Quantitative Ecology Research

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The goals of the Quantitative Ecology Research Program are to develop analytical methods and statistical models that broadly advance our understanding of the ecological mechanisms that influence wildlife population dynamics and demographics. Knowing how ecological processes influence key animal outcomes, such as behavior, foraging success, survival, and reproduction, provides vital insights into how and why populations have changed through time, and possibly how they may respond to ecosystem change anticipated in the future. Consequently, research products provide essential information to help manage and conserve wildlife populations. Research is often motivated by trust species managed by the U.S. Department of the Interior in Arctic and sub-Arctic habitats, but most research products are directly applicable to other species and ecosystems.

A polar bear walks across rubble ice in the Alaska portion of the southern Beaufort Sea

A polar bear walks across rubble ice in the Alaska portion of the southern Beaufort Sea, April 8, 2011. (Credit: Mike Lockhart, USGS. Public domain.)

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Population models

Research to develop improved mark-recapture models, integrated population models, and similar types of population models is a high priority. These models produce estimates of population vital rates, such as survival and birth or recruitment rates, and abundance that are difficult to obtain in other ways. The resulting estimates provide unique insights into the ecological factors that shape population dynamics and demographics, and are critical inputs for modeling population status into the future. Techniques to incorporate differences between individual animals with respect to behavior, habitat utilization, health, reproduction, and survival into model structure are of particular interest. Improved methods to incorporate multiple types and sources of data and evaluate model performance and reliability are also of interest.

 

Biotracer models in ecology

The use of “biotracers” such as fatty acids, stable isotopes, and genetics can provide informative and sometimes unique insights into numerous aspects of animal ecology. For that reason, research to study the performance of existing models and develop improved models has been a recent priority. This research is challenging because observed data are often dependent on processes which are difficult to quantify, particularly the health, metabolism, and physiology of free-ranging animals, as well as temporal and spatial variation in the data sources. Because of climate-induced change in the pathways of energy and nutrient flow, and the importance of lipids in Arctic ecosystems, the estimation of diet composition based on fatty acid data has been a recent focus. Research into genetic population mixture models has also been a priority, and a publication describing a new genetic mixture model, with application to Yukon River Chinook salmon ecology and implications for fishery management, received the 2012 Stevan Phelps Award from the American Fisheries Society.

 

Polar bear still hunting at a seal breathing hole

Polar bear still hunting at a seal breathing hole.
(Credit: Mike Lockhart, USGS. Public domain.)

Polar bear population dynamics

Research to develop more effective models of polar bear population dynamics is motivated by observed and projected reductions in the spatial and temporal extent of the Arctic sea ice habitat upon which they depend. Historically, most polar bear population assessments have been based on distance sampling or relatively simple mark-recapture models. Those methods have certainly been useful, but more general modeling frameworks offer numerous advantages and are necessary to accommodate relatively recent habitat-driven changes in polar bear behavior and ecology into population models. Our research is focused on the southern Beaufort Sea population, on which USGS maintains long-term research, providing population assessments necessary for the conservation and management of the population.