相岭山系大熊猫和小熊猫对生境的选择

１９９４年至１９９６年，作者在冕宁肥冶勒自然保护区设点，对同域分布，以同种竹子为食的大熊猫和小熊猫的生境利用进行了历时两年多的对比研究。研究结果表明，虽然它们在生境选择上有部分重叠，但是其微生境昨用方式明显不同，主要表现如下：大熊猫喜欢选择坡度平缓的山坡，小熊猫则喜欢选择较陡的山坡；     

邛崃和相岭山系小熊猫种群的遗传结构

测定了来自小熊猫主要分布的两大山系———相岭和邛崃的 2 3只小熊猫样品的mtDNA控制区 5’端 5 69bp序列 ,共发现 2 3个变异位点 ,定义了 8种单元型 ,其中邛崃山系 5种 ,相岭山系 3种。分析结果表明 ,两山系均表现出较低的核苷酸多态性 ;单元型多态性差异明显 ,其中邛崃山系高于相岭山系。分子变异分析表明 ,两山系的小熊猫种群间具有较高的基因流 (Nm =2 95 ) ,两种群遗传分化不明显 (ΦST=0 1 45 ,P >0 0 5 )。结合细胞色素b序列分析 ,认为两种群可能是从经历了近期瓶颈效应的同一祖先群衍生而来 ,并且可将两山系的小熊猫种群作为一个管理单元进行保护和管理     

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。     

小相岭山系大熊猫大中型伴生兽类

本文总结了小相岭山系与大熊猫同域分布的大中型兽类的种类、主要遗留痕迹的鉴别特征以及对大熊猫的影响;统计了大熊猫伴生动物的样线遇见率,反映了不同伴生动物的相对数量。本文对进一步研究小相岭山系大熊猫的伴生动物,更好地保护大熊猫具有一定的参考价值。     

岷山山系南端大熊猫栖息地分布分析

基于大熊猫Ailuropoda melanoleuca野外分布数据及环境变量,利用MaxEnt模型对岷山山系南端的大熊猫适宜栖息地分布进行了预测及分析。结果显示:研究区域内有大熊猫适宜栖息地330.9 km²,占研究区域内保护区总面积的23.2%;并且龙溪虹口-白水河-九顶山一线的大熊猫的栖息地存在一定的破碎化现象。建议继续加强对大熊猫栖息地的保护,减少人为干扰,促进大熊猫栖息地的恢复,增进各相邻保护区间的沟通交流、数据分享,更准确掌握、了解该区域大熊猫的动态。     

岷山山系大熊猫自然保护区2003年生物多样性监测

岷山山系是全球生物多样性保护的热点地区之一,有着全世界最大的大熊猫种群和面积最大的大熊猫栖息地。到2003年底,在该地区已建立了20个以保护大熊猫为主的自然保护区。从2003年开始,岷山17个大熊猫自然保护区实施了野外大熊猫及其栖息地监测。通过监测,了解了岷山自然保护区野生动物分布状况、人为活动对自然保护区的干扰情况,以及自然保护区周边社区经济情况,为自然保护区管理决策提供了依据。同时,通过监测活动还提高了自然保护区工作人员的业务水平。建议今后将自然保护区监测工作纳入自然保护区日常工作中。     

凉山山系,小相岭山系大熊猫遗传多样性的DNA指纹比较分析

利用同位素标记大熊猫ＤＮＡ指纹探针Ｆ２ＺＧＰ９６０６０８０１,比较检测了凉山山系和小相岭山系大熊猫随机个体的ＤＮＡ指纹图,获得的遗传多样性参数如下：（１）凉山山系和小相岭山系随机个体的平均谱带数分别是３３．１４和２８．２５条;平均等位基因频率分别是０．４３和０．４８;平均杂合率分别是５７％和５２％。（２）凉山山系和小相岭山系大熊猫各自群体内部个体之间ＤＮＡ指纹的相似系数分别是０．６８和０．７２。将两个山系并为一个大群体后,随机个体的平均谱带数为３０．５３;平均等位基因频率为０．３６;个体之间ＤＮＡ指纹的相似系数为０．５８;平均杂合率上升至６４％。（３）凉山山系和小相岭山系大熊猫群体之间的遗传距离为０．４２,两山系之间已有明显的遗传分化。大熊猫以分布的山系为群体单元时,个体之间遗传相似性高,遗传多样性贫乏;若群体单元扩大到两个山系时,个体之间遗传相似性下降,遗传多样性明显上升。此结果初步表明：大熊猫作为一个物种,遗传多样性可能不是很贫乏,但各个山系内的大熊猫群体,遗传多样性的贫乏程度是相当严重的。     

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。     

相岭山系冕宁冶勒自然保护区大熊猫-竹子种群数学模型的研究

本文对袁重桂、张洪德(1990)提出的大熊猫-竹子种群的数学模型做了较大的改进,加入了修正项(m-x2)y2/km得到新模型x=rx-ix-αx2-cy,y=by-dy-ey2-(m-x)y2/km其中的生命系数是作者在冕宁县冶勒自然保护区作实际资料收集统计得来的;并将α作为参数,当改变参数α时,正平衡点B是稳定的焦点或是不稳定的焦点;分支值α0存在于一个很小的区间,模型的相图的基本结构发生了较大的变化,出现了一个稳定的极限环。     

基于地理加权回归模型探究环境异质性对秦岭大熊猫空间利用的影响

环境异质性对野生动物分布的影响具有明显的空间不均匀性。传统分析中多采用经典线性回归模型来量化野生动物分布与环境变量之间的关系,难以准确反映物种-环境关系的空间异质特征。地理加权回归(GWR)是近年来提出的一种新的空间分析方法,通过将空间结构嵌入线性回归模型中,以此来探测空间关系的非均匀性。以秦岭大熊猫为例,应用GWR模型分析大熊猫空间分布与环境异质性特征之间的潜在关系,并同经典的全局最小二乘回归法(OLS)进行比较。结果表明,GWR模型的AIC、R²和校正R²均显著优于OLS模型,GWR模型的局部回归系数估计能够更加深刻地揭示大熊猫空间分布与环境变量间的复杂空间关系,且GWR模型能够为物种的科学保护提供更加有效的理论支撑。因此,GWR模型可为探究物种-环境关系的空间异质特征提供一种新的方法,在物种栖息地选择与利用研究中具有一定的应用前景。     

Vocal cues to male androgen levels in giant pandas

Little is known about the potential of non-human mammal vocalizations to signal information on the hormonal status of the caller. In the current study, we used endocrine data and acoustic analyses to determine whether male giant panda bleats provide reliable information about the caller''s current androgen levels. Our results revealed significant relationships between acoustic features of male giant panda bleats and the caller''s faecal androgen metabolite concentrations. To our knowledge, this constitutes the first demonstration that the acoustic structure of a non-human mammal call has the potential to yield information about the caller''s current androgen levels. We go on to discuss the anatomical basis for our findings and the potential functional relevance of signalling information on male androgen levels in giant panda sexual communication.     

Old-growth forest is what giant pandas really need

Giant pandas (Ailuropoda melanoleuca) are an iconic conservation species, but despite significant research effort, do we understand what they really need? Estimating and mapping suitable habitat play a critical role in conservation planning and policy. But if assumptions about ecological needs are wrong, maps with misidentified suitable habitat will misguide conservation action. Here, we use an information-theoretic approach to analyse the largest, landscape-level dataset on panda habitat use to date, and challenge the prevailing wisdom about panda habitat needs. We show that pandas are associated with old-growth forest more than with any ecological variable other than bamboo. Other factors traditionally used in panda habitat models, such as topographic slope, are less important. We suggest that our findings are disparate from previous research in part because our research was conducted over a larger ecological scale than previous research conducted over more circumscribed areas within individual reserves. Thus, extrapolating from habitat studies on small scales to conservation planning on large scales may entail some risk. As the Chinese government is considering the renewal of its logging ban, it should take heed of the panda''s dependency on old growth.     

Semen evaluation of giant pandas (Ailuropoda melanoleuca) at the Wolong Reserve

Semen from 4 wild-caught giant pandas (Ailuropoda melanoleuca) held at the China Conservation and Research Centre for the Giant Panda was collected (22 samples during 1991–1993) by electroejaculation, and evaluated for use in artificial insemination. Semen characteristics (mean ± SD) recorded were as follows: semen volume–1.5 ± .9 ml (range—0.3–3.5); sperm density 1.5 ± 0.1 × 10⁹/ml (range—0.24–4.2); motility 79 ± 10% (range—60–95); abnormal sperm 14 ± 5% (range—10–27); and pH 7.1 ± 0.2 (range—6.7–7.5). There were significant differences from year to year (P < 0.05) in semen volume collected and in the percentage abnormal sperm in 1993 compared to other years. There were no significant differences among semen produced from the four different pandas. Data collected were similar to reports for other giant pandas, and semen from all 4 giant pandas was considered suitable for use in artificial insemination. © 1994 Wiley-Liss, Inc.     

Molecular analysis of dispersal in giant pandas

Although dispersal in the giant panda (Ailuropoda melanoleuca) is a demographic mechanism which can potentially counteract the negative effect of habitat fragmentation, little is known about dispersal in this species because of difficulties in observing individuals. Using data from faecal microsatellite genotyping, we compared the spatial distribution of giant pandas in two populations and the proximity of relatives in one key population to infer their dispersal pattern. We conclude that giant pandas exhibit female-biased dispersal because: (i) vAIc (variance of assignment index) for females was significantly larger than for males, suggesting that females comprise both 'local' and 'foreign' genotypes; (ii) the average spatial distance of related female dyads was significantly larger than that of males; (iii) larger r (relatedness), F(ST) (genetic variance among populations) and mAIc (mean of assignment index) values were found in males using the software FSTAT, although the differences were not significant; (iv) males set up territories neighbouring to their birth place; (v) significant population structure using microsatellites with a concomitant lack of mitochondrial structure was found in a previous study, possibly indicating more extensive female dispersal; and (vi) female-biased dispersal was strongly supported by evidence from concomitant ecological studies. Considering previous ecological data and life-history characteristics of the giant panda, female-biased dispersal is most likely to be due to competition for birth dens among females, inbreeding avoidance and enhancing inclusive fitness among related males.     

大相岭北坡大熊猫生境适宜性评价

2005 年3 ～11月采用样线法和样方法对大相岭北坡大熊猫栖息地进行了调查,通过利用样方法发现的大熊猫痕迹频次对栖息地的适宜性进行景观连接度(适宜性)赋值,对大相岭北坡大熊猫栖息地的质量进行了分析评价。研究区面积约为2266.79 km² ,其中竹林分布面积约为842.3 km² 。仅有约56.8 km² 占6.8%的竹林面积是适宜大熊猫生存的地区,次适宜地区面积为96.3 km² ,约占11.4%,较差适宜地区面积为177.4 km²,约占21.1%,3 个等级加到一起共为330.5 km² ,占竹林面积的39.3%,主要分布在2200～2800 m 的平缓山坡,有60% 以上为不适宜地区。人为活动对大熊猫栖息地的影响主要是不仅减少了大熊猫的生境面积,也降低了大熊猫亚种群之间的景观连接度,对大熊猫种群之间的基因交流产生阻碍。作者通过实际调查提出了管理措施。     

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.     

海拔对大熊猫主食竹结构、营养及大熊猫季节性分布的影响

大熊猫主要采食竹子,因此主食竹对大熊猫生存具有重要的作用。在秦岭的佛坪地区的大熊猫主要取食巴山木竹以及秦岭箭竹。本文研究了海拔对这两种竹林的结构与营养含量的影响以及海拔与大熊猫季节性分布的关系。结果表明：（1）海拔对竹林基径、株高有显著影响（p0.05）;整齐度、均匀度、基径和株高分布的偏度值和峰度值均随海拔变化而变化。（2）海拔对主食竹营养含量的显著影响随季节而变化（春季粗蛋白和总糖p=0.02;夏季粗纤维p=0.01;秋季粗蛋白p=0.04、粗纤维p=0.04和总糖p0.01）。每个竹种在叶、枝、杆三个部位间的营养均有显著性差异（p0.05）。（3）海拔对竹林结构及营养的显著影响决定了大熊猫对主食竹的取食策略,夏季在高海拔活动,其余季节在低海拔活动。本文的研究结果对理解海拔、主食竹结构、营养以及大熊猫迁移活动之间的关系有重要作用,为圈养大熊猫的饲料配比提供理论依据,也为野外大熊猫的保护和规范保护区内部的人类活动提供科学支撑。     

A study on giant panda recognition based on images of a large proportion of captive pandas

1. As a highly endangered species, the giant panda (panda) has attracted significant attention in the past decades. Considerable efforts have been put on panda conservation and reproduction, offering the promising outcome of maintaining the population size of pandas. To evaluate the effectiveness of conservation and management strategies, recognizing individual pandas is critical. However, it remains a challenging task because the existing methods, such as traditional tracking method, discrimination method based on footprint identification, and molecular biology method, are invasive, inaccurate, expensive, or challenging to perform. The advances of imaging technologies have led to the wide applications of digital images and videos in panda conservation and management, which makes it possible for individual panda recognition in a noninvasive manner by using image‐based panda face recognition method.
2. In recent years, deep learning has achieved great success in the field of computer vision and pattern recognition. For panda face recognition, a fully automatic deep learning algorithm which consists of a sequence of deep neural networks (DNNs) used for panda face detection, segmentation, alignment, and identity prediction is developed in this study. To develop and evaluate the algorithm, the largest panda image dataset containing 6,441 images from 218 different pandas, which is 39.78% of captive pandas in the world, is established.
3. The algorithm achieved 96.27% accuracy in panda recognition and 100% accuracy in detection.
4. This study shows that panda faces can be used for panda recognition. It enables the use of the cameras installed in their habitat for monitoring their population and behavior. This noninvasive approach is much more cost‐effective than the approaches used in the previous panda surveys.