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Record W4408431420 · doi:10.5194/egusphere-egu25-12457

Warming Tipping Point for tree growth in boreal permafrost landscapes

2025· preprint· en· W4408431420 on OpenAlexaffabout
Raquel Alfaro‐Sánchez, Jennifer L. Baltzer, Sharon L. Smith

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicClimate change and permafrost
Canadian institutionsGeological Survey of CanadaNatural Resources CanadaWilfrid Laurier UniversityCanadian Forest Service
Fundersnot available
KeywordsTipping point (physics)PermafrostTaigaBorealClimate changePhysical geographyTree (set theory)Environmental scienceClimatologyGeographyGeologyForestryOceanographyArchaeologyMathematicsEngineering

Abstract

fetched live from OpenAlex

Boreal ecosystems are warming at three to four times the global average due to Arctic amplification. At these higher latitudes, where plant growth is constrained by low temperatures, climate warming is expected to shift the tree line northward and enhance vegetation productivity.Permafrost thaw is also a major driver of climate-induced landscape changes in the north, significantly impacting tree growth and productivity. Approximately 80% of the boreal biome lies within the permafrost region. With continued global warming, permafrost temperatures will rise, leading to increased thaw rates and a reduction in permafrost extent.Some studies suggest that permafrost thaw may benefit the functioning of overlying forests, primarily due to warmer soils, deeper permafrost tables, and access to newly released resources previously trapped in the frozen ground. However, the combined effects of climate change on growth trajectories in boreal trees remain uncertain. Indeed, satellite and ground-based vegetation studies, including tree-ring analyses, reveal substantial inconsistencies across the boreal and Arctic biomes, with some regions showing accelerated growth and greening, while others exhibit reduced growth and browning.Here, we assembled a network of tree-ring data from sites with a historical record of permafrost thaw, spanning a climatic gradient in the boreal-subarctic Canadian region, to analyze tree growth patterns and identify their primary drivers—temperature, moisture, or permafrost changes.Our findings revealed that the positive response of tree growth to warmer temperatures shifted in recent decades, with no significant positive temperature response at any studied site after 2007. Sensitivity to moisture also varied, showing exclusively negative impacts of higher vapor pressure deficit and precipitation on tree growth. Overall, tree growth exhibited a steady increase across the climatic gradient, peaking between 1993 and 2007, followed by a decline after 2007.Nearly all permafrost monitoring sites examined showed consistent increases in permafrost thaw since 2007, with more pronounced ground destabilization occurring at lower latitudes within the climatic gradient. We found that permafrost thaw generally had a negative impact on tree growth. These reductions in growth were linked to ground destabilization caused by seasonal and long-term changes in ice-rich permafrost, which led to trees tilting off-vertical. Tree leaning triggered the formation of reaction wood, which alters radial growth as the trees counteract the physical instability of the permafrost.Our results indicate that continued climate warming will drive widespread reductions in radial growth in boreal forests, leading to decreased carbon sequestration capacity.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.176
Threshold uncertainty score0.350

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.038
GPT teacher head0.264
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2025
Admission routes2
Has abstractyes

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