Spatial variation of soil quality indicators as a function of land use and topography

被引:17
|
作者
Kiani, Mina [1 ]
Hernandez-Ramirez, Guillermo [2 ]
Quideau, Sylvie A. M. [2 ]
机构
[1] Univ Helsinki, Dept Agr Sci, POB 27, FI-00014 Helsinki, Finland
[2] Univ Alberta, Dept Renewable Resources, 442 Earth Sci Bldg, Edmonton, AB T6G 2E3, Canada
关键词
cokriging; depth-to-water table; geostatistics; grassland; microbial community composition; topography; HEAVY-METAL SOURCES; ORGANIC-MATTER; HYDRAULIC CONDUCTIVITY; TERRAIN ATTRIBUTES; PHYSICAL QUALITY; TOTAL NITROGEN; VARIABILITY; REGRESSION; SCALE; CARBON;
D O I
10.1139/cjss-2019-0163
中图分类号
S15 [土壤学];
学科分类号
0903 ; 090301 ;
摘要
Soil quality (SQ) indicators such as plant available water (PAW), soil organic carbon (SOC), and microbial biomass carbon (MBC) can reveal agroecological functions; however, their spatial variabilities across contrasting land uses need to be better understood. This study examined the spatial variation of these key SQ indicators as a function of two land-use systems and using topography covariates. We sampled a total of 116 point locations in a native grassland (NG) site and an irrigated cultivated (IC) site located near Brooks, Alberta. Compared with NG, cultivation altered soil pore-size distribution by sharply reducing macroporosity by 25%. However, conditions in the IC soil supported greater accrual of microbial growth (MBC of 601 vs. 812 nmol phospholipid fatty acids g(-1) soil) probably due to more availability of water and nutrients. Focusing on the effects of topography on SQ indicators, terrain elevation (by light detection and ranging) and estimated depth-to-water were found to be key controllers of SQ at the two land-use systems. Also, there were gradual increases in both SOC and MBC where estimated water table was deeper, and higher SOC also associated with lower elevation. A comparison of ordinary kriging and cokriging (coK) geostatistical mapping indicated that the coK method performed better as demonstrated by improvements in the accuracies of spatial estimations of PAW, SOC concentration, and MBC. Thus, implementing coK using the aforementioned topography covariates enhances the capability for predictive mapping of SQ, which is particularly useful when spatial data for key SQ indicators are sparse and challenging to measure.
引用
收藏
页码:463 / 478
页数:16
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