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Surveying cephalopod diversity of the Amazon reef system using samples from red snapper stomachs and description of a new genus and species of octopus. | LitMetric

The cephalopod fauna of the southwestern Atlantic is especially poorly-known because sampling is mostly limited to commercial net-fishing operations that are relatively inefficient at obtaining cephalopods associated with complex benthic substrates. Cephalopods have been identified in the diets of many large marine species but, as few hard structures survive digestion in most cases, the identification of ingested specimens to species level is often impossible. Samples can be identified by molecular techniques like barcoding and for cephalopods, mitochondrial 16S and COI genes have proven to be useful diagnostic markers for this purpose. The Amazon River estuary and continental shelf are known to encompass a range of different substrates with recent mapping highlighting the existence of an extensive reef system, a type of habitat known to support cephalopod diversity. The present study identified samples of the cephalopod fauna of this region obtained from the stomachs of red snappers, Lutjanus purpureus, a large, commercially-important fish harvested by fisheries using traps and hook-and-line gear that are capable of sampling habitats inaccessible to nets. A total of 98 samples were identified using molecular tools, revealing the presence of three squid species and eight MOTUs within the Octopodidae, representing five major clades. These include four known genera, Macrotritopus, Octopus, Scaeurgus and Amphioctopus, and one basal group distinct from all known octopodid genera described here as Lepidoctopus joaquini Haimovici and Sales, new genus and species. Molecular analysis of large predatory fish stomach contents was found to be an incredibly effective extended sampling method for biodiversity surveys where direct sampling is very difficult.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC6459862PMC
http://dx.doi.org/10.1038/s41598-019-42464-8DOI Listing

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