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-24 | EM-1018 |
EM Short Name
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i-Tree Eco: Carbon storage & sequestration, USA | WMOSTsustainable water Danvers-Middleton, MA |
EM Full Name
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i-Tree Eco carbon storage and sequestration (trees), USA | WMOST sustainable water management initiative Danvers-Middleton, MA |
EM Source or Collection
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i-Tree | USDA Forest Service | US EPA |
EM Source Document ID
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195 | 477 |
Document Author
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Nowak, D. J., Greenfield, E. J., Hoehn, R. E. and Lapoint, E. | United States EPA |
Document Year
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2013 | 2013 |
Document Title
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Carbon storage and sequestration by trees in urban and community areas of the United States | Watershed Management Optimization Support Tool (WMOST) v1 User manual |
Document Status
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Peer reviewed and published | Peer reviewed and published |
Comments on Status
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Published journal manuscript | Published EPA report |
EM ID
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EM-24 | EM-1018 |
Not applicable | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | |
Contact Name
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David J. Nowak | Naomi Detenbeck |
Contact Address
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USDA Forest Service, Northern Research Station, Syracuse, NY 13210, USA | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 |
Contact Email
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dnowak@fs.fed.us | detenbeck.naomi@epa.gov |
EM ID
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EM-24 | EM-1018 |
Summary Description
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ABSTRACT: "Carbon storage and sequestration by urban trees in the United States was quantified to assess the magnitude and role of urban forests in relation to climate change. Urban tree field data from 28 cities and 6 states were used to determine the average carbon density per unit of tree cover. These data were applied to statewide urban tree cover measurements to determine total urban forest carbon storage and annual sequestration by state and nationally. Urban whole tree carbon storage densities average 7.69 kg C m^2 of tree cover and sequestration densities average 0.28 kg C m^2 of tree cover per year. Total tree carbon storage in U.S. urban areas (c. 2005) is estimated at 643 million tonnes ($50.5 billion value; 95% CI = 597 million and 690 million tonnes) and annual sequestration is estimated at 25.6 million tonnes ($2.0 billion value; 95% CI = 23.7 million to 27.4 million tonnes)." | ABSTRACT: "The Watershed Management Optimization Support Tool (WMOST) is intended to be used as a screening tool as part of an integrated watershed management process such as that described in EPA’s watershed planning handbook (EPA 2008).1 The objective of WMOST is to serve as a public-domain, efficient, and user-friendly tool for local water resources managers and planners to screen a widerange of potential water resources management options across their watershed or jurisdiction for costeffectiveness as well as environmental and economic sustainability (Zoltay et al 2010). Examples of options that could be evaluated with the tool include projects related to stormwater, water supply, wastewater and water-related resources such as Low-Impact Development (LID) and land conservation. The tool is intended to aid in evaluating the environmental and economic costs, benefits, trade-offs and co-benefits of various management options. In addition, the tool is intended to facilitate the evaluation of low impact development (LID) and green infrastructure as alternative or complementary management options in projects proposed for State Revolving Funds (SRF). WMOST is a screening model that is spatially lumped with a daily or monthly time step. The model considers water flows but does not yet consider water quality. The optimization of management options is solved using linear programming. The target user group for WMOST consists of local water resources managers, including municipal water works superintendents and their consultants. This document includes a presentation of a case study appling WMOST to the Danvers-Middleton, MA sustainable water management initiative. |
Specific Policy or Decision Context Cited
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Not reported | Not applicable |
Biophysical Context
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Urban areas 3.0% of land in U.S. and Urban/community land (5.3%) in 2000. | None |
EM Scenario Drivers
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No scenarios presented |
None ?Comment:Not presented with scenarios, but the model was run with multiple scenarios for costs related to varying instream minimum flows and provided the associated costs for each run. |
EM ID
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EM-24 | EM-1018 |
Method Only, Application of Method or Model Run
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Method + Application | Method + Application |
New or Pre-existing EM?
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Application of existing 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-24 | EM-1018 |
Document ID for related EM
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None | Doc-477 |
EM ID for related EM
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None | None |
EM Modeling Approach
EM ID
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EM-24 | EM-1018 |
EM Temporal Extent
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1989-2010 | Not applicable |
EM Time Dependence
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time-dependent | time-dependent |
EM Time Reference (Future/Past)
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future time |
Not applicable ?Comment:method description |
EM Time Continuity
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discrete | discrete |
EM Temporal Grain Size Value
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1 | 1 |
EM Temporal Grain Size Unit
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Year | Day |
EM ID
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EM-24 | EM-1018 |
Bounding Type
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Geopolitical | Watershed/Catchment/HUC |
Spatial Extent Name
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United States | Danvers-Middleton |
Spatial Extent Area (Magnitude)
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>1,000,000 km^2 | 10-100 km^2 |
EM ID
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EM-24 | EM-1018 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) |
Spatial Grain Type
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area, for pixel or radial feature | Not applicable |
Spatial Grain Size
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1 m^2 | Not applicable |
EM ID
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EM-24 | EM-1018 |
EM Computational Approach
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Numeric | Numeric |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-24 | EM-1018 |
Model Calibration Reported?
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No | Unclear |
Model Goodness of Fit Reported?
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No | Unclear |
Goodness of Fit (metric| value | unit)
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None | None |
Model Operational Validation Reported?
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No | Not applicable |
Model Uncertainty Analysis Reported?
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Yes ?Comment:An error of sampling was reported, but not an error of estimation Estimation error was unknown and reported as likely larger than the error of sampling. |
Not applicable |
Model Sensitivity Analysis Reported?
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No | Not applicable |
Model Sensitivity Analysis Include Interactions?
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Not applicable | Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
EM-24 | EM-1018 |
Comment:EM presents carbon storage and sequestration rates for country and by individual state |
None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-24 | EM-1018 |
None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-24 | EM-1018 |
Centroid Latitude
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40.16 | 42.58 |
Centroid Longitude
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-99.79 | -70.93 |
Centroid Datum
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WGS84 | WGS84 |
Centroid Coordinates Status
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Estimated | Estimated |
EM ID
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EM-24 | EM-1018 |
EM Environmental Sub-Class
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Forests | Created Greenspace | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Urban forests | watershed |
EM Ecological Scale
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Zone within an ecosystem | Ecological scale is finer than that of the Environmental Sub-class |
Scale of differentiation of organisms modeled
EM ID
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EM-24 | EM-1018 |
EM Organismal Scale
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Species ?Comment:Trees were identified to species for the differential growth and biomass estimates part of the analysis. |
Not applicable |
Taxonomic level and name of organisms or groups identified
EM-24 | EM-1018 |
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-24 | EM-1018 |
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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-24 | EM-1018 |
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None |