Regional patterns and controlling factors in plant species composition and diversity in Canadian lowland coastal bogs and laggs
Bibliographic record
Abstract
Inventories of natural assemblages of plant species are critical when planning ecological restoration of bogs. However, little is known about the regional variation in plant communities at the margins (laggs) of bogs, even though they are an integral element of raised bog ecosystems. Therefore, we investigated the regional patterns in the plant communities of bogs and laggs, and the factors that control them, for thirteen bogs in coastal British Columbia, Canada. Species richness was significantly higher in the bogs and laggs of the cooler, wetter Pacific Oceanic wetland region. Beta Diversity analyses showed that bogs in the Pacific Oceanic wetland region often shared species with their respective laggs, whereas half of the laggs in the warmer, drier Pacific Temperate wetland region had no species in common with the adjacent bogs and were thus more ecologically distinct from the bog. Primary climatic variables, such as mean annual precipitation, mean annual temperature and latitude, as well as climate-influenced variables, such as pH, peat depth, and Na+ concentrations were the main correlates of plant species composition in the studied bogs. Site-specific factors, particularly depth to water table, and fraction of inorganic material in peat samples, were as strongly related to lagg plant communities as climate, while hydrochemistry appeared to have less influence.
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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 | 0.000 | 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 | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| 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".