Considerations on cross‐linking by bivalent cations in soil organic matter with low exchange capacity

A soil's cation exchange capacity (CEC) is expected to be relatively inert against changes in cation loading. In this study, we treated a soil sample originating from the organic layer of a forest soil with various bivalent cations after removing the native cations. Sorption isotherms and cation exchange capacity were determined, the latter using the BaCl₂ method. Sorption showed Langmuir characteristics, with the maximum coverage (Q_max) increasing in the order Ba²⁺ < Ca²⁺ < Mg²⁺, but being clearly smaller than the initial load of native exchangeable cations. The Langmuir coefficient, k_Me, depended oppositely to the order obtained for Q_max. CEC increased upon cation treatment and it varied by a factor of almost two. The unexpected variation of CEC was explained by the low cation exchange capacity of the organic matter such that not all functional groups are close enough to be bridged and the second charge of a bivalent cation is not neutralized by the organic functional group. The Langmuir sorption type, and Q_max being smaller than the content of sorption sites and being largest for Mg, suggested that only a part of the sites can be cross‐linked and at least part of the cross‐links are formed by hydrated cations. Thermodynamic considerations allowed reconstruction of two contrasting processes during CEC determination by Ba²⁺: Case A: the disruption of cross‐links, which increases with the cationic strength and the cation load before CEC determination, but does not require structural re‐orientation in the SOM matrix, and Case B: the formation of new cross‐links during CEC determination, depending only on the content of unoccupied sites before CEC determination and requiring structural re‐organization of the matrix and thus a minimum matrix flexibility. The use of bivalent cations for CEC determination may thus result in an overestimation of CEC for organic matter with low CEC. This has, however, promising potential when comparing CEC determined with monovalent cations and bivalent cations. Using a set of bivalent cations, may allow probing distribution of distances between functional groups in the organic matter and even characterize the matrix rigidity of the cation‐cross‐linked network.     

Using support vector machines to predict cation exchange capacity of different soil horizons in Qingdao City,China

Agricultural, environmental and ecological modeling requires soil cation exchange capacity (CEC) that is difficult to measure. Pedotransfer functions (PTFs) are thus routinely applied to predict CEC from easily measured physicochemical properties (e.g., texture, soil organic matter, pH). This study developed the support vector machines (SVM)‐based PTFs to predict soil CEC based on 208 soil samples collected from A and B horizons in Qingdao City, Shandong Province, China. The database was randomly split into calibration and validation datasets in proportions of 3:1 using the bootstrap method. The optimal SVM parameters were searched by applying the genetic algorithm (GA). The performance of SVM models was compared to those of multiple stepwise regression (MSR) and artificial neural network (ANN) models. Results show that the accuracy of CEC predicted by SVM improves considerably over those predicted by MSR and ANN. The performance of SVM for B horizon (R² = 0.85) is slightly better than that for A horizon (R² = 0.81). The SVM is a powerful approach in the simulation of nonlinear relationship between CEC and physicochemical properties of widely distributed samples from different soil horizons. Sensitivity analysis was also conducted to explore the influence of each input parameter on the CEC predictions by SVM. The clay content is the most sensitive parameter, followed by soil organic matter and pH, while sand content has the weakest influence. This suggests that clay is the most important predictor for predicting CEC of both soil horizons.     

Influence of soil factors on the soil enzyme inhibition by Cd

A comparative study was conducted on the toxicity of Cd to alkaline phosphatase activity (ALP) and dehydrogenase activity (DHA) in 18 top soils with contrasting soil properties representative of 14 major soil types in China. Soil pH and carbonate content, soil organic matter, and cation exchange capacity (CEC) largely affected the Cd toxicity on two enzyme activities; with the soil pH having only minor effect on the median ecological dose values based on total Cd concentrations (ED_{50 T}). The values of ED_{50 T}/ED_{50 W} (based on water-soluble Cd content) of alkaline phosphatase and dehydrogenase were strongly influenced by pH and CEC contents, which explained up to 71% of the variation for alkaline phosphatase, 82% of the variation for dehydrogenase, and also were significantly correlated with the parameter K_F derived from Freundlich adsorption isotherms. This study suggests that the values of ED_{50 T}/ED_{50 W} could be useful to evaluate the buffer capacity of soils which protects soil enzymes from harmful effects of heavy metal.     

Ammonia volatilization from urea-treated pasture and tillage soils: effects of soil properties

Mean NH₃ losses after nine days incubation at 18°C and 60% FC were 3.1±2.9% and 7.6±6.0% of applied urea-N from the pasture and tillage counterparts of 10 soil series. These losses were highly correlated with buffered CEC and maximal pH values (pH_m) generated three days after urea application. NH₃ volatilization was apparently controlled by buffered CEC and initial pH (R²= 72–87%) and was related to variations in soil organic matter and texture (R²= 77–81%). Losses in the acid pasture soils were attributed largely to initial pH differences, and in the tillage soils to buffered CEC only. Evolution was greater from the tillage than from the pasture equivalent in eight series. This was attributed to differences in CEC, including buffered CEC and pH-dependent charge, caused by differences in OM content primarily but also in texture between the two soil groups. Differences in NH₃ evolution from urea in pasture and tillage soils, in general, are not related to pH differences.     

Soil sampling based on field spatial variability of soil microbial indicators

Microbial indicators exhibit a high spatial heterogeneity which often masks comparison of the effects of different soil management treatments. It is therefore desirable to use a proper sampling design which integrates spatial heterogeneity at field level. Thus, the objectives were: (1) to study the spatial heterogeneity of biological and chemical soil variables, and (2) with obtained maps of spatial variability to test different sampling strategies to assess the usefulness of this ‘new’ soil map unit. 63 soil samples were collected according to a 10 m × 10 m grid on a 0.48 ha plot. On each of these samples, 10 variables were measured: soil water content, cation exchange capacity (CEC), organic carbon (OC) and total nitrogen (N), C/N, soil microbial biomass (SMB), labile soil organic matter (LOM), mineralisable C (C_min) and N (N_min), inverse of specific respiratory activity (1/SRA = SBM/C_min). The spatial heterogeneity of each variable was charted with geostatistics. The biological variables exhibited spatial variability of the same order of magnitude as physicochemical parameters. From the maps, zones with different levels of organic matter, microbial biomass and specific respiratory activity were identified. The spatial patterns of SMB and SRA were related to CEC (positively for SMB and negatively for SRA), pointing out the effects of soil protection on microbial biomass and availability of organic substrates. The definition of these zones for a pool of variables (OC, N, SMB, LOM, CEC) is useful at 3 levels: (1) to record the initial values of the measured variables for each plot, (2) to integrate these zones as blocks in experimental design for future experiments, and (3) to focus analysis of specific biological mechanisms such as activity of micro-organisms.     

Contribution of separate solid-phase components to the formation of the cation exchange capacity in the main genetic horizons of meadow-chestnut soils

Different types of cation exchange capacity (CEC) and related chemical properties were determined in the main genetic horizons of meadow-chestnut soils in the mesodepressions at the Dzhanybek Research Station of the Institute of Forestry of the Russian Academy of Sciences. In the A horizon, the CEC is mainly due to the organic matter from the clay and coarse fractions, which provides 36% of the soil CEC, and to labile silicates and other clay minerals of the clay fraction. In the Bt horizon, the CEC is mainly provided by the labile minerals of the clay fraction and organic matter of the clay and coarse fractions. The standard soil CEC was found to be significantly higher than the sum of the exchangeable cations in the A horizon and slightly lower than the sum of the exchangeable cations in the Bt and Bca2 horizons. This difference can be related to the fact that the NH₄⁺ ion, which is selectively adsorbed by clay minerals, is used as a displacing cation during the determination of the exchangeable bases, while the Ba²⁺ ion, which is more selectively adsorbed by organic matter, is used during the determination of the standard CEC. In all the genetic horizons, the experimentally determined value of the standard CEC almost coincides with the CEC value obtained by summing the standard CECs of the different particle-size fractions with account for their contents; hence, this parameter is additive in nature.     

Soil solution concentration of Cd and Zn canbe predicted with a CaCl2 soil extract

Risk assessment of heavy metals in soil requires an estimate of the concentrations in the soil solution. In spite of the numerous studies on the distribution of Cd and Zn in soil, few measurements of the distribution coefficient in situ, K_d, have been reported. We determined the K_d of soils contaminated with Cd and Zn by measuring metal concentrations in the soil and in the soil solution and attempted to predict them from other soil variables by regression. Soil pH explained most of the variation in logK_d (R² = 0.55 for Cd and 0.70 for Zn). Introducing organic carbon content or cation exchange capacity (CEC) as second explanatory variable improved the prediction (R² = 0.67 for Cd and 0.72 for Zn), but these regression models, however, left more than a factor of 10 of uncertainty in the predicted K_d. This large degree of uncertainty may partly be due to the variable degree of metal fixation in contaminated soils. The labile metal content was measured by isotopic dilution (E value). The E value ranged from 18 to 92% of the total metal content for Cd and from 5 to 68% for Zn. The prediction of K_d improved when metals in solution were assumed to be in equilibrium with the labile metal pool instead of the total metal pool. It seems necessary therefore to discriminate between ‘labile’ and ‘fixed’ pools to predict K_d for Cd and Zn in field contaminated soils accurately. Dilute salt extracts (e.g. 0.01 m CaCl₂) can mimic soil solution and are unlikely to extract metals from the fixed pool. Concentrations of Cd and Zn in the soil solution were predicted from the concentrations of Cd and Zn in a 0.01 m CaCl₂ extract. These predictions were better correlated with the observations for field contaminated soils than the predictions based on the regression equations relating logK_d to soil properties (pH, CEC and organic C).     

Cadmium soil sorption at low concentrations: VIII. correlation with soil parameters

Cadmium distribution coefficients, K _d were determined at low Cd concentrations (solute: 0.2 to 3.0 μg Cd dm^?3, soil: 0.044 to 1.1 mg Cd kg^?1) for 63 Danish agricultural soils. The K _d values ranged from 15 to 2450 L kg^?1. About 40% of the soils had K _d values below 200 L kg^?1. The observed K _d values correlated very well with soil pH (r ² = 0.72). Introducing soil organic matter content as a second parameter improved the correlation some (r ² = 0.79). No further improvements were obtained by introducing traditional soil parameters as clay, silt, fine sand, coarse sand and CEC or ‘reactive’ parameters as oxyhydroxides of Mn, Fe and Al. The identified regression equation for predicting K _d values indicates that K _d approximately doubles for each 0.5 unit increase in pH or 2% increase (weight basis) in organic matter content.     

The effects of electrolyte concentrations on calcium-sodium exchange equilibria in two soil samples of india

The effects of total electrolyte concentrations of the equilibrium solutions (t.e.c.) on Ca²⁺-Na⁺ exchange equilibria in two soil samples (high and low in organic matter, clay content and CEC) were studied. Homoionic (Na⁺-saturated) soil samples were equilibrated with solutions having a large range in sodium adsorption ratio (SAR) at 25, 50, 75 and 100 meq. 1^-1 t.e.c. The exchange equilibria data were analysed, using a thermodynamic approach and the selectivity coefficients of Gapon (1933), Vanselow (1932) and Krishnamoorthy et al. (1948) (K_G, K_V and K_KDO). At a given proportion of Ca²⁺: Na⁺ in the equilibrium solution, the development of the exchangeable sodium percentage (ESP) in both soil samples increased with the increase in t.e.c. At a given SAR, the effect of t.e.c. on the development of ESP was less on a soil sample with high organic matter (O.M.), clay content and cation exchange capacity (CEC) than on a soil sample with low O.M., clay content and CEC. The values of exchange selectivity coefficients decreased with the increase in t.e.c, and did not remain constant throughout the exchange isotherm for any of the t.e.c. tried.     

In situ respiration determination as tool for classifying soils according to soil organic matter content

Abstract

Soil respiration is indicative of biological status of the soil and high respiration is correlated to high contents of available carbon (C) in soil and/or organic matter content. Because of soil respiration's relationship to soil organic matter status and content, soil respiration is considered one measurement that could aid in determining the quality of soil. In the global scale, the cycling of C in soil is important because the rise in CO₂ in the atmosphere is linked to global climate change. In situ measurement of CO₂ using instruments that are portable and perform analyses quickly are important to obtain sufficient number of measurements in the field to overcome spatial variability. Soil respiration tests were conducted in plots amended with fertilizer or organic amendments of agricultural or municipal residues since 1994. Besides CO₂, moisture and temperature were measured over a period where the moisture varied from near saturation to below wilting point. It was found that flux was curvilinearly related to moisture from 5 to 40% (v/v). Maximum flux occurred for all plots between 30 and 40% saturation. The ratio of flux normalized by temperature to the volumetric soil moisture divided soils into two categories, those with soil organic matter (SOM) content above or below 4.5%. The determinations of CO₂ flux, moisture and temperature uses equipment that is portable so that several sites in a field can be analyzed to reduce spatial variation. The only limitation is that the determinations must be performed on soils with less than 40% saturation or 25% moisture (v/v) because the normalized function is no longer linear above this moisture content. More than two SOM categories might be found if studies are expanded to soils with a wider range of SOM content.     

九龙坡花椒种植区地形、土壤肥力与花椒产量的关系

为了解九龙坡花椒种植区土壤养分状况及该区地形因子、土壤肥力因子与花椒产量的关系,为科学合理制定花椒高效施肥措施提供理论依据,本研究采用田间调查研究和室内分析的方法,研究了九龙坡花椒种植区低、中、高产区的海拔、坡度及土壤pH、有机质、大量微量元素含量和交换性能的变化特征,及其与花椒产量的关系。研究结果表明：九龙坡花椒普遍种植于200~500 m海拔范围,高产区集中在300 m左右的海拔;从低产区到高产区坡度略有增加,但未达显著水平。土壤均属酸性土,pH<6.5。土壤肥力总体属高水平范围,但各养分因子差异很大,其中土壤阳离子交换量（CEC）、有效磷、有效钙、有效镁、有效铁、有效锰、有效铜、有效锌含量丰富,分别为27.2 cmol（+）·kg^-1、35.2 mg·kg^-1、3 289.8 mg·kg^-1、271.8 mg·kg^-1、48.6 mg·kg^-1、62.1 mg·kg^-1、1.5 mg·kg^-1、4.5 mg·kg^-1;有机质、碱解氮、速效钾、交换性酸属适中水平,分别为19.1 mg·kg^-1、114.9 mg·kg^-1、107.0 mg·kg^-1、8.1 cmol（+）·kg^-1;水溶性硼缺乏,为0.28 mg·kg^-1。相关分析表明花椒产量与有效钙、CEC、pH、有效锰、水溶性硼呈显著正相关;通径分析结果表明有效钙、CEC、交换性酸、有效铜、有效铁、有效锌是影响花椒产量的主要因子,逐步回归分析构建了有效钙（X₆）与花椒产量（Y）的最优回归线性方程：Y=11.693+0.003X₆。综上所述,九龙坡花椒种植区土壤养分失衡较为严重,施肥应注重养分的平衡,增施有机肥,改善土壤理化性状,治理土壤酸化。     

Soil organic matter composition and soil lightness

Relationships between soil lightness, soil organic matter (SOM) composition, content of organic C, CaCO₃, and texture were studied using 42 top‐soil horizons from different soil types located in southern Germany. SOM composition was determined by CPMAS ¹³C NMR spectroscopy, soil color was measured by diffuse‐reflectance spectrophotometry and given in the CIE L*a*b* color coordination system (Commission Internationale de l'Eclairage, 1978). Multiple‐regression analysis showed, that soil lightness of top‐soil horizons is principally determined by OC concentration, but CaCO₃ and soil texture are also major variables. Soil lightness decreased with increasing OC content. Carbonate content had an important effect on soil lightness even at low concentrations due to its lightening property. Regressions between soil lightness and organic C content were strongly linear, when the soils were differentiated according to texture and CaCO₃ content. The aryl‐C content was the only SOM component which correlated significantly with soil lightness (r_S = –0.87). In the linear regressions carried out on the different soil groups, soil aryl‐C content was a more significant predictor for soil lightness than total OC content.     

Cation exchange capacity of an acid soil as influenced by different sources of organic litter

Abstract

A pot trial was conducted in order to relate the increase in the cation exchange capacity (CEC) of an acid soil (Quartspsament) to the CEC of several organic materials which were added to it. Peat, sugarcane bagasse and filter cake from sugar industry, worm compost, poultry and cattle manure, compost, and papermill sludge were incubated in natural and limed soil under controlled soil water content. Soil CEC was measured at soil pH after 30 and 90 days of incubation and results were strongly affected by pH of the incubated soil. About 32% of the soil CEC would be predicted by the CEC of the organic material measured at pH 7.0. This proportion increased to 78% when soil pH was included in the regression.     

广东省不同母质发育土壤颗粒分布的分形维数特征

采集广东省主要成土母质(玄武岩、砂页岩、第四纪红土和花岗岩)发育的林地、耕地和园地土壤剖面各发生层土壤,测定了土壤颗粒组成、有机质、CEC等理化性质,探讨了不同母质发育土壤颗粒分布的分形维数特征及其与土壤理化性质的关系。结果表明,玄武岩、第四纪红土、花岗岩和砂页岩发育土壤分形维数变幅分别为2.923 9~2.981 2,2.858 8~2.937 7,2.769 3~2.923 1和2.544 6~2.885 6;玄武岩和第四纪红土发育土壤颗粒分布分形维数与砂页岩发育土壤存在显著差异。土壤颗粒分布的分形维数随土壤深度增加呈增大的趋势,相同母质发育土壤的深层土壤颗粒分布的分形维数接近一致。玄武岩和第四纪红土发育土壤颗粒分布的分形维数在不同深度土壤之间变幅较小,砂页岩和花岗岩发育土壤变幅较大。土壤颗粒分布的分形维数与砂粒含量呈极显负相关,与黏粒含量呈极显著正相关,与土壤全磷、速效钾、全铁、CEC、有机质、全氮、碱解氮呈极显著或显著正相关;土壤颗粒分布的分形维数可以作为表征土壤肥力状况指标。     

Evaluation of the soil carbon budget under different upland cropping systems in central Hokkaido,Japan

Abstract

To evaluate the carbon budget in soils under different cropping systems, the carbon dioxide (CO₂) flux from soils was measured in a total of 11 upland crop fields within a small watershed in central Hokkaido over the no snow cover months for 3 years. The CO₂ flux was measured using a closed chamber method at bare plots established in each field to estimate soil organic matter decomposition. Temporal variation in instantaneous soil CO₂ fluxes within the sites was mainly controlled by soil temperature and moisture. Annual mean CO₂ fluxes and cumulative CO₂ emissions had no significant relationship with soil temperature and moisture (P > 0.2). However, there was a significant quadratic relationship between annual mean CO₂ flux or cumulative CO₂ emission and soil clay plus silt content (%) (R² = 0.72～0.74, P < 0.0003). According to this relationship, the optimum condition for soil CO₂ emission is at a clay plus silt content of 63%. The cumulative CO₂ emission during the no snow cover season within each year varied from 1,159 to 7,349 kg C ha^?1 at the different sites. The amount of crop residue carbon retained in the soils following a cropping season was not enough to offset the CO₂ emission from soil organic matter decomposition at all sites. As a consequence, the calculation of the soil carbon budget (i.e. the difference between the carbon added as crop residues and compost and the carbon lost as CO₂ from organic matter decomposition) ranged from –7,349 to –785 kg C ha^?1, except for a wheat site where a positive value of 4,901 kg C ha^?1 was observed because of a large input of organic carbon with compost. The negative values of the soil carbon budget indicate that these cropping systems were net sources of atmospheric CO₂.     

Methane emission and entrapment in flooded rice soils as affected by soil properties

Laboratory incubation experiments were conducted to study the effects of soil chemical and physical properties on CH₄ emission and entrapment in 16 selected soils with a pH range of 4.7–8.1, organic matter content of 0.72–2.38%, and soil texture from silt to clay. There was no significant correlation with CH₄ emission for most of the important soil properties, including soil aerobic pH (measured before anaerobic incubation), total Kjeldahl N, cation exchange capacity, especially soil organic matter, and soil water-soluble C, which were considered to be critical controlling factors of CH₄ emission. A lower CH₄ emission was observed in some soils with a higher organic matter content. Differences in soil Fe and Mn contents and their chemical forms contributed to the this observation. A significant correlation between the CH₄ emission and the soil organic C content was observed only after stratifying soils into subgroups according to the level of CH₄ emission in soils not amended with organic matter. The results also showed that the soil redox potential (Eh), anaerobic pH, anerobic pH, and biologically reducible Fe and Mn affected CH₄ emission significantly. Urea fertilization promoted CH₄ emission in some soils and inhibited it in others. This result appeared to be related to the original soil pH. CH₄ entrapment was positively correlated with soil clay content, indicating the importance of soil physical characteristics in reducing CH₄ emissions to the atmosphere.     

Comparison of the prediction efficiency of two pedotransfer functions for soil cation‐exchange capacity

The aim of this study was to provide knowledge of the prediction efficiency of two pedotransfer functions for soil cation‐exchange capacity (CEC), i.e., the approaches of Krogh et al. (2000) and Scheinost (1995). Potential CEC, i.e., CEC at pH 8.1, was predicted for 30 samples of German soils showing a strong variation of soil organic C and clay content which are important soil characteristics for CEC. The results were compared to analyzed potential CEC of the samples by coefficient‐of‐efficiency (EC) criterion of Nash and Sutcliffe (1970). Significant deviations between observed and measured CEC were found for both functions. The approach of Scheinost (1995) showed a higher prediction efficiency (EC = 0.77 in comparison to EC = 0.26 for Krogh et al., 2000) and better results under extrapolative conditions.     

东北典型县域稻田土壤肥力评价及其空间变异

  【目的】  明确东北典型县域稻田土壤肥力空间变异特征,为该区域稻田土壤合理培肥管理提供科学依据。  【方法】  以黑龙江省方正县为研究区域,2017年在该研究区域采取114个代表性点位的稻田土壤,选取容重、pH、全氮含量、有效磷含量、速效钾含量、有机质含量和阳离子交换量作为土壤综合肥力评价指标,采用相关系数法确定各个指标的权重,根据东北稻田土壤特征,选择隶属度函数曲线,并确定隶属度函数转折点,依据模糊数学法的加乘原理,利用各土壤肥力指标的权重值和隶属度值计算土壤综合肥力指数;采用GIS和地统计学相结合的方法,确定各项肥力指标和综合肥力指数的空间变异特征和分布格局;通过主成分分析探究土壤肥力差异的主控因子。  【结果】  描述性统计分析表明,方正县稻田土壤综合肥力指数在0.18～0.99,平均值为0.60。土壤容重和pH的变异系数分别为9.15%和5.69%,属于弱变异强度,其他肥力指标的变异系数在20.01%～36.18%,属于中等变异强度。地统计学研究表明,土壤容重、全氮含量、有机质含量和阳离子交换量的块金系数在39%～50%,它们具有中等强度的空间自相关性,土壤pH、有效磷含量、速效钾含量和综合肥力指数的块金系数均在25%以下,它们具有强烈的空间自相关性。方正县土壤综合肥力指数值在0.70以上的稻田占16%,在0.60～0.70的稻田占45%。各个肥力指标中,土壤有效磷含量和速效钾含量的分布特征与综合肥力指数相似,呈南高北低的分布格局;土壤pH和阳离子交换量由稻区中部向南北方向逐渐降低;土壤容重由西北向东南呈逐渐降低的趋势;土壤有机质和全氮含量均表现为由东南向西北逐渐降低的趋势,土壤有机质含量在30 g/kg以上的稻田占比为97%,土壤全氮含量在1.5 g/kg以上的稻田占比为84%;其中北部蚂蚁河沿岸土壤全氮、有效磷、速效钾和有机质含量相对较低。利用主成分分析得到各项肥力指标的综合得分值由大到小依次为:土壤有效磷含量、速效钾含量、有机质含量、阳离子交换量、全氮含量、pH和容重。  【结论】  方正县61%的稻田土壤肥力处于中等及以上水平,稻田土壤肥力整体呈现出南高北低的分布格局。土壤有效磷和速效钾含量是造成土壤肥力差异的主要因子。     

贵州表层土壤有机质空间变异特征及其影响因素分析

为探究贵州表层土壤有机质的空间变异特征及其主要影响因素,使用贵州省第二次土壤普查资料中193个土壤剖面数据,结合贵州省气象资料、土地利用类型图及土壤类型图等资料,运用地统计学和多元回归分析各因素对表层土壤有机质空间变异的解释能力。结果表明：(1)贵州省表层土壤有机质含量范围为0.05%～36.68%,平均含量为5.23%±4.96%,变异系数为94.90%;(2)表层土壤有机质在空间分布上表现出东北部高,西南部较低的格局;(3)半变异函数分析表明,贵州省土壤有机质主要受自然因素影响,海拔、CEC、耕作方式和土壤质地对表层土壤有机质含量变异的综合解释能力为35.9%,海拔作为最重要的影响因素能独立解释其变异的25.6%,CEC和耕作方式分别能解释11.3%,7.4%。贵州表层土壤有机质与年均气温呈负相关关系,与海拔呈正相关关系。研究区表层土壤有机质的分布与碳酸盐岩分布面积比例存在相关关系,整体上,随着喀斯特分布面积比例增大而受自然因素影响增大。喀斯特分布面积比例为0～10%区域主要受农业耕作施肥等人类活动的影响,11%～30%区域主要受海拔影响,31%～50%区域受年均温和CEC影响,5...