Forests fuel fish growth in freshwater deltas
Bibliographic record
Abstract
Aquatic ecosystems are fuelled by biogeochemical inputs from surrounding lands and within-lake primary production. Disturbances that change these inputs may affect how aquatic ecosystems function and deliver services vital to humans. Here we test, using a forest cover gradient across eight separate catchments, whether disturbances that remove terrestrial biomass lower organic matter inputs into freshwater lakes, thereby reducing food web productivity. We focus on deltas formed at the stream-lake interface where terrestrial-derived particulate material is deposited. We find that organic matter export increases from more forested catchments, enhancing bacterial biomass. This transfers energy upwards through communities of heavier zooplankton, leading to a fourfold increase in weights of planktivorous young-of-the-year fish. At least 34% of fish biomass is supported by terrestrial primary production, increasing to 66% with greater forest cover. Habitat tracers confirm fish were closely associated with individual catchments, demonstrating that watershed protection and restoration increase biomass in critical life-stages of fish. Vegetation close to streams and lakes provides organic matter to aquatic ecosystems. Here, the authors show that the dense forest cover around lakes feeds the near-shore lake food web through organic matter subsidies, leading to faster growth in planktivorous fish.
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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 | 0.001 | 0.001 |
| 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".