Spatial patterns of soil microbial communities and implications for precision soil management at the field scale
Spatial patterns of soil microbial communities and implications for precision soil management at the field scale
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DOI：
10.1007/s11119-021-09872-1
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发表时间：
2022-01
影响因子：
6.2
通讯作者：
Jasmine Neupane;Wenxuan Guo;G. Cao;Fangyuan Zhang;Lindsey C. Slaughter;S. Deb
中科院分区：
文献类型：
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作者：
Jasmine Neupane;Wenxuan Guo;G. Cao;Fangyuan Zhang;Lindsey C. Slaughter;S. Deb
了解土壤微生物群落的空间格局及其影响因素是进行土壤健康评估和特定地点管理以提高作物产量的前提。然而，在田间尺度上，土壤微生物群落结构由于地形和土壤性质的相互作用而变得复杂。本研究的目的是（1）在田间尺度上表征土壤微生物群落的空间变异模式;（2）评估土壤理化性质、地形和管理对土壤微生物生物量空间变异的影响。本研究于2017年在德克萨斯州黑尔县的一个194公顷的商业管理田地中进行。在0-0.15 m深度共采集了212个复合土壤样品，并通过酯键脂肪酸甲酯（EL-FAME）方法进行分析，以表征微生物群落结构和生物量。测定了土壤电导率（EC）、pH、土壤质地、土壤含水量（SWC）、土壤有机碳（SOC）和全氮（TN）。地形属性，包括海拔和坡度，来自实时动态（RTK）点高程数据。在这个尺度上的插值微生物群落图揭示了微生物量和多样性的空间结构分布，在不同的方向对应于土壤类型和地形的分布与数百米的补丁。大多数的微生物群落的自相关性在更大的范围内相同的土壤类型比在不同的土壤。土壤微生物生物量的分布主要受土壤有机碳和土壤水碳的影响。土壤pH和C：N比对细菌群落生物量有负面影响。坡度和海拔对真菌群落生物量有负影响。本研究的结果有可能提供一个基础，设计土壤采样计划，在表征微生物群落分布和特定地点的土壤健康管理。
Understanding the spatial patterns of soil microbial communities and influencing factors is a prerequisite for soil health assessments and site-specific management to improve crop production. However, soil microbial community structure at the field scale is complicated by the interactions among topography and soil properties. The objectives of this study were to (1) characterize the spatial variability patterns of soil microbial communities at the field scale; (2) assess the influence of soil physico-chemical properties, topography and management on soil microbial biomass spatial variability. This study was conducted in a 194-ha commercially-managed field in Hale County, Texas, in 2017. A total of 212 composite soil samples were collected at 0–0.15 m depth and analyzed via the ester-linked fatty acid methyl ester (EL-FAME) method to characterize the microbial community structure and biomass. Soil electrical conductivity (EC), pH, soil texture, soil water content (SWC), soil organic carbon (SOC) and total nitrogen (TN) were determined for each soil sample. Topographic attributes, including elevation and slope, were derived from real-time kinematic (RTK) point elevation data. Interpolated microbial community maps at this scale revealed a spatially structured distribution of microbial biomass and diversity with patches of several hundred meters in different directions corresponding to the distribution of soil types and topography. Most of the microbial communities were autocorrelated at greater ranges within the same soil types than across different soils. The distribution of total soil microbial biomass was mainly affected by SOC and SWC. Soil pH and C:N ratio had a negative impact on the biomass of bacterial communities. Biomass of fungal communities was negatively influenced by slope and elevation. The results of this study have the potential to provide a basis for designing soil sampling plans in characterizing microbial community distribution and site-specific soil health management.