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Composition of landscape impacts the distribution of the main vectors of Xylella fastidiosa in southern Spain
Author(s) -
Godefroid Martin,
Durán José M.
Publication year - 2022
Publication title -
journal of applied entomology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.795
H-Index - 60
eISSN - 1439-0418
pISSN - 0931-2048
DOI - 10.1111/jen.13003
Subject(s) - xylella fastidiosa , biology , ecology , vegetation (pathology) , mediterranean climate , medicine , genetics , pathology , bacteria
The bacterium Xylella fastidiosa ( Xf ) is a harmful insect‐borne plant pathogen that causes severe diseases to major agricultural crops and many forest, ornamental and uncultivated plants. The pathogen, native to the Americas, has recently been detected in Europe, where it causes huge agricultural losses. The effect of landscape composition on the distribution of the vectors of the bacterium in Europe remains little explored. The present study aims at identifying how landscape composition impacts the distribution of the spittlebugs Philaenus spumarius and Neophilaenus campestris , which can carry and transmit the pathogen to plants and are considered to be the main vectors of Xf in the Mediterranean region. During the period 2015–2018, we thoroughly sampled the distribution of both species in the southwest of Iberian Peninsula. We characterized landscape composition in the sampling area by computing landscape metrics and fitted multivariate analyses and species distribution models (SDMs) to investigate spittlebugs’ response to climate and landscape structure. High densities of Mediterranean agro‐forestry systems (named “ dehesas ” in Spanish), sclerophyllous vegetation and broad‐leaved forests in the landscape, were positively associated with the presence of P . spumarius . Conversely, the high density of coniferous vegetation in the landscape was positively associated with the occurrence of N . campestris . For P . spumarius , SDMs accounting for ecologically relevant landscape descriptors yielded better predictive accuracy than models relying on climate only. These results highlight the importance of considering landscape information when modelling pests’ distributions and provide practical information to design landscape‐informed monitoring plans to prevent the spread of Xf in Europe.