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-87 |
EM-177 ![]() |
EM Short Name
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Area & hotspots of soil accumulation, South Africa | Salmon habitat values, west coast of Canada |
EM Full Name
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Area and hotspots of soil accumulation, South Africa | Value of habitat quality changes for salmon populations, South Thompson watershed, west coast of Canada |
EM Source or Collection
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None | None |
EM Source Document ID
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271 | 286 |
Document Author
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Egoh, B., Reyers, B., Rouget, M., Richardson, D.M., Le Maitre, D.C., and van Jaarsveld, A.S. | Knowler, D.J., MacGregor, B.W., Bradford, M.J., Peterman, R.M |
Document Year
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2008 | 2003 |
Document Title
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Mapping ecosystem services for planning and management | Valuing freshwater salmon habitat on the west coast of Canada |
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 journal manuscript |
EM ID
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EM-87 |
EM-177 ![]() |
Not applicable | Not applicable | |
Contact Name
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Benis Egoh | Duncan Knowler |
Contact Address
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Water Resources Unit, Institute for Environment and Sustainability, European Commission - Joint Research Centre, Ispra, Italy | School of Resource and Environmental Management, Simon Fraser University, Burnaby, Canada BC V5H 1S6 |
Contact Email
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Not reported | djk@sfu.ca |
EM ID
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EM-87 |
EM-177 ![]() |
Summary Description
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AUTHOR'S DESCRIPTION: "We define the range of ecosystem services as areas of meaningful supply, similar to a species’ range or area of occupancy. The term ‘‘hotspots’’ was proposed by Norman Myers in the 1980s and refers to areas of high species richness, endemism and/or threat and has been widely used to prioritise areas for biodiversity conservation. Similarly, this study suggests that hotspots for ecosystem services are areas of critical management importance for the service. Here the term ecosystem service hotspot is used to refer to areas which provide large proportions of a particular service, and do not include measures of threat or endemism…Soil scientists often use soil depth to model soil production potential (soil formation) (Heimsath et al., 1997; Yuan et al., 2006). The accumulation of soil organic matter is an important process of soil formation which can be badly affected by habitat degradation and transformation (de Groot et al., 2002). Soil depth and leaf litter were used as proxies for soil accumulation. Soil depth is positively correlatedwith soil organic matter (Yuan et al., 2006); deep soils have the capacity to hold more nutrients. Litter cover was described above. Data on soil depth were obtained from the land capability map of South Africa and thresholds were based on the literature (Schoeman et al., 2002; Tekle, 2004). Areas with at least 0.4 m depth and 30% litter cover were mapped as important areas for soil accumulation, i.e. its geographic range. The hotspot was mapped as areas with at least 0.8 m depth and a 70% litter cover." | ABSTRACT: "In this paper, we present a framework for valuing benefits for fisheries from protecting areas from degradation, using the example of the Strait of Georgia coho salmon fishery in southern British Columbia, Canada. Our study improves upon previous methods used to value fish habitat in two major respects. First, we use a bioeconomic model of the coho fishery to derive estimates of value that are consistent with economic theory. Second, we estimate the value of changing the quality of fish habitat by using empirical analyses to link fish population dynamics with indices of land use in surrounding watersheds." |
Specific Policy or Decision Context Cited
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None identified | None identified |
Biophysical Context
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Semi-arid environment. Rainfall varies geographically from less than 50 to about 3000 mm per year (annual mean 450 mm). Soils are mostly very shallow with limited irrigation potential. | No additional description provided |
EM Scenario Drivers
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No scenarios presented | Habitat quality |
EM ID
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EM-87 |
EM-177 ![]() |
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-87 |
EM-177 ![]() |
Document ID for related EM
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Doc-271 | None |
EM ID for related EM
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EM-85 | EM-86 | EM-88 | EM-179 | EM-183 | EM-180 | EM-181 |
EM Modeling Approach
EM ID
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EM-87 |
EM-177 ![]() |
EM Temporal Extent
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Not reported | 1989-1999 |
EM Time Dependence
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time-stationary | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
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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Not applicable | Not applicable |
EM ID
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EM-87 |
EM-177 ![]() |
Bounding Type
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Geopolitical | Physiographic or ecological |
Spatial Extent Name
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South Africa | South Thompson watershed |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 1000-10,000 km^2. |
EM ID
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EM-87 |
EM-177 ![]() |
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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other (specify), for irregular (e.g., stream reach, lake basin) | Not applicable |
Spatial Grain Size
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Distributed across catchments with average size of 65,000 ha | Not applicable |
EM ID
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EM-87 |
EM-177 ![]() |
EM Computational Approach
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Analytic | Analytic |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-87 |
EM-177 ![]() |
Model Calibration Reported?
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No | Yes |
Model Goodness of Fit Reported?
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No | No |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | No |
Model Uncertainty Analysis Reported?
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No | No |
Model Sensitivity Analysis Reported?
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No | Yes |
Model Sensitivity Analysis Include Interactions?
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Not applicable | No |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-87 |
EM-177 ![]() |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-87 |
EM-177 ![]() |
None |
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Centroid Lat/Long (Decimal Degree)
EM ID
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EM-87 |
EM-177 ![]() |
Centroid Latitude
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-30 | 49.29 |
Centroid Longitude
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25 | -123.8 |
Centroid Datum
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WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated |
EM ID
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EM-87 |
EM-177 ![]() |
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) | Rivers and Streams | Near Coastal Marine and Estuarine |
Specific Environment Type
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Not applicable | Rivers and streams |
EM Ecological Scale
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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-87 |
EM-177 ![]() |
EM Organismal Scale
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Not applicable |
Other (Comment) ?Comment:Coho salmon stock |
Taxonomic level and name of organisms or groups identified
EM-87 |
EM-177 ![]() |
None Available |
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EnviroAtlas URL
EM-87 |
EM-177 ![]() |
None Available | The National Hydrography Dataset (NHD), GAP Ecological Systems, Ecosystem Markets: Imperiled Species and Habitats, Big game hunting recreation demand |
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-87 |
EM-177 ![]() |
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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-87 |
EM-177 ![]() |
None |
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