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Trait-based analyses explaining the different responses of species and communities to environmental changes are increasing in frequency. European butterflies are an indicator group that responds rapidly to environmental changes with extensive citizen science contributions to documenting changes of abundance and distribution. Species traits have been used to explain long- and short-term responses to climate, land-use and vegetation changes. Studies are often characterised by limited trait sets being used, with risks that the relative roles of different traits are not fully explored. Butterfly trait information is dispersed amongst various sources and descriptions sometimes differ between sources. We have therefore drawn together multiple information sets to provide a comprehensive trait database covering 542 taxa and 25 traits described by 217 variables and sub-states of the butterflies of Europe and Maghreb (northwest Africa) which should serve for improved trait-based ecological, conservation-related, phylogeographic and evolutionary studies of this group of insects. We provide this data in two forms; the basic data and as processed continuous and multinomial data, to enhance its potential usage.

Understanding the dynamics of biodiversity, including the spatial distribution of genetic diversity, is critical for predicting responses to environmental changes, as well as for effective conservation measures. This task requires tracking changes in biodiversity at large spatial scales and correlating with species functional traits. We provide three comprehensive resources to understand the determinants for mitochondrial DNA differentiation represented by (a) 15,609 COI sequences and (b) 14 traits belonging to 307 butterfly species occurring in Western-Central Europe and (c) the first multi-locus phylogenetic tree of all European butterfly species. By applying phylogenetic regressions we show that mitochondrial DNA spatial differentiation (as measured with G ST , G' ST , D and D ST ) is negatively correlated with species traits determining dispersal capability and colonization ability. Thanks to the high spatial resolution of the COI data, we also provide the first zoogeographic regionalization maps based on intraspecific genetic variation. The overall pattern obtained by averaging the spatial differentiation of all Western-Central European butterflies shows that the paradigm of long-term glacial isolation followed by rapid pulses of post-glacial expansion has been a pervasive phenomenon in European butterflies. The results and the extensive data sets we provide here constitute the basis for genetically-informed conservation plans for a charismatic group in a continent where flying insects are under alarming decline., (© 2019 John Wiley & Sons Ltd.)

We use field observations in two geographic regions within the British Isles and regression and neural network models to examine the relationship between microhabitat use, thoracic temperatures and activity in a widespread lycaenid butterfly, Polyommatus icarus. We also make predictions for future activity under climate change scenarios. Individuals from a univoltine northern population initiated flight with significantly lower thoracic temperatures than individuals from a bivoltine southern population. Activity is dependent on body temperature and neural network models of body temperature are better at predicting body temperature than generalized linear models. Neural network models of activity with a sole input of predicted body temperature (using weather and microclimate variables) are good predictors of observed activity and were better predictors than generalized linear models. By modelling activity under climate change scenarios for 2080 we predict differences in activity in relation to both regional differences of climate change and differing body temperature requirements for activity in different populations. Under average conditions for low-emission scenarios there will be little change in the activity of individuals from central-southern Britain and a reduction in northwest Scotland from 2003 activity levels. Under high-emission scenarios, flight-dependent activity in northwest Scotland will increase the greatest, despite smaller predicted increases in temperature and decreases in cloud cover. We suggest that neural network models are an effective way of predicting future activity in changing climates for microhabitat-specialist butterflies and that regional differences in the thermoregulatory response of populations will have profound effects on how they respond to climate change.

The number of butterfly species present in 22 woods in eastern England was recorded during fortnightly visits between May to October 1978. A total of 26 species was observed. The number of species present was significantly correlated with the area of woodland but not with the area of glades and rides, which provided both larval food plants and adult foraging sites. The number of vagile species, but not the number of poorly vagile species, present was correlated with the area of woodland within 1 km of the study wood, this being a measure of the sources of potential colonizers. It was predicted that a woodland area of about 460 ha would be required to support all the species recorded in the study.

The flight patterns of twenty species of butterflies present in two coniferous woods and one coppiced wood in eastern England were recorded from April to September 1979. The most mobile species were those characteristic of disturbed habitats, with spatially segregated larval and adult habitats, and those butterflies with early successional larval host plants. The least mobile species were those of permanent habitats and those with ubiquitous larval host plants. Flights of poorly vagile species, but not vagile species, were restricted in both coniferous and coppiced woodland, but were shorter in the latter due to the presence of vegetational barriers to flight. Vagile species remained in coppiced areas longer than in areas of coniferous woodland, flights being influenced by the location of larval and adult food resources.