In this research, species distribution modeling is used as a tool to understand the environmental determinants that control the distribution of species and to obtain spatial patterns on the species’ distribution. Current projects include evaluating the usefulness of newly available vegetation remote sensing data (e.g., from NASA’s Moderate Imaging Spectroradiometer [MODIS]) in species distributional modeling, understanding the spatial distribution of tree diversity in the Amazon basin, predicting present-day, future, and past distribution of biomes and vertebrates in the diverse Tropical Andes, predicting invasions of savanna reptiles into fragmented rainforests in Cameroon, and modeling the geographic distribution of avian malaria blood parasites throughout African rainforests. In species distributional modeling, also called “bioclimatic envelope modeling,” empirical relationships between observed species distributions and environmental variables are established and, thereafter, projected onto geographic space.
A relatively new research venue involves explaining and predicting genetic and morphological diversity over a landscape using environmental correlates. Species distribution modeling is used as a first step, and statistical relationships between phylogeographic and environmental patterns are determined and projected over the regions where the species of interest is predicted to reside. The results from this project will not only increase our fundamental understanding of evolutionary processes in a spatial context but will also enable decision makers to use this information in developing conservation strategies.
Many of these projects are carried out with NASA-funded grants to the Center for Tropical Research and in collaboration with scientists from NASA’s Jet Propulsion Laboratory.
Thomassen, H. A.; Fuller, T. L.; Asefi-Najafabady, S.; Shiplacoff, J. A.; Mulembakani, P. M.; Blumberg, S.; Johnston, S. C.; Kisalu, N. K.; Kinkela, T. L.; Fair, J. N.; Wolfe, N. D.; Shongo, R. L.; LeBreton, M.; Meyer, H.; Wright, L. L.; Muyembe, J.; Buermann, W.; Okitolonda, E.; Hensley, L. E.; Lloyd-Smith, J. O.; Smith, T. B.; Rimoin, A. W.
Fuller, T. L.; Thomassen, H. A.; Peralvo, M.; Wolfgang, B.; Mila, B.; Kieswetter, C. M.; Jarrin-V, P.; Cameron Devitt, S. E.; Mason, E.; Schweizer, R. M.; Schluneggar, J.; Chan, J.; Wang, O.; Schneider, C. J.; Pollinger, J. P.; Saatchi, S.; Graham, C. H.; Wayne, R. K.; Smith, T. B.
Published Work | 2013 | Proceedings of the Royal Society Biology 280(1763)
Thomassen, H. A.; Fuller, T.; Buermann, W.; Milá, B.; Kieswetter, C.; Jarrín-V, P.; Cameron, S. E.; Mason, E.; Schweizer, R.; Schlunegger, J.; Chan, J.; Wang, O.; Peralvo, M.; Schneider, C. J.; Graham, C. H.; Pollinger, J. P.; Saatchi, S.; Wayne, R. K.; Smith, T. B.
Published Work | 2011 | Evolutionary Applications 4(2), 397–413