Understanding what promotes invasiveness of species outside their native range and predicting which ecosystems and under which conditions will be invaded is an ultimate goal of the field of invasion ecology. Obtaining general answers to these questions requires synthesis of extensive yet heterogeneous empirical evidence, coupled with a solid theoretical background. In this dissertation, I sought to provide insight into the drivers of non-native plant invasions through combining and synthesizing ecological data from various sources using advanced statistical techniques. The results of this work are presented as three independent research studies.
In the first study, I aimed to understand what determines competitive advantage of non-native over native plants: the ability to suppress other plants, tolerate them, or both. For this, I collected data from 192 studies on plant competition and analyzed them within a Bayesian multilevel meta-analytic framework. I showed that non-native plants outperform their native counterparts due to the high tolerance of competition, as opposed to strong suppressive ability. Competitive tolerance ability of non-native plants was driven by neighbor’s origin and was expressed in response to native species and not to other non-native species. This synthesis demonstrates that non-native plants are competitively distinct from native plants and challenges the common notion that neighbor suppression is the primary strategy for plant invasion success.
In the second study, I quantified the extent to which regional, landscape and local environmental factors individually and jointly affect understory non-native invasive plants across northern US forests. I used boosted regression trees and Bayesian nonlinear regressions to analyze forest inventory data spanning 14 northern US states in combination with data on climate, land use, and disturbance. Regionally, the highest level of plant invasion was observed in hotter regions with lower annual precipitation and climate seasonality and higher summer precipitation. Locally, young forests with moist to wet soils and relatively flat topography in open, human-altered landscapes at low elevation were most susceptible to invasion. Climate and land use strongly interacted in their effect on plant invasions. This study refines the understanding of the non-native plant invasion process in northern US forests and the obtained models can be used to generate predictions under current and future environmental regimes to inform management.
In the third study, I tested the relationship between the long-term history of recurrent canopy disturbance by a non-native invasive defoliator, the gypsy moth (Lymantria dispar), and the level of non-native plant invasion in northeastern US forests. I reconstructed 46 years (1970–2015) of gypsy-moth defoliation history and quantified the cumulative effect of defoliation on understory non-native invasive plant species using multivariate techniques and Bayesian nonlinear regressions. Contrary to what is commonly expected, the cumulative severity of gypsy moth defoliation tended to be negatively associated with the presence and richness of invasive plant species, although this association was weak. This study suggests that the effect of biotic disturbance on forest plant invasions may vary in both the magnitude and direction depending on characteristics of disturbance regime and its effect on resident biota, and this needs to be explicitly taken into account when predicting future plant invasions.
| Identifer | oai:union.ndltd.org:uvm.edu/oai:scholarworks.uvm.edu:graddis-2025 |
| Date | 01 January 2019 |
| Creators | Golivets, Marina |
| Publisher | ScholarWorks @ UVM |
| Source Sets | University of Vermont |
| Language | English |
| Detected Language | English |
| Type | text |
| Format | application/pdf |
| Source | Graduate College Dissertations and Theses |
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