Integrated distance sampling models for simple point counts

Point counts (PCs) are widely used in biodiversity surveys but, despite numerous advantages, simple PCs suffer from several problems: detectability, and therefore abundance, is unknown; systematic spatiotemporal variation in detectability yields biased inferences, and unknown survey area prevents formal density estimation and scaling-up to the landscape level. We introduce integrated distance sampling (IDS) models that combine distance sampling (DS) with simple PC or detection/nondetection (DND) data to capitalize on the strengths and mitigate the weaknesses of each data type. Key to IDS models is the view of simple PC and DND data as aggregations of latent DS surveys that observe the same underlying density process. This enables the estimation of separate detection functions, along with distinct covariate effects, for all data types. Additional information from repeat or time-removal surveys, or variable survey duration, enables the separate estimation of the availability and perceptibility components of detectability with DS and PC data. IDS models reconcile spatial and temporal mismatches among data sets and solve the above-mentioned problems of simple PC and DND data. To fit IDS models, we provide JAGS code and the new "IDS()" function in the R package unmarked. Extant citizen-science data generally lack the information necessary to adjust for detection biases, but IDS models address this shortcoming, thus greatly extending the utility and reach of these data. In addition, they enable formal density estimation in hybrid designs, which efficiently combine DS with distance-free, point-based PC or DND surveys. We believe that IDS models have considerable scope in ecology, management, and monitoring.

Local and regional-scale effects of hedgerows on grassland- and forest-associated bird populations within agroecosystems

Linear woody features (LWFs), like hedgerows along field edges, provide wildlife habitat and support biodiversity in agroecosystems. Assessments of LWFs usually focus on community-level indices, such as species richness. However, effective conservation actions need to balance the contrasting habitat preferences of different wildlife species, necessitating a focus on population-level effects in working landscapes. We assessed associations between LWFs and abundance for 45 bird species within an intensive agroecosystem in eastern Ontario, Canada. We used distance- and removal-sampling methods across 4 years (2016-2019) to estimate local bird abundance in habitats representing a range of LWF densities. We also predicted abundance across a subset of the study region with and without LWFs to understand their contribution to regional population density. Associations between local bird abundance and LWFs were variable among species, but overall community effects were clearly positive, particularly for forest and shrubland species. At the site level, 20/45 species (44%) had higher densities associated with greater LWF presence on average, compared to 5/45 (11%) with negative associations. At the regional scale, LWFs had predicted benefits on total abundance for 31 species (69%), contributing to an estimated 20% increase on average. Positive effects were most pronounced in areas with greater agricultural land use (primarily field crops), suggesting LWFs may provide crucial habitat in heavily modified landscapes but have little to no additional benefit for the avian community in areas with greater existing heterogeneity and habitat retention. Species that responded negatively tended to be at risk with strong habitat preferences for intact forests or large, open grasslands and, thus, greater sensitivity to potential edge effects. With rapidly declining songbird populations and a global need for food security, conservation strategies that amplify biodiversity and enhance agricultural productivity through ecosystem services such as pest control, pollination, and water regulation are vital. We demonstrate the benefits of habitat heterogeneity in agroecosystems on songbird densities and highlight the need to integrate local and landscape-level assessments in conservation planning. An effective, balanced strategy includes concentrating LWFs in areas of extensive arable crops, with habitat retention patches where possible, while maintaining heterogeneity through mixtures of natural habitats and pastoral farming in less intensive regions.

How abundant is a species at the limit of its distribution range? Crested porcupine Hystrix cristata and its northern population

The crested porcupine (Hystrix cristata) is a rodent present in Africa and southern Europe (Italy exclusively). The Italian population is expanding from the centre to the north and south, but little is known about the species' abundance. Reliable population density estimates are important for monitoring trends in wildlife populations and for developing effective conservation and management strategies. In this context, we aimed to first report crested porcupine population density on the northern limit of its current distribution range using a non-invasive approach. Specifically, we randomly placed 38 camera traps in an area of 242 km2 in north Italy (Lombardy region), and we applied camera trap distance sampling. We estimated a porcupine density of 0.49 ind·km-2 (±0.33, standard error). The results presented here are the first crested porcupine density estimate accounting for imperfect detection (i.e. species present but not detected). The abundance estimate reported here is fundamental for a better understanding of the species status in Europe and for implementing conservation and management plans.

Assessing mammal population densities in response to urbanization using camera trap distance sampling

Environmental filtering is deemed to play a predominant role in regulating the abundance and distribution of animals during the urbanization process. However, the current knowledge about the effects of urbanization on the population densities of terrestrial mammals is limited. In this study, we compared two invasive mammals (dogs Canis lupus familiaris and cats Felis silvestris) and three indigenous mammals (Siberian weasels Mustela sibirica, Amur hedgehogs Erinaceus amurensis, and Tolai hares Lepus tolai) in response to urbanization using camera trap distance sampling (CTDS) in the rural-urban landscape of Tianjin, China. We used generalized additive mixed models (GAMMs) to test the specific responses of their densities to levels of urbanization. Invasive dogs (2.63 individuals/km2, 95% CI: 0.91-7.62) exhibited similar density estimations to cats (2.15 individuals/km2, 95% CI: 1.31-3.50). Amur hedgehogs were the most abundant species (6.73 individuals/km2, 95% CI: 3.15-14.38), followed by Tolai hares (2.22 individuals/km2, 95% CI: 0.87-5.68) and Siberian weasels (2.15 individuals/km2, 95% CI: 1.06-4.36). The densities of cats, Siberian weasels, and Amur hedgehogs increased with the level of urbanization. The population densities of dogs and cats were only influenced by urban-related variables, while the densities of Siberian weasels and Amur hedgehogs were influenced by both urban-related variables and nature-related variables. Our findings highlight that the CTDS is a suitable and promising method for wildlife surveys in rural-urban landscapes, and urban wildlife management needs to consider the integrated repercussions of urban- and nature-related factors, especially the critical impacts of green space habitats at finer scales.

Abundance and population growth estimates for bare-nosed wombats

Wildlife managers often rely on population estimates, but estimates can be challenging to obtain for geographically widespread species. Spotlight surveys provide abundance data for many species and, when conducted over wide spatial scales, have potential to provide population estimates of geographically widespread species. The bare-nosed wombat (Vombatus ursinus) has a broad geographical range and is subject to spotlight surveys. We used 19 years (2002-2020) of annual spotlight surveys to provide the first estimates of population abundance for two of the three extant bare-nosed wombat subspecies: V. u. ursinus on Flinders Island; and V. u. tasmaniensis on the Tasmanian mainland. Using distance sampling methods, we estimated annual rates of change and 2020 population sizes for both subspecies. Tasmanian mainland surveys included habitat data, which allowed us to also look for evidence of habitat associations for V. u. tasmaniensis. The average wombat density estimate was higher on Flinders Island (0.42 ha-1, 95% CI = 0.25-0.79) than on the Tasmanian mainland (0.11 ha-1, CI = 0.07-0.19) and both wombat subspecies increased over the 19-year survey period with an estimated annual growth rate of 2.90% (CI = -1.7 to 7.3) on Flinders Island and 1.20% (CI = -1.1 to 2.9) on mainland Tasmania. Habitat associations for V. u. tasmaniensis were weak, possibly owing to survey design; however, we detected regional variation in density for this subspecies. We estimated the population size of V. u. ursinus to be 71,826 (CI = 43,913-136,761) on Flinders Island, which when combined with a previously published estimate of 2599 (CI = 2254-2858) from Maria Island, where the subspecies was introduced, provides a total population estimate. We also estimated 840,665 (CI = 531,104-1,201,547) V. u. tasmaniensis on mainland Tasmania. These estimates may be conservative, owing to individual heterogeneity in when wombats emerge from burrows. Although these two subspecies are not currently threatened, our population estimates provide an important reference when assessing their population status in the future, and demonstrate how spotlight surveys can be valuable to inform management of geographically widespread species.

Pooling robustness in distance sampling: Avoiding bias when there is unmodelled heterogeneity

The pooling robustness property of distance sampling results in unbiased abundance estimation even when sources of variation in detection probability are not modeled. However, this property cannot be relied upon to produce unbiased subpopulation abundance estimates when using a single pooled detection function that ignores subpopulations. We investigate by simulation the effect of differences in subpopulation detectability upon bias in subpopulation abundance estimates. We contrast subpopulation abundance estimates using a pooled detection function with estimates derived using a detection function model employing a subpopulation covariate. Using point transect survey data from a multispecies songbird study, species-specific abundance estimates are compared using pooled detection functions with and without a small number of adjustment terms, and a detection function with species as a covariate. With simulation, we demonstrate the bias of subpopulation abundance estimates when a pooled detection function is employed. The magnitude of the bias is positively related to the magnitude of disparity between the subpopulation detection functions. However, the abundance estimate for the entire population remains unbiased except when there is extreme heterogeneity in detection functions. Inclusion of a detection function model with a subpopulation covariate essentially removes the bias of the subpopulation abundance estimates. The analysis of the songbird point count surveys shows some bias in species-specific abundance estimates when a pooled detection function is used. Pooling robustness is a unique property of distance sampling, producing unbiased abundance estimates at the level of the study area even in the presence of large differences in detectability between subpopulations. In situations where subpopulation abundance estimates are required for data-poor subpopulations and where the subpopulations can be identified, we recommend the use of subpopulation as a covariate to reduce bias induced in subpopulation abundance estimates.

Invasive snake causes massive reduction of all endemic herpetofauna on Gran Canaria

Invasive snakes represent a serious threat to island biodiversity, being responsible for far-reaching impacts that are noticeably understudied, particularly regarding native reptiles. We analysed the impact of the invasive California kingsnake, Lampropeltis californiae-recently introduced in the Canary Islands-on the abundance of all endemic herpetofauna of the island of Gran Canaria. We quantified the density in invaded and uninvaded sites for the Gran Canaria giant lizard, Gallotia stehlini, the Gran Canaria skink, Chalcides sexlineatus, and Boettger's wall gecko, Tarentola boettgeri. We used spatially explicit capture-recapture and distance-sampling methods for G. stehlini and active searches under rocks for the abundance of the other two reptiles. The abundance of all species was lower in invaded sites, with a reduction in the number of individuals greater than 90% for G. stehlini, greater than 80% for C. sexlineatus and greater than 50% for T. boettgeri in invaded sites. Our results illustrate the severe impact of L. californiae on the endemic herpetofauna of Gran Canaria and highlight the need for strengthened measures to manage this invasion. We also provide further evidence of the negative consequences of invasive snakes on island reptiles and emphasize the need for further research on this matter on islands worldwide.

Free-Roaming Dog Surveys in Quito, Ecuador: Experiences, Lessons Learned, and Future Work

The selection of a survey method of free-roaming dog populations should be based on analyses of local capacities and management priorities. Here, we compare the results of surveys of the stray dog population in Quito, Ecuador, using two different methodologies and propose an alternative method for future surveys in the city. We carried out all surveys in ~5 km-transects in a sample of eight urban and eight rural parishes (16 transects total). In 2018, we used the capture-recapture method to estimate absolute population size and 95% CI. We began transect surveys at 04 h 00 (local time) and identified individuals with photographs. The main limitations of this method were errors in identifying individuals, since photographs were not always clear, partly due to low light conditions during the surveys. This method also required more time and more complex logistics. In 2019, we used distance sampling to estimate population density and began the surveys at 08 h 00 (local time). Errors in the estimation of animal-observer distances and angles were our main concern when using this method. For future surveys, we propose to carry out direct observations of dog abundance (number of free-roaming dogs/km) during street counts, complemented with capture-recapture surveys every 5 years. This alternative method albeit simple, is sensitive enough to (1) provide local authorities with objective assessments of management interventions, (2) better understanding the dynamics of free-roaming dog populations and (3) increasing public awareness about the problem of pet abandonment through citizen participation in the surveys.

An open spatial capture-recapture model for estimating density, movement, and population dynamics from line-transect surveys

The purpose of many wildlife population studies is to estimate density, movement, or demographic parameters. Linking these parameters to covariates, such as habitat features, provides additional ecological insight and can be used to make predictions for management purposes. Line-transect surveys, combined with distance sampling methods, are often used to estimate density at discrete points in time, whereas capture-recapture methods are used to estimate movement and other demographic parameters. Recently, open population spatial capture-recapture models have been developed, which simultaneously estimate density and demographic parameters, but have been made available only for data collected from a fixed array of detectors and have not incorporated the effects of habitat covariates. We developed a spatial capture-recapture model that can be applied to line-transect survey data by modeling detection probability in a manner analogous to distance sampling. We extend this model to a) estimate demographic parameters using an open population framework and b) model variation in density and space use as a function of habitat covariates. The model is illustrated using simulated data and aerial line-transect survey data for North Atlantic right whales in the southeastern United States, which also demonstrates the ability to integrate data from multiple survey platforms and accommodate differences between strata or demographic groups. When individuals detected from line-transect surveys can be uniquely identified, our model can be used to simultaneously make inference on factors that influence spatial and temporal variation in density, movement, and population dynamics.

Integrating distance sampling and presence-only data to estimate species abundance

Integrated models combine multiple data types within a unified analysis to estimate species abundance and covariate effects. By sharing biological parameters, integrated models improve the accuracy and precision of estimates compared to separate analyses of individual data sets. We developed an integrated point process model to combine presence-only and distance sampling data for estimation of spatially explicit abundance patterns. Simulations across a range of parameter values demonstrate that our model can recover estimates of biological covariates, but parameter accuracy and precision varied with the quantity of each data type. We applied our model to a case study of black-backed jackals in the Masai Mara National Reserve, Kenya, to examine effects of spatially varying covariates on jackal abundance patterns. The model revealed that jackals were positively affected by anthropogenic disturbance on the landscape, with highest abundance estimated along the Reserve border near human activity. We found minimal effects of landscape cover, lion density, and distance to water source, suggesting that human use of the Reserve may be the biggest driver of jackal abundance patterns. Our integrated model expands the scope of ecological inference by taking advantage of widely available presence-only data, while simultaneously leveraging richer, but typically limited, distance sampling data.

Combining species distribution modeling and distance sampling to assess wildlife population size: A case study with the northern yellow-cheeked gibbon (Nomascus annamensis)

Population size and distribution data for wildlife species play an important role in conservation and management, especially for endangered species. However, scientists seriously lack data on the population status of many species. The northern yellow-cheeked gibbon (Nomascus annamensis) is found in southern Lao PDR, central Vietnam, and northeastern Cambodia. The population of the species has significantly declined due to hunting, habitat loss, and the wildlife trade. To examine the population size and distribution of N. annamensis, we conducted a field survey in Song Thanh Nature Reserve, Quang Nam Province, central Vietnam from February to April 2019 using the audio point count method. We combined Distance Sampling and Ecological Niche Modeling to estimate the population of the gibbons. Results showed that the total suitable area for the gibbons was about 302.32 km² , with the two most important variables of the habitat model being the distance-to-villages and forest type. We detected 36 gibbon groups through field surveys and estimated 443 (95% CI, 278-707) gibbon groups in Song Thanh Nature Reserve. Our results indicate that the gibbon population in Song Thanh Nature Reserve is the largest known population of N. annamensis in Vietnam. In addition, our study was the first to combine species distribution modeling with distance sampling to estimate gibbon density and population size. This approach might be useful in surveying and monitoring gibbon populations because it takes imperfect detection probability into account in estimating gibbon population density while estimating the area of potential habitat using environmental variables.

Model-Based Distribution and Abundance of Three Delphinidae in the Mediterranean

Monitoring of Delphinidae species population patterns in the Mediterranean Sea was carried out in a sequence of surveys employing different approaches. Data from seven-year surveys with small catamaran sailing boats were analyzed under model-based approaches. Density Surface Models were used to produce spatial distribution prediction of three Delphinidae species (Stenella coeruleoalba, Tursiops truncatus, and Delphinus delphis) in an extended study area covering much of the Mediterranean Sea. A classical distance sampling protocol was applied in order to calculate the detection probability of clusters. Static (depth, slope, distance from the coast, and distance from isobaths of 200 m) and nonstatic (sea surface temperature and chlorophyll) variables were used to predict the species distribution/abundance in a generalized additive model context. Stenella coeruleoalba was found to be the dominant species, with an extended distribution in the study area; its abundance was significantly affected by both depth and distance. Tursiops truncatus and Delphinus delphis illustrated a significant abundance correlation with depth and chlorophyll, respectively, while both species showed a robust longitude correlation. Our model pinpoints the significance of nondesigned transect line surveys, suggesting the importance of specific habitat areas for future monitoring and conservation aspects of marine mammals.

Estimating the population size of the Sanje mangabey (Cercocebus sanjei) using acoustic distance sampling

The Sanje mangabey (Cercocebus sanjei) is endemic to the Udzungwa Mountains, Tanzania, and is classified as Endangered due to its putatively declining population size, habitat degradation and fragmentation. Previous population size estimates have ranged from 1,350 to 3,500 individuals, with the last direct survey being conducted 15 years before the present study. Previous estimates are now thought to have underestimated the population due to a limited knowledge of group and habitat size, nonsystematic approaches and the use of visual methods that are not suitable for surveying the Sanje mangabey with its semi-terrestrial and elusive behaviors. We used an acoustic survey method with observers recording the distinctive "whoop-gobble" vocalization produced by mangabeys and point transect distance sampling to model a detection function and estimate abundance. Twenty-eight surveys were conducted throughout the two forests where Sanje mangabeys are found: Mwanihana forest in the Udzungwa Mountains National Park (n = 13), and the Uzungwa Scarp Nature Reserve (n = 15). Group density was found to be significantly lower in the relatively unprotected Uzungwa Scarp forest (0.15 groups/km² ; 95% CI: 0.08-0.27) compared to the well-protected Mwanihana forest (0.29 groups/km² ; 95% CI: 0.19-0.43; p = .03). We estimate that there are 1,712 (95% CI: 1,141-2,567) individuals in Mwanihana and 1,455 (95% CI: 783-2,702) in the Uzungwa Scarp, resulting in a total population size of 3,167 (95% CI: 2,181-4,596) individuals. The difference in group density between sites is likely a result of the differing protection status and levels of enforcement between the forests, suggesting that protection of the Uzungwa Scarp should be increased to encourage recovery of the population, and reduce the threat of degradation and hunting. Our results contribute to the reassessment of the species' IUCN Red List status and informing management and conservation action planning.

Community-based wildlife management area supports similar mammal species richness and densities compared to a national park

Community-based conservation models have been widely implemented across Africa to improve wildlife conservation and livelihoods of rural communities. In Tanzania, communities can set aside land and formally register it as Wildlife Management Area (WMA), which allows them to generate revenue via consumptive or nonconsumptive utilization of wildlife. The key, yet often untested, assumption of this model is that economic benefits accrued from wildlife motivate sustainable management of wildlife. To test the ecological effectiveness (here defined as persistence of wildlife populations) of Burunge Wildlife Management Area (BWMA), we employed a participatory monitoring approach involving WMA personnel. At intermittent intervals between 2011 and 2018, we estimated mammal species richness and population densities of ten mammal species (African elephant, giraffe, buffalo, zebra, wildebeest, waterbuck, warthog, impala, Kirk's dik-dik, and vervet monkey) along line transects. We compared mammal species accumulation curves and density estimates with those of time-matched road transect surveys conducted in adjacent Tarangire National Park (TNP). Mammal species richness estimates were similar in both areas, yet observed species richness per transect was greater in TNP compared to BWMA. Species-specific density estimates of time-matched surveys were mostly not significantly different between BWMA and TNP, but elephants occasionally reached greater densities in TNP compared to BWMA. In BWMA, elephant, wildebeest, and impala populations showed significant increases from 2011 to 2018. These results suggest that community-based conservation models can support mammal communities and densities that are similar to national park baselines. In light of the ecological success of this case study, we emphasize the need for continued efforts to ensure that the BWMA is effective. This will require adaptive management to counteract potential negative repercussions of wildlife populations on peoples' livelihoods. This study can be used as a model to evaluate the effectiveness of wildlife management areas across Tanzania.

The effect of a multi-target protocol on cetacean detection and abundance estimation in aerial surveys

A double-platform protocol was implemented in the Bay of Biscay and English Channel during the SCANS-III survey (2016). Two observation platforms using different protocols were operating on board a single aircraft: the reference platform (Scans), targeting cetaceans, and the 'Megafauna' platform, recording all the marine fauna visible at the sea surface (jellyfish to seabirds). We tested for a potential bias in small cetacean detection and density estimation when recording all marine fauna. At a small temporal scale (30 s, roughly 1.5 km), our results provided overall similar perception probabilities for both platforms. Small cetacean perception was higher following the detection of another cetacean within the previous 30 s in both platforms. The only prior target that decreased small cetacean perception during the subsequent 30 s was seabirds, in the Megafauna platform. However, at a larger scale (study area), this small-scale perception bias had no effect on the density estimates, which were similar for the two protocols. As a result, there was no evidence of lower performance regarding small cetacean population monitoring for the multi-target protocol in our study area. Because our study area was characterized by moderate cetacean densities and small spatial overlap of cetaceans and seabirds, any extrapolation to other areas or time requires caution. Nonetheless, by permitting the collection of cost-effective quantitative data for marine fauna, anthropogenic activities and marine litter at the sea surface, the multi-target protocol is valuable for optimizing logistical and financial resources to efficiently monitor biodiversity and study community ecology.

Effects of anthropogenic disturbance on primate density at the landscape scale

Accurate estimations of the abundance of threatened animal populations are required for assessment of species' status and vulnerability and conservation planning. However, density estimation is usually difficult and resource demanding, so researchers often collect data at local scales. However, anthropogenic pressures most often have landscape-level effects, for example, through habitat loss and fragmentation. We applied hierarchical distance sampling (HDS) to transect count data to determine the effect of habitat and anthropogenic factors on the density of 3 arboreal primate species inhabiting 5 distinct tropical forests across a landscape of 19,000 km² in the Udzungwa Mountains of Tanzania. We developed a novel, multiregion extension of HDS that allowed us to model density and detectability jointly across forests without losing site-specific information. For all species, the effect of anthropogenic disturbance on density was overwhelmingly negative among metapopulations: -0.63 Angolan colobus (Colobus angolensis palliatus) (95% Bayesian CI -1.03 to -0.27), -0.54 Udzungwa red colobus (Procolobus gordonorum) (-0.89 to -0.22), and -0.33 Sykes' monkey (Cercopithecus mitis monoides) (-0.63 to -0.07). Some responses to habitat factors were shared, notably the negative effect of elevation and the positive effect of climber coverage. These results are important for conservation science and practice because: the among-populations negative responses to anthropogenic disturbance provides a foundation for development of conservation plans that hold at the landscape scale, which is a comprehensive and cost-efficient approach; the among-species consistency in responses suggests conservation measures may be generalized at the guild level, which is especially relevant given the functional importance of primates in tropical rainforests; and the greater primate densities in areas at low elevation, which are closer to human settlements, point to specific management recommendations, such as the creation of buffer zones and prioritization of areas for protection.

Long-term population monitoring of the threatened and endemic black-headed squirrel monkey (Saimiri vanzolinii) shows the importance of protected areas for primate conservation in Amazonia

Population monitoring of endangered species is essential to the improvement of their management and conservation plans. The black-headed squirrel monkey (Saimiri vanzolinii) is a vulnerable species on the IUCN Red List and has extreme geographical endemism, exhibiting the smallest known distribution among Neotropical primates (ca. 870 km² ), over 90% of which occurs in white-water flooded forests within the Mamirauá Sustainable Development Reserve (MSDR), Brazilian Amazonia. To assess the effectiveness of this protected area in conserving the species, we conducted population monitoring of black-headed squirrel monkeys across five consecutive years (2009-2013) on nine trails 2 km each. Each year samples included both low and high river water periods. We used the distance sampling method, recording the distance to each observed social group as well as counting component individuals. We also calculated annual encounter rates based on the number of individuals sighted every 10 km traveled. Densities ranged from 256 individuals/km² (2011) to 453 individuals/km² (2013), and no seasonal differences were detected. Population size was estimated to be 147,848 mature individuals. Encounter rates ranged from 100 individuals/10 km (2010) to 179 individuals/10 km (2013); no significant difference among years was found. We found that S. vanzolinii populations remained stable throughout the years, which indicates that the MSDR has been playing an essential role on protecting this species. Due to difficulties of fulfilling assumptions of the distance sampling method, we consider the encounter rate analysis to be more effective for monitoring this and other Saimiri species. Given the critical endemism and worrying conservation status of S. vanzolinii, we suggest that monitoring of the species population should be carried out regularly.

Rejection of Schmidt et al.'s estimators for bear population size

Aerial distance sampling of bears to estimate population size has been used throughout many parts of Alaska. The distance sampling models are complex since they need to account for undetected bears and differences in detection probabilities. This will require covariates and mark-recapture data. The models proposed by Schmidt et al. do not use covariates or mark-recapture data and are inappropriate for these surveys.

Aerial surveys for Antarctic minke whales (Balaenoptera bonaerensis) reveal sea ice dependent distribution patterns

This study investigates the distribution of Antarctic minke whales (AMW) in relation to sea ice concentration and variations therein. Information on AMW densities in the sea ice-covered parts of the Southern Ocean is required to contextualize abundance estimates obtained from circumpolar shipboard surveys in open waters, suggesting a 30% decline in AMW abundance. Conventional line-transect shipboard surveys for density estimation are impossible in ice-covered regions, therefore we used icebreaker-supported helicopter surveys to obtain information on AMW densities along gradients of 0%-100% of ice concentration. We conducted five helicopter surveys in the Southern Ocean, between 2006 and 2013. Distance sampling data, satellite-derived sea-ice data, and bathymetric parameters were used in generalized additive models (GAMs) to produce predictions on how the density of AMWs varied over space and time, and with environmental covariates. Ice concentration, distance to the ice edge and distance from the shelf break were found to describe the distribution of AMWs. Highest densities were predicted at the ice edge and through to medium ice concentrations. Medium densities were found up to 500 km into the ice edge in all concentrations of ice. Very low numbers of AMWs were found in the ice-free waters of the West Antarctic Peninsula (WAP). A consistent relationship between AMW distribution and sea ice concentration weakens the support for the hypothesis that varying numbers of AMWs in ice-covered waters were responsible for observed changes in estimated abundance. The potential decline in AMW abundance stresses the need for conservation measures and further studies into the AMW population status. Very low numbers of AMWs recorded in the ice-free waters along the WAP support the hypothesis that this species is strongly dependent on sea ice and that forecasted sea ice changes have the potential of heavily impacting AMWs.

Multispecies hierarchical modeling reveals variable responses of African carnivores to management alternatives

Carnivore communities face unprecedented threats from humans. Yet, management regimes have variable effects on carnivores, where species may persist or decline in response to direct or indirect changes to the ecosystem. Using a hierarchical multispecies modeling approach, we examined the effects of alternative management regimes (i.e., active vs. passive enforcement of regulations) on carnivore abundances and group sizes at both species and community levels in the Masai Mara National Reserve, Kenya. Alternative management regimes have created a dichotomy in ecosystem conditions within the Reserve, where active enforcement of regulations maintains low levels of human disturbance in the Mara Triangle and passive enforcement of regulations in the Talek region permits multiple forms of human disturbance. Our results demonstrate that these alternative management regimes have variable effects on 11 observed carnivore species. As predicted, some species, such as African lions and bat-eared foxes, have higher population densities in the Mara Triangle, where regulations are actively enforced. Yet, other species, including black-backed jackals and spotted hyenas, have higher population densities in the Talek region where enforcement is passive. Multiple underlying mechanisms, including behavioral plasticity and competitive release, are likely causing higher black-backed jackals and spotted hyena densities in the disturbed Talek region. Our multispecies modeling framework reveals that carnivores do not react to management regimes uniformly, shaping carnivore communities by differentially producing winning and losing species. Some carnivore species require active enforcement of regulations for effective conservation, while others more readily adapt (and in some instances thrive in response) to lax management enforcement and resulting anthropogenic disturbance. Yet, high levels of human disturbance appear to be negatively affecting the majority of carnivores, with potential consequences that may permeate throughout the rest of the ecosystem. Community approaches to monitoring carnivores should be adopted as single species monitoring may overlook important intra-community variability.

Recent drought and tree mortality effects on the avian community in southern Sierra Nevada: a glimpse of the future?

Birds respond rapidly to changes in both habitat and climate conditions and thus are good indicators of the ecological effects of a changing climate, which may include warmer temperatures, changing habitat conditions, and increased frequency and magnitude of extreme events like drought. We investigated how a widespread tree mortality event concurrent with a severe drought influenced the avian community of the Sierra Nevada mountain range in California. We assessed and compared the separate effects of climate stresses and altered habitat conditions on the avian community and used this information to evaluate the changes that are likely to occur in the near future. We built tree mortality maps from freely available Landsat imagery with Google Earth Engine. We analyzed avian point counts from 2010 to 2016 in the southern Sierra Nevada, to model temperature, water deficit, and tree mortality effects on the abundances of 45 bird species, and then used these models to project abundances into the future based on three climate projections. A large portion of the avian community, 47%, had a positive relationship with temperature increase, compared to 20% that responded negatively. More species (36%) declined with drier conditions than increased (29%). More species declined in response to high tree mortality (36%) than increased (9%). A preponderance of species adapted to colder temperatures (higher elevation) had negative responses to high tree mortality and water deficit, but positive responses to increasing temperature. We projected the highest total bird abundances in the future under the warmest climate scenario that we considered, but habitat modification (e.g., tree mortality) and water deficit could offset the positive influence of temperature for many species. As other studies have shown, climate warming may lead to substantial but idiosyncratic effects on wildlife species that could result in community composition shifts. We conclude that future climate conditions may not have a universally negative effect on biodiversity in the Sierra Nevada, but probable vegetation changes and increased likelihood of extreme events such as drought should be incorporated into climate-smart forest and wildlife management decisions.

Effects of distance on detectability of Arctic waterfowl using double-observer sampling during helicopter surveys

Aerial survey is an important, widely employed approach for estimating free-ranging wildlife over large or inaccessible study areas. We studied how a distance covariate influenced probability of double-observer detections for birds counted during a helicopter survey in Canada's central Arctic. Two observers, one behind the other but visually obscured from each other, counted birds in an incompletely shared field of view to a distance of 200 m. Each observer assigned detections to one of five 40-m distance bins, guided by semi-transparent marks on aircraft windows. Detections were recorded with distance bin, taxonomic group, wing-flapping behavior, and group size. We compared two general model-based estimation approaches pertinent to sampling wildlife under such situations. One was based on double-observer methods without distance information, that provide sampling analogous to that required for mark-recapture (MR) estimation of detection probability, p ^ , and group abundance, G ^ , along a fixed-width strip transect. The other method incorporated double-observer MR with a categorical distance covariate (MRD). A priori, we were concerned that estimators from MR models were compromised by heterogeneity in p ^ due to un-modeled distance information; that is, more distant birds are less likely to be detected by both observers, with the predicted effect that p ^ would be biased high, and G ^ biased low. We found that, despite increased complexity, MRD models (ΔAICc range: 0-16) fit data far better than MR models (ΔAICc range: 204-258). However, contrary to expectation, the more naïve MR estimators of p ^ were biased low in all cases, but only by 2%-5% in most cases. We suspect that this apparently anomalous finding was the result of specific limitations to, and trade-offs in, visibility by observers on the survey platform used. While MR models provided acceptable point estimates of group abundance, their far higher stranded errors (0%-40%) compared to MRD estimates would compromise ability to detect temporal or spatial differences in abundance. Given improved precision of MRD models relative to MR models, and the possibility of bias when using MR methods from other survey platforms, we recommend avian ecologists use MRD protocols and estimation procedures when surveying Arctic bird populations.

Integrating population dynamics models and distance sampling data: a spatial hierarchical state-space approach

Stochastic versions of Gompertz, Ricker, and various other dynamics models play a fundamental role in quantifying strength of density dependence and studying long-term dynamics of wildlife populations. These models are frequently estimated using time series of abundance estimates that are inevitably subject to observation error and missing data. This issue can be addressed with a state-space modeling framework that jointly estimates the observed data model and the underlying stochastic population dynamics (SPD) model. In cases where abundance data are from multiple locations with a smaller spatial resolution (e.g., from mark-recapture and distance sampling studies), models are conventionally fitted to spatially pooled estimates of yearly abundances. Here, we demonstrate that a spatial version of SPD models can be directly estimated from short time series of spatially referenced distance sampling data in a unified hierarchical state-space modeling framework that also allows for spatial variance (covariance) in population growth. We also show that a full range of likelihood based inference, including estimability diagnostics and model selection, is feasible in this class of models using a data cloning algorithm. We further show through simulation experiments that the hierarchical state-space framework introduced herein efficiently captures the underlying dynamical parameters and spatial abundance distribution. We apply our methodology by analyzing a time series of line-transect distance sampling data for fin whales (Balaenoptera physalus) off the U.S. west coast. Although there were only seven surveys conducted during the study time frame, 1991-2014, our analysis detected presence of strong density regulation and provided reliable estimates of fin whale densities. In summary, we show that the integrative framework developed herein allows ecologists to better infer key population characteristics such as presence of density regulation and spatial variability in a population's intrinsic growth potential.

A distance sampling approach to estimate density and abundance of gibbon groups

All 18 species of gibbons are considered threatened with extinction and listed on the IUCN Red List of Threatened Species. Because gibbons (Hylobatidae) are one of the most threatened primate families, a great need exists to determine and monitor their status effectively. To meet this need, we employed distance sampling methods to estimate the density and number of gibbon groups. We focused on southern yellow-cheeked crested gibbon in the Nam Cat Tien sector of Cat Tien National Park, Vietnam, from July to October, 2016. We used an auditory point count method at 48 listening posts to detect gibbon groups. We estimated our detection probability of calling groups of gibbons within 1,200 m of a listening post was 0.63 (95% CI: 0.54-0.74). In addition, we estimated the daily calling probability of a gibbon group to be 0.46 (95% CI: 0.33-0.59) and interpreted this as the probability that a group was available to be detected. We adjusted our group density and abundance estimates by both detection and availability probabilities. Ultimately we estimated 325 (95% CI: 232-455) gibbon groups in the Nam Cat Tien sector. Our results suggest that Cat Tien National Park contains one of the largest populations of southern yellow-cheeked crested gibbon in Vietnam. Our methods are one way of avoiding underestimation of gibbon group density and abundance by incorporating uncertainty in gibbon group availability and detection.

Accounting for imperfect detection of groups and individuals when estimating abundance

If animals are independently detected during surveys, many methods exist for estimating animal abundance despite detection probabilities <1. Common estimators include double‐observer models, distance sampling models and combined double‐observer and distance sampling models (known as mark‐recapture‐distance‐sampling models; MRDS). When animals reside in groups, however, the assumption of independent detection is violated. In this case, the standard approach is to account for imperfect detection of groups, while assuming that individuals within groups are detected perfectly. However, this assumption is often unsupported. We introduce an abundance estimator for grouped animals when detection of groups is imperfect and group size may be under‐counted, but not over‐counted. The estimator combines an MRDS model with an N‐mixture model to account for imperfect detection of individuals. The new MRDS‐Nmix model requires the same data as an MRDS model (independent detection histories, an estimate of distance to transect, and an estimate of group size), plus a second estimate of group size provided by the second observer. We extend the model to situations in which detection of individuals within groups declines with distance. We simulated 12 data sets and used Bayesian methods to compare the performance of the new MRDS‐Nmix model to an MRDS model. Abundance estimates generated by the MRDS‐Nmix model exhibited minimal bias and nominal coverage levels. In contrast, MRDS abundance estimates were biased low and exhibited poor coverage. Many species of conservation interest reside in groups and could benefit from an estimator that better accounts for imperfect detection. Furthermore, the ability to relax the assumption of perfect detection of individuals within detected groups may allow surveyors to re‐allocate resources toward detection of new groups instead of extensive surveys of known groups. We believe the proposed estimator is feasible because the only additional field data required are a second estimate of group size.

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.

Biological traits, rather than environment, shape detection curves of large vertebrates in neotropical rainforests

Line transect surveys are widely used in Neotropical rainforests to estimate the population abundance of medium- and large-sized vertebrates. The use of indices such as encounter rate has been criticized because the probability of animal detection may fluctuate due to the heterogeneity of environmental conditions among sites. In addition, the morphological and behavioral characteristics (biological traits) of species affect their detectability. In this study, we compared the extent to which environmental conditions and species' biological traits bias abundance estimates in terra firme rainforests in French Guiana. The selected environmental conditions included both physical conditions and forest structure covariates, while the selected biological traits included the morphological and behavioral characteristics of species. We used the distance sampling method to model the detection probability as an explicit function of environmental conditions and biological traits and implemented a model selection process to determine the relative importance of each group of covariates. Biological traits contributed to the variability of animal detectability more than environmental conditions, which had only a marginal effect. Detectability was best for large animals with uniform or disruptive markings that live in groups in the canopy top. Detectability was worst for small, solitary, terrestrial animals with mottled markings. In the terra firme rainforests that represent ~80% of the Amazonia and Guianas regions, our findings support the use of relative indices such as the encounter rate to compare population abundance between sites in species-specific studies. Even though terra firme rainforests may appear similar between regions of Amazonia and the Guianas, comparability must be ensured, especially in forests disturbed by human activity. The detection probability can be used as an indicator of species' vulnerability to hunting and, thus, to the risk of local extinction. Only a few biological trait covariates are required to correctly estimate the detectability of the majority of medium- and large-sized vertebrates. Thus, a biological trait model could be useful in predicting the detection probabilities of rare, uncommon, or localized species for which few data are available to fit the detection function.

Density and Habitat Relationships of the Endemic White Mountain Fritillary (Boloria chariclea montinus) (Lepidoptera: Nymphalidae)

We conducted point counts in the alpine zone of the Presidential Range of the White Mountains, New Hampshire, USA, to estimate the distribution and density of the rare endemic White Mountain Fritillary (Boloria chariclea montinus). Incidence of occurrence and density of the endemic White Mountain Fritillary during surveys in 2012 and 2013 were greatest in the herbaceous-snowbank plant community. Densities at points in the heath-shrub-rush plant community were lower, but because this plant community is more widespread in the alpine zone, it likely supports the bulk of adult fritillaries. White Mountain Fritillary used cushion-tussock, the other alpine plant community suspected of providing habitat, only sparingly. Detectability of White Mountain Fritillaries varied as a consequence of weather conditions during the survey and among observers, suggesting that raw counts yield biased estimates of density and abundance. Point counts, commonly used to study and monitor populations of birds, were an effective means of sampling White Mountain Fritillary in the alpine environment where patches of habitat are small, irregularly shaped, and widely spaced, rendering line-transect methods inefficient and difficult to implement.

Resource partitioning between ungulate populations in arid environments

Herbivores are major drivers of ecosystem structure, diversity, and function. Resilient ecosystems therefore require viable herbivore populations in a sustainable balance with environmental resource availability. This balance is becoming harder to achieve, with increasingly threatened species reliant on small protected areas in increasingly harsh and unpredictable environments. Arid environments in North Africa exemplify this situation, featuring a biologically distinct species assemblage exposed to extreme and volatile conditions, including habitat loss and climate change‐associated threats. Here, we implement an integrated likelihood approach to relate scimitar‐horned oryx (Oryx dammah) and dorcas gazelle (Gazella dorcas) density, via dung distance sampling, to habitat, predator, and geographic correlates in Dghoumes National Park, Tunisia. We show how two threatened sympatric ungulates partition resources on the habitat axis, exhibiting nonuniform responses to the same vegetation gradient. Scimitar‐horned oryx were positively associated with plant species richness, selecting for vegetated ephemeral watercourses (wadis) dominated by herbaceous cover. Conversely, dorcas gazelle were negatively associated with vegetation density (herbaceous height, litter cover, and herbaceous cover), selecting instead for rocky plains with sparse vegetation. We suggest that adequate plant species richness should be a prerequisite for areas proposed for future ungulate reintroductions in arid and semi‐arid environments. This evidence will inform adaptive management of reintroduced ungulates in protected environments, helping managers and planners design sustainable ecosystems and effective conservation programs.

Ecological Monitoring and Health Research in Luambe National Park, Zambia: Generation of Baseline Data Layers

Classifying, describing and understanding the natural environment is an important element of studies of human, animal and ecosystem health, and baseline ecological data are commonly lacking in remote environments of the world. Human African trypanosomiasis is an important constraint on human well-being in sub-Saharan Africa, and spillover transmission occurs from the reservoir community of wild mammals. Here we use robust and repeatable methodology to generate baseline datasets on vegetation and mammal density to investigate the ecology of warthogs (Phacochoerus africanus) in the remote Luambe National Park in Zambia, in order to further our understanding of their interactions with tsetse (Glossina spp.) vectors of trypanosomiasis. Fuzzy set theory is used to produce an accurate landcover classification, and distance sampling techniques are applied to obtain species and habitat level density estimates for the most abundant wild mammals. The density of warthog burrows is also estimated and their spatial distribution mapped. The datasets generated provide an accurate baseline to further ecological and epidemiological understanding of disease systems such as trypanosomiasis. This study provides a reliable framework for ecological monitoring of wild mammal densities and vegetation composition in remote, relatively inaccessible environments.

Monitoring Whooping Crane Abundance Using Aerial Surveys: Influences on Detectability

The whooping crane (Grus americana), an endangered species, has been counted on its winter grounds in Texas, USA, since 1950 using fixed-wing aircraft. Many shortcomings of the traditional survey technique have been identified, calling into question its efficacy, defensibility, repeatability, and usefulness into the future. To improve and standardize monitoring effort, we began investigating new survey techniques. Here we focus on efficacy of line transect-based distance sampling during aerial surveys. We conducted a preliminary test of distance sampling during winter 2010-2011 while flying the traditional survey, which indicated that detectability within 500 m of transects was 0.558 (SE = 0.031). We then used an experimental decoy survey to evaluate impacts of observer experience, sun position, distance from transect, and group size on detectability. Our results indicated decoy detectability increased with group size and exhibited a quadratic relationship with distance likely due to pontoons on the aircraft. We found that detectability was 2.704 times greater when the sun was overhead and 3.912 times greater when the sun was at the observer's back than when it was in the observer's eyes. We found that an inexperienced observer misclassified non-target objects more often than an experienced observer. During the decoy experiment we used marks on the struts to categorize distances into intervals, but we found that observers misclassified distances 46.7% of the time (95% CI = 37.0-56.6%). Also, we found that detectability of individuals within detected groups was affected by group size and distance from transect. We discuss how these results inform design and implementation of future whooping crane monitoring efforts. Published 2013. This article is a U.S. Government work and is in the public domain in the USA.

New density estimates of a threatened sifaka species (Propithecus coquereli) in Ankarafantsika National Park

Propithecus coquereli is one of the last sifaka species for which no reliable and extensive density estimates are yet available. Despite its endangered conservation status [IUCN, 2012] and recognition as a flagship species of the northwestern dry forests of Madagascar, its population in its last main refugium, the Ankarafantsika National Park (ANP), is still poorly known. Using line transect distance sampling surveys we estimated population density and abundance in the ANP. Furthermore, we investigated the effects of road, forest edge, river proximity and group size on sighting frequencies, and density estimates. We provide here the first population density estimates throughout the ANP. We found that density varied greatly among surveyed sites (from 5 to ∼100 ind/km2) which could result from significant (negative) effects of road, and forest edge, and/or a (positive) effect of river proximity. Our results also suggest that the population size may be ∼47,000 individuals in the ANP, hinting that the population likely underwent a strong decline in some parts of the Park in recent decades, possibly caused by habitat loss from fires and charcoal production and by poaching. We suggest community-based conservation actions for the largest remaining population of Coquerel's sifaka which will (i) maintain forest connectivity; (ii) implement alternatives to deforestation through charcoal production, logging, and grass fires; (iii) reduce poaching; and (iv) enable long-term monitoring of the population in collaboration with local authorities and researchers.

Assessment of landscape-scale distribution of sympatric great apes in African rainforests: concurrent use of nest and camera-trap surveys

Information on the distribution and abundance of sympatric great apes (Pan troglodytes troglodytes and Gorilla gorilla gorilla) are important for effective conservation and management. Although much research has been done to improve the precision of nest-surveys, trade-offs between data-reliability and research-efficiency have not been solved. In this study, we used different approaches to assess the landscape-scale distribution patterns of great apes. We conducted a conventional nest survey and a camera-trap survey concurrently, and checked the consistency of the estimates. We divided the study area (ca. 500 km²), containing various types of vegetation and topography, into thirty 16-km² grids (4 km × 4 km) and performed both methods along 2-km transects centered in each grid. We determined the nest creator species according to the definitions by Tutin & Fernandez [Tutin & Fernandez, 1984, Am J Primatol 6:313-336] and estimated nest-site densities of each species by using the conventional distance-sampling approach. We calculated the mean capture rate of 3 camera traps left for 3 months at each grid as the abundance index. Our analyses showed that both methods provided roughly consistent results for the distribution patterns of the species; chimpanzee groups (parties) were more abundant in the montane forest, and gorilla groups were relatively homogeneously distributed across vegetation types. The line-transect survey also showed that the number of nests per nest site did not vary among vegetation types for either species. These spatial patterns seemed to reflect the ecological and sociological features of each species. Although the consistent results may be largely dependent on site-specific conditions (e.g., high density of each species, distinct distribution pattern between the two species), conventional nest-surveys and a subsequent check of their consistency with independent estimates may be a reasonable approach to obtain certain information on the species distribution patterns. Further analytical improvement is necessary for camera-traps to be considered a stand-alone method.