Issue |
Aquat. Living Resour.
Volume 32, 2019
|
|
---|---|---|
Article Number | 7 | |
Number of page(s) | 12 | |
DOI | https://doi.org/10.1051/alr/2019007 | |
Published online | 15 March 2019 |
Research Article
Age and growth estimates of the jumbo flying squid (Dosidicus gigas) off Peru
1
Instituto del Mar del Perú, Esquina Gamarra y General Valle s/n,
Chucuito,
Callao, Perú
2
Centro de Investigaciones Biológicas del Noroeste S.C.,
Av. Instituto Politécnico Nacional 195, Col. Playa Palo de Santa Rita Sur,
CP 23096,
La Paz,
Baja California Sur, México
3
Instituto Nacional de Pesca y Acuacultura-Ensenada,
Km 97.5 Carretera Tijuana Ensenada s/n, El Sauzal de Rodríguez,
CP 22760,
Ensenada,
Baja California, México
4
Instituto Nacional de Pesca y Acuacultura-Mazatlán,
Avenida Camarón Sábalo S/N, Estero del Yugo,
CP 8
2000,
Sinaloa, México
* Corresponding author: emorales@cibnor.mx
Handling Editor: David Kaplan
Received:
24
April
2018
Accepted:
26
February
2019
Mantle length (ML) and age data were analyzed to describe the growth patterns of the flying jumbo squid, Dosidicus gigas, in Peruvian waters. Six non-asymptotic growth models and four asymptotic growth models were fitted. Length-at-age data for males and females were analysed separately to assess the growth pattern. Multi-model inference and Akaike's information criterion were used to identify the best fitting model. For females, the best candidate growth model was the Schnute model with L∞ = 106.96 cm ML (CI 101.23–110.27 cm ML, P < 0.05), age at growth inflection 244.71 days (CI 232.82–284.86 days, P < 0.05), and length at growth inflection 57.26 cm ML (CI 55.42–58.51 cm ML, P < 0.05). The growth pattern in males was best described by a Gompertz growth model with L∞ = 127.58 cm ML (CI 115.27–131.80 cm ML, P < 0.05), t0 = 21.8 (CI 20.06–22.41, P < 0.05), and k = 0.007 (CI 0.006–0.007, P < 0.05). These results contrast with the growth model previously reported for D. gigas in the region, where the growth pattern was identified as non-asymptotic.
Key words: Age / Statoliths / Multi-model inference / Peru
© EDP Sciences 2019
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