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Bewertung und Auswirkungen der Simulationsgüte führender Klimamoden in einem Multi-Modell Ensemble
(2013)
Der rezente und zukünftige Anstieg der atmosphärischen Treibhausgaskonzentration bedeutet für das terrestrische Klimasystem einen grundlegenden Wandel, der für die globale Gesellschaft schwer zu bewältigende Aufgaben und Herausforderungen bereit hält. Eine effektive, rühzeitige Anpassung an diesen Klimawandel profitiert dabei enorm von möglichst genauen Abschätzungen künftiger Klimaänderungen.
Das geeignete Werkzeug hierfür sind Gekoppelte Atmosphäre Ozean Modelle (AOGCMs). Für solche Fragestellungen müssen allerdings weitreichende Annahmen über die zukünftigen klimarelevanten Randbedingungen getroffen werden. Individuelle Fehler dieser Klimamodelle, die aus der nicht perfekten Abbildung der realen Verhältnisse und Prozesse resultieren, erhöhen die Unsicherheit langfristiger Klimaprojektionen. So unterscheiden sich die Aussagen verschiedener AOGCMs im Hinblick auf den zukünftigen Klimawandel insbesondere bei regionaler Betrachtung, deutlich. Als Absicherung gegen Modellfehler werden üblicherweise die Ergebnisse mehrerer AOGCMs, eines Ensembles an Modellen, kombiniert. Um die Abschätzung des Klimawandels zu präzisieren, wird in der vorliegenden Arbeit der Versuch unternommen, eine Bewertung der Modellperformance der 24 AOGCMs, die an der dritten Phase des Vergleichsprojekts für gekoppelte Modelle (CMIP3) teilgenommen haben, zu erstellen. Auf dieser Basis wird dann eine nummerische Gewichtung für die Kombination des Ensembles erstellt. Zunächst werden die von den AOGCMs simulierten Klimatologien für einige
grundlegende Klimaelemente mit den betreffenden klimatologien verschiedener Beobachtungsdatensätze quantitativ abgeglichen. Ein wichtiger methodischer Aspekt
hierbei ist, dass auch die Unsicherheit der Beobachtungen, konkret Unterschiede zwischen verschiedenen Datensätzen, berücksichtigt werden. So zeigt sich, dass die Aussagen, die aus solchen Ansätzen resultieren, von zu vielen Unsicherheiten in den Referenzdaten beeinträchtigt werden, um generelle Aussagen zur Qualität von AOGCMs zu treffen. Die Nutzung der Köppen-Geiger Klassifikation offenbart jedoch, dass die prinzipielle Verteilung der bekannten Klimatypen im kompletten CMIP3 in vergleichbar guter Qualität reproduziert wird. Als Bewertungskriterium wird daher hier die Fähigkeit der AOGCMs die großskalige natürliche Klimavariabilität, konkret die hochkomplexe gekoppelte
El Niño-Southern Oscillation (ENSO), realistisch abzubilden herangezogen. Es kann anhand verschiedener Aspekte des ENSO-Phänomens gezeigt werden, dass nicht alle AOGCMs hierzu mit gleicher Realitätsnähe in der Lage sind. Dies steht im Gegensatz zu den dominierenden Klimamoden der Außertropen, die modellübergreifend überzeugend repräsentiert werden. Die wichtigsten Moden werden, in globaler Betrachtung, in verschiedenen Beobachtungsdaten über einen neuen Ansatz identifiziert. So können für einige bekannte Zirkulationsmuster neue Indexdefinitionen gewonnen werden, die sich sowohl als äquivalent zu den Standardverfahren erweisen und im Vergleich zu diesen zudem eine deutliche Reduzierung
des Rechenaufwandes bedeuten. Andere bekannte Moden werden dagegen als weniger bedeutsame, regionale Zirkulationsmuster eingestuft. Die hier vorgestellte
Methode zur Beurteilung der Simulation von ENSO ist in guter Übereinstimmung mit anderen Ansätzen, ebenso die daraus folgende Bewertung der gesamten Performance
der AOGCMs. Das Spektrum des Southern Oscillation-Index (SOI) stellt somit eine aussagekräftige Kenngröße der Modellqualität dar.
Die Unterschiede in der Fähigkeit, das ENSO-System abzubilden, erweisen sich als signifikante Unsicherheitsquelle im Hinblick auf die zukünftige Entwicklung einiger fundamentaler und bedeutsamer Klimagrößen, konkret der globalen Mitteltemperatur,
des SOIs selbst, sowie des indischen Monsuns. Ebenso zeigen sich signifikante Unterschiede für regionale Klimaänderungen zwischen zwei Teilensembles des CMIP3, die auf Grundlage der entwickelten Bewertungsfunktion eingeteilt werden. Jedoch sind diese Effekte im Allgemeinen nicht mit den Auswirkungen der
anthropogenen Klimaänderungssignale im Multi-Modell Ensemble vergleichbar, die für die meisten Klimagrößen in einem robusten multivariaten Ansatz detektiert und
quantifiziert werden können. Entsprechend sind die effektiven Klimaänderungen, die sich bei der Kombination aller Simulationen als grundlegende Aussage des
CMIP3 unter den speziellen Randbedingungen ergeben nahezu unabhängig davon, ob alle Läufe mit dem gleichen Einfluss berücksichtigt werden, oder ob die erstellte nummerische Gewichtung verwendet wird. Als eine wesentliche Begründung hierfür kann die Spannbreite der Entwicklung des ENSO-Systems identifiziert werden. Dies
bedeutet größere Schwankungen in den Ergebnissen der Modelle mit funktionierendem ENSO, was den Stellenwert der natürlichen Variabilität als Unsicherheitsquelle
in Fragen des Klimawandels unterstreicht. Sowohl bei Betrachtung der Teilensembles als auch der Gewichtung wirken sich dadurch gegenläufige Trends im SOI
ausgleichend auf die Entwicklung anderer Klimagrößen aus, was insbesondere bei letzterem Vorgehen signifikante mittlere Effekte des Ansatzes, verglichen mit der
Verwendung des üblichen arithmetischen Multi-Modell Mittelwert, verhindert.
Climate change assessment in Southeast Asia and implications for agricultural production in Vietnam
(2011)
For many years, the study of climatic changes and variations has become the main objective of climatic research, as has been appreciated in the IPCC's reports and several publications regarding climatic evolution on different space-time scales. Since the 80's, many research groups have generated the extensive database from which the analysis of temperature, precipitation and other climatic parameters has been performed on a global scale (Jones et al., 1986; Hansen and Lebedeff, 1987, 1988; Vinnikov et al., 1987, 1990). The most important result of these research projects is the evidence of global warming during the 20th century, especially in the last two decades. However, numerous challenges still exist about the structure and dimension of the climatic change on a considerable scale. Therefore, it is necessary to carry out studies on a local and regional scale that allow for a more precise evaluation of the global warming phenomenon. A statistical analysis approach was developed to identify systematic differences between large-scale climatic variable from the General Circulation Models (GCM), NCEP, CRU re-analysis data set and climatic parameters (temperature and precipitation data). Models are able to satisfactorily reproduce the spatial patterns of the regional temperature and precipitation field. The response of the climate system to various emission scenario simulated by the GCM was used to analyze and predict the local climate change. The main objective of this study is to analysis the time evolution of the annual and seasonal temperature and precipitation during the 21st century and in order to contribute to our knowledge of temperature and precipitation trends over the century on a regional scale, not only in Southeast Asia but also in Vietnam; the study focuses to develop a dynamical – statistical model describing the relationship between the major climate variation and agricultural production in Vietnam. This study will be an important contribution to the present-day assessment of climate change impacts in the low latitudes. Regional scenarios of climate change, including both rainfall and mean temperature were then used to assess the impact of climate change on crop production in the region in order to evaluate the vulnerability of the system to global warming. Climate change has adverse impacts on the socio - economic development of all nations. But the degree of the impact will vary across nations. It is expected that changes in the earth's climate will impact on developing countries like Vietnam, in particular, hardest because their economies are strongly dependent on crude forms of natural resources and their economic structure is less flexible to adjust to such drastic changes. In Chapter 1: Introduction and background I describe in general terms climate, climate change, climate change model with benefits and problems. Chapter 2: methodology discusses the methods including interpolation, validation, clustering, correlation and regression which were applied in the study. Chapter 3 and chapter 4 describe the database and study area. The most important is chapter 5 Results. The last is chapter 6 Conclusion and outlook followed by the reference list and an appendix.
Climate
Changes
Global Perspectives
brings together creative approaches to representing environmental crises in a globalized world, which originated in an eponymous symposium hosted virtually by the University of Würzburg in August of 2021. This volume, and the unruly texts that claim space here, are written not only to question and challenge standardized patterns of representation, but also to contribute to undisciplining the genres and practices of traditional academic writing by exploring alternative representational form(at)s.
Climate Changes Global Perspectives is the first publication in the Challenges of Modernity series, which seeks to collect and make available projects of engaged scholarship in the humanities.
Combined effects of climate change and extreme events on plants, arthropods and their interactions
(2013)
I. Global climate change directly and indirectly influences biotic and abiotic components of ecosystems. Changes in abiotic ecosystem components caused by climate change comprise temperature increases, precipitation changes and more frequently occurring extreme events. Mediated by these abiotic changes, biotic ecosystem components including all living organisms will also change. Expected changes of plants and animals are advanced phenologies and range shifts towards higher latitudes and altitudes which presumably induce changes in species interactions and composition. Altitudinal gradients provide an optimal opportunity for climate change studies, because they serve as natural experiments due to fast changing climatic conditions within short distances. In this dissertation two different approaches were conducted to reveal species and community responses to climate change. First, species richness and community trait analyses along an altitudinal gradient in the Bavarian Alps (chapters II, III) and second, climate change manipulation experiments under different climatic contexts (chapters IV, V, IV). II. We performed biodiversity surveys of butterfly and diurnal moth species on 34 grassland sites along an altitudinal gradient in the National Park Berchtesgaden. Additionally, we analysed the dominance structure of life-history traits in butterfly assemblages along altitude. Species richness of butterflies and diurnal moths decreased with increasing altitude. The dominance of certain life-history-traits changed along the altitudinal gradient with a higher proportion of larger-winged species and species with higher egg numbers towards higher altitudes. However, the mean egg maturation time, population density and geographic distribution within butterfly assemblages decreased with increasing altitude. Our results indicate that butterfly assemblages were mainly shaped by environmental filtering. We conclude that butterfly assemblages at higher altitudes will presumably lack adaptive capacity to future climatic conditions, because of specific trait combinations. III. In addition to butterfly and diurnal moth species richness we also studied plant species richness in combination with pollination type analyses along the altitudinal gradient. The management type of the alpine grasslands was also integrated in the analyses to detect combined effects of climate and management on plant diversity and pollination type. Plant species richness was highest at intermediate altitudes, whereby the management type influenced the plant diversity with more plant species at grazed compared to mown or non-managed grasslands. The pollination type was affected by both the changing climate along the gradient and the management type. These results suggest that extensive grazing can maintain high plant diversity along the whole altitudinal gradient. With ongoing climate change the diversity peak of plants may shift upwards, which can cause a decrease in biodiversity due to reduced grassland area but also changes in species composition and adaptive potential of pollination types. IV. We set up manipulation experiments on 15 grassland sites along the altitudinal gradient in order to determine the combined effects of extreme climatic events (extreme drought, advanced and delayed snowmelt) and elevation on the nutritional quality and herbivory rates of alpine plants. The leaf CN (carbon to nitrogen) ratio and the plant damage through herbivores were not significantly affected by the simulated extreme events. However, elevation influenced the CN ratios and herbivory rates of alpine plants with contrasting responses between plant guilds. Furthermore, we found differences in nitrogen concentrations and herbivory rates between grasses, legumes and forbs, whereas legumes had the highest nitrogen concentrations and were damaged most. Additionally, CN ratios and herbivory rates increased during the growing season, indicating a decrease of food plant quality during the growing season. Contrasting altitudinal responses of grasses, legumes and forbs presumably can change the dominance structure among these plant guilds with ongoing climate change. V. In this study we analysed the phenological responses of grassland species to an extreme drought event, advanced and delayed snowmelt along the altitudinal gradient. Advanced snowmelt caused an advanced beginning of flowering, whereas this effect was more pronounced at higher than at lower altitudes. Extreme drought and delayed snowmelt had rather low effects on the flower phenology and the responses did not differ between higher and lower sites. The strongest effect influencing flower phenology was altitude, with a declining effect through the season. The length of flowering duration was not significantly influenced by treatments. Our data suggest that plant species at higher altitudes may be more affected by changes in snowmelt timing in contrast to lowland species, as at higher altitudes more severe changes are expected. However, the risk of extreme drought events on flowering phenology seems to be low. VI. We established soil-emergence traps on the advanced snowmelt and control treatment plots in order to detect possible changes in abundances and emergence phenologies of five arthropod orders due to elevation and treatment. Additionally, we analysed the responses of Coleoptera species richness to elevation and treatment. We found that the abundance and species richness of Coleoptera increased with elevation as well as the abundance of Diptera. However, the abundance of Hemiptera decreased with elevation and the abundances of Araneae and Hymenoptera showed no elevational patterns. The advanced snowmelt treatment increased the abundances of Araneae and Hymenoptera. The emergence of soil-hibernating arthropods was delayed up to seven weeks at higher elevations, whereas advanced snowmelt did not influence the emergence phenology of arthropods immediately after snowmelt. With climate change earlier snowmelt will occur more often, which especially will affect soil-hibernating arthropods in alpine regions and may cause desynchronisations between species interactions. VII. In conclusion, we showed that alpine ecosystems are sensitive towards changing climate conditions and extreme events and that many alpine species in the Bavarian Alps are endangered. Many alpine species could exist under warmer climatic conditions, however they are expected to be outcompeted by more competitive lowland species. Furthermore, host-parasite or predator-prey interactions can be disrupted due to different responses of certain guilds to climate change. Understanding and predicting the complex dynamics and potential risks of future climate change remains a great challenge and therefore further studies analysing species and community responses to climate change are needed.
The glaciers in Norway exert a strong influence on Norwegian economy and society. Unlike many glaciers elsewhere and despite ongoing climate change and warming, many of them showed renewed advances and positive net mass changes in the 1980's and 1990's, followed by rapid retreats and mass losses since 2000. This difference in behaviour may be attributed to differences and shifts in the glaciological regime - the differences in the magnitude of impacts of climatic and non-climatic geographical factors on the glacier mass.
This study investigates the influence of various atmospheric variables on mass balance changes of a selection of glaciers in Norway by means of Pearson correlation analyses and cross-validated stepwise multiple regression analyses. The analyses are carried out for three time periods (1949-2008, 1949-1988, 1989-2008) separately in order to take into consideration the possible shift in the glaciological regime in the 1980's. The atmospheric variables are constructed from ERA40 and NCEP/NCAR re-analysis datasets and include regional means of seasonal air temperature and precipitation rates and atmospheric circulation indices. The multiple regression models trained in these time periods are then applied to predictors reconstructed from the CMIP3 climate model dataset to generate an estimate for mass changes from the year 1950 to 2100. The temporal overlap of estimates and observations is used for calibration. Finally, observed atmospheric states in seasons that are characterised by a particularly positive or negative mass balance are categorised into time periods of modelled climate by the application of a Bayesian classification procedure.
The strongest influence on winter mass balance is exerted by different indices of the North Atlantic Oscillation (NAO), Northern Annular Mode (NAM) and precipitation. The correlation coefficients and explained variances determined from the multiple regression analyses reveal an East-West gradient, suggesting a weaker influence of the NAO and NAM on glaciers underlying a more continental regime. The highest correlation coefficients and explained variances were obtained for the 1989-2008 time period, which might be due to a strong and predominantly positive phase of the NAO. Multi-model ensemble means of the estimates show a mass loss for all three eastern glaciers, while the estimates for the more maritime glaciers are ambivalent. In general, the estimates show a greater sensitivity to the training time period than to the greenhouse gas emission scenarios according to which the climates were simulated. The average net mass change by the end of 2100 is negative for all glaciers except for the northern Engabreen. For many glaciers, the Bayesian classification of observed atmospheric states into time periods of modelled climate reveals a decrease in probability of atmospheric states favouring extremes in winter, and an increase in probability of atmospheric states favouring extreme mass loss in summer for the distant future (2071-2100). This pattern of probabilities for the ablation season is most pronounced for glaciers underlying a continental and intermediate regime.
I. Climate change comprises average temperatures rise, changes in the distribution of precipitation and an increased amount and intensity of extreme climatic events in the last decades. Considering these serious changes in the abiotic environment it seems obvious that ecosystems also change. Flora and fauna have to adapt to the fast changing conditions, migrate or go extinct. This might result in shifts in biodiversity, species composition, species interactions and in ecosystem functioning and services. Mountains play an important role in the research of these climate impacts. They are hotspots of biodiversity and can be used as powerful natural experiments as they provide, within short distances, the opportunity to research changes in the ecosystem induced by different climatic contexts. In this dissertation two approaches were pursued: i) surveys of biodiversity, trait dominance and assembly rules in communities depending on the climatic context and different management regimes were conducted (chapters II and III) and ii) the effects of experimental climate treatments on essential ecosystem features along the altitudinal gradient were assessed (chapters IV, V and VI). II. We studied the relative importance of management, an altitudinal climatic gradient and their interactions for plant species richness and the dominance of pollination types in 34 alpine grasslands. Species richness peaked at intermediate temperatures and was higher in grazed grasslands compared to non-managed grasslands. We found the climatic context and also management to influence the distribution and dominance structures of wind- and insect-pollinated plants. Our results indicate that extensive grazing maintains high plant diversity over the full subalpine gradient. Rising temperatures may cause an upward shift of the diversity peak of plants and may also result in changed species composition and adaptive potential of pollination types. III. On the same alpine grasslands we studied the impact of the climatic context along an altitudinal gradient on species richness and community assembly in bee communities. Species richness and abundance declined linearly with increasing altitude. Bee species were more closely related at high altitudes than at low altitudes. The proportion of social and ground-nesting species, as well as mean body size and altitudinal range of bees, increased with increasing altitude, whereas the mean geographic distribution decreased. Our results suggest that community assembly at high altitudes is dominated by environmental filtering effects, while the relative importance of competition increases at low altitudes. We conclude that ongoing climate change poses a threat for alpine specialists with adaptations to cool environments but low competitive capacities. IV. We determined the impacts of short-term climate events on flower phenology and assessed whether those impacts differed between lower and higher altitudes. For that we simulated advanced and delayed snowmelt as well as drought events in a multi site experiment along an altitudinal gradient. Flower phenology was strongly affected by altitude, however, this effect declined through the season. The manipulative treatments caused only few changes in flowering phenology. The effects of advanced snowmelt were significantly greater at higher than at lower sites, but altitude did not influence the effect of the other treatments. The length of flowering duration was not significantly influenced by treatments. Our data indicate a rather low risk of drought events on flowering phenology in the Bavarian Alps. V. Changes in the structure of plant-pollinator networks were assessed along an altitudinal gradient combined with the experimental simulation of potential consequences of climate change: extreme drought events, advanced and delayed snowmelt. We found a trend of decreasing specialisation and therefore increasing complexity in networks with increasing altitude. After advanced snowmelt or drought networks were more specialised especially at higher altitudes compared to control plots. Our results show that changes in the network structures after climate manipulations depend on the climatic context and reveal an increasing susceptibility of plant-pollinator networks with increasing altitude. VI. The aim of this study was to determine the combined effects of extreme climatic events and altitude on leaf CN (carbon to nitrogen) ratios and herbivory rates in different plant guilds. We found no overall effect of climate manipulations (extreme drought events, advanced and delayed snowmelt) on leaf CN ratios and herbivory rates. However, plant guilds differed in CN ratios and herbivory rates and responded differently to altitude. CN ratios of forbs (legume and non-legume) decreased with altitude, whereas CN ratios of grasses increased with altitude. Further, CN ratios and herbivory rates increased during the growing season, indicating a decrease of food plant quality during the growing season. Insect herbivory rates were driven by food plant quality. Contrasting altitudinal responses of forbs versus grasses give reason to expect changed dominance structures among plant guilds with ongoing climate change. VII. This dissertation contributes to the understanding of factors that determine the composition and biotic interactions of communities in different climates. The results presented indicate that warmer climates will not only change species richness but also the assembly-rules for plant and bee communities depending on the species' functional traits. Our investigations provide insights in the resilience of different ecosystem features and processes towards climate change and how this resilience depends on the environmental context. It seems that mutualistic interactions are more susceptible to short-term climate events than flowering phenology and antagonistic interactions such as herbivory. However, to draw more general conclusions more empirical data is needed.
The right timing of phenological events is crucial for species fitness. Species should be highly synchronized with mutualists, but desynchronized with antagonists. With climate warming phenological events advance in many species. However, often species do not respond uniformly to warming temperatures. Species-specific responses to climate warming can lead to asynchrony or even temporal mismatch of interacting species. A temporal mismatch between mutualists, which benefit from each other, can have negative consequences for both interaction partners. For host-parasitoid interactions temporal asynchrony can benefit the host species, if it can temporally escape its parasitoid, with negative consequences for the parasitoid species, but benefit the parasitoid species if it increases synchrony with its host, which can negatively affect the host species. Knowledge about the drivers of phenology and the species-specific responses to these drivers are important to predict future effects of climate change on trophic interactions. In this dissertation I investigated how different drivers act on early flowering phenology and how climate warming affects the tritrophic relationship of two spring bees (Osmia cornuta & Osmia bicornis), an early spring plant (Pulsatilla vulgaris), which is one of the major food plants of the spring bees, and three main parasitoids of the spring bees (Cacoxenus indagator, Anthrax anthrax, Monodontomerus).
In Chapter II I present a study in which I investigated how different drivers and their change over the season affect the reproductive success of an early spring plant. For that I recorded on eight calcareous grasslands around Würzburg, Germany the intra-seasonal changes in pollinator availability, number of co-flowering plants and weather conditions and studied how they affect flower visitation rates, floral longevity and seed set of the early spring plant P. vulgaris. I show that bee abundances and the number of hours, which allowed pollinator foraging, were low at the beginning of the season, but increased over time. However, flower visitation rates and estimated total number of bee visits were higher on early flowers of P. vulgaris than later flowers. Flower visitation rates were also positively related to seed set. Over time and with increasing competition for pollinators by increasing numbers of co-flowering plants flower visitation rates decreased. My data shows that a major driver for early flowering dates seems to be low interspecific competition for pollinators, but not low pollinator abundances and unfavourable weather conditions.
Chapter III presents a study in which I investigated the effects of temperature on solitary bee emergence and on the flowering of their food plant and of co-flowering plants in the field. Therefore I placed bee cocoons of two spring bees (O. cornuta & O. bicornis) on eleven calcareous grasslands which differed in mean site temperature. On seven of these grasslands the early spring plant P. vulgaris occurred. I show that warmer temperatures advanced mean emergence in O. cornuta males. However, O. bicornis males and females of both species did not shift their emergence. Compared to the bees P. vulgaris advanced its flowering phenology more strongly with warmer temperatures. Co-flowering plants did not shift flowering onset. I suggest that with climate warming the first flowers of P. vulgaris face an increased risk of pollinator limitation whereas for bees a shift in floral resources may occur.
In Chapter IV I present a study in which I investigated the effects of climate warming on host-parasitoid relationships. I studied how temperature and photoperiod affect emergence phenology in two spring bees (O. cornuta & O. bicornis) and three of their main parasitoids (C. indagator, A. anthrax, Monodontomerus). In a climate chamber experiment with a crossed design I exposed cocoons within nest cavities and cocoons outside of nest cavities to two different temperature regimes (long-term mean of Würzburg, Germany and long-term mean of Würzburg + 4 °C) and three photoperiods (Würzburg vs. Snåsa, Norway vs. constant darkness) and recorded the time of bee and parasitoid emergence. I show that warmer temperatures advanced emergence in all studied species, but bees advanced less strongly than parasitoids. Consequently, the time period between female bee emergence and parasitoid emergence decreased in the warm temperature treatment compared to the cold one. Photoperiod influenced the time of emergence only in cocoons outside of nest cavities (except O. bicornis male emergence). The data also shows that the effect of photoperiod compared to the effect of temperature on emergence phenology was much weaker. I suggest that with climate warming the synchrony of emergence phenologies of bees and their parasitoids will amplify. Therefore, parasitism rates in solitary bees might increase which can negatively affect reproductive success and population size.
In this dissertation I show that for early flowering spring plants low interspecific competition for pollinators with co-flowering plants is a major driver of flowering phenology, whereas other drivers, like low pollinator abundances and unfavourable weather conditions are only of minor importance. With climate warming the strength of different drivers, which act on the timing of phenological events, can change, like temperature. I show that warmer temperatures advance early spring plant flowering more strongly than bee emergence and flowering phenology of later co-flowering plants. Furthermore, I show that warmer temperatures advance parasitoid emergence more strongly than bee emergence. Whereas temperature changes can lead to non-uniform temporal shifts, I demonstrate that geographic range shifts and with that altered photoperiods will not change emergence phenology in bees and their parasitoids. In the tritrophic system I investigated in this dissertation climate warming may negatively affect the reproductive success of the early spring plant and the spring bees but not of the parasitoids, which may even benefit from warming temperatures.
Der Klimawandel und insbesondere die globale Erwärmung gehören aktuell zu den größten Herausforderungen an Politik und Wissenschaft. Steigende CO2-Emissionen sind hierbei maßgeblich für die Klimaerwärmung verantwortlich. Ein regulierender Faktor beim CO2-Austausch mit der Atmosphäre ist die Vegetation, welche als CO2-Senke aber auch als CO2-Quelle fungieren kann. Diese Funktionen können durch Analysen der Landbedeckungsänderung in Kombination mit Modellierungen der Kohlenstoffbilanz quantifiziert werden, was insbesondere von aktuellen und zukünftigen politischen Instrumenten wie CDM (Clean Development Mechanism) oder REDD (Reducing Emissions from Deforestation and Degradation) gefordert wird. Vor allem in Regionen mit starker Landbedeckungsänderung und hoher Bevölkerungsdichte sowie bei geringem Wissen über die Produktivität und CO2-Speicherpotentiale der Vegetation, bedarf es einer Erforschung und Quantifizierung der terrestrischen Kohlenstoffspeicher. Eine Region, für die dies in besonderem Maße zutrifft, ist Westafrika. Jüngste Studien haben gezeigt, dass sich einerseits die Folgen des Klimawandels und Umweltveränderungen sehr stark in Westafrika auswirken werden und andererseits Bevölkerungswachstum eine starke Änderung der Landbedeckung für die Nutzung als agrarische Fläche bewirkt hat. Folglich sind in dieser Region die terrestrischen Kohlenstoffspeicher durch Ausdehnung der Landwirtschaft und Waldrodung besonders gefährdet. Große Flächen agieren anstelle ihrer ursprünglichen Funktion als CO2-Senke bereits als CO2-Quelle. [...]
Im Zeitalter des Anthropozäns rückt die Klimakrise ins Zentrum einer Betrachtung der vielschichtigen Beziehung zwischen Mensch und Wald. Die Auswirkungen des Klimawandels beeinflussen und verändern das Leben von Pflanzen und Tieren ebenso wie den menschlichen Blick auf den Wald und das forstliche Handeln in ihm. Angesichts der menschengemachten Klimaveränderungen geht die Autorin in der vorliegenden Multispezies-Ethnografie der Frage nach, wie der komplexe Wirtschafts-, Lebens- und Arbeitsort Wald speziesübergreifend geformt und gestaltet wird. Mit dem Verweis auf die Rolle tierlicher sowie pflanzlicher Agency werden dabei die Verflechtungen und gegenseitigen Abhängigkeiten der im Wald lebenden und mit dem Wald arbeitenden menschlichen wie mehr-als-menschlichen Akteur*innen in den Mittelpunkt gestellt. Zwischen klimawandelbedingten (Un)ordnungen, Störungen und Unsicherheiten ergeben sich Fragen nach dem Verhältnis zwischen menschlicher Nutzung und Bewahrung ebenso wie nach dem konkreten Umgang mit der Krise im Wald. Dabei eröffnet sich ein Blick auf die erforschten unterfränkischen Wälder als historisch und speziesübergreifend geprägte NaturenKulturen-Räume, in denen mögliche Zukünfte des gemeinsamen Lebens und Werdens ausgehandelt und gestaltet werden.
Considering its social, economic and natural conditions the Mediterranean Area is a highly vulnerable region by designated affections of climate change. Furthermore, its climatic characteristics are subordinated to high natural variability and are steered by various elements, leading to strong seasonal alterations. Additionally, General Circulation Models project compelling trends in specific climate variables within this region. These circumstances recommend this region for the scientific analyses conducted within this study. Based on the data of the CMIP3 database, the fundamental aim of this study is a detailed investigation of the total variability and the accompanied uncertainty, which superpose these trends, in the projections of temperature, precipitation and sea-level pressure by GCMs and their specific realizations. Special focus in the whole study is dedicated to the German model ECHAM5/MPI-OM. Following this ambition detailed trends and mean values are calculated and displayed for meaningful time periods and compared to reanalysis data of ERA40 and NCEP. To provide quantitative comparison the mentioned data are interpolated to a common 3x3° grid.
The total amount of variability is separated in its contributors by the application of an Analysis of Variance (ANOVA). For individual GCMs and their ensemble-members this is done with the application of a 1-way ANOVA, separating a treatment common to all ensemble-members and variability perturbating the signal given by different initial conditions. With the 2-way ANOVA the projections of numerous models and their realizations are analysed and the total amount of variability is separated into a common treatment effect, a linear bias between the models, an interaction coefficient and the residuals.
By doing this, the study is fulfilled in a very detailed approach, by considering yearly and seasonal variations in various reasonable time periods of 1961-2000 to match up with the reanalysis data, from 1961-2050 to provide a transient time period, 2001-2098 with exclusive regard on future simulations and 1901-2098 to comprise a time period of maximum length. The statistical analyses are conducted for regional-averages on the one hand and with respect to individual grid-cells on the other hand. For each of these applications the SRES scenarios of A1B, A2 and B1 are utilized. Furthermore, the spatial approach of the ANOVA is substituted by a temporal approach detecting the temporal development of individual variables. Additionally, an attempt is made to enlarge the signal by applying selected statistical methods.
In the detailed investigation it becomes evident, that the different parameters (i.e. length of temporal period, geographic location, climate variable, season, scenarios, models, etc…) have compelling impact on the results, either in enforcing or weakening them by different combinations. This holds on the one hand for the means and trends but also on the other hand for the contributions of the variabilities affecting the uncertainty and the signal. While temperature is a climate variable showing strong signals across these parameters, for precipitation mainly the noise comes to the fore, while for sea-level pressure a more differentiated result manifests. In turn, this recommends the distinguished consideration of the individual parameters in climate impact studies and processes in model generation, as the affecting parameters also provide information about the linkage within the system.
Finally, an investigation of extreme precipitation is conducted, implementing the variables of the total amount of heavy precipitation, the frequency of heavy-precipitation events, the percentage of this heavy precipitation to overall precipitation and the mean daily intensity from events of heavy precipitation. Each time heavy precipitation is defined to exceed the 95th percentile of overall precipitation. Consecutively mean values of these variables are displayed for ECHAM5/MPI-OM and the multi-model mean and climate sensitivities, by means of their difference between their average of the past period of 1981-2000 and the average of one of the future periods of 2046-2065 or 2081-2100. Following this investigation again an ANOVA is conducted providing a quantitative measurement of the severity of change of trends in heavy precipitation across several GCMs.
Besides it is a difficult task to account for extreme precipitation by GCMs, it is noteworthy that the investigated models differ highly in their projections, resulting partially in a more smoothed and meaningful multi-model mean. Seasonal alterations of the strength of this behaviour are quantitatively supported by the ANOVA.