Research Article |
Corresponding author: Arturo Cocco ( acocco@uniss.it ) Academic editor: Katelyn Faulkner
© 2024 Andrea Viviano, Arturo Cocco, Paolo Colangelo, Giuseppe Marco Delitala, Roberto Antonio Pantaleoni, Laura Loru.
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation:
Viviano A, Cocco A, Colangelo P, Delitala GM, Pantaleoni RA, Loru L (2024) Worldwide distribution and phylogeography of the agave weevil Scyphophorus acupunctatus (Coleoptera, Dryophthoridae): the rise of an overlooked invasion. NeoBiota 90: 53-78. https://doi.org/10.3897/neobiota.90.101797
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Global plant trade represents one of the main pathways of introduction for invertebrates, including insects, throughout the world. Non-native insects include some of the most important pests affecting cultivated and ornamental plants worldwide. Defining the origins and updating the distribution of non-native invasive species is pivotal to develop effective strategies to limit their spread. The agave weevil, Scyphophorus acupunctatus (Coleoptera, Dryophthoridae), is a curculionid beetle native to Central and North America, although it also occurs in Eurasia, Africa, Oceania and South America as a non-native species. Despite being widespread, the extent of occurrence and origins of European populations of the agave weevil have been overlooked. In the present study, the current and potential worldwide distribution of S. acupunctatus was assessed and an analysis of its genetic diversity in the native and non-native ranges was performed. By analysing occurrences from local phytosanitary bulletins and citizen-science platforms, the agave weevil was confirmed to be widely distributed and to occur on all continents, except Antarctica. Additionally, there is potential for expansion throughout the world, as estimated by species distribution models. Nucleotide and haplotype diversity of the COXI mitochondrial gene (about 650 bp) was lower in the non-native (n = 39 samples) than native populations (n = 26 samples). The majority of introduced individuals belonged to the same haplotype, suggesting that most introductions in Europe might have occurred from a small geographical area in Central America. Constant transboundary monitoring and national laws must be considered to reduce the spread of the agave weevil, given that a bridgehead effect may occur from non-native populations to new suitable areas.
Agave, mitochondrial COXI gene, non-native invasive insects, population genetics, species distribution model
Non-native invasive species are taxa that have been introduced and/or spread into regions outside their native ranges and have subsequently established and spread, affecting local ecosystem dynamics (
Crop pests are widely distributed worldwide due to accidental introductions through the intensive trade of goods, including plants of ornamental and agronomic interest (
The agave weevil is a major pest of agave. Agaves (Asparagaceae, Agavoideae/Agavaceae) include several genera and species that have been introduced worldwide for ornamental purposes (
The taxonomy of the Scyphophorus genus is still unresolved (
The aims of our work were to: (i) update the distribution of the agave weevil in non-native areas with special regard to Mediterranean countries; (ii) determine the climatic suitability throughout the world, with special regard to Europe, where most non-native populations occur and predict its potential distribution; and (iii) assess the phylogeographic pattern of S. acupunctatus and trace the origin of European populations.
The distribution of the agave weevil in its non-native range was updated by searching for published and unpublished records in the grey and scientific literature and online databases, including records collected through citizen-science and validated by experts (i.e. iNaturalist: www.inaturalist.org; GBIF: www.gbif.org DOI: https://doi.org/10.15468/dl.pd22mh; Forum Natura Mediterraneo: www.naturamediterraneo.com; Forum Entomologi Italiani: www.entomologiitaliani.net. All accessed on 15.05.2023). The search for occurrence records was conducted from October 2022 to May 2023. Further searches were performed on free posts with photos on Social Networks (e.g. Facebook) and on video-sharing websites (e.g. YouTube). The literature search was carried out by assessing studies in online databases (i.e. ISI Web of Science, Scopus, Zoological Records and Google Scholar). Search terms included all possible combinations of the words: ‘agave weevil’, ‘Scyphophorus acupunctatus’, ‘distribution’ and ‘non-native species’. The same words were searched in English, French, Spanish, Portuguese and Italian. Maps representing the agave weevil distribution using geographical coordinates were downloaded from the ESRI (https://server.arcgisonline.com) and Eurostat (Countries – GISCO – Eurostat, europa.eu) websites. The distribution of the weevil was mapped using QGIS software version 3.28 Firenze (
The potential worldwide distribution of S. acupunctatus was modelled to identify areas throughout the Globe that are climatically suitable for this weevil. To the best of our knowledge, no previous studies have focused on the climatic preferences of this weevil, despite its high impact on agro-economy and urban parks.
Occurrence records from both the native and non-native ranges were collected, representing the whole realised ecological niche (
Moran’s correlograms were employed to test for the presence of significant spatial autocorrelation (
The Moran’s correlogram is a graphical representation of the spatial autocorrelation coefficient (Moran’s I) at different distance intervals, which helps to identify patterns of spatial dependence and assess whether neighbouring observations are more similar or dissimilar from each other than expected by chance (
In this work, the computed Moran’s Index was 0.03, indicating a slight positive spatial autocorrelation in the dataset. The Z-score, which measures the standard deviation from the expected mean under the assumption of spatial randomness, was 0.18. The associated P-value was 0.86, suggesting that the observed spatial pattern was not significantly different from what would be expected by chance. Overall, these findings suggested the absence of significant spatial clustering or dispersion in the analysed spatial context. The final dataset used in the model consisted of 718 occurrences.
A distance threshold of 10 km was set to define spatial relationships between observations. This threshold represents the maximum distance at which observations are spatially related. The analysis was performed without any specific selection set, meaning that all observations within the study area were included in the analysis. No weight matrix file was used, suggesting that all observations were assumed to have equal influence in the analysis.
Dispersal abilities of Scyphophorus weevils are limited (< 50 metres), as reported by the scientific literature (
In the final analysis, occurrences were filtered by selecting the minimum distance of 10 km between different occurrence points using the “spThin” R package (
The modelling process was started by obtaining 19 climatic variable layers from the Worldclim (version 2.1) website, with a resolution of 2.5 minutes of a degree (
Additionally, the Variance Inflation Factor (VIF) for all selected variables was computed using the “usdm” package in R (
A first comprehensive evaluation was conducted to estimate the performance of nine algorithms through a combination of R packages such as “ENMeval” and “sdm” (
The evaluation encompassed a range of algorithms, namely the Generalised Linear Model (GLM, with a logit-link function), Boosted Regression Trees (BRT, with 15% holdout validation point and bagging fraction set to 0.5:
Species Distribution Models (SDM) were performed using the R packages “biomod2” and “sdm” (
The results of the models were assembled with a weighted average of all predictions from all fitted models (
Model performance was measured using TSS and AUC. For present and future projections, an occurrence probability raster was obtained for each statistical model by calculating the mean of all the projections with a TSS > 0.75 and an AUC > 0.90 (
Then, differences between predictions under future and current climates were obtained using consensus models, by subtracting the average predictions under current climates from those under future climate. Raster cells with positive values indicated a predicted improvement in climatic conditions for S. acupunctatus, whereas raster cells with negative values indicated a decreased climatic suitability for the future. To estimate the uncertainty in the predictions due to disagreements amongst four different algorithms, subtraction per model was performed and the following values were assigned: value -1 was assigned to all cells with negative values of the average single-model predictions; similarly, the value +1 was assigned to all cells with positive values and 0 otherwise (
The consensus of model predictions was obtained by summing the four three-value maps (-1, 0, 1). A raster map was obtained with values ranging between -4 and +4, with extreme values suggesting that all the four statistical models predicted a decrease (-4) or an increase (+4) in the probability of occurrence, whereas intermediate values indicated a partial (±2; ±3) or high disagreement (-1 to +1) amongst the predictions of the algorithms (Suppl. material
The potential non-analogue climate was checked using a Multivariate Environmental Similarity Surface (MESS) analysis (
A total of 32 individual samples of S. acupunctatus were collected in Europe and preserved in 95% ethanol at -20 °C, before genetic analyses. Four other sequences from Liguria (surrounding of Pallanca and Hanbury Botanical Gardens, located in Bordighera and Ventimiglia, respectively, Imperia Province, NW Italy) were already available in CNR-IRET and CREA-DC unpublished collections (Table
Location of the 32 sampling sites for Scyphophorus acupunctatus in Europe. Coordinates are expressed in UTM WGS84.
Sample ID | Location of origin | Country | Latitude (°N) / Longitude (°E) |
---|---|---|---|
S1 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.04893°N, 8.93734°E |
S2 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.04588°N, 8.93496°E |
S3 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.04454°N, 8.93399°E |
S4 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.04150°N, 8.92494°E |
S5 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.03500°N, 8.92161°E |
S6 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.03612°N, 8.92197°E |
S7 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.03348°N, 8.91776°E |
S8 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02657°N, 8.89292°E |
S9 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02547°N, 8.89186°E |
S10 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02617°N, 8.89052°E |
S22 | Villamaniscicle coll del Quirc, Girona | Spain | 42.38092°N, 3.07618°E |
S23 | Villamaniscicle coll del Quirc, Girona | Spain | 42.38092°N, 3.07618°E |
S29 | Tamaracciu, Corsica | France | 41.55294°N, 9.31810°E |
S30 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02632°N, 8.88836°E |
S31 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02580°N, 8.88484°E |
S32 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02669°N, 8.88217°E |
S33 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.02668°N, 8.88250°E |
S34 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.01517°N, 8.88777°E |
S35 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.01586°N, 8.88914°E |
S36 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.01103°N, 8.88029°E |
S37 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.01449°N, 8.87612°E |
S38 | Isola Rossa - Costa Paradiso, Sardinia | Italy | 41.05372°N, 8.94518°E |
S44 | La Crau, Var | France | 43.16317°N, 6.09292°E |
S47 | Sperlonga, Latium | Italy | 41.25847°N, 13.43976°E |
S57 | Cittadella Universitaria, Catania, Sicily | Italy | 37.52546°N, 15.07199°E |
S59 | Cittadella Universitaria, Catania, Sicily | Italy | 37.52546°N, 15.07199°E |
S61 | Località Balzi Rossi, Ventimiglia, Liguria | Italy | 43.78361°N, 7.53638°E |
Spal1 | Pallanca Garden, Bordighera, Liguria | Italy | 43.78835°N, 7.68749°E |
Spal2 | Pallanca Garden, Bordighera, Liguria | Italy | 43.78839°N, 7.68736°E |
Shan1 | Hanbury Garden, Ventimiglia, Liguria | Italy | 43.78408°N, 7.55429°E |
Shan2 | Hanbury Garden, Ventimiglia, Liguria | Italy | 43.78445°N, 7.55415°E |
Españ1 | Passeig Maritim de la Barceloneta, Barcelona | Spain | 41.38474°N, 2.19592°E |
Genomic DNA from all samples was extracted using QIAGEN Blood and Tissue kit (Qiagen Inc., USA), following the manufacturer’s protocol. A fragment of the mitochondrial DNA Cytochrome Oxidase I (COXI) was amplified and compared with sequences deposited in the GenBank. COXI was amplified using the primers LCO1490: 5’-GGTCAACAAATCATAAAGATATTGG-3’ and HCO2198: ‘5-TAAACTTCAGGGTGACCAAAAAATCA-3’ (
PCR products were run on a 1.5% agarose gel, then purified (ExoSAP-IT, Amersham Biosciences) and finally sent to BMR Genomics (Padua, Italy) for Sanger sequencing. Electropherograms were visualised with the software Chromas 1.45 (http://www.technelysium.com.au. Accessed on 17.12.2022). The sequences were visually corrected and aligned using ClustalX 2.1 (
Accession numbers of sequences used for the phylogenetic reconstructions of Scyphophorus acupunctatus.
Accession number | Sampling location | Sampling country | Population status | Reference |
---|---|---|---|---|
AY131110 | Not available | Continental USA | Native | Direct submission to GenBank |
AY131122 | Massachusetts | Continental USA | Native | Direct submission to GenBank |
GBCL49633-19 | California | Continental USA | Native | Direct submission to BOLD Systems |
HM433616 | Colorado | Continental USA | Native | Direct submission to GenBank |
KU896920 | Arizona | Continental USA | Native |
|
KU896921 | Arizona | Continental USA | Native |
|
KU896922 | Arizona | Continental USA | Native |
|
KU896923 | Arizona | Continental USA | Native |
|
KU896924 | Arizona | Continental USA | Native |
|
JX134898 | Not available | Mexico | Native |
|
JX134899 | Not available | Mexico | Native |
|
JX134900 | Not available | Mexico | Native |
|
JX134901 | Not available | Mexico | Native |
|
JX134902 | Not available | Mexico | Native |
|
JX134903 | Not available | Mexico | Native |
|
JX134904 | Not available | Mexico | Native |
|
JX134905 | Not available | Mexico | Native |
|
JX134906 | Not available | Mexico | Native |
|
JX134907 | Not available | Mexico | Native |
|
JX134908 | Not available | Mexico | Native |
|
JX134909 | Not available | Mexico | Native |
|
JX134910 | Not available | Mexico | Native |
|
ASSCR6360-12 | Not available | Costa Rica | Most likely native | Direct submission to BOLD Systems |
ASSCR6362-12 | Not available | Costa Rica | Most likely native | Direct submission to BOLD Systems |
KU896927 | Not available | Guatemala | Most likely native |
|
KU896929 | Not available | Guatemala | Most likely native |
|
OQ198464 | La Crau | Continental France | Non-native | Present work |
OQ198455 | Corsica | France | Non-native | Present work |
OQ193159 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193160 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193161 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193162 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193165 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193176 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ193177 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194007 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194008 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194015 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194016 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ198466 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194025 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194031 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194033 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ198456 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ198458 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ198459 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ198460 | Isola Rossa – Costa Paradiso, Sardinia | Italy | Non-native | Present work |
OQ194017 | Balzi Rossi, Ventimiglia, Liguria | Italy | Non-native | Present work |
OQ198461 | Pallanca Gardens, Liguria | Italy | Non-native | Present work |
OQ198457 | Pallanca Gardens, Liguria | Italy | Non-native | Present work |
OQ193174 | Hanbury Gardens, Liguria | Italy | Non-native | Present work |
OQ198462 | Hanbury Gardens, Liguria | Italy | Non-native | Present work |
OQ194018 | Catania, Sicily | Italy | Non-native | Present work |
OQ194019 | Catania, Sicily | Italy | Non-native | Present work |
OQ198463 | Sperlonga, Latium | Italy | Non-native | Present work |
OQ193157 | Villamaniscicle | Spain | Non-native | Present work |
OQ193158 | Villamaniscicle | Spain | Non-native | Present work |
OQ193175 | Passeig Maritim de la Barceloneta, Barcelona | Spain | Non-native | Present work |
MW520550 | Porto Santo | Portugal | Non-native |
|
HM433615 | Not available | Virgin Islands | Non-native | Direct submission to GenBank |
KU896925 | Not available | Virgin Islands | Non-native |
|
KU896926 | Not available | Virgin Islands | Non-native |
|
KU896928 | Not available | Virgin Islands | Non-native |
|
KU896931 | Not available | Virgin Islands | Non-native |
|
KU896932 | Not available | Virgin Islands | Non-native |
|
The phylogenetic reconstruction was conducted by applying Neighbour Joining (NJ), Bayesian Inference (BI) and Maximum Likelihood (ML) methods. The Kimura-2-parameters nucleotide substitution model was selected by jModelTest 2 (
Overall, the agave weevil was reported on all continents, except for Antarctica. Based on genetic analyses and literature, the native range of this species includes the USA, Mexico and, most likely, the rest of continental Central America (
a Worldwide distribution of Scyphophorus acupunctatus in both native (central and southern North America) and non-native ranges (n = 1135 occurrences) b distribution of S. acupunctatus in southern European Countries (orange dots refer to occurrence sites of agave weevil). The white dotted line includes occurrences from the native range, whereas the solid red line includes occurrences of uncertain origin. Occurrences outside dotted lines are non-native populations. Sources: Data SIO, NOAA, US Navy, NGA, GEBCO 2016 TerraMetrics 2016 Google; Wikimedia Commons, user Norman Einstein, CC-BY-SA-3.0.
Projections of each statistical model (Suppl. material
a Current potential distribution of Scyphophorus acupunctatus worldwide (suitability increasing from pink to black) b future potential distribution of S. acupunctatus under climate projections using the global climate model for 2070 (suitability increasing from pink to black) c differences between future and present conditions [future-current] for the RCP 2.6 scenario obtained by subtracting, for each cell, the predicted suitability under current climate from that under future climates. Pink to black: increase in climatic suitability in the future d consensus change for RCP 2.6 scenario. Dark blue (+4) indicates that all models predicted an increase in suitability, whereas dark orange (-4) indicates a full agreement in predicting a decrease in suitability; white indicates disagreement across models (0 value).
Considering future climate scenarios forecast for 2070, the areas suitable for S. acupunctatus would increase especially towards temperate-cold latitudes, both in Europe and worldwide (Fig.
Values representing the degree of climatic similarity between future and present conditions are shown in Fig.
The MESS analysis showed that the projection area shared a medium to high environmental similarity with many countries in the training area, except for a few northern Eurasian areas (Suppl. material
The COXI sequences were obtained from all analysed samples. All sequences generated in the present study were deposited in GenBank (Table
Indices of genetic diversity for native and most-likely native (n = 26 samples) and non-native (n = 39 samples) populations of Scyphophorus acupunctatus (cf. Table
Total | Native and most-likely native populations | Alien populations | |
---|---|---|---|
π (nucleotide diversity index ± standard deviation) | 0.22 ± 0.05 | 0.59 ± 0.05 | 0.03 ± 0.01 |
h (haplotype diversity index ± standard deviation) | 0.42 ± 0.15 | 0.61 ± 0.19 | 0.09 ± 0.01 |
Number of segregating sites | 170 | 161 | 115 |
Number of Parsimony Informative sites | 154 | 148 | 71 |
An ML tree is presented in Fig.
Maximum Likelihood (ML) phylogenetic tree obtained from the analysis of COXI for 65 individuals of Scyphophorus acupunctatus (n = 39 from non-native range, n = 22 from native range, n = 4 from most-likely native range, cf. Table
The TCS network highlighted that the majority of introduced individuals in Sardinia, Sicily, Corsica, continental Italy (Latium and Liguria), continental France, Spain and Portugal belonged to the same haplotype, as in Costa Rica and Guatemala (Fig.
This study showed for the first time the actual and potential global distribution of the agave weevil, both in the native and non-native ranges and assessed the phylogenetic relationships between native and non-native populations at the global scale.
The presence of this species was confirmed in several countries, whereas some of those listed in CABI’s overview of invasive species (the Netherlands, UK, Israel, New Zealand and Argentina:
Despite being reported as the most important pest for agave species (
The presence of the agave weevil in other Italian peninsular regions along the coastline (e.g. Molise, Abruzzo, Marche, Emilia Romagna and Veneto) cannot be ruled out. Thus, a focused monitoring programme is required, particularly in late spring and during the daytime, when most observations occur (
Species distribution modelling showed a high climatic suitability for this species throughout the Mediterranean Basin, potentially increasing with increasing temperature and decreasing precipitation, i.e. with the ongoing climatic change. Accordingly, the native range of S. acupunctatus currently includes mostly dry areas of Central America, also suggesting the adaptation of this insect to hot desert areas (including mountainous ones), where most Agavaceae, i.e. succulent plants representing the staple of its diet and reproductive sites, grow. The distribution of S. acupunctatus in Europe and Africa is linked to the distribution of Agavaceae and Dracaenaceae as ornamental plants. Particularly, in the Mediterranean countries, these plants mostly occur in botanical gardens and along the coastline, i.e. where most records of S. acupunctatus have been reported (
Genetic analyses showed a strong genetic uniformity for the non-native populations. A lower nucleotide and haplotype diversity was observed in the non-native range compared to the native range, possibly due to a founder effect. The presence of a single widespread haplotype in Europe suggested that most of the introductions may have originated from a small geographical area in Central America or a small number of introduction events occurred. This contrasts with other species, which were introduced through multiple unintentional introductions in Europe. These include C. ayyari, H. halys and Megachile (Callomegachile) sculpturalis Smith, which show a high genetic diversity linked to several introduction events (
Driving definite conclusions from single-gene analyses may be misleading. However, the largest genetic library for S. acupunctatus built in the present study may serve as a comparison for future studies and for species identification (
In general, our data showed a high climatic suitability for S. acupunctatus in Eurasia and Africa (particularly in the Mediterranean Basin coastline), including areas where this weevil is not yet present. This suggests that if no management actions are taken to limit its spread, there is potential for range expansion towards continental and temperate Europe in the upcoming years. Given the impacts on cultivated agave plants, early detection of this species in new areas should be promoted to prevent further invasions, by means of free online citizen-science platforms and coordination of phytosanitary services and national institutions for the prevention of biological invasions.
This work was supported by CNR: Research project FOE – Capitale Naturale e Risorse per il Futuro dell’Italia and Progetto di Ricerca@CNR – USEit Utilizzo di sinergie operative per lo studio e la gestione integrata di specie aliene invasive in Italia. AC gratefully acknowledges Project ALIEM APOSTROPHE “Action pour Limiter les risques de diffusion des espèces Introduites Envahissantes en Méditerranée” PC IFM 2014–2020 for financial support. Authors would like to thank E. Colonnelli, M. Depratis, L. Forbicioni, E. Giroux, S. Longo, L. Nuccitelli, E. Vandel, C. Berquier and J. Ventura who collected, provided or identified samples of Scyphophorus acupunctatus. We wish also to thank G. Mazza and E. Mori who provided us with four unpublished genetic sequences from Liguria. Moreover, we also thank M. Baratti and E. Paoletti, who allowed us to conduct genetic analyses at the CNR-IRET laboratories in Sesto Fiorentino. The Italian Legislative Decree 19/2021 (“Rules for the protection of plants from harmful organisms”) imposes that any previously unrecorded species in any Italian region must be immediately reported to the National Phytosanitary Service before any publication (both scientific and newspaper articles). Therefore, updated information on the distribution of this species in Italy has been sent to all Directors of Regional Phytosanitary Service before this publication. We are indebted with L. Pasquali, L. Ancillotto, M. Di Febbraro, L. Bosso, M. Falaschi and D. Strubbe, who provided us with deep help in species distribution model analyses. To conclude, we would like to thank the Subject Editor, Dr. Katelyn Faulkner and two reviewers for the insightful comments they provided on our early manuscript.
Supplementary data
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