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-657 | EM-939 |
EM Short Name
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Blue crabs and SAV, Chesapeake Bay, USA | REQI (River Ecosystem Quality Index), Italy | ESTIMAP- Recreation, Europe |
EM Full Name
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Blue crabs and submerged aquatic vegetation interaction, Chesapeake Bay, USA | REQI (River Ecosystem Quality Index), Marecchia River, Italy | ESTIMAP- Recreation, Europe |
EM Source or Collection
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None | None | None |
EM Source Document ID
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292 ?Comment:Conference paper |
378 | 432 |
Document Author
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Mykoniatis, N. and Ready, R. | Santolini, R, E. Morri, G. Pasini, G. Giovagnoli, C. Morolli, and G. Salmoiraghi | Zulian, G., Parrachini, M.L., Maes, J., |
Document Year
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2013 | 2014 | 2013 |
Document Title
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Evaluating habitat-fishery interactions: The case of submerged aquatic vegetation and blue crab fishery in the Chesapeake Bay | Assessing the quality of riparian areas: the case of River Ecosystem Quality Index applied to the Marecchia river (Italy) | ESTIMAP: Ecosystem services mapping at the European scale |
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 journal manuscript | Published report |
EM ID
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EM-185 | EM-657 | EM-939 |
Not applicable | Not applicable | N.A. | |
Contact Name
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Nikolaos Mykoniatis | Elisa Morri | Grazia Zulian |
Contact Address
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Department of Agricultural Economics, Sociology and Education The Pennsylvania State University | Dept. of Earth, Life, and Environmental Sciences, Urbino university, via ca le suore, campus scientifico Enrico Mattei, Urbino 61029 Italy | Joint Research Centre, Via Enrico Fermi 2749, TP 272, 21027 Ispra (VA), Italy |
Contact Email
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Not reported | elisa.morri@uniurb.it | grazia.zulian@jrc.ec.europa.e |
EM ID
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EM-185 | EM-657 | EM-939 |
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: "Riparian areas support a set of river functions and of ecosystem services (ESs). Their role is essential in reducing negative human impacts on river functionality. These aspects could be contained in the River Basin Management Plan, which is the tool for managing and planning freshwater ecosystems in a river basin. In this paper, a new index was developed, namely the River Ecosystem Quality Index (REQI). It is composed of five ecological indices, which assess the quality of riparian areas, and it was first applied to the Marecchia river (central Italy). The REQI was also compared with the Italian River Functionality Index (IFF) and the ESs measured as the capacity of land cover in providing human benefits. Data have shown a decrease in the quality of riparian areas, from the upper to lower part of river, with 53% of all subareas showing medium-quality values…" AUTHOR'S DESCRIPTION: "The evaluation of the quality of the riparian areas is based on the analysis of two fundamental elements of riparian areas: vegetation (characteristics and distribution) and wild birds, measured with standardized methodology and used as indicators of environmental quality and changes...To represent the REQI, each of the five indicators was initially scored with its own range (Figure 3(a)—(e)). Then, all results were redistributed in ranges from 1 to 5, where 5 is the best condition of all indices. Redistributed results were finally summed." | AUTHOR Descriptions: "ESTIMAP consists of a set of separate components, each of which can be run separately. The models have been all framed in the ecosystem services cascade model [4] which connects ecosystem structure and functioning to human well-being through the flow of ecosystem services. At present, three modules are operational and described in further detail in this report: pollination, recreation and coastal protectionPeople can benefit from the opportunities provided by nature for recreational activities if they are able to reach them. The Recreation Opportunity spectrum was chosen as a method to map different degrees of service available according to their proximity to the people. Remoteness and proximity have been addressed in the second step of the analysis, in order to assess how the benefit (recreation) can be delivered to people. The proxy that has been identified couples information on both variables and has been mapped by classifying the EU into zones of proximity versus remoteness. From the ROS perspective this part takes into account remoteness and to some extent expected social experience. Distance from roads and residential areas have been used as inputs. The information on the road network is provided by the TeleAtlas database, and covers all paved roads in Europe. Gravel roads have been discarded to ease the processing. Residential areas are extracted from CORINE land cover classes “continuous urban fabric” and “discontinuous urban fabric”, therefore, all urban patches larger than 25 ha are considered in the mapping. In the current exercise there was the necessity to adapt overseas experiences to the peculiarities of the European continent, especially considering that the EU does not contain large wilderness areas like other continents " |
Specific Policy or Decision Context Cited
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Not applicable | None identified | None |
Biophysical Context
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Submerged Aquatic Vegetation (SAV), eelgrass | No additional description provided | Continential Scale |
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-657 | EM-939 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application | 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-657 | EM-939 |
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 | EM-941 |
EM Modeling Approach
EM ID
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EM-185 | EM-657 | EM-939 |
EM Temporal Extent
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1993-2011 |
1996-2003 ?Comment:All the ecological analyses are based on the production of a 1:10,000 scale map of land cover with detailed classes for the vegetation obtained by overlapping the photogrammetric analysis (AIMA flight 1996) and the 2003 land-use map. |
Not applicable |
EM Time Dependence
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time-dependent | time-stationary | Not applicable |
EM Time Reference (Future/Past)
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past time | Not applicable | Not applicable |
EM Time Continuity
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discrete | Not applicable | Not applicable |
EM Temporal Grain Size Value
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1 | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Year | Not applicable | Not applicable |
EM ID
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EM-185 | EM-657 | EM-939 |
Bounding Type
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Physiographic or ecological | Watershed/Catchment/HUC | No location (no locational reference given) |
Spatial Extent Name
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Chesapeake Bay | Marecchia river catchment | Not applicable |
Spatial Extent Area (Magnitude)
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10,000-100,000 km^2 | 100-1000 km^2 | >1,000,000 km^2 |
EM ID
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EM-185 | EM-657 | EM-939 |
EM Spatial Distribution
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spatially lumped (in all cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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Not applicable | area, for pixel or radial feature | area, for pixel or radial feature |
Spatial Grain Size
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Not applicable | 500 m x 1000 m | Pixel size |
EM ID
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EM-185 | EM-657 | EM-939 |
EM Computational Approach
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Analytic | Analytic | Numeric |
EM Determinism
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deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-185 | EM-657 | EM-939 |
Model Calibration Reported?
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Yes | Not applicable | No |
Model Goodness of Fit Reported?
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Yes | Not applicable | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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Yes |
Yes ?Comment:R2 values of the analysis between the REQI, the capacity of land cover to provide ESs, and the Italian River Functionality Quality Index ? IFF. |
Unclear |
Model Uncertainty Analysis Reported?
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Yes | Not applicable | No |
Model Sensitivity Analysis Reported?
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Yes | Not applicable | Yes |
Model Sensitivity Analysis Include Interactions?
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Yes | Not applicable | Unclear |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-185 | EM-657 | EM-939 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-185 | EM-657 | EM-939 |
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None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-185 | EM-657 | EM-939 |
Centroid Latitude
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36.99 | 43.89 | Not applicable |
Centroid Longitude
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-75.95 | 12.3 | Not applicable |
Centroid Datum
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WGS84 | WGS84 | Not applicable |
Centroid Coordinates Status
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Estimated | Estimated | Not applicable |
EM ID
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EM-185 | EM-657 | EM-939 |
EM Environmental Sub-Class
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None | Rivers and Streams | Inland Wetlands | Terrestrial Environment (sub-classes not fully specified) | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Yes | Riparian zone along major river | Not applicable |
EM Ecological Scale
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Yes | 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-185 | EM-657 | EM-939 |
EM Organismal Scale
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Yes |
Species ?Comment:Bird species for faunistic index of conservation. |
Not applicable |
Taxonomic level and name of organisms or groups identified
EM-185 | EM-657 | EM-939 |
None Available | None Available | None Available |
EnviroAtlas URL
EM-185 | EM-657 | EM-939 |
None Available | Ecosystem Markets: Imperiled Species and Habitats | Dasymetric Allocation of Population, Ecosystem Markets: Imperiled Species and Habitats, Waterbody 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-185 | EM-657 | EM-939 |
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-657 | EM-939 |
None | None | None |