Paired Estimates of Metabolic Rate and Gill Surface Area in the Horn Shark (Heterodontus francisci)


Meeting Abstract

32-4  Saturday, Jan. 4 14:15 – 14:30  Paired Estimates of Metabolic Rate and Gill Surface Area in the Horn Shark (Heterodontus francisci) PRINZING, TS*; BIGMAN, BS; SKELTON, Z; WEGNER, NC; DULVY, NK; Simon Fraser University, Burnaby BC; Simon Fraser University, Burnaby BC; Scripps Institution of Oceanography, La Jolla CA; NOAA Southwest Fisheries Science, Center La Jolla CA; Simon Fraser University Burnaby, BC tprinzin@sfu.ca

Metabolic rate underpins life history traits such as reproduction and growth rate and in turn, the maximum population growth rate of a species. However, our understanding of the metabolic basis for life histories and population dynamics is hindered by the challenge of using laboratory respirometers to estimate metabolic rate, resulting in relatively few estimates of metabolic rate for larger, aquatic organisms. An alternate approach is to seek morphological proxies for metabolic rate, such as respiratory surface area. Metabolic rate is highly correlated with respiratory surface area, yet there are exceedingly few paired estimates to allow a direct comparison of these traits in the same individuals. Here, we estimated resting and maximum metabolic rates in addition to gill surface area in a coastal elasmobranch, the Horn Shark (Heterodontus francisci), across a broad size range. We found that resting metabolic rate and body mass scaled with a slope of one, while the slope of maximum metabolic rate and body mass was significantly greater than one. These results are consistent with those of similar species and suggest that the aerobic capacity of this species increases through ontogeny. We will also discuss the scaling of gill surface area with body mass and with resting and maximum metabolic rates. By estimating these traits together in the same individuals, our work elucidates the allometric scaling of gill surface area in relation to both resting and maximum metabolic rates while minimizing the confounding factor of intra-individual variation. Overall, the results of this study may be used to inform life histories and conservation efforts of vulnerable, data-poor species.

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