DECOD (Ecosystem Dynamics and Sustainability), IFREMER, INRAE, Institut Agro, Lorient, France.
DECOD (Ecosystem Dynamics and Sustainability), IFREMER, INRAE, Institut Agro, Lorient, France.
Mar Environ Res. 2023 Jun;188:106004. doi: 10.1016/j.marenvres.2023.106004. Epub 2023 Apr 26.
Marine stock assessments or biodiversity monitoring studies, which historically relied on extractive techniques (e.g., trawl or grab surveys), are being progressively replaced by non-extractive approaches. For instance, species abundance indices can be calculated using data obtained from high-definition underwater cameras that enable to identify taxa at low taxonomical level. In biodiversity studies, environmental DNA (eDNA) has proven to be a useful tool for characterising fish species richness. However, several marine phyla remain poorly represented in reference gene databases or release limited amounts of DNA, restricting their detection. The absence of amplification of some invertebrate taxa might also reflect primer bias. We here explore and compare the performance of eDNA and image data in describing the marine communities of several sites in the Bay of Biscay. This was achieved by deploying a remotely operated vehicle to both record images and collect seawater samples. A total of 88 taxa were identified from the eDNA samples and 121 taxa from the images. For both methods, the best characterised phylum was Chordata, with 29 and 27 Actinopterygii species detected using image versus eDNA, respectively. Neither Bryozoa nor Cnidaria was detected in the eDNA samples while the phyla were easily identifiable by imagery. Similarly, Asteroidea (Echinodermata) and Cephalopoda (Mollusca) were scarcely detected in the eDNA samples but present on the images, while Annelida were mostly identified by eDNA (18 taxa vs 7 taxa from imagery). The complementary community descriptions we highlight from these two methods therefore advocate for using both eDNA and imagery in tandem in order to capture the macroscopic biodiversity of bentho-demersal marine communities.
海洋存量评估或生物多样性监测研究,过去依赖于捕捞技术(例如拖网或抓斗调查),正在逐步被非捕捞方法所取代。例如,可以使用高清水下摄像机获取的数据来计算物种丰度指数,从而能够在低分类学水平上识别分类单元。在生物多样性研究中,环境 DNA(eDNA)已被证明是一种有用的工具,可用于描述鱼类物种丰富度。然而,一些海洋门在参考基因数据库中代表性较差,或释放的 DNA 数量有限,限制了它们的检测。某些无脊椎动物类群的扩增缺失也可能反映了引物偏倚。我们在这里探索并比较了 eDNA 和图像数据在描述比斯开湾几个地点的海洋群落方面的性能。这是通过部署遥控潜水器来同时记录图像和采集海水样本来实现的。从 eDNA 样本中鉴定出 88 个分类群,从图像中鉴定出 121 个分类群。对于这两种方法,最好的特征门是脊索动物门,使用图像分别检测到 29 种和 27 种硬骨鱼。eDNA 样本中未检测到苔藓动物门和刺胞动物门,而这两个门通过图像很容易识别。同样,棘皮动物门(棘皮动物)和头足类动物门(软体动物)在 eDNA 样本中很少被检测到,但在图像中存在,而环节动物门主要通过 eDNA 鉴定(18 个分类群与 7 个分类群来自图像)。我们从这两种方法中突出显示的互补群落描述因此主张将 eDNA 和图像结合使用,以捕获底栖海洋群落的宏观生物多样性。