Population and community variability in randomly fluctuating environments
Bibliographic record
Abstract
The prediction that environmental fluctuations may destabilise populations and yet stabilise aggregate community properties has remained largely untested. We examined population and community stability under constant and fluctuating temperatures in simple planktonic assemblages of differing algal richness. Temperature dependent resource competition produced a highly asymmetric community structure where algal community biomass was dominated by one species. For a given level of species richness, temperature fluctuations induced lower community covariance and thus stabilised community biomass. However, increasing algal species richness increased the variability of population abundance and growth rates, as well as population and community variability. Consumer dynamics were directly destabilised by environmental fluctuations. These results confirm recent theoretical studies suggesting a stabilising effect of environmental fluctuations at the community level. However, they also support the theoretical prediction that increasing species richness may be of limited value for community stability, most especially in asymmetric communities, when competition directly affects population variability.
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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 | 0.000 |
| 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".