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  • 标题:Digital Mapping of Habitat for Plant Communities Based on Soil Functions: A Case Study in the Virgin Forest-Steppe of Russia
  • 本地全文:下载
  • 作者:Nikolai Lozbenev ; Maria Smirnova ; Maxim Bocharnikov
  • 期刊名称:Soil Systems
  • 电子版ISSN:2571-8789
  • 出版年度:2019
  • 卷号:3
  • 期号:1
  • 页码:19-30
  • DOI:10.3390/soilsystems3010019
  • 出版社:MDPI AG
  • 摘要:The spatial structure of the habitat for plant communities based on soil functions in virgin forest-steppe of the Central Russian Upland is the focus of this study. The objectives include the identification of the leading factors of soil function variety and to determine the spatial heterogeneity of the soil function. A detailed topographic survey was carried out on a key site (35 hectares), 157 soil, and 34 geobotanical descriptions were made. The main factor of soil and plant cover differentiation is the redistribution of soil moisture along the microrelief. Redistributed runoff value was modelled in SIMWE and used as a tool for spatial prediction of soils due to their role in a habitat for plant communities’ functional context. The main methods of the study are the multidimensional scaling and discriminant analysis. We model the composition of plant communities (accuracy is 95%) and Reference Soil Group (accuracy is 88%) due to different soil moisture conditions. There are two stable soil habitat types: mesophytic communities on the Phaeozems (with additional water runoff more than 80 mm) and xerophytic communities on Chernozems (additional runoff less than 55 mm). A transitional type corresponded to xero- mesophytic communities on the Phaeozems with 55–80 mm additional redistributed runoff value. With acceptable accuracy, the habitat for natural plant communities based on soil function model predicts the position of contrastingly different components of biota in relation to their soil moisture requirements within the virgin forest-steppe of the Central Russian Upland.
  • 关键词:Chernozems; Phaeozems; Central Chernozem Reserve; predictive soil mapping Chernozems ; Phaeozems ; Central Chernozem Reserve ; predictive soil mapping
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