文章摘要
姜娓娓,白永安,袁明军,李伟伟,李昂,朱玲,毛玉泽,蒋增杰.辽东湾蛤蜊岗四角蛤蜊和光滑河蓝蛤的能量收支及其养殖容量评估.渔业科学进展,2024,45(6):47-56
辽东湾蛤蜊岗四角蛤蜊和光滑河蓝蛤的能量收支及其养殖容量评估
Energy budget and carrying capacity of the surf clam, Mactra veneriformis and the estuarine clam, Potamocorbula laevis in Geligang, Liaodong Bay
投稿时间:2023-11-12  修订日期:2023-12-07
DOI:10.19663/j.issn2095-9869.20231112001
中文关键词: 蛤蜊岗  四角蛤蜊  光滑河蓝蛤  能量收支  养殖容量
英文关键词: Geligang  Mactra veneriformis  Potamocorbula laevis  Energy budget  Carrying capacity
基金项目:国家自然科学基金(32303035)、山东省自然科学基金(ZR2021QD035)、山东省“泰山学者青年专家计划”(tsqn201909166)和财政部和农业农村部:国家现代农业产业技术体系共同资助
作者单位
姜娓娓 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266071 
白永安 盘锦光合蟹业有限公司 大连 盘锦 124200 
袁明军 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266071 
李伟伟 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266072 
李昂 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266073 
朱玲 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266074 
毛玉泽 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266075 
蒋增杰 海水养殖生物育种与可持续产出全国重点实验室 中国水产科学研究院黄海水产研究所 山东 青岛 266076 
摘要点击次数: 445
全文下载次数: 1610
中文摘要:
      为探究辽东湾蛤蜊岗四角蛤蜊(Mactra veneriformis)和光滑河蓝蛤(Potamocorbula laevis)的能量收支及其养殖容量情况,本研究利用便携式颗粒计数器、多通道溶氧仪以及现场流水系统,测定了四角蛤蜊[壳长(35.89±1.61) mm]和光滑河蓝蛤[壳长(17.66±0.66) mm]的摄食、代谢等生理指标,分析了其能量分配策略,并在此基础上,基于有机碳供需平衡模型估算了辽东湾蛤蜊岗2种主要滩涂贝类的养殖容量。结果显示:1)四角蛤蜊和光滑河蓝蛤的滤水率分别为(4.87±0.85) L/(h·g)和(6.46± 2.25) L/(h·g),耗氧率分别为(0.94±0.45) mg/(h·g)和(0.22±0.14) mg/(h·g),四角蛤蜊和光滑河蓝蛤的总吸收能分别为748.97~1 333.52 J/(h·g)和931.55~1 647.08 J/(h·g);2)基于有机碳供需平衡模型,结合海域初级生产力及贝类滤水率,估算出辽东湾蛤蜊岗海域1龄(总湿重6.7 g)、2龄(总湿重9.3 g)和3龄(总湿重14.6 g)四角蛤蜊的养殖容量分别为57、47和34 ind./m2;1龄(总湿重0.14 g)、2龄(总湿重0.69 g)和3龄(总湿重1.25 g)光滑河蓝蛤的养殖容量分别为346、143和99 ind./m2。四角蛤蜊的平均养殖密度已超出了该海域的养殖容量,而光滑河蓝蛤的养殖密度尚存在一定的空间。研究结果为滩涂贝类资源的合理开发利用以及生物多样性保护提供了基础数据。
英文摘要:
      China is the largest aquaculture country in the world, with mariculture production accounting for more than 50% of the total production in the world. In 2021, the production of shellfish in China increased to 1.546 × 107 tons, accounting for approximately 70% of the mariculture production. Filter-feeding bivalves such as oysters and clams are the main species of mariculture in China. In addition to the important economic values, filter-feeding bivalves influence ecosystem nutrient cycling through feeding, metabolism, and biodeposition and play roles in increasing the water transparency, preventing harmful algal blooms, controlling eutrophication, and promoting carbon storage. The physiological activities of filter-feeding bivalves, especially ingestion and metabolism, form the link between planktonic and benthic ecosystems, and their physiological indicators are the basic parameters for evaluating the energy budget and carrying capacity. However, although researchers have conducted a series of studies on the physiological activities of filter-feeding bivalves, some limitations in monitoring and the subsequent data processing remain. Therefore, it is urgent to improve the measurement of the physiological activities of filter-feeding bivalves, including the accuracy of data collection and the rigorousness of data processing, to ensure the accuracy of the experimental results. Mudflats are located in the interaction zone between the land and sea and are important areas for the habitat, growth, and reproduction of several macrobenthic organisms. As the dominant species of macrobenthic communities, mudflat-buried shellfish play a crucial role in the material and energy flows of a mudflat ecosystem. However, recently, with the expansion of shellfish aquaculture, the mudflat environment has been deteriorating accompanied by a series of ecological problems, such as high mortality and slow growth rates and alteration in the structure of phytoplankton community, which has led to significant losses to the shellfish aquaculture industry. Therefore, the ability of the ecosystem to support shellfish production must be evaluated, and its carrying capacity must be estimated. Generally, numerical methods for estimating the carrying capacity of shellfish based on food limiting indicators include physical-biological ecosystem modelling, trophodynamic modeling, and energy balance modeling. Current methodologies for estimating shellfish carrying capacity are divided into two main categories: dynamic and static modellings. Compared with the dynamic estimation model, static estimation methods are based on the environment of the target area and the key physiological parameters of shellfish and have been widely applied in some aquaculture areas such as Sanggou Bay, Jiaozhou Bay, and Zhangzidao in China. Here, to explore the energy budget and carrying capacity of the surf clam, Mactra veneriformis, and the estuarine clam, Potamocorbula laevis, in Geligang, Liaodong Bay, a portable particle counter and a continuous oxygen monitoring system were used in combination with flow-through chambers to detect the feeding and metabolic parameters of M. veneriformis and P. laevis. Furthermore, the carrying capacity of two mudflat-buried bivalves in Liaodong Bay was estimated based on the organic carbon supply-demand balance model. The results indicated that 1) the clearance rates of M. veneriformis and P. laevis were (4.87±0.85) L/(h·g) and (6.46±2.25) L/(h·g), respectively, and the oxygen consumption rates were (0.94±0.45) mg/(h·g) and (0.22±0.14) mg/(h·g), respectively. The energy absorption of M. veneriformis and P. laevis ranged from 748.97 to 1 333.52 J/(h·g), and 931.55 to 1 647.08 J/(h·g), respectively. 2) Using organic carbon supply-demand balance model combined with the primary productivity and shellfish clearance rate, we found that the carrying capacity of M. veneriformis in Geligang, Liaodong Bay, was 57, 47, and 34 ind./m2 for age-1 (total wet weight 6.7 g), age-2 (total wet weight 9.3 g) and age-3 (total wet weight 14.6 g), respectively; and the carrying capacity of P. laevis was 346, 143, and 99 ind./m2 for age-1 (total wet weight 0.14 g), age-2 (total wet weight 0.69 g), and age-3 (total wet weight 1.25 g), respectively. These results provide basic data for the rational exploitation and utilization of shellfish resources and the conservation of biodiversity in a mudflat ecosystem.
附件
查看全文   查看/发表评论  下载PDF阅读器
关闭