Literatura académica sobre el tema "Terrestrische Ökologie"

At present, carbon sequestration in terrestrial ecosystems slows the growth rate of atmospheric CO₂ concentrations, and thereby reduces the impact of anthropogenic fossil fuel emissions on the climate system. Changes in climate and land use affect terrestrial biosphere structure and functioning at present, and will likely impact on the terrestrial carbon balance during the coming decades - potentially providing a positive feedback to the climate system due to soil carbon releases under a warmer climate. Quantifying changes, and the associated uncertainties, in regional terrestrial carbon budgets resulting from these effects is relevant for the scientific understanding of the Earth system and for long-term climate mitigation strategies.

A model describing the relevant processes that govern the terrestrial carbon cycle is a necessary tool to project regional carbon budgets into the future. This study (1) provides an extensive evaluation of the parameter-based uncertainty in model results of a leading terrestrial biosphere model, the Lund-Potsdam-Jena Dynamic Global Vegetation Model (LPJ-DGVM), against a range of observations and under climate change, thereby complementing existing studies on other aspects of model uncertainty; (2) evaluates different hypotheses to explain the age-related decline in forest growth, both from theoretical and experimental evidence, and introduces the most promising hypothesis into the model; (3) demonstrates how forest statistics can be successfully integrated with process-based modelling to provide long-term constraints on regional-scale forest carbon budget estimates for a European forest case-study; and (4) elucidates the combined effects of land-use and climate changes on the present-day and future terrestrial carbon balance over Europe for four illustrative scenarios - implemented by four general circulation models - using a comprehensive description of different land-use types within the framework of LPJ-DGVM.

This study presents a way to assess and reduce uncertainty in process-based terrestrial carbon estimates on a regional scale. The results of this study demonstrate that simulated present-day land-atmosphere carbon fluxes are relatively well constrained, despite considerable uncertainty in modelled net primary production. Process-based terrestrial modelling and forest statistics are successfully combined to improve model-based estimates of vegetation carbon stocks and their change over time. Application of the advanced model for 77 European provinces shows that model-based estimates of biomass development with stand age compare favourably with forest inventory-based estimates for different tree species. Driven by historic changes in climate, atmospheric CO₂ concentration, forest area and wood demand between 1948 and 2000, the model predicts European-scale, present-day age structure of forests, ratio of biomass removals to increment, and vegetation carbon sequestration rates that are consistent with inventory-based estimates. Alternative scenarios of climate and land-use change in the 21^st century suggest carbon sequestration in the European terrestrial biosphere during the coming decades will likely be on magnitudes relevant to climate mitigation strategies. However, the uptake rates are small in comparison to the European emissions from fossil fuel combustion, and will likely decline towards the end of the century. Uncertainty in climate change projections is a key driver for uncertainty in simulated land-atmosphere carbon fluxes and needs to be accounted for in mitigation studies of the terrestrial biosphere.

Kohlenstoffspeicherung in terrestrischen Ökosystemen reduziert derzeit die Wirkung anthropogener CO₂-Emissionen auf das Klimasystem, indem sie die Wachstumsrate der atmosphärischer CO₂-Konzentration verlangsamt. Die heutige terrestrische Kohlenstoffbilanz wird wesentlich von Klima- und Landnutzungsänderungen beeinflusst. Diese Einflussfaktoren werden sich auch in den kommenden Dekaden auf die terrestrische Biosphäre auswirken, und dabei möglicherweise zu einer positiven Rückkopplung zwischen Biosphäre und Klimasystem aufgrund von starken Bodenkohlenstoffverlusten in einem wärmeren Klima führen. Quantitative Abschätzungen der Wirkung dieser Einflussfaktoren - sowie der mit ihnen verbundenen Unsicherheit - auf die terrestrische Kohlenstoffbilanz sind daher sowohl für das Verständnis des Erdsystems, als auch für eine langfristig angelegte Klimaschutzpolitik relevant.

Um regionale Kohlenstoffbilanzen in die Zukunft zu projizieren, sind Modelle erforderlich, die die wesentlichen Prozesse des terrestrischen Kohlenstoffkreislaufes beschreiben. Die vorliegende Arbeit (1) analysiert die parameterbasierte Unsicherheit in Modellergebnissen eines der führenden globalen terrestrischen Ökosystemmodelle (LPJ-DGVM) im Vergleich mit unterschiedlichen ökosystemaren Messgrößen, sowie unter Klimawandelprojektionen, und erweitert damit bereits vorliegende Studien zu anderen Aspekten der Modelunsicherheit; (2) diskutiert unter theoretischen und experimentellen Aspekten verschiedene Hypothesen über die altersbedingte Abnahme des Waldwachstums, und implementiert die vielversprechenste Hypothese in das Model; (3) zeigt für eine europäische Fallstudie, wie Waldbestandsstatistiken erfolgreich für eine verbesserte Abschätzung von regionalen Kohlenstoffbilanzen in Wäldern durch prozessbasierten Modelle angewandt werden können; (4) untersucht die Auswirkung möglicher zukünftiger Klima- und Landnutzungsänderungen auf die europäische Kohlenstoffbilanz anhand von vier verschiedenen illustrativen Szenarien, jeweils unter Berücksichtigung von Klimawandelprojektionen vier verschiedener Klimamodelle. Eine erweiterte Version von LPJ-DGVM findet hierfür Anwendung, die eine umfassende Beschreibung der Hauptlandnutzungstypen beinhaltet.

Die vorliegende Arbeit stellt einen Ansatz vor, um Unsicherheiten in der prozessbasierten Abschätzung von terrestrischen Kohlenstoffbilanzen auf regionaler Skala zu untersuchen und zu reduzieren. Die Ergebnisse dieser Arbeit zeigen, dass der Nettokohlenstoffaustausch zwischen terrestrischer Biosphäre und Atmosphäre unter heutigen klimatischen Bedingungen relativ sicher abgeschätzt werden kann, obwohl erhebliche Unsicherheit über die modelbasierte terrestrische Nettoprimärproduktion existiert. Prozessbasierte Modellierung und Waldbestandsstatistiken wurden erfolgreich kombiniert, um verbesserte Abschätzungen von regionalen Kohlenstoffvorräten und ihrer Änderung mit der Zeit zu ermöglichen. Die Anwendung des angepassten Modells in 77 europäischen Regionen zeigt, dass modellbasierte Abschätzungen des Biomasseaufwuchses in Wäldern weitgehend mit inventarbasierten Abschätzungen für verschiede Baumarten übereinstimmen. Unter Berücksichtigung von historischen Änderungen in Klima, atmosphärischem CO₂-Gehalt, Waldfläche und Holzernte (1948-2000) reproduziert das Model auf europäischer Ebene die heutigen, auf Bestandsstatistiken beruhenden, Abschätzungen von Waldaltersstruktur, das Verhältnis von Zuwachs und Entnahme von Biomasse, sowie die Speicherungsraten im Kohlenstoffspeicher der Vegetation. Alternative Szenarien von zukünftigen Landnutzungs- und Klimaänderungen legen nahe, dass die Kohlenstoffaufnahme der europäischen terrestrischen Biosphäre von relevanter Größenordnung für Klimaschutzstrategien sind. Die Speicherungsraten sind jedoch klein im Vergleich zu den absoluten europäischen CO₂-Emissionen, und nehmen zudem sehr wahrscheinlich gegen Ende des 21. Jahrhunderts ab. Unsicherheiten in Klimaprojektionen sind eine Hauptursache für die Unsicherheiten in den modellbasierten Abschätzungen des zukünftigen Nettokohlenstoffaustausches und müssen daher in Klimaschutzanalysen der terrestrischen Biosphäre berücksichtigt werden.

Terrestrial environments are highly complex and dynamic. It consists of various types of soils which are constantly exposed to fluctuating conditions affecting their physical and biological properties. Moreover, soils are delivering several ecosystem services with high relevance for the human well-being such as water purification, nutrient cycling, or biodegradation. For many of those ecosystem services, microorganisms are the main drivers. In consequence, it is important to understand the functional response of microbial ecosystems to disturbances. Thus, identifying key factors for the functional stability of microbial ecosystems in terrestrial environments is of high interest. A powerful tool for analysing dynamics and underlying mechanisms of ecosystems are computational simulation models. Within this doctoral thesis, a spatiotemporally explicit bacterial simulation model was developed for assessing dynamics of biodegradation as a typical microbial ecosystem function under the influence of disturbances. Disturbances were introduced as lethal events for the bacteria within a certain, randomly picked disturbance area. The disturbance characteristics vary in the spatial configuration and frequency of the disturbance events. Functional stability was analysed in terms of the ability to recover the function after a single disturbance event, i.e. functional resilience, and the ability to maintain the function during recurrent disturbance events, i.e. functional resistance. Key factors for functional stability were assessed by systematically varying properties and processes of the microbial ecosystem and characteristics of the disturbance regime. Simulation results show a high influence of the disturbance characteristics, especially its spatial distribution pattern, on the stability of biodegradation. Functional resistance and resilience increase with fragmentation of the spatial pattern of the disturbances. The frequency of recurrent disturbance events proved also essential for the functional resistance: if the disturbances occur too often, the emergence of a functional collapse may not be preventable. However, if the fragmentation of the applied disturbance patterns increases, the function is also maintained under more frequent disturbances without a functional collapse. Ecological processes such as bacterial dispersal and growth are shown to enhance the biodegradation performance, but only under specific disturbance regimes, again depending on frequency and fragmentation of the disturbances. Dispersal networks are shown to increase the functional stability in many scenarios and, thus, may serve as a buffer mechanism against disturbances. Therefore, strategies facilitating these ecological processes, for instance stimulating fungi that act as dispersal networks for bacteria, or modulating the physical soil structure to alter the spatial configuration of disturbances are proposed to increase the functional stability of microbial ecosystems.

In north-western Germany, inland dunes and natural floodplains were widespread in the past. Due to the regulation of the natural course, large rivers have experienced serious anthropogenic influences resulting in a decline of adjacent natural floodplains. The realization of a restoration project in north-western Germany had the aim to restore a floodplain composed of inland dunes and seasonally flooded grasslands. Within this project, the response of wild bee communities to such restoration measures was evaluated. Therefore, an analysis of the succession and distribution patterns of wild bee communities in restored and target habitats was conducted. In chapter 1 and 2 the success of the restoration measures was evaluated by a comparative analysis of wild bee communities at restoration and target sites. The results show a rapid colonization of a species-rich wild bee community reflecting a community composition which is composed of generalists, specialists and parasitic species. The quantity of entomophilous plant species and the proportion of bare ground had a strong influence on wild bee species composition. To gain insight into the connectivity of wild bee populations, the population genetic structure of two wild bee species, Andrena vaga and Andrena fuscipes was analysed in chapter 3 and 4. Additionally, general intrinsic factors that maintain the genetic diversity and influence the degree of inbreeding were evaluated in chapter 5 on the basis of an extensive literature survey. These results reflect a high dispersal ability and inter-population movement of wild bees. For both species a high genetic diversity within populations and a low genetic differentiation among populations was found. In conclusion, wild bees proved to be useful indicators for monitoring the effects of restoration projects. The combination of population genetic analyses and community monitoring provides the opportunity to evaluate different aspects of restoration success.

The objective of the thesis is the model-based analysis of spatial patterns of decomposition properties on the forested slopes of the montane level (ca. 1200-2200 m a.s.l.) in a study area in the Italian Alps (Val di Sole / Val di Rabbi, Autonomous Province of Trento). The analysis includes humus forms and enchytraeid assemblages as well as pH values, activities of extracellular enzymes and C/N ratios of the topsoil. The first aim is to develop, test and apply data-based techniques for spatial modelling of soil ecological parameters. This methodological approach is based on the concept of digital soil mapping. The second aim is to reveal the relationships between humus forms, soil organisms and soil microbiological parameters in the study area. The third aim is to analyze if the spatial patterns of indicators of decomposition differ between the landscape scale and the slope scale. At the landscape scale, sample data from six sites are used, covering three elevation levels at both north- and south-facing slopes. A knowledge-based approach that combines a decision tree analysis with the construction of fuzzy membership functions is introduced for spatial modelling. According to the sampling design, elevation and slope exposure are the explanatory variables. The investigations at the slope scale refer to one north-facing and one south-facing slope, with 30 sites occurring on each slope. These sites have been derived using conditioned Latin Hypercube Sampling, and thus reasonably represent the environmental conditions within the study area. Predictive maps have been produced in a purely data-based approach with random forests. At both scales, the models indicate a high variability of spatial decomposition patterns depending on the elevation and the slope exposure. In general, sites at high elevation on north-facing slopes almost exclusively exhibit the humus forms Moder and Mor. Sites on south-facing slopes and at low elevation exhibit also Mull and Amphimull. The predictions of those enchytraeid species characterized as Mull and Moder indicators match the occurrence of the corresponding humus forms well. Furthermore, referencing the mineral topsoil, the predictive models show increasing pH values, an increasing leucine-aminopeptidase activity, an increasing ratio alkaline/acid phosphomonoesterase activity and a decreasing C/N ratio from north-facing to south-facing slopes and from high to low elevation. The predicted spatial patterns of indicators of decomposition are basically similar at both scales. However, the patterns are predicted in more detail at the slope scale because of a larger data basis and a higher spatial precision of the environmental covariates. These factors enable the observation of additional correlations between the spatial patterns of indicators of decomposition and environmental influences, for example slope angle and curvature. Both the corresponding results and broad model evaluations have shown that the applied methods are generally suitable for modelling spatial patterns of indicators of decomposition in a heterogeneous high mountain environment. The overall results suggest that the humus form can be used as indicator of organic matter decomposition processes in the investigated high mountain area.