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
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EM ID
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EM-836 | EM-945 | EM-959 |
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EM Short Name
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Bird abundance on restored landfills, UK | Air pollution removal by green roofs, Chicago, USA | NC HUC-12 conservation prioritization tool |
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EM Full Name
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Bird abundance on restored landfills compared to paired reference sites, East Midlands, UK | Air pollution removal by green roofs, Chigago, 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 |
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EM Source Document ID
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406 |
438 ?Comment:Document 439 is an additional source for this EM. |
443 ?Comment:Doc 444 is an additional source for this EM |
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Document Author
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Rahman, M. L., S. Tarrant, D. McCollin, and J. Ollerton | Yang, J., Q. Yu and P. Gong | Warnell, K., I. Golden, and C. Canfield |
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Document Year
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2011 | 2008 | 2023 |
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Document Title
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The conservation value of restored landfill sites in the East Midlands, UK for supporting bird communities in the East Midlands, UK for supporting bird communities | Quantifying air pollution removal by green roofs in Chicago | 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 |
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Comments on Status
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Published journal manuscript | Published journal manuscript | Webpage |
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EM ID
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EM-836 | EM-945 | EM-959 |
| 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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Lutfor Rahman | Jun Yang | Katie Warnell |
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Contact Address
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Landscape and Biodiversity Research Group, School of Science and Technology, The University of Northampton, Avenue Campus, Northampton NN2 6JD, UK | Department of Landscape Architecture and Horticulture, Temple University, 580 Meetinghouse Road, Ambler, PA 19002, USA. | Not reported |
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Contact Email
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lutfor.rahman@northampton.ac.uk | juny@temple.edu | katie.warnell@duke.edu |
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EM ID
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EM-836 | EM-945 | EM-959 |
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Summary Description
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ABSTRACT: "There has been a rapid decline of grassland bird species in the UK over the last four decades. In order to stem declines in biodiversity such as this, mitigation in the form of newly created habitat and restoration of degraded habitats is advocated in the UK biodiversity action plan. One potential restored habitat that could support a number of bird species is re-created grassland on restored landfill sites. However, this potential largely remains unexplored. In this study, birds were counted using point sampling on nine restored landfill sites in the East Midlands region of the UK during 2007 and 2008. The effects of restoration were investigated by examining bird species composition, richness, and abundance in relation to habitat and landscape structure on the landfill sites in comparison to paired reference sites of existing wildlife value. Twelve bird species were found in total and species richness and abundance on restored landfill sites was found to be higher than that of reference sites. Restored landfill sites support both common grassland bird species and also UK Red List bird species such as skylark Alauda arvensis, grey partridge Perdix perdix, lapwing Vanellus vanellus, tree sparrow, Passer montanus, and starling Sturnus vulgaris. Size of the site, percentage of bare soil and amount of adjacent hedgerow were found to be the most influential habitat quality factors for the distribution of most bird species. Presence of open habitat and crop land in the surrounding landscape were also found to have an effect on bird species composition. Management of restored landfill sites should be targeted towards UK Red List bird species since such sites could potentially play a significant role in biodiversity action planning." AUTHOR'S DESCRIPTION: "Mean number of birds from multiple visits were used for data analysis. To analyse the data generalized linear models (GLMs) were constructed to compare local habitat and landscape parameters affecting different species, and to establish which habitat and landscape characteristics explained significant changes in the frequency of occurrence for each species. To ensure analyses focused on resident species, habitat associations were modelled for those seven bird species which were recorded at least three times in the surveys. The analysis was carried out with the software R (R Development Core Team 2003). Nonsignificant predictors (independent variables) were removed in a stepwise manner (least significant factor first). For distribution pattern of bird species, data were initially analysed using detrended correspondence analysis. Redundancy analysis (RDA) was performed on the same data using CANOCO for Windows version 4.0 (ter Braak and Smilauer 2002)." | ABSTRACT: "The level of air pollution removal by green roofs in Chicago was quantified using a dry deposition model. The result showed that a total of 1675 kg of air pollutants was removed by 19.8 ha of green roofs in one year with O3 accounting for 52% of the total, NO2 (27%), PM10 (14%), and SO2 (7%). The highest level of air pollution removal occurred in May and the lowest in February. The annual removal per hectare of green roof was 85 kg/ha/yr. The amount of pollutants removed would increase to 2046.89 metric tons if all rooftops in Chicago were covered with intensive green roofs. Although costly, the installation of green roofs could be justified in the long run if the environmental benefits were considered. The green roof can be used to supplement the use of urban trees in air pollution control, especially in situations where land and public funds are not readily available." | 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 | 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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The study area covered mainly Northamptonshire and parts of Bedfordshire, Buckinghamshire and Warwickshire, ranging from 51o58’44.74” N to 52o26’42.18” N and 0o27’49.94” W to 1o19’57.67” W. This region has countryside of low, undulating hills separated by valleys and lies entirely within the great belt of scarplands formed by rocks of Jurassic age which stretch across England from Yorkshire to Dorset (Beaver 1943; Sutherland 1995; Wilson 1995). | No additional description provided | No additional description provided |
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EM Scenario Drivers
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No scenarios presented | No scenarios presented | No scenarios presented |
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EM ID
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EM-836 | EM-945 | EM-959 |
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Method Only, Application of Method or Model Run
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Method Only | Method + Application | Method Only |
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New or Pre-existing EM?
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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
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EM ID
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EM-836 | EM-945 | EM-959 |
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Document ID for related EM
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None | Doc-439 |
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-837 | None | None |
EM Modeling Approach
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EM ID
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EM-836 | EM-945 | EM-959 |
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EM Temporal Extent
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Not applicable | July 2006 to July 2007 | Not applicable |
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EM Time Dependence
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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 |
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EM Time Continuity
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Not applicable | discrete | Not applicable |
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EM Temporal Grain Size Value
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Not applicable | 1 | Not applicable |
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EM Temporal Grain Size Unit
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Not applicable | Month | Not applicable |
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EM ID
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EM-836 | EM-945 | EM-959 |
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Bounding Type
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Multiple unrelated locations (e.g., meta-analysis) | Geopolitical | Not applicable |
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Spatial Extent Name
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East Midland | Chicago | Not applicable |
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Spatial Extent Area (Magnitude)
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1000-10,000 km^2. | 100-1000 km^2 | Not applicable |
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EM ID
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EM-836 | EM-945 | 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) |
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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) | map scale, for cartographic feature |
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Spatial Grain Size
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multiple unrelated sites | plot (green roof) size | HUC 12 |
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EM ID
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EM-836 | EM-945 | EM-959 |
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EM Computational Approach
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Analytic | Analytic | Other or unclear (comment) |
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EM Determinism
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deterministic | deterministic | deterministic |
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Statistical Estimation of EM
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EM ID
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EM-836 | EM-945 | EM-959 |
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Model Calibration Reported?
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Not applicable | Unclear | Not applicable |
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Model Goodness of Fit Reported?
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Not applicable | No | Not applicable |
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Goodness of Fit (metric| value | unit)
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None | None | None |
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Model Operational Validation Reported?
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Not applicable | No | Not applicable |
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Model Uncertainty Analysis Reported?
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Not applicable | No | Not applicable |
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Model Sensitivity Analysis Reported?
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Not applicable | No | Not applicable |
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Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-836 | EM-945 | EM-959 |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-836 | EM-945 | EM-959 |
| None | None | None |
Centroid Lat/Long (Decimal Degree)
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EM ID
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EM-836 | EM-945 | EM-959 |
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Centroid Latitude
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52.22 | 41.88 | Not applicable |
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Centroid Longitude
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-0.91 | 87.65 | Not applicable |
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Centroid Datum
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WGS84 | WGS84 | Not applicable |
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Centroid Coordinates Status
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Estimated | Provided | Not applicable |
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EM ID
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EM-836 | EM-945 | EM-959 |
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EM Environmental Sub-Class
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Created Greenspace | Grasslands | Created Greenspace | 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 conserved grasslands | urban green roofs | 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 is coarser than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
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EM ID
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EM-836 | EM-945 | EM-959 |
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EM Organismal Scale
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Individual or population, within a species | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-836 | EM-945 | 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-836 | EM-945 | 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>
(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
| EM-836 | EM-945 | EM-959 |
| None | None | None |
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