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Soil microbial community composition does not predominantly determine the variance of heterotrophic soil respiration across four subtropical forests

To explore the importance of soil microbial community composition on explaining the difference in heterotrophic soil respiration (R(h)) across forests, a field investigation was conducted on R(h) and soil physiochemical and microbial properties in four subtropical forests in southern China. We obser...

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Detalles Bibliográficos
Autores principales: Wei, Hui, Xiao, Guoliang, Guenet, Bertrand, Janssens, Ivan A., Shen, Weijun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4297967/
https://www.ncbi.nlm.nih.gov/pubmed/25598010
http://dx.doi.org/10.1038/srep07854
Descripción
Sumario:To explore the importance of soil microbial community composition on explaining the difference in heterotrophic soil respiration (R(h)) across forests, a field investigation was conducted on R(h) and soil physiochemical and microbial properties in four subtropical forests in southern China. We observed that R(h) differed significantly among forests, being 2.48 ± 0.23, 2.31 ± 0.21, 1.83 ± 0.08 and 1.56 ± 0.15 μmol m(−2) s(−1) in the climax evergreen broadleaf forest (BF), the mixed conifer and broadleaf forest (CF), the conifer plantation (CP), and the native broadleaved species plantation (BP), respectively. Both linear mixed effect model and variance decomposition analysis indicated that soil microbial community composition derived from phospholipid fatty acids (PLFAs) was not the first-order explanatory variable for the R(h) variance across the forests, with the explanatory power being 15.7%. Contrastingly, vegetational attributes such as root biomass (22.6%) and soil substrate availability (18.6%) were more important for explaining the observed R(h) variance. Our results therefore suggest that vegetation attributes and soil carbon pool size, rather than soil microbial community composition, should be preferentially considered to understand the spatial R(h) variance across the subtropical forests in southern China.