Using district-level occurrences in MaxEnt for predicting the invasion potential of an exotic insect pest in India
详细信息   
摘要
Insect pests are a major threat to agricultural biosecurity across the world, causing substantial economic losses. Majority of the species distribution modeling studies use precise coordinates (latitude/longitude) of species occurrences in MaxEnt (or maximum entropy model). However, lack of precise coordinates of insect pest occurrences at national/regional level is a common problem for many countries including India. This is because of the limited resources, lack of nationally coordinated surveys, and growers/farmers鈥?privacy issues; district-level occurrences are commonly available (e.g., National Agricultural Pest Information System or NAPIS in the United States; ). We demonstrated the use of MaxEnt to generate a preliminary, district-level map of the potential risk of invasion by an exotic cotton mealybug Phenacoccus solenopsis (Tinsley) (Hemiptera: Pseudococcidae) in India. District-level occurrence data were integrated with bioclimatic variables (values averaged within districts) using MaxEnt. The MaxEnt model performed better than random with an average test AUC value of 0.86 (卤0.05). Our model predictions matched closely with the documented occurrence of P. solenopsis in all nine cotton growing states, and also predicted suitable habitats in other districts across India. The greatest threat of P. solenopsis infestations were predicted in most districts of Gujarat, Maharashtra, Andhra Pradesh, southwestern Punjab, northwestern Rajasthan, and western Haryana. Precipitation of coldest quarter, temperature annual range, and precipitation seasonality were the strongest predictors associated with P. solenopsis distribution. Precipitation of coldest quarter was negatively correlated with P. solenopsis occurrence. Mapping the potential distribution of invasive species is an iterative process, and our study is the first attempt to model national-level risk assessment of P. solenopsis in India. Our results can be used for selecting monitoring and surveillance sites and designing local, regional and national-level integrated pest management policies for cotton and other cultivated crops in India. The maps of potential pest distributions are urgently needed by agriculture managers and policymakers. Our approach can be used in other countries that lack precise coordinates of insect pest occurrences and generate a preliminary map of potential risk because it may be too late to wait for the precise coordinates of pest occurrences to generate a perfect map.