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Abstract Drylands are unique among terrestrial ecosystems in that they have a significant proportion of primary production facilitated by non‐vascular plants such as colonial cyanobacteria, moss, and lichens, i.e., biocrusts, which occur on and in the surface soil. Biocrusts inhabit all continents, including Antarctica, an increasingly dynamic continent on the precipice of change. Here, we describe in‐situ field surveying and sampling, remote sensing, and modeling approaches to assess the habitat suitability of biocrusts in the Lake Fryxell basin of Taylor Valley, Antarctica, which is the main site of the McMurdo Dry Valleys Long‐Term Ecological Research Program. Soils suitable for the development of biocrusts are typically wetter, less alkaline, and less saline compared to unvegetated soils. Using random forest models, we show that gravimetric water content, electrical conductivity, and snow frequency are the top predictors of biocrust presence and biomass. Areas most suitable for the growth of dense biocrusts are soils associated with seasonal snow patches. Using geospatial data to extrapolate our habitat suitability model to the whole basin predicts that biocrusts are present in 2.7 × 10⁵m²and contain 11–72 Mg of aboveground carbon, based on the 90% probability of occurrence. Our study illustrates the synergistic effect of combining field and remote sensing data for understanding the distribution and biomass of biocrusts, a foundational community in the carbon balance of this region. Extreme weather events and changing climate conditions in this region, especially those influencing snow accumulation and persistence, could have significant effects on the future distribution and abundance of biocrusts and therefore soil organic carbon storage in the McMurdo Dry Valleys. 

Patterns in foliar nitrogen (N) stable isotope ratios (δ15N) have been shown to reveal trends in terrestrial N cycles, including the identification of ecosystems where N deficiencies limit forest ecosystem productivity. However, there is a gap in our understanding of within-species variation and species-level response to environmental gradients or forest management. Our objective is to examine the relationship between site index, foliar %N, foliar δ15N and spectral reflectance for managed Douglas-fir (Pseudotsuga menziesii) and loblolly pine (Pinus taeda) plantations across their geographic ranges in the Pacific Northwest and the southeastern United States, respectively. Foliage was measured at 28 sites for reflectance using a handheld spectroradiometer, and further analyzed for δ15N and N concentration. Unlike the prior work for grasslands and shrubland species, our results show that foliar δ15N and foliar %N are not well correlated for these tree species. However, multiple linear regression models suggest a strong predictive ability of spectroscopy data to quantify foliar δ15N, with some models explaining more than 65% of the variance in the δ15N. Additionally, moderate to strong explanations of variance were found between site index and foliar δ15N (R2 = 0.49) and reflectance and site index (R2 = 0.84) in the Douglas-fir data set. The development of relationships between foliar spectral reflectance, δ15N and measures of site productivity provides the first step toward mapping canopy δ15N for these managed forests with remote sensing.