22 Oct 2021

22 Oct 2021

Review status: a revised version of this preprint was accepted for the journal BG.

Implementation of mycorrhizal mechanisms into soil carbon model improves the prediction of long-term processes of plant litter decomposition

Weilin Huang1, Peter M. van Bodegom1, Toni Viskari2, Jari Liski2, and Nadejda A. Soudzilovskaia1,3 Weilin Huang et al.
  • 1Environmental Biology, Institute of Environmental Sciences, Leiden University, Einsteinweg 2, 2333CC Leiden, the Netherlands
  • 2Finnish Meteorological Institute, Helsinki, 00101, Finland
  • 3Centre for Environmental Sciences, Hasselt University, Martelarenlaan 42, 3500 Hasselt, Belgium

Abstract. Ecosystems dominated by plants featuring ectomycorrhizae (EM) and arbuscular mycorrhizae (AM) promote distinct soil carbon dynamics. AM and EM soil environments can thus have different impacts on litter decomposition. However, current soil carbon models treat mycorrhizal impacts on the processes of soil carbon transformation as a black box.

We re-formulated the soil carbon model Yasso15, and incorporated impacts of mycorrhizal vegetation on soil carbon pools of different recalcitrance. We examined alternative conceptualizations of mycorrhizal impacts on transformations of labile and stable carbon, and quantitatively assessed the performance of the selected optimal model in terms of the long-term fate of plant litter.

We found that mycorrhizal impacts on pools of labile carbon in the litter are distinct from that on recalcitrant pools. Plant litter of the same chemical composition decomposes slower when exposed to EM-dominated ecosystems compared to AM-dominated ones, and across time, EM-dominated ecosystems accumulate more recalcitrant residues of non-decomposed litter. Overall, adding our mycorrhizal module into the Yasso model improved the accuracy of the temporal dynamics of carbon sequestration predictions.

Our results suggest that mycorrhizal impacts on litter decomposition are underpinned by distinct decomposition pathways in AM- and EM-dominated ecosystems. Ignoring mycorrhiza-induced mechanisms will thus lead to an overestimation of climate impacts on decomposition dynamics. Our new model provides a benchmark for mechanistic and quantitative modelling of microbial impact on soil carbon. It helps to determine the relative importance of mycorrhizal associations and climate on organic matter decomposition rate and reduces the uncertainties in estimating soil carbon sequestration.

Weilin Huang et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on bg-2021-275', Anonymous Referee #1, 30 Oct 2021
    • AC1: 'Reply on RC1', Weilin Huang, 03 Dec 2021
  • RC2: 'Comment on bg-2021-275', Anonymous Referee #2, 02 Nov 2021
    • AC2: 'Reply on RC2', Weilin Huang, 03 Dec 2021
  • RC3: 'Comment on bg-2021-275', Anonymous Referee #3, 17 Nov 2021
    • AC3: 'Reply on RC3', Weilin Huang, 03 Dec 2021
  • RC4: 'Comment on bg-2021-275', Anonymous Referee #4, 19 Nov 2021
    • AC4: 'Reply on RC4', Weilin Huang, 03 Dec 2021

Weilin Huang et al.

Weilin Huang et al.


Total article views: 493 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
375 100 18 493 5 4
  • HTML: 375
  • PDF: 100
  • XML: 18
  • Total: 493
  • BibTeX: 5
  • EndNote: 4
Views and downloads (calculated since 22 Oct 2021)
Cumulative views and downloads (calculated since 22 Oct 2021)

Viewed (geographical distribution)

Total article views: 481 (including HTML, PDF, and XML) Thereof 481 with geography defined and 0 with unknown origin.
Country # Views %
  • 1
Latest update: 24 Jan 2022
Short summary
This work focuses on the worst understood pathway of mycorrhizal impact on C cycles: the mediation of plant litter decomposition. We present a mechanistic model based on litter chemical quality which precludes a conclusive examination of mycorrhizal impacts on soil C. It improves long-term decomposition predictions and advances our understanding of litter decomposition dynamics. It creates a benchmark in quantitatively examining the impacts of plant-microbial interactions on soil C dynamics.