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Caution is warranted when using animal space-use and movement to infer behavioral states

Cite this dataset

Buderman, Frances E. et al. (2022). Caution is warranted when using animal space-use and movement to infer behavioral states [Dataset]. Dryad. https://doi.org/10.5061/dryad.mgqnk98zz

Abstract

Background: Identifying the behavioral state for wild animals that can’t be directly observed is of growing interest to the ecological community. Advances in telemetry technology and statistical methodologies allow researchers to use space-use and movement metrics to infer the underlying, latent, behavioral state of an animal without direct observations. For example, researchers studying ungulate ecology have started using these methods to quantify behaviors related to mating strategies. However, little work has been done to determine if assumed behaviors inferred from movement and space-use patterns correspond to actual behaviors of individuals.

Methods: Using a dataset with male and female white-tailed deer location data, we evaluated the ability of these two methods to correctly identify male-female interaction events (MFIEs). We identified MFIEs using the proximity of their locations in space as indicators of when mating could have occurred. We then tested the ability of utilization distributions (UDs) and hidden Markov models (HMMs) rendered with single sex location data to identify these events.

Results: For white-tailed deer, male and female space-use and movement behavior did not vary consistently when with a potential mate. There was no evidence that a probability contour threshold based on UD volume applied to an individual’s UD could be used to identify MFIEs. Additionally, HMMs were unable to identify MFIEs, as single MFIEs were often split across multiple states and the primary state of each MFIE was not consistent across events.

Conclusions: Caution is warranted when interpreting behavioral insights rendered from statistical models applied to location data, particularly when there is no form of validation data. For these models to detect latent behaviors, the individual needs to exhibit a consistently different type of space-use and movement when engaged in the behavior. Unvalidated assumptions about that relationship may lead to incorrect inference about mating strategies or other behaviors.

Usage notes

wtd_mf_interactions.RData

Hidden Markov model state identification and utilization distribution values for male-female interaction events identified from collared white-tailed deer in Pennsylvania, USA, from 2013-2016. Guide to object name notation: HMM = hidden Markov model state, UD = utilzation distribution values, males = male white-tailed deer, females = female white-tailed deer, liberal = event identified using proximity, conservative = event identified using proximity and cohesion, rut = full rut period, rutseasons = rut split into early, peak, and late seasons.

Funding

Pennsylvania Game Commission, Award: 1434-03HQRU1548, Research Project No. 30

Pennsylvania Department of Conservation and Natural Resources, Award: 4400015622

National Institute of Food and Agriculture, Award: Hatch 1024904