Recent geospatial dynamics of Terceira (Azores, Portugal) and the theoretical implications for the biogeography of active volcanic islands

Ongoing work shows that species richness patterns on volcanic oceanic islands are shaped by surface area changes driven by longer time scale (>1 ka) geological processes and natural sea level fluctuations. A key question is: what are the rates and magnitudes of the forces driving spatial changes on volcanic oceanic islands which in turn affect evolutionary and biogeographic processes? We quantified the rates of surface-area changes of a whole island resulting from both volcanogenic flows and sea level change over the last glacial-interglacial (GI) cycle (120 ka) for the volcanically active island of Terceira, (Azores, Macaronesia, Portugal). Volcanogenic activity led to incidental but long-lasting surface area expansions by the formation of a new volcanic cone and lava-deltas, whereas sea level changes led to both contractions and expansions of area. The total surface area of Terceira decreased by as much as 24% per time step due to changing sea levels and increased by 37% per time step due to volcanism per time step of 10 ka. However, while sea levels nearly continuously changed the total surface area, volcanic activity only impacted total surface area during two time steps over the past 120 ka. The surface area of the coastal and lowland region (here defined as area [removed

Strategies to improve the explanatory power of a dynamic slope stability model by enhancing land cover parameterisation and model complexity

Despite the importance of land cover on landscape hydrology and slope stability, the representation of land cover dynamics in physically based models and their associated ecohydrological effects on slope stability is rather scarce. In this study, we assess the impact of different levels of complexity in land cover parameterisation on the explanatory power of a dynamic and process-based spatial slope stability model. Firstly, we present available and collected data sets and account for the stepwise parameterisation of the model. Secondly, we present approaches to simulate land cover: 1) a grassland landscape without forest coverage; 2) spatially static forest conditions, in which we assume limited knowledge about forest composition; 3) more detailed information of forested areas based on the computation of leaf area development and the implementation of vegetation-related processes; 4) similar to the third approach but with the additional consideration of the spatial expansion and vertical growth of vegetation. Lastly, the model is calibrated based on meteorological data sets and groundwater measurements. The model results are quantitatively validated for two landslide-triggering events that occurred in Western Austria. Predictive performances are estimated using the Area Under the receiver operating characteristic Curve (AUC). Our findings indicate that the performance of the slope stability model was strongly determined by model complexity and land cover parameterisation. The implementation of leaf area development and land cover dynamics further yield an acceptable predictive performance (AUC ~0.71-0.75) and a better conservativeness of the predicted unstable areas (FoC ~0.71). The consideration of dynamic land cover expansion provided better performances than the solely consideration of leaf area development. The results of this study highlight that an increase of effort in the land cover parameterisation of a dynamic slope stability model can increase the explanatory power of the model.Water Resource