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Abstract
Biotic homogenization, i.e., the increase in community similarity through time or space, is a commonly observed response following conversion of native ecosystems to agriculture, but our understanding of the ecological mechanisms underlying this process is limited for bacterial communities. Identifying mechanisms of bacterial community homogenization following rapid environmental change may be complicated by the fact only a minority of taxa is active at any time. Here we used RNA- and DNA-based metabarcoding to distinguish putatively active taxa in the bacterial community from inactive taxa. We asked how soil bacterial communities respond to land use change following a rapid transition from rainforest to agriculture in the Congo Basin using a chronosequence that spans from roughly 1 week following slash-and-burn to an active plantation roughly 1.5 years post-conversion. Our results indicate that the magnitude of community homogenization is larger in the RNA-inferred community than the DNA-inferred perspective. We show that as the soil environment changes, the RNA-inferred community structure tracks environmental variation and loses spatial structure. The DNA-inferred community does not respond to environmental variability to the same degree, and is instead homogenized by a subset of taxa that is shared between forest and conversion sites. Our results suggest that complementing DNA-based surveys with RNA can provide insights into the way bacterial communities respond to environmental change.
Highlights
One of the most rampant forms of environmental change today is land use change following the conversion of tropical rainforests to agriculture (Houghton, 1994; Dirzo and Raven, 2003; Foley et al, 2005; Laurance et al, 2014)
We first asked whether bacterial community structure differed by land use for RNA- and DNA-inferred communities by performing a PERMANOVA on Operational taxonomic units (OTUs)-level community Canberra distance, with land type as the independent variable
The most pronounced differences at the phylum level were lower relative abundances of Acidobacteria in the burned site compared to the forest and plantation sites [burned site (DNA): 6.86 ± 0.78%, forest site (DNA): 11.07 ± 1.73%, plantation site (DNA): 11.30 ± 1.32%], and higher relative abundances of Actinobacteria in the burned site relative to forest and plantation sites [burned site (DNA): 10.86 ± 1.16%, forest site (DNA): 7.69 ± 1.40%, plantation site (DNA): 8.73 ± 1.33%], and this trend was consistent whether communities were inferred via DNA or RNA (Supplementary Figure 1)
Summary
One of the most rampant forms of environmental change today is land use change following the conversion of tropical rainforests to agriculture (Houghton, 1994; Dirzo and Raven, 2003; Foley et al, 2005; Laurance et al, 2014). Biotic homogenization is a major consequence of land use change (McKinney and Lockwood, 1999) This process can be driven by two primary mechanisms: (1) the loss of environmental heterogeneity, which drives subsequent community convergence (Christensen and Peet, 1984; Lepš, 1991), and/or (2) increased rates of biotic mixing, which can be driven by the breakdown of dispersal barriers, invasion of exotic taxa, or the range expansion of existing taxa (Olden and Poff, 2003; Olden and Rooney, 2006). These mechanisms have both been implicated in the homogenization of microbial communities following land use change (Rodrigues et al, 2013; Mcguire et al, 2015; Gossner et al, 2016; Mueller et al, 2016, 2014; Tripathi et al, 2016), but it remains unknown how choices related to community inference method or analysis could influence our mechanistic conclusions
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