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Warner College of Natural Resources

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These digital collections include the materials from the Mongolia Project and datasets from the Warner College of Natural Resources.

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Browsing Warner College of Natural Resources by Subject "aridity"

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    Satellite-based assessments on regional summer and winter conditions triggering massive livestock loss (Dzud) in Mongolia
    (Colorado State University. Libraries, 2015-06) Kang, Sinkyu, author; Jang, Keunchang, author; Lkhamsuren, Bolorerdene, author; Nutag Action and Research Institute, publisher
    Dzud is a term referring either to conditions when melting snow refreezes to form an icy layer covering the grass, or to unusually heavy snow falls in Eurasian arid and semi-arid regions. Under dzud condition, animals cannot obtain food under snow or ice layer, which sometimes results in a dzud disaster, i.e. massive livestock kills. It has been recognized that the dzud disaster is directly induced by the harsh winter conditions but often influenced by drought in the previous summer. In this study, a data-intensive reanalysis on regional determinants of dzud disaster was conducted for more than 300 soums (an administrative unit equivalent with county in US) in Mongolia. Various climatic, hydrological, and vegetation variables were developed from satellite remote sensing (RS) data, which includes daily mean air temperature, dew-point temperature, and evapotranspiration, monthly precipitation, and 16-day NDVI from 2003 to 2010. Annual livestock census data were collected for every soum in Mongolia. Each variable was standardized to z-score and utilized for stepwise multiple regression analysis to identify factors statistically significant for explaining soum-level livestock mortality. The regression models were successfully constructed for two-third of total soums. Considerable spatial variability in the determinants of livestock mortality were found across soums in Mongolia. As the primary determinants, summer NDVI and dryness equally explained 22% of the soum mortality, while 33% and 16% of the mortality were explained with winter temperature and precipitation, respectively. Spatial patterns were also identified with winter precipitation and temperature being primary determinants in mountain regions and northern cool and semi-arid regions, while summer NDVI and dryness were important in southern hot and arid regions. Our results indicate combined efforts of monitoring RS-based summer NDVI and dryness and forecasting winter temperature and precipitation can provide useful tools for dzud disaster early warning.