摘要
农田生产力对气候变化的敏感性决定了其脆弱性,全球气候变暖及极端气候频发将严重影响农业粮食生产,进而将可能影响区域粮食安全。科学评估农田生产力脆弱性并分析其气候影响机制有助于积极应对气候变化,保障区域粮食安全,具有重要的现实和科学意义。以“一带一路”区域的“孟中印缅经济走廊”为研究区,基于1982—2015年卫星遥感数据的归一化植被指数,根据IPCC脆弱性定义,采用年际变率及其变化趋势计算农田生产力对气候变化的敏感性、适应性和脆弱性指数,分时段分析研究区农田生态系统脆弱性空间格局变化及气候影响机制。结果表明:(1)较之1982—2000年,2000—2015年期间研究区农田脆弱性程度略有提升,高度和极度脆弱面积略有增加(分别增加0.42%和1.12%),但其分布格局发生北移。(2)年降水、年平均气温和年辐射与年累积NDVI间线性回归分析表明,孟加拉和缅甸地区与气候因素显著相关的区域面积在本国农田面积中的比例分别增加21.3%和16.7%,而印度地区减少10.5%,全区减少8.1%;(3)线性回归方程的复相关系数(R2)表征气候变化的解释能力,整个研究区增加12%,其中印度气候解释能力从48%提升至64%,增加16%。(4)农田生产力脆弱性受气候影响的范围略有减小,但影响程度增大,且存在较大的区域性差异;高温和降水季节不均引发的旱涝灾害是农田高脆弱度形成的两个关键气候因素。为该地区农业应对气候变化适应性管理措施的提出及决策提供了科学依据,有效支撑“一带一路”建设;也为其他地区应用卫星遥感开展脆弱性研究提供了方法参考,为生态系统对全球变化响应研究提供重要知识参考。
Vulnerability of agriculture is mainly determined by the sensitivity of farmland productivity to climatic changes.The global climate is predicted to continue its warming trend with increases in some extreme events in the future,which will have a great impact on crop yield,and seriously threaten regional food security.The scientific assessment of farmland productivity vulnerability and analysis of climate impact mechanisms,are helpful for mitigating climate change in pact and ensuring regional food security,which has great practical and scientific implications.Based on the normalised vegetationindex of satellite remote sensing data from 1982 to 2015,this paper takes the“Bangladesh,China,India and Myanmar Economic Corridor”in the“Belt and Road”region as the study area,and the sensitivity,adaptability and vulnerability indexes of farmland productivity to climate change(as defined by the IPCC),were calculated for the concepts of interannual variability and its changing trend.Changes in the spatial pattern of farmland ecosystem vulnerability,and analysis of climate impact mechanisms in the study area were carried out for different time periods.The results showed that:(1)Compared with 1982—2000,the vulnerability of farmland in the study area increased in 2000—2015,the extent of the high and exceedingly vulnerable area expanded by 0.42%and 1.12%respectively,and their spatial distributions moved northward;(2)Linear regression analysis between annual precipitation,annual average temperature,annual radiation and annual accumulated NDVI,showed that the area influenced significantly by climate increased by 21.3%and 16.7%in Bangladesh and Myanmar respectively,relative to their total national farmland areas,while the area in India decreased by 10.5%,and in the whole study area it decreased by 8.1%;(3)The multiple correlation coefficient(R^2)of the linear regression equation is indicative of the variability that is attributable to climate change,and it increased in the overall study area by 12%,with India′s climatic contribution increasing from 48% to 64%,an increase of 16%;(4)The impacts were chariacterized with a slight decreasing of its scope but an increasing of its degree,and there are large regional differences;high temperatures,droughts and floods caused by uneven seasonal precipitation are key climatic factors contributing to the high vulnerability of farmland.This study not only mapped the vulnerability,but also revealed its changes and impacts from climate change over the 34 years,providing methods and insights for agricultural adaptation management and policy making in those countries,and for consideration of regional food security in“The Belt and Road Initiative”.
作者
王春雨
王军邦
孙晓芳
王猛
王绍强
崔惠娟
WANG Chunyu;WANG Junbang;SUN Xiaofang;WANG Meng;WANG Shaoqiang;CUI Huijuan(Key Laboratory of Ecosystem Network Observation and Modelling,Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101,China;College of Geography and Tourism,Qufu Normal University,Rizhao 276800,China)
出处
《生态学报》
CAS
CSCD
北大核心
2019年第21期7793-7804,共12页
Acta Ecologica Sinica
基金
中国科学院重点部署项目(ZDRW-ZS-2016-6-4-2)
国家自然科学基金项目(31861143015)
国家重点研发计划(2017YFC0503803)
山东省自然科学基金(ZR2017BD010)
山东省高校科技计划项目(J16LH01)
关键词
孟印缅
NDVI
农田生产力
脆弱性
时空格局
气候影响
Bangladesh
India
and Myanmar
NDVI
farmland productivity
vulnerability
spatial temporal pattern
climatic impact