两种温室气体排放方案下我国水稻产量变化模拟

利用最新的温室气体和SO₂排放方案,即政府间气候变化委员会(IPCC)排放情景特别报告(SRES)的A2和B2方案,通过区域气候模式PRECIS和作物模型CERES-Rcie相嵌套,在50 km×50 km网格尺度下,模拟了未来2080年我国水稻产量的变化.结果表明,两种温室气体排放方案下,我国水稻的年平均单产水平各地有增有减,增产地区主要集中在长江及长江流域以南地区,其中四川和湖北交界的山区增产幅度最大,减产地区主要集中在华北平原和东北平原;由于CO₂的肥效作用,A2温室气体排放方案对我国水稻单产的正面影响大于B2方案,A2排放方案下,我国水稻总产呈现一定程度的上升趋势,B2排放方案下,水稻总产表现为少量下降.     

太湖地区不同轮作模式对稻田温室气体(CH4和N2O)排放的影响

通过田间试验,研究了太湖地区不同轮作模式下稻季温室气体排放规律.结果表明: 水稻生长季CH₄排放呈先升高后降低趋势,CH₄排放主要集中在水稻生育前期,烤田后至水稻收获期间CH₄排放量较低;N₂O的排放主要集中在3次施肥及烤田期.稻季排放的CH₄对全球增温潜势(GWP)的贡献远高于N₂O,各处理所占比例为94.7%～99.6%,是温室气体减排的主要对象.不同轮作模式下,稻季CH₄排放总量及其GWP存在显著差异,表现为小麦-水稻>紫云英-水稻>休闲-水稻轮作;稻季N₂O排放总量及其GWP没有显著性差异.与不施肥处理相比,紫云英-水稻轮作模式下施加氮肥显著降低了CH₄排放量和GWP,但不同氮肥用量下的CH₄排放量和GWP没有显著性差异,而紫云英还田稻季施氮240 kg·hm^-2下的水稻产量却最高.综合经济效益和环境效益,紫云英还田稻季施氮240 kg·hm^-2下的增产减排综合效果更好,是值得当地推广的耕作制度.     

太湖地区不同轮作模式对稻田温室气体(CH4和N2O)排放的影响

通过田间试验,研究了太湖地区不同轮作模式下稻季温室气体排放规律.结果表明: 水稻生长季CH₄排放呈先升高后降低趋势,CH₄排放主要集中在水稻生育前期,烤田后至水稻收获期间CH₄排放量较低;N₂O的排放主要集中在3次施肥及烤田期.稻季排放的CH₄对全球增温潜势(GWP)的贡献远高于N₂O,各处理所占比例为94.7%～99.6%,是温室气体减排的主要对象.不同轮作模式下,稻季CH₄排放总量及其GWP存在显著差异,表现为小麦-水稻>紫云英-水稻>休闲-水稻轮作;稻季N₂O排放总量及其GWP没有显著性差异.与不施肥处理相比,紫云英-水稻轮作模式下施加氮肥显著降低了CH₄排放量和GWP,但不同氮肥用量下的CH₄排放量和GWP没有显著性差异,而紫云英还田稻季施氮240 kg·hm^-2下的水稻产量却最高.综合经济效益和环境效益,紫云英还田稻季施氮240 kg·hm^-2下的增产减排综合效果更好,是值得当地推广的耕作制度.     

缓/控释尿素对稻田周年CH4和N2O排放的影响

通过田间试验研究了不同缓/控释尿素对水稻产量和稻田周年温室气体排放的影响,评估生产单位质量水稻的温室气体排放量.结果表明: 优化施肥(OPT)处理在减氮(N)21.4%条件下产量与习惯施肥(FFP)处理持平,同时减少了稻田周年CH₄和N₂O的排放,其中水稻季CH₄和N₂O分别减排12.6%和12.5%,休闲季N₂O减排33.3%.与OPT处理相比,控释尿素(CRU)处理在水稻季CH₄减排28.9%,休闲季CH₄零排放;硝化抑制剂(DMPP)处理在水稻季CH₄和N₂O分别减排41.6%和85.7%,休闲季CH₄和N₂O分别减排76.9%和6.5%.休闲季节N₂O排放占周年N₂O排放的76.8%～94.9%,是评价整个稻田温室气体排放不容忽视的因素.OPT、CRU和DMPP处理生产1.0 kg稻谷的温室气体排放强度分别为0.50、0.41和0.33 kg·kg^-1,综合考虑周年的温室气体排放总量和产量,尿素和硝化抑制剂配合施用可以在保证水稻产量的情况下,减少温室气体的排放.     

缓/控释尿素对稻田周年CH4和N2O排放的影响

通过田间试验研究了不同缓/控释尿素对水稻产量和稻田周年温室气体排放的影响,评估生产单位质量水稻的温室气体排放量.结果表明: 优化施肥(OPT)处理在减氮(N)21.4%条件下产量与习惯施肥(FFP)处理持平,同时减少了稻田周年CH₄和N₂O的排放,其中水稻季CH₄和N₂O分别减排12.6%和12.5%,休闲季N₂O减排33.3%.与OPT处理相比,控释尿素(CRU)处理在水稻季CH₄减排28.9%,休闲季CH₄零排放;硝化抑制剂(DMPP)处理在水稻季CH₄和N₂O分别减排41.6%和85.7%,休闲季CH₄和N₂O分别减排76.9%和6.5%.休闲季节N₂O排放占周年N₂O排放的76.8%～94.9%,是评价整个稻田温室气体排放不容忽视的因素.OPT、CRU和DMPP处理生产1.0 kg稻谷的温室气体排放强度分别为0.50、0.41和0.33 kg·kg^-1,综合考虑周年的温室气体排放总量和产量,尿素和硝化抑制剂配合施用可以在保证水稻产量的情况下,减少温室气体的排放.     

日本长期不同施肥稻田N2O和CH4排放特征及其环境影响

观测了75年长期连续不施肥、施硫酸铵、施熟制水稻秸秆与豆饼混合堆肥、施绿肥苜蓿4种处理下日本单季稻田温室气体N₂O和CH₄的排放特征及其环境影响.结果表明： 在水稻生长季节,不同处理间N₂O排放无显著差异,但CH₄排放差异显著;长期连续施用有机肥虽然没有增加N₂O排放却促进了CH₄排放.各系统排放N₂O和CH₄所产生的累积全球增温潜势（GWP）以绿肥处理最大（310.7 g CO₂e·m^-2）,熟制有机堆肥次之（151g CO₂e·m^-2）,硫酸铵处理最小（60.6 g CO₂e·m^-2）.稻田系统的GWP主要来自CH₄排放,控制和减少稻田系统CH₄排放是稻田温室气体减排的核心问题.长期连续施用熟制有机堆肥既能增加土壤有机质,改善地力,满足水稻高产,又能实现CH₄减排,是实践中值得推荐的水稻生产模式.     

日本长期不同施肥稻田N2O和CH4排放特征及其环境影响

观测了75年长期连续不施肥、施硫酸铵、施熟制水稻秸秆与豆饼混合堆肥、施绿肥苜蓿4种处理下日本单季稻田温室气体N₂O和CH₄的排放特征及其环境影响.结果表明： 在水稻生长季节,不同处理间N₂O排放无显著差异,但CH₄排放差异显著;长期连续施用有机肥虽然没有增加N₂O排放却促进了CH₄排放.各系统排放N₂O和CH₄所产生的累积全球增温潜势（GWP）以绿肥处理最大（310.7 g CO₂e·m^-2）,熟制有机堆肥次之（151g CO₂e·m^-2）,硫酸铵处理最小（60.6 g CO₂e·m^-2）.稻田系统的GWP主要来自CH₄排放,控制和减少稻田系统CH₄排放是稻田温室气体减排的核心问题.长期连续施用熟制有机堆肥既能增加土壤有机质,改善地力,满足水稻高产,又能实现CH₄减排,是实践中值得推荐的水稻生产模式.     

天目山常绿落叶阔叶混交林土壤温室气体排放特点

采用静态箱-气象色谱法, 将试验样地按照自上而下分为A、B、C、D 四个梯度的采样点。研究了浙江天目山常绿落叶阔叶混交林2013 年3 月-11 月期间土壤温室气体排放的时空变化特点, 并分析了不同梯度的土壤温湿度与气体排放通量的相关性。结果表明: (1)天目山常绿落叶阔叶混交林土壤CO₂ 和CH₄ 两种温室气体排放/吸收季节变化特征较一致, 即夏季>春季>秋季; N₂O 排放通量季节变化表现为夏季>秋季>春季。其中, CO₂ 和N₂O 表现为土壤的排放源, CH₄ 为大气的吸收汇。(2)空间上, CO₂ 通量大小表现为: D 采样点> A 采样点> C 采样点 > B 采样点; 土壤对CH4吸收速率表现为A 采样点 > C 采样点 > B 采样点 > D 采样点; 土壤N₂O 通量大小依次为: A 采样点 > C 采样点 > B采样点 > D 采样点。(3)温度是影响天目山常绿落叶阔叶混交林土壤CO₂ 通量重要因子; CH₄ 的吸收通量随温度的升高和湿度的降低而增大; 在海拔较低的地区, 温度是N₂O 通量的重要影响因子, 海拔较高地区, 湿度是N₂O 通量的重要限制因子。     

黑土稻田CH4与N2O排放及减排措施研究

通过对黑土稻田CH₄和N₂O排放的观测,发现水稻生长季CH₄和N₂O排放量低于全国其它地区稻田.CH₄和N₂O排放之间存在互为消长关系(r=-0.513,P<0.05).但在同样施肥水平条件下,间歇灌溉与长期淹灌相比,CH₄排放明显减少而N₂O略有增加,其相对综合温室效应被大大减少且水稻产量未受影响.为此,间歇灌溉可作为减少稻田温室气体排放的水分管理措施.另外,通过对CH₄和N₂O排放的相关微生物过程探讨,揭示产甲烷菌数与CH₄排放间呈显著性正相关(R²=0.82,P<0.05),硝化菌数和反硝化菌数与N₂O排放有重要关系.     

剔除林下灌草和添加翅荚决明对尾叶桉林土壤温室气体排放的影响

森林土壤是CO₂、CH₄和N₂O等温室气体的重要排放源。采用静态箱/色谱分析技术对中国科学院鹤山丘陵综合开放试验站的尾叶桉(Eucalyptus urophylla)林土壤CO₂、CH₄和N₂O排放通量进行了原位测定, 研究剔除林下灌草和添加翅荚决明(Cassia alata)对尾叶桉林土壤温室气体排放的影响。结果表明: 尾叶桉林土壤CO₂排放通量在湿季维持在较高水平, 在旱季则明显降低。CH₄和N₂O在湿季波动幅度较大, 在旱季则相对稳定。土壤CO₂和CH₄通量峰值均出现在湿季, 但N₂O峰值出现在旱季的12月。尾叶桉林土壤在不同处理下可能是CH₄的源, 也可能是CH₄的汇, 而对于CO₂和N₂O则主要是源。尾叶桉林下剔除灌草及添加翅荚决明能显著增大土壤CO₂和N₂O的排放, 但林下灌草剔除后有利于CH₄的吸收, 添加翅荚决明有利于CH₄的排放。表层土壤温度和湿度是影响土壤温室气体排放的首要因子。呼吸底物(氮源)和土壤微生物量也是影响土壤温室气体排放的重要因子。     

中国五味子分布范围及气候变化影响预测

结合文献资料、标本记录和实际调查绘制了中国五味子分布图,并基于五味子分布范围和21个环境因子,运用Maxent软件预测了IPCC A2和A1B两种气候变化情景下21世纪50和80年代中国五味子分布范围.结果表明:五味子分布于中国15省/市(区),涉及151个县,随着纬度和经度的降低,面积逐渐减少,黑龙江、辽宁、内蒙古和吉林4省(区)是五味子主要分布区域;五味子在中国的潜在分布面积为145.12×104 km2,较好生境面积占48.6％,主要分布在长白山山脉、大兴安岭、小兴安岭以及河北省与辽宁省相邻区域;最佳生境面积仅占0.3％,主要分布在辽宁省的宽甸满族自治县、本溪满族自治县、桓仁满族自治县以及吉林省的安图县、和龙市和内蒙古自治区牙克石市.在A1B和A2两种情景下,未来五味子潜在分布区逐渐减少,A2情景的五味子潜在分布区下降比率大于AIB情景;至21世纪50年代,A1B和A2情景下五味子潜在分布区将缩减为当前潜在分布区面积的84.0％和81.5％;至21世纪80年代,A2情景下五味子潜在分布区仅为当前的0.5％,B2情景下五味子潜在分布区减至当前的1/2.     

北京山区3种暖温带森林生态系统未来碳平衡的模拟与分析

使用LPJ-GUESS植被动态模型, 在北京山区研究了未来100a以辽东栎 (Quercus liaotungensis) 为优势种的落叶阔叶林、以白桦 (Betula platyphylla) 为主的阔叶林和油松 (Pinus tabulaeformis) 为优势种的针阔混交林的碳变化, 定量分析了生态系统净初级生产力 (NPP) 、土壤异养呼吸 (Rh) 、净生态系统碳交换 (NEE) 和碳生物量 (Carbon bio-mass) 对两种未来气候情景 (SRES A2和B2) 以及相应大气CO2浓度变化情景的响应特征。结果表明:1) 未来100a两种气候情景下3种森林生态系统的NPP和Rh均增加, 并且A2情景下增加的程度更大;2) 由于3种生态系统树种组成的不同, 未来气候情景下各自NPP和Rh增加的比例不同, 导致三者NEE的变化也相异:100a后辽东栎林由碳汇转变为弱碳源, 白桦林仍保持为碳汇但功能减弱, 油松林成为一个更大的碳汇;3) 3种森林生态系统的碳生物量在未来气候情景下均增大, 21世纪末与20世纪末相比:辽东栎林在A2情景下碳生物量增加的比例为27.6%, 大于B2情景下的19.3%;白桦林和油松林在B2情景下碳生物量增加的比例分别为34.2%和52.2%, 大于A2情景下的30.8%和28.4%。     

Predictions of potential geographical distribution of Sinopodophyllum hexandrum under climate change

桃儿七(Sinopodophyllum hexandrum)为小檗科多年生草本植物, 是我国濒危传统藏药, 预测气候变化对该物种分布范围的影响对于其保护和资源可持续利用具有重要意义。该文利用获得的桃儿七136个地理分布记录和21个气候环境图层, 通过MaxEnt模型分析桃儿七在我国西部七省的潜在地理分布, 并基于该模型预测政府间气候变化专门委员会(IPCC)发布的SRES-A1B、SRES-A2和SRES-B1气候情景下21世纪20、50和80年代桃儿七分布范围。结果表明: 最热季平均温度、年降水量、温度季节性变动系数和等温性是影响桃儿七分布的主要气候因子; 在当前气候条件下, 桃儿七适宜的生境面积占研究区总面积的11.71%, 主要集中在青藏高原东缘的四川、甘肃、青海境内次生植被丰富、地形复杂的高海拔地区, 低适宜生境与不适宜生境分别占研究区总面积的15.86%与72.43%。由模型预测可知, 在SRES-A1B、SRES-A2和SRES-B1三种情景下, 桃儿七在研究区低适宜生境的数量相对变化较小, 在适宜生境先大幅减少后又缓慢增加。研究结果同时表明, 在未来气候变化条件下, 桃儿七的适宜生境平均海拔将逐渐升高, 范围以及几何重心极有可能先向北移, 然后再向西延伸至青藏高原内部较高海拔的山区。     

气候变化下桃儿七潜在地理分布的预测

桃儿七(Sinopodophyllum hexandrum)为小檗科多年生草本植物, 是我国濒危传统藏药, 预测气候变化对该物种分布范围的影响对于其保护和资源可持续利用具有重要意义。该文利用获得的桃儿七136个地理分布记录和21个气候环境图层, 通过MaxEnt模型分析桃儿七在我国西部七省的潜在地理分布, 并基于该模型预测政府间气候变化专门委员会(IPCC)发布的SRES-A1B、SRES-A2和SRES-B1气候情景下21世纪20、50和80年代桃儿七分布范围。结果表明: 最热季平均温度、年降水量、温度季节性变动系数和等温性是影响桃儿七分布的主要气候因子; 在当前气候条件下, 桃儿七适宜的生境面积占研究区总面积的11.71%, 主要集中在青藏高原东缘的四川、甘肃、青海境内次生植被丰富、地形复杂的高海拔地区, 低适宜生境与不适宜生境分别占研究区总面积的15.86%与72.43%。由模型预测可知, 在SRES-A1B、SRES-A2和SRES-B1三种情景下, 桃儿七在研究区低适宜生境的数量相对变化较小, 在适宜生境先大幅减少后又缓慢增加。研究结果同时表明, 在未来气候变化条件下, 桃儿七的适宜生境平均海拔将逐渐升高, 范围以及几何重心极有可能先向北移, 然后再向西延伸至青藏高原内部较高海拔的山区。     

Projected changes in mineral soil carbon of European croplands and grasslands, 1990–2080

We present the most comprehensive pan‐European assessment of future changes in cropland and grassland soil organic carbon (SOC) stocks to date, using a dedicated process‐based SOC model and state‐of‐the‐art databases of soil, climate change, land‐use change and technology change. Soil carbon change was calculated using the Rothamsted carbon model on a European 10 × 10′ grid using climate data from four global climate models implementing four Intergovernmental Panel on Climate Change (IPCC) emissions scenarios (SRES). Changes in net primary production (NPP) were calculated by the Lund–Potsdam–Jena model. Land‐use change scenarios, interpreted from the narratives of the IPCC SRES story lines, were used to project changes in cropland and grassland areas. Projections for 1990–2080 are presented for mineral soil only. Climate effects (soil temperature and moisture) will tend to speed decomposition and cause soil carbon stocks to decrease, whereas increases in carbon input because of increasing NPP will slow the loss. Technological improvement may further increase carbon inputs to the soil. Changes in cropland and grassland areas will further affect the total soil carbon stock of European croplands and grasslands. While climate change will be a key driver of change in soil carbon over the 21st Century, changes in technology and land‐use change are estimated to have very significant effects. When incorporating all factors, cropland and grassland soils show a small increase in soil carbon on a per area basis under future climate (1–7 t C ha^?1 for cropland and 3–6 t C ha^?1 for grassland), but when the greatly decreasing area of cropland and grassland are accounted for, total European cropland stocks decline in all scenarios, and grassland stocks decline in all but one scenario. Different trends are seen in different regions. For Europe (the EU25 plus Norway and Switzerland), the cropland SOC stock decreases from 11 Pg in 1990 by 4–6 Pg (39–54%) by 2080, and the grassland SOC stock increases from 6 Pg in 1990 to 1.5 Pg (25%) under the B1 scenario, but decreases to 1–3 Pg (20–44%) under the other scenarios. Uncertainty associated with the land‐use and technology scenarios remains unquantified, but worst‐case quantified uncertainties are 22.5% for croplands and 16% for grasslands, equivalent to potential errors of 2.5 and 1 Pg SOC, respectively. This is equivalent to 42–63% of the predicted SOC stock change for croplands and 33–100% of the predicted SOC stock change for grasslands. Implications for accounting for SOC changes under the Kyoto Protocol are discussed.     

Complex Spatiotemporal Responses of Global Terrestrial Primary Production to Climate Change and Increasing Atmospheric CO2 in the 21st Century

Quantitative information on the response of global terrestrial net primary production (NPP) to climate change and increasing atmospheric CO₂ is essential for climate change adaptation and mitigation in the 21^st century. Using a process-based ecosystem model (the Dynamic Land Ecosystem Model, DLEM), we quantified the magnitude and spatiotemporal variations of contemporary (2000s) global NPP, and projected its potential responses to climate and CO₂ changes in the 21^st century under the Special Report on Emission Scenarios (SRES) A2 and B1 of Intergovernmental Panel on Climate Change (IPCC). We estimated a global terrestrial NPP of 54.6 (52.8–56.4) PgC yr⁻¹ as a result of multiple factors during 2000–2009. Climate change would either reduce global NPP (4.6%) under the A2 scenario or slightly enhance NPP (2.2%) under the B1 scenario during 2010–2099. In response to climate change, global NPP would first increase until surface air temperature increases by 1.5°C (until the 2030s) and then level-off or decline after it increases by more than 1.5°C (after the 2030s). This result supports the Copenhagen Accord Acknowledgement, which states that staying below 2°C may not be sufficient and the need to potentially aim for staying below 1.5°C. The CO₂ fertilization effect would result in a 12%–13.9% increase in global NPP during the 21^st century. The relative CO₂ fertilization effect, i.e. change in NPP on per CO₂ (ppm) bases, is projected to first increase quickly then level off in the 2070s and even decline by the end of the 2080s, possibly due to CO₂ saturation and nutrient limitation. Terrestrial NPP responses to climate change and elevated atmospheric CO₂ largely varied among biomes, with the largest increases in the tundra and boreal needleleaf deciduous forest. Compared to the low emission scenario (B1), the high emission scenario (A2) would lead to larger spatiotemporal variations in NPP, and more dramatic and counteracting impacts from climate and increasing atmospheric CO₂.     

气候变化情景下中国自然植被净初级生产力分布

基于国际上较通用的Lund-Potsdam-Jena(LPJ)模型,根据中国自然环境特点对其运行机制进行调整,并重新进行了参数化,以B2情景气候数据作为主要的输入数据,以1961-1990年为基准时段,模拟了中国1991-2080自然植被净初级生产力(NPP)对气候变化的响应.结果表明:1961-1990年,中国自然植被的NPP总量为3.06 Pg C·a-1;1961-2080年,NPP总量呈波动下降趋势,且下降速度逐渐加快.在降水相对变化不大的条件下,平均温度的增加对我国植被生产力可能会产生一定的负面影响.NPP的空间分布从东南沿海向西北内陆呈逐渐递减趋势,在气候变化过程中,该格局基本没有太大变化.在东部NPP值相对较高地区,NPP值以减少为主,东北地区、华北东部和黄土高原地区的减少趋势尤为明显;在西部NPP值相对较低地区,NPP以增加趋势为主,青藏高原地区和塔里木盆地的表现尤为突出.随着气候变化的深入,东西部地区这种变化趋势的对比将越发明显.     

未来气候变化对河南省冬小麦需水量和缺水量的影响预估

采用美国农业部土壤保持局推荐的方法计算有效降水量,应用Penman-Monteith模型和作物系数法计算需水量,在对河南省1981—2010年冬小麦生育期内有效降水量、需水量和缺水量分析的基础上,结合《排放情景特别报告》的两种排放情景A2(强调经济发展)和B2(强调可持续发展)预估的未来气候情景,探讨了未来气候情景下河南省冬小麦的有效降水量、需水量和缺水量的时空演变规律及其主要气候影响因素.结果表明: 从整体上看,相对于基准时段(1981—2010年),A2和B2情景下,不同时段冬小麦全生育期的有效降水量、需水量和缺水量均表现出增加趋势,有效降水量均以2030s时段增加最多,分别增加33.5%和39.2%;需水量均以2010s时段增加最多,分别增加22.5%和17.5%,年代间呈现明显递减趋势;缺水量在A2情景下以2010s时段增加(23.6%)最多,B2情景下以2020s时段增加(13.0%)最多.偏相关分析表明,A2和B2情景下,太阳总辐射是影响河南省冬小麦需水量和缺水量变化的主要气候因素.由于地理环境和气候条件的差异,不同时段河南省冬小麦全生育期有效降水量、需水量和缺水量的距平百分率在空间分布上具有差异.未来河南省水资源可能更趋于短缺.     

Climate change and the outdoor regional living plant collections: an example from mainland Portugal

Climate change threatens not only plant species occurring naturally, but also impacts on regional living plant collections, which play an important role in ex situ conservation strategies. In the last few years, several global circulation models have been used to predict different global climate change scenarios. Due to their coarse resolutions, and while more detailed regional approaches are not available, downscaling techniques have been proposed, as a very simple first approach to increase detail. We analysed seven sites on mainland Portugal with potential for species conservation (four botanic gardens and three universities), in the light of downscaled climate change scenarios, using an environmental envelope approach and a predefined bioclimatic neighbourhood for each site. Thresholds for the bioclimatic neighbourhood were based on Rivas-Martínez’s Bioclimatic Classification of the Earth. For each site, the expected geographical shift of its original bioclimatic neighbourhood (1950–2000) was mapped for 2020, 2050 and 2080. Analysing those shifts enabled us to delineate knowledge-transfer paths between sites, according to the analysed scenarios. We concluded that, according to the Intergovernmental Panel on Climate Change A2 scenario, all considered sites will be outside the predefined bioclimatic neighbourhood by 2080, while according to the B2 scenario all of them will be inside that neighbourhood, although sometimes marginally so. Therefore, the implementation of global sustainability measures as considered in the B2 scenario family can be of great importance in order to delay significantly the impacts of climate change, giving extra time for the adaptation of the outdoor regional living plant collections.     

The projected effects of climatic and vegetation changes on the distribution and diversity of Southeast Asian bats

Southeast‐Asia (SEA) constitutes a global biodiversity hotspot, but is exposed to extensive deforestation and faces numerous threats to its biodiversity. Climate change represents a major challenge to the survival and viability of species, and the potential consequences must be assessed to allow for mitigation. We project the effects of several climate change scenarios on bat diversity, and predict changes in range size for 171 bat species throughout SEA. We predict decreases in species richness in all areas with high species richness (>80 species) at 2050–2080, using bioclimatic IPCC scenarios A2 (a severe scenario, continuously increasing human population size, regional changes in economic growth) and B1 (the ‘greenest’ scenario, global population peaking mid‐century). We also predicted changes in species richness in scenarios that project vegetation changes in addition to climate change up to 2050. At 2050 and 2080, A2 and B1 scenarios incorporating changes in climatic factors predicted that 3–9% species would lose all currently suitable niche space. When considering total extents of species distribution in SEA (including possible range expansions), 2–6% of species may have no suitable niche space in 2050–2080. When potential vegetation and climate changes were combined only 1% of species showed no changes in their predicted ranges by 2050. Although some species are projected to expand ranges, this may be ecologically impossible due to potential barriers to dispersal, especially for species with poor dispersal ability. Only 1–13% of species showed no projected reductions in their current range under bioclimatic scenarios. An effective way to facilitate range shift for dispersal‐limited species is to improve landscape connectivity. If current trends in environmental change continue and species cannot expand their ranges into new areas, then the majority of bat species in SEA may show decreases in range size and increased extinction risk within the next century.