Angela Dassow, assistant professor of biology at Carthage College, says wolf vocalization recordings can help monitor pack populations in a less invasive manner.
Professor Angela Dassow received her B.S. degrees in wildlife ecology and entomology from the University of Wisconsin-Madison in 2003. After spending several years as the head preparator and assistant curator of herpetology at a natural history museum, she joined Prof. Michael Coen’s lab and earned her M.S. in zoology in 2010 and Ph.D. in zoology in 2014. She joined the Carthage faculty in 2015.
Prof. Dassow’s research focuses on computational analyses of animal vocalizations, exploring correlates with human linguistic phenomena at the phonetic, morphological, and syntactic levels. This work has centered on understanding the vocal communication systems of wild and captive white-handed gibbons (Hylobates lar); however, she has examined other species as well, ranging across a variety of taxa including cetaceans, bats, canids, and song birds. By combining aspects of ecology, linguistics, computer science, and information theory, we are able to gain new insights into the communicative abilities of white-handed gibbons and demonstrate previously unrecognized complexity and structure in their vocal communication system.
Identifying Individual Gray Wolves Using Howls
What’s in a voice?
Many of us recognize that the individuals we speak with sound different from one another, but we rarely discuss why voices are unique or whether other animals have similar distinctions in their vocalizations.
Building upon previous research, we decided to test whether we could identify distinguishing acoustical properties, such as measures of frequency, duration or amplitude, in wild gray wolf howls. Holly Root-Gutteridge and her colleagues demonstrated that this is possible with captive wolves where the quality of the recordings are high, but our study focused on whether these identifying features are still viable in low-quality recordings in a noisy, wild environment.
With the help of a few Timber Wolf Information Network volunteers, we recorded wolves in central Wisconsin every night for a month. From these recordings, we were able to isolate twenty one howls from two adult wolves. For each howl, six types of frequency measurements and two types of duration measurements were made.
Upon analyzing these acoustical properties, we determined that maximum frequency and end frequency were the most individualistic for wild gray wolves. These findings differ from the captive wolf study which found fundamental frequency and scaled amplitude to be the most individualistic measures. These differences are likely a reflection of signal quality. As signal quality degrades, maximum frequency and end frequency become more useful in individual identification.
With this knowledge we propose a novel and non-invasive method for monitoring wild gray wolf populations which have previously been monitored using invasive trapping and radio-collaring procedures. While vocal identification cannot replace radio-collaring entirely, it is a beneficial and cost-effective way of monitoring individuals for most surveying purposes.