To explore the relationships between environmental factors and zooplanktonic beta diversity—and its component changes—zooplankton samples and corresponding environmental data were collected from 24 stations in Xiangshan Bay.Zooplanktonic beta diversity was analyzed by a generalized dissimilarity model (GDM) with the gdm package in the R language,and was further separated into two components—turnover and nestedness—using the betapart package.Analytical results with GDM showed that 10 environmental variables (surface water temperature,dissolved oxygen,water depth,transparency,pH,chlorophyll a,geographical distance,conductivity,salinity,and suspended particulate matter) affected zooplanktonic beta diversity and could explain 75.2％ of the GDM deviation.Among the 10 variables,water temperature,dissolved oxygen,and water depth were the important driving factors for beta diversity changes,which explained 63.9％ of the cumulative relative contribution (taking the interpretable proportion of the GDM deviation as 100％),while the other 7 factors accounted for 36.1％.Furthermore,water temperature was the most important driving factor among these three factors,which accounted for 38.4％ of the cumulative relative contribution.According to the gradient effects of predictors,beta diversity increased with the increasing gradients of factors when the geographical distance,pH,salinity,water temperature,and chlorophyll a were above ca.25 km,7.8,25,and under 22℃ and 0.5 μg/L respectively.Moreover,zooplanktonic beta diversity always increased with increasing dissolved oxygen,conductivity,transparency,and water depth.However,no obvious effect was found with the content change of suspended particulate matter.According to the results of partitioning beta diversity into turnover and nestedness components,turnover played a dominant role in the spatiotemporal changes of zooplankton,while the nestedness had small effects in Xiangshan Bay.Furthermore,the nestedness mainly occurred in the groups of macro-zooplankton and lava,especially in the latter group,and the spatiotemporal nestedness was almost always higher than turnover in the two groups.Further analyses of Pearson's correlation demonstrated that the water temperature and dissolved oxygen were significantly correlated with the nestedness of macro-zooplankton,and that the water temperature,dissolved oxygen,and two other factors—conductivity and velocity— were significantly associated with the nestedness in the lava group.%根据象山港24个站位浮游动物样品和配套环境数据,采用R语言的gdm工具包对浮游动物β多样性进行了广义非相似性模型(GDM)分析,并利用betapart工具包对β多样性进行了成分(周转和嵌套性)分解,探讨了环境因子与浮游动物β多样性及其成分间的关系.GDM模型分析结果表明,有10个环境变量(表层水温、溶解氧、水深、透明度、pH、叶绿素a、地理距离、电导率、盐度、悬浮颗粒物)对浮游动物β多样性有影响,解释了GDM模型偏差比例的75.2％.在这10个变量中,水温、溶解氧、水深是驱动β多样性变化重要因子,3个变量累计相对贡献比例占63.9％(以GDM模型偏差的可解释比例作为100％),其他7个变量占36.1％;3个变量中,又以水温最重要,相对贡献比例占到38.4％.从各预测变量的影响梯度看,地理距离、pH和盐度分别在约高于25 km、7.8和25,水温、叶绿素a含量分别在约低于22℃和0.5 μg/L时,随着变量梯度的增加,β多样性增大;而溶解氧、电导率、透明度和水深则随着梯度增加β多样性一直增加,悬浮颗粒物含量对β多样性几乎无影响.据β多样性成分分解结果,象山港浮游动物在时空变化上总体以周转为主,嵌套性很低.在象山港,浮游动物嵌套性主要发生于大型浮游动物和幼体类群,尤其是幼体类群,嵌套性在时空上几乎都高于周转.进一步的Pearson相关性分析表明,与大型浮游动物嵌套性显著相关的环境因子是水温和溶解氧,而与幼体类嵌套性显著相关的环境因子除水温和溶解氧外,还有电导率和流速.
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