Data from: 100-year time-series reveal little morphological change following impoundment and predator invasion in two Neotropical characids
Bibliographic record
Abstract
Human activities are dramatically altering ecosystems worldwide, often resulting in shifts in selection regimes. In response, natural populations sometimes undergo rapid phenotypic changes, which if adaptive, can increase their probability of persistence. However, in many instances, populations fail to undergo any phenotypic change, which might indicate a variety of possibilities, including maladaptation. In freshwater ecosystems, the impoundment of rivers and the introduction of exotic species are among the leading threats to native fishes. We examined how the construction of the Panama Canal, which formed Lake Gatun, and the subsequent invasion of the predatory Cichla monoculus influenced the morphology of two native fishes: Astyanax ruberrimus and Roeboides spp. Using a 100-year time series, we studied variation in overall body shape over time (pre vs. post impoundment and invasion) as well as across space (between an invaded and an uninvaded reservoir). In addition, we examined variation in linear morphological traits associated with swim performance and predator detection/avoidance. Notwithstanding a few significant changes in particular traits in particular comparisons, we found only limited evidence for morphological change associated with these two stressors. Most observed changes were subtle, and tended to be site and species-specific. The lack of a strong morphological response to these stressors, coupled with dramatic population declines in both species, suggests they may be maladapted to the anthropogenically-perturbed environment of Lake Gatun, but direct measures of fitness would be needed to test this. In general, our results suggest that morphological responses to anthropogenic disturbances can be very limited and when they do occur, are often complex and context-dependent.
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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".