The ecology of human-caused mortality for a protected large carnivore

Abstract

Mitigating human-caused mortality for large carnivores is a pressing global challenge for wildlife conservation. However, mortality is almost exclusively studied at local (within-population) scales creating a mismatch between our understanding of risk and the spatial extent most relevant to conservation and management of wide-ranging species. Here, we quantified mortality for 590 radio-collared mountain lions statewide across their distribution in California to identify drivers of human-caused mortality and investigate whether human-caused mortality is additive or compensatory. Human-caused mortality, primarily from conflict management and vehicles, exceeded natural mortality despite mountain lions being protected from hunting. Our data indicate that human-caused mortality is additive to natural mortality as population-level survival decreased as a function of increasing human-caused mortality and natural mortality did not decrease with increased human-caused mortality. Mortality risk increased for mountain lions closer to rural development and decreased in areas with higher proportions of citizens voting to support environmental initiatives. Thus, the presence of human infrastructure and variation in the mindset of humans sharing landscapes with mountain lions appear to be primary drivers of risk. We show that human-caused mortality can reduce population-level survival of large carnivores across large spatial scales, even when they are protected from hunting.

Keywords: Puma concolor; additive mortality; compensatory mortality; human–wildlife conflict; survival.

Fig. 1.

Study areas where we monitored survival and mortality of 590 radio-collared mountain lions across California, 1974 to 2020. Mountain lions are sized proportionally to the number of animals tracked.

Fig. 2.

Annual survival (for males and females; A) and cause-specific mortality (B) curves for 590 mountain lions tracked across California, 1974 to 2020. These analyses were done with the full dataset of GPS- and VHF-collared animals. Circles along trend lines in cause-specific mortality curves represent the timing of specific mortality events.

Fig. 3.

Principal components analysis (PCA) plots for landscape features and characteristics of human populations associated with mountain lion (n = 389) GPS telemetry locations across California. Shown are the percentage of variance explained by each dimension (A), contribution to variation in landscape and human populations of first dimensions of PCA (B), a dendrogram identifying 4 clusters of study areas with similar characteristics (C), and a plot showing the 3 main clusters of study areas identified with the PCA (D).

Fig. 4.

Plots showing relationships of overall survival and human-caused mortality (A and B) and natural mortality and human-caused mortality (C and D) across 8 study areas (n = 431 mountain lions) to test the compensatory mortality hypothesis. Shown are data points and regression lines (A and C) generated by drawing 10,000 samples from beta distributions to account for uncertainty in our estimates and regression plots used to estimate mean β and 90% highest posterior density intervals for these relationships (B and D).

Fig. 5.

Hazard ratio plot from the most strongly supported mixed-effects Cox proportional hazards model investigating factors influencing spatially varying mortality risk of GPS-collared mountain lions (n = 389) across the state of California. Hazard ratios above 1 indicate greater mortality risk, whereas those below 1 indicate reduced risk. Variables retained in the model included male (female is reference), distance to low-density development, proportion of voters supporting proenvironmental legislation, and the year (continuous, 2001 to 2020).