Changes in the distribution of sardine eggs and larvae off Portugal, 1985–2000

Generalized additive models (GAMs) were fitted to sardine (Sardina pilchardus) egg distribution data from three daily egg production method surveys. The results showed that the area of egg cover off Portugal decreased significantly from 11 800 km² in 1988 to 7000 km² in 1997 and 7400 km² in 1999. This is because of a significant reduction in sardine egg presence off northern Portugal, GAM estimated areas being similar or higher in the late 1990s for southwestern and southern Portugal. The distributional area covered by larvae was not estimated for 1988 (larval distribution extended beyond the survey area), although it was probably higher than the 9600 km² for 1997 and 5500 km² for 1999. In 1997 and 1999, the Gulf of Cadiz was also sampled, indicating extensive areas with sardine eggs and larvae (more than 50% of the total area of distribution off Portugal). Standardized data from 15 ichthyoplankton surveys between 1985 and 2000 show a decline in the mean probability of egg presence within the Portuguese continental shelf from the mid‐1980s to the late‐1990s, because of a marked reduction in egg presence off northern Portugal. Sardine larval data from the same surveys suggest that the reduction in mean probability of presence in the north is less marked than for eggs (although this comparison ignores the presence of sardine larvae beyond the continental shelf in the 1980s). Similar changes off northern Portugal and western Galicia are observed in commercial sardine catches and the acoustically estimated area of fish distribution. It is possible that the observed decline in spawning area off northwestern Iberia during the 1990s is indirectly reflecting the prevalence of environmental conditions detrimental to sardine recruitment (northerly winds during winter that favour coastal upwelling and offshore transport), which have reduced the spawning contribution of young fish in that area.     

迭代算法的广义Q—收敛阶和效率

推广了迭代算法收敛分析中的Q－收敛阶的概念，据此给出了算法效率的一种一般的度量。分析了新效率定义与已有的Ostrowski效率和Brent效率之间的关系。这种度量适用于任何迭代算法，因而为分析算法的优劣提供了一个理论依据。     

基于高分辨率遥感影像的森林蓄积量估测

为了快速有效获取《综合开发利用项目》项目区的森林蓄积量,利用SPOT5和Rapid Eye高分辨率遥感影像,结合野外实地调查数据,采用最小二乘回归方法构建森林蓄积量遥感估测模型,估算柬埔寨王国上丁省特许地2012年的森林蓄积量。结果表明:1利用预留独立样本对模型进行精度验证,不分类型的模型的总体预测精度可达到99.37%,分类型的模型的总体预测精度分别可达到99.57%、97.30%、99.41%、96.84%、76.25%;2不分类型建模反演得到2012年研究区的森林总蓄积量为33197465.008 m3,各类型的森林蓄积量分别为16660360.382、7124988.801、5716238.005、4016470.930、186695.185 m3。结果表明利用高分辨率遥感影像快速估测区域森林蓄积量的可行性,也为合理规划和开发利用特许地的森林资源提供参考。     

基于GAM模型的三种降雨因子对贵州地质灾害危险性预测的对比分析

针对贵州省地质灾害的发生特征,选取连续降雨日数、连续无雨日数以及前期累计降雨量等进行主成分分析得到降雨主成分,与10d累计雨量、10d有效雨量两个单一的降雨因子在贵州省地形条件下分别采用广义加性模型(GAM)构建贵州省地质灾害危险性预测模型。通过检验对比分析,得出以下结论：(1)降雨主成分较客观地解释了降水对贵州省地质灾害危险性的影响,贵州省地质灾害主要发生在前期出现持续性降水或前期连续无雨时的突发性降水这两种情况。(2)在相同的地形地貌下垫面下,降雨主成分对地质灾害危险性的预测检验结果明显优于其余两种降雨因子,对地质灾害预测的精细化程度更接近实际发生情况。(3)不同降雨因子的选择对影响地质灾害的重要性有差异,选择降雨主成分时降水对地质灾害危险性的贡献更突出,其余影响地质灾害的地形地貌因子重要性依次为曲率、高程、坡向、坡度和剖面曲率。     

基于WEB和移动设备的学生安全平台设计

考虑到赔付流量三角形数据同一事故年反复观测的纵向特征以及数据结构的层次性,建立了分层广义线性模型.与通常的随机模型相比,分层广义线性模型不但可以选择条件反应变量的分布而且风险参数分布范围也更加广泛.利用h-似然函数估计分层广义线性模型的模型参数,降低了计算量.为使模型具有可比性,评估模型的预测精度,推导了模型预测误差的估计式.为充分利用已知赔付信息,将赔付额和赔付次数两种赔付信息纳入未决赔款准备金评估模型,建立了两阶段分层广义线性模型.在线性预测量中考虑了各种固定效应和随机效应以及模型结构的散布参数,改进了线性预估量结构.研究表明：分层广义线性模型对于数据的各种分布及形式都具有很好的适应性,更加符合保险实务现实的赔付规律.     

Environmental and spatial effects on the distribution of blue marlin (Makaira nigricans) as inferred from data for longline fisheries in the Pacific Ocean

Blue marlin is distributed throughout tropical and temperate waters in the Pacific Ocean. However, the preference of this species for particular habitats may impact its vulnerability to being caught. The relationship between spatio‐temporal patterns of blue marlin abundance and environmental factors is examined using generalized additive models fitted to catch and effort data from longline fisheries. The presence of blue marlin, and the catch rate given presence, are modeled separately. Latitude, longitude, and sea‐surface temperature explain the greatest proportion of the deviance. Spatial distributions of relative density of blue marlin, based on combining the probability of presence and relative density given presence, indicate that there is seasonal variation in the distribution of blue marlin, and that the highest densities occur in the tropics. Seasonal patterns in the relative density of blue marlin appear to be related to shifts in SST. The distribution and relative abundance of blue marlin are sufficiently heterogeneous in space and time that the results of analyses of catch and effort data to identify ‘hotspots’ could be used as the basis for time‐area management to reduce the amount of blue marlin bycaught in longline fisheries.     

三元肥料效应模型的整合与优化建模策略

针对当前作物肥效模型建模成功率普遍偏低的问题,探讨了提高建模成功率的优化建模策略.在分析整合三元非结构肥效模型非线性最小二乘(NLS)和三元二次多项式肥效模型普通最小二乘(OLS)、主成分回归(PCR)和可行广义最小二乘回归(FGLS)四种建模法的适用性基础上,根据水稻和露地蔬菜的1122个氮磷钾田间肥效试验结果,探讨...     

Habitat suitability modelling for sardine juveniles (Sardina pilchardus) in the Mediterranean Sea

Identification of potential juvenile grounds of short‐lived species such as European sardine (Sardina pilchardus) in relation to the environment is a crucial issue for effective management. In the current work, habitat suitability modelling was applied to acoustic data derived from both the western and eastern part of the Mediterranean Sea. Early summer acoustic data of sardine juveniles were modelled using generalized additive models along with satellite environmental and bathymetry data. Selected models were used to construct maps that exhibit the probability of presence in the study areas, as well as throughout the entire Mediterranean basin, as a measure of habitat adequacy. Areas with high probability of supporting sardine juvenile presence persistently within the study period were identified throughout the Mediterranean Sea. Furthermore, within the study period, a positive relationship was found between suitable habitat extent and the changes in abundance of sardine juveniles in each study area.     

Albacore (Thunnus alalunga) fishing ground in relation to oceanographic conditions in the western North Pacific Ocean using remotely sensed satellite data

Satellite‐based oceanographic data of sea surface temperature (SST), sea surface chlorophyll‐a concentration (SSC), and sea surface height anomaly (SSHA) together with catch data were used to investigate the relationship between albacore fishing ground and oceanographic conditions and also to predict potential habitats for albacore in the western North Pacific Ocean. Empirical cumulative distribution function and high catch data analyses were used to calculate preferred ranges of the three oceanographic conditions. Results indicate that highest catch per unit efforts (CPUEs) corresponded with areas of SST 18.5–21.5°C, SSC 0.2–0.4 mg m^?3, and SSHA ?5.0 to 32.2 cm during the winter in the period 1998–2000. We used these ranges to generate a simple prediction map for detecting potential fishing grounds. Statistically, to predict spatial patterns of potential albacore habitats, we applied a combined generalized additive model (GAM) / generalized linear model (GLM). To build our model, we first constructed a GAM as an exploratory tool to identify the functional relationships between the environmental variables and CPUE; we then made parameters out of these relationships using the GLM to generate a robust prediction tool. The areas of highest CPUEs predicted by the models were consistent with the potential habitats on the simple prediction map and observation data, suggesting that the dynamics of ocean eddies (November 1998 and 2000) and fronts (November 1999) may account for the spatial patterns of highest albacore catch rates predicted in the study area. The results also suggest that multispectrum satellite data can provide useful information to characterize and predict potential tuna habitats.     

气象因素影响下小麦蚜虫种群动态突变模型分析

【目的】根据小麦蚜虫种群动态变化和气候因素的关系,建立小麦蚜虫种群动态的突变模型,以期为蚜虫的防治提供参考。【方法】假设研究区域不变,小麦的品种、天敌状况、农民施肥、喷洒农药年际变化变化很小时,将气候因素加以细化,以温度、相对湿度和作物生长状况为控制变量,在广义logistic模型的基础上建立蚜虫种群动态变化的燕尾突变模型,并对该模型进行了检验。【结果】构建了受温度、相对湿度、作物生长状况3种因素作用的小麦蚜虫种群动态模型,并在此基础上构建了燕尾突变模型。利用燕尾突变模型预测了蚜虫种群动态在气候因素影响下突然爆发的可能情况:当蚜虫种群动态处于分歧点集中的Ⅴ区,且控制变量有向Ⅰ、Ⅱ、Ⅲ、Ⅳ 4个区域发生变化趋势时,蚜虫种群系统将会产生突变;蚜虫种群动态处于分歧点集的Ⅱ区,且控制变量从Ⅱ区变到Ⅰ、Ⅲ、Ⅴ区时,系统的稳定性不会引起改变;当蚜虫种群动态处于分歧点集的Ⅰ、Ⅲ、Ⅳ区,且控制变量变化到Ⅴ区时,系统的稳定性也不会产生改变。验证结果表明,燕尾突变模型可以预测蚜虫种群生长过程中的突变行为。【结论】构建的燕尾突变模型可以较好地预测小麦蚜虫种群动态的突然变化。