Impacts of inundation and drought on eukaryote biodiversity in semi-arid floodplain soils.

Floodplain ecosystems are characterized by alternating wet and dry phases and periodic inundation defines their ecological character. Climate change, river regulation and the construction of levees have substantially altered natural flooding and drying regimes worldwide with uncertain effects on key biotic groups. In southern Australia, we hypothesized that soil eukaryotic communities in climate change affected areas of a semi-arid floodplain would transition towards comprising mainly dry-soil specialist species with increasing drought severity. Here, we used 18S rRNA amplicon pyrosequencing to measure the eukaryote community composition in soils that had been depleted of water to varying degrees to confirm that reproducible transitional changes occur in eukaryotic biodiversity on this floodplain. Interflood community structures (3 years post-flood) were dominated by persistent rather than either aquatic or dry-specialist organisms. Only 2% of taxa were unique to dry locations by 8 years post-flood, and 10% were restricted to wet locations (inundated a year to 2 weeks post-flood). Almost half (48%) of the total soil biota were detected in both these environments. The discovery of a large suite of organisms able to survive nearly a decade of drought, and up to a year submerged supports the concept of inherent resilience of Australian semi-arid floodplain soil communities under increasing pressure from climatic induced changes in water availability.

Sulfide formation in freshwater sediments, by sulfate-reducing microorganisms with diverse tolerance to salt.

Understanding how sulfate-reducing microbes in freshwater systems respond to added salt, and therefore sulfate, is becoming increasingly important in inland systems where the threat from salinisation is increasing. To address this knowledge gap, we carried out mesocosm studies to determine how the sulfate-reducing microbial community in sediments from a freshwater wetland would respond to salinisation. The levels of inorganic mineral sulfides produced after 6months incubation were measured to determine whether they were in sufficient quantity to be harmful if re-oxidized. Comparative sequence analysis of the dissimilatory sulfite reductase (DSR) gene was used to compare the sulfate-reducing community structure in mesocosms without salt and those incubated with moderate levels of salt. The amount of total S, acid volatile sulfide or chromium-reducible sulfide produced in sediments with 0, 1 or 5gL(-1) added salt were not significantly different. Sediments subjected to 15gL(-1) salt contained significantly higher total S and acid volatile sulfide, and levels were above trigger values for potential harm if re-oxidation occurred. The overall community structure of the sulfate-reducing microbiota (SRM) was explained by the level of salt added to sediments. However, a group of sulfate reducers were identified that occurred in both the high salt and freshwater treatments. These results demonstrate that freshwater sediments contain sulfate reducers with diverse abilities to respond to salt and can respond rapidly to increasing salinity, explaining the observation that harmful levels of acid volatile sulfides can form rapidly in sediments with no history of exposure to salt.

Ordination and significance testing of microbial community composition derived from terminal restriction fragment length polymorphisms: application of multivariate statistics.

Terminal restriction fragment length polymorphism (T-RFLP) is increasingly being used to examine microbial community structure and accordingly, a range of approaches have been used to analyze data sets. A number of published reports have included data and results that were statistically flawed or lacked rigorous statistical testing. A range of simple, yet powerful techniques are available to examine community data, however their use is seldom, if ever, discussed in microbial literature. We describe an approach that overcomes some of the problems associated with analyzing community datasets and offer an approach that makes data interpretation simple and effective. The Bray-Curtis coefficient is suggested as an ideal coefficient to be used for the construction of similarity matrices. Its strengths include its ability to deal with data sets containing multiple blocks of zeros in a meaningful manner. Non-metric multi-dimensional scaling is described as a powerful, yet easily interpreted method to examine community patterns based on T-RFLP data. Importantly, we describe the use of significance testing of data sets to allow quantitative assessment of similarity, removing subjectivity in comparing complex data sets. Finally, we introduce a quantitative measure of sample dispersion and suggest its usefulness in describing site heterogeneity.