Energetics and fear of humans constrain the spatial ecology of pumas

Abstract

Energetic demands and fear of predators are considered primary factors shaping animal behavior, and both are likely drivers of movement decisions that ultimately determine the spatial ecology of wildlife. Yet energetic constraints on movement imposed by the physical landscape have only been considered separately from those imposed by risk avoidance, limiting our understanding of how short-term movement decisions scale up to affect long-term space use. Here, we integrate the costs of both physical terrain and predation risk into a common currency, energy, and then quantify their effects on the short-term movement and long-term spatial ecology of a large carnivore living in a human-dominated landscape. Using high-resolution GPS and accelerometer data from collared pumas (Puma concolor), we calculated the short-term (i.e., 5-min) energetic costs of navigating both rugged physical terrain and a landscape of risk from humans (major sources of both mortality and fear for our study population). Both the physical and risk landscapes affected puma short-term movement costs, with risk having a relatively greater impact by inducing high-energy but low-efficiency movement behavior. The cumulative effects of short-term movement costs led to reductions of 29% to 68% in daily travel distances and total home range area. For male pumas, long-term patterns of space use were predominantly driven by the energetic costs of human-induced risk. This work demonstrates that, along with physical terrain, predation risk plays a primary role in shaping an animal’s “energy landscape” and suggests that fear of humans may be a major factor affecting wildlife movements worldwide.

Disturbance type and species life history predict mammal responses to humans

“…Despite the loss of natural habitat associated with increasing human footprint, agricultural lands and developed areas nonetheless present opportunities for some species through resource subsidies or relaxed predation/competition (Prugh & Sivy, 2020; Sévêque et al, 2020). Increased human footprint is also associated with decreased movement and smaller home ranges for many mammal species (Doherty et al, 2021; Tucker et al, 2018), including large predators such as pumas (Nickel et al, 2021). Thus, higher intensity of use in more heavily modified habitats by species that otherwise tend to avoid human footprint (e.g., pumas and bobcats, Serieys et al, 2021; Suraci et al, 2020) may reflect restricted movement options and thus intensified use of remaining habitat fragments in moderately developed areas.…”

COVID-19 suppression of human mobility releases mountain lions from a landscape of fear

“…The anthropogenic covariates considered were (i) housing density and (ii) distance to urban edge. Housing density has been shown to be an important driver of puma movement in our study system, 12,14 and impacts movement differently between the day and night (unpublished data). We calculated housing density using Epanechnikov kernels with a 150 m radius [in houses per sq.km], which is the scale at which housing most strongly impacts puma movement.…”

“…As such, human threat creates a landscape of fear whereby mountain lions generally avoid human voices [9][10][11] and habitat close to human infrastructure, 12 resulting in increased energy expenditure by mountain lions, 13 reduced vagility, and smaller home ranges. 14 This landscape of fear also has cascading impacts on mountain lion kill rates of deer, 15 plant architecture, 16 and rodent space use. 17 On March 17, this region initiated a shelter-in-place order (SIPO) in response to the COVID-19 pandemic.…”

“…In all models, we also included topographic and landscape covariates that previous analyses have shown to be important for puma habitat selection in the Santa Cruz Mountains. 12,14,31,32 Specifically, we included topographic slope, topographic position index (TPI, indicating whether a point is mid-slope or on a valley or ridge), the interaction between slope and TPI, distance to nearest perennial river or stream (National Hydrography Dataset, USGS available at https://www.usgs. gov/core-science-systems/ngp/national-hydrography), and percent vegetation cover.…”

Ecological inference using data from accelerometers needs careful protocols

“…The latter has developed rapidly since the demonstration that dynamic body acceleration (DBA) is related to energy expenditure across a range of vertebrates and invertebrates (Halsey et al, 2009; Wilson et al, 2019, 2006). Such measurements have great potential for understanding animal strategies, in particular studying how animals respond to change in food availability (Kokubun et al, 2011), climate (Gudk et al, 2019) and anthropogenic threats or activity (Nickel et al, 2021; Payne et al, 2015; Yorzinski et al, 2015).…”