文章摘要
蔡碧莹,朱长波,刘 慧,常丽荣,肖露阳,孙倩雯,蔺 凡.桑沟湾养殖海带生长的模型预测.渔业科学进展,2019,40(3):31-41
桑沟湾养殖海带生长的模型预测
Model simulated growth of the kelp Saccharina japonica in Sanggou Bay
投稿时间:2018-04-19  修订日期:2018-04-28
DOI:10.19663/j.issn2095-9869.20180419001
中文关键词: 桑沟湾  海带  个体生长模型  环境条件;STELLA
英文关键词: Sanggou Bay  Kelp  Individual growth model  Environmental conditions  STELLA
基金项目:科技部国际创新合作专项“基于生态系统的水产养殖空间规划研究”(2016YFE0112600)和欧盟地平线2020项目AquaSpace (633476-H2020-SFS-2014-2015)共同资助
作者单位
蔡碧莹 上海海洋大学水产与生命学院 上海 201306中国水产科学研究院黄海水产研究所 青岛 266071青岛海洋科学与技术试点国家实验室海洋渔业科学与食物产出过程功能实验室 青岛 266071 
朱长波 中国水产科学研究院南海水产研究所 广州 510300 
刘 慧 中国水产科学研究院黄海水产研究所 青岛 266071青岛海洋科学与技术试点国家实验室海洋渔业科学与食物产出过程功能实验室 青岛 266071 
常丽荣 威海长青海洋科技股份有限公司 荣成 264316 
肖露阳 威海长青海洋科技股份有限公司 荣成 264316 
孙倩雯 上海海洋大学水产与生命学院 上海 201306中国水产科学研究院黄海水产研究所 青岛 266071青岛海洋科学与技术试点国家实验室海洋渔业科学与食物产出过程功能实验室 青岛 266071 
蔺 凡 中国水产科学研究院黄海水产研究所 青岛 266071青岛海洋科学与技术试点国家实验室海洋渔业科学与食物产出过程功能实验室 青岛 266071 
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中文摘要:
      海带(Saccharina japonica)是一种常见的大型经济褐藻,是海洋生态系统重要的初级生产者,也是我国北方沿海主要的养殖藻类。本研究旨在建立海带个体生长数值模型,并以此预测中国北方近海大规模筏式养殖条件下海带的生长情况。本研究以桑沟湾养殖海带为例,利用可视化模型软件STELLA描述海带生长的关键过程及其与环境参数的关系,以净生长量(Ngrowth)=总生长量(Ggrowth)–呼吸作用(resp)–枯烂(Ekelp)为基本框架,模拟和预测海带的生物量和叶片长度变化。海带的总生长用光照、温度、盐度、海带体内营养盐(包括N和P)等强制函数定义,其中,光照参数来自桑沟湾气象记录,盐度、温度和营养盐为现场调查实测值。模型模拟桑沟湾养殖海带的长度与干重结果与实测值的拟合度R2值分别为0.936、0.963,说明该模型能够很好反映海带的真实生长情况。可靠的个体生长模型是评估海带养殖容量的基础,并可为水产养殖区的空间规划提供决策依据。
英文摘要:
      Saccharina japonica is a major economically important brown macroalgae. It is an important primary producer in the marine ecosystem and is also cultured under long-line in coastal northern China. The aim of this work was to develop an individual growth model capable of simulating the growth of the large-scale raft-cultured kelp in the north of China. The model can provide data support, to some extent, to northern kelp farming. The key processes for kelp growth and its relationship with environmental parameters were analyzed, using the Sanggou Bay aquaculture zone as the study area. We used the visualization model software STELLA, which simulated and predicted the growth of the length and dry weight of kelp. The individual growth model basic framework was Ngrowth = Ggrowth–resp–Ekelp, where, net growth was defined as gross growth minus respiration and erosion consumption. The gross growth of kelp was defined as a function of light, temperature, salinity, and internal nutrient (N and P) content in kelp, whereas the light parameters were obtained from the Sanggou Bay meteorological records, and salinity, temperature, and nutrient (N and P) measurements were observed at the site in Sanggou Bay. According to the model simulated results, model predictions are well within the observed results. The individual growth model simulated the length results and measured values of the kelp, with the fitting degree R2 in the high, medium, and low zones as 0.936, whereas dry weight simulated results and measured values of the kelp had fitting degree R2 in the high, medium, and low zones as 0.963. According to the results, the model can accurately reflect the true growth process of kelp. A reliable individual growth model is the basis for the assessment of aquaculture carrying capacity. In addition, the individual growth model may provide a scientific foundation for aquaculture spatial planning and management.
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