RESUMO
A strength of physiological ecology is its incorporation of aspects of both species' ecology and physiology; this holistic approach is needed to address current and future anthropogenic stressors affecting elasmobranch fishes that range from overexploitation to the effects of climate change. For example, physiology is one of several key determinants of an organism's ecological niche (along with evolutionary constraints and ecological interactions). The fundamental role of physiology in niche determination led to the development of the field of physiological ecology. This approach considers physiological mechanisms in the context of the environment to understand mechanistic variations that beget ecological trends. Physiological ecology, as an integrative discipline, has recently experienced a resurgence with respect to conservation applications, largely in conjunction with technological advances that extended physiological work from the lab into the natural world. This is of critical importance for species such as elasmobranchs (sharks, skates and rays), which are an especially understudied and threatened group of vertebrates. In 2017, at the American Elasmobranch Society meeting in Austin, Texas, the symposium entitled `Applications of Physiological Ecology in Elasmobranch Research' provided a platform for researchers to showcase work in which ecological questions were examined through a physiological lens. Here, we highlight the research presented at this symposium, which emphasized the strength of linking physiological tools with ecological questions. We also demonstrate the applicability of using physiological ecology research as a method to approach conservation issues, and advocate for a more available framework whereby results are more easily accessible for their implementation into management practices.
RESUMO
Spatial segregation of animals by class (i.e., maturity or sex) within a population due to differential rates of temporary emigration (TE) from study sites can be an important life history feature to consider in population assessment and management. However, such rates are poorly known; new quantitative approaches to address these knowledge gaps are needed. We present a novel application of multi-event models that takes advantage of two sources of detections to differentiate temporary emigration from apparent absence to quantify class segregation within a study population of double-marked (photo-identified and tagged with coded acoustic transmitters) white sharks (Carcharodon carcharias) in central California. We use this model to test if sex-specific patterns in TE result in disparate apparent capture probabilities (po ) between male and female white sharks, which can affect the observed sex ratio. The best-supported model showed a contrasting pattern of Pr(TE) from coastal aggregation sites between sexes (for males Pr[TE] = 0.015 [95% CI = 0.00, 0.31] and Pr[TE]= 0.57 [0.40, 0.72] for females), but not maturity classes. Additionally, by accounting for Pr(TE) and imperfect detection, we were able to estimate class-specific values of true capture probability (p* ) for tagged and untagged sharks. The best-supported model identified differences between maturity classes but no difference between sexes or tagging impacts (tagged mature sharks p* = 0.55 (0.46-0.63) and sub-adult sharks p* = 0.36 (0.25, 0.50); and untagged mature sharks p* = 0.50 (0.39-0.61) and sub-adults p* = 0.18 (0.10, 0.31). Estimated sex-based differences in po were linked to sex-specific differences in Pr(TE) but not in p* ; once the Pr(TE) is accounted for, the p* between sexes was not different. These results indicate that the observed sex ratio is not a consequence of unequal detectability and sex-specific values of Pr(TE) are important drivers of the observed male-dominated sex ratio. Our modeling approach reveals complex class-specific patterns in Pr(TE) and p* in a mark-recapture data set, and highlights challenges for the population modeling and conservation of white sharks in central California. The model we develop here can be used to estimate rates of temporary emigration and class segregation when two detection methods are used.