EcoService Models Library (ESML)
Home
Search EMs
My
EMs 
Learn about
ESML
View ESML Data Maploading
Compare EMs
Which comparison is best for me?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 CriteriaEM Identity and Description
EM Identification
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Short Name
em.detail.shortNameHelp
?
|
Community flowering date, Central French Alps | Divergence in flowering date, Central French Alps | Cultural ecosystem services, Bilbao, Spain | Coral taxa and land development, St.Croix, VI, USA | InVESTv3.0 Sed. retention, Guánica Bay, PR, USA | Beach visitation, Barnstable, MA, USA |
|
EM Full Name
em.detail.fullNameHelp
?
|
Community weighted mean flowering date, Central French Alps | Functional divergence in flowering date, Central French Alps | Cultural ecosystem services, Bilbao, Spain | Coral taxa richness and land development, St.Croix, Virgin Islands, USA | InVEST (Integrated Valuation of Environmental Services and Tradeoffs)v3.0 Sediment Retention, Guánica Bay, Puerto Rico, USA | Beach visitation, Barnstable, Massachusetts, USA |
|
EM Source or Collection
em.detail.emSourceOrCollectionHelp
?
|
EU Biodiversity Action 5 | EU Biodiversity Action 5 |
None ?Comment:EU Mapping Studies |
US EPA | US EPA | InVEST | US EPA |
|
EM Source Document ID
|
260 | 260 | 191 | 96 | 338 | 386 |
|
Document Author
em.detail.documentAuthorHelp
?
|
Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Lavorel, S., Grigulis, K., Lamarque, P., Colace, M-P, Garden, D., Girel, J., Pellet, G., and Douzet, R. | Casado-Arzuaga, I., Onaindia, M., Madariaga, I. and Verburg P. H. | Oliver, L. M., Lehrter, J. C. and Fisher, W. S. | Amelia Smith, Susan Harrell Yee, Marc Russell, Jill Awkerman and William S. Fisher | Lyon, Sarina F., Nathaniel H. Merrill, Kate K. Mulvaney, and Marisa J. Mazzotta |
|
Document Year
em.detail.documentYearHelp
?
|
2011 | 2011 | 2013 | 2011 | 2017 | 2018 |
|
Document Title
em.detail.sourceIdHelp
?
|
Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Using plant functional traits to understand the landscape distribution of multiple ecosystem services | Mapping recreation and aesthetic value of ecosystems in the Bilbao Metropolitan Greenbelt (northern Spain) to support landscape planning | Relating landscape development intensity to coral reef condition in the watersheds of St. Croix, US Virgin Islands | Linking ecosystem services supply to stakeholder concerns on both land and sea: An example from Guanica Bay watershed, Puerto Rico | Valuing coastal beaches and closures using benefit transfer: An application to Barnstable, Massachusetts |
|
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 journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript |
Software and Access
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| Not applicable | Not applicable | Not applicable | Not applicable | http://www.naturalcapitalproject.org/invest/ | Not applicable | |
|
Contact Name
em.detail.contactNameHelp
?
|
Sandra Lavorel | Sandra Lavorel | Izaskun Casado-Arzuaga | Leah Oliver | Susan H. Yee | Kate K, Mulvaney |
|
Contact Address
|
Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | Laboratoire d’Ecologie Alpine, UMR 5553 CNRS Université Joseph Fourier, BP 53, 38041 Grenoble Cedex 9, France | Plant Biology and Ecology Department, University of the Basque Country UPV/EHU, Campus de Leioa, Barrio Sarriena s/n, 48940 Leioa, Bizkaia, Spain | National Health and Environmental Research Effects Laboratory | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | Not reported |
|
Contact Email
|
sandra.lavorel@ujf-grenoble.fr | sandra.lavorel@ujf-grenoble.fr | izaskun.casado@ehu.es | leah.oliver@epa.gov | yee.susan@epa.gov | Mulvaney.Kate@EPA.gov |
EM Description
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Summary Description
em.detail.summaryDescriptionHelp
?
|
ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services." AUTHOR'S DESCRIPTION: "Community-weighted mean date of flowering onset was modelled using mixed models with land use and abiotic variables as fixed effects (LU + abiotic model) and year as a random effect…and modelled for each 20 x 20 m pixel using GLM estimated effects for each land use category and estimated regression coefficients with abiotic variables." | ABSTRACT: "Here, we propose a new approach for the analysis, mapping and understanding of multiple ES delivery in landscapes. Spatially explicit single ES models based on plant traits and abiotic characteristics are combined to identify ‘hot’ and ‘cold’ spots of multiple ES delivery, and the land use and biotic determinants of such distributions. We demonstrate the value of this trait-based approach as compared to a pure land-use approach for a pastoral landscape from the central French Alps, and highlight how it improves understanding of ecological constraints to, and opportunities for, the delivery of multiple services. Vegetative height and leaf traits such as leaf dry matter content were response traits strongly influenced by land use and abiotic environment, with follow-on effects on several ecosystem properties, and could therefore be used as functional markers of ES." AUTHOR'S DESCRIPTION: "Functional divergence of flowering date was modelled using mixed models with land use and abiotic variables as fixed effects (LU + abiotic model) and year as a random effect…and modelled for each 20 x 20 m pixel using GLM estimated effects for each land use category and estimated regression coefficients with abiotic variables." | ABSTRACT "This paper presents a method to quantify cultural ecosystem services (ES) and their spatial distribution in the landscape based on ecological structure and social evaluation approaches. The method aims to provide quantified assessments of ES to support land use planning decisions. A GIS-based approach was used to estimate and map the provision of recreation and aesthetic services supplied by ecosystems in a peri-urban area located in the Basque Country, northern Spain. Data of two different public participation processes (frequency of visits to 25 different sites within the study area and aesthetic value of different landscape units) were used to validate the maps. Three maps were obtained as results: a map showing the provision of recreation services, an aesthetic value map and a map of the correspondences and differences between both services. The data obtained in the participation processes were found useful for the validation of the maps. A weak spatial correlation was found between aesthetic quality and recreation provision services, with an overlap of the highest values for both services only in 7.2 % of the area. A consultation with decision-makers indicated that the results were considered useful to identify areas that can be targeted for improvement of landscape and recreation management." | AUTHOR'S DESCRIPTION: "In this exploratory comparison, stony coral condition was related to watershed LULC and LDI values. We also compared the capacity of other potential human activity indicators to predict coral reef condition using multivariate analysis." (294) | 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: "…were identified as relevant to stakeholder objectives in the Guanica Bay watershed identified during the 2013 Public Values Forum…Ecological production fuctions were applied to translate LULC measures of ecosystem conditions to supply of ecosystem services…Sediment retention in each watershed depends on geomorphology, climate, vegetation, and management, and was estimated by applying the Universal Soil Loss Equation (USLE) in each HUCH12 sub-watershed using a sediment retention model (InVEST 3.0.0…" | ABSTRACT: "Each year, millions of Americans visit beaches for recreation, resulting in significant social welfare benefits and economic activity. Considering the high use of coastal beaches for recreation, closures due to bacterial contamination have the potential to greatly impact coastal visitors and communities. We used readily-available information to develop two transferable models that, together, provide estimates for the value of a beach day as well as the lost value due to a beach closure. We modeled visitation for beaches in Barnstable, Massachusetts on Cape Cod through panel regressions to predict visitation by type of day, for the season, and for lost visits when a closure was posted. We used a meta-analysis of existing studies conducted throughout the United States to estimate a consumer surplus value of a beach visit of around $22 for our study area, accounting for water quality at beaches by using past closure history. We applied this value through a benefit transfer to estimate the value of a beach day, and combined it with lost town revenue from parking to estimate losses in the event of a closure. The results indicate a high value for beaches as a public resource and show significant losses to the town when beaches are closed due to an exceedance in bacterial concentrations." AUTHOR'S DESCRIPTION: "...We needed beach visitation estimates to assess the number of people who would be impacted by beach closures. We modeled visits by combining daily parking counts with other factors that help explain variations in attendance, including weather, day of the week or point within a season, and physical differences in sites (Kreitler et al. 2013). We designed the resulting model to estimate visitation for uncounted days as well as for beaches without counts on a given day. When combined with estimates of value per day, the visitation model can be used to value a lost beach day while accounting for beach size, time of season, and other factors...Since our count data of visitation for all four beaches are relatively large numbers (mean = 490, SD = 440), we used a log-linear regression model as opposed to a count data model. We selected a random effects model to account for time invariant variables such as parking spaces, modeling differences across beaches based on this variable…" Equation 2, page 15, provides the econometric regression. |
|
Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
?
|
None identified | None identified | Land management, ecosystem management, response to EU 2020 Biodiversity Strategy | Not applicable | None identified | To assess the number of people who would be impacted by beach closures. |
|
Biophysical Context
|
Elevation ranges from 1552 to 2442 m, on predominantly south-facing slopes | Elevations ranging from 1552 m to 2442 m, on predominantly south-facing slopes | Northern Spain; Bizkaia region | nearshore; <1.5 km offshore; <12 m depth | No additional description provided | Four separate beaches within the community of Barnstable |
|
EM Scenario Drivers
em.detail.scenarioDriverHelp
?
|
No scenarios presented | No scenarios presented | No scenarios presented | Not applicable | No scenarios presented | No scenarios presented |
EM Relationship to Other EMs or Applications
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
?
|
Method + Application | Method + Application | Method + Application | Method + Application | Method + Application | Method + Application |
|
New or Pre-existing EM?
em.detail.newOrExistHelp
?
|
New or revised model | New or revised model | New or revised model | New or revised model | Application of existing model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
em.detail.relatedEmHelp
?
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Document ID for related EM
em.detail.relatedEmDocumentIdHelp
?
|
Doc-260 | Doc-269 | Doc-260 | Doc-269 | None | None | Doc-309 | Doc-386 | Doc-387 |
|
EM ID for related EM
em.detail.relatedEmEmIdHelp
?
|
EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-79 | EM-80 | EM-81 | EM-82 | EM-83 | EM-65 | EM-66 | EM-68 | EM-69 | EM-70 | EM-71 | EM-80 | EM-81 | EM-82 | EM-83 | None | None | EM-359 | EM-682 | EM-685 | EM-683 | EM-686 |
EM Modeling Approach
EM Relationship to Time
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Temporal Extent
em.detail.tempExtentHelp
?
|
2007-2008 | 2007-2008 | 2000 - 2007 | 2006-2007 | 1978 - 2013 | 2011 - 2016 |
|
EM Time Dependence
em.detail.timeDependencyHelp
?
|
time-stationary | time-stationary | time-stationary | time-stationary | time-stationary | time-dependent |
|
EM Time Reference (Future/Past)
em.detail.futurePastHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | past time |
|
EM Time Continuity
em.detail.continueDiscreteHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | discrete |
|
EM Temporal Grain Size Value
em.detail.tempGrainSizeHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | 1 |
|
EM Temporal Grain Size Unit
em.detail.tempGrainSizeUnitHelp
?
|
Not applicable | Not applicable | Not applicable | Not applicable | Not applicable | Day |
EM Spatial Extent
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Bounding Type
em.detail.boundingTypeHelp
?
|
Physiographic or Ecological | Physiographic or Ecological | Geopolitical | Physiographic or Ecological | Watershed/Catchment/HUC | Physiographic or ecological |
|
Spatial Extent Name
em.detail.extentNameHelp
?
|
Central French Alps | Central French Alps | Bilbao Metropolitan Greenbelt | St.Croix, U.S. Virgin Islands | Guanica Bay watershed | Barnstable beaches (Craigville Beach, Kalmus Beach, Keyes Memorial Beach, and Veteran’s Park Beach) |
|
Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
?
|
10-100 km^2 | 10-100 km^2 | 100-1000 km^2 | 10-100 km^2 | 1000-10,000 km^2. | 10-100 ha |
Spatial Distribution of Computations
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Spatial Distribution
em.detail.distributeLumpHelp
?
|
spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
|
Spatial Grain Type
em.detail.spGrainTypeHelp
?
|
area, for pixel or radial feature | area, for pixel or radial feature | area, for pixel or radial feature | Not applicable | area, for pixel or radial feature | length, for linear feature (e.g., stream mile) |
|
Spatial Grain Size
em.detail.spGrainSizeHelp
?
|
20 m x 20 m | 20 m x 20 m | 2 m x 2 m | Not applicable | 30 m x 30 m | by beach site |
EM Structure and Computation Approach
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Computational Approach
em.detail.emComputationalApproachHelp
?
|
Analytic | Analytic | Analytic | Analytic | Analytic | Analytic |
|
EM Determinism
em.detail.deterStochHelp
?
|
deterministic | deterministic | deterministic | deterministic | deterministic | deterministic |
|
Statistical Estimation of EM
em.detail.statisticalEstimationHelp
?
|
|
|
|
|
|
|
Model Checking Procedures Used
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Model Calibration Reported?
em.detail.calibrationHelp
?
|
No | No | No | Yes | No | Yes |
|
Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
?
|
Yes | Yes | No | Yes | No | No |
|
Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
?
|
|
|
None |
|
None | None |
|
Model Operational Validation Reported?
em.detail.validationHelp
?
|
No | No | Yes | No | No | No |
|
Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
?
|
No | No | No | Yes | 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 | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
em.detail.relationToSpaceTerrestrialHelp
?
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
|
|
None |
|
|
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
em.detail.relationToSpaceMarineHelp
?
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| None | None | None |
|
None |
|
Centroid Lat/Long (Decimal Degree)
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
Centroid Latitude
em.detail.ddLatHelp
?
|
45.05 | 45.05 | 43.25 | 17.75 | 17.96 | 41.64 |
|
Centroid Longitude
em.detail.ddLongHelp
?
|
6.4 | 6.4 | -2.92 | -64.75 | -67.02 | -70.29 |
|
Centroid Datum
em.detail.datumHelp
?
|
WGS84 | WGS84 | WGS84 | NAD83 | WGS84 | WGS84 |
|
Centroid Coordinates Status
em.detail.coordinateStatusHelp
?
|
Provided | Provided | Provided | Estimated | Estimated | Estimated |
Environments and Scales Modeled
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
?
|
Agroecosystems | Grasslands | Agroecosystems | Grasslands | Aquatic Environment (sub-classes not fully specified) | Rivers and Streams | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Forests | Agroecosystems | Created Greenspace | Grasslands | Scrubland/Shrubland | Near Coastal Marine and Estuarine | Terrestrial Environment (sub-classes not fully specified) | Near Coastal Marine and Estuarine |
|
Specific Environment Type
em.detail.specificEnvTypeHelp
?
|
Subalpine terraces, grasslands, and meadows. | Subalpine terraces, grasslands, and meadows | none | stony coral reef | None reported | Saltwater beach |
|
EM Ecological Scale
em.detail.ecoScaleHelp
?
|
Not applicable | Ecological scale is coarser 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 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.detail.nameOfOrgsOrGroupsHelp
?
|
EM ID
em.detail.idHelp
?
|
EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
|
EM Organismal Scale
em.detail.orgScaleHelp
?
|
Community | Community | Not applicable | Guild or Assemblage | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
?
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| None Available | None Available | None Available |
|
None Available | None Available |
EnviroAtlas URL
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| None Available | None Available | Percent IUCN Status II, Percent GAP Status 1 & 2 | None Available | Acres of Land Enrolled in the Conservation Reserve Program (CRP), The Watershed Boundary Dataset (WBD) | Average Annual Precipitation |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
em.detail.cicesHelp
?
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| None | None |
|
|
|
|
<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>
fegs1Help
?
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
fegs2Help
?
| EM-71 | EM-79 | EM-193 | EM-260 | EM-435 | EM-684 |
| None | None |
|
|
None |
|