The effects of differing drought-heat signatures on terrestrial carbon dynamics and vegetation composition using dynamic vegetation modelling

The global carbon cycle is essential for many aspects of the climate system and life in general. Within this carbon cycle, the natural terrestrial carbon sink plays an important role removing CO2 from the atmosphere. Many factors influence this terrestrial cycle, particularly climate variability, both natural and human-made. Especially in the face of global warming, the evolution of the natural carbon sink is quite uncertain. In particular, the effects of extreme weather and climate events, which are expected to become more frequent and more severe in the future, on the carbon cycle are hard to quantify, since the extremes themselves are also associated with uncertainties. To contribute to the ever-growing scientific field of carbon cycle and extreme event research, this thesis is concerned with analysing the effects of differing drought-heat signatures on terrestrial carbon dynamics using dynamic vegetation modelling. We built six hypothetical 100-year long climate scenarios which differ in their occurrence frequency of hot and dry extremes. They are based on a large ensemble simulation generated by the climate model EC-Earth. This data has several advantages. Firstly, it represents present-day climate without any trends. Secondly, it is available on a global grid, and thirdly, it offers a very long time series, which is needed to study extreme events in order to have a large enough sample size. The scenarios only differ in their extreme occurrence, but are similar in their global means. However, the data does present some regional biases which have a potentially large impact on modelled impacts. The scenarios are described and characterized in Chapter 2. The six hypothetical scenarios were used to run the dynamic global vegetation model LPX-Bern v1.4, as well as five additional dynamic global vegetation models. The models were run using constant CO2 concentrations and not allowing any land-atmosphere feedbacks which might change our initially sampled scenarios. They also only consider natural vegetation, meaning no crops or other land uses. The LPX-Bern results, described in detail in Chapter 3, show clear differences between scenarios as well as between climate zones. While trees thrive under climate scenarios with few extremes or only hot extremes, especially in higher latitudes, they show a clear reduction in coverage for dry extremes and especially compound hot and dry extremes. The relatively large increase in tree coverage in high latitudes under more hot extremes is associated with an increased growing season length in these regions which are generally energy-limited. Grasses tend to compensate the changes in tree coverage to some extent. Changes in tree coverage are also associated with changes in plant productivity and carbon stored in vegetation. Most of these results are shown as global means with regional differences being potentially large. Chapter 4 discusses the comparison of different vegetation models all run with the same input scenarios. The carbon variables are comparable between the models in the global mean, but we see quite large differences in vegetation coverage, most likely due to biases in the input data. Regionally, these differences may be even larger. There is still overall agreement between the models that a compound hot and dry climate leads to a reduction in tree coverage with an associated reduction in carbon stored in vegetation. The scenario with frequent dry extremes suggests similar results, with slightly less agreement between the models. The effects of a climate with hot extremes and those of a climate with no compound extremes are generally small. Large differences can be seen in a climate with no extreme events at all, where some models simulate an increase in vegetation and others a decrease. However, it is clear that compound hot and dry events are associated with a reduction of carbon stored on land. Our results suggest a possible reduction in the natural land carbon sink under future climate change. The coupling of temperature and precipitation can vary substantially between models and biases can exist in the input data. Therefore, results can differ when studying compound events. This thesis contributes to the understanding of feedbacks and processes concerning variable interaction, which is crucial to improve models. The field of compound event research is still emerging and ever-growing and there is still a lot to investigate when it comes to the effects of extremes on the terrestrial carbon cycle. Future work could focus on other types of compound events, such as temporally compounding or preconditioning, or different impact models could be used, for example, crop or fire models

Identifying meteorological drivers of extreme impacts: an application to simulated crop yields

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.DFG, 251036843, GRK 2043: Naturgefahren und Risiken in einer Welt im Wande

Balancing competing needs in kidney transplantation: does an allocation system prioritizing children affect the renal transplant function?

Children often merit priority in access to deceased donor kidneys by organ-sharing organizations. We report the impact of the new Swiss Organ Allocation System (SOAS) introduced in 2007, offering all kidney allografts from deceased donors <60 years preferentially to children. The retrospective cohort study included all paediatric transplant patients (<20 years of age) before (n = 19) and after (n = 32) the new SOAS (from 2001 to 2014). Estimated glomerular filtration rate (eGFR), urine protein-to-creatinine ratio (UPC), need for antihypertensive medication, waiting times to kidney transplantation (KTX), number of pre-emptive transplantations and rejections, and the proportion of living donor transplants were considered as outcome parameters. Patients after the new SOAS had significantly better eGFRs 2 years after KTX (Mean Difference, MD = 25.7 ml/min/1.73 m(2) , P = 0.025), lower UPC ratios (Median Difference, MeD = -14.5 g/mol, P = 0.004), decreased waiting times to KTX (MeD = -97 days, P = 0.021) and a higher proportion of pre-emptive transplantations (Odds Ratio = 9.4, 95% CI = 1.1-80.3, P = 0.018), while the need for antihypertensive medication, number of rejections and living donor transplantations remained stable. The new SOAS is associated with improved short-term clinical outcomes and more rapid access to KTX. Despite lacking long-term research, the study results should encourage other policy makers to adopt the SOAS approach

Etude sur le suicide en Valais

[Table des matières] 1. Thème. 2. Définitions. 3. Méthodes et données. 3.1. Recherche de littérature. 3.2. Récolte des données. 3.3. Données. 4. Analyse des données. 4.1. Situation générale. 4. 2. Constats valaisans. 4.3. Les taux de mortalité par suicide. 4. 4. Comparaisons des sources. 4.5. Comparaison des phénomènes. 4. 5. Tentatives de suicide. 5. Discussion. 5.1. Résultats principaux. 5.2. Force et faiblesse de l'étude. 5.3. Valeur de cette étude. 5.4. Questions ouvertes. 6. Recommandations. 7. Sites internet avec des informations intéressantes. 8. Annexes. 8.1. Etiologie du suicide. 8.2. Concept de prévention (conditions, types de prévention, niveaux des interventions préventives). 8.3. Programmes - Recommandations professionnelles - Recherche (Suisse, étranger, recherches). 8.4. Littérature

Countrywide climate features during recorded climate-related disasters

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk

Countrywide climate features during recorded climate-related disasters

Climate-related disasters cause substantial disruptions to human societies. With climate change, many extreme weather and climate events are expected to become more severe and more frequent. The International Disaster Database (EM-DAT) records climate-related disasters associated with observed impacts such as affected people and economic damage on a country basis. Although disasters are classified into different meteorological categories, they are usually not linked to observed climate anomalies. Here, we investigate countrywide climate features associated with disasters that have occurred between 1950 and 2015 and have been classified as droughts, floods, heat waves, and cold waves using superposed epoch analysis. We find that disasters classified as heat waves are associated with significant countrywide increases in annual mean temperature of on average 0.13 ∘C and a significant decrease in annual precipitation of 3.2%. Drought disasters show positive temperature anomalies of 0.08 ∘C and a 4.8 % precipitation decrease. Disasters classified as droughts and heat waves are thus associated with significant annual countrywide anomalies in both temperature and precipitation. During years of flood disasters, precipitation is increased by 2.8 %. Cold wave disasters show no significant signal for either temperature or precipitation. We further find that climate anomalies tend to be larger in smaller countries, an expected behavior when computing countrywide averages. In addition, our results suggest that extreme weather disasters in developed countries are typically associated with larger climate anomalies compared to developing countries. This effect could be due to different levels of vulnerability, as a climate anomaly needs to be larger in a developed country to cause a societal disruption. Our analysis provides a first link between recorded climate-related disasters and observed climate data, which is an important step towards linking climate and impact communities and ultimately better constraining future disaster risk.ISSN:0165-0009ISSN:1573-148

Gesundheitsförderungs- und Präventionskonzept für den Kanton Wallis 2001-2004 : Rahmenkonzept und Massnahmen

1. Zusammenfassung. 1.1. Rechtlicher Rahmen. 1.2. Organe und Aufgaben. 1.3. Grundlagen und Berichte. 2.1. Ziele im Bereich der Gesundheitsförderung und der Verhütung von Krankheiten und Unfällen. 2.2. Die Aufgaben des Gesundheitswesens im Bereich der Gesundheitsförderung und Prävention. 3. Deckungsbereich. 4. Kontext, Rahmen : Kanton Wallis. 4.1. Bedarfsevaluation : Bericht über den Gesundheitszustand der Walliser Bevölkerung 2000. 4.2. Geschichtlicher Hintergrund. 4.3. Rolle der Kantonalen Kommission für Gesundheitsförderung. 4.4. Mandate an das Institut für Sozial- und Präventivmedizin der Universität Lausanne. 4.5. Organigramm der Gesundheitsförderung, Krankheits- und Unfällprävention. 5. Gesundheitsförderungs- und Präventions- programm. 5.1. Projekteinreichungsverfahren. 5.2. Qualitäts- sicherung in der Gesundheitsförderung. 6. Aufgabenverteilung. 7. Budget 43. 8. Finanzierung. 9. Massnahmen nach bereichen und themen. 9.1. Die Verkehrsunfälle vrringern, den durchschnittlichen Alkoholkonsum senken, den Tabakkonsum verringern, Infektionskrankheiten (Aids) und den Durchimpfungsgrad erhöhen (Grippe), die Verhütung psychischer Krankheiten und die Förderung der psychischen Gesundheit, Verringerung der Haushalts-, Freizeit- und Arbeitsunfälle. 9.2. Das Informationssystem weiter ausbauen, die Früherkennung von Krankheiten verbessern, die Autonomie chronisch kranker Patienten erhöhen, Verbesserung der Ernährung, Prozentsatz der regelmässigen Sport treibenden erhöhen, notwendige Voraussetzung für die erfolgreiche soziale Integration, Gesundheitsförderung am Arbeitsplatz, für Kleinkinder, Verbesserung der Zahngesundheit Gesundheitsförderung in der Schule. 9.3. Aktuelle Problematik : Auseinandersetzung mit dem Freizeitkonsum psychotroper Substanzen (Haschich). 10.1. Beschreibung einer Gesundheitsförderungs- und Präventionsmassnahme. 10.2. Expertise de projets soumis à la CCPS / Gutachten der KKGF