High‐throughput environmental sensing technologies are increasingly central to global monitoring of the ecological impacts of human activities. In particular, the recent boom in passive acoustic sensors has provided efficient, noninvasive, and taxonomically broad means to study wildlife populations and communities, and monitor their responses to environmental change. However, until recently, technological costs and constraints have largely confined research in passive acoustic monitoring (PAM) to a handful of taxonomic groups (e.g., bats, cetaceans, birds), often in relatively small‐scale, proof‐of‐concept studies. The arrival of low‐cost, open‐source sensors is now rapidly expanding access to PAM technologies, making it vital to evaluate where these tools can contribute to broader efforts in ecology and biodiversity research. Here, we synthesise and critically assess the current emerging opportunities and challenges for PAM for ecological assessment and monitoring of both species populations and communities. We show that terrestrial and marine PAM applications are advancing rapidly, facilitated by emerging sensor hardware, the application of machine learning innovations to automated wildlife call identification, and work towards developing acoustic biodiversity indicators. However, the broader scope of PAM research remains constrained by limited availability of reference sound libraries and open‐source audio processing tools, especially for the tropics, and lack of clarity around the accuracy, transferability and limitations of many analytical methods. In order to improve possibilities for PAM globally, we emphasise the need for collaborative work to develop standardised survey and analysis protocols, publicly archived sound libraries, multiyear audio datasets, and a more robust theoretical and analytical framework for monitoring vocalising animal communities.

Camera traps have become a ubiquitous tool in ecology and conservation. They are routinely deployed in wildlife survey and monitoring work, and are being advocated as a tool for planetary-scale biodiversity monitoring. The camera trap's widespread adoption is predicated on the assumption of its effectiveness, but the evidence base for this is lacking. Using 104 past studies, we recorded the qualitative overall recommendations made by study authors (for or against camera traps, or ambiguous), together with quantitative data on the effectiveness of camera traps (e.g. number of species detected or detection probabilities) relative to 22 other methods. Most studies recommended the use of camera traps overall and they were 39% more effective based on the quantitative data. They were significantly more effective compared with live traps (88%) and were otherwise comparable in effectiveness to other methods. Camera traps were significantly more effective than other methods at detecting a large number of species (31% more) and for generating detections of species (91% more). This makes camera traps particularly suitable for broad-spectrum biodiversity surveys. Film camera traps were found to be far less effective than digital models, which has led to an increase in camera trap effectiveness over time. There was also evidence from the authors that the use of attractants with camera traps reduced their effectiveness (counter to their intended effect), while the quantitative data indicated that camera traps were more effective in closed than open habitats. Camera traps are a highly effective wildlife survey tool and their performance will only improve with future technological advances. The images they produce also have a range of other benefits, for example as digital voucher specimens and as visual aids for outreach. The evidence-base supports the increasing use of camera traps and underlines their suitability for meeting the challenges of global-scale biodiversity monitoring.

Camera traps are a widely used tool in wildlife research and conservation, but in situ factors such as theft, poor performance in extreme environments and damage by wildlife may be hindering the effectiveness of the technology. However, we still know little about how widespread these constraints are and which are the priorities to solve in the short‐ and mid‐term. We present results from a global survey of camera‐trappers working across a diversity of institutions and habitats, and using camera traps for a range of purposes. We show that: (1) the major current constraints on effective camera‐trapping are cost, theft and sensor performance (with 66%, 50% and 42% of respondents respectively classifying those as important or extremely important barriers for camera‐trapping); (2) the most‐needed technological developments are related to sensor performance (faster triggering responses and higher sensitivity), resistance to extreme environmental conditions (extreme temperatures and high humidity) and automated filtering of blank images; and (3) there is considerable variation among camera trap manufacturers in user‐rated performance, and none of the manufacturer ratings exhibited a trend over time, despite improvements in the technology. Our results serve as valuable market research for both open‐source and commercial camera trap developers. On the basis of our survey of camera‐trappers, we foresee a transition towards camera‐trapping 3.0 in the near‐future, consisting of both more effective camera trap units, but also greater use of wireless data transmission, sensor networks, automation of processes using algorithms and better, more collaborative tools for managing and analysing camera trap data. Ultimately, this will increase the capacity of researchers and conservationists to implement coordinated wildlife monitoring at unprecedented scales.

We investigated the efficacy of a drone equipped with a thermal camera as a potential survey tool to detect wild Bornean orangutans (Pongo pygmaeus) and other tropical primates. Using the thermal camera we successfully detected 41 orangutans and a troop of proboscis monkeys, all of which were confirmed by ground observers. We discuss the potential advantages and limitations of thermal-equipped drones as a tool to complement other methods, and the potential of this technology for use as a future survey tool.