Acclimation of photosynthetic capacity and foliar respiration in Andean tree species to temperature change
Bibliographic record
Abstract
Summary Climate warming is causing compositional changes in Andean tropical montane forests (TMFs). These shifts are hypothesised to result from differential responses to warming of cold‐ and warm‐affiliated species, with the former experiencing mortality and the latter migrating upslope. The thermal acclimation potential of Andean TMFs remains unknown. Along a 2000 m Andean altitudinal gradient, we planted individuals of cold‐ and warm‐affiliated species (under common soil and irrigation), exposing them to the hot and cold extremes of their thermal niches, respectively. We measured the response of net photosynthesis (Anet), photosynthetic capacity and leaf dark respiration (Rdark) to warming/cooling, 5 months after planting. In all species, Anet and photosynthetic capacity at 25°C were highest when growing at growth temperatures (Tg) closest to their thermal means, declining with warming and cooling in cold‐affiliated and warm‐affiliated species, respectively. When expressed at Tg, photosynthetic capacity and Rdark remained unchanged in cold‐affiliated species, but the latter decreased in warm‐affiliated counterparts. Rdark at 25°C increased with temperature in all species, but remained unchanged when expressed at Tg. Both species groups acclimated to temperature, but only warm‐affiliated species decreased Rdark to photosynthetic capacity ratio at Tg as temperature increased. This could confer them a competitive advantage under future warming.
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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 | 0.001 | 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".