渤海底拖网主要渔业生物类别时空分布的初步研究

为研究目前渤海主要渔业生物的时空关系,文章依据2014年~2015年渤海双船底拖网4个季度调查数据,初步分析了渤海三类主要渔获物(鱼类、甲壳类和头足类)的水平空间分布特点、空间距离及四季变化特征。结果显示,三类生物的主要分布区水平方向上存在空间分化现象,且随着三类生物集中分布区聚集程度的提高,空间分化现象越来越明显。三类生物的水平空间分布距离在季节上表现出夏、秋季(平均欧氏距离,夏季为75.91;秋季为44.76)较远,冬、春季(冬季为8.55;春季为11.81)较近的特点。三类生物间,头足类与甲壳类的距离相对较近(平均欧氏距离,24.44),而头足类与鱼类(40.07)、鱼类与甲壳类(38.27)的距离相对较远。     

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     

基于农作制分区的1985—2015年中国小麦生产时空变化

Comparing spatio-temporal variation characteristics of China’s wheat production, yield, sown area and yield-area-contribution in different farming zones in the past 30 years could help improving wheat planting layout and adjusting planting structure. Concentration index, rate of change, moving of gravity and resolution of yield-area-contribution were used to analyze spatio-temporal changes of China’s wheat production and yield-area-contribution based on county wheat production statistics including sown area, production and yield from 1985 to 2015. The wheat sown area decreased obviously in Northeast farming region, Northwest farming region and South farming region and increased rapidly in Huang-Huai-Hai farming region and Yangtze Plain farming region. In Huang-Huai-Hai farming region, the concentration indexes of Haihe Plain farming region, Huang-huai Plain farming region and Fenwei Basin farming region reached to 20.64%, 25.77%, and 21.65% respectively in 2015. Wheat production increased significantly by more than 48 milliontons in Huang-Huai-Hai farming region, and nearly 8 million tons Yangtze Plain farming region but decreased by more than 2.6 million tons in Northeast farming region. In Huang-Huai-Hai farming region, wheat production was concentrated in Haihe Plain farming region, Huang-huai Plain farming region and Yuxi Hill farming region. The average wheat yield continuously improved during the study period, Huang-Huai-Hai farming region and Northwest farming region had the yield increase up to 103.5 kg hm ^-2 and 92.9 kg hm ^-2 each year. Wheat yield in Yuxi Hill farming region, Fenwei Basin farming region and Haihe Plain farming region was relatively high in Huang-Huai-Hai farming region. The yield-reduced area was mainly caused by the decreasing of sown area, while the yield-area-contribution rate was different in yield-increased area. Yield-dominant counties were reduced, area-dominant counties were increased and yield-area-dominant counties were relatively steady. In production increased area, yield-dominant and yield-area-dominant counties were the main types in Huang-Huai-Hai Farming region, area-dominant and yield-area-dominant counties were the main types in Yangtze Plain farming region. Chinese wheat production was increasingly concentrated in Huang-Huai-Hai farming region which has high and rapid increase of wheat yield over the past three decades. Haihe Plain farming region, Huang-huai Plain farming region and Fenwei Basin farming region were the most concentrated areas in Huang-Huai-Hai farming region for wheat production during this period. Wheat yield and sown area jointly promoted the increase of wheat production in Huang-Huai-Hai farming region, wheat sown area was the crucial factor to increase wheat production in Yangtze Plain farming region, especially in the north of Jiangsu, Anhui province and greater part of Xinjiang.     

流溪河保护区鱼类群落结构及其时空变动

为了解流溪河光倒刺鲃国家级水产种质资源保护区鱼类群落结构,分析不同河段、不同季节鱼类群落多样性的变化,于2017年12月-2018年10月对保护区上、中、下游的鱼类开展了每个季度一次的调查。调查结果显示,共采集鱼类57种,隶属于5目14科50属,其中鲤形目43种、鲈形目6种、鲇形目5种,合鳃鱼目2种,鳉形目1种;计算57种鱼类的相对重要性指数,结果显示,尼罗罗非鱼、越南■及鲤鱼为2017-2018年度优势种;Shannon-Wiener多样性指数、Margalef丰富度指数和Pielou均匀度指数计算结果显示,下游鱼类群落的多样性及均匀度最高,夏季鱼类群落的多样性、丰富度及均匀度最高;各监测点之间的种类相似性系数显示,保护区上中游、上下游之间鱼类种类组成为中等不相似,中下游种类组成为中等相似,春夏、春冬、夏冬及夏秋季节鱼类种类组成为中等不相似,春秋、秋冬季节为中等相似;ABC分析结果显示,春、夏及冬季鱼类群落处于稳定状态,秋季处于中度干扰状态。     

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.     

近35年红壤稻区土壤肥力时空演变特征—以进贤县为例

【目的】明确红壤稻区典型县域农业生产中土壤养分的变化特征以及当前土壤肥力水平,为红壤稻田土壤培肥改良提供依据。【方法】通过数据收集和野外采样分析得到江西省进贤县1982年、2008年和2017年3个时期稻田耕层土壤属性的数据,统一选取土壤pH、有机质、碱解氮、有效磷和速效钾作为土壤综合肥力评价指标,首先对3个时期各项肥力指标进行常规统计和差异性分析,采用主成分分析找出不同时期肥力差异的关键因子并确定权重,通过隶属度函数得到各项肥力指标的隶属度值,将各项肥力指标的权重和隶属度值加乘得到土壤综合肥力指数,最后结合土壤各项肥力指标和综合肥力指数的GIS空间分布图探究该区域稻田土壤肥力时空演变特征。【结果】1982—2017年进贤县稻田土壤有机质、碱解氮、有效磷和速效钾均呈不同程度的上升趋势,土壤pH呈下降趋势。1982、2008和2017年3个时期进贤县土壤pH的平均值分别为5.9、5.1、4.8,年均下降0.03个单位;35年来土壤pH整体由西部向东南和西北下降速率逐渐减低,2017年99%的稻田土壤处于酸性水平（4.5—5.5）。35年间稻田土壤有机质含量的平均值由28.1 g·kg^-1上升至36.8 g·kg^-1,1982—2008年和2008—2017年土壤有机质年均增加速率分别为0.21和0.31 g·kg^-1,2017年土壤有机质含量在30—40 g·kg^-1之间的稻田占比达94%,1982—2017年土壤有机质整体由东北向西南上升速率逐渐降低。1982—2017年土壤有效磷含量的平均值由7.0 mg·kg^-1上升至32.1 mg·kg^-1,2017年进贤县以土壤有效磷含量在20—40 mg·kg^-1的稻田为主,占比75%。1982—2017年稻田土壤速效钾累积缓慢,1982—2008年和2008—2017年土壤速效钾年均增加速率分别0.58和0.53 mg·kg^-1,2017年进贤县稻田土壤速效钾含量平均值为73.2 mg·kg^-1。稻田土壤碱解氮在1982—2008年和2008—2017年两个阶段增长均呈先快后慢的趋势,前后两个阶段的年增长速率分别为1.24和0.29 mg·kg^-1,1982—2017年进贤县土壤碱解氮含量东南地区上升速率高,西北地区上升速率低。1982、2008和2017年进贤县稻田土壤综合肥力指数的平均值分别为0.43、0.50和0.55。3个时期稻田土壤肥力指标综合得分分别为：碱解氮有效磷>pH>速效钾>有机质（1982年）;pH>有效磷>速效钾>有机质>碱解氮（2008年）;速效钾>有效磷>pH>碱解氮>有机质（2017年）。【结论】经过35年的长期耕作,进贤县稻田土壤肥力得到改善。当前进贤县稻田土壤仍存在碱解氮过量、速效钾亏缺、土壤酸化严重等问题。土壤碱解氮、pH和速效钾分别为1982年、2008年和2017年3个时期造成进贤县稻田土壤肥力空间分布差异性的关键因素。     

黑土区田块尺度下地形影响作物长势机理分析

为揭示作物长势及水肥运移的空间分异规律,探究田块尺度内作物长势与地形变化的关系,以东北典型黑土区东兴农机合作社为研究区,沿南北垄向提取高精度数字高程模型(Digital elevation model,DEM)与归一化植被指数(Normalized differential vegetation index,NDVI)信息,构建地形指标,分析NDVI的空间变异性。结果表明,坡型凸凹程度越明显,NDVI的空间变异性越大;同类坡型中阴坡NDVI的空间变异性与坡型凸凹程度呈负相关;坡度在±0.03范围内,作物长势好,空间变异性低;以坡度绝对值高于0.04的坡度均值与其对应直线距离所占整条直线的比值作为自变量,构建多元逐步回归模型,进行回归分析,可以解释大豆NDVI决定系数为0.965 2、高粱NDVI决定系数为0.888 3的空间变异性。不同地理空间的地形与成土母质差异显著,通过分析研究区内地形对作物长势的影响规律,可为田块尺度地形的分析提供借鉴,有助于指导农户合理地进行水肥分配。