Evidence map›Paper›PMID 36168143›Full record

ArticleThe New phytologist2022

Characterizing natural variability of lignin abundance and composition in fine roots across temperate trees: a comparison of analytical methods.

Mengxue Xia, Oscar J Valverde-Barrantes, Vidya Suseela, Christopher B Blackwood, Nishanth Tharayil

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Article in The New phytologist, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Mengxue XiaDepartment of Plant & Environmental Sciences, Clemson University, Clemson, SC, 29634, USA.ORCID 0000-0003-4366-3253
Oscar J Valverde-BarrantesInternational Center for Tropical Biodiversity, Institute of Environment, Florida International University, Miami, FL, 33199, USA.ORCID 0000-0002-7327-7647
Vidya SuseelaDepartment of Plant & Environmental Sciences, Clemson University, Clemson, SC, 29634, USA.ORCID 0000-0002-2934-4849
Christopher B BlackwoodDepartment of Biological Sciences, Kent State University, Kent, OH, 44242, USA.ORCID 0000-0001-5764-6978
Nishanth TharayilDepartment of Plant & Environmental Sciences, Clemson University, Clemson, SC, 29634, USA.ORCID 0000-0001-6866-0804

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lignin is an important root chemical component that is widely used in biogeochemical models to predict root decomposition. Across ecological studies, lignin abundance has been characterized using both proximate and lignin-specific methods, without much understanding of their comparability. This uncertainty in estimating lignin limits our ability to comprehend the mechanisms regulating root decomposition and to integrate lignin data for large-scale syntheses. We compared five methods of estimating lignin abundance and composition in fine roots across 34 phylogenetically diverse tree species. We also assessed the feasibility of high-throughput techniques for fast-screening of root lignin. Although acid-insoluble fraction (AIF) has been used to infer root lignin and decomposition, AIF-defined lignin content was disconnected from the lignin abundance estimated by techniques that specifically measure lignin-derived monomers. While lignin-specific techniques indicated lignin contents of 2-10% (w/w) in roots, AIF-defined lignin contents were c. 5-10-fold higher, and their interspecific variation was found to be largely unrelated to that determined using lignin-specific techniques. High-throughput pyrolysis-gas chromatography-mass spectrometry, when combined with quantitative modeling, accurately predicted lignin abundance and composition, highlighting its feasibility for quicker assessment of lignin in roots. We demonstrate that AIF should be interpreted separately from lignin in fine roots as its abundance is unrelated to that of lignin polymers. This study provides the basis for informed decision-making with respect to lignin methodology in ecology.

Indexed as

LigninTreesGas Chromatography-Mass SpectrometryLigninacid-insoluble fractioncupric oxide (CuO) oxidationfine rootsFourier transform infrared (FTIR) spectroscopyligninpyrolysis-gas chromatography-mass spectrometry (py-GC-MS)root chemical traitsthioacidolysis

Identifiers

PMID36168143
PMCPMC9828118

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.