Massive Birds Species Distribution Modeling using Cloud Computing

Research conducted by Universidade Federal de Pernambuco, in collaboration with Universidade Estadual Paulista Julio de Mesquita Filho (UNESP, Rio Claro) built a hundred thousand maps of endemic bird species distribution for Caatinga Biome. These maps were used as support to produced the 2015 version of the Priority Areas for Conservation, Sustainable Use and Benefit Sharing of Brazilian Biological Diversity. The computer tasks were powered by Microsoft Azure machines, which was funded by Microsoft Research and FAPESP.

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Assessing biodiversity threats in Brazil throughout Azure Cloud computing

Atlantic Forest and Cerrado are the two biomes of São State and both recognized as biodiversity hotspots, due to its high biodiversity and the threats they suffer. The key landscape structure that best explain biodiversity distribution are: spatial arrangement of fragments, edge effect, connectivity, degree of isolation. As deal with very large datasets are highly time demanding, we are using powerful virtual machines (VM) granted by the Microsoft Azure Cloud Computing for Research on the highly complex computational processing.

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Amazon endemic trees under climate changes

Climatic metrics can be good predictors of changes in biodiversity and this can severely impact the majority of endemic species in regions like Amazon. We predicted Amazon threat status in response to climate change for 21 century and evaluated whether climate velocities are as good surrogates to predict biodiversity change as are the climate trajectories. We found that climate trajectories are good predictors for tree´s biodiversity changes. Climate metrics should be good surrogates for changes in biodiversity, although, for a species point of view this association should be valid only for that species that can keep pace with climate change velocity.

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Resampling techniques applied to data analysis of biodiversity in Atlantic Forest

Research conducted by Universidade Estadual Paulista Julio de Mesquita Filho (UNESP, Rio Claro, Brazil, and Texas Tech University, project funded by FAPESP and CNPq) involving ecological modelling to understand multiscalebat community responses to landscape degradation. We built non-linear mixed models and resampled it 10,000 times using bootstrap technique in order to get model selection frequencies and best evaluation of null models. This wasvery time consuming and was achieved using Microsoft Azure machines, important tools to conclude tasks underlying large datasets.

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Cloud computing for modelling ecological corridors

jusilveira_msr_eng_2014_07Ecological corridor has been used as an important strategy for biodiversity maintenance worldwide. Research conducted by São Paulo State University (UNESP, Rio Claro, Brazil) scientists has used highly complex computational processing in the clouds provided by Microsoft Research & FAPESP, in order to assess the best strategies to design ecological corridors for Brazilian Atlantic Forest and Cerrado biodiversity hotspots.

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