Comparison of Aerial Thermal Infrared Imagery and Helicopter Surveys of Bison (Bison bison) in Grand Canyon National Park, USA.

Aerial thermal infrared (TIR) surveys are an attractive option for estimating abundances of large mammals inhabiting extensive and heterogeneous terrain. Compared to standard helicopter or fixed-wing aerial surveys, TIR flights can be conducted at higher altitudes translating into greater spatial coverage and increased observer safety; however, monetary costs are much greater. Further, there is no consensus on whether TIR surveys offer improved detection. Consequently, we performed a study to compare results of a TIR and helicopter survey of bison (Bison bison) on the Powell Plateau in Grand Canyon National Park, USA. We also compared results of both surveys to estimates obtained using a larger dataset of bison helicopter detections along the entire North Rim of the Grand Canyon. Observers in the TIR survey counted fewer individual bison than helicopter observers (101 to 127) and the TIR survey cost was 367% higher. Additionally, the TIR estimate was 18.8% lower than the estimate obtained using a larger dataset, while the comparative helicopter survey was 9.3% lower. Despite our small sample size, we found that helicopter surveys are currently the best method for estimating bison abundances in dense canopy cover sites due to ostensibly more accurate estimates and lower cost compared to TIR surveys. Additional research will be needed to evaluate the efficacy of these methods, as well as very high resolution satellite imagery, for bison populations in more open landscapes.

The use of an unoccupied aerial vehicle to survey shark species over sand and rocky-reef habitats in a marine protected area.

Cabo Pulmo National Park was established in 1995 and has since seen a large increase in fish biomass. An unoccupied aerial vehicle (UAV) was used to survey shallow coastal habitat in which lemon sharks (Negaprion brevirostris), bull sharks (Carcharhinus leucas) and Pacific nurse sharks (Ginglymostoma unami) were recorded. Sharks were more common in the afternoon, potentially using warmer shallow areas to behaviourally thermoregulate. This study highlights UAV surveying to be a viable tool for species identification, a limitation of previous terrestrial surveys conducted in the area.

Understanding the drivers of mortality in African savannah elephants.

Populations of African savannah elephants (Loxodonta africana) have been declining due to poaching, human-elephant conflict, and habitat loss. Understanding the causes of these declines could aid in stabilizing elephant populations. We used data from the Great Elephant Census, a 19-country aerial survey of savannah elephants conducted in 2014 and 2015, to examine effects of a suite of variables on elephant mortality. Independent variables included spatially explicit measures of natural processes and human presence as well as country-level socioeconomic measures. Our dependent variable was the carcass ratio, the ratio of dead elephants to live plus dead elephants, which is an index of recent elephant mortality. Carcass ratios are inversely proportional to population growth rates of elephants over the 4 yr prior to a survey. At the scale of survey strata (n = 275, median area = 1,222 km2 ), we found strong negative associations for carcass ratios with vegetation greenness at the time of the survey, overseas development aid to the country, and distance to the nearest international border. At the scale of ecosystems (n = 42, median area = 12,085 km2 ), carcass ratios increased with drought frequency and decreased with human density and overseas development aid to the country. Both stratum- and ecosystem-scale models explained well under one-half of the variance in carcass ratios. The differences in results between scales suggest that the drivers of mortality may be scale-specific and that the corresponding solutions may vary by scale as well.

Accurate Non-Disturbance Population Survey Method of Nesting Colonies in the Reedbed with Georeferenced Aerial Imagery.

High altitude aerial surveys have the potential to improve disturbance-free data collection in wildlife research, but previously, bird species were not recognizable in high-altitude orthophotos. This method of aerial surveying is effective and can be repeated frequently due to its low cost; it also has the additional advantage of being able to monitor the status of protected areas. In the case of waterbirds, due to the low vegetation coverage, aerial remote sensing is an exceptionally effective technique for surveying populations and detecting nests. Aerial surveys made at low altitudes can cause serious stress for birds. The method we developed and employed is unlikely to be detected by either ground-based or nesting birds but is far more reliable compared to the low-resolution imaging methods and to the evaluation of non-georeferenced photo series. The modern sensors and photogrammetric procedures enable the use of the present method worldwide; furthermore, the large-scale ortho image-derived information has become obtainable more frequently. Direct georeferencing makes the field geodetic survey unnecessary. Orthophotos with a 0.7 cm spatial resolution allow us to reliably identify even the individuals of smaller species, and by the use of oblique images, they can be tracked from two or four different directions.

Mapping out bare-nosed wombat (Vombatus ursinus) burrows with the use of a drone.

BACKGROUND: Wombats are large, nocturnal herbivores that build burrows in a variety of habitats, including grassland communities, and can come into conflict with people. Counting the number of active burrows provides information on the local distribution and abundance of wombats and could prove to be an important management tool to monitor population numbers over time. We compared traditional ground surveys and a new method employing drones, to determine if drones could be used to effectively identify and monitor bare-nosed wombat burrows. RESULTS: We surveyed burrows using both methods in eight 5-ha transects in grassland, that was interspersed with patches of tussock grassland. Ground surveys were conducted by systematically walking transects and searching for burrows. Drone surveys involved programming flights over transects to capture multiple images, from which an orthomosaic image of each transect was produced. These were subsequently viewed using ArcMap to detect burrows. A total of 204 individual burrows were recorded by drone and/or ground survey methods. In grassland, the methods were equally effective in terms of the numbers of burrows detected in transects. In the smaller areas of tussock grassland, ground surveys detected significantly more burrows, because burrow openings were obscured in orthomosaic images by overhanging grasses. There was agreement between the methods as to whether burrows were potentially active or inactive for most burrows in both vegetation communities. However, image interpretation tended to classify grassland burrows as potentially active. Overall time taken to conduct surveys was similar for both methods, but ground surveys utilised three observers and more time in the field. CONCLUSIONS: Drones provide an effective means to survey bare-nosed wombat burrows that are visible from the air, particularly in areas not accessible to observers and vehicles. Furthermore, drones provide alternative options for monitoring burrows at the landscape level, and for monitoring wombat populations based on observable changes in burrow appearance over time.

Conservation Reserve Program is a key element for managing white-tailed deer populations at multiple spatial scales.

Understanding the underlying mechanisms driving population demographics such as species-habitat relationships and the spatial scale in which these relationships occur is essential for developing optimal management strategies. Here we evaluated how landscape characteristics and winter severity measured at three spatial scales (1 km2, 9 km2, and hunting unit) influenced white-tailed deer occurrence and abundance across North Dakota by using 10 years of winter aerial survey data and generalized linear mixed effects models. In general, forest, wetland, and Conservation Reserve Program (CRP) lands were the main drivers of deer occurrence and abundance in most of the spatial scales analyzed. However, the effects of habitat features vary between the home-range scale (9 km2) and the finer spatial scale (1 km2; i.e., within home ranges). While escape cover was the main factor driving white-tailed deer occurrence and abundance at broad spatial scales, at a fine spatial scale deer also selected for food (mainly residual winter cropland). With CRP appearing in nearly all top models, here we had strong evidence that this type of program will be fundamental to sustaining populations of white-tailed deer that can meet recreational demands. In addition, land managers should focus on ways to protect other escape covers (e.g., forest and wetland) on a broad spatial scale while encouraging landowners to supply winter resources at finer spatial scales. We therefore suggest a spatial multi-scale approach that involves partnerships among landowners and government agencies for effectively managing white-tailed deer.

Large-scale bleaching of corals on the Great Barrier Reef.

In 2015-2016, record temperatures triggered a pan-tropical episode of coral bleaching. In the southern hemisphere summer of March-April 2016, we used aerial surveys to measure the level of bleaching on 1,156 individual reefs throughout the 2,300 km length of the Great Barrier Reef, the world's largest coral reef system. The accuracy of the aerial scores was ground-truthed with detailed underwater surveys of bleaching at 260 sites (104 reefs), allowing us to compare aerial and underwater bleaching data with satellite-derived temperatures and with associated model predictions of bleaching. The severity of bleaching on individual reefs in 2016 was tightly correlated with the level of local heat exposure: the southernmost region of the Great Barrier Reef escaped with only minor bleaching because summer temperatures there were close to average. Gradients in nutrients and turbidity from inshore to offshore across the Great Barrier Reef had minimal effect on the severity of bleaching. Similarly, bleaching was equally severe on reefs that are open or closed to fishing, once the level of satellite-derived heat exposure was accounted for. The level of post-bleaching mortality, measured underwater after 7-8 months, was tightly correlated with the aerial scores measured at the peak of bleaching. Similarly, reefs with a high aerial bleaching score also experienced major shifts in species composition due to extensive mortality of heat-sensitive species. Reefs with low bleaching scores did not change in composition, and some showed minor increases in coral cover. Two earlier mass bleaching events occurred on the Great Barrier Reef in 1998 and 2002, that were less severe than 2016. In 2016, <9% of scored reefs had no bleaching, compared to 42% in 2002 and 44% in 1998. Conversely, the proportion of reefs that were severely bleached (>60% of corals affected) was four times higher in 2016. The geographic footprint of each of the three events is distinctive, and matches satellite-derived sea surface temperature patterns. Our aerial surveys indicate that past exposure to bleaching in 1998 and 2002 did not lessen the severity of bleaching in 2016. This data set of aerial bleaching scores provides a historical baseline for comparison with future bleaching events. No copyright restrictions apply to the use of this data set other than citing this publication.

Using species traits to predict detectability of animals on aerial surveys.

In animal surveys, detectability can vary widely across species. We hypothesized that detectability of animals should be a function of species traits such as mass, color, and mean herd size. We also hypothesized that models of detectability based on species traits can be used to predict detectability for new species not in the original data set, leading to substantial benefits for ecology and conservation. We tested these hypotheses with double-observer aerial surveys of 10 mammal species in northern Botswana. We combined all 10 species and modeled their detectability with species traits (mass, mean herd size, color) as predictors while controlling for observer effects, vegetation, and herd size. We found support for effects of mass and an interaction between herd size and mean herd size on detectability. This model accurately predicted the ratio of herds detected by two observers vs. one observer for 8 of 10 species. To test whether a model based on species traits could be applied to a new species, we serially deleted each species from the data set, fit a trait-based model to the remaining nine species, and used this model to predict detectability for the deleted species. The model was able to reproduce the species-trait model for seven species and accurately predicted the ratio of detections by one or two observers for a different set of seven species; the model was successful by both measures for five species. To our knowledge, this represents the first time that a mechanistic model for detectability of animals has been used to predict detectability for new species. Prediction failed for species with extreme values of traits, suggesting that predicting detectability is not possible near or beyond the boundaries of one's data set. The approach taken in this paper can potentially be used with a variety of taxa and may provide new opportunities to apply detectability corrections where they have not been possible before.

Unmanned aerial vehicles for surveying marine fauna: assessing detection probability.

Aerial surveys are conducted for various fauna to assess abundance, distribution, and habitat use over large spatial scales. They are traditionally conducted using light aircraft with observers recording sightings in real time. Unmanned Aerial Vehicles (UAVs) offer an alternative with many potential advantages, including eliminating human risk. To be effective, this emerging platform needs to provide detection rates of animals comparable to traditional methods. UAVs can also acquire new types of information, and this new data requires a reevaluation of traditional analyses used in aerial surveys; including estimating the probability of detecting animals. We conducted 17 replicate UAV surveys of humpback whales (Megaptera novaeangliae) while simultaneously obtaining a 'census' of the population from land-based observations, to assess UAV detection probability. The ScanEagle UAV, carrying a digital SLR camera, continuously captured images (with 75% overlap) along transects covering the visual range of land-based observers. We also used ScanEagle to conduct focal follows of whale pods (n = 12, mean duration = 40 min), to assess a new method of estimating availability. A comparison of the whale detections from the UAV to the land-based census provided an estimated UAV detection probability of 0.33 (CV = 0.25; incorporating both availability and perception biases), which was not affected by environmental covariates (Beaufort sea state, glare, and cloud cover). According to our focal follows, the mean availability was 0.63 (CV = 0.37), with pods including mother/calf pairs having a higher availability (0.86, CV = 0.20) than those without (0.59, CV = 0.38). The follows also revealed (and provided a potential correction for) a downward bias in group size estimates from the UAV surveys, which resulted from asynchronous diving within whale pods, and a relatively short observation window of 9 s. We have shown that UAVs are an effective alternative to traditional methods, providing a detection probability that is within the range of previous studies for our target species. We also describe a method of assessing availability bias that represents spatial and temporal characteristics of a survey, from the same perspective as the survey platform, is benign, and provides additional data on animal behavior.

Spatial Ecology of Estuarine Crocodile (Crocodylus porosus) Nesting in a Fragmented Landscape.

The role that oil palm plays in the Lower Kinabatangan region of Eastern Sabah is of considerable scientific and conservation interest, providing a model habitat for many tropical regions as they become increasingly fragmented. Crocodilians, as apex predators, widely distributed throughout the tropics, are ideal indicator species for ecosystem health. Drones (or unmanned aerial vehicles (UAVs)) were used to identify crocodile nests in a fragmented landscape. Flights were targeted through the use of fuzzy overlay models and nests located primarily in areas indicated as suitable habitat. Nests displayed a number of similarities in terms of habitat characteristics allowing for refined modelling of survey locations. As well as being more cost-effective compared to traditional methods of nesting survey, the use of drones also enabled a larger survey area to be completed albeit with a limited number of flights. The study provides a methodology for targeted nest surveying, as well as a low-cost repeatable flight methodology. This approach has potential for widespread applicability across a range of species and for a variety of study designs.

Population and Conservation Status of Bighorn Sheep in the State of Baja California, Mexico.

The bighorn sheep in Mexico is classified as at-risk by the Mexican federal government. In the state of Baja California, wild sheep can be observed throughout the length of the state from the USA-Mexico border south to the Agua de Soda mountain range. This research aimed to document the historical trend of the bighorn population based on aerial surveys conducted in 1992, 1995, 1999, 2010, and 2021, and the abundance, distribution, and structure of bighorn sheep populations in Baja California, based on an aerial survey conducted from 8-14 November 2021, covering thirteen mountain ranges. The estimated sheep population in 2021 was based on the number of individuals observed; the sightability of the animals; the area sampled; and the total area of habitat available. In 30.5 flight hours, 456 bighorn sheep were observed, with an estimated population of 1697 ± 80 individuals. The observation rate was 16 sheep sighted per hour of flight, and the ram:ewe:lamb ratio was 62:100:19. When the results of the 2021 flight were compared to the results of the previous aerial surveys, there was a large variation between the data, which was related to the lack of consistency between the sampling designs used in each study. Nevertheless, a statistical test of the results of aerial surveys conducted in the state suggest that the Baja California bighorn sheep population remained stable between 1992 and 2021. This study highlights the need to standardize wild sheep aerial surveys by defining flight paths and establishing a consistent duration of flights. On the other hand, Baja California authorities should consider modifying the current conservation strategy for bighorn sheep to increase the species' population in the state by initiating community-based wildlife conservation programs in rural communities.

Confirmation of significant sea turtle nesting activity on a remote island chain in the Gulf of Mexico.

Globally, six of the seven sea turtle species are threatened or endangered and as such, monitoring reproductive activity for these species is necessary for effective population recovery. Remote beaches provide a challenge to conducting these surveys, which often results in data gaps that can hamper management planning. Throughout the summer of 2022, aerial surveys were conducted over the Chandeleur Islands in the Gulf of Mexico. Turtle crawls were photographed for subsequent review by 10 expert observers. Whenever possible, ground surveys were conducted, and samples of unhatched eggs or dead hatchlings were collected. A summary of historic reports of sea turtle nesting activity at this site was also compiled. On 11 days between May 4, 2022, and July 30, 2022, photographs of 55 potential sea turtle crawls were taken. Observers identified 54 of those as being made by a sea turtle. There was high-to-moderate certainty that 16 of those crawls were nests, that 14 were made by loggerheads, and that two were made by Kemp's ridleys. Observers were least certain of species identification when surveys were conducted during rainy weather. Genetic analyses based on mitochondrial and nuclear DNA were conducted on samples from five nests and those analyses confirmed that three nests were laid by Kemp's ridleys and two were laid by loggerheads. Historic records from the Chandeleur Islands substantiate claims that the Chandeleurs have supported sea turtle nesting activity for decades; however, the consistency of this activity remains unknown. Our aerial surveys, particularly when coupled with imaging, were a useful tool for documenting nesting activity on these remote islands. Future monitoring programs at this site could benefit from a standardized aerial survey program with a seaplane so trends in nesting activity could be determined particularly as the beach undergoes restoration.

Automated identification system for ships data as a proxy for marine vessel related stressors.

An increasing number of marine conservation initiatives rely on data from Automatic Identification System (AIS) to inform marine vessel traffic associated impact assessments and mitigation policy. However, a considerable proportion of vessel traffic is not captured by AIS in many regions of the world. Here we introduce two complementary techniques for collecting traffic data in the Canadian Salish Sea that rely on optical imagery. Vessel data pulled from imagery captured using a shore-based autonomous camera system ("Photobot") were used for temporal analyses, and data from imagery collected by the National Aerial Surveillance Program (NASP) were used for spatial analyses. The photobot imagery captured vessel passages through Boundary Pass every minute (Jan-Dec 2017), and NASP data collection occurred opportunistically across most of the Canadian Salish Sea (2017-2018). Based on photobot imagery data, we found that up to 72 % of total vessel passages through Boundary Pass were not broadcasting AIS, and in some vessel categories this proportion was much higher (i.e., 96 %). We fit negative binomial General Linearized Models to our photobot data and found a strong seasonal variation in non-AIS, and a weekend/weekday component that also varied by season (interaction term p < 0.0001). Non-AIS traffic was much higher during the summer (Apr-Sep) and during the weekend (Sat-Sun), reflecting patterns in recreational vessel traffic not obligated to broadcast AIS. Negative binomial General Additive Models based on the NASP data revealed strong spatial associations with distance from shore (up to 10 km) and non-AIS vessel traffic for both summer and winter seasons. There were also associations between non-AIS vessels and marina and anchorage densities, particularly during the winter, which again reflect seasonal recreational vessel traffic patterns. Overall, our GAMs explained 20-37 % of all vessel traffic during the summer and winter, and highlighted subregions where vessel traffic is under represented by AIS.

Drone images afford more detections of marine wildlife than real-time observers during simultaneous large-scale surveys.

There are many advantages to transitioning from conducting marine wildlife surveys via human observers onboard light-aircraft, to capturing aerial imagery using drones. However, it is important to maintain the validity of long-term data series whilst transitioning from observer to imagery surveys. We need to understand how the detection rates of target species in images compare to those collected from observers in piloted aircraft, and the factors influencing detection rates from each platform. We conducted trial ScanEagle drone surveys of dugongs in Shark Bay, Western Australia, covering the full extent of the drone's range (∼100 km), concurrently with observer surveys, with the drone flying above or just behind the piloted aircraft. We aimed to test the assumption that drone imagery could provide comparable detection rates of dugongs to human observers when influenced by same environmental conditions. Overall, the dugong sighting rate (i.e., count of individual dugongs) was 1.3 (95% CI [0.98-1.84]) times higher from the drone images than from the observers. The group sighting rate was similar for the two platforms, however the group sizes detected within the drone images were significantly larger than those recorded by the observers, which explained the overall difference in sighting rates. Cloud cover appeared to be the only covariate affecting the two platforms differently; the incidence of cloud cover resulted in smaller group sizes being detected by both platforms, but the observer group sizes dropped much more dramatically (by 71% (95% CI [31-88]) compared to no cloud) than the group sizes detected in the drone images (14% (95% CI [-28-57])). Water visibility and the Beaufort sea state also affected dugong counts and group sizes, but in the same way for both platforms. This is the first direct simultaneous comparison between sightings from observers in piloted aircraft and a drone and demonstrates the potential for drone surveys over a large spatial-scale.

Aircraft surveys for air eDNA: probing biodiversity in the sky.

Air is a medium for dispersal of environmental DNA (eDNA) carried in bioaerosols, yet the atmosphere is mostly unexplored as a source of genetic material encompassing all domains of life. In this study, we designed and deployed a robust, sterilizable hardware system for airborne nucleic acid capture featuring active filtration of a quantifiable, controllable volume of air and a high-integrity chamber to protect the sample from loss or contamination. We used our hardware system on an aircraft across multiple height transects over major aerosolization sources to collect air eDNA, coupled with high-throughput amplicon sequencing using multiple DNA metabarcoding markers targeting bacteria, plants, and vertebrates to test the hypothesis of large-scale genetic presence of these bioaerosols throughout the planetary boundary layer in the lower troposphere. Here, we demonstrate that the multi-taxa DNA assemblages inventoried up to 2,500 m using our airplane-mounted hardware system are reflective of major aerosolization sources in the survey area and show previously unreported airborne species detections (i.e., Allium sativum L). We also pioneer an aerial survey flight grid standardized for atmospheric sampling of genetic material and aeroallergens using a light aircraft and limited resources. Our results show that air eDNA from terrestrial bacteria, plants, and vertebrates is detectable up to high altitude using our airborne air sampler and demonstrate the usefulness of light aircraft in monitoring campaigns. However, our work also underscores the need for improved marker choices and reference databases for species in the air column, particularly eukaryotes. Taken together, our findings reveal strong connectivity or mixing of terrestrial-associated eDNA from ground level aerosolization sources and the atmosphere, and we recommend that parameters and indices considering lifting action, atmospheric instability, and potential for convection be incorporated in future surveys for air eDNA. Overall, this work establishes a foundation for light aircraft campaigns to comprehensively and economically inventory bioaerosol emissions and impacts at scale, enabling transformative future opportunities in airborne DNA technology.

UAV-based landfill operation monitoring: A year of volume and topographic measurements.

Unmanned Aerial Vehicles (UAVs) for photogrammetry operations configures a technology capable of extracting quantitative information from land surface in a fast, accurate and safe way, reproducing it in high-resolution Digital Elevation Models (DEMs) and orthomosaics. Due to the operational efficiency of this technique, there is an interest in evaluating its quality compared to other methodologies traditionally used for monitoring procedures in infrastructure earthwork. In sanitary landfills, operational monitoring is directly linked to topographic services, as these are the main source of data for the geometric assessment of the work. In this context, the aim of the study was to verify accuracy and application range of UAV photogrammetry for geometrical and volumetric measurements, when compared to usual conventional survey procedures using total station, and how it can aggregate reliable data to landfills monitoring activities. UAV flights were carried on monthly basis, over a year. For accuracy analysis, the maximum RMSE error observed was 7.1 cm for horizontal axis and 0.37 cm for vertical axis for the monitoring period. Volumetric measurements were tested using Ground Control Point (GCPs) configurations distributed first at the landfill perimeter, which resulted in an average difference of 9% from that calculated by conventional topography, and measurements where GCPs were placed also in the landfill operation fronts, when a 4% average difference diverging from conventional topography was obtained. The conclusion shows that such monitoring routines, when performed periodically, provides a robust database with a high level of operational performance, covering effective information for preventive and corrective monitoring in landfill projects.

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.

An on-ice aerial survey of the Kane Basin polar bear (Ursus maritimus) subpopulation.

There is an imminent need to collect information on distribution and abundance of polar bears (Ursus maritimus) to understand how they are affected by the ongoing decrease in Arctic sea ice. The Kane Basin (KB) subpopulation is a group of high-latitude polar bears that ranges between High Arctic Canada and NW Greenland around and north of the North Water polynya (NOW). We conducted a line transect distance sampling aerial survey of KB polar bears during 28 April-12 May 2014. A total of 4160 linear kilometers were flown in a helicopter over fast ice in the fjords and over offshore pack ice between 76° 50' and 80° N'. Using a mark-recapture distance sampling protocol, the estimated abundance was 190 bears (95% lognormal CI: 87-411; CV 39%). This estimate is likely negatively biased to an unknown degree because the offshore sectors of the NOW with much open water were not surveyed because of logistical and safety reasons. Our study demonstrated that aerial surveys may be a feasible method for obtaining abundance estimates for small subpopulations of polar bears.

Detection of Monema flavescens (Lepidoptera: Limacodidae) Cocoons Using Small Unmanned Aircraft System.

Current unmanned aircraft system (a.k.a. drone) technology is an effective tool for aerial survey of pests including weeds, plant diseases, and insects. This study was conducted to develop an aerial survey method that can locate cocoons of the oriental moth, Monema flavescens Walker, for precise and accurate detection of the cocoons in winter to prevent defoliation in the subsequent summer. We used a rotary-wing drone for an aerial survey of M. flavescens cocoons on 15 trees at 3-5 m above the tree canopy. We also conducted a conventional ground survey of M. flavescens cocoons on the same trees for two different conditions of cocoons: open (i.e., adult moths already emerged from cocoons) and closed (i.e., adult moths were not emerged yet). A validation census with destructive sampling was conducted to determine the precision and accuracy of the aerial and ground survey methods. The results of this study showed that from the aerial survey with the drone, images of open cocoons differed from those of closed cocoons. We found higher precision and accuracy and lower type I and II error rates for closed cocoons by the aerial survey with the drone than those by the ground survey. No significant relationships of the number of cocoons with tree height and diameter at breast height were found. This is the first study to demonstrate direct detection of insects with an aerial survey by using a drone.

Image dataset acquired from an unmanned aerial vehicle over an experimental site within El Soldado estuary in Guaymas, Sonora, México.

It is well known that remote sensing is a series of procedures which detects physical characteristics of the earth surface by remotely-measuring its reflected and emitted radiation using cameras or sensors. Lately, the increasing use of unmanned aerial vehicles (UAVs) as remote sensing platforms and the development of small-size sensors have resulted in the expansion of continuous monitoring of earth surface at smaller spatial scales. For this reason, the integration of UAV- and consumer-grade cameras can be useful to acquire surface characteristics at plot or footprint scale. This dataset contains 314 aerial images covering an area of aproximately 18,800 m2 within the footprint of an Eddy covariance and meterorological station. The monitoring site was deployed at "El Soldado" estuary (27°57'14.4″ N and 110°58'19.2″ W) located in the southern coast of the Mexican State of Sonora. UAV flight path was programmed to flight in autonomous mode with an altitude of 30 m, a velocity of 5 m/s and a frontal and side overlap of 85 and 75% respectively. This dataset was created to support mapping surveys for surface classification and site description. This dataset is aimed to support researchers, stakeholders and general public interested in coastal areas, natural resources management and ecosystem conservation. Finally, this dataset could be also used for those interested in digital photogrammetry and 3D reconstruction as benchmark example to develop high resolution orthomosaics.