GAPE-LIMITED PREDATORS AS AGENTS OF SELECTION ON THE DEFENSIVE MORPHOLOGY OF AN INVASIVE INVERTEBRATE
Bibliographic record
Abstract
Invasive species have widespread and pronounced effects on ecosystems and adaptive evolution of invaders is often considered responsible for their success. Despite the potential importance of adaptation to invasion, we still have limited knowledge of the agents of natural selection on invasive species. Bythotrephes longimanus, a cladoceran zooplankton, invaded multiple Canadian Shield lakes over the past several decades. Bythotrephes have a conspicuous caudal process (tail spine) that provides a morphological defense against fish predation. We measured viability selection on the longest component of the Bythotrephes spine, the distal spine segment, through a comparison of the lengths of first and second instar Bythotrephes collected from lakes differing in the dominance of gape-limited predation (GLP) and nongape-limited predation (NGLP) by fish. We found that natural selection varied by predator gape-limitation, with strong selection (selection intensity: 0.20-0.79) for increased distal spine length in lakes dominated by GLP, and no significant selection in lakes dominated by NGLP. Further, distal spine length was 17% longer in lakes dominated by GLP, suggesting the possibility of local adaptation. As all study lakes were invaded less than 20 years prior to our collections, our results suggest rapid divergence in defensive morphology in response to selection from fish predators.
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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 | 0.000 | 0.000 |
| 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".