The natural variability and climate change response in phytoplankton phenology

摘要

Large areas of the world’s oceans experience a significant seasonal cycle in phytoplankton biomass. Variability in the phenology of these phytoplankton blooms affect ecosystem dynamics with implications for carbon export production and food availability at higher trophic levels. Climate change is expected to alter phytoplankton seasonality through changes to the underlying physical drivers controlling bloom timing. This thesis focusses on the drivers of contemporary variability and climate change-driven trends in phytoplankton phenology. Satellite-derived chlorophyll data (GlobColour) are used to examine phenological characteristics on a global scale. This dataset is complimented by remotely sensed photosynthetically active radiation (PAR; MODIS), net heat flux (remotely sensed and reanalysis products) and Argo float-derived mixed layer depth datasets in addition to global biogeochemical model output.Four bloom timing metrics are developed to quantify the timing of bloom initiation and termination in a consistent manner. The advantages and limitations of each metric are discussed in the context of the required criteria for a suitable metric definition. The choice of metric definition is based on the performance of the metrics against these criteria.The impact of missing data in the time series on the accuracy of the bloom timing metrics is investigated using the global biogeochemical model NOBM. It is found that missing data cause errors of approximately 30, 15 and 50 days in the date of bloom initiation, peak and termination respectively. The exact cause and implications for phenological studies of these errors is discussed.The physical drivers of interannual variability are examined using global datasets of mixed layer depth, net heat flux and mean mixed layer PAR. The date the net heat flux becomes positive is seen to be a strong predictor for the onset of the subpolar spring bloom, especially in the North Atlantic. This finding is the first to support the critical turbulence hypothesis over Sverdrup’s critical depth theory using satellite observations on a global scale. Physical drivers are only weakly related to interannual variability in bloom timing in the subtropics. The reasons for these relationships and other potential drivers of bloom timing are discussed.Finally, the climate change-driven trends in phytoplankton phenology are investigated using a suite of global biogeochemical models. The ability of the models to capture contemporary seasonality is discussed. The climate change response is found to be strongest at higher latitudes and the phenological changes are consistent with longer periods of strong stratification and earlier onset of ocean warming. Furthermore, it is found that using higher temporal resolution may enable the earlier detection of climate change-driven trends but only at high latitudes.