Changes in movement, habitat use, and response to human disturbance accompany parturition events in bighorn sheep (Ovis canadensis)

Abstract

Parturition and the early neonatal period are critical life history stages in ungulates with considerable implications for population growth and persistence. Understanding the changes in behaviour induced by ungulate parturition is important for supporting effective population management, but reliably identifying birth sites and dates presents a challenge for managers. Rocky Mountain bighorn sheep (Ovis canadensis canadensis) are one such highly valued and ecologically important species in montane and subalpine ecosystems of Western North America. In the face of changing patterns of anthropogenic land use, wildlife managers increasingly require site-specific knowledge of the movement and habitat selection characteristics of periparturient sheep to better inform land use planning initiatives and ensure adequate protections for lambing habitat. We used movement data from GPS collared parturient (n = 13) and non-parturient (n = 8) bighorn sheep in Banff National Park, Canada to (1) identify lambing events based on changes in key movement metrics, and (2) investigate how resource selection and responses to human use change during the periparturient period. We fit a hidden Markov model (HMM) to a multivariate characterization of sheep movement (step length, daily home range area, residence time) to predict realistic lambing dates for the animals in our study system. Leave-one-out cross validation of our model resulted in a 93% success rate for parturient females. Our model, which we parameterized using data from known parturient females, also predicted lambing events in 25% of known non-parturient ewes in a test dataset. Using a latent selection difference function and resource selection functions, we tested for postpartum changes in habitat use, as well as seasonal differences in habitat selection. Immediately following lambing, ewes preferentially selected high-elevation sites on solar aspects that were more rugged, closer to escape terrain, and further from roads. Within-home range habitat selection was similar between individuals in different reproductive states, but parturient ewes had stronger selection for low snow depth, sites closer to barren ground, and sites further from trails. We propose that movement-based approaches such as HMMs are a valuable tool for identifying critical parturition habitat in species with complex movement patterns and may have particular utility in study areas without access to extensive field observations or vaginal implant transmitters. Furthermore, our results suggest that managers should minimize human disturbance in lambing areas to avoid interfering with maternal behaviour and ensure access to a broad range of suitable habitat in the periparturient period.

Keywords: Bighorn sheep; Conservation; Hidden Markov; Lambing; Ovis canadensis; Parturition; Resource selection; Wildlife management.

Fig. 1

Summer home range of the 24 collared female bighorn sheep in our study and relevant human infrastructure. Home range was calculated from a 95% minimum convex polygon around all GPS locations from May 15–July 15. Red points indicate the locations corresponding to the lambing dates inferred for parturient ewes using a hidden Markov model

Fig. 2

Estimated a posteriori hidden states (using the Viterbi algorithm) of B05-2020 based on a hidden Markov model fit to three response variables: step length, residence time, and day home range. The red hidden state corresponds to the ‘non-movement’ latent state associated with parturition, the grey state corresponds to the ‘low-movement’ latent state, and the white state corresponds to the ‘high-movement’ latent state. Day home range has been truncated at 100 Ha to improve scale. Using our decision rule, we identified a lambing date of May 20, 2020 (red line) which matched the lambing date estimated from field observations

Fig. 3

GPS-collar locations of ewe B05-2020 fifteen days before and after the lambing date inferred by a hidden Markov model (May 20, 2022), beginning and ending at the green circle and red square, respectively. The lambing date corresponded to a two-day (approx.) cluster of collar fixes within a small radius

Fig. 4

Aggregate movement trends for parturient bighorn sheep, aligned by inferred lambing date. Displayed values are the mean value of daily average movement metrics. Grey envelopes represent 95% confidence intervals. Generally, lambing events were preceded by an increase in home range and followed by a large reduction in movement rate for a period less than two days long

Fig. 5

Movement metrics and estimated a posteriori hidden states (using the Viterbi algorithm) of B08-2022 (non-parturient) based on our trained hidden Markov model. The grey state corresponds to the ‘low-movement’ latent state, and the white state corresponds to the ‘high-movement’ latent state. No time was spent in the “non-movement” behavioural state associated with parturition. Day home range has been truncated at 100 Ha to improve scale. We did not identify a lambing date, which matched expectations from field observations

Fig. 6

Coefficient estimates for each landscape covariate in a mixed-effect latent selection difference function modelling habitat use 15 days before and after the lambing dates inferred for parturient bighorn sheep ewes (n = 13). A random intercept was included in the model for each animal. Error bars are given as 95% confidence intervals. Positive values of relative usage for a “Distance to…” covariate imply selection for sites with a greater distance (i.e., further) from that landscape feature

Fig. 7

Selection coefficient estimates for each landscape covariate in use-availability resource selection functions modelling seasonal habitat selection (May 15–July 15) in parturient and non-parturient bighorn sheep ewes. A separate RSF was fit for each reproductive status. A random intercept was included for each animal in the models. Error bars are given as 95% confidence intervals. Positive values of relative usage for a “Distance to…” covariate imply selection for sites with a greater distance (i.e., further) from that landscape feature