Reach-Scale Land Use Drives the Stress Responses of a Resident Stream Fish
Bibliographic record
Abstract
Abstract To date, relatively few studies have tried to determine the practicality of using physiological information to help answer complex ecological questions and assist in conservation actions aimed at improving conditions for fish populations. In this study, the physiological stress responses of fish were evaluated in-stream between agricultural and forested stream reaches to determine whether differences in these responses can be used as tools to evaluate conservation actions. Creek chub Semotilus atromaculatus sampled directly from forested and agricultural stream segments did not show differences in a suite of physiological indicators. When given a thermal challenge in the laboratory, creek chub sampled from cooler forested stream reaches had higher cortisol levels and higher metabolic stress responses to thermal challenge than creek chub collected from warmer and more thermally variable agricultural reaches within the same stream. Despite fish from agricultural and forested stream segments having different primary and secondary stress responses, fish were able to maintain homeostasis of other physiological indicators to thermal challenge. These results demonstrate that local habitat conditions within discrete stream reaches may impact the stress responses of resident fish and provide insight into changes in community structure and the ability of tolerant fish species to persist in agricultural areas.
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 | 0.000 |
| 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) | 0.002 | 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".