Burn Severity Does Not Significantly Alter Pollen Abundance Across a Burn Matrix Four Years Post Wildfire in Sub-Boreal Forests of British Columbia, Canada
Bibliographic record
Abstract
Wildfires have had measurable impacts on pollen dispersal in some areas; both facilitation and potential barriers to pollen movement have been reported. These dispersal dynamics in turn affect population genetics and reestablishment of seed-producing plants, at times significantly impacting the successional trajectory of the area in question. However, research on post-fire pollen distribution and occurrence is lacking for the boreal and sub-boreal forests of western Canada, and many communities that have been heavily impacted by wildfire remain concerned about the future forest landscape of these areas. We analyzed post-fire pollen samples from unburned and severely burned sub-boreal spruce stands in north-central British Columbia four years after a major wildfire. We used pollen traps to measure the occurrence and abundance of pollen types from four important plant families: Asteraceae, Ericaceae, Onagraceae, and Pinaceae families, to address specific concerns of the First Nation communities with territories overlapping the Shovel Lake wildfire burned area. Pinaceae pollen was found across all traps and was observed as the most dominant pollen type at all study sites, while pollen belonging to other families was found less frequently. No significant differences in pollen occurrence or abundance were found between burn severities, despite differences in the plant communities; however, plant and pollen abundance were found to be positively correlated to one another. These results may indicate that, as previously noted in other conifer-dominated forests, openings of the forest landscape by wildfire may facilitate rather than hinder pollen movements. Understory species should be studied in more detail as the effect of wildfire on pollen transport may vary between taxa and pollination syndromes.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".