Bacterial community associated to the pine wilt disease insect vectors Monochamus galloprovincialis and Monochamus alternatus

Monochamus beetles are the dispersing vectors of the nematode Bursaphelenchus xylophilus, the causative agent of pine wilt disease (PWD). PWD inflicts significant damages in Eurasian pine forests. Symbiotic microorganisms have a large influence in insect survival. The aim of this study was to characterize the bacterial community associated to PWD vectors in Europe and East Asia using a culture-independent approach. Twenty-three Monochamus galloprovincialiswere collected in Portugal (two different locations); twelve Monochamus alternatus were collected in Japan. DNA was extracted from the insects’ tracheas for 16S rDNA analysis through denaturing gradient gel electrophoresis and barcoded pyrosequencing. Enterobacteriales, Pseudomonadales, Vibrionales and Oceanospirilales were present in all samples. Enterobacteriaceae was represented by 52.2% of the total number of reads. Twenty-three OTUs were present in all locations. Significant differences existed between the microbiomes of the two insect species while for M. galloprovincialis there were no significant differences between samples from different Portuguese locations. This study presents a detailed description of the bacterial community colonizing the Monochamus insects’ tracheas. Several of the identified bacterial groups were described previously in association with pine trees and B. xylophilus, and their previously described functions suggest that they may play a relevant role in PWD.

Generalities of vertebrate responses to landscape composition and configuration gradients in a highly heterogeneous Mediterranean region

Aim To examine the distributional patterns of vertebrates (including birds, bats, carnivores and lagomorphs) along landscape composition and configuration gradients to better understand the effects of landscape modification on occurrence patterns at both species and community level. Location The region of Alentejo, a forest-dominated area of southern Portugal. Methods The study area was framed using 1647 hexagonal plots, each of 259 ha in size. Composition and configuration gradients were obtained for each plot by integrating the proportions of the main land cover types and their configuration patterns using multivariate analyses. Species-specific vertebrate responses were investigated using data from 75 plots in which carnivores, bats and lagomorphs were sampled, and from 135 plots in the case of birds. Community- level responses were investigated through changes in species richness and beta-diversity in 57 plots where all vertebrate groups were simultaneously sampled. At the species-level, an information-theoretic approach was used to determine the effects of landscape gradients on species’ responses. At the community level, Mantel tests were used to determine between-plot differences in species composition using the Sørensen dissimilarity index. Results We found that the occurrence patterns of most vertebrate species were best predicted by composition-related gradients, although configuration gradients were also frequently included in species-specific occurrence models. We also found a weak correlation between species richness and most landscape gradients suggesting a turnover in the identity of species, something that was corroborated by the stronger correlation between environmental gradients and beta-diversity measures. The amount of forest cover and landscape complexity (estimated as the heterogeneity in the size and number of land cover types) were the main composition and configuration gradients determining vertebrate responses at both species and community level. Main conclusions Our work contributes to a more refined understanding of the mechanisms underlying species distributional patterns in real-world human-modified landscapes. By uncovering generalities of species with multiple ecological requirements and by describing the entire landscape mosaic through landscape gradients, we also suggest that our work greatly helps to fill the gap between existing conceptual landscape models aimed to understand species distributional patterns in human-modified landscapes.