Oceanographic investigation of the American Samoa albacore (Thunnus alalunga) habitat and longline fishing grounds

The American Samoa fishing ground is a dynamic region with strong mesoscale eddy activity and temporal variability on scales of <1 week. Seasonal and interannual variability in eddy activity, induced by baroclinic instability that is fueled by horizontal shear between the eastward‐flowing South Equatorial Counter Current (SECC) and the westward‐flowing South Equatorial Current (SEC), seems to play an important role in the performance of the longline fishery for albacore. Mesoscale eddy variability in the American Samoa Exclusive Economic Zone (EEZ) peaks from March to April, when the kinetic energy of the SECC is at its strongest. Longline albacore catch tends to be highest at the eddy edges, while albacore catch per effort (CPUE) shows intra‐annual variability with high CPUE that lags the periods of peak eddy activity by about 2 months. When CPUE is highest, the values are distributed toward the northern half of the EEZ, the region affected most by the SECC. Further indication of the possible importance of the SECC for longline performance is the significant drop in eddy variability in 2004 when compared with that observed in 2003 – resulting from a weak SECC – which was accompanied by a substantial drop in albacore CPUE rates and a lack of northward intensification of CPUE. From an ecosystem perspective, evidence to support higher micronekton biomass in the upper 200 m at eddy boundaries is inconclusive. Albacore's vertical distribution seems to be governed by the presence of prey. Albacore spend most of their time between 150 and 250 m, away from the deep daytime and shallow nighttime sonic scattering layers, at depths coinciding with those of small local maxima in micronekton biomass whose backscattering properties are consistent with those of albacore's preferred prey. Settling depths of longline sets during periods of decreased eddy activity correspond to those most occupied by albacore, possibly contributing to the lower CPUE by reducing catchability through rendering bait less attractive to albacore in the presence of prey.     

微咸水滴灌条件下沙穴种植的土壤水盐二维空间分布规律

河套灌区重度盐碱土具有结构性差、导水率低的特点,且该地区淡水资源短缺,为提高土壤水入渗性能,合理开发利用微咸水资源,可在滴头下方设置沙穴并利用微咸水灌溉。为探明不同矿化度微咸水滴灌的沙穴种植条件下二维土壤水盐分布规律,采用室内50 cm×50 cm二维土槽模拟试验,设置蒸馏水(0 g/L),2.0,3.0,4.0 g/L 4种不同矿化度处理,试验历时100 h。结果表明:在深度5 cm距滴头两侧15~20 cm及滴头下方25 cm的盐碱土处,土壤含水量较高,沙土土壤含水率随着矿化度的增加而增加,盐碱土土壤含水率随着矿化度的增加呈现先增加后降低的趋势,采用3.0 g/L灌溉水滴灌时,盐碱土含水率最大(变异系数为7.64%),说明利用3.0 g/L微咸水灌溉可有效提高沙穴种植条件下土壤含水率;入渗100 h后盐分主要聚集在滴头下方25~30 cm处,沙穴结构试验中,灌溉水矿化度为4.0 g/L的情况下土壤平均电导率最大(变异系数为50.59%),水平方向盐分淋洗效果优于垂直方向,且灌溉水矿化度越低,淋洗效果越显著,蒸馏水处理脱盐率为13.99%,灌溉水矿化度为2.0,3.0,4.0 g/L时积盐率分别为7.93%,14.57%,30.05%,脱盐半径随矿化度的增大而减小,3.0 g/L与2.0 g/L积盐量差异不显著(P=0.460>0.05),与4.0 g/L处理下积盐量差异显著(P=0.024<0.05)。结合土壤水盐空间分布规律,利用3.0 g/L微咸水可提高盐碱土土壤含水率,控制沙穴种植结构土壤积盐量,提高根系层土壤保水性。     

定西于家山黄土洞穴的分布特征与侵蚀临界研究

黄土洞穴与滑坡、沟蚀等侵蚀过程联系紧密并加剧了黄土高原的水土流失程度,但目前黄土洞穴发育的分布特征与侵蚀临界暂未明晰。利用无人机获得了研究区高分辨率影像与数字表面模型,基于影像标识了黄土洞穴并统计了其土地利用类型与洞穴直径,利用标识点在数字表面模型上提取了黄土洞穴的坡度、坡向、曲率和汇水面积等地形数据并分析了黄土洞穴的分布特征。结果表明,黄土洞穴直径大多4 m。黄土洞穴在耕地上发育较少,多发育于牧草地区域流水汇聚的凹形坡,且在阴坡更为发育。同时,黄土洞穴坡度正切值范围集中于0.4～1.0,汇水面积一般不超过3 000 m~2。依托统计的坡度正切值与汇水面积数据绘制了黄土洞穴的侵蚀临界图并对比了黄土洞穴与浅沟、切沟的侵蚀临界。黄土洞穴的侵蚀临界边界分别为SA~(0.150)=0.368与SA~(0.135)=7.580,分布较广且覆盖了浅沟与切沟的侵蚀临界。浅沟、切沟的演化与黄土洞穴的发育有关,黄土洞穴通过连通与坍塌促进了浅沟、切沟的发育、转换与扩展,并因此加剧了黄土高原的水土流失。研究量化了黄土洞穴发育的分布特征,建立了黄土洞穴与浅沟、切沟的联系并深化了对黄土洞穴侵蚀过程的认识。     

Effect of soil pore size distribution on plant-available water and least limiting water range as soil physical quality indicators

Soil pore size distribution(SPSD) is one of the most important soil physical properties. This research investigated the relationships of location and shape parameters of the SPSD curves with plant-available water(PAW) and least limiting water range(LLWR) of the light-textured soils at the Torogh Agricultural Research Station in north-eastern Iran. Soil moisture release curve(SMRC), PAW and LLWR in matric heads of 100 and 330 h Pa for the field capacity and location and shape parameters of the SPSD curves of 30 soils with different texture and organic carbon contents were determined, and the variable relationships were statistically analyzed. The results showed that the median equivalent pore diameter(de), mean de, standard deviation(SD*), and skewness of the SPSD curves were significantly correlated with PAW(PAW330) and LLWR(LLWR330) measured in a matric head of 330 h Pa. Decrease in deand increase in the diversity of soil pore size(SD*) increased PAW330 and LLWR330. The SD* values of all the soil samples were lower than the optimal ranges suggested in literature. Neither PAW nor LLWR values were significantly different in the soils with the optimal modal deand those with non-optimal modal de. Optimal values of median and mean equivalent pore diameters and kurtosis of SPSD curves led to a significant improvement of PAW330 and LLWR330 as soil physical quality indicators. It was recommended to revise the optimal ranges for SD* and modal defor future studies.     

植保无人机昼夜作业的雾滴沉积特性及棉蚜防效对比

针对无人机在棉蚜防治过程中夜间作业雾滴沉积特性和防效未知、目标喷洒区域雾滴沉积规律不明确等问题,该研究采用P20植保无人机进行棉蚜防治试验,对比了无人机白天和夜间作业时棉花植株不同部位的雾滴沉积规律及棉蚜防效,以常规喷杆喷雾机和喷枪为对照。结果表明,无人机白天和夜间作业的雾滴沉积数量及覆盖率差异显著,相同作业参数下,夜间作业的雾滴沉积数量平均比白天多42.82%,覆盖率平均比白天增加51.04%;夜间作业的雾滴穿透性较好,棉花植株的中下层及叶片背面雾滴沉积数量均多于白天。夜间作业时,棉花植株中、下层的雾滴沉积数量平均占垂直方向上雾滴总数量的比例分别为34.79%和22.07%,白天平均占33.27%和21.89%,喷枪为29.50%和19.98%,喷杆喷雾机为43.30%和15.84%;无人机夜间作业的叶片背面雾滴沉积数量平均占正反面总雾滴沉积数量的19.80%,白天作业占14.18%,夜间比白天多39.63%,各层叶片背面的雾滴沉积数量表现为上层下层中层;总体上,无人机作业的叶片背面雾滴沉积数量比例不超过25%,喷枪及喷杆喷雾机作业的叶片背面雾滴数量少,分别占7.09%和0.20%;在棉花花铃期和蕾期作业时,为提高雾滴沉积数量和雾滴穿透性,建议将无人机作业参数设置为飞行高度1.5～2 m,飞行速度3～4 m/s,选用较大的喷洒量,因为只有无人机下压风场不削弱、雾滴不大量损失的前提下,旋翼风场才能有效促进雾滴穿透性。就雾滴沉积数量和棉蚜防效关系而言,药后第1天棉蚜减退率与叶片背面雾滴沉积数量呈正相关关系,因受天敌影响药后第10天二者关联性不高。试验表明,无人机夜间作业更有利于棉蚜防治,其防效显著优于白天作业和其他2种常规设备,且农药剂量减少20%对棉蚜防效无显著影响。该研究结果可为植保无人机作业参数的合理设置提供参考,为棉蚜有效防控提供科学依据。     

植保无人机低空低量施药雾滴沉积飘移分布立体测试方法

随着植保无人机在中国的广泛使用,植保无人机的沉积分布均匀性与雾滴飘移流失也引起各方面的重视。目前,针对植保无人机施药雾滴沉积飘移的测试方法较少,且着重于从沉积或飘移中某一方面分析植保无人机雾滴沉积飘移规律,未对作业中全方位的雾滴的沉积飘失规律进行系统测试。该文基于国际标准ISO22866和ISO24253建了1套针对低空低量植保无人机的立体测试方法,分别在地面布置沉积和飘移收集器,在空中架设立体沉积和空中飘移收集器,结合航拍影像所获取的植保无人机准确作业参数,对4个型号植保无人机分别搭载德国Lechler公司的IDK120-015和TR80-0067喷头进行了测试,系统分析了无人机周边的总沉积以验证方法准确性,计算了总地面沉降以表征可利用部分和空中耗散以评估环境风险。结果表明,各植保无人机地面沉积率在53.6%~76.6%,地面飘移率最高17.4%,空中飘移率可高达14.7%;该测试系统可收集62.4%~101.7%无人机喷洒出的雾滴。测试的4种植保无人机在搭载IDK喷头后均明显降低了雾滴飘移,但也同时降低地面沉积率;各植保无人机在搭载2种喷头时沉积规律不同,不同植保无人机设计需要选择不同喷头。该测试方法能够有效的收集并分析植保无人机在作业区域的雾滴立体分布状态,可为植保无人机综合评估提供新的参考依据。     

考虑植株氮垂直分布的夏玉米营养诊断敏感位点筛选

探明夏玉米氮素营养生化指标(叶绿素a、叶绿素b、类胡萝卜素、叶片氮含量和叶片氮积累量)与叶片SPAD值垂直分布特征及两者间定量回归关系,确立基于叶绿素仪的夏玉米氮营养无损诊断敏感叶位和叶片部位,以实现氮营养时空变化的快捷和精准监测。利用2018-2019年连续2季不同氮营养水平下夏玉米关键生育期主茎各叶位(顶1叶~顶12叶,TL1~TL12)和叶片部位(每张叶片从叶片基部开始根据叶片长度每20%分为1个测试区间) SPAD值及氮营养指标数据,研究基于偏最小二乘(partial least square, PLS)回归模型的夏玉米不同位点SPAD值与氮营养指标间关系,确定可稳定指示夏玉米氮营养空间异质性变化的敏感叶位及叶片部位。结果表明,不同叶位间夏玉米叶片SPAD值和氮营养指标于植株间分布均呈典型的"钟型"特征,至TL5或TL6时达至峰值。同一叶位不同部位间SPAD值由20%至100%位点时则逐步升高,且80%~100%位点间无显著差异(P>0.05)。PLS分析结果显示,夏玉米不同叶位SPAD值与氮营养指标间模型精度决定系数(coefficient of determination, R2)和相对分析误差(relative percent deviation,RPD)范围分别为0.693~0.821和1.425~2.744。不同测试位点R2和RPD值范围则分别为0.660~0.847和1.607~2.451,满足模型精确诊断需求。此后,基于PLS模型中各叶位和叶片部位无量纲评价指标变量重要性投影值(variable importance for projection,VIP),确定顶4叶(TL4)完展叶60%~80%区间为夏玉米氮营养诊断的敏感区域,VIP值均高于临界值1.40,预测效果较为理想。研究可为实现氮营养的高效、快捷诊断和精准施氮提供参考。     

GFDL-ESM2M气候模式下京津冀地区未来潜在蒸散量时空变化

为探究未来潜在蒸散量时空变化特征,该研究以京津冀地区为例,基于美国GFDL提供的GFDL-ESM2M全球气候模式,得到京津冀地区92个格点2000-2050年的平均气温、最高气温、最低气温、太阳总辐射、平均相对湿度和近地面平均风速,应用Penman-Monteith公式计算京津冀地区未来92个格点的逐日潜在蒸散量(ET0),分析其时空分布特征及其与气象要素的相关关系。结果表明:未来年ET0总体呈增加趋势,RCP8.5情景下ET0上升速度最快,且随着时间推移增幅越来越大。夏季ET0增长速度最快,其次为春季、秋季与冬季,意味着未来ET0季节差异将愈加明显,可能出现更为严重的季节性干旱。ET0空间分布呈由西南向东北逐渐递减趋势,其中中部地区增速最快,增长趋势由中部向南北递减。不同气候情景下平均气温均呈逐年上升趋势,风速、太阳总辐射略微上升,而相对湿度下降。ET0与太阳总辐射的相关系数最大,呈由东北向西南递增趋势,其次为最高气温,呈由西北向东南递增趋势。ET0与相对湿度变化呈显著负相关,相关系数绝对值呈东北向西南递增趋势,ET0与风速相关度不明显。该研究可为农业需水预测与灌溉管理、科学应对气候变化提供基础支撑。     

基于Kjeldahl与Dumas方法的农作物秸秆总氮含量分析

凯氏定氮法(Kjeldahl)与杜马斯燃烧法(Dumas)是测定农业生物质总氮含量的主要检测手段,但二者的测定结果数值存在差异。该研究获取农作物秸秆样本(水稻、小麦、玉米、油菜和棉花)共计1 179个,分别采用Kjeldahl和Dumas方法测定总氮(TKN和TCN,total Kjeldahl nitrogen and total combustion nitroyen)含量,通过多种统计与分析方法,系统分析比较了不同农作物秸秆总氮含量及其分布的异同和相关关系。结果表明:不同农作物秸秆氮含量分布均呈非正态分布,建议采用中位数统计;5种秸秆总体的TKN质量分数为(7.12±1.87) g/kg,TCN质量分数为(8.00±2.13) g/kg,TKN含量显著小于TCN含量;小麦和棉花秸秆的TKN含量和TCN含量与其他秸秆间均存在显著差异(P <0.05);不同生物质TKN含量与TCN含量关系不同,建议采用最小中位数二乘法进行拟合分析。研究结果可为农作物秸秆科学利用提供数据及方法互通性支撑。