Bacterial communities are important for the health and productivity of soil ecosystems and have great potential as novel indicators of environmental perturbations. To assess how they are affected by anthropogenic activity and to determine their ability to provide alternative metrics of environmental health, we sought to define which soil variables bacteria respond to across multiple soil types and land uses. We determined, through 16S rRNA gene amplicon sequencing, the composition of bacterial communities in soil samples from 110 natural or human-impacted sites, located up to 300 km apart. Overall, soil bacterial communities varied more in response to changing soil environments than in response to changes in climate or increasing geographic distance. We identified strong correlations between the relative abundances of members of Pirellulaceae and soil pH, members of Gaiellaceae and carbon-to-nitrogen ratios, members of Bradyrhizobium and the levels of Olsen P (a measure of plant available phosphorus), and members of Chitinophagaceae and aluminum concentrations. These relationships between specific soil attributes and individual soil taxa not only highlight ecological characteristics of these organisms but also demonstrate the ability of key bacterial taxonomic groups to reflect the impact of specific anthropogenic activities, even in comparisons of samples across large geographic areas and diverse soil types. Overall, we provide strong evidence that there is scope to use relative taxon abundances as biological indicators of soil condition. IMPORTANCEThe impact of land use change and management on soil microbial community composition remains poorly understood. Therefore, we explored the relationship between a wide range of soil factors and soil bacterial community composition. We included variables related to anthropogenic activity and collected samples across a large spatial scale to interrogate the complex relationships between various bacterial community attributes and soil condition. We provide evidence of strong relationships between individual taxa and specific soil attributes even across large spatial scales and soil and land use types. Collectively, we were able to demonstrate the largely untapped potential of microorganisms to indicate the condition of soil and thereby influence the way that we monitor the effects of anthropogenic activity on soil ecosystems into the future.
Background Soil ecosystems consist of complex interactions between biological communities and physico-chemical variables, all of which contribute to the overall quality of soils. Despite this, changes in bacterial communities are ignored by most soil monitoring programs, which are crucial to ensure the sustainability of land management practices. We applied 16S rRNA gene sequencing to determine the bacterial community composition of over 3000 soil samples from 606 sites in New Zealand. Sites were classified as indigenous forests, exotic forest plantations, horticulture, or pastoral grasslands; soil physico-chemical variables related to soil quality were also collected. The composition of soil bacterial communities was then used to predict the land use and soil physico-chemical variables of each site. Results Soil bacterial community composition was strongly linked to land use, to the extent where it could correctly determine the type of land use with 85% accuracy. Despite the inherent variation introduced by sampling across ~ 1300 km distance gradient, the bacterial communities could also be used to differentiate sites grouped by key physico-chemical properties with up to 83% accuracy. Further, individual soil variables such as soil pH, nutrient concentrations and bulk density could be predicted; the correlations between predicted and true values ranged from weak (R2 value = 0.35) to strong (R2 value = 0.79). These predictions were accurate enough to allow bacterial communities to assign the correct soil quality scores with 50–95% accuracy. Conclusions The inclusion of biological information when monitoring soil quality is crucial if we wish to gain a better, more accurate understanding of how land management impacts the soil ecosystem. We have shown that soil bacterial communities can provide biologically relevant insights on the impacts of land use on soil ecosystems. Furthermore, their ability to indicate changes in individual soil parameters shows that analysing bacterial DNA data can be used to screen soil quality.
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