EcoService Models Library (ESML)
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EM: Human well-being index (HWBI), Pensacola Bay, Florida (EM-880)
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EM Identity and Description
EM Identification
EM ID
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EM-880 |
EM Short Name
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Human well-being index, Pensacola Bay, Florida |
EM Full Name
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Human well-being index (HWBI), Pensacola Bay, Florida |
EM Source or Collection
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US EPA |
EM Source Document ID
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418 |
Document Author
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Yee, S.H., Paulukonis, E., Simmons, C., Russell, M., Fullford, R., Harwell, L., and L.M. Smith |
Document Year
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2021 |
Document Title
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Projecting effects of land use change on human well being through changes in ecosystem services |
Document Status
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Peer reviewed and published |
Comments on Status
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Published journal manuscript |
Software and Access
Not applicable | |
Contact Name
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Susan Yee |
Contact Address
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Gulf Ecosystem Measurement and Modeling Division, Center for Environmental Measurement and Modeling, US Environmental Prntection Agency, Gulf Breeze, FL 32561, USA |
Contact Email
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yee.susan@epa.gov |
EM Description
Summary Description
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ABSTRACT: "Changing patterns of land use, temperature, and precipitation are expected to impact ecosystem se1vices, including water quality and quantity, buffering of extreme events, soil quality, and biodiversity. Scenario ana lyses that link such impacts on ecosystem se1vices to human well-being may be valuable in anticipating potential consequences of change that are meaningful to people living in a community. Ecosystem se1vices provide munerous benefits to community well-being, including living standards, health, cultural fulfillment, education, and connection to nature. Yet assessments of impacts of ecosystem se1vices on human well-being have largely focused on human health or moneta1y benefits (e.g. market values). This study applies a human well-being modeling framework to demonsffate the potential impacts of alternative land use scenarios on multi-faceted components of human well-being through changes in ecosystem se1vices (i.e., ecological benefits functions). The modeling framework quantitatively defines these relationships in a way that can be used to project the influence of ecosystem se1vice flows on indicators of human well-being, alongside social se1vice flows and economic se1vice flows. Land use changes are linked to changing indicators of ecosystem se1vices through the application of ecological production functions. The approach is demonstrated for two future land use scenarios in a Florida watershed, representing different degrees of population growth and environmental resource protection. Increasing rates of land development were almost universally associated with declines in ecosystem se1vices indicators and associated indicators of well-being, as natural ecosystems were replaced by impe1vious surfaces that depleted the ability of ecosystems to buffer air pollutants, provide habitat for biodiversity, and retain rainwater. Scenarios with increases in indicators of ecosystem se1vices, however, did not necessarily translate into increases in indicators of well-being, due to cova1ying changes in social and economic se1vices indicators. The approach is broadly ffansferable to other communities or decision scenarios and se1ves to illustrate the potential impacts of changing land use on ecosystem se1vices and human well-being. " |
Specific Policy or Decision Context Cited
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None identified |
Biophysical Context
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N/A |
EM Scenario Drivers
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N/A |
EM Relationship to Other EMs or Applications
Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
New or Pre-existing EM?
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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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Document ID for related EM
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None |
EM ID for related EM
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EM-882 |
EM Modeling Approach
EM Relationship to Time
EM Temporal Extent
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2010 |
EM Time Dependence
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time-stationary |
EM Time Reference (Future/Past)
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Not applicable |
EM Time Continuity
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Not applicable |
EM Temporal Grain Size Value
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Not applicable |
EM Temporal Grain Size Unit
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Not applicable |
EM Spatial Extent
Bounding Type
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Geopolitical |
Spatial Extent Name
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Pensacola Bay Region |
Spatial Extent Area (Magnitude)
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100-1000 km^2 |
Spatial Distribution of Computations
EM Spatial Distribution
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spatially distributed (in at least some cases) |
Spatial Grain Type
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area, for pixel or radial feature |
Spatial Grain Size
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county |
EM Structure and Computation Approach
EM Computational Approach
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Analytic |
EM Determinism
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deterministic |
Statistical Estimation of EM
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Model Checking Procedures Used
Model Calibration Reported?
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Unclear |
Model Goodness of Fit Reported?
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Not applicable |
Goodness of Fit (metric| value | unit)
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None |
Model Operational Validation Reported?
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No |
Model Uncertainty Analysis Reported?
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Yes |
Model Sensitivity Analysis Reported?
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Yes |
Model Sensitivity Analysis Include Interactions?
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Unclear |
EM Locations, Environments, Ecology
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
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Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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None |
Centroid Lat/Long (Decimal Degree)
Centroid Latitude
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30.05 |
Centroid Longitude
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-87.61 |
Centroid Datum
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WGS84 |
Centroid Coordinates Status
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Estimated |
Environments and Scales Modeled
EM Environmental Sub-Class
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Terrestrial Environment (sub-classes not fully specified) |
Specific Environment Type
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Mixed |
EM Ecological Scale
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Ecological scale is finer than that of the Environmental Sub-class |
Scale and taxa of organisms modeled
Scale of differentiation of organisms modeled
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EM Organismal Scale
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Not applicable |
Taxonomic level and name of organisms or groups identified
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None Available |
EnviroAtlas URL
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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)
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
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EM Variable Names (and Units)
Predictor
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Intermediate
Intermediate (Computed) Variables (and Units)
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None |
Response
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Observed Response Variables (and Units)
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None |
Computed Response Variables (and Units)
view details (9 variables)
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