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Abstract: We present an inverse modeling approach for reconstructing the effective thermal conductivity of snow on a daily basis using air temperature, ground temperature and snow depth measurements. The method is applied to four sites in Alaska. To validate the method we used measured snow densities and snow water equivalents. The modeled thermal conductivities of snow for the two interior Alaska sites have relatively low values and reach their maximum near the end of the snow season, while the conductivities at the two sites on the Alaskan North Slope are higher and reach their maximum earlier in the snow season. We show that the reconstructed daily thermal conductivities allow for more accurate modeling of ground...
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Executive Summary: We provide an analysis of Sonoran Desert water network connectivity to inform managers of current conditions for target wildlife and how the connectivity will change as the landscape becomes more water limited.Climate change is expected to lead to fragmentation of the network, increasing coalescence distance by 8% and reducing the persistence and overall number of waters on the landscape. Identification of key water sites, ranked by network connectivity metrics, are presented in Appendix B. Wetland number under our scenario of water limitation will decline by 43% reducing network resilience.Anurans and Caudates, although varying in ability to disperse, generally experienced reduced connectivity...


    map background search result map search result map Quantitative and Predictive Analysis: Landscape Connectivity of Isolated Waters for Wildlife in the Sonoran Desert The Effect of Snow: How to Better Model Ground Surface Temperatures The Effect of Snow: How to Better Model Ground Surface Temperatures Quantitative and Predictive Analysis: Landscape Connectivity of Isolated Waters for Wildlife in the Sonoran Desert