@article {5017,
	title = {Remote sensing for species distribution models: An illustration from a sentinel taxon of the world{\textquoteright}s driest ecosystem},
	journal = {Ecology},
	volume = {106},
	year = {2025},
	month = {02/2025},
	pages = {e70035},
	abstract = {<p>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 spp.) 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.</p>},
	keywords = {LTER-MCM, Antarctica, McMurdo Dry Valleys, microbial mats, remote sensing, species distribution modeling, species occurrence},
	issn = {0012-9658},
	doi = {10.1002/ecy.v106.210.1002/ecy.70035},
	url = {https://esajournals.onlinelibrary.wiley.com/doi/full/10.1002/ecy.70035},
	author = {Thapa-Magar, Khum B. and Eric R. Sokol and Michael N. Gooseff and Salvatore, Mark R. and John E. Barrett and Joseph S. Levy and Knightly, J. Paul and Power, Sarah N.}
}
@article {4942,
	title = {The distribution of surface soil moisture over space and time in eastern Taylor Valley, Antarctica},
	journal = {Remote Sensing},
	volume = {15},
	year = {2023},
	month = {06/2023},
	pages = {3170},
	abstract = {<p>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\&ndash;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 \&plusmn; 0.5\% gravimetric water content (GWC) across its non-fluvial landscape with ~23\% of the landscape experiencing an average GWC \&gt; 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.</p>},
	keywords = {LTER-MCM, Dry valleys, ecology, hydrology, remote sensing, soil moisture},
	doi = {10.3390/rs15123170},
	url = {https://www.mdpi.com/2072-4292/15/12/3170},
	author = {Salvatore, Mark R. and Barrett, John E. and Fackrell, Laura E. and Sokol, Eric R. and Levy, Joseph S. and Kuentz, Lily C. and Gooseff, Michael N. and Adams, Byron J. and Power, Sarah N. and Knightly, J. Paul and Matul, Haley M. and Szutu, Brian and Doran, Peter T.}
}
