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Mark Stafford Smith, Science Director Climate Adaptation Flagship

Anatomy of an integrated analysis involving adaptive capacity. Climate Adaptation National Research Flagship. Mark Stafford Smith, Science Director Climate Adaptation Flagship GEOSS/IPCC Workshop, Geneva, 1 Feb 2011. Topics.

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Mark Stafford Smith, Science Director Climate Adaptation Flagship

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  1. Anatomy of an integrated analysis involving adaptive capacity Climate Adaptation National Research Flagship Mark Stafford Smith, Science Director Climate Adaptation Flagship GEOSS/IPCC Workshop, Geneva, 1 Feb 2011

  2. Topics • Relating an experience: A multi-level analysis of drivers of migration from drylands globally • Project, not yet public, for UK Foresight process • Focus here on process and experience not results • (Really only proof of concept) • Characteristics • Linked some environmental and social drivers • Considered adaptive capacity and multiple levels explicitly • Needed to focus on consistent biome within-country • Trying to detect and forecast trends over time • Project to 2030+2060 • Implications for data??

  3. Drylands x countries From: http://geodata.grid.unep.ch/

  4. Land cover x aridity zone x country polygons Global Land Cover Facility, U Maryland

  5. Conceptualisation - 1 More movement is likely where there is: • more long term trend to less (environmental) resources per head • less national capacity and interest to invest in dryland regions • poorer investment outcomes in dryland regions • poorer recent or current environmental conditions, • all exacerbated by greater inequality

  6. Pressure to migrate Variance in population National capacity/ interest to invest in drylands National scale Local adaptive capacity (to move or to stay) Recent environmental conditions Local scale Trend in environmental services per head Conceptualisation - 2

  7. Variance in population well-being National capacity/ interest to invest in drylands Local adaptive capacity (to move or to stay) Recent environmental conditions Conceptualisation - 3 Pressure to migrate • % urban • GDP/capita • Corruption idx • GINI index • Drought idx 1y • Drought idx 10y • Child mortality • Road density (this polygon) Trend in environmental services per head • Pop’n increase • Trend in NPP/capita

  8. Slow variable: trends in environmental services • Trend in NPP • 1980-2000 AVHRR NDVI-derived NPP (Prince and Goward 1995 GloPEM) • Recognising MODIS would be better in the long run… • Averaged across each polygon • Future NPP: explored 5 DGVMs (Sitch et al. 2008) • V. variable performance in drylands; & much coarser resolution, so some polygons had to be dropped • Population: GPW from CIESIN • “Allocation gridding algorithm to assign population values to grid cells” – may be least accurate in drylands • NPP/population decadal trend • Created ratios within a polygon over time • Nb avoided comparing across space

  9. Trend in NPP/hd in drylands 85-90 to 95-00

  10. Environmental impacts • Drought index (Sheffield & Wood) • Indicator of acute drought and short-term changes in production capital • ‘Independent’ of NPP dataset • Looked within polygon at periods >12 months in its own lowest decile • Assumes local society ‘in balance’ with the polygon’s long-term median index • Generally seems good but poor in hyperarid • Long-term! 1948-2000 at 1° resolution • But not yet available for future runs at higher resolution

  11. Social projections • Country GDP (SRES) and population & urbanisation UN projections • Actually usually false resolution in databases since projected regionally • Ie. not even at country level, let alone drylands within country • Used as indicators of proportional change, not absolute • No future projections of other indicators • Sensitivity analysis instead • (still useful for decision-making)

  12. Case studies Easy 50% more if we could have gone back another decade in NPP…

  13. Projected migration intensity: A1, 2030

  14. Issues • Need long time series, unavoidably • Case studies over decades, + detection of change in variable environments • Historical and projections data need to be compatible • Problems with definition typologies (cf. ‘forest’) • Partially avoided by only looking at changes over time within one pixel (what is ‘one pixel’?….) • Data sets tuned for a particular purpose … • e.g. tuned for C mitigation don’t do drylands well • Adaptive capacity invariably multi-scaled! • Sub-national social data hard to come by • Not commensurate with environmental data • In space, in time, in collection units

  15. Some implications for adaptation research • Matched nested data sets • In space and time • Multiple levels, multiple scales • Accessibility • Documentation of data-set prejudices • What purpose in mind when it was cleaned up, etc? • Commensurate sampling • Especially social <-> environmental datasets • Need to make mature: learn to walk before we run • Work through in systematically chosen set of case studies

  16. Based on clear model of (different) systems functioning Resolving antagonistic paradigms • Adaptation – bottom-up local/regional/sectoral responses • Participatory ownership vital • Need a structured approach to extrapolation/scaling up Generalisations & global statements Typology of diverse systems x Categories of regional GEC impacts Complex sets of case studies without generalisability Broadly predictable sets of responses

  17. Directions for the workshop? • Long-term architecture and indicators needs • To deliver data for adaptation investment & evaluation for decision-makers (e.g. Adaptation Fund, nations) • What key decisions? • What key information for these decisions at what scales? • What architecture to aim towards? (i.e. Tues talk!) • Short term delivery to IPCC AR5 • Published description of needs; promote to parties • 2-3 proof-of-concept case studies, ??written up in time • Adaptations to changing water availability by basin? • Adaptation within mitigation actions of REDD+?? • Adaptive DRR preparations for one class of disasters? • Monitoring to a purpose!! but not just mitigation… • Biophysical and social data at multiple scales, including ‘in situ’, developed through demonstrators?

  18. Climate Adaptation Flagship Climate Adaptation Flagship Director: Andrew Ash [+61] 07 3214 2234 / andrew.ash@csiro.au Science Director: Mark Stafford Smith [+61] 0408 852 082 / mark.staffordsmith@csiro.au

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