Quantifying Planococcus ficus (Hemiptera: Pseudococcidae) Invasion in Northern California Vineyards to Inform Management Strategy

Abstract

The spread and impact of invasive species in exotic ranges can be mitigated by increased understanding of pest invasion dynamics. Here, we used geospatial analyses and habitat suitability modeling to characterize the invasion of an important vineyard pest, vine mealybug (Planococcus ficus Signoret, Hemiptera: Pseudococcidae), using nearly 15,000 trapping records from throughout Napa County, California, between 2012 and 2017. Spatial autocorrelation among P. ficus detections was strongest at distances of ~250 m and detectable at regional scales (up to 40 km), estimates of the rate and directionality of spread were highly idiosyncratic, and P. ficus detection hotspots were spatiotemporally dynamic. Generalized linear model, boosted regression tree, and random forest modeling methods performed well in predicting habitat suitability for P. ficus. The most important predictors of P. ficus occurrence were a positive effect of precipitation in the driest month, and negative effects of elevation and distance to nearest winery. Our results indicate that 250-m quarantine and treatment zones around P. ficus detections are likely sufficient to encompass most local establishment and spread, and that implementing localized regulatory procedures may limit inadvertent P. ficus spread via anthropogenic pathways. Finally, surveys of P. ficus presence at >300 vineyard sites validated that habitat suitability estimates were significantly and positively associated with P. ficus frequency of occurrence. Our findings indicate that habitat suitability predictions may offer a robust tool for identifying areas in the study region at risk to future P. ficus invasion and prioritizing locations for early detection and preventative management efforts.

Ants as mealybug detectors: a novel tool for monitoring Planococcus ficus infestation based on ant behaviour

“…As a result, monitoring activities require a high level of expertise and are time‐consuming. To overcome these problems, alternative monitoring techniques have been developed recently, such as molecular tools for safe and rapid pest identification (Daane et al, 2011), pheromone‐baited traps based on male capture to estimate pest density (Millar et al, 2002; Walton et al, 2004; Zada et al, 2008), and geospatial analyses and habitat suitability modelling to predict areas at risk to future VMB invasion (Schartel et al, 2020).…”