Impacts of a regional drought on the productivity, dieback, and biomass of western Canadian aspen forests
Bibliographic record
Abstract
We examined the impacts of a severe, regional drought (2001–2002) on trembling aspen ( Populus tremuloides Michx.) forests in the western Canadian interior. A total of 150 plots were established in 25 study areas as part of a regional-scale study (CIPHA). Aspen health and mortality were assessed annually during 2000–2005, and changes in stem biomass were estimated using tree-ring analysis and plot-based measurements. Net mean increment in living biomass for all plots was 2.2 t·ha –1 ·year –1 during 2000–2002 but subsequently decreased to near zero. This collapse was driven by a more than two-fold increase in stem mortality and a 30% decrease in regional stem growth during and following the drought. The analysis showed that spatial variation in aspen productivity and biomass across the region was positively related to multiyear mean values of a climate moisture index and mineral soil silt content but was negatively related to levels of insect defoliation and wood-boring insects. In contrast, mortality and dieback was best correlated with minimum annual climate moisture index, which provided a measure of short-term drought severity. The results support previous studies showing that aspen forests are moisture limited in this region, which poses concerns for the future under a changing 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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.000 | 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 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".