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Since about the year 2000 a hitherto unidentified species of the genus Leiobunum C. L. Koch, 1839, has rapidly invaded central and western Europe. Records are known from The Netherlands (probably the country of first occurrence in Europe), Germany, Austria and Switzerland. This introduced species, until now, mainly inhabits walls of buildings and rocky environments. Adults characteristically aggregate during daytime into groups of up to 1.000 individuals. The species is described and details on its present distribution, habitat preference, phenology and behaviour are presented.
During three field trips in 2009-2010 to Xuan Son National Park in Phu Tho province in northern Vietnam, a total of 13 species of damselflies of the superfamily Calo-pterygoidea were recorded. These records are documented here with field photo-graphs of living damselflies. Observations on their biology and behaviour are also noted. Three of the species are reported from Vietnam for the first time: Rhinocypha arguta, an undescribed Matrona species and Vestalaria miao. The last species was first found in Huu Lien Nature Reserve in Lang Son province in June 2008.
he 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.
During three field trips in 2006 and 2010 to Cuc Phuong National Park in northern Vietnam, a total of 19 anisopteran taxa was recorded. The most interesting records are documented here with field photographs of living specimens or collection material. Observations on their biology and behaviour are also noted.