Material Legacies and Environmental Constraints Underlie Fire Resilience of a Dominant Boreal Forest Type
Bibliographic record
Abstract
Abstract Resilience of plant communities to disturbance is supported by multiple mechanisms, including ecological legacies affecting propagule availability, species’ environmental tolerances, and biotic interactions. Understanding the relative importance of these mechanisms for plant community resilience supports predictions of where and how resilience will be altered with disturbance. We tested mechanisms underlying resilience of forests dominated by black spruce ( Picea mariana ) to fire disturbance across a heterogeneous forest landscape in the Northwest Territories, Canada. We combined surveys of naturally regenerating seedlings at 219 burned plots with experimental manipulations of ecological legacies via seed addition of four tree species and vertebrate exclosures to limit granivory and herbivory at 30 plots varying in moisture and fire severity. Black spruce recovery was greatest where it dominated pre-fire, at wet sites with deep residual soil organic layers, and fire conditions of low soil or canopy combustion and longer return intervals. Experimental addition of seed indicated all species were seed-limited, emphasizing the importance of propagule legacies. Black spruce and birch ( Betula papyrifera ) recruitment were enhanced with vertebrate exclusion. Our combination of observational and experimental studies demonstrates black spruce is vulnerable to effects of increased fire activity that erode ecological legacies. Moreover, black spruce relies on wet areas with deep soil organic layers where other species are less competitive. However, other species can colonize these areas if enough seed is available or soil moisture is altered by climate change. Testing mechanisms underlying species’ resilience to disturbance aids predictions of where vegetation will transform with effects of climate change.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".