Spotlight surveys for white-tailed deer: Monitoring panacea or exercise in futility?

Many monitoring programs for white-tailed deer (Odocoileus virginianus) on both private and public lands across the United States have long relied on the use of road-based spotlight surveys for monitoring population size and trends. Research has suggested spotlight surveys are ineffective and that road-based surveys for deer are biased because of highly variable detection rates. To evaluate variability in detection rates relative to the assumption that repeated surveys along roads will provide reliable trend data for use in calculating deer density estimates, we collected 5 years of thermal-imager and spotlight survey data using a multiple-observer, closed-capture approach. Using a Huggin's closed capture model, data bootstrapping, and variance components analyses, our results suggest that density estimates for white-tailed deer generated from data collected during road-based spotlight surveys are likely not reflective of the standing deer population. Detection probabilities during individual spotlight surveys ranged from 0.00 to 0.80 (median = 0.45) across all surveys, and differed by observer, survey, management unit, and survey transect replicate. Mean spotlight detection probability (0.41) and process standard deviation (0.12) estimates indicated considerable variability across surveys, observers, transects, and years, which precludes the generation of a correction factor or use of spotlight data to evaluate long-term trends at any scale. Although recommended by many state, federal, and non-governmental agencies, our results suggest that the benefit of spotlight survey data for monitoring deer populations is limited and likely represents a waste of resources with no appreciable management information gained. © 2012 The Wildlife Society.     

Variance of Stratified Survey Estimators With Probability of Detection Adjustments

Abstract: Estimates of wildlife population sizes are frequently constructed by combining counts of observed animals from a stratified survey of aerial sampling units with an estimated probability of detecting animals. Unlike traditional stratified survey designs, stratum-specific estimates of population size will be correlated if a common detection model is used to adjust counts for undetected animals in all strata. We illustrate this concept in the context of aerial surveys, considering 2 cases: 1) a single-detection parameter is estimated under the assumption of constant detection probabilities, and 2) a logistic-regression model is used to estimate heterogeneous detection probabilities. Naïve estimates of variance formed by summing stratum-specific estimates of variance may result in significant bias, particularly if there are a large number of strata, if detection probabilities are small, or if estimates of detection probabilities are imprecise. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):837–844; 2008)     

Using spotlight observations to predict resource selection and abundance for white-tailed deer

Spotlight surveys for white-tailed deer (Odocoileus virginianus) can yield large presence-only datasets applicable to a variety of resource selection modeling procedures. By understanding how populations distribute according to a given resource for a reference area, density and abundance can be predicted across new areas assuming the relationship between habitat quality (measured by an index of selection) and species distribution are equivalent. Habitat-based density estimators have been applied to wildlife species and are useful for addressing conservation and management concerns. Although achieving reliable population estimates is a primary goal for spotlighting studies, presence-only models have yet to be applied to spotlight data for estimating habitat selection and abundance for deer. From 2012 to 2017, we conducted spring spotlight surveys in each of 99 counties in Iowa, USA, and collected spatial locations for 20,149 groups of deer (n = 71,323 individuals). We used a resource selection function (RSF) based on deer locations to predict the relative probability of use for deer at the population level and to estimate statewide abundance. The number of deer observed statewide increased significantly with increasing RSF value for all years and the mean RSF value along survey transects explained 59% of the variability in county-level deer counts, indicating that a functional response between habitat quality and deer distribution existed at landscape scales. We applied our RSF to a habitat-based density estimator (extrapolation) and zero-inflated Poisson (ZIP) and negative binomial (ZINB) count models to predict statewide abundance from spotlight counts. Population estimates for 2012 were variable, indicating that atypical weather conditions may affect spotlight counts and population estimates in some years. For 2013–2017, we predicted a mean population of 439,129 (95% CI ∼ ± 55,926), 440,360 (∼ ± 43,676), and 465,959 (∼ ± 51,242) deer across years for extrapolation, ZIP, and ZINB models, respectively. Estimates from all models were not significantly different than estimates from an existing deer population accounting model in Iowa for 2013 and 2016, and differed by <76,000 deer for all models from 2013–2017. Extrapolation and ZIP models performed similarly and differed by <2,897 deer across all years, whereas ZINB models showed inconsistencies in model convergence and precision of estimates. Our results indicate that presence-only models are capable of producing reliable and precise estimates of resource selection and abundance for deer at broad landscape scales in Iowa and provide a tool for estimating deer abundance in a spatially explicit manner. © 2019 The Wildlife Society.     

Detection Probabilities for Ground-Based Breeding Waterfowl Surveys

ABSTRACT Current methods for conducting ground-based surveys of breeding waterfowl pairs make the unlikely assumption that detection probabilities are constant and approach 100%. To test this assumption, we conducted independent double-observer pair surveys in North Dakota, USA, to evaluate sources of variation in detection probabilities for 8 common species of prairie-nesting ducks. An experienced observer had 0.911 detection probability averaged over all 8 species (range = 0.866-0.944) versus 0.790 (range = 0.537-0.890) for a novice observer. Detection probabilities also varied substantially among species, but patterns were not consistent between observers. Detection probabilities declined as number of ducks per wetland increased, presumably due to difficulty in identifying large numbers of flushing ducks. Other covariates affecting detection probabilities included size of social groups, precipitation, survey methodology (roadside vs. walk-up), cloud cover, time of day, and amount of wetland vegetation, but these covariates only affected detection probabilities by 2–5%. Our results demonstrated that the assumption of 100% detection probabilities for ground-based waterfowl counts was clearly false and surveys based on this erroneous assumption underestimated population size by 10–29%. We recommend that future investigators measure detection probabilities explicitly by using double-observer methodologies.     

An examination of observer bias as a source of error in surveys of seagrass shoots

Abstract Mensurative experiments investigated the effects of different observers on estimates of the density of shoots of two species of seagrass: Posidonia australis Hook and Zostera capricorni Aschers. Balanced programmes of sampling were used to examine variation in counts of seagrass shoots attributable to different observers, sizes of quadrats, depths and locations within large beds of each species of seagrass. A separate experiment examined differences between novice observers and a more experienced observer, when an ‘optimal’ size of sampling unit was used. Estimated densities of Zostera shoots varied inconsistently among observers, quadrats, depths and locations. Differences between observers were not affected by the size of quadrat used to count Posidonia shoots, but varied between locations in the seagrass bed. Experience had only a minor impact on biases. Only two of 12 novices produced counts that were different from the experienced observer. These results emphasize the importance of considering both accuracy and precision in the design of field studies of seagrasses.     

Using soundscape recordings to estimate bird species abundance, richness, and composition

ABSTRACT Point counts are the most frequently used technique for sampling bird populations and communities, but have well‐known limitations such as inter‐ and intraobserver errors and limited availability of expert field observers. The use of acoustic recordings to survey birds offers solutions to these limitations. We designed a Soundscape Recording System (SRS) that combines a four‐channel, discrete microphone system with a quadraphonic playback system for surveying bird communities. We compared the effectiveness of SRS and point counts for estimating species abundance, richness, and composition of riparian breeding birds in California by comparing data collected simultaneously using both methods. We used the temporal‐removal method to estimate individual bird detection probabilities and species abundances using the program MARK. Akaike's Information Criterion provided strong evidence that detection probabilities differed between the two survey methods and among the 10 most common species. The probability of detecting birds was higher when listening to SRS recordings in the laboratory than during the field survey. Additionally, SRS data demonstrated a better fit to the temporal‐removal model assumptions and yielded more reliable estimates of detection probability and abundance than point‐count data. Our results demonstrate how the perceptual constraints of observers can affect temporal detection patterns during point counts and thus influence abundance estimates derived from time‐of‐detection approaches. We used a closed‐population capture–recapture approach to calculate jackknife estimates of species richness and average species detection probabilities for SRS and point counts using the program CAPTURE. SRS and point counts had similar species richness and detection probabilities. However, the methods differed in the composition of species detected based on Jaccard's similarity index. Most individuals (83%) detected during point counts vocalized at least once during the survey period and were available for detection using a purely acoustic technique, such as SRS. SRS provides an effective method for surveying bird communities, particularly when most species are detected by sound. SRS can eliminate or minimize observer biases, produce permanent records of surveys, and resolve problems associated with the limited availability of expert field observers.     

Methodology matters when estimating deer abundance: a global systematic review and recommendations for improvements

Deer (Cervidae) are key components of many ecosystems and estimating deer abundance or density is important to understanding these roles. Many field methods have been used to estimate deer abundance and density, but the factors determining where, when, and why a method was used, and its usefulness, have not been investigated. We systematically reviewed journal articles published during 2004–2018 to evaluate spatio-temporal trends in study objectives, methodologies, and deer abundance and density estimates, and determine how they varied with biophysical and anthropogenic attributes. We also reviewed the precision and bias of deer abundance estimation methods. We found 3,870 deer abundance and density estimates. Most estimates (58%) were for white-tailed deer (Odocoileus virginianus), red deer (Cervus elaphus), and roe deer (Capreolus capreolus). The 6 key methods used to estimate abundance and density were pedestrian sign (track or fecal) counts, pedestrian direct counts, vehicular direct counts, aerial direct counts, motion-sensitive cameras, and harvest data. There were regional differences in the use of these methods, but a general pattern was a temporal shift from using harvest data, pedestrian direct counts, and aerial direct counts to using pedestrian sign counts and motion-sensitive cameras. Only 32% of estimates were accompanied by a measure of precision. The most precise estimates were from vehicular spotlight counts and from capture–recapture analysis of images from motion-sensitive cameras. For aerial direct counts, capture–recapture methods provided the most precise estimates. Bias was robustly assessed in only 16 studies. Most abundance estimates were negatively biased, but capture–recapture methods were the least biased. The usefulness of deer abundance and density estimates would be substantially improved by 1) reporting key methodological details, 2) robustly assessing bias, 3) reporting the precision of estimates, 4) using methods that increase and estimate detection probability, and 5) staying up to date on new methods. The automation of image analysis using machine learning should increase the accuracy and precision of abundance estimates from direct aerial counts (visible and thermal infrared, including from unmanned aerial vehicles [drones]) and motion-sensitive cameras, and substantially reduce the time and cost burdens of manual image analysis.     

Double-observer approach to estimating egg mass abundance of pool-breeding amphibians

Interest in seasonally flooded pools, and the status of associated amphibian populations, has initiated programs in the northeastern United States to document and monitor these habitats. Counting egg masses is an effective way to determine the population size of pool-breeding amphibians, such as wood frogs (Rana sylvatica) and spotted salamanders (Ambystoma maculatum). However, bias is associated with counts if egg masses are missed. Counts unadjusted for the proportion missed (i.e., without adjustment for detection probability) could lead to false assessments of population trends. We used a dependent double-observer method in 2002–2003 to estimate numbers of wood frog and spotted salamander egg masses at seasonal forest pools in 13 National Wildlife Refuges, 1 National Park, 1 National Seashore, and 1 State Park in the northeastern United States. We calculated detection probabilities for egg masses and examined whether detection probabilities varied by species, observers, pools, and in relation to pool characteristics (pool area, pool maximum depth, within-pool vegetation). For the 2 years, model selection indicated that no consistent set of variables explained the variation in data sets from individual Refuges and Parks. Because our results indicated that egg mass detection probabilities vary spatially and temporally, we conclude that it is essential to use estimation procedures, such as double-observer methods with egg mass surveys, to determine population sizes and trends of these species.     

Estimating abundance and population trends when detection is low and highly variable: A comparison of three methods for the Hermann's tortoise

Assessing population trends is a basic prerequisite to carrying out adequate conservation strategies. Selecting an appropriate method to monitor animal populations can be challenging, particularly for low-detection species such as reptiles. This study compares 3 detection-corrected abundance methods (capture–recapture, distance sampling, and N-mixture) used to assess population size of the threatened Hermann's tortoise. We used a single dataset of 432 adult tortoise observations collected at 118 sampling sites in the Plaine des Maures, southeastern France. We also used a dataset of 520 tortoise observations based on radiotelemetry data collected from 10 adult females to estimate and model the availability (g0) needed for distance sampling. We evaluated bias for N-mixture and capture–recapture, by using simulations based on different values of detection probabilities. Finally, we conducted a power analysis to estimate the ability of the 3 methods to detect changes in Hermann's tortoise abundances. The abundance estimations we obtained using distance sampling and N-mixture models were respectively 1.75 and 2.19 times less than those obtained using the capture–recapture method. Our results indicated that g0 was influenced by temperature variations and can differ for the same temperature on different days. Simulations showed that the N-mixture models provide unstable estimations for species with detection probabilities <0.5, whereas capture–recapture estimations were unbiased. Power analysis showed that none of the 3 methods were precise enough to detect slow population changes. We recommend that great care should be taken when implementing monitoring designs for species with large variation in activity rates and low detection probabilities. Although N-mixture models are easy to implement, we would not recommend using them in situations where the detection probability is very low at the risk of providing biased estimates. Among the 3 methods allowing estimation of tortoise abundances, capture–recapture should be preferred to assess population trends. © 2013 The Wildlife Society.     

Distance models as a tool for modelling detection probability and density of native bumblebees

Effective monitoring of native bee populations requires accurate estimates of population size and relative abundance among habitats. Current bee survey methods, such as netting or pan trapping, may be adequate for a variety of study objectives but are limited by a failure to account for imperfect detection. Biases due to imperfect detection could result in inaccurate abundance estimates or erroneous insights about the response of bees to different environments. To gauge the potential biases of currently employed survey methods, we compared abundance estimates of bumblebees (Bombus spp.) derived from hierarchical distance sampling models (HDS) to bumblebee counts collected from fixed‐area net surveys (“net counts”) and fixed‐width transect counts (“transect counts”) at 47 early‐successional forest patches in Pennsylvania. Our HDS models indicated that detection probabilities of Bombus spp. were imperfect and varied with survey‐ and site‐covariates. Despite being conspicuous, Bombus spp. were not reliably detected beyond 5 m. Habitat associations of Bombus spp. density were similar across methods, but the strength of association with shrub cover differed between HDS and net counts. Additionally, net counts suggested sites with more grass hosted higher Bombus spp. densities whereas HDS suggested that grass cover was associated with higher detection probability but not Bombus spp. density. Density estimates generated from net counts and transect counts were 80%–89% lower than estimates generated from distance sampling. Our findings suggest that distance modelling provides a reliable method to assess Bombus spp. density and habitat associations, while accounting for imperfect detection caused by distance from observer, vegetation structure, and survey covariates. However, detection/non‐detection data collected via point‐counts, line‐transects and distance sampling for Bombus spp. are unlikely to yield species‐specific density estimates unless individuals can be identified by sight, without capture. Our results will be useful for informing the design of monitoring programs for Bombus spp. and other pollinators.     

Estimating Detection Probabilities of Waterfowl Broods From Ground-Based Surveys

ABSTRACT Brood:pair ratios could provide an economical method for assessing spatial or temporal variation in waterfowl productivity, but such estimators are severely biased by incomplete detection of broods. We conducted 3 sequential counts of 1,357 waterfowl broods in northeastern North Dakota, USA, and used closed-population mark-recapture models to estimate total brood abundance while controlling for variation in detection probabilities (p). Blue-winged teal (Anas discors) broods had the lowest average detection probability (p = 0.305), whereas diving-duck broods had the highest average detectability (p = 0.571). Detection was generally highest in morning or evening, but temporal patterns varied among species and there was no survey window that maximized detection probabilities for all species. Detection probabilities averaged 0.108 (SD = 0.056) higher for an experienced observer versus an inexperienced observer. Detection probabilities were 0.044 higher for roadside versus walk-up surveys and increased with increasing brood size, total brood abundance, survey date, wind speed, temperature, cloud cover, and amount of time spent surveying each wetland. Detection probabilities declined with increasing wetland size and amount of tall peripheral vegetation. Our mark-recapture results indicated that a traditional unreplicated brood survey would have missed 67.5% of estimated broods, summed over all species. Use of closed-population mark-recapture techniques provided an effective method for reducing this bias and identifying and quantifying factors that reduce detection probabilities of waterfowl broods. We recommend that future brood surveys incorporate 2 or 3 temporally segregated replicate counts to allow for formal estimation of detection probabilities.     

Variable effect of playback of chickadee mobbing calls on detection probability of boreal forest birds

Modification of the point count survey method to include playback of songbird mobbing calls in an attempt to increase detection probabilities has met with mixed success. We compared detection probabilities for boreal forest songbirds using traditional point count methods and counts using broadcasts of the mobbing calls of Black‐capped Chickadees (Poecile atricapillus) in an attempt to increase detection probability. We conducted 594 point counts during the 2010 breeding season in Newfoundland, Canada. Each point count consisted of an 8‐min silent observation period followed by an 8‐min broadcast of Black‐capped Chickadee mobbing calls. Occupancy model results showed that response to playback broadcast varied across species, with detection probabilities higher for seven of 17 species during the silent portions of point counts and three species more likely to be detected during playback intervals. For all species, the number of visual detections increased during periods of playback and, averaged across species, individuals were >6 times more likely to be seen during the playback period than during the silent period. Differences in detection probability among observers were apparent during both silent and playback periods. We suggest that using playback of chickadee mobbing calls during point count surveys of common boreal forest songbird species may be most beneficial when visual detection is important. However, playback may also be useful for species‐specific surveys during periods when birds are less likely to be vocal or for studies of less common species with chronically low detection probabilities. A combined silent and playback approach could also be useful, although observer and species differences should be accounted for if comparing data across species or studies.     

It counts who counts: an experimental evaluation of the importance of observer effects on spotlight count estimates

Spotlight surveys conducted by volunteers is a promising method to assess the abundance of nocturnally active mammals, but estimates are subject to bias if different observer groups differ in their ability to detect animals in the dark. We quantified the variation amongst volunteer spotlight observers with respect to their ability to detect and estimate distance to realistic animal silhouettes at different distances. Detection probabilities were higher for observers experienced in spotlighting mammals than for inexperienced observers, higher for observers with a hunting background compared with non-hunters and decreased as function of age but were independent of sex or educational background. If observer-specific detection probabilities were applied to real counting routes, point count estimates from inexperienced observers without a hunting background would only be 43 % (95 % CI, 39–48) of what inexperienced hunters with a hunting background would obtain and 29 % (25–33) of what experienced spotlight observers would detect. Mean estimated distances to objects did not deviate from true distances (no bias) but were highly imprecise. Female non-hunters estimated distances less precisely than other observers and precision increased with age. The study shows that observer effects may influence abundance estimates and underlines the importance of testing and accounting for observer effects when designing citizen science-based population survey programmes.     

How accurate are single site transect data for monitoring butterfly trends? Spatial and temporal issues identified in monitoring Lasiommata megera

Multiple transect counts following Butterfly Monitoring Scheme (UKBMS) guidelines and Jolly–Seber estimates of population size were used to monitor the abundance of second generation Lasiommata megera on a single site in southern England. The two methods resulted in different patterns of emergence being detected. The proportion of the population (estimated by Jolly–Seber) recorded with transect counts depended on the time of day and weather with afternoon transect counts best recording the trend in abundance over the flight period, but even then counts recorded a variable fraction of the population (6.2–51.3%). Increasing the frequency with which transect counts are carried out per week reduced variation and increased the fit of transect counts to Jolly–Seber generated population estimates. However, indices of abundance generated from randomly selected transect counts for L. megera within sampling weeks varied 4-fold and indices for other butterfly species were also highly variable. For L. megera, transect count variability is attributed to non-representative placement of the transect route and changes in the behaviour and spatial distribution in relation to population size and season. We suggest that transect counts need to be fully validated before the data are used to monitor changes of butterfly populations at individual sites.     

Integrating distance sampling with minimum counts to improve monitoring

Minimum counts are commonly used to estimate population size and trend for wildlife conservation and management; however, the scope of inference based on such data is limited by untestable assumptions regarding the detection process. Alternative approaches, such as distance sampling, occupancy surveys, and repeated counts, can be employed to produce detection-corrected estimates of population parameters. Unfortunately, these approaches can be more complicated and costly to implement, potentially limiting their use. We explored a conceptual framework linking datasets collected at different spatial scales under different survey designs, with the goal of improving inference. Specifically, we link landscape-scale distance sampling surveys with local-scale minimum counts in an integrated modeling framework to estimate mountain goat (Oreamnos americanus) abundance at both the local and regional scale in south-central Alaska, USA, and provide an estimate of detection probability (i.e., sightability) for the minimum counts. Estimated sightability for the minimum count surveys was 0.67 (95% credible interval [CrI] = 0.52–0.83) and abundance for the entire area was 5,600 goats (CV = 9%), both in broad agreement with estimates from previous studies. Abundance estimates at the local scale (i.e., individual min. count unit) were reasonably precise ( = 18%), suggesting the integrated approach can increase the amount of information produced at both spatial scales by linking minimum count approaches with more rigorous survey designs. We propose that our integrated approach may be implemented in the context of a modified split-panel monitoring design by altering survey protocols to include frequent minimum counts within local count units and intermittent but more rigorous survey designs with inference to the entire study area or population of interest. Doing so would provide estimates of abundance with appropriate measures of uncertainty at multiple spatial scales, thereby improving inference for population monitoring and management. © 2019 The Wildlife Society.     

Estimation of Detection Probability in Manatee Aerial Surveys at a Winter Aggregation Site

Abstract: Estimating components of detection probability is crucial to improving the design of aerial surveys for wildlife populations, and this is especially true for species of marine mammals that are threatened or endangered. To evaluate the probability that Florida manatees (Trichechus manatus latirostris) will be detected by observers during aerial surveys, we conducted 6 series of survey flights, during mornings and afternoons on 14-16 consecutive days over the Tampa Electric Company's (TECO) Big Bend power plant discharge canal in Tampa Bay, Florida, USA (winter 2000 through 2003). Our objective was to understand how our ability to detect manatees at a winter aggregation site affects aerial survey counts, so that we may improve techniques for estimating manatee population size. We estimated the probability that manatees would be present at the warm-water discharge of the plant during winter cold fronts and estimated the overall detection probability of manatees present at the plant and the 2 components that make up the probability of detection (the probability of being available and the probability of being detected given they are available). We used telemetry tags and marker flags (n = 15) to facilitate capture-recapture analyses. The probability that marked manatees would be at the plant varied from 48% to 68% across flight series and was inversely related to the ambient water temperature. Based on sightings of marked animals, estimates of the overall probability of detecting a manatee ranged from 45% to 69% across flight series (x̄ = 58%, n = 6). The probability that a manatee would be available to an observer ranged from 73% to 94% across flight series (x̄ = 83%) but was constant among years (83%, 81%, and 78%; x̄ = 81%). The probability that an available manatee would be detected by an aerial observer was variable across flight series (55-95%) and years (73%, 86%, and 66%, x̄ = 73%). Independent estimates of the probability that a manatee would be available to the observer on one pass were obtained from time-depth data loggers and ranged from 5% to 33% (x̄ = 19%, SE = 3.7%), and the probability that a manatee would be available during ≥1 of 10 passes ranged from 41% to 98% (x̄ = 88%, 95% confidence bounds 0.71-0.95). We adjusted survey counts using measures of detectability. Although corrected counts presented here are site-specific, adjusting counts based on detection probability will greatly improve reliability of population estimates from all aerial surveys. Special sampling to estimate components of detection probability should be built into all aerial surveys to ensure that reliable and unbiased information on species abundance is used to evaluate wildlife populations.     

Variation in the herd composition counts of sika deer

Herd composition counts (HCC) are commonly used to assess population status in deer. We evaluated the reliability of HCC of sika deer (Cervus nippon Temminck) using repeated counts and by comparing estimated sex ratios and calf-to-female ratios of marked deer on Nakanoshima Island, Hokkaido, Japan between April 1999 and October 2000. Although both total counts and sex and age ratios fluctuated greatly by month, seasonal changes showed a relatively small variance. This suggested that seasonal changes in behavior within sex and age classes contributed to biased ratio estimates obtained from HCC. Route counts should be used as a relative population abundance index with estimates of detection probability, especially for females. Adult sex ratios and age ratios from HCC were unbiased during the rutting season (October–November), and age ratios in spring could be used if yearlings are counted as adults.     

黑龙江省完达山东部林区东北虎猎物生物量

研究一个地区猎物种群生物量能否满足捕食动物种群数量的需求,这对于了解濒危大型食肉动物是否受到来自于食物缺乏的威胁和制定相应的保护措施极其重要。为了掌握黑龙江省完达山东部林区东北虎食物需求与猎物生物量之间的关系,于2008年冬季至2009早春积雪覆盖期采用随机布设样线,通过收集有蹄类动物在雪地上留下的足迹等活动的方法,在东方红林业局和迎春林业局管辖境内3 692.06 km²的区域布设大样方48个,并在大样方里共布设样线240条开展有蹄类动物种群数量调查,确定东北虎猎物生物量。调查结果表明:研究地区野猪(成体502 606只,亚成体209 210只)、马鹿(成体331 357只,亚成体67 72只)和狍子(成体810 815只,亚成体202 203只)的生物量分别为74 767.50 87 825.00 kg、79 744.50 85 984.50 kg 和 31 337.00 31 525.50 kg,3种有蹄类动物生物量共计1 85 849.00 205 335.00 kg。研究地区猎物总生物量为209 619.89 231 598.24 kg。如果按8%的生物提供给东北虎,3种主要猎物生物量可满足5.22 6.92只东北虎个体的食物需求,研究地区猎物总生物量则可满足5.89 7.81只东北虎个体的食物需求。此外,对足迹遇见率与抽样强度、抽样强度与足迹遇见率的均值标准误差之间关系的分析表明,在完达山东部林区布设120条样线(抽样距离600 km)、150条样线(抽样距离750 km)和115条样线(抽样距离675 km)能满足野猪、马鹿、狍子种群数量调查准确性的最低需求。     

The use of block counts,mark-resight and distance sampling to estimate population size of a mountain-dwelling ungulate

Population size estimates represent indispensable tools for many research programs and for conservation or management issues. Mountain ungulates in open areas are often surveyed through ground counts that normally underestimate population size. While the use of sample counts is desirable, few studies have compared different probabilistic approaches to estimate population size in this taxon. We compared the size estimates of a male population of Alpine chamois using mark-resight and line transect sampling methods, while block counts were used to obtain the minimum number of males alive in the study area. Surveys were conducted within the Gran Paradiso National Park (Italy), in August–September 2013, using block counts along purposely selected trails and vantage points, mark-resight over 5 consecutive resightings from vantage points and trails, and line transect sampling along 12 transects repeated 8 times. Block counts yielded a minimum number of males alive in the population of n = 72 individuals. This value was greater than the upper bound of the 95 % confidence interval achieved using line transect sampling {n = 54, CV = 14 % [95 % CI (40, 71)]} while mark-resight yielded a more realistic result of n = 93 individuals {CV = 18 % [95 % CI (63, 137)]}. Our results suggest that line transect sampling performed poorly in the Alpine environment, leading to underestimates of population size, likely due to violations of some assumptions imposed by the rugged nature of the terrain. The mark-resight yielded lower precision, possibly due to the limited number of marked individuals and resighting occasions, but it provided robustness and accurate estimates as marks were evenly distributed among animals.