PI Bastos contributed to the new DEFID2 dataset on forest disturbances in Europe (Forzieri et al., 2023).
In WP1 we focused on USA, where systematic forest inventory data and disturbance surveys are conducted on a regular basis across the whole domain. We first conducted a careful comparison of agreement between inventory-based and remote-sensing datasets, which allowed to derive uncertainty estimates of timing and location of disturbance events. Given limitations in the quality of labels to train our models identified in the preliminary analysis, we first worked on developing a new disturbance reference dataset based on the integration of the ground-based inventories, the uncertainty information from the analysis and a new radar-based disturbance detection approach.
Given the poor consistency of datasets on other disturbances beyond fire and drought, most of the work in WP2 has, so far, focused on drought and fire disturbances, and more generally on the links between climate variability and extremes and vegetation/carbon-cycle impacts. Therefore, the order of the tasks departs from the originally planned, but the overall progress is consistent with the objectives. We have first focused on quantifying fire regimes based on long-term satellite record and of drought regimes in the Iberian Peninsula (return time, intensity) and their link to vegetation activity.
Following the causal framework proposed in ForExD, we have applied multivariate logistic regression models to evaluate preconditioning and temporally compounding effects of winter climate variables on summer leaf-area index (a proxy for vegetation growth) extremes based on remote-sensing data, published in Anand et al. (2024). Using satellite vegetation optical depth data, we have analysed the large-scale patterns of vegetation drought responses to identify the relative contributions of climatic vs. land-cover and land-management factors (Xiao et al., 2023). C.Xiao was funded by HI MPG as part of the IMPRS graduate school funding.
In Na et al. (2024), we tested the hypothesis that the doubling sensitivity of global CO2 growth rate to tropical temperature was associated with climate-change driven changes in tropical drought regimes, as reported in previous studies. We used single model perturbed initial condition large ensembles (SMILES) to evaluate the role of internal climate variability versus anthropogenic climate change in the reported changes in CO2 sensitivity to temperature.
We developed a new impacts module in QUINCY for two primary insect types: bark beetles and defoliators. We further implemented the SPITFIRE model in QUINCY and extended the model to consider fire impacts on nutrient cycling, which carried scientific and technical challenges.
The perspective in Bastos et al. (2023) established the theoretical basis for developing storylines to separate different anthropogenic contributions (climate change, elevated CO2, management) to extreme event impacts, including an example illustrating their applicability.
