Effects of simulated climate change on post-disturbance «Populus tremuloides - Picea mariana» ecosystems in northwestern Quebec
Bibliographic record
Abstract
In the mixedwood-boreal transitional forest of northwestern Quebec, the establishment of trembling aspen (Populus tremuloides Michx.) has been observed at the extremes of their regional distribution, in areas previously dominated by black spruce (Picea mariana (Miller) BSP). Our main objective was to explore how climate change could affect the growth and performance of aspen and black spruce. Climate change simulation was provided by the installation of twenty open-top chambers (OTCs) and twenty control plots in the summer of 2005 at three disturbed sites (post-fire, logging road and logging). Each plot enclosed a pair of aspen and spruce seedlings. In comparison to control plots, the conditions in the OTCs were marked by higher air temperatures (2-3°C), drier soil (up to 10% volumetric moisture content) and cooler soil (up to 2.6°C), lower supply rates of Ca and Mg, and slower decomposition of aspen litter. Warm weather and high rainfall were likely responsible for increased height growth and advanced spring bud burst of aspen growing in the OTCs during the 2006 growing season, but not during the cooler and drier season of 2007. Leaf calcium concentration was higher, and beetle leaf herbivory was lower for OTC aspen in comparison to control plot aspen. Spruce was not affected by OTC treatment in terms of height growth, but its final dry biomass was higher, and spring bud burst was advanced by 2-3 days in the OTCs compared to control plots. Both species showed trends of higher root tip number and lower % ectomycorrhizae (ECM) colonization in the OTCs, and vice versa in the control plots. Aspen appeared to be more dependent on ECM colonization; therefore, potential ef
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".