Analysis of forest-livelihoods nexus:  how can global data set help?             Sonya Dewi, Brian Belcher,               ...
Outline• PEN study and dataset• Characterization of the diverse parts of the  tropics• Extrapolation domain of large scale...
ABOUT PEN STUDY
The PENis a…set                  PEN data• Large (360 villages, 10,000+ households)• pan-tropical (25 countries, 3 regions...
CHARACTERIZATION OF THEDIVERSE PARTS OF THE TROPICS
Global datasetSpatial analysis of global maps clipped for the tropics only:• Global land cover: JRC, 2006. The Global Land...
Ecosystem  Scale 1:10,000,000Source: WWF, 2005. WWF TerrestrialEcoregions
Ecosystem: Area and Population
How much is protected?100% 90% 80% 70% 60% 50% 40% 30% 20% 10%  0%                                Inside PA               ...
How much is forested?
Forest configurationMillions   1,800           1,600           1,400           1,200           1,000             800      ...
EXTRAPOLATION DOMAIN
Sub-basin: typology (FT)
% Medium Broadleaved forest% Open broadleaved forest% Mixed tree cover
Proportion of Area                                                                                            Of Populatio...
MULTILEVEL ANALYSIS OFRELATIONSHIPS OF LIVELIHOODS ANDFORESTS
- Multi-level  o Hh characteristics  o Resource base  o Access to market  o Access to    resources  o … - Policies should ...
Coeff Signif.                                      Coeff Signif.Total income (ln)                              Watershed-l...
Global dataset can help …• Providing context to case studies and  comparative studies at different scales• Finding the sam...
THANK YOU
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Seminar13 Mar 2013 - Sesion 1 - Analysis of forest-livelihoods nexus global data set by SDewi

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We explore methodologies that allow conclusions to be drawn from the large Poverty Environment Network (PEN) dataset. First, we characterize the diverse parts of the tropics in terms of factors that influence forest resources, access and livelihoods. Secondly, for the conclusions drawn from the site-based analysis to be useful for roader policy recommendations, we need to know the extrapolation domains. We compared the characteristics of landscapes where PEN studies took place with overall tropical landscapes, and those of PEN villages with 'random' villages. Both methods rely on variables derived from global data sets using spatial analysis. Thirdly, we study the relationships of livelihoods and forests using multilevel regression analysis. Our study suggests that for global comparative analysis, it is necessary to identify the overall variation of the system of interest, to define the extrapolation domain of the samples/study sites, and to address relationships that by nature involve multiple scale processes. Available global data set, advances in spatial techniques and relatively cheap computer storage and computational power allow such analysis to be done, adding value through global comparative analysis of the interesting site-level findings.

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Seminar13 Mar 2013 - Sesion 1 - Analysis of forest-livelihoods nexus global data set by SDewi

  1. 1. Analysis of forest-livelihoods nexus: how can global data set help? Sonya Dewi, Brian Belcher, Atie Puntodewo “Tree cover transitions & investment in multicolored economy” One Day Seminar, March 13 2013, Bogor
  2. 2. Outline• PEN study and dataset• Characterization of the diverse parts of the tropics• Extrapolation domain of large scale, comparative studies• Multilevel analysis of relationships of livelihoods and forests
  3. 3. ABOUT PEN STUDY
  4. 4. The PENis a…set PEN data• Large (360 villages, 10,000+ households)• pan-tropical (25 countries, 3 regions)• collection of detailed and (intended) high-quality data by• 38 PhD student partners on the• poverty-forest (environment) nexus at the household level,Aim: produce the most comprehensive (breadth and depth) analysis of poverty-forest links
  5. 5. CHARACTERIZATION OF THEDIVERSE PARTS OF THE TROPICS
  6. 6. Global datasetSpatial analysis of global maps clipped for the tropics only:• Global land cover: JRC, 2006. The Global Land Cover 2006• Ecoregion: WWF, 2005. WWF Terrestrial Ecoregions• Population density: CIESIN, 2005. Estimated Population Density 2005 from Gridded population of the World (GPW) version 2• Settlement locations: World Gazeteer – population figures for cities, places, regions, countries (http://world-gazeteer.com/)• Roads: DMA, 2006. Digital Chart of the World, Roads• Protected areas: UNEP, 2010. World Database on Protected Areas (WDPA)• Elevation: GTOPO30• Watersheds: WWF Conservation Science Program, 2009. Hydrological basins derived from HydroSHEDS.
  7. 7. Ecosystem Scale 1:10,000,000Source: WWF, 2005. WWF TerrestrialEcoregions
  8. 8. Ecosystem: Area and Population
  9. 9. How much is protected?100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% Inside PA 10 -100 km 1 - 10 km > 100 km < 1 km
  10. 10. How much is forested?
  11. 11. Forest configurationMillions 1,800 1,600 1,400 1,200 1,000 800 600 400 200 0 Forest Mosaics Forest Edge Forest Core Non-forest
  12. 12. EXTRAPOLATION DOMAIN
  13. 13. Sub-basin: typology (FT)
  14. 14. % Medium Broadleaved forest% Open broadleaved forest% Mixed tree cover
  15. 15. Proportion of Area Of PopulationDominant Ecosystem FT1 FT2 FT3 FT4 FT5 FT6Tropical and subtropicalmoist broadleaf forests 0.074 0.1077 0.152 0.0025 0.022 0.076Tropical and subtropical drybroadleaf forests 0.002 0.0051 0.0128 0.0143 0.0443 0.0386Tropical and subtropicalgrasslands, savannas, andshrublands 0.0204 0.1095 0.0763 0.0719 0.0086 0.0572Tropical and subtropicalconiferous forests 0.0003 0.0004 0.0009 0.0005 0.0003 0.0004Montane grasslands 0.0024 0.0006 0.0034 0.0013 0.004 0.0012Flooded grasslands 0.0001 0.0012 0 0 0 0Mangroves 0.0001 0.0008 0 0 0 0.0006Deserts and xericshrublands 0.0001 0.001 0 0.0038 0.0022 0.0642Total 0.0994 0.2263 0.2455 0.0943 0.0815 0.2383Number of PEN villages • In area under earlier FTDominant EcosystemTropical and subtropical FC 1 FC 2 FC 3 FC 4 FC 5 FC 6 Total stages for moistmoist broadleaf forests 83 21 34 5 28 171Tropical and subtropicaldry broadleaf forests 9 7 16 broadleaf forestTropical and subtropicalgrasslands, savannas, and • Livelihoods in tropicalshrublands 2 27 16 65 5 115Tropical and subtropicalconiferous forests 10 10 and subtropical dryMontane grasslandsDeserts and xeric 6 6 broadleaved forest areshrublands 2 2Outside the tropics 13 not much capturedTotal 85 48 60 80 10 37 333
  16. 16. MULTILEVEL ANALYSIS OFRELATIONSHIPS OF LIVELIHOODS ANDFORESTS
  17. 17. - Multi-level o Hh characteristics o Resource base o Access to market o Access to resources o … - Policies should address multiple- level issues
  18. 18. Coeff Signif. Coeff Signif.Total income (ln) Watershed-level variablesIntercept 0.805 Dry broadleaved forestHousehold-level variables compared to Moist broadleaved Members -0.159 ** forest -0.356 ** Age of head -0.003 ** Grassland, savanna, shrubland -0.747 ** Number of adults eq 0.162 ** Coniferous forest 0.733 ** Female headed -0.235 ** Montane grassland -0.737 * Percent of forest land managed -0.001 Desert and xeric shrubland -1.240 ** Percent of agricultural land Distance to core forest 0.154 ** managed -0.04 % Core forest 1.125 ** Total land (ln ha) 0.183 ** Mean Population dens 0.632 ** Herfindahl index (diversity of FT x dry broadleaved forest -0.077 source of income) ** FT x grassland, savanna,Village-level variables shrubland -0.217 ** Road density 0.443 ** FT x coniferous forest -0.275 ** Population density 2.84 ** FT x montane grassland -0.474 ** Road dens x Population dens -0.298 ** FT x Desert and xeric shrubland -0.133 Distance to Protected Areas 0.079 ** Village x WS-level Sub-montane compared to Population density -0.197 **lowland -0.227 **Montane compared to lowland -0.018 **Sub-alpine compared to lowland -0.675 **Alpine compared to lowland -0.445 **
  19. 19. Global dataset can help …• Providing context to case studies and comparative studies at different scales• Finding the sampling frame and population• Analysis of typologies; finding extrapolation domain• Generating data for multiple and cross-scale analysis, e.g., with multiple level regression analysis
  20. 20. THANK YOU

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