One of the most difficult interactions to observe in nature is the relationship between a predator and its prey. When direct observations are impossible, we rely on morphological classification of prey remains, although this is particularly challenging among generalist predators whose faeces contain mixed and degraded prey fragments. In this investigation, we used a polymerase chain reaction and sequence-based technique to identify prey fragments in the guano of the generalist insectivore, the eastern red bat (Lasiurus borealis), and evaluate several hypotheses about prey selection and prey defences. The interaction between bats and insects is of significant evolutionary interest because of the adaptive nature of insect hearing against echolocation. However, measuring the successes of predator tactics or particular prey defences is limited because we cannot normally identify these digested prey fragments beyond order or family. Using a molecular approach, we recovered sequences from 89% of the fragments tested, and through comparison to a reference database of sequences, we were able to identify 127 different species of prey. Our results indicate that despite the robust jaws of L. borealis, most prey taxa were softer-bodied Lepidoptera. Surprisingly, more than 60% of the prey species were tympanate, with ears thought to afford protection against these echolocating bats. Moths of the family Arctiidae, which employ multiple defensive strategies, were not detected as a significant dietary component. Our results provide an unprecedented level of detail for the study of predator-prey relationships in bats and demonstrate the advantages which molecular tools can provide in investigations of complex ecological systems and food-web relationships.

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We employ molecular methods to profile the diet of the little brown bat, Myotis lucifugus, and describe spatial and temporal changes in diet over their maternity season. We identified 61 prey species of insects and 5 species of arachnid. The largest proportion of prey (∼32%) were identified as species of the mass-emerging Ephemeroptera (mayfly) genus Caenis. Bats roosting in agricultural settings had lower dietary richness than those occupying a roost located on a forest fragment in a conservation area. We detected temporal fluctuations in diet over the maternity season. Dipteran (fly) species dominated the diet early in the season, replaced later by species of mayfly. Because our methodology provides species-level identification of prey, we were able to isolate environmental indicator species in the diet and draw conclusions about the location and type of their foraging habitat and the health of these aquatic systems. The species detected suggested that the bats use variable habitats; members of one agricultural roost foraged on insects originating in rivers or streams while those in another agricultural roost and the forest roost fed on insects from pond or lake environments. All source water for prey was of fair to good quality, though no species detected are intolerant of pollution thus the habitat cannot be classified as pristine. Our study outlines a model system to investigate the abiotic and biotic interactions between habitat factors through this simple food chain to the top predator.

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"Swarming" refers to the summer nocturnal flights through hibernacula by the five species of bats known to hibernate locally. A total of 6400 bats was handled during studies of swarming at 10 hibernacula in Ontario and Quebec from 1966 to 1968. Juveniles comprised over 50% of the swarming population, and the proportion of females in this population was greater than that observed in hibernating populations. Two phases of swarming have been distinguished: the first, occurring in August, lacks both sexual activity and a hibernating population, and the second, which begins in September, involves both sexual activity and the buildup of a hibernating population. Possible functions of swarming are discussed.

We analyzed the patterns of habitat use by insectivorous bats in Mexico City, one of the largest and most populated cities of the world. We tested the hypotheses that richer patches of food, expected in more vegetated areas, have higher bat activity levels, and that fast-flying species benefit most from urbanization. We compared activity of insectivorous species and relative abundance of insects in 5 habitats (large parks, small parks, illuminated open areas, residential areas, and natural forest). Sampling of bat activity and insects was conducted every 2 weeks in 12 sites per habitat during summer 2002. Measures of bat activity were based on 3,600 oneminute sequences of sound that were recorded and analyzed. The average number of taxa per site was significantly higher in the natural forest than in urban habitats, but overall bat activity was significantly higher in large parks and illuminated open areas than in small parks, residential areas and natural forest. Vespertilionid bats (Eptesicus fuscus, Myotis, and an unidentified species), along with Eumops perotis, occurred almost exclusively in extensive green areas (large parks or natural forest). The molossid Nyctinomops macrotis made the broadest use of the urban-natural mosaic, whereas Tadarida brasiliensis used urban sites (illuminated areas and large parks) more intensively. Insect abundance was higher in large parks and natural forest, and it was significantly correlated with overall bat activity and with the number of taxa recorded per site. The observed patterns of habitat use and foraging can be explained by considering the flight and echolocation performance of species. Although some species successfully exploited highly urbanized sites, large areas with vegetation are needed to maintain the most diverse insectivorous bat fauna in Mexico City.

Generalist species with numerous food web interactions are thought to provide stability to ecosystem dynamics; however, it is not always clear whether habitat generality translates into dietary diversity. Big brown bats are common across North America and employ a flexible foraging strategy over water, dense forests, forest edges and rural and urban settings. Despite this generalist use of habitat, they are paradoxically characterized as beetle specialists. However, hard carapaces may preferentially survive digestion leading to over-representation during morphological analysis of diet. This specialization has not been evaluated independently using molecular analysis and species-level identification of prey. We used next-generation sequencing to assess the diet of big brown bats. Beetles were consumed in the highest frequency but Lepidoptera species richness was highest among identified prey. The consumption of species showed strong seasonal and annual variation. While Coleoptera consumption varied, Lepidoptera and Ephemeroptera were relatively constant dietary components. Dietary diversity increased in late summer when insect diversity decreases. Our results indicate that big brown bats are dietary generalists and, while beetles are an important component of the diet, Lepidoptera are equally important, and Lepidoptera and Ephemeroptera are the only stable prey resource exploited. As resources become limited, big brown bats may respond by increasing the species richness of prey and thus their connectedness in the ecosystem. This characterization of diet corresponds well with a generalist approach to foraging, making them an important species in encouraging and maintaining ecosystem stability.

Summary1. The probability of detecting the echolocation calls of bats is affected by the strength of the signal as well as the directionality and frequency response of the acoustic detectors. Regardless of the research question, it is important to quantify variation in recording system performance and its impacts on bat detection results. The purpose of this study was to compare the detection of echolocation calls among five commonly used bat detectors: AnaBat SD2 (Titley Scientific), Avisoft UltraSoundGate 116 CM16/CMPA (Avisoft Bioacoustics), Batcorder 2Á0 (ecoObs), Batlogger (Elekon AG) and Song Meter SM2BAT (Wildlife Acoustics). 2. We used playback of synthetic calls to optimize detection settings for each system. We then played synthetic signals at four frequencies (25, 55, 85 and 115 kHz) at 5-m intervals (5-40 m) and three angles (0°, 45°, 90°) from the detectors. Finally, we recorded free-flying bats (Lasiurus cinereus), comparing the number of calls detected by each detector. 3. Detection was most affected by the frequency dominating the signal and the distance from the source. The effect of angle was less apparent. In the synthetic signal experiment, Avisoft and Batlogger outperformed other detectors, while Batcorder and Song Meter performed similarly. Batlogger performed better than the other detectors at angles off-centre (45°and 90°). AnaBat detected the fewest signals and none at 85 kHz or 115 kHz. Avisoft detected the most signals. In the free-flying bat experiment, Batlogger recorded 93% of calls relative to Avisoft, while AnaBat, Batcorder and Song Meter recorded 40-50% of the calls detected by Avisoft. 4. Numerous factors contribute to variation in data sets from acoustic monitoring; our results demonstrate that choice of detector plays a role in this variation. Differences among detectors make it difficult to compare data sets obtained with different systems. Therefore, the choice of detector should be taken into account in designing studies and considering bat activity levels among studies using different detectors.