Post-fire forest recovery at high latitudes: tree regeneration dominated by fire-adapted, early-seral species increases with latitude
Bibliographic record
Abstract
Abstract Key message Above 40° N/S, increasing latitude is linked to greater post-fire tree regeneration. However, species dominance shifts from conifers to short-lived deciduous trees, which may negatively impact flora, fauna, and ecosystem services dependent on coniferous forests. These results were primarily driven by studies from North America, highlighting the need for more research that directly measures post-fire forest recovery in other high-latitude regions. Context As the size and frequency of wildfires increase across many regions, high-latitude forests may be at particular risk for decreases in regeneration and state shifts post-fire. Aims Through this systematic review, we sought to determine the general relationship between post-fire tree regeneration densities and latitude in forests above 40° N/S. We expected regeneration densities post-fire would decrease with increasing latitude, and that forest regeneration would be negatively impacted by high burn severities, forest management, harsh site conditions, and unprotected microsites. We also anticipated that light-demanding species with adaptations to fire would replace shade-tolerant species that lack such adaptations post-fire. Methods We conducted a literature search that returned over 4500 articles. We selected those that directly measured post-fire regeneration at or above 40° N/S and retained 93 articles for analysis. Fire characteristics, pre- and post-fire tree species compositions and regeneration densities, and regeneration predictors were then extracted from the retained articles. We fit linear mixed models to post-fire regeneration density with latitude and species traits as explanatory variables and also explored the significance and magnitude of predictors that informed post-fire tree species response. Results Contrary to our expectations, post-fire regeneration increased significantly with latitude. High burn severities and unprotected microsites had negative impacts on post-fire regeneration; higher elevations and more prolific pre- or post-fire reproduction were positively correlated with post-fire regeneration, while management of any type did not have an impact. Conclusion Although forests are regenerating after wildfires at the most extreme latitudes included in this study (above 55° N), regeneration is often limited to only a handful of genera: aspen ( Populus ) and birch ( Betula ), for example. Regeneration was less abundant at the lower range of our study area. Certain lower latitude forests that occupy marginal habitats are under increasing stress from drier, warmer conditions that are exacerbated by wildfires. Results were largely driven by studies from Canada and the USA and may not be applicable to all high-latitude forests.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.002 |
| 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".