Algal communities in human‐impacted stream ecosystems suffer beta‐diversity decline
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Bibliographic record
Abstract
ABSTRACT Human‐mediated geomorphic degradation of streams and rivers is a serious environmental problem with negative effects on aquatic biota and social infrastructure. Billions of dollars are spent for stream restoration in the USA alone, but it is still unknown how algal diversity is affected by these efforts. In this investigation, we studied a geomorphically stable and heterogeneous reach and two degraded and homogeneous reaches of Batavia Kill, a highland stream in New York, USA. Spatial surveys of algae and geomorphic conditions were conducted in all three reaches for 2 years. After the first year of study, one of the two unstable reaches was subjected to a large‐scale streambed restoration. Species–area relationships (SAR) were examined for the first time in local algal communities of stream periphyton. Alpha‐ and gamma‐diversity, which represent the species richness at a sample and reach level, respectively, and cell density, were also explored. In all reaches, SAR were fitted with semi‐log models, which revealed that the rate of increase of species richness with area, i.e. algal beta‐diversity, was significantly higher in the geomorphically stable reach than in the two degraded reaches. Gamma‐diversity followed the same trend, whereas alpha‐diversity and cell density were significantly higher in the unstable reaches. Restoration significantly increased the heterogeneity of conditions, including depth and particle size. From all studied community descriptors, restoration had a benign influence on algal beta‐ and gamma‐diversity; however, beta‐diversity remained the highest in the stable reference reach and this difference was significant. Our results provide guidelines for the use of periphytic algae in future bioassessments of stream bank restoration. Community properties such as species richness and organismal density, which are common metrics of ecosystem health, may be inappropriate in stream restoration surveys; instead diversity measures, often overlooked in applied ecology, e.g. beta‐diversity, should be given full consideration.
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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 | 0.000 | 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 | 0.004 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.006 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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 it