Freshwater zooplankton metapopulations and metacommunities respond differently to environmental and spatial variation
Bibliographic record
Abstract
Theory predicts that population genetic structure and metacommunity structure are linked by the common processes of drift and migration, but how population genetic structure and metacommunity structure are related in nature is still unknown. Deeper understanding of the processes influencing both genetic and community diversity is vital for better predicting how environmental change will impact biodiversity patterns. We examined how crustacean zooplankton and rotifer species' metapopulation genetic structure and metacommunities respond to environmental and spatial variation both within and across four regions of boreal Canada. Metapopulation and metacommunity variation partitioning results were compared within and across the four regions. Metapopulations and metacommunities responded differently to environmental variation and spatial structure both within and across regions, as metapopulations were influenced by different environmental variables compared to metacommunities. At larger spatial scales both metapopulations and metacommunities exhibited greater spatial and environmental structuring, again responding to a different subset of environmental variables. Our findings suggest that even though both genetic and species diversity are linked by the same processes, regional variation in environmental characteristics and spatial structure influence resulting biodiversity patterns differently. To date, no other empirical research has explored relationships between entire metapopulation and metacommunity assemblages at large regional spatial scales.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 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".