Climate and soils together regulate photosynthetic carbon isotope discrimination within C<sub>3</sub> plants worldwide
Bibliographic record
Abstract
Abstract Aim Within C 3 plants, photosynthesis is a balance between CO 2 supply from the atmosphere via stomata and demand by enzymes within chloroplasts. This process is dynamic and a complex but crucial aspect of photosynthesis. We sought to understand the spatial pattern in CO 2 supply–demand balance on a global scale, via analysis of stable isotopes of carbon within leaves (Δ 13 C), which provide an integrative record of CO 2 drawdown during photosynthesis. Location Global Time period 1951–2011. Major taxa studied Vascular plants. Methods We assembled a database of leaf carbon isotope ratios containing 3,979 species–site combinations from across the globe, including 3,645 for C 3 species. We examined a wide array of potential climate and soil drivers of variation in Δ 13 C. Results The strongest drivers of carbon isotope discrimination at the global scale included atmospheric pressure, potential evapotranspiration and soil pH, which explained 44% of the variation in Δ 13 C. Addition of eight more climate and soil variables (each explaining small but highly significant amounts of variation) increased the explained variation to 60%. On top of this, the largest plant trait effect was leaf nitrogen per area, which explained 11% of Δ 13 C variation. Main conclusions: By considering variation in Δ 13 C at a considerably larger scale than previously, we were able to identify and quantify key drivers in CO 2 supply–demand balance previously unacknowledged. Of special note is the key role of soil properties, with greater discrimination on low‐pH and high‐silt soils. Unlike other plant traits, which show typically wide variation within sets of coexisting species, the global pattern in carbon stable isotope ratios is much more conservative; there is relatively narrow variation in time‐integrated CO 2 concentrations at the site of carboxylation among plants in a given soil and climate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".