Abstract
AbstractThis study aimed to explore the structure and stability characteristics of zonal soil aggregates in cold high‐altitude regions and reveal the variation patterns of alpine soil aggregates, using the Three Rivers Source of the Qinghai‐Tibetan Plateau as an example. Zonal soils representing the local vegetation types (alpine meadow soil, alpine grassland soil) were collected, and soil aggregates were separated using wet and dry sieving methods. Random forest modeling was used with climate data from 2011 to 2019 as variables in order to generate multifactor digital maps of water‐stable and mechanically stable aggregates. The composition and differences of zone‐specific soil aggregates were compared and analyzed using the evaluation indices of macroaggregate content (R > 0.25), mean weight diameter (MWD), geometric mean diameter, and fractal dimensions. Their controlling factors were also explored. The study results showed that the model's explanatory power for soil aggregates was over 68%. In the random forest model, elevation and sunshine duration contributed more to soil water‐stable aggregates, whereas precipitation contributed more to soil mechanically stable aggregates. The content of large aggregates with particle size greater than 0.5 mm was higher in alpine meadow soils than in alpine grassland soils. In contrast, the content of large aggregates with particle size less than 0.5 mm was lower than that of alpine grassland soils. There are also some differences in the distribution of water‐stable aggregates and mechanically stable aggregates between alpine meadow soils and alpine grassland soils in each particle size, and these differences are most pronounced in the particle sizes >2 and <0.25 mm. In addition, the stability of alpine meadow soil aggregates is higher than that of alpine grassland soil aggregates. Finally, the mapping results show that the stability of soil aggregates in the study area has similar zonal characteristics to the zonal variation of vegetation cover and climate and other factors.
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