Astaxanthin (3,3′-dihydroxy-β,β-carotene-4,4′-dione), a high-value ketocarotenoid with a broad range of applications in food, feed, nutraceutical, and pharmaceutical industries, has been gaining great attention from science and the public in recent years. The green microalgae Haematococcus pluvialis and Chlorella zofingiensis represent the most promising producers of natural astaxanthin. Although H. pluvialis possesses the highest intracellular astaxanthin content and is now believed to be a good producer of astaxanthin, it has intrinsic shortcomings such as slow growth rate, low biomass yield, and a high light requirement. In contrast, C. zofingiensis grows fast phototrophically, heterotrophically and mixtrophically, is easy to be cultured and scaled up both indoors and outdoors, and can achieve ultrahigh cell densities. These robust biotechnological traits provide C. zofingiensis with high potential to be a better organism than H. pluvialis for mass astaxanthin production. This review aims to provide an overview of the biology and industrial potential of C. zofingiensis as an alternative astaxanthin producer. The path forward for further expansion of the astaxanthin production from C. zofingiensis with respect to both challenges and opportunities is also discussed.

Abstract. Snow depth is one of the key physical parameters for understanding land surface energy balance, soil thermal regime, water cycle, and assessing water resources from local community to regional industrial water supply. Previous studies by using in situ data are mostly site specific; data from satellite remote sensing may cover a large area or global scale, but uncertainties remain large. The primary objective of this study is to investigate spatial variability and temporal change in snow depth across the Eurasian continent. Data used include long-term ground-based measurements from 1814 stations. Spatially, long-term (1971Spatially, long-term ( -2000 mean annual snow depths of >20 cm were recorded in northeastern European Russia, the Yenisei River basin, Kamchatka Peninsula, and Sakhalin. Annual mean and maximum snow depth increased by 0.2 and 0.6 cm decade −1 from 1966 through 2012. Seasonally, monthly mean snow depth decreased in autumn and increased in winter and spring over the study period. Regionally, snow depth significantly increased in areas north of 50 • N. Compared with air temperature, snowfall had greater influence on snow depth during November through March across the former Soviet Union. This study provides a baseline for snow depth climatology and changes across the Eurasian continent, which would significantly help to better understanding climate system and climate changes on regional, hemispheric, or even global scales.

The active layer plays a key role in geomorphic, hydrologic, and biogeochemical processes in permafrost regions. We conducted a systematic investigation of active layer thickness (ALT) in northeastern Qinghai‐Tibetan Plateau by using ground‐penetrating radar (GPR) with 100 and 200 MHz antennas. We used mechanical probing, pit, and soil temperature profiles for evaluating ALT derived from GPR. The results showed that GPR is competent for detecting ALT, and the error was ±0.08 m at common midpoint co‐located sites. Considerable spatial variability of ALT owing to variation in elevation, peat thickness, and slope aspect was found. The mean ALT was 1.32 ± 0.29 m with a range from 0.81 to 2.1 m in Eboling Mountain. In Yeniu Gou, mean ALT was 2.72 ± 0.88 m and varied from 1.07 m on the north‐facing slope to 4.86 m around the area near the lower boundary of permafrost. ALT in peat decreased with increasing elevation at rates of −1.31 m/km (Eboling Mountain) and −2.1 m/km (Yeniu Gou), and in mineral soil in Yeniu Gou, the rate changed to −4.18 m/km. At the same elevation, ALT on the south‐facing slope was about 0.8 m thicker than that on the north‐facing slopes, while the difference was only 0.18 m in peat‐covered area. Within a 100 m2 area with a local elevation difference of 0.8 m, ALT varied from 0.68 m to 1.25 m. Both field monitoring and modeling studies on spatial ALT variations require rethinking of the current strategy and comprehensive design.

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