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Meteorological drivers of extremes in daily stem radius variations of beech, oak, and pine in Northeastern Germany

  • Observed recent and expected future increases in frequency and intensity of climatic extremes in central Europe may pose critical challenges for domestic tree species. Continuous dendrometer recordings provide a valuable source of information on tree stem radius variations, offering the possibility to study a tree's response to environmental influences at a high temporal resolution. In this study, we analyze stem radius variations (SRV) of three domestic tree species (beech, oak, and pine) from 2012 to 2014. We use the novel statistical approach of event coincidence analysis (ECA) to investigate the simultaneous occurrence of extreme daily weather conditions and extreme SRVs, where extremes are defined with respect to the common values at a given phase of the annual growth period. Besides defining extreme events based on individual meteorological variables, we additionally introduce conditional and joint ECA as new multivariate extensions of the original methodology and apply them for testing 105 different combinations of variablesObserved recent and expected future increases in frequency and intensity of climatic extremes in central Europe may pose critical challenges for domestic tree species. Continuous dendrometer recordings provide a valuable source of information on tree stem radius variations, offering the possibility to study a tree's response to environmental influences at a high temporal resolution. In this study, we analyze stem radius variations (SRV) of three domestic tree species (beech, oak, and pine) from 2012 to 2014. We use the novel statistical approach of event coincidence analysis (ECA) to investigate the simultaneous occurrence of extreme daily weather conditions and extreme SRVs, where extremes are defined with respect to the common values at a given phase of the annual growth period. Besides defining extreme events based on individual meteorological variables, we additionally introduce conditional and joint ECA as new multivariate extensions of the original methodology and apply them for testing 105 different combinations of variables regarding their impact on SRV extremes. Our results reveal a strong susceptibility of all three species to the extremes of several meteorological variables. Yet, the inter-species differences regarding their response to the meteorological extremes are comparatively low. The obtained results provide a thorough extension of previous correlation-based studies by emphasizing on the timings of climatic extremes only. We suggest that the employed methodological approach should be further promoted in forest research regarding the investigation of tree responses to changing environmental conditions.show moreshow less

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Author details:Jonatan Frederik SiegmundORCiDGND, Tanja G. M. Sanders, Ingo HeinrichGND, Ernst van der Maaten, Sonia Simard, Gerhard HelleORCiDGND, Reik Volker DonnerORCiDGND
URN:urn:nbn:de:kobv:517-opus4-407943
Title of parent work (English):Frontiers in plant science
Subtitle (English):an event coincidence analysis
Publication series (Volume number):Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe (456)
Publication type:Postprint
Language:English
Date of first publication:2018/07/02
Publication year:2016
Publishing institution:Universität Potsdam
Release date:2018/07/02
Tag:climate extremes; dendrometer measurements; event coincidence analysis; growth response
Number of pages:14
Source:Frontiers in plant science 7 (2016), Art. 733 ; DOI: 10.3389/fpls.2016.00733
Organizational units:Mathematisch-Naturwissenschaftliche Fakultät
Mathematisch-Naturwissenschaftliche Fakultät / Institut für Geowissenschaften
DDC classification:5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie
Peer review:Referiert
Publishing method:Open Access
Grantor:Frontiers
Institution name at the time of the publication:Mathematisch-Naturwissenschaftliche Fakultät / Institut für Erd- und Umweltwissenschaften
License (German):License LogoCC-BY - Namensnennung 4.0 International
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