An underwater light attenuation scheme for marine ecosystem models.

PubMed

Penta, Bradley; Lee, Zhongping; Kudela, Raphael M; Palacios, Sherry L; Gray, Deric J; Jolliff, Jason K; Shulman, Igor G

2008-10-13

Simulation of underwater light is essential for modeling marine ecosystems. A new model of underwater light attenuation is presented and compared with previous models. In situ data collected in Monterey Bay, CA. during September 2006 are used for validation. It is demonstrated that while the new light model is computationally simple and efficient it maintains accuracy and flexibility. When this light model is incorporated into an ecosystem model, the correlation between modeled and observed coastal chlorophyll is improved over an eight-year time period. While the simulation of a deep chlorophyll maximum demonstrates the effect of the new model at depth.

Enhanced science-stakeholder communication to improve ecosystem model performances for climate change impact assessments.

PubMed

Jönsson, Anna Maria; Anderbrant, Olle; Holmér, Jennie; Johansson, Jacob; Schurgers, Guy; Svensson, Glenn P; Smith, Henrik G

2015-04-01

In recent years, climate impact assessments of relevance to the agricultural and forestry sectors have received considerable attention. Current ecosystem models commonly capture the effect of a warmer climate on biomass production, but they rarely sufficiently capture potential losses caused by pests, pathogens and extreme weather events. In addition, alternative management regimes may not be integrated in the models. A way to improve the quality of climate impact assessments is to increase the science-stakeholder collaboration, and in a two-way dialog link empirical experience and impact modelling with policy and strategies for sustainable management. In this paper we give a brief overview of different ecosystem modelling methods, discuss how to include ecological and management aspects, and highlight the importance of science-stakeholder communication. By this, we hope to stimulate a discussion among the science-stakeholder communities on how to quantify the potential for climate change adaptation by improving the realism in the models.

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...

Improving Marine Ecosystem Models with Biochemical Tracers

NASA Astrophysics Data System (ADS)

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

2018-01-01

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

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.

Plant water potential improves prediction of empirical stomatal models.

PubMed

Anderegg, William R L; Wolf, Adam; Arango-Velez, Adriana; Choat, Brendan; Chmura, Daniel J; Jansen, Steven; Kolb, Thomas; Li, Shan; Meinzer, Frederick; Pita, Pilar; Resco de Dios, Víctor; Sperry, John S; Wolfe, Brett T; Pacala, Stephen

2017-01-01

Climate change is expected to lead to increases in drought frequency and severity, with deleterious effects on many ecosystems. Stomatal responses to changing environmental conditions form the backbone of all ecosystem models, but are based on empirical relationships and are not well-tested during drought conditions. Here, we use a dataset of 34 woody plant species spanning global forest biomes to examine the effect of leaf water potential on stomatal conductance and test the predictive accuracy of three major stomatal models and a recently proposed model. We find that current leaf-level empirical models have consistent biases of over-prediction of stomatal conductance during dry conditions, particularly at low soil water potentials. Furthermore, the recently proposed stomatal conductance model yields increases in predictive capability compared to current models, and with particular improvement during drought conditions. Our results reveal that including stomatal sensitivity to declining water potential and consequent impairment of plant water transport will improve predictions during drought conditions and show that many biomes contain a diversity of plant stomatal strategies that range from risky to conservative stomatal regulation during water stress. Such improvements in stomatal simulation are greatly needed to help unravel and predict the response of ecosystems to future climate extremes.

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.

Comparing approaches to spatially explicit ecosystem service modeling: a case study from the San Pedro River, Arizona

USGS Publications Warehouse

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

2013-01-01

Although the number of ecosystem service modeling tools has grown in recent years, quantitative comparative studies of these tools have been lacking. In this study, we applied two leading open-source, spatially explicit ecosystem services modeling tools – Artificial Intelligence for Ecosystem Services (ARIES) and Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) – to the San Pedro River watershed in southeast Arizona, USA, and northern Sonora, Mexico. We modeled locally important services that both modeling systems could address – carbon, water, and scenic viewsheds. We then applied managerially relevant scenarios for urban growth and mesquite management to quantify ecosystem service changes. InVEST and ARIES use different modeling approaches and ecosystem services metrics; for carbon, metrics were more similar and results were more easily comparable than for viewsheds or water. However, findings demonstrate similar gains and losses of ecosystem services and conclusions when comparing effects across our scenarios. Results were more closely aligned for landscape-scale urban-growth scenarios and more divergent for a site-scale mesquite-management scenario. Follow-up studies, including testing in different geographic contexts, can improve our understanding of the strengths and weaknesses of these and other ecosystem services modeling tools as they move closer to readiness for supporting day-to-day resource management.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

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.

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.

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

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.

Improving the precision of lake ecosystem metabolism estimates by identifying predictors of model uncertainty

USGS Publications Warehouse

Rose, Kevin C.; Winslow, Luke A.; Read, Jordan S.; Read, Emily K.; Solomon, Christopher T.; Adrian, Rita; Hanson, Paul C.

2014-01-01

Diel changes in dissolved oxygen are often used to estimate gross primary production (GPP) and ecosystem respiration (ER) in aquatic ecosystems. Despite the widespread use of this approach to understand ecosystem metabolism, we are only beginning to understand the degree and underlying causes of uncertainty for metabolism model parameter estimates. Here, we present a novel approach to improve the precision and accuracy of ecosystem metabolism estimates by identifying physical metrics that indicate when metabolism estimates are highly uncertain. Using datasets from seventeen instrumented GLEON (Global Lake Ecological Observatory Network) lakes, we discovered that many physical characteristics correlated with uncertainty, including PAR (photosynthetically active radiation, 400-700 nm), daily variance in Schmidt stability, and wind speed. Low PAR was a consistent predictor of high variance in GPP model parameters, but also corresponded with low ER model parameter variance. We identified a threshold (30% of clear sky PAR) below which GPP parameter variance increased rapidly and was significantly greater in nearly all lakes compared with variance on days with PAR levels above this threshold. The relationship between daily variance in Schmidt stability and GPP model parameter variance depended on trophic status, whereas daily variance in Schmidt stability was consistently positively related to ER model parameter variance. Wind speeds in the range of ~0.8-3 m s–1 were consistent predictors of high variance for both GPP and ER model parameters, with greater uncertainty in eutrophic lakes. Our findings can be used to reduce ecosystem metabolism model parameter uncertainty and identify potential sources of that uncertainty.

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

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.

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

USGS Publications Warehouse

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

1999-01-01

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

Constraining terrestrial ecosystem CO2 fluxes by integrating models of biogeochemistry and atmospheric transport and data of surface carbon fluxes and atmospheric CO2 concentrations

NASA Astrophysics Data System (ADS)

Zhu, Q.; Zhuang, Q.; Henze, D.; Bowman, K.; Chen, M.; Liu, Y.; He, Y.; Matsueda, H.; Machida, T.; Sawa, Y.; Oechel, W.

2014-09-01

Regional net carbon fluxes of terrestrial ecosystems could be estimated with either biogeochemistry models by assimilating surface carbon flux measurements or atmospheric CO2 inversions by assimilating observations of atmospheric CO2 concentrations. Here we combine the ecosystem biogeochemistry modeling and atmospheric CO2 inverse modeling to investigate the magnitude and spatial distribution of the terrestrial ecosystem CO2 sources and sinks. First, we constrain a terrestrial ecosystem model (TEM) at site level by assimilating the observed net ecosystem production (NEP) for various plant functional types. We find that the uncertainties of model parameters are reduced up to 90% and model predictability is greatly improved for all the plant functional types (coefficients of determination are enhanced up to 0.73). We then extrapolate the model to a global scale at a 0.5° × 0.5° resolution to estimate the large-scale terrestrial ecosystem CO2 fluxes, which serve as prior for atmospheric CO2 inversion. Second, we constrain the large-scale terrestrial CO2 fluxes by assimilating the GLOBALVIEW-CO2 and mid-tropospheric CO2 retrievals from the Atmospheric Infrared Sounder (AIRS) into an atmospheric transport model (GEOS-Chem). The transport inversion estimates that: (1) the annual terrestrial ecosystem carbon sink in 2003 is -2.47 Pg C yr-1, which agrees reasonably well with the most recent inter-comparison studies of CO2 inversions (-2.82 Pg C yr-1); (2) North America temperate, Europe and Eurasia temperate regions act as major terrestrial carbon sinks; and (3) The posterior transport model is able to reasonably reproduce the atmospheric CO2 concentrations, which are validated against Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) CO2 concentration data. This study indicates that biogeochemistry modeling or atmospheric transport and inverse modeling alone might not be able to well quantify regional terrestrial carbon fluxes. However, combining the two modeling approaches and assimilating data of surface carbon flux as well as atmospheric CO2 mixing ratios might significantly improve the quantification of terrestrial carbon fluxes.

Validating a method for transferring social values of ecosystem services between public lands in the Rocky Mountain region

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.

2014-01-01

With growing pressures on ecosystem services, social values attributed to them are increasingly important to land management decisions. Social values, defined here as perceived values the public ascribes to ecosystem services, particularly cultural services, are generally not accounted for through economic markets or considered alongside economic and ecological values in ecosystem service assessments. Social-values data can be elicited through public value and preference surveys; however, limitations prevent them from being regularly collected. These limitations led to our three study objectives: (1) demonstrate an approach for applying benefit transfer, a nonmarket-valuation method, to spatially explicit social values; (2) validate the approach; and (3) identify potential improvements. We applied Social Values for Ecosystem Services (SolVES) to survey data for three national forests in Colorado and Wyoming. Social-value maps and models were generated, describing relationships between the maps and various combinations of environmental variables. Models from each forest were used to estimate social-value maps for the other forests via benefit transfer. Model performance was evaluated relative to the locally derived models. Performance varied with the number and type of environmental variables used, as well as differences in the forests' physical and social contexts. Enhanced metadata and better social-context matching could improve model transferability.

Identifying key areas of ecosystem services potential to improve ecological management in Chongqing City, southwest China.

PubMed

Xiao, Yang; Xiao, Qiang

2018-03-29

Because natural ecosystems and ecosystem services (ES) are both critical to the well-being of humankind, it is important to understand their relationships and congruence for conservation planning. Spatial conservation planning is required to set focused preservation priorities and to assess future ecological implications. This study uses the combined measures of ES models and ES potential to estimate and analyze all four groups of ecosystem services to generate opportunities to maximize ecosystem services. Subsequently, we identify the key areas of conservation priorities as future forestation and conservation hotspot zones to improve the ecological management in Chongqing City, located in the upper reaches of the Three Gorges Reservoir Area, China. Results show that ecosystem services potential is extremely obvious. Compared to ecosystem services from 2000, we determined that soil conservation could be increased by 59.11%, carbon sequestration by 129.51%, water flow regulation by 83.42%, and water purification by 84.42%. According to our prioritization results, approximately 48% of area converted to forests exhibited high improvements in all ecosystem services (categorized as hotspot-1, hotspot-2, and hotspot-3). The hotspots identified in this study can be used as an excellent surrogate for evaluation ecological engineering benefits and can be effectively applied in improving ecological management planning.

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

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

USGS Publications Warehouse

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

2008-01-01

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

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).

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

A framework for the resilience of seagrass ecosystems.

PubMed

Unsworth, Richard K F; Collier, Catherine J; Waycott, Michelle; Mckenzie, Len J; Cullen-Unsworth, Leanne C

2015-11-15

Seagrass ecosystems represent a global marine resource that is declining across its range. To halt degradation and promote recovery over large scales, management requires a radical change in emphasis and application that seeks to enhance seagrass ecosystem resilience. In this review we examine how the resilience of seagrass ecosystems is becoming compromised by a range of local to global stressors, resulting in ecological regime shifts that undermine the long-term viability of these productive ecosystems. To examine regime shifts and the management actions that can influence this phenomenon we present a conceptual model of resilience in seagrass ecosystems. The model is founded on a series of features and modifiers that act as interacting influences upon seagrass ecosystem resilience. Improved understanding and appreciation of the factors and modifiers that govern resilience in seagrass ecosystems can be utilised to support much needed evidence based management of a vital natural resource. Copyright © 2015 Elsevier Ltd. All rights reserved.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2018-02-01

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

Linking remote-sensing and ecosystem services modeling to support and assess management for regenerative grazing in the South Gobi, Mongolia

NASA Astrophysics Data System (ADS)

Chaplin-Kramer, R.; Kowal, V. A.; Sharp, R.

2017-12-01

Managing and monitoring supply chain sustainability is a major challenge and opportunity for business, especially in rangelands, heavily managed and often degraded natural systems that provide significant resources and raw materials for production. One of the largest and most threatened rangeland systems in the world is in Mongolia, which has seen a rapid rise in grazing pressure due to increasing global demand for cashmere along with privatization of a formerly government-run livestock industry. A new opportunity is emerging for remote-sensing to improve the management decisions of the producers and their incentive-setters, leading to a more sustainable rangeland system and better outcomes for biodiversity and people in this unique and imperiled landscape. Oyu Tolgoi (OT), the Mongolian subsidiary of the mining company Rio Tinto, in cooperation with Kering, an apparel conglomerate that sources cashmere from the region, are providing financial incentives to improve grazing patterns through a Sustainable Cashmere program, in order to restore the degraded rangeland ecosystem in the Gobi desert region. We present a framework and approach for predicting the effect of changing grazing practices on biodiversity and ecosystem services, which we are developing into decision-support tools for OT, Kering, and their local partner Wildlife Conservation Society to quantify the impacts of their programs and where these interventions will have greatest benefit. Our approach integrates remote-sensing and ecosystem modeling to scale up field monitoring data and forecast future impacts. Our rangeland production model, based on the soil-vegetation model CENTURY and the livestock model GRAZPLAN, predicts biomass production and plant species composition changes, and can feed into ecosystem services models such as soil retention and water regulation in the InVEST (Integrated Valuation of Ecosystem Services and Trade-offs) software suite. This presents a significant advance in ecosystem services modeling, moving toward continuous functions related to remotely-sensed ecosystem condition or quality rather than categorical land cover class. Preliminary findings suggest that categorical approaches may underestimate ecosystem services loss from degradation or gain from restoration by a factor of 2-5.

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

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.

Why Quantify Uncertainty in Ecosystem Studies: Obligation versus Discovery Tool?

NASA Astrophysics Data System (ADS)

Harmon, M. E.

2016-12-01

There are multiple motivations for quantifying uncertainty in ecosystem studies. One is as an obligation; the other is as a tool useful in moving ecosystem science toward discovery. While reporting uncertainty should become a routine expectation, a more convincing motivation involves discovery. By clarifying what is known and to what degree it is known, uncertainty analyses can point the way toward improvements in measurements, sampling designs, and models. While some of these improvements (e.g., better sampling designs) may lead to incremental gains, those involving models (particularly model selection) may require large gains in knowledge. To be fully harnessed as a discovery tool, attitudes toward uncertainty may have to change: rather than viewing uncertainty as a negative assessment of what was done, it should be viewed as positive, helpful assessment of what remains to be done.

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

Treesearch

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

2015-01-01

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

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

USDA-ARS?s Scientific Manuscript database

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

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

Stavros, E. Natasha; Schimel, David; Pavlick, Ryan

Technologies on the International Space Station will provide ~1 year of synchronous observations of ecosystem composition, structure and function, in 2018. Here, we discuss these instruments and how they can be used to constrain global models and improve our understanding of the current state of terrestrial ecosystems.

Biodiversity and ecosystem stability across scales in metacommunities

PubMed Central

Wang, Shaopeng; Loreau, Michel

2016-01-01

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

Influence of physiological phenology on the seasonal pattern of ecosystem respiration in deciduous forests.

PubMed

Migliavacca, Mirco; Reichstein, Markus; Richardson, Andrew D; Mahecha, Miguel D; Cremonese, Edoardo; Delpierre, Nicolas; Galvagno, Marta; Law, Beverly E; Wohlfahrt, Georg; Black, T Andrew; Carvalhais, Nuno; Ceccherini, Guido; Chen, Jiquan; Gobron, Nadine; Koffi, Ernest; Munger, J William; Perez-Priego, Oscar; Robustelli, Monica; Tomelleri, Enrico; Cescatti, Alessandro

2015-01-01

Understanding the environmental and biotic drivers of respiration at the ecosystem level is a prerequisite to further improve scenarios of the global carbon cycle. In this study we investigated the relevance of physiological phenology, defined as seasonal changes in plant physiological properties, for explaining the temporal dynamics of ecosystem respiration (RECO) in deciduous forests. Previous studies showed that empirical RECO models can be substantially improved by considering the biotic dependency of RECO on the short-term productivity (e.g., daily gross primary production, GPP) in addition to the well-known environmental controls of temperature and water availability. Here, we use a model-data integration approach to investigate the added value of physiological phenology, represented by the first temporal derivative of GPP, or alternatively of the fraction of absorbed photosynthetically active radiation, for modeling RECO at 19 deciduous broadleaved forests in the FLUXNET La Thuile database. The new data-oriented semiempirical model leads to an 8% decrease in root mean square error (RMSE) and a 6% increase in the modeling efficiency (EF) of modeled RECO when compared to a version of the model that does not consider the physiological phenology. The reduction of the model-observation bias occurred mainly at the monthly time scale, and in spring and summer, while a smaller reduction was observed at the annual time scale. The proposed approach did not improve the model performance at several sites, and we identified as potential causes the plant canopy heterogeneity and the use of air temperature as a driver of ecosystem respiration instead of soil temperature. However, in the majority of sites the model-error remained unchanged regardless of the driving temperature. Overall, our results point toward the potential for improving current approaches for modeling RECO in deciduous forests by including the phenological cycle of the canopy. © 2014 John Wiley & Sons Ltd.

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.

Assessment of coastal management options by means of multilayered ecosystem models

NASA Astrophysics Data System (ADS)

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

2010-03-01

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

Effects of Disturbance on Carbon Sequestration in the New Jersey Pine Barrens

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

Schafer, Karina; Bohrer, Gil

While carbon and water cycling of forests contribute significantly to the Earth's overall biogeochemical cycling, it may be affected by disturbance and climate change. In this research, we contributed to the body of research on leaf-level, ecosystem and regional scale effects of disturbances on forest ecosystems, in an effort to foster more mechanistic understanding, which in turn can improve modeling efforts. Here, we summarize some of the major findings in this research of physical and biogenic disturbances, such as drought, prescribed fire, and insect defoliation, on leaf and ecosystem-scale physiological responses as well as impacts on carbon and water cyclingmore » in an Atlantic Coastal Plain upland oak/pine and upland pine forest. Following we have incorporated some of our findings into a new version of the Finite-element Tree-Crown Hydrodynamics (model version 2) model, which improved timing and hysteresis of transpiration modeling for trees. Furthermore, incorporation of hydrodynamics into modeling transpiration improved latent heat flux estimates. In our study on the physiology of the trees, we showed that during drought, stomatal conductance and canopy stomatal conductance were reduced, however, defoliation increased conductance on both leaf-level and canopy scale. Furthermore, after prescribed fire, leaf-level stomatal conductance was unchanged for pines but decreased for oaks, while canopy stomatal conductance decreased temporarily, but then rebounded the following growing season, thus exhibiting transient responses. This study suggests that forest response to disturbance varies from the leaf to ecosystem level as well as species level and thus, these differential responses interplay to determine the fate of forest structure and functioning post disturbance. Incorporating this responses improves model outcome.« less

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

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

USGS Publications Warehouse

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

2016-01-01

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

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.

Modeling the Ecosystem Services Provided by Trees in Urban Ecosystems: Using Biome-BGC to Improve i-Tree Eco

NASA Technical Reports Server (NTRS)

Brown, Molly E.; McGroddy, Megan; Spence, Caitlin; Flake, Leah; Sarfraz, Amna; Nowak, David J.; Milesi, Cristina

2012-01-01

As the world becomes increasingly urban, the need to quantify the effect of trees in urban environments on energy usage, air pollution, local climate and nutrient run-off has increased. By identifying, quantifying and valuing the ecological activity that provides services in urban areas, stronger policies and improved quality of life for urban residents can be obtained. Here we focus on two radically different models that can be used to characterize urban forests. The i-Tree Eco model (formerly UFORE model) quantifies ecosystem services (e.g., air pollution removal, carbon storage) and values derived from urban trees based on field measurements of trees and local ancillary data sets. Biome-BGC (Biome BioGeoChemistry) is used to simulate the fluxes and storage of carbon, water, and nitrogen in natural environments. This paper compares i-Tree Eco's methods to those of Biome-BGC, which estimates the fluxes and storage of energy, carbon, water and nitrogen for vegetation and soil components of the ecosystem. We describe the two models and their differences in the way they calculate similar properties, with a focus on carbon and nitrogen. Finally, we discuss the implications of further integration of these two communities for land managers such as those in Maryland.

How models can support ecosystem-based management of coral reefs

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

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.

Modeling Net Ecosystem Carbon Exchange of Alpine Grasslands with a Satellite-Driven Model

PubMed Central

Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model. PMID:25849325

Modeling net ecosystem carbon exchange of alpine grasslands with a satellite-driven model.

PubMed

Yan, Wei; Hu, Zhongmin; Zhao, Yuping; Zhang, Xianzhou; Fan, Yuzhi; Shi, Peili; He, Yongtao; Yu, Guirui; Li, Yingnian

2015-01-01

Estimate of net ecosystem carbon exchange (NEE) between the atmosphere and terrestrial ecosystems, the balance of gross primary productivity (GPP) and ecosystem respiration (Reco) has significant importance for studying the regional and global carbon cycles. Using models driven by satellite data and climatic data is a promising approach to estimate NEE at regional scales. For this purpose, we proposed a semi-empirical model to estimate NEE in this study. In our model, the component GPP was estimated with a light response curve of a rectangular hyperbola. The component Reco was estimated with an exponential function of soil temperature. To test the feasibility of applying our model at regional scales, the temporal variations in the model parameters derived from NEE observations in an alpine grassland ecosystem on Tibetan Plateau were investigated. The results indicated that all the inverted parameters exhibit apparent seasonality, which is in accordance with air temperature and canopy phenology. In addition, all the parameters have significant correlations with the remote sensed vegetation indexes or environment temperature. With parameters estimated with these correlations, the model illustrated fair accuracy both in the validation years and at another alpine grassland ecosystem on Tibetan Plateau. Our results also indicated that the model prediction was less accurate in drought years, implying that soil moisture is an important factor affecting the model performance. Incorporating soil water content into the model would be a critical step for the improvement of the model.

Biodiversity and ecosystem stability across scales in metacommunities.

PubMed

Wang, Shaopeng; Loreau, Michel

2016-05-01

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

ISS observations offer insights into plant function

DOE PAGES

Stavros, E. Natasha; Schimel, David; Pavlick, Ryan; ...

2017-06-22

Technologies on the International Space Station will provide ~1 year of synchronous observations of ecosystem composition, structure and function, in 2018. Here, we discuss these instruments and how they can be used to constrain global models and improve our understanding of the current state of terrestrial ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2014-11-01

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

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

PubMed

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

2014-04-01

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

The role of a peri-urban forest on air quality improvement in the Mexico City megalopolis.

PubMed

Baumgardner, Darrel; Varela, Sebastian; Escobedo, Francisco J; Chacalo, Alicia; Ochoa, Carlos

2012-04-01

Air quality improvement by a forested, peri-urban national park was quantified by combining the Urban Forest Effects (UFORE) and the Weather Research and Forecasting coupled with Chemistry (WRF-Chem) models. We estimated the ecosystem-level annual pollution removal function of the park's trees, shrub and grasses using pollution concentration data for carbon monoxide (CO), ozone (O(3)), and particulate matter less than 10 microns in diameter (PM(10)), modeled meteorological and pollution variables, and measured forest structure data. Ecosystem-level O(3) and CO removal and formation were also analyzed for a representative month. Total annual air quality improvement of the park's vegetation was approximately 0.02% for CO, 1% for O(3,) and 2% for PM(10), of the annual concentrations for these three pollutants. Results can be used to understand the air quality regulation ecosystem services of peri-urban forests and regional dynamics of air pollution emissions from major urban areas. Copyright © 2011 Elsevier Ltd. All rights reserved.

A comparison of tools for modeling freshwater ecosystem services.

PubMed

Vigerstol, Kari L; Aukema, Juliann E

2011-10-01

Interest in ecosystem services has grown tremendously among a wide range of sectors, including government agencies, NGO's and the business community. Ecosystem services entailing freshwater (e.g. flood control, the provision of hydropower, and water supply), as well as carbon storage and sequestration, have received the greatest attention in both scientific and on-the-ground applications. Given the newness of the field and the variety of tools for predicting water-based services, it is difficult to know which tools to use for different questions. There are two types of freshwater-related tools--traditional hydrologic tools and newer ecosystem services tools. Here we review two of the most prominent tools of each type and their possible applications. In particular, we compare the data requirements, ease of use, questions addressed, and interpretability of results among the models. We discuss the strengths, challenges and most appropriate applications of the different models. Traditional hydrological tools provide more detail whereas ecosystem services tools tend to be more accessible to non-experts and can provide a good general picture of these ecosystem services. We also suggest gaps in the modeling toolbox that would provide the greatest advances by improving existing tools. Copyright © 2011 Elsevier Ltd. All rights reserved.

Recent drought effects on ecosystem carbon uptake in California ecosystems

NASA Astrophysics Data System (ADS)

Chen, M.; Guan, K.; Brodrick, P. G.; Berry, J. A.; Asner, G. P.

2016-12-01

California is one of the Earth's most biodiverse places and most of California has experienced an extreme (millennium scale) drought in the period of 2012-2015. Although the effect of the drought on the water resources have been well studied, the responses of ecosystems has not been explored in this detail. This study used advanced remotely sensed data (e.g., remotely sensed vegetation indices and solar-induced fluorescence), an ecosystem model, and model-data fusion techniques to study the impacts of the severe drought on ecosystem carbon uptakes in California. We have found that: (1) the drought has significantly suppressed carbon uptake and light use efficiency in California ecosystems - except in the semi-deserts, and the moist forests in the northern coast; (2) effects on the photosynthetic capacity of the ecosystems extends after the drought is relieved; and (3) the drought has shifted both the timing and magnitude of the seasonality of the carbon uptake in non-forested regions. These findings provide a better understanding of the impacts of droughts, and provide an improved basis for prediction of ecosystem responses under a more extreme climate in the future.

Merging a mechanistic enzymatic model of soil heterotrophic respiration into an ecosystem model in two AmeriFlux sites of northeastern USA

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

Sihi, Debjani; Davidson, Eric A.; Chen, Min

Heterotrophic respiration (Rh), microbial processing of soil organic matter to carbon dioxide (CO 2), is a major, yet highly uncertain, carbon (C) flux from terrestrial systems to the atmosphere. Temperature sensitivity of Rh is often represented with a simple Q 10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed as a way to disentangle the confounding factors of apparent temperature sensitivity of Rh and improve the performance of ecosystem models and ESMs.more » The objective of this work was to insert into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh and evaluate the model performance in terms of soil and ecosystem respiration. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen, soluble C substrates, and extracellular enzymes to the enzymatic reaction site. Here, we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration). We used high-frequency soil flux data from automated soil chambers and landscape-scale ecosystem fluxes from eddy covariance towers at two AmeriFlux sites (Harvard Forest, MA and Howland Forest, ME) in the northeastern USA to estimate parameters, validate the merged model, and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal and inter-annual dynamics of soil respiration (Soil R) compared to the FöBAAR-only model for the Harvard Forest, where higher frequency and duration of drying events significantly regulate substrate supply to heterotrophs. However, DAMM-FöBAAR showed improvement over FöBAAR-only at the boreal transition Howland Forest only in unusually dry years. The frequency of synoptic-scale dry periods is lower at Howland, resulting in only brief water limitation of Rh in some years. At both sites, the declining trend of soil R during drying events was captured by the DAMM-FöBAAR model; however, model performance was also contingent on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the model-data mismatch. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than the wide variety of empirical functions that are commonly used, and these DAMM functions could be readily incorporated into other ecosystem models and ESMs.« less

Biological interactions and cooperative management of multiple species.

PubMed

Jiang, Jinwei; Min, Yong; Chang, Jie; Ge, Ying

2017-01-01

Coordinated decision making and actions have become the primary solution for the overexploitation of interacting resources within ecosystems. However, the success of coordinated management is highly sensitive to biological, economic, and social conditions. Here, using a game theoretic framework and a 2-species model that considers various biological relationships (competition, predation, and mutualism), we compute cooperative (or joint) and non-cooperative (or separate) management equilibrium outcomes of the model and investigate the effects of the type and strength of the relationships. We find that cooperation does not always show superiority to non-cooperation in all biological interactions: (1) if and only if resources are involved in high-intensity predation relationships, cooperation can achieve a win-win scenario for ecosystem services and resource diversity; (2) for competitive resources, cooperation realizes higher ecosystem services by sacrificing resource diversity; and (3) for mutual resources, cooperation has no obvious advantage for either ecosystem services or resource evenness but can slightly improve resource abundance. Furthermore, by using a fishery model of the North California Current Marine Ecosystem with 63 species and seven fleets, we demonstrate that the theoretical results can be reproduced in real ecosystems. Therefore, effective ecosystem management should consider the interconnection between stakeholders' social relationship and resources' biological relationships.

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.

Impacts of Climate Change on Biofuels Production

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

Melillo, Jerry M.

2014-04-30

The overall goal of this research project was to improve and use our biogeochemistry model, TEM, to simulate the effects of climate change and other environmental changes on the production of biofuel feedstocks. We used the improved version of TEM that is coupled with the economic model, EPPA, a part of MIT’s Earth System Model, to explore how alternative uses of land, including land for biofuels production, can help society meet proposed climate targets. During the course of this project, we have made refinements to TEM that include development of a more mechanistic plant module, with improved ecohydrology and considerationmore » of plant-water relations, and a more detailed treatment of soil nitrogen dynamics, especially processes that add or remove nitrogen from ecosystems. We have documented our changes to TEM and used the model to explore the effects on production in land ecosystems, including changes in biofuels production.« less

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

EPA Science Inventory

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

Methodological Considerations in the Study of Earthworms in Forest Ecosystems

Treesearch

Dylan Rhea-Fournier; Grizelle Gonzalez

2017-01-01

Decades of studies have shown that soil macrofauna, especially earthworms, play dominant engineering roles in soils, affecting physical, chemical, and biological components of ecosystems. Quantifying these effects would allow crucial improvement in biogeochemical budgets and modeling, predicting response of land use and disturbance, and could be applied to...

Carbon and water vapor fluxes of different ecosystems in Oklahoma

USDA-ARS?s Scientific Manuscript database

Information on exchange of energy, carbon dioxide (CO2), and water vapor (H2O) for major terrestrial ecosystems is vital to quantify carbon and water balances on a large-scale. It is also necessary to develop, test, and improve crop models and satellite-based production efficiency and evapotranspira...

[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.

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.

The importance of radiation for semiempirical water-use efficiency models

NASA Astrophysics Data System (ADS)

Boese, Sven; Jung, Martin; Carvalhais, Nuno; Reichstein, Markus

2017-06-01

Water-use efficiency (WUE) is a fundamental property for the coupling of carbon and water cycles in plants and ecosystems. Existing model formulations predicting this variable differ in the type of response of WUE to the atmospheric vapor pressure deficit of water (VPD). We tested a representative WUE model on the ecosystem scale at 110 eddy covariance sites of the FLUXNET initiative by predicting evapotranspiration (ET) based on gross primary productivity (GPP) and VPD. We found that introducing an intercept term in the formulation increases model performance considerably, indicating that an additional factor needs to be considered. We demonstrate that this intercept term varies seasonally and we subsequently associate it with radiation. Replacing the constant intercept term with a linear function of global radiation was found to further improve model predictions of ET. Our new semiempirical ecosystem WUE formulation indicates that, averaged over all sites, this radiation term accounts for up to half (39-47 %) of transpiration. These empirical findings challenge the current understanding of water-use efficiency on the ecosystem scale.

Redefinition and global estimation of basal ecosystem respiration rate

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

Yuan, Wenping; Luo, Yiqi; Li, Xianglan

2011-10-13

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

Interacting coastal based ecosystem services: recreation and water quality in Puget Sound, WA

USGS Publications Warehouse

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments.

Interacting Coastal Based Ecosystem Services: Recreation and Water Quality in Puget Sound, WA

PubMed Central

Kreitler, Jason; Papenfus, Michael; Byrd, Kristin; Labiosa, William

2013-01-01

Coastal recreation and water quality are major contributors to human well-being in coastal regions. They can also interact, creating opportunities for ecosystem based management, ecological restoration, and water quality improvement that can positively affect people and the environment. Yet the effect of environmental quality on human behavior is often poorly quantified, but commonly assumed in coastal ecosystem service studies. To clarify this effect we investigate a water quality dataset for evidence that environmental condition partially explains variation in recreational visitation, our indicator of human behavior. In Puget Sound, WA, we investigate variation in visitation in both visitation rate and fixed effects (FE) models. The visitation rate model relates the differences in annual recreational visitation among parks to environmental conditions, park characteristics, travel cost, and recreational demand. In our FE model we control for all time-invariant unobserved variables and compare monthly variation at the park level to determine how water quality affects visitation during the summer season. The results of our first model illustrate how visitation relates to various amenities and costs. In the FE analysis, monthly visitation was negatively related to water quality while controlling for monthly visitation trends. This indicates people are responding to changes in water quality, and an improvement would yield an increase in the value of recreation. Together, these results could help in prioritizing water quality improvements, could assist the creation of new parks or the modification of existing recreational infrastructure, and provide quantitative estimates for the expected benefits from potential changes in recreational visitation and water quality improvements. Our results also provide an example of how recreational visitation can be quantified and used in ecosystem service assessments. PMID:23451067

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

NASA Astrophysics Data System (ADS)

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

2011-12-01

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

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

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-07-01

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

Same pattern, different mechanism: Locking onto the role of key species in seafloor ecosystem process

PubMed Central

Woodin, Sarah Ann; Volkenborn, Nils; Pilditch, Conrad A.; Lohrer, Andrew M.; Wethey, David S.; Hewitt, Judi E.; Thrush, Simon F.

2016-01-01

Seafloor biodiversity is a key mediator of ecosystem functioning, but its role is often excluded from global budgets or simplified to black boxes in models. New techniques allow quantification of the behavior of animals living below the sediment surface and assessment of the ecosystem consequences of complex interactions, yielding a better understanding of the role of seafloor animals in affecting key processes like primary productivity. Combining predictions based on natural history, behavior of key benthic species and environmental context allow assessment of differences in functioning and process, even when the measured ecosystem property in different systems is similar. Data from three sedimentary systems in New Zealand illustrate this. Analysis of the behaviors of the infaunal ecosystem engineers in each system revealed three very different mechanisms driving ecosystem function: density and excretion, sediment turnover and surface rugosity, and hydraulic activities and porewater bioadvection. Integrative metrics of ecosystem function in some cases differentiate among the systems (gross primary production) and in others do not (photosynthetic efficiency). Analyses based on behaviors and activities revealed important ecosystem functional differences and can dramatically improve our ability to model the impact of stressors on ecosystem and global processes. PMID:27230562

Same pattern, different mechanism: Locking onto the role of key species in seafloor ecosystem process.

PubMed

Woodin, Sarah Ann; Volkenborn, Nils; Pilditch, Conrad A; Lohrer, Andrew M; Wethey, David S; Hewitt, Judi E; Thrush, Simon F

2016-05-27

Seafloor biodiversity is a key mediator of ecosystem functioning, but its role is often excluded from global budgets or simplified to black boxes in models. New techniques allow quantification of the behavior of animals living below the sediment surface and assessment of the ecosystem consequences of complex interactions, yielding a better understanding of the role of seafloor animals in affecting key processes like primary productivity. Combining predictions based on natural history, behavior of key benthic species and environmental context allow assessment of differences in functioning and process, even when the measured ecosystem property in different systems is similar. Data from three sedimentary systems in New Zealand illustrate this. Analysis of the behaviors of the infaunal ecosystem engineers in each system revealed three very different mechanisms driving ecosystem function: density and excretion, sediment turnover and surface rugosity, and hydraulic activities and porewater bioadvection. Integrative metrics of ecosystem function in some cases differentiate among the systems (gross primary production) and in others do not (photosynthetic efficiency). Analyses based on behaviors and activities revealed important ecosystem functional differences and can dramatically improve our ability to model the impact of stressors on ecosystem and global processes.

Linking biodiversity to ecosystem function: Implications for conservation ecology

USGS Publications Warehouse

Schwartz, M.W.; Brigham, C.A.; Hoeksema, J.D.; Lyons, K.G.; Mills, M.H.; van Mantgem, P.

2000-01-01

We evaluate the empirical and theoretical support for the hypothesis that a large proportion of native species richness is required to maximize ecosystem stability and sustain function. This assessment is important for conservation strategies because sustenance of ecosystem functions has been used as an argument for the conservation of species. If ecosystem functions are sustained at relatively low species richness, then arguing for the conservation of ecosystem function, no matter how important in its own right, does not strongly argue for the conservation of species. Additionally, for this to be a strong conservation argument the link between species diversity and ecosystem functions of value to the human community must be clear. We review the empirical literature to quantify the support for two hypotheses: (1) species richness is positively correlated with ecosystem function, and (2) ecosystem functions do not saturate at low species richness relative to the observed or experimental diversity. Few empirical studies demonstrate improved function at high levels of species richness. Second, we analyze recent theoretical models in order to estimate the level of species richness required to maintain ecosystem function. Again we find that, within a single trophic level, most mathematical models predict saturation of ecosystem function at a low proportion of local species richness. We also analyze a theoretical model linking species number to ecosystem stability. This model predicts that species richness beyond the first few species does not typically increase ecosystem stability. One reason that high species richness may not contribute significantly to function or stability is that most communities are characterized by strong dominance such that a few species provide the vast majority of the community biomass. Rapid turnover of species may rescue the concept that diversity leads to maximum function and stability. The role of turnover in ecosystem function and stability has not been investigated. Despite the recent rush to embrace the linkage between biodiversity and ecosystem function, we find little support for the hypothesis that there is a strong dependence of ecosystem function on the full complement of diversity within sites. Given this observation, the conservation community should take a cautious view of endorsing this linkage as a model to promote conservation goals.

Development of an integrated ecosystem model to determine effectiveness of potential watershed management projects on improving Old Tampa Bay

Treesearch

Edward T. Sherwood; Holly Greening; Lizanne Garcia; Kris Kaufman; Tony Janicki; Ray Pribble; Brett Cunningham; Steve Peene; Jim Fitzpatrick; Kellie Dixon; Mike Wessel

2016-01-01

The Tampa Bay estuary has undergone a remarkable ecosystem recovery since the 1980s despite continued population growth within the region. However during this time, the Old Tampa Bay (OTB) segment has lagged behind the rest of the Bay’s recovery relative to improvements in overall water quality and seagrass coverage. In 2011, the Tampa Bay Estuary Program, in...

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

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

Significant trade-off for the impact of Grain-for-Green Programme on ecosystem services in North-western Yunnan, China.

PubMed

Wang, Jitao; Peng, Jian; Zhao, Mingyue; Liu, Yanxu; Chen, Yunqian

2017-01-01

Ecological restoration can mitigate human disturbance to the natural environment and restore ecosystem functions. China's Grain-for-Green Programme (GFGP) has been widely adopted in the last 15years and exerted significant impact on land-use and ecosystem services. North-western Yunnan is one of the key areas of GFGP implementation in the upper Yangtze River. Promotion of ecosystem services in this region is of great importance to the ecological sustainability of Yangtze River watershed. In this study, remote sensing and modelling techniques are applied to analyse the impact of GFGP on ecosystem services. Results show that the transformation from non-irrigated farmland to forestland could potentially improve soil conservation by 24.89%. Soil conservation of restored forest was 78.17% of retained forest while net primary production (NPP) already reached 88.65%, which suggested different recovery rates of NPP and soil conservation. Increasing extent of GFGP implementation improved soil conservation but decreased NPP and water yield at sub-watershed scale, which revealed trade-offs between ecosystem services under ecological restoration. Future ecosystem management and GFGP policy-making should consider trade-offs of ecosystem services in order to achieve sustainable provision of ecosystem services. Copyright © 2016 Elsevier B.V. All rights reserved.

Efficient ensemble forecasting of marine ecology with clustered 1D models and statistical lateral exchange: application to the Red Sea

NASA Astrophysics Data System (ADS)

Dreano, Denis; Tsiaras, Kostas; Triantafyllou, George; Hoteit, Ibrahim

2017-07-01

Forecasting the state of large marine ecosystems is important for many economic and public health applications. However, advanced three-dimensional (3D) ecosystem models, such as the European Regional Seas Ecosystem Model (ERSEM), are computationally expensive, especially when implemented within an ensemble data assimilation system requiring several parallel integrations. As an alternative to 3D ecological forecasting systems, we propose to implement a set of regional one-dimensional (1D) water-column ecological models that run at a fraction of the computational cost. The 1D model domains are determined using a Gaussian mixture model (GMM)-based clustering method and satellite chlorophyll-a (Chl-a) data. Regionally averaged Chl-a data is assimilated into the 1D models using the singular evolutive interpolated Kalman (SEIK) filter. To laterally exchange information between subregions and improve the forecasting skills, we introduce a new correction step to the assimilation scheme, in which we assimilate a statistical forecast of future Chl-a observations based on information from neighbouring regions. We apply this approach to the Red Sea and show that the assimilative 1D ecological models can forecast surface Chl-a concentration with high accuracy. The statistical assimilation step further improves the forecasting skill by as much as 50%. This general approach of clustering large marine areas and running several interacting 1D ecological models is very flexible. It allows many combinations of clustering, filtering and regression technics to be used and can be applied to build efficient forecasting systems in other large marine ecosystems.

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

NASA Astrophysics Data System (ADS)

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

2010-04-01

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

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.

Modeling catchment nutrients and sediment loads to inform regional management of water quality in coastal-marine ecosystems: a comparison of two approaches.

PubMed

Álvarez-Romero, Jorge G; Wilkinson, Scott N; Pressey, Robert L; Ban, Natalie C; Kool, Johnathan; Brodie, Jon

2014-12-15

Human-induced changes in flows of water, nutrients, and sediments have impacts on marine ecosystems. Quantifying these changes to systematically allocate management actions is a priority for many areas worldwide. Modeling nutrient and sediment loads and contributions from subcatchments can inform prioritization of management interventions to mitigate the impacts of land-based pollution on marine ecosystems. Among the catchment models appropriate for large-scale applications, N-SPECT and SedNet have been used to prioritize areas for management of water quality in coastal-marine ecosystems. However, an assessment of their relative performance, parameterization, and utility for regional-scale planning is needed. We examined how these considerations can influence the choice between the two models and the areas identified as priorities for management actions. We assessed their application in selected catchments of the Gulf of California, where managing land-based threats to marine ecosystems is a priority. We found important differences in performance between models. SedNet consistently estimated spatial variations in runoff with higher accuracy than N-SPECT and modeled suspended sediment (TSS) loads mostly within the range of variation in observed loads. N-SPECT overestimated TSS loads by orders of magnitude when using the spatially-distributed sediment delivery ratio (SDR), but outperformed SedNet when using a calibrated SDR. Differences in subcatchments' contribution to pollutant loads were principally due to explicit representation of sediment sinks and particulate nutrients by SedNet. Improving the floodplain extent model, and constraining erosion estimates by local data including gully erosion in SedNet, would improve results of this model and help identify effective management responses. Differences between models in the patterns of modeled pollutant supply were modest, but significantly influenced the prioritization of subcatchments for management. Copyright © 2014 Elsevier Ltd. All rights reserved.

A framework for simulating map error in ecosystem models

Treesearch

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

2014-01-01

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

Amazon forest structure generates diurnal and seasonal variability in light utilization

Treesearch

Douglas C. Morton; Jeremy Rubio; Bruce D. Cook; Jean-Philippe Gastellu-Etchegorry; Marcos Longo; Hyeungu Choi; Maria Hunter; Michael Keller

2016-01-01

The complex three-dimensional (3-D) structure of tropical forests generates a diversity of light environments for canopy and understory trees. Understanding diurnal and seasonal changes in light availability is critical for interpreting measurements of net ecosystem exchange and improving ecosystem models. Here, we used the Discrete Anisotropic Radiative Transfer (DART...

Evaluating Energy Flows Through Jellyfish and Forage Fish and the Effects of Fishing on the Northern Humboldt Current Ecosystem

NASA Astrophysics Data System (ADS)

Chiaverano, L.; Robinson, K. L.; Ruzicka, J.; Quiñones, J.; Tam, J.; Acha, M.; Graham, W. M.; Brodeur, R.; Decker, M. B.; Hernandez, F., Jr.; Leaf, R.; Mianzan, H.; Uye, S. I.

2016-02-01

Increases in the frequency of jellyfish mass occurrences in a number of coastal areas around the globe have intensified concerns that some ecosystems are becoming "jellyfish-dominated". Gelatinous planktivores not only compete with forage fish for food, but also feed on fish eggs and larvae. When jellyfish abundance is high, the fraction of the energy and the efficiency at which it is transferred upwards in the food web are reduced compared with times when fish are dominant. Hence, ecosystems supporting major forage fish fisheries are the most likely to experience fish-to-jellyfish shifts due to the harvest pressure on mid-trophic planktivores. Although forage fish-jellyfish replacement cycles have been detected in recent decades in some productive, coastal ecosystems (e.g. Gulf of Mexico, Northern California Current), jellyfish are typically not included in ecosystem-based fisheries management (EBFM) production models. Here we explored the roles of jellyfish and forage fish as trophic energy transfer pathways to higher trophic levels in the Northern Humboldt Current (NHC) ecosystem, one of the most productive ecosystems in the world. A trophic network model with 33 functional groups was developed using ECOPATH and transformed to an end-to-end model using ECOTRAN techniques to map food web energy flows. Predicted, relative changes in functional group productivity were analyzed in simulations with varying forage fish consumption rates, jellyfish consumption rates, and forage fish harvest rates in a suite of static, alternative-energy-demand scenarios. Our modeling efforts will not only improve EBFM of forage fish and their predators in the NHC ecosystem, but also increase our understanding of trophic interactions between forage fish and large jellyfish, an important, but overlooked component in most ecosystem models to date.

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

Estimation of Ecosystem Parameters of the Community Land Model with DREAM: Evaluation of the Potential for Upscaling Net Ecosystem Exchange

NASA Astrophysics Data System (ADS)

Hendricks Franssen, H. J.; Post, H.; Vrugt, J. A.; Fox, A. M.; Baatz, R.; Kumbhar, P.; Vereecken, H.

2015-12-01

Estimation of net ecosystem exchange (NEE) by land surface models is strongly affected by uncertain ecosystem parameters and initial conditions. A possible approach is the estimation of plant functional type (PFT) specific parameters for sites with measurement data like NEE and application of the parameters at other sites with the same PFT and no measurements. This upscaling strategy was evaluated in this work for sites in Germany and France. Ecosystem parameters and initial conditions were estimated with NEE-time series of one year length, or a time series of only one season. The DREAM(zs) algorithm was used for the estimation of parameters and initial conditions. DREAM(zs) is not limited to Gaussian distributions and can condition to large time series of measurement data simultaneously. DREAM(zs) was used in combination with the Community Land Model (CLM) v4.5. Parameter estimates were evaluated by model predictions at the same site for an independent verification period. In addition, the parameter estimates were evaluated at other, independent sites situated >500km away with the same PFT. The main conclusions are: i) simulations with estimated parameters reproduced better the NEE measurement data in the verification periods, including the annual NEE-sum (23% improvement), annual NEE-cycle and average diurnal NEE course (error reduction by factor 1,6); ii) estimated parameters based on seasonal NEE-data outperformed estimated parameters based on yearly data; iii) in addition, those seasonal parameters were often also significantly different from their yearly equivalents; iv) estimated parameters were significantly different if initial conditions were estimated together with the parameters. We conclude that estimated PFT-specific parameters improve land surface model predictions significantly at independent verification sites and for independent verification periods so that their potential for upscaling is demonstrated. However, simulation results also indicate that possibly the estimated parameters mask other model errors. This would imply that their application at climatic time scales would not improve model predictions. A central question is whether the integration of many different data streams (e.g., biomass, remotely sensed LAI) could solve the problems indicated here.

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

NASA Astrophysics Data System (ADS)

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

2017-07-01

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

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

NASA Astrophysics Data System (ADS)

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

2010-12-01

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

Tree diversity does not always improve resistance of forest ecosystems to drought.

PubMed

Grossiord, Charlotte; Granier, André; Ratcliffe, Sophia; Bouriaud, Olivier; Bruelheide, Helge; Chećko, Ewa; Forrester, David Ian; Dawud, Seid Muhie; Finér, Leena; Pollastrini, Martina; Scherer-Lorenzen, Michael; Valladares, Fernando; Bonal, Damien; Gessler, Arthur

2014-10-14

Climate models predict an increase in the intensity and frequency of drought episodes in the Northern Hemisphere. Among terrestrial ecosystems, forests will be profoundly impacted by drier climatic conditions, with drastic consequences for the functions and services they supply. Simultaneously, biodiversity is known to support a wide range of forest ecosystem functions and services. However, whether biodiversity also improves the resistance of these ecosystems to drought remains unclear. We compared soil drought exposure levels in a total of 160 forest stands within five major forest types across Europe along a gradient of tree species diversity. We assessed soil drought exposure in each forest stand by calculating the stand-level increase in carbon isotope composition of late wood from a wet to a dry year (Δδ(13)CS). Δδ(13)CS exhibited a negative linear relationship with tree species diversity in two forest types, suggesting that species interactions in these forests diminished the drought exposure of the ecosystem. However, the other three forest types were unaffected by tree species diversity. We conclude that higher diversity enhances resistance to drought events only in drought-prone environments. Managing forest ecosystems for high tree species diversity does not necessarily assure improved adaptability to the more severe and frequent drought events predicted for the future.

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

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.

Biodiversity and Climate Modeling Workshop Series: Identifying gaps and needs for improving large-scale biodiversity models

NASA Astrophysics Data System (ADS)

Weiskopf, S. R.; Myers, B.; Beard, T. D.; Jackson, S. T.; Tittensor, D.; Harfoot, M.; Senay, G. B.

2017-12-01

At the global scale, well-accepted global circulation models and agreed-upon scenarios for future climate from the Intergovernmental Panel on Climate Change (IPCC) are available. In contrast, biodiversity modeling at the global scale lacks analogous tools. While there is great interest in development of similar bodies and efforts for international monitoring and modelling of biodiversity at the global scale, equivalent modelling tools are in their infancy. This lack of global biodiversity models compared to the extensive array of general circulation models provides a unique opportunity to bring together climate, ecosystem, and biodiversity modeling experts to promote development of integrated approaches in modeling global biodiversity. Improved models are needed to understand how we are progressing towards the Aichi Biodiversity Targets, many of which are not on track to meet the 2020 goal, threatening global biodiversity conservation, monitoring, and sustainable use. We brought together biodiversity, climate, and remote sensing experts to try to 1) identify lessons learned from the climate community that can be used to improve global biodiversity models; 2) explore how NASA and other remote sensing products could be better integrated into global biodiversity models and 3) advance global biodiversity modeling, prediction, and forecasting to inform the Aichi Biodiversity Targets, the 2030 Sustainable Development Goals, and the Intergovernmental Platform on Biodiversity and Ecosystem Services Global Assessment of Biodiversity and Ecosystem Services. The 1st In-Person meeting focused on determining a roadmap for effective assessment of biodiversity model projections and forecasts by 2030 while integrating and assimilating remote sensing data and applying lessons learned, when appropriate, from climate modeling. Here, we present the outcomes and lessons learned from our first E-discussion and in-person meeting and discuss the next steps for future meetings.

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

PubMed Central

Pitcher, Tony J.

2005-01-01

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

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

Exploring the resilience of industrial ecosystems.

PubMed

Zhu, Junming; Ruth, Matthias

2013-06-15

Industrial ecosystems improve eco-efficiency at the system level through optimizing material and energy flows, which however raises a concern for system resilience because efficiency, as traditionally conceived, not necessarily promotes resilience. By drawing on the concept of resilience in ecological systems and in supply chains, resilience in industrial ecosystems is specified on the basis of a system's ability to maintain eco-efficient material and energy flows under disruptions. Using a network model that captures supply, asset, and organizational dependencies and propagation of disruptions among firms, the resilience, and particularly resistance as an important dimension of resilience, of two real industrial ecosystems and generalized specifications are examined. The results show that an industrial ecosystem is less resistant and less resilient with high inter-firm dependency, preferentially organized physical exchanges, and under disruptions targeted at highly connected firms. An industrial ecosystem with more firms and exchanges is less resistant, but has more eco-efficient flows and potentials, and therefore is less likely to lose its function of eco-efficiency. Taking these determinants for resilience into consideration improves the adaptability of an industrial ecosystem, which helps increase its resilience. Copyright © 2013 Elsevier Ltd. All rights reserved.

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

PubMed

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

2013-10-01

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

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.

Freshwater Ecosystem Service Flow Model To Evaluate Regional Water Security: A Case Study In Beijing-Tianjin-Hebei Region, China

NASA Astrophysics Data System (ADS)

Li, D.; Li, S.

2016-12-01

Freshwater service, as the most important support ecosystem service, is essential to human survival and development. Many studies have evidenced the spatial differences in the supply and demand of ecosystem services and raised the concept of ecosystem service flow. However, rather few studies quantitatively characterize the freshwater service flow. This paper aims to quantify the effect of freshwater ecosystem service flow on downstream areas in Beijing-Tianjin-Hebei (BTH) region, China over 2000, 2005 and 2010. We computed the freshwater ecosystem service provision with InVEST model. We calculated freshwater ecosystem service consumption with water quota method. We simulated the freshwater ecosystem service flow using our simplified flow model and assessed the regional water security with the improved freshwater security index. The freshwater provision service mainly depends on climatic factors that cannot be influenced by management, while the freshwater consumption service is constrained by human activities. Furthermore, the decrease of water quota for agricultural, domestic and industrial water counteracts the impact of increasing freshwater demand. The analysis of freshwater ecosystem service flow reveals that the majority area of the BTH (69.2%) is affected by upstream freshwater. If freshwater ecosystem service flow is considered, the water safety areas of the whole BTH account for 66.9%, 66.1%, 71.3%, which increase 6.4%, 6.8% and 5.7% in 2000, 2005 and 2010, respectively. These results highlight the need to understand the teleconnections between distant freshwater ecosystem service provision and local freshwater ecosystem service use. This approach therefore helps managers choose specific management and investment strategies for critical upstream freshwater provisions across different regions.

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

USGS Publications Warehouse

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

2009-01-01

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

[Health assessment of Qi'ao Island mangrove wetland ecosystem in Pearl River Estuary].

PubMed

Wang, Shu-Gong; Zheng, Yao-Hui; Peng, Yi-Sheng; Chen, Gui-Zhu

2010-02-01

Based on the theories of wetland ecosystem health and by using "Pressure-State-Response" model, a health assessment indicator system for Qi' ao Island mangrove wetland ecosystem in Pearl River Estuary was built, and the assessment indices, assessment criteria, indices weighted values, assessment grades, and assessment methods were established to assess the health state of this ecosystem. In 2008, the overall health index of this ecosystem was 0.6580, health level was of grade II (healthy), and the pressure, state, and response indices were 0.3469, 0.8718, and 0.7754, respectively, suggesting that this ecosystem was good in state and response, but still had definite pressure. As a provincial nature reserve, this ecosystem was to be further improved in its health level. However, the research on the health assessment of mangrove wetland ecosystem was still young. Further studies should be made on the selection of assessment indices, long-term oriented monitoring of these indices, and quantification of the relations between ecosystem health level and ecosystem services.

Ecosystem services valuation to support decisionmaking on public lands—A case study of the San Pedro River watershed, Arizona

USGS Publications Warehouse

Bagstad, Kenneth J.; Semmens, Darius; Winthrop, Rob; Jaworksi, Delilah; Larson, Joel

2012-01-01

This report details the findings of the Bureau of Land Management–U.S. Geological Survey Ecosystem Services Valuation Pilot Study. This project evaluated alternative methods and tools that quantify and value ecosystem services, and it assessed the tools’ readiness for use in the Bureau of Land Management decisionmaking process. We tested these tools on the San Pedro River watershed in northern Sonora, Mexico, and southeast Arizona. The study area includes the San Pedro Riparian National Conservation Area (managed by the Bureau of Land Management), which has been a focal point for conservation activities and scientific research in recent decades. We applied past site-specific primary valuation studies, value transfer, the Wildlife Habitat Benefits Estimation Toolkit, and the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) and Artificial Intelligence for Ecosystem Services (ARIES) models to value locally important ecosystem services for the San Pedro River watershed—water, carbon, biodiversity, and cultural values. We tested these approaches on a series of scenarios to evaluate ecosystem service changes and the ability of the tools to accommodate scenarios. A suite of additional tools were either at too early a stage of development to run, were proprietary, or were place-specific tools inappropriate for application to the San Pedro River watershed. We described the strengths and weaknesses of these additional ecosystem service tools against a series of evaluative criteria related to their usefulness for Bureau of Land Management decisionmaking. Using these tools, we quantified gains or losses of ecosystem services under three categories of scenarios: urban growth, mesquite management, and water augmentation. These results quantify tradeoffs and could be useful for decisionmaking within Bureau of Land Management district or field offices. Results are accompanied by a relatively high level of uncertainty associated with model outputs, valuation methods, and discount rates applied. Further guidance on representing uncertainty and applying uncertain results in decisionmaking would benefit both tool developers and those offices in using ecosystem services to compare management tradeoffs. Decisionmakers and Bureau of Land Management managers at the State-, district-, and field-office level would also benefit from continuing model improvements, training, and guidance on tool use that can be provided by the U.S. Geological Survey, the Bureau of Land Management, and the Department of the Interior. Tradeoffs were identified in the level of effort needed to parameterize and run tools and the amount and quality of information they provide to the decision process. We found the Wildlife Habitat Benefits Estimation Toolkit, Ecosystem Services Review, and United Nations Environment Programme–World Conservation Monitoring Centre Ecosystem Services Toolkit to be immediately feasible for application by the Bureau of Land Management, given proper guidance on their use. It is also feasible for the Bureau of Land Management to use the InVEST model, but in early 2012 the process of parameterizing the model required resources and expertise that are unlikely to be available in most Bureau of Land Management district or field offices. Application of past primary valuation is feasible, but developing new primary-valuation studies is too time consuming for regular application. Value transfer approaches (aside from the Wildlife Habitat Benefits Estimation Toolkit) are best applied carefully on the basis of guidelines described in this report, to reduce transfer error. The ARIES model can provide useful information in regions modeled in the past (Arizona, California, Colorado, and Washington), but it lacks some features that will improve its usability, such as a generalized model that could be applied anywhere in the United States. Eleven other tools described in this report could become useful as the tools more fully develop, in high-profile cases for which additional resources are available for tool application or in case-study regions where place-specific models have already been developed. To improve the value of these tools in decisionmaking, we suggest scientific needs that agencies such as U.S. Geological Survey can help meet—for instance, development and support of data archives. Such archives could greatly reduce resource needs and improve the reliability and consistency of results. Given the rapid state of evolution in the field, periodic follow-up studies on ecosystem services tools would help to ensure that the Bureau of Land Management and other public land management agencies are kept up to date on new tools and features that bring ecosystem services closer to readiness for use in regular decisionmaking.

Mercury concentrations in lentic fish populations related to ecosystem and watershed characteristics

Treesearch

Andrew L. Rypel

2010-01-01

Predicting mercury (Hg) concentrations of fishes at large spatial scales is a fundamental environmental challenge with the potential to improve human health. In this study, mercury concentrations were examined for five species across 161 lakes and ecosystem, and watershed parameters were investigated as explanatory variables in statistical models. For all species, Hg...

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.

The importance of radiation for semiempirical water-use efficiency models

DOE PAGES

Boese, Sven; Jung, Martin; Carvalhais, Nuno; ...

2017-06-22

Water-use efficiency (WUE) is a fundamental property for the coupling of carbon and water cycles in plants and ecosystems. Existing model formulations predicting this variable differ in the type of response of WUE to the atmospheric vapor pressure deficit of water (VPD). We tested a representative WUE model on the ecosystem scale at 110 eddy covariance sites of the FLUXNET initiative by predicting evapotranspiration (ET) based on gross primary productivity (GPP) and VPD. We found that introducing an intercept term in the formulation increases model performance considerably, indicating that an additional factor needs to be considered. We demonstrate that thismore » intercept term varies seasonally and we subsequently associate it with radiation. Replacing the constant intercept term with a linear function of global radiation was found to further improve model predictions of ET. Our new semiempirical ecosystem WUE formulation indicates that, averaged over all sites, this radiation term accounts for up to half (39–47 %) of transpiration. These empirical findings challenge the current understanding of water-use efficiency on the ecosystem scale.« less

Model development of a participatory Bayesian network for coupling ecosystem services into integrated water resources management

NASA Astrophysics Data System (ADS)

Xue, Jie; Gui, Dongwei; Lei, Jiaqiang; Zeng, Fanjiang; Mao, Donglei; Zhang, Zhiwei

2017-11-01

There is an increasing consensus on the importance of coupling ecosystem services (ES) into integrated water resource management (IWRM), due to a wide range of benefits to human from the ES. This paper proposes an ES-based IWRM framework within which a participatory Bayesian network (BN) model is developed to assist with the coupling between ES and IWRM. The framework includes three steps: identifying water-related services of ecosystems; analysis of the tradeoff and synergy among users of water; and ES-based IWRM implementation using the participatory BN model. We present the development, evaluation and application of the participatory BN model with the involvement of four participant groups (stakeholders, water manager, water management experts, and research team) in Qira oasis area, Northwest China. As a typical catchment-scale region, the Qira oasis area is facing severe water competition between the demands of human activities and natural ecosystems. Results demonstrate that the BN model developed provides effective integration of ES into a quantitative IWMR framework via public negotiation and feedback. The network results, sensitivity evaluation, and management scenarios are broadly accepted by the participant groups. The intervention scenarios from the model conclude that any water management measure remains unable to sustain the ecosystem health in water-related ES. Greater cooperation among the stakeholders is highly necessary for dealing with such water conflicts. In particular, a proportion of the agricultural water saved through improving water-use efficiency should be transferred to natural ecosystems via water trade. The BN model developed is appropriate for areas throughout the world in which there is intense competition for water between human activities and ecosystems.

Partitioning sources of uncertainty in projecting the impact of future climate extremes on site to regional ecosystem carbon cycling

NASA Astrophysics Data System (ADS)

Simkins, J.; Desai, A. R.; Cowdery, E.; Dietze, M.; Rollinson, C.

2016-12-01

The terrestrial biosphere assimilates nearly one fourth of anthropogenic carbon dioxide emissions, providing a significant ecosystem service. Anthropogenic climate changes that influence the distribution and frequency of weather extremes and can have a momentous impact on this useful function that ecosystems provide. However, most analyses of the impact of extreme events on ecosystem carbon uptake do not integrate across the wide range of structural, parametric, and driver uncertainty that needs to be taken into account to estimate probability of changes to ecosystem function under shifts in climate patterns. In order to improve ecosystem model forecasts, we integrated and estimated these sources of uncertainty using an open-sourced informatics workflow, the Predictive ECosystem Analyzer (PEcAn, http://pecanproject.org). PEcAn allows any researcher to parameterize and run multiple ecosystem models and automate extraction of meteorological forcing and estimation of its uncertainty. Trait databases and a uniform protocol for parameterizing and driving models were used to test parametric and structural uncertainty. In order to sample the uncertainty in future projected meteorological drivers, we developed automated extraction routines to acquire site-level three-hourly Coupled Model Intercomparison Project 5 (CMIP5) forcing data from the Geophysical Fluid Dynamics Laboratory general circulation models (CM3, ESM2M, and ESM2G) across the r1i1p1, r3i1p1 and r5i1p1 ensembles and AR5 emission scenarios. We also implemented a site-level high temporal resolution downscaling technique for these forcings calibrated against half-hourly eddy covariance flux tower observations. Our hypothesis claims that parametric and driver uncertainty dominate over the model structural uncertainty. In order to test this, we partition the uncertainty budget on the ChEAS regional network of towers in Northern Wisconsin, USA where each tower is located in forest and wetland ecosystems.

Improving Estimates and Forecasts of Lake Carbon Pools and Fluxes Using Data Assimilation

NASA Astrophysics Data System (ADS)

Zwart, J. A.; Hararuk, O.; Prairie, Y.; Solomon, C.; Jones, S.

2017-12-01

Lakes are biogeochemical hotspots on the landscape, contributing significantly to the global carbon cycle despite their small areal coverage. Observations and models of lake carbon pools and fluxes are rarely explicitly combined through data assimilation despite significant use of this technique in other fields with great success. Data assimilation adds value to both observations and models by constraining models with observations of the system and by leveraging knowledge of the system formalized by the model to objectively fill information gaps. In this analysis, we highlight the utility of data assimilation in lake carbon cycling research by using the Ensemble Kalman Filter to combine simple lake carbon models with observations of lake carbon pools. We demonstrate the use of data assimilation to improve a model's representation of lake carbon dynamics, to reduce uncertainty in estimates of lake carbon pools and fluxes, and to improve the accuracy of carbon pool size estimates relative to estimates derived from observations alone. Data assimilation techniques should be embraced as valuable tools for lake biogeochemists interested in learning about ecosystem dynamics and forecasting ecosystem states and processes.

Integrated modelling of ecosystem services and energy systems research

NASA Astrophysics Data System (ADS)

Agarwala, Matthew; Lovett, Andrew; Bateman, Ian; Day, Brett; Agnolucci, Paolo; Ziv, Guy

2016-04-01

The UK Government is formally committed to reducing carbon emissions and protecting and improving natural capital and the environment. However, actually delivering on these objectives requires an integrated approach to addressing two parallel challenges: de-carbonising future energy system pathways; and safeguarding natural capital to ensure the continued flow of ecosystem services. Although both emphasise benefiting from natural resources, efforts to connect natural capital and energy systems research have been limited, meaning opportunities to improve management of natural resources and meet society's energy needs could be missed. The ecosystem services paradigm provides a consistent conceptual framework that applies in multiple disciplines across the natural and economic sciences, and facilitates collaboration between them. At the forefront of the field, integrated ecosystem service - economy models have guided public- and private-sector decision making at all levels. Models vary in sophistication from simple spreadsheet tools to complex software packages integrating biophysical, GIS and economic models and draw upon many fields, including ecology, hydrology, geography, systems theory, economics and the social sciences. They also differ in their ability to value changes in natural capital and ecosystem services at various spatial and temporal scales. Despite these differences, current models share a common feature: their treatment of energy systems is superficial at best. In contrast, energy systems research has no widely adopted, unifying conceptual framework that organises thinking about key system components and interactions. Instead, the literature is organised around modelling approaches, including life cycle analyses, econometric investigations, linear programming and computable general equilibrium models. However, some consistencies do emerge. First, often contain a linear set of steps, from exploration to resource supply, fuel processing, conversion/generation, transmission, distribution, and finally, end energy use. Although each step clearly impacts upon natural capital, links to the natural environment are rarely identified or quantified within energy research. In short, the respective conceptual frameworks guiding ecosystem service and energy research are not well integrated. Major knowledge and research gaps appear at the system boundaries: while energy models may mention flows of residuals, exploring where exactly these flows enter the environment, and how they impact ecosystems and natural capital is often considered to be 'outside the system boundary'. While integrated modelling represents the frontier of ecosystem service research, current efforts largely ignore the future energy pathways set out by energy systems models and government carbon targets. This disconnect means that policy-oriented research on how best to (i) maintain natural capital and (ii) meet specific climate targets may be poorly aligned, or worse, offer conflicting advice. We present a re-imagined version of the ecosystem services conceptual framework, in which emphasis is placed on interactions between energy systems and the natural environment. Using the UK as a case study, we employ a recent integrated environmental-economic ecosystem service model, TIM, developed by Bateman et al (2014) and energy pathways developed by the UK Energy Research Centre and the UK Government Committee on Climate Change to illustrate how the new conceptual framework might apply in real world applications.

LakeMetabolizer: An R package for estimating lake metabolism from free-water oxygen using diverse statistical models

USGS Publications Warehouse

Winslow, Luke; Zwart, Jacob A.; Batt, Ryan D.; Dugan, Hilary; Woolway, R. Iestyn; Corman, Jessica; Hanson, Paul C.; Read, Jordan S.

2016-01-01

Metabolism is a fundamental process in ecosystems that crosses multiple scales of organization from individual organisms to whole ecosystems. To improve sharing and reuse of published metabolism models, we developed LakeMetabolizer, an R package for estimating lake metabolism from in situ time series of dissolved oxygen, water temperature, and, optionally, additional environmental variables. LakeMetabolizer implements 5 different metabolism models with diverse statistical underpinnings: bookkeeping, ordinary least squares, maximum likelihood, Kalman filter, and Bayesian. Each of these 5 metabolism models can be combined with 1 of 7 models for computing the coefficient of gas exchange across the air–water interface (k). LakeMetabolizer also features a variety of supporting functions that compute conversions and implement calculations commonly applied to raw data prior to estimating metabolism (e.g., oxygen saturation and optical conversion models). These tools have been organized into an R package that contains example data, example use-cases, and function documentation. The release package version is available on the Comprehensive R Archive Network (CRAN), and the full open-source GPL-licensed code is freely available for examination and extension online. With this unified, open-source, and freely available package, we hope to improve access and facilitate the application of metabolism in studies and management of lentic ecosystems.

Global carbon assimilation system using a local ensemble Kalman filter with multiple ecosystem models

NASA Astrophysics Data System (ADS)

Zhang, Shupeng; Yi, Xue; Zheng, Xiaogu; Chen, Zhuoqi; Dan, Bo; Zhang, Xuanze

2014-11-01

In this paper, a global carbon assimilation system (GCAS) is developed for optimizing the global land surface carbon flux at 1° resolution using multiple ecosystem models. In GCAS, three ecosystem models, Boreal Ecosystem Productivity Simulator, Carnegie-Ames-Stanford Approach, and Community Atmosphere Biosphere Land Exchange, produce the prior fluxes, and an atmospheric transport model, Model for OZone And Related chemical Tracers, is used to calculate atmospheric CO2 concentrations resulting from these prior fluxes. A local ensemble Kalman filter is developed to assimilate atmospheric CO2 data observed at 92 stations to optimize the carbon flux for six land regions, and the Bayesian model averaging method is implemented in GCAS to calculate the weighted average of the optimized fluxes based on individual ecosystem models. The weights for the models are found according to the closeness of their forecasted CO2 concentration to observation. Results of this study show that the model weights vary in time and space, allowing for an optimum utilization of different strengths of different ecosystem models. It is also demonstrated that spatial localization is an effective technique to avoid spurious optimization results for regions that are not well constrained by the atmospheric data. Based on the multimodel optimized flux from GCAS, we found that the average global terrestrial carbon sink over the 2002-2008 period is 2.97 ± 1.1 PgC yr-1, and the sinks are 0.88 ± 0.52, 0.27 ± 0.33, 0.67 ± 0.39, 0.90 ± 0.68, 0.21 ± 0.31, and 0.04 ± 0.08 PgC yr-1 for the North America, South America, Africa, Eurasia, Tropical Asia, and Australia, respectively. This multimodel GCAS can be used to improve global carbon cycle estimation.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Technical Reports Server (NTRS)

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

2016-01-01

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

Follow-on proposal identifying environmental features for land management decisions

NASA Technical Reports Server (NTRS)

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

1986-01-01

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

Pajarito Aerosol Couplings to Ecosystems (PACE) Field Campaign Report

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

Dubey, M

Laboratory (LANL) worked on the Pajarito Aerosol Couplings to Ecosystems (PACE) intensive operational period (IOP). PACE’s primary goal was to demonstrate routine Mobile Aerosol Observing System (MAOS) field operations and improve instrumental and operational performance. LANL operated the instruments efficiently and effectively with remote guidance by the instrument mentors. This was the first time a complex suite of instruments had been operated under the ARM model and it proved to be a very successful and cost-effective model to build upon.

Leaf bacterial diversity mediates plant diversity and ecosystem function relationships.

PubMed

Laforest-Lapointe, Isabelle; Paquette, Alain; Messier, Christian; Kembel, Steven W

2017-06-01

Research on biodiversity and ecosystem functioning has demonstrated links between plant diversity and ecosystem functions such as productivity. At other trophic levels, the plant microbiome has been shown to influence host plant fitness and function, and host-associated microbes have been proposed to influence ecosystem function through their role in defining the extended phenotype of host organisms However, the importance of the plant microbiome for ecosystem function has not been quantified in the context of the known importance of plant diversity and traits. Here, using a tree biodiversity-ecosystem functioning experiment, we provide strong support for the hypothesis that leaf bacterial diversity is positively linked to ecosystem productivity, even after accounting for the role of plant diversity. Our results also show that host species identity, functional identity and functional diversity are the main determinants of leaf bacterial community structure and diversity. Our study provides evidence of a positive correlation between plant-associated microbial diversity and terrestrial ecosystem productivity, and a new mechanism by which models of biodiversity-ecosystem functioning relationships can be improved.

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.

The unseen iceberg: Plant roots in arctic tundra

USGS Publications Warehouse

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

2015-01-01

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

Sharing the floodplain: Mediated modeling for environmental management

USGS Publications Warehouse

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

2010-01-01

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

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.

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.

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.

Social values for ecosystem services (SolVES): Documentation and user manual, version 2.0

USGS Publications Warehouse

Sherrouse, Benson C.; Semmens, Darius J.

2012-01-01

In response to the need for incorporating quantified and spatially explicit measures of social values into ecosystem services assessments, the Rocky Mountain Geographic Science Center (RMGSC), in collaboration with Colorado State University, developed a geographic information system (GIS) application, Social Values for Ecosystem Services (SolVES). With version 2.0 (SolVES 2.0), RMGSC has improved and extended the functionality of SolVES, which was designed to assess, map, and quantify the perceived social values of ecosystem services. Social values such as aesthetics, biodiversity, and recreation can be evaluated for various stakeholder groups as distinguished by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with the previous version, SolVES 2.0 derives a quantitative, 10-point, social-values metric, the Value Index, from a combination of spatial and nonspatial responses to public attitude and preference surveys and calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. Additionally, SolVES 2.0 integrates Maxent maximum entropy modeling software to generate more complete social value maps and to produce robust statistical models describing the relationship between the social values maps and explanatory environmental variables. The performance of these models can be evaluated for a primary study area, as well as for similar areas where primary survey data are not available but where social value mapping could potentially be completed using value-transfer methodology. SolVES 2.0 also introduces the flexibility for users to define their own social values and public uses, model any number and type of environmental variable, and modify the spatial resolution of analysis. With these enhancements, SolVES 2.0 provides an improved public domain tool for decisionmakers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among different ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

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.

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

PubMed

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

2018-04-13

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

Comparative review of multifunctionality and ecosystem services in sustainable agriculture.

PubMed

Huang, Jiao; Tichit, Muriel; Poulot, Monique; Darly, Ségolène; Li, Shuangcheng; Petit, Caroline; Aubry, Christine

2015-02-01

Two scientific communities with broad interest in sustainable agriculture independently focus on multifunctional agriculture or ecosystem services. These communities have limited interaction and exchange, and each group faces research challenges according to independently operating paradigms. This paper presents a comparative review of published research in multifunctional agriculture and ecosystem services. The motivation for this work is to improve communication, integrate experimental approaches, and propose areas of consensus and dialog for the two communities. This extensive analysis of publication trends, ideologies, and approaches enables formulation of four main conclusions. First, the two communities are closely related through their use of the term "function." However, multifunctional agriculture considers functions as agricultural activity outputs and prefers farm-centred approaches, whereas ecosystem services considers ecosystem functions in the provision of services and prefers service-centred approaches. Second, research approaches to common questions in these two communities share some similarities, and there would be great value in integrating these approaches. Third, the two communities have potential for dialog regarding the bundle of ecosystem services and the spectrum of multifunctional agriculture, or regarding land sharing and land sparing. Fourth, we propose an integrated conceptual framework that distinguishes six groups of ecosystem services and disservices in the agricultural landscape, and combines the concepts of multifunctional agriculture and ecosystem services. This integrated framework improves applications of multifunctional agriculture and ecosystem services for operational use. Future research should examine if the framework can be readily adapted for modelling specific problems in agricultural management. Copyright © 2014 Elsevier Ltd. All rights reserved.

Taking the pulse of mountains: Ecosystem responses to climatic variability

USGS Publications Warehouse

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

2003-01-01

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

Hybrid modeling approach for the northern Adriatic watershed management.

PubMed

Volf, Goran; Atanasova, Nataša; Škerjanec, Mateja; Ožanić, Nevenka

2018-04-23

Northern Adriatic (NA) is one of the most productive parts of the Mediterranean Sea due to vast nutrient discharges from the contributing watershed. To understand better the excess of nutrients as stressors to the state of the marine ecosystem, a hybrid modeling approach following the DPSIR framework and terminology was developed, linking: 1) the AVGWLF model for modeling the pressures, i.e. nutrients originating from the watershed caused by two major drivers (urbanization and agriculture), 2) the ML tool MTSMOTI for inducing a model tree connecting the pressures with the marine ecosystem state, and 3) the water quality index, TRIX, equation to evaluate the trophic state of the marine ecosystem. Data used for the modeling purpose comprised GIS layers (i.e., digital terrain model, land use/cover data, soil map, locations of hydro-meteorological stations and WWTPs), time series data (i.e., hydro-meteorological data and nutrient concentrations), and statistical data (i.e., number of inhabitants, connections to wastewater treatment, livestock statistics, etc.) as well as physical, chemical and biological parameters, measured at six marine water monitoring stations, located between the Po River delta (Italy) and the city of Rovinj (west Istrian coast, Croatia). Using the model, seven watershed management scenarios related to wastewater treatment and agricultural activities were evaluated for their influence on the state of the NA marine ecosystem. According to the results, the gradual implementation of the UWWTD in the last 10years contributed significantly to the preservation and improvement of the NA marine ecosystem state. However, despite the full implementation of the UWWTD, the state of the NA marine ecosystem could deteriorate in case of increased nutrient loads from agriculture. Since the UWWTD is already close to its full implementation, NA watershed management should focus on controlling agricultural activities in order to maintain 'high' state of the NA marine ecosystem. Copyright © 2018 Elsevier B.V. All rights reserved.

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.

A methodology for adaptable and robust ecosystem services assessment.

PubMed

Villa, Ferdinando; Bagstad, Kenneth J; Voigt, Brian; Johnson, Gary W; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant "one model fits all" paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES--both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

A methodology for adaptable and robust ecosystem services assessment

USGS Publications Warehouse

Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts.

A Methodology for Adaptable and Robust Ecosystem Services Assessment

PubMed Central

Villa, Ferdinando; Bagstad, Kenneth J.; Voigt, Brian; Johnson, Gary W.; Portela, Rosimeiry; Honzák, Miroslav; Batker, David

2014-01-01

Ecosystem Services (ES) are an established conceptual framework for attributing value to the benefits that nature provides to humans. As the promise of robust ES-driven management is put to the test, shortcomings in our ability to accurately measure, map, and value ES have surfaced. On the research side, mainstream methods for ES assessment still fall short of addressing the complex, multi-scale biophysical and socioeconomic dynamics inherent in ES provision, flow, and use. On the practitioner side, application of methods remains onerous due to data and model parameterization requirements. Further, it is increasingly clear that the dominant “one model fits all” paradigm is often ill-suited to address the diversity of real-world management situations that exist across the broad spectrum of coupled human-natural systems. This article introduces an integrated ES modeling methodology, named ARIES (ARtificial Intelligence for Ecosystem Services), which aims to introduce improvements on these fronts. To improve conceptual detail and representation of ES dynamics, it adopts a uniform conceptualization of ES that gives equal emphasis to their production, flow and use by society, while keeping model complexity low enough to enable rapid and inexpensive assessment in many contexts and for multiple services. To improve fit to diverse application contexts, the methodology is assisted by model integration technologies that allow assembly of customized models from a growing model base. By using computer learning and reasoning, model structure may be specialized for each application context without requiring costly expertise. In this article we discuss the founding principles of ARIES - both its innovative aspects for ES science and as an example of a new strategy to support more accurate decision making in diverse application contexts. PMID:24625496

Modeling the potential impacts of climate change on the water table level of selected forested wetlands in the southeastern United States

Treesearch

Jie Zhu; Ge Sun; Wenhong Li; Yu Zhang; Guofang Miao; Asko Noormets; Steve G. McNulty; John S. King; Mukesh Kumar; Xuan Wang

2017-01-01

The southeastern United States hosts extensive forested wetlands, providing ecosystem services including carbon sequestration, water quality improvement, ground- water recharge, and wildlife habitat. However, these wet- land ecosystems are dependent on local climate and hydrol- ogy, and are therefore at risk due to climate and land use change. This study develops site-...

Ecological role and services of tropical mangrove ecosystems: a reassessment

USGS Publications Warehouse

Lee, Shing Yip; Primavera, Jurgene H.; Dahdouh-Guebas, Farid; McKee, Karen; Bosire, Jared O.; Cannicci, Stefano; Diele, Karen; Fromard, Francois; Koedam, Nico; Marchand, Cyril; Mendelssohn, Irving; Mukherjee, Nibedita; Record, Sydne

2014-01-01

Knowledge of thresholds, spatio-temporal scaling and variability due to geographic, biogeographic and socio-economic settings will improve the management of mangrove ecosystem services. Many drivers respond to global trends in climate change and local changes such as urbanization. While mangroves have traditionally been managed for subsistence, future governance models must involve partnerships between local custodians of mangroves and offsite beneficiaries of the services.

[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.

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.

Systems Modeling to Improve River, Riparian, and Wetland Habitat Quality and Area

NASA Astrophysics Data System (ADS)

Alafifi, A.

2016-12-01

The suitability of watershed habitat to support the livelihood of its biota primarily depends on managing flow. Ecological restoration requires finding opportunities to reallocate available water in a watershed to increase ecological benefits and maintain other beneficial uses. We present the Watershed Area of Suitable Habitat (WASH) systems model that recommends reservoir releases, streamflows, and water allocations throughout a watershed to maximize the ecosystem habitat quality. WASH embeds and aggregates area-weighted metrics for aquatic, floodplain, and wetland habitat components as an ecosystem objective to maximize, while maintaining water deliveries for domestic and agricultural uses, mass balance, and available budget for restoration actions. The metrics add spatial and temporal functionality and area coverage to traditional habitat quality indexes and can accommodate multiple species of concern. We apply the WASH model to the Utah portion of the Bear River watershed which includes 8 demand sites, 5 reservoirs and 37 nodes between the Utah-Idaho state line and the Great Salt Lake. We recommend water allocations to improve current conservation efforts and show tradeoffs between human and ecosystem uses of water. WASH results are displayed on an open-source web mapping application that allows stakeholders to access, visualize, and interact with the model data and results and compare current and model-recommended operations. Results show that the Bear River is largely developed and appropriated for human water uses. However, increasing reservoirs winter and early spring releases and minimizing late spring spill volumes can significantly improve habitat quality without harming agricultural or urban water users. The spatial and temporal reallocation of spring spills to environmental uses creates additional 70 thousand acres of suitable habitat in the watershed without harming human users. WASH also quantifies the potential environmental gains and losses from conserving water and from the impact of climate change on head flows and thus helps planning for the future of our water resources and ecosystem.

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.

Sensitivity of global terrestrial carbon cycle dynamics to variability in satellite-observed burned area

NASA Astrophysics Data System (ADS)

Poulter, Benjamin; Cadule, Patricia; Cheiney, Audrey; Ciais, Philippe; Hodson, Elke; Peylin, Philippe; Plummer, Stephen; Spessa, Allan; Saatchi, Sassan; Yue, Chao; Zimmermann, Niklaus E.

2015-02-01

Fire plays an important role in terrestrial ecosystems by regulating biogeochemistry, biogeography, and energy budgets, yet despite the importance of fire as an integral ecosystem process, significant advances remain to improve its prognostic representation in carbon cycle models. To recommend and to help prioritize model improvements, this study investigates the sensitivity of a coupled global biogeography and biogeochemistry model, LPJ, to observed burned area measured by three independent satellite-derived products, GFED v3.1, L3JRC, and GlobCarbon. Model variables are compared with benchmarks that include pantropical aboveground biomass, global tree cover, and CO2 and CO trace gas concentrations. Depending on prescribed burned area product, global aboveground carbon stocks varied by 300 Pg C, and woody cover ranged from 50 to 73 Mkm2. Tree cover and biomass were both reduced linearly with increasing burned area, i.e., at regional scales, a 10% reduction in tree cover per 1000 km2, and 0.04-to-0.40 Mg C reduction per 1000 km2. In boreal regions, satellite burned area improved simulated tree cover and biomass distributions, but in savanna regions, model-data correlations decreased. Global net biome production was relatively insensitive to burned area, and the long-term land carbon sink was robust, 2.5 Pg C yr-1, suggesting that feedbacks from ecosystem respiration compensated for reductions in fuel consumption via fire. CO2 transport provided further evidence that heterotrophic respiration compensated any emission reductions in the absence of fire, with minor differences in modeled CO2 fluxes among burned area products. CO was a more sensitive indicator for evaluating fire emissions, with MODIS-GFED burned area producing CO concentrations largely in agreement with independent observations in high latitudes. This study illustrates how ensembles of burned area data sets can be used to diagnose model structures and parameters for further improvement and also highlights the importance in considering uncertainties and variability in observed burned area data products for model applications.

Collaborative Proposal: Improving Decadal Prediction of Arctic Climate Variability and Change Using a Regional Arctic System Model (RASM)

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

Maslowski, Wieslaw

This project aims to develop, apply and evaluate a regional Arctic System model (RASM) for enhanced decadal predictions. Its overarching goal is to advance understanding of the past and present states of arctic climate and to facilitate improvements in seasonal to decadal predictions. In particular, it will focus on variability and long-term change of energy and freshwater flows through the arctic climate system. The project will also address modes of natural climate variability as well as extreme and rapid climate change in a region of the Earth that is: (i) a key indicator of the state of global climate throughmore » polar amplification and (ii) which is undergoing environmental transitions not seen in instrumental records. RASM will readily allow the addition of other earth system components, such as ecosystem or biochemistry models, thus allowing it to facilitate studies of climate impacts (e.g., droughts and fires) and of ecosystem adaptations to these impacts. As such, RASM is expected to become a foundation for more complete Arctic System models and part of a model hierarchy important for improving climate modeling and predictions.« less

The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate.

PubMed

Jing, Xin; Sanders, Nathan J; Shi, Yu; Chu, Haiyan; Classen, Aimée T; Zhao, Ke; Chen, Litong; Shi, Yue; Jiang, Youxu; He, Jin-Sheng

2015-09-02

Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation in EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems.

The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate

DOE PAGES

Jing, Xin; Sanders, Nathan J.; Shi, Yu; ...

2015-09-02

Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation inmore » EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems.« less

The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate

PubMed Central

Jing, Xin; Sanders, Nathan J.; Shi, Yu; Chu, Haiyan; Classen, Aimée T.; Zhao, Ke; Chen, Litong; Shi, Yue; Jiang, Youxu; He, Jin-Sheng

2015-01-01

Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation in EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems. PMID:26328906

The links between ecosystem multifunctionality and above- and belowground biodiversity are mediated by climate

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

Jing, Xin; Sanders, Nathan J.; Shi, Yu

Plant biodiversity is often correlated with ecosystem functioning in terrestrial ecosystems. However, we know little about the relative and combined effects of above- and belowground biodiversity on multiple ecosystem functions (for example, ecosystem multifunctionality, EMF) or how climate might mediate those relationships. Here we tease apart the effects of biotic and abiotic factors, both above- and belowground, on EMF on the Tibetan Plateau, China. We found that a suite of biotic and abiotic variables account for up to 86% of the variation in EMF, with the combined effects of above- and belowground biodiversity accounting for 45% of the variation inmore » EMF. Our results have two important implications: first, including belowground biodiversity in models can improve the ability to explain and predict EMF. Second, regional-scale variation in climate, and perhaps climate change, can determine, or at least modify, the effects of biodiversity on EMF in natural ecosystems.« less

Challenges and opportunities for integrating lake ecosystem modelling approaches

USGS Publications Warehouse

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

2010-01-01

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

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.

Preface [to special section on recent Loch Vale Watershed research

USGS Publications Warehouse

Baron, Jill S.; Williams, Mark W.

2000-01-01

Catchment-scale intensive and extensive research conducted over the last decade shows that our understanding of the biogeochemical and hydrologic processes in subalpine and alpine basins is not yet sufficiently mature to model and predict how biogeochemical transformations and surface water quality will change in response to climatic or human-driven changes in energy, water, and chemicals. A better understanding of these processes is needed for input to decision-making regulatory agencies and federal land managers. In recognition of this problem the National Research Council [1998] has identified as a critical research need an improved understanding of how global change will affect biogeochemical interactions with the hydrologic cycle and biogeochemical controls over the transport of water, nutrients, and materials from land to freshwater ecosystems. Improved knowledge of alpine and subalpine ecosystems is particularly important since high-elevation catchments are very sensitive to small changes in the flux of energy, chemicals, and water. Furthermore, alpine ecosystems may act as early warning indicators for ecosystem changes at lower elevations.

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.

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.

Functional responses and scaling in predator-prey interactions of marine fishes: contemporary issues and emerging concepts.

PubMed

Hunsicker, Mary E; Ciannelli, Lorenzo; Bailey, Kevin M; Buckel, Jeffrey A; Wilson White, J; Link, Jason S; Essington, Timothy E; Gaichas, Sarah; Anderson, Todd W; Brodeur, Richard D; Chan, Kung-Sik; Chen, Kun; Englund, Göran; Frank, Kenneth T; Freitas, Vânia; Hixon, Mark A; Hurst, Thomas; Johnson, Darren W; Kitchell, James F; Reese, Doug; Rose, George A; Sjodin, Henrik; Sydeman, William J; van der Veer, Henk W; Vollset, Knut; Zador, Stephani

2011-12-01

Predator-prey interactions are a primary structuring force vital to the resilience of marine communities and sustainability of the world's oceans. Human influences on marine ecosystems mediate changes in species interactions. This generality is evinced by the cascading effects of overharvesting top predators on the structure and function of marine ecosystems. It follows that ecological forecasting, ecosystem management, and marine spatial planning require a better understanding of food web relationships. Characterising and scaling predator-prey interactions for use in tactical and strategic tools (i.e. multi-species management and ecosystem models) are paramount in this effort. Here, we explore what issues are involved and must be considered to advance the use of predator-prey theory in the context of marine fisheries science. We address pertinent contemporary ecological issues including (1) the approaches and complexities of evaluating predator responses in marine systems; (2) the 'scaling up' of predator-prey interactions to the population, community, and ecosystem level; (3) the role of predator-prey theory in contemporary fisheries and ecosystem modelling approaches; and (4) directions for the future. Our intent is to point out needed research directions that will improve our understanding of predator-prey interactions in the context of the sustainable marine fisheries and ecosystem management. 2011 Blackwell Publishing Ltd/CNRS.

The unseen iceberg: plant roots in arctic tundra.

PubMed

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

2015-01-01

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

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.

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

PubMed Central

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2009-04-01

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

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

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.

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.

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.

A framework to assess biogeochemical response to ecosystem disturbance using nutrient partitioning ratios

USGS Publications Warehouse

Kranabetter, J. Marty; McLauchlan, Kendra K.; Enders, Sara K.; Fraterrigo, Jennifer M.; Higuera, Philip E.; Morris, Jesse L.; Rastetter, Edward B.; Barnes, Rebecca; Buma, Brian; Gavin, Daniel G.; Gerhart, Laci M.; Gillson, Lindsey; Hietz, Peter; Mack, Michelle C.; McNeil, Brenden; Perakis, Steven

2016-01-01

Disturbances affect almost all terrestrial ecosystems, but it has been difficult to identify general principles regarding these influences. To improve our understanding of the long-term consequences of disturbance on terrestrial ecosystems, we present a conceptual framework that analyzes disturbances by their biogeochemical impacts. We posit that the ratio of soil and plant nutrient stocks in mature ecosystems represents a characteristic site property. Focusing on nitrogen (N), we hypothesize that this partitioning ratio (soil N: plant N) will undergo a predictable trajectory after disturbance. We investigate the nature of this partitioning ratio with three approaches: (1) nutrient stock data from forested ecosystems in North America, (2) a process-based ecosystem model, and (3) conceptual shifts in site nutrient availability with altered disturbance frequency. Partitioning ratios could be applied to a variety of ecosystems and successional states, allowing for improved temporal scaling of disturbance events. The generally short-term empirical evidence for recovery trajectories of nutrient stocks and partitioning ratios suggests two areas for future research. First, we need to recognize and quantify how disturbance effects can be accreting or depleting, depending on whether their net effect is to increase or decrease ecosystem nutrient stocks. Second, we need to test how altered disturbance frequencies from the present state may be constructive or destructive in their effects on biogeochemical cycling and nutrient availability. Long-term studies, with repeated sampling of soils and vegetation, will be essential in further developing this framework of biogeochemical response to disturbance.

Identifying Thresholds for Ecosystem-Based Management

PubMed Central

Samhouri, Jameal F.; Levin, Phillip S.; Ainsworth, Cameron H.

2010-01-01

Background One of the greatest obstacles to moving ecosystem-based management (EBM) from concept to practice is the lack of a systematic approach to defining ecosystem-level decision criteria, or reference points that trigger management action. Methodology/Principal Findings To assist resource managers and policymakers in developing EBM decision criteria, we introduce a quantitative, transferable method for identifying utility thresholds. A utility threshold is the level of human-induced pressure (e.g., pollution) at which small changes produce substantial improvements toward the EBM goal of protecting an ecosystem's structural (e.g., diversity) and functional (e.g., resilience) attributes. The analytical approach is based on the detection of nonlinearities in relationships between ecosystem attributes and pressures. We illustrate the method with a hypothetical case study of (1) fishing and (2) nearshore habitat pressure using an empirically-validated marine ecosystem model for British Columbia, Canada, and derive numerical threshold values in terms of the density of two empirically-tractable indicator groups, sablefish and jellyfish. We also describe how to incorporate uncertainty into the estimation of utility thresholds and highlight their value in the context of understanding EBM trade-offs. Conclusions/Significance For any policy scenario, an understanding of utility thresholds provides insight into the amount and type of management intervention required to make significant progress toward improved ecosystem structure and function. The approach outlined in this paper can be applied in the context of single or multiple human-induced pressures, to any marine, freshwater, or terrestrial ecosystem, and should facilitate more effective management. PMID:20126647

Economics of social trade-off: Balancing wastewater treatment cost and ecosystem damage.

PubMed

Jiang, Yu; Dinar, Ariel; Hellegers, Petra

2018-04-01

We have developed a social optimization model that integrates the financial and ecological costs associated with wastewater treatment and ecosystem damage. The social optimal abatement level of water pollution is determined by finding the trade-off between the cost of pollution control and its resulting ecosystem damage. The model is applied to data from the Lake Taihu region in China to demonstrate this trade-off. A wastewater treatment cost function is estimated with a sizable sample from China, and an ecological damage cost function is estimated following an ecosystem service valuation framework. Results show that the wastewater treatment cost function has economies of scale in facility capacity, and diseconomies in pollutant removal efficiency. Results also show that a low value of the ecosystem service will lead to serious ecological damage. One important policy implication is that the assimilative capacity of the lake should be enhanced by forbidding over extraction of water from the lake. It is also suggested that more work should be done to improve the accuracy of the economic valuation. Copyright © 2018 Elsevier Ltd. All rights reserved.

Proactive responses to human impacts that balance development and Atlantic salmon (Salmo salar) conservation: An integrative model

USGS Publications Warehouse

Wilzbach, M.A.; Mather, M. E.; Folt, C.L.; Moore, A.; Naiman, R.J.; Youngson, A.F.; McMenemy, J.

1998-01-01

Incorporating human impacts into conservation plans is critical to protect natural resources. Using a model that examines how anthropogenic changes might be proactively influenced to promote conservation, we argue that a denser human population does not spell inevitable doom for Atlantic salmon (Salmo salar). Humans affect the Atlantic salmon ecosystem deleteriously through landscape alteration, exploitation, external inputs, and resource competition. An intact ecosystem provides positive feedback to society by providing food, ecosystem services, and improving the quality of life. As Atlantic salmon and associated ecosystem benefits are increasingly valued by society, policies, laws, and regulations that protect salmon populations and habitats are codified into a 'control system' or institutional infrastructure. Via research that helps maintain wild salmon populations and in informing the public about the benefits of a healthy Atlantic salmon ecosystem, scientists can influence public attitudes and facilitate the implementation of environmental policies that moderate harmful anthropogenic changes. Because exchange among scientists is of paramount importance in increasing our understanding of important interrelationships between humans and fish, we recommend the establishment of an international salmon organizational for research.

Comparison of Coral Reef Ecosystems along a Fishing Pressure Gradient

PubMed Central

Weijerman, Mariska; Fulton, Elizabeth A.; Parrish, Frank A.

2013-01-01

Three trophic mass-balance models representing coral reef ecosystems along a fishery gradient were compared to evaluate ecosystem effects of fishing. The majority of the biomass estimates came directly from a large-scale visual survey program; therefore, data were collected in the same way for all three models, enhancing comparability. Model outputs–such as net system production, size structure of the community, total throughput, production, consumption, production-to-respiration ratio, and Finn’s cycling index and mean path length–indicate that the systems around the unpopulated French Frigate Shoals and along the relatively lightly populated Kona Coast of Hawai’i Island are mature, stable systems with a high efficiency in recycling of biomass. In contrast, model results show that the reef system around the most populated island in the State of Hawai’i, O’ahu, is in a transitional state with reduced ecosystem resilience and appears to be shifting to an algal-dominated system. Evaluation of the candidate indicators for fishing pressure showed that indicators at the community level (e.g., total biomass, community size structure, trophic level of the community) were most robust (i.e., showed the clearest trend) and that multiple indicators are necessary to identify fishing perturbations. These indicators could be used as performance indicators when compared to a baseline for management purposes. This study shows that ecosystem models can be valuable tools in identification of the system state in terms of complexity, stability, and resilience and, therefore, can complement biological metrics currently used by monitoring programs as indicators for coral reef status. Moreover, ecosystem models can improve our understanding of a system’s internal structure that can be used to support management in identification of approaches to reverse unfavorable states. PMID:23737951

Edutourism Taka Bonerate National Park through Scientific Approach to Improve Student Learning Outcomes

NASA Astrophysics Data System (ADS)

Hayati, R. S.

2017-02-01

This research aim is develop the potential of Taka Bonerate National Park as learning resources through edutourism with scientific approach to improve student learning outcomes. Focus of student learning outcomes are students psychomotor abilities and comprehension on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. The edutourism development products are teacher manual, edutourism worksheet, material booklet, guide’s manual, and Taka Bonerate National Park governor manual. The method to develop edutourism products is ADDIE research and development model that consist of analysis, design, development and production, implementation, and evaluation step. The subjects in the implementation step were given a pretest and posttest and observation sheet to see the effect of edutourism Taka Bonerate National Park through scientific approach to student learning outcomes on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. The data were analyzed qualitative descriptively. The research result is edutourism Taka Bonerate National Park through scientific approach can improve students learning outcomes on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics. Edutourism Taka Bonerate National Park can be an alternative of learning method on Biodiversity of Marine Biota, Corals Ecosystem, and Conservation topics.

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

NASA Astrophysics Data System (ADS)

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

2012-12-01

The phenology of arctic ecosystems is driven primarily by abiotic forces, with temperature acting as the main determinant of growing season onset and leaf budburst and in the spring. However, while the plant species in arctic ecosystems require differing amounts of accumulated heat for leaf-out, dynamic vegetation models simulated over a regional to global scale typically assume some average leaf-out for all of the species within an ecosystem. Here, we make use of air temperature records and observational data of spring leaf phenology collected across dominant groupings of species (dwarf birch shrubs, willow shrubs, other deciduous shrubs, grasses, sedges, and forbs) in arctic and ecotonal boreal ecosystems in Alaska. We then parameterize a dynamic vegetation model based on these data for four types of tundra ecosystems (heath tundra, shrub tundra, wet sedge tundra, and tussock tundra), as well as ecotonal boreal white spruce forest. This implementation improves the timing of the onset of carbon uptake in the spring, permitting a more accurate assessment of the contribution of each grouping of species to ecosystem performance. Furthermore, this implementation provides a more nuanced perspective on light competition among species and across ecosystems. For example, in the shrub tundra, the sedges and grasses leaf-out before the shade-inducing willow and dwarf birch, thereby providing the sedges and grasses time to accumulate biomass before shading effects arise. Also in the shrub tundra, the forbs leaf-out last, and are therefore, more prone to shading impacts by the taller willow and dwarf birch shrubs. However, in the wet sedge and heath tundra ecosystems, the forbs leaf-out before the shrubs, and are therefore less prone to shading impacts early in the growing season. These findings indicate the importance of leaf phenology data collection by species and across the various ecosystem types within the highly heterogeneous Arctic landscape. These findings also demonstrate that high-latitude dynamic vegetation models should consider variation in leaf-out by groupings of species within and across ecosystems in order to provide more accurate projections of future plant distributions in Arctic regions.

Using CarbonTracker carbon flux estimates to improve a terrestrial carbon cycle model

NASA Astrophysics Data System (ADS)

Peters, W.; Krol, M.; Miller, J. B.; Tans, P. P.; Carvalhais, N.; Schaefer, K.

2009-12-01

Estimates of net ecosystem exchange (NEE) from NOAA’s CarbonTracker CO2 data assimilation system show patterns of annual net uptake not represented in most terrestrial carbon cycle models. This is mainly because such models lack information on the land-use history of individual ecosystems, which is the main driver of long-term mean carbon exchange. Instead, they assume the biosphere to be in steady-state, with annual gross photosynthesis equalling ecosystem respiration everywhere. This limits their use in interpreting observations of carbon dynamics such as with eddy-covariance techniques or through atmospheric CO2 records. We have implemented a method that takes the long-term mean NEE estimates from CarbonTracker to derive the size of the dominant carbon pool in each ecosystem of the SIBCASA biosphere model. With the new pool sizes, the SIBCASA model is no longer in steady-state and reproduces annual carbon uptake patterns from CarbonTracker. We will show that the non steady-state SIBCASA model is not only much more consistent with the atmospheric CO2 record, but also with independent data on standing wood biomass and forest age from the Forest Inventory and Analysis (FIA) Program of the U.S. Forest Service. Four years of CarbonTracker NEE are needed to reliably derive a long term mean for this process, and we use three other years from CarbonTracker to evaluate the non steady state SIBCASA NEE. We will furthermore show that the non steady-state SIBCASA NEE is a much better first-guess for the CarbonTracker data assimilation process, allowing more confidence in its final NEE estimate, and reducing a systematic bias in CarbonTracker modeled atmospheric CO2. This overcomes a long standing issue in inverse modeling, and opens the way for further assessment and improvement of carbon cycle models such as SIBCASA.

A data-model integration approach toward improved understanding on wetland functions and hydrological benefits at the catchment scale

NASA Astrophysics Data System (ADS)

Yeo, I. Y.; Lang, M.; Lee, S.; Huang, C.; Jin, H.; McCarty, G.; Sadeghi, A.

2017-12-01

The wetland ecosystem plays crucial roles in improving hydrological function and ecological integrity for the downstream water and the surrounding landscape. However, changing behaviours and functioning of wetland ecosystems are poorly understood and extremely difficult to characterize. Improved understanding on hydrological behaviours of wetlands, considering their interaction with surrounding landscapes and impacts on downstream waters, is an essential first step toward closing the knowledge gap. We present an integrated wetland-catchment modelling study that capitalizes on recently developed inundation maps and other geospatial data. The aim of the data-model integration is to improve spatial prediction of wetland inundation and evaluate cumulative hydrological benefits at the catchment scale. In this paper, we highlight problems arising from data preparation, parameterization, and process representation in simulating wetlands within a distributed catchment model, and report the recent progress on mapping of wetland dynamics (i.e., inundation) using multiple remotely sensed data. We demonstrate the value of spatially explicit inundation information to develop site-specific wetland parameters and to evaluate model prediction at multi-spatial and temporal scales. This spatial data-model integrated framework is tested using Soil and Water Assessment Tool (SWAT) with improved wetland extension, and applied for an agricultural watershed in the Mid-Atlantic Coastal Plain, USA. This study illustrates necessity of spatially distributed information and a data integrated modelling approach to predict inundation of wetlands and hydrologic function at the local landscape scale, where monitoring and conservation decision making take place.

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration.

PubMed

Stegen, James C

2018-01-01

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modeling frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. We can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.

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.

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.

Throughfall Displacement Experiment (TDE) Ecosystem Model Intercomparison Project Data Archive

DOE Data Explorer

Hanson, Paul J. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Amthor, Jeffrey S. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Baldocchi, Dennis D. [University of California, Berkeley; Grant, Robert F. [University of Alberta, Canada; Hartley, Anne E. [Ohio State University; Hui, Dafeng [University of Oklahoma; Hunt, Jr., E. Raymond [Agricultural Research Service, U.S. Department of Agriculture; Johnson, Dale W. [University of Nevada, Reno; Kimball, John S. [University of Montana; King, Anthony W. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA); Luo, Yiqi [University of Oklahoma; McNulty, Steven G. [Southern Global Change Program, U.S. Forest Service, U.S. Department of Agriculture; Sun, Ge [North Carolina State University, Raleigh, NC (USA); Thornton, Peter E. [University of Montana; Wang, Shusen [Geomatics Canada - Canada Centre for Remote Sensing Natural Resources, Canada; Williams, Matthew [University of Edinburgh, United Kingdom; Wilson, Kell B. [National Oceanic and Atmospheric Administration, U.S. Department of Commerce; Wullschleger, Stanley D. [Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (USA)

2002-08-01

This archive provides and documents data from a project whose purpose is to compare the output of various ecosystem models when they are run with the data from the Throughfall Displacement Experiment (TDE) at Walker Branch Watershed, Oak Ridge, Tennessee. The project is not designed to determine which models are "best" for diagnosis (i.e., explaining the current functioning of the system) or prognosis (i.e., predicting the response of the system to future conditions), but, rather, to clarify similarities and differences among the models and their components, so that all models can be improved. Data archive: ftp://cdiac.ornl.gov/ftp/tdemodel/. TDE data archive web site: http://cdiac.ess-dive.lbl.gov/epubs/ndp/ndp078a/ndp078a.html.

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

Ehleringer, James; Randerson, James; Lai, Chun-Ta

The objective of the proposed research was to collect data and develop models to improve our understanding of the role of drought and fire impacts on the terrestrial carbon cycle in the western US, including impacts associated with urban systems as they impacted regional carbon cycles. Using data we collected and a synthesis of other measurements, we developed new ways (a) to evaluate the representation of drought stress and fire emissions in the Community Land Model, (b) to model net ecosystem exchange combining ground level atmospheric observations with boundary layer theory, (c) to model upstream impacts of fire and fossilmore » fuel emissions on atmospheric carbon dioxide observations, and (d) to model carbon dioxide observations within urban systems and at the urban-wildland interfaces of forest ecosystems.« less

Controls on seasonal patterns of maximum ecosystem carbon uptake and canopy-scale photosynthetic light response: contributions from both temperature and photoperiod.

PubMed

Stoy, Paul C; Trowbridge, Amy M; Bauerle, William L

2014-02-01

Most models of photosynthetic activity assume that temperature is the dominant control over physiological processes. Recent studies have found, however, that photoperiod is a better descriptor than temperature of the seasonal variability of photosynthetic physiology at the leaf scale. Incorporating photoperiodic control into global models consequently improves their representation of the seasonality and magnitude of atmospheric CO2 concentration. The role of photoperiod versus that of temperature in controlling the seasonal variability of photosynthetic function at the canopy scale remains unexplored. We quantified the seasonal variability of ecosystem-level light response curves using nearly 400 site years of eddy covariance data from over eighty Free Fair-Use sites in the FLUXNET database. Model parameters describing maximum canopy CO2 uptake and the initial slope of the light response curve peaked after peak temperature in about 2/3 of site years examined, emphasizing the important role of temperature in controlling seasonal photosynthetic function. Akaike's Information Criterion analyses indicated that photoperiod should be included in models of seasonal parameter variability in over 90% of the site years investigated here, demonstrating that photoperiod also plays an important role in controlling seasonal photosynthetic function. We also performed a Granger causality analysis on both gross ecosystem productivity (GEP) and GEP normalized by photosynthetic photon flux density (GEP n ). While photoperiod Granger-caused GEP and GEP n in 99 and 92% of all site years, respectively, air temperature Granger-caused GEP in a mere 32% of site years but Granger-caused GEP n in 81% of all site years. Results demonstrate that incorporating photoperiod may be a logical step toward improving models of ecosystem carbon uptake, but not at the expense of including enzyme kinetic-based temperature constraints on canopy-scale photosynthesis.

Incorporating an enzymatic model of effects of temperature, moisture, and substrate supply on soil respiration into an ecosystem model for two forests of northeastern USA

NASA Astrophysics Data System (ADS)

Sihi, Debjani; Davidson, Eric; Chen, Min; Savage, Kathleen; Richardson, Andrew; Keenan, Trevor; Hollinger, David

2017-04-01

Soils represent the largest terrestrial carbon (C) pool, and microbial decomposition of soil organic matter (SOM) to carbon dioxide, also called heterotrophic respiration (Rh), is an important component of the global C cycle. Temperature sensitivity of Rh is often represented with a simple Q10 function in ecosystem models and earth system models (ESMs), sometimes accompanied by an empirical soil moisture modifier. More explicit representation of the effects of soil moisture, substrate supply, and their interactions with temperature has been proposed to disentangle the confounding factors of apparent temperature sensitivity of SOM decomposition and improve performance of ecosystem models and ESMs. The objective of this work was to incorporate into an ecosystem model a more mechanistic, but still parsimonious, model of environmental factors controlling Rh. The Dual Arrhenius and Michaelis-Menten (DAMM) model simulates Rh using Michaelis-Menten, Arrhenius, and diffusion functions. Soil moisture affects Rh and its apparent temperature sensitivity in DAMM by regulating the diffusion of oxygen and soluble carbon substrates to the enzymatic reaction site. However, in its current configuration, DAMM depends on assumptions or inputs from other models regarding soil C inputs. Here we merged the DAMM soil flux model with a parsimonious ecosystem flux model, FöBAAR (Forest Biomass, Assimilation, Allocation and Respiration) by replacing FöBAAR's algorithms for Rh with those of DAMM. Classical root trenching experiments provided data to partition soil CO2 efflux into Rh (trenched plot) and root respiration (untrenched minus trenched plots). We used three years of high-frequency soil flux data from automated soil chambers (trenched and untrenched plots) and landscape-scale ecosystem fluxes from eddy covariance towers from two mid-latitude forests (Harvard Forest, MA and Howland Forest, ME) of northeastern USA to develop and validate the merged model and to quantify the uncertainties in a multiple constraints approach. The optimized DAMM-FöBAAR model better captured the seasonal dynamics of Rh compared to the FöBAAR-only model for the Harvard Forest, as indicated by lower cost functions (model-data mismatch). However, DAMM-FöBAAR showed less improvement over FöBAAR-only for the boreal transition forest at Howland. The frequency of droughts is lower at Howland, due to a shallow water table, resulting in only brief water limitation affecting Rh in some years. At both sites, the declining trend of soil respiration during drought episodes was captured by the DAMM-FöBAAR model, but not the FöBAAR-only model, which simulates Rh using only a Q10 type function. Greater confidence in model prediction resulting from the inclusion of mechanistic simulation of moisture limitation on substrate availability, an emergent property of DAMM, depends on site conditions, climate, and the temporal scale of interest. While the DAMM functions require a few more parameters than a simple Q10 function, we have demonstrated that they can be included in an ecosystem model and reduce the cost function. Moreover, the mechanistic structure of the soil moisture effects using DAMM functions should be more generalizable than other commonly used empirical functions.

Going with the flow: the role of ocean circulation in global marine ecosystems under a changing climate.

PubMed

van Gennip, Simon J; Popova, Ekaterina E; Yool, Andrew; Pecl, Gretta T; Hobday, Alistair J; Sorte, Cascade J B

2017-07-01

Ocean warming, acidification, deoxygenation and reduced productivity are widely considered to be the major stressors to ocean ecosystems induced by emissions of CO 2 . However, an overlooked stressor is the change in ocean circulation in response to climate change. Strong changes in the intensity and position of the western boundary currents have already been observed, and the consequences of such changes for ecosystems are beginning to emerge. In this study, we address climatically induced changes in ocean circulation on a global scale but relevant to propagule dispersal for species inhabiting global shelf ecosystems, using a high-resolution global ocean model run under the IPCC RCP 8.5 scenario. The ¼ degree model resolution allows improved regional realism of the ocean circulation beyond that of available CMIP5-class models. We use a Lagrangian approach forced by modelled ocean circulation to simulate the circulation pathways that disperse planktonic life stages. Based on trajectory backtracking, we identify present-day coastal retention, dominant flow and dispersal range for coastal regions at the global scale. Projecting into the future, we identify areas of the strongest projected circulation change and present regional examples with the most significant modifications in their dominant pathways. Climatically induced changes in ocean circulation should be considered as an additional stressor of marine ecosystems in a similar way to ocean warming or acidification. © 2017 John Wiley & Sons Ltd.

Development Biology Worksheet Oriented Accelerated Learning on Plantae and Ecosystems for 10th-Grade Senior High School Students

NASA Astrophysics Data System (ADS)

Dipuja, D. A.; Lufri, L.; Ahda, Y.

2018-04-01

The problem that found are learning outcomes student is low on the plantae and ecosystems. Students less motivated and passive learning because learning is teacher center and teaching materials not facilitate student. Therefore, it is necessary to design a worksheet oriented accelerated learning. Accelerated learning approach that can improve motivation and learning activities. The purpose of the research was to produce worksheet oriented accelerated learning on plantae and ecosystems. This research is designed as a research and development by using Plomp model, consists of the preliminary, prototyping, and assessment phase. Data was collected through questionnaires, observation sheet, test, and documentation. The results of the research was worksheet oriented accelerated learning on plantae and ecosystems is very valid.

Pan-Arctic modelling of net ecosystem exchange of CO2

PubMed Central

Shaver, G. R.; Rastetter, E. B.; Salmon, V.; Street, L. E.; van de Weg, M. J.; Rocha, A.; van Wijk, M. T.; Williams, M.

2013-01-01

Net ecosystem exchange (NEE) of C varies greatly among Arctic ecosystems. Here, we show that approximately 75 per cent of this variation can be accounted for in a single regression model that predicts NEE as a function of leaf area index (LAI), air temperature and photosynthetically active radiation (PAR). The model was developed in concert with a survey of the light response of NEE in Arctic and subarctic tundras in Alaska, Greenland, Svalbard and Sweden. Model parametrizations based on data collected in one part of the Arctic can be used to predict NEE in other parts of the Arctic with accuracy similar to that of predictions based on data collected in the same site where NEE is predicted. The principal requirement for the dataset is that it should contain a sufficiently wide range of measurements of NEE at both high and low values of LAI, air temperature and PAR, to properly constrain the estimates of model parameters. Canopy N content can also be substituted for leaf area in predicting NEE, with equal or greater accuracy, but substitution of soil temperature for air temperature does not improve predictions. Overall, the results suggest a remarkable convergence in regulation of NEE in diverse ecosystem types throughout the Arctic. PMID:23836790

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

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

Lu, Dan; Ricciuto, Daniel; Walker, Anthony

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

Bayesian calibration of terrestrial ecosystem models: A study of advanced Markov chain Monte Carlo methods

DOE PAGES

Lu, Dan; Ricciuto, Daniel; Walker, Anthony; ...

2017-02-22

Calibration of terrestrial ecosystem models is important but challenging. Bayesian inference implemented by Markov chain Monte Carlo (MCMC) sampling provides a comprehensive framework to estimate model parameters and associated uncertainties using their posterior distributions. The effectiveness and efficiency of the method strongly depend on the MCMC algorithm used. In this study, a Differential Evolution Adaptive Metropolis (DREAM) algorithm was used to estimate posterior distributions of 21 parameters for the data assimilation linked ecosystem carbon (DALEC) model using 14 years of daily net ecosystem exchange data collected at the Harvard Forest Environmental Measurement Site eddy-flux tower. The DREAM is a multi-chainmore » method and uses differential evolution technique for chain movement, allowing it to be efficiently applied to high-dimensional problems, and can reliably estimate heavy-tailed and multimodal distributions that are difficult for single-chain schemes using a Gaussian proposal distribution. The results were evaluated against the popular Adaptive Metropolis (AM) scheme. DREAM indicated that two parameters controlling autumn phenology have multiple modes in their posterior distributions while AM only identified one mode. The calibration of DREAM resulted in a better model fit and predictive performance compared to the AM. DREAM provides means for a good exploration of the posterior distributions of model parameters. Lastly, it reduces the risk of false convergence to a local optimum and potentially improves the predictive performance of the calibrated model.« less

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

USGS Publications Warehouse

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

2009-01-01

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

IMPROVED VALUATION OF ECOLOGICAL BENEFITS ASSOCIATED WITH AQUATIC LIVING RESOURCES: DEVELOPMENT AND TESTING OF INDICATOR-BASED STATED PREFERENCE VALUATION AND TRANSFER

EPA Science Inventory

In addition to development and systematic qualitative/quantitative testing of indicator-based valuation for aquatic living resources, the proposed work will improve interdisciplinary mechanisms to model and communicate aquatic ecosystem change within SP valuation—an area...

When What You See Isn’t What You Get: How Viewshed Analysis is Impacted by Digital Surface Model (DSM) Resolution

EPA Science Inventory

A key factor for improving models of ecosystem benefits is the availability of high quality spatial data. High resolution LIDAR data are now commonly available and can be used to produce more accurate model outputs. However, increased resolution leads to higher computer resource...

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.

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

NASA Astrophysics Data System (ADS)

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

2015-11-01

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

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.

Redefinition and global estimation of basal ecosystem respiration rate

NASA Astrophysics Data System (ADS)

Yuan, Wenping; Luo, Yiqi; Li, Xianglan; Liu, Shuguang; Yu, Guirui; Zhou, Tao; Bahn, Michael; Black, Andy; Desai, Ankur R.; Cescatti, Alessandro; Marcolla, Barbara; Jacobs, Cor; Chen, Jiquan; Aurela, Mika; Bernhofer, Christian; Gielen, Bert; Bohrer, Gil; Cook, David R.; Dragoni, Danilo; Dunn, Allison L.; Gianelle, Damiano; Grünwald, Thomas; Ibrom, Andreas; Leclerc, Monique Y.; Lindroth, Anders; Liu, Heping; Marchesini, Luca Belelli; Montagnani, Leonardo; Pita, Gabriel; Rodeghiero, Mirco; Rodrigues, Abel; Starr, Gregory; Stoy, Paul C.

2011-12-01

Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from ˜3°S to ˜70°N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr -1, with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.

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

NASA Astrophysics Data System (ADS)

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

2013-11-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-04-01

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

Redefinition and global estimation of basal ecosystem respiration rate

USGS Publications Warehouse

Yuan, W.; Luo, Y.; Li, X.; Liu, S.; Yu, G.; Zhou, T.; Bahn, M.; Black, A.; Desai, A.R.; Cescatti, A.; Marcolla, B.; Jacobs, C.; Chen, J.; Aurela, M.; Bernhofer, C.; Gielen, B.; Bohrer, G.; Cook, D.R.; Dragoni, D.; Dunn, A.L.; Gianelle, D.; Grnwald, T.; Ibrom, A.; Leclerc, M.Y.; Lindroth, A.; Liu, H.; Marchesini, L.B.; Montagnani, L.; Pita, G.; Rodeghiero, M.; Rodrigues, A.; Starr, G.; Stoy, Paul C.

2011-01-01

Basal ecosystem respiration rate (BR), the ecosystem respiration rate at a given temperature, is a common and important parameter in empirical models for quantifying ecosystem respiration (ER) globally. Numerous studies have indicated that BR varies in space. However, many empirical ER models still use a global constant BR largely due to the lack of a functional description for BR. In this study, we redefined BR to be ecosystem respiration rate at the mean annual temperature. To test the validity of this concept, we conducted a synthesis analysis using 276 site-years of eddy covariance data, from 79 research sites located at latitudes ranging from ∼3°S to ∼70°N. Results showed that mean annual ER rate closely matches ER rate at mean annual temperature. Incorporation of site-specific BR into global ER model substantially improved simulated ER compared to an invariant BR at all sites. These results confirm that ER at the mean annual temperature can be considered as BR in empirical models. A strong correlation was found between the mean annual ER and mean annual gross primary production (GPP). Consequently, GPP, which is typically more accurately modeled, can be used to estimate BR. A light use efficiency GPP model (i.e., EC-LUE) was applied to estimate global GPP, BR and ER with input data from MERRA (Modern Era Retrospective-Analysis for Research and Applications) and MODIS (Moderate resolution Imaging Spectroradiometer). The global ER was 103 Pg C yr −1, with the highest respiration rate over tropical forests and the lowest value in dry and high-latitude areas.

Trade-Off and Synergy among Ecosystem Services in the Guanzhong-Tianshui Economic Region of China.

PubMed

Qin, Keyu; Li, Jing; Yang, Xiaonan

2015-11-03

Natural ecosystems provide society with important goods and services. With rapidly increasing populations and excessive utilization of natural resources, humans have been enhancing the production of some services at the expense of others. Although the need for certain trade-offs between conservation and development is urgent, having only a small number of efficient methods to assess such trade-offs has impeded progress. This study focuses on the evaluation of ecosystem services under different land use schemes. It reveals the spatial and temporal distributions of and changes in ecosystem services. Based on a correlation rate model and distribution mapping, the trade-offs and synergies of these ecosystem services can be found. Here, we also describe a new simple approach to quantify the relationships of every trade-off and synergy. The results show that all ecosystem services possess trade-offs and synergies in the study area. The trend of improving carbon sequestration and water interception indicate that these key ecosystem services have the strongest synergy. And the decrease in regional agricultural production and other services, except water yield, may be considered as trade-offs. The synergy between water yield and agricultural production was the most significant, while the trade-off between water interception and carbon sequestration was the most apparent, according to our interaction quantification model. The results of this study have implications for planning and monitoring the future management of natural capital and ecosystem services, and can be integrated into land use decision-making.

Trade-Off and Synergy among Ecosystem Services in the Guanzhong-Tianshui Economic Region of China

PubMed Central

Qin, Keyu; Li, Jing; Yang, Xiaonan

2015-01-01

Natural ecosystems provide society with important goods and services. With rapidly increasing populations and excessive utilization of natural resources, humans have been enhancing the production of some services at the expense of others. Although the need for certain trade-offs between conservation and development is urgent, having only a small number of efficient methods to assess such trade-offs has impeded progress. This study focuses on the evaluation of ecosystem services under different land use schemes. It reveals the spatial and temporal distributions of and changes in ecosystem services. Based on a correlation rate model and distribution mapping, the trade-offs and synergies of these ecosystem services can be found. Here, we also describe a new simple approach to quantify the relationships of every trade-off and synergy. The results show that all ecosystem services possess trade-offs and synergies in the study area. The trend of improving carbon sequestration and water interception indicate that these key ecosystem services have the strongest synergy. And the decrease in regional agricultural production and other services, except water yield, may be considered as trade-offs. The synergy between water yield and agricultural production was the most significant, while the trade-off between water interception and carbon sequestration was the most apparent, according to our interaction quantification model. The results of this study have implications for planning and monitoring the future management of natural capital and ecosystem services, and can be integrated into land use decision-making. PMID:26540068

Mechanistic insights on the responses of plant and ecosystem gas exchange to global environmental change: lessons from Biosphere 2.

PubMed

Gonzalez-Meler, Miquel A; Rucks, Jessica S; Aubanell, Gerard

2014-09-01

Scaling up leaf processes to canopy/ecosystem level fluxes is critical for examining feedbacks between vegetation and climate. Collectively, studies from Biosphere 2 Laboratory have provided important insight of leaf-to-ecosystem investigations of multiple environmental parameters that were not before possible in enclosed or field studies. B2L has been a testing lab for the applicability of new technologies such as spectral approaches to detect spatial and temporal changes in photosynthesis within canopies, or for the development of cavity ring-down isotope applications for ecosystem evapotranspiration. Short and long term changes in atmospheric CO2, drought or temperature allowed for intensive investigation of the interactions between photosynthesis and leaf, soil and ecosystem respiration. Experiments conducted in the rainforest biome have provided some of the most comprehensive dataset to date on the effects of climate change variables on tropical ecosystems. Results from these studies have been later corroborated in natural rainforest ecosystems and have improved the predictive capabilities of models that now show increased resilience of tropics to climate change. Studies of temperature and CO2 effects on ecosystem respiration and its leaf and soil components have helped reconsider the use of simple first-order kinetics for characterizing respiration in models. The B2L also provided opportunities to quantify the rhizosphere priming effect, or establish the relationships between net primary productivity, atmospheric CO2 and isoprene emissions. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Healthcare model with use of information and communication technology for patients with chronic disease.

PubMed

Lisiecka-Biełanowicz, Mira; Wawrzyniak, Zbigniew

2016-07-15

The healthcare system is positioned in the patient's environment and works with other determinants of the treatment. Patient care requires a whole system compatible to the needs of organizational and technical solutions. The purpose of this study is to present a new model of patient-oriented care, in which the use of information and communication technology (ICT) can improve the effectiveness of healthcare for patients with chronic diseases. The study material is the process of healthcare for chronically ill patients. Knowledge of the circumstances surrounding ecosystem and of the patients' needs, taking into account the fundamental healthcare goals allows us to build a new models of care, starting with the economic assumptions. The method used is modeling the construction of efficient healthcare system with the patient-centered model using ICT tools. We present a new systemic concept of building patient's environment in which he is the central figure of the healthcare organization - so called patient centered system. The use of ICT in the model of chronic patient's healthcare can improve the effectiveness of this kind of care. The concept is a vision to making wide platform of information management in chronic disease in a real environment ecosystem of patient using ICT tools. On the basis of a systematic approach to the model of chronic disease, and the knowledge of the patient itself, a model of the ecosystem impacts and interactions through information feedback and the provision of services can be constructed. ICT assisted techniques will increase the effectiveness of patient care, in which nowadays information exchange plays a key role.

Soil Carbon Residence Time in the Arctic - Potential Drivers of Past and Future Change

NASA Astrophysics Data System (ADS)

Huntzinger, D. N.; Fisher, J.; Schwalm, C. R.; Hayes, D. J.; Stofferahn, E.; Hantson, W.; Schaefer, K. M.; Fang, Y.; Michalak, A. M.; Wei, Y.

2017-12-01

Carbon residence time is one of the most important factors controlling carbon cycling in ecosystems. Residence time depends on carbon allocation and conversion among various carbon pools and the rate of organic matter decomposition; all of which rely on environmental conditions, primarily temperature and soil moisture. As a result, residence time is an emergent property of models and a strong determinant of terrestrial carbon storage capacity. However, residence time is poorly constrained in process-based models due, in part, to the lack of data with which to benchmark global-scale models in order to guide model improvements and, ultimately, reduce uncertainty in model projections. Here we focus on improving the understanding of the drivers to observed and simulated carbon residence time in the Arctic-Boreal region (ABR). Carbon-cycling in the ABR represents one of the largest sources of uncertainty in historical and future projections of land-atmosphere carbon dynamics. This uncertainty is depicted in the large spread of terrestrial biospheric model (TBM) estimates of carbon flux and ecosystem carbon pool size in this region. Recent efforts, such as the Arctic-Boreal Vulnerability Experiment (ABoVE), have increased the availability of spatially explicit in-situ and remotely sensed carbon and ecosystem focused data products in the ABR. Together with simulations from Multi-scale Synthesis and Terrestrial Model Intercomparison Project (MsTMIP), we use these observations to evaluate the ability of models to capture soil carbon stocks and changes in the ABR. Specifically, we compare simulated versus observed soil carbon residence times in order to evaluate the functional response and sensitivity of modeled soil carbon stocks to changes in key environmental drivers. Understanding how simulated carbon residence time compares with observations and what drives these differences is critical for improving projections of changing carbon dynamics in the ABR and globally.

Policy Analysis: Valuation of Ecosystem Services in the Southern Appalachian Mountains.

PubMed

Banzhaf, H Spencer; Burtraw, Dallas; Criscimagna, Susie Chung; Cosby, Bernard J; Evans, David A; Krupnick, Alan J; Siikamäki, Juha V

2016-03-15

This study estimates the economic value of an increase in ecosystem services attributable to the reduced acidification expected from more stringent air pollution policy. By integrating a detailed biogeochemical model that projects future ecological recovery with economic methods that measure preferences for specific ecological improvements, we estimate the economic value of ecological benefits from new air pollution policies in the Southern Appalachian ecosystem. Our results indicate that these policies generate aggregate benefits of about $3.7 billion, or about $16 per year per household in the region. The study provides currently missing information about the ecological benefits from air pollution policies that is needed to evaluate such policies comprehensively. More broadly, the study also illustrates how integrated biogeochemical and economic assessments of multidimensional ecosystems can evaluate the relative benefits of different policy options that vary by scale and across ecosystem attributes.

Adapting California’s ecosystems to a changing climate

USGS Publications Warehouse

Elizabeth Chornesky,; David Ackerly,; Paul Beier,; Frank Davis,; Flint, Lorraine E.; Lawler, Joshua J.; Moyle, Peter B.; Moritz, Max A.; Scoonover, Mary; Byrd, Kristin B.; Alvarez, Pelayo; Heller, Nicole E.; Micheli, Elisabeth; Weiss, Stuart

2017-01-01

Significant efforts are underway to translate improved understanding of how climate change is altering ecosystems into practical actions for sustaining ecosystem functions and benefits. We explore this transition in California, where adaptation and mitigation are advancing relatively rapidly, through four case studies that span large spatial domains and encompass diverse ecological systems, institutions, ownerships, and policies. The case studies demonstrate the context specificity of societal efforts to adapt ecosystems to climate change and involve applications of diverse scientific tools (e.g., scenario analyses, downscaled climate projections, ecological and connectivity models) tailored to specific planning and management situations (alternative energy siting, wetland management, rangeland management, open space planning). They illustrate how existing institutional and policy frameworks provide numerous opportunities to advance adaptation related to ecosystems and suggest that progress is likely to be greatest when scientific knowledge is integrated into collective planning and when supportive policies and financing enable action.

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.

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

PubMed

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

2015-11-15

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

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

PubMed Central

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

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

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Intensive land use in the Swedish mountains between AD 800 and 1200 led to deforestation and ecosystem transformation with long-lasting effects.

PubMed

Östlund, Lars; Hörnberg, Greger; DeLuca, Thomas H; Liedgren, Lars; Wikström, Peder; Zackrisson, Olle; Josefsson, Torbjörn

2015-10-01

Anthropogenic deforestation has shaped ecosystems worldwide. In subarctic ecosystems, primarily inhabited by native peoples, deforestation is generally considered to be mainly associated with the industrial period. Here we examined mechanisms underlying deforestation a thousand years ago in a high-mountain valley with settlement artifacts located in subarctic Scandinavia. Using the Heureka Forestry Decision Support System, we modeled pre-settlement conditions and effects of tree cutting on forest cover. To examine lack of regeneration and present nutrient status, we analyzed soil nitrogen. We found that tree cutting could have deforested the valley within some hundred years. Overexploitation left the soil depleted beyond the capacity of re-establishment of trees. We suggest that pre-historical deforestation has occurred also in subarctic ecosystems and that ecosystem boundaries were especially vulnerable to this process. This study improves our understanding of mechanisms behind human-induced ecosystem transformations and tree-line changes, and of the concept of wilderness in the Scandinavian mountain range.

Collected Data of The Boreal Ecosystem and Atmosphere Study (BOREAS)

NASA Technical Reports Server (NTRS)

Newcomer, J. (Editor); Landis, D. (Editor); Conrad, S. (Editor); Curd, S. (Editor); Huemmrich, K. (Editor); Knapp, D. (Editor); Morrell, A. (Editor); Nickerson, J. (Editor); Papagno, A. (Editor); Rinker, D. (Editor)

2000-01-01

The Boreal Ecosystem-Atmosphere Study (BOREAS) was a large-scale international interdisciplinary climate-ecosystem interaction experiment in the northern boreal forests of Canada. Its goal was to improve our understanding of the boreal forests -- how they interact with the atmosphere, how much CO2 they can store, and how climate change will affect them. BOREAS wanted to learn to use satellite data to monitor the forests, and to improve computer simulation and weather models so scientists can anticipate the effects of global change. This BOREAS CD-ROM set is a set of 12 CD-ROMs containing the finalized point data sets and compressed image data from the BOREAS Project. All point data are stored in ASCII text files, and all image and GIS products are stored as binary images, compressed using GZip. Additional descriptions of the various data sets on this CD-ROM are available in other documents in the BOREAS series.

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

NASA Technical Reports Server (NTRS)

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

1992-01-01

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

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

PubMed

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

2015-03-01

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

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

PubMed

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

2015-03-01

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

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

DOE PAGES

Zhu, Qing; Zhuang, Qianlai

2015-12-21

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

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

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

Zhu, Qing; Zhuang, Qianlai

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

Spring leaf phenology and the diurnal temperature range in a temperate maple forest.

PubMed

Hanes, Jonathan M

2014-03-01

Spring leaf phenology in temperate climates is intricately related to numerous aspects of the lower atmosphere [e.g., surface energy balance, carbon flux, humidity, the diurnal temperature range (DTR)]. To further develop and improve the accuracy of ecosystem and climate models, additional investigations of the specific nature of the relationships between spring leaf phenology and various ecosystem and climate processes are required in different environments. This study used visual observations of maple leaf phenology, below-canopy light intensities, and micrometeorological data collected during the spring seasons of 2008, 2009, and 2010 to examine the potential influence of leaf phenology on a seasonal transition in the trend of the DTR. The timing of a reversal in the DTR trend occurred near the time when the leaves were unfolding and expanding. The results suggest that the spring decline in the DTR can be attributed primarily to the effect of canopy closure on daily maximum temperature. These findings improve our understanding of the relationship between leaf phenology and the diurnal temperature range in temperate maple forests during the spring. They also demonstrate the necessity of incorporating accurate phenological data into ecosystem and climate models and warrant a careful examination of the extent to which canopy phenology is currently incorporated into existing models.

Modelling the influence of ectomycorrhizal decomposition on plant nutrition and soil carbon sequestration in boreal forest ecosystems.

PubMed

Baskaran, Preetisri; Hyvönen, Riitta; Berglund, S Linnea; Clemmensen, Karina E; Ågren, Göran I; Lindahl, Björn D; Manzoni, Stefano

2017-02-01

Tree growth in boreal forests is limited by nitrogen (N) availability. Most boreal forest trees form symbiotic associations with ectomycorrhizal (ECM) fungi, which improve the uptake of inorganic N and also have the capacity to decompose soil organic matter (SOM) and to mobilize organic N ('ECM decomposition'). To study the effects of 'ECM decomposition' on ecosystem carbon (C) and N balances, we performed a sensitivity analysis on a model of C and N flows between plants, SOM, saprotrophs, ECM fungi, and inorganic N stores. The analysis indicates that C and N balances were sensitive to model parameters regulating ECM biomass and decomposition. Under low N availability, the optimal C allocation to ECM fungi, above which the symbiosis switches from mutualism to parasitism, increases with increasing relative involvement of ECM fungi in SOM decomposition. Under low N conditions, increased ECM organic N mining promotes tree growth but decreases soil C storage, leading to a negative correlation between C stores above- and below-ground. The interplay between plant production and soil C storage is sensitive to the partitioning of decomposition between ECM fungi and saprotrophs. Better understanding of interactions between functional guilds of soil fungi may significantly improve predictions of ecosystem responses to environmental change. © 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Baseline and projected future carbon storage and carbon fluxes in ecosystems of Hawai‘i

USGS Publications Warehouse

Selmants, Paul C.; Giardina, Christian P.; Jacobi, James D.; Zhu, Zhiliang

2017-05-04

This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act of 2007 and to improve understanding of factors influencing carbon balance in ecosystems of Hawai‘i. Ecosystem carbon storage, carbon fluxes, and carbon balance were examined for major terrestrial ecosystems on the seven main Hawaiian islands in two time periods: baseline (from 2007 through 2012) and future (projections from 2012 through 2061). The assessment incorporated observed data, remote sensing, statistical methods, and simulation models. The national assessment has been completed for the conterminous United States, using methodology described in SIR 2010-5233, with results provided in three regional reports (PP 1804, PP 1797, and PP 1897), and for Alaska, with results provided in PP 1826.

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.

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.

Facing uncertainty in ecosystem services-based resource management.

PubMed

Grêt-Regamey, Adrienne; Brunner, Sibyl H; Altwegg, Jürg; Bebi, Peter

2013-09-01

The concept of ecosystem services is increasingly used as a support for natural resource management decisions. While the science for assessing ecosystem services is improving, appropriate methods to address uncertainties in a quantitative manner are missing. Ignoring parameter uncertainties, modeling uncertainties and uncertainties related to human-environment interactions can modify decisions and lead to overlooking important management possibilities. In this contribution, we present a new approach for mapping the uncertainties in the assessment of multiple ecosystem services. The spatially explicit risk approach links Bayesian networks to a Geographic Information System for forecasting the value of a bundle of ecosystem services and quantifies the uncertainties related to the outcomes in a spatially explicit manner. We demonstrate that mapping uncertainties in ecosystem services assessments provides key information for decision-makers seeking critical areas in the delivery of ecosystem services in a case study in the Swiss Alps. The results suggest that not only the total value of the bundle of ecosystem services is highly dependent on uncertainties, but the spatial pattern of the ecosystem services values changes substantially when considering uncertainties. This is particularly important for the long-term management of mountain forest ecosystems, which have long rotation stands and are highly sensitive to pressing climate and socio-economic changes. Copyright © 2012 Elsevier Ltd. All rights reserved.

Integrating modeling, monitoring, and management to reduce critical uncertainties in water resource decision making.

PubMed

Peterson, James T; Freeman, Mary C

2016-12-01

Stream ecosystems provide multiple, valued services to society, including water supply, waste assimilation, recreation, and habitat for diverse and productive biological communities. Managers striving to sustain these services in the face of changing climate, land uses, and water demands need tools to assess the potential effectiveness of alternative management actions, and often, the resulting tradeoffs between competing objectives. Integrating predictive modeling with monitoring data in an adaptive management framework provides a process by which managers can reduce model uncertainties and thus improve the scientific bases for subsequent decisions. We demonstrate an integration of monitoring data with a dynamic, metapopulation model developed to assess effects of streamflow alteration on fish occupancy in a southeastern US stream system. Although not extensive (collected over three years at nine sites), the monitoring data allowed us to assess and update support for alternative population dynamic models using model probabilities and Bayes rule. We then use the updated model weights to estimate the effects of water withdrawal on stream fish communities and demonstrate how feedback in the form of monitoring data can be used to improve water resource decision making. We conclude that investment in more strategic monitoring, guided by a priori model predictions under alternative hypotheses and an adaptive sampling design, could substantially improve the information available to guide decision-making and management for ecosystem services from lotic systems. Published by Elsevier Ltd.

Land use changes and socio-economic development strongly deteriorate river ecosystem health in one of the largest basins in China.

PubMed

Cheng, Xian; Chen, Liding; Sun, Ranhao; Kong, Peiru

2018-03-01

It is important to assess river ecosystem health in large-scale basins when considering the complex influence of anthropogenic activities on these ecosystems. This study investigated the river ecosystem health in the Haihe River Basin (HRB) by sampling 148 river sites during the pre- and post-rainy seasons in 2013. A model was established to assess the river ecosystem health based on water physicochemical, nutrient, and macroinvertebrate indices, and the health level was divided into "very poor," "poor," "fair," "good," and "excellent" according to the health score calculated from the assessment model. The assessment results demonstrated that the river ecosystem health of the HRB was "poor" overall, and no catchments were labeled "excellent." The percentages of catchments deemed to have "very poor," "poor," "fair," or "good" river ecosystem health were 12.88%, 40.91%, 40.15%, and 6.06%, respectively. From the pre- to the post-rainy season, the macroinvertebrate health levels improved from "poor" to "fair." The results of a redundancy analysis (RDA), path analysis of the structural equation model (SEM), and X-Y plots indicated that the land use types of forest land and grassland had positive relationships with river ecosystem health, whereas arable land, urban land, gross domestic product (GDP) per capita, and population density had negative relationships with river ecosystem health. The variance partitioning (VP) results showed that anthropogenic activities (including land use and socio-economy) together explained 30.9% of the variations in river ecosystem health in the pre-rainy season, and this value increased to 35.9% in the post-rainy season. Land use intensity was the first driver of river ecosystem health, and socio-economic activities was the second driver. Land use variables explained 20.5% and 25.7% of the variations in river ecosystem health in the pre- and post-rainy season samples, respectively, and socio-economic variables explained 12.3% and 17.2% of the variations, respectively. The SEM results revealed that urban land had the strongest impact on water quality health and that forest land had the strongest impact on macroinvertebrate health. This study has implications for the selection of appropriate indicators to assess river ecosystem health and generated data to examine the effects of anthropogenic activities on river ecosystem health in a fast-growing region. Copyright © 2017 Elsevier B.V. All rights reserved.

Measuring and Modeling the U.S. Regulatory Ecosystem

NASA Astrophysics Data System (ADS)

Bommarito, Michael J., II; Katz, Daniel Martin

2017-09-01

Over the last 23 years, the U.S. Securities and Exchange Commission has required over 34,000 companies to file over 165,000 annual reports. These reports, the so-called "Form 10-Ks," contain a characterization of a company's financial performance and its risks, including the regulatory environment in which a company operates. In this paper, we analyze over 4.5 million references to U.S. Federal Acts and Agencies contained within these reports to measure the regulatory ecosystem, in which companies are organisms inhabiting a regulatory environment. While individuals across the political, economic, and academic world frequently refer to trends in this regulatory ecosystem, far less attention has been paid to supporting such claims with large-scale, longitudinal data. In this paper, in addition to positing a model of regulatory ecosystems, we document an increase in the regulatory energy per filing, i.e., a warming "temperature." We also find that the diversity of the regulatory ecosystem has been increasing over the past two decades. These findings support the claim that regulatory activity and complexity are increasing, and this framework contributes an important step towards improving academic and policy discussions around legal complexity and regulation.

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

USDA-ARS?s Scientific Manuscript database

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2016-02-01

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

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

75 FR 64726 - Science Advisory Board Staff Office; Request for Nominations of Experts To Serve on the Clean Air...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-10-20

... the most recently revised ozone NAAQS and changes to atmospheric chemistry that have occurred over the... Organic Compounds (VOCs)--Advice on potential improvements to TO-15 with particular emphasis on improving..., atmospheric chemistry, ecosystem modeling, aquatic chemistry, environmental science and engineering, risk...

Identifying optimal remotely-sensed variables for ecosystem monitoring in Colorado Plateau drylands

USGS Publications Warehouse

Poitras, Travis; Villarreal, Miguel; Waller, Eric K.; Nauman, Travis; Miller, Mark E.; Duniway, Michael C.

2018-01-01

Water-limited ecosystems often recover slowly following anthropogenic or natural disturbance. Multitemporal remote sensing can be used to monitor ecosystem recovery after disturbance; however, dryland vegetation cover can be challenging to accurately measure due to sparse cover and spectral confusion between soils and non-photosynthetic vegetation. With the goal of optimizing a monitoring approach for identifying both abrupt and gradual vegetation changes, we evaluated the ability of Landsat-derived spectral variables to characterize surface variability of vegetation cover and bare ground across a range of vegetation community types. Using three year composites of Landsat data, we modeled relationships between spectral information and field data collected at monitoring sites near Canyonlands National Park, UT. We also developed multiple regression models to assess improvement over single variables. We found that for all vegetation types, percent cover bare ground could be accurately modeled with single indices that included a combination of red and shortwave infrared bands, while near infrared-based vegetation indices like NDVI worked best for quantifying tree cover and total live vegetation cover in woodlands. We applied four models to characterize the spatial distribution of putative grassland ecological states across our study area, illustrating how this approach can be implemented to guide dryland ecosystem management.

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

DOE PAGES

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard; ...

2018-01-02

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

Soil carbon stocks across tropical forests of Panama regulated by base cation effects on fine roots

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

Cusack, Daniela F.; Markesteijn, Lars; Condit, Richard

We report that tropical forests are the most carbon (C)- rich ecosystems on Earth, containing 25–40% of global terrestrial C stocks. While large-scale quantifi- cation of aboveground biomass in tropical forests has improved recently, soil C dynamics remain one of the largest sources of uncertainty in Earth system models, which inhibits our ability to predict future climate. Globally, soil texture and climate predict B 30% of the variation in soil C stocks, so ecosystem models often predict soil C using measures of aboveground plant growth. However, this approach can underestimate tropical soil C stocks, and has proven inaccurate when comparedmore » with data for soil C in data-rich northern ecosystems. By quantifying soil organic C stocks to 1 m depth for 48 humid tropical forest plots across gradients of rainfall and soil fertility in Panama, we show that soil C does not correlate with common predictors used in models, such as plant biomass or litter production. Instead, a structural equation model including base cations, soil clay content, and rainfall as exogenous factors and root biomass as an endogenous factor predicted nearly 50% of the variation in tropical soil C stocks, indicating a strong indirect effect of base cation availability on tropical soil C storage. Including soil base cations in C cycle models, and thus emphasizing mechanistic links among nutrients, root biomass, and soil C stocks, will improve prediction of climate-soil feedbacks in tropical forests.« less

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.

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.

A Coupled Surface Nudging Scheme for use in Retrospective ...

EPA Pesticide Factsheets

A surface analysis nudging scheme coupling atmospheric and land surface thermodynamic parameters has been implemented into WRF v3.8 (latest version) for use with retrospective weather and climate simulations, as well as for applications in air quality, hydrology, and ecosystem modeling. This scheme is known as the flux-adjusting surface data assimilation system (FASDAS) developed by Alapaty et al. (2008). This scheme provides continuous adjustments for soil moisture and temperature (via indirect nudging) and for surface air temperature and water vapor mixing ratio (via direct nudging). The simultaneous application of indirect and direct nudging maintains greater consistency between the soil temperature–moisture and the atmospheric surface layer mass-field variables. The new method, FASDAS, consistently improved the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as well as for high resolution regional climate predictions. This new capability has been released in WRF Version 3.8 as option grid_sfdda = 2. This new capability increased the accuracy of atmospheric inputs for use air quality, hydrology, and ecosystem modeling research to improve the accuracy of respective end-point research outcome. IMPACT: A new method, FASDAS, was implemented into the WRF model to consistently improve the accuracy of the model simulations at weather prediction scales for different horizontal grid resolutions, as wel

Global variation of carbon use efficiency in terrestrial ecosystems

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowground respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model-observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha-1 yr-1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Modeling the temporal dynamics of nonstructural carbohydrate pools in forest trees

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

Richardson, Andrew D.

Trees store carbohydrates, in the form of sugars and starch, as reserves to be used to power both future growth as well as to support day-to-day metabolic functions. These reserves are particularly important in the context of how trees cope with disturbance and stress—for example, as related to pest outbreaks, wind or ice damage, and extreme climate events. In this project, we measured the size of carbon reserves in forest trees, and determined how quickly these reserves are used and replaced—i.e., their “turnover time”. Our work was conducted at Harvard Forest, a temperate deciduous forest in central Massachusetts. Through fieldmore » sampling, laboratory-based chemical analyses, and allometric modeling, we scaled these measurements up to whole-tree NSC budgets. We used these data to test and improve computer simulation models of carbon flow through forest ecosystems. Our modeling focused on the mathematical representation of these stored carbon reserves, and we examined the sensitivity of model performance to different model structures. This project contributes to DOE’s goal to improve next-generation models of the earth system, and to understand the impacts of climate change on terrestrial ecosystems.« less

Preliminary analysis of the Jimo coastal ecosystem with the ecopath model

NASA Astrophysics Data System (ADS)

Su, Meng

2016-12-01

The Jimo coast encompasses an area of 2157 km2, and the ecosystem is valuable both socially and economically with regional fisheries substantially contributing to the value. A mass-balanced trophic model consisting of 15 functional ecological groups was developed for the coastal ecosystem using the Ecopath model in Ecopath with Ecosim (EwE) software (version 6.4.3). The results of the model simulations indicated that the trophic levels of the functional groups varied between 1.0 and 3.76, and the total production of the system was estimated to be 5112.733 t km-2 yr-1 with a total energy transfer efficiency of 17.6%. The proportion of the total flow originating from detritus was estimated to be 48%, whereas that from primary producers was 52%, indicating that the grazing food chain dominated the energy flow. The ratio of total primary productivity to total respiration in the system was 3.78, and the connectivity index was 0.4. The fin cycling index and the mean path length of the energy flow were 4.92% and 2.57%, respectively, which indicated that the ecosystem exhibits relatively low maturity and stability. The mixed trophic impact (MTI) procedure suggested that the ecological groups at lower trophic levels dominated the feeding dynamics in the Jimo coastal ecosystem. Overfishing is thought to be the primary reason for the degeneration of the Jimo coastal ecosystem, resulting in a decline in the abundance of pelagic and demersal fish species and a subsequent shift to the predominance of lower-trophic-level functional groups. Finally, we offered some recommendations for improving current fishery management practices.

LPJmL4 - a dynamic global vegetation model with managed land - Part 2: Model evaluation

NASA Astrophysics Data System (ADS)

Schaphoff, Sibyll; Forkel, Matthias; Müller, Christoph; Knauer, Jürgen; von Bloh, Werner; Gerten, Dieter; Jägermeyr, Jonas; Lucht, Wolfgang; Rammig, Anja; Thonicke, Kirsten; Waha, Katharina

2018-04-01

The dynamic global vegetation model LPJmL4 is a process-based model that simulates climate and land use change impacts on the terrestrial biosphere, agricultural production, and the water and carbon cycle. Different versions of the model have been developed and applied to evaluate the role of natural and managed ecosystems in the Earth system and the potential impacts of global environmental change. A comprehensive model description of the new model version, LPJmL4, is provided in a companion paper (Schaphoff et al., 2018c). Here, we provide a full picture of the model performance, going beyond standard benchmark procedures and give hints on the strengths and shortcomings of the model to identify the need for further model improvement. Specifically, we evaluate LPJmL4 against various datasets from in situ measurement sites, satellite observations, and agricultural yield statistics. We apply a range of metrics to evaluate the quality of the model to simulate stocks and flows of carbon and water in natural and managed ecosystems at different temporal and spatial scales. We show that an advanced phenology scheme improves the simulation of seasonal fluctuations in the atmospheric CO2 concentration, while the permafrost scheme improves estimates of carbon stocks. The full LPJmL4 code including the new developments will be supplied open source through https://gitlab.pik-potsdam.de/lpjml/LPJmL. We hope that this will lead to new model developments and applications that improve the model performance and possibly build up a new understanding of the terrestrial biosphere.

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

USGS Publications Warehouse

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

2013-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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

DOE PAGES

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

2017-09-18

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

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

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

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

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

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2015-08-01

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

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

PubMed

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

2015-08-01

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

Partitioning CO 2 fluxes with isotopologue measurements and modeling to understand mechanisms of forest carbon sequestration

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

Saleska, Scott; Davidson, Eric; Finzi, Adrien

1. Objectives This project combines automated in situ observations of the isotopologues of CO 2 with root observations, novel experimental manipulations of belowground processes, and isotope-enabled ecosystem modeling to investigate mechanisms of below- vs. aboveground carbon sequestration at the Harvard Forest Environmental Measurements Site (EMS). The proposed objectives, which have now been largely accomplished, include: A. Partitioning of net ecosystem CO 2 exchange (NEE) into photosynthesis and respiration using long-term continuous observations of the isotopic composition of NEE, and analysis of their dynamics ; B. Investigation of the influence of vegetation phenology on the timing and magnitude of carbon allocatedmore » belowground using measurements of root growth and indices of belowground autotrophic vs. heterotrophic respiration (via trenched plots and isotope measurements); C. Testing whether plant allocation of carbon belowground stimulates the microbial decomposition of soil organic matter, using in situ rhizosphere simulation experiments wherein realistic quantities of artificial isotopically-labeled exudates are released into the soil; and D. Synthesis and interpretation of the above data using the Ecosystem Demography Model 2 (ED2). 2. Highlights Accomplishments: • Our isotopic eddy flux record has completed its 5th full year and has been used to independently estimate ecosystem-scale respiration and photosynthesis. • Soil surface chamber isotopic flux measurements were carried out during three growing seasons, in conjunction with a trenching manipulation. Key findings to date (listed by objective): A. Partitioning of Net Ecosystem Exchange: 1. Ecosystem respiration is lower during the day than at night—the first robust evidence of the inhibition of leaf respiration by light (the “Kok effect”) at the ecosystem scale. 2. Because it neglects the Kok effect, the standard NEE partitioning approach overestimates ecosystem photosynthesis (by ~25%) and daytime respiration (by ~100%) in the first half of the growing season at our site, and portrays ecosystem photosynthetic light-use efficiency as declining when in fact it is stable until autumnal senescence. B. Vegetation Phenology and belowground allocation: Findings: 1. Autotrophic respiration (Ra) showed a seasonal pattern, peaking in mid-summer when trees were most active. 2. The effective age of the substrate for belowground respiration is less than 2 weeks. 3. Above and belowground phenology are more synchronous in deciduous hardwood stands than evergreen hemlock stands. 4. The decline in root respiration rates in the fall is related to temperature rather than acclimation of root respiration or substrate limitations. Methodological Issues: 5. The isotopic signatures of autotrophic and heterotrophic respiration are too similar for isotopic partitioning of belowground respiration into these two components at our site—in keeping with the recent findings of Bowling et al. (2015) in a subalpine conifer forest. 6. Artifacts of the trenching method, such as changes in soil moisture and increased carbon substrate from the newly severed roots, are significant and need to be quantified when determining daily to annual estimates of autotrophic and heterotrophic respiration. C. Effects of simulated exudates on priming of microbial decomposition: The stoichiometry of root exudates influences both the amount and the mechanism by which priming occurs. At low C:N, SOC loss is caused by an increase in microbial efficiency. At high C:N, SOC loss is caused by an increase in microbial biomass. D. Modeling with the Ecosystem Demography Model (ED2): 1. Incorporation of 13C tracking to create an isotopically-enabled Ecosystem Demography v2 model (ED2) 2. State-of-the-art parameter optimization methodology developed for improving ED2 model predictions and parameters. 3. Significantly improved model predictions of growth- and maintenance-related carbon fluxes and 13C fluxes« less

Partitioning CO2 fluxes with isotopologue measurements and modeling to understand mechanisms of forest carbon sequestration

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

Saleska, Scott; Davidson, Eric; Finzi, Adrien

1. Objectives This project combines automated in situ observations of the isotopologues of CO2 with root observations, novel experimental manipulations of belowground processes, and isotope-enabled ecosystem modeling to investigate mechanisms of below- vs. aboveground carbon sequestration at the Harvard Forest Environmental Measurements Site (EMS). The proposed objectives, which have now been largely accomplished, include: A. Partitioning of net ecosystem CO2 exchange (NEE) into photosynthesis and respiration using long-term continuous observations of the isotopic composition of NEE, and analysis of their dynamics ; B. Investigation of the influence of vegetation phenology on the timing and magnitude of carbon allocated belowground usingmore » measurements of root growth and indices of belowground autotrophic vs. heterotrophic respiration (via trenched plots and isotope measurements); C. Testing whether plant allocation of carbon belowground stimulates the microbial decomposition of soil organic matter, using in situ rhizosphere simulation experiments wherein realistic quantities of artificial isotopically-labeled exudates are released into the soil; and D. Synthesis and interpretation of the above data using the Ecosystem Demography Model 2 (ED2). 2. Highlights Accomplishments: • Our isotopic eddy flux record has completed its 5th full year and has been used to independently estimate ecosystem-scale respiration and photosynthesis. • Soil surface chamber isotopic flux measurements were carried out during three growing seasons, in conjunction with a trenching manipulation. Key findings to date (listed by objective): A. Partitioning of Net Ecosystem Exchange: 1. Ecosystem respiration is lower during the day than at night—the first robust evidence of the inhibition of leaf respiration by light (the “Kok effect”) at the ecosystem scale. 2. Because it neglects the Kok effect, the standard NEE partitioning approach overestimates ecosystem photosynthesis (by ~25%) and daytime respiration (by ~100%) in the first half of the growing season at our site, and portrays ecosystem photosynthetic light-use efficiency as declining when in fact it is stable until autumnal senescence. B. Vegetation Phenology and belowground allocation: Findings: 1. Autotrophic respiration (Ra) showed a seasonal pattern, peaking in mid-summer when trees were most active. 2. The effective age of the substrate for belowground respiration is less than 2 weeks. 3. Above and belowground phenology are more synchronous in deciduous hardwood stands than evergreen hemlock stands. 4. The decline in root respiration rates in the fall is related to temperature rather than acclimation of root respiration or substrate limitations. Methodological Issues: 5. The isotopic signatures of autotrophic and heterotrophic respiration are too similar for isotopic partitioning of belowground respiration into these two components at our site—in keeping with the recent findings of Bowling et al. (2015) in a subalpine conifer forest. 6. Artifacts of the trenching method, such as changes in soil moisture and increased carbon substrate from the newly severed roots, are significant and need to be quantified when determining daily to annual estimates of autotrophic and heterotrophic respiration. C. Effects of simulated exudates on priming of microbial decomposition: The stoichiometry of root exudates influences both the amount and the mechanism by which priming occurs. At low C:N, SOC loss is caused by an increase in microbial efficiency. At high C:N, SOC loss is caused by an increase in microbial biomass. D. Modeling with the Ecosystem Demography Model (ED2): 1. Incorporation of 13C tracking to create an isotopically-enabled Ecosystem Demography v2 model (ED2) 2. State-of-the-art parameter optimization methodology developed for improving ED2 model predictions and parameters. 3. Significantly improved model predictions of growth- and maintenance-related carbon fluxes and 13C fluxes« less

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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.

Implementing seasonal carbon allocation into a dynamic vegetation model

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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

DOE PAGES

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

2014-12-11

Accurate representation of ecosystem processes in land models is crucial for reducing predictive uncertainty in energy and greenhouse gas feedbacks with the climate. Here we describe an observational and modeling meta-analysis approach to benchmark land models, and apply the method to the land model CLM4.5 with two versions of belowground biogeochemistry. We focused our analysis on the aboveground and belowground responses to warming and nitrogen addition in high-latitude ecosystems, and identified absent or poorly parameterized mechanisms in CLM4.5. While the two model versions predicted similar soil carbon stock trajectories following both warming and nitrogen addition, other predicted variables (e.g., belowgroundmore » respiration) differed from observations in both magnitude and direction, indicating that CLM4.5 has inadequate underlying mechanisms for representing high-latitude ecosystems. On the basis of observational synthesis, we attribute the model–observation differences to missing representations of microbial dynamics, aboveground and belowground coupling, and nutrient cycling, and we use the observational meta-analysis to discuss potential approaches to improving the current models. However, we also urge caution concerning the selection of data sets and experiments for meta-analysis. For example, the concentrations of nitrogen applied in the synthesized field experiments (average = 72 kg ha -1 yr -1) are many times higher than projected soil nitrogen concentrations (from nitrogen deposition and release during mineralization), which precludes a rigorous evaluation of the model responses to likely nitrogen perturbations. Overall, we demonstrate that elucidating ecological mechanisms via meta-analysis can identify deficiencies in ecosystem models and empirical experiments.« less

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

DOE PAGES

Stegen, James C.

2018-04-10

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

At the Nexus of History, Ecology, and Hydrobiogeochemistry: Improved Predictions across Scales through Integration

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

Stegen, James C.

To improve predictions of ecosystem function in future environments, we need to integrate the ecological and environmental histories experienced by microbial communities with hydrobiogeochemistry across scales. A key issue is whether we can derive generalizable scaling relationships that describe this multiscale integration. There is a strong foundation for addressing these challenges. We have the ability to infer ecological history with null models and reveal impacts of environmental history through laboratory and field experimentation. Recent developments also provide opportunities to inform ecosystem models with targeted omics data. A major next step is coupling knowledge derived from such studies with multiscale modelingmore » frameworks that are predictive under non-steady-state conditions. This is particularly true for systems spanning dynamic interfaces, which are often hot spots of hydrobiogeochemical function. Here, we can advance predictive capabilities through a holistic perspective focused on the nexus of history, ecology, and hydrobiogeochemistry.« less

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.

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.

Challenges and opportunities to improve understanding on wetland ecosystem and function at the local catchment scale: data fusion, data-model integration, and prediction uncertainty.

NASA Astrophysics Data System (ADS)

Yeo, I. Y.

2016-12-01

Wetlands are valuable landscape features that provide important ecosystem functions and services. The ecosystem processes in wetlands are highly dependent on the hydrology. However, hydroperiod (i.e., change dynamics in inundation extent) is highly variable spatially and temporarily, and extremely difficult to predict owing to the complexity in hydrological processes within wetlands and its interaction with surrounding areas. This study reports the challenges and progress in assessing the catchment scale benefits of wetlands to regulate hydrological regime and water quality improvement in agricultural watershed. A process-based watershed model, Soil and Water Assessment Tool (SWAT) was improved to simulate the cumulative impacts of wetlands on downstream. Newly developed remote sensing products from LiDAR intensity and time series Landsat records, which show the inter-annual changes in fraction inundation, were utilized to describe the change status of inundated areas within forested wetlands, develop spatially varying wetland parameters, and evaluate the predicted inundated areas at the landscape level. We outline the challenges on developing the time series inundation mapping products at a high spatial and temporal resolution and reconciling the catchment scale model with the moderate remote sensing products. We then highlight the importance of integrating spatialized information to model calibration and evaluation to address the issues of equi-finality and prediction uncertainty. This integrated approach was applied to the upper region of Choptank River Watershed, the agricultural watershed in the Coastal Plain of Chesapeake Bay Watershed (in US). In the Mid- Atlantic US, the provision of pollution regulation services provided by wetlands has been emphasized due to declining water quality within the Chesapeake Bay and watersheds, and the preservation and restoration of wetlands has become the top priority to manage nonpoint source water pollution.

Valuing ecological systems and services

PubMed Central

Kubiszewski, Ida; Ervin, David; Bluffstone, Randy; Boyd, James; Brown, Darrell; Chang, Heejun; Dujon, Veronica; Granek, Elise; Polasky, Stephen; Shandas, Vivek; Yeakley, Alan

2011-01-01

Making trade-offs between ecological services and other contributors to human well-being is a difficult but critical process that requires valuation. This allows both better recognition of the ecological, social, and economic trade-offs and also allows us to bill those who use up or destroy ecological services and reward those that produce or enhance them. It also aids improved ecosystems policy. In this paper we clarify some of the controversies in defining the contributions to human well-being from functioning ecosystems, many of which people are not even aware of. We go on to describe the applicability of the various valuation methods that can be used in estimating the benefits of ecosystem services. Finally, we describe some recent case studies and lay out the research agenda for ecosystem services analysis, modeling, and valuation going forward. PMID:21876725

Baseline and projected future carbon storage and greenhouse-gas fluxes in ecosystems of the Western United States

USGS Publications Warehouse

Zhu, Zhi-Liang; Reed, Bradley C.

2012-01-01

This assessment was conducted to fulfill the requirements of section 712 of the Energy Independence and Security Act (EISA) of 2007 and to improve understanding of carbon and greenhouse gas (GHG) fluxes in ecosystems of the Western United States. The assessment examined carbon storage, carbon fluxes, and other GHG fluxes (methane and nitrous oxide) in all major terrestrial ecosystems (forests, grasslands/shrublands, agricultural lands, and wetlands) and aquatic ecosystems (rivers, streams, lakes, reservoirs, and coastal waters) in two time periods: baseline (generally in the first half of the 2010s) and future (projections from baseline to 2050). The assessment was based on measured and observed data collected by the U.S. Geological Survey (USGS) and many other agencies and organizations and used remote sensing, statistical methods, and simulation models.

A Spectral Evaluation of Models Performances in Mediterranean Oak Woodlands

NASA Astrophysics Data System (ADS)

Vargas, R.; Baldocchi, D. D.; Abramowitz, G.; Carrara, A.; Correia, A.; Kobayashi, H.; Papale, D.; Pearson, D.; Pereira, J.; Piao, S.; Rambal, S.; Sonnentag, O.

2009-12-01

Ecosystem processes are influenced by climatic trends at multiple temporal scales including diel patterns and other mid-term climatic modes, such as interannual and seasonal variability. Because interactions between biophysical components of ecosystem processes are complex, it is important to test how models perform in frequency (e.g. hours, days, weeks, months, years) and time (i.e. day of the year) domains in addition to traditional tests of annual or monthly sums. Here we present a spectral evaluation using wavelet time series analysis of model performance in seven Mediterranean Oak Woodlands that encompass three deciduous and four evergreen sites. We tested the performance of five models (CABLE, ORCHIDEE, BEPS, Biome-BGC, and JULES) on measured variables of gross primary production (GPP) and evapotranspiration (ET). In general, model performance fails at intermediate periods (e.g. weeks to months) likely because these models do not represent the water pulse dynamics that influence GPP and ET at these Mediterranean systems. To improve the performance of a model it is critical to identify first where and when the model fails. Only by identifying where a model fails we can improve the model performance and use them as prognostic tools and to generate further hypotheses that can be tested by new experiments and measurements.

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

PubMed

Zhang, Wei; Swinton, Scott M

2012-04-15

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

Improving Quality of Life and Career Attitudes of Youth with Disabilities: Experiences from the Adolescent Employment Readiness Center

ERIC Educational Resources Information Center

Wolf-Branigin, Michael; Schuyler, Vincent; White, Patience

2007-01-01

Improving quality of life is the primary focus as adolescents with disabilities enter adulthood. They increasingly, however, encounter difficulties transitioning into domains such as employment as these services occur near the end of their high school experience. Using an ecosystems model within a developmental approach, the program sought to…

Mapping SOC (Soil Organic Carbon) using LiDAR-derived vegetation indices in a random forest regression model

NASA Astrophysics Data System (ADS)

Will, R. M.; Glenn, N. F.; Benner, S. G.; Pierce, J. L.; Spaete, L.; Li, A.

2015-12-01

Quantifying SOC (Soil Organic Carbon) storage in complex terrain is challenging due to high spatial variability. Generally, the challenge is met by transforming point data to the entire landscape using surrogate, spatially-distributed, variables like elevation or precipitation. In many ecosystems, remotely sensed information on above-ground vegetation (e.g. NDVI) is a good predictor of below-ground carbon stocks. In this project, we are attempting to improve this predictive method by incorporating LiDAR-derived vegetation indices. LiDAR provides a mechanism for improved characterization of aboveground vegetation by providing structural parameters such as vegetation height and biomass. In this study, a random forest model is used to predict SOC using a suite of LiDAR-derived vegetation indices as predictor variables. The Reynolds Creek Experimental Watershed (RCEW) is an ideal location for a study of this type since it encompasses a strong elevation/precipitation gradient that supports lower biomass sagebrush ecosystems at low elevations and forests with more biomass at higher elevations. Sagebrush ecosystems composed of Wyoming, Low and Mountain Sagebrush have SOC values ranging from .4 to 1% (top 30 cm), while higher biomass ecosystems composed of aspen, juniper and fir have SOC values approaching 4% (top 30 cm). Large differences in SOC have been observed between canopy and interspace locations and high resolution vegetation information is likely to explain plot scale variability in SOC. Mapping of the SOC reservoir will help identify underlying controls on SOC distribution and provide insight into which processes are most important in determining SOC in semi-arid mountainous regions. In addition, airborne LiDAR has the potential to characterize vegetation communities at a high resolution and could be a tool for improving estimates of SOC at larger scales.

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...

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.

MIDWESTERN REGIONAL CENTER OF THE DOE NATIONAL INSTITUTE FOR CLIMATIC CHANGE RESEARCH

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

Burton, Andrew J.

2014-02-28

The goal of NICCR (National Institute for Climatic Change Research) was to mobilize university researchers, from all regions of the country, in support of the climatic change research objectives of DOE/BER. The NICCR Midwestern Regional Center (MRC) supported work in the following states: North Dakota, South Dakota, Nebraska, Kansas, Oklahoma, Minnesota, Iowa, Missouri, Wisconsin, Illinois, Michigan, Indiana, and Ohio. The MRC of NICCR was able to support nearly $8 million in climatic change research, including $6,671,303 for twenty projects solicited and selected by the MRC over five requests for proposals (RFPs) and $1,051,666 for the final year of ten projectsmore » from the discontinued DOE NIGEC (National Institute for Global Environmental Change) program. The projects selected and funded by the MRC resulted in 135 peer-reviewed publications and supported the training of 25 PhD students and 23 Masters students. Another 36 publications were generated by the final year of continuing NIGEC projects supported by the MRC. The projects funded by the MRC used a variety of approaches to answer questions relevant to the DOE’s climate change research program. These included experiments that manipulated temperature, moisture and other global change factors; studies that sought to understand how the distribution of species and ecosystems might change under future climates; studies that used measurements and modeling to examine current ecosystem fluxes of energy and mass and those that would exist under future conditions; and studies that synthesized existing data sets to improve our understanding of the effects of climatic change on terrestrial ecosystems. In all of these efforts, the MRC specifically sought to identify and quantify responses of terrestrial ecosystems that were not well understood or not well modeled by current efforts. The MRC also sought to better understand and model important feedbacks between terrestrial ecosystems, atmospheric chemistry, and regional and global climate systems. The broad variety of projects the MRC has supported gave us a unique opportunity to greatly improve our ability to predict the future health, composition and function of important agricultural and natural terrestrial ecosystems within the Midwestern Region.« less

Analysis of High Spatial, Temporal, and Directional Resolution Recordings of Biological Sounds in the Southern California Bight

DTIC Science & Technology

2013-09-30

transiting whales in the Southern California Bight, b) the use of passive underwater acoustic techniques for improved habitat assessment in biologically...sensitive areas and improved ecosystem modeling, and c) the application of the physics of excitable media to numerical modeling of biological choruses...was on the potential impact of man-made sounds on the calling behavior of transiting humpback whales in the Southern California Bight. The main

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

PubMed

Medvigy, David; Moorcroft, Paul R

2012-01-19

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

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

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

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers

DOE PAGES

Le Page, Yannick LB; Morton, Douglas; Bond-Lamberty, Benjamin; ...

2015-02-13

Vegetation fires are a major driver of ecosystem dynamics and greenhouse gas emissions. Anticipating potential changes in fire activity and their impacts relies first on a realistic model of fire activity (e.g., fire incidence and interannual variability) and second on a model accounting for fire impacts (e.g., mortality and emissions). In this paper, we focus on our understanding of fire activity and describe a new fire model, HESFIRE (Human–Earth System FIRE), which integrates the influence of weather, vegetation characteristics, and human activities on fires in a stand-alone framework. It was developed with a particular emphasis on allowing fires to spreadmore » over consecutive days given their major contribution to burned areas in many ecosystems. A subset of the model parameters was calibrated through an optimization procedure using observation data to enhance our knowledge of regional drivers of fire activity and improve the performance of the model on a global scale. Modeled fire activity showed reasonable agreement with observations of burned area, fire seasonality, and interannual variability in many regions, including for spatial and temporal domains not included in the optimization procedure. Significant discrepancies are investigated, most notably regarding fires in boreal regions and in xeric ecosystems and also fire size distribution. The sensitivity of fire activity to model parameters is analyzed to explore the dominance of specific drivers across regions and ecosystems. The characteristics of HESFIRE and the outcome of its evaluation provide insights into the influence of anthropogenic activities and weather, and their interactions, on fire activity.« less

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.

Carbon and Water Vapor Fluxes of Different Ecosystems in Oklahoma

NASA Astrophysics Data System (ADS)

Wagle, P.; Gowda, P. H.; Northup, B. K.

2016-12-01

Information on exchange of energy, carbon dioxide (CO2), and water vapor (H2O) for major terrestrial ecosystems is vital to quantify carbon and water balances on a large-scale. It is also necessary to develop, test, and improve crop models and satellite-based production efficiency and evapotranspiration (ET) models, and to better understand the potential of terrestrial ecosystems to mitigate rising atmospheric CO2 concentration and climate change. A network (GRL-FLUXNET) of nine eddy flux towers has been established over a diverse range of terrestrial ecosystems, including native and improved perennial grasslands [unburned and grazed tallgrass prairie, burned and grazed tallgrass prairie, and burned Bermuda grass (Cynodon dactylon L.)], grazed and non-grazed winter wheat (Triticum aestivum L.), till and no-till winter wheat and canola (Brassica napus L.), alfalfa (Medicago sativa L.), and soybean (Glycine max L.), at the USDA-ARS, Grazinglands Research Laboratory, El Reno, OK. In this presentation, we quantify and compare net ecosystem CO2 exchange (NEE) and ET between recently burned and grazed tallgrass prairie and burned and non-grazed Bermuda grass pastures, alfalfa, and soybean. Preliminary results show monthly ensembles average NEE reached seasonal peak values of -29, -35, -25, and -20 µmol m-2 s-1 in burned tallgrass prairie pasture, burned Bermuda grass pasture, alfalfa, and soybean, respectively. Similarly, monthly ensembles average ET reached seasonal peak values of 0.22, 0.27, 0.25, 0.28 mm 30-min-1 in burned tallgrass prairie pasture, burned Bermuda grass pasture, alfalfa, and soybean, respectively. Seasonal patterns and daily magnitudes of NEE and ET and their responses to the similar climatic conditions will be further investigated.

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

NASA Astrophysics Data System (ADS)

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

2012-03-01

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

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

NASA Astrophysics Data System (ADS)

Xu, Y.; Ba, Q.

2011-12-01

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

GLIMPSE – A computational framework for supporting state-level environmental and energy planning

EPA Pesticide Factsheets

GLIMPSE is an EPA modeling tool for environmental and energy planning used to find U.S. policy scenarios that simultaneously improve air quality, human health, reduce impacts to ecosystems, and mitigate climate change.

Assimilation of seasonal chlorophyll and nutrient data into an adjoint three-dimensional ocean carbon cycle model: Sensitivity analysis and ecosystem parameter optimization

NASA Astrophysics Data System (ADS)

Tjiputra, Jerry F.; Polzin, Dierk; Winguth, Arne M. E.

2007-03-01

An adjoint method is applied to a three-dimensional global ocean biogeochemical cycle model to optimize the ecosystem parameters on the basis of SeaWiFS surface chlorophyll observation. We showed with identical twin experiments that the model simulated chlorophyll concentration is sensitive to perturbation of phytoplankton and zooplankton exudation, herbivore egestion as fecal pellets, zooplankton grazing, and the assimilation efficiency parameters. The assimilation of SeaWiFS chlorophyll data significantly improved the prediction of chlorophyll concentration, especially in the high-latitude regions. Experiments that considered regional variations of parameters yielded a high seasonal variance of ecosystem parameters in the high latitudes, but a low variance in the tropical regions. These experiments indicate that the adjoint model is, despite the many uncertainties, generally capable to optimize sensitive parameters and carbon fluxes in the euphotic zone. The best fit regional parameters predict a global net primary production of 36 Pg C yr-1, which lies within the range suggested by Antoine et al. (1996). Additional constraints of nutrient data from the World Ocean Atlas showed further reduction in the model-data misfit and that assimilation with extensive data sets is necessary.

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

PubMed

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

2015-03-01

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

Ecosystem-scale plant hydraulic strategies inferred from remotely-sensed soil moisture

NASA Astrophysics Data System (ADS)

Bassiouni, M.; Good, S. P.; Higgins, C. W.

2017-12-01

Characterizing plant hydraulic strategies at the ecosystem scale is important to improve estimates of evapotranspiration and to understand ecosystem productivity and resilience. However, quantifying plant hydraulic traits beyond the species level is a challenge. The probability density function of soil moisture observations provides key information about the soil moisture states at which evapotranspiration is reduced by water stress. Here, an inverse Bayesian approach is applied to a standard bucket model of soil column hydrology forced with stochastic precipitation inputs. Through this approach, we are able to determine the soil moisture thresholds at which stomata are open or closed that are most consistent with observed soil moisture probability density functions. This research utilizes remotely-sensed soil moisture data to explore global patterns of ecosystem-scale plant hydraulic strategies. Results are complementary to literature values of measured hydraulic traits of various species in different climates and previous estimates of ecosystem-scale plant isohydricity. The presented approach provides a novel relation between plant physiological behavior and soil-water dynamics.

An improved state-parameter analysis of ecosystem models using data assimilation

USGS Publications Warehouse

Chen, M.; Liu, S.; Tieszen, L.L.; Hollinger, D.Y.

2008-01-01

Much of the effort spent in developing data assimilation methods for carbon dynamics analysis has focused on estimating optimal values for either model parameters or state variables. The main weakness of estimating parameter values alone (i.e., without considering state variables) is that all errors from input, output, and model structure are attributed to model parameter uncertainties. On the other hand, the accuracy of estimating state variables may be lowered if the temporal evolution of parameter values is not incorporated. This research develops a smoothed ensemble Kalman filter (SEnKF) by combining ensemble Kalman filter with kernel smoothing technique. SEnKF has following characteristics: (1) to estimate simultaneously the model states and parameters through concatenating unknown parameters and state variables into a joint state vector; (2) to mitigate dramatic, sudden changes of parameter values in parameter sampling and parameter evolution process, and control narrowing of parameter variance which results in filter divergence through adjusting smoothing factor in kernel smoothing algorithm; (3) to assimilate recursively data into the model and thus detect possible time variation of parameters; and (4) to address properly various sources of uncertainties stemming from input, output and parameter uncertainties. The SEnKF is tested by assimilating observed fluxes of carbon dioxide and environmental driving factor data from an AmeriFlux forest station located near Howland, Maine, USA, into a partition eddy flux model. Our analysis demonstrates that model parameters, such as light use efficiency, respiration coefficients, minimum and optimum temperatures for photosynthetic activity, and others, are highly constrained by eddy flux data at daily-to-seasonal time scales. The SEnKF stabilizes parameter values quickly regardless of the initial values of the parameters. Potential ecosystem light use efficiency demonstrates a strong seasonality. Results show that the simultaneous parameter estimation procedure significantly improves model predictions. Results also show that the SEnKF can dramatically reduce the variance in state variables stemming from the uncertainty of parameters and driving variables. The SEnKF is a robust and effective algorithm in evaluating and developing ecosystem models and in improving the understanding and quantification of carbon cycle parameters and processes. ?? 2008 Elsevier B.V.

Integrating ecosystem services analysis into scenario planning practice: accounting for street tree benefits with i-Tree valuation in Central Texas.

PubMed

Hilde, Thomas; Paterson, Robert

2014-12-15

Scenario planning continues to gain momentum in the United States as an effective process for building consensus on long-range community plans and creating regional visions for the future. However, efforts to integrate more sophisticated information into the analytical framework to help identify important ecosystem services have lagged in practice. This is problematic because understanding the tradeoffs of land consumption patterns on ecological integrity is central to mitigating the environmental degradation caused by land use change and new development. In this paper we describe how an ecosystem services valuation model, i-Tree, was integrated into a mainstream scenario planning software tool, Envision Tomorrow, to assess the benefits of public street trees for alternative future development scenarios. The tool is then applied to development scenarios from the City of Hutto, TX, a Central Texas Sustainable Places Project demonstration community. The integrated tool represents a methodological improvement for scenario planning practice, offers a way to incorporate ecosystem services analysis into mainstream planning processes, and serves as an example of how open source software tools can expand the range of issues available for community and regional planning consideration, even in cases where community resources are limited. The tool also offers room for future improvements; feasible options include canopy analysis of various future land use typologies, as well as a generalized street tree model for broader U.S. application. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Towards 250 m mapping of terrestrial primary productivity over Canada

NASA Astrophysics Data System (ADS)

Gonsamo, A.; Chen, J. M.

2011-12-01

Terrestrial ecosystems are an important part of the climate and global change systems. Their role in climate change and in the global carbon cycle is yet to be well understood. Dataset from satellite earth observation, coupled with numerical models provide the unique tools for monitoring the spatial and temporal dynamics of territorial carbon cycle. The Boreal Ecosystems Productivity Simulator (BEPS) is a remote sensing based approach to quantifying the terrestrial carbon cycle by that gross and net primary productivity (GPP and NPP) and terrestrial carbon sinks and sources expressed as net ecosystem productivity (NEP). We have currently implemented a scheme to map the GPP, NPP and NEP at 250 m for first time over Canada using BEPS model. This is supplemented by improved mapping of land cover and leaf area index (LAI) at 250 m over Canada from MODIS satellite dataset. The results from BEPS are compared with MODIS GPP product and further evaluated with estimated LAI from various sources to evaluate if the results capture the trend in amount of photosynthetic biomass distributions. Final evaluation will be to validate both BEPS and MODIS primary productivity estimates over the Fluxnet sites over Canada. The primary evaluation indicate that BEPS GPP estimates capture the over storey LAI variations over Canada very well compared to MODIS GPP estimates. There is a large offset of MODIS GPP, over-estimating the lower GPP value compared to BEPS GPP estimates. These variations will further be validated based on the measured values from the Fluxnet tower measurements over Canadian. The high resolution GPP (NPP) products at 250 m will further be used to scale the outputs between different ecosystem productivity models, in our case the Canadian carbon budget model of Canadian forest sector CBM-CFS) and the Integrated Terrestrial Ecosystem Carbon model (InTEC).

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.

Why we need better predictive models of vegetation phenology

NASA Astrophysics Data System (ADS)

Richardson, Andrew; Migliavacca, Mirco; Keenan, Trevor

2014-05-01

Vegetation phenology is strongly affected by climate change, with warmer temperatures causing earlier spring onset and delayed autumn senescence in most temperate and boreal ecosystems. In arid regions where phenology is driven by the seasonality of soil water availability, shifts in the timing, intensity, and total amount of precipitation are, likewise, affecting the seasonality of vegetation activity. Changes in the duration of the growing season have important implications for ecosystem productivity and uptake of CO2 from the atmosphere, as well as site water balance and runoff, microclimate, ecological interactions within and across trophic levels, and numerous feedbacks to the climate system associated with the surface energy budget. However, an outstanding challenge is that existing phenology sub-models used in ecosystem, land surface, and terrestrial biosphere models fail to adequately represent the seasonality, or sensitivity to environmental drivers, of vegetation phenology. This has two implications. First, these models are therefore likely to perform poorly under future climate scenarios. Second, the seasonality of important ecological processes and interactions, as well as biosphere-atmosphere feedbacks, is likely to be misrepresented as a result. Using data from several recent analyses, and focusing on temperate and boreal ecosystems, we will review current challenges associated with modeling vegetation phenology. We will discuss uncertainties associated with phenology model structure, model parameters, and driver sensitivity (forcing, chilling, and photoperiod). We will show why being able to extrapolate and generalize models (and model parameterization) is essential. We will consider added challenges associated with trying to model autumn phenology. Finally, we will use canopy photosynthesis and uptake of CO2 as an example of why improved understanding of the "rhythm of the seasons" is critically important.

Mapping Stormwater Retention in the Cities: A Flexible Model for Data-Scarce Environments

NASA Astrophysics Data System (ADS)

Hamel, P.; Keeler, B.

2014-12-01

There is a growing demand for understanding and mapping urban hydrological ecosystem services, including stormwater retention for flood mitigation and water quality improvement. Progress in integrated urban water management and low impact development in Western countries increased our understanding of how grey and green infrastructure interact to enhance these services. However, valuation methods that account for a diverse group of beneficiaries are typically not made explicit in urban water management models. In addition, the lack of spatial data on the stormwater network in developing countries makes it challenging to apply state-of-the-art models needed to understand both the magnitude and spatial distribution of the stormwater retention service. To fill this gap, we designed the Urban InVEST stormwater retention model, a tool that complements the suite of InVEST software models to quantify and map ecosystem services. We present the model structure emphasizing the data requirements from a user's perspective and the representation of services and beneficiaries. We illustrate the model application with two case studies in a data-rich (New York City) and data-scarce environment. We discuss the difference in the level of information obtained when less resources (data, time, or expertise) are available, and how this affects multiple ecosystem service assessments that the tool is ultimately designed for.

Using Science Skills to Understand Ecophysiology and Manage Resources

NASA Technical Reports Server (NTRS)

Bubenheim, David

2015-01-01

Presentation will be for a general audience and focus on plant science and ecosystem science in NASA. Examples from the projects involving the presenter will be used to illustrate. Specifically, the California Sacramento-San Joaquin River Delta project. This collaboration supports the goals of the Delta Plan in developing science-based, adaptive-management strategies. The mission is to improve reliability of water supply and restore a healthy Delta ecosystem while enhancing agriculture and recreation. NASA can contribute gap-filling science understanding of overall functions in the Delta ecosystem and assess and help develop management plans for specific issues. Airborne and satellite remote-sensing, ecosystem modeling, and biological studies provide underlying data needed by Delta stakeholders to assess and address water, ecosystem restoration, and environmental and economic impacts of potential actions in the Delta. The California Sacramento-San Joaquin River Delta, the hub for California's water supply, supports important ecosystem services for fisheries, supplies drinking water for millions, and distributes water from Northern California to agriculture and urban communities to the south; millions of people and businesses depend on Delta water. Decades of competing demands for Delta resources and year-to-year variability in precipitation has resulted in diminished overall health of the Delta. Declines in fish populations, threatened ecosystems, endangered species, invasive plants and animals, cuts in agricultural exports, and increased water conservation is the result. NASA and the USDA, building on previous collaborations, aide local Delta stakeholders in assessing and developing an invasive weed management approach. Aquatic, terrestrial, and riparian invasive weeds threaten aquatic and terrestrial ecosystem restoration efforts. Aquatic weeds are currently detrimental economically, environmentally, and sociologically in the Delta. They negatively impact the redistribution of water and disrupt the ecology of the Bay Delta food web. Filling current science gaps in the Delta Plan and improving management practices within the Delta are important to achieving the mission of improved Delta health. Methods developed can become routine land and water management tools. New high-resolution NASA sensor systems could be used to provide data packages specifically designed for water system The presenter will also speak about his personal experience and the role Delaware Valley College played in preparation for a professional career science.

Toward a Predictive Understanding of Earth’s Microbiomes to Address 21st Century Challenges

PubMed Central

Blaser, Martin J.; Cardon, Zoe G.; Cho, Mildred K.; Dangl, Jeffrey L.; Green, Jessica L.; Knight, Rob; Maxon, Mary E.; Northen, Trent R.; Pollard, Katherine S.

2016-01-01

ABSTRACT Microorganisms have shaped our planet and its inhabitants for over 3.5 billion years. Humankind has had a profound influence on the biosphere, manifested as global climate and land use changes, and extensive urbanization in response to a growing population. The challenges we face to supply food, energy, and clean water while maintaining and improving the health of our population and ecosystems are significant. Given the extensive influence of microorganisms across our biosphere, we propose that a coordinated, cross-disciplinary effort is required to understand, predict, and harness microbiome function. From the parallelization of gene function testing to precision manipulation of genes, communities, and model ecosystems and development of novel analytical and simulation approaches, we outline strategies to move microbiome research into an era of causality. These efforts will improve prediction of ecosystem response and enable the development of new, responsible, microbiome-based solutions to significant challenges of our time. PMID:27178263

Toward a Predictive Understanding of Earth's Microbiomes to Address 21st Century Challenges.

PubMed

Blaser, Martin J; Cardon, Zoe G; Cho, Mildred K; Dangl, Jeffrey L; Donohue, Timothy J; Green, Jessica L; Knight, Rob; Maxon, Mary E; Northen, Trent R; Pollard, Katherine S; Brodie, Eoin L

2016-05-13

Microorganisms have shaped our planet and its inhabitants for over 3.5 billion years. Humankind has had a profound influence on the biosphere, manifested as global climate and land use changes, and extensive urbanization in response to a growing population. The challenges we face to supply food, energy, and clean water while maintaining and improving the health of our population and ecosystems are significant. Given the extensive influence of microorganisms across our biosphere, we propose that a coordinated, cross-disciplinary effort is required to understand, predict, and harness microbiome function. From the parallelization of gene function testing to precision manipulation of genes, communities, and model ecosystems and development of novel analytical and simulation approaches, we outline strategies to move microbiome research into an era of causality. These efforts will improve prediction of ecosystem response and enable the development of new, responsible, microbiome-based solutions to significant challenges of our time. Copyright © 2016 Blaser et al.

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part II: Evaluations and Applications

NASA Astrophysics Data System (ADS)

Murakami, K.; Sasai, T.; Kato, S.; Niwa, Y.; Saito, M.; Takagi, H.; Matsunaga, T.; Hiraki, K.; Maksyutov, S. S.; Yokota, T.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.Global terrestrial carbon cycle largely depends on a spatial pattern of land cover type, which is heterogeneously-distributed over regional and global scales. Many studies have been trying to reveal distribution of carbon exchanges between terrestrial ecosystems and atmosphere for understanding global carbon cycle dynamics by using terrestrial biosphere models, satellite data, inventory data, and so on. However, most studies remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community and to evaluate the carbon stocks by forest ecosystems in each countries. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. We show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. The methodology for these estimations are shown in the 2015 AGU FM poster "Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling". In this study, we evaluated the carbon exchanges in various regions with other approaches. We used the satellite-driven biosphere model (BEAMS) as our estimations, GOSAT L4A CO2 flux data, NEP retrieved by NICAM and CarbonTracer2013 flux data, for period from Jun 2001 to Dec 2012. The temporal patterns for this period were indicated similar trends between BEAMS, GOSAT, NICAM, and CT2013 in many sub-continental regions. Then, we estimated the terrestrial carbon exchanges in each countries, and could indicated the temporal patterns of the exchanges in large carbon stock regions.

Habitat-Mediated Variation in the Importance of Ecosystem Engineers for Secondary Cavity Nesters in a Nest Web

PubMed Central

Robles, Hugo; Martin, Kathy

2014-01-01

Through physical state changes in biotic or abiotic materials, ecosystem engineers modulate resource availability to other organisms and are major drivers of evolutionary and ecological dynamics. Understanding whether and how ecosystem engineers are interchangeable for resource users in different habitats is a largely neglected topic in ecosystem engineering research that can improve our understanding of the structure of communities. We addressed this issue in a cavity-nest web (1999–2011). In aspen groves, the presence of mountain bluebird (Sialia currucoides) and tree swallow (Tachycineta bicolour) nests was positively related to the density of cavities supplied by northern flickers (Colaptes auratus), which provided the most abundant cavities (1.61 cavities/ha). Flickers in aspen groves provided numerous nesting cavities to bluebirds (66%) and swallows (46%), despite previous research showing that flicker cavities are avoided by swallows. In continuous mixed forests, however, the presence of nesting swallows was mainly related to cavity density of red-naped sapsuckers (Sphyrapicus nuchalis), which provided the most abundant cavities (0.52 cavities/ha), and to cavity density of hairy woodpeckers (Picoides villosus), which provided few (0.14 cavities/ha) but high-quality cavities. Overall, sapsuckers and hairy woodpeckers provided 86% of nesting cavities to swallows in continuous forests. In contrast, the presence of nesting bluebirds in continuous forests was associated with the density of cavities supplied by all the ecosystem engineers. These results suggest that (i) habitat type may mediate the associations between ecosystem engineers and resource users, and (ii) different ecosystem engineers may be interchangeable for resource users depending on the quantity and quality of resources that each engineer supplies in each habitat type. We, therefore, urge the incorporation of the variation in the quantity and quality of resources provided by ecosystem engineers across habitats into models that assess community dynamics to improve our understanding of the importance of ecosystem engineers in shaping ecological communities. PMID:24587211

Habitat-mediated variation in the importance of ecosystem engineers for secondary cavity nesters in a nest web.

PubMed

Robles, Hugo; Martin, Kathy

2014-01-01

Through physical state changes in biotic or abiotic materials, ecosystem engineers modulate resource availability to other organisms and are major drivers of evolutionary and ecological dynamics. Understanding whether and how ecosystem engineers are interchangeable for resource users in different habitats is a largely neglected topic in ecosystem engineering research that can improve our understanding of the structure of communities. We addressed this issue in a cavity-nest web (1999-2011). In aspen groves, the presence of mountain bluebird (Sialia currucoides) and tree swallow (Tachycineta bicolour) nests was positively related to the density of cavities supplied by northern flickers (Colaptes auratus), which provided the most abundant cavities (1.61 cavities/ha). Flickers in aspen groves provided numerous nesting cavities to bluebirds (66%) and swallows (46%), despite previous research showing that flicker cavities are avoided by swallows. In continuous mixed forests, however, the presence of nesting swallows was mainly related to cavity density of red-naped sapsuckers (Sphyrapicus nuchalis), which provided the most abundant cavities (0.52 cavities/ha), and to cavity density of hairy woodpeckers (Picoides villosus), which provided few (0.14 cavities/ha) but high-quality cavities. Overall, sapsuckers and hairy woodpeckers provided 86% of nesting cavities to swallows in continuous forests. In contrast, the presence of nesting bluebirds in continuous forests was associated with the density of cavities supplied by all the ecosystem engineers. These results suggest that (i) habitat type may mediate the associations between ecosystem engineers and resource users, and (ii) different ecosystem engineers may be interchangeable for resource users depending on the quantity and quality of resources that each engineer supplies in each habitat type. We, therefore, urge the incorporation of the variation in the quantity and quality of resources provided by ecosystem engineers across habitats into models that assess community dynamics to improve our understanding of the importance of ecosystem engineers in shaping ecological communities.

Geosphere-biosphere interactions in European Protected Areas: a view from the H2020 ECOPOTENTIAL Project

NASA Astrophysics Data System (ADS)

Provenzale, Antonello; Beierkuhnlein, Carl; Karnieli, Arnon; Marangi, Carmela; Giamberini, Mariasilvia; Imperio, Simona

2017-04-01

The large H2020 project ECOPOTENTIAL (2015-2019, 47 partners, contributing to GEO and GEOSS - http://www.ecopotential-project.eu/) is devoted to making best use of remote sensing and in situ data to improve future ecosystem benefits, adopting the view of ecosystems as one physical system with their environment, focusing on geosphere-biosphere interactions, Earth Critical Zone dynamics, Macrosystem Ecology and cross-scale interactions, the effect of extreme events and using Essential (Climate, Biodiversity and Ocean) Variables as descriptors of change. In ECOPOTENTIAL, remote sensing and in situ data are collected, processed and used for a better understanding of the ecosystem dynamics, analysing and modelling the effects of global changes on ecosystem functions and services, over an array of different ecosystem types, including mountain, marine, coastal, arid and semi-arid ecosystems. The project focuses on a network of Protected Areas of international relevance, that is representative of the range of environmental and biogeographical conditions characterizing Europe. Some of the activities of the project are devoted to detect and quantify the changes taking place in the Protected Areas, through the analysis of remote sensing observations, in-situ data and gridded climatic datasets. Likewise, the project aims at providing estimates of the future ecosystem conditions in different climate and environmental change scenarios. In all such endeavours, one is faced with cross-scale issues: downscaling of climate information to drive ecosystem response, and upscaling of local ecosystem changes to larger scales. So far, the analysis has been conducted mainly by using traditional methods, but there is wide room for improvement by using more refined approaches. In particular, a crucial question is how to upscale the information gained at single-site scale to larger, regional or continental scale, an issue that could benefit from using, for example, complex network analysis.

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

USGS Publications Warehouse

Rafique, Rashad; Fienen, Michael N.; Parkin, Timothy B.; Anex, Robert P.

2013-01-01

DayCent is a biogeochemical model of intermediate complexity widely used to simulate greenhouse gases (GHG), soil organic carbon and nutrients in crop, grassland, forest and savannah ecosystems. Although this model has been applied to a wide range of ecosystems, it is still typically parameterized through a traditional “trial and error” approach and has not been calibrated using statistical inverse modelling (i.e. algorithmic parameter estimation). The aim of this study is to establish and demonstrate a procedure for calibration of DayCent to improve estimation of GHG emissions. We coupled DayCent with the parameter estimation (PEST) software for inverse modelling. The PEST software can be used for calibration through regularized inversion as well as model sensitivity and uncertainty analysis. The DayCent model was analysed and calibrated using N2O flux data collected over 2 years at the Iowa State University Agronomy and Agricultural Engineering Research Farms, Boone, IA. Crop year 2003 data were used for model calibration and 2004 data were used for validation. The optimization of DayCent model parameters using PEST significantly reduced model residuals relative to the default DayCent parameter values. Parameter estimation improved the model performance by reducing the sum of weighted squared residual difference between measured and modelled outputs by up to 67 %. For the calibration period, simulation with the default model parameter values underestimated mean daily N2O flux by 98 %. After parameter estimation, the model underestimated the mean daily fluxes by 35 %. During the validation period, the calibrated model reduced sum of weighted squared residuals by 20 % relative to the default simulation. Sensitivity analysis performed provides important insights into the model structure providing guidance for model improvement.

Modeling the potential of the Northern China forest shelterbelt in improving hydroclimate conditions

Treesearch

Yongqiang Liu; John Stanturf; Houquan Lu

2008-01-01

The forest shelterbelt (afforestation) project in northern China is the most significant ecosystem project initiated in China during the past three decades. It aims to improve and conserve the ecological environment in the project areas. The tree belt stands along the southern edge of the sandy lands, nearly paralleling to the Great Wall. This study used a regional...

[Ecosystem services supply and consumption and their relationships with human well-being].

PubMed

Wang, Da-Shang; Zheng, Hua; Ouyang, Zhi-Yun

2013-06-01

Sustainable ecosystem services supply is the basis of regional sustainable development, and human beings can satisfy and improve their well-being through ecosystem services consumption. To understand the relationships between ecosystem services supply and consumption and human well-being is of vital importance for coordinating the relationships between the conservation of ecosystem services and the improvement of human well-being. This paper summarized the diversity, complexity, and regionality of ecosystem services supply, the diversity and indispensability of ecosystem services consumption, and the multi-dimension, regionality, and various evaluation indices of human well-being, analyzed the uncertainty and multi-scale correlations between ecosystem services supply and consumption, and elaborated the feedback and asynchronous relationships between ecosystem services and human well-being. Some further research directions for the relationships between ecosystem services supply and consumption and human well-being were recommended.

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.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

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...

"Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidrectional Ammonia Flux in CMAQ"

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

CAN A MODEL TRANSFERABILITY FRAMEWORK IMPROVE ECOSYSTEM SERVICE ESTIMATES? A CASE STUDY OF SOIL FOREST CARBON SEQUESTRATION IN TILLAMOOK BAY, OR, USA

EPA Science Inventory

Budget constraints and policies that limit primary data collection have fueled a practice of transferring estimates (or models to generate estimates) of ecological endpoints from sites where primary data exists to sites where little to no primary data were collected. Whereas bene...

Advances in Linked Air Quality, Farm Management and Biogeochemistry Models to Address Bidirectional Ammonia Flux in CMAQ

EPA Science Inventory

Recent increases in anthropogenic inputs of nitrogen to air, land and water media pose a growing threat to human health and ecosystems. Modeling of air-surface N flux is one area in need of improvement. Implementation of a linked air quality and cropland management system is de...

Evaluation on island ecological vulnerability and its spatial heterogeneity.

PubMed

Chi, Yuan; Shi, Honghua; Wang, Yuanyuan; Guo, Zhen; Wang, Enkang

2017-12-15

The evaluation on island ecological vulnerability (IEV) can help reveal the comprehensive characteristics of the island ecosystem and provide reference for controlling human activities on islands. An IEV evaluation model which reflects the land-sea dual features, natural and anthropogenic attributes, and spatial heterogeneity of the island ecosystem was established, and the southern islands of Miaodao Archipelago in North China were taken as the study area. The IEV, its spatial heterogeneity, and its sensitivities to the evaluation elements were analyzed. Results indicated that the IEV was in status of mild vulnerability in the archipelago scale, and population pressure, ecosystem productivity, environmental quality, landscape pattern, and economic development were the sensitive elements. The IEV showed significant spatial heterogeneities both in land and surrounding waters sub-ecosystems. Construction scale control, optimization of development allocation, improvement of exploitation methods, and reasonable ecological construction are important measures to control the IEV. Copyright © 2017 Elsevier Ltd. All rights reserved.

Assessing the effects of fire disturbances on ecosystems: A scientific agenda for research and management

USGS Publications Warehouse

Schmoldt, D.L.; Peterson, D.L.; Keane, R.E.; Lenihan, J.M.; McKenzie, D.; Weise, D.R.; Sandberg, D.V.

1999-01-01

A team of fire scientists and resource managers convened 17-19 April 1996 in Seattle, Washington, to assess the effects of fire disturbance on ecosystems. Objectives of this workshop were to develop scientific recommendations for future fire research and management activities. These recommendations included a series of numerically ranked scientific and managerial questions and responses focusing on (1) links among fire effects, fuels, and climate; (2) fire as a large-scale disturbance; (3) fire-effects modeling structures; and (4) managerial concerns, applications, and decision support. At the present time, understanding of fire effects and the ability to extrapolate fire-effects knowledge to large spatial scales are limited, because most data have been collected at small spatial scales for specific applications. Although we clearly need more large-scale fire-effects data, it will be more expedient to concentrate efforts on improving and linking existing models that simulate fire effects in a georeferenced format while integrating empirical data as they become available. A significant component of this effort should be improved communication between modelers and managers to develop modeling tools to use in a planning context. Another component of this modeling effort should improve our ability to predict the interactions of fire and potential climatic change at very large spatial scales. The priority issues and approaches described here provide a template for fire science and fire management programs in the next decade and beyond.

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

NASA Astrophysics Data System (ADS)

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

2014-08-01

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

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

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

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

2014-08-18

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

Synthetic microbial ecosystems for biotechnology.

PubMed

Pandhal, Jagroop; Noirel, Josselin

2014-06-01

Most highly controlled and specific applications of microorganisms in biotechnology involve pure cultures. Maintaining single strain cultures is important for industry as contaminants can reduce productivity and lead to longer "down-times" during sterilisation. However, microbes working together provide distinct advantages over pure cultures. They can undertake more metabolically complex tasks, improve efficiency and even expand applications to open systems. By combining rapidly advancing technologies with ecological theory, the use of microbial ecosystems in biotechnology will inevitably increase. This review provides insight into the use of synthetic microbial communities in biotechnology by applying the engineering paradigm of measure, model, manipulate and manufacture, and illustrate the emerging wider potential of the synthetic ecology field. Systems to improve biofuel production using microalgae are also discussed.

Alternative states of a semiarid grassland ecosystem: implications for ecosystem services

USGS Publications Warehouse

Miller, Mark E.; Belote, R. Travis; Bowker, Matthew A.; Garman, Steven L.

2011-01-01

Ecosystems can shift between alternative states characterized by persistent differences in structure, function, and capacity to provide ecosystem services valued by society. We examined empirical evidence for alternative states in a semiarid grassland ecosystem where topographic complexity and contrasting management regimes have led to spatial variations in levels of livestock grazing. Using an inventory data set, we found that plots (n = 72) cluster into three groups corresponding to generalized alternative states identified in an a priori conceptual model. One cluster (biocrust) is notable for high coverage of a biological soil crust functional group in addition to vascular plants. Another (grass-bare) lacks biological crust but retains perennial grasses at levels similar to the biocrust cluster. A third (annualized-bare) is dominated by invasive annual plants. Occurrence of grass-bare and annualized-bare conditions in areas where livestock have been excluded for over 30 years demonstrates the persistence of these states. Significant differences among all three clusters were found for percent bare ground, percent total live cover, and functional group richness. Using data for vegetation structure and soil erodibility, we also found large among-cluster differences in average levels of dust emissions predicted by a wind-erosion model. Predicted emissions were highest for the annualized-bare cluster and lowest for the biocrust cluster, which was characterized by zero or minimal emissions even under conditions of extreme wind. Results illustrate potential trade-offs among ecosystem services including livestock production, soil retention, carbon storage, and biodiversity conservation. Improved understanding of these trade-offs may assist ecosystem managers when evaluating alternative management strategies.

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.

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

NASA Astrophysics Data System (ADS)

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

2017-04-01

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

Open access and preservation of data on the coupled geosphere-biosphere system: the case of the H2020 Project ECOPOTENTIAL

NASA Astrophysics Data System (ADS)

Provenzale, Antonello; Nativi, Stefano

2016-04-01

The H2020 ECOPOTENTIAL Project addresses the entire chain of ecosystem-related services, by focusing on the interaction between the biotic and abiotic components of ecosystems (geosphere-biosphere interactions), developing ecosystem data services with special emphasis on Copernicus services, implementing model output services to distribute the results of the modelling activities, and estimating current and future ecosystem services and benefits combining ecosystem functions (supply) with beneficiaries needs (demand). In ECOPOTENTIAL all data, model results and acquired knowledge will be made available on common and open platforms, coherent with the Global Earth Observation System of Systems (GEOSS) data sharing principles and fully interoperable with the GEOSS Common Infrastructure (GCI). ECOPOTENTIAL will be conducted in the context of the implementation of the Copernicus EO Component and in synergy with the ESA Climate Change Initiative. The project activities will contribute to Copernicus and non-Copernicus contexts for ecosystems, and will create an Ecosystem Data Service for Copernicus (ECOPERNICUS), a new open-access, smart and user-friendly geospatial data/products retrieval portal and web coverage service using a dedicated online server. ECOPOTENTIAL will make data, scientific results, models and information accessible and available through a cloud-based open platform implementing virtual laboratories. The platform will be a major contribution to the GEOSS Common Infrastructure, reinforcing the GEOSS Data-CORE. By the end of the project, new prototype products and ecosystem services, based on improved access (notably via GEOSS) and long-term storage of ecosystem EO data and information in existing PAs, will be realized. In this contribution, we discuss the approach followed in the project for Open Data access and use. ECOPOTENTIAL introduced a set of architecture and interoperability principles to facilitate data (and the associated software) discovery, access, (re-)use, and preservation. According to these principles, ECOPOTENTIAL worked out a Data Management Plan that describes how the different data types (generated and/or collected by the project) are going to be managed in the project; in particular: (1) What standards will be used for these data discoverability, accessibility and (re-)use; (2) How these data will be exploited and/or shared/made accessible for verification and reuse; if data cannot be made available, the reasons will be fully explained; and (3) How these data will be curated and preserved, even after the project duration.

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.

Improvements in ecosystem services from investments in natural capital.

PubMed

Ouyang, Zhiyun; Zheng, Hua; Xiao, Yi; Polasky, Stephen; Liu, Jianguo; Xu, Weihua; Wang, Qiao; Zhang, Lu; Xiao, Yang; Rao, Enming; Jiang, Ling; Lu, Fei; Wang, Xiaoke; Yang, Guangbin; Gong, Shihan; Wu, Bingfang; Zeng, Yuan; Yang, Wu; Daily, Gretchen C

2016-06-17

In response to ecosystem degradation from rapid economic development, China began investing heavily in protecting and restoring natural capital starting in 2000. We report on China's first national ecosystem assessment (2000-2010), designed to quantify and help manage change in ecosystem services, including food production, carbon sequestration, soil retention, sandstorm prevention, water retention, flood mitigation, and provision of habitat for biodiversity. Overall, ecosystem services improved from 2000 to 2010, apart from habitat provision. China's national conservation policies contributed significantly to the increases in those ecosystem services. Copyright © 2016, American Association for the Advancement of Science.

The centrality of meta-programming in the ES-DOC eco-system

NASA Astrophysics Data System (ADS)

Greenslade, Mark

2017-04-01

The Earth System Documentation (ES-DOC) project is an international effort aiming to deliver a robust earth system model inter-comparison project documentation infrastructure. Such infrastructure both simplifies & standardizes the process of documenting (in detail) projects, experiments, models, forcings & simulations. In support of CMIP6, ES-DOC has upgraded its eco-system of tools, web-services & web-sites. The upgrade consolidates the existing infrastructure (built for CMIP5) and extends it with the introduction of new capabilities. The strategic focus of the upgrade is improvements in the documentation experience and broadening the range of scientific use-cases that the archived documentation may help deliver. Whether it is highlighting dataset errors, exploring experimental protocols, comparing forcings across ensemble runs, understanding MIP objectives, reviewing citations, exploring component properties of configured models, visualising inter-model relationships, scientists involved in CMIP6 will find the ES-DOC infrastructure helpful. This presentation underlines the centrality of meta-programming within the ES-DOC eco-system. We will demonstrate how agility is greatly enhanced by taking a meta-programming approach to representing data models and controlled vocabularies. Such an approach nicely decouples representations from encodings. Meta-models will be presented along with the associated tooling chain that forward engineers artefacts as diverse as: class hierarchies, IPython notebooks, mindmaps, configuration files, OWL & SKOS documents, spreadsheets …etc.

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.

Resilience of the Eastern Chukchi Sea Food Web to Mortality Based Perturbations and Identification of Ecologically Important Species

NASA Astrophysics Data System (ADS)

Whitehouse, G. A.; Aydin, K.

2016-02-01

Evidence of climate impacts on Arctic marine ecosystems is accumulating and Arctic marine ecosystems face additional pressures that may accompany increasing human activities due to improved access following reductions in sea ice cover. Thus, there is growing demand for information on how Arctic ecosystems may respond to potential disturbance. We explore the response of the eastern Chukchi Sea food web to mortality based perturbations using the dynamic food web modeling framework, Ecopath with Ecosim. We generated thousands of ecosystems by drawing random sets of model parameters from informative prior distributions and only retained those ecosystems that resulted in plausible, numerically stable configurations (no extinctions or population growth without limit). To perturb the systems, we increased mortality rates for selected functional groups then ran the retained models forward 50 years to examine how the biomass of other functional groups responded, and evaluated the resilience of the food web as the time for all functional groups to return to within 10 percent of their starting biomass. Ecologically important species were identified as those species (or functional groups of species) for whom changes in mortality had the greatest effect on the remainder of the food web. We also report on how a selection of ecosystem scale properties were affected by selected perturbations, including mean biomass longevity, the distribution of biomass across trophic levels, and a selection of dimensionless biomass ratios. These perturbations simulate a range of potential impacts that mortality events may have on the food web of the eastern Chukchi Sea, and indicate the directional response of other species and functional groups to these simulated events. This information will be of value to decision makers and resource managers developing guidelines for commercial and industrial development in the eastern Chukchi Sea.

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

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

Laufkotter, Charlotte; Vogt, Meike; Gruber, Nicolas

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

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

DOE PAGES

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

2016-07-14

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

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.

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

USGS Publications Warehouse

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

2003-01-01

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

Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J. F.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-12-01

This study describes how management of grasslands is included in the Organizing Carbon and Hydrology in Dynamic Ecosystems (ORCHIDEE) process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (grassland management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites, equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can realistically capture the cut-induced seasonal variation in biometric variables (LAI: leaf area index; AGB: aboveground biomass) and in CO2 fluxes (GPP: gross primary productivity; TER: total ecosystem respiration; and NEE: net ecosystem exchange). However, improvements at grazing sites are only marginal in ORCHIDEE-GM due to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. For annual CO2 fluxes, the NEE bias and RMSE (root mean square error) in ORCHIDEE-GM are reduced by 53% and 20%, respectively, compared to ORCHIDEE. ORCHIDEE-GM is capable of modeling the net carbon balance (NBP) of managed temperate grasslands (37 ± 30 gC m-2 yr-1 (P < 0.01) over the 11 sites) because the management module contains provisions to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Assimilation of ocean colour to improve the simulation and understanding of the North West European shelf-sea ecosystem

NASA Astrophysics Data System (ADS)

Ciavatta, Stefano; Brewin, Robert; Skakala, Jozef; Sursham, David; Ford, David

2017-04-01

Shelf-seas and coastal zones provide essential goods and services to humankind, such as fisheries, aquaculture, tourism and climate regulation. The understanding and management of these regions can be enhanced by merging ocean-colour observations and marine ecosystem simulations through data assimilation, which provides (sub)optimal estimates of key biogeochemical variables. Here we present a range of applications of ocean-colour data assimilation in the North West European shelf-sea. A reanalysis application illustrates that assimilation of error-characterized chlorophyll concentrations could provide a map of the shelf sea vulnerability to oxygen deficiency, as well as estimates of the shelf sea uptake of atmospheric carbon dioxide (CO2) in the last decade. The interannual variability of CO2 uptake and its uncertainty were related significantly to interannual fluctuations of the simulated primary production. However, the reanalysis also indicates that assimilation of total chlorophyll did not improve significantly the simulation of some other variables, e.g. nutrients. We show that the assimilation of alternative products derived from ocean colour (i.e. spectral diffuse attenuation coefficient and phytoplankton size classes) can overcome this limitation. In fact, these products can constrain a larger number of model variables, which define either the underwater light field or the structure of the lower trophic levels. Therefore, the assimilation of such ocean-colour products into marine ecosystem models is an advantageous novel approach to improve the understanding and simulation of shelf-sea environments.

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

DOE PAGES

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer; ...

2017-02-28

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology

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

Iversen, Colleen M.; McCormack, M. Luke; Powell, A. Shafer

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. And while fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of rootmore » traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. There has been a continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time.« less

Assessment of Coastal Ecosystem Services for Conservation Strategies in South Korea.

PubMed

Chung, Min Gon; Kang, Hojeong; Choi, Sung-Uk

2015-01-01

Despite the fact that scientific and political consideration for ecosystem services has dramatically increased over the past decade, few studies have focused on marine and coastal ecosystem services for conservation strategies. We used an ecosystem services approach to assess spatial distributions of habitat risks and four ecosystem services (coastal protection, carbon storage, recreation, and aesthetic quality), and explored the tradeoffs among them in coastal areas of South Korea. Additionally, we analyzed how the social and ecological characteristics in coastal areas interact with conservation and development policies by using this approach. We found strong negative associations between the habitat risks and ecosystem services (aquaculture, carbon storage, recreation, and aesthetic quality) across the coastal counties. Our results showed that the intensity of the habitat risks and the provision of ecosystem services were significantly different between reclamation-dominated and conservation-dominated counties, except for coastal vulnerability. A generalized linear model suggested that reclamation projects were dependent on economic efficiency, whereas demographic pressures and habitat conditions influenced the designation of protected areas at a county level. The ecosystem services approach provided guidelines to achieve both sustainable development and environment conservation. By using the approach, we can select the priority areas for developments while we can minimize the degradation of biodiversity and ecosystem services. As cultural ecosystem services are evenly distributed throughout coastal areas of South Korea, decision makers may employ them to improve the conditions of coastal wetlands outside of protected areas.

Assessment of Coastal Ecosystem Services for Conservation Strategies in South Korea

PubMed Central

Chung, Min Gon; Kang, Hojeong; Choi, Sung-Uk

2015-01-01

Despite the fact that scientific and political consideration for ecosystem services has dramatically increased over the past decade, few studies have focused on marine and coastal ecosystem services for conservation strategies. We used an ecosystem services approach to assess spatial distributions of habitat risks and four ecosystem services (coastal protection, carbon storage, recreation, and aesthetic quality), and explored the tradeoffs among them in coastal areas of South Korea. Additionally, we analyzed how the social and ecological characteristics in coastal areas interact with conservation and development policies by using this approach. We found strong negative associations between the habitat risks and ecosystem services (aquaculture, carbon storage, recreation, and aesthetic quality) across the coastal counties. Our results showed that the intensity of the habitat risks and the provision of ecosystem services were significantly different between reclamation-dominated and conservation-dominated counties, except for coastal vulnerability. A generalized linear model suggested that reclamation projects were dependent on economic efficiency, whereas demographic pressures and habitat conditions influenced the designation of protected areas at a county level. The ecosystem services approach provided guidelines to achieve both sustainable development and environment conservation. By using the approach, we can select the priority areas for developments while we can minimize the degradation of biodiversity and ecosystem services. As cultural ecosystem services are evenly distributed throughout coastal areas of South Korea, decision makers may employ them to improve the conditions of coastal wetlands outside of protected areas. PMID:26221950

Evaluating simulated functional trait patterns and quantifying modelled trait diversity effects on simulated ecosystem fluxes

NASA Astrophysics Data System (ADS)

Pavlick, R.; Schimel, D.

2014-12-01

Dynamic Global Vegetation Models (DGVMs) typically employ only a small set of Plant Functional Types (PFTs) to represent the vast diversity of observed vegetation forms and functioning. There is growing evidence, however, that this abstraction may not adequately represent the observed variation in plant functional traits, which is thought to play an important role for many ecosystem functions and for ecosystem resilience to environmental change. The geographic distribution of PFTs in these models is also often based on empirical relationships between present-day climate and vegetation patterns. Projections of future climate change, however, point toward the possibility of novel regional climates, which could lead to no-analog vegetation compositions incompatible with the PFT paradigm. Here, we present results from the Jena Diversity-DGVM (JeDi-DGVM), a novel traits-based vegetation model, which simulates a large number of hypothetical plant growth strategies constrained by functional tradeoffs, thereby allowing for a more flexible temporal and spatial representation of the terrestrial biosphere. First, we compare simulated present-day geographical patterns of functional traits with empirical trait observations (in-situ and from airborne imaging spectroscopy). The observed trait patterns are then used to improve the tradeoff parameterizations of JeDi-DGVM. Finally, focusing primarily on the simulated leaf traits, we run the model with various amounts of trait diversity. We quantify the effects of these modeled biodiversity manipulations on simulated ecosystem fluxes and stocks for both present-day conditions and transient climate change scenarios. The simulation results reveal that the coarse treatment of plant functional traits by current PFT-based vegetation models may contribute substantial uncertainty regarding carbon-climate feedbacks. Further development of trait-based models and further investment in global in-situ and spectroscopic plant trait observations are needed.

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

NASA Astrophysics Data System (ADS)

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

2014-07-01

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

Ecosystem evapotranspiration: Challenges in measurements, estimates, and modeling

USDA-ARS?s Scientific Manuscript database

Evapotranspiration (ET) processes at the leaf-to-landscape scales in multiple land uses have important controls and feedbacks for the local, regional and global climate and water resource systems. Innovative methods, tools, and technologies for improved understanding and quantification of ET and cro...

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.

Modeling the effect of photosynthetic vegetation properties on the NDVI--LAI relationship.

PubMed

Steltzer, Heidi; Welker, Jeffrey M

2006-11-01

Developing a relationship between the normalized difference vegetation index (NDVI) and the leaf area index (LAI) is essential to describe the pattern of spatial or temporal variation in LAI that controls carbon, water, and energy exchange in many ecosystem process models. Photosynthetic vegetation (PV) properties can affect the estimation of LAI, but no models integrate the effects of multiple species. We developed four alternative NDVI-LAI models, three of which integrate PV effects: no PV effects, leaf-level effects, canopy-level effects, and effects at both levels. The models were fit to data across the natural range of variation in NDVI for a widespread High Arctic ecosystem. The weight of evidence supported the canopy-level model (Akaike weight, wr = 0.98), which includes species-specific canopy coefficients that primarily scale fractional PV cover to LAI by accounting for the area of unexposed PV. Modeling the canopy-level effects improved prediction of LAI (R2 = 0.82) over the model with no PV effect (R2 = 0.71) across the natural range of variation in NDVI but did not affect the site-level estimate of LAI. Satellite-based methods to estimate species composition, a variable in the model, will need to be developed. We expect that including the effects of PV properties in NDVI-LAI models will improve prediction of LAI where species composition varies across space or changes over time.

Knowing requires data

USGS Publications Warehouse

Naranjo, Ramon C.

2017-01-01

Groundwater-flow models are often calibrated using a limited number of observations relative to the unknown inputs required for the model. This is especially true for models that simulate groundwater surface-water interactions. In this case, subsurface temperature sensors can be an efficient means for collecting long-term data that capture the transient nature of physical processes such as seepage losses. Continuous and spatially dense network of diverse observation data can be used to improve knowledge of important physical drivers, conceptualize and calibrate variably saturated groundwater flow models. An example is presented for which the results of such analysis were used to help guide irrigation districts and water management decisions on costly upgrades to conveyance systems to improve water usage, farm productivity and restoration efforts to improve downstream water quality and ecosystems.

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.

Seasonality of Overstory and Understory Fluxes in a Semi-Arid Oak Savanna: What can be Learned from Comparing Measured and Modeled Fluxes?

NASA Astrophysics Data System (ADS)

Raz-Yaseef, N.; Sonnentag, O.; Kobayashi, H.; Chen, J. M.; Verfaillie, J. G.; Ma, S.; Baldocchi, D. D.

2011-12-01

Semi-arid climates experience large seasonal and inter-annual variability in radiation and precipitation, creating natural conditions adequate to study how year-to-year changes affect atmosphere-biosphere fluxes. Especially, savanna ecosystems, that combine tree and below-canopy components, create a unique environment in which phenology dramatically changes between seasons. We used a 10-year flux database in order to define seasonal and interannual variability of climatic inputs and fluxes, and evaluate model capability to reproduce observed variability. This is based on the perception that model capability to construct the deviation, and not the average, is important in order to correctly predict ecosystem sensitivity to climate change. Our research site is a low density and low LAI (0.8) semi-arid savanna, located at Tonzi Ranch, Northern California. In this system, trees are active during the warm season (Mar - Oct), and grasses are active during the wet season (Dec - May). Measurements of carbon and water fluxes above and below the tree canopy using eddy covariance and supplementary measurements have been made since 2001. Fluxes were simulated using bio-meteorological process-oriented ecosystem models: BEPS and 3D-CAONAK. Models were partly capable of reproducing fluxes on daily scales (R2=0.66). We then compared model outputs for different ecosystem components and seasons, and found distinct seasons with high correlations while other seasons were purely represented. Comparison was much higher for ET than for GPP. The understory was better simulated than the overstory. CANOAK overestimated spring understory fluxes, probably due to the capability to directly calculated 3D radiative transfer. BEPS underestimated spring understory fluxes, following the pre-description of grass die-off. Both models underestimated peak spring overstory fluxes. During winter tree dormant, modeled fluxes were null, but occasional high fluxes of both ET and GPP were measured following precipitation events, likely produced by an adverse measurement effect. This analysis enabled to pinpoint specific areas where models break, and stress that model capability to reproduce fluxes vary among seasons and ecosystem components. The combined response was such, that comparison decreases when ecosystem fluxes were partitioned between overstory and understory fluxes. Model performance decreases with time scale; while performance was high for some seasons, models were less capable of reproducing the high variability in understory fluxes vs. the conservative overstory fluxes on annual scales. Discrepancies were not always a result of models' faults; comparison largely improved when measurements of overstory fluxes during precipitation events were excluded. Conclusions raised from this research enable to answer the critical question of the level and type of details needed in order to correctly predict ecosystem respond to environmental and climatic change.

Benefits of collaborative and comparative research on land use change and climate mitigation

NASA Astrophysics Data System (ADS)

Zhu, Zhiliang; Gong, Peng

2016-04-01

The world's two largest economies are also the latest greenhouse gas emitters. The United States is committed to reduce the net greenhouse gas emission by 28% below the 2005 level by 2025. Similarly China also announced significant climate mitigation steps at the Paris climate convention. These policy plans will require actions including reduction of GHG emissions as well as protection of carbon stored in biologic pools and increase of carbon sequestration by the natural ecosystems. Major drivers of ecosystem carbon sequestration and protection of existing carbon resources include land use, disturbances, and climate change. Recent studies indicate that vegetated ecosystems in the United States remain as a carbon sink but the sink is weakening due to increased disturbances (such as wildfire and harvesting) and aging of forests. Unique land use policies in China such as large-scale afforestation in the recent decades have reportedly led to significant increase in total forest area and aboveground biomass, although it is not clear to what degree the increase has translated to strengthened net uptake of atmospheric CO2 and the rate of sequestration by vegetated ecosystems. What lessons can we draw from different land management and land use practices in the U.S. and China that can benefit scientific advances and climate mitigation goals? Research conducted collaboratively by the U.S. Geological Survey and China Ministry of Science and Technology has led to improved techniques for tracking and modeling land use change and ecosystem disturbances and improved understanding of consequences of different land use change and management practices on ecosystem carbon sequestration capacities.

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).

Modeling Temporal and Spatial Flows of Ecosystem Services in Chittenden County, VT

NASA Astrophysics Data System (ADS)

Voigt, B. G.; Bagstad, K.; Johnson, G.; Villa, F.

2010-12-01

This paper documents the integration of ARIES (ARtificial Intelligence for Ecosystem Services) with the land use change model UrbanSim to explore the impacts of current and future land use patterns on flood protection and water provision services in Chittenden County, VT. ARIES, an open source modeling platform, is particularly well-suited for measuring, mapping, and modeling the temporal and spatial flows of ecosystem services across the landscape, linking the areas of provision (sources) with human beneficiaries (users) through a spatially explicit agent-based modeling approach. UrbanSim is an open source agent-based land use model designed to facilitate a wide-range of scenarios based on user-specified behavioral assumptions, zoning regulations, and demographic, economic, and infrastructure (e.g. transportation, water, sewer, etc.) parameters. Ecosystem services travel through time and space and are susceptible to disruption and destruction from both natural and anthropogenic perturbations. The conversion of forested or agricultural land to urbanizing uses is replete with a long history of hydrologic impairment, habitat fragmentation, and the degradation of sensitive landscapes. Development decisions are predicated on the presence of landscape characteristics that meet the needs of developers and satisfy the desires of consumers, with minimal consideration of access to or effect on the provision of ecosystem services. The County houses nearly 25% of the state’s population and several employment centers that draw labor from throughout the region. Additionally, the County is expected to maintain modest residential and employment growth over the next 30 years, and will continue to serve as the state’s population and employment center. Expected future growth is likely to adversely affect the remaining farm and forest land in the County in the absence of policies to support sustainable development. We demonstrate how ARIES can be used to quantify changes in ecosystem service provision based on the outcomes of alternative land use change model scenarios. Stakeholder workshops were hosted to develop scenarios relevant to planning for future growth in the County, including alternative zoning regulations, road network improvements, and a range of future population projections. The results of the land use change simulations were passed to ARIES to model flood protection and water provision services for each of the alternative scenarios. We present Bayesian models of the ecosystem services as individual source, sink, and use components coupled with models of temporal and spatial flows of services across the landscape. Specific beneficiaries include homeowners, farmers, and other business property owners. The location choice decisions of residential and non-residential agents under the alternative scenarios resulted in varying access to ecosystem services depending on development density, habitat fragmentation, and the degree of hydrological impairment, among other factors. Modeled outputs include maps depicting flow paths (linking sources to beneficiaries), changes in land use, hotspot locations that are critical to sustain the flow of services across the landscape, and the demand for and supply of the modeled services.

Evidence of Microbial Regulation of Biogeochemical Cycles from a Study on Methane Flux and Land Use Change

PubMed Central

Nazaries, Loïc; Pan, Yao; Bodrossy, Levente; Baggs, Elizabeth M.; Millard, Peter; Murrell, J. Colin

2013-01-01

Microbes play an essential role in ecosystem functions, including carrying out biogeochemical cycles, but are currently considered a black box in predictive models and all global biodiversity debates. This is due to (i) perceived temporal and spatial variations in microbial communities and (ii) lack of ecological theory explaining how microbes regulate ecosystem functions. Providing evidence of the microbial regulation of biogeochemical cycles is key for predicting ecosystem functions, including greenhouse gas fluxes, under current and future climate scenarios. Using functional measures, stable-isotope probing, and molecular methods, we show that microbial (community diversity and function) response to land use change is stable over time. We investigated the change in net methane flux and associated microbial communities due to afforestation of bog, grassland, and moorland. Afforestation resulted in the stable and consistent enhancement in sink of atmospheric methane at all sites. This change in function was linked to a niche-specific separation of microbial communities (methanotrophs). The results suggest that ecological theories developed for macroecology may explain the microbial regulation of the methane cycle. Our findings provide support for the explicit consideration of microbial data in ecosystem/climate models to improve predictions of biogeochemical cycles. PMID:23624469

Coupled ecosystem/supply chain modelling of fish products from sea to shelf: the Peruvian anchoveta case.

PubMed

Avadí, Angel; Fréon, Pierre; Tam, Jorge

2014-01-01

Sustainability assessment of food supply chains is relevant for global sustainable development. A framework is proposed for analysing fishfood (fish products for direct human consumption) supply chains with local or international scopes. It combines a material flow model (including an ecosystem dimension) of the supply chains, calculation of sustainability indicators (environmental, socio-economic, nutritional), and finally multi-criteria comparison of alternative supply chains (e.g. fates of landed fish) and future exploitation scenarios. The Peruvian anchoveta fishery is the starting point for various local and global supply chains, especially via reduction of anchoveta into fishmeal and oil, used worldwide as a key input in livestock and fish feeds. The Peruvian anchoveta supply chains are described, and the proposed methodology is used to model them. Three scenarios were explored: status quo of fish exploitation (Scenario 1), increase in anchoveta landings for food (Scenario 2), and radical decrease in total anchoveta landings to allow other fish stocks to prosper (Scenario 3). It was found that Scenario 2 provided the best balance of sustainability improvements among the three scenarios, but further refinement of the assessment is recommended. In the long term, the best opportunities for improving the environmental and socio-economic performance of Peruvian fisheries are related to sustainability-improving management and policy changes affecting the reduction industry. Our approach provides the tools and quantitative results to identify these best improvement opportunities.

Coupled Ecosystem/Supply Chain Modelling of Fish Products from Sea to Shelf: The Peruvian Anchoveta Case

PubMed Central

Avadí, Angel; Fréon, Pierre; Tam, Jorge

2014-01-01

Sustainability assessment of food supply chains is relevant for global sustainable development. A framework is proposed for analysing fishfood (fish products for direct human consumption) supply chains with local or international scopes. It combines a material flow model (including an ecosystem dimension) of the supply chains, calculation of sustainability indicators (environmental, socio-economic, nutritional), and finally multi-criteria comparison of alternative supply chains (e.g. fates of landed fish) and future exploitation scenarios. The Peruvian anchoveta fishery is the starting point for various local and global supply chains, especially via reduction of anchoveta into fishmeal and oil, used worldwide as a key input in livestock and fish feeds. The Peruvian anchoveta supply chains are described, and the proposed methodology is used to model them. Three scenarios were explored: status quo of fish exploitation (Scenario 1), increase in anchoveta landings for food (Scenario 2), and radical decrease in total anchoveta landings to allow other fish stocks to prosper (Scenario 3). It was found that Scenario 2 provided the best balance of sustainability improvements among the three scenarios, but further refinement of the assessment is recommended. In the long term, the best opportunities for improving the environmental and socio-economic performance of Peruvian fisheries are related to sustainability-improving management and policy changes affecting the reduction industry. Our approach provides the tools and quantitative results to identify these best improvement opportunities. PMID:25003196

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.

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

DOE PAGES

Drewniak, Beth; Gonzalez-Meler, Miquel

2017-07-27

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

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

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

Drewniak, Beth; Gonzalez-Meler, Miquel

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

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

USGS Publications Warehouse

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie A.; Reed, Sasha C.; Reich, Peter B.; Ryan, Michael G.; Wood, Tana E.; Yang, Xiaojuan

2017-01-01

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

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

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO 2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is tomore » compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO 2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.« less

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

NASA Astrophysics Data System (ADS)

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie; Reed, Sasha; Reich, Peter B.; Ryan, Michael G.; Wood, Tana E.; Yang, Xiaojuan

2017-10-01

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is to compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.

Reviews and syntheses: Field data to benchmark the carbon cycle models for tropical forests

DOE PAGES

Clark, Deborah A.; Asao, Shinichi; Fisher, Rosie; ...

2017-10-23

For more accurate projections of both the global carbon (C) cycle and the changing climate, a critical current need is to improve the representation of tropical forests in Earth system models. Tropical forests exchange more C, energy, and water with the atmosphere than any other class of land ecosystems. Further, tropical-forest C cycling is likely responding to the rapid global warming, intensifying water stress, and increasing atmospheric CO 2 levels. Projections of the future C balance of the tropics vary widely among global models. A current effort of the modeling community, the ILAMB (International Land Model Benchmarking) project, is tomore » compile robust observations that can be used to improve the accuracy and realism of the land models for all major biomes. Our goal with this paper is to identify field observations of tropical-forest ecosystem C stocks and fluxes, and of their long-term trends and climatic and CO 2 sensitivities, that can serve this effort. We propose criteria for reference-level field data from this biome and present a set of documented examples from old-growth lowland tropical forests. We offer these as a starting point towards the goal of a regularly updated consensus set of benchmark field observations of C cycling in tropical forests.« less

Ecosystem Services Modeling as a Tool for Defining Priority Areas for Conservation.

PubMed

Duarte, Gabriela Teixeira; Ribeiro, Milton Cezar; Paglia, Adriano Pereira

2016-01-01

Conservationists often have difficulty obtaining financial and social support for protected areas that do not demonstrate their benefits for society. Therefore, ecosystem services have gained importance in conservation science in the last decade, as these services provide further justification for appropriate management and conservation of natural systems. We used InVEST software and a set of GIS procedures to quantify, spatialize and evaluated the overlap between ecosystem services-carbon stock and sediment retention-and a biodiversity proxy-habitat quality. In addition, we proposed a method that serves as an initial approach of a priority areas selection process. The method considers the synergism between ecosystem services and biodiversity conservation. Our study region is the Iron Quadrangle, an important Brazilian mining province and a conservation priority area located in the interface of two biodiversity hotspots, the Cerrado and Atlantic Forest biomes. The resultant priority area for the maintenance of the highest values of ecosystem services and habitat quality was about 13% of the study area. Among those priority areas, 30% are already within established strictly protected areas, and 12% are in sustainable use protected areas. Following the transparent and highly replicable method we proposed in this study, conservation planners can better determine which areas fulfill multiple goals and can locate the trade-offs in the landscape. We also gave a step towards the improvement of the habitat quality model with a topography parameter. In areas of very rugged topography, we have to consider geomorfometric barriers for anthropogenic impacts and for species movement and we must think beyond the linear distances. Moreover, we used a model that considers the tree mortality caused by edge effects in the estimation of carbon stock. We found low spatial congruence among the modeled services, mostly because of the pattern of sediment retention distribution.

Ecosystem Services Modeling as a Tool for Defining Priority Areas for Conservation

PubMed Central

Duarte, Gabriela Teixeira; Ribeiro, Milton Cezar; Paglia, Adriano Pereira

2016-01-01

Conservationists often have difficulty obtaining financial and social support for protected areas that do not demonstrate their benefits for society. Therefore, ecosystem services have gained importance in conservation science in the last decade, as these services provide further justification for appropriate management and conservation of natural systems. We used InVEST software and a set of GIS procedures to quantify, spatialize and evaluated the overlap between ecosystem services—carbon stock and sediment retention—and a biodiversity proxy–habitat quality. In addition, we proposed a method that serves as an initial approach of a priority areas selection process. The method considers the synergism between ecosystem services and biodiversity conservation. Our study region is the Iron Quadrangle, an important Brazilian mining province and a conservation priority area located in the interface of two biodiversity hotspots, the Cerrado and Atlantic Forest biomes. The resultant priority area for the maintenance of the highest values of ecosystem services and habitat quality was about 13% of the study area. Among those priority areas, 30% are already within established strictly protected areas, and 12% are in sustainable use protected areas. Following the transparent and highly replicable method we proposed in this study, conservation planners can better determine which areas fulfill multiple goals and can locate the trade-offs in the landscape. We also gave a step towards the improvement of the habitat quality model with a topography parameter. In areas of very rugged topography, we have to consider geomorfometric barriers for anthropogenic impacts and for species movement and we must think beyond the linear distances. Moreover, we used a model that considers the tree mortality caused by edge effects in the estimation of carbon stock. We found low spatial congruence among the modeled services, mostly because of the pattern of sediment retention distribution. PMID:27145031

Using a Forest Health Index as an Outreach Tool for Improving Public Understanding of Ecosystem Dynamics and Research-Based Management

NASA Astrophysics Data System (ADS)

Osenga, E. C.; Cundiff, J.; Arnott, J. C.; Katzenberger, J.; Taylor, J. R.; Jack-Scott, E.

2015-12-01

An interactive tool called the Forest Health Index (FHI) has been developed for the Roaring Fork watershed of Colorado, with the purpose of improving public understanding of local forest management and ecosystem dynamics. The watershed contains large areas of White River National Forest, which plays a significant role in the local economy, particularly for recreation and tourism. Local interest in healthy forests is therefore strong, but public understanding of forest ecosystems is often simplified. This can pose challenges for land managers and researchers seeking a scientifically informed approach to forest restoration, management, and planning. Now in its second iteration, the FHI is a tool designed to help bridge that gap. The FHI uses a suite of indicators to create a numeric rating of forest functionality and change, based on the desired forest state in relation to four categories: Ecological Integrity, Public Health and Safety, Ecosystem Services, and Sustainable Use and Management. The rating is based on data derived from several sources including local weather stations, stream gauge data, SNOTEL sites, and National Forest Service archives. In addition to offering local outreach and education, this project offers broader insight into effective communication methods, as well as into the challenges of using quantitative analysis to rate ecosystem health. Goals of the FHI include its use in schools as a means of using local data and place-based learning to teach basic math and science concepts, improved public understanding of ecological complexity and need for ongoing forest management, and, in the future, its use as a model for outreach tools in other forested communities in the Intermountain West.

A community based approach to improving resilience of forests and water resources: A local and regional climate adaptation methodology

Treesearch

Toby Thaler; Gwen Griffith; Nancy Gilliam

2014-01-01

Forest-based ecosystem services are at risk from human-caused stressors, including climate change. Improving governance and management of forests to reduce impacts and increase community resilience to all stressors is the objective of forest-related climate change adaptation. The Model Forest Policy Program (MFPP) has applied one method designed to meet this objective...

FEGS at the inflection point: How linking Ecosystem Services to Human Benefit improves management of coastal ecosystems.

EPA Science Inventory

Final ecosystem goods and services (FEGS) are the connection between the ecosystem resources and human stakeholders that benefit from natural capital. The FEGS concept is an extension of the ecosystem services (ES) concept (e.g., Millennium Ecosystem Assessment) and results from...

Eddy Covariance Measurements of Methane Flux at a Tropical Peat Forest in Sarawak, Malaysian Borneo

NASA Astrophysics Data System (ADS)

Tang, Angela C. I.; Stoy, Paul C.; Hirata, Ryuichi; Musin, Kevin K.; Aeries, Edward B.; Wenceslaus, Joseph; Melling, Lulie

2018-05-01

Tropical biogenic sources are a likely cause of the recent increase in global atmospheric methane concentration. To improve our understanding of tropical methane sources, we used the eddy covariance technique to measure CH4 flux (FCH4) between a tropical peat forest ecosystem and the atmosphere in Malaysian Borneo over a 2-month period during the wet season. Mean daily FCH4 during the measurement period, on the order of 0.024 g C-CH4·m-2·day-1, was similar to eddy covariance FCH4 measurements from tropical rice agroecosystems and boreal fen ecosystems. A linear modeling analysis demonstrated that air temperature (Tair) was critical for modeling FCH4 before the water table breached the surface and that water table alone explained some 20% of observed FCH4 variability once standing water emerged. Future research should measure FCH4 on an annual basis from multiple tropical ecosystems to better constrain tropical biogenic methane sources.

Temporal variation of ecosystem scale methane emission from a boreal fen in relation to common model drivers

NASA Astrophysics Data System (ADS)

Rinne, J.; Tuittila, E. S.; Peltola, O.; Li, X.; Raivonen, M.; Alekseychik, P.; Haapanala, S.; Pihlatie, M.; Aurela, M.; Mammarella, I.; Vesala, T.

2017-12-01

Models for calculating methane emission from wetland ecosystems typically relate the methane emission to carbon dioxide assimilation. Other parameters that control emission in these models are e.g. peat temperature and water table position. Many of these relations are derived from spatial variation between chamber measurements by space-for-time approach. Continuous longer term ecosystem scale methane emission measurements by eddy covariance method provide us independent data to assess the validity of the relations derived by space-for-time approach.We have analyzed eleven-year methane flux data-set, measured at a boreal fen, together with data on environmental parameters and carbon dioxide exchange to assess the relations to typical model drivers. The data was obtained by the eddy covariance method at Siikaneva mire complex, Southern Finland, during 2005-2015. The methane flux showed seasonal cycles in methane emission, with strongest correlation with peat temperature at 35 cm depth. The temperature relation was exponential throughout the whole peat temperature range of 0-16°C. The methane emission normalized to remove temperature dependence showed a non-monotonous relation on water table and positive correlation with gross primary production (GPP). However, inclusion of these as explaining variables improved algorithm-measurement correlation only slightly, with r2=0.74 for exponential temperature dependent algorithm, r2=0.76 for temperature - water table algorithm, and r2=0.79 for temperature - GPP algorithm. The methane emission lagged behind net ecosystem exchange (NEE) and GPP by two to three weeks. Annual methane emission ranged from 8.3 to 14 gC m-2, and was 20 % of NEE and 2.8 % of GPP. The inter-annual variation of methane emission was of similar magnitude as that of GPP and ecosystem respiration (Reco), but much smaller than that of NEE. The interannual variability of June-September average methane emission correlated significantly with that of GPP indicating a close link between these two processes in boreal fen ecosystems.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform.

PubMed

Marshall-Colon, Amy; Long, Stephen P; Allen, Douglas K; Allen, Gabrielle; Beard, Daniel A; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A J; Cox, Donna J; Hart, John C; Hirst, Peter M; Kannan, Kavya; Katz, Daniel S; Lynch, Jonathan P; Millar, Andrew J; Panneerselvam, Balaji; Price, Nathan D; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J; Voit, Eberhard O; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop.

Crops In Silico: Generating Virtual Crops Using an Integrative and Multi-scale Modeling Platform

PubMed Central

Marshall-Colon, Amy; Long, Stephen P.; Allen, Douglas K.; Allen, Gabrielle; Beard, Daniel A.; Benes, Bedrich; von Caemmerer, Susanne; Christensen, A. J.; Cox, Donna J.; Hart, John C.; Hirst, Peter M.; Kannan, Kavya; Katz, Daniel S.; Lynch, Jonathan P.; Millar, Andrew J.; Panneerselvam, Balaji; Price, Nathan D.; Prusinkiewicz, Przemyslaw; Raila, David; Shekar, Rachel G.; Shrivastava, Stuti; Shukla, Diwakar; Srinivasan, Venkatraman; Stitt, Mark; Turk, Matthew J.; Voit, Eberhard O.; Wang, Yu; Yin, Xinyou; Zhu, Xin-Guang

2017-01-01

Multi-scale models can facilitate whole plant simulations by linking gene networks, protein synthesis, metabolic pathways, physiology, and growth. Whole plant models can be further integrated with ecosystem, weather, and climate models to predict how various interactions respond to environmental perturbations. These models have the potential to fill in missing mechanistic details and generate new hypotheses to prioritize directed engineering efforts. Outcomes will potentially accelerate improvement of crop yield, sustainability, and increase future food security. It is time for a paradigm shift in plant modeling, from largely isolated efforts to a connected community that takes advantage of advances in high performance computing and mechanistic understanding of plant processes. Tools for guiding future crop breeding and engineering, understanding the implications of discoveries at the molecular level for whole plant behavior, and improved prediction of plant and ecosystem responses to the environment are urgently needed. The purpose of this perspective is to introduce Crops in silico (cropsinsilico.org), an integrative and multi-scale modeling platform, as one solution that combines isolated modeling efforts toward the generation of virtual crops, which is open and accessible to the entire plant biology community. The major challenges involved both in the development and deployment of a shared, multi-scale modeling platform, which are summarized in this prospectus, were recently identified during the first Crops in silico Symposium and Workshop. PMID:28555150

Modeling for Policy Change: A Feedback Perspective on Improving the Effectiveness of Coastal and Marine Management

ERIC Educational Resources Information Center

Robadue, Donald D., Jr.

2012-01-01

Those advocating for effective management of the use of coastal areas and ecosystems have long aspired for an approach to governance that includes information systems with the capability to predict the end results of various courses of action, monitor the impacts of decisions and compare results with those predicted by computer models in order to…

Using global sensitivity analysis to understand higher order interactions in complex models: an application of GSA on the Revised Universal Soil Loss Equation (RUSLE) to quantify model sensitivity and implications for ecosystem services management in Costa Rica

NASA Astrophysics Data System (ADS)

Fremier, A. K.; Estrada Carmona, N.; Harper, E.; DeClerck, F.

2011-12-01

Appropriate application of complex models to estimate system behavior requires understanding the influence of model structure and parameter estimates on model output. To date, most researchers perform local sensitivity analyses, rather than global, because of computational time and quantity of data produced. Local sensitivity analyses are limited in quantifying the higher order interactions among parameters, which could lead to incomplete analysis of model behavior. To address this concern, we performed a GSA on a commonly applied equation for soil loss - the Revised Universal Soil Loss Equation. USLE is an empirical model built on plot-scale data from the USA and the Revised version (RUSLE) includes improved equations for wider conditions, with 25 parameters grouped into six factors to estimate long-term plot and watershed scale soil loss. Despite RUSLE's widespread application, a complete sensitivity analysis has yet to be performed. In this research, we applied a GSA to plot and watershed scale data from the US and Costa Rica to parameterize the RUSLE in an effort to understand the relative importance of model factors and parameters across wide environmental space. We analyzed the GSA results using Random Forest, a statistical approach to evaluate parameter importance accounting for the higher order interactions, and used Classification and Regression Trees to show the dominant trends in complex interactions. In all GSA calculations the management of cover crops (C factor) ranks the highest among factors (compared to rain-runoff erosivity, topography, support practices, and soil erodibility). This is counter to previous sensitivity analyses where the topographic factor was determined to be the most important. The GSA finding is consistent across multiple model runs, including data from the US, Costa Rica, and a synthetic dataset of the widest theoretical space. The three most important parameters were: Mass density of live and dead roots found in the upper inch of soil (C factor), slope angle (L and S factor), and percentage of land area covered by surface cover (C factor). Our findings give further support to the importance of vegetation as a vital ecosystem service provider - soil loss reduction. Concurrent, progress is already been made in Costa Rica, where dam managers are moving forward on a Payment for Ecosystem Services scheme to help keep private lands forested and to improve crop management through targeted investments. Use of complex watershed models, such as RUSLE can help managers quantify the effect of specific land use changes. Moreover, effective land management of vegetation has other important benefits, such as bundled ecosystem services (e.g. pollination, habitat connectivity, etc) and improvements of communities' livelihoods.

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.

Fitting rainfall interception models to forest ecosystems of Mexico

NASA Astrophysics Data System (ADS)

Návar, José

2017-05-01

Models that accurately predict forest interception are essential both for water balance studies and for assessing watershed responses to changes in land use and the long-term climate variability. This paper compares the performance of four rainfall interception models-the sparse Gash (1995), Rutter et al. (1975), Liu (1997) and two new models (NvMxa and NvMxb)-using data from four spatially extensive, structurally diverse forest ecosystems in Mexico. Ninety-eight case studies measuring interception in tropical dry (25), arid/semi-arid (29), temperate (26), and tropical montane cloud forests (18) were compiled and analyzed. Coefficients derived from raw data or published statistical relationships were used as model input to evaluate multi-storm forest interception at the case study scale. On average empirical data showed that, tropical montane cloud, temperate, arid/semi-arid and tropical dry forests intercepted 14%, 18%, 22% and 26% of total precipitation, respectively. The models performed well in predicting interception, with mean deviations between measured and modeled interception as a function of total precipitation (ME) generally <5.8% and Nash-Sutcliffe efficiency E estimators >0.66. Model fitting precision was dependent on the forest ecosystem. Arid/semi-arid forests exhibited the smallest, while tropical montane cloud forest displayed the largest ME deviations. Improved agreement between measured and modeled data requires modification of in-storm evaporation rate in the Liu; the canopy storage in the sparse Gash model; and the throughfall coefficient in the Rutter and the NvMx models. This research concludes on recommending the wide application of rainfall interception models with some caution as they provide mixed results. The extensive forest interception data source, the fitting and testing of four models, the introduction of a new model, and the availability of coefficient values for all four forest ecosystems are an important source of information and a benchmark for future investigations in this area of hydrology.

Plant community mediation of ecosystem responses to global change factors

NASA Astrophysics Data System (ADS)

Churchill, A. C.

2017-12-01

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

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.

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

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

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

2011-08-31

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

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

DOE Data Explorer

Kalukin, Andrew; Endo, Satashi

2016-08-30

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

An improved representation of geographically isolated wetlands in a watershed-scale hydrologic model

EPA Science Inventory

Geographically isolated wetlands (GIWs), defined as wetlands surrounded by uplands, provide an array of ecosystem goods and services. Within the United States, federal regulatory protections for GIWs are contingent, in part, on the quantification of their singular or aggregate ef...

A modelling framework for improving plant establishment during ecological restoration

USDA-ARS?s Scientific Manuscript database

Plants seeded during ecological restoration projects often perish en masse, and researchers are currently searching for traits promoting increased survival. In this study of a big sagebrush (Artemisia tridentata Nutt.) ecosystem, we found survivorship rankings of seeded grass species varied across 3...

Improving predictions of carbon fluxes in the tropics undre climatic changes using ED2

NASA Astrophysics Data System (ADS)

Feng, X.; Uriarte, M.

2016-12-01

Tropical forests play a critical role in the exchange of carbon between land and atmosphere, highlighting the urgency of understanding the effects of climate change on these ecosystems. The most optimistic predictions of climate models indicate that global mean temperatures will increase by up to 2 0C with some tropical regions experiencing extreme heat. Drought and heat-induced tree mortality will accelerate the release of carbon to the atmosphere creating a positive feedback that greatly exacerbates global warming. Thus, under a warmer and drier climate, tropical forests may become net sources, rather than sinks, of carbon. Earth system models have not reached a consensus on the magnitude and direction of climate change impacts on tropical forests, calling into question the reliability of their predictions. Thus, there is an immediate need to improve the representation of tropical forests in earth system models to make robust predictions. The goal of our study is to quantify the responses of tropical forests to climate variability and improve the predictive capacity of terrestrial ecosystem models. We have collected species-specific physiological and functional trait data from 144 tree species in a Puerto Rican rainforest to parameterize the Ecosystem Demography model (ED2). The large amount of data generated by this research will lead to better validation and lowering the uncertainty in future model predictions. To best represent the forest landscape in ED2, all the trees have been assigned to three plant functional types (PFTs): early, mid, and late successional species. Trait data for each PFT were synthesized in a Bayesian meta-analytical model and posterior distributions of traits were used to parameterize the ED2 model. Model predictions show that biomass production of late successional PFT (118.89 ton/ha) was consistently higher than mid (71.33 ton/ha) and early (13.21 ton/ha) PFTs. However, mid successional PFT had the highest contributions to NPP for the modeled period. Tropical forest biomass reduces by 30% under future drought scenario turning the tropics into carbon sources. Ensemble runs were conducted to construct error estimates around model forecasts, to compare modeled and observed aboveground biomass, and to identify which processes and tree species need further study.

Mapping Tamarix: New techniques for field measurements, spatial modeling and remote sensing

NASA Astrophysics Data System (ADS)

Evangelista, Paul H.

Native riparian ecosystems throughout the southwestern United States are being altered by the rapid invasion of Tamarix species, commonly known as tamarisk. The effects that tamarisk has on ecosystem processes have been poorly quantified largely due to inadequate survey methods. I tested new approaches for field measurements, spatial models and remote sensing to improve our ability measure and to map tamarisk occurrence, and provide new methods that will assist in management and control efforts. Examining allometric relationships between basal cover and height measurements collected in the field, I was able to produce several models to accurately estimate aboveground biomass. The best two models were explained 97% of the variance (R 2 = 0.97). Next, I tested five commonly used predictive spatial models to identify which methods performed best for tamarisk using different types of data collected in the field. Most spatial models performed well for tamarisk, with logistic regression performing best with an Area Under the receiver-operating characteristic Curve (AUC) of 0.89 and overall accuracy of 85%. The results of this study also suggested that models may not perform equally with different invasive species, and that results may be influenced by species traits and their interaction with environmental factors. Lastly, I tested several approaches to improve the ability to remotely sense tamarisk occurrence. Using Landsat7 ETM+ satellite scenes and derived vegetation indices for six different months of the growing season, I examined their ability to detect tamarisk individually (single-scene analyses) and collectively (time-series). My results showed that time-series analyses were best suited to distinguish tamarisk from other vegetation and landscape features (AUC = 0.96, overall accuracy = 90%). June, August and September were the best months to detect unique phenological attributes that are likely related to the species' extended growing season and green-up during peak growing months. These studies demonstrate that new techniques can further our understanding of tamarisk's impacts on ecosystem processes, predict potential distribution and new invasions, and improve our ability to detect occurrence using remote sensing techniques. Collectively, the results of my studies may increase our ability to map tamarisk distributions and better quantify its impacts over multiple spatial and temporal scales.

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

NASA Astrophysics Data System (ADS)

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

2017-09-01

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

Estimation of Global 1km-grid Terrestrial Carbon Exchange Part I: Developing Inputs and Modelling

NASA Astrophysics Data System (ADS)

Sasai, T.; Murakami, K.; Kato, S.; Matsunaga, T.; Saigusa, N.; Hiraki, K.

2015-12-01

Global terrestrial carbon cycle largely depends on a spatial pattern in land cover type, which is heterogeneously-distributed over regional and global scales. However, most studies, which aimed at the estimation of carbon exchanges between ecosystem and atmosphere, remained within several tens of kilometers grid spatial resolution, and the results have not been enough to understand the detailed pattern of carbon exchanges based on ecological community. Improving the sophistication of spatial resolution is obviously necessary to enhance the accuracy of carbon exchanges. Moreover, the improvement may contribute to global warming awareness, policy makers and other social activities. In this study, we show global terrestrial carbon exchanges (net ecosystem production, net primary production, and gross primary production) with 1km-grid resolution. As methodology for computing the exchanges, we 1) developed a global 1km-grid climate and satellite dataset based on the approach in Setoyama and Sasai (2013); 2) used the satellite-driven biosphere model (Biosphere model integrating Eco-physiological And Mechanistic approaches using Satellite data: BEAMS) (Sasai et al., 2005, 2007, 2011); 3) simulated the carbon exchanges by using the new dataset and BEAMS by the use of a supercomputer that includes 1280 CPU and 320 GPGPU cores (GOSAT RCF of NIES). As a result, we could develop a global uniform system for realistically estimating terrestrial carbon exchange, and evaluate net ecosystem production in each community level; leading to obtain highly detailed understanding of terrestrial carbon exchanges.

A geospatial framework for improving the vertical accuracy of elevation models in Florida's coastal Everglades

NASA Astrophysics Data System (ADS)

Cooper, H.; Zhang, C.; Sirianni, M.

2016-12-01

South Florida relies upon the health of the Everglades, the largest subtropical wetland in North America, as a vital source of water. Since the late 1800's, this imperiled ecosystem has been highly engineered to meet human needs of flood control and water use. The Comprehensive Everglades Restoration Plan (CERP) was initiated in 2000 to restore original water flows to the Everglades and improve overall ecosystem health, while also aiming to achieve balance with human water usage. Due to subtle changes in the Everglades terrain, better vertical accuracy elevation data are needed to model groundwater and surface water levels that are integral to monitoring the effects of restoration under impacts such as sea-level rise. The current best available elevation datasets for the coastal Everglades include High Accuracy Elevation Data (HAED) and Florida Department of Emergency Management (FDEM) Light Detection and Ranging (LiDAR). However, the horizontal resolution of the HAED data is too coarse ( 400 m) for fine scale mapping, and the LiDAR data does not contain an accuracy assessment for coastal Everglades' vegetation communities. The purpose of this study is to develop a framework for generating better vertical accuracy and horizontal resolution Digital Elevation Models in the Flamingo District of Everglades National Park. In the framework, field work is conducted to collect RTK GPS and total station elevation measurements for mangrove swamp, coastal prairies, and freshwater marsh, and the proposed accuracy assessment and elevation modeling methodology is integrated with a Geographical Information System (GIS). It is anticipated that this study will provide more accurate models of the soil substrate elevation that can be used by restoration planners to better predict the future state of the Everglades ecosystem.

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.

Landscape controls on dissolved organic carbon export from watersheds of the British Columbia outer-coast

NASA Astrophysics Data System (ADS)

Giesbrecht, I.; Tank, S. E.; Frazer, G. W.; Gonzalez Arriola, S.; Korver, M.; Floyd, B. C.; Oliver, A. A.; Lertzman, K. P.

2016-12-01

Global models suggest that the Pacific Coastal Temperate Rainforest of North America (PCTR) exports significant quantities of dissolved organic carbon (DOC) to the coastal ocean. This aquatic flux from land to sea has implications for marine ecosystems and regional carbon budgets. However, DOC concentrations and flux estimates vary substantially across watersheds and drivers of spatial variation are poorly described for this region. For an outer-coast area of the PCTR, with among the highest per unit area DOC yields in the world (Oliver et al. in prep.), we describe and model landscape controls on DOC exports to the coastal ocean. In 2015 we collected three rounds of synoptic samples on Calvert Island, observing a nine-fold variation in DOC concentration (3.8 - 34.3 mg/L) across 59 watersheds that range in size from 0.26 to 21.12 km2 and reach a maximum elevation of 1012 m. We use standard ecosystem maps (Province of BC), LiDAR and other remote sensing data to measure watershed attributes. We use freshwater cation concentrations to explore geochemical signals of bedrock and surficial deposits that may be poorly represented by available geospatial data. We examine the role of topography, climate, waterbodies, geology and the local ecosystem mosaic in controlling DOC concentration and flux. An improved model of spatial controls on freshwater DOC export from the outer-coast of the PCTR will inform regional carbon modeling efforts and enhance our understanding of ecosystem processes at the coastal margin.

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Applications of the BIOPHYS Algorithm for Physically-Based Retrieval of Biophysical, Structural and Forest Disturbance Information

NASA Technical Reports Server (NTRS)

Peddle, Derek R.; Huemmrich, K. Fred; Hall, Forrest G.; Masek, Jeffrey G.; Soenen, Scott A.; Jackson, Chris D.

2011-01-01

Canopy reflectance model inversion using look-up table approaches provides powerful and flexible options for deriving improved forest biophysical structural information (BSI) compared with traditional statistical empirical methods. The BIOPHYS algorithm is an improved, physically-based inversion approach for deriving BSI for independent use and validation and for monitoring, inventory and quantifying forest disturbance as well as input to ecosystem, climate and carbon models. Based on the multiple-forward mode (MFM) inversion approach, BIOPHYS results were summarized from different studies (Minnesota/NASA COVER; Virginia/LEDAPS; Saskatchewan/BOREAS), sensors (airborne MMR; Landsat; MODIS) and models (GeoSail; GOMS). Applications output included forest density, height, crown dimension, branch and green leaf area, canopy cover, disturbance estimates based on multi-temporal chronosequences, and structural change following recovery from forest fires over the last century. Good correspondences with validation field data were obtained. Integrated analyses of multiple solar and view angle imagery further improved retrievals compared with single pass data. Quantifying ecosystem dynamics such as the area and percent of forest disturbance, early regrowth and succession provide essential inputs to process-driven models of carbon flux. BIOPHYS is well suited for large-area, multi-temporal applications involving multiple image sets and mosaics for assessing vegetation disturbance and quantifying biophysical structural dynamics and change. It is also suitable for integration with forest inventory, monitoring, updating, and other programs.

Promoting the confluence of tropical cyclone research.

PubMed

Marler, Thomas E

2015-01-01

Contributions of biologists to tropical cyclone research may improve by integrating concepts from other disciplines. Employing accumulated cyclone energy into protocols may foster greater integration of ecology and meteorology research. Considering experienced ecosystems as antifragile instead of just resilient may improve cross-referencing among ecological and social scientists. Quantifying ecosystem capital as distinct from ecosystem services may improve integration of tropical cyclone ecology research into the expansive global climate change research community.

Incorporating grassland management in a global vegetation model: model description and evaluation at 11 eddy-covariance sites in Europe

NASA Astrophysics Data System (ADS)

Chang, J.; Viovy, N.; Vuichard, N.; Ciais, P.; Wang, T.; Cozic, A.; Lardy, R.; Graux, A.-I.; Klumpp, K.; Martin, R.; Soussana, J.-F.

2013-05-01

This study describes how management of grasslands is included in the ORCHIDEE process-based ecosystem model designed for large-scale applications, and how management affects modeled grassland-atmosphere CO2 fluxes. The new model, ORCHIDEE-GM (Grassland Management) is enabled with a management module inspired from a grassland model (PaSim, version 5.0), with two grassland management practices being considered, cutting and grazing, respectively. The evaluation of the results from ORCHIDEE compared with those of ORCHIDEE-GM at 11 European sites equipped with eddy covariance and biometric measurements, shows that ORCHIDEE-GM can capture realistically the cut-induced seasonal variation in biometric variables (LAI: Leaf Area Index; AGB: Aboveground Biomass) and in CO2 fluxes (GPP: Gross Primary Productivity; TER: Total Ecosystem Respiration; and NEE: Net Ecosystem Exchange). But improvements at grazing sites are only marginal in ORCHIDEE-GM, which relates to the difficulty in accounting for continuous grazing disturbance and its induced complex animal-vegetation interactions. Both NEE and GPP on monthly to annual timescales can be better simulated in ORCHIDEE-GM than in ORCHIDEE without management. ORCHIDEE-GM is capable to model the net carbon balance (NBP) of managed grasslands better than ORCHIDEE, because the management module allows to simulate the carbon fluxes of forage yield, herbage consumption, animal respiration and methane emissions.

Drought and resprouting plants

DOE PAGES

Zeppel, Melanie J. B.; Harrison, Sandy P.; Adams, Henry D.; ...

2014-12-17

Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21 st century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly thanmore » ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. Furthermore, the strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented.« less

Drought and resprouting plants.

PubMed

Zeppel, Melanie J B; Harrison, Sandy P; Adams, Henry D; Kelley, Douglas I; Li, Guangqi; Tissue, David T; Dawson, Todd E; Fensham, Rod; Medlyn, Belinda E; Palmer, Anthony; West, Adam G; McDowell, Nate G

2015-04-01

Many species have the ability to resprout vegetatively after a substantial loss of biomass induced by environmental stress, including drought. Many of the regions characterised by ecosystems where resprouting is common are projected to experience more frequent and intense drought during the 21st Century. However, in assessments of ecosystem response to drought disturbance there has been scant consideration of the resilience and post-drought recovery of resprouting species. Systematic differences in hydraulic and allocation traits suggest that resprouting species are more resilient to drought-stress than nonresprouting species. Evidence suggests that ecosystems dominated by resprouters recover from disturbance more quickly than ecosystems dominated by nonresprouters. The ability of resprouters to avoid mortality and withstand drought, coupled with their ability to recover rapidly, suggests that the impact of increased drought stress in ecosystems dominated by these species may be small. The strategy of resprouting needs to be modelled explicitly to improve estimates of future climate-change impacts on the carbon cycle, but this will require several important knowledge gaps to be filled before resprouting can be properly implemented. © 2014 The Authors. New Phytologist © 2014 New Phytologist Trust.

Urban ecosystem services: tree diversity and stability of tropospheric ozone removal.

PubMed

Manes, Fausto; Incerti, Guido; Salvatori, Elisabetta; Vitale, Marcello; Ricotta, Carlo; Costanza, Robert

2012-01-01

Urban forests provide important ecosystem services, such as urban air quality improvement by removing pollutants. While robust evidence exists that plant physiology, abundance, and distribution within cities are basic parameters affecting the magnitude and efficiency of air pollution removal, little is known about effects of plant diversity on the stability of this ecosystem service. Here, by means of a spatial analysis integrating system dynamic modeling and geostatistics, we assessed the effects of tree diversity on the removal of tropospheric ozone (O3) in Rome, Italy, in two years (2003 and 2004) that were very different for climatic conditions and ozone levels. Different tree functional groups showed complementary uptake patterns, related to tree physiology and phenology, maintaining a stable community function across different climatic conditions. Our results, although depending on the city-specific conditions of the studied area, suggest a higher function stability at increasing diversity levels in urban ecosystems. In Rome, such ecosystem services, based on published unitary costs of externalities and of mortality associated with O3, can be prudently valued to roughly US$2 and $3 million/year, respectively.

Assimilation of satellite color observations in a coupled ocean GCM-ecosystem model

NASA Technical Reports Server (NTRS)

Sarmiento, Jorge L.

1992-01-01

Monthly average coastal zone color scanner (CZCS) estimates of chlorophyll concentration were assimilated into an ocean global circulation model(GCM) containing a simple model of the pelagic ecosystem. The assimilation was performed in the simplest possible manner, to allow the assessment of whether there were major problems with the ecosystem model or with the assimilation procedure. The current ecosystem model performed well in some regions, but failed in others to assimilate chlorophyll estimates without disrupting important ecosystem properties. This experiment gave insight into those properties of the ecosystem model that must be changed to allow data assimilation to be generally successful, while raising other important issues about the assimilation procedure.

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

NASA Astrophysics Data System (ADS)

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

2014-12-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-12-01

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

Integrating Climate and Ocean Change Vulnerability into Conservation Planning

NASA Astrophysics Data System (ADS)

Mcleod, E.; Green, A.; Game, E.; Anthony, K.; Cinner, J.; Heron, S. F.; Kleypas, J. A.; Lovelock, C.; Pandolfi, J.; Pressey, B.; Salm, R.; Schill, S.; Woodroffe, C. D.

2013-05-01

Tropical coastal and marine ecosystems are particularly vulnerable to ocean warming, ocean acidification, and sea-level rise. Yet these projected climate and ocean change impacts are rarely considered in conservation planning due to the lack of guidance on how existing climate and ocean change models, tools, and data can be applied. We address this gap by describing how conservation planning can use available tools and data for assessing the vulnerability of tropical marine ecosystems to key climate threats. Additionally, we identify limitations of existing tools and provide recommendations for future research to improve integration of climate and ocean change information and conservation planning. Such information is critical for developing a conservation response that adequately protects these ecosystems and dependent coastal communities in the face of climate and ocean change.

Linking models and data on vegetation structure

NASA Astrophysics Data System (ADS)

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

2010-06-01

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

Coupling habitat suitability and ecosystem health with AEHRA to estimate E-flows under intensive human activities

NASA Astrophysics Data System (ADS)

Zhao, C. S.; Yang, S. T.; Zhang, H. T.; Liu, C. M.; Sun, Y.; Yang, Z. Y.; Zhang, Y.; Dong, B. E.; Lim, R. P.

2017-08-01

Sustaining adequate environmental flows (e-flows) is a key principle for maintaining river biodiversity and ecosystem health, and for supporting sustainable water resource management in basins under intensive human activities. But few methods could correctly relate river health to e-flows assessment at the catchment scale when they are applied to rivers highly impacted by human activities. An effective method is presented in this study to closely link river health to e-flows assessment for rivers at the catchment scale. Key fish species, as indicators of ecosystem health, were selected by using the foodweb model. A multi-species-based habitat suitability model (MHSI) was improved, and coupled with dominance of the key fish species as well as the Index of Biological Integrity (IBI) to enhance its accuracy in determining the fish-preferred key hydrologic habitat variables related to ecosystem health. Taking 5964 fish samples and concurrent hydrological habitat variables as the basis, the combination of key variables of flow-velocity and water-depth were determined and used to drive the Adapted Ecological Hydraulic Radius Approach (AEHRA) to study e-flows in a Chinese urban river impacted by intensive human activities. Results showed that upstream urbanization resulted in abnormal river-course geomorphology and consequently abnormal e-flows under intensive human activities. Selection of key species based on the foodweb and trophic levels of aquatic ecosystems can reflect a comprehensive requirement on e-flows of the whole aquatic ecosystem, which greatly increases its potential to be used as a guidance tool for rehabilitation of degraded ecosystems at large spatial scales. These findings have significant ramifications for catchment e-flows assessment under intensive human activities and for river ecohealth restoration in such rivers globally.

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.

Social Values for Ecosystem Services, version 3.0 (SolVES 3.0): documentation and user manual

USGS Publications Warehouse

Sherrouse, Ben C.; Semmens, Darius J.

2015-01-01

The geographic information system (GIS) tool, Social Values for Ecosystem Services (SolVES), was developed to incorporate quantified and spatially explicit measures of social values into ecosystem service assessments. SolVES 3.0 continues to extend the functionality of SolVES, which was designed to assess, map, and quantify the social values of ecosystem services. Social values—the perceived, nonmarket values the public ascribes to ecosystem services, particularly cultural services, such as aesthetics and recreation—can be evaluated for various stakeholder groups. These groups are distinguishable by their attitudes and preferences regarding public uses, such as motorized recreation and logging. As with previous versions, SolVES 3.0 derives a quantitative 10-point, social-values metric—the value index—from a combination of spatial and nonspatial responses to public value and preference surveys. The tool also calculates metrics characterizing the underlying environment, such as average distance to water and dominant landcover. SolVES 3.0 is integrated with Maxent maximum entropy modeling software to generate more complete social-value maps and offer robust statistical models describing the relationship between the value index and explanatory environmental variables. A model’s goodness of fit to a primary study area and its potential performance in transferring social values to similar areas using value-transfer methodology can be evaluated. SolVES 3.0 provides an improved public-domain tool for decision makers and researchers to evaluate the social values of ecosystem services and to facilitate discussions among diverse stakeholders regarding the tradeoffs among ecosystem services in a variety of physical and social contexts ranging from forest and rangeland to coastal and marine.

Transforming Ecosystems: When, Where, and How to Restore Contaminated Sites

PubMed Central

Rohr, Jason R; Farag, Aïda M; Cadotte, Marc W; Clements, William H; Smith, James R; Ulrich, Cheryl P; Woods, Richard

2016-01-01

Chemical contamination has impaired ecosystems, reducing biodiversity and the provisioning of functions and services. This has spurred a movement to restore contaminated ecosystems and develop and implement national and international regulations that require it. Nevertheless, ecological restoration remains a young and rapidly growing discipline and its intersection with toxicology is even more nascent and underdeveloped. Consequently, we provide guidance to scientists and practitioners on when, where, and how to restore contaminated ecosystems. Although restoration has many benefits, it also can be expensive, and in many cases systems can recover without human intervention. Hence, the first question we address is: “When should we restore contaminated ecosystems?” Second, we provide suggestions on what to restore—biodiversity, functions, services, all 3, or something else—and where to restore given expected changes to habitats driven by global climate change. Finally, we provide guidance on how to restore contaminated ecosystems. To do this, we analyze critical aspects of the literature dealing with the ecology of restoring contaminated ecosystems. Additionally, we review approaches for translating the science of restoration to on-the-ground actions, which includes discussions of market incentives and the finances of restoration, stakeholder outreach and governance models for ecosystem restoration, and working with contractors to implement restoration plans. By explicitly considering the mechanisms and strategies that maximize the success of the restoration of contaminated sites, we hope that our synthesis serves to increase and improve collaborations between restoration ecologists and ecotoxicologists and set a roadmap for the restoration of contaminated ecosystems. PMID:26033665

Transforming ecosystems: When, where, and how to restore contaminated sites

USGS Publications Warehouse

Rohr, Jason R.; Farag, Aïda M.; Cadotte, Marc W.; Clements, William H.; Smith, James R.; Ulrich, Cheryl P.; Woods, Richard

2016-01-01

Chemical contamination has impaired ecosystems, reducing biodiversity and the provisioning of functions and services. This has spurred a movement to restore contaminated ecosystems and develop and implement national and international regulations that require it. Nevertheless, ecological restoration remains a young and rapidly growing discipline and its intersection with toxicology is even more nascent and underdeveloped. Consequently, we provide guidance to scientists and practitioners on when, where, and how to restore contaminated ecosystems. Although restoration has many benefits, it also can be expensive, and in many cases systems can recover without human intervention. Hence, the first question we address is: “When should we restore contaminated ecosystems?” Second, we provide suggestions on what to restore—biodiversity, functions, services, all 3, or something else—and where to restore given expected changes to habitats driven by global climate change. Finally, we provide guidance on how to restore contaminated ecosystems. To do this, we analyze critical aspects of the literature dealing with the ecology of restoring contaminated ecosystems. Additionally, we review approaches for translating the science of restoration to on-the-ground actions, which includes discussions of market incentives and the finances of restoration, stakeholder outreach and governance models for ecosystem restoration, and working with contractors to implement restoration plans. By explicitly considering the mechanisms and strategies that maximize the success of the restoration of contaminated sites, we hope that our synthesis serves to increase and improve collaborations between restoration ecologists and ecotoxicologists and set a roadmap for the restoration of contaminated ecosystems.

A succession of theories: purging redundancy from disturbance theory.

PubMed

Pulsford, Stephanie A; Lindenmayer, David B; Driscoll, Don A

2016-02-01

The topics of succession and post-disturbance ecosystem recovery have a long and convoluted history. There is extensive redundancy within this body of theory, which has resulted in confusion, and the links among theories have not been adequately drawn. This review aims to distil the unique ideas from the array of theory related to ecosystem change in response to disturbance. This will help to reduce redundancy, and improve communication and understanding between researchers. We first outline the broad range of concepts that have developed over the past century to describe community change in response to disturbance. The body of work spans overlapping succession concepts presented by Clements in 1916, Egler in 1954, and Connell and Slatyer in 1977. Other theories describing community change include state and transition models, biological legacy theory, and the application of functional traits to predict responses to disturbance. Second, we identify areas of overlap of these theories, in addition to highlighting the conceptual and taxonomic limitations of each. In aligning each of these theories with one another, the limited scope and relative inflexibility of some theories becomes apparent, and redundancy becomes explicit. We identify a set of unique concepts to describe the range of mechanisms driving ecosystem responses to disturbance. We present a schematic model of our proposed synthesis which brings together the range of unique mechanisms that were identified in our review. The model describes five main mechanisms of transition away from a post-disturbance community: (i) pulse events with rapid state shifts; (ii) stochastic community drift; (iii) facilitation; (iv) competition; and (v) the influence of the initial composition of a post-disturbance community. In addition, stabilising processes such as biological legacies, inhibition or continuing disturbance may prevent a transition between community types. Integrating these six mechanisms with the functional trait approach is likely to improve the predictive capacity of disturbance theory. Finally, we complement our discussion of theory with a case study which emphasises that many post-disturbance theories apply simultaneously to the same ecosystem. Using the well-studied mountain ash (Eucalyptus regnans) forests of south-eastern Australia, we illustrate phenomena that align with six of the theories described in our model of rationalised disturbance theory. We encourage further work to improve our schematic model, increase coverage of disturbance-related theory, and to show how the model may link to, or integrate with, other domains of ecological theory. © 2014 Cambridge Philosophical Society.

Integrating Emergy into LCA: potential added value and lingering obstacles

EPA Science Inventory

Emergy attempts to measure the environmental work required to generate (ecosystem) goods and services that can be used by humans. It is claimed that the use of inventory modelling principles behind the Life Cycle Assessment (LCA) method (European Commission, 2010a) may improve th...

Application of a hybrid model to reduce bias and improve precision in population estimates for elk (Cervus elaphus) inhabiting a cold desert ecosystem

USGS Publications Warehouse

Schoenecker, Kathryn A.; Lubow, Bruce C.

2016-01-01

Accurately estimating the size of wildlife populations is critical to wildlife management and conservation of species. Raw counts or “minimum counts” are still used as a basis for wildlife management decisions. Uncorrected raw counts are not only negatively biased due to failure to account for undetected animals, but also provide no estimate of precision on which to judge the utility of counts. We applied a hybrid population estimation technique that combined sightability modeling, radio collar-based mark-resight, and simultaneous double count (double-observer) modeling to estimate the population size of elk in a high elevation desert ecosystem. Combining several models maximizes the strengths of each individual model while minimizing their singular weaknesses. We collected data with aerial helicopter surveys of the elk population in the San Luis Valley and adjacent mountains in Colorado State, USA in 2005 and 2007. We present estimates from 7 alternative analyses: 3 based on different methods for obtaining a raw count and 4 based on different statistical models to correct for sighting probability bias. The most reliable of these approaches is a hybrid double-observer sightability model (model MH), which uses detection patterns of 2 independent observers in a helicopter plus telemetry-based detections of radio collared elk groups. Data were fit to customized mark-resight models with individual sighting covariates. Error estimates were obtained by a bootstrapping procedure. The hybrid method was an improvement over commonly used alternatives, with improved precision compared to sightability modeling and reduced bias compared to double-observer modeling. The resulting population estimate corrected for multiple sources of undercount bias that, if left uncorrected, would have underestimated the true population size by as much as 22.9%. Our comparison of these alternative methods demonstrates how various components of our method contribute to improving the final estimate and demonstrates why each is necessary.

Promoting the confluence of tropical cyclone research

PubMed Central

Marler, Thomas E

2015-01-01

Contributions of biologists to tropical cyclone research may improve by integrating concepts from other disciplines. Employing accumulated cyclone energy into protocols may foster greater integration of ecology and meteorology research. Considering experienced ecosystems as antifragile instead of just resilient may improve cross-referencing among ecological and social scientists. Quantifying ecosystem capital as distinct from ecosystem services may improve integration of tropical cyclone ecology research into the expansive global climate change research community. PMID:26480001

The complexity of earth observation valuation: Modeling the patterns and processes of agricultural production and groundwater quality to construct a production possibilities frontier

NASA Astrophysics Data System (ADS)

Forney, W.; Raunikar, R. P.; Bernknopf, R.; Mishra, S.

2012-12-01

A production possibilities frontier (PPF) is a graph comparing the production interdependencies for two commodities. In this case, the commodities are defined as the ecosystem services of agricultural production and groundwater quality. This presentation focuses on the refinement of techniques used in an application to estimate the value of remote sensing information. Value of information focuses on the use of uncertain and varying qualities of information within a specific decision-making context for a certain application, which in this case included land use, biogeochemical, hydrogeologic, economic and geospatial data and models. The refined techniques include deriving alternate patterns and processes of ecosystem functions, new estimates of ecosystem service values to construct a PPF, and the extension of this work into decision support systems. We have coupled earth observations of agricultural production with groundwater quality measurements to estimate the value of remote sensing information in northeastern Iowa to be 857M ± 198M (at the 2010 price level) per year. We will present an improved method for modeling crop rotation patterns to include multiple years of rotation, reduction in the assumptions associated with optimal land use allocations, and prioritized improvement of the resolution of input data (for example, soil resources and topography). The prioritization focuses on watersheds that were identified at a coarse-scale of analysis to have higher intensities of agricultural production and lower probabilities of groundwater survivability (in other words, remaining below a regulatory threshold for nitrate pollution) over time, and thus require finer-scaled modeling and analysis. These improved techniques and the simulation of certain scale-dependent policy and management actions, which trade-off the objectives of optimizing crop value versus maintaining potable groundwater, and provide new estimates for the empirical values of the PPF. The calculation of a PPF in this way provides a decision maker with a tool to consider the ramifications of different policies, management practices and regional objectives.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush–steppe ecosystem

USGS Publications Warehouse

Wylie, Bruce K.; Johnson, Douglas A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, Tagir G.; Reed, Bradley C.; Tieszen, Larry L.; Worstell, Bruce B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rnwere measured with a Bowen ratio–energy balance (BREB) technique in a sagebrush (Artemisia spp.)–steppe ecosystem in northeast Idaho, USA, during 1996–1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996–1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday(R2=0.79, n=66, P<0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of Fday (R2=0.82, n=66, P<0.0001). Crossvalidation indicated that regression tree predictions of Fday were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted Rn quite well (R2=0.75–0.77, n=66) with the regression tree model being slightly more robust in crossvalidation. Temporal mapping of Fday and Rn is possible with these techniques and would allow the assessment of NEE in sagebrush–steppe ecosystems. Simulations of periodic Fday measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict Fday. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models.

Calibration of remotely sensed, coarse resolution NDVI to CO2 fluxes in a sagebrush-steppe ecosystem

USGS Publications Warehouse

Wylie, B.K.; Johnson, D.A.; Laca, Emilio; Saliendra, Nicanor Z.; Gilmanov, T.G.; Reed, B.C.; Tieszen, L.L.; Worstell, B.B.

2003-01-01

The net ecosystem exchange (NEE) of carbon flux can be partitioned into gross primary productivity (GPP) and respiration (R). The contribution of remote sensing and modeling holds the potential to predict these components and map them spatially and temporally. This has obvious utility to quantify carbon sink and source relationships and to identify improved land management strategies for optimizing carbon sequestration. The objective of our study was to evaluate prediction of 14-day average daytime CO2 fluxes (Fday) and nighttime CO2 fluxes (Rn) using remote sensing and other data. Fday and Rn were measured with a Bowen ratio-energy balance (BREB) technique in a sagebrush (Artemisia spp.)-steppe ecosystem in northeast Idaho, USA, during 1996-1999. Micrometeorological variables aggregated across 14-day periods and time-integrated Advanced Very High Resolution Radiometer (AVHRR) Normalized Difference Vegetation Index (iNDVI) were determined during four growing seasons (1996-1999) and used to predict Fday and Rn. We found that iNDVI was a strong predictor of Fday (R2 = 0.79, n = 66, P < 0.0001). Inclusion of evapotranspiration in the predictive equation led to improved predictions of Fday (R2= 0.82, n = 66, P < 0.0001). Crossvalidation indicated that regression tree predictions of Fday were prone to overfitting and that linear regression models were more robust. Multiple regression and regression tree models predicted Rn quite well (R2 = 0.75-0.77, n = 66) with the regression tree model being slightly more robust in crossvalidation. Temporal mapping of Fday and Rn is possible with these techniques and would allow the assessment of NEE in sagebrush-steppe ecosystems. Simulations of periodic Fday measurements, as might be provided by a mobile flux tower, indicated that such measurements could be used in combination with iNDVI to accurately predict Fday. These periodic measurements could maximize the utility of expensive flux towers for evaluating various carbon management strategies, carbon certification, and validation and calibration of carbon flux models. ?? 2003 Elsevier Science Inc. All rights reserved.

Hypoxia monitoring activities within the FP7 EU-project HYPOX: diverse approaches to understand a complex phenomenon

NASA Astrophysics Data System (ADS)

Janssen, F.; Waldmann, C.; Boetius, A.

2012-04-01

Hypoxic conditions in aquatic systems and the occurrence of 'dead zones' increase worldwide due to man-made eutrophication and global warming with consequences for biodiversity, ecosystem functions and services such as fisheries, aquaculture and tourism. Monitoring of hypoxia and its consequences has to (1) account for the appropriate temporal and spatial scales, (2) separate anthropogenic from natural drivers and long-term trends from natural variations, (3) assess ecosystem response, (4) use modeling tools for generalization and prediction, and (5) share data and obtained knowledge. In 2009 the EU FP7 project HYPOX (www.hypox.net) started out as a pioneering attempt to improve and integrate hypoxia observation capacities addressing these requirements. Target ecosystems selected for HYPOX cover a broad range of settings (e.g., hydrography, oxygenation status, biological activity, anthropogenic impact) and differ in their sensitivity towards change. Semi-enclosed basins with permanent anoxia (Black Sea, Baltic Sea), are included as well as seasonally or locally hypoxic land-locked systems (fjords, lagoons, lakes) and open ocean systems with high sensitivity to global warming (North Atlantic - Arctic transition). Adopted monitoring approaches involve autonomous, cabled, and shipboard instruments and include static and profiling moorings, benthic observatories, drifters, as well as classical CTD surveys. In order to improve observatory performance, project activities encompass developments of oxygen sensors as well as calibration procedures and technologies to reduce biofouling. Modeling and data assimilation are used to synthesize findings, to obtain an in-depth understanding of hypoxia causes and consequences, and to improve forecasting capacities. For integration of the collected information into a global oxygen observing system, results are disseminated through the HYPOX portal following GEOSS data sharing principles. This presentation will give an overview of the scientific approach of HYPOX and highlight some key results comprising findings from individual ecosystems and indentified general patterns. The driving forces that lead to hypoxia are assessed as well as consequences of oxygen depletion for aquatic life and biogeochemical processes.

Wetland fire remote sensing research--The Greater Everglades example

USGS Publications Warehouse

Jones, John W.

2012-01-01

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

Improving assessment and modelling of climate change impacts on global terrestrial biodiversity.

PubMed

McMahon, Sean M; Harrison, Sandy P; Armbruster, W Scott; Bartlein, Patrick J; Beale, Colin M; Edwards, Mary E; Kattge, Jens; Midgley, Guy; Morin, Xavier; Prentice, I Colin

2011-05-01

Understanding how species and ecosystems respond to climate change has become a major focus of ecology and conservation biology. Modelling approaches provide important tools for making future projections, but current models of the climate-biosphere interface remain overly simplistic, undermining the credibility of projections. We identify five ways in which substantial advances could be made in the next few years: (i) improving the accessibility and efficiency of biodiversity monitoring data, (ii) quantifying the main determinants of the sensitivity of species to climate change, (iii) incorporating community dynamics into projections of biodiversity responses, (iv) accounting for the influence of evolutionary processes on the response of species to climate change, and (v) improving the biophysical rule sets that define functional groupings of species in global models. Published by Elsevier Ltd.

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

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Ecosystem restoration: a systems approach to exotic plant control

Treesearch

Karl D. Smith

1998-01-01

Ecosystem restoration is a systems approach because it relates to all of the thousands of interrelated and interacting systems within the ecosystem. Ecosystem restoration also changes your role in the forest from observer to participant. Some of the goals of ecosystem restoration are to improve the health, vigor, and diversity of the ecosystem--and these goals can and...

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.

Evapotranspiration partitioning for three agro-ecosystems with contrasting moisture conditions: a comparison of an isotope method and a two-source model calculation

NASA Astrophysics Data System (ADS)

Wei, Z.; Lee, X.; Wen, X.; Xiao, W.

2017-12-01

Quantification of the contribution of transpiration (T) to evapotranspiration (ET) is a requirement for understanding changes in carbon assimilation and water cycling in a changing environment. So far, few studies have examined seasonal variability of T/ET and compared different ET partitioning methods under natural conditions across diverse agro-ecosystems. In this study, we apply a two-source model to partition ET for three agro-ecosystems (rice, wheat and corn). The model-estimated T/ET ranges from 0 to 1, with a near continuous increase over time in the early growing season when leaf area index (LAI) is less than 2.5 and then convergence towards a stable value beyond LAI of 2.5. The seasonal change in T/ET can be described well as a function of LAI, implying that LAI is a first-order factor affecting ET partitioning. The two-source model results show that the growing-season (May - September for rice, April - June for wheat and June to September for corn) T/ET is 0.50, 0.84 and 0.64, while an isotopic approach shows that T/ET is 0.74, 0.93 and 0.81 for rice, wheat and maize, respectively. The two-source model results are supported by soil lysimeter and eddy covariance measurements made during the same time period for wheat (0.87). Uncertainty analysis suggests that further improvements to the Craig-Gordon model prediction of the evaporation isotope composition and to measurement of the isotopic composition of ET are necessary to achieve accurate flux partitioning at the ecosystem scale using water isotopes as tracers.

Bioenergy crop productivity and potential climate change mitigation from marginal lands in the United States: An ecosystem modeling perspective

DOE PAGES

Qin, Zhangcai; Zhuang, Qianlai; Cai, Ximing

2014-06-16

Growing biomass feedstocks from marginal lands is becoming an increasingly attractive choice for producing biofuel as an alternative energy to fossil fuels. Here, we used a biogeochemical model at ecosystem scale to estimate crop productivity and greenhouse gas (GHG) emissions from bioenergy crops grown on marginal lands in the United States. Two broadly tested cellulosic crops, switchgrass, and Miscanthus, were assumed to be grown on the abandoned land and mixed crop–vegetation land with marginal productivity. Production of biomass and biofuel as well as net carbon exchange and nitrous oxide emissions were estimated in a spatially explicit manner. We found that,more » cellulosic crops, especially Miscanthus could produce a considerable amount of biomass, and the effective ethanol yield is high on these marginal lands. For every hectare of marginal land, switchgrass and Miscanthus could produce 1.0–2.3 kl and 2.9–6.9 kl ethanol, respectively, depending on nitrogen fertilization rate and biofuel conversion efficiency. Nationally, both crop systems act as net GHG sources. Switchgrass has high global warming intensity (100–390 g CO 2eq l –1 ethanol), in terms of GHG emissions per unit ethanol produced. Miscanthus, however, emits only 21–36 g CO 2eq to produce every liter of ethanol. To reach the mandated cellulosic ethanol target in the United States, growing Miscanthus on the marginal lands could potentially save land and reduce GHG emissions in comparison to growing switchgrass. Furthermore, the ecosystem modeling is still limited by data availability and model deficiencies, further efforts should be made to classify crop–specific marginal land availability, improve model structure, and better integrate ecosystem modeling into life cycle assessment.« less

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.

Stormwater Management Effects on Ecosystem Services: A Literature Review

NASA Astrophysics Data System (ADS)

Prudencio, L.; Null, S. E.

2016-12-01

Managing stormwater provides benefits for enhancing water supplies while reducing urban runoff. Yet, there has been little research focused on understanding how stormwater management affects ecosystem services, the benefits that ecosystems provide to humans. Garnering more knowledge of the changes to ecosystem services from stormwater management will ultimately improve management and decision-making. The objective of this research is to review and synthesize published literature on 1) ecosystem services and stormwater management and 2) changes in ecosystem services from anthropogenic impacts and climate warming, to establish a foundation for research at the intersection of ecosystems services, stormwater management, and global environmental change. We outline four research areas for ecosystem services and stormwater management that should be further explored. These four areas, named after the four types of ecosystem services, highlight context-specific research questions and human and climate change effects. We conclude that effective and sustainable stormwater management requires incorporating engineering, social, and environmental criteria to quantify benefits of provisioning, regulating, cultural, and supporting ecosystem services. Lastly, improved current and potential stormwater management policy may better support sustainable stormwater methods at the institutional level. Stormwater quality and monitoring could be improved through the use of the Clean Water Act (e.g. Total Maximum Daily Loads), the Endangered Species Act, and public health measures. Additional policies regulating groundwater quantity and quality have been and may continue to be implemented by states, encouraging sustainable and cleaner stormwater practices.

Coupled eco-hydrology and biogeochemistry algorithms enable the simulation of water table depth effects on boreal peatland net CO2 exchange

NASA Astrophysics Data System (ADS)

Mezbahuddin, Mohammad; Grant, Robert F.; Flanagan, Lawrence B.

2017-12-01

Water table depth (WTD) effects on net ecosystem CO2 exchange of boreal peatlands are largely mediated by hydrological effects on peat biogeochemistry and the ecophysiology of peatland vegetation. The lack of representation of these effects in carbon models currently limits our predictive capacity for changes in boreal peatland carbon deposits under potential future drier and warmer climates. We examined whether a process-level coupling of a prognostic WTD with (1) oxygen transport, which controls energy yields from microbial and root oxidation-reduction reactions, and (2) vascular and nonvascular plant water relations could explain mechanisms that control variations in net CO2 exchange of a boreal fen under contrasting WTD conditions, i.e., shallow vs. deep WTD. Such coupling of eco-hydrology and biogeochemistry algorithms in a process-based ecosystem model, ecosys, was tested against net ecosystem CO2 exchange measurements in a western Canadian boreal fen peatland over a period of drier-weather-driven gradual WTD drawdown. A May-October WTD drawdown of ˜ 0.25 m from 2004 to 2009 hastened oxygen transport to microbial and root surfaces, enabling greater microbial and root energy yields and peat and litter decomposition, which raised modeled ecosystem respiration (Re) by 0.26 µmol CO2 m-2 s-1 per 0.1 m of WTD drawdown. It also augmented nutrient mineralization, and hence root nutrient availability and uptake, which resulted in improved leaf nutrient (nitrogen) status that facilitated carboxylation and raised modeled vascular gross primary productivity (GPP) and plant growth. The increase in modeled vascular GPP exceeded declines in modeled nonvascular (moss) GPP due to greater shading from increased vascular plant growth and moss drying from near-surface peat desiccation, thereby causing a net increase in modeled growing season GPP by 0.39 µmol CO2 m-2 s-1 per 0.1 m of WTD drawdown. Similar increases in GPP and Re caused no significant WTD effects on modeled seasonal and interannual variations in net ecosystem productivity (NEP). These modeled trends were corroborated well by eddy covariance measured hourly net CO2 fluxes (modeled vs. measured: R2 ˜ 0.8, slopes ˜ 1 ± 0.1, intercepts ˜ 0.05 µmol m-2 s-1), hourly measured automated chamber net CO2 fluxes (modeled vs. measured: R2 ˜ 0.7, slopes ˜ 1 ± 0.1, intercepts ˜ 0.4 µmol m-2 s-1), and other biometric and laboratory measurements. Modeled drainage as an analog for WTD drawdown induced by climate-change-driven drying showed that this boreal peatland would switch from a large carbon sink (NEP ˜ 160 g C m-2 yr-1) to carbon neutrality (NEP ˜ 10 g C m-2 yr-1) should the water table deepen by a further ˜ 0.5 m. This decline in projected NEP indicated that a further WTD drawdown at this fen would eventually lead to a decline in GPP due to water limitation. Therefore, representing the effects of interactions among hydrology, biogeochemistry and plant physiological ecology on ecosystem carbon, water, and nutrient cycling in global carbon models would improve our predictive capacity for changes in boreal peatland carbon sequestration under changing climates.

Science for managing ecosystem services: Beyond the Millennium Ecosystem Assessment

PubMed Central

Carpenter, Stephen R.; Mooney, Harold A.; Agard, John; Capistrano, Doris; DeFries, Ruth S.; Díaz, Sandra; Dietz, Thomas; Duraiappah, Anantha K.; Oteng-Yeboah, Alfred; Pereira, Henrique Miguel; Perrings, Charles; Reid, Walter V.; Sarukhan, José; Scholes, Robert J.; Whyte, Anne

2009-01-01

The Millennium Ecosystem Assessment (MA) introduced a new framework for analyzing social–ecological systems that has had wide influence in the policy and scientific communities. Studies after the MA are taking up new challenges in the basic science needed to assess, project, and manage flows of ecosystem services and effects on human well-being. Yet, our ability to draw general conclusions remains limited by focus on discipline-bound sectors of the full social–ecological system. At the same time, some polices and practices intended to improve ecosystem services and human well-being are based on untested assumptions and sparse information. The people who are affected and those who provide resources are increasingly asking for evidence that interventions improve ecosystem services and human well-being. New research is needed that considers the full ensemble of processes and feedbacks, for a range of biophysical and social systems, to better understand and manage the dynamics of the relationship between humans and the ecosystems on which they rely. Such research will expand the capacity to address fundamental questions about complex social–ecological systems while evaluating assumptions of policies and practices intended to advance human well-being through improved ecosystem services. PMID:19179280

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 ...

Advancing the adaptive capacity of social-ecological systems to absorb climate extremes

NASA Astrophysics Data System (ADS)

Thonicke, Kirsten; Bahn, Michael; Bardgett, Richard; Bloemen, Jasper; Chabay, Ilan; Erb, Karlheinz; Giamberini, Mariasilvia; Gingrich, Simone; Lavorel, Sandra; Liehr, Stefan; Rammig, Anja

2017-04-01

The recent and projected increases in climate variability and the frequency of climate extremes are posing a profound challenge to society and the biosphere (IPCC 2012, IPCC 2013). Climate extremes can affect natural and managed ecosystems more severely than gradual warming. The ability of ecosystems to resist and recover from climate extremes is therefore of fundamental importance for society, which strongly relies on their ability to supply provisioning, regulating, supporting and cultural services. Society in turn triggers land-use and management decisions that affect ecosystem properties. Thus, ecological and socio-economic conditions are tightly coupled in what has been referred to as the social-ecological system. For ensuring human well-being in the light of climate extremes it is crucial to enhance the resilience of the social-ecological system (SES) across spatial, temporal and institutional scales. Stakeholders, such as resource managers, urban, landscape and conservation planners, decision-makers in agriculture and forestry, as well as natural hazards managers, require an improved knowledge base for better-informed decision making. To date the vulnerability and adaptive capacity of SESs to climate extremes is not well understood and large uncertainties exist as to the legacies of climate extremes on ecosystems and on related societal structures and processes. Moreover, we lack empirical evidence and incorporation of simulated future ecosystem and societal responses to support pro-active management and enhance social-ecological resilience. In our presentation, we outline the major research gaps and challenges to be addressed for understanding and enhancing the adaptive capacity of SES to absorb and adapt to climate extremes, including acquisition and elaboration of long-term monitoring data and improvement of ecological models to better project climate extreme effects and provide model uncertainties. We highlight scientific challenges and discuss conceptual and observational gaps that need to be overcome to advance this inter- and transdisciplinary topic.

Green Infrastructure, Ecosystem Services, and Human Health.

PubMed

Coutts, Christopher; Hahn, Micah

2015-08-18

Contemporary ecological models of health prominently feature the natural environment as fundamental to the ecosystem services that support human life, health, and well-being. The natural environment encompasses and permeates all other spheres of influence on health. Reviews of the natural environment and health literature have tended, at times intentionally, to focus on a limited subset of ecosystem services as well as health benefits stemming from the presence, and access and exposure to, green infrastructure. The sweeping influence of green infrastructure on the myriad ecosystem services essential to health has therefore often been underrepresented. This survey of the literature aims to provide a more comprehensive picture-in the form of a primer-of the many simultaneously acting health co-benefits of green infrastructure. It is hoped that a more accurately exhaustive list of benefits will not only instigate further research into the health co-benefits of green infrastructure but also promote consilience in the many fields, including public health, that must be involved in the landscape conservation necessary to protect and improve health and well-being.

Evaluating the Return in Ecosystem Services from Investment in Public Land Acquisitions

PubMed Central

Kovacs, Kent; Polasky, Stephen; Nelson, Erik; Keeler, Bonnie L.; Pennington, Derric; Plantinga, Andrew J.; Taff, Steven J.

2013-01-01

We evaluate the return on investment (ROI) from public land conservation in the state of Minnesota, USA. We use a spatially-explicit modeling tool, the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST), to estimate how changes in land use and land cover (LULC), including public land acquisitions for conservation, influence the joint provision and value of multiple ecosystem services. We calculate the ROI of a public conservation acquisition as the ratio of the present value of ecosystem services generated by the conservation to the cost of the conservation. For the land scenarios analyzed, carbon sequestration services generated the greatest benefits followed by water quality improvements and recreation opportunities. We found ROI values ranged from 0.21 to 5.28 depending on assumptions about future land use change, service values, and discount rate. Our study suggests conservation is a good investment as long as investments are targeted to areas with low land costs and high service values. PMID:23776429

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.

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.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling.

PubMed

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha; Thompson, Jill; Zimmerman, Jess K; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here, we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured interannual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including aboveground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate. © 2017 John Wiley & Sons Ltd.

Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling

USGS Publications Warehouse

Feng, Xiaohui; Uriarte, María; González, Grizelle; Reed, Sasha C.; Thompson, Jill; Zimmerman, Jess K.; Murphy, Lora

2018-01-01

Tropical forests play a critical role in carbon and water cycles at a global scale. Rapid climate change is anticipated in tropical regions over the coming decades and, under a warmer and drier climate, tropical forests are likely to be net sources of carbon rather than sinks. However, our understanding of tropical forest response and feedback to climate change is very limited. Efforts to model climate change impacts on carbon fluxes in tropical forests have not reached a consensus. Here we use the Ecosystem Demography model (ED2) to predict carbon fluxes of a Puerto Rican tropical forest under realistic climate change scenarios. We parameterized ED2 with species-specific tree physiological data using the Predictive Ecosystem Analyzer workflow and projected the fate of this ecosystem under five future climate scenarios. The model successfully captured inter-annual variability in the dynamics of this tropical forest. Model predictions closely followed observed values across a wide range of metrics including above-ground biomass, tree diameter growth, tree size class distributions, and leaf area index. Under a future warming and drying climate scenario, the model predicted reductions in carbon storage and tree growth, together with large shifts in forest community composition and structure. Such rapid changes in climate led the forest to transition from a sink to a source of carbon. Growth respiration and root allocation parameters were responsible for the highest fraction of predictive uncertainty in modeled biomass, highlighting the need to target these processes in future data collection. Our study is the first effort to rely on Bayesian model calibration and synthesis to elucidate the key physiological parameters that drive uncertainty in tropical forests responses to climatic change. We propose a new path forward for model-data synthesis that can substantially reduce uncertainty in our ability to model tropical forest responses to future climate.

Assessing Ecosystem Drought Response in CLM 4.5 Using Site-Level Flux and Carbon-Isotope Measurements: Results From a Pacific Northwest Coniferous Forest

NASA Astrophysics Data System (ADS)

Duarte, H.; Raczka, B. M.; Koven, C. D.; Ricciuto, D. M.; Lin, J. C.; Bowling, D. R.; Ehleringer, J. R.

2015-12-01

The frequency, extent, and severity of droughts are expected to increase in the western United States as climate changes occur. The combination of warmer temperature, larger vapor pressure deficit, reduced snowfall and snow pack, earlier snow melt, and extended growing seasons is expected to lead to an intensification of summer droughts, with a direct impact on ecosystem productivity and therefore on the carbon budget of the region. In this scenario, an accurate representation of ecosystem drought response in land models becomes fundamental, but the task is challenging, especially in regards to stomatal response to drought. In this study we used the most recent release of the Community Land Model (CLM 4.5), which now includes photosynthetic carbon isotope discrimination and revised photosynthesis and hydrology schemes, among an extensive list of updates. We evaluated the model's performance at a coniferous forest site in the Pacific northwest (Wind River AmeriFlux Site), characterized by a climate that has a strong winter precipitation component followed by a summer drought. We ran the model in offline mode (i.e., decoupled from an atmospheric model), forced by observed meteorological data, and used site observations (e.g., surface fluxes, biomass values, and carbon isotope data) to assess the model. Previous field observations indicated a significant negative correlation between soil water content and the carbon isotope ratio of ecosystem respiration (δ13CR), suggesting that δ13CR was closely related to the photosynthetic discrimination against 13CO2 as controlled by stomatal conductance. We used these observations and latent-heat flux measurements to assess the modeled stomatal conductance values and their responses to extended summer drought. We first present the model results, followed by a discussion of potential CLM model improvements in stomatal conductance responses and in the representation of soil water stress (parameter βt) that would more precisely incorporate features that would allow the model to correctly simulate field observations.

USGS River Ecosystem Modeling: Where Are We, How Did We Get Here, and Where Are We Going?

USGS Publications Warehouse

Hanson, Leanne; Schrock, Robin; Waddle, Terry; Duda, Jeffrey J.; Lellis, Bill

2009-01-01

This report developed as an outcome of the USGS River Ecosystem Modeling Work Group, convened on February 11, 2008 as a preconference session to the second USGS Modeling Conference in Orange Beach, Ala. Work Group participants gained an understanding of the types of models currently being applied to river ecosystem studies within the USGS, learned how model outputs are being used by a Federal land management agency, and developed recommendations for advancing the state of the art in river ecosystem modeling within the USGS. During a break-out session, participants restated many of the recommendations developed at the first USGS Modeling Conference in 2006 and in previous USGS needs assessments. All Work Group recommendations require organization and coordination across USGS disciplines and regions, and include (1) enhancing communications, (2) increasing efficiency through better use of current human and technologic resources, and (3) providing a national infrastructure for river ecosystem modeling resources, making it easier to integrate modeling efforts. By implementing these recommendations, the USGS will benefit from enhanced multi-disciplinary, integrated models for river ecosystems that provide valuable risk assessment and decision support tools for adaptive management of natural and managed riverine ecosystems. These tools generate key information that resource managers need and can use in making decisions about river ecosystem resources.

PiTS-1: Carbon Partitioning in Loblolly Pine after 13C Labeling and Shade Treatments

DOE Data Explorer

Warren, J. M.; Iversen, C. M.; Garten, Jr., C. T.; Norby, R. J.; Childs, J.; Brice, D.; Evans, R. M.; Gu, L.; Thornton, P.; Weston, D. J.

2013-01-01

The PiTS task was established with the objective of improving the C partitioning routines in existing ecosystem models by exploring mechanistic model representations of partitioning tested against field observations. We used short-term field manipulations of C flow, through 13CO2 labeling, canopy shading and stem girdling, to dramatically alter C partitioning, and resultant data are being used to test model representation of C partitioning processes in the Community Land Model (CLM4 or CLM4.5).

Integrating watershed hydrology and economics to establish a local market for water quality improvement: A field experiment

EPA Science Inventory

Innovative market mechanisms are being increasingly recognized as effective decision-making institutions to incorporate the value of ecosystem services into the economy. We present a field experiment that integrates an economic auction and a biophysical water flux model to develo...

Future riverine nitrogen export to US coastal regions: Prospects for improving water quality amid population growth.

EPA Science Inventory

Excess nitrogen (N) in the environment degrades ecosystems and adversely affects human health. Here we examine predictions of contemporary (2000) and future (2030) coastal N loading in the continental US by the Nutrient Export from WaterSheds (NEWS) model. Future scenarios were b...

Inclusion of Riparian Wetland Module (RWM) into the SWAT model for assessment of wetland hydrological benefit

USDA-ARS?s Scientific Manuscript database

Wetlands are an integral part of many agricultural watersheds. They provide multiple ecosystem functions, such as improving water quality, mitigating flooding, and serving as natural habitats. Those functions are highly depended on wetland hydrological characteristics and their connectivity to the d...

"Advances in Coupled Air Quality, Farm Management and Biogeochemistry to address bidirectional ammonia flux"

EPA Science Inventory

A cropland farm management modeling system for regional air quality and field-scale applications of bi-directional ammonia exchange was presented at ITM XXI. The goal of this research is to improve estimates of nitrogen deposition to terrestrial and aquatic ecosystems and ambien...

Development of known-fate survival monitoring techniques for juvenile wild pigs (Sus scrofa)

Treesearch

David A. Keiter; John C. Kilgo; Mark A. Vukovich; Fred L. Cunningham; James C. Beasley

2017-01-01

Context. Wild pigs are an invasive species linked to numerous negative impacts on natural and anthropogenic ecosystems in many regions of the world. Robust estimates of juvenile wild pig survival are needed to improve population dynamics models to facilitate management of this economically and ecologically...

An open and extensible framework for spatially explicit land use change modelling in R: the lulccR package (0.1.0)

NASA Astrophysics Data System (ADS)

Moulds, S.; Buytaert, W.; Mijic, A.

2015-04-01

Land use change has important consequences for biodiversity and the sustainability of ecosystem services, as well as for global environmental change. Spatially explicit land use change models improve our understanding of the processes driving change and make predictions about the quantity and location of future and past change. Here we present the lulccR package, an object-oriented framework for land use change modelling written in the R programming language. The contribution of the work is to resolve the following limitations associated with the current land use change modelling paradigm: (1) the source code for model implementations is frequently unavailable, severely compromising the reproducibility of scientific results and making it impossible for members of the community to improve or adapt models for their own purposes; (2) ensemble experiments to capture model structural uncertainty are difficult because of fundamental differences between implementations of different models; (3) different aspects of the modelling procedure must be performed in different environments because existing applications usually only perform the spatial allocation of change. The package includes a stochastic ordered allocation procedure as well as an implementation of the widely used CLUE-S algorithm. We demonstrate its functionality by simulating land use change at the Plum Island Ecosystems site, using a dataset included with the package. It is envisaged that lulccR will enable future model development and comparison within an open environment.

CMIP5 land surface models systematically underestimate inter-annual variability of net ecosystem exchange in semi-arid southwestern North America.

NASA Astrophysics Data System (ADS)

MacBean, N.; Scott, R. L.; Biederman, J. A.; Vuichard, N.; Hudson, A.; Barnes, M.; Fox, A. M.; Smith, W. K.; Peylin, P. P.; Maignan, F.; Moore, D. J.

2017-12-01

Recent studies based on analysis of atmospheric CO2 inversions, satellite data and terrestrial biosphere model simulations have suggested that semi-arid ecosystems play a dominant role in the interannual variability and long-term trend in the global carbon sink. These studies have largely cited the response of vegetation activity to changing moisture availability as the primary mechanism of variability. However, some land surface models (LSMs) used in these studies have performed poorly in comparison to satellite-based observations of vegetation dynamics in semi-arid regions. Further analysis is therefore needed to ensure semi-arid carbon cycle processes are well represented in global scale LSMs before we can fully establish their contribution to the global carbon cycle. In this study, we evaluated annual net ecosystem exchange (NEE) simulated by CMIP5 land surface models using observations from 20 Ameriflux sites across semi-arid southwestern North America. We found that CMIP5 models systematically underestimate the magnitude and sign of NEE inter-annual variability; therefore, the true role of semi-arid regions in the global carbon cycle may be even more important than previously thought. To diagnose the factors responsible for this bias, we used the ORCHIDEE LSM to test different climate forcing data, prescribed vegetation fractions and model structures. Climate and prescribed vegetation do contribute to uncertainty in annual NEE simulations, but the bias is primarily caused by incorrect timing and magnitude of peak gross carbon fluxes. Modifications to the hydrology scheme improved simulations of soil moisture in comparison to data. This in turn improved the seasonal cycle of carbon uptake due to a more realistic limitation on photosynthesis during water stress. However, the peak fluxes are still too low, and phenology is poorly represented for desert shrubs and grasses. We provide suggestions on model developments needed to tackle these issues in the future.

Assimilating AmeriFlux Site Data into the Community Land Model with Carbon-Nitrogen Coupling via the Ensemble Kalman Filter

NASA Astrophysics Data System (ADS)

Pettijohn, J. C.; Law, B. E.; Williams, M. D.; Stoeckli, R.; Thornton, P. E.; Hudiburg, T. M.; Thomas, C. K.; Martin, J.; Hill, T. C.

2009-12-01

The assimilation of terrestrial carbon, water and nutrient cycle measurements into land surface models of these processes is fundamental to improving our ability to predict how these ecosystems may respond to climate change. A combination of measurements and models, each with their own systematic biases, must be considered when constraining the nonlinear behavior of these coupled dynamics. As such, we use the sequential Ensemble Kalman Filter (EnKF) to assimilate eddy covariance (EC) and other site-level AmeriFlux measurements into the NCAR Community Land Model with Carbon-Nitrogen coupling (CLM-CN v3.5), run in single-column mode at a 30-minute time step, to improve estimates of relatively unconstrained model state variables and parameters. Specifically, we focus on a semi-arid ponderosa pine site (US-ME2) in the Pacific Northwest to identify the mechanisms by which this ecosystem responds to severe late summer drought. Our EnKF analysis includes water, carbon, energy and nitrogen state variables (e.g., 10 volumetric soil moisture levels (0-3.43 m), ponderosa pine and shrub evapotranspiration and net ecosystem exchange of carbon dioxide stocks and flux components, snow depth, etc.) and associated parameters (e.g., PFT-level rooting distribution parameters, maximum subsurface runoff coefficient, soil hydraulic conductivity decay factor, snow aging parameters, maximum canopy conductance, C:N ratios, etc.). The effectiveness of the EnKF in constraining state variables and associated parameters is sensitive to their relative frequencies, in that C-N state variables and parameters with long time constants require similarly long time series in the analysis. We apply the EnKF kernel perturbation routine to disrupt preliminary convergence of covariances, which has been found in recent studies to be a problem more characteristic of low frequency vegetation state variables and parameters than high frequency ones more heavily coupled with highly varying climate (e.g., shallow soil moisture, snow depth). Preliminary results demonstrate that the assimilation of EC and other available AmeriFlux site physical, chemical and biological data significantly helps quantify and reduce CLM-CN model uncertainties and helps to constrain ‘hidden’ states and parameters that are essential in the coupled water, carbon, energy and nutrient dynamics of these sites. Such site-level calibration of CLM-CN is an initial step in identifying model deficiencies and in forecasts of future ecosystem responses to climate change.

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

NASA Astrophysics Data System (ADS)

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

2015-06-01

We explore cropland management alternatives and the effect these can have on future C and N pools and fluxes using the land use-enabled dynamic vegetation model LPJ-GUESS. Simulated crop production, cropland carbon storage, carbon sequestration and nitrogen leaching from croplands are evaluated and discussed. Compared to the version of LPJ-GUESS that does not include land use dynamics, estimates of soil carbon stocks and nitrogen leaching from terrestrial to aquatic ecosystems were improved. We explore trade-offs between important ecosystem services that can be provided from agricultural fields such as crop yields, retention of nitrogen and carbon storage. These trade-offs are evaluated for current land use and climate and further explored for future conditions within the two future climate change scenarios, RCP 2.6 and 8.5. Our results show that the potential for carbon sequestration due to typical cropland management practices such as no-till and cover-crops proposed in literature is not realised, globally or over larger climatic regions. Our results highlight important considerations to be made when modelling C-N interactions in agricultural ecosystems under future environmental change, and the effects these have on terrestrial biogeochemical cycles.

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

NASA Astrophysics Data System (ADS)

Pappas, C.

2017-12-01

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

A global Fine-Root Ecology Database to address below-ground challenges in plant ecology.

PubMed

Iversen, Colleen M; McCormack, M Luke; Powell, A Shafer; Blackwood, Christopher B; Freschet, Grégoire T; Kattge, Jens; Roumet, Catherine; Stover, Daniel B; Soudzilovskaia, Nadejda A; Valverde-Barrantes, Oscar J; van Bodegom, Peter M; Violle, Cyrille

2017-07-01

Variation and tradeoffs within and among plant traits are increasingly being harnessed by empiricists and modelers to understand and predict ecosystem processes under changing environmental conditions. While fine roots play an important role in ecosystem functioning, fine-root traits are underrepresented in global trait databases. This has hindered efforts to analyze fine-root trait variation and link it with plant function and environmental conditions at a global scale. This Viewpoint addresses the need for a centralized fine-root trait database, and introduces the Fine-Root Ecology Database (FRED, http://roots.ornl.gov) which so far includes > 70 000 observations encompassing a broad range of root traits and also includes associated environmental data. FRED represents a critical step toward improving our understanding of below-ground plant ecology. For example, FRED facilitates the quantification of variation in fine-root traits across root orders, species, biomes, and environmental gradients while also providing a platform for assessments of covariation among root, leaf, and wood traits, the role of fine roots in ecosystem functioning, and the representation of fine roots in terrestrial biosphere models. Continued input of observations into FRED to fill gaps in trait coverage will improve our understanding of changes in fine-root traits across space and time. © 2017 UT-Battelle LLC. New Phytologist © 2017 New Phytologist Trust.

CLASSIFICATION FRAMEWORK FOR COASTAL ECOSYSTEM RESPONSES TO AQUATIC STRESSORS

EPA Science Inventory

Many classification schemes have been developed to group ecosystems based on similar characteristics. To date, however, no single scheme has addressed coastal ecosystem responses to multiple stressors. We developed a classification framework for coastal ecosystems to improve the ...

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.

POEM: PESTICIDE ORCHARD ECOSYSTEM MODEL

EPA Science Inventory

The Pesticide Orchard Ecosystem Model (POEM) is a mathematical model of organophosphate pesticide movement in an apple orchard ecosystem. In addition submodels on invertebrate population dynamics are included. The fate model allows the user to select the pesticide, its applicatio...

Development of an Unmanned Aerial System (UAS) for Scaling Terrestrial Ecosystem Traits

NASA Astrophysics Data System (ADS)

Meng, R.; McMahon, A. M.; Serbin, S.; Rogers, A.

2015-12-01

The next generation of Ecosystem and Earth System Models (EESMs) will require detailed information on ecosystem structure and function, including properties of vegetation related to carbon (C), water, and energy cycling, in order to project the future state of ecosystems. High spatial-temporal resolution measurements of terrestrial ecosystem are also important for EESMs, because they can provide critical inputs and benchmark datasets for evaluation of EESMs simulations across scales. The recent development of high-quality, low-altitude remote sensing platforms or small UAS (< 25 kg) enables measurements of terrestrial ecosystems at unprecedented temporal and spatial scales. Specifically, these new platforms can provide detailed information on patterns and processes of terrestrial ecosystems at a critical intermediate scale between point measurements and suborbital and satellite platforms. Given their potential for sub-decimeter spatial resolution, improved mission safety, high revisit frequency, and reduced operation cost, these platforms are of particular interest in the development of ecological scaling algorithms to parameterize and benchmark EESMs, particularly over complex and remote terrain. Our group is developing a small UAS platform and integrated sensor package focused on measurement needs for scaling and informing ecosystem modeling activities, as well as scaling and mapping plant functional traits. To do this we are developing an integrated software workflow and hardware package using off-the-shelf instrumentation including a high-resolution digital camera for Structure from Motion, spectroradiometer, and a thermal infrared camera. Our workflow includes platform design, measurement, image processing, data management, and information extraction. The fusion of 3D structure information, thermal-infrared imagery, and spectroscopic measurements, will provide a foundation for the development of ecological scaling and mapping algorithms. Our initial focus is in temperate forests but near-term research will expand into the high-arctic and eventually tropical systems. The results of this prototype study show that off-the-shelf technology can be used to develop a low-cost alternative for mapping plant traits and three-dimensional structure for ecological research.

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.

Wood phenology: from organ-scale processes to terrestrial ecosystem models

NASA Astrophysics Data System (ADS)

Delpierre, Nicolas; Guillemot, Joannès

2016-04-01

In temperate and boreal trees, a dormancy period prevents organ development during adverse climatic conditions. Whereas the phenology of leaves and flowers has received considerable attention, to date, little is known regarding the phenology of other tree organs such as wood, fine roots, fruits and reserve compounds. In this presentation, we review both the role of environmental drivers in determining the phenology of wood and the models used to predict its phenology in temperate and boreal forest trees. Temperature is a key driver of the resumption of wood activity in spring. There is no such clear dominant environmental cue involved in the cessation of wood formation in autumn, but temperature and water stress appear as prominent factors. We show that wood phenology is a key driver of the interannual variability of wood growth in temperate tree species. Incorporating representations of wood phenology in a terrestrial ecosystem model substantially improved the simulation of wood growth under current climate.

Collective evolution of cyanobacteria and cyanophages mediated by horizontal gene transfer

NASA Astrophysics Data System (ADS)

Shih, Hong-Yan; Rogers, Tim; Goldenfeld, Nigel

We describe a model for how antagonistic predator-prey coevolution can lead to mutualistic adaptation to an environment, as a result of horizontal gene transfer. Our model is a simple description of ecosystems such as marine cyanobacteria and their predator cyanophages, which carry photosynthesis genes. These genes evolve more rapidly in the virosphere than the bacterial pan-genome, and thus the bacterial population could potentially benefit from phage predation. By modeling both the barrier to predation and horizontal gene transfer, we study this balance between individual sacrifice and collective benefits. The outcome is an emergent mutualistic coevolution of improved photosynthesis capability, benefiting both bacteria and phage. This form of multi-level selection can contribute to niche stratification in the cyanobacteria-phage ecosystem. This work is supported in part by a cooperative agreement with NASA, Grant NNA13AA91A/A0018.

Revisiting drought impact on tropical forest photosynthesis: a novel multi-scale integrated approach reveals new insights

NASA Astrophysics Data System (ADS)

Detto, M.; Wu, J.; Xu, X.; Serbin, S.; Rogers, A.

2017-12-01

A fundamental unanswered question for global change ecology is to determine the vulnerability of tropical forests to climate change, particularly with increasing intensity and frequency of drought events. This question, despite its apparent simplicity, remains difficult for earth system models to answer, and is controversial in remote sensing literature. Here, we leverage unique multi-scale remote sensing measurements (from leaf to crown) in conjunction with four-continuous-year (2013-2017) eddy covariance measurements of ecosystem carbon fluxes in a tropical forest in Panama to revisit this question. We hypothesize that drought impacts tropical forest photosynthesis through variation in abiotic drivers (solar radiation, diffuse light fraction, and vapor pressure deficit) that interact with physiological traits that govern photosynthesis, and biotic variation in ecosystem photosynthetic capacity associated with changes in the traits themselves. Our study site, located in a seasonal tropical forest on Barro Colorado Island (BCI), Panama, experienced a significant drought in 2015. Local eddy covariance derived photosynthesis shows an abrupt increase during the drought year. Our specific goal here is to assess the relative impact of abiotic and biotic drivers of such photosynthesis response to interannual drought. To this goal, we derived abiotic drivers from eddy tower-based meteorological measurements. We will derive the biotic drivers using a recently developed leaf demography-ontogeny model, where ecosystem photosynthetic capacity can be described as the product of field measured, age-dependent leaf photosynthetic capacity and local tower-camera derived ecosystem-scale inter-annual variability in leaf age demography of the same time period (2013-2017). Lastly, we will use a process-based model to assess the separate and joint effects of abiotic and biotic drivers on eddy covariance derive photosynthetic interannual variability. Collectively, this novel multi-scale integrated study aims to improve ecophysiological understanding of tropical forest response to interannual climate variability, highlighting the importance to combine state-of-the-art technology and theories to improve future projections of carbon dynamics in the tropics.

Ecosystem-atmosphere exchange of CO2 in a temperate herbaceous peatland in the Sanjiang Plain of northeast China

USGS Publications Warehouse

Zhu, Xiaoyan; Song, Changchun; Swarzenski, Christopher M.; Guo, Yuedong; Zhang, Xinhow; Wang, Jiaoyue

2015-01-01

Northern peatlands contain a considerable share of the terrestrial carbon pool, which will be affected by future climatic variability. Using the static chamber technique, we investigated ecosystem respiration and soil respiration over two growing seasons (2012 and 2013) in a Carex lasiocarpa-dominated peatland in the Sanjiang Plain in China. We synchronously monitored the environmental factors controlling CO2 fluxes. Ecosystem respiration during these two growing seasons ranged from 33.3 to 506.7 mg CO2–C m−2 h−1. Through step-wise regression, variations in soil temperature at 10 cm depth alone explained 73.7% of the observed variance in log10(ER). The mean Q10 values ranged from 2.1 to 2.9 depending on the choice of depth where soil temperature was measured. The Q10 value at the 10 cm depth (2.9) appears to be a good representation for herbaceous peatland in the Sanjiang Plain when applying field-estimation based Q10values to current terrestrial ecosystem models due to the most optimized regression coefficient (63.2%). Soil respiration amounted to 57% of ecosystem respiration and played a major role in peatland carbon balance in our study. Emphasis on ecosystem respiration from temperate peatlands in the Sanjiang Plain will improve our basic understanding of carbon exchange between peatland ecosystem and the atmosphere.

Can biomass responses to warming at plant to ecosystem levels be predicted by leaf-level responses?

NASA Astrophysics Data System (ADS)

Xia, J.; Shao, J.; Zhou, X.; Yan, W.; Lu, M.

2015-12-01

Global warming has the profound impacts on terrestrial C processes from leaf to ecosystem scales, potentially feeding back to climate dynamics. Although numerous studies had investigated the effects of warming on C processes from leaf to plant and ecosystem levels, how leaf-level responses to warming scale up to biomass responses at plant, population, and community levels are largely unknown. In this study, we compiled a dataset from 468 papers at 300 experimental sites and synthesized the warming effects on leaf-level parameters, and plant, population and ecosystem biomass. Our results showed that responses of plant biomass to warming mainly resulted from the changed leaf area rather than the altered photosynthetic capacity. The response of ecosystem biomass to warming was weaker than those of leaf area and plant biomass. However, the scaling functions from responses of leaf area to plant biomass to warming were different in diverse forest types, but functions were similar in non-forested biomes. In addition, it is challenging to scale the biomass responses from plant up to ecosystem. These results indicated that leaf area might be the appropriate index for plant biomass response to warming, and the interspecific competition might hamper the scaling of the warming effects on plant and ecosystem levels, suggesting that the acclimation capacity of plant community should be incorporated into land surface models to improve the prediction of climate-C cycle feedback.

Modelling impacts of second generation bioenergy production on Ecosystem Services in Europe

NASA Astrophysics Data System (ADS)

Henner, Dagmar N.; Smith, Pete; Davies, Christian; McNamara, Niall P.

2015-04-01

Bioenergy crops are an important source of renewable energy and are a possible mechanism to mitigate global climate warming, by replacing fossil fuel energy with higher greenhouse gas emissions. There is, however, uncertainty about the impacts of the growth of bioenergy crops on ecosystem services. This uncertainty is further enhanced by the unpredictable climate change currently going on. The goal of this project is to develop a comprehensive model that covers as many ecosystem services as possible at a Continental level including biodiversity, water, GHG emissions, soil, and cultural services. The distribution and production of second generation energy crops, such as Miscanthus, Short Rotation Coppice (SRC) and Short Rotation Forestry (SRF), is currently being modelled, and ecosystem models will be used to examine the impacts of these crops on ecosystem services. The project builds on models of energy crop production, biodiversity, soil impacts, greenhouse gas emissions and other ecosystem services, and on work undertaken in the UK on the ETI-funded ELUM project (www.elum.ac.uk). In addition, methods like water footprint tools, tourism value maps and ecosystem valuation tools and models (e.g. InVest, TEEB database, GREET LCA Model, World Business Council for Sustainable Development corporate ecosystem valuation, Millennium Ecosystem Assessment and the Ecosystem Services Framework) will be utilised. Research will focus on optimisation of land use change feedbacks on ecosystem services and biodiversity, and weighting of the importance of the individual ecosystem services. Energy crops will be modelled using low, medium and high climate change scenarios for the years between 2015 and 2050. We will present first results for GHG emissions and soil organic carbon change after different land use change scenarios (e.g. arable to Miscanthus, forest to SRF), and with different climate warming scenarios. All this will be complemented by the presentation of a matrix including all the factors and ecosystem services influenced by land use change to bioenergy crop production under different climate change scenarios.

Vegetation canopy and physiological control of GPP decline during drought and heat wave

NASA Astrophysics Data System (ADS)

Zhang, Y.; Xiao, X.; Zhou, S.; McCarthy, H. R.; Ciais, P.; Luo, Y.

2015-12-01

Different vegetation indices derived from satellites were often used as a proxy of vegetation activity to monitor and evaluate the impacts of drought and heat wave on ecosystem carbon fluxes (gross primary production, respiration) through the production efficiency models (PEMs). However, photosynthesis is also regulated by a series of physiological processes which cannot be directly observed through satellites. In this study, we analyzed the response of drought and heat wave induced GPP and climate anomaly from 15 Euroflux sites and the corresponding vegetation indices from Moderate Resolution Imaging Spectroradiometer (MODIS) satellite. Correlation analysis suggests that the vegetation indices are more responsive to GPP variation in grasslands and open shrublands, but less responsive in forest ecosystems. Physiology control can be up to 20% of the total GPP during the drought period without changing the canopy structure. At temporal scale for each site, VPD and vegetation indices can be used to track the GPP for forest and non-forest, respectively. However, different stand characteristics should be taken into consideration for forest ecosystems. Based on the above findings, a conceptual model is built to illuminate the physiological and canopy control on the GPP during the drought period. Improvement for future PEMs should incorporate better indicators to deal with drought conditions for different ecosystems.

A floodplain continuum for Atlantic coast rivers of the Southeastern US: Predictable changes in floodplain biota along a river's length

USGS Publications Warehouse

Batzer, Darold P.; Noe, Gregory; Lee, Linda; Galatowitsch, Mark

2018-01-01

Floodplains are among the world’s economically-most-valuable, environmentally-most-threatened, and yet conceptually-least-understood ecosystems. Drawing on concepts from existing riverine and wetland models, and empirical data from floodplains of Atlantic Coast rivers in the Southeastern US (and elsewhere when possible), we introduce a conceptual model to explain a continuum of longitudinal variation in floodplain ecosystem functions with a particular focus on biotic change. Our hypothesis maintains that major controls on floodplain ecology are either external (ecotonal interactions with uplands or stream/river channels) or internal (wetland-specific functions), and the relative importance of these controls changes progressively from headwater to mid-river to lower-river floodplains. Inputs of water, sediments, nutrients, flora, and fauna from uplands-to-floodplains decrease, while the impacts of wetland biogeochemistry and obligate wetland plants and animals within-floodplains increase, along the length of a river floodplain. Inputs of water, sediment, nutrients, and fauna from river/stream channels to floodplains are greatest mid-river, and lower either up- or down-stream. While the floodplain continuum we develop is regional in scope, we review how aspects may apply more broadly. Management of coupled floodplain-river ecosystems would be improved by accounting for how factors controlling the floodplain ecosystem progressively change along longitudinal riverine gradients.

Using ecological production functions to link ecological ...

EPA Pesticide Factsheets

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

Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function.

PubMed

Antonarakis, Alexander S; Saatchi, Sassan S; Chazdon, Robin L; Moorcroft, Paul R

2011-06-01

Insights into vegetation and aboveground biomass dynamics within terrestrial ecosystems have come almost exclusively from ground-based forest inventories that are limited in their spatial extent. Lidar and synthetic-aperture Radar are promising remote-sensing-based techniques for obtaining comprehensive measurements of forest structure at regional to global scales. In this study we investigate how Lidar-derived forest heights and Radar-derived aboveground biomass can be used to constrain the dynamics of the ED2 terrestrial biosphere model. Four-year simulations initialized with Lidar and Radar structure variables were compared against simulations initialized from forest-inventory data and output from a long-term potential-vegtation simulation. Both height and biomass initializations from Lidar and Radar measurements significantly improved the representation of forest structure within the model, eliminating the bias of too many large trees that arose in the potential-vegtation-initialized simulation. The Lidar and Radar initializations decreased the proportion of larger trees estimated by the potential vegetation by approximately 20-30%, matching the forest inventory. This resulted in improved predictions of ecosystem-scale carbon fluxes and structural dynamics compared to predictions from the potential-vegtation simulation. The Radar initialization produced biomass values that were 75% closer to the forest inventory, with Lidar initializations producing canopy height values closest to the forest inventory. Net primary production values for the Radar and Lidar initializations were around 6-8% closer to the forest inventory. Correcting the Lidar and Radar initializations for forest composition resulted in improved biomass and basal-area dynamics as well as leaf-area index. Correcting the Lidar and Radar initializations for forest composition and fine-scale structure by combining the remote-sensing measurements with ground-based inventory data further improved predictions, suggesting that further improvements of structural and carbon-flux metrics will also depend on obtaining reliable estimates of forest composition and accurate representation of the fine-scale vertical and horizontal structure of plant canopies.

Population-reaction model and microbial experimental ecosystems for understanding hierarchical dynamics of ecosystems.

PubMed

Hosoda, Kazufumi; Tsuda, Soichiro; Kadowaki, Kohmei; Nakamura, Yutaka; Nakano, Tadashi; Ishii, Kojiro

2016-02-01

Understanding ecosystem dynamics is crucial as contemporary human societies face ecosystem degradation. One of the challenges that needs to be recognized is the complex hierarchical dynamics. Conventional dynamic models in ecology often represent only the population level and have yet to include the dynamics of the sub-organism level, which makes an ecosystem a complex adaptive system that shows characteristic behaviors such as resilience and regime shifts. The neglect of the sub-organism level in the conventional dynamic models would be because integrating multiple hierarchical levels makes the models unnecessarily complex unless supporting experimental data are present. Now that large amounts of molecular and ecological data are increasingly accessible in microbial experimental ecosystems, it is worthwhile to tackle the questions of their complex hierarchical dynamics. Here, we propose an approach that combines microbial experimental ecosystems and a hierarchical dynamic model named population-reaction model. We present a simple microbial experimental ecosystem as an example and show how the system can be analyzed by a population-reaction model. We also show that population-reaction models can be applied to various ecological concepts, such as predator-prey interactions, climate change, evolution, and stability of diversity. Our approach will reveal a path to the general understanding of various ecosystems and organisms. Copyright © 2015 The Authors. Published by Elsevier Ireland Ltd.. All rights reserved.

Transdisciplinary science: a path to understanding the interactions among ocean acidification, ecosystems, and society

USGS Publications Warehouse

Yates, Kimberly K.; Turley, Carol; Hopkinson, Brian M.; Todgham, Anne E.; Cross, Jessica N.; Greening, Holly; Williamson, Phillip; Van Hooidonk, Ruben; Deheyn, Dimitri D.; Johnson, Zachary

2015-01-01

The global nature of ocean acidification (OA) transcends habitats, ecosystems, regions, and science disciplines. The scientific community recognizes that the biggest challenge in improving understanding of how changing OA conditions affect ecosystems, and associated consequences for human society, requires integration of experimental, observational, and modeling approaches from many disciplines over a wide range of temporal and spatial scales. Such transdisciplinary science is the next step in providing relevant, meaningful results and optimal guidance to policymakers and coastal managers. We discuss the challenges associated with integrating ocean acidification science across funding agencies, institutions, disciplines, topical areas, and regions, and the value of unifying science objectives and activities to deliver insights into local, regional, and global scale impacts. We identify guiding principles and strategies for developing transdisciplinary research in the ocean acidification science community.

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.

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.

Linking water quality and well-being for improved assessment and valuation of ecosystem services

PubMed Central

Keeler, Bonnie L.; Polasky, Stephen; Brauman, Kate A.; Johnson, Kris A.; Finlay, Jacques C.; O’Neill, Ann; Kovacs, Kent; Dalzell, Brent

2012-01-01

Despite broad recognition of the value of the goods and services provided by nature, existing tools for assessing and valuing ecosystem services often fall short of the needs and expectations of decision makers. Here we address one of the most important missing components in the current ecosystem services toolbox: a comprehensive and generalizable framework for describing and valuing water quality-related services. Water quality is often misrepresented as a final ecosystem service. We argue that it is actually an important contributor to many different services, from recreation to human health. We present a valuation approach for water quality-related services that is sensitive to different actions that affect water quality, identifies aquatic endpoints where the consequences of changing water quality on human well-being are realized, and recognizes the unique groups of beneficiaries affected by those changes. We describe the multiple biophysical and economic pathways that link actions to changes in water quality-related ecosystem goods and services and provide guidance to researchers interested in valuing these changes. Finally, we present a valuation template that integrates biophysical and economic models, links actions to changes in service provision and value estimates, and considers multiple sources of water quality-related ecosystem service values without double counting. PMID:23091018

Linking water quality and well-being for improved assessment and valuation of ecosystem services.

PubMed

Keeler, Bonnie L; Polasky, Stephen; Brauman, Kate A; Johnson, Kris A; Finlay, Jacques C; O'Neill, Ann; Kovacs, Kent; Dalzell, Brent

2012-11-06

Despite broad recognition of the value of the goods and services provided by nature, existing tools for assessing and valuing ecosystem services often fall short of the needs and expectations of decision makers. Here we address one of the most important missing components in the current ecosystem services toolbox: a comprehensive and generalizable framework for describing and valuing water quality-related services. Water quality is often misrepresented as a final ecosystem service. We argue that it is actually an important contributor to many different services, from recreation to human health. We present a valuation approach for water quality-related services that is sensitive to different actions that affect water quality, identifies aquatic endpoints where the consequences of changing water quality on human well-being are realized, and recognizes the unique groups of beneficiaries affected by those changes. We describe the multiple biophysical and economic pathways that link actions to changes in water quality-related ecosystem goods and services and provide guidance to researchers interested in valuing these changes. Finally, we present a valuation template that integrates biophysical and economic models, links actions to changes in service provision and value estimates, and considers multiple sources of water quality-related ecosystem service values without double counting.

Buffer capacity, ecosystem feedbacks, and seawater chemistry under global change

NASA Astrophysics Data System (ADS)

Jury, C. P.; Thomas, F. I.; Atkinson, M. J.; Jokiel, P. L.; Onuma, M. A.; Kaku, N.; Toonen, R. J.

2013-12-01

Ocean acidification (OA) results in reduced seawater pH and aragonite saturation state (Ωarag), but also reduced seawater buffer capacity. As buffer capacity decreases, diel variation in seawater chemistry increases. However, a variety of ecosystem feedbacks can modulate changes in both average seawater chemistry and diel seawater chemistry variation. Here we model these effects for a coastal, reef flat ecosystem. We show that an increase in offshore pCO2 and temperature (to 900 μatm and +3°C) can increase diel pH variation by as much as a factor of 2.5 and can increase diel pCO2 variation by a factor of 4.6, depending on ecosystem feedbacks and seawater residence time. Importantly, these effects are different between day and night. With increasing seawater residence time and increasing feedback intensity, daytime seawater chemistry becomes more similar to present-day conditions while nighttime seawater chemistry becomes less similar to present-day conditions. Better constraining ecosystem feedbacks under global change will improve projections of coastal water chemistry, but this study shows the importance of considering changes in both average carbonate chemistry and diel chemistry variation for organisms and ecosystems. Further, we will discuss our recent work examining the effects of diel seawater chemistry variation on coral calcification rates.

Realizing the potential of ecosystem services: a framework for relating ecological changes to economic benefits.

PubMed

Wainger, Lisa; Mazzotta, Marisa

2011-10-01

Increasingly government agencies are seeking to quantify the outcomes of proposed policy options in terms of ecosystem service benefits, yet conflicting definitions and ad hoc approaches to measuring ecosystem services have created confusion regarding how to rigorously link ecological change to changes in human well-being. Here, we describe a step-by-step framework for producing ecological models and metrics that can effectively serve an economic-benefits assessment of a proposed change in policy or management. A focus of the framework is developing comparable units of ecosystem goods and services to support decision-making, even if outcomes cannot be monetized. Because the challenges to translating ecological changes to outcomes appropriate for economic analyses are many, we discuss examples that demonstrate practical methods and approaches to overcoming data limitations. The numerous difficult decisions that government agencies must make to fairly use and allocate natural resources provides ample opportunity for interdisciplinary teams of natural and social scientists to improve methods for quantifying changes in ecosystem services and their effects on human well-being. This framework is offered with the intent of promoting the success of such teams as they support managers in evaluating the equivalency of ecosystem service offsets and trades, establishing restoration and preservation priorities, and more generally, in developing environmental policy that effectively balances multiple perspectives.

VOC Metabolite Emissions from the Brachypodium/Soil/Microbe Ecosystem

NASA Astrophysics Data System (ADS)

Gu, D.; Shilling, J.; Guenther, A. B.; Lindenmaier, R.

2017-12-01

Volatile Organic Compounds (VOCs) emitted from plants and associated microbiota are important for understanding the plant responses to environmental perturbations. VOC emissions from plants are the largest source of hydrocarbons to the atmosphere, which influence oxidants and aerosols leading to complex feed backs and interactions between atmosphere and biosphere. The integrated Plant-Atmosphere-Soil Systems (iPASS) Initiative is a Pacific Northwest National Laboratory (PNNL) project aimed at deciphering fundamental principles that govern the plant ecosystem, from plant genotype through multiple scales to ecosystem traits and response. We take the opportunity of iPASS initiative, and measured VOC metabolite emissions from the Brachypodium/Soil/Microbe Ecosystem. In the experiments, we have been working on (1) identifying VOC metabolites emitted by Brachypodium plants using dynamic vegetation enclosure measurements, (2) understanding the relative contribution of plants, microbes, and soil to VOC emissions, (3) investigating changes that occur in these emissions under different induced stress, and (4) relating VOC emissions from the plant/soil/microbe ecosystem to plant genotype. Taking advantage of experiment results, we also can develop a noninvasive technique for quantifying plant stress by using VOC observations, use VOC observations to improve screening tool for identifying stress resistant phenotypes, and apply the measurements into earth system modeling for better understanding of the impacts of stress on ecosystems.

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.

Effects of payments for ecosystem services on wildlife habitat recovery.

PubMed

Tuanmu, Mao-Ning; Viña, Andrés; Yang, Wu; Chen, Xiaodong; Shortridge, Ashton M; Liu, Jianguo

2016-08-01

Conflicts between local people's livelihoods and conservation have led to many unsuccessful conservation efforts and have stimulated debates on policies that might simultaneously promote sustainable management of protected areas and improve the living conditions of local people. Many government-sponsored payments-for-ecosystem-services (PES) schemes have been implemented around the world. However, few empirical assessments of their effectiveness have been conducted, and even fewer assessments have directly measured their effects on ecosystem services. We conducted an empirical and spatially explicit assessment of the conservation effectiveness of one of the world's largest PES programs through the use of a long-term empirical data set, a satellite-based habitat model, and spatial autoregressive analyses on direct measures of change in an ecosystem service (i.e., the provision of wildlife species habitat). Giant panda (Ailuropoda melanoleuca) habitat improved in Wolong Nature Reserve of China after the implementation of the Natural Forest Conservation Program. The improvement was more pronounced in areas monitored by local residents than those monitored by the local government, but only when a higher payment was provided. Our results suggest that the effectiveness of a PES program depends on who receives the payment and on whether the payment provides sufficient incentives. As engagement of local residents has not been incorporated in many conservation strategies elsewhere in China or around the world, our results also suggest that using an incentive-based strategy as a complement to command-and-control, community- and norm-based strategies may help achieve greater conservation effectiveness and provide a potential solution for the park versus people conflict. © 2016 Society for Conservation Biology.

Modeling and dynamic monitoring of ecosystem performance in the Yukon River Basin

USGS Publications Warehouse

Wylie, Bruce K.; Zhang, L.; Ji, Lei; Tieszen, Larry L.; Bliss, N.B.

2008-01-01

Central Alaska is ecologically sensitive and experiencing stress in response to marked regional warming. Resource managers would benefit from an improved ability to monitor ecosystem processes in response to climate change, fire, insect damage, and management policies and to predict responses to future climate scenarios. We have developed a method for analyzing ecosystem performance as represented by the growing season integral of normalized difference vegetation index (NDVI), which is a measure of greenness that can be interpreted in terms of plant growth or photosynthetic activity (gross primary productivity). The approach illustrates the status and trends of ecosystem changes and separates the influences of climate and local site conditions from the influences of disturbances and land management.We emphasize the ability to quantify ecosystem processes, not simply changes in land cover, across the entire period of the remote sensing archive (Wylie and others, 2008). The method builds upon remotely sensed measures of vegetation greenness for each growing season. By itself, however, a time series of greenness often reflects annual climate variations in temperature and precipitation. Our method seeks to remove the influence of climate so that changes in underlying ecological conditions are identified and quantified. We define an "expected ecosystem performance" to represent the greenness response expected in a particular year given the climate of that year. We distinguish "performance anomalies" as cases where the ecosystem response is significantly different from the expected ecosystem performance. Maps of the performance anomalies (fig. 1) and trends in the anomalies give valuable information on the ecosystems for land managers and policy makers at a resolution of 1 km to 250 m.

Transforming ecosystems: When, where, and how to restore contaminated sites.

PubMed

Rohr, Jason R; Farag, Aïda M; Cadotte, Marc W; Clements, William H; Smith, James R; Ulrich, Cheryl P; Woods, Richard

2016-04-01

Chemical contamination has impaired ecosystems, reducing biodiversity and the provisioning of functions and services. This has spurred a movement to restore contaminated ecosystems and develop and implement national and international regulations that require it. Nevertheless, ecological restoration remains a young and rapidly growing discipline and its intersection with toxicology is even more nascent and underdeveloped. Consequently, we provide guidance to scientists and practitioners on when, where, and how to restore contaminated ecosystems. Although restoration has many benefits, it also can be expensive, and in many cases systems can recover without human intervention. Hence, the first question we address is: "When should we restore contaminated ecosystems?" Second, we provide suggestions on what to restore-biodiversity, functions, services, all 3, or something else--and where to restore given expected changes to habitats driven by global climate change. Finally, we provide guidance on how to restore contaminated ecosystems. To do this, we analyze critical aspects of the literature dealing with the ecology of restoring contaminated ecosystems. Additionally, we review approaches for translating the science of restoration to on-the-ground actions, which includes discussions of market incentives and the finances of restoration, stakeholder outreach and governance models for ecosystem restoration, and working with contractors to implement restoration plans. By explicitly considering the mechanisms and strategies that maximize the success of the restoration of contaminated sites, we hope that our synthesis serves to increase and improve collaborations between restoration ecologists and ecotoxicologists and set a roadmap for the restoration of contaminated ecosystems. © 2015 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals, Inc. on behalf of SETAC.

A spatial framework for representing nearshore ecosystems

NASA Astrophysics Data System (ADS)

Gregr, Edward J.; Lessard, Joanne; Harper, John

2013-08-01

The shallow, coastal regions of the world's oceans are highly productive ecosystems providing important habitat for commercial, forage, endangered, and iconic species. Given the diversity of ecosystem services produced or supported by this ecosystem, a better understanding of its structure and function is central to developing an ecosystem-based approach to management. However this region - termed the ‘white strip' by marine geologists because of the general lack of high-resolution bathymetric data - is dynamic, highly variable, and difficult to access making data collection challenging and expensive. Since substrate is a key indicator of habitat in this important ecosystem, our objective was to create a continuous substrate map from the best available bottom type data. Such data are critical to assessments of species distributions and anthropogenic risk. Using the Strait of Georgia in coastal British Columbia, Canada, as a case study, we demonstrate how such a map can be created from a diversity of sources. Our approach is simple, quantitative, and transparent making it amenable to iterative improvement as data quality and availability improve. We evaluated the ecological performance of our bottom patches using observed shellfish distributions. We found that observations of geoduck clam, an infaunal species, and red urchins, a species preferentially associated with hard bottom, were strongly and significantly associated with our soft and hard patches respectively. Our description of bottom patches also corresponded well with a more traditional, morphological classification of a portion of the study area. To provide subsequent analyses (such as habitat models) with some confidence in the defined bottom type values, we developed a corresponding confidence surface based on the agreement of, and distance between observations. Our continuous map of nearshore bottom patches thus provides a spatial framework to which other types of data, both abiotic (e.g., energy) and biotic, can be attached. As more data are associated with the bottom patches, we anticipate they will become increasingly useful for representing and developing species-habitat relationships, ultimately leading to a comprehensive representation of the nearshore ecosystem.

Large scale afforestation projects mitigate degradation and increase the stability of the karst ecosystems in southwest China

NASA Astrophysics Data System (ADS)

Yue, Y.; Tong, X.; Wang, K.; Fensholt, R.; Brandt, M.

2017-12-01

With the aim to combat desertification and improve the ecological environment, mega-engineering afforestation projects have been launched in the karst regions of southwest China around the turn of the new millennium. A positive impact of these projects on vegetation cover has been shown, however, it remains unclear if conservation efforts have been able to effectively restore ecosystem properties and reduce the sensitivity of the karst ecosystem to climate variations at large scales. Here we use passive microwave and optical satellite time series data combined with the ecosystem model LPJ-GUESS and show widespread increase in vegetation cover with a clear demarcation at the Chinese national border contrasting the conditions of neighboring countries. We apply a breakpoint detection to identify permanent changes in vegetation time series and assess the vegetation's sensitivity against climate before and after the breakpoints. A majority (74%) of the breakpoints were detected between 2001 and 2004 and are remarkably in line with the implementation and spatial extent of the Grain to Green project. We stratify the counties of the study area into four groups according to the extent of Grain to Green conservation areas and find distinct differences between the groups. Vegetation trends are similar prior to afforestation activities (1982-2000), but clearly diverge at a later stage, following the spatial extent of conservation areas. Moreover, vegetation cover dynamics were increasingly decoupled from climatic influence in areas of high conservation efforts. Whereas both vegetation resilience and resistance were considerably improved in areas with large conservation efforts thereby showing an increase in ecosystem stability, ongoing degradation and an amplified sensitivity to climate variability was found in areas with limited project implementation. Our study concludes that large scale conservation projects can regionally contribute to a greening Earth and are able to mitigate desertification by increasing the vegetation cover and reducing the ecosystem sensitivity to climate change, however, degradation remains a serious issue in the karst ecosystem of southwest China.

Optimal Plant Carbon Allocation Implies a Biological Control on Nitrogen Availability

NASA Astrophysics Data System (ADS)

Prentice, I. C.; Stocker, B. D.

2015-12-01

The degree to which nitrogen availability limits the terrestrial C sink under rising CO2 is a key uncertainty in carbon cycle and climate change projections. Results from ecosystem manipulation studies and meta-analyses suggest that plant C allocation to roots adjusts dynamically under varying degrees of nitrogen availability and other soil fertility parameters. In addition, the ratio of biomass production to GPP appears to decline under nutrient scarcity. This reflects increasing plant C exudation into the soil (Cex) with decreasing nutrient availability. Cex is consumed by an array of soil organisms and may imply an improvement of nutrient availability to the plant. Thus, N availability is under biological control, but incurs a C cost. In spite of clear observational support, this concept is left unaccounted for in Earth system models. We develop a model for the coupled cycles of C and N in terrestrial ecosystems to explore optimal plant C allocation under rising CO2 and its implications for the ecosystem C balance. The model follows a balanced growth approach, accounting for the trade-offs between leaf versus root growth and Cex in balancing C fixation and N uptake. We assume that Cex is proportional to root mass, and that the ratio of N uptake (Nup) to Cex is proportional to inorganic N concentration in the soil solution. We further assume that Cex is consumed by N2-fixing processes if the ratio of Nup:Cex falls below the inverse of the C cost of N2-fixation. Our analysis thereby accounts for the feedbacks between ecosystem C and N cycling and stoichiometry. We address the question of how the plant C economy will adjust under rising atmospheric CO2 and what this implies for the ecosystem C balance and the degree of N limitation.

Managing bay and estuarine ecosystems for multiple services

USGS Publications Warehouse

Needles, Lisa A.; Lester, Sarah E.; Ambrose, Richard; Andren, Anders; Beyeler, Marc; Connor, Michael S.; Eckman, James E.; Costa-Pierce, Barry A.; Gaines, Steven D.; Lafferty, Kevin D.; Lenihan, Junter S.; Parrish, Julia; Peterson, Mark S.; Scaroni, Amy E.; Weis, Judith S.; Wendt, Dean E.

2013-01-01

Managers are moving from a model of managing individual sectors, human activities, or ecosystem services to an ecosystem-based management (EBM) approach which attempts to balance the range of services provided by ecosystems. Applying EBM is often difficult due to inherent tradeoffs in managing for different services. This challenge particularly holds for estuarine systems, which have been heavily altered in most regions and are often subject to intense management interventions. Estuarine managers can often choose among a range of management tactics to enhance a particular service; although some management actions will result in strong tradeoffs, others may enhance multiple services simultaneously. Management of estuarine ecosystems could be improved by distinguishing between optimal management actions for enhancing multiple services and those that have severe tradeoffs. This requires a framework that evaluates tradeoff scenarios and identifies management actions likely to benefit multiple services. We created a management action-services matrix as a first step towards assessing tradeoffs and providing managers with a decision support tool. We found that management actions that restored or enhanced natural vegetation (e.g., salt marsh and mangroves) and some shellfish (particularly oysters and oyster reef habitat) benefited multiple services. In contrast, management actions such as desalination, salt pond creation, sand mining, and large container shipping had large net negative effects on several of the other services considered in the matrix. Our framework provides resource managers a simple way to inform EBM decisions and can also be used as a first step in more sophisticated approaches that model service delivery.

Riparian livestock exclosure research in the western United States: a critique and some recommendations.

PubMed

Sarr, Daniel A

2002-10-01

Over the last three decades, livestock exclosure research has emerged as a preferred method to evaluate the ecology of riparian ecosystems and their susceptibility to livestock impacts. This research has addressed the effects of livestock exclusion on many characteristics of riparian ecosystems, including vegetation, aquatic and terrestrial animals, and geomorphology. This paper reviews, critiques, and provides recommendations for the improvement of riparian livestock exclosure research. Exclosure-based research has left considerable scientific uncertainty due to popularization of relatively few studies, weak study designs, a poor understanding of the scales and mechanisms of ecosystem recovery, and selective, agenda-laden literature reviews advocating for or against public lands livestock grazing. Exclosures are often too small (<50 ha) and improperly placed to accurately measure the responses of aquatic organisms or geomorphic processes to livestock removal. Depending upon the site conditions when and where livestock exclosures are established, postexclusion dynamics may vary considerably. Systems can recover quickly and predictably with livestock removal (the "rubber band" model), fail to recover due to changes in system structure or function (the "Humpty Dumpty" model), or recover slowly and remain more sensitive to livestock impacts than they were before grazing was initiated (the "broken leg" model). Several initial ideas for strengthening the scientific basis for livestock exclosure research are presented: (1) incorporation of meta-analyses and critical reviews. (2) use of restoration ecology as a unifying conceptual framework; (3) development of long-term research programs; (4) improved exclosure placement/ design; and (5) a stronger commitment to collection of pretreatment data.

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

PubMed

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

2016-07-15

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

Importance of soil thermal regime in terrestrial ecosystem carbon dynamics in the circumpolar north

NASA Astrophysics Data System (ADS)

Jiang, Yueyang; Zhuang, Qianlai; Sitch, Stephen; O'Donnell, Jonathan A.; Kicklighter, David; Sokolov, Andrei; Melillo, Jerry

2016-07-01

In the circumpolar north (45-90°N), permafrost plays an important role in vegetation and carbon (C) dynamics. Permafrost thawing has been accelerated by the warming climate and exerts a positive feedback to climate through increasing soil C release to the atmosphere. To evaluate the influence of permafrost on C dynamics, changes in soil temperature profiles should be considered in global C models. This study incorporates a sophisticated soil thermal model (STM) into a dynamic global vegetation model (LPJ-DGVM) to improve simulations of changes in soil temperature profiles from the ground surface to 3 m depth, and its impacts on C pools and fluxes during the 20th and 21st centuries. With cooler simulated soil temperatures during the summer, LPJ-STM estimates 0.4 Pg C yr- 1 lower present-day heterotrophic respiration but 0.5 Pg C yr- 1 higher net primary production than the original LPJ model resulting in an additional 0.8 to 1.0 Pg C yr- 1 being sequestered in circumpolar ecosystems. Under a suite of projected warming scenarios, we show that the increasing active layer thickness results in the mobilization of permafrost C, which contributes to a more rapid increase in heterotrophic respiration in LPJ-STM compared to the stand-alone LPJ model. Except under the extreme warming conditions, increases in plant production due to warming and rising CO2, overwhelm the e nhanced ecosystem respiration so that both boreal forest and arctic tundra ecosystems remain a net C sink over the 21st century. This study highlights the importance of considering changes in the soil thermal regime when quantifying the C budget in the circumpolar north.

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.

Interactions between drought and soil biogeochemistry: scaling from molecules to meters

NASA Astrophysics Data System (ADS)

Schimel, J.; Schaeffer, S. M.

2011-12-01

Water is the perhaps the single most critical resource for life, yet most terrestrial ecosystems experience regular drought. Reduced water potential causes physiological stress; reduced diffusion limits resource availability when microbes may need resources to acclimate. Most biogeochemical models, however, have assumed that soil processes either slow down or stop during drought. But organisms survive and enzymes remain viable. In California, as soils stay dry through the long summer drought, microbial biomass actually increases and pools of extractable organic C increase, probably because extracellular enzymes continue to break down plant detritus (notably roots). Yet 14C suggests that in deeper soils, the pulse of C released on rewetting comes from pools with turnover times of as long as 800 years. What are the mechanisms that regulate these complex dynamics? They appear to involve differential moisture sensitivity for the activity of extracellular enzymes, substrate diffusion, and microbial metabolism. Rewetting not only redistributes materials made available during the drought, but it also disrupts aggregates and may make previously-protected substrates available as well. We have used several methods to simply capture these linkages between water and carbon in models that are applicable at the ecosystem scale and that could improve our ability to model biogeochemical cycles in arid and semi-arid ecosystems. One is a simple empirical modification to the DAYCENT model while the other is a mechanistic model that incorporates microbial dry-season processes.

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

NASA Astrophysics Data System (ADS)

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

2016-09-01

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

Examining Ecological and Ecosystem Level Impacts of Aquatic Invasive Species in Lake Michigan Using An Ecosystem Productivity Model, LM-Eco

EPA Science Inventory

Ecological and ecosystem-level impacts of aquatic invasive species in Lake Michigan were examined using the Lake Michigan Ecosystem Model (LM-Eco). The LM-Eco model includes a detailed description of trophic levels and their interactions within the lower food web of Lake Michiga...