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-367 | EM-416 | EM-1011 |
EM Short Name
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InVEST Coastal Blue Carbon | Sed. denitrification, St. Louis River, MN/WI, USA | WMOST method |
EM Full Name
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InVEST v3.0 Coastal Blue Carbon | Sediment denitrification, St. Louis River estuary, Lake Superior, MN & WI, USA | Watershed Management Optimization Support Tool (WMOST) v1 method |
EM Source or Collection
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InVEST | US EPA | US EPA |
EM Source Document ID
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310 | 333 | 477 |
Document Author
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Natural Capital Project | Brent J. Bellinger, Terri M. Jicha, LaRae P. Lehto, Lindsey R. Seifert-Monson, David W. Bolgrien, Matthew A. Starry, Theodore R. Angradi, Mark S. Pearson, Colleen Elonen, and Brian H. Hill | United States EPA |
Document Year
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2014 | 2014 | 2013 |
Document Title
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Blue Carbon model - InVEST (v3.0) | Sediment nitrification and denitrification in a Lake Superior estuary | Watershed Management Optimization Support Tool (WMOST) v1 User manual |
Document Status
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Documented, not peer reviewed | Peer reviewed and published | Peer reviewed and published |
Comments on Status
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other | Published journal manuscript | Published EPA report |
EM ID
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EM-367 | EM-416 | EM-1011 |
http://ncp-dev.stanford.edu/~dataportal/invest-releases/documentation/current_release/blue_carbon.html#running-the-model | Not applicable | https://cfpub.epa.gov/si/si_public_record_report.cfm?Lab=NHEERL&dirEntryId=262280 | |
Contact Name
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Gregg Verutes | Brent J. Bellinger | Naomi Detenbeck |
Contact Address
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Stanford University | U.S. Environmental Protection Agency, Office of Research and Development, National Health and Environmental Effects Research Laboratory, Mid-Continent Ecology Division, 6201 Congdon Blvd., Duluth, MN 55804, USA | NHEERL, Atlantic Ecology Division Narragansett, RI 02882 |
Contact Email
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gverutes@stanford.edu | bellinger.brent@epa.ogv | detenbeck.naomi@epa.gov |
EM ID
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EM-367 | EM-416 | EM-1011 |
Summary Description
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Please note: This ESML entry describes an InVEST model version that was current as of 2014. More recent versions may be available at the InVEST website. "InVEST Coastal Blue Carbon models the carbon cycle through a bookkeeping-type approach (Houghton, 2003). This approach simplifies the carbon cycle by accounting for storage in four main pools (aboveground biomass, belowground biomass, standing dead carbon and sediment carbon… Accumulation of carbon in coastal habitats occurs primarily in sediments (Pendleton et al., 2012). The model requires users to provide maps of coastal ecosystems that store carbon, such as mangroves and seagrasses. Users must also provide data on the amount of carbon stored in the four carbon pools and the rate of annual carbon accumulation in the sediments. If local information is not available, users can draw on the global database of values for carbon stocks and accumulation rates sourced from the peer-reviewed literature that is included in the model. If data from field studies or other local sources are available, these values should be used instead of those in the global database. The model requires land cover maps, which represent changes in human use patterns in coastal areas or changes to sea level, to estimate the amount of carbon lost or gained over a specified period of time. The model quantifies carbon storage across the land or seascape by summing the carbon stored in these four carbon pools. |
ABSTRACT: "Inorganic nitrogen (N) transformations and removal in aquatic sediments are microbially mediated, and rates influence N-transport. In this study we related physicochemical properties of a large Great Lakes embayment, the St. Louis River Estuary (SLRE) of western Lake Superior, to sediment N-transformation rates. We tested for associations among rates and N-inputs, vegetation biomass, and temperature.We measured rates of nitrification (NIT), unamended base denitrification (DeNIT), and potential denitrification [denitrifying enzyme activity (DEA)] in 2011 and 2012 across spatial and depth zones. In vegetated habitats, NIT and DeNIT rateswere highest in deep (ca. 2 m) water (249 and 2111 mg N m−2 d−1, respectively) and in the upper and lower reaches of the SLRE (N126 and 274 mg N m−2 d−1, respectively). Rates of DEA were similar among zones. In 2012, NIT, DeNIT, and DEA rateswere highest in July, May, and June, respectively. System-wide, we observed highest NIT (223 and 287 mgNm−2 d−1) and DeNIT (77 and 64 mgNm−2 d−1) rates in the harbor and from deep water, respectively. Amendment with NO3 − enhanced DeNIT rates more than carbon amendment; however, DeNIT and NIT rates were inversely related, suggesting the two processes are decoupled in sediments. Average proportion of N2O released during DEA (23–54%) was greater than from DeNIT (0–41%). Nitrogen cycling rates were spatially and temporally variable, but we modeled how alterations to water depth and N-inputs may impact DeNIT rates. A large flood occurred in 2012 which temporarily altered water chemistry and sediment nitrogen cycling." ?Comment:BH: I pasted the entire abstract because there is not specific mention of the combined sediment nitrification model. |
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 user guide and presentation of two case studies as examples of how to apply WMOST. Theoretical documentation is provided in a separate report (EPA/600/R-13/151). " |
Specific Policy or Decision Context Cited
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None identified | None identified | Not applicable |
Biophysical Context
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Land use land class; habitat type | Estuarine system | None |
EM Scenario Drivers
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Land use land cover changes; habitat disturbance | No scenarios presented | None |
EM ID
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EM-367 | EM-416 | EM-1011 |
Method Only, Application of Method or Model Run
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Method Only | Method + Application | Method Only |
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
EM ID
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EM-367 | EM-416 | EM-1011 |
Document ID for related EM
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None | None | None |
EM ID for related EM
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None | None | None |
EM Modeling Approach
EM ID
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EM-367 | EM-416 | EM-1011 |
EM Temporal Extent
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Not applicable | 2011 - 2012 | Not applicable |
EM Time Dependence
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time-dependent | time-stationary | time-dependent |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
Not applicable ?Comment:method description |
EM Time Continuity
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discrete | Not applicable | discrete |
EM Temporal Grain Size Value
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1 | Not applicable | 1 |
EM Temporal Grain Size Unit
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Year | Not applicable | Month |
EM ID
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EM-367 | EM-416 | EM-1011 |
Bounding Type
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Not applicable | Watershed/Catchment/HUC | Not applicable |
Spatial Extent Name
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Not applicable | St. Louis River estuary | Not applicable |
Spatial Extent Area (Magnitude)
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Not applicable | 10-100 km^2 | Not applicable |
EM ID
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EM-367 | EM-416 | EM-1011 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially lumped (in all cases) | spatially lumped (in all cases) |
Spatial Grain Type
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volume, for 3-D feature | Not applicable | Not applicable |
Spatial Grain Size
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user-specified | Not applicable | Not applicable |
EM ID
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EM-367 | EM-416 | EM-1011 |
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-367 | EM-416 | EM-1011 |
Model Calibration Reported?
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Not applicable | No | Not applicable |
Model Goodness of Fit Reported?
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Not applicable | No | Not applicable |
Goodness of Fit (metric| value | unit)
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None | None | None |
Model Operational Validation Reported?
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Not applicable | No | Not applicable |
Model Uncertainty Analysis Reported?
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Not applicable | No | Not applicable |
Model Sensitivity Analysis Reported?
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Not applicable | No | Not applicable |
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-367 | EM-416 | EM-1011 |
None |
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None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-367 | EM-416 | EM-1011 |
None | None | None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-367 | EM-416 | EM-1011 |
Centroid Latitude
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-9999 | 46.75 | Not applicable |
Centroid Longitude
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-9999 | -92.08 | Not applicable |
Centroid Datum
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Not applicable | WGS84 | Not applicable |
Centroid Coordinates Status
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Not applicable | Estimated | Not applicable |
EM ID
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EM-367 | EM-416 | EM-1011 |
EM Environmental Sub-Class
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Inland Wetlands | Near Coastal Marine and Estuarine | Rivers and Streams | Inland Wetlands | Lakes and Ponds | Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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user specified | Freshwater estuary | watershed |
EM Ecological Scale
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Ecological scale is finer than that of 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-367 | EM-416 | EM-1011 |
EM Organismal Scale
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Not applicable | Not applicable | Not applicable |
Taxonomic level and name of organisms or groups identified
EM-367 | EM-416 | EM-1011 |
None Available | 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-367 | EM-416 | EM-1011 |
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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-367 | EM-416 | EM-1011 |
None | None | None |