Poster Session #1: UC Ballroom

Photos and Phenotypes: Using Camera Traps to Monitor Seasonal Mismatch Between Snowshoe Hares (Lepus americanus) Coat Color Change and Snow Cover

Presentation Type

Poster

Faculty Mentor’s Full Name

L. Scott Mills

Faculty Mentor’s Department

Wildlife Biology

Abstract / Artist's Statement

Snowshoe hares biannually change coat color to match the landscape. They depend on this photoperiod-cued change to hide from predators. With climate change affecting snowfall patterns, hares are at risk of higher predation. This issue is the subject of a long-term study.

The project uses traditional methods--field technicians, live trapping, and telemetry--to collect data. These methods are constrained by access, weather, daylight, and other limiting factors. Using camera trap images, I have developed a new data collection protocol that addresses these constraints After analyzing 3,400 photos to date, I have found that photo data can provide relevant, accurate, and detailed information. It would provide an easy and cost-efficient way to supplement traditionally-gathered data.

My thesis has grown to include four stages. The initial project was developing a novel and noninvasive way to track the hares’ seasonal coat color changes. Now I am applying my protocol to a 10,000 image database. The photos are donated by-catch from unrelated research projects (a lynx survey, wolf project, and general biodiversity study).

Already I have confirmed, developed, and applied my method. I was able to fine-tune my protocol as to maximize efficiency. Now I am continuing the application on a grand scale: 10,000 images from five different locations in the United States and Canada.

The remaining analysis will be complete by 31 July. With the resulting dataset, I can statistically plot correlations, looking for trends and differences between locations, at different elevations, and across the latitudinal gradient.

This camera-based method can be modified and applied to any species that changes appearance over time. As such, it can be used to monitor a number of species across the planet. Such a development would open many doors in wildlife research.

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Apr 12th, 11:00 AM Apr 12th, 12:00 PM

Photos and Phenotypes: Using Camera Traps to Monitor Seasonal Mismatch Between Snowshoe Hares (Lepus americanus) Coat Color Change and Snow Cover

UC Ballroom

Snowshoe hares biannually change coat color to match the landscape. They depend on this photoperiod-cued change to hide from predators. With climate change affecting snowfall patterns, hares are at risk of higher predation. This issue is the subject of a long-term study.

The project uses traditional methods--field technicians, live trapping, and telemetry--to collect data. These methods are constrained by access, weather, daylight, and other limiting factors. Using camera trap images, I have developed a new data collection protocol that addresses these constraints After analyzing 3,400 photos to date, I have found that photo data can provide relevant, accurate, and detailed information. It would provide an easy and cost-efficient way to supplement traditionally-gathered data.

My thesis has grown to include four stages. The initial project was developing a novel and noninvasive way to track the hares’ seasonal coat color changes. Now I am applying my protocol to a 10,000 image database. The photos are donated by-catch from unrelated research projects (a lynx survey, wolf project, and general biodiversity study).

Already I have confirmed, developed, and applied my method. I was able to fine-tune my protocol as to maximize efficiency. Now I am continuing the application on a grand scale: 10,000 images from five different locations in the United States and Canada.

The remaining analysis will be complete by 31 July. With the resulting dataset, I can statistically plot correlations, looking for trends and differences between locations, at different elevations, and across the latitudinal gradient.

This camera-based method can be modified and applied to any species that changes appearance over time. As such, it can be used to monitor a number of species across the planet. Such a development would open many doors in wildlife research.