Khakass Technical Institute, Siberian Federal University, 27 Shchetinkina St., Abakan, 655017, Russia.
Birbal Sahni Institute of Palaeosciences, 53 University Road, Lucknow, 226007, India.
Int J Biometeorol. 2018 Jun;62(6):939-948. doi: 10.1007/s00484-017-1496-9. Epub 2017 Dec 30.
We investigated the variability of yield of the three main crop cultures in the Khakassia Republic: spring wheat, spring barley, and oats. In terms of yield values, variability characteristics, and climatic response, the agricultural territory of Khakassia can be divided into three zones: (1) the Northern Zone, where crops yield has a high positive response to the amount of precipitation, May-July, and a moderately negative one to the temperatures of the same period; (2) the Central Zone, where crops yield depends mainly on temperatures; and (3) the Southern Zone, where climate has the least expressed impact on yield. The dominant pattern in the crops yield is caused by water stress during periods of high temperatures and low moisture supply with heat stress as additional reason. Differences between zones are due to combinations of temperature latitudinal gradient, precipitation altitudinal gradient, and the presence of a well-developed hydrological network and the irrigational system as moisture sources in the Central Zone. More detailed analysis shows differences in the climatic sensitivity of crops during phases of their vegetative growth and grain development and, to a lesser extent, during harvesting period. Multifactor linear regression models were constructed to estimate climate- and autocorrelation-induced variability of the crops yield. These models allowed prediction of the possibility of yield decreasing by at least 2-11% in the next decade due to increasing of the regional summer temperatures.
我们研究了哈卡斯共和国三种主要作物(春小麦、春大麦和燕麦)的产量变化。就产量值、变异特征和气候响应而言,哈卡斯农业区可分为三个区:(1)北部区,作物产量对 5 月至 7 月的降水量有高度正响应,对同期温度有中度负响应;(2)中部区,作物产量主要取决于温度;(3)南部区,气候对产量的影响最小。作物产量的主要模式是由高温期间的水分胁迫和热量胁迫引起的,而水分胁迫和热量胁迫是主要原因。各区之间的差异是由于温度纬度梯度、降水海拔梯度以及中部区发达的水文网和灌溉系统作为水分源的组合造成的。更详细的分析表明,作物在营养生长和籽粒发育阶段以及在收获期对气候的敏感性存在差异。构建了多因子线性回归模型来估计气候和自相关引起的作物产量变化。这些模型可以预测由于区域夏季温度升高,未来十年作物产量至少下降 2-11%的可能性。