EcoService Models Library (ESML)

Compare EMs

EM Variables by Variable Role

One quick way to compare ecological models (EMs) is by comparing their variables. Predictor variables show what kinds of influences a model is able to account for, and what kinds of data it requires. Response variables show what information a model is capable of estimating.

This first comparison shows the names (and units) of each EM’s variables, side-by-side, sorted by variable role. Variable roles in ESML are as follows:

Predictor Variables
- Time- or Space-Varying Variables
- Constants and Parameters
Intermediate (Computed) Variables
Response Variables
- Computed Response Variables
- Measured Response Variables

EM Variables by Category

A second way to use variables to compare EMs is by focusing on the kind of information each variable represents. The top-level categories in the ESML Variable Classification Hierarchy are as follows:

Policy Regarding Use or Management of Ecosystem Resources
Land Surface (or Water Body Bed) Cover, Use or Substrate
Human Demographic Data
Human-Produced Stressor or Enhancer of Ecosystem Goods and Services Production
Ecosystem Attributes and Potential Supply of Ecosystem Goods and Services
Non-monetary Indicators of Human Demand, Use or Benefit of Ecosystem Goods and Services
Monetary Values

Besides understanding model similarities, sorting the variables for each EM by these 7 categories makes it easier to see if the compared models can be linked using similar variables. For example, if one model estimates an ecosystem attribute (in Category 5), such as water clarity, as a response variable, and a second model uses a similar attribute (also in Category 5) as a predictor of recreational use, the two models can potentially be used in tandem. This comparison makes it easier to spot potential model linkages.

All EM Descriptors

This selection allows a more detailed comparison of EMs by model characteristics other than their variables. The 50-or-so EM descriptors for each model are presented, side-by-side, in the following categories:

EM Identity and Description
EM Modeling Approach
EM Locations, Environments, Ecology
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system

EM Descriptors by Modeling Concepts

This feature guides the user through the use of the following seven concepts for comparing and selecting EMs:

Conceptual Model
Modeling Objective
Modeling Context
Potential for Model Linkage
Feasibility of Model Use
Model Certainty
Model Structural Information

Though presented separately, these concepts are interdependent, and information presented under one concept may have relevance to other concepts as well.

Compare Criteria:

Show Criteria

Hide Criteria

Comparing:

EM-105
EM-185
EM-195
EM-657
EM-939

Add EM to Compare:

EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Short Name em.detail.shortNameHelp ?	Benthic habitat associations, Willapa Bay, OR, USA	Blue crabs and SAV, Chesapeake Bay, USA	C Sequestration and De-N, Tampa Bay, FL, USA	REQI (River Ecosystem Quality Index), Italy	ESTIMAP- Recreation, Europe
EM Full Name em.detail.fullNameHelp ?	Benthic macrofaunal habitat associations, Willapa Bay, OR, USA	Blue crabs and submerged aquatic vegetation interaction, Chesapeake Bay, USA	Value of Carbon Sequestration and Denitrification benefits, Tampa Bay, FL, USA	REQI (River Ecosystem Quality Index), Marecchia River, Italy	ESTIMAP- Recreation, Europe
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	US EPA	None	US EPA	None	None
EM Source Document ID	39	292 ? Comment: Conference paper	186	378	432
Document Author em.detail.documentAuthorHelp ?	Ferraro, S. P. and Cole, F. A.	Mykoniatis, N. and Ready, R.	Russell, M. and Greening, H.	Santolini, R, E. Morri, G. Pasini, G. Giovagnoli, C. Morolli, and G. Salmoiraghi	Zulian, G., Parrachini, M.L., Maes, J.,
Document Year em.detail.documentYearHelp ?	2007	2013	2013	2014	2013
Document Title em.detail.sourceIdHelp ?	Benthic macrofauna–habitat associations in Willapa Bay, Washington, USA	Evaluating habitat-fishery interactions: The case of submerged aquatic vegetation and blue crab fishery in the Chesapeake Bay	Estimating benefits in a recovering estuary: Tampa Bay, Florida	Assessing the quality of riparian areas: the case of River Ecosystem Quality Index applied to the Marecchia river (Italy)	ESTIMAP: Ecosystem services mapping at the European scale
Document Status em.detail.statusCategoryHelp ?	Peer reviewed and published	Not formally documented	Peer reviewed and published	Peer reviewed and published	Peer reviewed and published
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	Conference proceedings	Published journal manuscript	Published journal manuscript	Published report

Software and Access

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	Not applicable	Not applicable	N.A.
Contact Name em.detail.contactNameHelp ?	Steve Ferraro	Nikolaos Mykoniatis	M. Russell	Elisa Morri	Grazia Zulian
Contact Address	U.S. EPA 2111 SE Marine Science Drive Newport, OR 97365	Department of Agricultural Economics, Sociology and Education The Pennsylvania State University	US EPA, Gulf Ecology Division, 1 Sabine Island Dr, Gulf Breeze, FL 32563, USA	Dept. of Earth, Life, and Environmental Sciences, Urbino university, via ca le suore, campus scientifico Enrico Mattei, Urbino 61029 Italy	Joint Research Centre, Via Enrico Fermi 2749, TP 272, 21027 Ispra (VA), Italy
Contact Email	ferraro.steven@epa.gov	Not reported	Russell.Marc@epamail.epa.gov	elisa.morri@uniurb.it	grazia.zulian@jrc.ec.europa.e

EM Description

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
Summary Description em.detail.summaryDescriptionHelp ?	AUTHOR'S DESCRIPTION: "In this paper we report the results of 2 estuary-wide studies of benthic macrofaunal habitat associations in Willapa Bay, Washington, USA. This research is part of an effort to develop empirical models of biota-habitat associations that can be used to help identify critical habitats, prioritize habitats for environmental protection, index habitat suitability (U.S. Fish and Wildlife Service, 1980; Kapustka, 2003), perform habitat equivalency and compensatory restoration analyses (Fonseca et al., 2002; Kirsch et al., 2005), and as habitat value criteria in ecological risk assessments (Obery and Landis, 2002; Ferraro and Cole, 2004; Landis et al., 2004)." (491)	ABSTRACT: "This paper investigates habitat-fisheries interaction between two important resources in the Chesapeake Bay: blue crabs and Submerged Aquatic Vegetation (SAV). A habitat can be essential to a species (the species is driven to extinction without it), facultative (more habitat means more of the species, but species can exist at some level without any of the habitat) or irrelevant (more habitat is not associated with more of the species). An empirical bioeconomic model that nests the essential-habitat model into its facultative-habitat counterpart is estimated. Two alternative approaches are used to test whether SAV matters for the crab stock. Our results indicate that, if we do not have perfect information on habitat-fisheries linkages, the right approach would be to run the more general facultative-habitat model instead of the essential- habitat one."	AUTHOR'S DESCRIPTION: "...we examine the change in the production of ecosystem goods produced as a result of restoration efforts and potential relative cost savings for the Tampa Bay community from seagrass expansion (more than 3,100 ha) and coastal marsh and mangrove restoration (∼600 ha), since 1990… The objectives of this article are to explore the roles that ecological processes and resulting ecosystem goods have in maintaining healthy estuarine systems by (1) quantifying the production of specific ecosystem goods in a subtropical estuarine system and (2) determining potential cost savings of improved water quality and increased habitat in a recovering estuary." (pp. 2)	ABSTRACT: "Riparian areas support a set of river functions and of ecosystem services (ESs). Their role is essential in reducing negative human impacts on river functionality. These aspects could be contained in the River Basin Management Plan, which is the tool for managing and planning freshwater ecosystems in a river basin. In this paper, a new index was developed, namely the River Ecosystem Quality Index (REQI). It is composed of five ecological indices, which assess the quality of riparian areas, and it was first applied to the Marecchia river (central Italy). The REQI was also compared with the Italian River Functionality Index (IFF) and the ESs measured as the capacity of land cover in providing human benefits. Data have shown a decrease in the quality of riparian areas, from the upper to lower part of river, with 53% of all subareas showing medium-quality values…" AUTHOR'S DESCRIPTION: "The evaluation of the quality of the riparian areas is based on the analysis of two fundamental elements of riparian areas: vegetation (characteristics and distribution) and wild birds, measured with standardized methodology and used as indicators of environmental quality and changes...To represent the REQI, each of the five indicators was initially scored with its own range (Figure 3(a)—(e)). Then, all results were redistributed in ranges from 1 to 5, where 5 is the best condition of all indices. Redistributed results were finally summed."	AUTHOR Descriptions: "ESTIMAP consists of a set of separate components, each of which can be run separately. The models have been all framed in the ecosystem services cascade model [4] which connects ecosystem structure and functioning to human well-being through the flow of ecosystem services. At present, three modules are operational and described in further detail in this report: pollination, recreation and coastal protectionPeople can benefit from the opportunities provided by nature for recreational activities if they are able to reach them. The Recreation Opportunity spectrum was chosen as a method to map different degrees of service available according to their proximity to the people. Remoteness and proximity have been addressed in the second step of the analysis, in order to assess how the benefit (recreation) can be delivered to people. The proxy that has been identified couples information on both variables and has been mapped by classifying the EU into zones of proximity versus remoteness. From the ROS perspective this part takes into account remoteness and to some extent expected social experience. Distance from roads and residential areas have been used as inputs. The information on the road network is provided by the TeleAtlas database, and covers all paved roads in Europe. Gravel roads have been discarded to ease the processing. Residential areas are extracted from CORINE land cover classes “continuous urban fabric” and “discontinuous urban fabric”, therefore, all urban patches larger than 25 ha are considered in the mapping. In the current exercise there was the necessity to adapt overseas experiences to the peculiarities of the European continent, especially considering that the EU does not contain large wilderness areas like other continents "
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	None identified	Not applicable	Restoration of seagrass	None identified	None
Biophysical Context	benthic estuarine	Submerged Aquatic Vegetation (SAV), eelgrass	Recovering estuary; Seagrass; Coastal fringe; Saltwater marsh; Mangrove	No additional description provided	Continential Scale
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	Essential or Facultative habitat	Habitat loss or restoration in Tampa Bay Estuary	No scenarios presented	N.A.

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application	Method + Application	Method Only
New or Pre-existing EM? em.detail.newOrExistHelp ?	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-105	EM-185	EM-195	EM-657	EM-939
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	None	Doc-227	None	None	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	EM-106	None	None	EM-941

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Temporal Extent em.detail.tempExtentHelp ?	1996,1998	1993-2011	1982-2010	1996-2003 ? Comment: All the ecological analyses are based on the production of a 1:10,000 scale map of land cover with detailed classes for the vegetation obtained by overlapping the photogrammetric analysis (AIMA flight 1996) and the 2003 land-use map.	Not applicable
EM Time Dependence em.detail.timeDependencyHelp ?	time-stationary	time-dependent	time-stationary	time-stationary	Not applicable
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	past time	Not applicable	Not applicable	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	discrete	Not applicable	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	1	Not applicable	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Year	Not applicable	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
Bounding Type em.detail.boundingTypeHelp ?	Physiographic or Ecological	Physiographic or ecological	Physiographic or Ecological	Watershed/Catchment/HUC	No location (no locational reference given)
Spatial Extent Name em.detail.extentNameHelp ?	Willapa Bay	Chesapeake Bay	Tampa Bay Estuary	Marecchia river catchment	Not applicable
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	100-1000 km^2	10,000-100,000 km^2	1000-10,000 km^2.	100-1000 km^2	>1,000,000 km^2

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially lumped (in all 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)
Spatial Grain Type em.detail.spGrainTypeHelp ?	Not applicable	Not applicable	area, for pixel or radial feature	area, for pixel or radial feature	area, for pixel or radial feature
Spatial Grain Size em.detail.spGrainSizeHelp ?	Not applicable	Not applicable	1 ha	500 m x 1000 m	Pixel size

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Analytic	Analytic	Analytic	Numeric
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
Model Calibration Reported? em.detail.calibrationHelp ?	Yes	Yes	Yes	Not applicable	No
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	Yes	Yes	No	Not applicable	Not applicable
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	R^2 \| 0.34-0.82 \| Not applicable R^2 \| 0.29-0.68 \| Not applicable R^2 \| 0.07-0.17 \| Not applicable	None	None	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	Yes	No	Yes ? Comment: R2 values of the analysis between the REQI, the capacity of land cover to provide ESs, and the Italian River Functionality Quality Index ? IFF.	Unclear
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	Yes	Yes	No	Not applicable	No
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	Yes	No	Not applicable	Yes
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	Yes	Not applicable	Not applicable	Unclear

EM Locations, Environments, Ecology

Location of EM Application

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

EM-105	EM-185	EM-195	EM-657	EM-939
None	North America United States Maryland Virgina	None	Europe Italy	Europe

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

EM-105	EM-185	EM-195	EM-657	EM-939
Temperate North Pacific Northeast Pacific Cold Temperate Northeast Pacific Oregon, Washington, Vancouver Coast and Shelf	Temperate North Atlantic Northwest Atlantic Cold Temperate Northwest Atlantic Virginian	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Floridian	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
Centroid Latitude em.detail.ddLatHelp ?	46.24	36.99	27.95	43.89	Not applicable
Centroid Longitude em.detail.ddLongHelp ?	-124.06	-75.95	-82.47	12.3	Not applicable
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	Not applicable
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Provided	Estimated	Estimated	Estimated	Not applicable

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-105	EM-185	EM-195	EM-657	EM-939
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Near Coastal Marine and Estuarine	None	Near Coastal Marine and Estuarine	Rivers and Streams \| Inland Wetlands \| Terrestrial Environment (sub-classes not fully specified)	Terrestrial Environment (sub-classes not fully specified)
Specific Environment Type em.detail.specificEnvTypeHelp ?	Drowned river valley estuary	Yes	Subtropical Estuary	Riparian zone along major river	Not applicable
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecological scale is finer than that of the Environmental Sub-class	Yes	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-105	EM-185	EM-195	EM-657	EM-939
EM Organismal Scale em.detail.orgScaleHelp ?	Species	Yes	Not applicable	Species ? Comment: Bird species for faunistic index of conservation.	Not applicable

Taxonomic level and name of organisms or groups identified

EM-105	EM-185	EM-195	EM-657	EM-939
Species Zostera marina Neotrypaea californiensis Manayunkia aestuarina Upogebia pugettensis Spartina alterniflora	None Available	None Available	None Available	None Available

EnviroAtlas URL

EM-105	EM-185	EM-195	EM-657	EM-939
None Available	None Available	Carbon Storage by Tree Biomass	Ecosystem Markets: Imperiled Species and Habitats	Dasymetric Allocation of Population, Ecosystem Markets: Imperiled Species and Habitats, Waterbody area

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-105	EM-185	EM-195	EM-657	EM-939
[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 Atmospheric composition and climate regulation Global climate regulation by reduction of greenhouse gas concentrations Mediation of waste, toxics and other nuisances Mediation by biota Bio-remediation by micro-organisms, algae, plants, and animals 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 Water conditions Chemical condition of freshwaters	[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

<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-105	EM-185	EM-195	EM-657	EM-939
Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Stock Indicator	None	Near Coastal Marine/Estuarine (113) Water (3) Liquid water Quality Indicator	None	None

EcoService Models Library (ESML)

Compare EMs

EM Variables by Variable Role

EM Variables by Category

All EM Descriptors

EM Descriptors by Modeling Concepts

Comparing:

EM Identity and Description

Comment:

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

EM Modeling Approach

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

Comment:

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)