Thomas Gillespie

Research Interests

My past research interests have focused on using geographic information systems (GIS) and remote sensing data for predicting patterns of species richness and rarity for plants and birds at a regional spatial scale.

Subfields

Biogeography, Forest Ecosystems, Remote Sensing

Biodiversity Research

My botanical research will continue to focus on surveying tropical dry forests in biodiversity hotspots. I have collected floristic data from Wallacea, Sundaland, Indo-Burma, Mesoamerica, New Caledonia, and Caribbean hotspots and within four years, I will collect data from a number of other tropical dry forests in biodiversity hotspots. This research is field intensive and taxonomically challenging but provides comparative floristic and structural data for regions where relatively little information exists. This research will result in a number of publications on global conservation priorities, natural resource management, and tropical ecology and will be used as ground truth data for remote sensing studies of anthropogenic disturbance and estimates of forest biomass.

My faunal research has focused predominately on tropical bird communities, but I have published papers on mammal and herpetofauna diversity. My long-term research agenda for fauna will focus primarily on combining detailed natural history and field data with remote sensing data to model species distributions and probability of extinction in fragmented landscapes. Models of species distributions will also be examined for a number of environmental change scenarios to predict the future distribution of species.

Remote Sensing Research

My remote sensing research is divided into airborne and spaceborne sensors that can be used to measure and monitor terrestrial vegetation. My spaceborne sensor research focuses specifically on high-resolution data from Landsat and IKONOS satellites to test hypotheses on the utility of these sensors for predicting floristic composition and structure in fragmented landscapes and to develop new algorithms that predict the distribution and abundance of endangered species. Advances in geographic information systems and remote sensing techniques have resulted in a number of landscape metrics and indices that may be used to predict the distribution of species richness in habitat fragments. I am currently testing the utility and accuracy of landscape metrics and remote sensing indices for predicting patterns of woody plant species richness and rarity in tropical dry forests of south Florida and Oceania. In particular, I focus on testing the accuracy of landscape metrics within three fragmented systems: anthropogenic fragments, natural habitat fragments, and true islands. The long-term goal is to develop algorithms that predict the distribution of plants and endangered species in other tropical dry forest regions and California ecosystems.

Dr. Gillespie’s interests focus on using geographic information systems (GIS) and remote sensing data for predicting patterns of species richness and rarity for plants and birds at a regional spatial scale.

Selected Publications

Gallerani, E.M., Ostermann-Kelm, S., Williams, C.B., Fricker, G.A., Cavanaugh, K.C. and Gillespie, T.W., 2026. Sensor fusion and downscaled climate projections reveal climate refugia in the California Channel Islands. Scientific Reports.

Cao, Z., Xue, Y., Ye, F. and Gillespie, T.W., 2026. Time-resolved moving‐window machine learning modeling for human‐caused wildfire ignitions from 2001 to 2020 in California. Environmental Research Letters, 21(10), p.104003.

MacDonald, Z.G., Beninde, J., Dupuis, J.R., Gillespie, T.W., Shaffer, H.B. and Grether, G.F., 2026. From Lineage Discovery to Conservation Prioritisation: An Integrative Genomic Framework Applied to a Model Damselfly System. Molecular Ecology, 35(11), p.e70385.

Bueno, A.S., et al. 2026. High-quality surrounding landscapes mitigate avian extirpations from forest remnants. Proceedings of the National Academy of Sciences, 123(14), p.e2521783123.

Gallerani, E.M., Camp, R. J., Banko, P. C., Madson, A., Dong, C., Berio Fortini, L., Ma, Z., and Gillespie, T. W. 2025. Breaking down Palila decline: Assessing the role of drought and vegetation health in the population loss of an endangered Hawaiian Honeycreeper. Global Ecology and Conservation, 62, p.e03831.

MacDonald, Z.G., Schoville, S., Escalona, M., Marimuthu, M.P., Nguyen, O., Chumchim, N., Fairbairn, C.W., Seligmann, W., Toffelmier, E., Gillespie, T. and Shaffer, H.B. 2024. A genome assembly for the Chryxus Arctic (Oeneis chryxus), the highest butterfly in North America. Journal of Heredity, 116 (3), 324-334.

Gallerani, E.M., Williams, A.P., Cavanaugh, K.C., and Gillespie, T.W. 2025. Uncertainties in modeling Hawaii’s future precipitation and what it means for endangered forest birds: A review. Journal of Biogeography, 52(6), e15121.

Dimson, M., Cavanaugh, K. C., von Allmen, E. Burney D. A., Kapua Kawelo, K., Jane Beachy, J., and Gillespie, T.W. 2024. Monitoring native, non-native, and restored tropical dry forest with Landsat: A case study from the Hawaiian Islands. Ecological Informatics, 83, 102821.

Bardou, R., Friess, D.A., Gillespie, T.W., and Cavanaugh, K.C. 2024. Assessing mangrove cover change in Madagascar (1972 to 2019): Widespread mangrove deforestation is slowing down. Global Ecology and Conservation 53, e03022.

Fortini, L.B., Kaiser, L., Daehler, C. Jacobi, J., Dimson, M. and Gillespie, T. 2024. Exploring and integrating differences in niche characteristics across regional and global scales to better understand plant invasions in Hawaiʻi. Biological Invasions 26, 1827-1843.