The lack of variance estimates constrain the utility of abundance indices calculated from camera-trap data. We adapted a General Index model, which allows variance estimation, to analyze cameratrap observations of feral pigs (Sus scrofa) for population monitoring in a tropical rainforest. We tested whether the index would respond to population manipulation, and found that it decreased by 57% following removal of 24 pigs and remained low in the following period. Our method is useful for monitoring other large animals in difficult landscapes, and the model can be used to enhance the value of existing data sets.

The monitoring and management of species depends on reliable population estimates, and this can be both difficult and very costly for cryptic large vertebrates that live in forested habitats. Recently developed camera trapping techniques have already been shown to be an effective means of making mark-recapture estimates of individually identifiable animals (e.g. tigers). Camera traps also provide a new method for surveying animal abundance. Through computer simulations, and an analysis of the rates of camera trap capture from 19 studies of tigers across the species' range, we show that the number of camera days/tiger photograph correlates with independent estimates of tiger density. This statistic does not rely on individual identity and is particularly useful for estimating the population density of species that are not individually identifiable. Finally, we used the comparison between observed trapping rates and the computer simulations to estimate the minimum effort required to determine that tigers,or other species, do not exist in an area, a measure that is critical for conservation planning.

通过在唐家河国家级自然保护区内自然死亡的8具动物尸体周围布设红外相机,详细记录了动物尸体在保护良好的自然条件下的分解过程。研究发现,除微生物与无脊椎动物外,脊椎动物在尸体分解过程中也起到很重要的作用:(1)动物尸体会吸引多种脊椎动物前来取食,不同脊椎动物对尸体的利用方式和利用程度不一样。其中利用强度最高的动物为野猪Sus scrofa、亚洲黑熊Ursus thibetanus和大嘴乌鸦Corvus macrorhynchhos,实际贡献率分别为:87.15%、9.08%、3.72%,占所有脊椎动物对尸体取食强度的99.9%,其他动物贡献0.1%,如果子狸Paguma larvata、啮齿动物。(2)野猪有同类相食和拖动尸体的行为;绿背山雀Parus monticolus有采集尸体毛发筑巢的行为;未发现灵长类动物在尸体旁长时间逗留。根据研究结果,建议保护区在不污染水源的情况下,让自然死亡的尸体自然分解而不作深埋处理。

通过在唐家河国家级自然保护区内自然死亡的8具动物尸体周围布设红外相机,详细记录了动物尸体在保护良好的自然条件下的分解过程。研究发现,除微生物与无脊椎动物外,脊椎动物在尸体分解过程中也起到很重要的作用:(1)动物尸体会吸引多种脊椎动物前来取食,不同脊椎动物对尸体的利用方式和利用程度不一样。其中利用强度最高的动物为野猪Sus scrofa、亚洲黑熊Ursus thibetanus和大嘴乌鸦Corvus macrorhynchhos,实际贡献率分别为:87.15%、9.08%、3.72%,占所有脊椎动物对尸体取食强度的99.9%,其他动物贡献0.1%,如果子狸Paguma larvata、啮齿动物。(2)野猪有同类相食和拖动尸体的行为;绿背山雀Parus monticolus有采集尸体毛发筑巢的行为;未发现灵长类动物在尸体旁长时间逗留。根据研究结果,建议保护区在不污染水源的情况下,让自然死亡的尸体自然分解而不作深埋处理。

Wild pigs (Sus scrofa) are widespread across many landscapes throughout the world and are considered to be an invasive pest to agriculture and the environment, or conversely a native or desired game species and resource for hunting. Wild pig population monitoring is often required for a variety of management or research objectives, and many methods and analyses for monitoring abundance are available. Here, we describe monitoring methods that have proven or potential applications to wild pig management. We describe the advantages and disadvantages of methods so that potential users can efficiently consider and identify the option(s) best suited to their combination of objectives, circumstances, and resources. This paper offers guidance to wildlife managers, researchers, and stakeholders considering population monitoring of wild pigs and will help ensure that they can fulfill their monitoring objectives while optimizing their use of resources.

http://doi.wiley.com/10.1017/S1367943002002160

We report on the use of infrared-triggered cameras as an effective tool to survey phasianid populations in Wanglang and Wolong Nature Reserves, China. Surveys at 183 camera-trapping sites recorded 30 bird species, including nine phasianids (one grouse and eight pheasant species). Blood Pheasant Ithaginis cruentus and Temminck's Tragopan Tragopan temminckii were the phasianids most often detected at both reserves and were found within the mid-elevation range (2400 3600 m asl). The occupancy rate and detection probability of both species were examined using an occupancy model relative to eight sampling covariates and three detection covariates. The model estimates of occupancy for Blood Pheasant (0.30) and Temminck's Tragopan (0.14) are close to the na茂ve estimates based on camera detections (0.27 and 0.13, respectively). The estimated detection probability during a 5-day period was 0.36 for Blood Pheasant and 0.30 for Temminck's Tragopan. The daily activity patterns for these two species were assessed from the time/date stamps on the photographs and sex ratios calculated for Blood Pheasant (152M : 72F) and Temminck's Tragopan (48M : 21F). Infrared cameras are valuable for surveying these reclusive species and our protocol is applicable to research or monitoring of phasianids.

20年来,红外相机技术在国内外野生动物研究、监测与保护中得到了广泛应用。基于红外相机技术,我国在野生动物生态学研究、动物行为学研究、稀有物种的探测与记录、动物本底资源调查、生物多样性监测及保护地管理与保护评价等领域取得了众多成果。目前,数学模型、统计分析方法和新的概念正在促进红外相机技术在野生动物监测研究与保护管理中的发展和推广应用。同时,随着红外相机技术的成熟、成本降低和应用普及,这一技术也将会被更多的野生动物研究人员、管理人员和自然保护区管理者所采用,并成为全国各级保护地和区域生物多样性监测研究的关键技术和方法。今后,建立并完善系统化的监测网络和数据共享平台、开发新一代的数据分析方法与模型,将是此项技术进一步发展和应用的主要方向。

20年来,红外相机技术在国内外野生动物研究、监测与保护中得到了广泛应用。基于红外相机技术,我国在野生动物生态学研究、动物行为学研究、稀有物种的探测与记录、动物本底资源调查、生物多样性监测及保护地管理与保护评价等领域取得了众多成果。目前,数学模型、统计分析方法和新的概念正在促进红外相机技术在野生动物监测研究与保护管理中的发展和推广应用。同时,随着红外相机技术的成熟、成本降低和应用普及,这一技术也将会被更多的野生动物研究人员、管理人员和自然保护区管理者所采用,并成为全国各级保护地和区域生物多样性监测研究的关键技术和方法。今后,建立并完善系统化的监测网络和数据共享平台、开发新一代的数据分析方法与模型,将是此项技术进一步发展和应用的主要方向。

自然保护区的生物物种编目是区域性和全国性生物多样性研究与监测的基础,而红外相机调查技术已成为兽类物种编目的重要手段之一.老河沟自然保护区位于四川省岷山北部,地处大熊猫岷山种群分布核心地区,是2012年新建保护区.从2011年至2014年,我们把保护区划分为1 km×1 km的方格,采用红外相机技术,对区内的兽类多样性进行了系统全面的调查.经过9 188个相机日的调查,共记录到分属7目18科的兽类.其中,有81 709份记录可以鉴定出具体物种,包括野生兽类24种,家畜1种(家狗),分属5目14科,有效探测数总计1 766次.其余未能鉴定出具体物种的兽类记录为小型翼手目、食虫目和啮齿目动物.在24种野生兽类中,食肉目物种数最多,共4科9种;其次为偶蹄目(4科7种)与啮齿目(3科6种).就有效探测数而言,偶蹄目兽类是记录到次数最多的类群(占总探测数43.97％),其次是啮齿目(25.61％)和食肉目(22.44％).被IUCN红色名录评估为“濒危EN”、“易危VU”和“近危NT”级别的物种各3种,被列为国家Ⅰ级和Ⅱ级重点保护野生动物的分别为4种和5种.本次调查对老河沟自然保护区内的大中型兽类进行了首次系统性编目,了解了区内兽类群落的物种组成、空间分布与相对多度,为后续的科研项目和保护管理提供了本底数据和基础信息.

自然保护区的生物物种编目是区域性和全国性生物多样性研究与监测的基础,而红外相机调查技术已成为兽类物种编目的重要手段之一.老河沟自然保护区位于四川省岷山北部,地处大熊猫岷山种群分布核心地区,是2012年新建保护区.从2011年至2014年,我们把保护区划分为1 km×1 km的方格,采用红外相机技术,对区内的兽类多样性进行了系统全面的调查.经过9 188个相机日的调查,共记录到分属7目18科的兽类.其中,有81 709份记录可以鉴定出具体物种,包括野生兽类24种,家畜1种(家狗),分属5目14科,有效探测数总计1 766次.其余未能鉴定出具体物种的兽类记录为小型翼手目、食虫目和啮齿目动物.在24种野生兽类中,食肉目物种数最多,共4科9种;其次为偶蹄目(4科7种)与啮齿目(3科6种).就有效探测数而言,偶蹄目兽类是记录到次数最多的类群(占总探测数43.97％),其次是啮齿目(25.61％)和食肉目(22.44％).被IUCN红色名录评估为“濒危EN”、“易危VU”和“近危NT”级别的物种各3种,被列为国家Ⅰ级和Ⅱ级重点保护野生动物的分别为4种和5种.本次调查对老河沟自然保护区内的大中型兽类进行了首次系统性编目,了解了区内兽类群落的物种组成、空间分布与相对多度,为后续的科研项目和保护管理提供了本底数据和基础信息.

Ecological indicators or indices have been widely used to simplify and measure complex ecosystems. It is critical to identify suitable indicators or indices to improve monitoring and understanding of complex natural systems. Camera trapping is an objective technique that can provide a large amount of information on wildlife. The purpose of our study is to explore the effective ecological indices for wildlife diversity analysis and monitoring in Guanyinshan Nature Reserve of Shaanxi Province, China. Since July 2009, a total of 18 cameras were installed in the reserve from August 2009 to July 2011, collecting 2115 photo captures during these 24 months. We developed five abundance indices, including relative abundance index (RAI), monthly relative abundance index (MRAI), time-period relative abundance index (TRAI), night-time relative abundance index (NRAI) and species abundance index (N) to integrate the information derived from captures. Results are: (1) 27 species were detected and 6 species had high RAI values of over 79.3%, including takin (Budorcas taxicolor), common goral (Naemorhedus goral), tufted deer (Elaphodus cephalophus), golden pheasant (Chtysolophus pictus), wild boar (Sus scrofa), and mainland serow (Capricornis sumatraensis). (2) MRAI shows a consistent monthly activity pattern of all animals being active in June and July and inactive in February. (3) TRAIs of the most abundant six species show that takin, tufted deer and common goral have the similar daily activity pattern with one peak at dawn and one peak at dusk. The daily activity patterns of golden pheasant and wild boar show that they are most active during the day time, with wild boar being particularly active at noon. NRAIs of mainland serow show the highest nocturnality and of golden pheasant the lowest nocturnality. (4) We estimated abundance of takin, tufted deer and wild boar by using our developed index. The abundance for the three species shows an increasing trend during the 2-year study period, particularly for wild boar. Our results provided an interesting comparison of species diversity and their activity patterns. As trapping continues we will have a consistent source of monitoring data to evaluate changes in species abundance and activities. Therefore, the conclusion is that the methods we used and the indices we developed are capable to estimate species activity patterns and abundance dynamics which are useful for future wildlife management in Guanyinshan Nature Reserve and elsewhere. (C) 2012 Elsevier Ltd. All rights reserved.

Nondetection of a species at a site does not imply that the species is absent unless the probability of detection is 1. We propose a model and likelihood-based method for estimating site occupancy rates when detection probabilities are < 1. The model provides a flexible framework enabling covariate information to be included and allowing for missing observations. Via computer simulation, we found that the model provides good estimates of the occupancy rates, generally unbiased for moderate detection probabilities (>0.3). We estimated site occupancy rates for two anuran species at 32 wetland sites in Maryland, USA, from data collected during 2000 as part of an amphibian monitoring program, Frog-watch USA. Site occupancy rates were estimated as 0.49 for American toads (Bufo americanus), a 44% increase over the proportion of sites at which they were actually observed, and as 0.85 for spring peepers (Pseudacris crucifer), slightly above the observed proportion of 0.83.

We examine the abundance and distribution of Sumatran tigers ( Panthera tigris sumatrae ) and nine prey species in Bukit Barisan Selatan National Park on Sumatra, Indonesia. Our study is the first to demonstrate that the relative abundance of tigers and their prey, as measured by camera traps, is directly related to independently derived estimates of densities for these species. The tiger population in the park is estimated at 40 43 individuals. Results indicate that illegal hunting of prey and tigers, measured as a function of human density within 10 km of the park, is primarily responsible for observed patterns of abundance, and that habitat loss is an increasingly serious problem. Abundance of tigers, two mouse deer ( Tragulus spp.), pigs ( Sus scrofa ) and Sambar deer ( Cervus unicolor ) was more than four times higher in areas with low human population density, while densities of red muntjac ( Muntiacus muntjac ) and pigtail macaques ( Macaca nemestrina ) were twice as high. Malay tapir ( Tapirus indicus ) and argus pheasant ( Argusianus argus ), species infrequently hunted, had higher indices of relative abundance in areas with high human density. Edge effects associated with park boundaries were not a significant factor in abundance of tigers or prey once human density was considered. Tigers in Bukit Barisan Selatan National Park, and probably other protected areas throughout Sumatra, are in imminent danger of extinction unless trends in hunting and deforestation are reversed.

Techniques for estimation of absolute abundance of wildlife populations have received a lot of attention in recent years. The statistical research has been focused on intensive small-scale studies. Recently, however, wildlife biologists have desired to study populations of animals at very large scales for monitoring purposes. Population indices are widely used in these extensive monitoring programs because they are inexpensive compared to estimates of absolute abundance. A crucial underlying assumption is that the population index ( C ) is directly proportional to the population density ( D ). The proportionality constant, , is simply the probability of detection for animals in the survey. As spatial and temporal comparisons of indices are crucial, it is necessary to also assume that the probability of detection is constant over space and time. Biologists intuitively recognize this when they design rigid protocols for the studies where the indices are collected. Unfortunately, however, in many field studies the assumption is clearly invalid. We believe that the estimation of detection probability should be built into the monitoring design through a double sampling approach. A large sample of points provides an abundance index, and a smaller sub-sample of the same points is used to estimate detection probability. There is an important need for statistical research on the design and analysis of these complex studies. Some basic concepts based on actual avian, amphibian, and fish monitoring studies are presented in this article. Copyright 2002 John Wiley & Sons, Ltd.

1. Calibrating indices of animal abundance to true densities is critical in wildlife studies especially when direct density estimations are precluded by high costs, lack of required data or model parameters, elusiveness and rarity of target species. For studies deploying camera traps, the use of photographic rate (photographs per sampling time) as an index of abundance potentially applies to the majority of terrestrial mammals where individual recognition, and hence capture-recapture analysis, are unfeasible. The very few studies addressing this method have either been limited by lack of independence between trapping rates and density estimations, or because they combined different species, thus introducing potential bias in camera trap detection rates. This study uses a single model species from several sites to analyse calibration of trapping rates to independently derived estimations of density. The study also makes the first field test of the method by Rowcliffe et al. (2008) for density derivation from camera trapping rates based on modelling animal-camera contacts.2. We deployed camera traps along line transects at six sites in the Udzungwa Mountains of Tanzania and correlated trapping rates of Harvey's duiker Cephalophus harveyi with densities estimated from counts made along the same transects.3. We found a strong, linear relationship (R-2 = 0.90) between trapping rate and density. Sampling precision analysis indicates that camera trapping rates reach satisfactory precision when trapping effort amounts to 250-300 camera days. Density estimates using Rowcliffe et al.'s (2008) gas model conversion are higher than from transect censuses; we discuss the possible reasons and stress the need for more field tests.4. Synthesis and applications. Subject to rigorous and periodic calibration, and standardization of sampling procedures in time and over different sites, camera trapping rate is shown to be, in this study, a valid index of density in the target species. Comparative data indicate that this may also apply to forest ungulates in general. The method has great potential for standardizing monitoring programmes and reducing the costs of wildlife surveys, especially in remote areas.

1. Density estimation is of fundamental importance in wildlife management. The use of camera traps to estimate animal density has so far been restricted to capture鈥搑ecapture analysis of species with individually identifiable markings. This study developed a method that eliminates the requirement for individual recognition of animals by modelling the underlying process of contact between animals and cameras. 2. The model provides a factor that linearly scales trapping rate with density, depending on two key biological variables (average animal group size and day range) and two characteristics of the camera sensor (distance and angle within which it detects animals). 3. We tested the approach in an enclosed animal park with known abundances of four species, obtaining accurate estimates in three out of four cases. Inaccuracy in the fourth species was because of biased placement of cameras with respect to the distribution of this species. 4. Synthesis and applications. Subject to unbiased camera placement and accurate measurement of model parameters, this method opens the possibility of reduced labour costs for estimating wildlife density and may make estimation possible where it has not been previously. We provide guidelines on the trapping effort required to obtain reasonably precise estimates.

<p>Summary. Spatial replication is a common theme in count surveys of animals. Such surveys often generate sparse count data from which it is difficult to estimate population size while formally accounting for detection probability. In this article, I describe a class of models ( N -mixture models) which allow for estimation of population size from such data. The key idea is to view site-specific population sizes, N , as independent random variables distributed according to some mixing distribution (e.g., Poisson). Prior parameters are estimated from the marginal likelihood of the data, having integrated over the prior distribution for N .

We describe an approach for estimating occupancy rate or the proportion of area occupied when heterogeneity in detection probability exists as a result of variation in abundance of the organism under study. The key feature of such problems, which we exploit, is that variation in abundance induces variation in detection probability. Thus, heterogeneity in abundance can be modeled as heterogeneity in detection probability. Moreover, this linkage between heterogeneity in abundance and heterogeneity in detection probability allows one to exploit a heterogeneous detection probability model to estimate the underlying distribution of abundances. Therefore, our method allows estimation of abundance from repeated observations of the presence or absence of animals without having to uniquely mark individuals in the population.

Camera-traps are a widely applied to monitor wildlife populations. For individually marked species, capture-recapture models provide robust population estimates, but for unmarked species, inference is often based on relative abundance indices (RAI, number of records per trap effort), although these do not account for imperfect and variable detection. We use a simulation study and empirical camera-trapping data to illustrate how ecological and sampling-related factors can bias RAIs. Our simulations showed that (1) differences in detection between species led to bias in RAT ratios toward the more detectable species, especially at low detection levels, (2) species with larger home ranges were photographed more often, inflating RAIs, (3) species specific responses to different types of trap setup biased RAT ratios, and (4) changes in detection over time blurred true population trends inferred from RAIs. Empirical data for leopard cats Prionailurus bengalensis and common palm civets Paradoxurus hermaphroditus showed that traps set up along roads led to higher RAIs than off-road traps, but targeting roads increased detection more for leopard cats than for common palm civets. Comparing RAIs of Sunda clouded leopards Neofelis diardi and leopard cats with spatial capture-recapture based density estimates across sites, RAIs did not reflect differences in density. Analytical options for estimating density from camera-trapping data of unmarked populations are limited. Consequently, we fear that RAIs will continue to be applied. This is alarming, since these measures often form the basis for conservation and management decisions. We suggest considering alternative analytical and survey methods, especially when dealing with threatened species. (C) 2012 Elsevier Ltd. All rights reserved.

基于全国哺乳动物观测网络中四川王朗、四姑娘山、贡嘎山及亚丁4个自然保护区2017年6—11月红外相机数据,利用相对丰富度指数RAI对四川羚牛(Budorcas tibetanus)、中华鬣羚(Capricornis milneedwardsii)、水鹿(Cervus unicolor)、毛冠鹿(Elaphodus cephalophus)、林麝(Moschus berezovskii)、高山麝(Moschus chrysogaster)、小麂(Muntiacus reevesi)、中华斑羚(Naemorhedus griseus)和岩羊(Pseudois nayaur)9种有蹄类动物的相对种群数量和日活动规律进行研究。结果表明:(1)毛冠鹿在九种有蹄类动物中的相对丰富度(64.12%)最高,且明显高于其他动物。(2)小麂、毛冠鹿和中华斑羚的日活动模式呈双峰型,具有明显的晨昏习性。(3)水鹿和中华鬣羚是典型的夜行性动物。(4)毛冠鹿在不同地区日活动模式均呈双峰型,但不同地区其活动高峰出现的时间段存在差异。有蹄类动物种群数量与食物资源、捕食压力等有关,活动节律受多种生物和非生物因素影响。研究四川地区有蹄类活动节律,可以为该地区有蹄类的监测及有效保护管理提供依据,并能为其捕食者行为学研究和保护提供数据支持。

基于全国哺乳动物观测网络中四川王朗、四姑娘山、贡嘎山及亚丁4个自然保护区2017年6—11月红外相机数据,利用相对丰富度指数RAI对四川羚牛(Budorcas tibetanus)、中华鬣羚(Capricornis milneedwardsii)、水鹿(Cervus unicolor)、毛冠鹿(Elaphodus cephalophus)、林麝(Moschus berezovskii)、高山麝(Moschus chrysogaster)、小麂(Muntiacus reevesi)、中华斑羚(Naemorhedus griseus)和岩羊(Pseudois nayaur)9种有蹄类动物的相对种群数量和日活动规律进行研究。结果表明:(1)毛冠鹿在九种有蹄类动物中的相对丰富度(64.12%)最高,且明显高于其他动物。(2)小麂、毛冠鹿和中华斑羚的日活动模式呈双峰型,具有明显的晨昏习性。(3)水鹿和中华鬣羚是典型的夜行性动物。(4)毛冠鹿在不同地区日活动模式均呈双峰型,但不同地区其活动高峰出现的时间段存在差异。有蹄类动物种群数量与食物资源、捕食压力等有关,活动节律受多种生物和非生物因素影响。研究四川地区有蹄类活动节律,可以为该地区有蹄类的监测及有效保护管理提供依据,并能为其捕食者行为学研究和保护提供数据支持。

The present study demonstrates the possibility of estimating species numbers of animal or plant communities from samples using relative abundance distributions. We use log-abundance pecies-rank order plots and derive two new estimators that are based on log-series and lognormal distributions. At small to moderate sample sizes these estimators appear to be more precise than previous parametric and nonparametric estimators. We test our estimators using samples from 171 published medium-sized to large animal and plant communities taken from the literature. By this we show that our new estimators define also limits of precision.

正国外使用红外相机技术开展野生动物调查研究已有较长的历史,最早的报道见于Champion(1927),在20世纪90年代逐渐发展成熟,广泛用于动物种群数量和密度的研究。如应用红外相机和

正国外使用红外相机技术开展野生动物调查研究已有较长的历史,最早的报道见于Champion(1927),在20世纪90年代逐渐发展成熟,广泛用于动物种群数量和密度的研究。如应用红外相机和

长期以来,野生动物(特别是兽类)监测面临着极大困难,具体表现在:(1)许多野生动物种群数量日渐减 少,甚至濒临灭绝;(2)未经许可,许多珍稀种类禁止采集实体样本;(3)许多动物昼伏夜出,活动隐秘,很难观察到实体,甚至很难发现痕迹;(4)许多动 物仅分布在人稀罕至的森林或其他生境中,监测难度大、成本高;(5)野生动物行为习性和生存空间多种多样,难以形成统一的监测方法和技术标准.20世纪 90年代以来,“3S”技术、分子生物学技术、数码影像技术(如自动相机技术或红外相机技术(automated-camera monitoring technology或cameratrapping)等开始广泛应用于野生动物的监测与研究.

长期以来,野生动物(特别是兽类)监测面临着极大困难,具体表现在:(1)许多野生动物种群数量日渐减 少,甚至濒临灭绝;(2)未经许可,许多珍稀种类禁止采集实体样本;(3)许多动物昼伏夜出,活动隐秘,很难观察到实体,甚至很难发现痕迹;(4)许多动 物仅分布在人稀罕至的森林或其他生境中,监测难度大、成本高;(5)野生动物行为习性和生存空间多种多样,难以形成统一的监测方法和技术标准.20世纪 90年代以来,“3S”技术、分子生物学技术、数码影像技术(如自动相机技术或红外相机技术(automated-camera monitoring technology或cameratrapping)等开始广泛应用于野生动物的监测与研究.

2012年8月至2015年8月,在壶瓶山国家级自然保护区布设20个红外相机监测公里网格,对保护区的兽类和鸟类多样性进行了初步调查。经过19 592个有效相机工作日的调查,共记录到兽类4目11科21种和鸟类4目8科33种,其中有国家Ⅰ级重点保护野生动物1种(林麝Moschus berezovskii)、国家Ⅱ级重点保护野生动物8种和保护区新纪录兽类1种(红腿长吻松鼠Dremomys pyrrhomerus)。兽类以食肉目种类最多(9种),其次为偶蹄目(6种)和啮齿目(5种)。毛冠鹿(Elaphodus cephalophus)、野猪(Sus scrofa)、红腿长吻松鼠、小麂(Muntiacus reevesi)和猪獾(Arctonyx collaris)的相对丰富度居于兽类的前五位。鸟类以雀形目的种类最多(25种),其次是鸡形目(5种)和鴷形目(2种)。红腹锦鸡(Chrysolophus pictus)、红腹角雉(Tragopan temminckii)和眼纹噪鹛(Garrulax ocellatus)的相对丰富度指数居于鸟类的前三位。此外,本文对红腹锦鸡、红腹角雉、红腿长吻松鼠、毛冠鹿、野猪和小麂等常见物种的日活动节律和年活动节律进行了初步分析。本次调查初步了解了保护区内地栖大中型兽类和鸟类的本底信息,为保护区今后开展野生动物长期监测提供了重要依据。

2012年8月至2015年8月,在壶瓶山国家级自然保护区布设20个红外相机监测公里网格,对保护区的兽类和鸟类多样性进行了初步调查。经过19 592个有效相机工作日的调查,共记录到兽类4目11科21种和鸟类4目8科33种,其中有国家Ⅰ级重点保护野生动物1种(林麝Moschus berezovskii)、国家Ⅱ级重点保护野生动物8种和保护区新纪录兽类1种(红腿长吻松鼠Dremomys pyrrhomerus)。兽类以食肉目种类最多(9种),其次为偶蹄目(6种)和啮齿目(5种)。毛冠鹿(Elaphodus cephalophus)、野猪(Sus scrofa)、红腿长吻松鼠、小麂(Muntiacus reevesi)和猪獾(Arctonyx collaris)的相对丰富度居于兽类的前五位。鸟类以雀形目的种类最多(25种),其次是鸡形目(5种)和鴷形目(2种)。红腹锦鸡(Chrysolophus pictus)、红腹角雉(Tragopan temminckii)和眼纹噪鹛(Garrulax ocellatus)的相对丰富度指数居于鸟类的前三位。此外,本文对红腹锦鸡、红腹角雉、红腿长吻松鼠、毛冠鹿、野猪和小麂等常见物种的日活动节律和年活动节律进行了初步分析。本次调查初步了解了保护区内地栖大中型兽类和鸟类的本底信息,为保护区今后开展野生动物长期监测提供了重要依据。

From June 2010 to August 2011, four different camera trap placement patterns, >0.05), but the three patterns had significant difference (<0.01) with same elevation pattern. Due to its grid model, welldistributed camera, and arrangement specifications, same elevation pattern operated better than the other three patterns.

From June 2010 to August 2011, four different camera trap placement patterns, >0.05), but the three patterns had significant difference (<0.01) with same elevation pattern. Due to its grid model, welldistributed camera, and arrangement specifications, same elevation pattern operated better than the other three patterns.