In this research, a recent version of the Boreal Ecosystem Productivity Simulator (BEPS), called BEPS-TerrainLab, was adapted to northern peatlands and evaluated using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was extended and modified with a major focus on the adequate representation of northern peatlands' multi-layer canopy and the associated processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. An important prerequisite for the successful mapping of LAI based on remote sensing imagery is the accurate measurement of LAI in the field with a standard technique such as the LAI-2000 plant canopy analyzer. As part of this research, a quick and reliable method to determine shrub LAI with the LAI-2000 instrument was developed. This method was used to collect a large number of LAI data at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple endmember spectral unmixing that allows for separate tree and shrub LAI mapping in ombrotrophic peatlands. A slight modification of this methodology allows for its application to minerotrophic peatlands and their surrounding landscapes. These LAI maps were used to explicitly represent the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandill fen within BEPS-TerrainLab. The adapted version of BEPS-TerrainLab was used to investigate the in fluence of mescoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. This research suggests that future peatland ecosystem modelling efforts at regional and continental scales should include a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology, to allow for a more realistic simulation of peatlands' soil water balance. This is an important prerequisite for the reduction of currently existing uncertainties in wetlands' contribution to North America's carbon dioxide and methane annual fluxes from an ecosystem modelling perspective.

An agent based-model of mobility of pastoralists was developed and applied to the semi-arid rangeland region extending from southern Ethiopia to northern Kenya. This model was used to investigate temporal adaptation of pastoralists to the spatial heterogeneity of their environment. This dissertation describes the development, structure, and corroboration process of the simulation model, Pastoral Livestock Movement Model (PLMMO). PLMMO is a spatially explicit, individual-based pastoralists-animal foraging and movement model. It simultaneously simulates the foraging and movement behavior of individual pastoralists and their livestock in a rangeland ecosystem. Pastoralists?? herd mobility patterns and other measures of movement were compared to data from field studies. Predictions of the model correspond to observed mobility patterns across seasons. The distances moved were found to be significantly correlated (r2 = 0.927 to 0.977, p<0.0001) to drought and non-drought climatic regimes. The PLMMO model therefore proved to be a useful tool for simulating general movement patterns of pastoralists relative to movement range sizes in the pastoral rangelands of southern Ethiopia and northern Kenya. We then used the PLMMO model to explore the impact of emerging changes in rangeland use in the study area. The ways in which pastoralists?? mobility patterns adapt to emerging challenges in the study area were explored by simulating the following four scenarios: 1) climate change with concomitant reduction in forage yield, 2) climate change with concomitant improvement and higher variability in forage yield, 3) increased livestock population densities and 4) improved access to water. The climate induced change scenario with increased and more variable forage production resulted in the shortest distances moved by pastoralists in comparison to all other scenarios. The total search distances under this scenario were only 20% of normal season distances. The improved water access scenario also returned a significant (p=0.017) drop in distances moved. There was, however, no significant impact on either increase in livestock numbers or reduction in available forage on mobility. We judged the agent-based model PLMMO developed here as a robust system for emulating pastoral mobility in the rangelands of eastern Africa and for exploring the consequences of climate change and adaptive management scenarios.

In this research, a recent version of the Boreal Ecosystem Productivity Simulator (BEPS), called BEPS-TerrainLab, was adapted to northern peatlands and evaluated using observations made at the Mer Bleue bog located near Ottawa, Ontario, and the Sandhill fen located near Prince Albert, Saskatchewan. The code was extended and modified with a major focus on the adequate representation of northern peatlands' multi-layer canopy and the associated processes related to energy, water vapour and carbon dioxide fluxes through remotely-sensed leaf area index (LAI) maps. An important prerequisite for the successful mapping of LAI based on remote sensing imagery is the accurate measurement of LAI in the field with a standard technique such as the LAI-2000 plant canopy analyzer. As part of this research, a quick and reliable method to determine shrub LAI with the LAI-2000 instrument was developed. This method was used to collect a large number of LAI data at the Mer Bleue bog for the development of a new remote sensing-based methodology using multiple endmember spectral unmixing that allows for separate tree and shrub LAI mapping in ombrotrophic peatlands. A slight modification of this methodology allows for its application to minerotrophic peatlands and their surrounding landscapes. These LAI maps were used to explicitly represent the tree and shrub layers of the Mer Bleue bog and the tree and shrub/sedge layers of the Sandill fen within BEPS-TerrainLab. The adapted version of BEPS-TerrainLab was used to investigate the in fluence of mescoscale topography (Mer Bleue bog) and macro- and mesoscale topography (Sandhill fen) on wetness, evapotranspiration, and gross primary productivity during the snow-free period of 2004. This research suggests that future peatland ecosystem modelling efforts at regional and continental scales should include a peatland type-specific differentiation of macro- and mesoscale topographic effects on hydrology, to allow for a more realistic simulation of peatlands' soil water balance. This is an important prerequisite for the reduction of currently existing uncertainties in wetlands' contribution to North America's carbon dioxide and methane annual fluxes from an ecosystem modelling perspective.

This thesis focuses on the spread of organisms in both ecological and epidemiological contexts. In most of the studies presented, displacement is modeled with a spatial kernel function, which is characterized by scale and shape. These are measured by the net squared displacement (or kernel variance) and kurtosis, respectively. If organisms disperse by the assumptions of a random walk or correlated random walk, a Gaussian shaped kernel is expected. Empirical studies often report deviations from this, and commonly leptokurtic distributions are found, often as a result of heterogeneity in the dispersal process. In the studies presented in two of the included papers, the importance of the kernel shape is tested, by using a family of kernels where the shape and scale can be separated effectively. Both studies utilize spectral density approaches for modeling the spatial environment. It is concluded that the shape is not important when studying the population distribution in a habitat/matrix context. The shape is however important when looking at the invasion of organisms in a patchy environment, when the arrangement of patches deviates from randomly distributed. The introduced method for generating patch distribution is also compared to empirical distributions of patches (farms and old trees). Here it is concluded that the assumptions used for modeling of the spatial environment are consistent with the observed patterns. These assumptions include fractal properties such that the same aggregational patterns are found at different scales. In a series of papers, movements of animals are considered as vectors for between-herd disease spread. The studies are based on data found in databases held by the Swedish Board of Agricultural (SJV), consisting of reported movements, as well as farm location and characteristics. The first study focuses on the distance related probability of contacts between herds. In the following papers, the analysis is expanded to include production type and herd size. Movement data of pigs (and cattle in Paper I) are analyzed with Bayesian models, implemented with Markov Chain Monte Carlo (MCMC). This is a flexible approach that allows for parameter estimations of complex models, and at the same time includes parameter uncertainty. In Paper IV, the effects of the included factors are investigated. It is shown that all three factors (herd size, production type structure and distance related probability of contacts) are expected to influence disease spread dynamics, however the production type structure is found to be the most important factor. This emphasizes the value of keeping such information in central databases. The models presented can be used as support for risk analysis and disease tracing. However, data reliability is always a problem, and implementation may be improved with better quality data. The thesis also shows that utilizing spatial kernels for description of the spatial spread of organisms is an appropriate approach. However, these kernels must be flexible and flawed assumptions about the shape may lead to erroneous conclusions. Hence, the joint distribution of kernel shape and scale should be estimated. The flexibility of Bayesian analysis, implemented with MCMC techniques, is a good approach for this, and further allows for implementation of more complex models where other factors may be included.

Der Rückgang des Steinkauzes (Athene noctua) hat in Thüringen und Sachsen seit den 60er Jahren dramatische Ausmaße angenommen. In den 50er Jahren noch flächendeckend beobachtet, wurden für das Jahr 2000 nur noch 18 Individuen durch Bestandserfassungen registriert. Die vielfach diskutierten Rückgangsursachen beziehen sich vor Allem auf die großflächige Änderung der Landschaftsstrukturen, die zum Verlust der Lebensgrundlagen des Steinkauzes führten. So haben u.a. der Verlust an Brut- und Vorratshöhlen und an ganzjährig kurzgehaltenen Grünlandflächen, sowie der zunehmende Einfluss von Prädatoren erheblich zum Rückgang beigetragen. Eingeleitete Schutzmaßnahmen, ehrenamtlich oder auf dem allgemeinen Naturschutzprogramm des Freistaates Thüringen beruhend, wie das Anbringen von Nisthilfen mit Marderschutz oder Pflegeverträge für Streuobstwiesen, zeigen bisher keine sichtbare Wirkung. Als weitergehende Maßnahmen stehen die Reduzierung von Füchsen (Vulpes vulpes) und Steinmardern (Martes foina), Ausbreitungskorridore für Steinkäuze und ein Auswilderungsprogramm zur Diskussion. Angesichts des Populationsrückgangs des Steinkauz war es Aufgabe dieser Arbeit durch ein Simulationsmodell Untersuchungen zum Überleben einer Steinkauzpopulation (Athene noctua) in Thüringen durchzuführen. Die zusammengetragenen Bestandszahlen ergaben geringe Individuenzahlen in den thüringischen Landkreisen Altenburger Land, Greiz und der Stadt Gera sowie in den sächsischen Landkreisen Chemnitzer Land und Mittweida. Die Bestandszahlen der Jahre 1989-2001, sowie weitere der Literatur entnommene Daten zum populationsökologischen Hintergrund, wie auch Analysen des Gebietes in Thüringen und Sachsen und dessen besetzter Reviere der Jahre 1989- 2001, wurden in ein stochastisches, räumlich-explizites, auf Individuen basierendes Simulationsmodell eingebracht. Es wurde eine Sensitivitätsanalyse durchgeführt, die beruhend auf den erfassten Populationsentwicklungen in Thüringen und Sachsen und auf Literaturangaben, ausgewählte Parameterkonstellationen für die Untersuchungenergab. Die Untersuchungen zum Überleben vor dem Hintergrund möglicher Gefährdungsfaktoren und zur Ermittelung des Nutzens von Managementoptionen, wurden mit Schwerpunkten auf „Prädation“, „Habitatverbesserung“ und „Auswilderung“ durchgeführt. Als Ergebnis der Simulationen kam heraus, dass die Prädation keinen großen Einfluss auf das Überleben der Population hat, und Schutzmaßnahmen die Chancen für das Überleben der Population nicht erhöhen würden. Habitatverbesserungen, die die Juvenilen animieren sich im Umkreis von bis zu 5 km vom elterlichen Revier anzusiedeln, würden aber deutlich zum Überleben der Population, auch in längerfristiger Perspektive, beitragen. Habitatverbesserungen, die zu weiter entfernteren Ansiedlungen animieren, könnten sich dagegen ungünstig auf das Überleben der Population auswirken. Für eine mögliche Auswilderung als Schutzmaßnahme ergab sich im Modell, dass eine Auswilderung von 5 Individuen pro Jahr über einen Zeitraum von 5 Jahren, die Überlebenswahrscheinlichkeit kurzfristig deutlich verbessern würde. Es ergab sich allerdings kein Unterschied, ob 5, 10 oder 15 Individuen ausgewildert werden. Eine länger durchgeführte Auswilderung würde vermutlich die Überlebenswahrscheinlichkeit entsprechend langfristiger verbessern.

Small livestock is an important resource for rural human populations in dry climates. How strongly will climate change affect the capacity of the rangeland? We used hierarchical modelling to scale quantitatively the growth of shrubs and annual plants, the main food of sheep and goats, to the landscape extent in the eastern Mediterranean region. Without grazing, productivity increased in a sigmoid way with mean annual precipitation. Grazing reduced productivity more strongly the drier the landscape. At a point just under the stocking capacity of the vegetation, productivity declined precipitously with more intense grazing due to a lack of seed production of annuals. We repeated simulations with precipitation patterns projected by two contrasting IPCC scenarios. Compared to results based on historic patterns, productivity and stocking capacity did not differ in most cases. Thus, grazing intensity remains the stronger impact on landscape productivity in this dry region even in the future. / Kleinvieh ist eine wichtige Lebensgrundlage für die Landbevölkerung in trockenen Regionen. Wie stark wird sich der Klimawandel auf die Tragfähigkeit der Weideflächen auswirken? Wir benutzten hierarchische Modellierung, um das Wachstum von Sträuchern und einjährigen Kräutern, das wichtigste Futter für Ziegen und Schafe, quantitativ auf die Fläche von Landschaften in der östlichen Mittelmeerregion zu dimensionieren. Die Produktivität ohne Beweidung stieg sigmoidal mit dem mittleren Jahresniederschlag. Je trockener die Landschaft, desto stärker verminderte Beweidung die Produktion. An einem Punkt knapp unter der Tragfähigkeit der Vegetation, sank die Produktion stark mit zunehmender Beweidung, weil die Samenproduktion der Kräuter zu gering war. Wir wiederholten die Simulationen mit Niederschlagsverteilungsmustern gemäß zweier gegensätzlicher IPCC-Szenarien. Zukünftige Produktivität und Tragfähigkeit unterschieden sich in den meisten Fällen nicht von Ergebnissen auf Grund von historischer Niederschlagsverteilung. Allerdings war die zukünftige Produktivität in trockenen Habitaten der semiariden und trocken-mediterranen Regionen niedriger. Somit hat auch in Zukunft die Besatzdichte die größere Auswirkung auf die Produktivität dieser trockenen Landschaft als das Klima. "This abstract is provided by the authors, and is for convenience of the users only. The author certifies that the translation faithfully represents the official version in the language of the journal, which is the published Abstract of record and is the only Abstract to be used for reference and citation."

The paper presents a simulation and parameter-estimation approach for evaluating stochastic patterns of population growth and spread of an annual forest herb, Melampyrum pratense (Orobanchaceae). The survival of a species during large-scale changes in land use and climate will depend, to a considerable extent, on its dispersal and colonisation abilities. Predictions on species migration need a combination of field studies and modelling efforts. Our study on the ability of M. pratense to disperse into so far unoccupied areas was based on experiments in secondary woodland in NE Germany. Experiments started in 1997 at three sites where the species was not yet present, with 300 seeds sown within one square meter. Population development was then recorded until 2001 by mapping of individuals with a resolution of 5 cm. Additional observations considered density dependence of seed production. We designed a spatially explicit individual-based computer simulation model to explain the spatial patterns of population development and to predict future population spread. Besides primary drop of seeds (barochory) it assumed secondary seed transport by ants (myrmecochory) with an exponentially decreasing dispersal tail. An important feature of populationpattern explanation was the simultaneous estimation of both population-growth and dispersal parameters from consistent spatio-temporal data sets. As the simulation model produced stochastic time series and random spatially discrete distributions of individuals we estimated parameters by minimising the expectation of weighted sums of squares. These sums-ofsquares criteria considered population sizes, radial population distributions around the area of origin and distributions of individuals within squares of 25*25 cm, the range of density action. Optimal parameter values, together with the precision of the estimates, were obtained from calculating sums of squares in regular grids of parameter values. Our modelling results showed that transport of fractions of seeds by ants over distances of 1…2 m was indispensable for explaining the observed population spread that led to distances of at most 8 m from population origin within 3 years. Projections of population development over 4 additional years gave a diffusion-like increase of population area without any “outposts”. This prediction generated by the simulation model gave a hypothesis which should be revised by additional field observations. Some structural deviations between observations and model output already indicated that for full understanding of population spread the set of dispersal mechanisms assumed in the model may have to be extended by additional features of plant-animal mutualism.

An increasing demand for food, and in particular animal products, is putting high pressure on natural resources, often at places distant from the consumption. Nitrogen and phosphorus are essential nutrients in food production but an excessive use can cause environmental impacts such as eutrophication that can harm ecosystems services vital to local communities. This study developed sub-national spatially explicit N and P footprints that were extended with an assessment of nutrient leaching risk and risk of impact on biodiversity. The consumption of N and P in Brazilian soybean production at municipal level was estimated for the whole of Brazil as well as for UK soybean demand. This was then combined with the risk of nutrient leaching (Nrisk and Prisk) and species richness (Nbio and Pbio). The results showed high Nbio and Pbio in Mato Grosso, Paraná, and Rio Grande do Sul. The same analysis of the effects of UK soybean demand showed a higher risk of impacts in Rondônia and less in Paraná and Rio Grande do Sul compared to total Brazilian soybean production. A municipal case study showed that the demand of Brazilian soybean in the UK, EU, and China generated different spatial patterns of impact risks at municipal level. Spatially explicit footprints that also encompass risks of impacts are important for being able to identify the responsible consumer and parts of the supply chain where sustainability interventions will be most effective. There are several opportunities for future development within this research field as data availability is continuingly increasing.

Understanding the link between environmental factors such as disturbance events, land cover, and soil productivity to spatial variation in animal distributions and vital rates is fundamental to population ecology and wildlife management. The Longleaf pine (Pinus palustris; hereafter, LLP) ecosystem is an archetypal fire-mediated ecosystem, which has seen drastic reductions in land area due to fire suppression. Current restoration utilizes prescribed fire and hardwood removal, but more research is needed to understand the influence of these restoration efforts on the wildlife that exist in that ecosystem. As such, we conducted field surveys on Camp Blanding Joint Training Center and Wildlife Management Area to understand how fire influences relative abundances of mammalian predators, occupancy and species richness of avian species, guilds and communities, and vital rates of white-tailed deer (Odocoileus viginianus) fawns. Our results indicated that mammalian predator space use, and avian species richness were influenced by fire and land cover. Mammalian predator space use was altered by fire conditions and land cover. This mechanism may support predator management strategies that utilizes commonly management techniques for the restoration and conservation of the LLP ecosystem to indirectly alter predator distributions, which has the potential to positively affect the management of important species within this ecosystem. Some mammalian mesocarnivores historically common throughout the southeastern United States were rarely detected, suggesting more research is needed to identify the cause of the potential decline in mesocarnivores in the Southeastern United States. Avian species richness at the community level was positively influenced by the heterogeneity of post fire conditions, or pyrodiversity. Avian species richness of the cavity nesting guild was negatively influenced by increasing time-since-fire. Our results suggest that managers can promote avian community diversity by reducing the size of burn units to create areas with multiple adjacent burn units, with unique fire histories and a mosaic of post-fire conditions. Lastly, fawn recruitment was greater on the higher productivity site than the low productivity site on CB. However, within sites soil productivity did not have a demonstrable effect. In fact, we observed differences between sites, but did not observe any effects of covariates on spatial variation in density or survival of fawns within sites. Although we did not explicitly test the factors influencing our parameters between sites, we hypothesize that the variation in coyote activity rates as well as soil productivity and its subsequent effects (i.e. forage availability, concealment cover, and land cover type) likely drove the differences we saw between sites. These results are relevant to local managers and provide support for unit-specific, deer management on CB. In conclusion, understanding the influence of fire in a frequently burned landscape allows us to better inform management of predators and avian communities using prescribed burns, and the differences in deer populations between areas allowed us to better in inform managers on harvest quotas so that the magnitude of the effect of harvest can better match the population vital rates of each area. / Master of Science / Understanding the link between environmental factors such as fire, land cover and soil productivity is essential for wildlife managers to maintain healthy wildlife populations. The Longleaf pine (Pinus palustris) ecosystem requires frequent fire and has seen drastic reductions in land area due to fire suppression. Current restoration utilizes prescribed fire, controlled burning of an area, and hardwood removal, logging hardwood trees such as oaks, but more research is needed to understand how this restoration influences the wildlife in the longleaf pine ecosystem. As such, we collected data collected from Camp Blanding Joint Training Center and Wildlife Management Area to understand how fire influences the relative numbers of mammalian predators, the distribution and species richness (i.e. number of unique species) of avian species, guilds and communities, and vital rates (i.e. births, survival to a certain age) of white-tailed deer fawns. Our results indicated that mammalian predator distributions, and avian species richness were influenced by fire and land cover. Mammalian predator space use was altered by fire conditions and landcover, which supports a predator management strategy that utilizes prescribed burning and hardwood removal used in restoration and conservation of the LLP ecosystem to indirectly alter predator distributions. Some mammalian mesocarnivores (i.e. foxes, skunks, weasels, etc.) historically common throughout the southeastern United States were rarely detected, suggesting more research is needed to identify the cause of the potential decline of cryptic mesocarnivores in the Southeastern United States. Avian species richness, number of unique species, at the community level was positively influenced by pyrodiversity, the number of unique burn years in an area. This supports and further extends the 'pyrodiversity begets biodiversity' hypothesis for avian species, which states that greater pyrodiversity increases the diversity of bird species in that area. Avian species richness of cavity nesting birds decreased with increasing time since fire. Our results suggest that managers can promote avian community diversity by reducing the size of burn units to create areas with multiple adjacent burn units, with unique fire histories and a mosaic of post-fire conditions. Lastly, fawn recruitment was greater on the higher productivity site than the low productivity site, however, within sites soil productivity did not seem to influence birth and recruitment. Although we did not statistically test the factors influencing our parameters between sites, we hypothesize that the variation in coyote activity rates as well as soil productivity and its subsequent effects (i.e. forage availability, concealment cover, and land cover type) likely drove the differences we saw between sites. These results are relevant to local managers and provide support for managing deer differently across both sites. In conclusion, understanding the influence of fire in a frequently burned landscape allows us to better inform management of predators and avian communities using prescribed burns, and the differences in deer populations between areas allowed us to better in inform managers on harvest quotas so that the magnitude of the effect of harvest can better match the population vital rates of each area.

The pronounced constraints on ecosystem functioning and human livelihoods in drylands are frequently exacerbated by natural and socio-economic stresses, including weather extremes and inequitable trade conditions. Therefore, a better understanding of the relation between these stresses and the socio-ecological systems is important for advancing dryland development. The concept of vulnerability as applied in this dissertation describes this relation as encompassing the exposure to climate, market and other stresses as well as the sensitivity of the systems to these stresses and their capacity to adapt. With regard to the interest in improving environmental and living conditions in drylands, this dissertation aims at a meaningful generalisation of heterogeneous vulnerability situations. A pattern recognition approach based on clustering revealed typical vulnerability-creating mechanisms at global and local scales. One study presents the first analysis of dryland vulnerability with global coverage at a sub-national resolution. The cluster analysis resulted in seven typical patterns of vulnerability according to quantitative indication of poverty, water stress, soil degradation, natural agro-constraints and isolation. Independent case studies served to validate the identified patterns and to prove the transferability of vulnerability-reducing approaches. Due to their worldwide coverage, the global results allow the evaluation of a specific system’s vulnerability in its wider context, even in poorly-documented areas. Moreover, climate vulnerability of smallholders was investigated with regard to their food security in the Peruvian Altiplano. Four typical groups of households were identified in this local dryland context using indicators for harvest failure risk, agricultural resources, education and non-agricultural income. An elaborate validation relying on independently acquired information demonstrated the clear correlation between weather-related damages and the identified clusters. It also showed that household-specific causes of vulnerability were consistent with the mechanisms implied by the corresponding patterns. The synthesis of the local study provides valuable insights into the tailoring of interventions that reflect the heterogeneity within the social group of smallholders. The conditions necessary to identify typical vulnerability patterns were summarised in five methodological steps. They aim to motivate and to facilitate the application of the selected pattern recognition approach in future vulnerability analyses. The five steps outline the elicitation of relevant cause-effect hypotheses and the quantitative indication of mechanisms as well as an evaluation of robustness, a validation and a ranking of the identified patterns. The precise definition of the hypotheses is essential to appropriately quantify the basic processes as well as to consistently interpret, validate and rank the clusters. In particular, the five steps reflect scale-dependent opportunities, such as the outcome-oriented aspect of validation in the local study. Furthermore, the clusters identified in Northeast Brazil were assessed in the light of important endogenous processes in the smallholder systems which dominate this region. In order to capture these processes, a qualitative dynamic model was developed using generalised rules of labour allocation, yield extraction, budget constitution and the dynamics of natural and technological resources. The model resulted in a cyclic trajectory encompassing four states with differing degree of criticality. The joint assessment revealed aggravating conditions in major parts of the study region due to the overuse of natural resources and the potential for impoverishment. The changes in vulnerability-creating mechanisms identified in Northeast Brazil are well-suited to informing local adjustments to large-scale intervention programmes, such as “Avança Brasil”. Overall, the categorisation of a limited number of typical patterns and dynamics presents an efficient approach to improving our understanding of dryland vulnerability. Appropriate decision-making for sustainable dryland development through vulnerability reduction can be significantly enhanced by pattern-specific entry points combined with insights into changing hotspots of vulnerability and the transferability of successful adaptation strategies. / Die Grenzen ökologischer Funktionen und menschlicher Lebensweisen in Trockengebieten werden häufig durch natürlichen und sozio-ökonomischen Stress, wie extreme Wetterereignisse und ungerechte Handelsbedingungen, weiter verengt. Zur Förderung der Entwicklung in Trockengebieten ist es daher wichtig, die Beziehung zwischen den Stressfaktoren und den sozio-ökologischen Systemen besser zu verstehen. Das Konzept der Vulnerabilität, welches in der vorliegenden Dissertation angewandt wird, beschreibt dieses Verhältnis durch die Exposition, Sensitivität und Anpassungsfähigkeit von Systemen im Hinblick auf Klima-, Markt- und anderen Stress. Bezüglich des Interesses, die Umwelt- und Lebensbedingungen in Trockengebieten zu verbessern, zielt diese Dissertation darauf ab, die vielschichtigen Ursachen und Veränderungen von Vulnerabilität sinnvoll zu verallgemeinern. Eine clusterbasierte Mustererkennung zeigte typische Mechanismen auf, welche Vulnerabilität auf globaler und lokaler Ebene verursachen. Dabei stellt die globale Studie die erste flächendeckende Untersuchung von Vulnerabilität in Trockengebieten mit sub-nationaler Auflösung dar. Die Clusteranalyse identifizierte sieben typische Muster basierend auf der quantitativen Beschreibung von Armut, Wasserknappheit, Bodendegradation, natürlichen Produktionshemmnissen und Isolation. Die Gültigkeit der ermittelten Cluster und die Übertragbarkeit von Anpassungsmaßnahmen innerhalb ähnlicher Gebiete wurden anhand unabhängiger Fallstudien belegt. Die flächendeckende Erfassung erlaubt es, die Vulnerabilität eines Systems in seinem größeren Kontext zu bewerten, auch in weniger gut durch Fallstudien dokumentierten Gebieten. Weiterhin wurde die Klimavulnerabilität von Kleinbauern bezüglich ihrer Nahrungsmittelsicherung im peruanischen Altiplano untersucht. In diesem lokalen Kontext wurden vier Cluster von Haushalten gemäß ihrer Produktionsrisiken, landwirtschaftlichen Ressourcen, der Bildung und ihres nicht-landwirtschaftlichen Einkommens unterschieden. Eine erweiterte Gültigkeitsprüfung unter Nutzung unabhängig erhobener Informationen stellte heraus, dass wetterbedingte Schäden mit den ermittelten Clustern korrelieren und dass haushaltsspezifische Schadensursachen mit den durch die Muster angezeigten Mechanismen übereinstimmen. Die lokale Studie liefert wertvolle Hinweise auf bedarfsgerechte Eingriffe unter Beachtung der Heterogenität innerhalb der sozialen Gruppe der Kleinbauern. Die notwendigen Bedingungen zur Erkennung typischer Muster ergaben fünf methodische Schritte. Ihre Darlegung soll die Anwendung der gewählten Methode in zukünftigen Vulnerabilitätsstudien anregen und erleichtern. Die fünf Schritte umfassen die Ableitung relevanter Ursache-Wirkungs-Hypothesen, die Quantifizierung der Mechanismen, die Bewertung von Robustheit und Gültigkeit sowie die Ordnung der ermittelten Muster nach dem Grad der Vulnerabilität. Dabei ist die genaue Beschreibung der Hypothesen eine wesentliche Voraussetzung für die Quantifizierung der grundlegenden Prozesse sowie eine einheitliche Interpretation, Gültigkeitsprüfung und Ordnung der ermittelten Muster. Besondere Beachtung finden skalenbedingte Aspekte, wie beispielsweise die ergebnisorientierte Gültigkeitsprüfung in der lokalen Studie. Weiterhin wurden die in Nordostbrasilien ermittelten Cluster im Hinblick auf wichtige endogene Prozesse in den dort vorherrschenden kleinbäuerlichen Nutzungssystemen untersucht. Diese Prozesse umfassen die Aufteilung der Arbeitskraft, die landwirtschaftliche Produktion sowie Einkommens- und Ressourcendynamiken. Sie wurden in einem qualitativen dynamischen Modell erfasst, welches eine zyklische Trajektorie mit vier unterschiedlich problematischen Entwicklungszuständen ergab. Als besonders problematischer Aspekt verschärfte sich die Vulnerabilität in weiten Teilen des Untersuchungsgebietes durch die Übernutzung natürlicher Ressourcen und die Möglichkeit weiterer Verarmung. Die in Nordostbrasilien gezeigten Veränderungen sind dazu geeignet, groß angelegte Entwicklungsprogramme, wie zum Beispiel “Avança Brasil”, angemessen an lokale Gegebenheiten anzupassen. Insgesamt ermöglicht es die Kategorisierung einer begrenzten Anzahl typischer Muster und Veränderungen, die Vulnerabilität in Trockengebieten besser zu verstehen. Eine nachhaltige Entwicklung von Trockengebieten basierend auf der Minderung von Vulnerabilität kann durch musterspezifische Ansätze zusammen mit Hinweisen zu Veränderungen im Schweregrad und zur Übertragbarkeit erfolgreicher Anpassungsstrategien wirkungsvoll unterstützt werden.