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Reconstructing bioclimatic variables from remote sensing data sets

Project funded by City College Seed Grant, with Kyle McDonald (EAS/CUNY and JPL) and Charles Vorosmarty (Crossroads Initiative)

Potential distribution ranges of species can be predicted from environmental surrogates or climatic factors. To date, biologists have been relying on a single major set of global environmental data to delimitate species ranges and project them through space and time. This dataset, also known as the WorldClim database, relies on elevation, temperature, and precipitation data collected from weather stations distributed across the world. Although the WorldClim database has been successfully applied to a suite of ecological and evolutionary research questions, its performance can still be suboptimal.


This project focuses on investigating the use of Earth remote sensing data sets to derive novel bioclimatic data layers relevant to defining ecological niches, and will test the ability of these new measures to improve species distribution models in South America.


First results were published in Methods in Ecology and Evolution!

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