Remote Sensing Phenology of Antarctic Green and Red Snow Algae Using WorldView Satellites

Abstract

Snow algae are an important group of terrestrial photosynthetic organisms in Antarctica, where they mostly grow in low lying coastal snow fields. Reliable observations of Antarctic snow algae are difficult owing to the transient nature of their blooms and the logistics involved to travel and work there. Previous studies have used Sentinel 2 satellite imagery to detect and monitor snow algal blooms remotely, but were limited by the coarse spatial resolution and difficulties detecting red blooms. Here, for the first time, we use high-resolution WorldView multispectral satellite imagery to study Antarctic snow algal blooms in detail, tracking the growth of red and green blooms throughout the summer. Our remote sensing approach was developed alongside two Antarctic field seasons, where field spectroscopy was used to build a detection model capable of estimating cell density. Global Positioning System (GPS) tagging of blooms and in situ life cycle analysis was used to validate and verify our model output. WorldView imagery was then used successfully to identify red and green snow algae on Anchorage Island (Ryder Bay, 67°S), estimating peak coverage to be 9.48 × 104 and 6.26 × 104 m2, respectively. Combined, this was greater than terrestrial vegetation area coverage for the island, measured using a normalized difference vegetation index. Green snow algae had greater cell density and average layer thickness than red blooms (6.0 × 104 vs. 4.3 × 104 cells ml−1) and so for Anchorage Island we estimated that green algae dry biomass was over three times that of red algae (567 vs. 180 kg, respectively). Because the high spatial resolution of the WorldView imagery and its ability to detect red blooms, calculated snow algal area was 17.5 times greater than estimated with Sentinel 2 imagery. This highlights a scaling problem of using coarse resolution imagery and suggests snow algal contribution to net primary productivity on Antarctica may be far greater than previously recognized.

DNA Barcoding and ITS-tufA multi-local molecular phylogeny of nitrophilic alga Prasiola crispa growing on penguin guano at Larsemann Hills, Eastern Antarctica

“…Recent studies have mentioned the greenification of Antarctica due to climate warming, which leads to the growth of moss and green algae growth in the region (Klaus 2021, Antonello 2019, Shibistova et al 2017, Gray et al 2021. As compared to brown and red algae, green algae biodiversity is however, studied in Antarctica to a lesser extent.…”

Antarctica's vegetation in a changing climate

“…Under laboratory conditions, different snow algal species grow across a range of temperatures with various growth optima around 10°C is commonplace, however, our understanding of the physiology and genetics of these organisms isolated from Antarctica is still limited to a few experimental studies (e.g., Gálvez et al, 2021; Zhang et al, 2020). Initial estimates show that green snow algae blooms (Figure 4e) can cover up to 1.95 km 2 seasonally in the West Antarctic Peninsula (Gray et al, 2020), but with better and higher resolution satellite detection, the total value may be 17.5x greater (Gray et al, 2021). On one Antarctic maritime island, the area of the snow algae blooms was measured to be similar to that of other moss and lichen vegetation (1.57 × 10 5 vs. 1.37 × 10 5 m 2 ; Gray et al, 2020), meaning that although they are more spatially and temporally transient, the snow algae blooms do have a significant ecological role to play to local ecosystem primary productivity.…”

Multispectral Characteristics of Glacier Surface Facies (Chandra-Bhaga Basin, Himalaya, and Ny-Ålesund, Svalbard) through Investigations of Pixel and Object-Based Mapping Using Variable Processing Routines

“…Yellow and red edge did not add any significant improvement and could be easily replaced by green or red band. Gray et al [156] highlighted an interesting application of WV-2/3 imagery for mapping green and red snow algae. The imagery was converted to reflectance using the 6S radiative transfer model.…”