ON THE RELATIONSHIP BETWEEN REGIONAL AND LOCAL SPECIES RICHNESS: A TEST OF SATURATION THEORY
Bibliographic record
Abstract
What are the local community consequences of changes in regional species richness and composition? To answer this question we followed the assembly of microarthropod communities in defaunated areas of moss, embedded in a larger moss "region." Regions were created by combining moss from spatially distinct sites, resulting in regional species pools that differed in both microarthropod richness and composition, but not area. Regional effects were less important than seasonality for local richness. Initial differences in regional richness had no direct effect on local species richness at any time along a successional gradient of 0.5-16 months. The structure of the regional pool affected both local richness and local composition, but these effects were seasonally dependent. Local species richness differed substantially between dates along the successional gradient and continued to increase 16 months after assembly began. To the best of our knowledge, this is the first critical test of saturation theory that experimentally manipulates regional richness. Further, our results failed to support the most important mechanisms proposed to explain the local richness-regional richness relationship. The results demonstrate that complicated interactions between assembly time, seasonality, and regional species pools contribute to structuring local species richness and composition in this community.
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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 | 0.029 | 0.133 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.007 |
| Scholarly communication | 0.001 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".