Spatial distribution of soil organic carbon and total nitrogen stocks in a karst polje located in Bosnia and Herzegovina

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作者
Igor Bogunovic
Paulo Pereira
Radica Coric
Stjepan Husnjak
Eric C. Brevik
机构
[1] University of Zagreb,Department of General Agronomy, Faculty of Agriculture
[2] Mykolas Romeris University,Environmental Management Laboratory
[3] University of Mostar,Faculty of Agronomy and Food Technology
[4] University of Zagreb,Department of Soil Science, Faculty of Agriculture
[5] Dickinson State University,Department of Agriculture and Technical Studies
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Soil carbon; Total nitrogen; Soil mapping; Co-variates; Geostatistics;
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摘要
Karst poljes in the Dinaric Mountains have a complex hydrological regime and high potential for crop production. Little information is available about soil organic carbon (SOC), total nitrogen (TN), carbon stocks (SOCS), and nitrogen stocks (TNS) in karst poljes located in the Dinaric area. The objective of this paper was to study the spatial distribution of SOC and TN in topsoil (ranged from 9 to 53 cm depth) and whole profile SOCS and TNS (ranged from 15 to 160 cm depth) in the Livno karst polje depression (Bosnia and Herzegovina) using kriging and co-kriging approaches. We used the following properties as co-variates: distance from hills (DFH), distance from the lake (DFL), sand, silt, and clay content, TN, SOC, SOCS, and TNS. We only used the properties that had a significant correlation with the estimated properties as co-variates. The results showed that soils in the study area had high average SOC (7.92%), TN (0.79%), SOCS (191.05 t ha−1), and TNS (17.91 t ha−1) values. Histosols had the highest SOCS and TNS and Arenosols the lowest. The experimental variogram of LogSOC and LogTN was best-fitted by the spherical model, while the exponential model was the most accurate for LogSOCS and LogTNS. The spatial dependence was moderate for all studied soil properties. The incorporation of auxiliary variables increased the precision of the estimations from 35.7% (SOC × TN) to 49.2% (TNS × SOCS).
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