Anne Gnilke

Over the last decade, several extreme weather events contributed to considerable loss and degradation of forest ecosystems throughout central Europe [1]. For future forest protection an in-depth understanding of these disturbances and their interactions is crucial to target the transformation and adaptation of forests [2]. The vulnerability of forest stands to disturbances is determined by the interaction of a large number of environmental influences and their characteristics. The influencing variables are interrelated at multiple dimensions and scales [3]. Due to the complexity of cause-effect relationships in forest ecosystems and the multitude of factors involved, stress response of forests and trees has not been fully decoded as yet and hence remains a research topic of growing importance for climate adaptation [4].The recording of small-scale ecological phenomena and their dynamics requires spatially and temporally continuous high-resolution data to retrieve explicit information, which cannot fully be covered by current terrestrial monitoring networks e.g., the ICP Forests crown conditions survey or national forest inventories. The combination of satellite time series analysis and change detection algorithms can detect forest vitality changes across time and space at a high resolution in order to extract disturbance signatures with event-specific patterns from phenological time series [5].In this study, we use forest disturbance recordings of forest fires, storm damage, and forest defoliation or dieback induced by insects, fungal pathogens, or drought from the European Forest Fire Information System (EFFIS), the Database of wind disturbances in European forest (FORWIND), the Database of European Forest Insect & Disease Disturbances (DEFIS2), and the Global Drought Observatory (GDO) as well as MODIS phenological time series ranging from 2001 to 2023 to gather disturbance sequences and compile a pan-European disturbance interaction chronology map in order to identify forest disturbance hotspots in Europe, extract disturbance interaction related signatures from phenological time series and quantify the interaction effects in terms of disturbance specific changes in forest vitality over space and time. References:[1] Patacca, M, Lindner, M, Lucas‐Borja, ME, Cordonnier, T, Fidej, G, Gardiner, B, ... & Schelhaas, MJ (2023). Significant increase in natural disturbance impacts on European forests since 1950. Global change biology, 29(5), 1359-1376. https://doi.org/10.1111/gcb.16531[2] Bolte, A, Ammer, C, Löf, M, Madsen, P, Nabuurs, GJ, Schall, P, ... & Rock, J (2009). Adaptive forest management in central Europe: climate change impacts, strategies and integrative concept. Scandinavian Journal of Forest Research, 24(6), 473-482. https://doi.org/10.1080/02827580903418224[3] Sanders, TGM, Spathelf, P, & Bolte, A (2019). The response of forest trees to abiotic stress. In Achieving sustainable management of boreal and temperate forests (pp. 99-128). Burleigh Dodds Science Publishing. DOI:10.19103/AS.2019.0057.05[4] Ammer, C, Fichtner, A, Fischer, A, Gossner, MM, Meyer, P, Seidl, R, ... & Wagner, S (2018). Key ecological research questions for Central European forests. Basic and Applied Ecology, 32, 3-25. https://doi.org/10.1016/j.baae.2018.07.006[5] Gnilke, A, & Sanders, TGM (2022). Distinguishing abrupt and gradual forest disturbances with MODIS-based phenological anomaly series. Frontiers in Plant Science, 13, 863116. https://doi.org/10.3389/fpls.2022.863

Wildfire risk increases following non-fire disturbance events, but this relationship is not always linear or cumulative, and previous studies are not consistent in differentiating between disturbance loops versus cascades. Previous research on disturbance interactions and their influence on forest fires has primarily focused on fire-prone regions, such as North America, Australia, and Southern Europe. In contrast, less is known about these dynamics in Central Europe, where wildfire risk and hazard are increasing. In recent years, forest disturbances, particularly windthrow, insect outbreaks, and drought, have become more frequent in Central Europe. At the same time, climate change is influencing fire weather conditions that further intensify forest fire dynamics. Here, we synthesize findings from the recent literature on disturbance interactions in Central Europe with the aim to identify disturbance-driven processes that influence the regional fire regime. We propose a conceptual framework of interacting disturbances that can be used in wildfire risk assessments and beyond. In addition, we identify knowledge gaps and make suggestions for future research regarding disturbance interactions and their implications for wildfire activity. Our findings indicate that fire risk in the temperate forests of Central Europe is increasing and that non-fire disturbances and their interactions modify fuel properties that subsequently influence wildfire dynamics in multiple ways.

Capturing forest disturbances over time is increasingly important to determine the ecosystem's capacity to recover as well as aiding a timely response of foresters. With changes due to climate change increasing the frequencies, a better understanding of forest disturbances and their role in historical development is needed to, on the one hand, develop forest management approaches promoting ecosystem resilience and, on the other hand, provide quick and spatially explicit information to foresters. A large, publicly available satellite imagery spanning more than two decades for large areas of the Earth's surface at varying spatial and temporal resolutions represents a vast, free data source for this. The challenge is 2-fold: (1) obtaining reliable information on forest condition and development from satellite data requires not only quantification of forest loss but rather a differentiated assessment of the extent and severity of forest degradation; (2) standardized and efficient processing routines both are needed to bridge the gap between remote-sensing signals and conventional forest condition parameters to enable forest managers for the operational use of the data. Here, we investigated abiotic and biotic disturbances based on a set of ground validated occurrences in various forest areas across Germany to build disturbance response chronologies and examine event-specific patterns. The proposed workflow is based on the R-package “npphen” for non-parametric vegetation phenology reconstruction and anomaly detection using MODIS EVI time series data. Results show the potential to detect distinct disturbance responses in forest ecosystems and reveal event-specific characteristics. Difficulties still exist for the determination of, e.g., scattered wind throw, due to its subpixel resolution, especially in highly fragmented landscapes and small forest patches. However, the demonstrated method shows potential for operational use as a semi-automatic system to augment terrestrial monitoring in the forestry sector. Combining the more robust EVI and the assessment of the phenological series at a pixel-by-pixel level allows for a changing species cover without false classification as forest loss.