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In the last decade, the number and dimensions of catastrophic flooding events in the Niger River Basin (NRB) have markedly increased. Despite the devastating impact of the floods on the population and the mainly agriculturally based economy of the riverine nations, awareness of the hazards in policy and science is still low. The urgency of this topic and the existing research deficits are the motivation for the present dissertation.
The thesis is an initial detailed assessment of the increasing flood risk in the NRB. The research strategy is based on four questions regarding (1) features of the change in flood risk, (2) reasons for the change in the flood regime, (3) expected changes of the flood regime given climate and land use changes, and (4) recommendations from previous analysis for reducing the flood risk in the NRB.
The question examining the features of change in the flood regime is answered by means of statistical analysis. Trend, correlation, changepoint, and variance analyses show that, in addition to the factors exposure and vulnerability, the hazard itself has also increased significantly in the NRB, in accordance with the decadal climate pattern of West Africa. The northern arid and semi-arid parts of the NRB are those most affected by the changes.
As potential reasons for the increase in flood magnitudes, climate and land use changes are attributed by means of a hypothesis-testing framework. Two different approaches, based on either data analysis or simulation, lead to similar results, showing that the influence of climatic changes is generally larger compared to that of land use changes. Only in the dry areas of the NRB is the influence of land use changes comparable to that of climatic alterations.
Future changes of the flood regime are evaluated using modelling results. First ensembles of statistically and dynamically downscaled climate models based on different emission scenarios are analyzed. The models agree with a distinct increase in temperature. The precipitation signal, however, is not coherent. The climate scenarios are used to drive an eco-hydrological model. The influence of climatic changes on the flood regime is uncertain due to the unclear precipitation signal. Still, in general, higher flood peaks are expected. In a next step, effects of land use changes are integrated into the model. Different scenarios show that regreening might help to reduce flood peaks. In contrast, an expansion of agriculture might enhance the flood peaks in the NRB. Similarly to the analysis of observed changes in the flood regime, the impacts of climate- and land use changes for the future scenarios are also most severe in the dry areas of the NRB.
In order to answer the final research question, the results of the above analysis are integrated into a range of recommendations for science and policy on how to reduce flood risk in the NRB. The main recommendations include a stronger consideration of the enormous natural climate variability in the NRB and a focus on so called “no-regret” adaptation strategies which account for high uncertainty, as well as a stronger consideration of regional differences. Regarding the prevention and mitigation of catastrophic flooding, the most vulnerable and sensitive areas in the basin, the arid and semi-arid Sahelian and Sudano-Sahelian regions, should be prioritized. Eventually, an active, science-based and science-guided flood policy is recommended. The enormous population growth in the NRB in connection with the expected deterioration of environmental and climatic conditions is likely to enhance the region´s vulnerability to flooding. A smart and sustainable flood policy can help mitigate these negative impacts of flooding on the development of riverine societies in West Africa.
Anthropogenic activities have transformed the Earth's environment, not only on local level, but on the planetary-scale causing global change. Besides industrialization, agriculture is a major driver of global change. This change in turn impairs the agriculture sector, reducing crop yields namely due to soil degradation, water scarcity, and climate change. However, this is a more complex issue than it appears. Crop yields can be increased by use of agrochemicals and fertilizers which are mainly produced by fossil energy. This is important to meet the increasing food demand driven by global demographic change, which is further accelerated by changes in regional lifestyles. In this dissertation, we attempt to address this complex problem exploring agricultural potential globally but on a local scale. For this, we considered the influence of lifestyle changes (dietary patterns) as well as technological progress and their effects on climate change, mainly greenhouse gas (GHG) emissions. Furthermore, we examined options for optimizing crop yields in the current cultivated land with the current cropping patterns by closing yield gaps. Using this, we investigated in a five-minute resolution the extent to which food demand can be met locally, and/or by regional and/or global trade. Globally, food consumption habits are shifting towards calorie rich diets. Due to dietary shifts combined with population growth, the global food demand is expected to increase by 60-110% between 2005 and 2050. Hence, one of the challenges to global sustainability is to meet the growing food demand, while at the same time, reducing agricultural inputs and environmental consequences. In order to address the above problem, we used several freely available datasets and applied multiple interconnected analytical approaches that include artificial neural network, scenario analysis, data aggregation and harmonization, downscaling algorithm, and cross-scale analysis.
Globally, we identified sixteen dietary patterns between 1961 and 2007 with food intakes ranging from 1,870 to 3,400 kcal/cap/day. These dietary patterns also reflected changing dietary habits to meat rich diets worldwide. Due to the large share of animal products, very high calorie diets that are common in the developed world, exhibit high total per capita emissions of 3.7-6.1 kg CO2eq./day. This is higher than total per capita emissions of 1.4-4.5 kg CO2eq./day associated with low and moderate calorie diets that are common in developing countries. Currently, 40% of the global crop calories are fed to livestock and the feed calorie use is four times the produced animal calories. However, these values vary from less than 1 kcal to greater 10 kcal around the world. On the local and national scale, we found that the local and national food production could meet demand of 1.9 and 4.4 billion people in 2000, respectively. However, 1 billion people from Asia and Africa require intercontinental agricultural trade to meet their food demand. Nevertheless, these regions can become food self-sufficient by closing yield gaps that require location specific inputs and agricultural management strategies. Such strategies include: fertilizers, pesticides, soil and land improvement, management targeted on mitigating climate induced yield variability, and improving market accessibility. However, closing yield gaps in particular requires global N-fertilizer application to increase by 45-73%, P2O5 by 22-46%, and K2O by 2-3 times compare to 2010. Considering population growth, we found that the global agricultural GHG emissions will approach 7 Gt CO2eq./yr by 2050, while the global livestock feed demand will remain similar to 2000. This changes tremendously when diet shifts are also taken into account, resulting in GHG emissions of 20 Gt CO2eq./yr and an increase of 1.3 times in the crop-based feed demand between 2000 and 2050. However, when population growth, diet shifts, and technological progress by 2050 were considered, GHG emissions can be reduced to 14 Gt CO2eq./yr and the feed demand to nearly 1.8 times compare to that in 2000. Additionally, our findings shows that based on the progress made in closing yield gaps, the number of people depending on international trade can vary between 1.5 and 6 billion by 2050. In medium term, this requires additional fossil energy. Furthermore, climate change, affecting crop yields, will increase the need for international agricultural trade by 4% to 16%.
In summary, three general conclusions are drawn from this dissertation. First, changing dietary patterns will significantly increase crop demand, agricultural GHG emissions, and international food trade in the future when compared to population growth only. Second, such increments can be reduced by technology transfer and technological progress that will enhance crop yields, decrease agricultural emission intensities, and increase livestock feed conversion efficiencies. Moreover, international trade dependency can be lowered by consuming local and regional food products, by producing diverse types of food, and by closing yield gaps. Third, location specific inputs and management options are required to close yield gaps. Sustainability of such inputs and management largely depends on which options are chosen and how they are implemented. However, while every cultivated land may not need to attain its potential yields to enable food security, closing yield gaps only may not be enough to achieve food self-sufficiency in some regions. Hence, a combination of sustainable implementations of agricultural intensification, expansion, and trade as well as shifting dietary habits towards a lower share of animal products is required to feed the growing population.
Permafrost, defined as ground that is frozen for at least two consecutive years, is a distinct feature of the terrestrial unglaciated Arctic. It covers approximately one quarter of the land area of the Northern Hemisphere (23,000,000 km²). Arctic landscapes, especially those underlain by permafrost, are threatened by climate warming and may degrade in different ways, including active layer deepening, thermal erosion, and development of rapid thaw features. In Siberian and Alaskan late Pleistocene ice-rich Yedoma permafrost, rapid and deep thaw processes (called thermokarst) can mobilize deep organic carbon (below 3 m depth) by surface subsidence due to loss of ground ice. Increased permafrost thaw could cause a feedback loop of global significance if its stored frozen organic carbon is reintroduced into the active carbon cycle as greenhouse gases, which accelerate warming and inducing more permafrost thaw and carbon release. To assess this concern, the major objective of the thesis was to enhance the understanding of the origin of Yedoma as well as to assess the associated organic carbon pool size and carbon quality (concerning degradability). The key research questions were:
- How did Yedoma deposits accumulate?
- How much organic carbon is stored in the Yedoma region?
- What is the susceptibility of the Yedoma region's carbon for future decomposition?
To address these three research questions, an interdisciplinary approach, including detailed field studies and sampling in Siberia and Alaska as well as methods of sedimentology, organic biogeochemistry, remote sensing, statistical analyses, and computational modeling were applied. To provide a panarctic context, this thesis additionally includes results both from a newly compiled northern circumpolar carbon database and from a model assessment of carbon fluxes in a warming Arctic.
The Yedoma samples show a homogeneous grain-size composition. All samples were poorly sorted with a multi-modal grain-size distribution, indicating various (re-) transport processes. This contradicts the popular pure loess deposition hypothesis for the origin of Yedoma permafrost. The absence of large-scale grinding processes via glaciers and ice sheets in northeast Siberian lowlands, processes which are necessary to create loess as material source, suggests the polygenetic origin of Yedoma deposits.
Based on the largest available data set of the key parameters, including organic carbon content, bulk density, ground ice content, and deposit volume (thickness and coverage) from Siberian and Alaskan study sites, this thesis further shows that deep frozen organic carbon in the Yedoma region consists of two distinct major reservoirs, Yedoma deposits and thermokarst deposits (formed in thaw-lake basins). Yedoma deposits contain ~80 Gt and thermokarst deposits ~130 Gt organic carbon, or a total of ~210 Gt. Depending on the approach used for calculating uncertainty, the range for the total Yedoma region carbon store is ±75 % and ±20 % for conservative single and multiple bootstrapping calculations, respectively. Despite the fact that these findings reduce the Yedoma region carbon pool by nearly a factor of two compared to previous estimates, this frozen organic carbon is still capable of inducing a permafrost carbon feedback to climate warming. The complete northern circumpolar permafrost region contains between 1100 and 1500 Gt organic carbon, of which ~60 % is perennially frozen and decoupled from the short-term carbon cycle.
When thawed and reintroduced into the active carbon cycle, the organic matter qualities become relevant. Furthermore, results from investigations into Yedoma and thermokarst organic matter quality studies showed that Yedoma and thermokarst organic matter exhibit no depth-dependent quality trend. This is evidence that after freezing, the ancient organic matter is preserved in a state of constant quality. The applied alkane and fatty-acid-based biomarker proxies including the carbon-preference and the higher-land-plant-fatty-acid indices show a broad range of organic matter quality and thus no significantly different qualities of the organic matter stored in thermokarst deposits compared to Yedoma deposits. This lack of quality differences shows that the organic matter biodegradability depends on different decomposition trajectories and the previous decomposition/incorporation history. Finally, the fate of the organic matter has been assessed by implementing deep carbon pools and thermokarst processes in a permafrost carbon model. Under various warming scenarios for the northern circumpolar permafrost region, model results show a carbon release from permafrost regions of up to ~140 Gt and ~310 Gt by the years 2100 and 2300, respectively. The additional warming caused by the carbon release from newly-thawed permafrost contributes 0.03 to 0.14°C by the year 2100. The model simulations predict that a further increase by the 23rd century will add 0.4°C to global mean surface air temperatures.
In conclusion, Yedoma deposit formation during the late Pleistocene was dominated by water-related (alluvial/fluvial/lacustrine) as well as aeolian processes under periglacial conditions. The circumarctic permafrost region, including the Yedoma region, contains a substantial amount of currently frozen organic carbon. The carbon of the Yedoma region is well-preserved and therefore available for decomposition after thaw. A missing quality-depth trend shows that permafrost preserves the quality of ancient organic matter. When the organic matter is mobilized by deep degradation processes, the northern permafrost region may add up to 0.4°C to the global warming by the year 2300.
The Arctic is considered as a focal region in the ongoing climate change debate. The currently observed and predicted climate warming is particularly pronounced in the high northern latitudes. Rising temperatures in the Arctic cause progressive deepening and duration of permafrost thawing during the arctic summer, creating an ‘active layer’ with high bioavailability of nutrients and labile carbon for microbial consumption. The microbial mineralization of permafrost carbon creates large amounts of greenhouse gases, including carbon dioxide and methane, which can be released to the atmosphere, creating a positive feedback to global warming. However, to date, the microbial communities that drive the overall carbon cycle and specifically methane production in the Arctic are poorly constrained. To assess how these microbial communities will respond to the predicted climate changes, such as an increase in atmospheric and soil temperatures causing increased bioavailability of organic carbon, it is necessary to investigate the current status of this environment, but also how these microbial communities reacted to climate changes in the past. This PhD thesis investigated three records from two different study sites in the Russian Arctic, including permafrost, lake shore and lake deposits from Siberia and Chukotka. A combined stratigraphic approach of microbial and molecular organic geochemical techniques were used to identify and quantify characteristic microbial gene and lipid biomarkers. Based on this data it was possible to characterize and identify the climate response of microbial communities involved in past carbon cycling during the Middle Pleistocene and the Late Pleistocene to Holocene. It is shown that previous warmer periods were associated with an expansion of bacterial and archaeal communities throughout the Russian Arctic, similar to present day conditions. Different from this situation, past glacial and stadial periods experienced a substantial decrease in the abundance of Bacteria and Archaea. This trend can also be confirmed for the community of methanogenic archaea that were highly abundant and diverse during warm and particularly wet conditions. For the terrestrial permafrost, a direct effect of the temperature on the microbial communities is likely. In contrast, it is suggested that the temperature rise in scope of the glacial-interglacial climate variations led to an increase of the primary production in the Arctic lake setting, as can be seen in the corresponding biogenic silica distribution. The availability of this algae-derived carbon is suggested to be a driver for the observed pattern in the microbial abundance. This work demonstrates the effect of climate changes on the community composition of methanogenic archae. Methanosarcina-related species were abundant throughout the Russian Arctic and were able to adapt to changing environmental conditions. In contrast, members of Methanocellales and Methanomicrobiales were not able to adapt to past climate changes. This PhD thesis provides first evidence that past climatic warming led to an increased abundance of microbial communities in the Arctic, closely linked to the cycling of carbon and methane production. With the predicted climate warming, it may, therefore, be anticipated that extensive amounts of microbial communities will develop. Increasing temperatures in the Arctic will affect the temperature sensitive parts of the current microbiological communities, possibly leading to a suppression of cold adapted species and the prevalence of methanogenic archaea that tolerate or adapt to increasing temperatures. These changes in the composition of methanogenic archaea will likely increase the methane production potential of high latitude terrestrial regions, changing the Arctic from a carbon sink to a source.
Die Anpassung von Sektoren an veränderte klimatische Bedingungen erfordert ein Verständnis von regionalen Vulnerabilitäten. Vulnerabilität ist als Funktion von Sensitivität und Exposition, welche potentielle Auswirkungen des Klimawandels darstellen, und der Anpassungsfähigkeit von Systemen definiert. Vulnerabilitätsstudien, die diese Komponenten quantifizieren, sind zu einem wichtigen Werkzeug in der Klimawissenschaft geworden. Allerdings besteht von der wissenschaftlichen Perspektive aus gesehen Uneinigkeit darüber, wie diese Definition in Studien umgesetzt werden soll. Ausdiesem Konflikt ergeben sich viele Herausforderungen, vor allem bezüglich der Quantifizierung und Aggregierung der einzelnen Komponenten und deren angemessenen Komplexitätsniveaus. Die vorliegende Dissertation hat daher zum Ziel die Anwendbarkeit des Vulnerabilitätskonzepts voranzubringen, indem es in eine systematische Struktur übersetzt wird. Dies beinhaltet alle Komponenten und schlägt für jede Klimaauswirkung (z.B. Sturzfluten) eine Beschreibung des vulnerablen Systems vor (z.B. Siedlungen), welches direkt mit einer bestimmten Richtung eines relevanten klimatischen Stimulus in Verbindung gebracht wird (z.B. stärkere Auswirkungen bei Zunahme der Starkregentage). Bezüglich der herausfordernden Prozedur der Aggregierung werden zwei alternative Methoden, die einen sektorübergreifenden Überblick ermöglichen, vorgestellt und deren Vor- und Nachteile diskutiert. Anschließend wird die entwickelte Struktur einer Vulnerabilitätsstudie mittels eines indikatorbasierten und deduktiven Ansatzes beispielhaft für Gemeinden in Nordrhein-Westfalen in Deutschland angewandt. Eine Übertragbarkeit auf andere Regionen ist dennoch möglich. Die Quantifizierung für die Gemeinden stützt sich dabei auf Informationen aus der Literatur. Da für viele Sektoren keine geeigneten Indikatoren vorhanden waren, werden in dieser Arbeit neue Indikatoren entwickelt und angewandt, beispielsweise für den Forst- oder Gesundheitssektor. Allerdings stellen fehlende empirische Daten bezüglich relevanter Schwellenwerte eine Lücke dar, beispielsweise welche Stärke von Klimaänderungen eine signifikante Auswirkung hervorruft. Dies führt dazu, dass die Studie nur relative Aussagen zum Grad der Vulnerabilität jeder Gemeinde im Vergleich zum Rest des Bundeslandes machen kann. Um diese Lücke zu füllen, wird für den Forstsektor beispielhaft die heutige und zukünftige Sturmwurfgefahr von Wäldern berechnet. Zu diesem Zweck werden die Eigenschaften der Wälder mit empirischen Schadensdaten eines vergangenen Sturmereignisses in Verbindung gebracht. Der sich daraus ergebende Sensitivitätswert wird anschließend mit den Windverhältnissen verknüpft. Sektorübergreifende Vulnerabilitätsstudien erfordern beträchtliche Ressourcen, was oft deren Anwendbarkeit erschwert. In einem nächsten Schritt wird daher das Potential einer Vereinfachung der Komplexität anhand zweier sektoraler Beispiele untersucht. Um das Auftreten von Waldbränden vorherzusagen, stehen zahlreiche meteorologische Indices zur Verfügung, welche eine Spannbreite unterschiedlicher Komplexitäten aufweisen. Bezüglich der Anzahl monatlicher Waldbrände weist die relative Luftfeuchtigkeit für die meisten deutschen Bundesländer eine bessere Vorhersagekraft als komplexere Indices auf. Dies ist er Fall, obgleich sie selbst als Eingangsvariable für die komplexeren Indices verwendet wird. Mit Hilfe dieses einzelnen meteorologischen Faktors kann also die Waldbrandgefahr in deutschen Region ausreichend genau ausgedrückt werden, was die Ressourceneffizienz von Studien erhöht. Die Methodenkomplexität wird auf ähnliche Weise hinsichtlich der Anwendung des ökohydrologischen Modells SWIM für die Region Brandenburg untersucht. Die interannuellen Bodenwasserwerte, welche durch dieses Modell simuliert werden, können nur unzureichend durch ein einfacheres statistisches Modell, welches auf denselben Eingangsdaten aufbaut, abgebildet werden. Innerhalb eines Zeithorizonts von Jahrzehnten, kann der statistische Ansatz jedoch das Bodenwasser zufriedenstellend abbilden und zeigt eine Dominanz der Bodeneigenschaft Feldkapazität. Dies deutet darauf hin, dass die Komplexität im Hinblick auf die Anzahl der Eingangsvariablen für langfristige Berechnungen reduziert werden kann. Allerdings sind die Aussagen durch fehlende beobachtete Bodenwasserwerte zur Validierung beschränkt. Die vorliegenden Studien zur Vulnerabilität und ihren Komponenten haben gezeigt, dass eine Anwendung noch immer wissenschaftlich herausfordernd ist. Folgt man der hier verwendeten Vulnerabilitätsdefinition, treten zahlreiche Probleme bei der Implementierung in regionalen Studien auf. Mit dieser Dissertation wurden Fortschritte bezüglich der aufgezeigten Lücken bisheriger Studien erzielt, indem eine systematische Struktur für die Beschreibung und Aggregierung von Vulnerabilitätskomponenten erarbeitet wurde. Hierfür wurden mehrere Ansätze diskutiert, die jedoch Vor- und Nachteile besitzen. Diese sollten vor der Anwendung von zukünftigen Studien daher ebenfalls sorgfältig abgewogen werden. Darüber hinaus hat sich gezeigt, dass ein Potential besteht einige Ansätze zu vereinfachen, jedoch sind hierfür weitere Untersuchungen nötig. Insgesamt konnte die Dissertation die Anwendung von Vulnerabilitätsstudien als Werkzeug zur Unterstützung von Anpassungsmaßnahmen stärken.
Sustainable management of semi-arid African savannas under environmental and political change
(2012)
Drylands cover about 40% of the earth’s land surface and provide the basis for the livelihoods of 38% of the global human population. Worldwide, these ecosystems are prone to heavy degradation. Increasing levels of dryland degradation result a strong decline of ecosystem services. In addition, in highly variable semi-arid environments changing future environmental conditions will potentially have severe consequences for productivity and ecosystem dynamics. Hence, global efforts have to be made to understand the particular causes and consequences of dryland degradation and to promote sustainable management options for semi-arid and arid ecosystems in a changing world. Here I particularly address the problem of semi-arid savanna degradation, which mostly occurs in form of woody plant encroachment. At this, I aim at finding viable sustainable management strategies and improving the general understanding of semi-arid savanna vegetation dynamics under conditions of extensive livestock production. Moreover, the influence of external forces, i.e. environmental change and land reform, on the use of savanna vegetation and on the ecosystem response to this land use is assessed. Based on this I identify conditions and strategies that facilitate a sustainable use of semi-arid savanna rangelands in a changing world. I extended an eco-hydrological model to simulate rangeland vegetation dynamics for a typical semi-arid savanna in eastern Namibia. In particular, I identified the response of semi-arid savanna vegetation to different land use strategies (including fire management) also with regard to different predicted precipitation, temperature and CO2 regimes. Not only environmental but also economic and political constraints like e.g. land reform programmes are shaping rangeland management strategies. Hence, I aimed at understanding the effects of the ongoing process of land reform in southern Africa on land use and the semi-arid savanna vegetation. Therefore, I developed and implemented an agent-based ecological-economic modelling tool for interactive role plays with land users. This tool was applied in an interdisciplinary empirical study to identify general patterns of management decisions and the between-farm cooperation of land reform beneficiaries in eastern Namibia. The eco-hydrological simulations revealed that the future dynamics of semi-arid savanna vegetation strongly depend on the respective climate change scenario. In particular, I found that the capacity of the system to sustain domestic livestock production will strongly depend on changes in the amount and temporal distribution of precipitation. In addition, my simulations revealed that shrub encroachment will become less likely under future climatic conditions although positive effects of CO2 on woody plant growth and transpiration have been considered. While earlier studies predicted a further increase in shrub encroachment due to increased levels of atmospheric CO2, my contrary finding is based on the negative impacts of temperature increase on the drought sensitive seedling germination and establishment of woody plant species. Further simulation experiments revealed that prescribed fires are an efficient tool for semi-arid rangeland management, since they suppress woody plant seedling establishment. The strategies tested have increased the long term productivity of the savanna in terms of livestock production and decreased the risk for shrub encroachment (i.e. savanna degradation). This finding refutes the views promoted by existing studies, which state that fires are of minor importance for the vegetation dynamics of semi-arid and arid savannas. Again, the difference in predictions is related to the bottleneck at the seedling establishment stage of woody plants, which has not been sufficiently considered in earlier studies. The ecological-economic role plays with Namibian land reform beneficiaries showed that the farmers made their decisions with regard to herd size adjustments according to economic but not according to environmental variables. Hence, they do not manage opportunistically by tracking grass biomass availability but rather apply conservative management strategies with low stocking rates. This implies that under the given circumstances the management of these farmers will not per se cause (or further worsen) the problem of savanna degradation and shrub encroachment due to overgrazing. However, as my results indicate that this management strategy is rather based on high financial pressure, it is not an indicator for successful rangeland management. Rather, farmers struggle hard to make any positive revenue from their farming business and the success of the Namibian land reform is currently disputable. The role-plays also revealed that cooperation between farmers is difficult even though obligatory due to the often small farm sizes. I thus propose that cooperation needs to be facilitated to improve the success of land reform beneficiaries.
Rainfall, snow-, and glacial melt throughout the Himalaya control river discharge, which is vital for maintaining agriculture, drinking water and hydropower generation. However, the spatiotemporal contribution of these discharge components to Himalayan rivers is not well understood, mainly because of the scarcity of ground-based observations. Consequently, there is also little known about the triggers and sources of peak sediment flux events, which account for extensive hydropower reservoir filling and turbine abrasion. We therefore lack basic information on the distribution of water resources and controls of erosion processes. In this thesis, I employ various methods to assess and quantify general characteristics of and links between precipitation, river discharge, and sediment flux in the Sutlej Valley. First, I analyze daily precipitation data (1998-2007) from 80 weather stations in the western Himalaya, to decipher the distribution of rain- and snowfall. Rainfall magnitude frequency analyses indicate that 40% of the summer rainfall budget is attributed to monsoonal rainstorms, which show higher variability in the orogenic interior than in frontal regions. Combined analysis of rainstorms and sediment flux data of a major Sutlej River tributary indicate that monsoonal rainfall has a first order control on erosion processes in the orogenic interior, despite the dominance of snowfall in this region. Second, I examine the contribution of rainfall, snow and glacial melt to river discharge in the Sutlej Valley (s55,000 km2), based on a distributed hydrological model, which covers the period 2000-2008. To achieve high spatial and daily resolution despite limited ground-based observations the hydrological model is forced by daily remote sensing data, which I adjusted and calibrated with ground station data. The calibration shows that the Tropical Rainfall Measuring Mission (TRMM) 3B42 rainfall product systematically overestimates rainfall in semi-arid and arid regions, increasing with aridity. The model results indicate that snowmelt-derived discharge (74%) is most important during the pre-monsoon season (April to June) whereas rainfall (56%) and glacial melt (17%) dominate the monsoon season (July-September). Therefore, climate change most likely causes a reduction in river discharge during the pre-monsoon season, which especially affects the orogenic interior. Third, I investigate the controls on suspended sediment flux in different parts of the Sutlej catchments, based on daily gauging data from the past decade. In conjunction with meteorological data, earthquake records, and rock strength measurements I find that rainstorms are the most frequent trigger of high-discharge events with peaks in suspended sediment concentrations (SSC) that account for the bulk of the suspended sediment flux. The suspended sediment flux increases downstream, mainly due to increases in runoff. Pronounced erosion along the Himalayan Front occurs throughout the monsoon season, whereas efficient erosion of the orogenic interior is confined to single extreme events. The results of this thesis highlight the importance of snow and glacially derived melt waters in the western Himalaya, where extensive regions receive only limited amounts of monsoonal rainfall. These regions are therefore particularly susceptible to global warming with major implications on the hydrological cycle. However, the sediment discharge data show that infrequent monsoonal rainstorms that pass the orographic barrier of the Higher Himalaya are still the primary trigger of the highest-impact erosion events, despite being subordinate to snow and glacially–derived discharge. These findings may help to predict peak sediment flux events and could underpin the strategic development of preventative measures for hydropower infrastructures.
Species respond to environmental change by dynamically adjusting their geographical ranges. Robust predictions of these changes are prerequisites to inform dynamic and sustainable conservation strategies. Correlative species distribution models (SDMs) relate species’ occurrence records to prevailing environmental factors to describe the environmental niche. They have been widely applied in global change context as they have comparably low data requirements and allow for rapid assessments of potential future species’ distributions. However, due to their static nature, transient responses to environmental change are essentially ignored in SDMs. Furthermore, neither dispersal nor demographic processes and biotic interactions are explicitly incorporated. Therefore, it has often been suggested to link statistical and mechanistic modelling approaches in order to make more realistic predictions of species’ distributions for scenarios of environmental change. In this thesis, I present two different ways of such linkage. (i) Mechanistic modelling can act as virtual playground for testing statistical models and allows extensive exploration of specific questions. I promote this ‘virtual ecologist’ approach as a powerful evaluation framework for testing sampling protocols, analyses and modelling tools. Also, I employ such an approach to systematically assess the effects of transient dynamics and ecological properties and processes on the prediction accuracy of SDMs for climate change projections. That way, relevant mechanisms are identified that shape the species’ response to altered environmental conditions and which should hence be considered when trying to project species’ distribution through time. (ii) I supplement SDM projections of potential future habitat for black grouse in Switzerland with an individual-based population model. By explicitly considering complex interactions between habitat availability and demographic processes, this allows for a more direct assessment of expected population response to environmental change and associated extinction risks. However, predictions were highly variable across simulations emphasising the need for principal evaluation tools like sensitivity analysis to assess uncertainty and robustness in dynamic range predictions. Furthermore, I identify data coverage of the environmental niche as a likely cause for contrasted range predictions between SDM algorithms. SDMs may fail to make reliable predictions for truncated and edge niches, meaning that portions of the niche are not represented in the data or niche edges coincide with data limits. Overall, my thesis contributes to an improved understanding of uncertainty factors in predictions of range dynamics and presents ways how to deal with these. Finally I provide preliminary guidelines for predictive modelling of dynamic species’ response to environmental change, identify key challenges for future research and discuss emerging developments.
Küsten und Klimawandel in den Augen von Touristen : eine Wahrnehmungsanalyse an der deutschen Ostsee
(2011)
Aufgrund seiner wirtschaftlichen Bedeutung spielt der Tourismus in Mecklenburg-Vorpommern eine große Rolle. Insbesondere die Küstengebiete sind beliebte Reiseziele. In den letzten Jahren konnte ein kontinuierlicher Anstieg der Ankünfte und Übernachtungen verzeichnet werden. Neben anderen Faktoren werden die regionalen Auswirkungen des Klimawandels jedoch in Zukunft eine Herausforderung für den Tourismussektor darstellen. Die globale Erwärmung wird für den Strand- und Badetourismus sowohl negative, als auch positive Folgen haben, auf die reagiert werden muss. Neben vorbeugenden Klimaschutzmaßnahmen werden künftig auch Anpassungsstrategien entwickelt werden müssen, die den zu erwartenden Veränderungen Rechnung tragen. Doch zu welchen tourismusrelevanten Veränderungen wird es überhaupt kommen und was geschieht bereits aktuell? Sind die Folgen des Klimawandels durch Touristen schon jetzt wahrnehmbar? Wie reagieren die Urlauber auf eventuelle Veränderungen? Diese und andere Fragen soll die vorliegende Arbeit, die innerhalb des RAdOST-Vorhabens (Regionale Anpassungsstrategien für die deutsche Ostseeküste) angesiedelt ist, beantworten. Dazu wurde zum einen eine Literaturrecherche zu tourismusrelevanten Klimawandelfolgen an der deutschen Ostseeküste durchgeführt. Zum anderen erfolgte in den Sommermonaten 2010 eine Befragung der Strandgäste in Markgrafenheide, Warnemünde und Nienhagen an der mecklenburgischen Ostseeküste. Im Mittelpunkt der Umfrage stand die Wahrnehmung von Erscheinungen (z.B. viele Quallen oder warmes Ostseewasser) sowie kurz- oder langfristigen Veränderungen an der Küste (z.B. schmalere Strände, vermehrter Strandanwurf) durch die Urlauber. Außerdem wurden die Einstellung und der Informationsgrad der Gäste zum Thema Klimawandel an der Ostseeküste analysiert. Ziel war es, aus den Umfrageergebnissen Handlungsempfehlungen für das lokale Strandmanagement hinsichtlich künftiger Anpassungsstrategien abzuleiten. Die Literaturrecherche zeigte, dass in einigen Bereichen schon jetzt Veränderungen (z.B. der Luft- und Wassertemperatur oder des Meeresspiegels) nachweisbar sind und laut verschiedener Modellprojektionen von weiteren Veränderungen ausgegangen werden kann. Wie die Umfrage deutlich machte, sind die Veränderungen momentan durch Touristen jedoch kaum oder gar nicht wahrnehmbar. Dementsprechend gering ist auch ihre Reaktion auf die einzelnen Phänomene. Generell ist die Wahrnehmung der Urlauber sehr subjektiv und selektiv. Manche Gegebenheiten wie beispielsweise existierende Küstenschutzmaßnahmen werden von einem großen Teil der Touristen gar nicht wahrgenommen. Hinsichtlich anderer Erscheinungen wie Strandanwurf und Quallen sind viele Besucher wiederum sehr sensibel. Es zeigte sich außerdem, dass es für die meisten Urlauber schwierig ist, zu beurteilen, ob bestimmte Gegebenheiten am Strand und an der Küste mit der globalen Erwärmung in Verbindung stehen oder nicht. Es besteht eine große Unsicherheit zu diesem Thema und oft wird der Klimawandel als Ursache für Erscheinungen genannt, auch wenn der kausale Zusammenhang wissenschaftlich nicht nachzuweisen ist. Es zeigte sich, dass die Urlauber sehr wenig über die regionalen Auswirkungen des Klimawandels informiert sind, sich aber Informationen wünschen. Folglich sollte zunächst die Aufklärung und Information der Urlauber über die Folgen der Veränderung des Klimas im Vordergrund stehen. Denn manche Aspekte, wie der Verlust von Strandabschnitten durch Erosion oder eine eventuelle Zunahme von Blaualgen in der Sommersaison, können nicht gänzlich vermieden werden. Durch gezielte Aufklärung könnte jedoch beispielsweise eine Akzeptanz für naturnahe Strände oder für den Rückzug aus einzelnen Gebieten geschaffen werden. Darüber hinaus sollte die zu erwartende Saisonverlängerung systematisch genutzt werden, um sowohl die Küste, als auch das Hinterland durch gezielte Angebote für Touristen attraktiv zu machen. Auf diese Weise könnte eine Entzerrung der Hauptsaison und eine bessere Auslastung der Beherbergungsbetriebe sowie der touristischen Infrastruktur erreicht werden.
In den letzten drei Jahrzehnten wurden in einigen Seen und Feuchtgebieten in bewaldeten Einzugsgebieten Nordost-Brandenburgs sinkende Wasserstände beobachtet. In diesen Gebieten bestimmt die Grundwasserneubildung im Einzugsgebiet maßgeblich das Wasserdargebot der Seen und Feuchtgebiete, die deshalb hier als grundwasserabhängige Landschaftselemente bezeichnet werden. Somit weisen die sinkenden Wasserstände auf einen Rückgang der wegen des geringen Niederschlagsdargebotes ohnehin schon geringen Grundwasserneubildung hin. Die Höhe der Grundwasserneubildung ist neben den hydroklimatischen Randbedingungen auch von der Landnutzung abhängig. Veränderungen in der Waldvegetation und der hydroklimatischen Randbedingungen bewirken Änderungen der Grundwasserneubildung und beeinflussen somit auch den Wasserhaushalt der Seen und Feuchtgebiete. Aktuell wird die Waldvegetation durch Kiefernmonokulturen dominiert, mit im Vergleich zu anderen Baumarten höherer Evapotranspiration. Entwicklungen in der Forstwirtschaft streben die Verringerung von Kiefernmonokulturen an. Diese sollen langfristig auf geeigneten Standorten durch Laubmischwälder ersetzt werden. Dadurch lassen sich eine geringere Evapotranspiration und damit eine höhere Grundwasserneubildung erreichen. In der vorliegenden Arbeit werden am Beispiel des Redernswalder Sees und des Briesensees die Ursachen der beobachteten sinkenden Wasserstände analysiert. Ihre Wasserstände nahmen in den letzten 25 Jahren um mehr als 3 Meter ab. Weiterhin wird untersucht, wie die erwarteten Klimaänderungen und Veränderungen in der Waldbewirtschaftung die zukünftige Grundwasserneubildung und den Wasserhaushalt von Seen beeinflussen können. Die Entwicklung der Grundwasserneubildung im Untersuchungsgebiet wurde mit dem Wasserhaushaltsmodell WaSiM-ETH simuliert. Die Analyse der Wechselwirkungen der Seen mit dem regionalen quartären Grundwasserleitersystem erfolgte mit dem 3D-Grundwassermodell FEFLOW. Mögliche zukünftige Veränderungen der Grundwasserneubildung und der Seewasserstände durch Klimaänderungen und Waldumbau wurden mit Szenarienrechnungen bis zum Jahr 2100 analysiert. Die modellgestützte Analyse zeigte, dass die beobachteten abnehmenden Wasserstände zu etwa gleichen Anteilen durch Veränderungen der hydroklimatischen Randbedingungen sowie durch Veränderungen in der Waldvegetation und damit abnehmenden Grundwasserneubildungsraten zu erklären sind. Die zukünftigen Entwicklungen der Grundwasserneubildung und der Wasserstände sind geprägt von sich ändernden hydroklimatischen Randbedingungen und einem sukzessiven Wandel der Kiefernbestände zu Laubwäldern. Der Waldumbau hat positive Wirkungen auf die Grundwasserneubildung und damit auf die Wasserstände. Damit können die Einflüsse des eingesetzten REMO-A1B-Klimaszenarios zum Ende des Modellzeitraumes durch den Waldumbau nicht kompensiert werden, das Sinken des Wasserstandes wird jedoch wesentlich reduziert. Bei dem moderateren REMO-B1-Klimaszenario werden die Wasserstände des Jahres 2008 durch den Waldumbau bis zum Jahr 2100 überschritten.
The Greenland Ice Sheet (GIS) contains enough water volume to raise global sea level by over 7 meters. It is a relic of past glacial climates that could be strongly affected by a warming world. Several studies have been performed to investigate the sensitivity of the ice sheet to changes in climate, but large uncertainties in its long-term response still exist. In this thesis, a new approach has been developed and applied to modeling the GIS response to climate change. The advantages compared to previous approaches are (i) that it can be applied over a wide range of climatic scenarios (both in the deep past and the future), (ii) that it includes the relevant feedback processes between the climate and the ice sheet and (iii) that it is highly computationally efficient, allowing simulations over very long timescales. The new regional energy-moisture balance model (REMBO) has been developed to model the climate and surface mass balance over Greenland and it represents an improvement compared to conventional approaches in modeling present-day conditions. Furthermore, the evolution of the GIS has been simulated over the last glacial cycle using an ensemble of model versions. The model performance has been validated against field observations of the present-day climate and surface mass balance, as well as paleo information from ice cores. The GIS contribution to sea level rise during the last interglacial is estimated to be between 0.5-4.1 m, consistent with previous estimates. The ensemble of model versions has been constrained to those that are consistent with the data, and a range of valid parameter values has been defined, allowing quantification of the uncertainty and sensitivity of the modeling approach. Using the constrained model ensemble, the sensitivity of the GIS to long-term climate change was investigated. It was found that the GIS exhibits hysteresis behavior (i.e., it is multi-stable under certain conditions), and that a temperature threshold exists above which the ice sheet transitions to an essentially ice-free state. The threshold in the global temperature is estimated to be in the range of 1.3-2.3°C above preindustrial conditions, significantly lower than previously believed. The timescale of total melt scales non-linearly with the overshoot above the temperature threshold, such that a 2°C anomaly causes the ice sheet to melt in ca. 50,000 years, but an anomaly of 6°C will melt the ice sheet in less than 4,000 years. The meltback of the ice sheet was found to become irreversible after a fraction of the ice sheet is already lost – but this level of irreversibility also depends on the temperature anomaly.
Lake ecosystems across the globe have responded to climate warming of recent decades. However, correctly attributing observed changes to altered climatic conditions is complicated by multiple anthropogenic influences on lakes. This thesis contributes to a better understanding of climate impacts on freshwater phytoplankton, which forms the basis of the food chain and decisively influences water quality. The analyses were, for the most part, based on a long-term data set of physical, chemical and biological variables of a shallow, polymictic lake in north-eastern Germany (Müggelsee), which was subject to a simultaneous change in climate and trophic state during the past three decades. Data analysis included constructing a dynamic simulation model, implementing a genetic algorithm to parameterize models, and applying statistical techniques of classification tree and time-series analysis. Model results indicated that climatic factors and trophic state interactively determine the timing of the phytoplankton spring bloom (phenology) in shallow lakes. Under equally mild spring conditions, the phytoplankton spring bloom collapsed earlier under high than under low nutrient availability, due to a switch from a bottom-up driven to a top-down driven collapse. A novel approach to model phenology proved useful to assess the timings of population peaks in an artificially forced zooplankton-phytoplankton system. Mimicking climate warming by lengthening the growing period advanced algal blooms and consequently also peaks in zooplankton abundance. Investigating the reasons for the contrasting development of cyanobacteria during two recent summer heat wave events revealed that anomalously hot weather did not always, as often hypothesized, promote cyanobacteria in the nutrient-rich lake studied. The seasonal timing and duration of heat waves determined whether critical thresholds of thermal stratification, decisive for cyanobacterial bloom formation, were crossed. In addition, the temporal patterns of heat wave events influenced the summer abundance of some zooplankton species, which as predators may serve as a buffer by suppressing phytoplankton bloom formation. This thesis adds to the growing body of evidence that lake ecosystems have strongly responded to climatic changes of recent decades. It reaches beyond many previous studies of climate impacts on lakes by focusing on underlying mechanisms and explicitly considering multiple environmental changes. Key findings show that climate impacts are more severe in nutrient-rich than in nutrient-poor lakes. Hence, to develop lake management plans for the future, limnologists need to seek a comprehensive, mechanistic understanding of overlapping effects of the multi-faceted human footprint on aquatic ecosystems.
The need to develop sustainable resource management strategies for semi-arid and arid rangelands is acute as non-adapted grazing strategies lead to irreversible environmental problems such as desertification and associated loss of economic support to society. In such vulnerable ecosystems, successful implementation of sustainable management strategies depends on well-founded under-standing of processes at different scales that underlay the complex system dynamic. There is ample evidence that, in contrast to traditional sectoral approaches, only interdisciplinary research does work for resolving problems in conservation and natural resource management. In this thesis I combined a range of modeling approaches that integrate different disciplines and spatial scales in order to contribute to basic guidelines for sustainable management of semi-arid and arid range-lands. Since water availability and livestock management are seen as most potent determinants for the dynamics of semi-arid and arid ecosystems I focused on (i) the interaction of ecological and hydro-logical processes and (ii) the effect of farming strategies. First, I developed a grid-based and small-scaled model simulating vegetation dynamics and inter-linked hydrological processes. The simulation results suggest that ecohydrological interactions gain importance in rangelands with ascending slope where vegetation cover serves to obstruct run-off and decreases evaporation from the soil. Disturbances like overgrazing influence these positive feedback mechanisms by affecting vegetation cover and composition. In the second part, I present a modeling approach that has the power to transfer and integrate ecological information from the small scale vegetation model to the landscape scale, most relevant for the conservation of biodiversity and sustainable management of natural resources. I combined techniques of stochastic modeling with remotely sensed data and GIS to investigate to which ex-tent spatial interactions, like the movement of surface water by run-off in water limited environments, affect ecosystem functioning at the landscape scale. My simulation experiments show that overgrazing decreases the number of vegetation patches that act as hydrological sinks and run-off increases. The results of both simulation models implicate that different vegetation types should not only be regarded as provider of forage production but also as regulator of ecosystem functioning. Vegetation patches with good cover of perennial vegetation are capable to catch and conserve surface run-off from degraded surrounding areas. Therefore, downstream out of the simulated system is prevented and efficient use of water resources is guaranteed at all times. This consequence also applies to commercial rotational grazing strategies for semi-arid and arid rangelands with ascending slope where non-degraded paddocks act as hydrological sinks. Finally, by the help of an integrated ecological-economic modeling approach, I analyzed the relevance of farmers’ ecological knowledge for longterm functioning of semi-arid and arid grazing systems under current and future climatic conditions. The modeling approach consists of an ecological and an economic module and combines relevant processes on either level. Again, vegetation dynamics and forage productivity is derived by the small-scaled vegetation model. I showed that sustainable management of semi-arid and arid rangelands relies strongly on the farmers’ knowledge on how the ecosystem works. Furthermore, my simulation results indicate that the projected lower annual rainfall due to climate change in combination with non-adapted grazing strategies adds an additional layer of risk to these ecosystems that are already prone to land degradation. All simulation models focus on the most essential factors and ignore specific details. Therefore, even though all simulation models are parameterized for a specific dwarf shrub savanna in arid southern Namibia, the conclusions drawn are applicable for semi-arid and arid rangelands in general.
Soils contain a large amount of carbon (C) that is a critical regulator of the global C budget. Already small changes in the processes governing soil C cycling have the potential to release considerable amounts of CO2, a greenhouse gas (GHG), adding additional radiative forcing to the atmosphere and hence to changing climate. Increased temperatures will probably create a feedback, causing soils to release more GHGs. Furthermore changes in soil C balance impact soil fertility and soil quality, potentially degrading soils and reducing soils function as important resource. Consequently the assessment of soil C dynamics under present, recent past and future environmental conditions is not only of scientific interest and requires an integrated consideration of main factors and processes governing soil C dynamics. To perform this assessment an eco-hydrological modelling tool was used and extended by a process-based description of coupled soil carbon and nitrogen turnover. The extended model aims at delivering sound information on soil C storage changes beside changes in water quality, quantity and vegetation growth under global change impacts in meso- to macro-scale river basins, exemplary demonstrated for a Central European river basin (the Elbe). As a result this study: ▪ Provides information on joint effects of land-use (land cover and land management) and climate changes on croplands soil C balance in the Elbe river basin (Central Europe) presently and in the future. ▪ Evaluates which processes, and at what level of process detail, have to be considered to perform an integrated simulation of soil C dynamics at the meso- to macro-scale and demonstrates the model’s capability to simulate these processes compared to observations. ▪ Proposes a process description relating soil C pools and turnover properties to readily measurable quantities. This reduces the number of model parameters, enhances the comparability of model results to observations, and delivers same performance simulating long-term soil C dynamics as other models. ▪ Presents an extensive assessment of the parameter and input data uncertainty and their importance both temporally and spatially on modelling soil C dynamics. For the basin scale assessments it is estimated that croplands in the Elbe basin currently act as a net source of carbon (net annual C flux of 11 g C m-2 yr-1, 1.57 106 tons CO2 yr-1 entire croplands on average). Although this highly depends on the amount of harvest by-products remaining on the field. Future anticipated climate change and observed climate change in the basin already accelerates soil C loss and increases source strengths (additional 3.2 g C m-2 yr-1, 0.48 106 tons CO2 yr-1 entire croplands). But anticipated changes of agro-economic conditions, translating to altered crop share distributions, display stronger effects on soil C storage than climate change. Depending on future use of land expected to fall out of agricultural use in the future (~ 30 % of croplands area as “surplus” land), the basin either considerably looses soil C and the net annual C flux to the atmosphere increases (surplus used as black fallow) or the basin converts to a net sink of C (sequestering 0.44 106 tons CO2 yr-1 under extensified use as ley-arable) or reacts with decrease in source strength when using bioenergy crops. Bioenergy crops additionally offer a considerable potential for fossil fuel substitution (~37 PJ, 1015 J per year), whereas the basin wide use of harvest by-products for energy generation has to be seen critically although offering an annual energy potential of approximately 125 PJ. Harvest by-products play a central role in soil C reproduction and a percentage between 50 and 80 % should remain on the fields in order to maintain soil quality and fertility. The established modelling tool allows quantifying climate, land use and major land management impacts on soil C balance. New is that the SOM turnover description is embedded in an eco-hydrological river basin model, allowing an integrated consideration of water quantity, water quality, vegetation growth, agricultural productivity and soil carbon changes under different environmental conditions. The methodology and assessment presented here demonstrates the potential for integrated assessment of soil C dynamics alongside with other ecosystem services under global change impacts and provides information on the potentials of soils for climate change mitigation (soil C sequestration) and on their soil fertility status.
Natural and human induced environmental changes affect populations at different time scales. If they occur in a spatial heterogeneous way, they cause spatial variation in abundance. In this thesis I addressed three topics, all related to the question, how environmental changes influence population dynamics. In the first part, I analysed the effect of positive temporal autocorrelation in environmental noise on the extinction risk of a population, using a simple population model. The effect of autocorrelation depended on the magnitude of the effect of single catastrophic events of bad environmental conditions on a population. If a population was threatened by extinction only, when bad conditions occurred repeatedly, positive autocorrelation increased extinction risk. If a population could become extinct, even if bad conditions occurred only once, positive autocorrelation decreased extinction risk. These opposing effects could be explained by two features of an autocorrelated time series. On the one hand, positive autocorrelation increased the probability of series of bad environmental conditions, implying a negative effect on populations. On the other hand, aggregation of bad years also implied longer periods with relatively good conditions. Therefore, for a given time period, the overall probability of occurrence of at least one extremely bad year was reduced in autocorrelated noise. This can imply a positive effect on populations. The results could solve a contradiction in the literature, where opposing effects of autocorrelated noise were found in very similar population models. In the second part, I compared two approaches, which are commonly used for predicting effects of climate change on future abundance and distribution of species: a "space for time approach", where predictions are based on the geographic pattern of current abundance in relation to climate, and a "population modelling approach" which is based on correlations between demographic parameters and the inter-annual variation of climate. In this case study, I compared the two approaches for predicting the effect of a shift in mean precipitation on a population of the sociable weaver Philetairus socius, a common colonially living passerine bird of semiarid savannahs of southern Africa. In the space for time approach, I compared abundance and population structure of the sociable weaver in two areas with highly different mean annual precipitation. The analysis showed no difference between the two populations. This result, as well as the wide distribution range of the species, would lead to the prediction of no sensitive response of the species to a slight shift in mean precipitation. In contrast, the population modelling approach, based on a correlation between reproductive success and rainfall, predicted a sensitive response in most model types. The inconsistency of predictions was confirmed in a cross-validation between the two approaches. I concluded that the inconsistency was caused, because the two approaches reflect different time scales. On a short time scale, the population may respond sensitively to rainfall. However, on a long time scale, or in a regional comparison, the response may be compensated or buffered by a variety of mechanisms. These may include behavioural or life history adaptations, shifts in the interactions with other species, or differences in the physical environment. The study implies that understanding, how such mechanisms work, and at what time scale they would follow climate change, is a crucial precondition for predicting ecological consequences of climate change. In the third part of the thesis, I tested why colony sizes of the sociable weaver are highly variable. The high variation of colony sizes is surprising, as in studies on coloniality it is often assumed that an optimal colony size exists, in which individual bird fitness is maximized. Following this assumption, the pattern of bird dispersal should keep colony sizes near an optimum. However, I showed by analysing data on reproductive success and survival that for the sociable weaver fitness in relation to colony size did not follow an optimum curve. Instead, positive and negative effects of living in large colonies overlaid each other in a way that fitness was generally close to one, and density dependence was low. I showed in a population model, which included an evolutionary optimisation process of dispersal that this specific shape of the fitness function could lead to a dispersal strategy, where the variation of colony sizes was maintained.
Studies of the role of disturbance in vegetation or ecosystems showed that disturbances are an essential and intrinsic element of ecosystems that contribute substantially to ecosystem health, to structural diversity of ecosystems and to nutrient cycling at the local as well as global level. Fire as a grassland, bush or forest fire is a special disturbance agent, since it is caused by biotic as well abiotic environmental factors. Fire affects biogeochemical cycles and plays an important role in atmospheric chemistry by releasing climate-sensitive trace gases and aerosols, and thus in the global carbon cycle by releasing approximately 3.9 Gt C p.a. through biomass burning. A combined model to describe effects and feedbacks between fire and vegetation became relevant as changes in fire regimes due to land use and land management were observed and the global dimension of biomass burnt as an important carbon flux to the atmosphere, its influence on atmospheric chemistry and climate as well as vegetation dynamics were emphasized. The existing modelling approaches would not allow these investigations. As a consequence, an optimal set of variables that best describes fire occurrence, fire spread and its effects in ecosystems had to be defined, which can simulate observed fire regimes and help to analyse interactions between fire and vegetation dynamics as well as to allude to the reasons behind changing fire regimes. Especially, dynamic links between vegetation, climate and fire processes are required to analyse dynamic feedbacks and effects of changes of single environmental factors. This led us to the point, where new fire models had to be developed that would allow the investigations, mentioned above, and could help to improve our understanding of the role of fire in global ecology. In conclusion of the thesis, one can state that moisture conditions, its persistence over time and fuel load are the important components that describe global fire pattern. If time series of a particular region are to be reproduced, specific ignition sources, fire-critical climate conditions and vegetation composition become additional determinants. Vegetation composition changes the level of fire occurrence and spread, but has limited impact on the inter-annual variability of fire. The importance to consider the full range of major fire processes and links to vegetation dynamics become apparent under climate change conditions. Increases in climate-dependent length of fire season does not automatically imply increases in biomass burnt, it can be buffered or accelerated by changes in vegetation productivity. Changes in vegetation composition as well as enhanced vegetation productivity can intensify changes in fire and lead to even more fire-related emissions. --- Anmerkung: Die Autorin ist Trägerin des von der Mathematisch-Naturwissenschaftlichen Fakultät der Universität Potsdam vergebenen Michelson-Preises für die beste Promotion des Jahres 2002/2003.
Semi-arid areas are, due to their climatic setting, characterized by small water resources. An increasing water demand as a consequence of population growth and economic development as well as a decreasing water availability in the course of possible climate change may aggravate water scarcity in future, which often exists already for present-day conditions in these areas. Understanding the mechanisms and feedbacks of complex natural and human systems, together with the quantitative assessment of future changes in volume, timing and quality of water resources are a prerequisite for the development of sustainable measures of water management to enhance the adaptive capacity of these regions. For this task, dynamic integrated models, containing a hydrological model as one component, are indispensable tools. The main objective of this study is to develop a hydrological model for the quantification of water availability in view of environmental change over a large geographic domain of semi-arid environments. The study area is the Federal State of Ceará (150 000 km2) in the semi-arid north-east of Brazil. Mean annual precipitation in this area is 850 mm, falling in a rainy season with duration of about five months. Being mainly characterized by crystalline bedrock and shallow soils, surface water provides the largest part of the water supply. The area has recurrently been affected by droughts which caused serious economic losses and social impacts like migration from the rural regions. The hydrological model Wasa (Model of Water Availability in Semi-Arid Environments) developed in this study is a deterministic, spatially distributed model being composed of conceptual, process-based approaches. Water availability (river discharge, storage volumes in reservoirs, soil moisture) is determined with daily resolution. Sub-basins, grid cells or administrative units (municipalities) can be chosen as spatial target units. The administrative units enable the coupling of Wasa in the framework of an integrated model which contains modules that do not work on the basis of natural spatial units. The target units mentioned above are disaggregated in Wasa into smaller modelling units within a new multi-scale, hierarchical approach. The landscape units defined in this scheme capture in particular the effect of structured variability of terrain, soil and vegetation characteristics along toposequences on soil moisture and runoff generation. Lateral hydrological processes at the hillslope scale, as reinfiltration of surface runoff, being of particular importance in semi-arid environments, can thus be represented also within the large-scale model in a simplified form. Depending on the resolution of available data, small-scale variability is not represented explicitly with geographic reference in Wasa, but by the distribution of sub-scale units and by statistical transition frequencies for lateral fluxes between these units. Further model components of Wasa which respect specific features of semi-arid hydrology are: (1) A two-layer model for evapotranspiration comprises energy transfer at the soil surface (including soil evaporation), which is of importance in view of the mainly sparse vegetation cover. Additionally, vegetation parameters are differentiated in space and time in dependence on the occurrence of the rainy season. (2) The infiltration module represents in particular infiltration-excess surface runoff as the dominant runoff component. (3) For the aggregate description of the water balance of reservoirs that cannot be represented explicitly in the model, a storage approach respecting different reservoirs size classes and their interaction via the river network is applied. (4) A model for the quantification of water withdrawal by water use in different sectors is coupled to Wasa. (5) A cascade model for the temporal disaggregation of precipitation time series, adapted to the specific characteristics of tropical convective rainfall, is applied for the generating rainfall time series of higher temporal resolution. All model parameters of Wasa can be derived from physiographic information of the study area. Thus, model calibration is primarily not required. Model applications of Wasa for historical time series generally results in a good model performance when comparing the simulation results of river discharge and reservoir storage volumes with observed data for river basins of various sizes. The mean water balance as well as the high interannual and intra-annual variability is reasonably represented by the model. Limitations of the modelling concept are most markedly seen for sub-basins with a runoff component from deep groundwater bodies of which the dynamics cannot be satisfactorily represented without calibration. Further results of model applications are: (1) Lateral processes of redistribution of runoff and soil moisture at the hillslope scale, in particular reinfiltration of surface runoff, lead to markedly smaller discharge volumes at the basin scale than the simple sum of runoff of the individual sub-areas. Thus, these processes are to be captured also in large-scale models. The different relevance of these processes for different conditions is demonstrated by a larger percentage decrease of discharge volumes in dry as compared to wet years. (2) Precipitation characteristics have a major impact on the hydrological response of semi-arid environments. In particular, underestimated rainfall intensities in the rainfall input due to the rough temporal resolution of the model and due to interpolation effects and, consequently, underestimated runoff volumes have to be compensated in the model. A scaling factor in the infiltration module or the use of disaggregated hourly rainfall data show good results in this respect. The simulation results of Wasa are characterized by large uncertainties. These are, on the one hand, due to uncertainties of the model structure to adequately represent the relevant hydrological processes. On the other hand, they are due to uncertainties of input data and parameters particularly in view of the low data availability. Of major importance is: (1) The uncertainty of rainfall data with regard to their spatial and temporal pattern has, due to the strong non-linear hydrological response, a large impact on the simulation results. (2) The uncertainty of soil parameters is in general of larger importance on model uncertainty than uncertainty of vegetation or topographic parameters. (3) The effect of uncertainty of individual model components or parameters is usually different for years with rainfall volumes being above or below the average, because individual hydrological processes are of different relevance in both cases. Thus, the uncertainty of individual model components or parameters is of different importance for the uncertainty of scenario simulations with increasing or decreasing precipitation trends. (4) The most important factor of uncertainty for scenarios of water availability in the study area is the uncertainty in the results of global climate models on which the regional climate scenarios are based. Both a marked increase or a decrease in precipitation can be assumed for the given data. Results of model simulations for climate scenarios until the year 2050 show that a possible future change in precipitation volumes causes a larger percentage change in runoff volumes by a factor of two to three. In the case of a decreasing precipitation trend, the efficiency of new reservoirs for securing water availability tends to decrease in the study area because of the interaction of the large number of reservoirs in retaining the overall decreasing runoff volumes.