中国水产科学Issue(5)：1007-1014,8.DOI:10.3724/SP.J.1118.2015.14552
阿根廷滑柔鱼渔场预报模型最适时空尺度和环境因子分析
Impacts of temporal and spatial scale as well as environmental data on fishery forecasting models for Illex argentinus in the southwest Atlantic
摘要
Abstract
Fishery forecasting is an important component of fisheries science. It has vital significance for fishery production and management. Illex argentinus is an important target for Chinese squid jigging fleets in the southwest Atlantic Ocean. Some previous studies employed various approaches to forecast optimal I. argentinus fishing grounds based on environmental factors, such as sea surface temperature (SST), sea surface height (SSH), and chlorophyll-a concentration (Chl-a). These approaches use experiential knowledge obtained from historical fisheries and environmental data to forecast fishing grounds, but there is no research on how to select the most appropriate spatial and temporal scales or environmental data to forecast models. In this study, models were constructed based on different environmental factors with various spatial and temporal scales to better forecast optimal I. argentinus fishing grounds in the southwest Atlantic Ocean. <br> In this study, historical fishing data from Chinese mainland squid jigging fleets from 2003 to 2011, sea surface temperature (SST), sea surface height (SSH), and chlorophyll-a (CHL-a) data were divided into different temporal and spatial scales. Temporal scales included “weekly” and “monthly, ” spatial scales included “0.25° × 0.25°, ” “0.5°× 0.5°,”and“1.0° × 1.0°,”environmental factors were divided into four categories, including I (SST), II (SST and SSH), III (SST and Chl-a), and IV (SST, SSH, and Chl-a). A total of 24 models were constructed using error backpropagation artificial neural network; model training, validating, and testing were completed in Matlab. Mean square error and average relative variance (ARV) were used to evaluate accuracy, and sensitivity analyses were used to evaluate the interpretation of models for fishing grounds. <br> The results indicated that the fishery forecasting model with maximum accuracy and minimum ARV was constructed by two models, one was with a “weekly” temporal scale, “1.0° × 1.0°” spatial scale, and “SST”environmental factor, whereas the other was with a“monthly”temporal scale,“0.25° × 0.25°”spatial scale, and“SST”environmental factor. Sensitivity analyses using those two models showed that models with different temporal and spatial scales expressed different habitat suitability. <br> This research revealed that when models had the same temporal scales, there were no proportional or inverse relationships between spatial scale and model accuracy, when models had same spatial scales, there was no proportional or inverse relationships between temporal scale and model accuracy. Additionally, more environmental factors were not always better;sometimes more environmental factors increased the difficulty of model fitting. In summary, considering the temporal and spatial scale of fishing and environmental data was needed to construct fishing ground forecasting models for I. argentinus.关键词
阿根廷滑柔鱼/渔情预报/神经网络/时空尺度/环境因子Key words
Illex argentines/fishery forecasting/artificial neural network/temporal and spatial scale/environmental factor引用本文复制引用
汪金涛,高峰,雷林,官文江,陈新军..阿根廷滑柔鱼渔场预报模型最适时空尺度和环境因子分析[J].中国水产科学,2015,(5):1007-1014,8.基金项目
国家863计划项目(2012AA092303) （2012AA092303）
国家发改委产业化专项(2159999) （2159999）
上海市科技创新行动计划项目(12231203900) （12231203900）
国家科技支撑计划项目(2013BAD13B01) （2013BAD13B01）
