Remote bioenergetics measurements in wild fish: Opportunities and challenges

Cooke, Steven J.; Brownscombe, Jacob W.; Raby, Graham D.; Broell, Franziska; Hinch, Scott G.; Clark, Timothy D.; Semmens, Jayson M.

doi:10.1016/j.cbpa.2016.03.022

Cited by 140 publications

(134 citation statements)

References 171 publications

Supporting

Mentioning

134

Contrasting

Order By: Relevance

“…Understanding the emergent movement properties of fish and fishers can notably enhance our understanding of why a fish is captured. With the recent development of biotelemetry (Hussey et al., ; Krause et al., ) and biologging (Cooke et al., ), we can measure movement and other traits (e.g., physiology using accelerometers or heart rate loggers) that can contribute to vulnerability as well as develop an understanding of how correlated traits and environmental factors generate a vulnerability landscape (Figure ). Advances can be made in relating fish vulnerability and movement using experimental lakes, bays or reefs with tagged fish and passive telemetry arrays and may even be enhanced by incorporating trait data of fish released with tags (e.g., metabolism, personality, morphology) or by using biologgers to characterize acceleration, depth or temperature use of fish (Cooke et al., ).…”

Section: Conclusion and Research Needsmentioning

confidence: 99%

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

et al. 2017

View full text Add to dashboard Cite

Considerable time and money are expended in the pursuit of catching fish with hooks (e.g., handlining, angling, longlining, trolling, drumlining) across the recreational, commercial and subsistence fishing sectors. The fish and other aquatic organisms (e.g., squid) that are captured are not a random sample of the population because external (e.g., turbidity) and underlying internal variables (e.g., morphology) contribute to variation in vulnerability to hooks. Vulnerability is the probability of capture for any given fish in a given location at a given time and mechanistically explains the population‐level catchability coefficient, which is a fundamental and usually time‐varying (i.e., dynamic) variable in fisheries science and stock assessment. The mechanistic drivers of individual vulnerability to capture are thus of interest to fishers by affecting catch rates, but are also of considerable importance to fisheries managers whenever hook‐and‐line‐generated data contribute to stock assessments. In this paper, individual vulnerability to hooks is conceptualized as a dynamic state, in which individual fish switch between vulnerable and invulnerable states as a function of three interdependent key processes: an individual fish's internal state, its encounter with the gear, and the characteristics of the encountered gear. We develop a new conceptual framework of “vulnerability,” summarize the major drivers of fish vulnerability, and conclude that fish vulnerability involves complex processes. To understand vulnerability, a shift to interdisciplinary research and the integration of ecophysiology, fish ecology, fisheries ecology and human movement ecology, facilitated by new technological developments, is required.

show abstract

Section: Conclusion and Research Needsmentioning

confidence: 99%

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

et al. 2017

View full text Add to dashboard Cite

show abstract

“…Archival data storage tags (DST), which can collect data on both the internal and external environments of fish are the only method available to assess internal states ( e.g . bioenergetics; Cooke et al, ). DSTs, however, currently only provide information on the environment experienced by the tagged fish if the tag is recovered, meaning these data are lost if recapture rates are low, as is often the case in fish tagging surveys.…”

Section: Tagging and Telemetrymentioning

confidence: 99%

Understanding and managing fish populations: keeping the toolbox fit for purpose

Paris

Sherman

Bell

et al. 2018

Journal of Fish Biology

View full text Add to dashboard Cite

Wild fish populations are currently experiencing unprecedented pressures, which are projected to intensify in the coming decades. Developing a thorough understanding of the influences of both biotic and abiotic factors on fish populations is a salient issue in contemporary fish conservation and management. During the 50th Anniversary Symposium of The Fisheries Society of the British Isles at the University of Exeter, UK, in July 2017, scientists from diverse research backgrounds gathered to discuss key topics under the broad umbrella of 'Understanding Fish Populations'. Below, the output of one such discussion group is detailed, focusing on tools used to investigate natural fish populations. Five main groups of approaches were identified: tagging and telemetry; molecular tools; survey tools; statistical and modelling tools; tissue analyses. The appraisal covered current challenges and potential solutions for each of these topics. In addition, three key themes were identified as applicable across all tool-based applications. These included data management, public engagement, and fisheries policy and governance. The continued innovation of tools and capacity to integrate interdisciplinary approaches into the future assessment and management of fish populations is highlighted as an important focus for the next 50 years of fisheries research.

show abstract

“…Salinity and DO are other abiotic variables that, to a lesser extent, may influence metabolism in the field (Carlson et al, 2004) and were not included in these calibrations. Deploying water quality sensors alongside accelerometers in the field may help to extrapolate some of these effects (Cooke et al, 2016). Other biotic factors, including specific dynamic action (SDA, the proportion of energy dedicated to food processing and digestion) and recovery from anaerobic exercise, are more difficult to account for using the ODBA method, and have not been incorporated into the present calibrations.…”

Section: Application To Estimates Of Fmrmentioning

confidence: 99%

“…As the success and magnitude of feeding events generally cannot be discerned from accelerometer data, elevated metabolic rates due to SDA can be difficult to incorporate into FMR estimates. Additionally, when anaerobic respiration is used during short bouts of increased activity, such as during prey capture, predator avoidance or mating, animals incur an oxygen debt that leads to increased metabolism during post-exercise recovery periods, which again is difficult to directly account for using accelerometry (Cooke et al, 2016), though with additional calibrations anaerobic respiration can be successfully quantified from acceleration data (e.g. Robson et al, 2012).…”

Section: Application To Estimates Of Fmrmentioning

confidence: 99%

“…Robson et al, 2012). Using heart rate telemetry simultaneously with accelerometry may increase the accuracy of metabolic rate estimates (Clark et al, 2010;Cooke et al, 2016), as heart rate may scale more closely with ṀO 2 during physiological challenges, particularly during resting periods (Green et al, 2009;Halsey et al, 2011a).…”

Section: Application To Estimates Of Fmrmentioning

confidence: 99%

See 1 more Smart Citation

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes

Lear

Whitney

Brewster

et al. 2016

Journal of Experimental Biology

View full text Add to dashboard Cite

The ability to produce estimates of the metabolic rate of free-ranging animals is fundamental to the study of their ecology. However, measuring the energy expenditure of animals in the field has proved difficult, especially for aquatic taxa. Accelerometry presents a means of translating metabolic rates measured in the laboratory to individuals studied in the field, pending appropriate laboratory calibrations. Such calibrations have only been performed on a few fish species to date, and only one where the effects of temperature were accounted for. Here, we present calibrations between activity, measured as overall dynamic body acceleration (ODBA), and metabolic rate, measured through respirometry, for nurse sharks (Ginglymostoma cirratum), lemon sharks (Negaprion brevirostris) and blacktip sharks (Carcharhinus limbatus). Calibrations were made at a range of volitional swimming speeds and experimental temperatures. Linear mixed models were used to determine a predictive equation for metabolic rate based on measured ODBA values, with the optimal model using ODBA in combination with activity state and temperature to predict metabolic rate in lemon and nurse sharks, and ODBA and temperature to predict metabolic rate in blacktip sharks. This study lays the groundwork for calculating the metabolic rate of these species in the wild using acceleration data.

show abstract

Remote bioenergetics measurements in wild fish: Opportunities and challenges

Cited by 140 publications

References 171 publications

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

What makes fish vulnerable to capture by hooks? A conceptual framework and a review of key determinants

Understanding and managing fish populations: keeping the toolbox fit for purpose

Correlations of metabolic rate and body acceleration in three species of coastal sharks under contrasting temperature regimes

Contact Info

Product

Resources

About