Reliable Estimates Of Population Size Research Articles

Assessing population status and influencing factors of alpine musk deer in patchy habitats: Implications for conservation strategies

Musk deer (Moschus spp.) are widely known for its musk and are globally endangered as a result of poaching, habitat loss, and fragmentation. To facilitate restoration of the alpine musk deer (M. chrysogaster) in existing areas, reliable estimates of population size and influencing factors are essential to assess effectiveness of conservation interventions, particularly for isolated musk deer populations in patches. In this paper, we used line transect and camera trap data collected from 2020 to 2022 in the Helan mountains to assess the population status and characterized the influencing factors of alpine musk deer. Our findings indicate that musk deer are patchily distributed in three areas of high elevation, with the population limited to less than 200 individuals, remaining below historic levels (compared to 1995). There was a significant positive correlation between the role of sympatric species on musk deer, with red fox (Vulpes vulpes), badger (Meles meles) and blue eared-pheasant (Crossoptilon auritum) having a significant effect on the out-modeled pathway. Variable but insignificant effects of anthropogenic activities were observed across all species categories, which could be due to mutual adaptation over time. Our results imply that the recovery of sensitive population in island-like habitats remains challenging and may be exacerbated by limited environment and resources. Our study underscores the necessity of establishing ecological corridors to enhance habitat connectivity for alpine musk deer, undertaking conservation genetics research on isolated populations, controlling stray dogs to maintain interspecific balance, and implementing electronic fencing to mitigate human disturbance and resource competition. This study provides basic information for understanding the population status of alpine musk deer and offers insights for conservation efforts.

Optimizing the automated recognition of individual animals to support population monitoring.

Reliable estimates of population size and demographic rates are central to assessing the status of threatened species. However, obtaining individual-based demographic rates requires long-term data, which is often costly and difficult to collect. Photographic data offer an inexpensive, noninvasive method for individual-based monitoring of species with unique markings, and could therefore increase available demographic data for many species. However, selecting suitable images and identifying individuals from photographic catalogs is prohibitively time-consuming. Automated identification software can significantly speed up this process. Nevertheless, automated methods for selecting suitable images are lacking, as are studies comparing the performance of the most prominent identification software packages. In this study, we develop a framework that automatically selects images suitable for individual identification, and compare the performance of three commonly used identification software packages; Hotspotter, I3S-Pattern, and WildID. As a case study, we consider the African wild dog, Lycaon pictus, a species whose conservation is limited by a lack of cost-effective large-scale monitoring. To evaluate intraspecific variation in the performance of software packages, we compare identification accuracy between two populations (in Kenya and Zimbabwe) that have markedly different coat coloration patterns. The process of selecting suitable images was automated using convolutional neural networks that crop individuals from images, filter out unsuitable images, separate left and right flanks, and remove image backgrounds. Hotspotter had the highest image-matching accuracy for both populations. However, the accuracy was significantly lower for the Kenyan population (62%), compared to the Zimbabwean population (88%). Our automated image preprocessing has immediate application for expanding monitoring based on image matching. However, the difference in accuracy between populations highlights that population-specific detection rates are likely and may influence certainty in derived statistics. For species such as the African wild dog, where monitoring is both challenging and expensive, automated individual recognition could greatly expand and expedite conservation efforts.

Key Population Size Estimation to Guide HIV Epidemic Responses in Nigeria: Bayesian Analysis of 3-Source Capture-Recapture Data.

Nigeria has the fourth largest burden of HIV globally. Key populations, including female sex workers, men who have sex with men, and people who inject drugs, are more vulnerable to HIV than the general population due to stigmatized and criminalized behaviors. Reliable key population size estimates are needed to guide HIV epidemic response efforts. The objective of our study was to use empirical methods for sampling and analysis to improve the quality of population size estimates of female sex workers, men who have sex with men, and people who inject drugs in 7 states (Akwa Ibom, Benue, Cross River, Lagos, Nasarawa, Rivers, and the Federal Capital Territory) of Nigeria for program planning and to demonstrate improved statistical estimation methods. From October to December 2018, we used 3-source capture-recapture to produce population size estimates in 7 states in Nigeria. Hotspots were mapped before 3-source capture-recapture started. We sampled female sex workers, men who have sex with men, and people who inject drugs during 3 independent captures about one week apart. During hotspot encounters, key population members were offered inexpensive, memorable objects unique to each capture round. In subsequent rounds, key population members were offered an object and asked to identify objects received during previous rounds (if any). Correct responses were tallied and recorded on tablets. Data were aggregated by key population and state for analysis. Median population size estimates were derived using Bayesian nonparametric latent-class models with 80% highest density intervals. Overall, we sampled approximately 310,000 persons at 9015 hotspots during 3 independent captures. Population size estimates for female sex workers ranged from 14,500 to 64,300; population size estimates for men who have sex with men ranged from 3200 to 41,400; and population size estimates for people who inject drugs ranged from 3400 to 30,400. This was the first implementation of these 3-source capture-recapture methods in Nigeria. Our population size estimates were larger than previously documented for each key population in all states. The Bayesian models account for factors, such as social visibility, that influence heterogeneous capture probabilities, resulting in more reliable population size estimates. The larger population size estimates suggest a need for programmatic scale-up to reach these populations, which are at highest risk for HIV.

A comparison of density estimation methods for monitoring marked and unmarked animal populations

AbstractEffective monitoring of wildlife populations forms the foundation of modern‐day conservation biology. Without reliable estimates of population size, it is not possible to determine population trends, a key requirement in determining species status under international legislation. Carnivores are one of the more difficult taxonomic groups to monitor due to low population densities and elusive behavior. Here, we compare conventional live trapping and two more modern, noninvasive field methods of population estimation: genetic fingerprinting from hair tube sampling and camera trapping for the pine marten (Martes martes). We apply marked spatial capture–recapture (SCR) models to the genetic and live‐trapping data where individuals were identifiable, and unmarked SCR (uSCR), camera‐trap distance sampling (CT‐DS), and random encounter models (REMs) to the camera‐trap data where individual ID was not possible. All five approaches produced plausible and relatively consistent point estimates (0.49–1.20 individuals/km2) despite differences in precision, cost, and effort being apparent. Genetic fingerprinting produced the most precise estimate out of the two approaches for marked animal populations and had the key benefit of being noninvasive but was the most expensive of all the methods. Live trapping produced the highest point estimate while being cheapest, but the most labor intensive and least precise. The camera‐trapping methods for unmarked animal populations were the most time efficient and precise except uSCR with a moderately informative prior (uSCRm), which produced the second least precise density estimate of all the methods compared. The CT‐DS produced the most precise estimate of all the methods, followed by REM and then uSCR with a strongly informative prior (uSCRs). While choice of method of density estimation depends on objectives and funding constraints, as well as the species of interest, we demonstrate the importance of usinga prioriknowledge of target species and consideration of planned statistical analysis to produce appropriate experimental designs with critical consideration required regarding trap spacing and spatial extent. Such considerations broaden the comparability and applicability of these methods and will serve to provide key reference estimates for researchers, wildlife managers, and non‐governmental organizations involved in monitoring wildlife populations.

Combining N-mixture models with ecological niche modeling supplies a low-cost and fast procedure for estimating population size in remote areas

Monitoring population changes and trends is a central task in conservation. However, obtaining detailed information for wide and low accessible areas, such as remote islands, is challenging, and cannot be achieved with conventional approaches, such as capture–mark–recapture protocols (CMR). In this paper, we show that combining N-mixture models with ecological niche modeling allows assessing reliable estimates of population size over large target areas on short time intervals. We used it to estimate the population size of a subspecies of the Italian wall lizards (Podarcis siculus calabresiae) endemic to the Island of Montecristo (10.39 km2 in surface). During a single week, we first generated a niche model of the species based on satellite images sampled few days before sampling. Then, we estimated lizard abundance through Bayesian N-mixture models on repeated counts (n = 3) along transects (n = 6), settled in different areas of habitat suitability defined on the basis of the niche model. Finally, we estimated in approximately 20.000 the total number of lizards living in the Island by extrapolating the values computed on transects to the areas of the islands with the same suitability estimated by the niche model. The procedure can be easily repeated allowing monitoring the status of conservation of the species in the island of Montecristo. More in general, this procedure has the potential to be applied to monitor any other species of conservation interest in remote areas whenever detailed satellite images are available.Graphical

Passive acoustic monitoring provides predictable and reliable underestimates of population size and longevity in wild Savannah Sparrows

Abstract Many breeding birds produce conspicuous sounds, providing tremendous opportunities to study free-living birds through acoustic recordings. Traditional methods for studying population size and demographic features depend on labor-intensive field research. Passive acoustic monitoring provides an alternative method for quantifying population size and demographic parameters, but this approach requires careful validation. To determine the accuracy of passive acoustic monitoring for estimating population size and demographic parameters, we used autonomous recorders to sample an island-living population of Savannah Sparrows (Passerculus sandwichensis) over a 6-year period. Using the individually distinctive songs of males, we estimated the male population size as the number of unique songs detected in the recordings. We analyzed songs across 6 years to estimate birth year, death year, and longevity. We then compared the estimates with field data in a blind analysis. Estimates of male population size through passive acoustic monitoring were, on average, 72% of the true male population size, with higher accuracy in lower-density years. Estimates of demographic rates were lower than true values by 29% for birth year, 23% for death year, and 29% for longevity. This is the first investigation to estimate longevity with passive acoustic monitoring and adds to a growing number of studies that have used passive acoustic monitoring to estimate population size. Although passive acoustic monitoring underestimated true population parameters, likely due to the high similarity among many male songs, our findings suggest that autonomous recorders can provide reliable estimates of population size and longevity in a wild songbird.

Scaling Occupancy Estimates up to Abundance for Wolves

ABSTRACTManagement of wildlife populations often requires reliable estimates of population size or distribution. Estimating abundance can be logistically difficult, and occupancy models have been used as a less expensive proxy for abundance estimation. Another alternative is to use independent estimates of home‐range size and mean group size to directly scale occupancy estimates up to abundance. We used simulations to explore when scaling occupancy up to abundance is reliable, and as an example we applied an occupancy approach to estimate abundance of wolves (Canis lupus) from roadside snow‐tracking surveys in northern Wisconsin, USA, in 2016 and 2018. Estimates of wolf abundance were plausible and compared favorably with independent estimates produced by territory mapping, and snow‐tracking data requirements were lower than for territory mapping. Simulation results suggested that reasonable abundance estimates could be obtained under some conditions but also that severe positive bias could result under other conditions, especially when populations were small and dispersed, home range size was small, and areal sampling units were large. Positive bias in abundance estimates occurs because of closure assumption violations when tracks from a single wolf or pack are detected in >1 sample unit, and the sum of the sample unit areas where tracks were detected exceed the sum of the home range areas. Bias was minimized when sampling units were small relative to home range size or when sampling units were route segments that approximate point sample units, and when home ranges were highly aggregated. We conclude that, although caution is warranted when scaling occupancy estimates up to abundance, scaled occupancy models can provide feasible and reliable estimates of abundance, assuming home range size and mean group size are accurately known or estimated, sampling units are appropriately chosen, and covariates that aggregate home ranges can be used to accurately predict occupancy probability. © 2021 The Authors. The Journal of Wildlife Management published by Wiley Periodicals LLC on behalf of The Wildlife Society.

Visibility Bias of Waterbirds During Aerial Surveys in the Nonbreeding Season

ABSTRACTAerial surveys for waterfowl and other waterbirds provide abundance estimates that are commonly used by state and federal agencies for waterfowl and wetland management. However, most existing surveys provide an index of abundance and are uncorrected for visibility bias, which may limit their use in accurately determining local population size. We used concurrent ground and aerial surveys to estimate visibility bias during cruise‐style waterfowl surveys from September through January 2014–2017 along the Illinois River Valley, Illinois, USA. Immediately before an aerial survey, a ground observer counted waterfowl and other waterbirds by species within a distinct survey area and counts were compared with aerial abundance estimates to quantify detection rate and count bias (i.e., visibility bias). Overall, waterfowl guilds had high detection rates and low count bias, resulting in low overall visibility bias (ducks, −11% [SE = 5%]; geese, −8% [SE = 3%]; swans, −5% [SE = 3%]). At the species level, visibility bias varied greatly (e.g., green‐winged teal [Anas crecca], 182% [SE = 221%]; American wigeon [Mareca americana], −74% [SE = 20%]). Group size, species prevalence, cloud cover, and temperature influenced visibility bias, but direction and magnitude of effects were variable among taxa. Low visibility bias for most guilds indicated that well‐designed, cruise‐style aerial surveys with bias estimation techniques provided reliable estimates of population size and have great utility for monitoring waterfowl and other waterbirds as part of an adaptive management framework. © 2021 The Wildlife Society.

Playback point counts and N-mixture models suggest higher than expected abundance of the critically endangered blond titi monkey in northeastern Brazil.

Effective management of threatened species requires accurate population size estimation and monitoring. However, reliable population size estimates are lacking for many endangered species. The critically endangered blond titi monkey (Callicebus barbarabrownae) is an endemic primate of the Caatinga biome in Northeastern Brazil. A previous assessment based on presence-only data estimated a minimum population size of 260 mature individuals in 2,636 km2 , and studies based on visual records suggested very low local relative abundance. However, this cryptic species is known to be difficult to visually detect. We played back recordings of C. barbarabrownae loud calls to count the number of responding groups in 34 sampling sites during 9 consecutive days in a 221-km2 study area. Repeated group counts at sites were used in N-mixture models, which account for imperfect detection, to estimate the number of groups in relation to dry forest area and distance to villages. We estimated a total of 91 groups in the study area. Considering the mean number of adults per group as three, we estimated a population of 273 adult individuals, resulting in a density of 2.3 individuals/km2 in the dry forest habitat. Detection probability was four times higher for surveys conducted between sunrise to midmorning than between midmorning to sunset. We also found that C. barbarabrownae abundance increases with increasing dry forest area and increasing distance to the nearest village, indicating the need to promote dry forest restoration in the Caatinga. As our results suggest a larger population of C. barbarabrownae than had been previously estimated for its entire distribution, our results suggest a need for similar assessments in other areas to reliably estimate the total population size. This study demonstrates how playback surveys coupled with N-mixture models can be used to estimate population sizes of acoustically-responsive primates, and thus contribute to more effective conservation management.

Modelling the effect of covariates on the detectability and density of native blackbucks and invasive feral-horse using Multiple Covariate Distance Sampling at Point Calimere Wildlife Sanctuary, Southern India

Reliable estimates of population size and a knowledge of determinants of detectability and density estimates are crucial for effective conservation of species. Using Multiple Covariate Distance Sampling (MCDS), we modelled the influence of covariates on detection probability and density estimates of native blackbuck Antilope cervicapra and the invasive feral-horse Equus caballus at Point Calimere Wildlife Sanctuary. Grids of 1 × 1 km size were overlaid on the study area with a 1-km line transect in alternate grid cells. Sixteen transects were walked four times each, which detected 199 blackbuck and 152 feral-horse clusters. On each sighting, the climatic, habitat and anthropogenic covariates were recorded, which are likely to affect detection probability. At first, exploratory analyses were made using Conventional Distance Sampling (CDS) to arrive at estimates. Later, in Multiple Covariate Distance Sampling (MCDS), key models were fit into the dataset after selecting the potential covariates that had a significant effect on detection distances obtained from FAMD/PCA, and the best one was selected based on AIC. The MCDS analysis in blackbuck included covariates, viz., distance to water in the best model (29 individuals/km2; CI 22–36; detection probability = 0.58), followed by distance to feral-horse, sampling time and principal diet. The covariate distance to water emerged as the best model for feral-horse as well (13 individuals/km2; CI 9–18; detection probability = 0.36), followed by distance to cattle and principal diet. While the MCDS approach outperformed the CDS global and survey-strata estimates in blackbuck, both the approaches had a marginal difference in feral-horse. Post-stratification analysis showed that blackbuck density increased significantly with distance to water and feral-horse, but insignificantly with the absence of principal diet; whereas, the density of the feral-horse increased significantly with distance to water and cattle in the presence of principal diet. These findings suggest the ability of feral-horse to keep the blackbuck away from optimal areas, where the principal diet is abundant. Our study, thus, illustrates the need for the use of MCDS approach that ascertained (i) reliable population density estimates, (ii) spatiotemporal constraint on large herbivores caused by overabundance of water during the wet season, and (iii) competitive interaction of the invasive feral-horse with the native blackbuck and its likely effect on the latter keeping away from the former and the principal diet to overcome competition. Thus, the study highlights the impact of feral-horse on the native species and suggests measures for the long-term conservation of the blackbuck.

Population size estimation with interval censored counts and external information: Prevalence of multiple sclerosis in Rome.

We discuss Bayesian log-linear models for incomplete contingency tables with both missing and interval censored cells, with the aim of obtaining reliable population size estimates. We also discuss use of external information on the censoring probability, which may substantially reduce uncertainty. We show in simulation that information on lower bounds and external information can each improve the mean squared error of population size estimates, even when the external information is not completely accurate. We conclude with an original example on estimation of prevalence of multiple sclerosis in the metropolitan area of Rome, where five out of six lists have interval censored counts. External information comes from mortality rates of multiple sclerosispatients.

Population estimates of Antillean manatees in Puerto Rico: an analytical framework for aerial surveys using multi-pass removal sampling

AbstractEffective management of the threatened Antillean manatee (Trichechus manatus manatus) in Puerto Rico requires reliable estimates of population size. Estimates are needed to assess population responses to management actions, and whether recovery objectives have been met. Aerial surveys have been conducted since 1976, but none adjusted for imperfect detection. We summarize surveys since 1976, report on current distribution, and provide population estimates after accounting for apparent detection probability for surveys between June 2010 and March 2014. Estimates in areas of high concentration (hotspots) averaged 317 ± 101, three times higher than unadjusted counts (104 ± 0.56). Adjusted estimates in three areas outside hotspots also differed markedly from counts (75 ± 9.89 versus 19.5 ± 3.5). Average minimum island-wide estimate was 386 ± 89, similar to the maximum estimate of 360 suggested in 2005, but fewer than the 700 recently suggested by the Puerto Rico Manatee Conservation Center. Manatees were more widespread than previously understood. Improving estimates, locally or island-wide, will require stratifying the island differently and greater knowledge about factors affecting detection probability. Sharing our protocol with partners in nearby islands (e.g., Cuba, Jamaica, Hispaniola), whose populations share genetic make-up, would contribute to enhanced regional conservation through better population estimates and tracking range expansion.El manejo efectivo del manatí antillano amenazado en Puerto Rico requiere estimados de tamaños de poblaciónes confiables. Dichas estimaciones poblacionales son necesarias para evaluar las respuestas a las acciones de manejo, y para determinar si los objetivos de recuperación han sido alcanzados. Se han realizado censos aéreos desde 1976, pero ninguno de ellos han sido ajustados para detecciones imperfectas. Aquí resumimos los censos desde 1976, actualizamos la distribución, y reportamos los primeros estimados poblacionales ajustados para la probabilidad de detección aparente en los censos de Junio 2010 a Marzo 2014. Las estimaciones poblacionales en áreas de mayor concentración del manatí promedió 317 ± 103, tres veces más abundante que los conteos sin ajuste (104 ± 0.56). Las estimaciones poblacionales en tres áreas fuera de las áreas de mayor concentración del manatí también fueron marcadamente diferentes (75 ± 9.89 vs 19.5 ± 3.5). El estimado mínimo poblacional en la isla entera fue de 386 ± 89, similar al estimado máximo de 360 sugerido en el año 2005, pero menor a los 700 sugeridos recientemente por el Centro de Conservación de Manatíes de Puerto Rico. Documentamos que el manatí tiene una distribución más amplia de lo que se sabía con anterioridad. El mejoramiento de los estimados poblacionales locales o a nivel de isla requerirá que se estratifique a la isla en forma diferente y que se investiguen los factores que influencian a la probabilidad de detección. Compartir protocolos como este con colaboradores de islas vecinas (por. ej., Cuba, Jamaica, Española), cuyas poblaciones de manatíes comparten material genético, contribuiría a la conservación regional mediante mejores estimaciones poblacionales y monitoreo de la expansión de su ámbito doméstico.

On the robustness of N‐mixture models

N-mixture models provide an appealing alternative to mark-recapture models, in that they allow for estimation of detection probability and population size from count data, without requiring that individual animals be identified. There is, however, a cost to using the N-mixture models: inference is very sensitive to the model's assumptions. We consider the effects of three violations of assumptions that might reasonably be expected in practice: double counting, unmodeled variation in population size over time, and unmodeled variation in detection probability over time. These three examples show that small violations of assumptions can lead to large biases in estimation. The violations of assumptions we consider are not only small qualitatively, but are also small in the sense that they are unlikely to be detected using goodness-of-fit tests. In cases where reliable estimates of population size are needed, we encourage investigators to allocate resources to acquiring additional data, such as recaptures of marked individuals, for estimation of detection probabilities.

Toward reliable population estimates of wolves by combining spatial capture-recapture models and non-invasive DNA monitoring

Decision-makers in wildlife policy require reliable population size estimates to justify interventions, to build acceptance and support in their decisions and, ultimately, to build trust in managing authorities. Traditional capture-recapture approaches present two main shortcomings, namely, the uncertainty in defining the effective sampling area, and the spatially-induced heterogeneity in encounter probabilities. These limitations are overcome using spatially explicit capture-recapture approaches (SCR). Using wolves as case study, and non-invasive DNA monitoring (faeces), we implemented a SCR with a Poisson observation model in a single survey to estimate wolf density and population size, and identify the locations of individual activity centres, in NW Iberia over 4,378 km2. During the breeding period, posterior mean wolf density was 2.55 wolves/100 km2 (95%BCI = 1.87–3.51), and the posterior mean population size was 111.6 ± 18.8 wolves (95%BCI = 81.8–153.6). From simulation studies, addressing different scenarios of non-independence and spatial aggregation of individuals, we only found a slight underestimation in population size estimates, supporting the reliability of SCR for social species. The strategy used here (DNA monitoring combined with SCR) may be a cost-effective way to generate reliable population estimates for large carnivores at regional scales, especially for endangered species or populations under game management.

Effective implementation of age restrictions increases selectivity of sport hunting of the African lion

Abstract Sport hunting of wildlife can play a role in conservation but can also drive population declines if not managed sustainably. Previous simulation modelling found that large felid species could theoretically be hunted sustainably by restricting harvests to older individuals that have likely reproduced. Several African countries currently use age‐based hunting for lions although the outcomes have yet to be evaluated in a wild population. Here we provide the first empirical evidence that a system of incentives sufficiently encouraged age‐based hunting and reduced offtake of a wild felid, thereby reducing the potential risk of unsustainable hunting on a threatened species. We examined long‐term hunting data and the lion population trend in Niassa National Reserve, Mozambique. To incentivise hunter compliance, a “points” system was developed, which rewards operators that harvest lions older than the 6‐year minimum trophy age recommended for sustainable hunting and penalises operators that hunt “underage” lions (<4 years). A key component of this system is the ecological application of key physical traits that predictably change with age in order to estimate (by hunters) and validate (by authorities) trophy individuals’ ages pre‐ and post‐mortem, respectively. Analysis of 138 lion hunts and 87 lion trophies from 2003 to 2015 revealed that after enforcement of age restrictions in 2006, hunters shifted harvests to suitably aged lions (>6 years), from 25% of offtakes in 2004 to 100% by 2014. Simultaneously, the number of lions and percentage of quota harvested decreased, resulting in lower lion offtakes. Following an initial decrease after enforcement of the ageing system, the percentage of hunts harvesting lions stabilised, demonstrating that hunters successfully located and aged older lions. Synthesis and applications. Evidence suggests that age restrictions combined with an incentive‐based points system regulated sport hunting and reduced pressure on the lion population. We attribute the successful implementation of this management system to: (1) committed, consistent enforcement by management authorities, (2) genuine involvement of all stakeholders from the start, (3) annual auditing by an independent third party, (4) the reliable, transparent, straightforward ageing process and (5) the simple, pragmatic points system for incentivising hunter compliance. Our study demonstrates that the use of age restrictions can increase the selectivity of sport hunting and lower trophy offtakes to reduce the possibility of unsustainable sport hunting negatively impacting species populations in the absence of reliable estimates of population size. It must be noted, however, that there was no measurable change in the lion numbers over the past decade that could be attributed to the implementation of this policy alone.

Estimating the Size of the MSM Population in Metro Vancouver, Canada, Using Multiple Methods and Diverse Data Sources.

Men who have sex with men (MSM) are disproportionately affected by HIV globally, regionally in Canada, and locally in Vancouver. Lack of reliable population size estimates of MSM impedes effective implementation of health care services and limits our understanding of the HIV epidemic. We estimated the population size of MSM residing in Metro Vancouver drawing on four data sources: the Canadian Community Health Survey (CCHS), a cross-sectional bio-behavioural MSM survey, HIV testing services data from sexually transmitted infection (STI) clinics serving MSM, and online social networking site Facebook. Estimates were calculated using (1) direct estimates from the CCHS, (2) "Wisdom of the Crowds" (WOTC), and (3) the multiplier method using data from a bio-behavioural MSM survey, clinic-based HIV testing, and online social media network site Facebook. Data sources requiring greater public disclosure of sexual orientation resulted in our mid-range population estimates (Facebook 23,760, CCHS 30,605). The WOTC method produced the lowest estimate, 10,000. The multiplier method using STI clinic HIV testing data produced the largest estimate, 41,777. The median of all estimates was 27,183, representing 2.9% of the Metro Vancouver census male adult population, with an interquartile range of 1.1-4.5%. Using multiple data sources, our estimates of the MSM population in Metro Vancouver are similar to population prevalence estimates based on population data from other industrialized nations. These findings will support understanding of the HIV burden among MSM and corresponding public health and health services planning for this key population.

Population size, distribution and status of the remote and Critically Endangered Bawean deer Axis kuhlii

AbstractConservation of rare ungulates requires reliable population size estimates and distribution maps for prioritizing investments and assessing the effectiveness of conservation measures. We used both camera trapping and a random encounter model approach, and faecal pellet group counts, to update the range and population size of the Bawean deer Axis kuhlii in the Bawean Island Nature Reserve and Wildlife Sanctuary, Indonesia. We studied 2-month periods to fulfil the assumption of population closure. Both methods provided similar population density estimates (higher in the dry season) of c. 227–416 individuals. The estimated range of the species is significantly narrower than previously reported. The main threats (habitat loss as a result of illegal logging, and disturbance by dogs and hunters) are ongoing. Based on these results we suggest that the species should retain its Critically Endangered status on the IUCN Red List.

Estimating abundance and density of Amur tigers along the Sino-Russian border.

As an apex predator the Amur tiger (Panthera tigris altaica) could play a pivotal role in maintaining the integrity of forest ecosystems in Northeast Asia. Due to habitat loss and harvest over the past century, tigers rapidly declined in China and are now restricted to the Russian Far East and bordering habitat in nearby China. To facilitate restoration of the tiger in its historical range, reliable estimates of population size are essential to assess effectiveness of conservation interventions. Here we used camera trap data collected in Hunchun National Nature Reserve from April to June 2013 and 2014 to estimate tiger density and abundance using both maximum likelihood and Bayesian spatially explicit capture-recapture (SECR) methods. A minimum of 8 individuals were detected in both sample periods and the documentation of marking behavior and reproduction suggests the presence of a resident population. Using Bayesian SECR modeling within the 11 400 km(2) state space, density estimates were 0.33 and 0.40 individuals/100 km(2) in 2013 and 2014, respectively, corresponding to an estimated abundance of 38 and 45 animals for this transboundary Sino-Russian population. In a maximum likelihood framework, we estimated densities of 0.30 and 0.24 individuals/100 km(2) corresponding to abundances of 34 and 27, in 2013 and 2014, respectively. These density estimates are comparable to other published estimates for resident Amur tiger populations in the Russian Far East. This study reveals promising signs of tiger recovery in Northeast China, and demonstrates the importance of connectivity between the Russian and Chinese populations for recovering tigers in Northeast China.

Limited catching bias in a wild population of birds with near-complete census information.

Animal research often relies on catching wild animals; however, individuals may have different trappability, and this can generate bias. We studied bias in mist netting, the main method for catching wild birds. The unusually high resighting rate in our study population—house sparrows (Passer domesticus) on Lundy Island (England)—allowed us to obtain accurate estimates of the population size. This unique situation enabled us to test for catching bias in mist netting using deviations from the expected Poisson distribution. There was no evidence that a fraction of the birds in the population consistently remained uncaught. However, we detected a different bias: More birds than expected were captured only once within a year. This bias probably resulted from a mixture of fieldworkers sometimes ignoring rapid recaptures and birds becoming net shy after their first capture. We had sufficient statistical power with the available data to detect a substantial uncaught fraction. Therefore, our data are probably unbiased toward catching specific individuals from our population. Our analyses demonstrate that intensively monitored natural insular populations, in which population size can be estimated precisely, provide the potential to address important unanswered questions without concerns about a fraction of the population remaining uncaught. Our approach can help researchers to test for catching bias in closely monitored wild populations for which reliable estimates of population size and dispersal are available.

Reliability of different mark-recapture methods for population size estimation tested against reference population sizes constructed from field data.

Reliable estimates of population size are fundamental in many ecological studies and biodiversity conservation. Selecting appropriate methods to estimate abundance is often very difficult, especially if data are scarce. Most studies concerning the reliability of different estimators used simulation data based on assumptions about capture variability that do not necessarily reflect conditions in natural populations. Here, we used data from an intensively studied closed population of the arboreal gecko Gehyra variegata to construct reference population sizes for assessing twelve different population size estimators in terms of bias, precision, accuracy, and their 95%-confidence intervals. Two of the reference populations reflect natural biological entities, whereas the other reference populations reflect artificial subsets of the population. Since individual heterogeneity was assumed, we tested modifications of the Lincoln-Petersen estimator, a set of models in programs MARK and CARE-2, and a truncated geometric distribution. Ranking of methods was similar across criteria. Models accounting for individual heterogeneity performed best in all assessment criteria. For populations from heterogeneous habitats without obvious covariates explaining individual heterogeneity, we recommend using the moment estimator or the interpolated jackknife estimator (both implemented in CAPTURE/MARK). If data for capture frequencies are substantial, we recommend the sample coverage or the estimating equation (both models implemented in CARE-2). Depending on the distribution of catchabilities, our proposed multiple Lincoln-Petersen and a truncated geometric distribution obtained comparably good results. The former usually resulted in a minimum population size and the latter can be recommended when there is a long tail of low capture probabilities. Models with covariates and mixture models performed poorly. Our approach identified suitable methods and extended options to evaluate the performance of mark-recapture population size estimators under field conditions, which is essential for selecting an appropriate method and obtaining reliable results in ecology and conservation biology, and thus for sound management.