Growth sensitivity to climate varies with soil moisture regime in spruce–fir forests in central British Columbia
Bibliographic record
Abstract
Abstract Key message Growth sensitivity to climate varies with soil moisture regime in spruce–fir forests in central British Columbia. Stands growing at their dry edaphic limits displayed especially strong and unique climatic sensitivities. Abstract Soil moisture regime is an important influence of productivity, process, and structure in forested ecosystems. In western North America, projected warming trends may result in decreasing available soil moisture; however, the potential effects on forest growth remain unclear. This study aimed to determine the influence of stand-level soil moisture regime on the climatic sensitivity of mature hybrid white spruce (Picea glauca (Moensch) Voss x Picea engelmannii Parry) and subalpine fir (Abies lasiocarpa (Hook.) Nutt.) forests in central British Columbia, Canada. We collected and analyzed tree-ring data from 51 stands spanning a range of soil moisture regimes. Dendroecological analyses of climate–growth relationships indicated that warm summer temperatures and drought limit growth for both species across all soil moisture regimes; however, responses were strongest on the driest sites. Spruce populations across the gradient of soil moisture regimes displayed unique climate-growth relationships; growth in populations on wetter sites was more correlated with summer climate from the year prior to growth. Radial growth responses to prior summer temperatures strengthened over the past ca. 80 years in both species and across most sites, suggesting that climate–growth relationships are shifting in this region. This study presents evidence of the importance of considering site-level ecological factors such as soil moisture regime when studying forest growth responses to climate.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".