Abstract

Environmental contextMicrobes play key roles in controlling acidification and metal toxicity in coastal acid-sulfate soils. We characterised the time-dependent metabolic activities of abundant and rare taxa in acidifying tidal wetlands and showed that rare taxa exhibiting higher activity may exert significant influence on iron- and sulfur-cycling. Our findings yield new insights into the drivers and timing of iron- and sulfur-cycling in coastal acid-sulfate systems. AbstractTidal inundation has been trialled as a remediation strategy for coastal acid-sulfate soil (CASS) environments. Microbial community structure and activity are hypothesised to play key roles in this process, but remain poorly understood for long-term (decadal or longer) CASS ecosystems. More detailed understanding of the distribution and timing of microbial activity in CASS ecosystems is necessary to evaluate their real bioremediation potential. In this study, we compared 16S ribosomal DNA (rRNA) and RNA (as copy DNA, cDNA, a proxy for overall enzymatic activity) sequence datasets to characterise and resolve microbial community structure and activity across a tidal cycle in the East Trinity long-term CASS wetland (Queensland, Australia). The timing and extent of activity among abundant (>1 %) and rare (<0.1 %) microbial taxa showed that a larger number of rare members (phylotype) displayed greater overall range in activity than was apparent for more abundant members. Certain taxa from both abundant and rare populations varied rapidly in their 16S rRNA levels in response to tidal cycling. The observation of rRNA accumulation in response to drying and rewetting was used to divide the microbial community structure into ‘early responders’ (within 3 h of dry-down or wet-up) and ‘delayed responders’ (3+ h after wet-up). Response patterns were phylogenetically constrained across supra- to subtidal zones across all tidal stages. Microbial iron- and sulfur-cycling networks included these rare but active taxa, illustrating their spatiotemporal complexity, which should be considered for an accurate assessment of bioremediation efficiency, and specially for validating predictive biogeochemical models of long-term CASS ecosystems.

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