Effects of ENSO phases on Peruvian anchovy spatial aggregation patterns
Abstract
The Peruvian anchovy (Engraulis ringens) is the most important small pelagic of the Humboldt Current, supporting the largest mono-specific fishery in the world. Previous studies have tried to link spatial indicators with environmental variables, being the most of them limited to a temporal analysis. The aim of this study is to analyse fluctuations on anchovy aggregation patterns and its relationships with set of variables in the period 1992-2016, focusing on the main El Niño/La Niña events. We employed survey acoustic data to model anchovy spatial abundance in a Bayesian framework, using the integrated nested Laplace approximation method with a SPDE approach to model the spatial component. Having obtained spatial distribution, we calculated a set of patchiness indicators which were modelled, using generalized linear models (GLM), by a suite of oceanographic variables, including zooplankton biomass and fish length size. During the most important El Niño/La Niña events, map comparison tests was employed to look for similarities between anchovy spatial distribution and oceanographic features. A detailed discussion is made using the main variables that trigger patchiness and temporal changes in aggregation patterns in a wide temporal window, being able to observe similar patterns during El Niño 1997/1998 and 2014-2015/2016 and the opposite during La Niña 2013. Spatial analysis gives us clues about preferences of anchovy high density patches, finding zooplankton as an important driver of this behaviour. Finally, we include in our discussion other sources of information in order to have a complete view of all processes carrying out during these events.
