Elie Gurarie

Eliezer (Elie) Gurarie

Quantitative Ecologist

Faculty Specialist

Department of Biology
University of Maryland

Address: 3237 Biology-Psychology Building
University of Maryland
College Park, MD 20742
Affiliations:School of Environmental and Forest Science
Professional and Continuing Education
University of Washington, Seattle - Seattle, WA 98195
Ph.D: QERM , University of Washington, 2008


| Research | Teaching | Publications | Background | Links | CV |


Research Interests^

I am a quantitative ecologist interested in exploring various aspects of movement, abundance, survival and behavior of animals, both aquatic and terrestrial. I apply statistical and mathematical tools to explore behavioral complexity in movement data, responses to environmental cues, memory effects, and to model encounter rates. I try to develop theory on one side, inform analysis of data on the other, and bring the two together whenever possible.

I have worked on a variety of animals (mostly in cold places), including Pacific salmon, Steller sea lions in Russia, motile algae in a lab, wolves, reindeer and moose in Finland, Antarctic seals, invasive sea lamprey in the Great Lakes. Lately, research projects have also included management of invasive willow in Australia, large-scale phenological data from Russian boreal forests, and Giant Panda reintroductions to wildlife reserves in Sichuan, China

I have ongoing collaborations with the National Marine Mammal Laboratory, (NOAA Fisheries), the Finnish Fish and Game Research Institute, the Centre of Excellence for Environmental Decisions in Australia, the Fondazione Edmund Mach in the Italian alps, the Smithsonian Conservation Biology Institute in northern Virginia, with the Chengdu Institude of Biology and China West Normal University and other fun and inspiring colleagues worldwide.

My home is in the lab of Dr. Bill Fagan at the University of Maryland.

Publications^

Below, a list of some of my more favorite ones. A more complete list with links can be accessed here.

Teaching^

I very much enjoy teaching - in particular providing students interested in exploring the natural and human world the quantitative tools to really bring out the underlying structure in the ever growing soup of data. Or something like that.

Background^

For a cv that was almost surely up-to-date once upon a time, click here.

Some links^

(updated August 15, 2016)