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From Nucleotides to Satellite Imagery: Approaches to Identify and Manage the Invasive Pathogen Xylella fastidiosa and Its Insect Vectors in Europe

doi: 10.3390/su12114508
handle: 11588/833754 , 20.500.14243/470296 , 11392/2425360
Biological invasions represent some of the most severe threats to local communities and ecosystems. Among invasive species, the vector-borne pathogen Xylella fastidiosa is responsible for a wide variety of plant diseases and has profound environmental, social and economic impacts. Once restricted to the Americas, it has recently invaded Europe, where multiple dramatic outbreaks have highlighted critical challenges for its management. Here, we review the most recent advances on the identification, distribution and management of X. fastidiosa and its insect vectors in Europe through genetic and spatial ecology methodologies. We underline the most important theoretical and technological gaps that remain to be bridged. Challenges and future research directions are discussed in the light of improving our understanding of this invasive species, its vectors and host–pathogen interactions. We highlight the need of including different, complimentary outlooks in integrated frameworks to substantially improve our knowledge on invasive processes and optimize resources allocation. We provide an overview of genetic, spatial ecology and integrated approaches that will aid successful and sustainable management of one of the most dangerous threats to European agriculture and ecosystems.
- University Federico II of Naples Italy
- John Innes Centre United Kingdom
- Norwich Research Park United Kingdom
- University of Ferrara Italy
- University of Pavia Italy
Epidemiology, TJ807-830, TD194-195, Genetic diversity, Renewable energy sources, genomic, Ecological niche model; Epidemiology; Genetic diversity; Genomic; GIS; Insect vector; Remote sensing; Spatially explicit model; Whole genome sequencing; Xylella fastidiosa, GE1-350, ecological niche model, Xylella fastidiosa, Environmental effects of industries and plants, ecological niche model, epidemiology, genetic diversity, genomic, GIS, insect vector, remote sensing, spatially explicit model, whole genome sequencing, Xylella fastidiosa, genetic diversity, Remote sensing, GIS, Environmental sciences, Ecological niche model, Insect vector, Whole genome sequencing, insect vector, Genomic, epidemiology, Spatially explicit model
Epidemiology, TJ807-830, TD194-195, Genetic diversity, Renewable energy sources, genomic, Ecological niche model; Epidemiology; Genetic diversity; Genomic; GIS; Insect vector; Remote sensing; Spatially explicit model; Whole genome sequencing; Xylella fastidiosa, GE1-350, ecological niche model, Xylella fastidiosa, Environmental effects of industries and plants, ecological niche model, epidemiology, genetic diversity, genomic, GIS, insect vector, remote sensing, spatially explicit model, whole genome sequencing, Xylella fastidiosa, genetic diversity, Remote sensing, GIS, Environmental sciences, Ecological niche model, Insect vector, Whole genome sequencing, insect vector, Genomic, epidemiology, Spatially explicit model
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).75 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 1%
