Prediction of Soil Organic Carbon at the European Scale by Visible and Near InfraRed Reflectance Spectroscopy

Soil organic carbon is a key soil property related to soil fertility, aggregate stability and the exchange of CO₂ with the atmosphere. Existing soil maps and inventories can rarely be used to monitor the state and evolution in soil organic carbon content due to their poor spatial resolution, lack of consistency and high updating costs. Visible and Near Infrared diffuse reflectance spectroscopy is an alternative method to provide cheap and high-density soil data. However, there are still some uncertainties on its capacity to produce reliable predictions for areas characterized by large soil diversity. Using a large-scale EU soil survey of about 20,000 samples and covering 23 countries, we assessed the performance of reflectance spectroscopy for the prediction of soil organic carbon content. The best calibrations achieved a root mean square error ranging from 4 to 15 g C kg⁻¹ for mineral soils and a root mean square error of 50 g C kg⁻¹ for organic soil materials. Model errors are shown to be related to the levels of soil organic carbon and variations in other soil properties such as sand and clay content. Although errors are ∼5 times larger than the reproducibility error of the laboratory method, reflectance spectroscopy provides unbiased predictions of the soil organic carbon content. Such estimates could be used for assessing the mean soil organic carbon content of large geographical entities or countries. This study is a first step towards providing uniform continental-scale spectroscopic estimations of soil organic carbon, meeting an increasing demand for information on the state of the soil that can be used in biogeochemical models and the monitoring of soil degradation.     

The retention of organic matter in soils

The turnover of C in soils is controlled mainly by water regimes and temperature, but is modified by factors such as size and physicochemical properties of C additions in litter or root systems, distribution of C throughout the soil as root systems, or addition as litter, distribution of C within the soil matrix and its interaction with clay surfaces.Soil factors which retard mineralization of C in soils are identified from correlations of C contents of soils with other properties such as clay content and base status. The rate and extent of C mineralization depends on the chemistry of the added organic matter and interaction with clays of the microbial biomass and metabolites.The organomineral interactions are shown to depend on cation bridges involving mainly Ca in neutral to alkaline soils, Al in acid soils and adsorption of organic materials on iron oxide surfaces. The various organomineral interactions lead to aggregations of clay particles and organic materials, which stabilizes both soil structure and the carbon compounds within the aggregates.     

Pyrolysis-field ionization mass spectrometry of agricultural soils and humic substances: Effect of cropping systems and influence of the mineral matrix

Whole soil samples, extracted humic substances, the corresponding fulvic (FA) and humic acids (HA) and the extraction residues (humins) from long-term, agricultural test plots were investigated by in-source pyrolysis-field ionization mass spectrometry (Py-FIMS). For the soils distinct differences in the chemical composition of the organic matter in differently managed fields were observed. The FI mass spectra of the extracted humic substances gave complementary chemical information, as they cover a larger mass range compared to the whole soil spectra. The chemical, structural information of the conventional alkaline extraction residues was demonstrated by Py-FIMS spectra to be similar to that of the related soil samples. Influences of mineral matrix to organic matter ratios were studied on mixtures of extracted humic substances with defined mineral components such as quartz, basalt, iron oxide (Fe₂O₃), Ca-montmorillonite, kaolinite and illite. It was shown that in these mixtures the number of mass signals detected and the covered mass range decreased, when organic carbon concentrations (C_org) in this synthetic mineral matrix dropped below 2% (w/w). Limitations in the direct application of Py-FIMS might arise in the case of natural soil samples with C_org concentrations below 0.5% (w/w), high contents of swelling clay minerals and iron oxides. ei]{gnR}{fnMerckx}     

Association of Soil Aggregation with the Distribution and Quality of Organic Carbon in Soil along an Elevation Gradient on Wuyi Mountain in China

Forest soils play a critical role in the sequestration of atmospheric CO₂ and subsequent attenuation of global warming. The nature and properties of organic matter in soils have an influence on the sequestration of carbon. In this study, soils were collected from representative forestlands, including a subtropical evergreen broad-leaved forest (EBF), a coniferous forest (CF), a subalpine dwarf forest (DF), and alpine meadow (AM) along an elevation gradient on Wuyi Mountain, which is located in a subtropical area of southeastern China. These soil samples were analyzed in the laboratory to examine the distribution and speciation of organic carbon (OC) within different size fractions of water-stable soil aggregates, and subsequently to determine effects on carbon sequestration. Soil aggregation rate increased with increasing elevation. Soil aggregation rate, rather than soil temperature, moisture or clay content, showed the strongest correlation with OC in bulk soil, indicating soil structure was the critical factor in carbon sequestration of Wuyi Mountain. The content of coarse particulate organic matter fraction, rather than the silt and clay particles, represented OC stock in bulk soil and different soil aggregate fractions. With increasing soil aggregation rate, more carbon was accumulated within the macroaggregates, particularly within the coarse particulate organic matter fraction (250–2000 μm), rather than within the microaggregates (53–250μm) or silt and clay particles (< 53μm). In consideration of the high instability of macroaggregates and the liability of SOC within them, further research is needed to verify whether highly-aggregated soils at higher altitudes are more likely to lose SOC under warmer conditions.     

Prediction of soil carbon levels in calcareous soils of Iran by mid-infrared reflectance spectroscopy

The objective of this study was to assess the predictive performance of midDRIFTS-PLSR models in quantifying total carbon (TC), total organic carbon (TOC), total inorganic carbon (TIC), total nitrogen (TN), hot water extractable carbon and nitrogen (C_HWE, N_HWE), pH, and the clay, silt, and sand content of soils. A total of 68 soil samples were taken across an agroecological region in southwest Iran, and analyzed in the laboratory using mid-DRIFTS-PLSR. midDRIFTS-PLSR calibration models were developed, and external validation was performed for each of the soil properties via an independent algorithm. The calibration and validation models allowed for a sufficient prediction of TC, TIC, and TOC with residual prediction deviations ≥3 and R² values >0.9. The precise prediction ofcarbon fractions, such as TC, TIC, and TOC, in a rapid and inexpensive manner confirmed that midDRIFTS analysis was a rapid-throughput and cost-effective technique for monitoring soil carbon at the regional scale.     

Three-Dimensional Mapping of Soil Chemical Characteristics at Micrometric Scale by Combining 2D SEM-EDX Data and 3D X-Ray CT Images

There is currently a significant need to improve our understanding of the factors that control a number of critical soil processes by integrating physical, chemical and biological measurements on soils at microscopic scales to help produce 3D maps of the related properties. Because of technological limitations, most chemical and biological measurements can be carried out only on exposed soil surfaces or 2-dimensional cuts through soil samples. Methods need to be developed to produce 3D maps of soil properties based on spatial sequences of 2D maps. In this general context, the objective of the research described here was to develop a method to generate 3D maps of soil chemical properties at the microscale by combining 2D SEM-EDX data with 3D X-ray computed tomography images. A statistical approach using the regression tree method and ordinary kriging applied to the residuals was developed and applied to predict the 3D spatial distribution of carbon, silicon, iron, and oxygen at the microscale. The spatial correlation between the X-ray grayscale intensities and the chemical maps made it possible to use a regression-tree model as an initial step to predict the 3D chemical composition. For chemical elements, e.g., iron, that are sparsely distributed in a soil sample, the regression-tree model provides a good prediction, explaining as much as 90% of the variability in some of the data. However, for chemical elements that are more homogenously distributed, such as carbon, silicon, or oxygen, the additional kriging of the regression tree residuals improved significantly the prediction with an increase in the R² value from 0.221 to 0.324 for carbon, 0.312 to 0.423 for silicon, and 0.218 to 0.374 for oxygen, respectively. The present research develops for the first time an integrated experimental and theoretical framework, which combines geostatistical methods with imaging techniques to unveil the 3-D chemical structure of soil at very fine scales. The methodology presented in this study can be easily adapted and applied to other types of data such as bacterial or fungal population densities for the 3D characterization of microbial distribution.     

气候、植被及土壤因素交互作用对宁夏土壤有机碳的影响机制

基于宁夏全区121个土壤剖面样点,研究不同深度(0—30、30—80、80—120cm)土壤有机碳的空间分布特征,通过相关性、方差分解和构建结构方程模型,分析气候、植被和土壤因素对宁夏不同深度土壤有机碳的影响及其作用途径。结果表明：(1)宁夏不同深度土壤有机碳含量均呈现中间低南北高的空间分布趋势,0—120cm剖面土壤有机碳含量随着土壤深度的增加而降低,土壤有机碳含量均值为5.49g/kg,变异系数达90.71%,含量偏低且空间异质性强。(2)各土层土壤有机碳与年均气温、干燥度、碳酸钙、pH均呈现极显著的负相关性(P<0.01),与年均降水量、相对湿度、植被净初级生产力、全氮、全磷、全钾、钙离子、阳离子交换量、粘粒含量均呈现极显著的正相关性(P<0.01)。(3)各因素对不同土层土壤有机碳的作用方式和影响程度有差异。土壤全氮、全磷、碳酸钙、阳离子交换量均能直接影响土壤有机碳,年均气温和植被净初级生产力对土壤有机碳的直接影响效应不显著,主要通过土壤属性间接影响土壤有机碳含量。随着土层深度的增加,气候和植被因素作用明显减弱,土壤因素作用增强并成为主要影响因素。该结果有助于宁夏土...     

Laboratory investigations of mars: Chemical and spectroscopic characteristics of a suite of clays as Mars Soil Analogs

Two major questions have been raised by prior explorations of Mars. Has there ever been abundant water on Mars? Why is the iron found in the Martian soil not readily seen in the reflectance spectra of the surface? The work reported here describes a model soil system of Mars Soil Analog Materials, MarSAM, with attributes which could help resolve both of these dilemmas. The first set of MarSAM consisted of a suite of variably iron/calcium-exchanged montmorillonite clays. Several properties, including chemical composition, surface-ion composition, water adsorption isotherms, and reflectance spectra, of these clays have been examined. Also, simulations of the Viking Labeled Release Experiment using the MarSAM were performed. The results of these studies show that surface iron and adsorbed water are important determinants of clay behavior as evidenced by changes in reflectance, water absorption, and clay surface reactions. Thus, these materials provide a model soil system which reasonably satisfies the constraints imposed by the Viking analyses and remote spectral observations of the Martian surface, and which offers a sink for significant amounts of water. Finally, our initial results may provide insights into the mechanisms of reactions that occur on clay surfaces as well as a more specific approach to determining the mineralogy of Martian soils.     

亚热带不同林分土壤表层有机碳组成及其稳定性

在浙江临安玲珑山选取了常绿阔叶林、马尾松林、板栗林和雷竹林4种林分,采用传统的化学方法与固态13C核磁共振(NMR)技术研究其土壤有机碳在不同粒径土壤颗粒中的分布规律和结构特征,探讨林分类别和管理措施对土壤有机碳含量及其结构的影响,为亚热带地区森林固碳和土壤碳库管理提供科学依据。结果显示:(1)土壤表层(0—20 cm)有机碳含量按以下次序递减:雷竹林>常绿阔叶林>马尾松林>板栗林,且板栗林以粉黏粒结合态碳为主,其他林分土壤则以粗砂结合态碳为主;(2)13C NMR结果表明,阔叶林和马尾松林土壤有机碳中烷基碳所占比例最大,而雷竹林和板栗林则是烷氧碳比例最大,表明人工经营措施改变了土壤有机碳的成分组成;(3)随着土壤颗粒变细,有机碳中烷基碳比例增加,烷氧碳比例减少,A/O-A值和疏水碳/亲水碳值逐渐增大,表明颗粒越细,其结合的有机碳结构稳定性越高。     

High resolution mapping of sediment organic matter from acoustic reflectance data

Spatial mapping of the marine environment is challenging when the properties concerned are difficult to measure except by shore-based analysis of discrete samples of material, usually from sparsely distributed sites. This is the case for many seabed sediment properties. We developed an indirect approach to mapping the organic content of coastal sediments from hydro-acoustic reflectance data. The basis was that both organic matter and acoustic reflectance are related to sediment type and grain size composition. Hence there is a collateral relationship between organic matter content and reflectance properties which can be exploited to enable high resolution mapping. We surveyed an area of seabed off the east coast of Scotland using a vessel mounted single beam echosounder with RoxAnn signal processing. Organic carbon, nitrogen and phytoplankton pigment contents were then measured in material from grab and core samples collected at intervals over a year. Relationships between the organic components and hydro–acoustic characteristics were derived by general additive models, and used to construct high resolution maps from the acoustic survey data. Our method is an advance on traditional interpolation techniques sparse spatial data, and represents a generic approach that could be applied to other properties.     

可溶性有机碳在米槠天然林不同土层中的迁移特征

选取我国中亚热带典型的常绿阔叶林米槠天然林(Castanopsis carlesii)为研究对象,采集林内米槠凋落物并通过挖剖面法分6个土层采集土样至1m。通过浸提米槠凋落物得到可溶性有机碳(dissolved organic carbon,DOC)溶液并在室内模拟其在不同土层的淋溶过程,不仅分析了土壤性质对DOC淋溶的影响,还研究了淋溶前后DOC化学结构的变化,以阐明DOC在不同土层中的迁移特征及影响因素,探寻米槠天然林土壤的固碳潜力和DOC在土壤有机碳循环中的作用。结果表明:(1)下层土壤比上层土壤吸附DOC的能力更强,亲水性DOC与疏水性DOC间会争夺土壤颗粒表面的吸附位点,而且芳香化合物和大分子物质等疏水性DOC组分会被优先吸附;(2)红外光谱表明,芳香类和醚类等疏水性物质会优先被吸附,烷烃类物质却不易被吸附,土壤中原有的酚、醇类亲水性物质会被初始DOC中的疏水性物质置换出来;(3)土壤DOC的截留能力与粘粒、游离氧化铁含量呈极显著正相关,而与土壤有机碳和砂粒含量呈极显著负相关,其中土壤有机碳的含量是影响米槠天然林不同土层DOC截留量的关键因素。     

Inter-regional predictability of cation-exchange capacity by multiple regression

Summary Based on 125 surface soil samples, a multiple-regression prediction equation of the form, CEC=b₀+b₁ (% clay) +b₂ (% organic matter) was developed for Mississippi soils. These data plus data from comparable studies in Ohio, Wisconsin, North Carolina, and Florida were utilized to develop a relationship between the percentage contribution of organic matter to CEC and the clay content of the horizon. Multiple-regression equations from Mississippi, Florida, and Wisconsin studies were employed with data from Mississippi soils to determine the amount of variation between predicted and reported values of CEC. Although statistical differences were found between the three populations, the majority of these differences are within the realm of laboratory error, and it appears feasible to develop inter-regional CEC prediction equations.     

Stabilization of recent soil carbon in the humid tropics following land use changes: evidence from aggregate fractionation and stable isotope analyses

Quantitative knowledge of stabilization- and decomposition processes is necessary to understand, assess and predict effects of land use changes on storage and stability of soil organic carbon (soil C) in the tropics. Although it is well documented that different soil types have different soil C stocks, it is presently unknown how different soil types affect the stability of recently formed soil C. Here, we analyze the main controls of soil C storage in the top 0.1 m of soils developed on Tertiary sediments and soils developed on volcanic ashes. Using a combination of fractionation techniques with ¹³C isotopes analyses we had the opportunity to trace origin and stability of soil carbon in different aggregate fractions under pasture and secondary forest. Soil C contents were higher in volcanic ash soils (47–130 g kg⁻¹) than in sedimentary soils (19–50 g kg⁻¹). Mean residence time (MRT) of forest-derived carbon in pastures increased from 37 to 57 years with increasing silt + clay content in sedimentary soils, but was independent from soil properties in volcanic ash soils. MRTs of pasture-derived carbon in secondary forests were considerably shorter, especially in volcanic ash soils, where no pasture-derived carbon could be detected in any of the four studied secondary forests. The implications of these results are that the MRT of recently incorporated organic carbon depends on clay mineralogy and is longer in soils dominated by smectite than non-crystalline minerals. Our results show that the presence of soil C stabilization processes, does not necessarily mean that recent incorporated soil C will also be effectively stabilized.     

基于数字土壤制图技术的土壤有机碳储量估算

精准的土壤属性空间分布信息有助于提升土壤有机碳储量估算的精度。本研究以河南省济源市南山林场为研究区,以地形因子为预测因子,利用模糊C均值(FCM)聚类方法对土壤有机碳含量、土壤容重、土壤厚度和土壤砾石含量进行数字土壤预测制图,基于数字制图结果实现土壤有机碳密度预测制图和土壤有机碳储量估算。结果表明: 基于数字土壤制图方法得到的研究区土壤有机碳密度平均值为4.24 kg·m^-2,其预测图的平均误差(ME)为0.08 kg·m^-2,平均绝对误差(MAE)为2.80 kg·m^-2,均方根误差(RMSE)为5.03 kg·m^-2,与传统类型方法相比,预测结果的精度和稳定性更高,具有较高的可信度,最终估算得到研究区土壤有机碳储量为3.08×10⁸ kg。基于数字土壤制图技术仅采用少量土壤样点即可实现较高精度的土壤有机碳密度制图和储量估算,且能表征土壤有机碳密度空间分布特征。本研究为土壤有机碳储量估算提供了新途径,有助于提升土壤有机碳储量估算的精度和效率。     

Modeling Soil Organic Carbon at Regional Scale by Combining Multi-Spectral Images with Laboratory Spectra

There is a great challenge in combining soil proximal spectra and remote sensing spectra to improve the accuracy of soil organic carbon (SOC) models. This is primarily because mixing of spectral data from different sources and technologies to improve soil models is still in its infancy. The first objective of this study was to integrate information of SOC derived from visible near-infrared reflectance (Vis-NIR) spectra in the laboratory with remote sensing (RS) images to improve predictions of topsoil SOC in the Skjern river catchment, Denmark. The second objective was to improve SOC prediction results by separately modeling uplands and wetlands. A total of 328 topsoil samples were collected and analyzed for SOC. Satellite Pour l’Observation de la Terre (SPOT5), Landsat Data Continuity Mission (Landsat 8) images, laboratory Vis-NIR and other ancillary environmental data including terrain parameters and soil maps were compiled to predict topsoil SOC using Cubist regression and Bayesian kriging. The results showed that the model developed from RS data, ancillary environmental data and laboratory spectral data yielded a lower root mean square error (RMSE) (2.8%) and higher R² (0.59) than the model developed from only RS data and ancillary environmental data (RMSE: 3.6%, R²: 0.46). Plant-available water (PAW) was the most important predictor for all the models because of its close relationship with soil organic matter content. Moreover, vegetation indices, such as the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI), were very important predictors in SOC spatial models. Furthermore, the ‘upland model’ was able to more accurately predict SOC compared with the ‘upland & wetland model’. However, the separately calibrated ‘upland and wetland model’ did not improve the prediction accuracy for wetland sites, since it was not possible to adequately discriminate the vegetation in the RS summer images. We conclude that laboratory Vis-NIR spectroscopy adds critical information that significantly improves the prediction accuracy of SOC compared to using RS data alone. We recommend the incorporation of laboratory spectra with RS data and other environmental data to improve soil spatial modeling and digital soil mapping (DSM).     

Quantification and correlation of vesicular-arbuscular mycorrhizal propagules with soil properties of some mollisols of northern India

The populations of vesicular-arbuscular mycorrhizae (VAM) propagules by the most probable number method in some mollisols and their correlations with some important soil properties were determined. On average, the six soils, Phoolbagh clay loam, Beni silty clay loam, Haldi loam, Nagla loam, Khamia sandy loam and Patherchatta sandy loam contained 4.9, 4.0, 7.9, 7.9, 3.3 and 13.0 propagules/g soil, respectively, i.e. none of the soils was found to be high in VAM. The size of the VAM population was compared to soil properties such as pH, organic carbon, sand content, available phosphorus and available potassium, cation-exchange capacity, silt and clay contents. A significant positive correlation (r=0.586) was only found with available soil phosphorus (P<0.05) and a significant negative correlation (r=-0.555) with soil clay content (P<0.05).Directorate research paper series No. 7862     

Contribution of organic carbon and clay to cation exchange capacity in a chronosequence of sandy soils

Summary CEC and oxidisable carbon content were highly correlated (r=0.96) whereas a lower coefficient was obtained for a correlation of CEC and clay content (r=0.57) in a chronosequence of sandy soils from New Zealand. Partial regression coefficients for oxidisable carbon were highly significant in multiple regression equations for all soil groupings whereas in only one equation was the coefficient for clay significant. The CEC of the organic matter for all soils was 1.4 me/g and this value decreased from 1.64 me/g in the young soils to 1.22 me/g in old soils. Peroxidation of selected surface samples caused a reduction in CEC but the results indicated that the clay fractions had a considerably higher CEC (0.57 me/g) than that inferred from multiple regression equations for untreated samples. Selective dissolution analysis indicated that the clay fractions of these soils contained an appreciable amount of amorphous material. Reduction in the CEC of the clay fraction apparently occurs through a blocking by organic matter of the negative charge of the clay components.     

Regulatory effects of soil properties on background N2O emissions from agricultural soils in China

The background nitrous oxide (N₂O) emission (BNE) from agricultural soils originates from microbial nitrification and denitrification processes of soil nitrogen supplies, excluding emissions from nitrogen fertilizers applied in the current year. It is of great necessity to quantify BNE accurately at various spatial scales since BNE contributes considerably to the overall N₂O emissions from croplands. Annual BNE rates across various soil/climate regions and major cropping systems of China were determined by network observations during 2002–2006 using the static chamber technique. The observations show BNE rates ranging from 0.1 to 3.67 kg N ha⁻¹ year⁻¹, with a mean of 1.35 kg N ha⁻¹ year⁻¹. Empirical functions are derived for cultivated mineral soils and describe the dependences of annual BNE rates upon soil total nitrogen (TN) content, soil organic carbon (SOC) content, bulk density (BD) and clay fraction (CF), separately or collectively. These empirical functions provide simple approaches to scale up estimated national/regional BNE inventories using available database of soil properties surveys and cropland area statistics. The national BNE of China is estimated to be 0.114–0.184 Tg (1 Tg = 10¹² g) N year⁻¹ in 2000, with the range being due to the use of different approaches. However, the available observations of annual BNE rates do not cover the entire range of soil properties on a national scale. Further work is needed to verify the empirical models for a complete range of soil types. In addition, a predictive empirical relationship between annual BNE rates and TN or SOC is established for cultivated mineral soil at the global scale. However, the empirical models could not accurately predict the BNE rates of cultivated organic soils. Further studies are required to understand the regulatory effects of soil properties on annual BNE rates of cultivated organic soils.     

溶解性有机碳在红壤水稻土中的吸附及其影响因素

吸附作用是影响土壤中溶解性有机碳(DOC)迁移转化及生物有效性的重要反应过程,研究DOC在土壤中的吸附行为,对正确阐明土壤有机碳的循环和转化特征以及进行污染风险评估有重要意义.采用平衡法研究了红壤水稻土对DOC的吸附特征,并分析土壤有机质、粘粒含量及pH值与DOC吸附量之间的关系.结果表明,供试土壤对DOC的吸附等温线符合Freundlich和Linear方程.不同土壤对DOC的吸附能力有明显差异.在相同浓度下,DOC吸附量以第四纪红色粘土发育的低肥力水稻土最大,第三纪红砂岩风化物发育的低肥力水稻土次之,两种高肥力水稻土最小.土壤对DOC的吸附过程分为快、慢两个阶段,0-0.25 h内DOC的吸附速率最大,随着时间的推移,吸附速率渐小,2-4 h后基本达到吸附平衡.描述供试土壤对DOC吸附动力学过程的最优模型为一级扩散方程,其次为Elovich方程和抛物扩散方程.粘粒含量和有机质是影响土壤DOC吸附量的重要因素,随着粘粒含量的增加,有机质含量的降低,DOC的吸附量增大.     

Nutrient dynamics and plant assemblages of Macrotermes falciger mounds in a savanna ecosystem

Termites through mound construction and foraging activities contribute significantly to carbon and nutrient fluxes in nutrient-poor savannas. Despite this recognition, studies on the influence of termite mounds on carbon and nitrogen dynamics in sub-tropical savannas are limited. In this regard, we examined soil nutrient concentrations, organic carbon and nitrogen mineralization in incubation experiments in mounds of Macrotermes falciger and surrounding soils of sub-tropical savanna, northeast Zimbabwe. We also addressed whether termite mounds altered the plant community and if effects were similar across functional groups i.e. grasses, forbs or woody plants. Mound soils had significantly higher silt and clay content, pH and concentrations of calcium (Ca), magnesium (Mg), potassium (K), organic carbon (C), ammonium (NH₄⁺) and nitrate (NO₃⁻) than surrounding soils, with marginal differences in phosphorus (P) and sodium (Na) between mounds and matrix soils. Nutrient enrichment increased by a factor ranging from 1.5 for C, 4.9 for Mg up to 10.3 for Ca. Although C mineralization, nitrification and nitrification fraction were similar between mounds and matrix soils, nitrogen mineralization was elevated on mounds relative to surrounding matrix soils. As a result, termite mounds supported unique plant communities rich and abundant in woody species but less diverse in grasses and forbs than the surrounding savanna matrix in response to mound-induced shifts in soil parameters specifically increased clay content, drainage and water availability, nutrient status and base cation (mainly Ca, Mg and Na) concentration. In conclusion, by altering soil properties such as texture, moisture content and nutrient status, termite mounds can alter the structure and composition of sub-tropical savanna plant communities, and these results are consistent with findings in other savanna systems suggesting that increase in soil clay content, nutrient status and associated changes in the plant community assemblage may be a general property of mound building termites.