Ecological memory effects in Norway spruce ring-width chronologies across managed forests of Central-East Germany: Implications for modelling and planning
- ThüringenForst AöR, Forestry Research and Competence Centre, Germany (jakob.wernicke@gmail.com)
The combined negative effects of climate change and adverse forest structures currently result in large amounts of random timber use all over Central Europe. Particularly Norway spruce (Picea abies [L.] Karst) is threatened by summer droughts and secondary pests. Hence, achieving insights in the drought tolerance of spruce is highly relevant to reduce the vulnerability of forest systems under climate change. Especially long-living spruce individuals witness several periods of drought in their ring-width variability. A common measure of trees drought tolerance is referred to resistance, resilience and recovery ability. Besides forest management and site characteristic, the ecological memory of trees might distinctly affect spruce drought tolerance.
Therefore we investigate the spatio-temporal variability of the ecological memory effect from more than 1500 individual ring-width time series of spruce trees collected from the managed forests of Central-East Germany. The memory effect is examined via time series first to third autocorrelation. We are particularly interested in the question: ‘can trees with a ‘good memory’ cope better with climate extremes than trees with a ‘bad memory’? If so, is it possible to influence the memory of trees via specific thinning strategies? Finally, how can autocorrelation improve the assessment of site productivity, taking the climate change induced displacement of growth areas into consideration? The study results reveal crucial insights in the drought vulnerability of spruce dominated forests in relation to forest structure and management strategies.
How to cite: Wernicke, J., Seltmann, C. T., and Körner, M.: Ecological memory effects in Norway spruce ring-width chronologies across managed forests of Central-East Germany: Implications for modelling and planning, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-20690, https://doi.org/10.5194/egusphere-egu2020-20690, 2020