Changes in turnover rather than production regulate biomass of ectomycorrhizal fungal mycelium across a Pinus sylvestris chronosequence

© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.

Bibliographische Detailangaben
Veröffentlicht in:The New phytologist. - 1979. - 214(2017), 1 vom: 13. Apr., Seite 424-431
1. Verfasser: Hagenbo, Andreas (VerfasserIn)
Weitere Verfasser: Clemmensen, Karina E, Finlay, Roger D, Kyaschenko, Julia, Lindahl, Björn D, Fransson, Petra, Ekblad, Alf
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2017
Zugriff auf das übergeordnete Werk:The New phytologist
Schlagworte:Journal Article chronosequence ectomycorrhiza ergosterol extramatrical mycelium extraradical mycelium fungal biomass production turnover
Beschreibung
Zusammenfassung:© 2016 The Authors. New Phytologist © 2016 New Phytologist Trust.
In boreal forest soils, ectomycorrhizal fungi are fundamentally important for carbon (C) dynamics and nutrient cycling. Although their extraradical mycelium (ERM) is pivotal for processes such as soil organic matter build-up and nitrogen cycling, very little is known about its dynamics and regulation. In this study, we quantified ERM production and turnover, and examined how these two processes together regulated standing ERM biomass in seven sites forming a chronosequence of 12- to 100-yr-old managed Pinus sylvestris forests. This was done by determining ERM biomass, using ergosterol as a proxy, in sequentially harvested in-growth mesh bags and by applying mathematical models. Although ERM production declined with increasing forest age from 1.2 to 0.5 kg ha-1  d-1 , the standing biomass increased from 50 to 112 kg ha-1 . This was explained by a drastic decline in mycelial turnover from seven times to one time per year with increasing forest age, corresponding to mean residence times from 25 d up to 1 yr. Our results demonstrate that ERM turnover is the main factor regulating biomass across differently aged forest stands. Explicit inclusion of ERM parameters in forest ecosystem C models may significantly improve their capacity to predict responses of mycorrhiza-mediated processes to management and environmental changes
Beschreibung:Date Completed 16.02.2018
Date Revised 30.09.2020
published: Print-Electronic
Citation Status MEDLINE
ISSN:1469-8137
DOI:10.1111/nph.14379