Mechanisms underlying lack of functional compensation by insect grazers after tadpole declines in a Neotropical stream
Bibliographic record
Abstract
Abstract Resilience of ecosystems to the sudden decline of large‐bodied species is dependent on characteristics of surviving guild members. However, that response may also be mediated by local habitat conditions. Here, we examine the mechanisms behind the observed lack of functional compensation in the algal‐grazing guild by insect grazers following the decline of tadpole grazers in a forested Panamanian stream. We examined: (1) shifts to the individual size distribution of insect grazers between pre‐ and post‐tadpole declines in pool and riffle habitats; (2) tadpole and insect preferences for small‐, medium‐, and large‐sized diatoms; and (3) a causal explanation for why insects did not functionally compensate for tadpole declines. The size distribution of insect grazers following tadpole declines differed between habitats, becoming uniform in pools and more right skewed toward a smaller size class in riffles. In both habitats, tadpoles selectively consumed medium‐sized diatoms but avoided the largest‐sized diatoms. In contrast, grazing insects selectively consumed small‐sized diatoms, but switched to medium‐sized diatoms after tadpole declines. Tadpole declines led to the loss of the strongest interactions between consumers and diatoms. Smaller‐bodied grazing insects could not duplicate these interactions, even with a shift in resource use, providing an explanation for the lack of functional compensation. Furthermore, tadpole declines led to different community structures in each habitat indicating that local habitat conditions mediated the response of surviving guild members. This suggests that the sudden decline of a large‐bodied species does not lead to a singular outcome for the surviving community.
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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 | 0.000 |
| 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 | 0.000 |
| 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".