East or west: the energetic cost of being a gray whale and the consequence of losing energy to disturbance

Abstract

Western gray whales (WGW) Eschrichtius robustus are considered one of the world's most endangered baleen whale populations. Development of oil and gas fields in northeastern Sakhalin, Russia, is a concern, because they overlap with WGW feeding grounds. Some WGW migrate ~10 000 km from feeding grounds around Sakhalin Island (Russia), to breeding grounds in Baja California (BajaC; Mexico) and possibly ~6000 km to the South China Sea (China). We developed a WGW female bioenergetics model to examine potential consequences of energy lost from foraging cessation caused by anthropogenic disturbance, and compared it to eastern gray whales (EGW). Energy loss was then linked to potential reductions in reproduction and survival. Mean total energy requirements were 11 and 15% greater for WGW breeding in BajaC and China, respectively, compared to EGW, due to longer migration distance (25%) to BajaC and higher metabolic rates at foraging grounds. However, this difference is minimal for EGW that use the northern extent of their foraging range. On average, WGW breeding in BajaC and China need 9 and 17% more energy for survival than EGW. Our model predicts that WGW mortality would likely occur at 38 to 40% annual energetic loss. Long-term yearly energy loss of < 30% would reduce population growth due to lower reproductive rates. Ongoing yearly energy losses of > 30% would result in adult female mortality the first year, followed by lower reproductive rates of survivors. Our model suggests that energy losses of > 30% caused by disturbance should be considered a threshold for concern for this Critically Endangered population.

Understanding the population consequences of disturbance

“…Telemetry data can provide information on the patterns of repeated exposure for specific individuals (Costa et al., ; Falcone et al., ; Jones et al., ; Madsen et al., ; Pirotta, New, & Marcoux, ), and photographic identification (e.g., Calambokidis, Barlow, Ford, Chandler, & Douglas, ) can be used to estimate exposure risks for regularly monitored populations (Christiansen, Bertulli, Rasmussen, & Lusseau, ; Pirotta, Thompson, Cheney, Donovan, & Lusseau, ). In alternative, some studies examined the consequences of exposing all individuals in a population to the same amount of disturbance (Braithwaite, Meeuwig, & Hipsey, ; New et al., ; Villegas‐Amtmann, Schwarz, Gailey, Sychenko, & Costa, ; Villegas‐Amtmann, Schwarz, Sumich, & Costa, ).…”

“…They have been used to assess the responses of harbor porpoises ( Phocoena phocoena ) to wind farm developments (Brandt, Diederichs, Betke, & Nehls, ; Nabe‐Nielsen, Sibly, Tougaard, Teilmann, & Sveegaard, ; Nabe‐Nielsen et al., ), of Blainville's beaked whales ( Mesoplodon densirostris ) to sonar (Moretti et al., ; Tyack et al., ), and of bottlenose dolphins ( Tursiops truncatus ) to boat presence (Pirotta, Merchant, Thompson, Barton, & Lusseau, ). In the absence of empirical data, behavioral responses have been extrapolated from better‐studied species or assumed, often in terms of the number of lost foraging days (King et al., ; New et al., ; Villegas‐Amtmann et al., , ). Most studies (e.g., Williams, Lusseau, & Hammond, ) have evaluated the decrease in energy intake due to the observed behavioral responses.…”

“…() examined the relation between foraging activity and energy stores (estimated from changes in buoyancy) of female southern elephant seals ( Mirounga leonina ) over the course of a foraging trip. Other applications have inferred changes in energy stores from models of foraging activity that either treat energy explicitly using a bioenergetic approach (Beltran, Testa, & Burns, ; Christiansen & Lusseau, ; Farmer, Noren, Fougères, Machernis, & Baker, ; McHuron, Costa, Schwarz, & Mangel, ; McHuron, Mangel, Schwarz, & Costa, ; Noren, ; Pirotta, Mangel, et al., ; Villegas‐Amtmann et al., , ) or use an arbitrarily scaled energy metric that represents an underlying motivational state (Nabe‐Nielsen et al., , ; New, Harwood, et al., ; Pirotta, Harwood, et al., ; Pirotta, New, Harwood, & Lusseau, ). Although technologies that can measure the morphometrics of individuals remotely may make it easier to estimate changes in body condition directly (e.g., Christiansen, Dujon, Sprogis, Arnould, & Bejder, ; Miller, Best, Perryman, Baumgartner, & Moore, ), extensive health assessment in cetaceans will probably remain limited to a few closely monitored coastal populations, due to logistical constraints (Wells et al., ).…”

“…In the absence of a direct estimate of calf survival, Christiansen and Lusseau () used the fetal length of minke whales ( Balaenoptera acutorostrata ) as a proxy, and investigated how fetal length was associated with female body condition (Christiansen, Víkingsson, Rasmussen, & Lusseau, ). All other PCoD studies of marine mammals have assumed a simple relationship between various health metrics and vital rates (McHuron, Costa, et al., ; Nabe‐Nielsen et al., , ; Pirotta, Mangel, et al., ; Villegas‐Amtmann et al., , ).…”

“…Some PCoD applications developed IBMs that simulate individuals moving, accessing prey, and accumulating energy stores to sustain survival and reproduction (New, Harwood, et al., ; Pirotta, Harwood, et al., ; Pirotta et al., ; Villegas‐Amtmann et al., ). However, only three studies (Nabe‐Nielsen et al., , ; Villegas‐Amtmann et al., ) have used IBMs to predict the dynamics of a population over time. Although IBMs require considerable data, they are extremely flexible.…”