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-878 |
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EM Short Name
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Health, safety and greening urban space, PA, USA |
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EM Full Name
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Health, safety and greening urban vacant space, Pennsylvania, USA |
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EM Source or Collection
em.detail.emSourceOrCollectionHelp
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None |
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EM Source Document ID
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419 |
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Document Author
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Branas, C. C., R. A. Cheney, J. M. MacDonald, V. W. Tam, T. D. Jackson, and T. R. Ten Havey |
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Document Year
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2011 |
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Document Title
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A difference-in-differences analysis of health, safety, and greening vacant urban space |
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Document Status
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Peer reviewed and published |
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Comments on Status
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Published journal manuscript |
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EM ID
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EM-878 |
| Not applicable | |
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Contact Name
em.detail.contactNameHelp
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Charles C. Branas |
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Contact Address
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Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, Blockley Hall, Room 936, 423 Guardian Drive, Philadelphia, PA 19104-6021 |
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Contact Email
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cbranas@upenn.edu |
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EM ID
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EM-878 |
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Summary Description
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ABSTRACT: "Greening of vacant urban land may affect health and safety. The authors conducted a decade-long difference-indifferences analysis of the impact of a vacant lot greening program in Philadelphia, Pennsylvania, on health and safety outcomes. ‘‘Before’’ and ‘‘after’’ outcome differences among treated vacant lots were compared with matched groups of control vacant lots that were eligible but did not receive treatment. Control lots from 2 eligibility pools were randomly selected and matched to treated lots at a 3:1 ratio by city section. Random-effects regression models were fitted, along with alternative models and robustness checks. Across 4 sections of Philadelphia, 4,436 vacant lots totaling over 7.8 million square feet (about 725,000 m^2) were greened from 1999 to 2008. Regression adjusted estimates showed that vacant lot greening was associated with consistent reductions in gun assaults across all 4 sections of the city (P < 0.001) and consistent reductions in vandalism in 1 section of the city (P < 0.001). Regression-adjusted estimates also showed that vacant lot greening was associated with residents’ reporting less stress and more exercise in select sections of the city (P < 0.01). Once greened, vacant lots may reduce certain crimes and promote some aspects of health. Limitations of the current study are discussed. Community-based trials are warranted to further test these findings." REVIEWER'S COMMENTS: Regression models were fitted separately for point-based, tract-based, and block group-based outcomes, and for the four sections of Philadelphia separately and combined. This entry presents just the point-based outcomes for the whole of Philadelphia. |
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Specific Policy or Decision Context Cited
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None identified |
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Biophysical Context
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No additional description provided |
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EM Scenario Drivers
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No scenarios presented |
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EM ID
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EM-878 |
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Method Only, Application of Method or Model Run
em.detail.methodOrAppHelp
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Method + Application |
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New or Pre-existing EM?
em.detail.newOrExistHelp
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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-878 |
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Document ID for related EM
em.detail.relatedEmDocumentIdHelp
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None |
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EM ID for related EM
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None |
EM Modeling Approach
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EM ID
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EM-878 |
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EM Temporal Extent
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1998-2008 |
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EM Time Dependence
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time-stationary |
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EM Time Reference (Future/Past)
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Not applicable |
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EM Time Continuity
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Not applicable |
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EM Temporal Grain Size Value
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Not applicable |
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EM Temporal Grain Size Unit
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Not applicable |
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EM ID
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EM-878 |
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Bounding Type
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Geopolitical |
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Spatial Extent Name
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Philadelphia |
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Spatial Extent Area (Magnitude)
em.detail.extentAreaHelp
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100-1000 km^2 |
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EM ID
em.detail.idHelp
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EM-878 |
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EM Spatial Distribution
em.detail.distributeLumpHelp
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spatially distributed (in at least some cases) ?Comment:Point-based measures are continuous and boundary-free, assign each lot to its own unique neighborhood, and avoid aggregation effects while directly accounting for spillover and the variability of neighboring areas. |
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Spatial Grain Type
em.detail.spGrainTypeHelp
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other (specify), for irregular (e.g., stream reach, lake basin) |
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Spatial Grain Size
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Point based |
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EM ID
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EM-878 |
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EM Computational Approach
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Analytic |
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EM Determinism
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deterministic |
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Statistical Estimation of EM
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EM ID
em.detail.idHelp
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EM-878 |
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Model Calibration Reported?
em.detail.calibrationHelp
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No |
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Model Goodness of Fit Reported?
em.detail.goodnessFitHelp
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No ?Comment:Each outcome was fitted separatly, with R2 provided. See Variable Value comment for each Response. |
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Goodness of Fit (metric| value | unit)
em.detail.goodnessFitValuesHelp
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None |
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Model Operational Validation Reported?
em.detail.validationHelp
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No |
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Model Uncertainty Analysis Reported?
em.detail.uncertaintyAnalysisHelp
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No |
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Model Sensitivity Analysis Reported?
em.detail.sensAnalysisHelp
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No |
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Model Sensitivity Analysis Include Interactions?
em.detail.interactionConsiderHelp
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Not applicable |
EM Locations, Environments, Ecology
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
| EM-878 |
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
| EM-878 |
| None |
Centroid Lat/Long (Decimal Degree)
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EM ID
em.detail.idHelp
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EM-878 |
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Centroid Latitude
em.detail.ddLatHelp
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39.95 |
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Centroid Longitude
em.detail.ddLongHelp
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-75.17 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
em.detail.coordinateStatusHelp
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Estimated |
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EM ID
em.detail.idHelp
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EM-878 |
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EM Environmental Sub-Class
em.detail.emEnvironmentalSubclassHelp
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Created Greenspace |
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Specific Environment Type
em.detail.specificEnvTypeHelp
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Urban and urban green space |
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EM Ecological Scale
em.detail.ecoScaleHelp
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Ecological scale corresponds to the Environmental Sub-class |
Scale of differentiation of organisms modeled
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EM ID
em.detail.idHelp
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EM-878 |
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EM Organismal Scale
em.detail.orgScaleHelp
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Not applicable |
Taxonomic level and name of organisms or groups identified
| EM-878 |
| None Available |
EnviroAtlas URL
| EM-878 |
| Percent Population other than White, Non-Hispanic, GAP Ecological Systems, Green Space per Capita, Total Employment, Percent Population under 13 Years Old, Employment Rate |
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-878 |
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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-878 |
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