Accounting for automated identification errors in acoustic surveys

Disentangling mechanisms responsible for wind energy effects on European bats

Mitigating anthropogenic climate change involves deployments of renewable energy worldwide, including wind energy, which can cause significant impacts on flying animals. Bats have highly contrasted responses to wind turbines (WT), either through attraction increasing collision risks, or avoidance leading to habitat losses. However, the underlying mechanisms remain largely unknown despite the expected rapid evolution of WT size and densities. Here, using an extensive acoustic sampling (i.e. 361 sites-nights) up to 1483 m from WT at regional scale, we disentangle the effects of WT size (ground clearance and rotor diameter), configuration (density and distance), and operation (blade rotation speed and wake effect) on hedgerow use by 8 bat species/groups and one vertical community distribution index. Our results reveal that all WT parameters affected bat activity and their vertical distribution. Especially, we show that the relative activity of high-flying species in the community was lower for higher WT density and lower ground clearance. Medium-flying species were sensitive to wind turbine distance, with either attraction or avoidance depending on proximity to the wake area and wind conditions. Specifically, wind turbine distance, wake effect and their interaction each affected the activity of one, three, and three species out of eight, respectively. Blade rotation and rotor diameter affected the activity of four and three species/groups, respectively, and ground clearance affected the activity of five ones. Taken together, WT configuration, operation, and size parameters affected the activity of three, five, and seven out of eight species/groups, respectively. These results call for the consideration of all these factors when assessing the ecological sustainability of future wind farms. The study especially advocates to avoid high WT densities, large rotors, and to site WT as far as possible from optimal habitats such as woody edges and not between them and the source of prevailing winds, in order to limit bats-WT interactions.

What drives bat activity at field boundaries?

Field boundaries are important habitat for bats in agricultural landscapes, serving as commuting and foraging areas for many species. The goal of our study was to better understand the drivers of bat activity in agricultural landscapes to inform conservation policy and make specific recommendations for habitat management. We placed sixty-four full spectrum bat detectors at random recording locations, weekly, along field boundaries in North Somerset between July and October 2020. We used an automated classifier to analyse recordings and performed error rate modelling to account for and remove the majority of error in automated classifications. We used generalised additive models to explore bat response to recording location metrics, controlling for spatial-autocorrelation and temporal differences in sampling. We validated our models with k-fold cross-validation and explored the utility of our models for predicting bat activity at new sites. We found that field boundary characteristics better describe bat activity than adjacent field characteristics or measures of local landscape for the majority of species studied. Bat activity was higher along tall, wide, vegetated field boundaries containing trees; there was lower activity at arable recording locations. Still, bat activity was highly variable and predictive error was high. We found a large spatial effect driving activity patterns, meaning models are not able to predict activity beyond the extent of the study area. We recommend management strategies that give incentives to farmers for replacing fences with hedgerows, planting hedgerow trees, and maintaining tall and outgrown field boundaries.

Even low light pollution levels affect the spatial distribution and timing of activity of a "light tolerant" bat species

By disrupting nocturnal landscapes worldwide, light pollution caused by Artificial Light At Night (ALAN) is recognized as a major threat to biodiversity. As even low light intensities might affect some taxa, concerns are arising about biological responses to widespread low light levels. We used data from a French citizen science bat monitoring program (1894 full-nights monitored on 1055 sites) to explore the landscape-scale effects of light on an open-space-foraging bat species, the Serotine bat (Eptesicus serotinus). We assessed this species' abundance and timing of night-time activity (median time of activity) at foraging sites. ALAN, and to a lesser extent moonlight, reduced E. serotinus abundance. ALAN delayed activity, and this delay was amplified during overcast nights. On the contrary, where there was no ALAN, the higher the cloud cover, the earlier the activity occurred. Cloud cover likely darkened the night sky in rural locations, whereas it amplified skyglow in light-polluted places, increasing ALAN effects on bats. Interestingly, moonlight also delayed activity but this effect was weakened where there was ALAN. Our study shows that even fine variations of light levels could affect the spatiotemporal distribution of a common species usually considered to be "light tolerant", with potential cascading effects on individual fitness and population dynamics. It stresses how urgent it is to preserve and restore dark areas to protect biodiversity from light pollution while working on light intensity and directivity where ALAN is needed.

Landscape composition drives the impacts of artificial light at night on insectivorous bats

Among the most prevalent sources of biodiversity declines, Artificial Light At Night (ALAN) is an emerging threat to global biodiversity. Much knowledge has already been gained to reduce impacts. However, the spatial variation of ALAN effects on biodiversity in interaction with landscape composition remains little studied, though it is of the utmost importance to identify lightscapes most in need of action. Several studies have shown that, at local scale, tree cover can intensify positive or negative effects of ALAN on biodiversity, but none have - at landscape scale - studied a wider range of landscape compositions around lit sites. We hypothesized that the magnitude of ALAN effects will depend on landscape composition and species' tolerance to light. Taking the case of insectivorous bats because of their varying sensitivity to ALAN, we investigated the species-specific activity response to ALAN. Bat activity was recorded along a gradient of light radiance. We ensured a large variability in landscape composition around 253 sampling sites. Among the 13 bat taxa studied, radiance decreased the activity of two groups of the slow-flying gleaner guild (Myotis and Plecotus spp.) and one species of the aerial-hawking guild (Pipistrellus pipistrellus), and increased the activity of two species of the aerial-hawking guild (Pipistrellus kuhlii and Pipistrellus pygmaeus). Among these five effects, the magnitude of four of them was driven by landscape composition. For five other species, ALAN effects were only detectable in particular landscape compositions, making the main effect of radiance undetectable without account for interactions with landscape. Specifically, effects were strongest in non-urban habitats, for both guilds. Results highlight the importance to prioritize ALAN reduction efforts in non-urban habitats, and how important is to account for landscape composition when studying ALAN effects on bats to avoid missing effects.

Optimizing bat bioacoustic surveys in human-modified Neotropical landscapes

During the last decades, the use of bioacoustics as a non-invasive and cost-effective sampling method has greatly increased worldwide. For bats, acoustic surveys have long been known to complement traditional mist-netting, however, appropriate protocol guidelines are still lacking for tropical regions. Establishing the minimum sampling effort needed to detect ecological changes in bat assemblages (e.g., activity, composition, and richness) is crucial in view of workload and project cost constraints, and because detecting such changes must be reliable enough to support effective conservation management. Using one of the most comprehensive tropical bat acoustic data sets, collected in the Amazon, we assessed the minimum survey effort required to accurately assess the completeness of assemblage inventories and habitat selection in fragmented forest landscapes for aerial insectivorous bats. We evaluated a combination of 20 different temporal sampling schemes, which differed regarding number of hours per night, number of nights per site, and sampling only during the wet or dry season, or both. This was assessed under two different landscape scenarios: in primary forest fragments embedded in a matrix of secondary forest and in the same forest fragments, but after they had been re-isolated through clearing of the secondary forest. We found that the sampling effort required to achieve 90% inventory completeness varied considerably depending on the research aim and the landscape scenario evaluated, averaging ~80 and 10 nights before and after fragment re-isolation, respectively. Recording for more than 4 h per night did not result in a substantial reduction in the required number of sampling nights. Regarding the effects of habitat selection, except for assemblage composition, bat responses in terms of richness, diversity, and activity were similar across all sampling schemes after fragment re-isolation. However, before re-isolation, a minimum of four to six sampling hours per night after dusk and three to five nights of sampling per site were needed to detect significant effects that could otherwise go unnoticed. Based on our results, we propose guidelines that will aid to optimize sampling protocols for bat acoustic surveys in the Neotropics.

Effects of Environmental Clutter on Synthesized Chiropteran Echolocation Signals in an Anechoic Chamber

Ultrasonic bat detectors are useful for research and monitoring purposes to assess occupancy and relative activity of bat communities. Environmental “clutter” such as tree boles and foliage can affect the recording quality and identification of bat echolocation calls collected using ultrasonic detectors. It can also affect the transmission of calls and recognition by bats when using acoustic lure devices to attract bats to mist-nets. Bat detectors are often placed in forests, yet automatic identification programs are trained on call libraries using echolocation passes recorded largely from open spaces. Research indicates that using clutter-recorded calls can increase classification accuracy for some bat species and decrease accuracy for others, but a detailed understanding of how clutter impacts the recording and identification of echolocation calls remains elusive. To clarify this, we experimentally investigated how two measures of clutter (i.e., total basal area and number of stems of simulated woody growth, as well as recording angle) affected the recording and classification of a synthesized echolocation signal under controlled conditions in an anechoic chamber. Recording angle (i.e., receiver position relative to emitter) significantly influenced the probability of correct classification and differed significantly for many of the call parameters measured. The probability of recording echo pulses was also a function of clutter but only for the detector angle at 0° from the emitter that could receive deflected pulses. Overall, the two clutter metrics were overshadowed by proximity and angle of the receiver to the sound source but some deviations from the synthesized call in terms of maximum, minimum, and mean frequency parameters were observed. Results from our work may aid efforts to better understand underlying environmental conditions that produce false-positive and -negative identifications for bat species of interest and how this could be used to adjust survey accuracy estimates. Our results also help pave the way for future research into the development of acoustic lure technology by exploring the effects of environmental clutter on ultrasound transmission.

Bat responses to changes in forest composition and prey abundance depend on landscape matrix and stand structure

Despite the key importance of the landscape matrix for bats, we still not fully understand how the effect of forest composition interacts at combined stand and landscape scales to shape bat communities. In addition, we lack detailed knowledge on the effects of local habitat structure on bat-prey relationships in forested landscapes. We tested the assumptions that (i) forest composition has interacting effects on bats between stand and landscape scales; and (ii) stand structure mediates prey abundance effects on bat activity. Our results indicated that in conifer-dominated landscapes (> 80% of coniferous forests) bat activity was higher in stands with a higher proportion of deciduous trees while bats were less active in stands with a higher proportion of deciduous trees in mixed forest landscapes (~ 50% of deciduous forests). Moth abundance was selected in the best models for six among nine bat species. The positive effect of moth abundance on Barbastella barbastellus was mediated by vegetation clutter, with dense understory cover likely reducing prey accessibility. Altogether, our findings deepen our understanding of the ecological processes affecting bats in forest landscapes and strengthen the need to consider both landscape context and trophic linkage when assessing the effects of stand-scale compositional and structural attributes on bats.

Bats actively prey on mosquitoes and other deleterious insects in rice paddies: Potential impact on human health and agriculture

BACKGROUND

The fact that bats suppress agricultural pests has been measured for some particular dyads of predator and prey species in both economic and food security terms. The recent emergence of new molecular techniques allows for more precise screenings of bat's diet than the traditional visual identification systems and provides further evidence that bats consume an ample array of agricultural pest species. The main focus of the regulatory services that bats provide in agroecosystems has been on crop pests that cause yield losses. Rice paddies constitute a particular agronomic system with specific challenges, not only related to crop productivity but also to human health. Dipteran density in such ecosystems poses a serious threat to human wellbeing and hinders crop production. Mosquitoes cause direct harm to human populations, transmitting a number of infectious diseases. Non-biting midges (Chironomidae) can consume and weaken rice seedlings and can cause major yield losses.

RESULTS

Mosquito populations and bat activity were assessed in rice paddies of Montgrí, Medes i Baix Ter Natural Park (NE Iberian Peninsula). Molecular analyses of bats faeces (6-weekly samples of 15 faeces each between mid-August and September) proved the presence of both mosquitoes and nonbiting midges in all diet samples. Furthermore, bat activity at the sampling locations was related to adult mosquito density.

CONCLUSION

Our results suggest that bats actively exploit the emergence of adult mosquitoes and further prove that they prey on mosquitoes, nonbiting midges and other deleterious insects. Promoting the presence of bats next to human settlements in such agroecosystems may constitute a biological control system with direct impact on both human health and crop yield. © 2020 Society of Chemical Industry.

Validation prediction: a flexible protocol to increase efficiency of automated acoustic processing for wildlife research

Automated recognition is increasingly used to extract species detections from audio recordings; however, the time required to manually review each detection can be prohibitive. We developed a flexible protocol called "validation prediction" that uses machine learning to predict whether recognizer detections are true or false positives and can be applied to any recognizer type, ecological application, or analytical approach. Validation prediction uses a predictable relationship between recognizer score and the energy of an acoustic signal but can also incorporate any other ecological or spectral predictors (e.g., time of day, dominant frequency) that will help separate true from false-positive recognizer detections. First, we documented the relationship between recognizer score and the energy of an acoustic signal for two different recognizer algorithm types (hidden Markov models and convolutional neural networks). Next, we demonstrated our protocol using a case study of two species, the Common Nighthawk (Chordeiles minor) and Ovenbird (Seiurus aurocapilla). We reduced the number of detections that required validation by 75.7% and 42.9%, respectively, while retaining at least 98% of the true-positive detections. Validation prediction substantially improves the efficiency of using automated recognition on acoustic data sets. Our method can be of use to wildlife monitoring and research programs and will facilitate using automated recognition to mine bioacoustic data sets.

Autonomous sound recording outperforms human observation for sampling birds: a systematic map and user guide

Autonomous sound recording techniques have gained considerable traction in the last decade, but the question remains whether they can replace human observation surveys to sample sonant animals. For birds in particular, survey methods have been tested extensively using point counts and sound recording surveys. Here, we review the latest evidence for this taxon within the frame of a systematic map. We compare sampling effectiveness of these two survey methods, the output variables they produce, and their practicality. When assessed against the standard of point counts, autonomous sound recording proves to be a powerful tool that samples at least as many species. This technology can monitor birds in an exhaustive, standardized, and verifiable way. Moreover, sound recorders give access to entire soundscapes from which new data types can be derived (vocal activity, acoustic indices). Variables such as abundance, density, occupancy, or species richness can be obtained to yield data sets that are comparable to and compatible with point counts. Finally, autonomous sound recorders allow investigations at high temporal and spatial resolution and coverage, which are more cost effective and cannot be achieved by human observations alone, even though small-scale studies might be more cost effective when carried out with point counts. Sound recorders can be deployed in many places, they are more scalable and reliable, making them the better choice for bird surveys in an increasingly data-driven time. We provide an overview of currently available recorders and discuss their specifications to guide future study designs.

Bat Pass Duration Measurement: An Indirect Measure of Distance of Detection

Few reports have been published on detection distances of bat calls because the evaluation of detection distance is complicated. Several of the approaches used to measure detection distances are based on the researcher’s experience and judgment. More recently, multiple microphones have been used to model flight path. In this study, the validity of a low-cost and simple detectability metric was tested. We hypothesize that the duration of an echolocating-bat-pass within the area of an ultrasonic bat detector is correlated with the distance of detection. Two independent datasets from a large-scale acoustic bat survey—a total of 25,786 bat-passes from 20 taxa (18 species and two genera)—were measured. We found a strong relationship between these measures of bat-pass duration and published detection distances. The advantages of bat-pass duration measures are that, for each study, experimenters easily produce their own proxy for the distance of detection. This indirect measure of the distance of detection could be mobilized to monitor the loss in microphone sensitivity used to monitor long-term population trends. Finally, the possibility of producing an index for distance of detection provides a weight for each bat species’ activity when they are aggregated to produce a bat community metric, such as the widely used “total activity”.