报告时间：7月30日 10:00-11:00am
报告地点：天津大学地科院（第16教学楼）221报告厅
主讲嘉宾：Dani Or，土壤水文物理和微生态领域杰出专家，美国国家工程院院士，内华达大学杰出教授，苏黎世联邦理工离休讲席教授，美国土壤学会、地球物理学会和地质学会等会士、戈登会议主席，土壤学及相关领域至高荣誉 Kirkham Soil Physics Award、Birdsal-Dreiss distinguished lecturer、Helmholtz International Fellow Award、AGU Langbein lecturer、European Geosciences Union Dalton Medal、 Caltech Moore scholar等获得者；主要开展土壤水分、能量及溶质运移、土壤滑坡和雪崩机理解析与预警、土壤蒸散发及其对士壤生物物理过程和生命活动的影响等前沿交叉研究，在Nature(2)、PNAS(4)、Nat Comm(4)、Nat Rev Earth Environ(2)、ISME(3)、WRR(92)等发表SCI 论文 360 余篇。
Abstract：Soil water dynamics within the highly fragmented soil physical environment limit soil bacterial dispersion ranges and modulate diffusion and access to patchy resources. We developed a mechanistic modeling framework that integrates soil hydration status and organic carbon inputs towards estimating community size distributions and interaction distances of modeled soil bacterial populations. Understanding the spatial patterns of bacterial communities is critical for interpreting micro-ecological exchanges and functions. Experimental data have shown that soil bacterial cluster sizes can be described by an exponentially truncated power law with parameters that vary with mean soil water content and biome carbon inputs. To understand the origins of these relations, we show that soil bacterial community size distribution obeys the so-called Gibrat’s law. This law emerges in human settlement size distributions, tree sizes and other spatially fixed systems in which growth rates are defined by the environment independent of object size (city or a tree). Results support generalization in soil using positively skewed distributions of soil bacterial community sizes, specifically, the log-normal distribution emerging from Gibrat’s law. We show that soil bacteria reside in numerous small communities (with over 90% of soil bacterial communities containing less than 100 cells), supported by theoretical predictions of log-normal distribution for non-interacting soil bacterial community sizes with scaling parameters that vary with biome characteristics. Importantly, the results can be used to establish conditions for the onset of anoxic metabolism in large bacterial clusters even under fully aerated soil conditions.
