Induced morphological defence: evidence from whole-lake manipulation experiments
Bibliographic record
Abstract
Predator-induced defences are activated by cues associated with predators and confer some degree of resistance to subsequent attacks. Laboratory studies of many taxa have revealed such induced defences, and these data often conform to large-scale surveys of defence levels in habitats with and without predators. However, there have been no studies that make the direct connection between these laboratory studies and field surveys. We conducted a large-scale field manipulation of predators to provide this connection. Previous laboratory experiments on dragonfly (Leucorrhinia dubia) larvae have demonstrated that the presence of fish predators induces the development of elongated abdominal spines that serve to reduce mortality risk. In this study we determine the effect of whole-lake predator manipulation on this induced morphological defence of L. dubia. We monitored the spine lengths of final-instar larvae in two experimental lakes for 7 consecutive years. Fish were present during the first 2 years and then removed for the remaining 5 years. Results demonstrate that the spine lengths of L. dubia larvae decreased significantly in both lakes after the removal of fish. In contrast, there was no corresponding change in the spine lengths of larvae in reference lakes, and we found little change in food supply for larvae. Our results suggest that the plastic response in spine length is strong and attributable to the presence of predators.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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".