Refuge increases food chain length: modeled impacts of littoral structure in lake food webs
Bibliographic record
Abstract
Food chain length (FCL) represents a fundamental metric within ecology because it has implications for ecosystem function and responses to environmental change. Omnivory between linked food chains situated within large ecosystems can increase FCL, whereas overlap of food chains within small or spatially compressed ecosystems is generally thought to decrease FCL. Yet FCL varies widely in small ecosystems and the mechanisms underlying determinants of FCL in these systems is unclear. In small shallow lakes, littoral structure is a predictor of FCL but it is unclear whether this is due to productivity or refuge mechanisms. Here we provide evidence, using consumer resource food web modules parameterized with empirical data, that refuge in spatially compressed ecosystems has the ability on its own to increase the trophic position of top predators by increasing the biomass of top and intermediate predators across a range of common food web module structures. Our results suggest that refuge is an important driver of FCL in small ecosystems, which has implications for determining responses of these systems to environmental change.
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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".