Quantifying energetic costs and defining energy landscapes experienced by grizzly bears

Abstract

Animal movements are major determinants of energy expenditure and ultimately the cost–benefit of landscape use. Thus, we sought to understand those costs and how grizzly bears (Ursus arctos) move in mountainous landscapes. We trained captive grizzly bears to walk on a horizontal treadmill and up and down 10% and 20% slopes. The cost of moving upslope increased linearly with speed and slope angle, and this was more costly than moving horizontally. The cost of downslope travel at slower speeds was greater than the cost of traveling horizontally but appeared to decrease at higher speeds. The most efficient walking speed that minimized cost per unit distance was 1.19±0.11 m s−1. However, grizzly bears fitted with GPS collars in the Greater Yellowstone Ecosystem moved at an average velocity of 0.61±0.28 m s−1 and preferred to travel on near-horizontal slopes at twice their occurrence. When traveling uphill or downhill, grizzly bears chose paths across all slopes that were ∼54% less steep and costly than the maximum available slope. The net costs (J kg−1 m−1) of moving horizontally and uphill were the same for grizzly bears, humans and digitigrade carnivores, but those costs were 46% higher than movement costs for ungulates. These movement costs and characteristics of landscape use determined using captive and wild grizzly bears were used to understand the strategies that grizzly bears use for preying on large ungulates and the similarities in travel between people and grizzly bears that might affect the risk of encountering each other on shared landscapes.

Environmental correlates of activity and energetics in a wide-ranging social carnivore

“…incline −1 = 0.00743 + 0.028 * Speed n = 5, R 2 = 0.98, p < 0.001 . energy expenditure associated with downhill travel can be either more or less costly than level costs depending on the down-slope angle travelled [95,119,120].…”

Energy landscapes of Kodiak brown bears: A comparison of accelerometer and global positioning system derived estimates

“…Accelerometers are also data intensive due to their continuous high frequency measurements, making analysis computationally demanding. A GPS-derived measure of energy expenditure offers an alternative to study animal energetic ecology when accelerometer data may not be available (Carnahan et al 2021;Bryce et al 2022). We found that the GPS-derived estimates of MDEE were on average 1.6 times greater than the ACC method, displayed less overall variation and likely overestimated true energetic expenditure.…”

“…Predation risk, intraspeci c competition, resource distribution, landscape structure and temperature can impact an animal's physical activity levels and subsequent energetics (Brownscombe et al 2017). As these factors can vary across space and time, quantifying an animal's energetic landscape allows us to identify the biological and physical constraints underpinning their movement ecology (Carnahan et al 2021).…”

Certainty and integration of options in animal movement

“…Perhaps the greatest challenge will be to adjust our analyses to this way of thinking (Box 3). This will require data collection that captures variation in energy availability, analytical assessment of options available to animals at decision points (as some studies are beginning to explore, e.g., [15,53,54,74]), and the mathematical development of OMT within movement ecology [20]. Box…”

“…We call for the development of an optimal movement theory (OMT) that integrates this complexity and the certainty thereof according to the currency of energya common denominator of all ecological landscapes that influence movement simultaneously. [8,9] and of currents by aquatic species [10,11], to the avoidance of steep slopes, dense vegetation, and costly substrate types (e.g., snow cover) for terrestrial species [12][13][14][15]. Some species have even evolved to harvest and store this energy, such as the use of thermal and slope updrafts by soaring birds (Box 1) [16,17] and of underwater updrafts by negatively buoyant sharks [18], where potential energy is stored in height (altitude or shallower depth) and spent (by dropping/gliding) to cover distance while minimising the use of energy-expensive types of locomotion.…”