Drought-driven lake level decline: effects on coarse woody habitat and fishes
Bibliographic record
Abstract
Research testing for the effects of climate change on lentic fishes has focused on changing thermal and dissolved oxygen regimes, but has often overlooked potential influences of altered lake levels on littoral habitat availability and species interactions. Natural littoral structures such as coarse woody habitat (CWH) can be critical to fishes for prey production, refuge, and spawning. Drought-driven lake level declines may strand these structures above the waterline and thereby remove them from littoral zones. A prolonged drought in northern Wisconsin, USA, allowed us to test for effects of lake level decline on CWH and the response of a fish community. During our study (2001–2009), the lake level of Little Rock Lake South declined over 1.1 m and >75% of the previously submerged CWH was lost from the littoral zone. The loss of CWH coincided with the forage fish species (yellow perch, Perca flavescens) falling below detection and reduced growth of the top piscivore (largemouth bass, Micropterus salmoides). Our study highlights the importance of lake level fluctuations as a mechanism by which climate change may affect aquatic ecosystems and species interactions.
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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".