Literature DB >> 21302839

The trait contribution to wood decomposition rates of 15 Neotropical tree species.

Koert G van Geffen1, Lourens Poorter, Ute Sass-Klaassen, Richard S P van Logtestijn, Johannes H C Cornelissen.   

Abstract

The decomposition of dead wood is a critical uncertainty in models of the global carbon cycle. Despite this, relatively few studies have focused on dead wood decomposition, with a strong bias to higher latitudes. Especially the effect of interspecific variation in species traits on differences in wood decomposition rates remains unknown. In order to fill these gaps, we applied a novel method to study long-term wood decomposition of 15 tree species in a Bolivian semi-evergreen tropical moist forest. We hypothesized that interspecific differences in species traits are important drivers of variation in wood decomposition rates. Wood decomposition rates (fractional mass loss) varied between 0.01 and 0.31 yr(-1). We measured 10 different chemical, anatomical, and morphological traits for all species. The species' average traits were useful predictors of wood decomposition rates, particularly the average diameter (dbh) of the tree species (R2 = 0.41). Lignin concentration further increased the proportion of explained inter-specific variation in wood decomposition (both negative relations, cumulative R2 = 0.55), although it did not significantly explain variation in wood decomposition rates if considered alone. When dbh values of the actual dead trees sampled for decomposition rate determination were used as a predictor variable, the final model (including dead tree dbh and lignin concentration) explained even more variation in wood decomposition rates (R2 = 0.71), underlining the importance of dbh in wood decomposition. Other traits, including wood density, wood anatomical traits, macronutrient concentrations, and the amount of phenolic extractives could not significantly explain the variation in wood decomposition rates. The surprising results of this multi-species study, in which for the first time a large set of traits is explicitly linked to wood decomposition rates, merits further testing in other forest ecosystems.

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Year:  2010        PMID: 21302839     DOI: 10.1890/09-2224.1

Source DB:  PubMed          Journal:  Ecology        ISSN: 0012-9658            Impact factor:   5.499


  6 in total

1.  Controls on coarse wood decay in temperate tree species: birth of the LOGLIFE experiment.

Authors:  Johannes H C Cornelissen; Ute Sass-Klaassen; Lourens Poorter; Koert van Geffen; Richard S P van Logtestijn; Jurgen van Hal; Leo Goudzwaard; Frank J Sterck; René K W M Klaassen; Grégoire T Freschet; Annemieke van der Wal; Henk Eshuis; Juan Zuo; Wietse de Boer; Teun Lamers; Monique Weemstra; Vincent Cretin; Rozan Martin; Jan den Ouden; Matty P Berg; Rien Aerts; Godefridus M J Mohren; Mariet M Hefting
Journal:  Ambio       Date:  2012       Impact factor: 5.129

2.  A global database of woody tissue carbon concentrations.

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Journal:  Sci Data       Date:  2022-06-09       Impact factor: 6.444

3.  Signature wood modifications reveal decomposer community history.

Authors:  Jonathan S Schilling; Justin T Kaffenberger; Feng Jin Liew; Zewei Song
Journal:  PLoS One       Date:  2015-03-26       Impact factor: 3.240

4.  Various effects of the expression of the xyloglucanase gene from Penicillium canescens in transgenic aspen under semi-natural conditions.

Authors:  Elena O Vidyagina; Natalia M Subbotina; Vladimir A Belyi; Vadim G Lebedev; Konstantin V Krutovsky; Konstantin A Shestibratov
Journal:  BMC Plant Biol       Date:  2020-06-03       Impact factor: 4.215

5.  Factors controlling bark decomposition and its role in wood decomposition in five tropical tree species.

Authors:  Gbadamassi G O Dossa; Ekananda Paudel; Kunfang Cao; Douglas Schaefer; Rhett D Harrison
Journal:  Sci Rep       Date:  2016-10-04       Impact factor: 4.379

6.  Bacterial Community Succession in Pine-Wood Decomposition.

Authors:  Anna M Kielak; Tanja R Scheublin; Lucas W Mendes; Johannes A van Veen; Eiko E Kuramae
Journal:  Front Microbiol       Date:  2016-03-01       Impact factor: 5.640

  6 in total

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