Remote sensing reveals Antarctic green snow algae as important terrestrial carbon sink

Unraveling the mystery of antibiotic resistance genes in green and red Antarctic snow

Antarctic snow is a thriving habitat for a diverse array of complex microorganisms, and can present in different colors due to algae blooms. However, the potential role of Antarctic snow as reservoirs for antibiotic resistance genes (ARGs) has not been studied. Using metagenomic sequencing, we studied ARGs in green-snow and red-snow on the Fildes Peninsula, Antarctica. Alpha and beta diversities of ARGs, as well as co-occurrence between ARGs and bacteria were assessed. The results showed that a total of 525 ARGs conferring resistance to 30 antibiotic classes were detected across the samples, with half of the ARGs presented in all samples. Green-snow exhibited a higher number of ARGs compared to red-snow. The most abundant ARGs conferring resistance to commonly used antibiotics, including disinfecting agents and antiseptics, peptide, isoniazid, MLS, fluoroquinolone, aminocoumarin, etc. Multidrug resistance genes stood out as the most diverse and abundant, with antibiotic efflux emerging as the dominant resistance mechanism. Interestingly, the composition of ARGs in green-snow markedly differed from that in red-snow, highlighting distinct ARG profiles. Beta-diversity partitioning showed a higher contribution of nestedness for ARG's variation in green-snow, while higher contribution of turnover in red-snow. Furthermore, the co-occurrence analysis between ARGs and bacteria unveiled intricate relationships, indicating that certain ARGs may have multiple potential hosts. The observed differences in co-occurrence networks between green-snow and red-snow suggested distinct host relationships between ARGs and bacteria in these colored snows. Given the increasing appearance of the colored snow around the world due to the climate change, the results shed light on the mystery and potential implication of ARGs in green and red Antarctic snow.

Antarctic snow algae: unraveling the processes underlying microbial community assembly during blooms formation

BACKGROUND AND AIMS

At the West Antarctic Peninsula, snow algae blooms are composed of complex microbial communities dominated by green microalgae and bacteria. During their progression, the assembly of these microbial communities occurs under harsh environmental conditions and variable nutrient content due to fast snow melting. To date, it is still unclear what are the ecological mechanisms governing the composition and abundance of microorganisms during the formation of snow algae blooms. In this study, we aim to examine the main ecological mechanisms governing the assembly of snow algae blooms from early stages to colorful stages blooms.

METHODS

The composition of the microbial communities within snow algae blooms was recorded in the West Antarctic Peninsula (Isabel Riquelme Islet) during a 35-day period using 16S rRNA and 18S rRNA metabarcoding. In addition, the contribution of different ecological processes to the assembly of the microbial community was quantified using phylogenetic bin-based null model analysis.

RESULTS

Our results showed that alpha diversity indices of the eukaryotic communities displayed a higher variation during the formation of the algae bloom compared with the bacterial community. Additionally, in a macronutrients rich environment, the content of nitrate, ammonium, phosphate, and organic carbon did not play a major role in structuring the community. The quantification of ecological processes showed that the bacterial community assembly was governed by selective processes such as homogenous selection. In contrast, stochastic processes such as dispersal limitation and drift, and to a lesser extent, homogenous selection, regulate the eukaryotic community.

CONCLUSIONS

Overall, our study highlights the differences in the microbial assembly between bacteria and eukaryotes in snow algae blooms and proposes a model to integrate both assembly processes. Video Abstract.

Future carbon storages of ecosystem based on land use change and carbon sequestration practices in a large economic belt

Assessments of ecosystem carbon storage are needed to form the scientific basis for carbon policies. Due to lack of data, there are few accurate, large-scale, and long-term predictions of ecosystem carbon storage. This study used the Distributed Land-Use Change Prediction (DLUCP) model with ten socioeconomic and two climate change scenarios for a total of 20 combinations that take into account population increase, technology innovation, climate change, and Grain for Green Project to make high-resolution predictions of land use change in the Yangtze River Economic Belt. Low and high carbon sequestration practices were considered to predict future carbon densities. Land use change data, carbon densities data, and the InVEST model were used to predict changes in ecosystem carbon storage from now to 2070. The results show a slight increase (1.88-4.17%) in carbon storage in the study area only based on land use change. Grain for Green Project has the largest impact on carbon storage among population increase, technology innovation, climate scenarios, and Grain for Green Project, which increases carbon storage by 4.17%. After the implementation of carbon sequestration practices, there is an increase in carbon storages from 28.51 to 56.77% in the study area from now to 2070, and increasing carbon storages of forest in each stream and carbon storage of cropland in downstream are efficient ways to achieve carbon neutralization.

The snow alga Chloromonas kaweckae sp. nov. (Volvocales, Chlorophyta) causes green surface blooms in the high tatras (Slovakia) and tolerates high irradiance

Seasonally slowly melting mountain snowfields are populated by extremophilic microalgae. In alpine habitats, high-light sensitive, green phytoflagellates are usually observed in subsurface layers deeper in the snowpack under dim conditions, while robust orange to reddish cyst stages can be seen exposed on the surface. In this study, uncommon surface green snow was investigated in the High Tatra Mountains (Slovakia). The monospecific community found in the green surface bloom consisted of vegetative Chloromonas cells (Volvocales, Chlorophyta). Molecular data demonstrated that the field sample and the strain isolated and established from the bloom were conspecific, and they represent a new species, Chloromonas kaweckae sp. nov., which is described based on the morphology of the vegetative cells and asexual reproduction and on molecular analyses of the strain. Cells of C. kaweckae accumulated approximately 50% polyunsaturated fatty acids, which is advantageous at low temperatures. In addition, this new species performed active photosynthesis at temperatures close to the freezing point showed a light compensation point of 126 ± 22 μmol photons · m-2  · s-1 and some signs of photoinhibition at irradiances greater than 600 μmol photons · m-2  · s-1 . These data indicate that the photosynthetic apparatus of C. kaweckae could be regarded as adapted to relatively high light intensities, otherwise unusual for most flagellate stages of snow algae.

Performance and validation of water surface temperature estimates from Landsat 8 of the Itaipu Reservoir, State of Paraná, Brazil

Studies on water surface temperature (WST) from thermal infrared remote sensing are still incipient in Brazil, and for many water resources, they do not exist. Many algorithms have been developed to estimate surface temperature in satellite images. There are also many difficulties in implementing these algorithms due to their complexity, especially in free software, which restricts the satisfactory processing of these data by users of the technique. Thus, this work aimed to validate an algorithm used to estimate land surface temperature (LST) when applied to the surface of inland water bodies. Water surface temperature estimates (WSTe) were generated from Itaipu State of Paraná (PR) reservoir, Brazil, calculated from Landsat 8 - TIRS satellite images (WSTs) and water surface temperature data from 37 in situ stations (WSTi). A linear regression model of the WSTe was generated in 60% of the samples and its validation with the remaining 40%, subject to prior evaluation of some statistical indicators. The model was considered significant since the coefficient of determination (r²) was 0.90 (95% of confidence), root mean square deviation (RMSD) 0.8 °C, Willmott Index (d) = 0.97, and Nash-Sutcliffe efficiency coefficient (NSE) = 0.89. The methodology used to extract WSTs from the Python QGIS plugin was relatively quick to apply, easy to understand, and had a better performance of the estimates than those presented in the literature review.

Exopolysaccharides from Marine Microbes: Source, Structure and Application

The unique living environment of marine microorganisms endows them with the potential to produce novel chemical compounds with various biological activities. Among them, the exopolysaccharides produced by marine microbes are an important factor for them to survive in these extreme environments. Up to now, exopolysaccharides from marine microbes, especially from extremophiles, have attracted more and more attention due to their structural complexity, biodegradability, biological activities, and biocompatibility. With the development of culture and separation methods, an increasing number of novel exopolysaccharides are being found and investigated. Here, the source, structure and biological activities of exopolysaccharides, as well as their potential applications in environmental restoration fields of the last decade are summarized, indicating the commercial potential of these versatile EPS in different areas, such as food, cosmetic, and biomedical industries, and also in environmental remediation.

Sampling a gradient of red snow algae bloom density reveals novel connections between microbial communities and environmental features

Snow algae blooms and associated microbial communities play large roles in snow ecosystem processes. Patterns and mechanisms underpinning snow algae bloom spatial distribution and associated microbial community assembly dynamics are poorly understood. Here we examine associations of microbial communities and environmental measures between/within snow algae blooms. Snows from the Cascade Mountains and the Rocky Mountains (USA) were collected from medial (M), peripheral (P), and adjacent (A) zones of red snow algae blooms. Medial snow shows increased levels of pollen, lower oxidation–reduction potential, decreased algal and increased bacterial richness, and increased levels of potassium when compared to A and P within the same bloom. Between the Cascade and Rocky Mountains, fungal communities are distinct but bacterial and algal communities show little differentiation. A weighted OTU co-expression analysis (WOCNA) explores OTU modules and their differential correlation with environmental features, suggesting certain subcommunities may be altered by ecological patterns. Individual OTU interaction networks (fungi and bacteria) show high levels of connectivity compared to networks based on the red snow alga Sanguina nivaloides, which underscores associative differences between algal dominated networks and other taxa.

Antarctic Hairgrass Rhizosphere Microbiomes: Microscale Effects Shape Diversity, Structure, and Function

The rhizosphere microbiome of the native Antarctic hairgrass Deschampsia antarctica from the central maritime Antarctic was investigated using 16S RNA metagenomics and compared to those of the second native Antarctic plant Colobanthus quitensis and closely related temperate D. cespitosa. The rhizosphere microbial communities of D. antarctica and D. cespitosa had high taxon richness, while that of C. quitensis had markedly lower diversity. The majority of bacteria in the rhizosphere communities of the hairgrass were affiliated to Proteobacteria, Bacteroidetes, and Actinobacteria. The rhizosphere of C. quitensis was dominated by Actinobacteria. All microbial communities included high proportions of unique amplicon sequence variants (ASVs) and there was high heterogeneity between samples at the ASV level. The soil parameters examined did not explain this heterogeneity. Bacteria belonging to Actinobacteria, Bacteroidetes, and Proteobacteria were sensitive to fluctuations in the soil surface temperature. The values of the United Soil Surface Temperature Influence Index (UTII, I^t_i) showed that variations in most microbial communities from Galindez Island were associated with microscale variations in temperature. Metabolic predictions in silico using PICRUSt 2.0, based on the taxonomically affiliated part of the microbiomes, showed similarities with the rhizosphere community of D. antarctica in terms of the predicted functional repertoire. The results obtained indicate that these communities are involved in the primary processes of soil development (particularly the degradation of lignin and lignin-derived compounds) in the central maritime Antarctic and may be beneficial for the growth of Antarctic vascular plants. However, due to the limitations associated with interpreting PICRUSt 2.0 outputs, these predictions need to be verified experimentally.

Water quality monitoring with Sentinel-2 and Landsat-8 satellites during the 2021 volcanic eruption in La Palma (Canary Islands)

In this study, seawater quality was monitored with high-resolution satellite imagery during the 2021 volcanic eruption (September-December) on La Palma Island (Spain), the longest recorded in the history of the island, and the most destructive in the last century in Europe. The Sentinel-2A/B twin satellites and Landsat-8 satellite were jointly used as an optical constellation, which allowed us to successfully characterize the short- and medium-term evolution of the new lava delta and subsequent impact on the seawater. Robust atmospheric and sunglint correction approaches were applied to thoroughly quantify the environmental changes caused on the adjacent coastal waters. The cloud and volcanic ash coverage remained very high over the coast during the event, so restricted information with 14 images (45% of the total scenes) was retrieved from the multi-sensor approach. Nevertheless, the availability of pre-, syn-, and post-eruption satellite products allowed us to map and detect the main water quality variations in the marine environment. On the one hand, during the eruption, a change in the properties of the water quality was observed, with a markedly increased turbidity on the western side of the island near the new lava delta due to the deposition of volcanic ash and material. On the other hand, chlorophyll-a concentration did not significantly increase, algal blooms were not observed, and oligotrophic conditions were not swiftly altered towards eutrophic conditions. This information offered an excellent opportunity to characterize the emplacement of the new lava delta and its impact on the marine environment in La Palma. The present multi-sensor strategy is an excellent opportunity to highlight the potential of remote sensing technology as a relevant and powerful tool for future hazard monitoring and assessment during catastrophes and for a better interpretation of their impact on the marine environment.

Antarctic biological soil crusts surface reflectance patterns from landsat and sentinel-2 images

The remote sensing techniques must be used to obtain long-term information in remote areas, like the Antarctic continent, to monitor the environmental productivity and its changes. The aim of this work was to analyze the surface reflectance profile patterns for the Antarctic biological soil crusts (algae, lichens, and mosses) in an area of Nelson Island (South Shetland Islands, maritime Antarctic), calculated from Landsat and Sentinel-2 images to identify its similarities and differences due to targets, sensors and acquired date. The surface reflectance values for Antarctic biological soil crusts are similar for those observed for biological soil crusts in other Earth extreme environments, like deserts. In Landsat images, the differences among biological soil crusts surface reflectance were identified at visible and near-infrared wavelengths and for Sentinel-2 images, the differences occur at visible, red-edge and shortwave infrared wavelengths, showing the feasibility of using surface reflectance products to identify these different crusts, despite its inherent pixel spectral mixture. Long-term biophysical parameters from such crusts as retrieved from orbital data is not possible due to very low cloud-free images over the Antarctic, which prevents building a consistent surface reflectance time-series which covers all biological soil crusts growth season.

Black carbon footprint of human presence in Antarctica

Black carbon (BC) from fossil fuel and biomass combustion darkens the snow and makes it melt sooner. The BC footprint of research activities and tourism in Antarctica has likely increased as human presence in the continent has surged in recent decades. Here, we report on measurements of the BC concentration in snow samples from 28 sites across a transect of about 2,000 km from the northern tip of Antarctica (62°S) to the southern Ellsworth Mountains (79°S). Our surveys show that BC content in snow surrounding research facilities and popular shore tourist-landing sites is considerably above background levels measured elsewhere in the continent. The resulting radiative forcing is accelerating snow melting and shrinking the snowpack on BC-impacted areas on the Antarctic Peninsula and associated archipelagos by up to 23 mm water equivalent (w.e.) every summer.

In-situ generation of In2O3 nanoparticles inside In[Co(CN)6] quasi-metal-organic-framework nanocubes for efficient electroreduction of CO2 to formate

Three-dimensional (3D) network structure of metal-organic framework (MOF) can accommodate outstanding electrocatalysis performances, but always collapse during the conversion to active materials or applications process. How to maintain the 3D network when producing active species is of great importance for full application of MOF. Herein, a new MOF material, In[Co(CN)₆] (In-Co PBA) nanocubes, are firstly synthesized. Through a controlled low-temperature deligandation process, the In-Co PBA nanocubes are transformed to a novel In₂O₃@In-Co PBA quasi-MOF nanocubes, which basically retain the 3D porous structure of PBA but with in situ generated In₂O₃ nanoparticles inside. When used as CO₂RR electrocatalyst, such a novel cubic composite structure exhibits excellent performances with faradaic efficiency of 85% for formate at a potential of -0.96 V and with current density of 31.5 mA·cm^-2 at -1.32 V, surpassing most of the reported indium-based catalysts. The excellent performance can be attributed to the special composite structure, which provides not only active sites by In₂O₃ nanoparticles to catalyze CO₂RR, but also the 3D porous framework by quasi-MOF to accelerate gaseous exchange and electrolyte permeation and prevent the electrode choking. This work offers a new strategy for the design of post-transition metal catalysts and the structure design of quasi-MOF.

Similar heterotrophic communities but distinct interactions supported by red and green-snow algae in the Antarctic Peninsula

Snow algae are predicted to expand in polar regions due to climate warming, which can accelerate snowmelt by reducing albedo. Green snow frequently occurs near penguin colonies, and red snow distributes widely along ocean shores. However, the mechanisms underpinning the assemblage of algae and heterotrophs in colored snow remain poorly characterized. We investigated algal, bacterial, and fungal communities and their interactions in red and green snows in the Antarctic Peninsula using a high-throughput sequencing method. We found distinct algal community structure in red and green snows, and the relative abundance of dominant taxa varied, potentially due to nutrient status differences. Contrastingly, red and green snows exhibited similar heterotrophic communities (bacteria and fungi), whereas the relative abundance of fungal pathogens was substantially higher in red snow by 3.8-fold. Red snow exhibited a higher network complexity, indicated by a higher number of nodes and edges. Red snow exhibited a higher proportion of negative correlations among heterotrophs (62.2% vs 3.4%) and stronger network stability, suggesting the red-snow network is more resistant to external disturbance. Our study revealed that the red snow microbiome exhibits a more stable microbial network than the green snow microbiome.

Functional filtering and random processes affect the assembly of microbial communities of snow algae blooms at Maritime Antarctic

The increasing temperatures at the West Antarctic Peninsula (Maritime Antarctic) could lead to a higher occurrence of snow algal blooms which are ubiquitous events that change the snow coloration, reducing albedo and in turn exacerbating melting. However, there is a limited understanding of snow algae blooms biodiversity, composition, and their functional profiles, especially in one of the world's areas most affected by climate change. In this study we used 16S rRNA and 18S rRNA metabarcoding, and shotgun metagenomics to assess the diversity, composition, and functional potential of the snow algae blooms bacterial and eukaryotic communities at three different sites of Maritime Antarctic, between different colors of the algae blooms and between seasonal and semi-permanent snowfields. We tested the hypothesis that the functional potential of snow algae blooms is conserved despite a changing taxonomic composition. Furthermore, we determined taxonomic co-occurrence patterns of bacteria and eukaryotes and assessed the potential for the exchange of metabolites among bacterial taxa. Here, we tested the prediction that there are co-occurring taxa within snow algae whose biotic interactions are marked by the exchange of metabolites. Our results show that the composition of snow algae blooms vary significantly among sites. For instance, a higher abundance of fungi and protists were detected in Fildes Peninsula compared with Doumer Island and O'Higgins. Likewise, the composition varied between snow colors and snow types. However, the functional potential varied only among sampling sites with a higher abundance of genes involved in tolerance to environmental stress at O'Higgins. Co-occurrence patterns of dominant bacterial genera such as Pedobacter, Polaromonas, Flavobacterium and Hymenobacter were recorded, contrasting the absence of co-occurring patterns displayed by Chlamydomonadales algae with other eukaryotes. Finally, genome-scale metabolic models revealed that bacteria within snow algae blooms likely compete for resources instead of forming cooperative communities.

Global Warming: Is It (Im)Possible to Stop It? The Systems Thinking Approach

For some time, there has been a slow but gradual rise in the average temperature of the entire globe, a “global warming”, in fact, the result of human and natural processes that have been producing this phenomenon for decades. Since they are not directly perceived by individuals, these processes and their effects have been ignored for a long time, or at least not considered to be immediately harmful and dangerous. Global warming does not depend so much on solar radiation as it does on the greenhouse effect deriving from the continuous emission, by human activities and natural events, of greenhouse gases that accumulate in the atmosphere and form a barrier to the dispersion of heat produced by solar radiation. A good number of models exists to explain how global warming is produced, which are technical in nature and consider the production of greenhouse gases as the most important cause; however, they do not always analyze and justify the reasons for such emissions. Following the logic, language and methods of Senge’s systems thinking, the paper aims to present a general model, the GEAM—qualitative in nature, but rational and coherent—for highlighting the interacting factors that give rise to and maintain global warming. This model constitutes a reference framework to identify possible “strategic areas” within which to identify man-made “artificial” and “natural” factors that can control the phenomenon and to order the countless ideas and interventions that different nations carry out individually to control global warming. The model presented is qualitative in nature and does not allow immediate calculations or forecasts to be performed. However, it could guide in-depth scientific research in generating accurate forecasts and simulation using the tools of systems dynamics. In conclusion, understanding how global warming is created and if and how it could be controlled is the aim of this work. Finally, I want to note that the purpose of this work is not to analyze the technical aspects of the phenomenon of global warming, or to deepen the measures and actions to contrast it, but to provide a “general model of description and understanding” of the phenomenon using logic and language of the Systems Thinking Approach (according to Peter’s Senge and Piero Mella), with the aim of highlighting three fundamental strategic areas for countering the phenomenon and four uncontrollable phenomena, triggered by global warming itself, which can make strategic control difficult. Furthermore, I highlight the role played by the world population, understood both quantitatively as a number and qualitatively as a level of economic development, in the production of global warming. Lastly, I observe how the different strategic actions that nations can, indeed must, implement to stem global warming are systematically interconnected and interacting; however, these interactions can produce unknown effects and consequences that must be carefully researched and evaluated—encouraged, if positive, reduced or eliminated if negative.

The Antarctic Moss Pohlia nutans Genome Provides Insights Into the Evolution of Bryophytes and the Adaptation to Extreme Terrestrial Habitats

The Antarctic continent has extreme natural environment and fragile ecosystem. Mosses are one of the dominant floras in the Antarctic continent. However, their genomic features and adaptation processes to extreme environments remain poorly understood. Here, we assembled the high-quality genome sequence of the Antarctic moss (Pohlia nutans) with 698.20 Mb and 22 chromosomes. We found that the high proportion of repeat sequences and a recent whole-genome duplication (WGD) contribute to the large size genome of P. nutans when compared to other bryophytes. The genome of P. nutans harbors the signatures of massive segmental gene duplications and large expansions of gene families, likely facilitating neofunctionalization. Genomic characteristics that may support the Antarctic lifestyle of this moss comprise expanded gene families involved in phenylpropanoid biosynthesis, unsaturated fatty acid biosynthesis, and plant hormone signal transduction. Additional contributions include the significant expansion and upregulation of several genes encoding DNA photolyase, antioxidant enzymes, flavonoid biosynthesis enzymes, possibly reflecting diverse adaptive strategies. Notably, integrated multi-omic analyses elucidate flavonoid biosynthesis may function as the reactive oxygen species detoxification under UV-B radiation. Our studies provide insight into the unique features of the Antarctic moss genome and their molecular responses to extreme terrestrial environments.

Continuous and Synoptic Assessment of Indian Inland Waters for Harmful Algae Blooms

Cyanobacterial Harmful Algal Blooms (CyanoHABs) are progressively becoming a major water quality, socioeconomic, and health hazard worldwide. In India, there are frequent episodes of severe CyanoHABs, which are left untreated due to a lack of awareness and monitoring infrastructure, affecting the economy of the country gravely. In this study, for the first time, we present a country-wide analysis of CyanoHABs in India by developing a novel interactive cloud-based dashboard called "CyanoKhoj" in Google Earth Engine (GEE) which uses Sentinel-3 Ocean and Land Colour Instrument (OLCI) remotely sensed datasets. The main goal of this study was to showcase the utility of CyanoKhoj for rapid monitoring and discuss the widespread CyanoHABs problems across India. We demonstrate the utility of Cyanokhoj by including select case studies of lakes and reservoirs geographically spread across five states: Bargi and Gandhisagar Dams in Madhya Pradesh, Hirakud Reservoir in Odisha, Ukai Dam in Gujarat, Linganamakki Reservoir in Karnataka, and Pulicat Lake in Tamil Nadu. These sites were studied from September to November 2018 using CyanoKhoj, which is capable of near-real-time monitoring and country-wide assessment of CyanoHABs. We used CyanoKhoj to prepare spatiotemporal maps of Chlorophyll-a (Chl-a) content and Cyanobacterial Cell Density (CCD) to study the local spread of the CyanoHABs and their phenology in these waterbodies. A first-ever all-India CCD map is also presented for the year 2018, which highlights the spatial spread of CyanoHABs throughout the country (32 large waterbodies across India with severe bloom: CCD>2,500,000). Results indicate that CyanoHABs are most prevalent in nutrient-rich waterbodies prone to industrial and other nutrient-rich discharges. A clear temporal evolution of the blooms showed that they are dominant during the post-monsoon season (September-October) when the nutrient concentrations in the waterbodies are at their peak, and they begin to decline towards winter (November-December). CyanoKhoj is an open-source tool that can have a significant broader impact in mapping CyanoHABs not only throughout cyanobacteria data-scarce India, but on a global level using archived and future Sentinel-3A/B OLCI data.

Photosynthetic adaptation to polar life: Energy balance, photoprotection and genetic redundancy

The persistent low temperature that characterize polar habitats combined with the requirement for light for all photoautotrophs creates a conundrum. The absorption of too much light at low temperature can cause an energy imbalance that decreases photosynthetic performance that has a negative impact on growth and can affect long-term survival. The goal of this review is to survey the mechanism(s) by which polar photoautotrophs maintain cellular energy balance, that is, photostasis to overcome the potential for cellular energy imbalance in their low temperature environments. Photopsychrophiles are photosynthetic organisms that are obligately adapted to low temperature (0⁰- 15 °C) but usually die at higher temperatures (≥20 °C). In contrast, photopsychrotolerant species can usually tolerate and survive a broad range of temperatures (5⁰- 40 °C). First, we summarize the basic concepts of excess excitation energy, energy balance, photoprotection and photostasis and their importance to survival in polar habitats. Second, we compare the photoprotective mechanisms that underlie photostasis and survival in aquatic cyanobacteria and green algae as well as terrestrial Antarctic and Arctic plants. We show that polar photopsychrophilic and photopsychrotolerant organisms attain energy balance at low temperature either through a regulated reduction in the efficiency of light absorption or through enhanced capacity to consume photosynthetic electrons by the induction of O₂ as an alternative electron acceptor. Finally, we compare the published genomes of three photopsychrophilic and one photopsychrotolerant alga with five mesophilic green algae including the model green alga, Chlamydomonas reinhardtii. We relate our genomic analyses to photoprotective mechanisms that contribute to the potential attainment of photostasis. Finally, we discuss how the observed genomic redundancy in photopsychrophilic genomes may confer energy balance, photoprotection and resilience to their harsh polar environment. Primary production in aquatic, Antarctic and Arctic environments is dependent on diverse algal and cyanobacterial communities. Although mosses and lichens dominate the Antarctic terrestrial landscape, only two extant angiosperms exist in the Antarctic. The identification of a single 'molecular key' to unravel adaptation of photopsychrophily and photopsychrotolerance remains elusive. Since these photoautotrophs represent excellent biomarkers to assess the impact of global warming on polar ecosystems, increased study of these polar photoautotrophs remains essential.

An investigation of traffic density changes inside Wuhan during the COVID-19 epidemic with GF-2 time-series images

In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restriction between cities and provinces, few studies focus on the effect of transportation control inside the city due to the lack of the measurement and available data in Wuhan. Since the public transports have been shut down in the beginning of city lockdown, the change of traffic density is a good indicator to reflect the intracity population flow. Therefore, in this paper, we collected time-series high-resolution remote sensing images with the resolution of 1 m acquired before, during and after Wuhan lockdown by GF-2 satellite. Vehicles on the road were extracted and counted for the statistics of traffic density to reflect the changes of human transmissions in the whole period of Wuhan lockdown. Open Street Map was used to obtain observation road surfaces, and a vehicle detection method combing morphology filter and deep learning was utilized to extract vehicles with the accuracy of 62.56%. According to the experimental results, the traffic density of Wuhan dropped with the percentage higher than 80%, and even higher than 90% on main roads during city lockdown; after lockdown lift, the traffic density recovered to the normal rate. Traffic density distributions also show the obvious reduction and increase throughout the whole study area. The significant reduction and recovery of traffic density indicates that the lockdown policy in Wuhan show effectiveness in controlling human transmission inside the city, and the city returned to normal after lockdown lift.

An investigation of traffic density changes inside Wuhan during the COVID-19 epidemic with GF-2 time-series images

In order to mitigate the spread of COVID-19, Wuhan was the first city to implement strict lockdown policy in 2020. Even though numerous researches have discussed the travel restriction between cities and provinces, few studies focus on the effect of transportation control inside the city due to the lack of the measurement and available data in Wuhan. Since the public transports have been shut down in the beginning of city lockdown, the change of traffic density is a good indicator to reflect the intracity population flow. Therefore, in this paper, we collected time-series high-resolution remote sensing images with the resolution of 1 m acquired before, during and after Wuhan lockdown by GF-2 satellite. Vehicles on the road were extracted and counted for the statistics of traffic density to reflect the changes of human transmissions in the whole period of Wuhan lockdown. Open Street Map was used to obtain observation road surfaces, and a vehicle detection method combing morphology filter and deep learning was utilized to extract vehicles with the accuracy of 62.56%. According to the experimental results, the traffic density of Wuhan dropped with the percentage higher than 80%, and even higher than 90% on main roads during city lockdown; after lockdown lift, the traffic density recovered to the normal rate. Traffic density distributions also show the obvious reduction and increase throughout the whole study area. The significant reduction and recovery of traffic density indicates that the lockdown policy in Wuhan show effectiveness in controlling human transmission inside the city, and the city returned to normal after lockdown lift.

Applications of unmanned aerial vehicles in Antarctic environmental research

Antarctica plays a fundamental role in the Earth's climate, oceanic circulation and global ecosystem. It is a priority and a scientific challenge to understand its functioning and responses under different scenarios of global warming. However, extreme environmental conditions, seasonality and isolation hampers the efforts to achieve a comprehensive understanding of the physical, biological, chemical and geological processes taking place in Antarctica. Here we present unmanned aerial vehicles (UAVs) as feasible, rapid and accurate tools for environmental and wildlife research in Antarctica. UAV surveys were carried out on Deception Island (South Shetland Islands) using visible, multispectral and thermal sensors, and a water sampling device to develop precise thematic ecological maps, detect anomalous thermal zones, identify and census wildlife, build 3D images of geometrically complex geological formations, and sample dissolved chemicals (< 0.22 µm) waters from inaccessible or protected areas.

Green algae (Viridiplantae) in sediments from three lakes on Vega Island, Antarctica, assessed using DNA metabarcoding

BACKGROUND

Vega Island is located off the eastern tip of the Antarctic Peninsula (Maritime Antarctica), in the Weddell Sea. In this study, we used metabarcoding to investigate green algal DNA sequence diversity present in sediments from three lakes on Vega Island (Esmeralda, Copépodo, and Pan Negro Lakes).

METHODS AND RESULTS

Total DNA was extracted and the internal transcribed spacer 2 region of the nuclear ribosomal DNA was used as a DNA barcode for molecular identification. Green algae were represented by sequences representing 78 taxa belonging to Phylum Chlorophyta, of which 32% have not previously been recorded from Antarctica. Sediment from Pan Negro Lake generated the highest number of DNA reads (11,205), followed by Esmeralda (9085) and Copépodo (1595) Lakes. Esmeralda Lake was the richest in terms of number of taxa (59), with Copépodo and Pan Negro Lakes having 30 taxa each. Bray-Curtis dissimilarity among lakes was high (~ 0.80). The Order Chlamydomonadales (Chlorophyceae) gave the highest contribution in terms of numbers of taxa and DNA reads in all lakes. The most abundant taxon was Chlorococcum microstigmatum.

CONCLUSIONS

The study confirms the utility of DNA metabarcoding in assessing potential green algal diversity in Antarctic lakes, generating new Antarctic records.

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

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.

Antarctic ecosystems in transition - life between stresses and opportunities

Important findings from the second decade of the 21st century on the impact of environmental change on biological processes in the Antarctic were synthesised by 26 international experts. Ten key messages emerged that have stakeholder-relevance and/or a high impact for the scientific community. They address (i) altered biogeochemical cycles, (ii) ocean acidification, (iii) climate change hotspots, (iv) unexpected dynamism in seabed-dwelling populations, (v) spatial range shifts, (vi) adaptation and thermal resilience, (vii) sea ice related biological fluctuations, (viii) pollution, (ix) endangered terrestrial endemism and (x) the discovery of unknown habitats. Most Antarctic biotas are exposed to multiple stresses and considered vulnerable to environmental change due to narrow tolerance ranges, rapid change, projected circumpolar impacts, low potential for timely genetic adaptation, and migration barriers. Important ecosystem functions, such as primary production and energy transfer between trophic levels, have already changed, and biodiversity patterns have shifted. A confidence assessment of the degree of 'scientific understanding' revealed an intermediate level for most of the more detailed sub-messages, indicating that process-oriented research has been successful in the past decade. Additional efforts are necessary, however, to achieve the level of robustness in scientific knowledge that is required to inform protection measures of the unique Antarctic terrestrial and marine ecosystems, and their contributions to global biodiversity and ecosystem services.

Cysts of the Snow Alga Chloromonas krienitzii (Chlorophyceae) Show Increased Tolerance to Ultraviolet Radiation and Elevated Visible Light

Melting mountainous snowfields are populated by extremophilic microorganisms. An alga causing orange snow above timberline in the High Tatra Mountains (Poland) was characterised using multiple methods examining its ultrastructure, genetics, life cycle, photosynthesis and ecophysiology. Based on light and electron microscopy and ITS2 rDNA, the species was identified as Chloromonas krienitzii (Chlorophyceae). Recently, the taxon was described from Japan. However, cellular adaptations to its harsh environment and details about the life cycle were so far unknown. In this study, the snow surface population consisted of egg-shaped cysts containing large numbers of lipid bodies filled presumably with the secondary carotenoid astaxanthin. The outer, spiked cell wall was shed during cell maturation. Before this developmental step, the cysts resembled a different snow alga, Chloromonas brevispina. The remaining, long-lasting smooth cell wall showed a striking UV-induced blue autofluorescence, indicating the presence of short wavelengths absorbing, protective compounds, potentially sporopollenin containing polyphenolic components. Applying a chlorophyll fluorescence assay on intact cells, a significant UV-A and UV-B screening capability of about 30 and 50%, respectively, was measured. Moreover, intracellular secondary carotenoids were responsible for a reduction of blue-green light absorbed by chloroplasts by about 50%. These results revealed the high capacity of cysts to reduce the impact of harmful UV and high visible irradiation to the chloroplast and nucleus when exposed at alpine snow surfaces during melting. Consistently, the observed photosynthetic performance of photosystem II (evaluated by fluorometry) showed no decline up to 2100 μmol photons m-2 s-1. Cysts accumulated high contents of polyunsaturated fatty acids (about 60% of fatty acids), which are advantageous at low temperatures. In the course of this study, C. krienitzii was found also in Slovakia, Italy, Greece and the United States, indicating a widespread distribution in the Northern Hemisphere.