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Quantitative Bioscience at the University of Tennessee

Quantitative Ecology/Ethnoecology

Ecosystem image.

Quantitative ecology/ethnoecology draws upon environmental science, agricultural sciences, research methodology, and biometrics to study how humans understand and interact with the ecosystems around them. The discipline applies biomathematics, environmental informatics, and biostatistical methods in the life and environmental sciences to data collection, data analysis, modeling, monitoring, evaluation, and data communication. A quantitative approach has great significance in ecology and ethnoecology where large quantities of observation, measurement, experiment, or literature data are available to describe and understand complex systems, processes, or phenomena.

Researcher Department Research Interests
P. Armsworth photo. Paul Armsworth
Email
Ecology & Evolutionary Biology Applications of mathematical modeling, statistics and optimization to inform conservation of biodiversity and the management of ecosystem services
 photo. Michael J. Blum
Email
Ecology & Evolutionary Biology Aquatic ecology, socioecology, sustainability, conservation biology
O. Gaoue. Orou Gaoue
Email
Ecology & Evolutionary Biology Conservation biology, demography, plant-human interactions
X. Giam. Xingli Giam
Email
Ecology & Evolutionary Biology Conservation ecology, global environmental change
L. Gross. Louis Gross
Email
Ecology & Evolutionary Biology; Mathematics Mathematical ecology. Director, NIMBioS; Director, The Institute for Environmental Modeling (TIEM)
M. Papes. Monica Papeş
Email
Ecology & Evolutionary Biology; Director, Spatial Analysis Lab Ecological niche modeling, conservation science, GIS and remote sensing



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From 2008 until early 2021, NIMBioS was supported by the National Science Foundation through NSF Award #DBI-1300426, with additional support from The University of Tennessee, Knoxville. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation.
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