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.

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Comparing:

EM-92
EM-121
EM-194
EM-369
EM-697
EM-842

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EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Short Name em.detail.shortNameHelp ?	Runoff potential of pesticides, Europe	Landscape importance for recreation, Europe	Coral and land development, St.Croix, VI, USA	Envision, Puget Sound, WA, USA	Floral resources on landfill sites, United Kingdom	Horned lark abundance, Piedmont region, USA
EM Full Name em.detail.fullNameHelp ?	Runoff potential of pesticides, Europe	Landscape importance for recreation, Europe	Coral colony density and land development, St.Croix, Virgin Islands, USA	Envision, Puget Sound, WA, USA	Floral resources on landfill sites, East Midlands, United Kingdom	Horned lark abundance, Piedmont ecoregion, USA
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	None	EU Biodiversity Action 5	US EPA	Envision	None	None
EM Source Document ID	254	228	96	313 ? Comment: Doc 314 is a secondary source. It is a webpage guide intended to provide support for developing an application using ENVISION.	389	405
Document Author em.detail.documentAuthorHelp ?	Schriever, C. A., and Liess, M.	Haines-Young, R., Potschin, M. and Kienast, F.	Oliver, L. M., Lehrter, J. C. and Fisher, W. S.	Bolte, J. and Vache, K.	Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin	Riffel, S., Scognamillo, D., and L. W. Burger
Document Year em.detail.documentYearHelp ?	2007	2012	2011	2010	2013	2008
Document Title em.detail.sourceIdHelp ?	Mapping ecological risk of agricultural pesticide runoff	Indicators of ecosystem service potential at European scales: Mapping marginal changes and trade-offs	Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands	Envisioning Puget Sound Alternative Futures: PSNERP Final Report	Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects	Effects of the Conservation Reserve Program on northern bobwhite and grassland birds
Document Status em.detail.statusCategoryHelp ?	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published	Documentation is 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	Published journal manuscript

Software and Access

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	Not applicable	http://envision.bioe.orst.edu	Not applicable	Not applicable
Contact Name em.detail.contactNameHelp ?	Carola Alexandra Schriever	Marion Potschin	Leah Oliver	John Bolte ? Comment: Phone# 541-737-2041	Sam Tarrant	Sam Riffell
Contact Address	Helmholtz Centre for Environmental Research - UFZ, Department of System Ecotoxicology, Permoserstrasse 15, 04318 Leipzig, Germany	Centre for Environmental Management, School of Geography, University of Nottingham, NG7 2RD, United Kingdom	National Health and Environmental Research Effects Laboratory	Oregon State University, Dept. of Biological & Ecological Engineering, 116C Gilmore Hall, Corvallis, OR 97333	RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K.	Department of Wildlife & Fisheries, Mississippi State University, Mississippi State, MS 39762, USA
Contact Email	carola.schriever@ufz.de	marion.potschin@nottingham.ac.uk	leah.oliver@epa.gov	boltej@engr.orst.edu	sam.tarrant@rspb.org.uk	sriffell@cfr.msstate.edu

EM Description

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Summary Description em.detail.summaryDescriptionHelp ?	ABSTRACT: "The approach is based on the runoff potential (RP) of stream sites, by a spatially explicit calculation based on pesticide use, precipitation, topography, land use and soil characteristics in the near-stream environment. The underlying simplified model complies with the limited availability and resolution of data at larger scales." AUTHOR'S DESCRIPTION: "The RP is based on a mathematical model that describes runoff losses of a compound with generalized properties and which was developed from a proposal by the Organisation for Economic Co-operation and Development (OECD) for estimating dissolved runoff inputs of a pesticide into surface waters (OECD, 1998)...The runoff model underlying RP calculates the dissolved amount of a generic substance that was applied in the near environment of a stream site and that is expected to reach the stream site during one rainfall event. The dissolved amount results from a single application in the near-stream environment (i.e., a two-sided 100-m stream corridor extending for 1500 m upstream of the site) and is the amount of applied substance in the designated corridor reduced due to the influence of the site-specific key environmental factors precipitation, soil characteristics, topography, and plant interception."	ABSTRACT: "The study focuses on the EU-25 plus Switzerland and Norway, and develops the methodology proposed by Kienast et al. (2009), which uses expert-and literature-driven modelling methods. The methods are explored in relation to mapping and assessing … “Recreation” ... The potential to deliver services is assumed to be influenced by land-use ... and bioclimatic and landscape properties such as mountainous terrain, adjacency to coastal and wetland ecosystems, as well as adjacency to landscape protection zones." AUTHOR'S DESCRIPTION: "Recreation… is broadly defined as all areas where landscape properties are favourable for active recreation purposes."	AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294)	SUMMARY: "...the Puget Sound Nearshore Ecosystem Restoration Project, completed an analysis of alternative future regional trajectories of landscape change for the Puget Sound region. This effort developed three scenarios of change: 1) Status Quo, reflecting a continuation of current trends in the region, 2) Managed Growth, reflecting the adoption of an aggressive set of land use management policies focusing on protecting and restoring ecosystem function and concentrating growth within Urban Growth Areas (UGA) and near regional growth centers, and 3) Unmanaged Growth, reflecting a relaxation of land use restrictions with limited protection of ecosystem functions. Analyses assumed a fixed population growth rate across all three scenarios, defined by the Washington Office of Financial Management county level growth estimates. Scenarios were generated using a spatially- and temporally-explicit alternative futures analysis model, Envision, previously developed by Oregon State University researchers. The model accepts as input a vector-based representation of the landscape and associated datasets describing relevant landscape characteristics, descriptors of various processes influencing landscape change, and a set of policies, or decision alternatives, which reflect scenario-specific land management alternatives. The model generates 1) a set of spatial coverages (maps) reflecting scenario outcomes of a variety of landscape variables, most notably land use/land cover, shoreline modifications, and population projections, and 2) a set of summary statistics describing landscape change variables summarized across spatial reporting units. Analyses were run on each of such sub-basins in the Puget Sound, and aggregated to providing Sound-wide results. This information is being used by PSNERP to project future impairment of ecosystem functions, goods, and services. The Puget Sound Nearshore Ecosystem project data also provide inputs to calculate aspects of future nearshore process degradation. Impairment and degradation are primary factors being used to define future conditions for the PSNERP General Investigation Study." AUTHOR'S DESCRIPTION: "In this report, we document the application of an alternative futures analysis framework that incorporates these capabilities to the analysis of alternative future trajectories in the Puget Sound region. This framework, Envision (Bolte et al, 2007; Hulse et al. 2008) is a spatially and temporally explicit, standards-based, open source toolset specifically designed to facilitate alternative futures analyses. It employs a multiagent-based modeling approach that contains a robust capability for defining alternative management strategies and scenarios, incorporating a variety of landscape change processes, and creating maps of alternative landscape trajectories, expressed though a variety of metrics defined in an application-specific way." ABOUT ENVISION (ENVISION WEBSITE): "Central to Envision, and conceived at the s	ABSTRACT: "...Restored landfill sites are a significant potential reserve of semi-natural habitat, so their conservation value for supporting populations of pollinating insects was here examined by assessing whether the plant and pollinator assemblages of restored landfill sites are comparable to reference sites of existing wildlife value. Floral characteristics of the vegetation and the species richness and abundance of flower-visiting insect assemblages were compared between nine pairs of restored landfill sites and reference sites in the East Midlands of the United Kingdom, using standardized methods over two field seasons. …" AUTHOR'S DESCRIPTION: "The selection criteria for the landfill sites were greater than or equal to 50% of the site restored (to avoid undue influence from ongoing landfilling operations), greater than or equal to 0.5 ha in area and restored for greater than or equal to 4 years to allow establishment of vegetation. Comparison reference sites were the closest grassland sites of recognized nature conservation value, being designated as either Local Nature Reserves (LNRs) or Sites of Special Scientific Interest (SSSI)…All sites were surveyed three times each during the fieldwork season, in Spring, Summer, and Autumn. Paired sites were sampled on consecutive days whenever weather conditions permitted to reduce temporal bias. Standardized plant surveys were used (Dicks et al. 2002; Potts et al. 2006). Transects (100 × 2m) were centered from the approximate middle of the site and orientated using randomized bearing tables. All flowering plants were identified to species level… A “floral cover” method to represent available floral resources was used which combines floral abundance with inflorescence size. Mean area of the floral unit from above was measured for each flowering plant species and then multiplied by their frequencies." "Insect pollinated flowering plant species composition and floral abundance between sites by type were represented by non-metric multidimensional scaling (NMDS)...This method is sensitive to showing outliers and the distance between points shows the relative similarity (McCune & Grace 2002; Ollerton et al. 2009)." (This data is not entered into ESML)	ABSTRACT:"The Conservation Reserve Program (CRP) has converted just over 36 million acres of cropland into potential wildlife habitat, primarily grassland. Thus, the CRP should benefit grassland songbirds, a group of species that is declining across the United States and is of conservation concern. Additionally, the CRP is an important part of multi-agency, regional efforts to restore northern bobwhite populations. However, comprehensive assessments of the wildlife benefits of CRP at regional scales are lacking. We used Breeding Bird Survey and National Resources Inventory data to assess the potential for the CRP to benefit northern bobwhite and other grassland birds with overlapping ranges and similar habitat associations. We built regression models for 15 species in seven different ecological regions. Forty-nine of 108 total models contained significant CRP effects (P < 0.05), and 48 of the 49 contained positive effects. Responses to CRP varied across ecological regions. Only eastern meadowlark was positively related to CRP in all the ecological regions, and western meadowlark was the only species never related to CRP. CRP was a strong predictor of bird abundance compared to other land cover types. The potential for CRP habitat as a regional conservation tool to benefit declining grassland bird populations should continue to be assessed at a variety of spatial scales. We caution that bird-CRP relations varied from region to region and among species. Because the NRI provides relatively coarse resolution information on CRP, more detailed information about CRP habitats (spatial arrangement, age of the habitat (time since planting), specific conservation practices used) should be included in future assessments to fully understand where and to what extent CRP can benefit grassland birds."
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	European Commission Water Framework Directive (WFD, Directive 2000/60/EC)	None identified	Not applicable	None identified	None identified	None reported
Biophysical Context	Not applicable	No additional description provided	nearshore; <1.5 km offshore; <12 m depth	No additional description provided	No additional description provided	Conservation Reserve Program lands left to go fallow
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	No scenarios presented	Not applicable	Alternative future land management strategies (status quo, managed growth, unmanaged growth)	No scenarios presented	N/A

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application	Method + Application (multiple runs exist) View EM Runs	Method + Application (multiple runs exist) View EM Runs	Method + Application
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	New or revised model	New or revised 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-92	EM-121	EM-194	EM-369	EM-697	EM-842
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-255 \| Doc-256 \| Doc-257	Doc-231 \| Doc-228	None	Doc-314 \| Doc-47 ? Comment: Doc 314 is a secondary source. It is a webpage guide intended to provide support for developing an application using ENVISION.	None	Doc-405
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	EM-99 \| EM-119 \| EM-120 \| EM-162 \| EM-164 \| EM-165 \| EM-122 \| EM-123 \| EM-124 \| EM-125 \| EM-170 \| EM-171	None	EM-12 \| EM-333	EM-709	EM-831 \| EM-838 \| EM-839 \| EM-840 \| EM-841 \| EM-843 \| EM-844 \| EM-845 \| EM-846 \| EM-847

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Temporal Extent em.detail.tempExtentHelp ?	2000	2000	2006-2007	2000-2060	2007-2008	2008
EM Time Dependence em.detail.timeDependencyHelp ?	time-dependent	time-stationary	time-stationary	time-dependent	time-stationary	time-stationary
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	future time	Not applicable	Not applicable	future time	Not applicable	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	discrete	Not applicable	Not applicable	discrete	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	1	Not applicable	Not applicable	1	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Day	Not applicable	Not applicable	Year	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	Geopolitical	Physiographic or Ecological	Watershed/Catchment/HUC	Multiple unrelated locations (e.g., meta-analysis)	Physiographic or ecological
Spatial Extent Name em.detail.extentNameHelp ?	EU-15	The EU-25 plus Switzerland and Norway	St. Croix, U.S. Virgin Islands	Puget Sound watershed	East Midlands	Piedmont Ecoregion
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	>1,000,000 km^2	>1,000,000 km^2	10-100 km^2	10,000-100,000 km^2	1000-10,000 km^2.	100,000-1,000,000 km^2

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
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 distributed (in at least some cases)	spatially distributed (in at least some cases)	spatially lumped (in all cases)
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable	Irregular	other (specify), for irregular (e.g., stream reach, lake basin)	Not applicable
Spatial Grain Size em.detail.spGrainSizeHelp ?	10 km x 10 km	1 km x 1 km	Not applicable	Varies	multiple unrelated locations	Not applicable

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Logic- or rule-based	Analytic	Numeric	Analytic	Analytic
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic	deterministic
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	None	None	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Model Calibration Reported? em.detail.calibrationHelp ?	No	No	Yes	Unclear	Not applicable	Yes
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	No	Yes	Not applicable	Not applicable	No
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	None	None	R squared (for coral density) \| 0.90 \| Not applicable p-value \| 0.0002 \| unitless	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	Yes	No	Not applicable	Not applicable	No
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	Yes	No	Yes	Not applicable	Not applicable	No
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	Yes	No	No	Not applicable	Not applicable	Yes
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	No	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-92	EM-121	EM-194	EM-369	EM-697	EM-842
Europe United Kingdom Portugal Spain Greece Austria Netherlands Sweden Belgium Ireland Luxembourg Finland Denmark Italy France Germany	Europe Cyprus Portugal Malta Greece Austria Latvia Netherlands Sweden Ireland Luxembourg Poland Slovakia Slovenia France Lithuania Hungary Switzerland Spain Czech Republic Belgium Norway Finland Denmark Italy Germany Estonia	None	North America United States Washington	Europe United Kingdom	North America United States North Carolina Georgia Alabama Maryland New Jersey South Carolina Pennsylvania

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

EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
None	None	Tropical Atlantic West Tropical Atlantic Tropical Southwestern Atlantic	Temperate North Pacific Northeast Pacific Cold Temperate Northeast Pacific Oregon, Washington, Vancouver Coast and Shelf	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Centroid Latitude em.detail.ddLatHelp ?	50.01	50.53	17.75	47.58	52.22	36.23
Centroid Longitude em.detail.ddLongHelp ?	4.67	7.6	-64.75	-122.32	-0.91	-81.9
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	NAD83	WGS84	WGS84	WGS84
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Estimated	Estimated	Estimated	Estimated	Estimated

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Rivers and Streams \| Forests \| Agroecosystems \| Grasslands \| Scrubland/Shrubland	Aquatic Environment (sub-classes not fully specified) \| Terrestrial Environment (sub-classes not fully specified)	Near Coastal Marine and Estuarine	Aquatic Environment (sub-classes not fully specified) \| Near Coastal Marine and Estuarine \| Terrestrial Environment (sub-classes not fully specified)	Created Greenspace \| Grasslands	Grasslands
Specific Environment Type em.detail.specificEnvTypeHelp ?	Arable lands in near-stream environments	Not applicable	stony coral reef	Pacific NW US region, coastal to montane, urban to rural	restored landfills and grasslands	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 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 corresponds to the Environmental Sub-class

Scale and taxa of organisms modeled

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	Not applicable	Guild or Assemblage	Not applicable	Individual or population, within a species	Species

Taxonomic level and name of organisms or groups identified

EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
None Available	None Available	Genus Acropora Porites spp. Diploria spp. Species Mycetophylia lamarckiana Mycetophylia ferox Montastrea cavernosa Dichocoenia stokesii Meandrina meandrites Agaricia tenuifolia Agaricia fragilis Montastrea annularis Agaricia agaricites Dendrogyra cylindricus Millepora complanata Montastrea faveolata Porites astreoides Montastrea franksii	None Available	Species Rhinanthus minor Picris echioides Lotus corniculatus Cardamine flexuosa Ranunculus acris Ranunculus bulbosus Stellaria graminea Trifolium dubium Picris hieracioides Ranunculus repens Trifolium repens Galium verum Cirsium arvense	Species Horned lark

EnviroAtlas URL

EM-92	EM-121	EM-194	EM-369	EM-697	EM-842
Average Annual Precipitation, Stream Length Impaired by Pesticides, The Watershed Boundary Dataset (WBD), Hectares of Vegetable Crops	Percent GAP Status 1 & 2	None Available	Dasymetric Allocation of Population, GAP Ecological Systems, Stream Length, Percent GAP Status 1 & 2, Acres of Land Enrolled in the Conservation Reserve Program (CRP), The Watershed Boundary Dataset (WBD), Percent Impervious Area	GAP Ecological Systems	U.S. EPA (Omernik) ecoregions

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-92	EM-121	EM-194	EM-369	EM-697	EM-842
None	[Ecosystem] Cultural Physical and intellectual interactions with biota, ecosystems, and land-/seascapes [environmental settings] Physical and experiential interactions Physical use of land-/seascapes in different environmental settings Experiential use of plants, animals and land-/seascapes in different environmental settings Intellectual and representative interactions Aesthetic Entertainment	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	None	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	[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-92	EM-121	EM-194	EM-369	EM-697	EM-842
None	Rivers and Streams (111) Composite (8) Presence of environmental class/subclass Quality Indicator Barren / Rock and Sand (28) Composite (8) Presence of environmental class/subclass Quality Indicator Forests (21) Composite (8) Presence of environmental class/subclass Quality Indicator Tundra (25) Composite (8) Presence of environmental class/subclass Quality Indicator Scrubland/Shrubland (24) Composite (8) Presence of environmental class/subclass Quality Indicator Grasslands (23) Composite (8) Presence of environmental class/subclass Quality Indicator Wetlands (12) Composite (8) Presence of environmental class/subclass Quality Indicator Lakes and Ponds (112) Composite (8) Presence of environmental class/subclass Quality Indicator Urban/Suburban (27) Composite (8) Presence of environmental class/subclass Quality Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Quality Indicator	None	None	Grasslands (23) Fauna (4) Birds Stock Indicator

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

Comment:

EM Modeling Approach

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)