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Making Natural Capital Data Meaningful -in Scotland

Making Natural Capital Data Meaningful -in Scotland

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Making Natural Capital Data Meaningful -in Scotland

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  1. Making Natural Capital Data Meaningful -in Scotland Alessandro Gimona, Laura Poggio, Andrea Baggio, Marie Castellazzi, David Donnelly, Justin Irvine

  2. Landscape Resilience: the overarching objective Resilience “refers to the magnitude of change or disturbance that a system can experience without shifting into an alternate state that has different structural and functional properties and supplies different bundles of the ecosystem services that benefit people” Rationale: reconciling human activities/development with environmental quality

  3. Policy drivers • EU -Action 5 of the EU Biodiversity Strategy : Map, assess, value, ecosystem services; -ESS help the integration of BS ,CAP ,WFD, Forest and Climate policies • Scotland Biodiversity strategy; Land Use Strategy principles: delivering multiple benefits implies providing multiple ecosystem services.

  4. Research Programme • System State—biophysical and socio-economics • Institutions - coordination of policy; adaptive governance; participation • Scenarios (resilience to CC and LUC)

  5. Research Programme • System State—biophysical and socio-economics • Institutions - coordination of policy; adaptive governance; participation • Scenarios (resilience to CC and LUC)

  6. Indicator of resilience: landscape multifunctionality Multifunctional: A range of ESS and benefits Loss of biodiversity, resilience and ultimately, of well-being Fewer ESS and benefits

  7. Main messages • NC/ESS assessment strengthens the case for the conservation of ecosystems and allows better spatial targeting • There is a great deal of information and complexity in ESS assessment that makes participation challenging and requires tools to aid stakeholders

  8. Landscape Description • MA + CICES classification (Provisioning Regulating Cultural) • ESS and landscape patterns

  9. Mapped indicators of ESS Compared to UK-NEA: More indicators Better spatial resolution More detailed models and data Partly in: Verhagen et al. 2016, Landscape Ecology

  10. Data Integration –Satellite and ground data • General workflow model selection from many possible sat. covariates Restored (cloud-cleared) Images Poggio, L., Gimona, A., Brewer, M.J.Regional scale mapping of soil properties and their uncertainty with a large number of satellite-derived covariatesGeoderma 209–210, 1–14, 2013.http://www.sciencedirect.com/science/article/pii/S0016706113001997

  11. Hotspots & Coldspots H.S.: Areas with Co-occurrence of high service values Robustness to sensitivity analysis Gimona and van der Horst 2007;Schroter and Remme, 2016

  12. Hotspots –by ESS type regulating cultural provisioning

  13. ES-Scapes functional areas based on ESS Cluster Analysis

  14. ES-Scapes functional areas based on ESS

  15. ESS-based landscape planning • Adaptive governance • Complexity • Need for participation • Need for tools

  16. Wind turbines: strategic planning based on 19 criteria (9 were ESS) Many factors: Existing zonation and legislation; landscape character and morphology Protected areas .. Perth and Kinross Pioneering use of ESS in official planning

  17. Web-based tool to assess options

  18. Web-based MCA +ESS user can explore the effect of altering the weighting of related groups of criteria on suitability for the land use change in question. By moving the slider (altering the weighting) the user affects the weights of the input layers (criteria) used to calculate the suitability and hence produce the map to visualise the effect Clusters of criteria

  19. Land Change Advice-many ESS at one time Lake District National Park

  20. Lake District National Park Level of Multi-functionality based on ESS delivery

  21. Park Stakeholders want to know: • Where are opportunities to change land use? • What land use changes should they consider and where given: • Stkhs. Priorities & interests • Spatial suitability for each LU change • Gaps in ESS delivery (spatial)

  22. Sustainable Land Management - OptionsTool Input : ESS-derived opportunity maps Stakeholders define ESS priorities for improvement Output: land use/management change advice (where & what) SLM-OptionsTool

  23. Conclusions Earth Observation MODIS Landsat Sentinel1 (radar) Sentinel2 (optical) Soil NSIS Soil Properties DB Digital Terrain Model 50m to 5m Land Cover/Use LCM2007 Forest Inventories IACS Natural Heritage Habitats Protected areas Spp. distributions Cultural artefacts NC/ESS Models Volunteered Geographic Information e.g. Photos submitted to Google Earth; citizen science.. Combine to according to Policy Goals; MCA; Valuation; Scenarios

  24. Conclusions • Mapping ESS and monitoring change is a qualitative leap in • environmental understanding & management ..but • it involves complex, data demanding tasks • Knowledge co-production and adaptive and • participated governance are necessary but difficult to implement • Stakeholders buy-in does not mean accurate results. • Capacity building and friendly tools improve the quality • and adaptiveness of the process

  25. Thanks for your attention Contact: alessandro.gimona@hutton.ac.uk Thanks to the Scottish government for financial support