@article{VogelPatonAich2021, author = {Vogel, Johannes and Paton, Eva Nora and Aich, Valentin}, title = {Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean}, series = {Biogeosciences}, volume = {18}, journal = {Biogeosciences}, edition = {22}, publisher = {Copernicus}, address = {G{\"o}ttingen}, issn = {1726-4189}, doi = {10.5194/bg-18-5903-2021}, pages = {5903 -- 5927}, year = {2021}, abstract = {Mediterranean ecosystems are particularly vulnerable to climate change and the associated increase in climate anomalies. This study investigates extreme ecosystem responses evoked by climatic drivers in the Mediterranean Basin for the time span 1999-2019 with a specific focus on seasonal variations as the seasonal timing of climatic anomalies is considered essential for impact and vulnerability assessment. A bivariate vulnerability analysis is performed for each month of the year to quantify which combinations of the drivers temperature (obtained from ERA5-Land) and soil moisture (obtained from ESA CCI and ERA5-Land) lead to extreme reductions in ecosystem productivity using the fraction of absorbed photosynthetically active radiation (FAPAR; obtained from the Copernicus Global Land Service) as a proxy. The bivariate analysis clearly showed that, in many cases, it is not just one but a combination of both drivers that causes ecosystem vulnerability. The overall pattern shows that Mediterranean ecosystems are prone to three soil moisture regimes during the yearly cycle: they are vulnerable to hot and dry conditions from May to July, to cold and dry conditions from August to October, and to cold conditions from November to April, illustrating the shift from a soil-moisture-limited regime in summer to an energy-limited regime in winter. In late spring, a month with significant vulnerability to hot conditions only often precedes the next stage of vulnerability to both hot and dry conditions, suggesting that high temperatures lead to critically low soil moisture levels with a certain time lag. In the eastern Mediterranean, the period of vulnerability to hot and dry conditions within the year is much longer than in the western Mediterranean. Our results show that it is crucial to account for both spatial and temporal variability to adequately assess ecosystem vulnerability. The seasonal vulnerability approach presented in this study helps to provide detailed insights regarding the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs. How to cite. Vogel, J., Paton, E., and Aich, V.: Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean, Biogeosciences, 18, 5903-5927, https://doi.org/10.5194/bg-18-5903-2021, 2021.}, language = {en} } @article{VogelRivoireDeiddaetal.2021, author = {Vogel, Johannes and Rivoire, Pauline and Deidda, Cristina and Rahimi, Leila and Sauter, Christoph A. and Tschumi, Elisabeth and van der Wiel, Karin and Zhang, Tianyi and Zscheischler, Jakob}, title = {Identifying meteorological drivers of extreme impacts}, series = {Earth System Dynamics}, volume = {12}, journal = {Earth System Dynamics}, issn = {2190-4987}, doi = {10.5194/esd-12-151-2021}, pages = {151 -- 172}, year = {2021}, abstract = {Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.}, language = {en} } @misc{VogelRivoireDeiddaetal.2021, author = {Vogel, Johannes and Rivoire, Pauline and Deidda, Cristina and Rahimi, Leila and Sauter, Christoph A. and Tschumi, Elisabeth and van der Wiel, Karin and Zhang, Tianyi and Zscheischler, Jakob}, title = {Identifying meteorological drivers of extreme impacts}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1126}, issn = {1866-8372}, doi = {10.25932/publishup-49627}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-496273}, pages = {151 -- 172}, year = {2021}, abstract = {Compound weather events may lead to extreme impacts that can affect many aspects of society including agriculture. Identifying the underlying mechanisms that cause extreme impacts, such as crop failure, is of crucial importance to improve their understanding and forecasting. In this study, we investigate whether key meteorological drivers of extreme impacts can be identified using the least absolute shrinkage and selection operator (LASSO) in a model environment, a method that allows for automated variable selection and is able to handle collinearity between variables. As an example of an extreme impact, we investigate crop failure using annual wheat yield as simulated by the Agricultural Production Systems sIMulator (APSIM) crop model driven by 1600 years of daily weather data from a global climate model (EC-Earth) under present-day conditions for the Northern Hemisphere. We then apply LASSO logistic regression to determine which weather conditions during the growing season lead to crop failure. We obtain good model performance in central Europe and the eastern half of the United States, while crop failure years in regions in Asia and the western half of the United States are less accurately predicted. Model performance correlates strongly with annual mean and variability of crop yields; that is, model performance is highest in regions with relatively large annual crop yield mean and variability. Overall, for nearly all grid points, the inclusion of temperature, precipitation and vapour pressure deficit is key to predict crop failure. In addition, meteorological predictors during all seasons are required for a good prediction. These results illustrate the omnipresence of compounding effects of both meteorological drivers and different periods of the growing season for creating crop failure events. Especially vapour pressure deficit and climate extreme indicators such as diurnal temperature range and the number of frost days are selected by the statistical model as relevant predictors for crop failure at most grid points, underlining their overarching relevance. We conclude that the LASSO regression model is a useful tool to automatically detect compound drivers of extreme impacts and could be applied to other weather impacts such as wildfires or floods. As the detected relationships are of purely correlative nature, more detailed analyses are required to establish the causal structure between drivers and impacts.}, language = {en} } @misc{VogelPatonAich2021, author = {Vogel, Johannes Joscha and Paton, Eva Nora and Aich, Valentin}, title = {Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, volume = {18}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, edition = {22}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {1866-8372}, doi = {10.25932/publishup-55497}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-554974}, pages = {5903 -- 5927}, year = {2021}, abstract = {Mediterranean ecosystems are particularly vulnerable to climate change and the associated increase in climate anomalies. This study investigates extreme ecosystem responses evoked by climatic drivers in the Mediterranean Basin for the time span 1999-2019 with a specific focus on seasonal variations as the seasonal timing of climatic anomalies is considered essential for impact and vulnerability assessment. A bivariate vulnerability analysis is performed for each month of the year to quantify which combinations of the drivers temperature (obtained from ERA5-Land) and soil moisture (obtained from ESA CCI and ERA5-Land) lead to extreme reductions in ecosystem productivity using the fraction of absorbed photosynthetically active radiation (FAPAR; obtained from the Copernicus Global Land Service) as a proxy. The bivariate analysis clearly showed that, in many cases, it is not just one but a combination of both drivers that causes ecosystem vulnerability. The overall pattern shows that Mediterranean ecosystems are prone to three soil moisture regimes during the yearly cycle: they are vulnerable to hot and dry conditions from May to July, to cold and dry conditions from August to October, and to cold conditions from November to April, illustrating the shift from a soil-moisture-limited regime in summer to an energy-limited regime in winter. In late spring, a month with significant vulnerability to hot conditions only often precedes the next stage of vulnerability to both hot and dry conditions, suggesting that high temperatures lead to critically low soil moisture levels with a certain time lag. In the eastern Mediterranean, the period of vulnerability to hot and dry conditions within the year is much longer than in the western Mediterranean. Our results show that it is crucial to account for both spatial and temporal variability to adequately assess ecosystem vulnerability. The seasonal vulnerability approach presented in this study helps to provide detailed insights regarding the specific phenological stage of the year in which ecosystem vulnerability to a certain climatic condition occurs. How to cite. Vogel, J., Paton, E., and Aich, V.: Seasonal ecosystem vulnerability to climatic anomalies in the Mediterranean, Biogeosciences, 18, 5903-5927, https://doi.org/10.5194/bg-18-5903-2021, 2021.}, language = {en} } @article{PatonVogelKlugeetal.2021, author = {Paton, Eva and Vogel, Johannes Joscha and Kluge, Bj{\"o}rn and Nehls, Thomas}, title = {Ausmaß, Trend und Extrema von D{\"u}rren im urbanen Raum}, series = {Hydrologie und Wasserbewirtschaftung}, volume = {65}, journal = {Hydrologie und Wasserbewirtschaftung}, number = {1}, publisher = {Bundesanstalt f{\"u}r Gew{\"a}sserkunde}, address = {Koblenz}, issn = {1439-1783}, doi = {10.5675/HyWa_2021.1_1}, pages = {5 -- 16}, year = {2021}, abstract = {Summers are currently perceived to be getting longer, hotter and more extreme - and this impression is reinforced in urban areas by the occurrence of heat island effects in densely built-up areas. To assess the real extent of increasing drought occurrences in German cities, a DWD data set of 31 urban climate stations for the period 1950 to 2019 was analysed using the standardised precipitation index (SPI) with regard to meteorological drought lengths, drought extrema, heat waves and compound events in the form of simultaneously occurring heat waves and drought months. The analysis shows a large degree of heterogeneity within Germany: a severe drought occurred in most cities in 2018, while the year 2018 was among the three years with the longest droughts (since 1950) for only one third of the cities. Some southern and central German cities show a statistically significant increase in drought months per decade since 1950, other cities, mostly in the north and northwest, only show an increase in the past two decades or even no trend at all. The compound analysis of simultaneously occurring heat and drought months shows a strong increase at most stations in the last two decades, whereby the two components are responsible with a very different proportion regionally for the increase in compound events.}, language = {de} } @article{AnsellStenoienGrundmannetal.2010, author = {Ansell, Stephen W. and Stenoien, Hans K. and Grundmann, Michael and Schneider, Harald and Hemp, Andreas and Bauer, N. and Russell, S. J. and Vogel, Johannes C.}, title = {Population structure and historical biogeography of European Arabidopsis lyrata}, issn = {0018-067X}, doi = {10.1038/Hdy.2010.10}, year = {2010}, abstract = {Understanding the natural history of model organisms is important for the effective use of their genomic resourses. Arabidopsis lyrata has emerged as a useful plant for studying ecological and evolutionary genetics, based on its extensive natural variation, sequenced genome and close relationship to A. thaliana. We studied genetic diversity across the entire range of European Arabidopsis lyrata ssp. petraea, in order to explore how population history has influenced population structure. We sampled multiple populations from each region, using nuclear and chloroplast genome markers, and combined population genetic and phylogeographic approaches. Within-population diversity is substantial for nuclear allozyme markers (mean P = 0.610, A(e) = 1.580, H-e = 0.277) and significantly partitioned among populations (F- ST = 0.271). The Northern populations have modestly increased inbreeding (F-IS = 0.163 verses F-IS = 0.093), but retain comparable diversity to central European populations. Bottlenecks are common among central and northern Europe populations, indicating recent demographic history as a dominant factor in structuring the European diversity. Although the genetic structure was detected at all geographic scales, two clear differentiated units covering northern and central European areas (F-CT = 0.155) were identified by Bayesian analysis and supported by regional pairwise F-CT calculations. A highly similar geographic pattern was observed from the distribution of chloroplast haplotypes, with the dominant northern haplotypes absent from central Europe. We conclude A. l. petraea's cold-tolerance and preference for disturbed habitats enabled glacial survival between the alpine and Nordic glaciers in central Europe and an additional cryptic refugium. While German populations are probable peri-glacial leftovers, Eastern Austrian populations have diversity patterns possibly compatible with longer-term survival.}, language = {en} } @article{MunnesHarschKnoblochetal.2022, author = {Munnes, Stefan and Harsch, Corinna and Knobloch, Marcel and Vogel, Johannes S. and Hipp, Lena and Schilling, Erik}, title = {Examining Sentiment in Complex Texts. A Comparison of Different Computational Approaches}, series = {Frontiers in Big Data}, volume = {5}, journal = {Frontiers in Big Data}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2624-909X}, doi = {10.3389/fdata.2022.886362}, pages = {16}, year = {2022}, abstract = {Can we rely on computational methods to accurately analyze complex texts? To answer this question, we compared different dictionary and scaling methods used in predicting the sentiment of German literature reviews to the "gold standard " of human-coded sentiments. Literature reviews constitute a challenging text corpus for computational analysis as they not only contain different text levels-for example, a summary of the work and the reviewer's appraisal-but are also characterized by subtle and ambiguous language elements. To take the nuanced sentiments of literature reviews into account, we worked with a metric rather than a dichotomous scale for sentiment analysis. The results of our analyses show that the predicted sentiments of prefabricated dictionaries, which are computationally efficient and require minimal adaption, have a low to medium correlation with the human-coded sentiments (r between 0.32 and 0.39). The accuracy of self-created dictionaries using word embeddings (both pre-trained and self-trained) was considerably lower (r between 0.10 and 0.28). Given the high coding intensity and contingency on seed selection as well as the degree of data pre-processing of word embeddings that we found with our data, we would not recommend them for complex texts without further adaptation. While fully automated approaches appear not to work in accurately predicting text sentiments with complex texts such as ours, we found relatively high correlations with a semiautomated approach (r of around 0.6)-which, however, requires intensive human coding efforts for the training dataset. In addition to illustrating the benefits and limits of computational approaches in analyzing complex text corpora and the potential of metric rather than binary scales of text sentiment, we also provide a practical guide for researchers to select an appropriate method and degree of pre-processing when working with complex texts.}, language = {en} } @misc{VolckmarHanPuetteretal.2016, author = {Volckmar, Anna-Lena and Han, Chung-Ting and P{\"u}tter, Carolin and Haas, Stefan and Vogel, Carla I. G. and Knoll, Nadja and Struve, Christoph and G{\"o}bel, Maria and Haas, Katharina and Herrfurth, Nikolas and Jarick, Ivonne and Grallert, Harald and Sch{\"u}rmann, Annette and Al- Hasani, Hadi and Hebebrand, Johannes and Sauer, Sascha and Hinney, Anke}, title = {Analysis of genes involved in body weight regulation by targeted re-sequencing}, series = {PLoS ONE}, journal = {PLoS ONE}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-410289}, pages = {16}, year = {2016}, abstract = {Introduction Genes involved in body weight regulation that were previously investigated in genome-wide association studies (GWAS) and in animal models were target-enriched followed by massive parallel next generation sequencing. Methods We enriched and re-sequenced continuous genomic regions comprising FTO, MC4R, TMEM18, SDCCAG8, TKNS, MSRA and TBC1D1 in a screening sample of 196 extremely obese children and adolescents with age and sex specific body mass index (BMI) >= 99th percentile and 176 lean adults (BMI <= 15th percentile). 22 variants were confirmed by Sanger sequencing. Genotyping was performed in up to 705 independent obesity trios (extremely obese child and both parents), 243 extremely obese cases and 261 lean adults. Results and Conclusion We detected 20 different non-synonymous variants, one frame shift and one nonsense mutation in the 7 continuous genomic regions in study groups of different weight extremes. For SNP Arg695Cys (rs58983546) in TBC1D1 we detected nominal association with obesity (p(TDT) = 0.03 in 705 trios). Eleven of the variants were rare, thus were only detected heterozygously in up to ten individual(s) of the complete screening sample of 372 individuals. Two of them (in FTO and MSRA) were found in lean individuals, nine in extremely obese. In silico analyses of the 11 variants did not reveal functional implications for the mutations. Concordant with our hypothesis we detected a rare variant that potentially leads to loss of FTO function in a lean individual. For TBC1D1, in contrary to our hypothesis, the loss of function variant (Arg443Stop) was found in an obese individual. Functional in vitro studies are warranted.}, language = {en} } @article{Vogel2022, author = {Vogel, Johannes}, title = {Drivers of phenological changes in southern Europe}, series = {International Journal of Biometeorology}, volume = {66}, journal = {International Journal of Biometeorology}, number = {9}, publisher = {Springer}, address = {New York}, issn = {0020-7128}, doi = {10.1007/s00484-022-02331-0}, pages = {1903 -- 1914}, year = {2022}, abstract = {The life cycle of plants is largely determined by climate, which renders phenological responses to climate change a highly suitable bioindicator of climate change. Yet, it remains unclear, which are the key drivers of phenological patterns at certain life stages. Furthermore, the varying responses of species belonging to different plant functional types are not fully understood. In this study, the role of temperature and precipitation as environmental drivers of phenological changes in southern Europe is assessed. The trends of the phenophases leaf unfolding, flowering, fruiting, and senescence are quantified, and the corresponding main environmental drivers are identified. A clear trend towards an earlier onset of leaf unfolding, flowering, and fruiting is detected, while there is no clear pattern for senescence. In general, the advancement of leaf unfolding, flowering and fruiting is smaller for deciduous broadleaf trees in comparison to deciduous shrubs and crops. Many broadleaf trees are photoperiod-sensitive; therefore, their comparatively small phenological advancements are likely the effect of photoperiod counterbalancing the impact of increasing temperatures. While temperature is identified as the main driver of phenological changes, precipitation also plays a crucial role in determining the onset of leaf unfolding and flowering. Phenological phases advance under dry conditions, which can be linked to the lack of transpirational cooling leading to rising temperatures, which subsequently accelerate plant growth.}, language = {en} } @misc{VogelPatonAichetal.2021, author = {Vogel, Johannes and Paton, Eva and Aich, Valentin and Bronstert, Axel}, title = {Increasing compound warm spells and droughts in the Mediterranean Basin}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1127}, issn = {1866-8372}, doi = {10.25932/publishup-49629}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-496294}, pages = {16}, year = {2021}, abstract = {The co-occurrence of warm spells and droughts can lead to detrimental socio-economic and ecological impacts, largely surpassing the impacts of either warm spells or droughts alone. We quantify changes in the number of compound warm spells and droughts from 1979 to 2018 in the Mediterranean Basin using the ERA5 data set. We analyse two types of compound events: 1) warm season compound events, which are extreme in absolute terms in the warm season from May to October and 2) year-round deseasonalised compound events, which are extreme in relative terms respective to the time of the year. The number of compound events increases significantly and especially warm spells are increasing strongly - with an annual growth rates of 3.9 (3.5) \% for warm season (deseasonalised) compound events and 4.6 (4.4) \% for warm spells -, whereas for droughts the change is more ambiguous depending on the applied definition. Therefore, the rise in the number of compound events is primarily driven by temperature changes and not the lack of precipitation. The months July and August show the highest increases in warm season compound events, whereas the highest increases of deseasonalised compound events occur in spring and early summer. This increase in deseasonalised compound events can potentially have a significant impact on the functioning of Mediterranean ecosystems as this is the peak phase of ecosystem productivity and a vital phenophase.}, language = {en} }