Predicting the potential invasion of kudzu bug, Megacopta cribraria (Heteroptera: Plataspidae), in North and South America and determining its climatic preference

Biological invasions have long placed challenges on ecosystems, agricultural production, and human health. Modeling potential invasion of an introduced organism becomes a critical tool for early management of damaging species, such as kudzu bug, Megacopta cribraria (F.) (Hemiptera:Heteroptera:Plataspidae). Since it was first found in the United States in 2009, kudzu bug has spread rapidly, economically impacted agricultural production, and became a household pest. To better predict the potential invasion of kudzu bug in North and South America, we used the species distribution models Genetic Algorithm for Rule-set Production (GARP) and Maximum Entropy (Maxent). We used the D metric to test for niche equivalency and similarity between native and invaded populations of kudzu bug. We found that kudzu bugs currently occupied unequal environmental space between the two ranges. Therefore, distribution models using GARP and Maxent were constructed using occurrences in both native and invaded ranges. Area under the curve (AUC), true skill statistics (TSS), and omission rate (OR) were used to evaluate and compare the models. Results indicated both models had good performance, but Maxent (AUC = 0.971, TSS = 0.946, OR = 0.019) performed better than GARP (AUC = 0.922, TSS = 0.860, OR = 0.037). This research confirmed the effectiveness of using occurrence data in both ranges to predict potential invasions. Kudzu bugs prefer warm (annual mean temperature around 15 °C) and humid (annual mean precipitation around 1300 mm) regions. Distribution models generated by both methods indicated similar regions with high invasion risk. Management programs that include quarantine and prevention measures are suggested for these regions to avoid outbreaks of kudzu bug.