Mosses and vascular plants show diverging diversity patterns along a latitudinal gradient in boreal bogs and fens
Bibliographic record
Abstract
Abstract Questions The latitudinal biodiversity gradient; i.e., the increase in biodiversity towards the equator, is one of the most prominent biodiversity patterns. Nevertheless, many questions remain to be answered about the influence of multiple environmental factors on the latitudinal biodiversity gradient, especially for mosses, and the functional diversity of mosses and vascular plants. This study aims at evaluating the influence of latitude, climate, environmental variables, and habitat types (bog vs fen) on taxonomic and functional diversity (α‐diversity and β‐diversity) and the composition of vascular plant and moss species. Location 49° N to 55° N in Northwestern Quebec, Canada. Taxon Mosses, vascular plants. Methods We used a database containing 376 phytosociological plots (400 m 2 ) sampled in boreal peatlands located along a 600‐km latitudinal gradient. We evaluated changes in α‐diversity and β‐diversity in response to latitude, longitude, climate, and local abiotic variables for both taxonomic groups using linear mixed effect models. We evaluated the effects of these variables on taxonomic and functional composition using variance partitioning by redundancy analysis. Results Moss diversity increased with latitude, although the effects were masked by environmental variables, whereas vascular plant diversity decreased with latitude in fens and did not vary with latitude in bogs. We observed a decrease in taxonomic and functional uniqueness with latitude. Moss and vascular plant taxonomic and functional composition were primarily structured by contrasting local conditions in bogs and fens, whereas climatic variations along the latitudinal gradient played a secondary role. Conclusions Our results highlight the contrasting biodiversity patterns in both peatland types and the importance of local habitat conditions in structuring vascular plant and moss diversity. These patterns varied depending on the diversity indicator used, as α‐ and β‐diversity and functional and taxonomic diversity were often decoupled. Future studies should therefore include more than one diversity indicator and consider the differences between ecosystems and taxon groups.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 teacher head, 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".