Fine-root turnover rates of European forests revisited: An analysis of data from sequential coring and ingrowth cores

I. Brunner, M. R. Bakker, R. G. Björk, Y. Hirano, M. Lukac, X. Aranda, I. Børja, T. D. Eldhuset, H. S. Helmisaari, C. Jourdan, B. Konôpka, B. C. López, C. Miguel Pérez, H. Persson, I. Ostonen

Research output: Contribution to journalReview articleResearchpeer-review

112 Citations (Scopus)

Abstract

Background and Aims: Forest trees directly contribute to carbon cycling in forest soils through the turnover of their fine roots. In this study we aimed to calculate root turnover rates of common European forest tree species and to compare them with most frequently published values. Methods: We compiled available European data and applied various turnover rate calculation methods to the resulting database. We used Decision Matrix and Maximum-Minimum formula as suggested in the literature. Results: Mean turnover rates obtained by the combination of sequential coring and Decision Matrix were 0. 86 yr-1 for Fagus sylvatica and 0. 88 yr-1 for Picea abies when maximum biomass data were used for the calculation, and 1. 11 yr-1 for both species when mean biomass data were used. Using mean biomass rather than maximum resulted in about 30 % higher values of root turnover. Using the Decision Matrix to calculate turnover rate doubled the rates when compared to the Maximum-Minimum formula. The Decision Matrix, however, makes use of more input information than the Maximum-Minimum formula. Conclusions: We propose that calculations using the Decision Matrix with mean biomass give the most reliable estimates of root turnover rates in European forests and should preferentially be used in models and C reporting. © 2012 The Author(s).
Original languageEnglish
Pages (from-to)357-372
JournalPlant and Soil
Volume362
Issue number1-2
DOIs
Publication statusPublished - 1 Jan 2013

Keywords

  • Annual production
  • Decision Matrix
  • Fine-root turnover rates
  • Ingrowth cores
  • Maximum-Minimum formula
  • Sequential coring

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