Actual and potential distribution of non-native plants in the Central-Southern Andes of Chile : the role of anthropization at multiple spatial scales

Several factors have been identified as relevant for the distribution of non-native plants in mountain ecosystems. These factors depend mainly on the environmental and vegetational characteristics of each ecosystem (invasibility) and the traits of each invasive species (invasiveness). Knowing the importance of each factor that determines the distribution of non- native plants at multiple scales, is critical to advance the knowledge of the invasion process and efficient protocols for the control and management of non-native in the Andes, all this considering that these ecosystems are a hotspot of biodiversity. Therefore, the general objective of this doctoral thesis is to deepen the existing knowledge on the distribution of non-native plants in the Andes. More specifically, I aim to evaluate how abiotic, biotic, and anthropogenic factors determine the distribution patterns, richness, and abundance of non-native plants along elevational gradients at multiple scales in the Andes. Complementarily, using the current distribution patterns of the most abundant non-native lowland plants, we sought to project their potential future distribution using anthropogenic and microclimatic variables, to understand how the inclusion of these variables can improve the performance of species distribution models and would thus allow us to assess more accurately the redistribution of invasive plants in the Chilean Andes. In this thesis, the following hypotheses were evaluated: (1) The richness and abundance of non- native plants at the regional scale in the Andes Mountains will be determined by abiotic variables such as soil temperature and nitrogen content, while at the local scale anthropogenic variables, such as the presence of roads and human settlements, will be the main drivers. Due to the importance of anthropogenic and microclimatic factors for non-native plant distributions in mountain ecosystems (2), the inclusion of microclimatic and anthropogenic data should improve the performance of models of these ...