Engraulis ringens (E. ringens) is a small pelagic fish of which the geographic and bathymetric distribution is conditioned by fluctuations in oceanographic conditions at different time scales (daily, weekly, monthly, annually, supra-annually, and longer) and by fishing. Understanding the organism−environment interactions and predicting the spatial distribution of its schools can improve conservation actions and fishery management, along with the operation of the fleets targeting E. ringens. There is an important fishery of E. ringens in Northern Chile (18°21′ S–26°00′ S), which provides about 80% of the purse seine catch. To identify and predict potential fishing grounds for E. ringens in this system, we implemented a predictive model of fishing grounds based on neural networks, which was trained with the georeferenced data of daily catches by industrial purse sein ships from 2003 to 2020 and information on oceanographic variables (sea surface temperature, salinity, depth of the mixed layer, sea height, and currents) obtained from the Copernicus Marine Enviroment Monitoring Service (CMEMS program). The neural network model had a very good performance (86%). Longitude (23%) was the most relevant variable for identifying potential fishing grounds, followed by the mixed layer depth (18%), latitude (15%), sea surface temperature (12%), month (12%), sea height (9%), salinity (9%), and the zonal and meridional components of the current velocity (2%). The neural network model classified correctly the majority of the areas with and without fishing potential; thus, its use is recommended to predict fishing grounds for E. ringens in the study area. Its application could increase by 88% of the probability of capture anchovy by the purse seine fleet of Northern Chile.

The structure and functioning of the food web of the Francisco Coloane Marine Area in the Magellan Strait, Chile, was quantified, with an emphasis on identifying the ecological role of the squat lobster (Munida gregaria) and the Fuegian sprat (Sprattus fuegensis). Food web indicators, the trophic level, and centrality indices were estimated using Ecopath with Ecosim. Dynamic simulations were carried out to evaluate the ecosystem impacts of biomass changes in squat lobster and Fuegian sprat. The model calculated a total ecosystem biomass of 71.7 t km⁻² and a total primary production of 2450.9 t km⁻² year⁻¹. Squat lobster and Fuegian sprat were located in specific trophic levels of 2.3 and 2.7, respectively. Squat lobster reduction produced a decrease in the biomass of red cod (42–56%) and humpback whales (25–28%) and Fuegian sprat reduction a decrease in penguins (15–37%) and seabirds (11–34%). The Francisco Coloane Area is an immature ecosystem with productivity and energy flows values within those reported for productive ecosystems; the role of the squat lobster seems to be related to the structure of the food web, and the role of the Fuegian sprat seems to be related to the functioning of the ecosystem and to the energy transfer to top predators.