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Updated: Jul 9, 2025

Monitoring Spatial Segregation in Surface Colonizing Microbial Populations
Published on: October 29, 2016
Temporal dynamics of the microbial heterogeneity-diversity relationship in microcosmic systems
Wei Deng1,2,3, Nong-En Bai1,2,3, Fu-Liang Qi1,2,3
1Institute of Eastern-Himalaya Biodiversity Research, Dali University, Dali, 671003, Yunnan, China.
Abstract:
Spatial heterogeneity significantly enhances biodiversity, representing one of the ecology's most enduring paradigms. However, many studies have found decreasing, humped, and neutral correlations between spatial heterogeneity and biodiversity (heterogeneity-diversity relationships, HDR). These findings have pushed this widely accepted theory back into controversy. Microbial HDR research has lagged compared to that of plants and animals. Nevertheless, microbes have features that add a temporal-scale perspective to HDR research that is critical to understanding patterns of HDR. In this study, 157 microcosms with different types spatial heterogeneity were set up to map the HDR of microorganisms and their temporal dynamics using high-throughput sequencing techniques. The results show that the following: 1. Spatial heterogeneity can significantly alter microbial diversity in microcosmic systems. Changes in microbial diversity, in turn, lead to changes in environmental conditions. These changes caused microorganisms to exhibit increasing, decreasing, humped, U-shaped, and neutral HDR patterns. 2. The emergence of HDR patterns is characterized by temporal dynamics. Additionally, the HDR patterns generated by spatial structural and compositional heterogeneity exhibit inconsistent emergence times. These results suggest that the temporal dynamics of HDR may be one of the reasons for the coexistence of multiple patterns in previous studies. The feedback regulation between spatial heterogeneity-biodiversity-environmental conditions is an essential reason for the temporally dynamics of HDR patterns. All future ecological studies should pay attention to the temporal dynamic patterns of ecological factors.
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