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-185 | EM-819 | EM-964 |
EM Short Name
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Blue crabs and SAV, Chesapeake Bay, USA | QHEI | EcoSim II - method |
EM Full Name
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Blue crabs and submerged aquatic vegetation interaction, Chesapeake Bay, USA | QHEI (Qualitative Habitat Evaluation Index) | EcoSim II - method |
EM Source or Collection
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None | None | None |
EM Source Document ID
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292 ?Comment:Conference paper |
402 | 448 |
Document Author
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Mykoniatis, N. and Ready, R. | Taft, B., J. P. Koncelik | Walters, C., Pauly, D., Christensen, V., and J.F. Kitchell |
Document Year
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2013 | 2006 | 2000 |
Document Title
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Evaluating habitat-fishery interactions: The case of submerged aquatic vegetation and blue crab fishery in the Chesapeake Bay | Methods for assessing habitat in flowing waters: Using the Qualitative Habitat Evaluation Index (QHEI) | Representing density dependent consequences of life history strategies in aquatic ecostems: EcoSim II |
Document Status
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Not formally documented | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Conference proceedings | Published report | Published journal manuscript |
EM ID
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EM-185 | EM-819 | EM-964 |
Not applicable | Not applicable | https://ecopath.org/downloads/ | |
Contact Name
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Nikolaos Mykoniatis | Edward T. Rankin | Carl Walters |
Contact Address
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Department of Agricultural Economics, Sociology and Education The Pennsylvania State University | Midwest Biodiversity Institute, P.O. Box 21561, Columbus, OH 43221-0561 | Fisheries Centre, University of British Columbia, Vancouver, British Columbia, British Columbia, Canada, V6T 1Z4 |
Contact Email
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Not reported | Not reported | c.walters@oceans.ubc.ca |
EM ID
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EM-185 | EM-819 | EM-964 |
Summary Description
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ABSTRACT: "This paper investigates habitat-fisheries interaction between two important resources in the Chesapeake Bay: blue crabs and Submerged Aquatic Vegetation (SAV). A habitat can be essential to a species (the species is driven to extinction without it), facultative (more habitat means more of the species, but species can exist at some level without any of the habitat) or irrelevant (more habitat is not associated with more of the species). An empirical bioeconomic model that nests the essential-habitat model into its facultative-habitat counterpart is estimated. Two alternative approaches are used to test whether SAV matters for the crab stock. Our results indicate that, if we do not have perfect information on habitat-fisheries linkages, the right approach would be to run the more general facultative-habitat model instead of the essential- habitat one." | ABSTRACT: "This document summarizes the methodology for completing a general evaluation of macrohabitat, generally done by the fish field crew leader while sampling each location using the Ohio EPA Site Description Sheet - Fish (Appendix 1). This form is used to tabulate data and information for calculating the Qualitative Habitat Evaluation Index (QHEI). The following guidance should be used when completing the site evaluation form." AUTHORS' DESCRIPTION: "The Qualitative Habitat Evaluation Index (QHEI) is a physical habitat index designed to provide an empirical, quantified evaluation of the general lotic macrohabitat characteristics that are important to fish communities. A detailed analysis of the development and use of the QHEI is available in Rankin (1989) and Rankin (1995). The QHEI is composed of six principal metrics each of which are described below. The maximum possible QHEI site score is 100. Each of the metrics are scored individually and then summed to provide the total QHEI site score. This is completed at least once for each sampling site during each year of sampling. An exception to this convention would be when substantial changes to the macrohabitat have occurred between sampling passes. Standardized definitions for pool, run, and riffle habitats, for which a variety of existing definitions and perceptions exist, are essential for accurately using the QHEI." ENTERERS' DESCRIPTION: "Additional information is entered on the back of the data sheet, including; method, distance, stage, canopy, clarity, aesthetics, maintenance, recreation, issues, measurments and stream drawing." | ABSTRACT: " EcoSim II uses results from the Ecopath procedure for trophic mass-balance analysis to define biomass dynamics models for predicting temporal change in exploited ecosystems. Key populations can be repre- sented in further detail by using delay-difference models to account for both biomass and numbers dynamics. A major problem revealed by linking the population and biomass dynamics models is in representation of population responses to changes in food supply; simple proportional growth and reproductive responses lead to unrealistic predic- tions of changes in mean body size with changes in fishing mortality. EcoSim II allows users to specify life history mechanisms to avoid such unrealistic predictions: animals may translate changes in feed- ing rate into changes in reproductive rather than growth rates, or they may translate changes in food availability into changes in foraging time that in turn affects predation risk. These options, along with model relationships for limits on prey availabil- ity caused by predation avoidance tactics, tend to cause strong compensatory responses in modeled populations. It is likely that such compensatory responses are responsible for our inability to find obvious correlations between interacting trophic components in fisheries time-series data. But Eco- sim II does not just predict strong compensatory responses: it also suggests that large piscivores may be vulnerable to delayed recruitment collapses caused by increases in prey species that are in turn competitors/predators of juvenile piscivores " |
Specific Policy or Decision Context Cited
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Not applicable | Flowing water habitat assessment for Ohio EPA | None |
Biophysical Context
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Submerged Aquatic Vegetation (SAV), eelgrass | No additional description provided | None, Ocean ecosystems |
EM Scenario Drivers
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Essential or Facultative habitat | No scenarios presented | N/A |
EM ID
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EM-185 | EM-819 | EM-964 |
Method Only, Application of Method or Model Run
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Method + Application | Method Only | Method Only |
New or Pre-existing EM?
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Application of existing model | 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-185 | EM-819 | EM-964 |
Document ID for related EM
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Doc-227 | None | None |
EM ID for related EM
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EM-106 | None | None |
EM Modeling Approach
EM ID
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EM-185 | EM-819 | EM-964 |
EM Temporal Extent
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1993-2011 | Not applicable | Not applicable |
EM Time Dependence
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time-dependent | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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past time | Not applicable | both |
EM Time Continuity
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discrete | Not applicable |
discrete ?Comment:Modeller dependent |
EM Temporal Grain Size Value
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1 | Not applicable | 1 |
EM Temporal Grain Size Unit
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Year | Not applicable | Day |
EM ID
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EM-185 | EM-819 | EM-964 |
Bounding Type
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Physiographic or ecological | Not applicable | Other |
Spatial Extent Name
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Chesapeake Bay | Not applicable | Not applicable |
Spatial Extent Area (Magnitude)
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10,000-100,000 km^2 | Not applicable | Not applicable |
EM ID
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EM-185 | EM-819 | EM-964 |
EM Spatial Distribution
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spatially lumped (in all cases) | spatially lumped (in all cases) | spatially lumped (in all cases) |
Spatial Grain Type
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Not applicable | Not applicable | Not applicable |
Spatial Grain Size
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Not applicable | Not applicable | Not applicable |
EM ID
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EM-185 | EM-819 | EM-964 |
EM Computational Approach
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Analytic | Not applicable | Analytic |
EM Determinism
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deterministic | Not applicable | deterministic |
Statistical Estimation of EM
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EM ID
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EM-185 | EM-819 | EM-964 |
Model Calibration Reported?
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Yes | Not applicable | No |
Model Goodness of Fit Reported?
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Yes | Not applicable | No |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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Yes | Not applicable | Not applicable |
Model Uncertainty Analysis Reported?
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Yes | Not applicable | Not applicable |
Model Sensitivity Analysis Reported?
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Yes | Not applicable | Not applicable |
Model Sensitivity Analysis Include Interactions?
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Yes | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-185 | EM-819 | EM-964 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-185 | EM-819 | EM-964 |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-185 | EM-819 | EM-964 |
Centroid Latitude
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36.99 | Not applicable | Not applicable |
Centroid Longitude
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-75.95 | Not applicable | Not applicable |
Centroid Datum
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WGS84 | Not applicable | Not applicable |
Centroid Coordinates Status
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Estimated | Not applicable | Not applicable |
EM ID
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EM-185 | EM-819 | EM-964 |
EM Environmental Sub-Class
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None | Rivers and Streams | Open Ocean and Seas |
Specific Environment Type
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Yes | Flowing fresh waters | Pelagic |
EM Ecological Scale
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Yes | 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-185 | EM-819 | EM-964 |
EM Organismal Scale
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Yes | Not applicable |
Other (Comment) ?Comment:Varied levels of taxonomic order |
Taxonomic level and name of organisms or groups identified
EM-185 | EM-819 | EM-964 |
None Available | None Available |
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EnviroAtlas URL
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-185 | EM-819 | EM-964 |
None |
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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-185 | EM-819 | EM-964 |
None | None |
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