Effect of lake size, isolation and top predator presence on nested fish community structure
Bibliographic record
Abstract
Abstract Aim Predator–prey interactions are important determinants of community composition in freshwater habitats but have rarely been examined as a potential cause of nested community structure. In nested communities, species present in small assemblages are proper subsets of those present in larger assemblages. The goal of our study was to determine whether fish communities in the lakes of two regions were significantly nested, and if so, whether lake size, isolation and piscivorous fish (top predator) presence contributed to the nested pattern. Location We used fish community data from two regions in Ontario, Canada that differ in terms of range in lake size and lake isolation. The Black and Hollow Rivers and Manitoulin Island data sets contain fish community data from 52 and 49 lakes respectively. Methods Using two metrics, we tested whether fish assemblages were significantly nested. We evaluated the impact of lake size, isolation and top predator presence on both lake nested rank order and species richness. We then assessed idiosyncratic species that did not conform to the nested pattern. Results Fish assemblages in both regions were significantly nested. There was a significant positive correlation between lake size and nestedness of fish assemblages in both data sets. One measure of lake isolation explained some residual variation in species richness in both regions. Top predator presence was a significant predictor of richness of other fishes in one region. Examination of idiosyncratic species suggested that top predators may have affected community structure in both regions. Main conclusions Lake size was the strongest predictor of fish community nestedness in these regions. Although we found mixed results with respect to the effect of top predator presence, our study demonstrates that it can affect assemblage nestedness, and that spatial variables may influence the importance of predation as a causal mechanism.
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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 | 0.000 |
| 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) | 0.000 | 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".