Intermittent low temperatures constrain spring recovery of photosynthesis in boreal Scots pine forests
Bibliographic record
Abstract
Abstract During winter and early spring, evergreen boreal conifers are severely stressed because light energy cannot be used when photosynthesis is pre‐empted by low ambient temperatures. To study photosynthetic performance dynamics in a severe boreal climate, seasonal changes in photosynthetic pigments, chloroplast proteins and photochemical efficiency were studied in a Scots pine forest near Zotino, Central Siberia. In winter, downregulation of photosynthesis involved loss of chlorophylls, a twofold increase in xanthophyll cycle pigments and sustained high levels of the light stress‐induced zeaxanthin pigment. The highest levels of xanthophylls and zeaxanthin did not occur during the coldest winter period, but rather in April when light was increasing, indicating an increased capacity for thermal dissipation of excitation energy at that time. Concomitantly, in early spring the D1 protein of the photosystem II (PSII) reaction centre and the light‐harvesting complex of PSII dropped to their lowest annual levels. In April and May, recovery of PSII activity, chloroplast protein synthesis and rearrangements of pigments were observed as air temperatures increased above 0°C. Nevertheless, severe intermittent low‐temperature episodes during this period not only halted but actually reversed the physiological recovery. During these spring low‐temperature episodes, protective processes involved a complementary function of the PsbS and early light‐induced protein thylakoid proteins. Full recovery of photosynthesis did not occur until the end of May. Our results show that even after winter cold hardening, photosynthetic activity in evergreens responds opportunistically to environmental change throughout the cold season. Therefore, climate change effects potentially improve the sink capacity of boreal forests for atmospheric carbon. However, earlier photosynthesis in spring in response to warmer temperatures is strongly constrained by environmental variation, counteracting the positive effects of an early recovery process.
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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".