Advancing and reversing succession as a function of time since fire and insect outbreaks: An 18 year in situ remeasurement of changes in forest composition
Bibliographic record
Abstract
Abstract Aims In the boreal mixedwood, fire initiates forest succession; however, over time other disturbances such as insect outbreaks cause pulses of mortality and opportunities for recruitment of shade‐intolerant species. Questions What are the respective roles of time since fire and insect outbreaks in driving directional, vs cyclical and retrogressive succession? Do assessments from direct measurements and chronosequence approaches converge? We hypothesise that the chronosequence approach will accurately characterise large‐scale compositional patterns especially in younger stands and that direct measurements will better describe small‐scale, non‐directional changes in succession. Location Boreal mixed wood of northwestern Quebec (79°1′ W, 48°30′ N). Methods We sampled 469 plots over an 18‐year interval (in 1991 and 2009) in mixed hardwood/conifer forests to observe in situ the changes in stands having originated from seven fires covering a 249‐year chronosequence. Results The combination of the remeasurement and chronosequence analyses validates predictions of forest succession. Our results indicate that time since last fire is the dominant factor explaining forest succession for the first 150 years after fire and globally at the scale of the entire forest, although smaller‐scale disturbances such as spruce budworm outbreaks can change the course of forest succession, especially at stand scales. Conclusion While time since fire is the dominant driver of forest succession in younger forests, secondary disturbances, such as spruce budworm outbreaks, can advance or reverse forest succession in older forests. This study also serves as a validation of the overall patterns described in spatial chronosequence approaches at the landscape level in fire‐dominated systems but highlights that local succession may deviate from the overall pattern especially in older forests or in forests affected by non‐stand re‐initiating intermediate disturbances.
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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 | 0.001 |
| Open science | 0.000 | 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".