Variation in reciprocal subsidies between lakes and land: perspectives from the mountains of California
Bibliographic record
Abstract
Lakes are connected to surrounding terrestrial habitats by reciprocal flows of energy and nutrients. We synthesize data from California’s mountain lake catchments to investigate how these reciprocal subsidies change along an elevational gradient and with the introduction of a top aquatic predator. At lower elevations, well-developed terrestrial vegetation provides relatively large inputs of organic material to lakes, whereas at higher elevations, the paucity of terrestrial vegetation provides minimal organic input but allows for higher inputs of inorganic nitrogen. There are also pronounced elevational patterns in amphibians and aquatic insects, which represent important vectors for resource flows from lakes back to land. The introduction of trout can reduce this lake-to-land resource transfer, as trout consume amphibians and aquatic insects. We propose a conceptual model in which within-lake processes influence terrestrial consumers at higher elevations, while terrestrial inputs govern within-lake processes at lower elevations. This model contributes to a more general understanding of the connections between aquatic and terrestrial habitats in complex landscapes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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 source (direct Gemma or distilled Codex), 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".