FINE-SCALE MOVEMENT AND SPACE USE OF BEAVERS IN SOUTHERN ILLINOIS

Author

John Brooks Pitman III, Southern Illinois University CarbondaleFollow

Date of Award

5-1-2023

Degree Name

Master of Science

Department

Zoology

First Advisor

Bastille-Rousseau, Guillaume

Abstract

Movement is a core mechanism through which animals interact with their environment. A popular approach for investigating animal movement involves the use of GPS telemetry, which provides insights into both the spatial and temporal patterns exhibited by an individual or population. While many approaches for evaluating movement data have often analyzed intensity of use, most studies focused on a single property of use: the total duration an animal spent in a location. While this can provide insight into which landscape and habitat characteristics an individual may be selecting for, it does not fully account for how that space is being used. Therefore, it could be beneficial to combine more than one aspect of intensity of use to evaluate the behavioral mechanisms leading to patterns in space use, and by extension the drivers of home range structuring. As a territorial, central-place forager, the North American beaver (Castor canadensis) presents an ideal system for investigating drivers of home range structuring. However, while some species are easily tracked through traditional GPS attachment methods (such as GPS collars or backpacks), other species such as beavers present unique challenges given their fusiform shape and tapered neck. The overall objective of my thesis was to better understand fine-scale movement of beavers and the drivers of home range structuring. To do so, in chapter 1, I first developed and tested three different GPS transmitter attachment methods to determine which was most effective in terms of retention time (RT, total number of days a transmitter remains attached) and GPS fix success rate (FSR, % of successful fixes vs. attempted) and investigated to what degree various factors (season, sex, and age class) affected these results. In chapter 2, I analyzed space use in relation to four intensity of use metrics with machine learning to define homogenous types of space use. These metrics included the total number of visits, total and mean duration of visits, and mean interval between visits. GPS transmitters glued to the lower back of beavers provided up to two months of fine-scale data, as well as producing the highest FSR. In addition, longer retention times were found for transmitters attached to males versus females, and for transmitters deployed in the fall versus the spring. Using these data, I was able to capture five distinct population level intensity of use types including, low use – irregular, low use – regular, medium use – short duration, medium use – long duration, and lodge use. These types of use were all generally observed towards the core of the home range. In addition, all types of use were characterized by low intervals between visits except for the low use – irregular cluster. These results suggest highly structured, regular movements occurring in the core of beaver home ranges related primarily to shelter, foraging patches, and the movement paths used to link these locations. Overall, this approach allowed me to delineate between two distinct low use and medium use types and provided insight into the different behavioral mechanisms that may be driving these similar types of use. Capturing these different types of use was only possible by specifically combining multiple movement metrics at once to evaluate space use, as opposed to strictly using the number of GPS fixes to evaluate a location.