Empirical analysis of the influence of swimming pattern on the net energetic cost of swimming in fishes

Boisclair, Daniel; Ming, Tang

doi:10.1111/j.1095-8649.1993.tb00319.x

Cited by 165 publications

(111 citation statements)

References 41 publications

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“…Swimming ability could explain this relationship because fish will swim longer distances more frequently if unhampered (Boisclair & Tang 1993). Swimming ability could explain this relationship because fish will swim longer distances more frequently if unhampered (Boisclair & Tang 1993).…”

Section: How Far Do Fish Move?mentioning

confidence: 99%

Fish movement and habitat use depends on water body size and shape

Woolnough

Downing

Newton

2009

Ecology of Freshwater Fish

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Woolnough DA, Downing JA, Newton TJ. Fish movement and habitat use depends on water body size and shape.Abstract -Home ranges are central to understanding habitat diversity, effects of fragmentation and conservation. The distance that an organism moves yields information on life history, genetics and interactions with other organisms. Present theory suggests that home range is set by body size of individuals. Here, we analyse estimates of home ranges in lakes and rivers to show that body size of fish and water body size and shape influence home range size. Using 71 studies including 66 fish species on five continents, we show that home range estimates increased with increasing water body size across water body shapes. This contrasts with past studies concluding that body size sets home range. We show that water body size was a consistently significant predictor of home range. In conjunction, body size and water body size can provide improved estimates of home range than just body size alone. As habitat patches are decreasing in size worldwide, our findings have implications for ecology, conservation and genetics of populations in fragmented ecosystems.

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Section: How Far Do Fish Move?mentioning

confidence: 99%

Fish movement and habitat use depends on water body size and shape

Woolnough

Downing

Newton

2009

Ecology of Freshwater Fish

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“…We focused on these variables first since they can be regarded as an approximate individual measure of energy expenditure [28]. Attacks in both the symmetric and asymmetric phases had higher velocities than the pre-fight phase.…”

Section: Resultsmentioning

confidence: 99%

Zebrafish aggression on the sub-second time scale: evidence for mutual motor coordination and multi-functional attack manoeuvres

Laan¹,

Iglesias-Julios²,

Polavieja³

2018

R. Soc. open sci.

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Most animals fight by repeating complex stereotypic behaviours, yet the internal structure of these behaviours has rarely been dissected in detail. We characterized the internal structure of fighting behaviours by developing a machine learning pipeline that measures and classifies the behaviour of individual unmarked animals on a sub-second time scale. This allowed us to quantify several previously hidden features of zebrafish fighting strategies. We found strong correlations between the velocity of the attacker and the defender, indicating a dynamic matching of approach and avoidance efforts. While velocity matching was ubiquitous, the spatial dynamics of attacks showed phase-specific differences. Contest-phase attacks were characterized by a paradoxical sideways attraction of the retreating animal towards the attacker, suggesting that the defender combines avoidance manoeuvres with display-like manoeuvres. Post-resolution attacks lacked display-like features and the defender was avoidance focused. From the perspective of the winner, game-theory modelling further suggested that highly energetically costly post-resolution attacks occurred because the winner was trying to increase its relative dominance over the loser. Overall, the rich structure of zebrafish motor coordination during fighting indicates a greater complexity and layering of strategies than has previously been recognized.

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“…However, it has long been recognised that the costs of swimming at a constant speed and direction may not correspond to those of swimming at the same average speed but with accelerations, decelerations, and turns (Beamish and Dickie 1967). Empirical analyses by Boisclair and Tang (1993) suggested that the energetic costs of spontaneous swimming (including changes of speed and direction) for a given fish weight and average swimming speed may be 6 to 14 times higher than those estimated by forced swimming models. These results supported the hypothesis that accelerations and turns are very expensive and led to experiments to develop models aimed at estimating the spontaneous swimming costs of fish using a more detailed suite of swimming characteristics as independent variables.…”

Section: Surplus = Ingestion -(Expenditures + Losses)mentioning

confidence: 97%

“…Relationship between the respiration rates of brook trout predicted by a forced swimming model (Boisclair and Tang 1993) and the observed spontaneous costs of swimming for these fish during 45 respirometry experiments.…”

Section: Figmentioning

confidence: 99%

Fish habitat modeling: from conceptual framework to functional tools

Boisclair¹

2001

Can. J. Fish. Aquat. Sci.

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Natural and anthropogenic perturbations do not always equally affect all parts of an ecosystem, and all parts of an ecosystem do not equally contribute to maintain fish communities. The increasing pressure to use natural resources and to modify habitats led to the development of approaches to identify areas of key importance for fish communities. Following these approaches, aquatic systems could be perceived as puzzles, composed of a multitude of pieces with temporally flexible physical attributes and biological roles. Such a spatially explicit framework requires models that may allow one to predict fish distribution patterns and fish net energy gain once they have adopted a specific distribution pattern. Despite the conceptual appeal of spatially explicit approaches, functional tools may be obtained only after their assumptions have been tested and their models have been validated. Efforts must be deployed to identify temporal and spatial scales at which fish distribution and abundance should be estimated and modeled. Studies on fish behaviour and the energetic consequences of these behaviours must be conducted to insure that bioenergetic criteria used to define fish habitat quality do not depend on arbitrary assumptions about fish activity costs.Résumé : Les perturbations naturelles et anthropiques n'affectent pas toujours également toutes les parties d'un écosystème et toutes les parties d'un écosystème ne contribuent pas également au maintien des communautés de poissons. La pression grandissante d'utiliser les ressources naturelles ont amené le développement d'approches permettant d'identifier les régions d'une importance clé pour les communautés de poissons. Suivant ces approches, les rivières relativement peu profondes pourraient être perçues comme des mosaïques de parcelles ayant chacune sa valeur énergétique spécifique pour les poissons et les rivières plus profondes et les lacs pourraient ressembler à des sculptures de blocs ayant chacun sa valeur de croissance potentielle pour les poissons. Un cadre de référence spatialement explicite requiert des modèles qui permettent de prédire les patrons de distribution des poissons et le gain énergétique net des poissons une fois qu'ils ont adopté un patron de distribution spécifique. Malgré l'attrait conceptuel des approches spatialement explicites, des outils fonctionnels ne pourront être obtenus qu'une fois leurs prémisses testées et leurs modèles validés. Des efforts doivent être déployés pour identifier les échelles temporelles et spatiales auxquelles la distribution et l'abondance des poissons devraient être estimées et modelisées. Des études sur le comportement des poissons et les conséquences énergétiques de ces comportements doivent être effectuées pour s'assurer que les critères bioénergétiques utilisés pour définir la qualité de l'habitat des poissons ne dépendent pas de prémisses arbitraires au sujet des coûts de l'activité des poissons. Boisclair 9 Fig. 3. Day-night variations of mean FRA in the nearshore (N) and farshore (F) areas of the pelagic zone...

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Empirical analysis of the influence of swimming pattern on the net energetic cost of swimming in fishes

Cited by 165 publications

References 41 publications

Fish movement and habitat use depends on water body size and shape

Fish movement and habitat use depends on water body size and shape

Zebrafish aggression on the sub-second time scale: evidence for mutual motor coordination and multi-functional attack manoeuvres

Fish habitat modeling: from conceptual framework to functional tools

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