Locating chimpanzee nests and identifying fruiting trees with an unmanned aerial vehicle

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.

Noninvasive Technologies for Primate Conservation in the 21st Century

Observing and quantifying primate behavior in the wild is challenging. Human presence affects primate behavior and habituation of new, especially terrestrial, individuals is a time-intensive process that carries with it ethical and health concerns, especially during the recent pandemic when primates are at even greater risk than usual. As a result, wildlife researchers, including primatologists, have increasingly turned to new technologies to answer questions and provide important data related to primate conservation. Tools and methods should be chosen carefully to maximize and improve the data that will be used to answer the research questions. We review here the role of four indirect methods—camera traps, acoustic monitoring, drones, and portable field labs—and improvements in machine learning that offer rapid, reliable means of combing through large datasets that these methods generate. We describe key applications and limitations of each tool in primate conservation, and where we anticipate primate conservation technology moving forward in the coming years.

Using knowledge mapping to rethink the gap between science and action

Scholars have long stressed the need to bridge the gap between science and action and seek the most efficient use of knowledge for decision making. Many contributors have attempted to consider and understand the sociopolitical forces involved in knowledge generation and exchange. We argue, however, that a model is still needed to adequately conceptualize and frame the knowledge networks in which these processes are embedded. We devised a model for knowledge mapping as a prerequisite for knowledge management in the context of conservation. Using great ape conservation to frame our approach, we propose that knowledge mapping should be based on 2 key principles. First, each conservation network results from the conglomeration of subnetworks of expertise producing and using knowledge. Second, beyond the research-management gradient, other dimensions, such as the scale of operation, geographic location, and organizational characteristics, must also be considered. Assessing both knowledge production and trajectory across different dimensions of the network opens new space for investigating and reducing the gap between science and action.

An experimental approach to evaluate the potential of drones in terrestrial mammal research: a gregarious ungulate as a study model

Research on the use of unmanned aircraft systems (UAS) in wildlife has made remarkable progress recently. Few studies to date have experimentally evaluated the effect of UAS on animals and have usually focused primarily on aquatic fauna. In terrestrial open arid ecosystems, with relatively good visibility to detect animals but little environmental noise, there should be a trade-off between flying the UAS at high height above ground level (AGL) to limit the disturbance of animals and flying low enough to maintain count precision. In addition, body size or social aggregation of species can also affect the ability to detect animals from the air and their response to the UAS approach. To address this gap, we used a gregarious ungulate, the guanaco (Lama guanicoe), as a study model. Based on three types of experimental flights, we demonstrated that (i) the likelihood of miscounting guanacos in images increases with UAS height, but only for offspring and (ii) higher height AGL and lower UAS speed reduce disturbance, except for large groups, which always reacted. Our results call into question mostly indirect and observational previous evidence that terrestrial mammals are more tolerant to UAS than other species and highlight the need for experimental and species-specific studies before using UAS methods.

Integrating UAV Technology in an Ecological Monitoring System for Community Wildlife Management Areas in Tanzania

Unmanned aerial vehicles (UAV) have recently emerged as a new remote sensing aerial platform, and they are seemingly advancing real-time data generation. Nonetheless, considerable uncertainties remain in the extent to which wildlife managers can integrate UAVs into ecological monitoring systems for wildlife and their habitats. In this review, we discuss the recent progress and gaps in UAV use in wildlife conservation and management. The review notes that there is scanty information on UAV use in ecological monitoring of medium-to-large mammals found in groups in heterogeneous habitats. We also explore the need and extent to which the technology can be integrated into ecological monitoring systems for mammals in heterogeneous habitats and in topographically-challenging community wildlife-management areas, as a complementary platform to the traditional techniques. Based on its ability to provide high-resolution images in real-time, further experiments on its wider use in the ecological monitoring of wildlife on a spatiotemporal scale are important. The experimentation outputs will make the UAV a very reliable remote sensing platform that addresses the challenges facing conventional techniques.

What animals do not do or fail to find: A novel observational approach for studying cognition in the wild

To understand how our brain evolved and what it is for, we are in urgent need of knowledge about the cognitive skills of a large variety of animal species and individuals, and their relationships to rapidly disappearing social and ecological conditions. But how do we obtain this knowledge? Studying cognition in the wild is a challenge. Field researchers (and their study subjects) face many factors that can easily interfere with their variables of interest. Although field studies of cognition present unique challenges, they are still invaluable for understanding the evolutionary drivers of cognition. In this review, I discuss the advantages and urgency of field-based studies on animal cognition and introduce a novel observational approach for field research that is guided by three questions: (a) what do animals fail to find?, (b) what do they not do?, and (c) what do they only do when certain conditions are met? My goal is to provide guidance to future field researchers examining primate cognition.

Thermal Infrared Imaging from Drones Offers a Major Advance for Spider Monkey Surveys

Accurate and precise population estimates form the basis of conservation action but are lacking for many arboreal species due to the high costs and difficulty in surveying these species. Recently, researchers have started to use drones to obtain data on animal distribution and density. In this study, we compared ground and drone counts for spider monkeys (Ateles geoffroyi) at their sleeping sites using a custom-built drone fitted with a thermal infrared (TIR) camera. We demonstrated that a drone with a TIR camera can be successfully employed to determine the presence and count the number of spider monkeys in a forested area. Using a concordance analysis, we found high agreement between ground and drone counts for small monkey subgroups (<10 individuals), indicating that the methods do not differ when surveying small subgroups. However, we found low agreement between methods for larger subgroups (>10 individuals), with drone counts being higher than the corresponding ground counts in 83% of surveys. We could identify additional individuals from TIR drone footage due to a greater area covered compared to ground surveys. We recommend using TIR drones for surveys of spider monkey sleeping sites and discuss current challenges to implementation.

Seabird species vary in behavioural response to drone census

Unmanned aerial vehicles (UAVs) provide an opportunity to rapidly census wildlife in remote areas while removing some of the hazards. However, wildlife may respond negatively to the UAVs, thereby skewing counts. We surveyed four species of Arctic cliff-nesting seabirds (glaucous gull Larus hyperboreus, Iceland gull Larus glaucoides, common murre Uria aalge and thick-billed murre Uria lomvia) using a UAV and compared censusing techniques to ground photography. An average of 8.5% of murres flew off in response to the UAV, but >99% of those birds were non-breeders. We were unable to detect any impact of the UAV on breeding success of murres, except at a site where aerial predators were abundant and several birds lost their eggs to predators following UAV flights. Furthermore, we found little evidence for habituation by murres to the UAV. Most gulls flew off in response to the UAV, but returned to the nest within five minutes. Counts of gull nests and adults were similar between UAV and ground photography, however the UAV detected up to 52.4% more chicks because chicks were camouflaged and invisible to ground observers. UAVs provide a less hazardous and potentially more accurate method for surveying wildlife. We provide some simple recommendations for their use.

A computer vision for animal ecology

A central goal of animal ecology is to observe species in the natural world. The cost and challenge of data collection often limit the breadth and scope of ecological study. Ecologists often use image capture to bolster data collection in time and space. However, the ability to process these images remains a bottleneck. Computer vision can greatly increase the efficiency, repeatability and accuracy of image review. Computer vision uses image features, such as colour, shape and texture to infer image content. I provide a brief primer on ecological computer vision to outline its goals, tools and applications to animal ecology. I reviewed 187 existing applications of computer vision and divided articles into ecological description, counting and identity tasks. I discuss recommendations for enhancing the collaboration between ecologists and computer scientists and highlight areas for future growth of automated image analysis.

Biology goes in the air : Unmanned aerial vehicles offer biologists an efficient tool for observation and sampling from a safe distance

Drones are becoming popular among biologists as a tool to observe wildlife, take samples from the air or remote locations, or even perform in-flight DNA analysis.

Impending extinction crisis of the world's primates: Why primates matter

Nonhuman primates, our closest biological relatives, play important roles in the livelihoods, cultures, and religions of many societies and offer unique insights into human evolution, biology, behavior, and the threat of emerging diseases. They are an essential component of tropical biodiversity, contributing to forest regeneration and ecosystem health. Current information shows the existence of 504 species in 79 genera distributed in the Neotropics, mainland Africa, Madagascar, and Asia. Alarmingly, ~60% of primate species are now threatened with extinction and ~75% have declining populations. This situation is the result of escalating anthropogenic pressures on primates and their habitats-mainly global and local market demands, leading to extensive habitat loss through the expansion of industrial agriculture, large-scale cattle ranching, logging, oil and gas drilling, mining, dam building, and the construction of new road networks in primate range regions. Other important drivers are increased bushmeat hunting and the illegal trade of primates as pets and primate body parts, along with emerging threats, such as climate change and anthroponotic diseases. Often, these pressures act in synergy, exacerbating primate population declines. Given that primate range regions overlap extensively with a large, and rapidly growing, human population characterized by high levels of poverty, global attention is needed immediately to reverse the looming risk of primate extinctions and to attend to local human needs in sustainable ways. Raising global scientific and public awareness of the plight of the world's primates and the costs of their loss to ecosystem health and human society is imperative.

Precision wildlife monitoring using unmanned aerial vehicles

Unmanned aerial vehicles (UAVs) represent a new frontier in environmental research. Their use has the potential to revolutionise the field if they prove capable of improving data quality or the ease with which data are collected beyond traditional methods. We apply UAV technology to wildlife monitoring in tropical and polar environments and demonstrate that UAV-derived counts of colony nesting birds are an order of magnitude more precise than traditional ground counts. The increased count precision afforded by UAVs, along with their ability to survey hard-to-reach populations and places, will likely drive many wildlife monitoring projects that rely on population counts to transition from traditional methods to UAV technology. Careful consideration will be required to ensure the coherence of historic data sets with new UAV-derived data and we propose a method for determining the number of duplicated (concurrent UAV and ground counts) sampling points needed to achieve data compatibility.