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Use of biodiversity modelling in environmental conservation - a case study Marinez Ferreira de Siqueira Giselda Durigan Mauro Muñoz Fabrício Pavarin A.

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Presentation on theme: "Use of biodiversity modelling in environmental conservation - a case study Marinez Ferreira de Siqueira Giselda Durigan Mauro Muñoz Fabrício Pavarin A."— Presentation transcript:

1 Use of biodiversity modelling in environmental conservation - a case study Marinez Ferreira de Siqueira Giselda Durigan Mauro Muñoz Fabrício Pavarin A. Townsend Peterson

2 Use of biodiversity modelling in environmental conservation - a case study CRIA is working on the development of predictive geographic distribution models of trees in areas where the original vegetation is very fragmented or has been completely destroyed. We are testing the use of modeling tools to help in biodiversity conservation studies. Environmental data with good resolution together with precise data on species occurrence is fundamental OBJECTIVE: TO PRODUCE DETAILED AND ACCURATE PREDICTIVE MAPS OF GEOGRAPHIC DISTRIBUTIONS OF SPECIES OF INTEREST FOR CONSERVATION

3 Aspidosperma cylindrocarpon Müll. Arg. (Apocynaceae) Data points come from Species Link (http://splink.cria.org.br/simple_search) and the geographic coordinates of points were obtained using geoLoc (http://splink.cria.org.br/geoloc)http://splink.cria.org.br/simple_search Climate IPCC - Intergovernmental Panel on Climate Change (1961-1990) http://www.ipcc.ch CIAT (Jones, 1991 in http://www.floramap- ciat.org/ing/climate- grid.htm) Resolution: 0,17º (10). Worldclim Version 1.1 Global Climate Surfaces (obtained courtesy of Robert Hijmans) Resolution: 0,0083333o. (a square kilometer grid) source: Dr Ingrid Koch Topography U.S. Geological Surveys Hydro-1K, resolution: 0.01º (http://edcdaac.usgs.gov/gtopo30/hydro) Layers: elevation, slope, aspect, and topographic index (tendency to pool water) Soil IAC – 1:500.000 Modelling biodiversity for São Paulo State

4 Soil Map - Brazil Scale: Brazil: 1: 5.000.000 – source: LBA IBGE 1981

5 Scale: Brazil: 1: 5.000.000 – source: IBGE 1981 São Paulo: 1:500.000 – source IAC 1999 Watershed of Médio Paranapanema: 1:250.000 – source IAC 1996 Soil Map of Brazil, São Paulo State and Watershed of Médio Paranapanema

6 Use of biodiversity modelling in environmental conservation - a case study Data completely available on SinBiota and SpeciesLinK projects (CRIA Fapesp) Xylopia aromatica (Annonaceae)Environmental data: soil, geology, temperature, precipitation Blue: present points for Xylopia Red: absence points for Xylopia Green: probable absence points for Xylopia

7 Use of biodiversity modelling in environmental conservation - a case study Summary of species richness (19 species) Areas of maximal species richness Area with great probability of occurrence of all species

8 Use of biodiversity modelling in environmental conservation - a case study Map: erosion risk Intersection between areas with great risk of erosion and greater probability of species occurence Areas with great risk of erosion

9 Casearia sylvestris Copaifera langsdorffii Croton floribundus Gochnatia polymorpha Luehea grandiflora Machaerium acutifolium Machaerium brasiliense Matayba elaeagnoides Ocotea corymbosa Pera obovata Platypodium elegans Siparuna guianensis Stryphnodendron obovatum Syagrus romanzoffiana Tabebuia ochracea Tabernamontana hystrix Tapirira guianensis Terminalia glabrescens Vochysia tucanorum Use of biodiversity modelling in environmental conservation - a case study Species list based on the greater probability of species occurence

10 Use of biodiversity modelling in environmental conservation - a case study Data completely available on SinBiota and SpeciesLinK projects (CRIA Fapesp) Xylopia aromatica (Annonaceae)Environmental data: soil, geology, temperature, precipitation

11 Xylopia aromatica (Annonaceae) Multitemporal NDVI (greenness) Source: AVHRR satellite Resolution: 1Km 1 month composition Use of biodiversity modelling in environmental conservation - a case study Blue: present points for Xylopia Yellow: absence points for Xylopia Source: EROS Data Center

12 Conclusions And we need to develop and automate these methodologies to make broad application more feasible. To do that properly we need more and better environmental data such as the remotely sensed data shown earlier. Using these tools, a methodology is being developed to help identify key areas representing concentrations of native species, which can be used in planning for habitat restoration. marinez@cria.org.br THANK YOU!!


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