贺兰山马麝秋季生境选择

为了更好地保护和管理贺兰山的马麝Moschus sifanicus种群,2014—2016年秋季,采用样线法和样方法对贺兰山马麝的秋季生境选择进行研究。共记录利用样方181个,对照样方75个,测定了17种生态因子。对非数值型生态因子采用拟合优度卡方检验进行分析,使用Bonferroni不等式分析马麝对其的偏好性,然后通过非参数检验Mann-Whitney U检验对利用样方与对照样方中的13种数值型生态因子进行比较,最后对数值型生态因子中差异显著的8个生态因子采用逐步判别分析。结果表明:(1)马麝偏好以青海云杉Picea crassifolia为优势乔木的山地针叶林阴坡的中坡位。(2)马麝趋向于海拔高、乔木密度高、乔木距离近、灌木密度低、人为干扰距离远、距裸岩距离远、隐蔽级高的栖息地类型。(3)差异性显著的生态因子按照贡献值大小依次为:隐蔽级、距裸岩距离、海拔、人为干扰距离、灌木密度、乔木高度、乔木距离和乔木密度,隐蔽级是影响马麝秋季生境选择最重要的生态因子。     

贺兰山同域分布岩羊和马鹿发情季节的生境选择差异

2007年和2008年9—12月,在宁夏贺兰山国家级自然保护区和内蒙古贺兰山国家级自然保护区利用痕迹检验法和直接观察法对同域分布的岩羊和马鹿发情季节生境选择进行研究。通过在选定的15条沟段里进行调查,分别测定了岩羊和马鹿的177个和154个样方的18种生态因子。结果表明,发情季节岩羊和马鹿在植被类型、地形特征、优势乔木、坡向、坡位、灌木密度、灌木高度、植被盖度、坡度、海拔高度、距水源距离、人为干扰距离、距裸岩距离和隐蔽级等生态因子选择上存在极显著差异(P0.01),乔木高度存在显著差异(P0.05),而其余生态因子无显著差异(P0.05),相对于马鹿选择的生境而言,岩羊发情季节更偏爱选择地势陡峭的山地疏林草原带,优势乔木以较高的灰榆为主,灌木密度低但高度较高,植被盖度较低,坡度较大的阳坡中上部,海拔较低,接近水源和裸岩,隐蔽程度低的生境。典则系数显示发情季节岩羊和马鹿的生境选择几乎完全分离,Wilk’sλ值也显示发情季节岩羊和马鹿的生境选择具有很高的差异性(Wilk’sλ=0.123,χ2=679.172,df=10,P0.001)。发情季节岩羊和马鹿的Fisher线性判别函数分别为:F岩羊=3.638×乔木高度+0.242×乔木距离+7.766×灌木高度+0.663×灌木距离+0.232×植被盖度+0.191×坡度+0.001×距水源距离+0.008×距裸岩距离+0.307×隐蔽级-31.078;F马鹿=4.850×乔木高度+0.321×乔木距离+12.024×灌木高度+0.929×灌木距离+0.192×植被盖度+0.482×坡度+0.002×距水源距离-0.001×人为干扰距离-0.003×距裸岩距离+0.511×隐蔽级-50.787。逐步判别分析表明在区分发情季节岩羊和马鹿生境方面有一系列生态因子发挥作用,依照贡献值的大小依次为坡度、人为干扰距离、隐蔽级、距裸岩距离、乔木高度、乔木距离、距水源距离、灌木高度、灌木距离和植被盖度,由这10个变量构成的方程对发情季节岩羊和马鹿生境的正确区分率达到99.7%。     

贺兰山马鹿冬春季生境的选择

2007年12月～2008年1月和2008年4～5月,在贺兰山利用痕迹检验法和直接观察法对马鹿阿拉善亚种冬春季生境选择进行研究.通过在选定的15条沟段里进行调查,冬春季各测定了131个和181个样方的18种生态因子.结果表明,冬春季贺兰山马鹿在植被类型、优势乔木、灌木密度、灌木高度、灌木距离、坡向、坡位、海拔高度、距裸岩距离和隐蔽级10种生态因子上差异极显著(P ＜ 0.001),其余生态因子无显著差异(P ＜ 0.05),相对于冬季生境而言,马鹿春季更偏爱选择以油松和青海云杉为优势乔木的山地针叶林带,灌木密度大、高度高、距离近,半阴半阳坡的中坡位,海拔较高,距裸岩较近,隐蔽程度高的生境.典则判别系数显示冬春季马鹿在生境选择上存在一定程度的重叠,但春季马鹿的分布范围要比冬季更广一些,Wilk's λ值显示冬春季马鹿的生境选择具有较高的差异性(Wilk's λ = 0.683,x2 = 116.995,df = 13,P ＜ 0.001).逐步判别分析表明在区分冬春季马鹿生境方面有一系列生态因子发挥作用,依照贡献值的大小依次为:乔木密度、灌木距离、坡度、海拔高度、距水源距离、距裸岩距离和隐蔽级,由这7个变量构成的方程对冬春季马鹿生境的正确区分率达到79.9%,其中对春季的误判率为22.1%,对冬季的误判率为20.6%.     

桃红岭国家级自然保护区梅花鹿和野猪秋季生境选择差异

于2012年10—12月在桃红岭国家级自然保护区采用随机样方法调查了梅花鹿和野猪的生境选择。结果表明:梅花鹿秋季频繁在高海拔(365.5 m±141.7 m)、坡度平缓(17.80°±12.68°)、阳坡、上坡位空间活动,选择高度为0.81 m±0.36 m的灌丛或草丛,灌木高度较高(4.70 m±1.68 m)、密度较小(7.56棵±4.55棵)的生境活动,对乔木直径、郁闭度和覆盖度3个生态因子表现为随机选择;野猪则选择灌林木生境,对其余的生态因子表现为随机选择。逐步判别分析结果显示,坡度、海拔和灌木密度3个变量导致了梅花鹿与野猪之间的生境分离(Wilk'sλ=0.801,x2=24.89,df=3,P<0.001),判别函数方程:F=0.653×坡度-0.546×海拔+0.840×灌木密度+0.144,正确判别率达82.4%。     

陕西黄龙山林区褐马鸡春季觅食地选择

2006年4～5月,在陕西黄龙山林区采用样带法对褐马鸡(Crossoptilon mantchuricum)春季觅食地选择进行了研究.共测定了9条样带上的54个随机样方和54个栖息地利用样方的20个生态因子.结果表明,褐马鸡春季觅食期间偏好利用针阔混交林,避免针叶林和阔叶林;偏向于下坡位,避免上坡位和中坡位;偏向于中等坡度的山坡(10～20°),避免坡度较大和较小的山坡;对坡向没有明显的选择性.对利用样方和随机样方进行比较,发现利用样方具有海拔较低、与林间小路和水源较近、乔木种类较少、乔木密度较小、乔木最大胸径较大、乔木最大高度较高、灌木种类较少、灌木密度较小、食物丰富度较大、灌木层植物盖度较小、乔木层植物盖度较大、隐蔽级较小等特征.逐步判别分析表明,乔木密度、与水源距离、灌木密度、灌木种类、乔木最大高度、海拔具有重要作用,由这6个变量构成的方程在对繁殖季节觅食地利用样方和对照样方进行区分时,正确判别率可以达到97.22%.褐马鸡春季觅食地选择主要与食物条件、隐蔽条件和水源有关.     

四川唐家河自然保护区黑腹绒鼠对夏季生境的选择

为揭示影响黑腹绒鼠夏季空间分布的生态因素,采用样线法和样方取样法,于2009年6～8月在四川省唐家河国家级自然保护区对该物种夏季生境选择进行了研究.野外工作期间,共调查生境样方和对照样方各58个.在21个生境变量中,海拔、坡度、坡向等16个变量在生境样方和对照样方间存在显著差异,表明该地黑腹绒鼠对夏季生境的利用具有明显的选择性.该地黑腹绒鼠夏季频繁出现的生境为:坡向朝南,偏好选择处于较早植被演替阶段,海拔较低,乔木和竹子较矮,离水源较近,乔木层郁闭度、乔木胸径、竹子盖度、竹子密度和落叶层盖度较小,而草本层较高,草本盖度、密度及灌木密度均较大.Logistic回归分析表明坡向和草本盖度是影响该地黑腹绒鼠夏季生境选择的主要生态因子,可能反映了来自食物丰富度和捕食两方面的选择压力决定着该物种空间分布.在此基础上构建了黑腹绒鼠夏季生境资源选择函数logit(P)=8.027+2.792×草本盖度+0.325×坡向,其对生境的选择概率为P=elogit(P)/(1+elogit(P)),可用于预测夏季黑腹绒鼠在该保护区内的空间分布.     

贺兰山蓝马鸡越冬期栖息地的选择

2003年11～12月,在贺兰山采用样带法对蓝马鸡(Crossoptilon auritum)的栖息地选择进行了研究。共测定了25条样带上的62个蓝马鸡栖息地利用样方和50个任意样方的13个生态因子,结果表明,蓝马鸡偏好利用山地针叶林带,避免选择山地草原带、山地疏林草原带、亚高山灌丛和草甸带;偏好利用油松和青海云杉占优势的生境,避免选择山杨、杜松占优势和无树的生境;偏好阳坡和阴坡,避免利用半阳坡和半阴坡。对利用样方和任意样方进行Mann—Whitey U检验,发现利用样方以乔木密度高、灌木密度高、坡度大、隐蔽程度高、雪覆盖浅、高海拔为主要特征。逐步判别分析表明,隐蔽级、灌木密度、乔木密度、距水源距离和坡度具有重要作用,由这5个变量构成的方程对利用样方和任意样方进行正确区分的概率达到91．7％。蓝马鸡的栖息地选择主要与食物条件和隐蔽性有关。     

贺兰山区马鹿对冬季生境的选择性

2003年11—12月,在贺兰山采用样带法对马鹿阿拉善亚种的生境选择性做了研究。在选定的25条样带上一共测定了87个利用样方以及50个任意样方的14种生态因子(植被类型、优势乔木、坡向、坡位、食物丰富度、乔木密度、灌木密度、坡度、海拔高度、雪深、水源距离、人为干扰距离、裸岩距离和隐蔽级)。结果表明,马鹿对4种生态因子有选择性：①植被类型：偏好利用山地草原带和山地针叶林带,避免选择亚高山灌丛和草甸带;②优势乔木：偏好利用混合型的生境,避免选择杜松、油松和无树的生境;③坡向：偏好位于阳坡的生境,避免利用阴坡;④坡位：偏好位于下坡位的生境,避免选择上坡位和中坡位。对利用样方和任意样方进行比较,发现马鹿的利用样方以灌木密度高、食物丰富、坡度小、接近水源、雪覆盖浅、远离裸岩和人为干扰为主要特征。对各种生态因子的主成分分析表明前6个主成分的累积贡献率已经达到了84．89％,可以较好地反映马鹿的生境特征。第1主成分反映出马鹿在选择生态因子方面与植被类型、乔木密度、灌木密度、坡向、坡度、距水源距离、雪深、海拔高度正相关。     

内蒙古贺兰山国家级自然保护区荒漠沙蜥春秋季生境选择

为更好的了解及保护荒漠沙蜥(Phrynocephalus przewalskii)资源,于2017年5—6月和9—10月,在内蒙古贺兰山国家级自然保护区采用样线调查法对其春、秋2季的生境选择进行研究。春季测定了92个荒漠沙蜥生境利用样方和64个对照样方、秋季测定了71个荒漠沙蜥生境利用样方和76个对照样方的共13种生态因子。利用拟合优度卡方检验、VanderploegScavia′s选择指数、 Mann-White U检验和逐步判别分析确定影响其春秋季生境选择的关键因子。结果表明,荒漠沙蜥的生境选择存在季节性差异。春季一般选择食物丰富度高,隐蔽性好,光照强,地表温度高、湿度低的生境,既保证安全因素又利于达到最适体温,满足繁殖需求;秋季偏好选择土壤质地疏松,食物丰富度高和中的草甸地区,便于隐蔽及累积食物,以满足其躲避天敌、储存越冬能量的需要。     

四川铁布梅花鹿自然保护区梅花鹿夏季栖息地选择

四川梅花鹿Cervus nippon sichuanicus为国家Ⅰ级重点保护动物,四川铁布梅花鹿自然保护区分布有我国现存最大的梅花鹿野生种群。2011年6-9月,采用样方法对保护区梅花鹿夏季栖息地选择进行了调查,共布设109个样方(利用样方61个,对照样方48个),测量并比较了海拔、坡度等20个生境因子。结果显示,梅花鹿偏好利用的植被类型为灌丛、草甸、针叶林,同时选择隐蔽度较高的生境;此外,距水源距离、灌木高度、灌木盖度、灌木密度、草本高度和草本盖度6个连续变量在利用样方和对照样方之间差异有统计学意义(F<0.05或U<0.05)。回归模型分析结果表明,梅花鹿夏季偏好选择草本盖度大、靠近水源和林缘的生境,回避远离水源和林缘的生境。     

Resource dispersion and badger population density in Mediterranean woodlands: is food,water or geology the limiting factor?

Eurasian badgers, Meles meles, in Mediterranean cork‐oak woodlands live in small groups within territories that embrace a mosaic of habitats where several setts (dens) are scattered. Assuming that their population density was related to home range sizes and that this in turn was influenced by food and water availability and the existence of substrate suitable for sett construction, we explored the relationship between these parameters. Two biotopes were predominantly important in providing food security to badgers in the ‘Grândola’ mountain study area: olive groves and orchards or vegetable gardens. Analysis of the mean total area of these two habitats in the ranges of radio‐tracked badgers permitted us to extrapolate to an estimate that the 66 km² encompassed eleven areas with the capacity to support badger groups each composed by 6–8 individuals. Since only three groups populated the area we concluded that food availability was not limiting badger density. Sites with surface water in summer (the dry season) seem sufficient to support more badger groups than existed, leading us to believe that this factor was also not limiting badger density. Simultaneously, using a logistic regression model and the biophysical characteristics of sett sites as explanatory variables, four predictor variables determined sett location: the existence of a geological fault/discontinuity, ridges, valleys and the distance to abandoned farm houses, of which the former had the higher odds ratio, being thus the best sett location predictor. Indeed, 56% of the areas predicted with >80% confidence to contain a badger sett were encompassed within a known home range. Therefore, our results suggest that, in Mediterranean cork oak woodlands in SW Portugal, the main factor limiting badger's density is the availability of suitable sites for setts. However, in areas where suitable sites for burrows existed, but food patches were absent, badgers were not found. This could indicate that the presence of both factors was necessary for badgers, although in this area sites suitable for digging setts appeared to be the primary limiting factor.     

张广才岭藏獾洞穴生境选择

2008年9月至2009年8月,在黑龙江省方正林业局新风林场,用不定宽样线法对藏獾洞穴生境选择进行研究,共记录了55组藏獾洞穴,藏獾洞口平均直径为(27.40±7.15)cm,洞深平均为(84.18±22.04)cm,倾角平均为(26.36±9.10)°,洞口总数=3.02个常用洞数+0.80个不常用洞数+0.56个废弃洞数。相对于对照样方而言,藏獾洞穴更偏爱选择位于郁闭度和植被盖度小,灌木密度大、距离近,乔木距离远,距水源和农田近、人为干扰距离远,坡度较缓的向阳中坡位的生境。资源选择函数模型为:logit(p)=246.980-1.059×植被盖度-0.703×距水源距离-1.403×坡度-45.005×坡向,模型的正确预测率为93.9%。     

The distribution of Eurasian badger, Meles meles, setts in a high-density area: field observations contradict the sett dispersion hypothesis

Are setts significant determinants of badger socio‐spatial organisation, and do suitable sett sites represent a limited resource, potentially affecting badger distributions? The factors determining diurnal resting den, or sett, location and selection by Eurasian badgers Meles meles L. were investigated in Wytham Woods, Oxfordshire. 279 sett sites were located. The habitat parameters that were associated with the siting of these setts were analysed and associations were sought between sett location and character and the body condition and body weight of resident badgers Habitat characteristics in the vicinity of setts were significantly different from randomly selected points. Badgers preferentially selected sites with sandy, well‐drained soils, situated on NW‐facing, convex and moderately inclined slopes at moderate altitude. There was no evidence that sett morphology (number of entrances, sett area, number of hinterland latrines) was affected by the surrounding sett site habitat characteristics. Mean body weight was significantly higher for badgers occupying territories with setts in sandy soils, situated on NW‐facing slopes, than in territories with less optimal sett characteristics. Contrary to the hypothesis that the availability of sett sites was limiting, and therefore that sett dispersion dictates the spatial and social organisation of their populations, the badgers were clearly able to excavate new setts. On our measures, these new setts were not inferior to old established ones, despite occupying subsequently exploited sites; the badgers utilising these new setts had neither lighter body weights nor poorer body condition scores. During the period of our study badgers have manifestly been able to dig numerous new setts; as satisfactory sites still remain available, this indicates that suitable sett sites have not yet become a limiting resource. There was no relationship between sett age and the characteristics of the site in which it was dug, as suitable sites were not limiting. Significantly, population expansion during the decade 1987–1997 was not constrained by lack of setts, rather the main proliferation in setts occurred after the population size had peaked in 1996. Some implications for the management and conservation of the Eurasian badger are considered.     

Antibodies to Toxoplasma gondii in Eurasian badgers

Antibodies to Toxoplasma gondii were detected in samples collected from 90 live-trapped adult Eurasian badgers (Meles meles) sampled at three sites (two agricultural and one woodland) in southern England. Serum was tested using a qualitative latex agglutination test procedure and 63 of 90 (70%) badgers tested positive for T. gondii antibodies. Antibody prevalence varied between the sites; 67% and 77% of badgers from agricultural sites and 39% from a nonagricultural site tested positive.     

Mitochondrial DNA reveals a strong phylogeographic structure in the badger across Eurasia

The badger, Meles meles, is a widely distributed mustelid in Eurasia and shows large geographic variability in morphological characters whose evolutionary significance is unclear and needs to be contrasted with molecular data. We sequenced 512 bp of the mitochondrial DNA control region in 115 Eurasian badgers from 21 countries in order to test for the existence of structuring in their phylogeography, to describe the genetic relationships among their populations across its widespread geographic range, and to infer demographic and biogeographic processes. We found that the Eurasian badger is divided into four groups regarding their mitochondrial DNA: Europe, Southwest Asia, North and East Asia, and Japan. This result suggests that the separation of badgers into phylogeographic groups was influenced by cold Pleistocene glacial stages and permafrost boundaries in Eurasia, and by geographic barriers, such as mountains and deserts. Genetic variation within phylogeographic groups based on distances assuming the Tamura-Nei model with rate heterogeneity and invariable sites (d(T-N) range: 3.3-4.2) was much lower than among them (d(T-N) range: 10.7-38.0), and 80% of the variation could be attributed to differences among regions. Spatial analysis of molecular variance (samova), median-joining network, and Mantel test did not detect genetic structuring within any of the phylogeographic groups with the exception of Europe, where 50% of variation was explained by differences among groups of populations. Our data suggest that the European, Southwest Asian, and North and East Asian badgers evolved separately since the end of Pliocene, at the beginnings of glacial ages, whereas Japanese badgers separated from continental Asian badgers during the middle Pleistocene. Endangered badgers from Crete Island, classified as Meles meles arcalus subspecies, were closely related to badgers from Southwest Asia. We also detected sudden demographic growth in European and Southwest Asian badgers that occurred during the Middle Pleistocene.     

Use of human buildings by Eurasian badgers in the Moravskoslezské Beskydy Mountains,Czech Republic

An inspection of human buildings used by Eurasian badgersMeles meles (Linnaeus, 1758) in 28 sites in the Moravskoslezské Beskydy Mountains, Czech Republic, was carried out in 2001. The buildings inhabited or visited by badgers were as follows: wooden barns (18 cases), masonry buildings used for residential purposes (4), abandoned buildings (1), wooden sheds (2), wooden beehouses (2) and a non-residential part of a house (1). In three sites, female badgers with their cubs inhabited buildings. Badgers use the buildings more frequently in winter than in summer. Use of human buildings and the occurrence of badgers in setts in the wild in these mountains was observed in detail on a study area of 950 ha around the village of Lubno. In total, 12 setts were discovered. Eight of them were in the wild: two setts were located closer than 50 m, five between 100 m and 300 m, and one 700 m from human buildings. In four sites badgers inhabited human buildings.     

Spatial Targeting for Bovine Tuberculosis Control: Can the Locations of Infected Cattle Be Used to Find Infected Badgers?

Bovine tuberculosis is a disease of historical importance to human health in the UK that remains a major animal health and economic issue. Control of the disease in cattle is complicated by the presence of a reservoir species, the Eurasian badger. In spite of uncertainty in the degree to which cattle disease results from transmission from badgers, and opposition from environmental groups, culling of badgers has been licenced in two large areas in England. Methods to limit culls to smaller areas that target badgers infected with TB whilst minimising the number of uninfected badgers culled is therefore of considerable interest. Here, we use historical data from a large-scale field trial of badger culling to assess two alternative hypothetical methods of targeting TB-infected badgers based on the distribution of cattle TB incidents: (i) a simple circular ‘ring cull’; and (ii) geographic profiling, a novel technique for spatial targeting of infectious disease control that predicts the locations of sources of infection based on the distribution of linked cases. Our results showed that both methods required coverage of very large areas to ensure a substantial proportion of infected badgers were removed, and would result in many uninfected badgers being culled. Geographic profiling, which accounts for clustering of infections in badger and cattle populations, produced a small but non-significant increase in the proportion of setts with TB-infected compared to uninfected badgers included in a cull. It also provided no overall improvement at targeting setts with infected badgers compared to the ring cull. Cattle TB incidents in this study were therefore insufficiently clustered around TB-infected badger setts to design an efficient spatially targeted cull; and this analysis provided no evidence to support a move towards spatially targeted badger culling policies for bovine TB control.     

Genetic evidence that culling increases badger movement: implications for the spread of bovine tuberculosis

The Eurasian badger (Meles meles) has been implicated in the transmission of bovine tuberculosis (TB, caused by Mycobacterium bovis) to cattle. However, evidence suggests that attempts to reduce the spread of TB among cattle in Britain by culling badgers have mixed effects. A large-scale field experiment (the randomized badger culling trial, RBCT) showed that widespread proactive badger culling reduced the incidence of TB in cattle within culled areas but that TB incidence increased in adjoining areas. Additionally, localized reactive badger culling increased the incidence of TB in cattle. It has been suggested that culling-induced perturbation of badger social structure may increase individual movements and elevate the risk of disease transmission between badgers and cattle. Field studies support this hypothesis, by demonstrating increases in badger group ranges and the prevalence of TB infection in badgers following culling. However, more evidence on the effect of culling on badger movements is needed in order to predict the epidemiological consequences of this control strategy. Here, analysis of the genetic signatures of badger populations in the RBCT revealed increased dispersal following culling. While standard tests provided evidence for greater dispersal after culling, a novel method indicated that this was due to medium- and long-distance dispersal, in addition to previously reported increases in home-range size. Our results also indicated that, on average, badgers infected with M. bovis moved significantly farther than did uninfected badgers. A disease control strategy that included culling would need to take account of the potentially negative epidemiological consequences of increased badger dispersal.     

Distribution and population density of badgers Meles meles in Luxembourg

1. The distribution and density of Eurasian badgers Meles meles in Luxembourg was estimated by gathering information about the location of badger setts with a questionnaire survey, by visiting 708 setts in order to classify them as ‘main setts’ or ‘outliers’, and by estimating social group size by directly counting emerging badgers. 2. Badgers were found to be widely distributed in Luxembourg, with a minimum main sett density of 0.17 setts/km². Setts were sited preferentially in forest habitat. The mean minimum group size was 4.6 badgers. 3. The Luxembourg badger population was conservatively estimated to contain at least 2010 adult and young badgers (95% CI 1674–2347) in spring 2002, equivalent to a density of 0.78 adult and young badgers/km² (95% CI 0.65–0.91). This is moderate compared to most of continental Europe.