Quantifying root turnover in grasslands from biomass dynamics: Application of the growth-maintenance respiration paradigm and re-analysis of historical data

Matthew T. Amato and Daniel Giménez

Ecological Modelling, 2022, vol. 467, issue C

Abstract: Root turnover rates define how frequently plants replace their root systems and input organic matter into soil. Turnover rates are often computed using measurements of total living and dead (standing) root biomass (r) by assuming gross and net production are equivalent during the growing season. This assumption may be inappropriate in grasslands where root lifespans are relatively short, and decomposition substantially offsets growth. The objective of this study was to quantify turnover rates from measurements of r over time assuming growth and decomposition happen simultaneously, and that net r changes (ΔrΔt) decrease linearly as the size of r increases (first-order kinetics). These hypotheses were interpreted with the growth-maintenance respiration paradigm (GMRP) based on whether daily growth is constant (GP) or reduced by the costs of tissue maintenance (MP). The two parameters of the linear GMRP models were inferred using Bayesian methods from 111 growing season records of r versus ΔrΔt from 15 grasslands. Two-level (hierarchical) inferences were setup for the 14 grasslands that had multiple records, assuming parameters from each grassland originated from the same population. For the grassland with one record, a single-level inference was conducted. A total of 89 records, at least one per grassland, substantially supported the GMRP models. Median predicted turnover rates based on production/decomposition for the GP and MP models were 1.8/1.1 and 1.4/1.2 per growing season, respectively. These estimates were 3 to 7 times faster than those from traditional algorithms that neglect decomposition, suggesting organic matter inputs from roots may be larger than expected in some grasslands, especially where growth occurs almost year-round.

Keywords: Soil organic matter; Root decomposition; Carbon cycle; Ecosystem process; Bayesian inference; Parameter scaling (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S030438002200062X
Full text for ScienceDirect subscribers only

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:467:y:2022:i:c:s030438002200062x

DOI: 10.1016/j.ecolmodel.2022.109940

Access Statistics for this article

Ecological Modelling is currently edited by Brian D. Fath

More articles in Ecological Modelling from Elsevier
Bibliographic data for series maintained by Catherine Liu ().