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Incorporating sea surface temperature into the stock-recruitment relationship: Applications to jack mackerel (Trachurus murphyi) off Chile

Autores

CORRESPONSAL

Fernando Espíndola

fernando.espindola@ifop.cl

1

1

División de Investigación Pesquera, Instituto de Fomento Pesquero, Casilla 8V, Valparaíso, Chile

Juan Carlos Quiroz

1

1

División de Investigación Pesquera, Instituto de Fomento Pesquero, Casilla 8V, Valparaíso, Chile

2

2

Institute for Marine and Antarctic Studies, University of Tasmania (UTAS), 49 Private Bag, Hobart 7001, Australia

Rodrigo Wiff

3

3

Center of Applied Ecology and Sustainability (CAPES), Pontificia Universidad Católica de Chile, Av. Alameda 340, Santiago, Chile

Eleuterio Yáñez

4

4

Escuela de Ciencias del Mar, Facultad de Ciencias del Mar y Geografía, Pontificia Universidad Católica de Valparaíso, Casilla 1020, Valparaíso, Chile

Resumen

The recruitment rate was modeled in relation to spawning biomass and to sea surface temperature (SST) for the jack mackerel (Trachurus murphyi) population off the Chilean coast using the Ricker model. Data regarding recruitment and spawning biomass were obtained from indirect stock assessment models from 1975 to 2001, while annual time series of SST were collected from the meteorological stations placed along the Chilean coast by the National Center of Hydrographic and Oceanographic Data (CENDHOC). The standard Ricker model was thus modified as follows: (1) the SST temporal series was included as a linear predictor; (2) the SST temporal series was modeled through smoothing functions; and (3) spawning biomass and SST temporal series were both modeled using smoothing functions. The resulting models were compared with the standard Ricker model without SST. Model selection was carried out using automatic information criteria (AIC). Including SST improved the fit of the recruitment model, despite the penalty of an additional term and a possible additional source of variability. The best model resulting includes the SST temporal series with smoothing functions and the spawning biomass with parametric functions, with a goodness-of-fit of 90%. Incorporating an environmental variable into stock-recruitment relationships may be a promising method for simultaneously considering effects from fishing and the environment, and is particularly relevant for managing fisheries in light of climate change.

Palabras clave

Generalized additive models, stock-recruitment relationships, SST, non-parametric

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