摘要
根据2002、2004、2008、2010、2012和2016年白令海陆坡海域底层拖网的资源调查数据,探讨了白令海大陆坡头足类优势种及其空间分布与环境因子的关系,分析了白令海陆坡头足类的群落组成,量化了其资源丰度(以CPUE表征)在经纬度上的分布情况,并通过生态学方法对头足类群落多样性进行了研究。结果显示,调查共鉴定头足类20种,分别隶属于3目9 科15属。在纬度上,CPUE最高值(0.78 kg/k
白令海是位于亚北极的半封闭海,北以白令海峡与北冰洋相通,南接阿留申群岛,西接俄罗斯的西伯利亚,东邻美国的阿拉斯加。白令海水域可分为深浅两部分,东北部是陆架区,西南部是深海盆。白令海陆坡是大陆架外缘与深海盆地之间的过渡地带,一头担着大陆型地壳,一头担着大洋型地壳,地理位置优越,物产丰盛,是许多海洋生物喜欢居住的“鱼米之乡
头足类是白令海食物链中的“关键种”,主要捕食甲壳类动物、鱼类和其他头足
白令海陆坡海域底层拖网资源调查数据来源于阿拉斯加渔业科学中心网站(https://www.fisheries.noaa.gov/alaska/commercial-fishing/alaska-groundfish-bottom-trawlsurvey-data)。时间范围为2002、2004、2008、2010、2012和2016年夏季(6、7月),包含调查时间、调查站点的经纬度、调查站点对应的底层深度、表层水温和底层水温、渔获物种的种名及其对应的单位捕捞努力量渔获量(Catch per unit effort,CPUE,单位kg/k
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图1 调查站点的空间分布图
Fig.1 Spatial distribution of the sampling stations
对每网调查的渔获数据进行分类整理,选取所有头足类进行分类统计。确定其优势种和优势种的空间分布及与环境因子的响应关系,并计算群落多样性指标。
优势度(Z)计
(1) |
(2) |
式中:为物种i的资源丰度;为总丰度;S为样品中物种总数;为物种i在各站位出现的频率。取优势度Z≥0.01的头足类为优势种。
优势种的空间分布:根据计算后的优势度,对各站点优势种CPUE所占比例和分布进行分析,空间分布图采用ArcGIS软件绘制。
优势种资源丰度与环境因子的关系采用GAM模型对优势种的CPUE进行标准化处理,以CPUE作为响应变量,经度、纬度、作业深度、底层水温和表层水温作为其解释变量建立GAM模型,对所有的名义CPUE值加上常数“0.1”后进行对数化处理,防止CPUE为0的情况出
(3) |
式中:为年份的分类变量;为将变量以分类因子纳入模型;为纬度(Latitude,LA);为经度(Longitude,LON);为作业深度(Bottom depth,BOT_DEPTH);为底层水温(Bottom temperature,BOT_TEMP);为表层水温(Surface temperature, SURF_TEMP);s()为连接解释变量的样条平滑函数(Spline smoothing); 为随机残差项。
利用赤池信息准则(Akaike information criterion, AIC)检验加入因子后模型的拟合程度,AIC值越小拟合越好,其次利用GAM模型统计的F值、P值对模型参数进行显著性检
物种多样性指数的计算采用 Shannon-Wiener指数(
(4) |
式中:为物种i的资源丰度与样品总资源丰度的比值;S为样品中物种总数。
均匀度指数采用Pielou指数()计算公
(5) |
物种丰富度指数采用Margalef指数(
(6) |
式中:为采集样品中所有物种的总个体数。
对群落多样性指数进行聚类分析。将计算后的多样性指数标准化,将标准化后的数据利用SPSS对各站点进行聚类分析(Cluster analysis
(7) |
式中:为第i个聚类;为该聚类的均值向量(也称聚类中心);k为该聚类中对象的个数;为聚类中的一个样本点。该式在一定程度上刻画了聚类对象围绕聚类均值向量的紧密程度,值越小则聚类中样本相似度越高。
根据白令海陆坡头足类数据分类统计结果,共鉴定出头足类20 种,隶属于3目9科15属(
目Order | 科Family | 属Genus | 种类Species |
---|---|---|---|
八腕目Octopoda | 幽灵蛸科Vampyroteuthidae | 幽灵蛸属Vampyroteuthis | 幽灵蛸Vampyroteuthis infernalis |
单盘蛸科Bolitaenidae | 乍波蛸属Japetella | 乍波蛸Japetellad iaphana | |
面蛸科Opisthoteuthidae | 面蛸属Opisthoteuthis | 加利福尼亚面蛸Opisthoteuthis californiana | |
蛸科Octopodidae | 肠腕蛸属Enteroctopus | 水蛸Enteroctopus dofleini | |
谷蛸属Graneledone | 北方太平洋谷蛸Graneledone boreopacifica | ||
深海蛸属Benthoctopus | 俄勒冈深海蛸Benthoctopus oregonensis | ||
光滑深海蛸Benthoctopus leioderma | |||
枪形目Teuthoidea | 爪乌贼科Onychoteuthidae | 桑椹乌贼属Moroteuthis | 桑椹乌贼Moroteuthis robusta |
手乌贼科Chiroteuthidae | 手乌贼属Chiroteuthis | 杯状手乌贼Chiroteuthis calyx | |
小头乌贼科Cranchiidae | 盖乌贼属Galiteuthis | 叶状盖乌贼Galiteuthis phyllura | |
孔雀乌贼属Taonius | 孔雀乌贼Taonius pavo | ||
黵乌贼科Gonatidae | 贝乌贼属Berryteuthis | 贝乌贼Berryteuthis magister | |
东黵乌贼属Eogonatus | 东黵乌贼Eogonatus tinro | ||
拟黵乌贼属Gonatopsis | 北方拟黵乌贼Gonatopsis borealis | ||
黵乌贼属Gonatus | 贝氏黵乌贼Gonatus berry | ||
短腕黵乌贼Gonatus middendorffi | |||
火黵乌贼Gonatus pyros | |||
马氏黵乌贼Gonatus madokai | |||
爪黵乌贼Gonatus onyx | |||
乌贼目Sepioidea | 耳乌贼科Sepiolidae | 僧头乌贼属Rossia | 太平洋僧头乌贼Rossia pacifica |
通过计算后的结果发现(
种类 Species | 出现频率 Frequency of occurrence/% | 资源丰度 CPUE | 优势度 Dominance degree |
---|---|---|---|
贝乌贼Berryteuthis magister | 98.18 | 9.719 5 |
5.3×1 |
水蛸Enteroctopus dofleini | 89.09 | 3.661 1 |
1.8×1 |
加利福尼亚面蛸Opisthoteuthis californiana | 78.18 | 1.979 5 |
8.7×1 |
光滑深海蛸Benthoctopus leioderma | 67.27 | 1.036 7 |
3.9×1 |
太平洋僧头乌贼Rossia pacifica | 74.55 | 0.295 3 |
1.2×1 |
北方太平洋谷蛸Graneledone boreopacifica | 20.00 | 0.585 8 |
6.6×1 |
北方拟黵乌贼Gonatopsis borealis | 58.18 | 0.164 5 |
5.4×1 |
俄勒冈深海蛸Benthoctopus oregonensis | 27.27 | 0.205 3 |
3.1×1 |
乍波蛸Japetella diaphana | 27.27 | 0.027 4 |
4.2×1 |
杯状手乌贼Chiroteuthis calyx | 16.36 | 0.014 5 |
1.3×1 |
桑椹乌贼Moroteuthis robusta | 1.82 | 0.113 9 |
1.2×1 |
叶状盖乌贼Galiteuthis phyllura | 16.36 | 0.009 1 |
8.4×1 |
爪黵乌贼Gonatus onyx | 23.64 | 0.006 0 |
8.0×1 |
孔雀乌贼Taonius pavo | 12.73 | 0.011 2 |
8.0×1 |
贝氏黵乌贼Gonatus berry | 10.91 | 0.004 5 |
2.7×1 |
马氏黵乌贼Gonatus madokai | 5.45 | 0.001 3 |
4.1×1 |
东黵乌贼Eogonatus tinro | 7.27 | 0.000 6 |
2.3×1 |
火黵乌贼Gonatus pyros | 5.45 | 0.000 6 |
1.7×1 |
短腕黵乌贼Gonatus middendorffi | 1.82 | 0.001 0 |
9.9×1 |
幽灵蛸Vampyroteuthis infernalis | 3.64 | 0.000 4 |
8.2×1 |
通过对优势种的空间分布分析发现(
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图2 白令海陆坡海域头足类优势种分布
Fig.2 Distribution of dominant cephalopod species in the Bering Sea slope
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图3 白令海陆坡海域头足类在经纬度上的分布
Fig.3 Distribution of cephalopods in latitude and longitude in the Bering Sea slope
为探究优势种资源丰度与环境因子的关系,依次将各个解释变量逐一加入了GAM 模型,根据GAM 模型拟合结果(
优势种 Dominant species | 影响因子 Factors | 估计自由度 Estimated degree of freedom | 参考自由度 Referred degree of freedom | F值 F value | P值 P value | 显著性 Significance |
---|---|---|---|---|---|---|
贝乌贼 Berryteuthis magister | LON | 7.715 | 8.450 | 10.698 |
<2×1 | *** |
LA | 6.851 | 7.745 | 10.149 |
<2×1 | *** | |
BOT_DEPTH | 6.684 | 7.611 | 24.596 |
<2×1 | *** | |
BOT_TEMP | 3.444 | 4.271 | 5.480 |
1.83×1 | *** | |
SURF_TEMP | 5.573 | 6.705 | 5.871 |
3.26×1 | *** | |
总偏差解释率Deviance explained = 42.2% | ||||||
水蛸 Enteroctopus dofleini | LON | 1.000 | 1.000 | 11.081 | 0.001 | ** |
LA | 7.580 | 8.266 | 9.257 |
< 2×1 | *** | |
BOT_DEPTH | 1.000 | 1.000 | 53.298 |
< 2×1 | *** | |
BOT_TEMP | 7.016 | 7.650 | 8.189 |
< 2×1 | *** | |
SURF_TEMP | 3.525 | 4.186 | 11.911 |
< 2×1 | *** | |
总偏差解释率Deviance explained = 70.1% | ||||||
加利福尼亚面蛸 Opisthoteuthis californiana | LON | 1.000 | 1.000 | 1.242 | 0.267 | |
LA | 5.089 | 6.034 | 15.559 |
< 2×1 | *** | |
BOT_DEPTH | 1.831 | 2.299 | 13.585 |
4.57×1 | *** | |
BOT_TEMP | 4.081 | 4.936 | 10.798 |
< 2×1 | *** | |
SURF_TEMP | 5.357 | 6.299 | 5.293 |
5.36×1 | *** | |
总偏差解释率Deviance explained = 69.1% | ||||||
光滑深海蛸 Benthoctopus leioderma | LON | 7.262 | 8.166 | 7.299 |
< 2×1 | *** |
LA | 1.915 | 2.343 | 1.544 | 0.286 | ||
BOT_DEPTH | 3.946 | 4.922 | 1.957 | 0.081 | ||
BOT_TEMP | 4.435 | 5.472 | 6.788 |
4.99×1 | *** | |
SURF_TEMP | 7.536 | 8.408 | 7.507 |
< 2×1 | *** | |
总偏差解释率Deviance explained = 46.9% | ||||||
太平洋僧头乌贼 Rossia pacifica | LON | 1.000 | 1.000 | 3.184 | 0.076 | |
LA | 1.000 | 1.000 | 2.130 | 0.147 | ||
BOT_DEPTH | 1.000 | 1.000 | 2.267 | 0.134 | ||
BOT_TEMP | 1.000 | 1.000 | 7.961 | 0.005 | ** | |
SURF_TEMP | 1.000 | 1.000 | 0.001 | 0.977 | ||
总偏差解释率Deviance explained = 18.8% |
注: ***表示极为显著(P<0.001),**表示非常显著(P<0.01)。
Notes: *** means extremely significant(P<0.001), ** means very significant(P<0.01).
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图4 优势种资源丰度与环境因子的GAM 模型拟合结果
Fig.4 GAM simulation results of CPUE and environment factors of dominant species
根据计算结果来看(
站点 Station | 纬度 Latitude(N)/ | 经度 Longitude(W)/ | 香农威纳指数Shannon-Wiener index() | 均匀度指数 Pielou index(') | 丰富度指数 Margalef index() |
---|---|---|---|---|---|
T01 | 54.0 | 168.0 | 1.724 | 0.962 | 1.091 |
T02 | 54.0 | 167.5 | 1.616 | 0.777 | 1.298 |
T03 | 54.0 | 167.0 | 1.442 | 0.656 | 1.305 |
T04 | 54.0 | 166.5 | 1.490 | 0.647 | 1.454 |
T05 | 54.0 | 166.0 | 0.608 | 0.312 | 1.439 |
T06 | 54.5 | 168.0 | 1.447 | 0.658 | 1.305 |
T07 | 54.5 | 167.5 | 1.177 | 0.473 | 1.622 |
T08 | 54.5 | 167.0 | 1.336 | 0.608 | 1.277 |
T09 | 54.5 | 166.5 | 1.841 | 0.946 | 0.963 |
T10 | 54.5 | 166.0 | 1.415 | 0.727 | 0.989 |
T11 | 54.5 | 165.5 | 1.024 | 0.932 | 1.000 |
T12 | 55.0 | 168.5 | 1.309 | 0.672 | 1.004 |
T13 | 55.0 | 168.0 | 1.146 | 0.589 | 0.993 |
T14 | 55.0 | 167.5 | 1.521 | 1.097 | 0.837 |
T15 | 55.5 | 170.5 | 1.188 | 0.738 | 0.897 |
T16 | 55.5 | 170.0 | 1.233 | 0.766 | 0.959 |
T17 | 55.5 | 169.0 | 1.587 | 0.763 | 1.267 |
T18 | 55.5 | 168.5 | 1.460 | 0.907 | 1.051 |
T19 | 56.0 | 173.0 | 2.069 | 1.155 | 1.934 |
T20 | 56.0 | 172.5 | 1.510 | 1.089 | 1.161 |
T21 | 56.0 | 172.0 | 1.500 | 1.082 | 0.706 |
T22 | 56.0 | 171.5 | 0.676 | 0.348 | 1.893 |
T23 | 56.0 | 171.0 | 1.119 | 0.807 | 0.903 |
T24 | 56.0 | 170.0 | 1.124 | 0.811 | 0.734 |
T25 | 56.0 | 169.5 | 0.746 | 0.384 | 1.120 |
T26 | 56.0 | 169.0 | 1.835 | 0.835 | 1.630 |
T27 | 56.0 | 168.5 | 0.773 | 0.703 | 0.540 |
T28 | 56.5 | 174.0 | 1.547 | 0.864 | 1.577 |
T29 | 56.5 | 173.5 | 1.383 | 0.772 | 0.983 |
T30 | 56.5 | 173.0 | 1.674 | 1.207 | 0.867 |
T31 | 56.5 | 172.5 | 2.147 | 1.032 | 1.413 |
T32 | 56.5 | 172.0 | 0.058 | 0.084 | 1.000 |
T33 | 57.0 | 174.0 | 1.664 | 0.855 | 1.080 |
T34 | 57.5 | 174.5 | 0.659 | 0.600 | 0.558 |
T35 | 57.5 | 174.0 | 1.039 | 0.580 | 1.029 |
T36 | 58.0 | 176.0 | 2.154 | 0.981 | 1.547 |
T37 | 58.0 | 175.5 | 2.006 | 0.913 | 1.647 |
T38 | 58.0 | 175.0 | 1.487 | 0.924 | 1.156 |
T39 | 58.0 | 174.5 | 1.667 | 1.203 | 1.161 |
T40 | 58.5 | 178.5 | 1.894 | 0.973 | 1.309 |
T41 | 58.5 | 178.0 | 2.529 | 0.958 | 2.354 |
T42 | 58.5 | 177.5 | 1.212 | 0.874 | 0.768 |
T43 | 58.5 | 177.0 | 2.288 | 1.100 | 1.648 |
T44 | 58.5 | 176.5 | 1.291 | 0.721 | 1.199 |
T45 | 58.5 | 175.5 | 1.105 | 0.617 | 1.121 |
T46 | 58.5 | 175.0 | 2.443 | 1.255 | 1.276 |
T47 | 59.0 | 178.5 | 2.333 | 1.062 | 1.664 |
T48 | 59.0 | 178.0 | 1.157 | 0.595 | 1.099 |
T49 | 59.5 | 179.0 | 2.005 | 0.912 | 1.229 |
T50 | 59.5 | 178.5 | 1.234 | 0.689 | 0.916 |
T51 | 59.5 | 178.0 | 1.261 | 1.148 | 0.578 |
T52 | 60.0 | 179.5 | 2.476 | 0.996 | 2.040 |
T53 | 60.0 | 179.0 | 1.473 | 0.915 | 0.815 |
T54 | 60.0 | 178.5 | 0.933 | 1.346 | 1.000 |
T55 | 60.5 | 179.0 | 1.492 | 0.927 | 1.051 |
通过聚类分析结果可以发现(
变量 Variable | 集群1 Cluster 1(n=28) | 集群2 Cluster 2(n=27) |
---|---|---|
香农威纳指数Shannon-Wiener index | 0.723 | -0.698 |
均匀度指数Pielou index | 0.704 | -0.679 |
丰富度指数Margalef index | 0.378 | -0.364 |
注: 其中n为站点的个数。
Notes: n indicates the number of sites.
变量 Variable | 聚类 Cluster | 误差Error | F值 F value | 显著性 Significance | ||
---|---|---|---|---|---|---|
均方 Mean square | 自由度 Degree of freedom | 均方 Mean square | 自由度 Degree of freedom | |||
香农威纳指数Shannon-Wiener index | 27.750 | 1 | 0.495 | 53 | 56.028 | <0.001 |
均匀度指数Pielou index | 26.281 | 1 | 0.523 | 53 | 50.251 | <0.001 |
丰富度指数Margalef index | 7.568 | 1 | 0.876 | 53 | 8.639 | 0.005 |
注: 其中聚类均方对应组间均方差,误差均方对应组内均方差。
Notes: The clustering mean square corresponds to the interspecific mean square error, and the error mean square corresponds to the intraspecific mean square error.
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图5 站点聚类分布
Fig.5 Clustering distribution of the stations
根据以往的研
与传统回归方法相比,在探究头足类丰度与环境因子的关系方面,GAM模型被认为是一个信息更为丰富的工
根据多样性指数的结果判断白令海陆坡头足类丰富度较低,水体污染情况为中度,这可能与海水酸化有关。从海洋生物的生活史来看,钙化动物最容易受到海洋酸化的影响,而头足类由于存在钙质的壳体,并且壳内通常含有大量的气室或体管钙质沉积物,在酸性海水中容易发生溶解,不利于物种的生长和发
本研究通过对白令海陆坡头足类优势种及其空间分布与环境因子的关系的分析,首次阐述了亚北极头足类的群落结构以及其中优势种对环境因子的响应,随着海洋环境的不断变化,在今后的研究中,应该更加注重结合两者之间的联系,这对于亚北极地区头足类资源管理、保护以及可持续利用具有重要意义。
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