; Piroddi, Chiara; Macías, Diego; Druon, Jean-Noël; Zulian, Grazia

2016-01-01

Mediterranean ecosystems support important processes and functions that bring direct benefits to human society. Yet, marine ecosystem services are usually overlooked due to the challenges in identifying and quantifying them. This paper proposes the application of several biophysical and ecosystem modelling approaches to assess spatially and temporally the sustainable use and supply of selected marine ecosystem services. Such services include food provision, water purification, coastal protection, lifecycle maintenance and recreation, focusing on the Mediterranean region. Overall, our study found a higher number of decreasing than increasing trends in the natural capacity of the ecosystems to provide marine and coastal services, while in contrast the opposite was observed to be true for the realised flow of services to humans. Such a study paves the way towards an effective support for Blue Growth and the European maritime policies, although little attention is paid to the quantification of marine ecosystem services in this context. We identify a key challenge of integrating biophysical and socio-economic models as a necessary step to further this research. PMID:27686533

Multiple resource use efficiency (mRUE): A new concept for ecosystem production

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

Han, Juanjuan; Chen, Jiquan; Miao, Yuan

The resource-driven concept, which is an important school for investigating ecosystem production, has been applied for decades. However, the regulatory mechanisms of production by multiple resources remain unclear. We formulated a new algorithm model that integrates multiple resource uses to study ecosystem production and tested its applications on a water-availability gradient in semi-arid grassland. The result of our experiment showed that changes in water availability significantly affected the resources of light and nitrogen, and altered the relationships among multiple resource absorption rate (ε), multiple resource use efficiency (mRUE), and available resource (R avail). The increased water availability suppressed ecosystem mRUEmore » (i.e., “declining marginal returns”); The changes in mRUE had a negative effect on ε (i.e., “inverse feedback”). These two processes jointly regulated that the stimulated single resource availability would promote ecosystem production rather than suppress it, even when mRUE was reduced. This study illustrated the use of the mRUE model in exploring the coherent relationships among the key parameters on regulating the ecosystem production for future modeling, and evaluated the sensitivity of this conceptual model under different dataset properties. Furthermore, this model needs extensive validation by the ecological community before it can extrapolate this method to other ecosystems in the future.« less

Multiple resource use efficiency (mRUE): A new concept for ecosystem production

DOE PAGES

Han, Juanjuan; Chen, Jiquan; Miao, Yuan; ...

2016-11-21

The resource-driven concept, which is an important school for investigating ecosystem production, has been applied for decades. However, the regulatory mechanisms of production by multiple resources remain unclear. We formulated a new algorithm model that integrates multiple resource uses to study ecosystem production and tested its applications on a water-availability gradient in semi-arid grassland. The result of our experiment showed that changes in water availability significantly affected the resources of light and nitrogen, and altered the relationships among multiple resource absorption rate (ε), multiple resource use efficiency (mRUE), and available resource (R avail). The increased water availability suppressed ecosystem mRUEmore » (i.e., “declining marginal returns”); The changes in mRUE had a negative effect on ε (i.e., “inverse feedback”). These two processes jointly regulated that the stimulated single resource availability would promote ecosystem production rather than suppress it, even when mRUE was reduced. This study illustrated the use of the mRUE model in exploring the coherent relationships among the key parameters on regulating the ecosystem production for future modeling, and evaluated the sensitivity of this conceptual model under different dataset properties. Furthermore, this model needs extensive validation by the ecological community before it can extrapolate this method to other ecosystems in the future.« less

Multiple Resource Use Efficiency (mRUE): A New Concept for Ecosystem Production.

PubMed

Han, Juanjuan; Chen, Jiquan; Miao, Yuan; Wan, Shiqiang

2016-11-21

The resource-driven concept, which is an important school for investigating ecosystem production, has been applied for decades. However, the regulatory mechanisms of production by multiple resources remain unclear. We formulated a new algorithm model that integrates multiple resource uses to study ecosystem production and tested its applications on a water-availability gradient in semi-arid grassland. The result of our experiment showed that changes in water availability significantly affected the resources of light and nitrogen, and altered the relationships among multiple resource absorption rate (ε), multiple resource use efficiency (mRUE), and available resource (R avail ). The increased water availability suppressed ecosystem mRUE (i.e., "declining marginal returns"); The changes in mRUE had a negative effect on ε (i.e., "inverse feedback"). These two processes jointly regulated that the stimulated single resource availability would promote ecosystem production rather than suppress it, even when mRUE was reduced. This study illustrated the use of the mRUE model in exploring the coherent relationships among the key parameters on regulating the ecosystem production for future modeling, and evaluated the sensitivity of this conceptual model under different dataset properties. However, this model needs extensive validation by the ecological community before it can extrapolate this method to other ecosystems in the future.

Rising tides, cumulative impacts and cascading changes to estuarine ecosystem functions.

PubMed

O'Meara, Theresa A; Hillman, Jenny R; Thrush, Simon F

2017-08-31

In coastal ecosystems, climate change affects multiple environmental factors, yet most predictive models are based on simple cause-and-effect relationships. Multiple stressor scenarios are difficult to predict because they can create a ripple effect through networked ecosystem functions. Estuarine ecosystem function relies on an interconnected network of physical and biological processes. Estuarine habitats play critical roles in service provision and represent global hotspots for organic matter processing, nutrient cycling and primary production. Within these systems, we predicted functional changes in the impacts of land-based stressors, mediated by changing light climate and sediment permeability. Our in-situ field experiment manipulated sea level, nutrient supply, and mud content. We used these stressors to determine how interacting environmental stressors influence ecosystem function and compared results with data collected along elevation gradients to substitute space for time. We show non-linear, multi-stressor effects deconstruct networks governing ecosystem function. Sea level rise altered nutrient processing and impacted broader estuarine services ameliorating nutrient and sediment pollution. Our experiment demonstrates how the relationships between nutrient processing and biological/physical controls degrade with environmental stress. Our results emphasise the importance of moving beyond simple physically-forced relationships to assess consequences of climate change in the context of ecosystem interactions and multiple stressors.

Assimilation of Leaf and Canopy Spectroscopic Data to Improve the Representation of Vegetation Dynamics in Terrestrial Ecosystem Models

NASA Astrophysics Data System (ADS)

Serbin, S. P.; Dietze, M.; Desai, A. R.; LeBauer, D.; Viskari, T.; Kooper, R.; McHenry, K. G.; Townsend, P. A.

2013-12-01

The ability to seamlessly integrate information on vegetation structure and function across a continuum of scales, from field to satellite observations, greatly enhances our ability to understand how terrestrial vegetation-atmosphere interactions change over time and in response to disturbances. In particular, terrestrial ecosystem models require detailed information on ecosystem states and canopy properties in order to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere as well as address the vulnerability of ecosystems to environmental and other perturbations. Over the last several decades the amount of available data to constrain ecological predictions has increased substantially, resulting in a progressively data-rich era for global change research. In particular remote sensing data, specifically optical data (leaf and canopy), offers the potential for an important and direct data constraint on ecosystem model projections of C and energy fluxes. Here we highlight the utility of coupling information provided through the Ecosystem Spectral Information System (EcoSIS) with complex process models through the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) eco-informatics framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. We also present this an efficient approach for understanding and correcting implicit assumptions and model structural deficiencies. We first illustrate the challenges and issues in adequately characterizing ecosystem fluxes with the Ecosystem Demography model (ED2, Medvigy et al., 2009) due to improper parameterization of leaf and canopy properties, as well as assumptions describing radiative transfer within the canopy. ED2 is especially relevant to these efforts because it contains a sophisticated structure for scaling ecological processes across a range of spatial scales: from the tree-level (demography, physiology) to the distribution of stands across a landscape, which allows for the direct use of remotely sensed data at the appropriate spatial scale. A sensitivity analysis is employed within PEcAn to illustrate the influence of ED2 parameterizations on modeled C and energy fluxes for a northern temperate forest ecosystem as an example of the need for more detailed information on leaf and canopy optical properties. We then demonstrate a data assimilation approach to synthesize spectral data contained within EcoSIS in order to update model parameterizations across key vegetation plant functional types, as well as a means to update vegetation state information (i.e. composition, LAI) and improve the description of radiation transfer through model structural updates. A better understanding of the radiation balance of ecosystems will improve regional and global scale C and energy balance projections.

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.

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.

Application of a predator-prey overlap metric to determine the impact of sub-grid scale feeding dynamics on ecosystem productivity

NASA Astrophysics Data System (ADS)

Greer, A. T.; Woodson, C. B.

2016-02-01

Because of the complexity and extremely large size of marine ecosystems, research attention has a strong focus on modelling the system through space and time to elucidate processes driving ecosystem state. One of the major weaknesses of current modelling approaches is the reliance on a particular grid cell size (usually 10's of km in the horizontal & water column mean) to capture the relevant processes, even though empirical research has shown that marine systems are highly structured on fine scales, and this structure can persist over relatively long time scales (days to weeks). Fine-scale features can have a strong influence on the predator-prey interactions driving trophic transfer. Here we apply a statistic, the AB ratio, used to quantify increased predator production due to predator-prey overlap on fine scales in a manner that is computationally feasible for larger scale models. We calculated the AB ratio for predator-prey distributions throughout the scientific literature, as well as for data obtained with a towed plankton imaging system, demonstrating that averaging across a typical model grid cell neglects the fine-scale predator-prey overlap that is an essential component of ecosystem productivity. Organisms from a range of trophic levels and oceanographic regions tended to overlap with their prey both in the horizontal and vertical dimensions. When predator swimming over a diel cycle was incorporated, the amount of production indicated by the AB ratio increased substantially. For the plankton image data, the AB ratio was higher with increasing sampling resolution, especially when prey were highly aggregated. We recommend that ecosystem models incorporate more fine-scale information both to more accurately capture trophic transfer processes and to capitalize on the increasing sampling resolution and data volume from empirical studies.

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

Modeling species invasions in Ecopath with Ecosim: an evaluation using Laurentian Great Lakes models

USGS Publications Warehouse

Langseth, Brian J.; Rogers, Mark; Zhang, Hongyan

2012-01-01

Invasive species affect the structure and processes of ecosystems they invade. Invasive species have been particularly relevant to the Laurentian Great Lakes, where they have played a part in both historical and recent changes to Great Lakes food webs and the fisheries supported therein. There is increased interest in understanding the effects of ecosystem changes on fisheries within the Great Lakes, and ecosystem models provide an essential tool from which this understanding can take place. A commonly used model for exploring fisheries management questions within an ecosystem context is the Ecopath with Ecosim (EwE) modeling software. Incorporating invasive species into EwE models is a challenging process, and descriptions and comparisons of methods for modeling species invasions are lacking. We compared four methods for incorporating invasive species into EwE models for both Lake Huron and Lake Michigan based on the ability of each to reproduce patterns in observed data time series. The methods differed in whether invasive species biomass was forced in the model, the initial level of invasive species biomass at the beginning of time dynamic simulations, and the approach to cause invasive species biomass to increase at the time of invasion. The overall process of species invasion could be reproduced by all methods, but fits to observed time series varied among the methods and models considered. We recommend forcing invasive species biomass when model objectives are to understand ecosystem impacts in the past and when time series of invasive species biomass are available. Among methods where invasive species time series were not forced, mediating the strength of predator–prey interactions performed best for the Lake Huron model, but worse for the Lake Michigan model. Starting invasive species biomass at high values and then artificially removing biomass until the time of invasion performed well for both models, but was more complex than starting invasive species biomass at low values. In general, for understanding the effect of invasive species on future fisheries management actions, we recommend initiating invasive species biomass at low levels based on the greater simplicity and realism of the method compared to others.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-02-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Bringing the ecosystem services concept into marine management decisions, supporting ecosystems-based management.

NASA Astrophysics Data System (ADS)

Tweddle, J. F.; Byg, A.; Davies, I.; Gubbins, M.; Irvine, K.; Kafas, A.; Kenter, J.; MacDonald, A.; Murray, R. B. O.; Potts, T.; Slater, A. M.; Wright, K.; Scott, B. E.

2016-12-01

The marine environment is under increasing use, putting pressure on marine ecosystems and increasing competition for space. New activities (e.g. renewable energy developments), evolving marine policies (e.g. implementation of marine protected areas), and climate change may drive changes in biodiversity and resulting ecosystem services (ES) that society and business utilise from coastal and marine systems. A process is needed that integrates ecological assessment of changes with stakeholder perceptions and valuation of ES, whilst balancing ease of application with the ability to deal with complex social-economic-ecological issues. The project "Cooperative participatory assessment of the impact of renewable technology on ecosystem services: CORPORATES" involved natural and social scientists, law and policy experts, and marine managers, with the aim of promoting more integrated decision making using ES concepts in marine management. CORPORATES developed a process to bring ES concepts into stakeholders' awareness. The interactive process, involving 2 workshops, employs interludes of knowledge exchange by experts on ecological processes underpinning ES and on law and policy. These enable mapping of benefits linked to activities, participatory system modelling, and deliberation of policy impacts on different sectors. The workshops were attended by industry representatives, regulatory/advisory partners, and other stakeholders (NGOs, SMEs, recreationalists, local government). Mixed sector groups produced new insights into links between activities and ES, and highlighted cross-sector concerns. Here we present the aspects of the process that successfully built shared understanding between industry and stakeholders of inter-linkages and interactions between ES, benefits, activities, and economic and cultural values. These methods provide an ES-based decision-support model for exchanging societal-ecological knowledge and providing stakeholder interaction in marine planning, supporting ecosystem-based management.

Are there links between responses of soil microbes and ecosystem functioning to elevated CO2, N deposition and warming? A global perspective.

PubMed

García-Palacios, Pablo; Vandegehuchte, Martijn L; Shaw, E Ashley; Dam, Marie; Post, Keith H; Ramirez, Kelly S; Sylvain, Zachary A; de Tomasel, Cecilia Milano; Wall, Diana H

2015-04-01

In recent years, there has been an increase in research to understand how global changes' impacts on soil biota translate into altered ecosystem functioning. However, results vary between global change effects, soil taxa, and ecosystem processes studied, and a synthesis of relationships is lacking. Therefore, here we initiate such a synthesis to assess whether the effect size of global change drivers (elevated CO2, N deposition, and warming) on soil microbial abundance is related with the effect size of these drivers on ecosystem functioning (plant biomass, soil C cycle, and soil N cycle) using meta-analysis and structural equation modeling. For N deposition and warming, the global change effect size on soil microbes was positively associated with the global change effect size on ecosystem functioning, and these relationships were consistent across taxa and ecosystem processes. However, for elevated CO2, such links were more taxon and ecosystem process specific. For example, fungal abundance responses to elevated CO2 were positively correlated with those of plant biomass but negatively with those of the N cycle. Our results go beyond previous assessments of the sensitivity of soil microbes and ecosystem processes to global change, and demonstrate the existence of general links between the responses of soil microbial abundance and ecosystem functioning. Further we identify critical areas for future research, specifically altered precipitation, soil fauna, soil community composition, and litter decomposition, that are need to better quantify the ecosystem consequences of global change impacts on soil biodiversity. © 2014 John Wiley & Sons Ltd.

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.

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...

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.

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...

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

DOE PAGES

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; ...

2017-09-28

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

NASA Astrophysics Data System (ADS)

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan; Zhou, Xiaolu; Wang, Meng; Zhang, Kerou; Wang, Gangsheng

2017-10-01

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195 Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated by Xu et al. (2014). We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC), and mineral-associated organic carbon (MOC). However, our work represents the first step toward a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.

Modeling Global Soil Carbon and Soil Microbial Carbon by Integrating Microbial Processes into the Ecosystem Process Model TRIPLEX-GHG

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

Wang, Kefeng; Peng, Changhui; Zhu, Qiuan

Microbial physiology plays a critical role in the biogeochemical cycles of the Earth system. However, most traditional soil carbon models are lacking in terms of the representation of key microbial processes that control the soil carbon response to global climate change. In this study, the improved process-based model TRIPLEX-GHG was developed by coupling it with the new MEND (Microbial-ENzyme-mediated Decomposition) model to estimate total global soil organic carbon (SOC) and global soil microbial carbon. The new model (TRIPLEX-MICROBE) shows considerable improvement over the previous version (TRIPLEX-GHG) in simulating SOC. We estimated the global soil carbon stock to be approximately 1195more » Pg C, with 348 Pg C located in the high northern latitudes, which is in good agreement with the well-regarded Harmonized World Soil Database (HWSD) and the Northern Circumpolar Soil Carbon Database (NCSCD). We also estimated the global soil microbial carbon to be 21 Pg C, similar to the 23 Pg C estimated. We found that the microbial carbon quantity in the latitudinal direction showed reversions at approximately 30°N, near the equator and at 25°S. A sensitivity analysis suggested that the tundra ecosystem exhibited the highest sensitivity to a 1°C increase or decrease in temperature in terms of dissolved organic carbon (DOC), microbial biomass carbon (MBC) and mineral-associated organic carbon (MOC). Furthermore, our work represents the first step towards a new generation of ecosystem process models capable of integrating key microbial processes into soil carbon cycles.« less

Effect of Freeze-Thaw Cycles on Soil Nitrogen Reactive Transport in a Polygonal Arctic Tundra Ecosystem at Barrow AK Using 3-D Coupled ALM-PFLOTRAN

NASA Astrophysics Data System (ADS)

Yuan, F.; Wang, G.; Painter, S. L.; Tang, G.; Xu, X.; Kumar, J.; Bisht, G.; Hammond, G. E.; Mills, R. T.; Thornton, P. E.; Wullschleger, S. D.

2017-12-01

In Arctic tundra ecosystem soil freezing-thawing is one of dominant physical processes through which biogeochemical (e.g., carbon and nitrogen) cycles are tightly coupled. Besides hydraulic transport, freezing-thawing can cause pore water movement and aqueous species gradients, which are additional mechanisms for soil nitrogen (N) reactive-transport in Tundra ecosystem. In this study, we have fully coupled an in-development ESM(i.e., Advanced Climate Model for Energy, ACME)'s Land Model (ALM) aboveground processes with a state-of-the-art massively parallel 3-D subsurface thermal-hydrology and reactive transport code, PFLOTRAN. The resulting coupled ALM-PFLOTRAN model is a Land Surface Model (LSM) capable of resolving 3-D soil thermal-hydrological-biogeochemical cycles. This specific version of PFLOTRAN has incorporated CLM-CN Converging Trophic Cascade (CTC) model and a full and simple but robust soil N cycle. It includes absorption-desorption for soil NH4+ and gas dissolving-degasing process as well. It also implements thermal-hydrology mode codes with three newly-modified freezing-thawing algorithms which can greatly improve computing performance in regarding to numerical stiffness at freezing-point. Here we tested the model in fully 3-D coupled mode at the Next Generation Ecosystem Experiment-Arctic (NGEE-Arctic) field intensive study site at the Barrow Environmental Observatory (BEO), AK. The simulations show that: (1) synchronous coupling of soil thermal-hydrology and biogeochemistry in 3-D can greatly impact ecosystem dynamics across polygonal tundra landscape; and (2) freezing-thawing cycles can add more complexity to the system, resulting in greater mobility of soil N vertically and laterally, depending upon local micro-topography. As a preliminary experiment, the model is also implemented for Pan-Arctic region in 1-D column mode (i.e. no lateral connection), showing significant differences compared to stand-alone ALM. The developed ALM-PFLOTRAN coupling codes embeded within ESM will be used for Pan-Arctic regional evaluation of climate change-caused ecosystem responses and their feedbacks to climate system at various scales.

Interactive effects of global climate change and pollution on marine microbes: the way ahead.

PubMed

Coelho, Francisco J R C; Santos, Ana L; Coimbra, Joana; Almeida, Adelaide; Cunha, Angela; Cleary, Daniel F R; Calado, Ricardo; Gomes, Newton C M

2013-06-01

Global climate change has the potential to seriously and adversely affect marine ecosystem functioning. Numerous experimental and modeling studies have demonstrated how predicted ocean acidification and increased ultraviolet radiation (UVR) can affect marine microbes. However, researchers have largely ignored interactions between ocean acidification, increased UVR and anthropogenic pollutants in marine environments. Such interactions can alter chemical speciation and the bioavailability of several organic and inorganic pollutants with potentially deleterious effects, such as modifying microbial-mediated detoxification processes. Microbes mediate major biogeochemical cycles, providing fundamental ecosystems services such as environmental detoxification and recovery. It is, therefore, important that we understand how predicted changes to oceanic pH, UVR, and temperature will affect microbial pollutant detoxification processes in marine ecosystems. The intrinsic characteristics of microbes, such as their short generation time, small size, and functional role in biogeochemical cycles combined with recent advances in molecular techniques (e.g., metagenomics and metatranscriptomics) make microbes excellent models to evaluate the consequences of various climate change scenarios on detoxification processes in marine ecosystems. In this review, we highlight the importance of microbial microcosm experiments, coupled with high-resolution molecular biology techniques, to provide a critical experimental framework to start understanding how climate change, anthropogenic pollution, and microbiological interactions may affect marine ecosystems in the future.

Interactive effects of global climate change and pollution on marine microbes: the way ahead

PubMed Central

Coelho, Francisco J R C; Santos, Ana L; Coimbra, Joana; Almeida, Adelaide; Cunha, Ângela; Cleary, Daniel F R; Calado, Ricardo; Gomes, Newton C M

2013-01-01

Global climate change has the potential to seriously and adversely affect marine ecosystem functioning. Numerous experimental and modeling studies have demonstrated how predicted ocean acidification and increased ultraviolet radiation (UVR) can affect marine microbes. However, researchers have largely ignored interactions between ocean acidification, increased UVR and anthropogenic pollutants in marine environments. Such interactions can alter chemical speciation and the bioavailability of several organic and inorganic pollutants with potentially deleterious effects, such as modifying microbial-mediated detoxification processes. Microbes mediate major biogeochemical cycles, providing fundamental ecosystems services such as environmental detoxification and recovery. It is, therefore, important that we understand how predicted changes to oceanic pH, UVR, and temperature will affect microbial pollutant detoxification processes in marine ecosystems. The intrinsic characteristics of microbes, such as their short generation time, small size, and functional role in biogeochemical cycles combined with recent advances in molecular techniques (e.g., metagenomics and metatranscriptomics) make microbes excellent models to evaluate the consequences of various climate change scenarios on detoxification processes in marine ecosystems. In this review, we highlight the importance of microbial microcosm experiments, coupled with high-resolution molecular biology techniques, to provide a critical experimental framework to start understanding how climate change, anthropogenic pollution, and microbiological interactions may affect marine ecosystems in the future. PMID:23789087

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.

Compartmentalized metabolic network reconstruction of microbial communities to determine the effect of agricultural intervention on soils

PubMed Central

Álvarez-Yela, Astrid Catalina; Gómez-Cano, Fabio; Zambrano, María Mercedes; Husserl, Johana; Danies, Giovanna; Restrepo, Silvia; González-Barrios, Andrés Fernando

2017-01-01

Soil microbial communities are responsible for a wide range of ecological processes and have an important economic impact in agriculture. Determining the metabolic processes performed by microbial communities is crucial for understanding and managing ecosystem properties. Metagenomic approaches allow the elucidation of the main metabolic processes that determine the performance of microbial communities under different environmental conditions and perturbations. Here we present the first compartmentalized metabolic reconstruction at a metagenomics scale of a microbial ecosystem. This systematic approach conceives a meta-organism without boundaries between individual organisms and allows the in silico evaluation of the effect of agricultural intervention on soils at a metagenomics level. To characterize the microbial ecosystems, topological properties, taxonomic and metabolic profiles, as well as a Flux Balance Analysis (FBA) were considered. Furthermore, topological and optimization algorithms were implemented to carry out the curation of the models, to ensure the continuity of the fluxes between the metabolic pathways, and to confirm the metabolite exchange between subcellular compartments. The proposed models provide specific information about ecosystems that are generally overlooked in non-compartmentalized or non-curated networks, like the influence of transport reactions in the metabolic processes, especially the important effect on mitochondrial processes, as well as provide more accurate results of the fluxes used to optimize the metabolic processes within the microbial community. PMID:28767679

Space images processing methodology for assessment of atmosphere pollution impact on forest-swamp territories

NASA Astrophysics Data System (ADS)

Polichtchouk, Yuri; Tokareva, Olga; Bulgakova, Irina V.

2003-03-01

Methodical problems of space images processing for assessment of atmosphere pollution impact on forest ecosystems using geoinformation systems are developed. An approach to quantitative assessment of atmosphere pollution impact on forest ecosystems is based on calculating relative squares of forest landscapes which are inside atmosphere pollution zones. Landscape structure of forested territories in the southern part of Western Siberia are determined on the basis of procession of middle resolution space images from spaceborn Resource-O. Particularities of atmosphere pollution zones modeling caused by gas burning in torches on territories of oil fields are considered. Pollution zones were revealed by modeling of contaminants dispersal in atmosphere with standard models. Polluted landscapes squares are calculated depending on atmosphere pollution level.

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

NASA Astrophysics Data System (ADS)

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

2013-02-01

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

Do microbial processes regulate the stability of a coral atoll's enclosed pelagic ecosystem?

EPA Science Inventory

Complex marine ecosystems contain multiple feedback cycles that can cause unexpected responses to perturbations. To better predict these responses, complicated models are increasingly being developed to enable the study of feedback cycles. However, the sparseness of ecological da...

Changing ecophysiological processes and carbon budget in East Asian ecosystems under near-future changes in climate: implications for long-term monitoring from a process-based model.

PubMed

Ito, Akihiko

2010-07-01

Using a process-based model, I assessed how ecophysiological processes would respond to near-future global changes predicted by coupled atmosphere-ocean climate models. An ecosystem model, Vegetation Integrative SImulator for Trace gases (VISIT), was applied to four sites in East Asia (different types of forest in Takayama, Tomakomai, and Fujiyoshida, Japan, and an Alpine grassland in Qinghai, China) where observational flux data are available for model calibration. The climate models predicted +1-3 degrees C warming and slight change in annual precipitation by 2050 as a result of an increase in atmospheric CO2. Gross primary production (GPP) was estimated to increase substantially at each site because of improved efficiency in the use of water and radiation. Although increased respiration partly offset the GPP increase, the simulation showed that these ecosystems would act as net carbon sinks independent of disturbance-induced uptake for recovery. However, the carbon budget response relied strongly on nitrogen availability, such that photosynthetic down-regulation resulting from leaf nitrogen dilution largely decreased GPP. In relation to long-term monitoring, these results indicate that the impacts of global warming may be more evident in gross fluxes (e.g., photosynthesis and respiration) than in the net CO2 budget, because changes in these fluxes offset each other.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

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

NASA Technical Reports Server (NTRS)

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

1998-01-01

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

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.

Change in terrestrial ecosystem water-use efficiency over the last three decades.

PubMed

Huang, Mengtian; Piao, Shilong; Sun, Yan; Ciais, Philippe; Cheng, Lei; Mao, Jiafu; Poulter, Ben; Shi, Xiaoying; Zeng, Zhenzhong; Wang, Yingping

2015-06-01

Defined as the ratio between gross primary productivity (GPP) and evapotranspiration (ET), ecosystem-scale water-use efficiency (EWUE) is an indicator of the adjustment of vegetation photosynthesis to water loss. The processes controlling EWUE are complex and reflect both a slow evolution of plants and plant communities as well as fast adjustments of ecosystem functioning to changes of limiting resources. In this study, we investigated EWUE trends from 1982 to 2008 using data-driven models derived from satellite observations and process-oriented carbon cycle models. Our findings suggest positive EWUE trends of 0.0056, 0.0007 and 0.0001 g C m(-2)  mm(-1)  yr(-1) under the single effect of rising CO2 ('CO2 '), climate change ('CLIM') and nitrogen deposition ('NDEP'), respectively. Global patterns of EWUE trends under different scenarios suggest that (i) EWUE-CO2 shows global increases, (ii) EWUE-CLIM increases in mainly high latitudes and decreases at middle and low latitudes, (iii) EWUE-NDEP displays slight increasing trends except in west Siberia, eastern Europe, parts of North America and central Amazonia. The data-driven MTE model, however, shows a slight decline of EWUE during the same period (-0.0005 g C m(-2)  mm(-1)  yr(-1) ), which differs from process-model (0.0064 g C m(-2)  mm(-1)  yr(-1) ) simulations with all drivers taken into account. We attribute this discrepancy to the fact that the nonmodeled physiological effects of elevated CO2 reducing stomatal conductance and transpiration (TR) in the MTE model. Partial correlation analysis between EWUE and climate drivers shows similar responses to climatic variables with the data-driven model and the process-oriented models across different ecosystems. Change in water-use efficiency defined from transpiration-based WUEt (GPP/TR) and inherent water-use efficiency (IWUEt , GPP×VPD/TR) in response to rising CO2 , climate change, and nitrogen deposition are also discussed. Our analyses will facilitate mechanistic understanding of the carbon-water interactions over terrestrial ecosystems under global change. © 2015 John Wiley & Sons Ltd.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-11-01

In the Mediterranean region, climate and land use change are expected to impact on natural and agricultural ecosystems by warming, reduced rainfall, direct degradation of ecosystems and biodiversity loss. Human population growth and socioeconomic changes, notably on the eastern and southern shores, will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (Lund-Potsdam-Jena managed Land - LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development paves the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments of the consequences of land use transitions, the influence of management practices and climate change impacts.

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.

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.

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

Empirically Derived and Simulated Sensitivity of Vegetation to Climate Across Global Gradients of Temperature and Precipitation

NASA Astrophysics Data System (ADS)

Quetin, G. R.; Swann, A. L. S.

2017-12-01

Successfully predicting the state of vegetation in a novel environment is dependent on our process level understanding of the ecosystem and its interactions with the environment. We derive a global empirical map of the sensitivity of vegetation to climate using the response of satellite-observed greenness and leaf area to interannual variations in temperature and precipitation. Our analysis provides observations of ecosystem functioning; the vegetation interactions with the physical environment, across a wide range of climates and provide a functional constraint for hypotheses engendered in process-based models. We infer mechanisms constraining ecosystem functioning by contrasting how the observed and simulated sensitivity of vegetation to climate varies across climate space. Our analysis yields empirical evidence for multiple physical and biological mediators of the sensitivity of vegetation to climate as a systematic change across climate space. Our comparison of remote sensing-based vegetation sensitivity with modeled estimates provides evidence for which physiological mechanisms - photosynthetic efficiency, respiration, water supply, atmospheric water demand, and sunlight availability - dominate the ecosystem functioning in places with different climates. Earth system models are generally successful in reproducing the broad sign and shape of ecosystem functioning across climate space. However, this general agreement breaks down in hot wet climates where models simulate less leaf area during a warmer year, while observations show a mixed response but overall more leaf area during warmer years. In addition, simulated ecosystem interaction with temperature is generally larger and changes more rapidly across a gradient of temperature than is observed. We hypothesize that the amplified interaction and change are both due to a lack of adaptation and acclimation in simulations. This discrepancy with observations suggests that simulated responses of vegetation to global warming, and feedbacks between vegetation and climate, are too strong in the models.

An Ecosystem Service Evaluation Tool to Support Ridge-to-Reef Management and Conservation in Hawaii

NASA Astrophysics Data System (ADS)

Oleson, K.; Callender, T.; Delevaux, J. M. S.; Falinski, K. A.; Htun, H.; Jin, G.

2014-12-01

Faced with increasing anthropogenic stressors and diverse stakeholders, local managers are adopting a ridge-to-reef and multi-objective management approach to restore declining coral reef health state. An ecosystem services framework, which integrates ecological indicators and stakeholder values, can foster more applied and integrated research, data collection, and modeling, and thus better inform the decision-making process and realize decision outcomes grounded in stakeholders' values. Here, we describe a research program that (i) leverages remotely sensed and empirical data to build an ecosystem services-based decision-support tool geared towards ridge-to-reef management; and (ii) applies it as part of a structured, value-based decision-making process to inform management in west Maui, a NOAA coral reef conservation priority site. The tool links terrestrial and marine biophysical models in a spatially explicit manner to quantify and map changes in ecosystem services delivery resulting from management actions, projected climate change impacts, and adaptive responses. We couple model outputs with localized valuation studies to translate ecosystem service outcomes into benefits and their associated socio-cultural and/or economic values. Managers can use this tool to run scenarios during their deliberations to evaluate trade-offs, cost-effectiveness, and equity implications of proposed policies. Ultimately, this research program aims at improving the effectiveness, efficiency, and equity outcomes of ecosystem-based management. This presentation will describe our approach, summarize initial results from the terrestrial modeling and economic valuations for west Maui, and highlight how this decision support tool benefits managers in west Maui.

An eddy covariance study of a spruce beetle outbreak on summertime evapotranspiration and ecosystem CO2 exchange and winter sublimation dynamics

NASA Astrophysics Data System (ADS)

Frank, John Michael

Water and carbon cycles are important from ecosystem to global scales because of their feedbacks with climate change and natural disturbance. In order to quantify both primary and compensating responses in an ecosystem under disturbance, an approach that observes the ecosystem in its entirety is preferred. In recent decades, the eddy covariance technique has become ubiquitous in modern ecosystem studies because its fundamental measurement scale integrates across an ecosystem. Yet, across flux networks a trend towards energy imbalance has implicated a systematic bias in these measurements that has no mechanistic explanation. This dissertation concentrates on a historical transducer shadowing correction for sonic anemometers, the fundamental instrument in eddy covariance studies, and whether the omission of it can explain these underestimated ecosystem fluxes. It then focuses on the response of water and carbon processes in a subalpine spruce-fir forest in southeastern Wyoming, USA that experienced 80% forested basal area mortality following a spruce beetle outbreak. To evaluate an uncertainty in eddy covariance measurements, a novel experiment is devised to test the consistency to which an omnidirectional sonic anemometer can measure the three dimensions, to compare of the effect of different designs and different manufacturers to link an underestimate in vertical wind velocity to the lack of transducer shadowing correction, and to construct a Bayesian model to estimate the three dimensional shadowing correction required to fix the problem. Results show that at the 60% of ecosystem flux sites in North American that use this equipment, their ecosystem flux measurements are probably underestimated by 8-12%. During the growing season, the change in ecosystem processes due to disturbance are explained through the physiological response of dying spruce trees and their observed mortality. Evapotranspiration declines immediately following the attack because of hydraulic failure due to the spruce beetle associated blue-stain fungi. In response, impacted spruce trees regulate their stomatal conductance and ecosystem photosynthesis declines slightly. A few years later these trees die and ecosystem photosynthesis falls by 50%. During winter, a Bayesian analysis shows a fundamental preference for ecosystem sublimation to originate from the canopy, which in combination with the loss of canopy and limited ability to intercept fresh snowfall, has led to substantially less total sublimation because of the outbreak. Because the ecosystem’s response to disturbance can be explained through physiological processes at the organism scale, this work provides an opportunity to test hypotheses about bottom up approaches and offers new insights into hydrological and ecological models. The anemometer error investigation and Bayesian analyses provide new tools to examine ecological phenomena that are uncertain or where no standard of “truth” is available. By demonstrating an ecosystem response that can be explained by the dominate species, implementing a two source energy and canopy mass model to explain ecosystem sublimation, investigating a prevalent error in the majority of eddy covariance systems, and advancing statistical analysis from which all of these processes can be inferred, this work as a whole is applicable to nearly all terrestrial ecosystem studies.

Disturbance Distance: Combining a process based ecosystem model and remote sensing data to map the vulnerability of U.S. forested ecosystems to potentially altered disturbance rates

NASA Astrophysics Data System (ADS)

Dolan, K. A.

2015-12-01

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. In addition, recent studies suggest that disturbance rates may increase in the future under altered climate and land use scenarios. Thus understanding how vulnerable forested ecosystems are to potential changes in disturbance rates is of high importance. This study calculated the theoretical threshold rate of disturbance for which forest ecosystems could no longer be sustained (λ*) across the Coterminous U.S. using an advanced process based ecosystem model (ED). Published rates of disturbance (λ) in 50 study sites were obtained from the North American Forest Disturbance (NAFD) program. Disturbance distance (λ* - λ) was calculated for each site by differencing the model based threshold under current climate conditions and average observed rates of disturbance over the last quarter century. Preliminary results confirm all sample forest sites have current average rates of disturbance below λ*, but there were interesting patterns in the recorded disturbance distances. In general western sites had much smaller disturbance distances, suggesting higher vulnerability to change, while eastern sites showed larger buffers. Ongoing work is being conducted to assess the vulnerability of these sites in the context of potential future changes by propagating scenarios of future climate and land-use change through the analysis.

Variational methods to estimate terrestrial ecosystem model parameters

NASA Astrophysics Data System (ADS)

Delahaies, Sylvain; Roulstone, Ian

2016-04-01

Carbon is at the basis of the chemistry of life. Its ubiquity in the Earth system is the result of complex recycling processes. Present in the atmosphere in the form of carbon dioxide it is adsorbed by marine and terrestrial ecosystems and stored within living biomass and decaying organic matter. Then soil chemistry and a non negligible amount of time transform the dead matter into fossil fuels. Throughout this cycle, carbon dioxide is released in the atmosphere through respiration and combustion of fossils fuels. Model-data fusion techniques allow us to combine our understanding of these complex processes with an ever-growing amount of observational data to help improving models and predictions. The data assimilation linked ecosystem carbon (DALEC) model is a simple box model simulating the carbon budget allocation for terrestrial ecosystems. Over the last decade several studies have demonstrated the relative merit of various inverse modelling strategies (MCMC, ENKF, 4DVAR) to estimate model parameters and initial carbon stocks for DALEC and to quantify the uncertainty in the predictions. Despite its simplicity, DALEC represents the basic processes at the heart of more sophisticated models of the carbon cycle. Using adjoint based methods we study inverse problems for DALEC with various data streams (8 days MODIS LAI, monthly MODIS LAI, NEE). The framework of constraint optimization allows us to incorporate ecological common sense into the variational framework. We use resolution matrices to study the nature of the inverse problems and to obtain data importance and information content for the different type of data. We study how varying the time step affect the solutions, and we show how "spin up" naturally improves the conditioning of the inverse problems.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

On the Need to Establish an International Soil Modeling Consortium

NASA Astrophysics Data System (ADS)

Vereecken, H.; Vanderborght, J.; Schnepf, A.

2014-12-01

Soil is one of the most critical life-supporting compartments of the Biosphere. Soil provides numerous ecosystem services such as a habitat for biodiversity, water and nutrients, as well as producing food, feed, fiber and energy. To feed the rapidly growing world population in 2050, agricultural food production must be doubled using the same land resources footprint. At the same time, soil resources are threatened due to improper management and climate change. Despite the many important functions of soil, many fundamental knowledge gaps remain, regarding the role of soil biota and biodiversity on ecosystem services, the structure and dynamics of soil communities, the interplay between hydrologic and biotic processes, the quantification of soil biogeochemical processes and soil structural processes, the resilience and recovery of soils from stress, as well as the prediction of soil development and the evolution of soils in the landscape, to name a few. Soil models have long played an important role in quantifying and predicting soil processes and related ecosystem services. However, a new generation of soil models based on a whole systems approach comprising all physical, mechanical, chemical and biological processes is now required to address these critical knowledge gaps and thus contribute to the preservation of ecosystem services, improve our understanding of climate-change-feedback processes, bridge basic soil science research and management, and facilitate the communication between science and society. To meet these challenges an international community effort is required, similar to initiatives in systems biology, hydrology, and climate and crop research. Our consortium will bring together modelers and experimental soil scientists at the forefront of new technologies and approaches to characterize soils. By addressing these aims, the consortium will contribute to improve the role of soil modeling as a knowledge dissemination instrument in addressing key global issues and stimulate the development of translational research activities. This presentation will provide a compelling case for this much-needed effort, with a focus on tangible benefits to the scientific and food security communities.

Nonlinear ecosystem services response to groundwater availability under climate extremes

NASA Astrophysics Data System (ADS)

Qiu, J.; Zipper, S. C.; Motew, M.; Booth, E.; Kucharik, C. J.; Steven, L. I.

2017-12-01

Depletion of groundwater has been accelerating at regional to global scales. Besides serving domestic, industrial and agricultural needs, in situ groundwater is also a key control on biological, physical and chemical processes across the critical zone, all of which underpin supply of ecosystem services essential for humanity. While there is a rich history of research on groundwater effects on subsurface and surface processes, understanding interactions, nonlinearity and feedbacks between groundwater and ecosystem services remain limited, and almost absent in the ecosystem service literature. Moreover, how climate extremes may alter groundwater effects on services is underexplored. In this research, we used a process-based ecosystem model (Agro-IBIS) to quantify groundwater effects on eight ecosystem services related to food, water and biogeochemical processes in an urbanizing agricultural watershed in the Midwest, USA. We asked: (1) Which ecosystem services are more susceptible to shallow groundwater influences? (2) Do effects of groundwater on ecosystem services vary under contrasting climate conditions (i.e., dry, wet and average)? (3) Where on the landscape are groundwater effects on ecosystem services most pronounced? (4) How do groundwater effects depend on water table depth? Overall, groundwater significantly impacted all services studied, with the largest effects on food production, water quality and quantity, and flood regulation services. Climate also mediated groundwater effects with the strongest effects occurring under dry climatic conditions. There was substantial spatial heterogeneity in groundwater effects across the landscape that is driven in part by spatial variations in water table depth. Most ecosystem services responded nonlinearly to groundwater availability, with most apparent groundwater effects occurring when the water table is shallower than a critical depth of 2.5-m. Our findings provide compelling evidence that groundwater plays a vital role in sustaining ecosystem services. Our research highlights the pressing need to consider groundwater during the assessment and management of ecosystem services, and suggests that protecting groundwater resources may enhance ecosystem service resilience to future climate extremes and increased climate variability.

Diurnal hysteresis between soil CO2 and soil temperature is controlled by soil water content

Treesearch

Diego A. Riveros-Iregui; Ryan E. Emanuel; Daniel J. Muth; L. McGlynn Brian; Howard E. Epstein; Daniel L. Welsch; Vincent J. Pacific; Jon M. Wraith

2007-01-01

Recent years have seen a growing interest in measuring and modeling soil CO2 efflux, as this flux represents a large component of ecosystem respiration and is a key determinant of ecosystem carbon balance. Process-based models of soil CO2 production and efflux, commonly based on soil temperature, are limited by nonlinearities such as the observed diurnal hysteresis...

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...

Higher biodiversity is required to sustain multiple ecosystem processes across temperature regimes

PubMed Central

Perkins, Daniel M; Bailey, R A; Dossena, Matteo; Gamfeldt, Lars; Reiss, Julia; Trimmer, Mark; Woodward, Guy

2015-01-01

Biodiversity loss is occurring rapidly worldwide, yet it is uncertain whether few or many species are required to sustain ecosystem functioning in the face of environmental change. The importance of biodiversity might be enhanced when multiple ecosystem processes (termed multifunctionality) and environmental contexts are considered, yet no studies have quantified this explicitly to date. We measured five key processes and their combined multifunctionality at three temperatures (5, 10 and 15 °C) in freshwater aquaria containing different animal assemblages (1–4 benthic macroinvertebrate species). For single processes, biodiversity effects were weak and were best predicted by additive-based models, i.e. polyculture performances represented the sum of their monoculture parts. There were, however, significant effects of biodiversity on multifunctionality at the low and the high (but not the intermediate) temperature. Variation in the contribution of species to processes across temperatures meant that greater biodiversity was required to sustain multifunctionality across different temperatures than was the case for single processes. This suggests that previous studies might have underestimated the importance of biodiversity in sustaining ecosystem functioning in a changing environment. PMID:25131335

Assessing simulated ecosystem processes for climate variability research at Glacier National Park, USA

USGS Publications Warehouse

White, J.D.; Running, S.W.; Thornton, P.E.; Keane, R.E.; Ryan, K.C.; Fagre, D.B.; Key, C.H.

1998-01-01

Glacier National Park served as a test site for ecosystem analyses than involved a suite of integrated models embedded within a geographic information system. The goal of the exercise was to provide managers with maps that could illustrate probable shifts in vegetation, net primary production (NPP), and hydrologic responses associated with two selected climatic scenarios. The climatic scenarios were (a) a recent 12-yr record of weather data, and (b) a reconstituted set that sequentially introduced in repeated 3-yr intervals wetter-cooler, drier-warmer, and typical conditions. To extrapolate the implications of changes in ecosystem processes and resulting growth and distribution of vegetation and snowpack, the model incorporated geographic data. With underlying digital elevation maps, soil depth and texture, extrapolated climate, and current information on vegetation types and satellite-derived estimates of a leaf area indices, simulations were extended to envision how the park might look after 120 yr. The predictions of change included underlying processes affecting the availability of water and nitrogen. Considerable field data were acquired to compare with model predictions under current climatic conditions. In general, the integrated landscape models of ecosystem processes had good agreement with measured NPP, snowpack, and streamflow, but the exercise revealed the difficulty and necessity of averaging point measurements across landscapes to achieve comparable results with modeled values. Under the extremely variable climate scenario significant changes in vegetation composition and growth as well as hydrologic responses were predicted across the park. In particular, a general rise in both the upper and lower limits of treeline was predicted. These shifts would probably occur along with a variety of disturbances (fire, insect, and disease outbreaks) as predictions of physiological stress (water, nutrients, light) altered competitive relations and hydrologic responses. The use of integrated landscape models applied in this exercise should provide managers with insights into the underlying processes important in maintaining community structure, and at the same time, locate where changes on the landscape are most likely to occur.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Climate change impacts on ecosystems and ecosystem services in the United States: Process and prospects for sustained assessment

USGS Publications Warehouse

Grimm, Nancy B.; Groffman, Peter M; Staudinger, Michelle D.; Tallis, Heather

2016-01-01

The third United States National Climate Assessment emphasized an evaluation of not just the impacts of climate change on species and ecosystems, but also the impacts of climate change on the benefits that people derive from nature, known as ecosystem services. The ecosystems, biodiversity, and ecosystem services component of the assessment largely drew upon the findings of a transdisciplinary workshop aimed at developing technical input for the assessment, involving participants from diverse sectors. A small author team distilled and synthesized this and hundreds of other technical input to develop the key findings of the assessment. The process of developing and ranking key findings hinged on identifying impacts that had particular, demonstrable effects on the U.S. public via changes in national ecosystem services. Findings showed that ecosystem services are threatened by the impacts of climate change on water supplies, species distributions and phenology, as well as multiple assaults on ecosystem integrity that, when compounded by climate change, reduce the capacity of ecosystems to buffer against extreme events. As ecosystems change, such benefits as water sustainability and protection from storms that are afforded by intact ecosystems are projected to decline across the continent due to climate change. An ongoing, sustained assessment that focuses on the co-production of actionable climate science will allow scientists from a range of disciplines to ascertain the capability of their forecasting models to project environmental and ecological change and link it to ecosystem services; additionally, an iterative process of evaluation, development of management strategies, monitoring, and reevaluation will increase the applicability and usability of the science by the U.S. public.

A comparative assessment of tools for ecosystem services quantification and valuation

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius; Waage, Sissel; Winthrop, Robert

2013-01-01

To enter widespread use, ecosystem service assessments need to be quantifiable, replicable, credible, flexible, and affordable. With recent growth in the field of ecosystem services, a variety of decision-support tools has emerged to support more systematic ecosystem services assessment. Despite the growing complexity of the tool landscape, thorough reviews of tools for identifying, assessing, modeling and in some cases monetarily valuing ecosystem services have generally been lacking. In this study, we describe 17 ecosystem services tools and rate their performance against eight evaluative criteria that gauge their readiness for widespread application in public- and private-sector decision making. We describe each of the tools′ intended uses, services modeled, analytical approaches, data requirements, and outputs, as well time requirements to run seven tools in a first comparative concurrent application of multiple tools to a common location – the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. Based on this work, we offer conclusions about these tools′ current ‘readiness’ for widespread application within both public- and private-sector decision making processes. Finally, we describe potential pathways forward to reduce the resource requirements for running ecosystem services models, which are essential to facilitate their more widespread use in environmental decision making.

Genetic information and ecosystem health: arguments for the application of chaos theory to identify boundary conditions for ecosystem management.

PubMed Central

Stomp, A M

1994-01-01

To meet the demands for goods and services of an exponentially growing human population, global ecosystems will come under increasing human management. The hallmark of successful ecosystem management will be long-term ecosystem stability. Ecosystems and the genetic information and processes which underlie interactions of organisms with the environment in populations and communities exhibit behaviors which have nonlinear characteristics. Nonlinear mathematical formulations describing deterministic chaos have been used successfully to model such systems in physics, chemistry, economics, physiology, and epidemiology. This approach can be extended to ecotoxicology and can be used to investigate how changes in genetic information determine the behavior of populations and communities. This article seeks to provide the arguments for such an approach and to give initial direction to the search for the boundary conditions within which lies ecosystem stability. The identification of a theoretical framework for ecotoxicology and the parameters which drive the underlying model is a critical component in the formulation of a prioritized research agenda and appropriate ecosystem management policy and regulation. PMID:7713038

Vegetation ecology meets ecosystem science: Permanent grasslands as a functional biogeography case study.

PubMed

Violle, Cyrille; Choler, Philippe; Borgy, Benjamin; Garnier, Eric; Amiaud, Bernard; Debarros, Guilhem; Diquelou, Sylvain; Gachet, Sophie; Jolivet, Claudy; Kattge, Jens; Lavorel, Sandra; Lemauviel-Lavenant, Servane; Loranger, Jessy; Mikolajczak, Alexis; Munoz, François; Olivier, Jean; Viovy, Nicolas

2015-11-15

The effect of biodiversity on ecosystem functioning has been widely acknowledged, and the importance of the functional roles of species, as well as their diversity, in the control of ecosystem processes has been emphasised recently. However, bridging biodiversity and ecosystem science to address issues at a biogeographic scale is still in its infancy. Bridging this gap is the primary goal of the emerging field of functional biogeography. While the rise of Big Data has catalysed functional biogeography studies in recent years, comprehensive evidence remains scarce. Here, we present the rationale and the first results of a country-wide initiative focused on the C3 permanent grasslands. We aimed to collate, integrate and process large databases of vegetation relevés, plant traits and environmental layers to provide a country-wide assessment of ecosystem properties and services which can be used to improve regional models of climate and land use changes. We outline the theoretical background, data availability, and ecoinformatics challenges associated with the approach and its feasibility. We provide a case study of upscaling of leaf dry matter content averaged at ecosystem level and country-wide predictions of forage digestibility. Our framework sets milestones for further hypothesis testing in functional biogeography and earth system modelling. Copyright © 2015 Elsevier B.V. All rights reserved.

Coupling Spatiotemporal Community Assembly Processes to Changes in Microbial Metabolism.

PubMed

Graham, Emily B; Crump, Alex R; Resch, Charles T; Fansler, Sarah; Arntzen, Evan; Kennedy, David W; Fredrickson, Jim K; Stegen, James C

2016-01-01

Community assembly processes generate shifts in species abundances that influence ecosystem cycling of carbon and nutrients, yet our understanding of assembly remains largely separate from ecosystem-level functioning. Here, we investigate relationships between assembly and changes in microbial metabolism across space and time in hyporheic microbial communities. We pair sampling of two habitat types (i.e., attached and planktonic) through seasonal and sub-hourly hydrologic fluctuation with null modeling and temporally explicit multivariate statistics. We demonstrate that multiple selective pressures-imposed by sediment and porewater physicochemistry-integrate to generate changes in microbial community composition at distinct timescales among habitat types. These changes in composition are reflective of contrasting associations of Betaproteobacteria and Thaumarchaeota with ecological selection and with seasonal changes in microbial metabolism. We present a conceptual model based on our results in which metabolism increases when oscillating selective pressures oppose temporally stable selective pressures. Our conceptual model is pertinent to both macrobial and microbial systems experiencing multiple selective pressures and presents an avenue for assimilating community assembly processes into predictions of ecosystem-level functioning.

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

Science in the public process of ecosystem management: lessons from Hawaii, Southeast Asia, Africa and the US Mainland.

PubMed

Gutrich, John; Donovan, Deanna; Finucane, Melissa; Focht, Will; Hitzhusen, Fred; Manopimoke, Supachit; McCauley, David; Norton, Bryan; Sabatier, Paul; Salzman, Jim; Sasmitawidjaja, Virza

2005-08-01

Partnerships and co-operative environmental management are increasing worldwide as is the call for scientific input in the public process of ecosystem management. In Hawaii, private landowners, non-governmental organizations, and state and federal agencies have formed watershed partnerships to conserve and better manage upland forested watersheds. In this paper, findings of an international workshop convened in Hawaii to explore the strengths of approaches used to assess stakeholder values of environmental resources and foster consensus in the public process of ecosystem management are presented. Authors draw upon field experience in projects throughout Hawaii, Southeast Asia, Africa and the US mainland to derive a set of lessons learned that can be applied to Hawaiian and other watershed partnerships in an effort to promote consensus and sustainable ecosystem management. Interdisciplinary science-based models can serve as effective tools to identify areas of potential consensus in the process of ecosystem management. Effective integration of scientific input in co-operative ecosystem management depends on the role of science, the stakeholders and decision-makers involved, and the common language utilized to compare tradeoffs. Trust is essential to consensus building and the integration of scientific input must be transparent and inclusive of public feedback. Consideration of all relevant stakeholders and the actual benefits and costs of management activities to each stakeholder is essential. Perceptions and intuitive responses of people can be as influential as analytical processes in decision-making and must be addressed. Deliberative, dynamic and iterative decision-making processes all influence the level of stakeholder achievement of consensus. In Hawaii, application of lessons learned can promote more informed and democratic decision processes, quality scientific analysis that is relevant, and legitimacy and public acceptance of ecosystem management.

Ecosystem Research in EPA: Process Studies, Field Investigations, and Integrated Environmental Modeling

EPA Science Inventory

The Ecosystems Research Division (ERD) is located in Athens, GA, USA. The research goals of ERD is to assess and quantify pathways and transformations of contaminants in the environment and to determine how physical changes (e.g., development, mining roads, green infrastructure, ...

Estimating the ecology of extinct species with paleoecological data assimilation

NASA Astrophysics Data System (ADS)

Raiho, A.; McLachlan, J. S.; Dietze, M.

2017-12-01

In order to understand long term, unobservable ecosystem processes, ecologists must use both paleoecoloigcal data and ecosystem models. Models parameterize species competitive interactions using modern data. But, modern ecological or physiological observations are not available for extinct species, making it difficult for models to conceptualize their ecology. For instance, American chestnut (Castanea dentata), who played a large role in forests of northeastern US, was decimated by disease to virtual extinction. Since chestnut's demise, defining its ecology has been controversial. Models typically assume that chestnut's ecology was very similar to oak; They parameterize chestnut like oak species. These assumptions are drawn from paleoecological data, but these data are often reported without uncertainty. Since the paleoecological data are often reported without uncertainty, paleoecological data has never been directly incorporated with ecosystem models. We developed a Bayesian statistical model to estimate fractional composition from paleoecological data with uncertainty. Then, we assimilated this data product into an ecosystem model for long term forest succession using a generalized ensemble adjustment filter to determine which species demographic parameters lead to changes in species composition over the last 2,000 years at Harvard Forest. We found that chestnut was strongly negatively correlated with white pine (Pinus strobus) and red oak (Quercus rubra) in the process covariance matrix, suggesting a strong competitive interaction that is not currently understood by models for forest succession. These findings provide support for utilizing a data assimilation framework to ecologically interpret paleoecological data or data products to learn about the ecology of extinct species.

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

NASA Technical Reports Server (NTRS)

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

2004-01-01

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

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.

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.

Decomposition

USGS Publications Warehouse

Middleton, Beth A.

2014-01-01

A cornerstone of ecosystem ecology, decomposition was recognized as a fundamental process driving the exchange of energy in ecosystems by early ecologists such as Lindeman 1942 and Odum 1960). In the history of ecology, studies of decomposition were incorporated into the International Biological Program in the 1960s to compare the nature of organic matter breakdown in various ecosystem types. Such studies still have an important role in ecological studies of today. More recent refinements have brought debates on the relative role microbes, invertebrates and environment in the breakdown and release of carbon into the atmosphere, as well as how nutrient cycling, production and other ecosystem processes regulated by decomposition may shift with climate change. Therefore, this bibliography examines the primary literature related to organic matter breakdown, but it also explores topics in which decomposition plays a key supporting role including vegetation composition, latitudinal gradients, altered ecosystems, anthropogenic impacts, carbon storage, and climate change models. Knowledge of these topics is relevant to both the study of ecosystem ecology as well projections of future conditions for human societies.

[Environmental quality assessment of regional agro-ecosystem in Loess Plateau].

PubMed

Wang, Limei; Meng, Fanping; Zheng, Jiyong; Wang, Zhonglin

2004-03-01

Based on the detection and analysis of the contamination status of agro-ecosystem with apple-crops intercropping as the dominant cropping model in Loess Plateau, the individual factor and comprehensive environmental quality were assessed by multilevel fuzzy synthetic evaluation model, analytical hierarchy process(AHP), and improved standard weight deciding method. The results showed that the quality of soil, water and agricultural products was grade I, the social economical environmental quality was grade II, the ecological environmental quality was grade III, and the comprehensive environmental quality was grade I. The regional agro-ecosystem dominated by apple-crops intercropping was not the best model for the ecological benefits, but had the better social economical benefits.

Effects of fire on major forest ecosystem processes: an overview.

PubMed

Chen, Zhong

2006-09-01

Fire and fire ecology are among the best-studied topics in contemporary ecosystem ecology. The large body of existing literature on fire and fire ecology indicates an urgent need to synthesize the information on the pattern of fire effects on ecosystem composition, structure, and functions for application in fire and ecosystem management. Understanding fire effects and underlying principles are critical to reduce the risk of uncharacteristic wildfires and for proper use of fire as an effective management tool toward management goals. This overview is a synthesis of current knowledge on major effects of fire on fire-prone ecosystems, particularly those in the boreal and temperate regions of the North America. Four closely related ecosystem processes in vegetation dynamics, nutrient cycling, soil and belowground process and water relations were discussed with emphases on fire as the driving force. Clearly, fire can shape ecosystem composition, structure and functions by selecting fire adapted species and removing other susceptible species, releasing nutrients from the biomass and improving nutrient cycling, affecting soil properties through changing soil microbial activities and water relations, and creating heterogeneous mosaics, which in turn, can further influence fire behavior and ecological processes. Fire as a destructive force can rapidly consume large amount of biomass and cause negative impacts such as post-fire soil erosion and water runoff, and air pollution; however, as a constructive force fire is also responsible for maintaining the health and perpetuity of certain fire-dependent ecosystems. Considering the unique ecological roles of fire in mediating and regulating ecosystems, fire should be incorporated as an integral component of ecosystems and management. However, the effects of fire on an ecosystem depend on the fire regime, vegetation type, climate, physical environments, and the scale of time and space of assessment. More ecosystem-specific studies are needed in future, especially those focusing on temporal and spatial variations of fire effects through long-term experimental monitoring and modeling.

Examining responses of ecosystem carbon exchange to environmental changes using particle filtering mathod

NASA Astrophysics Data System (ADS)

Yokozawa, M.

2017-12-01

Attention has been paid to the agricultural field that could regulate ecosystem carbon exchange by water management and residual treatments. However, there have been less known about the dynamic responses of the ecosystem to environmental changes. In this study, focussing on paddy field, where CO2 emissions due to microbial decomposition of organic matter are suppressed and alternatively CH4 emitted under flooding condition during rice growth season and subsequently CO2 emission following the fallow season after harvest, the responses of ecosystem carbon exchange were examined. We conducted model data fusion analysis for examining the response of cropland-atmosphere carbon exchange to environmental variation. The used model consists of two sub models, paddy rice growth sub-model and soil decomposition sub-model. The crop growth sub-model mimics the rice plant growth processes including formation of reproductive organs as well as leaf expansion. The soil decomposition sub-model simulates the decomposition process of soil organic carbon. Assimilating the data on the time changes in CO2 flux measured by eddy covariance method, rice plant biomass, LAI and the final yield with the model, the parameters were calibrated using a stochastic optimization algorithm with a particle filter method. The particle filter method, which is one of the Monte Carlo filters, enable us to evaluating time changes in parameters based on the observed data until the time and to make prediction of the system. Iterative filtering and prediction with changing parameters and/or boundary condition enable us to obtain time changes in parameters governing the crop production as well as carbon exchange. In this study, we focused on the parameters related to crop production as well as soil carbon storage. As the results, the calibrated model with estimated parameters could accurately predict the NEE flux in the subsequent years. The temperature sensitivity, denoted by Q10s in the decomposition rate of soil organic carbon (SOC) were obtained as 1.4 for no cultivation period and 2.9 for cultivation period (submerged soil condition in flooding season). It suggests that the response of ecosystem carbon exchange differs due to SOC decomposition process which is sensitive to environmental variation during paddy rice cultivation period.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Uncertainty and inference in the world of paleoecological data

NASA Astrophysics Data System (ADS)

McLachlan, J. S.; Dawson, A.; Dietze, M.; Finley, M.; Hooten, M.; Itter, M.; Jackson, S. T.; Marlon, J. R.; Raiho, A.; Tipton, J.; Williams, J.

2017-12-01

Proxy data in paleoecology and paleoclimatology share a common set of biases and uncertainties: spatiotemporal error associated with the taphonomic processes of deposition, preservation, and dating; calibration error between proxy data and the ecosystem states of interest; and error in the interpolation of calibrated estimates across space and time. Researchers often account for this daunting suite of challenges by applying qualitave expert judgment: inferring the past states of ecosystems and assessing the level of uncertainty in those states subjectively. The effectiveness of this approach can be seen by the extent to which future observations confirm previous assertions. Hierarchical Bayesian (HB) statistical approaches allow an alternative approach to accounting for multiple uncertainties in paleo data. HB estimates of ecosystem state formally account for each of the common uncertainties listed above. HB approaches can readily incorporate additional data, and data of different types into estimates of ecosystem state. And HB estimates of ecosystem state, with associated uncertainty, can be used to constrain forecasts of ecosystem dynamics based on mechanistic ecosystem models using data assimilation. Decisions about how to structure an HB model are also subjective, which creates a parallel framework for deciding how to interpret data from the deep past.Our group, the Paleoecological Observatory Network (PalEON), has applied hierarchical Bayesian statistics to formally account for uncertainties in proxy based estimates of past climate, fire, primary productivity, biomass, and vegetation composition. Our estimates often reveal new patterns of past ecosystem change, which is an unambiguously good thing, but we also often estimate a level of uncertainty that is uncomfortably high for many researchers. High levels of uncertainty are due to several features of the HB approach: spatiotemporal smoothing, the formal aggregation of multiple types of uncertainty, and a coarseness in statistical models of taphonomic process. Each of these features provides useful opportunities for statisticians and data-generating researchers to assess what we know about the signal and the noise in paleo data and to improve inference about past changes in ecosystem state.

Bridging Food Webs, Ecosystem Metabolism, and Biogeochemistry Using Ecological Stoichiometry Theory.

PubMed

Welti, Nina; Striebel, Maren; Ulseth, Amber J; Cross, Wyatt F; DeVilbiss, Stephen; Glibert, Patricia M; Guo, Laodong; Hirst, Andrew G; Hood, Jim; Kominoski, John S; MacNeill, Keeley L; Mehring, Andrew S; Welter, Jill R; Hillebrand, Helmut

2017-01-01

Although aquatic ecologists and biogeochemists are well aware of the crucial importance of ecosystem functions, i.e., how biota drive biogeochemical processes and vice-versa, linking these fields in conceptual models is still uncommon. Attempts to explain the variability in elemental cycling consequently miss an important biological component and thereby impede a comprehensive understanding of the underlying processes governing energy and matter flow and transformation. The fate of multiple chemical elements in ecosystems is strongly linked by biotic demand and uptake; thus, considering elemental stoichiometry is important for both biogeochemical and ecological research. Nonetheless, assessments of ecological stoichiometry (ES) often focus on the elemental content of biota rather than taking a more holistic view by examining both elemental pools and fluxes (e.g., organismal stoichiometry and ecosystem process rates). ES theory holds the promise to be a unifying concept to link across hierarchical scales of patterns and processes in ecology, but this has not been fully achieved. Therefore, we propose connecting the expertise of aquatic ecologists and biogeochemists with ES theory as a common currency to connect food webs, ecosystem metabolism, and biogeochemistry, as they are inherently concatenated by the transfer of carbon, nitrogen, and phosphorous through biotic and abiotic nutrient transformation and fluxes. Several new studies exist that demonstrate the connections between food web ecology, biogeochemistry, and ecosystem metabolism. In addition to a general introduction into the topic, this paper presents examples of how these fields can be combined with a focus on ES. In this review, a series of concepts have guided the discussion: (1) changing biogeochemistry affects trophic interactions and ecosystem processes by altering the elemental ratios of key species and assemblages; (2) changing trophic dynamics influences the transformation and fluxes of matter across environmental boundaries; (3) changing ecosystem metabolism will alter the chemical diversity of the non-living environment. Finally, we propose that using ES to link nutrient cycling, trophic dynamics, and ecosystem metabolism would allow for a more holistic understanding of ecosystem functions in a changing environment.

Embedding ecosystem services in coastal planning leads to better outcomes for people and nature

PubMed Central

Arkema, Katie K.; Verutes, Gregory M.; Wood, Spencer A.; Clarke-Samuels, Chantalle; Rosado, Samir; Canto, Maritza; Rosenthal, Amy; Ruckelshaus, Mary; Guannel, Gregory; Toft, Jodie; Faries, Joe; Silver, Jessica M.; Griffin, Robert; Guerry, Anne D.

2015-01-01

Recent calls for ocean planning envision informed management of social and ecological systems to sustain delivery of ecosystem services to people. However, until now, no coastal and marine planning process has applied an ecosystem-services framework to understand how human activities affect the flow of benefits, to create scenarios, and to design a management plan. We developed models that quantify services provided by corals, mangroves, and seagrasses. We used these models within an extensive engagement process to design a national spatial plan for Belize’s coastal zone. Through iteration of modeling and stakeholder engagement, we developed a preferred plan, currently under formal consideration by the Belizean government. Our results suggest that the preferred plan will lead to greater returns from coastal protection and tourism than outcomes from scenarios oriented toward achieving either conservation or development goals. The plan will also reduce impacts to coastal habitat and increase revenues from lobster fishing relative to current management. By accounting for spatial variation in the impacts of coastal and ocean activities on benefits that ecosystems provide to people, our models allowed stakeholders and policymakers to refine zones of human use. The final version of the preferred plan improved expected coastal protection by >25% and more than doubled the revenue from fishing, compared with earlier versions based on stakeholder preferences alone. Including outcomes in terms of ecosystem-service supply and value allowed for explicit consideration of multiple benefits from oceans and coasts that typically are evaluated separately in management decisions. PMID:26082545

Embedding ecosystem services in coastal planning leads to better outcomes for people and nature.

PubMed

Arkema, Katie K; Verutes, Gregory M; Wood, Spencer A; Clarke-Samuels, Chantalle; Rosado, Samir; Canto, Maritza; Rosenthal, Amy; Ruckelshaus, Mary; Guannel, Gregory; Toft, Jodie; Faries, Joe; Silver, Jessica M; Griffin, Robert; Guerry, Anne D

2015-06-16

Recent calls for ocean planning envision informed management of social and ecological systems to sustain delivery of ecosystem services to people. However, until now, no coastal and marine planning process has applied an ecosystem-services framework to understand how human activities affect the flow of benefits, to create scenarios, and to design a management plan. We developed models that quantify services provided by corals, mangroves, and seagrasses. We used these models within an extensive engagement process to design a national spatial plan for Belize's coastal zone. Through iteration of modeling and stakeholder engagement, we developed a preferred plan, currently under formal consideration by the Belizean government. Our results suggest that the preferred plan will lead to greater returns from coastal protection and tourism than outcomes from scenarios oriented toward achieving either conservation or development goals. The plan will also reduce impacts to coastal habitat and increase revenues from lobster fishing relative to current management. By accounting for spatial variation in the impacts of coastal and ocean activities on benefits that ecosystems provide to people, our models allowed stakeholders and policymakers to refine zones of human use. The final version of the preferred plan improved expected coastal protection by >25% and more than doubled the revenue from fishing, compared with earlier versions based on stakeholder preferences alone. Including outcomes in terms of ecosystem-service supply and value allowed for explicit consideration of multiple benefits from oceans and coasts that typically are evaluated separately in management decisions.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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.

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.

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

EPA Science Inventory

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

Towards an integrated understanding of how micro scale processes shape groundwater ecosystem functions.

PubMed

Schmidt, Susanne I; Cuthbert, Mark O; Schwientek, Marc

2017-08-15

Micro scale processes are expected to have a fundamental role in shaping groundwater ecosystems and yet they remain poorly understood and under-researched. In part, this is due to the fact that sampling is rarely carried out at the scale at which microorganisms, and their grazers and predators, function and thus we lack essential information. While set within a larger scale framework in terms of geochemical features, supply with energy and nutrients, and exchange intensity and dynamics, the micro scale adds variability, by providing heterogeneous zones at the micro scale which enable a wider range of redox reactions. Here we outline how understanding micro scale processes better may lead to improved appreciation of the range of ecosystems functions taking place at all scales. Such processes are relied upon in bioremediation and we demonstrate that ecosystem modelling as well as engineering measures have to take into account, and use, understanding at the micro scale. We discuss the importance of integrating faunal processes and computational appraisals in research, in order to continue to secure sustainable water resources from groundwater. Copyright © 2017 Elsevier B.V. All rights reserved.

Regional and climate forcing on forage fish and apex predators in the California Current: new insights from a fully coupled ecosystem model.

NASA Astrophysics Data System (ADS)

Fiechter, J.; Rose, K.; Curchitser, E. N.; Huckstadt, L. A.; Costa, D. P.; Hedstrom, K.

2016-12-01

A fully coupled ecosystem model is used to describe the impact of regional and climate variability on changes in abundance and distribution of forage fish and apex predators in the California Current Large Marine Ecosystem. The ecosystem model consists of a biogeochemical submodel (NEMURO) embedded in a regional ocean circulation submodel (ROMS), and both coupled with a multi-species individual-based submodel for two forage fish species (sardine and anchovy) and one apex predator (California sea lion). Sardine and anchovy are specifically included in the model as they exhibit significant interannual and decadal variability in population abundances, and are commonly found in the diet of California sea lions. Output from the model demonstrates how regional-scale (i.e., upwelling intensity) and basin-scale (i.e., PDO and ENSO signals) physical processes control species distributions and predator-prey interactions on interannual time scales. The results also illustrate how variability in environmental conditions leads to the formation of seasonal hotspots where prey and predator spatially overlap. While specifically focused on sardine, anchovy and sea lions, the modeling framework presented here can provide new insights into the physical and biological mechanisms controlling trophic interactions in the California Current, or other regions where similar end-to-end ecosystem models may be implemented.

An exactly solvable coarse-grained model for species diversity

NASA Astrophysics Data System (ADS)

Suweis, Samir; Rinaldo, Andrea; Maritan, Amos

2012-07-01

We present novel analytical results concerning ecosystem species diversity that stem from a proposed coarse-grained neutral model based on birth-death processes. The relevance of the problem lies in the urgency for understanding and synthesizing both theoretical results from ecological neutral theory and empirical evidence on species diversity preservation. The neutral model of biodiversity deals with ecosystems at the same trophic level, where per capita vital rates are assumed to be species independent. Closed-form analytical solutions for the neutral theory are obtained within a coarse-grained model, where the only input is the species persistence time distribution. Our results pertain to: the probability distribution function of the number of species in the ecosystem, both in transient and in stationary states; the n-point connected time correlation function; and the survival probability, defined as the distribution of time spans to local extinction for a species randomly sampled from the community. Analytical predictions are also tested on empirical data from an estuarine fish ecosystem. We find that emerging properties of the ecosystem are very robust and do not depend on specific details of the model, with implications for biodiversity and conservation biology.

When does diversity matter? Species functional diversity and ecosystem functioning across habitats and seasons in a field experiment.

PubMed

Frainer, André; McKie, Brendan G; Malmqvist, Björn

2014-03-01

Despite ample experimental evidence indicating that biodiversity might be an important driver of ecosystem processes, its role in the functioning of real ecosystems remains unclear. In particular, the understanding of which aspects of biodiversity are most important for ecosystem functioning, their importance relative to other biotic and abiotic drivers, and the circumstances under which biodiversity is most likely to influence functioning in nature, is limited. We conducted a field study that focussed on a guild of insect detritivores in streams, in which we quantified variation in the process of leaf decomposition across two habitats (riffles and pools) and two seasons (autumn and spring). The study was conducted in six streams, and the same locations were sampled in the two seasons. With the aid of structural equations modelling, we assessed spatiotemporal variation in the roles of three key biotic drivers in this process: functional diversity, quantified based on a species trait matrix, consumer density and biomass. Our models also accounted for variability related to different litter resources, and other sources of biotic and abiotic variability among streams. All three of our focal biotic drivers influenced leaf decomposition, but none was important in all habitats and seasons. Functional diversity had contrasting effects on decomposition between habitats and seasons. A positive relationship was observed in pool habitats in spring, associated with high trait dispersion, whereas a negative relationship was observed in riffle habitats during autumn. Our results demonstrate that functional biodiversity can be as significant for functioning in natural ecosystems as other important biotic drivers. In particular, variation in the role of functional diversity between seasons highlights the importance of fluctuations in the relative abundances of traits for ecosystem process rates in real ecosystems. © 2013 The Authors. Journal of Animal Ecology © 2013 British Ecological Society.

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.

Population density of North American elk: effects on plant diversity.

PubMed

Stewart, Kelley M; Bowyer, R Terry; Kie, John G; Dick, Brian L; Ruess, Roger W

2009-08-01

Large, herbivorous mammals have profound effects on ecosystem structure and function and often act as keystone species in ecosystems they inhabit. Density-dependent processes associated with population structure of large mammals may interact with ecosystem functioning to increase or decrease biodiversity, depending on the relationship of herbivore populations relative to the carrying capacity (K) of the ecosystem. We tested for indirect effects of population density of large herbivores on plant species richness and diversity in a montane ecosystem, where increased net aboveground primary productivity (NAPP) in response to low levels of herbivory has been reported. We documented a positive, linear relationship between plant-species diversity and richness with NAPP. Structural equation modeling revealed significant indirect relationships between population density of herbivores, NAPP, and species diversity. We observed an indirect effect of density-dependent processes in large, herbivorous mammals and species diversity of plants through changes in NAPP in this montane ecosystem. Changes in species diversity of plants in response to herbivory may be more indirect in ecosystems with long histories of herbivory. Those subtle or indirect effects of herbivory may have strong effects on ecosystem functioning, but may be overlooked in plant communities that are relatively resilient to herbivory.

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.

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.

An operational model for mainstreaming ecosystem services for implementation

PubMed Central

Cowling, Richard M.; Egoh, Benis; Knight, Andrew T.; O'Farrell, Patrick J.; Reyers, Belinda; Rouget, Mathieu; Roux, Dirk J.; Welz, Adam; Wilhelm-Rechman, Angelika

2008-01-01

Research on ecosystem services has grown markedly in recent years. However, few studies are embedded in a social process designed to ensure effective management of ecosystem services. Most research has focused only on biophysical and valuation assessments of putative services. As a mission-oriented discipline, ecosystem service research should be user-inspired and user-useful, which will require that researchers respond to stakeholder needs from the outset and collaborate with them in strategy development and implementation. Here we provide a pragmatic operational model for achieving the safeguarding of ecosystem services. The model comprises three phases: assessment, planning, and management. Outcomes of social, biophysical, and valuation assessments are used to identify opportunities and constraints for implementation. The latter then are transformed into user-friendly products to identify, with stakeholders, strategic objectives for implementation (the planning phase). The management phase undertakes and coordinates actions that achieve the protection of ecosystem services and ensure the flow of these services to beneficiaries. This outcome is achieved via mainstreaming, or incorporating the safeguarding of ecosystem services into the policies and practices of sectors that deal with land- and water-use planning. Management needs to be adaptive and should be institutionalized in a suite of learning organizations that are representative of the sectors that are concerned with decision-making and planning. By following the phases of our operational model, projects for safeguarding ecosystem services are likely to empower stakeholders to implement effective on-the-ground management that will achieve resilience of the corresponding social-ecological systems. PMID:18621695

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

USGS Publications Warehouse

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

2005-01-01

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

Establishing an International Soil Modelling Consortium

NASA Astrophysics Data System (ADS)

Vereecken, Harry; Schnepf, Andrea; Vanderborght, Jan

2015-04-01

Soil is one of the most critical life-supporting compartments of the Biosphere. Soil provides numerous ecosystem services such as a habitat for biodiversity, water and nutrients, as well as producing food, feed, fiber and energy. To feed the rapidly growing world population in 2050, agricultural food production must be doubled using the same land resources footprint. At the same time, soil resources are threatened due to improper management and climate change. Soil is not only essential for establishing a sustainable bio-economy, but also plays a key role also in a broad range of societal challenges including 1) climate change mitigation and adaptation, 2) land use change 3) water resource protection, 4) biotechnology for human health, 5) biodiversity and ecological sustainability, and 6) combating desertification. Soils regulate and support water, mass and energy fluxes between the land surface, the vegetation, the atmosphere and the deep subsurface and control storage and release of organic matter affecting climate regulation and biogeochemical cycles. Despite the many important functions of soil, many fundamental knowledge gaps remain, regarding the role of soil biota and biodiversity on ecosystem services, the structure and dynamics of soil communities, the interplay between hydrologic and biotic processes, the quantification of soil biogeochemical processes and soil structural processes, the resilience and recovery of soils from stress, as well as the prediction of soil development and the evolution of soils in the landscape, to name a few. Soil models have long played an important role in quantifying and predicting soil processes and related ecosystem services. However, a new generation of soil models based on a whole systems approach comprising all physical, mechanical, chemical and biological processes is now required to address these critical knowledge gaps and thus contribute to the preservation of ecosystem services, improve our understanding of climate-change-feedback processes, bridge basic soil science research and management, and facilitate the communication between science and society . To meet these challenges an international community effort is required, similar to initiatives in systems biology, hydrology, and climate and crop research. We therefore propose to establish an international soil modelling consortium with the aims of 1) bringing together leading experts in modelling soil processes within all major soil disciplines, 2) addressing major scientific gaps in describing key processes and their long term impacts with respect to the different functions and ecosystem services provided by soil, 3) intercomparing soil model performance based on standardized and harmonized data sets, 4) identifying interactions with other relevant platforms related to common data formats, protocols and ontologies, 5) developing new approaches to inverse modelling, calibration, and validation of soil models, 6) integrating soil modelling expertise and state of the art knowledge on soil processes in climate, land surface, ecological, crop and contaminant models, and 7) linking process models with new observation, measurement and data evaluation technologies for mapping and characterizing soil properties across scales. Our consortium will bring together modelers and experimental soil scientists at the forefront of new technologies and approaches to characterize soils. By addressing these aims, the consortium will contribute to improve the role of soil modeling as a knowledge dissemination instrument in addressing key global issues and stimulate the development of translational research activities. This presentation will provide a compelling case for this much-needed effort, with a focus on tangible benefits to the scientific and food security communities.

Using an ecosystem service decision support tool to support ridge to reef management: An example of sediment reduction in west Maui, Hawaii

NASA Astrophysics Data System (ADS)

Falinski, K. A.; Oleson, K.; Htun, H.; Kappel, C.; Lecky, J.; Rowe, C.; Selkoe, K.; White, C.

2016-12-01

Faced with anthropogenic stressors and declining coral reef states, managers concerned with restoration and resilience of coral reefs are increasingly recognizing the need to take a ridge-to-reef, ecosystem-based approach. An ecosystem services framing can help managers move towards these goals, helping to illustrate trade-offs and opportunities of management actions in terms of their impacts on society. We describe a research program building a spatial ecosystem services-based decision-support tool, and being applied to guide ridge-to-reef management in a NOAA priority site in West Maui. We use multiple modeling methods to link biophysical processes to ecosystem services and their spatial flows and social values in an integrating platform. Modeled services include water availability, sediment retention, nutrient retention and carbon sequestration on land. A coral reef ecosystem service model is under development to capture the linkages between terrestrial and coastal ecosystem services. Valuation studies are underway to quantify the implications for human well-being. The tool integrates techniques from decision science to facilitate decision making. We use the sediment retention model to illustrate the types of analyses the tool can support. The case study explores the tradeoffs between road rehabilitation costs and sediment export avoided. We couple the sediment and cost models with trade-off analysis to identify optimal distributed solutions that are most cost-effective in reducing erosion, and then use those models to estimate sediment exposure to coral reefs. We find that cooperation between land owners reveals opportunities for maximizing the benefits of fixing roads and minimizes costs. This research forms the building blocks of an ecosystem service decision support tool that we intend to continue to test and apply in other Pacific Island settings.

A practical approach for comparing management strategies in complex forest ecosystems using meta-modelling toolkits

Treesearch

Andrew Fall; B. Sturtevant; M.-J. Fortin; M. Papaik; F. Doyon; D. Morgan; K. Berninger; C. Messier

2010-01-01

The complexity and multi-scaled nature of forests poses significant challenges to understanding and management. Models can provide useful insights into process and their interactions, and implications of alternative management options. Most models, particularly scientific models, focus on a relatively small set of processes and are designed to operate within a...

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.

Temperature-dependence of biomass accumulation rates during secondary succession.

PubMed

Anderson, Kristina J; Allen, Andrew P; Gillooly, James F; Brown, James H

2006-06-01

Rates of ecosystem recovery following disturbance affect many ecological processes, including carbon cycling in the biosphere. Here, we present a model that predicts the temperature dependence of the biomass accumulation rate following disturbances in forests. Model predictions are derived based on allometric and biochemical principles that govern plant energetics and are tested using a global database of 91 studies of secondary succession compiled from the literature. The rate of biomass accumulation during secondary succession increases with average growing season temperature as predicted based on the biochemical kinetics of photosynthesis in chloroplasts. In addition, the rate of biomass accumulation is greater in angiosperm-dominated communities than in gymnosperm-dominated ones and greater in plantations than in naturally regenerating stands. By linking the temperature-dependence of photosynthesis to the rate of whole-ecosystem biomass accumulation during secondary succession, our model and results provide one example of how emergent, ecosystem-level rate processes can be predicted based on the kinetics of individual metabolic rate.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Parameter optimization, sensitivity, and uncertainty analysis of an ecosystem model at a forest flux tower site in the United States

USGS Publications Warehouse

Wu, Yiping; Liu, Shuguang; Huang, Zhihong; Yan, Wende

2014-01-01

Ecosystem models are useful tools for understanding ecological processes and for sustainable management of resources. In biogeochemical field, numerical models have been widely used for investigating carbon dynamics under global changes from site to regional and global scales. However, it is still challenging to optimize parameters and estimate parameterization uncertainty for complex process-based models such as the Erosion Deposition Carbon Model (EDCM), a modified version of CENTURY, that consider carbon, water, and nutrient cycles of ecosystems. This study was designed to conduct the parameter identifiability, optimization, sensitivity, and uncertainty analysis of EDCM using our developed EDCM-Auto, which incorporated a comprehensive R package—Flexible Modeling Framework (FME) and the Shuffled Complex Evolution (SCE) algorithm. Using a forest flux tower site as a case study, we implemented a comprehensive modeling analysis involving nine parameters and four target variables (carbon and water fluxes) with their corresponding measurements based on the eddy covariance technique. The local sensitivity analysis shows that the plant production-related parameters (e.g., PPDF1 and PRDX) are most sensitive to the model cost function. Both SCE and FME are comparable and performed well in deriving the optimal parameter set with satisfactory simulations of target variables. Global sensitivity and uncertainty analysis indicate that the parameter uncertainty and the resulting output uncertainty can be quantified, and that the magnitude of parameter-uncertainty effects depends on variables and seasons. This study also demonstrates that using the cutting-edge R functions such as FME can be feasible and attractive for conducting comprehensive parameter analysis for ecosystem modeling.

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).

Carbon cycling at the tipping point: Does ecosystem structure predict resistance to disturbance?

NASA Astrophysics Data System (ADS)

Gough, C. M.; Bond-Lamberty, B. P.; Stuart-Haentjens, E.; Atkins, J.; Haber, L.; Fahey, R. T.

2017-12-01

Ecosystems worldwide are subjected to disturbances that reshape their physical and biological structure and modify biogeochemical processes, including carbon storage and cycling rates. Disturbances, including those from insect pests, pathogens, and extreme weather, span a continuum of severity and, accordingly, may have different effects on carbon cycling processes. Some ecosystems resist biogeochemical changes following disturbance, until a critical threshold of severity is exceeded. The ecosystem properties underlying such functional resistance, and signifying when a tipping point will occur, however, are almost entirely unknown. Here, we present observational and experimental results from forests in the Great Lakes region, showing ecosystem structure is closely coupled with carbon cycling responses to disturbance, with shifts in structure predicting thresholds of and, in some cases, increases in carbon storage. We find, among forests in the region, that carbon storage regularly exhibits a non-linear threshold response to increasing disturbance levels, but the severity at which a threshold is reached varies among disturbed forests. More biologically and structurally complex forest ecosystems sometimes exhibit greater functional resistance than simpler forests, and consequently may have a higher disturbance severity threshold. Counter to model predictions but consistent with some theoretical frameworks, empirical data show moderate levels of disturbance may increase ecosystem complexity to a point, thereby increasing rates of carbon storage. Disturbances that increase complexity therefore may stimulate carbon storage, while severe disturbances at or beyond thresholds may simplify structure, leading to carbon storage declines. We conclude that ecosystem structural attributes are closely coupled with biogeochemical thresholds across disturbance severity gradients, suggesting that improved predictions of disturbance-related changes in the carbon cycle require better representation of ecosystem structure in models.

Reducing the uncertainty in the projection of the terrestrial carbon cycle by fusing models with remote sensing data

NASA Astrophysics Data System (ADS)

Serbin, S.; Shiklomanov, A. N.; Viskari, T.; Desai, A. R.; Townsend, P. A.; Dietze, M.

2015-12-01

Modeling global change requires accurate representation of terrestrial carbon (C), energy and water fluxes. In particular, capturing the properties of vegetation canopies that describe the radiation regime are a key focus for global change research because the properties related to radiation utilization and penetration within plant canopies provide an important constraint on terrestrial ecosystem productivity, as well as the fluxes of water and energy from vegetation to the atmosphere. As such, optical remote sensing observations present an important, and as yet relatively untapped, source of observations that can be used to inform modeling activities. In particular, high-spectral resolution optical data at the leaf and canopy scales offers the potential for an important and direct data constraint on the parameterization and structure of the radiative transfer model (RTM) scheme within ecosystem models across diverse vegetation types, disturbance and management histories. In this presentation we highlight ongoing work to integrate optical remote sensing observations, specifically leaf and imaging spectroscopy (IS) data across a range of forest ecosystems, into complex ecosystem process models within an efficient computational assimilation framework as a means to improve the description of canopy optical properties, vegetation composition, and modeled radiation balance. Our work leverages the Predictive Ecosystem Analyzer (PEcAn; http://www.pecanproject.org/) ecoinformatics toolbox together with a RTM module designed for efficient assimilation of leaf and IS observations to inform vegetation optical properties as well as associated plant traits. Ultimately, an improved understanding of the radiation balance of ecosystems will provide a better constraint on model projections of energy balance, vegetation composition, and carbon pools and fluxes thus allowing for a better diagnosis of the vulnerability of terrestrial ecosystems in response to global change.

Biogeochemical modelling vs. tree-ring data - comparison of forest ecosystem productivity estimates

NASA Astrophysics Data System (ADS)

Zorana Ostrogović Sever, Maša; Barcza, Zoltán; Hidy, Dóra; Paladinić, Elvis; Kern, Anikó; Marjanović, Hrvoje

2017-04-01

Forest ecosystems are sensitive to environmental changes as well as human-induce disturbances, therefore process-based models with integrated management modules represent valuable tool for estimating and forecasting forest ecosystem productivity under changing conditions. Biogeochemical model Biome-BGC simulates carbon, nitrogen and water fluxes, and it is widely used for different terrestrial ecosystems. It was modified and parameterised by many researchers in the past to meet the specific local conditions. In this research, we used recently published improved version of the model Biome-BGCMuSo (BBGCMuSo), with multilayer soil module and integrated management module. The aim of our research is to validate modelling results of forest ecosystem productivity (NPP) from BBGCMuSo model with observed productivity estimated from an extensive dataset of tree-rings. The research was conducted in two distinct forest complexes of managed Pedunculate oak in SE Europe (Croatia), namely Pokupsko basin and Spačva basin. First, we parameterized BBGCMuSo model at a local level using eddy-covariance (EC) data from Jastrebarsko EC site. Parameterized model was used for the assessment of productivity on a larger scale. Results of NPP assessment with BBGCMuSo are compared with NPP estimated from tree ring data taken from trees on over 100 plots in both forest complexes. Keywords: Biome-BGCMuSo, forest productivity, model parameterization, NPP, Pedunculate oak

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.

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.

Modelling Mediterranean agro-ecosystems by including agricultural trees in the LPJmL model

NASA Astrophysics Data System (ADS)

Fader, M.; von Bloh, W.; Shi, S.; Bondeau, A.; Cramer, W.

2015-06-01

Climate and land use change in the Mediterranean region is expected to affect natural and agricultural ecosystems by decreases in precipitation, increases in temperature as well as biodiversity loss and anthropogenic degradation of natural resources. Demographic growth in the Eastern and Southern shores will require increases in food production and put additional pressure on agro-ecosystems and water resources. Coping with these challenges requires informed decisions that, in turn, require assessments by means of a comprehensive agro-ecosystem and hydrological model. This study presents the inclusion of 10 Mediterranean agricultural plants, mainly perennial crops, in an agro-ecosystem model (LPJmL): nut trees, date palms, citrus trees, orchards, olive trees, grapes, cotton, potatoes, vegetables and fodder grasses. The model was successfully tested in three model outputs: agricultural yields, irrigation requirements and soil carbon density. With the development presented in this study, LPJmL is now able to simulate in good detail and mechanistically the functioning of Mediterranean agriculture with a comprehensive representation of ecophysiological processes for all vegetation types (natural and agricultural) and in a consistent framework that produces estimates of carbon, agricultural and hydrological variables for the entire Mediterranean basin. This development pave the way for further model extensions aiming at the representation of alternative agro-ecosystems (e.g. agroforestry), and opens the door for a large number of applications in the Mediterranean region, for example assessments on the consequences of land use transitions, the influence of management practices and climate change impacts.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Vegetation Demographics in Earth System Models: a review of progress and priorities

DOE PAGES

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.; ...

2017-09-18

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Vegetation Demographics in Earth System Models: a review of progress and priorities

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

Fisher, Rosie A.; Koven, Charles D.; Anderegg, William R. L.

Numerous current efforts seek to improve the representation of ecosystem ecology and vegetation demographic processes within Earth System Models (ESMs). Furthermore, these developments are widely viewed as an important step in developing greater realism in predictions of future ecosystem states and fluxes. Increased realism, however, leads to increased model complexity, with new features raising a suite of ecological questions that require empirical constraints. We review the developments that permit the representation of plant demographics in ESMs, and identify issues raised by these developments that highlight important gaps in ecological understanding. These issues inevitably translate into uncertainty in model projections butmore » also allow models to be applied to new processes and questions concerning the dynamics of real-world ecosystems. We also argue that stronger and more innovative connections to data, across the range of scales considered, are required to address these gaps in understanding. The development of first-generation land surface models as a unifying framework for ecophysiological understanding stimulated much research into plant physiological traits and gas exchange. Constraining predictions at ecologically relevant spatial and temporal scales will require a similar investment of effort and intensified inter-disciplinary communication.« less

Evaluating Ecosystem Services for Reducing Groundwater Nitrate Contamination: Nitrate Attenuation in the Unsaturated and Saturated Zones

NASA Astrophysics Data System (ADS)

Wang, J.

2013-12-01

Nitrates are the most common type of groundwater contamination in agricultural regions. Environmental policies targeting nitrates have focused on input control (e.g., restricted fertilizer application), intermediate loads control (e.g., reduce nitrate leached from crop fields), and final loads control (e.g., reduce catchment nitrate loads). Nitrate loads can be affected by hydrological processes in both unsaturated and saturated zones. Although many of these processes have been extensively investigated in literature, they are commonly modeled as exogenous to farm management. A couple of recent studies by scientists from the Lawrence Livermore National Laboratory show that in some situations nitrate attenuation processes in the unsaturated/saturated zone, particularly denitrification, can be intensified by certain management practices to mitigate nitrate loads. Therefore, these nitrate attenuation processes can be regarded as a set of ecosystem services that farmers can take advantage of to reduce their cost of complying with environmental policies. In this paper, a representative California dairy farm is used as a case study to show how such ecosystem attenuation services can be framed within the farm owner's decision-making framework as an option for reducing groundwater nitrate contamination. I develop an integrated dynamic model, where the farmer maximizes discounted net farm profit over multiple periods subject to environmental regulations. The model consists of three submodels: animal-waste-crop, hydrologic, and economic model. In addition to common choice variables such as irrigation, fertilization, and waste disposal options, the farmer can also endogenously choose from three water sources: surface water, deep groundwater (old groundwater in the deep aquifer that is not affected by farm effluent in the short term), and shallow groundwater (drainage water that can be recycled via capture wells at the downstream end of the farm). The capture wells not only recycle wastewater, but can also increase the likelihood of denitrification. Thus the farmer essentially can choose whether, and to which extent, to install capture wells and take advantage of the ecosystem attenuation services. Decision rules from the dynamic optimization model demonstrate best management practices for the farm to improve its economic and environmental performance. I further use an economic valuation technique to value these services. Under the Millennium Ecosystem Assessment framework, nitrate attenuation in the unsaturated and saturated zone provides regulatory ecosystem services to humans, mainly nutrient regulation and waste treatment. With the integrated farm model, the production function approach is adopted to get the economic value of these regulatory services. The results highlight the significant role the environment can play in nitrate pollution control and potential benefits from designing policies that acknowledge this role. The most desirable policies are those that create incentive for farmers to use potential ecosystem services, which significantly reduce environmental compliance costs and increase social welfare.

U.S. Geological Survey Program on the South Florida Ecosystem - Proceedings of South Florida Restoration Science Forum, May 17-19, 1999, Boca Raton, Florida

DTIC Science & Technology

1999-01-01

Study (the Restudy), assessing the hydrologic and ecological results of the Restudy modifications through pre- and postmodification monitoring and...of the south Florida ecosystem and its response to restoration activities. • Model Development—Robust models of ecological processes and the... ecological interactions are all underway. • Data Synthesis and Information Dissemination—Topical syntheses will analyze, summarize, and integrate

Looking Past Primary Productivity: Benchmarking System Processes that Drive Ecosystem Level Responses in Models

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2017-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentration are highly variable and contain a considerable amount of uncertainty. Benchmarking model predictions against data are necessary to assess their ability to replicate observed patterns, but also to identify and evaluate the assumptions causing inter-model differences. We have implemented a novel benchmarking workflow as part of the Predictive Ecosystem Analyzer (PEcAn) that is automated, repeatable, and generalized to incorporate different sites and ecological models. Building on the recent Free-Air CO2 Enrichment Model Data Synthesis (FACE-MDS) project, we used observational data from the FACE experiments to test this flexible, extensible benchmarking approach aimed at providing repeatable tests of model process representation that can be performed quickly and frequently. Model performance assessments are often limited to traditional residual error analysis; however, this can result in a loss of critical information. Models that fail tests of relative measures of fit may still perform well under measures of absolute fit and mathematical similarity. This implies that models that are discounted as poor predictors of ecological productivity may still be capturing important patterns. Conversely, models that have been found to be good predictors of productivity may be hiding error in their sub-process that result in the right answers for the wrong reasons. Our suite of tests have not only highlighted process based sources of uncertainty in model productivity calculations, they have also quantified the patterns and scale of this error. Combining these findings with PEcAn's model sensitivity analysis and variance decomposition strengthen our ability to identify which processes need further study and additional data constraints. This can be used to inform future experimental design and in turn can provide an informative starting point for data assimilation.

Atmospheric redistribution of reactive nitrogen and phosphorus by wildfires and implications for global carbon cycling

NASA Astrophysics Data System (ADS)

Randerson, J. T.; Xu, L.; Wiggins, E. B.; Chen, Y.; Riley, W. J.; Mekonnen, Z. A.; Pellegrini, A.; Mahowald, N. M.

2017-12-01

Fires are an important process regulating the redistribution of nutrients within terrestrial ecosystems. Frequently burning ecosystems such as savannas are a net source of N and P to the atmosphere each year, with atmospheric transport and dry and wet deposition increasing nutrient availability in downwind ecosystems and over the open ocean. Transport of N and P aerosols from savanna fires within the Hadley circulation contributes to nutrient deposition over tropical forests, yielding an important cross-biome nutrient transfer. Pyrodenitrification of reactive N increases with fire temperature and modified combustion efficiency, generating a global net biospheric loss of approximately 14 Tg N per year. Here we analyze atmospheric N and P redistribution using the Global Fire Emissions Database version 4s and the Accelerated Climate Modeling for Energy earth system model. We synthesize literature estimates of N and P concentrations in fire-emitted aerosols and ecosystem mass balance measurements to help constrain model estimates of these biosphere-atmosphere fluxes. In our analysis, we estimate the fraction of terrestrial net primary production (NPP) that is sustained by fire-emitted P and reactive N from upwind ecosystems. We then evaluate how recent global declines in burned area in savanna and grassland ecosystems may be changing nutrient availability in downwind ecosystems.

Danish heathland manipulation experiment data in Model-Data-Fusion

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

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.

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

PubMed Central

Pitcher, Tony J.

2005-01-01

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

Integrating ecosystems measurements from multiple eddy-covariance sites to a simple model of ecosystem process - Are there possibilities for a uniform model calibration?

NASA Astrophysics Data System (ADS)

Minunno, Francesco; Peltoniemi, Mikko; Launiainen, Samuli; Mäkelä, Annikki

2014-05-01

Biogeochemical models quantify the material and energy flux exchanges between biosphere, atmosphere and soil, however there is still considerable uncertainty underpinning model structure and parametrization. The increasing availability of data from of multiple sources provides useful information for model calibration and validation at different space and time scales. We calibrated a simplified ecosystem process model PRELES to data from multiple sites. In this work we had the following objective: to compare a multi-site calibration and site-specific calibrations, in order to test if PRELES is a model of general applicability, and to test how well one parameterization can predict ecosystem fluxes. Model calibration and evaluation were carried out by the means of the Bayesian method; Bayesian calibration (BC) and Bayesian model comparison (BMC) were used to quantify the uncertainty in model parameters and model structure. Evapotranspiration (ET) and gross primary production (GPP) measurements collected in 9 sites of Finland and Sweden were used in the study; half dataset was used for model calibrations and half for the comparative analyses. 10 BCs were performed; the model was independently calibrated for each of the nine sites (site-specific calibrations) and a multi-site calibration was achieved using the data from all the sites in one BC. Then 9 BMCs were carried out, one for each site, using output from the multi-site and the site-specific versions of PRELES. Similar estimates were obtained for the parameters at which model outputs are most sensitive. Not surprisingly, the joint posterior distribution achieved through the multi-site calibration was characterized by lower uncertainty, because more data were involved in the calibration process. No significant differences were encountered in the prediction of the multi-site and site-specific versions of PRELES, and after BMC, we concluded that the model can be reliably used at regional scale to simulate carbon and water fluxes of Boreal forests. Despite being a simple model, PRELES provided good estimates of GPP and ET; only for one site PRELES multi-site version underestimated water fluxes. Our study implies convergence of GPP and water processes in boreal zone to the extent that their plausible prediction is possible with a simple model using global parameterization.

On the use of tower-flux measurements to assess the performance of global ecosystem models

NASA Astrophysics Data System (ADS)

El Maayar, M.; Kucharik, C.

2003-04-01

Global ecosystem models are important tools for the study of biospheric processes and their responses to environmental changes. Such models typically translate knowledge, gained from local observations, into estimates of regional or even global outcomes of ecosystem processes. A typical test of ecosystem models consists of comparing their output against tower-flux measurements of land surface-atmosphere exchange of heat and mass. To perform such tests, models are typically run using detailed information on soil properties (texture, carbon content,...) and vegetation structure observed at the experimental site (e.g., vegetation height, vegetation phenology, leaf photosynthetic characteristics,...). In global simulations, however, earth's vegetation is typically represented by a limited number of plant functional types (PFT; group of plant species that have similar physiological and ecological characteristics). For each PFT (e.g., temperate broadleaf trees, boreal conifer evergreen trees,...), which can cover a very large area, a set of typical physiological and physical parameters are assigned. Thus, a legitimate question arises: How does the performance of a global ecosystem model run using detailed site-specific parameters compare with the performance of a less detailed global version where generic parameters are attributed to a group of vegetation species forming a PFT? To answer this question, we used a multiyear dataset, measured at two forest sites with contrasting environments, to compare seasonal and interannual variability of surface-atmosphere exchange of water and carbon predicted by the Integrated BIosphere Simulator-Dynamic Global Vegetation Model. Two types of simulations were, thus, performed: a) Detailed runs: observed vegetation characteristics (leaf area index, vegetation height,...) and soil carbon content, in addition to climate and soil type, are specified for model run; and b) Generic runs: when only observed climates and soil types at the measurement sites are used to run the model. The generic runs were performed for the number of years equal to the current age of the forests, initialized with no vegetation and a soil carbon density equal to zero.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Evaluation of 11 terrestrial carbon–nitrogen cycle models against observations from two temperate Free-Air CO2 Enrichment studies

PubMed Central

Zaehle, Sönke; Medlyn, Belinda E; De Kauwe, Martin G; Walker, Anthony P; Dietze, Michael C; Hickler, Thomas; Luo, Yiqi; Wang, Ying-Ping; El-Masri, Bassil; Thornton, Peter; Jain, Atul; Wang, Shusen; Warlind, David; Weng, Ensheng; Parton, William; Iversen, Colleen M; Gallet-Budynek, Anne; McCarthy, Heather; Finzi, Adrien; Hanson, Paul J; Prentice, I Colin; Oren, Ram; Norby, Richard J

2014-01-01

We analysed the responses of 11 ecosystem models to elevated atmospheric [CO2] (eCO2) at two temperate forest ecosystems (Duke and Oak Ridge National Laboratory (ORNL) Free-Air CO2 Enrichment (FACE) experiments) to test alternative representations of carbon (C)–nitrogen (N) cycle processes. We decomposed the model responses into component processes affecting the response to eCO2 and confronted these with observations from the FACE experiments. Most of the models reproduced the observed initial enhancement of net primary production (NPP) at both sites, but none was able to simulate both the sustained 10-yr enhancement at Duke and the declining response at ORNL: models generally showed signs of progressive N limitation as a result of lower than observed plant N uptake. Nonetheless, many models showed qualitative agreement with observed component processes. The results suggest that improved representation of above-ground–below-ground interactions and better constraints on plant stoichiometry are important for a predictive understanding of eCO2 effects. Improved accuracy of soil organic matter inventories is pivotal to reduce uncertainty in the observed C–N budgets. The two FACE experiments are insufficient to fully constrain terrestrial responses to eCO2, given the complexity of factors leading to the observed diverging trends, and the consequential inability of the models to explain these trends. Nevertheless, the ecosystem models were able to capture important features of the experiments, lending some support to their projections. PMID:24467623

Forest Ecosystem Analysis Using a GIS

Treesearch

S.G. McNulty; W.T. Swank

1996-01-01

Forest ecosystem studies have expanded spatially in recent years to address large scale environmental issues. We are using a geographic information system (GIS) to understand and integrate forest processes at landscape to regional spatial scales. This paper presents three diverse research studies using a GIS. First, we used a GIS to develop a landscape scale model to...

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.

Gaussian Process Regression for Uncertainty Estimation on Ecosystem Data

NASA Astrophysics Data System (ADS)

Menzer, O.; Moffat, A.; Lasslop, G.; Reichstein, M.

2011-12-01

The flow of carbon between terrestrial ecosystems and the atmosphere is mainly driven by nonlinear, complex and time-lagged processes. Understanding the associated ecosystem responses and climatic feedbacks is a key challenge regarding climate change questions such as increasing atmospheric CO2 levels. Usually, the underlying relationships are implemented in models as prescribed functions which interlink numerous meteorological, radiative and gas exchange variables. In contrast, supervised Machine Learning algorithms, such as Artificial Neural Networks or Gaussian Processes, allow for an insight into the relationships directly from a data perspective. Micrometeorological, high resolution measurements at flux towers of the FLUXNET observational network are an essential tool for obtaining quantifications of the ecosystem variables, as they continuously record e.g. CO2 exchange, solar radiation and air temperature. In order to facilitate the investigation of the interactions and feedbacks between these variables, several challenging data properties need to be taken into account: noisy, multidimensional and incomplete (Moffat, Accepted). The task of estimating uncertainties in such micrometeorological measurements can be addressed by Gaussian Processes (GPs), a modern nonparametric method for nonlinear regression. The GP approach has recently been shown to be a powerful modeling tool, regardless of the input dimensionality, the degree of nonlinearity and the noise level (Rasmussen and Williams, 2006). Heteroscedastic Gaussian Processes (HGPs) are a specialized GP method for data with a varying, inhomogeneous noise variance (Goldberg et al., 1998; Kersting et al., 2007), as usually observed in CO2 flux measurements (Richardson et al., 2006). Here, we showed by an evaluation of the HGP performance in several artificial experiments and a comparison to existing nonlinear regression methods, that their outstanding ability is to capture measurement noise levels, concurrently providing reasonable data fits under relatively few assumptions. On the basis of incomplete, half-hourly measured ecosystem data, a HGP was trained to model NEP (Net Ecosystem Production), only with the drivers PPFD (Photosynthetic Photon Flux Density) and Air Temperature. Time information was added to account for the autocorrelation in the flux measurements. Provided with a gap-filled, meteorological time series, NEP and the corresponding random error estimates can then be predicted empirically at high temporal resolution. We report uncertainties in annual sums of CO2 exchange at two flux tower sites in Hainich, Germany and Hesse, France. Similar noise patterns, but different magnitudes between sites were detected, with annual random error estimates of +/- 14.1 gCm^-2yr^-1 and +/- 23.5 gCm^-2yr^-1, respectively, for the year 2001. Existing models calculate uncertainties by evaluating the standard deviation of the model residuals. A comparison to the methods of Reichstein et al. (2005) and Lasslop et al. (2008) showed confidence both in the predictive uncertainties and the annual sums modeled with the HGP approach.

Harnessing ecosystem models and multi-criteria decision analysis for the support of forest management.

PubMed

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Harnessing Ecosystem Models and Multi-Criteria Decision Analysis for the Support of Forest Management

NASA Astrophysics Data System (ADS)

Wolfslehner, Bernhard; Seidl, Rupert

2010-12-01

The decision-making environment in forest management (FM) has changed drastically during the last decades. Forest management planning is facing increasing complexity due to a widening portfolio of forest goods and services, a societal demand for a rational, transparent decision process and rising uncertainties concerning future environmental conditions (e.g., climate change). Methodological responses to these challenges include an intensified use of ecosystem models to provide an enriched, quantitative information base for FM planning. Furthermore, multi-criteria methods are increasingly used to amalgamate information, preferences, expert judgments and value expressions, in support of the participatory and communicative dimensions of modern forestry. Although the potential of combining these two approaches has been demonstrated in a number of studies, methodological aspects in interfacing forest ecosystem models (FEM) and multi-criteria decision analysis (MCDA) are scarcely addressed explicitly. In this contribution we review the state of the art in FEM and MCDA in the context of FM planning and highlight some of the crucial issues when combining ecosystem and preference modeling. We discuss issues and requirements in selecting approaches suitable for supporting FM planning problems from the growing body of FEM and MCDA concepts. We furthermore identify two major challenges in a harmonized application of FEM-MCDA: (i) the design and implementation of an indicator-based analysis framework capturing ecological and social aspects and their interactions relevant for the decision process, and (ii) holistic information management that supports consistent use of different information sources, provides meta-information as well as information on uncertainties throughout the planning process.

Radionuclide transfer in marine coastal ecosystems, a modelling study using metabolic processes and site data.

PubMed

Konovalenko, L; Bradshaw, C; Kumblad, L; Kautsky, U

2014-07-01

This study implements new site-specific data and improved process-based transport model for 26 elements (Ac, Ag, Am, Ca, Cl, Cm, Cs, Ho, I, Nb, Ni, Np, Pa, Pb, Pd, Po, Pu, Ra, Se, Sm, Sn, Sr, Tc, Th, U, Zr), and validates model predictions with site measurements and literature data. The model was applied in the safety assessment of a planned nuclear waste repository in Forsmark, Öregrundsgrepen (Baltic Sea). Radionuclide transport models are central in radiological risk assessments to predict radionuclide concentrations in biota and doses to humans. Usually concentration ratios (CRs), the ratio of the measured radionuclide concentration in an organism to the concentration in water, drive such models. However, CRs vary with space and time and CR estimates for many organisms are lacking. In the model used in this study, radionuclides were assumed to follow the circulation of organic matter in the ecosystem and regulated by radionuclide-specific mechanisms and metabolic rates of the organisms. Most input parameters were represented by log-normally distributed probability density functions (PDFs) to account for parameter uncertainty. Generally, modelled CRs for grazers, benthos, zooplankton and fish for the 26 elements were in good agreement with site-specific measurements. The uncertainty was reduced when the model was parameterized with site data, and modelled CRs were most similar to measured values for particle reactive elements and for primary consumers. This study clearly demonstrated that it is necessary to validate models with more than just a few elements (e.g. Cs, Sr) in order to make them robust. The use of PDFs as input parameters, rather than averages or best estimates, enabled the estimation of the probable range of modelled CR values for the organism groups, an improvement over models that only estimate means. Using a mechanistic model that is constrained by ecological processes enables (i) the evaluation of the relative importance of food and water uptake pathways and processes such as assimilation and excretion, (ii) the possibility to extrapolate within element groups (a common requirement in many risk assessments when initial model parameters are scarce) and (iii) predictions of radionuclide uptake in the ecosystem after changes in ecosystem structure or environmental conditions. These features are important for the longterm (>1000 year) risk assessments that need to be considered for a deep nuclear waste repository. Copyright © 2013. Published by Elsevier Ltd.

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.

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

Kremer, R.G.

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

Linking vegetation structure, function and physiology through spectroscopic remote sensing

NASA Astrophysics Data System (ADS)

Serbin, S.; Singh, A.; Couture, J. J.; Shiklomanov, A. N.; Rogers, A.; Desai, A. R.; Kruger, E. L.; Townsend, P. A.

2015-12-01

Terrestrial ecosystem process models require detailed information on ecosystem states and canopy properties to properly simulate the fluxes of carbon (C), water and energy from the land to the atmosphere and assess the vulnerability of ecosystems to perturbations. Current models fail to adequately capture the magnitude, spatial variation, and seasonality of terrestrial C uptake and storage, leading to significant uncertainties in the size and fate of the terrestrial C sink. By and large, these parameter and process uncertainties arise from inadequate spatial and temporal representation of plant traits, vegetation structure, and functioning. With increases in computational power and changes to model architecture and approaches, it is now possible for models to leverage detailed, data rich and spatially explicit descriptions of ecosystems to inform parameter distributions and trait tradeoffs. In this regard, spectroscopy and imaging spectroscopy data have been shown to be invaluable observational datasets to capture broad-scale spatial and, eventually, temporal dynamics in important vegetation properties. We illustrate the linkage of plant traits and spectral observations to supply key data constraints for model parameterization. These constraints can come either in the form of the raw spectroscopic data (reflectance, absorbtance) or physiological traits derived from spectroscopy. In this presentation we highlight our ongoing work to build ecological scaling relationships between critical vegetation characteristics and optical properties across diverse and complex canopies, including temperate broadleaf and conifer forests, Mediterranean vegetation, Arctic systems, and agriculture. We focus on work at the leaf, stand, and landscape scales, illustrating the importance of capturing the underlying variability in a range of parameters (including vertical variation within canopies) to enable more efficient scaling of traits related to functional diversity of ecosystems.

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.

Using ecological production functions to link ecological ...

EPA Pesticide Factsheets

Ecological production functions (EPFs) link ecosystems, stressors, and management actions to ecosystem services (ES) production. Although EPFs are acknowledged as being essential to improve environmental management, their use in ecological risk assessment has received relatively little attention. Ecological production functions may be defined as usable expressions (i.e., models) of the processes by which ecosystems produce ES, often including external influences on those processes. We identify key attributes of EPFs and discuss both actual and idealized examples of their use to inform decision making. Whenever possible, EPFs should estimate final, rather than intermediate, ES. Although various types of EPFs have been developed, we suggest that EPFs are more useful for decision making if they quantify ES outcomes, respond to ecosystem condition, respond to stressor levels or management scenarios, reflect ecological complexity, rely on data with broad coverage, have performed well previously, are practical to use, and are open and transparent. In an example using pesticides, we illustrate how EPFs with these attributes could enable the inclusion of ES in ecological risk assessment. The biggest challenges to ES inclusion are limited data sets that are easily adapted for use in modeling EPFs and generally poor understanding of linkages among ecological components and the processes that ultimately deliver the ES. We conclude by advocating for the incorporation into E

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

PubMed

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

2017-06-01

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

Developing and applying metamodels of high resolution process-based simulations for high throughput exposure assessment of organic chemicals in riverine ecosystems

EPA Science Inventory

As defined by Wikipedia (https://en.wikipedia.org/wiki/Metamodeling), “(a) metamodel or surrogate model is a model of a model, and metamodeling is the process of generating such metamodels.” The goals of metamodeling include, but are not limited to (1) developing func...

The functional value of Caribbean coral reef, seagrass and mangrove habitats to ecosystem processes.

PubMed

Harborne, Alastair R; Mumby, Peter J; Micheli, Fiorenza; Perry, Christopher T; Dahlgren, Craig P; Holmes, Katherine E; Brumbaugh, Daniel R

2006-01-01

Caribbean coral reef habitats, seagrass beds and mangroves provide important goods and services both individually and through functional linkages. A range of anthropogenic factors are threatening the ecological and economic importance of these habitats and it is vital to understand how ecosystem processes vary across seascapes. A greater understanding of processes will facilitate further insight into the effects of disturbances and assist with assessing management options. Despite the need to study processes across whole seascapes, few spatially explicit ecosystem-scale assessments exist. We review the empirical literature to examine the role of different habitat types for a range of processes. The importance of each of 10 generic habitats to each process is defined as its "functional value" (none, low, medium or high), quantitatively derived from published data wherever possible and summarised in a single figure. This summary represents the first time the importance of habitats across an entire Caribbean seascape has been assessed for a range of processes. Furthermore, we review the susceptibility of each habitat to disturbances to investigate spatial patterns that might affect functional values. Habitat types are considered at the scale discriminated by remotely-sensed imagery and we envisage that functional values can be combined with habitat maps to provide spatially explicit information on processes across ecosystems. We provide examples of mapping the functional values of habitats for populations of three commercially important species. The resulting data layers were then used to generate seascape-scale assessments of "hot spots" of functional value that might be considered priorities for conservation. We also provide an example of how the literature reviewed here can be used to parameterise a habitat-specific model investigating reef resilience under different scenarios of herbivory. Finally, we use multidimensional scaling to provide a basic analysis of the overall functional roles of different habitats. The resulting ordination suggests that each habitat has a unique suite of functional values and, potentially, a distinct role within the ecosystem. This review shows that further data are required for many habitat types and processes, particularly forereef and escarpment habitats on reefs and for seagrass beds and mangroves. Furthermore, many data were collected prior to the regional mass mortality of Diadema and Acropora, and subsequent changes to benthic communities have, in many cases, altered a habitat's functional value, hindering the use of these data for parameterising maps and models. Similarly, few data exist on how functional values change when environmental parameters, such as water clarity, are altered by natural or anthropogenic influences or the effects of a habitat's spatial context within the seascape. Despite these limitations, sufficient data are available to construct maps and models to better understand tropical marine ecosystem processes and assist more effective mitigation of threats that alter habitats and their functional values.

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.

Ecosystem properties self-organize in response to a directional fog-vegetation interaction.

PubMed

Stanton, Daniel E; Armesto, Juan J; Hedin, Lars O

2014-05-01

Feedbacks between vegetation and resource inputs can lead to the local, self-organization of ecosystem properties. In particular, feedbacks in response to directional resources (e.g., coastal fog, slope runoff) can create complex spatial patterns, such as vegetation banding. Although similar feedbacks are thought to be involved in the development of ecosystems, clear empirical examples are rare. We created a simple model of a fog-influenced, temperate rainforest in central Chile, which allows the comparison of natural banding patterns to simulations of various putative mechanisms. We show that only feedbacks between plants and fog were able to replicate the characteristic distributions of vegetation, soil water, and soil nutrients observed in field transects. Other processes, such as rainfall, were unable to match these diagnostic distributions. Furthermore, fog interception by windward trees leads to increased downwind mortality, leading to progressive extinction of the leeward edge. This pattern of ecosystem development and decay through self-organized processes illustrates, on a relatively small spatial and temporal scale, the patterns predicted for ecosystem evolution.

Photodegradation Pathways in Arid Ecosystems

NASA Astrophysics Data System (ADS)

King, J. Y.; Lin, Y.; Adair, E. C.; Brandt, L.; Carbone, M. S.

2013-12-01

Recent interest in improving our understanding of decomposition patterns in arid and semi-arid ecosystems and under potentially drier future conditions has led to a flurry of research related to abiotic degradation processes. Oxidation of organic matter by solar radiation (photodegradation) is one abiotic degradation process that contributes significantly to litter decomposition rates. Our meta-analysis results show that increasing solar radiation exposure corresponds to an average increase of 23% in litter mass loss rate with large variation among studies associated primarily with environmental and litter chemistry characteristics. Laboratory studies demonstrate that photodegradation results in CO2 emissions. Indirect estimates suggest that photodegradation could account for as much as 60% of ecosystem CO2 emissions from dry ecosystems, but these CO2 fluxes have not been measured in intact ecosystems. The current data suggest that photodegradation is important, not only for understanding decomposition patterns, but also for modeling organic matter turnover and ecosystem C cycling. However, the mechanisms by which photodegradation operates, along with their environmental and litter chemistry controls, are still poorly understood. Photodegradation can directly influence decomposition rates and ecosystem CO2 flux via photochemical mineralization. It can also indirectly influence biotic decomposition rates by facilitating microbial degradation through breakdown of more recalcitrant compounds into simpler substrates or by suppressing microbial activity directly. All of these pathways influence the decomposition process, but the relative importance of each is uncertain. Furthermore, a specific suite of controls regulates each of these pathways (e.g., environmental conditions such as temperature and relative humidity; physical environment such as canopy architecture and contact with soil; and litter chemistry characteristics such as lignin and cellulose content), and these controls have not yet been identified or quantified. To advance our understanding of photodegradation and its role in decomposition and in ecosystem C cycling, we must characterize its mechanisms and their associated controls and incorporate this understanding into biogeochemical models. Our objective is to summarize the current state of understanding of photodegradation and discuss some paths forward to address remaining critical gaps in knowledge about its mechanisms and influence on ecosystem C balance.

Modeling dynamic interactions and coherence between marine zooplankton and fishes linked to environmental variability

NASA Astrophysics Data System (ADS)

Liu, Hui; Fogarty, Michael J.; Hare, Jonathan A.; Hsieh, Chih-hao; Glaser, Sarah M.; Ye, Hao; Deyle, Ethan; Sugihara, George

2014-03-01

The dynamics of marine fishes are closely related to lower trophic levels and the environment. Quantitatively understanding ecosystem dynamics linking environmental variability and prey resources to exploited fishes is crucial for ecosystem-based management of marine living resources. However, standard statistical models typically grounded in the concept of linear system may fail to capture the complexity of ecological processes. We have attempted to model ecosystem dynamics using a flexible, nonparametric class of nonlinear forecasting models. We analyzed annual time series of four environmental indices, 22 marine copepod taxa, and four ecologically and commercially important fish species during 1977 to 2009 on Georges Bank, a highly productive and intensively studied area of the northeast U.S. continental shelf ecosystem. We examined the underlying dynamic features of environmental indices and copepods, quantified the dynamic interactions and coherence with fishes, and explored the potential control mechanisms of ecosystem dynamics from a nonlinear perspective. We found: (1) the dynamics of marine copepods and environmental indices exhibiting clear nonlinearity; (2) little evidence of complex dynamics across taxonomic levels of copepods; (3) strong dynamic interactions and coherence between copepods and fishes; and (4) the bottom-up forcing of fishes and top-down control of copepods coexisting as target trophic levels vary. These findings highlight the nonlinear interactions among ecosystem components and the importance of marine zooplankton to fish populations which point to two forcing mechanisms likely interactively regulating the ecosystem dynamics on Georges Bank under a changing environment.

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.

NASA 1990 Multisensor Airborne Campaigns (MACs) for ecosystem and watershed studies

NASA Technical Reports Server (NTRS)

Wickland, Diane E.; Asrar, Ghassem; Murphy, Robert E.

1991-01-01

The Multisensor Airborne Campaign (MAC) focus within NASA's former Land Processes research program was conceived to achieve the following objectives: to acquire relatively complete, multisensor data sets for well-studied field sites, to add a strong remote sensing science component to ecology-, hydrology-, and geology-oriented field projects, to create a research environment that promotes strong interactions among scientists within the program, and to more efficiently utilize and compete for the NASA fleet of remote sensing aircraft. Four new MAC's were conducted in 1990: the Oregon Transect Ecosystem Research (OTTER) project along an east-west transect through central Oregon, the Forest Ecosystem Dynamics (FED) project at the Northern Experimental Forest in Howland, Maine, the MACHYDRO project in the Mahantango Creek watershed in central Pennsylvania, and the Walnut Gulch project near Tombstone, Arizona. The OTTER project is testing a model that estimates the major fluxes of carbon, nitrogen, and water through temperate coniferous forest ecosystems. The focus in the project is on short time-scale (days-year) variations in ecosystem function. The FED project is concerned with modeling vegetation changes of forest ecosystems using remotely sensed observations to extract biophysical properties of forest canopies. The focus in this project is on long time-scale (decades to millenia) changes in ecosystem structure. The MACHYDRO project is studying the role of soil moisture and its regulating effects on hydrologic processes. The focus of the study is to delineate soil moisture differences within a basin and their changes with respect to evapotranspiration, rainfall, and streamflow. The Walnut Gulch project is focused on the effects of soil moisture in the energy and water balance of arid and semiarid ecosystems and their feedbacks to the atmosphere via thermal forcing.

Effect of interannual climate variability on carbon storage in Amazonian ecosystems

USGS Publications Warehouse

Tian, H.; Melillo, J.M.; Kicklighter, D.W.; McGuire, David A.; Helfrich, J. V. K.; Moore, B.; Vorosmarty, C.J.

1998-01-01

The Amazon Basin contains almost one-half of the world's undisturbed tropical evergreen forest as well as large areas of tropical savanna. The forests account for about 10 per cent of the world's terrestrial primary productivity and for a similar fraction of the carbon stored in land ecosystems, and short-term field measurements suggest that these ecosystems are globally important carbon sinks. But tropical land ecosystems have experienced substantial interannual climate variability owing to frequent El Nino episodes in recent decades. Of particular importance to climate change policy is how such climate variations, coupled with increases in atmospheric CO2 concentration, affect terrestrial carbon storage. Previous model analyses have demonstrated the importance of temperature in controlling carbon storage. Here we use a transient process-based biogeochemical model of terrestrial ecosystems to investigate interannual variations of carbon storage in undisturbed Amazonian ecosystems in response to climate variability and increasing atmospheric CO2 concentration during the period 1980 to 1994. In El Nino years, which bring hot, dry weather to much of the Amazon region, the ecosystems act as a source of carbon to the atmosphere (up to 0.2 petagrams of carbon in 1987 and 1992). In other years, these ecosystems act as a carbon sink (up to 0.7 Pg C in 1981 and 1993). These fluxes are large; they compare to a 0.3 Pg C per year source to the atmosphere associated with deforestation in the Amazon Basin in the early 1990s. Soil moisture, which is affected by both precipitation and temperature, and which affects both plant and soil processes, appears to be an important control on carbon storage.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability

NASA Astrophysics Data System (ADS)

Steenberg, James W. N.; Millward, Andrew A.; Nowak, David J.; Robinson, Pamela J.; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Forecasting Urban Forest Ecosystem Structure, Function, and Vulnerability.

PubMed

Steenberg, James W N; Millward, Andrew A; Nowak, David J; Robinson, Pamela J; Ellis, Alexis

2017-03-01

The benefits derived from urban forest ecosystems are garnering increasing attention in ecological research and municipal planning. However, because of their location in heterogeneous and highly-altered urban landscapes, urban forests are vulnerable and commonly suffer disproportionate and varying levels of stress and disturbance. The objective of this study is to assess and analyze the spatial and temporal changes, and potential vulnerability, of the urban forest resource in Toronto, Canada. This research was conducted using a spatially-explicit, indicator-based assessment of vulnerability and i-Tree Forecast modeling of temporal changes in forest structure and function. Nine scenarios were simulated for 45 years and model output was analyzed at the ecosystem and municipal scale. Substantial mismatches in ecological processes between spatial scales were found, which can translate into unanticipated loss of function and social inequities if not accounted for in planning and management. At the municipal scale, the effects of Asian longhorned beetle and ice storm disturbance were far less influential on structure and function than changes in management actions. The strategic goals of removing invasive species and increasing tree planting resulted in a decline in carbon storage and leaf biomass. Introducing vulnerability parameters in the modeling increased the spatial heterogeneity in structure and function while expanding the disparities of resident access to ecosystem services. There was often a variable and uncertain relationship between vulnerability and ecosystem structure and function. Vulnerability assessment and analysis can provide strategic planning initiatives with valuable insight into the processes of structural and functional change resulting from management intervention.

Partitioning net ecosystem exchange of CO2 into gross primary production and ecosystem respiration in northern high-latitude ecosystems

NASA Astrophysics Data System (ADS)

Lund, M.; Zona, D.; Jackowicz-Korczynski, M.; Xu, X.

2017-12-01

The eddy covariance methodology is the primary tool for studying landscape-scale land-atmosphere exchange of greenhouse gases. Since the choice of instrumental setup and processing algorithms may influence the results, efforts within the international flux community have been made towards methodological harmonization and standardization. Performing eddy covariance measurements in high-latitude, Arctic tundra sites involves several challenges, related not only to remoteness and harsh climate conditions but also to the choice of processing algorithms. Partitioning of net ecosystem exchange (NEE) of CO2 into gross primary production (GPP) and ecosystem respiration (Reco) in the FLUXNET2015 dataset is made using either Nighttime or Daytime methods. These variables, GPP and Reco, are essential for calibration and validation of Earth system models. North of the Arctic Circle, sun remains visible at local midnight for a period of time, the number of days per year with midnight sun being dependent on latitude. The absence of nighttime conditions during Arctic summers renders the Nighttime method uncertain, however, no extensive assessment on the implications for flux partitioning has yet been made. In this study, we will assess the performance and validity of both partitioning methods along a latitudinal transect of northern sites included in the FLUXNET2015 dataset. We will evaluate the partitioned flux components against model simulations using the Community Land Model (CLM). Our results will be valuable for users interested in simulating Arctic and global carbon cycling.

Bridging Food Webs, Ecosystem Metabolism, and Biogeochemistry Using Ecological Stoichiometry Theory

PubMed Central

Welti, Nina; Striebel, Maren; Ulseth, Amber J.; Cross, Wyatt F.; DeVilbiss, Stephen; Glibert, Patricia M.; Guo, Laodong; Hirst, Andrew G.; Hood, Jim; Kominoski, John S.; MacNeill, Keeley L.; Mehring, Andrew S.; Welter, Jill R.; Hillebrand, Helmut

2017-01-01

Although aquatic ecologists and biogeochemists are well aware of the crucial importance of ecosystem functions, i.e., how biota drive biogeochemical processes and vice-versa, linking these fields in conceptual models is still uncommon. Attempts to explain the variability in elemental cycling consequently miss an important biological component and thereby impede a comprehensive understanding of the underlying processes governing energy and matter flow and transformation. The fate of multiple chemical elements in ecosystems is strongly linked by biotic demand and uptake; thus, considering elemental stoichiometry is important for both biogeochemical and ecological research. Nonetheless, assessments of ecological stoichiometry (ES) often focus on the elemental content of biota rather than taking a more holistic view by examining both elemental pools and fluxes (e.g., organismal stoichiometry and ecosystem process rates). ES theory holds the promise to be a unifying concept to link across hierarchical scales of patterns and processes in ecology, but this has not been fully achieved. Therefore, we propose connecting the expertise of aquatic ecologists and biogeochemists with ES theory as a common currency to connect food webs, ecosystem metabolism, and biogeochemistry, as they are inherently concatenated by the transfer of carbon, nitrogen, and phosphorous through biotic and abiotic nutrient transformation and fluxes. Several new studies exist that demonstrate the connections between food web ecology, biogeochemistry, and ecosystem metabolism. In addition to a general introduction into the topic, this paper presents examples of how these fields can be combined with a focus on ES. In this review, a series of concepts have guided the discussion: (1) changing biogeochemistry affects trophic interactions and ecosystem processes by altering the elemental ratios of key species and assemblages; (2) changing trophic dynamics influences the transformation and fluxes of matter across environmental boundaries; (3) changing ecosystem metabolism will alter the chemical diversity of the non-living environment. Finally, we propose that using ES to link nutrient cycling, trophic dynamics, and ecosystem metabolism would allow for a more holistic understanding of ecosystem functions in a changing environment. PMID:28747904

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

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

USGS Publications Warehouse

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

2001-01-01

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

Climate, ecosystems, and planetary futures: The challenge to predict life in Earth system models.

PubMed

Bonan, Gordon B; Doney, Scott C

2018-02-02

Many global change stresses on terrestrial and marine ecosystems affect not only ecosystem services that are essential to humankind, but also the trajectory of future climate by altering energy and mass exchanges with the atmosphere. Earth system models, which simulate terrestrial and marine ecosystems and biogeochemical cycles, offer a common framework for ecological research related to climate processes; analyses of vulnerability, impacts, and adaptation; and climate change mitigation. They provide an opportunity to move beyond physical descriptors of atmospheric and oceanic states to societally relevant quantities such as wildfire risk, habitat loss, water availability, and crop, fishery, and timber yields. To achieve this, the science of climate prediction must be extended to a more multifaceted Earth system prediction that includes the biosphere and its resources. Copyright © 2018, American Association for the Advancement of Science.

Comparing algorithms for estimating foliar biomass of conifers in the Pacific Northwest

Treesearch

Crystal L. Raymond; Donald McKenzie

2013-01-01

Accurate estimates of foliar biomass (FB) are important for quantifying carbon storage in forest ecosystems, but FB is not always reported in regional or national inventories. Foliar biomass also drives key ecological processes in ecosystem models. Published algorithms for estimating FB in conifer species of the Pacific Northwest can yield signifi cantly different...

Tree mortality from drought, insects, and their interactions in a changing climate

Treesearch

William R. L. Anderegg; Jeffrey A. Hicke; Rosie A. Fisher; Craig D. Allen; Juliann Aukema; Barbara Bentz; Sharon Hood; Jeremy W. Lichstein; Alison K. Macalady; Nate McDowell; Yude Pan; Kenneth Raffa; Anna Sala; John D. Shaw; Nathan L. Stephenson; Christina Tague; Melanie Zeppel

2015-01-01

Climate change is expected to drive increased tree mortality through drought, heat stress, and insect attacks, with manifold impacts on forest ecosystems. Yet, climate-induced tree mortality and biotic disturbance agents are largely absent from process-based ecosystem models. Using data sets from the western USA and associated studies, we present a framework for...

Hydrologic connectivity between geographically isolated wetlands and surface water systems: A review of select modeling methods

Treesearch

Heather E. Golden; Charles R. Lane; Devendra M. Amatya; Karl W. Bandilla; Hadas Raanan Kiperwas Kiperwas; Christopher D. Knightes; Herbert Ssegane

2014-01-01

Geographically isolated wetlands (GIW), depressional landscape features entirely surrounded by upland areas, provide a wide range of ecological functions and ecosystem services for human well-being. Current and future ecosystem management and decision-making rely on a solid scientific understanding of how hydrologic processes affect these important GIW services and...

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...

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

Treesearch

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

2008-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2011-06-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Modeling approaches to describe H2O and CO2 exchange in mare ecosystems

NASA Astrophysics Data System (ADS)

Olchev, A.; Novenko, E.; Volkova, E.

2012-04-01

The modern climatic conditions is strongly influenced by both internal variability of climatic system, and various external natural and anthropogenic factors (IPCC 2007). Significant increase of concentration of greenhouse gases in the atmosphere and especially the growth of atmospheric CO2 due to human activity are considered as the main factors that are responsible for global warming and climate changes. A significant part of anthropogenic CO2 is absorbed from the atmosphere by land biota and especially by vegetation cover. However, it is still not completely clear what is the role of different land ecosystems and especially forests and mares in global cycles of H2O and CO2 and what is a sensitivity of these ecosystems to climate changes. Within the frameworks of this study the spatial and temporal variability of H2O and CO2 fluxes in different types of mare ecosystems of the forest-steppe zone in European part of Russia was described using modeling approaches and results of field measurements. For this modeling and experimental study the mare ecosystems of Tula region were selected. The Tula region is located mostly in the forest-steppe zone and it is unique area for such studies because almost all existed types of mare ecosystems of Northern Eurasia distinguished by a geomorphological position, water and mineral supply can be found there. Most mares in Tula region have a relatively small size and surrounded by very heterogeneous forests that make not possible an application of the classical measuring and modeling approaches e.g. an eddy covariance technique or one-dimensional H2O and CO2 exchange models for flux estimation in such sites. In our study to describe the radiation, sensible heat, H2O and CO2 exchange between such heterogeneous mare ecosystems and the atmosphere a three-dimensional model Forbog-3D and one-dimensional Mixfor-SVAT were applied. The main concept used in the Forbog-3D and Mixfor-SVAT models is an aggregated description of physical and biological processes at various hierarchical levels of forest and mire ecosystems: from a single leaf to a tree and an entire ecosystem. The models consist of the several closely coupled sub-models describing: transfer of direct and diffuse solar radiation; turbulent exchange of sensible heat, H2O and CO2 within and above a vegetation cover; transpiration, photosynthesis and respiration of vegetation and soil; heat and moisture transfer in different soil layers. The models were validated and applied to describe the H2O and CO2 exchange processes in various mare ecosystems with different relief position, type of water and mineral supply as well as vegetation composition. Selected mares are located in different parts of the Tula region (both in forest and forest-steppe zones) and characterized by different microclimatic conditions. The study was supported by grants (11-04-97538-r_center_a, 11-04-01622-a and 11-05-00557-a) of the Russian Foundation for Basic Research (RFBR) and by grant of Government of Russian Federation N 11.G34.31.0079.

Advancing research on animal-transported subsidies by integrating animal movement and ecosystem modelling.

PubMed

Earl, Julia E; Zollner, Patrick A

2017-09-01

Connections between ecosystems via animals (active subsidies) support ecosystem services and contribute to numerous ecological effects. Thus, the ability to predict the spatial distribution of active subsidies would be useful for ecology and conservation. Previous work modelling active subsidies focused on implicit space or static distributions, which treat passive and active subsidies similarly. Active subsidies are fundamentally different from passive subsidies, because animals can respond to the process of subsidy deposition and ecosystem changes caused by subsidy deposition. We propose addressing this disparity by integrating animal movement and ecosystem ecology to advance active subsidy investigations, make more accurate predictions of subsidy spatial distributions, and enable a mechanistic understanding of subsidy spatial distributions. We review selected quantitative techniques that could be used to accomplish integration and lead to novel insights. The ultimate objective for these types of studies is predictions of subsidy spatial distributions from characteristics of the subsidy and the movement strategy employed by animals that transport subsidies. These advances will be critical in informing the management of ecosystem services, species conservation and ecosystem degradation related to active subsidies. © 2017 The Authors. Journal of Animal Ecology © 2017 British Ecological Society.

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.

Taking a closer look: disentangling effects of functional diversity on ecosystem functions with a trait-based model across hierarchy and time

PubMed Central

Holzwarth, Frédéric; Rüger, Nadja; Wirth, Christian

2015-01-01

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. PMID:26064620

Ecological extension of the theory of evolution by natural selection from a perspective of Western and Eastern holistic philosophy.

PubMed

Nakajima, Toshiyuki

2017-12-01

Evolution by natural selection requires the following conditions: (1) a particular selective environment; (2) variation of traits in the population; (3) differential survival/reproduction among the types of organisms; and (4) heritable traits. However, the traditional (standard) model does not clearly explain how and why these conditions are generated or determined. What generates a selective environment? What generates new types? How does a certain type replace, or coexist with, others? In this paper, based on the holistic philosophy of Western and Eastern traditions, I focus on the ecosystem as a higher-level system and generator of conditions that induce the evolution of component populations; I also aim to identify the ecosystem processes that generate those conditions. In particular, I employ what I call the scientific principle of dependent-arising (SDA), which is tailored for scientific use and is based on Buddhism principle called "pratītya-samutpāda" in Sanskrit. The SDA principle asserts that there exists a higher-level system, or entity, which includes a focal process of a system as a part within it; this determines or generates the conditions required for the focal process to work in a particular way. I conclude that the ecosystem generates (1) selective environments for component species through ecosystem dynamics; (2) new genetic types through lateral gene transfer, hybridization, and symbiogenesis among the component species of the ecosystem; (3) mechanistic processes of replacement of an old type with a new one. The results of this study indicate that the ecological extension of the theoretical model of adaptive evolution is required for better understanding of adaptive evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

How can we transfer scientific knowledge to citizens? : Case studies from huge earthquake and tsunami researches

NASA Astrophysics Data System (ADS)

Kitazato, Hiroshi; Kijima, Akihiro; Kogure, Kazuhiro; Fujikura, Katsunori

2017-04-01

On March 11, 2011, huge earthquake and tsunamis took place coastal regions of Northeast Japan. Coastal infrastructure collapsed due to high waves of tsunamis. Marine ecosystems were also strongly disturbed by the earthquakes and tsunamis. TEAMS (Tohoku Ecosystem-Associated Marine Sciences) has started for monitoring recovering process of marine ecosystems. The project continues ten years. First five years are mainly monitored recovery process, then we should transfer our knowledge to fishermen and citizens for restoration of fishery and social systems. But, how can we actually transfer our knowledge from science to citizens? This is new experience for us. Socio-technology constructs a "high quality risk communication" model how scientific knowledge or technologies from scientific communities to citizens. They are progressing as follows, "observation, measurements and data", → "modeling and synthesis" → "information process" → "delivery to society" → " take action in society". These steps show detailed transition from inter-disciplinarity to trans-disciplinarity in science and technology. In our presentation, we plan to show a couple of case studies that are going forward from science to society.

Linkages between terrestrial ecosystems and the atmosphere

NASA Technical Reports Server (NTRS)

Bretherton, Francis; Dickinson, Robert E.; Fung, Inez; Moore, Berrien, III; Prather, Michael; Running, Steven W.; Tiessen, Holm

1992-01-01

The primary research issue in understanding the role of terrestrial ecosystems in global change is analyzing the coupling between processes with vastly differing rates of change, from photosynthesis to community change. Representing this coupling in models is the central challenge to modeling the terrestrial biosphere as part of the earth system. Terrestrial ecosystems participate in climate and in the biogeochemical cycles on several temporal scales. Some of the carbon fixed by photosynthesis is incorporated into plant tissue and is delayed from returning to the atmosphere until it is oxidized by decomposition or fire. This slower (i.e., days to months) carbon loop through the terrestrial component of the carbon cycle, which is matched by cycles of nutrients required by plants and decomposers, affects the increasing trend in atmospheric CO2 concentration and imposes a seasonal cycle on that trend. Moreover, this cycle includes key controls over biogenic trace gas production. The structure of terrestrial ecosystems, which responds on even longer time scales (annual to century), is the integrated response to the biogeochemical and environmental constraints that develop over the intermediate time scale. The loop is closed back to the climate system since it is the structure of ecosystems, including species composition, that sets the terrestrial boundary condition in the climate system through modification of surface roughness, albedo, and, to a great extent, latent heat exchange. These separate temporal scales contain explicit feedback loops which may modify ecosystem dynamics and linkages between ecosystems and the atmosphere. The long-term change in climate, resulting from increased atmospheric concentrations of greenhouse gases (e.g., CO2, CH4, and nitrous oxide (N2O)) will further modify the global environment and potentially induce further ecosystem change. Modeling these interactions requires coupling successional models to biogeochemical models to physiological models that describe the exchange of water, energy, and biogenic trace gases between the vegetation and the atmosphere at fine time scales. There does not appear to be any obvious way to allow direct reciprocal coupling of atmospheric general circulation models (GCM's), which inherently run with fine time steps, to ecosystem or successional models, which have coarse temporal resolution, without the interposition of physiological canopy models. This is equally true for biogeochemical models of the exchange of carbon dioxide and trace gases. This coupling across time scales is nontrivial and sets the focus for the modeling strategy.

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.

Landscape Characterization of Arctic Ecosystems Using Data Mining Algorithms and Large Geospatial Datasets

NASA Astrophysics Data System (ADS)

Langford, Z. L.; Kumar, J.; Hoffman, F. M.

2015-12-01

Observations indicate that over the past several decades, landscape processes in the Arctic have been changing or intensifying. A dynamic Arctic landscape has the potential to alter ecosystems across a broad range of scales. Accurate characterization is useful to understand the properties and organization of the landscape, optimal sampling network design, measurement and process upscaling and to establish a landscape-based framework for multi-scale modeling of ecosystem processes. This study seeks to delineate the landscape at Seward Peninsula of Alaska into ecoregions using large volumes (terabytes) of high spatial resolution satellite remote-sensing data. Defining high-resolution ecoregion boundaries is difficult because many ecosystem processes in Arctic ecosystems occur at small local to regional scales, which are often resolved in by coarse resolution satellites (e.g., MODIS). We seek to use data-fusion techniques and data analytics algorithms applied to Phased Array type L-band Synthetic Aperture Radar (PALSAR), Interferometric Synthetic Aperture Radar (IFSAR), Satellite for Observation of Earth (SPOT), WorldView-2, WorldView-3, and QuickBird-2 to develop high-resolution (˜5m) ecoregion maps for multiple time periods. Traditional analysis methods and algorithms are insufficient for analyzing and synthesizing such large geospatial data sets, and those algorithms rarely scale out onto large distributed- memory parallel computer systems. We seek to develop computationally efficient algorithms and techniques using high-performance computing for characterization of Arctic landscapes. We will apply a variety of data analytics algorithms, such as cluster analysis, complex object-based image analysis (COBIA), and neural networks. We also propose to use representativeness analysis within the Seward Peninsula domain to determine optimal sampling locations for fine-scale measurements. This methodology should provide an initial framework for analyzing dynamic landscape trends in Arctic ecosystems, such as shrubification and disturbances, and integration of ecoregions into multi-scale models.

A spatial implementation of the BIOME-BGC to model grassland GPP production and water budgets in the Ecuadorian Andean Region

NASA Astrophysics Data System (ADS)

Minaya, Veronica; Corzo, Gerald; van der Kwast, Johannes; Mynett, Arthur

2016-04-01

Many terrestrial biogeochemistry process models have been applied around the world at different scales and for a large range of ecosystems. Grasslands, and in particular the ones located in the Andean Region are essential ecosystems that sustain important ecological processes; however, just a few efforts have been made to estimate the gross primary production (GPP) and the hydrological budgets for this specific ecosystem along an altitudinal gradient. A previous study, which is one of the few available in the region, considered the heterogeneity of the main properties of the páramo vegetation and showed significant differences in plant functional types, site/soil parameters and daily meteorology. This study extends the work above mentioned and uses spatio-temporal analysis of the BIOME-BGC model results. This was done to simulate the GPP and the water fluxes in space and time, by applying altitudinal analysis. The catchment located at the southwestern slope of the Antisana volcano in Ecuador was selected as a representative area of the Andean páramos and its hydrological importance as one of the main sources of a water supply reservoir in the region. An accurate estimation of temporal changes in GPP in the region is important for carbon budget assessments, evaluation of the impact of climate change and biomass productivity. This complex and yet interesting problem was integrated by the ecosystem process model BIOME-BGC, the results were evaluated and associated to the land cover map where the growth forms of vegetation were identified. The responses of GPP and the water fluxes were not only dependent on the environmental drivers but also on the ecophysiology and the site specific parameters. The model estimated that the GPP at lower elevations doubles the amount estimated at higher elevations, which might have a large implication during extrapolations at larger spatio-temporal scales. The outcomes of the stand hydrological processes demonstrated a wrong consideration of a unique input of water in the system in addition to the poor estimation of the water storage leading to a wrong assessment of the water fluxes in the páramo ecosystem. A further development of the BIOME-BGC is needed to be applicable in the spatio-temporal analysis of the páramo vegetation in the region that can potentially assess the changes in the terrestrial ecosystem due to variations in the climatic drivers.

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.

Research infrastructure support to address ecosystem dynamics

NASA Astrophysics Data System (ADS)

Los, Wouter

2014-05-01

Predicting the evolution of ecosystems to climate change or human pressures is a challenge. Even understanding past or current processes is complicated as a result of the many interactions and feedbacks that occur within and between components of the system. This talk will present an example of current research on changes in landscape evolution, hydrology, soil biogeochemical processes, zoological food webs, and plant community succession, and how these affect feedbacks to components of the systems, including the climate system. Multiple observations, experiments, and simulations provide a wealth of data, but not necessarily understanding. Model development on the coupled processes on different spatial and temporal scales is sensitive for variations in data and of parameter change. Fast high performance computing may help to visualize the effect of these changes and the potential stability (and reliability) of the models. This may than allow for iteration between data production and models towards stable models reducing uncertainty and improving the prediction of change. The role of research infrastructures becomes crucial is overcoming barriers for such research. Environmental infrastructures are covering physical site facilities, dedicated instrumentation and e-infrastructure. The LifeWatch infrastructure for biodiversity and ecosystem research will provide services for data integration, analysis and modeling. But it has to cooperate intensively with the other kinds of infrastructures in order to support the iteration between data production and model computation. The cooperation in the ENVRI project (Common operations of environmental research infrastructures) is one of the initiatives to foster such multidisciplinary research.

Error quantification of a high-resolution coupled hydrodynamic-ecosystem coastal-ocean model: Part 2. Chlorophyll-a, nutrients and SPM

NASA Astrophysics Data System (ADS)

Allen, J. Icarus; Holt, Jason T.; Blackford, Jerry; Proctor, Roger

2007-12-01

Marine systems models are becoming increasingly complex and sophisticated, but far too little attention has been paid to model errors and the extent to which model outputs actually relate to ecosystem processes. Here we describe the application of summary error statistics to a complex 3D model (POLCOMS-ERSEM) run for the period 1988-1989 in the southern North Sea utilising information from the North Sea Project, which collected a wealth of observational data. We demonstrate that to understand model data misfit and the mechanisms creating errors, we need to use a hierarchy of techniques, including simple correlations, model bias, model efficiency, binary discriminator analysis and the distribution of model errors to assess model errors spatially and temporally. We also demonstrate that a linear cost function is an inappropriate measure of misfit. This analysis indicates that the model has some skill for all variables analysed. A summary plot of model performance indicates that model performance deteriorates as we move through the ecosystem from the physics, to the nutrients and plankton.

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.

Modeling for Ecosystem Services: Challenges and Opportunities

NASA Astrophysics Data System (ADS)

Guswa, A. J.; Brauman, K. A.; Ghile, Y.

2012-12-01

Ecosystem services are those values provided to human society by the structure and processes of ecosystems and landscapes. Water-related services include the transformation of precipitation impulses into supplies of water for hydropower, irrigation, and industrial and municipal uses, the retention and removal of applied nutrients and pollutants, flood-damage mitigation, recreation, and the provision of cultural and aesthetic values. Incorporation of changes to the value of these services in land-use planning and decision making requires identification of the relevant services, engagement of stakeholders, knowledge of how land-use changes impact water quality, quantity, and timing, and mechanisms for putting value on the hydrologic and biogeochemical changes. We present three examples that highlight the characteristics, challenges, and opportunities associated with prototypical decisions that incorporate ecosystem services values: scenario analysis, payment for ecosystem services, and optimal spatial planning. Through these examples, we emphasize the challenges of data availability, model resolution and complexity, and attribution of value. We also provide some suggestions for ways forward.

Functional groups of ecosystem engineers: a proposed classification with comments on current issues.

PubMed

Berke, Sarah K

2010-08-01

Ecologists have long known that certain organisms fundamentally modify, create, or define habitats by altering the habitat's physical properties. In the past 15 years, these processes have been formally defined as "ecosystem engineering", reflecting a growing consensus that environmental structuring by organisms represents a fundamental class of ecological interactions occurring in most, if not all, ecosystems. Yet, the precise definition and scope of ecosystem engineering remains debated, as one should expect given the complexity, enormity, and variability of ecological systems. Here I briefly comment on a few specific current points of contention in the ecosystem engineering concept. I then suggest that ecosystem engineering can be profitably subdivided into four narrower functional categories reflecting four broad mechanisms by which ecosystem engineering occurs: structural engineers, bioturbators, chemical engineers, and light engineers. Finally, I suggest some conceptual model frameworks that could apply broadly within these functional groups.

Sharing the floodplain: Mediated modeling for environmental management

USGS Publications Warehouse

Metcalf, S.S.; Wheeler, E.; BenDor, T.K.; Lubinski, S.J.; Hannon, B.M.

2010-01-01

Complex ecosystems, such as the Upper Mississippi River (UMR), present major management challenges. Such systems often provide a range of ecosystem services that are differentially valued by stakeholders representing distinct interests (e.g., agriculture, conservation, navigation) or institutions (e.g., federal and state agencies). When no single entity has the knowledge or authority to resolve conflicts over shared resource use, stakeholders may struggle to jointly understand the scope of the problem and to reach reasonable compromises. This paper explores mediated modeling as a group consensus building process for understanding relationships between ecological, economic and cultural well-being in the UMR floodplain. We describe a workshop structure used to engage UMR stakeholders that may be extended to resource use conflicts in other complex ecosystems. We provide recommendations for improving on these participatory methods in structuring future efforts. In conclusion, we suggest that tools which facilitate collaborative learning, such as mediated modeling, need to be incorporated at an institutional level as a vital element of integrated ecosystem management. ?? 2008 Elsevier Ltd.

Plant–herbivore–decomposer stoichiometric mismatches and nutrient cycling in ecosystems

PubMed Central

Cherif, Mehdi; Loreau, Michel

2013-01-01

Plant stoichiometry is thought to have a major influence on how herbivores affect nutrient availability in ecosystems. Most conceptual models predict that plants with high nutrient contents increase nutrient excretion by herbivores, in turn raising nutrient availability. To test this hypothesis, we built a stoichiometrically explicit model that includes a simple but thorough description of the processes of herbivory and decomposition. Our results challenge traditional views of herbivore impacts on nutrient availability in many ways. They show that the relationship between plant nutrient content and the impact of herbivores predicted by conceptual models holds only at high plant nutrient contents. At low plant nutrient contents, the impact of herbivores is mediated by the mineralization/immobilization of nutrients by decomposers and by the type of resource limiting the growth of decomposers. Both parameters are functions of the mismatch between plant and decomposer stoichiometries. Our work provides new predictions about the impacts of herbivores on ecosystem fertility that depend on critical interactions between plant, herbivore and decomposer stoichiometries in ecosystems. PMID:23303537

Follow-on proposal identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

Wright, P. M.; Ridd, M. K.

1986-01-01

Urban morphology (an examination of spatial fabric and structure), natural ecosystem (investigations emphasizing biophysical processes and patterns), and human ecosystem (emphasizing socio-economic and engineering parameters) were studied. The most critical variable, transpiration, in the ASPCON model, created by Jaynes (1978), describing the hydrology of aspen to conifer succession was studied to improve the accuracy. Transpiration is determined by a canopy transpiration model which estimates consumptive water use (CWU) for specific species and a plant activity index. Also studied was Pinyon-Juniper woodland erosion.

Great Lakes rivermouth ecosystems: scientific synthesis and management implications

USGS Publications Warehouse

Larson, James H.; Trebitz, Anett S.; Steinman, Alan D.; Wiley, Michael J.; Carlson Mazur, Martha; Pebbles, Victoria; Braun, Heather A.; Seelbach, Paul W.

2013-01-01

At the interface of the Great Lakes and their tributary rivers lies the rivermouths, a class of aquatic ecosystem where lake and lotic processes mix and distinct features emerge. Many rivermouths are the focal point of both human interaction with the Great Lakes and human impacts to the lakes; many cities, ports, and beaches are located in rivermouth ecosystems, and these human pressures often degrade key ecological functions that rivermouths provide. Despite their ecological uniqueness and apparent economic importance, there has been relatively little research on these ecosystems as a class relative to studies on upstream rivers or the open-lake waters. Here we present a synthesis of current knowledge about ecosystem structure and function in Great Lakes rivermouths based on studies in both Laurentian rivermouths, coastal wetlands, and marine estuarine systems. A conceptual model is presented that establishes a common semantic framework for discussing the characteristic spatial features of rivermouths. This model then is used to conceptually link ecosystem structure and function to ecological services provided by rivermouths. This synthesis helps identify the critical gaps in understanding rivermouth ecology. Specifically, additional information is needed on how rivermouths collectively influence the Great Lakes ecosystem, how human alterations influence rivermouth functions, and how ecosystem services provided by rivermouths can be managed to benefit the surrounding socioeconomic networks.

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

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

Turetsky, Merritt; Bond-Lamberty, Benjamin; Euskirchen, Eugenie S.

2012-08-24

Mosses in boreal and arctic ecosystems are ubiquitous components of plant communities, represent an important component of plant diversity, and strongly influence the cycling of water, nutrients, energy and carbon. Here we use a literature review and synthesis as well as model simulations to explore the role of moss in ecological stability and resilience. Our literature review of moss community responses to disturbance showed all possible responses (increases, decreases, no change) within most disturbance categories in boreal and arctic regions. Our modeling simulations suggest that loss of moss within northern plant communities will reduce soil carbon accumulation primarily by influencingmore » decomposition rates and soil nitrogen availability. While two models (HPM and STM-TEM) showed a significant effect of moss removal, results from the Biome-BGC and DVM-TEM models suggest that northern, moss-rich ecosystems would need to experience extreme perturbation before mosses were eliminated. We highlight a number of issues that have not been adequately explored in moss communities, such as functional redundancy and singularity, relationships between response and effect traits, phenotypical plasticity in traits, and whether the effects of moss on ecosystem processes scale with local abundance. We also suggest that as more models explore issues related to ecological resilience, issues related to both parameter and conceptual uncertainty should be addressed: are the models more limited by uncertainty in the parameterization of the processes included or by what is not represented in the model at all? It seems clear from our review that mosses need to be incorporated into models as one or more plant functional types, but more empirical work is needed to determine how to best aggregate species.« less

Comparative analysis of marine ecosystems: workshop on predator-prey interactions.

PubMed

Bailey, Kevin M; Ciannelli, Lorenzo; Hunsicker, Mary; Rindorf, Anna; Neuenfeldt, Stefan; Möllmann, Christian; Guichard, Frederic; Huse, Geir

2010-10-23

Climate and human influences on marine ecosystems are largely manifested by changes in predator-prey interactions. It follows that ecosystem-based management of the world's oceans requires a better understanding of food web relationships. An international workshop on predator-prey interactions in marine ecosystems was held at the Oregon State University, Corvallis, OR, USA on 16-18 March 2010. The meeting brought together scientists from diverse fields of expertise including theoretical ecology, animal behaviour, fish and seabird ecology, statistics, fisheries science and ecosystem modelling. The goals of the workshop were to critically examine the methods of scaling-up predator-prey interactions from local observations to systems, the role of shifting ecological processes with scale changes, and the complexity and organizational structure in trophic interactions.

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

USGS Publications Warehouse

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

2003-01-01

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

Global and regional ecosystem modeling: comparison of model outputs and field measurements

NASA Astrophysics Data System (ADS)

Olson, R. J.; Hibbard, K.

2003-04-01

The Ecosystem Model-Data Intercomparison (EMDI) Workshops provide a venue for global ecosystem modeling groups to compare model outputs against measurements of net primary productivity (NPP). The objective of EMDI Workshops is to evaluate model performance relative to observations in order to improve confidence in global model projections terrestrial carbon cycling. The questions addressed by EMDI include: How does the simulated NPP compare with the field data across biome and environmental gradients? How sensitive are models to site-specific climate? Does additional mechanistic detail in models result in a better match with field measurements? How useful are the measures of NPP for evaluating model predictions? How well do models represent regional patterns of NPP? Initial EMDI results showed general agreement between model predictions and field measurements but with obvious differences that indicated areas for potential data and model improvement. The effort was built on the development and compilation of complete and consistent databases for model initialization and comparison. Database development improves the data as well as models; however, there is a need to incorporate additional observations and model outputs (LAI, hydrology, etc.) for comprehensive analyses of biogeochemical processes and their relationships to ecosystem structure and function. EMDI initialization and NPP data sets are available from the Oak Ridge National Laboratory Distributed Active Archive Center http://www.daac.ornl.gov/. Acknowledgements: This work was partially supported by the International Geosphere-Biosphere Programme - Data and Information System (IGBP-DIS); the IGBP-Global Analysis, Interpretation and Modelling Task Force (GAIM); the National Center for Ecological Analysis and Synthesis (NCEAS); and the National Aeronautics and Space Administration (NASA) Terrestrial Ecosystem Program. Oak Ridge National Laboratory is managed by UT-Battelle LLC for the U.S. Department of Energy under contract DE-AC05-00OR22725

Hydraulic redistribution affects modeled carbon cycling via soil microbial activity and suppressed fire.

PubMed

Fu, Congsheng; Wang, Guiling; Bible, Kenneth; Goulden, Michael L; Saleska, Scott R; Scott, Russell L; Cardon, Zoe G

2018-04-13

Hydraulic redistribution (HR) of water from moist to drier soils, through plant roots, occurs world-wide in seasonally dry ecosystems. Although the influence of HR on landscape hydrology and plant water use has been amply demonstrated, HR's effects on microbe-controlled processes sensitive to soil moisture, including carbon and nutrient cycling at ecosystem scales, remain difficult to observe in the field and have not been integrated into a predictive framework. We incorporated a representation of HR into the Community Land Model (CLM4.5) and found the new model improved predictions of water, energy, and system-scale carbon fluxes observed by eddy covariance at four seasonally dry yet ecologically diverse temperate and tropical AmeriFlux sites. Modeled plant productivity and microbial activities were differentially stimulated by upward HR, resulting at times in increased plant demand outstripping increased nutrient supply. Modeled plant productivity and microbial activities were diminished by downward HR. Overall, inclusion of HR tended to increase modeled annual ecosystem uptake of CO 2 (or reduce annual CO 2 release to the atmosphere). Moreover, engagement of CLM4.5's ground-truthed fire module indicated that though HR increased modeled fuel load at all four sites, upward HR also moistened surface soil and hydrated vegetation sufficiently to limit the modeled spread of dry season fire and concomitant very large CO 2 emissions to the atmosphere. Historically, fire has been a dominant ecological force in many seasonally dry ecosystems, and intensification of soil drought and altered precipitation regimes are expected for seasonally dry ecosystems in the future. HR may play an increasingly important role mitigating development of extreme soil water potential gradients and associated limitations on plant and soil microbial activities, and may inhibit the spread of fire in seasonally dry ecosystems. © 2018 John Wiley & Sons Ltd.

Developing and applying metamodels of high resolution process-based simulations for high throughput exposure assessment of organic chemicals in riverine ecosystems

EPA Science Inventory

As defined by Wikipedia (https://en.wikipedia.org/wiki/Metamodeling), “(a) metamodel or surrogate model is a model of a model, and metamodeling is the process of generating such metamodels.” The goals of metamodeling include, but are not limited to (1) developing functional or st...

A Linked Model for Simulating Stand Development and Growth Processes of Loblolly Pine

Treesearch

V. Clark Baldwin; Phillip M. Dougherty; Harold E. Burkhart

1998-01-01

Linking models of different scales (e.g., process, tree-stand-ecosystem) is essential for furthering our understanding of stand, climatic, and edaphic effects on tree growth and forest productivity. Moreover, linking existing models that differ in scale and levels of resolution quickly identifies knowledge gaps in information required to scale from one level to another...

Simulation and sensitivity analysis of carbon storage and fluxes in the New Jersey Pinelands

Treesearch

Zewei Miao; Richard G. Lathrop; Ming Xu; Inga P. La Puma; Kenneth L. Clark; John Hom; Nicholas Skowronski; Steve Van Tuyl

2011-01-01

A major challenge in modeling the carbon dynamics of vegetation communities is the proper parameterization and calibration of eco-physiological variables that are critical determinants of the ecosystem process-based model behavior. In this study, we improved and calibrated a biochemical process-based WxBGC model by using in situ AmeriFlux eddy covariance tower...

Modeling plankton ecosystem functioning and nitrogen fluxes in the oligotrophic waters of the Beaufort Sea, Arctic Ocean: a focus on light-driven processes

NASA Astrophysics Data System (ADS)

Le Fouest, V.; Zakardjian, B.; Xie, H.; Raimbault, P.; Joux, F.; Babin, M.

2013-07-01

The Arctic Ocean (AO) undergoes profound changes of its physical and biotic environments due to climate change. In some areas of the Beaufort Sea, the stronger haline stratification observed in summer alters the plankton ecosystem structure, functioning and productivity, promoting oligotrophy. A one-dimension (1-D) physical-biological coupled model based on the large multiparametric database of the Malina project in the Beaufort Sea was used (i) to infer the plankton ecosystem functioning and related nitrogen fluxes and (ii) to assess the model sensitivity to key light-driven processes involved in nutrient recycling and phytoplankton growth. The coupled model suggested that ammonium photochemically produced from photosensitive dissolved organic nitrogen (i.e., photoammonification process) was a necessary nitrogen source to achieve the observed levels of microbial biomass and production. Photoammonification directly and indirectly (by stimulating the microbial food web activity) contributed to 70% and 18.5% of the 0-10 m and whole water column, respectively, simulated primary production (respectively 66% and 16% for the bacterial production). The model also suggested that variable carbon to chlorophyll ratios were required to simulate the observed herbivorous versus microbial food web competition and realistic nitrogen fluxes in the Beaufort Sea oligotrophic waters. In face of accelerating Arctic warming, more attention should be paid in the future to the mechanistic processes involved in food webs and functional group competition, nutrient recycling and primary production in poorly productive waters of the AO, as they are expected to expand rapidly.

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.

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.

Incorporating microbes into large-scale biogeochemical models

NASA Astrophysics Data System (ADS)

Allison, S. D.; Martiny, J. B.

2008-12-01

Micro-organisms, including Bacteria, Archaea, and Fungi, control major processes throughout the Earth system. Recent advances in microbial ecology and microbiology have revealed an astounding level of genetic and metabolic diversity in microbial communities. However, a framework for interpreting the meaning of this diversity has lagged behind the initial discoveries. Microbial communities have yet to be included explicitly in any major biogeochemical models in terrestrial ecosystems, and have only recently broken into ocean models. Although simplification of microbial communities is essential in complex systems, omission of community parameters may seriously compromise model predictions of biogeochemical processes. Two key questions arise from this tradeoff: 1) When and where must microbial community parameters be included in biogeochemical models? 2) If microbial communities are important, how should they be simplified, aggregated, and parameterized in models? To address these questions, we conducted a meta-analysis to determine if microbial communities are sensitive to four environmental disturbances that are associated with global change. In all cases, we found that community composition changed significantly following disturbance. However, the implications for ecosystem function were unclear in most of the published studies. Therefore, we developed a simple model framework to illustrate the situations in which microbial community changes would affect rates of biogeochemical processes. We found that these scenarios could be quite common, but powerful predictive models cannot be developed without much more information on the functions and disturbance responses of microbial taxa. Small-scale models that explicitly incorporate microbial communities also suggest that process rates strongly depend on microbial interactions and disturbance responses. The challenge is to scale up these models to make predictions at the ecosystem and global scales based on measurable parameters. We argue that meeting this challenge will require a coordinated effort to develop a series of nested models at scales ranging from the micron to the globe in order to optimize the tradeoff between model realism and feasibility.

Challenges of including nitrogen effects on decomposition in earth system models

NASA Astrophysics Data System (ADS)

Hobbie, S. E.

2011-12-01

Despite the importance of litter decomposition for ecosystem fertility and carbon balance, key uncertainties remain about how this fundamental process is affected by nitrogen (N) availability. Nevertheless, resolving such uncertainties is critical for mechanistic inclusion of such processes in earth system models, towards predicting the ecosystem consequences of increased anthropogenic reactive N. Towards that end, we have conducted a series of experiments examining nitrogen effects on litter decomposition. We found that both substrate N and externally supplied N (regardless of form) accelerated the initial decomposition rate. Faster initial decomposition rates were linked to the higher activity of carbohydrate-degrading enzymes associated with externally supplied N and the greater relative abundances of Gram negative and Gram positive bacteria associated with green leaves and externally supplied organic N (assessed using phospholipid fatty acid analysis, PLFA). By contrast, later in decomposition, externally supplied N slowed decomposition, increasing the fraction of slowly decomposing litter and reducing lignin-degrading enzyme activity and relative abundances of Gram negative and Gram positive bacteria. Our results suggest that elevated atmospheric N deposition may have contrasting effects on the dynamics of different soil carbon pools, decreasing mean residence times of active fractions comprising very fresh litter, while increasing those of more slowly decomposing fractions including more processed litter. Incorporating these contrasting effects of N on decomposition processes into models is complicated by lingering uncertainties about how these effects generalize across ecosystems and substrates.

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.

Linking Belowground Plant Traits With Ecosystem Processes: A Multi-Biome Perspective

NASA Astrophysics Data System (ADS)

Iversen, C. M.; Norby, R. J.; Childs, J.; McCormack, M. L.; Walker, A. P.; Hanson, P. J.; Warren, J.; Sloan, V. L.; Sullivan, P. F.; Wullschleger, S.; Powell, A. S.

2015-12-01

Fine plant roots are short-lived, narrow-diameter roots that play an important role in ecosystem carbon, water, and nutrient cycling in biomes ranging from the tundra to the tropics. Root ecologists make measurements at a millimeter scale to answer a question with global implications: In response to a changing climate, how do fine roots modulate the exchange of carbon between soils and the atmosphere and how will this response affect our future climate? In a Free-Air CO2 Enrichment experiment in Oak Ridge, TN, elevated [CO2] caused fine roots to dive deeper into the soil profile in search of limiting nitrogen, which led to increased soil C storage in deep soils. In contrast, the fine roots of trees and shrubs in an ombrotrophic bog are constrained to nutrient-poor, oxic soils above the average summer water table depth, though this may change with warmer, drier conditions. Tundra plant species are similarly constrained to surface organic soils by permafrost or waterlogged soils, but have many adaptations that alter ecosystem C fluxes, including aerenchyma that oxygenate the rhizosphere but also allow direct methane flux to the atmosphere. FRED, a global root trait database, will allow terrestrial biosphere models to represent the complexity of root traits across the globe, informing both model representation of ecosystem C and nutrient fluxes, but also the gaps where measurements are needed on plant-soil interactions (for example, in the tropical biome). While the complexity of mm-scale measurements may never have a place in large-scale global models, close collaboration between empiricists and modelers can help to guide the scaling of important, yet small-scale, processes to quantify their important roles in larger-scale ecosystem fluxes.

Combining Microbial Enzyme Kinetics Models with Light Use Efficiency Models to Predict CO2 and CH4 Ecosystem Exchange from Flooded and Drained Peatland Systems

NASA Astrophysics Data System (ADS)

Oikawa, P. Y.; Jenerette, D.; Knox, S. H.; Sturtevant, C. S.; Verfaillie, J. G.; Baldocchi, D. D.

2014-12-01

Under California's Cap-and-Trade program, companies are looking to invest in land-use practices that will reduce greenhouse gas (GHG) emissions. The Sacramento-San Joaquin River Delta is a drained cultivated peatland system and a large source of CO2. To slow soil subsidence and reduce CO2 emissions, there is growing interest in converting drained peatlands to wetlands. However, wetlands are large sources of CH4 that could offset CO2-based GHG reductions. The goal of our research is to provide accurate measurements and model predictions of the changes in GHG budgets that occur when drained peatlands are restored to wetland conditions. We have installed a network of eddy covariance towers across multiple land use types in the Delta and have been measuring CO2 and CH4 ecosystem exchange for multiple years. In order to upscale these measurements through space and time we are using these data to parameterize and validate a process-based biogeochemical model. To predict gross primary productivity (GPP), we are using a simple light use efficiency (LUE) model which requires estimates of light, leaf area index and air temperature and can explain 90% of the observed variation in GPP in a mature wetland. To predict ecosystem respiration we have adapted the Dual Arrhenius Michaelis-Menten (DAMM) model. The LUE-DAMM model allows accurate simulation of half-hourly net ecosystem exchange (NEE) in a mature wetland (r2=0.85). We are working to expand the model to pasture, rice and alfalfa systems in the Delta. To predict methanogenesis, we again apply a modified DAMM model, using simple enzyme kinetics. However CH4 exchange is complex and we have thus expanded the model to predict not only microbial CH4 production, but also CH4 oxidation, CH4 storage and the physical processes regulating the release of CH4 to the atmosphere. The CH4-DAMM model allows accurate simulation of daily CH4 ecosystem exchange in a mature wetland (r2=0.55) and robust estimates of annual CH4 budgets. The LUE- and CH4-DAMM models will advance understanding of biogeochemisty and microbial processes in managed peatland systems as well as aid the development of a GHG protocol in the Delta that can provide financial incentive to farmers to reduce GHG emissions under California's Cap and Trade program.

Stable isotope views on ecosystem function: challenging or challenged?

PubMed

Resco, Víctor; Querejeta, José I; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A; Torres-Cañabate, Patricia; Valladares, Fernando

2010-06-23

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Ubeda, 18-22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes.

Stable isotope views on ecosystem function: challenging or challenged?

PubMed Central

Resco, Víctor; Querejeta, José I.; Ogle, Kiona; Voltas, Jordi; Sebastià, Maria-Teresa; Serrano-Ortiz, Penélope; Linares, Juan C.; Moreno-Gutiérrez, Cristina; Herrero, Asier; Carreira, José A.; Torres-Cañabate, Patricia; Valladares, Fernando

2010-01-01

Stable isotopes and their potential for detecting various and complex ecosystem processes are attracting an increasing number of scientists. Progress is challenging, particularly under global change scenarios, but some established views have been challenged. The IX meeting of the Spanish Association of Terrestrial Ecology (AAET, Úbeda, 18–22 October 2009) hosted a symposium on the ecology of stable isotopes where the linear mixing model approach of partitioning sinks and sources of carbon and water fluxes within an ecosystem was challenged, and new applications of stable isotopes for the study of plant interactions were evaluated. Discussion was also centred on the need for networks that monitor ecological processes using stable isotopes and key ideas for fostering future research with isotopes. PMID:20015858

Evaluating alternative approaches to modeling terrestrial C and N interactions using observations of ecosystem response to nitrogen deposition and experimental fertilization

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Bonan, G. B.; Goodale, C. L.

2012-12-01

In many forest ecosystems, nitrogen deposition is increasing carbon storage and reducing climate warming from fossil fuel emissions. Accurately modeling the forest carbon sequestration response to elevated nitrogen deposition using global biogeochemical models coupled to climate models is therefore important. Here, we use observations of the forest carbon response to both nitrogen fertilization experiments and nitrogen deposition gradients to test and improve a global biogeochemical model (CLM-CN 4.0). We introduce a series of model modifications to the CLM-CN that 1) creates a more closed nitrogen cycle with reduced nitrogen fixation and N gas loss and 2) includes buffering of plant nitrogen uptake and buffering of soil nitrogen available for plants and microbial processes. Overall, the modifications improved the comparison of the model predictions to the observational data by increasing the carbon storage response to historical nitrogen deposition (1850-2004) in temperate forest ecosystems by 144% and reducing the response to nitrogen fertilization. The increased sensitivity to nitrogen deposition was primarily attributable to greater retention of nitrogen deposition in the ecosystem and a greater role of synergy between nitrogen deposition and rising atmospheric CO2. Based on our results, we suggest that nitrogen retention should be an important attribute investigated in model inter-comparisons. To understand the specific ecosystem processes that contribute to the sensitivity of carbon storage to nitrogen deposition, we examined sensitivity to nitrogen deposition in a set of intermediary models that isolate the key differences in model structure between the CLM-CN 4.0 and the modified version. We demonstrate that the nitrogen deposition response was most sensitive to the implementation of a more closed nitrogen cycle and buffered plant uptake of soil mineral nitrogen, and less sensitive to modifications of the canopy scaling of photosynthesis, soil buffering of available nitrogen, and plant buffering of labile nitrogen. By comparing carbon storage sensitivity to observational data from both nitrogen deposition gradients and nitrogen fertilization experiments, we show different observed estimates of sensitivity between these two approaches could be explained by differences in the magnitude and time-scale of nitrogen additions.

Modeling for regional ecosystem sustainable development under uncertainty--A case study of Dongying, China.

PubMed

Zhang, K; Li, Y P; Huang, G H; You, L; Jin, S W

2015-11-15

In this study, a superiority-inferiority two-stage stochastic programming (STSP) method is developed for planning regional ecosystem sustainable development. STSP can tackle uncertainties expressed as fuzzy sets and probability distributions; it can be used to analyze various policy scenarios that are associated with different levels of economic penalties when the promised targets are violated. STSP is applied to a real case of planning regional ecosystem sustainable development in the City of Dongying, where ecosystem services valuation approaches are incorporated within the optimization process. Regional ecosystem can provide direct and indirect services and intangible benefits to local economy. Land trading mechanism is introduced for planning the regional ecosystem's sustainable development, where wetlands are buyers who would protect regional ecosystem components and self-organization and maintain its integrity. Results of regional ecosystem activities, land use patterns, and land trading schemes have been obtained. Results reveal that, although large-scale reclamation projects can bring benefits to the local economy development, they can also bring with negative effects to the coastal ecosystem; among all industry activities oil field is the major contributor with a large number of pollutant discharges into local ecosystem. Results also show that uncertainty has an important role in successfully launching such a land trading program and trading scheme can provide more effective manner to sustain the regional ecosystem. The findings can help decision makers to realize the sustainable development of ecological resources in the process of rapid industrialization, as well as the integration of economic and ecological benefits. Copyright © 2015 Elsevier B.V. All rights reserved.

Combined global change effects on ecosystem processes in nine U.S

Treesearch

Melannie D. Hartman; Jill S. Baron; Holly A. Ewing; Kathleen C. Weathers; Chelcy Miniat

2014-01-01

Concurrent changes in climate, atmospheric nitrogen (N) deposition, and increasing levels of atmospheric carbon dioxide (CO2) affect ecosystems in complex ways. The DayCent-Chem model was used to investigate the combined effects of these human-caused drivers of change over the period 1980–2075 at seven forested montane and two alpine watersheds...

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...

Windstorm damage in Boundary Waters Canoe Area Wilderness (Minnesota, USA): Evaluating landscape-level risk factors

Treesearch

W. Keith Moser; Mark D. Nelson

2009-01-01

Ecosystem management requires an understanding of disturbance processes and their influence on forests. One of these disturbances is damage due to severe wind events. In an ideal model, assessing risk of windstorm damage to a forested ecosystem entails defining tree-, stand-, and landscape-level factors that influence response and recovery. Data are not always...

Statistical uncertainty of eddy flux-based estimates of gross ecosystem carbon exchange at Howland Forest, Maine

Treesearch

S.C. Hagen; B.H. Braswell; E. Linder; S. Frolking; A.D. Richardson; David Hollinger. D.Y; Hollinger. D.Y

2006-01-01

We present an uncertainty analysis of gross ecosystem carbon exchange (GEE) estimates derived from 7 years of continuous eddy covariance measurements of forest atmosphere CO2 fluxes at Howland Forest, Maine, USA. These data, which have high temporal resolution, can be used to validate process modeling analyses, remote sensing assessments, and field surveys. However,...

Terrestrial biosphere models need better representation of vegetation phenology: results from the North American Carbon Program Site Synthesis

Treesearch

Andrew D. Richardson; Ryan S. Anderson; M. Altaf Arain; Alan G. Barr; Gil Bohrer; Guangsheng Chen; Jing M. Chen; Philippe Ciais; Kenneth J. David; Ankur R. Desai; Michael C. Dietze; Danilo Dragoni; Steven R. Garrity; Christopher M. Gough; Robert Grant; David Hollinger; Hank A. Margolis; Harry McCaughey; Mirco Migliavacca; Russel K. Monson; J. William Munger; Benjamin Poulter; Brett M. Raczka; Daniel M. Ricciuto; Alok K. Sahoo; Kevin Schaefer; Hanqin Tian; Rodrigo Vargas; Hans Verbeeck; Jingfeng Xiao; Yongkang Xue

2012-01-01

Phenology, by controlling the seasonal activity of vegetation on the land surface, plays a fundamental role in regulating photosynthesis and other ecosystem processes, as well as competitive interactions and feedbacks to the climate system. We conducted an analysis to evaluate the representation of phenology, and the associated seasonality of ecosystem-scale CO

From precipitation to groundwater baseflow in a native prairie ecosystem: a regional study of the Konza LTER in the Flint Hills of Kansas, USA

USDA-ARS?s Scientific Manuscript database

Methods are developed to study hydrologic interactions across the surficial/groundwater interface in a native prairie ecosystem. Surficial ecohydrologic processes are simulated with the USDA’s EPIC model using daily climate data from the Kansas Weather Data Library, vegetation and soil data from the...

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

DOE PAGES

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; ...

2018-03-13

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery,more » we derived time series characterizing vegetation colour, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the "greenness rising" and end of the "greenness falling" stages. Lastly, the database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.« less

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

PubMed Central

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; Aubrecht, Donald M.; Chen, Min; Gray, Josh M.; Johnston, Miriam R.; Keenan, Trevor F.; Klosterman, Stephen T.; Kosmala, Margaret; Melaas, Eli K.; Friedl, Mark A.; Frolking, Steve

2018-01-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems. PMID:29533393

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

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

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery,more » we derived time series characterizing vegetation colour, including "canopy greenness", processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the "greenness rising" and end of the "greenness falling" stages. Lastly, the database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.« less

Tracking vegetation phenology across diverse North American biomes using PhenoCam imagery

NASA Astrophysics Data System (ADS)

Richardson, Andrew D.; Hufkens, Koen; Milliman, Tom; Aubrecht, Donald M.; Chen, Min; Gray, Josh M.; Johnston, Miriam R.; Keenan, Trevor F.; Klosterman, Stephen T.; Kosmala, Margaret; Melaas, Eli K.; Friedl, Mark A.; Frolking, Steve

2018-03-01

Vegetation phenology controls the seasonality of many ecosystem processes, as well as numerous biosphere-atmosphere feedbacks. Phenology is also highly sensitive to climate change and variability. Here we present a series of datasets, together consisting of almost 750 years of observations, characterizing vegetation phenology in diverse ecosystems across North America. Our data are derived from conventional, visible-wavelength, automated digital camera imagery collected through the PhenoCam network. For each archived image, we extracted RGB (red, green, blue) colour channel information, with means and other statistics calculated across a region-of-interest (ROI) delineating a specific vegetation type. From the high-frequency (typically, 30 min) imagery, we derived time series characterizing vegetation colour, including “canopy greenness”, processed to 1- and 3-day intervals. For ecosystems with one or more annual cycles of vegetation activity, we provide estimates, with uncertainties, for the start of the “greenness rising” and end of the “greenness falling” stages. The database can be used for phenological model validation and development, evaluation of satellite remote sensing data products, benchmarking earth system models, and studies of climate change impacts on terrestrial ecosystems.

Evaluating Productivity Predictions Under Elevated CO2 Conditions: Multi-Model Benchmarking Across FACE Experiments

NASA Astrophysics Data System (ADS)

Cowdery, E.; Dietze, M.

2016-12-01

As atmospheric levels of carbon dioxide levels continue to increase, it is critical that terrestrial ecosystem models can accurately predict ecological responses to the changing environment. Current predictions of net primary productivity (NPP) in response to elevated atmospheric CO2 concentration are highly variable and contain a considerable amount of uncertainty.The Predictive Ecosystem Analyzer (PEcAn) is an informatics toolbox that wraps around an ecosystem model and can be used to help identify which factors drive uncertainty. We tested a suite of models (LPJ-GUESS, MAESPA, GDAY, CLM5, DALEC, ED2), which represent a range from low to high structural complexity, across a range of Free-Air CO2 Enrichment (FACE) experiments: the Kennedy Space Center Open Top Chamber Experiment, the Rhinelander FACE experiment, the Duke Forest FACE experiment and the Oak Ridge Experiment on CO2 Enrichment. These tests were implemented in a novel benchmarking workflow that is automated, repeatable, and generalized to incorporate different sites and ecological models. Observational data from the FACE experiments represent a first test of this flexible, extensible approach aimed at providing repeatable tests of model process representation.To identify and evaluate the assumptions causing inter-model differences we used PEcAn to perform model sensitivity and uncertainty analysis, not only to assess the components of NPP, but also to examine system processes such nutrient uptake and and water use. Combining the observed patterns of uncertainty between multiple models with results of the recent FACE-model data synthesis project (FACE-MDS) can help identify which processes need further study and additional data constraints. These findings can be used to inform future experimental design and in turn can provide informative starting point for data assimilation.

Global patterns and climate drivers of water-use efficiency in terrestrial ecosystems deduced from satellite-based datasets and carbon cycle models

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

Sun, Yan; Piao, Shilong; Huang, Mengtian

Our aim is to investigate how ecosystem water-use efficiency (WUE) varies spatially under different climate conditions, and how spatial variations in WUE differ from those of transpiration-based water-use efficiency (WUE t) and transpiration-based inherent water-use efficiency (IWUE t). LocationGlobal terrestrial ecosystems. We investigated spatial patterns of WUE using two datasets of gross primary productivity (GPP) and evapotranspiration (ET) and four biosphere model estimates of GPP and ET. Spatial relationships between WUE and climate variables were further explored through regression analyses. Global WUE estimated by two satellite-based datasets is 1.9 ± 0.1 and 1.8 ± 0.6g C m -2mm -1 lowermore » than the simulations from four process-based models (2.0 ± 0.3g C m -2mm -1) but comparable within the uncertainty of both approaches. In both satellite-based datasets and process models, precipitation is more strongly associated with spatial gradients of WUE for temperate and tropical regions, but temperature dominates north of 50 degrees N. WUE also increases with increasing solar radiation at high latitudes. The values of WUE from datasets and process-based models are systematically higher in wet regions (with higher GPP) than in dry regions. WUE t shows a lower precipitation sensitivity than WUE, which is contrary to leaf- and plant-level observations. IWUE t, the product of WUE t and water vapour deficit, is found to be rather conservative with spatially increasing precipitation, in agreement with leaf- and plant-level measurements. In conclusion, WUE, WUE t and IWUE t produce different spatial relationships with climate variables. In dry ecosystems, water losses from evaporation from bare soil, uncorrelated with productivity, tend to make WUE lower than in wetter regions. Yet canopy conductance is intrinsically efficient in those ecosystems and maintains a higher IWUEt. This suggests that the responses of each component flux of evapotranspiration should be analysed separately when investigating regional gradients in WUE, its temporal variability and its trends.« less

Global patterns and climate drivers of water-use efficiency in terrestrial ecosystems deduced from satellite-based datasets and carbon cycle models

DOE PAGES

Sun, Yan; Piao, Shilong; Huang, Mengtian; ...

2015-12-23

Our aim is to investigate how ecosystem water-use efficiency (WUE) varies spatially under different climate conditions, and how spatial variations in WUE differ from those of transpiration-based water-use efficiency (WUE t) and transpiration-based inherent water-use efficiency (IWUE t). LocationGlobal terrestrial ecosystems. We investigated spatial patterns of WUE using two datasets of gross primary productivity (GPP) and evapotranspiration (ET) and four biosphere model estimates of GPP and ET. Spatial relationships between WUE and climate variables were further explored through regression analyses. Global WUE estimated by two satellite-based datasets is 1.9 ± 0.1 and 1.8 ± 0.6g C m -2mm -1 lowermore » than the simulations from four process-based models (2.0 ± 0.3g C m -2mm -1) but comparable within the uncertainty of both approaches. In both satellite-based datasets and process models, precipitation is more strongly associated with spatial gradients of WUE for temperate and tropical regions, but temperature dominates north of 50 degrees N. WUE also increases with increasing solar radiation at high latitudes. The values of WUE from datasets and process-based models are systematically higher in wet regions (with higher GPP) than in dry regions. WUE t shows a lower precipitation sensitivity than WUE, which is contrary to leaf- and plant-level observations. IWUE t, the product of WUE t and water vapour deficit, is found to be rather conservative with spatially increasing precipitation, in agreement with leaf- and plant-level measurements. In conclusion, WUE, WUE t and IWUE t produce different spatial relationships with climate variables. In dry ecosystems, water losses from evaporation from bare soil, uncorrelated with productivity, tend to make WUE lower than in wetter regions. Yet canopy conductance is intrinsically efficient in those ecosystems and maintains a higher IWUEt. This suggests that the responses of each component flux of evapotranspiration should be analysed separately when investigating regional gradients in WUE, its temporal variability and its trends.« less

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.

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.

Functional outcomes of fungal community shifts driven by tree genotype and spatial-temporal factors in Mediterranean pine forests.

PubMed

Pérez-Izquierdo, Leticia; Zabal-Aguirre, Mario; Flores-Rentería, Dulce; González-Martínez, Santiago C; Buée, Marc; Rincón, Ana

2017-04-01

Fungi provide relevant ecosystem services contributing to primary productivity and the cycling of nutrients in forests. These fungal inputs can be decisive for the resilience of Mediterranean forests under global change scenarios, making necessary an in-deep knowledge about how fungal communities operate in these ecosystems. By using high-throughput sequencing and enzymatic approaches, we studied the fungal communities associated with three genotypic variants of Pinus pinaster trees, in 45-year-old common garden plantations. We aimed to determine the impact of biotic (i.e., tree genotype) and abiotic (i.e., season, site) factors on the fungal community structure, and to explore whether structural shifts triggered functional responses affecting relevant ecosystem processes. Tree genotype and spatial-temporal factors were pivotal structuring fungal communities, mainly by influencing their assemblage and selecting certain fungi. Diversity variations of total fungal community and of that of specific fungal guilds, together with edaphic properties and tree's productivity, explained relevant ecosystem services such as processes involved in carbon turnover and phosphorous mobilization. A mechanistic model integrating relations of these variables and ecosystem functional outcomes is provided. Our results highlight the importance of structural shifts in fungal communities because they may have functional consequences for key ecosystem processes in Mediterranean forests. © 2017 Society for Applied Microbiology and John Wiley and Sons Ltd.

Contrasting responses of water use efficiency to drought across global terrestrial ecosystems

PubMed Central

Yang, Yuting; Guan, Huade; Batelaan, Okke; McVicar, Tim R.; Long, Di; Piao, Shilong; Liang, Wei; Liu, Bing; Jin, Zhao; Simmons, Craig T.

2016-01-01

Drought is an intermittent disturbance of the water cycle that profoundly affects the terrestrial carbon cycle. However, the response of the coupled water and carbon cycles to drought and the underlying mechanisms remain unclear. Here we provide the first global synthesis of the drought effect on ecosystem water use efficiency (WUE = gross primary production (GPP)/evapotranspiration (ET)). Using two observational WUE datasets (i.e., eddy-covariance measurements at 95 sites (526 site-years) and global gridded diagnostic modelling based on existing observation and a data-adaptive machine learning approach), we find a contrasting response of WUE to drought between arid (WUE increases with drought) and semi-arid/sub-humid ecosystems (WUE decreases with drought), which is attributed to different sensitivities of ecosystem processes to changes in hydro-climatic conditions. WUE variability in arid ecosystems is primarily controlled by physical processes (i.e., evaporation), whereas WUE variability in semi-arid/sub-humid regions is mostly regulated by biological processes (i.e., assimilation). We also find that shifts in hydro-climatic conditions over years would intensify the drought effect on WUE. Our findings suggest that future drought events, when coupled with an increase in climate variability, will bring further threats to semi-arid/sub-humid ecosystems and potentially result in biome reorganization, starting with low-productivity and high water-sensitivity grassland. PMID:26983909

Process-Driven Ecological Modeling for Landscape Change Analysis

NASA Astrophysics Data System (ADS)

Altman, S.; Reif, M. K.; Swannack, T. M.

2013-12-01

Landscape pattern is an important driver in ecosystem dynamics and can control system-level functions such as nutrient cycling, connectivity, biodiversity and carbon sequestration. However, the links between process, pattern and function remain ambiguous. Understanding the quantitative relationship between ecological processes and landscape pattern across temporal and spatial scales is vital for successful management and implementation of ecosystem-level projects. We used remote sensing imagery to develop critical landscape metrics to understand the factors influencing landscape change. Our study area, a coastal area in southwest Florida, is highly dynamic with critically eroding beaches and a range of natural and developed land cover types. Hurricanes in 2004 and 2005 caused a breach along the coast of North Captiva Island that filled in by 2010. We used a time series of light detection and ranging (lidar) elevation data and hyperspectral imagery from 2006 and 2010 to determine land cover changes. Landscape level metrics used included: Largest Patch Index, Class Area, Area-weighted mean area, Clumpiness, Area-weighted Contiguity Index, Number of Patches, Percent of landcover, Area-weighted Shape. Our results showed 1) 27% increase in sand/soil class as the channel repaired itself and shoreline was reestablished, 2) 40% decrease in the mudflat class area due to conversion to sand/soil and water, 3) 30% increase in non-wetland vegetation class as a result of new vegetation around the repaired channel, and 4) the water class only slightly increased though there was a marked increase in the patch size area. Thus, the smaller channels disappeared with the infilling of the channel, leaving much larger, less complex patches behind the breach. Our analysis demonstrated that quantification of landscape pattern is critical to linking patterns to ecological processes and understanding how both affect landscape change. Our proof of concept indicated that ecological processes can correlate to landscape pattern and that ecosystem function changes significantly as pattern changes. However, the number of links between landscape metrics and ecological processes are highly variable. Extensively studied processes such as biodiversity can be linked to numerous landscape metrics. In contrast, correlations between sediment cycling and landscape pattern have only been evaluated for a limited number of metrics. We are incorporating these data into a relational database linking landscape and ecological patterns, processes and metrics. The database will be used to parameterize site-specific landscape evolution models projecting how landscape pattern will change as a result of future ecosystem restoration projects. The model is a spatially-explicit, grid-based model that projects changes in community composition based on changes in soil elevations. To capture scalar differences in landscape change, local and regional landscape metrics are analyzed at each time step and correlated with ecological processes to determine how ecosystem function changes with scale over time.

OysterFutures: Integrating Stakeholder Objectives with Natural System Models to Promote Sustainable Natural Resource Policy

NASA Astrophysics Data System (ADS)

North, E. W.; Blair, J.; Cornwell, J. C.; Freitag, A. E.; Gawde, R. K.; Hartley, T. W.; Hood, R. R.; Jones, R. M.; Miller, T. J.; Thomas, J. E.; Wainger, L. A.; Wilberg, M. J.

2016-02-01

Achieving effective natural resource management is challenged by multiple and often competing objectives, a restricted set of policy options, and uncertainty in the performance of those options. Yet, managers need policies that allow continued use of natural resources while ensuring access for future generations and maintenance of ecosystem services. Formal approaches are needed that will assist managers and stakeholders in choosing policy options that have a high likelihood of achieving social, ecological, and economic goals. The goal of this project, OysterFutures, is to address this need by improving the use of predictive models to support sustainable natural resource policy and management. A stakeholder-centered process will be used to build an integrated model that combines estuarine physics, oyster life history, and the ecosystem services that oysters provide (e.g., harvest, water quality) to forecast outcomes under alternative management strategies. Through a series of facilitated meetings, stakeholders will participate in a science-based collaborative process which will allow them to project how well policies are expected to meet their objectives using the integrated model. This iterative process will ensure that the model will incorporate the complex human uses of the ecosystem as well as focus on the outcomes most important to the stakeholders. In addition, a study of the socioeconomic drivers of stakeholder involvement, information flow, use and influence, and policy formation will be undertaken to improve the process, enhance implementation success of recommended policies, and provide new ideas for integrating natural and social sciences, and scientists, in sustainable resource management. In this presentation, the strategy for integrating natural system models, stakeholder views, and sociological studies as well as methods for selecting stakeholders and facilitating stakeholder meetings will be described and discussed.

[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.

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

PubMed

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

2016-12-01

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

A process-based framework for soil ecosystem services study and management.

PubMed

Su, Changhong; Liu, Huifang; Wang, Shuai

2018-06-15

Soil provides various indispensable ecosystem services for human society. Soil's complex structure and property makes the soil ecological processes complicated and brings about tough challenges for soil ecosystem services study. Most of the current frameworks on soil services focus exclusively on services per se, neglecting the links and underlying ecological mechanisms. This article put forward a framework on soil services by stressing the underlying soil mechanisms and processes, which includes: 1) analyzing soil natural capital stock based on soil structure and property, 2) disentangling the underlying complex links and soil processes, 3) soil services valuation based on field investigation and spatial explicit models, and 4) enacting soil management strategy based on soil services and their driving factors. By application of this framework, we assessed the soil services of sediment retention, water yield, and grain production in the Upper-reach Fenhe Watershed. Based on the ecosystem services and human driving factors, the whole watershed was clustered into five groups: 1) municipal area, 2) typical coal mining area, 3) traditional farming area, 4) unsustainable urbanizing area, and 5) ecological conservation area. Management strategies on soils were made according to the clustering based soil services and human activities. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

Plant community mediation of ecosystem responses to global change factors

NASA Astrophysics Data System (ADS)

Churchill, A. C.

2017-12-01

Human alteration of the numerous environmental drivers affecting ecosystem processes is unprecedented in the last century, including changes in climate regimes and rapid increases in the availability of biologically active nitrogen (N). Plant communities may offer stabilizing or amplifying feedbacks mediating potential ecosystem responses to these alterations, and my research seeks to examine the conditions associated with when plant feedbacks are important for ecosystem change. My dissertation research focused on the unintended consequences of N deposition into natural landscapes, including alpine ecosystems which are particularly susceptible to adverse environmental impacts. In particular, I examined alpine plant and soil responses to N deposition 1) across multiple spatial scales throughout the Southern Rocky Mountains, 2) among diverse plant communities associated with unique environmental conditions common in the alpine of this region, and 3) among ecosystem pools of N contributing to stabilization of N inputs within those communities. I found that communities responded to inputs of N differently, often associated with traits of dominant plant species but these responses were intimately linked with the abiotic conditions of each independent community. Even so, statistical models predicting metrics of N processing in the alpine were improved by encompassing both abiotic and biotic components of the main community types.

Modeling the effect of land use change on hydrology of a forested watershed in coastal South Carolina.

Treesearch

Zhaohua Dai; Devendra M. Amatya; Ge Sun; Changsheng Li; Carl C. Trettin; Harbin Li

2009-01-01

Since hydrology is one of main factors controlling wetland functions, hydrologic models are useful for evaluating the effects of land use change on we land ecosystems. We evaluated two process-based hydrologic models with...

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.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

Cold air drainage flows subsidize montane valley ecosystem productivity.

PubMed

Novick, Kimberly A; Oishi, A Christopher; Miniat, Chelcy Ford

2016-12-01

In mountainous areas, cold air drainage from high to low elevations has pronounced effects on local temperature, which is a critical driver of many ecosystem processes, including carbon uptake and storage. Here, we leverage new approaches for interpreting ecosystem carbon flux observations in complex terrain to quantify the links between macro-climate condition, drainage flows, local microclimate, and ecosystem carbon cycling in a southern Appalachian valley. Data from multiple long-running climate stations and multiple eddy covariance flux towers are combined with simple models for ecosystem carbon fluxes. We show that cold air drainage into the valley suppresses local temperature by several degrees at night and for several hours before and after sunset, leading to reductions in growing season respiration on the order of ~8%. As a result, we estimate that drainage flows increase growing season and annual net carbon uptake in the valley by >10% and >15%, respectively, via effects on microclimate that are not be adequately represented in regional- and global-scale terrestrial ecosystem models. Analyses driven by chamber-based estimates of soil and plant respiration reveal cold air drainage effects on ecosystem respiration are dominated by reductions to the respiration of aboveground biomass. We further show that cold air drainage proceeds more readily when cloud cover and humidity are low, resulting in the greatest enhancements to net carbon uptake in the valley under clear, cloud-free (i.e., drought-like) conditions. This is a counterintuitive result that is neither observed nor predicted outside of the valley, where nocturnal temperature and respiration increase during dry periods. This result should motivate efforts to explore how topographic flows may buffer eco-physiological processes from macroscale climate change. © 2016 John Wiley & Sons Ltd.

Trophic flow structure of a neotropical estuary in northeastern Brazil and the comparison of ecosystem model indicators of estuaries

NASA Astrophysics Data System (ADS)

Lira, Alex; Angelini, Ronaldo; Le Loc'h, François; Ménard, Frédéric; Lacerda, Carlos; Frédou, Thierry; Lucena Frédou, Flávia

2018-06-01

We developed an Ecopath model for the Estuary of Sirinhaém River (SIR), a small-sized system surrounded by mangroves, subject to high impact, mainly by the sugar cane and other farming industries in order to describe the food web structure and trophic interactions. In addition, we compared our findings with those of 20 available Ecopath estuarine models for tropical, subtropical and temperate regions, aiming to synthesize the knowledge on trophic dynamics and provide a comprehensive analysis of the structures and functioning of estuaries. Our model consisted of 25 compartments and its indicators were within the expected range for estuarine areas around the world. The average trophic transfer efficiency for the entire system was 11.8%, similar to the theoretical value of 10%. The Keystone Index and MTI (Mixed Trophic Impact) analysis indicated that the snook (Centropomus undecimalis and Centropomus parallelus) and jack (Caranx latus and Caranx hippos) are considered as key resources in the system, revealing their high impact in the food web. Both groups have a high ecological and commercial relevance, despite the unregulated fisheries. As result of the comparison of ecosystem model indicators in estuaries, differences in the ecosystem structure from the low latitude zones (tropical estuaries) to the high latitude zones (temperate system) were noticed. The structure of temperate and sub-tropical estuaries is based on high flows of detritus and export, while tropical systems have high biomass, respiration and consumption rates. Higher values of System Omnivory Index (SOI) and Overhead (SO) were observed in the tropical and subtropical estuaries, denoting a more complex food chain. Globally, none of the estuarine models were classified as fully mature ecosystems, although the tropical ecosystems were considered more mature than the subtropical and temperate ecosystems. This study is an important contribution to the trophic modeling of estuaries, which may also help the knowledge of the role of key ecosystem processes in SIR.

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.

Proposal for including what is valuable to ecosystems in environmental assessments.

PubMed

Campbell, D E

2001-07-15

Assessment scientists and managers depend on social values to identify the goals that will be used to guide environmental assessments. These goals are commonly identified by examining the vested interests of the various social groups that are stakeholders in a region. However, knowledge about what people value represents only part of the information needed to identify comprehensive assessment goals for environmental systems that include both economic and ecological components and processes. All parties also need to understand what is valuable to ecosystems because that determines the ecological patterns and processes that prevail in the long run. The competition among alternate system designs for available energy determines the viability of the choices that people make for their environment. Ecosystems that prevail in competition use the process of self-organization to create system designs that maximize the use of ever-changing sources of available energy. The efficacy of ecosystem designs can be evaluated using the maximum empower principle, which states that ecosystems evolve toward designs that maximize empower (energy use per unit time). Energy is an accounting quantity that normalizes the different kinds of energy developed in a system so that they may be compared. The counter-intuitive and sometimes controversial results that come from energy analyses are illustrated by examining three environmental problems on the interface between ecology and economics. A process for identifying and using social and ecosystem values to guide environmental assessments is proposed using a conceptual energy systems model that shows how these processes might interact within a region. The probability of realizing a given change in system empower production is suggested as a decision criterion that can be used by managers to evaluate the efficacy of alternatives.

The metabolic regimes of flowing waters

USGS Publications Warehouse

Bernhardt, Emily S.; Heffernan, Jim B.; Grimm, Nancy B.; Stanley, Emily H.; Harvey, Judson; Arroita, M.; Appling, Alison; Cohen, M.J.; McDowell, William H.; Hall, R.O.; Read, Jordan S.; Roberts, B.J.; Stets, Edward; Yackulic, Charles B.

2018-01-01

The processes and biomass that characterize any ecosystem are fundamentally constrained by the total amount of energy that is either fixed within or delivered across its boundaries. Ultimately, ecosystems may be understood and classified by their rates of total and net productivity and by the seasonal patterns of photosynthesis and respiration. Such understanding is well developed for terrestrial and lentic ecosystems but our understanding of ecosystem phenology has lagged well behind for rivers. The proliferation of reliable and inexpensive sensors for monitoring dissolved oxygen and carbon dioxide is underpinning a revolution in our understanding of the ecosystem energetics of rivers. Here, we synthesize our current understanding of the drivers and constraints on river metabolism, and set out a research agenda aimed at characterizing, classifying and modeling the current and future metabolic regimes of flowing waters.

List identifies threatened ecosystems

NASA Astrophysics Data System (ADS)

Showstack, Randy

2012-09-01

The International Union for Conservation of Nature (IUCN) announced on 9 September that it will develop a new Red List of Ecosystems that will identify which ecosystems are vulnerable or endangered. The list, which is modeled on the group's Red List of Threatened Species™, could help to guide conservation activities and influence policy processes such as the Convention on Biological Diversity, according to the group. “We will assess the status of marine, terrestrial, freshwater, and subterranean ecosystems at local, regional, and global levels,” stated Jon Paul Rodriguez, leader of IUCN's Ecosystems Red List Thematic Group. “The assessment can then form the basis for concerted implementation action so that we can manage them sustainably if their risk of collapse is low or restore them if they are threatened and then monitor their recovery.”

Potential Applications of Gosat Based Carbon Budget Products to Refine Terrestrial Ecosystem Model

NASA Astrophysics Data System (ADS)

Kondo, M.; Ichii, K.

2011-12-01

Estimation of carbon exchange in terrestrial ecosystem associates with difficulties due to complex entanglement of physical and biological processes: thus, the net ecosystem productivity (NEP) estimated from simulation often differs among process-based terrestrial ecosystem models. In addition to complexity of the system, validation can only be conducted in a point scale since reliable observation is only available from ground observations. With a lack of large spatial data, extension of model simulation to a global scale results in significant uncertainty in the future carbon balance and climate change. Greenhouse gases Observing SATellite (GOSAT), launched by the Japanese space agency (JAXA) in January, 2009, is the 1st operational satellite promised to deliver the net land-atmosphere carbon budget to the terrestrial biosphere research community. Using that information, the model reproducibility of carbon budget is expected to improve: hence, gives a better estimation of the future climate change. This initial analysis is to seek and evaluate the potential applications of GOSAT observation toward the sophistication of terrestrial ecosystem model. The present study was conducted in two processes: site-based analysis using eddy covariance observation data to assess the potential use of terrestrial carbon fluxes (GPP, RE, and NEP) to refine the model, and extension of the point scale analysis to spatial using Carbon Tracker product as a prototype of GOSAT product. In the first phase of the experiment, it was verified that an optimization routine adapted to a terrestrial model, Biome-BGC, yielded the improved result with respect to eddy covariance observation data from AsiaFlux Network. Spatial data sets used in the second phase were consists of GPP from empirical algorithm (e.g. support vector machine), NEP from Carbon Tracker, and RE from the combination of these. These spatial carbon flux estimations was used to refine the model applying the exactly same optimization procedure as the point analysis, and found that these spatial data help to improve the model's overall reproducibility. The GOSAT product is expected to have higher accuracy since it uses global CO2 observations. Therefore, with the application of GOSAT data, a better estimation of terrestrial carbon cycle can be achieved with optimization. It is anticipated to carry out more detailed analysis upon the arrival of GOSAT product and to verify the reduction in the uncertainty in the future carbon budget and the climate change with the calibrated models, which is the major contribution can be achieved from GOSAT.

Applying and Individual-Based Model to Simultaneously Evaluate Net Ecosystem Production and Tree Diameter Increment

NASA Astrophysics Data System (ADS)

Fang, F. J.

2017-12-01

Reconciling observations at fundamentally different scales is central in understanding the global carbon cycle. This study investigates a model-based melding of forest inventory data, remote-sensing data and micrometeorological-station data ("flux towers" estimating forest heat, CO2 and H2O fluxes). The individual tree-based model FORCCHN was used to evaluate the tree DBH increment and forest carbon fluxes. These are the first simultaneous simulations of the forest carbon budgets from flux towers and individual-tree growth estimates of forest carbon budgets using the continuous forest inventory data — under circumstances in which both predictions can be tested. Along with the global implications of such findings, this also improves the capacity for forest sustainable management and the comprehensive understanding of forest ecosystems. In forest ecology, diameter at breast height (DBH) of a tree significantly determines an individual tree's cross-sectional sapwood area, its biomass and carbon storage. Evaluation the annual DBH increment (ΔDBH) of an individual tree is central to understanding tree growth and forest ecology. Ecosystem Carbon flux is a consequence of key ecosystem processes in the forest-ecosystem carbon cycle, Gross and Net Primary Production (GPP and NPP, respectively) and Net Ecosystem Respiration (NEP). All of these closely relate with tree DBH changes and tree death. Despite advances in evaluating forest carbon fluxes with flux towers and forest inventories for individual tree ΔDBH, few current ecological models can simultaneously quantify and predict the tree ΔDBH and forest carbon flux.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-08-01

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

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

NASA Astrophysics Data System (ADS)

Wang, Shaoqiang

2014-05-01

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

The future of nearshore processes research

USGS Publications Warehouse

Elko, Nicole A.; Feddersen, Falk; Foster, Diane; Hapke, Cheryl J.; McNinch, Jesse E.; Mulligan, Ryan P.; Tuba Ӧzkan-Haller, H.; Plant, Nathaniel G.; Raubenheimer, Britt

2014-01-01

The nearshore is the transition region between land and the continental shelf including (from onshore to offshore) coastal plains, wetlands, estuaries, coastal cliffs, dunes, beaches, surf zones (regions of wave breaking), and the inner shelf (Figure ES-1). Nearshore regions are vital to the national economy, security, commerce, and recreation. The nearshore is dynamically evolving, is often densely populated, and is under increasing threat from sea level rise, long-term erosion, extreme storms, and anthropogenic influences. Worldwide, almost one billion people live at elevations within 10 m of present sea level. Long-term erosion threatens communities, infrastructure, ecosystems, and habitat. Extreme storms can cause billions of dollars of damage. Degraded water quality impacts ecosystem and human health. Nearshore processes, the complex interactions between water, sediment, biota, and humans, must be understood and predicted to manage this often highly developed yet vulnerable nearshore environment. Over the past three decades, the understanding of nearshore processes has improved. However, societal needs are growing with increased coastal urbanization and threats of future climate change, and significant scientific challenges remain. To address these challenges, members of academia, industry, and federal agencies (USGS, USACE, NPS, NOAA, FEMA, ONR) met at the “The Past and Future of Nearshore Processes Research: Reflections on the Sallenger Years and a New Vision for the Future” workshop to develop a nearshore processes research vision where societal needs and science challenges intersect. The resulting vision is comprised of three broad research themes: Long-term coastal evolution due to natural and anthropogenic processes: As global climate change alters the rates of sea level rise and potentially storm patterns and coastal urbanization increases over the coming decades, an understanding of coastal evolution is critical. Improved knowledge of long-term morphological, ecological, and societal processes and their interactions will result in an improved ability to simulate coastal change. This will enable proactive solutions for resilient coasts and better guidance for reducing coastal vulnerability.Extreme Events: Flooding, erosion, and the subsequent recovery: Hurricane Sandy caused flooding and erosion along hundreds of miles of shoreline, flooded New York City, and impacted communities and infrastructure. Overall U.S. coastal extreme event related economic losses have increased substantially. Furthermore, climate change may cause an increase in coastal extreme events and rising sea levels could increase the occurrence of extreme events. Addressing this research theme will result in an improved understanding of the physical processes during extreme events, leading to improved models of flooding, erosion, and recovery. The resulting societal benefit will be more resilient coastal communities.The physical, biological and chemical processes impacting human and ecosystem health: Nearshore regions are used for recreation, tourism, and human habitation, and provide habitat and valuable ecosystem services. These areas must be sustained for future generations, however overall coastal water quality is declining due to microbial pathogens, fertilizers, pesticides, and heavy metal contamination, threatening ecosystem and human health. To ensure sustainable nearshore regions, predictive real-time water- and sediment-based based pollutant modeling capabilities must be developed, which requires expanding our knowledge of the physics, chemistry, and biology of the nearshore. The resulting societal benefits will include better beach safety, healthier ecosystems, and improved mitigation and regulatory policies.The scientists and engineers of the U.S. nearshore community are poised to make significant progress on these research themes, which have significant societal impact. The U.S. nearshore community, including academic, government, and industry colleagues, recommends multi-agency investment into a coordinated development of observational and modeling research infrastructure to address these themes, as discussed in the whitepaper. The observational infrastructure should include development of new sensors and methods, focused observational programs, and expanded nearshore observing systems. The modeling infrastructure should include improved process representation, better model coupling, incorporation of data assimilation techniques, and testing of real-time models. The observations will provide test beds to compare and improve models.

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.

Cross-disciplinarity in the advance of Antarctic ecosystem research.

PubMed

Gutt, J; Isla, E; Bertler, A N; Bodeker, G E; Bracegirdle, T J; Cavanagh, R D; Comiso, J C; Convey, P; Cummings, V; De Conto, R; De Master, D; di Prisco, G; d'Ovidio, F; Griffiths, H J; Khan, A L; López-Martínez, J; Murray, A E; Nielsen, U N; Ott, S; Post, A; Ropert-Coudert, Y; Saucède, T; Scherer, R; Schiaparelli, S; Schloss, I R; Smith, C R; Stefels, J; Stevens, C; Strugnell, J M; Trimborn, S; Verde, C; Verleyen, E; Wall, D H; Wilson, N G; Xavier, J C

2018-02-01

The biodiversity, ecosystem services and climate variability of the Antarctic continent and the Southern Ocean are major components of the whole Earth system. Antarctic ecosystems are driven more strongly by the physical environment than many other marine and terrestrial ecosystems. As a consequence, to understand ecological functioning, cross-disciplinary studies are especially important in Antarctic research. The conceptual study presented here is based on a workshop initiated by the Research Programme Antarctic Thresholds - Ecosystem Resilience and Adaptation of the Scientific Committee on Antarctic Research, which focussed on challenges in identifying and applying cross-disciplinary approaches in the Antarctic. Novel ideas and first steps in their implementation were clustered into eight themes. These ranged from scale problems, through risk maps, and organism/ecosystem responses to multiple environmental changes and evolutionary processes. Scaling models and data across different spatial and temporal scales were identified as an overarching challenge. Approaches to bridge gaps in Antarctic research programmes included multi-disciplinary monitoring, linking biomolecular findings and simulated physical environments, as well as integrative ecological modelling. The results of advanced cross-disciplinary approaches can contribute significantly to our knowledge of Antarctic and global ecosystem functioning, the consequences of climate change, and to global assessments that ultimately benefit humankind. Crown Copyright © 2017. Published by Elsevier B.V. All rights reserved.

Response diversity, nonnative species, and disassembly rules buffer freshwater ecosystem processes from anthropogenic change.

PubMed

Moore, Jonathan W; Olden, Julian D

2017-05-01

Integrating knowledge of environmental degradation, biodiversity change, and ecosystem processes across large spatial scales remains a key challenge to illuminating the resilience of earth's systems. There is now a growing realization that the manner in which communities will respond to anthropogenic impacts will ultimately control the ecosystem consequences. Here, we examine the response of freshwater fishes and their nutrient excretion - a key ecosystem process that can control aquatic productivity - to human land development across the contiguous United States. By linking a continental-scale dataset of 533 fish species from 8100 stream locations with species functional traits, nutrient excretion, and land remote sensing, we present four key findings. First, we provide the first geographic footprint of nutrient excretion by freshwater fishes across the United States and reveal distinct local- and continental-scale heterogeneity in community excretion rates. Second, fish species exhibited substantial response diversity in their sensitivity to land development; for native species, the more tolerant species were also the species contributing greater ecosystem function in terms of nutrient excretion. Third, by modeling increased land-use change and resultant shifts in fish community composition, land development is estimated to decrease fish nutrient excretion in the majority (63%) of ecoregions. Fourth, the loss of nutrient excretion would be 28% greater if biodiversity loss was random or 84% greater if there were no nonnative species. Thus, ecosystem processes are sensitive to increased anthropogenic degradation but biotic communities provide multiple pathways for resistance and this resistance varies across space. © 2016 John Wiley & Sons Ltd.

Ecohydrodynamics of cold-water coral reefs: a case study of the Mingulay Reef Complex (western Scotland).

PubMed

Moreno Navas, Juan; Miller, Peter I; Miller, Peter L; Henry, Lea-Anne; Hennige, Sebastian J; Roberts, J Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications.

Ecohydrodynamics of Cold-Water Coral Reefs: A Case Study of the Mingulay Reef Complex (Western Scotland)

PubMed Central

Navas, Juan Moreno; Miller, Peter L.; Henry, Lea-Anne; Hennige, Sebastian J.; Roberts, J. Murray

2014-01-01

Ecohydrodynamics investigates the hydrodynamic constraints on ecosystems across different temporal and spatial scales. Ecohydrodynamics play a pivotal role in the structure and functioning of marine ecosystems, however the lack of integrated complex flow models for deep-water ecosystems beyond the coastal zone prevents further synthesis in these settings. We present a hydrodynamic model for one of Earth's most biologically diverse deep-water ecosystems, cold-water coral reefs. The Mingulay Reef Complex (western Scotland) is an inshore seascape of cold-water coral reefs formed by the scleractinian coral Lophelia pertusa. We applied single-image edge detection and composite front maps using satellite remote sensing, to detect oceanographic fronts and peaks of chlorophyll a values that likely affect food supply to corals and other suspension-feeding fauna. We also present a high resolution 3D ocean model to incorporate salient aspects of the regional and local oceanography. Model validation using in situ current speed, direction and sea elevation data confirmed the model's realistic representation of spatial and temporal aspects of circulation at the reef complex including a tidally driven current regime, eddies, and downwelling phenomena. This novel combination of 3D hydrodynamic modelling and remote sensing in deep-water ecosystems improves our understanding of the temporal and spatial scales of ecological processes occurring in marine systems. The modelled information has been integrated into a 3D GIS, providing a user interface for visualization and interrogation of results that allows wider ecological application of the model and that can provide valuable input for marine biodiversity and conservation applications. PMID:24873971

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

NASA Astrophysics Data System (ADS)

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

2015-01-01

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

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

DOE PAGES

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

2015-01-27

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

Temporal and Spatial Variation in Peatland Carbon Cycling and Implications for Interpreting Responses of an Ecosystem-Scale Warming Experiment

Treesearch

Natalie A. Griffiths; Paul J. Hanson; Daniel M. Ricciuto; Colleen M. Iversen; Anna M. Jensen; Avni Malhotra; Karis J. McFarlane; Richard J. Norby; Khachik Sargsyan; Stephen D. Sebestyen; Xiaoying Shi; Anthony P. Walker; Eric J. Ward; Jeffrey M. Warren; David J. Weston

2017-01-01

We are conducting a large-scale, long-term climate change response experiment in an ombrotrophic peat bog in Minnesota to evaluate the effects of warming and elevated CO2 on ecosystem processes using empirical and modeling approaches. To better frame future assessments of peatland responses to climate change, we characterized and compared spatial...

Developing Conceptual Models for Assessing Climate Change Impacts to Contaminant Availability in Terrestrial Ecosystems

DTIC Science & Technology

2015-03-01

Stressors Secondary Source/ Stressors Measures of Effect Score Summary Individual Scores Compile Results Land Management (e.g., controlled fire ...Secondary Source/ Stressors Measures of Effect Score Summary Individual Scores Compile Results Land Management (e.g., controlled fire , timber...Greenberg 2005), effects of dredged material (PIANC 2006), and ecosystem restoration (Fischenich 2008) among others. The process of developing a conceptual

. Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability

USGS Publications Warehouse

Gentile, J.H.; Harwell, M.A.; Cropper, W.; Harwell, C. C.; DeAngelis, Donald L.; Davis, S.; Ogden, J.C.; Lirman, D.

2001-01-01

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.

Unraveling the Plant-Soil Interactome

NASA Astrophysics Data System (ADS)

Lipton, M. S.; Hixson, K.; Ahkami, A. H.; HaHandkumbura, P. P.; Hess, N. J.; Fang, Y.; Fortin, D.; Stanfill, B.; Yabusaki, S.; Engbrecht, K. M.; Baker, E.; Renslow, R.; Jansson, C.

2017-12-01

Plant photosynthesis is the primary conduit of carbon fixation from the atmosphere to the terrestrial ecosystem. While more is known about plant physiology and biochemistry, the interplay between genetic and environmental factors that govern partitioning of carbon to above- and below ground plant biomass, to microbes, to the soil, and respired to the atmosphere is not well understood holistically. To address this knowledge gap there is a need to define, study, comprehend, and model the plant ecosystem as an integrated system of integrated biotic and abiotic processes and feedbacks. Local rhizosphere conditions are an important control on plant performance but are in turn affected by plant uptake and rhizodeposition processes. C3 and C4 plants have different CO2 fixation strategies and likely have differential metabolic profiles resulting in different carbon sources exuding to the rhizosphere. In this presentation, we report on an integrated capability to better understand plant-soil interactions, including modeling tools that address the spatiotemporal hydrobiogeochemistry in the rhizosphere. Comparing Brachypodium distachyon, (Brachypodium) as our C3 representative and Setaria viridis (Setaria) as our C4 representative, we designed, highly controlled single-plant experimental ecosystems based these model grasses to enable quantitative prediction of ecosystem traits and responses as a function of plant genotype and environmental variables. A metabolomics survey of 30 Brachypodium genotypes grown under control and drought conditions revealed specific metabolites that correlated with biomass production and drought tolerance. A comparison of Brachypodium and Setaria grown with control and a future predicted elevated CO2 level revealed changes in biomass accumulation and metabolite profiles between the C3 and C4 species in both leaves and roots. Finally, we are building an mechanistic modeling capability that will contribute to a better basis for modeling plant water and nutrient cycling in larger scale models.

Understanding hydrologic budgets, dynamics in an arid basin and explore spatial scaling properties using Process-based Adaptive Watershed Simulator (PAWS)

NASA Astrophysics Data System (ADS)

Fang, K.; Shen, C.; Salve, R.

2013-12-01

The Southern California hot desert hosts a fragile ecosystem as well as a range of human economic activities, primarily mining, energy production and recreation. This inland arid landscape is characterized by occasional intensive precipitation events and year-round strong potential evapotranspiration. In this landscape, water and especially groundwater is vital for ecosystem functions and human use. However, the impact of recent development on the sustainability of groundwater resources in the area has not been thoroughly investigated. We apply an integrated, physically-based hydrologic-land surface model, the Process-based Adaptive Watershed Simulator + Community Land Model (PAWS+CLM) to evaluate the sustainability of the groundwater resources in the area. We elucidate the spatio-temporal patterns of hydrologic fluxes and budgets. The modeling results indicate that mountain front recharge is the essential recharging mechanism for the alluvial aquifer. Although pumping activities do not exceed annual-average recharge values, they are still expected to contribute significantly to groundwater drawdown in business-as-usual scenario. The impact of groundwater withdrawals is significant on the desert ecosystem. The relative importance of groundwater flow on NPP rises significantly as compared to other ecosystems. We further evaluate the fractal scaling properties of soil moisture in this very arid system and found the relationship to be much more static in time than that found in a humid continental climate system. The scaling exponents can be predicted using simple functions of the mean. Therefore, multi-scale model based on coarse-resolution surrogate model is expected to perform well in this system. The modeling result is also important for assessing the groundwater sustainability and impact of human activities in the desert environment.

Ecological conceptual models: a framework and case study on ecosystem management for South Florida sustainability.

PubMed

Gentile, J H; Harwell, M A; Cropper, W; Harwell, C C; DeAngelis, D; Davis, S; Ogden, J C; Lirman, D

2001-07-02

The Everglades and South Florida ecosystems are the focus of national and international attention because of their current degraded and threatened state. Ecological risk assessment, sustainability, and ecosystem and adaptive management principles and processes are being used nationally as a decision and policy framework for a variety of types of ecological assessments. The intent of this study is to demonstrate the application of these paradigms and principles at a regional scale. The effects-directed assessment approach used in this study consists of a retrospective, eco-epidemiological phase to determine the causes for the current conditions and a prospective predictive risk-based assessment using scenario analysis to evaluate future options. Embedded in these assessment phases is a process that begins with the identification of goals and societal preferences which are used to develop an integrated suite of risk-based and policy relevant conceptual models. Conceptual models are used to illustrate the linkages among management (societal) actions, environmental stressors, and societal/ecological effects, and provide the basis for developing and testing causal hypotheses. These models, developed for a variety of landscape units and their drivers, stressors, and endpoints, are used to formulate hypotheses to explain the current conditions. They are also used as the basis for structuring management scenarios and analyses to project the temporal and spatial magnitude of risk reduction and system recovery. Within the context of recovery, the conceptual models are used in the initial development of performance criteria for those stressors that are determined to be most important in shaping the landscape, and to guide the use of numerical models used to develop quantitative performance criteria in the scenario analysis. The results will be discussed within an ecosystem and adaptive management framework that provides the foundation for decision making.

Plankton ecosystem functioning and nitrogen fluxes in the most oligotrophic waters of the Beaufort Sea, Arctic Ocean: a modeling study

NASA Astrophysics Data System (ADS)

Le Fouest, V.; Zakardjian, B.; Xie, H.; Raimbault, P.; Joux, F.; Babin, M.

2012-10-01

The Arctic Ocean (AO) undergoes profound changes of its physical and biotic environments due to climate change. The greater light exposure and stratification alter its plankton ecosystem structure, functioning and productivity promoting oligotrophy in some areas as the Beaufort Sea. A one-dimension (1-D) physical-biological coupled model based on the large multiparametric database of the Malina project in the Beaufort Sea was used (i) to infer the functioning and nitrogen fluxes within the summer plankton ecosystem and (ii) to assess the model sensitivity to key light-associated processes involved in nutrient recycling and phytoplankton growth. The coupled model suggested that ammonium photochemically produced from photosensitive dissolved organic nitrogen (i.e. photoammonification process) was a necessary nitrogen source to achieve the observed levels of microbial biomass and production. It contributed to ca. two-thirds and one-third of the simulated surface (0-10 m) and depth-integrated primary and bacterial production, respectively. The model also suggested that carbon to chlorophyll ratios for small (< 5 μm) phytoplankton (ca. 15-45 g g-1) lower than those commonly used in biogeochemical models applied to the AO were required to simulate the observed herbivorous versus microbial food web competition and realistic nitrogen fluxes in the Beaufort Sea oligotrophic waters. In face of accelerating Arctic warming, more attention should be paid in the future to the mechanistic processes involved in food webs and functional groups competition, nutrient recycling and primary production in poorly productive waters of the AO as they are expected to expand rapidly.

Multi-Hypothesis Modelling Capabilities for Robust Data-Model Integration

NASA Astrophysics Data System (ADS)

Walker, A. P.; De Kauwe, M. G.; Lu, D.; Medlyn, B.; Norby, R. J.; Ricciuto, D. M.; Rogers, A.; Serbin, S.; Weston, D. J.; Ye, M.; Zaehle, S.

2017-12-01

Large uncertainty is often inherent in model predictions due to imperfect knowledge of how to describe the mechanistic processes (hypotheses) that a model is intended to represent. Yet this model hypothesis uncertainty (MHU) is often overlooked or informally evaluated, as methods to quantify and evaluate MHU are limited. MHU is increased as models become more complex because each additional processes added to a model comes with inherent MHU as well as parametric unceratinty. With the current trend of adding more processes to Earth System Models (ESMs), we are adding uncertainty, which can be quantified for parameters but not MHU. Model inter-comparison projects do allow for some consideration of hypothesis uncertainty but in an ad hoc and non-independent fashion. This has stymied efforts to evaluate ecosystem models against data and intepret the results mechanistically because it is not simple to interpret exactly why a model is producing the results it does and identify which model assumptions are key as they combine models of many sub-systems and processes, each of which may be conceptualised and represented mathematically in various ways. We present a novel modelling framework—the multi-assumption architecture and testbed (MAAT)—that automates the combination, generation, and execution of a model ensemble built with different representations of process. We will present the argument that multi-hypothesis modelling needs to be considered in conjunction with other capabilities (e.g. the Predictive Ecosystem Analyser; PecAn) and statistical methods (e.g. sensitivity anaylsis, data assimilation) to aid efforts in robust data model integration to enhance our predictive understanding of biological systems.

The PEcAn Project: Model-Data Ecoinformatics for the Observatory Era

NASA Astrophysics Data System (ADS)

Dietze, M. C.; LeBauer, D. S.; Davidson, C. D.; Desai, A. R.; Kooper, R.; McHenry, K.; Mulrooney, P.

2011-12-01

The fundamental questions about how terrestrial ecosystems will respond to climate change are straightforward and well known, yet a small number of important gaps separate the information we have gathered from the understanding required to inform policy and management. A critical gap is that no one data source provides a complete picture of the terrestrial biosphere, and therefore multiple data sources must be integrated in a sensible manner. Process-based models represent an ideal framework for this synthesis, but to date model-data synthesize has only made use of a subset of the available data types, and remains inaccessible to much of the scientific community, largely due to the daunting ecoinformatics challenges. The Predictive Ecosystem Analyzer (PEcAn) is an open-source scientific workflow system and ecoinformatics toolbox that manages the flow of information in and out of regional-scale terrestrial biosphere models, facilitates formal data assimilation, and enables more effective feedbacks between models and field research. PEcAn makes complex analyses transparent, repeatable, and accessible to a diverse array of researchers. PEcAn is not model specific, but rather encapsulates any ecosystem model within a set of standardized input and output modules. Herein we demonstrate PEcAn's ability to automate many of the tasks involved in modeling by gathering and processing a diverse arrays of data sets, initiating ensembles of model runs, visualizing output, and comparing models to observations. PEcAn employs a fully Bayesian approach to model parameterization and the estimation of ecosystem pools and fluxes that allows a straightforward propagation of uncertainties into analyses and forecasts. This approach also makes possible the synthesis of a diverse array of data types operating at different spatial and temporal scales and to easily update predictions as new information becomes available. We also demonstrate PEcAn's ability to iteratively synthesize information for literature trait databases, ground observations, eddy-covariance towers and quantify the reductions in overall uncertainty as each new dataset is added. PEcAn also automates a number of model analyses, such as sensitivity analyses, ensemble prediction, and variance decomposition which collectively allow the system to partition and ascribe uncertainties to different model parameters and processes. PEcAn provides a direct feedback to field research by further automating the estimation of sample sizes and sampling distributions required to reduce model uncertainties, enabling further measurements to be targeted and optimized. Finally, we will present the PEcAn development plan and timeline, including new features such as the synthesis of remotely sensed data, regional-scale data assimilation, and real-time forecasting. Ultimately, PEcAn aims to make ecosystem modeling and data assimilation routine tools for answering scientific questions and informing policy and management.

Influence of Gap-Filling to Generate Continuous Datasets on Process Network Analysis

NASA Astrophysics Data System (ADS)

Yun, J.; Kim, J.; Kim, S.; Chun, J.

2013-12-01

The interplay of environmental conditions, energy, matter, and information defines the context and constraints for the set of processes and structures that may emerge during self-organization in complex ecosystems. Following Ruddell and Kumar (2009), we have evaluated statistical measures of characterizing the organization of the information flow in ecohydrological process networks in a deciduous forest ecosystem. We used the time series data obtained in 2008 (normal year) from the KoFlux forest tower site in central Korea. The 30-minute averages of eddy fluxes of energy, water and CO2 were measured at 40m above an oak-dominated old deciduous forest along with other micrometeorological variables. In this analysis, we selected 13 variables: atmospheric pressure (Pa), net ecosystem CO2 exchange (NEE), gross primary productivity (GPP), ecosystem respiration (RE), latent heat flux (LE), precipitation (Precip), solar radiation (Rg), air temperature (T), vapor pressure deficit (VPD), sensible heat flux (H), canopy temperature (Tc), wind direction (WD), and wind speed (WS). Our results support that a process network approach can be used to formally resolve feedback, time scales, and subsystems that define the complex ecosystem's organization by considering mutual information and transfer entropy simultaneously. We also observed that the turbulent and atmospheric boundary layer subsystems are coupled through feedback loops, and form a regional self-organizing subsystem in August when the forest is in healthy environment. In particular, we noted that the observed feedback loops in the process network disappeared when the time series data were artificially gap-filled for missing data, which is a common practice in post-data processing. In this presentation, we report the influence of gap-filling on the process network analysis by artificially assigning different sizes and periods of missing data and discuss the implication of our results on validation and calibration of ecosystem models. Acknowledgment. This research was supported by the Korea Meteorological Administration Research and Development Program under Grant CATER 2013-3030.

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

NASA Astrophysics Data System (ADS)

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

2011-09-01

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

A simple estimate of ecosystem respiration across biomes based on MODIS products

NASA Astrophysics Data System (ADS)

Jaegermeyr, J.; Hostert, P.; Lucht, W.

2010-12-01

Beside carbon sequestration by terrestrial photosynthesis, in particular the subsequent carbon release by ecosystem respiration (Reco) is a crucial flux for estimating carbon budgets. Heterotrophic soil decomposition rates (Rh) and autotrophic respiration rates (Ra), which add up to Reco, are highly sensitive to environmental conditions and in some cases they determine net ecosystem productivity. Prior respiration modeling approaches revealed that a precise process-based and bottom-up modeling is important for realistic estimates. On a short timescale, as in the case of satellite environmental monitoring, simplified empirical models are not necessarily less accurate, though. For most major biomes, ecosystem carbon efflux is predominantly driven by air temperature. It can further be limited by water stress, plant activity and substrate quality. Developing simple, empirical and wall-to-wall respiration models from continuous Moderate Resolution Imaging Spectroradiometer (MODIS) land products on a continental scale can enhance our understanding of spatially explicit respiration patterns. We therefore accept model uncertainties by simplifying decay and respiratory processes in that we account for a single static carbon pool and do not include any feedback mechanisms. Preliminary results suggest that the 8-day MODIS 1km land surface temperature product (LST) and the vegetation-water index (NDWI) derived from the 8-day MODIS 500m surface reflectance product are sufficient to largely explain the variability of Reco. Spatial flux variations can be attributed to plant activity variation. We therefore introduce a site-specific, maximum leaf area index (LAI) from the MODIS 1km LAI product as a proxy. A biome-specific model parameterization and validation is performed, based on 8-day composite FLUXNET tower data representing major global biomes. We found that the frequently used temperature model by Loyd and Taylor (1994) does not show superior performance on 8-day ecosystem respiration data. The model by Del Grosso et al. (2005) is more flexible to account for lower Q10 values at high temperatures and thus it is used to describe the temperature dependency here. Although we cannot explain flux variations arising from overall carbon pool variations, results suggest that our approach may contribute to simplified Reco estimates.

Sensitivity of secondary production and export flux to choice of trophic transfer formulation in marine ecosystem models

NASA Astrophysics Data System (ADS)

Anderson, Thomas R.; Hessen, Dag O.; Mitra, Aditee; Mayor, Daniel J.; Yool, Andrew

2013-09-01

The performance of four contemporary formulations describing trophic transfer, which have strongly contrasting assumptions as regards the way that consumer growth is calculated as a function of food C:N ratio and in the fate of non-limiting substrates, was compared in two settings: a simple steady-state ecosystem model and a 3D biogeochemical general circulation model. Considerable variation was seen in predictions for primary production, transfer to higher trophic levels and export to the ocean interior. The physiological basis of the various assumptions underpinning the chosen formulations is open to question. Assumptions include Liebig-style limitation of growth, strict homeostasis in zooplankton biomass, and whether excess C and N are released by voiding in faecal pellets or via respiration/excretion post-absorption by the gut. Deciding upon the most appropriate means of formulating trophic transfer is not straightforward because, despite advances in ecological stoichiometry, the physiological mechanisms underlying these phenomena remain incompletely understood. Nevertheless, worrying inconsistencies are evident in the way in which fundamental transfer processes are justified and parameterised in the current generation of marine ecosystem models, manifested in the resulting simulations of ocean biogeochemistry. Our work highlights the need for modellers to revisit and appraise the equations and parameter values used to describe trophic transfer in marine ecosystem models.

Implementation of marine spatial planning in shellfish aquaculture management: modeling studies in a Norwegian fjord.

PubMed

Filgueira, Ramon; Grant, Jon; Strand, Øivind

2014-06-01

Shellfish carrying capacity is determined by the interaction of a cultured species with its ecosystem, which is strongly influenced by hydrodynamics. Water circulation controls the exchange of matter between farms and the adjacent areas, which in turn establishes the nutrient supply that supports phytoplankton populations. The complexity of water circulation makes necessary the use of hydrodynamic models with detailed spatial resolution in carrying capacity estimations. This detailed spatial resolution also allows for the study of processes that depend on specific spatial arrangements, e.g., the most suitable location to place farms, which is crucial for marine spatial planning, and consequently for decision support systems. In the present study, a fully spatial physical-biogeochemical model has been combined with scenario building and optimization techniques as a proof of concept of the use of ecosystem modeling as an objective tool to inform marine spatial planning. The object of this exercise was to generate objective knowledge based on an ecosystem approach to establish new mussel aquaculture areas in a Norwegian fjord. Scenario building was used to determine the best location of a pump that can be used to bring nutrient-rich deep waters to the euphotic layer, increasing primary production, and consequently, carrying capacity for mussel cultivation. In addition, an optimization tool, parameter estimation (PEST), was applied to the optimal location and mussel standing stock biomass that maximize production, according to a preestablished carrying capacity criterion. Optimization tools allow us to make rational and transparent decisions to solve a well-defined question, decisions that are essential for policy makers. The outcomes of combining ecosystem models with scenario building and optimization facilitate planning based on an ecosystem approach, highlighting the capabilities of ecosystem modeling as a tool for marine spatial planning.

Future directions of ecosystem science

USGS Publications Warehouse

Baron, Jill S.; Galvin, Kathleen A.

1990-01-01

Scientific knowledge about ecosystem structure and function has expanded greatly during the past few decades. Terrestrial and aquatic nutrient cycling, ecosystem energetics, population dynamics, belowground processes, and food webs have been studied at the plot, stand, watershed, and landscape levels at many locations around the globe. Ideas about terrestrial-atmospheric interactions and human interference in these processes have changed dramatically. There is new appreciation of the need to incorporate into ecosystem studies the interactions between human populations and the ecosystem, not only because humans affect ecosystem processes, but because these systems support human populations (Glantz 1988, Holden 1988, Parry et al. 1988, WCED 1987). Recent advances in ecosystem science are due, in part, to technological improvements in computing power, new laboratory and field physical and chemical analytical techniques, and satellite imagery for remote sensing of Earth's structure and dynamics. Modeling and geographic information systems have provided the capability for integrating multiple data sets with process simulations to generate hypotheses about regional ecosystem function. Concurrent with these scientific developments has been a growing concern about the links between the health of the environment and world-wide industrial, land, and resource-management practices. Environmental damage at the local level was widely recognized in the 1960s, prompting the environmental movement of that decade. Regional environmental problems with multiple effects and politically difficult solutions have been perceived more recently; the issue of acidic deposition provides an example of such a second-generation concern (Clark and Holling 1985). Today there is a growing awareness of global-scale environmental degradation brought about by the combined actions of all peoples on Earth (Clark 1989, Woodmansee et al. 1988). The three levels of environmental concern--local, regional, and global--have not replaced one another (Clark and Holling 1985). Instead, the effects are superimposed, creating what some perceive as impending global environmental crisis (Clark 1989, MacNeill 1989, WCED 1987). Public demands are developing for economic, political, social, and environmental efforts directed toward creating a state of global sustainability.

Process-Based Modeling of Upland Erosion and Salt Load in the Upper Colorado River Basin

USDA-ARS?s Scientific Manuscript database

Hillslope runoff and soil erosion processes are indicators of sustainability in rangeland ecosystem due to their control on resource mobility. Hillslope processes are dominant contributors to sediment delivery on semi-arid rangeland watersheds. The influence of vegetation on hillslope runoff and sed...

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

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius; Winthrop, Rob; Jaworksi, Delilah; Larson, Joel

2012-01-01

This report details the findings of the Bureau of Land Management–U.S. Geological Survey Ecosystem Services Valuation Pilot Study. This project evaluated alternative methods and tools that quantify and value ecosystem services, and it assessed the tools’ readiness for use in the Bureau of Land Management decisionmaking process. We tested these tools on the San Pedro River watershed in northern Sonora, Mexico, and southeast Arizona. The study area includes the San Pedro Riparian National Conservation Area (managed by the Bureau of Land Management), which has been a focal point for conservation activities and scientific research in recent decades. We applied past site-specific primary valuation studies, value transfer, the Wildlife Habitat Benefits Estimation Toolkit, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Artificial Intelligence for Ecosystem Services (ARIES) models to value locally important ecosystem services for the San Pedro River watershed—water, carbon, biodiversity, and cultural values. We tested these approaches on a series of scenarios to evaluate ecosystem service changes and the ability of the tools to accommodate scenarios. A suite of additional tools were either at too early a stage of development to run, were proprietary, or were place-specific tools inappropriate for application to the San Pedro River watershed. We described the strengths and weaknesses of these additional ecosystem service tools against a series of evaluative criteria related to their usefulness for Bureau of Land Management decisionmaking. Using these tools, we quantified gains or losses of ecosystem services under three categories of scenarios: urban growth, mesquite management, and water augmentation. These results quantify tradeoffs and could be useful for decisionmaking within Bureau of Land Management district or field offices. Results are accompanied by a relatively high level of uncertainty associated with model outputs, valuation methods, and discount rates applied. Further guidance on representing uncertainty and applying uncertain results in decisionmaking would benefit both tool developers and those offices in using ecosystem services to compare management tradeoffs. Decisionmakers and Bureau of Land Management managers at the State-, district-, and field-office level would also benefit from continuing model improvements, training, and guidance on tool use that can be provided by the U.S. Geological Survey, the Bureau of Land Management, and the Department of the Interior. Tradeoffs were identified in the level of effort needed to parameterize and run tools and the amount and quality of information they provide to the decision process. We found the Wildlife Habitat Benefits Estimation Toolkit, Ecosystem Services Review, and United Nations Environment Programme–World Conservation Monitoring Centre Ecosystem Services Toolkit to be immediately feasible for application by the Bureau of Land Management, given proper guidance on their use. It is also feasible for the Bureau of Land Management to use the InVEST model, but in early 2012 the process of parameterizing the model required resources and expertise that are unlikely to be available in most Bureau of Land Management district or field offices. Application of past primary valuation is feasible, but developing new primary-valuation studies is too time consuming for regular application. Value transfer approaches (aside from the Wildlife Habitat Benefits Estimation Toolkit) are best applied carefully on the basis of guidelines described in this report, to reduce transfer error. The ARIES model can provide useful information in regions modeled in the past (Arizona, California, Colorado, and Washington), but it lacks some features that will improve its usability, such as a generalized model that could be applied anywhere in the United States. Eleven other tools described in this report could become useful as the tools more fully develop, in high-profile cases for which additional resources are available for tool application or in case-study regions where place-specific models have already been developed. To improve the value of these tools in decisionmaking, we suggest scientific needs that agencies such as U.S. Geological Survey can help meet—for instance, development and support of data archives. Such archives could greatly reduce resource needs and improve the reliability and consistency of results. Given the rapid state of evolution in the field, periodic follow-up studies on ecosystem services tools would help to ensure that the Bureau of Land Management and other public land management agencies are kept up to date on new tools and features that bring ecosystem services closer to readiness for use in regular decisionmaking.

MARINE AEROSOLS ALTER SOIL PROCESSES IN COASTAL FORESTS

EPA Science Inventory

Most models of watershed biogeochemistry include the movement of materials from land to rivers and eventually the ocean. Few conceptual views, however, acknowledge the influence of materials derived from the ocean on terrestrial ecosystems processes. Based on spatial patterns o...

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.

The importance of benthic-pelagic coupling for marine ecosystem functioning in a changing world.

PubMed

Griffiths, Jennifer R; Kadin, Martina; Nascimento, Francisco J A; Tamelander, Tobias; Törnroos, Anna; Bonaglia, Stefano; Bonsdorff, Erik; Brüchert, Volker; Gårdmark, Anna; Järnström, Marie; Kotta, Jonne; Lindegren, Martin; Nordström, Marie C; Norkko, Alf; Olsson, Jens; Weigel, Benjamin; Žydelis, Ramunas; Blenckner, Thorsten; Niiranen, Susa; Winder, Monika

2017-06-01

Benthic-pelagic coupling is manifested as the exchange of energy, mass, or nutrients between benthic and pelagic habitats. It plays a prominent role in aquatic ecosystems, and it is crucial to functions from nutrient cycling to energy transfer in food webs. Coastal and estuarine ecosystem structure and function are strongly affected by anthropogenic pressures; however, there are large gaps in our understanding of the responses of inorganic nutrient and organic matter fluxes between benthic habitats and the water column. We illustrate the varied nature of physical and biological benthic-pelagic coupling processes and their potential sensitivity to three anthropogenic pressures - climate change, nutrient loading, and fishing - using the Baltic Sea as a case study and summarize current knowledge on the exchange of inorganic nutrients and organic material between habitats. Traditionally measured benthic-pelagic coupling processes (e.g., nutrient exchange and sedimentation of organic material) are to some extent quantifiable, but the magnitude and variability of biological processes are rarely assessed, preventing quantitative comparisons. Changing oxygen conditions will continue to have widespread effects on the processes that govern inorganic and organic matter exchange among habitats while climate change and nutrient load reductions may have large effects on organic matter sedimentation. Many biological processes (predation, bioturbation) are expected to be sensitive to anthropogenic drivers, but the outcomes for ecosystem function are largely unknown. We emphasize how improved empirical and experimental understanding of benthic-pelagic coupling processes and their variability are necessary to inform models that can quantify the feedbacks among processes and ecosystem responses to a changing world. © 2017 The Authors. Global Change Biology Published by John Wiley & Sons Ltd.

Meta-Modeling: A Knowledge-Based Approach to Facilitating Model Construction and Reuse

NASA Technical Reports Server (NTRS)

Keller, Richard M.; Dungan, Jennifer L.

1997-01-01

In this paper, we introduce a new modeling approach called meta-modeling and illustrate its practical applicability to the construction of physically-based ecosystem process models. As a critical adjunct to modeling codes meta-modeling requires explicit specification of certain background information related to the construction and conceptual underpinnings of a model. This information formalizes the heretofore tacit relationship between the mathematical modeling code and the underlying real-world phenomena being investigated, and gives insight into the process by which the model was constructed. We show how the explicit availability of such information can make models more understandable and reusable and less subject to misinterpretation. In particular, background information enables potential users to better interpret an implemented ecosystem model without direct assistance from the model author. Additionally, we show how the discipline involved in specifying background information leads to improved management of model complexity and fewer implementation errors. We illustrate the meta-modeling approach in the context of the Scientists' Intelligent Graphical Modeling Assistant (SIGMA) a new model construction environment. As the user constructs a model using SIGMA the system adds appropriate background information that ties the executable model to the underlying physical phenomena under investigation. Not only does this information improve the understandability of the final model it also serves to reduce the overall time and programming expertise necessary to initially build and subsequently modify models. Furthermore, SIGMA's use of background knowledge helps eliminate coding errors resulting from scientific and dimensional inconsistencies that are otherwise difficult to avoid when building complex models. As a. demonstration of SIGMA's utility, the system was used to reimplement and extend a well-known forest ecosystem dynamics model: Forest-BGC.

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

Modelling the growth of Populus species using Ecosystem Demography (ED) model

NASA Astrophysics Data System (ADS)

Wang, D.; Lebauer, D. S.; Feng, X.; Dietze, M. C.

2010-12-01

Hybrid poplar plantations are an important source being evaluated for biomass production. Effective management of such plantations requires adequate growth and yield models. The Ecosystem Demography model (ED) makes predictions about the large scales of interest in above- and belowground ecosystem structure and the fluxes of carbon and water from a description of the fine-scale physiological processes. In this study, we used a workflow management tool, the Predictive Ecophysiological Carbon flux Analyzer (PECAn), to integrate literature data, field measurement and the ED model to provide predictions of ecosystem functioning. Parameters for the ED ensemble runs were sampled from the posterior distribution of ecophysiological traits of Populus species compiled from the literature using a Bayesian meta-analysis approach. Sensitivity analysis was performed to identify the parameters which contribute the most to the uncertainties of the ED model output. Model emulation techniques were used to update parameter posterior distributions using field-observed data in northern Wisconsin hybrid poplar plantations. Model results were evaluated with 5-year field-observed data in a hybrid poplar plantation at New Franklin, MO. ED was then used to predict the spatial variability of poplar yield in the coterminous United States (United States minus Alaska and Hawaii). Sensitivity analysis showed that root respiration, dark respiration, growth respiration, stomatal slope and specific leaf area contribute the most to the uncertainty, which suggests that our field measurements and data collection should focus on these parameters. The ED model successfully captured the inter-annual and spatial variability of the yield of poplar. Analyses in progress with the ED model focus on evaluating the ecosystem services of short-rotation woody plantations, such as impacts on soil carbon storage, water use, and nutrient retention.

Ant-mediated ecosystem processes are driven by trophic community structure but mainly by the environment.

PubMed

Salas-Lopez, Alex; Mickal, Houadria; Menzel, Florian; Orivel, Jérôme

2017-01-01

The diversity and functional identity of organisms are known to be relevant to the maintenance of ecosystem processes but can be variable in different environments. Particularly, it is uncertain whether ecosystem processes are driven by complementary effects or by dominant groups of species. We investigated how community structure (i.e., the diversity and relative abundance of biological entities) explains the community-level contribution of Neotropical ant communities to different ecosystem processes in different environments. Ants were attracted with food resources representing six ant-mediated ecosystem processes in four environments: ground and vegetation strata in cropland and forest habitats. The exploitation frequencies of the baits were used to calculate the taxonomic and trophic structures of ant communities and their contribution to ecosystem processes considered individually or in combination (i.e., multifunctionality). We then investigated whether community structure variables could predict ecosystem processes and whether such relationships were affected by the environment. We found that forests presented a greater biodiversity and trophic complementarity and lower dominance than croplands, but this did not affect ecosystem processes. In contrast, trophic complementarity was greater on the ground than on vegetation and was followed by greater resource exploitation levels. Although ant participation in ecosystem processes can be predicted by means of trophic-based indices, we found that variations in community structure and performance in ecosystem processes were best explained by environment. We conclude that determining the extent to which the dominance and complementarity of communities affect ecosystem processes in different environments requires a better understanding of resource availability to different species.

Development of an Unmanned Aerial System (UAS) for Scaling Terrestrial Ecosystem Traits

NASA Astrophysics Data System (ADS)

Meng, R.; McMahon, A. M.; Serbin, S.; Rogers, A.

2015-12-01

The next generation of Ecosystem and Earth System Models (EESMs) will require detailed information on ecosystem structure and function, including properties of vegetation related to carbon (C), water, and energy cycling, in order to project the future state of ecosystems. High spatial-temporal resolution measurements of terrestrial ecosystem are also important for EESMs, because they can provide critical inputs and benchmark datasets for evaluation of EESMs simulations across scales. The recent development of high-quality, low-altitude remote sensing platforms or small UAS (< 25 kg) enables measurements of terrestrial ecosystems at unprecedented temporal and spatial scales. Specifically, these new platforms can provide detailed information on patterns and processes of terrestrial ecosystems at a critical intermediate scale between point measurements and suborbital and satellite platforms. Given their potential for sub-decimeter spatial resolution, improved mission safety, high revisit frequency, and reduced operation cost, these platforms are of particular interest in the development of ecological scaling algorithms to parameterize and benchmark EESMs, particularly over complex and remote terrain. Our group is developing a small UAS platform and integrated sensor package focused on measurement needs for scaling and informing ecosystem modeling activities, as well as scaling and mapping plant functional traits. To do this we are developing an integrated software workflow and hardware package using off-the-shelf instrumentation including a high-resolution digital camera for Structure from Motion, spectroradiometer, and a thermal infrared camera. Our workflow includes platform design, measurement, image processing, data management, and information extraction. The fusion of 3D structure information, thermal-infrared imagery, and spectroscopic measurements, will provide a foundation for the development of ecological scaling and mapping algorithms. Our initial focus is in temperate forests but near-term research will expand into the high-arctic and eventually tropical systems. The results of this prototype study show that off-the-shelf technology can be used to develop a low-cost alternative for mapping plant traits and three-dimensional structure for ecological research.

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

USGS Publications Warehouse

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

2015-01-01

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

The global susceptibility of coastal forage fish to competition by large jellyfish

PubMed Central

Mariani, Patrizio

2016-01-01

Competition between large jellyfish and forage fish for zooplankton prey is both a possible cause of jellyfish increases and a concern for the management of marine ecosystems and fisheries. Identifying principal factors affecting this competition is therefore important for marine management, but the lack of both good quality data and a robust theoretical framework have prevented general global analyses. Here, we present a general mechanistic food web model that considers fundamental differences in feeding modes and predation pressure between fish and jellyfish. The model predicts forage fish dominance at low primary production, and a shift towards jellyfish with increasing productivity, turbidity and fishing. We present an index of global ecosystem susceptibility to shifts in fish–jellyfish dominance that compares well with data on jellyfish distributions and trends. The results are a step towards better understanding the processes that govern jellyfish occurrences globally and highlight the advantage of considering feeding traits in ecosystem models. PMID:28120793

Filling the gaps: Predicting the distribution of temperate reef biota using high resolution biological and acoustic data

NASA Astrophysics Data System (ADS)

Hill, Nicole A.; Lucieer, Vanessa; Barrett, Neville S.; Anderson, Tara J.; Williams, Stefan B.

2014-06-01

Management of the marine environment is often hampered by a lack of comprehensive spatial information on the distribution of diversity and the bio-physical processes structuring regional ecosystems. This is particularly true in temperate reef systems beyond depths easily accessible to divers. Yet these systems harbor a diversity of sessile life that provide essential ecosystem services, sustain fisheries and, as with shallower ecosystems, are also increasingly vulnerable to anthropogenic impacts and environmental change. Here we use cutting-edge tools (Autonomous Underwater Vehicles and ship-borne acoustics) and analytical approaches (predictive modelling) to quantify and map these highly productive ecosystems. We find the occurrence of key temperate-reef biota can be explained and predicted using standard (depth) and novel (texture) surrogates derived from multibeam acoustic data, and geographic surrogates. This suggests that combinations of fine-scale processes, such as light limitation and habitat complexity, and broad-scale processes, such as regional currents and exposure regimes, are important in structuring these diverse deep-reef communities. While some dominant habitat forming biota, including canopy algae, were widely distributed, others, including gorgonians and sea whips, exhibited patchy and restricted distributions across the reef system. In addition to providing the first quantitative and full coverage maps of reef diversity for this area, our modelling revealed that offshore reefs represented a regional diversity hotspot that is of high ecological and conservation value. Regional reef systems should not, therefore, be considered homogenous units in conservation planning and management. Full-coverage maps of the predicted distribution of biota (and associated uncertainty) are likely to be increasingly valuable, not only for conservation planning, but in the ongoing management and monitoring of these less-accessible ecosystems.

Preface [to special section on recent Loch Vale Watershed research

USGS Publications Warehouse

Baron, Jill S.; Williams, Mark W.

2000-01-01

Catchment-scale intensive and extensive research conducted over the last decade shows that our understanding of the biogeochemical and hydrologic processes in subalpine and alpine basins is not yet sufficiently mature to model and predict how biogeochemical transformations and surface water quality will change in response to climatic or human-driven changes in energy, water, and chemicals. A better understanding of these processes is needed for input to decision-making regulatory agencies and federal land managers. In recognition of this problem the National Research Council [1998] has identified as a critical research need an improved understanding of how global change will affect biogeochemical interactions with the hydrologic cycle and biogeochemical controls over the transport of water, nutrients, and materials from land to freshwater ecosystems. Improved knowledge of alpine and subalpine ecosystems is particularly important since high-elevation catchments are very sensitive to small changes in the flux of energy, chemicals, and water. Furthermore, alpine ecosystems may act as early warning indicators for ecosystem changes at lower elevations.

Fishing down nutrients on coral reefs.

PubMed

Allgeier, Jacob E; Valdivia, Abel; Cox, Courtney; Layman, Craig A

2016-08-16

Fishing is widely considered a leading cause of biodiversity loss in marine environments, but the potential effect on ecosystem processes, such as nutrient fluxes, is less explored. Here, we test how fishing on Caribbean coral reefs influences biodiversity and ecosystem functions provided by the fish community, that is, fish-mediated nutrient capacity. Specifically, we modelled five processes of nutrient storage (in biomass) and supply (via excretion) of nutrients, as well as a measure of their multifunctionality, onto 143 species of coral reef fishes across 110 coral reef fish communities. These communities span a gradient from extreme fishing pressure to protected areas with little to no fishing. We find that in fished sites fish-mediated nutrient capacity is reduced almost 50%, despite no substantial changes in the number of species. Instead, changes in community size and trophic structure were the primary cause of shifts in ecosystem function. These findings suggest that a broader perspective that incorporates predictable impacts of fishing pressure on ecosystem function is imperative for effective coral reef conservation and management.

Using CarbonTracker carbon flux estimates to improve a terrestrial carbon cycle model

NASA Astrophysics Data System (ADS)

Peters, W.; Krol, M.; Miller, J. B.; Tans, P. P.; Carvalhais, N.; Schaefer, K.

2009-12-01

Estimates of net ecosystem exchange (NEE) from NOAA’s CarbonTracker CO2 data assimilation system show patterns of annual net uptake not represented in most terrestrial carbon cycle models. This is mainly because such models lack information on the land-use history of individual ecosystems, which is the main driver of long-term mean carbon exchange. Instead, they assume the biosphere to be in steady-state, with annual gross photosynthesis equalling ecosystem respiration everywhere. This limits their use in interpreting observations of carbon dynamics such as with eddy-covariance techniques or through atmospheric CO2 records. We have implemented a method that takes the long-term mean NEE estimates from CarbonTracker to derive the size of the dominant carbon pool in each ecosystem of the SIBCASA biosphere model. With the new pool sizes, the SIBCASA model is no longer in steady-state and reproduces annual carbon uptake patterns from CarbonTracker. We will show that the non steady-state SIBCASA model is not only much more consistent with the atmospheric CO2 record, but also with independent data on standing wood biomass and forest age from the Forest Inventory and Analysis (FIA) Program of the U.S. Forest Service. Four years of CarbonTracker NEE are needed to reliably derive a long term mean for this process, and we use three other years from CarbonTracker to evaluate the non steady state SIBCASA NEE. We will furthermore show that the non steady-state SIBCASA NEE is a much better first-guess for the CarbonTracker data assimilation process, allowing more confidence in its final NEE estimate, and reducing a systematic bias in CarbonTracker modeled atmospheric CO2. This overcomes a long standing issue in inverse modeling, and opens the way for further assessment and improvement of carbon cycle models such as SIBCASA.

Puget Sound Applications of the VELMA Ecohydrological Model

EPA Science Inventory

This seminar will present an overview of EPA’s Visualizing Ecosystem Land Management Assessments (VELMA) model and its applications in the Puget Sound Basin. Topics will include a description of how VELMA simulates the interaction of hydrological and biogeochemical processe...

Can biomass responses to warming at plant to ecosystem levels be predicted by leaf-level responses?

NASA Astrophysics Data System (ADS)

Xia, J.; Shao, J.; Zhou, X.; Yan, W.; Lu, M.

2015-12-01

Global warming has the profound impacts on terrestrial C processes from leaf to ecosystem scales, potentially feeding back to climate dynamics. Although numerous studies had investigated the effects of warming on C processes from leaf to plant and ecosystem levels, how leaf-level responses to warming scale up to biomass responses at plant, population, and community levels are largely unknown. In this study, we compiled a dataset from 468 papers at 300 experimental sites and synthesized the warming effects on leaf-level parameters, and plant, population and ecosystem biomass. Our results showed that responses of plant biomass to warming mainly resulted from the changed leaf area rather than the altered photosynthetic capacity. The response of ecosystem biomass to warming was weaker than those of leaf area and plant biomass. However, the scaling functions from responses of leaf area to plant biomass to warming were different in diverse forest types, but functions were similar in non-forested biomes. In addition, it is challenging to scale the biomass responses from plant up to ecosystem. These results indicated that leaf area might be the appropriate index for plant biomass response to warming, and the interspecific competition might hamper the scaling of the warming effects on plant and ecosystem levels, suggesting that the acclimation capacity of plant community should be incorporated into land surface models to improve the prediction of climate-C cycle feedback.

Using nocturnal cold air drainage flow to monitor ecosystem processes in complex terrain

Treesearch

Thomas G. Pypker; Michael H. Unsworth; Alan C. Mix; William Rugh; Troy Ocheltree; Karrin Alstad; Barbara J. Bond

2007-01-01

This paper presents initial investigations of a new approach to monitor ecosystem processes in complex terrain on large scales. Metabolic processes in mountainous ecosystems are poorly represented in current ecosystem monitoring campaigns because the methods used for monitoring metabolism at the ecosystem scale (e.g., eddy covariance) require flat study sites. Our goal...

Evaluating the agreement between measurements and models of net ecosystem exchange at different times and timescales using wavelet coherence: an example using data from the North American Carbon Program Site-Level Interim Synthesis

Treesearch

P.C. Stoy; M.C. Dietze; A.D. Richardson; R. Vargas; A.G. Barr; R.S. Anderson; M.A. Arain; I.T. Baker; T.A. Black; J.M. Chen; R.B. Cook; C.M. Gough; R.F. Grant; D.Y. Hollinger; R.C. Izaurralde; C.J. Kucharik; P. Lafleur; B.E. Law; S. Liu; E. Lokupitiya; Y. Luo; J. W. Munger; C. Peng; B. Poulter; D.T. Price; D. M. Ricciuto; W. J. Riley; A. K. Sahoo; K. Schaefer; C.R. Schwalm; H. Tian; H. Verbeeck; E. Weng

2013-01-01

Earth system processes exhibit complex patterns across time, as do the models that seek to replicate these processes. Model output may or may not be significantly related to observations at different times and on different frequencies. Conventional model diagnostics provide an aggregate view of model-data agreement, but usually do not identify the time and frequency...

Monitoring landscape level processes using remote sensing of large plots

Treesearch

Raymond L. Czaplewski

1991-01-01

Global and regional assessaents require timely information on landscape level status (e.g., areal extent of different ecosystems) and processes (e.g., changes in land use and land cover). To measure and understand these processes at the regional level, and model their impacts, remote sensing is often necessary. However, processing massive volumes of remotely sensing...

Linking hydrology, ecosystem function, and livelihood sustainability in African papyrus wetlands using a Bayesian Network Model

NASA Astrophysics Data System (ADS)

van Dam, A.; Gettel, G. M.; Kipkemboi, J.; Rahman, M. M.

2011-12-01

Papyrus wetlands in East Africa provide ecosystem services supporting the livelihoods of millions but are rapidly degrading due to economic development. For ecosystem conservation, an integrated understanding of the natural and social processes driving ecosystem change is needed. This research focuses on integrating the causal relationships between hydrology, ecosystem function, and livelihood sustainability in Nyando wetland, western Kenya. Livelihood sustainability is based on ecosystem services that include plant and animal harvest for building material and food, conversion of wetlands to crop and grazing land, water supply, and water quality regulation. Specific objectives were: to integrate studies of hydrology, ecology, and livelihood activities using a Bayesian Network (BN) model and include stakeholder involvement in model development. The BN model (Netica 4.16) had 35 nodes with seven decision nodes describing demography, economy, papyrus market, and rainfall, and two target nodes describing ecosystem function (defined by groundwater recharge, nutrient and sediment retention, and biodiversity) and livelihood sustainability (drinking water supply, crop production, livestock production, and papyrus yield). The conditional probability tables were populated using results of ecohydrological and socio-economic field work and consultations with stakeholders. The model was evaluated for an average year with decision node probabilities set according to data from research, expert opinion, and stakeholders' views. Then, scenarios for dry and wet seasons and for economic development (low population growth and unemployment) and policy development (more awareness of wetland value) were evaluated. In an average year, the probability for maintaining a "good" level of sediment and nutrient retention functions, groundwater recharge, and biodiversity was about 60%. ("Good" is defined by expert opinion based on ongoing field research.) In the dry season, the probability was reduced to about 40% and in the wet season increased to about 85%. Both ecosystem functions and livelihood sustainability were most sensitive to flooding and the human pressure, notably the area of crop conversion, grazing pressure, and papyrus harvest. Flooded conditions limit cropping, livestock herding and vegetation harvesting but have a strong positive effect on ecosystem function. Preliminary results suggest that the effects of economic and policy development on ecosystem function and livelihood sustainability were negligible, but more data on these aspects will be included in further model development. The advantage of this modeling approach, which integrates data from hydrological, ecological, and socio-economic studies, is that it highlights the relative effect of hydrologic conditions and socio-economic pressures on ecosystem function. This model is static, however, with long-term changes in climate and exploitation levels superimposed on seasonal hydrology dynamics. Further work should address this issue as well as further constrain probabilities at each node as field research continues.

Modeling and dynamic monitoring of ecosystem performance in the Yukon River Basin

USGS Publications Warehouse

Wylie, Bruce K.; Zhang, L.; Ji, Lei; Tieszen, Larry L.; Bliss, N.B.

2008-01-01

Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. Resource managers would benefit from an improved ability to monitor ecosystem processes in response to climate change, fire, insect damage, and management policies and to predict responses to future climate scenarios. We have developed a method for analyzing ecosystem performance as represented by the growing season integral of normalized difference vegetation index (NDVI), which is a measure of greenness that can be interpreted in terms of plant growth or photosynthetic activity (gross primary productivity). The approach illustrates the status and trends of ecosystem changes and separates the influences of climate and local site conditions from the influences of disturbances and land management.We emphasize the ability to quantify ecosystem processes, not simply changes in land cover, across the entire period of the remote sensing archive (Wylie and others, 2008). The method builds upon remotely sensed measures of vegetation greenness for each growing season. By itself, however, a time series of greenness often reflects annual climate variations in temperature and precipitation. Our method seeks to remove the influence of climate so that changes in underlying ecological conditions are identified and quantified. We define an "expected ecosystem performance" to represent the greenness response expected in a particular year given the climate of that year. We distinguish "performance anomalies" as cases where the ecosystem response is significantly different from the expected ecosystem performance. Maps of the performance anomalies (fig. 1) and trends in the anomalies give valuable information on the ecosystems for land managers and policy makers at a resolution of 1 km to 250 m.

Overcoming uncertainty with carbonyl sulfide-based GPP estimates: observing and modeling soil COS fluxes in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Whelan, M.; Hilton, T. W.; Berry, J. A.; Berkelhammer, M. B.; Desai, A. R.; Rastogi, B.; Campbell, J. E.

2015-12-01

Significant carbonyl sulfide (COS) exchange by soils limits the applicability of net ecosystem COS flux observations as a proxy for stomatal trace gas exchange. High frequency measurements of COS over urban and natural ecosystems offer a potential window into processes regulating the carbon and water cycle: photosynthetic carbon uptake and stomatal conductance. COS diffuses through plant stomata and is irreversibly consumed by enzymes involved in photosynthesis. In certain environments, the magnitude of soil COS fluxes may constitute one-quarter of COS uptake by plants. Here we present a way of anticipating conditions when anomalously large soil COS fluxes are likely to occur and be taken into account. Previous studies have pointed to either a tendency for soil uptake of COS from the atmosphere with a soil moisture optimum, or exponential COS production coincident with temperature. Data from field and laboratory studies were used to deconvolve the two processes. CO2 and COS fluxes were observed from forest, desert, grassland, and agricultural soils under a range of temperature and soil moisture conditions. We demonstrate how to estimate temperature and soil moisture impacts on COS soil production based on our cross-site incubations. By building a model of soil COS exchange that combines production and consumption terms, we offer a framework for interpreting the two disparate conclusions about soil COS exchange in previous studies. Such a construction should be used in ecosystem and continental scale modeling of COS fluxes to anticipate where the influence of soil COS exchange needs to be accounted for, resulting in greater utility of carbonyl sulfide as a tracer of plant physiological processes.

Pre-industrial baseline variation of upper midwestern forests in the United States

NASA Astrophysics Data System (ADS)

Dawson, A.; Paciorek, C. J.; Goring, S. J.; Williams, J. W.; Jackson, S. T.; McLachlan, J. S.

2016-12-01

Terrestrial ecosystems play an important role in Earth systems processes, yet we still do not understand how they respond to changes in climate. While it has been argued that terrestrial ecosystems were fairly stable (by Quaternary standards) in the millennia before major anthropogenic disruption, others have emphasized vegetation response to environmental variability during this time. These competing perspectives are not necessarily in conflict, but argue for a quantitative assessment of forest ecosystem variability over the last several millennia. Here we reconstruct maps of forest composition for the last two millenia, with uncertainty. To do this, we use a network of fossil pollen records - the most reliable paleoecological proxy for forest composition. We link the fossil pollen records to public land survey forest composition using a Bayesian hierarchical model which accounts for key processes including pollen production and dispersal. The model is calibrated using data from the pre-settlement time with the hope of minimizing anthropogenic impacts. Process parameters are estimated in the calibration phase, and are subsequently used in the prediction phase to generate spatially explicit maps of relative species composition across the upper Midwestern US over the last 2000 years, with robust uncertainty estimates. Estimates of forest composition and uncertainty show many previously noted vegetation shifts, three of which we discuss here. First, we see expansion of the hemlock range into western Wisconsin. Second, we see changes along the prairie-forest ecotone. Third, we see significant increases in elm at approximately 500 YBP in the region known as the Minnesota Big Woods. These changes are significant in both a statistical and ecological sense, but the scale of these changes is small relative to changes in the early holocene. Our novel spatio-temporal composition estimates will be used to improve the forecasting capabilities of ecosystem models.

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

Treesearch

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

2014-01-01

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

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

Treesearch

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

2011-01-01

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

Evaluation of a hierarchy of models reveals importance of substrate limitation for predicting carbon dioxide and methane exchange in restored wetlands

NASA Astrophysics Data System (ADS)

Oikawa, P. Y.; Jenerette, G. D.; Knox, S. H.; Sturtevant, C.; Verfaillie, J.; Dronova, I.; Poindexter, C. M.; Eichelmann, E.; Baldocchi, D. D.

2017-01-01

Wetlands and flooded peatlands can sequester large amounts of carbon (C) and have high greenhouse gas mitigation potential. There is growing interest in financing wetland restoration using C markets; however, this requires careful accounting of both CO2 and CH4 exchange at the ecosystem scale. Here we present a new model, the PEPRMT model (Peatland Ecosystem Photosynthesis Respiration and Methane Transport), which consists of a hierarchy of biogeochemical models designed to estimate CO2 and CH4 exchange in restored managed wetlands. Empirical models using temperature and/or photosynthesis to predict respiration and CH4 production were contrasted with a more process-based model that simulated substrate-limited respiration and CH4 production using multiple carbon pools. Models were parameterized by using a model-data fusion approach with multiple years of eddy covariance data collected in a recently restored wetland and a mature restored wetland. A third recently restored wetland site was used for model validation. During model validation, the process-based model explained 70% of the variance in net ecosystem exchange of CO2 (NEE) and 50% of the variance in CH4 exchange. Not accounting for high respiration following restoration led to empirical models overestimating annual NEE by 33-51%. By employing a model-data fusion approach we provide rigorous estimates of uncertainty in model predictions, accounting for uncertainty in data, model parameters, and model structure. The PEPRMT model is a valuable tool for understanding carbon cycling in restored wetlands and for application in carbon market-funded wetland restoration, thereby advancing opportunity to counteract the vast degradation of wetlands and flooded peatlands.

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; Wullschleger, Stan D.; Thornton, Peter E.; Riley, William J.; Song, Xia; Graham, David E.; Song, Changchun; Tian, Hanqin

2016-06-01

Over the past 4 decades, a number of numerical models have been developed to quantify the magnitude, investigate the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH4) fluxes within terrestrial ecosystems. These CH4 models are also used for integrating multi-scale CH4 data, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. Here we summarize 40 terrestrial CH4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvement and application. Our key findings are that (1) the focus of CH4 models has shifted from theoretical to site- and regional-level applications over the past 4 decades, (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls, and (3) significant data-model and model-model mismatches are partially attributed to different representations of landscape characterization and inundation dynamics. Three areas for future improvements and applications of terrestrial CH4 models are that (1) CH4 models should more explicitly represent the mechanisms underlying land-atmosphere CH4 exchange, with an emphasis on improving and validating individual CH4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH4 emissions across highly heterogeneous spatial and temporal scales, particularly hot moments and hotspots, and (3) efforts should be invested to develop model benchmarking frameworks that can easily be used for model improvement, evaluation, and integration with data from molecular to global scales. These improvements in CH4 models would be beneficial for the Earth system models and further simulation of climate-carbon cycle feedbacks.

Biospheric Monitoring and Ecological Forecasting using EOS/MODIS data, ecosystem modeling, planning and scheduling technologies

NASA Astrophysics Data System (ADS)

Nemani, R. R.; Votava, P.; Golden, K.; Hashimoto, H.; Jolly, M.; White, M.; Running, S.; Coughlan, J.

2003-12-01

The latest generation of NASA Earth Observing System satellites has brought a new dimension to continuous monitoring of the living part of the Earth System, the Biosphere. EOS data can now provide weekly global measures of vegetation productivity and ocean chlorophyll, and many related biophysical factors such as land cover changes or snowmelt rates. However, information with the highest economic value would be forecasting impending conditions of the biosphere that would allow advanced decision-making to mitigate dangers, or exploit positive trends. We have developed a software system called the Terrestrial Observation and Prediction System (TOPS) to facilitate rapid analysis of ecosystem states/functions by integrating EOS data with ecosystem models, surface weather observations and weather/climate forecasts. Land products from MODIS (Moderate Resolution Imaging Spectroradiometer) including land cover, albedo, snow, surface temperature, leaf area index are ingested into TOPS for parameterization of models and for verifying model outputs such as snow cover and vegetation phenology. TOPS is programmed to gather data from observing networks such as USDA soil moisture, AMERIFLUX, SNOWTEL to further enhance model predictions. Key technologies enabling TOPS implementation include the ability to understand and process heterogeneous-distributed data sets, automated planning and execution of ecosystem models, causation analysis for understanding model outputs. Current TOPS implementations at local (vineyard) to global scales (global net primary production) can be found at http://www.ntsg.umt.edu/tops.

Revealing Invisible Water: Moisture Recycling as an Ecosystem Service.

PubMed

Keys, Patrick W; Wang-Erlandsson, Lan; Gordon, Line J

2016-01-01

An ecosystem service is a benefit derived by humanity that can be traced back to an ecological process. Although ecosystem services related to surface water have been thoroughly described, the relationship between atmospheric water and ecosystem services has been mostly neglected, and perhaps misunderstood. Recent advances in land-atmosphere modeling have revealed the importance of terrestrial ecosystems for moisture recycling. In this paper, we analyze the extent to which vegetation sustains the supply of atmospheric moisture and precipitation for downwind beneficiaries, globally. We simulate land-surface evaporation with a global hydrology model and track changes to moisture recycling using an atmospheric moisture budget model, and we define vegetation-regulated moisture recycling as the difference in moisture recycling between current vegetation and a hypothetical desert world. Our results show that nearly a fifth of annual average precipitation falling on land is from vegetation-regulated moisture recycling, but the global variability is large, with many places receiving nearly half their precipitation from this ecosystem service. The largest potential impacts for changes to this ecosystem service are land-use changes across temperate regions in North America and Russia. Likewise, in semi-arid regions reliant on rainfed agricultural production, land-use change that even modestly reduces evaporation and subsequent precipitation, could significantly affect human well-being. We also present a regional case study in the Mato Grosso region of Brazil, where we identify the specific moisture recycling ecosystem services associated with the vegetation in Mato Grosso. We find that Mato Grosso vegetation regulates some internal precipitation, with a diffuse region of benefit downwind, primarily to the south and east, including the La Plata River basin and the megacities of Sao Paulo and Rio de Janeiro. We synthesize our global and regional results into a generalized framework for describing moisture recycling as an ecosystem service. We conclude that future work ought to disentangle whether and how this vegetation-regulated moisture recycling interacts with other ecosystem services, so that trade-offs can be assessed in a comprehensive and sustainable manner.

Application of the Ecosystem Diagnosis and Treatment Method to the Grande Ronde Model Watershed project : Final Report.

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

Mobrand, Lars Erik; Lestelle, Lawrence C.

In the spring of 1994 a technical planning support project was initiated by the Grande Ronde Model Watershed Board of Directors (Board) with funding from the Bonneville Power Administration. The project was motivated by a need for a science based method for prioritizing restoration actions in the basin that would promote effectiveness and accountability. In this section the authors recall the premises for the project. The authors also present a set of recommendations for implementing a watershed planning process that incorporates a science-based framework to help guide decision making. This process is intended to assist the Grande Ronde Model Watershedmore » Board in its effort to plan and implement watershed improvement measures. The process would also assist the Board in coordinating its efforts with other entities in the region. The planning process is based on an approach for developing an ecosystem management strategy referred to as the Ecosystem Diagnosis and Treatment (EDT) method (Lichatowich et al. 1995, Lestelle et al. 1996). The process consists of an on-going planning cycle. Included in this cycle is an assessment of the ability of the watershed to support and sustain natural resources and other economic and societal values. This step in the process, which the authors refer to as the diagnosis, helps guide the development of actions (also referred to as treatments) aimed at improving the conditions of the watershed to achieve long-term objectives. The planning cycle calls for routinely reviewing and updating, as necessary, the basis for the diagnosis and other analyses used by the Board in adopting actions for implementation. The recommendations offered here address this critical need to habitually update the information used in setting priorities for action.« less

Identification of the main processes underlying ecosystem functioning in the Eastern English Channel, with a focus on flatfish species, as revealed through the application of the Atlantis end-to-end model

NASA Astrophysics Data System (ADS)

Girardin, Raphaël; Fulton, Elizabeth A.; Lehuta, Sigrid; Rolland, Marie; Thébaud, Olivier; Travers-Trolet, Morgane; Vermard, Youen; Marchal, Paul

2018-02-01

The ecosystem model Atlantis was used to investigate the key dynamics and processes that structure the Eastern English Channel ecosystem, with a particular focus on two commercial flatfish species, sole (Solea solea) and plaice (Pleuronectes platessa). This complex model was parameterized with data collected from diverse sources (a literature review, survey data, as well as landings and stock assessment information) and tuned so both simulated biomass and catch fit 2002-2011 observations. Here, the outputs are mainly presented for the two focus species and for some other vertebrates found to be important in the trophic network. The calibration process revealed the importance of coastal areas in the Eastern English Channel and of nutrient inputs from estuaries: a lack of river nutrients decreases the productivity of nursery grounds and adversely affects the production of sole and plaice. The role of discards in the trophic network is also highlighted. While sole and plaice did not have a strong influence on the trophic network of vertebrates, they are important predators for benthic invertebrates and compete for food with crustaceans, whiting (Merlangius merlangus) and other demersal fish. We also found that two key species, cod (Gadus morhua) and whiting, thoroughly structured the Eastern English Channel trophic network.

Modeling the dynamics of metabolism in montane streams using continuous dissolved oxygen measurements

NASA Astrophysics Data System (ADS)

Birkel, Christian; Soulsby, Chris; Malcolm, Iain; Tetzlaff, Doerthe

2013-09-01

We inferred in-stream ecosystem processes in terms of photosynthetic productivity (P), system respiration (R), and reaeration capacity (RC) from a five parameter numerical oxygen mass balance model driven by radiation, stream and air temperature, and stream depth. This was calibrated to high-resolution (15 min), long-term (2.5 years) dissolved oxygen (DO) time series for moorland and forest reaches of a third-order montane stream in Scotland. The model was multicriteria calibrated to continuous 24 h periods within the time series to identify behavioral simulations representative of ecosystem functioning. Results were evaluated using a seasonal regional sensitivity analysis and a colinearity index for parameter sensitivity. This showed that >95 % of the behavioral models for the moorland and forest sites were identifiable and able to infer in-stream processes from the DO time series for around 40% and 32% of the time period, respectively. Monthly P/R ratios <1 indicate a heterotrophic system with both sites exhibiting similar temporal patterns; with a maximum in February and a second peak during summer months. However, the estimated net ecosystem productivity suggests that the moorland reach without riparian tree cover is likely to be a much larger source of carbon to the atmosphere (122 mmol C m-2 d-1) compared to the forested reach (64 mmol C m-2 d-1). We conclude that such process-based oxygen mass balance models may be transferable tools for investigating other systems; specifically, well-oxygenated upland channels with high hydraulic roughness and lacking reaeration measurements.

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.

Biological soil crusts (biocrusts) as a model system in community, landscape and ecosystem ecology

USGS Publications Warehouse

Bowker, Matthew A.; Maestre, Fernando T.; Eldridge, David; Belnap, Jayne; Castillo-Monroy, Andrea; Escolar, Cristina; Soliveres, Santiago

2014-01-01

Model systems have had a profound influence on the development of ecological theory and general principles. Compared to alternatives, the most effective models share some combination of the following characteristics: simpler, smaller, faster, general, idiosyncratic or manipulable. We argue that biological soil crusts (biocrusts) have unique combinations of these features that should be more widely exploited in community, landscape and ecosystem ecology. In community ecology, biocrusts are elucidating the importance of biodiversity and spatial pattern for maintaining ecosystem multifunctionality due to their manipulability in experiments. Due to idiosyncrasies in their modes of facilitation and competition, biocrusts have led to new models on the interplay between environmental stress and biotic interactions and on the maintenance of biodiversity by competitive processes. Biocrusts are perhaps one of the best examples of micro-landscapes—real landscapes that are small in size. Although they exhibit varying patch heterogeneity, aggregation, connectivity and fragmentation, like macro-landscapes, they are also compatible with well-replicated experiments (unlike macro-landscapes). In ecosystem ecology, a number of studies are imposing small-scale, low cost manipulations of global change or state factors in biocrust micro-landscapes. The versatility of biocrusts to inform such disparate lines of inquiry suggests that they are an especially useful model system that can enable researchers to see ecological principles more clearly and quickly.

A computer model to forecast wetland vegetation changes resulting from restoration and protection in coastal Louisiana

USGS Publications Warehouse

Visser, Jenneke M.; Duke-Sylvester, Scott M.; Carter, Jacoby; Broussard, Whitney P.

2013-01-01

The coastal wetlands of Louisiana are a unique ecosystem that supports a diversity of wildlife as well as a diverse community of commercial interests of both local and national importance. The state of Louisiana has established a 5-year cycle of scientific investigation to provide up-to-date information to guide future legislation and regulation aimed at preserving this critical ecosystem. Here we report on a model that projects changes in plant community distribution and composition in response to environmental conditions. This model is linked to a suite of other models and requires input from those that simulate the hydrology and morphology of coastal Louisiana. Collectively, these models are used to assess how alternative management plans may affect the wetland ecosystem through explicit spatial modeling of the physical and biological processes affected by proposed modifications to the ecosystem. We have also taken the opportunity to advance the state-of-the-art in wetland plant community modeling by using a model that is more species-based in its description of plant communities instead of one based on aggregated community types such as brackish marsh and saline marsh. The resulting model provides an increased level of ecological detail about how wetland communities are expected to respond. In addition, the output from this model provides critical inputs for estimating the effects of management on higher trophic level species though a more complete description of the shifts in habitat.

The implications of microbial and substrate limitation for the fates of carbon in different organic soil horizon types of boreal forest ecosystems: a mechanistically based model analysis

USGS Publications Warehouse

He, Y.; Zhuang, Q.; Harden, Jennifer W.; McGuire, A. David; Fan, Z.; Liu, Y.; Wickland, Kimberly P.

2014-01-01

The large amount of soil carbon in boreal forest ecosystems has the potential to influence the climate system if released in large quantities in response to warming. Thus, there is a need to better understand and represent the environmental sensitivity of soil carbon decomposition. Most soil carbon decomposition models rely on empirical relationships omitting key biogeochemical mechanisms and their response to climate change is highly uncertain. In this study, we developed a multi-layer microbial explicit soil decomposition model framework for boreal forest ecosystems. A thorough sensitivity analysis was conducted to identify dominating biogeochemical processes and to highlight structural limitations. Our results indicate that substrate availability (limited by soil water diffusion and substrate quality) is likely to be a major constraint on soil decomposition in the fibrous horizon (40–60% of soil organic carbon (SOC) pool size variation), while energy limited microbial activity in the amorphous horizon exerts a predominant control on soil decomposition (>70% of SOC pool size variation). Elevated temperature alleviated the energy constraint of microbial activity most notably in amorphous soils, whereas moisture only exhibited a marginal effect on dissolved substrate supply and microbial activity. Our study highlights the different decomposition properties and underlying mechanisms of soil dynamics between fibrous and amorphous soil horizons. Soil decomposition models should consider explicitly representing different boreal soil horizons and soil–microbial interactions to better characterize biogeochemical processes in boreal forest ecosystems. A more comprehensive representation of critical biogeochemical mechanisms of soil moisture effects may be required to improve the performance of the soil model we analyzed in this study.

The National Ecosystem Services Classification System: A Framework for Identifying and Reducing Relevant Uncertainties

NASA Astrophysics Data System (ADS)

Rhodes, C. R.; Sinha, P.; Amanda, N.

2013-12-01

In recent years the gap between what scientists know and what policymakers should appreciate in environmental decision making has received more attention, as the costs of the disconnect have become more apparent to both groups. Particularly for water-related policies, the EPA's Office of Water has struggled with benefit estimates held low by the inability to quantify ecological and economic effects that theory, modeling, and anecdotal or isolated case evidence suggest may prove to be larger. Better coordination with ecologists and hydrologists is being explored as a solution. The ecosystem services (ES) concept now nearly two decades old links ecosystem functions and processes to the human value system. But there remains no clear mapping of which ecosystem goods and services affect which individual or economic values. The National Ecosystem Services Classification System (NESCS, 'nexus') project brings together ecologists, hydrologists, and social scientists to do this mapping for aquatic and other ecosystem service-generating systems. The objective is to greatly reduce the uncertainty in water-related policy making by mapping and ultimately quantifying the various functions and products of aquatic systems, as well as how changes to aquatic systems impact the human economy and individual levels of non-monetary appreciation for those functions and products. Primary challenges to fostering interaction between scientists, social scientists, and policymakers are lack of a common vocabulary, and the need for a cohesive comprehensive framework that organizes concepts across disciplines and accommodates scientific data from a range of sources. NESCS builds the vocabulary and the framework so both may inform a scalable transdisciplinary policy-making application. This talk presents for discussion the process and progress in developing both this vocabulary and a classifying framework capable of bridging the gap between a newer but existing ecosystem services classification system, and a standardized industrial classification system. Our goal is to model then predict the effects of a policy choice on the environment, from impacts on ecological components and processes all the way through to endpoints in the human value chain.

Assessing climate-sensitive ecosystems in the southeastern United States

USGS Publications Warehouse

Costanza, Jennifer; Beck, Scott; Pyne, Milo; Terando, Adam; Rubino, Matthew J.; White, Rickie; Collazo, Jaime

2016-08-11

Climate change impacts ecosystems in many ways, from effects on species to phenology to wildfire dynamics. Assessing the potential vulnerability of ecosystems to future changes in climate is an important first step in prioritizing and planning for conservation. Although assessments of climate change vulnerability commonly are done for species, fewer have been done for ecosystems. To aid regional conservation planning efforts, we assessed climate change vulnerability for ecosystems in the Southeastern United States and Caribbean.First, we solicited input from experts to create a list of candidate ecosystems for assessment. From that list, 12 ecosystems were selected for a vulnerability assessment that was based on a synthesis of available geographic information system (GIS) data and literature related to 3 components of vulnerability—sensitivity, exposure, and adaptive capacity. This literature and data synthesis comprised “Phase I” of the assessment. Sensitivity is the degree to which the species or processes in the ecosystem are affected by climate. Exposure is the likely future change in important climate and sea level variables. Adaptive capacity is the degree to which ecosystems can adjust to changing conditions. Where available, GIS data relevant to each of these components were used. For example, we summarized observed and projected climate, protected areas existing in 2011, projected sea-level rise, and projected urbanization across each ecosystem’s distribution. These summaries were supplemented with information in the literature, and a short narrative assessment was compiled for each ecosystem. We also summarized all information into a qualitative vulnerability rating for each ecosystem.Next, for 2 of the 12 ecosystems (East Gulf Coastal Plain Near-Coast Pine Flatwoods and Nashville Basin Limestone Glade and Woodland), the NatureServe Habitat Climate Change Vulnerability Index (HCCVI) framework was used as an alternative approach for assessing vulnerability. Use of the HCCVI approach comprised “Phase II” of the assessment. This approach uses summaries of GIS data and models to develop a series of numeric indices for components of vulnerability. We incorporated many of the data sources used in Phase I, but added the results of several other data sources, including climate envelope modeling and vegetation dynamics modeling. The results of Phase II were high and low numeric vulnerability ratings for mid-century and the end of century for each ecosystem. The high and low ratings represented the potential range of vulnerability scores owing to uncertainties in future climate conditions and ecosystem effects.Of the 12 ecosystems assessed in the first approach, five were rated as having high vulnerability (Caribbean Coastal Mangrove, Caribbean Montane Wet Elfin Forest, East Gulf Coastal Plain Southern Loess Bluff Forest, Edwards Plateau Limestone Shrubland, and Nashville Basin Limestone Glade and Woodland). Six ecosystems had medium vulnerability, and one ecosystem had low vulnerability. For the two ecosystems assessed with both approaches, vulnerability ratings generally agreed. The assessment concluded by comparing the two approaches, identifying critical research needs, and making suggestions for future ecosystem vulnerability assessments in the Southeast and beyond. Research needs include reducing uncertainty in the degree of climate exposure likely in the future, as well as acquiring more information on how climate might affect biotic interactions and hydrologic processes. Ideally, a comprehensive vulnerability assessment would include both the narrative summaries that resulted from the synthesis in Phase I, as well as a numeric index that incorporates uncertainty as in Phase II.

Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA

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

Sihi, Debjani; Davidson, Eric A.; Chen, Min

Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO 2), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q 10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs.more » The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.« less

Emergent climate and CO2 sensitivities of net primary productivity in ecosystem models do not agree with empirical data in temperate forests of eastern North America.

PubMed

Rollinson, Christine R; Liu, Yao; Raiho, Ann; Moore, David J P; McLachlan, Jason; Bishop, Daniel A; Dye, Alex; Matthes, Jaclyn H; Hessl, Amy; Hickler, Thomas; Pederson, Neil; Poulter, Benjamin; Quaife, Tristan; Schaefer, Kevin; Steinkamp, Jörg; Dietze, Michael C

2017-07-01

Ecosystem models show divergent responses of the terrestrial carbon cycle to global change over the next century. Individual model evaluation and multimodel comparisons with data have largely focused on individual processes at subannual to decadal scales. Thus far, data-based evaluations of emergent ecosystem responses to climate and CO 2 at multidecadal and centennial timescales have been rare. We compared the sensitivity of net primary productivity (NPP) to temperature, precipitation, and CO 2 in ten ecosystem models with the sensitivities found in tree-ring reconstructions of NPP and raw ring-width series at six temperate forest sites. These model-data comparisons were evaluated at three temporal extents to determine whether the rapid, directional changes in temperature and CO 2 in the recent past skew our observed responses to multiple drivers of change. All models tested here were more sensitive to low growing season precipitation than tree-ring NPP and ring widths in the past 30 years, although some model precipitation responses were more consistent with tree rings when evaluated over a full century. Similarly, all models had negative or no response to warm-growing season temperatures, while tree-ring data showed consistently positive effects of temperature. Although precipitation responses were least consistent among models, differences among models to CO 2 drive divergence and ensemble uncertainty in relative change in NPP over the past century. Changes in forest composition within models had no effect on climate or CO 2 sensitivity. Fire in model simulations reduced model sensitivity to climate and CO 2 , but only over the course of multiple centuries. Formal evaluation of emergent model behavior at multidecadal and multicentennial timescales is essential to reconciling model projections with observed ecosystem responses to past climate change. Future evaluation should focus on improved representation of disturbance and biomass change as well as the feedbacks with moisture balance and CO 2 in individual models. © 2017 John Wiley & Sons Ltd.

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.

Linkages of plant stoichiometry to ecosystem production and carbon fluxes with increasing nitrogen inputs in an alpine steppe.

PubMed

Peng, Yunfeng; Li, Fei; Zhou, Guoying; Fang, Kai; Zhang, Dianye; Li, Changbin; Yang, Guibiao; Wang, Guanqin; Wang, Jun; Yang, Yuanhe

2017-12-01

Unprecedented levels of nitrogen (N) have entered terrestrial ecosystems over the past century, which substantially influences the carbon (C) exchange between the atmosphere and biosphere. Temperature and moisture are generally regarded as the major controllers over the N effects on ecosystem C uptake and release. N-phosphorous (P) stoichiometry regulates the growth and metabolisms of plants and soil organisms, thereby affecting many ecosystem C processes. However, it remains unclear how the N-induced shift in the plant N:P ratio affects ecosystem production and C fluxes and its relative importance. We conducted a field manipulative experiment with eight N addition levels in a Tibetan alpine steppe and assessed the influences of N on aboveground net primary production (ANPP), gross ecosystem productivity (GEP), ecosystem respiration (ER), and net ecosystem exchange (NEE); we used linear mixed-effects models to further determine the relative contributions of various factors to the N-induced changes in these parameters. Our results showed that the ANPP, GEP, ER, and NEE all exhibited nonlinear responses to increasing N additions. Further analysis demonstrated that the plant N:P ratio played a dominate role in shaping these C exchange processes. There was a positive relationship between the N-induced changes in ANPP (ΔANPP) and the plant N:P ratio (ΔN:P), whereas the ΔGEP, ΔER, and ΔNEE exhibited quadratic correlations with the ΔN:P. In contrast, soil temperature and moisture were only secondary predictors for the changes in ecosystem production and C fluxes along the N addition gradient. These findings highlight the importance of plant N:P ratio in regulating ecosystem C exchange, which is crucial for improving our understanding of C cycles under the scenarios of global N enrichment. © 2017 John Wiley & Sons Ltd.

[Response of water yield function of ecosystem to land use change in Nansi Lake Basin based on CLUE-S model and InVEST model .

PubMed

Guo, Hong Wei; Sun, Xiao Yin; Lian, Li Shu; Zhang, Da Zhi; Xu, Yan

2016-09-01

Land use change has an important role in hydrological processes and utilization of water resources, and is the main driving force of water yield function of ecosystem. This paper analyzed the change of land use from 1990 to 2013 in Nansi Lake Basin, Shandong Province. The future land use in 2030 was also predicted and simulated by CLUE-S model. Based on land use scenarios, we analyzed the influence of land use change on ecosystem function of water yield in nearly 25 years through InVEST water yield model and spatial mapping. The results showed that the area of construction land increased by 3.5% in 2013 because of burgeoning urbanization process, but farmland area decreased by 2.4% which was conversed to construction land mostly. The simulated result of InVEST model suggested that water yield level of whole basin decreased firstly and increased subsequently during last 25 years and peaked at 232.1 mm in 2013. The construction land area would increase by 6.7% in 2030 based on the land use scenarios of fast urbanization, which would lead to a remarkable growth for water yield and risk of flowing flooding. However, the water yield level of whole basin would decrease by 1.2 % in 2013 if 300 meter-wide forest buffer strips around Nansi Lake were built up.

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

Interactions between drought and soil biogeochemistry: scaling from molecules to meters

NASA Astrophysics Data System (ADS)

Schimel, J.; Schaeffer, S. M.

2011-12-01

Water is the perhaps the single most critical resource for life, yet most terrestrial ecosystems experience regular drought. Reduced water potential causes physiological stress; reduced diffusion limits resource availability when microbes may need resources to acclimate. Most biogeochemical models, however, have assumed that soil processes either slow down or stop during drought. But organisms survive and enzymes remain viable. In California, as soils stay dry through the long summer drought, microbial biomass actually increases and pools of extractable organic C increase, probably because extracellular enzymes continue to break down plant detritus (notably roots). Yet 14C suggests that in deeper soils, the pulse of C released on rewetting comes from pools with turnover times of as long as 800 years. What are the mechanisms that regulate these complex dynamics? They appear to involve differential moisture sensitivity for the activity of extracellular enzymes, substrate diffusion, and microbial metabolism. Rewetting not only redistributes materials made available during the drought, but it also disrupts aggregates and may make previously-protected substrates available as well. We have used several methods to simply capture these linkages between water and carbon in models that are applicable at the ecosystem scale and that could improve our ability to model biogeochemical cycles in arid and semi-arid ecosystems. One is a simple empirical modification to the DAYCENT model while the other is a mechanistic model that incorporates microbial dry-season processes.

Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS)

NASA Technical Reports Server (NTRS)

Masek, Jeffrey G.

2006-01-01

The Landsat Ecosystem Disturbance Adaptive Processing System (LEDAPS) project is creating a record of forest disturbance and regrowth for North America from the Landsat satellite record, in support of the carbon modeling activities. LEDAPS relies on the decadal Landsat GeoCover data set supplemented by dense image time series for selected locations. Imagery is first atmospherically corrected to surface reflectance, and then change detection algorithms are used to extract disturbance area, type, and frequency. Reuse of the MODIS Land processing system (MODAPS) architecture allows rapid throughput of over 2200 MSS, TM, and ETM+ scenes. Initial ("Beta") surface reflectance products are currently available for testing, and initial continental disturbance products will be available by the middle of 2006.

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.

Soil mapping and processes modelling for sustainable land management: a review

NASA Astrophysics Data System (ADS)

Pereira, Paulo; Brevik, Eric; Muñoz-Rojas, Miriam; Miller, Bradley; Smetanova, Anna; Depellegrin, Daniel; Misiune, Ieva; Novara, Agata; Cerda, Artemi

2017-04-01

Soil maps and models are fundamental for a correct and sustainable land management (Pereira et al., 2017). They are an important in the assessment of the territory and implementation of sustainable measures in urban areas, agriculture, forests, ecosystem services, among others. Soil maps represent an important basis for the evaluation and restoration of degraded areas, an important issue for our society, as consequence of climate change and the increasing pressure of humans on the ecosystems (Brevik et al. 2016; Depellegrin et al., 2016). The understanding of soil spatial variability and the phenomena that influence this dynamic is crucial to the implementation of sustainable practices that prevent degradation, and decrease the economic costs of soil restoration. In this context, soil maps and models are important to identify areas affected by degradation and optimize the resources available to restore them. Overall, soil data alone or integrated with data from other sciences, is an important part of sustainable land management. This information is extremely important land managers and decision maker's implements sustainable land management policies. The objective of this work is to present a review about the advantages of soil mapping and process modeling for sustainable land management. References Brevik, E., Calzolari, C., Miller, B., Pereira, P., Kabala, C., Baumgarten, A., Jordán, A. (2016) Historical perspectives and future needs in soil mapping, classification and pedological modelling, Geoderma, 264, Part B, 256-274. Depellegrin, D.A., Pereira, P., Misiune, I., Egarter-Vigl, L. (2016) Mapping Ecosystem Services in Lithuania. International Journal of Sustainable Development and World Ecology, 23, 441-455. Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B., Smetanova, A., Depellegrin, D., Misiune, I., Novara, A., Cerda, A. (2017) Soil mapping and process modelling for sustainable land management. In: Pereira, P., Brevik, E., Munoz-Rojas, M., Miller, B. (Eds.) Soil mapping and process modelling for sustainable land use management (Elsevier Publishing House) ISBN: 9780128052006

The Arctic Marine Pulses Model: Linking Contiguous Domains in the Pacific Arctic Region

NASA Astrophysics Data System (ADS)

Moore, S. E.; Stabeno, P. J.

2016-02-01

The Pacific Arctic marine ecosystem extends from the northern Bering Sea, across the Chukchi and into the East Siberian and Beaufort seas. Food webs in this domain are short, a simplicity that belies the biophysical complexity underlying trophic linkages from primary production to humans. Existing biophysical models, such as pelagic-benthic coupling and advective processes, provide frameworks for connecting certain aspects of the marine food web, but do not offer a full accounting of events that occur seasonally across the Pacific Arctic. In the course of the Synthesis of Arctic Research (SOAR) project, a holistic Arctic Marine Pulses (AMP) model was developed that depicts seasonal biophysical `pulses' across a latitudinal gradient, and linking four previously-described contiguous domains, including the: (i) Pacific-Arctic domain = the focal region; (ii) seasonal ice zone domain; (iii) Pacific marginal domain; and (iv) riverine coastal domain. The AMP model provides a spatial-temporal framework to guide research on dynamic ecosystem processes during this period of rapid biophysical changes in the Pacific Arctic. Some of the processes included in the model, such as pelagic-benthic coupling in the Northern Bering and Chukchi seas, and advection and upwelling along the Beaufort shelf, are already the focus of sampling via the Distributed Biological Observatory (DBO) and other research programs. Other aspects such as biological processes associated with the seasonal ice zone and trophic responses to riverine outflow have received less attention. The AMP model could be enhanced by the application of visualization tools to provide a means to watch a season unfold in space and time. The capability to track sea ice dynamics and water masses and to move nutrients, prey and upper-trophic predators in space and time would provide a strong foundation for the development of predictive human-inclusive ecosystem models for the Pacific Arctic.