The spatial pattern and driving factors on the prevalence of red imported fire ant (Solenopsis invicta) in island cities: A case study of Haitan Island, Fujian

Abstract

Aims: The red imported fire ant (RIFA), Solenopsis invicta, is one of the world’s worst invasive species, both environmentally and ecologically. In this study, we analyzed the spatial pattern of RIFA and the interactive mechanism of driving factors of its population density in island cities, in order to protect the island ecosystem. Methods: We use the Haitan Island as an example, the biggest island in Fujian Province, to analyze the spatial pattern of RIFA populations using Kernel density estimation and spatial autocorrelation models. We also used geographical detector to elucidate the individual and interactive effects of both environmental factors (8 types) and socio-economic factors (10 types) on RIFA prevalence. Results: Our results show that the spatial density of RIFA populations in the study area is characterized by uneven distribution, with the highest population density occurring in farmland (high-high aggregation), followed by landscaping and greening land (high-low and low-low aggregation), and the lowest density around residential areas. There are positive spatial autocorrelations within the population range. The q value for the explanatory power of 18 influencing factors on the spatial differentiation ranged from 0.014 to 0.278. Overall, there are differences between the effects of the two types of factors on RIFA occurrence, and the mean q value of the socio-economic factors are higher than those of the environmental factors. The socio-economic factors that have the greatest impact on RIFA occurrence are rural population size (q = 0.278) and township area (q = 0.268). The impact of soil classification (q = 0.172) and average annual precipitation (q = 0.149) are stronger than other environmental factors. The interaction between township area and distance to nearby scenic spot, and average annual precipitation and distance to nearby scenic spot, have the greatest influence on the occurance of RIFA (q = 0.466). The superposition of environmental and socio-economic factors positively enhance the occurance of RIFA. Conclusion: Our study indicates that agricultural cultivation, seedling introduction in urban greening construction, and transportation significantly affect the spatial pattern of RIFA pravalence in island cities. As far as its prevention and control strategy is concerned, we should not only implement strict plant quarantine regulations on imported seedlings and cargo, but also take locally-appropriate measures to effectively reduce the population size and prevent the spread of RIFA.