南方花岗岩红壤典型区土壤有机质的空间变异特征

 通过野外实地调查与室内试验,以长汀县为研究区,在GIS的支持下,运用地统计学方法分析南方花岗岩红壤典型区表层土壤有机质的空间变异特征。结果表明:研究区土壤有机质质量分数总体水平中等并具有中等的空间相关性,平均为2.73%;变异系数为72.73%,属中等变异;由空间自相关部分引起的空间变异性程度较大,C0/(C0+C)值为47.13%,变程为21.48km;在空间分布上呈现四周高中间低的分布特征,在中部地区形成连片的低值区,西部有机质质量分数整体较高,存在最高值。研究成果可为南方花岗岩红壤侵蚀退化地的生态恢复与重建提供参考。     

Spatial evaluation of soil salinity using the WET sensor in the irrigated area of the Segura river lowland

The electrical conductivity of the water within the soil pores (EC_p) measured with the WET sensor, appears to be a reliable estimate of soil salinity. A methodology combining the use of the WET sensor along with geostatistics was developed to delimit and evaluate soil salinity within an irrigated area under arid to semiarid Mediterranean climate in SE Spain. A systematic random sampling of 104 points was carried out. The association between EC_p and the saturation‐extract electrical conductivity (EC_se) was assessed by means of correlation analysis. The semivariograms for EC_p were obtained at three different soil depths. Interpolation techniques, such as ordinary kriging and cokriging, were applied to obtain EC_p levels in the unknown places. For each one of the soil depths, a model able to predict EC_se from EC_p was developed by means of ordinary least squares regression analysis. A good correlation (r = 0.818, p < 0.001) between EC_p and EC_se was found. Spherical spatial distribution was the best model to fit to experimental semivariograms of EC_p at 10, 30, and 50 cm soil depths. Nevertheless, cokriging using the EC_p of an adjacent soil depth as an auxiliary variable provided the best results, compared to ordinary kriging. An analytical propagation‐error methodology was found to be useful to ascertain the contribution of the spatial interpolation and ordinary least squares analysis to the uncertainty of the EC_se mapping. This methodology allowed us to identify 98% of the study area as affected by salinity problems within a rooting depth of 50 cm, with the threshold of EC_se value at 2 dS m^–1. However, considering the crops actually grown and 10% potential reduction yield, the soil‐salinity‐affected area decreased to 83%. The use of sensors to measure soil salinity in combination with geostatistics is a cost‐effective way to draw maps of soil salinity at regional scale. This methodology is applicable to other agricultural irrigated areas under risk of salinization.     

稻纵卷叶螟种群动态的地统计学分析

概述了地统计学在昆虫种群时空动态分析中的基本方法,应用该方法分析了省通州市和安徽省凤阳县稻纵卷叶螟２３个各世代种群时间格局的结构特征和自相关性,并对历年各世代的种群数量进行了模拟估计。结果表明：种群每世代的累计蛾量和高峰日蛾量在一定世代间隔内均存在着自相关性,当世代间隔超过一定距离时表现为相互独立。两地区种群世代间的影响范围和作用程度的大小存在差异。     

内蒙古腰坝绿洲土壤盐分空间变异性规律

采用经典统计学、地统计学及Kriging最优内插法,对内蒙古腰坝绿洲耕层土(0~20cm)的土壤盐分空间变异性进行分析,以期为该区土壤盐渍化防治提供参考依据。结果表明:研究区土壤为碱性氯化物-硫酸盐型轻度盐渍化土,全盐量、SO4^2-具有中等空间自相关性,其余盐分指标具有强烈的空间自相关性,空间采样尺度以1km为佳;在空间分布格局上,土壤全盐量、Ca^2+、K^++Na^+、Mg^2+、SO4^2-、Cl^-呈西南高东北低的特征,而pH、HCO3-呈西南低东北高的特征。     

基于不同人为干扰的土壤全量氮磷钾空间变异性研究

采用地统计学与GIS技术相结合的方法，对无人为干扰区25个样本、人为干扰区30个样本土壤全量氮磷钾的空间异质性进行了研究。结果表明：人为干扰区土地多被开发成林地、育苗地，自然植被残体等被移除，土壤腐殖质来源减少，加之由于土层翻动，土壤透气性变好，加快了养分分解与利用，土壤全量氮磷钾含量均值分别降低至0.433、0.902、15.325 g·kg-1，数据间的差异性和分布状态也发生变化;球状模型能较好地拟合无人为干扰区土壤全磷分布,而高斯模型则能较高地拟合两区其余养分指标的分布,两区理论模型的R²介于0.66和0.90之间，拟合精度高;土壤全量氮磷钾的理论模型中，均以无人为干扰区模型的R²高且RSS小;无人为干扰区全量氮磷钾的高值区均在植被覆盖度高的区域内。干扰程度较大的区域，土壤全氮和全磷含量较低，因此应补充适量氮肥和磷肥，满足养分需求。     

农田表层土壤养分空间变异特性研究

为给田间养分监测设施布设方法提供依据,在陕西杨凌选取2块农田,采用12 m×12 m嵌套6 m×6 m的采样方法,采集表层土壤(0～20 cm)养分数据,运用经典统计、地统计学结合Kriging插值方法,分析农田土壤养分空间变异特征。结果表明:冬小麦抽穗期与成熟期农田表层土壤全氮(TN)变异系数10%,为弱变异,土壤有机质(SOM)、有效磷(AP)变异系数介于10%与100%之间,为中等变异,有效钾(AK)和铵态氮(NH_4~+-N)变异系数100%,为强变异,成熟期硝态氮(NO_3~--N)由强变异转为中等变异。土壤养分最优半方差模型为球状模型,作物不同生育阶段,土壤养分空间相关性存在一定的差异,土壤SOM、TN块金系数25%,空间相关性强烈,以结构性因素为主导;冬小麦抽穗期速效态养分块金系数介于25%与75%之间,空间相关性中等,随机性因素主导,成熟期25%,空间相关性增强。采样密度由6 m×6 m变为12 m×12 m时,变异程度保持不变,土壤养分空间变异系数差值在0.04%～59.48%范围内,成熟期2号样地的AK除外,块金系数差值在0.065%～34.177%范围内,2种采样间距获得的土壤养分空间变异特征基本一致,建议选用12 m×12 m网格。     

山西省森林土壤因子空间变异特征

为了揭示山西省森林土壤因子的空间分布特征,为评价森林土壤肥力提供参考,为森林可持续经营提供技术支撑,并为区域林业发展规划的制定提供依据。基于山西省297块样地的土壤采样检测数据,包括森林土壤碱解氮、全氮、有机质、速效磷、全钾、pH、含水量7个因子,利用GIS进行趋势分析、半变异函数模型选取,利用克里金插值法揭示森林土壤因子的空间变异特征。结果表明：全氮、碱解氮、pH的最优模型为高斯函数模型;速效磷、全钾的最优模型为指数函数模型;有机质、含水量的最优模型分别为三角函数模型和球面函数模型。利用克里金插值法绘制了各森林土壤因子的空间分布图,揭示了山西省森林土壤因子的分布特征。山西省森林土壤因子均有明显的空间分异特征：碱解氮、全氮、有机质含量相对较高的多集中在省境主体山脉沿线的中高山地区;全钾含量整体表现较为丰富;含水量表现出明显的东南多西北少的差异;速效磷作为一种瞬时变量,在空间分布上比较杂乱;pH的空间变异显示,山西省整体森林土壤呈弱碱性,朔州市部分地区森林土壤表现为强碱性,可作为盐碱地研究典型区域。     

Cokriging of Soil Cation Exchange Capacity Using the First Principal Component Derived from Soil Physico-Chemical Properties

As soil cation exchange capacity (CEC) is a vital indicator of soil quality and pollutant sequestration capacity,a study was conducted to evaluate cokriging of CEC with the principal components derived from soil physico-chemical properties.In Qingdao,China,107 soil samples were collected.Soil CEC was estimated by using 86 soil samples for prediction and 21 soil samples for test.The first two principal components (PC1 and PC2) together explained 60.2％ of the total variance of soil physico-chemical properties.The PC1 was highly correlated with CEC (r=0.76,P＜0.01),whereas there was no significant correlation between CEC and PC2 (r=0.03).The PC1 was then used as an auxiliary variable for the prediction of soil CEC.Mean error (ME) and root mean square error (RMSE) of kriging for the test dataset were -1.76 and 3.67 cmolc kg-1,and ME and RMSE of cokriging for the test dataset were -1.47 and 2.95 cmolc kg-1,respectively.The cross-validation R2 for the prediction dataset was 0.24 for kriging and 0.39 for cokriging.The results show that cokriging with PC1 is more reliable than kriging for spatial interpolation.In addition,principal components have the highest potential for cokriging predictions when the principal components have good correlations with the primary variables.     

不同深度土壤中氮素的空间变异研究

对供试区分析土壤中的氨态氮和硝态氮含量,用区域化变量理论和半方差函数分析,研究结果表明不同深度土壤中氨态氮和硝态氮含量具有空间变异性,均属于中等程度变异.通过对其半方差函授进行拟合,其变异程度主要由土壤本身的空间结构引起,不同深度土壤中氨态氮和硝态氮含量的空间相关尺度不同.     

废弃地复垦土壤重金属空间格局及其与复垦措施的关系

基于经典统计学、变异函数理论以及经验贝叶斯克里格法,以西南地区某历史遗留硫磺矿废弃地为研究对象,从点与区域两方面系统分析其复垦土壤重金属空间分布特征,揭示其与复垦措施的量化关系。结果表明,经典统计学、变异函数理论以及经验贝叶斯克里格法相结合方法用于揭示硫磺矿废弃地复垦土壤重金属空间分布格局是可行和科学的。该硫磺矿废弃地复垦土地的5种土壤重金属的变异系数均较大,这与复垦土壤无序、易变以及空间均匀性和突变性统一的特征相符合。土壤重金属富集系数均在2以上。在历史矿山开采、复垦措施和地形地貌的共同作用下,不同土壤重金属在全局空间上具有一定的相似,在南北和东西方向均基本呈现两头低和中间高的倒U字形趋势。绝大多数复垦土壤重金属的块基比在50%,复垦过程中覆土、培肥和土壤pH值调节措施等随机因素在各重金属的空间变异中占主导作用。无论是何种重金属,一区东部、二区北部、四区西部均呈现较高的重金属含量;一区和二区西部、三区北部地区含量相对较低。复垦为林地和草地的重金属平均含量均高于耕地,对于复垦为耕地后续需进一步防控重金属污染,特别是Cd元素;随着有效土层厚度的逐渐增加,土壤重金属总体呈下降趋势。有效土层厚度在30~100 cm之间土壤重金属无明显差异,建议研究区复垦覆土后有效土层厚度达到100 cm以上。随着土壤pH值变小,复垦土壤重金属总体呈上升趋势,通过调控pH值来降低土壤重金属含量需要持续保证在一定范围,建议研究区pH值持续控制在7~8。