Trophic consequences of non-native pumpkinseed Lepomis gibbosus for native pond fishes
Bibliographic record
Abstract
Introduced non-native fishes can cause considerable adverse impacts on freshwater ecosystems. The pumpkinseed Lepomis gibbosus , a North American centrarchid, is one of the most widely distributed non-native fishes in Europe, having established self-sustaining populations in at least 28 countries, including the U.K. where it is predicted to become invasive under warmer climate conditions. To predict the consequences of increased invasiveness, a field experiment was completed over a summer period using a Control comprising of an assemblage of native fishes of known starting abundance and a Treatment using the same assemblage but with elevated L. gibbosus densities. The trophic consequences of L. gibbosus invasion were assessed with stable isotope analysis and associated metrics including the isotopic niche, measured as standard ellipse area. The isotopic niches of native gudgeon Gobio gobio and roach Rutilus rutilus overlapped substantially with that of non-native L. gibbosus , and were also substantially reduced in size compared to ponds where L. gibbosus were absent. This suggests these native fishes shifted to a more specialized diet in L. gibbosus presence. Both of these native fishes also demonstrated a concomitant and significant reduction in their trophic position in L. gibbosus presence, with a significant decrease also evident in the somatic growth rate and body condition of G. gobio . Thus, there were marked changes detected in the isotopic ecology and growth rates of the native fish in the presence of non-native L. gibbosus. The implications of these results for present and future invaded pond communities are discussed.
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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 | 0.000 | 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".