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EM: Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa (EM-541)
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EM Identity and Description
EM Identification
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EM ID
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EM-541 |
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EM Short Name
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InVEST fisheries, lobster, South Africa |
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EM Full Name
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Integrated Valuation of Ecosystem Services and Trade-offs Fisheries, rock lobster, South Africa |
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EM Source or Collection
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InVEST |
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EM Source Document ID
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349 ?Comment:Supplemented with the InVEST Users Guide fisheries. |
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Document Author
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Ward, Michelle, Hugh Possingham, Johathan R. Rhodes, Peter Mumby |
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Document Year
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2018 |
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Document Title
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Food, money and lobsters: Valuing ecosystem services to align environmental management with Sustainable Development Goals |
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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 |
Software and Access
| https://www.naturalcapitalproject.org/invest/ | |
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Contact Name
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Michelle Ward |
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Contact Address
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ARC Centre of Excellence for Environmental Decisions, The University of Queensland, Brisbane, QLD 4072, Australia |
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Contact Email
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m.ward@uq.edu.au |
EM Description
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Summary Description
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AUTHOR'S DESCRIPTION: "Here we develop a method for assessing future scenarios of environmental management change that improve coastal ecosystem services and thereby, support the success of the SDGs. We illustrate application of the method using a case study of South Africa’s West Coast Rock Lobster fishery within the Table Mountain National Park (TMNP) Marine Protected Area...We calculated the retrospective and current value of the West Coast Rock Lobster fishery using published and unpublished data from various sources and combined the market worth of landed lobster from recreational fishers, small-scale fisheries (SSF), large-scale fisheries (LSF) and poachers. Then using the InVEST tool, we combined data to build scenarios that describe possible futures for the West Coast Rock Lobster fishery (see Table 1). The first scenario, entitled ‘Business as Usual’ (BAU), takes the current situation and most up-to-date data to model the future if harvest continues at the existing rate. The second scenario is entitled ‘Redirect the Poachers’ (RP), which attempts to model implementation of strict management, whereby poaching is minimised from the Marine Protected Area and other economic and nutritional sources are made available through government initiatives. The third scenario, entitled ‘Large Scale Cutbacks’ (LSC), excludes large-scale fisheries from harvesting West Coast Rock Lobster within the TMNP Marine Protected Area." |
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Specific Policy or Decision Context Cited
em.detail.policyDecisionContextHelp
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Future rock lobster fisheries management |
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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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Fisheries exploitation; fishing vulnerability (of age classes) |
EM Relationship to Other EMs or Applications
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Method Only, Application of Method or Model Run
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Method + Application (multiple runs exist) View EM Runs |
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New or Pre-existing EM?
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Application of existing 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 |
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EM ID for related EM
em.detail.relatedEmEmIdHelp
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None |
EM Modeling Approach
EM Relationship to Time
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EM Temporal Extent
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1986-2115 |
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EM Time Dependence
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time-dependent |
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EM Time Reference (Future/Past)
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future time |
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EM Time Continuity
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discrete |
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EM Temporal Grain Size Value
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1 |
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EM Temporal Grain Size Unit
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Year |
EM Spatial Extent
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Bounding Type
em.detail.boundingTypeHelp
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Geopolitical |
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Spatial Extent Name
em.detail.extentNameHelp
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Table Mountain National Park Marine Protected Area |
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Spatial Extent Area (Magnitude)
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100-1000 km^2 |
Spatial Distribution of Computations
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EM Spatial Distribution
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spatially lumped (in all cases) |
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Spatial Grain Type
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Not applicable |
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Spatial Grain Size
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Not applicable |
EM Structure and Computation Approach
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EM Computational Approach
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Numeric |
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EM Determinism
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deterministic |
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Statistical Estimation of EM
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Model Checking Procedures Used
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Model Calibration Reported?
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No |
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Model Goodness of Fit Reported?
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No |
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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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Yes ?Comment:A validation analysis was carried out running the model using data from 1880 to 2001, and then comparing the output for the adult population with the 2001 published data. |
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Model Uncertainty Analysis Reported?
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No |
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Model Sensitivity Analysis Reported?
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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
Location of EM Application
Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])
em.detail.relationToSpaceTerrestrialHelp
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| None |
Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)
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Centroid Lat/Long (Decimal Degree)
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Centroid Latitude
em.detail.ddLatHelp
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-34.18 |
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Centroid Longitude
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18.35 |
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Centroid Datum
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WGS84 |
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Centroid Coordinates Status
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Provided |
Environments and Scales Modeled
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EM Environmental Sub-Class
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Near Coastal Marine and Estuarine |
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Specific Environment Type
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Rocky coast, mixed coast, sandy coast, rocky inshore, sandy inshore, rocky shelf and unconsolidated shelf |
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EM Ecological Scale
em.detail.ecoScaleHelp
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Ecological scale corresponds to 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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Individual or population, within a species |
Taxonomic level and name of organisms or groups identified
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EnviroAtlas URL
em.detail.enviroAtlasURLHelp
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| Big game hunting recreation demand |
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.detail.cicesHelp
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(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)
fegs2Help
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EM Variable Names (and Units)
Predictor
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Intermediate
Response
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Observed Response Variables (and Units)
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None |
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Computed Response Variables (and Units)
view details (3 variables)
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