Local and regional drivers of taxonomic homogenization in stream communities along a land use gradient
Bibliographic record
Abstract
Abstract Aim The interaction of land use with local versus regional processes driving biological homogenization (β‐diversity loss) is poorly understood. We explored: (a) stream β‐diversity responses to land cover (forest versus agriculture) in terms of physicochemistry and physicochemical heterogeneity; (b) whether these responses were constrained by the regional species pool, i.e. γ‐diversity, or local assembly processes through local (α) diversity; (c) whether local assembly operated through the regional species abundance distribution (SAD) or intraspecific spatial aggregation; and (d) the dependence on body size, dispersal capacity and trophic level (producer versus consumer). Location USA, Canada and France. Time period 1993–2012. Major taxa studied Stream diatoms, insects and fish. Methods We analysed six datasets totalling 1,225 stream samples. We compared diversity responses to eutrophication and physicochemical heterogeneity in forested versus agricultural streams with regression methods. Null models quantified the contribution of local assembly to β‐diversity (β‐deviance, β DEV ) for both types of land covers and partitioned it into fractions explained by the regional SAD (β SAD ) versus aggregation (β AGG ). Results Eutrophication explained homogenization and more uneven regional SADs across groups, but local and regional biodiversity responses differed across taxa. The β DEV was insensitive to land use. The β SAD largely exceeded β AGG and was higher in agriculture. Main conclusions Eutrophication but not physicochemical heterogeneity of agricultural streams underlay β‐diversity loss in diatoms, insects and fish. Agriculture did not constrain the magnitude of local versus regional effects on β‐diversity but controlled the local assembly mechanisms. Although the SAD fraction dominated in both land covers, it increased further in agriculture at the expense of aggregation. Notably, the regional SADs were more uneven in agriculture, exhibiting excess common species or stronger dominance. Diatoms and insects diverged from fish in terms of biodiversity, SAD shape and β DEV patterns, suggesting an overriding role of body size and/or dispersal capacity compared with trophic position.
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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 | 0.001 | 0.002 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".