青藏高原植被生态系统垂直分布变化的情景模拟

如何模拟和揭示青藏高原植被生态系统垂直分布在全球气候变化驱动下的时空变化情景,对定量解析青藏高原陆地生态系统对气候变化响应效应具有重要意义。该论文基于Holdridge life zone （HLZ）模型,结合数字高程模型（DEM）数据,改变模型输入参数模式,发展了改进型HLZ生态系统模型。结合1981-2010（T0）时段的气候观测数据和IPCC CMIP5 RCP2.6、RCP4.5、RCP8.5三种情景2011-2040（T1）、2041-2070（T2）、2071-2100（T3）三个时段气候情景数据,实现了青藏高原植被生态系统垂直分布的时空变化情景模拟。引入生态系统平均中心时空偏移趋势模型和生态多样性指数模型,定量揭示了青藏高原植被生态系统在不同垂直带上的时空变化情景。结果显示：青藏高原共有16种植被生态系统类型;冰雪/冰原、高山潮湿苔原和亚高山湿润森林为青藏高原主要的植被生态系统类型,其面积之和占到了青藏高原总面积的56.26%;高山干苔原、亚高山潮湿森林、山地灌丛、山地湿润森林和荒漠等对气候变化的敏感性总体上高于其它类型;在T0-T3期间,青藏高原的高山湿润苔原、高山干苔原、荒漠呈持续减少趋势,平均每10年将分别减少1.96×10⁴km²、0.15×10⁴km²和1.58×10⁴km²;亚高山潮湿森林、山地湿润森林和山地灌丛呈持续增加趋势,平均每10年将分别增加3.42×10⁴km²、2.98×10⁴km²和1.19×10⁴km²;RCP8.5情景下青藏高原的植被生态系统平均中心的偏移幅度最大,RCP4.5情景下的偏移幅度次之,而RCP2.6情景下的偏移幅度最小。另外,在三种气候变化情景驱动下,青藏高原植被生态系统的生态多样性呈减少趋势。总之,未来不同情景的气候变化将直接影响青藏高原植被生态系统的时空分布格局及其生态多样性,气候变化强度越高,影响就越大,而且气候变化对青藏高原植被生态系统的影响呈现出从低海拔到高海拔递增的影响效应。     

辅助数据在面向对象分类方法中的应用——以密云水库上游为例

密云水库上游位于华北平原向蒙古高原的过渡带内,自然条件差异大,人类活动对该区域影响显著。因此,对该地区土地覆盖类型遥感监测方法的研究具有典型的指导意义。基于高分辨率遥感影像,着重探讨辅助数据在面向对象分类方法中的应用,对密云水库上游地区的土地覆盖进行分类提取。结果显示,研究区内共包含26类土地覆盖类型,其中落叶阔叶灌木林、落叶阔叶林、草丛以及旱地,这4种类型的面积占总面积的85%,是全区的主要土地覆盖类型。在分类时,采用多源异构辅助数据,研究了北方山区常绿针叶林、旱地等土地覆盖类型的识别方法,有效降低了"同物异谱"和"同谱异物"现象对分类精度的影响。     

欧亚大陆植被生态系统平均中心时空偏移的情景模拟

欧亚大陆复杂多样的植被生态系统在全球气候变化的驱动下,其时空分布格局将发生系列的偏移变化,进而对欧亚大陆"一带一路"沿线国家和地区的生态环境产生重要影响。如何从全球气候变化驱动的角度来实现欧亚大陆植被生态系统时空偏移趋势的模拟分析,已成为"一带一路"沿线国家和地区生态环境研究的热点科学问题之一。在对HLZ生态系统模型进行改进和构建植被生态系统平均中心时空偏移分析模型的基础上,基于欧亚大陆的气候观测数据(1981—2010年)和CMIP5 RCP2.6、RCP4.5和RCP8.5三种情景数据(2011—2100年),实现欧亚大陆植被生态系统平均中心时空偏移趋势的模拟分析。结果表明:欧亚大陆植被生态系统平均中心主要分布在欧亚大陆的中部和南部地区;3种气候情景下,欧亚大陆的亚热带干旱森林、暖温带湿润森林、亚热带有刺疏林、亚热带潮湿森林、冷温带潮湿森林、寒温带湿润森林、冷温带湿润森林、亚热带湿润森林、暖温带干旱森林、亚极地/高山湿润苔原和极地/冰原等植被生态系统的平均中心偏移幅度大于其他植被生态系统类型;欧亚大陆植被生态系统在RCP8.5情景下的植被生态系统平均中心偏移幅度大于其他两种情景;在2011—2100年期间,3种气候变化情景下,欧亚大陆植被生态系统平均中心整体上将呈向北偏移的变化趋势。     

气候变化下西南地区植物功能型地理分布响应

以中国西南地区(云南、贵州、四川和重庆)为研究区,基于中国植被图划分植物功能型,筛选影响各植物功能型分布的主导环境因子,进而通过最大熵模型结合未来气候情景(2050年)预测西南地区植物功能型地理分布。结果表明:(1)根据植物冠层特征(针叶/阔叶、常绿/落叶)及对水分和温度的需求,结合研究区实际植被数据,筛选得到15类植物功能型,包含6类乔木、6类灌木和3类草本功能型;(2)影响西南地区热带乔木分布的主导因子为最冷月最低温度和年降水量(贡献率达90.3%),亚热带植物功能型分布主要受到温度变化影响(贡献率达41.7%),温带植物功能型则受降水因子的影响最大(贡献率约40.1%),高寒草甸草和高寒常绿阔叶灌木主要受温度和海拔因子影响,高寒落叶阔叶灌木受降水因子影响大;(3)随CO_2排放量增加,未来西南各植物功能型分布呈现不同变化,其中,热带常绿阔叶乔木适宜区逐渐扩大;亚热带落叶木本类植物功能型的高适宜区面积2050年(RCP8.5)增至10.3%,呈东移趋势;亚热带常绿木本和草本类植物功能型适宜区广(占研究区总面积86.5%),未来气候下分布呈不规则波动;温带植物功能型(除温带灌木类外)适宜区面积减小至2050年(RCP8.5)的13.6%;温带常绿针叶灌木适宜区面积增大,2050年(RCP2.6)高适宜区向西移动且面积增至当前的8.25倍;高寒类植物功能型适宜区面积则呈缩小趋势,高适宜区东移。     

气候变化对我国南方人工林地上生物量影响的模拟研究——以会同生态站磨哨实验林场为例

全球气候变暖对陆地生态系统尤其是森林生态系统有着重要的影响,气温升高、辐射强迫的增强将显著改变森林生态系统的结构和功能.南方人工林作为我国森林的重要组成部分,对气候变化的响应日益强烈.为了探究未来气候情景下我国南方人工林对气候变化的响应,降低未来气候变化对人工林可能带来的损失,本研究采用3种最新的气候情景—典型浓度排放路径情景(RCP2.6情景、RCP4.5情景、RCP8.5情景)预估数据,应用生态系统过程模型PnET-Ⅱ和空间直观景观模型LANDIS-Ⅱ模拟2014—2094年间湖南省会同森林生态实验站磨哨实验林场森林的地表净初级生产力(ANPP)、物种建立可能性(SEP)和地上生物量的变化.结果表明: 不同森林类型的SEP和ANPP对气候变化的响应有明显的差异,各森林类型对气候变化的响应程度表现为: 对于SEP,在RCP2.6和RCP4.5情景下,人工针叶林＞天然阔叶林＞人工阔叶林;在RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.对于ANPP,在RCP2.6情景下,人工阔叶林＞天然阔叶林＞人工针叶林;在RCP4.5和RCP8.5情景下,天然阔叶林＞人工阔叶林＞人工针叶林.人工针叶林的地上生物量在2050年左右开始下降,天然阔叶林和人工阔叶林整体呈现上升趋势.2014—2094年,研究区地上总生物量在不同气候情景下增加幅度不同,RCP2.6情景下增加了68.2%,RCP4.5情景下增加了79.3%,RCP8.5情景下增加了72.6%.3种情景下的总地上生物量大小排序为: RCP4.5> RCP8.5> RCP2.6.我们认为,适当的增温将有助于未来研究区森林总地上生物量的积累,但过度的增温也可能会阻碍森林的生产和生态功能的持续发展.     

2000—2019年石羊河流域植被总初级生产力变化及其气候特征

石羊河流域是我国典型的内陆河流域,生态特征敏感脆弱,是了解干旱地区陆地生态系统总初级生产力(gross primary productivity, GPP)对气候变化响应及反馈的典型区域。本研究通过卫星数据和地面观测数据建立光能利用率模型,模拟估算了石羊河流域2000—2019年植被GPP,分析了气候影响下的不同植被类型GPP的空间分布以及年际变化。结果表明：石羊河流域GPP的平均值为256.52 g C·m^-2;落叶阔叶林、常绿针叶林、灌木林、耕地、草原、湿地和荒漠植被GPP分别为676.38、609.96、144.42、404.49、314.07、75.15和110.21 g C·m^-2,表现为南部祁连山区的落叶阔叶林GPP最高,北部荒漠区的湿地GPP最低;GPP的变化呈上升趋势,年际变化存在波动,趋势增加的面积为92%,平均速率为6.99 g C·m^-2·a^-1;流域内不同植被类型GPP增加速度从大到小顺序为落叶阔叶林>常绿针叶林>草地>耕地>灌木林>荒漠>...     

区域尺度的中国植物功能型与生物群区

利用“生态－外貌”原则,中国的现状植被类型及其分布,确定中国的39种优势植物功能型：高山常绿针叶、北方常绿针叶、北方夏绿针叶、冷温带常绿针叶、温带常绿针叶、暖温带常绿阔叶、暖温带硬叶阔叶、暖温带夏绿阔叶、热带常绿阔叶、热带 雨绿阔叶、热带落叶阔叶、暖温带竹、高山／亚高山灌木、温带草原灌木、温带荒漠灌木、冷温带灌木、温带灌木、暖温带灌木、热带灌木、干旱灌木、高山草、荒漠草、温带草原草、温带草、沼泽草、红树、北方农作物、冷温带农作物、温带农作物、暖温带农作物、热带农作物和裸地。再依据优势植物功能型归并中国的21类潜在生物群区：北方（寒温带）落叶林、北方（寒温带）常绿林、冷温带针阔叶混交林、温带落叶阔叶林、暖温带（亚热带）落叶常绿阔叶混交林、暖温带（亚热带）常绿阔叶林、暖温带（亚）常绿阔叶季风林、热带雨林、热带季雨林、热带落叶林、红树林、干旱疏林／稀树草原、;温带草甸／稀树草原、温带草原、温带半草原、温带荒漠、温带半荒漠、高山／高山针叶林、高山／亚高山灌丛／草甸、高山／亚高山草原和高山／亚高山荒漠。如果考虑现状农业植被类型：一年一熟农作物、二年三熟农作物、一年二熟农作物和一年三熟农作物,可归并为25类现状生物群区。这是全球生态学和古生态学研究中区域尺度旧我国植物功能型和生物群区分类的一次尝试。     

广西金钟山自然保护区主要植被类型的特征

金钟山自然保护区计有种子植物101科273属514种,落叶栎林分布面积最广。随海拔升高,植被依次呈现出4个分布带:沟谷落叶阔叶林、沟谷常绿阔叶林、常绿落叶阔叶混交林和落叶阔叶林、山地苔藓矮林和山地常绿阔叶林。该区主要有4个分布区类型:世界分布、热带分布、温带分布和中国特有分布,其中热带分布占总属数的75.21%,表明本保护区的植物分布具有热带性质。其天然植被类型可划分为5个植被型组,7个植被型含暖性针叶林、暖性落叶阔叶林、常绿落叶阔叶混交林、常绿阔叶林、竹林和草丛,2个植被亚型含南亚热带山地常绿阔叶林、山顶阔叶矮林,以及33个群系。     

三江平原植被水分利用效率时空变化及其对气象因子变化的响应

水分利用效率(water use efficiency,WUE)是陆地生态系统响应全球变化的重要参数,分析区域生态系统WUE的变化特征及其与气象因子之间的响应关系,对于区域生态系统碳水循环研究以及水资源的科学管理具有重要意义。本文以三江平原为研究区,基于MODIS GPP和ET遥感数据、气象数据以及2000年、2014年土地覆盖数据,分析2000-2014年间植被WUE的时空变化特征以及植被WUE与关键气象因子之间的响应关系,并分析了土地覆盖变化下各植被类型WUE的变化特征。结果表明:三江平原WUE年均值变化呈波动式减少趋势,多年平均植被WUE为1.44 g C·kg^-1H2O;WUE年内变化均近似呈"单峰型"曲线,1-3月及11、12月,WUE均处于最低值,在植被生长季(5-9月)期间,WUE均较高;季节WUE均值由高到低依次为夏季>秋季>春季>冬季;各植被类型WUE年内变化呈"双峰型"曲线,峰值主要分布在4-6月和9月;不同植被类型的年均WUE值从大到小依次为:混交林>针叶林>阔叶林>草地>耕地>永久湿地;三江平原植被WUE与降水、相对湿度、水气压呈正相关,与气温、日照时数呈负相关;随着耕地面积的减少,耕地WUE增加了11.1%,随着落叶阔叶林、草地面积的增加,其植被WUE分别增加了12.8%、15.9%。     

利用MODIS数据评估冷冻灾害对广东植被的损害

2008年初我国南方地区发生的极端冷冻灾害对植被造成了极大破坏。以广东为例,利用MODIS数据,对比分析了受损植被与正常植被的NDVI变化;利用ISODATA非监督分类方法提取受损植被分布信息,借助90m SRTM DEM数据研究受损植被与地形因子的关系,发现广东植被受损严重,受损植被总面积达19 011.06 km²。受损植被受海拔高程、坡度、坡向等地形因子影响较大;受损植被主要集中于海拔大于400 m,坡度小于15°的阴坡区域;通过MODIS土地覆盖图与受损植被的复合分析,研究了该地区受损植被的类型,发现受损植被以常绿阔叶林、混交林、落叶阔叶林、灌丛、落叶针叶林及常绿针叶林为主。     

Land suitability for energy crops under scenarios of climate change and land‐use

Bioenergy is expected to play a critical role in climate change mitigation. Most integrated assessment models assume an expansion of agricultural land for cultivation of energy crops. This study examines the suitability of land for growing a range of energy crops on areas that are not required for food production, accounting for climate change impacts and conservation requirements. A global fuzzy logic model is employed to ascertain the suitable cropping areas for a number of sugar, starch and oil crops, energy grasses and short rotation tree species that could be grown specifically for energy. Two climate change scenarios are modelled (RCP2.6 and RCP8.5), along with two scenarios representing the land which cannot be used for energy crops due to forest and biodiversity conservation, food agriculture and urban areas. Results indicate that 40% of the global area currently suitable for energy crops overlaps with food land and 31% overlaps with forested or protected areas, highlighting hotspots of potential land competition risks. Approximately 18.8 million km² is suitable for energy crops, to some degree, and does not overlap with protected, forested, urban or food agricultural land. Under the climate change scenario RCP8.5, this increases to 19.6 million km² by the end of the century. Broadly, climate change is projected to decrease suitable areas in southern regions and increase them in northern regions, most notably for grass crops in Russia and China, indicating that potential production areas will shift northwards which could potentially affect domestic use and trade of biomass significantly. The majority of the land which becomes suitable is in current grasslands and is just marginally or moderately suitable. This study therefore highlights the vital importance of further studies examining the carbon and ecosystem balance of this potential land‐use change, energy crop yields in sub‐optimal soil and climatic conditions and potential impacts on livelihoods.     

Future climate change effects on US forest composition may offset benefits of reduced atmospheric deposition of N and S

Climate change and atmospheric deposition of nitrogen (N) and sulfur (S) are important drivers of forest demography. Here we apply previously derived growth and survival responses for 94 tree species, representing >90% of the contiguous US forest basal area, to project how changes in mean annual temperature, precipitation, and N and S deposition from 20 different future scenarios may affect forest composition to 2100. We find that under the low climate change scenario (RCP 4.5), reductions in aboveground tree biomass from higher temperatures are roughly offset by increases in aboveground tree biomass from reductions in N and S deposition. However, under the higher climate change scenario (RCP 8.5) the decreases from climate change overwhelm increases from reductions in N and S deposition. These broad trends underlie wide variation among species. We found averaged across temperature scenarios the relative abundance of 60 species were projected to decrease more than 5% and 20 species were projected to increase more than 5%; and reductions of N and S deposition led to a decrease for 13 species and an increase for 40 species. This suggests large shifts in the composition of US forests in the future. Negative climate effects were mostly from elevated temperature and were not offset by scenarios with wetter conditions. We found that by 2100 an estimated 1 billion trees under the RCP 4.5 scenario and 20 billion trees under the RCP 8.5 scenario may be pushed outside the temperature record upon which these relationships were derived. These results may not fully capture future changes in forest composition as several other factors were not included. Overall efforts to reduce atmospheric deposition of N and S will likely be insufficient to overcome climate change impacts on forest demography across much of the United States unless we adhere to the low climate change scenario.     

Assessing the influence of historic net and gross land changes on the carbon fluxes of Europe

Legacy effects of land cover/use on carbon fluxes require considering both present and past land cover/use change dynamics. To assess past land use dynamics, model‐based reconstructions of historic land cover/use are needed. Most historic reconstructions consider only the net area difference between two time steps (net changes) instead of accounting for all area gains and losses (gross changes). Studies about the impact of gross and net land change accounting methods on the carbon balance are still lacking. In this study, we assessed historic changes in carbon in soils for five land cover/use types and of carbon in above‐ground biomass of forests. The assessment focused on Europe for the period 1950 to 2010 with decadal time steps at 1‐km spatial resolution using a bookkeeping approach. To assess the implications of gross land change data, we also used net land changes for comparison. Main contributors to carbon sequestration between 1950 and 2010 were afforestation and cropland abandonment leading to 14.6 PgC sequestered carbon (of which 7.6 PgC was in forest biomass). Sequestration was highest for old‐growth forest areas. A sequestration dip was reached during the 1970s due to changes in forest management practices. Main contributors to carbon emissions were deforestation (1.7 PgC) and stable cropland areas on peaty soils (0.8 PgC). In total, net fluxes summed up to 203 TgC yr^?1 (98 TgC yr^?1 in forest biomass and 105 TgC yr^?1 in soils). For areas that were subject to land changes in both reconstructions (35% of total area), the differences in carbon fluxes were about 68%. Overall for Europe the difference between accounting for either gross or net land changes led to 7% difference (up to 11% per decade) in carbon fluxes with systematically higher fluxes for gross land change data.     

不同土地覆被格局情景下多种生态系统服务的响应与权衡——以雅砻江二滩水利枢纽为例

在二滩水库集水区,按照当地生态政策发展以坡度为指标构建了10种未来土地覆被格局情景,研究生态系统减轻水库泥沙淤积、减轻水库面源污染、产水发电服务及价值对未来覆被格局的响应程度,并兼顾相关产业收益的变化,权衡各种情景格局的服务效益,优选利益相关方福祉提升幅度最大的情景格局。结果表明:1)现有土地覆被格局对减轻水库泥沙淤积功效的发挥不合理,而以退耕还林政策指导区域土地覆被格局变化,对集水区减轻河道和水库泥沙淤积具有较好功效。10种情景下,保沙价值的高低关系同入库泥沙量正好相反,遵循"随地表林地和草地面积比例的增加,保沙价值增加"的规律。随产沙总量的增加,高产沙强度像元呈现从水库周边逐渐向中上游蔓延的趋势。2)退耕还林政策单纯以坡度作为指标,指导土地覆被的转化,对集水区减轻水环境磷素非点源污染功效较差。除了全为未利用地覆被的情景10,余下9类情景模拟的入库磷素量及过滤磷素经济价值的高低关系完全一致,呈农田草地林地的规律。随入库磷素总量的增加,高强度磷素输出像元从雅砻江流域源区和大河湾区,逐渐蔓延扩散至集水区整个水网。3)随着集水区地表林地覆盖面积比例的减少,集水区生态系统总发电净利润值增加,且高净利润像元呈现从冕宁和喜德县的东部逐渐向整个集水区东南部乃至整个下游蔓延的趋势。4)从减轻对环境的负效应以及提升利益相关方福祉的角度,以坡度6°上下划分林地和耕地的情景5和以坡度15°和6°为阈值划分林草农的情景3为除极端的情景外,综合指标提升最高的两种情景。     

Assessing uncertainties in land cover projections

Understanding uncertainties in land cover projections is critical to investigating land‐based climate mitigation policies, assessing the potential of climate adaptation strategies and quantifying the impacts of land cover change on the climate system. Here, we identify and quantify uncertainties in global and European land cover projections over a diverse range of model types and scenarios, extending the analysis beyond the agro‐economic models included in previous comparisons. The results from 75 simulations over 18 models are analysed and show a large range in land cover area projections, with the highest variability occurring in future cropland areas. We demonstrate systematic differences in land cover areas associated with the characteristics of the modelling approach, which is at least as great as the differences attributed to the scenario variations. The results lead us to conclude that a higher degree of uncertainty exists in land use projections than currently included in climate or earth system projections. To account for land use uncertainty, it is recommended to use a diverse set of models and approaches when assessing the potential impacts of land cover change on future climate. Additionally, further work is needed to better understand the assumptions driving land use model results and reveal the causes of uncertainty in more depth, to help reduce model uncertainty and improve the projections of land cover.     

Land cover dynamics of different topographic conditions in Beijing,China

Topographic conditions play an important role in controlling land cover dynamic processes.In this study,remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing,a rapidly urbanized mega city in China.The study was based on five periods of land cover maps derived from remotely sensed data:Landsat MSS for 1978,Landsat TM for 1984,"1992,1996 and 2001,and the digital elevation model (DEM) derived from 1:250,000 topographic map.The whole area was divided into ten land cover types:conifer forest,broadleaf forest,mixed forest,shrub,brushwood,meadow,farmland,built-up,water body and bare land.The results are summarized as follows.(1) Shrub,forest,farmland and builtup consist of the main land cover types of the Beijing area.The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area.Farmland decreased from 6354 to 3813 km2 in the 23 years,while the built-up area increased from 421 to 2642 km2.Meanwhile,the coverage of forest increased from 17.2% to 24.7% of the total area.The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest.(2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes.Elevation has an intensive impact on the distribution of land cover types.The area below 100 m mostly consists of farmland and built-up areas,while the area above 100 m is mainly covered by shrub and forest.Shrub has the maximum frequency in areas between 100 and 1000 m,while forest has dominance in areas above 800 m.According to the analysis of land cover changes in different ranges of elevation,the greatest change below 100 m was the process of urbanization.The process of the main land cover change occurred above 100 m was the transformation from shrub to forest.This result was consistent with the vertical change of natural vegetation distribution in Beijing.(3) Slope has a great influence on the distribution of land cover.Farmland and built-up areas are mostly distributed in fiat areas,while shrub and forest occupy steeper areas compared with other land cover types.Forest frequency increased with the increasing slope.Land cover changes differed from the slope gradients.In the plain area,the land cover change occurred as the result of urbanization.With the increasing of the slope gradient,afforestation,which converts shrub to forest,was the process of the primary land cover change.     

Land cover dynamics of different topographic conditions in Beijing, China

Topographic conditions play an important role in controlling land cover dynamic processes. In this study, remotely sensed data and the geographic information system were applied to analyze the changes in land cover along topographic gradients from 1978 to 2001 in Beijing, a rapidly urbanized mega city in China. The study was based on five periods of land cover maps derived from remotely sensed data: Landsat MSS for 1978, Landsat TM for 1984, 1992, 1996 and 2001, and the digital elevation model (DEM) derived from 1:250,000 topographic map. The whole area was divided into ten land cover types: conifer forest, broadleaf forest, mixed forest, shrub, brushwood, meadow, farmland, built-up, water body and bare land. The results are summarized as follows. (1) Shrub, forest, farmland and builtup consist of the main land cover types of the Beijing area. The most significant land cover change from 1978 to 2001 was the decrease of the farmland and expansion of the builtup area. Farmland decreased from 6354 to 3813 km2 in the 23 years, while the built-up area increased from 421 to 2642 km2. Meanwhile, the coverage of forest increased from 17.2% to 24.7% of the total area. The conversion matrix analysis indicated that the transformation of farmland to the built-up area was the most significant process and afforestation was the primary cause of the replacement of shrub to forest. (2) Topographic conditions are of great importance to the distribution of land cover types and the process of land cover changes. Elevation has an intensive impact on the distribution of land cover types. The area below 100 m mostly consists of farmland and built-up areas, while the area above 100 m is mainly covered by shrub and forest. Shrub has the maximum frequency in areas between 100 and 1000 m, while forest has dominance in areas above 800 m. According to the analysis of land cover changes in different ranges of elevation, the greatest change below 100 m was the process of urbanization. The process of the main land cover change occurred above 100 m was the transformation from shrub to forest. This result was consistent with the vertical change of natural vegetation distribution in Beijing. (3) Slope has a great influence on the distribution of land cover. Farmland and built-up areas are mostly distributed in flat areas, while shrub and forest occupy steeper areas compared with other land cover types. Forest frequency increased with the increasing slope. Land cover changes differed from the slope gradients. In the plain area, the land cover change occurred as the result of urbanization. With the increasing of the slope gradient, afforestation, which converts shrub to forest, was the process of the primary land cover change. __________ Translated from Journal of Plant Ecology, 2006, 30(2): 239–251 [译自: 植物生态学报]     

Land‐use change outweighs projected effects of changing rainfall on tree cover in sub‐Saharan Africa

Global change will likely affect savanna and forest structure and distributions, with implications for diversity within both biomes. Few studies have examined the impacts of both expected precipitation and land use changes on vegetation structure in the future, despite their likely severity. Here, we modeled tree cover in sub‐Saharan Africa, as a proxy for vegetation structure and land cover change, using climatic, edaphic, and anthropic data (R² = 0.97). Projected tree cover for the year 2070, simulated using scenarios that include climate and land use projections, generally decreased, both in forest and savanna, although the directionality of changes varied locally. The main driver of tree cover changes was land use change; the effects of precipitation change were minor by comparison. Interestingly, carbon emissions mitigation via increasing biofuels production resulted in decreases in tree cover, more severe than scenarios with more intense precipitation change, especially within savannas. Evaluation of tree cover change against protected area extent at the WWF Ecoregion scale suggested areas of high biodiversity and ecosystem services concern. Those forests most vulnerable to large decreases in tree cover were also highly protected, potentially buffering the effects of global change. Meanwhile, savannas, especially where they immediately bordered forests (e.g. West and Central Africa), were characterized by a dearth of protected areas, making them highly vulnerable. Savanna must become an explicit policy priority in the face of climate and land use change if conservation and livelihoods are to remain viable into the next century.