河南内乡宝天曼国家级自然保护区豹猫及其潜在猎物之间日活动节律的季节性

日活动节律是动物应对食物可利用性、天敌捕食风险和环境条件等变化的适应性特征。阐明捕食者与猎物之间的日活动节律以及相关影响因素, 对于理解不同物种的生存策略、指导保护对策至关重要。然而, 由于采样方法的限制和人类干扰下的快速环境变化, 人们对许多野生动物日活动节律的了解并不全面, 甚至与实际情况存在偏差。以往认为夜行性的豹猫(Prionailurus bengalensis)被发现有一定程度的日间活动, 并增加晨昏活动, 这说明有必要深入调查豹猫等野生动物的昼夜节律为何存在这些变化。本研究在河南内乡宝天曼国家级自然保护区通过红外相机技术对豹猫及其潜在猎物进行调查, 基于核密度函数比较分析了豹猫与其潜在猎物在冷、暖季节的日活动节律。2016年全年设置了55个红外相机位点, 累计14,972个相机工作日, 获得豹猫及其潜在猎物的独立有效照片1,343张。结果显示, 该保护区内豹猫、蒙古兔(Lepus tolai)和鼠类以夜间活动为主, 其中豹猫有明显的晨昏活动高峰, 而赤腹松鼠(Callosciurus erythraeus)、岩松鼠(Sciurotamias davidianus)、红腹锦鸡(Chrysolophus pictus)和勺鸡(Pucrasia macrolopha)均在昼间活动。活动重叠度分析结果显示, 豹猫与夜行性的蒙古兔和鼠类在冷季和暖季均有较高重叠度(Δ ≥ 0.50), 但与其他猎物之间的重叠度均相对较低(Δ ≤ 0.40)。本研究显示豹猫及其猎物的昼夜节律既有保守性, 也具有一定的季节可塑性, 可能受到季节性猎物分布和环境变化的影响。因此, 需要加强调查研究来充分认识不同物种日活动节律的季节性变化规律及其驱动因素。     

四川王朗国家级自然保护区红喉雉鹑的日活动节律及种群密度

红喉雉鹑Tetraophasis obscurus是我国特有高山雉类,国家一级重点保护野生动物。为了解其生活习性及种群参数,2020—2021年在四川王朗国家级自然保护区采用红外相机技术、样线法和样点法对红喉雉鹑的日活动节律及其种群密度进行了调查。红喉雉鹑在保护区分布海拔为2 773～3 777 m,主要活动在3 200～3 400 m,常见于针叶林和针阔混交林,未在草甸生境中记录到;核密度函数绘制的日活动节律曲线表明,红喉雉鹑为昼行性动物,全年日活动曲线整体呈单峰模式,日活动强度在06∶00后快速升高,在08∶00—10∶00达到最高,之后快速降低至12∶00,其后缓慢下降,20∶00趋近于无;繁殖季和非繁殖季的日活动节律均呈双峰模式,但差异不显著（Δ=0.79）,均以早晨最为活跃,非繁殖季比繁殖季的活动高峰推迟1～2 h;红外相机拍摄的群体平均大小为2.63只/群,样线调查的为3只/群,样线法和样点法估算的种群密度分别为7.60只/km²和5.42～6.18只/km²。本研究丰富了红喉雉鹑的野外生态学资料,为其保护管理和种群监测、评估提供...     

探讨基于红外相机技术对大型猫科动物及其猎物的种群评估方法

红外相机技术的发展促进了对东北虎(Panthera tigris altaica)、东北豹(Panthera pardus orientalis)及其猎物种群的研究。本研究以珲春保护区春化和马滴达两个区域的监测结果为例, 介绍利用该技术对我国长白山区东北虎、东北豹及其猎物的种群评估方法, 包括监测位点的选择、相机的架设方式及参数设置、数据筛选、东北虎和东北豹体侧花纹个体识别方法、物种相对丰富度的计算以及捕食者与猎物丰富度关系模型的构建。最后就东北虎、东北豹体侧花纹个体识别技术的适用性、红外相机监测与传统调查方法的差异, 相机监测的误差进行了讨论。研究表明, 利用红外相机技术进行密度预测以及东北虎、东北豹个体自动识别技术还需继续完善。1对/25 km²的相机架设密度基本上满足对于珲春保护区春化至马滴达区域虎豹的监测强度要求, 但对于有蹄类则需要另外的监测方案。     

狗獾夜间活动节律是受人类活动影响而形成的吗?基于青海湖地区的研究实例

青海湖地区是目前已知的狗獾分布海拔最高点。为了解狗獾在青藏高原严酷生态环境下的生活史特点, 并验证是否人类干扰造成了狗獾夜行性的假说, 我们利用红外相机技术, 结合无线电遥测和野外调查研究了青海湖湖东地区亚洲狗獾(Meles leucurus)的种群密度、洞穴口的行为及活动节律。结果表明: (1)研究地区狗獾的平均种群密度为1.2 ± 0.6只/km², 其分布受食物丰富度的影响; (2)狗獾基本在夜间活动, 出洞时间集中在20:00-23:00之间, 而回洞时间则集中在清晨4:00-7:00之间, 23:00-4:00之间是狗獾的活动高峰; (3)狗獾离洞前行为主要是警戒行为, 回洞穴时的行为主要是嬉戏行为, 其他行为较少见, 表达具有特定的时间性; (4)人类活动对于狗獾活动没有显著性影响(P < 0.05)。     

基于红外相机技术对亚洲象个体识别和种群数量的评估

以云南西双版纳国家级自然保护区尚勇子保护区内亚洲象种群为研究对象,通过自动红外照相技术,估算了该地区亚洲象的最小种群数量。本研究于2016年1月,在研究区域内共布设了27个相机位点,野外安放时间为4个月。调查期间,每台相机的有效捕获日为9-52d不等（均值为24d）,红外相机有效捕获日621d,拍摄到亚洲象照片共1944张。通过红外相机照片开展个体识别,最终估算出尚勇保护区内亚洲象的最小种群数量为69头（其中成年象38头,亚成象15头,幼象16头）。拍到7头活动于中国-老挝边境区域的跨境象群。本文探讨利用红外相机拍摄的亚洲象照片进行个体识别的方法,指出与常规调查方法相比较的优势和不足,作为快速、实时有效的种群评估方法的价值。研究结果丰富了保护区内亚洲象种群数据库,为研究、制定和开展亚洲象保护行动提供重要支撑。     

泰国Khao Yai国家公园豹猫和云豹的生态和保护

于1997年10月到1999年10月在泰国KhaoYai国家公园对两种同域分布的物种（即豹猫和云豹）进行了研究。使用带诱饵的陷阱捕捉了这些动物,进行麻醉,确定了性别、年龄,并戴上了无线电项圈,对6只雌性豹猫和4只雄性豹猫进行了1—18个月的无线电追踪。豹猫在干旱季节的利用区域大于雨季,雄性利用的区域大于雌性。在夜间和晨昏时节,豹猫活动增加,但是并没有节律性活动。所有豹猫个体在旱季和雨季的活动都相似,但雄性个体的白天活动多于雌性。豹猫的行走距离有性别差异但是没有季节差异;其食物以鼠类为主。分别对1只雌性云豹和1只雄性云豹进行了17个月和7个月的无线电追踪,雌性个体的活动面积为39．4km^2,而雄性个体活动面积为42．2km^2,核心区都是2．9km2。云豹对半绿林的使用大于其它类型的植被,在晨昏和夜间的活动增加,其活动无节律。     

应用红外相机监测结果估计小型啮齿类物种的种群密度

红外相机(或称相机陷阱)技术可以提供物种组成、种群数量和行为等信息,广泛应用于野生动物的监测与管理。对于可以个体识别的物种,红外相机结合标志重捕法可准确估计其种群密度。但对于不可个体识别的动物,目前尚无成熟方法来估计其种群密度。建立了一个新方法,通过模拟个体运动并匹配红外相机监测数据来估计动物的种群密度。在长白山国家级自然保护区25hm2森林动态监测样地中,以每公顷一台的密度布设红外相机,调查小型啮齿动物的种群数量。在2011年和2012年冬季分别监测41d和40d。然后,设计模型模拟不同密度下啮齿类物种的运动过程,同时记录它们在25hm2的区域内被25台相机拍摄的次数。应用随机森林算法建立回归模型来匹配模拟结果与监测结果,估计啮齿类物种在样地内的密度及其置信区间。这是一种全新的利用红外相机监测数据估计种群密度的方法,可以填补对不可个体识别物种密度估计方法的空缺。     

基于红外相机监测的藏酋猴日活动节律及其季节性变化

日活动节律是动物在一天中不同时间段的活动强度及其周期性变化规律,与身体控制代谢和能量收支成本密切相关。2015年8月至2017年8月,在贵州赤水桫椤国家级自然保护区,借助红外相机监测,对藏酋猴(Macaca thibetana)日活动节律及不同季节的日活动节律的变化进行了研究。调查期间红外相机累计6370个工作日,共收获687张藏酋猴照片,其中独立有效照片105张。日活动节律分析显示,藏酋猴属于典型性的昼行性动物,日活动呈现"M"型,活动高峰出现在12:00—16:00。不同季节的日活动节律比较结果显示,藏酋猴在雨季和旱季的行为节律差异不显著(P>0.05)。与雨季相比,旱季的行为差异表现为活动时间缩短、日出时段活动减少以及主要活动时间从中午推移到下午。另外,随着年气温的变化,藏酋猴日活动温度范围在-2~34℃,其中,15~25℃时活动频次较高(占比59%)。本研究从红外相机的视角揭示了藏酋猴的日活动节律及其变化,为藏酋猴行为生态学研究的深入提供了科学依据。     

三江源国家级自然保护区内云塔村雪豹种群动态

种群监测可为物种研究和保护提供关键信息和依据。雪豹(Panthera uncia)作为亚洲高山生态系统的顶级捕食者和旗舰种, 一直是研究和保护的重点, 但其难以到达的栖息地、隐秘的行踪和广阔的家域使其监测工作开展难度较大, 雪豹种群动态研究较为匮乏。本研究在2013年10月至2019年1月期间, 使用当地社区维护的红外相机, 监测三江源国家级自然保护区通天河沿保护分区内青海省玉树州哈秀乡云塔村雪豹种群的密度和动态, 共识别出35只雪豹个体。基于数据质量较好的2015、2016、2017年连续3年的红外相机数据各年截取3个月数据, 使用空间标记-重捕模型估算种群数量和密度, 发现当地雪豹种群和成年个体密度基本维持稳定, 种群增长率为1.02, 但监测期间雪豹个体更替明显, 平均个体更替率为0.44, 并且围绕两片雪豹核心利用区域发生了领域取代。推测雪豹种群具有较多个体更替和领域取代是因为种群处在雪豹潜在扩散通道上, 或调查范围未覆盖完整种群。本研究是国内首次对雪豹进行较为长期的种群动态监测和分析, 研究结果体现了动态监测的重要性, 也显示出以当地社区为主体监测哺乳动物种群的可能性。     

西双版纳尚勇自然保护区野生印支虎及其三种主要有蹄类猎物种群现状调查

中国野生印支虎及其猎物种群状况的野外实地研究一直处于空白。本研究使用足迹鉴别法、粪堆计数法,首次对西双版纳尚勇自然保护区野生印支虎种群数量现状及该区域内的虎猎物种群状况进行了调查研究。结果显示:2004 ～ 2009 年间,确认西双版纳保护区存在3 只成年印支虎个体(2 雌1 雄),西双版纳尚勇保护区拥有比较丰富的有蹄类种群,其中虎的主要猎物:水鹿平均密度为7.63 (7.40 ～ 9.23)只/ km² ;赤麂平均密度为17. 39 (11.33 ～24.94)只/ km² ,野猪平均密度为10.26 (7.69 ～ 14.51) 只/ km² ,该区域虎猎物生物量为1 715. 74 kg/ km² 。本研究还探讨了该区域印支虎种群的保护前景以及中国境内开展虎种群调查的适用办法等。     

基于红外相机对云南腾冲高黎贡山云猫的调查

云猫(Pardofelis marmorata)在中国分布狭窄、种群稀少, 目前尚缺少有关其调查与研究的报道。通过红外相机分析野生动物的空间分布以及日活动节律, 有助于了解濒危物种的生态学特征, 为保护管理提供科学依据。我们于2014年4月至2021年5月在云南高黎贡山国家级自然保护区腾冲辖区34个位点放置红外相机进行监测。基于监测数据分析了云猫的空间分布, 并利用核密度估计方法(kernel-density estimation)对云猫与豹猫(Prionailurus bengalensis)的日活动节律进行了比较。通过31,462个相机日的监测, 共获得230个云猫的独立探测事件。探测数据显示: 云猫在研究区域内主要分布于海拔2,300‒3,100 m保存完好的常绿阔叶林中。记录到的云猫主要出现在白天, 于6:00‒11:00和14:00‒19:00活动最为频繁。在云猫记录密集的北部地区, 同域分布的豹猫表现出明显的夜行性, 而在南部地区则倾向于晨昏活动, 与云猫活动节律的重叠度较低。腾冲高黎贡山云猫的相对多度指数明显高于低纬度的热带地区, 对该区域云猫进行更为深入的研究对于了解与保护此物种至关重要。     

Bayes and Empirical Bayes Estimators of Abundance and Density from Spatial Capture-Recapture Data

In capture-recapture and mark-resight surveys, movements of individuals both within and between sampling periods can alter the susceptibility of individuals to detection over the region of sampling. In these circumstances spatially explicit capture-recapture (SECR) models, which incorporate the observed locations of individuals, allow population density and abundance to be estimated while accounting for differences in detectability of individuals. In this paper I propose two Bayesian SECR models, one for the analysis of recaptures observed in trapping arrays and another for the analysis of recaptures observed in area searches. In formulating these models I used distinct submodels to specify the distribution of individual home-range centers and the observable recaptures associated with these individuals. This separation of ecological and observational processes allowed me to derive a formal connection between Bayes and empirical Bayes estimators of population abundance that has not been established previously. I showed that this connection applies to every Poisson point-process model of SECR data and provides theoretical support for a previously proposed estimator of abundance based on recaptures in trapping arrays. To illustrate results of both classical and Bayesian methods of analysis, I compared Bayes and empirical Bayes esimates of abundance and density using recaptures from simulated and real populations of animals. Real populations included two iconic datasets: recaptures of tigers detected in camera-trap surveys and recaptures of lizards detected in area-search surveys. In the datasets I analyzed, classical and Bayesian methods provided similar – and often identical – inferences, which is not surprising given the sample sizes and the noninformative priors used in the analyses.     

Application of Spatial and Closed Capture-Recapture Models on Known Population of the Western Derby Eland (Taurotragus derbianus derbianus) in Senegal

Camera trapping with capture-recapture analyses has provided estimates of the abundances of elusive species over the last two decades. Closed capture-recapture models (CR) based on the recognition of individuals and incorporating natural heterogeneity in capture probabilities are considered robust tools; however, closure assumption is often questionable and the use of an M_h jackknife estimator may fail in estimations of real abundance when the heterogeneity is high and data is sparse. A novel, spatially explicit capture-recapture (SECR) approach based on the location-specific capture histories of individuals overcomes the limitations of closed models. We applied both methods on a closed population of 16 critically endangered Western Derby elands in the fenced 1,060-ha Fathala reserve, Senegal. We analyzed the data from 30 cameras operating during a 66-day sampling period deployed in two densities in grid and line arrays. We captured and identified all 16 individuals in 962 trap-days. Abundances were estimated in the programs CAPTURE (models M₀, M_h and M_h Chao) and R, package secr (basic Null and Finite mixture models), and compared with the true population size. We specified 66 days as a threshold in which SECR provides an accurate estimate in all trapping designs within the 7-times divergent density from 0.004 to 0.028 camera trap/ha. Both SECR models showed uniform tendency to overestimate abundance when sampling lasted shorter with no major differences between their outputs. Unlike the closed models, SECR performed well in the line patterns, which indicates promising potential for linear sampling of properly defined habitats of non-territorial and identifiable herbivores in dense wooded savanna conditions. The CR models provided reliable estimates in the grid and we confirmed the advantage of M_h Chao estimator over M_h jackknife when data appeared sparse. We also demonstrated the pooling of trapping occasions with an increase in the capture probabilities, avoiding violation of results.     

Ecology driving genetic variation: a comparative phylogeography of jungle cat (Felis chaus) and leopard cat (Prionailurus bengalensis) in India

Background

Comparative phylogeography links historical population processes to current/ecological processes through congruent/incongruent patterns of genetic variation among species/lineages. Despite high biodiversity, India lacks a phylogeographic paradigm due to limited comparative studies. We compared the phylogenetic patterns of Indian populations of jungle cat (Felis chaus) and leopard cat (Prionailurus bengalensis). Given similarities in their distribution within India, evolutionary histories, body size and habits, congruent patterns of genetic variation were expected.

Methodology/Principal Findings

We collected scats from various biogeographic zones in India and analyzed mtDNA from 55 jungle cats (460 bp NADH5, 141 bp cytochrome b) and 40 leopard cats (362 bp NADH5, 202 bp cytochrome b). Jungle cats revealed high genetic variation, relatively low population structure and demographic expansion around the mid-Pleistocene. In contrast, leopard cats revealed lower genetic variation and high population structure with a F _ST of 0.86 between North and South Indian populations. Niche-model analyses using two approaches (BIOCLIM and MaxEnt) support absence of leopard cats from Central India, indicating a climate associated barrier. We hypothesize that high summer temperatures limit leopard cat distribution and that a rise in temperature in the peninsular region of India during the LGM caused the split in leopard cat population in India.

Conclusions/Significance

Our results indicate that ecological variables describing a species range can predict genetic patterns. Our study has also resolved the confusion over the distribution of the leopard cat in India. The reciprocally monophyletic island population in the South mandates conservation attention.     

Estimating population size by spatially explicit capture–recapture

The number of animals in a population is conventionally estimated by capture–recapture without modelling the spatial relationships between animals and detectors. Problems arise with non‐spatial estimators when individuals differ in their exposure to traps or the target population is poorly defined. Spatially explicit capture–recapture (SECR) methods devised recently to estimate population density largely avoid these problems. Some applications require estimates of population size rather than density, and population size in a defined area may be obtained as a derived parameter from SECR models. While this use of SECR has potential benefits over conventional capture–recapture, including reduced bias, it is unfamiliar to field biologists and no study has examined the precision and robustness of the estimates. We used simulation to compare the performance of SECR and conventional estimators of population size with respect to bias and confidence interval coverage for several spatial scenarios. Three possible estimators for the sampling variance of realised population size all performed well. The precision of SECR estimates was nearly the same as that of the null‐model conventional population estimator. SECR estimates of population size were nearly unbiased (relative bias 0–10%) in all scenarios, including surveys in randomly generated patchy landscapes. Confidence interval coverage was near the nominal level. We used SECR to estimate the population of a species of skink Oligosoma infrapunctatum from pitfall trapping. The estimated number in the area bounded by the outermost traps differed little between a homogeneous density model and models with a quadratic trend in density or a habitat effect on density, despite evidence that the latter models fitted better. Extrapolation of trend models to a larger plot may be misleading. To avoid extrapolation, a large region of interest should be sampled throughout, either with one continuous trapping grid or with clusters of traps dispersed widely according to a probability‐based and spatially representative sampling design.     

Evidence of a High Density Population of Harvested Leopards in a Montane Environment

Populations of large carnivores can persist in mountainous environments following extensive land use change and the conversion of suitable habitat for agriculture and human habitation in lower lying areas of their range. The significance of these populations is poorly understood, however, and little attention has focussed on why certain mountainous areas can hold high densities of large carnivores and what the conservation implications of such populations might be. Here we use the leopard (Panthera pardus) population in the western Soutpansberg Mountains, South Africa, as a model system and show that montane habitats can support high numbers of leopards. Spatially explicit capture-recapture (SECR) analysis recorded the highest density of leopards reported outside of state-protected areas in sub-Saharan Africa. This density represents a temporally high local abundance of leopards and we explore the explanations for this alongside some of the potential conservation implications.     

Free-ranging domestic cats (<Emphasis Type="Italic">Felis catus</Emphasis>) on public lands: estimating density,activity, and diet in the Florida Keys

Feral and free-ranging domestic cats (Felis catus) can have strong negative effects on small mammals and birds, particularly in island ecosystems. We deployed camera traps to study free-ranging cats in national wildlife refuges and state parks on Big Pine Key and Key Largo in the Florida Keys, USA, and used spatial capture–recapture models to estimate cat abundance, movement, and activities. We also used stable isotope analyses to examine the diet of cats captured on public lands. Top population models separated cats based on differences in movement and detection with three and two latent groups on Big Pine Key and Key Largo, respectively. We hypothesize that these latent groups represent feral, semi-feral, and indoor/outdoor house cats based on the estimated movement parameters of each group. Estimated cat densities and activity varied between the two islands, with relatively high densities (~4 cats/km²) exhibiting crepuscular diel patterns on Big Pine Key and lower densities (~1 cat/km²) exhibiting nocturnal diel patterns on Key Largo. These differences are most likely related to the higher proportion of house cats on Big Pine relative to Key Largo. Carbon and nitrogen isotope ratios from hair samples of free-ranging cats (n = 43) provided estimates of the proportion of wild and anthropogenic foods in cat diets. At the population level, cats on both islands consumed mostly anthropogenic foods (>80% of the diet), but eight individuals were effective predators of wildlife (>50% of the diet). We provide evidence that cat groups within a population move different distances, exhibit different activity patterns, and that individuals consume wildlife at different rates, which all have implications for managing this invasive predator.