Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps

Date 2018-05
Temporal extent 2008-11-01 -2012-12-01
Author(s) Mendoza-Carranza ManuelORCID1
Affiliation(s) 1 : El Colegio de la Frontera Sur
DOI 10.17882/55020
Publisher SEANOE
Keyword(s) Small-scale fisheries, Mexico, neural networks
Abstract

Data serie of small-scale fisheries of San Pedro port, Tabasco, México. These data are kg/fishery trip (lines) by species (common name, columns), by gear type year and month. For reference about gear names and fish common names please look for the paper:  Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps. publised in PlosOne

Licence CC-BY-NC-ND
Acknowledgments Wendi Arévalo, Arturo Alvarez, Chrystian Hernandez, Elsy Segura, Edith Ramirez, Alfredo Hernandez, Solano
Data
File Size Format Processing Access
Database about small-scale fisheries of San Pedro port, Tabasco, México by common name. Data are based on commercial logbooks. 454 KB CSV Raw data Open access
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How to cite 

Mendoza-Carranza Manuel (2018). Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps. SEANOE. https://doi.org/10.17882/55020


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 :


Mendoza-Carranza Manuel, Ejarque Elisabet, Nagelkerke Leopold A. J., Corriero Aldo (2018). Disentangling the complexity of tropical small-scale fisheries dynamics using supervised Self-Organizing Maps. PLOS ONE, 13(5), e0196991-. https://doi.org/10.1371/journal.pone.0196991