International Journal of Disaster Risk Reduction, vol.90, 2023 (SCI-Expanded)
Recent global climatic changes have caused frequent cold-season climate hazards and associated damage to societies in Mongolia. Here, we investigated the interannual variability of cold-season hazard indicators and their relationships to livestock health (mortality, health, and weight). A principal component analysis was applied to indicators (snow depth in January, SD1; air temperature for October–March, AT10-3) to extract significant modes. Then, we performed correlation and regression analyses to identify the contribution of each indicator to mortality and weight. Prior to analysis, we classified the cold season into two periods: early winter (EW) and late winter (LW). To our knowledge, this is the first study involving a detailed analysis of monthly indicators for livestock that reveals the dynamics of how weather affects health over time. The results showed that the higher SD1 and lower AT10-3 coefficients of the first modes coincided with severe winters (SW) and, conversely, mild winters (MW). Compositing SW and MW, mortality increased seven times per winter, and weight decreased twice as fast per month during SW. Focusing on EW and LW, the accumulated temperature of cold outbreak events was most significantly correlated with mortality during EW. This indicates that when temperatures are moderate, a sudden drop in temperature may have deleterious effects on livestock, leading to rapid weight loss and death because they have not had sufficient time to acclimatize. These seasonally changing dynamics connecting weather events and health will provide vital information for disaster risk management, including timely weather forecasts and proactive countermeasures to avoid a mass loss of livestock.