Aim: To combat the global biodiversity crisis, robust and scalable data are needed to target, monitor and evaluate conservation efforts, particularly in data-poor regions and for cryptic taxa. Passive acoustic monitoring (PAM) has the potential to provide solutions, but real-world examples are still rare. We demonstrate how PAM data can be used to rapidly and effectively map distributions of multiple taxa over large scales, in data-poor regions. We show how these data can be used to assess the importance of existing protected areas and prioritise future conservation efforts, including for rare and cryptic species often neglected in such assessments. Location: Global with a case study from Polesia, Eastern Europe. Time Period: Present. Major Taxa Studied: Bats, Birds, Small mammals and Bush crickets. Methods: Using machine-learning and manual verification, we identified bats, nocturnally active birds, small mammals and bush crickets from over 34,000 monitoring hours at 506 sites in the Polesia region of Belarus and Ukraine. Using multi-species generalised mixed models in a Bayesian framework, we then predicted occupancy and acoustic activity for these species and their associations with protected areas, over a 151,000 km(2) project area. We identified areas of high conservation priority as measured by species richness and/or importance for globally or regionally threatened species. Main Conclusions: Our approach provides a roadmap for collecting and processing large-scale, multi-taxa biodiversity data using passive acoustic monitoring. In our case study region, we show that although existing protected areas contain a relatively large proportion of high conservation priority areas, there are significant gaps in the protected area network. We also show low surrogacy of areas of high conservation priority between taxa at fine scales, but did at larger scales, showing the importance of multi-taxa monitoring to prioritise protected areas that conserve a wide variety of species.

Use of species-specific field methods may be required for taxa that are inherently difficult to survey, for example species with cryptic camouflage or secretive behaviour. However, these methods often require more manual effort and therefore cost. Passive acoustic monitoring (PAM) is now an established tool to reduce manual effort to monitor species, and analysis of spectrograms provides the means to discriminate individuals by call characteristics. At night, male Eurasian Woodcock Scolopax rusticola make distinct, audible 'roding' displays above the tree canopy to advertise to females. Studying this behaviour at an individual level while using PAM presents opportunities to improve monitoring methods of this cryptic, Red-Listed species. This study evaluates the potential use of vocal individuality measurements in distinguishing Woodcock individuals and interpreting spatial and temporal patterns in their roding displays across woodland sites. Woodcock roding calls were recorded from woodland fragments across two regions comprising 20 sites. A random forest classifier was applied to reduce the time needed to find and manually verify calls. Principal component analysis (PCA) and hierarchical clustering algorithms were used on call measurements, describing duration and frequency differences in calls. When clusters formed, they were used to qualitatively assess supposed individual spatial and temporal variation in roding behaviour. The variance of dimensionally reduced measurements was used to interpret local Woodcock abundance and changes over time. Supposed individuals used many sites within a region, and many sites were used by multiple birds. However, sites showed clusters of calls from supposed individuals in different proportions. It was difficult to discriminate individuals using PCA with more than six birds because the degree of call overlap increased. Though the call measurement variance is associated with number of call events, it may provide a suitable method for representing population size without call count bias.

Conifer plantations are a major land use globally and provide a range of social, economic and environmental benefits, particularly the provision of timber. There is a growing interest in alternative forestry techniques, such as irregular silviculture, to create more sustainable and resilient plantations in response to climate change. Plantations are often considered poor for bats due to limited structural diversity. Irregular forestry increases structural diversity and reduces growing stocks, with potentially positive effects on bats, but this remains poorly understood in conifer plantations. At two estates in south-west Britain, we specifically tested whether bat species richness and activity respond to (1) the surrounding landscape cover types (2) habitat structure within irregular stands and (3) increasing progress along the transformation continuum in three continuous cover forestry stands undergoing transformation including irregular high forest. Stands further progressed along the transformation continuum had lower basal area, higher mean tree diameter, higher levels of fallen deadwood and greater canopy cover of broadleaf trees. A total of 13 species of bat, equivalent to 76% of the UK resident species were recorded. The activity of six species was significantly influenced by the proportion of four land use types (two positive and two negative associations with conifer woodland, one positive and one negative association with broadleaved woodland, two positive associations with improved grassland and two negative associations with arable) in the surrounding landscape at three spatial scales (500 m, 1500 m and 3000 m around each survey plot). Four species showed significant positive associations with habitat structural features including larger mean tree diameter, greater canopy openness, higher vertical structural complexity, higher quantities of standing and fallen deadwood, and higher canopy cover of broadleaved trees. Many of these habitat features were more prevalent in stands further progressed towards irregular high forest. We did not detect any significant differences in bat species richness or activity levels between the three stand stages, except for Plecotus auritus/austriacus which had higher activity in the Stage 3 stand compared to Stage 2, as the limited replication of our study may have precluded detection of any differences. Our study helps inform us on how bats populations respond to novel management of conifer plantations. Further research to determine thresholds for deadwood and broadleaved trees to further support bats in plantations would be beneficial.

This ground-breaking volume covers 42 species of terrestrial mammal – from the red deer to the pygmy shrew, from the pine marten to the hedgehog. The subject is introduced for the first time as a single overarching field of study, including guidance on survey methods, analysis of sound recordings and appropriate software. The book covers species in Britain, Ireland, the Isle of Man and the Channel Islands. Containing nearly 300 figures in total, each species is considered in detail, with specific spectrogram examples. Furthermore, the book allows the reader access to a downloadable sound library containing more than 250 recordings. The authors have extensive experience and expertise in bioacoustics, including in the sound identification of mammals. They are also heavily involved in creating tools that use machine-learning algorithms to recognise mammal species from their calls. A real ear-opener, this will be the essential handbook for many years to come, serving ecological consultants, academics, conservationists, hobbyists and serious mammal recorders alike.

Urban expansion is a severe threat to biodiversity. In the UK, bats are protected meaning new developments need to be surveyed, potential impacts assessed, and appropriate mitigation action taken. However, efforts to minimise effects of urbanisation on bats are hampered by a lack of data for many species making it difficult to implement effective conservation measures. Here we explore whether citizen science data on bat activity via a passive acoustic network can be used to produce maps of high risk areas to bats from urbanisation and areas with the best opportunities for habitat mitigation. We combine the passive acoustic dataset with fine-scale habitat data and use models to quantify the effect of increasing urban areas or increasing suitable habitat (woodland, wetland, or grass and heathland). Passive acoustic detection can provide a high volume of data and large area of coverage, which is vital to the success of this modelling approach, but the data quality is dependent on accurate species classification. Therefore, we also assess the effect of identification uncertainty on the accuracy of the risk and opportunity maps. We found agreement between results accounting for species uncertainty and those that did not was high, although approximately 15% of high-risk areas would have been missed, and about 23% of habitat creation opportunities falsely prioritised. This modelling and mapping approach has great potential for use in the planning process to reduce impacts on the most important habitat features in the landscape and enable targeted habitat creation.

Road ecology, the study of the impacts of roads and their traffic on wildlife, including birds, is a rapidly growing field, with research showing effects on local avian population densities up to several kilometres from a road. However, in most studies, the effects of roads on the detectability of birds by surveyors are not accounted for. This could be a significant source of error in estimates of the impacts of roads on birds and could also affect other studies of bird populations. Using road density, traffic volume and bird count data from across Great Britain, we assess the relationships between roads and detectability of a range of bird species. Of 51 species analysed, the detectability of 36 was significantly associated with road exposure, in most cases inversely. Across the range of road exposure recorded for each species, the mean positive change in detectability was 52% and the mean negative change was 36%, with the strongest negative associations found in smaller-bodied species and those for which aural cues are more important in detection. These associations between road exposure and detectability could be caused by a reduction in surveyors' abilities to hear birds or by changes in birds' behaviour, making them harder or easier to detect. We suggest that future studies of the impacts of roads on populations of birds or other taxa, and other studies using survey data from road-exposed areas, should account for the potential impacts of roads on detectability.

Roads and their traffic can affect wildlife over large areas and, in regions with dense road networks, may influence a high proportion of the ecological landscape. We assess the abundance of 75 bird species in relation to roads across Great Britain. Of these, 77% vary significantly in abundance with increasing road exposure, just over half negatively so. The effect distances of these negative associations average 700m from a road, covering over 70% of Great Britain and over 40% of the total area of terrestrial protected sites. Species with smaller national populations generally have lower relative abundance with increasing road exposure, whereas the opposite is true for more common species. Smaller-bodied and migratory species are also more negatively associated with road exposure. By creating environmental conditions that benefit generally common species at the expense of others, road networks may echo other anthropogenic disturbances in bringing about large-scale simplification of avian communities.

The global road network, currently over 45 million lane-km in length, is expected to reach 70 million lane-km by 2050, while the number of vehicles utilizing it is expected to double. Roads have been shown to affect a range of wildlife, including birds, but most studies have been relatively small scale. We use data from across Great Britain to analyse the relationships between roads and the spatial distributions of bird populations. We model counts of 51 common and widespread species from the U.K. Breeding Bird Survey in relation to road exposure, which we calculated for each count site using the density, distance and traffic volume of all roads within a 5-km radius. In these models, we incorporate other factors known to affect bird populations, including agricultural intensity, human population, habitat and climate. Importantly, we also account for differences in detectability of birds near to roads. The abundances of 30 species were strongly significantly related to exposure to either major or minor roads. Species were generally in higher abundances with increasing exposure to minor roads (20/28). In contrast, most significant associations between major road exposure and bird abundance were negative (7/8). For species with significant effects of road exposure, we assessed how estimated abundance changed across the central 50% of road exposure experienced for each species. The mean decrease in abundance was 19% and the mean increase was 47%. These changes in bird abundance were up to half as large as those associated with increasing agricultural intensity, a factor often cited as a major cause of bird population changes. Synthesis and applications. Our research shows many species to vary in abundance with increasing road exposure. This suggests that roads may modify bird populations on a national scale and that their potential as drivers of biodiversity change should not be overlooked. Our work highlights the need for appropriate mitigation of roads, particularly in areas important for avian biodiversity. This could include efforts to reduce impacts of road noise and/or collisions, such as reduced speed limits or quieter road surfaces in sensitive areas.

Urbanisation is among the most ecologically damaging change in land use, posing significant threats to global biodiversity. Most bat species are threatened by urbanisation, although urban areas can also offer important roosting and foraging opportunities. Urban development should consider how bats are likely to respond to development, and take measures to minimise impacts. We used acoustic data from four years of citizen science monitoring (2013–2016) to quantify the importance of fine-scale habitat configuration and composition for bats in urban areas in eastern England. Bat distribution and activity were analysed in relation to remote sensing data representing impervious surface, waterbodies and tree-cover density. Furthermore, hypothetical future scenarios of urban development were considered, assuming an increase in impervious or woodland surface. Lakes and discontinuous woodland were the most selected habitats and urban areas were the least selected, with Barbastellus, Myotis and Plecotus species being the most vulnerable. Nyctalus, Pipistrellus and Eptesicus species were less influenced by the presence of urban areas. Our results suggest that urban growth should be sought through the expansion of existing urban blocks, rather than creating new urban patches, to minimise impacts on commuting or foraging sites. Creating bat-friendly habitat of an area at least equal to any new urban settlement could provide mitigation for negative effects of urbanisation. Opportunities to increase areas of discontinuous woodland should be encouraged, while preserving unmanaged areas within large plantations would likely support the exploitation of continuous woodland by bats.

Changing economics in the 20th century led to losses and fragmentation of semi-natural woodland in Britain and to a reduction in active woodland management with many becoming increasingly neglected, even-aged and with closed canopy. Lack of woodland management is known to contribute to declines in some taxonomic groups, for example birds. However, the response of bats to changes in woodland structure are poorly understood. We compared two measures of bat activity, derived from static acoustic recorders across 120 sample plots in coppice, irregular high forest (uneven-aged, continuous cover) and limited intervention (under-managed, even-aged) management stands, within a large tract of ancient woodland in southern England. Bat species richness was highest in irregular high forest stands, and there were significant differences in occupancy rates for most bat species across stand management types. Coppice recorded low activity of several bat species and irregular high forest showed high occupancy rates, including for Barbastelle Barbastella barbastellus, which is IUCN listed as near threatened. The occupancy rates in stand management types differed for some bat species between mid- and late summer counts, suggesting seasonal variation in habitat use. Within stands, most bat species were associated with opened canopy, lower growing stocks and reduced densities of understorey, and to a lesser extent, with large-girthed trees and presence of deadwood snags. In some cases, species responded to a given habitat variable similarly across the three stand management types, whereas in others, the response differed among stand management types. For example, increased numbers of large-girthed trees benefitted a number of bat species within coppice where these were least common, but not in irregular stands. Irregular silviculture high forest appears to provide many of the structural attributes that positively influence occupancy of several woodland bat species, including Barbastella barbastellus.

Assessing the state and trend of biodiversity in the face of anthropogenic threats requires large‐scale and long‐time monitoring, for which new recording methods offer interesting possibilities. Reduced costs and a huge increase in storage capacity of acoustic recorders have resulted in an exponential use of passive acoustic monitoring (PAM) on a wide range of animal groups in recent years. PAM has led to a rapid growth in the quantity of acoustic data, making manual identification increasingly time‐consuming. Therefore, software detecting sound events, extracting numerous features and automatically identifying species have been developed. However, automated identification generates identification errors, which could influence analyses which look at the ecological response of species. Taking the case of bats for which PAM constitutes an efficient tool, we propose a cautious method to account for errors in acoustic identifications of any taxa without excessive manual checking of recordings. We propose to check a representative sample of the outputs of a software commonly used in acoustic surveys (Tadarida), to model the identification success probability of 10 species and two species groups as a function of the confidence score provided for each automated identification. Using this relationship, we then investigated the effect of setting different false positive tolerances (FPTs), from a 50% to 10% false positive rate, above which data are discarded, by repeating a large‐scale analysis of bat response to environmental variables and checking for consistency in the results. Considering estimates, standard errors and significance of species response to environmental variables, the main changes occurred between the naive (i.e. raw data) and robust analyses (i.e. using FPTs). Responses were highly stable between FPTs. We conclude it was essential to, at least, remove data above 50% FPT to minimize false positives. We recommend systematically checking the consistency of responses for at least two contrasting FPTs (e.g. 50% and 10%), in order to ensure robustness, and only going on to conclusive interpretation when these are consistent. This study provides a huge saving of time for manual checking, which will facilitate the improvement in large‐scale monitoring, and ultimately our understanding of ecological responses.

Many migratory bird species are undergoing population declines as a result of potentially multiple, interacting mechanisms. Understanding the environmental associations of spatial variation in population change can help tease out the likely mechanisms involved. Common Cuckoo Cuculus canorus populations have declined by 69% in England but increased by 33% in Scotland. The declines have mainly occurred in lowland agricultural landscapes, but their mechanisms are unknown. At both the local scale within the county of Devon (SE England) and at the national (UK) scale, we analysed the breeding season distribution of Cuckoos in relation to habitat variation, the abundance of host species and the abundance of moth species whose caterpillars are a key food of adult Cuckoos. At the local scale, we found that Cuckoos were more likely to be detected in areas with more semi-natural habitat, more Meadow Pipits Anthus pratensis (but fewer Dunnocks Prunella modularis) and where, later in the summer, higher numbers of moths were captured whose larvae are Cuckoo prey. Nationally, Cuckoos have become more associated with upland heath characterized by the presence of Meadow Pipit hosts, and with wetland habitats occupied by Eurasian Reed Warbler Acrocephalus scirpaceus hosts. The core distribution of Cuckoos has shifted from south to north within the UK. By the end of 2009, the abundance of macro-moth species identified as prey had also declined four times faster than that of species not known to be taken by Cuckoos. The abundance of these moths has shown the sharpest declines in grassland, arable and woodland habitats and has increased in semi-natural habitats (heaths and rough grassland). Our study suggests that Cuckoos are likely to remain a very scarce bird in lowland agricultural landscapes without large-scale changes in agricultural practices.

Passive acoustic sensing has emerged as a powerful tool for quantifying anthropogenic impacts on biodiversity, especially for echolocating bat species. To better assess bat population trends there is a critical need for accurate, reliable, and open source tools that allow the detection and classification of bat calls in large collections of audio recordings. The majority of existing tools are commercial or have focused on the species classification task, neglecting the important problem of first localizing echolocation calls in audio which is particularly problematic in noisy recordings. We developed a convolutional neural network based open-source pipeline for detecting ultrasonic, full-spectrum, search-phase calls produced by echolocating bats. Our deep learning algorithms were trained on full-spectrum ultrasonic audio collected along road-transects across Europe and labelled by citizen scientists from www.batdetective.org. When compared to other existing algorithms and commercial systems, we show significantly higher detection performance of search-phase echolocation calls with our test sets. As an example application, we ran our detection pipeline on bat monitoring data collected over five years from Jersey (UK), and compared results to a widely-used commercial system. Our detection pipeline can be used for the automatic detection and monitoring of bat populations, and further facilitates their use as indicator species on a large scale. Our proposed pipeline makes only a small number of bat specific design decisions, and with appropriate training data it could be applied to detecting other species in audio. A crucial novelty of our work is showing that with careful, non-trivial, design and implementation considerations, state-of-the-art deep learning methods can be used for accurate and efficient monitoring in audio.

In order to ensure that the placement of future wind energy developments does not conflict with important areas for bats, surveys and analyses are required to deliver a robust understanding of large-scale patterns in species’ distributions and abundance. We demonstrate that extensive presence-absence survey data can be collected for bats across a large (>20,000km2) region of southern Scotland using volunteers supplemented with additional fieldworker effort in remote areas. We advocate a survey design that allows data to be collected for all bat species, but provide more focused analyses on three species (Leisler's bat, noctule and Nathusius' pipistrelle) that are currently considered to be at highest risk from wind turbines. We estimate that between 16% and 24% of the regional populations of these three high risk species overlap existing and approved wind farms, with 50% of this overlap concentrated at just 10% of wind farms. This emphasises the importance of new wind farm placement to minimise impact on these species. We have stratified the region according to the potential impact on bats of future wind farm development, highlighting those areas in the top 1%, 5% and 10% of risk. We conclude that there is a need for higher quality data of this type in order to inform spatial models of bat distribution and activity. As a minimum standard, researchers working on bats should prioritise the collection and use of presence-absence data with consideration of the underlying survey design and representativeness of the data collected. This can be achieved most cost-effectively by working with the public to develop large-scale acoustic monitoring schemes.

Summary Monitoring biodiversity over large spatial and temporal scales is crucial for assessing the impact of global changes and environmental mitigation measures. However, large‐scale monitoring of invertebrates remains poorly developed despite the importance of these organisms in ecosystem functioning. Exciting possibilities applicable to professional and citizen science are offered by new recording techniques and methods of semi‐automated species recognition based on sound detection. Static broad‐spectrum detectors deployed to record throughout whole nights have been recommended for standardised acoustic monitoring of bats, but they have the potential to also collect acoustic data for other species groups. Large‐scale deployment of such systems is only viable when combined with robust automated species identification algorithms. Here we examine the potential of such a system for detecting, identifying and monitoring bush‐crickets (Orthoptera of the family Tettigoniidae). We use incidental sound recordings generated by an extensive citizen science bat survey and recordings from intensive site surveys to test a semi‐automated step‐wise method with a classifier for assigning species identities. We assess species’ diel activity patterns to make recommendations for survey timing and interpretation of existing nocturnal data sets and consider the feasibility of determining site occupancy. Of six species of bush‐crickets, the species classifier achieved over 85% accuracy for three, speckled bush‐cricket, dark bush‐cricket and Roesel's bush‐cricket. It should be possible to automatically scan recordings for these species with minimal manual validation. Further refinement of the classifier is required for the three remaining species, in particular for the acoustically similar short‐winged conehead and long‐winged conehead. Diel activity patterns are species specific and it may be necessary to adjust the hours over which the detectors record to increase detection of key species, but this must be weighed against the costs in terms of increased memory and battery use and equipment security during daytime. We conclude that with logistical support and centralised semi‐automated species identification it is now possible for the public to contribute to large‐scale acoustic monitoring of Orthoptera while recording bats. Further innovation of sound classifier algorithms is needed and would be aided by improved reference sound libraries from multiple locations spanning species’ ranges.

Summary Modelling species distribution and abundance is important for many conservation applications, but it is typically performed using relatively coarse‐scale environmental variables such as the area of broad land‐cover types. Fine‐scale environmental data capturing the most biologically relevant variables have the potential to improve these models. For example, field studies have demonstrated the importance of linear features, such as hedgerows, for multiple taxa, but the absence of large‐scale datasets of their extent prevents their inclusion in large‐scale modelling studies. We assessed whether a novel spatial dataset mapping linear and woody‐linear features across the UK improves the performance of abundance models of 18 bird and 24 butterfly species across 3723 and 1547 UK monitoring sites, respectively. Although improvements in explanatory power were small, the inclusion of linear features data significantly improved model predictive performance for many species. For some species, the importance of linear features depended on landscape context, with greater importance in agricultural areas. Synthesis and applications . This study demonstrates that a national‐scale model of the extent and distribution of linear features improves predictions of farmland biodiversity. The ability to model spatial variability in the role of linear features such as hedgerows will be important in targeting agri‐environment schemes to maximally deliver biodiversity benefits. Although this study focuses on farmland, data on the extent of different linear features are likely to improve species distribution and abundance models in a wide range of systems and also can potentially be used to assess habitat connectivity.

Urban land cover is the fastest growing land-use form globally and there is concern that urbanisation will negatively impact native biodiversity. Bats are ecologically diverse predators and their responses to urban development may provide insights into wider biodiversity responses to urbanisation. Developments in bat detection methods mean it is now possible for citizen scientists to collect detailed bat distribution data. The geographical and habitat coverage of such data make them ideal for addressing urban planning issues. In this paper we quantify the impact of planned housing on bat populations and evaluate possible mitigation measures. We combined data on 12 bat species collected through a large citizen science project in Norfolk, UK, with spatially explicit housing plans for the next decade and tested the impact of mitigation planning scenarios operating at different spatial scales. The planned housing was predicted to decrease occurrence or activity for all 12 bat species. Locally, these decreases could be substantial, leading to a reduction in the likelihood of occurrence from 40% to 1%. However, at a county-scale the proposed level of housing is equivalent to less than a 2% decrease in total occurrence and abundance across all species. The negative effect of planned housing could be reduced by 46% on average by preferentially building on less preferred habitats and in areas with low populations of urban-sensitive bat species. This paper demonstrates an easily transferable method for determining rich habitats where new developments should be avoided and for investigating the potential of mitigation strategies. (C) 2017 Elsevier B.V. All rights reserved.

Bats frequently roost in historic churches, and these colonies are of considerable conservation value. Inside churches, bat droppings and urine can cause damage to the historic fabric of the building and to items of cultural significance. In extreme cases, large quantities of droppings can restrict the use of a church for worship and/or other community functions. In the United Kingdom, bats and their roosts are protected by law, and striking a balance between conserving the natural and cultural heritage can be a significant challenge. We investigated mitigation strategies that could be employed in churches and other historic buildings to alleviate problems caused by bats without adversely affecting their welfare or conservation status. We used a combination of artificial roost provision and deterrence at churches in Norfolk, England, where significant maternity colonies of Natterer's bats Myotis nattereri damage church features. Radio-tracking data and population modelling showed that excluding M. nattereri from churches is likely to have a negative impact on their welfare and conservation status, but that judicious use of deterrents, especially high intensity ultrasound, can mitigate problems caused by bats. We show that deterrence can be used to move bats humanely from specific roosting sites within a church and limit the spread of droppings and urine so that problems to congregations and damage to cultural heritage can be much reduced. In addition, construction of bespoke roost spaces within churches can allow bats to continue to roost within the fabric of the building without flying in the church interior. We highlight that deterrence has the potential to cause serious harm to M. nattereri populations if not used judiciously, and so the effects of deterrents will need careful monitoring, and their use needs strict regulation.

Generalist species are becoming increasingly dominant in European bird communities. This has been taken as evidence of biotic homogenization, whereby generalist winners' systematically replace specialist losers'. We test this pattern by relating changes in the average specialization of UK bird communities to changes in the density of species with different degrees of habitat specialization. Although we find the expected decline in community specialization, this was driven by a combination of a strong increase in the density of the most generalist quartile of species and declines in the density of moderately generalist species. Contrary to expectation, specialist species increased slightly over the 18-year study period but had little effect on the overall trend in community specialization. Our results indicate that the apparent homogenization of UK bird communities is not driven by the replacement of specialists by generalists, but instead by the changing fortunes of generalist species.

Robust information on bat species distribution and activity is lacking. With developments in passive full spectrum bat detectors and software packages for automating the analysis of sound files, there is the potential to analyse large volumes of acoustic data and thus inform a better understanding of bat ecology and distribution. However, for anyone making use of such tools, it is essential to understand the limitations and likely biases of the software, in order to make an informed interpretation.