Invasive species are reported as one of the top current and future concerns for the health and functioning of native ecosystems. In response, identification of invasive plant impacts are one of the top most studied aspects of plant invasions. Yet we still know very little about invasive plant impacts, and many land managers remove invasive plants not because of known negative impacts, but because of the general negative connotation associated with invasions. Here, I develop and utilize integrative methods to more holistically measure the ecological impacts of invasive plants. I develop a meta-analysis of current invasive plant impact literature, I integrate independent ecosystem metrics into holistic measures of total ecological impact, I examine the potential for legacy and temporal effects in newly established and recently managed invasions, and I measure ecological impact of co-invaded ecosystems. Through these studies, I find that magnitude, and not direction, of impact better represents actual ecosystem changes when evaluating invasions holistically. I also find invasive plant management may not only fail to remove long term legacy effects, but may in some cases further negatively impact the plant community. Finally, I find that co-invaded systems are not intrinsically worse off than single invaded systems. Collectively, these studies help to better our understanding of the impacts of invasive plants and their implications for management, and show that simple attempts at eradication may not always be desirable. / Ph. D.

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The Connecticut River watershed is experiencing a rapid invasion of aggressive non-native plant species, which threaten watershed function and structure. Volunteer-based monitoring programs such as the University of Massachusetts’ OutSmart Invasives Species Project, Early Detection Distribution Mapping System (EDDMapS) and the Invasive Plant Atlas of New England (IPANE) have gathered valuable invasive plant data. These programs provide a unique opportunity for researchers to model invasive plant species utilizing citizen-sourced data. This study took advantage of these large data sources to model invasive plant distribution and to determine environmental and biophysical predictors that are most influential in dispersion, and to identify a suitable presence-only model for use by conservation biologists and land managers at varying spatial scales. This research focused on the invasive plant species of high interest - Japanese stiltgrass (Mircostegium vimineum). This was identified as a threat by U.S. Fish and Wildlife Service refuge biologists and refuge managers, but for which no mutli-scale practical and systematic approach for detection, has yet been developed. Environmental and biophysical variables include factors directly affecting species physiology and locality such as annual temperatures, growing degree days, soil pH, available water supply, elevation, closeness to hydrology and roads, and NDVI. Spatial scales selected for this study include New England (regional), the Connecticut River watershed (watershed), and the U.S. Fish and Wildlife, Silvio O. Conte National Fish and Wildlife Refuge, Salmon River Division (local). At each spatial scale, three software programs were implemented: maximum entropy habitat model by means of the MaxEnt software, ecological niche factor analysis (ENFA) using Openmodeller software, and a generalized linear model (GLM) employed in the statistical software R. Results suggest that each modeling algorithm performance varies among spatial scales. The best fit modeling software designated for each scale will be useful for refuge biologists and managers in determining where to allocate resources and what areas are prone to invasion. Utilizing the regional scale results, managers will understand what areas on a broad-scale are at risk of M. vimineum invasion under current climatic variables. The watershed-scale results will be practical for protecting areas designated as most critical for ensuring the persistence of rare and endangered species and their habitats. Furthermore, the local-scale, or fine-scale, analysis will be directly useful for on-the-ground conservation efforts. Managers and biologists can use results to direct resources to areas where M. vimineum is most likely to occur to effectively improve early detection rapid response (EDRR).