Growth in marine mammals: a review of growth patterns, composition and energy investment
Bibliographic record
Abstract
Growth of structural mass and energy reserves influences individual survival, reproductive success, population and species life history. Metrics of structural growth and energy storage of individuals are often used to assess population health and reproductive potential, which can inform conservation. However, the energetic costs of tissue deposition for structural growth and energy stores and their prioritization within bioenergetic budgets are poorly documented. This is particularly true across marine mammal species as resources are accumulated at sea, limiting the ability to measure energy allocation and prioritization. We reviewed the literature on marine mammal growth to summarize growth patterns, explore their tissue compositions, assess the energetic costs of depositing these tissues and explore the tradeoffs associated with growth. Generally, marine mammals exhibit logarithmic growth. This means that the energetic costs related to growth and tissue deposition are high for early postnatal animals, but small compared to the total energy budget as animals get older. Growth patterns can also change in response to resource availability, habitat and other energy demands, such that they can serve as an indicator of individual and population health. Composition of tissues remained consistent with respect to protein and water content across species; however, there was a high degree of variability in the lipid content of both muscle (0.1-74.3%) and blubber (0.4-97.9%) due to the use of lipids as energy storage. We found that relatively few well-studied species dominate the literature, leaving data gaps for entire taxa, such as beaked whales. The purpose of this review was to identify such gaps, to inform future research priorities and to improve our understanding of how marine mammals grow and the associated energetic costs.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".