Evaluating the Influence of Climatic and Hydrologic Variables on Fish Communities in Channelised Agricultural Headwater Streams in the Midwestern <scp>USA</scp>
Bibliographic record
Abstract
ABSTRACT Channelised headwater streams are common in agricultural catchments in the Midwestern United States, Canada and Europe and serve as fish habitat despite being impacted by agriculture. The influence of climatic variables on fish communities in channelised agricultural headwater streams has not been documented. Our research objectives were to identify the relationship between fish community structure and climatic variables in channelised agricultural headwater streams in northeast Indiana and central Ohio and to determine if fish community structure is better predicted by climatic variables or stream variables. We sampled fishes, compiled climatic data and measured water temperature and several stream hydrologic variables from 10 channelised agricultural headwater streams in northeast Indiana and central Ohio for 14 years. Mixed effects modelling indicated that fish diversity and relative abundance of warmwater fishes, coolwater fishes, intermediate tolerant fishes, Cyprinidae, Percidae, invertivores and brood hiders were positively correlated ( p < 0.05) with precipitation and fish abundance and the relative abundance of planktivores and guarder substrate choosers were negatively correlated ( p < 0.05) with precipitation. Fish abundance and the relative abundance of invertivores, planktivores and brood hiders were positively correlated ( p > 0.05) with air temperature. In general, stream variables were better predictors of fish community structure than climatic variables. Our results provide insights into the relationships of fish communities with climatic and stream variables in channelised agricultural headwater streams that can be applied to help prioritise monitoring and management strategies for these small streams.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".