Issue 6.9 is now online!
This month’s issue contains one Applications article and two Open Access articles, all of which are freely available.
– POPART: An integrated software package that provides a comprehensive implementation of haplotype network methods, phylogeographic visualisation tools and standard statistical tests, together with publication-ready figure production. The package also provides a platform for the implementation and distribution of new network-based methods.
Michalis Vardakis et al. provide this month’s first Open Access article. In ‘Discrete choice modelling of natal dispersal: ‘Choosing’ where to breed from a finite set of available areas‘ the authors show how the dispersal discrete choice model can be used for analysing natal dispersal data in patchy environments given that the natal and the breeding area of the disperser are observed. This model can be used for any species or system that uses some form of discrete breeding location or a certain degree of discretization can be applied.
This issue also contains an article which was accompanied by one of our most popular blog posts this year. In ‘Comparing methods to separate components of beta diversity‘ Andrés Baselga and Fabien Laprieur conduct a systematic comparison of parallel components in the BAS and POD frameworks for partitioning compositional dissimilarity into replacement and nestedness-resultant component or into replacement and richness-difference components. In the related blog post, Dr Baselga answers the question ‘What is Beta Diversity?‘
This month’s cover image shows a bumblebee (Bombus sp.) on a flower in Princeton, New Jersey (US). Simulation studies have suggested that to achieve enough statistical power to detect community-wide declines and/or positive responses to agri-environment remedies, large-scale monitoring programmes for bees will require identifying at least hundreds of thousands of bees to species level. Morphology-based taxonomy is infeasible at this scale, and amplicon-based methods (‘metabarcoding’) are prone to false positives and negatives, as well as being unable to provide estimates of species biomass or counts.
In the related article, ‘High-throughput monitoring of wild bee diversity and abundance via mitogenomics‘, Tang et al. apply metagenomic methods to the assessment of bee biodiversity. It is now feasible to assemble hundreds of mitochondrial genomes from insect species, allowing the efficient creation of comprehensive reference databases. As a result, mass bee samples can be shotgun sequenced on high-throughput Illumina sequencers, and the resulting reads mapped to reference mitogenomes. Tang et al.’s pilot study shows that species detection is highly reliable, even for morphologically cryptic species. Moreover, read frequencies are correlated with estimated bee species biomasses, allowing estimates of species counts via a combination of occupancy across traps and estimated biomasses within traps. Mitogenomic methods for biodiversity assessment can be straightforwardly scaled up to hundreds of taxa or more per sample (e.g. ‘all pollinating insects + parasites’) by building up reference databases and increasing sequencing depth.
This article has also received some media attention following a press release. You may have seen it reported in a number of media outlets, including Yahoo! News, the Irish Independent, Phys.org and many more
Photo © Xin Zhou