Literature DB >> 31066936

Comparative power law analysis for the spatial heterogeneity scaling of the hot-spring microbiomes.

Lianwei Li1,2, Zhanshan Sam Ma1,2,3.   

Abstract

Spatial heterogeneity is a fundamental property of any natural ecosystems, including hot spring and human microbiomes. Two important scales that spatial heterogeneity exhibits are population and community scales, and Taylor's power law (PL) and its extensions (PLEs) offer ideal quantitative models to assess population- and community-level heterogeneities. Here we analyse 165 hot spring microbiome samples at the global scale that cover a wide range of temperatures (7.5-99°C) and pH levels (3.3-9). We explore a question of fundamental importance for measuring the spatial heterogeneity of the hot-spring microbiome and further discuss their ecological implications: How do critical environmental factors such as temperature and pH influence the scaling of community spatial heterogeneity? We are particularly interested in the existence of a universal scaling model that is independent of environmental gradients. By applying PL and PLEs, we were able to obtain such scaling parameters of the hot spring at both community and population levels, which are temperature- and pH-invariant. These findings suggest that while the hot-spring microbiomes located at different regions may have different environmental conditions, they share a fundamental heterogeneity scaling parameter, analogically similar to the gravitational acceleration on Earth, which may vary slightly depending on altitude and latitude, but is invariant overall. In contrast, similar to the physics of the Moon and Earth, which have different gravitational accelerations, the hot spring and human microbiomes can have different scaling parameters as demonstrated in this study.
© 2019 John Wiley & Sons Ltd.

Entities:  

Keywords:  Taylor's power law (PL); community spatial heterogeneity; hot spring microbiome; population spatial aggregation (heterogeneity); power law extensions (PLEs)

Mesh:

Year:  2019        PMID: 31066936     DOI: 10.1111/mec.15124

Source DB:  PubMed          Journal:  Mol Ecol        ISSN: 0962-1083            Impact factor:   6.185


  2 in total

1.  Variance in Landscape Connectivity Shifts Microbial Population Scaling.

Authors:  Miles T Wetherington; Krisztina Nagy; László Dér; Janneke Noorlag; Peter Galajda; Juan E Keymer
Journal:  Front Microbiol       Date:  2022-04-01       Impact factor: 6.064

2.  Species Sorting and Neutral Theory Analyses Reveal Archaeal and Bacterial Communities Are Assembled Differently in Hot Springs.

Authors:  Lianwei Li; Zhanshan Sam Ma
Journal:  Front Bioeng Biotechnol       Date:  2020-05-28
  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.