OC4-SO: A New Chlorophyll-a Algorithm for the Western Antarctic Peninsula Using Multi-Sensor Satellite Data

Climate change is associated with higher phytoplankton biomass and longer blooms in the West Antarctic Peninsula

The Antarctic Peninsula (West Antarctica) marine ecosystem has undergone substantial changes due to climate-induced shifts in atmospheric and oceanic temperatures since the 1950s. Using 25 years of satellite data (1998-2022), this study presents evidence that phytoplankton biomass and bloom phenology in the West Antarctic Peninsula are significantly changing as a response to anthropogenic climate change. Enhanced phytoplankton biomass was observed along the West Antarctic Peninsula, particularly in the early austral autumn, resulting in longer blooms. Long-term sea ice decline was identified as the main driver enabling phytoplankton growth in early spring and autumn, in parallel with a recent intensification of the Southern Annular Mode (2010-ongoing), which was observed to influence regional variability. Our findings contribute to the understanding of the complex interplay between environmental changes and phytoplankton responses in this climatically key region of the Southern Ocean and raise important questions regarding the far-reaching consequences that these ecological changes may have on global carbon sequestration and Antarctic food webs in the future.

Physical-biological drivers modulating phytoplankton seasonal succession along the Northern Antarctic Peninsula

The Northern Antarctic Peninsula (NAP) shows shifts in phytoplankton distribution and composition along its warming marine ecosystems. However, despite recent efforts to mechanistically understand these changes, little focus has been given to the phytoplankton seasonal succession, remaining uncertainties regarding to distribution patterns of emerging taxa along the NAP. To fill this gap, we collected phytoplankton (pigment and microscopy analysis) and physico-chemical datasets during spring and summer (November, February and March) of 2013/2014 and 2014/2015 off the NAP. Satellite measurements (sea surface temperature, sea ice concentration and chlorophyll-a) were used to extend the temporal coverage of analysis associated with the in situ sampling. We improved the quantification and distribution pattern of emerging taxa, such as dinoflagellates and cryptophytes, and described a contrasting seasonal behavior and distinct fundamental niche between centric and pennate diatoms. Cryptophytes and pennate diatoms preferentially occupied relatively shallower mixing layers compared with centric diatoms and dinoflagellates, suggesting differences between these groups in distribution and environment occupation over the phytoplankton seasonal succession. Under colder conditions, negative sea surface temperature anomalies were associated with positive anomalies of sea ice concentration and duration. Therefore, based on sea ice-phytoplankton growth relationship, large phytoplankton biomass accumulation was expected during the spring/summer of 2013/2014 and 2014/2015 along the NAP. However, there was a decoupling between sea ice concentration/duration and phytoplankton biomass, characterizing two seasonal periods of low biomass accumulation (negative chlorophyll-a anomalies), associated with the top-down control in the region. These results provide an improved mechanistic understanding on physical-biological drivers modulating phytoplankton seasonal succession along the Antarctic coastal waters.

An intercomparison of models predicting growth of Antarctic krill (Euphausia superba): The importance of recognizing model specificity

Antarctic krill (Euphausia superba) is a key species of the Southern Ocean, impacted by climate change and human exploitation. Understanding how these changes affect the distribution and abundance of krill is crucial for generating projections of change for Southern Ocean ecosystems. Krill growth is an important indicator of habitat suitability and a series of models have been developed and used to examine krill growth potential at different spatial and temporal scales. The available models have been developed using a range of empirical and mechanistic approaches, providing alternative perspectives and comparative analyses of the key processes influencing krill growth. Here we undertake an intercomparison of a suite of the available models to understand their sensitivities to major driving variables. This illustrates that the results are strongly determined by the model structure and technical characteristics, and the data on which they were developed and validated. Our results emphasize the importance of assessing the constraints and requirements of individual krill growth models to ensure their appropriate application. The study also demonstrates the value of the development of alternative modelling approaches to identify key processes affecting the dynamics of krill. Of critical importance for modelling the growth of krill is appropriately assessing and accounting for differences in estimates of food availability resulting from alternative methods of observation. We suggest that an intercomparison approach is particularly valuable in the development and application of models for the assessment of krill growth potential at circumpolar scales and for future projections. As another result of the intercomparison, the implementations of the models used in this study are now publicly available for future use and analyses.