Evaluation of three methods to estimate density and detectability from roadside point counts

Roadside point counts are often used to estimate trends of bird populations. The use of aural counts of birds without adjustment for detection probability, however, can lead to incorrect population trend estimates. We compared precision of estimates of density and detectability of whistling northern bobwhites (Colinus virginianus) using distance sampling, independent double-observer, and removal methods from roadside surveys. Two observers independently recorded each whistling bird heard, distance from the observer, and time of first detection at 362 call-count stops in Ohio. We examined models that included covariates for year and observer effects for each method and distance from observer effects for the double-observer and removal methods using Akaike's Information Criterion (AIC). The best model of detectability from distance sampling included observer and year effects. The best models from the removal and double-observer techniques included observer and distance effects. All 3 methods provided precise estimates of detection probability (CV = 2.4–4.4%) with a range of detectability of 0.44–0.95 for a 6-min survey. Density estimates from double-observer surveys had the lowest coefficient of variation (2005 = 3.2%, 2006 = 1.7%), but the removal method also provided precise estimates of density (2005 CV = 3.4%, 2006 CV = 4.8%), and density estimates from distance sampling were less precise (2005 CV = 9.6%, 2006 CV = 7.9%). Assumptions of distance sampling were violated in our study because probability of detecting bobwhites near the observer was <1 or the roadside survey points were not randomly distributed with respect to the birds. Distances also were not consistently recorded by individual members of observer pairs. Although double-observer surveys provided more precise estimates, we recommend using the removal method to estimate detectability and abundance of bobwhites. The removal method provided precise estimates of density and detection probability and requires half the personnel time as double-observer surveys. Furthermore, the likelihood of meeting model assumptions is higher for the removal survey than with independent double-observers. © 2011 The Wildlife Society.     

Performance of ground-based and aerial survey methods for monitoring wildlife assemblages in a conservation area of northern Tanzania

Validating and improving field-sampling techniques for estimating wildlife community composition and population size is essential for wildlife management and conservation. We conducted ground distance sampling surveys along line transects and block counts from a small aircraft in Manyara Ranch in Northern Tanzania and contrasted estimates of species richness and species-specific densities from both sampling techniques. We used regression analyses (logistic regression and generalized linear mixed models) and model selection to investigate whether a species’ body size, group size, body color, as well as vegetation cover explained the variation in species presence/absence and relative density differences in aerial vs. ground-based sampling. Ground surveys detected significantly more species than aerial surveys. However, aerial surveys detected three species that were missed by ground surveys (African lions, African buffalo, and spotted hyena). Model selection suggested that species with smaller body mass and small group sizes were more likely to be missed in aerial surveys. Densities estimated from the aerial surveys were generally but non-significantly lower than the densities estimated from the ground surveys, with the exception of density estimates for African elephants which were slightly higher from aerial surveys. Density differences between the two methods were greater for species with small group size, light body color, and in areas with denser vegetation cover; these variables explained 75% of the variation in density differences between the two survey methods. Albeit being similar in operational costs in our relatively small study area, ground surveys yielded (1) more complete information with respect to wildlife community composition and (2) density estimates were mostly higher and (3) more precise and (4) appear more feasible to be implemented in community-based conservation schemes.     

Sampling tiger ungulate prey by the distance method: lessons learned in Bardia National Park, Nepal

Because tiger Panthera tigris numbers are regulated by their prey base, prey abundance needs to monitored and estimated reliably. Recently, distance sampling has been adopted as the most appropriate method and is now becoming the standard monitoring protocol in all tiger range countries in south Asia. However, the accuracy of the density estimates generated by this method has not been assessed. From total counts within habitat blocks, we obtained accurate density estimates of ungulates within three main habitats in Bardia National Park, Nepal. We then applied the distance sampling method in the same habitats and compared the results. Distance sampling on foot in dense habitats (riverine forest and tallgrass floodplain) violated method assumptions, and sampling from vehicle along roads gave biased estimates. Sampling from elephant back worked well in all habitat types, but owing to their behaviour, the density of barking deer Muntiacus muntjak was underestimated. The accuracy of the estimates varied with sampling effort; for the very abundant chital deer Axis axis , estimates varied markedly at <200 animal observations, but converged at larger sample sizes to a similar point estimate as intensive block counts when approaching 300 observations. For the less abundant species, with <20 observations along >100 km of transect lines, the confidence intervals were quite high, and, hence, of limited value for detecting short-term populations trends. It is therefore difficult to obtain accurate density estimates of rare species by the distance method. In areas consisting of dense habitats, we recommend that the food base of tiger be estimated by distance sampling from elephant back, not on foot, directed at the main and most abundant prey species. For rare species, encounter rates obtained simultaneously may then serve as indices of relative abundances.     

Comparison of methods for estimating density of forest songbirds from point counts

New analytical methods have been promoted for estimating the probability of detection and density of birds from count data but few studies have compared these methods using real data. We compared estimates of detection probability and density from distance and time-removal models and survey protocols based on 5- or 10-min counts and outer radii of 50 or 100 m. We surveyed singing male Acadian flycatchers (Empidonax virescens), cerulean warblers (Dendroica cerulea), Kentucky warblers (Oporornis formosus), Louisiana waterthrushes (Parkesia motacilla), wood thrushes (Hylocichla mustelina), and worm-eating warblers (Helmitheros vermivorum) in bottomland and upland forest across 5 states in the Central Hardwoods Bird Conservation Region during the breeding season in 2007 and 2008. Detection probabilities differed between distance and time-removal models and species detectabilities were affected differently by year, forest type, and state. Density estimates from distance models were generally higher than from time-removal models, resulting from lower detection probabilities estimated by distance models. We found support for individual heterogeneity (modeled as a finite mixture model) in the time-removal models and that 50-m radius counts generated density estimates approximately twice as high as 100-m radius counts. Users should be aware that in addition to estimating different components of detectability, density estimates derived from distance and time-removal models can be affected by survey protocol because some count durations and plot radii may better meet model assumptions than others. The choice of a method may not affect the use of estimates for relative comparisons (e.g., when comparing habitats) but could affect conclusions when used to estimate population size. We recommend careful consideration of assumptions when deciding on point-count protocol and selection of analysis methods. © 2011 The Wildlife Society.     

Evaluation of three field monitoring-density estimation protocols and their relevance to Komodo dragon conservation

Finding practical ways to robustly estimate abundance or density trends in threatened species is a key facet for effective conservation management. Further identifying less expensive monitoring methods that provide adequate data for robust population density estimates can facilitate increased investment into other conservation initiatives needed for species recovery. Here we evaluated and compared inference-and cost-effectiveness criteria for three field monitoring-density estimation protocols to improve conservation activities for the threatened Komodo dragon (Varanus komodoensis). We undertook line-transect counts, cage trapping and camera monitoring surveys for Komodo dragons at 11 sites within protected areas in Eastern Indonesia to collect data to estimate density using distance sampling methods or the Royle–Nichols abundance induced heterogeneity model. Distance sampling estimates were considered poor due to large confidence intervals, a high coefficient of variation and that false absences were obtained in 45 % of sites where other monitoring methods detected lizards present. The Royle–Nichols model using presence/absence data obtained from cage trapping and camera monitoring produced highly correlated density estimates, obtained similar measures of precision and recorded no false absences in data collation. However because costs associated with camera monitoring were considerably less than cage trapping methods, albeit marginally more expensive than distance sampling, better inference from this method is advocated for ongoing population monitoring of Komodo dragons. Further the cost-savings achieved by adopting this field monitoring method could facilitate increased expenditure on alternative management strategies that could help address current declines in two Komodo dragon populations.     

A Field Evaluation of Distance Measurement Error in Auditory Avian Point Count Surveys

ABSTRACT Detection distance is an important and common auxiliary variable measured during avian point count surveys. Distance data are used to determine the area sampled and to model the detection process using distance sampling theory. In densely forested habitats, visual detections of birds are rare, and most estimates of detection distance are based on auditory cues. Distance sampling theory assumes detection distances are measured accurately, but empirical validation of this assumption for auditory detections is lacking. We used a song playback system to simulate avian point counts with known distances in a forested habitat to determine the error structure of distance estimates based on auditory detections. We conducted field evaluations with 6 experienced observers both before and after distance estimation training. We conducted additional studies to determine the effect of height and speaker orientation (toward or away from observers) on distance estimation error. Distance estimation errors for all evaluations were substantial, although training reduced errors and bias in distance estimates by approximately 15%. Measurement errors showed a nonlinear relationship to distance. Our results suggest observers were not able to differentiate distances beyond 65 m. The height from which we played songs had no effect on distance estimation errors in this habitat. The orientation of the song source did have a large effect on distance estimation errors; observers generally doubled their distance estimates for songs played away from them compared with distance estimates for songs played directly toward them. These findings, which we based on realistic field conditions, suggest measures of uncertainty in distance estimates to auditory detections are substantially higher than assumed by most researchers. This means aural point count estimates of avian abundance based on distance methods deserve careful scrutiny because they are likely biased.     

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.     

Distance sampling techniques compared for a New Zealand endemic passerine (

The effectiveness of line- and point-transect distance sampling methods was compared for estimating the density of a conspicuous endemic passerine, the North Island saddleback Philesturnus carunculatus rufusater, in two forest habitats on Tiritiri Matangi Island, Hauraki Gulf, New Zealand. The reference population abundance in each habitat was calculated through an intensive capture, colour-banding, and resighting effort. Line transects consistently produced unbiased estimates of density for both sites at two time periods (morning and afternoon), and proved to be the most efficient of the distance sampling methods tested. Point-transect methods proved to be biased in this instance, consistently producing overestimates of density for this species, and were unreliable as indices of the small differences in density between habitats. Transect counts conducted from established walking tracks underestimated both density and the variance of estimated density. We conclude that in situations requiring estimates of absolute density for North Island saddleback, a series of randomly positioned line transects will accurately represent the density of individuals. Furthermore, this study highlights the need to pilot distance survey techniques on the species of interest to detect possible violation of the assumptions underlying these methods. We question the widespread use of point-transect counts for censusing avian species without such preliminary investigation, and recommend further comparisons of distance sampling methods in New Zealand with reference populations where opportunity provides.     

Comparison and Assessment of Aerial and Ground Estimates of Waterbird Colonies

Abstract: Aerial surveys are often used to quantify sizes of waterbird colonies; however, these surveys would benefit from a better understanding of associated biases. We compared estimates of breeding pairs of waterbirds, in colonies across southern Louisiana, USA, made from the ground, fixed-wing aircraft, and a helicopter. We used a marked-subsample method for ground-counting colonies to obtain estimates of error and visibility bias. We made comparisons over 2 sampling periods: 1) surveys conducted on the same colonies using all 3 methods during 3–11 May 2005 and 2) an expanded fixed-wing and ground-survey comparison conducted over 4 periods (May and Jun, 2004–2005). Estimates from fixed-wing aircraft were approximately 65% higher than those from ground counts for overall estimated number of breeding pairs and for both dark and white-plumaged species. The coefficient of determination between estimates based on ground and fixed-wing aircraft was ≤0.40 for most species, and based on the assumption that estimates from the ground were closer to the true count, fixed-wing aerial surveys appeared to overestimate numbers of nesting birds of some species; this bias often increased with the size of the colony. Unlike estimates from fixed-wing aircraft, numbers of nesting pairs made from ground and helicopter surveys were very similar for all species we observed. Ground counts by one observer resulted in underestimated number of breeding pairs by 20% on average. The marked-subsample method provided an estimate of the number of missed nests as well as an estimate of precision. These estimates represent a major advantage of marked-subsample ground counts over aerial methods; however, ground counts are difficult in large or remote colonies. Helicopter surveys and ground counts provide less biased, more precise estimates of breeding pairs than do surveys made from fixed-wing aircraft. We recommend managers employ ground counts using double observers for surveying waterbird colonies when feasible. Fixed-wing aerial surveys may be suitable to determine colony activity and composition of common waterbird species. The most appropriate combination of survey approaches will be based on the need for precise and unbiased estimates, balanced with financial and logistical constraints. (JOURNAL OF WILDLIFE MANAGEMENT 72(3):697–706; 2008)     

Improving inference for aerial surveys of bears: The importance of assumptions and the cost of unnecessary complexity

Obtaining useful estimates of wildlife abundance or density requires thoughtful attention to potential sources of bias and precision, and it is widely understood that addressing incomplete detection is critical to appropriate inference. When the underlying assumptions of sampling approaches are violated, both increased bias and reduced precision of the population estimator may result. Bear (Ursus spp.) populations can be difficult to sample and are often monitored using mark‐recapture distance sampling (MRDS) methods, although obtaining adequate sample sizes can be cost prohibitive. With the goal of improving inference, we examined the underlying methodological assumptions and estimator efficiency of three datasets collected under an MRDS protocol designed specifically for bears. We analyzed these data using MRDS, conventional distance sampling (CDS), and open‐distance sampling approaches to evaluate the apparent bias‐precision tradeoff relative to the assumptions inherent under each approach. We also evaluated the incorporation of informative priors on detection parameters within a Bayesian context. We found that the CDS estimator had low apparent bias and was more efficient than the more complex MRDS estimator. When combined with informative priors on the detection process, precision was increased by >50% compared to the MRDS approach with little apparent bias. In addition, open‐distance sampling models revealed a serious violation of the assumption that all bears were available to be sampled. Inference is directly related to the underlying assumptions of the survey design and the analytical tools employed. We show that for aerial surveys of bears, avoidance of unnecessary model complexity, use of prior information, and the application of open population models can be used to greatly improve estimator performance and simplify field protocols. Although we focused on distance sampling‐based aerial surveys for bears, the general concepts we addressed apply to a variety of wildlife survey contexts.     

Pellet group count methods to estimate red deer densities: Precision,potential accuracy and efficiency

Pellet group count methods are key tools for wildlife conservation and management. Therefore, it is essential to clarify the performance and suitability of the different pellet group count methods at distinct realities. This issue has been discussed by other researchers but with inconsistent conclusions, leaving open the necessity of additional studies. Aiming to fill this need, we used a combination of field data and simulation models to evaluate the density estimates, precision and potential accuracy of the results obtained through each pellet group count method, and also the sampling effort and efficiency associated with them. The methods evaluated were standing crop plot counts (FSCP), clearance plot counts (FAR), standing crop strip transect counts (ST) and standing crop line transect counts (LT). Deer density estimates by the four methods were statistically similar at all effort levels simulated. The analyses of CV trends reveal a better precision supplied by FSCP than by FAR for the same effort, while ST and LT yielded comparable values in analogous situations. The time required to make a survey is a key factor in the choice of a field technique. LT with distance sampling was the most efficient method to count pellet groups, while FAR seems to be the less proficient method. Attending to the limitations usually inherent to field surveys, like time, technicians and budget, LT appeared more efficient than the other methods, providing great precision and accuracy in less time. Nevertheless, at high densities and pronounced habitat heterogeneity, FAR became more efficient than FSC, do not requiring the decay rates, allowing accurate estimates in a few months when applied with the proper effort and environmental conditions. This study highlights the importance of carrying out pilot studies and simulation models to evaluate the sampling design prior to its implementation in the field.     

The use of faeces counts to estimate relative densities of wild boar in a Mediterranean area

The monitoring of population trends of wild ungulates is important to evaluate their population dynamics and to develop sound conservation/management plans. The wild boar Sus scrofa can impose heavy impacts on ecosytems and human activities, as well as be responsible for disease transmission. Estimating abundance of wild boars is a challenging issue, because of some peculiar biological and ecological traits of this ungulate. Indices of relative abundance could be used to evaluate its population trends. In a Mediterranean area we used faeces counts, through a two-stage stratified sampling, to estimate relative densities of wild boars, between 2007 and 2014. Faeces density estimates increased not significantly between 2007 (151.5 faeces/100 ha) and 2010 (203.8 faeces/100 ha) and decreased significantly from 2010 to 2014 (95.5 faeces/100 ha). The decrease in faeces density estimates was consistent with the increased harvest effort (number of harvest days), performed from 2010 to 2013 to limit impact on ecosystems and reduce damages to crops. The variation of faeces density estimates was also consistent with that of harvest indices (total harvest to harvest effort), with significantly positive values of Pearson and rank correlation coefficients. Results suggest that faeces density estimates achieved with the adopted sampling strategies can be effectively used as indices of relative abundance.     

A field test of the distance sampling method using Golden‐cheeked Warblers

ABSTRACT Criteria for delisting Golden‐cheeked Warblers (Dendroica chrysoparia) include protection of sufficient breeding habitat to ensure the continued existence of 1000 to 3000 singing males in each of eight recovery regions for ≥10 consecutive years. Hence, accurate abundance estimation is an integral component in the recovery of this species. I conducted a field test to determine if the distance sampling method provided unbiased abundance estimates for Golden‐cheeked Warblers and develop recommendations to improve the accuracy of estimates by minimizing the effects of violating this method's assumptions. To determine if observers could satisfy the assumptions that birds are detected at the point with certainty and at their initial locations, I compared point‐transect sampling estimates from 2‐, 3‐, 4‐, and 5‐min time intervals to actual abundance determined by intensive territory monitoring. Point‐transect abundance estimates were 15%, 29%, 43%, and 59% greater than actual abundance (N= 156) for the 2‐, 3‐, 4‐, and 5‐min intervals, respectively. Point‐transect sampling produced unbiased estimates of Golden‐cheeked Warbler abundance when counts were limited to 2 min (N= 154–207). Abundance estimates derived from point‐transect sampling were likely greater than actual abundance because observers did not satisfy the assumption that birds were detected at their initial locations due to the frequent movements and large territory sizes of male Golden‐cheeked Warblers. To minimize the effect of movement on abundance estimates, I recommend limiting counts of singing males to 2‐min per point. Counts for other species in similar habitats with similar behavior and movement patterns also should be limited to 2 min when unbiased estimates are important and conducting field tests of the point‐transect distance sampling method is not possible.     

An Evaluation of Survey Methods for Estimating Northern Bobwhite Abundance in Southern Texas

Abstract: Distance sampling has been identified as a reliable and well-suited method for estimating northern bobwhite (Colinus virginianus) density. However, distance sampling using walked transects requires intense sampling to obtain precise estimates, thus making the technique impractical for large acreages. Researchers have addressed this limitation by either resorting to the use of indices (e.g., morning covey-call surveys) or incorporating the use of aerial surveys with distance sampling. Both approaches remain relatively untested. Our objectives were to 1) compare density estimates among morning covey-call surveys, helicopter transects, and walked transects; 2) test a critical assumption of distance sampling pertinent to helicopter surveys (i.e., all objects on line are detected); and 3) evaluate the underlying premise of morning covey-call surveys (i.e., that the no. of calling coveys correlates with bobwhite density). Our study was conducted on 3 study sites in Brooks County, Texas, USA, during October to December, 2001 to 2005. Comparisons between walked transects and morning covey-call surveys involved the entire 5-year data set, whereas helicopter transects involved only the latter 2 years. Density estimates obtained from helicopter transects were similar to walked transect estimates for both years. We documented a detection probability on the helicopter transect line of 70 ± 10.2% (% ± SE; n = 20 coveys). Morning covey-call surveys yielded similar density estimates to walked transect estimates during only 2 of 5 years, when walked transect estimates were the least accurate and precise. We detected a positive relationship (R² = 0.51; 95% CI for slope: 29.5–53.1; n = 63 observations) between covey density and number of coveys heard calling. We conclude that helicopter transects appear to be a viable alternative to walked transects for estimating density of bobwhites. Morning covey-call surveys appear to be a poor method to estimate absolute abundance and to depict general population trajectories.     

Monitoring Strategy for Eight Amphibian Species in French Guiana,South America

Although dramatic amphibian declines have been documented worldwide, only few of such events have been quantitatively documented for the tropical forests of South America. This is due partly to the fact that tropical amphibians are patchily distributed and difficult to detect. We tested three methods often used to monitor population trends in amphibian species in a remote lowland tropical forest of French Guiana. These methods are capture-mark-recapture (CMR), estimation of the number of calling males with repeated counts data and distance sampling, and rates of occupancy inferred by presence/absence data. We monitored eight diurnal, terrestrial amphibian species including five Dendrobatidae and three Bufonidae. We found that CMR, the most precise way of estimating population size, can be used only with two species in high density patches where the recapture rate is high enough. Only for one of the species (Dendrobates tinctorius), a low coefficient of variation (CV = 0.19) can be achieved with 15 to 20 capture events. For dendrobatid species with day-calling males, audio surveys yield a better probability of detection with only 8 audio surveys needed; quantitative estimates can be achieved by computing the number of calling males inferred from audio counts or distance sampling analysis. We therefore suggest that an efficient monitoring protocol for Neotropical amphibian species should include a combination of sighting and audio techniques, and we discuss the need of implementing a large-scale monitoring in order to provide a baseline for comparison with future changes.     

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.     

Estimating population density from indirect sign: track counts and the Formozov–Malyshev–Pereleshin formula

For many purposes it is often desirable to estimate animal population densities over large areas. Where total counts are not possible and sightings are relatively rare, a range of methods exists to estimate densities from indirect sign. Such methods are frequently unreliable and usually require independent calibration or confirmation. We present an analytical method for estimating population density from track counts. The method, widely known in the Russian Federation but not in the English language scientific literature, requires counts of tracks of known age, together with estimates of animal daily travel distances. We use simulations to verify the theoretical basis of the approach and to indicate potential precision that may be achieved. We illustrate application of the approach using a large data set on ungulate track counts in the Russian Far East. We suggest that under most circumstances, nonparametric bootstrapping will be the most appropriate method for deriving estimates of confidence intervals about density estimates. As with other approaches to estimating density from indirect sign, the method that we discuss is vulnerable to violations of an array of underlying assumptions. However, it is easily applied and could represent an important method by which the relationship between indices of abundance and absolute density can be understood.     

Using distance sampling techniques to estimate bottlenose dolphin (Tursiops truncatus) abundance at Turneffe Atoll,Belize

Reliable abundance estimates are critical for management and conservation of coastal small cetaceans. This is particularly important in developing countries where coastal human populations are increasing, the impacts of anthropogenic activities are often unknown, and the resources necessary to assess coastal cetaceans are limited. We adapted ship‐based line transect methods to small‐boat surveys to estimate the abundance of bottlenose dolphins (Tursiops truncatus) at Turneffe Atoll, Belize. Using a systematic survey design with random start and uniform coverage, 34 dolphin clusters were sighted during small‐boat line transect surveys conducted in 2005–2006. Distance sampling methods estimated abundance at 216 individuals (CV = 27.7%, 95% CI = 126–370). Due to species rarity in the Atoll, small sample size, and potential violations in line transect assumptions, the estimate should be considered preliminary. Nevertheless, it provides up‐to‐date information on the status of a regional population in an area under increasing threat of habitat loss and prey depletion via uncontrolled development and unsustainable fishing. This information will be useful as Belize develops a new conservation initiative to create a comprehensive and resilient marine protected area system. Our study illustrates the application of distance sampling methods to small‐boat surveys to obtain abundance estimates of coastal cetaceans in a region lacking resources.     

Measurement errors in line transect surveys where detectability varies with distance and size

When using bivariate line transect methods to estimate the biomass density of a tightly clustered biological population, it is generally assumed that both the perpendicular distance from the trackline to the cluster and the cluster size, or biomass, are measured without error. This is unlikely to be the case in practice. In this article, assuming additive mean zero errors in distance and multiplicative errors in size, we develop an estimator of density that corrects for these errors. We use the method of moments for the case of gamma cluster size, randomly placed transect lines, and the generalized exponential detection function. We derive results that show that it may not be necessary to correct for errors in distance or size when the distance and size estimates are not biased. When the size estimates are biased, the biomass density estimate has approximately the same bias as the size estimates. The work is illustrated in the context of annual aerial surveys for juvenile southern bluefin tuna in the Great Australian Bight.     

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.