Feeding habits of albacore Thunnus alalunga in the transition region of the central North Pacific

ABSTRACT:   The feeding habits of albacore Thunnus alalunga (fork length: 48.9–76.2 cm, n  = 132) were examined from late spring to early autumn in relation to its northward migration in the transition region between the subtropical and subarctic fronts in the central North Pacific. Samples were collected at night using surface gill nets or during daytime pole-and-line surveys in 2001 and 2002. During May and June, albacore fed mainly on Japanese anchovy Engraulis japonicus , which accounted for 27.2%, 67.0%, and 45.5% of the total stomach contents by number ( Cn ), wet weight ( WW ), and frequency of occurrence ( F ), respectively, and secondarily on the subarctic gonatid squid Gonatopsis borealis ( Cn , 15.8%; WW , 10.8%; F , 28.8%). From July to September, albacore continued to depend on Japanese anchovy ( Cn , 48.2–52.8%; WW , 79.9–95.2%; F , 27.8–85.4%). These results corresponded well with the remarkable rebound of the Japanese anchovy stock since the 1990s. Gonatopsis borealis , the main squid prey from May to June, almost disappeared from the stomachs of albacore from July to September, probably due to the northward migration of this squid to subarctic waters in summer. The feeding impact of albacore on the Japanese anchovy stock in the transition region was conservatively estimated to be from 1400 to 2100 tons per day from late spring to early autumn.     

Springtime abundance of chaetognaths in the shelf region of the northern Gulf of Alaska, with observations on the vertical distribution and feeding of Sagitta elegans

Chaetognatha were among the most dominant macrozooplankton taxa collected in 6 years of springtime collections, both throughout the water column and near-bottom on the continental shelf in the northern Gulf of Alaska. Three species ( Sagitta elegans, S. scrippsae, and Eukrohnia hamata ) were collected in 248 collections, although S. elegans was the numerically dominant species overall during most cruises. Collections taken in epibenthic sleds generally contained about two orders of magnitude more chaetognaths than those that sampled throughout the water column. Two size modes were apparent in the S. elegans size-frequency distributions which were believed to belong to different cohorts. Growth rate was on the order of 2–3 mm per month. The two cohorts showed asynchronous diel vertical distribution patterns, with the smaller individuals found near the surface during the day whereas the larger individuals were near the surface at night. About 7.5% of the S. elegans examined contained food. Copepods made up the majority (∼89% by number) of the diet of both large and small individuals. Euphausiid juveniles and cirripede larvae were also observed, as well as several incidences of cannibalism by large chaetognaths on smaller individuals. Based on the results of two diel series, this species was observed to feed mainly during the night-time.     

闽南-台湾浅滩渔场狗母鱼类食性的研究

本文对闽南一台湾浅滩渔场狗母鱼类(多齿蛇鲻、花斑蛇鲻和大头狗母鱼)的食料生物组成、摄食强度的季节变化以及消化器官与食性等方面进行了探讨。结果表明，这三种狗母鱼类都属于游泳动物食性的底层鱼类，而且是同种残食的中级肉食性鱼类，其食料生物组成比较简单，主要摄食鱼类和头足类，还兼食长尾类、短尾类和口足类。被捕食对象的大小，随着捕食对象(多齿蛇鲻或花斑蛇鲻)叉长的增加而增大。狗母鱼类周年均有摄食，多齿蛇鲻和花斑蛇鲻在产卵盛期(3—4月)摄食强度较高。它们的消化器官的形态结构与其肉食性相适应，多齿蛇鲻和花斑蛇鲻的消化器官和食性相近似，比大头狗母鱼的食性较凶猛。     

瘤背石磺的生态习性观察

2003年4～7月,作者对江苏射阳河口滩涂的瘤背石磺作了生态调查,并在室内进行温箱试养,观察其运动、呼吸、消化、生殖及对刺激物的反应等。结果表明,瘤背石磺栖息在潮上带滩涂,其每千克土壤中含N 0．325g、P 0．020g、K 0．521g、Cl 0．084g、有机质7．68g,土壤pH值9．43,含盐量1．615;在温度20～28℃,湿度接近100％时瘤背石磺才出来活动和摄食;在人工饲养下,瘤背石磺喜食螺旋藻。从解剖上看,它用呼吸腔呼吸,外套膜切片中有钙质颗粒,说明该物种是腹足纲动物由水生向陆生过渡的类型,体现了肺螺亚纲的特征。     

鸭绿江上游花羔红点鲑的年龄_生长_食性和繁殖的研究

花羔红点鲑的鳞片年累特征为疏密一切割混合型。体长和体重关系密切,属均匀性生长类型。主要以水生昆虫为食,对食物有明显的选择性;主要摄食季节为夏秋两季,但可终年摄食。雌雄鱼几乎２＋龄达到性成熟,产卵期为１０￣１１月,绝对繁殖力为２８０￣５００粒,每年产一次卵,属秋季产卵类型。产卵场底质为石砾,水深５０￣７０ｃｍ,水流速度１．５￣２．０ｍ／ｓ,水温一般为５￣８℃。     

基于显著性增强和迁移学习的鱼类识别研究

针对水下鱼类无法快速准确识别的难点,提出一种具有图像主体自动增强功能的鱼类迁移学习方法。该方法将鱼类RGB图像转换至Lab颜色空间后,利用中央周边算子计算得到整个输入图像的显著性值,进而提供鱼类目标的潜在区域,并结合GrabCut算法获取鱼类分割图像,最终将融合分割图的原始图像送入优化后的残差网络中进行训练。通过对23种鱼类进行识别试验,结果显示,固定ImageNet数据集上ResNet-50预训练模型的conv1层和conv2层参数,微调高层参数的方法能够取得最好的识别效果,且在公开的Fish4Knowledge数据集上,该模型取得了最高的识别准确率,平均识别精度达到99.63%。与其他卷积神经网络方法的对比结果显示,本方法在Fish4Knowledge和Fish30Image数据集上的识别精度和时间性能均具有较大优势,其中识别准确率至少提升4.98%。多个数据集上的试验验证了模型的有效性。     

基于学习通平台的高职专业课程数字化教学资源设计与应用——以“农产品质量安全检测”课程数字化资源构建为例

随着计算机技术与网络技术的不断发展,利用网络平台进行优质数字化资源建设与整合,并加以应用,已成为高职院校教学模式改革的主要手段。综述目前高职专业课数字化教学资源建设情况,并结合超星学习通平台的特点,以“农产品质量安全检测”课程为例阐述高职院校专业课程优质数字化资源建设的设计思路、制作方法及应用方式,对于丰富教学手段、提高学生的学习兴趣和教学质量具有重要作用。     

Predicting soil depth in a large and complex area using machine learning and environmental correlations

Soil depth is critical for eco-hydrological modeling, carbon storage calculation and land evaluation. However, its spatial variation is poorly understood and rarely mapped. With a limited number of sparse samples, how to predict soil depth in a large area of complex landscapes is still an issue. This study constructed an ensemble machine learning model, i.e., quantile regression forest, to quantify the relationship between soil depth and environmental conditions. The model was then combined with a rich set of environmental covariates to predict spatial variation of soil depth and straightforwardly estimate the associated predictive uncertainty in the 140 000 km² Heihe River basin of northwestern China. A total of 275 soil depth observation points and 26 covariates were used. The results showed a model predictive accuracy with coefficient of determination (R²) of 0.587 and root mean square error (RMSE) of 2.98 cm (square root scale), i.e., almost 60% of soil depth variation explained. The resulting soil depth map clearly exhibited regional patterns as well as local details. Relatively deep soils occurred in low lying landscape positions such as valley bottoms and plains while shallow soils occurred in high and steep landscape positions such as hillslopes, ridges and terraces. The oases had much deeper soils than outside semi-desert areas, the middle of an alluvial plain had deeper soils than its margins, and the middle of a lacustrine plain had shallower soils than its margins. Large predictive uncertainty mainly occurred in areas with a lack of soil survey points. Both pedogenic and geomorphic processes contributed to the shaping of soil depth pattern of this basin but the latter was dominant. This findings may be applicable to other similar basins in cold and arid regions around the world.     

基于高光谱与在线序列极限学习机确证大米产地方法

为满足快速无损的大米产地确证需求,采集吉林省梅河口市水稻主产区及松原、大安、辉南等其他水稻产区共990个大米样本的高光谱图像（400~1 000 nm）作为研究对象,利用多元散射校正（MSC）处理方法对光谱进行预处理。采用多层感知机（MLP）、极限学习机(ELM)与在线序列极限学习机(OS-ELM)算法,分别基于全波段高光谱数据以及经多维尺度分析（MDS）方法降维后的数据建立产地确证模型。结果表明,基于全波段高光谱数据的OS-ELM模型分类性能最好,准确率达到98.3%。经MDS处理后,输入的数据变量减少了96.6%,MDS-OS-ELM模型准确率稳定在97.4%。对三种模型的训练时间进行对比分析,OS-ELM训练时间明显优于MLP,在分批次获取数据时训练时间优于ELM。为大米产地确证提供了一种高效、准确、稳定的方法。     

谈高校管理中的激励技术

在高校的管理过程中,科学地选择激励技术是调动教职工积极性,发挥教职工创造性,质量和办学水平的有效的一从六个方面对此了探讨。