Disruption of the lower food web in Lake Ontario: Did it affect alewife growth or condition?
Bibliographic record
Abstract
From the early 1980s to the late 1990s, a succession of non-native invertebrates colonized Lake Ontario and the suite of consequences caused by their colonization became known as “food web disruption”. For example, the native burrowing amphipod Diporeia spp., a key link in the profundal food web, declined to near absence, exotic predaceous cladocerans with long spines proliferated, altering the zooplankton community, and depth distributions of fishes shifted. These changes had the potential to affect growth and condition of planktivorous alewife Alosa pseudoharengus, the most abundant fish in the lake. To determine if food web disruption affected alewife, we used change-point analysis to examine alewife growth and adult alewife condition during 1976–2006 and analysis-of-variance to determine if values between change points differed significantly. There were no change points in growth during the first year of life. Of three change points in growth during the second year of life, one coincided with the shift in springtime distribution of alewife to deeper water but it was not associated with a significant change in growth. After the second year of life, no change points in growth were evident, although growth in the third year of life spiked in those years when Bythotrephes, the largest of the exotic cladocerans, was abundant suggesting that it was a profitable prey item for age-2 fish. We detected two change points in condition of adult alewife in fall, but the first occurred in 1981, well before disruption began. A second change point occurred in 2003, well after disruption began. After the springtime distribution of alewife shifted deeper during 1992–1994, growth in the first two years of life became more variable, and growth in years of life two and older became correlated (P < 0.05). In conclusion, food web disruption had no negative affect on growth and condition of alewife in Lake Ontario although it appears to have resulted in growth in the first two years of life becoming more variable, growth in years of life two and older becoming correlated (P < 0.05), and growth spurts in year of life three.
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 | 0.001 | 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) | 0.002 | 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".