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-131 | EM-970 |
EM Short Name
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InVEST marine water quality, Hood Canal, WA, USA | Air quality regulation, Lisbon |
EM Full Name
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InVEST (Integrated Valuation of Envl. Services and Tradeoffs) marine water quality, Hood Canal, WA, USA | Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators |
EM Source or Collection
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InVEST | None |
EM Source Document ID
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205 | 454 |
Document Author
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Toft, J. E., Burke, J. L., Carey, M. P., Kim, C. K., Marsik, M., Sutherland, D. A., Arkema, K. K., Guerry, A. D., Levin, P. S., Minello, T. J., Plummer, M., Ruckelshaus, M. H., and Townsend, H. M. | Matos, P., Vieira, J., Rocha, B., Branquinho, C., & Pinho, P. |
Document Year
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2013 | 2019 |
Document Title
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From mountains to sound: modelling the sensitivity of dungeness crab and Pacific oyster to land–sea interactions in Hood Canal,WA | Modeling the provision of air-quality regulation ecosystem service provided by urban green spaces using lichens as ecological indicators |
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 journal manuscript |
EM ID
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EM-131 | EM-970 |
https://www.naturalcapitalproject.org/invest/ | Not applicable | |
Contact Name
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J.E. Toft | Pedro Pinho |
Contact Address
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Not reported | N/A |
Contact Email
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jetoft@stanford.edu | ppinho@fc.ul.pt |
EM ID
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EM-131 | EM-970 |
Summary Description
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Marine Water Quality Model. Please note: This ESML entry describes a specific, published application of an InVEST model. Different versions (e.g. different tiers) or more recent versions of this model may be available at the InVEST website. AUTHOR'S DESCRIPTION: "We used outputs from the freshwater models as inputs to the marine water quality model.We adapted a box model that has been successfully applied in Puget Sound (Babson et al., 2006; Sutherland et al., 2011) to simulate seasonal and interannual variations in salinity, water temperature, and nitrates in the Canal." (p. 4) | The UN Sustainable Development Goals states that urban air pollution must be tackled to create more inclusive, safe, resilient and sustainable cities. Urban green infrastructures can mitigate air pollution, but a crucial step to use this knowledge into urban management is to quantify how much air-quality regulation can green spaces provide and to understand how the provision of this ecosystem service is affected by other environmental factors. Considering the insufficient number of air quality monitoring stations in cities to monitor the wide range of natural and anthropic sources of pollution with high spatial resolution, ecological indicators of air quality are an alternative cost-effective tool. The aim of this work was to model the supply of air-quality regulation based on urban green spaces characteristics and other environmental factors. For that, we sampled lichen diversity in the centroids of 42 urban green spaces in Lisbon, Portugal. Species richness was the best biodiversity metric responding to air pollution, considering its simplicity and its significative response to the air pollutants concentration data measured in the existent air quality monitoring stations. Using that metric, we then created a model to estimate the supply of air quality regulation provided by green spaces in all green spaces of Lisbon based on the response to the following environmental drivers: the urban green spaces size and its vegetation density. We also used the unexplained variance of this model to map the background air pollution. Overall, we suggest that management should target the smallest urban green spaces by increasing green space size or tree density. The use of ecological indicators, very flexible in space, allow the understanding and the modeling of the provision of air-quality regulation by urban green spaces, and how urban green spaces can be managed to improve air quality and thus improve human well-being and cities resilience. |
Specific Policy or Decision Context Cited
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Land use change | None identified |
Biophysical Context
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No additional description provided | Green spaces in Lisbon, Portugal |
EM Scenario Drivers
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future land use and land cover; Climate change | No scenarios presented |
EM ID
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EM-131 | EM-970 |
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) | Method + Application |
New or Pre-existing EM?
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Application of existing 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-131 | EM-970 |
Document ID for related EM
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None | None |
EM ID for related EM
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None | None |
EM Modeling Approach
EM ID
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EM-131 | EM-970 |
EM Temporal Extent
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varies by run, see runs for values | 2015-2018 |
EM Time Dependence
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time-stationary | time-stationary |
EM Time Reference (Future/Past)
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Not applicable | Not applicable |
EM Time Continuity
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Not applicable | Not applicable |
EM Temporal Grain Size Value
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Not applicable | Not applicable |
EM Temporal Grain Size Unit
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Not applicable | Not applicable |
EM ID
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EM-131 | EM-970 |
Bounding Type
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Physiographic or ecological | Physiographic or ecological |
Spatial Extent Name
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Hood Canal | Urban green spaces in Lisbon |
Spatial Extent Area (Magnitude)
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100-1000 km^2 | 100-1000 km^2 |
EM ID
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EM-131 | EM-970 |
EM Spatial Distribution
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spatially distributed (in at least some cases) | spatially distributed (in at least some cases) |
Spatial Grain Type
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other (specify), for irregular (e.g., stream reach, lake basin) | map scale, for cartographic feature |
Spatial Grain Size
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Not reported | N/A |
EM ID
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EM-131 | EM-970 |
EM Computational Approach
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Analytic | Analytic |
EM Determinism
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deterministic | deterministic |
Statistical Estimation of EM
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EM ID
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EM-131 | EM-970 |
Model Calibration Reported?
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No | Yes |
Model Goodness of Fit Reported?
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No | Yes |
Goodness of Fit (metric| value | unit)
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None |
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Model Operational Validation Reported?
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No | No |
Model Uncertainty Analysis Reported?
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No | No |
Model Sensitivity Analysis Reported?
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No | Unclear |
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-131 | EM-970 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
EM-131 | EM-970 |
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None |
Centroid Lat/Long (Decimal Degree)
EM ID
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EM-131 | EM-970 |
Centroid Latitude
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47.8 | 38.75 |
Centroid Longitude
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-122.7 | 9.8 |
Centroid Datum
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NAD83 | None provided |
Centroid Coordinates Status
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Estimated | Estimated |
EM ID
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EM-131 | EM-970 |
EM Environmental Sub-Class
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Near Coastal Marine and Estuarine | Created Greenspace |
Specific Environment Type
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glacier-carver saltwater fjord | Green spaces in Lisbon, Portugal |
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 |
Scale of differentiation of organisms modeled
EM ID
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EM-131 | EM-970 |
EM Organismal Scale
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Not applicable | Guild or Assemblage |
Taxonomic level and name of organisms or groups identified
EM-131 | EM-970 |
None Available |
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EnviroAtlas URL
EM-131 | EM-970 |
None Available | Green Space per Capita |
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-131 | EM-970 |
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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-131 | EM-970 |
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