Unlocking the potential of historical abundance datasets to study biomass change in flying insects

Asynchrony in terrestrial insect abundance corresponds with species traits

Asynchrony in population abundance can buffer the effects of environmental change leading to greater community and ecosystem stability. Both environmental (abiotic) drivers and species functional (biotic) traits can influence population dynamics leading to asynchrony. However, empirical evidence linking dissimilarity in species traits to abundance asynchrony is limited, especially for understudied taxa such as insects. To fill this knowledge gap, we explored the relationship between pairwise species trait dissimilarity and asynchrony in interannual abundance change between pairs of species for 422 moth, butterfly, and bumblebee species in Great Britain. We also explored patterns differentiating traits that we assumed to capture 'sensitivity to environmental variables' (such as body mass), and traits that may reflect 'diversity in exposure' to environmental conditions and lead to niche partitioning (for example, habitat uses, and intra-annual emergence periods). As expected, species trait dissimilarity calculated overall and for many individual traits representing response and exposure was positively correlated with asynchrony in all three insect groups. We found that 'exposure' traits, especially those relating to the phenology of species, had the strongest relationship with abundance asynchrony from all tested traits. Positive relationships were not simply due to shared evolutionary history leading to similar life-history strategies: detected effects remained significant for most traits after accounting for phylogenetic relationships within models. Our results provide empirical support that dissimilarity in traits linked to species exposure and sensitivity to the environment could be important for temporal dissimilarity in insect abundance. Hence, we suggest that general trait diversity, but especially diversity in 'exposure' traits, could play a significant role in the resilience of insect communities to short-term environmental perturbations through driving asynchrony between species abundances.

The development of an unsupervised hierarchical clustering analysis of dual-polarization weather surveillance radar observations to assess nocturnal insect abundance and diversity

Contemporary analyses of insect population trends are based, for the most part, on a large body of heterogeneous and short-term datasets of diurnal species that are representative of limited spatial domains. This makes monitoring changes in insect biomass and biodiversity difficult. What is needed is a method for monitoring that provides a consistent, high-resolution picture of insect populations through time over large areas during day and night. Here, we explore the use of X-band weather surveillance radar (WSR) for the study of local insect populations using a high-quality, multi-week time series of nocturnal moth light trapping data. Specifically, we test the hypotheses that (i) unsupervised data-driven classification algorithms can differentiate meteorological and biological phenomena, (ii) the diversity of the classes of bioscatterers are quantitatively related to the diversity of insects as measured on the ground and (iii) insect abundance measured at ground level can be predicted quantitatively based on dual-polarization Doppler WSR variables. Adapting the quasi-vertical profile analysis method and data clustering techniques developed for the analysis of hydrometeors, we demonstrate that our bioscatterer classification algorithm successfully differentiates bioscatterers from hydrometeors over a large spatial scale and at high temporal resolutions. Furthermore, our results also show a clear relationship between biological and meteorological scatterers and a link between the abundance and diversity of radar-based bioscatterer clusters and that of nocturnal aerial insects. Thus, we demonstrate the potential utility of this approach for landscape scale monitoring of biodiversity.

Moth declines are most severe in broadleaf woodlands despite a net gain in habitat availability

While agricultural intensification and habitat loss are cited as key drivers of moth decline, these alone cannot explain declines observed in UK woodlands - a habitat that has expanded in area since 1968.We quantified how moth communities changed across habitats and regions and determined how species traits interacted with habitat in predicting moth abundance change. We hypothesised that, in woodlands, species more vulnerable to shading and browsing by deer (species specialising on forbs, shrubs and shade-intolerant plants) had declined more severely than other species, and that moth decline in woodlands was more severe at sites more susceptible to deer damage.We modelled abundance, biomass, species richness and diversity from 1968 to 2016 and explored how these interacted with habitat and region. We also modelled the interaction between habitat and two moth species traits: larval feeding guild and shade-tolerance of hostplant.Moth declines were consistently highest in broadleaf woodland. Abundance, biomass, species richness and diversity declined significantly by -51%, -52%, -14% and -15% in woodlands, respectively, compared to national trends of -34%, -39%, -1% (non-significant) and +10%. Declines were no greater in woodlands more susceptible to deer browsing damage. Traits based analysis found no evidence that shading and intensive browsing by deer explained moth declines in woodland.Moth decline was more severe in broadleaf woodlands than in intensively managed farmlands. We found no evidence that deer browsing or increased shading has driven these trends: the primary cause of the decline of moths in woodlands remains unclear.

No pervasive relationship between species size and local abundance trends

Although there is some evidence that larger species could be more prone to population declines, the potential role of size traits in determining changes in community composition has been underexplored in global-scale analyses. Here, we combine a large cross-taxon assemblage time series database (BioTIME) with multiple trait databases to show that there is no clear correlation within communities between size traits and changes in abundance over time, suggesting that there is no consistent tendency for larger species to be doing proportionally better or worse than smaller species at local scales.