渔业科学进展  2024, Vol. 45 Issue (2): 28-38  DOI: 10.19663/j.issn2095-9869.20230719001
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引用本文 

刘倩, 刘永, 张林宝, 陈海刚, 张喆, 田斐, 王学锋. 基于综合生物标志物响应法的渔港重金属污染风险评价[J]. 渔业科学进展, 2024, 45(2): 28-38. DOI: 10.19663/j.issn2095-9869.20230719001.
LIU Qian, LIU Yong, ZHANG Linbao, CHEN Haigang, ZHANG Zhe, TIAN Fei, WANG Xuefeng. Risk Assessment of Heavy Metals Pollution in Fishing Ports Using an Integrated Biomarker Response Approach[J]. Progress in Fishery Sciences, 2024, 45(2): 28-38. DOI: 10.19663/j.issn2095-9869.20230719001.

基金项目

广东省农业科研和农业技术推广项目(2021-440000-26080100-8990)、中国水产科学研究院南海水产研究所中央级公益性科研院所基本科研业务费专项资金(2021SD17)、农业农村部南海渔业资源开发利用重点实验室开放基金(FREU2020-01)和广东省科技计划(2019B121201001)共同资助

作者简介

刘倩,E-mail: 18212078794@163.com

通讯作者

张林宝,副研究员,E-mail: zhanglinbao1984@163.com

文章历史

收稿日期:2023-07-19
收修改稿日期:2023-08-28
基于综合生物标志物响应法的渔港重金属污染风险评价
刘倩 1,2, 刘永 1, 张林宝 1, 陈海刚 1, 张喆 1, 田斐 1, 王学锋 2     
1. 中国水产科学研究院南海水产研究所 农业农村部南海渔业资源环境科学观测实验站 广东省渔业生态环境重点实验室 广东 广州 510300;
2. 广东海洋大学水产学院 广东 湛江 524088
摘要:渔港是近海污染物的重要汇集地之一,其中重金属污染尤为突出,但往往缺乏充分的环境监测数据和科学研究。本研究采集了广东和广西4个渔港的表层海水和翡翠贻贝(Perna viridis)样品,测定海水和贻贝软组织中的重金属(Cu、Zn、Pb、Cd、As和Cr)含量,同时分析贻贝肝胰腺组织中超氧化物歧化酶(superoxide dismutase, SOD)、谷胱甘肽过氧化物酶(glutathione peroxidase, GPx)、过氧化氢酶(catalase, CAT)活力以及丙二醛(malondialdehyde, MDA)含量等与抗氧化防御系统有关的生物标志物水平,并利用综合生物标志物响应(integrated biomarker response, IBR)指数法对不同渔港重金属污染水平进行综合评价。结果表明,海水和贻贝软组织中重金属含量均为较低水平,海水重金属综合污染指数(PI)由高至低依次为蛇口渔港 > 南澫渔港 > 达濠渔港 > 渔万渔港,处于自然本底状态。贻贝体内重金属综合污染指数(Pin)由高至低依次为渔万渔港 > 蛇口渔港 > 南澫渔港 > 达濠渔港,处于无污染水平。另外,蛇口渔港海水与贻贝组织中Cu浓度在4个渔港中均表现为最高。IBR指数评价结果表现为蛇口渔港 > 渔万渔港 > 达濠渔港 > 南澫渔港,蛇口渔港的IBR值最高,这与海水重金属综合污染指数结果相一致。相关性分析表明,IBR指数与海水和贻贝体内重金属综合污染指数无显著相关性,但与海水和贻贝组织中Cu的浓度具有显著正相关性。综上,蛇口渔港重金属污染风险相对较高,渔港环境中Cu污染可能需要重点关注,IBR指数综合评价与化学分析相结合在渔港环境污染评价方面具有较好的应用价值。
关键词渔港    重金属    翡翠贻贝    生物标志物    IBR指数    
Risk Assessment of Heavy Metals Pollution in Fishing Ports Using an Integrated Biomarker Response Approach
LIU Qian 1,2, LIU Yong 1, ZHANG Linbao 1, CHEN Haigang 1, ZHANG Zhe 1, TIAN Fei 1, WANG Xuefeng 2     
1. South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Scientific Observing and Experimental Station of South China Sea Fishery Resources and Environment, Ministry of Agriculture and Rural Affairs, Key Laboratory of Fishery Ecology and Environment, Guangzhou 510300, China;
2. College of Fisheries, Guangdong Ocean University, Zhanjiang 524088, China
Abstract: Fishing ports play an essential role in fisheries development and supply chains, as all catches are landed through fishing ports to enter the seafood market. Frequent and intensive fishing activities inevitably affect the fishing port ecosystem by discharging sewage and waste oil from sources such as fishing vessels, leaching ship paint, and operating wharves. However, fishing ports are usually located in semi-enclosed seas, leading to the accumulation of land-based pollution in port environments. Fishing ports are known potential sinks for land-sourced pollutants, such as heavy metals, phthalates, polycyclic aromatic hydrocarbons, and petroleum hydrocarbons. Currently, comprehensive research on the distribution and ecological risk of heavy metals in fishing ports is very limited. With no environmental and scientific data available for reference, it is difficult to formulate appropriate pollution control and prevention strategies for fishing ports. Environmental risk assessment in aquatic ecosystems typically uses biomarkers to detect interactions between potential hazards and biological systems. Next to knowing environmental contaminant levels in tissues and the environment, it is important to link to potentially deleterious effects at higher levels of biological organization, such as biochemistry, physiology, and overall health status. Biochemical reactions are frequently used as biomarkers in sentinel model species sampled from reference sites, for monitoring xenobiotic pollution in coastal areas. However, multiple biomarkers were too complex and could not directly reflect the toxic effects of pollutants on organisms, while the integrated biomarker response (IBR) index could overcome this and comprehensively evaluate the aquatic ecosystem health status.The primary purpose of this study was to evaluate the overall pollution level and risks in fishing ports. Samples of green mussels (Perna viridis) and surface water were collected at 12 sampling points in four fishing ports located in Guangdong and Guangxi provinces, China. Six types of heavy metals were measured in the surface water and soft tissues of P. viridis by inductively coupled plasma mass spectrometry. Moreover, biomarkers of the antioxidant defense system, such as superoxide dismutase (SOD), glutathione peroxidase (GPx), catalase (CAT), and malondialdehyde (MDA), were analyzed in the hepatopancreas of P. viridis to calculate the IBR index. The results showed that the range of concentrations of Cu, Zn, Pb, Cd, As, and Cr in seawater was 1.13–2.37, 6.67–33.43, 0.14–0.32, 0.03–0.32, 1.09–1.73, and 0.80–1.20 μg/L, respectively, while in the soft tissues of P. viridis, it was 8.31–11.93, 67.92–103.17, 0.88–3.07, 0.80–2.33, 9.61–12.70, and 2.54–4.75 mg/kg, respectively. The mean concentrations of Cu, Zn, Pb, Cd, As, and Cr in each fishing port were lower than the fourth grade of the National Seawater Quality Standard (GB 3097-1997). The concentrations of heavy metals in the surface water and soft tissues of P. viridis were generally at a low level, the comprehensive pollution indices (PI) of heavy metals in the surface water of all four fishing ports were within the natural background range, and the comprehensive pollution indices (Pin) of heavy metals in the soft tissues of P. viridis were in the no pollution category. The PI of heavy metals in the surface water was Shekou Port > Nanwan Port > Dahao Port > Yuwan Port, while the Pin of heavy metals in the soft tissues of P. viridis was Yuwan Port > Shekou Port > Nanwan Port > Dahao Port. In addition, Cu concentrations in both the surface water and soft tissues of P. viridis from Shekou Port were the highest among those from the four fishing ports. Furthermore, there was no significant difference in MDA content or SOD, CAT, and GPx enzyme activities, in the hepatopancreas of P. viridis from the four fishing ports. The IBR index of P. viridis was 4.50 in Shekou Port, 2.14 in Yuwan Port, 1.91 in Dahao Port, and 1.50 in Nanwan Port, which showed a decreasing trend from Shekou Port > Yuwan Port > Dahao Port > Nanwan Port. The highest IBR index was identified at Shekou Port, which agreed with the profiles of the comprehensive pollution index of seawater. According to the correlation analysis, the IBR index showed no significant correlation with the comprehensive pollution index of seawater and marine mussels. It was noteworthy that the IBR index displayed significant positive correlations with Cu concentrations in seawater and mussel tissues, which indicated that Cu pollution may be an important factor to consider in pollution assessments of fishing ports.Overall, this study provides the first evidence of using the IBR index to evaluate the heavy metal pollution status of fishing ports. The pollution level and potential risk of heavy metals in Shekou Port were higher than those of the other three fishing ports. The IBR index coupled with chemical analysis is useful to assess the environmental pollution status of fishing ports for pollution source control and management policy formulation.
Key words: Fishing port    Heavy metals    Perna viridis    Biomarker    Integrated biomarker response (IBR) index    

近几十年来,由于沿海地区渔业经济活动飞速发展和人口快速增长,近海海域污染日益加重,给海岸带生态环境带来了一定的压力。渔港是海岸带人类活动最为频繁的地段,且多为半封闭式港湾,水动力条件差,自净能力弱,重金属、石油、船舶油漆、垃圾和其他污染物在海水中积累并沉积,导致渔港生态环境恶化(Jahan et al, 2018; 巩慧敏等, 2018)。胡朝晖等(2008)研究发现,渔港沉积物中重金属含量普遍较高,尤其是珠江三角洲地区渔港Cu和Zn污染水平明显高于国内其他的河口、海湾水平。研究发现,蛇口渔港和渔万渔港邻近海域水体中Cu含量均值分别为1.69和1.01 μg/L (付涛等, 2022; 雷学铁等, 2022),南澫渔港附近海域水体中Cu含量相对较低,均值为0.40 μg/L (欧阳贤清等, 2022)。重金属污染具有毒性大、来源广、持久性、降解缓慢、累积快速等特点,已成为全球关注的环境问题(杨文超等, 2020)。水环境中的重金属被水生动物吸收后能够在体内积累,不同程度地影响水生动物的胚胎发育、幼体存活和成体繁殖,从而对水生动物的健康造成较高风险(陈玉翠等, 2016; Jaiswal et al, 2018)。因此,渔港水体作为海岸带水环境的重要组成部分,其重金属污染程度应引起必要的关注和评价。目前,我国对海洋环境中的重金属污染评价以化学监测为主,通过调查海水、沉积物和生物体中的重金属含量,根据相关质量标准进行评价。化学分析方法虽然能够准确测定每一种污染物的含量,但由于污染物之间具有协同或拮抗作用,测定结果往往难以反映其对生物体的真实效应,从而导致评价结果缺乏客观性,远不能满足海洋生态系统管理和海洋环境保护的需求(孟范平等, 2013)。因此,开发新型海洋环境质量评价技术十分必要。

生物标志物对化学污染具有早期预警功能,其在海洋环境污染监测中的作用得到世界各国学者的认可(El-Agri et al, 2022)。然而,由于自然海洋环境污染复杂,导致生物标志物的响应趋势亦复杂多变。为更好地评价海洋环境质量,欧洲地区广泛开展系列生物标志物联合使用法指示海洋环境污染水平(Broeg et al, 2006; Beyer et al, 2017)。其中,综合生物标志物响应指数法能够将多种生物标志物综合起来进行定量分析,反映污染物对生物体影响的程度(徐青霞等, 2023)。Beliaeff等(2002)首次提出综合生物标志物响应(integrated biomarker response, IBR)指数法,对德国波罗的海沿岸各站位贻贝(Mytilus edulis)鳃中乙酰胆碱酯酶(acetylcholine esterase, AChE)、谷胱甘肽硫转移酶(glutathione-S-transferase, GST)与消化腺中过氧化氢酶(catalase, CAT)和GST酶活性进行测定,计算各站位的IBR指数值并进行排序来区分各站位的污染程度。目前,IBR指数已被应用于北部湾(孟范平等, 2013)、莱州湾(曹云浩等, 2023)、胶州湾(Qi et al, 2022)和地中海西北部戛纳湾(Damiens et al, 2007)等海域的污染评估,但国内尚未有将IBR指数法应用于渔港水域污染评价的研究。因此,本研究以渔港中自然生长的双壳贝类翡翠贻贝(Perna viridis)作为指示生物,将IBR指数法引入渔港水域环境质量评价,旨在为海洋管理部门及时掌握渔港重金属污染程度并进行有效控制提供科学依据。

1 材料与方法 1.1 样品采集与贮存

本研究于2020年10月分别在广东达濠渔港和蛇口渔港,广西南澫渔港和渔万渔港采集海水与翡翠贻贝样品,每个渔港港池内均匀设置3个取样点,采样点基本信息见表 1。海水样品的采集和储运按照《海洋监测规范》(GB 17378.3-2007)相关规定操作,用有机玻璃采水器在每个取样点表层(海面下25~50 cm)采集水样1份,取500 mL至采样瓶中,低温冷藏保存,用于海水中重金属含量测定。每个取样点分别取5只翡翠贻贝进行解剖获取肝胰腺组织,速冻于液氮中,用于后续抗氧化指标的测定,剩余软组织样品用于贻贝体内重金属含量的测定。

表 1 各渔港采样点位置 Tab.1 Location of sampling points for each fishing port
1.2 样品测定 1.2.1 重金属含量测定

海水样品使用0.45 μm微孔滤膜过滤后加入硝酸酸化;贻贝软组织样品放入80 ℃电热恒温鼓风干燥箱内烘干至恒质量后称量,加入2 mL硝酸完全消化后定容至20 mL。所有样品预处理后采用电感耦合等离子体质谱仪(7900 ICP- MS, Agilent公司)测定海水和生物体组织中Cu、Zn、Pb、Cd、As和Cr的含量(Yi et al, 2022)。用锗(Ge,72)、铟(In,115)、铋(Bi,209)、锂(Li,7)的混合标准溶液(溶于1% V/V硝酸中)作为在线内标。

1.2.2 生物标志物测定

向贻贝肝胰腺组织中加入9倍体积的生理盐水进行匀浆后,于4 ℃、1 000 r/min离心15 min,取其上清液,保存于–80 ℃,用于总蛋白和丙二醛(malondialdehyde, MDA)含量、超氧化物歧化酶(superoxide dismutase, SOD)、谷胱甘肽过氧化物酶(glutathione peroxidase, GPx)和CAT活性测定。总蛋白和MDA含量以mg/mL与nmol/mg prot表示,SOD、GPx和CAT的测定结果用U/mg prot表示。以上指标均采用南京建成生物工程研究所生产的试剂盒进行测定。

1.3 评价方法 1.3.1 重金属污染状况

(1) 单因子污染指数法

单因子污染指数法(Pi)是利用实测值与标准值对比进行污染评价,公式为(孙铭阳等, 2022):

$ {P_i} = \frac{{{C_i}}}{{{S_i}}} $ (1)

式中,Ci为各渔港海水和翡翠贻贝组织中重金属浓度实测值,海水中Si为《海水水质标准》(GB 3097-1997) 4类海水水质标准重金属浓度的标准值,翡翠贻贝组织中Si为《海洋生物质量》(GB 18421-2001)中第3类重金属浓度的标准值。海水中,Pi < 0.4为自然本底状态,0.4 < Pi≤0.6为清洁状态,0.6 < Pi≤0.8为较清洁状态,0.8 < Pi≤1.0为轻度污染状态,1.0 < Pi≤2.0为污染状态,Pi > 2.0为严重污染状态。生物体中,Pi < 0.2为正常背景值水平,0.2≤Pi < 0.6为轻污染水平,0.6≤Pi < 1.0为中度污染水平,Pi≥1.0为重污染水平。

(2) 综合污染指数法

PI为海水中重金属的综合污染指数,公式如式(1);Pin为内梅罗综合污染指数,是目前国内对生物体内重金属进行综合污染指数计算最常用的方法之一(刘洋等, 2021),公式如式(2):

$ \begin{array}{*{20}{c}} {{P_I} = \frac{1}{n}\mathop \sum \limits_1^n {P_i}} \end{array} $ (2)
$ \begin{array}{*{20}{c}} {{P_{in}} = \sqrt {\frac{{{{({\text{max}}{P_i})}^2} + {{({\text{ave}}{P_i})}^2}}}{2}} } \end{array} $ (3)

式中,maxPi为单因子污染指数的最大值,avePi为各单因子污染指数的平均值。若PI < 0.2,质量状况为优级;0.2 < PI≤0.4,质量状况为优良;0.4 < PI≤0.6,质量状况为良好;0.6 < PI≤0.8,质量状况为一般;0.8 < PI≤ 1.0,质量状况为较差;PI > 1.0,质量状况为很差。Pin≤1为无污染水平,1 < Pin≤2为轻污染水平,2 < Pin≤3为中污染水平,Pin > 3为重污染水平。

1.3.2 IBR指数评价方法

根据Beliaeff等(2002)首次建立的理论,并参照Devin等(2014)Xu等(2023)修正的方法进行计算和评价:

(1) Y = (XXi)/SY为生物标志物的标准化值,X为每种标志物在每个渔港的平均值,Xi为所有渔港该种生物标志物的总平均值,S为总标准差。

(2) S = Z + |Xmin|,S≥0。如果该生物标志物因污染被诱导,则Z=Y,反之则Z = –Y。|Xmin| =每个生物标志物Z值中最小值的绝对值。

(3) 用Si绘制星状图,通过星状图的面积计算IBR,即为相邻生物标志物围成的三角形面积之和。

$ {\text{IBR}} = \mathop \sum \limits_{i = 1}^n \frac{{{S_i} \times {S_i} + 1 \times {\text{sin}}\left({\frac{{2\pi }}{n}} \right)}}{2} $ (4)
1.4 数据分析

所有数据使用平均值±标准差(Mean±SD)表示。对于重金属含量和生物标志物水平的数据,采用单因素方差分析(one-way ANOVA)及Tukey´s多重比较检验、Games-Howell检验法进行差异性检验;利用双变量Pearson相关性分析验证各渔港IBR值、重金属含量、综合污染指数之间的相关性,P < 0.05表示显著相关。相关统计分析均在SPSS 19.0软件中完成。

2 结果与讨论 2.1 渔港海水重金属分布特征与评价

港口海域受航运需求增大和港口规模扩大的影响,承载着较大的环境污染压力(曲良等, 2023)。由于未经处理的生活和工业废物排入海洋生态系统,导致渔港水体中重金属含量增加(Islam et al, 2015)。本研究结果显示,各渔港海水中重金属总含量由大到小依次为蛇口渔港 > 南澫渔港 > 达濠渔港 > 渔万渔港,且存在显著差异(P < 0.05)(表 2)。蛇口渔港中Cu和Zn含量分别为(2.37±0.56)和(33.43±13.60) μg/L,均高于其他3个渔港,且Zn含量显著高于达濠渔港和渔万渔港(P < 0.05)。依据《海水水质标准》4类标准计算PiPI,结果显示,各渔港6种重金属综合污染指数大小排序为蛇口渔港(0.026) > 南澫渔港(0.024) > 达濠渔港(0.017) > 渔万渔港(0.012),污染程度均处于自然本底范围(表 3)。与防城港、新村港和铁山港海水中重金属含量相比,蛇口渔港海水中Cu和Zn含量处于较高水平;南澫渔港海水中Cd含量处于较高水平;各渔港Pb含量处于较低水平,其他重金属含量相近(表 4)。

表 2 渔港海水中重金属含量 Tab.2 Heavy metal contents in seawater of fishing ports/(μg/L)
表 3 渔港海水重金属污染指数 Tab.3 Heavy metal pollution index in seawater of fishing ports
表 4 不同渔港海水中重金属含量比较 Tab.4 Comparison of heavy metal concentrations in seawater of different fishing ports/(μg/L)

渔港重金属污染与人类活动、周边地区的工业化和城市化密不可分。蛇口渔港作为国家一级渔港,是珠江三角洲地区最大的海鲜进出口渔港之一,受人类活动和珠三角地区高度的工业化和城市化影响较为严重,因而其重金属污染较严重(胡朝晖等, 2008)。胡朝晖等(2010)对青岛、宁波、舟山、厦门、深圳、珠海、澳门、茂名和三亚共9个渔港表层沉积物中的重金属进行调查发现,深圳蛇口渔港的重金属含量显著高于其他地区的渔港,其中Cu的平均含量高达652 mg/kg,是三亚港的20倍。南澫渔港作为免费的公益渔港是一个典型的滩涂港湾,港内渔民以船为家,船上生活垃圾和岸上生活垃圾直排入海,导致渔港水质污染。达濠渔港属港湾渔港,位于粤东的汕头达濠区。渔万渔港作为防城港的主港区,以大宗散货运输和集装箱远洋干线运输为重点。相较于珠江三角洲地区,粤东与防城港地区渔业经济发展相对落后,因而其水体中重金属含量处于较低水平。

2.2 翡翠贻贝软组织中重金属水平与评价

贝类在海洋中分布广、适应性强,且生长位置相对固定,对重金属污染物富集能力较强(许道艳等, 2021)。本研究各渔港翡翠贻贝软组织中6种重金属均有检出,重金属总含量由高到低排序依次为渔万渔港 > 南澫渔港 > 蛇口渔港 > 达濠渔港,且在各渔港间存在显著差异(P < 0.05)。蛇口渔港贻贝组织中Cu含量为(11.93±0.93) mg/kg,显著高于其他渔港(P < 0.05),Zn、As、Cr、Pb以及Cd含量则在渔万渔港中最高,且Zn、As、Pb和Cd含量显著高于其他3个渔港(P < 0.05)(表 5)。Cu污染主要来源于工业废水和船舶防污漆。蛇口渔港作为珠三角地区最大的海鲜进出口港,来往渔船较多。陈敏嫣等(2020)认为,海水中Cu含量可能随着渔船防污漆脱落而增加,从而导致紫贻贝(Mytilus galloprovincialis)软组织中Cu含量相应增加。孙铭阳等(2022)研究发现,Zn污染的主要来源为农业废水、养殖污水和工业污染,As污染主要来自沿岸工业废水,Pb污染主要来自河流、排污口、燃料燃烧和大气沉降。由此可推断,渔万渔港贻贝体内重金属污染可能是由于周边地区工业和农业发展导致。

表 5 翡翠贻贝软组织中重金属含量 Tab.5 Heavy metal contents in P. viridis/(mg/kg)

研究表明,贝类体内重金属含量会受到水体中重金属含量水平的影响,贝类体内重金属含量与水体中的重金属含量呈正相关关系(章誉兴等, 2018)。孙珊等(2017)对山东省近岸养殖区海水、沉积物和贝类中的重金属含量进行分析,发现As和Cu的含量在海水中较高,在贝类体内含量也较高;Cr和Pb的含量在沉积物中较高,但在贝类体内含量相对较低,表明海水中重金属含量对贝类的影响更大。本研究也发现,蛇口渔港海水中Cu含量高于其他3个渔港,这与蛇口渔港贻贝组织中Cu含量显著高于其他渔港具有一致性。其他3个渔港贻贝体内重金属富集水平与海水中重金属含量排序不一致,这说明贝类对重金属的富集不完全取决于海水中的重金属含量,重金属的理化性质、沉积物中的含量、水体环境因素(如温度、盐度、光照等)以及生物体的生理状况和摄食情况等均会影响重金属在生物体中的累积(徐阁等, 2023)。

各渔港翡翠贻贝软组织中重金属含量单因子污染指数及综合污染评价结果见表 6。根据Pin值大小,不同渔港贻贝软组织中重金属污染程度依次为渔万渔港 > 蛇口渔港 > 南澫渔港 > 达濠渔港,综合污染程度均处于无污染水平。Pi均值为As > Zn > Cr > Pb > Cd > Cu。其中,渔万渔港贻贝中Zn、Pb、Cd和As的Pi值最高,而Cu和Cr的Pi最高值均出现在蛇口渔港。各渔港贻贝软组织中As单因子污染指数均大于1,为重污染状态。这可能与贝类对海水中As高达1.2× 103~1.9×103的累积系数有关,当累积系数超过1 000时,被认为可能具有潜在的生物累积危害(许道艳等, 2021)。因而,As可能是本研究涉及的4个渔港中贻贝体内的主要污染因子,需引起重视。

表 6 翡翠贻贝软组织中重金属污染指数 Tab.6 Heavy metal pollution index in P. viridis
2.3 翡翠贻贝肝胰腺生物标志物水平

当环境中的重金属浓度在生物体中蓄积超出一定阈值后,会诱导机体产生大量的活性氧自由基(reactive oxygen species, ROS),进而引起细胞氧化损伤效应(Boudjema et al, 2023)。为维持自由基和氧化还原作用之间的动态平衡,生物体自身形成了一套抗氧化防御系统来避免机体受到自由基的损伤(于振兴等, 2022; Cunha et al, 2023)。其中,SOD是抵抗ROS的第一道防线,当生物体受到外界胁迫时可将超氧自由基发生歧化反应生成H2O2和O2,再由GPx和CAT等酶进一步催化H2O2为H2O和O2,从而起到缓解氧化压力的作用(Ji et al, 2010)。当重金属污染物对机体的氧化损伤已经超过了细胞本身的调节能力,大量的活性氧产物在体内积累则会削弱SOD、GPx和CAT等抗氧化酶的活力(王进华等, 2022)。本研究发现,蛇口渔港翡翠贻贝肝胰腺组织中SOD、GPx和CAT活性在4个渔港中均表现为最低,分别为(230.86± 37.67)、(122.16±27.45)和(0.66±0.56) U/mg prot,其中CAT活性显著低于渔万渔港(P < 0.05)(图 1),这可能是因为蛇口渔港中重金属浓度已超过贻贝细胞的承受能力,对翡翠贻贝造成了氧化损伤。Ji等(2020)研究发现,重污染区中华圆田螺(Cipangopaludina cahayensis)组织中的抗氧化酶活性被抑制,相同的研究在鲫鱼(Carassius auratus) (Ji et al, 2010)、菲律宾蛤仔(Ruditapes philippinarum) (Ji et al, 2019)以及蜗牛(Achatina achatina) (Abarikwu et al, 2017)中也有发现。

图 1 不同渔港翡翠贻贝中生物标志物的水平 Fig.1 Content of biomarkers in P. viridis from different fishing ports 不同字母代表组间差异显著,Tukey´s检验,P < 0.05 Different letters represent significant differences among fishing ports, Tukey´s test, P < 0.05

MDA是脂质过氧化反应的重要产物,其含量多少可以直接反映脂质过氧化程度(Xia et al, 2017; 张林宝等, 2020)。Taylor等(2012)研究发现,MDA含量升高往往表明机体抗氧化防御系统的自我修复能力不足以消除外界污染给生物体造成的氧化损伤。本研究结果显示,蛇口渔港贻贝肝胰腺中MDA含量最高,南澫渔港和达濠渔港次之,渔万渔港最低,这与各渔港海水中重金属总含量的排序一致。蛇口渔港海水中重金属总浓度最高,渔港中翡翠贻贝受重金属污染胁迫,其体内ROS含量可能相对高于其他3个渔港,因此,其MDA含量也随之升高(Lin et al, 2018)。相同的结果在斑尾刺虾虎鱼(Acanthogobius ommaturus)中也有发现,重金属浓度高的站位其肝脏中的MDA含量也高(Liu et al, 2023)。

2.4 IBR指数综合评价

不同生物大分子标志物对污染压力的响应存在差异和复杂性,IBR指数法可以将多个生物标志物整合为一个数值,从生物机体响应的角度整体评估其生活环境的污染程度。IBR数值越高,表明生物受环境污染物影响的程度越高(Beliaeff et al, 2002)。Meng等(2013)以文蛤(Meretrix meretrix)鳃组织内综合生物标志物对北部湾沿岸沉积物污染程度进行评估,结果发现,IBR值在污染程度高的站位最高,在污染程度低的站位最低,表明IBR指数能够明显区分不同采样点的污染程度。曹云浩等(2023)研究也发现,基于四角蛤蜊(Mactra veneriformi)的IBR评价结果与沉积物化学检测结果具有一致性。本研究根据各渔港中翡翠贻贝肝胰腺组织内几种抗氧化酶活性及MDA含量计算得出各渔港翡翠贻贝综合生物标志物响应指数的值(图 2)。4个渔港的IBR值由高到低的排序依次为蛇口渔港(4.50) > 渔万渔港(2.14) > 达濠渔港(1.91) > 南澫渔港(1.50),表明蛇口渔港中翡翠贻贝受重金属污染影响最大,渔万和达濠渔港次之,南澫渔港最轻。蛇口渔港翡翠贻贝IBR指数评价结果与海水中重金属综合污染程度一致,但其他渔港IBR数值与重金属含量不具有一致性。Gao等(2020)以鲫鱼作为研究对象,采用IBR指数法结合化学监测方法对滇池不同区域重金属生态风险进行评价,发现大部分站位污染程度与IBR评价结果一致,个别站位与IBR评价结果不相符,且IBR值与鲫鱼体内重金属含量无相关性。Li等(2022)以菲律宾蛤仔作为指示生物,对山东半岛多环芳烃污染进行监测,也发现有部分站位化学监测结果与IBR评价结果不一致。产生以上结果的原因一方面可能是环境中自然生长的指示生物长时间暴露于污染环境中,其体内抗氧化系统对重金属污染物产生了一定的适应性,另一方面可能是环境中重金属的污染程度不足以使抗氧化酶系统产生响应(Tsangaris et al, 2011; Cravo et al, 2012)。将渔港海水和贻贝软组织中重金属含量及综合污染指数与IBR值进行相关性分析,结果显示,IBR值与海水和贻贝软组织中Cu的含量呈显著正相关性(P < 0.05) (表 7),与其他重金属含量和综合污染指数无相关性。Pytharopoulou等(2008)将紫贻贝分别暴露于重金属污染程度不同的2个区域,贻贝IBR值与消化腺中Cu的浓度也具有一致性。

图 2 不同渔港综合生物标志物响应指数 Fig.2 Integrated biomarker response index for different fishing ports A:IBR星状图;B:IBR值 A: The star plot of IBR; B: IBR value
表 7 IBR值与重金属含量的相关性分析 Tab.7 Correlation of IBR values with heavy metal contents
3 结论

综上所述,本研究通过化学分析测定渔港海水和贻贝组织内重金属含量,并对渔港重金属污染进行评价,发现4个渔港海水重金属污染程度均处于自然本底范围,其中,蛇口渔港海水重金属综合污染指数高于其他3个渔港。贻贝软组织中重金属综合污染程度评价表明,4个渔港贻贝组织均属于无污染水平,其中As单因子污染指数评价为重污染状态。另外,蛇口渔港海水和贻贝组织中Cu含量均高于其他3个渔港。4个渔港翡翠贻贝肝胰腺组织中MDA含量,SOD、CAT和GPx酶活性基本无显著性差异,IBR指数法综合评价分析显示,蛇口渔港IBR值最高,与海水重金属综合污染程度评价结果相一致。以上结论表明,IBR指数法能够从生物体响应角度评估渔港重金属污染状况,IBR指数法与化学分析相结合有助于全面评价渔港环境污染状况,为渔港环境管理和重金属污染控制提供有价值的数据。

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