Predicting the invasion risk of Bactrocera dorsalis in Italy under climate and land cover change

Abstract

Bactrocera dorsalis, the oriental fruit fly (OFF), is a highly polyphagous and multivoltine invasive insect threatening over 600 fruit crop species globally. Originating in Asia, OFF has spread to Africa, Europe, and the United States. This study assessed the current and future potential distribution of OFF in Italy, a likely entry point for its invasion into Europe. Climate and land cover changes projected for 2070 and 2100 were considered. Potential connectivity corridors were identified, and habitat suitability was evaluated within orchards and vineyards. Ecological Niche Models (ENMs) and connectivity analyses revealed a dramatic increase in suitable habitats for OFF under future scenarios. The potential distribution is projected to expand on average by over 1600% under mild conditions and over 7000% under severe conditions, up to 2100. Key environmental factors include mean temperature of the driest quarter, isothermality, precipitation during the driest months, and proximity to forests, urban areas, and roads. Our findings suggest a significant rise in OFF suitability within agricultural areas, particularly vineyards and orchards, posing increased risks to these sectors. Effective management strategies - possibly supported by ecological modelling such as this study - should focus on mass trapping, habitat management, and public awareness to mitigate and contain this pest's spread. These predictions are based on the working assumption that B. dorsalis is locally acclimatized in inland Campania, southern Italy. Although definitive evidence of establishment is still pending, repeated detections in the same area over four consecutive years support the use of Italian records in risk modelling as an early warning strategy.

Keywords: Agricultural pest; Connectivity corridors; Ecological niche models; Global change.; Invasion risk; Invasive alien species.

Fig. 1

Variables importance (a) and response curves (b) as generated by regional ENMs.

Fig. 2

Overlay of the B. dorsalis binary distribution maps generated by regional ENMs for the current time (a), 2070 (b, c) and 2100 (d, e). Panels labelled with “(b)” and “(d)” report predictions under the mild climate and land cover change scenario, while the “(c)” and “(e)” panels refer to predictions under the severe one. Red (blue) colours indicate pixels of predicted presence by a high (low) percentage of binarization threshold and global circulation model combinations and are depicted with a logarithmic colour ramp.

Fig. 3

Statistics calculated on B. dorsalis binary distribution maps generated by regional ENMs and connectivity analysis. Panel “(a)” depicts the range net change values calculated on binary distribution maps. The plots in the other panels summarize the percentage of connected suitable habitat (b), the number of connectivity corridors per patch (c) and the connectivity corridor length (d), as calculated under the “nearly linear” suitability–to–resistance transformation (see text). Each plot reports the mean value for each statistic, along with the standard deviation representing the variation across the five global circulation models and the four binarization thresholds. Differences in mean statistic values were tested via permutational ANOVA, depicting statistical significance using the following notation: “ns” – not significant; “*” – p < 0.05; “**” – p < 0.01; “***” – p < 0.001.

Fig. 4

Connectivity corridors and degree of patch reachability for B. dorsalis as derived by Circuitscape analysis considering the “nearly linear” suitability–to–resistance transformation (see text), for the current time (a) and 2070 under the mild (b) and severe (c) climate and land cover change scenarios. Red (yellow) colours indicate corridors that resulted among the most important ones (i.e., those passing through mean conductance values above the third quartile of the conductance values of the entire network) in a high (low) percentage of binarization thresholds and global circulation models combinations. Similarly, blue (green) colours refer to patches that are reached by the most important corridors in a high (low) percentage of binarization thresholds and global circulation models combinations. Patches in black were not reached by any important corridor. Insets in the upper right corners depict a zoom on the Campania Region, where most OFF detections occur.

Fig. 5

Connectivity corridors and degree of patch reachability for B. dorsalis as derived by Circuitscape analysis considering the “nearly linear” suitability–to–resistance transformation (see text), for the current time (a) and 2100 under the mild (b) and severe (c) climate and land cover change scenarios. Red (yellow) colours indicate corridors that resulted among the most important ones (i.e., those passing through mean conductance values above the third quartile of the conductance values of the entire network) in a high (low) percentage of binarization thresholds and global circulation models combinations. Similarly, blue (green) colours refer to patches that are reached by the most important corridors in a high (low) percentage of binarization thresholds and global circulation models combinations. Patches in black were not reached by any important corridor. Insets in the upper right corners depict a zoom on the Campania Region, where most OFF detections occur.

Fig. 6

Study area and occurrence records (blue dots) used to calibrate regional ENMs. The background elevation map was derived from https://srtm.csi.cgiar.org/)