Sales Naiara G, Mariani Stefano, Salvador Gilberto N, Pessali Tiago C, Carvalho Daniel C
Ecosystems and Environment Research Centre, School of Environment & Life Sciences, University of Salford, Salford, United Kingdom.
Laboratório de Ecologia e Conservação, Universidade Federal do Pará, Belém, Brazil.
Front Genet. 2018 Jul 24;9:271. doi: 10.3389/fgene.2018.00271. eCollection 2018.
Neotropical Rivers host a highly diverse ichthyofauna, but taxonomic uncertainty prevents appropriate conservation measures. The Doce River Basin (DRB), lying within two Brazilian threatened hotspots (Atlantic Forest and Brazilian Savanna) in south-east Brazil, faced the worst ever environmental accident reported for South American catchments, due to a dam collapse that spread toxic mining tailings along the course of its main river. Its ichthyofauna was known to comprise 71 native freshwater fish species, of which 13 endemic. Here, we build a DNA barcode library for the DRB ichthyofauna, using samples obtained before the 2015 mining disaster, in order to provide a more robust biodiversity record for this basin, as a baseline for future management actions. Throughout the whole DRB, we obtained a total of 306 barcodes, assigned to 69 putative species (with a mean of 4.54 barcodes per species), belonging to 45 genera, 18 families, and 5 orders. Average genetic distances within species, genus, and families were 2.59, 11.4, and 20.5%, respectively. The 69 species identified represent over 76% of the known DRB ichthyofauna, comprising 43 native (five endemic, of which three threatened by extinction), 13 already known introduced species, and 13 unknown species (such as sp., sp., and specimens identified only at the sub-family level Neoplecostominae, according to morphological identification provided by the museum collections). Over one fifth of all analyzed species ( = 16) had a mean intraspecific genetic divergence higher than 2%. An integrative approach, combining NND (nearest neighbor distance), BIN (barcode index number), ABGD (automatic barcode gap discovery), and bPTP (Bayesian Poisson Tree Processes model) analyses, suggested the occurrence of potential cryptic species, species complex, or historical errors in morphological identification. The evidence presented calls for a more robust, DNA-assisted cataloging of biodiversity-rich ecosystems, in order to enable effective monitoring and informed actions to preserve and restore these delicate habitats.
新热带地区的河流拥有高度多样化的鱼类区系，但分类学上的不确定性阻碍了采取适当的保护措施。多西河盆地（DRB）位于巴西东南部的两个巴西受威胁热点地区（大西洋森林和巴西稀树草原）内，由于一座大坝坍塌，有毒的采矿尾矿沿其主要河道扩散，该地区遭遇了南美流域有史以来最严重的环境事故。已知其鱼类区系包括71种本地淡水鱼，其中13种为特有种。在此，我们利用2015年采矿灾难前采集的样本，为DRB鱼类区系建立了一个DNA条形码库，以便为该流域提供更可靠的生物多样性记录，作为未来管理行动的基线。在整个DRB地区，我们总共获得了306个条形码，这些条形码被分配到69个假定物种（平均每个物种有4.54个条形码），属于45个属、18个科和5个目。物种、属和科内的平均遗传距离分别为2.59%、11.4%和20.5%。所识别的69个物种占已知DRB鱼类区系的76%以上，包括43种本地物种（5种特有种，其中3种面临灭绝威胁）、13种已知的外来物种和13种未知物种（如博物馆收藏提供的形态学鉴定显示，有 种、 种以及仅在新吸甲鲶亚科水平鉴定的标本）。所有分析物种中超过五分之一（=16种）的种内平均遗传差异高于2%。一种综合方法，结合最近邻距离（NND）、条形码索引号（BIN）、自动条形码间隙发现（ABGD）和贝叶斯泊松树过程模型（bPTP）分析，表明可能存在潜在的隐存物种、物种复合体或形态学鉴定中的历史错误。所提供的证据呼吁对生物多样性丰富的生态系统进行更可靠的、基于DNA的编目，以便能够进行有效的监测并采取明智的行动来保护和恢复这些脆弱的栖息地。
