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-963 |
EM Short Name
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Eastern Meadowlark Abundance |
EM Full Name
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TEST: CRP Impacts on Eastern Meadowlark Abundance |
EM Source or Collection
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None ?Comment:Could not find any information pertaining to a model collection. |
EM Source Document ID
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405 |
Document Author
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Riffel, S., Scognamillo, D., and L. W. Burger |
Document Year
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2008 |
Document Title
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Effects of the Conservation Reserve Program on northern bobwhite and grassland birds |
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-963 |
Not applicable | |
Contact Name
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L. Wes Burger ?Comment:Lead author, Sam Riffell, pass away. Using last author. |
Contact Address
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Mississippi State University, Mississippi State, MS |
Contact Email
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w.burger@msstate.edu |
EM ID
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EM-963 |
Summary Description
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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, comprehen- sive 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. AUTHOR'S DESCRIPTION: For each species, we developed multiple regression models for the entire study area and for each of the seven ecological regions separately. We included only those routes that met quality standards for both bird abundance and land use data, and this left a total of 636 useable routes. The number of routes within individual ecological regions ranged from a low of 55 (central hardwoods) to a high of 154 (Appalachian Mountains). Using our estimates of bird abundance as response variables and landscape variables as explanatory variables, we used a stepwise selection process (retaining only explanatory variables that satisfied α < 0.05) to build models for each of the seven ecological regions and for the study region as a whole. |
Specific Policy or Decision Context Cited
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Food Security Act of 1985 |
Biophysical Context
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Bird Conservation Regions ranging from Central to eastern United States and from the Gulf of Mexico to the Great Lakes. |
EM Scenario Drivers
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Separate models created for each Bird Conservation Region, including different land use, agriculture, and CRP variable values. |
EM ID
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EM-963 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) |
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-963 |
Document ID for related EM
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None |
EM ID for related EM
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None |
EM Modeling Approach
EM ID
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EM-963 |
EM Temporal Extent
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1995-1999 |
EM Time Dependence
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time-stationary |
EM Time Reference (Future/Past)
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Not applicable |
EM Time Continuity
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Not applicable |
EM Temporal Grain Size Value
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Not applicable |
EM Temporal Grain Size Unit
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Not applicable |
EM ID
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EM-963 |
Bounding Type
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Physiographic or ecological |
Spatial Extent Name
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Bird Conservation Regions comprising the northern bobwhite breeding range. |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 |
EM ID
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EM-963 |
EM Spatial Distribution
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spatially distributed (in at least some cases) |
Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) |
Spatial Grain Size
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1962 km^2 |
EM ID
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EM-963 |
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-963 |
Model Calibration Reported?
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Unclear ?Comment:Does accounting for autocorrelation count as validation? |
Model Goodness of Fit Reported?
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Not applicable |
Goodness of Fit (metric| value | unit)
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None |
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-963 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-963 |
None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-963 |
Centroid Latitude
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36.53 |
Centroid Longitude
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-88.45 |
Centroid Datum
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NAD83 |
Centroid Coordinates Status
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Estimated |
EM ID
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EM-963 |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) ?Comment:Is there a way to choose more than one? |
Specific Environment Type
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A mixture of developed and natural environments including cultivated and non-cultivated cropland, pastures, roads / railways, and urban areas as well as grasslands, forest, and freshwater habitats spanning the central to eastern United States. |
EM Ecological Scale
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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-963 |
EM Organismal Scale
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Species |
Taxonomic level and name of organisms or groups identified
EM-963 |
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EnviroAtlas URL
EM-963 |
GAP Ecological Systems |
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-963 |
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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-963 |
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