Examing the climate drivers of phytoplankton variation along the Chilean coast

The South American east coast is a very productive region, with more than 10% of the worldwide marine fish catch, especially along the Chilean shores. The base of this production is the phytoplankton that can be easily measured by the MODIS-aqua satellite through its chlorophyll (Chl). The Chl conce...

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Bibliographic Details
Main Author: Tornquist, Felipe
Format: Thesis
Language:unknown
Published: 2022
Subjects:
Online Access:https://etheses.whiterose.ac.uk/31964/
Description
Summary:The South American east coast is a very productive region, with more than 10% of the worldwide marine fish catch, especially along the Chilean shores. The base of this production is the phytoplankton that can be easily measured by the MODIS-aqua satellite through its chlorophyll (Chl). The Chl concentration depends on specific parameters such as precipitation rate (PR), surface sea temperature (SST), or wind direction (U, V), obtained by ERA5. These parameters have a different impact along the extensive Chilean coast, having different climates. Additionally, they are forced by climate drivers such as El Niño Southern Oscillation (ENSO), the Antarctic Oscillation (AAO), the Southern Pacific Subtropical Anticyclone (SPSA), and the Pacific Decadal Oscillation (PDO) obtained by NOAA. The study area was split into ten subsections, grouped into three Zones (the Northern, Central and Southern Zone). The Chl and physical parameters were studied in each subsection from 2002 to 2018. The analysis revealed that the southerly winds driven by the presence of the SPSA and the shelf size are the main triggers for the phytoplankton bloom. Therefore, the most productive region is the middle Central Zone having a broad shelf. However, despite its extreme aridity and low southerly winds, the Northern Zone’s extreme subsection (1N) had a significant Chl signal. In contrast, although the Southern Zone had high PR and predominant westerly winds leading to stratification, its production was significant, with a slightly lower concentration further south (3S). Thus, these regions need a deeper analysis. Composites were created selecting the years when the climate drivers were either strongly positive or negative to understand their influence on the different parameters. The study period was extended towards 1979 to have enough years in the composite samples. Nonetheless, the Chl is only available from 2002 onwards. The Chl dataset from the long preMODIS period was reconstructed by Canonical Correlation Analysis (CCA), based on another ...