Interannual variability in the distribution and biomass of five demersal fish species from shrimp bycatch and their relationship with environment in the Gulf of California

Abstract

In the Gulf of California (GC), five fish species —Balistes polylepis, Paralabrax maculatofasciatus, Sphoeroides annulatus, Haemulopsis elongatus, and Diapterus brevirostris— are caught as bycatch in the industrial shrimp trawl fisheries. This study analyzed their distribution using the positive hauls from prospecting cruises, biomass through the swept area method, and environmental influences using multivariate methods from 2002 to 2018. The estimated absolute abundance was 52,181,219 individual organisms, with a total biomass of 4394.5 tons. The highest values were recorded in 2011, contributing more than 46 % of the total abundance and 54 % of the biomass, while the lowest values were observed in 2008 and 2018. H. elongatus (33 %) and D. brevirostris (25 %) were the most abundant species, whereas B. polylepis (41 %) and H. elongatus (22 %) dominated the biomass. According to our zoning of the GC, the North (N) zone contributed more than 50 % of the total abundance and biomass, followed by the Central (C) zone in the early years, with an increasing contribution from the South (S) and Southeast (SE) zones after 2015. Bathymetrically, the biomass in the SE and S zones was concentrated in the < 20 m stratum, while the > 40 m strata were relevant only in the N and S zones. H. elongatus and D. brevirostris exhibited a northward expansion, evidencing shifts in their geographic distribution. The PERMANOVA analysis indicated significant differences in biomass across years (F = 1.82, p = 0.00011) and zones (F = 1.95, p = 0.00141), but not across depth strata (p = 0.1971). Non-metric multidimensional scaling revealed temporal and spatial groupings, particularly for 2011, 2016, and 2005. Principal Component Analysis (PCA) explained 61.6 % of the variability, associating H. elongatus with the N zone and 2011, and D. brevirostris with the SE zone and 2016. Generalized Additive Models (GAMs) identified chlorophyll a (CHLA) and the Multivariate ENSO Index (MEI) as important environmental predictors of biomass variability in most species, explaining a significant portion of the deviance in their biomass patterns. These findings highlight the influence of environmental variability on biomass distribution, providing crucial insights for fisheries management in the GC region.