Soil cation exchange capacity (CEC) is one of the most important chemical characteristics of agricultural lands , which can influence the stability of soil structure, nutrient availability, soil pH and the soil’s reaction to fertilizers and other ameliorants, provide a buffer against soil acidification . CEC is often used as a measure of soil fertility, nutrient retention capacity , and also used as an identification and classification index of soil types in soil taxonomy  , in which the NH4OAc (pH = 7.0) exchange method   is recommended to determine CEC for all soils with different pH values. However, for highly-weathered acid soils in the tropical and subtropical regions, the BaCl2-MgSO4 forced-exchange method , which doesn’t adjust pH of soil samples, is recommended to determining CEC. Comparatively, because the buffer salt system (pH = 7.0) in the first method will increase soil pH, thus will increase the charge of soil colloids and result in higher measurement results  , which may lead to the misjudgment of soil types .
But so far, little is known about the difference in CEC values determined by the two methods, thus, in this study the physiochemical data of 114 acid B horizon soils from 112 soil series in the tropical and subtropical regions of south China were used to: 1) disclose the difference in CEC values determined by the two methods, 2) clarify the influencing factors of the difference, and 3) setup the regression model for predicting CEC2 by CEC1.
2. Materials and Methods
2.1. Background of Tested Soil Samples
Figure 1 shows the spatial distribution of used 112 soil series in the tropical and subtropical regions of south China  - . For a soil sample, the particle size distribution was determined by the pipette method, pH was measured with by the potentiometer method (soil:water = 1:2.5), organic matter was obtained by the Walkley-Black wet oxidation method, free Fe2O3 was determined by the phenanthroline colorimetry method, CEC was analyzed by the NH4OAc (pH = 7.0) exchange method (CEC1)   and the BaCl2-MgSO4 forced-exchange method (CEC2) , respectively.
2.2. Data Statistical Analysis
Microsoft Excel 2016 and IBM Statistics SPSS 22.0 software were used for statistical analysis of the data, and Duncan test method (2-tailed) was used for variance analyses and multiple comparisons.
Figure 1. Spatial distribution of used 112 soil series in tropical and subtropical regions of south China.
3.1. Statistical Results of Soil Physiochemical Properties
Table 1 lists the measured values of soil physiochemical properties, it showed that CEC1 ranged from 5.12 to 35.41 cmol(+) kg−1 with a mean of 12.40 cmol(+) kg−1, while CEC2 ranged from 2.22 to 6.60 cmol(+) kg−1 with a mean of 4.16 cmol(+) kg−1. Comparatively, CEC2 was significantly lower than CEC1 (p < 0.01), CEC2 was 14.76% - 63.31% with a mean of 36.32% of CEC1.
Table 1 also showed that clay content was meanly 412 g·kg−1, while sand content was meanly 281 g·kg−1; meanwhile, free Fe2O3 content was meanly 44.01 g·kg−1, which prove further that soils in the tropical and subtropical regions of south China are clayey and rich in free Fe2O3 .
3.2. Factors Influencing CEC1, CEC2 and Their Difference
Table 2 lists the correlation between CEC1, CEC2 and the difference between CEC1 and CEC2 (ΔCEC, CEC1-CEC2) with other properties. It could be found that pH had significant positive correlation with CEC1 (p < 0.01), CEC2 (p < 0.01) and ΔCEC (p < 0.05), free Fe2O3 had significant positive correlation with CEC1 and ΔCEC (p < 0.01), sand content had significant negative correlation with CEC1 and ΔCEC (p < 0.05), silt content had significant positive correlation with CEC1 (p < 0.05) and CEC2(p < 0.01), while clay content had significant negative correlation with CEC2 (p < 0.05).
Table 1. Statical descriptions of soil chemical properties.
Note: 1) Sand, silt, clay, SOM and free Fe2O3, g·kg−1; CEC1 and CEC2, cmol(+) kg−1; 2) CEC1 and CEC2, determined by the methods of NH4OAc (pH = 7.0) and BaCl2-MgSO4, respectively. The same below; 3) data of CEC1 and CEC2 followed by different capitals are significantly different at p < 0.01 level.
Table 2. Pearson correlation between soil CEC and other properties.
Note: 1) *, **, Correlation is significant at p < 0.05 or 0.01 level (2-tailed)l; 2) ΔCEC = CEC1 − CEC2.
The contribution of one property to CEC was calculated as the follows: firstly, all properties were normalized by the Z-score method with IBM Statistics SPSS 20.0 to ensure them with the same magnitude, and then the regression coefficients between each property with CEC was used to indicate their contribution to CEC   . The contribution of one property (Ci) to CEC was calculated as Ci = Ki/Ksum, in which Ki is the regression coefficient of the i property, and Ksum is the total sum of all coefficients, the obtained linear regression models of CEC with other properties were listed in Table 3, and the calculated contribution of other properties to CEC were listed in Table 4.
In view of the contribution of other properties to CEC, it can be seen from Table 4 that CEC1 was mainly decided by free Fe2O3 (40.38%), followed by pH and silt content (28.39% and 27.29%, respectively); CEC2 was mainly determined by pH (45.92%), followed by silt content (21.05%), then followed by free Fe2O3 and clay content (17.35% and 12.76%, respectively), and ΔCEC was mainly affected by free Fe2O3 (50.92%), followed by silt content and pH (26.46% and 21.80%, respectively).
Table 3. Linear regression model between CEC and other soil properties.
Table 4. Contribution of other soil properties to CEC.
3.3. CEC2 Predicting Model Based on CEC1
The scatter diagram of CEC2 and CEC1 are shown in Figure 2, and IBM statistics SPSS 20.0 was used to obtain the optimal regression model between CEC2 and CEC1. It could be found from Figure 2 that a significant positive power correlation between CEC2 and CEC1, and the optimal regression model was as CEC2 = 2.3114 × (R2 = 0.410**, P < 0.001 F = 77.99, RMSE = 0.15, RMSE/S.D = 0.19).
4.1. Value Difference CEC Determined by Different Methods
For highly-weathered acid soils in the subtropical and tropical regions, because the buffer salt system (pH = 7.0) could increase soil pH, thus would increase the charge of soil colloids, so CEC determined by the NH4OAc (pH = 7.0) exchange method (CEC1) usually is higher than that determined by the BaCl2-MgSO4 forced-exchange method (CEC2)  . Our study quantitatively assessed this phenomenon, for the acid B horizon soils in the subtropical and tropical regions of south China, CEC2 was significantly lower (P < 0.01) than CEC1, the former meanly 36.32% of the latter (see Table 1).
Our study also disclosed the differences in the influencing factors of CEC1 and CEC2, in which pH and silt content were the common factors of CEC1 and CEC2, but CEC1 was also influenced by free Fe2O3 and sand content, while CEC2 was also affected by clay content (see Table 2). Furthermore, our study proved further that the difference between CEC1 and CEC2 was mainly decided by free Fe2O3 content (the contribution was 50.92%, see Table 4), followed by silt content and pH (the contributions were 26.46% and 21.80%, respectively, see Table 4), while little or no effect from sand and clay contents.
4.2. Influencing Factors of CEC
Table 5 lists the correlation between CEC and other properties of soils found in
Figure 2. Relationship between soil CEC1 and CEC2 determined by methods of NH4OAc (pH = 7.0) and BaCl2-MgSO4, respectively.
Table 5. Correlation between soil CEC and other properties in published literatures.
some previous studies. pH usually has significant negative correlation with CEC for soils with high pH (for example, higher than 7.0)     but has positive correlation with CEC for soils with low pH (for example, lower than 7.0)     . Since all soil samples used in our study were acid (pH < 7.0), so significant positive correlation was found in our study between pH and CEC1 and CEC2.
SOM usually has significant positive correlation with CEC    - , but our results showed that SOM had no significant correlation with CEC1 and CEC2 (Pearson correlation coefficient was 0.069 and 0.001, respectively, See Table 2; contribution to CEC was 1.42% and 2.93%, respectively, see Table 4), which could be attributed to the low SOM content     in B horizon soils in the subtropical and tropical regions of south China (mean SOM content was 8.24 g·kg−1 in our study).
Clay content usually also has significant positive correlation with CEC of humid soils  - , but our results showed that clay had no significant correlation with CEC1 (R was 0.060, see Table 2; contribution to CEC was 2.52%, see Table 4) and had weak negative significant correlation with CEC2 (R was 0.220, p < 0.05, see Table 2; contribution to CEC was 12.76%, see Table 4), which could be attributed to greater microaggregating effect of Fe oxides in highly-weathered soils in the tropical and subtropical regions , which enhanced the participation of clay in the microaggregation, reduced the amount of “free” clay particles, thus decreased clay contribution to CEC . Few studies analyzed the correlation between free Fe2O3 and CEC because free Fe2O3 in subtropical and tropical highly-weathered soils usually exist as clay fraction or strongly cemented with clays   , so more attentions were paid to the correlation between clay content rather than free Fe2O3 with CEC (p < 0.01). However, our studies found that free Fe2O3 was significantly correlated with CEC1, while clay content was significantly correlated with CEC2 (p < 0.05).
Our study also found that CEC1 had negative correlation with sand content, which is consist with the previous studies     , while CEC2 had significant positive correlation with silt content as found in other studies  , which could be attributed to that in subtropical and tropical humid climate soils, sand fraction is mainly composed of quartz and iron concretions which present low charge density , while the silt fraction is often composed of vermiculite and mica minerals which can hold negative charges .
4.3. Recommendation Using CEC2 Predicting Model for Soil Taxonomy
In Chinese Soil Taxonomy, the LAC-ferric horizon is the diagnostic horizon for Ferrosols, one of its requirements is that CEC7 < 24 cmol (+) kg−1 clay in partial B horizons (≥10 cm in thickness) . However, CEC7clay is not directly measured by the extracted clays, it was calculated as: soil CEC7 × 1000/clay content . Our study shows that for B horizons of the highly-weathered acid soils in the tropical and subtropical regions of south China, CEC determined by the NH4OAc (pH = 7.0) exchange method is 1.58 - 6.78 times with a mean of 2.96 times of that decided by the BaCl2-MgSO4 forced-exchange method. This obvious overestimation of CEC  is most likely to lead to some authentic LAC-ferric horizons being misjudged as other diagnostic horizons, thus leading to misjudgment of soil types . However, since the NH4OAc (pH = 7.0) exchange method was used in almost all previous studies on soil taxonomy, thus, to verify the identification accuracy of soil types in the previous studies, the CEC2 predicting model established in our study based on CEC1 is recommended to obtain CEC of highly-weathered acid soils in the tropical and subtropical regions in order to ensure the accurate identification of soil types. Nevertheless, for the future studies, it is recommended to using the BaCl2-MgSO4 forced-exchange method for CEC determination of the highly-weathered acid soils in the tropical and subtropical regions.
Our study quantitatively proved that for the highly-weathered acid soils in the tropical and subtropical regions of south China, CEC determined by the NH4OAc (pH = 7.0) exchange method was significantly higher than that determined by the BaCl2-MgSO4 forced-exchange method. CEC of the former method was mainly affected by free Fe2O3 and pH, followed by silt and sand contents, while CEC of the latter method was mainly affected by pH, followed by silt and clay contents. CEC differences between the two methods were mainly influenced by free Fe2O3, followed by sand content and pH. For the studies on soil taxonomy, the BaCl2-MgSO4 forced-exchange method is recommended for CEC determination of the highly-weathered acid soils in the tropical and subtropical regions.
This study was supported by projects of the National Natural Science Foundation of China (No. 41877008) and the National S&T Basic Special Foundation Project (No. 2014FY110200). We would like to express thanks to the contribution of all colleagues in the data preparation and the establishment of the soil series.
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