Regional-scale hydrologic settings buffer black spruce regeneration in the presence of post-fire droughts
Bibliographic record
Abstract
Climate change is increasing the frequency of droughts and wildfires, reducing tree recruitment, and altering post-fire species composition. In Canada’s western boreal forests, postfire recruitment, particularly of drought-intolerant coniferous species like black spruce, has declined in recent decades to the benefit of early-successional species like jack pine and trembling aspen. Groundwater supplied to forests via adjacent peatlands may help to resist such reductions in recruitment and compositional shifts, particularly during droughts. The degree to which peatlands buffer adjacent forests from drought-induced regeneration failure may therefore depend on topographic position and soil texture, factors that govern groundwater connectivity. I examined how these topoedaphic factors influence upland tree regeneration from post-fire drought, defined in this study as the post-fire climate moisture deficit across sampled fires. Since higher-positioned peatlands (bogs, poor fens) are mostly fed by precipitation, they are more vulnerable to drought compared to fen-like peatlands at lower topographic positions that are fed by groundwater. I therefore hypothesized that regenerating forest density, growth, and composition at lower topographic positions would be buffered from post-fire drought by water sources from the adjacent fen across a range of soil textures. Specifically, I predicted that tree density, volume, and proportions of black spruce should decline with high topographic positions, favoring instead jack pine and aspen following post-fire drought. I tested this prediction by measuring 58 post-fire upland forest stands ranging from 5 – 20-years old that experienced wet or dry post-fire weather. Study sites spanned local (relative to adjacent peatland) and regional topographic position (relative to a regional low) gradients. I used generalized linear mixed effects models to test interactions between these local and regional topographic positions, soil texture, and post-fire climate. I found significant reductions in regenerating black spruceiii proportions at high regional topographic positions across fine- and coarse-textured soils with post-fire drought. Total regeneration (stem density), tree volume (basal area), and species of jack pine and aspen showed no correlations with post-fire drought. This study highlights that hydrologically well-connected areas of Alberta’s boreal forest may act as refugia from drought and fire for drought-intolerant black spruce, and that more predominant upland jack pine and aspen species appeared to be resilient under the current fire regime. Larger scale ecohydrological dynamics therefore interact with forest regeneration and should be considered to identify areas that may resist altered post-fire trajectories.
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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 | 0.000 | 0.000 |
| 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".