Impacts of elevated ozone and nitrogen on growth and photosynthesis of European aspen (<i>Populus tremula</i>) and hybrid aspen (<i>P. tremula</i> × <i>Populus tremuloides</i>) clones
Bibliographic record
Abstract
Impacts of elevated tropospheric ozone and soil nitrogen amendment on two native European aspen ( Populus tremula L.) and eight hybrid aspen (P. tremula L. × Populus tremuloides Michx.) clones were studied in a free-air ozone exposure system. Potted saplings were exposed to ambient (ca. 20 ppb) or 1.5× ambient ozone and two levels of soil nitrogen (39 and 78 kg N·ha–1·year–1 in the first year, 60 and 140 kg N·ha–1·year–1 in the second year for low-nitrogen and high-nitrogen treatments, respectively) over two growing seasons. The plants were measured for photosynthesis, chlorophyll fluorescence, and biomass accumulation. Ozone decreased leaf-level net photosynthesis (Asat) in particular early in the growing season and maximum quantum yield of photosystem II (Fv/Fm) at the end of the growing season. Nitrogen amendment increased the growth of all plant parts and mitigated the adverse ozone effects. There were significant differences in ozone responses among the clones, and we were able to cluster the clones into sensitivity groups based on their growth responses. The most ozone-tolerant genotypes were hybrid aspen clones, indicating that populations that have already experienced selection for ozone-tolerant genotypes should be used to cross-breed with ozone-sensitive populations to achieve tolerance of a climate with increasing tropospheric ozone concentrations.
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) | 0.000 | 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 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".