Photosynthetic thermal acclimation capacity of tropical montane rainforest trees in Rwanda and in the Colombian Andes
Bibliographic record
Abstract
Tropical montane forests are among the most productive ecosystems within the tropical region and store a significant amount of carbon in live biomass. With ongoing global climate warming, tropical climates are also getting warmer. The productivity and climate feedbacks of future tropical montane forests depend on the ability of trees to acclimate their photosynthetic metabolism to these new, warmer conditions. However, knowledge of acclimation ability of photosynthesis and its underlying biochemical processes to warming in trees grown under natural field conditions is currently limited due to data scarcity. To reduce this knowledge gap, we used two separate field experiments located in Colombia (with 15 species) and Rwanda (16 species), and for each experiment, tree species were grown at three different sites along an elevation gradient differing in ambient air temperature. At all three sites, we measured the responses of net CO2 assimilation at different CO2 concentration (50 to 2000 ppm) and at different leaf temperatures (15 to 40 °C) in ≈ 3 years old trees. We used these data to derive key photosynthetic biochemical parameters (maximum Rubisco carboxylation capacity - Vcmax and maximum electron transport rate - Jmax) and their temperature sensitivity, as well as the thermal optimum of net photosynthesis (ToptA). We show that tropical montane tree species from the two continents are generally able to acclimate their ToptA by increasing in trees grown in warmer conditions, but the magnitude of change in ToptA differs among species from different successional groups (early- versus late succession) and climate of origin (lowland versus montane). Shifts in ToptA are largely driven by concomitant changes in thermal sensitivity parameters of underlying biochemical processes of photosynthesis (Vcmax and Jmax) with warming. We also show that, at a standard temperature of 25 °C, Vcmax is largely constant, while Jmax decreases with warming. Our findings indicate tropical montane tree species from Latin America and Africa can thermally acclimate their photosynthetic physiology, but that this thermal acclimation ability is related to species successional group and their climate of origin.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".