Energetic costs of locomotion in bears: is plantigrade locomotion energetically economical?

Abstract

Ursids are the largest mammals to retain a plantigrade posture. This primitive posture has been proposed to result in reduced locomotor speed and economy relative to digitigrade and unguligrade species, particularly at high speeds. Previous energetics research on polar bears () found locomotor costs were more than double predictions for similarly sized quadrupedal mammals, which could be a result of their plantigrade posture or due to adaptations to their Arctic marine existence. To evaluate whether polar bears are representative of terrestrial ursids or distinctly uneconomical walkers, this study measured the mass-specific metabolism, overall dynamic body acceleration, and gait kinematics of polar bears and grizzly bears () trained to rest and walk on a treadmill. At routine walking speeds, we found polar bears and grizzly bears exhibited similar costs of locomotion and gait kinematics, but differing measures of overall dynamic body acceleration. Minimum cost of transport while walking in the two species (2.21 J kg m) was comparable to predictions for similarly sized quadrupedal mammals, but these costs doubled (4.42 J kg m) at speeds ≥5.4 km h Similar to humans, another large plantigrade mammal, bears appear to exhibit a greater economy while moving at slow speeds.

Estimating the energy expenditure of free‐ranging polar bears using tri‐axial accelerometers: A validation with doubly labeled water

“…The relationship we developed on the treadmill was limited to a maximum speed of 3 km/hr, which may have limited our ability to predict energy expenditure at greater speeds. However, in polar bears, V̇O 2 has been shown to increase linearly at speeds up to 5.4 km/hr (Pagano, Carnahan et al, ) and free‐ranging polar bears, including those in this study, rarely exceed this speed (Pagano, Carnahan et al, ; Whiteman et al, ). Another factor that can influence the relationship between ODBA and V̇O 2 , and thus cost of locomotion, is uneven surfaces including moving on rough or icy surfaces, and traversing inclines and declines (Halsey, ; Halsey et al, ).…”

“…Energy expenditure during nonswimming behaviors was based on the relationship between ODBA and oxygen consumption (V̇O 2 ) derived by Pagano, Carnahan et al (). However, Pagano, Carnahan et al () found a negative intercept between ODBA and V̇O 2 and suggested this relationship needed to be further developed. This negative intercept may have been related to head movements of the bears during resting V̇O 2 and ODBA measurements.…”

“…To correct for the potential that head movements during resting measurements biased our ODBA measures, we measured the mean ODBA of 3 captive adult female polar bears (body mass: 237, 242, and 288 kg; age: 14, 31, and 15 years) while resting and motionless in their enclosures (Pagano, Rode, Cutting et al, ) and assigned them the mean mass‐specific resting metabolic rate summarized by Pagano, Carnahan et al () from three studies (0.230 ml O 2 g −1 hr −1 ). We incorporated these three measures with the previous measures determined by Pagano, Carnahan et al () and found V̇O 2 (ml O 2 g −1 hr −1 ) increased linearly as a function of ODBA ( g ) where: V̇O 2 = 0.07 + 1.90 × ODBA ( r 2 = 0.71, p < 0.001, n = 21, Figure ). For swimming movements, we used the mean swimming energetic cost determined by Griffen () (2.75 ml O 2 g −1 hr −1 ).…”

“…This negative intercept may have been related to head movements of the bears during resting V̇O 2 and ODBA measurements. To correct for the potential that head movements during resting measurements biased our ODBA measures, we measured the mean ODBA of 3 captive adult female polar bears (body mass: 237, 242, and 288 kg; age: 14, 31, and 15 years) while resting and motionless in their enclosures (Pagano, Rode, Cutting et al, 2017) and assigned them the mean mass-specific resting metabolic rate summarized by Pagano, Carnahan et al (2018) from three studies (0.230 ml O 2 g −1 hr −1 ).…”

“…The behaviors and activity rates of individual bears were identified based on a previously developed random forest model using tri-axial accelerometer and conductivity sensor data (Pagano, Rode, Cutting et al, 2017). A relationship between oxygen consumption and ODBA was developed from measures of metabolic rate from captive, collared adult female polar bears resting and walking on a treadmill (Pagano, Carnahan et al, 2018). Energetic costs of swimming were derived from modeled estimates using internal body temperature data from free-ranging polar bears while swimming (Griffen, 2018).…”