Development of habitat prediction models to reduce by-catch of sailfish (Istiophorus platypterus) within the purse-seine fishery in the eastern Pacific Ocean
Raul O. Martinez-Rincon A E , Sofia Ortega-Garcia A , Juan G. Vaca-Rodriguez B D and Shane P. Griffiths D
+ Author Affiliations
- Author Affiliations
A Instituto Politécnico Nacional – Centro Interdisciplinario de Ciencias Marinas (CICIMAR), Departamento de pesquerías, Avenida IPN s/n, La Paz, B.C.S. 23096, México.
B Programa Nacional de Aprovechamiento del Atún y de Protección de Delfines (PNAAPD), Km 107 Carretera Tijuana-Ensenada, campus CICESE, Ensenada, Baja California, México.
C Commonwealth Scientific and Industrial Research Organisation (CSIRO), Oceans and Atmosphere Flagship, GPO Box 2583, Brisbane, Qld 4001, Australia.
D Present address: Facultad de Ciencias Marinas, Universidad Autónoma de Baja California (UABC), Km 103 Carretera Tijuana-Ensenada, campus UABC, Ensenada, Baja California, México.
E Corresponding author. Present address: Centro de Investigaciones Biológicas del Noroeste (CIBNOR), Avenida IPN s/n, La Paz, B.C.S. 23096, Mexico. Email: raul.martinez.rincon@gmail.com
Marine and Freshwater Research 66(7) 644-653 https://doi.org/10.1071/MF14062
Submitted: 5 March 2014 Accepted: 8 September 2014 Published: 19 February 2015
Abstract
Sailfish (Istiophorus platypterus) is an important apex predator in neritic and oceanic pelagic ecosystems. The species is also a primary target of important catch-and-release sport fisheries that the support local economies of developing countries. However, commercial purse-seine fisheries that target tuna in the eastern Pacific Ocean (EPO) incidentally catch and discard large numbers of sailfish. Sailfish by-catch data recorded by scientific observers in the Mexican tuna purse-seine fleet in the EPO from 1998 to 2007 was used in generalised additive models (GAMs) to predict environmental and spatial preferences of sailfish. GAM predicted the highest sailfish catches to occur in coastal waters during El Niño events during late autumn and winter, with sea surface temperatures >26°C, with negative values of deviation in sea surface height (<–10 cm), and low chlorophyll-a (<0.25 mg m–3). GAM predicted that the catch probability for sailfish increased 1.8-fold during El Niño events in coastal waters and 1.5-fold under La Niña. However, the spatial distribution of sailfish remained largely unchanged during El Niño and La Niña events. Our models may be an additional fisheries management tool that may be used to support temporary spatial-temporal throughout the fishing season to reduce sailfish by-catch in the EPO.
Additional keywords: environmental predictors, generalised additive model, spatial predictors.
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