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Reconstructing bioclimatic variables from remote sensing data sets

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.

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

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

Our lab also developed PaleoClim, a free database of downscaled paleoclimate outputs at 2.5-minute resolution (~5 km at equator) that includes surface temperature and precipitation estimates using HadCM3, a version of the UK Met Office Hadley Centre General Circulation Model. With them, our goal was to contribute to integrative studies of the impacts of climate change in the Early Pleistocene and Pliocene – periods in which recent speciation events are known to concentrate. Time periods available include the Marine Isotope Stage 19 (MIS19) in the Pleistocene (~787 ka), the mid-Pliocene Warm Period (~3.264–3.025 Ma), and MIS M2 in the Late Pliocene (~3.3 Ma).

This project was facilitated by the University of Leeds International Research Collaboration Award to Alan M. Haywood.
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