Temperature drives local contributions to beta diversity in mountain streams: Stochastic and deterministic processes
Bibliographic record
Abstract
Abstract Aim Community variation (i.e. beta diversity) along geographical gradients is of substantial interest in ecology and biodiversity reserves in the face of global changes. However, the generality in beta diversity patterns and underlying processes remains less studied across trophic levels and geographical regions. We documented beta diversity patterns and underlying ecological processes of stream bacteria, diatoms and macroinvertebrates along six elevational gradients. Locations Asia and Europe. Methods We examined stream communities using molecular and morphological methods. We characterised community uniqueness with local contributions to beta diversity (LCBD), and investigated the drivers of its geographic patterns using Mid‐Domain Effect (MDE), coenocline simulation, Raup‐Crick null model approach, and through comparisons to environmental factors. MDE is a stochastic model by considering species elevational range, while coenocline simulation is a deterministic model by considering species niche optima and tolerance. The null model provides possible underlying mechanisms of community assembly with the degree to which deterministic processes create communities deviating from those of null expectations. Results Across all taxa, we revealed a general U‐shaped LCBD‐elevation relationship, suggesting higher uniqueness of community composition at both elevational ends. This pattern was confirmed and could be explained by both stochastic and deterministic models, that is, MDE and coenocline simulation, respectively, and was supported by the dominance of species replacement. Temperature was the main environmental factor underlying elevational patterns in LCBD. The generalists with broad niche breadths were key in maintaining community uniqueness, and the higher relative importance of deterministic processes resulted in stronger U‐shaped patterns regardless of taxonomic group. Conclusions Our synthesis across both mountains and taxonomic groups clearly shows that there are consistent elevational patterns in LCBD among taxonomic groups, and that these patterns are explained by similar ecological mechanisms, producing a more complete picture for understanding and bridging the spatial variation in biodiversity under changing climate.
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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 | 0.000 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".