Elise Zipkin

Quantitative Ecologist (2008-2013)
US Geological Survey

PhD in Biology (2012)
University of Maryland

MS in Natural Resources (2008)
Cornell University

BS in Mathematics (2003)
University of Michigan

BS in Applied Ecology (2003)
University of Michigan

As a quantitative ecologist, Dr. Elise Zipkin connects the complexities of natural communities with the precision of mathematics to shine light on mysteries in ecology and conservation. Elise and her team develop analytical frameworks to address grand challenges in the study of biodiversity loss and the effects of anthropogenic activities, such as climate change. She harnesses empirical data (big and small) to understand fine and subtle interactions in the natural world, revealing the causes and consequences of species’ declines and biodiversity loss while charting pathways to mitigate and reverse these alarming trends.

Elise has published over 85 peer-reviewed articles and delivered more than 40 invited talks nationally and internationally. Among her honors is being named an Ecological Society of America Early Career Fellow and a Fulbright U.S. Senior Scholar. Elise regularly works with management agencies to translate the results of her research for conservation. She is committed to open, accessible, and reproducible science and to supporting and mentoring the next generation of scientists, natural resource managers, policy makers, and scientific communicators.

Select work

Publications (see publications for a complete list)

Addressing data integration challenges to link ecological processes across scalesFrontiers in Ecology and the Environment (2021)

Changes in climate drive recent monarch butterfly dynamicsNature Ecology and Evolution (2021)

Tropical snake diversity collapses after widespread amphibian lossScience (2020)

Multiscale seasonal factors drive the size of winter monarch coloniesProceedings of the National Academy of Sciences (2019)

Synthesizing multiple data types for biological conservation using integrated populations modelsBiological Conservation (2018)

Funded projects

Estimating and forecasting nonstationary, multi-scale climate and land-use effects on avian communities – NSF Division of Environmental Biology (2023-2028)

Evaluating the role of climate on Midwestern butterfly trajectories, monarch declines, and the broader “insect apocalypse” – USGS Midwest Climate Adaptation Science Center (2021-2024)

A generalized modeling framework for integrating multi-species data sources to estimate biodiversity processes – NSF Division of Biological Infrastructure (2020-2024)

A multi-scale framework to quantify and forecast population changes and associated uncertainties – Macrosystems Biology: Early Career Award, NSF Division of Environmental Biology (2017-2021)

Modeling seabird dynamics for the Gulf of Mexico Marine Assessment Program for Protected Species (GoMMAPPS) – US Fish and Wildlife Service (2017-2021)


Print: ForbesPopular ScienceNew ScientistSmithsonian MagazineThe Atlantic, National Geographic, BBC, Scientific American, Science Daily, UPI, Futurity

Radio: WABE Atlanta NPR, KCBS San Francisco Radio, Michigan Radio NPRDetroit Today

Invited talks

Why are monarch butterflies declining? – National Academy of Sciences Distinctive Voices (2022)

Using data integration to evaluate ecological processes across scales – Euring Analytical Meeting & Workshop (2021)  *Plenary speaker

Tales from the crypt: Stories of research successes (and a few failures) at the nexus of statistical ecology and biological conservation The U.K. National Centre for Statistical Ecology Meeting (2021)  *Plenary speaker

Combining multiple data sets to improve scientific inference: Overview and synthesis – American Fisheries Society & The Wildlife Society Joint Conference (2019)

Quantifying uncertainty in forecasts of animal populations – Ecological Society of America Annual Meeting (2019)

What are community models and how can they help with biodiversity analyses? – Wildlife Society Annual Conference (2018)

Expanding the scope of biodiversity modeling through data integration – Opening Symposium for the Max Planck-Yale Center for Biodiversity, Movement, and Global Change (2018)  *Keynote speaker


IBIO 860 – Modern Statistical Models in Ecology

This advanced graduate level course provides an introduction to modern statistical models used in the analysis of population and community dynamics in ecology. The class covers some theory but primarily focuses on practical applications including model development and analysis using the programs R and JAGS. The first third of the class reviews (generalized) linear (mixed) models and their use in ecology. The remainder of the course explores more advanced topics including state-space models, mark-recapture models, binomial mixture models for estimating population abundance and demographic rates from count data, occupancy models for the analysis of species distributions, and integrated population models.

This class is generally taught every other spring. See the syllabus for more information.