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-63
EM-119
EM-178
EM-380
EM-702
EM-837

Add EM to Compare:

EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Short Name em.detail.shortNameHelp ?	EnviroAtlas - Natural biological nitrogen fixation	Landscape importance for wildlife products, Europe	Natural attenuation by soil, The Netherlands	VELMA plant-soil, Oregon, USA	Northern Shoveler recruits, CREP wetlands, IA, USA	Bird species diversity on restored landfills, UK
EM Full Name em.detail.fullNameHelp ?	US EPA EnviroAtlas - BNF (Natural biological nitrogen fixation), USA	Landscape importance for wildlife products, Europe	Natural attenuation capacity of the soil, The Netherlands	VELMA (Visualizing Ecosystems for Land Management Assessments) plant-soil, Oregon, USA	Northern Shoveler duck recruits, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA	Bird species diversity on restored landfills compared to paired reference sites, East Midlands, UK
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	US EPA \| EnviroAtlas	EU Biodiversity Action 5	None	US EPA	None	None
EM Source Document ID	262 ? Comment: EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM.	228	287	317	372 ? Comment: Document 373 is a secondary source for this EM.	406
Document Author em.detail.documentAuthorHelp ?	US EPA Office of Research and Development - National Exposure Research Laboratory	Haines-Young, R., Potschin, M. and Kienast, F.	van Wijnen, H.J., Rutgers, M., Schouten, A.J., Mulder, C., de Zwart, D., and Breure, A.M.	Abdelnour, A., McKane, R. B., Stieglitz, M., Pan, F., and Chen, Y.	Otis, D. L., W. G. Crumpton, D. Green, A. K. Loan-Wilsey, R. L. McNeely, K. L. Kane, R. Johnson, T. Cooper, and M. Vandever	Rahman, M. L., S. Tarrant, D. McCollin, and J. Ollerton
Document Year em.detail.documentYearHelp ?	2013	2012	2012	2013	2010	2011
Document Title em.detail.sourceIdHelp ?	EnviroAtlas - National	Indicators of ecosystem service potential at European scales: Mapping marginal changes and trade-offs	How to calculate the spatial distribution of ecosystem services - Natural attenuation as example from the Netherlands	Effects of harvest on carbon and nitrogen dynamics in a Pacific Northwest forest catchment	Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt	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	Peer reviewed and published
Comments on Status em.detail.commentsOnStatusHelp ?	Published on US EPA EnviroAtlas website	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published report	Published journal manuscript

Software and Access

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	https://www.epa.gov/enviroatlas	Not applicable	Not applicable	Bob McKane, VELMA Team Lead, USEPA-ORD-NHEERL-WED, Corvallis, OR (541) 754-4631; mckane.bob@epa.gov	Not applicable	Not applicable
Contact Name em.detail.contactNameHelp ?	EnviroAtlas Team ? Comment: Additional contact: Jana Compton, EPA	Marion Potschin	H.J. van Wijnen	Alex Abdelnour	David Otis	Lutfor Rahman
Contact Address	Not reported	Centre for Environmental Management, School of Geography, University of Nottingham, NG7 2RD, United Kingdom	National Institute for Public Health and the Environment, P.O. Box 1, 3720 BA Bilthoven, The Netherlands	Dept. of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta, GA 30332-0355, USA	U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University	Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton NN2 6JD, UK
Contact Email	enviroatlas@epa.gov	marion.potschin@nottingham.ac.uk	harm.van.wijnen@rivm.nl	abdelnouralex@gmail.com	dotis@iastate.edu	lutfor.rahman@northampton.ac.uk

EM Description

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
Summary Description em.detail.summaryDescriptionHelp ?	DATA FACT SHEET: "This EnviroAtlas national map displays the rate of biological nitrogen (N) fixation (BNF) in natural/semi-natural ecosystems within each watershed (12-digit HUC) in the conterminous United States (excluding Hawaii and Alaska) for the year 2006. These data are based on the modeled relationship of BNF with actual evapotranspiration (AET) in natural/semi-natural ecosystems. The mean rate of BNF is for the 12-digit HUC, not to natural/semi-natural lands within the HUC." "BNF in natural/semi-natural ecosystems was estimated using a correlation with actual evapotranspiration (AET). This correlation is based on a global meta-analysis of BNF in natural/semi-natural ecosystems. AET estimates for 2006 were calculated using a regression equation describing the correlation of AET with climate and land use/land cover variables in the conterminous US. Data describing annual average minimum and maximum daily temperatures and total precipitation at the 2.5 arcmin (~4 km) scale for 2006 were acquired from the PRISM climate dataset. The National Land Cover Database (NLCD) for 2006 was acquired from the USGS at the scale of 30 x 30 m. BNF in natural/semi-natural ecosystems within individual 12-digit HUCs was modeled with an equation describing the statistical relationship between BNF (kg N ha-1 yr-1) and actual evapotranspiration (AET; cm yr–1) and scaled to the proportion of non-developed and non-agricultural land in the 12-digit HUC." EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM."	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 … “Wildlife Products” . . . The potential to deliver services is assumed to be influenced by (a) land-use, (b) net primary production, and (c) 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: "Wildlife Products…includes the provisioning of all non-edible raw material products that are gained through non-agriculutural practices or which are produced as a by-product of commercial and non-commercial forests, primarily in non-intensively used land or semi-natural and natural areas."	ABSTRACT: "Maps play an important role during the entire process of spatial planning and bring ecosystem services to the attention of stakeholders' negotiation more easily. As example we show the quantification of the ecosystem service ‘natural attenuation of pollutants’, which is a service necessary to keep the soil clean for production of safe food and provision of drinking water, and to provide a healthy habitat for soil organisms to support other ecosystem services. A method was developed to plot the relative measure of the natural attenuation capacity of the soil in a map. Several properties of Dutch soils were related to property-specific reference values and subsequently combined into one proxy for the natural attenuation of pollutants." AUTHOR'S DESCRIPTION: "The natural attenuation capacity that is modeled in this study must be seen as a measure that describes the ‘biodegradation capacity’ of the soil, including biodegradation of all types of contaminants"	ABSTRACT: "We used a new ecohydrological model, Visualizing Ecosystems for Land Management Assessments (VELMA), to analyze the effects of forest harvest on catchment carbon and nitrogen dynamics. We applied the model to a 10 ha headwater catchment in the western Oregon Cascade Range where two major disturbance events have occurred during the past 500 years: a stand-replacing fire circa 1525 and a clear-cut in 1975. Hydrological and biogeochemical data from this site and other Pacific Northwest forest ecosystems were used to calibrate the model. Model parameters were first calibrated to simulate the postfire buildup of ecosystem carbon and nitrogen stocks in plants and soil from 1525 to 1969, the year when stream flow and chemistry measurements were begun. Thereafter, the model was used to simulate old-growth (1969–1974) and postharvest (1975–2008) temporal changes in carbon and nitrogen dynamics…" AUTHOR'S DESCRIPTION: "The soil column model consists of three coupled submodels:...a plant-soil model (Figure (A3)) that simulates ecosystem carbon storage and the cycling of C and N between a plant biomass layer and the active soil pools. Specifically, the plant-soil model simulates the interaction among aboveground plant biomass, soil organic carbon (SOC), soil nitrogen including dissolved nitrate (NO3), ammonium (NH4), and organic nitrogen, as well as DOC (equations (A7)–(A12)). Daily atmospheric inputs of wet and dry nitrogen deposition are accounted for in the ammonium pool of the shallow soil layer (equation (A13)). Uptake of ammonium and nitrate by plants is modeled using a Type II Michaelis-Menten function (equation (A14)). Loss of plant biomass is simulated through a density-dependent mortality. The mortality rate and the nitrogen uptake rate mimic the exponential increase in biomass mortality and the accelerated growth rate, respectively, as plants go through succession and reach equilibrium (equations (A14)–(A18)). Vertical transport of nutrients from one layer to another in a soil column is a function of water drainage (equations (A19)–(A22)). Decomposition of SOC follows first-order kinetics controlled by soil temperature and moisture content as described in the terrestrial ecosystem model (TEM) of Raich et al. [1991] (equations (A23)–(A26)). Nitrification (equations (A27)–(A30)) and denitrification (equations (A31)–(A34)) were simulated using the equations from the generalized model of N2 and N2O production of Parton et al. [1996, 2001] and Del Grosso et al. [2000]. [12] The soil column model is placed within a catchment framework to create a spatially distributed model applicable to watersheds and landscapes. Adjacent soil columns interact with each other through the downslope lateral transport of water and nutrients (Figure (A1)). Surface and subsurface lateral flow are routed using a multiple flow direction method [Freeman, 1991; Quinn et al., 1991]. As with vertical drainage of soil water, lateral subsurface downslope flow i	ABSTRACT: "Our initial primary objective (Progress Report I) was prediction of environmental services provided by the 27 Iowa Conservation Reserve Enhancement Program (CREP) wetland sites that had been completed by 2007 in the Prairie Pothole Region of northcentral Iowa. The sites contain 102.4 ha of wetlands and 377.4 ha of associated grassland buffers…" AUTHOR'S DESCRIPTION: "The first phase of the U.S. Fish and Wildlife Service task was to evaluate the contribution of the 27 approved sites to migratory birds breeding in the Prairie Pothole Region of Iowa. To date, evaluation has been completed for 7 species of waterfowl and 5 species of grassland birds. All evaluations were completed using existing models that relate landscape composition to bird populations. As such, the first objective was to develop a current land cover geographic information system (GIS) that reflected current landscape conditions including the incorporation of habitat restored through the CREP program. The second objective was to input landscape variables from our land cover GIS into models to estimate various migratory bird population parameters (i.e. the number of pairs, individuals, or recruits) for each site. Recruitment for the 27 sites was estimated for Mallards, Blue-winged Teal, Northern Shoveler, Gadwall, and Northern Pintail according to recruitment models presented by Cowardin et al. (1995). Recruitment was not estimated for Canada Geese and Wood Ducks because recruitment models do not exist for these species. Variables used to estimate recruitment included the number of pairs, the composition of the landscape in a 4-square mile area around the CREP wetland, species-specific habitat preferences, and species- and habitat-specific clutch success rates. Recruitment estimates were derived using the following equations: Recruits = 2Rn where, 2 = constant based on the assumption of equal sex ratio at hatch, n = number of breeding pairs estimated using the pairs equation previously outlined, R = Recruitment rate as defined by Cowardin and Johnson (1979) where, R = HZB/2 where, H = hen success (see Cowardin et al. (1995) for methods used to calculate H, which is related to land cover types in the 4-mile2 landscape around each wetland), Z = proportion of broods that survived to fledge at least 1 recruit (= 0.74 based on Cowardin and Johnson 1979), B = average brood size at fledging (= 4.9 based on Cowardin and Johnson 1979)." ENTERER'S COMMENT: The number of breeding pairs (n) is estimated by a separate submodel from this paper, and as such is also entered as a separate model in ESML (EM 632).	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	None identified	None identified	None identified	None identified
Biophysical Context	No additional description provided	No additional description provided	Five soil types including Löss, Fluvial clay, Peat, Sand, and Silty Loam. Five land-use types including Pasture, Arable farming, Semi-natural grassland, Heathland, and Forest.	Basin elevation ranges from 430 m at the stream gauging station to 700 m at the southeastern ridgeline. Near stream and side slope gradients are approximately 24o and 25o to 50o, respectively. The climate is relatively mild with wet winters and dry summer. Mean annual temperature is 8.5 oC. Daily temperature extremes vary from 39 oC in the summer to -20 oC in the winter.	Prairie Pothole Region of Iowa	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	No scenarios presented	Forest management (harvest/no harvest)	No scenarios presented	No scenarios presented

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
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	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	New or revised model

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

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-346 \| Doc-347 ? Comment: EnviroAtlas maps BNF based on a correlation with AET modeled by Cleveland et al. 1999, and modified by land use (% natural vs. ag/developed) within each HUC. AET was modeled using climate and land use parameters (equation from Sanford and Selnick 2013). For full citations of these related models, see below, "Document ID for related EM.	Doc-231 \| Doc-228	Doc-288	Doc-13 \| Doc-317	Doc-372 \| Doc-373	Doc-406
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	EM-99 \| EM-120 \| EM-121 \| EM-162 \| EM-164 \| EM-165 \| EM-122 \| EM-123 \| EM-124 \| EM-125 \| EM-166 \| EM-170 \| EM-171	None	EM-375 \| EM-379 \| EM-884 \| EM-883 \| EM-887	EM-705 \| EM-704 \| EM-703 \| EM-701 \| EM-700 \| EM-632	EM-836

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Temporal Extent em.detail.tempExtentHelp ?	2006-2010	2000	1999-2005	1969-2008	1987-2007	Not applicable
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-stationary	time-stationary	time-dependent	time-stationary	time-stationary
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	Not applicable	Not applicable	future time	Not applicable	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	Not applicable	Not applicable	discrete	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	Not applicable	1	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Not applicable	Not applicable	Day	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	Geopolitical	Geopolitical	Watershed/Catchment/HUC	Multiple unrelated locations (e.g., meta-analysis)	Not applicable
Spatial Extent Name em.detail.extentNameHelp ?	counterminous United States	The EU-25 plus Switzerland and Norway	The Netherlands	H. J. Andrews LTER WS10	CREP (Conservation Reserve Enhancement Program	Not applicable
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	>1,000,000 km^2	>1,000,000 km^2	10,000-100,000 km^2	10-100 ha	10,000-100,000 km^2	Not applicable

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially distributed (in at least some cases) ? Comment: Watersheds (12-digit HUCs).	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 distributed (in at least some cases)
Spatial Grain Type em.detail.spGrainTypeHelp ?	other (specify), for irregular (e.g., stream reach, lake basin)	area, for pixel or radial feature	area, for pixel or radial feature	other (specify), for irregular (e.g., stream reach, lake basin)	other (specify), for irregular (e.g., stream reach, lake basin)	other (specify), for irregular (e.g., stream reach, lake basin)
Spatial Grain Size em.detail.spGrainSizeHelp ?	irregular	1 km x 1 km	100 m x 100 m	30 m x 30 m surface pixel and 2-m depth soil column	multiple, individual, irregular sites	multiple unrelated sites

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
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 ?	Conventional (frequentist) statistics	None	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
Model Calibration Reported? em.detail.calibrationHelp ?	No	No	No	Yes	Unclear	Not applicable
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	No	No	No	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	No	No	Not applicable
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	No	No	No	No	No	Not applicable
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	No	No	Yes	No	Not applicable
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	Not applicable	Not applicable	No	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-63	EM-119	EM-178	EM-380	EM-702	EM-837
North America United States	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	Europe Netherlands	North America United States Oregon	North America United States Iowa	None

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

EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
None	None	None	None	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
Centroid Latitude em.detail.ddLatHelp ?	39.5	50.53	52.37	44.25	42.62	Not applicable
Centroid Longitude em.detail.ddLongHelp ?	-98.35	7.6	4.88	-122.33	-93.84	Not applicable
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	WGS84	Not applicable
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Estimated	Estimated	Provided	Estimated	Not applicable

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Terrestrial Environment (sub-classes not fully specified)	Aquatic Environment (sub-classes not fully specified) \| Terrestrial Environment (sub-classes not fully specified)	Terrestrial Environment (sub-classes not fully specified) \| Forests \| Agroecosystems \| Grasslands \| Scrubland/Shrubland	Rivers and Streams \| Ground Water \| Forests	Inland Wetlands \| Agroecosystems \| Grasslands	Created Greenspace \| Grasslands
Specific Environment Type em.detail.specificEnvTypeHelp ?	Terrestrial	Not applicable	Not applicable	400 to 500 year old forest dominated by Douglas-fir (Pseudotsuga menziesii), western hemlock (Tsuga heterophylla), and western red cedar (Thuja plicata).	Wetlands buffered by grassland within agroecosystems	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 corresponds to 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-63	EM-119	EM-178	EM-380	EM-702	EM-837
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Individual or population, within a species	Individual or population, within a species

Taxonomic level and name of organisms or groups identified

EM-63	EM-119	EM-178	EM-380	EM-702	EM-837
None Available	None Available	None Available	None Available	Species Northern Shoveler (Anas clypeata)	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-63	EM-119	EM-178	EM-380	EM-702	EM-837
Average Annual Precipitation, Natural Biological Nitrogen Fixation, The Watershed Boundary Dataset (WBD)	Percent GAP Status 1 & 2	GAP Ecological Systems	GAP Ecological Systems, Average Annual Precipitation, Total Annual Reduced Nitrogen Deposition, Total Annual Nitrogen Deposition	Acres of Land Enrolled in the Conservation Reserve Program (CRP)	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-63	EM-119	EM-178	EM-380	EM-702	EM-837
[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Soil formation and composition Decomposition and fixing processes	[Ecosystem] Provisioning Materials Biomass Fibres and other materials from plants, algae and animals for direct use or processing	[Ecosystem] Regulation & Maintenance Mediation of flows Mass flows Buffering and attenuation of mass flows	None	[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

<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-63	EM-119	EM-178	EM-380	EM-702	EM-837
Atmosphere Soil (2) Specific types of soil Quality Indicator	Rivers and Streams (111) Fauna (4) Wildlife Stock Indicator Barren / Rock and Sand (28) Fauna (4) Wildlife Stock Indicator Forests (21) Fauna (4) Wildlife Stock Indicator Tundra (25) Fauna (4) Wildlife Stock Indicator Scrubland/Shrubland (24) Fauna (4) Wildlife Stock Indicator Grasslands (23) Fauna (4) Wildlife Stock Indicator Wetlands (12) Fauna (4) Wildlife Stock Indicator Lakes and Ponds (112) Fauna (4) Wildlife Stock Indicator	None	None	Wetlands (12) Fauna (4) Duck Stock Indicator	None

EcoService Models Library (ESML)

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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)