Finding and monitoring nests are key components of avian research, but they are often expensive, time-consuming, and inefficient operations. This is certainly true for diving ducks that nest in wetlands with thick emergent vegetation where nests are typically located by teams of technicians that wade through a marsh and beat vegetation with sticks, hoping to flush incubating females or encounter nests without a female present. Taking advantage of recent advances in both unmanned aerial vehicles (UAVs) and thermal-imaging cameras, our objectives were to (1) compare our ability to locate duck nests using a UAV and using traditional on-foot searching methods, and (2) determine if nests monitored remotely with the UAV had different survival rates than nests monitored with traditional nest-site visits. We searched for nests with a UAV system in southern Manitoba during the springs of 2018 and 2019. Using the UAV, we located 48 nests not found by ground crews, ground crews found 164 nests not found with the UAV, and 71 nests were found using both methods. Overall, nests were less likely to be detected with the UAV (0.34) than by ground crews (0.71), but surveys were completed approximately four times faster with the UAV. Detectability of nests varied among duck species (range = 0.55-0.04). We found no difference in nest survival between nests monitored with the UAV (0.95) and those repeatedly visited by ground crews (0.95). However, in 2018, ground monitoring resulted in 19 nests being abandoned by females, compared to only one monitored with the UAV. Our results demonstrate that UAVs equipped with thermal cameras can be used to find nests of ducks located over water, with greater success for species that nest earlier and those whose nests are not buried under matted vegetation. Furthermore, monitoring nests with the UAV resulted in lower rates of nest abandonment, and survival of nests monitored with the UAV was similar to that of nests monitored using traditional methods. Additional species-and habitat-specific studies are needed to fully understand the utility and challenges associated with using UAVs equipped with thermal imaging to survey species of wetland wildlife.

With the widespread extirpation of top predators over the past two centuries, mesocarnivores play an increasingly important role in structuring terrestrial trophic webs. However, mesocarnivores are difficult to survey at a population level because their widely spaced territories and nocturnal behavior result in low detection probability. Existing field survey techniques such as track plates and motion-sensitive camera traps are time-consuming and expensive, and yet still yield data prone to systematic errors. Unmanned Aerial Vehicles (UAVs) have recently emerged as a new tool for conducting population surveys on a wide variety of wildlife, eclipsing the efficiency and even accuracy of traditional methods. We used a UAV equipped with a thermal imaging camera to conduct nighttime mesocarnivore surveys in the prairie pothole region of southern Manitoba, Canada. This was part of a much larger ecological study evaluating how lethal removal of mesocarnivores affects duck nest success. Here, our objective was to describe methods and equipment that were successful in detecting mesocarnivores. We used a modified point-count survey from six waypoints that surveyed a spatial extent of 29.5 ha. We conducted a total of 200 flights over 53 survey nights during which we detected 32 mesocarnivores of eight different species. Given the large home ranges of mesocarnivores relative to the spatial and temporal scale of our spot sampling approach, results of these types of point-count surveys should be considered estimates of minimum abundance and not a population census. However, more frequent sampling and advanced statistics could be used to formally estimate population occupancy and abundance. UAV-mounted thermal imaging cameras appear to be an effective tool for conducting nocturnal population surveys on mesocarnivores at a moderate spatial scale.

Brood surveys are used to estimate productivity in ducks, but road‐side transects, aerial surveys, and double‐observer ground surveys have likely underestimated productivity. Duck broods are elusive and prefer wetlands with emergent vegetation where they hide at signs of disturbance, making it difficult to get accurate brood counts. Estimates of brood detection probabilities are typically below 50% and variable, which makes biological inferences about abundance tenuous. We conducted a study to evaluate the efficacy of using an unmanned aerial vehicle (UAV) equipped with a thermal imaging camera to survey duck broods in 2 study areas. In Manitoba we located 669 broods with the UAV, compared to 344 detected by double‐observer ground surveys. In Minnesota we detected 225 ducks broods with the UAV, whereas only 105 duck broods were detected by ground observers. Using a Huggins closed‐capture model in program MARK we estimated an average detection probability across both sites of 0.55 (SE = 0.02) with the UAV compared to 0.24 (SE = 0.02) for the ground crews. Although the UAV detected twice as many broods as the ground surveys, detection probability with the UAV was impacted by temperature, humidity, vegetation density, and the criteria we used to determine whether a brood could be classified as resighted. Nevertheless, using a UAV equipped with a thermal imaging camera effectively doubled the number of broods detected compared to traditional methods, and surveys were completed 3 times faster. With advancing drone and camera technology we believe UAV brood counts will become increasingly accurate and provide reliable measures of local duck productivity. © 2021 The Wildlife Society.

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