EcoService Models Library (ESML)
Home
Search EMs
My
EMs 
Learn about
ESML
View ESML Data Maploading
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.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735 
|
EM-774
|
EM-893 | EM-972 |
|
EM Short Name
em.detail.shortNameHelp
?
|
ARIES viewsheds, Puget Sound Region, USA | Reef density of E. striatus, St. Croix, USVI | C sequestration in grassland restoration, England | Plant-pollinator networks at reclaimed mine, USA | HWB indicator-ADI, Great Lakes, USA | NC HUC-12 conservation prioritization tool |
|
EM Full Name
em.detail.fullNameHelp
?
|
ARIES (Artificial Intelligence for Ecosystem Services) Scenic viewsheds for homeowners, Puget Sound Region, Washington, USA | Relative density of Epinephelus striatus (on reef), St. Croix, USVI | Carbon sequestration in grassland diversity restoration, England | Restoration of plant-pollinator networks at reclaimed strip mine, Ohio, USA | Human well being indicator- Area Deprivation Index (ADI) , Great Lakes waterfront, USA | NC HUC-12 conservation prioritization tool v. 1.0, North Carolina, USA |
|
EM Source or Collection
em.detail.emSourceOrCollectionHelp
?
|
ARIES | US EPA | None | None | US EPA | None |
|
EM Source Document ID
|
302 | 335 | 396 | 397 |
422 ?Comment:Has not been submitted to Journal yet, but has been peer reviewed by EPA inhouse and outside reviewers |
443 ?Comment:Doc 444 is an additional source for this EM |
|
Document Author
em.detail.documentAuthorHelp
?
|
Bagstad, K.J., Villa, F., Batker, D., Harrison-Cox, J., Voigt, B., and Johnson, G.W. | Yee, S. H., Dittmar, J. A., and L. M. Oliver | 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 | Cusser, S. and K. Goodell | Ted R. Angradi, Jonathon J. Launspach, and Molly J. Wick | Warnell, K., I. Golden, and C. Canfield |
|
Document Year
em.detail.documentYearHelp
?
|
2014 | 2014 | 2011 | 2013 | None | 2023 |
|
Document Title
em.detail.sourceIdHelp
?
|
From theoretical to actual ecosystem services: mapping beneficiaries and spatial flows in ecosystem service assessments | Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI | Additional carbon sequestration benefits of grassland diversity restoration | Diversity and distribution of floral resources influence the restoration of plant-pollinator networks on a reclaimed strip mine | Human well-being and natural capital indictors for Great Lakes waterfront revitalization | Conservation planning tools for NC's people & nature |
|
Document Status
em.detail.statusCategoryHelp
?
|
Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed but unpublished (explain in Comment) | Peer reviewed and published |
|
Comments on Status
em.detail.commentsOnStatusHelp
?
|
Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Journal manuscript submitted or in review | Webpage |
Software and Access
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
| http://aries.integratedmodelling.org/ | Not applicable | Not applicable | Not applicable | Not applicable | https://prioritizationcobenefitstool.users.earthengine.app/view/nc-huc-12-conservation-prioritizer | |
|
Contact Name
em.detail.contactNameHelp
?
|
Ken Bagstad | Susan H. Yee | Gerlinde B. De Deyn |
Sarah Cusser ?Comment:Department of Evolution, Ecology, and Organismal Biology, Ohio State University, 318 West 12th Avenue, Columbus, OH 43202, U.S.A. |
Ted Angradi | Katie Warnell |
|
Contact Address
|
Geosciences and Environmental Change Science Center, US Geological Survey | US EPA, Office of Research and Development, NHEERL, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | Dept. of Terrestrial Ecology, Netherlands Institute of Ecology, P O Box 40, 6666 ZG Heteren, The Netherlands | Department of Evolution, Ecology, and Behavior, School of Biological Sciences, The University of Texas at Austin, 100 East 24th Street Stop A6500, Austin, TX 78712-1598, U.S.A. | USEPA, Center for Computational Toxicology and Ecology, Great Lakes Toxicology and Ecology Division, Duluth, MN 55804 | Not reported |
|
Contact Email
|
kjbagstad@usgs.gov | yee.susan@epa.gov | g.dedeyn@nioo.knaw.nl; gerlindede@gmail.com | sarah.cusser@gmail.com | tedangradi@gmail.com | katie.warnell@duke.edu |
EM Description
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Summary Description
em.detail.summaryDescriptionHelp
?
|
ABSTRACT: "...new modeling approaches that map and quantify service-specific sources (ecosystem capacity to provide a service), sinks (biophysical or anthropogenic features that deplete or alter service flows), users (user locations and level of demand), and spatial flows can provide a more complete understanding of ecosystem services. Through a case study in Puget Sound, Washington State, USA, we quantify and differentiate between the theoretical or in situ provision of services, i.e., ecosystems’ capacity to supply services, and their actual provision when accounting for the location of beneficiaries and the spatial connections that mediate service flows between people and ecosystems... Using the ARtificial Intelligence for Ecosystem Services (ARIES) methodology we map service supply, demand, and flow, extending on simpler approaches used by past studies to map service provision and use." AUTHOR'S NOTE: "Within a given viewshed, our models quantified the contribution of viewshed source features such as mountains and water bodies and sinks that detract from view quality, including obstructions or visual blight such as industrial or commercial development. Source, sink, and use locations were linked by a flow model that computed visibility along lines of sight from use locations to scenic viewshed features. The model includes a distance decay function that accounts for changes with distance in the value of views. We then computed the ratio of actual to theoretical provision of scenic views to compare the values accruing to homeowners relative to those for the entire landscape." | ABSTRACT: "...We investigated and compared a number of existing methods for quantifying ecological integrity, shoreline protection, recreational opportunities, fisheries production, and the potential for natural products discovery from reefs. Methods were applied to mapping potential ecosystem services production around St. Croix, U.S. Virgin Islands. Overall, we found that a number of different methods produced similar predictions." AUTHOR'S DESCRIPTION: "A number of methods have been developed for linking biophysical attributes of reef condition, such as reef structural complexity, fish biomass, or species richness, to provisioning of ecosystem goods and services (Principe et al., 2012). We investigated the feasibility of using existing methods and data for mapping production of reef ecosystem goods and services. We applied these methods toward mapping potential ecosystem goods and services production in St. Croix, U.S. Virgin Islands (USVI)...For each of the five categories of ecosystem services, we chose a suite of models and indices for estimating potential production based on relative ease of implementation, consisting of well-defined parameters, and likely availability of input data, to maximize potential for transferability to other locations. For each method, we assembled the necessary reef condition and environmental data as spatial data layers for St. Croix (Table1). The coastal zone surrounding St. Croix was divided into 10x10 m grid cells, and production functions were applied to quantify ecosystem services provisioning in each grid cell...A number of recreational activities are associated directly or indirectly with coral reefs including scuba diving, snorkeling, surfing, underwater photography, recreational fishing, wildlife viewing, beach sunbathing and swimming, and beachcombing (Principe et al., 2012)…Synthesis of scientific literature and expert opinion can be used to estimate the relative potential for recreational opportunities across different benthic habitat types (Mumby et al., 2008). For each grid cell, we estimated the contribution of coral reefs to recreational opportunities as the overall weighted average of relative magnitudes of contribution across habitat types within that grid cell: Relative recreational opportunity j = ΣiciMij where ci is the fraction of area within each grid cell for each habitat type i (dense, medium dense, or sparse seagrass, mangroves, sand, macroalgae, A.palmata, Montastraea reef, patch reef, and dense or sparse gorgonians), and Mij is the magnitude associated with each habitat for a given metric j: density of E. striatus" | 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…" | ABSTRACT: "Plant–pollinator mutualisms are one of the several functional relationships that must be reinstated to ensure the long-term success of habitat restoration projects. These mutualisms are unlikely to reinstate themselves until all of the resource requirements of pollinators have been met. By meeting these requirements, projects can improve their long-term success. We hypothesized that pollinator assemblage and structure and stability of plant–pollinator networks depend both on aspects of the surrounding landscape and of the restoration effort itself. We predicted that pollinator species diversity and network stability would be negatively associated with distance from remnant habitat, but that local floral diversity might rescue pollinator diversity and network stability in locations distant from the remnant. We created plots of native prairie on a reclaimed strip mine in central Ohio, U.S.A. that ranged in floral diversity and isolation from the remnant habitat. We found that the pollinator diversity declined with distance from the remnant habitat. Furthermore, reduced pollinator diversity in low floral diversity plots far from the remnant habitat was associated with loss of network stability. High floral diversity, however, compensated for losses in pollinator diversity in plots far from the remnant habitat through the attraction of generalist pollinators. Generalist pollinators increased network connectance and plant-niche overlap. Asa result, network robustness of high floral diversity plots was independent of isolation. We conclude that the aspects of the restoration effort itself, such as floral community composition, can be successfully tailored to incorporate the restoration of pollinators and improve success given a particular landscape context." | ABSTRACT: "Revitalization of natural capital amenities at the Great Lakes waterfront can result from sediment remediation, habitat restoration, climate resilience projects, brownfield reuse, economic redevelopment and other efforts. Practical indicators are needed to assess the socioeconomic and cultural benefits of these investments. We compiled U.S. census-tract scale data for five Great Lakes communities: Duluth/Superior, Green Bay, Milwaukee, Chicago, and Cleveland. We downloaded data from the US Census Bureau, Centers for Disease Control and Prevention, Environmental Protection Agency, National Oceanic and Atmospheric Administration, and non-governmental organizations. We compiled a final set of 19 objective human well-being (HWB) metrics and 26 metrics representing attributes of natural and 7 seminatural amenities (natural capital). We rated the reliability of metrics according to their consistency of correlations with metric of the other type (HWB vs. natural capital) at the census-tract scale, how often they were correlated in the expected direction, strength of correlations, and other attributes. Among the highest rated HWB indicators were measures of mean health, mental health, home ownership, home value, life success, and educational attainment. Highest rated natural capital metrics included tree cover and impervious surface metrics, walkability, density of recreational amenities, and shoreline type. Two ociodemographic covariates, household income and population density, had a strong influence on the associations between HWB and natural capital and must be included in any assessment of change in HWB benefits in the waterfront setting. Our findings are a starting point for applying objective HWB and natural capital indicators in a waterfront revitalization context." | ABSTRACT: "Conservation organizations and land trusts in North Carolina are increasingly focused on how their work can contribute to both human and ecosystem resilience and adaptation to climate change, as well as directly mitigate climate change through carbon storage and sequestration. Recent state executive and legislative actions also underscore the importance of natural systems for climate adaptation and mitigation, and may provide additional funding for conservation and restoration for those purposes in the near term. To make it more efficient for conservation organizations working in North Carolina to consider a broad suite of conservation benefits in their work, the Conservation Trust for North Carolina and the Nicholas Institute for Energy, Environment & Sustainability at Duke University have developed two online tools for identifying priority areas for conservation action and estimating benefit metrics for specific properties. The conservation prioritization tool finds the sub-watersheds in North Carolina with the greatest potential to provide a set of user-selected conservation benefits. It allows users to identify priority areas for future conservation work within the entire state or a defined region. This high-level tool allows for quick and easy exploration without the need for spatial analysis expertise." |
|
Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
?
|
None identified | None identified | None identified | None identified | None identified | Allows users to prioritize HUCs within their area of interest based on their conservation goals. |
|
Biophysical Context
|
No additional description provided | No additional description provided | Lolium perenne-Cynosorus cristatus grassland; The soil is a shallow brown-earth (average depth 28 cm) over limestone of moderate-high residual fertility. | The site was surface mined for coal until the mid-1980s and soon after recontoured and seeded with a low diversity of non-native grasses and forbes. The property is grassland in a state of arrested succession, unable to support tree growth because of shallow, infertile soils. | Waterfront districts on south Lake Michigan and south lake Erie | No additional description provided |
|
EM Scenario Drivers
em.detail.scenarioDriverHelp
?
|
No scenarios presented | No scenarios presented | Additional benefits due to biodiversity restoration practices | No scenarios presented | N/A | No scenarios presented |
EM Relationship to Other EMs or Applications
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
?
|
Method + Application | Method + Application | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method Only |
|
New or Pre-existing EM?
em.detail.newOrExistHelp
?
|
New or revised model | Application of existing model | 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.detail.relatedEmHelp
?
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Document ID for related EM
em.detail.relatedEmDocumentIdHelp
?
|
Doc-303 | Doc-305 | None | None | None | Doc-422 |
Doc-444 ?Comment:The secondary source, document 444, is the website for running the tool. |
|
EM ID for related EM
em.detail.relatedEmEmIdHelp
?
|
None | None | None | None | EM-886 | EM-888 | EM-889 | EM-890 | EM-891 | EM-894 | EM-895 | None |
EM Modeling Approach
EM Relationship to Time
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
EM Temporal Extent
em.detail.tempExtentHelp
?
|
1992-2006 | 2006-2007, 2010 | 1990-2007 | 2009-2010 | 2022 | Not applicable |
|
EM Time Dependence
em.detail.timeDependencyHelp
?
|
time-stationary | time-stationary | time-stationary | time-stationary | time-stationary | time-stationary |
|
EM Time Reference (Future/Past)
em.detail.futurePastHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
|
EM Time Continuity
em.detail.continueDiscreteHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
|
EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
|
EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Spatial Extent
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Bounding Type
em.detail.boundingTypeHelp
?
|
Watershed/Catchment/HUC | Physiographic or ecological | Other | Physiographic or ecological | Geopolitical | Not applicable |
|
Spatial Extent Name
em.detail.extentNameHelp
?
|
Puget Sound Region | Coastal zone surrounding St. Croix | Colt Park meadows, Ingleborough National Nature Reserve, northern England | The Wilds | Great Lakes waterfront | Not applicable |
|
Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
?
|
10,000-100,000 km^2 | 100-1000 km^2 | <1 ha | 1-10 km^2 | 1000-10,000 km^2. | Not applicable |
Spatial Distribution of Computations
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
EM Spatial Distribution
em.detail.distributeLumpHelp
?
|
spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) |
|
Spatial Grain Type
em.detail.spGrainTypeHelp
?
|
area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | Not applicable | map scale, for cartographic feature |
|
Spatial Grain Size
em.detail.spGrainSizeHelp
?
|
200m x 200m | 10 m x 10 m | 3 m x 3 m | 10 m radius | Not applicable | HUC 12 |
EM Structure and Computation Approach
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
EM Computational Approach
em.detail.emComputationalApproachHelp
?
|
Analytic | Analytic | Analytic | Analytic | Numeric | Other or unclear (comment) |
|
EM Determinism
em.detail.deterStochHelp
?
|
stochastic | deterministic | stochastic | deterministic | deterministic | deterministic |
|
Statistical Estimation of EM
em.detail.statisticalEstimationHelp
?
|
|
|
|
|
|
|
Model Checking Procedures Used
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Model Calibration Reported?
em.detail.calibrationHelp
?
|
No | Yes | Not applicable | Not applicable | No | Not applicable |
|
Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
?
|
No | No | Not applicable | Not applicable | No | Not applicable |
|
Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
?
|
None | None | None | None | None | None |
|
Model Operational Validation Reported?
em.detail.validationHelp
?
|
No | Yes | No | Yes | No | Not applicable |
|
Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
?
|
No | No | No | Yes | No | Not applicable |
|
Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
?
|
No | No | No | No | Yes | Not applicable |
|
Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
em.detail.relationToSpaceTerrestrialHelp
?
| EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
None |
|
|
|
None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
em.detail.relationToSpaceMarineHelp
?
| EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
|
None | None | None | None |
Centroid Lat/Long (Decimal Degree)
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
Centroid Latitude
em.detail.ddLatHelp
?
|
48 | 17.73 | 54.2 | 39.82 | 42.26 | Not applicable |
|
Centroid Longitude
em.detail.ddLongHelp
?
|
-123 | -64.77 | -2.35 | -81.75 | -87.84 | Not applicable |
|
Centroid Datum
em.detail.datumHelp
?
|
WGS84 | WGS84 | WGS84 | WGS84 | WGS84 | Not applicable |
|
Centroid Coordinates Status
em.detail.coordinateStatusHelp
?
|
Estimated | Estimated | Provided | Provided | Estimated | Not applicable |
Environments and Scales Modeled
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
?
|
Lakes and Ponds | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Near Coastal Marine and Estuarine | Agroecosystems | Grasslands | Grasslands | Terrestrial Environment (sub-classes not fully specified) | Aquatic Environment (sub-classes not fully specified) | Terrestrial Environment (sub-classes not fully specified) |
|
Specific Environment Type
em.detail.specificEnvTypeHelp
?
|
Terrestrial environment surrounding a large estuary | Coral reefs | fertilized grassland (historically hayed) | Grassland | Lake Michigan & Lake Erie waterfront | Terrestrial and freshwater aquatic |
|
EM Ecological Scale
em.detail.ecoScaleHelp
?
|
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 corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is coarser than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
em.detail.nameOfOrgsOrGroupsHelp
?
|
EM ID
em.detail.idHelp
?
|
EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
EM Organismal Scale
em.detail.orgScaleHelp
?
|
Not applicable | Guild or Assemblage | Community | Species | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
?
| EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
| 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.detail.cicesHelp
?
| EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
|
|
|
None | None |
<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>
fegs1Help
?
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
fegs2Help
?
| EM-419 | EM-453 |
EM-735
|
EM-774
|
EM-893 | EM-972 |
|
|
None | None | None | None |