Unravelling links between squid catch variations and biophysical mechanisms in South African waters

Using satellite observations, this study uncovers the biophysical drivers of the lucrative chokka squid fishery in South Africa over the last two decades (1998–2017) and addresses their potential links with low squid catches. Chokka squid fishing is crucial to the economic wellbeing of local communities. However, the squid biomass is prone to considerable fluctuations, including abrupt declines with negative socio-economic impacts. We show that the squid catch is significantly and positively correlated with satellite-derived chlorophyll-a (Chl-a, an index of phytoplankton biomass) from year to year in South African coastal waters. Two main phytoplankton blooms are observed to occur seasonally in the austral spring and autumn, peaking in October and April, respectively. From October to April, phytoplankton abundance is influenced by the occurrence of wind-driven upwelling over the South African west coast (southern Benguela) and the central Agulhas Bank (so-called Cold Ridge upwelling), while the surface currents appear more important for shelf edge processes and advection along the Cold Ridge on shorter timescales. Low squid catches are observed in 2001 and 2013 and linked to declines in Chl-a induced by weak winds and relaxed negative wind stress curl over the southwest coast in 2001, and over the southwest coast and the central Agulhas Bank in 2013. Phytoplankton phenology (bloom timing) analysis reveals absent, or shorter and delayed blooms, over the Benguela upwelling region in 2001 and both the Benguela and Cold Ridge upwelling areas in 2013. In contrast, the high catch years of 2004 and 2009, associated with elevated Chl-a, coincide with early and/or prolonged seasonal blooms. These are induced by strong winds over the Benguela upwelling and Cold Ridge areas in 2004, and by intensified negative wind stress curl over the Benguela upwelling area in 2009. These results show that the squid catch fluctuations are potentially predictable and could support policymakers seeking to improve their planning of adaptation strategies and risk mitigation