<?xml version="1.0" encoding="UTF-8"?><xml><records><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Stone, Michael S.</style></author><author><style face="normal" font="default" size="100%">Salvatore, Mark R.</style></author><author><style face="normal" font="default" size="100%">Hilary A. Dugan</style></author><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author><author><style face="normal" font="default" size="100%">Peter T. Doran</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Measuring and modelling functional moat area in perennially ice-covered Lake Fryxell, Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">Arctic, Antarctic, and Alpine Research</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">Lake Fryxell</style></keyword><keyword><style  face="normal" font="default" size="100%">lake ice</style></keyword><keyword><style  face="normal" font="default" size="100%">McMurdo Dry Valleys</style></keyword><keyword><style  face="normal" font="default" size="100%">moat</style></keyword><keyword><style  face="normal" font="default" size="100%">NDWI</style></keyword><keyword><style  face="normal" font="default" size="100%">predictive model</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2024</style></year><pub-dates><date><style  face="normal" font="default" size="100%">10/2024</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.tandfonline.com/doi/full/10.1080/15230430.2024.2406626</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">56</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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 &amp;ldquo;moat&amp;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&amp;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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">1</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author><author><style face="normal" font="default" size="100%">Peter T. Doran</style></author><author><style face="normal" font="default" size="100%">Myers, Krista F.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Valley-floor snowfall in Taylor Valley, Antarctica, from 1995 to 2017: Spring, summer and autumn</style></title><secondary-title><style face="normal" font="default" size="100%">Antarctic Science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">automated weather station</style></keyword><keyword><style  face="normal" font="default" size="100%">camera</style></keyword><keyword><style  face="normal" font="default" size="100%">McMurdo Dry Valleys</style></keyword><keyword><style  face="normal" font="default" size="100%">snow cover</style></keyword><keyword><style  face="normal" font="default" size="100%">snow persistence</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2022</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2022</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.cambridge.org/core/product/identifier/S0954102022000256/type/journal_article</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">34</style></volume><pages><style face="normal" font="default" size="100%">325-335</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;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&lt;sup&gt;-1&lt;/sup&gt;, 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&lt;sup&gt;-1&lt;/sup&gt;) to decreasing snowfall (1 mm w.e. yr&lt;sup&gt;-1&lt;/sup&gt;), 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.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">4</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Chignell, Stephen M.</style></author><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author><author><style face="normal" font="default" size="100%">Howkins, Adrian</style></author><author><style face="normal" font="default" size="100%">Andrew G Fountain</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Research sites get closer to field camps over time: Informing environmental management through a geospatial analysis of science in the McMurdo Dry Valleys, Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">PLOS ONE</style></secondary-title><short-title><style face="normal" font="default" size="100%">PLoS ONE</style></short-title></titles><dates><year><style  face="normal" font="default" size="100%">2021</style></year><pub-dates><date><style  face="normal" font="default" size="100%">11/2021</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0257950</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">16</style></volume><pages><style face="normal" font="default" size="100%">e0257950</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;As in many parts of the world, the management of environmental science research in Antarctica relies on cost-benefit analysis of negative environmental impact versus positive scientific gain. Several studies have examined the environmental impact of Antarctic field camps, but very little work looks at how the placement of these camps influences scientific research. In this study, we integrate bibliometrics, geospatial analysis, and historical research to understand the relationship between field camp placement and scientific production in the McMurdo Dry Valleys of East Antarctica. Our analysis of the scientific corpus from 1907&amp;ndash;2016 shows that, on average, research sites have become less dispersed and closer to field camps over time. Scientific output does not necessarily correspond to the number of field camps, and constructing a field camp does not always lead to a subsequent increase in research in the local area. Our results underscore the need to consider the complex historical and spatial relationships between field camps and research sites in environmental management decision-making in Antarctica and other protected areas.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">11</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Acosta, Dimitri R.</style></author><author><style face="normal" font="default" size="100%">Peter T. Doran</style></author><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">GIS tool to predict photosynthetically active radiation in a Dry Valley</style></title><secondary-title><style face="normal" font="default" size="100%">Antarctic Science</style></secondary-title></titles><keywords><keyword><style  face="normal" font="default" size="100%">ArcMap</style></keyword><keyword><style  face="normal" font="default" size="100%">automated weather station</style></keyword><keyword><style  face="normal" font="default" size="100%">digital elevation model</style></keyword><keyword><style  face="normal" font="default" size="100%">ice-covered lakes</style></keyword><keyword><style  face="normal" font="default" size="100%">McMurdo Dry Valleys</style></keyword><keyword><style  face="normal" font="default" size="100%">R model</style></keyword><keyword><style  face="normal" font="default" size="100%">Taylor Valley</style></keyword></keywords><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">04/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.cambridge.org/core/journals/antarctic-science/article/gis-tool-to-predict-photosynthetically-active-radiation-in-a-dry-valley/BD0BE4FF6A8F3DAAF32D698797287078</style></url></web-urls></urls><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;Understanding primary productivity is a core research area of the National Science Foundation&amp;#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&amp;#39;s major lakes during the 2014&amp;ndash;15 and 2015&amp;ndash;16 field seasons. The average daily error ranges from 0.13 mol photons m&lt;sup&gt;-2&lt;/sup&gt; day&lt;sup&gt;-1&lt;/sup&gt; (0.6%) at Lake Fryxell to 3.8 mol photons m&lt;sup&gt;-2&lt;/sup&gt; day&lt;sup&gt;-1&lt;/sup&gt; (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%.&lt;/p&gt;</style></abstract></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>17</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Bergstrom, Anna J.</style></author><author><style face="normal" font="default" size="100%">Michael N. Gooseff</style></author><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author><author><style face="normal" font="default" size="100%">Peter T. Doran</style></author><author><style face="normal" font="default" size="100%">Cross, Julian M.</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">The seasonal evolution of albedo across glaciers and the surrounding landscape of Taylor Valley, Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">The Cryosphere</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2020</style></year><pub-dates><date><style  face="normal" font="default" size="100%">03/2020</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://www.the-cryosphere.net/14/769/2020/</style></url></web-urls></urls><volume><style face="normal" font="default" size="100%">14</style></volume><pages><style face="normal" font="default" size="100%">769-788</style></pages><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The McMurdo Dry Valleys (MDVs) of Antarctica are a polar desert ecosystem consisting of alpine glaciers, ice-covered lakes, streams, and expanses of vegetation-free rocky soil. Because average summer temperatures are close to 0&amp;thinsp;∘C, the MDV ecosystem in general, and glacier melt dynamics in particular, are both closely linked to the energy balance. A slight increase in incoming radiation or change in albedo can have large effects on the timing and volume of meltwater. However, the seasonal evolution or spatial variability of albedo in the valleys has yet to fully characterized. In this study, we aim to understand the drivers of landscape albedo change within and across seasons. To do so, a box with a camera, GPS, and shortwave radiometer was hung from a helicopter that flew transects four to five times a season along Taylor Valley. Measurements were repeated over three seasons. These data were coupled with incoming radiation measured at six meteorological stations distributed along the valley to calculate the distribution of albedo across individual glaciers, lakes, and soil surfaces. We hypothesized that albedo would decrease throughout the austral summer with ablation of snow patches and increasing sediment exposure on the glacier and lake surfaces. However, small snow events (&amp;lt;6&amp;thinsp;mm water equivalent) coupled with ice whitening caused spatial and temporal variability of albedo across the entire landscape. Glaciers frequently followed a pattern of increasing albedo with increasing elevation, as well as increasing albedo moving from east to west laterally across the ablation zone. We suggest that spatial patterns of albedo are a function of landscape morphology trapping snow and sediment, longitudinal gradients in snowfall magnitude, and wind-driven snow redistribution from east to west along the valley. We also compare our albedo measurements to the MODIS albedo product and found that overall the data have reasonable agreement. The mismatch in spatial scale between these two datasets results in variability, which is reduced after a snow event due to albedo following valley-scale gradients of snowfall magnitude. These findings highlight the importance of understanding the spatial and temporal variability in albedo and the close coupling of climate and landscape response. This new understanding of landscape albedo can constrain landscape energy budgets, better predict meltwater generation on from MDV glaciers, and how these ecosystems will respond to changing climate at the landscape scale.&lt;/p&gt;</style></abstract><issue><style face="normal" font="default" size="100%">3</style></issue></record><record><source-app name="Biblio" version="7.x">Drupal-Biblio</source-app><ref-type>32</ref-type><contributors><authors><author><style face="normal" font="default" size="100%">Myers, Madeline</style></author><author><style face="normal" font="default" size="100%">Peter T. Doran</style></author></authors></contributors><titles><title><style face="normal" font="default" size="100%">Spatiotemporal impact of snow on underwater photosynthetically active radiation in Taylor Valley, East Antarctica</style></title><secondary-title><style face="normal" font="default" size="100%">Department of Geology and Geophysics</style></secondary-title></titles><dates><year><style  face="normal" font="default" size="100%">2019</style></year><pub-dates><date><style  face="normal" font="default" size="100%">08/2019</style></date></pub-dates></dates><urls><web-urls><url><style face="normal" font="default" size="100%">https://digitalcommons.lsu.edu/gradschool_theses/4965</style></url></web-urls></urls><publisher><style face="normal" font="default" size="100%">Louisiana State University</style></publisher><pub-location><style face="normal" font="default" size="100%">Baton Rouge, LA</style></pub-location><volume><style face="normal" font="default" size="100%">M.S.</style></volume><language><style face="normal" font="default" size="100%">eng</style></language><abstract><style face="normal" font="default" size="100%">&lt;p&gt;The role of snow on underwater photosynthetically active radiation (UW PAR) in the McMurdo Dry Valleys (MDVs) has been understudied due to lack of a detailed snowfall record. Research has shown that a relationship between snow cover and UW PAR exists, but the extent has never been evaluated in great detail. Although annual snowfall values in the MDVs are low (3 to 50 mm water equivalent annually), trends of increasing snowfall on the continent under future warming conditions could lead to an increased role for snow in regulating UW PAR (and associated primary productivity). Here, I discuss evidence from the snowfall record, surface PAR, and UW PAR, of the influence of snowfall on UW PAR in the major lakes of Taylor Valley. This study aims to quantify the spatiotemporal impact of lake ice snow packs on UW PAR in Taylor Valley from field surveys, long-term UW PAR, and meteorological data. Lake Fryxell has the strongest seasonality to precipitation, which decreases inland. On average, Lake Fryxell also has the most days with snow cover on the lake ice. Lake Hoare is experiencing an increase in Fall snow persistence since the 2007 snow year. Snow less than 0.5 mm snow water equivalent (SWE) can suppress UW PAR by 40%. The calendar day that snow falls often determines whether phototrophs will switch from photosynthesis to respiration, which suggests the importance to seasonality in determining the impact of snow on photoautotrophs and lake-wide carbon budget.&lt;/p&gt;</style></abstract><work-type><style face="normal" font="default" size="100%">masters</style></work-type></record></records></xml>