气候变化情景下油茶生长的适宜性特征

基于气候情景数据与油茶标本,运用MaxEnt模型分析全新世中期、当代与未来阶段油茶生长的气候适宜性特征,将概率分布结果由不适宜到最适宜分为4个等级,分析了各时段空间分布变化与最适宜区北界变化、几何中心变化及位移情况。结果如下：1）MaxEnt模型的AUC值为0.848,评估结果达到“好”的标准,说明该模型可用;年降水量、最湿季降水量、最暖季平均温、温度季节性变化的标准差、最干月降水量、最湿季平均温和最冷季平均温等是7个主要环境因子。2）中国油茶主要适宜生长于长江以南、云贵高原以东,经纬度范围为30°N以南、107°E以东地区;适宜及以上等级占研究区面积的34.9%~61%;适宜性变化,空间上西南地区波动明显,面积上稳定和降低类占比较高。3）油茶最适宜区北界位于亚热带中部,不同年代、不同地区北界各异,长江中下游地区变化较小,而秦岭、渝、贵和桂等地变动较大,整体趋势为全新世中期至1980s向南推移,未来情景下2050s和2070s缓慢向北推移;几何中心在全新世中期时位于湖南郴州,至1980s时向东南方位移至广东韶关,至2050s时向东北位移至江西吉安,并相对稳定。4）基于气候情景数据和MaxEnt物种分布模型分析中国南方地区油茶气候适宜性时空分布与变化特征结果可靠。     

陕北黄土高原红枣种植区水热资源变化及未来趋势预测

为了揭示陕北黄土高原红枣种植区水热资源变化特征,给当地红枣产业适应气候变化提供科学依据,利用陕北黄土高原红枣种植区8个气象站1971—2019年的气温、降水资料,及中等(RCP4.5)和高等(RCP8.5)排放气候情景下2021—2050年的气候变化预估数据,采用线性倾向估计、M-K检验、Morlet小波分析方法对气温...     

中国生态过渡带分布的空间识别及情景模拟

在全球变化及其生态环境效应研究中,如何对生态过渡带的空间分布格局及变化情景进行空间定量识别和模拟分析,对揭示气候变化和人类活动对全球变化的响应及反馈具有指示性意义.在对HLZ模型进行修正和拓展的基础上,建立了生态过渡带类型的空间识别方法.并基于1981-2010年的全国782个气候观测站点数据,在实现全国生态过渡带类型...     

Spatial identification and scenario simulation of the ecological transition zones under the climate change in China

Explicitly identifying the spatial distribution of ecological transition zones(ETZs) and simulating their response to climate scenarios is of significance in understanding the response and feedback of ecosystems to global climate change. In this study, a quantitative spatial identification method was developed to assess ETZ distribution in terms of the improved Holdridge life zone(iHLZ) model. Based on climate observations collected from 782 weather stations in China in the T0(1981–2010) period, and the Intergovernmental Panel on Climate Change Coupled Model Intercomparison Project(IPCC CMIP5) RCP2.6, RCP4.5, and RCP8.5 climate scenario data in the T1(2011–2040), T2(2041–2070), and T3(2071–2100) periods, the spatial distribution of ETZs and their response to climate scenarios in China were simulated in the four periods of T0, T1, T2, and T3. Additionally, a spatial shift of mean center model was developed to quantitatively calculate the shift direction and distance of each ETZ type during the periods from T0 to T3. The simulated results revealed 41 ETZ types in China, accounting for 18% of the whole land area. Cold temperate grassland/humid forest and warm temperate arid forest(564,238.5 km~2), cold temperate humid forest and warm temperate arid/humid forest(566,549.75 km~2), and north humid/humid forest and cold temperate humid forest(525,750.25 km~2) were the main ETZ types, accounting for 35% of the total ETZ area in China. Between 2010 and 2100, the area of cold temperate desert shrub and warm temperate desert shrub/thorn steppe ETZs were projected to increase at a rate of 4% per decade, which represented an increase of 3604.2, 10063.1, and 17,242 km~2 per decade under the RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. The cold ETZ was projected to transform to the warm humid ETZ in the future. The average shift distance of the mean center in the north wet forest and cold temperate desert shrub/thorn grassland ETZs was generally larger than that of other ETZs, with the mean center moving to the northeast and the shift distance being more than 150 km during the periods from T0 to T3.In addition, with a gradual increase of temperature and precipitation, the ETZs in northern China displayed a shifting northward trend, while the area of ETZs in southern China decreased gradually, and their mean center moved to high-altitude areas. The effects of climate change on ETZs presented an increasing trend in China, especially in the Qinghai-Tibet Plateau.     

青藏高原维管植物物种丰富度分布的情景模拟

如何充分利用离散的观测数据,通过对维管植物物种分布丰富度及其与生境因子之间的相互作用和影响机理的定量分析,实现维管植物物种丰富度的空间分布及其情景模拟,是目前生物多样性研究前沿和核心内容之一。针对这一问题,在实现青藏高原37个国家自然保护区的维管植物物种数量收集和边界数据矢量化的基础上,分别进行维管植物物种数量与土地覆盖类型、环境因子和景观生态指数等三大类生境因子之间的相关关系的定量计算和对比分析,筛选和确定最佳相关分析方程,进而构建青藏高原维管植物物种丰富度的空间模拟分析模型。该模型中,维管植物物种丰富度与生境因子之间的复相关系数为0.94,模型验证结果表明,青藏高原的维管植物物种的平均丰富度为496.79种/100 km²,其空间分布格局整体上呈东南向西北逐渐减少趋势;另外,除柴达木盆地荒漠区域以外,维管植物物种的空间分布随海拔的升高而减少。基于CMIP5 RCP 2.6、RCP 4.5和RCP 8.5三种气候情景模拟获得的青藏高原维管植物物种丰富度未来情景结果显示,在T0-T4（2010-2100）时段内,青藏高原维管植物物种丰富度整体将呈减少趋势。RCP 8.5情景下青藏高原维管植物物种丰富度的变化幅度最大,而RCP 2.6情景下的维管植物物种丰富度的变化幅度最小。研究表明,本文构建的模型能够对青藏高原维管植物物种丰富度的空间分布格局及其未来情景进行模拟分析,模拟结果可为青藏高原生物多样性及其对气候变化响应的综合评估和情景模拟提供方法和技术支持。     

基于HASM方法对气候模式气温降水的降尺度研究——以黑河流域为例

基于空间平稳性分析,引入地理因素结合回归分析及高精度曲面建模方法（HASM）对黑河流域多年平均气温、降水给出了降尺度模拟。基于过去器测资料的验证,提出了CMIP5模式资料的合理降尺度方法。比较了降尺度结果与站点实测值的差异,同时比较了所给出的方法与经典插值方法的模拟精度。最后,基于历史时期T₁（1976—2005年）的降尺度方法结合RCP2.6、RCP4.5及RCP8.5不同情景下未来时段T₂（2011—2040年）、T₃（2041—2070年）、T₄（2071—2100年） CMIP5模式结果,对降尺度方法进行了修正,给出了未来时段气温的降尺度模拟公式,并基于此对上述3种情景下多年平均气温的CMIP5模拟结果进行了降尺度模拟。结果表明：本文所提出的降尺度方法模拟结果与站点观测值具有较好的相关性,且精度高于其他经典插值方法。对未来时段的模拟结果表明,升温最快的是RCP8.5情景,在2071—2100年,除祁连山地区外,大部分地区年平均气温大于10℃。     

Impacts of future climate change on agroclimatic resources in Northeast China

In this study, the spatial distribution and changing trends of agricultural heat and precipitation resources in Northeast China were analyzed to explore the impacts of future climate changes on agroclimatic resources in the region. This research is based on the output meteorological data from the regional climate model system for Northeast China from 2005 to 2099, under low and high radiative forcing scenarios RCP4.5 (low emission scenario) and RCP8.5 (high emission scenario) as proposed in IPCC AR5. Model outputs under the baseline scenario, and RCP4.5 and RCP8.5 scenarios were assimilated with observed data from 91 meteorological stations in Northeast China from 1961 to 2010 to perform the analyses. The results indicate that: (1) The spatial distribution of temperature decreases from south to north, and the temperature is projected to increase in all regions, especially under a high emission scenario. The average annual temperature under the baseline scenario is 7.70°C, and the average annual temperatures under RCP4.5 and RCP8.5 are 9.67°C and 10.66°C, respectively. Other agricultural heat resources change in accordance with temperature changes. Specifically, the first day with temperatures ≥10°C arrives 3 to 4 d earlier, the first frost date is delayed by 2 to 6 d, and the duration of the growing season is lengthened by 4 to 10 d, and the accumulated temperature increases by 400 to 700°C·d. Water resources exhibit slight but not significant increases. (2) While the historical temperature increase rate is 0.35°C/10a, the rate of future temperature increase is the highest under the RCP8.5 scenario at 0.48°C/10a, compared to 0.19°C/10a under the RCP4.5 scenario. In the later part of this century, the trend of temperature increase is significantly faster under the RCP8.5 scenario than under the RCP4.5 scenario, with faster increases in the northern region. Other agricultural heat resources exhibit similar trends as temperature, but with different specific spatial distributions. Precipitation in the growing season generally shows an increasing but insignificant trend in the future, with relatively large yearly fluctuations. Precipitation in the eastern region is projected to increase, while a decrease is expected in the western region. The future climate in Northeast China will change towards higher temperature and humidity. The heat resource will increase globally, however its disparity with the change in precipitation may negatively affect agricultural activities.     

青藏高原维管植物物种丰富度分布的情景模拟（英文）

For quantitatively explaining the correlations between the vascular plant species abundance(VPSA) and habitat factors, a spatial simulation method has been developed to simulate the distribution of VPSA on the Qinghai-Tibet Plateau. In this paper, the vascular plant type, land cover, mean annual biotemperature, average total annual precipitation, topographic relief, patch connectivity and ecological diversity index were selected to screen the best correlation equation between the VPSA and habitat factors on the basis of 37 national nature reserves on the Qinghai-Tibet Plateau. The research results show that the coefficient of determination between VPSA and habitat factors is 0.94, and the mean error is 2.21 types per km~2. The distribution of VPSA gradually decreases from southeast to northwest, and reduces with increasing altitude except the desert area of Qaidam Basin. Furthermore, the scenarios of VPSA on the Qinghai-Tibet Plateau during the periods from 1981 to 2010(T0),from 2011 to 2040(T2), from 2041 to 2070(T3) and from 2071 to 2100(T4) were simulated by combining the land cover change and the climatic scenarios of CMIP5 RCP2.6, RCP4.5 and RCP8.5. The simulated results show that the VPSA would generally decrease on the Qinghai-Tibet Plateau from T0 to T4. The VPSA has the largest change ratio under RCP8.5 scenario, and the smallest change ratio under RCP2.6 scenario. In general, the dynamic change of habitat factors would directly affect the spatial distribution of VPSA on the Qinghai-Tibet Plateau in the future.     

我国亚热带划分中的一些问题

我国的亚热带幅员辽阔、物产丰富、人口密集、地形复杂、气候多样,气候带如何划分是一个重要问题。在区划的原则、等级、指标和界线等问题上,都有不同的看法。作者就这些问题发表了意见,并提出了划分亚热带的具体方案。     

RCP4.5情景下中国人口对高温暴露度预估研究

基于CMIP5的逐日最高温度模拟资料、GGI情景数据库逐年代人口数据,在RCP4.5情景下,以对应栅格高温日数与人口数量的乘积作为人口对高温的暴露度指标,通过多模式集合平均预估未来中国人口对不同强度高温的暴露度变化。结果表明：相比于基准时段（1981-2010年）,中国人口对高温和强危害性高温的暴露度从2021-2040年开始明显增加,至2081-2100年暴露度分别增加了5.7倍和17.5倍;除了中国西部部分地区外,全国大部地区人群均受高温的影响,在21世纪中后期中东部大部人口对高温的暴露度超过10.0×10⁶人?d;相比基准时段,随着年代的增长,中国人口对强危害性高温的暴露度在范围和强度上均有明显增加;2081-2100年,人口对高温和强危害性高温的暴露度增幅减缓。从气象地理区域上看,未来各时段人口对高温、强危害性高温的暴露度均有一定程度增加,但增加明显的区域主要集中在华北、黄淮、江南和江淮地区,华南地区对强危害性高温的暴露度增幅较小。高温日数变化对全国人口对高温暴露度的变化所产生的作用最明显。多模式集合的预估结果可以为防控未来高温风险提供重要的参考价值。     

1967—2017年甘肃省小麦需水量和缺水量时空特征

基于甘肃省28个气象站点1967—2017年的逐日气象数据,采用Penman-Monteith公式和作物系数计算了小麦的需水量,结合美国农业部土壤保持局推荐的方法计算了有效降水量,进一步得出小麦缺水量,并分析了小麦需水量与缺水量的变化趋势和空间分布特征,探讨了小麦需水量影响因子重要程度。结果表明:1967—2017年甘肃省春、冬小麦全生育期的年平均需水量分别为517.03 mm和436.70 mm,年平均缺水量分别为468.24 mm和301.54 mm;在时间上,51 a来春小麦种植区内的需水量与缺水量整体上无明显的趋势变化,而冬小麦种植区内的需水量与缺水量整体上呈明显上升趋势;在空间上,春小麦种植区内需水量和缺水量大致由西北向东南递减,冬小麦种植区内的需水量和缺水量大致由西向东递减。甘肃省小麦生育期内日照时数和日平均气温是影响小麦需水量的主要因素。     

气候变暖对西北干旱区农作物种植结构的影响

采用年平均气温与冬小麦、春小麦、玉米和棉花种植面积的相关分析得出：年平均气温与新疆冬小麦种植面积呈显著负相关,与西北干旱区大部地方春小麦种植面积呈显著负相关,与西北干旱区大部地方玉米种植面积呈显著正相关,与新疆和甘肃河西棉花种植面积呈显著正相关。气候变暖、热量资源增加,使喜凉的春小麦和冬小麦种植面积呈迅速减少趋势,喜温的玉米和棉花种植面积呈迅速扩大,夏秋作物种植结构发生明显改变。     

Impacts of climate change on winter wheat growth in Panzhuang Irrigation District, Shandong Province

Global climate change has significant impacts on agricultural production. Future climate change will bring important influences to the food security. The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District (PID) during 2011–2040 under B2 climate scenario based on the Special Report on Emissions Scenarios (SRES) assumptions with the result of RCMs (Regional Climate Models) projections by PRECIS (Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research. The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002–2003 and 2007–2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station (YCES), Chinese Academy of Sciences (CAS). The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area. Average temperature at Yucheng Station rose by 0.86℃ for 1961–2008 in general. Under the B2 climate scenario, average temperature rose by 0.55℃ for 2011–2040 compared with the baseline period (1998–2008), which drastically shortened the growth period of winter-wheat. However, as the temperature keep increasing after 2030, the top-weight and yield of the winter wheat will turn to decrease. The simulated evapotranspiration shows an increasing trend, although it is not very significant, during 2011–2040. Water use efficiency will increase during 2011–2031, but decrease during 2031–2040. The results indicate that climate change enhances agricultural production in the short-term, whereas continuous increase in temperature limits crop production in the long-term.     

近30年中国农作物种植结构时空变化分析

综合运用时序变化趋势、空间集聚分析等方法,从种植结构类型和种植比例变化趋势分析了1980年以来中国县域种植结构的时空特征。结果表明：① 近30年来中国前10位的种植结构类型有16种,2002年后多元种植结构逐步替代单一型种植结构。粮食作物占优的单一种植结构类型呈逐年递减趋势,其中1980年全国82.7%的县级农业种植结构是水稻、小麦、玉米及其组合种植类型,2002年后的果蔬类型增加改变了种植结构格局。② 全国种植县中有47%的水稻、61%的小麦和29.6%的玉米的种植比例显著减少,其他作物呈现增加趋势。粮食作物由以水稻为主的格局调整为水稻、小麦和玉米共存格局,其中玉米种植面积比例在空间上变化最为显著,在中国形成北东—西南向的“玉米减少带”。种植结构调整热点的城市地区,城市化对种植结构变化影响显著,水果和蔬菜类种植比例在城市化地区快速增加。③ 种植结构变化趋势在1300个县形成空间集聚效应,水稻的高高聚集占全国县数的2.86%、小麦占5.64%、玉米占6.11%、大豆为4.53%、麻类为1.62%、棉花占7.77%、蔬菜占8.24%、薯类占12%、水果占10%、糖料占1.41%、油料占9.35%,主要分布于中国东北、新疆和沿海的城市化地区。     

气候变化对山东省潘庄灌区冬小麦生长的影响(英文)

Global climate change has significant impacts on agricultural production.Future climate change will bring important influences to the food security.The CERES-Wheat model was used to simulate the winter wheat growing process and production in Panzhuang Irrigation District(PID) during 2011-2040 under B2 climate scenario based on the Special Report on Emissions Scenarios(SRES) assumptions with the result of RCMs(Regional Climate Models) projections by PRECIS(Providing Regional Climates for Impacts Studies) system introduced to China from the Hadley Centre for Climate Prediction and Research.The CERES-Wheat model was calibrated and validated with independent field-measured growth data in 2002-2003 and 2007-2008 growing season under current climatic conditions at Yucheng Comprehensive Experimental Station(YCES),Chinese Academy of Sciences(CAS).The results show that a significant impact of climate change on crop growth and yield was noted in the PID study area.Average temperature at Yucheng Station rose by 0.86℃ for 1961-2008 in general.Under the B2 climate scenario,average temperature rose by 0.55℃ for 2011-2040 compared with the baseline period(1998-2008),which drastically shortened the growth period of winter-wheat.However,as the temperature keep increasing after 2030,the top-weight and yield of the winter wheat will turn to decrease.The simulated evapotranspiration shows an increasing trend,although it is not very significant,during 2011-2040.Water use efficiency will increase during 2011-2031,but decrease during 2031-2040.The results indicate that climate change enhances agricultural production in the short-term,whereas continuous increase in temperature limits crop production in the long-term.     

综合湿度和温度影响的中国未来热浪预估

地面空气湿度直接影响人体驱散热负荷的效率,持续高温高湿天气将会严重影响人体健康。基于综合考虑温度和湿度协同作用的热胁迫指数——湿球黑球温度(WBGT)指数定义热浪,利用参考时期(1986—2005年)中国824个气象站点逐日平均气温和逐日相对湿度资料以及CMIP5多模式相应模拟数据,论文定量描述了未来时期(2076—2095年)不同排放情景下(RCP2.6、RCP4.5和RCP8.5)中国大陆地区可能遭遇的热浪事件的空间分布特征及其变化。研究结果表明：① 最有效的减排情景(RCP2.6)和高排放情景(RCP8.5)下中国大陆地区的平均热浪日数分别是参考时期的3.4倍和6.6倍,平均热浪强度(一年内所有热浪事件中日平均WBGT指数的最大值)也相对升高了1.6 ℃和4.9 ℃,未来时期RCP8.5情景下中国东部和南部地区的最高年均热浪强度甚至将达到40 ℃;② 虽然青藏高原地区的热浪强度等级低,但是未来时期热浪日数的增加幅度较为显著;③ 华南、长江中下游以及少数西南地区是综合考虑气温和湿度协同作用对人体热舒适的影响下,未来时期可能发生热浪最严重的地区,如果不考虑湿度要素的影响,那么将极有可能低估热浪在中国华南和东部等湿度较高地区的强度和影响。     

一种新的气候变化敏感区的定义方法与预估

气候变化敏感区的研究是气候变化研究的一个重要方向,前人对气候变化敏感区的定义大多基于单一的指标,而对综合性指标研究较少。基于柯本气候分类法所划分出的中国气候类型分布及其变化频次,提出一种新的气候变化敏感区定义方法,并使用该方法划分中国的气候变化敏感区,气候类型变化频繁的区域被认为是敏感区。选取CESM模型中等碳排放（RCP 4.5）下的模拟数据计算2006-2013年、21世纪40年代和90年代气候类型的变化,以此预估未来30~80年间气候变化敏感带的变化。结果显示：依据本文提出的方法划分的气候变化敏感区,与降水变化敏感区有较好拟合;中国气候变化最敏感的区域分布在黑河腾冲线附近、秦岭淮河一线、青藏高原西部和天山以北部分地区,气候最为稳定的区域分布在青藏高原中东部、昆仑山、祁连山以北、天山以南、贺兰山以西的大片区域和大兴安岭附近;未来30~80年间,西部（贺兰山、横断山以西）地区气候变化敏感区基本不变,而东部地区的气候变化敏感区则逐渐向北偏移。     

RCP8.5气候变化情景下21世纪印度粮食单产变化的多模式集合模拟

基于跨部门影响模型比较计划（ISI-MIP）中20种气候模式与作物模型组合的模拟结果,预估了RCP 8.5排放情景下21世纪印度小麦和水稻单产变化。研究发现：① 多模式集合模拟结果基本再现了印度小麦和水稻单产的空间差异;同时,再现了小麦和水稻单产对温度和降水变化的响应特征：与温度呈负相关,与降水呈正相关。② RCP 8.5情景下,水稻和小麦生长季温度和降水均呈增加趋势,小麦生长季的温度、降水增加幅度大于水稻。空间上,温度增加幅度自北向南逐渐减小,降水增幅则逐渐增加,并且小麦种植区升温幅度大于非种植区,降水增幅则少于非种植区,水稻种植区升温幅度小于非种植区,降水增幅则多于非种植区。③ RCP 8.5情景下,小麦和水稻单产均呈下降趋势,21世纪后半叶尤为明显。小麦单产的下降速度明显大于水稻,其中21世纪前半叶小麦和水稻单产下降速度约分别为1.3%/10a （P < 0.001）和0.7%/10a （P < 0.05）,后半叶分别增至4.9%/10a （P < 0.001）和4.4%/10a （P < 0.001）。小麦和水稻单产变化存在明显的空间异质性,小麦单产的最大下降幅度出现在德干高原西南部,降幅约60%,水稻单产最大下降幅度出现在印度河平原北部,降幅约50%。这意味着未来气候变化情景下印度粮食供给将面临较大的挑战。     

基于植被动态模式预估中国植被净初级生产力变化格局

本文选用部门间影响模式比较计划（ISI-MIP）提供的6个植被动态模式数据,对比遥感反演值计算了各模式在中国不同植被区的拟合优度,评估了模式的适用性;并提出了以拟合优度为权重的区域年均净初级生产力（NPP）算法,有效解决了已有研究由于数据和方法的不同而对中国NPP估算效果较差的问题。结合两种浓度路径下（RCP2.6和RCP6.0）的模式估算结果,评估了未来30 中国NPP的变化格局。结果表明：单个模式数据对中国大部分区域NPP的拟合效果较差（R² < 0.4）,所计算的中国平均NPP整体偏高33%~97%,但能较为准确地反映空间上从东南向西北递减的趋势。通过加权合成的新序列整体拟合优度为0.86,在单一植被区的拟合优度也基本大于0.3,能更好地反映未来NPP的变化格局。未来中国平均NPP仍将保持由东南向西北递减的分布,中国均值呈波动增长状态,在2035年达到8.8 μg/(m² s),2050年达到9.7 μg/(m² s)左右。随着时间的推移,RCP2.6路径下主要增长区将由南方地区向北偏移,在华北地区增长变显著,在西南、中南地区增速变慢,显著增长的面积变小;在RCP6.0路径下主要增长区将向东北、东南和西部地区退缩,中东部地区增长变不显著。研究发现高浓度路径对2016—2025年间植被NPP的增长主要起促进作用,但在2035—2050年间开始起抑制作用。同时,高浓度路径下NPP的空间分布将变得更加极端,特别是位于青藏高原西北部的高寒荒漠、温性荒漠及灌木半灌木荒漠将增长缓慢或不增长。     

基于FAO-GAEZ模型的中国马铃薯县域种植空间布局优化

马铃薯“主粮化”战略要求在不挤占三大主粮的前提下提升国家马铃薯种植面积和产量。已有关于马铃薯种植空间布局的研究缺少定量支撑的相关优化证据。本文结合统计数据分析中国马铃薯的消费结构及其消费量的变化趋势,应用ARMA模型预测中国2022—2040年马铃薯年均需求量。结合耕地空间分布数据和马铃薯县域种植面积数据,应用GAEZ模型以适宜性等级作为优先级对未来中国马铃薯种植布局进行县域尺度空间推演,提出未来中国马铃薯县域尺度的种植空间布局优化方案。结果表明：① 1961—2019年,中国马铃薯的总消费量由1290万t增加到了9152.5万t,其中食用消费结构变化最为显著。② 2022—2040年,中国马铃薯年均需求量为1.10亿t,基本适宜及以上程度马铃薯种植区域共计5423万hm²,种植其中532万hm²可满足相应消费需求。③ 基于适宜度指数的未来中国马铃薯最优生产布局为东北一季作区、华北一季作区、西北一季作区和西南一二季混作区（包含55个县级区域）。建议坚持整体推进与重点突破相统一的原则,推动马铃薯种植布局优化升级。研究结果能够为中国粮食安全政策制定和马铃薯种植空间布局提供理论参考。