Institute of Development Studies (IDS), The University of Agriculture, Peshawar, Pakistan.
Department of Agricultural Economics, Sichuan Agriculture University, Chengdu, China.
Environ Sci Pollut Res Int. 2021 Nov;28(42):60235-60245. doi: 10.1007/s11356-021-14954-8. Epub 2021 Jun 22.
This study investigates the impacts of climate change on yield of selected cereal crops (wheat and maize) in the northern climatic region of Khyber Pakhtunkhwa (KP) province of Pakistan for the period 1986-2015. The first-generation unit root tests such as the Levin, Lin, and Chu (LLC), augmented Dickey-Fuller (ADF)-Fisher, and the second-generation unit root tests such as cross-sectional augmented Im-Pesaran-Shin (CIPS) and cross-sectional ADF (CADF) are used to check stationarity of the series. The cointegration among the variables is discovered via Pedroni test and Westerlund method. The long- and short-run impacts of climatic variables (average precipitation, maximum temperature, and minimum temperature) on yield of wheat and maize crops are assessed through the autoregressive distributed lag (ARDL) model. The empirical findings reveal that average precipitation has a significantly positive impact on yield of both crops in long- as well as short-run. The results further reveal that the effect of average minimum temperature on both crops is insignificant in long-run. However, the short-run effect of average minimum temperature is significantly positive on yield of maize crop but insignificant on yield of wheat crop. In long-run, an increase in average maximum temperature negatively affects crop yield. In short-run, however, it positively affects the yield of wheat and maize crops. The study recommends that increase in area under cultivation, development of advanced irrigation system, and farmers' access to metrological information will help in lowering the drastic impacts of climate change on crop productivity.
本研究调查了气候变化对巴基斯坦开伯尔-普赫图赫瓦省(KP)北部气候区选定谷物(小麦和玉米)产量的影响,时间跨度为 1986 年至 2015 年。采用了第一代单位根检验,如 Levin、Lin 和 Chu(LLC)、增强 Dickey-Fuller(ADF)-Fisher 检验,以及第二代单位根检验,如横截面增强 Im-Pesaran-Shin(CIPS)和横截面 ADF(CADF)检验,以检查序列的平稳性。通过 Pedroni 检验和 Westerlund 方法发现变量之间的协整关系。通过自回归分布滞后(ARDL)模型评估气候变量(平均降水量、最高温度和最低温度)对小麦和玉米产量的长期和短期影响。实证结果表明,平均降水量在长期和短期对两种作物的产量都有显著的正向影响。结果还表明,平均最低温度对两种作物的长期影响不显著。然而,平均最低温度的短期效应对玉米产量有显著的正向影响,但对小麦产量没有显著影响。在长期内,平均最高温度的升高会对作物产量产生负面影响。然而,在短期内,它会对小麦和玉米作物的产量产生正向影响。研究建议增加种植面积、开发先进的灌溉系统以及农民获得气象信息,将有助于降低气候变化对作物生产力的巨大影响。