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EM Identity and Description

EM Identification (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Short Name em.detail.shortNameHelp ?	Biodiversity offsetting, Germany	*	*	*
EM Full Name em.detail.fullNameHelp ?	Integrated assessment of regional approaches for biodiversity offsetting in urban-rural areas – A future based case study from Germany using arable land as an example	*	*	*
EM Source or Collection em.detail.emSourceOrCollectionHelp ?	None	*	*	*
EM Source Document ID	499	*	*	*
Document Author em.detail.documentAuthorHelp ?	Sponagel, C., Bendel, D., Angenendt, E., Weber, T.K.D., Gayler, S., Streck, T. and Bahrs, E.	*	*	*
Document Year em.detail.documentYearHelp ?	2022	*	*	*
Document Title em.detail.sourceIdHelp ?	Integrated assessment of regional approaches for biodiversity offsetting in urban-rural areas–A future based case study from Germany using arable land as an example	*	*	*
Document Status em.detail.statusCategoryHelp ?	Peer reviewed and published	*	*	*
Comments on Status em.detail.commentsOnStatusHelp ?	Published journal manuscript	*	*	*

Software and Access (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Software Access info Exit em.detail.modelAccessInformationHelp ?	Not applicable	*	*	*
Contact Name em.detail.contactNameHelp ?	Christian Sponagel	*	*	*
Contact Address	Department of Farm Management (410b), Institute of Farm Management, University of Hohenheim, Schwerzstraße 44, 70593 Stuttgart, Germany	*	*	*
Contact Email	Christian.Sponagel@Uni-Hohenheim.de	*	*	*

EM Description (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Summary Description em.detail.summaryDescriptionHelp ?	Human interventions, i.e. settlement and construction activities, in the agricultural landscape including farmland but also natural and semi-natural habitats are a major driver of biodiversity loss. Consequently, their impacts on nature and landscape have to be compensated by no net loss policies in many countries around the world. However, their practical implementation often poses challenges with regard to the optimal spatial coordination and assessment of measures, especially in the case of eco-accounts or other habitat banking approaches. Against this backdrop, different approaches to offset biodiversity loss at regional level are analysed with due consideration of indicators of economy, ecology, landscape aesthetics and food production. We used an interdisciplinary modelling approach based on estimates for offsetting demand until 2030. In the integrated land use model, we associated a biophysical crop growth model with an economic optimisation model. The Stuttgart Region – an area with stiff competition amongst anthropogenic land use patterns in Germany – served as the study area. Our main focus was on arable land that has a high potential for nature conservation enhancement. In this context, farmers are deemed to be a major stakeholder group. We observed differing economic and ecological outcomes for the offsetting scenarios we considered. In urban areas with high population density and low biodiversity (e.g. Stuttgart city), compensation close to the site of intervention (on-site) may be more expensive than off-site compensation. However, further added value can be generated by on-site compensation in terms of visual landscape quality enhancement and habitat connectivity, provided that the measures lend themselves to establishing connectivity. Consequently, spatially unrestricted markets for eco credits may exacerbate ecological polarisation between urban and rural areas. Therefore, we concluded that offset site selection should not be driven solely by economics, as this may not optimise overall welfare from a societal perspective, resulting in the need for legal constraints. Our results show the trade-offs between the political goals of spatial planning approaches and compensation strategies. They can, therefore, thus provide valuable information that enables political decision-makers to more clearly weigh up the effects of policy measures in this area.	*	*	*
Specific Policy or Decision Context Cited em.detail.policyDecisionContextHelp ?	Demonstration of trade-offs between political goals of spatial planning approaches and compensation strategies to inform decision making.	*	*	*
Biophysical Context	Stuttgart region, Germany	*	*	*
EM Scenario Drivers em.detail.scenarioDriverHelp ?	1. Off-site	1. On-site	1. Off-site with coordination	1. Partly off-site with coordination

EM Relationship to Other EMs or Applications

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Method Only, Application of Method or Model Run em.detail.methodOrAppHelp ?	Method + Application (multiple runs exist)	Model Run Associated with a Specific EM Application	Model Run Associated with a Specific EM Application	Model Run Associated with a Specific EM Application
New or Pre-existing EM? em.detail.newOrExistHelp ?	New or revised model	1. On-site	Off-site with coordination	Partly off-site with coordination

Related EMs (for example, other versions or derivations of this EM) described in ESML

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Document ID for related EM em.detail.relatedEmDocumentIdHelp ?	None	None	None	None
EM ID for related EM em.detail.relatedEmEmIdHelp ?	None	None	None	None

EM Modeling Approach

EM Relationship to Time (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Temporal Extent em.detail.tempExtentHelp ?	2022-2030	*	*	*
EM Time Dependence em.detail.timeDependencyHelp ?	time-dependent	*	*	*
EM Time Reference (Future/Past) em.detail.futurePastHelp ?	future time	*	*	*
EM Time Continuity em.detail.continueDiscreteHelp ?	continuous	*	*	*
EM Temporal Grain Size Value em.detail.tempGrainSizeHelp ?	Not applicable	*	*	*
EM Temporal Grain Size Unit em.detail.tempGrainSizeUnitHelp ?	Not applicable	*	*	*

EM spatial extent (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Bounding Type em.detail.boundingTypeHelp ?	Geopolitical	*	*	*
Spatial Extent Name em.detail.extentNameHelp ?	Stuttgart Region	*	*	*
Spatial Extent Area (Magnitude) em.detail.extentAreaHelp ?	1000-10,000 km^2.	*	*	*

Spatial Distribution of Computations (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Spatial Distribution em.detail.distributeLumpHelp ?	spatially distributed (in at least some cases)	*	*	*
Spatial Grain Type em.detail.spGrainTypeHelp ?	map scale, for cartographic feature	*	*	*
Spatial Grain Size em.detail.spGrainSizeHelp ?	Not reported	*	*	*

EM Structure and Computation Approach (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Computational Approach em.detail.emComputationalApproachHelp ?	Analytic	*	*	*
EM Determinism em.detail.deterStochHelp ?	deterministic	*	*	*
Statistical Estimation of EM em.detail.statisticalEstimationHelp ?	Conventional (frequentist) statistics	*	*	*

Model Checking Procedures Used (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Model Calibration Reported? em.detail.calibrationHelp ?	Yes	*	*	*
Model Goodness of Fit Reported? em.detail.goodnessFitHelp ?	Unclear	*	*	*
Goodness of Fit (metric\| value \| unit) em.detail.goodnessFitValuesHelp ?	None	*	*	*
Model Operational Validation Reported? em.detail.validationHelp ?	Unclear	*	*	*
Model Uncertainty Analysis Reported? em.detail.uncertaintyAnalysisHelp ?	Unclear	*	*	*
Model Sensitivity Analysis Reported? em.detail.sensAnalysisHelp ?	Yes	*	*	*
Model Sensitivity Analysis Include Interactions? em.detail.interactionConsiderHelp ?	Unclear	*	*	*

EM Locations, Environments, Ecology

Location of EM Application (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

Terrestrial location (Classification hierarchy: Continent > Country > U.S. State [United States only])

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Europe Germany	*	*	*

Marine location (Classification hierarchy: Realm > Region > Province > Ecoregion)

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
None	*	*	*

Centroid Lat/Long (Decimal Degree)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Centroid Latitude em.detail.ddLatHelp ?	49.12	*	*	*
Centroid Longitude em.detail.ddLongHelp ?	9.71	*	*	*
Centroid Datum em.detail.datumHelp ?	WGS84	*	*	*
Centroid Coordinates Status em.detail.coordinateStatusHelp ?	Estimated	*	*	*

Environments and Scales Modeled (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Environmental Sub-Class em.detail.emEnvironmentalSubclassHelp ?	Terrestrial Environment (sub-classes not fully specified)	*	*	*
Specific Environment Type em.detail.specificEnvTypeHelp ?	Mixed urban, rural, and natural ecosystems	*	*	*
EM Ecological Scale em.detail.ecoScaleHelp ?	Ecological scale corresponds to the Environmental Sub-class	*	*	*

Organisms modeled (* Note that run information is shown only where run data differ from the "parent" entry shown at left)

Scale of differentiation of organisms modeled

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
EM Organismal Scale em.detail.orgScaleHelp ?	Community	*	*	*

Taxonomic level and name of organisms or groups identified

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
None Available	*	*	*

EnviroAtlas URL

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
GAP Ecological Systems, Average Annual Precipitation, Agricultural water use (million gallons/day), Enabling Conditions, Employment Rate	GAP Ecological Systems, Average Annual Precipitation, Agricultural water use (million gallons/day), Enabling Conditions, Employment Rate	GAP Ecological Systems, Average Annual Precipitation, Agricultural water use (million gallons/day), Enabling Conditions, Employment Rate	GAP Ecological Systems, Average Annual Precipitation, Agricultural water use (million gallons/day), Enabling Conditions, Employment Rate

EM Ecosystem Goods and Services (EGS) potentially modeled, by classification system

* Note that run information is shown only where run data differ from the "parent" entry shown at left

CICES v 4.3 - Common International Classification of Ecosystem Services (Section > Division > Group > Class)

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
[Non-ecosystem] Cultural settings dependent on abiotic structures Physical and intellectual interactions with land-/seascapes [physical settings] By physical and experiential interactions or intellectual and representational interactions Not applicable [Ecosystem] Provisioning Nutrition Biomass Cultivated crops [Ecosystem] Regulation & Maintenance Maintenance of physical, chemical, biological conditions Lifecycle maintenance, habitat and gene pool protection Maintaining nursery populations and habitats Pollination and seed dispersal	*	*	*

National Ecosystem Services Classification System (NESCS) Plus

(Environmental Subclass > Ecological End-Product (EEP) > EEP Subclass > EEP Modifier)

EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
None	*	*	*

EM Variable Names (and Units)

* Note that for runs, variable name is displayed only where data for that variable differed by run AND those differences were reported in the source document. Where differences occurred but were not reported, the variable is not listed. Click on variable name to view details.

To view run information for variables, select any variable below or view run data for all variables.

Predictor

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Driving Variables (and Units) em.detail.drivingVariableHelp ?	Assessment of land use options in eco credits (eco credits / m^2) Cereal and livestock unit key (Not reported) Crop management (Not reported) District level crop yields (dt FM / ha) Fertilization (Not reported) Land use (Not reported) Landscape aesthetic weights (NA) Landscape elements and biotope network (Not reported) Offset demand per municipality (million €) Offset scenarios (NA) Prices (€) Soil data (Not reported) Standard land values at municipal level (€ / ha) Variable costs (€) Weather / climate input (Not reported) Willingness to accept for offset measures (€ / ha)	*	*	*
Constant or Factor Variables (and Units) em.detail.constantFactorVariableHelp ?	None	*	*	*

Intermediate

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Intermediate (Computed) Variables (and Units) em.detail.intermediateVariableHelp ?	Agricultural land use (maximize net return) (Not reported) Biophysical yield simulation at field level (Not reported) Land use per field (Not reported)	*	*	*

Response

EM ID em.detail.idHelp ?	EM-1049	1. On-site	Off-site with coordination	Partly off-site with coordination
Observed Response Variables (and Units) em.detail.observedResponseHelp ?	None	*	*	*
Computed Response Variables (and Units) em.detail.computedResponseHelp ?	Area covered by offset measures in relation to arable land scenario (%) Average price per eco credit (€) Average price per eco credit with a +20% change in producer prices (€) Average price per eco credit with an interest rate of 1% (€) Average price per eco credit with an interest rate of 3% (€) Change in food production relative to scenario 1 (%) Coverage of the offset demand at the municipal level (%) Future crop yields (dt FM / ha) Implementation areas of offset measures on arable land (1000 ha) Landscape connectivity in arable land (%) Price change in relation to scenario 1 (%) Share of total offset area in above average landscape quality (%) Share of total offset area in average landscape quality (%) Share of total offset area in below average landscape quality (%) Spatial volume of the individuals offset measures by scenario (ha) Total costs for offsetting (million €) Weighted Shannon diversity index for above average landscape quality (NA) Weighted Shannon diversity index for average landscape quality (NA) Weighted Shannon diversity index for below average landscape quality (NA)	Area covered by offset measures in relation to arable land scenario (%) Average price per eco credit (€) Average price per eco credit with a +20% change in producer prices (€) Average price per eco credit with an interest rate of 1% (€) Average price per eco credit with an interest rate of 3% (€) Change in food production relative to scenario 1 (%) Implementation areas of offset measures on arable land (1000 ha) Landscape connectivity in arable land (%) Price change in relation to scenario 1 (%) Share of total offset area in above average landscape quality (%) Share of total offset area in average landscape quality (%) Share of total offset area in below average landscape quality (%) Spatial volume of the individuals offset measures by scenario (ha) Total costs for offsetting (million €) Weighted Shannon diversity index for below average landscape quality (NA)	Area covered by offset measures in relation to arable land scenario (%) Average price per eco credit (€) Average price per eco credit with a +20% change in producer prices (€) Average price per eco credit with an interest rate of 1% (€) Average price per eco credit with an interest rate of 3% (€) Change in food production relative to scenario 1 (%) Implementation areas of offset measures on arable land (1000 ha) Landscape connectivity in arable land (%) Price change in relation to scenario 1 (%) Share of total offset area in above average landscape quality (%) Share of total offset area in average landscape quality (%) Share of total offset area in below average landscape quality (%) Spatial volume of the individuals offset measures by scenario (ha) Total costs for offsetting (million €) Weighted Shannon diversity index for average landscape quality (NA) Weighted Shannon diversity index for below average landscape quality (NA)	Area covered by offset measures in relation to arable land scenario (%) Average price per eco credit (€) Average price per eco credit with a +20% change in producer prices (€) Average price per eco credit with an interest rate of 1% (€) Average price per eco credit with an interest rate of 3% (€) Change in food production relative to scenario 1 (%) Implementation areas of offset measures on arable land (1000 ha) Landscape connectivity in arable land (%) Price change in relation to scenario 1 (%) Share of total offset area in above average landscape quality (%) Share of total offset area in average landscape quality (%) Share of total offset area in below average landscape quality (%) Spatial volume of the individuals offset measures by scenario (ha) Total costs for offsetting (million €) Weighted Shannon diversity index for below average landscape quality (NA)

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: Integrated assessment of regional approaches for biodiversity offsetting in urban-rural areas ? A future based case study from Germany using arable land as an example (EM-1049)