河套平原典型县域耕地土壤养分空间变异特征研究

为研究河套平原地区土壤养分状况,探究县域尺度土壤养分的空间变异性与分布特征,以杭锦后旗县域耕地为对象,采用实地调查和地统计学相结合的方法,研究该区耕层土壤有机质、全氮、有效磷、速效钾养分含量状况,分析土壤养分空间分布及其变异特征。结果表明,研究区耕层土壤有机质、全氮、速效磷和速效钾平均含量依次为13.90 g/kg、0.93 g/kg、16.25 mg/kg和170.79 mg/kg,土壤有机质和全氮处于缺乏状态,速效磷含量中等,而速效钾的含量较为丰富。从空间变异及相关性看,各土壤养分的变异程度都为中等变异,有机质和速效钾为中等相关性,全氮和有效磷均为弱相关性。从空间分布格局看,土壤有机质与全氮分布规律相近,呈现西北部高、东南部和东北部低的特点;土壤速效钾整体分布较为均衡;速效磷空间差异明显,呈东高西低格局。针对该地区土壤养分含量及分布规律,在进行养分管理过程中,应以控氮、稳磷、稳钾、全区规划与重点应对相结合的原则,坚持以有机肥为主、有机与无机相结合的施肥策略。对县域尺度耕地土壤养分状况的调查研究和统计分析,明晰了区域土壤养分空间分布特征及其与土地利用方式之间的关系,为河套平原耕地土壤养分管理、地力培育以及合理施肥运筹等提供科学依据。     

夏玉米产量时空变化及气候年型分析

定量分析夏玉米同一品种产量及产量构成要素时空变化,探讨造成产量时空差异的气候年型组合变化特征。基于2004～2013年夏玉米种植区郑单958多点田间试验数据分析表明,夏玉米区域平均产量为9 055 kg/hm~2,年际差为1 635 kg/hm~2,变幅为18.1%;地点差4 258 kg/hm~2,变幅为47.1%。夏玉米区域平均千粒重为313 g,年际变幅为13.1%;地点变幅为27.8%。夏玉米区域平均穗粒数为479,年际变幅为18.0%,地点变幅为38.7%。千粒重的增加导致夏玉米产量显著增加。穗粒数显著降低和时空差异大是造成产量波动和时空差异变幅大的主要原因。夏玉米产量和产量构成要素,低产点受各气候要素变化的影响显著;平产点受温度和日最高温度大于33℃的天数影响显著;高产点受降水影响显著。     

水力侵蚀对砒砂岩区土壤有机碳空间变异性的影响

以侵蚀剧烈的砒砂岩区为研究对象，应用地统计学Kriging插值法准确描述水力侵蚀下土壤有机碳空间动态迁移过程来探究侵蚀与碳平衡的关系并为有效治理砒砂岩区坡面水土流失提供科学的参考。结果表明：（1）降雨前后各土层有机碳均随着土层增加而减少，表现为中等变异、空间自相关均为正相关且0—10 cm土层自相关性最大。降雨后0—20 cm土层有机碳含量减少而20—40 cm土层增加，且各土层变异程度均较雨前减弱。（2）降雨前后土壤有机碳分别与高斯模型，球状模型较为拟合，且变程值均随土层增加而增大。降雨前后0—10 cm土层表现均为强烈空间相关性且雨后结构比增大，而10—40 cm均为中等相关性雨后结构比减小。（3）降雨后空间异质性减弱斑块面积变大，总体表现为同一土层坡上侵蚀坡下沉积，而不同土层下0—20 cm土层表现为侵蚀，20—40 cm土层表现为沉积。（4）降雨前后土壤有机碳均与黏粒呈现较显著正相关，其中降雨前0—10 cm土层有机碳与黏粒为极显著正相关，降雨后各土层相关性增强均为极显著正相关。但降雨前后土壤有机碳与粉粒相关性均较小且不显著，与砂粒则基本表现为负相关。     

城市池塘水质时间变化特性--以扬州大学江阳路南校区池塘为例

城市中的池塘是城市水体的重要组成部分,为揭示城市化背景下池塘水体水质的时间变化特性,选取扬州大学江阳路南校区池塘为研究区,对该池塘2018年7月至2019年6月的水质参数蓝绿藻浓度(Phyco)、水温(WT)、溶解氧(DO)、pH与电导率(EC)进行观测,采用变异系数法、单因子水质标识指数法以及多元线性回归法对各参数的变化特性进行评价。结果显示:池塘WT呈季节性变化;观测期间pH变化范围为7.74~9.98,水体呈碱性;DO变化的随机性较强,未表现出明显变化规律;各水质参数变异性及权重从大到小依次为WT>DO>EC>pH;以DO为指标的单因子水质标识指数结果表明:池塘DO达到Ⅲ类水要求的时段占总观测时段的84%;多元线性回归分析结果表明:DO与WT、pH呈正相关,与Phyco呈负相关,Phyco及pH的变化对DO浓度的影响相对于WT大。     

Thresholds,sensitive stages and genetic variability of finger millet to high temperature stress

Finger millet [Eleusine coracana (L.) Gaertn.] is an important coarse cereal crop grown in the arid and semi‐arid regions and often experiences high temperature (HT) stress. The objectives of this research were (i) to quantify effects of season‐long HT stress on physiological and yield traits, (ii) to identify the developmental stages most sensitive to HT stress and (iii) to quantify the genetic variability for HT stress tolerance in finger millet. Research was conducted in controlled environment conditions. HT stress decreased the chlorophyll index, photosystem II activity, grain yield and harvest index. Maximum decrease in number of seeds per panicle and grain yield per plant was observed when stress was imposed during booting, panicle emergence or flowering stages. Maximum genotypic variation was explained by panicle width and number of seeds per panicle at optimum temperature (OT) and grain yield per plant at HT and number of seeds at HT. Based on the stress response and grain yield, tolerant or susceptible genotypes were identified. Finger millet is sensitive to HT stress during reproductive stages, and there was genotypic variability among the finger millet genotypes for number of seeds per panicle and grain yield under HT, which can be exploited to enhance stress tolerance.     

杉木全同胞家系的遗传分析及重要树冠因子的筛选

通过对5年生杉木6×6全双列杂交(Griffing Ⅲ)试验林的调查与分析，研究杉木若干性状的遗传与变异规律，并筛选决定理想株型的重要树冠结构因子，为杂交育种和杉木理想株型无性系选育提供科学依据。运用转化分析法来处理不平衡试验数据，结合配合力分析法、相关分析法和通径分析法,研究杉木遗传变异、基因作用方式和重要树冠因子的选择。通过对杉木若干性状进行研究，获得了不同性状遗传变异大小。结果表明，杉木材积、枝下高和饱满度等性状具有中度遗传变性，树高、胸径具有窄的遗传变异性，同时杉木改良性状具有中度以上的遗传力，因此杉木生长形质性状宜采用连续多世代改良；在杉木生长、形质性状和树冠结构性状中，12个研究性状有8个重要性状的基因作用方式以非加性遗传基因效应为主，杉木高世代育种亲本是多世代与高强度选择的产物,杂合体居多,杉木的多性状、高世代遗传改良以杂交育种为主；生长、形质和树冠结构性状间具有明显的遗传相关性，通径分析揭示:决定杉木理想株型育种中重要树冠结构性状是冠形率和树冠表面积大小。由此可见:杉木多性状、多世代连续改良以杂交育种为主，杉木无性系理想株型选择时，应注重冠形率和树冠表面积的作用。     

盐渍化灌区节水改造后土壤盐分时空变化规律研究

为探明沈乌灌域节水改造后因地下水水位变化造成的土壤盐分重分布规律,采用区域土壤信息定点监测,并结合经典统计学、空间插值、缓冲区分析和空间自相关分析方法,研究节水改造前后沈乌灌域土壤盐分空间变异、时空分布规律及不同改造年限区域土壤盐分变化差异。结果表明:节水改造后,秋浇前土壤整体含盐量平均降幅7. 30%,秋浇水量减少,秋浇后土壤盐分淋洗效果减弱9. 26%;空间上,土壤盐分高值区(大于6 g/kg)多位于地下水埋深较浅的东北和南部区域,低值区(小于2 g/kg)位于西南和东部沙区。节水改造后,秋浇前土壤盐分全局Moran’s I指数平均增幅为5%,空间相关性增强;秋浇水量减少,全局Moran’s I指数变化不显著,秋浇作用对土壤盐分空间自相关影响度减弱。由LISA集聚分析可知,改造后、秋浇前南部高-高显著区向不显著和高-低区转变,秋浇后南部集聚特征仍十分显著,存在盐渍化风险,改造后仍是盐渍化防治重点区域。针对中度耐盐作物,沈乌灌域耕层作物生长安全区和深层非盐渍土面积比例分别为49. 66%和71. 57%;改造后,秋浇前耕层作物生长安全区和深层非盐渍土分别增加4. 82、1. 85个百分点,秋浇后,耕层作物生长安全区面积增幅下降5. 02个百分点,深层变化不显著。不同距离缓冲区对平均土壤含盐量的解释能力较强,长期改造区和短期改造区受渠道影响半径分别为1. 5 km和0. 7 km,长期改造区缓冲区内平均土壤含盐量下降速率高于短期改造区,均一化程度较高。综上所述,节水改造工程实施后,土壤盐渍化程度减轻,作物生长安全区面积增加,表聚作用弱化,秋浇水量减少,土壤盐分淋洗效果减弱,土壤环境有所改善。     

Determining corn nitrogen rates using multiple prediction models

Weather uncertainty and soil spatial variability impact nitrogen (N) cycling and corn (Zea mays L.) growth, making accurate N predictions a challenge. Field studies were conducted in Lansing, Michigan, to evaluate a computer model (i.e., Adapt-N), a preseason year-based model (i.e., maximum return to N [MRTN]), and a crop sensor model (i.e., active canopy sensor with algorithm) for recommending corn N rates. To determine site-specific economic optimum N rates (EONR), five N rates were also applied (0, 33%, 66%, 133%, and 166% of the suggested MRTN) as starter + sidedress (SD) at V4. In a wet year (i.e., 2015), Adapt-N increased V8 SD N rates 35 kg N ha^?1 relative to the MRTN V4 SD N application. Although the greater rate of N may have provided additional yield protection, no statistical yield differences were observed between the two models. The MRTN model increased partial factor productivity (PFP) 20% relative to Adapt-N. Limited expression of V8 corn N deficiency reduced crop sensor total N rates (21–56 kg N ha^?1) and yield (0.82–1.05 Mg ha^?1) relative to other models. In a drier year (i.e., 2016), N demand was reduced (EONR 64 kg N ha^?1 less than 2015), resulting in similar corn response to all three models. Despite differences in actual corn N rate recommendations, all three models resulted in similar economic net returns across study years.

Abbreviations: EONR, economic optimum nitrogen rate; MRTN, Maximum Return to Nitrogen; NUE, nitrogen-use efficiency; PFP, partial factor productivity; SBNRC, sensor-based nitrogen rate calculator; SD, side-dress     

Soil carbon change across ten New South Wales farms under different farm management regimes in Australia

This paper examines the potential influence of soil management and land use on soil carbon on cropping farms in New South Wales (NSW), Australia. Soil organic carbon (SOC) data from ten farms spatially distributed across NSW were examined on two occasions. Soil cores to a depth 0–30 cm were measured for SOC and, as expected, SOC in the A horizon (1.16%) was significantly (p < .001) greater than in the B horizon (0.74%) of all profiles. Analysis of the 2013 and 2015 SOC data indicated that in many ways, the results runs counter to other SOC studies in Australia. Importantly, the mean SOC concentration in these agricultural soils was significantly (p < .001) less under cropping (2013-1.05%, 2015-0.97%) than in native sites (2013-1.20%, 2015-1.16%). Out of the total of 35 sites sampled from 10 farms, SOC in 49% of sites did not change significantly over 2 years, in 17% it increased significantly, whereas in 34% it decreased. Further, a clear implication of drought on SOC was seen on sites that were uncropped based on a critical value for a 95% confidence interval (p < .05) and complemented by the significant correlation (p < .05) between average annual precipitation deficit (ANPD) and SOC across the state with R² = 0.39. The mean SOC was found to be directly proportional to standard deviation and standard error. In terms of spatial variability, the C0 (nugget) value was greatest for farms with a large mean SOC and the average variogram in this study has a range of approximately 200 m which is potentially useful in determining sampling spacing for soil carbon auditing purpose. Similar empirical data over more years are required to better estimate SOC levels and to determine whether at a farm scale, factors such as land management, land use and climate can be related to soil carbon change and variability.