The potential links between climate change and grassland fires have received considerable attention, but few studies have examined the potential effects of climate variability on burned grassland area within the extensive grassland steppes of Eurasia. We used a novel econometric approach, dynamic simulated autoregressive distributed lag (ARDL) modeling, to explore the relationship among average monthly wind speed, sunlight, maximum temperature, mean temperature, relative humidity, and precipitation on burned grassland area in Xilingol, a large grassland-dominated landscape of Inner Mongolia in northern China. We provide a detailed explanation of this methodology and its potential usefulness to fire ecologists. Dynamic ARDL modeling indicated that burned grassland area was associated with both short-term fluctuations in climate and long-term climate trends. Our long-term analysis demonstrates that burned grassland area was most sensitive to wind speed and temperature. A 1% increase in wind speed was associated with an 86% increase in burned grassland area while a 1% increase in maximum temperature was associated with a 55% increase in burned grassland area. Under future climate change scenarios, our model predicts that by the year 2050 increases in average monthly wind speed, maximum temperature, and mean temperature will play a critical role in increasing the area of grassland burned relative to the baseline period of 2001−2018. Dynamic simulated ARDL methodology provides insights into the variability of area burned across Inner Mongolia grassland in the context of anthropogenic climate change, as well as the potential for broader applicability to predict changes in burned area with future climate scenarios across a range of grass-dominated ecosystems.

气候变化与草原火灾之间的潜在联系已受到相当多的关注，但是很少有研究研究气候变化对欧亚大陆广泛草原草原内被烧草地面积的潜在影响。我们使用一种新颖的计量经济学方法，动态模拟自回归分布滞后（ARDL）建模，研究了大草原锡林郭勒的平均月风速，日照，最高温度，平均温度，相对湿度和降水量与燃烧草地面积之间的关系。北方内蒙古的自然景观。我们提供了这种方法的详细说明及其对消防生态学家的潜在实用性。动态ARDL模型表明，草场被烧与气候的短期波动和长期的气候趋势都有关。我们的长期分析表明，被烧草地面积对风速和温度最敏感。风速增加1％与草场燃烧面积增加86％有关，而最高温度增加1％与草场燃烧面积增加55％相关。在未来的气候变化情景下，我们的模型预测到2050年，平均每月风速，最高温度和平均温度的增加将在相对于2001-2018年基准期的草地面积增加中起关键作用。