Winter in water: differential responses and the maintenance of biodiversity
Bibliographic record
Abstract
The ecological consequences of winter in freshwater systems are an understudied but rapidly emerging research area. Here, we argue that winter periods of reduced temperature and light (and potentially oxygen and resources) could play an underappreciated role in mediating the coexistence of species. This may be especially true for temperate and subarctic lakes, where seasonal changes in the thermal environment might fundamentally structure species interactions. With climate change already shortening ice-covered periods on temperate and polar lakes, consideration of how winter conditions shape biotic interactions is urgently needed. Using freshwater fishes in northern temperate lakes as a case study, we demonstrate how physiological trait differences (e.g. thermal preference, light sensitivity) drive differential behavioural responses to winter among competing species. Specifically, some species have a higher capacity for winter activity than others. Existing and new theory is presented to argue that such differential responses to winter can promote species coexistence. Importantly, if winter is a driver of niche differences that weaken competition between, relative to within species, then shrinking winter periods could threaten coexistence by tipping the scales in favour of certain sets of species over others.
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 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 | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".