Spatial scale affects the importance of deterministic and stochastic factors in the structuring of tadpole assemblages in Brazilian Cerrado
Bibliographic record
Abstract
Many factors influence the structure of natural assemblages. Species interaction and environmental factors may generate deterministic patterns, whereas dispersal and ecological drift may generate stochastic patterns. We used pond systems to understand how deterministic and stochastic factors interact and influence tadpole assemblages at different spatial scales. We used variation partitioning and a co-occurrence analysis to evaluate how local environment heterogeneity, species interaction, and spatial variables affected species composition at local and regional scales in Brazilian savanna. Both deterministic and stochastic processes were important to explain tadpole distribution at regional scale, but with a greater contribution of stochastic factors. At local scales, environmental and niche traits were more important to explain tadpole distribution into the habitats. We demonstrate that in Brazilian Cerrado, species composition can be explained by the "MacArthur paradox", in which niche processes are important at local scales, whereas dispersal constraints and population processes lead to stochastic patterns in species distribution at large spatial scales.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 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".