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| 基于灰色–马尔科夫模型评估石雀滩海洋牧场岩礁鱼类碳储量 |
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李梦迪1,2, 李娇2, 薛月光3, 关长涛2, 公丕海2, 段勇杰1,2, 程浩1,2
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1.浙江海洋大学水产学院 浙江 舟山 316022;2.中国水产科学研究院黄海水产研究所
农业农村部海洋渔业与可持续发展重点实验室 碳汇渔业实验室 山东 青岛 266071;3.青岛市黄岛区薛家岛农业服务中心 山东 青岛 26653
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| 摘要: |
| 本研究以石雀滩海洋牧场许氏平鲉(Sebastes schlegelii)、大泷六线鱼(Hexagrammos otakii)、褐菖鲉(Sebasticus marmoratus)、铠平鲉(Sebastes hubbsi)、厚头平鲉(Sebastes pachycephalus)等岩礁鱼类为研究对象，基于2017—2020年地笼网采捕的渔获量数据，采用元素分析法和灰色−马尔科夫模型，统计并预测了岩礁鱼类现存生物量的碳储量(以下简称岩礁鱼类碳储量)。结果显示，岩礁鱼类干样碳含量分布范围为42.95%~50.19%，平均值为(46.11±2.34)%；鲜样碳含量分布范围为11.05%~13.25%，平均值为12.30%。2017年春季、2018年冬季、2019年春季和2020年冬季鱼礁区岩礁鱼类碳储量分别为293.46、104.49、119.40和48.48 t，呈波动式下降趋势；对照区分别为21.64、59.07、6.73和0 t，呈先上升后下降的趋势。灰色−马尔科夫模型验证数据平均相对误差为8%，较GM(1,1)模型预测精度提升了12%。经预测，鱼礁区岩礁鱼类碳储量呈下降趋势，2021年春季、2022年冬季、2023年春季和2024年冬季分别为64.84 、49.84、25.28和19.43 t。研究结果可为评估岩礁鱼类碳汇潜力提供依据，为建立渔业碳汇基础上的海洋牧场岩礁鱼类资源开发策略提供科学参考。 |
| 关键词: 海洋牧场 岩礁鱼类 碳储量 GM(1,1)模型 灰色−马尔科夫模型 |
| DOI：10.19663/j.issn2095-9869.20220718001 |
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| Assessment of carbon storage of reef fish in Shique Beach marine ranching based on Grey-Markov model |
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LI Mengdi1,2, LI Jiao2, XUE Yueguang3, GUAN Changtao2, GONG Pihai2, DUAN Yongjie1,2, CHENG Hao1,2
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1.School of Fishery, Zhejiang Ocean University, Zhoushan 316022, China;2.Yellow Sea Fisheries Research Institute,
Chinese Academy of Fishery Sciences, Key Laboratory of Marine Fisheries and Sustainable Development,
Ministry of Agriculture and Rural Affairs, Carbon-Sink Fisheries Laboratory, Qingdao 266071, China;3.Agricultural Service Center of Xuejiadao, Qingdao 266530, China
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| Abstract: |
| At present, the world is still experiencing a climate warming trend, which has severe implications for Earth’s sustainable development. Increasing carbon sinks mitigates climate change and improves national and social development through carbon trade. As the largest carbon pool on the planet, the ocean serves as a major carbon sink. The fishery carbon sink is an important part of the ocean carbon sink, which can increase the capacity of aquatic fishery ecosystems to absorb atmospheric CO2. Marine ranching is a typical example of a carbon sink fishery and an effective model for ensuring the sustainability of the carbon sink effect of aquatic fishery ecosystems. Despite the fact that marine ranching plays an important role in enhancing the carbon capacity of fishery carbon sinks, there have been few studies on marine ranching carbon storage. Reef fish species are the target population for marine ranching conservation and enhancement and are the most typical biological community of an artificial reef ecosystem, with substantial ecological and economic benefits. Reef fish species have an important influence on the carbon cycling, deposition, and removal processes in the ocean. It is one of the key carbon storage components of the marine ranching carbon sink. However, there are currently only a few studies on the carbon storage capacity of reef fish. Therefore, estimating and predicting the carbon storage of reef fish are useful for assessing the carbon sink potential and formulating a stock enhancement strategy for reef fish based on the carbon sink target. Based on this, we conducted research on five species of reef fish. On the one hand, we determined the carbon content of reef fish and used the standing biomass of reef fish harvested by cage nets from Shique Beach marine ranching in April 2017, January 2018, May 2019, and December 2020 to estimate the carbon capacity of reef fish in the artificial reef area and contrast areas in spring 2017, winter 2018, spring 2019, and winter 2020. On the other hand, we used the Grey-Markov model, a prediction model that we initially employed in a fishery study, to predict the carbon potential of reef fish in the artificial reef area in spring 2021, winter 2022, spring 2023, and winter 2024. The results showed that the mean carbon contents of dry reef fish samples were 42.95%~50.19% and that the mean carbon contents of fresh reef fish samples were 11.05%~13.25%. The standing biomass carbon storage of reef fish decreased on a regular basis in reef areas, whereas it fluctuated in contrast areas. The standing biomass carbon storage values of reef fish in the reef area in spring 2017, winter 2018, spring 2019, and winter 2020 were 293.46 t, 104.49 t, 119.40 t, and 48.48 t, respectively. This equates to approximately 0.73 × 104~4.40 × 104 USD carbon sink economic value. The standing biomass carbon storage values of reef fish in contrast areas in spring 2017, winter 2018, spring 2019, and winter 2020 were 21.64 t, 59.07 t, 6.73 t, and 0 t, respectively. Reef fish in reef areas had much higher standing biomass carbon storage values than those in contrast areas. The average relative error of the validation data of the Grey-Markov model was 8%, which was 12% better than the prediction accuracy of the GM(1,1) model; therefore, we were able to fully demonstrate the superiority of the Grey-Markov model for accurate short-term prediction of the carbon storage of reef fish. The standing biomass carbon storage values of reef fish in reef areas in spring 2021, winter 2022, spring 2023, and winter 2024 were 64.84 t, 49.84 t, 25.28 t, and 19.43 t, showing a decreasing trend. In summary, reef fish species have a strong carbon storage capacity and a high ecological value, which give them an important role in fishery carbon sinks. However, the carbon storage capacity of reef fish is expected to decline in the future, which may be related to their overexploitation. Reef fish species are the primary targets of traditional fisheries. Therefore, we can take the following measures: First, we should consider the carbon storage effect of reef fish; Second, marine ranching operators can strengthen their investment in the construction of artificial reef areas and conduct active stock enhancement of reef fish, which can increase reef fish resources and subsequently reef fish carbon storage. Third, we can strengthen the environmental protection and management of marine ranching. The findings of this study not only provide a basis for assessing the carbon storage potential of reef fish but also serve as a scientific reference for establishing a strategy to develop reef fish resources in marine ranching based on fishery carbon sinks. |
| Key words: Marine ranching Reef fish Carbon storage GM(1,1) model Grey-Markov model |
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