Temporal variations of the multifaceted biodiversity and assembly mechanisms in lake fish assemblages
Bibliographic record
Abstract
Abstract Understanding long‐term changes in fish diversity and community assembly rules is crucial for freshwater conservation. Growing evidence indicates that studying functional and phylogenetic diversity beyond purely taxonomic considerations can provide different but complementary information on community assembly. Here, the taxonomic, functional, and phylogenetic β‐diversity of fish communities, as well as the community assembly mechanisms, were explored in five impounded lakes of the China's South‐to‐North Water Diversion Project (SNWDP) from the 1980s to the 2010s. We found that (1) there was an obvious trend of species homogenization in the five impounded lakes, but the long‐term transformations of different dimensional β‐diversity were divergent; (2) water quality and land use variables have greater impacts on multidimensional β‐diversity; and (3) community assembly process in taxonomic and functional dimensions were dominated by random process in both periods, while shifting from limiting similarity to habitat filtering in the phylogenetic dimension. These results highlight that functional and phylogenetic diversity are important additional ecological indices for assessing the patterns of fish diversity in lakes.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".