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Measuring Fine Root Turnover in Forest Ecosystems
University of Gävle, Department of Mathematics, Natural and Computer Sciences, Ämnesavdelningen för naturvetenskap. (Biologi)
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2005 (English)In: Plant and Soil, ISSN 0032-079X, E-ISSN 1573-5036, Vol. 276, no 1-2, 1-8 p.Article in journal (Refereed) Published
Abstract [en]

Development of direct and indirect methods for measuring root turnover and the status of knowledge on fine root turnover in forest ecosystems are discussed. While soil and ingrowth cores give estimates of standing root biomass and relative growth, respectively, minirhizotrons provide estimates of median root longevity (turnover time) i.e., the time by which 50% of the roots are dead. Advanced minirhizotron and carbon tracer studies combined with demographic statistical methods and new models hold the promise of improving our fundamental understanding of the factors controlling root turnover. Using minirhizotron data, fine root turnover (y−1) can be estimated in two ways: as the ratio of annual root length production to average live root length observed and as the inverse of median root longevity. Fine root production and mortality can be estimated by combining data from minirhizotrons and soil cores, provided that these data are based on roots of the same diameter class (e.g., < 1 mm in diameter) and changes in the same time steps. Fluxes of carbon and nutrients via fine root mortality can then be estimated by multiplying the amount of carbon and nutrients in fine root biomass by fine root turnover. It is suggested that the minirhizotron method is suitable for estimating median fine root longevity. In comparison to the minirhizotron method, the radio carbon technique favor larger fine roots that are less dynamics. We need to reconcile and improve both methods to develop a more complete understanding of root turnover.

Place, publisher, year, edition, pages
2005. Vol. 276, no 1-2, 1-8 p.
Keyword [en]
minirhizotron, radio carbon technique, root mortality, root production, root turnover, soil cores, statistical analysis
Identifiers
URN: urn:nbn:se:hig:diva-2085DOI: 10.1007/s11104-005-3104-8ISI: 000233629900002OAI: oai:DiVA.org:hig-2085DiVA: diva2:118747
Available from: 2008-06-21 Created: 2008-06-21 Last updated: 2010-10-12Bibliographically approved

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CiteExportLink to record
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Cite
Citation style
  • apa
  • harvard-cite-them-right
  • ieee
  • modern-language-association-8th-edition
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  • Other style
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Language
  • sv-SE
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