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
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 teacher head, 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".