1. Geospatial web services applied to Biodiversity Modelling Karla Donato Fook Advisors: Dr. Antônio Miguel V. Monteiro Dr. Gilberto Câmara Collaboration: Dr. Silvana Amaral

2. Biodiversity

3. Species Distribution Modelling Experiment

4. Species Distribution Modelling Geographical Position Occurrence Points Predictive Distribution Species Distribution Model precipitation topography temperature Environmental Variables Algorithm Source: Siqueira (2005)

5. Environmental recovery Contaminated area – before and after recovery work in 2001 Companhia Mineira de Metais (CMM) Três Marias-MG Source: http://cienciahoje.uol.com.br/ controlPanel/materia/view/2419

6. Species conservation Source: Ibama Callicebus Coimbrai & Callicebus barbarabrownae

7. Impacts of climate change Source: http://cedoc.ensp.fiocruz.brhttp://cedoc.ensp.fiocruz.br www.multirio.rj.gov.br / www.meioambiente.uerj.brwww.multirio.rj.gov.br

8. Expansion of invasive species Source: USDA – United States Department of Agriculture / http://www.glerl.noaa.gov/res/projects/multi_stressors/graphics/invasive.jpg

9. Web Biodiversity Collaborative Modelling Services Pelargonium Cordifolium Callicebus Coimbrai & Callicebus barbarabrownae WBCMS Web Biodiversity Collaborative Modelling Services

10. General Objective Support collaboration in a Species Distribution Modelling Network: Sharing modelling

11. Key Concept Model Instance Species Distribution Modelling

12. Model Instance Species Model

13. Model Instance Species Model Metadata +

14. Model Instance Occurrence Environmental Variables Algorithm Model Instance Species Model generation Absence Metadata + Data

15. Model Instance Occurrence Environmental Variables Algorithm Model Instance Species Model generation Absence Metadata + + + + Data

16. Model Instance Occurrence Environmental Variables Algorithm Distribution Map Evaluation Index Model Instance Species Model generation Absence Reports Results Metadata + + + + Data

17. Model Instance Occurrence Environmental Variables Algorithm Distribution Map Evaluation Index Metadata + Model Instance Species Model generation Absence Reports Results Metadata + + + + Data

18. Model Instance Occurrence Environmental Variables Algorithm Distribution Map Evaluation Index Metadata + + Model Instance Species Model generation Absence Reports Results Metadata + + + + Data

19. Provide answers What species are being modelled? Where does the data come from? What are the environmental variables? What are the algorithms? If I have a question, how can I look for similar results?

20. WBCMS Architecture Web Client applications Researcher Model instances Biodiversity Collections WS_2WS_N Map Servers WS_1 Catalogue WBCMS ModelProcessorAccessProcessorCatalogueProcessor

21. WBCMS Architecture Web Client applications Researcher Model instances Biodiversity Collections WS_2WS_N Map Servers WS_1 Catalogue WBCMS ModelProcessorAccessProcessorCatalogueProcessor Client Applications

22. WBCMS Prototype OpenModeller Project

23. Catalogue Client Application OpenModeller modelling result status msg Model Instances WBCMSWBCMS Model Instance Web Services Biodiversity Data Researcher

25. Access Client Application Model Instance Query Reaearcher WBCMSWBCMS Model Instances

35. Species Distribution Maps

36. Final Comments  The conceptual framework of web services supplies a base for development of collaborative environment for species distribution modelling  Our experiments, have demonstrated the viability of the proposals and ideas  WBCMS architecture Allows sharing experiments in a species distribution network Enables researchers to perform new models based in previous ones Allows comparing results

37. Lençóis Maranhenses Thanks ! karla@dpi.inpe.br

38. Catalogue Processor

43. Access Processor

47. Model Processor