The effects of site type and shoot age on gas exchange and photosynthetic nitrogen use efficiency in pure and mixed <i>Picea abies</i> forests
Bibliographic record
Abstract
Norway spruce ( Picea abies) is considered vulnerable to climate change in several parts of its range and growing in mixed stands is recommended as a mitigation solution. However, understanding spruce's physiological responses to site conditions depending on stand composition is still incomplete. We examined net photosynthesis (Pn), stomatal conductance, needle macronutrients content, and photosynthetic nitrogen use efficiency (PNUE) in different-aged shoots of spruce in response to site conditions and spruce proportions in the stands. The measurements were conducted in five typical spruce site types in Estonia ( Carex-Filipendula, Filipendula, Oxalis drained swamp, Oxalis, and Hepatica) ranging from waterlogged to moderately dry soils. The Hepatica site type had the lowest stomatal conductance, Pn, and PNUE, while the distinction between moderately wet and temporarily waterlogged sites was unclear. Needle nitrogen concentration was higher in mixed stands in current-year shoots, whereas Pn was higher in mixed than in pure stands in 1-year-old shoots suggesting acclimation to higher light availability in early growing season. However, the PNUE of current-year shoots was greater in pure stands. Our findings highlight the importance of stand composition and site conditions in shaping Norway spruce's photosynthetic traits, adaptive responses to environmental variations, and the advantage of mixed stands for enhancing resilience to climate change.
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 | 0.000 | 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".