小麦冻害发生原因及防御对策

分析了小麦发生冻害的多种原因,并结合多年工作实践,提出了一些预防小麦冻害发生的对策,以促进小麦获得高产。     

高致病性禽流感与天气条件分析

利用全国气象观测资料、NCEP／NCAR日平均再分析数据资料集和我国高致病性禽流感疫情资料,分析高致病性禽流感发生的时空特征以及与天气条件的关系。结果表明,我国高致病性禽流感全年可以发生,疫情的分布范围广,大部分地区都有出现。发生和传播与环境气象条件有关,季节性明显,冬季和秋季为主要发病季节。冬季禽流感发生前高空500hPa以槽为主,冷空气活动频繁。发生日基本在高压系统的控制之下,地面流场呈辐散状,风速稳定少变。     

一次短时强降水暴雨天气过程成因分析

利用常规气象资料、自动区域站降水资料及卫星云图资料,对2013年7月22日发生在甘肃省陇南市两当县的暴雨天气进行了分析.结果表明,此次暴雨是在东高西低的典型暴雨环流形势下,高原短波槽、副高西伸北抬及低层切变线共同作用造成的,同时,偏南气流和地面锋面也是造成暴雨的重要因子;物理量诊断分析表明水汽通量、水汽通量散度、垂直速度等物理量在相同的时间均最有利于暴雨的发生发展;卫星云图上对流云团的发展移动与TBB梯度大值区暴雨落区有很好对应关系.     

淮安市农田土壤pH值变化趋势及原因分析

研究淮安市不同农域、不同土壤类型1982年以来土壤p H值变化规律,结果表明:2013年全市省级监测点耕层土壤p H值在5.4~8.1,平均值7.0,平均值与1982年相比减少0.8个单位;1982—2013年,土壤p H值平均值总体呈下降趋势;2009—2013年,土壤p H值基本趋于稳定。氮肥过量施用是农田土壤酸化加速的首要原因,其次作物根系分泌物直接导致根际土壤p H值降低。另外,生理酸性肥料的施用也会引起土壤p H值的下降。     

瑞昌市大壤灌区农业干旱成因与抗旱对策

以江西省瑞昌市大壤灌区为例,着重分析江西省灌区农业干旱的成因,提出灌区抗旱的对策,以期为从事相关研究人员提供有益借鉴。     

Population trends in northern spotted owls: Associations with climate in the Pacific Northwest

We used reverse time capture-mark-recapture models to describe associations between rate of population change (λ) and climate for northern spotted owls (Strix occidentalis caurina) at six long-term study areas in Washington and Oregon, USA. Populations in three of six areas showed strong evidence of declining populations, while populations in two additional areas were likely declining as well. At four areas, λ was positively associated with wetter-than-normal conditions during the growing season, which likely affects prey availability. Lambda was also negatively associated with cold, wet winters and nesting seasons, and the number of hot summer days. The amount of annual variation in λ accounted for by climate varied across study areas (3-85%). Rate of population change was more sensitive to adult survival than to recruitment; however, there was considerable variation among years and across study areas for all demographic rates. While annual survival was more closely related to regional climate conditions, recruitment was often associated with local weather. In addition to climate, declines in recruitment at four of six areas were associated with increased presence of barred owls. Climate change models predict warmer, wetter winters and hotter, drier summers for the Pacific Northwest in the first half of the 21st century. Our results indicate that these conditions have the potential to negatively affect annual survival, recruitment, and consequently population growth rates for northern spotted owls.     

2008年持续低温降雪冻雨对梁子湖流域鸟类的影响调查

2008年1月,梁子湖流域遭遇历时罕见的持续低温降雪冻雨极端天气,304km~2梁子湖冰冻封湖15 d。地面持续冰雪覆盖,导致鸟类生境结构破坏,生境资源不可利用,最终因长时间食物匮乏和冷害的双重影响出现严重灾害性死亡。涉及鸟类22科42种,流域内数量损失30万～40万只。     

湖州市1998年迟中秋蚕血液型脓病暴发原因分析

分析了湖州市１９９８年迟中秋蚕血液型脓病暴发的原因，并提出了若干控制该病的对策。     

钻孔误差产生原因及防止方法探究

职业学校钳工实习教学的钻孔是钳工专业一项重要基本操作技能,要求进行系统的技能和技巧训练,掌握加工要求较高的孔及位置精度的方法。但由于钻孔中的累积误差很难完全消除,钻孔的位置精度也就很难保证,因此如何消除或减少钻孔的误差是钳工实习教学中的难点和终点。文章从钻孔误差产生的原因和防止方法两个角度出发,探索了钳工实习教学中,如何消除或减少钻孔误差的教育教学生产实践。     

AFLA-maize,a mechanistic model for Aspergillus flavus infection and aflatoxin B1 contamination in maize

A mechanistic weather-driven model was developed based on the infection cycle of Aspergillus flavus on maize to predict the risk of aflatoxin contamination in field on a daily basis from silk emergence to harvest; hourly data of temperature, relative humidity and rain were used as model input. The work was done in four steps: (i) development of the model prototype; (ii) collection of Italian field data on aflatoxin contamination in maize with related crop and weather data; (iii) development of a probability index to exceed the legal limit of 5 μg of aflatoxin B₁ per kg of unprocessed maize by combining model predictions and field data in a logistic regression; and (iv) validation with Italian data of the probability index and release of the predictive model, named AFLA-maize. Predictions of maize contamination above the threshold of 5 μg/kg in the data set used for parameterization of the regression equation were correct for 73% of field samples; 59% and 14%, respectively, were not contaminated and contaminated. In a second independent data set, 68% of samples were correctly predicted. The model AFLA-maize provides prediction of A. flavus infection and aflatoxin contamination along the growing season and at harvest. This information is useful to support decision-making for (i) crop management, (ii) harvest timing, (iii) maize lots cleaning and logistic, and (iv) maize sampling for aflatoxin analysis at consignment.