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Abstract 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 -1 , 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 -1 ) to decreasing snowfall (1 mm w.e. yr -1 ), 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. 

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 1907–2016 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. 

Abstract Understanding primary productivity is a core research area of the National Science Foundation'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's major lakes during the 2014–15 and 2015–16 field seasons. The average daily error ranges from 0.13 mol photons m -2 day -1 (0.6%) at Lake Fryxell to 3.8 mol photons m -2 day -1 (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%. 

Abstract. The McMurdo Dry Valleys (MDVs) of Antarctica are a polar desertecosystem consisting of alpine glaciers, ice-covered lakes, streams, andexpanses of vegetation-free rocky soil. Because average summer temperaturesare close to 0 ∘C, theMDV ecosystem in general, and glacier melt dynamics in particular, are both closely linked to the energy balance. A slightincrease in incoming radiation or change in albedo can have large effects onthe timing and volume of meltwater. However, the seasonal evolution orspatial variability of albedo in the valleys has yet to fully characterized.In this study, we aim to understand the drivers of landscape albedo changewithin and across seasons. To do so, a box with a camera, GPS, andshortwave radiometer was hung from a helicopter that flew transects four to fivetimes a season along Taylor Valley. Measurements were repeated over threeseasons. These data were coupled with incoming radiation measured at sixmeteorological stations distributed along the valley to calculate thedistribution of albedo across individual glaciers, lakes, and soilsurfaces. We hypothesized that albedo would decrease throughout the australsummer with ablation of snow patches and increasing sediment exposure on theglacier and lake surfaces. However, small snow events (<6 mm waterequivalent) coupled with ice whitening caused spatial and temporalvariability of albedo across the entire landscape. Glaciers frequentlyfollowed a pattern of increasing albedo with increasing elevation, as well asincreasing albedo moving from east to west laterally across the ablationzone. We suggest that spatial patterns of albedo are a function of landscapemorphology trapping snow and sediment, longitudinal gradients in snowfallmagnitude, and wind-driven snow redistribution from east to west alongthe valley. We also compare our albedo measurements to the MODIS albedo productand found that overall the data have reasonable agreement. The mismatch inspatial scale between these two datasets results in variability, which isreduced after a snow event due to albedo following valley-scale gradients ofsnowfall magnitude. These findings highlight the importance of understandingthe spatial and temporal variability in albedo and the close coupling ofclimate and landscape response. This new understanding of landscape albedocan constrain landscape energy budgets, better predict meltwater generationon from MDV glaciers, and how these ecosystems will respond to changingclimate at the landscape scale.