Analysing the contribution of intermittent rivers to beta diversity can improve freshwater conservation in Mediterranean rivers
Bibliographic record
Abstract
Abstract In Mediterranean climate regions, intermittent rivers (IRs) harbor highly dynamic communities with species and trait composition changing over time and space. Simultaneously considering multiple biodiversity facets and a spatiotemporal perspective is, therefore, key to developing effective conservation strategies for these ecosystems. We studied the spatiotemporal dynamics of aquatic macroinvertebrates in rivers of the western Mediterranean Basin by analysing (1) the taxonomic and functional richness and the local contribution to beta diversity (LCBD; measured considering taxonomic and functional facets) of perennial rivers and IRs over five sampling times, and (2) their relation with flow intermittence, local environmental uniqueness, and the number of anthropogenic impacts. Both analyses were also conducted for the subset of data including only IRs to compare values between their flowing and disconnected pool phases. According to our results, taxonomic and functional richness tended to be higher in perennial rivers than in IRs, while taxonomic and functional LCBD tended to be higher in IRs than in perennial rivers. When comparing IR sites over time, higher values of taxonomic and functional LCBD corresponded mostly to their disconnected pool phase. Flow intermittence, the number of anthropogenic impacts and the environmental uniqueness were significant predictors of taxonomic and functional richness, but only flow intermittence was an important predictor of taxonomic LCBD. For the IR-only data subset, disconnected pool permanence was the main predictor explaining spatiotemporal patterns. Our results highlight the importance of IRs to biodiversity conservation of Mediterranean climate rivers, especially during the disconnected pool phase, suggesting that these ecosystems cannot be ignored in conservation planning strategies.
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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 | 0.001 |
| 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".