Changes in the structural composition and reactivity of <i>Acer rubrum</i> leaf litter tannins exposed to warming and altered precipitation: climatic stress‐induced tannins are more reactive
Bibliographic record
Abstract
• Climate change could increase the frequency with which plants experience abiotic stresses, leading to changes in their metabolic pathways. These stresses may induce the production of compounds that are structurally and biologically different from constitutive compounds. • We studied how warming and altered precipitation affected the composition, structure, and biological reactivity of leaf litter tannins in Acer rubrum at the Boston-Area Climate Experiment, in Massachusetts, USA. • Warmer and drier climatic conditions led to higher concentrations of protective compounds, including flavonoids and cutin. The abundance and structure of leaf tannins also responded consistently to climatic treatments. Drought and warming in combination doubled the concentration of total tannins, which reached 30% of leaf-litter DW. This treatment also produced condensed tannins with lower polymerization and a greater proportion of procyanidin units, which in turn reduced sequestration of tannins by litter fiber. Furthermore, because of the structural flexibility of these tannins, litter from this treatment exhibited five times more enzyme (β-glucosidase) complexation capacity on a per-weight basis. Warmer and wetter conditions decreased the amount of foliar condensed tannins. • Our finding that warming and drought result in the production of highly reactive tannins is novel, and highly relevant to climate change research as these tannins, by immobilizing microbial enzymes, could slow litter decomposition and thus carbon and nutrient cycling in a warmer, drier world.
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".