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-88
EM-105
EM-148
EM-185
EM-195
EM-467
EM-657
EM-939

Add EM to Compare:

EM Identity and Description

EM Identification

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Short Name em.detail.shortNameHelp ?	Area and hotspots of carbon storage, South Africa	Benthic habitat associations, Willapa Bay, OR, USA	InVEST - Water provision, Francoli River, Spain	Blue crabs and SAV, Chesapeake Bay, USA	C Sequestration and De-N, Tampa Bay, FL, USA	Yasso07 v1.0.1, Switzerland	REQI (River Ecosystem Quality Index), Italy	ESTIMAP- Recreation, Europe
EM Full Name em.detail.fullNameHelp ?	Area and hotspots of carbon storage, South Africa	Benthic macrofaunal habitat associations, Willapa Bay, OR, USA	InVEST (Integrated Valuation of Envl. Services and Tradeoffs) v2.4.2 - Water provision, Francoli River, Spain	Blue crabs and submerged aquatic vegetation interaction, Chesapeake Bay, USA	Value of Carbon Sequestration and Denitrification benefits, Tampa Bay, FL, USA	Yasso07 v1.0.1 forest litter decomposition, Switzerland	REQI (River Ecosystem Quality Index), Marecchia River, Italy	ESTIMAP- Recreation, Europe
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	None	US EPA	InVEST	None	US EPA	None	None	None
EM Source Document ID	271	39	280	292 ? Comment: Conference paper	186	343	378	432
Document Author em.detail.documentAuthorHelp ?	Egoh, B., Reyers, B., Rouget, M., Richardson, D.M., Le Maitre, D.C., and van Jaarsveld, A.S.	Ferraro, S. P. and Cole, F. A.	Marques, M., Bangash, R.F., Kumar, V., Sharp, R., and Schuhmacher, M.	Mykoniatis, N. and Ready, R.	Russell, M. and Greening, H.	Didion, M., B. Frey, N. Rogiers, and E. Thurig	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 ?	2008	2007	2013	2013	2013	2014	2014	2013
Document Title em.detail.sourceIdHelp ?	Mapping ecosystem services for planning and management	Benthic macrofauna–habitat associations in Willapa Bay, Washington, USA	The impact of climate change on water provision under a low flow regime: A case study of the ecosystems services in the Francoli river basin	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	Validating tree litter decomposition in the Yasso07 carbon model	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	Peer reviewed and published	Peer reviewed and published	Not formally documented	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	Conference proceedings	Published journal manuscript	Published journal manuscript	Published journal manuscript	Published report

Software and Access

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	Not applicable	https://www.naturalcapitalproject.org/invest/	Not applicable	Not applicable	http://en.ilmatieteenlaitos.fi/yasso-download-and-support	Not applicable	N.A.
Contact Name em.detail.contactNameHelp ?	Benis Egoh	Steve Ferraro	Montse Marquès	Nikolaos Mykoniatis	M. Russell	Markus Didion ? Comment: Tel.: +41 44 7392 427	Elisa Morri	Grazia Zulian
Contact Address	Water Resources Unit, Institute for Environment and Sustainability, European Commission - Joint Research Centre, Ispra, Italy	U.S. EPA 2111 SE Marine Science Drive Newport, OR 97365	Environmental Analysis and Management Group, Department d'Enginyeria Qimica, Universitat Rovira I Virgili, Tarragona, Catalonia, Spain	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	Swiss Federal Institute for Forest, Snow and Landscape Research WSL, 8903 Birmensdorf, Switzerland	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	Not reported	ferraro.steven@epa.gov	montserrat.marques@fundacio.urv.cat	Not reported	Russell.Marc@epamail.epa.gov	markus.didion@wsl.ch	elisa.morri@uniurb.it	grazia.zulian@jrc.ec.europa.e

EM Description

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Summary Description em.detail.summaryDescriptionHelp ?	AUTHOR'S DESCRIPTION: "We define the range of ecosystem services as areas of meaningful supply, similar to a species’ range or area of occupancy. The term ‘‘hotspots’’ was proposed by Norman Myers in the 1980s and refers to areas of high species richness, endemism and/or threat and has been widely used to prioritise areas for biodiversity conservation. Similarly, this study suggests that hotspots for ecosystem services are areas of critical management importance for the service. Here the term ecosystem service hotspot is used to refer to areas which provide large proportions of a particular service, and do not include measures of threat or endemism…In this study, only carbon storage was mapped because of a lack of data on the other functions related to the regulation of global climate such as carbon sequestration and the effects of changes in albedo. Carbon is stored above or below the ground and South African studies have found higher levels of carbon storage in thicket than in savanna, grassland and renosterveld (Mills et al., 2005). This information was used by experts to classify vegetation types (Mucina and Rutherford, 2006), according to their carbon storage potential, into three categories: low to none (e.g. desert), medium (e.g. grassland), high (e.g. thicket, forest) (Rouget et al., 2004). All vegetation types with medium and high carbon storage potential were identified as the range of carbon storage. Areas of high carbon storage potential where it is essential to retain this store were mapped as the carbon storage hotspot."	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)	Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "InVEST 2.4.2 model runs as script tool in the ArcGIS 10 ArcTool-Box on a gridded map at an annual average time step, and its results can be reported in either biophysical or monetary terms, depending on the needs and the availability of information. It is most effectively used within a decision making process that starts with a series of stakeholder consultations to identify questions and services of interest to policy makers, communities, and various interest groups. These questions may concern current service delivery and how services may be affected by new programmes, policies, and conditions in the future. For questions regarding the future, stakeholders develop scenarios of management interventions or natural changes to explore the consequences of potential changes on natural resources [21]. This tool informs managers and policy makers about the impacts of alternative resource management choices on the economy, human well-being, and the environment, in an integrated way [22]. The spatial resolution of analyses is flexible, allowing users to address questions at the local, regional or global scales.	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: "...We examined the validity of the litter decomposition and soil carbon model Yasso07 in Swiss forests based on data on observed decomposition of (i) foliage and fine root litter from sites along a climatic and altitudinal gradient and (ii) of 588 dead trees from 394 plots of the Swiss National Forest Inventory. Our objectives were to (i) examine the effect of the application of three different published Yasso07 parameter sets on simulated decay rate; (ii) analyze the accuracy of Yasso07 for reproducing observed decomposition of litter and dead wood in Swiss forests;…" AUTHOR'S DESCRIPTION: "Yasso07 (Tuomi et al., 2011a, 2009) is a litter decomposition model to calculate C stocks and stock changes in mineral soil, litter and deadwood. For estimating stocks of organic C in these pools and their temporal dynamics, Yasso07 (Y07) requires information on C inputs from dead organic matter (e.g., foliage and woody material) and climate (temperature, temperature amplitude and precipitation). DOM decomposition is modelled based on the chemical composition of the C input, size of woody parts and climate (Tuomi et al., 2011 a, b, 2009). In Y07 it is assumed that DOM consists of four compound groups with specific mass loss rates. The mass flows between compounds that are either insoluble (N), soluble in ethanol (E), in water (W) or in acid (A) and to a more stable humus compartment (H), as well as the flux out of the five pools (Fig. 1, Table A.1; Liski et al., 2009) are described by a range of parameters (Tuomi et al., 2011a, 2009)." "For this study, we used the Yasso07 release 1.0.1 (cf. project homepage). The Yasso07 Fortran source code was compiled for the Windows7 operating system. The statistical software R (R Core Team, 2013) version 3.0.1 (64 bit) was used for administrating theYasso07 simulations. The decomposition of DOM was simulated with Y07 using the parameter sets P09, P11 and P12 with the purpose of identifying a parameter set that is applicable to conditions in Switzerland. In the simulations we used the value of the maximum a posteriori point estimate (cf. Tuomi et al., 2009) derived from the distribution of parameter values for each set (Table A.1). The simulations were initialized with the C mass contained in (a) one litterbag at the start of the litterbag experiment for foliage and fine root litter (Heim and Frey, 2004) and (b) individual deadwood pieces at the time of the NFI2 for deadwood. The respective mass of C was separated into the four compound groups used by Y07. The simulations were run for the time span of the observed data. The result of the simulation was an annual estimate of the remaining fraction of the initial mass, which could then be compared with observed data."	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	None identified	None identified	Not applicable	Restoration of seagrass	None identified	None identified	None
Biophysical Context	Semi-arid environment. Rainfall varies geographically from less than 50 to about 3000 mm per year (annual mean 450 mm). Soils are mostly very shallow with limited irrigation potential.	benthic estuarine	Mediteranean coastal mountains	Submerged Aquatic Vegetation (SAV), eelgrass	Recovering estuary; Seagrass; Coastal fringe; Saltwater marsh; Mangrove	Different forest types dominated by Norway Spruce (Picea abies), European Beech (Fagus sylvatica) and Sweet Chestnut (Castanea sativa).	No additional description provided	Continential Scale
EM Scenario Drivers em.detail.scenarioDriverHelp ?	No scenarios presented	No scenarios presented	IPPC scenarios A2- severe changes in temperature and precipitation, B1 - more moderate variations in temperature and precipitation schemes from the present	Essential or Facultative habitat	Habitat loss or restoration in Tampa Bay Estuary	No scenarios presented ? Comment: Yasso model simulations were run using 3 different parameter sets from: 1) Tuomi et al., 2009 (P09), 2) Tuomi et al., 2011 (P11), and 3) Rantakari et al., 2012 (P12).	No scenarios presented	N.A.

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application	Method + Application	Method + Application (multiple runs exist) View EM Runs	Method + Application	Method + Application	Method + Application (multiple runs exist) View EM Runs ? Comment: Yasso model simulations were run using 3 different parameter sets from: 1) Tuomi et al., 2009 (P09), 2) Tuomi et al., 2011 (P11), and 3) Rantakari et al., 2012 (P12).	Method + Application	Method Only
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	New or revised model	Application of existing model	Application of existing model	New or revised model	Application of existing model	New or revised model	New or revised model

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

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	Doc-271	None	Doc-307 \| Doc-311 \| Doc-338 \| Doc-205	Doc-227	None	Doc-342 \| Doc-344	None	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	EM-85 \| EM-86 \| EM-87	None	EM-344 \| EM-368 \| EM-437 \| EM-111	EM-106	None	EM-466 \| EM-469 \| EM-480 \| EM-485	None	EM-941

EM Modeling Approach

EM Relationship to Time

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Temporal Extent em.detail.tempExtentHelp ?	Not reported	1996,1998	1971-2100	1993-2011	1982-2010	1993-2013	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-stationary	time-stationary	time-dependent	time-stationary	time-dependent	time-stationary	Not applicable
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	Not applicable	Not applicable	Not applicable	past time	Not applicable	future time	Not applicable	Not applicable
EM Time Continuity em.detail.continueDiscreteHelp ?	Not applicable	Not applicable	Not applicable	discrete	Not applicable	discrete	Not applicable	Not applicable
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	Not applicable	Not applicable	1	Not applicable	1	Not applicable	Not applicable
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	Not applicable	Not applicable	Year	Not applicable	Year	Not applicable	Not applicable

EM Spatial Extent

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	Physiographic or Ecological	Watershed/Catchment/HUC	Physiographic or ecological	Physiographic or Ecological	Geopolitical	Watershed/Catchment/HUC	No location (no locational reference given)
Spatial Extent Name em.detail.extentNameHelp ?	South Africa	Willapa Bay	Francoli River	Chesapeake Bay	Tampa Bay Estuary	Switzerland	Marecchia river catchment	Not applicable
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	>1,000,000 km^2	100-1000 km^2	100-1000 km^2	10,000-100,000 km^2	1000-10,000 km^2.	10,000-100,000 km^2	100-1000 km^2	>1,000,000 km^2

Spatial Distribution of Computations

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially distributed (in at least some cases)	spatially lumped (in all 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)	spatially distributed (in at least some cases)
Spatial Grain Type em.detail.spGrainTypeHelp ?	other (specify), for irregular (e.g., stream reach, lake basin)	Not applicable	area, for pixel or radial feature	Not applicable	area, for pixel or radial feature	other (specify), for irregular (e.g., stream reach, lake basin)	area, for pixel or radial feature	area, for pixel or radial feature
Spatial Grain Size em.detail.spGrainSizeHelp ?	Distributed across catchments with average size of 65,000 ha	Not applicable	30m x 30m	Not applicable	1 ha	5 sites	500 m x 1000 m	Pixel size

EM Structure and Computation Approach

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	Analytic	Numeric	Analytic	Analytic	Numeric	Analytic	Numeric
EM Determinism em.detail.deterStochHelp ?	deterministic	deterministic	deterministic	deterministic	deterministic	stochastic	deterministic	deterministic
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	None	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics	Bayesian statistics	Conventional (frequentist) statistics	Conventional (frequentist) statistics

Model Checking Procedures Used

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Model Calibration Reported? em.detail.calibrationHelp ?	No	Yes	No	Yes	Yes	No	Not applicable	No
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	No	Yes	No	Yes	No	No	Not applicable	Not applicable
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	None	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	None	None
Model Operational Validation Reported? em.detail.validationHelp ?	No	No	Yes ? Comment: Used Nash-Sutcliffe model efficiency index	Yes	No	Yes	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 ?	No	Yes	No	Yes	No	No	Not applicable	No
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	No	No	No	Yes	No	No	Not applicable	Yes
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Not applicable	Not applicable	Not applicable	Yes	Not applicable	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-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Africa South Africa	None	Europe Spain	North America United States Maryland Virgina	None	Europe Switzerland	Europe Italy	Europe

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

EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
None	Temperate North Pacific Northeast Pacific Cold Temperate Northeast Pacific Oregon, Washington, Vancouver Coast and Shelf	None	Temperate North Atlantic Northwest Atlantic Cold Temperate Northwest Atlantic Virginian	Tropical Atlantic West Tropical Atlantic Tropical Northwestern Atlantic Floridian	None	None	None

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
Centroid Latitude em.detail.ddLatHelp ?	-30	46.24	41.26	36.99	27.95	46.82	43.89	Not applicable
Centroid Longitude em.detail.ddLongHelp ?	25	-124.06	1.18	-75.95	-82.47	8.23	12.3	Not applicable
Centroid Datum em.detail.datumHelp ?	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84	WGS84	Not applicable
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	Provided	Estimated	Estimated	Estimated	Estimated	Estimated	Not applicable

Environments and Scales Modeled

EM ID em.detail.idHelp ?	EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Terrestrial Environment (sub-classes not fully specified)	Near Coastal Marine and Estuarine	Rivers and Streams	None	Near Coastal Marine and Estuarine	Forests	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 ?	Not applicable	Drowned river valley estuary	Coastal mountains	Yes	Subtropical Estuary	forests	Riparian zone along major river	Not applicable
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	Yes	Ecological scale is finer 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 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-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
EM Organismal Scale em.detail.orgScaleHelp ?	Not applicable	Species	Not applicable	Yes	Not applicable	Community	Species ? Comment: Bird species for faunistic index of conservation.	Not applicable

Taxonomic level and name of organisms or groups identified

EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
None Available	Species Zostera marina Neotrypaea californiensis Manayunkia aestuarina Upogebia pugettensis Spartina alterniflora	None Available	None Available	None Available	None Available	None Available	None Available

EnviroAtlas URL

EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
None Available	None Available	Average Annual Precipitation, The Watershed Boundary Dataset (WBD)	None Available	Carbon Storage by Tree Biomass	GAP Ecological Systems, Average Annual Precipitation, Carbon storage by tree biomass (kg/m2), 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-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Atmospheric composition and climate regulation Global climate regulation by reduction of greenhouse gas concentrations	[Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats	[Ecosystem] Provisioning Nutrition Water Surface water for drinking	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 Soil formation and composition Decomposition and fixing processes	[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

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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)

EM-88	EM-105	EM-148	EM-185	EM-195	EM-467	EM-657	EM-939
None	Near Coastal Marine/Estuarine (113) Fauna (4) Invertebrates Stock Indicator	Rivers and Streams (111) Water (3) Liquid water Stock Indicator	None	Near Coastal Marine/Estuarine (113) Water (3) Liquid water Quality Indicator	None	None	None

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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)