Department of Agricultural Biotechnology and Biosciences, School of Agriculture and Natural Resources, Mulungushi University, Kabwe, Central Province, Zambia.
School of the Environment, Natural Resources & Geography, Bangor University, Bangor, Gwynedd, United Kingdom.
PLoS One. 2021 Oct 22;16(10):e0248665. doi: 10.1371/journal.pone.0248665. eCollection 2021.
The physical, chemical and biological attributes of a soil combined with abiotic factors (e.g. climate and topography) drive pedogenesis and some of these attributes have been used as proxies to soil quality. Thus, we investigated: (1) whether appropriate soil quality indicators (SQIs) could be identified in soils of Great Britain, (2) whether conventional soil classification or aggregate vegetation classes (AVCs) could predict SQIs and (3) to what extent do soil types and/ or AVCs act as major regulators of SQIs. Factor analysis was used to group 20 soil attributes into six SQI which were named as; soil organic matter (SOM), dissolved organic matter (DOM), soluble N, reduced N, microbial biomass, DOM humification (DOMH). SOM was identified as the most important SQI in the discrimination of both soil types and AVCs. Soil attributes constituting highly to the SOM factor were, microbial quotient and bulk density. The SOM indicator discriminated three soil type groupings and four aggregate vegetation class groupings. Among the soil types, only the peat soils were discriminated from other groups while among the AVCs only the heath and bog classes were isolated from others. However, the peat soil and heath and bog AVC were the only groups that were distinctly discriminated from other groups. All other groups heavily overlapped with one another, making it practically impossible to define reference values for each soil type or AVC. The two-way ANOVA showed that the AVCs were a better regulator of the SQIs than the soil types. We conclude that conventionally classified soil types cannot predict the SQIs defined from large areas with differing climatic and edaphic factors. Localised areas with similar climatic and topoedaphic factors may hold promise for the definition of SQI that may predict the soil types or AVCs.
土壤的物理、化学和生物学特性与非生物因素(如气候和地形)相结合,驱动着成土作用,其中一些特性已被用作土壤质量的指标。因此,我们调查了:(1)在英国土壤中是否可以识别出适当的土壤质量指标(SQIs),(2)传统的土壤分类或聚集植被类(AVCs)是否可以预测 SQIs,(3)土壤类型和/或 AVC 在多大程度上作为 SQIs 的主要调节剂。因子分析将 20 个土壤属性分为 6 个 SQI,分别命名为土壤有机质(SOM)、溶解有机质(DOM)、可溶性 N、还原 N、微生物生物量和 DOM 腐殖化(DOMH)。SOM 被认为是区分土壤类型和 AVC 的最重要的 SQI。构成 SOM 因子的土壤属性包括微生物商和体密度。SOM 指标区分了三种土壤类型分组和四种聚集植被类分组。在土壤类型中,只有泥炭土与其他组区分开来,而在 AVC 中,只有石南和沼泽类与其他组区分开来。然而,泥炭土和石南和沼泽 AVC 是唯一与其他组明显区分开来的组。所有其他组彼此重叠严重,使得为每个土壤类型或 AVC 定义参考值实际上变得不可能。双向方差分析表明,AVCs 是 SQIs 的更好调节剂,而土壤类型则不是。我们得出结论,传统分类的土壤类型不能预测在具有不同气候和土壤因素的大面积地区定义的 SQIs。具有相似气候和地形因素的局部地区可能有希望定义可预测土壤类型或 AVC 的 SQI。