Lineage-specific phylogenetic structure of boreal habitats suggests different assembly processes across phylogenetic and spatial scales
Bibliographic record
Abstract
The phylogenetic distance among species in a community (community phylogenetic structure) has been used to infer deterministic and stochastic assembly processes, albeit with criticisms. The effect of phylogenetic scale (old versus young lineages) and spatial scale on measures of community phylogenetic structure are rarely tested simultaneously especially in the boreal biome, yet are essential to unravel different assembly processes that might operate in a community. We examined lineage-specific phylogenetic structure for six vascular plant communities defined at the habitat scale (arctic-alpine barren, bog, fen, kalmia barren, limestone barren, and serpentine barren) on the island of Newfoundland, Canada, and the phylogenetic structure of plant communities defined at a plot scale (72 plots x 1m2). Contrary to the expectation under the stress-dominance hypothesis of phylogenetic clustering in challenging boreal environments, the majority of clades across the six boreal habitats had random phylogenetic structure. However, we observed a shift from phylogenetic clustering at the deepest nodes of the angiosperms to no phylogenetic structure at shallower nodes (<110 mya), suggesting changes in assembly processes with phylogenetic scale within a habitat, and the potential role for deterministic processes at deep nodes. The random phylogenetic structure of 1m2 plots and our modeling effort to test the effect of an environmental stress gradient on community composition suggest that a complex set of stochastic and deterministic factors is responsible for species assembly at this fine spatial scale, not just abiotic filtering in hostile environments like the serpentine as predicted by the stress-dominance hypothesis. The interpretation of phylogenetic structure metrics did not change when considering species abundances or when polytomies were resolved. Taken together, inference of assembly processes must be lineage-, habitat- and spatial scale-specific, supplemented with knowledge on trait role and evolution for which we outline future research hypotheses.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".