RESUMO
Determining when animal populations have experienced stress in the past is fundamental to understanding how risk factors drive contemporary and future species' responses to environmental change. For insects, quantifying stress and associating it with environmental factors has been challenging due to a paucity of time-series data and because detectable population-level responses can show varying lag effects. One solution is to leverage historic entomological specimens to detect morphological proxies of stress experienced at the time stressors emerged, allowing us to more accurately determine population responses. Here we studied specimens of four bumblebee species, an invaluable group of insect pollinators, from five museums collected across Britain over the 20th century. We calculated the degree of fluctuating asymmetry (FA; random deviations from bilateral symmetry) between the right and left forewings as a potential proxy of developmental stress. We: (a) investigated whether baseline FA levels vary between species, and how this compares between the first and second half of the century; (b) determined the extent of FA change over the century in the four bumblebee species, and whether this followed a linear or nonlinear trend; (c) tested which annual climatic conditions correlated with increased FA in bumblebees. Species differed in their baseline FA, with FA being higher in the two species that have recently expanded their ranges in Britain. Overall, FA significantly increased over the century but followed a nonlinear trend, with the increase starting c. 1925. We found relatively warm and wet years were associated with higher FA. Collectively our findings show that FA in bumblebees increased over the 20th century and under weather conditions that will likely increase in frequency with climate change. By plotting FA trends and quantifying the contribution of annual climate conditions on past populations, we provide an important step towards improving our understanding of how environmental factors could impact future populations of wild beneficial insects.
Assuntos
Mudança Climática , Museus , Animais , AbelhasRESUMO
Since the classic work of E.B. Ford, explanations for eyespot variation in the Meadow Brown butterfly have focused on the role of genetic polymorphism. The potential role of thermal plasticity in this classic example of natural selection has therefore been overlooked. Here, we use large daily field collections of butterflies from three sites, over multiple years, to examine whether field temperature is correlated with eyespot variation, using the same presence/absence scoring as Ford. We show that higher developmental temperature in the field leads to the disappearance of the spots visible while the butterfly is at rest, explaining the historical observation that hindwing spotting declines across the season. Strikingly, females developing at 11°C have a median of six spots and those developing at 15°C only have three. In contrast, the large forewing eyespot is always present and scales with forewing length. Furthermore, in contrast to the smaller spots, the size of the large forewing spot is best explained by calendar date (days since 1st March) rather than the temperature at pupation. As this large forewing spot is involved in startling predators and/or sexual selection, its constant presence is therefore likely required for defence, whereas the disappearance of the smaller spots over the season may help with female crypsis. We model annual total spot variation with phenological data from the UK and derive predictions as to how spot patterns will continue to change, predicting that female spotting will decrease year on year as our climate warms.
RESUMO
Remote sensing has revolutionised many aspects of ecological research, enabling spatiotemporal data to be collected in an efficient and highly automated manner. The last two decades have seen phenomenal growth in capabilities for high-resolution remote sensing that increasingly offers opportunities to study small, but ecologically important organisms, such as insects. Here we review current applications for using remote sensing within entomological research, highlighting the emerging opportunities that now arise through advances in spatial, temporal and spectral resolution. Remote sensing can be used to map environmental variables, such as habitat, microclimate and light pollution, capturing data on topography, vegetation structure and composition, and luminosity at spatial scales appropriate to insects. Such data can also be used to detect insects indirectly from the influences that they have on the environment, such as feeding damage or nest structures, whilst opportunities for directly detecting insects are also increasingly available. Entomological radar and light detection and ranging (LiDAR), for example, are transforming our understanding of aerial insect abundance and movement ecology, whilst ultra-high spatial resolution drone imagery presents tantalising new opportunities for direct observation. Remote sensing is rapidly developing into a powerful toolkit for entomologists, that we envisage will soon become an integral part of insect science.