Weather or weathering? Growth of<i>Nothofagus dombeyi</i>on volcanic soils differing in nitrogen and phosphorus concentrations
Bibliographic record
Abstract
Aims We tested whether—in addition to weather conditions—the concentrations of nitrogen and phosphorus in the substrate have an effect on the radial stem increment of Nothofagus dombeyi trees in old-growth forest stands on volcanic soil at the western slopes of the Andes in South-Central Chile. Methods We took soil samples and tree increment cores from five proximate sites (1000–1300 m a.s.l.) that are located in the volcanic region of the Conguill i ´ o National Park and differ in the age of the substrate (Miocene—3500 years B.P.) and in its concentrations of nitrogen (N) and phosphorus (P). The soil samples were also analysed on their concentrations of other plant mineral nutrients, carbon (C) and nitrogen isotope ratios (δ15N). Tree-ring widths and the stem basal area increment (BAI) were related to climate parameters. In selected tree rings, the stable isotope ratios of carbon (δ13C) and oxygen (δ18O) were determined and related to growth and climate parameters. Important Findings Consistent with theory, the soils on the oldest substrate showed the highest (least negative) δ15N values, but mineral N was the only nutrient whose concentration exhibited a straightforward (increasing) relationship with increasing substrate age. The BAI was largest on the soil with the highest concentration of plant-available P. In contrast to BAI, tree-ring chronologies did not differ among the study sites. However, tree-ring chronologies and BAI exhibited significantly positive correlations with summer precipitation, and negative correlations, with summer (December) temperature. A negative correlation was found between δ13C and precipitation anomalies in the growing season (November–March). We interpret the negative correlations between growth and temperature, and between δ13C and δ18O in the tree rings, as an impairment of net carbon assimilation by anomalously warm weather conditions during the growing season. We conclude that the growth of N. dombeyi is mainly affected by high temperature and low precipitation in spring and summer irrespective of the substrate’s age, and enhanced by higher concentrations of plant-available P in the soil. Our results may be representative of N. dombeyi stands on volcanic substrate within their principal distribution range along the Andes of South America.
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) | 0.001 | 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".