Toward reliable population density estimates of partially marked populations using spatially explicit mark–resight methods

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Random Encounter and Staying Time Model Testing with Human Volunteers

Ecology and management programs designed to track population trends over time increasingly are using passive monitoring methods to estimate terrestrial mammal densities. Researchers use motion-sensing cameras in mammal studies because they are cost-effective and advances in statistical methods incorporate motion-sensing camera data to estimate mammal densities. Density estimation involving unmarked individuals, however, remains challenging and empirical tests of statistical models are relatively rare. We tested the random encounter and staying time model (REST), a new means of estimating the density of an unmarked population, using human volunteers and simulated camera surveys. The REST method produced unbiased estimates of density, regardless of changes in human abundance, movement rates, home range sizes, or simulated camera effort. These advances in statistical methods when applied to motion-sensing camera data provide innovative avenues of large-mammal monitoring that have the potential to be applied to a broad spectrum of conservation and management studies, provided assumptions for the REST method are rigorously tested and met. © 2020 The Wildlife Society.     

Estimating Abundance of an Unmarked,Low-Density Species using Cameras

Estimating abundance of wildlife populations can be challenging and costly, especially for species that are difficult to detect and that live at low densities, such as cougars (Puma concolor). Remote, motion-sensitive cameras are a relatively efficient monitoring tool, but most abundance estimation techniques using remote cameras rely on some or all of the population being uniquely identifiable. Recently developed methods estimate abundance from encounter rates with remote cameras and do not require identifiable individuals. We used 2 methods, the time-to-event and space-to-event models, to estimate the density of 2 cougar populations in Idaho, USA, over 3 winters from 2016–2019. We concurrently estimated cougar density using the random encounter model (REM), an existing camera-based method for unmarked populations, and genetic spatial capture recapture (SCR), an established method for monitoring cougar populations. In surveys for which we successfully estimated density using the SCR model, the time-to-event estimates were more precise and showed comparable variation between survey years. The space-to-event estimates were less precise than the SCR estimates and were more variable between survey years. Compared to REM, time-to-event was more precise and consistent, and space-to-event was less precise and consistent. Low sample sizes made the space-to-event and SCR models inconsistent from survey to survey, and non-random camera placement may have biased both of the camera-based estimators high. We show that camera-based estimators can perform comparably to existing methods for estimating abundance in unmarked species that live at low densities. With the time- and space-to-event models, managers could use remote cameras to monitor populations of multiple species at broader spatial and temporal scales than existing methods allow. © 2020 The Wildlife Society.     

Cameras,Coyotes, and the Assumption of Equal Detectability

Abstract: Remote cameras are an increasingly important tool in management and wildlife studies. However, we often do not know if they provide an unbiased sample of populations. Using a marked, radiocollared population of coyotes (Canis latrans) of known social status, we evaluated the influence of temporal (daily and seasonal) and spatial (distance between units, habitat, and proximity to human structures) factors on vulnerability to photo-captures. During 8 unbaited camera sessions of 6 weeks each, we obtained 158 coyote photographs at a photo-capture success rate of 1.6%. We were able to identify not only marked individuals, but also a number of uncollared adults through variation in their pelage. Photo-capture of adults peaked 2 weeks after we established camera stations. Annual success for photographing adult coyotes was greatest during March and April, which corresponded with the dispersal season. The majority of photo-captures occurred at night, and adult photo-captures peaked around midnight, with smaller peaks at dawn and dusk. Rather than reflecting a circadian activity pattern, nighttime captures seemed to reflect when adult coyotes were most vulnerable to photo-capture. Characteristics of camera locations, such as amount of human activity, being on roads versus trails, and habitat type, also influenced the number of photo-captures. We conclude that remote cameras do not always provide an unbiased sample of populations and that animal behavior is important to consider when using these systems. Researchers using camera techniques need to carefully consider when, where, and how cameras are placed to reduce this bias.     

Estimating elephant density using motion-sensitive cameras: challenges,opportunities, and parameters for consideration

With extinction rates far exceeding the natural background rate, reliable monitoring of wildlife populations has become crucial for adaptive management and conservation. Robust monitoring is often labor intensive with high economic costs, particularly in the case of those species that are subject to illegal poaching, such as elephants, which require frequent and accurate population estimates over large spatial scales. Dung counting methods are commonly employed to estimate the density of elephants; however, in the absence of a full survey calibration, these can be unreliable in heterogeneous habitats where dung decay rates may be highly variable. We explored whether motion-sensitive cameras offer a simple, lower cost, and reliable alternative for monitoring in challenging forest environments. We estimated the density of African savanna elephants (Loxodanta africana) in a montane forest using the random encounter model and assessed the importance of surveying parameters for future survey design. We deployed motion-sensitive cameras in 65 locations in the Aberdare Conservation Area in Kenya during June to August in 2015 to 2017, for a survey effort of 967 days, and a mean encounter rate of 0.09 ± 0.29 (SD) images/day. Elephants were captured in 16 locations. Density estimates varied between vegetation types, with estimates ranging from 6.27/km² in shrub, 1.1/km² in forest, 0.53/km² in bamboo (Yushania alpine), and 0.44/km² in the moorlands. The average speed of animal movement and the camera detection zone had the strongest linear associations with density estimates (R = −0.97). The random encounter model has the potential to offer an alternative, or complementary method within the active management framework for monitoring elephant populations in forests at a relatively low cost.     

Efficacy of N-mixture models for surveying and monitoring white-tailed deer populations

Automated cameras have become increasingly common for monitoring wildlife populations and estimating abundance. Most analytical methods, however, fail to account for incomplete and variable detection probabilities, which biases abundance estimates. Methods which do account for detection have not been thoroughly tested, and those that have been tested were compared to other methods of abundance estimation. The goal of this study was to evaluate the accuracy and effectiveness of the N-mixture method, which explicitly incorporates detection probability, to monitor white-tailed deer (Odocoileus virginianus) by using camera surveys and a known, marked population to collect data and estimate abundance. Motion-triggered camera surveys were conducted at Auburn University’s deer research facility in 2010. Abundance estimates were generated using N-mixture models and compared to the known number of marked deer in the population. We compared abundance estimates generated from a decreasing number of survey days used in analysis and by time periods (DAY, NIGHT, SUNRISE, SUNSET, CREPUSCULAR, ALL TIMES). Accurate abundance estimates were generated using 24 h of data and nighttime only data. Accuracy of abundance estimates increased with increasing number of survey days until day 5, and there was no improvement with additional data. This suggests that, for our system, 5-day camera surveys conducted at night were adequate for abundance estimation and population monitoring. Further, our study demonstrates that camera surveys and N-mixture models may be a highly effective method for estimation and monitoring of ungulate populations.     

Estimating sika deer abundance using camera surveys

Cameras have been used throughout the world to estimate wildlife abundance and occupancy. Abundance estimates generated by camera surveys tend to be less invasive, less costly, and more accurate than other means in certain situations. We sought to expand and test the effectiveness of camera surveys on sika deer in Maryland. In 2008, we setup surveys with a 7-day pre-bait period followed by a 7-day active camera survey with 15 cameras. In 2009, we ran the cameras for the entire 14-day survey and moved cameras after each survey to determine if biases occur when using the same camera sites. During both years and all surveys, camera density was approximately 1-camera/65-ha. The abundance estimates were similar between years and estimators. In 2009, increasing photo intervals from 1-min to 5- and 10-min intervals reduced the number of pictures by 66 and 81%, respectively, while providing similar abundance estimates. We calculated the daily detection probabilities for all identifiable deer and we used radio-collared males that occurred within 2 km of the survey grid to assist in determining the optimum survey length. Detection probability did not vary between surveys in the same year, but varied between 2008 and 2009, most likely due to unlimited bait being available during 2008 surveys. Camera surveys have proven to be an accurate and cost effective means of estimating wildlife abundance and can be used successfully to determine sika deer abundance.     

Total Counts Versus Line Transects for Estimating Abundance of Small Gopher Tortoise Populations

Abstract: Status and trends of gopher tortoise (Gopherus polyphemus) populations are a critical information need for natural resource managers, researchers, and policy makers. Many tortoise populations are small and isolated, which can present challenges for deriving population estimates. Our objective was to compare abundance and density estimates for a small tortoise population derived using a total burrow count versus estimates obtained with line transect distance sampling (LTDS) using repeated surveys. We also compared results of the 2 survey methods using standard burrow-to-tortoise correction factors versus assessing occupancy of all burrows with a camera scope. In addition, we compared LTDS data obtained using a compass and measuring tape to define transects to those obtained using a Global Positioning System (GPS) and Personal Data Assistant (PDA) field computer to navigate transects. Line transect distance sampling with repeated surveys (both with a measuring tape and compass and with a GPS—PDA) yielded sufficient observations of tortoises to calculate population estimates. From 18% to 31% of burrows were occupied by tortoises as determined with the burrow camera. We found 25 burrows during the LTDS survey that we did not find in the total count survey, which demonstrated that the assumption of 100% detection for the total count was not met; hence, density or abundance measurements derived with this method were underestimates. We recommend using GPS—PDA technology, scoping all burrows detected, and using LTDS with repeated surveys to estimate abundance and density for small gopher tortoise populations.     

cameratrapR: An R package for estimating animal density using camera trapping data

• 1.Camera trapping plays an important role in wildlife surveys, and provides valuable information for estimation of population density. While mark-recapture techniques can estimate population density for species that can be individually recognized or marked, there are no robust methods to estimate density of species that cannot be individually identified.
• 2.We developed a new approach to estimate population density based on the simulation of individual movement within the camera grid. Simulated animals followed a correlated random walk with the movement parameters of segment length, angular deflection, movement distance and home-range size derived from empirical movement paths. Movement was simulated under a series of population densities. We used the Random Forest algorithm to determine the population density with the highest likelihood of matching the camera trap data. We developed an R package, cameratrapR, to conduct simulations and estimate population density.
• 3.Compared with line transect surveys and the random encounter model, cameratrapR provides more reliable estimates of wildlife density with narrower confidence intervals. Functions are provided to visualize movement paths, derive movement parameters, and plot camera trapping results.
• 4.The package allows researchers to estimate population sizes/densities of animals that cannot be individually identified and cameras are deployed in a grid pattern.

     

Scent Lure Effect on Camera-Trap Based Leopard Density Estimates

Density estimates for large carnivores derived from camera surveys often have wide confidence intervals due to low detection rates. Such estimates are of limited value to authorities, which require precise population estimates to inform conservation strategies. Using lures can potentially increase detection, improving the precision of estimates. However, by altering the spatio-temporal patterning of individuals across the camera array, lures may violate closure, a fundamental assumption of capture-recapture. Here, we test the effect of scent lures on the precision and veracity of density estimates derived from camera-trap surveys of a protected African leopard population. We undertook two surveys (a ‘control’ and ‘treatment’ survey) on Phinda Game Reserve, South Africa. Survey design remained consistent except a scent lure was applied at camera-trap stations during the treatment survey. Lures did not affect the maximum movement distances (p = 0.96) or temporal activity of female (p = 0.12) or male leopards (p = 0.79), and the assumption of geographic closure was met for both surveys (p >0.05). The numbers of photographic captures were also similar for control and treatment surveys (p = 0.90). Accordingly, density estimates were comparable between surveys (although estimates derived using non-spatial methods (7.28–9.28 leopards/100km²) were considerably higher than estimates from spatially-explicit methods (3.40–3.65 leopards/100km²). The precision of estimates from the control and treatment surveys, were also comparable and this applied to both non-spatial and spatial methods of estimation. Our findings suggest that at least in the context of leopard research in productive habitats, the use of lures is not warranted.     

Video and acoustic camera techniques for studying fish under ice: a review and comparison

Researchers attempting to study the presence, abundance, size, and behavior of fish species in northern and arctic climates during winter face many challenges, including the presence of thick ice cover, snow cover, and, sometimes, extremely low temperatures. This paper describes and compares the use of video and acoustic cameras for determining fish presence and behavior in lakes, rivers, and streams with ice cover. Methods are provided for determining fish density and size, identifying species, and measuring swimming speed and successful applications of previous surveys of fish under the ice are described. These include drilling ice holes, selecting batteries and generators, deploying pan and tilt cameras, and using paired colored lasers to determine fish size and habitat associations. We also discuss use of infrared and white light to enhance image-capturing capabilities, deployment of digital recording systems and time-lapse techniques, and the use of imaging software. Data are presented from initial surveys with video and acoustic cameras in the Sagavanirktok River Delta, Alaska, during late winter 2004. These surveys represent the first known successful application of a dual-frequency identification sonar (DIDSON^TM) acoustic camera under the ice that achieved fish detection and sizing at camera ranges up to 16 m. Feasibility tests of video and acoustic cameras for determining fish size and density at various turbidity levels are also presented. Comparisons are made of the different techniques in terms of suitability for achieving various fisheries research objectives. This information is intended to assist researchers in choosing the equipment that best meets their study needs.     

The effect of attractant lures in camera trapping: a case study of population estimates for the Iberian lynx (Lynx pardinus)

Capture–recapture analysis of camera trap data is a conventional method to estimate the abundance of free-ranging wild felids. Due to notorious low detection rates of felids, it is important to increase the detection probability during sampling. In this study, we report the effectiveness of attractants as a tool for improving the efficiency of camera trap sampling in abundance estimation of Iberian lynx. We developed a grid system of camera stations in which stations with and without attractant lures were spatially alternated across known Iberian lynx habitat. Of the ten individuals identified, five were detected at stations with no attractant (blind sets), and nine, at the lured stations. Thirty-eight percent of blind set station’s independent captures and 10?% of lured station’s independent captures resulted in photographs unsuitable for correct individual identification. The total capture probability at lured stations was higher than that obtained at blind set stations. The estimates obtained with blind set cameras underestimated the number of lynxes compared to lured cameras. In our study, it appears that the use of lures increased the efficiency of trail camera captures and, therefore, the accuracy of capture–recapture analysis. The observed failure to detect known individuals at blind set camera stations may violate capture–recapture assumptions and bias abundance estimates.     

Using remote underwater video to estimate freshwater fish species richness

Species richness records from replicated deployments of baited remote underwater video stations (BRUVS) and unbaited remote underwater video stations (UBRUVS) in shallow (<1 m) and deep (>1 m) water were compared with those obtained from using fyke nets, gillnets and beach seines. Maximum species richness (14 species) was achieved through a combination of conventional netting and camera‐based techniques. Chanos chanos was the only species not recorded on camera, whereas Lutjanus argentimaculatus, Selenotoca multifasciata and Gerres filamentosus were recorded on camera in all three waterholes but were not detected by netting. BRUVSs and UBRUVSs provided versatile techniques that were effective at a range of depths and microhabitats. It is concluded that cameras warrant application in aquatic areas of high conservation value with high visibility. Non‐extractive video methods are particularly desirable where threatened species are a focus of monitoring or might be encountered as by‐catch in net meshes.     

Potentiality and limitations of N-mixture and Royle-Nichols models to estimate animal abundance based on noninstantaneous point surveys

Reliable and accurate information on animal abundance is fundamental for the conservation and management of wildlife. Recently, a number of innovative devices (such as camera traps) have been widely used in field surveys and have largely improved survey efficiency. However, these devices often constitute noninstantaneous point surveys, resulting in the multiple counts of the same animal individuals within a single sampling occasion (i.e., false-positive errors). Many commonly-used statistical models do not explicitly account for the false-positive error, with its effects on estimates being poorly understood. Here, I tested the performance of the commonly-used Poisson-binomial N-mixture and the Royle-Nichols model in the presence of both false-positive and negative errors (i.e., individuals in a population might not be detected). I also implemented the Poisson-Poisson mixture model in the Bayesian framework to evaluate its reliability. The results of the simulation using random walks based on Ornstein-Uhlenbeck processes showed that the Poisson-binomial model was not robust to false-positive errors. In comparison, the Royle-Nichols and Poisson-Poisson models provided reasonable estimates of the number of animals whose home range included the survey point. However, the number of animals whose home range included the survey point is inherently influenced by the size of animal home ranges, and thus cannot be used as a surrogate of animal density. Although the N-mixture and Royle-Nichols models are widely used, their utility might be restricted by this limitation. In conclusion, studies should clearly define the objective of surveys and carefully consider whether the models used are valid.     

Distance and size matters: A comparison of six wildlife camera traps and their usefulness for wild birds

Camera traps are increasingly used in ecological research. However, tests of their performance are scarce. It is already known from previous work that camera traps frequently fail to capture visits by animals. This can lead to a misinterpretation of ecological results such as density estimates or predation events. While previous work is mainly based on mammals, for birds, no data about if and how camera traps can be successfully used to estimate species diversity or density are available. Hence, the goal of our study was an empirical validation of six different camera traps in the field. We observed a total number of N = 4567 events (independent visits of a bird) in 100 different sessions from March 2017 until January 2018 while camera traps were deployed. In addition, N = 641 events are based on a comparison of the two close‐up camera traps especially designed for birds. These events were all directly observed by the authors. Thus, the cameras can be compared against the human observer. To give an overall assessment and a more generalizable result, we combined the data from the six camera traps and showed that bird size category (effect size = 0.207) and distance (effect size = 0.132) are the most important predictors for a successful trigger. Also, temperature had a small effect, and flock size had an impact with larger flocks being captured more often. The approach of the bird, whether it approached the camera frontally or laterally had no influence. In Table 8 , we give some recommendations, based on our results, at which distances camera traps should be placed to get a 25%, 50%, and 75% capture rate for a given bird size.     

A camera trap assessment of terrestrial vertebrates in Bwindi Impenetrable National Park,Uganda

We placed camera traps for a month at sixty locations in Bwindi Impenetrable National Park to determine the species composition and distribution of medium‐to‐large terrestrial vertebrates. A total of 15912 images were recorded from 1800 camera trap days. These provided a total of 625 and 338 camera events when filtered by hour and day, respectively. Twenty mammal species were recorded from 594 and 314 camera events by hour and day, respectively. Four bird species were recorded from 31 and 24 camera events by hour and day, respectively. The African golden cat Profelis aurata Temminck was recorded from 27 and nineteen camera events by hour and day, respectively. The black‐fronted duiker Cephalophus nigrifrons Gray was most frequently photographed with 179 and 65 camera events by hour and day, respectively. Analyses reveal two species possessed a significantly interior‐biased distribution. One species showed an edge‐biased pattern. Five species were detected to have significantly biased altitudinal distributions with higher elevations. Distance to park edge and elevation can significantly influence species distribution. The selective use of the park limits the area that each species utilizes, with implications for maximum population sizes and viability. Our observations provide a baseline for long‐term terrestrial vertebrate monitoring in Bwindi.     

Using nest captures and video cameras to estimate survival and abundance of breeding Piping Plovers Charadrius melodus

The estimation of abundance is fundamental to ecology and conservation but often is difficult or impossible to accomplish reliably. Recent improvements in wildlife cameras and ecological modelling have allowed for improved accuracy in estimates of abundance. In this study, we paired nest captures and high-definition nest video camera monitoring with modelling for a novel approach to estimate survival and abundance of threatened Piping Plovers Charadrius melodus breeding on Missouri River sandbars. From 2005 to 2014, we captured individuals on nests and uniquely marked them and recaptured previously marked individuals. In 2015–2017, we resighted marked individuals using small, high-definition video cameras deployed at nests, and counted the number of marked and unmarked breeding individuals associated with nests. We estimated apparent survival and derived estimates of the abundance of breeding individuals and population growth each year using a state-space Jolly–Seber superpopulation model with the addition of a binomial band ratio model for data collected using nest video cameras. Apparent survival averaged 0.73 ± 0.03 (mean ± sd) throughout the study. The number of breeding individuals varied, with the population increasing from 2012 to 2017 following a major habitat creation event. This study provides one of the few examples of camera data being used to produce demographic parameter and abundance estimates for an avian species. The camera and modelling methods described in this study may be applicable to other avian species in which some portion of the breeding population is uniquely marked.     

利用红外相机调查北京松山国家级自然保护区的野生动物物种

红外相机是监测野生动物的有效工具,目前广泛用于兽类资源调查以及动物损害、鸟巢生态学、种群评估、行为生态学等研究领域。为了调查北京松山国家级自然保护区的野生动物,于2010年5—12月采用红外相机进行系统调查,在210个位点放置了红外相机,每台相机在每个地点上放置一个月。研究期间共拍摄到照片2203张,其中73%为兽类,12%为鸟类,13%为工作人员,2%为其它人员。共鉴定出17种兽类(分属5目10科)以及36种鸟类(分属5目17科)。兽类中拍摄率最高的前5种动物分别是岩松鼠(Sciurotamias davidianus)、猪獾(Arctonyx collaris)、豹猫(Prionailurus bengalensis)、狗獾(Meles meles)和貉(Nyctereutes procyonoides),鸟类中拍摄率最高的前5种动物分别是紫啸鸫(Myophonus caeruleus)、雉鸡(Phasianus colchicus)、松鸦(Garrulus glandarius)、勺鸡(Pucrasia macrolopha)和宝兴歌鸫(Turdus mupinensis)。红外相机在不同海拔、不同植被类型以及不同月份所拍摄动物的拍摄率不同:在1000—1400m的海拔段,拍摄率显著高于低海拔(600—1000m)以及中高海拔(1400—1700m);在阔叶林中的拍摄率最高,在针叶林、针阔混交林和灌丛中的拍摄率相似;秋季(8—10月)拍摄率较高,夏季(6—7月)次之,冬季(11—12月)最低。红外相机拍摄到的累积物种数与相机放置的时间成上升曲线,但曲线的增长速率逐渐变缓。研究表明红外相机适合于调查和监测大中型兽类和部分鸟类,所采集的动物数据以及拍摄的图片和视频资料将为保护区的监测、科研和环境教育提供资料。讨论了应用红外相机调查和监测野生动物的技术细节。     

基于红外相机技术调查桃红岭梅花鹿国家级自然保护区鸟兽多样性

2017年3月—2018年3月期间,采用红外相机技术调查了桃红岭梅花鹿国家级自然保护区内鸟类和兽类的物种多样性。红外相机监测期间,共累计4442个相机日,获得野生动物独立有效照片1003张,其中兽类独立有效照片683张,共4目9科16种;鸟类独立有效照片320张,共9目23科46种;保护区内兽类相对丰富度最高的是小麂(Muntiacus reevesi),鸟类丰富度最高的是黑领噪鹛(Garrulax perspicillatus);其中国家Ⅰ级保护动物有2种,梅花鹿(Cervus nippon)和白颈长尾雉(Syrmaticus ellioti);国家Ⅱ级保护动物有6种,分别为小灵猫(Viverricula indica)、勺鸡(Pucrasia macrolopha)、白鹇(Lophura nycthemera)、草鸮(Tyto longimembris)、红角鸮(Otus sunia)和松雀鹰(Accipiter virgatus)。红外相机在灌丛中拍摄率最高,在草甸中拍摄率最低。通过稀疏外推曲线对物种多样性进行估计可得,保护区实际的物种数远大于监测到的物种数,因此有待继续进行长期监测。通过物种与相机位点的PCA排序图可知,各个相机位点和物种的相关性较强。调查结果为保护区提供了重要的兽类和鸟类资源信息,为保护区对野生动物的有效管理和长期监测提供了数据支持。     

Efficiency of time-lapse intervals and simple baits for camera surveys of wild pigs

Growing concerns surrounding established and expanding populations of wild pigs (Sus scrofa) have created the need for rapid and accurate surveys of these populations. We conducted surveys of a portion of the wild pig population on Fort Benning, Georgia, to determine if a longer time-lapse interval than had been previously used in surveys of wild pigs would generate similar detection results. We concurrently examined whether use of soured corn at camera sites affected the time necessary for pigs to locate a new camera site or the time pigs remained at a site. Our results suggest that a 9-min time-lapse interval generated dependable detection results for pigs and that soured corn neither attracted pigs to a site any quicker than plain, dry, whole-kernel corn, nor held them at a site longer. Maximization of time-lapse interval should decrease data and processing loads, and use of a simple, available bait should decrease cost and effort associated with more complicated baits; combination of these concepts should increase efficiency of wild pig surveys. © 2011 The Wildlife Society.