Vocal features used to determine individuality among wild gray wolves (Canis lupus) — Presentation Detail — Celebration of Scholars

Instructions

Student presentations must have a faculty sponsor.

Abstracts must include a title and a description of the research, scholarship, or creative work. The description should be 150-225 words in length and constructed in a format or style appropriate for the presenter’s discipline.

The following points should be addressed within the selected format or style for the abstract:

A clear statement of the problem or question you pursued, or the scholarly goal or creative theme achieved in your work.
A brief comment about the significance or uniqueness of the work.
A clear description of the methods used to achieve the purpose or goals for the work.
A statement of the conclusions, results, outcomes, or recommendations, or if the work is still in progress, the results you expect to report at the event.

Presenter photographs should be head and shoulder shots comparable to passport photos.

Additional Information

More information is available at carthage.edu/celebration-scholars/. The following are members of the Research, Scholarship, and Creativity Committee who are eager to listen to ideas and answer questions:

Jun Wang
Kim Instenes
John Kirk
Nora Nickels
Andrew Pustina
James Ripley

Vocal features used to determine individuality among wild gray wolves (Canis lupus)

Name: Cara Hull
Major: Biology
Hometown: Colby
Faculty Sponsor: Angela Dassow
Other Sponsors:
Type of research: SURE
Funding: SURE

Name: Caitlin McCombe
Major: Biology
Hometown: Cedarburg
Faculty Sponsor: Angela Dassow
Other Sponsors:
Type of research: SURE
Funding: SURE

Abstract

Conservation biologists currently depend on invasive trapping and radio-collaring techniques to study population dynamics of gray wolves (Canis lupus). Previous research has found wolf howls can be used to determine individual identity on high quality recordings from captive animals, offering an opportunity for non-invasive monitoring of packs. In this study, wild wolves were recorded in Central Wisconsin to determine the effectiveness of these features in determining individuality in low quality recordings. We analyzed wolf howls from two adult individuals from separate packs. Using a principle component analysis we determined that the maximum frequency, start frequency, dominant frequency, and end frequency of the calls were highly individualistic, but some overlap across individual identities remained. Through a discriminant function analysis using end frequency and maximum frequency, we were able to separate the individuals with 100% accuracy. During the 2018 field season, we aim to collect more calls from individuals to add into the analysis. These howls will allow us to determine the effectiveness of our method of individual identification by examining how accurately howls from new individuals are classified. Upon completion of future testing, a novel and non-invasive method for monitoring gray wolves will be available for use in wildlife management.

Poster file