Biological invasions alter the structure of a tropical freshwater food web
Bibliographic record
Abstract
Biological invasions are expected to alter food web structure, but there are limited empirical data directly comparing invaded versus uninvaded food webs, particularly in species-rich, tropical systems. We characterize for the first time the food web of Lake Gatun-a diverse and highly invaded tropical freshwater lake within the Panama Canal. We used stable isotope analysis to reconstruct the trophic structure of the fish community of Lake Gatun and to compare it to that of a minimally invaded reference lake, Lake Bayano. We found significant differences between the trophic structures of these two Neotropical lakes, notably that Lake Gatun's fish community was characterized by a longer food chain, greater isotopic diversity, a broader range of trophic positions and body sizes, and shifts in the isotopic positions of several native taxa relative to Lake Bayano. The degree of isotopic overlap between native and non-native trophic guilds in Lake Gatun was variable, with herbivores exhibiting the lowest (20%-29%) overlap and carnivores the greatest (81%-100%). Overall, our results provide some of the first empirical evidence for the ways in which multiple introduced and native species may partition isotopic space in a species-rich tropical freshwater food web.
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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 | 0.001 |
| 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".