气候变化下中国潜在植被演替及其敏感性

潜在植被的研究能够真实反映气候条件对植被形态变化的影响,是植被-环境分类与关系研究的起点,也是全球变化与陆地生态系统研究的关键,对区域植被生态的恢复和重建具有重要的指导意义。本研究基于综合顺序分类系统,对过去30年(1986—2015年)和IPCC5发布的RCP4.5情景下未来3个时期(2030s、2050s和2080s)潜在植被的空间分布进行了GIS模拟,并分析了潜在植被对气候变化响应的敏感性。结果表明:(1)中国分布的潜在植被类型数量及各类在不同时期所占比例均存在差异,同时炎热极干热带荒漠类(VIIA)为各个时期共同缺失的潜在植被类型。(2)潜在植被的分布面积整体上呈现出冷干型潜在植被类型面积逐渐减少、暖湿型潜在植被类型面积逐渐增加的趋势,具体表现为扩展型、缩减型和波动型3类;潜在植被类组的重心发生了不同方向、不同距离的移动变化。(3)中国潜在植被对气候变化的响应存在敏感性差异,其空间分布形态总体呈现出不同敏感性程度的区域相间分布的特点。敏感性高的区域、敏感性较高的区域和敏感性较低的区域分别占国土总面积的2.28%、14.39%和43.82%。     

基于MaxEnt模型西南地区高山植被对气候变化的响应评估

采用1∶100万的中国植被类型图以及19个气候环境变量数据,基于最大熵(MaxEnt)算法和ArcGIS空间分析模块构建西南地区高山植被地理分布的气候适宜性预测模型,模拟其在基准期(1960—2000年)和不同气候情景下(A2、A1B和B1)的气候适宜性分布格局,并评价其对气候变化的适应性。结果表明:MaxEnt模型分析研究区高山植被地理分布气候适宜性的适用性非常高(AUC=0.93);最暖月均温、最湿季均温、最冷月均温等温度变量是限制其地理分布的主要气候因子;研究区高山植被地理分布的气候适宜区主要集中在西藏自治区、青海省、四川省西部及云南省西北部的部分地区;完全适宜、中度适宜、轻度适宜、不适宜的面积所占总面积比例约为1∶1∶2∶5;1960—2050年研究区高山植被潜在地理分布的气候适宜性面积有不同定程度的减少;未来3种气候变化情景下高山植被地理分布对气候变化的适应性分布格局基本一致,均为不适应区所占总面积比例较大;伴随气候变化,研究区高山植被的适应性减弱,体现在其潜在地理分布对气候变化的适应区分布范围减少;海拔5000—5500m适应性较强,适应区所占面积比例最大(53%左右);3500—4500m适应性最弱,适应区所占面积比例最小(5%左右)。     

基于潜在植被的中国陆地生态系统对气候变化的脆弱性定量评价

 陆地生态系统对气候变化的响应及其脆弱性评价研究是当前全球变化领域的重要内容之一。该研究在生态系统过程模型的基础上,耦合了潜在 植被对气候变化的动态响应,模拟气候变化对潜在植被分布格局和生态系统主要功能的影响,以潜在植被的变化次数和变化方 向定义植被分布 对气候变化的敏感性和适应性,以生态系统功能特征量的年际变率及其变化趋势定义生态系统功能对气候变化的敏感性和适应性,进而对生态 系统的脆弱性进行定量评价,分析不同气候条件下我国陆地生态系统的脆弱性分布格局及其区域特点。结果表明,我国自然生态系统气候脆弱 性的总体特点为南低北高、东低西高,气候变化将会增加系统的脆弱性。采用政府间气候变化委员会排放情景特别报告国内和区域资源情景, 即IPCC-SRES-A2气候情景进行的预测模拟表明,到21世纪末我国不脆弱的生态系统比例将减少22%左右,高度脆弱和极度脆弱的生态系统所占的 比例较当前气候条件下分别减少1.3%和0.4%。气候变化对我国陆地生态系统的脆弱性分布格局影响不大。不同气候条件下,高度脆弱和极度脆 弱的自然生态系统主要分布在我国内蒙古、东北和西北等地区的生态过渡带上及荒漠-草地生态系统中。总体而言,华南及西南大部分地区的生 态系统脆弱性将随气候变化而有所增加,而华北及东北地区则有所减小。     

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.     

气候变化下大兴安岭地区鹤类潜在分布及优先保护区

为了解气候变化对大兴安岭地区鹤类潜在分布的影响,促进其有效保护,本文以大兴安岭地区6种鹤为研究对象,基于Pearson相关性分析和Jackknife分析,筛选气候、地形和植被类型等关键环境因子,采用MaxEnt模型模拟了当前和未来两种气候变化情景(RCP4.5和8.5)下6种鹤的潜在分布区域,通过Zonation和ArcGIS软件确定了其优先保护区域并分析了目标优先保护区域.结果表明:当前气候条件下,6种鹤的潜在适宜生境集中分布于大兴安岭中部和西北部;RCP4.5和RCP8.5气候情景下,6种鹤的高适宜生境将缩减.白头鹤、丹顶鹤、白枕鹤、灰鹤和蓑羽鹤的潜在适宜生境整体呈缩减趋势,而白鹤的潜在适宜生境将比当前扩张5.4%~6.3%;当前及未来气候条件下,6种鹤的优先保护区域主要分布于大兴安岭的西北部、东南部以及中部偏西地区,目标优先保护区域的保护率达20.1%~23.8%,保护空缺主要分布于漠河县西部、额尔古纳市中部偏北地区、根河市中东部、牙克石市东北部和鄂伦春自治旗南部,建议适当增加保护地面积,为鹤类的有效保护提供保障.     

中国陆地自然植物有氧甲烷排放空间分布模拟及其气候效应

区域尺度陆地植物有氧条件下排放甲烷及其气候效应研究不仅对甲烷收支平衡研究具有重要意义,对于全球变化研究也具有重要推动作用。通过改进Keppler提出的公式,模拟了中国区域植物有氧甲烷排放的时空分布。利用IBIS模拟的NPP数据结合相关文献统计生物量与NPP的比值,计算得到中国区域自然植物叶片生物量,以及叶片甲烷排放。结果显示,2001年至2012年中国植物生物量与植物叶片甲烷排放量在Sres A2和Sres B1两种情景下差异不明显;但是气候变化模式差异的影响会随着时间的推移而扩大。在Sres A2情景下,中国地区年均植物生物量为10803.22Tg C,叶片生物量为1156.15Tg C。如果不考虑天气对光照的影响,植物叶片甲烷排放年均2.69Tg,约是全国年甲烷排放总量7.01%,是中国稻田甲烷排放总量的29.05%。在各植被类型中,草地叶片甲烷排放量最高,达到47.53%,其次是混交林。森林(针叶林、阔叶林、混交林)是主要的植物甲烷排放源,占中国区域植物甲烷排放总量的51.28%,其次是草地,占47.47%。中国区域植物叶片甲烷排放南高北低,东高西低的分布状态主要由地表植被覆盖类型决定,光照和温度也是重要影响因素。对Sres A2和Sres B1两种气候情景下中国植物甲烷排放预测分析,中国区域植物甲烷排放不断增加,在Sres A2情景下不同时期的平均增长率为9.73%,高于Sres B1情景的5.17%,且两种情景下的增长率都在降低。21世纪Sres A2和Sres B1变化情景下,年均植物排放的甲烷CO_2当量分别为83.18Tg和77.34Tg,约占中国年均CO_2排放总量的1.39%和1.29%。     

基于CSCS和RegCM3模型的21世纪末中国潜在植被

潜在植被作为陆地生态系统的重要组成部分,能够真实反映立地气候环境,对其分布特征的研究可为生态工程评价提供依据。本文以综合顺序分类系统理论为基础,选取RegCM3模型及A2情景下的预测数据,模拟了2071—2100年中国潜在植被的空间分布。结果表明,21世纪中国潜在植被均发生了不同程度、不同方向的变化,具体表现为:温带森林和冻原高山草地向冷干方向变化,其中温带森林为中国主体潜在植被;亚热带森林向较冷地区演替;温带荒漠、热带森林及热带稀树草原向冷湿方向迁移;半荒漠向暖湿地区集中分布;干草原、温带湿润草地及热带荒漠向暖干方向变化,其中温带湿润草地和热带荒漠的空间分布重心迁移显著。本文揭示了21世纪中国潜在植被的变化规律,可为我国21世纪生态建设战略提供参考。     

气候变化对邛崃山系大熊猫主食竹和栖息地分布的影响

气候变化对生物多样性的影响,特别是珍稀濒危物种的影响是当前的研究热点。全球气候变化对大熊猫的影响一直受到广泛关注。根据野外调查的大熊猫活动痕迹点、竹类分布点和主食竹扩散距离数据,采用Maxent模型,利用植被、地形、气候等因素,在RCP8.5下分析了2050年和2070年邛崃山系大熊猫主食竹分布及栖息地变化趋势。结果显示:(1)未来大熊猫适宜生境及主食竹气候适宜区面积均有所减少,到2070年分别减少37.2%和4.7%;(2)未来主食竹分布范围总体向高海拔扩展,但面积持续减少,到2070年分布面积比当前减少8.3%;(3)大熊猫栖息地未来有向高海拔扩张的趋势,在低海拔地区退缩明显,到2070年较当前减少27.2%;但到2070年大熊猫栖息地面积加上非栖息地有主食竹分布的面积,较现有大熊猫栖息地面积大1.5%;(4)受气候变化影响较严重的区域是邛崃山系南部以及低海拔地区,其余区域所受影响相对较小;(5)未来需要加强对受气候变化影响严重区域的监测与保护,特别是邛崃山系中部的大熊猫集中分布区。     

气候变暖背景下秦岭陕西段植被潜在分布区格局变化

植被分布在一定程度上受控于气候因子,在气候变化背景下,利用生物气候指标研究地带性植被的潜在分布区格局变化对于区域生态系统应对气候变化具有有益的参考价值。从生态气候学角度出发,利用植被热量指标——有效温暖指数(EWI),研究1959—2020年以及未来气候模式下秦岭山地陕西段植被潜在分布格局的变化。结果表明：(1)气候变暖导致植被热量指标发生变化,近62年来,秦岭山地陕西段EWI总体呈上升趋势,并于2001年发生上升突变。(2)基于EWI对秦岭陕西段植被类型的潜在分布区划分发现,2001年以前秦岭北坡无暖温带落阔常绿混交林的分布区,2001年后秦岭北坡渭河东部出现了该植被类型的潜在分布区。(3)随着气候变暖,秦岭陕西段暖温带植被潜在分布区不断扩张,而温带、寒温带以及高寒植被分布区持续缩减,同时各植被类型分布区的平均海拔高度均呈上移趋势。从面积及海拔变化幅度来看,秦岭南坡较北坡植被对气候变化更为敏感,高海拔区较低海拔区植被对气候变化更为敏感。(4)在代表性浓度路径4.5及8.5(RCP4.5及RCP8.5)情景下,未来50年,秦岭南北坡均将可能出现亚热带常绿阔叶林潜在分布区,亚热带常绿阔叶...     

气候变化对蒙古扁桃适宜分布范围和空间格局的影响

为模拟、预测气候变化对孑遗、濒危植物蒙古扁桃(Amygdalus mongolica)潜在分布的影响, 利用最大熵(MAXENT)模型模拟、预测、对比、分析、揭示蒙古扁桃在最大冰期(CCSM及MIROC模型)、历史气候(1961-1990年)及未来气候(2020年、2050年和2080年, 政府间气候变化专门委员会排放情景特别报告的A2A情景)条件下的适宜分布范围和空间格局的变化。结果表明: (1)蒙古扁桃在历史气候条件下的潜在分布区集中在蒙古的南戈壁省及东戈壁省, 我国内蒙古巴彦淖尔市、阿拉善左旗、鄂尔多斯市、锡林郭勒盟西部, 河西走廊中部及东部, 宁夏北部及陕西北部, 以及河北北部的部分地区; (2)与历史气候条件下的潜在分布相比, 蒙古扁桃在最大冰期CCSM气候情景下的分布经历了明显的、大范围的向南迁移和范围缩小; (3)未来A2A气候情景下, 其潜在分布范围表现出在2020年明显扩大, 在2050年减小, 到2080年又略有增大的趋势。分布格局表现出不断向我国河北及内蒙古东部, 蒙古东部、北部及西部大幅度扩散、迁移的趋势。     

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。     

A GIS simulation of potential vegetation in China under different climate scenarios at the end of the 21st century

The study of potential vegetation can reveal the impact of climate on changes in vegetation patterns. It is the starting point for studying vegetation-environmental classification and relationships, and it is the key point for studying global change and terrestrial ecosystems. By using the Comprehensive Sequential Classification System (CSCS) and the meteorological data under the four climate change scenarios from the IPCC5 publication, the present paper carries out a GIS simulation study of the spatial distribution of potential vegetation in China at the end of the 21st century. The results indicate that under the four climate scenarios at the end of the 21st century: (1) The potential vegetation in China shows significant horizontal and vertical distribution, which corresponds well to those of natural topographic features. (2) There are 40 classes of potential vegetation in China. Tropical-extrarid tropical desert (VIIA), which has no corresponding condition of growth in China, is commonly lacking, and differences exist among the potential vegetation classes and among the ratios of the classes under different scenarios. (3) From the perspective of categories, temperate forest is the most widely distributed, and savanna is the least widely distributed. Together with the strengthening of the radiation intensity according to RCP2.6 → RCP4.5 → RCP6.0 → RCP8.5, the area covered by cold-dry potential vegetation decreases as the area covered by warm-humid potential vegetation increases. As a result, the areas of tundra and alpine steppe, frigid desert, steppe, and temperate humid grassland tend to decrease, and those of semi-desert, temperate forest, sub-tropical forest, tropical forest, warm desert, and savanna tend to increase. Moreover, the potential vegetation in China at the end of the 21st century would change at different levels and in different directions when compared with that at the end of the 20th century. (4) In the same period, potential vegetation in different regions shows differences in their sensitivity to climate change, and by the end of the 21st century, 30.73% of land in China would be classified as a sensitive region, which highly corresponds to the current ecologically vulnerable zone, and whose potential vegetation easily evolves along with changes of climate scenarios.     

Prediction of potential distribution of soybean in the frigid region in China with MaxEnt modeling

Soybean (Glycine max (L.) Merr.) is one of the most important grains and oil-producing plants grown in China. Understanding the potential suitable characteristics of areas where soybean is grown and predicting its potential habitat under different climate scenarios are a significant part of ensuring food security. This study compiled 65 occurrence locations of soybean and 32 environmental variables obtained from the WorldClim database. Nine environmental variables were selected for model training. We identified potential suitable distribution areas for soybean in the frigid region and predicted changes in its geographical distribution under four shared socioeconomic pathways, SSP1–2.6, SSP2–4.5, SSP3–7.0, and SSP5–8.5, for the periods from 2021 to 2040, 2041 to 2060, 2061 to 2080, and 2081 to 2100 using the MaxEnt model. The results showed that annual mean temperature, elevation, and April solar radiation were the dominant factors affecting the distribution of soybean, contributing 48.8%, 17.9%, and 15.7% of the variability in the data, respectively. Highly suitable habitats (defined as having a suitability variable P of 0.66–1.0) for the current conditions included the Songnen and Sanjiang plains, covering about 2.36 × 10⁵ km². The total areas of highly (as defined above) and moderately suitable (0.33–0.66) habitats would be reduced under the four climate scenarios. However, the centroids of the highly suitable habitat had a small mobile range under different scenarios. These results along with previous research on the potential distribution of soybean offer useful information; ecological modeling approaches need to be considered in future crop planting management and land use.     

Modelling biome shifts and tree cover change for 2050 in West Africa

Aim Africa is expected to face severe changes in climatic conditions. Our objectives are: (1) to model trends and the extent of future biome shifts that may occur by 2050, (2) to model a trend in tree cover change, while accounting for human impact, and (3) to evaluate uncertainty in future climate projections. Location West Africa. Methods We modelled the potential future spatial distribution of desert, grassland, savanna, deciduous and evergreen forest in West Africa using six bioclimatic models. Future tree cover change was analysed with generalized additive models (GAMs). We used climate data from 17 general circulation models (GCMs) and included human population density and fire intensity to model tree cover. Consensus projections were derived via weighted averages to: (1) reduce inter‐model variability, and (2) describe trends extracted from different GCM projections. Results The strongest predicted effect of climate change was on desert and grasslands, where the bioclimatic envelope of grassland is projected to expand into the desert by an area of 2 million km². While savannas are predicted to contract in the south (by 54 ± 22 × 10⁴ km²), deciduous and evergreen forest biomes are expected to expand (64 ± 13 × 10⁴ km² and 77 ± 26 × 10⁴ km²). However, uncertainty due to different GCMs was particularly high for the grassland and the evergreen biome shift. Increasing tree cover (1–10%) was projected for large parts of Benin, Burkina Faso, Côte d’Ivoire, Ghana and Togo, but a decrease was projected for coastal areas (1–20%). Furthermore, human impact negatively affected tree cover and partly changed the direction of the projected change from increase to decrease. Main conclusions Considering climate change alone, the model results of potential vegetation (biomes) show a ‘greening’ trend by 2050. However, the modelled effects of human impact suggest future forest degradation. Thus, it is essential to consider both climate change and human impact in order to generate realistic future tree cover projections.     

Modelling the vegetation of China using the process-based equilibrium terrestrial biosphere model BIOME3

1 We model the potential vegetation and annual net primary production (NPP) of China on a 10′ grid under the present climate using the processed‐based equilibrium terrestrial biosphere model BIOME3. The simulated distribution of the vegetation was in general in good agreement with the potential natural vegetation based on a numerical comparison between the two maps using the ΔV statistic (ΔV = 0.23). Predicted and measured NPP were also similar, especially in terms of biome‐averages. 2 A coupled ocean–atmosphere general circulation model including sulphate aerosols was used to drive a double greenhouse gas scenario for 2070–2099. Simulated vegetation maps from two different CO₂ scenarios (340 and 500 p.p.m.v.) were compared to the baseline biome map using ΔV. Climate change alone produced a large reduction in desert, alpine tundra and ice/polar desert, and a general pole‐ward shift of the boreal, temperate deciduous, warm–temperate evergreen and tropical forest belts, a decline in boreal deciduous forest and the appearance of tropical deciduous forest. The inclusion of CO₂ physiological effects led to a marked decrease in moist savannas and desert, a general decrease for grasslands and steppe, and disappearance of xeric woodland/scrub. Temperate deciduous broadleaved forest, however, shifted north to occupy nearly half the area of previously temperate mixed forest. 3 The impact of climate change and increasing CO₂ is not only on biogeography, but also on potential NPP. The NPP values for most of the biomes in the scenarios with CO₂ set at 340 p.p.m.v. and 500 p.p.m.v. are greater than those under the current climate, except for the temperate deciduous forest, temperate evergreen broadleaved forest, tropical rain forest, tropical seasonal forest, and xeric woodland/scrub biomes. Total vegetation and total carbon is simulated to increase significantly in the future climate scenario, both with and without the CO₂ direct physiological effect. 4 Our results show that the global process‐based equilibrium terrestrial biosphere model BIOME3 can be used successfully at a regional scale.     

中国陆地生态系统分类识别及其近20年的时空变化

生态系统分类制图是理解生态系统时空格局和支撑生态系统分类管理的基础。研究以反映生态系统主导服务功能和人类干预强度为主线，构建了包括9个一级和25个二级类的生态系统分类体系，集成土地利用、气候、地形、植被、土壤、居民点分布等多源数据，开展了2000和2020年中国陆地生态系统的分类制图，并对其类型、结构、格局及时空变化特征进行了分析。结果表明：近20年，我国城镇生态系统扩张1.1倍，64.51%来自耕种生态系统。耕种生态系统缩减0.88万km²，其中水田和旱田分别减少0.60万km²和2.09万km²，但绿洲扩张1.81万km²。受退耕还林还草影响，农牧和农林混合生态系统分别减少2.88万km²和0.92万km²，林地生态系统增加1.61万km²。水域湿地生态系统增加0.31万km²，70%源自沼泽生态系统的扩张，尤其是青藏高原水域湿地，受气候变暖影响扩张明显。气候暖湿化促使部分干旱荒漠和冰冻寒漠生态系统的盖度增加，使牧草地生态系统增加9.97万km²，而干旱荒漠和冰冻寒漠生态系统分别减少14.98万km²和0.92万km²。我国生态系统变化导致整体景观的连接性下降、破碎度增加、类型多样性增加，斑块间生态过程的阻碍增强。我国生态状况明显改善，92.06%的区域NDVI增加，平均NDVI增幅为0.74%/a，其中农牧和农林混合生态系统NDVI增幅最显著，分别为1.26%/a和0.85%/a。该分类方案与制图结果突出了生态系统结构、生态环境风险和生产力的差异，可为宏观尺度的生态系统管理提供科学支撑。     

气候变化情景下中国荒漠锦鸡儿潜在适生区的时空变化分析

荒漠锦鸡儿是一种强旱生矮灌木,主要分布在荒漠草原和草原化荒漠中。该研究以植物志和数字标本库中获取的130条记录生成的荒漠锦鸡儿分布记录样点图为基础,运用组合模型(ESDM)模拟荒漠锦鸡儿在末次冰盛期、全新世中期、当前和未来(2030s)气候情景下的潜在地理分布,通过ArcGIS计算适生区面积及质心迁移轨迹,探讨末次冰盛期以来气候变迁对荒漠锦鸡儿分布的影响,为气候变化背景下荒漠锦鸡儿的保护提供理论基础。结果表明:(1)降水因子对荒漠锦鸡儿分布的影响高于温度因子和地形因子。(2)当前荒漠锦鸡儿的中、高适生区面积为10.172×10^(5) km^(2),质心位于阿拉善左旗。(3)末次冰盛期质心向东南迁移至全新世中期质心,继而向东北迁移至当前质心,荒漠锦鸡儿能较好地适应末次冰盛期寒冷干燥的环境。(4)在未来RCP2.6、RCP4.5和RCP6.0情景下,荒漠锦鸡儿中、高适生区面积均成增加趋势,但RCP8.5情景下的适生区面积却比当前减少了1.981×105 km^(2)。研究推测,轻度的气候变暖有利于荒漠锦鸡儿的生存与分布。     

Net primary production, carbon storage and climate change in Chinese biomes

Net primary production (NPP) and leaf area index (LAI) of Chinese biomes were simulated by BIOME3 under the present climate, and their responses to climate change and doubled CO₂ under a future climatic scenario using output from Hadley Center coupled ocean‐atmosphere general circulation model with CO₂ modelled at 340 and 500 ppmv. The model estimated annual mean NPP of the biomes in China to be between 0 and 1270.7 gC m^‐2 yr^‐1 at present. The highest productivity was found in tropical seasonal and rain forests while temperate forests had an intermediate NPP, which is higher than a lower NPP of temperate savannas, grasslands and steppes. The lowest NPP occurred in desert, alpine tundra and ice/polar desert in cold or arid regions, especially on the Tibetan Plateau. The lowest monthly NPP of each biome occurred generally in February and the highest monthly NPP occurred during the summer (June to August). The annual mean NPP and LAI of most of biomes at changed climate with CO₂ at 340 and 500 ppmv (direct effects on physiology) would be greater than present. The direct effects of carbon dioxide on plant physiology result in significant increase of LAI and NPP. The carbon storage of Chinese biomes at present and changed climates was calculated by the carbon density and vegetation area method. The present estimates of carbon storage are totally 175.83 × 10¹² gC (57.57 × 10¹² gC in vegetation and 118.28 × 10¹² gC in soils). Changed climate without and with the CO₂ direct physiological effects will result in an increase of carbon storage of 5.1 and 16.33 × 10¹², gC compared to present, respectively. The interaction between elevated CO₂ and climate change plays an important role in the overall responses of NPP and carbon to climate change.     

美味猕猴桃地理分布模拟与气候变化影响分析

为了解气候变化对美味猕猴桃(Actinidia deliciosa)地理分布的影响,结合气候情景,采用Maxent预测美味猕猴桃的适生区的变化趋势。结果表明,基准气候和未来情景下构建的美味猕猴桃分布模型的AUC值均达到极好的标准。基准气候条件下,美味猕猴桃在中国的适生区为22°~38°N,96°~122°E,总面积为3.367 9×106 km2,高适生区位于秦岭-巴山、四川盆地东部、云贵高原东部、武陵山-巫山、武夷山脉。RCP4.5和RCP8.5情景下,美味猕猴桃在中国的高适生区面积将显著减少,中适生区面积则呈增加趋势,两种情景下高、中质心均向偏南或低纬度方向移动,RCP8.5情景下质心的迁移轨迹最长,变动范围最大。Maxent模型的准确预测对于优化猕猴桃产业结构具有重要指导意义。     

Effects of climate change,coal mining and grazing on vegetation dynamics in the mountain permafrost regions

The ecological environment in alpine regions is fragile and sensitive to land-use and land-cover (LULC) change and climate warming. However, there are limited studies on the response of LULC and vegetation activity to climate change and human interference in mountainous permafrost regions. Based on in-situ meteorological and multi-source remote sensing data, we performed time trend and partial correlation analyses to investigate the spatial and temporal variation of LULC, landscape pattern, and vegetation growth under the impact of climate change and human activities in the source region of the Datong River from 2000 to 2019. Our results showed that the alpine desert area decreased significantly at a rate of −13.1 km² yr⁻¹ (p < 0.05), while the alpine meadow area increased at a rate of 8.3 km² yr⁻¹ (p < 0.1). Mining and road areas showed a significant increasing trend at a rate of 3.2 km² yr⁻¹ and 1.2 km² yr⁻¹, respectively. The increasing alpine meadow and mining areas were mainly derived from alpine deserts and alpine wetlands, respectively. The number of alpine wetland patches increased significantly along with a significant decrease in the landscape shape index of the rivers. Vegetation growth, as indicated by the enhanced vegetation index (EVI) was positively correlated with temperature but negatively correlated with precipitation and solar radiation in 59.6%, 52.3%, and 56.5% of the vegetated areas, respectively (p < 0.05). Temperature was the dominant climate factor controlling vegetation dynamics, and the recent warming hiatus resulted in a significant increase in EVI for alpine deserts, but no significant changes in EVI for alpine wetlands and alpine meadows. Increasing risk of negative impacts from human activities, including mineral exploration and grazing, on vegetation distribution and growth was observed. This study provides clear evidence of the upward invasion of alpine meadows into alpine desert areas under warm and humid climatic conditions. As climate warming intensifies, alpine meadow expansion may be impeded by extreme precipitation and permafrost thawing.