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Record W2613109549 · doi:10.3389/fpls.2017.00423

Climate Influences the Content and Chemical Composition of Foliar Tannins in Green and Senesced Tissues of Quercus rubra

2017· article· en· W2613109549 on OpenAlex
Sara Top, Caroline M. Preston, Jeffrey S. Dukes, Nishanth Tharayil

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueFrontiers in Plant Science · 2017
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicHorticultural and Viticultural Research
Canadian institutionsNatural Resources Canada
FundersPurdue Climate Change Research Center, Purdue UniversityNational Institute of Food and AgricultureClemson UniversityPurdue UniversityOffice of ScienceU.S. Department of AgricultureU.S. Department of EnergyNational Science Foundation
KeywordsProanthocyanidinTanninCondensed tanninChemistryChemical compositionComposition (language)PolyphenolBotanyLitterHorticultureAgronomyBiologyAntioxidant

Abstract

fetched live from OpenAlex

Environmental stresses not only influence production of plant metabolites but could also modify their resorption during leaf senescence. The production-resorption dynamics of polyphenolic tannins, a class of defense compound whose ecological role extends beyond tissue senescence, could amplify the influence of climate on ecosystem processes. We studied the quantity, chemical composition, and tissue-association of tannins in green and freshly-senesced Quercus rubra leaves exposed to different temperature (Warming and No Warming) and precipitation treatments (Dry, Ambient, Wet) at the Boston-Area Climate Experiment (BACE) in Massachusetts, USA. Climate influence not only the quantity of tannins, but also their molecular composition and cell-wall associations. Irrespective of climatic treatments, tannin composition in Q. rubra was dominated by condensed tannins (CTs, proanthocyanidins). When exposed to Dry conditions, Q. rubra produced higher quantities of tannins that were less polymerized. In contrast, under favorable conditions (Wet), tannins were produced in lower quantities, but the CTs were highly polymerized. Further, even as the overall tissue tannin content declined, the content of hydrolysable tannins (HTs) increased under Wet treatments. The molecular composition of tannins influenced their content in senesced litter. Compared to the green leaves, the content of HTs decreased in senesced leaves across treatments, whereas the CT content was similar between green and senesced leaves in Wet treatments that produced highly polymerized tannins. The content of total tannins in senesced leaves was higher in Warming treatments under both dry and ambient precipitation treatments. The more polymerized tannins in leaves produced under Wet treatments could withstand leaching loss and could potentially decrease the decomposition of these tissues. Our results suggest that, though climate directly influenced the production of tannins in green tissues (and similar patterns were observed in the senesced tissue), the influence of climate on tannin content of senesced tissue was partly mediated by the effect on the chemical composition of tannins. These different climatic impacts on leaves over the course of a growing season may alter forest dynamics, not only in decomposition and nutrient cycling dynamics, but also in herbivory dynamics.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.627
Threshold uncertainty score0.466

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.041
GPT teacher head0.279
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it