Species specific growth responses of black spruce and trembling aspen may enhance resilience of boreal forest to climate change
Bibliographic record
Abstract
Summary To understand how the future climate will affect the boreal forest, we studied growth responses to climate variability in black spruce ( Picea mariana [Mill.] B.S.P.) and trembling aspen ( Populus tremuloides Michx.), two major co‐occurring boreal tree species of the eastern Canadian boreal forest. We analysed climate–growth interaction during (i) periods of non‐anomalous growth and (ii) in years with strong growth anomalies. We utilized paired tree‐level data for both growth and soil variables, which helped ensure that the studied growth variability was a function of species‐specific biology, and not of within stand variation in soil conditions. Redundancy analysis conducted on spruce and aspen tree ring chronologies showed that their growth was affected differently by climate. During non‐anomalous years, growth of spruce was favoured by cooler temperatures and wetter conditions, while aspen growth was favoured by higher temperatures and drier conditions. Black spruce and trembling aspen also showed an inverse pattern in respect to expression of growth anomalies (pointer years). A negative growth anomaly in spruce tended to be associated with positive ones in aspen and vice versa. This suggested that spruce and aspen had largely contrasting species‐specific responses to both ‘average’ weather conditions and extreme weather events. Synthesis . Species‐specific responses to environmental variability imply that tree responses to future climate will likely be not synchronized among species, which may translate into changes in structure and composition of future forest communities. In particular, we speculate that outcome of climate change in respect to relative abundance of black spruce and trembling aspen at the regional levels will be highly dependent on the balance between increasing temperatures and precipitation. Further, species‐specific responses of trees to annual climate variability may enhance the resilience of mixed forests by constraining variability in their annual biomass accumulation, as compared with pure stands, under periods with high frequency of climatically extreme conditions.
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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 | 0.000 | 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 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".