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...

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...

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.

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...

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

DOE PAGES

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.; ...

2017-03-13

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

Building a better foundation: improving root-trait measurements to understand and model plant and ecosystem processes

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

McCormack, M. Luke; Guo, Dali; Iversen, Colleen M.

Trait-based approaches provide a useful framework to investigate plant strategies for resource acquisition, growth, and competition, as well as plant impacts on ecosystem processes. Despite significant progress capturing trait variation within and among stems and leaves, identification of trait syndromes within fine-root systems and between fine roots and other plant organs is limited. Here we discuss three underappreciated areas where focused measurements of fine-root traits can make significant contributions to ecosystem science. These include assessment of spatiotemporal variation in fine-root traits, integration of mycorrhizal fungi into fine-root-trait frameworks, and the need for improved scaling of traits measured on individual rootsmore » to ecosystem-level processes. Progress in each of these areas is providing opportunities to revisit how below-ground processes are represented in terrestrial biosphere models. Targeted measurements of fine-root traits with clear linkages to ecosystem processes and plant responses to environmental change are strongly needed to reduce empirical and model uncertainties. Further identifying how and when suites of root and whole-plant traits are coordinated or decoupled will ultimately provide a powerful tool for modeling plant form and function at local and global scales.« less

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.

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,…

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.

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...

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.

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

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.

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...

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.

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.

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.

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.

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.

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.

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.

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...

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

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.

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.

One carbon cycle: Impacts of model integration, ecosystem process detail, model resolution, and initialization data, on projections of future climate mitigation strategies

NASA Astrophysics Data System (ADS)

Fisk, J.; Hurtt, G. C.; le page, Y.; Patel, P. L.; Chini, L. P.; Sahajpal, R.; Dubayah, R.; Thomson, A. M.; Edmonds, J.; Janetos, A. C.

2013-12-01

Integrated assessment models (IAMs) simulate the interactions between human and natural systems at a global scale, representing a broad suite of phenomena across the global economy, energy system, land-use, and carbon cycling. Most proposed climate mitigation strategies rely on maintaining or enhancing the terrestrial carbon sink as a substantial contribution to restrain the concentration of greenhouse gases in the atmosphere, however most IAMs rely on simplified regional representations of terrestrial carbon dynamics. Our research aims to reduce uncertainties associated with forest modeling within integrated assessments, and to quantify the impacts of climate change on forest growth and productivity for integrated assessments of terrestrial carbon management. We developed the new Integrated Ecosystem Demography (iED) to increase terrestrial ecosystem process detail, resolution, and the utilization of remote sensing in integrated assessments. iED brings together state-of-the-art models of human society (GCAM), spatial land-use patterns (GLM) and terrestrial ecosystems (ED) in a fully coupled framework. The major innovative feature of iED is a consistent, process-based representation of ecosystem dynamics and carbon cycle throughout the human, terrestrial, land-use, and atmospheric components. One of the most challenging aspects of ecosystem modeling is to provide accurate initialization of land surface conditions to reflect non-equilibrium conditions, i.e., the actual successional state of the forest. As all plants in ED have an explicit height, it is one of the few ecosystem models that can be initialized directly with vegetation height data. Previous work has demonstrated that ecosystem model resolution and initialization data quality have a large effect on flux predictions at continental scales. Here we use a factorial modeling experiment to quantify the impacts of model integration, process detail, model resolution, and initialization data on projections of future climate mitigation strategies. We find substantial effects on key integrated assessment projections including the magnitude of emissions to mitigate, the economic value of ecosystem carbon storage, future land-use patterns, food prices and energy technology.

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.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

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.

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.

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.

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.

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.

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.

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.

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...

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.

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.

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.

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.

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.

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.

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

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.

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.

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...

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.

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.

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.

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.

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.

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.

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.

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.

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

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...

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.

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.

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

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.

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.

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

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.

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.

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.

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.

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.

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.

Comparison of modeling approaches for carbon partitioning: Impact on estimates of global net primary production and equilibrium biomass of woody vegetation from MODIS GPP

NASA Astrophysics Data System (ADS)

Ise, Takeshi; Litton, Creighton M.; Giardina, Christian P.; Ito, Akihiko

2010-12-01

Partitioning of gross primary production (GPP) to aboveground versus belowground, to growth versus respiration, and to short versus long-lived tissues exerts a strong influence on ecosystem structure and function, with potentially large implications for the global carbon budget. A recent meta-analysis of forest ecosystems suggests that carbon partitioning to leaves, stems, and roots varies consistently with GPP and that the ratio of net primary production (NPP) to GPP is conservative across environmental gradients. To examine influences of carbon partitioning schemes employed by global ecosystem models, we used this meta-analysis-based model and a satellite-based (MODIS) terrestrial GPP data set to estimate global woody NPP and equilibrium biomass, and then compared it to two process-based ecosystem models (Biome-BGC and VISIT) using the same GPP data set. We hypothesized that different carbon partitioning schemes would result in large differences in global estimates of woody NPP and equilibrium biomass. Woody NPP estimated by Biome-BGC and VISIT was 25% and 29% higher than the meta-analysis-based model for boreal forests, with smaller differences in temperate and tropics. Global equilibrium woody biomass, calculated from model-specific NPP estimates and a single set of tissue turnover rates, was 48 and 226 Pg C higher for Biome-BGC and VISIT compared to the meta-analysis-based model, reflecting differences in carbon partitioning to structural versus metabolically active tissues. In summary, we found that different carbon partitioning schemes resulted in large variations in estimates of global woody carbon flux and storage, indicating that stand-level controls on carbon partitioning are not yet accurately represented in ecosystem 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.

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.

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.

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.

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

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

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.

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.

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...

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.

Quantifying the Global Nitrous Oxide Emissions Using a Trait-based Biogeochemistry Model

NASA Astrophysics Data System (ADS)

Zhuang, Q.; Yu, T.

2017-12-01

Nitrogen is an essential element for the global biogeochemical cycle. It is a key nutrient for organisms and N compounds including nitrous oxide significantly influence the global climate. The activities of bacteria and archaea are responsible for the nitrification and denitrification in a wide variety of environments, so microbes play an important role in the nitrogen cycle in soils. To date, most existing process-based models treated nitrification and denitrification as chemical reactions driven by soil physical variables including soil temperature and moisture. In general, the effect of microbes on N cycling has not been modeled in sufficient details. Soil organic carbon also affects the N cycle because it supplies energy to microbes. In my study, a trait-based biogeochemistry model quantifying N2O emissions from the terrestrial ecosystems is developed based on an extant process-based model TEM (Terrestrial Ecosystem Model). Specifically, the improvement to TEM includes: 1) Incorporating the N fixation process to account for the inflow of N from the atmosphere to biosphere; 2) Implementing the effects of microbial dynamics on nitrification process; 3) fully considering the effects of carbon cycling on N nitrogen cycling following the principles of stoichiometry of carbon and nitrogen in soils, plants, and microbes. The difference between simulations with and without the consideration of bacterial activity lies between 5% 25% based on climate conditions and vegetation types. The trait based module allows a more detailed estimation of global N2O emissions.

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...

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...

Process-based principles for restoring river ecosystems

Treesearch

Timothy J. Beechie; David A. Sear; Julian D. Olden; George R. Pess; John M. Buffington; Hamish Moir; Philip Roni; Michael M. Pollock

2010-01-01

Process-based restoration aims to reestablish normative rates and magnitudes of physical, chemical, and biological processes that sustain river and floodplain ecosystems. Ecosystem conditions at any site are governed by hierarchical regional, watershed, and reach-scale processes controlling hydrologic and sediment regimes; floodplain and aquatic habitat...

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.

[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.

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.

[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.

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.

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.

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 services as a common language for coastal ecosystem-based management.

PubMed

Granek, Elise F; Polasky, Stephen; Kappel, Carrie V; Reed, Denise J; Stoms, David M; Koch, Evamaria W; Kennedy, Chris J; Cramer, Lori A; Hacker, Sally D; Barbier, Edward B; Aswani, Shankar; Ruckelshaus, Mary; Perillo, Gerardo M E; Silliman, Brian R; Muthiga, Nyawira; Bael, David; Wolanski, Eric

2010-02-01

Ecosystem-based management is logistically and politically challenging because ecosystems are inherently complex and management decisions affect a multitude of groups. Coastal ecosystems, which lie at the interface between marine and terrestrial ecosystems and provide an array of ecosystem services to different groups, aptly illustrate these challenges. Successful ecosystem-based management of coastal ecosystems requires incorporating scientific information and the knowledge and views of interested parties into the decision-making process. Estimating the provision of ecosystem services under alternative management schemes offers a systematic way to incorporate biogeophysical and socioeconomic information and the views of individuals and groups in the policy and management process. Employing ecosystem services as a common language to improve the process of ecosystem-based management presents both benefits and difficulties. Benefits include a transparent method for assessing trade-offs associated with management alternatives, a common set of facts and common currency on which to base negotiations, and improved communication among groups with competing interests or differing worldviews. Yet challenges to this approach remain, including predicting how human interventions will affect ecosystems, how such changes will affect the provision of ecosystem services, and how changes in service provision will affect the welfare of different groups in society. In a case study from Puget Sound, Washington, we illustrate the potential of applying ecosystem services as a common language for ecosystem-based management.

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...

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.

Estimates of natural salinity and hydrology in a subtropical estuarine ecosystem: implications for Greater Everglades restoration

USGS Publications Warehouse

Marshall, Frank E.; Wingard, G. Lynn; Pitts, Patrick A.

2014-01-01

Disruption of the natural patterns of freshwater flow into estuarine ecosystems occurred in many locations around the world beginning in the twentieth century. To effectively restore these systems, establishing a pre-alteration perspective allows managers to develop science-based restoration targets for salinity and hydrology. This paper describes a process to develop targets based on natural hydrologic functions by coupling paleoecology and regression models using the subtropical Greater Everglades Ecosystem as an example. Paleoecological investigations characterize the circa 1900 CE (pre-alteration) salinity regime in Florida Bay based on molluscan remains in sediment cores. These paleosalinity estimates are converted into time series estimates of paleo-based salinity, stage, and flow using numeric and statistical models. Model outputs are weighted using the mean square error statistic and then combined. Results indicate that, in the absence of water management, salinity in Florida Bay would be about 3 to 9 salinity units lower than current conditions. To achieve this target, upstream freshwater levels must be about 0.25 m higher than indicated by recent observed data, with increased flow inputs to Florida Bay between 2.1 and 3.7 times existing flows. This flow deficit is comparable to the average volume of water currently being diverted from the Everglades ecosystem by water management. The products (paleo-based Florida Bay salinity and upstream hydrology) provide estimates of pre-alteration hydrology and salinity that represent target restoration conditions. This method can be applied to any estuarine ecosystem with available paleoecologic data and empirical and/or model-based hydrologic data.

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.

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).

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...

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.

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.

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,...

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.

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...

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.

[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.

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.

Modeling regeneration responses of big sagebrush (Artemisia tridentata) to abiotic conditions

USGS Publications Warehouse

Schlaepfer, Daniel R.; Lauenroth, William K.; Bradford, John B.

2014-01-01

Ecosystems dominated by big sagebrush, Artemisia tridentata Nuttall (Asteraceae), which are the most widespread ecosystems in semiarid western North America, have been affected by land use practices and invasive species. Loss of big sagebrush and the decline of associated species, such as greater sage-grouse, are a concern to land managers and conservationists. However, big sagebrush regeneration remains difficult to achieve by restoration and reclamation efforts and there is no regeneration simulation model available. We present here the first process-based, daily time-step, simulation model to predict yearly big sagebrush regeneration including relevant germination and seedling responses to abiotic factors. We estimated values, uncertainty, and importance of 27 model parameters using a total of 1435 site-years of observation. Our model explained 74% of variability of number of years with successful regeneration at 46 sites. It also achieved 60% overall accuracy predicting yearly regeneration success/failure. Our results identify specific future research needed to improve our understanding of big sagebrush regeneration, including data at the subspecies level and improved parameter estimates for start of seed dispersal, modified wet thermal-time model of germination, and soil water potential influences. We found that relationships between big sagebrush regeneration and climate conditions were site specific, varying across the distribution of big sagebrush. This indicates that statistical models based on climate are unsuitable for understanding range-wide regeneration patterns or for assessing the potential consequences of changing climate on sagebrush regeneration and underscores the value of this process-based model. We used our model to predict potential regeneration across the range of sagebrush ecosystems in the western United States, which confirmed that seedling survival is a limiting factor, whereas germination is not. Our results also suggested that modeled regeneration suitability is necessary but not sufficient to explain sagebrush presence. We conclude that future assessment of big sagebrush responses to climate change will need to account for responses of regenerative stages using a process-based understanding, such as provided by our model.

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.

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...

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.

Bottom-up assessment of the Net Ecosystem Carbon Balance of Russian forests in 2010 for comparison to Top-down estimates.

NASA Astrophysics Data System (ADS)

Maksyutov, S. S.; Shvidenko, A.; Shchepashchenko, D.

2014-12-01

The verified full carbon assessment of Russian forests (FCA) is based on an Integrated Land Information System (ILIS) that includes a multi-layer and multi-scale GIS with basic resolution of 1 km and corresponding attributive databases. The ILIS aggregates all available information about ecosystems and landscapes, sets of empirical and semi-empirical data and aggregations, data of different inventories and surveys, and multi-sensor remote sensing data. The ILIS serves as an information base for application of the landscape-ecosystem approach (LEA) of the FCA and as a systems design for comparison and mutual constraints with other methods of study of carbon cycling of forest ecosystems (eddy covariance; process models; inverse modeling; and multi-sensor application of remote sensing). The LEA is based on a complimentary use of the flux-based method with some elements of the pool-based method. Introduction of climatic parameters of individual years in the LEA, as well as some process-based elements, allows providing a substantial decrease of the uncertainties of carbon cycling yearly indicators of forest ecosystems. Major carbon pools (live biomass, coarse woody debris, soil organic carbon) are estimated based on data on areas, distribution and major biometric characteristics of Russian forests presented in form of the ILIS for the country. The major fluxes accounted for include Net Primary Production (NPP), Soil Heterotrophic Respiration (SHR), as well as fluxes caused by decomposition of Coarse Woody Debris (CWD), harvest and use of forest products, fluxes caused by natural disturbances (fire, insect outbreaks, impacts of unfavorable environment) and lateral fluxes to hydrosphere and lithosphere. Use of landscape-ecosystem approach resulted in the NECB at 573±140 Tg C yr-1 (CI 0.9). While the total carbon sink is high, large forest areas, particularly on permafrost, serve as a carbon source. The ratio between net primary production and soil heterotrophic respiration, together with natural and human-induced disturbances are major drivers of the magnitude and spatial distribution of the NECB of forest ecosystems. We also present comparison to the recent top-down estimates of the Siberian carbon sink.

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

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.

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.

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.

Carbon Budget and its Dynamics over Northern Eurasia Forest Ecosystems

NASA Astrophysics Data System (ADS)

Shvidenko, Anatoly; Schepaschenko, Dmitry; Kraxner, Florian; Maksyutov, Shamil

2016-04-01

The presentation contains an overview of recent findings and results of assessment of carbon cycling of forest ecosystems of Northern Eurasia. From a methodological point of view, there is a clear tendency in understanding a need of a Full and Verified Carbon Account (FCA), i.e. in reliable assessment of uncertainties for all modules and all stages of FCA. FCA is considered as a fuzzy (underspecified) system that supposes a system integration of major methods of carbon cycling study (land-ecosystem approach, LEA; process-based models; eddy covariance; and inverse modelling). Landscape-ecosystem approach 1) serves for accumulation of all relevant knowledge of landscape and ecosystems; 2) for strict systems designing the account, 3) contains all relevant spatially distributed empirical and semi-empirical data and models, and 4) is presented in form of an Integrated Land Information System (ILIS). The ILIS includes a hybrid land cover in a spatially and temporarily explicit way and corresponding attributive databases. The forest mask is provided by utilizing multi-sensor remote sensing data, geographically weighed regression and validation within GEO-wiki platform. By-pixel parametrization of forest cover is based on a special optimization algorithms using all available knowledge and information sources (data of forest inventory and different surveys, observations in situ, official statistics of forest management etc.). Major carbon fluxes within the LEA (NPP, HR, disturbances etc.) are estimated based on fusion of empirical data and aggregations with process-based elements by sets of regionally distributed models. Uncertainties within LEA are assessed for each module and at each step of the account. Within method results of LEA and corresponding uncertainties are harmonized and mutually constrained with independent outputs received by other methods based on the Bayesian approach. The above methodology have been applied to carbon account of Russian forests for 2000-2012. It has been shown that the Net Ecosystem Carbon Budget (NECB) of Russian forests for this period was in range of 0.5-0.7 Pg C yr-1 with a slight negative trend during the period due to acceleration of disturbance regimes and negative impacts of weather extremes (heat waves etc.). Uncertainties of the FCA for individual years were estimated at about 25% (CI 0.9). It has been shown that some models (e.g. majority of DGVMs) do not describe some processes on permafrost satisfactory while results of applications of ensembles of inverse models on average are closed to empirical assessments. A most important conclusion from this experience is that future improvements of knowledge of carbon cycling of Northern Eurasia forests requires development of an integrated observing system as a unified information background, as well as systems methodological improvements of all methods of cognition of carbon cycling.

Spatial Assessment of Forest Ecosystem Functions and Services using Human Relating Factors for SDG

NASA Astrophysics Data System (ADS)

Song, C.; Lee, W. K.; Jeon, S. W.; Kim, T.; Lim, C. H.

2015-12-01

Application of ecosystem service concept in environmental related decision making could be numerical and objective standard for policy maker between preserving and developing perspective of environment. However, pursuing maximum benefit from natural capital through ecosystem services caused failure by losing ecosystem functions through its trade-offs. Therefore, difference between ecosystem functions and services were demonstrated and would apply human relating perspectives. Assessment results of ecosystem functions and services can be divided 3 parts. Tree growth per year set as the ecosystem function factor and indicated through so called pure function map. After that, relating functions can be driven such as water conservation, air pollutant purification, climate change regulation, and timber production. Overall process and amount are numerically quantified. These functional results can be transferred to ecosystem services by multiplying economic unit value, so function reflecting service maps can be generated. On the other hand, above services, to implement more reliable human demand, human reflecting service maps are also be developed. As the validation, quantified ecosystem functions are compared with former results through pixel based analysis. Three maps are compared, and through comparing difference between ecosystem function and services and inversed trends in function based and human based service are analysed. In this study, we could find differences in PF, FRS, and HRS in relation to based ecosystem conditions. This study suggests that the differences in PF, FRS, and HRS should be understood in the decision making process for sustainable management of ecosystem services. Although the analysis is based on in sort existing process separation, it is important to consider the possibility of different usage of ecosystem function assessment results and ecosystem service assessment results in SDG policy making. Furthermore, process based functional approach can suggest environmental information which is reflected the other kinds of perspective.

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating.

PubMed

Lu, Xiaoman; Zheng, Guang; Miller, Colton; Alvarado, Ernesto

2017-09-08

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% ( n = 35, p < 0.05, RMSE = 2.20 kg/m²) and 85% ( n = 100, p < 0.01, RMSE = 1.71 kg/m²) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB.

Combining Multi-Source Remotely Sensed Data and a Process-Based Model for Forest Aboveground Biomass Updating

PubMed Central

Lu, Xiaoman; Zheng, Guang; Miller, Colton

2017-01-01

Monitoring and understanding the spatio-temporal variations of forest aboveground biomass (AGB) is a key basis to quantitatively assess the carbon sequestration capacity of a forest ecosystem. To map and update forest AGB in the Greater Khingan Mountains (GKM) of China, this work proposes a physical-based approach. Based on the baseline forest AGB from Landsat Enhanced Thematic Mapper Plus (ETM+) images in 2008, we dynamically updated the annual forest AGB from 2009 to 2012 by adding the annual AGB increment (ABI) obtained from the simulated daily and annual net primary productivity (NPP) using the Boreal Ecosystem Productivity Simulator (BEPS) model. The 2012 result was validated by both field- and aerial laser scanning (ALS)-based AGBs. The predicted forest AGB for 2012 estimated from the process-based model can explain 31% (n = 35, p < 0.05, RMSE = 2.20 kg/m2) and 85% (n = 100, p < 0.01, RMSE = 1.71 kg/m2) of variation in field- and ALS-based forest AGBs, respectively. However, due to the saturation of optical remote sensing-based spectral signals and contribution of understory vegetation, the BEPS-based AGB tended to underestimate/overestimate the AGB for dense/sparse forests. Generally, our results showed that the remotely sensed forest AGB estimates could serve as the initial carbon pool to parameterize the process-based model for NPP simulation, and the combination of the baseline forest AGB and BEPS model could effectively update the spatiotemporal distribution of forest AGB. PMID:28885556

Assessing Ecosystem Model Performance in Semiarid Systems

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-05-01

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

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.

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2009-12-01

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

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.

Two takes on the ecosystem impacts of climate change and fishing: Comparing a size-based and a species-based ecosystem model in the central North Pacific

NASA Astrophysics Data System (ADS)

Woodworth-Jefcoats, Phoebe A.; Polovina, Jeffrey J.; Howell, Evan A.; Blanchard, Julia L.

2015-11-01

We compare two ecosystem model projections of 21st century climate change and fishing impacts in the central North Pacific. Both a species-based and a size-based ecosystem modeling approach are examined. While both models project a decline in biomass across all sizes in response to climate change and a decline in large fish biomass in response to increased fishing mortality, the models vary significantly in their handling of climate and fishing scenarios. For example, based on the same climate forcing the species-based model projects a 15% decline in catch by the end of the century while the size-based model projects a 30% decline. Disparities in the models' output highlight the limitations of each approach by showing the influence model structure can have on model output. The aspects of bottom-up change to which each model is most sensitive appear linked to model structure, as does the propagation of interannual variability through the food web and the relative impact of combined top-down and bottom-up change. Incorporating integrated size- and species-based ecosystem modeling approaches into future ensemble studies may help separate the influence of model structure from robust projections of ecosystem change.

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.

Exploring Third-Grade Student Model-Based Explanations about Plant Relationships within an Ecosystem

NASA Astrophysics Data System (ADS)

Zangori, Laura; Forbes, Cory T.

2015-12-01

Elementary students should have opportunities to develop scientific models to reason and build understanding about how and why plants depend on relationships within an ecosystem for growth and survival. However, scientific modeling practices are rarely included within elementary science learning environments and disciplinary content is often treated as discrete pieces separate from scientific practice. Elementary students have few, if any, opportunities to reason about how individual organisms, such as plants, hold critical relationships with their surrounding environment. The purpose of this design-based research study is to build a learning performance to identify and explore the third-grade students' baseline understanding of and their reasoning about plant-ecosystem relationships when engaged in the practices of modeling. The developed learning performance integrated scientific content and core scientific activity to identify and measure how students build knowledge about the role of plants in ecosystems through the practices of modeling. Our findings indicate that the third-grade students' ideas about plant growth include abiotic and biotic relationships. Further, they used their models to reason about how and why these relationships were necessary to maintain plant stasis. However, while the majority of the third-grade students were able to identify and reason about plant-abiotic relationships, a much smaller group reasoned about plant-abiotic-animal relationships. Implications from the study suggest that modeling serves as a tool to support elementary students in reasoning about system relationships, but they require greater curricular and instructional support in conceptualizing how and why ecosystem relationships are necessary for plant growth and development. This paper is based on data from a doctoral dissertation. An earlier version of this paper was presented at the 2015 international conference for the National Association for Research in Science Teaching (NARST) Zangori, L., & Forbes, C. T. (2015). Exploring 3rd-grade student model-based explanations about plant process interactions within the hydrosphere Portions of this paper are based on that work.

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.

Placing biodiversity in ecosystem models without getting lost in translation

NASA Astrophysics Data System (ADS)

Queirós, Ana M.; Bruggeman, Jorn; Stephens, Nicholas; Artioli, Yuri; Butenschön, Momme; Blackford, Jeremy C.; Widdicombe, Stephen; Allen, J. Icarus; Somerfield, Paul J.

2015-04-01

A key challenge to progressing our understanding of biodiversity's role in the sustenance of ecosystem function is the extrapolation of the results of two decades of dedicated empirical research to regional, global and future landscapes. Ecosystem models provide a platform for this progression, potentially offering a holistic view of ecosystems where, guided by the mechanistic understanding of processes and their connection to the environment and biota, large-scale questions can be investigated. While the benefits of depicting biodiversity in such models are widely recognized, its application is limited by difficulties in the transfer of knowledge from small process oriented ecology into macro-scale modelling. Here, we build on previous work, breaking down key challenges of that knowledge transfer into a tangible framework, highlighting successful strategies that both modelling and ecology communities have developed to better interact with one another. We use a benthic and a pelagic case-study to illustrate how aspects of the links between biodiversity and ecosystem process have been depicted in marine ecosystem models (ERSEM and MIRO), from data, to conceptualisation and model development. We hope that this framework may help future interactions between biodiversity researchers and model developers by highlighting concrete solutions to common problems, and in this way contribute to the advance of the mechanistic understanding of the role of biodiversity in marine (and terrestrial) ecosystems.

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.

Modeling temperature and humidity profiles within forest canopies

USDA-ARS?s Scientific Manuscript database

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

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.

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.

Science-Based Strategies for Sustaining Coral Ecosystems

USGS Publications Warehouse

,

2009-01-01

Coral ecosystems and their natural capital are at risk. Greenhouse gas emissions, overfishing, and harmful land-use practices are damaging our coral reefs. Overwhelming scientific evidence indicates that the threats are serious, and if they are left unchecked, the ecological and social consequences will be significant and widespread. Although the primary stressors to coral ecosystems are known, science-based strategies are needed to more accurately explain natural processes and forecast human-induced change. Collaborations among managers and scientists and enhanced mapping, monitoring, research, and modeling can lead to effective mitigation plans. U.S. Geological Survey scientists and their partners assess coral ecosystem history, ecology, vulnerability, and resiliency and provide study results to decisionmakers who may devise policies to sustain coral resources and the essential goods and services they provide.

Integration of multispectral and SAR data for monitoring forest ecosystems recovery after fire

NASA Astrophysics Data System (ADS)

Stankova, Nataliya; Nedkov, Roumen; Ivanova, Iva; Avetisyan, Daniela

2017-09-01

The aim of this study is assessing the impacts and monitoring the condition and recovery processes of forest ecosystems after fire based on remote aerospace methods and data. To achieve this goal, satellite imagery in microwave and optical range of the spectrum were used. A hybrid model for assessing the instantaneous condition of forest ecosystems after fire that uses parallel data from optical and Synthetic Aperture Radar (SAR) was developed. Based on the three Tasseled Cap components (Brightness-BR, Greenness-GR and Wetness-W), a vector describing the current condition of the forest ecosystems was obtained and used as input data from the optical range. Results obtained by implementation of the proposed approach show that the integrated composite images of VIC and SAR represent the degree of recovery.

Multiscale analysis of restoration priorities for marine shoreline planning.

PubMed

Diefenderfer, Heida L; Sobocinski, Kathryn L; Thom, Ronald M; May, Christopher W; Borde, Amy B; Southard, Susan L; Vavrinec, John; Sather, Nichole K

2009-10-01

Planners are being called on to prioritize marine shorelines for conservation status and restoration action. This study documents an approach to determining the management strategy most likely to succeed based on current conditions at local and landscape scales. The conceptual framework based in restoration ecology pairs appropriate restoration strategies with sites based on the likelihood of producing long-term resilience given the condition of ecosystem structures and processes at three scales: the shorezone unit (site), the drift cell reach (nearshore marine landscape), and the watershed (terrestrial landscape). The analysis is structured by a conceptual ecosystem model that identifies anthropogenic impacts on targeted ecosystem functions. A scoring system, weighted by geomorphic class, is applied to available spatial data for indicators of stress and function using geographic information systems. This planning tool augments other approaches to prioritizing restoration, including historical conditions and change analysis and ecosystem valuation.

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.

Terrestrial Ecosystems of the Conterminous United States

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Cress, Jill; Warner, Harumi

2010-01-01

The U.S. Geological Survey (USGS), with support from NatureServe, has modeled the potential distribution of 419 terrestrial ecosystems for the conterminous United States using a comprehensive biophysical stratification approach that identifies distinct biophysical environments and associates them with known vegetation distributions (Sayre and others, 2009). This standardized ecosystem mapping effort used an ecosystems classification developed by NatureServe (Comer and others, 2003). The ecosystem mapping methodology was developed for South America (Sayre and others, 2008) and is now being implemented globally (Sayre and others, 2007). The biophysical stratification approach is based on mapping the major structural components of ecosystems (land surface forms, topographic moisture potential, surficial lithology, isobioclimates and biogeographic regions) and then spatially combining them to produce a set of unique biophysical environments. These physically distinct areas are considered as the fundamental structural units ('building blocks') of ecosystems, and are subsequently aggregated and labeled using the NatureServe classification. The structural footprints were developed from the geospatial union of several base layers including biogeographic regions, isobioclimates (Cress and others, 2009a), land surface forms (Cress and others, 2009b), topographic moisture potential (Cress and others, 2009c), and surficial lithology (Cress and others, in press). Among the 49,168 unique structural footprint classes that resulted from the union, 13,482 classes met a minimum pixel count threshold (20,000 pixels) and were aggregated into 419 NatureServe ecosystems using a semiautomated labeling process based on rule-set formulations for attribution of each ecosystem. The resulting ecosystems are those that are expected to occur based on the combination of the bioclimate, biogeography, and geomorphology. Where land use by humans has not altered land cover, natural vegetation assemblages are expected to occur, and these are described in the ecosystems classification. The map does not show the distribution of urban and agricultural areas - these will be masked out in subsequent analyses to depict the current land cover in addition to the potential distribution of natural ecosystems. This map depicts the smoothed and generalized image of the terrestrial ecosystems dataset. Additional information about this map and any data developed for the ecosystems modeling of the conterminous United States is available online at: http://rmgsc.cr.usgs.gov/ecosystems/.

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.

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Roedig, Edna; Cuntz, Matthias; Huth, Andreas

2015-04-01

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

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.

[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.

Sensitivity of alpine watersheds to global change

NASA Astrophysics Data System (ADS)

Zierl, B.; Bugmann, H.

2003-04-01

Mountains provide society with a wide range of goods and services, so-called mountain ecosystem services. Besides many others, these services include the most precious element for life on earth: fresh water. Global change imposes significant environmental pressure on mountain watersheds. Climate change is predicted to modify water availability as well as shift its seasonality. In fact, the continued capacity of mountain regions to provide fresh water to society is threatened by the impact of environmental and social changes. We use RHESSys (Regional HydroEcological Simulation System) to analyse the impact of climate as well as land use change (e.g. afforestation or deforestation) on hydrological processes in mountain catchments using sophisticated climate and land use scenarios. RHESSys combines distributed flow modelling based on TOPMODEL with an ecophysiological canopy model based on BIOME-BGC and a climate interpolation scheme based on MTCLIM. It is a spatially distributed daily time step model designed to solve the coupled cycles of water, carbon, and nitrogen in mountain catchments. The model is applied to various mountain catchments in the alpine area. Dynamic hydrological and ecological properties such as river discharge, seasonality of discharge, peak flows, snow cover processes, soil moisture, and the feedback of a changing biosphere on hydrology are simulated under current as well as under changed environmental conditions. Results of these studies will be presented and discussed. This project is part of an over overarching EU-project called ATEAM (acronym for Advanced Terrestrial Ecosystem Analysis and Modelling) assessing the vulnerability of European ecosystem services.

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.

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.

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.

Conceptual ecological models to guide integrated landscape monitoring of the Great Basin

USGS Publications Warehouse

Miller, D.M.; Finn, S.P.; Woodward, Andrea; Torregrosa, Alicia; Miller, M.E.; Bedford, D.R.; Brasher, A.M.

2010-01-01

The Great Basin Integrated Landscape Monitoring Pilot Project was developed in response to the need for a monitoring and predictive capability that addresses changes in broad landscapes and waterscapes. Human communities and needs are nested within landscapes formed by interactions among the hydrosphere, geosphere, and biosphere. Understanding the complex processes that shape landscapes and deriving ways to manage them sustainably while meeting human needs require sophisticated modeling and monitoring. This document summarizes current understanding of ecosystem structure and function for many of the ecosystems within the Great Basin using conceptual models. The conceptual ecosystem models identify key ecological components and processes, identify external drivers, develop a hierarchical set of models that address both site and landscape attributes, inform regional monitoring strategy, and identify critical gaps in our knowledge of ecosystem function. The report also illustrates an approach for temporal and spatial scaling from site-specific models to landscape models and for understanding cumulative effects. Eventually, conceptual models can provide a structure for designing monitoring programs, interpreting monitoring and other data, and assessing the accuracy of our understanding of ecosystem functions and processes.

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

NASA Astrophysics Data System (ADS)

Hotchkiss, E. R.

2017-12-01

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

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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.

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

PubMed

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

2016-02-01

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

. 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.

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.

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.

Modelling the role of fires in the terrestrial carbon balance by incorporating SPITFIRE into the global vegetation modelORCHIDEE - Part 1: Simulating historical global burned area and fire regimes

Treesearch

C. Yue; P. Ciais; P. Cadule; K. Thonicke; S. Archibald; B. Poulter; W. M. Hao; S. Hantson; F. Mouillot; P. Friedlingstein; F. Maignan; N. Viovy

2014-01-01

Fire is an important global ecological process that influences the distribution of biomes, with consequences for carbon, water, and energy budgets. Therefore it is impossible to appropriately model the history and future of the terrestrial ecosystems and the climate system without including fire. This study incorporates the process-based prognostic fire module SPITFIRE...

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

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.

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.

Evaluating the Potential of Southampton Carbon Flux Model (SCARF) for Monitoring Terrestrial Gross Primary Productivity Across African Ecosystems

NASA Astrophysics Data System (ADS)

Chiwara, P.; Dash, J.; Ardö, J.; Ogutu, B. O.; Milton, E. J.; Saunders, M. J.; Nicolini, G.

2016-12-01

Accurate knowledge about the amount and dynamics of terrestrial gross primary productivity is an important component for understanding of ecosystem functioning and processes. Recently a new diagnostic model, Southampton Carbon Flux (SCARF), was developed to predict terrestrial gross primary productivity at regional to global scale based on a chlorophyll index derived from MERIS data. The model aims at mitigating some shortcomings in traditional light-use-efficiency based models by (i) using the fraction of photosynthetic active radiation absorbed only by the photosynthetic components of the canopy (FAPARps) and (ii) using the intrinsic quantum yields of C3 and C4 photosynthesis thereby reducing errors from land cover misclassification. Initial evaluation of the model in northern higher latitude ecosystems shows good agreement with in situ measurements. The current study calibrated and validated the model for a diversity of vegetation types across Africa in order to test its performance over a water limiting environment. The validation was based on GPP measurements from seven eddy flux towers across Africa. Sensitivity and uncertainty analyses were also performed to determine the importance of key biophysical and meteorological input parameters.Overall, modelled GPP values show good agreement with in situ measured GPP at most sites except tropical rainforest site. Mean daily GPP varied significantly across sites depending on the vegetation types and climate; from a minimum of -0.12 gC m2 day-1 for the semi-arid savannah to a maximum of 7.30 gC m2 day-1 for tropical rain forest ecosystems at Ankasa (Ghana). The model results have modest to very strong positive agreement with observed GPP at most sites (R2 values ranging from 0.60 for Skukuza in South Africa) and 0.85 for Mongu in Zambia) except tropical rain forest ecosystem (R2=0.34). Overall, the model has a stronger across-site coefficient of determination (R2=0.78) than MOD17 GPP product (R2=0.68). PAR and VPD are the parameters that propagate much variation in model output at most sites especially in semi-arid and sub-humid ecosystems. The results demonstrate that the SCARF model can improve prediction of GPP across a wide range of African ecosystems..Key words: GPP, climate change, diagnostic model, photosynthetic quantum yield, C3/C4 photosynthesis

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.

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 role of climate in the global patterns of ecosystem carbon turnover rates - contrasts between data and models

NASA Astrophysics Data System (ADS)

Carvalhais, N.; Forkel, M.; Khomik, M.; Bellarby, J.; Migliavacca, M.; Thurner, M.; Beer, C.; Jung, M.; Mu, M.; Randerson, J. T.; Saatchi, S. S.; Santoro, M.; Reichstein, M.

2012-12-01

The turnover rates of carbon in terrestrial ecosystems and their sensitivity to climate are instrumental properties for diagnosing the interannual variability and forecasting trends of biogeochemical processes and carbon-cycle-climate feedbacks. We propose to globally look at the spatial distribution of turnover rates of carbon to explore the association between bioclimatic regimes and the rates at which carbon cycles in terrestrial ecosystems. Based on data-driven approaches of ecosystem carbon fluxes and data-based estimates of ecosystem carbon stocks it is possible to build fully observationally supported diagnostics. These data driven diagnostics support the benchmarking of CMIP5 model outputs (Coupled Model Intercomparison Project Phase 5) with observationally based estimates. The models' performance is addressed by confronting spatial patterns of carbon fluxes and stocks with data, as well as the global and regional sensitivities of turnover rates to climate. Our results show strong latitudinal gradients globally, mostly controlled by temperature, which are not always paralleled by CMIP5 simulations. In northern colder regions is also where the largest difference in temperature sensitivity between models and data occurs. Interestingly, there seem to be two different statistical populations in the data (some with high, others with low apparent temperature sensitivity of carbon turnover rates), where the different models only seem to describe either one or the other population. Additionally, the comparisons within bioclimatic classes can even show opposite patterns between turnover rates and temperature in water limited regions. Overall, our analysis emphasizes the role of finding patterns and intrinsic properties instead of plain magnitudes of fluxes for diagnosing the sensitivities of terrestrial biogeochemical cycles to climate. Further, our regional analysis suggests a significant gap in addressing the partial influence of water in the ecosystem carbon turnover rates especially in very cold or water limited regions.

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.

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.

Balancing trade-offs between ecosystem services in Germany’s forests under climate change

NASA Astrophysics Data System (ADS)

Gutsch, Martin; Lasch-Born, Petra; Kollas, Chris; Suckow, Felicitas; Reyer, Christopher P. O.

2018-04-01

Germany’s forests provide a variety of ecosystem services. Sustainable forest management aims to optimize the provision of these services at regional level. However, climate change will impact forest ecosystems and subsequently ecosystem services. The objective of this study is to quantify the effects of two alternative management scenarios and climate impacts on forest variables indicative of ecosystem services related to timber, habitat, water, and carbon. The ecosystem services are represented through nine model output variables (timber harvest, above and belowground biomass, net ecosystem production, soil carbon, percolation, nitrogen leaching, deadwood, tree dimension, broadleaf tree proportion) from the process-based forest model 4C. We simulated forest growth, carbon and water cycling until 2045 with 4C set-up for the whole German forest area based on National Forest Inventory data and driven by three management strategies (nature protection, biomass production and a baseline management) and an ensemble of regional climate scenarios (RCP2.6, RCP 4.5, RCP 8.5). We provide results as relative changes compared to the baseline management and observed climate. Forest management measures have the strongest effects on ecosystem services inducing positive or negative changes of up to 40% depending on the ecosystem service in question, whereas climate change only slightly alters ecosystem services averaged over the whole forest area. The ecosystem services ‘carbon’ and ‘timber’ benefit from climate change, while ‘water’ and ‘habitat’ lose. We detect clear trade-offs between ‘timber’ and all other ecosystem services, as well as synergies between ‘habitat’ and ‘carbon’. When evaluating all ecosystem services simultaneously, our results reveal certain interrelations between climate and management scenarios. North-eastern and western forest regions are more suitable to provide timber (while minimizing the negative impacts on remaining ecosystem services) whereas southern and central forest regions are more suitable to fulfil ‘habitat’ and ‘carbon’ services. The results provide the base for future forest management optimizations at the regional scale in order to maximize ecosystem services and forest ecosystem sustainability at the national scale.

APPLICATION OF AQUATOX, A PROCESS-BASED MODEL FOR ECOLOGICAL ASSESSMENT, TO CONTENTNEA CREEK IN NORTH CAROLINA

EPA Science Inventory

The aquatic ecosystem simulation model AQUATOX was parameterized and applied to Contentnea Creek in the coastal plain of North Carolina to determine the response of fish to moderate levels of physical and chemical habitat alterations. Biomass of four fish groups was most sensiti...

Agent-Based Phytoplankton Models of Cellular and Population Processes: Fostering Individual-Based Learning in Undergraduate Research

NASA Astrophysics Data System (ADS)

Berges, J. A.; Raphael, T.; Rafa Todd, C. S.; Bate, T. C.; Hellweger, F. L.

2016-02-01

Engaging undergraduate students in research projects that require expertise in multiple disciplines (e.g. cell biology, population ecology, and mathematical modeling) can be challenging because they have often not developed the expertise that allows them to participate at a satisfying level. Use of agent-based modeling can allow exploration of concepts at more intuitive levels, and encourage experimentation that emphasizes processes over computational skills. Over the past several years, we have involved undergraduate students in projects examining both ecological and cell biological aspects of aquatic microbial biology, using the freely-downloadable, agent-based modeling environment NetLogo (https://ccl.northwestern.edu/netlogo/). In Netlogo, actions of large numbers of individuals can be simulated, leading to complex systems with emergent behavior. The interface features appealing graphics, monitors, and control structures. In one example, a group of sophomores in a BioMathematics program developed an agent-based model of phytoplankton population dynamics in a pond ecosystem, motivated by observed macroscopic changes in cell numbers (due to growth and death), and driven by responses to irradiance, temperature and a limiting nutrient. In a second example, junior and senior undergraduates conducting Independent Studies created a model of the intracellular processes governing stress and cell death for individual phytoplankton cells (based on parameters derived from experiments using single-cell culturing and flow cytometry), and then this model was embedded in the agents in the pond ecosystem model. In our experience, students with a range of mathematical abilities learned to code quickly and could use the software with varying degrees of sophistication, for example, creation of spatially-explicit two and three-dimensional models. Skills developed quickly and transferred readily to other platforms (e.g. Matlab).

The Lagrangian Ensemble metamodel for simulating plankton ecosystems

NASA Astrophysics Data System (ADS)

Woods, J. D.

2005-10-01

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

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.

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.

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

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.

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.

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

PubMed

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

2017-01-01

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

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.

Process-Based Thinking in Ecosystem Education

ERIC Educational Resources Information Center

Jordan, Rebecca C.; Gray, Steven A.; Brooks, Wesley R.; Honwad, Sameer; Hmelo-Silver, Cindy E.

2013-01-01

Understanding complex systems such as ecosystems is difficult for young K-12 students, and students' representations of ecosystems are often limited to nebulously defined relationships between macro-level structural components inherent to the ecosystem in focus (rainforest, desert, pond, etc.) instead of generalizing processes across ecosystems…

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.

Porting marine ecosystem model spin-up using transport matrices to GPUs

NASA Astrophysics Data System (ADS)

Siewertsen, E.; Piwonski, J.; Slawig, T.

2013-01-01

We have ported an implementation of the spin-up for marine ecosystem models based on transport matrices to graphics processing units (GPUs). The original implementation was designed for distributed-memory architectures and uses the Portable, Extensible Toolkit for Scientific Computation (PETSc) library that is based on the Message Passing Interface (MPI) standard. The spin-up computes a steady seasonal cycle of ecosystem tracers with climatological ocean circulation data as forcing. Since the transport is linear with respect to the tracers, the resulting operator is represented by matrices. Each iteration of the spin-up involves two matrix-vector multiplications and the evaluation of the used biogeochemical model. The original code was written in C and Fortran. On the GPU, we use the Compute Unified Device Architecture (CUDA) standard, a customized version of PETSc and a commercial CUDA Fortran compiler. We describe the extensions to PETSc and the modifications of the original C and Fortran codes that had to be done. Here we make use of freely available libraries for the GPU. We analyze the computational effort of the main parts of the spin-up for two exemplar ecosystem models and compare the overall computational time to those necessary on different CPUs. The results show that a consumer GPU can compete with a significant number of cluster CPUs without further code optimization.

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

Treesearch

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

2010-01-01

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

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.

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

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.

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.

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.

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

PubMed

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

2012-02-01

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

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.

Impacts of alternative climate information on hydrologic processes with SWAT: A comparison of NCDC, PRISM and NEXRAD datasets

USDA-ARS?s Scientific Manuscript database

Precipitation and temperature are two primary drivers that significantly affect hydrologic processes in a watershed. A network of land-based National Climatic Data Center (NCDC) weather stations has been typically used as a primary source of climate input for agro-ecosystem models. However, the ne...

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...

Soil Functional Mapping: A Geospatial Framework for Scaling Soil Carbon Cycling

NASA Astrophysics Data System (ADS)

Lawrence, C. R.

2017-12-01

Climate change is dramatically altering biogeochemical cycles in most terrestrial ecosystems, particularly the cycles of water and carbon (C). These changes will affect myriad ecosystem processes of importance, including plant productivity, C exports to aquatic systems, and terrestrial C storage. Soil C storage represents a critical feedback to climate change as soils store more C than the atmosphere and aboveground plant biomass combined. While we know plant and soil C cycling are strongly coupled with soil moisture, substantial unknowns remain regarding how these relationships can be scaled up from soil profiles to ecosystems. This greatly limits our ability to build a process-based understanding of the controls on and consequences of climate change at regional scales. In an effort to address this limitation we: (1) describe an approach to classifying soils that is based on underlying differences in soil functional characteristics and (2) examine the utility of this approach as a scaling tool that honors the underlying soil processes. First, geospatial datasets are analyzed in the context of our current understanding of soil C and water cycling in order to predict soil functional units that can be mapped at the scale of ecosystems or watersheds. Next, the integrity of each soil functional unit is evaluated using available soil C data and mapping units are refined as needed. Finally, targeted sampling is conducted to further differentiate functional units or fill in any data gaps that are identified. Completion of this workflow provides new geospatial datasets that are based on specific soil functions, in this case the coupling of soil C and water cycling, and are well suited for integration with regional-scale soil models. Preliminary results from this effort highlight the advantages of a scaling approach that balances theory, measurement, and modeling.

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.

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

PubMed

Louca, Stilianos; Doebeli, Michael

2015-10-16

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

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.

From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health.

PubMed

Fock, Heino O; Kraus, Gerd

2016-01-01

Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR assessment for the southern North Sea showed, that with the selected 36 indicators 48% of ecosystem variability could be explained. Tools for the ex-ante branch are risk and ecosystem models with the capability to analyze trade-offs, generating model output for each of the pressure chains to allow for a phasing-out of human pressures. The Bayesian measure of ecosystem health is sensitive to trends in environmental features, but robust to ecosystem variability in line with state space models. The combination of the ex-ante and ex-post branch is essential to evaluate ecosystem resilience and to adopt adaptive management. Based on requirements of the heuristic approach, three possible developments of this concept can be envisioned, i.e. a governance driven approach built upon participatory processes, a science driven functional-holistic approach requiring extensive monitoring to analyze complete ecosystem variability, and an approach with emphasis on ex-ante modeling and ex-post assessment of well-studied subsystems.

From Metaphors to Formalism: A Heuristic Approach to Holistic Assessments of Ecosystem Health

PubMed Central

Kraus, Gerd

2016-01-01

Environmental policies employ metaphoric objectives such as ecosystem health, resilience and sustainable provision of ecosystem services, which influence corresponding sustainability assessments by means of normative settings such as assumptions on system description, indicator selection, aggregation of information and target setting. A heuristic approach is developed for sustainability assessments to avoid ambiguity and applications to the EU Marine Strategy Framework Directive (MSFD) and OSPAR assessments are presented. For MSFD, nineteen different assessment procedures have been proposed, but at present no agreed assessment procedure is available. The heuristic assessment framework is a functional-holistic approach comprising an ex-ante/ex-post assessment framework with specifically defined normative and systemic dimensions (EAEPNS). The outer normative dimension defines the ex-ante/ex-post framework, of which the latter branch delivers one measure of ecosystem health based on indicators and the former allows to account for the multi-dimensional nature of sustainability (social, economic, ecological) in terms of modeling approaches. For MSFD, the ex-ante/ex-post framework replaces the current distinction between assessments based on pressure and state descriptors. The ex-ante and the ex-post branch each comprise an inner normative and a systemic dimension. The inner normative dimension in the ex-post branch considers additive utility models and likelihood functions to standardize variables normalized with Bayesian modeling. Likelihood functions allow precautionary target setting. The ex-post systemic dimension considers a posteriori indicator selection by means of analysis of indicator space to avoid redundant indicator information as opposed to a priori indicator selection in deconstructive-structural approaches. Indicator information is expressed in terms of ecosystem variability by means of multivariate analysis procedures. The application to the OSPAR assessment for the southern North Sea showed, that with the selected 36 indicators 48% of ecosystem variability could be explained. Tools for the ex-ante branch are risk and ecosystem models with the capability to analyze trade-offs, generating model output for each of the pressure chains to allow for a phasing-out of human pressures. The Bayesian measure of ecosystem health is sensitive to trends in environmental features, but robust to ecosystem variability in line with state space models. The combination of the ex-ante and ex-post branch is essential to evaluate ecosystem resilience and to adopt adaptive management. Based on requirements of the heuristic approach, three possible developments of this concept can be envisioned, i.e. a governance driven approach built upon participatory processes, a science driven functional-holistic approach requiring extensive monitoring to analyze complete ecosystem variability, and an approach with emphasis on ex-ante modeling and ex-post assessment of well-studied subsystems. PMID:27509185

Using models in Integrated Ecosystem Assessment of coastal areas

NASA Astrophysics Data System (ADS)

Solidoro, Cosimo; Bandelj, Vinko; Cossarini, Gianpiero; Melaku Canu, Donata; Libralato, Simone

2014-05-01

Numerical Models can greatly contribute to integrated ecological assessment of coastal and marine systems. Indeed, models can: i) assist in the identification of efficient sampling strategy; ii) provide space interpolation and time extrapolation of experiemtanl data which are based on the knowedge on processes dynamics and causal realtionships which is coded within the model, iii) provide estimates of hardly measurable indicators. Furthermore model can provide indication on potential effects of implementation of alternative management policies. Finally, by providing a synthetic representation of an ideal system, based on its essential dynamic, model return a picture of ideal behaviour of a system in the absence of external perturbation, alteration, noise, which might help in the identification of reference behaivuor. As an important example, model based reanalyses of biogeochemical and ecological properties are an urgent need for the estimate of the environmental status and the assessment of efficacy of conservation and environmental policies, also with reference to the enforcement of the European MSFD. However, the use of numerical models, and particularly of ecological models, in modeling and in environmental management still is far from be the rule, possibly because of a lack in realizing the benefits which a full integration of modeling and montoring systems might provide, possibly because of a lack of trust in modeling results, or because many problems still exists in the development, validation and implementation of models. For istance, assessing the validity of model results is a complex process that requires the definition of appropriate indicators, metrics, methodologies and faces with the scarcity of real-time in-situ biogeochemical data. Furthermore, biogeochemical models typically consider dozens of variables which are heavily undersampled. Here we show how the integration of mathematical model and monitoring data can support integrated ecosystem assessment of a waterbody by reviewing applications from a complex coastal ecosystem, the Lagoon of Venice, and explore potential applications to other coastal and open sea system, up to the scale of the Mediterannean Sea.

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

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

Ecological forecasting is critical in various aspects of our coupled human-nature systems, such as disaster risk reduction, natural resource management and climate change mitigation. Novel advancements are in urgent need to deepen our understandings of ecosystem dynamics, boost the predictive capacity of ecology, and provide timely and effective information for decision-makers in a rapidly changing world. Our Ecological Platform for Assimilation of Data (EcoPAD) facilitates the integration of current best knowledge from models, manipulative experimentations, observations and other modern techniques and provides both near real-time and long-term forecasting of ecosystem dynamics. As a case study, the web-based EcoPAD platform synchronizes real- or near real-time field measurements from the Spruce and Peatland Responses Under Climatic and Environmental Change Experiment (SPRUCE), a whole ecosystem warming and CO2 enrichment treatment experiment, assimilates multiple data streams into process based models, enhances timely feedback between modelers and experimenters, and ultimately improves ecosystem forecasting and makes best utilization of current knowledge. In addition to enable users to (i) estimate model parameters or state variables, (ii) quantify uncertainty of estimated parameters and projected states of ecosystems, (iii) evaluate model structures, (iv) assess sampling strategies, and (v) conduct ecological forecasting, EcoPAD-SPRUCE automated the workflow from real-time data acquisition, model simulation to result visualization. EcoPAD-SPRUCE promotes seamless feedback between modelers and experimenters, hand in hand to make better forecasting of future changes. The framework of EcoPAD-SPRUCE (with flexible API, Application Programming Interface) is easily portable and will benefit scientific communities, policy makers as well as the general public.

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.

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.

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.

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.

Integration of Long term experiments on terrestrial ecosystem in AnaEE-France Research Infrastructure : concept and adding value

NASA Astrophysics Data System (ADS)

Chanzy, André; Chabbi, Abad; Houot, Sabine; Lafolie, François; Pichot, Christian; Raynal, Hélène; Saint-André, Laurent; Clobert, Jean; Greiveldinger, Lucile

2015-04-01

Continental ecosystems represent a critical zone that provide key ecological services to human populations like biomass production, that participate to the regulation of the global biogeochemical cycles and contribute and contribute to the maintenance of air and water quality. Global changes effects on continental ecosystems are likely to impact the fate of humanity, which is thus facing numerous challenges, such as an increasing demand for food and energy, competition for land and water use, or rapid climate warming. Hence, scientific progress in our understanding of the continental critical zone will come from studies that address how biotic and abiotic processes react to global changes. Long term experiments are required to take into account ecosystem inertia and feedback loops and to characterize trends and threshold in ecosystem dynamics. In France, 20 long-term experiments on terrestrial ecosystems are gathered within a single Research Infrastructure: ANAEE-France (http://www.anaee-s.fr), which is a part of AnaEE-Europe (http://www.anaee.com/). Each experiment consist in applying differentiated pressures on different plot over a long period (>20 years) representative of a range of management options. The originality of such infrastructure is a combination of experimental set up and long-term monitoring of simultaneous measurements of key ecosystem variables and parameters through a multi-disciplinary approach and replications of each treatment that improve the statistical strength of the results. The sites encompass gradients of climate conditions, ecosystem complexity and/or management, and can be used for calibration/validation of ecosystem functioning models as well as for the design of ecosystem management strategies. Gathering those experiments in a single research infrastructure is an important issue to enhance their visibility and increase the number of hosting scientific team by offering a range of services. These are: • Access to the ongoing long term experiments to implement novel observational systems. Through active collaboration with the teams in charge of the experiments, users will take advantage of the site characterization, historical data, monitoring setup and access to different treatments experimental field with differentiated properties induced by repeated treatment. • Access to soil and vegetation samples collected at different dates that may be reanalyzed a posteriori to take profit of technological progress. • Delivery of reference data on ecosystems subjected to a gradient of anthropogenic and climatic pressures. The research infrastructure level is appropriate to implement a harmonization policy for the measurement and observation protocols. Moreover it offers the possibility of developing an ambitious strategy in integrating data and models. These can contribute to the experimental process for protocol design or data quality control. Moreover, they offer an efficient way for promoting data reuse thus giving a strong added value to the existing data bases. Therefore, building interoperability between models and experimental platform data bases is an important objective to improve the quality of experimental infrastructure and provide users with seamless and integrated information systems. We present how this is operated in AnaEE-France with different tasks as the development of a controlled vocabulary, tools to annotate data and model variables with metadata based on ontologies and the development of webservice to harvest data from the data base to the modelling platform environment. Finally some examples of key results taking profit of the range of experiments are provided.

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.

How to Make Our Models More Physically-based

NASA Astrophysics Data System (ADS)

Savenije, H. H. G.

2016-12-01

Models that are generally called "physically-based" unfortunately only have a partial view of the physical processes at play in hydrology. Although the coupled partial differential equations in these models reflect the water balance equations and the flow descriptors at laboratory scale, they miss essential characteristics of what determines the functioning of catchments. The most important active agent in catchments is the ecosystem (and sometimes people). What these agents do is manipulate the substrate in a way that it supports the essential functions of survival and productivity: infiltration of water, retention of moisture, mobilization and retention of nutrients, and drainage. Ecosystems do this in the most efficient way, in agreement with the landscape, and in response to climatic drivers. In brief, our hydrological system is alive and has a strong capacity to adjust to prevailing and changing circumstances. Although most physically based models take Newtonian theory at heart, as best they can, what they generally miss is Darwinian thinking on how an ecosystem evolves and adjusts its environment to maintain crucial hydrological functions. If this active agent is not reflected in our models, then they miss essential physics. Through a Darwinian approach, we can determine the root zone storage capacity of ecosystems, as a crucial component of hydrological models, determining the partitioning of fluxes and the conservation of moisture to bridge periods of drought. Another crucial element of physical systems is the evolution of drainage patterns, both on and below the surface. On the surface, such patterns facilitate infiltration or surface drainage with minimal erosion; in the unsaturated zone, patterns facilitate efficient replenishment of moisture deficits and preferential drainage when there is excess moisture; in the groundwater, patterns facilitate the efficient and gradual drainage of groundwater, resulting in linear reservoir recession. Models that do not incorporate these patterns are not physical. The parameters in the equations may be adjusted to compensate for the lake of patterns, but this involves scale-dependent calibration. In contrast to what is widely believed, relatively simple conceptual models can accommodate these physical processes accurately and very efficiently.

Thresholds of understanding: Exploring assumptions of scale invariance vs. scale dependence in global biogeochemical models

NASA Astrophysics Data System (ADS)

Wieder, W. R.; Bradford, M.; Koven, C.; Talbot, J. M.; Wood, S.; Chadwick, O.

2016-12-01

High uncertainty and low confidence in terrestrial carbon (C) cycle projections reflect the incomplete understanding of how best to represent biologically-driven C cycle processes at global scales. Ecosystem theories, and consequently biogeochemical models, are based on the assumption that different belowground communities function similarly and interact with the abiotic environment in consistent ways. This assumption of "Scale Invariance" posits that environmental conditions will change the rate of ecosystem processes, but the biotic response will be consistent across sites. Indeed, cross-site comparisons and global-scale analyses suggest that climate strongly controls rates of litter mass loss and soil organic matter turnover. Alternatively, activities of belowground communities are shaped by particular local environmental conditions, such as climate and edaphic conditions. Under this assumption of "Scale Dependence", relationships generated by evolutionary trade-offs in acquiring resources and withstanding environmental stress dictate the activities of belowground communities and their functional response to environmental change. Similarly, local edaphic conditions (e.g. permafrost soils or reactive minerals that physicochemically stabilize soil organic matter on mineral surfaces) may strongly constrain the availability of substrates that biota decompose—altering the trajectory of soil biogeochemical response to perturbations. Identifying when scale invariant assumptions hold vs. where local variation in biotic communities or edaphic conditions must be considered is critical to advancing our understanding and representation of belowground processes in the face of environmental change. Here we introduce data sets that support assumptions of scale invariance and scale dependent processes and discuss their application in global-scale biogeochemical models. We identify particular domains over which assumptions of scale invariance may be appropriate and potential thresholds where shifts in ecosystem function may be expected. Finally, we discuss the mechanistic insight that can be applied in process-based models and datasets that can evaluate models across spatial and temporal scales.

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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.

Modeling greenhouse gas emissions and nutrient transport in managed arable soils with a fully coupled hydrology-biogeochemical modeling system

NASA Astrophysics Data System (ADS)

Haas, Edwin; Klatt, Steffen; Kiese, Ralf; Butterbach-Bahl, Klaus; Kraft, Philipp; Breuer, Lutz

2015-04-01

The use of mineral nitrogen fertilizer sustains the global food production and therefore the livelihood of human kind. The rise in world population will put pressure on the global agricultural system to increase its productivity leading most likely to an intensification of mineral nitrogen fertilizer use. The fate of excess nitrogen and its distribution within landscapes is manifold. Process knowledge on the site scale has rapidly grown in recent years and models have been developed to simulate carbon and nitrogen cycling in managed ecosystems on the site scale. Despite first regional studies, the carbon and nitrogen cycling on the landscape or catchment scale is not fully understood. In this study we present a newly developed modelling approach by coupling the fully distributed hydrology model CMF (catchment modelling framework) to the process based regional ecosystem model LandscapeDNDC for the investigation of hydrological processes and carbon and nitrogen transport and cycling, with a focus on nutrient displacement and resulting greenhouse gas emissions in various virtual landscapes / catchment to demonstrate the capabilities of the modelling system. The modelling system was applied to simulate water and nutrient transport at the at the Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan province, China. The catchment hosts cypress forests on the outer regions, arable fields on the sloping croplands cultivated with wheat-maize rotations and paddy rice fields in the lowland. The catchment consists of 300 polygons vertically stratified into 10 soil layers. Ecosystem states (soil water content and nutrients) and fluxes (evapotranspiration) are exchanged between the models at high temporal scales (hourly to daily) forming a 3-dimensional model application. The water flux and nutrients transport in the soil is modelled using a 3D Richards/Darcy approach for subsurface fluxes with a kinematic wave approach for surface water runoff and the evapotranspiration is based on Penman-Monteith. Biogeochemical processes are modelled by LandscapeDNDC, including soil microclimate, plant growth and biomass allocation, organic matter mineralisation, nitrification, denitrification, chemodenitrification and methanogenesis producing and consuming soil based greenhouse gases. The model application will present first results of the coupled model to simulate soil based greenhouse gas emissions as well as nitrate discharge from the Yanting catchment. The model application will also present the effects of different management practices (fertilization rates and timings, tilling, residues management) on the redistribution of N surplus within the catchment causing biomass productivity gradients and different levels of indirect N2O emissions along topographical gradients.

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.

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.

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.

Animal movement: Statistical models for telemetry data

USGS Publications Warehouse

Hooten, Mevin B.; Johnson, Devin S.; McClintock, Brett T.; Morales, Juan M.

2017-01-01

The study of animal movement has always been a key element in ecological science, because it is inherently linked to critical processes that scale from individuals to populations and communities to ecosystems. Rapid improvements in biotelemetry data collection and processing technology have given rise to a variety of statistical methods for characterizing animal movement. The book serves as a comprehensive reference for the types of statistical models used to study individual-based animal movement. 

Parameterisation of Biome BGC to assess forest ecosystems in Africa

NASA Astrophysics Data System (ADS)

Gautam, Sishir; Pietsch, Stephan A.

2010-05-01

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

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.

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...

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

PubMed Central

De Kauwe, Martin G; Medlyn, Belinda E; Zaehle, Sönke; Walker, Anthony P; Dietze, Michael C; Wang, Ying-Ping; Luo, Yiqi; Jain, Atul K; El-Masri, Bassil; Hickler, Thomas; Wårlind, David; Weng, Ensheng; Parton, William J; Thornton, Peter E; Wang, Shusen; Prentice, I Colin; Asao, Shinichi; Smith, Benjamin; McCarthy, Heather R; Iversen, Colleen M; Hanson, Paul J; Warren, Jeffrey M; Oren, Ram; Norby, Richard J

2014-01-01

Elevated atmospheric CO2 concentration (eCO2) has the potential to increase vegetation carbon storage if increased net primary production causes increased long-lived biomass. Model predictions of eCO2 effects on vegetation carbon storage depend on how allocation and turnover processes are represented. We used data from two temperate forest free-air CO2 enrichment (FACE) experiments to evaluate representations of allocation and turnover in 11 ecosystem models. Observed eCO2 effects on allocation were dynamic. Allocation schemes based on functional relationships among biomass fractions that vary with resource availability were best able to capture the general features of the observations. Allocation schemes based on constant fractions or resource limitations performed less well, with some models having unintended outcomes. Few models represent turnover processes mechanistically and there was wide variation in predictions of tissue lifespan. Consequently, models did not perform well at predicting eCO2 effects on vegetation carbon storage. Our recommendations to reduce uncertainty include: use of allocation schemes constrained by biomass fractions; careful testing of allocation schemes; and synthesis of allocation and turnover data in terms of model parameters. Data from intensively studied ecosystem manipulation experiments are invaluable for constraining models and we recommend that such experiments should attempt to fully quantify carbon, water and nutrient budgets. PMID:24844873

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.

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.

Assessment of watershed scale nitrogen cycling and dynamics by hydrochemical modeling

NASA Astrophysics Data System (ADS)

Onishi, T.; Hiramatsu, K.; Somura, H.

2017-12-01

Nitrogen cycling in terrestrial areas is affecting water quality and ecosystem of aquatic area such as lakes and oceans through rivers. Owing to the intensive researches on nitrogen cycling in each different type of ecosystem, we acquired rich knowledge on nitrogen cycling of each ecosystem. On the other hand, since watershed are composed of many different kinds of ecosystems, nitrogen cycling in a watershed as a complex of these ecosystems is not well quantified. Thus, comprehensive understanding of nitrogen cycling of watersheds by modelling efforts are required. In this study, we attempted to construct hydrochemical model of the Ise Bay watershed to reproduce discharge, TN, and NO3 concentration. The model is based on SWAT (Soil and Water Assessment Tools) model. As anthropogenic impacts related to both hydrological cycling and nitrogen cycling, agricultural water intake/drainage, and domestic water intake/drainage were considered. In addition, fertilizer input to agricultural lands were also considered. Calibration period and validation period are 2004-2006, and 2007-2009, respectively. As a result of calibration using 2000 times LCS (Latin Cubic Sampling) method, discharge of rivers were reproduced fairly well with NS of 0.6-0.8. In contrast, the calibration result of TN and NO3 concentration tended to show overestimate values in spite of considering parameter uncertainties. This implies that unimplemented denitrification processes in the model. Through exploring the results, it is indicated that riparian areas, and agricultural drainages might be important spots for denitrification. Based on the result, we also attempted to evaluate the impact of climate change on nitrogen cycling. Though it is fully explored, this result will also be reported.

Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

USGS Publications Warehouse

Forcada, J.; Malone, D.; Royle, J. Andrew; Staniland, I.J.

2009-01-01

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90-125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12-16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the "escapement" due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management. ?? 2009 Elsevier B.V.

Modelling predation by transient leopard seals for an ecosystem-based management of Southern Ocean fisheries

USGS Publications Warehouse

Forcada, J.; Royle, J. Andrew; Staniland, I.J.

2009-01-01

Correctly quantifying the impacts of rare apex marine predators is essential to ecosystem-based approaches to fisheries management, where harvesting must be sustainable for targeted species and their dependent predators. This requires modelling the uncertainty in such processes as predator life history, seasonal abundance and movement, size-based predation, energetic requirements, and prey vulnerability. We combined these uncertainties to evaluate the predatory impact of transient leopard seals on a community of mesopredators (seals and penguins) and their prey at South Georgia, and assess the implications for an ecosystem-based management. The mesopredators are highly dependent on Antarctic krill and icefish, which are targeted by regional fisheries. We used a state-space formulation to combine (1) a mark-recapture open-population model and individual identification data to assess seasonally variable leopard seal arrival and departure dates, numbers, and residency times; (2) a size-based bioenergetic model; and (3) a size-based prey choice model from a diet analysis. Our models indicated that prey choice and consumption reflected seasonal changes in leopard seal population size and structure, size-selective predation and prey vulnerability. A population of 104 (90?125) leopard seals, of which 64% were juveniles, consumed less than 2% of the Antarctic fur seal pup production of the area (50% of total ingested energy, IE), but ca. 12?16% of the local gentoo penguin population (20% IE). Antarctic krill (28% IE) were the only observed food of leopard seal pups and supplemented the diet of older individuals. Direct impacts on krill and fish were negligible, but the ?escapement? due to leopard seal predation on fur seal pups and penguins could be significant for the mackerel icefish fishery at South Georgia. These results suggest that: (1) rare apex predators like leopard seals may control, and may depend on, populations of mesopredators dependent on prey species targeted by fisheries; and (2) predatory impacts and community control may vary throughout the predator's geographic range, and differ across ecosystems and management areas, depending on the seasonal abundance of the prey and the predator's dispersal movements. This understanding is important to integrate the predator needs as natural mortality of its prey in models to set prey catch limits for fisheries. Reliable estimates of the variability of these needs are essential for a precautionary interpretation in the context of an ecosystem-based management.

Modeling greenhouse gas emissions (CO2, N2O, CH4) from managed arable soils with a fully coupled hydrology-biogeochemical modeling system simulating water and nutrient transport and associated carbon and nitrogen cycling at catchment scale

NASA Astrophysics Data System (ADS)

Klatt, Steffen; Haas, Edwin; Kraus, David; Kiese, Ralf; Butterbach-Bahl, Klaus; Kraft, Philipp; Plesca, Ina; Breuer, Lutz; Zhu, Bo; Zhou, Minghua; Zhang, Wei; Zheng, Xunhua; Wlotzka, Martin; Heuveline, Vincent

2014-05-01

The use of mineral nitrogen fertilizer sustains the global food production and therefore the livelihood of human kind. The rise in world population will put pressure on the global agricultural system to increase its productivity leading most likely to an intensification of mineral nitrogen fertilizer use. The fate of excess nitrogen and its distribution within landscapes is manifold. Process knowledge on the site scale has rapidly grown in recent years and models have been developed to simulate carbon and nitrogen cycling in managed ecosystems on the site scale. Despite first regional studies, the carbon and nitrogen cycling on the landscape or catchment scale is not fully understood. In this study we present a newly developed modelling approach by coupling the fully distributed hydrology model CMF (catchment modelling framework) to the process based regional ecosystem model LandscapeDNDC for the investigation of hydrological processes and carbon and nitrogen transport and cycling, with a focus on nutrient displacement and resulting greenhouse gas emissions in a small catchment at the Yanting Agro-ecological Experimental Station of Purple Soil, Sichuan province, China. The catchment hosts cypress forests on the outer regions, arable fields on the sloping croplands cultivated with wheat-maize rotations and paddy rice fields in the lowland. The catchment consists of 300 polygons vertically stratified into 10 soil layers. Ecosystem states (soil water content and nutrients) and fluxes (evapotranspiration) are exchanged between the models at high temporal scales (hourly to daily) forming a 3-dimensional model application. The water flux and nutrients transport in the soil is modelled using a 3D Richards/Darcy approach for subsurface fluxes with a kinematic wave approach for surface water runoff and the evapotranspiration is based on Penman-Monteith. Biogeochemical processes are modelled by LandscapeDNDC, including soil microclimate, plant growth and biomass allocation, organic matter mineralisation, nitrification, denitrification, chemodenitrification and methanogenesis producing and consuming soil based greenhouse gases. The model application will present first validation results of the coupled model to simulate soil based greenhouse gas emissions as well as nitrate discharge from the Yanting catchment. The model application will also present the effects of different management practices (fertilization rates and timings, tilling, residues management) on the redistribution of N surplus within the catchment causing biomass productivity gradients and different levels of indirect N2O emissions along topographical gradients.

Quantitative food web analysis supports the energy-limitation hypothesis in cave stream ecosystems.

PubMed

Venarsky, Michael P; Huntsman, Brock M; Huryn, Alexander D; Benstead, Jonathan P; Kuhajda, Bernard R

2014-11-01

Energy limitation has long been the primary assumption underlying conceptual models of evolutionary and ecological processes in cave ecosystems. However, the prediction that cave communities are actually energy-limited in the sense that constituent populations are consuming all or most of their resource supply is untested. We assessed the energy-limitation hypothesis in three cave streams in northeastern Alabama (USA) by combining measurements of animal production, demand, and resource supplies (detritus, primarily decomposing wood particles). Comparisons of animal consumption and detritus supply rates in each cave showed that all, or nearly all, available detritus was required to support macroinvertebrate production. Furthermore, only a small amount of macroinvertebrate prey production remained to support other predatory taxa (i.e., cave fish and salamanders) after accounting for crayfish consumption. Placing the energy demands of a cave community within the context of resource supply rates provided quantitative support for the energy-limitation hypothesis, confirming the mechanism (limited energy surpluses) that likely influences the evolutionary processes and population dynamics that shape cave communities. Detritus-based surface ecosystems often have large detrital surpluses. Thus, cave ecosystems, which show minimal surpluses, occupy the extreme oligotrophic end of the spectrum of detritus-based food webs.

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.

The EBM-DPSER Conceptual Model: Integrating Ecosystem Services into the DPSIR Framework

PubMed Central

Kelble, Christopher R.; Loomis, Dave K.; Lovelace, Susan; Nuttle, William K.; Ortner, Peter B.; Fletcher, Pamela; Cook, Geoffrey S.; Lorenz, Jerry J.; Boyer, Joseph N.

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers. PMID:23951002

The EBM-DPSER conceptual model: integrating ecosystem services into the DPSIR framework.

PubMed

Kelble, Christopher R; Loomis, Dave K; Lovelace, Susan; Nuttle, William K; Ortner, Peter B; Fletcher, Pamela; Cook, Geoffrey S; Lorenz, Jerry J; Boyer, Joseph N

2013-01-01

There is a pressing need to integrate biophysical and human dimensions science to better inform holistic ecosystem management supporting the transition from single species or single-sector management to multi-sector ecosystem-based management. Ecosystem-based management should focus upon ecosystem services, since they reflect societal goals, values, desires, and benefits. The inclusion of ecosystem services into holistic management strategies improves management by better capturing the diversity of positive and negative human-natural interactions and making explicit the benefits to society. To facilitate this inclusion, we propose a conceptual model that merges the broadly applied Driver, Pressure, State, Impact, and Response (DPSIR) conceptual model with ecosystem services yielding a Driver, Pressure, State, Ecosystem service, and Response (EBM-DPSER) conceptual model. The impact module in traditional DPSIR models focuses attention upon negative anthropomorphic impacts on the ecosystem; by replacing impacts with ecosystem services the EBM-DPSER model incorporates not only negative, but also positive changes in the ecosystem. Responses occur as a result of changes in ecosystem services and include inter alia management actions directed at proactively altering human population or individual behavior and infrastructure to meet societal goals. The EBM-DPSER conceptual model was applied to the Florida Keys and Dry Tortugas marine ecosystem as a case study to illustrate how it can inform management decisions. This case study captures our system-level understanding and results in a more holistic representation of ecosystem and human society interactions, thus improving our ability to identify trade-offs. The EBM-DPSER model should be a useful operational tool for implementing EBM, in that it fully integrates our knowledge of all ecosystem components while focusing management attention upon those aspects of the ecosystem most important to human society and does so within a framework already familiar to resource managers.

From Process Understanding Via Soil Functions to Sustainable Soil Management - A Systemic Approach

NASA Astrophysics Data System (ADS)

Wollschlaeger, U.; Bartke, S.; Bartkowski, B.; Daedlow, K.; Helming, K.; Kogel-Knabner, I.; Lang, B.; Rabot, E.; Russell, D.; Stößel, B.; Weller, U.; Wiesmeier, M.; Rabot, E.; Vogel, H. J.

2017-12-01

Fertile soils are central resources for the production of biomass and the provision of food and energy. A growing world population and latest climate targets lead to an increasing demand for both, food and bio-energy, which requires preserving and improving the long-term productivity of soils as a bio-economic resource. At the same time, other soil functions and ecosystem services need to be maintained: filter for clean water, carbon sequestration, provision and recycling of nutrients, and habitat for biological activity. All these soil functions result from the interaction of a multitude of physical, chemical and biological processes that are not yet sufficiently understood. In addition, we lack understanding about the interplay between the socio-economic system and the soil system and how soil functions benefit human wellbeing. Hence, a solid and integrated assessment of soil quality requires the consideration of the ensemble of soil functions and its relation to soil management to finally be able to develop site-specific options for sustainable soil management. We present an integrated modeling approach that investigates the influence of soil management on the ensemble of soil functions. It is based on the mechanistic relationships between soil functional attributes, each explained by a network of interacting processes as derived from scientific evidence. As the evidence base required for feeding the model is for the most part stored in the existing scientific literature, another central component of our work is to set up a public "knowledge-portal" providing the infrastructure for a community effort towards a comprehensive knowledge base on soil processes as a basis for model developments. The connection to the socio-economic system is established using the Drivers-Pressures-Impacts-States-Responses (DPSIR) framework where our improved understanding about soil ecosystem processes is linked to ecosystem services and resource efficiency via the soil functions.

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...

Calibration of two complex ecosystem models with different likelihood functions

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Simulating Forest Dynamics of Lowland Rainforests in Eastern Madagascar

NASA Technical Reports Server (NTRS)

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

2018-01-01

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

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.

Freshwater as shared between society and ecosystems: from divided approaches to integrated challenges.

PubMed

Falkenmark, Malin

2003-12-29

The paper has its focus on water's key functions behind ecosystem dynamics and the water-related balancing involved in a catchment-based ecosystem approach. A conceptual framework is being developed to address fundamental trade-offs between humans and ecosystems. This is done by paying attention to society's unavoidable landscape modifications and their unavoidable ecological effects mediated by water processes. Because the coevolution of societal and environmental processes indicates resonance rather than a cause-effect relationship, humanity will have to learn to live with change while securing ecosystem resilience. In view of the partial incompatibility of the social imperative of the millennium goals and its environmental sustainability goal, human activities and ecosystems have to be orchestrated for compatibility. To this end a catchment-based approach has to be taken by integrating water, land use and ecosystems. It is being suggested that ecosystem protection has to be thought of in two scales: site-specific biotic landscape components to be protected for their social value, and a catchment-based ecosystem approach to secure sustainable supply of crucial ecosystem goods and services on which social and economic development depends.

Evaluation of dielectric mixing models for microwave soil moisture retrieval using data from the Combined Radar/Radiometer (ComRAD) ground-based SMAP simulator

USDA-ARS?s Scientific Manuscript database

Soil moisture measurements are required to improve our understanding of hydrological processes, ecosystem functions, and linkages between the Earth’s water, energy, and carbon cycles. The efficient retrieval of soil moisture depends on various factors in which soil dielectric mixing models are consi...

Interactions and feedbacks among phytobenthos, hydrodynamics, nutrient cycling and sediment transport in estuarine ecosystems

NASA Astrophysics Data System (ADS)

Bergamasco, A.; De Nat, L.; Flindt, M. R.; Amos, C. L.

2003-11-01

Phytobenthic communities can play an active role in modifying the environmental characteristics of the ecosystem in which they live so mediating the human impact on Coastal Zone habitats. Complicated feedbacks couple the establishment of phytobenthic communities with water quality and physical parameters in estuaries. Direct and indirect interactions between physical and biological attributes need to be considered in order to improve the management of these ecosystems to guarantee a sustainable use of coastal resources. Within the project F-ECTS ("Feedbacks of Estuarine Circulation and Transport of Sediments on phytobenthos") this issue was approached through a three-step strategy: (i) Monitoring: detailed fieldwork activities focusing on the measurement and evaluation of the main processes involving hydrodynamics, sediments, nutrients, light and phytobenthic biomass; (ii) Modeling: joint modeling of the suspended particulate matter erosion/transport/deposition and biological mediation of the hydrodynamics and (iii) GIS: development of GIS-based practical tools able to manage and exploit measured and modeled data on the basis of scientific investigation guidelines and procedures. The overall strategy is described by illustrating results of field measurements, providing details of model implementation and demonstrating the GIS-based tools.

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

Evaluating the effects of ecosystem management: a case study in a Missouri Ozark forest

Treesearch

Wendy K. Gram; Victoria L. Sork; Robert J. Marquis; Rochelle B. Renken; Richard L. Clawson; et. al.

2002-01-01

Many federal and state management agencies have shifted from commodity-based management systems to multiple resource-based management systems that emphasize sustainable ecosystem management. Long-term sustainability of ecosystem functions and processes is at the core of ecosystem management, but a blueprint for assessing sustainability under different management...

Development of a data driven process-based model for remote sensing of terrestrial ecosystem productivity, evapotranspiration, and above-ground biomass

NASA Astrophysics Data System (ADS)

El Masri, Bassil

2011-12-01

Modeling terrestrial ecosystem functions and structure has been a subject of increasing interest because of the importance of the terrestrial carbon cycle in global carbon budget and climate change. In this study, satellite data were used to estimate gross primary production (GPP), evapotranspiration (ET) for two deciduous forests: Morgan Monroe State forest (MMSF) in Indiana and Harvard forest in Massachusetts. Also, above-ground biomass (AGB) was estimated for the MMSF and the Howland forest (mixed forest) in Maine. Surface reflectance and temperature, vegetation indices, soil moisture, tree height and canopy area derived from the Moderate Resolution Imagining Spectroradiometer (MODIS), the Advanced Microwave Scanning Radiometer (AMRS-E), LIDAR, and aerial imagery respectively, were used for this purpose. These variables along with others derived from remotely sensed data were used as inputs variables to process-based models which estimated GPP and ET and to a regression model which estimated AGB. The process-based models were BIOME-BGC and the Penman-Monteith equation. Measured values for the carbon and water fluxes obtained from the Eddy covariance flux tower were compared to the modeled GPP and ET. The data driven methods produced good estimation of GPP and ET with an average root mean square error (RMSE) of 0.17 molC/m2 and 0.40 mm/day, respectively for the MMSF and the Harvard forest. In addition, allometric data for the MMSF were used to develop the regression model relating AGB with stem volume. The performance of the AGB regression model was compared to site measurements using remotely sensed data for the MMSF and the Howland forest where the model AGB RMSE ranged between 2.92--3.30 Kg C/m2. Sensitivity analysis revealed that improvement in maintenance respiration estimation and remotely sensed maximum photosynthetic activity as well as accurate estimate of canopy resistance will result in improved GPP and ET predictions. Moreover, AGB estimates were found to decrease as large grid size is used in rasterizing LIDAR return points. The analysis suggested that this methodology could be used as an operational procedure for monitoring changes in terrestrial ecosystem functions and structure brought by environmental changes.

Statistical modelling of variability in sediment-water nutrient and oxygen fluxes

NASA Astrophysics Data System (ADS)

Serpetti, Natalia; Witte, Ursula; Heath, Michael

2016-06-01

Organic detritus entering, or produced, in the marine environment is re-mineralised to inorganic nutrient in the seafloor sediments. The flux of dissolved inorganic nutrient between the sediment and overlying water column is a key process in the marine ecosystem, which binds the biogeochemical sub-system to the living food web. These fluxes are potentially affected by a wide range of physical and biological factors and disentangling these is a significant challenge. Here we develop a set of General Additive Models (GAM) of nitrate, nitrite, ammonia, phosphate, silicate and oxygen fluxes, based on a year-long campaign of field measurements off the north-east coast of Scotland. We show that sediment grain size, turbidity due to sediment re-suspension, temperature, and biogenic matter content were the key factors affecting oxygen consumption, ammonia and silicate fluxes. However, phosphate fluxes were only related to suspended sediment concentrations, whilst nitrate fluxes showed no clear relationship to any of the expected drivers of change, probably due to the effects of denitrification. Our analyses show that the stoichiometry of nutrient regeneration in the ecosystem is not necessarily constant and may be affected by combinations of processes. We anticipate that our statistical modelling results will form the basis for testing the functionality of process-based mathematical models of whole-sediment biogeochemistry.

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.

A condition metric for Eucalyptus woodland derived from expert evaluations.

PubMed

Sinclair, Steve J; Bruce, Matthew J; Griffioen, Peter; Dodd, Amanda; White, Matthew D

2018-02-01

The evaluation of ecosystem quality is important for land-management and land-use planning. Evaluation is unavoidably subjective, and robust metrics must be based on consensus and the structured use of observations. We devised a transparent and repeatable process for building and testing ecosystem metrics based on expert data. We gathered quantitative evaluation data on the quality of hypothetical grassy woodland sites from experts. We used these data to train a model (an ensemble of 30 bagged regression trees) capable of predicting the perceived quality of similar hypothetical woodlands based on a set of 13 site variables as inputs (e.g., cover of shrubs, richness of native forbs). These variables can be measured at any site and the model implemented in a spreadsheet as a metric of woodland quality. We also investigated the number of experts required to produce an opinion data set sufficient for the construction of a metric. The model produced evaluations similar to those provided by experts, as shown by assessing the model's quality scores of expert-evaluated test sites not used to train the model. We applied the metric to 13 woodland conservation reserves and asked managers of these sites to independently evaluate their quality. To assess metric performance, we compared the model's evaluation of site quality with the managers' evaluations through multidimensional scaling. The metric performed relatively well, plotting close to the center of the space defined by the evaluators. Given the method provides data-driven consensus and repeatability, which no single human evaluator can provide, we suggest it is a valuable tool for evaluating ecosystem quality in real-world contexts. We believe our approach is applicable to any ecosystem. © 2017 State of Victoria.

The Ned IIS project - forest ecosystem management

Treesearch

W. Potter; D. Nute; J. Wang; F. Maier; Michael Twery; H. Michael Rauscher; P. Knopp; S. Thomasma; M. Dass; H. Uchiyama

2002-01-01

For many years we have held to the notion that an Intelligent Information System (IIS) is composed of a unified knowledge base, database, and model base. The main idea behind this notion is the transparent processing of user queries. The system is responsible for "deciding" which information sources to access in order to fulfil a query regardless of whether...

Multiple constraint analysis of regional land-surface carbon flux

Treesearch

D.P. Turner; M. Göckede; B.E. Law; W.D. Ritts; W.B. Cohen; Z. Yang; T. Hudiburg; R. Kennedy; M. Duane

2011-01-01

We applied and compared bottom-up (process model-based) and top-down (atmospheric inversion-based) scaling approaches to evaluate the spatial and temporal patterns of net ecosystem production (NEP) over a 2.5 × 105 km2 area (the state of Oregon) in the western United States. Both approaches indicated a carbon sink over this...

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.

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.

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.

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.

Impacts of land use/cover change on ecosystem services for Xiamen

NASA Astrophysics Data System (ADS)

Shi, L.; Cui, S.

2009-12-01

Based on remote sensing images of Xiamen in 1987, 1997 and 2007, the process of ecosystem service alteration resulting from land use/cover change was quantitatively analyzed through RS and GIS techniques. Consulting relative researches, an integrated assessment model was built to evaluating regional ecosystem services of Xiamen. The results showed that the total ecosystem service value of Xiamen was increased by 14.67%, from 3271.5 million to 3751.39 RMB. The relative change rate of supplying service, regulation service, cultural service and supporting service were 97.8%, -25.1%, 165.0% and -44.7% respectively, which indicated that land use/ cover change had positive effects on supplying and cultural service, whereas it had negatively affected both regulation service and supporting service. Land use/cover types of Xiamen in 1987, 1997 and 2007 Ecosystem values of Xiamen in 1987, 1997 and 2007 10 thousand RMB

More than Anecdotes: Fishers' Ecological Knowledge Can Fill Gaps for Ecosystem Modeling.

PubMed

Bevilacqua, Ana Helena V; Carvalho, Adriana R; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers' knowledge could fill this gap, improving participation in and the management of fisheries. The same fishing area was modeled using two approaches: based on fishers' knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers' knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. The ecosystem attributes produced from the fishers' knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. This study provides evidence that fishers' knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries.

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.

Defining, Measuring, and Incentivizing Sustainable Land Use to Meet Human Needs

NASA Astrophysics Data System (ADS)

Nicholas, K. A.; Brady, M. V.; Olin, S.; Ekroos, J.; Hall, M.; Seaquist, J. W.; Lehsten, V.; Smith, H.

2016-12-01

Land is a natural capital that supports the flow of an enormous amount of ecosystem services critical to human welfare. Sustainable land use, which we define as land use that meets both current and future human needs for ecosystem services, is essential to meet global goals for climate mitigation and sustainable development, while maintaining natural capital. However, it is not clear what governance is needed to achieve sustainable land use under multiple goals (as defined by the values of relevant decision-makers and land managers), particularly under climate change. Here we develop a conceptual model for examining the interactions and tradeoffs among multiple goals, as well as their spatial interactions (teleconnections), in research developed using Design Thinking principles. We have selected five metrics for provisioning (food production, and fiber production for wood and energy), regulating and maintenance (climate mitigation and biodiversity conservation), and cultural (heritage) ecosystem services. Using the case of Sweden, we estimate indicators for these metrics using a combination of existing data synthesis and process-based simulation modeling. We also develop and analyze new indicators (e.g., combining data on land use, bird conservation status, and habitat specificity to make a predictive model of bird diversity changes on agricultural or forested land). Our results highlight both expected tradeoffs (e.g., between food production and biodiversity conservation) as well as unexpected opportunities for synergies under different land management scenarios and strategies. Our model also provides a practical way to make decision-maker values explicit by comparing both quantity and preferences for bundles of ecosystem services under various scenarios. We hope our model will help in considering competing interests and shaping economic incentives and governance structures to meet national targets in support of global goals for sustainable management of land-based ecosystem services.

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…

Coupling biology and oceanography in models.

PubMed

Fennel, W; Neumann, T

2001-08-01

The dynamics of marine ecosystems, i.e. the changes of observable chemical-biological quantities in space and time, are driven by biological and physical processes. Predictions of future developments of marine systems need a theoretical framework, i.e. models, solidly based on research and understanding of the different processes involved. The natural way to describe marine systems theoretically seems to be the embedding of chemical-biological models into circulation models. However, while circulation models are relatively advanced the quantitative theoretical description of chemical-biological processes lags behind. This paper discusses some of the approaches and problems in the development of consistent theories and indicates the beneficial potential of the coupling of marine biology and oceanography in models.

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.

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

NASA Astrophysics Data System (ADS)

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

2007-12-01

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

A methodology for ecosystem-scale modeling of selenium

USGS Publications Warehouse

Presser, T.S.; Luoma, S.N.

2010-01-01

The main route of exposure for selenium (Se) is dietary, yet regulations lack biologically based protocols for evaluations of risk. We propose here an ecosystem-scale model that conceptualizes and quantifies the variables that determinehow Se is processed from water through diet to predators. This approach uses biogeochemical and physiological factors from laboratory and field studies and considers loading, speciation, transformation to particulate material, bioavailability, bioaccumulation in invertebrates, and trophic transfer to predators. Validation of the model is through data sets from 29 historic and recent field case studies of Se-exposed sites. The model links Se concentrations across media (water, particulate, tissue of different food web species). It can be used to forecast toxicity under different management or regulatory proposals or as a methodology for translating a fish-tissue (or other predator tissue) Se concentration guideline to a dissolved Se concentration. The model illustrates some critical aspects of implementing a tissue criterion: 1) the choice of fish species determines the food web through which Se should be modeled, 2) the choice of food web is critical because the particulate material to prey kinetics of bioaccumulation differs widely among invertebrates, 3) the characterization of the type and phase of particulate material is important to quantifying Se exposure to prey through the base of the food web, and 4) the metric describing partitioning between particulate material and dissolved Se concentrations allows determination of a site-specific dissolved Se concentration that would be responsible for that fish body burden in the specific environment. The linked approach illustrates that environmentally safe dissolved Se concentrations will differ among ecosystems depending on the ecological pathways and biogeochemical conditions in that system. Uncertainties and model sensitivities can be directly illustrated by varying exposure scenarios based on site-specific knowledge. The model can also be used to facilitate site-specific regulation and to present generic comparisons to illustrate limitations imposed by ecosystem setting and inhabitants. Used optimally, the model provides a tool for framing a site-specific ecological problem or occurrence of Se exposure, quantify exposure within that ecosystem, and narrow uncertainties abouthowto protect it by understanding the specifics of the underlying system ecology, biogeochemistry, and hydrology.?? 2010 SETAC.

A methodology for ecosystem-scale modeling of selenium.

PubMed

Presser, Theresa S; Luoma, Samuel N

2010-10-01

The main route of exposure for selenium (Se) is dietary, yet regulations lack biologically based protocols for evaluations of risk. We propose here an ecosystem-scale model that conceptualizes and quantifies the variables that determine how Se is processed from water through diet to predators. This approach uses biogeochemical and physiological factors from laboratory and field studies and considers loading, speciation, transformation to particulate material, bioavailability, bioaccumulation in invertebrates, and trophic transfer to predators. Validation of the model is through data sets from 29 historic and recent field case studies of Se-exposed sites. The model links Se concentrations across media (water, particulate, tissue of different food web species). It can be used to forecast toxicity under different management or regulatory proposals or as a methodology for translating a fish-tissue (or other predator tissue) Se concentration guideline to a dissolved Se concentration. The model illustrates some critical aspects of implementing a tissue criterion: 1) the choice of fish species determines the food web through which Se should be modeled, 2) the choice of food web is critical because the particulate material to prey kinetics of bioaccumulation differs widely among invertebrates, 3) the characterization of the type and phase of particulate material is important to quantifying Se exposure to prey through the base of the food web, and 4) the metric describing partitioning between particulate material and dissolved Se concentrations allows determination of a site-specific dissolved Se concentration that would be responsible for that fish body burden in the specific environment. The linked approach illustrates that environmentally safe dissolved Se concentrations will differ among ecosystems depending on the ecological pathways and biogeochemical conditions in that system. Uncertainties and model sensitivities can be directly illustrated by varying exposure scenarios based on site-specific knowledge. The model can also be used to facilitate site-specific regulation and to present generic comparisons to illustrate limitations imposed by ecosystem setting and inhabitants. Used optimally, the model provides a tool for framing a site-specific ecological problem or occurrence of Se exposure, quantify exposure within that ecosystem, and narrow uncertainties about how to protect it by understanding the specifics of the underlying system ecology, biogeochemistry, and hydrology. © 2010 SETAC.

Emerging methods for the study of coastal ecosystem landscape structure and change

USGS Publications Warehouse

Brock, John C.; Danielson, Jeffrey J.; Purkis, Sam

2013-01-01

Coastal landscapes are heterogeneous, dynamic, and evolve over a range of time scales due to intertwined climatic, geologic, hydrologic, biologic, and meteorological processes, and are also heavily impacted by human development, commercial activities, and resource extraction. A diversity of complex coastal systems around the globe, spanning glaciated shorelines to tropical atolls, wetlands, and barrier islands are responding to multiple human and natural drivers. Interdisciplinary research based on remote-sensing observations linked to process studies and models is required to understand coastal ecosystem landscape structure and change. Moreover, new techniques for coastal mapping and monitoring are increasingly serving the needs of policy-makers and resource managers across local, regional, and national scales. Emerging remote-sensing methods associated with a diversity of instruments and platforms are a key enabling element of integrated coastal ecosystem studies. These investigations require both targeted and synoptic mapping, and involve the monitoring of formative processes such as hydrodynamics, sediment transport, erosion, accretion, flooding, habitat modification, land-cover change, and biogeochemical fluxes.

Nitrogen deposition and its effect on carbon storage in Chinese forests during 1981-2010

NASA Astrophysics Data System (ADS)

Gu, Fengxue; Zhang, Yuandong; Huang, Mei; Tao, Bo; Yan, Huimin; Guo, Rui; Li, Jie

2015-12-01

Human activities have resulted in dramatically increased nitrogen (N) deposition worldwide, which is closely linked to the carbon (C)-cycle processes and is considered to facilitate terrestrial C sinks. In this study, we firstly estimated the spatial and temporal variations of N deposition during 1981-2010 based on a new algorithm; then we used a newly improved process-based ecosystem model, CEVSA2, to examine the effects of N deposition on C storage in Chinese forests. The results show that the rate of N deposition increased by 0.058 g N m-2 yr-1 between 1981 and 2010. The N deposition rate in 2010 was 2.32 g N m-2 yr-1, representing a large spatial variation from 0 to 0.25 g N m-2 yr-1 on the northwestern Qinghai-Tibet Plateau to over 4.5 g N m-2 yr-1 in the southeastern China. The model simulations suggest that N deposition induced a 4.78% increase in the total C storage in Chinese forests, most of which accumulated in vegetation. C storage increased together with the increase in N deposition, in both space and time. However, N use efficiency was highest when N deposition was 0.4-1.0 g N m-2 yr-1. We suggest conducting more manipulation experiments and observations in different vegetation types, which will be greatly helpful to incorporate additional processes and mechanisms into the ecosystem modeling. Further development of ecosystem models and identification of C-N interactions will be important for determining the effects of N input on C cycles on both regional and global scales.

Integrating ecosystem sampling, gradient modeling, remote sensing, and ecosystem simulation to create spatially explicit landscape inventories

Treesearch

Robert E. Keane; Matthew G. Rollins; Cecilia H. McNicoll; Russell A. Parsons

2002-01-01

Presented is a prototype of the Landscape Ecosystem Inventory System (LEIS), a system for creating maps of important landscape characteristics for natural resource planning. This system uses gradient-based field inventories coupled with gradient modeling remote sensing, ecosystem simulation, and statistical analyses to derive spatial data layers required for ecosystem...

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

PubMed

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

2014-07-01

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

Linking biophysical models and public preferences for ecosystem service assessments: a case study for the Southern Rocky Mountains

USGS Publications Warehouse

Bagstad, Kenneth J.; Reed, James; Semmens, Darius J.; Sherrouse, Ben C.; Troy, Austin

2016-01-01

Through extensive research, ecosystem services have been mapped using both survey-based and biophysical approaches, but comparative mapping of public values and those quantified using models has been lacking. In this paper, we mapped hot and cold spots for perceived and modeled ecosystem services by synthesizing results from a social-values mapping study of residents living near the Pike–San Isabel National Forest (PSI), located in the Southern Rocky Mountains, with corresponding biophysically modeled ecosystem services. Social-value maps for the PSI were developed using the Social Values for Ecosystem Services tool, providing statistically modeled continuous value surfaces for 12 value types, including aesthetic, biodiversity, and life-sustaining values. Biophysically modeled maps of carbon sequestration and storage, scenic viewsheds, sediment regulation, and water yield were generated using the Artificial Intelligence for Ecosystem Services tool. Hotspots for both perceived and modeled services were disproportionately located within the PSI’s wilderness areas. Additionally, we used regression analysis to evaluate spatial relationships between perceived biodiversity and cultural ecosystem services and corresponding biophysical model outputs. Our goal was to determine whether publicly valued locations for aesthetic, biodiversity, and life-sustaining values relate meaningfully to results from corresponding biophysical ecosystem service models. We found weak relationships between perceived and biophysically modeled services, indicating that public perception of ecosystem service provisioning regions is limited. We believe that biophysical and social approaches to ecosystem service mapping can serve as methodological complements that can advance ecosystem services-based resource management, benefitting resource managers by showing potential locations of synergy or conflict between areas supplying ecosystem services and those valued by the public.

Economic compensation standard for irrigation processes to safeguard environmental flows in the Yellow River Estuary, China

NASA Astrophysics Data System (ADS)

Pang, Aiping; Sun, Tao; Yang, Zhifeng

2013-03-01

SummaryAgriculture and ecosystems are increasingly competing for water. We propose an approach to assess the economic compensation standard required to release water from agricultural use to ecosystems while taking into account seasonal variability in river flow. First, we defined agricultural water shortage as the difference in water volume between agricultural demands and actual supply after maintaining environmental flows for ecosystems. Second, we developed a production loss model to establish the relationship between production losses and agricultural water shortages in view of seasonal variation in river discharge. Finally, we estimated the appropriate economic compensation for different irrigation stakeholders based on crop prices and production losses. A case study in the Yellow River Estuary, China, demonstrated that relatively stable economic compensation for irrigation processes can be defined based on the developed model, taking into account seasonal variations in river discharge and different levels of environmental flow. Annual economic compensation is not directly related to annual water shortage because of the temporal variability in river flow rate and environmental flow. Crops that have stable planting areas to guarantee food security should be selected as indicator crops in economic compensation assessments in the important grain production zone. Economic compensation may be implemented by creating funds to update water-saving measures in agricultural facilities.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

Developing a Data Driven Process-Based Model for Remote Sensing of Ecosystem Production

NASA Astrophysics Data System (ADS)

Elmasri, B.; Rahman, A. F.

2010-12-01

Estimating ecosystem carbon fluxes at various spatial and temporal scales is essential for quantifying the global carbon cycle. Numerous models have been developed for this purpose using several environmental variables as well as vegetation indices derived from remotely sensed data. Here we present a data driven modeling approach for gross primary production (GPP) that is based on a process based model BIOME-BGC. The proposed model was run using available remote sensing data and it does not depend on look-up tables. Furthermore, this approach combines the merits of both empirical and process models, and empirical models were used to estimate certain input variables such as light use efficiency (LUE). This was achieved by using remotely sensed data to the mathematical equations that represent biophysical photosynthesis processes in the BIOME-BGC model. Moreover, a new spectral index for estimating maximum photosynthetic activity, maximum photosynthetic rate index (MPRI), is also developed and presented here. This new index is based on the ratio between the near infrared and the green bands (ρ858.5/ρ555). The model was tested and validated against MODIS GPP product and flux measurements from two eddy covariance flux towers located at Morgan Monroe State Forest (MMSF) in Indiana and Harvard Forest in Massachusetts. Satellite data acquired by the Advanced Microwave Scanning Radiometer (AMSR-E) and MODIS were used. The data driven model showed a strong correlation between the predicted and measured GPP at the two eddy covariance flux towers sites. This methodology produced better predictions of GPP than did the MODIS GPP product. Moreover, the proportion of error in the predicted GPP for MMSF and Harvard forest was dominated by unsystematic errors suggesting that the results are unbiased. The analysis indicated that maintenance respiration is one of the main factors that dominate the overall model outcome errors and improvement in maintenance respiration estimation will result in improved GPP predictions. Although there might be a room for improvements in our model outcomes through improved parameterization, our results suggest that such a methodology for running BIOME-BGC model based entirely on routinely available data can produce good predictions of GPP.

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.

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.

A New Map of Standardized Terrestrial Ecosystems of the Conterminous United States

USGS Publications Warehouse

Sayre, Roger G.; Comer, Patrick; Warner, Harumi; Cress, Jill

2009-01-01

A new map of standardized, mesoscale (tens to thousands of hectares) terrestrial ecosystems for the conterminous United States was developed by using a biophysical stratification approach. The ecosystems delineated in this top-down, deductive modeling effort are described in NatureServe's classification of terrestrial ecological systems of the United States. The ecosystems were mapped as physically distinct areas and were associated with known distributions of vegetation assemblages by using a standardized methodology first developed for South America. This approach follows the geoecosystems concept of R.J. Huggett and the ecosystem geography approach of R.G. Bailey. Unique physical environments were delineated through a geospatial combination of national data layers for biogeography, bioclimate, surficial materials lithology, land surface forms, and topographic moisture potential. Combining these layers resulted in a comprehensive biophysical stratification of the conterminous United States, which produced 13,482 unique biophysical areas. These were considered as fundamental units of ecosystem structure and were aggregated into 419 potential terrestrial ecosystems. The ecosystems classification effort preceded the mapping effort and involved the independent development of diagnostic criteria, descriptions, and nomenclature for describing expert-derived ecological systems. The aggregation and labeling of the mapped ecosystem structure units into the ecological systems classification was accomplished in an iterative, expert-knowledge-based process using automated rulesets for identifying ecosystems on the basis of their biophysical and biogeographic attributes. The mapped ecosystems, at a 30-meter base resolution, represent an improvement in spatial and thematic (class) resolution over existing ecoregionalizations and are useful for a variety of applications, including ecosystem services assessments, climate change impact studies, biodiversity conservation, and resource management.

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

Treesearch

Donald McKenzie; Jeremy S. Littell

2017-01-01

Wildfire area is predicted to increase with global warming. Empirical statistical models and process-based simulations agree almost universally. The key relationship for this unanimity, observed at multiple spatial and temporal scales, is between drought and fire. Predictive models often focus on ecosystems in which this relationship appears to be particularly strong,...

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.

A strategy to study regional hydrology and terrestrial ecosystem processes using satellite remote sensing, ground-based data and computer modeling

NASA Technical Reports Server (NTRS)

Vorosmarty, C.; Grace, A.; Moore, B.; Choudhury, B.; Willmott, C. J.

1990-01-01

A strategy is presented for integrating scanning multichannel microwave radiometer data from the Nimbus-7 satellite with meteorological station records and computer simulations of land surface hydrology, terrestrial nutrient cycling, and trace gas emission. Analysis of the observations together with radiative transfer analysis shows that in the tropics the temporal and spatial variations of the polarization difference are determined primarily by the structure and phenology of vegetation and seasonal inundations of major rivers and wetlands. It is concluded that the proposed surface hydrology model, along with climatological records, and, potentially, 37-GHz data for phenology, will provide inputs to a terrestrial ecosystem model that predicts regional net primary production and CO2 gas exchange.

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.

Decision support system based on DPSIR framework for a low flow Mediterranean river basin

NASA Astrophysics Data System (ADS)

Bangash, Rubab Fatima; Kumar, Vikas; Schuhmacher, Marta

2013-04-01

The application of decision making practices are effectively enhanced by adopting a procedural approach setting out a general methodological framework within which specific methods, models and tools can be integrated. Integrated Catchment Management is a process that recognizes the river catchment as a basic organizing unit for understanding and managing ecosystem process. Decision support system becomes more complex by considering unavoidable human activities within a catchment that are motivated by multiple and often competing criteria and/or constraints. DPSIR is a causal framework for describing the interactions between society and the environment. This framework has been adopted by the European Environment Agency and the components of this model are: Driving forces, Pressures, States, Impacts and Responses. The proposed decision support system is a two step framework based on DPSIR. Considering first three component of DPSIR, Driving forces, Pressures and States, hydrological and ecosystem services models are developed. The last two components, Impact and Responses, helped to develop Bayesian Network to integrate the models. This decision support system also takes account of social, economic and environmental aspects. A small river of Catalonia (Northeastern Spain), Francoli River with a low flow (~2 m3/s) is selected for integration of catchment assessment models and to improve knowledge transfer from research to the stakeholders with a view to improve decision making process. DHI's MIKE BASIN software is used to evaluate the low-flow Francolí River with respect to the water bodies' characteristics and also to assess the impact of human activities aiming to achieve good water status for all waters to comply with the WFD's River Basin Management Plan. Based on ArcGIS, MIKE BASIN is a versatile decision support tool that provides a simple and powerful framework for managers and stakeholders to address multisectoral allocation and environmental issues in river basins. While InVEST is a spatially explicit tool, used to model and map a suite of ecosystem services caused by land cover changes or climate change impacts. Moreover, results obtained from low-flow hydrological simulation and ecosystem services models serves as useful tools to develop decision support system based on DPSIR framework by integrating models. Bayesian Networks is used as a knowledge integration and visualization tool to summarize the outcomes of hydrological and ecosystem services models at the "Response" stage of DPSIR. Bayesian Networks provide a framework for modelling the logical relationship between catchment variables and decision objectives by quantifying the strength of these relationships using conditional probabilities. Participatory nature of this framework can provide better communication of water research, particularly in the context of a perceived lack of future awareness-raising with the public that helps to develop more sustainable water management strategies. Acknowledgements The present study was financially supported by Spanish Ministry of Economy and Competitiveness for its financial support through the project SCARCE (Consolider-Ingenio 2010 CSD2009-00065). R. F. Bangash also received PhD fellowship from AGAUR (Commissioner for Universities and Research of the Department of Innovation, Universities and Enterprise of the "Generalitat de Catalunya" and the European Social Fund).

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

PubMed

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

2017-05-15

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

Freshwater as shared between society and ecosystems: from divided approaches to integrated challenges.

PubMed Central

Falkenmark, Malin

2003-01-01

The paper has its focus on water's key functions behind ecosystem dynamics and the water-related balancing involved in a catchment-based ecosystem approach. A conceptual framework is being developed to address fundamental trade-offs between humans and ecosystems. This is done by paying attention to society's unavoidable landscape modifications and their unavoidable ecological effects mediated by water processes. Because the coevolution of societal and environmental processes indicates resonance rather than a cause-effect relationship, humanity will have to learn to live with change while securing ecosystem resilience. In view of the partial incompatibility of the social imperative of the millennium goals and its environmental sustainability goal, human activities and ecosystems have to be orchestrated for compatibility. To this end a catchment-based approach has to be taken by integrating water, land use and ecosystems. It is being suggested that ecosystem protection has to be thought of in two scales: site-specific biotic landscape components to be protected for their social value, and a catchment-based ecosystem approach to secure sustainable supply of crucial ecosystem goods and services on which social and economic development depends. PMID:14728797

Towards a community Earth System Model

NASA Astrophysics Data System (ADS)

Blackmon, M.

2003-04-01

The Community Climate System Model, version 2 (CCSM2), was released in June 2002. CCSM2 has several new components and features, which I will discuss briefly. I will also show a few results from a multi-century equilibrium run with this model, emphasizing the improvements over the earlier simulation using the original CSM. A few flaws and inadequacies in CCSM2 have been identified. I will also discuss briefly work underway to improve the model and present results, if available. CCSM2, with improvements, will be the basis for the development of a Community Earth System Model (CESM). The highest priority for expansion of the model involves incorporation of biogeosciences into the coupled model system, with emphasis given to the carbon, nitrogen and iron cycles. The overall goal of the biogeosciences project within CESM is to understand the regulation of planetary energetics, planetary ecology, and planetary metabolism through exchanges of energy, momentum, and materials among atmosphere, land, and ocean, and the response of the climate system through these processes to changes in land cover and land use. In particular, this research addresses how biogeochemical coupling of carbon, nitrogen, and iron cycles affects climate and how human perturbations of these cycles alter climate. To accomplish these goals, the Community Land Model, the land component of CCSM2, is being developed to include river routing, carbon and nitrogen cycles, emissions of mineral aerosols and biogenic volatile organic compounds, dry deposition of various gases, and vegetation dynamics. The carbon and nitrogen cycles are being implemented using parameterizations developed as part of a state-of-the-art ecosystem biogeochemistry model. The primary goal of this research is to provide an accurate net flux of CO2 between the land and the atmosphere so that CESM can be used to study the dynamics of the coupled climate-carbon system. Emissions of biogenic volatile organic compounds are also based on a state-of-the-art emissions model and depend on plant type, leaf area index, photosynthetically active radiation, and leaf temperature. Dust emissions and deposition are being developed to implement a fully coupled dust cycle in CCSM, including the radiative effects of dust and carbon feedbacks related to fertilization of ocean and terrestrial ecosystems. Dust mobilization depends on surface wind speed, soil moisture, plant cover, and soil texture. Dust dry deposition processes include sedimentation and turbulent mix-out. A major research focus is how natural and human-mediated changes in land cover and ecosystem functions alter surface energy fluxes, the hydrological cycle, and biogeochemical cycles. Human land uses include conversion of natural vegetation to cropland, soil degradation, and urbanization. Climate feedbacks associated with natural changes in land cover are being assessed by developing and implementing a model of natural vegetation dynamics for use with the Community Land Model. Development of a marine ecosystem model is also underway. The ecosystem model is based on the global, mixed-layer marine ecosystem model of Moore et al., which includes parameterizations for such things as iron limitation and scavenging, zooplankton grazing, nitrogen fixation, calcification, and ballast-based remineralization. A series of experiments is being planned to assess the coupling of the ecology to the biogeochemistry, to adequately tune some of the model parameters that are poorly constrained by data, to explore new parameterizations and processes (e.g., riverine and atmospheric inputs of nutrients), and to conduct uncoupled application studies (e.g., deliberate carbon sequestration, retrospective historical simulations, iron-dust deposition response). Longer term plans include investigating biogeochemical processes in the coastal zone and how to incorporate these processes into a global ocean model, either through subgrid-scale parameterizations or model nesting. A Whole Atmosphere Community Climate Model(WACCM) is being developed. The vertical extent of the model is 150 km at present, but extension to 500 km is eventually expected. Interactive chemistry is being incorporated. This model will be used as the atmospheric component of CESM for some experiments. One expected application is the study of solar variability and its impact on climate variability in the troposphere and at the atmosphere, ocean, land interface. Preliminary results using some of these model components will be shown. A timeline for development and use of the models will be given.

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.

Reviews and syntheses: Four decades of modeling methane cycling in terrestrial ecosystems

DOE PAGES

Xu, Xiaofeng; Yuan, Fengming; Hanson, Paul J.; ...

2016-01-28

A number of numerical models have been developed to quantify the magnitude, over the past 4 decades, such that we have investigated the spatial and temporal variations, and understand the underlying mechanisms and environmental controls of methane (CH 4) fluxes within terrestrial ecosystems. These CH 4 models are also used for integrating multi-scale CH 4 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 CH 4 models to characterize their strengths and weaknesses and to suggest a roadmap for future model improvementmore » and application. Our key findings are that (1) the focus of CH 4 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 CH 4 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. Furthermore three areas for future improvements and applications of terrestrial CH 4 models are that (1) CH 4 models should more explicitly represent the mechanisms underlying land–atmosphere CH 4 exchange, with an emphasis on improving and validating individual CH 4 processes over depth and horizontal space, (2) models should be developed that are capable of simulating CH 4 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. Finally, these improvements in CH 4 models would be beneficial for the Earth system models and further simulation of climate–carbon cycle feedbacks.« less

Overestimation of marsh vulnerability to sea level rise

USGS Publications Warehouse

Kirwan, Matthew L.; Temmerman, Stijn; Skeehan, Emily E.; Guntenspergen, Glenn R.; Fagherazzi, Sergio

2016-01-01

Coastal marshes are considered to be among the most valuable and vulnerable ecosystems on Earth, where the imminent loss of ecosystem services is a feared consequence of sea level rise. However, we show with a meta-analysis that global measurements of marsh elevation change indicate that marshes are generally building at rates similar to or exceeding historical sea level rise, and that process-based models predict survival under a wide range of future sea level scenarios. We argue that marsh vulnerability tends to be overstated because assessment methods often fail to consider biophysical feedback processes known to accelerate soil building with sea level rise, and the potential for marshes to migrate inland.

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.

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.

How does complex terrain influence responses of carbon and water cycle processes to climate variability and climate change? (Invited)

NASA Astrophysics Data System (ADS)

Bond, B. J.; Peterson, K.; McKane, R.; Lajtha, K.; Quandt, D. J.; Allen, S. T.; Sell, S.; Daly, C.; Harmon, M. E.; Johnson, S. L.; Spies, T.; Sollins, P.; Abdelnour, A. G.; Stieglitz, M.

2010-12-01

We are pursuing the ambitious goal of understanding how complex terrain influences the responses of carbon and water cycle processes to climate variability and climate change. Our studies take place in H.J. Andrews Experimental Forest, an LTER (Long Term Ecological Research) site situated in Oregon’s central-western Cascade Range. Decades of long-term measurements and intensive research have revealed influences of topography on vegetation patterns, disturbance history, and hydrology. More recent research has shown surprising interactions between microclimates and synoptic weather patterns due to cold air drainage and pooling in mountain valleys. Using these data and insights, in addition to a recent LiDAR (Light Detection and Ranging) reconnaissance and a small sensor network, we are employing process-based models, including “SPA” (Soil-Plant-Atmosphere, developed by Mathew Williams of the University of Edinburgh), and “VELMA” (Visualizing Ecosystems for Land Management Alternatives, developed by Marc Stieglitz and colleagues of the Georgia Institute of Technology) to focus on two important features of mountainous landscapes: heterogeneity (both spatial and temporal) and connectivity (atmosphere-canopy-hillslope-stream). Our research questions include: 1) Do fine-scale spatial and temporal heterogeneity result in emergent properties at the basin scale, and if so, what are they? 2) How does connectivity across ecosystem components affect system responses to climate variability and change? Initial results show that for environmental drivers that elicit non-linear ecosystem responses on the plot scale, such as solar radiation, soil depth and soil water content, fine-scale spatial heterogeneity may produce unexpected emergent properties at larger scales. The results from such modeling experiments are necessarily a function of the supporting algorithms. However, comparisons based on models such as SPA and VELMA that operate at much different spatial scales (plots vs. hillslopes) and levels of biophysical organization (individual plants vs. aggregate plant biomass) can help us to understand how and why mountainous ecosystems may have distinctive responses to climate variability and climate change.

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.

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.

Impact of climate, CO2 and land use on terrestrial carbon and water fluxes in China based on a multi-model analysis

NASA Astrophysics Data System (ADS)

Jia, B.; Xie, Z.

2017-12-01

Climate change and anthropogenic activities have been exerting profound influences on ecosystem function and processes, including tightly coupled terrestrial carbon and water cycles. However, their relative contributions of the key controlling factors, e.g., climate, CO2 fertilization, land use and land cover change (LULCC), on spatial-temporal patterns of terrestrial carbon and water fluxes in China are still not well understood due to the lack of ecosystem-level flux observations and uncertainties in single terrestrial biosphere model (TBM). In the present study, we quantified the effect of climate, CO2, and LULCC on terrestrial carbon and water fluxes in China using multi-model simulations for their inter-annual variability (IAV), seasonal cycle amplitude (SCA) and long-term trend during the past five decades (1961-2010). In addition, their relative contributions to the temporal variations of gross primary productivity (GPP), net ecosystem productivity (NEP) and evapotranspiration (ET) were investigated through factorial experiments. Finally, the discussions about the inter-model differences and model uncertainties were presented.

Model parameters for representative wetland plant functional groups

USGS Publications Warehouse

Williams, Amber S.; Kiniry, James R.; Mushet, David M.; Smith, Loren M.; McMurry, Scott T.; Attebury, Kelly; Lang, Megan; McCarty, Gregory W.; Shaffer, Jill A.; Effland, William R.; Johnson, Mari-Vaughn V.

2017-01-01

Wetlands provide a wide variety of ecosystem services including water quality remediation, biodiversity refugia, groundwater recharge, and floodwater storage. Realistic estimation of ecosystem service benefits associated with wetlands requires reasonable simulation of the hydrology of each site and realistic simulation of the upland and wetland plant growth cycles. Objectives of this study were to quantify leaf area index (LAI), light extinction coefficient (k), and plant nitrogen (N), phosphorus (P), and potassium (K) concentrations in natural stands of representative plant species for some major plant functional groups in the United States. Functional groups in this study were based on these parameters and plant growth types to enable process-based modeling. We collected data at four locations representing some of the main wetland regions of the United States. At each site, we collected on-the-ground measurements of fraction of light intercepted, LAI, and dry matter within the 2013–2015 growing seasons. Maximum LAI and k variables showed noticeable variations among sites and years, while overall averages and functional group averages give useful estimates for multisite simulation modeling. Variation within each species gives an indication of what can be expected in such natural ecosystems. For P and K, the concentrations from highest to lowest were spikerush (Eleocharis macrostachya), reed canary grass (Phalaris arundinacea), smartweed (Polygonum spp.), cattail (Typha spp.), and hardstem bulrush (Schoenoplectus acutus). Spikerush had the highest N concentration, followed by smartweed, bulrush, reed canary grass, and then cattail. These parameters will be useful for the actual wetland species measured and for the wetland plant functional groups they represent. These parameters and the associated process-based models offer promise as valuable tools for evaluating environmental benefits of wetlands and for evaluating impacts of various agronomic practices in adjacent areas as they affect wetlands.

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.

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.

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.

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.

Secondary dispersal driven by overland flow in drylands: Review and mechanistic model development.

PubMed

Thompson, Sally E; Assouline, Shmuel; Chen, Li; Trahktenbrot, Ana; Svoray, Tal; Katul, Gabriel G

2014-01-01

Seed dispersal alters gene flow, reproduction, migration and ultimately spatial organization of dryland ecosystems. Because many seeds in drylands lack adaptations for long-distance dispersal, seed transport by secondary processes such as tumbling in the wind or mobilization in overland flow plays a dominant role in determining where seeds ultimately germinate. Here, recent developments in modeling runoff generation in spatially complex dryland ecosystems are reviewed with the aim of proposing improvements to mechanistic modeling of seed dispersal processes. The objective is to develop a physically-based yet operational framework for determining seed dispersal due to surface runoff, a process that has gained recent experimental attention. A Buoyant OBject Coupled Eulerian - Lagrangian Closure model (BOB-CELC) is proposed to represent seed movement in shallow surface flows. The BOB-CELC is then employed to investigate the sensitivity of seed transport to landscape and storm properties and to the spatial configuration of vegetation patches interspersed within bare earth. The potential to simplify seed transport outcomes by considering the limiting behavior of multiple runoff events is briefly considered, as is the potential for developing highly mechanistic, spatially explicit models that link seed transport, vegetation structure and water movement across multiple generations of dryland plants.

Analysis of ecosystem controls on soil carbon source-sink relationships in the northwest Great Plains

USGS Publications Warehouse

Tan, Z.; Liu, S.; Johnston, C.A.; Liu, J.; Tieszen, L.L.

2006-01-01

Our ability to forecast the role of ecosystem processes in mitigating global greenhouse effects relies on understanding the driving forces on terrestrial C dynamics. This study evaluated the controls on soil organic C (SOC) changes from 1973 to 2000 in the northwest Great Plains. SOC source-sink relationships were quantified using the General Ensemble Biogeochemical Modeling System (GEMS) based on 40 randomly located 10 × 10 km2 sample blocks. These sample blocks were aggregated into cropland, grassland, and forestland groups based on land cover composition within each sample block. Canonical correlation analysis indicated that SOC source-sink relationship from 1973 to 2000 was significantly related to the land cover type while the change rates mainly depended on the baseline SOC level and annual precipitation. Of all selected driving factors, the baseline SOC and nitrogen levels controlled the SOC change rates for the forestland and cropland groups, while annual precipitation determined the C source-sink relationship for the grassland group in which noticeable SOC sink strength was attributed to the conversion from cropped area to grass cover. Canonical correlation analysis also showed that grassland ecosystems are more complicated than others in the ecoregion, which may be difficult to identify on a field scale. Current model simulations need further adjustments to the model input variables for the grass cover-dominated ecosystems in the ecoregion.

Applying principles from economics to improve the transfer of ecological production estimates in fisheries ecosystem services research

EPA Science Inventory

Ecosystem services (ES) represent a way to represent and quantify multiple uses, values as well as connectivity between ecosystem processes and human well-being. Ecosystem-based fisheries management approaches may seek to quantify expected trade-offs in ecosystem services due to ...

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

NASA Technical Reports Server (NTRS)

Kimball, John; Kang, Sinkyu

2003-01-01

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

ICT use for information management in healthcare system for chronic disease patient

NASA Astrophysics Data System (ADS)

Wawrzyniak, Zbigniew M.; Lisiecka-Biełanowicz, Mira

2013-10-01

Modern healthcare systems are designed to fulfill needs of the patient, his system environment and other determinants of the treatment with proper support of technical aids. A whole system of care is compatible to the technical solutions and organizational framework based on legal rules. The purpose of this study is to present how can we use Information and Communication Technology (ICT) systemic tools in a new model of patient-oriented care, improving the effectiveness of healthcare for patients with chronic diseases. The study material is the long-term process of healthcare for patients with chronic illness. Basing on the knowledge of the whole circumstances of patient's ecosystem and his needs allow us to build a new ICT model of long term care. The method used is construction, modeling and constant improvement the efficient ICT layer for the patient-centered healthcare model. We present a new constructive approach to systemic process how to use ICT for information management in healthcare system for chronic disease patient. The use of ICT tools in the model for chronic disease can improve all aspects of data management and communication, and the effectiveness of long-term complex healthcare. In conclusion: ICT based model of healthcare can be constructed basing on the interactions of ecosystem's functional parts through information feedback and the provision of services and models as well as the knowledge of the patient itself. Systematic approach to the model of long term healthcare assisted functionally by ICT tools and data management methods will increase the effectiveness of patient care and organizational efficiency.

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

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-12-01

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

Improving SWAT for simulating water and carbon fluxes of forest ecosystems

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

Yang, Qichun; Zhang, Xuesong

2016-11-01

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

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.

FROM THE FOREST TO THE SEA AND BACK AGAIN: MARINE INPUTS AND TERRESTRIAL BIOGEOCHEMISTRY IN THE PACIFIC NORTHWEST

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 ecosystem processes. Based on spatial patterns of...

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...

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.

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

NASA Astrophysics Data System (ADS)

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

2011-03-01

More reliable estimates of carbon (C) stock within forest ecosystems and C emission induced by deforestation are urgently needed to mitigate the effects of emissions on climate change. A process-based terrestrial biogeochemical model (VISIT) was applied to tropical primary forests of two types (a seasonal dry forest in Thailand and a rainforest in Malaysia) and one agro-forest (an oil palm plantation in Malaysia) to estimate the C budget of tropical ecosystems, including the impacts of land-use conversion, in Southeast Asia. Observations and VISIT model simulations indicated that the primary forests had high photosynthetic uptake: gross primary production was estimated at 31.5-35.5 t C ha-1 yr-1. In the VISIT model simulation, the rainforest had a higher total C stock (plant biomass and soil organic matter, 301.5 t C ha-1) than that in the seasonal dry forest (266.5 t C ha-1) in 2008. The VISIT model appropriately captured the impacts of disturbances such as deforestation and land-use conversions on the C budget. Results of sensitivity analysis implied that the ratio of remaining residual debris was a key parameter determining the soil C budget after deforestation events. The C stock of the oil palm plantation was about 46% of the rainforest's C at 30 yr following initiation of the plantation, when the ratio of remaining residual debris was assumed to be about 33%. These results show that adequate forest management is important for reducing C emission from soil and C budget of each ecosystem must be evaluated over a long term using both the model simulations and observations.

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...

Linking GIS-based models to value ecosystem services in an Alpine region.

PubMed

Grêt-Regamey, Adrienne; Bebi, Peter; Bishop, Ian D; Schmid, Willy A

2008-11-01

Planning frequently fails to include the valuation of public goods and services. This can have long-term negative economic consequences for a region. This is especially the case in mountainous regions such as the Alps, which depend on tourism and where land-use changes can negatively impact key ecosystem services and hence the economy. In this study, we develop a semi-automatic procedure to value ecosystem goods and services. Several existing process-based models linked to economic valuation methods are integrated into a geographic information system (GIS) platform. The model requires the input of a digital elevation model, a land-cover map, and a spatially explicit temperature dataset. These datasets are available for most regions in Europe. We illustrate the approach by valuing four ecosystem services: avalanche protection, timber production, scenic beauty, and habitat, which are supplied by the "Landschaft Davos", an administrative district in the Swiss Alps. We compare the impacts of a human development scenario and a climate scenario on the value of these ecosystem services. Urban expansion and tourist infrastructure developments have a negative impact on scenic beauty and habitats. These impacts outweigh the benefits of the developments in the long-term. Forest expansion, predictable under a climate change scenario, favours natural avalanche protection and habitats. In general, such non-marketed benefits provided by the case-study region more than compensate for the costs of forest maintenance. Finally, we discuss the advantages and disadvantages of the approach. Despite its limitations, we show how this approach could well help decision-makers balance the impacts of different planning options on the economic accounting of a region, and guide them in selecting sustainable and economically feasible development strategies.

More than Anecdotes: Fishers’ Ecological Knowledge Can Fill Gaps for Ecosystem Modeling

PubMed Central

Bevilacqua, Ana Helena V.; Carvalho, Adriana R.; Angelini, Ronaldo; Christensen, Villy

2016-01-01

Background Ecosystem modeling applied to fisheries remains hampered by a lack of local information. Fishers’ knowledge could fill this gap, improving participation in and the management of fisheries. Methodology The same fishing area was modeled using two approaches: based on fishers’ knowledge and based on scientific information. For the former, the data was collected by interviews through the Delphi methodology, and for the latter, the data was gathered from the literature. Agreement between the attributes generated by the fishers’ knowledge model and scientific model is discussed and explored, aiming to improve data availability, the ecosystem model, and fisheries management. Principal Findings The ecosystem attributes produced from the fishers’ knowledge model were consistent with the ecosystem attributes produced by the scientific model, and elaborated using only the scientific data from literature. Conclusions/Significance This study provides evidence that fishers’ knowledge may suitably complement scientific data, and may improve the modeling tools for the research and management of fisheries. PMID:27196131

[Research progress of ecosystem service flow.

PubMed

Liu, Hui Min; Fan, Yu Long; Ding, Sheng Yan

2016-07-01

With the development of social economy, human disturbance has resulted in a variety of ecosystem service degradation or disappearance. Ecosystem services flow plays an important role in delivery, transformation and maintenance of ecosystem services, and becomes one of the new research directions. In this paper, based on the classification of ecosystem services flow, we analyzed ecosystem service delivery carrier, and investigated the mechanism of ecosystem service flow, including the information, property, scale features, quantification and cartography. Moreover, a tentative analysis on cost-effective of ecosystem services flow (such as transportation costs, conversion costs, usage costs and cost of relativity) was made to analyze the consumption cost in ecosystem services flow process. It aimed to analyze dissipation cost in ecosystem services flow process. To a certain extent, the study of ecosystem service flow solved the problem of "double counting" in ecosystem services valuation, which could make a contribution for the sake of recognizing hot supply and consumption spots of ecosystem services. In addition, it would be conducive to maximizing the ecosystem service benefits in the transmission process and putting forward scientific and reasonable ecological compensation.

The Earth System Documentation (ES-DOC) Software Process

NASA Astrophysics Data System (ADS)

Greenslade, M. A.; Murphy, S.; Treshansky, A.; DeLuca, C.; Guilyardi, E.; Denvil, S.

2013-12-01

Earth System Documentation (ES-DOC) is an international project supplying high-quality tools & services in support of earth system documentation creation, analysis and dissemination. It is nurturing a sustainable standards based documentation eco-system that aims to become an integral part of the next generation of exa-scale dataset archives. ES-DOC leverages open source software, and applies a software development methodology that places end-user narratives at the heart of all it does. ES-DOC has initially focused upon nurturing the Earth System Model (ESM) documentation eco-system and currently supporting the following projects: * Coupled Model Inter-comparison Project Phase 5 (CMIP5); * Dynamical Core Model Inter-comparison Project (DCMIP); * National Climate Predictions and Projections Platforms Quantitative Evaluation of Downscaling Workshop. This talk will demonstrate that ES-DOC implements a relatively mature software development process. Taking a pragmatic Agile process as inspiration, ES-DOC: * Iteratively develops and releases working software; * Captures user requirements via a narrative based approach; * Uses online collaboration tools (e.g. Earth System CoG) to manage progress; * Prototypes applications to validate their feasibility; * Leverages meta-programming techniques where appropriate; * Automates testing whenever sensibly feasible; * Streamlines complex deployments to a single command; * Extensively leverages GitHub and Pivotal Tracker; * Enforces strict separation of the UI from underlying API's; * Conducts code reviews.

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.

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.

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.

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.

Satellite-based modeling of gross primary production in an evergreen needleleaf forest

Treesearch

Xiangming Xiao; David Hollinger; John Aber; Mike Goltz; Eric A. Davidson; Qingyuan Zhang; Berrien Moore III

2004-01-01

The eddy covariance technique provides valuable information on net ecosystem exchange (NEE) of CO2, between the atmosphere and terrestrial ecosystems, ecosystem respiration, and gross primary production (GPP) at a variety of C02 eddy flux tower sites. In this paper, we develop a new, satellite-based Vegetation Photosynthesis Model (VPM) to estimate the seasonal dynamcs...

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

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.

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

PubMed Central

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

2012-01-01

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

Brief communication: the ecosystem perspective in ecotoxicology as a way forward for the ecological risk assessment of chemicals.

PubMed

De Laender, Frederik; Janssen, Colin R

2013-07-01

One of the objectives of the European Union (EU) ecological risk assessment of chemicals (ERA) is to derive maximum environmental concentrations that are not expected to cause adverse ecological effects. To this end, related EU directives list protection goals as well as guidelines that should be used to reach these goals. It is generally accepted that the individual-level endpoints on which these guidelines are based do not correspond to the listed population- and ecosystem-level protection goals. In this article, we identify 5 research topics that are key to bridging this gap: 1) the refinement of population-level effects and recovery rates by explicitly taking into account competition and 2) predation, 3) the assessment of chemical effects on biodiversity, 4) the assessment of chemical stress on ecosystem functions and services, and 5) the quantification of the effects of chemical mixtures. In addition, we illustrate why an ecosystem perspective is needed to address these topics and to inform the risk assessment process. We propose the use of existing ecotoxicological community, food web, and ecosystem models to tackle these issues and discuss why new models are needed to predict chemical effects on biodiversity. Copyright © 2013 SETAC.

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

PubMed

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

2012-08-01

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

[Measuring water ecological carrying capacity with the ecosystem-service-based ecological footprint (ESEF) method: Theory, models and application].

PubMed

Jiao, Wen-jun; Min, Qing-wen; Li, Wen-hua; Fuller, Anthony M

2015-04-01

Integrated watershed management based on aquatic ecosystems has been increasingly acknowledged. Such a change in the philosophy of water environment management requires recognizing the carrying capacity of aquatic ecosystems for human society from a more general perspective. The concept of the water ecological carrying capacity is therefore put forward, which considers both water resources and water environment, connects socio-economic development to aquatic ecosystems and provides strong support for integrated watershed management. In this paper, the authors proposed an ESEF-based measure of water ecological carrying capacity and constructed ESEF-based models of water ecological footprint and capacity, aiming to evaluate water ecological carrying capacity with footprint methods. A regional model of Taihu Lake Basin was constructed and applied to evaluate the water ecological carrying capacity in Changzhou City which located in the upper reaches of the basin. Results showed that human demand for water ecosystem services in this city had exceeded the supply capacity of local aquatic ecosystems and the significant gap between demand and supply had jeopardized the sustainability of local aquatic ecosystems. Considering aqua-product provision, water supply and pollutant absorption in an integrated way, the scale of population and economy aquatic ecosystems in Changzhou could bear only 54% of the current status.

When relationships estimated in the past cannot be used to predict the future: using mechanistic models to predict landscape ecological dynamics in a changing world

Treesearch

Eric J. Gustafson

2013-01-01

Researchers and natural resource managers need predictions of how multiple global changes (e.g., climate change, rising levels of air pollutants, exotic invasions) will affect landscape composition and ecosystem function. Ecological predictive models used for this purpose are constructed using either a mechanistic (process-based) or a phenomenological (empirical)...

MERINOVA: Meteorological risks as drivers of environmental innovation in agro-ecosystem management

NASA Astrophysics Data System (ADS)

Gobin, Anne; Oger, Robert; Marlier, Catherine; Van De Vijver, Hans; Vandermeulen, Valerie; Van Huylenbroeck, Guido; Zamani, Sepideh; Curnel, Yannick; Mettepenningen, Evi

2013-04-01

The BELSPO funded project 'MERINOVA' deals with risks associated with extreme weather phenomena and with risks of biological origin such as pests and diseases. The major objectives of the proposed project are to characterise extreme meteorological events, assess the impact on Belgian agro-ecosystems, characterise their vulnerability and resilience to these events, and explore innovative adaptation options to agricultural risk management. The project comprises of five major parts that reflect the chain of risks: (i) Hazard: Assessing the likely frequency and magnitude of extreme meteorological events by means of probability density functions; (ii) Impact: Analysing the potential bio-physical and socio-economic impact of extreme weather events on agro-ecosystems in Belgium using process-based modelling techniques commensurate with the regional scale; (iii) Vulnerability: Identifying the most vulnerable agro-ecosystems using fuzzy multi-criteria and spatial analysis; (iv) Risk Management: Uncovering innovative risk management and adaptation options using actor-network theory and fuzzy cognitive mapping techniques; and, (v) Communication: Communicating to research, policy and practitioner communities using web-based techniques. The different tasks of the MERINOVA project require expertise in several scientific disciplines: meteorology, statistics, spatial database management, agronomy, bio-physical impact modelling, socio-economic modelling, actor-network theory, fuzzy cognitive mapping techniques. These expertises are shared by the four scientific partners who each lead one work package. The MERINOVA project will concentrate on promoting a robust and flexible framework by demonstrating its performance across Belgian agro-ecosystems, and by ensuring its relevance to policy makers and practitioners. Impacts developed from physically based models will not only provide information on the state of the damage at any given time, but also assist in understanding the links between different factors causing damage and determining bio-physical vulnerability. Socio-economic impacts will enlarge the basis for vulnerability mapping, risk management and adaptation options. A strong expert and end-user network will be established to help disseminating and exploiting project results to meet user needs.

Chapter 6: Temperature

USGS Publications Warehouse

Jones, Leslie A.; Muhlfeld, Clint C.; Hauer, F. Richard; F. Richard Hauer,; Lamberti, G.A.

2017-01-01

Stream temperature has direct and indirect effects on stream ecology and is critical in determining both abiotic and biotic system responses across a hierarchy of spatial and temporal scales. Temperature variation is primarily driven by solar radiation, while landscape topography, geology, and stream reach scale ecosystem processes contribute to local variability. Spatiotemporal heterogeneity in freshwater ecosystems influences habitat distributions, physiological functions, and phenology of all aquatic organisms. In this chapter we provide an overview of methods for monitoring stream temperature, characterization of thermal profiles, and modeling approaches to stream temperature prediction. Recent advances in temperature monitoring allow for more comprehensive studies of the underlying processes influencing annual variation of temperatures and how thermal variability may impact aquatic organisms at individual, population, and community based scales. Likewise, the development of spatially explicit predictive models provide a framework for simulating natural and anthropogenic effects on thermal regimes which is integral for sustainable management of freshwater systems.

Process contributions of Australian ecosystems to interannual variations in the carbon cycle

NASA Astrophysics Data System (ADS)

Haverd, Vanessa; Smith, Benjamin; Trudinger, Cathy

2016-05-01

New evidence is emerging that semi-arid ecosystems dominate interannual variability (IAV) of the global carbon cycle, largely via fluctuating water availability associated with El Niño/Southern Oscillation. Recent evidence from global terrestrial biosphere modelling and satellite-based inversion of atmospheric CO2 point to a large role of Australian ecosystems in global carbon cycle variability, including a large contribution from Australia to the record land sink of 2011. However the specific mechanisms governing this variability, and their bioclimatic distribution within Australia, have not been identified. Here we provide a regional assessment, based on best available observational data, of IAV in the Australian terrestrial carbon cycle and the role of Australia in the record land sink anomaly of 2011. We find that IAV in Australian net carbon uptake is dominated by semi-arid ecosystems in the east of the continent, whereas the 2011 anomaly was more uniformly spread across most of the continent. Further, and in contrast to global modelling results suggesting that IAV in Australian net carbon uptake is amplified by lags between production and decomposition, we find that, at continental scale, annual variations in production are dampened by annual variations in decomposition, with both fluxes responding positively to precipitation anomalies.

Global Sensitivity Analysis and Parameter Calibration for an Ecosystem Carbon Model

NASA Astrophysics Data System (ADS)

Safta, C.; Ricciuto, D. M.; Sargsyan, K.; Najm, H. N.; Debusschere, B.; Thornton, P. E.

2013-12-01

We present uncertainty quantification results for a process-based ecosystem carbon model. The model employs 18 parameters and is driven by meteorological data corresponding to years 1992-2006 at the Harvard Forest site. Daily Net Ecosystem Exchange (NEE) observations were available to calibrate the model parameters and test the performance of the model. Posterior distributions show good predictive capabilities for the calibrated model. A global sensitivity analysis was first performed to determine the important model parameters based on their contribution to the variance of NEE. We then proceed to calibrate the model parameters in a Bayesian framework. The daily discrepancies between measured and predicted NEE values were modeled as independent and identically distributed Gaussians with prescribed daily variance according to the recorded instrument error. All model parameters were assumed to have uninformative priors with bounds set according to expert opinion. The global sensitivity results show that the rate of leaf fall (LEAFALL) is responsible for approximately 25% of the total variance in the average NEE for 1992-2005. A set of 4 other parameters, Nitrogen use efficiency (NUE), base rate for maintenance respiration (BR_MR), growth respiration fraction (RG_FRAC), and allocation to plant stem pool (ASTEM) contribute between 5% and 12% to the variance in average NEE, while the rest of the parameters have smaller contributions. The posterior distributions, sampled with a Markov Chain Monte Carlo algorithm, exhibit significant correlations between model parameters. However LEAFALL, the most important parameter for the average NEE, is not informed by the observational data, while less important parameters show significant updates between their prior and posterior densities. The Fisher information matrix values, indicating which parameters are most informed by the experimental observations, are examined to augment the comparison between the calibration and global sensitivity analysis results.

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.

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

Origin of Pareto-like spatial distributions in ecosystems.

PubMed

Manor, Alon; Shnerb, Nadav M

2008-12-31

Recent studies of cluster distribution in various ecosystems revealed Pareto statistics for the size of spatial colonies. These results were supported by cellular automata simulations that yield robust criticality for endogenous pattern formation based on positive feedback. We show that this patch statistics is a manifestation of the law of proportionate effect. Mapping the stochastic model to a Markov birth-death process, the transition rates are shown to scale linearly with cluster size. This mapping provides a connection between patch statistics and the dynamics of the ecosystem; the "first passage time" for different colonies emerges as a powerful tool that discriminates between endogenous and exogenous clustering mechanisms. Imminent catastrophic shifts (such as desertification) manifest themselves in a drastic change of the stability properties of spatial colonies.

Contributions of wildland fire to terrestrial ecosystem carbon dynamics in North America from 1990 to 2012

USGS Publications Warehouse

Chen, Guangsheng; Hayes, Daniel J.; McGuire, A. David

2017-01-01

Burn area and the frequency of extreme fire events have been increasing during recent decades in North America, and this trend is expected to continue over the 21st century. While many aspects of the North American carbon budget have been intensively studied, the net contribution of fire disturbance to the overall net carbon flux at the continental scale remains uncertain. Based on national scale, spatially explicit and long-term fire data, along with the improved model parameterization in a process-based ecosystem model, we simulated the impact of fire disturbance on both direct carbon emissions and net terrestrial ecosystem carbon balance in North America. Fire-caused direct carbon emissions were 106.55 ± 15.98 Tg C/yr during 1990–2012; however, the net ecosystem carbon balance associated with fire was −26.09 ± 5.22 Tg C/yr, indicating that most of the emitted carbon was resequestered by the terrestrial ecosystem. Direct carbon emissions showed an increase in Alaska and Canada during 1990–2012 as compared to prior periods due to more extreme fire events, resulting in a large carbon source from these two regions. Among biomes, the largest carbon source was found to be from the boreal forest, primarily due to large reductions in soil organic matter during, and with slower recovery after, fire events. The interactions between fire and environmental factors reduced the fire-caused ecosystem carbon source. Fire disturbance only caused a weak carbon source as compared to the best estimate terrestrial carbon sink in North America owing to the long-term legacy effects of historical burn area coupled with fast ecosystem recovery during 1990–2012.

Using natural selection and optimization for smarter vegetation models - challenges and opportunities

NASA Astrophysics Data System (ADS)

Franklin, Oskar; Han, Wang; Dieckmann, Ulf; Cramer, Wolfgang; Brännström, Åke; Pietsch, Stephan; Rovenskaya, Elena; Prentice, Iain Colin

2017-04-01

Dynamic global vegetation models (DGVMs) are now indispensable for understanding the biosphere and for estimating the capacity of ecosystems to provide services. The models are continuously developed to include an increasing number of processes and to utilize the growing amounts of observed data becoming available. However, while the versatility of the models is increasing as new processes and variables are added, their accuracy suffers from the accumulation of uncertainty, especially in the absence of overarching principles controlling their concerted behaviour. We have initiated a collaborative working group to address this problem based on a 'missing law' - adaptation and optimization principles rooted in natural selection. Even though this 'missing law' constrains relationships between traits, and therefore can vastly reduce the number of uncertain parameters in ecosystem models, it has rarely been applied to DGVMs. Our recent research have shown that optimization- and trait-based models of gross primary production can be both much simpler and more accurate than current models based on fixed functional types, and that observed plant carbon allocations and distributions of plant functional traits are predictable with eco-evolutionary models. While there are also many other examples of the usefulness of these and other theoretical principles, it is not always straight-forward to make them operational in predictive models. In particular on longer time scales, the representation of functional diversity and the dynamical interactions among individuals and species presents a formidable challenge. Here we will present recent ideas on the use of adaptation and optimization principles in vegetation models, including examples of promising developments, but also limitations of the principles and some key challenges.

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

[Land use and land cover charnge (LUCC) and landscape service: Evaluation, mapping and modeling].

PubMed

Song, Zhang-jian; Cao, Yu; Tan, Yong-zhong; Chen, Xiao-dong; Chen, Xian-peng

2015-05-01

Studies on ecosystem service from landscape scale aspect have received increasing attention from researchers all over the world. Compared with ecosystem scale, it should be more suitable to explore the influence of human activities on land use and land cover change (LUCC), and to interpret the mechanisms and processes of sustainable landscape dynamics on landscape scale. Based on comprehensive and systematic analysis of researches on landscape service, this paper firstly discussed basic concepts and classification of landscape service. Then, methods of evaluation, mapping and modeling of landscape service were analyzed and concluded. Finally, future trends for the research on landscape service were proposed. It was put forward that, exploring further connotation and classification system of landscape service, improving methods and quantitative indicators for evaluation, mapping and modelling of landscape service, carrying out long-term integrated researches on landscape pattern-process-service-scale relationships and enhancing the applications of theories and methods on landscape economics and landscape ecology are very important fields of the research on landscape service in future.

Four decades of modeling methane cycling in terrestrial ecosystems: Where we are heading?

NASA Astrophysics Data System (ADS)

Xu, X.; Yuan, F.; Hanson, P. J.; Wullschleger, S. D.; Thornton, P. E.; Tian, H.; Riley, W. J.; Song, X.; Graham, D. E.; Song, C.

2015-12-01

A modeling approach to methane (CH4) is widely used to quantify the budget, investigate spatial and temporal variabilities, and understand the mechanistic processes and environmental controls on CH4 fluxes across spatial and temporal scales. Moreover, CH4 models are an important tool for integrating CH4 data from multiple sources, such as laboratory-based incubation and molecular analysis, field observational experiments, remote sensing, and aircraft-based measurements across a variety of terrestrial ecosystems. We reviewed 39 terrestrial CH4 models to characterize their strengths and weaknesses and to design a roadmap for future model improvement and application. We found that: (1) the focus of CH4 models have been shifted from theoretical to site- to regional-level application over the past four decades, expressed as dramatic increases in CH4 model development on regional budget quantification; (2) large discrepancies exist among models in terms of representing CH4 processes and their environmental controls; (3) significant data-model and model-model mismatches are partially attributed to different representations of wetland characterization and inundation dynamics. Three efforts should be paid special attention for future improvements and applications of fully mechanistic CH4 models: (1) CH4 models should be improved to represent the mechanisms underlying land-atmosphere CH4 exchange, with emphasis on improving and validating individual CH4 processes over depth and horizontal space; (2) models should be developed that are capable of simulating CH4 fluxes across space and time (particularly hot moments and hot spots); (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. A newly developed microbial functional group-based CH4 model (CLM-Microbe) was further used to demonstrate the features of mechanistic representation and integration with multiple source of observational datasets.

Input-decomposition balance of heterotrophic processes in a warm-temperate mixed forest in Japan

NASA Astrophysics Data System (ADS)

Jomura, M.; Kominami, Y.; Ataka, M.; Makita, N.; Dannoura, M.; Miyama, T.; Tamai, K.; Goto, Y.; Sakurai, S.

2010-12-01

Carbon accumulation in forest ecosystem has been evaluated using three approaches. One is net ecosystem exchange (NEE) estimated by tower flux measurement. The second is net ecosystem production (NEP) estimated by biometric measurements. NEP can be expressed as the difference between net primary production and heterotrophic respiration. NEP can also be expressed as the annual increment in the plant biomass (ΔW) plus soil (ΔS) carbon pools defined as follows; NEP = ΔW+ΔS The third approach needs to evaluate annual carbon increment in soil compartment. Soil carbon accumulation rate could not be measured directly in a short term because of the small amount of annual accumulation. Soil carbon accumulation rate can be estimated by a model calculation. Rothamsted carbon model is a soil organic carbon turnover model and a useful tool to estimate the rate of soil carbon accumulation. However, the model has not sufficiently included variations in decomposition processes of organic matters in forest ecosystems. Organic matter in forest ecosystems have a different turnover rate that creates temporal variations in input-decomposition balance and also have a large variation in spatial distribution. Thus, in order to estimate the rate of soil carbon accumulation, temporal and spatial variation in input-decomposition balance of heterotrophic processes should be incorporated in the model. In this study, we estimated input-decomposition balance and the rate of soil carbon accumulation using the modified Roth-C model. We measured respiration rate of many types of organic matters, such as leaf litter, fine root litter, twigs and coarse woody debris using a chamber method. We can illustrate the relation of respiration rate to diameter of organic matters. Leaf and fine root litters have no diameter, so assumed to be zero in diameter. Organic matters in small size, such as leaf and fine root litter, have high decomposition respiration. It could be caused by the difference in structure of organic matter. Because coarse woody debris has shape of cylinder, microbes decompose from the surface of it. Thus, respiration rate of coarse woody debris is lower than that of leaf and fine root litter. Based on this result, we modified Roth-C model and estimate soil carbon accumulation rate in recent years. Based on the results from a soil survey, the forest soil stored 30tC ha-1 in O and A horizon. We can evaluate the modified model using this result. NEP can be expressed as the annual increment in the plant biomass plus soil carbon pools. So if we can estimate NEP using this approach, then we can evaluate NEP estimated by micrometeorological and ecological approaches and reduce uncertainty of NEP estimation.

Lessons learned studying design issues for lunar and Mars settlements

NASA Technical Reports Server (NTRS)

Litton, C. E.

1997-01-01

In a study of lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues (mining, material processing, and manufacturing), and the human elements of physiology, behavior, and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the Earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models.

Lessons learned studying design issues for lunar and Mars settlements.

PubMed

Litton, C E

1997-01-01

In a study of lunar and Mars settlement concepts, an analysis was made of fundamental design assumptions in five technical areas against a model list of occupational and environmental health concerns. The technical areas included the proposed science projects to be supported, habitat and construction issues, closed ecosystem issues, the "MMM" issues (mining, material processing, and manufacturing), and the human elements of physiology, behavior, and mission approach. Four major lessons were learned. First it is possible to relate public health concerns to complex technological development in a proactive design mode, which has the potential for long-term cost savings. Second, it became very apparent that prior to committing any nation or international group to spending the billions to start and complete a lunar settlement, over the next century, that a significantly different approach must be taken from those previously proposed, to solve the closed ecosystem and "MMM" problems. Third, it also appears that the health concerns and technology issues to be addressed for human exploration into space are fundamentally those to be solved for human habitation of the Earth (as a closed ecosystem) in the 21st century. Finally, it is proposed that ecosystem design modeling must develop new tools, based on probabilistic models as a step up from closed circuit models.

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

NASA Astrophysics Data System (ADS)

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

2008-05-01

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

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.

Climate changes impact the surface albedo of a forest ecosystem based on MODIS satellite data

NASA Astrophysics Data System (ADS)

Zoran, M. A.; Nemuc, A. V.

2007-10-01

Surface albedo is one of the most important biophysical parameter responsible for energy balance control and the surface temperature and boundary-layer structure of the atmosphere. Forest land surface albedo is also highly variable temporally showing both diurnal as well as seasonal variations. In forest systems, albedo controls the microclimate conditions which affects ecosystem physical, physiological, and biogeochemical processes such as energy balance, evapotranspiration, photosynthesis. Due to anthropogenic and natural factors, land cover and land use changes result is the land surfaces albedo change. The main aim of this paper is to investigate the albedo patterns due to the impact of atmospheric pollution and climate variations of a forest ecosystem Branesti-Cernica, placed to the North-East of Bucharest city, Romania based on satellite Landsat ETM+, IKONOS and MODIS data and climate station observations. Our study focuses on 3 years of data (2003-2005), each of which had a different climatic regime. As the physical climate system is very sensitive to surface albedo, forest ecosystems could significantly feedback to the projected climate change modeling scenarios through albedo changes. The results of this research have a number of applications in weather forecasting, climate change, and forest ecosystem studies.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Inferring biogeochemistry past: a millennial-scale multimodel assimilation of multiple paleoecological proxies.

NASA Astrophysics Data System (ADS)

Dietze, M.; Raiho, A.; Fer, I.; Dawson, A.; Heilman, K.; Hooten, M.; McLachlan, J. S.; Moore, D. J.; Paciorek, C. J.; Pederson, N.; Rollinson, C.; Tipton, J.

2017-12-01

The pre-industrial period serves as an essential baseline against which we judge anthropogenic impacts on the earth's systems. However, direct measurements of key biogeochemical processes, such as carbon, water, and nutrient cycling, are absent for this period and there is no direct way to link paleoecological proxies, such as pollen and tree rings, to these processes. Process-based terrestrial ecosystem models provide a way to make inferences about the past, but have large uncertainties and by themselves often fail to capture much of the observed variability. Here we investigate the ability to improve inferences about pre-industrial biogeochemical cycles through the formal assimilation of proxy data into multiple process-based models. A Tobit ensemble filter with explicit estimation of process error was run at five sites across the eastern US for three models (LINKAGES, ED2, LPJ-GUESS). In addition to process error, the ensemble accounted for parameter uncertainty, estimated through the assimilation of the TRY and BETY trait databases, and driver uncertainty, accommodated by probabilistically downscaling and debiasing CMIP5 GCM output then filtering based on paleoclimate reconstructions. The assimilation was informed by four PalEON data products, each of which includes an explicit Bayesian error estimate: (1) STEPPS forest composition estimated from fossil pollen; (2) REFAB aboveground biomass (AGB) estimated from fossil pollen; (3) tree ring AGB and woody net primary productivity (wNPP); and (4) public land survey composition, stem density, and AGB. By comparing ensemble runs with and without data assimilation we are able to assess the information contribution of the proxy data to constraining biogeochemical fluxes, which is driven by the combination of model uncertainty, data uncertainty, and the strength of correlation between observed and unobserved quantities in the model ensemble. To our knowledge this is the first attempt at multi-model data assimilation with terrestrial ecosystem models. Results from the data-model assimilation allow us to assess the consistency across models in post-assimilation inferences about indirectly inferred quantities, such as GPP, soil carbon, and the water budget.

Mapping rice ecosystem dynamics and greenhouse gas emissions using multiscale imagery and biogeochemical models

NASA Astrophysics Data System (ADS)

Salas, W.; Torbick, N.

2017-12-01

Rice greenhouse gas (GHG) emissions in production hot spots have been mapped using multiscale satellite imagery and a processed-based biogeochemical model. The multiscale Synthetic Aperture Radar (SAR) and optical imagery were co-processed and fed into a machine leanring framework to map paddy attributes that are tuned using field observations and surveys. Geospatial maps of rice extent, crop calendar, hydroperiod, and cropping intensity were then used to parameterize the DeNitrification-DeComposition (DNDC) model to estimate emissions. Results, in the Red River Detla for example, show total methane emissions at 345.4 million kgCH4-C equivalent to 11.5 million tonnes CO2e (carbon dioxide equivalent). We further assessed the role of Alternative Wetting and Drying and the impact on GHG and yield across production hot spots with uncertainty estimates. The approach described in this research provides a framework for using SAR to derive maps of rice and landscape characteristics to drive process models like DNDC. These types of tools and approaches will support the next generation of Monitoring, Reporting, and Verification (MRV) to combat climate change and support ecosystem service markets.

Global and Time-Resolved Monitoring of Crop Photosynthesis with Chlorophyll Fluorescence

NASA Technical Reports Server (NTRS)

Guanter, Luis; Zhang, Yongguang; Jung, Martin; Joiner, Joanna; Voigt, Maximilian; Berry, Joseph A.; Frankenberg, Christian; Huete, Alfredo R.; Zarco-Tejada, Pablo; Lee, Jung-Eun;

Global and time-resolved monitoring of crop photosynthesis with chlorophyll fluorescence

PubMed Central

Guanter, Luis; Zhang, Yongguang; Jung, Martin; Joiner, Joanna; Voigt, Maximilian; Berry, Joseph A.; Frankenberg, Christian; Huete, Alfredo R.; Zarco-Tejada, Pablo; Lee, Jung-Eun; Moran, M. Susan; Ponce-Campos, Guillermo; Beer, Christian; Camps-Valls, Gustavo; Buchmann, Nina; Gianelle, Damiano; Klumpp, Katja; Cescatti, Alessandro; Baker, John M.; Griffis, Timothy J.

2014-01-01

Photosynthesis is the process by which plants harvest sunlight to produce sugars from carbon dioxide and water. It is the primary source of energy for all life on Earth; hence it is important to understand how this process responds to climate change and human impact. However, model-based estimates of gross primary production (GPP, output from photosynthesis) are highly uncertain, in particular over heavily managed agricultural areas. Recent advances in spectroscopy enable the space-based monitoring of sun-induced chlorophyll fluorescence (SIF) from terrestrial plants. Here we demonstrate that spaceborne SIF retrievals provide a direct measure of the GPP of cropland and grassland ecosystems. Such a strong link with crop photosynthesis is not evident for traditional remotely sensed vegetation indices, nor for more complex carbon cycle models. We use SIF observations to provide a global perspective on agricultural productivity. Our SIF-based crop GPP estimates are 50–75% higher than results from state-of-the-art carbon cycle models over, for example, the US Corn Belt and the Indo-Gangetic Plain, implying that current models severely underestimate the role of management. Our results indicate that SIF data can help us improve our global models for more accurate projections of agricultural productivity and climate impact on crop yields. Extension of our approach to other ecosystems, along with increased observational capabilities for SIF in the near future, holds the prospect of reducing uncertainties in the modeling of the current and future carbon cycle. PMID:24706867

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.

Year-round simulated methane emissions from a permafrost ecosystem in Northeast Siberia

NASA Astrophysics Data System (ADS)

Castro-Morales, Karel; Kleinen, Thomas; Kaiser, Sonja; Zaehle, Sönke; Kittler, Fanny; Kwon, Min Jung; Beer, Christian; Göckede, Mathias

2018-05-01

Wetlands of northern high latitudes are ecosystems highly vulnerable to climate change. Some degradation effects include soil hydrologic changes due to permafrost thaw, formation of deeper active layers, and rising topsoil temperatures that accelerate the degradation of permafrost carbon and increase in CO2 and CH4 emissions. In this work we present 2 years of modeled year-round CH4 emissions into the atmosphere from a Northeast Siberian region in the Russian Far East. We use a revisited version of the process-based JSBACH-methane model that includes four CH4 transport pathways: plant-mediated transport, ebullition and molecular diffusion in the presence or absence of snow. The gas is emitted through wetlands represented by grid cell inundated areas simulated with a TOPMODEL approach. The magnitude of the summertime modeled CH4 emissions is comparable to ground-based CH4 fluxes measured with the eddy covariance technique and flux chambers in the same area of study, whereas wintertime modeled values are underestimated by 1 order of magnitude. In an annual balance, the most important mechanism for transport of methane into the atmosphere is through plants (61 %). This is followed by ebullition ( ˜ 35 %), while summertime molecular diffusion is negligible (0.02 %) compared to the diffusion through the snow during winter ( ˜ 4 %). We investigate the relationship between temporal changes in the CH4 fluxes, soil temperature, and soil moisture content. Our results highlight the heterogeneity in CH4 emissions at landscape scale and suggest that further improvements to the representation of large-scale hydrological conditions in the model will facilitate a more process-oriented land surface scheme and better simulate CH4 emissions under climate change. This is especially necessary at regional scales in Arctic ecosystems influenced by permafrost thaw.

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.

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

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

Liu, Shaoqing; Zhuang, Qianlai; Chen, Min

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

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

DOE PAGES

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

2016-07-25

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

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

[New model of accumulation and agro-business: the ecological and epidemiological implications of the Ecuadorian cut flower production].

PubMed

Breilh, Jaime

2007-01-01

The article refers to the results of an integrative research project that aim to analyze ecosystem and human health's impacts of cut flower production in Cuencas del Rio Grande region (Cayambe and Tabacundo zones). In order to assess the complex object of study and its multiple dimensions, an interdisciplinary approach has been constructed, based on the following components: a) pesticides dynamics analysis; b) pesticides distribution and commercialization processes in the region; c) economic and anthropological transformation determinate by the flower production; d) epidemiological process of human health impacts; e) and the design of participatory, multicultural and integrative information. The research consolidated an important geo-codified data base on the impacts of cut flower production to workers, communities, aquatic systems and soils, offering evidences of the actual flower production system severe impacts and leading to a reflection about the sustainability of the productive systems and the future of the ecosystems.

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.

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

PubMed

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

2015-01-01

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

Strategy for modeling putative multilevel ecosystems on Europa.

PubMed

Irwin, Louis N; Schulze-Makuch, Dirk

2003-01-01

A general strategy for modeling ecosystems on other worlds is described. Two alternative biospheres beneath the ice surface of Europa are modeled, based on analogous ecosystems on Earth in potentially comparable habitats, with reallocation of biomass quantities consistent with different sources of energy and chemical constituents. The first ecosystem models a benthic biosphere supported by chemoautotrophic producers. The second models two concentrations of biota at the top and bottom of the subsurface water column supported by energy harvested from transmembrane ionic gradients. Calculations indicate the plausibility of both ecosystems, including small macroorganisms at the highest trophic levels, with ionotrophy supporting a larger biomass than chemoautotrophy.

Resilience of riverbed vegetation to uprooting by flow

NASA Astrophysics Data System (ADS)

Perona, P.; Crouzy, B.

2018-03-01

Riverine ecosystem biodiversity is largely maintained by ecogeomorphic processes including vegetation renewal via uprooting and recovery times to flow disturbances. Plant roots thus heavily contribute to engineering resilience to perturbation of such ecosystems. We show that vegetation uprooting by flow occurs as a fatigue-like mechanism, which statistically requires a given exposure time to imposed riverbed flow erosion rates before the plant collapses. We formulate a physically based stochastic model for the actual plant rooting depth and the time-to-uprooting, which allows us to define plant resilience to uprooting for generic time-dependent flow erosion dynamics. This theory shows that plant resilience to uprooting depends on the time-to-uprooting and that root mechanical anchoring acts as a process memory stored within the plant-soil system. The model is validated against measured data of time-to-uprooting of Avena sativa seedlings with various root lengths under different flow conditions. This allows for assessing the natural variance of the uprooting-by-flow process and to compute the prediction entropy, which quantifies the relative importance of the deterministic and the random components affecting the process.

Integrating Nutrient Enrichment and Forest Management Experiments in Sweden to Constrain the Process-Based Land Surface Model ORCHIDEE

NASA Astrophysics Data System (ADS)

Resovsky, A.; Luyssaert, S.; Guenet, B.; Peylin, P.; Lansø, A. S.; Vuichard, N.; Messina, P.; Smith, B.; Ryder, J.; Naudts, K.; Chen, Y.; Otto, J.; McGrath, M.; Valade, A.

2017-12-01

Understanding coupling between carbon (C) and nitrogen (N) cycling in forest ecosystems is key to predicting global change. Numerous experimental studies have demonstrated the positive response of stand-level photosynthesis and net primary production (NPP) to atmospheric CO2 enrichment, while N availability has been shown to exert an important control on the timing and magnitude of such responses. However, several factors complicate efforts to precisely represent ecosystem-level C and N cycling in the current generation of land surface models (LSMs), including sparse in-situ data, uncertainty with regard to key state variables and disregard for the effects of natural and anthropogenic forest management. In this study, we incorporate empirical data from N-fertilization experiments at two long-term manipulation sites in Sweden to improve the representation of C and N interaction in the ORCHIDEE land surface model. Our version of the model represents the union of two existing ORCHIDEE branches: 1) ORCHIDEE-CN, which resolves processes related to terrestrial C and N cycling, and 2) ORCHIDEE-CAN, which integrates a multi-layer canopy structure and includes representation of forest management practices. Using this new model branch (referred to as ORCHIDEE-CN-CAN), we aim to replicate the growth patterns of managed forests both with and without N limitations. Our hope is that the results, in combination with measurements of various ecosystem parameters (such as soil N) will facilitate LSM optimization, inform future model development, and reduce structural uncertainty in global change predictions.

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

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

From actors to agents in socio-ecological systems models

PubMed Central

Rounsevell, M. D. A.; Robinson, D. T.; Murray-Rust, D.

2012-01-01

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept. PMID:22144388

From actors to agents in socio-ecological systems models.

PubMed

Rounsevell, M D A; Robinson, D T; Murray-Rust, D

2012-01-19

The ecosystem service concept has emphasized the role of people within socio-ecological systems (SESs). In this paper, we review and discuss alternative ways of representing people, their behaviour and decision-making processes in SES models using an agent-based modelling (ABM) approach. We also explore how ABM can be empirically grounded using information from social survey. The capacity for ABM to be generalized beyond case studies represents a crucial next step in modelling SESs, although this comes with considerable intellectual challenges. We propose the notion of human functional types, as an analogy of plant functional types, to support the expansion (scaling) of ABM to larger areas. The expansion of scope also implies the need to represent institutional agents in SES models in order to account for alternative governance structures and policy feedbacks. Further development in the coupling of human-environment systems would contribute considerably to better application and use of the ecosystem service concept.

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.

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.

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.

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

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,...

Using model-data fusion to analyze the interannual variability of NEE of an alpine grassland

NASA Astrophysics Data System (ADS)

Scholz, Katharina; Hammerle, Albin; Hiltbrunner, Erika; Wohlfahrt, Georg

2017-04-01

To understand the processes and magnitude of carbon dynamics of the biosphere, modeling approaches are an important tool to analyze carbon budgets from regional to global scale. Here, a simple process-based ecosystem carbon model was used to investigate differences in CO2 fluxes of a high mountain grassland near Furka Pass in the Swiss central Alps at an elevation of about 2400 m a.s.l. during two growing seasons differing in snow melt date. Data on net ecosystem CO2 exchange (NEE) as well as meteorological conditions was available from 20.06.2013 - 08.10.2014 covering two snow free periods. The NEE data indicates that the carbon uptake during the growing season in 2013 was considerably lower than in 2014. To investigate whether the lower carbon uptake in 2013 was mainly due to the short growing season, an effect of biotic response to spring environmental conditions, or the direct effect of the weather conditions during the growing season, a modeling approach was applied. For this purpose, an ecosystem mass balance C model with 13 unknown parameters was constructed based on the DALEC model to represent the major C fluxes among six carbon pools (foliage, roots, necromass, litter, soil organic carbon and a labile pool to support leaf onset in spring) of the grassland ecosystem. Daily gross primary production was estimated by use of a sun/shade big-leaf model of canopy photosynthesis. By calibrating the model with NEE data from individual years, two sets of parameters were retrieved which were then used to run the model under environmental conditions of the same as well as the other year. The parameter estimation was done using DREAM, an algorithm for statistical inference of parameters using Bayesian statistics. In order to account for non-normality, heteroscedasticity and correlation of model residuals, a common problem in ecological modeling, a generalized likelihood function was applied. The results indicate that the late growing season start in 2013 led to a slower structural development of the grassland in the beginning. Nevertheless, maximum daily NEE values in 2013 were comparable to those in 2014. Moreover, the analysis showed that there was no direct effect of weather conditions during the snow free period. This indicates that the overall lower carbon uptake in 2013 was due to a slow start and the short growing season.

Potential effects of climate change on aquatic ecosystems of the Great Plains of North America

USGS Publications Warehouse

Covich, A.P.; Fritz, S.C.; Lamb, P.J.; Marzolf, R.D.; Matthews, W.J.; Poiani, K.A.; Prepas, E.E.; Richman, M.B.; Winter, T.C.

1997-01-01

The Great Plains landscape is less topographically complex than most other regions within North America, but diverse aquatic ecosystems, such as playas, pothole lakes, ox-bow lakes, springs, groundwater aquifers, intermittent and ephemeral streams, as well as large rivers and wetlands, are highly dynamic and responsive to extreme climatic fluctuations. We review the evidence for climatic change that demonstrates the historical importance of extremes in north-south differences in summer temperatures and east-west differences in aridity across four large subregions. These physical driving forces alter density stratification, deoxygenation, decomposition and salinity. Biotic community composition and associated ecosystem processes of productivity and nutrient cycling respond rapidly to these climatically driven dynamics. Ecosystem processes also respond to cultural effects such as dams and diversions of water for irrigation, waste dilution and urban demands for drinking water and industrial uses. Distinguishing climatic from cultural effects in future models of aquatic ecosystem functioning will require more refinement in both climatic and economic forecasting. There is a need, for example, to predict how long-term climatic forecasts (based on both ENSO and global warming simulations) relate to the permanence and productivity of shallow water ecosystems. Aquatic ecologists, hydrologists, climatologists and geographers have much to discuss regarding the synthesis of available data and the design of future interdisciplinary research. ?? 1997 by John Wiley & Sons, Ltd.

Seeking Energy System Pathways to Reduce Ozone Damage to Ecosystems through Adjoint-based Sensitivity Analysis

NASA Astrophysics Data System (ADS)

Capps, S. L.; Pinder, R. W.; Loughlin, D. H.; Bash, J. O.; Turner, M. D.; Henze, D. K.; Percell, P.; Zhao, S.; Russell, M. G.; Hakami, A.

2014-12-01

Tropospheric ozone (O3) affects the productivity of ecosystems in addition to degrading human health. Concentrations of this pollutant are significantly influenced by precursor gas emissions, many of which emanate from energy production and use processes. Energy system optimization models could inform policy decisions that are intended to reduce these harmful effects if the contribution of precursor gas emissions to human health and ecosystem degradation could be elucidated. Nevertheless, determining the degree to which precursor gas emissions harm ecosystems and human health is challenging because of the photochemical production of ozone and the distinct mechanisms by which ozone causes harm to different crops, tree species, and humans. Here, the adjoint of a regional chemical transport model is employed to efficiently calculate the relative influences of ozone precursor gas emissions on ecosystem and human health degradation, which informs an energy system optimization. Specifically, for the summer of 2007 the Community Multiscale Air Quality (CMAQ) model adjoint is used to calculate the location- and sector-specific influences of precursor gas emissions on potential productivity losses for the major crops and sensitive tree species as well as human mortality attributable to chronic ozone exposure in the continental U.S. The atmospheric concentrations are evaluated with 12-km horizontal resolution with crop production and timber biomass data gridded similarly. These location-specific factors inform the energy production and use technologies selected in the MARKet ALlocation (MARKAL) model.

Practical Strategies for Integrating Final Ecosystem Goods and ...

EPA Pesticide Factsheets

The concept of Final Ecosystem Goods and Services (FEGS) explicitly connects ecosystem services to the people that benefit from them. This report presents a number of practical strategies for incorporating FEGS, and more broadly ecosystem services, into the decision-making process. Whether a decision process is in early or late stages, or whether a process includes informal or formal decision analysis, there are multiple points where ecosystem services concepts can be integrated. This report uses Structured Decision Making (SDM) as an organizing framework to illustrate the role ecosystem services can play in a values-focused decision-process, including: • Clarifying the decision context: Ecosystem services can help clarify the potential impacts of an issue on natural resources together with their spatial and temporal extent based on supply and delivery of those services, and help identify beneficiaries for inclusion as stakeholders in the deliberative process. • Defining objectives and performance measures: Ecosystem services may directly represent stakeholder objectives, or may be means toward achieving other objectives. • Creating alternatives: Ecosystem services can bring to light creative alternatives for achieving other social, economic, health, or general well-being objectives. • Estimating consequences: Ecosystem services assessments can implement ecological production functions (EPFs) and ecological benefits functions (EBFs) to link decision alt

Riverine settlement in the evolution of prehistoric land-use systems in the Middle Rio Grande Valley, New Mexico

Treesearch

Joseph A. Tainter; Bonnie Bagley Tainter

1996-01-01

Ecosystem management should be based on the fullest possible knowledge of ecological structures and processes. In prehistoric North America, the involvement of Indian populations in ecosystem processes ranged from inadvertent alteration of the distribution and abundance of species to large-scale management of landscapes. The knowledge needed to manage ecosystems today...

Global climate change and terrestrial net primary production

NASA Technical Reports Server (NTRS)

Melillo, Jerry M.; Mcguire, A. D.; Kicklighter, David W.; Moore, Berrien, III; Vorosmarty, Charles J.; Schloss, Annette L.

1993-01-01

A process-based model was used to estimate global patterns of net primary production and soil nitrogen cycling for contemporary climate conditions and current atmospheric CO2 concentration. Over half of the global annual net primary production was estimated to occur in the tropics, with most of the production attributable to tropical evergreen forest. The effects of CO2 doubling and associated climate changes were also explored. The responses in tropical and dry temperate ecosystems were dominated by CO2, but those in northern and moist temperate ecosystems reflected the effects of temperature on nitrogen availability.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

1998-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data; (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC; (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Pre-Launch Tasks Proposed in our Contract of December 1991

NASA Technical Reports Server (NTRS)

Running, Steven W.; Nemani, Ramakrishna R.; Glassy, Joseph

1997-01-01

We propose, during the pre-EOS phase to: (1) develop, with other MODIS Team Members, a means of discriminating different major biome types with NDVI and other AVHRR-based data. (2) develop a simple ecosystem process model for each of these biomes, BIOME-BGC (3) relate the seasonal trend of weekly composite NDVI to vegetation phenology and temperature limits to develop a satellite defined growing season for vegetation; and (4) define physiologically based energy to mass conversion factors for carbon and water for each biome. Our final core at-launch product will be simplified, completely satellite driven biome specific models for net primary production. We will build these biome specific satellite driven algorithms using a family of simple ecosystem process models as calibration models, collectively called BIOME-BGC, and establish coordination with an existing network of ecological study sites in order to test and validate these products. Field datasets will then be available for both BIOME-BGC development and testing, use for algorithm developments of other MODIS Team Members, and ultimately be our first test point for MODIS land vegetation products upon launch. We will use field sites from the National Science Foundation Long-Term Ecological Research network, and develop Glacier National Park as a major site for intensive validation.

Assimilation of remote sensing data into a process-based ecosystem model for monitoring changes of soil water content in croplands

NASA Astrophysics Data System (ADS)

Ju, Weimin; Gao, Ping; Wang, Jun; Li, Xianfeng; Chen, Shu

2008-10-01

Soil water content (SWC) is an important factor affecting photosynthesis, growth, and final yields of crops. The information on SWC is of importance for mitigating the reduction of crop yields caused by drought through proper agricultural water management. A variety of methodologies have been developed to estimate SWC at local and regional scales, including field sampling, remote sensing monitoring and model simulations. The reliability of regional SWC simulation depends largely on the accuracy of spatial input datasets, including vegetation parameters, soil and meteorological data. Remote sensing has been proved to be an effective technique for controlling uncertainties in vegetation parameters. In this study, the vegetation parameters (leaf area index and land cover type) derived from the Moderate Resolution Imaging Spectrometer (MODIS) were assimilated into a process-based ecosystem model BEPS for simulating the variations of SWC in croplands of Jiangsu province, China. Validation shows that the BEPS model is able to capture 81% and 83% of across-site variations of SWC at 10 and 20 cm depths during the period from September to December, 2006 when a serous autumn drought occurred. The simulated SWC responded the events of rainfall well at regional scale, demonstrating the usefulness of our methodology for SWC and practical agricultural water management at large scales.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Fogwater deposition modeling for terrestrial ecosystems: A review of developments and measurements

NASA Astrophysics Data System (ADS)

Katata, Genki

2014-07-01

Recent progress in modeling fogwater (and low cloud water) deposition over terrestrial ecosystems during fogwater droplet interception by vegetative surfaces is reviewed. Several types of models and parameterizations for fogwater deposition are discussed with comparing assumptions, input parameter requirements, and modeled processes. The relationships among deposition velocity of fogwater (Vd) in model results, wind speed, and plant species structures associated with literature values are gathered for model validation. Quantitative comparisons between model results and observations in forest environments revealed differences as large as 2 orders of magnitude, which are likely caused by uncertainties in measurement techniques over heterogeneous landscapes. Results from the literature review show that Vd values ranged from 2.1 to 8.0 cm s-1 for short vegetation, whereas Vd = 7.7-92 cm s-1 and 0-20 cm s-1 for forests measured by throughfall-based methods and the eddy covariance method, respectively. This review also discusses the current understanding of the impacts of fogwater deposition on atmosphere-land interactions and over complex terrain based on results from numerical studies. Lastly, future research priorities in innovative modeling and observational approaches for model validation are outlined.

Evaluating the ecosystem water use efficiency and gross primary productivity in boreal forest based on tree ring data

NASA Astrophysics Data System (ADS)

Liu, S.; Zhuang, Q.

2016-12-01

Climatic change affects the plant physiological and biogeochemistry processes, and therefore on the ecosystem water use efficiency (WUE). Therefore, a comprehensive understanding of WUE would help us understand the adaptability of ecosystem to variable climate conditions. Tree ring data have great potential in addressing the forest response to climatic changes compared with mechanistic model simulations, eddy flux measurement and manipulative experiments. Here, we collected the tree ring isotopic carbon data in 12 boreal forest sites to develop a multiple linear regression model, and the model was extrapolated to the whole boreal region to obtain the WUE spatial and temporal variation from 1948 to 2010. Two algorithms were also used to estimate the inter-annual gross primary productivity (GPP) based on our derived WUE. Our results demonstrated that most of boreal regions showed significant increasing WUE trend during the period except parts of Alaska. The spatial averaged annual mean WUE was predicted to increase by 13%, from 2.3±0.4 g C kg-1 H2O at 1948 to 2.6±0.7 g C kg-1 H2O at 2012, which was much higher than other land surface models. Our predicted GPP by the WUE definition algorithm was comparable with site observation, while for the revised light use efficiency algorithm, GPP estimation was higher than site observation as well as than land surface models. In addition, the increasing GPP trends by two algorithms were similar with land surface model simulations. This is the first study to evaluate regional WUE and GPP in forest ecosystem based on tree ring data and future work should consider other variables (elevation, nitrogen deposition) that influence tree ring isotopic signals and the dual-isotope approach may help improve predicting the inter-annual WUE variation.

Full uncertainty quantification of N2O and NO emissions using the biogeochemical model LandscapeDNDC on site and regional scale

NASA Astrophysics Data System (ADS)

Haas, Edwin; Santabarbara, Ignacio; Kiese, Ralf; Butterbach-Bahl, Klaus

2017-04-01

Numerical simulation models are increasingly used to estimate greenhouse gas emissions at site to regional / national scale and are outlined as the most advanced methodology (Tier 3) in the framework of UNFCCC reporting. Process-based models incorporate the major processes of the carbon and nitrogen cycle of terrestrial ecosystems and are thus thought to be widely applicable at various conditions and spatial scales. Process based modelling requires high spatial resolution input data on soil properties, climate drivers and management information. The acceptance of model based inventory calculations depends on the assessment of the inventory's uncertainty (model, input data and parameter induced uncertainties). In this study we fully quantify the uncertainty in modelling soil N2O and NO emissions from arable, grassland and forest soils using the biogeochemical model LandscapeDNDC. We address model induced uncertainty (MU) by contrasting two different soil biogeochemistry modules within LandscapeDNDC. The parameter induced uncertainty (PU) was assessed by using joint parameter distributions for key parameters describing microbial C and N turnover processes as obtained by different Bayesian calibration studies for each model configuration. Input data induced uncertainty (DU) was addressed by Bayesian calibration of soil properties, climate drivers and agricultural management practices data. For the MU, DU and PU we performed several hundred simulations each to contribute to the individual uncertainty assessment. For the overall uncertainty quantification we assessed the model prediction probability, followed by sampled sets of input datasets and parameter distributions. Statistical analysis of the simulation results have been used to quantify the overall full uncertainty of the modelling approach. With this study we can contrast the variation in model results to the different sources of uncertainties for each ecosystem. Further we have been able to perform a fully uncertainty analysis for modelling N2O and NO emissions from arable, grassland and forest soils necessary for the comprehensibility of modelling results. We have applied the methodology to a regional inventory to assess the overall modelling uncertainty for a regional N2O and NO emissions inventory for the state of Saxony, Germany.

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...

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 N Cycling during Succession after Forest Disturbance: an Analysis of N Mining and Retention Hypothesis

NASA Astrophysics Data System (ADS)

Zhou, Z.; Ollinger, S. V.; Ouimette, A.; Lovett, G. M.; Fuss, C. B.; Goodale, C. L.

2017-12-01

Dissolved inorganic nitrogen losses at the Hubbard Brook Experimental Forest (HBEF), New Hampshire, USA, have declined in recent decades, a pattern that counters expectations based on prevailing theory. An unbalanced ecosystem nitrogen (N) budget implies there is a missing component for N sink. Hypotheses to explain this discrepancy include increasing rates of denitrification and accumulation of N in mineral soil pools following N mining by plants. Here, we conducted a modeling analysis fused with field measurements of N cycling, specifically examining the hypothesis relevant to N mining and retention in mineral soils. We included simplified representations of both mechanisms, N mining and retention, in a revised ecosystem process model, PnET-SOM, to evaluate the dynamics of N cycling during succession after forest disturbance at the HBEF. The predicted N mining during the early succession was regulated by a metric representing a potential demand of extra soil N for large wood growth. The accumulation of nitrate in mineral soil pools was a function of the net aboveground biomass accumulation and soil N availability and parameterized based on field 15N tracer incubation data. The predicted patterns of forest N dynamics were consistent with observations. The addition of the new algorithms also improved the predicted DIN export in stream water with an R squared of 0.35 (P<0.01) aganist observations. Predicted mining processes had an average rate of 7.4 kgNha-1yr-1 and Predicted rates of N retention processes were 5.2 kgNha-1yr-1, both of which were in line with estimates only based on field data. The predicted trend of low DIN export could continue for another 70 years to pay back the mined N in mineral soils. Predicted ecosystem N balance showed that N gas loss could account for 14-46% of the total N deposition, the soil mining about 103% during the early succession, and soil retention about 35% at the current forest stage at the HBEF.

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…

Transitions in Arctic ecosystems: Ecological implications of a changing hydrological regime

NASA Astrophysics Data System (ADS)

Wrona, Frederick J.; Johansson, Margareta; Culp, Joseph M.; Jenkins, Alan; Mârd, Johanna; Myers-Smith, Isla H.; Prowse, Terry D.; Vincent, Warwick F.; Wookey, Philip A.

2016-03-01

Numerous international scientific assessments and related articles have, during the last decade, described the observed and potential impacts of climate change as well as other related environmental stressors on Arctic ecosystems. There is increasing recognition that observed and projected changes in freshwater sources, fluxes, and storage will have profound implications for the physical, biogeochemical, biological, and ecological processes and properties of Arctic terrestrial and freshwater ecosystems. However, a significant level of uncertainty remains in relation to forecasting the impacts of an intensified hydrological regime and related cryospheric change on ecosystem structure and function. As the terrestrial and freshwater ecology component of the Arctic Freshwater Synthesis, we review these uncertainties and recommend enhanced coordinated circumpolar research and monitoring efforts to improve quantification and prediction of how an altered hydrological regime influences local, regional, and circumpolar-level responses in terrestrial and freshwater systems. Specifically, we evaluate (i) changes in ecosystem productivity; (ii) alterations in ecosystem-level biogeochemical cycling and chemical transport; (iii) altered landscapes, successional trajectories, and creation of new habitats; (iv) altered seasonality and phenological mismatches; and (v) gains or losses of species and associated trophic interactions. We emphasize the need for developing a process-based understanding of interecosystem interactions, along with improved predictive models. We recommend enhanced use of the catchment scale as an integrated unit of study, thereby more explicitly considering the physical, chemical, and ecological processes and fluxes across a full freshwater continuum in a geographic region and spatial range of hydroecological units (e.g., stream-pond-lake-river-near shore marine environments).

The methane sink associated to soils of natural and agricultural ecosystems in Italy.

PubMed

Castaldi, Simona; Costantini, Massimo; Cenciarelli, Pietro; Ciccioli, Paolo; Valentini, Riccardo

2007-01-01

In the present work, the CH4 sink associated to Italian soils was calculated by using a process-based model controlled by gas diffusivity and microbial activity, which was run by using a raster-based geographical information system. Georeferenced data included land cover CLC2000, soil properties from the European Soil Database, climatic data from the MARS-STAT database, plus several derived soils properties based on published algorithms applied to the above mentioned databases. Overall CH4 consumption from natural and agricultural sources accounted for a total of 43.3 Gg CH4 yr(-1), with 28.1 Gg CH4 yr(-1) removed in natural ecosystems and 15.1 Gg CH4 yr(-1) in agricultural ecosystems. The highest CH4 uptake rates were obtained for natural areas of Southern Apennines and islands of Sardinia and Sicily, and were mainly associated to areas covered by sclerophyllous vegetation (259.7+/-30.2 mg CH4 m(-2) yr(-1)) and broad-leaved forest (237.5 mg CH4 m(-2) yr(-1)). In terms of total sink strength broad-leaved forests were the dominant ecosystem. The overall contribution of each ecosystem type to the whole CH4 sink depended on the total area covered by the specific ecosystem and on its exact geographic distribution. The latter determines the type of climate present in the area and the dominant soil type, both factors which showed to have a strong influence on CH4 uptake rates. The aggregated CH4 sink, calculated for natural ecosystems present in the Italian region, is significantly higher than previously reported estimates, which were extrapolated from fluxes measured in other temperate ecosystems.

Seasonal carbon fluxes for an old-growth temperate forest inferred from carbonyl sulphide

NASA Astrophysics Data System (ADS)

Rastogi, Bharat; Jiang, Yueyang; Berkelhammer, Maxwell; Wharton, Sonia; Noone, David; Still, Christopher

2017-04-01

Characterizing and quantifying the processes that control terrestrial ecosystem exchanges of carbon and water are critical for understanding how forested ecosystems respond to a changing climate. A small but increasing number of studies has identified carbonyl sulfide (OCS) as a potential tracer of canopy photosynthesis and stomatal function. Here we present seasonal fluxes of OCS from a 60m tall old-growth temperate forest. An off-axis integrated cavity output spectroscopy analyzer (Los Gatos Research Inc.) was deployed at the Wind River Experimental Forest in Washington (45.8205°N, 121.9519°W) in 2014 and 2015. GPP (Gross Primary Production) is inferred from OCS fluxes and compared with estimates derived from measurements of NEE (Net Ecosystem Exchange) from eddy flux data as well as GPP predictions using a process based model. Our findings seek to resolve scientific questions regarding ecosystem carbon exchange from tall old growth forests, which have a complicated vertical leaf area structure, high above ground biomass and amount and aerial cover of epiphytic vegetation. Estimates of canopy conductance calculated using tower flux data are also combined with measurements of stable isotopologues of CO2 to infer emergent ecosystem properties such as canopy ci/ca and water use efficiency.

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 New Perspective on the Foraging Ecology of Apex Predators in the California Current: Results from a Fully Coupled Ecosystem Model

NASA Astrophysics Data System (ADS)

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

2016-02-01

Results from a fully coupled end-to-end ecosystem model for the California Current Large Marine Ecosystem are used to describe the impact of environmental variability on the foraging ecology of its most abundant apex predator, California sea lions (Zalophus californianus). The ecosystem model consists of a biogeochemical submodel embedded in a regional ocean circulation submodel, and both coupled with a multi-species individual-based submodel for forage fish (sardine and anchovy) and California sea lions. For sea lions, bioenergetics and behavioral attributes are specified using available TOPP (Tagging Of Pacific Predators) data on their foraging patterns and diet in the California Current. Sardine and anchovy are explicitly included in the model as they represent important prey sources for California sea lions and exhibit significant interannual and decadal variability in population abundances. Output from a 20-year run (1989-2008) of the model demonstrates how different physical and biological processes control habitat utilization and foraging success of California sea lions on interannual time scales. A principal component analysis of sea lion foraging patterns indicates that the first mode of variability is alongshore and tied to sardine availability, while the second mode is cross-shore and associated with coastal upwelling intensity (a behavior consistent with male sea lion tracking data collected in 2004 vs. 2005). The results also illustrate how variability in environmental conditions and forage fish distribution affects sea lions feeding success. While specifically focusing on the foraging ecology of sea lions, our modeling framework has the ability to provide new and unique perspectives on trophic interactions in the California Current, or other regions where similar end-to-end ecosystem models may be implemented.

Southwest Ecosystem Services Project (SwESP): Identifying Ecosystems Services Based on Tribal Values

EPA Science Inventory

USEPA Office of Research Development (ORD) new strategic focus is the measurement of benefits and services of ecosystem. The primary objective of the Ecosystem Services Research Program (ESRP) is to identify, measure, monitor, model and map ecosystem services and to enable their ...

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...

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

PubMed

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

2013-01-01

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

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

PubMed

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

2012-03-01

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

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...

Chesapeake Bay Forecast System: Oxygen Prediction for the Sustainable Ecosystem Management

NASA Astrophysics Data System (ADS)

Mathukumalli, B.; Long, W.; Zhang, X.; Wood, R.; Murtugudde, R. G.

2010-12-01

The Chesapeake Bay Forecast System (CBFS) is a flexible, end-to-end expert prediction tool for decision makers that will provide customizable, user-specified predictions and projections of the region’s climate, air and water quality, local chemistry, and ecosystems at days to decades. As a part of CBFS, the long-term water quality data were collected and assembled to develop ecological models for the sustainable management of the Chesapeake Bay. Cultural eutrophication depletes oxygen levels in this ecosystem particularly in summer which has several negative implications on the structure and function of ecosystem. In order to understand dynamics and prediction of spatially-explicit oxygen levels in the Bay, an empirical process based ecological model is developed with long-term control variables (water temperature, salinity, nitrogen and phosphorus). Statistical validation methods were employed to demonstrate usability of predictions for management purposes and the predicted oxygen levels are quite faithful to observations. The predicted oxygen values and other physical outputs from downscaling of regional weather and climate predictions, or forecasts from hydrodynamic models can be used to forecast various ecological components. Such forecasts would be useful for both recreational and commercial users of the bay (for example, bass fishing). Furthermore, this work can also be used to predict extent of hypoxia/anoxia not only from anthropogenic nutrient pollution, but also from global warming. Some hindcasts and forecasts are discussed along with the ongoing efforts at a mechanistic ecosystem model to provide prognostic oxygen predictions and projections and upper trophic modeling using an energetics approach.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

The influence of competition between plant functional types in the Canadian Terrestrial Ecosystem Model (CTEM) v. 2.0

NASA Astrophysics Data System (ADS)

Melton, Joe; Arora, Vivek

2015-04-01

The Canadian Terrestrial Ecosystem Model (CTEM) is the interactive vegetation component in the earth system modelling framework of the Canadian Centre for Climate Modelling and Analysis (CCCma). In its current framework, CTEM uses prescribed fractional coverage of plant functional types (PFTs) in each grid cell. In reality, vegetation cover is continually adjusting to changes in climate, atmospheric composition, and anthropogenic forcing, for example, through human-caused fires and CO2 fertilization. These changes in vegetation spatial patterns occur over timescales of years to centuries as tree migration is a slow process and vegetation distributions inherently have inertia. Here, we present version 2.0 of CTEM that includes a representation of competition between PFTs through a modified version of the Lotka-Volterra (L-V) predator-prey equations. The simulated areal extents of CTEM's seven non-crop PFTs are compared with available observation-based estimates, and simulations using unmodified L-V equations (similar to other models like TRIFFID), to demonstrate that the model is able to represent the broad spatial distributions of its seven PFTs at the global scale. Differences remain, however, since representing the multitude of plant species with just seven non-crop PFTs only allows the large scale climatic controls on the distributions of PFTs to be captured. As expected, PFTs that exist in climate niches are difficult to represent either due to the coarse spatial resolution of the model and the corresponding driving climate or the limited number of PFTs used to model the terrestrial ecosystem processes. The geographic and zonal distributions of primary terrestrial carbon pools and fluxes from the versions of CTEM that use prescribed and dynamically simulated fractional coverage of PFTs compare reasonably with each other and observation-based estimates. These results illustrate that the parametrization of competition between PFTs in CTEM behaves in a reasonably realistic manner while the use of unmodified L-V equations results in unrealistic plant distributions.

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

NASA Astrophysics Data System (ADS)

Thomas, R. Q.; Williams, M.

2014-09-01

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

Constraining ecosystem processes from tower fluxes and atmospheric profiles.

PubMed

Hill, T C; Williams, M; Woodward, F I; Moncrieff, J B

2011-07-01

The planetary boundary layer (PBL) provides an important link between the scales and processes resolved by global atmospheric sampling/modeling and site-based flux measurements. The PBL is in direct contact with the land surface, both driving and responding to ecosystem processes. Measurements within the PBL (e.g., by radiosondes, aircraft profiles, and flask measurements) have a footprint, and thus an integrating scale, on the order of 1-100 km. We use the coupled atmosphere-biosphere model (CAB) and a Bayesian data assimilation framework to investigate the amount of biosphere process information that can be inferred from PBL measurements. We investigate the information content of PBL measurements in a two-stage study. First, we demonstrate consistency between the coupled model (CAB) and measurements, by comparing the model to eddy covariance flux tower measurements (i.e., water and carbon fluxes) and also PBL scalar profile measurements (i.e., water, carbon dioxide, and temperature) from Canadian boreal forest. Second, we use the CAB model in a set of Bayesian inversions experiments using synthetic data for a single day. In the synthetic experiment, leaf area and respiration were relatively well constrained, whereas surface albedo and plant hydraulic conductance were only moderately constrained. Finally, the abilities of the PBL profiles and the eddy covariance data to constrain the parameters were largely similar and only slightly lower than the combination of both observations.

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.

Rewilding as nature based solution in land management

NASA Astrophysics Data System (ADS)

Novara, Agata; Gristina, Luciano; Keesstra, Saskia; Pereira, Paulo; Cerda, Artemio

2017-04-01

Rewilding is an effective tool of ecological restoration and a nature based solution for hydro-meteorological risk control. Rewilding contributes to reduce flood risk, resist droughts, helps to restore soil organic matter content, increases soil and plant biodiversity, improves the overall ecosystem and human health. The key element of rewilding is not the nature control, but following the natural processes to restore the key soil ecological factors and their connectivity. Rewilding can be applicable at different ecosystem stages, from natural reserve to more anthropogenic system such as agricultural land through the restoration of wild soil function trough permaculture or forest farming. The proposed nature based solution not only avoid the investment in traditional engineering but it also an opportunities for creating new economics model based on wild nature (ecoturism, education, wild edible plants). This work is a review of applied rewilding actions and considerations on future nature based solutions applications will be discussed .

Consumer trophic diversity as a fundamental mechanism linking predation and ecosystem functioning.

PubMed

Hines, Jes; Gessner, Mark O

2012-11-01

1. Primary production and decomposition, two fundamental processes determining the functioning of ecosystems, may be sensitive to changes in biodiversity and food web interactions. 2. The impacts of food web interactions on ecosystem functioning are generally quantified by experimentally decoupling these linked processes and examining either primary production-based (green) or decomposition-based (brown) food webs in isolation. This decoupling may strongly limit our ability to assess the importance of food web interactions on ecosystem processes. 3. To evaluate how consumer trophic diversity mediates predator effects on ecosystem functioning, we conducted a mesocosm experiment and a field study using an assemblage of invertebrates that naturally co-occur on North Atlantic coastal saltmarshes. We measured the indirect impact of predation on primary production and leaf decomposition as a result of prey communities composed of herbivores alone, detritivores alone or both prey in combination. 4. We find that primary consumers can influence ecosystem process rates not only within, but also across green and brown sub-webs. Moreover, by feeding on a functionally diverse consumer assemblage comprised of both herbivores and detritivores, generalist predators can diffuse consumer effects on decomposition, primary production and feedbacks between the two processes. 5. These results indicate that maintaining functional diversity among primary consumers can alter the consequences of traditional trophic cascades, and they emphasize the role of the detritus-based sub-web when seeking key biotic drivers of plant production. Clearly, traditional compartmentalization of empirical food webs can limit our ability to predict the influence of food web interactions on ecosystem functioning. © 2012 The Authors. Journal of Animal Ecology © 2012 British Ecological Society.

The large mean body size of mammalian herbivores explains the productivity paradox during the Last Glacial Maximum.

PubMed

Zhu, Dan; Ciais, Philippe; Chang, Jinfeng; Krinner, Gerhard; Peng, Shushi; Viovy, Nicolas; Peñuelas, Josep; Zimov, Sergey

2018-04-01

Large herbivores are a major agent in ecosystems, influencing vegetation structure, and carbon and nutrient flows. During the last glacial period, a mammoth steppe ecosystem prevailed in the unglaciated northern lands, supporting a high diversity and density of megafaunal herbivores. The apparent discrepancy between abundant megafauna and the expected low vegetation productivity under a generally harsher climate with a lower CO 2 concentration, termed the productivity paradox, requires large-scale quantitative analysis using process-based ecosystem models. However, most of the current global dynamic vegetation models (DGVMs) lack explicit representation of large herbivores. Here we incorporated a grazing module in a DGVM based on physiological and demographic equations for wild large grazers, taking into account feedbacks of large grazers on vegetation. The model was applied globally for present-day and the Last Glacial Maximum (LGM). The present-day results of potential grazer biomass, combined with an empirical land-use map, infer a reduction in wild grazer biomass by 79-93% owing to anthropogenic land replacement of natural grasslands. For the LGM, we find that the larger mean body size of mammalian herbivores than today is the crucial clue to explain the productivity paradox, due to a more efficient exploitation of grass production by grazers with a large body size.

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

Broad-scale climate influences on spring-spawning herring (Clupea harengus, L.) recruitment in the Western Baltic Sea.

PubMed

Gröger, Joachim P; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea.

Broad-Scale Climate Influences on Spring-Spawning Herring (Clupea harengus, L.) Recruitment in the Western Baltic Sea

PubMed Central

Gröger, Joachim P.; Hinrichsen, Hans-Harald; Polte, Patrick

2014-01-01

Climate forcing in complex ecosystems can have profound implications for ecosystem sustainability and may thus challenge a precautionary ecosystem management. Climatic influences documented to affect various ecological functions on a global scale, may themselves be observed on quantitative or qualitative scales including regime shifts in complex marine ecosystems. This study investigates the potential climatic impact on the reproduction success of spring-spawning herring (Clupea harengus) in the Western Baltic Sea (WBSS herring). To test for climate effects on reproduction success, the regionally determined and scientifically well-documented spawning grounds of WBSS herring represent an ideal model system. Climate effects on herring reproduction were investigated using two global indices of atmospheric variability and sea surface temperature, represented by the North Atlantic Oscillation (NAO) and the Atlantic Multi-decadal Oscillation (AMO), respectively, and the Baltic Sea Index (BSI) which is a regional-scale atmospheric index for the Baltic Sea. Moreover, we combined a traditional approach with modern time series analysis based on a recruitment model connecting parental population components with reproduction success. Generalized transfer functions (ARIMAX models) allowed evaluating the dynamic nature of exogenous climate processes interacting with the endogenous recruitment process. Using different model selection criteria our results reveal that in contrast to NAO and AMO, the BSI shows a significant positive but delayed signal on the annual dynamics of herring recruitment. The westward influence of the Siberian high is considered strongly suppressing the influence of the NAO in this area leading to a higher explanatory power of the BSI reflecting the atmospheric pressure regime on a North-South transect between Oslo, Norway and Szczecin, Poland. We suggest incorporating climate-induced effects into stock and risk assessments and management strategies as part of the EU ecosystem approach to support sustainable herring fisheries in the Western Baltic Sea. PMID:24586279

Multiple hypotheses testing of fish incidence patterns in an urbanized ecosystem

USGS Publications Warehouse

Chizinski, C.J.; Higgins, C.L.; Shavlik, C.E.; Pope, K.L.

2006-01-01

Ecological and evolutionary theories have focused traditionally on natural processes with little attempt to incorporate anthropogenic influences despite the fact that humans are such an integral part of virtually all ecosystems. A series of alternate models that incorporated anthropogenic factors and traditional ecological mechanisms of invasion to account for fish incidence patterns in urban lakes was tested. The models were based on fish biology, human intervention, and habitat characteristics. However, the only models to account for empirical patterns were those that included fish invasiveness, which incorporated species-specific information about overall tolerance and fecundity. This suggests that species-specific characteristics are more important in general distributional patterns than human-mediated dispersal. Better information of illegal stocking activities is needed to improve human-mediated models, and more insight into basic life history of ubiquitous species is needed to truly understand underlying mechanisms of biotic homogenization. ?? Springer 2005.

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.

An Evidence-Based Evaluation of the Cumulative Effects of Tidal Freshwater and Estuarine Ecosystem Restoration on Endangered Juvenile Salmon in the Columbia River: Final Report

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

Diefenderfer, Heida L.; Johnson, Gary E.; Thom, Ronald M.

The listing of 13 salmon and steelhead stocks in the Columbia River basin (hereafter collectively referred to as “salmon”) under the Endangered Species Act of 1973, as amended, has stimulated tidal wetland restoration in the lower 235 kilometers of the Columbia River and estuary for juvenile salmon habitat functions. The purpose of the research reported herein was to evaluate the effect on listed salmon of the restoration effort currently being conducted under the auspices of the federal Columbia Estuary Ecosystem Restoration Program (CEERP). Linking changes in the quality and landscape pattern of tidal wetlands in the lower Columbia River andmore » estuary (LCRE) to salmon recovery is a complex problem because of the characteristics of the ecosystem, the salmon, the restoration actions, and available sampling technologies. Therefore, we designed an evidence-based approach to develop, synthesize, and evaluate information to determine early-stage (~10 years) outcomes of the CEERP. We developed an ecosystem conceptual model and from that, a primary hypothesis that habitat restoration activities in the LCRE have a cumulative beneficial effect on juvenile salmon. There are two necessary conditions of the hypothesis: • habitat-based indicators of ecosystem controlling factors, processes, and structures show positive effects from restoration actions, and • fish-based indicators of ecosystem processes and functions show positive effects from restoration actions and habitats undergoing restoration. Our evidence-based approach to evaluate the primary hypothesis incorporated seven lines of evidence, most of which are drawn from the LCRE. The lines of evidence are spatial and temporal synergies, cumulative net ecosystem improvement, estuary-wide meta-analysis, offsite benefits to juvenile salmon, landscape condition evaluation, and evidence-based scoring of global literature. The general methods we used to develop information for the lines of evidence included field measurements, data analyses, modeling, meta-analysis, and reanalysis of previously collected data sets. We identified a set of 12 ancillary hypotheses regarding habitat and salmon response. Each ancillary hypothesis states that the response metric will trend toward conditions at relatively undisturbed reference sites. We synthesized the evidence for and against the two necessary conditions by using eleven causal criteria: strength, consistency, specificity, temporality, biological gradient, plausibility, coherence, experiment, analogy, complete exposure pathway, and predictive performance. Our final evaluation included cumulative effects assessment because restoration is occurring at multiple sites and the collective effect is important to salmon recovery. We concluded that all five lines of evidence from the LCRE indicated positive habitat-based and fish-based responses to the restoration performed under the CEERP, although tide gate replacements on small sloughs were an exception. Our analyses suggested that hydrologic reconnections restore access for fish to move into a site to find prey produced there. Reconnections also restore the potential for the flux of prey from the site to the main stem river, where our data show that they are consumed by salmon. We infer that LCRE ecosystem restoration supports increased juvenile salmon growth and enhanced fitness (condition), thereby potentially improving survival rates during the early ocean stage.« less

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.

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...

Assessing the vulnerability of human and biological communities to changing ecosystem services using a GIS-based multi-criteria decision support tool

USGS Publications Warehouse

Villarreal, Miguel; Norman, Laura M.; Labiosa, William B.

2012-01-01

In this paper we describe an application of a GIS-based multi-criteria decision support web tool that models and evaluates relative changes in ecosystem services to policy and land management decisions. The Santa Cruz Watershed Ecosystem Portfolio (SCWEPM) was designed to provide credible forecasts of responses to ecosystem drivers and stressors and to illustrate the role of land use decisions on spatial and temporal distributions of ecosystem services within a binational (U.S. and Mexico) watershed. We present two SCWEPM sub-models that when analyzed together address bidirectional relationships between social and ecological vulnerability and ecosystem services. The first model employs the Modified Socio-Environmental Vulnerability Index (M-SEVI), which assesses community vulnerability using information from U.S. and Mexico censuses on education, access to resources, migratory status, housing situation, and number of dependents. The second, relating land cover change to biodiversity (provisioning services), models changes in the distribution of terrestrial vertebrate habitat based on multitemporal vegetation and land cover maps, wildlife habitat relationships, and changes in land use/land cover patterns. When assessed concurrently, the models exposed some unexpected relationships between vulnerable communities and ecosystem services provisioning. For instance, the most species-rich habitat type in the watershed, Desert Riparian Forest, increased over time in areas occupied by the most vulnerable populations and declined in areas with less vulnerable populations. This type of information can be used to identify ecological conservation and restoration targets that enhance the livelihoods of people in vulnerable communities and promote biodiversity and ecosystem health.

A coupled modeling framework for sustainable watershed management in transboundary river basins

NASA Astrophysics Data System (ADS)

Furqan Khan, Hassaan; Yang, Y. C. Ethan; Xie, Hua; Ringler, Claudia

2017-12-01

There is a growing recognition among water resource managers that sustainable watershed management needs to not only account for the diverse ways humans benefit from the environment, but also incorporate the impact of human actions on the natural system. Coupled natural-human system modeling through explicit modeling of both natural and human behavior can help reveal the reciprocal interactions and co-evolution of the natural and human systems. This study develops a spatially scalable, generalized agent-based modeling (ABM) framework consisting of a process-based semi-distributed hydrologic model (SWAT) and a decentralized water system model to simulate the impacts of water resource management decisions that affect the food-water-energy-environment (FWEE) nexus at a watershed scale. Agents within a river basin are geographically delineated based on both political and watershed boundaries and represent key stakeholders of ecosystem services. Agents decide about the priority across three primary water uses: food production, hydropower generation and ecosystem health within their geographical domains. Agents interact with the environment (streamflow) through the SWAT model and interact with other agents through a parameter representing willingness to cooperate. The innovative two-way coupling between the water system model and SWAT enables this framework to fully explore the feedback of human decisions on the environmental dynamics and vice versa. To support non-technical stakeholder interactions, a web-based user interface has been developed that allows for role-play and participatory modeling. The generalized ABM framework is also tested in two key transboundary river basins, the Mekong River basin in Southeast Asia and the Niger River basin in West Africa, where water uses for ecosystem health compete with growing human demands on food and energy resources. We present modeling results for crop production, energy generation and violation of eco-hydrological indicators at both the agent and basin-wide levels to shed light on holistic FWEE management policies in these two basins.

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

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

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

2009-01-01

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

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.

Wetland ecosystem health assessment through integrating remote sensing and inventory data with an assessment model for the Hangzhou Bay, China.

PubMed

Sun, Tengteng; Lin, Wenpeng; Chen, Guangsheng; Guo, Pupu; Zeng, Ying

2016-10-01

Due to rapid urbanization, industrialization and population growth, wetland area in China has shrunk rapidly and many wetland ecosystems have been reported to degrade during recent decades. Wetland health assessment could raise the public awareness of the wetland condition and guide policy makers to make reasonable and sustainable policies or strategies to protect and restore wetland ecosystems. This study assessed the health levels of wetland ecosystem at the Hangzhou Bay, China using the pressure-state-response (PSR) model through synthesizing remote sensing and statistical data. Ten ecological and social-economic indicators were selected to build the wetland health assessment system. Weights of these indicators and PSR model components as well as the normalized wetland health score were assigned and calculated based on the analytic hierarchy process (AHP) method. We analyzed the spatio-temporal changes in wetland ecosystem health status during the past 20years (1990-2010) from the perspectives of ecosystem pressure, state and response. The results showed that the overall wetland health score was in a fair health level, but displayed large spatial variability in 2010. The wetland health score declined from good health level to fair health level from 1990 to 2000, then restored slightly from 2000 to 2010. Overall, wetland health levels showed a decline from 1990 to 2010 for most administrative units. The temporal change patterns in wetland ecosystem health varied significantly among administrative units. Our results could help to clarify the administrative responsibilities and obligations and provide scientific guides not only for wetland protection but also for restoration and city development planning at the Hangzhou Bay area. Copyright © 2016 Elsevier B.V. All rights reserved.

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.

A process model of technology innovation in governmental agencies: Insights from NASA’s science directorate

NASA Astrophysics Data System (ADS)

Szajnfarber, Zoe; Weigel, Annalisa L.

2013-03-01

This paper investigates the process through which new technical concepts are matured in the NASA innovation ecosystem. We propose an "epoch-shock" conceptualization as an alternative mental model to the traditional stage-gate view. The epoch-shock model is developed inductively, based on detailed empirical observations of the process, and validated, to the extent possible, through expert review. The paper concludes by illustrating how the new epoch-shock conceptualization could provide a useful basis for rethinking feasible interventions to improve innovation management in the space agency context. Where the more traditional stage-gate model leads to an emphasis on centralized flow control, the epoch-shock model acknowledges the decentralized, probabilistic nature of key interactions and highlights which aspects may be influenced.

Long-Term Forest Hydrologic Monitoring in Coastal Carolinas

Treesearch

Devendra M. Amatya; Ge Sun; Carl C. Trettin; R. Wayne Skaggs

2003-01-01

Long-term hydrologic data are essential for understanding the hydrologic processes, as base line data for assessment of impacts and conservation of regional ecosystems, and for developing and testing eco-hydrological models. This study presents 6-year (1996-2001) of rainfall, water table and outflow data from a USDA Forest Service coastal experimental watershed on a...

Modeling Complex Marine Ecosystems: An Investigation of Two Teaching Approaches with Fifth Graders

ERIC Educational Resources Information Center

Papaevripidou, M.; Constantinou, C. P.; Zacharia, Z. C.

2007-01-01

This study investigated acquisition and transfer of the modeling ability of fifth graders in various domains. Teaching interventions concentrated on the topic of marine ecosystems either through a modeling-based approach or a worksheet-based approach. A quasi-experimental (pre-post comparison study) design was used. The control group (n = 17)…

Climate data induced uncertainty in model based estimations of terrestrial primary productivity

NASA Astrophysics Data System (ADS)

Wu, Z.; Ahlström, A.; Smith, B.; Ardö, J.; Eklundh, L.; Fensholt, R.; Lehsten, V.

2016-12-01

Models used to project global vegetation and carbon cycle differ in their estimates of historical fluxes and pools. These differences arise not only from differences between models but also from differences in the environmental and climatic data that forces the models. Here we investigate the role of uncertainties in historical climate data, encapsulated by a set of six historical climate datasets. We focus on terrestrial gross primary productivity (GPP) and analyze the results from a dynamic process-based vegetation model (LPJ-GUESS) forced by six different climate datasets and two empirical datasets of GPP (derived from flux towers and remote sensing). We find that the climate induced uncertainty, defined as the difference among historical simulations in GPP when forcing the model with the different climate datasets, can be as high as 33 Pg C yr-1 globally (19% of mean GPP). The uncertainty is partitioned into the three main climatic drivers, temperature, precipitation, and shortwave radiation. Additionally, we illustrate how the uncertainty due to a given climate driver depends both on the magnitude of the forcing data uncertainty (the data range) and the sensitivity of the modeled GPP to the driver (the ecosystem sensitivity). The analysis is performed globally and stratified into five land cover classes. We find that the dynamic vegetation model overestimates GPP, compared to empirically based GPP data over most areas, except for the tropical region. Both the simulations and empirical estimates agree that the tropical region is a disproportionate source of uncertainty in GPP estimation. This is mainly caused by uncertainties in shortwave radiation forcing, of which climate data range contributes slightly higher uncertainty than ecosystem sensitivity to shortwave radiation. We also find that precipitation dominated the climate induced uncertainty over nearly half of terrestrial vegetated surfaces, which is mainly due to large ecosystem sensitivity to precipitation. Overall, climate data ranges are found to contribute more to the climate induced uncertainty than ecosystem sensitivity. Our study highlights the need to better constrain tropical climate and demonstrate that uncertainty caused by climatic forcing data must be considered when comparing and evaluating model results and empirical datasets.

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

Multi-model inference for incorporating trophic and climate uncertainty into stock assessments

NASA Astrophysics Data System (ADS)

Ianelli, James; Holsman, Kirstin K.; Punt, André E.; Aydin, Kerim

2016-12-01

Ecosystem-based fisheries management (EBFM) approaches allow a broader and more extensive consideration of objectives than is typically possible with conventional single-species approaches. Ecosystem linkages may include trophic interactions and climate change effects on productivity for the relevant species within the system. Presently, models are evolving to include a comprehensive set of fishery and ecosystem information to address these broader management considerations. The increased scope of EBFM approaches is accompanied with a greater number of plausible models to describe the systems. This can lead to harvest recommendations and biological reference points that differ considerably among models. Model selection for projections (and specific catch recommendations) often occurs through a process that tends to adopt familiar, often simpler, models without considering those that incorporate more complex ecosystem information. Multi-model inference provides a framework that resolves this dilemma by providing a means of including information from alternative, often divergent models to inform biological reference points and possible catch consequences. We apply an example of this approach to data for three species of groundfish in the Bering Sea: walleye pollock, Pacific cod, and arrowtooth flounder using three models: 1) an age-structured "conventional" single-species model, 2) an age-structured single-species model with temperature-specific weight at age, and 3) a temperature-specific multi-species stock assessment model. The latter two approaches also include consideration of alternative future climate scenarios, adding another dimension to evaluate model projection uncertainty. We show how Bayesian model-averaging methods can be used to incorporate such trophic and climate information to broaden single-species stock assessments by using an EBFM approach that may better characterize uncertainty.

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

USGS Publications Warehouse

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

2008-01-01

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

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

USGS Publications Warehouse

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

2011-01-01

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

Accounting for ecosystem services in Life Cycle Assessment, Part II: toward an ecologically based LCA.

PubMed

Zhang, Yi; Baral, Anil; Bakshi, Bhavik R

2010-04-01

Despite the essential role of ecosystem goods and services in sustaining all human activities, they are often ignored in engineering decision making, even in methods that are meant to encourage sustainability. For example, conventional Life Cycle Assessment focuses on the impact of emissions and consumption of some resources. While aggregation and interpretation methods are quite advanced for emissions, similar methods for resources have been lagging, and most ignore the role of nature. Such oversight may even result in perverse decisions that encourage reliance on deteriorating ecosystem services. This article presents a step toward including the direct and indirect role of ecosystems in LCA, and a hierarchical scheme to interpret their contribution. The resulting Ecologically Based LCA (Eco-LCA) includes a large number of provisioning, regulating, and supporting ecosystem services as inputs to a life cycle model at the process or economy scale. These resources are represented in diverse physical units and may be compared via their mass, fuel value, industrial cumulative exergy consumption, or ecological cumulative exergy consumption or by normalization with total consumption of each resource or their availability. Such results at a fine scale provide insight about relative resource use and the risk and vulnerability to the loss of specific resources. Aggregate indicators are also defined to obtain indices such as renewability, efficiency, and return on investment. An Eco-LCA model of the 1997 economy is developed and made available via the web (www.resilience.osu.edu/ecolca). An illustrative example comparing paper and plastic cups provides insight into the features of the proposed approach. The need for further work in bridging the gap between knowledge about ecosystem services and their direct and indirect role in supporting human activities is discussed as an important area for future work.

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

USGS Publications Warehouse

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

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 determining the relative contribution of drought stress, insect attack, and their interactions, which is critical for modeling mortality in future climates. We outline a simple approach that identifies the mechanisms associated with two guilds of insects – bark beetles and defoliators – which are responsible for substantial tree mortality. We then discuss cross-biome patterns of insect-driven tree mortality and draw upon available evidence contrasting the prevalence of insect outbreaks in temperate and tropical regions. We conclude with an overview of tools and promising avenues to address major challenges. Ultimately, a multitrophic approach that captures tree physiology, insect populations, and tree–insect interactions will better inform projections of forest ecosystem responses to climate change.

Adding ecosystem function to agent-based land use models

USDA-ARS?s Scientific Manuscript database

The objective of this paper is to examine issues in the inclusion of simulations of ecosystem functions in agent-based models of land use decision-making. The reasons for incorporating these simulations include local interests in land fertility and global interests in carbon sequestration. Biogeoche...

Grassland Npp Monitoring Based on Multi-Source Remote Sensing Data Fusion

NASA Astrophysics Data System (ADS)

Cai, Y. R.; Zheng, J. H.; Du, M. J.; Mu, C.; Peng, J.

2018-04-01

Vegetation is an important part of the terrestrial ecosystem. It plays an important role in the energy and material exchange of the ground-atmosphere system and is a key part of the global carbon cycle process.Climate change has an important influence on the carbon cycle of terrestrial ecosystems. Net Primary Productivity (Net Primary Productivity)is an important parameter for evaluating global terrestrial ecosystems. For the Xinjiang region, the study of grassland NPP has gradually become a hot issue in the ecological environment.Increasing the estimation accuracy of NPP is of great significance to the development of the ecosystem in Xinjiang. Based on the third-generation GIMMS AVHRR NDVI global vegetation dataset and the MODIS NDVI (MOD13A3) collected each month by the United States Atmospheric and Oceanic Administration (NOAA),combining the advantages of different remotely sensed datasets, this paper obtained the maximum synthesis fusion for New normalized vegetation index (NDVI) time series in 2006-2015.Analysis of Net Primary Productivity of Grassland Vegetation in Xinjiang Using Improved CASA Model The method described in this article proves the feasibility of applying data processing, and the accuracy of the NPP calculation using the fusion processed NDVI has been greatly improved. The results show that: (1) The NPP calculated from the new normalized vegetation index (NDVI) obtained from the fusion of GIMMS AVHRR NDVI and MODIS NDVI is significantly higher than the NPP calculated from these two raw data; (2) The grassland NPP in Xinjiang Interannual changes show an overall increase trend; interannual changes in NPP have a certain relationship with precipitation.

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.

Does more mean less? The value of information for conservation planning under sea level rise.

PubMed

Runting, Rebecca K; Wilson, Kerrie A; Rhodes, Jonathan R

2013-02-01

Many studies have explored the benefits of adopting more sophisticated modelling techniques or spatial data in terms of our ability to accurately predict ecosystem responses to global change. However, we currently know little about whether the improved predictions will actually lead to better conservation outcomes once the costs of gaining improved models or data are accounted for. This severely limits our ability to make strategic decisions for adaptation to global pressures, particularly in landscapes subject to dynamic change such as the coastal zone. In such landscapes, the global phenomenon of sea level rise is a critical consideration for preserving biodiversity. Here, we address this issue in the context of making decisions about where to locate a reserve system to preserve coastal biodiversity with a limited budget. Specifically, we determined the cost-effectiveness of investing in high-resolution elevation data and process-based models for predicting wetland shifts in a coastal region of South East Queensland, Australia. We evaluated the resulting priority areas for reserve selection to quantify the cost-effectiveness of investment in better quantifying biological and physical processes. We show that, in this case, it is considerably more cost effective to use a process-based model and high-resolution elevation data, even if this requires a substantial proportion of the project budget to be expended (up to 99% in one instance). The less accurate model and data set failed to identify areas of high conservation value, reducing the cost-effectiveness of the resultant conservation plan. This suggests that when developing conservation plans in areas where sea level rise threatens biodiversity, investing in high-resolution elevation data and process-based models to predict shifts in coastal ecosystems may be highly cost effective. A future research priority is to determine how this cost-effectiveness varies among different regions across the globe. © 2012 Blackwell Publishing Ltd.

Developing multi-tracer approaches to constrain the parameterisation of leaf and soil CO2 and H2O exchange in land surface models

NASA Astrophysics Data System (ADS)

Ogée, Jerome; Wehr, Richard; Commane, Roisin; Launois, Thomas; Meredith, Laura; Munger, Bill; Nelson, David; Saleska, Scott; Zahniser, Mark; Wofsy, Steve; Wingate, Lisa

2016-04-01

The net flux of carbon dioxide between the land surface and the atmosphere is dominated by photosynthesis and soil respiration, two of the largest gross CO2 fluxes in the carbon cycle. More robust estimates of these gross fluxes could be obtained from the atmospheric budgets of other valuable tracers, such as carbonyl sulfide (COS) or the carbon and oxygen isotope compositions (δ13C and δ18O) of atmospheric CO2. Over the past decades, the global atmospheric flask network has measured the inter-annual and intra-annual variations in the concentrations of these tracers. However, knowledge gaps and a lack of high-resolution multi-tracer ecosystem-scale measurements have hindered the development of process-based models that can simulate the behaviour of each tracer in response to environmental drivers. We present novel datasets of net ecosystem COS, 13CO2 and CO18O exchange and vertical profile data collected over 3 consecutive growing seasons (2011-2013) at the Harvard forest flux site. We then used the process-based model MuSICA (multi-layer Simulator of the Interactions between vegetation Canopy and the Atmosphere) to include the transport, reaction, diffusion and production of each tracer within the forest and exchanged with the atmosphere. Model simulations over the three years captured well the impact of diurnally and seasonally varying environmental conditions on the net ecosystem exchange of each tracer. The model also captured well the dynamic vertical features of tracer behaviour within the canopy. This unique dataset and model sensitivity analysis highlights the benefit in the collection of multi-tracer high-resolution field datasets and the developement of multi-tracer land surface models to provide valuable constraints on photosynthesis and respiration across scales in the near future.

A framework to assess the impacts of climate change on stream health indicators in Michigan watersheds

NASA Astrophysics Data System (ADS)

Woznicki, S. A.; Nejadhashemi, A. P.; Tang, Y.; Wang, L.

2016-12-01

Climate change is projected to alter watershed hydrology and potentially amplify nonpoint source pollution transport. These changes have implications for fish and macroinvertebrates, which are often used as measures of aquatic ecosystem health. By quantifying the risk of adverse impacts to aquatic ecosystem health at the reach-scale, watershed climate change adaptation strategies can be developed and prioritized. The objective of this research was to quantify the impacts of climate change on stream health in seven Michigan watersheds. A process-based watershed model, the Soil and Water Assessment Tool (SWAT), was linked to adaptive neuro-fuzzy inferenced (ANFIS) stream health models. SWAT models were used to simulate reach-scale flow regime (magnitude, frequency, timing, duration, and rate of change) and water quality variables. The ANFIS models were developed based on relationships between the in-stream variables and sampling points of four stream health indicators: the fish index of biotic integrity (IBI), macroinvertebrate family index of biotic integrity (FIBI), Hilsenhoff biotic index (HBI), and number of Ephemeroptera, Plecoptera, and Trichoptera (EPT) taxa. The combined SWAT-ANFIS models extended stream health predictions to all watershed reaches. A climate model ensemble from the Coupled Model Intercomparison Project Phase 5 (CMIP5) was used to develop projections of changes to flow regime (using SWAT) and stream health indicators (using ANFIS) from a baseline of 1980-2000 to 2020-2040. Flow regime variables representing variability, duration of extreme events, and timing of low and high flow events were sensitive to changes in climate. The stream health indicators were relatively insensitive to changing climate at the watershed scale. However, there were many instances of individual reaches that were projected to experience declines in stream health. Using the probability of stream health decline coupled with the magnitude of the decline, maps of vulnerable stream ecosystems were developed, which can be used in the watershed management decision-making process.

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

Lowering the Barriers to Integrative Aquatic Ecosystem Science: Semantic Provenance, Open Linked Data, and Workflows

NASA Astrophysics Data System (ADS)

Harmon, T.; Hofmann, A. F.; Utz, R.; Deelman, E.; Hanson, P. C.; Szekely, P.; Villamizar, S. R.; Knoblock, C.; Guo, Q.; Crichton, D. J.; McCann, M. P.; Gil, Y.

2011-12-01

Environmental cyber-observatory (ECO) planning and implementation has been ongoing for more than a decade now, and several major efforts have recently come online or will soon. Some investigators in the relevant research communities will use ECO data, traditionally by developing their own client-side services to acquire data and then manually create custom tools to integrate and analyze it. However, a significant portion of the aquatic ecosystem science community will need more custom services to manage locally collected data. The latter group represents enormous intellectual capacity when one envisions thousands of ecosystems scientists supplementing ECO baseline data by sharing their own locally intensive observational efforts. This poster summarizes the outcomes of the June 2011 Workshop for Aquatic Ecosystem Sustainability (WAES) which focused on the needs of aquatic ecosystem research on inland waters and oceans. Here we advocate new approaches to support scientists to model, integrate, and analyze data based on: 1) a new breed of software tools in which semantic provenance is automatically created and used by the system, 2) the use of open standards based on RDF and Linked Data Principles to facilitate sharing of data and provenance annotations, 3) the use of workflows to represent explicitly all data preparation, integration, and processing steps in a way that is automatically repeatable. Aquatic ecosystems workflow exemplars are provided and discussed in terms of their potential broaden data sharing, analysis and synthesis thereby increasing the impact of aquatic ecosystem research.

Compensatory Water Effects Link Yearly Global Land CO2 Sink Changes to Temperature

NASA Technical Reports Server (NTRS)

Jung, Martin; Reichstein, Markus; Tramontana, Gianluca; Viovy, Nicolas; Schwalm, Christopher R.; Wang, Ying-Ping; Weber, Ulrich; Weber, Ulrich; Zaehle, Soenke; Zeng, Ning;