Institutional Repository of Key Laboratory of Marine Ecology & Environmental Sciences, CAS
基于广义相加模型的黄东海沙海蜇生物量年际变化初步研究 | |
郭东杰 | |
学位类型 | 硕士 |
导师 | 张芳 |
2020-05-15 | |
学位授予单位 | 中国科学院大学 |
学位授予地点 | 中国科学院海洋研究所 |
关键词 | 水母暴发 大型水母 长期变化 广义相加(混合)模型 无性繁殖 |
摘要 | 上个世纪90年度末起,我国渤海、黄海及东海北部海域频繁出现大型水母沙海蜇暴发现象,严重影响渔业生产和沿岸工业设施的运行,威胁整个东亚海域的生态系统健康发展和生态安全。 本文基于黄海及东海北部2009-2018年8个航次的沙海蜇野外调查数据,总结了近年来我国近海沙海蜇暴发的时空分布特征以及生物量的年际变化;分析了2009-2018年调查海区沙海蜇平均生物量与海水表层不同温度持续时间的关系;构建了沙海蜇生物量与温度、盐度以及太平洋年代际涛动指数等环境因子之间的广义相加混合模型;基于模型初步分析了8月份温度、盐度和沙海蜇生物量分布之间的响应关系,初步尝试对未来增加0.5°C (10年) 和2°C(100年)的情况下,黄东海沙海蜇夏季种群分布情况的情景预测。本文为进一步分析黄东海沙海蜇的年际变化、暴发机理及数量预测提供了理论基础。具体研究结果包括: 基于黄海及东海北部2009-2018年夏季8个航次的沙海蜇野外调查数据,以沙海蜇种群特征之一的生物量作为响应变量,以相应的环境因子温度、盐度以及太平洋年代际涛动指数等作为解释变量,构建了模拟黄东海沙海蜇的种群特征对环境因子的响应动态的广义相加混合模型(Generalized Additive Mixed Models, GAMMs)。本模型将受陆源影响较大的近岸浅水区域与黄海冷水团控制的水动力学特征相对稳定的深水区域区分开来,构建了对实测数据描述能力更强的区域模型。浅水区与深水区的最优模型分别可解释方差61.1%、49.2%的变化,对验证数据集的拟合度分别为46.2%、58.8%,拟合值与实测值之间具有较好的线性关系。 基于构建的区域模型,统计分析结果表明,浅水区与深水区夏季8月份沙海蜇的生物量都受到表层温度与表层盐度的交互作用、底层盐度与底层温度的交互作用以及太平洋年代际涛动指数的影响。表层温度较高时,沙海蜇种群生物量维持在较高的水平。南黄海近岸海域沙海蜇分布与海水底层21℃等温线基本吻合。由于长江口外海海域较高的底层温度对沙海蜇生物量的抑制作用明显,沙海蜇生物量水平显示出较低水平。高温对沙海蜇的这种抑制作用受到盐度的显著影响,受高温高盐的黑潮分支水影响的东海北部海域,部分站位沙海蜇生物量水平较高。底层盐度很可能是影响低温海域沙海蜇生物量变化的主要影响因子。基于本模型,沙海蜇夏季对温度的响应规律以及未来全球海水温度的变化趋势,尝试对我国近海沙海蜇夏季(8月份)种群的分布情况进行预测,初步结果显示随着未来海水温度的上升,沙海蜇分布中心向北移动。 以黄东海沙海蜇发源地之一的长江口附近海域(122.00-123.00°E,32.00-33.00°N)作为目标区域,分析了2009-2019年间沙海蜇暴发年份和非暴发年份调查海区的平均生物量与海水表层温度以及不同温度持续时间的关系。结果发现,对于沙海蜇暴发程度较高的2009年、2012年和2013年,前一年秋季18-10℃持续时间约为45天,而在沙海蜇生物量较低的2018年和2019年,前一年秋季18-10℃持续时间平均为60天。沙海蜇暴发年份前一年冬季低温(T<10℃)持续时间为92-104天,显著高于非暴发年份(71-91天)。此外,暴发程度较高的2012年,前一年夏季表层温度18-25℃持续时间长达148天,显著高于其他年份。以上结果支持和证实了实验室内控制实验得出的一年四季的温度分布格局对沙海蛰生物量的影响的假设:秋季18-10℃持续时间短(不利于水螅体秋季横裂生殖)、冬季低温持续时间长有利于春季水螅体的横裂生殖和夏季18-25℃持续时间长有利于足囊繁殖产生更多的水螅体,从而有利于来年夏季沙海蜇暴发的结论。同时,广义相加模型(GAMs)结果显示,与其他季节相比,冬季低温持续时间的长短显著影响来年夏季沙海蜇的平均生物量水平,能够解释其96.6%的变化。 2019年5月,对我国黄海以及东海北部海域进行了全面系统的大型水母调查,结果分析了大型水母的种类组成、伞径大小和生物量以及与温度、盐度的关系。其中就沙海蜇来说,其生物量最高,集中分布在调查海域南部,各海域伞径差异显著,在黄东海交界海域采集到幼水母体(<10cm),生物量高值区出现在东海北部离岸海域,可达6422.16 kg/km2;与2015年同期相比,调查海域南部沙海蜇的丰度和生物量水平明显增加。本此调查详细描述了沙海蜇水母体起始阶段的种群特征,为分析本海域沙海蜇年际变化规律提供了数据基础。 |
其他摘要 | Since the end of 1990s, the population explosion of giant jellyfish have frequently appeared in the Yellow Sea and the northern East China Sea, which negatively affected on the fishery and operation of coastal industrial facilities, threatened the ecosystem healthy and ecological security in East Asia waters. This paper summarized the spatial and temporal distribution characteristics and interannual changes in biomass of jellyfish Nemopilema nomurai based on the field surveys data of 8 cruises from 2009 to 2018 in the Yellow Sea (YS) and northern East China Sea (ECS). The relationship between the average biomass of N.nomurai in study area and the duration of different surface temperature stages in targeted area from 2009-2019 was analyzed. A Generalized Additive Mixed Model (GAMM) was constructed applied to simulate the response of N.nomurai biomass to environmental factors such as temperature, salinity, Pacific Decadal Oscillation index and so on. The responsible relationship between temperature, salinity and biomass in August was preliminarily analyzed based on GAMMs model, and a preliminarily attempt was made to predict distribution of N.nomurai in the future scenario when temperature increases by 0.5℃(10 yrs)or 2℃ (100 yrs). This study provided a theoretical basis for further analysis of N.nomurai interannual changes, bloom mechanisms and quantitative prediction of N.nomurai population in YS and ECS. Specific results include: Based on the field survey data of 8 cruises from 2009 to 2018 in the YS and northern ECS, we constructed a Generalized Additive Mixed Model to fit the responsible relationship between N.nomurai characteristics and environmental factors. The biomass was taken as response variables, and the corresponding environmental factors were taken as explanatory variables. The regional model could better describe variations of observed data by distinguishing the shallow area greatly affected by river runoff from the deep area controlled by relatively stable Yellow Sea Cold Bottom Water (YSCBW). The optimal models could explain the variance of 61.1% and 49.2% in the deep area and shallow area, respectively. There was a linear relationship between the fitted values and observed values of validate datasets, and the fitting degree was 46.2% and 58.8%, respectively. The results of statistical analysis showed that the N. nomurai biomass in study area was significantly affected by the interaction between sea surface temperature (SST) and sea surface salinity (SSS), the interaction between sea bottom temperature (SBT) and sea bottom salinity (SBS), and the Pacific Decadal Oscillation (PDO) index. The biomass maintained at a high level when SST was relatively high. The distribution of N.nomurai population in the south of coastal YS basically coincided with the 21℃ isotherm. Biomass of N.nomurai is lower in Changjiang estuary area, because the higher bottom temperature significantly inhabited the distribution of N.nomurai population. This inhibitory effect was significantly influenced by salinity. Under the influence of the branches of Kuroshio Water, the N.nomurai biomass was higher in some stations in the northern ECS. The bottom salinity was likely to be the main factor that affected N.nomurai population in cold water. Based on the response of N.nomurai to temperature in GAMMs and the trend of global ocean temperature in future scenario, the distribution pattern of the N. nomurai in the YS and the northern ECS was predicted. With the increase of temperature, the distribution of N.nomurai population would possibly move northward. The relationship between the mean biomass of N.nomurai in the study area and the durations of different temperature from 2009 to 2019 was analyzed. The Yangtze estuary (122.00-123.00°E, 32.00-33.00°N) was considered as the study area, which was one of the breeding place of N.nomurai .The results showed that in the bloom year such as 2009, 2012 and 2013, the durations of lower temperature (T<10℃) lasted about 92-104 days, these durations were significantly longer than that in non-bloom years, which lasted about 71 to 91 days. In addition, the surface temperature lasted 148 days at 18-25℃ in previous summer 2012 with a higher biomass of N.nomurai, this was significantly longer than other years. The results shown above supported and confirmed the hypothesis that temperature distribution pattern throughout the year affected the N.nomurai biomass in laboratory experiments: the shorter duration of 18-10℃ in previous autumn and longer duration of low temperature in previous winter were conducive to strobilation of N.nomurai polyp in spring and longer duration of 18 to 25℃ in previous summer was beneficial to podocyst reproduction, which could accelerate to outbreak in summer. At the same time, the GAMMs results showed that compared to other seasons, the duration of low temperature in previous winter significantly affected the biomass in coming summer compared with others seasons, which could explained 96.6% of the variations. In May 2019, a comprehensive and systematic survey of giant jellyfish was conducted in the YS and the northern ECS. The species composition, bell diameter, biomass and relationship with both temperature and salinity were analyzed. N.nomurai with the highest biomass mainly distributed in the southern part of study area. The bell diameter had a significant variation in different study area. The juvenile jellyfish (<10cm) was collected in the border of the YS and the ECS. The biomass was highest in northern ECS, which could reach 6422.16kg/km2. Compared with same period in 2015, the abundance and biomass increased significantly in the southern part of study area. This research described in detail the population characteristics of N.nomurai in initial stage, and provided a data basis for the analysis of interannual variation in this area. |
语种 | 中文 |
文献类型 | 学位论文 |
条目标识符 | http://ir.qdio.ac.cn/handle/337002/164728 |
专题 | 海洋生态与环境科学重点实验室 |
推荐引用方式 GB/T 7714 | 郭东杰. 基于广义相加模型的黄东海沙海蜇生物量年际变化初步研究[D]. 中国科学院海洋研究所. 中国科学院大学,2020. |
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