Characterizing the spatial and temporal dynamics of phytoplankton phenology in the British Columbia and Southeast Alaska coastal oceans using satellite ocean colour data

The coastal waters of British Columbia (B.C.) support diverse food webs and provide habitats for various species of Pacific salmon, which are of vital importance to the regional economy and for First Nations culture and subsistence. To effectively monitor marine environmental health of these regions and any changes thereof, it is necessary to employ ecological indicators to provide objective and quantitative metrics upon which to evaluate the state of the ecosystem and their response to environmental and climatic perturbation. Phytoplankton phenology is an important ecological indicator that characterises the timing of annually occurring phytoplankton growing periods and has been typically synthesized into a set of indices encompassing the timing, duration, and magnitude of bloom events. Observing changes in phytoplankton phenology in this region requires vast spatial coverage and short temporal frequencies, which is achieved through ocean colour satellite imagery. Here, we evaluate the performance of the merged multi-sensor ocean colour chlorophyll-a products, GlobColour and OC-CCI, in the British Columbia coastal waters via a statistical match-up analysis and a qualitative analysis to determine whether the data reflects the region's large-scale seasonal trends and latitudinal dynamics. Using the chlorophyll-a product that is best suited to our purpose, we then derive a suite of phenological indices on a pixel-by-pixel basis, which is used to partition the study area into phenological bioregions using an objective, unsupervised partition strategy (Hierarchical Agglomerative Clustering method). The delineated bioregions are then used to describe region-specific phytoplankton phenological patterns associated with bloom magnitude, frequency, duration, and timing. The interannual variability of spring bloom initiation was evaluated considering interactions with environmental variables, sea surface temperature anomaly and the El Nino Southern Oscillation index. The GlobColour interpolated chlorophyll-a product revealed sound statistical results (r2 = 0.63, slope = 0.88, bias = 0.81, MdAD = 1.69, RMSE = 0.37, n = 797) and demonstrated the expected seasonal and local dynamics for this region, and average concentrations within ranges reported for satellite-derived observations. The derived phenology indices showed longitudinal gradients. From east to west, bloom initiation along the coast was observed in spring, gradually progressing to fall dominated blooms further offshore, with peak chlorophyll concentrations of 38.5mg.m-3 and 3mg.m-3, respectively. The spatial patterns of number of blooms per pixel has shown to be inversely correlated to average bloom duration, with lower number of blooms having longer durations and vice versa. Four coherent bioregions were identified over the study region with distinctive phytoplankton phenological properties: two coastal regions, one shelf region and an offshore region. We found that early spring blooms were associated with a positive SST anomaly and El Nino conditions. Conversely, average or late spring blooms occurred in years where there was a negative SST anomaly and La Nina conditions. Furthermore, the relationship between spring bloom initiation and principal bloom initiation was evaluated, and we found that when there is a later spring bloom initiation we can expect a later principal bloom initiation, and vice versa. The findings of this study can help better inform fisheries management and conservation programs, by being able to infer the timing of spring bloom initiation in relation to SST anomalies and ENSO index.

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