Yves Bas

Accounting for weather and time-of-day parameters when analysing count data from monitoring programs

Problems induced by heterogeneity in species and individuals detectability are now well recognized when analysing count data. Yet, most recent techniques developed to handle this problem are still hardly applicable to many monitoring schemes, and do not provide abundance estimates at the point count scale. Here, we show how using simple weather variables can be a useful surrogate to detect variability in species detectability. We further look for a potential bias or loss in statistical power based on count data while ignoring weather and time-of-day variables. We first used the French Breeding Bird Survey to test how each of the counts of the 97 most common breeding species was influenced by weather and time-of-day variables. We assessed how the estimation of each species response to fragmentation could be influenced by correcting counts with such variables. Among 97 species, 75 were affected by at least one of the five weather and time-of-day variables considered. Despite these strong influences, the relationship between species abundance and fragmentation was not biased when not controlling counts for weather and time-of-day variables and further found no improvement in statistical power when accounting for these variables. Our results show that simple variables can be very powerful to assess how species detectability is influenced by weather conditions but they are inconsistent with any specific bias due to heterogeneous detectability. We suggest that raw count data can be used without any correction in case the sources of variation in detectability could be considered independent to the factor of interest.

Use of Large‐Scale Acoustic Monitoring to Assess Anthropogenic Pressures on Orthoptera Communities

Biodiversity monitoring at large spatial and temporal scales is greatly needed in the context of global changes. Although insects are a species-rich group and are important for ecosystem functioning, they have been largely neglected in conservation studies and policies, mainly due to technical and methodological constraints. Sound detection, a nondestructive method, is easily applied within a citizen-science framework and could be an interesting solution for insect monitoring. However, it has not yet been tested at a large scale. We assessed the value of a citizen-science program in which Orthoptera species (Tettigoniidae) were monitored acoustically along roads. We used Bayesian model-averaging analyses to test whether we could detect widely known patterns of anthropogenic effects on insects, such as the negative effects of urbanization or intensive agriculture on Orthoptera populations and communities. We also examined site-abundance correlations between years and estimated the biases in species detection to evaluate and improve the protocol. Urbanization and intensive agricultural landscapes negatively affected Orthoptera species richness, diversity, and abundance. This finding is consistent with results of previous studies of Orthoptera, vertebrates, carabids, and butterflies. The average mass of communities decreased as urbanization increased. The dispersal ability of communities increased as the percentage of agricultural land and, to a lesser extent, urban area increased. Despite changes in abundances over time, we found significant correlations between yearly abundances. We identified biases linked to the protocol (e.g., car speed or temperature) that can be accounted for ease in analyses. We argue that acoustic monitoring of Orthoptera along roads offers several advantages for assessing Orthoptera biodiversity at large spatial and temporal extents, particularly in a citizen science framework.

Potential for coupling the monitoring of bush-crickets with established large-scale acoustic monitoring of bats

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 Roesels 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.

Potential of bat pass duration measures for studies of bat activity

Abstract Acoustic detectors have become increasingly used by bat workers to investigate bat ecology and assess the impacts of anthropogenic pressures. Within these studies, the metric used, ‘bat activity’, is based on the number of bat passes, without considering the bat pass duration (i.e. each event of a bat detected within the range of an ultrasonic detector). We expected that bat pass duration may contain information about site quality in terms of foraging potential. Because bats are expected to have a more sinuous trajectory and slower velocity when they exhibit foraging behaviour, as opposed to commuting behaviour, we hypothesize a longer bat pass duration in favourable habitats; during seasons with important energetic demands; or during night peak activity. We used datasets from a large-scale acoustic bat survey (n = 2890 sites), with a total of 24,597 bat pass measures from 6 taxa, and performed GLMM modelling. We detected a significant effect of habitat type on bat pass duration for five taxa. Shorter bat pass durations were detected at the beginning of the night. We detected longer pass durations during the lactation period or just before hibernating, while weather conditions or ageing and wear of the detector rarely influenced bat pass duration. Bat pass duration appears to be a simple and easy measure for position calls on a gradient between commuting vs. foraging behaviour. We suggest that the traditional measure of bat activity may be weighted by bat pass duration by giving more weight to events with potentially stronger links to foraging behaviour.

Echolocation Calls and Flight Behaviour of the Elusive Pied Butterfly Bat (Glauconycteris superba), and New Data on Its Morphology and Ecology

The pied butterfly bat, Glauconycteris superba, is endemic to the tropical forest zone of Africa, where it was previously known from only five specimens. Here we report the capture of 10 individuals in two localities of the Democratic Republic of the Congo (Mbiye Island and Yoko forest reserve), and we present the first acoustic data of the species recorded using a conventional microphone and a home-made acoustic system for real time 3D localization. Our morphological comparisons show that females are larger and heavier than males, and that the two sexes exhibit the same fur coloration pattern. We found some individual variations concerning the width of the two lateral white stripes on the belly, and the number and extension of white shoulder-spots. The echolocation recordings show evidence for alternation between two call types (A and B), differing in frequency, bandwidth, and duration. The acoustic signals obtained before captures and after releases revealed important variations depending on the trajectories and environmental conditions. Acoustic characteristics, wing measurements, and the unique black and white fur pattern of G. superba suggest that it is a canopy species able to fly at high speeds. Our findings will be useful for future ecological studies to provide new data on the range, population size, trend and threats of G. superba in order to better assess its conservation status.