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-106 |
EM-760 ![]() |
EM Short Name
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Value of Habitat for Shrimp, Campeche, Mexico | WESP: Marsh & wet meadow, ID, USA |
EM Full Name
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Value of Habitat for Shrimp, Campeche, Mexico | WESP: Seasonally flooded marsh & wet meadow, Idaho, USA |
EM Source or Collection
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None | None |
EM Source Document ID
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227 |
393 ?Comment:Additional data came from electronic appendix provided by author Chris Murphy. |
Document Author
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Barbier, E. B., and Strand, I. | Murphy, C. and T. Weekley |
Document Year
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1998 | 2012 |
Document Title
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Valuing mangrove-fishery linkages: A case study of Campeche, Mexico | Measuring outcomes of wetland restoration, enhancement, and creation in Idaho-- Assessing potential functions, values, and condition in a watershed context. |
Document Status
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Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published report |
EM ID
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EM-106 |
EM-760 ![]() |
Not applicable | Not applicable | |
Contact Name
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E.B. Barbier | Chris Murphy |
Contact Address
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Environment Department, University of York, York YO1 5DD, UK | Idaho Dept. Fish and Game, Wildlife Bureau, Habitat Section, Boise, ID |
Contact Email
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Not reported | chris.murphy@idfg.idaho.gov |
EM ID
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EM-106 |
EM-760 ![]() |
Summary Description
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AUTHOR'S DESCRIPTION: "We assume throughout that shrimp harvesting occurs through open access management that yields production which is exported internationally, and we modify a standard open access fishery model to account explicitly for the effect of the mangrove area on carrying capacity and thus production.We derive the conditions determining the long-run equilibrium of the model, including the comparative static effects of a change in mangrove area, on this equilibrium. Through regressing a relationship between shrimp harvest, effort and mangrove area over time, we estimate parameters based on the combinations of the bioeconomic parameters of the model determining the comparative statics. By incorporating additional economic data, we are able to simulate an estimate of the effect of changes in mangrove area in Laguna de Terminos on the production and value of shrimp harvests in Campeche state." (153) | A wetland restoration monitoring and assessment program framework was developed for Idaho. The project goal was to assess outcomes of substantial governmental and private investment in wetland restoration, enhancement and creation. The functions, values, condition, and vegetation at restored, enhanced, and created wetlands on private and state lands across Idaho were retrospectively evaluated. Assessment was conducted at multiple spatial scales and intensities. Potential functions and values (ecosystem services) were rapidly assessed using the Oregon Rapid Wetland Assessment Protocol. Vegetation samples were analyzed using Floristic Quality Assessment indices from Washington State. We compared vegetation of restored, enhanced, and created wetlands with reference wetlands that occurred in similar hydrogeomorphic environments determined at the HUC 12 level. |
Specific Policy or Decision Context Cited
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None identified | None identified |
Biophysical Context
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Gulf of Mexico; mangrove-lagoon system | restored, enhanced and created wetlands |
EM Scenario Drivers
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No scenarios presented | Sites, function or habitat focus |
EM ID
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EM-106 |
EM-760 ![]() |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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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-106 |
EM-760 ![]() |
Document ID for related EM
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None | Doc-390 |
EM ID for related EM
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EM-185 | EM-319 | EM-718 | EM-734 | EM-743 |
EM Modeling Approach
EM ID
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EM-106 |
EM-760 ![]() |
EM Temporal Extent
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1980-1990 | 2010-2012 |
EM Time Dependence
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time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | past time |
EM Time Continuity
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Not applicable | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Year | Not applicable |
EM ID
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EM-106 |
EM-760 ![]() |
Bounding Type
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Physiographic or Ecological | Multiple unrelated locations (e.g., meta-analysis) |
Spatial Extent Name
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Laguna de Terminos Mangrove system | Wetlands in idaho |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 100,000-1,000,000 km^2 |
EM ID
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EM-106 |
EM-760 ![]() |
EM Spatial Distribution
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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 | Not applicable |
Spatial Grain Size
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1 km x 1 km | Not applicable |
EM ID
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EM-106 |
EM-760 ![]() |
EM Computational Approach
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Analytic | Numeric |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-106 |
EM-760 ![]() |
Model Calibration Reported?
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Yes | No |
Model Goodness of Fit Reported?
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Yes | No |
Goodness of Fit (metric| value | unit)
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None |
Model Operational Validation Reported?
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No | No |
Model Uncertainty Analysis Reported?
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Yes | No |
Model Sensitivity Analysis Reported?
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Yes | No |
Model Sensitivity Analysis Include Interactions?
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Unclear | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-106 |
EM-760 ![]() |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-106 |
EM-760 ![]() |
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None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-106 |
EM-760 ![]() |
Centroid Latitude
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18.61 | 44.06 |
Centroid Longitude
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-91.55 | -114.69 |
Centroid Datum
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WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated |
EM ID
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EM-106 |
EM-760 ![]() |
EM Environmental Sub-Class
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Near Coastal Marine and Estuarine | Inland Wetlands |
Specific Environment Type
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Mangrove | created, restored and enhanced wetlands |
EM Ecological Scale
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Ecological scale is finer than that of 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-106 |
EM-760 ![]() |
EM Organismal Scale
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Guild or Assemblage | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-106 |
EM-760 ![]() |
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None Available |
EnviroAtlas URL
EM-106 |
EM-760 ![]() |
GAP Ecological Systems, Big game hunting recreation demand | Total Annual Reduced Nitrogen Deposition, Carbon Storage by Tree Biomass |
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-106 |
EM-760 ![]() |
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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-106 |
EM-760 ![]() |
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None |