Polar Bears from Space: Assessing Satellite Imagery as a Tool to Track Arctic Wildlife

Development of efficient techniques for monitoring wildlife is a priority in the Arctic, where the impacts of climate change are acute and remoteness and logistical constraints hinder access. We evaluated high resolution satellite imagery as a tool to track the distribution and abundance of polar bears. We examined satellite images of a small island in Foxe Basin, Canada, occupied by a high density of bears during the summer ice-free season. Bears were distinguished from other light-colored spots by comparing images collected on different dates. A sample of ground-truthed points demonstrated that we accurately classified bears. Independent observers reviewed images and a population estimate was obtained using mark–recapture models. This estimate (: 94; 95% Confidence Interval: 92–105) was remarkably similar to an abundance estimate derived from a line transect aerial survey conducted a few days earlier (: 102; 95% CI: 69–152). Our findings suggest that satellite imagery is a promising tool for monitoring polar bears on land, with implications for use with other Arctic wildlife. Large scale applications may require development of automated detection processes to expedite review and analysis. Future research should assess the utility of multi-spectral imagery and examine sites with different environmental characteristics.     

Seismic Survey Design and Effects on Maternal Polar Bear Dens

Large-scale industrial activities can have negative effects on wildlife populations. Some of these effects, however, could be reduced with effective planning prior to development. The Coastal Plain of the Arctic National Wildlife Refuge, in northeastern Alaska, USA, is an important maternal denning area for polar bears (Ursus maritimus). Recent legislation has opened the area for potential oil and gas development. As a result, there is interest in conducting winter seismic surveys across the area that could disturb denning female polar bears and lead to decreased cub survival. We sought to demonstrate how different seismic survey designs, with and without aerial den detection surveys, could affect the level of potential effect on denning polar bears during spring (Feb–Apr). We developed 5 hypothetical seismic survey designs for a portion of the Coastal Plain ranging from no spatial or temporal restrictions on activities to explicit consideration of when and where operations can occur. We evaluated how many dens might be disturbed by seismic surveys and the average distance activity came within simulated polar bear dens. Survey design had a large effect on the estimated number of dens that could be disturbed; the scenario with the highest spatial and temporal specificity reduced the number of dens disturbed by >90% compared to the scenario with no restrictions on when and where activity could occur. The use of an aerial den detection survey prior to seismic activity further reduced the number of dens disturbed by 68% across all scenarios. The scenario with the highest spatial and temporal specificity always had the lowest level of disturbance for all scenarios with and without the aerial survey included. Our study suggests that large reductions in the probability of disturbance can occur through careful planning on the timing and distribution of proposed activities even when surveys are planned in areas with a high density of polar bear dens. Published 2019. This article is a U.S. Government work and is in the public domain in the USA. The Journal of Wildlife Management published by Wiley Periodicals, Inc. on behalf of The Wildlife Society.     

Aerial surveys suggest long‐term stability in the seasonally ice‐free Foxe Basin (Nunavut) polar bear population

Significant information gaps exist regarding the status of polar bears, especially with respect to the impacts of climate change, across large portions of the Arctic. To obtain an updated abundance estimate for the Foxe Basin population, we conducted comprehensive aerial surveys during the 2009 and 2010 ice‐free seasons, when bears are confined to land. We sampled with mark‐recapture distance sampling protocols on inland and coastal transects and surveyed small islands and remnant ice floes. We observed 816 and 1,003 bears in 2009 and 2010, respectively. Although detection functions differed substantially between years, estimates were consistent between analytical methods and years. Averaging four estimates (two from each year) yielded 2,585 (2,096–3,189) bears, which is similar to an estimate from the 1990s. This result, along with robust cub production, suggests a stable and healthy population despite deteriorating sea ice conditions. Collectively, this and other recent on‐land surveys provide a framework for implementing aerial surveys elsewhere. Although aerial surveys do not yield estimates of vital rates or population growth, they enable more rapid and frequent monitoring than mark‐recapture. Integrating them in long‐term monitoring programs will require consideration of ancillary data to infer status and facilitate setting harvest levels.     

Bayesian estimation of group sizes for a coastal cetacean using aerial survey data

Many small cetacean, sirenian, and pinniped species aggregate in groups of large or variable size. Accurate estimation of group sizes is essential for estimating the abundance and distribution of these species, but is challenging as individuals are highly mobile and only partially visible. We developed a Bayesian approach for estimating group sizes using wide‐angle aerial photographic or video imagery. Our approach accounts for both availability and perception bias, including a new method (analogous to distance sampling) for estimating perception bias due to small image size in wide‐angle images. We demonstrate our approach through an application to aerial survey data for an endangered population of beluga whales (Delphinapterus leucas) in Cook Inlet, Alaska. Our results strengthen understanding of variation in group size estimates and allow for probabilistic statements about the size of detected groups. Aerial surveys are a standard tool for estimating the abundance and distribution of various marine mammal species. The role of aerial photographic and video data in wildlife assessment is expected to increase substantially with the widespread uptake of unmanned aerial vehicle technology. Key aspects of our approach are relevant to group size estimation for a broad range of marine mammal, seabird, other waterfowl, and terrestrial ungulate species.     

The use of infrared thermography to noninvasively measure the surface temperature of polar bears during bouts of social play

Infrared thermography or thermal imagery is a noninvasive tool that can be used to measure the temperature of surfaces. Typically, thermal imagery is used for construction or military purposes but is increasingly used as a noninvasive tool in wildlife studies. We investigated the use of thermal imagery to measure surface temperature changes as a proxy for energetic expenditure. We measured the surface temperature of polar bear (Ursus maritimus) eyes, while immobilized, to determine whether the eye is a thermal window that can accurately indicate internal temperature. We found a significant difference (2.68 ± 0.41°C) between the surface temperature of the eye measured with thermal imagery and the internal rectal temperature. Additionally, we measured surface temperature changes in polar bears after bouts of social play as a proxy for energy expenditure. Mean temperature of the eye increased by 1.34 ± 0.43°C after social play, indicating that this activity increased energy expenditure. During the fasting season, polar bears rely on fat stores, and any energy expenditure beyond what is required to travel may be costly to their survival, particularly in years of low resource availability. We conclude that thermal imagery is a useful tool to noninvasively investigate the energetics of social play.     

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.     

Computer‐automated bird detection and counts in high‐resolution aerial images: a review

Bird surveys conducted using aerial images can be more accurate than those using airborne observers, but can also be more time‐consuming if images must be analyzed manually. Recent advances in digital cameras and image‐analysis software offer unprecedented potential for computer‐automated bird detection and counts in high‐resolution aerial images. We review the literature on this subject and provide an overview of the main image‐analysis techniques. Birds that contrast sharply with image backgrounds (e.g., bright birds on dark ground) are generally the most amenable to automated detection, in some cases requiring only basic image‐analysis software. However, the sophisticated analysis capabilities of modern object‐based image analysis software provide ways to detect birds in more challenging situations based on a variety of attributes including color, size, shape, texture, and spatial context. Some techniques developed to detect mammals may also be applicable to birds, although the prevalent use of aerial thermal‐infrared images for detecting large mammals is of limited applicability to birds because of the low pixel resolution of thermal cameras and the smaller size of birds. However, the increasingly high resolution of true‐color cameras and availability of small unmanned aircraft systems (drones) that can fly at very low altitude now make it feasible to detect even small shorebirds in aerial images. Continued advances in camera and drone technology, in combination with increasingly sophisticated image analysis software, now make it possible for investigators involved in monitoring bird populations to save time and resources by increasing their use of automated bird detection and counts in aerial images. We recommend close collaboration between wildlife‐monitoring practitioners and experts in the fields of remote sensing and computer science to help generate relevant, accessible, and readily applicable computer‐automated aerial photographic census techniques.     

Observations of mortality associated with extended open-water swimming by polar bears in the Alaskan Beaufort Sea

During aerial surveys in September 1987–2003, a total of 315 live polar bears were observed with 12 (3.8%) animals in open water, defined for purposes of this analysis as marine waters >2 km north of the Alaska Beaufort Sea coastline or associated barrier islands. No polar bear carcasses were observed. During aerial surveys in early September, 2004, 55 polar bears (Ursus maritimus) were seen, 51 were alive and of those 10 (19.9%) were in open water. In addition, four polar bear carcasses were seen floating in open water and had, presumably, drowned. Average distance from land and pack ice edge for live polar bears swimming in open water in 2004 (n=10) were 8.3±3.0 and 177.4±5.1 km, respectively. We speculate that mortalities due to offshore swimming during late-ice (or mild ice) years may be an important and unaccounted source of natural mortality given energetic demands placed on individual bears engaged in long-distance swimming. We further suggest that drowning-related deaths of polar bears may increase in the future if the observed trend of regression of pack ice and/or longer open water periods continues.     

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

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

Estimating distribution of hidden objects with drones: from tennis balls to manatees

Unmanned aerial vehicles (UAV), or drones, have been used widely in military applications, but more recently civilian applications have emerged (e.g., wildlife population monitoring, traffic monitoring, law enforcement, oil and gas pipeline threat detection). UAV can have several advantages over manned aircraft for wildlife surveys, including reduced ecological footprint, increased safety, and the ability to collect high-resolution geo-referenced imagery that can document the presence of species without the use of a human observer. We illustrate how geo-referenced data collected with UAV technology in combination with recently developed statistical models can improve our ability to estimate the distribution of organisms. To demonstrate the efficacy of this methodology, we conducted an experiment in which tennis balls were used as surrogates of organisms to be surveyed. We used a UAV to collect images of an experimental field with a known number of tennis balls, each of which had a certain probability of being hidden. We then applied spatially explicit occupancy models to estimate the number of balls and created precise distribution maps. We conducted three consecutive surveys over the experimental field and estimated the total number of balls to be 328 (95%CI: 312, 348). The true number was 329 balls, but simple counts based on the UAV pictures would have led to a total maximum count of 284. The distribution of the balls in the field followed a simulated environmental gradient. We also were able to accurately estimate the relationship between the gradient and the distribution of balls. Our experiment demonstrates how this technology can be used to create precise distribution maps in which discrete regions of the study area are assigned a probability of presence of an object. Finally, we discuss the applicability and relevance of this experimental study to the case study of Florida manatee distribution at power plants.     

Investigating the potential use of aerial line transect surveys for estimating polar bear abundance in sea ice habitats: A case study for the Chukchi Sea

The expense of traditional capture‐recapture methods, interest in less invasive survey methods, and the circumpolar decline of polar bear (Ursus maritimus) habitat require evaluation of alternative methods for monitoring polar bear populations. Aerial line transect distance sampling (DS) surveys are thought to be a promising monitoring tool. However, low densities and few observations during a survey can result in low precision, and logistical constraints such as heavy ice and fuel and safety limitations may restrict survey coverage. We used simulations to investigate the accuracy and precision of, DS for estimating polar bear abundance in sea ice habitats, using the Chukchi Sea subpopulation as an example. Simulation parameters were informed from a recent pilot survey. Predictions from a resource selection model were used for stratification, and we compared two ratio estimators to account for areas that cannot be sampled. The ratio estimator using predictions of resource selection by polar bears allowed for extrapolation beyond sampled areas and provided results with low bias and CVs ranging from 21% to 36% when abundance was >1,000. These techniques could be applied to other DS surveys to allocate effort and potentially extrapolate estimates to include portions of the landscape that are logistically impossible to survey.     

Variation in detection probability of polar bear maternity dens

In surveys recording polar bear maternity dens, the proportion of actual dens in an area detected has usually been unknown. In this study, I evaluate how the proportion of dens that are observable varies with time in spring based on three 3–4 weeks ground surveys and observations of 25, 13, and 5 dens in Svalbard, Norwegian Arctic, during 2009, 2011 and 2012. The data indicate that few dens will be detected in surveys before early April, as few bears will have emerged at that time. Dens became unobservable after periods of drifting snow but are subsequently reopened within one or 2 days by occupying bears. Most bears departed dens by late April, and abandoned dens were quickly concealed by drifting snows. As such, I suggest that the optimal period for conducting an aerial survey is early to mid-April on a day with low winds and good visibility, because about half of the dens could be expected to be observable. Because emergence date, duration at den site, and abandonment dates varied considerably, uncertainty around the proportion of polar bear maternal dens detected during a survey will be large.     

Hyperspectral Analysis of Columbia Spotted Frog Habitat

Abstract: Wildlife managers increasingly are using remotely sensed imagery to improve habitat delineations and sampling strategies. Advances in remote sensing technology, such as hyperspectral imagery, provide more information than previously was available with multispectral sensors. We evaluated accuracy of high-resolution hyperspectral image classifications to identify wetlands and wetland habitat features important for Columbia spotted frogs (Rana luteiventris) and compared the results to multispectral image classification and United States Geological Survey topographic maps. The study area spanned 3 lake basins in the Salmon River Mountains, Idaho, USA. Hyperspectral data were collected with an airborne sensor on 30 June 2002 and on 8 July 2006. A 12-year comprehensive ground survey of the study area for Columbia spotted frog reproduction served as validation for image classifications. Hyperspectral image classification accuracy of wetlands was high, with a producer's accuracy of 96% (44 wetlands) correctly classified with the 2002 data and 89% (41 wetlands) correctly classified with the 2006 data. We applied habitat-based rules to delineate breeding habitat from other wetlands, and successfully predicted 74% (14 wetlands) of known breeding wetlands for the Columbia spotted frog. Emergent sedge microhabitat classification showed promise for directly predicting Columbia spotted frog egg mass locations within a wetland by correctly identifying 72% (23 of 32) of known locations. Our study indicates hyperspectral imagery can be an effective tool for mapping spotted frog breeding habitat in the selected mountain basins. We conclude that this technique has potential for improving site selection for inventory and monitoring programs conducted across similar wetland habitat and can be a useful tool for delineating wildlife habitats.     

Caught in the mesh: roads and their network‐scale impediment to animal movement

Roads have a pervasive multi‐faceted influence on ecosystems, including pronounced impacts on wildlife movements. In recognition of the scale‐transcending impacts of transportation infrastructure, ecologists have been encouraged to extend the study of barrier impacts from individual roads and animals to networks and populations. In this study, we adopt an analytical representation of road networks as mosaics of landscape tiles, separated by roads. We then adapt spatial capture–recapture analysis to estimate the propensity of wildlife to stay within the boundaries of the road network tiles (RNTs) that hold their activity centres. We fit the model to national non‐invasive genetic monitoring data for brown bears Ursus arctos in Sweden and show that bears had up to 73% lower odds of using areas outside the network tile of their home range centre, even after accounting for the effect of natural barriers (major rivers) and the decrease in utilization with increasing distance from a bear's activity centre. Our study highlights the pronounced landscape‐level barrier effect on wildlife mobility and, in doing so, introduces a novel and flexible approach for quantifying contemporary fragmentation from the scale of RNTs and individual animals to transportation networks and populations.     

Wildlife Abundance and Diversity as Indicators of Tourism Potential in Northern Botswana

Wildlife tourism can provide economic incentives for conservation. Due to the abundance of wildlife and the presence of charismatic species some areas are better suited to wildlife tourism. Our first objective was to develop criteria based on wildlife abundance and diversity to evaluate tourism potential in the Northern Conservation Zone of Botswana. Secondly we wanted to quantify and compare tourism experiences in areas with high and low tourism potential. We used aerial survey data to estimate wildlife biomass and diversity to determine tourism potential, while data from ground surveys quantified the tourist experience. Areas used for High Paying Low Volume tourism had significantly higher mean wildlife biomass and wildlife diversity than the areas avoided for this type of tourism. Only 22% of the Northern Conservation Zone has intermediate to high tourism potential. The areas with high tourism potential, as determined from the aerial survey data, provided tourists with significantly better wildlife sightings (ground surveys) than the low tourism potential areas. Even Low Paying tourism may not be economically viable in concessions that lack areas with intermediate to high tourism potential. The largest part of the Northern Conservation Zone has low tourism potential, but low tourism potential is not equal to low conservation value. Alternative conservation strategies should be developed to complement the economic incentive provided by wildlife-based tourism in Botswana.     

Errors in aerial survey count data: Identifying pitfalls and solutions

Accurate estimates of animal abundance are essential for guiding effective management, and poor survey data can produce misleading inferences. Aerial surveys are an efficient survey platform, capable of collecting wildlife data across large spatial extents in short timeframes. However, these surveys can yield unreliable data if not carefully executed. Despite a long history of aerial survey use in ecological research, problems common to aerial surveys have not yet been adequately resolved. Through an extensive review of the aerial survey literature over the last 50 years, we evaluated how common problems encountered in the data (including nondetection, counting error, and species misidentification) can manifest, the potential difficulties conferred, and the history of how these challenges have been addressed. Additionally, we used a double‐observer case study focused on waterbird data collected via aerial surveys and an online group (flock) counting quiz to explore the potential extent of each challenge and possible resolutions. We found that nearly three quarters of the aerial survey methodology literature focused on accounting for nondetection errors, while issues of counting error and misidentification were less commonly addressed. Through our case study, we demonstrated how these challenges can prove problematic by detailing the extent and magnitude of potential errors. Using our online quiz, we showed that aerial observers typically undercount group size and that the magnitude of counting errors increases with group size. Our results illustrate how each issue can act to bias inferences, highlighting the importance of considering individual methods for mitigating potential problems separately during survey design and analysis. We synthesized the information gained from our analyses to evaluate strategies for overcoming the challenges of using aerial survey data to estimate wildlife abundance, such as digital data collection methods, pooling species records by family, and ordinal modeling using binned data. Recognizing conditions that can lead to data collection errors and having reasonable solutions for addressing errors can allow researchers to allocate resources effectively to mitigate the most significant challenges for obtaining reliable aerial survey data.     

Use of aerial imagery to assess habitat suitability and predict site occupancy for a declining wetland-dependent bird

Remote sensing is a valuable tool for wetland habitat quantification, monitoring and assessment. Here we show that habitat assessment via aerial image inspection is useful in predicting wetland site occupancy by black terns (Chlidonias niger), an imperiled and declining species throughout much of North America. We used Google Earth^® images and National Wetlands Inventory maps to rank 390 candidate wetlands throughout Wisconsin (USA) according to their apparent suitability as nesting habitat for black terns and quantified habitat features associated with the suitability rankings. We then conducted ground-based suitability assessments and point counts of terns at most wetlands from May to July 2010. Pre-survey assessment resulted in 123 wetlands classified as suitable, 81 as marginal, and 186 as unsuitable. Wetlands ranked as suitable were more likely to be in the hemi-marsh stage, part of a wetland complex and relatively undisturbed. Black terns were present at 47 % of the wetlands considered suitable but only 11 % of the sites considered marginal or unsuitable. Of the 42 sites where nesting was confirmed, 79 % were at wetlands classified as suitable; no nesting was recorded in any wetlands deemed unsuitable. We found strong concordance in wetland suitability rankings between the two assessment methods (remote sensing, site surveys). We propose that remote sensing is an efficient and inexpensive way to predict site occupancy by wetland birds, such as black terns, that prefer a specific kind of habitat discernible from aerial imagery. This method may be particularly useful in areas, such as the Prairie Pothole region of North America, where ground surveys of all wetlands are not feasible.     

Effects of sea ice extent and food availability on spatial and temporal distribution of polar bears during the fall open-water period in the Southern Beaufort Sea

We investigated the relationship between sea ice conditions, food availability, and the fall distribution of polar bears (Ursus maritimus) in terrestrial habitats of the Southern Beaufort Sea via weekly aerial surveys in 2000–2005. Aerial surveys were conducted weekly during September and October along the Southern Beaufort Sea coastline and barrier islands between Barrow and the Canadian border to determine polar bear density on land. The number of bears on land both within and among years increased when sea-ice was retreated furthest from the shore. However, spatial distribution also appeared to be related to the availability of subsistence-harvested bowhead whale (Balaena mysticetus) carcasses and the density of ringed seals (Phoca hispida) in offshore waters. Our results suggest that long-term reductions in sea-ice could result in an increasing proportion of the Southern Beaufort Sea polar bear population coming on land during the fall open-water period and an increase in the amount of time individual bears spend on land.     

Unmanned Aerial Survey of Elephants

The use of a UAS (Unmanned Aircraft System) was tested to survey large mammals in the Nazinga Game Ranch in the south of Burkina Faso. The Gatewing ×100™ equipped with a Ricoh GR III camera was used to test animal reaction as the UAS passed, and visibility on the images. No reaction was recorded as the UAS passed at a height of 100 m. Observations, made on a set of more than 7000 images, revealed that only elephants (Loxodonta africana) were easily visible while medium and small sized mammals were not. The easy observation of elephants allows experts to enumerate them on images acquired at a height of 100 m. We, therefore, implemented an aerial strip sample count along transects used for the annual wildlife foot count. A total of 34 elephants were recorded on 4 transects, each overflown twice. The elephant density was estimated at 2.47 elephants/km² with a coefficient of variation (CV%) of 36.10%. The main drawback of our UAS was its low autonomy (45 min). Increased endurance of small UAS is required to replace manned aircraft survey of large areas (about 1000 km of transect per day vs 40 km for our UAS). The monitoring strategy should be adapted according to the sampling plan. Also, the UAS is as expensive as a second-hand light aircraft. However the logistic and flight implementation are easier, the running costs are lower and its use is safer. Technological evolution will make civil UAS more efficient, allowing them to compete with light aircraft for aerial wildlife surveys.