A comparison of phylogenetic and species beta diversity measures describing vegetation assemblages along an elevation gradient
Bibliographic record
Abstract
Abstract Question Ecologists have long been interested in the delineation and description of plant communities but have only recently included phylogenetic data into these analyses. Here, we assess whether species‐based dissimilarities (beta diversity, BD) and more recent phylogenetic beta diversity (PhBD) measures are correlated with dissimilarities among sites based on abiotic variables. Additionally, we examine whether BD and PhBD measures aggregate sites into clusters that reflect their environmental attributes. Assuming phylogenetic conservatism in abiotic niche preferences, we predict PhBD dissimilarity matrices will correlate to those based on abiotic site variables, and that clusters determined by PhBD will more closely match to assemblages clustered by abiotic environment than will clusters determined by species BD. Location Mount Irony, Labrador in the Eastern Canadian subarctic. Methods We combine vascular plant co‐occurrence data collected from an elevation gradient on Mount Irony with information on phylogenetic relatedness to compare site dissimilarities based on abiotic variables with those estimated on measures of BD and PhBD. We also examine whether clusters based on BD and PhBD resemble clusters based on abiotic variables, and investigate whether similarly clustered sites are composed of species with similar evolutionary histories. Results We found significant correlations among the dissimilarity matrices and ordinations for the abiotic variables, BD and PhBD; however, neither BD nor PhBD aggregated assemblages into clusters that reflected their environmental differences. Further, we found no evidence that species within clusters were any more closely related than expected by chance. We observed similar patterns when communities were defined by all vascular plants and only angiosperms. Conclusions The correlations among site dissimilarities based on abiotic variables, BD and PhBD suggest environmental filtering; however, sites clustered by BD and PhBD did not resemble those clustered by abiotic variables, indicating that the added value of phylogenetic data for local scale analyses might be limited.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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 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".