摘要
鱼类体长数据是渔业资源评估和管理的基础信息之一,来自渔业非独立调查(fishery dependent survey)的体长频率数据可以用来反映目标鱼种亲体和补充量的分布情况,并为基于体长结构的渔业资源评估模型重要输入信息。多元回归树是一种用来分析生物数据与环境特征数据间关系的挖掘技术。本文根据2007年12月-2009年12月中国远洋金枪鱼渔船渔捞日志所记录的大眼金枪鱼生物学数据,利用多元回归树方法并结合地理信息系统分析了大西洋大眼金枪鱼的空间分布及季度变化情况。结果表明:空间分布上大型大眼金枪鱼主要集中在7.5°N^15°N,17.5°W^45°W;中型大眼金枪鱼主要集中12.5°S^5°N,17.5°W^45°W;小型个体主要分布在7.5°S^5°N,5°W^17.5°W;经K-S检验,各空间尺度内体长分布差异显著。2009年1、2季度体长分布相对同质;3、4季度体长分布相对同质。
Size data is the basic information in fishery stock assessment and management. The spatio-temporal distribution of length-frequency derived from fisheries dependent data can be used to estimate the distribution of stock and recruitment. Multivariate regression tree （MRT） is a data-mining methodology that can analyze the relationships between multispecies data and environmental characteristics. In this study, based on the dressed weight data in the logbooks collected by Tuna Technology Group of China Distant-water Fisheries Association from December 2007 to December 2009, Multivariate Regression Tree and Geographical Information System （GIS） were applied to analyze spatial distribution and seasonal variation of bigeye tuna are size in the Central Atlantic Ocean. The result showed that the large-sized bigeye tuna are mainly distributed in 7.5 o N - 15 ° N, 17.5 ° W - 45 o W area ; Medium-sized bigeye tuna are mainly distributed in 12.5 ° S - 5 ° N, 17.5°W -45°W area; Small-sized individuals are mainly distributed in 7.5°S - 5°N,5°W - 17.5°W area. The results of K-S test showed that size distribution had seasonal differences apparently; Kolmogorov-Smirnov test proved that there were significant differences in size distribution among spatial areas. Quarters 1 and 2 were relatively homogeneous, and quarters 3 and 4 were relatively homogeneous.
出处
《上海海洋大学学报》
CAS
CSCD
北大核心
2013年第5期770-777,共8页
Journal of Shanghai Ocean University
基金
农业部三大洋金枪鱼观察员项目(08-54)
上海市自然科学基金(11ZR1415500)
关键词
体长频率
时空分布
多元回归树
延绳钓
大西洋
大眼金枪鱼
length-frequency
spatio-temporal distribution
multivariate regression tree
longline
AtlanticOcean
bigeye tuna
