Characterizing natural variability of lignin abundance and composition in fine roots across temperate trees: a comparison of analytical methods. Issue 6 (26th October 2022)

• Record Type: Journal Article
• Authors: Xia, Mengxue; Valverde‐Barrantes, Oscar J.; Suseela, Vidya; Blackwood, Christopher B.; Tharayil, Nishanth
• Is Part Of: New phytologist. Volume 236:Issue 6(2022)
• Page Start: 2358
• Page End: 2373
• Publication Date: 2022-10-26
• Subjects: acid‐insoluble fraction -- cupric oxide (CuO) oxidation -- fine roots -- Fourier transform infrared (FTIR) spectroscopy -- lignin -- pyrolysis–gas chromatography–mass spectrometry (py‐GC‐MS) -- root chemical traits -- thioacidolysis; Botany -- Periodicals; 580
• DOI: 10.1111/nph.18515
• Languages: English
• ISSNs: 0028-646X

Abstract

Summary: 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.