ALBERT

Description: In coupled human-environment systems where well established and proven general theories are often lacking cluster analysis provides the possibility to discover regularities – a first step in empirically based theory building. The aim of this report is to share the experiences and knowledge on cluster analysis we gained in several applications in this realm helping to avoid typical problems and pitfalls. In our description of issues and methods we will highlight well-known main-stream methods as well as promising new developments, referring to pertinent literature for further information, thus offering also some potential new insights for the more experienced. The following aspects are discussed in detail: data-selection and pre-treatment, selection of a distance measure in the data space, selection of clustering method, performing clustering (parameterizing the algorithm(s), determining the number of clusters etc.) and the interpretation and evaluation of results. We link our description – as far as tools for performing the analysis are concerned - to the R software environment and its associated cluster analysis packages. We have used this public domain software, together with own tailor-made extensions, documented in the appendix.

Description: Historical agreed minimum discharges of river Elbe at the czech-german border profile Hřensko/Schöna Discharges of the river Elbe at the border profile between the Czech Republic and Germany at Hřensko/ Schöna play an essential role for the suitability of the German river section downstream for shipping. A cascade of reservoirs upstream the border profile was mainly built between 1950 and 1964. Since then a significant supplemental low water management at the boarder profile is possible. Although the low wa¬ter control at the German-Czech boarder profile is currently managed by a network of German and Czech institutions the legal basis of this management regime is currently not fully understood. In particular, the question raised weather current management targets for low water supplement can be seen based on still valid German-Czech agreements between the former states German Democratic Republic and Czech Slovakian Socialistic Republic. This report summarizes the chronological follow up of the construction of the Czech reservoir system and the related agreements between the German and Czech site.The authors have assembled the development of the effectively agreed minimum discharges at the border profile ČSSR/GDR at Hřensko/Schöna. The available joint coordination statements between ČSSR and GDR during the period April 1983 and May 1988 were reviewed and compared to the recorded discharges. The capacity for low water supplements at Hřensko/Schöna increased since 1900 from 143,58 Mil. m³ to 2 566,24 Mil. m³ in 2010. The greatest parts of the total storage capacity are located in the Vltava and in the Ohře river basin with storage capacities of 1 894,03 Mil. m³ and 404,35 Mil. m³, respectively. The Vltava cascade is currently managed in a way that a minimum discharge is guaranteed of about 40,0 m³/s at barrage Vrané. This compares to a natural discharge situation with minimum flows between 12,0 to 15,0 m³/s. The barrage system in the Ohře river system can currently ensure minimum discharges of about 8,00 m³/s compared with natural discharges between 1,50 and 2,00 m³/s. The boarder profile at Hřensko/ Schöna is directly affected by the reservoir control in Vltava and Ohře. The GDR made several efforts to agree with the ČSSR on minimum discharge levels for the river Elbe at the border profile at Hřensko/Schöna. After years of negotiations minimum monthly medial discharges (Min MQ month) were defined for a hydrological year starting from November until October. However, these monthly medial values still allowed for shortfalls at the daily scale. Based on the monthly medial values two coordination arrangements were concluded between the ČSSR and the GDR about the supply of minimum discharge at their joint border profile at Hřensko/Schöna. The first started in April, 1983 and was valid till 1990. The agreement was updated and extended in May, 1988 till 2000. The lastly agreed monthly minimum values range between 86,8 m³/s in August and 185,2 m³/s in April. Although an agreement about these values exists, it never had a legally binding character. However, these values are still used as orientation for the control of Czech reservoirs in practise. In the past, the agreed minimum discharges felled only once below the limit. In July 1964, the observed monthly discharge was 89,1 m³/s which is 7.1 m³/s short of the agreed value of 96,2 m³/s. Climate change might lead to a more frequent short fall of the once agreed minimum values. Considering this fact and the informal nature of the current target values for control a new formal framework for the minimum flow regime at the German-Czech boarder might be in the interest of the German water users downstream.

Description: A methodology to assess future development in patterns of vulnerability is presented which can support the assessment of global policies with regard to their impacts on specific vulnerabilities on the regional or local scale. Patterns of vulnerability, formalized by vulnerability profiles (e.g. for the livelihoods of dryland smallholder farmers) were investigated under different consistent indicator scenarios reflecting different global policies. After unfolding several principal possibilities to do such an analysis of temporal change in vulnerability patterns we could conclude that the concept of “Clusters of Change” (CoCs) is the most straight forward and promising approach. The main arguments are that each interpretation has necessarily to consider both, the starting situation and it’s change over time (”poor and heavily improving”, ”rich and stagnating” etc.). This implies that we are looking for patterns which represent typical combinations of present states AND expected future changes. An application of the CoC-concept to the drylands vulnerability patterns considering the indicator set for the present situation and the same indicator set for 2050 under a baseline scenario was performed as a test. Comparison of the present vulnerability cluster partition with the spatial distribution of the CoCs revealed that most of these clusters are separated into an improving and a deteriorating part which shows where winners and losers of the baseline scenario are – an interesting result which illustrates the appropriateness of the CoC – method. To explore the potential of CoCs for the dryland vulnerability we applied the method to two different sets of scenarios until 2050: a baseline vs. Climate policy scenario (OECD, 2012) and a ”policy first” scenario vs. ”security first” scenario (UNEP, 2007). The first one serves as an example for a policy assessment while the second compares the vulnerability consequences of two scenarios based on different story-lines of further global development. The main conclusion to be drawn from these calculations is that the CoCs are rather insensitive with regard to the small differences between the scenarios. Regarding the first set of scenarios the relatively short time horizon of relevant influences of climate policies on climate change impacts and several indicators which are not influenced at all generate only a very small difference. The only significant change in the resulting vulnerability profiles was in the values of change in water scarcity: it was lower for all profiles in the climate policy case. The second set of scenarios is not directly related to policy decisions but to different global story-lines which deviate stronger. This resulted in an increasing cluster number from 4 (policy first) to 5 (security first) clusters, about 20% of the pixels changing cluster membership, 3 clusters showing the same spatial extent for both scenarios but the 4th cluster (“policy first”) “losing” India which generates a separate cluster in the “security first” scenario. This allows for the interpretation that a further development according to the “security first”-storyline compared to the “policy first”-storyline would make a difference particularly for India. Closer inspection of the respective profile shows a qualitatively different situation indicating increased vulnerability compared to the “policy first” scenario where India shares one cluster with e.g., Northern Africa.

Description: Climate change and socioeconomic developments will have a decisive impact on people exposed to hunger. This study analyses climate change impacts on agriculture and potential implications for the occurrence of hunger under different socioeconomic scenarios for 2030, focusing on the world regions most affected by poverty today: the Middle East and North Africa, South Asia, and Sub-Saharan Africa. We use a spatially explicit, agroeconomic land-use model to assess agricultural vulnerability to climate change. The aims of our study are to provide spatially explicit projections of climate change impacts on Costs of Food, and to combine them with spatially explicit hunger projections for the year 2030, both under a poverty, as well as a prosperity scenario. Our model results indicate that while average yields decrease with climate change in all focus regions, the impact on the Costs of Food is very diverse. Costs of Food increase most in the Middle East and North Africa, where available agricultural land is already fully utilized and options to import food are limited. The increase is least in Sub-Saharan Africa, since production there can be shifted to areas which are only marginally affected by climate change and imports from other regions increase. South Asia and Sub-Saharan Africa can partly adapt to climate change, in our model, by modifying trade and expanding agricultural land. In the Middle East and North Africa, almost the entire population is affected by increasing Costs of Food, but the share of people vulnerable to hunger is relatively low, due to relatively strong economic development in these projections. In Sub-Saharan Africa, the Vulnerability to Hunger will persist, but increases in Costs of Food are moderate. While in South Asia a high share of the population suffers from increases in Costs of Food and is exposed to hunger, only a negligible number of people will be exposed at extreme levels. Independent of the region, the impacts of climate change are less severe in a richer and more globalized world. Adverse climate impacts on the Costs of Food could be moderated by promoting technological progress in agriculture. Improving market access would be advantageous for farmers, providing the opportunity to profitably increase production in the Middle East and North Africa as well as in South Asia, but may lead to increasing Costs of Food for consumers. In the long-term perspective until 2080, the consequences of climate change will become even more severe: while in 2030 56% of the global population may face increasing Costs of Food in a poor and fragmented world, in 2080 the proportion will rise to 73%.

Description: In den 10 Must-Knows aus der Biodiversitätsforschung legen 45 Wissenschaftlerinnen und Wissenschaftler fundiert und allgemein verständlich Fakten zur biologischen Vielfalt dar. Sie analysieren die komplexen Systeme der Erde, indem sie zehn Schlüsselbereiche hervorheben, von denen wiederum jeder untrennbar mit allen anderen verbunden ist. Sie zeigen Wege auf, um einen weiteren Verlust an Artenvielfalt und Ökosystemen zu stoppen und die biologische Vielfalt zu fördern. Ihr Ziel ist, für Politik und Gesellschaft wissenschaftlich gesicherte Bewertungen der aktuellen Erkenntnisse für bessere politische Entscheidungen und Maßnahmen auf lokaler, regionaler, nationaler und globaler Ebene zur Verfügung zu stellen, um die Vielfalt des Lebens – die Biodiversität – zu erhalten. Dies sind die 10MustKnows 2022: 1. Klima- und Biodiversitätsschutz zusammen verwirklichen 2. Planetare Gesundheit stärken 3. Unsichtbare Biodiversität beachten 4. Biokulturelle Lebensräume fördern 5. Wald nachhaltig nutzen 6. Landwirtschaft umbauen 7. Land und Ressourcen schützen 8. Transnationale Infrastrukturen und Bildung für Nachhaltigkeit 9. Zugang und offene Nutzung von Forschungsdaten sichern 10. Biodiversitätsfreundliche Anreize setzen