Distance Sampling Surveys Research Articles

Supplemental structured surveys and pre-existing detection models improve fine-scale density and population estimation with opportunistic community science data

Density and population estimates aid in conservation and stakeholder communication. While free and broadly available community science data can effectively inform species distribution models, they often lack the information necessary to estimate imperfect detection and area sampled, thus limiting their use in fine-scale density modeling. We used structured distance-sampling surveys to model detection probability and calculate survey-specific detection offsets in community science models. We estimated density and population for 16 songbird species under three frameworks: (1) a fixed framework that assumes perfect detection within a specified survey radius, (2) an independent framework that calculates offsets from an independent source, and (3) a calibration framework that calculates offsets from supplemental surveys. Within the calibration framework, we examined the effects of calibration dataset size and data pooling. Estimates of density and population size were consistently biased low in the fixed framework. The independent and calibration frameworks produced reliable estimates for some species, but biased estimates for others, indicating discrepancies in detection probability between structured and community science surveys. The calibration framework produced reliable population estimates with as few as 10 calibration surveys with positive detections. Data pooling dramatically decreased bias. This study provides conservationists and managers with a cost-effective method of estimating density and population.

Correcting detection bias in mapping the abundance of marine megafauna using a Mediterranean seabird as an example

Abstract Distance sampling surveys are extensively used to estimate the abundance of wide-ranging species but are prone to detection biases. This may be particularly acute for strip-transect protocols, which assume perfect detection. We examined this assumption by quantifying the detection probability of a declining seabird (Scopoli’s shearwater, Calonectris diomedea), with particular attention to time of day and observation conditions at sea. We found detection probability was negatively affected by sun glare but positively by cloud cover and considerably dropped during mid-day hours due to circadian changes in behaviour (reduced detectability while resting). This result urges for systematically assessing and correcting detection bias when using strip-transect data to derive abundance information. Here, we did so by building a detection-corrected presence-absence ensemble model and combining it with a compilation of colony sizes and locations. A Monte-Carlo simulation ensured uncertainty propagation within and across data sources. The corrected abundance map showed shearwaters were largely prevalent in the central Mediterranean, Tunisia hosting most of the population both at sea and at colonies (45% of the global population; 79% of breeding pairs). This first accurate map is an essential conservation tool, emphasizing the importance of transnational actions for such species, that know no political boundaries.

Population Abundance and Density Estimates of Poorly Documented Near-Threatened Calabar Angwantibo (Arctocebus calabarensis) in Oban Hills Region.

Population abundance and density estimates play important roles in biodiversity conservation assessment and can lead to prioritization of conservation efforts, strategies, and management. The Calabar angwantibo (Arctocebus calabarensis) is a poorly studied, Near-Threatened nocturnal, arboreal mammal species occurring only in the lowland moist tropical rainforest blocks of southeastern Nigeria and southwestern Cameroon. Like other arboreal nocturnal mammals, there are gaps in knowledge of the distribution and abundance of this species, which may be facing population declines due to habitat loss and hunting. In this study, we investigated the abundance and density of A. calabarensis in the Oban Hills Region of Nigeria. We conducted systematic distance sampling survey along 32 transects in different habitats in a 1227 km of survey efforts. A total of 41 sightings of A. calabarensis were detected, resulting in an abundance of 7345 individuals (95% CI = 1.51-4.37) with an estimated density of 2.57 animals/km2. The estimated population abundance is 6515 individuals in closed-canopy forests and 830 individuals in secondary forests, with encounter rates of 0.52 individual/km2 and 0.60 individuals/km2 in the closed canopy and secondary forest habitats. The global estimates encounter rate of A. calabarensis across the habitat types is 0.33 individuals/km2 and population abundance of 4456 individuals. Our findings indicate that the A. calabarensis populations can adapt to low changes in forest habitat modifications resulting from increasing and widespread forest disturbance by human-dominated activity, which is giving way to forest clearance for agriculture cultivation and infrastructural development. Our findings help to fill a knowledge gap regarding this species and may help establish a baseline for future management, population monitoring, and conservation of the cryptic population of A. calabarensis in Cross-Sanaga Forests.

Assessment of the global population size of the Mongolian gazelle Procapra gutturosa

Abstract The Mongolian gazelle Procapra gutturosa is a wild ungulate ubiquitous across the largest remaining temperate grasslands of Mongolia, Russia and China. The species is nomadic and ranges over long distances, resulting in widely fluctuating abundance in any given location. Therefore, a comprehensive and range-wide survey is required to accurately estimate its global population size, but challenges are posed by the expansive geographical distribution and the political boundaries across the species’ vast range. To obtain an estimate of the total population, we compiled data from recent range-wide surveys. During 2019–2020, we estimated the population size in Mongolia by conducting line transect distance surveys and total counts, and by deriving numerical predictions for unsurveyed areas through data analysis. The gazelle's population in Russia was surveyed in 2020 across its summer range using simultaneous counts, transect surveys and expert knowledge. The distance sampling surveys in Mongolia revealed that slightly more than half of the gazelles along the transects were detected. Our assessment of the gazelle population, although probably an underestimate, suggests there are c. 2.14 million individuals in Mongolia and c. 30,000 in Russia. These results confirm that the Mongolian gazelle is the most abundant nomadic ungulate in the open plains across its range. However, to obtain more accurate estimates across all range states and effectively monitor the gazelle's population status, it is essential to implement standardized survey protocols that correct for imperfect detection. At present, the management of the Mongolian gazelle is inadequate, as there is a lack of regular monitoring to identify any adverse population changes that could necessitate conservation interventions.

Using density surface models to assess the ecological effectiveness of a protected area network in Tanzania

AbstractGiven recent global endeavors to increase protected area coverage, it is crucial to comprehensively evaluate the efficacy of various area‐based conservation strategies in effectively reducing biodiversity loss. Here, we investigated the responses of wildlife populations to different protection levels and environmental variables at the landscape scale in the Katavi–Rukwa Ecosystem, western Tanzania. To this end, we conducted line distance sampling surveys and counted the dung of six target mammal species (elephant, giraffe, buffalo, zebra, topi, and hartebeest) along foot transects within areas differing in protection levels (from strict to less‐strictly protected: national park, game reserve, forest reserve, game‐controlled area, and unprotected areas). Based on these dung counts, we modeled the spatial distribution of these six mammal species using a species‐specific density surface modeling framework. We found consistent effects of protection level and land use variables on the spatial distribution of the target mammal species: dung densities were highest in the national park and game reserves, intermediate in less‐strictly protected areas, and lowest in unprotected areas. Beyond species‐specific environmental predictors for dung densities, our results highlight consistent negative associations between dung densities of the target species and distance to cropland and avoidance of areas in proximity to houses. Our findings underpin differences in ecological effectiveness of protected areas within one ecosystem. Protection level and land use play crucial roles in moderating the spatial distribution of all considered mammal species. Our findings suggest that a landscape approach needs to guide effective conservation across the entire protection gradient of the Katavi–Rukwa Ecosystem.

A negative trend in abundance and an exceeded mortality limit call for conservation action for the Vulnerable Belt Sea harbour porpoise population

The management and conservation of biodiversity relies on information on both the abundance of species and the potential impact of threats. Globally, one of the largest threats towards marine biodiversity is bycatch in fisheries. Under the Marine Strategy Framework Directive (MSFD), EU Member States are required to assess the status of species, such as the harbour porpoise (Phocoena phocoena), in relation to their abundance and mortality due to bycatch every six years. The Vulnerable (HELCOM) Belt Sea population of harbour porpoise has been surveyed to determine its abundance six times using dedicated aerial or ship-based line-transect distance sampling surveys. Here, we estimated the first trend in population abundance over an 18 year period (2005-2022). Using the most recent abundance estimate, we computed a mortality limit applying the modified Potential Biological Removal (mPBR) method based on the regionally agreed conservation objective to restore or maintain 80% of carrying capacity over 100 years with an 80% probability. Over the past 18 years there has been a strong negative trend (-2.7% p.a.; 95% CI: -4.1%; + 1.3%) in abundance, with a 90.5% probability. The mortality limit was estimated to be 24 animals, which the current bycatch estimates (~900 porpoises/year from the commercial Danish and Swedish set net fishery fleets, with no data from Germany and other fishery types) exceed by far. The frequency and quality of data available on abundance for this population are higher than those available for the majority of marine species. Given the observed population decline and likely unsustainable levels of bycatch, the results presented here provide a strong basis to make informed, evidence-based management decisions for action for this population. Such action is needed urgently, before the dire situation of other porpoise species and populations around the globe is repeated.

PelaSIG, a QGIS plugin for marine megafauna census: application to the aerial ACCOBAMS Survey Initiative dataset

The distribution of wild animals and their monitoring over large areas raises many logistical and technical difficulties that hinder the collection of observation data. The use of Geographic Information Systems (GIS) has increased significantly in recent years. QGIS, an open-source GIS software dedicated to the processing of geospatial data, enables the development of dedicated plugins for specific workflows. The open-source PelaSIG plugin has been developed in Python for QGIS 3 to facilitate and standardise the different steps before and after distance sampling surveys. It brings together a set of tools for survey preparation, automatic data checking, visualisation and presentation of survey effort and sightings to provide an adapted workflow. This plugin is currently designed to process dedicated aerial datasets collected with the SAMMOA software during marine megafauna surveys (i.e., marine mammals, seabirds, elasmobranchs, sea turtles, etc.). Here, we first describe the different tools already available, and then, we present an application with the dataset from the aerial survey of the ACCOBAMS Survey Initiative (ASI) conducted in 2018 over the Mediterranean Sea and using a multi-target protocol.

Simulation Modeling to Assess Line Transect Distance Sampling Under a Range of Translocation Scenarios

Abstract The accuracy of posttranslocation population monitoring methods is critical to assessing long-term success in translocation programs. Translocation can produce unique challenges to monitoring efforts; therefore, it is important to understand the flexibility and robustness of commonly used monitoring methods. In Florida, USA, thousands of gopher tortoises Gopherus polyphemus have been, and continue to be, translocated from development sites to permitted recipient sites. These recipient sites create a broad range of potential monitoring scenarios due to variability in soft-release strategies, habitat conditions, and population demographics. Line transect distance sampling is an effective method for monitoring natural tortoise populations, but it is currently untested for translocated populations. We therefore produced 3,024 individual-based, spatially explicit scenarios of translocated tortoise populations that differed in recipient site and tortoise population properties, based on real-world examples, literature review, and expert opinion. We virtually sampled simulated tortoise populations by using line transect distance sampling methods and built a Bayesian hierarchical model to estimate the population density for each simulation, which incorporated individual-level covariates (i.e., burrow width and burrow occupancy). Line transect distance sampling was largely appropriate for the conditions that typify gopher tortoise recipient sites, particularly when detection probability on the transect lines was greater than or equal to 0.85. Designing the layout of transects relative to the orientation of soft-release pens, to avoid possible sampling biases that lead to extreme outliers in estimates of tortoise densities, resulted in more accurate population estimates. We also suggest that use of individual-level covariates, applied using a Bayesian framework as demonstrated in our study, may improve the applicability of line transect distance sampling surveys in a variety of contexts and that simulation can be a powerful tool for assessing survey design in complex sampling situations.

Estimating effective survey duration in camera trap distance sampling surveys.

Among other approaches, camera trap distance sampling (CTDS) is used to estimate animal abundance from unmarked populations. It was formulated for videos and observation distances are measured at predetermined 'snapshot moments'. Surveys recording still images with passive infrared motion sensors suffer from frequent periods where animals are not photographed, either because of technical delays before the camera can be triggered again (i.e. 'camera recovery time') or because they remain stationary and do not immediately retrigger the camera following camera recovery time (i.e. 'retrigger delays'). These effects need to be considered when calculating temporal survey effort to avoid downwardly biased abundance estimates. Here, we extend the CTDS model for passive infrared motion sensor recording of single images or short photo series. We propose estimating 'mean time intervals between triggers' as combined mean camera recovery time and mean retrigger delays from the time interval distribution of pairs of consecutive pictures, using a Gamma and Exponential function, respectively. We apply the approach to survey data on red deer, roe deer and wild boar. Mean time intervals between triggers were very similar when estimated empirically and when derived from the model-based approach. Depending on truncation times (i.e. the time interval between consecutive pictures beyond which data are discarded) and species, we estimated mean time intervals between retriggers between 8.28 and 15.05 s. Using a predefined snapshot interval, not accounting for these intervals, would lead to underestimated density by up to 96% due to overestimated temporal survey effort. The proposed approach is applicable to any taxa surveyed with camera traps. As programming of cameras to record still images is often preferred over video recording due to reduced consumption of energy and memory, we expect this approach to find broad application, also for other camera trap methods than CTDS.

Evaluation of replicate sampling using hierarchical spatial modeling of population surveys accounting for imperfect detectability

AbstractEffective species management and conservation benefit from knowledge of species distribution and status. Surveys to obtain that information often involve replicate sampling, which increases survey effort and costs. We simultaneously modeled species distribution, abundance and spatial correlation, and compared the uncertainty in replicate abundance estimates of the endangered palila (Loxioides bailleui) using hierarchical generalized additive models with a soap film smoother that incorporated random effects for visit. Based on survey coverage and detections, we selected the 2017 point‐transect distance sampling survey on Mauna Kea, Hawai‘i Island, for our modeling. Our modeling approach allowed us to account for imperfect detections, control the effects of boundary features, and generate visit‐specific density surface maps. We found that visit‐specific smooths were nearly identical, indicating that little information was gained from a subsequent visit, and that most of the estimator uncertainty was derived from within‐visit variability. Scaling back the palila survey to a single visit would halve the survey effort and logistical costs and increase efficiencies in data management and processing. Changing the sampling protocol warrants careful consideration and our findings may help management and regulatory agencies by maximizing efficiency and minimizing costs of surveying protocols, while providing guidelines on how to best collect information critical to species' conservation.

The effect of line-transect placement in a coastal distance sampling survey

Distance sampling surveys are commonly used to estimate animal abundance (N). The choice of survey design has only recently received attention in the line-transect research literature, which has tended to focus more on the violation of assumptions. In this study, simulation methods were used to assess the effect of line placement on the accuracy and precision of a line-transect survey for estimating dolphin abundance. In 1998, a vessel-based line-transect survey of Hector’s dolphin (Cephalorhynchus hectori) was carried out around Banks Peninsula (New Zealand). These data were used to generate a spatially realistic dolphin distribution onto which different survey designs were overlaid. Eight types of design were considered, consisting of four types of stratification and two methods for allocating lines: random or systematic. None of the designs showed any evidence of significant bias in the estimate of N(Nˆ). Systematic placement of lines generally provided more precise estimates of N, with an average reduction (over all designs) of 14% in the coefficient of variation of Nˆ, [CV(Nˆ)]. These results correspond well with those expected from classical sampling theory for the case of estimating a population mean. However, these designs also overestimated CV(Nˆ) by 10-28% (mean=22%). Systematic line-placement has several practical advantages over random placement, including more uniform spatial coverage. For coastal cetacean populations with spatial dynamics similar to the one considered here, we recommend the use of systematic line-placement, with the proviso that the estimate of CV(Nˆ) is likely to be overestimated by 10-28%.

Assessing the viability of estimating baleen whale abundance from tourist vessels

Many populations of southern hemisphere baleen whales are recovering and are again becoming dominant consumers in the Southern Ocean. Key to understanding the present and future role of baleen whales in Southern Ocean ecosystems is determining their abundance on foraging grounds. Distance sampling is the standard method for estimating baleen whale abundance but requires specific logistic requirements which are rarely achieved in the remote Southern Ocean. We explore the potential use of tourist vessel-based sampling as a cost-effective solution for conducting distance sampling surveys for baleen whales in the Southern Ocean. We used a dataset of tourist vessel locations from the southwest Atlantic sector of the Southern Ocean and published knowledge from Southern Ocean sighting surveys to determine the number of tourist vessel voyages required for robust abundance estimates. Second, we simulated the abundance and distributions of four baleen whale species for the study area and sampled them with both standardized line transect surveys and non-standardized tourist vessel-based surveys, then compared modeled abundance and distributions from each survey to the original simulation. For the southwest Atlantic, we show that 12-22 tourist vessel voyages are likely required to estimate abundance for humpback and fin whales, with relative estimates for blue, sei, Antarctic minke, and southern right whales. Second, we show tourist vessel-based surveys outperformed standardized line transect surveys at reproducing simulated baleen whale abundances and distribution. These analyses suggest tourist vessel-based surveys are a viable method for estimating baleen whale abundance in remote regions. For the southwest Atlantic, the relatively cost-effective nature of tourist vessel-based survey and regularity of tourist vessel voyages could allow for annual and intra-annual estimates of abundance, a fundamental improvement on current methods, which may capture spatiotemporal trends in baleen whale movements on forging grounds. Comparative modeling of sampling methods provided insights into the behavior of general additive model-based abundance modeling, contributing to the development of detailed guidelines of best practices for these approaches. Through successful engagement with tourist company partners, this method has the potential to characterize abundance across a variety of marine species and spaces globally, and deliver high-quality scientific outcomes relevant to management organizations.

Seasonal Abundance, Density and Distribution of Cetaceans in the Bulgarian Black Sea Shelf in 2017

Black Sea cetaceans are isolated and nominated as endemic subspecies listed in the IUCN Red List of Endangered species: the harbour porpoise and bottlenose dolphin as Endangered (EN) and the common dolphin as Vulnerable (VU). Studies of their distribution and abundance are scarce but obligatory for assessment of their conservation status. Being highly mobile apex predators entails large variations in spatial and temporal distribution. Two vessel line–transect distance sampling surveys were conducted in 2017 in the Bulgarian shelf with the aim to estimate the density, abundance and distribution during spring and autumn. Results have revealed a shift from the coastal to offshore shelf of harbour porpoises with marked southern movement. Density of porpoises varied from 1.423 ind./km2 (CV = 25.4%) in spring to 0.576 ind./km2 (CV = 43.43%) in autumn. The density of common dolphins was also decreasing, from 0.391 ind./km2 (CV = 36.84%) to 0.088 ind./km2 (CV = 42.13%), which was more significant in offshore (0.031 ind./km2, CV = 58.04%) than in the coastal shelf (0.138 ind./km2, CV = 48.59%). Bottlenose dolphins had almost constant density in both seasons in the coastal shelf: 0.211 ind./km2 (CV = 52.15%) and 0.187 ind./km2 (CV = 52.13%) but a very low density in the offshore shelf in autumn: 0.042 ind./km2 (CV = 71.07%). The importance of existing NATURA 2000 sites for the harbour porpoise (BG0000621 Shabla-Ezerets, BG0000573 Kompleks Kaliaka, BG0001001 Ropotamo and BG0001007 Strandzha) and bottlenose dolphin (BG0000621 Shabla-Ezerets, BG0000573 Kompleks Kaliaka, BG0001501 Emona and BG0001001 Ropotamo) were confirmed.

Accounting for spatial heterogeneity in visual obstruction in line‐transect distance sampling of gopher tortoises

AbstractLine‐transect distance sampling (LTDS) surveys are commonly used to estimate abundance of animals or objects. In terrestrial LTDS surveys of gopher tortoise (Gopherus polyphemus) burrows, the presence of ground‐level vegetation substantially decreases detection of burrows of all sizes, but no field or analytical methods exist to control for spatially heterogeneous vegetation obstruction as a source of variation in detection. We propose the addition of a simple measurement of ground‐level vegetation that serves as a covariate for the detection function. We present a Bayesian hierarchical model in which covariates burrow width and nearby vegetation height help to account for detection bias and improve precision of estimated density. We investigate the performance of this covariate by simulation and by using real LTDS data collected before and after application of prescribed fire. We collected data in 2018 at the Jones Center at Ichauway in Newton, Georgia, USA. Across all simulations, our model including both covariates produced the most accurate density point estimates of any of the models tested. For our case study, our Bayesian model with vegetation covariates tended to produce similar estimates of density before and after burns. Our study indicates that any level of spatial variation in vegetation obstruction decreases detection of burrows and may lead to underestimation in population size (≤68%) and proportion of individuals with small burrow sizes (≤32%) when not considered during analysis. Our work is extensible to other terrestrial sampling efforts where systematic measurement of a spatially distributed obstructing feature is feasible during the LTDS survey.

Interaction between transect design and animal distribution in distance sampling of deer

AbstractWe conducted a simulation study to evaluate the consequences of violating statistical assumptions of distance sampling (DS) on the bias and precision of population estimates of white‐tailed deer (Odocoileus virginianus). Distance sampling is a method for estimating the density of organisms using a distribution of observed distances to individuals. A key assumption of DS is that sampling transects are randomly located with respect to the population being sampled. Most DS transects used in National Parks follow roads and trails, which are not positioned randomly. We constructed spatially explicit simulations of surveys using 7 different types of deer spatial distributions and 3 survey designs. A significant interaction between survey type and deer distribution type explained most of the variation in population estimates across simulations and this interaction was also a significant predictor of the coefficient of variation (CV) of population estimates. Simulation results suggested that 1) non‐road surveys were more robust to bias than were road surveys, 2) effectiveness of each of 3 survey types was dependent on the way deer were distributed across the landscape, and 3) non‐road surveys produced unbiased estimates of populations affected by roads, whereas road surveys did not. The results of our study suggest that DS surveys using pre‐existing roads and trails have potential biases resulting from study design, something that could be considered by land managers when constructing surveys.

Density surface and excursion sets modeling as an approach to estimating population densities

AbstractEffective species management and conservation require knowledge of species distribution and status. We used point‐transect distance sampling surveys of the endangered palila (Loxioides bailleui), a honeycreeper currently found only on the Island of Hawai'i, USA, to generate robust estimates of total abundance and simultaneously model the distribution, abundance, and spatial correlation of the species as a density surface model (DSM). Point‐transect distance sampling is a widely applied method to estimate bird densities accounting for imperfect detection probability. For the DSM we used a generalized additive model framework and soap film smoothers to control the effects of boundary features. This modeling approach allowed us to account for imperfect detection and propagate detection probability uncertainty. We compared the uncertainty in palila abundance estimates using standard point‐transect distance sampling to estimates from the DSM. The DSM, accounting for both distance‐sampling‐derived detection probability variance and the generalized additive model density estimate variance, did not improve population estimator precision; however, it provided insight into the species' distribution, density, and uncertainty. We also applied excursion sets analysis to objectively identify areas where the species occurs in high densities. The 2017 global population of <2,000 individuals was limited to an excursion area of 1,500 ha. Our findings can help management and regulatory agencies by simultaneously mapping a species' distribution and density, improving survey protocols, and providing information important to species conservation.

Distance sampling surveys: using components of detection and total error to select among approaches

AbstractWildlife population estimators often require formal adjustment for imperfect detection of individuals during surveys. Conventional distance sampling (CDS) and its extensions (mark‐recapture distance sampling [MRDS], temporary emigration distance sampling [TEDS]) are popular approaches for producing unbiased estimators of wildlife abundance. However, despite extensive discussion and development of distance sampling theory in the literature, deciding which of these alternatives is most appropriate for a particular scenario can be confusing. Some of this confusion may stem from an incomplete understanding of how each approach addresses the components of the detection process. Here we describe the proper application of CDS, MRDS, and TEDS approaches and use applied examples to help clarify their differing assumptions with respect to the components of the detection process. To further aid the practitioner, we summarize the differences in a decision tree that can be used to identify cases where a more complex alternative (e.g., MRDS or TEDS) may be appropriate for a given survey application. Although the more complex approaches can account for additional sources of bias, in practical applications one also must consider estimator precision. Therefore, we also review the concept of total estimator error in the context of comparing competing methods for a given application to aid in the selection of the most appropriate distance sampling approach. Finally, we detail how the use of more advanced techniques (i.e., informed priors, open‐population distance sampling models, and integrated modeling approaches) can further reduce total estimator error by leveraging information from existing and ongoing data collection. By synthesizing the existing literature on CDS, MRDS, TEDS and their extensions, in conjunction with the concepts of total estimator error and the components of the detection process, we provide a comprehensive guide that can be used by the practitioner to more efficiently, effectively, and appropriately apply distance sampling in a variety of settings.

Distance sampling survey effort to improve density estimates of northern bobwhite

AbstractDistance sampling from aerial platforms can provide researchers with precise and efficient density estimates for wildlife populations, particularly over large areas. The intensity of the distance sampling survey depends on the survey effort. Effort can be referred to as coverage, where transect spacing is determined by the observer's sightability distance of the object or animal. Managers and researchers in Texas often use helicopters to survey and collect data for northern bobwhite (Colinus virginianus) density estimates. For bobwhites, 100% coverage represents transect spacing of 200 m, assuming observers can cover out to 100 m on either side of the transects. Often surveys are conducted at 50% coverage or 400 m spacing to reduce cost. Still, the implications of lowering survey effort on the precision of density estimates are unknown, particularly in coverage prescriptions. We flew 2,641 km of line transects each December from 2014 to 2017 and detected 2,333 bobwhite coveys across 7,648 ha of rangeland on the San Antonio Viejo Ranch in Jim Hogg County, TX, USA. We conducted line‐transect distance sampling from a helicopter platform at 50 and 100% coverage and simulated results at coverage <50% using empirical data. Based on the results of simulated surveys at <100% coverage, surveying for bobwhites using helicopters with less than 50% coverage results in variable density estimates (wide 95% confidence intervals) and low precision (coefficient of variation >20%). Empirical surveys conducted at 50 and 100% coverage show little variation in density estimates between the 2 levels of coverage. However, when broken into substrata (areas less than ~1,000 ha), conducting surveys at 50% coverage resulted in <60 detections, which led to low precision in density estimates (coefficient of variation >20%). Our results are based on surveys conducted at the juncture of the Coastal Sand Sheet and Tamaulipan Thorn Scrub ecoregions in south Texas and need to be evaluated in other arid and semi‐arid rangeland systems.

Evaluating unmarked abundance estimators using remote cameras and aerial surveys

AbstractReliable population abundance estimates are invaluable to wildlife management programs. Mark‐recapture techniques are regarded as the gold standard for estimating abundance but can be financially or logistically prohibitive. Recent developments in remote camera analytical approaches have provided alternative methods to estimate unmarked populations efficiently but have undergone limited field testing. In September and October 2020, I assessed 2 camera methods that use the same set of time‐lapse photographs; a space to event (STE) model and instantaneous sampling (IS), applied to a case study of feral sheep (Ovis aries) at the US Army's Pōhakuloa Training Area (PTA) on Hawai`i Island. Results of the camera methods were compared to an abundance estimate calculated from an aerial distance sampling survey completed concurrently with camera sampling. A comparison of confidence intervals indicated no statistical difference between estimates, but the relative imprecision of IS suggested the STE model to be a more reliable estimator. The cost of camera sampling was approximately 3 times that of the aerial survey, but camera sampling became more economical if the area was resurveyed 3 or more times. My study showed the STE model to be a cost effective, practical abundance estimator of feral sheep when compared to well‐established aerial distance sampling techniques, and therefore should offer considerable potential for the conservation and management of other easily identifiable species.

Road-based line distance surveys overestimate densities of olive baboons.

Estimating population density and population dynamics is essential for understanding primate ecology and relies on robust methods. While distance sampling theory provides a robust framework for estimating animal abundance, implementing a constrained, non-systematic transect design could bias density estimates. Here, we assessed potential bias associated with line distance sampling surveys along roads based on a case study with olive baboons (Papio anubis) in Lake Manyara National Park (Tanzania). This was achieved by comparing density estimates of olive baboons derived from road transect surveys with density estimates derived from estimating the maximum number of social groups (via sleeping site counts) and multiplying this metric with the estimated average size of social groups. From 2011 to 2019, we counted olive baboons along road transects, estimated survey-specific densities in a distance sampling framework, and assessed temporal population trends. Based on the fitted half-normal detection function, the mean density was 132.5 baboons km-2 (95% CI: 110.4–159.2), however, detection models did not fit well due to heaping of sightings on and near the transects. Density estimates were associated with relatively wide confidence intervals that were mostly caused by encounter rate variance. Based on a generalized additive model, baboon densities were greater during the rainy seasons compared to the dry seasons but did not show marked annual trends. Compared to estimates derived from the alternative method (sleeping site survey), distance sampling along road transects overestimated the abundance of baboons more than threefold. Possibly, this overestimation was caused by the preferred use of roads by baboons. While being a frequently used technique (due to its relative ease of implementation compared to spatially randomized survey techniques), inferring population density of baboons (and possibly other species) based on road transects should be treated with caution. Beyond these methodological concerns and considering only the most conservative estimates, baboon densities in LMNP are among the highest across their geographic distribution range.