Changing alpine vegetation dynamics: insight from complementary modelling and observation approaches

Abstract

Plants are vital resources and biodiversity components, and an important link between humans and the Earth system. Yet, data sets and theories in vegetation ecology are generally disjunct and only cover parts of the processes occurring at different temporal and spatial scales, and phylogenetic and organisational levels. This thesis brings together four different modelling approaches, and different types of data, that capture different aspects of how ecosystems and species within communities interact and may change alongside the climate. The study area comprises four alpine grassland ecosystems in western Norway. The thesis (1) presents new software to improve access to a demographic vegetation model, (2) identifies challenges in a model experiment replicating a field-based vegetation warming experiment using the demographic vegetation model, (3) shows that that trait differences do not explain co-occurrence at the species level, and (4) that direct positive effects of climate warming on alpine plants can be cancelled out by interactions with more competitive species. For scaling up from empirical and statistical studies in the long term, further exploration of dynamical process-based models and trait-based ecology is warranted. Complementary approaches are needed to combine data, theory, and models to get the best possible understanding of dynamical vegetation processes.