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Abstract The Western Antarctic Peninsula is undergoing rapid environmental change. Regional warming is causing increased glacial meltwater discharge, but the ecological impact of this meltwater over large spatiotemporal scales is not well understood. Here, we leverage 20 years of remote sensing data, reanalysis products, and field observations to assess the effects of sea surface glacial meltwater on phytoplankton biomass and highlight its importance as a key environmental driver for this region’s productive ecosystem. We find a strong correlation between meltwater and phytoplankton chlorophyll-a across multiple time scales and datasets. We attribute this relationship to nutrient fertilization by glacial meltwater, with potential additional contribution from surface ocean stabilization associated with sea-ice presence. While high phytoplankton biomass typically follows prolonged winter sea-ice seasons and depends on the interplay between light and nutrient limitation, our results indicate that the positive effects of increased glacial meltwater on phytoplankton communities likely mitigate the negative impact of sea-ice loss in this region in recent years. Our findings underscore the critical need to consider glacial meltwater as a key ecological driver in polar coastal ecosystems. 

Glacial meltwater is an important environmental variable for ecosystem dynamics along the biologically productive Western Antarctic Peninsula (WAP) shelf. This region is experiencing rapid change, including increasing glacial meltwater discharge associated with the melting of land ice. To better understand the WAP environment and aid ecosystem forecasting, additional methods are needed for monitoring and quantifying glacial meltwater for this remote, sparsely sampled location. Prior studies showed that sea surface glacial meltwater (SSGM) has unique optical characteristics which may allow remote sensing detection via ocean color data. In this study, we develop a first-generation model for quantifying SSGM that can be applied to both spaceborne (MODIS-Aqua) and airborne (PRISM) ocean color platforms. In addition, the model was prepared and verified with one of the more comprehensivein-situstable oxygen isotope datasets compiled for the WAP region. The SSGM model appears robust and provides accurate predictions of the fractional contribution of glacial meltwater to seawater when compared within-situdata (r= 0.82, median absolute percent difference = 6.38%, median bias = −0.04), thus offering an additional novel method for quantifying and studying glacial meltwater in the WAP region. 

Abstract The size distribution of suspended particles influences several processes in aquatic ecosystems, including light propagation, trophic interactions, and biogeochemical cycling. The shape of the particle size distribution (PSD) is commonly modeled as a single‐slope power law in oceanographic studies, which can be used to further estimate the relative contributions of different particle size classes to particle number, area, and volume concentration. We use a data set of 168 high size‐resolution PSD measurements in Arctic oceanic waters to examine variability in the shape of the PSD over the particle diameter range 0.8 to 120 μm. An average value of −3.6 ± 0.33 was obtained for the slope of a power law fitted over this size range, consistent with other studies. Our analysis indicates, however, that this model has significant limitations in adequately parameterizing the complexity of the PSD, and thus performs poorly in predicting the relative contributions of different size intervals such as those based on picoplankton, nanoplankton, and microplankton size classes. Similarly, median particle size was also generally a poor indicator of these size class contributions. Our results suggest that alternative percentile diameters derived from the cumulative distribution functions of particle number, cross‐sectional area, and volume concentration may provide better metrics to capture the overall shape of the PSD and to quantify the contributions of different particle size classes.