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-651 |
EM-821 ![]() |
EM Short Name
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Urban Temperature, Baltimore, MD, USA | Dickcissel density, CREP, Iowa, USA | Aquatic vertebrate IBI for Western streams, USA |
EM Full Name
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Urban Air Temperature Change, Baltimore, MD, USA | Dickcissel population density, CREP (Conservation Reserve Enhancement Program) wetlands, Iowa, USA | Development of an aquatic vertebrate index of biotic integrity (IBI) for Western streams, USA |
EM Source or Collection
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i-Tree | USDA Forest Service | None | None |
EM Source Document ID
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217 | 372 | 404 |
Document Author
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Heisler, G. M., Ellis, A., Nowak, D. and Yesilonis, I. | Otis, D. L., W. G. Crumpton, D. Green, A. K. Loan-Wilsey, R. L. McNeely, K. L. Kane, R. Johnson, T. Cooper, and M. Vandever | Pont, D., Hughes, R.M., Whittier, T.R., and S. Schmutz. |
Document Year
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2016 | 2010 | 2009 |
Document Title
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Modeling and imaging land-cover influences on air-temperature in and near Baltimore, MD | Assessment of environmental services of CREP wetlands in Iowa and the midwestern corn belt | A Predictive Index of Biotic Integrity Model for A predictive index of biotic integrity model foraquatic-vertebrate assemblages of Western U.S. Streams |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published report | Published journal manuscript |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
Not applicable | Not applicable | Not applicable | |
Contact Name
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Gordon M. Heisler | David Otis | Didier Pont |
Contact Address
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5 Moon Library, c/o SUNY-ESF, Syracuse, NY 13210 | U.S. Geological Survey, Iowa Cooperative Fish and Wildlife Research Unit, Iowa State University | Centre d’E´ tude du Machinisme Agricole et du Genie Rural, des Eaux et Foreˆts (Cemagref), Unit HYAX Hydrobiologie, 3275 Route de Ce´zanne, Le Tholonet, 13612 Aix en Provence, France |
Contact Email
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gheisler@fs.fed.us | dotis@iastate.edu | didier.pont@cemagref.fr |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
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." | ABSTRACT: "This final project report is a compendium of 3 previously submitted progress reports and a 4th report for work accomplished from August – December, 2009. Our initial primary objective (Progress Report I) was prediction of environmental services provided by the 27 Iowa Conservation Reserve Enhancement Program (CREP) wetland sites that had been completed by 2007 in the Prairie Pothole Region of northcentral Iowa. The sites contain 102.4 ha of wetlands and 377.4 ha of associated grassland buffers... With respect to wildlife habitat value, USFWS models predicted that the 27 wetlands would provide habitat for 136 pairs of 6 species of ducks, 48 pairs of Canada Geese, and 839 individuals of 5 grassland songbird species of special concern..." AUTHOR'S DESCRIPTION: "The migratory bird benefits of the 27 CREP sites were predicted for Dickcissel (Spiza americana)... Population estimates for these species were calculated using models developed by Quamen (2007) for the Prairie Pothole Region of Iowa (Table 3). The “neighborhood analysis” tool in the spatial analysis extension of ArcGIS (2008) was used to create landscape composition variables (grass400, grass3200, hay400, hay3200, tree400) needed for model input (see Table 3 for variable definitions). Values for the species-specific relative abundance (bbspath) variable were acquired from Diane Granfors, USFWS HAPET office. The equations for each model were used to calculate bird density (birds/ha) for each 15-m2 pixel of the land coverage. Next, the “zonal statistics” tool in the spatial analyst extension of ArcGIS (ESRI 2008) was used to calculate the average bird density for each CREP buffer. A population estimate for each site was then calculated by multiplying the average density by the buffer size." Equation: DICK density = 1-1/1+e^(-6.811334 + 1.889878 * bbspath) * e^(-1.831015 + 0.0312571 * hay400) | ABSTRACT: "Because of natural environmental and faunal differences and scientific perspectives, numerous indices of biological integrity (IBIs) have been developed at local, state, and regional scales in the USA. These multiple IBIs, plus different criteria for judging impairment, hinder rigorous national and multistate assessments. Many IBI metrics are calibrated for water body size, but none are calibrated explicitly for other equally important natural variables such as air temperature, channel gradient, or geology. We developed a predictive aquatic-vertebrate IBI model using a total of 871 stream sites (including 162 least-disturbed and 163 most-disturbed sites) sampled as part of the U.S. Environmental Protection Agency’s Environmental Monitoring and Assessment Program survey of 12 conterminous western U.S. states. The selected IBI metrics (calculated from both fish and aquatic amphibians) were vertebrate species richness, benthic native species richness, assemblage tolerance index, proportion of invertivore–piscivore species, and proportion of lithophilic-reproducing species. Mean model IBI scores differed significantly between least-disturbed and most-disturbed sites as well as among ecoregions. Based on a model IBI impairment criterion of 0.44 (risks of type I and II errors balanced), an estimated 34.7% of stream kilometers in the western USA were deemed impaired, compared with 18% for a set of traditional IBIs. Also, the model IBI usually displayed less variability than the traditional IBIs, presumably because it was better calibrated for natural variability. " |
Specific Policy or Decision Context Cited
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None identified | None identified | 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. | Prairie pothole region of north-central Iowa | Wadeable and boatable streams in 12 western USA states |
EM Scenario Drivers
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No scenarios presented | No scenarios presented | not applicable |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application View EM Runs |
New or Pre-existing EM?
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New or revised model |
Application of existing model ?Comment:Models developed by Quamen (2007). |
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-651 |
EM-821 ![]() |
Document ID for related EM
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Doc-220 | Doc-219 | Doc-218 | Doc-372 | Doc-403 |
EM ID for related EM
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None | EM-652 | EM-650 | EM-649 | EM-648 | EM-820 | EM-826 |
EM Modeling Approach
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
EM Temporal Extent
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May 5-Sept 30 2006 | 1992-2007 | 2004-2005 |
EM Time Dependence
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time-dependent | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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future time | Not applicable | past time |
EM Time Continuity
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discrete | Not applicable | Not applicable |
EM Temporal Grain Size Value
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1 | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Hour | Not applicable | Not applicable |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
Bounding Type
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Geopolitical | Multiple unrelated locations (e.g., meta-analysis) | Geopolitical |
Spatial Extent Name
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Baltimore, MD | CREP (Conservation Reserve Enhancement Program) wetland sites | Western 12 states |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 1-10 km^2 | >1,000,000 km^2 |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
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) ?Comment:871 total sites surveyed for this work |
Spatial Grain Type
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area, for pixel or radial feature | other (specify), for irregular (e.g., stream reach, lake basin) | other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
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10m x 10m | multiple, individual, irregular shaped sites | stream reach |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
EM Computational Approach
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Analytic | Analytic | Analytic |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
Model Calibration Reported?
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Yes | Unclear | No |
Model Goodness of Fit Reported?
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Yes | No | No |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | Unclear |
Yes ?Comment:Compared to another journal manuscript IBI scores (Whittier et al) |
Model Uncertainty Analysis Reported?
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No | No | No |
Model Sensitivity Analysis Reported?
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No | No | Yes |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Yes |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-306 | EM-651 |
EM-821 ![]() |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-306 | EM-651 |
EM-821 ![]() |
None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
Centroid Latitude
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39.28 | 42.62 | 44.2 |
Centroid Longitude
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-76.62 | -93.84 | -113.07 |
Centroid Datum
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WGS84 | WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated | Estimated |
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Created Greenspace | Atmosphere | Inland Wetlands | Agroecosystems | Grasslands | Rivers and Streams |
Specific Environment Type
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Urban landscape and surrounding area | Grassland buffering inland wetlands set in agricultural land | wadeable and boatable streams |
EM Ecological Scale
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Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-306 | EM-651 |
EM-821 ![]() |
EM Organismal Scale
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Not applicable | Species | Guild or Assemblage |
Taxonomic level and name of organisms or groups identified
EM-306 | EM-651 |
EM-821 ![]() |
None Available |
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EnviroAtlas URL
EM-306 | EM-651 |
EM-821 ![]() |
Average Annual Precipitation, Percent Impervious Area | GAP Ecological Systems | Total Annual Reduced Nitrogen Deposition, U.S. EPA (Omernik) ecoregions |
EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system
CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)
EM-306 | EM-651 |
EM-821 ![]() |
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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)
EM-306 | EM-651 |
EM-821 ![]() |
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