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-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Short Name
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SPARROW, Northeastern USA | Redfish and cold water coral (EFH), Norway | Red-winged blackbird abun, Piedmont region, USA | i-Tree species selector v. 4.0 | ESTIMAP - Pollination potential, Iran |
EM Full Name
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SPARROW (SPAtially Referenced Regressions On Watershed Attributes), Northeastern USA | Linkage between redfish and cold water coral, Norway (essential fish habitat model) | Red-winged blackbird abundance, Piedmont ecoregion, USA | i-Tree species selector v. 4.0 | ESTIMAP - Pollination potential, Iran |
EM Source or Collection
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US EPA | None | None | i-Tree | None |
EM Source Document ID
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86 | 259 | 405 |
426 ?Comment:Doc# 427 is an additional source for this EM. |
434 |
Document Author
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Moore, R. B., Johnston, C.M., Smith, R. A. and Milstead, B. | Foley N.S., Kahui V.K., Armstrong C.W., Van Rensburg T.M | Riffel, S., Scognamillo, D., and L. W. Burger | i-Tree | Rahimi, E., Barghjelveh, S., and P. Dong |
Document Year
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2011 | 2010 | 2008 | None | 2020 |
Document Title
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Source and delivery of nutrients to receiving waters in the northeastern and mid-Atlantic regions of the United States | Estimating linkages between redfish and cold water coral on the Norwegian coast | Effects of the Conservation Reserve Program on northern bobwhite and grassland birds | i-Tree Species Selector User's Manual v. 4.0 | Using the Lonsdorf and ESTIMAP models for large-scale pollination Using the Lonsdorf and ESTIMAP models for large-scale pollination mapping (Case study: Iran) |
Document Status
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Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Webpage | Published journal manuscript |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Not applicable | Not applicable | Not applicable | https://species.itreetools.org/ | Not applicable | |
Contact Name
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Richard Moore | Naomi S. Foley | Sam Riffell |
Not reported ?Comment:send comments through any of the means listed on the i-Tree support page: http://www.itreetools.org/support/. |
Ehsan Rahini |
Contact Address
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U.S. Environmental Protection Agency, 27 Tarzwell Drive, Narragansett, Rhode Island 02882 | Dept. of Economics and Management, Univeristy of Tromso, Norway | Department of Wildlife & Fisheries, Mississippi State University, Mississippi State, MS 39762, USA | Not reported | Environmental Sciences Research Institute, Shahid Beheshti University, Tehran, Iran |
Contact Email
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rmoore@usgs.gov | naomifoley@gmail.com | sriffell@cfr.msstate.edu | info@itreetools.org | ehsanrahimi666@gmail.com |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Summary Description
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AUTHOR'S DESCRIPTION: "SPAtially Referenced Regressions On Watershed attributes (SPARROW) nutrient models were developed for the Northeastern and Mid-Atlantic (NE US) regions of the United States to represent source conditions for the year 2002. The model developed to examine the source and delivery of nitrogen to the estuaries of nine large rivers along the NE US Seaboard indicated that agricultural sources contribute the largest percentage (37%) of the total nitrogen load delivered to the estuaries" | ABSTRACT: "…This paper applies the production function approach to estimate the link between cold water corals and redfish in Norway. Both the carrying capacity and growth rate of redfish are found to be functions of cold water coral habitat and thus cold water corals can be considered an essential fish habitat…The essential habitat model shows the best fit to the data…" AUTHOR'S DESCRIPTION: "…the EFH model presented by Barbier and Strand (1998), in which the habitat is considered essential to the stock; i.e., if the habitat declines to zero the fish stock will perish…based on the Gordon-Schaefer model, which is a single-species biomass model, where effort is the control variable and fish stock is the state variable. In the case of habitat-fisheries interactions, such as in our case, a second state variable is introduced, the habitat (CWC)…Scientists have stimated that 30-50% of CWC habitat has been damaged (Fossa, Mortensen, and Furevik 2002. Working within these bounds, we empirically estimate the relationship between CWC as a habitat and a fish stock..." | 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, comprehensive 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." | ABSTRACT: "The Species Selector is a free-standing i-Tree utility that ranks tree species based on their environmental benefits at maturity. As such, it complements existing tree selection programs that rank species based on esthetics or other features. Species are selected based on three types of information. First, hardiness is considered. The hardiness zone is determined based on state and city, and all species that are not sufficiently hardy are eliminated from consideration. Second, mature height is considered. Users are asked to specify minimum and maximum heights, and species outside of that range are eliminated. Finally, eight environmental factors are considered in the rankings created by the Species Selector: • Air pollution removal • Air temperature reduction • Ultraviolet radiation reduction • Carbon storage • Pollen allergenicity • Building energy conservation • Wind reduction • Stream flow reduction (stormwater management). Users are asked to rank the importance of each of these factors on a scale of 0 to 10. The combination of hardiness, mature height, and desired functionality produces a ranked list of appropriate species from an initial database of about 1,600 species. The large species database covers a broad range of native, naturalized and exotic trees, some of which are commonly planted in urban areas. Since only city hardiness zone, tree height and user functional preferences are used to produce the list, there may well be many species on the list that are unsuitable to the local context for a variety of reasons. A species may have particular structural, drainage, sun, pest, or soil pH limitations that should exclude it from use. Furthermore, since many native and exotic species are included, items may appear that are simply not available in the local trade. For these reasons, the list should be considered a beginning rather than an end. The list will need to be whittled down to meet local needs and limitations. Relevant cultural needs should be taken into account as well. The result will be a list of recommended species suited for local use that maximizes environmental services." | Abstract: ". ..we used the ESTIMAP model to improve the results of the Lonsdorf model. For this, we included the effects of roads, railways, rivers, wetlands, lakes, altitude, climate, and ecosystem boundaries in the ESTIMAP modeling and compared the results with the Lonsdorf model. The results of the Lonsdorf model showed that the majority of Iran had a very low potential for providing pollination service and only three percent of the northern and western parts of Iran had high potential. However, the results of the ESTIMAP model showed that 16% of Iran had a high potential to provide pollination that covers most of the northern and southern parts of the country. The results of the ESTIMAP model for pollination mapping in Iran showed the Lonsdorf model of estimating pollination service can be improved through considering other relevant factors." |
Specific Policy or Decision Context Cited
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water-quality assessment, total maximum daily load(TMDL) determination | None identified | None reported | None identified | None reported |
Biophysical Context
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Norteneastern region (U.S.); Mid-Atlantic region (U.S.) | Continental slope | Conservation Reserve Program lands left to go fallow | No additional description provided | None additional |
EM Scenario Drivers
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No scenarios presented | Estimated impact differences due to fishing effort; minimum (30%), and maximum (50%) degredation (reduction) in coral reef area. | N/A | No scenarios presented | N/A |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application | Method + Application | Method Only | Method + Application |
New or Pre-existing EM?
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Application of existing model | Application of existing model | New or revised model | New or revised model | Application of existing model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Document ID for related EM
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None | Doc-227 | Doc-405 | Doc-427 | Doc-432 |
EM ID for related EM
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None | EM-106 | EM-831 | EM-838 | EM-839 | EM-840 | EM-841 | EM-842 | EM-843 | EM-844 | EM-846 | EM-847 | None | EM-939 |
EM Modeling Approach
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Temporal Extent
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2002 ?Comment:Several nationwide database development and modeling efforts were necessary to create models consistent with 2002 conditions. |
1986-2002 | 2008 | Not applicable | 2020 |
EM Time Dependence
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time-stationary | time-stationary | time-stationary | Not applicable | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Time Continuity
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Bounding Type
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Geopolitical | Physiographic or ecological | Physiographic or ecological | Not applicable | Geopolitical |
Spatial Extent Name
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NE U.S. Regions | Norwegian Sea (ICES areas I and II) | Piedmont Ecoregion | Not applicable | Iran |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 1000-10,000 km^2. | 100,000-1,000,000 km^2 | Not applicable | >1,000,000 km^2 |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially lumped (in all cases) | Not applicable |
spatially distributed (in at least some cases) ?Comment:Varies by inputs, but results are for areas of country |
Spatial Grain Type
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area, for pixel or radial feature | Not applicable | Not applicable | Not applicable | area, for pixel or radial feature |
Spatial Grain Size
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30 x 30 m | Not applicable | Not applicable | Not applicable | ha^2 |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Computational Approach
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Analytic | Analytic | Analytic | Analytic | Numeric |
EM Determinism
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deterministic | deterministic | deterministic | deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Model Calibration Reported?
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Yes | Yes | Yes | Not applicable | No |
Model Goodness of Fit Reported?
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Yes ?Comment:R-squared of .97 refers to the modelled loading whereas .83 refers to yield (see table 1, pg 972 for more information) |
Yes | No | 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 | No | No | Not applicable | No |
Model Uncertainty Analysis Reported?
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Unclear | No | No | Not applicable | No |
Model Sensitivity Analysis Reported?
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Yes | Yes | Yes | Not applicable | No |
Model Sensitivity Analysis Include Interactions?
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Unclear | Yes | Unclear | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
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None |
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Comment:Model for Iran - no form preset id for country |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
None |
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None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
Centroid Latitude
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42 | 70 | 36.23 | Not applicable | 32.29 |
Centroid Longitude
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-73 | 10 | -81.9 | Not applicable | 53.68 |
Centroid Datum
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WGS84 | WGS84 | WGS84 | Not applicable | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated | Estimated | Not applicable | Estimated |
EM ID
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EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Environmental Sub-Class
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Rivers and Streams | Ground Water | Terrestrial Environment (sub-classes not fully specified) | Agroecosystems | Atmosphere | Near Coastal Marine and Estuarine | Open Ocean and Seas | Grasslands | Created Greenspace | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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none | cold water coral reefs | grasslands | Urban greenspace | terrestrial land types |
EM Ecological Scale
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Ecological scale is coarser than that of the Environmental Sub-class | Ecological scale is finer than that of the Environmental Sub-class | Ecological scale corresponds to the Environmental Sub-class | Ecological scale corresponds to 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-104 | EM-319 | EM-845 | EM-936 | EM-941 |
EM Organismal Scale
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Not applicable | Guild or Assemblage | Species | Species | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-104 | EM-319 | EM-845 | EM-936 | EM-941 |
None Available |
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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-104 | EM-319 | EM-845 | EM-936 | EM-941 |
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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-104 | EM-319 | EM-845 | EM-936 | EM-941 |
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None |
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