印度农田扩张对区域气候影响的数值模拟

选取耕地面积居世界第二位的印度作为研究区域,利用中国自主研发的区域气候模式(RIEMS2.0)和土地利用变化资料,进行潜在植被和雨养农田的长时间积分模拟对比试验,分析了印度农田扩张对区域气候的影响及其机制。结果表明:农田扩张使得印度区域平均气温升高0.1℃,平均降水强度减少0.1 mm·d~(-1),总降水量减少12.8%;农田扩张的气候效应存在明显区域差异和季节差异,在副热带湿润区气温增加0.5~1.0℃,在干旱和半干旱区气温增加0.3~0.5℃,在热带地区气温则下降;农田扩张使得季风前期和冬季气温分别增加0.5℃和0.2℃;季风后期气温降低0.5℃,季风季节气温没有明显变化;在副热带湿润区、干旱和半干旱区降水明显减少,干旱季节特别是季风前期降水减少最为显著,达到0.3 mm·d~(-1);印度农田扩张使得年平均感热通量增加、潜热通量减少,其中植被的蒸散作用引起的潜热通量的变化,尤其是季风前期潜热通量明显减少,是区域气温升高、降水减少的重要原因;农田扩张使得印度大陆上空(850 h Pa高度)受较弱的辐散环流控制,辐散下沉气流是造成当地气温升高、降水减少的又一原因。     

农田灌溉对印度区域气候的影响模拟

为满足人类对粮食的需求,全球灌溉农田面积迅速扩张,农田灌溉对区域气候的影响引起广泛地关注。利用区域环境系统集成模式(RIEMS2.0)和最新的土地利用变化资料,选取农田灌溉面积最大的印度区域作为研究区域,进行雨养农田和灌溉农田的对比试验,探讨农田灌溉对区域气候的影响。结果表明:(1)农田灌溉使得印度区域年平均气温降低1.4℃,年平均降水率增加0.35mm/d。农田灌溉对印度区域气候的影响存在明显的季节波动,季风前期及6月份该区域气候对下垫面变化的响应最为敏感;7-9月各气候要素变化较小。(2) 农田灌溉使得印度区域地表净辐射增加,且地表净辐射在潜热通量和感热通量之间的分配发生了较大的改变,潜热通量增加,感热通量减少;对地表起冷却作用;同时由于土壤湿度增加,蒸散作用增强,大气中水汽含量增加,潜热不稳定能量增加,导致对流性降水增加。     

宁南半干旱地区农田和草地生态系统能量通量的季节变化

根据2002~2003年宁南山区不同下垫面小气候考察资料,用能量平衡法计算了不同下垫面不同季节的感热、潜热通量。分析结果表明:(1)宁南半干旱地区夏季农田和草地的净辐射峰值可达到700W/m2以上,土壤热通量的值比净辐射小1个量级。同类下垫面净辐射通量日积分值夏季>春季>秋季>冬季。(2)宁南半干旱山区感热输送强度以典型草地的最大,其次是禁牧草地,稀树草地的最小。春季各类下垫面地表热量平衡以感热输送为主。在春、夏、秋季的晴天,感热通量日积分值为正,冬季为负。(3)农田在夏、秋季、冬季水汽输送大于各类草地的,其次是稀树草地的,典型草地向上的水汽输送量是最小的。夏季白天农田β在0.2~0.7,稀树草地β为0.2~1.0,能量输送以潜热为主。禁牧草地β为0.2~9.2,典型草地为1.5~13.1,能量输送以感热为主。(4)宁南半干旱地区宜退耕,发展典型草原,在水分充足的山地背阴坡少量发展稀树草地。     

重庆缙云山针阔混交林水汽通量特征及其影响因子

利用涡度相关技术于2019年9月-2020年8月在重庆缙云山针阔混交林生态系统观测了水汽通量和其他环境要素。基于观测数据, 分析了水汽通量特征及其与环境因子的关系。结果表明: (1)针阔混交林生态系统能量闭合率为0.77, 且通量足迹高贡献区域所处方向与风玫瑰图的全年主风方向(东北风向)一致, 累计通量贡献区变异系数比较小, 证明涡度相关技术在研究区适应性较好, 数据可靠。(2)缙云山针阔混交林的全年水汽通量基本为正值, 月平均日变化范围为-0.001-6.623 mmol·m^-2·s^-1, 说明研究区为水汽源。水汽通量月平均日变化和季节变化均为单峰趋势。夏季水汽通量平均值最大(4.620 mmol·m^-2·s^-1), 变化趋势强; 冬季水汽通量值最低(2.077 mmol·m^-2·s^-1), 变化趋势弱。(3)该地区全年蒸散总量(792.40 mm)占降水总量(1 489.18 mm)的53.12%, 夏季的蒸散量(325.53 mm)和降水量(680.52 mm)最高, 分别占到全年蒸散量和降水量的41%和46%。缙云山针阔混交林生态系统站点与其他地区不同生态系统站点对比, 得出全年蒸散量为湿地>森林>农田。(4)净辐射、气温、饱和水汽压差和风速对水汽通量的影响在各季节均显著, 净辐射、气温和饱和水汽压差与水汽通量呈正相关关系, R²最大分别为0.85、0.53和0.60, 风速与水汽通量呈负相关关系, R²为0.61, 均是夏季的相关性最高, 其中净辐射和气温是影响水汽通量的最主要因子。     

宁南退耕还草区近地面湍流通量观测初报

根据 2 0 0 2～ 2 0 0 3年小气候考察资料 ,分别分析了四季晴天条件下宁南退耕还草区净辐射、感热、潜热和土壤热通量比例和变化特征。结果表明 ,近地层各通量有较规则的日变化。白天 ,感热通量占净辐射的 5 0 %以上 ,一般达 80 %～ 10 0 %。只有夏季全天和秋季白天的潜热通量为正 ,在春季的早晨和秋季的傍晚潜热通量为负。冬春季节土壤的热量收支大于夏秋季节。     

神农架大九湖亚高山泥炭湿地水汽通量特征及其与相关环境因子的关系

以神农架大九湖亚高山泥炭湿地为对象,采用涡度相关技术,通过采集湿地水汽通量的年际数据,并进行数据统计和分析,研究水汽通量特征及其与环境因子的关系。结果显示:(1)大九湖泥炭湿地全年蒸散量占降水量的58.59%,能够满足大九湖生态系统水汽循环的需要。(2)大九湖泥炭湿地的水汽通量全年各月份日均变化大多为正值,即释放水汽,表明该地区总体表现为水汽源;在季节尺度上,水汽通量最大值出现在夏季,夏季水汽通量日均变化幅度最大。(3)净辐射月均变化幅度较大,其中夏季净辐射最大,占全年的34.96%。各季节的净辐射与水汽通量均呈正相关,春季、夏季和秋季的拟合效果(R2)均超过0.7,夏季最高(0.8347),且高于其他同纬度6个地区。(4)除2018年1月外,各月份水汽通量与气温均呈显著正相关,特别是夏季最显著相关,这与夏季植物蒸腾和水分蒸发旺盛有关。(5)气温和净辐射对水汽通量的影响在各季节均显著,但各季节间有所差异。研究表明净辐射在大九湖泥炭湿地水汽循环中的作用大于气温对水汽通量的影响。     

亚热带毛竹林生态系统能量通量及平衡分析

利用开路涡度相关系统和常规气象观测仪器,对亚热带(浙江省)毛竹林生态系统2011年的净辐射、显热通量、潜热通量、土壤热通量以及气温、地温、降雨量等气象要素进行了连续观测,定量分析了毛竹林生态系统能量通量的变化和各能量分量的分配特征,并计算了能量闭合度以及波文比。结果表明:毛竹林全年净辐射为2628.00 MJ/m2,显热通量为576.80 MJ/m2,潜热通量为1666.77 MJ/m2,土壤热通量为-7.52 MJ/m2,土壤为热源,各能量分量季节变化明显,日变化基本呈单峰型曲线变化。显热通量占净辐射的22.0%,潜热通量占63.4%,毛竹林生态系统潜热通量为能量散失的主要形式。波文比逐月变化规律不明显,波动较大,在0.07—1.77之间变化,能量平衡比率法得出毛竹林年能量闭合度为0.85,月平均闭合度为0.84,能量闭合度高于线性回归法计算结果,但仍有15%的能量不闭合。     

中国农田土壤呼吸速率及驱动因子

土壤呼吸在全球碳收支中具有重要地位.研究中国典型农业区土壤呼吸的时空格局及影响因素,有助于构建区域尺度土壤呼吸定量评价模型,能够为评估中国乃至全球农业生态系统碳/源汇特征提供依据.本研究整合了2000~2012年中国农田生态系统土壤呼吸的主要研究成果,分析了华南、西南、华北、西北和东北5个典型农业区土壤呼吸的季节变化和区域差异,以及影响土壤呼吸的主要驱动因子.结果表明,5个典型农业区的土壤呼吸均存在明显的季节变化特征;中国农田生态系统年均土壤呼吸速率为(682.8±18.3)g C m?2.5个典型农业区年均土壤呼吸速率大小表现为华南区西南区华北区东北区西北区.全国农业土壤的年呼吸通量为(0.90±0.02)Pg C;水作和旱作两种土地利用类型间土壤呼吸速率差异显著(P0.05),旱作土壤呼吸速率约为水作的1.3倍;不同作物类型间土壤呼吸速率差异显著(P0.05),其排序为棉花玉米大豆水稻小麦;农田土壤呼吸与年均气温、土壤温度、土壤含水量和净初级生产力等影响因素呈显著正相关(P0.01),而与年均降水量的相关性不显著.     

神农架大九湖亚高山泥炭湿地水汽通量特征及其与相关环境因子的关系

以神农架大九湖亚高山泥炭湿地为对象,采用涡度相关技术,通过采集湿地水汽通量的年际数据,并进行数据统计和分析,研究水汽通量特征及其与环境因子的关系。结果显示：（1）大九湖泥炭湿地全年蒸散量占降水量的58.59%,能够满足大九湖生态系统水汽循环的需要。（2）大九湖泥炭湿地的水汽通量全年各月份日均变化大多为正值,即释放水汽,表明该地区总体表现为水汽源;在季节尺度上,水汽通量最大值出现在夏季,夏季水汽通量日均变化幅度最大。（3）净辐射月均变化幅度较大,其中夏季净辐射最大,占全年的34.96%。各季节的净辐射与水汽通量均呈正相关,春季、夏季和秋季的拟合效果（R²）均超过0.7,夏季最高（0.8347）,且高于其他同纬度6个地区。（4）除2018年1月外,各月份水汽通量与气温均呈显著正相关,特别是夏季最显著相关,这与夏季植物蒸腾和水分蒸发旺盛有关。（5）气温和净辐射对水汽通量的影响在各季节均显著,但各季节间有所差异。研究表明净辐射在大九湖泥炭湿地水汽循环中的作用大于气温对水汽通量的影响。     

黄土高原农牧交错带稀疏自然植被生态系统的地表能量特征

基于2011-2012年黄土高原农牧交错带稀疏自然植被生态系统的地表能量通量以及气象数据,对该地区能量平衡各分量(净辐射、感热、潜热和土壤热通量)以及波文比进行日、季节动态的特征分析,研究了潜热通量和感热通量对不同强度降雨事件响应程度的差异,并分析了潜热通量和感热通量的主控因子.结果表明:该地区净辐射、感热、潜热和土壤热通量的日、季节动态曲线均为单峰型曲线,净辐射、感热通量、潜热通量和土壤热通量的年平均值分别为78.19、33.32、24.91和2.65 W·m-2.在全年能量收支平衡中,感热通量占净辐射的43％,潜热通量占32％,土壤热通量占3％,表明对于黄土高原农牧交错带自然稀疏灌木生态系统,全年能量主要以感热的形式交换.生长季感热和潜热占净辐射的比例相同(36％);而在非生长季,感热占主导,占净辐射的比例高达54％.潜热通量在强、弱降雨事件发生后明显升高,感热通量则明显下降.潜热通量与净辐射、水汽压差及植被参数均显著相关,感热通量与净辐射及空气温度梯度显著相关.     

Varying responses in mean surface air temperature from land use/cover change in different seasons over northern China

Research on the impacts of land use change on climate change has become a foremost topic in the field of global climate change research. Although many researchers have studied the impacts of LUCC, data related to these impacts on the Chinese climate system remain sparse because of the diversity of China’s regional changes in land use, especially related to agricultural changes. Therefore, additional studies are needed that address regional LUCC in combination with climate modeling. Two simulations with current land use/cover patterns and potential natural vegetation cover were used to investigate the impact of LUCC on surface air temperature in northern China. Simulations of 11 years of climate in northern China (1 January 1990–31 December 2000) were carried out using Regional Environment Integrated Modeling System 2.0 (RIEMS2.0). The results showed that: (1) When potential natural vegetation cover types were changed to current vegetation cover types, mean summer surface air temperature decreased in the central northeastern area, eastern Gansu Province and Ningxia Hui Autonomous Region, but increased in Shanxi, Henan and Anhui provinces. Also, surface air temperature changed significantly on a local scale in the central northeastern area, central Henan Province and eastern Gansu Province (P < 0.05). In winter, major portions of the study area exhibited non-significant decreases in mean surface air temperature. (2) In summer, a temperate forests removal simulation in northern China behaved more like a tropical forests removal simulation. In winter, removal of the temperate forests in northern China behaved more like a boreal forests removal simulation. In model grids where forest were converted to cropland, the net radiation absorbed has less influence on surface air temperature at lower vs. higher latitudes. Further, latent heat flux has a stronger influence on surface air temperature at lower latitudes.     

黄河流域植被时空变化及其对气候要素的响应

在气候变化和人类活动的双重作用下,黄河流域生态环境不断发生变化。探讨植被生长动态对于实施生态保护政策至关重要。利用Advanced Very High Resolution Radiometer(AVHRR) Leaf Area Index(LAI)遥感资料,结合气候要素数据,分析1981—2017年黄河流域植被覆盖的时空分布特征,探讨气候要素对其变化的影响及贡献率。研究结果表明：(1)时序上,黄河流域植被覆盖呈显著增长趋势,夏季植被覆盖的增长幅度和年际波动最大,冬季植被覆盖呈缓慢平稳增长,波动最小。(2)空间上,植被覆盖显著提高的区域占整个区域的52.1%,主要分布在中东部平原;显著降低的区域占4%,主要分布在北部和西部高原山地;生态脆弱的区域植被覆盖率大多有不同程度的提高,但生态环境良好的部分区域植被覆盖率降低。(3)时序上,黄河流域植被覆盖与气温具有显著的正相关关系。春夏冬三季的植被覆盖与气温呈显著正相关,与降水呈不显著关系;秋季的植被覆盖与气温和降水量均呈显著正相关;春秋冬三季的植被覆盖与太阳辐射呈不显著负相关,夏季的植被覆盖与太阳辐射呈不显著正相关。春夏秋冬四季的气温对植被覆...     

Reforestation and surface cooling in temperate zones: Mechanisms and implications

Land‐use/cover change (LUCC) is an important driver of environmental change, occurring at the same time as, and often interacting with, global climate change. Reforestation and deforestation have been critical aspects of LUCC over the past two centuries and are widely studied for their potential to perturb the global carbon cycle. More recently, there has been keen interest in understanding the extent to which reforestation affects terrestrial energy cycling and thus surface temperature directly by altering surface physical properties (e.g., albedo and emissivity) and land–atmosphere energy exchange. The impacts of reforestation on land surface temperature and their mechanisms are relatively well understood in tropical and boreal climates, but the effects of reforestation on warming and/or cooling in temperate zones are less certain. This study is designed to elucidate the biophysical mechanisms that link land cover and surface temperature in temperate ecosystems. To achieve this goal, we used data from six paired eddy‐covariance towers over co‐located forests and grasslands in the temperate eastern United States, where radiation components, latent and sensible heat fluxes, and meteorological conditions were measured. The results show that, at the annual time scale, the surface of the forests is 1–2°C cooler than grasslands, indicating a substantial cooling effect of reforestation. The enhanced latent and sensible heat fluxes of forests have an average cooling effect of ?2.5°C, which offsets the net warming effect (+1.5°C) of albedo warming (+2.3°C) and emissivity cooling effect (?0.8°C) associated with surface properties. Additional daytime cooling over forests is driven by local feedbacks to incoming radiation. We further show that the forest cooling effect is most pronounced when land surface temperature is higher, often exceeding ?5°C. Our results contribute important observational evidence that reforestation in the temperate zone offers opportunities for local climate mitigation and adaptation.     

An empirical test of the relative and combined effects of land‐cover and climate change on local colonization and extinction

Land‐cover and climate change are two main drivers of changes in species ranges. Yet, the majority of studies investigating the impacts of global change on biodiversity focus on one global change driver and usually use simulations to project biodiversity responses to future conditions. We conduct an empirical test of the relative and combined effects of land‐cover and climate change on species occurrence changes. Specifically, we examine whether observed local colonization and extinctions of North American birds between 1981–1985 and 2001–2005 are correlated with land‐cover and climate change and whether bird life history and ecological traits explain interspecific variation in observed occurrence changes. We fit logistic regression models to test the impact of physical land‐cover change, changes in net primary productivity, winter precipitation, mean summer temperature, and mean winter temperature on the probability of Ontario breeding bird local colonization and extinction. Models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local colonization for 30%, 27%, and 29% of species, respectively. Conversely, models with climate change, land‐cover change, and the combination of these two drivers were the top ranked models of local extinction for 61%, 7%, and 9% of species, respectively. The quantitative impacts of land‐cover and climate change variables also vary among bird species. We then fit linear regression models to test whether the variation in regional colonization and extinction rate could be explained by mean body mass, migratory strategy, and habitat preference of birds. Overall, species traits were weakly correlated with heterogeneity in species occurrence changes. We provide empirical evidence showing that land‐cover change, climate change, and the combination of multiple global change drivers can differentially explain observed species local colonization and extinction.     

我国6ka BP植被变化的气候模拟研究

根据花粉恢复的古植被表面中国森林区的常绿阔叶,和叶阔叶林以及针叶林在6Ka BP向北扩张,反映了6ka BP夏季和冬季均比现代温暖的气候特征,然而,根据地球轨道参数变化驱动的气候模式,由于6kaBP时北半球夏季太阳辐射高于现代,而冬季太阳辐射低于现代,模拟的6ka BP夏季温度比规划温暖,但冬季比现代寒冷,模拟得出的冬季寒冷与地 冬季增温不一致,说明6ka BP的气候和植被变化并不完全受到太阳辐射变化的控制,针对这一重大缺陷,我们利用具有陆面过程的全球大气环流模型（ACCM＋SsiB),采用了外动力太阳辐射变化和古地表状史的强迫边界场进行了古气候模拟试验,模拟结果能够捕捉到亚洲季风地区6kaBP冬季气候变暖的气候特征,初步阐明6ka BP植被变化的气候动力学机制。     

Uncertainties in the 20th century carbon budget associated with land use change

Uncertainties in the 20th century carbon budget associated with the treatment of land use change (LUC) are assessed using the Canadian Centre for Climate Modelling and Analysis (CCCma) first‐generation Earth System Model (CanESM1). Eight coupled climate carbon cycle simulations are performed using different reconstructions of 1850–2000 land cover derived from historical information on changes in cropland and pasture area. The simulations provide estimates of the emissions associated with LUC, the relative contribution of changes in cropland and pasture to LUC emissions and the uncertainty associated with differences among historical data sets of crop area as well as in the manner in which the historical land cover data are constructed. The resulting estimates of the amount of biomass deforested over the 1850–2000 period range from 63 to 145 Pg C with cumulative implied LUC emissions ranging from 40 to 77 Pg C. These values of LUC emissions are considerably lower than Houghton's estimate of 156 Pg C. The year 2000 atmospheric CO₂ concentration ranges between 371.1 ± 3.7 ppm depending on the data set used and the manner in which historical land cover is constructed. This compares to the observed value of 369.6 ppm at Mauna Loa and is 17.3 ± 6.3 ppm larger than for simulations without LUC. Although increases in cropland result in the expected increase in LUC emissions, changes in pasture area decrease these emissions because of carbon sequestration in soils.     

未来10年黄土高原气候变化对农业和生态环境的影响

利用区域气候模式PRECIS输出的未来A2和B2气候情景及基准气候时段逐日资料,选择生态环境极其脆弱的黄土高原为研究区,分析了未来10a黄土高原气候变化特征及其对主要农作物和生态环境的影响。结果表明,未来10a,黄土高原光热资源增加,降水量减少。增温将对冬小麦和春玉米产量影响较大,对马铃薯产量的影响程度可能较小,但降水量减少对主要农作物的产量都有较大影响。在主要作物品种不发生较大变化的前提下,作物生育期太阳辐射和积温增加可能导致生育期需水量增加10%-15%,冬小麦、春玉米和马铃薯的播期分别延迟或提前1-3d,收获期提前1-2d,生育期缩短3-5d,可能引起冬小麦和春玉米气候产量下降50%-100%。未来10a,降水量减少可能导致草地盖度的增幅下降和人工林地稀疏化,引起黄土高原片状水力侵蚀程度下降。但突发性暴雨洪水和土地利用现状改变可能增强切沟溯源冲蚀能力,增加了黄土高原水土流失和农田及道路被冲毁的风险。     

季节增温方式对小兴安岭红松针阔混交林演替的潜在影响

应用林窗模型LINKAGES对小兴安岭红松针阔混交林在不同季节增温方式下的未来演替过程进行了模拟预测.以温度增加5℃、降水无明显变化作为未来变暖气候的模拟假设,共设计3种气候变暖方式预案,分别为冬季增温幅度大于夏季、冬季与夏季增温幅度相同以及冬季增温幅度小于夏季.模拟结果表明,当冬季增温幅度大于夏季时,小兴安岭现存林分的演替受气候变暖的影响相对最小,树种组成仍然能够保持较为稳定的针阔混交林状态;当冬季增温幅度小于夏季时,现存林分的演替受气候变暖的影响最显著,树种衰退最迅速.可见,小兴安岭针阔混交林的演替与未来的增温方式关系密切,上限温度是现存树种能否继续存活的重要决定因子.     

Human modification of the landscape and surface climate in the next fifty years

Human modification of the landscape potentially affects exchanges of energy and water between the terrestrial biosphere and the atmosphere. This study develops a possible scenario for land cover in the year 2050 based on results from the IMAGE 2 (Integrated Model to Assess the Greenhouse Effect) model, which projects land‐cover changes in response to demographic and economic activity. We use the land‐cover scenario as a surface boundary condition in a biophysically‐based land‐surface model coupled to a general circulation model for a 15‐years simulation with prescribed sea surface temperature and compare with a control run using current land cover. To assess the sensitivity of climate to anthropogenic land‐cover change relative to the sensitivity to decadal‐scale interannual variations in vegetation density, we also carry out two additional simulations using observed normalized difference vegetation index (NDVI) from relatively low (1982–83) and high (1989–90) years to describe the seasonal phenology of the vegetation. In the past several centuries, large‐scale land‐cover change occurred primarily in temperate latitudes through conversion of forests and grassland to highly productive cropland and pasture. Several studies in the literature indicate that past changes in surface climate resulting from this conversion had a cooling effect owing to changes in vegetation morphology (increased albedo). In contrast, this study indicates that future land‐cover change, likely to occur predominantly in the tropics and subtropics, has a warming effect governed by physiological rather than morphological mechanisms. The physiological mechanism is to reduce carbon assimilation and consequently latent relative to sensible heat flux resulting in surface temperature increases up to 2 °C and drier hydrologic conditions in locations where land cover was altered in the experiment. In addition, in contrast to an observed decrease in diurnal temperature range (DTR) over land expected with greenhouse warming, results here suggest that future land‐cover conversion in tropics could increase the DTR resulting from decreased evaporative cooling during the daytime. For grid cells with altered land cover, the sensitivity of surface temperature to future anthropogenic land‐cover change is generally within the range induced by decadal‐scale interannual variability in vegetation density in temperate latitudes but up to 1.5 °C warmer in the tropics.     

A global risk assessment of primates under climate and land use/cover scenarios

Primates are facing an impending extinction crisis, driven by extensive habitat loss, land use change and hunting. Climate change is an additional threat, which alone or in combination with other drivers, may severely impact those taxa unable to track suitable environmental conditions. Here, we investigate the extent of climate and land use/cover (LUC) change‐related risks for primates. We employed an analytical approach to objectively select a subset of climate scenarios, for which we then calculated changes in climatic and LUC conditions for 2050 across primate ranges (N = 426 species) under a best‐case scenario and a worst‐case scenario. Generalized linear models were used to examine whether these changes varied according to region, conservation status, range extent and dominant habitat. Finally, we reclassified primate ranges based on different magnitudes of maximum temperature change, and quantified the proportion of ranges overall and of primate hotspots in particular that are likely to be exposed to extreme temperature increases. We found that, under the worst‐case scenario, 74% of Neotropical forest‐dwelling primates are likely to be exposed to maximum temperature increases up to 7°C. In contrast, 38% of Malagasy savanna primates will experience less pronounced warming of up to 3.5°C. About one quarter of Asian and African primates will face up to 50% crop expansion within their range. Primary land (undisturbed habitat) is expected to disappear across species' ranges, whereas secondary land (disturbed habitat) will increase by up to 98%. With 86% of primate ranges likely to be exposed to maximum temperature increases >3°C, primate hotspots in the Neotropics are expected to be particularly vulnerable. Our study highlights the fundamental exposure risk of a large percentage of primate ranges to predicted climate and LUC changes. Importantly, our findings underscore the urgency with which climate change mitigation measures need to be implemented to avert primate extinctions on an unprecedented scale.