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%。     

四川西部石渠地区夏季藏狐巢穴选择的生境分析

通过对四川石渠地区夏季藏狐洞穴生境选择的研究 ,以水源距离、洞口朝向、坡向、坡度、坡位、植被类型及鼠兔和鼠类洞穴等 7项指标为变量 ,运用主成分分析和聚类分析相结合的方法对收集到的 5 4个藏狐洞穴样本进行了分析。主成分分析在 4个主成分下达到 85 %的显著性。在第一主成分中水源距离、坡度和坡位是重要的影响变量 ,在另外 3个主成分中鼠类洞穴数量以及植被类型两变量也非常重要。聚类分析显示 ,5 4个洞穴样本在 3个水平上聚成 5类。藏狐易于选择草甸地带 ,中缓坡和低坡位 ,坡向多为阳坡或半阳坡 ,水源距离小于5 0 0m的地方筑巢 ,其穴口朝向多位于 135°～ 36 0°之间。此外 ,鼠兔和鼠类洞穴在藏狐洞穴样方内的出现 ,但数量变异较大 ,揭示小型哺乳动物和藏狐之间可能存在着复杂的相互关系。通过对四川石渠地区夏季藏狐洞穴生境选择的研究 ,以水源距离、洞口朝向、坡向、坡度、坡位、植被类型及鼠兔和鼠类洞穴等 7项指标为变量 ,运用主成分分析和聚类分析相结合的方法对收集到的 5 4个藏狐洞穴样本进行了分析。主成分分析在 4个主成分下达到 85 %的显著性。在第一主成分中水源距离、坡度和坡位是重要的影响变量 ,在另外 3个主成分中鼠类洞穴数量以及植被类型两变量也非常重要。聚类分析显示 ,5 4     

基于红外相机数据的贵州高原山地环境野猪生境选择研究

近年来野猪(Sus scrofa)在我国南方山地森林生态系统中种群数量激增、生态影响强烈,是人兽冲突的典型代表,然而对其生境选择规律仍缺乏深入研究。利用2015年7月至2020年1月的长时红外相机监测数据,对贵州高原几处环境中野猪的生境选择进行了研究,共得到野猪利用样方201个,非利用样方121个。(1)Vanderploeg和Scavia选择指数分析表明,野猪喜爱活动于坡度≤20°、乔木郁闭度>0.8和草本盖度为0.2—0.4的生境类型;不喜爱的生境类型为海拔>1600 m,坡度>25°,草本盖度<0.1,距道路距离≤100 m。(2)野猪生境资源选择函数为Logit(P)=3.226-海拔×0.002-坡度×0.161+乔木郁闭度×2.078+灌木平均高×0.401+草本盖度×3.566+距道路距离×0.001+距居民点距离×0.0003,选择概率为P=e⁽logit(p))/(1+e⁽logit(p))),受试者工作特征曲线(ROC)评估模型的预测精度为87.8%,能够较好预测野猪的生境选择。(3)利用Mann-...     

狼洞穴空间格局及生境选择的分析

内蒙古东部草原地区狼洞穴空间分布格局及其生境选择的聚类分析结果表明,影响狼洞穴分布的主要因子为人类活动干扰和水源距离,其次为隐蔽条件、坡位和坡度,狼选择洞穴的最适生境为陡坡,洞口北向,隐蔽条件中等以上,距人为干扰大于１０００ｍ和距水源小于１０００ｍ的地方     

甘肃兴隆山保护区野生马麝的冬季卧息地生境特征

生境是野生动物的栖息基底,卧息地是野生动物重要的功能性生境。为深入了解野生马麝（Moschus chrysogaster）冬季卧息地生境的特征及选择利用,于2021年12月至2022年1月对甘肃兴隆山国家级自然保护区的野生马麝的功能性生境开展了基于生境取样的研究。通过样线调查法获取马麝卧息痕迹位点,采用主成分分析和资源选择函数法进行其卧息生境选择的研究。结果表明,野生马麝冬季卧息地生境的海拔较低[（2 488.5±26.6）m]、灌木较高[（1.3±0.3）m]、灌木盖度（31.08%±3.14%）和地表植被盖度（38.36%±3.27%）较大、倒木较多[（0.5±0.1）个]且积雪较浅[（1.0±0.3）cm];马麝冬季卧息地多选择位于南坡的下坡位灌丛生境,而且距水源较近、隐蔽度较好。主成分分析表明,乔木因子、食物因子、安全因子和地形因子的累计贡献率达67%;马麝的卧息生境资源选择函数为：Logit(x)=﹣4.967+0.001×海拔﹣0.02×坡度+0.03×乔木郁闭度+0.104×乔木高度+0.17×灌木盖度﹣0.466×雪被深度﹣1.015×坡向,模型预测正确率为91.1%。...     

莫莫格自然保护区白鹤秋季迁徙停歇期觅食生境选择

2008年秋季(10月8日—20日)及2009年秋季(9月20日—10月16日),通过样方法对觅食生境11个生态因子进行调查,利用卡方检验、资源选择指数和资源选择函数在莫莫格保护区对秋季迁徙停歇期白鹤觅食生境选择进行研究。结果表明,白鹤对距人为干扰源距离、植被密度、盖度、高度、植物性食物密度以及水深均具有选择性,但对宏观尺度干扰因子的选择性较低。其偏好觅食生境的特点为:距一级路>5000m,>二级路1500m以上,>三级路1000m以上,>居民点1000m以上,农田>1000m;植被密度20~50株/m2,盖度<10%,高度<20cm,扁杆藨草密度1~50株/m2,藨草密度1~10株/m2,水深40~60cm。白鹤秋季觅食生境资源选择函数为Logistic(P)=0.663+0.565×与一级道路距离+0.042×与二级道路距离+0.519×与三级道路距离+0.353×与居民点距离+0.169×与农田距离–0.455×植被密度–0.618×植被盖度–0.548×植被高度–0.158×扁杆藨草密度–0.404×藨草密度+0.920×水深,T(x)=eLogistic(p)/[1+eLogistic(p)],模型正确预测率为82.9%。     

阿尔金山保护区藏野驴和野牦牛夏季生境选择分析

本研究在2012至2013年进行两次调查,采用样带法和样方法在阿尔金山自然保护区东部(37°15'~37°23'N,90°11'~90°20'E)对藏野驴(Equus kiang)、野牦牛(Bos grunniens)的分布及其栖息地进行调查,共设置3条样线(总长达146.9 km)和128个样方。调查发现,藏野驴主要集中于伊协克帕提附近的荒漠草原,而野牦牛的主要栖息地位于沙山附近的阿坝堤坝草场。通过Vanderloeg和Scavia选择系数以及主成分分析,对藏野驴和野牦牛对不同环境因子(包括植被类型、植被盖度、草本种类数、土壤pH、海拔、坡度、坡向、水源)的选择性以及各因子在物种栖息地选择的重要程度进行研究,同时利用独立T检验分析两物种之间的环境变量选择差异性。结果表明,藏野驴倾向选择植被盖度小于70%,坡度2°~5°的南坡,海拔3800~4000 m,土壤pH 8.0~8.5的高寒荒漠生境;野牦牛则偏好选择植被盖度大于70%,坡度5°~15°的东坡或者北坡,海拔4200~4600 m,土壤pH 7.0~8.0,与水源距离小于1000 m的高寒荒漠草原以及沼泽草甸生境;影响藏野驴生境选择的主要因子为植被类型和坡度,而影响野牦牛生境选择的主要因子是植被盖度;虽然藏野驴和野牦牛在资源利用上存在部分重叠,但它们对栖息地植被盖度、植被高度、海拔和坡度的选择存在显著差异性(P0.05)。     

太行山东北部豹猫(Prionailurus bengalensis)秋季生境利用研究

深入了解动物的生境利用特征是对野生动物及其生境进行就地保护的前提和基础。于2019年9月15日至11月15日期间,结合红外相机陷阱技术和生境样地调查,对太行山东北部的豹猫秋季利用生境进行了对照取样。记录了生境的海拔、乔木胸径及距水源距离等20个生境变量,比较了豹猫利用生境(n=39)和非利用生境(n=141)的群落结构差异。结果表明:同非利用生境相比,太行山东北部豹猫偏好选择海拔较高(791.36±80.94) m、坡上位(53.80%)、乔木胸径较大(22.11±3.85)cm、株数较少(6.90±1.50)株、郁闭度较大(49.65%±2.60%)、灌木较高(1.31±0.11) m、灌木盖度较大(51.30%)、枯草盖度较大(18.97%±4.71%)、土壤较湿润(87.20%)、距水源距离较近(66.70%)、距社区距离较近(61.50%)和距人为干扰较近(71.80%)的生境。此外,豹猫偏好生境变量主成分分析结果表明,生境的乔木特征(乔木胸径、乔木高度和乔木郁闭度)、人为干扰(坡位、距社区距离和距干扰距离)、海拔及距水源距离是影响豹猫秋季生境利用的关键因素,反映了该区域豹猫秋...     

内蒙古达赉湖西岸地区大鵟巢穴特征和巢址选择

2010年和2011年3月-6月,对内蒙古达赉湖国家级保护区达赉湖西岸地区大鵟(Buteo hemilasius)的巢穴结构和巢址选择因子进行了调查研究.采用野外观察和样方法定位了13个大鵟巢址,并对巢址样方的20个生态因子进行测量,运用主成分分析法对影响大鵟巢址选择的主要因子进行了分析.测量显示,大鵟巢穴的基本结构特征为:外径(94.7+4.2) cm;巢高度(46.1±2.7) cm;内径(24.8±1.5)cm;巢深(14.0±+0.9)cm.生境因子分析结果表明,达赉湖西岸地区大鵟的巢集中分布在湖岸或水塘附近的悬崖,营巢点坡度为15°-45°之间的阳坡或半阳坡;隐蔽度高于20％;草本密度大于5株/m2;植被均高大于30cm;巢距悬崖上部距离2-5m;距水源l00m以内;距居民点距离大于lkm;距草原道路的距离大于0.5km;而对于物种丰富度没有特殊要求.主成分分析显示,影响大鵟巢址选择的主要因子有3个,依次为:隐蔽性因子(主要包括巢址区域的植物特征和地形特征)、干扰因子和食物因子.各主成分中,相对系数绝对值最高的变量依次是:植被盖度、距居民点距离、巢的高度和距草原道路距离.     

大兴安岭驯鹿(Rangifer tarandus)的春季生境选择

为确定分布于我国大兴安岭西北麓的濒危驯鹿(Rangifer tarandus)的春季生境选择特征,于2012和2013年的3—4月间,采用样线样方结合的生境调查方法,对内蒙根河驯鹿的春季偏好生境和对照生境进行了取样,并对样方的海拔和乔木郁闭度等23个生境变量进行了计测与分析。结果表明:与非利用样方(n=132)相比,驯鹿春季偏好生境(n=79)的海拔((957.27±1.68)m)、乔木郁闭度((32.84±2.72)%)、乔木密度(21.72±1.52)、地表植被盖度((85.06±1.03)%)、树桩数(6.81±0.45)和倒木数(5.73±0.54)均显著较大(Mann-Whitney U test,P0.05),而灌木盖度((57.95±2.79)%)、枯草盖度((33.11±2.79)%)、乔木高度((9.58±0.27)m)和灌木均高((59.85±2.69)cm)显著较小(Mann-Whitney U test,P0.05),而且驯鹿春季趋向于选择西坡和南坡(77.21%)的坡度较缓(93.67%)、位于坡中下位(67.09%)的生境,并偏好选择针叶林(68.35%)中的隐蔽度好(82.28%)、避风状况良好(64.56%)、湿润(60.76%)、距水源较近(≤1000 m,94.94%)及距人为干扰较远(≥1000m,87.34%)的生境(Chi-Square test,P0.05)。此外,驯鹿偏好生境的变量主成分分析结果表明,坡位、乔木特征(乔木胸径和乔木高度)、食物多度(灌木盖度、倒木数及树桩数)、雪被特征(雪深、雪盖度和郁闭度)、干扰强度(距人为干扰距离)、植被类型(坡向和植被类型)是影响驯鹿春季生境选择的重要因素,综合体现了驯鹿在春季对保温、食物和安全性的需求。     

Feeding habitats of blue sheep (Pseudois nayaur) during winter and spring in Helan Mountains, China

The feeding habitat selection of blue sheep (Pseudois nayaur) was studied by direct observation method in the Helan Mountains, China during winter (from November to December) and spring (from April to June) from 2003 to 2004. We established 25 line transects to collect information on feeding habitats used by blue sheep. Blue sheep in the study area preferred mountain savanna forests, a habitat dominated by Ulmus glaucescens, with medium tree density (<4 individuals / 400 m²), moderate tree height (4–6 m), higher shrub density (> 5 individuals / 100 m²), higher shrub (> 1.3 m), higher food abundance (> 50 g), moderate distance to human disturbance (< 500 m), and mild distance to bare rock (< 2 m). Such habitats characterized by 12 ecological factors were preferred as feeding areas by blue sheep during winter. Similar to habitat selection by the species during winter, blue sheep also showed a preference for mountain savanna with tree dominated by Ulmus glaucescens and medium tree density (< 4 individuals / 400 m²) during spring. Nevertheless, blue sheep preferred medium tree height (< 6 m), moderate tree density (5–10 individuals / 100 m²), medium shrub height (1.3–1.7 m), higher food abundance (> 100 g), moderate altitude (< 2 000 m), moderate distance to water resource (< 500 m), and medium hiding cover (50%–75%) during spring. Selection of the feeding habitats by sheep showed a significant difference in vegetation type, landform feature, dominant tree, tree height, shrub density, distance to the nearest shrub, food abundance, slope direction, slope degree, distance to water resource, and hiding cover between winter and spring. Results of principal components analysis indicated that the first principal component accounted for 24.493% of the total variance among feeding habitat variance during winter, with higher loadings for vegetation type, dominant tree, tree height, distance to the nearest tree, shrub density, shrub height, altitude, distance to water resource, and distance to human disturbance. In spring, the first principal components explained 28.777% of the variance, with higher loadings for vegetation type, distance to the nearest tree, shrub height, distance to the nearest shrub, food abundance, altitude, and distance to human disturbance. Translated from Zoological Research, 2005, 26(6): 580–589 [译自: 动物学研究]     

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.     

Changes in the prevalence of badger persecution in Northern Ireland

Animal populations generally increase after release from hunting pressure and/or cessation of illegal persecution. Implementation of full legislative protection of the Eurasian badger Meles meles in Great Britain is thought to have led to increases in badger abundance due to reduced levels of persecution. Conversely, prevalence of badger persecution in Northern Ireland was historically much higher than in Great Britain, and badger abundance remained stable over time despite similar legislative protection. We examined temporal changes in the prevalence of badger sett disturbance in Northern Ireland from 1990/1993 to 2007/2008 in relation to population status. A total of 56 (12.6%) of 445 setts surveyed during 1990/1993 had been disturbed compared to 29 (4.4%) of 653 setts during 2007/2008. This was a significant decline (−65%) in the incidence of sett disturbance over the 14–18-year period. Most notably, the incidence of digging at badger setts, indicative of local badger baiting activity, declined from 50% to 3.5% of disturbed setts. Signs of recent disturbance were significantly more frequent at disused setts suggesting that once disturbed, badgers may vacate a sett. The number of badger social groups in Northern Ireland did not differ between the two study periods, suggesting that previously high levels of badger persecution did not limit the number of badger social groups. The stability of the badger population in Northern Ireland compared to the growing population in Great Britain cannot be attributed to changes in the prevalence of persecution. Differences in the trajectories of both populations could be due to a range of factors including climate, habitat composition and structure, farming practices or food availability. More work is needed to determine how such factors influence badger population dynamics.     

Predicting Distribution and Density of European Badger (<Emphasis Type="Italic">Meles Meles</Emphasis>) Setts in Denmark

Predictive models of the spatial distribution and abundance of species based on habitat characteristics are finding increasing use in management and conservation. The European badger attracts interest as a model species both for conservation reasons and because of the important role the species is playing in understanding carnivore sociality. We developed a statistical habitat model based on presence/absence data on badger setts. To maximise the utility of the model in management, we limited the choice of model variables to those that had a clear basis in badger ecology and that could be obtained on a nation-wide digital format. We extrapolated the habitat model to a region in Denmark and developed a threshold-independent sett distribution algorithm to estimate sett densities. The habitat model was simpler than previously published models of badger sett habitat selection, but nevertheless had a predictive ability in excess of 80% judged against independent data. The sett distribution algorithm was able to simultaneously reproduce several observed patterns of sett density and distribution over the probability gradient. It thus represents a significant improvement over threshold-dependent methods used to discriminate between suitable and unsuitable habitat predicted by presence/absence regression models. Our approach demonstrates that a model of badger sett habitat suitability with high predictive power can be obtained using easily accessible map-variables and presence/absence data. This is a prerequisite for using habitat models as predictive tools over large areas. The use of a simple sett distribution algorithm circumvents the common problem of subjectively fixing a threshold to discriminate between suitable and unsuitable habitat. In conjunction the models presented here constitute an important contribution to the management of the badger in Denmark and, upon further validation, possibly to similar regions in Northern Europe.     

Drivers of sett site location by European badgers in Portugal

European badgers (Meles meles) are considered central-place foragers, whose spatial ecology is predominantly determined by sett location. Many studies have assessed the factors determining sett site selection throughout this species’ range, but these have often been geographically limited and have primarily identified locally dependent factors. To infer key factors determining sett location, a broader scale approach is needed. Between June 2014 and January 2017, we surveyed mainland Portugal to detect badger setts in 10?×?10 km cells, corresponding to a total of 657.5 km walked line transects. We detected 54 main setts in 136 surveyed cells. Each sett and non-sett site (i.e. transects without setts) was characterised using bioenvironmental variables (e.g. land cover, presence of human infrastructure, soil). We used generalized linear mixed models to test five hypotheses potentially explaining sett location: land cover composition; anthropogenic disturbance; abiotic environmental drivers; trophic resource availability; and a combined effect of all these factors. Our findings show that the key factors for badger sett site selection in Portugal are: (1) disturbance avoidance (low beehive density; absence of livestock; far from hunting reserves), but with a tendency to be located close to highways and unpaved roads; and (2) ease of excavation (avoidance of sedimentary/metamorphic composite rocks). Although specific factors among these drivers may be more important locally or regionally, these major drivers have also been identified elsewhere in Europe. Our nationwide approach contributes to a broader understanding of general patterns of sett site selection by badgers in southern Europe. Furthermore, it provides the national authorities with novel and broad-scale data to facilitate sustainable species conservation of badgers in the southwestern limit of their range.     

江西官山自然保护区四种雉类的生境选择差异

2009年10月—2010年11月在江西官山国家级自然保护区对白颈长尾雉、白鹇、勺鸡和灰胸竹鸡4种雉类的生境选择进行了研究:共调查了6条样线上的388个样方,选取了与这四种雉类栖息地相关的17个生态因子进行观测和测量。结果显示,4种雉类均偏好阔叶林和针阔混交林、阳坡或半阴半阳坡的生境。Kruskal-Wallistest检验表明,4种雉类在海拔、坡度、乔木盖度、灌木盖度、灌木数量、灌木高度、草本盖度、草本种类、草本数量、落叶层盖度和水源距离11个生态因子上存在极显著差异(P<0.01),乔木种类存在显著差异(P<0.05),其余生态因子无显著差异(P>0.05)。典则判别函数图显示,4种雉类在生境选择上存在一定程度的重叠,又有比较明显的差异。逐步判别表明在区分4种雉类生境选择差异方面有一系列的生态因子发挥作用,依照贡献值的大小依次为海拔、草本数量、灌木高度、水源距离、灌木盖度、乔木盖度、坡度、落叶层盖度、灌木数量、草本盖度。由这10个变量构成的方程对4种雉类生境选择差异的正确区分率为74.7%。     

The density and distribution of badger setts in the Sudety Mountains,Poland

The density and distribution of badgerMeles meles (Linnaeus, 1758) setts was estimated by questionnaires and field studies, carried out in the Sudety Mountains between 1995–2002. The questionnaire referred to the whole territory of Polish Sudety Mts, while field studies were conducted in four different habitat types: low mountains with a mosaic farm-forest landscape, highly industrialised hilly areas, high mountain ranges of natural character and high mountain ranges of severe microclimate and heavily destroyed tree stands. On the basis of both questionnaires and field surveys, a total of 378 badger setts, classified according to their size and status, were identified. Among these, 119 (31.5%) were situated on three areas, while in the fourth area we did not find any badger setts. According to their size and traces of intensive occupation, 54 setts were regarded as main badger setts. The mean density of main setts on three areas was much the same and amounted to 0.05–0.07/km² of their total surface, despite differences in their natural environment and agricultural or industrial changes in landscapes. In the Sudety Mts badgers selected settlements in forest habitats, bordering rich in food open areas. The density of main setts in forest areas ranged from 0.12 to 0.33/km² depending on the proportion of forest, type and age of tree stands and size of forest complexes. The mean distance of main setts from open areas ranged from 209 to 280 m. The mean nearest neighbour distance (NND) between main setts ranged from 2.85 to 3.75 km. The home range size estimated for a social group varied from 7.9 to 13.6 km². The highest occupied setts of our study were found on the ?nie?nik Massif, at an altitude of 700 m a.s.l.     

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.     

贺兰山马鹿冬季取食和卧息生境选择

2007 年12 月至2008 年1 月,在贺兰山地区,利用痕迹检验法和直接观察法对马鹿阿拉善亚种的冬季取食和卧息生境选择进行研究。通过在选定的15 条沟段里进行调查,共测定了72 个取食利用样方,59 个卧息利用样方和131 个对照样方的18 种生态因子。结果表明,马鹿在冬季偏好的取食地为平滑起伏坡,以酸枣、柳为优势乔木、混合型树林或空地,乔木高大稀疏、间距较远,灌木密度大,草本盖度较高,位于< 15°的半阴半阳坡的下坡位,距裸岩远,隐蔽度高;偏好的卧息地在山地疏林草原带的平滑起伏坡上,以酸枣、柳为优势乔木、混合型树林或空地,乔木高大稀疏,灌木矮小、稀疏且距离较远,草本盖度较高,位于< 15°阳坡的下坡位,远离裸岩,隐蔽程度高。马鹿冬季的取食和卧息生境在草本盖度和隐蔽度上差异极显著。相对于卧息生境,马鹿冬季的取食生境对草本盖度和隐蔽度要求更低一些。马鹿冬季取食地的资源选择函数为1.155 - 0.149 × 乔木高度- 0.066 × 草本盖度+ 0.190 × 坡度,模型的正确判别率为86.8% ;马鹿冬季卧息地的资源选择函数为- 30.936
+ 0.494 × 乔木高度+ 0.257 × 坡度-0.002 × 海拔高度+ 0.387 × 隐蔽度,模型的正确判别率为95.8% 。食物、隐蔽条件以及贺兰山的独特地形特征是影响马鹿冬季取食和卧息生境选择的主要因素。     

Using the Mahalanobis distance statistic with unplanned presence-only survey data for biogeographical models of species distribution and abundance: a case study of badger setts

Aim Project‐specific data for biogeographical models are often logistically impractical to collect, forcing the use of existing data from a variety of sources. Use of these data is complicated when neither absence nor an estimate of the area sampled is available, as these are requirements of most analytical techniques. We demonstrate the Mahalanobis distance statistic (D²), which is a presence‐only modelling technique and does not require information on species absence or the sampled area. We use badger (Meles meles) setts as the basis for this investigation, as their landscape associations are well understood, and survey data exist against which to compare estimates of sett distribution and abundance. Location  England and Wales (151,403 km²). Methods We used stratified random samples of sett locations, and landscape variables that are known to be important for choice of badger sett location within a geographic information system at a cell resolution of 100 × 100 m. Landscape conditions at two scales were extracted, at and around sett locations, and the D² was used to classify all cells in England and Wales into a sett suitability model. Comparison of this sett suitability model with known main sett densities allowed estimates of main sett density to be made across England and Wales, with associated uncertainty. Results The sett suitability model was shown through iterative sampling and model evaluation using independent data to be stable and accurate. Main sett density estimates were biologically plausible in comparison with previous field‐derived estimates. We estimate 58,000 main setts within England and Wales, with 95% confidence intervals suggesting a value between 31,000 and 93,000. Main conclusions The D², which could be applied to other species and locations, proved useful in our context, where absence data were not available and the sampled area could not be reliably established. We were able to predict sett suitability across a large area and at a fine resolution, and to generate plausible estimates of main sett density. The final model provides valuable information on probable badger sett distribution and abundance, and may contribute to future research on the spatial ecology of badgers in England and Wales.