The adenylate energy charge as a new and useful indicator of capture stress in chondrichthyans
Quantifying the physiological stress response of chondrichthyans to capture has assisted the development of fishing practices conducive to their survival. However, currently used indicators of stress show significant interspecific and intraspecific variation in species’ physiological responses and tolerances to capture. To improve our understanding of chondrichthyan stress physiology and potentially reduce variation when quantifying the stress response, we investigated the use of the adenylate energy charge (AEC); a measure of available metabolic energy. To determine tissues sensitive to metabolic stress, we extracted samples of the brain, heart, liver, white muscle and blood from gummy sharks (Mustelus antarcticus) immediately following gillnet capture and after 3 h recovery under laboratory conditions. Capture caused significant declines in liver, white muscle and blood AEC, whereas no decline was detected in the heart and brain AEC. Following 3 h of recovery from capture, the AEC of the liver and blood returned to “unstressed” levels (control values) whereas white muscle AEC was not significantly different to that immediately after capture. Our results show that the liver is most sensitive to metabolic stress and white muscle offers a practical method to sample animals non-lethally for determination of the AEC. The AEC is a highly informative indicator of stress and unlike current indicators, it can directly measure the change in available energy and thus the metabolic stress experienced by a given tissue. Cellular metabolism is highly conserved across organisms and, therefore, we think the AEC can also provide a standardised form of measuring capture stress in many chondrichthyan species.
KeywordsElasmobranch Fisheries Gillnet Shark Metabolism
We thank Carolina and Thomas Weller, Derek Dapp, Lauren Hall and Ricky Tate for fieldwork and manuscript assistance. We thank Roderick Watson and Elizabeth McGrath from the Victorian Marine Science Consortium (VMSC) and Phillip Holt from Monash University for logistical assistance. Funding for this study was provided by the Australian Research Council (ARC) Linkage Grant LP110200572, the Department of Economic Development, Jobs, Transport and Resources Victoria, Australian Fisheries Management Authority (AFMA) and Melbourne Aquarium. This study was conducted in accordance with Monash University Animal Ethics approval number BSCI/2012/16 and DELWP Fisheries permit number RP1115.
- Coles, JA, Sigg, DC, Iaizzo, PA (2009) Reversible and irreversible damage of the myocardium: new ischemic syndromes, ischemia/reperfusion injury, and cardioprotection. In: Iaizzo PA (ed) Handbook of cardiac anatomy, physiology, and devices (2nd edn), pp 219–229. (Springer Science + Business Media, LLC)Google Scholar
- Development Core Team R (2013) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, AustriaGoogle Scholar
- Dulvy NK, Fowler SL, Musick JA, Cavanagh RD, Kyne PM, Harrison LR, Carlson JK, Davidson LNK, Fordham SV, Francis MP, Pollock CM, Simpfendorfer CA, Burgess GH, Carpenter KE, Compagno LJV, Ebert DA, Gibson C, Heupel MR, Livingstone SR, Sanciangco JC, Stevens JD, Valenti S, White WT (2014) Extinction risk and conservation of the world’s sharks and rays. Elife 3:1–34CrossRefGoogle Scholar
- Gamperl, AK, Driedzic, WR (2009) Cardiovascular function and cardiac metabolism. In: Richards JG, Farrell AP, Brauner CJ (eds) Hypoxia, vol 27. Elsevier Academic Press, USA, pp 301–360Google Scholar
- Hyatt MW, Anderson PA, O’Donnell PM, Berzins IK (2012) Assessment of acid-base derangements among bonnethead (Sphyrna tiburo), bull (Carcharhinus leucas), and lemon (Negaprion brevirostris) sharks from gillnet and longline capture and handling methods. Comp Biochem Physiol A Mol Integr Physiol 162:113–120PubMedCrossRefGoogle Scholar
- Konietschke F, Placzek M, Schaarschmidt F, Hothorn LA (2014) nparcomp: an R software package for nonparametric multiple comparisons and simultaneous confidence intervals. J Stat Softw 61:1–17Google Scholar
- Richards JG (2009) Metabolic and molecular responses of fish to hypoxia. In: Richards JG, Farrell AP, Brauner CJ (eds) Hypoxia, vol 27. Elsevier Academic Press, USA, pp 443–485Google Scholar
- Storey KB, Storey JM (2005) Oxygen limitation and metabolic rate depression. In: KB Storey (ed) Functional metabolism. Wiley, USA, pp 415–442Google Scholar
- Van der Boon J, de Jong RL, Van den Thillart G, Addink ADF (1992) Reversed-phase ion-paired HPLC of purine nucleotides from skeletal muscle, heart and brain of the goldfish, Crassius auratus L.-II. Influence of environmental anoxia on metabolite levels. Comp Biochem Physiol B Biochem Mol Biol 101:583–586CrossRefGoogle Scholar