阐述课堂观察的概念及其在阅读教学中的应用原则。以外研版初中《英语》九年级(上)Module 3 Unit 2 There were few doctors,so he had to work very hard on his own阅读教学为例,简析以发展学生思维品质为主导的阅读教学课堂观察的流...阐述课堂观察的概念及其在阅读教学中的应用原则。以外研版初中《英语》九年级(上)Module 3 Unit 2 There were few doctors,so he had to work very hard on his own阅读教学为例,简析以发展学生思维品质为主导的阅读教学课堂观察的流程和反思,旨在探寻阅读教学课例中的目标设置、教师提问和学生应答与学生思维品质发展的适切性,进而探寻培养其思维品质的有效策略。展开更多
基于2012—2018年4—8月我国东南太平洋智利竹䇲鱼(Trachurus murphyi)渔捞日志数据,应用地理权重回归模型(GWR)探究智利竹䇲鱼渔场资源分布与环境因子的空间异质性关系。结果表明,环境因子海面温度基于GWR模型回归的拟合优度为0.54,校正...基于2012—2018年4—8月我国东南太平洋智利竹䇲鱼(Trachurus murphyi)渔捞日志数据,应用地理权重回归模型(GWR)探究智利竹䇲鱼渔场资源分布与环境因子的空间异质性关系。结果表明,环境因子海面温度基于GWR模型回归的拟合优度为0.54,校正的拟合优度为0.34,赤池信息准则(Akaike Information Criterion,AIC)值为1022.08;叶绿素a浓度基于GWR模型回归的拟合优度为0.48,校正的拟合优度为0.36,AIC值为2321.95;海面温度异常值的拟合优度为0.74,校正的拟合优度为0.58,AIC值为2268.07;海面高度异常值的拟合优度为0.72,校正的拟合优度为0.59,AIC值为2201.93;作业水深的拟合优度为0.46,校正的拟合优度为0.42,AIC值为2675.07;海面温度异常对东南太平洋智利竹䇲鱼渔场时空分布影响最大。GWR模型便于发现资源分布的“热点”海域,可为我国智利竹筴鱼渔船生产提供科学依据。展开更多
The generalized linear model （GLM） and generalized additive model （GAM） were applied to the standardization of catch per unit effort （CPUE） for Chilean jack mackerel from Chinese factory trawl fishing fleets in ...The generalized linear model （GLM） and generalized additive model （GAM） were applied to the standardization of catch per unit effort （CPUE） for Chilean jack mackerel from Chinese factory trawl fishing fleets in the Southeast Pacific Ocean from 2001 to 2010 by removing the operational, environmental, spatial and temporal impacts. A total of 9 factors were selected to build the GLM and GAM, i.e., Year, Month, Vessel, La Nifia and E1 Nifio events （ELE）, Latitude, Longitude, Sea surface temperature （SST）, SST anomaly （SSTA）, Nino3.4 index and an interaction term between Longitude and Latitude. The first 5 factors were significant components in the GLM, which in combination explained 27.34% of the total variance in nominal CPUE. In the stepwise GAM, all factors explained 30.78% of the total variance, with Month, Year and Vessel as the main factors influencing CPUE. The higher CPUE occurred during the period April to July at a SST range of 12-15℃ and a SSTA range of 0.2-1.0℃. The CPUE was significantly higher in normal years compared with that in La Nifia and E1 Nifio years. The abundance of Chilean jack mackerel declined during 2001 and 2010, with an increase in 2007. This work provided the relative abundance index of Chilean jack mackerel for stock as- sessment by standardizing catch and effort data of Chinese trawl fisheries and examined the influence of temporal, spatial, environ- mental and fisheries operational factors on Chilean jack mackerel CPUE.展开更多
文摘阐述课堂观察的概念及其在阅读教学中的应用原则。以外研版初中《英语》九年级(上)Module 3 Unit 2 There were few doctors,so he had to work very hard on his own阅读教学为例,简析以发展学生思维品质为主导的阅读教学课堂观察的流程和反思,旨在探寻阅读教学课例中的目标设置、教师提问和学生应答与学生思维品质发展的适切性,进而探寻培养其思维品质的有效策略。
文摘基于2012—2018年4—8月我国东南太平洋智利竹䇲鱼(Trachurus murphyi)渔捞日志数据,应用地理权重回归模型(GWR)探究智利竹䇲鱼渔场资源分布与环境因子的空间异质性关系。结果表明,环境因子海面温度基于GWR模型回归的拟合优度为0.54,校正的拟合优度为0.34,赤池信息准则(Akaike Information Criterion,AIC)值为1022.08;叶绿素a浓度基于GWR模型回归的拟合优度为0.48,校正的拟合优度为0.36,AIC值为2321.95;海面温度异常值的拟合优度为0.74,校正的拟合优度为0.58,AIC值为2268.07;海面高度异常值的拟合优度为0.72,校正的拟合优度为0.59,AIC值为2201.93;作业水深的拟合优度为0.46,校正的拟合优度为0.42,AIC值为2675.07;海面温度异常对东南太平洋智利竹䇲鱼渔场时空分布影响最大。GWR模型便于发现资源分布的“热点”海域,可为我国智利竹筴鱼渔船生产提供科学依据。
基金co-funded by the National High Technology Research and Development program of China(No.2012AA092301)the Agriculture Science Technology Achievement Transformation Fund(No.2010C00001)the Project of Fishery Exploration in High Seas of the Ministry of Agriculture of China(2010–2011)
文摘The generalized linear model （GLM） and generalized additive model （GAM） were applied to the standardization of catch per unit effort （CPUE） for Chilean jack mackerel from Chinese factory trawl fishing fleets in the Southeast Pacific Ocean from 2001 to 2010 by removing the operational, environmental, spatial and temporal impacts. A total of 9 factors were selected to build the GLM and GAM, i.e., Year, Month, Vessel, La Nifia and E1 Nifio events （ELE）, Latitude, Longitude, Sea surface temperature （SST）, SST anomaly （SSTA）, Nino3.4 index and an interaction term between Longitude and Latitude. The first 5 factors were significant components in the GLM, which in combination explained 27.34% of the total variance in nominal CPUE. In the stepwise GAM, all factors explained 30.78% of the total variance, with Month, Year and Vessel as the main factors influencing CPUE. The higher CPUE occurred during the period April to July at a SST range of 12-15℃ and a SSTA range of 0.2-1.0℃. The CPUE was significantly higher in normal years compared with that in La Nifia and E1 Nifio years. The abundance of Chilean jack mackerel declined during 2001 and 2010, with an increase in 2007. This work provided the relative abundance index of Chilean jack mackerel for stock as- sessment by standardizing catch and effort data of Chinese trawl fisheries and examined the influence of temporal, spatial, environ- mental and fisheries operational factors on Chilean jack mackerel CPUE.
