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.

中文翻译：

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量化榕树球藻（半翅目：假球菌科）对北加州葡萄园的入侵以告知管理策略

通过增加对害虫入侵动态的了解，可以减轻入侵物种在外来范围内的传播和影响。在这里，我们使用地理空间分析和栖息地适宜性模型来描述一种重要的葡萄园害虫，葡萄粉蚧（Planococcus ficus Signoret，半翅目：Pseudococcidae）的入侵情况，使用了 2012 年至 2017 年间来自加利福尼亚州纳帕县的近 15,000 条诱捕记录。 P. ficus 检测之间的自相关在约 250 m 的距离内最强，可在区域尺度（最多 40 km）检测到，传播速度和方向性的估计是高度特殊的，并且 P. ficus 检测热点是时空动态的。广义线性模型、增强回归树和随机森林建模方法在预测榕树的栖息地适宜性方面表现良好。P. ficus 发生的最重要预测因素是最干燥月份降水的积极影响，以及海拔和到最近酿酒厂距离的负面影响。我们的结果表明，在 P. ficus 检测点周围 250 米的隔离和处理区可能足以涵盖大多数本地建立和传播，并且实施本地化监管程序可能会限制 P. ficus 通过人为途径无意传播。最后，对超过 300 个葡萄园地点的 P. ficus 存在的调查证实，栖息地适宜性估计与 P. ficus 的发生频率显着正相关。我们的研究结果表明，栖息地适宜性预测可能提供一个强大的工具，用于识别研究区域中可能对未来 P.