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Moths (Lepidoptera) are major agricultural and forest pests in many parts of the world, including Europe, with many causing great economic damage to crops, horticultural plants, stored items, and wool products. Here, we focus on two ecologically similar inchworms, Operophtera brumata and Erannis defoliaria , known for their high foliage consumption during the spring emergence of caterpillars. We hypothesise that bats could play a role in reducing pests such as caterpillars by switching to this abundant emerging prey. At two infested and one control forest sites, caterpillars were sampled during spring to determine levels of infestation. At the same time, bat flight activity was monitored during the peak in caterpillar abundance. During the spring caterpillar outbreak, we collected faecal samples of forest-dwelling bats capable of using gleaning. The majority of samples were positive for our focus species, being 51.85% for O. brumata and 29.63% for E. defoliaria faecal samples. The foraging activity of two gleaning bats, Myotis nattereri and Myotis bechsteinii , increased at both infested sites, but not at the control site, during caterpillar emergence, as did foraging of Plecotus auritus/austriacus , which used both gleaning and aerial hawking. We conclude that both specialists and occasional gleaners, which prefer different prey but are able to switch their foraging strategies, aggregate at sites during pest emergence and, as such, our results confirm the high potential of bats to reduce numbers of pest species such as caterpillars.

Fluctuating asymmetry, the non-directional deviation from bilateral symmetry resulting from developmental instability, can indicate early-life environmental stress. While fluctuating asymmetry can affect individual survival and reproductive success, its effect on fitness differs between species. Here, we analyzed up to 27 years of mark-recapture data from 894 RFID tagged individuals of three forest-living bat species in southern Germany to investigate the degree of fluctuating asymmetry in forearm length. In Bechstein’s bats, Myotis bechsteinii , the species with the highest sample size, we furthermore investigated if fluctuating asymmetry has become more frequent over the study period, a time when juvenile bats have grown larger forearms in response to warmer summers. We also investigated whether fluctuating asymmetry affects individual lifespan and lifetime reproductive success in female Myotis bechsteinii . The degree of fluctuating asymmetry clearly exceeding the measurement error estimated on recaptured individuals was similar in all three species (1.8%). In female Myotis bechsteinii , the frequency of fluctuating asymmetry did not increase over the course of the study and even strong asymmetry had no effect on individual reproductive success and life expectancy. Our data suggest that fluctuating asymmetry is a poor predictor of fitness in the female Myotis bechsteinii studied, and is so far unaffected by the warming environment which is leading to larger individuals in our study population.

Social dynamics are an important but poorly understood aspect of bat ecology. Herein we use a combination of graph theoretic and spatial approaches to describe the roost and social network characteristics and foraging associations of an Indiana bat (Myotis sodalis) maternity colony in an agricultural landscape in Ohio, USA. We tracked 46 bats to 50 roosts (423 total relocations) and collected 2,306 foraging locations for 40 bats during the summers of 2009 and 2010. We found the colony roosting network was highly centralized in both years and that roost and social networks differed significantly from random networks. Roost and social network structure also differed substantially between years. Social network structure appeared to be unrelated to segregation of roosts between age classes. For bats whose individual foraging ranges were calculated, many shared foraging space with at least one other bat. Compared across all possible bat dyads, 47% and 43% of the dyads showed more than expected overlap of foraging areas in 2009 and 2010 respectively. Colony roosting area differed between years, but the roosting area centroid shifted only 332 m. In contrast, whole colony foraging area use was similar between years. Random roost removal simulations suggest that Indiana bat colonies may be robust to loss of a limited number of roosts but may respond differently from year to year. Our study emphasizes the utility of graphic theoretic and spatial approaches for examining the sociality and roosting behavior of bats. Detailed knowledge of the relationships between social and spatial aspects of bat ecology could greatly increase conservation effectiveness by allowing more structured approaches to roost and habitat retention for tree-roosting, socially-aggregating bat species.

Social structure evolves from a trade-off between the costs and benefits of group-living, which are in turn dependent upon the distribution of key resources such as food and shelter. Males and females, or juveniles and adults, may have different priorities when selecting habitat due to differences in physiological or behavioural imperatives, leading to complex patterns in group composition. We studied social structure and mating behaviour in the insectivorous bat Myotis daubentonii along an altitudinal gradient, combining field studies with molecular genetics. With increasing altitude the proportion of males in summer roosts increased and only males were present in the highest roosts. With increasing altitude environmental temperature decreased, nightly variation in temperature increased, and bat foraging activity decreased, supporting the hypothesis that the harsher, high elevation sites cannot support breeding females. We found that offspring in female-dominated lowland roosts had a very high probability of being fathered by bats caught during autumn swarming at hibernation sites, in contrast to those in intermediate roosts, which had a high probability of being fathered by males sharing the nursery roost with the females. Whilst females normally appear to exclude males from nursery colonies, for those in marginal habitats, one explanation for the presence of males is that the thermoregulatory benefits to the females may outweigh disadvantages, such as competition for food, and give some males an opportunity to increase their breeding success. We suggest that the environment, and its effects on resource distribution, thus determine social structure, which in turn determines the mating pattern that has evolved.

The most basic behavioural states of animals can be described as active or passive. While high‐resolution observations of activity patterns can provide insights into the ecology of animal species, few methods are able to measure the activity of individuals of small taxa in their natural environment. We present a novel approach in which a combination of automatic radiotracking and machine learning is used to distinguish between active and passive behaviour in small vertebrates fitted with lightweight transmitters (<0.4 g). We used a dataset containing >3 million signals from very‐high‐frequency (VHF) telemetry from two forest‐dwelling bat species (Myotis bechsteinii [n = 52] and Nyctalus leisleri [n = 20]) to train and test a random forest model in assigning either active or passive behaviour to VHF‐tagged individuals. The generalisability of the model was demonstrated by recording and classifying the behaviour of tagged birds and by simulating the effect of different activity levels with the help of humans carrying transmitters. The model successfully classified the activity states of bats as well as those of birds and humans, although the latter were not included in model training (F1 0.96–0.98). We provide an ecological case‐study demonstrating the potential of this automated monitoring tool. We used the trained models to compare differences in the daily activity patterns of two bat species. The analysis showed a pronounced bimodal activity distribution of N. leisleri over the course of the night while the night‐time activity of M. bechsteinii was relatively constant. These results show that subtle differences in the timing of species' activity can be distinguished using our method. Our approach can classify VHF‐signal patterns into fundamental behavioural states with high precision and is applicable to different terrestrial and flying vertebrates. To encourage the broader use of our radiotracking method, we provide the trained random forest models together with an R package that includes all necessary data processing functionalities. In combination with state‐of‐the‐art open‐source automated radiotracking, this toolset can be used by the scientific community to investigate the activity patterns of small vertebrates with high temporal resolution, even in dense vegetation.

Animals have evolved different cognitive processes to localize crucial resources that are difficult to find. Relevant cognitive processes such as associative learning and spatial memory have commonly been studied in a foraging related context under controlled laboratory conditions. However, in natural environments, animals can use multiple cognitive processes to localize resources. In this field study, we used a pairwise choice experiment and automatic roost monitoring to assess how individually marked, free-ranging Bechstein’s bats belonging to two different colonies use associative learning, spatial memory and social information when localizing suitable day roosts. To our knowledge, this study tests for the first time how associative learning, spatial memory and social information are used in the process of roost localization in bats under the natural conditions. We show that, when searching for new roosts, bats used associative learning to discriminate between suitable and unsuitable roosts. For re-localizing previously occupied roosts, bats used spatial memory rather than associative learning. Moreover, bats significantly improved the localization of suitable unfamiliar roosts and tended to increase their accuracy to re-localize previously occupied day roosts using social information. Our field experiments suggest that Bechstein’s bats make hierarchical use of different cognitive processes when localizing day roosts. More generally, our study underlines that evaluating different cues under natural conditions is fundamental to understanding how natural selection has shaped the cognitive processes used for localizing resources.

ContextHabitat suitability models (HSM) have been used to understand the impacts of landscape-scale habitat connectivity and gene flow mostly by assuming a regular decrease in the cost of movement as habitat improves. Yet, habitat selection and gene flow are governed by different behavioural processes which may limit the reliability of this approach as individuals are likely to disperse through unsuitable habitat for breeding.ObjectivesThe aim of this study was to identify the optimal relationship between gene flow and HSMs for two bat species (Myotis bechsteinii and Eptesicus serotinus) in Britain by testing a range of nonlinear negative exponential functions for the transformation of HSMs into resistance surfaces.MethodsWe modelled habitat suitability using a hierarchical, multi-level approach that integrates models across three nested levels. Then, we measured the relationship between published genetics data of both species and six negative exponential transformations of the predicted outputs.ResultsThe two most extreme transformations provided the best fit to genetic data for both M. bechsteinii (c = 32; R2 = 0.87) and E. serotinus (c = 16; R2 = 0.42). The negative linear transformations had the poorest fit.ConclusionsThese results suggest that bats are able to disperse through areas of poor habitat for breeding, but will avoid the most unsuitable areas. We recommend comparing multiple transformations of HSMs at different resolutions to gain a more accurate representation of gene flow across heterogeneous landscapes and to inform cost-effective, targeted management.

During late summer and early autumn, temperate bats migrate from their summering sites to swarming sites, where mating likely occurs. However, the extent to which individuals of a single summering site migrate to the same swarming site, and vice versa, is not known. We examined the migratory connectivity between summering and swarming sites in two temperate, North American, bat species, the little brown bat (Myotis lucifugus) and the northern long-eared bat (Myotis septentrionalis). Using mitochondrial and microsatellite DNA markers, we examined population structuring within and among summering and swarming sites. Both species exhibited moderate degrees of mitochondrial DNA differentiation (little brown bat: FST(SUMMER) = 0.093, FST(SWARMING) = 0.052; northern long-eared bat: FST(SUMMER) = 0.117, FST(SWARMING) = 0.043) and little microsatellite DNA differentiation among summering and among swarming sites[corrected]. Haplotype diversity was significantly higher at swarming sites than summering sites, supporting the idea that swarming sites are comprised of individuals from various summering sites. Further, pairwise analyses suggest that swarming sites are not necessarily comprised of only individuals from the most proximal summering colonies.

In response to the pressing challenges of the ongoing biodiversity crisis, the protection of endangered species and their habitats, as well as the monitoring of invasive species are crucial. Habitat suitability modeling (HSM) is often treated as the silver bullet to address these challenges, commonly relying on generic variables sourced from widely available datasets. However, for species with high habitat requirements, or for modeling the suitability of habitats within the geographic range of a species, variables at a coarse level of detail may fall short. Consequently, there is potential value in considering the incorporation of more targeted data, which may extend beyond readily available land cover and climate datasets. In this study, we investigate the impact of incorporating targeted land cover variables (specifically tree species composition) and vertical structure information (derived from LiDAR data) on HSM outcomes for three forest specialist bat species (Barbastella barbastellus, Myotis bechsteinii, and Plecotus auritus) in Rhineland‐Palatinate, Germany, compared to commonly utilized environmental variables, such as generic land‐cover classifications (e.g., Corine Land Cover) and climate variables (e.g., Bioclim). The integration of targeted variables enhanced the performance of habitat suitability models for all three bat species. Furthermore, our results showed a high difference in the distribution maps that resulted from using different levels of detail in environmental variables. This underscores the importance of making the effort to generate the appropriate variables, rather than simply relying on commonly used ones, and the necessity of exercising caution when using habitat models as a tool to inform conservation strategies and spatial planning efforts. Traditional habitat suitability models, relying on variables with coarse level of detail, may inadequately represent the complexities of specialized species. This study shows that habitat suitability modeling for forest specialist bat species can be improved by integrating more targeted data, such as tree species classification map and LiDAR‐derived vertical structure information. Furthermore, the results show a high difference in resulting distribution maps when using different levels of detail in environmental predictors, which underscores the importance of exercising caution when using habitat models as a tool to inform conservation strategies and spatial planning efforts.