9 research outputs found

    Global invasion history of the agricultural pest butterfly revealed with genomics and citizen science.

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    The small cabbage white butterfly, , is a major agricultural pest of cruciferous crops and has been introduced to every continent except South America and Antarctica as a result of human activities. In an effort to reconstruct the near-global invasion history of , we developed a citizen science project, the "Pieris Project," and successfully amassed thousands of specimens from 32 countries worldwide. We then generated and analyzed nuclear (double-digest restriction site-associated DNA fragment procedure [ddRAD]) and mitochondrial DNA sequence data for these samples to reconstruct and compare different global invasion history scenarios. Our results bolster historical accounts of the global spread and timing of introductions. We provide molecular evidence supporting the hypothesis that the ongoing divergence of the European and Asian subspecies of (∼1,200 y B.P.) coincides with the diversification of brassicaceous crops and the development of human trade routes such as the Silk Route (Silk Road). The further spread of over the last ∼160 y was facilitated by human movement and trade, resulting in an almost linear series of at least 4 founding events, with each introduced population going through a severe bottleneck and serving as the source for the next introduction. Management efforts of this agricultural pest may need to consider the current existence of multiple genetically distinct populations. Finally, the international success of the Pieris Project demonstrates the power of the public to aid scientists in collections-based research addressing important questions in invasion biology, and in ecology and evolutionary biology more broadly

    Species with more volatile population dynamics are differentially impacted by weather.

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    Climatic variation has been invoked as an explanation of population dynamics for a variety of taxa. Much work investigating the link between climatic forcings and population fluctuation uses single-taxon case studies. Here, we conduct comparative analyses of a multi-decadal dataset describing population dynamics of 50 co-occurring butterfly species at 10 sites in Northern California. Specifically, we explore the potential commonality of response to weather among species that encompass a gradient of population dynamics via a hierarchical Bayesian modelling framework. Results of this analysis demonstrate that certain weather conditions impact volatile, or irruptive, species differently as compared with relatively stable species. Notably, precipitation-related variables, including indices of the El Niño Southern Oscillation, have a more pronounced impact on the most volatile species. We hypothesize that these variables influence vegetation resource availability, and thus indirectly influence population dynamics of volatile taxa. As one of the first studies to show a common influence of weather among taxa with similar population dynamics, the results presented here suggest new lines of research in the field of biotic-abiotic interactions

    Species with more volatile population dynamics are differentially impacted by weather

    No full text
    Climatic variation has been invoked as an explanation of population dynamics for a variety of taxa. Much work investigating the link between climatic forcings and population fluctuation uses single-taxon case studies. Here, we conduct comparative analyses of a multi-decadal dataset describing population dynamics of 50 co-occurring butterfly species at 10 sites in Northern California. Specifically, we explore the potential commonality of response to weather among species that encompass a gradient of population dynamics via a hierarchical Bayesian modelling framework. Results of this analysis demonstrate that certain weather conditions impact volatile, or irruptive, species differently as compared with relatively stable species. Notably, precipitation-related variables, including indices of the El Niño Southern Oscillation, have a more pronounced impact on the most volatile species. We hypothesize that these variables influence vegetation resource availability, and thus indirectly influence population dynamics of volatile taxa. As one of the first studies to show a common influence of weather among taxa with similar population dynamics, the results presented here suggest new lines of research in the field of biotic–abiotic interactions

    Understanding a migratory species in a changing world: climatic effects and demographic declines in the western monarch revealed by four decades of intensive monitoring

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    Migratory animals pose unique challenges for conservation biologists, and we have much to learn about how migratory species respond to drivers of global change. Research has cast doubt on the stability of the eastern monarch butterfly (Danaus plexippus) population in North America, but the western monarchs have not been as intensively examined. Using a Bayesian hierarchical model, sightings of western monarchs over approximately 40 years were investigated using summer flight records from ten sites along an elevational transect in Northern California. Multiple weather variables were examined, including local and regional temperature and precipitation. Population trends from the ten focal sites and a subset of western overwintering sites were compared to summer and overwintering data from the eastern migration. Records showed western overwintering grounds and western breeding grounds had negative trends over time, with declines concentrated early in the breeding season, which were potentially more severe than in the eastern population. Temporal variation in the western monarch also appears to be largely independent of (uncorrelated with) the dynamics in the east. For our focal sites, warmer temperatures had positive effects during winter and spring, and precipitation had a positive effect during spring. These climatic associations add to our understanding of biotic-abiotic interactions in a migratory butterfly, but shifting climatic conditions do not explain the overall, long-term, negative population trajectory observed in our data
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