基于时空变异的旱地土壤有机碳高效采样策略研究

土壤有机碳(SOC)空间分布具有时序差异性,明确样点数量对不同时期SOC预测精度影响是制定高效采样策略的基础.选取3.93×104 km2江苏北部旱地作为案例区,运用普通克里金插值方法,分析样点数量对不同时期SOC空间预测精度的影响.结果表明:不同数量样点数据集下1980年苏北旱地SOC预测值与实测值的相关系数r和均方...     

低场核磁探测水稻田改蔬菜地土壤水分的相态变化

为了解水稻土转变为设施蔬菜地后土壤水分的相态变化,该研究在田间土壤调查的基础上,结合低场核磁测氢技术,评价了田间状态的水稻土和不同转化年限设施蔬菜地土壤水分的相态分布情况。结果表明:随着转化时间的延长,耕层土壤大孔隙吸持的自由水比重下降,土壤小孔隙吸持的束缚水比重上升,犁底层土壤水分的相态分布却无明显变化,土壤水分吸持性能在转化时间序列上呈现下降的趋势,但长期施用有机肥可以优化耕层质量,提升土壤大孔隙吸持自由水的能力,改善土壤水分供释性能;水稻土转化为设施蔬菜地土壤2 a后,出现新犁底层,使得原有的耕层土壤变薄,土壤水分吸持性能下降。核磁共振作为一种新的技术手段,可以实现实时、快速、准确地检测土壤水分的相态变化,可为设施农业的可持续管理提供新的技术支持。     

4种水生植物深度净化村镇生活污水厂尾水效果研究

通过设置动态模拟试验,持续进水、出水条件下分析比较了漂浮植物凤眼莲和水浮莲、沉水植物轮叶黑藻和挺水植物黄菖蒲对村镇生活污水厂(一级A标准)尾水深度净化效果,筛选出具有去污效果优势的水生植物,为优化水生植物生态修复工程技术在尾水深度净化中的应用提供依据。结果表明:经水生植物深度净化后,尾水水质得到明显改善,漂浮植物凤眼莲和水浮莲对尾水氮、磷的净化效果优于挺水植物黄菖蒲和沉水植物轮叶黑藻。试验周期内,污水厂尾水总氮、总磷和高锰酸盐指数(CODMn)平均浓度为12.22 mg?L-1、0.38mg?L-1和3.88 mg?L-1,凤眼莲、水浮莲、轮叶黑藻、黄菖蒲和对照各系统的总氮平均去除率分别为46.25%、45.74%、43.41%、38.39%和29.22%,总磷去除率分别为36.84%、34.21%、31.58%、28.95%和26.32%,CODMn去除率分别为42.27%、30.93%、32.47%、32.47%和37.89%。凤眼莲、水浮莲、黄菖蒲和轮叶黑藻生物量净增长率分别为550.5%、418.8%、210.6%和80.3%,凤眼莲生物量净增率最大。各处理系统内凤眼莲、水浮莲、黄菖蒲和轮叶黑藻对尾水氮富集量分别为7.36 g、2.33 g、5.12 g和4.46 g,对磷的富集量分别为0.60 g、0.19 g、0.33 g和0.78 g,凤眼莲富集氮能力优于另外3种水生植物,轮叶黑藻磷富集量高于另外3种水生植物。凤眼莲、水浮莲、黄菖蒲和轮叶黑藻植株吸收作用对尾水总氮去除的表观贡献率分别为15.29%、4.90%、11.17%和11.34%,对尾水总磷去除的表观贡献率分别为50.34%、17.17%、35.24%和76.34%。因此,可利用漂浮植物凤眼莲和沉水植物轮叶黑藻立体复合种养的方式深度净化生活污水厂尾水。     

秸秆覆盖对不同初始含水率土壤产沙过程的影响

秸秆覆盖是防治水土流失最有效的措施之一。该文通过模拟降雨（降雨强度为60 mm/h,降雨历时1 h）研究坡耕地在不同土壤初始含水率状态下秸秆覆盖变化对产沙过程的影响。试验地位于中国科学院红壤生态实验站,土壤类型为耕作铝质湿润淋溶土,试验小区为12 m×3 m,坡度为9%。处理分为5个水平的覆盖度（0、15%、30%、60%和90%）和2种土壤初始含水率（干态和湿态）。结果表明,在0、15%、30%、60%和90%覆盖度下,干态土壤平均产沙速率依次为24.5、15.8、10.4、11.2和1.0 g/(m2·h),同一覆盖度下产沙速率在模拟降雨时段内略微增大。湿态土壤条件下平均产沙速率依次为115.6、70.0、49.6、34.8和31.9 g/(m2·h),同一覆盖度下产沙速率在模拟降雨时段内下降明显。0、15%、30%、60%和90%覆盖度下平衡时产沙速率依次为52.5、30.5、22.8、19.8和15.4 g/(m2·h)。另外,5个水平的覆盖度中,30%的花生秸秆覆盖降低不同前期含水率下土壤产沙速率50%以上。因此,不同前期含水率情况下土壤产沙速率对秸秆覆盖度变化的响应非常明显,30%秸秆覆盖具有较为经济的水土保持效果。     

基于地统计学和GIS的太湖典型地区土壤属性制图研究——以土壤全氮制图为例

在地理信息系统(GIS)支持下，运用地统计学方法对太湖典型地区耕层土壤全氮含量的空间变异特征进行分析，探讨了适用于研究区域土壤全氮制图的最佳邻域，并在此基础上利用块段克立格(Block Kriging)法绘制了土壤全氮含量空间分布图。结果表明，土壤全氮的空间变异性在40km步长变化域上表现为明显的各向同性，超出这个范围，土壤全氮空间变异的各向异性明显增强，以40km步长变化域上土壤全氮的空间结构特征作为Kriging插值依据有助于提高制图精度。制图结果表明，研究区域土壤全氮含量在江阴和宜兴两市境内普遍较高，锡山和武进两市相对较低；且高值斑块区主要分布在地势低洼的圩田区，这是人为施肥和土壤特性共同影响的结果。Kriging估值标准差分布图可为评价和提高制图精度提供十分有用信息。     

苏南典型地区土壤锌的空间分布特征及其与土壤颗粒组成的关系

在GIS的支持下,运用地统计学方法研究了苏南典型地区原锡山市土壤全Zn和有效Zn的空间分布特征,并简要分析了土壤全Zn和有效Zn含量与土壤颗粒组成之间的关系。结果表明,研究区域土壤全Zn和有效Zn的空间分布表现出一定的结构性,其空间相关范围分别达到6.6km和7.5km。Kriging插值结果表明,土壤全Zn含量在研究区域东北部最低,东南部相对较高;有效Zn含量与全Zn有着相似的空间分布趋势,受土壤自身特性的影响,其含量在北部地区普遍较低。土壤全Zn和有效Zn含量与土壤粘粒含量之间呈极显著正相关,而与砂粒含量之间呈显著负相关。     

Assessment of soil aggregation properties after conversion from rice to greenhouse organic cultivation on SOC controlling mechanism

Journal of Soils and Sediments - Organic manure is beneficial for macro-aggregate formation and soil organic carbon (SOC), but how SOC change in aggregate fractions in time-series is still...     

引黄灌溉耕作对土壤团聚体有机碳的影响

为研究灌溉耕作影响下土壤团聚体及有机碳的特征情况,以宁夏引黄灌区为研究对象,选取对照土壤与耕作土壤,通过干、湿筛结合的方法,得到大团聚体(2mm)、中间团聚体(2~0.25mm)、微团聚体(0.25~0.053mm)和粉+黏团聚体(0.053mm),并测定团聚体有机碳含量,分析团聚体有机碳与总有机碳之间的关系。结果表明,灌溉耕作对团聚体分布具有极显著影响(P0.01),其中大团聚体和中间团聚体质量分数上升,微团聚体和粉+黏团聚体质量分数下降,灌溉土壤团聚体分布趋势为微团聚体粉+黏团聚体中间团聚体大团聚体。经灌溉耕作后土壤团聚体稳定性大于对照土壤,不同类型的灌溉土壤稳定性基本一致,对照土壤间差异明显。除0.053mm外,团聚体有机碳分布在经过灌溉耕作后有显著性差异(P0.05),团聚体有机碳分布随粒级大小基本呈V形分布。团聚体有机碳含量均表现出灌溉土壤高于对照土壤,其中灌溉土壤中灌淤土和潮土团聚体有机碳总量较高。未受人为灌溉耕作影响的自然土壤团聚体有机碳与总有机碳间具有显著的正相关性,土壤总有机碳增加主要依赖0.053mm团聚体有机碳增加。引黄灌溉耕作有利于增加大粒级团聚体的比例,提升团聚体稳定,显著增加有机碳含量。     

Changes in soil macropores: Superposition of the roles of organic nutrient amendments and the greenhouse pattern in vegetable plantations

Organic farming can potentially mitigate soil compaction, which commonly occurs in vegetable plantations, particularly in greenhouses when compared with open‐air systems. Although several studies have addressed the effect of planting patterns on soil pore characteristics, few studies have focused on changes in pore attributes under organic fertilization. We used adjacent fields during green manure planting as a control to compare the differences in soil physicochemical and macropore parameters between 14‐year‐old greenhouse plots and open‐air plots under organic fertilization. Pearson's correlation analysis was performed to analyse the drivers of soil macropore characteristics in vegetable plantations in Jiangsu Province, China. A significant increase in connectivity, fractal dimensions and total macroporosity and a decrease in bulk density after 14 years of organic farming, particularly in the surface layer in the greenhouse, were observed. However, the difference in pores in the plough pan layer was not significant between the treatments. The volume of small pores (50–500 μm) and medium pores (500–1,000 μm) increased significantly (p < 0.05) in both the greenhouse and open‐air systems, showing significantly positive relationships with soil organic matter (SOM) and total nitrogen (TN) content. Large pores (>1,000 μm) showed a clear decrease, especially in open‐air fields, possibly due to the disappearance of the original straw residues in the surface layer. Small and medium pores in the plough layer increased in greenhouse fields, whereas the opposite occurred in open‐air fields. Overall, compared with open‐air systems, long‐term organic greenhouse patterns had a significantly positive effect on soil pore attributes.     

Comparison of multivariate models and variable selection algorithms for rapid analysis of the chemical composition of field crops

This study evaluates the use of visible and near-infrared spectroscopy for rapid prediction of total carbon, total nitrogen, and total phosphorus concentrations in field crop samples. Two multivariate models (partial least squares regression and support vector machine regression) were compared. In addition, four spectral variable selection algorithms (competitive adaptive reweighted sampling, genetic algorithm, uninformative variable elimination, and variable importance for projection) were applied with support vector machine regression to determine the most accurate predictions. The results showed that support vector machine regression performed better than partial least squares regression for predicting the three chemical compositions. The combination of competitive adaptive reweighted sampling and support vector machine regression outperformed the other models for the predictions of total carbon and total nitrogen with high coefficients of determination of 0.91 and 0.90, respectively. For the determination of total phosphorus, the prediction accuracy of competitive adaptive reweighted sampling was comparable with the best result obtained from genetic algorithm with the coefficients of determination of 0.73 and 0.77, respectively. In conclusion, the support vector machine regression combined with competitive adaptive reweighted sampling has great potential to accurately determine the chemical composition of field crops using the visible and near-infrared spectroscopy.