Metacommunity phylogenetics: separating the roles of environmental filters and historical biogeography
Bibliographic record
Abstract
Biogeographical, evolutionary and ecological processes interact to regulate patterns in metacommunities. However, as there are few quantitative methods for evaluating their joint effects, resolving this interaction is difficult. We develop a method that aims to evaluate the interaction between phylogenetic structure, historical biogeographic events and environmental filtering in driving species distributions in a large-scale metacommunity. Using freshwater zooplankton as a case study, we contrast the phylogenetic metacommunity structure of calanoid copepods and an ecologically similar but more vagile group, daphniids, in the northeastern US. We find that legacies of historical biogeographical events have strongly constrained calanoid distributions within this area, but that adaptation to different water chemistry and lake morphology drives the metacommunity structure of daphniids. Our findings show that biogeographic history and metacommunity processes jointly regulate community structure in these lakes and suggest that this also depends on factors that affect the colonization rate of different types of organisms.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.001 |
| 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 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".