Temporal Changes in Water Quality with Increasing Ambient Temperatures Affect the Distribution and Relative Abundance of 10 Species of Balitorid Fishes in Small Streams of Eastern Thailand
Bibliographic record
Abstract
Stream degradation increases with high anthropogenic activity and climate variability, while declines occur in biodiversity. However, few studies have been undertaken on tropical waterways, a major impediment to biodiversity conservation. The present study was conducted on 95 relatively pristine small streams in Eastern Thailand with 10 reasonably uncommon species of balitorid fishes. Measurements were made of 21 physical and chemical factors and the substrate particle size. Stepwise regression identified the direct importance of substrate particle size and nitrate on the species’ richness of balitorids, whereas its abundance was negatively related with iron concentrations. A Canonical Correspondence Analysis identified three fish groups: the 1st group was negatively correlated with ammonia and positively correlated with dissolved silica, the 2nd group was positively correlated with substrate particle size and negatively correlated with stream ambient temperature and ammonia concentration, and the 3rd group was negatively correlated with low dissolved silica, respectively. The results of this study may indicate the vulnerability of balitorids under climate warming and anthropogenic pressure that alter the water physicochemical factors and river degradation including the substrate type. Thus, a conservation framework should be provided regarding the limits for water temperature, ammonia, and iron in Thailand’s Water Quality Criteria to better protect its freshwater ecosystem. Balitorid is a potential bioindicator for evaluating the river temperature effect in combination with ammonia nutrient stressors as long as the way-of-life habits of the species are taken into account.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".