Embracing fine-root system complexity in terrestrial ecosystem modeling

Bin Wang, Michael Luke McCormack, Daniel M. Ricciuto, Xiaojuan Yang, Colleen M. Iversen

Research output: Contribution to journalArticlepeer-review

8 Scopus citations

Abstract

Projecting the dynamics and functioning of the biosphere requires a holistic consideration of whole-ecosystem processes. However, biases toward leaf, canopy, and soil modeling since the 1970s have constantly left fine-root systems being rudimentarily treated. As accelerated empirical advances in the last two decades establish clearly functional differentiation conferred by the hierarchical structure of fine-root orders and associations with mycorrhizal fungi, a need emerges to embrace this complexity to bridge the data-model gap in still extremely uncertain models. Here, we propose a three-pool structure comprising transport and absorptive fine roots with mycorrhizal fungi (TAM) to model vertically resolved fine-root systems across organizational and spatial–temporal scales. Emerging from a conceptual shift away from arbitrary homogenization, TAM builds upon theoretical and empirical foundations as an effective and efficient approximation that balances realism and simplicity. A proof-of-concept demonstration of TAM in a big-leaf model both conservatively and radically shows robust impacts of differentiation within fine-root systems on simulating carbon cycling in temperate forests. Theoretical and quantitative support warrants exploiting its rich potentials across ecosystems and models to confront uncertainties and challenges for a predictive understanding of the biosphere. Echoing a broad trend of embracing ecological complexity in integrative ecosystem modeling, TAM may offer a consistent framework where modelers and empiricists can work together toward this grand goal.

Original languageEnglish
Pages (from-to)2871-2885
Number of pages15
JournalGlobal Change Biology
Volume29
Issue number11
DOIs
StatePublished - Jun 2023

Funding

We thank Drs. Rich Norby and Peter Thornton for friendly but critical comments and suggestions during the early stages of this work. The three reviewers are sincerely acknowledged for their candid, constructive, and timely reviews that largely improved the rigor and conciseness of this manuscript. The Fine-Root Ecology Database (FRED), BW, CMI, DMR, and XY were supported by the Biological and Environmental Research program within the Department of Energy's Office of Science. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE-AC05-00OR22725. This manuscript has been authored in part by UT-Battelle, LLC, under contract DE-AC05-00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan (http://energy.gov/downloads/doe-public-access-plan). We thank Drs. Rich Norby and Peter Thornton for friendly but critical comments and suggestions during the early stages of this work. The three reviewers are sincerely acknowledged for their candid, constructive, and timely reviews that largely improved the rigor and conciseness of this manuscript. The Fine‐Root Ecology Database (FRED), BW, CMI, DMR, and XY were supported by the Biological and Environmental Research program within the Department of Energy's Office of Science. This research used resources of the Compute and Data Environment for Science (CADES) at the Oak Ridge National Laboratory, which is supported by the Office of Science of the U.S. Department of Energy under Contract No. DE‐AC05‐00OR22725. This manuscript has been authored in part by UT‐Battelle, LLC, under contract DE‐AC05‐00OR22725 with the US Department of Energy (DOE). The publisher acknowledges the US government license to provide public access under the DOE Public Access Plan ( http://energy.gov/downloads/doe‐public‐access‐plan ).

FundersFunder number
CADES
DOE Public Access Plan
Data Environment for Science
U.S. Department of EnergyDE‐AC05‐00OR22725
Office of Science
Biological and Environmental Research

    Keywords

    • TAM
    • complexity
    • demography
    • ecosystem model
    • fine root
    • mycorrhiza
    • partitioning
    • phenology

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