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Identifying tree populations for conservation actions through geospatial analyses Riina Jalonen, Maarten van Zonneveld, Evert Thomas, Hannes Gaisberger, Barbara Vinceti, Hong Lay Thong and Judy Loo Bioversity International Contact: [email protected]

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Jalonen R, van Zonneveld M, Thomas E, Gaisberger H, Vinceti B, Hong LT, Loo J. 2012. Identifying tree populations for conservation action through geospatial analyses. In: Multinational and Transboundary Conservation of Valuable and Endangered Forest Tree Species. Asia and the Pacific Workshop, Guangzhou, China, 5-7 December 2011. IUFRO World Series 30, pp. 98-101 Read more about Bioversity International’s work on forest and tree genetic diversity: http://www.bioversityinternational.org/research-portfolio/forest-tree-genetic-diversity/


  • 1. Identifying tree populations for conservation actions throughgeospatial analysesRiina Jalonen, Maarten van Zonneveld, Evert Thomas,Hannes Gaisberger, Barbara Vinceti, Hong Lay Thongand Judy Loo Bioversity InternationalContact: [email protected]

2. Spatial biodiversity analysesCan help to answer Where are the most diverse or most uniqueresources and why? Are they threatened by land use changes orclimate change? Where should action be taken to most efficientlyconserve diversity or tap useful variation? VisualizationData Field studies Existing records Species distribution modeling can complementThis presentation: Case studies about the uses ofspatial analysis tools on tropical tree species 3. Freely available tools and datasets DIVA-GIS software www.diva-gis.org Special features for analyzing biodiversity data Free spatial data Training manual (Scheldeman & van Zonneveld 2010) w ww.bioversityinternational.org/training/training_materials/gis_ma The Global Biodiversity Information Facility (GBIF) 312,669,756 species records (15 Nov 2011) www.gbif.org WORLDCLIM Current, future and past climate data www.worldclim.org 4. MAPFORGEN - Threat profiles 100 useful tree species of LatinFire risk America and the Caribbean(Jarvis et al. 2010) Data from the GBIF, nationalsystems, herbaria, literature,research groups Species distribution modeling Comparison with threat maps Individual threat profilesAccessibility Main threats Most threatened populationsOil and gas FragmentationAgriculture Proportion of distribution area in protected areasMiningClimate changeInvasive species Threat diagram for Annona cherimola 5. Pinus kesiya climate change threatsPredicted distribution (current) Predicted shifts in distribution (2050)(Species distribution modeling) Van Zonneveld et al. 2009 6. Cherimoya Allelic diversitySouthern Peru high diversityAllelic richness (number of alleles) Cluster analysis Bolivia low but distinctive diversity CHERLA 2009; van Zonneveld et al. 2012 7. Cherimoya Reserve selectionPrinciple ofcomplementarity:Which combination ofreserves best covers theoverall diversity?Bolivia: low but distinctivediversity ranks high inselection CHERLA 2009; van Zonneveld et al. 2012 8. Asian tree species Data availabilityPriority species of APFORGEN (Asia Pacific Forest Genetic Resources Programme)Species Specified CountrieslocationsChukrasia tabularis177Cambodia, China, India, Lao PDR,Malaysia, Thailand, VietnamDipterocarpus227Cambodia, Indonesia, India, Lao PDR,alatusMyanmar, Thailand, VietnamFagraea fragrans 557Cambodia, India, Indonesia, Lao PDR,Malaysia, Thailand, VietnamHopea odorata7 6Cambodia, India, Indonesia, Lao PDR,Myanmar, ThailandPterocarpus995Cambodia, Lao PDR, Myanmar,macrocarpus Thailand, VietnamTectona grandis1 1Philippines Data: GBIF 9. Asian tree species Regional collaborationDependency of the predicted distribution on the number of observations Fagraea fragrans used in the analysis. Data from one country only does not necessarilyresult in good prediction of species distribution even in that country itself. data from one country two countriesthree countriesData: GBIF, WORLDCLIM (Hijmans et al. 2005) Analyses: Maxent (Phillips et al. 2006)