未来气候变化对山地生物气候类型分布的影响--以四川省为例

使用生物气候分类法评估气候变化下生态系统变化的区域,对于气候变化下生态系统的保护有着重要的意义。但是现有的研究由于分析尺度较大,难以反映气候变化对于山地生态系统的影响。选取四川省为研究区,使用区域气候模型(Reg CM4.0)对未来气候变化进行预估,在此基础上按照柯本生物气候分类法划分原则,分别对当前1981—2010,未来2011—2040,2031—2060以及2070—2099时段四川省柯本气候类型进行识别并分析各类型的转变。结果表明(1)当前四川省分布的柯本气候类型共包括3个主要类型,分别为暖温带气候带(C),冷温带气候带(D),极地气候带(E),其面积分别占四川省总面积的54%,22%和24%。(2)在未来各时段内,四川省柯本气候类型总体分布格局并无明显变化。但是未来气候变化程度足以使得部分区域内的生物气候类型发生转变,其中最大的转变发生于E类型向D类型的转变。相比当前时段,到2070—2099时段C类型和D类型增加面积占当前分布面积的13%和20%,E类型减少面积占当前分布面积的48%。对比不同时段的转变速率,近期的气候变化对于生物气候类型的影响要大于远期的气候变化。(3)由于受气候变化的影响,各柯本气候类型分布的平均海拔均向高海拔区域上移,C类,D类和E类型分布平均海拔的上移速率分别为2.9,3.4 m/a和1.8 m/a。此外,经统计生物气候类型发生变化区域的海拔主要为3800—4500 m。     

西南地区红花龙胆分布格局模拟与气候变化影响评价

应用最大熵(MaxEnt)模型,基于230条分布记录及33个气候因子数据,模拟全新世中期(约6000年前)、当前时期(1950—2000年)和未来(2050s、2070s)气候条件下,红花龙胆西南地区的潜在分布范围;结合多元统计分析和ArcGIS空间分析,筛选影响物种分布的关键气候因子,探讨不同分布区对气候变化的敏感性.结果表明: 模型训练集AUC值为0.942,验证集AUC值为0.849,表明模型预测的准确性较高.5个气候因子(7月最高气温、8月最低气温、昼夜温差与年温差比值、7月最低气温和6月最低气温)对模型贡献最大,累计贡献率达59.9%.随未来气候变化,红花龙胆适生区将呈现先减少后增加的变化趋势,在RCP 8.5情景下,至2070s阶段,西南地区红花龙胆适宜生境总面积与当前气候条件相比减少15.0%,但云南境内适生区和高适生区面积较当前分别增加32.8%和32.7%.红花龙胆适宜生长于温暖、湿润的气候条件下,气候变暖明显影响着适宜生境的面积和范围,尤其低海拔分布区对气候变化较敏感,适宜生境退缩严重,而高海拔地区由于降水、温度条件的改善适宜生境有所增加.随着全球气候的变化,未来西南地区红花龙胆主要分布区可能向西迁移,并向更高海拔扩张.     

汶川地震对大熊猫栖息地的影响与恢复对策

 大熊猫是生物多样性保护的旗舰种, 保护大熊猫及其栖息地是保护生物多样性和生态系统功能完整性与稳定性的重要保障体现。汶川地震灾区位于大熊猫重点分布区岷山-邛崃山, 地震及其次生灾害导致该区27个大熊猫自然保护区不同程度受损, 8.3%的大熊猫栖息地因地震而被破坏。地震及其次生灾害对大熊猫栖息地的影响主要表现在: 1) 地震埋没和砸毁大熊猫赖以生存的主食竹, 地震可能诱发主食竹开花, 威胁到大熊猫的健康和食物安全; 2) 地震及其诱发的土壤和山石运动显著影响森林的动态特征, 森林大面积丧失或质量下降; 3) 地震改变大熊猫栖息地生境特征, 大熊猫个体交流的廊道阻断, 形成“生殖孤岛”, 遗传多样性降低, 栖息地破碎化进程加快。应对震后大熊猫栖息地恢复的主要对策有: 1) 重新评估震后大熊猫栖息地质量, 并重新规划现有大熊猫保护区群的布局; 2) 应用地理信息系统、遥感及数学模型等手段与野外实地实证研究相结合的方法, 全面查清震后大熊猫栖息地主食竹资源状况及分布规律并及时监测其动态, 复壮更新大熊猫主食竹; 3) 利用天然植被自然恢复和人工重建等措施恢复因地震而退化或丧失的大熊猫栖息地。     

岷山北部竹类开花状况及对大熊猫的影响调查

2006年12月、2007年7～8月对岷山北部4县的竹类开花及大熊猫活动情况进行了调查.结果表明:(1)该区域竹种单一,仅有华西箭竹Fargesia nitida和缺苞箭竹F.denudata两种竹类,其中华西箭竹的分布面积最大;(2)该区域竹类从2004年开始出现开花现象,到2007年调查时开花过程已基本结束,开花竹面积达73 082 hm2,占竹类分布面积的51.36%;(3)在整个开花过程中,大熊猫实体被发现的频次增加,没有发现病、饿、死大熊猫的个体,现有大熊猫分布在竹类未开花的迭部县东部和舟曲县境内.此次竹类开花枯死,使该区域原有的大面积的大熊猫栖息地消失,因此需要加强对栖息地的保护和研究工作,使之尽快恢复成为大熊猫适合的栖息地.     

气候变化对黄腹角雉潜在栖息地的影响

气候变化直接影响物种赖以生存的栖息地环境条件,进而影响物种的分布、数量和存活率。基于优化后最大熵(MaxEnt)模型预测气候变化下黄腹角雉(Tragopan caboti)过去、当前、未来时期的潜在栖息地格局。结果表明,降水量、温度、海拔是栖息地的主要影响因子。当前时期适宜栖息地面积较过去时期下降24.69%;未来2041—2060年间,共享社会经济路径(SSP)3-7.0与SSP5-8.5情景下黄腹角雉适宜栖息地面积较当前时期分别下降55.19%、58.10%。浙江、江西和福建是当前以及未来黄腹角雉核心适宜栖息地,适宜栖息地面积呈现下降的趋势,并往高纬度区域移动。     

采笋对八月竹生长和大熊猫活动的影响研究

采笋是大相岭山系大熊猫栖息地内一种传统的资源利用活动。为了了解采笋活动对大熊猫活动以及不同采笋管理方式对八月竹Chimonobambusa szechuanensis生长的影响,2008—2012年在大相岭山系对大熊猫的活动情况进行了调查和监测,2013年对规模性采笋的四川省洪雅县和限制规模性采笋的四川省荥经县内的八月竹生长状况进行了调查。结果表明:(1)洪雅县一年生八月竹密度显著高于荥经县(P=0.002),荥经县多年生八月竹的株高显著高于洪雅县(P=0.005);(2)八月竹种群密度与海拔呈正相关。洪雅县八月竹的多年生基径、多年生株高和一年生株高与海拔均呈显著负相关,而荥经县八月竹的多年生基径、多年生株高和一年生株高则与海拔呈显著正相关;(3)大相岭山系大熊猫主要活动于海拔1 400~2 700 m,85%的痕迹点出现在2 000 m以上;(4)采笋期间未在八月竹林发现大熊猫活动痕迹,而采笋期前、后均能在八月竹林发现大熊猫痕迹。规模性采笋对八月竹的株高、基径和密度都有影响,并且采笋活动对大熊猫活动产生影响,应进一步规范采笋行为,协调保护与社区经济的可持续发展。     

东北地区5个物种潜在栖息地变化与优化保护规划

气候变化广泛影响着物种多样性及其分布变迁。优化模型模拟结果,获取气候变化影响下的优先保护区域将为制定应对气候变化的物种保护政策或行动提供理论依据,提升保护绩效。选取东北地区五种代表性动物,包括黑熊(Ursus thibetanus)、驼鹿(Alces alces)、水獭(Lutra lutra)、紫貂(Martes zibellina)及黑嘴松鸡(Tetrao parvirostris);结合最大熵模型(Maxent)模拟在不同RCP情景下未来3个年代(2030s,2050s,2070s)的物种潜在栖息地。根据九个常用气候模式的评价结果,获取东北地区合适的气候模式,了解气候变化对物种潜在栖息地的影响,同时开展物种保护规划,识别保护空缺,为应对气候变化、保持生物多样性提供支持。结果显示,在气候变化背景下物种潜在栖息地面积整体呈现下降趋势,但不同气候模式之间存在差异;评价结果推荐CCSM4、Nor ESM1-M、Had GEM2-AO及GFDL-CM3气候模式,推荐在东北地区使用以上气候模式进行物种未来潜在分布的研究。5个物种潜在栖息地平均面积变化率分别为-62.16%,-73.93%,-78.46%(2030s,2050s,2070s)。综合5个重点保护物种的保护优先区,大兴安岭的呼中、汗马与额尔古纳国家级自然保护区,延边地区的天佛指山、老爷岭东北虎、珲春东北虎与汪清原麝国家级自然保护区,长白山国家级自然保护区是气候变化下物种保护的热点区域。     

气候变化对中国马可波罗盘羊适宜生境的潜在影响

气候变化可能造成生物多样性下降和物种灭绝。开展气候变化对濒危野生动物分布格局影响的研究,对识别野生动物优先保护区、制定相关保护策略具有重要价值。本研究基于2017—2018年在新疆塔什库尔干野生动物自然保护区野外调查获得的马可波罗盘羊(Ovis ammon polii)分布位点,采用最大熵模型预测了气候变化下其适宜生境分布格局动态。结果表明: 马可波罗盘羊当前的适宜生境主要分布于保护区西北部,温度是影响其适宜生境分布的关键因子。在中、高排放浓度(RCP4.5和RCP8.5)下,未来2050s和2070s两个时期马可波罗盘羊的适宜生境面积主要呈下降趋势,适宜生境丧失率高达40.5%;丧失的适宜生境主要位于低海拔区域,高海拔区域的适宜生境面积相应增加;由低海拔向高海拔转移的适宜生境面积随温室气体排放浓度升高而增加。从质心转移结果来看,其适宜生境主要向西(即马可波罗盘羊主要分布国塔吉克斯坦)迁移。     

四川小相岭山系大熊猫种群及栖息地调查

小相岭山系是现存大熊猫种群数量最少的山系之一。根据全国第3次大熊猫及其栖息地调查结果,小相岭山系大熊猫栖息地分布在石棉、冕宁和九龙三县,栖息地总面积802.04 km²,大熊猫种群数量有32只。大熊猫在3个位于小相岭山系的自然保护区内种群数量和栖息地面积分别为:四川冶勒自然保护区9只,栖息地面积168.01 km²;四川栗子坪自然保护区14只,栖息地面积306.38 km²;四川贡嘎山自然保护区1只,栖息地面积15.19 km²。在3个保护区大熊猫栖息地总面积为489.58 km²,占各山系大熊猫栖息地总面积的61.05%;有大熊猫24只,占大熊猫种群数量的75.0%。小相岭山系大熊猫meta种群栖息地片段化比较严重,它由2个种群和2个孤立分布点组成。南北方向从成都至昆明的108国道以东的种群A有大熊猫13只,栖息地面积263.54 km², 完整性较好,大熊猫分布比较集中。108国道以西的种群B有大熊猫19只,栖息地面积为538.50 km²,栖息地破碎。该山系大熊猫数量少,栖息地片段化严重,需加强保护。
     

青木川自然保护区大熊猫生境评价

在实地调查和收集资料的基础上,对陕西省青木川自然保护区大熊猫生境选择的特点进行研究;利用层次分析法以及ArcMap、ArcView等地理信息系统辅助软件,从地理环境因素、生物群落因素、主食竹因素和干扰因素4方面对大熊猫栖息地的核心区和缓冲区进行质量评价.结果表明：研究区适宜大熊猫生存的生境面积比例为62.1%;次适宜生境面积占31.0%;不适宜生境面积占6.9%.大熊猫适宜生境主要分布在研究区西部和北部海拔较高的地带,不适宜生境主要受植被类型、竹子因素、干扰因素等影响.为减少大熊猫不适宜生境,需要保护区管理者进一步完善管理机制,控制人类活动,特别是海拔900～1600 m范围内的放牧、割竹和砍柴活动.     

Hopes and challenges for giant panda conservation under climate change in the Qinling Mountains of China

One way that climate change will impact animal distributions is by altering habitat suitability and habitat fragmentation. Understanding the impacts of climate change on currently threatened species is of immediate importance because complex conservation planning will be required. Here, we mapped changes to the distribution, suitability, and fragmentation of giant panda habitat under climate change and quantified the direction and elevation of habitat shift and fragmentation patterns. These data were used to develop a series of new conservation strategies for the giant panda. Qinling Mountains, Shaanxi, China. Data from the most recent giant panda census, habitat factors, anthropogenic disturbance, climate variables, and climate predictions for the year 2050 (averaged across four general circulation models) were used to project giant panda habitat in Maxent. Differences in habitat patches were compared between now and 2050. While climate change will cause a 9.1% increase in suitable habitat and 9% reduction in subsuitable habitat by 2050, no significant net variation in the proportion of suitable and subsuitable habitat was found. However, a distinct climate change‐induced habitat shift of 11 km eastward by 2050 is predicted firstly. Climate change will reduce the fragmentation of suitable habitat at high elevations and exacerbate the fragmentation of subsuitable habitat below 1,900 m above sea level. Reduced fragmentation at higher elevations and worsening fragmentation at lower elevations have the potential to cause overcrowding of giant pandas at higher altitudes, further exacerbating habitat shortage in the central Qinling Mountains. The habitat shift to the east due to climate change may provide new areas for giant pandas but poses severe challenges for future conservation.     

An ecophysiological perspective on likely giant panda habitat responses to climate change

Threatened and endangered species are more vulnerable to climate change due to small population and specific geographical distribution. Therefore, identifying and incorporating the biological processes underlying a species’ adaptation to its environment are important for determining whether they can persist in situ. Correlative models are widely used to predict species’ distribution changes, but generally fail to capture the buffering capacity of organisms. Giant pandas (Ailuropoda melanoleuca) live in topographically complex mountains and are known to avoid heat stress. Although many studies have found that climate change will lead to severe habitat loss and threaten previous conservation efforts, the mechanisms underlying panda's responses to climate change have not been explored. Here, we present a case study in Daxiangling Mountains, one of the six Mountain Systems that giant panda distributes. We used a mechanistic model, Niche Mapper, to explore what are likely panda habitat response to climate change taking physiological, behavioral and ecological responses into account, through which we map panda's climatic suitable activity area (SAA) for the first time. We combined SAA with bamboo forest distribution to yield highly suitable habitat (HSH) and seasonal suitable habitat (SSH), and their temporal dynamics under climate change were predicted. In general, SAA in the hottest month (July) would reduce 11.7%–52.2% by 2070, which is more moderate than predicted bamboo habitat loss (45.6%–86.9%). Limited by the availability of bamboo and forest, panda's suitable habitat loss increases, and only 15.5%–68.8% of current HSH would remain in 2070. Our method of mechanistic modeling can help to distinguish whether habitat loss is caused by thermal environmental deterioration or food loss under climate change. Furthermore, mechanistic models can produce robust predictions by incorporating ecophysiological feedbacks and minimizing extrapolation into novel environments. We suggest that a mechanistic approach should be incorporated into distribution predictions and conservation planning.     

Impacts of temperature on giant panda habitat in the north Minshan Mountains

Understanding the impacts of meteorological factors on giant pandas is necessary for future conservation measures in response to global climate change. We integrated temperature data with three main habitat parameters (elevation, vegetation type, and bamboo species) to evaluate the influence of climate change on giant panda habitat in the northern Minshan Mountains using a habitat assessment model. Our study shows that temperature (relative importance = 25.1%) was the second most important variable influencing giant panda habitat excepting the elevation. There was a significant negative correlation between temperature and panda presence (ρ = −0.133, P < 0.05), and the temperature range preferred by giant pandas within the study area was 18–21°C, followed by 15–17°C and 22–24°C. The overall suitability of giant panda habitats will increase by 2.7%, however, it showed a opposite variation patterns between the eastern and northwestern region of the study area. Suitable and subsuitable habitats in the northwestern region of the study area, which is characterized by higher elevation and latitude, will increase by 18007.8 hm² (9.8% habitat suitability), while the eastern region will suffer a decrease of 9543.5 hm² (7.1% habitat suitability). Our results suggest that increasing areas of suitable giant panda habitat will support future giant panda expansion, and food shortage and insufficient living space will not arise as problems in the northwest Minshan Mountains, which means that giant pandas can adapt to climate change, and therefore may be resilient to climate change. Thus, for the safety and survival of giant pandas in the Baishuijiang Reserve, we propose strengthening the giant panda monitoring program in the west and improving the integrity of habitats to promote population dispersal with adjacent populations in the east.     

邛崃山系大熊猫和小熊猫生境选择的比较

采用随机样方法,对邛崃山系同域分布的大熊猫与小熊猫的生境选择行为进行了比较研究。在13个生境因子48个项目中,植被、食物、水源、外界干扰、地形等概括了两种熊猫生境的主要特征。在对生境的利用上,两种熊猫均喜欢选择离水源较近、兽类和人为干扰程度较小、竹子生长发育较好的位于山体中、上部的原生针阔叶混交林或针叶林中的生境;大熊猫更喜好选择东南坡向、坡度相对较小、郁闭度相对较大、林中倒木和树桩等较少的竹林,小熊猫则更喜好选择南坡或西坡、坡度相对较大、郁闭度相对较小、林中倒木和树桩等较多的竹林。两种熊猫在生境利用上的差异可能是其同域分布长期共存的原因之一。     

用间接遥感方法探测大熊猫栖息地竹林分布

竹子是野生大熊猫赖以生存的唯一食物。探测大熊猫栖息地内的竹林分布状况,有助于深入了解大熊猫及其栖息地的空间分布格局与特点,并为评估其栖息地适宜性、破碎化程度和生态承载力提供科学依据。由于大熊猫的主食竹大都生长于林下,直接通过遥感影像解译的方法很难实现对其分布密度的探测。以佛坪自然保护区的两大优势竹种——巴山木竹和秦岭箭竹为例,在运用遥感和GIS方法获取空间连续的环境变量时,引入了林上和林下的光照条件,通过分析不同竹种与各环境要素之间的关系,建立竹子密度的预测模型,最后在GIS空间分析技术的支持下实现了对林下竹子密度的绘制。研究结果显示:该方法能够比较准确地预测出林下竹子的分布状态,对两种竹子的密度预测精度均可达到70%以上。     

Impact of livestock on giant pandas and their habitat

Livestock production is one of the greatest threats to biodiversity worldwide. However, impacts of livestock on endangered species have been understudied, particularly across the livestock–wildlife interface in forested protected areas. We investigated the impact of an emerging livestock sector in China's renowned Wolong Nature Reserve for giant pandas. We integrated empirical data from field surveys, remotely sensed imagery, and GPS collar tracking to analyze (1) the spatial distribution of horses in giant panda habitat, (2) space use and habitat selection patterns of horses and pandas, and (3) the impact of horses on pandas and bamboo (panda's main food source). We discovered that the horse distribution overlapped with suitable giant panda habitat. Horses had smaller home ranges than pandas but both species showed similarities in habitat selection. Horses consumed considerable amounts of bamboo, and may have resulted in a decline in panda habitat use. Our study highlights the need to formulate policies to address this emerging threat to the endangered giant panda. It also has implications for understanding livestock impacts in other protected areas across the globe.     

Synergistic effects of anthropogenic disturbances on giant pandas

Livestock grazing and the collection of bamboo shoots are the main threats to giant panda (Ailuropoda melanoleuca) habitat in the Liangshan Mountains in China. It is important to clarify the effect of these disturbances to the giant panda to formulate targeted management policies. Based on species distribution models and daily activity models, we investigated the effects of livestock grazing and bamboo shoot collection on giant pandas from May 2021 to July 2022. Our results indicated the giant panda's suitable habitat in the reserve covered 51.83 km² (15.02% of the reserve area). Grazing and bamboo shoot collection led to losses of 19.08 km² and 7.68 km² of suitable habitat, respectively. Together, the 2 activities resulted in a loss of 28.35 km² of suitable habitat, which was more than half of the area of panda habitat. The areas of suitable habitat for giant pandas significantly overlapped with the areas affected by both disturbances. Giant pandas did not show significant differences in daily activity rhythms under a single disturbance, but the daily activity rhythms of giant pandas differed when we compared the area combining the 2 disturbances with the undisturbed area. Our study reveals that the anthropogenic disturbances in the reserve have varying effects on the suitable habitat range and daily activity rhythm of giant pandas and evidence of a synergistic effect. Therefore, when formulating relevant conservation policies, it is important to fully evaluate the extent and characteristics of anthropogenic disturbances in shaping the population distribution and habitat preferences of the giant panda and other wildlife to enhance the efficacy of conservation management practices.     

野生大熊猫现状、面临的挑战及展望

截至2003年底,我国野生大熊猫种群数量达1596只,分布在陕西、四川和甘肃3省的45个县境内,总栖息地面积达2304991hm^2。与第2次大熊猫调查相比,野生大熊猫生存状况已得到改善,分布范围扩大、栖息地面积增加、种群数量进一步增长。本文在第3次大熊猫调查的基础上,就野生大熊猫种群及栖息地现状进行了分析,指出未来保护大熊猫所面临的3个方面的挑战,即来自物种自身生物学特性的挑战、栖息地破碎化及隔离小种群未来命运的挑战以及大熊猫保护与社区经济发展需求相冲突的挑战。作者还就我国大熊猫保护前景进行了展望,即自然保护区数量将进一步增加,栖息地状况将进一步改善;种群数量在总体保持稳定的基础上将逐步增长,但局部小种群灭绝风险将加剧;圈养种群将形成能自我维持的种群,圈养个体通过培训将逐步放归到隔离野生小种群中以改变其命运。     

Assessing vulnerability of giant pandas to climate change in the Qinling Mountains of China

Climate change might pose an additional threat to the already vulnerable giant panda (Ailuropoda melanoleuca). Effective conservation efforts require projections of vulnerability of the giant panda in facing climate change and proactive strategies to reduce emerging climate‐related threats. We used the maximum entropy model to assess the vulnerability of giant panda to climate change in the Qinling Mountains of China. The results of modeling included the following findings: (1) the area of suitable habitat for giant pandas was projected to decrease by 281 km² from climate change by the 2050s; (2) the mean elevation of suitable habitat of giant panda was predicted to shift 30 m higher due to climate change over this period; (3) the network of nature reserves protect 61.73% of current suitable habitat for the species, and 59.23% of future suitable habitat; (4) current suitable habitat mainly located in Chenggu, Taibai, and Yangxian counties (with a total area of 987 km²) was predicted to be vulnerable. Assessing the vulnerability of giant panda provided adaptive strategies for conservation programs and national park construction. We proposed adaptation strategies to ameliorate the predicted impacts of climate change on giant panda, including establishing and adjusting reserves, establishing habitat corridors, improving adaptive capacity to climate change, and strengthening monitoring of giant panda.