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 Short Name
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Urban Temperature, Baltimore, MD, USA |
EM Full Name
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Urban Air Temperature Change, Baltimore, MD, USA |
EM Source or Collection
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i-Tree | USDA Forest Service |
EM Source Document ID
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217 |
Document Author
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Heisler, G. M., Ellis, A., Nowak, D. and Yesilonis, I. |
Document Year
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2016 |
Document Title
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Modeling and imaging land-cover influences on air-temperature in and near Baltimore, MD |
Document Status
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Peer reviewed and published |
Comments on Status
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Published journal manuscript |
EM ID
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EM-306 |
Not applicable | |
Contact Name
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Gordon M. Heisler |
Contact Address
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5 Moon Library, c/o SUNY-ESF, Syracuse, NY 13210 |
Contact Email
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gheisler@fs.fed.us |
EM ID
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EM-306 |
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." |
Specific Policy or Decision Context Cited
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None identified |
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. |
EM Scenario Drivers
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No scenarios presented |
EM ID
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EM-306 |
Method Only, Application of Method or Model Run
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Method + Application |
New or Pre-existing EM?
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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 |
Document ID for related EM
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Doc-220 | Doc-219 | Doc-218 |
EM ID for related EM
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None |
EM Modeling Approach
EM ID
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EM-306 |
EM Temporal Extent
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May 5-Sept 30 2006 |
EM Time Dependence
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time-dependent |
EM Time Reference (Future/Past)
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future time |
EM Time Continuity
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discrete |
EM Temporal Grain Size Value
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1 |
EM Temporal Grain Size Unit
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Hour |
EM ID
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EM-306 |
Bounding Type
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Geopolitical |
Spatial Extent Name
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Baltimore, MD |
Spatial Extent Area (Magnitude)
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100-1000 km^2 |
EM ID
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EM-306 |
EM Spatial Distribution
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spatially distributed (in at least some cases) |
Spatial Grain Type
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area, for pixel or radial feature |
Spatial Grain Size
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10m x 10m |
EM ID
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EM-306 |
EM Computational Approach
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Analytic |
EM Determinism
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deterministic |
Statistical Estimation of EM
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EM ID
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EM-306 |
Model Calibration Reported?
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Yes |
Model Goodness of Fit Reported?
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Yes |
Goodness of Fit (metric| value | unit)
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Model Operational Validation Reported?
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No |
Model Uncertainty Analysis Reported?
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No |
Model Sensitivity Analysis Reported?
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No |
Model Sensitivity Analysis Include Interactions?
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Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-306 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-306 |
None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-306 |
Centroid Latitude
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39.28 |
Centroid Longitude
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-76.62 |
Centroid Datum
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WGS84 |
Centroid Coordinates Status
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Estimated |
EM ID
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EM-306 |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Created Greenspace | Atmosphere |
Specific Environment Type
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Urban landscape and surrounding area |
EM Ecological Scale
em.detail.ecoScaleHelp
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Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-306 |
EM Organismal Scale
em.detail.orgScaleHelp
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Not applicable |
Taxonomic level and name of organisms or groups identified
EM-306 |
None Available |
EnviroAtlas URL
EM-306 |
Average Annual Precipitation, Percent Impervious 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-306 |
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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 |
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