Combined effects of rising [CO<sub>2</sub>] and temperature on boreal forests: growth, physiology and limitations
Bibliographic record
Abstract
Climate change is expected to be most pronounced at high latitudes, but we have little data on how dominant boreal tree species will respond to rising temperatures and CO2 concentrations ([CO2]). We review the mechanisms through which elevated growth temperatures and atmospheric CO2 alter tree physiology and growth, focusing on the dominant species in northern forests. Water and nutrient availability, as well as day length, are likely to constrain the ability of these forests to respond positively to warmer, potentially longer growing seasons and higher CO2 levels. We also analyze published tree responses to future climate scenarios for key boreal tree species and show that (i) high [CO2] increases biomass and net photosynthetic rates compared with ambient [CO2], under both current temperatures and warmer climates; (ii) increases in temperature above current levels have little effect on growth or carbon gain; and (iii) the combination of elevated [CO2] and elevated temperatures increases plant biomass, but this effect appears to have a threshold above a 5 °C increase in growth temperatures. While rising temperatures and [CO2], therefore, have the potential to increase the productivity of northern forest species (based on experiments that supply ample water and fertilizer), this response is likely to be limited by these soil resources and the photoperiod in the field, and may not occur under the more extreme warming conditions predicted for the future in this region.
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 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 | 0.001 | 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 | 0.001 | 0.001 |
| 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".