| Description: |
Unfolding dynamic processes in nature by conserving and restoring ecosystem functioning are essential for sustaining optimal conditions for biodiversity under increasing anthropogenic pressures. During recent years, rewilding approaches, by e.g. introducing large herbivores, has been initiated in grasslands to mitigate a lack of natural grazing and disturbance dynamics. Yet, the influence of large animals in natural landscapes is highly contextual and understanding its impact on natural ecosystems remains limited in both, temporal and spatial scales. Thus, to ensure that rewilding and restoration interventions contribute to desirable trajectories for long-term support of biodiversity and ecosystem functioning, it is crucial to determine whether identified effects are consistent across time and space. This demands a long-term monitoring effort at a high frequency, e.g. yearly. Our study leverages a robust experimental design of contrasting management and grazing regimes using exclosure treatments in a rewilded area, currently applied over eight consecutive years in a semi-natural mosaicked landscape of mixed habitat types. Through yearly vegetation surveys, we assess the development of plant diversity, community composition, and vegetation structure in response to these treatments. This long-term time-series allows us to disentangle the effects of management and grazing interventions, in near-natural conditions, offering an enhanced understanding of the impact on plant diversity and vegetation dynamics from rewilding practices. By analysing this comprehensive dataset, we are able to capture dynamic vegetation patterns and trajectories which single-time snapshot datasets cannot reveal, such as shifts in alpha-, beta-, and gamma-diversity in response to environmental variability and extreme climatic events. These insights emphasize the importance of high frequency monitoring and temporal analysis for understanding ecosystem resilience and stability in relation to grazing and management practices. Additionally, our ... |