SPECTRAL ANALYSIS UNMASKS SYNCHRONOUS AND COMPENSATORY DYNAMICS IN PLANKTON COMMUNITIES
Bibliographic record
Abstract
Community biomass is often less variable than the biomasses of populations within the community, yet attempts to implicate compensatory dynamics between populations as a cause of this relationship often fail. In part, this may be due to the lack of appropriate metrics for variability, but there is also great potential for large-scale processes such as seasonality or longer-term environmental change to obscure important dynamics at other temporal scales. In this study, we apply a scale-resolving method to long-term plankton data, to identify the specific temporal scales at which community-level variability is influenced by synchrony or compensatory dynamics at the population level. We show that variability at both the population and community level is influenced strongly by a few distinct temporal scales: in phytoplankton, ciliate, rotifer, and crustacean communities, synchronous dynamics are predominant at most temporal scales. However, in phytoplankton and crustacean communities, compensatory dynamics occur at a sub-annual scale (and at the annual scale in crustaceans) leading to substantial reductions in community-level variability. Aggregate measures of population and community variability do not detect compensatory dynamics in these communities; thus, resolving their scale dependence unmasks dynamics that are important for community stability in this system. The methods and results presented herein will ultimately lead to a better understanding of how stability is achieved in communities.
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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 | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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 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".