Population variability is lower in diverse rock pools when the obscuring effects of local processes are removed
Bibliographic record
Abstract
:Ecological theory predicts that species richness should impact population variability. In contrast, most empirical evidence suggests no or only a weak positive relationship between species richness and population variability. We investigated the hypothesis that the obscuring noise of local processes at small scales such as differences in environmental conditions and species composition may mask the effects of species richness on population variability. Using long-term data on invertebrate populations in rock pools, we considered species richness-population variability relationships using three analytic resolutions in which data for the two key variables, species richness and population variability, were averaged for each population at decreasing levels of resolution to successively remove more noise arising from local processes. Of these levels the resolution most useful in making predictions about the effect of species richness on population variability removed the most noise in population responses arising from local processes. Our results show that populations are less variable in species-rich environments, a finding that reiterates the importance of species richness not only for aggregate properties such as biomass stability, but also for individual species abundances. Comparing results at different resolutions also provides a methodology to identify relevant detail in richness-population variability relationships.
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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 | 0.000 |
| 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".