气候变化情景下湿地净初级生产力风险评价—以三江平原富锦地区小叶章湿地为例

采用BIOME-BGC模型,模拟了气候变化情景下(A1B,A2,B2)三江平原富锦地区小叶章(Calamagrostis angustifolia)湿地的净初级生产力(NPP)变化,并通过NPP变化情况评价小叶章湿地风险等级.结果表明二未来30年(2013~2042年)各气候情景下富锦小叶章湿地NPP均值均高于基准期均值(1961~1990),A1B和B2情景下未来30年间NPP波动范围变大,A2情景下NPP有降低趋势.风险评价结果表明,气候变化情景下小叶章湿地存在一定风险,尤其是在A1B情景下,未来30年中可能有6年以上的年份存在高风险,A2情景下湿地风险最低湿地NPP变化与降水量呈显著正相关(R~2=0.58,P0.05),说明降水量是影响区域湿地的重要因素尽管气候变化情景下假设了存在升温CO_2浓度升高等有利于植物生长的因素,但降水量的的剧烈变化以及极端气候事件的增加河能会导致湿地在未来气候变化情景下面临较高风险,未来湿地保护与管理过程中应重点关注水的补给和调配.     

长江流域植被净初级生产力对未来气候变化的响应

研究基于气象观测和B2气候变化情景数据,利用大气-植被相互作用模型(AVIM2)模拟了1981—2000年和2010—2050年两个时段内植被NPP的空间分布格局及其时间变化趋势并分析了其时空变化与气温和降水量的关系。研究表明1981—2000年流域内植被NPP的空间分布大致呈现自西向东、自北向南递增的趋势。未来长江流域气温将整体增加,但各地增温幅度不同。流域降水量有增有减,主要增加区域位于长江源头和上游及中游的江北地区。未来在气温增加幅度较小而降水量增加的区域,如长江源头和上游的青海、西藏、川西及云南的部分地区的植被NPP将增加。在气温增幅较大而降水量减少或者降水量增加不多的区域如长江中游和下游的广大地区植被NPP将减少。从植被类型来看,长江流域大部分森林、郁闭灌丛和农作物的NPP在B2气候变化情景下将减少,每年减少量分别在0~4.5 gC.m-2、0~2 gC.m-2和0~2.5 gC.m-2之间。高寒草甸、草地和稀疏灌丛的NPP将增加,每年增长量介于0~2 gC.m-2之间。     

未来气候变化对武夷山自然保护区毛竹异戊二烯排放速率的影响

采用全球气候模式Nor ESM1-M产生的RCP2.6、RCP4.5、RCP6.0和RCP8.5气候变化情景数据和植物异戊二烯排放计算模型,模拟分析了未来气候变化对武夷山自然保护区毛竹(Phyllostachys pubescens)异戊二烯排放速率的影响.结果显示,气候变化下武夷山自然保护区气温上升,年降水量和辐射强度波动较大,呈增加或下降趋势.毛竹异戊二烯平均日排放速率在未来气候变化情景下比基准情景下高约30μg·g~(-1)·d~(-1),在RCP8.5情景下比基准情景下高约48μg·g~(-1)·d~(-1);毛竹异戊二烯日排放速率在未来气候变化情景与基准情景下的差异在1~90 d和301~365 d较小,在91~300 d差异较大;相比基准情景,未来气候变化情景下毛竹异戊二烯日排放速率在1~190 d(平均增加15%以上)和271~365 d(平均增加20%)增幅较大,在191~270 d增幅较小,在RCP8.5情景下增幅最大(平均增加17%).另外,毛竹异戊二烯年排放速率在未来气候变化情景下比基准情景下约高10000μg·g~(-1)·a~(-1)以上,在RCP8.5情景下比基准情景下约高13%.研究表明,未来气候变化将使毛竹异戊二烯排放速率增加.     

气候变化对大熊猫分布的潜在影响

分析气候变化对动物分布影响,对气候变化下保护生物多样性具有重要意义。文章利用CART(classification and regression tree),分类和回归树模型,采用A1、A2、B1和B2气候变化情景,模拟分析了气候变化对大熊猫分布范围及空间格局的影响。结果显示:气候变化下,大熊猫目前适宜分布范围将缩小,新适宜和总适宜分布范围在1991~2020年时段较大,从1991~2020年到2081~2100年时段呈现缩小趋势,其中A1情景下变化最大,B1情景下最小。气候变化下,大熊猫目前适宜分布区的东部、东北和南部一些适宜范围将不再适宜,新适宜分布区将主要向目前适宜分布区西部一些区域扩展,并且适宜分布区破碎化,在2051~2080年时段程度最高。另外,气候变化下,大熊猫目前适宜、新适宜和总适宜分布区范围与我国年均气温和年降水量变化呈负相关性。多元回归分析表明,大熊猫目前适宜、新适宜和总适宜分布范围随我国年均气温和年降水量增加而减少,其中气温变化影响比降水量变化影响要大。结果说明,气候变化后,近期将使大熊猫目前适宜分布范围减小,新适宜分布范围增加,随气候变化程度增加,新适宜和总适宜分布范围又将减小。     

气候变化背景下人类活动对承德接坝区植被净初级生产力的影响

承德接坝区位于农牧过渡区,对气候变化和人类活动极为敏感.以植被净初级生产力(NPP)作为评价指标,基于Thornthwaite Memorial模型计算潜在NPP和MODIS NPP遥感影像获取实际NPP数据,利用潜在NPP与实际NPP间的差值衡量人类活动作用下NPP的大小,运用Slope趋势和变异系数法分析实际NPP、潜在NPP和人类活动作用下NPP的变化趋势及稳定性分布,并采用相关系数法分析实际NPP与年降水量和年均气温间的相关性,最终量化气候变化和人类活动对该区域植被变化的影响.结果表明,潜在NPP自西北向东南递增,其变化趋势和稳定性均为自西向东递增.实际NPP与年降水量和年均气温呈正相关区域面积占比分别是99.87%和91.66%.该区域99.85%的植被得到改善且变化稳定,主要是由气候因素和人类活动共同主导(99.71%),而植被退化完全是由人为因素所导致(0.15%).     

气候变化对我国干旱区分布及其范围的潜在影响

为确定气候变化对土地荒漠化影响,以干燥度指数及A1,A2,B1和B2气候变化情景分析了气候变化对我国干旱区分布范围的影响. 模拟结果表明:气候变化将导致我国极端干旱区和湿润区分布范围缩小,干旱区、半干旱区和半湿润区分布范围扩大. 极端干旱区分布范围缩小并被干旱区所代替,半干旱区向半湿润区东、南部方向扩展,湿润区东北部和西部被半干旱和半湿润区所代替. 极端干旱区和湿润区分布范围变化与全国年均气温增量呈负相关性,干旱区、半干旱区和半湿润区分布范围变化与全国年均气温增量呈正相关性. 多元回归分析表明,干旱区和极端干旱区分布范围随全国年降水量增加而减少;半湿润区和湿润区分布范围随全国年降水量增加而增加;除A1情景外,其他气候情景下半干旱区分布范围均随全国年降水量增加而减少;湿润区分布范围随全国年均气温增加而减少,其他气候区范围随全国年均气温升高而增加. 随着气候变化,我国荒漠化范围将增加,干旱胁迫总体上减弱.      

气候变化对珙桐分布的潜在影响

分析气候变化对植物分布的影响,对气候变化影响下的生物多样性保护具有重要意义. 利用分类和回归树 (Classification and Regression Tree,CART)生态位模型,设定A1,A2,B1和B2 4种气候变化情景,模拟分析了气候变化对珙桐(Davidia involucrata Baill)分布的影响. 结果表明:随气候变化,珙桐目前适宜分布范围将减小,但新适宜及总适宜分布范围将扩大;珙桐适宜分布范围在模拟时段呈缩小趋势,在A1情景下减幅最大,B1情景下减幅最小. 气候变化后,由于珙桐目前适宜分布范围的东部、南部、北部、东北部和东南部地区缩小,而新适宜分布范围将主要向我国西部及西南部地区扩展,因此,目前适宜分布范围将被破碎化. 气温变化对珙桐分布范围的影响大于降水量的影响.      

气候和土地利用变化对上海市农田生态系统净初级生产力的影响

以上海市主要植被类型农田为研究对象,利用大气-植被相互作用模型(AVIM2)模拟的近50年上海市农田净初级生产力(NPP)以及1987、1997和2004年上海市的TM遥感影像数据,分别计算了气候变化和土地利用变化对上海市农田生态系统NPP总量变化的影响.研究结果表明,如果只考虑气候变化,1961～2006年上海农田年平均NPP值增加了64.37g·m-2(以C计),平均每年增长1.43g·m-2.年平均温度和降水量均与NPP显著正相关.另一方面,上海农田面积占总面积的比例由1987年的76%递减到2004年的43%.在土地利用变化和气候变化双重因素的驱动下,自20世纪80年代以来,上海农田NPP总量减少了42%;相对于气候变化影响,土地利用变化对农田NPP总量影响较大,其中,20世纪80年代到90年代,土地利用变化对NPP总量变化的贡献率占78%;20世纪90年代到21世纪初土地利用变化的贡献率达92%.     

我国东部河流水文水质对气候变化响应的研究

基于A2和B2气候变化情景,采用统计降尺度模型SDSM,将由3个国际上流行的大气环流模式GCMs(Had CM3、CSIRO-Mk2和CGCM2)模拟的未来我国东部长乐江流域的气温和降水,与水土评价模型SWAT相耦合,分析了该流域水文水质对气候变化的响应,并比较了3个大气环流模式模拟结果的异同.结果表明,所有气候情景下,TN浓度有明显的升高趋势;TP浓度有增有减,总体上仍呈微弱增加趋势.河川径流呈微弱减少趋势,而营养物负荷量呈微弱增加趋势,说明该流域水文水质状况受气温升高的影响大于降水微弱增加的影响.另外,在不同的气候变化情景下,年内径流和营养物负荷变化情况存在较大差异.研究结果可为理解河流水环境对气候变化的响应及其应对管理提供理论依据.     

气候变化对湿地景观格局的影响研究综述

气候变化是影响湿地景观格局变化的主要自然因素。文章从气候变化对湿地水资源面积、湿地土地利用格局、湿地植被空间格局及湿地生物多样性格局的影响研究等方面进行了综述,并对完善气候变化下湿地景观格局变化的研究方法和技术手段进行了探讨。指出:应用气候模型进行未来气候预测时,应合理选择气候变化情景,并确保不同模型的时空尺度匹配;应用"3S"技术提取湿地类型信息、观测湿地土地覆盖变化时要确保信息的精度,不同来源的数据必须采取制图综合等手段;实现气候变化下湿地景观结构与生态过程相结合的动态格局分析。     

典型湿地生态系统碳循环模拟与预测

以植物生理生态特性和有机碳周转动力学原理为基础,利用室内模拟培养试验结果率定了温度、积水强度、冻融交替对湿地有机碳分解矿化的影响参数,建立了典型湿地生态系统碳循环模拟模型.利用实地观测的数据对模型进行了检验,对模型的灵敏性进行了分析,同时利用该模型进行了情景预测.结果表明,所建模型能较好地模拟中温带（三江平原）和亚热带（洞庭湖）湿地生态系统的碳通量和碳累积特征,沉积物呼吸的模拟值与实测值呈极显著相关关系（p<0.01）;三江平原常年积水沼泽有机碳密度约为80×10⁹ g·km^-2,洞庭湖湿地碳密度约为20×10⁹ g·km^-2;三江平原常年积水沼泽和季节性积水沼泽每年碳的净固定速率分别为104　g·m^-2和76 g·m^-2;该模型对温度和大气CO₂浓度变化反应敏感.在既定的水文条件下,大气CO₂浓度升高和增温可能会使湿地生态系统的碳交换变得更为活跃;在CO₂浓度倍增和增温小于2.5℃的气候变化情景时,系统净初级生产力（NPP）和积累的有机碳密度增加,系统仍为大气的CO₂ 汇,但气候变暖的进一步加剧并不利于湿地有机碳的积累,由于CO₂施肥效应和温度升高增加的系统NPP补偿不了因温度升高导致的沉积物呼吸速率加快而损失的碳,季节性积水沼泽生态系统积累的有机碳甚至出现明显的下降趋势.     

Implications of climate change on mitigation potential estimates for forest sector in India

Climate change is projected to impact forest ecosystems, including biodiversity and Net Primary Productivity (NPP). National level carbon forest sector mitigation potential estimates are available for India; however impacts of projected climate change are not included in the mitigation potential estimates. Change in NPP (in gC/m²/yr) is taken to represent the impacts of climate change. Long term impacts of climate change (2085) on the NPP of Indian forests are available; however no such regional estimates are available for short and medium terms. The present study based on GCM climatology scenarios projects the short, medium and long term impacts of climate change on forest ecosystems especially on NPP using BIOME4 vegetation model. We estimate that under A2 scenario by the year 2030 the NPP changes by (−5) to 40% across different agro-ecological zones (AEZ). By 2050 it increases by 15% to 59% and by 2070 it increases by 34 to 84%. However, under B2 scenario it increases only by 3 to 25%, 3.5 to 34% and (−2.5) to 38% respectively, in the same time periods. The cumulative mitigation potential is estimated to increase by up to 21% (by nearly 1 GtC) under A2 scenario between the years 2008 and 2108, whereas, under B2 the mitigation potential increases only by 14% (646 MtC). However, cumulative mitigation potential estimates obtained from IBIS—a dynamic global vegetation model suggest much smaller gains, where mitigation potential increases by only 6% and 5% during the period 2008 to 2108.     

Future production of rainfed wheat in Iran (Khorasan province): climate change scenario analysis

Projecting staple crop production including wheat under future climate plays a fundamental role in planning the required adaptation and mitigation strategies for climate change effects especially in developing countries. The main aim of this study was to investigate the direction and magnitude of climate change impacts on grain yield of rainfed wheat (Triticum aestivum L.) production and precipitation within growing season. This study was performed for various regions in Khorasan province which is located in northeast of Iran. Climate projections of two General Circulation Models (GCM) for four locations under three climate change scenarios were employed in this study for different future time periods. A stochastic weather generator (LARS-WG5) was used for downscaling to generate daily climate parameters from GCMs output. The Decision Support System for Agrotechnology Transfer (DSSAT) Version 4.5 was employed to evaluate rainfed wheat performance under future climate. Grain yield of rainfed wheat and precipitation during growth period considerably decreased under different scenarios in various time periods in contrast to baseline. Highest grain yield and precipitation during growth period was obtained under B1 scenario but A1B and A2 scenarios resulted in sharp decrease (by ?57 %) of grain yield. Climate change did not have marked effects on evapotranspiration during the rainfed wheat growth. A significant correlation was detected between grain yield, precipitation and evapotranspiration under climate change for both GCMs and under all study scenarios. It was concluded, that rainfed wheat production may decline during the next 80 years especially under A2 scenario. Therefore, planning the comprehensive adaptation and mitigation program is necessary for avoiding climate change negative impact on rainfed wheat production.     

Impact of climate change on Indian forests: a dynamic vegetation modeling approach

We make an assessment of the impact of projected climate change on forest ecosystems in India. This assessment is based on climate projections of the Regional Climate Model of the Hadley Centre (HadRM3) and the dynamic global vegetation model IBIS for A2 and B2 scenarios. According to the model projections, 39% of forest grids are likely to undergo vegetation type change under the A2 scenario and 34% under the B2 scenario by the end of this century. However, in many forest dominant states such as Chattisgarh, Karnataka and Andhra Pradesh up to 73%, 67% and 62% of forested grids are projected to undergo change. Net Primary Productivity (NPP) is projected to increase by 68.8% and 51.2% under the A2 and B2 scenarios, respectively, and soil organic carbon (SOC) by 37.5% for A2 and 30.2% for B2 scenario. Based on the dynamic global vegetation modeling, we present a forest vulnerability index for India which is based on the observed datasets of forest density, forest biodiversity as well as model predicted vegetation type shift estimates for forested grids. The vulnerability index suggests that upper Himalayas, northern and central parts of Western Ghats and parts of central India are most vulnerable to projected impacts of climate change, while Northeastern forests are more resilient. Thus our study points to the need for developing and implementing adaptation strategies to reduce vulnerability of forests to projected climate change.     

Regional climate change projections for the Northeast USA

Climate projections at relevant temporal and spatial scales are essential to assess potential future climate change impacts on climatologically diverse regions such as the northeast United States. Here, we show how both statistical and dynamical downscaling methods applied to relatively coarse-scale atmosphere-ocean general circulation model output are able to improve simulation of spatial and temporal variability in temperature and precipitation across the region. We then develop high-resolution projections of future climate change across the northeast USA, using IPCC SRES emission scenarios combined with these downscaling methods. The projections show increases in temperature that are larger at higher latitudes and inland, as well as the potential for changing precipitation patterns, particularly along the coast. While the absolute magnitude of change expected over the coming century depends on the sensitivity of the climate system to human forcing, significantly higher increases in temperature and in winter precipitation are expected under a higher as compared to lower scenario of future emissions from human activities.     

Impact of Climate Change on Maize Yield in Central and Northern Greece: A Simulation Study with Ceres-Maize

The potential impacts of climate change on the phenology and yield of two maize varieties in Greece were studied. Three sites representing the central and northern agricultural regions were selected: Karditsa, Naoussa and Xanthi. The CERES-Maize model, embedded in the Decision Support System for Agrotechnology Transfer (DSSAT 3.0), was used for the crop simulations, with current and possible future management practices. Equilibrium doubled CO₂ climate change scenarios were derived from the GISS, GFDL, and UKMO general circulation models (GCMs); a transient scenario was developed from the GISS GCM transient run A. These scenarios predict consistent increases in air temperature, small increases in solar radiation and precipitation changes that vary considerably over the study regions in Greece. Physiological effects of CO₂ on crop growth and yield were simulated. Under present management practices, the climate change scenarios generally resulted in decreases in maize yield due to reduced duration of the growing period at all sites. Adaptation analyses showed that mitigation of climate change effects may be achieved through earlier sowing dates and the use of new maize varieties. Varieties with higher kernel-filling rates, currently restricted to the central regions, could be extended to the northern regions of Greece. In the central regions, new maize varieties with longer grain-filling periods might be needed.     

气候变化对太岳山中部油松单萜烯排放的影响

以全球气候模式NorESM1-M产生的RCP2.6,RCP4.5,RCP6.0和RCP8.5气候变化情景数据和植物VOCs排放计算模型,模拟分析了气候变化对山西太岳山中部油松叶片单萜烯排放速率的影响.结果显示,未来气候变化影响下山西太岳山中部气温呈上升趋势,降水和辐射强度波动大.在RCP2.6,RCP4.5,RCP6.0和RCP8.5情景与基准情景下,油松单萜烯日排放速率在1~210d呈上升趋势,在210~365d呈下降趋势;在未来气候变化情景下比基准情景下高约2μg/（g·d）,在RCP8.5情景下最高;油松单萜烯日排放速率在未来气候变化情景与基准情景下差异在1~95d和296~365d较小,在96~295d波动较大.同时,相比基准情景,单萜烯日排放速率增幅在1~190d较高（增加12%~14%以上）,在191~315d较小（增加9%~13%以上）,在316~365d增加12%~18%以上,在RCP8.5情景下增幅最大（增加14%以上）.另外,油松单萜烯年排放速率在未来气候变化情景下比基准情景下平均高约1000μg/（g·a）以上,在RCP8.5情景下增幅最大（约12%）.说明,未来气候变化将使油松单萜烯排放速率增加.