Current Projects

Seattle Coyote Study

Coyotes are a clear “winner” of the Anthropocene. They are thriving in cities throughout North America and continuing to expand their range. What makes them so successful? We have launched a study of Seattle’s coyote population, in collaboration with the Seattle Urban Carnivore Project. What are coyotes eating? How many of them are there? We seek to answer these questions and more by combining fecal genotyping and metabarcoding of collected scats.

Project website

Funding: National Science Foundation (DEB-2223973), UW Royalty Research Fund, Animal Welfare Institute, Woodland Park Zoo

Student thesis: Sami Kreling (PhD)

Collaborators: Robert Long (Woodland Park Zoo)

Linking seasonal snow processes to wildlife population dynamics

Seasonal changes in snowpack have a profound influence on the energetics and population dynamics of wildlife that reside in snow-covered regions. The overarching goal of our study is to address the coupled question: What are the key factors driving snow accumulation and ablation during shoulder seasons, and which snow properties are most important for wildlife applications? We hypothesize that fall weather has a disproportionately large impact on snowpack dynamics of relevance to wildlife over the entire snow year. For example, we predict that patterns of temperature and precipitation during fall will have strong and persistent effects on ice layer formation, soil insulation, and annual snow cover duration. We further hypothesize that snow density, icing events, and snow depth will each have distinct and scale-dependent impacts on the movements and population dynamics of ungulates and their predators. To test these hypotheses, we are using snow modeling, remote sensing, and data assimilation at multiple spatial and temporal scales coupled with large datasets of ungulate and carnivore GPS locations, snow track measurements, and population-level metrics in northwestern North America. This project builds directly from the NASA ABoVE Dall Sheep Project and the Washington Predator Prey Project to examine impacts of snow properties on Dall sheep, moose, caribou, mule deer, white-tailed deer, elk, wolves, cougars, coyotes, and bobcats. This project will provide new insights into how climate change is likely to alter shoulder season snow properties, and what the implications are for wildlife population dynamics.

Funding: NASA Interdisciplinary Science Program (IDS), NASA Arctic and Boreal Vulnerability Experiment (ABoVE)

Co-PIs: Jessica Lundquist (UW), Mike Durand (OSU), Natalie Boelman (Columbia U), Glen Liston (CSU), Todd Brinkman (UAF)

Staff:  Taylor Ganz (postdoc), Ben Sullender (PhD student)

Project Website

Evaluating camera traps as ground-based remote sensing networks linking snow and wildlife

Changing snow conditions as a result of climate change will have major effects on ecosystems and wildlife. For example, rain-on-snow (ROS) events are increasing in frequency, leading to catastrophic die-offs of northern ungulates by blocking access to forage. Remote sensing data and in-situ observations are the traditional way to capture snow information, but with the increasing use of camera traps, their ability to supplement and verify this data is ready to be further explored. In collaboration with the Norwegian Institute for Nature Research (NINA), we are using an extensive camera trap network (ScandCam) to validate and supplement remotely-sensed MODIS snow cover and freeze-thaw data from the Freeze/Thaw Earth System Data Record (FT-ESDR), a NASA MEaSUREs product. By comparing snow cover, temperature, and precipitation data between camera traps and satellite data from 2011-2019 in Norway and southern Sweden, this project will accomplish three main goals: (1) develop algorithms to automate extraction of snow and rain data from camera photos for satellite data validation at multiple scales; (2) develop a new ROS product, and (3) connect changing snow cover and ROS frequency to changes in wildlife populations. This project will facilitate extraction and public archiving of data from camera trap networks, providing a direct link between remotely-sensed environmental conditions and biodiversity observations to increase the availability of ground-based data for earth science applications.

Funding: NASA Graduate Fellowship, American-Scandinavian Foundation, ERASMUS

PhD student: Katie Breen

Collaborators: Carrie Voyuvich (NASA), John Odden (NINA), Dan Morris (Microsoft AI for Earth)

Effects of human social-ecological patterns on urban carnivore movement and health