EcoService Models Library (ESML)
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Compare EMs
Which comparison is best for me?EM Variables by Variable Role
One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.
This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:
- Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
- Intermediate (Computed) Variables
- Response Variables
- Computed Response Variables
- Measured Response Variables
EM Variables by Category
A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:
- Policy Regarding Use or Management of Ecosystem Resources
- Land Surface (or Water Body Bed) Cover, Use or Substrate
- Human Demographic Data
- Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
- Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
- Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
- Monetary Values
Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.
All EM Descriptors
This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:
- EM Identity and Description
- EM Modeling Approach
- EM Locations, Environments, Ecology
- EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
EM Descriptors by Modeling Concepts
This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:
- Conceptual Model
- Modeling Objective
- Modeling Context
- Potential for Model Linkage
- Feasibility of Model Use
- Model Certainty
- Model Structural Information
Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.
EM Identity and Description
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Short Name
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InVEST (v1.004) Carbon, Indonesia | Nitrogen fixation rates, Guánica Bay, Puerto Rico | InVEST fisheries, lobster, South Africa | WESP: Urban Stormwater Treatment, ID, USA | C sequestration in grassland restoration, England | WESP: Marsh & wet meadow, ID, USA | VELMA v. 2.0 disturbance | Predicting ecosystem service values, Bangladesh |
EM Full Name
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InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004) carbon storage and sequestration, Sumatra, Indonesia | Nitrogen fixation rates, Guánica Bay, Puerto Rico, USA | Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa | WESP: Urban Stormwater Treament, ID, USA | Carbon sequestration in grassland diversity restoration, England | WESP: Seasonally flooded marsh & wet meadow, Idaho, USA | VELMA (Visualizing Ecosystems for Land Management Assessment) version 2.0 disturbance | Future ecosystem service value modeling with land cover dynamics by using machine learning based Artificial Neural Network model for Jashore city, Bangladesh |
EM Source or Collection
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InVEST | US EPA | InVEST | None | None | None | US EPA | None |
EM Source Document ID
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309 |
338 ?Comment:WE received a draft copy prior to journal publication that was agency reviewed. |
349 ?Comment:Supplemented with the InVEST Users Guide fisheries. |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
396 |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
366 | 457 |
Document Author
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Bhagabati, N. K., Ricketts, T., Sulistyawan, T. B. S., Conte, M., Ennaanay, D., Hadian, O., McKenzie, E., Olwero, N., Rosenthal, A., Tallis, H., and Wolney, S. | Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher | Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby | Murphy, C. and T. Weekley | De Deyn, G. B., R. S. Shiel, N. J. Ostle, N. P. McNamara, S. Oakley, I. Young, C. Freeman, N. Fenner, H. Quirk, and R. D. Bardgett | Murphy, C. and T. Weekley | McKane, R. B., A. Brookes, K. Djang, M. Stieglitz, A. G. Abdelnour, F. Pan, J. J. Halama, P. B. Pettus and D. L. Phillips | Morshed, S. R., Fattah, M. A., Haque, M. N., & Morshed, S. Y. |
Document Year
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2014 | 2017 | 2018 | 2012 | 2011 | 2012 | 2014 | 2022 |
Document Title
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Ecosystem services reinforce Sumatran tiger conservation in land use plans | Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico | Food, money and lobsters: Valuing ecosystem services to align environmental management with Sustainable Development Goals | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. | Additional carbon sequestration benefits of grassland diversity restoration | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. | VELMA Version 2.0 User Manual and Technical Documentation | Future ecosystem service value modeling with land cover dynamics by using machine learning based Artificial Neural Network model for Jashore city, Bangladesh |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published report | Published journal manuscript | Published report | Published report | Published journal manuscript |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
https://www.naturalcapitalproject.org/invest/ | Not applicable | https://www.naturalcapitalproject.org/invest/ | Not applicable | Not applicable | Not applicable | https://www.epa.gov/water-research/visualizing-ecosystem-land-management-assessments-velma-model-20 | Not applicable | |
Contact Name
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Nirmal K. Bhagabati | Susan H. Yee | Michelle Ward | Chris Murphy | Gerlinde B. De Deyn | Chris Murphy | Robert B. McKane | Syed Riad Morshed |
Contact Address
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The Nature Conservancy, 1107 Laurel Avenue, Felton, CA 95018 | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | ARC Centre of Excellence for Environmental Decisions, The University of Queensland, Brisbane, QLD 4072, Australia | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID | Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID | U.S. EPA, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Western Ecology Division, Corvallis, Oregon 97333 | Department of Urban and Regional Planning, Khulna University of Engineering and Technology, Khulna, Bangladesh |
Contact Email
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nirmal.bhagabati@wwfus.org | yee.susan@epa.gov | m.ward@uq.edu.au | chris.murphy@idfg.idaho.gov | g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com | chris.murphy@idfg.idaho.gov | mckane.bob@epa.gov | riad.kuet.urp16@gmail.com |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Summary Description
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Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. ABSTRACT: "...Here we use simple spatial analyses on readily available datasets to compare the distribution of five ecosystem services with tiger habitat in central Sumatra. We assessed services and habitat in 2008 and the changes in these variables under two future scenarios: a conservation-friendly Green Vision, and a Spatial Plan developed by the Indonesian government..." AUTHOR'S DESCRIPTION: "We used a modeling tool, InVEST (Integrated Valuation of Environmental Services and Tradeoffs version 1.004; Tallis et al., 2010), to map and quantify tiger habitat quality and five ecosystem services. InVEST maps ecosystem services and the quality of species habitat as production functions of LULC using simple biophysical models. Models were parameterized using data from regional agencies, literature surveys, global databases, site visits and prior field experience (Table 1)... We mapped biomass carbon by assigning carbon values (in ton ha_1) for aboveground, belowground, and dead organic matter to each LULC class based on values from literature, as described in Tallis et al. (2010). We mapped soil carbon separately, as large quantities of carbon are stored in peat soil (Page et al., 2011). We estimated total losses in peat carbon over 50 years into the future scenarios, using reported annual emission rates for specific LULC transitions on peat (Uryu et al., 2008)...Although InVEST reports ecosystem services in biophysical units, its simple models are best suited to understanding broad patterns of spatial variation (Tallis and Polasky, 2011), rather than for precise quantification. Additionally, we lacked field measurements against which to calibrate our outputs. Therefore, we focused on relative spatial distribution across the landscape, and relative change to scenarios." | AUTHOR'S DESCRIPTION: " …In Guánica Bay watershed, Puerto Rico, deforestation and drainage of a large lagoon have led to sediment, contaminant, and nutrient transport into the bay, resulting in declining quality of coral reefs. A watershed management plan is currently being implemented to restore reefs through a variety of proposed actions…After the workshops, fifteen indicators of terrestrial ecosystem services in the watershed and four indicators in the coastal zone were identified to reflect the wide range of stakeholder concerns that could be impacted by management decisions. Ecosystem service production functions were applied to quantify and map ecosystem services supply in the Guánica Bay watershed, as well as an additional highly engineered upper multi-watershed area connected to the lower watershed via a series of reservoirs and tunnels,…” AUTHOR''S DESCRIPTION: "The U.S. Coral Reef Task Force (CRTF), a collaboration of federal, state and territorial agencies, initiated a program in 2009 to better incorporate land-based sources of pollution and socio-economic considerations into watershed strategies for coral reef protection (Bradley et al., 2016)...Baseline measures for relevant ecosystem services were calculated by parameterizing existing methods, largely based on land cover (Egoh et al., 2012; Martinez- Harms and Balvanera, 2012), with relevant rates of ecosystem services production for Puerto Rico, and applying them to map ecosystem services supply for the Guánica Bay Watershed...The Guánica Bay watershed is a highly engineered watershed in southwestern Puerto Rico, with a series of five reservoirs and extensive tunnel systems artificially connecting multiple mountainous sub-watersheds to the lower watershed of the Rio Loco, which itself is altered by an irrigation canal and return drainage ditch that diverts water through the Lajas Valley (PRWRA, 1948)...For each objective, a translator of ecosystem services production, i.e., ecological production function, was used to quantify baseline measurements of ecosystem services supply from land use/land cover (LULC) maps for watersheds across Puerto Rico...Two additional metrics, nitrogen fixation and rates of carbon sequestration into soil and sediment, were also calculated as potential measures of soil quality and agricultural productivity. Carbon sequestration and nitrogen fixation rates were assigned to each land cover class" | AUTHOR'S DESCRIPTION: "Here we develop a method for assessing future scenarios of environmental management change that improve coastal ecosystem services and thereby, support the success of the SDGs. We illustrate application of the method using a case study of South Africa’s West Coast Rock Lobster fishery within the Table Mountain National Park (TMNP) Marine Protected Area...We calculated the retrospective and current value of the West Coast Rock Lobster fishery using published and unpublished data from various sources and combined the market worth of landed lobster from recreational fishers, small-scale fisheries (SSF), large-scale fisheries (LSF) and poachers. Then using the InVEST tool, we combined data to build scenarios that describe possible futures for the West Coast Rock Lobster fishery (see Table 1). The first scenario, entitled ‘Business as Usual’ (BAU), takes the current situation and most up-to-date data to model the future if harvest continues at the existing rate. The second scenario is entitled ‘Redirect the Poachers’ (RP), which attempts to model implementation of strict management, whereby poaching is minimised from the Marine Protected Area and other economic and nutritional sources are made available through government initiatives. The third scenario, entitled ‘Large Scale Cutbacks’ (LSC), excludes large-scale fisheries from harvesting West Coast Rock Lobster within the TMNP Marine Protected Area." | A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level. | ABSTRACT: "A major aim of European agri-environment policy is the management of grassland for botanical diversity conservation and restoration, together with the delivery of ecosystem services including soil carbon (C) sequestration. To test whether management for biodiversity restoration has additional benefits for soil C sequestration, we investigated C and nitrogen (N) accumulation rates in soil and C and N pools in vegetation in a long-term field experiment (16 years) in which fertilizer application and plant seeding were manipulated. In addition, the abundance of the legume Trifolium pratense was manipulated for the last 2 years. To unravel the mechanisms underlying changes in soil C and N pools, we also tested for effects of diversity restoration management on soil structure, ecosystem respiration and soil enzyme activities…" AUTHOR'S DESCRIPTION: "Measurements were made on 36 plots of 3 x 3 m comprising two management treatments (and their controls) in a long-term multifactorial grassland restoration experiment which have successfully increased plant species diversity, namely the cessation of NPK fertilizer application and the addition of seed mixtures…" | A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level. | VELMA – Visualizing Ecosystems for Land Management Assessments - is a spatially distributed, eco-hydrological model that links a land surface hydrology model with a terrestrial biogeochemistry model for simulating the integrated responses of vegetation, soil, and water resources to interacting stressors. For example, VELMA can simulate how changes in climate and land use interact to affect soil water storage, surface and subsurface runoff, vertical drainage, evapotranspiration, vegetation and soil carbon and nitrogen dynamics, and transport of nitrate, ammonium, and dissolved organic carbon and nitrogen to water bodies. VELMA differs from other existing eco-hydrology models in its simplicity, flexibility, and theoretical foundation. The model has a user-friendly Graphics User Interface (GUI) for easy input of model parameter values. In addition, advanced visualization of simulation results can enhance understanding of results and underlying concepts. VELMA’s visualization and interactivity features are packaged in an open-source, open-platform programming environment (Java / Eclipse). The development team for VELMA version 2.0 includes Dr. Bob McKane and coworkers at the U.S. Environmental Protection Agency’s Western Ecology Division, Dr. Marc Stieglitz and coworkers at the Georgia Institute of Technology, and Dr. Feifei Pan at the University of North Texas. AUTHOR'S DESCRIPTION: "Understanding how disturbances such as harvest, fire and fertilization affect ecosystem services has been a major motivation in the development of VELMA. For example, how do disturbances such as forest harvest or the application of agronomic fertilizers affect hydrological and biogeochemical processes controlling water quality and quantity, carbon sequestration, production of greenhouse gases, etc.? Abdelnour et al. (2011, 2013) have already demonstrated the use of VELMA v1.0 to simulate the effects of forest clearcutting on ecohydrological processes that regulate a variety of ecosystem services. With the addition of a tissue-specific plant biomass (LSR) simulator and an enhanced GUI, VELMA v2.0 significantly expands the detail, flexibility, and ease of use for simulating disturbance effects. Currently available disturbance models include: - BurnDisturbanceModel, effects of fire. - GrazeDisturbanceModel, effects of grazing. - FertilizeLsrDisturbanceModel, effects of fertilizer applications. - HarvestLsrDisturbanceModel, effects of biomass harvest. Each of these disturbance models specifies where and when a disturbance event will occur. The Burn, Graze and Harvest models have options for specifying how much of each plant tissue and detritus pool (leaves, stems, roots) will be removed and where it goes (offsite and/or to a specified onsite C and N pools). The Fertilize model has options for applying nitrogen as ammonium, nitrate, urea and/or manure." | Land Use/Land Cover (LULC) provides provisional, supporting, cultural, and regulating ecosystem services that contribute to ecological environments, enhance human health and living, have economic advantages for sustaining living organisms. LULC transformation due to enormous urban expansion diminishing Ecosystem Services Values (ESVs) and discouraging sustainability. Though unplanned LULC transformation practice became more prevalent in developing countries, comprehensive assessment of LULC changes and their influences in ESVs are rarely attempted. This study aimed to illustrate and forecast the LULC changes and their influences on ESVs change in Jashore using remote sensing technologies. ESVs estimation and change analysis were conducted by utilizing -derived LULC data of the year 2000, 2010, and 2020 with the corresponding global value coefficients of each LULC type which are previously published. For simulating future LULC and ESVs, Land Change Modeler of TerrSet Geospatial Monitoring and Modeling Software was used in Multi-Layer Perceptron-Markov Chain and Artificial Neural Network method. The decline of agricultural land by 13.13% and waterbody by 5.79% has resulted in the reduction of total ESVs US$0.23 million (24.47%) during 2000–2020. The forecasted result shows that the built-up area will be dominant LULC in the future, and ESVs of provisioning and cultural services will be diminished by $0.107 million, $63400.3 by 2050 with the declination of agricultural, waterbody, vegetation, and vacant land covers. The study signifies the importance of a strategic rational land-use plan to strictly monitor and control the encroachment of built-up areas into vegetation, waterbodies, and agricultural land in addition to scientific mitigative policies for ensuring ecological sustainability. |
Specific Policy or Decision Context Cited
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This analysis provided input to government-led spatial planning and strategic environmental assessments in the study area. This region contains some of the last remaining forest habitat of the critically endangered Sumatran tiger, Panthera tigris sumatrae. | None provided | Future rock lobster fisheries management | None identified | None identified | None identified | None identified | N/A |
Biophysical Context
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Six watersheds in central Sumatra covering portions of Riau, Jambi and West Sumatra provinces. The Barisan mountain range comprises the western edge of the watersheds, while peat swamps predominate in the east. | No additional description provided | No additional description provided | restored, enhanced and created wetlands | Lolium perenne-Cynosorus cristatus grassland; The soil is a shallow brown-earth (average depth 28 cm) over limestone of moderate-high residual fertility. | restored, enhanced and created wetlands | No additional description provided | Jashore city, Bangladesh |
EM Scenario Drivers
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Baseline year 2008, future LULC Sumatra 2020 Roadmap (Vision), future LULC Government Spatial Plan | No scenarios presented | Fisheries exploitation; fishing vulnerability (of age classes) | Sites, function or habitat focus | Additional benefits due to biodiversity restoration practices | Sites, function or habitat focus | No scenarios presented | No scenarios presented |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method Only | Method + Application |
New or Pre-existing EM?
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Application of existing model | Application of existing model | Application of existing model | WESP - Urban Stormwater Treatment | New or revised model | New or revised model | New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Document ID for related EM
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Doc-315 | None | None | Doc-390 | None | Doc-390 | Doc-13 | Doc-317 | Doc-366 | Doc-359 | None |
EM ID for related EM
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EM-374 | None | None | EM-718 | EM-734 | None | EM-718 | EM-734 | EM-743 | EM-883 | EM-884 | EM-375 | EM-379 | EM-380 | EM-605 | EM-892 | None |
EM Modeling Approach
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Temporal Extent
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2008-2020 | 1978 - 2009 | 1986-2115 | 2010-2011 | 1990-2007 | 2010-2012 | Not applicable | 2000-2050 |
EM Time Dependence
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time-stationary | time-stationary | time-dependent | time-dependent | time-stationary | time-dependent | time-dependent | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | future time | past time | Not applicable | past time | Not applicable | both |
EM Time Continuity
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Not applicable | Not applicable | discrete | Not applicable | Not applicable | Not applicable | discrete | discrete |
EM Temporal Grain Size Value
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Not applicable | Not applicable | 1 | Not applicable | Not applicable | Not applicable | 1 | 10 |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Year | Not applicable | Not applicable | Not applicable | Day | Year |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Bounding Type
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Watershed/Catchment/HUC | Watershed/Catchment/HUC | Geopolitical | Multiple unrelated locations (e.g., meta-analysis) | Other | Multiple unrelated locations (e.g., meta-analysis) | Not applicable | Geopolitical |
Spatial Extent Name
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central Sumatra | Guanica Bay watershed | Table Mountain National Park Marine Protected Area | Wetlands in idaho | Colt Park meadows, Ingleborough National Nature Reserve, northern England | Wetlands in idaho | Not applicable | Jashore city, Bangladesh |
Spatial Extent Area (Magnitude)
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100,000-1,000,000 km^2 | 100-1000 km^2 | 100-1000 km^2 | 100,000-1,000,000 km^2 | <1 ha | 100,000-1,000,000 km^2 | Not applicable | 1000-10,000 km^2. |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable | Not applicable | area, for pixel or radial feature | Not applicable | area, for pixel or radial feature | map scale, for cartographic feature |
Spatial Grain Size
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30 m x 30 m | HUC | Not applicable | Not applicable | 3 m x 3 m | Not applicable | user defined | 30m |
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Computational Approach
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Analytic | Analytic | Numeric | Numeric | Analytic | Numeric | Numeric | Analytic |
EM Determinism
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deterministic | deterministic | deterministic | deterministic | stochastic | deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Model Calibration Reported?
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No | No | No | No | Not applicable | No | Not applicable | Yes |
Model Goodness of Fit Reported?
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No | No | No | No | Not applicable | No | Not applicable | Yes |
Goodness of Fit (metric| value | unit)
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None | None | None | None | None | None | None |
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Model Operational Validation Reported?
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No | No |
Yes ?Comment:A validation analysis was carried out running the model using data from 1880 to 2001, and then comparing the output for the adult population with the 2001 published data. |
No | No | No | Not applicable | Yes |
Model Uncertainty Analysis Reported?
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No | No | No | No | No | No | Not applicable | Unclear |
Model Sensitivity Analysis Reported?
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No | No | No | No | No | No | Not applicable | Unclear |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
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None |
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None |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
None | None |
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None | None | None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
Centroid Latitude
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0 | 17.96 | -34.18 | 44.06 | 54.2 | 44.06 | Not applicable | 23.95 |
Centroid Longitude
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102 | -67.02 | 18.35 | -114.69 | -2.35 | -114.69 | Not applicable | 89.12 |
Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | Not applicable | other |
Centroid Coordinates Status
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Provided | Estimated | Provided | Estimated | Provided | Estimated | Not applicable | Provided |
EM ID
em.detail.idHelp
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
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Inland Wetlands | Lakes and Ponds | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Barren | Inland Wetlands | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Barren | Near Coastal Marine and Estuarine | Inland Wetlands | Agroecosystems | Grasslands | Inland Wetlands | Terrestrial Environment (sub-classes not fully specified) | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
em.detail.specificEnvTypeHelp
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104 land use land cover classes | Tropical terrestrial | Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf | created, restored and enhanced wetlands | fertilized grassland (historically hayed) | created, restored and enhanced wetlands | Terrestrial environment sub-classes | Urban city |
EM Ecological Scale
em.detail.ecoScaleHelp
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Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
em.detail.idHelp
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EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
EM Organismal Scale
em.detail.orgScaleHelp
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Community | Not applicable | Individual or population, within a species | Not applicable | Community | Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
None Available | None Available |
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None Available | None Available | None Available | None Available | None Available |
EnviroAtlas URL
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
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<a target="_blank" rel="noopener noreferrer" href="https://www.epa.gov/eco-research/national-ecosystem-services-classification-system-nescs-plus">National Ecosystem Services Classification System (NESCS) Plus</a>
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
EM-349 ![]() |
EM-432 |
EM-541 ![]() |
EM-729 ![]() |
EM-735 ![]() |
EM-760 ![]() |
EM-887 | EM-979 |
None |
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None | None | None | None |
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