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描述路易斯安那大陆架上的常见浮游植物。

Characterization of common phytoplankton on the Louisiana shelf.

机构信息

Coastal Watershed Institute, Florida Gulf Coast University, 10501 FGCU Blvd South, Fort Myers, FL 33965, United States of America.

Coastal Watershed Institute, Florida Gulf Coast University, 10501 FGCU Blvd South, Fort Myers, FL 33965, United States of America.

出版信息

Mar Pollut Bull. 2021 Jul;168:112458. doi: 10.1016/j.marpolbul.2021.112458. Epub 2021 May 13.

Abstract

Phytoplankton and accompanying environmental data (temperature, salinity, secchi depth, stratification, and inorganic nutrients) were analyzed from 672 surface water samples (0 to 1.5 m depth) collected from 95 stations located on the Louisiana shelf between April 1990 and August 2011. Phytoplankton were identified to the lowest practical taxonomic unit from glutaraldehyde-preserved samples using epifluorescent microscopy and reported as cells L. Twenty-six phytoplankton taxa (primarily diatoms) that were > 8 μm in size, identified to genus-level resolution and ranked in the top 20 in at least one of three separate categories (average abundance; frequency of occurrence; and bloom frequency) were used in subsequent analyses. Temperature, stratification, and secchi depth constituted the environmental variable combination best related to the phytoplankton community composition patterns across the 672 samples (r = 0.288; p < 0.01) according to BEST analysis (PRIMER 7). The environmental optima of the 26 taxa were calculated using the weighted-averaging algorithm in the C2 program and then used to group the taxa into common phytoplankton clusters (i.e., niches) using PRIMER 7 CLUSTER. The phytoplankton clustered into three groups: Group A (summer assemblage), Group B (winter assemblage), and Group C (spring bloom assemblage). The results demonstrate that the composition of the phytoplankton community is most related to seasonality and physical variables, whereas nutrients appear to play a larger role in driving overall phytoplankton biomass. This study provides a platform to examine phytoplankton responses to future environmental perturbations in the region.

摘要

从 1990 年 4 月至 2011 年 8 月期间,在路易斯安那大陆架的 95 个站位采集了 672 个表层水样(0 至 1.5 米深度),分析了浮游植物和相关环境数据(温度、盐度、分光光度计深度、分层和无机养分)。用戊二醛保存的样品,通过荧光显微镜将浮游植物鉴定到最低实用分类单元,并以细胞 L 报告。使用大小大于 8μm、鉴定到属级分辨率且在至少三个独立类别(平均丰度、出现频率和暴发频率)之一中排名前 20 的 26 种浮游植物类群(主要是硅藻)进行后续分析。根据 BEST 分析(PRIMER 7),温度、分层和分光光度计深度是与 672 个样本中浮游植物群落组成模式最相关的环境变量组合(r=0.288;p<0.01)。使用 C2 程序中的加权平均算法计算 26 个分类群的环境最佳值,然后使用 PRIMER 7 CLUSTER 将这些分类群分为常见浮游植物群(即生态位)。浮游植物分为三组:A 组(夏季组合)、B 组(冬季组合)和 C 组(春季暴发组合)。结果表明,浮游植物群落的组成与季节性和物理变量最相关,而营养物质似乎在驱动浮游植物总生物量方面发挥更大的作用。本研究为研究该地区浮游植物对未来环境干扰的响应提供了一个平台。

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