EcoService Models Library (ESML)

Compare EMs

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 Criteria

Comparing:

EM-106
EM-456
EM-541
EM-760
EM-836

Add EM to Compare:

EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Short Name em.detail.shortNameHelp ?	Value of Habitat for Shrimp, Campeche, Mexico	Reef dive site favorability, St. Croix, USVI	InVEST fisheries, lobster, South Africa	WESP: Marsh & wet meadow, ID, USA	Bird abundance on restored landfills, UK
EM Full Name em.detail.fullNameHelp ?	Value of Habitat for Shrimp, Campeche, Mexico	Dive site favorability (reef), St. Croix, USVI	Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa	WESP: Seasonally flooded marsh & wet meadow, Idaho, USA	Bird abundance on restored landfills compared to paired reference sites, East Midlands, UK
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	None	US EPA	InVEST	None	None
EM Source Document ID	227	335	349 ? Comment: Supplemented with the InVEST Users Guide fisheries.	393 ? Comment: Additional data came from electronic appendix provided by author Chris Murphy.	406
Document Author em.detail.documentAuthorHelp ?	Barbier, E. B., and Strand, I.	Yee, S. H., Dittmar, J. A., and L. M. Oliver	Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby	Murphy, C. and T. Weekley	Rahman, M. L., S. Tarrant, D. McCollin, and J. Ollerton
Document Year em.detail.documentYearHelp ?	1998	2014	2018	2012	2011
Document Title em.detail.sourceIdHelp ?	Valuing mangrove-fishery linkages: A case study of Campeche, Mexico	Comparison of methods for quantifying reef ecosystem services: A case study mapping services for St. Croix, USVI	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.	The conservation value of restored landfill sites in the East Midlands, UK for supporting bird communities in the East Midlands, UK for supporting bird communities
Document Status em.detail.statusCategoryHelp ?	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published report	Published journal manuscript

Software and Access

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	https://www.naturalcapitalproject.org/invest/	Not applicable	Not applicable
Contact Name em.detail.contactNameHelp ?	E.B. Barbier	Susan H. Yee	Michelle Ward	Chris Murphy	Lutfor Rahman
Contact Address	Environment Department, University of York, York YO1 5DD, UK	US EPA, Office of Research and Development, NHEERL, 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	Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton NN2 6JD, UK
Contact Email	Not reported	yee.susan@epa.gov	m.ward@uq.edu.au	chris.murphy@idfg.idaho.gov	lutfor.rahman@northampton.ac.uk

EM Description

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
Summary Description em.detail.summaryDescriptionHelp ?	AUTHOR'S DESCRIPTION: "We assume throughout that shrimp harvesting occurs through open access management that yields production which is exported internationally, and we modify a standard open access fishery model to account explicitly for the effect of the mangrove area on carrying capacity and thus production.We derive the conditions determining the long-run equilibrium of the model, including the comparative static effects of a change in mangrove area, on this equilibrium. Through regressing a relationship between shrimp harvest, effort and mangrove area over time, we estimate parameters based on the combinations of the bioeconomic parameters of the model determining the comparative statics. By incorporating additional economic data, we are able to simulate an estimate of the effect of changes in mangrove area in Laguna de Terminos on the production and value of shrimp harvests in Campeche state." (153)	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)…In lieu of surveys of diver opinion, recreational opportunities can also be estimated by actual field data of coral condition at preferred dive sites. A few studies have directly examined links between coral condition and production of recreational opportunities through field monitoring in an attempt to validate perceptions of recreational quality (Pendleton, 1994; Williams and Polunin, 2002; Leeworthy et al., 2004; Leujakand Ormond, 2007; Uyarraetal., 2009). Uyarraetal. (2009) used surveys to determine reef attributes related to diver perceptions of most and least favorite dive sites. Field data was used to narrow down the suite of potential preferred attributes to those that reflected actual site condition. We combined these attributes to form an index of dive site favorability: Dive site favorability = ΣipiRi where pi is the proportion of respondents indicating each attribute i that affected dive enjoyment positively. Ri is the mean relative magnitude of measured variables used to quantify each descriptive attribute i, including ‘fish abundance’ (pi=0.803), quantified by number of fish schools and fish species richness, and	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: "There has been a rapid decline of grassland bird species in the UK over the last four decades. In order to stem declines in biodiversity such as this, mitigation in the form of newly created habitat and restoration of degraded habitats is advocated in the UK biodiversity action plan. One potential restored habitat that could support a number of bird species is re-created grassland on restored landfill sites. However, this potential largely remains unexplored. In this study, birds were counted using point sampling on nine restored landfill sites in the East Midlands region of the UK during 2007 and 2008. The effects of restoration were investigated by examining bird species composition, richness, and abundance in relation to habitat and landscape structure on the landfill sites in comparison to paired reference sites of existing wildlife value. Twelve bird species were found in total and species richness and abundance on restored landfill sites was found to be higher than that of reference sites. Restored landfill sites support both common grassland bird species and also UK Red List bird species such as skylark Alauda arvensis, grey partridge Perdix perdix, lapwing Vanellus vanellus, tree sparrow, Passer montanus, and starling Sturnus vulgaris. Size of the site, percentage of bare soil and amount of adjacent hedgerow were found to be the most influential habitat quality factors for the distribution of most bird species. Presence of open habitat and crop land in the surrounding landscape were also found to have an effect on bird species composition. Management of restored landfill sites should be targeted towards UK Red List bird species since such sites could potentially play a significant role in biodiversity action planning." AUTHOR'S DESCRIPTION: "Mean number of birds from multiple visits were used for data analysis. To analyse the data generalized linear models (GLMs) were constructed to compare local habitat and landscape parameters affecting different species, and to establish which habitat and landscape characteristics explained significant changes in the frequency of occurrence for each species. To ensure analyses focused on resident species, habitat associations were modelled for those seven bird species which were recorded at least three times in the surveys. The analysis was carried out with the software R (R Development Core Team 2003). Nonsignificant predictors (independent variables) were removed in a stepwise manner (least significant factor first). For distribution pattern of bird species, data were initially analysed using detrended correspondence analysis. Redundancy analysis (RDA) was performed on the same data using CANOCO for Windows version 4.0 (ter Braak and Smilauer 2002)."
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	None identified	None identified	Future rock lobster fisheries management	None identified	None identified
Biophysical Context	Gulf of Mexico; mangrove-lagoon system	No additional description provided	No additional description provided	restored, enhanced and created wetlands	The study area covered mainly Northamptonshire and parts of Bedfordshire, Buckinghamshire and Warwickshire, ranging from 51o58’44.74” N to 52o26’42.18” N and 0o27’49.94” W to 1o19’57.67” W. This region has countryside of low, undulating hills separated by valleys and lies entirely within the great belt of scarplands formed by rocks of Jurassic age which stretch across England from Yorkshire to Dorset (Beaver 1943; Sutherland 1995; Wilson 1995).
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	No scenarios presented	Fisheries exploitation; fishing vulnerability (of age classes)	Sites, function or habitat focus	No scenarios presented

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
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 Only
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	Application of existing model	Application of existing 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 em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	None	None	None	Doc-390	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	EM-185 \| EM-319	None	None	EM-718 \| EM-734 \| EM-743	EM-837

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Temporal Extent em.detail.tempExtentHelp ?	1980-1990	2006-2007, 2010	1986-2115	2010-2012	Not applicable
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-stationary	time-dependent	time-dependent	time-stationary
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	Not applicable	future time	past time	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	Not applicable	discrete	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	1	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Year	Not applicable	Year	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
Bounding Type em.detail.boundingTypeHelp ?	Physiographic or Ecological	Physiographic or ecological	Geopolitical	Multiple unrelated locations (e.g., meta-analysis)	Multiple unrelated locations (e.g., meta-analysis)
Spatial Extent Name em.detail.extentNameHelp ?	Laguna de Terminos Mangrove system	Coastal zone surrounding St. Croix	Table Mountain National Park Marine Protected Area	Wetlands in idaho	East Midland
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	100-1000 km^2	100-1000 km^2	100-1000 km^2	100,000-1,000,000 km^2	1000-10,000 km^2.

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Spatial Distribution em.detail.distributeLumpHelp ?	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)
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable	Not applicable	other (specify), for irregular (e.g., stream reach, lake basin)
Spatial Grain Size em.detail.spGrainSizeHelp ?	1 km x 1 km	10 m x 10 m	Not applicable	Not applicable	multiple unrelated sites

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Analytic	Numeric	Numeric	Analytic
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
Model Calibration Reported? em.detail.calibrationHelp ?	Yes	Yes	No	No	Not applicable
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	Yes	No	No	No	Not applicable
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	Adjusted R^2 \| 0.745 \| Not applicable F-stat \| 30.216 \| Not applicable SE of regression \| 639745.7 \| Not applicable	None	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	Yes	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	Not applicable
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	Yes	No	No	No	Not applicable
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	Yes	No	No	No	Not applicable
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Unclear	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-106	EM-456	EM-541	EM-760	EM-836
North America Mexico	None	None	North America United States Idaho	Europe United Kingdom

Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)

EM-106	EM-456	EM-541	EM-760	EM-836
Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Southern Gulf of Mexico	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Eastern Caribbean	Temperate South Africa South Africa Benguela Namaqua	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
Centroid Latitude em.detail.ddLatHelp ?	18.61	17.73	-34.18	44.06	52.22
Centroid Longitude em.detail.ddLongHelp ?	-91.55	-64.77	18.35	-114.69	-0.91
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	WGS84
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Estimated	Provided	Estimated	Estimated

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Near Coastal Marine and Estuarine	Near Coastal Marine and Estuarine	Near Coastal Marine and Estuarine	Inland Wetlands	Created Greenspace \| Grasslands
Specific Environment Type em.detail.specificEnvTypeHelp ?	Mangrove	Coral reefs	Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf	created, restored and enhanced wetlands	restored landfills and conserved grasslands
EM Ecological Scale em.detail.ecoScaleHelp ?	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

Scale and taxa of organisms modeled

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	EM-106	EM-456	EM-541	EM-760	EM-836
EM Organismal Scale em.detail.orgScaleHelp ?	Guild or Assemblage	Guild or Assemblage	Individual or population, within a species	Not applicable	Individual or population, within a species

Taxonomic level and name of organisms or groups identified

EM-106	EM-456	EM-541	EM-760	EM-836
other Shrimp	None Available	Species West Coast Rock Lobster (Jasus lalandii)	None Available	Species Grey partridge (Perdix perdix) Collared dove (Streptopelia decaocto) Woodpidgeon (Columba palumbus) Lapwing (Vanellus vanellus) Magpie (Pica pica) Dunnock (Prunella modularis) Starling (Sturnus vulgaris) Skylark (Alauda arvensis) Pheasant (Phasianus colchicus) Blackbird (Turdus merula) Carrion crow (Corvus corone) Tree sparrow (Passer montanus)

EnviroAtlas URL

EM-106	EM-456	EM-541	EM-760	EM-836
GAP Ecological Systems, Big game hunting recreation demand	None Available	Big game hunting recreation demand	Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass	None Available

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-106	EM-456	EM-541	EM-760	EM-836
[Ecosystem] Provisioning Nutrition Biomass Wild animals and their outputs	[Ecosystem] Cultural Physical and intellectual interactions with biota, ecosystems, and land-/seascapes [environmental settings] Physical and experiential interactions Experiential use of plants, animals and land-/seascapes in different environmental settings	[Ecosystem] Provisioning Nutrition Biomass Wild animals and their outputs	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats Water conditions Chemical condition of freshwaters Mediation of flows Liquid flows Flood protection Hydrological cycle and water flow maintenance Mass flows Mass stabilisation and control of erosion rates Mediation of waste, toxics and other nuisances Mediation by biota Filtration/sequestration/storage/accumulation by micro-organisms, algae, plants, and animals	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats

<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-106	EM-456	EM-541	EM-760	EM-836
Near Coastal Marine/Estuarine (113) Fauna (4) Shrimp Stock Indicator	Near Coastal Marine/Estuarine (113) Composite (8) Presence of environmental class/subclass Quality Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Stock Indicator	None	None

EcoService Models Library (ESML)

Compare EMs

EM Variables by Variable Role

EM Variables by Category

All EM Descriptors

EM Descriptors by Modeling Concepts

Comparing:

EM Identity and Description

Comment:

Comment:

Related EMs (for example, other versions or derivations of this EM) described in ESML

EM Modeling Approach

Comment:

EM Locations, Environments, Ecology

Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])

Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)

Centroid Lat/Long (Decimal Degree)

Scale of differentiation of organisms modeled

Taxonomic level and name of organisms or groups identified

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)

<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)