Biodiversity data for decision making. Jörn P. W. Scharlemann

Transcription

1 Biodiversity data for decision making Jörn P. W. Scharlemann

2 UNEP-WCMC is UNEP s Biodiversity Assessment Centre Founded in 1981 Mission To provide authoritative information about biodiversity and ecosystem services in a manner that is useful to decision-makers who are driving change in environment and development policy

3 Databases for biodiversity assessment 3

4 Databases for biodiversity assessment 4

5 Databases for biodiversity assessment 5

6 Global Ecoregion Protection. Published in Protected Areas Annual Report: UNEP-WCMC 2008

7 Global analysis of the protection status of the world s forests. Biological Conservation 2009

8 Toward representative protection of the world s coasts and oceans progress, gaps, and opportunities. Conservation Letters 2008

9 Aichi Target 11 By 2020, at least 17 per cent of terrestrial and inland water areas, and 10 per cent of coastal and marine areas, especially areas of particular importance for biodiversity and ecosystem services, are conserved through effectively and equitably managed, ecologically representative and well connected systems of protected areas and other effective area-based conservation measures, and integrated into the wider landscapes and seascapes.

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11 Improvements in WDPA % 59% Databases for biodiversity assessment 11

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14 New wiki-style, web-interface for learning about and contributing to WDPA

15 Interact with Data Download / Upload Data Reconcile Data Edit data on-line Cut out the middle man View users (stakeholder) opinions

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17 Global Biodiversity Information Facility (GBIF) Species & Protected Areas Widget..more like this to come...

18 Databases for biodiversity assessment 18

19 Existing global data for mangroves Two recent global studies: World Atlas of Mangroves 2010, published by UNEP, ISME, ITTO, FAO, UNU, UNESCO & TNC Giri et al, 2010: Global Ecology and Biogeography 20(1), UNEP, USGS, NASA

20 Global Spatial similarity: 0.4 Fitzgerald, C, Giri, C., Kainuma, M., Latham, J., Wilkie, M., Singh, A., Spalding, M., Wood, L

21 Some National Examples Kenya Australia Indonesia Work is ongoing to do more in-depth comparison of all countries to try to estimate uncertainties more comprehensively this is indicative only.

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24 HarmBio Harmonizing Global Biodiversity Modelling Jörn P. W. Scharlemann

25 HarmBio COST Action Harmonizing Global Biodiversity Modelling Aim The harmonization of current models and datasets of terrestrial, freshwater and marine biodiversity to improve the reliability of future projections of biodiversity change under various policy options enabling better environmental decision making.

26 Modelling climate change +2 C EU target

27 Biodiversity data GEO-BON

28 Biodiversity metrics

29 Biodiversity scenarios Pereira et al Science 330:

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31 Modelling Models are simplified mathematical representations of complex systems

32 Modelling Models are simplified mathematical representations of complex systems. Epidemiological models inform responses to disease pandemics Atmospheric models project future climate Economic models guide financial decisions

33 Modelling biodiversity change Statistical niche models Integrated assessment models

34 Overview HarmBio Data Metrics Models Metrics Policy Scenarios

35 HarmBio COST Action Harmonizing Global Biodiversity Modelling Aim The harmonization of current models and datasets of terrestrial, freshwater and marine biodiversity to improve the reliability of future projections of biodiversity change under various policy options enabling better environmental decision making.

36 HarmBio COST Action Harmonizing Global Biodiversity Modelling Better models transparent scientifically robust intercomparable common data and scenarios Better decisions based on state-of-the-art approved projections feed into assessments, eg. IPBES, post 2010 EU Biodiversity Strategy

37 HarmBio COST Action Harmonizing Global Biodiversity Modelling Biodiversity and Climate Research Centre, Senckenberg University of British Columbia, Canada Yale University, USA University of Copenhagen National Museum of Natural Sciences, Madrid Universite Paris-Sud Sapienzia Universita di Roma Alterra Wageningen PBL NL Environmental Assessment Agency UNEP GRID Arendal Universidade de Lisboa Imperial College London University of East Anglia University of York UNEP-WCMC CSIRO, Australia 22 participants from 15 COST countries, 1 COST reciprocal country & 2 other countries

38 HarmBio COST Action Harmonizing Global Biodiversity Modelling

39 HarmBio COST Action Harmonizing Global Biodiversity Modelling Inauguration, election MC & WG chairs Opening symposium Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC 2 nd symposium Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC Final symposium Year 1 Year 2 Year 3 Year 4 WG1: Consensus on metrics STSM WG2: Harmonized datasets WG3: Agree standards for models STSM STSM STSM WG4: Intercomparison of models STSM

40 HarmBio COST Action Harmonizing Global Biodiversity Modelling WG1: Consensus on biodiversity metrics currently every model produces different output metric (species richness, extinction risk, abundance, habitats,...) multitude of national, regional & global indicators consensus required for comparison, integration into Earth system models and to guide policy agree on scientifically robust and policy relevant metrics of biodiversity & processes

41 HarmBio COST Action Harmonizing Global Biodiversity Modelling WG2: Harmonized datasets currently every model uses different input data and different data on environmental conditions and human activities consensus required for model comparison long-term access to data and metadata agree and compile datasets incl. full description & long-term storage of key datasets; collaborate with GEO-BON, GBIF, etc.

42 HarmBio COST Action Harmonizing Global Biodiversity Modelling WG3: Standards for biodiversity models currently every model addresses different components of biodiversity and different processes documentation variable explicit about components and feedbacks consensus required for model comparison and link to global climate models build consensus on processes and components essential for model development; standards for documentation and transparency

43 HarmBio COST Action Harmonizing Global Biodiversity Modelling WG4: Intercomparison of biodiversity models currently individual models cannot be compared comparison needed to assess model capability to hindcast historic/observed changes in biodiversity future projections based on standardised scenarios facilitate systematic intercomparison and benchmarking of biodiversity models

44 HarmBio COST Action Harmonizing Global Biodiversity Modelling Inauguration, election MC & WG chairs Opening symposium Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC 2 nd symposium Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC Meetings of WG & MC Final symposium Year 1 Year 2 Year 3 Year 4 WG1: Consensus on metrics STSM WG2: Harmonized datasets WG3: Agree standards for models STSM STSM STSM WG4: Intercomparison of models STSM

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48 ...from a technical perspective Managed Off-line Managed On-line.fgdb

49 Global Data Partnership Strengthen the business case for better data Transform the volume & rate of improvement of coastal ecosystem data Beneficiaries clearer: Governments Citizens Private Sector

50 Outcomes Transformed methodologies for data collection Citizen Science communities of contributors Core standards and protocols Freely available, reliable data Transparency of contributions Consistency of monitoring in local initiatives Enable better decision-making across sectors Blue C & Ecosystem Service assessments Robust basis of market-based instruments Strengthened local capacity to integrate coastal issues in national management strategies, EIA, etc

51 Outputs Consolidated Partnership networks Consistent global baselines Validated and enriched datasets Improved transparency, accessibility, visualisation of data