Refining Amino Sugar-Based Conversion Factors for Quantification of Microbial Necromass Carbon in Soils
© 2025 John Wiley & Sons Ltd.
| Veröffentlicht in: | Global change biology. - 1999. - 31(2025), 8 vom: 19. Aug., Seite e70443 |
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| 1. Verfasser: | |
| Weitere Verfasser: | , , , , , |
| Format: | Online-Aufsatz |
| Sprache: | English |
| Veröffentlicht: |
2025
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| Zugriff auf das übergeordnete Werk: | Global change biology |
| Schlagworte: | Journal Article amino sugar biomarkers microbial necromass carbon n‐alkanes soil biocrust Soil Carbon 7440-44-0 Amino Sugars |
| Zusammenfassung: | © 2025 John Wiley & Sons Ltd. Quantifying the contribution of microbial necromass to soil organic carbon (SOC) has been a hot topic in the past decade, offering critical insights into soil carbon sequestration mechanisms. Amino sugars (AS) are widely used biomarkers for estimating microbial necromass in soils, with the ratios of AS to microbial necromass carbon (MNC) serving as conversion factors to derive MNC from AS measurement. Because AS decomposes more slowly than bulk necromass and persists longer in soil, the ratio of AS to microbial necromass should exceed the AS to biomass ratio in living microbes. However, current conversion factors are derived from microbial biomass data, potentially leading to overestimation of MNC in soils. Here we propose a novel approach to refine AS-based conversion factors for more accurate MNC estimation. Using biocrust soils as an ideal model system with minimal plant inputs, we derived MNC values by subtracting microbial biomass carbon from SOC. Our method directly quantified ratios of AS to MNC in soils and reduced the overestimation of MNC observed when using conventional biomass-derived conversion factors in biocrust systems. Additionally, results from other ecosystem types suggested the potential of using biocrust-derived ratios of AS to MNC in other soil types. This refined quantification approach enhances our understanding of SOC sequestration dynamics and provides more accurate parameters for modeling soil carbon cycling processes |
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| Beschreibung: | Date Completed 20.08.2025 Date Revised 20.08.2025 published: Print Citation Status MEDLINE |
| ISSN: | 1365-2486 |
| DOI: | 10.1111/gcb.70443 |