Movement, resting, and attack behaviors of wild pumas are revealed by tri-axial accelerometer measurements

Movement Ecology

Christopher C Wilmers³  Gabriel Elkaim²  Terrie M Williams¹  Caleb M Bryce¹  Matthew Rutishauser⁴  Barry Nickel³  Yiwei Wang³ 

[1] Ecology and Evolutionary Biology Department, University of California, 1156 High Street, Santa Cruz 95064, CA, USA;Computer Engineering Department, Autonomous Systems Lab, University of California, 1156 High Street, Santa Cruz 95064, CA, USA;Environmental Studies Department, Center for Integrated Spatial Research, University of California, 1156 High Street, Santa Cruz 95064, CA, USA;Wildlife Computers, 8345 154th Ave. NE, Redmond 98052, WA, USA

关键词: Predation;    Random forest;    Behavior;    Accelerometer;    Puma concolor;   

Others  :  1132165
DOI  :  10.1186/s40462-015-0030-0

 received in 2014-10-26, accepted in 2015-01-12,  发布年份 2015

【 摘 要 】

Background

Accelerometers are useful tools for biologists seeking to gain a deeper understanding of the daily behavior of cryptic species. We describe how we used GPS and tri-axial accelerometer (sampling at 64 Hz) collars to monitor behaviors of free-ranging pumas (Puma concolor), which are difficult or impossible to observe in the wild. We attached collars to twelve pumas in the Santa Cruz Mountains, CA from 2010-2012. By implementing Random Forest models, we classified behaviors in wild pumas based on training data from observations and measurements of captive puma behavior.

Results

We applied these models to accelerometer data collected from wild pumas and identified mobile and non-mobile behaviors in captive animals with an accuracy rate greater than 96%. Accuracy remained above 95% even after downsampling our accelerometer data to 16 Hz. We were further able to predict low-acceleration movement behavior (e.g. walking) and high-acceleration movement behavior (e.g. running) with 93.8% and 92% accuracy, respectively. We had difficulty predicting non-movement behaviors such as feeding and grooming due to the small size of our training dataset. Lastly, we used model-predicted and field-verified predation events to quantify acceleration characteristics of puma attacks on large prey.

Conclusion

These results demonstrate that accelerometers are useful tools for classifying the behaviors of cryptic medium and large-sized terrestrial mammals in their natural habitats and can help scientists gain deeper insight into their fine-scale behavioral patterns. We also show how accelerometer measurements can provide novel insights on the energetics and predation behavior of wild animals. Lastly we discuss the conservation implications of identifying these behavioral patterns in free-ranging species as natural and anthropogenic landscape features influence animal energy allocation and habitat use.

【 授权许可】

   
2015 Wang et al.; licensee BioMed Central.

【 图 表 】

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