Lake microbial communities are not resistant or resilient to repeated large-scale natural pulse disturbances.

Opportunities to study community-level responses to extreme natural pulse disturbances in unaltered ecosystems are rare. Lake sediment records that span thousands of years can contain well-resolved sediment pulses, triggered by earthquakes. These palaeorecords provide a means to study repeated pulse disturbances and processes of resistance (insensitivity to disturbance) and ecological resilience (capacity to regain structure, function and process). In this study, sedimentary DNA was extracted from a sediment core from Lake Paringa (New Zealand) that is situated in a near natural catchment. Metabarcoding and inferred functions were used to assess the lake microbial community over the past 1100 years - a period that included four major earthquakes. Microbial community composition and function differed significantly between highly perturbed (postseismic, ~50 years) phases directly after the earthquakes and more stable (interseismic, ~250 years) phases, indicating a lack of community resistance. Although community structure differed significantly in successive postseismic phases, function did not, suggesting potential functional redundancy. Significant differences in composition and function in successive interseismic phases demonstrate that communities are not resilient to large-scale natural pulse disturbances. The clear difference in structure and function, and high number of indicator taxa (responsible for driving differences in communities between phases) in the fourth interseismic phase probably represents a regime shift, possibly due to the two-fold increase in sediment and terrestrial biospheric organic carbon fluxes recorded following the fourth earthquake. Large pulse disturbances that enhance sediment inputs into lake systems may produce an underappreciated mechanism that destabilises lake ecosystem processes.

Successional change in microbial communities of benthic Phormidium-dominated biofilms.

Benthic cyanobacterial blooms are increasing worldwide and can be harmful to human and animal health if they contain toxin-producing species. Microbial interactions are important in the formation of benthic biofilms and can lead to increased dominance and/or toxin production of one or few taxa. This study investigated how microbial interactions contribute to proliferation of benthic blooms dominated by the neurotoxin-producing Phormidium autumnale. Following a rainfall event that cleared the substrate, biofilm succession was characterised at a site on the Hutt River (New Zealand) by sampling every 2-3 days over 32 days. A combination of morphological and molecular community analyses (automated ribosomal intergenic spacer analysis and Illumina™ MiSeq sequencing) identified three distinct phases of succession in both the micro-algal and bacterial communities within P. autumnale-dominated biofilms. Bacterial composition shifted between the phases, and these changes occurred several days before those of the micro-algal community. Alphaproteobacteria and Betaproteobacteria dominate in the early phase; Alphaproteobacteria, Betaproteobacteria, Sphingobacteria and Flavobacteria in the mid-phase; and Sphingobacteria and Flavobacteria in the late phase. Collectively, the results suggest that succession is driven by bacteria in the early stages but becomes dependent on micro-algae in the mid- and late stages of biofilm formation.

A bacterial index to estimate lake trophic level: National scale validation.

Lakes and their catchments have been subjected to centuries to millennia of exploitation by humans. Efficient monitoring methods are required to promote proactive protection and management. Traditional monitoring is time consuming and expensive, which limits the number of lakes monitored. Lake surface sediments provide a temporally integrated representation of environmental conditions and contain high microbial biomass. Based on these attributes, we hypothesized that bacteria associated with lake trophic states could be identified and used to develop an index that would not be confounded by non-nutrient stressor gradients. Metabarcoding (16S rRNA gene) was used to assess bacterial communities present in surface sediments from 259 non-saline lakes in New Zealand encompassing a range of trophic states from alpine microtrophic lakes to lowland hypertrophic lakes. A subset of lakes (n = 96) with monitoring data was used to identify indicator amplicon sequence variants (ASVs) associated with different trophic states. A total of 10,888 indicator taxa were identified and used to develop a Sediment Bacterial Trophic Index (SBTI), which signficantly correlated (r2 = 0.842, P < 0.001) with the Trophic Lake Index. The SBTI was then derived for the remaining 163 lakes, providing new knowledge of the trophic state of these unmonitored lakes. This new, robust DNA-based tool provides a rapid and cost-effective method that will allow a greater number of lakes to be monitored and more effectively managed in New Zealand and globally. The SBTI could also be applied in a paleolimnological context to investigate changes in trophic status over centuries to millennia.