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Abstract Primary production is fundamental to ecosystems, and in many extreme environments production is facilitated by microbial mats. Microbial mats are complex assemblages of photo- and heterotrophic microorganisms colonizing sediment and soil surfaces. These communities are the dominant producers of the McMurdo Dry Valleys, Antarctica, where they occupy lentic and lotic environments as well as intermittently wet soils. While the influence of microbial mats on stream nutrient dynamics and lake organic matter cycling is well documented, the influence of microbial mats on underlying soil is less well understood, particularly the effects of microbial mat nitrogen and carbon fixation. Taylor Valley soils occur across variable levels of inorganic phosphorus availability, with the Ross Sea drift containing four times that of the Taylor drifts, providing opportunities to examine how soil geochemistry influences microbial mats and the ecological functions they regulate. We found that inorganic phosphorus availability is positively correlated with microbial mat biomass, pigment concentration and nitrogen fixation potential. Additionally, our results demonstrate that dense microbial mats influence the ecological functioning of underlying soils by enriching organic carbon and total nitrogen stocks (two times higher). This work contributes to ongoing questions regarding the sources of energy fuelling soil food webs and the regional carbon balance in the McMurdo Dry Valleys. 

Abstract Antarctic soils are unique from those found nearly anywhere else on Earth yet can still harbor a broad diversity of microorganisms able to tolerate the challenging conditions typical of the continent. For these reasons, microbiologists have been drawn to Antarctica for decades. However, our understanding of which microbes thrive in Antarctic soils and how they to do so remains limited. To help resolve these knowledge gaps, we analyzed a collection of 200 archived Antarctic soils—from Livingston Island on the Antarctic Peninsula to Cape Hallett in northern Victoria Land. We analyzed the prokaryotic and fungal communities in these soils using both cultivation-independent marker gene sequencing and cultivation-dependent approaches (microbial isolation), paired with extensive soil geochemical analyses. Our cultivation-independent analyses indicate that colder, saltier, and drier soils harbor less diverse communities of bacteria and fungi, distinct from those found in soils with less challenging conditions. We also built a culture collection from a subset of these soils that encompasses more than 50 bacterial and fungal genera, including cold-tolerant organisms, such asCryobacteriumandCryomyces. By directly comparing the diversity of our cultured isolates against our cultivation-independent data, we show that many of the more abundant Antarctic taxa are not readily cultivated and highlight bacterial and fungal taxa that should be the focus of future cultivation efforts. Together, we hope that our collection of isolates, the comprehensive data compiled from the cultivation-independent analyses, and our geochemical analyses will serve as a community resource to accelerate the study of Antarctic soil microbes. 

In situ observed data are commonly used as species occurrence response variables in species distribution models. However, the use of remotely observed data from high‐resolution multispectral remote‐sensing images as a source of presence/absence data for species distribution models remains under‐developed. Here, we describe an ensemble species distribution model of black microbial mats "Nostoc" using presence/absence points derived from the unmixing of 4‐m resolution WorldView‐2 and WorldView‐3 images in the Lake Fryxell basin region of Taylor Valley, Antarctica. Environmental and topographical characteristics such as soil moisture, snow, elevation, slope, and aspect were used as predictor variables in our models. We demonstrate that we can build and run ensemble species distribution models using both dependent and independent variables derived from remote‐sensing data to generate spatially explicit habitat suitability maps. Snow and soil moisture were found to be the most important variables accounting for about 80% of the variation in the distribution of black mats throughout the Fryxell basin. This study highlights the potential contribution of high‐resolution remote‐sensing to species distribution modeling and informs new studies incorporating remotely derived species occurrences in species distribution models, especially in remote areas where access to in situ data is often limited. 

This data package offers comprehensive insights into Antarctic soil microbial diversity and composition. From 2003 to 2023, a total of 186 samples were collected from diverse locations spanning the Antarctic Peninsula to East Antarctica, representing a wide range of environmental gradients and climatic conditions. Soils were stored at -20°C to preserve their integrity for downstream analyses. This data package integrates cultivation-independent sequencing of prokaryotic and fungal communities alongside a robust cultivation-dependent culture collection to enable direct comparisons across microbial diversity assessment methods. Accompanying geochemical, physicochemical, and environmental parameters provide critical context for biogeographical analyses, offering a valuable resource for studying microbial adaptations and community dynamics in extreme Antarctic environments. 

Available soil moisture is thought to be the limiting factor for most ecosystem processes in the cold polar desert of the McMurdo Dry Valleys (MDVs) of Antarctica. Previous studies have shown that microfauna throughout the MDVs are capable of biological activity when sufficient soil moisture is available (~2–10% gravimetric water content), but few studies have attempted to quantify the distribution, abundance, and frequency of soil moisture on scales beyond that of traditional field work or local field investigations. In this study, we present our work to quantify the soil moisture content of soils throughout the Fryxell basin using multispectral satellite remote sensing techniques. Our efforts demonstrate that ecologically relevant abundances of liquid water are common across the landscape throughout the austral summer. On average, the Fryxell basin of Taylor Valley is modeled as containing 1.5 ± 0.5% gravimetric water content (GWC) across its non-fluvial landscape with ~23% of the landscape experiencing an average GWC > 2% throughout the study period, which is the observed limit of soil nematode activity. These results indicate that liquid water in the soils of the MDVs may be more abundant than previously thought, and that the distribution and availability of liquid water is dependent on both soil properties and the distribution of water sources. These results can also help to identify ecological hotspots in the harsh polar Antarctic environment and serve as a baseline for detecting future changes in the soil hydrological regime. 

ABSTRACT Accurately accounting for spectral structure in spectrometer data induced by instrumental chromaticity on scales relevant for detection of the 21-cm signal is among the most significant challenges in global 21-cm signal analysis. In the publicly available Experiment to Detect the Global Epoch of Reionization Signature low-band data set, this complicating structure is suppressed using beam-factor-based chromaticity correction (BFCC), which works by dividing the data by a sky-map-weighted model of the spectral structure of the instrument beam. Several analyses of these data have employed models that start with the assumption that this correction is complete. However, while BFCC mitigates the impact of instrumental chromaticity on the data, given realistic assumptions regarding the spectral structure of the foregrounds, the correction is only partial. This complicates the interpretation of fits to the data with intrinsic sky models (models that assume no instrumental contribution to the spectral structure of the data). In this paper, we derive a BFCC data model from an analytical treatment of BFCC and demonstrate using simulated observations that, in contrast to using an intrinsic sky model for the data, the BFCC data model enables unbiased recovery of a simulated global 21-cm signal from beam-factor chromaticity-corrected data in the limit that the data are corrected with an error-free beam-factor model.