Volume backscattering strength samples and echograms (38 kHz) associated to small pelagic fish schools in the Gulf of California, Mexico

Sv (dB re m-1) data samples taken from fish schools and their surrounding echoes in echograms associated to small pelagic fish in the Midriff Islands Region of the Gulf of California, Mexico. Acoustic data was acquired using a SIMRAD EK60 scientific echosounder with a 38 kHz split-beam transducer during May, 2013. Two files are provided, the data itself (Sv samples and three echograms) and the R-code needed to recreate figures and analysis in López-Serrano et al. 2017 (https://doi.org/10.1051/alr/2017048).

 

File description:

  • LopezSerrano_et_al_code.R

Ascii file (encoding UTF-8) with the R-code for re-creating the figures and analysis in the paper.

  • LopezSerrano_et_al_data.RData

Binary RData file with all the data used in the paper. Once loaded in R, it contains 4 objects: A table (data frame) and three echograms.

The first table contains nine columns:

id, x, y, pingNumber, pingTime, depth, Sv038, trawlNo, category

 

The echograms (eco.L04, eco.L14, eco.L17) are objects of class “echogram”, which are described below according to the R package echogram:

An object of class “echogram” (a list) with components:

depth : a vector of mean sample depth (in m) of length p.

Sv : a p by k matrix of sampled values, currently the mean volume backscattering strength (Sv, in dB).

pings : a k by four data frame with ping time, detected bottom depth, vessel speed and cummulated traveled distance.

Disciplines

Fisheries and aquaculture

Location

30.375513N, 27.725142S, -110.742187E, -115.004883W

Data

FileSizeFormatProcessingAccess
LopezSerrano_et_al_code.R
9 KoR Code
LopezSerrano_et_al_data.RData
9 MoR Data
How to cite
Villalobos Héctor, López-Serrano Antonio, Nevárez-Martínez Manuel O. (2018). Volume backscattering strength samples and echograms (38 kHz) associated to small pelagic fish schools in the Gulf of California, Mexico. SEANOE. https://doi.org/10.17882/53034
In addition to properly cite this dataset, it would be appreciated that the following work(s) be cited too, when using this dataset in a publication :
López-Serrano Antonio, Villalobos Héctor, Nevárez-Martínez Manuel O. (2018). A probabilistic procedure for estimating an optimal echo-integration threshold using the Expectation-Maximisation algorithm. Aquatic Living Resources, 31, 12-. https://doi.org/10.1051/alr/2017048

Copy this text