EcoService Models Library (ESML)
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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.
Compare Criteria:
Show Criteria
Hide CriteriaEM Identity and Description
EM Identification
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EM ID
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EM-697 
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Short Name
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Floral resources on landfill sites, United Kingdom | Pollinators on landfill sites, United Kingdom | Wild bees over 26 yrs of restored prairie, IL, USA | Recreational fishery index, USA | NC HUC-12 conservation prioritization tool |
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EM Full Name
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Floral resources on landfill sites, East Midlands, United Kingdom | Pollinating insects on landfill sites, East Midlands, United Kingdon | Wild bee community change over a 26 year chronosequence of restored tallgrass prairie, IL, USA | Recreational fishery index for streams and rivers, USA | NC HUC-12 conservation prioritization tool v. 1.0, North Carolina, USA |
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EM Source or Collection
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None | None | None | US EPA | None |
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EM Source Document ID
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389 | 389 | 401 | 414 |
443 ?Comment:Doc 444 is an additional source for this EM |
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Document Author
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Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | Tarrant S., J. Ollerton, M. L Rahman, J. Tarrant, and D. McCollin | Griffin, S. R, B. Bruninga-Socolar, M. A. Kerr, J. Gibbs and R. Winfree | Lomnicky. G.A., Hughes, R.M., Peck, D.V., and P.L. Ringold | Warnell, K., I. Golden, and C. Canfield |
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Document Year
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2013 | 2013 | 2017 | 2021 | 2023 |
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Document Title
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Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | Grassland restoration on landfill sites in the East Midlands, United Kingdom: An evaluation of floral resources and pollinating insects | Wild bee community change over a 26-year chronosequence of restored tallgrass prairie | Correspondence between a recreational fishery index and ecological condition for U.S.A. streams and rivers. | Conservation planning tools for NC's people & nature |
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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 |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Published journal manuscript | Published journal manuscript | Webpage |
Software and Access
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
| Not applicable | Not applicable | Not applicable | Not applicable | https://prioritizationcobenefitstool.users.earthengine.app/view/nc-huc-12-conservation-prioritizer | |
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Contact Name
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Sam Tarrant | Sam Tarrant | Sean R. Griffin | Gregg Lomnicky | Katie Warnell |
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Contact Address
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RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | RSPB UK Headquarters, The Lodge, Sandy, Bedfordshire SG19 2DL, U.K. | Department of Ecology, Evolution, and Natural Resources, Rutgers University, New Brunswick, NJ 08901, U.S.A. | 200 SW 35th St., Corvallis, OR, 97333 | Not reported |
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Contact Email
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sam.tarrant@rspb.org.uk | sam.tarrant@rspb.org.uk | srgriffin108@gmail.com | lomnicky.gregg@epa.gov | katie.warnell@duke.edu |
EM Description
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EM ID
em.detail.idHelp
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Summary Description
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ABSTRACT: "...Restored landfill sites are a significant potential reserve of semi-natural habitat, so their conservation value for supporting populations of pollinating insects was here examined by assessing whether the plant and pollinator assemblages of restored landfill sites are comparable to reference sites of existing wildlife value. Floral characteristics of the vegetation and the species richness and abundance of flower-visiting insect assemblages were compared between nine pairs of restored landfill sites and reference sites in the East Midlands of the United Kingdom, using standardized methods over two field seasons. …" AUTHOR'S DESCRIPTION: "The selection criteria for the landfill sites were greater than or equal to 50% of the site restored (to avoid undue influence from ongoing landfilling operations), greater than or equal to 0.5 ha in area and restored for greater than or equal to 4 years to allow establishment of vegetation. Comparison reference sites were the closest grassland sites of recognized nature conservation value, being designated as either Local Nature Reserves (LNRs) or Sites of Special Scientific Interest (SSSI)…All sites were surveyed three times each during the fieldwork season, in Spring, Summer, and Autumn. Paired sites were sampled on consecutive days whenever weather conditions permitted to reduce temporal bias. Standardized plant surveys were used (Dicks et al. 2002; Potts et al. 2006). Transects (100 × 2m) were centered from the approximate middle of the site and orientated using randomized bearing tables. All flowering plants were identified to species level… A “floral cover” method to represent available floral resources was used which combines floral abundance with inflorescence size. Mean area of the floral unit from above was measured for each flowering plant species and then multiplied by their frequencies." "Insect pollinated flowering plant species composition and floral abundance between sites by type were represented by non-metric multidimensional scaling (NMDS)...This method is sensitive to showing outliers and the distance between points shows the relative similarity (McCune & Grace 2002; Ollerton et al. 2009)." (This data is not entered into ESML) | ABSTRACT: "...Restored landfill sites are a significant potential reserve of semi-natural habitat, so their conservation value for supporting populations of pollinating insects was here examined by assessing whether the plant and pollinator assemblages of restored landfill sites are comparable to reference sites of existing wildlife value. Floral characteristics of the vegetation and the species richness and abundance of flower-visiting insect assemblages were compared between nine pairs of restored landfill sites and reference sites in the East Midlands of the United Kingdom, using standardized methods over two field seasons. …" AUTHOR'S DESCRIPTION: "The selection criteria for the landfill sites were greater than or equal to 50% of the site restored (to avoid undue influence from ongoing landfilling operations), greater than or equal to 0.5 ha in area and restored for greater than or equal to 4 years to allow establishment of vegetation. Comparison reference sites were the closest grassland sites of recognized nature conservation value, being designated as either Local Nature Reserves (LNRs) or Sites of Special Scientific Interest (SSSI)…All sites were surveyed three times each during the fieldwork season, in Spring, Summer, and Autumn. Paired sites were sampled on consecutive days whenever weather conditions permitted to reduce temporal bias. Standardized plant surveys were used (Dicks et al. 2002; Potts et al. 2006). Transects (100 × 2m) were centered from the approximate middle of the site and orientated using randomized bearing tables. All flowering plants were identified to species level…In the first year of study, plants in flower and flower visitors were surveyed using the same transects as for the floral resources surveys. The transect was left undisturbed for 20 minutes following the initial plant survey to allow the flower visitors to return. Each transect was surveyed at a rate of approximately 3m/minute for 30 minutes. All insects observed to touch the sexual parts of flowers were either captured using a butterfly net and transferred into individually labeled specimen jars, or directly captured into the jars. After the survey was completed, those insects that could be identified in the field were recorded and released. The flower-visitor surveys were conducted in the morning, within 1 hour of midday, and in the afternoon to sample those insects active at different times. Insects that could not be identified in the field were collected as voucher specimens for later identification. Identifications were verified using reference collections and by taxon specialists. Relatively low capture rates in the first year led to methods being altered in the second year when surveying followed a spiral pattern from a randomly determined point on the sites, at a standard pace of 10 m/minute for 30 minutes, following Nielsen and Bascompte (2007) and Kalikhman (2007). Given a 2-m wide transect, an area of approximately 600m2 was sampled in each | ABSTRACT: "Restoration efforts often focus on plants, but additionally require the establishment and long-term persistence of diverse groups of nontarget organisms, such as bees, for important ecosystem functions and meeting restoration goals. We investigated long-term patterns in the response of bees to habitat restoration by sampling bee communities along a 26-year chronosequence of restored tallgrass prairie in north-central Illinois, U.S.A. Specifically, we examined how bee communities changed over time since restoration in terms of (1) abundance and richness, (2) community composition, and (3) the two components of beta diversity, one-to-one species replacement, and changes in species richness. Bee abundance and raw richness increased with restoration age from the low level of the pre-restoration (agricultural) sites to the target level of the remnant prairie within the first 2–3 years after restoration, and these high levels were maintained throughout the entire restoration chronosequence. Bee community composition of the youngest restored sites differed from that of prairie remnants, but 5–7 years post-restoration the community composition of restored prairie converged with that of remnants. Landscape context, particularly nearby wooded land, was found to affect abundance, rarefied richness, and community composition. Partitioning overall beta diversity between sites into species replacement and richness effects revealed that the main driver of community change over time was the gradual accumulation of species, rather than one-to-one species replacement. At the spatial and temporal scales we studied, we conclude that prairie restoration efforts targeting plants also successfully restore bee communities." | ABSTRACT: [Sport fishing is an important recreational and economic activity, especially in Australia, Europe and North America, and the condition of sport fish populations is a key ecological indicator of water body condition for millions of anglers and the public. Despite its importance as an ecological indicator representing the status of sport fish populations, an index for measuring this ecosystem service has not been quantified by analyzing actual fish taxa, size and abundance data across the U.S.A. Therefore, we used game fish data collected from 1,561 stream and river sites located throughout the conterminous U.S.A. combined with specific fish species and size dollar weights to calculate site-specific recreational fishery index (RFI) scores. We then regressed those scores against 38 potential site-specific environmental predictor variables, as well as site-specific fish assemblage condition (multimetric index; MMI) scores based on entire fish assemblages, to determine the factors most associated with the RFI scores. We found weak correlations between RFI and MMI scores and weak to moderate correlations with environmental variables, which varied in importance with each of 9 ecoregions. We conclude that the RFI is a useful indicator of a stream ecosystem service, which should be of greater interest to the U.S.A. public and traditional fishery management agencies than are MMIs, which tend to be more useful for ecologists, environmentalists and environmental quality agencies.] | ABSTRACT: "Conservation organizations and land trusts in North Carolina are increasingly focused on how their work can contribute to both human and ecosystem resilience and adaptation to climate change, as well as directly mitigate climate change through carbon storage and sequestration. Recent state executive and legislative actions also underscore the importance of natural systems for climate adaptation and mitigation, and may provide additional funding for conservation and restoration for those purposes in the near term. To make it more efficient for conservation organizations working in North Carolina to consider a broad suite of conservation benefits in their work, the Conservation Trust for North Carolina and the Nicholas Institute for Energy, Environment & Sustainability at Duke University have developed two online tools for identifying priority areas for conservation action and estimating benefit metrics for specific properties. The conservation prioritization tool finds the sub-watersheds in North Carolina with the greatest potential to provide a set of user-selected conservation benefits. It allows users to identify priority areas for future conservation work within the entire state or a defined region. This high-level tool allows for quick and easy exploration without the need for spatial analysis expertise." |
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Specific Policy or Decision Context Cited
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None identified | None identified | None identified | None identified | Allows users to prioritize HUCs within their area of interest based on their conservation goals. |
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Biophysical Context
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No additional description provided | No additional description provided | The Nachusa Grasslands consists of over 1,900 ha of restored prairie plantings, prairie remnants, and other habitats such as wetlands and oak savanna. The area is generally mesic with an average annual precipitation of 975 mm, and most precipitation occurs during the growing season. | None | No additional description provided |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented | No scenarios presented | N/A | No scenarios presented |
EM Relationship to Other EMs or Applications
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application (multiple runs exist) View EM Runs | Method + Application | Method Only |
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New or Pre-existing EM?
em.detail.newOrExistHelp
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New or revised model | New or revised model | New or revised model | New or revised model | New or revised model |
Related EMs (for example, other versions or derivations of this EM) described in ESML
em.detail.relatedEmHelp
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Document ID for related EM
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None | Doc-389 | None | None |
Doc-444 ?Comment:The secondary source, document 444, is the website for running the tool. |
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EM ID for related EM
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EM-709 | EM-697 | None | None | None |
EM Modeling Approach
EM Relationship to Time
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Temporal Extent
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2007-2008 | 2007-2008 | 1988-2014 | 2013-2014 | Not applicable |
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EM Time Dependence
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time-stationary | time-stationary | time-stationary | time-dependent | time-stationary |
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EM Time Reference (Future/Past)
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Not applicable | Not applicable | Not applicable | past time | Not applicable |
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EM Time Continuity
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Not applicable | Not applicable | Not applicable | discrete | Not applicable |
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EM Temporal Grain Size Value
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Not applicable | Not applicable | Not applicable | 1 | Not applicable |
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EM Temporal Grain Size Unit
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Not applicable | Not applicable | Not applicable | Year | Not applicable |
EM Spatial Extent
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Bounding Type
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Multiple unrelated locations (e.g., meta-analysis) | Multiple unrelated locations (e.g., meta-analysis) | Physiographic or ecological | Geopolitical | Not applicable |
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Spatial Extent Name
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East Midlands | East Midlands | Nachusa Grasslands | United States | Not applicable |
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Spatial Extent Area (Magnitude)
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1000-10,000 km^2. | 1000-10,000 km^2. | 10-100 km^2 | >1,000,000 km^2 | Not applicable |
Spatial Distribution of Computations
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
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Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) | other (specify), for irregular (e.g., stream reach, lake basin) | other (specify), for irregular (e.g., stream reach, lake basin) | length, for linear feature (e.g., stream mile) | map scale, for cartographic feature |
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Spatial Grain Size
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multiple unrelated locations | multiple unrelated locations | Area varies by site | stream reach (site) | HUC 12 |
EM Structure and Computation Approach
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Computational Approach
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Analytic | Analytic | Analytic | Analytic | Other or unclear (comment) |
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EM Determinism
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deterministic | deterministic | deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Model Calibration Reported?
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Not applicable | Not applicable | No | No | Not applicable |
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Model Goodness of Fit Reported?
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Not applicable | Not applicable | No | No | Not applicable |
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Goodness of Fit (metric| value | unit)
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None | None | None | None | None |
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Model Operational Validation Reported?
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Not applicable | Not applicable | No | No | Not applicable |
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Model Uncertainty Analysis Reported?
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Not applicable | Not applicable | No | No | Not applicable |
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Model Sensitivity Analysis Reported?
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Not applicable | Not applicable | No | No | Not applicable |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
| None | None | None | None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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Centroid Latitude
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52.22 | 52.22 | 41.89 | 36.21 | Not applicable |
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Centroid Longitude
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-0.91 | -0.91 | -89.34 | -113.76 | Not applicable |
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Centroid Datum
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WGS84 | WGS84 | WGS84 | WGS84 | Not applicable |
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Centroid Coordinates Status
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Estimated | Estimated | Provided | Estimated | Not applicable |
Environments and Scales Modeled
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Environmental Sub-Class
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Created Greenspace | Grasslands | Created Greenspace | Grasslands | Agroecosystems | Grasslands | Rivers and Streams | Aquatic Environment (sub-classes not fully specified) | Terrestrial Environment (sub-classes not fully specified) |
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Specific Environment Type
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restored landfills and grasslands | restored landfills and grasslands | Restored prairie, prairie remnants, and cropland | reach | Terrestrial and freshwater aquatic |
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EM Ecological Scale
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Ecological scale corresponds to 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 | Ecological scale is coarser than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
em.detail.nameOfOrgsOrGroupsHelp
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EM ID
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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EM Organismal Scale
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Individual or population, within a species | Individual or population, within a species | Species | Guild or Assemblage | Not applicable |
Taxonomic level and name of organisms or groups identified
taxonomyHelp
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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None Available | None Available |
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.detail.cicesHelp
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
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None |
<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>
fegs1Help
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
fegs2Help
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EM-697
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EM-709
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EM-788
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EM-862 | EM-959 |
| None | None | None |
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None |