Individual‐based models of community assembly: Neighbourhood competition drives phylogenetic community structure
Bibliographic record
Abstract
Abstract It is now commonplace for community ecologists to infer assembly processes from the evolutionary relatedness of co‐occurring species. Such inferences, however, have typically depended on assembly theories that assume competitive equilibrium and that are species based. In reality, all natural communities are dynamic, particularly during the course of succession, and the ecological interactions which drive phylogenetic community structure actually occur among neighbouring individuals rather than species. To bridge this gap between theory and reality, we examine how colonisation, competition, and consequent replacement of individuals translate into phylogenetic community structure by using an individual‐based model. The model we use assumes a trade‐off between competition and colonisation abilities and that the points where species fall on the trade‐off curve are phylogenetically conserved. We find that the phylogenetic alpha diversity of a given community will be equal to or greater than the null expectation generated by randomly drawing individuals from communities at the same time step (i.e. phylogenetic overdispersion). This pattern results from the combination of interspecific differences in colonisation ability and neighbourhood competition that lead to individuals being regularly distributed in two‐dimensional space. We also show that phylogenetic beta diversity increases with increasing temporal differences between two communities. However, when this positive relationship is analysed only among the communities at close time steps, it becomes insignificant as they approach competitive equilibrium. We find similar patterns for functional alpha and beta diversity when phylogeny is replaced with functional traits. Synthesis. Though questions concerning community assembly have often been spatially framed, our model shows that the span of the time frame can also affect, or even reverse, inferences about assembly processes. Our model also implies that a shift in the frame of reference from species to individuals brings a new perspective to community assembly. Careful consideration of non‐equilibrium and individual‐level aspects provides better insights into the consequences of the evolutionary and functional similarities of individuals on community assembly.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".