2015Soil Use and ManagementRequires access

Development of ensemble pedotransfer functions for cation exchange capacity of soils of Q ingdao in C hina

Kaihua Liao, Sifa Xu, Qing Zhu

Open publisher page 18 citations

Abstract

Abstract Soil cation exchange capacity ( CEC ), which is considered to be an indicator of buffering capacity, is an important soil attribute that influences soil fertility but is costly, time‐consuming and labour‐intensive to measure. Pedotransfer functions ( PTF s) have routinely been used to predict soil CEC from easily measured soil properties, such as soil pH , texture and organic matter content. However, uncertainty in which one to select can be substantial as different PTF s do not necessarily produce the same result. In this study, a total of 100 soil samples were collected from surface horizons (0–20 cm) in different regions of Qingdao City, China. Three ensemble PTF s ( ePTF s), including simple ensemble mean ( SEM ), individually bias‐removed ensemble mean ( IBREM ) and collective bias‐removed ensemble mean ( CBREM ), were developed to reduce the uncertainty in CEC prediction based on 12 published regression‐based PTF s. In addition, a local PTF ( LPTF ) for CEC was also developed using multiple stepwise regression and basic soil properties. The performances of the three ePTF s were compared with those of the published PTF s and LPTF . Results show that the differences between the performances of the published PTF s were substantial. When the systematic bias of each published PTF was removed separately, the prediction capability of the PTF s was increased. The performance of LPTF was significantly better than that of SEM , but slightly worse than IBREM . It is noted that CBREM had higher accuracy than all of the other methods. Overall, CBREM is a promising approach for estimating soil CEC in the study area.

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What this paper is about

Abstract Soil cation exchange capacity ( CEC ), which is considered to be an indicator of buffering capacity, is an important soil attribute that influences soil fertility but is costly, time‐consuming and labour‐intensive to measure. Pedotransfer functions ( PTF s) have routinely been used to predict soil CEC from easily measured soil properties, such as soil pH , texture and organic matter content. However, uncertainty in which one to select can be substantial as different PTF s do not necessarily produce the same result. In this study, a total of 100 soil samples were collected from surface horizons (0–20 cm) in different regions of Qingdao City, China. Three ensemble PTF s ( ePTF s), including simple ensemble mean ( SEM ), individually bias‐removed ensemble mean ( IBREM ) and collective bias‐removed ensemble mean ( CBREM ), were developed to reduce the uncertainty in CEC prediction based on 12 published regression‐based PTF s. In addition, a local PTF ( LPTF ) for CEC was also developed using multiple stepwise regression and basic soil properties. The performances of the three ePTF s were compared with those of the published PTF s and LPTF . Results show that the differences between the performances of the published PTF s were substantial. When the systematic bias of each published PTF was removed separately, the prediction capability of the PTF s was increased. The performance of LPTF was significantly better than that of SEM , but slightly worse than IBREM . It is noted that CBREM had higher accuracy than all of the other methods. Overall, CBREM is a promising approach for estimating soil CEC in the study area.

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Available abstract

Abstract Soil cation exchange capacity ( CEC ), which is considered to be an indicator of buffering capacity, is an important soil attribute that influences soil fertility but is costly, time‐consuming and labour‐intensive to measure. Pedotransfer functions ( PTF s) have routinely been used to predict soil CEC from easily measured soil properties, such as soil pH , texture and organic matter content. However, uncertainty in which one to select can be substantial as different PTF s do not necessarily produce the same result. In this study, a total of 100 soil samples were collected from surface horizons (0–20 cm) in different regions of Qingdao City, China. Three ensemble PTF s ( ePTF s), including simple ensemble mean ( SEM ), individually bias‐removed ensemble mean ( IBREM ) and collective bias‐removed ensemble mean ( CBREM ), were developed to reduce the uncertainty in CEC prediction based on 12 published regression‐based PTF s. In addition, a local PTF ( LPTF ) for CEC was also developed using multiple stepwise regression and basic soil properties. The performances of the three ePTF s were compared with those of the published PTF s and LPTF . Results show that the differences between the performances of the published PTF s were substantial. When the systematic bias of each published PTF was removed separately, the prediction capability of the PTF s was increased. The performance of LPTF was significantly better than that of SEM , but slightly worse than IBREM . It is noted that CBREM had higher accuracy than all of the other methods. Overall, CBREM is a promising approach for estimating soil CEC in the study area.

Key concepts: Cation-exchange capacity, Pedotransfer function, Soil science, Soil texture, Soil water, Environmental science, Soil test, Soil fertility

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