EcoService Models Library (ESML)
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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.
EM Identity and Description
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Short Name
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Urban Temperature, Baltimore, MD, USA | Retained rainwater, Guánica Bay, Puerto Rico | WTP for a beach day, Massachusetts, USA | Indigo bunting abund, Piedmont region, USA |
EM Full Name
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Urban Air Temperature Change, Baltimore, MD, USA | Retained rainwater, Guánica Bay, Puerto Rico, USA | Willingness to pay (WTP) for a beach day, Barnstable, Massachusetts, USA | Indigo bunting abundance, Piedmont ecoregion, USA |
EM Source or Collection
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i-Tree | USDA Forest Service | US EPA | US EPA | None |
EM Source Document ID
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217 | 338 | 386 | 405 |
Document Author
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Heisler, G. M., Ellis, A., Nowak, D. and Yesilonis, I. | 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 | Riffel, S., Scognamillo, D., and L. W. Burger |
Document Year
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2016 | 2017 | 2018 | 2008 |
Document Title
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Modeling and imaging land-cover influences on air-temperature in and near Baltimore, MD | 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 | Effects of the Conservation Reserve Program on northern bobwhite and grassland birds |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Not applicable | Not applicable | Not applicable | Not applicable | |
Contact Name
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Gordon M. Heisler | Susan H. Yee | Kate K, Mulvaney | Sam Riffell |
Contact Address
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5 Moon Library, c/o SUNY-ESF, Syracuse, NY 13210 | U.S. Environmental Protection Agency, Gulf Ecology Division, Gulf Breeze, FL 32561, USA | Not reported | Department of Wildlife & Fisheries, Mississippi State University, Mississippi State, MS 39762, USA |
Contact Email
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gheisler@fs.fed.us | yee.susan@epa.gov | Mulvaney.Kate@EPA.gov | sriffell@cfr.msstate.edu |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Summary Description
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An empirical model for predicting below-canopy air temperature differences is developed for evaluating urban structural and vegetation influences on air temperature in and near Baltimore, MD. AUTHOR'S DESCRIPTION: "The study . . . Developed an equation for predicting air temperature at the 1.5m height as temperature difference, T, between a reference weather station and other stations in a variety of land uses. Predictor variables were derived from differences in land cover and topography along with forcing atmospheric conditions. The model method was empirical multiple linear regression analysis.. . Independent variables included remotely sensed tree cover, impervious cover, water cover, descriptors of topography, an index of thermal stability, vapor pressure deficit, and antecedent precipitation." | AUTHOR'S DESCRIPTION: "In total, 19 ecosystem services metrics were identified as relevant to stakeholder objectives in the Guánica Bay watershed identified during the 2013 Public Values Forum (Table 2)...Ecological production functions were applied to translate LULC measures of ecosystem condition to supply of ecosystem services…The volume of retained rainwater per unit area (in^3/in^2) includes both the maximum soil moisture retention and the initial abstraction of water before runoff due to infiltration, evaporation, or interception by vegetation…" | 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 used existing studies in a meta-analysis to estimate appropriate benefit transfer values of consumer surplus per beach visit for Barnstable. The studies we include in the model are for beaches across the United States, allowing the metaregression model to be more broadly applicable to other beaches and for values to be adjusted based on appropriate site attributes...To identify relevant studies, we selected 25 studies of beach use and swimming from the Recreation Use Values Database (RUVD), where consumer surplus values are presented as value per day in 2016 dollars...We added beach length and history of closures to contextualize the model for our application by proxying water quality and site quality." Equation 1, page 11, provides the meta-regression. | ABSTRACT:"The Conservation Reserve Program (CRP) has converted just over 36 million acres of cropland into potential wildlife habitat, primarily grassland. Thus, the CRP should benefit grassland songbirds, a group of species that is declining across the United States and is of conservation concern. Additionally, the CRP is an important part of multi-agency, regional efforts to restore northern bobwhite populations. However, comprehensive assessments of the wildlife benefits of CRP at regional scales are lacking. We used Breeding Bird Survey and National Resources Inventory data to assess the potential for the CRP to benefit northern bobwhite and other grassland birds with overlapping ranges and similar habitat associations. We built regression models for 15 species in seven different ecological regions. Forty-nine of 108 total models contained significant CRP effects (P < 0.05), and 48 of the 49 contained positive effects. Responses to CRP varied across ecological regions. Only eastern meadowlark was positively related to CRP in all the ecological regions, and western meadowlark was the only species never related to CRP. CRP was a strong predictor of bird abundance compared to other land cover types. The potential for CRP habitat as a regional conservation tool to benefit declining grassland bird populations should continue to be assessed at a variety of spatial scales. We caution that bird-CRP relations varied from region to region and among species. Because the NRI provides relatively coarse resolution information on CRP, more detailed information about CRP habitats (spatial arrangement, age of the habitat (time since planting), specific conservation practices used) should be included in future assessments to fully understand where and to what extent CRP can benefit grassland birds." |
Specific Policy or Decision Context Cited
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None identified | Meeting water demands for agriculture and domestic purposes. | Economic value of protecting coastal beach water quality from contamination caused closures. | None reported |
Biophysical Context
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One airport site, one urban site, one site in deciduous leaf litter, and four sites in short grass ground cover. Measured sky view percentages ranged from 6% at the woods site, to 96% at the rural open site. | No additional descriptions provided | Four separate beaches within the community of Barnstable | Conservation Reserve Program lands left to go fallow |
EM Scenario Drivers
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No scenarios presented | No scenarios presented | No scenarios presented | N/A |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application | Method + Application |
New or Pre-existing EM?
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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
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EM-306 | EM-428 | EM-682 | EM-846 |
Document ID for related EM
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Doc-220 | Doc-219 | Doc-218 | None | Doc-386 | Doc-387 | Doc-405 |
EM ID for related EM
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None | None | EM-684 | EM-685 | EM-683 | EM-686 | EM-831 | EM-838 | EM-839 | EM-840 | EM-841 | EM-842 | EM-843 | EM-844 | EM-845 | EM-847 |
EM Modeling Approach
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Temporal Extent
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May 5-Sept 30 2006 | 2006 - 2012 | July 1, 2011 to June 31, 2016 | 2008 |
EM Time Dependence
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time-dependent | time-stationary | time-stationary | time-stationary |
EM Time Reference (Future/Past)
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future time | Not applicable | Not applicable | Not applicable |
EM Time Continuity
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discrete | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Value
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1 | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Hour | Not applicable | Not applicable | Not applicable |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Bounding Type
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Geopolitical | Watershed/Catchment/HUC | Physiographic or ecological | Physiographic or ecological |
Spatial Extent Name
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Baltimore, MD | Guanica Bay watershed | Barnstable beaches (Craigville Beach, Kalmus Beach, Keyes Memorial Beach, and Veteran’s Park Beach) | Piedmont Ecoregion |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 1000-10,000 km^2. | 10-100 ha | 100,000-1,000,000 km^2 |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Spatial Distribution
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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) |
Spatial Grain Type
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area, for pixel or radial feature | area, for pixel or radial feature | length, for linear feature (e.g., stream mile) | Not applicable |
Spatial Grain Size
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10m x 10m | 30 m x 30 m | by beach site | Not applicable |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Computational Approach
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Analytic | Analytic | Analytic | Analytic |
EM Determinism
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deterministic | deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Model Calibration Reported?
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Yes | No | Yes | Yes |
Model Goodness of Fit Reported?
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Yes | No | Yes | No |
Goodness of Fit (metric| value | unit)
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None |
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None |
Model Operational Validation Reported?
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No | No | No | No |
Model Uncertainty Analysis Reported?
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No | No | No | No |
Model Sensitivity Analysis Reported?
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No | No |
Yes ?Comment:p-values of <0.05 and <0.01 provided for regression coefficient explanatory variables. |
Yes |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-306 | EM-428 | EM-682 | EM-846 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-306 | EM-428 | EM-682 | EM-846 |
None | None |
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None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
Centroid Latitude
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39.28 | 17.96 | 41.64 | 36.23 |
Centroid Longitude
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-76.62 | -67.02 | -70.29 | -81.9 |
Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated | Estimated | Estimated |
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Created Greenspace | Atmosphere | Inland Wetlands | Forests | Agroecosystems | Grasslands | Scrubland/Shrubland | Barren | Near Coastal Marine and Estuarine | Grasslands |
Specific Environment Type
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Urban landscape and surrounding area | 13 LULC were used | Saltwater beach | grasslands |
EM Ecological Scale
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Ecological scale corresponds to 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 of differentiation of organisms modeled
EM ID
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EM-306 | EM-428 | EM-682 | EM-846 |
EM Organismal Scale
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Not applicable | Not applicable | Not applicable | Species |
Taxonomic level and name of organisms or groups identified
EM-306 | EM-428 | EM-682 | EM-846 |
None Available | None Available | None Available |
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EnviroAtlas URL
EM-306 | EM-428 | EM-682 | EM-846 |
Average Annual Precipitation, Percent Impervious Area | The Watershed Boundary Dataset (WBD) | None Available | GAP Ecological Systems, 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-306 | EM-428 | EM-682 | EM-846 |
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<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)
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None |
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