01966nas a2200253   4500008004100000022001400041245010100055210006900156260001200225490000700237520119400244653001701438653001301455653002401468653000901492653000901501653002101510100002301531700002401554700002201578700002001600700002101620856007101641       2024                        eng d  a1523-043000aMeasuring and modelling functional moat area in perennially ice-covered Lake Fryxell, Antarctica0 aMeasuring and modelling functional moat area in perennially icec  c10/20240 v563 a<p>The perennially ice-covered lakes of the McMurdo Dry Valleys (MDVs), Antarctica, are an important reservoir of liquid water in an arid and largely frozen environment. During the austral summer, the margins of these ice covers melt, forming a &ldquo;moat&rdquo; of liquid water and thin ice, allowing exchange between lake waters and the atmosphere to occur and serving as an interface between lake, soil, and stream ecosystems. The size of these moats varies from year to year. Here, we have established the first published record of moat area changes at MDVs&rsquo; Lake Fryxell through time using manual traces of the moat as observed via satellite imagery. We have also tested a semi-automated approach for measuring moat area and found that it consistently underestimated the manual record, which we suspect may be due to the lower spatial resolution of images used in this versus the manual approach. Finally, we developed a predictive model based on readily available climate data, allowing moat area to be predicted beyond the limits of the satellite-based records. We found that functional moat area varies annually, potentially influencing ecosystem processes in the moats.</p>10aLake Fryxell10alake ice10aMcMurdo Dry Valleys10amoat10aNDWI10apredictive model1 aStone, Michael, S.1 aSalvatore, Mark, R.1 aDugan, Hilary, A.1 aMyers, Madeline1 aDoran, Peter, T.  uhttps://www.tandfonline.com/doi/full/10.1080/15230430.2024.240662601961nas a2200217   4500008004100000245010100041210006900142260001200211300001200223490000700235520124400242653003001486653001101516653002401527653001501551653002101566100002001587700002101607700002201628856009301650       2022                        eng d00aValley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: Spring, summer and autumn0 aValleyfloor snowfall in Taylor Valley Antarctica from 1995 to 20  c08/2022  a325-3350 v343 a<p>We present an analysis of the 20 year snowfall dataset in Taylor Valley and the results of a new snow cover monitoring study. Snowfall has been measured at four sites in Taylor Valley from 1995 to 2017. We focus on valley-floor snowfall when wind does not exceed 5 m s<sup>-1</sup>, and we exclude winter from our analysis due to poor data quality. Snowfall averaged 11 mm water equivalent (w.e.) from 1995 to 2017 across all stations and ranged from 1 to 58 mm w.e. Standard deviations ranged from 3 to 17 mm w.e., highlighting the strong interannual variability of snowfall in Taylor Valley. During spring and autumn there is a spatial gradient in snowfall such that the coast received twice as much snowfall as more central and inland stations. We identified a changepoint in 2007 from increasing snowfall (3 mm w.e. yr<sup>-1</sup>) to decreasing snowfall (1 mm w.e. yr<sup>-1</sup>), which coincides with a shift from decreasing temperature to no detectable temperature trend. Daily camera imagery from 2007 to 2017 augments the snowfall measurements. The camera imagery revealed a near tripling of the average number of days with snow cover from 37 days between 2006 and 2012 to 106 days with snow cover between 2012 and 2017.</p>10aautomated weather station10acamera10aMcMurdo Dry Valleys10asnow cover10asnow persistence1 aMyers, Madeline1 aDoran, Peter, T.1 aMyers, Krista, F.  uhttps://www.cambridge.org/core/product/identifier/S0954102022000256/type/journal_article02119nas a2200217   4500008004100000245007600041210006900117260001200186520131800198653001101516653003001527653002801557653002201585653002401607653001201631653001801643100002401661700002101685700002001706856017501726       2020                        eng d00aGIS tool to predict photosynthetically active radiation in a Dry Valley0 aGIS tool to predict photosynthetically active radiation in a Dry  c04/20203 a<p>Understanding primary productivity is a core research area of the National Science Foundation&#39;s Long-Term Ecological Research Network. This study presents the development of the GIS-based Topographic Solar Photosynthetically Active Radiation (T-sPAR) toolbox for Taylor Valley. It maps surface photosynthetically active radiation using four meteorological stations with ~20 years of data. T-sPAR estimates were validated with ground-truth data collected at Taylor Valley&#39;s major lakes during the 2014&ndash;15 and 2015&ndash;16 field seasons. The average daily error ranges from 0.13 mol photons m<sup>-2</sup> day<sup>-1</sup> (0.6%) at Lake Fryxell to 3.8 mol photons m<sup>-2</sup> day<sup>-1</sup> (5.8%) at Lake Hoare. We attribute error to variability in terrain and sun position. Finally, a user interface was developed in order to estimate total daily surface photosynthetically active radiation for any location and date within the basin. T-sPAR improves upon existing toolboxes and models by allowing for the inclusion of a statistical treatment of light attenuation due to cloud cover. The T-sPAR toolbox could be used to inform biological sampling sites based on radiation distribution, which could collectively improve estimates of net primary productivity, in some cases by up to 25%.</p>10aArcMap10aautomated weather station10adigital elevation model10aice-covered lakes10aMcMurdo Dry Valleys10aR model10aTaylor Valley1 aAcosta, Dimitri, R.1 aDoran, Peter, T.1 aMyers, Madeline  uhttps://www.cambridge.org/core/journals/antarctic-science/article/gis-tool-to-predict-photosynthetically-active-radiation-in-a-dry-valley/BD0BE4FF6A8F3DAAF32D698797287078