The Effect of Cold and Warm Anomalies on Phytoplankton Pigment Composition in Waters off the Northern Baja California Peninsula (México): 2007–2016

• Main Authors: Adriana González-Silvera, Eduardo Santamaría-del-Ángel, Víctor Camacho-Ibar, Jorge López-Calderón, Jonatan Santander-Cruz, Alfredo Mercado-Santana
• Format: Article
• Language: English
• Published: MDPI AG 2020-07-01
• Series: Journal of Marine Science and Engineering
• Subjects: phytoplankton community composition; phytoplankton pigments; Chemtax; MODIS; Pacific Warm Anomaly; El Niño
• Online Access: https://www.mdpi.com/2077-1312/8/7/533

In<b> </b>this study, we report the response of phytoplankton community composition to cold and warm interannual events affecting the waters off the Baja California Peninsula from 2007 to 2016 based on data obtained from a single marine station (31.75^oN/116.96^oW). Included variables were satellite chlorophyll <i>a</i>, sea surface temperature (MODIS/Aqua), upwelling intensity, and field data (phytoplankton pigments, inorganic nutrients, light penetration). Phytoplankton pigments were determined by high performance liquid chromatography, and CHEMTAX software was used to determine the relative contributions of the main taxonomic groups to chlorophyll <i>a</i>. Our results confirm the decrease in phytoplankton biomass due to the influence of the recent Pacific Warm Anomaly (2014) and El Niño 2015-2016. However, this decrease was especially marked at the surface. When data from the entire water column was considered, this decrease was not significant, because at the subsurface Chla did not decrease as much. Nevertheless, significant changes in community composition occurred in the entire water column with Cyanobacteria (including <i>Prochlorococcus</i>) and Prymnesiophytes being dominant at the surface, while Chlorophytes and Prasinophytes made a strong contribution at the subsurface. Analysis of the spatial distribution of SST and satellite chlorophyll <i>a</i> made it possible to infer the spatial extension of these anomalies at a regional scale.