Forest structure and snow depth alter the movement patterns and subsequent expenditures of a forest carnivore, the Pacific marten

Abstract

Energetic balance is central to the survival and persistence of free‐ranging animals. Quantifying expenditures and identifying factors that drive energetics informs our understanding of species' ecology and their responses to shifting environmental conditions. Approaches used to estimate energetic expenditures of free‐ranging species, such as doubly‐labelled water (DLW), are precise but difficult to implement. Global positioning system (GPS) collars and accelerometers have emerged as alternatives for estimating expenditures, but these techniques have few applications in terrestrial species and no applications in small‐bodied (<5 kg) terrestrial animals. Here, we estimated movement characteristics and field metabolic rates (FMR) of Pacific martens Martes caurina, a small‐bodied carnivore with relatively high energetic costs, in a heterogeneous landscape to explore the role of movement and landscape characteristics in energetics. We concurrently used DLW and GPS collars to investigate the relationship between movement characteristics and FMR. Movement velocity explained the greatest amount of variation in mass‐specific FMR and we used this relationship to predict expenditures of previously collared martens. We found that predicted mass‐specific FMR was highest among males and increased in open patches primarily as a result of increased velocity and more erratic movements. Additionally, martens moving through deep snow also exhibited increased FMR. Our work shows movement metrics can effectively explain variation in FMR and identify landscape features, like forest structure and snow depth, that influence movements with cascading effects on energetics for free‐ranging mammals in rapidly changing systems.

Whole‐genome resequencing reveals persistence of forest‐associated mammals in Late Pleistocene refugia along North America’s North Pacific Coast

“…Timing demographic events is sensitive to assumed mutation rates and generation times, which can expand or contract the estimated distribution of N e across evolutionary time. Mutation rates in mammals are reasonably clock-like (Gillooly et al, 2005) with carnivorans having a relatively slow mutation rate (Nabholz et al, 2008), which suggests that the timing of demographic splits approximated here may underestimate actual divergence times, which may be older, consistent with divergence date estimates of Martens rely on deep persistent snow and complex forest structure (Manlick et al, 2017;Martin et al, 2019;Pauli et al, 2013;Proulx, 1997) for predator avoidance, thermal management, and locomotion, suggesting that refugial ecosystems capable of supporting martens could also support forest communities, however, simplified.…”

Winter fidelity, movements, and energy expenditure of Midcontinent Greater White-fronted Geese

“…Likewise, energy expenditure varies spatially and is temporally dependent on many factors, including an individual’s physiological state (e.g., egg production or feather molt in birds), movement rates (e.g., migration, disturbance), environmental and landscape conditions (e.g., weather, habitat quality), or season [ 41 , 42 , 53 ]. Individuals may also experience carry-over effects (i.e., lagged effects on fitness of conditions from a previous season in the current or future season; see [ 67 ]) as a result of performance during previous seasons.…”

Quantifying behavior and life‐history events of an Arctic ungulate from year‐long continuous accelerometer data

“…Seasonality and environmental conditions modulate the movement patterns of animals and, consequently, their associated energetic balance (Smith 1974). For example, by combining muscle efficiency and slow locomotion, wildebeest minimize thermoregulatory challenges during long migrations under arid conditions (Curtin et al 2018), bottlenose dolphins modulate swimming speed in response to tidal currents (Bailey and Thompson 2010), and Pacific martens alter movement velocity and energetic expenditure in relation to forest structure (Martin et al 2020). Alpine and arctic regions are highly seasonal environments, and the snow-covered periods can pose severe constraints on movements and food availability/accessibility of terrestrial mammals.…”