Bioregionalization of the coastal and open oceans of British Columbia and Southeast Alaska based on Sentinel-3A satellite-derived phytoplankton seasonality

Abstract

Classifying the ocean into regions with distinct biogeochemical or physical properties may enhance our interpretation of ocean processes. High-resolution satellite-derived products provide valuable data to address this task. Notwithstanding, no regionalization at a regional scale has been attempted for the coastal and open oceans of British Columbia (BC) and Southeast Alaska (SEA), which host essential habitats for several ecologically, culturally, and commercially important species. Across this heterogeneous marine domain, phytoplankton are subject to dynamic ocean circulation patterns and atmosphere-ocean-land interactions, and their variability, in turn, influences marine food web structure and function. Regionalization based on phytoplankton biomass patterns along BC and SEA’s coastal and open oceans can be valuable in identifying pelagic habitats and representing a baseline for assessing future changes. We developed a two-step classification procedure, i.e., a Self-Organizing Maps (SOM) analysis followed by the affinity propagation clustering method, to define ten bioregions based on the seasonal climatology of high-resolution (300 m) Sentinel-3 surface chlorophyll-a data (a proxy for phytoplankton biomass), for the period 2016-2020. The classification procedure allowed high precision delineation of the ten bioregions, revealing separation between off-shelf bioregions and those in neritic waters. Consistent with the high-nutrient, low-chlorophyll regime, relatively low values of phytoplankton biomass (< 1 mg/m3) distinguished off-shelf bioregions, which also displayed, on average, more prominent autumn biomass peaks. In sharp contrast, neritic bioregions were highly productive (>> 1 mg/m3) and characterized by different phytoplankton dynamics. The spring phytoplankton bloom onset varied spatially and inter-annually, with substantial differences among bioregions. The proposed high-spatial-resolution regionalization constitutes a reference point for practical and more extensive implementation in understanding the spatial dynamics of the regional ecology, data-driven ocean observing systems, and objective regional management.