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Context-dependent Role of Abiotic and Biotic Factors Structuring Nematode Communities along Two Environmental Gradients.

Molecular ecology(2022)

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摘要
Although abiotic environmental factors have been historically regarded as the dominant deterministic process in microbial community assembly, recent studies indicate that biotic interactions may be equally significant. However, the extent to which both processes are important in assembly of belowground communities is unknown. Along two environmental gradients: alkalinity (ranging from pH ~7 to ~11) and habitat type (lakes, shorelines, and prairies around lakes) present in the Western Nebraska Sandhills, we used 18S rRNA gene marker metabarcoding and statistical analyses, including generalized dissimilarity modelling (GDM), to evaluate the dynamics between abiotic and biotic factors that might play a role in nematode community assembly. Lakes supported the least diverse and prairies the most diverse communities with completely distinct compositions. We also observed a potential role of alkalinity in shaping these communities but only in lakes. Generally, GDMs indicated the influence of both abiotic and biotic factors. However, their relative importance in explaining community variability was dependent on the habitat. Biotic factors influenced the lake communities most, followed by shorelines and prairies, explaining ~47%, 27% and 8% of the variation, respectively. In contrast, the role of abiotic factors was relatively similar in lakes, shorelines and prairies (~15%, 18% and 14% of the variation, respectively). Most variation in the shorelines (62%) and prairies (82%) remained unexplained, suggesting the potential importance of factors associated with specific traits or a stronger role of stochastic processes. Nevertheless, our findings suggest both deterministic processes are important in nematode community assembly, but their specific contributions are context-dependent.
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关键词
biotic interactions,community assembly,deterministic,environmental factors,microbial community,soil,stochasticity
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