Accounting for residential propagule pressure improves prediction of urban plant invasion
Description
Plant invasions substantially impact the ecosystem services provided by forests in urbanizing regions. Knowing where invasion risk is greatest helps target early detection and eradication efforts, but developing an accurate predictive model of invasive species presence and spread on the basis of habitat suitability remains a challenge due to spatial variation in propagule pressure (the number of individuals released) which is likely conflated with suitability. In addition to neighborhood propagule pressure that originates with propagules dispersing from naturalized populations within invaded habitats, we expect residential propagule pressure arising from the widespread use of exotic plants in the yards of single-family residences to be an important driver of invasions, and to notably improve the predictive accuracy of species distribution models (SDMs). To this end, we collected presence/absence data for a widespread forest invader, Ligustrum sinense (Chinese privet), from 400 stratified random plots located along an urban gradient across the Charlotte, North Carolina metropolitan area. We assessed the relative contribution of residential propagule pressure and neighborhood propagule pressure to improving the predictive performance of a probit SDM for Chinese privet that only contains environmental predictors. Our results indicate that, although the environment-only model predicted the highest geographic area to be at risk of invasion by privet, it also had the highest rate of failure to accurately predict observed privet occurrences as indicated by the omission (incorrectly predicted absence) and commission (incorrectly predicted presence) error rates. Accounting for residential propagule pressure substantially improved model performance by reducing the omission error by nearly 50%, thereby improving upon the ability of the model to predict privet invasion in suboptimal habitat. Given that this increase in detection was accompanied by a decrease in the geographic area predicted at risk, we conclude that SDMs for invasive exotic shrubs and potentially for other synanthropic generalist plants may be highly inefficient when residential propagule pressure is not accounted for. Accounting for residential propagule pressure in models of invasive plants results in a more focused and accurate prediction of the area at risk, thus enabling decision makers to feasibly prioritize regional scale monitoring and control efforts.
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