Population genetic structure of the Australian caddisfly Lectrides varians Mosely (Trichoptera: Leptoceridae) and the identification of cryptic species in south-eastern Australia

Lectrides varians (Mosely) is a large, ecologically-important, caddisfly found in perennial and intermittent streams throughout much of eastern Australia. We conducted a population genetic analysis to investigate the dispersal potential of L. varians, building on previous works that have assessed life-history traits associated with drought resistance. Genetic analyses of L. varians from the Grampians region of Victoria, based on mitochondrial DNA sequence data, revealed extensive gene flow and a lack of genetic structure across the sample range (ΦST = 0.04). This suggests that the species is a strong disperser and is likely to be resilient to increased drying and habitat fragmentation under climate change considering other known resistance traits. However, during this study, two divergent genotypes were identified, indicating a potential species complex. A comprehensive phylogenetic analysis of L. varians across its current range was subsequently performed, confirming the species is indeed paraphyletic, consisting of one lineage that is restricted to the Grampians National Park and the other being widespread throughout south-eastern Australia. Further analyses revealed consistent morphological differences between these lineages supporting the notion that L. varians is a species complex. We discuss the implications of these findings with regard to conservation and taxonomy of this important invertebrate group.

Big data sensing and service: a tutorial

As the advance of the Internet of Things (IoT), more M2M sensors and devices are connected to the Internet. These sensors and devices generate sensor-based big data and bring new business opportunities and demands for creating and developing sensor-oriented big data infrastructures, platforms and analytics service applications. Big data sensing is becoming a new concept and next technology trend based on a connected sensor world because of IoT. It brings a strong impact on many sensor-oriented applications, including smart city, disaster control and monitor, healthcare services, and environment protection and climate change study. This paper is written as a tutorial paper by providing the informative concepts and taxonomy on big data sensing and services. The paper not only discusses the motivation, research scope, and features of big data sensing and services, but also exams the required services in big data sensing based on the state-of-the-art research work. Moreover, the paper discusses big data sensing challenges, issues, and needs.