RESUMEN
This is the first description of a betanodavirus infection in the dusky grouper Epinephelus marginatus within the marine protected areas (MPAs) of the Balearic Islands. Histopathology techniques were employed to describe neurological lesions in infected fish. Abnormal swimming, mortality, and neurological lesions were detected in all analysed grouper individuals. Virus particles were observed by means of transmission electron microscopy. Reverse transcription of RNA1 and RNA2 followed by cDNA amplification and sequencing allowed viral classification. Phylogenetic analysis showed the isolates from wild E. marginatus of the Balearic Islands MPAs to be closely related to Dicentrarchus labrax and Mullus barbatus strains from Cyprus and Italy. Although vertical transmission from infected spawners has been described as the major route for nodavirus infection, we point out in this work that horizontal transmission among sub-clinical fishes after migration or commercial import for aquaculture production could play a major role in the spreading of the disease in MPAs.
Asunto(s)
Lubina , Encefalopatías , Enfermedades de los Peces , Nodaviridae , Infecciones por Virus ARN , Animales , Encefalopatías/veterinaria , Italia , Filogenia , Infecciones por Virus ARN/veterinaria , EspañaRESUMEN
BACKGROUND: The yellow-legged hornet (Vespa velutina) is native to Southeast Asia and is an invasive alien species of concern in many countries. More effective management of populations of V. velutina could be achieved through more widespread and intensive monitoring in the field, however current methods are labor intensive and costly. To address this issue, we have assessed the performance of an optical sensor combined with a machine learning model to classify V. velutina and native wasps/hornets and bees. Our aim is to use the results of the present work as a step towards the development of a monitoring solution for V. velutina in the field. RESULTS: We recorded a total 935 flights from three bee species: Apis mellifera, Bombus terrestris and Osmia bicornis; and four wasp/hornet species: Polistes dominula, Vespula germanica, Vespa crabro and V. velutina. The machine learning model achieved an average accuracy for species classification of 80.1 ± 13.9% and 74.5 ± 7.0% for V. velutina. V. crabro had the highest level of misclassification, confused mainly with V. velutina and P. dominula. These results were obtained using a 14-value peak and valley feature derived from the wingbeat power spectral density. CONCLUSION: This study demonstrates that the wingbeat recordings from a flying insect sensor can be used with machine learning methods to differentiate V. velutina from six other Hymenoptera species in the laboratory and this knowledge could be used to help develop a tool for use in integrated invasive alien species management programs. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.
Asunto(s)
Abejas , Control de Plagas , Avispas , Animales , Especies Introducidas , Control de Plagas/métodos , Aprendizaje AutomáticoRESUMEN
Several outbreaks of mosquito-borne diseases have taken place in Europe in recent years. In Spain, both active and passive surveillance have demonstrated that dengue and West Nile viruses are currently circulating, and seven autochthonous dengue cases have been reported in the last 2 yr. The effectiveness of vector control programs largely depends on the accuracy of the taxonomic identification of the species. However, in Spain, identification almost completely relies on the use of morphological keys to characterize the mosquito fauna. This study investigates the congruence between molecular and morphological species boundaries in 13 Spanish mosquito taxa. The Cytochrome c oxidase subunit I (COI) gene region was sequenced from 60 adult specimens collected in Mallorca, plus several representatives from other Spanish regions for comparative purposes. Phylogenetic relationships were established using Bayesian and maximum-likelihood approaches. Using three species delimitation algorithms (ABGD, mPTP, and GMYC), we found strong evidence for cryptic speciation within Anopheles algeriensis Theobald, a widespread mosquito in the Mediterranean basin. We also delimited the Mallorcan rock pool mosquito Aedes mariae (Sergent & Sergent), from mainland European populations. Finally, we found difficulties in the use of wing characters in species keys to distinguish Culiseta annulata (Schrk) from Culiseta subochrea (Edwards). Given that these species are vectors of pathogens of medical relevance and have veterinary importance, their accurate taxonomic identification is essential in European vector surveillance programs.