Insects tend to feed on related hosts. Coevolution tends to be dominated by interactions resulting from plant chemistry in defense strategies, and evolution of secondary metabolisms being in response to insect herbivory remains a classic explanation of coevolution. The present study examines whether evolutionary constraints existing in host associations of economically important fruit flies in the species‐rich tribe Dacini (Diptera: Tephritidae) and to what extent these species have evolved specialized dietary patterns. We found a strong effect of host phylogeny on associations on the 37 fruit flies tested, although the fruit fly species feeding on ripe commercially grown fruits that lost the toxic compounds after long‐term domestication are mostly polyphagous. We assessed the phylogenetic signal of host breadth across the fruit fly species, showing that the results were substantially different depending on partition levels. Further, we mapped main host family associations onto the fruit fly phylogeny and Cucurbitaceae has been inferred as the most likely ancestral host family for Dacini based on ancestral state reconstruction.

Invasive polyphagous fruit fly (Diptera: Tephritidae) species, including Zeugodacus cucurbitae (Coquillett), Zeugodacus tau (Walker), and Bactrocera zonata (Saunders), pose significant threats to agricultural and food security, particularly in Southeast Asia. This study aims to develop and evaluate species distribution models to predict the potential distribution of the 3 tephritid species based on climatic, soil, and topographic factors. Individual models and ensemble models were employed and tested to identify suitable areas across the region. The study also assesses the ecological niches of the 3 species across key environmental gradients. Our findings highlight that soil factors, often overlooked in predictive modeling, play a critical role in shaping their distributions and improving model prediction accuracy. The outperformance of ensemble models is further demonstrated among different modeling algorithms. The results provide valuable insights into the ecological niches of these invasive fruit fly species, and underscore the necessary of incorporating soil factors in model predictions, to improve invasive risk assessments and inform biosecurity measures.

The impact of invasive alien species (IAS) on nature and society is increasing globally. It is crucial to utilize information systems for evidence-based management, enabling the assessment and supporting survey and control actions. However, the lack of accessible and comprehensive baseline IAS data often impedes the ability to prioritize and allocate resources efficiently. Despite the increased public awareness of biological invasions in China over the past decades, the critical importance of data requirements has not been fully recognized, leading to gaps in available data. Here, we outline the key data demands for the management of biological invasions and highlight the current lack of high-quality data for invasion management in China, and critically assess data gaps in IAS distribution, inventory, and impact. Additionally, we propose a conceptual framework to illustrate the data requirements throughout the invasion management process, along with indicators to assess data quality within three dimensions: relevance, resolution, and reliability.