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Comparative Power Law Analysis for the Spatial Heterogeneity Scaling of the Hot-Spring Microbiomes
论文题目: Comparative Power Law Analysis for the Spatial Heterogeneity Scaling of the Hot-Spring Microbiomes
作者: Li L, Ma ZS
联系作者: ma@vandals.uidaho.edu
发表年度: 2019
DOI: doi: 10.1111/mec.15124
摘要:

Spatial heterogeneity is a fundamental property of any natural ecosystems including hot spring and human microbiomes. Two most important scales that the spatial heterogeneity exhibits are the population and community, and Taylor's power law (PL) and its extensions (PLEs) offer ideal quantitative models to assess the population- and community-level heterogeneities. In this article, we analyze 165 hot springmicrobiome samples at global scale that cover a wide range of temperatures (7.5°C-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. That is, how do critical environmental factors such as the temperature and pH influence the scaling of community spatialheterogeneity? We are particularly interested in the existence of a universal scaling model that is independent of the environmental gradients. Through the applications of PL and PLEs, we were able to get 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 with the acceleration rate of gravity on the earth, which may slightly vary depending on altitude and latitude, but is invariant overall. In contrast, similar to the physics of moon and earth, which may have different acceleration rates due to different gravities, the hot spring and human microbiomes can have different scaling parameters as demonstrated in this study

刊物名称: Molecular Ecology
论文出处: https://onlinelibrary.wiley.com/doi/abs/10.1111/mec.15124
影响因子: 6.131(2017年)
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