10.5061/DRYAD.7M0CFXPSH
Talarico, Lorenzo
0000-0002-5037-2676
University of Rome Tor Vergata
Russo, Tommaso
University of Rome Tor Vergata
Maiello, Giulia
0000-0002-0431-4205
University of Rome Tor Vergata
Baillie, Charles
University of Salford
Colosimo, Giuliano
0000-0002-0485-9758
San Diego Zoo Institute for Conservation Research
D'Andrea, Lorenzo
University of Rome Tor Vergata
Di Maio, Federico
University of Bologna
Fiorentino, Fabio
National Research Council
Franceschini, Simone
0000-0001-9725-4346
University of Rome Tor Vergata
Garofalo, Germana
National Research Council
Scannella, Dario
National Research Council
Cataudella, Stefano
University of Rome Tor Vergata
Mariani, Stefano
0000-0002-5329-0553
Liverpool John Moores University
Data from: All is fish that comes to the net: metabarcoding for rapid
fisheries catch assessment
Dryad
dataset
2020
FOS: Biological sciences
Natural Environment Research Council
https://ror.org/02b5d8509
NE/N005759/1
Ministry of Agricultural, Food and Forestry Policies
https://ror.org/023kmpc59
Italian Program for the Data Collection in the Fisheries Sector
2020-11-18T00:00:00Z
2020-11-18T00:00:00Z
en
https://doi.org/10.1101/2020.06.18.159830
2750527820 bytes
2
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
AbstractMonitoring marine resource exploitation is a key activity in
fisheries science and biodiversity conservation. Since research surveys
are time-consuming and costly, fishery-dependent data (i.e. derived
directly from fishing vessels) are increasingly credited with a key role
in expanding the reach of ocean monitoring. Fishing vessels may be seen as
widely ranging data-collecting platforms, which could act as a fleet of
sentinels for monitoring marine life, in particular exploited stocks.
Here, we investigate the possibility of assessing catch composition of
single hauls carried out by trawlers by applying DNA metabarcoding to the
“slush” collected from fishing nets just after the end of hauling
operations. We assess the performance of this approach in portraying
β-diversity and examining the quantitative relationship between species
abundances in the catch and DNA amount in the slush (reads counts
generated by amplicon sequencing). We demonstrate that the assemblages
identified using DNA in the slush mirror those returned by visual
inspection of net content and detect a strong relationship between read
counts and species abundances in the catch. We therefore argue that this
approach could be upscaled to serve as a powerful source of information on
the structure of demersal assemblages and the impact of fisheries.
COI_R1.fastq and COI_R2.fastq: COI paired-end FastQ files from the
Illumina HiSeq 2x250 bp run. COI_tag&primers.txt: COI primers and
unique dual-tag combinations (forward and reverse) for 63 COI amplicons
(54 slush samples, 2 extraction blanks, 1 PCR negative control, 6 seawater
blanks). 12S_R1.fastq and 12S_R2.fastq: 12S paired-end FastQ files from
the Illumina MiSeq 2x150 bp run. 12S_tag&primers.txt: 12S primers
and unique dual-tag combinations (forward and reverse) for 63 12S
amplicons (54 slush samples, 2 extraction blanks, 1 PCR negative control,
6 seawater blanks). metabarcoding_COI_data.xlsx: number of reads per
species/replicate/site after data post-processing and cleaning. Data refer
to analyzed taxa: teleosts, elasmobranchs, cephalopods and decapods.
metabarcoding_12S_data.xlsx: number of reads per species/replicate/site
after data post-processing and cleaning. Data refer to analyzed taxa:
teleosts and elasmobranchs.