青藏高原高寒区青稞光温生产潜力和产量差时空分布特征及其对气候变化的响应  

Spatial-Temporal Variations of Photo-Temperature Potential Productivity and Yield Gap of Highland Barley and Its Response to Climate Change in the Cold Regions of the Tibetan Plateau

作　　者：弓开元 何亮 邬定荣[3] 吕昌河[4] 李俊[4] 周文彬 杜军[6] 于强[4,7] GONG KaiYuan;HE Liang;WU DingRong;LüChangHe;LI Jun;ZHOU WenBin;DU Jun;YU Qiang(College of Natural Resources and Environment,Northwest A&F University,Yangling 712100,Shaanxi;National Meteorological Center,Beijing 100081;Chinese Academy of Meteorological Sciences,Beijing 100081;Institute of Geographic Sciences and Natural Resources Research,Chinese Academy of Sciences,Beijing 100101;Institute of Crop Sciences,Chinese Academy of Agricultural Sciences,Beijing 100081;Institute of Plateau Meteorology,China Meteorological Administration,Chengdu,610071;State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau,Northwest A&F University,Yangling 712100,Shaanxi)

机构地区：[1]西北农林科技大学资源环境学院,陕西杨凌712100 [2]国家气象中心,北京100081 [3]中国气象科学研究院,北京100081 [4]中国科学院地理科学与资源研究所,北京100101 [5]中国农业科学院作物科学研究所,北京100081 [6]中国气象局成都高原气象研究所,成都610071 [7]西北农林科技大学黄土高原土壤侵蚀与旱地农业国家重点实验室,陕西杨凌712100

出　　处：《中国农业科学》2020年第4期720-733,共14页Scientia Agricultura Sinica

基　　金：中国科学院战略性先导科技专项（XDA20040301）;国家自然科学基金（41705095）;国家重点研发计划（2016YFD0300102）

摘　　要：【目的】探讨有气象数据记录以来1977—2017年青藏高原青稞生长季内气候变化,以及对青稞光温生产潜力和产量差的影响。【方法】基于青藏高原农气资料,校正DSSAT-CERES-barley模型,模拟过去40年间青藏高原青稞生育期长度及光温生产潜力,并结合实际统计产量计算产量差,通过数理方法解析气候变化对其影响情况。【结果】(1)青藏高原多数站点过去40年间青稞生长季内温度、降水呈显著上升趋势,太阳辐射量呈下降趋势,且林芝站达到显著水平,与增湿相比增温趋势更加明显;(2)在播期和品种不变的情况下,过去40年青稞生育期长度显著缩短,引起不同站点下降的主要气候因子不同,高海拔站点主要由平均最高气温升高所致,低海拔站点主要由生育期内平均温度升高导致有效积温增加所致;(3)青藏高原青稞光温生产潜力受海拔影响,3500 m左右的高海拔站点光温生产潜力高且稳定,如山南站平均光温生产潜力最高可达12000 kg·hm^-2。3000 m左右的低海拔站点光温生产潜力低,平均在6000 kg·hm^-2,且易受气候变化影响,高海拔站点光温生产潜力对太阳辐射更敏感;(4)青藏高原在过去30年间由于实际产量增加,导致绝对和相对产量差都呈减小趋势,平均相对产量差由58.2%缩小至34.5%,但缩小幅度放缓,2007—2017年拉萨和日喀则站点平均相对产量差最低,小于25%。【结论】青藏高原不同站点光温生产潜力差异较大,高海拔站点青稞光温生产潜力显著高于低海拔站点,过去40年气候变化导致低海拔站点光温生产潜力波动大,而高海拔站点较为稳定。由于品种改良和栽培管理水平提高,过去30年青藏高原产量差逐渐缩小,但除拉萨和日喀则外,其他站点产量差仍较大,未来有较高的增产潜力。【Objective】The climate change of highland barley during the growth season and effect on photo-temperature potential productivity as well as yield gap over Tibetan Plateau from 1977 to 2017 were investigated.【Method】The DSSAT-CERES-barley was validated against statistical and field observational data,and then applied to simulate the potential yield of the highland barley on Tibetan Plateau.Then yield gaps were calculated by using observed yields and simulations.Finally,we analyzed the impact of climate change on highland barley production and yield gaps by using statistical methods.【Result】(1)Temperature and precipitation during highland barley growth period significantly increased on Tibetan Plateau over the past 40 years,whereas solar radiation decreased and it decreased significantly at Lizhi station;(2)The growth period of highland barley has significantly decreased if using the same variety at a fixed sowing date.The decrease of growth period in high-altitude was mainly caused by the increasing of the average maximum temperature,however,at low-altitude,which were mainly caused by the increase of the effective accumulated temperature during the whole growing period due to rising of mean temperature;(3)The potential barley yield was limited by the altitude and more sensitive to solar radiation at the high altitude stations.It was large and stable at the high-altitude stations with an altitude of 3500 m.The average potential yield of Shannan station approached to 12000 kg·hm^-2 while only 6000 kg·hm^-2 at low altitude stations around 3000 m;(4)The yield gaps of highland barley in Tibetan Plateau in the past 30 years has decreased from 58.2%to 34.5%due to the increase of actual production.And the decreasing rate of yield gaps decelerated in recent decade.The yield gaps in Lasa and Shigatse were the least during 2007-2017,which were less than 25%.【Conclusion】The potential yields of highland barley on Tibetan Plateau were different greatly in different stations on Tibetan Plateau.The potential yie

关 键 词：青藏高原 青稞 光温生产潜力 作物模型 气候变化 

分 类 号：S512.3[农业科学—作物学] S162.53