TY - THES A1 - Siegmund, Jonatan Frederik T1 - Quantifying impacts of climate extreme events on vegetation T1 - Über die Quantifizierung des Einflusses extremer Klimaereignisse auf Vegetation BT - event coincidence analysis and its applications across scales BT - die Event Koinzidenz Analyse und deren Anwendung auf verschiedenen Skalen N2 - Together with the gradual change of mean values, ongoing climate change is projected to increase frequency and amplitude of temperature and precipitation extremes in many regions of Europe. The impacts of such in most cases short term extraordinary climate situations on terrestrial ecosystems are a matter of central interest of recent climate change research, because it can not per se be assumed that known dependencies between climate variables and ecosystems are linearly scalable. So far, yet, there is a high demand for a method to quantify such impacts in terms of simultaneities of event time series. In the course of this manuscript the new statistical approach of Event Coincidence Analysis (ECA) as well as it's R implementation is introduced, a methodology that allows assessing whether or not two types of event time series exhibit similar sequences of occurrences. Applications of the method are presented, analyzing climate impacts on different temporal and spacial scales: the impact of extraordinary expressions of various climatic variables on tree stem variations (subdaily and local scale), the impact of extreme temperature and precipitation events on the owering time of European shrub species (weekly and country scale), the impact of extreme temperature events on ecosystem health in terms of NDVI (weekly and continental scale) and the impact of El Niño and La Niña events on precipitation anomalies (seasonal and global scale). The applications presented in this thesis refine already known relationships based on classical methods and also deliver substantial new findings to the scientific community: the widely known positive correlation between flowering time and temperature for example is confirmed to be valid for the tails of the distributions while the widely assumed positive dependency between stem diameter variation and temperature is shown to be not valid for very warm and very cold days. The larger scale investigations underline the sensitivity of anthrogenically shaped landscapes towards temperature extremes in Europe and provide a comprehensive global ENSO impact map for strong precipitation events. Finally, by publishing the R implementation of the method, this thesis shall enable other researcher to further investigate on similar research questions by using Event Coincidence Analysis. N2 - Neben der graduellen Änderung der mittleren klimatischen Bedingungen wird für viele Regionen Europas ein Anstieg in Häufigkeit und Intensität der Temperatur- und Niederschlagsextreme projiziert. Die Auswirkungen solcher meist nur kurz anhaltenden Klimaextreme auf terrestrische Ökosysteme sind zentraler Bestandteile aktueller Klimaforschung, weil nicht per se davon ausgegangen werden kann, dass Abhängihkeitsverhältnisse zwischen Klima- und Umweltvariblen linear skalierbar sind. Weil klimatische Extremereignisse selten und in der Regel nur von kurzer Dauer sind, wird für Untersuchungen über deren Auswirkungen eine analytische Methode benötigt, welche es erlaubt die Gleichzeitigkeit von Events in zwei Zeitreihen zu quantifizieren. In diesem Manuskript wird der neue statistische Ansatz der Event Coincidence Analysis sowie deren R-Implementierung vorgestellt. Zusätzlich werden verschiedene Anwendungen der Methode im Bereich der Klimafolgenforschung auf unterschiedlichen Skalen vorgelegt: Die Auswirkungen außergewöhnlicher Ausprägungen verschiedener meteorologischer Parameter auf den Stammumfang heimischer Bäume auf der täglichen lokalen Skala, die Auswirkungen von extremen Temperatur- und Niederschlagsereignissen auf die Blühzeitpunkte heimischer Sträucher auf der wöchentlichen regionalen Skala, die Auswirkung von Temperaturextremen auf den Allgemeinzustand eines Ökosystems (NDVI) auf der wöchentlichen kontinentalen Skala und der Einfluss von El Nino und La Nina Events auf Niedeschlagsanomalien auf der saisonalen globalen Skala. Schließlich soll die Veröffentlichung einer R-Implementierung der Methodik andere Wissenschaftler zur Nutzung letzterer befähigen und diese bei der Beantwortung weiterer Forschungsfragen unterstützen. KW - vegetation KW - event coincidence analysis KW - climate extreme events KW - climate impacts KW - Vegetation KW - Event Koinzidenz Analyse KW - extreme Klimaereignisse Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-407095 ER - TY - GEN A1 - Siegmund, Jonatan Frederik A1 - Sanders, Tanja G. M. A1 - Heinrich, Ingo A1 - Maaten, Ernst van der A1 - Simard, Sonia A1 - Helle, Gerhard A1 - Donner, Reik Volker T1 - Meteorological drivers of extremes in daily stem radius variations of beech, oak, and pine in Northeastern Germany BT - an event coincidence analysis T2 - Frontiers in plant science N2 - 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 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. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 456 KW - dendrometer measurements KW - event coincidence analysis KW - climate extremes KW - growth response Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-407943 ER - TY - GEN A1 - Siegmund, Jonatan Frederik A1 - Wiedermann, Marc A1 - Donges, Jonathan Friedemann A1 - Donner, Reik Volker T1 - Impact of temperature and precipitation extremes on the flowering dates of four German wildlife shrub species T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Ongoing climate change is known to cause an increase in the frequency and amplitude of local temperature and precipitation extremes in many regions of the Earth. While gradual changes in the climatological conditions have already been shown to strongly influence plant flowering dates, the question arises if and how extremes specifically impact the timing of this important phenological phase. Studying this question calls for the application of statistical methods that are tailored to the specific properties of event time series. Here, we employ event coincidence analysis, a novel statistical tool that allows assessing whether or not two types of events exhibit similar sequences of occurrences in order to systematically quantify simultaneities between meteorological extremes and the timing of the flowering of four shrub species across Germany. Our study confirms previous findings of experimental studies by highlighting the impact of early spring temperatures on the flowering of the investigated plants. However, previous studies solely based on correlation analysis do not allow deriving explicit estimates of the strength of such interdependencies without further assumptions, a gap that is closed by our analysis. In addition to direct impacts of extremely warm and cold spring temperatures, our analysis reveals statistically significant indications of an influence of temperature extremes in the autumn preceding the flowering. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 497 KW - event coincidence analysis KW - climate-change KW - weather extremes KW - plant phenology KW - interannual variability KW - air-temperature KW - responses KW - drought KW - trends KW - summer Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-408352 SN - 1866-8372 IS - 497 ER - TY - GEN A1 - Baumbach, Lukas A1 - Siegmund, Jonatan Frederik A1 - Mittermeier, Magdalena A1 - Donner, Reik Volker T1 - Impacts of temperature extremes on European vegetation during the growing season T2 - Postprints der Universität Potsdam : Mathematisch Naturwissenschaftliche Reihe N2 - Temperature is a key factor controlling plant growth and vitality in the temperate climates of the mid-latitudes like in vast parts of the European continent. Beyond the effect of average conditions, the timings and magnitudes of temperature extremes play a particularly crucial role, which needs to be better understood in the context of projected future rises in the frequency and/or intensity of such events. In this work, we employ event coincidence analysis (ECA) to quantify the likelihood of simultaneous occurrences of extremes in daytime land surface temperature anomalies (LSTAD) and the normalized difference vegetation index (NDVI). We perform this analysis for entire Europe based upon remote sensing data, differentiating between three periods corresponding to different stages of plant development during the growing season. In addition, we analyze the typical elevation and land cover type of the regions showing significantly large event coincidences rates to identify the most severely affected vegetation types. Our results reveal distinct spatio-temporal impact patterns in terms of extraordinarily large co-occurrence rates between several combinations of temperature and NDVI extremes. Croplands are among the most frequently affected land cover types, while elevation is found to have only a minor effect on the spatial distribution of corresponding extreme weather impacts. These findings provide important insights into the vulnerability of European terrestrial ecosystems to extreme temperature events and demonstrate how event-based statistics like ECA can provide a valuable perspective on environmental nexuses. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 642 KW - event coincidence analysis KW - Central Great-Plains KW - climate-change KW - precipitation extremes KW - weather extremes KW - soil-moisture KW - time-series KW - NDVI KW - phenology KW - trends Y1 - 2019 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-418018 SN - 1866-8372 IS - 642 SP - 4891 EP - 4903 ER -