Assessing the presence and abundance of birds is important for monitoring specific species as well as overall ecosystem health. Many birds are most readily detected by their sounds, and thus, passive acoustic monitoring is highly appropriate. Yet acoustic monitoring is often held back by practical limitations such as the need for manual configuration, reliance on example sound libraries, low accuracy, low robustness, and limited ability to generalise to novel acoustic conditions. Here, we report outcomes from a collaborative data challenge. We present new acoustic monitoring datasets, summarise the machine learning techniques proposed by challenge teams, conduct detailed performance evaluation, and discuss how such approaches to detection can be integrated into remote monitoring projects. Multiple methods were able to attain performance of around 88% area under the receiver operating characteristic (ROC) curve (AUC), much higher performance than previous general‐purpose methods. With modern machine learning, including deep learning, general‐purpose acoustic bird detection can achieve very high retrieval rates in remote monitoring data, with no manual recalibration, and no pretraining of the detector for the target species or the acoustic conditions in the target environment.

An understanding of animal behaviour is important if conservation initiatives are to be effective. However, quantifying the behaviour of wild animals presents significant challenges. Remote-sensing camera traps are becoming increasingly popular survey instruments that have been used to non-invasively study a variety of animal behaviours, yielding key insights into behavioural repertoires. They are well suited to ethological studies and provide considerable opportunities for generating conservation-relevant behavioural data if novel and robust methodological and analytical solutions can be developed. This paper reviews the current state of camera-trap-based ethological studies, describes new and emerging directions in camera-based conservation behaviour, and highlights a number of limitations and considerations of particular relevance for camerabased studies. Three promising areas of study are discussed: (1) documenting anthropogenic impacts on behaviour; (2) incorporating behavioural responses into management planning and (3) using behavioural indicators such as giving up densities and daily activity patterns. We emphasize the importance of reporting methodological details, utilizing emerging camera trap metadata standards and central data repositories for facilitating reproducibility, comparison and synthesis across studies. Behavioural studies using camera traps are in their infancy; the full potential of the technology is as yet unrealized. Researchers are encouraged to embrace conservation-driven hypotheses in order to meet future challenges and improve the efficacy of conservation and management processes.

Many biological monitoring projects rely on acoustic detection of birds. Despite increasingly large datasets, this detection is often manual or semi-automatic, requiring manual tuning/postprocessing. We review the state of the art in automatic bird sound detection, and identify a widespread need for tuning-free and species-agnostic approaches. We introduce new datasets and an IEEE research challenge to address this need, to make possible the development of fully automatic algorithms for bird sound detection.

This study addresses a significant data deficiency in the developing environmental protection framework of the International Commission on Radiological Protection, namely a lack of radionuclide transfer data for some of the Reference Animals and Plants (RAPs). It is also the first study that has sampled such a wide range of species (invertebrates, plants, amphibians and small mammals) from a single terrestrial site in the Chernobyl Exclusion Zone (CEZ). Samples were collected in 2014 from the 0.4 km sampling site, located 5 km west of the Chernobyl Nuclear Power complex. We report radionuclide (Cs, Sr,Am and Pu-isotopes) and stable element concentrations in wildlife and soil samples and use these to determine whole organism-soil concentration ratios and absorbed dose rates. Increasingly, stable element analyses are used to provide transfer parameters for radiological models. The study described here found that for both Cs and Sr the transfer of the stable element tended to be lower than that of the radionuclide; this is the first time that this has been demonstrated for Sr, though it is in agreement with limited evidence previously reported for Cs. Studies reporting radiation effects on wildlife in the CEZ generally relate observations to ambient dose rates determined using handheld dose meters. For the first time, we demonstrate that ambient dose rates may underestimate the actual dose rate for some organisms by more than an order of magnitude. When reporting effects studies from the CEZ, it has previously been suggested that the area has comparatively low natural background dose rates. However, on the basis of data reported here, dose rates to wildlife from natural background radionuclides within the CEZ are similar to those in many areas of Europe.

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