Warming induces synchrony and destabilizes experimental pond zooplankton metacommunities
Bibliographic record
Abstract
The spatial insurance hypothesis predicts that intermediate rates of dispersal between patches in a metacommunity allow species to track favourable conditions, preserving diversity and stabilizing biomass at local and regional scales. However, theory is unclear as to whether dispersal will provide spatial insurance when environmental conditions are changing directionally. In particular, increased temperatures as a result of climate change are expected to cause synchronous growth or decline across species and communities, and this has the potential to erode the stabilizing compensatory dynamics facilitated by dispersal. Here we report on an experimental test of how dispersal affects the diversity and stability of metacommunities under warming using replicate two‐patch pond zooplankton metacommunities. Initial differences in local community composition and abiotic conditions were established by seeding each patch in the metacommunities with plankton and sediment from one of two natural ponds that differed in water chemistry and species composition. We exposed metacommunities to a 2°C increase in average ambient temperature, crossed with three rates of dispersal (none, intermediate, high). In ambient conditions, intermediate dispersal rates preserved diversity and stabilized metacommunities by promoting spatially asynchronous fluctuations in biomass, especially between local populations of the dominant genus, Ceriodaphnia . However, warming synchronized their populations so that these effects of dispersal were lost. Furthermore, because the stabilizing effect of dispersal was primarily due to asynchronous fluctuations between populations of a single genus, metacommunity biomass was stabilized, but dispersal did not stabilize local community biomass. Our results show that dispersal can preserve diversity and provide stability to metacommunities, but also show that this benefit can be eroded when warming is directional and synchronous across patches of a metacommunity, as is expected with climate warming.
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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) | 0.001 | 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 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".