Invasive salmonids and lake order interact in the decline of puye grande <i>Galaxias platei</i> in western Patagonia lakes
Bibliographic record
Abstract
Salmonid fishes, native to the northern hemisphere, have become naturalized in many austral countries and appear linked to the decline of native fishes, particularly galaxiids. However, a lack of baseline information and the potential for confounding anthropogenic stressors have led to uncertainty regarding the association between salmonid invasions and galaxiid declines, especially in lakes, as these have been much less studied than streams. We surveyed 25 lakes in the Aysén region of Chilean Patagonia, including both uninvaded and salmonid-invaded lakes. Abundance indices (AI) of Galaxias platei and salmonids (Salmo trutta and Oncorhynchus mykiss) were calculated using capture-per-unit-effort data from gillnets, minnow traps, and electrofishing. We also measured additional environmental variables, including deforestation, lake morphometrics, altitude, and hydrological position (i.e., lake order). An information-theoretic approach to explaining the AI of G. platei revealed that by far the strongest effect was a negative association with the AI of salmonids. Lake order was also important, and using structural equation modeling, we show that this is an indirect effect naturally constraining the salmonid invasion success in Patagonia. Supporting this conclusion, an analysis of an independent data set from 106 mountain lakes in western Canada showed that introduced salmonids are indeed less successful in low-order lakes. Reproductive failure due to insufficient spawning habitat and harsh environmental conditions could be the cause of these limits to salmonid success. The existence of this effect in Chilean Patagonia suggests that low-order lakes are likely to provide natural ecological refugia for G. platei. Finally, pristine, high-order lakes should be actively protected as these have become rare and irreplaceable unspoiled references of the most diverse, natural lake ecosystems in Patagonia.
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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 | 0.001 |
| Scholarly communication | 0.001 | 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".