对驱动土壤微生物群落结构和活动的环境和土壤属性进行排序,特别关注空间和时间尺度

IF 4.5 Q1 MICROBIOLOGY mLife Pub Date : 2024-03-01 DOI:10.1002/mlf2.12116
Vadakattu V. S. R. Gupta, J. Tiedje
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引用次数: 0

摘要

小尺度土壤微生物群落极其复杂,因此对其进行分析并确定观察到的结构的原因具有挑战性。微生物群落结构主要是接种物(散播)、这些生物在基于生境的环境属性下的选择优势以及这些定殖者长期自我维持能力的结果。由于土壤具有保护性,而且土壤中的微生物居民早已适应了不同的土壤条件,因此土壤微生物群落结构的很大一部分很可能是稳定的。因此,群落的很大一部分不会与经常测量的土壤属性相关联。我们建议根据驱动因素对微生物基本需求的重要性对其进行排序:(i) 提供能量的驱动因素,即有机碳和电子受体;(ii) 环境影响因素或压力因素,即 pH 值、盐分、干旱和干旱、(iii)大生物体关联,即植物及其季节性、动物及其排泄物和土壤动物群;以及(iv)养分,依次为氮、磷,以及重要性较低的其他微量营养元素和金属。驱动因素的相关性也随空间和时间尺度的变化而变化,例如,从总体到田野再到区域,从持久种群到动态种群再到转录本,以及随系统发育差异的程度而变化,因此生物群体的表型差异也会随之变化。我们提出了一个汇总矩阵,为哪些驱动因素对特定研究具有重要意义提供指导,特别强调了广泛的空间和时间尺度,并用部分研究的基因组和种群(rRNA 基因)数据进行了说明。
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Ranking environmental and edaphic attributes driving soil microbial community structure and activity with special attention to spatial and temporal scales
The incredibly complex soil microbial communities at small scales make their analysis and identification of reasons for the observed structures challenging. Microbial community structure is mainly a result of the inoculum (dispersal), the selective advantages of those organisms under the habitat‐based environmental attributes, and the ability of those colonizers to sustain themselves over time. Since soil is protective, and its microbial inhabitants have long adapted to varied soil conditions, significant portions of the soil microbial community structure are likely stable. Hence, a substantial portion of the community will not correlate to often measured soil attributes. We suggest that the drivers be ranked on the basis of their importance to the fundamental needs of the microbes: (i) those that supply energy, i.e., organic carbon and electron acceptors; (ii) environmental effectors or stressors, i.e., pH, salt, drought, and toxic chemicals; (iii) macro‐organism associations, i.e., plants and their seasonality, animals and their fecal matter, and soil fauna; and (iv) nutrients, in order, N, P, and probably of lesser importance, other micronutrients, and metals. The relevance of drivers also varies with spatial and time scales, for example, aggregate to field to regional, and persistent to dynamic populations to transcripts, and with the extent of phylogenetic difference, hence phenotypic differences in organismal groups. We present a summary matrix to provide guidance on which drivers are important for particular studies, with special emphasis on a wide range of spatial and temporal scales, and illustrate this with genomic and population (rRNA gene) data from selected studies.
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