Life‐history variation in a species complex of nonmigratory galaxiids
Bibliographic record
Abstract
Abstract Life‐history theory predicts that the optimal strategy in the trade‐off between egg size and number varies in relation to resource availability and environmental disturbance. We assessed interspecific differences in egg size, fecundity and other life‐history traits in a species complex of stream‐resident galaxiid fish, which are distributed across a range of contrasting habitat types on the South Island, New Zealand. Oocyte size, fecundity and reproductive effort were measured from gravid females collected immediately before spawning. Proxy measures of stream productivity, flow variability and predation pressure were extracted from modelled data sets. A suite of different egg sizes were identified across species within theGalaxias vulgariscomplex, with mean oocyte volume differing by up to 133% between species. The species with the smallest eggs showed mean size‐relative fecundities 246% higher than the species with the largest eggs. A significant negative relationship was found between species’ mean egg size and size‐relative fecundity, suggesting a trade‐off between these traits. Species with larger eggs had larger maternal body size, lower reproductive effort and delayed maturity compared to ‘small‐egg’ species. Consistent with the predictions of life‐history theory, species with larger eggs, lower size‐relative fecundity, lower reproductive effort and delayed maturity were associated with low productivity, stable streams, whereas species exhibiting the opposite set of traits occurred in relatively productive but disturbed systems.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".