Suchergebnisse

1. Climate extremes and their implications for impact modeling: A short introduction / Jana Sillmann and Sebastian Sippel -- 2. Climate scenarios and their relevance and implications for impact studies / Claudia Tebaldi and Brian O'Neill -- 3. Changes in climate extremes in observations and climate model simulations. From the past into the future / Markus Donat, Jana Sillmann and Erich Fischer -- 4. Multivariate extremes and compound events / Jakob Zscheischler, Bart van den Hurk, Philip Ward and Seth Westra -- 5. Bias-correction of climate model output for impact models / Alex J. Cannon, Claudio Piani and Sebastian Sippel -- 6. Anthropogenic changes in tropical cyclones and its impacts / Michael Wehner -- 7. Machine Learning Applications for Agricultural Impacts Under Extreme Events / Carlos Felipe Gaitan -- 8. Assessing the F rance 2016 extreme wheat production loss -- evaluating our operational capacity to predict complex compound events / Marijn Van der Velde, Rémi Lecerf, Raphaël d'Andrimont and Tamara Ben-Ari -- 9. Probabilistic drought risk analysis for even-aged forests / Marcel Van Oijen and Miguel Angel de Zavala -- 10. Projecting health impacts of climate extremes: a methodological overview / Ana Maria Vicedo-Cabrera, Francesco Sera and Antonio Gasparrini -- 11. Climate extremes and their implications for impact modelling in transport / Maria Pregnolato, David Jaroszweski, Alistair Ford and Richard Dawson -- 12. Assessing Vulnerability and Risk of Climate Change Bapon SHM Fakhruddin, Kate Boylan, Alec Wild and Rebekah Robertson -- 13. Data challenges limit our global understanding of humanitarian disasters triggered by climate extremes / Miguel D. Mahecha, Debarati Guha-Sapir, Jeroen Smits, Fabian Gans and Guido Kraemer -- 14. Adaptive capacity of coupled socio-ecological systems to absorb climate extremes / Anja Rammig, Michael Bahn, Carolina Vera, Thomas Knoke, Carola Paul, Björn Vollan, Karlheinz Erb, Richard Bardgett, Stefan Liehr, Sandra Lavorel and Kirsten Thonicke -- 15. Impacts of Extreme Events on Medieval Societies: Lesson from Climate History / Martin Bauch -- 16. Climate Extremes and Conflict Dynamics / Jürgen Scheffran -- 17. Avoiding impacts and impacts avoided -- new frontiers in impact science for adaptation research and policy relevant assessments / Carl-Friedrich Schleussner and Benoit P. Guillod -- 18. Outlook: Challenges for societal resilience under climate extremesOutlook / Markus Reichstein, Dorothea Frank, Jana Sillmann and Sebastian Sippel.

Abstract
Recent extreme weather events and their impacts on societies have highlighted the need for timely adaptation to the changing odds of their occurrence. Such measures require appropriate information about likely changes in event frequency and magnitude on relevant spatiotemporal scales. However, to support robust climate information for decision-making, an effective communication between scientists and stakeholders is crucial. In this context, weather event attribution studies are increasingly raising attention beyond academic circles, although the understanding of how to take it beyond academia is still evolving. This paper presents the results of a study that involved in-depth interviews with stakeholders from a range of sectors about potential applications and the general usefulness of event attribution studies. A case study of the hot and dry summer 2012 in southeast Europe is used as a concrete example, with a focus on the applicability of attribution results across sectors. An analysis of the interviews reveals an abundant interest among the interviewed stakeholders and highlights the need for information on the causes and odds of extreme events, in particular on regional scales. From this data key aspects of stakeholder engagement are emerging, which could productively feed back into how probabilistic event attribution studies are designed and communicated to ensure practical relevance and usefulness for the stakeholder community.

Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. ; TRY initiative on plant traits German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. European Union's Horizon 2020 project BACI 640176 University of Zurich University Research Priority Program on Global Change and Biodiversity National Science Foundation (NSF) 20-508 NOMIS grant of Remotely Sensing Ecological Genomics Max Planck Society via its fellowship programme German Research Foundation (DFG) RU 1536/3-1 project Resilient Forests of the Dutch Ministry of Economic Affairs KB-29-009-003 EU-FP7-KBBE project: BACCARA-Biodiversity and climate change, a risk analysis 226299 Australian Research Council DP170103410 European Research Council (ERC) ERC-SyG-2013-610028 IMBALANCE-P VIDI by the Netherlands Organization of Scientific Research 016.161.318 II. Oldenburgischer Deichband Wasserverbandstag e.V. NWS 10/05 Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 369617/2017-2 307689/2014-0 National Research Foundation of Korea (NRF) - Korea government (MSIT) 2018R1C1B6005351 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11150835 1200468 Russian Science Foundation (RSF) 19-14-00038 Future Earth ; Versión publicada - versión final del editor

The authors investigate the broad-scale climatological and soil properties that co-vary with major axes of plant functional traits. They find that variation in plant size is attributed to latitudinal gradients in water or energy limitation, while variation in leaf economics traits is attributed to both climate and soil fertility including their interaction. Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. ; The study was supported by the TRY initiative on plant traits (http://www.try-db. org). The TRY database is hosted at the Max Planck Institute for Biogeochemistry (MPI BGC, Germany) and supported by Future Earth and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. We would like to thank all PIs contributing to the TRY database, whose efforts allowed this analysis. In detail, we thank: J.H.C. Cornelissen, R. Milla, W. Cornwell, K. Kramer, S. Gachet, Ingolf Kühn, P. Poschlod, M. Scherer, J. Pausas, B. Sandal, K. Verheyen, J. Penuelas, N. Soudzilovskaia, P. Reich, J. Fang, S. Harrison, R. Gallagher, B. Hawkins, B. Finegan, J. Powers, F. Lenti, S. Higgins, B. Medlyn, H. Ford, V. Pillar, M. Bahn, E. Sosinski, T. He, B. Cerabolini, J. Cavender-Bares, I. J. Wright, F. Louault, B. Amiaud, G. Gonzalez-Melo, P. Adler, F. Schurr, J. Craine, Y. Niinemets, A. Zanne, H. Jactel, M. Harze, R. Montgomery, C. Römermann, T. Hickler, A. Pahl, M. Dainese, D. Kirkup, J. Dickie, W. Hattingh, P. Higuchi, T. Domingues, A. Araujo, M. Williams, C. Price, B. Shipley, L. Sack, B. Schamp, W. Han, Y. Onoda, K. Fleischer, J.P. Wright, G. Guerin, F. de Vries, D.D. Baldocchi, J. Kattge, B. Blonder, K. Brown, D. Campetella, G. Frechet, Q. Read, N. G. Swenson, V. Lanta, E. Weiher, M. Leishman, A. Siefert, M. Spasojevic, R. Jackson, J. Messier, S. J. Wright, D. Craven, J. Molofsky, P. Meir, E. Forey, A. Totte, C. Frenette Dussault, O. Atkin, F. Koike, D. Laughlin, S. Burrascano, K. Ollerer, N. Gross, A. Madhur, P. Begonna, B. Bond-Lamberty, B. von Holle, W. Green, B. Yguel, A. C. Malhado, P. Manning, G. Zotz, E. Lamb, J. Fagundez, Z. Wang, S. Diaz, C. Byun, W. Bond, B. Enquist, C. Baraloto, P. Manning, M. Kleyer, W. Ozinga, J. Ordonez, J. Lloyd, H. Poorter, E. Garnier, F. Valladares, C. Pladevall, G. Freschet, M. Moretti, H. Kurokawa, V. Minden, A. Demey, F. Férnandez-Méndez, J. Butterfield, T. Domingu, E. Swaine, L. Poorter, S. Shiodera, T. Chapin, M. Beckmann, J.A. Gutierrez, M. Mencuccini, S. Jansen, and N. J. B. Kraft. We appreciate the discussions at the MPI BGC. We thank F. Fazayeli for preparing the gap-filled trait data. We thank F. Gans and U. Weber for preparing ancillary data and B. Ahrens for pointing out some soil data availability. We acknowledge Environmental Systems Research Institute (ESRI) and its licensor(s) for the Geodata product of the Missions Database 'ArcWorld Supplement' (GMI), published by Global Mapping International and originated from Global Mapping International for producing Extended Data Fig. 1 and Supplementary Fig. 7 and available in ArcGIS software by ESRI. ArcGIS and ArcMap are the intellectual property of ESRI and are used herein under license. For more information about ESRI software, please visit www.esri.com. The authors affiliated with the MPI BGC acknowledge funding by the European Union's Horizon 2020 project BACI under grant agreement no. 640176. We are thankful to the data providers for the SoilGrids, hosted by ISRIC. J.S.J. acknowledges the International Max Planck Research School for global biogeochemical cycles. J.S.J., M.E.S. and M.C.S. acknowledge support from the University of Zurich University Research Priority Program on Global Change and Biodiversity. P.B.R., M.E.S. and M.C.S. acknowledge membership in the US NSF 20-508 BII-Implementation project, 'The causes and consequences of plant biodiversity across scales in a rapidly changing world'. M.E.S. acknowledges the NOMIS grant of Remotely Sensing Ecological Genomics that funds J.S.J. and M.C.S. C.W. acknowledges the support of the Max Planck Society via its fellowship programme. N.R. was funded by a research grant from Deutsche Forschungsgemeinschaft DFG (RU 1536/3-1). K.K. was supported by the project Resilient Forests (KB-29-009-003) of the Dutch Ministry of Economic Affairs. The trait data supplied were co-funded by the EU-FP7-KBBE project: BACCARA—Biodiversity and climate change, a risk analysis (project ID 226299). I.W. acknowledges support from the Australian Research Council (DP170103410). J.P. acknowledges financial support from the European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE-P. N.A.S. is financed by a VIDI grant (016.161.318) issued by the Netherlands Organization of Scientific Research. The data V.M. provided were funded by II. Oldenburgischer Deichband and the Wasserverbandstag e.V. (NWS 10/05). We thank M. Kleyer for his critical input. P.H. and V.D.P. have been supported by CNPq (grant nos 369617/2017-2 and 307689/2014-0, respectively). C.B. was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2018R1C1B6005351). A.G.G. was funded by FONDECYT grant nos 11150835 and 1200468. V.O. thanks Russian science foundation (RSF, 19-14-00038) for financial support.