The recent trend of global warming has exerted a disproportionately strong influence on the Eurasian land surface, causing a steady decline in snow cover extent over the Himalayan-Tibetan Plateau region. Here we show that this loss of snow is undermining winter convective mixing and causing stratification of the upper layer of the Arabian Sea at a much faster rate than predicted by global climate models. Over the past four decades, the Arabian Sea has also experienced a profound loss of inorganic nitrate. In all probability, this is due to increased denitrification caused by the expansion of the permanent oxygen minimum zone and consequent changes in nutrient stoichiometries. These exceptional changes appear to be creating a niche particularly favorable to the mixotroph, Noctiluca scintillans which has recently replaced diatoms as the dominant winter, bloom forming organism. Although Noctiluca blooms are non-toxic, they can cause fish mortality by exacerbating oxygen deficiency and ammonification of seawater. As a consequence, their continued range expansion represents a significant and growing threat for regional fisheries and the welfare of coastal populations dependent on the Arabian Sea for sustenance.

The conventional use of optically determined 1% of surface photosynthetically available radiation (PAR) depth (Z_1%^PAR, λ = 400–700 nm) as a metric for the euphotic zone depth (Z_eu) has been a matter of debate for several decades because of frequent inconsistencies with the base of euphotic zone determined biologically, that is, the compensation depth (Z_c). In this study, we attempt to reconcile between optical and biological determinants of the euphotic zone through the use of a large data set of coincidental profiles of downwelling irradiance and primary production. These measurements cover open ocean waters in the tropics, subtropics, temperate regions, and from two time‐series stations, the Hawaii Ocean Time‐series (HOT) and the Bermuda Atlantic Time‐series Study (BATS). We report that, at least for these measurements, Z_1%^PAR is too shallow (by 14.1%) compared to Z_c, while Z_0.1%^PAR is too deep (by 32.7%). Further, the irradiance at Z_c (i.e., the compensation irradiance, I_c) varies by a factor of more than five, but its ratio to surface irradiance is relatively stable. In general, I_c corresponds to 0.48 ± 0.23% of surface PAR, or 0.87 ± 0.40% of surface usable solar radiation (USR, for λ = 400–560 nm), or 1.50 ± 0.67% of surface downwelling irradiance at 490 nm. These results suggest that Z_0.5%^PAR, or Z_0.9%^USR, or Z_1.5%⁴⁹⁰ could be promising alternatives to bridge the optical and biological determinants of the euphotic zone depths for waters in the open ocean at low to middle latitudes.

The accurate retrieval of chlorophyll-a concentration (Chl-a) from ocean color satellite data is extremely challenging in turbid, optically complex coastal waters. Ariake Bay in Japan is a turbid semi-enclosed bay of great socio-economic significance, but it suffers from serious water quality problems, particularly due to red tide events. Chl-a derived from the MODerate resolution Imaging Spectroradiometer (MODIS) sensor on satellite Aqua in Ariake Bay was investigated, and it was determined that the causes of the errors were from inaccurate atmospheric correction and inappropriate in-water algorithms. To improve the accuracy of MODIS remote sensing reflectance (Rrs) in the blue and green bands, a simple method was adopted using in situ Rrs data. This method assumes that the error in MODIS Rrs(547) is small, and MODIS Rrs(412) can be estimated from MODIS Rrs(547) using a linear relation between in situ Rrs(412) and Rrs(547). We also showed that the standard MODIS Chl-a algorithm, OC3M, underestimated Chl-a, which was mostly due to water column turbidity. A new empirical switching algorithm was generated based on the relationship between in situ Chl-a and the blue-to-green band ratio, max(Rrs(443), Rrs(448)/Rrs(547), which was the same as the OC3M algorithm. The criterion of Rrs(667) of 0.005 sr⁻¹ was used to evaluate the extent of turbidity for the switching algorithm. The results showed that the switching algorithm performed better than OC3M, and the root mean square error (RMSE) of estimated Chl-a decreased from 0.414 to 0.326. The RMSE for MODIS Chl-a using the recalculated Rrs and the switching algorithm was 0.287, which was a significant improvement from the RMSE of 0.610, which was obtained using standard MODIS Chl-a. Finally, the accuracy of our method was tested with an independent dataset collected by the local Fisheries Research Institute, and the results revealed that the switching algorithm with the recalculated Rrs reduced the RMSE of MODIS Chl-a from 0.412 of the standard to 0.335.

The partial pressure of carbon dioxide (pCO₂) was surveyed across the Amazon River plume and the surrounding western tropical North Atlantic Ocean (15–0°N, 43–60°W) during three oceanic expeditions (May–June 2010, September–October 2011, and July 2012). The survey timing was chosen according to previously described temporal variability in plume behavior due to changing river discharge and winds. In situ sea surface pCO₂ and air‐sea CO₂ flux exhibited robust linear relationships with sea surface salinity (SSS; 15 < SSS < 35), although the relationships differed among the surveys. Regional distributions of pCO₂ and CO₂ flux were estimated using SSS maps from high‐resolution ocean color satellite‐derived (MODIS‐Aqua) diffuse attenuation coefficient at 490 nm (K_d490) during the periods of study. Results confirmed that the plume is a net CO₂ sink with distinctive temporal variability: the strongest drawdown occurred during the spring flood (−2.39 ± 1.29 mmol m⁻² d⁻¹ in June 2010), while moderate drawdown with relatively greater spatial variability was observed during the transitional stages of declining river discharge (−0.42 ± 0.76 mmol m⁻² d⁻¹ in September–October 2011). The region turned into a weak source in July 2012 (0.26 ± 0.62 mmol m⁻² d⁻¹) when strong CO₂ uptake in the mid‐plume was overwhelmed by weak CO₂ outgassing over a larger area in the outer plume. Outgassing near the mouth of the river was observed in July 2012. Our observations draw attention to the importance of assessing the variable impacts of biological activity, export, and air‐sea gas exchange before estimating regional CO₂ fluxes from salinity distributions alone.

Shoreline changes are of great importance for evaluating the interaction between humans and ecosystems in coastal areas. They serve as a useful metric for assessing the ecological costs of socioeconomic developmental activities along the coast. In this paper, we present an assessment of shoreline changes along the eastern coast of mainland China from ~1990 to 2019 by applying a novel method recently developed by us. This method which we call the Nearest Distance Method (NDM) is used to make a detailed assessment of shorelines delineated from Landsat Thematic Mapper (TM) and Operational Land Imager (OLI) images. The results indicate a dramatic decline in natural shorelines that correspond to the rapid increase in the construction of artificial shorelines, driven by China’s economic growth. Of the entire coast of mainland China, the biggest change occurred along the Bohai Sea, where artificial shorelines expanded from 42.4% in ~1990 to 81.5% in 2019. Over this period, this study indicates that China lost > 60% of its biological shorelines, a trend that is especially worrisome because these include areas that were once biologically diverse and extremely rich. As anticipated, shoreline losses were greatest where regions of low economic value had been transformed to areas of higher economic value. Overall, this influence of human activities on shorelines in China is unprecedented. The repercussions of these changes on ecosystems, and the susceptibility of new shoreline developments to population growth and sea-level rise, need to be assessed urgently before additional changes are effected.