【目的】研究东北地区春玉米适种区域及其生育期、产量对气候变化的响应。【方法】基于气候模式RegCM4输出的未来RCP4.5新气候情景逐日资料，采用经验频率法预测80%保证率下2011—2050年中国东北地区早、中、晚熟型春玉米种植区域时空变化，同时结合作物模型DSSAT4.5对黑龙江省晚熟品种的生育期、产量变化特征及该省因气候变化而新增的晚熟品种可能种植区内晚熟玉米的适种性进行模拟评估。【结果】RCP4.5情景下，2011—2050年东北三省≥10℃的积温呈增加趋势，早、中、晚熟型玉米品种种植界限均有不同程度的北扩或东移，可能种植范围扩大。黑龙江省2011—2050年间晚熟玉米新增可能种植区域内适宜种植晚熟品种；气候变化对原有种植区内晚熟品种生殖生长期的影响程度大于对营养生长期的影响，全生育期天数平均缩短2—11 d；产量变化存在明显空间差异，不考虑CO2肥效作用和考虑CO2肥效作用两种方案下的产量变化范围均介于±20%以内，但考虑CO2肥效作用时的产量较高。【结论】因气候条件变化而新增的春玉米种植区域的适种性需要综合考虑多方面因素来评估。未来40a玉米全生育期天数变化主要源于生殖生长期缩短，大气中CO2浓度增加带来的肥效作用可抵消一部分因温度升高产生的对玉米产量形成的不利影响。

在气候变暖背景下，昼夜非对称性升温和大气CO₂浓度升高成为气候变化的重要特征与驱动因素。气候变化影响水热资源分布，驱动三大粮食作物（小麦、玉米、水稻）的种植结构、种植界限等发生改变，研究主要粮食作物对气候变暖的响应，对保障粮食安全具有重要意义。基于高密度气象台站资料，采用统计方法分析1990年前、后30 a热量资源变化及其对中国三大粮食作物潜在种植区的可能影响；同时，汇总“大田条件下的自由空气增温实验（Free Air Temperature Increase， FATI）”和“控温控CO₂的开顶箱实验（Open-Top Chamber， OTC）”多站点试验结果，结合文献荟萃方法，探讨气候变暖对三大作物生育期和产量的影响。 结果表明：1）中国农业热量资源总体在增加，农耕期持续天数和积温显著上升，无霜期延长；极端高温日数普遍增多，部分地区（如陕甘宁）农耕期极端低温日数亦有所增加，极端气象灾害风险加剧。2）三大作物种植北界发生了程度不一的北移，潜在适宜种植面积增加。3）气候变暖初期利于冬小麦生长，过度升温将致发育提前、霜冻风险上升，春小麦生育期缩短、产量受限；CO₂浓度升高虽有增产效应，但难以抵消高温带来的不利影响。4）气候变暖通过缩短玉米生育期、减少穗粒数和千粒重，抑制产量形成，夜间增温加剧产量下降；CO₂浓度升高对玉米生长与产量的作用有限，增温为主导因子。5）单纯增温对早稻产量有抑制作用，对晚稻则有促进作用；早稻增温削弱CO₂的增产效应，晚稻则表现为协同促进，提升产量。

Maize crop (Zea mays) is one of the staple foods in the East African (EA) region. However, the suitability of its production area is threatened by projected climate change. The Multimodel Ensemble (MME) from eight Coupled Model Intercomparison Project 5 (CMIP5) models was used in this paper to show climate change between the recent past (1970-2000) and the future (2041-2060), i.e., the mid-twenty-first century. The climatic suitability of maize crop production areas is evaluated based on these climate datasets and the current maize crop presence points using Maximum entropy models (MaxEnt). The MME projection showed a slight increase in precipitation under both RCP4.5 and RCP8.5 in certain places and a reduction in most of southern Tanzania. The temperature projection showed that the minimum temperature would increase by 0.3 to 2.95 °C and 0.3 to 3.2 °C under RCP4.5 and 8.5, respectively. Moreover, the maximum temperature would increase by 1.0 to 3.0 °C and 1.2 to 3.6 °C under RCP4.5 and 8.5 respectively. The impacts of these projected changes in climate on maize production areas are the reduction in the suitability of the crop, especially around central and western Tanzania, mid-northern and western Uganda, and parts of western Kenya by 20-40%, and patches of EA will experience a reduction of as high as 40-60%, especially in northern Uganda, and western Kenya. The projected changes in temperature and precipitation present a significant negative change in maize crop suitability. Thus, food security and the efforts towards the elimination of hunger in EA by the mid-twenty-first century will be hampered significantly. We recommend crop diversification to suit the new future environments, modernizing maize farming programs through the adoption of new technologies including irrigation, and climate-smart agricultural practices, etc.© 2021. The Author(s), under exclusive licence to Springer Nature Switzerland AG.

反距离权重(Inverse Distance Weighting,IDW)插值通常采用距离搜索策略选择插值参考点,当采样点集分布不均匀时,距离搜索策略使得参考点聚集一侧影响插值精度。自然邻近关系具有良好的自适应分布特性,可有效地解决参考点分布不均匀问题。结合自然邻近关系,提出自适应的反距离权重(Adaptive-IDW,AIDW)插值方法。首先对采样数据构建初始Delaunay三角网,然后采用逐点插入法,将待插值点插入初始Delaunay三角网中,局部调整得到新的Delaunay三角网,以待插值点的一阶邻近点作为IDW插值的参考点,使参考点自适应均匀地分布在待插值点周围,再进行IDW插值计算。利用AIDW插值方法对Franke函数、全国气温观测数据进行插值实验,结果表明此方法具有较高的精度,且减少了“牛眼”现象。