Abstract

Topic: Conservation technology

Using biologging technology to study moose behavioral responses to and energetic consequences of human disturbance

Theresa Margret Kirchner¹, Olivier Devineau¹, Marianna Chimienti², Daniel P. Thompson³, Barbara Zimmermann⁴, Alina L. Evans⁴, John Crouse⁵, Ane Eriksen⁴

University of Inland Norway, Department of Forestry and Wildlife Management, Faculty of Applied Sciences and Biotechnology, Anne Evenstads vei 80, 2480 Koppang, Norway
School of Ocean Sciences, Bangor University, Askew St, Menai Bridge LL59 5AB UK
Colorado Parks and Wildlife, 711 Independent Ave., Grand Junction, Colorado
University of Inland Norway, Department of Forestry and Wildlife Management, Faculty of Applied Sciences and Biotechnology, Anne Evenstads vei 80, 2480 Koppang, Norway
Alaska Department of Fish and Game, Kenai Moose Research Center, 43961 Kalifornsky Beach Road, Suite B, Soldotna, AK 99669, USA

Abstract
Background Rapid improvements in biologging technology continuously evolve our understanding of wild animal behavior. Here, we leverage accelerometry, physio-logging and GPS technology to quantify the behavioral and energetic responses of wild moose to encounters with humans engaging in recreational activities. Methods We deployed accelerometer collars and simultaneously conducted behavioral observations on captive Alaskan moose to develop a random forest machine learning model predicting behavior from accelerometer data. We also implanted heart rate loggers in the collared captive moose to develop a generalized additive mixed model predicting movement-based heart rate from accelerometer data. Using an existing equation, we calculated energy expenditure from predicted heart rates. We then applied these models to data from a behavioral response study: We equipped nine wild female moose in Norway with accelerometer-GPS collars and approached the collared moose on foot or snowshoes in summer, fall (hunting season) and winter, simulating common recreational activities in the area. We used our models to quantify changes in behavior and energy expenditure during the approaches compared to controls. Results Our random forest model predicts seven common behaviors from accelerometer data: Lying with head tucked or elevated, ruminating, standing, foraging, walking and running. Our heart rate model predicts increasing heart rate with increasing body movement intensity and overall seasonal variation in heart rate. For our behavioral response study, we conducted 48 approaches with contact (defined as closest observer-moose proximity during an approach) distance ranging between 17-266 m. The main responses were increased locomotor and decreased foraging and ruminating activity concomitant with increased energy expenditure, particularly during the first 10 minutes following contact. Approximately two hours after contact, foraging activity during approaches was comparable to that during controls. Seasonal variation in approach response included stronger flight response following close contact, particularly in summer, with reversed trend in the fall. Conclusions We illustrate the utility of our models in furthering our understanding of fine-scale moose behavior and energy expenditure. We quantify moose behavioral disturbance response and energetic consequences on an unprecedented level of detail and discuss our finding of seasonal variation in disturbance response in the context of hunting activity.