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首页> 外文期刊>Marine ecology progress series >Real-time observation of taxa-specific plankton distributions: an optical sampling method
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Real-time observation of taxa-specific plankton distributions: an optical sampling method

机译:实时观察特定分类群的浮游生物分布:一种光学采样方法

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A fundamental problem in limnology and oceanography is the inability to measure the taxonomic composition of plankton quickly over a broad range of scales. Traditional sampling with bottles and nets provides critical data at the species-level, but has limited spatio-temporal coverage and can destroy ubiquitous delicate forms. To augment traditional sampling, recent advances in bio-acoustics and non-imaging optics provide real-time high-resolution data on biomass abundance and size composition. New optical imaging approaches provide coarse taxonomic composition but require manual image identification, preventing real-time observation. Here, we describe a method of optical sampling and analysis, using the Video Plankton Recorder, to automatically identify plankton to major taxa (and to species in some cases) and observe their distributions at sea in real time. We present a detailed assessment of classifier accuracy, including a comparison of machine- and hand-classification of images. The automated classification method was found to be sufficiently accurate for estimating abundance patterns of dominant taxa but not for less abundant taxa. The range in overall accuracy was 60 to 70 % for 7 taxa and 79 to 82 % for 2 taxa, with accuracies for individual taxa ranging between 45 and 91 %. Classification error was small relative to natural variability in abundance of dominant taxa. For a given taxon, the error in the abundance estimate was low in regions of high relative abundance. A manual correction step can be used in areas of low relative abundance to obtain accurate abundance estimates. Example data from 2 cruises are presented to illustrate the utility of real-time taxa-specific data collection. These data represent the first real-time automatic identification and mapping of plankton taxa at sea. This methodology represents an intermediate step towards the ultimate goal of real-time identification of plankton to the level of species and life stage. At present, optical imaging methods cannot replace net and bottle surveys, but can be used to obtain coarse taxonomic composition of plankton (including fragile forms) with an identification accuracy that is high enough to produce quantitative high-resolution maps of abundant taxa in real time.
机译:湖泊学和海洋学的一个基本问题是无法在广泛的尺度上快速测量浮游生物的生物分类组成。使用瓶和网的传统采样提供了物种级别的关键数据,但时空覆盖范围有限,并且可能破坏无处不在的精致形式。为了增加传统的采样,生物声学和非成像光学的最新进展提供了有关生物质丰度和大小组成的实时高分辨率数据。新的光学成像方法可提供粗略的分类学成分,但需要手动识别图像,从而无法进行实时观察。在这里,我们介绍一种使用视频浮游生物记录仪的光学采样和分析方法,以自动识别主要分类单元(在某些情况下还包括物种)的浮游生物,并实时观察其在海上的分布。我们提供了对分类器准确性的详细评估,包括图像的机器分类和手工分类的比较。发现自动分类方法对于估计优势类群的丰度模式是足够准确的,但对于数量较少的类群却不够准确。对于7个分类单元,整体准确度范围为60%至70%,对于2个分类单元,整体精度范围为79%至82%,单个分类单元的准确度介于45%至91%之间。相对于优势类群丰富度的自然可变性而言,分类误差较小。对于给定的分类单元,相对丰度高的区域中丰度估计的误差很小。可以在相对丰度较低的区域中使用手动校正步骤,以获取准确的丰度估计。给出了来自2个航程的示例数据,以说明实时特定分类单元数据收集的实用性。这些数据代表海上浮游生物类群的首次实时自动识别和制图。这种方法代表了朝着实时识别浮游生物到物种和生命阶段的最终目标的中间步骤。目前,光学成像方法无法代替网状和瓶状调查,但可用于获得浮游生物(包括易碎形态)的粗分类分类,其识别精度足以实时生成数量丰富的高分辨率分类单元的高分辨率地图。 。

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