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:

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Comparing:

EM-83
EM-93
EM-194
EM-306
EM-836
EM-851
EM-938

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EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Short Name em.detail.shortNameHelp ?	Soil carbon and plant traits, Central French Alps	Stream nitrogen removal, Mississippi R. basin, USA	Coral and land development, St.Croix, VI, USA	Urban Temperature, Baltimore, MD, USA	Bird abundance on restored landfills, UK	InVEST Coastal Vulnerability, New York, USA	OpenNSPECT v. 1.2
EM Full Name em.detail.fullNameHelp ?	Soil carbon potential estimated from plant functional traits, Central French Alps	Stream nitrogen removal, Upper Mississippi, Ohio and Missouri River sub-basins, USA	Coral colony density and land development, St.Croix, Virgin Islands, USA	Urban Air Temperature Change, Baltimore, MD, USA	Bird abundance on restored landfills compared to paired reference sites, East Midlands, UK	InVEST Coastal Vulnerability, Jamaica Bay, New York, USA	OpenNSPECT v. 1.2
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	EU Biodiversity Action 5	US EPA	US EPA	i-Tree \| USDA Forest Service	None	InVEST	None
EM Source Document ID	260	52	96	217	406	410 ? Comment: Sharp R, Tallis H, Ricketts T, Guerry A, Wood S, Chaplin-Kramer R, et al. InVEST User?s Guide. User Guide. Stanford (CA): The Natural Capital Project, Stanford University, University of Minnesota, The Nature Conservancy, World Wildlife Fund; 2015.	431
Document Author em.detail.documentAuthorHelp ?	Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R.	Hill, B. and Bolgrien, D.	Oliver, L. M., Lehrter, J. C. and Fisher, W. S.	Heisler, G. M., Ellis, A., Nowak, D. and Yesilonis, I.	Rahman, M. L., S. Tarrant, D. McCollin, and J. Ollerton	Hopper T. and M. S. Meixler	Eslinger, David L., H. Jamieson Carter, Matt Pendleton, Shan Burkhalter, Margaret Allen
Document Year em.detail.documentYearHelp ?	2011	2011	2011	2016	2011	2016	2012
Document Title em.detail.sourceIdHelp ?	Using plant functional traits to understand the landscape distribution of multiple ecosystem services	Nitrogen removal by streams and rivers of the Upper Mississippi River basin	Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands	Modeling and imaging land-cover influences on air-temperature in and near Baltimore, MD	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	Modeling coastal vulnerability through space and time	“OpenNSPECT: The Open-source Nonpoint Source Pollution and Erosion Comparison Tool.” NOAA Office for Coastal Management, Charleston, South Carolina. Accessed (11/2022) at https://coast.noaa.gov/digitalcoast/tools/opennspect.html
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	Peer reviewed and published	Peer reviewed and published
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published journal manuscript	Webpage

Software and Access

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	https://naturalcapitalproject.stanford.edu/software/invest-models/coastal-vulnerability	https://coast.noaa.gov/digitalcoast/tools/opennspect.html
Contact Name em.detail.contactNameHelp ?	Sandra Lavorel	Brian Hill	Leah Oliver	Gordon M. Heisler	Lutfor Rahman	Thomas Hopper	Not reported
Contact Address	Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France	Mid-Continent Ecology Division NHEERL, ORD. USEPA 6201 Congdon Blvd. Duluth, MN 55804, USA	National Health and Environmental Research Effects Laboratory	5 Moon Library, c/o SUNY-ESF, Syracuse, NY 13210	Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton NN2 6JD, UK	Not reported	NOAA Coastal Services Center, 2234 South Hobson Avenue Charleston, South Carolina 29405-2413
Contact Email	sandra.lavorel@ujf-grenoble.fr	hill.brian@epa.gov	leah.oliver@epa.gov	gheisler@fs.fed.us	lutfor.rahman@northampton.ac.uk	Tjhop1123@gmail.com	Not reported

EM Description

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Summary Description em.detail.summaryDescriptionHelp ?	ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services." AUTHOR'S DESCRIPTION: "The soil carbon ecosystem service map was a simple sum of maps for relevant Ecosystem Properties (produced in related EMs) after scaling to a 0–100 baseline and trimming outliers to the 5–95% quantiles (Venables&Ripley 2002)…Coefficients used for the summing of individual ecosystem properties to the soil carbon ecosystem service are based on stakeholders’ perceptions, given positive (+1) or negative (-1) contributions."	ABSTRACT: "We used stream chemistry and hydrogeomorphology data from 549 stream and 447 river sites to estimate NO3–N removal in the Upper Mississippi, Missouri, and Ohio Rivers. We used two N removal models to predict NO3–N input and removal. NO3–N input ranged from 0.01 to 338 kg/kmd in the Upper Mississippi River to 0.01–54 kg/ kmd in the Missouri River. Cumulative river network NO3–N input was 98700–101676 Mg/year in the Ohio River, 85,961–89,288 Mg/year in the Upper Mississippi River, and 59,463–61,541 Mg/year in the Missouri River. NO3–N output was highest in the Upper Mississippi River (0.01–329 kg/kmd ), followed by the Ohio and Missouri Rivers (0.01–236 kg/kmd ) sub-basins. Cumulative river network NO3–N output was 97,499 Mg/year for the Ohio River, 84,361 Mg/year for the Upper Mississippi River, and 59,200 Mg/year for the Missouri River. Proportional NO3–N removal (PNR) based on the two models ranged from 0.01 to 0.28. NO3–N removal was inversely correlated with stream order, and ranged from 0.01 to 8.57 kg/kmd in the Upper Mississippi River to 0.001–1.43 kg/kmd in the Missouri River. Cumulative river network NO3–N removal predicted by the two models was: Upper Mississippi River 4152 and 4152 Mg/year, Ohio River 3743 and 378 Mg/year, and Missouri River 2,277 and 197 Mg/year. PNR removal was negatively correlated with both stream order (r = −0.80–0.87) and the percent of the catchment in agriculture (r = −0.38–0.76)."	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)	An empirical model for predicting below-canopy air temperature differences is developed for evaluating urban structural and vegetation influences on air temperature in and near Baltimore, MD. AUTHOR'S DESCRIPTION: "The study . . . Developed an equation for predicting air temperature at the 1.5m height as temperature difference, T, between a reference weather station and other stations in a variety of land uses. Predictor variables were derived from differences in land cover and topography along with forcing atmospheric conditions. The model method was empirical multiple linear regression analysis.. . Independent variables included remotely sensed tree cover, impervious cover, water cover, descriptors of topography, an index of thermal stability, vapor pressure deficit, and antecedent precipitation."	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)."	ABSTRACT: "Coastal ecosystems experience a wide range of stressors including wave forces, storm surge, sea-level rise, and anthropogenic modification and are thus vulnerable to erosion. Urban coastal ecosystems are especially important due to the large populations these limited ecosystems serve. However, few studies have addressed the issue of urban coastal vulnerability at the landscape scale with spatial data that are finely resolved. The purpose of this study was to model and map coastal vulnerability and the role of natural habitats in reducing vulnerability in Jamaica Bay, New York, in terms of nine coastal vulnerability metrics (relief, wave exposure, geomorphology, natural habitats, exposure, exposure with no habitat, habitat role, erodible shoreline, and surge) under past (1609), current (2015), and future (2080) scenarios using InVEST 3.2.0. We analyzed vulnerability results both spatially and across all time periods, by stakeholder (ownership) and by distance to damage from Hurricane Sandy. We found significant differences in vulnerability metrics between past, current and future scenarios for all nine metrics except relief and wave exposure…"	"This open-source version of the Nonpoint Source Pollution and Erosion Comparison Tool is used to investigate potential water quality impacts from climate change and development to other land uses. The downloadable tool is designed to be broadly applicable for coastal and noncoastal areas alike. Tool functions simulate erosion, pollution, and the accumulation from overland flow. OpenNSPECT uses spatial elevation data to calculate flow direction and flow accumulation throughout a watershed. To do this, land cover, precipitation, and soils data are processed to estimate runoff volume at both the local and watershed levels. Coefficients representing the contribution of each land cover class to the expected pollutant load are also applied to land cover data to approximate total pollutant loads. These coefficients are taken from published sources or can be derived from local water quality studies. The output layers display estimates of runoff volume, pollutant loads, pollutant concentration, and total sediment yield. Requires MapWindow GIS v.4.8.8 (open source software)"
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	None identified	Not applicable	Not applicable	None identified	None identified	None identified	None identified
Biophysical Context	Elevations ranging from 1552 m to 2442 m, on predominantly south-facing slopes	Agricultural landuse , 1st-10th order streams	nearshore; <1.5 km offshore; <12 m depth	One airport site, one urban site, one site in deciduous leaf litter, and four sites in short grass ground cover. Measured sky view percentages ranged from 6% at the woods site, to 96% at the rural open site.	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).	Jamaica Bay, New York, situated on the southern shore of Long Island, and characterized by extensive coastal ecosystems in the central bay juxtaposed with a largely urbanized shoreline containing fragmented and fringing coastal habitat.	No additional description provided
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	Not applicable	Not applicable	No scenarios presented	No scenarios presented	Past (1609), current (2015), and future (2080) scenarios	No scenarios presented

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application	Method + Application	Method Only	Method + Application (multiple runs exist) View EM Runs	Method Only
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	New or revised model	New or revised model	New or revised model	New or revised model	Application of existing 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-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-260	Doc-154 \| Doc-155	None	Doc-220 \| Doc-219 \| Doc-218	None	Doc-408	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	EM-65 \| EM-66 \| EM-68 \| EM-69 \| EM-70 \| EM-71 \| EM-79 \| EM-80 \| EM-81 \| EM-82	None	None	None	EM-837	EM-849	EM-940

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Temporal Extent em.detail.tempExtentHelp ?	Not reported	2000-2008	2006-2007	May 5-Sept 30 2006	Not applicable	1609-2080	Not applicable
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-stationary	time-stationary	time-dependent	time-stationary	time-stationary	time-stationary
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	Not applicable	Not applicable	future time	Not applicable	Not applicable	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	Not applicable	Not applicable	discrete	Not applicable	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	Not applicable	1	Not applicable	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Not applicable	Not applicable	Hour	Not applicable	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Bounding Type em.detail.boundingTypeHelp ?	Physiographic or Ecological	Watershed/Catchment/HUC	Physiographic or Ecological	Geopolitical	Multiple unrelated locations (e.g., meta-analysis)	Physiographic or ecological	Not applicable
Spatial Extent Name em.detail.extentNameHelp ?	Central French Alps	Upper Mississippi, Ohio and Missouri River sub-basins	St. Croix, U.S. Virgin Islands	Baltimore, MD	East Midland	Jamaica Bay, Long Island, New York	Not applicable
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	10-100 km^2	>1,000,000 km^2	10-100 km^2	100-1000 km^2	1000-10,000 km^2.	10-100 km^2	Not applicable

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
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 distributed (in at least some cases) ? Comment: by coastal segment	spatially distributed (in at least some cases)
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	length, for linear feature (e.g., stream mile)	Not applicable	area, for pixel or radial feature	other (specify), for irregular (e.g., stream reach, lake basin)	length, for linear feature (e.g., stream mile)	area, for pixel or radial feature
Spatial Grain Size em.detail.spGrainSizeHelp ?	20 m x 20 m	1 km	Not applicable	10m x 10m	multiple unrelated sites	80 m	30 m

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Analytic	Analytic	Analytic	Analytic	Analytic	Analytic
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	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	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Model Calibration Reported? em.detail.calibrationHelp ?	No	No	Yes	Yes	Not applicable	No	Not applicable
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	No	Yes	Yes	Not applicable	No	Not applicable
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	Adjusted R squared \| 0.50 \| unitless	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	No	No	No	Not applicable	No	Not applicable
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	No	Yes	Yes	No	Not applicable	No	Not applicable
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	Unclear	No	No	Not applicable	No	Not applicable
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	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-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Europe France	North America United States New York Montana Indiana Kentucky Minnesota Kansas Alabama Nebraska Pennsylvania Iowa Colorado Illinois Missouri Ohio Georgia	None	North America United States Maryland	Europe United Kingdom	North America United States New York	None

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

EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
None	None	Tropical Atlantic West Tropical Atlantic Tropical Southwestern Atlantic	None	None	Temperate North Atlantic Northwest Atlantic Cold Temperate Northwest Atlantic Virginian	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
Centroid Latitude em.detail.ddLatHelp ?	45.05	36.98	17.75	39.28	52.22	40.61	Not applicable
Centroid Longitude em.detail.ddLongHelp ?	6.4	-89.13	-64.75	-76.62	-0.91	-73.84	Not applicable
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	NAD83	WGS84	WGS84	WGS84	Not applicable
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Provided	Estimated	Estimated	Estimated	Estimated	Provided	Not applicable

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Agroecosystems \| Grasslands	Rivers and Streams	Near Coastal Marine and Estuarine	Terrestrial Environment (sub-classes not fully specified) \| Created Greenspace \| Atmosphere	Created Greenspace \| Grasslands	Near Coastal Marine and Estuarine	Aquatic Environment (sub-classes not fully specified) \| Near Coastal Marine and Estuarine \| Terrestrial Environment (sub-classes not fully specified)
Specific Environment Type em.detail.specificEnvTypeHelp ?	Subalpine terraces, grasslands, and meadows.	Not applicable	stony coral reef	Urban landscape and surrounding area	restored landfills and conserved grasslands	Coastal	Coastal and non-coastal
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecological scale is coarser 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 corresponds to the Environmental Sub-class	Ecological scale corresponds to the Environmental Sub-class	Ecological scale is finer than that of the Environmental Sub-class

Scale and taxa of organisms modeled

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
EM Organismal Scale em.detail.orgScaleHelp ?	Community	Not applicable	Guild or Assemblage	Not applicable	Individual or population, within a species	Not applicable	Not applicable

Taxonomic level and name of organisms or groups identified

EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
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 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)	None Available	None Available

EnviroAtlas URL

EM-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
None Available	National Hydrography Dataset Plus (NHD PlusV2), Total Annual Reduced Nitrogen Deposition, Total Annual Nitrogen Deposition	None Available	Average Annual Precipitation, Percent Impervious Area	None Available	National Hydrography Dataset Plus (NHD PlusV2), Average Annual Precipitation	Average Annual Precipitation

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-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
[Ecosystem] Regulation & Maintenance Mediation of waste, toxics and other nuisances Mediation by ecosystems Filtration/sequestration/storage/accumulation by ecosystems	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Water conditions Chemical condition of freshwaters	[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 Atmospheric composition and climate regulation Micro and regional climate regulation	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	[Ecosystem] Regulation & Maintenance Mediation of flows Liquid flows Flood protection	[Ecosystem] Regulation & Maintenance Mediation of flows Liquid flows Hydrological cycle and water flow maintenance Mediation of waste, toxics and other nuisances Mediation by ecosystems Filtration/sequestration/storage/accumulation by ecosystems

<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-83	EM-93	EM-194	EM-306	EM-836	EM-851	EM-938
None	Rivers and Streams (111) Water (3) Liquid water Quality Indicator	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Quality Indicator	Atmosphere Atmosphere (1) Air Site Characteristic Indicator	None	None	None