Shifting Trophic Control of Fishery–Ecosystem Dynamics Following Biological Invasions
Bibliographic record
Abstract
Nonnative species often interact with native species in unexpected ways, posing threats to conservation of biodiversity and ecosystem services. Synthesizing 30 years of extensive ecosystem monitoring data, we show how two pervasive invasive consumers, dreissenids and Bythotrephes, rewire trophic interactions and undermine efforts to rebuild cold-water fisheries in a large, intensely exploited lake in Ontario, Canada (Lake Simcoe). We found that large-scale shifts in community composition (from pelagic to demersal dominance) brought on by the invaders have diminished ecosystem productivity, thereby shrinking fishery yields. Our work underscores the need to account for altered ecological reality in managing invaded ecosystems. These photographs illustrate the article “Shifting trophic control of fishery–ecosystem dynamics following biological invasions” by Daisuke Goto, Erin S. Dunlop, Joelle D. Young, and Donald A. Jackson published in Ecological Applications. https://doi.org/10.1002//eap.2190
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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 | 0.000 |
| 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".