Climate teleconnections synchronize <i>Picea glauca</i> masting and fire disturbance: Evidence for a fire‐related form of environmental prediction
Bibliographic record
Abstract
Abstract Synchronous pulses of seed masting and natural disturbance have positive feedbacks on the reproduction of masting species in disturbance‐prone ecosystems. We test the hypotheses that disturbances and proximate causes of masting are correlated, and that their large‐scale synchrony is driven by similar climate teleconnection patterns at both inter‐annual and decadal time scales. Hypotheses were tested on white spruce ( Picea glauca ), a masting species which surprisingly persists in fire‐prone boreal forests while lacking clear fire adaptations. We built masting, drought and fire indices at regional (Alaska, Yukon, Alberta, Quebec) and sub‐continental scales (western North America) spanning the second half of the 20th century. Superposed Epoch Analysis tested the temporal associations between masting events, drought and burnt area at the regional scale. At the sub‐continental scale, Superposed Epoch Analysis tested whether El Niño‐Southern Oscillation (ENSO) and its coupled effects with the Atlantic Multidecadal Oscillation (AMO) in the positive phase (AMO+/ENSO+) synchronize drought, burnt area and masting. We additionally tested the consistency of our synchronization hypotheses on a decadal temporal scale to verify whether long‐term oscillations in AMO+/ENSO+ are coherent to decadal variation in drought, burnt area and masting. Analyses demonstrated synchronicity between drought, fire and masting. In all regions the year before a mast event was drier and more fire‐prone than usual. During AMO+/ENSO+ events sub‐continental indices of drought and burnt area experienced significant departures from mean values. The same was observed for large‐scale masting in the subsequent year, confirming 1‐year lag between fire and masting. Sub‐continental indices of burnt area and masting showed in‐phase decadal fluctuations led by the AMO+/ENSO+. Results support the ‘Environmental prediction hypothesis’ for mast seeding. Synthesis . We provide evidence of large‐scale synchronicity between seed masting in Picea glauca and fire regimes in boreal forests of western North America at both inter‐annual and decadal time scales. We conclude that seed production in white spruce predicts changes in disturbance regimes by sharing the same large‐scale climate drivers with drought and fire. This gives new insides in a mechanism providing a fire‐sensitive species with higher than expected adaptability to changes in climate.
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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 | 0.000 |
| 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) | 0.001 | 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 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".