Ecology of Exercise in Wild Fish: Integrating Concepts of Individual Physiological Capacity, Behavior, and Fitness Through Diverse Case Studies
Bibliographic record
Abstract
SYNOPSIS: Wild animals maximize fitness through certain behaviors (e.g., foraging, mating, predator avoidance) that incur metabolic costs and often require high levels of locomotor activity. Consequently, the ability of animals to achieve high fitness often relies on their physiological capacity for exercise (aerobic scope) and/or their ability to acquire and utilize energy judiciously. Here, we explore how environmental factors and physiological limitations influence exercise and metabolism in fish while foraging, migrating to spawning grounds, and providing parental care. We do so with three case studies that use a number of approaches to studying exercise in wild fish using biologging and biotelemetry platforms. Bonefish (Albula vulpes) selectively use shallow water tropical marine environments to forage when temperatures are near optimal for aerobic scope and exercise capacity. Bonefish energy expenditure at upper thermal extremes is maximal while activity levels diminish, likely caused by reduced aerobic scope. Pacific salmon (Oncorhynchus spp.) reproductive migrations frequently involve passage through hydraulically challenging areas, and their ability to successfully pass these regions is constrained by their physiological capacity for exercise. Aerobic scope and swim performance are correlated with migration difficulty among sockeye salmon (O. nerka) populations; however, depletion of endogenous energy stores can also limit migration success. In another example, male smallmouth bass (Micropterus dolomieu) allocate a significant amount of energy to nest-guarding behaviors to protect their developing brood. Smallmouth bass body size, endogenous energy reserves, and physiological state influence nest-guarding behaviors and reproductive success. We suggest that in some scenarios (e.g., bonefish foraging, Pacific salmon dam passage) metabolic capacity for exercise may be the strongest determinant of biological fitness, while in others (e.g., long distance salmon migration, smallmouth bass parental care) energy stores may be more important. Interactions among environmental and ecological factors, fish behavior, and fish physiology offer important avenues of mechanistic inquiry to explain ecological dynamics and demonstrate how exercise is fundamental to the ecology of fish.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".