Allometric relationships of ecologically important Antarctic and Arctic zooplankton and fish species
Bibliographic record
Abstract
Abstract Allometric relationships between body properties of animals are useful for a wide variety of purposes, such as estimation of biomass, growth, population structure, bioenergetic modelling and carbon flux studies. This study summarizes allometric relationships of zooplankton and nekton species that play major roles in polar marine food webs. Measurements were performed on 639 individuals of 15 species sampled during three expeditions in the Southern Ocean (winter and summer) and 2374 individuals of 14 species sampled during three expeditions in the Arctic Ocean (spring and summer). The information provided by this study fills current knowledge gaps on relationships between length and wet/dry mass of understudied animals, such as various gelatinous zooplankton, and of animals from understudied seasons and maturity stages, for example, for the krillThysanoessa macruraand larvalEuphausia superbacaught in winter. Comparisons show that there is intra-specific variation in length–mass relationships of several species depending on season, e.g. for the amphipodThemisto libellula. To investigate the potential use of generalized regression models, comparisons between sexes, maturity stages or age classes were performed and are discussed, such as for the several krill species andT. libellula. Regression model comparisons on age classes of the fishE. antarcticawere inconclusive about their general use. Other allometric measurements performed on carapaces, eyes, heads, telsons, tails and otoliths provided models that proved to be useful for estimating length or mass in, e.g. diet studies. In some cases, the suitability of these models may depend on species or developmental stages.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".