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-120
EM-124
EM-146
EM-686
EM-743
EM-821

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EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Short Name em.detail.shortNameHelp ?	Landscape importance for habitat diversity, Europe	Land-use change and habitat diversity, Europe	FORCLIM v2.9, Transect in Western OR, USA	Estuary recreational use, Cape Cod, MA	WESP: Irrigation water, ID, USA	Aquatic vertebrate IBI for Western streams, USA
EM Full Name em.detail.fullNameHelp ?	Landscape importance for habitat diversity, Europe	Land-use change effects on habitat diversity, Europe	FORCLIM (FORests in a changing CLIMate) v2.9, Western OR, USA	Estuary recreational use, Cape Cod, MA	WESP: Irrigation return water treatment, Idaho, USA	Development of an aquatic vertebrate index of biotic integrity (IBI) for Western streams, USA
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	EU Biodiversity Action 5	EU Biodiversity Action 5	US EPA	US EPA	None	None
EM Source Document ID	228	228	23 ? Comment: Related document ID 22 is a secondary source providing tree species specific parameters in appendix.	387	393 ? Comment: Additional data came from electronic appendix provided by author Chris Murphy.	404
Document Author em.detail.documentAuthorHelp ?	Haines-Young, R., Potschin, M. and Kienast, F.	Haines-Young, R., Potschin, M. and Kienast, F.	Busing, R. T., Solomon, A. M., McKane, R. B. and Burdick, C. A.	Mulvaney, K K., Atkinson, S.F., Merrill, N.H., Twichell, J.H., and M.J. Mazzotta	Murphy, C. and T. Weekley	Pont, D., Hughes, R.M., Whittier, T.R., and S. Schmutz.
Document Year em.detail.documentYearHelp ?	2012	2012	2007	2019	2012	2009
Document Title em.detail.sourceIdHelp ?	Indicators of ecosystem service potential at European scales: Mapping marginal changes and trade-offs	Indicators of ecosystem service potential at European scales: Mapping marginal changes and trade-offs	Forest dynamics in Oregon landscapes: evaluation and application of an individual-based model	Quantifying Recreational Use of an Estuary: A case study of three bays, Cape Cod, USA	Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context.	A Predictive Index of Biotic Integrity Model for A predictive index of biotic integrity model foraquatic-vertebrate assemblages of Western U.S. Streams
Document Status em.detail.statusCategoryHelp ?	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published	Peer reviewed but unpublished (explain in Comment)	Peer reviewed and published	Peer reviewed and published
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	Published journal manuscript	Published journal manuscript	Draft manuscript-work progressing	Published report	Published journal manuscript

Software and Access

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable
Contact Name em.detail.contactNameHelp ?	Marion Potschin	Marion Potschin	Richard T. Busing	Mulvaney, Kate	Chris Murphy	Didier Pont
Contact Address	Centre for Environmental Management, School of Geography, University of Nottingham, NG7 2RD, United Kingdom	Centre for Environmental Management, School of Geography, University of Nottingham, NG7 2RD, United Kingdom	U.S. Geological Survey, 200 SW 35th Street, Corvallis, Oregon 97333 USA	US EPA, ORD, NHEERL, Atlantic Ecology Division, Narragansett, RI	Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID	Centre d’E´ tude du Machinisme Agricole et du Genie Rural, des Eaux et Foreˆts (Cemagref), Unit HYAX Hydrobiologie, 3275 Route de Ce´zanne, Le Tholonet, 13612 Aix en Provence, France
Contact Email	marion.potschin@nottingham.ac.uk	marion.potschin@nottingham.ac.uk	rtbusing@aol.com	Mulvaney.Kate@epa.gov	chris.murphy@idfg.idaho.gov	didier.pont@cemagref.fr

EM Description

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
Summary Description em.detail.summaryDescriptionHelp ?	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 … “Habitat diversity” … 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: "The analysis for the regulating service "Habitat Diversity" seeks to identify all the areas with potential to support biodiversity."	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 novel aspect of this work is an analysis of whether the historical and the projected land use changes...are likely to be supportive or degenerative in the capacity of ecosystems to deliver (Habitat diversity); we refer to these as ‘marginal’ or incremental changes. The latter are assessed by using land account data for 1990–2000." AUTHOR'S DESCRIPTION: "The analysis for the regulating service “Habitat diversity” seeks to identify all the areas with potential to support biodiversity…The historic assessment of marginal changes was undertaken using the Land and Ecosystem Accounting database (LEAC) created by the EEA using successive CORINE Land Cover data. The analysis of these incremental changes was included in the study in order to examine whether recent trend data could add additional insights to spatial assessment techniques, particularly where change against some base-line status is of interest to decision makers."	ABSTRACT: "The FORCLIM model of forest dynamics was tested against field survey data for its ability to simulate basal area and composition of old forests across broad climatic gradients in western Oregon, USA." Author's Description: "The first set of tests involved eight sites on western Oregon transect from west to east… Individual sites were chosen to represent a particular type of potential natural vegetation as described by Franklin and Dyrness (1988)."	[ABSTRACT: "Estimates of the types and number of recreational users visiting an estuary are critical data for quantifying the value of recreation and how that value might change with variations in water quality or other management decisions. However, estimates of recreational use are minimal and conventional intercept surveys methods are often infeasible for widespread application to estuaries. Therefore, a practical observational sampling approach was developed to quantify the recreational use of an estuary without the use of surveys. Designed to be simple and fast to allow for replication, the methods involved the use of periodic instantaneous car counts multiplied by extrapolation factors derived from all-day counts. This simple sampling approach can be used to estimate visitation to diverse types of access points on an estuary in a single day as well as across multiple days. Evaluation of this method showed that when periodic counts were taken within a preferred time window (from 11am-4:30pm), the estimates were within 44 percent of actual daily visitation. These methods were applied to the Three Bays estuary system on Cape Cod, USA. The estimated combined use across all its public access sites is similar to the use at a mid-sized coastal beach, demonstrating the value of estuarine systems. Further, this study is the first to quantify the variety and magnitude of recreational uses at several different types of access points throughout the estuary using observational methods. This model focused on the various use by access point type (beaches, landings and way to water, boat use). This work can be transferred to the many small coastal access points used for recreation across New England and beyond." ]	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: "Because of natural environmental and faunal differences and scientific perspectives, numerous indices of biological integrity (IBIs) have been developed at local, state, and regional scales in the USA. These multiple IBIs, plus different criteria for judging impairment, hinder rigorous national and multistate assessments. Many IBI metrics are calibrated for water body size, but none are calibrated explicitly for other equally important natural variables such as air temperature, channel gradient, or geology. We developed a predictive aquatic-vertebrate IBI model using a total of 871 stream sites (including 162 least-disturbed and 163 most-disturbed sites) sampled as part of the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program survey of 12 conterminous western U.S. states. The selected IBI metrics (calculated from both fish and aquatic amphibians) were vertebrate species richness, benthic native species richness, assemblage tolerance index, proportion of invertivore–piscivore species, and proportion of lithophilic-reproducing species. Mean model IBI scores differed significantly between least-disturbed and most-disturbed sites as well as among ecoregions. Based on a model IBI impairment criterion of 0.44 (risks of type I and II errors balanced), an estimated 34.7% of stream kilometers in the western USA were deemed impaired, compared with 18% for a set of traditional IBIs. Also, the model IBI usually displayed less variability than the traditional IBIs, presumably because it was better calibrated for natural variability. "
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	None identified	None identified	None Identified	None identified	None identified	None reported
Biophysical Context	No additional description provided	No additional description provided	Coastal to montane	None identified	restored, enhanced and created wetlands	Wadeable and boatable streams in 12 western USA states
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	Recent historical land use change from 1990-2000	No scenarios presented	N/A	Sites, function or habitat focus	not applicable

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application (multiple runs exist) View EM Runs ? Comment: Each of the seven runs represents a different site (ecoregion) along a west to east Oregon transect. An eighth site was not forested and its results were not included.	Method + Application (multiple runs exist) View EM Runs	Method + Application (multiple runs exist) View EM Runs	Method + Application View EM Runs
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	New or revised model	Application of existing 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-120	EM-124	EM-146	EM-686	EM-743	EM-821
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-231 \| Doc-228	Doc-238 \| Doc-239 \| Doc-240 \| Doc-241 \| Doc-242 \| Doc-228	Doc-22 \| Doc-23 ? Comment: Related document ID 22 is a secondary source providing tree species specific parameters in appendix.	None	Doc-390	Doc-403
EM ID for related EM em.detail.relatedEmEmIdHelp ?	EM-99 \| EM-119 \| EM-121 \| EM-162 \| EM-164 \| EM-165 \| EM-122 \| EM-123 \| EM-124 \| EM-125 \| EM-166 \| EM-170 \| EM-171	EM-122 \| EM-123 \| EM-125 \| EM-162 \| EM-164 \| EM-165 \| EM-166 \| EM-170 \| EM-171 \| EM-99 \| EM-119 \| EM-120 \| EM-121	EM-186 \| EM-208 \| EM-224	EM-682 \| EM-684 \| EM-685	EM-718 \| EM-734 \| EM-760 \| EM-761 \| EM-763 \| EM-764 \| EM-766 \| EM-767 \| EM-768	EM-820 \| EM-826

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Temporal Extent em.detail.tempExtentHelp ?	2000	1990-2000	1500 yrs	Summer 2017	2010-2012	2004-2005
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-stationary	time-dependent	time-dependent	time-dependent	time-dependent
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	Not applicable	past time	past time	past time	past time
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	Not applicable	discrete	discrete	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	1	1	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Not applicable	Year	Day	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	Geopolitical	Physiographic or ecological	Physiographic or ecological	Multiple unrelated locations (e.g., meta-analysis)	Geopolitical
Spatial Extent Name em.detail.extentNameHelp ?	The EU-25 plus Switzerland and Norway	The EU-25 plus Switzerland and Norway	Western Oregon transect	Three Bays, Cape Cod	Wetlands in idaho	Western 12 states
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	>1,000,000 km^2	>1,000,000 km^2	1000-10,000 km^2.	1000-10,000 km^2.	100,000-1,000,000 km^2	>1,000,000 km^2

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
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) ? Comment: Computations performed at the area size of 0.08 ha.	spatially distributed (in at least some cases)	spatially lumped (in all cases)	spatially distributed (in at least some cases) ? Comment: 871 total sites surveyed for this work
Spatial Grain Type em.detail.spGrainTypeHelp ?	area, for pixel or radial feature	area, for pixel or radial feature	Not applicable	length, for linear feature (e.g., stream mile)	Not applicable	other (specify), for irregular (e.g., stream reach, lake basin)
Spatial Grain Size em.detail.spGrainSizeHelp ?	1 km x 1 km	1 km x 1 km	Not applicable	beach length	Not applicable	stream reach

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Computational Approach em.detail.emComputationalApproachHelp ?	Logic- or rule-based	Logic- or rule-based	Numeric	Numeric	Numeric	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-120	EM-124	EM-146	EM-686	EM-743	EM-821
Model Calibration Reported? em.detail.calibrationHelp ?	No	No	No	Yes	No	No
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	No	No	No	No	No
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	None	None	None	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	Yes	No	Yes	No	No	Yes ? Comment: Compared to another journal manuscript IBI scores (Whittier et al)
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	No	No	No	No	No	No
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	No	No	No	No	Yes
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	Not applicable	Yes

EM Locations, Environments, Ecology

Location of EM Application

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

EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
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 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	North America United States Oregon	None	North America United States Idaho	North America United States Oregon Montana Wyoming Colorado South Dakota California North Dakota Arizona Idaho Utah Washington Nevada

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

EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
None	None	None	Temperate North Atlantic Northwest Atlantic Cold Temperate Northwest Atlantic Gulf of Maine/Bay of Fundy	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
Centroid Latitude em.detail.ddLatHelp ?	50.53	50.53	44.13	41.62	44.06	44.2
Centroid Longitude em.detail.ddLongHelp ?	7.6	7.6	-122.5	-70.42	-114.69	-113.07
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Estimated	Provided	Estimated	Estimated	Estimated

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Aquatic Environment (sub-classes not fully specified) \| Terrestrial Environment (sub-classes not fully specified)	Aquatic Environment (sub-classes not fully specified) \| Terrestrial Environment (sub-classes not fully specified)	Forests	Near Coastal Marine and Estuarine	Inland Wetlands	Rivers and Streams
Specific Environment Type em.detail.specificEnvTypeHelp ?	Not applicable	Not applicable	Primarily conifer forest	Beaches	created, restored and enhanced wetlands	wadeable and boatable streams
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 is finer than that of 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-120	EM-124	EM-146	EM-686	EM-743	EM-821
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	Not applicable	Species	Not applicable	Not applicable	Guild or Assemblage

Taxonomic level and name of organisms or groups identified

EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
None Available	None Available	Species Pinus ponderosa Abies amabilis Tsuga mertensiana Thuja plicata Abies procera Abies grandis Chamaecyparis nootkatensis Tsuga heterophylla Other (trees) Pseudotsuga menziesii	None Available	None Available	other fish amphibians

EnviroAtlas URL

EM-120	EM-124	EM-146	EM-686	EM-743	EM-821
Percent GAP Status 1 & 2	None Available	GAP Ecological Systems, Average Annual Precipitation	None Available	Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass	Total Annual Reduced Nitrogen Deposition, 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-120	EM-124	EM-146	EM-686	EM-743	EM-821
[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	[Ecosystem] Provisioning Materials Biomass Fibres and other materials from plants, algae and animals for direct use or processing [Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	[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 Physical use of land-/seascapes in different environmental settings	[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-120	EM-124	EM-146	EM-686	EM-743	EM-821
None	None	None	Near Coastal Marine/Estuarine (113) Composite (8) Scapes: views, sounds and scents of land, sea, sky or a combination Site Indicator Quality Indicator Fauna (4) Fish Stock Indicator Clams Stock Indicator	None	Rivers and Streams (111) Fauna (4) Fish Site 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:

Comment:

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

Comment:

EM Modeling Approach

Comment:

Comment:

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)