Incorporating high-resolution climate, remote sensing and topographic data to map annual forest growth in central and eastern Europe.

To enhance our understanding of forest carbon sequestration, climate change mitigation and drought impact on forest ecosystems, the availability of high-resolution annual forest growth maps based on tree-ring width (TRW) would provide a significant advancement to the field. Site-specific characteristics, which can be approximated by high-resolution Earth observation by satellites (EOS), emerge as crucial drivers of forest growth, influencing how climate translates into tree growth. EOS provides information on surface reflectance related to forest characteristics and thus can potentially improve the accuracy of forest growth models based on TRW. Through the modelling of TRW using EOS, climate and topography data, we showed that species-specific models can explain up to 52 % of model variance (Quercus petraea), while combining different species results in relatively poor model performance (R2 = 13 %). The integration of EOS into models based solely on climate and elevation data improved the explained variance by 6 % on average. Leveraging these insights, we successfully generated a map of annual TRW for the year 2021. We employed the area of applicability (AOA) approach to delineate the range in which our models are deemed valid. The calculated AOA for the established forest-type models was 73 % of the study region, indicating robust spatial applicability. Notably, unreliable predictions predominantly occurred in the climate margins of our dataset. In conclusion, our large-scale assessment underscores the efficacy of combining climate, EOS and topographic data to develop robust models for mapping annual TRW. This research not only fills a critical void in the current understanding of forest growth dynamics but also highlights the potential of integrated data sources for comprehensive ecosystem assessments.

Nutrient regime modulates drought response patterns of three temperate tree species.

Against the backdrop of global change, the intensity, duration, and frequency of droughts are projected to increase and threaten forest ecosystems worldwide. Tree responses to drought are complex and likely to vary among species, drought characteristics, and site conditions. Here, we examined the drought response patterns of three major temperate tree species, s. fir (Abies alba), E. beech (Fagus sylvatica), and N. spruce (Picea abies), along an ecological gradient in the South - Central - East part of Germany that included a total of 37 sites with varying climatic and soil conditions. We relied on annual tree-ring data to assess the influence of different drought characteristics and (micro-) site conditions on components of tree resilience and to detect associated temporal changes. Our study revealed that nutrient regime, drought frequency, and hydraulic conditions in the previous and subsequent years were the main determinants of drought responses, with pronounced differences among species. Specifically, we found that (a) higher drought frequency was associated with higher resistance and resilience for N. spruce and E. beech; (b) more favorable climatic conditions in the two preceding and following years increased drought resilience and determined recovery potential of E. beech after extreme drought; (c) a site's nutrient regime, rather than micro-site differences in water availability, determined drought responses, with trees growing on sites with a balanced nutrient regime having a higher capacity to withstand extreme drought stress; (d) E. beech and N. spruce experienced a long-term decline in resilience. Our results indicate that trees under extreme drought stress benefit from a balanced nutrient supply and highlight the relevance of water availability immediately after droughts. Observed long-term trends confirm that N. spruce is suffering from persistent climatic changes, while s. fir is coping better. These findings might be especially relevant for monitoring, scenario analyses, and forest ecosystem management.