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Climate controls the broad-scale distribution of vegetation and change in climate will alter the vegetation distribution, biome boundaries, biodiversity, phenology and supply of ecosystem services. A better understanding of the consequences of climate change is required, particularly in under-investigated regions such as tropical Asia, i.e., South and South-east Asia, which is a host to 7 of the 36 global biodiversity hotspots. Conservation strategies would also require an in-depth understanding of the response of vegetation to climate change. Therefore, the main objective of this thesis was to investigate the impact of climate change and rising CO2 vegetation in tropical Asia. Dynamic global vegetation model (DGVMs) are the well-known tools to investigate vegetation-climate interactions and climate change impacts on ecosystems. In this thesis, I used a complex trait-based DGVM called adaptive dynamic vegetation model version 2 (aDGVM2).
In Chapter 1, I presented a brief background of the phytogeography and discussed the exiting knowledge gap on vegetation-climate interactions in the region. One major disadvantage for available DGVMs studies for the tropical Asia is that most of them have used fixed plant functional types (PFTs) and do not explicitly represent the distinct varieties of vegetation type of the region such as Asian savannas. In Chapter 2, I discussed at great length to improve DGVMs for South Asia and discussed ways to include them in the model for better representation of region vegetation-climate interaction.
I upgraded the current version of aDGVM2 and added a new vegetation type i.e., C3 grasses, and modified the sub-module to simulate photosynthesis for each individual plants to aDGVM2. In chapter 3, I used this updated version of aDGVM2 to simulate the current and future vegetation distribution in South Asia under RCP4.5 and RCP8.5 (RCP: representative concentration pathway). The model predicted an increase in biomass, canopy cover, and tree height under the presence of CO2 fertilization, which triggered transitions towards tree-dominated biomes by the end of the 21st century under both RCPs. I found that vegetation along the Western Ghats and the Himalayas are more susceptible to change due to climate change and open biomes such as grassland and savanna are prone to woody encroachment.
In Chapter 4, the study domain was extended to include South-east Asia to verify if the model configuration used in Chapter 3 can also simulate vegetation patterns in tropical Asia. The aDGVM2 simulations showed a robust trend of increasing vegetation biomass and transitions from small deciduous vegetation to taller evergreen vegetation across most of tropical Asia. Shifts in plant phenology also affect ecosystem carbon cycles and ecosystem feedback to climate, yet the quantification of such impacts remains challenging. The study showed increased biomass due to CO2 fertilization, indicates that the region can remain a carbon sink given there is no other resource limitation. However, nutrient limitations on CO2 fertilization effects were not included in the study, and carbon sink potential has to be seen with caution.
In Chapter 5, I focused on Asian savannas, which have been mismanaged since the colonial era due to misinterpretation as a degraded forest. I proposed a biome classification scheme to distinguish between degraded forest or woodland and savanna based on the abundance of grass biomass and canopy cover. I found that considering vegetation systems as woodland or degraded forest could easily be mistaken as a potential for forest restoration within a tree-centric perspective. This would put approximately 35% to 40% of a unique savanna biome at risk. Although projected woody encroachments may imply a transition toward the forest that benefits climate mitigation. This raises potential conflicts of interest between biodiversity conservation in open ecosystems, i.e., savanna and active afforestation, to enhance carbon sequestration. Proper management strategies should be taken into account to maintain a balance for both objective
In conclusion, the model predicted that vegetation in South and South-East Asia would significantly shift towards tree-dominated biomes due to CO2-induced fertilization of C3-photosynthesis. The simulation under fixed CO2 and rising CO2 scenarios clearly showed that rising level of atmospheric CO2 is responsible for most of the predicted change in biome properties. This study is an important step towards understanding ecosystems of South and Southeast Asia, specifically savannas. The aDGVM2 can serve as tools to inform decision making for climate adaptation and mitigation for savanna. The thesis, thus contributes to our ability to improve conservation strategies to mitigate the consequences of climate change.
The weather of the atmospheric boundary layer significantly affects our life on Earth. Thus, a realistic modelling of the atmospheric boundary layer is crucial. Hereby, the processes of the atmospheric boundary layer depend on an accurate representation of the land-atmosphere coupling in the model. In this context the land surface temperature (LST) plays an important role. In this thesis, it is examined if the assimilation of LST can lead to improved estimates of the boundary layer and its processes.
To properly assimilate the LST retrievals, a suitable model equivalent in the weather prediction model is necessary. In the weather forecast model of the German Weather Service used here, the LST is modelled without a vegetation temperature. To compensate for this deficit, two different vegetation parameterizations were investigated and the better one, a conductivity scheme, was implemented. In order to make optimal use of the influence of the assimilation of the LST observation on the model system, it is useful to pass on the information of the observation to land and atmosphere already in the assimilation step. For that reason, a fully coupled land-atmosphere prediction model was used. Therefore, the existing control vector of the assimilation system, a local ensemble transform Kalman filter, was extended by the soil temperature and moisture. In two-day case studies in March and August 2017, different configurations of the augmented assimilation system were evaluated based on observing system simulation experiments (OSSE).
LST was assimilated hourly over two days in the weakly and strongly coupled assimilation system. In addition, every six hours a free 24-hour forecast was simulated. The experiments were validated with the simulated truth (a high-resolution model run) and compared against an experiment without assimilation. It was shown that the prediction of the boundary layer temperature, especially during the day, and the prediction of the soil temperature, during the whole day and night, could be improved.
The best impact of LST assimilation was achieved with the fully coupled system. The humidity variables of the model benefited only partially from the LST assimilation. For this reason, covariances in the model ensemble were investigated in more detail. To check their compatibility with the high-resolution model run the ensemble consistency score was introduced. It was found that the covariances between the LST and the temperatures of the high-resolution model run were better represented in the ensemble than those between the LST and the humidity variables.
Shrubs are a characteristic component of savannas, where they coexist with trees and grasses. They are often part of woody encroachment phenomena, which have been observed globally, and the determinant of shrub encroachment cases, which are particularly of concern in African savannas. In response to climate change and land use change, African savannas are vulnerable to biome shifts and shrub encroachment is a process driving and explaining this risk.
We contribute to furthering the understanding of shrubs biogeography and ecology by considering the number of stems of woody plants to characterise shrubs phenotype and strategy. We postulate that shrubs are multi-stemmed, compared to single-stemmed trees and integrate this assumption in aDGVM2 (adaptive Dynamic Global Vegetation Model 2). Modelling a trait representing the number of stems of a woody plant implies a trade-off between single-stemmed plants having higher height growth potential and multi-stemmed plants having higher hydraulic capacity but limited height growth. Multi-stemmed individuals, being shorter, are more likely to suffer severe damage from fires than tall single-stemmed trees managing to grow their crown out of the flame zone.
We simulate potential vegetation over sub-Saharan Africa at 1° spatial resolution, with aDGVM2 and compare it to simulations without our shrub model turned on. We also test the impact of fire by including or excluding it from our simulations. To assess the accuracy and relevance of our approach, we benchmark our overall model’s performance against multiple satellite derived products of above ground biomass (AGBM), and against specific field measurements of AGBM. We further benchmark our results against vegetation cover type derived from satellite data.
We demonstrate that shrubs can be modelled as multi-stemmed woody plants in African savannas based on whole-plant trait trade-off without being predefined as static functional types. Indeed, the addition of our shrub model to aDGVM2 allows for shrubs to emerge dynamically through community assembly processes without a priori categorisation. Our shrub model also improves the simulated vegetation patterns simulated by aDGVM2 in sub-Saharan Africa, particularly in savannas. The simulated pattern of stem number per woody individual broadly follows our assumptions about biogeographic patterns as it is lowest in equatorial African forests and increases in savannas and grasslands as precipitation decreases. Shrubs are more abundant in more water-stressed regions where they have a competitive advantage over trees due to their increased relative water transport potential. However, in arid and hyper-arid regions, further investigations are required. Simulated shrub prevalence is higher in more open and fire prone landscapes, where woody cover and biomass are reduced.
Adding shrubs to aDGVM2, while increasing complexity allows for greater simulated diversity. As resilience and resistance of ecosystems have been shown to be influenced by diversity, such model development is necessary to improve our ability to forecast ecosystems responses to changes. However, there are challenges to fully tap this benefit. Assessing the accuracy and relevance of our approach is challenging. Data and simulations are conceptually different which limit the possibility to conclude based on comparison. Benchmarking challenge is exacerbated by the variability existing among satellite derived products and site studies observations. In areas of extremely low biomass and vegetation cover, such as deserts and semi-deserts, the accuracy of our model is more concerning as small differences in absolute values are relatively more important.
Categorisation of life-forms shapes our understanding of their ecology and biogeography, thus, consensus about their definition is direly needed. To contribute to this debate, we investigate how vegetation distribution patterns arising from our shrub model inform our understanding of shrub biogeography. First, shrub distribution in trait space (considering stem number), relatively to environmental drivers, concurs with our assumptions. Second, shrub spatial distribution is consistent with our characterisation assumptions. Third, the role of simulated shrubs in an ecosystem supports realistic ecological dynamics. Our model allows for, shrubs to exhibit a specific phenotype, but also a specific life-strategy, which we characterise in terms of persistence strategy (shrubs are mainly resprouters, in contrast to trees, which can be either resprouters or reseeders) and in terms of resource acquisition (rooting strategy) and allocation (carbon investment). Adding stem count as a trait to aDGVM2 increase the range of simulated functional diversity.
Our shrub model allows for aDGVM2 to simulate realistic ratio of grass to woody vegetation across sub-saharan Africa. Similarly, it simulates ratio of shrubs to trees consistent with our hypotheses.
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This Ph.D. thesis demonstrates i) the highly precise performance of refined and new analytical setups for clumped isotope analysis (Δ47 and Δ48) and ii) the applicability of clumped isotope analyses to biogenic and abiogenic carbonated apatite (Δ47) and abiogenic carbonates (Δ47 and Δ48) for research related to paleothermophysiology and paleoclimatology, whereas the overall analytical precision has been increased.
A comprehensive Δ47 dataset with 122 replicate analyses is provided from which the temperature dependence of Δ47 for (bio)apatite (Δ47-1/T2) is calculated between 1 °C and 80 °C. The temperature dependence of oxygen isotope equilibrium fractionation between carbonated synthetic apatite and water (1,000ln(αCHAP-H2O)) is experimentally determined. When applied to tooth enameloid from a modern Greenland shark (Somniosus microcephalus), a Late Miocene megatooth shark (Carcharodon megalodon), and an Upper Cretaceous Tyrannosaurus rex, reconstructed Δ47-based temperatures and δ18OH2O are in line with previously published data.
An analytical setup for highly precise clumped isotope analysis is described that allows for the simultaneous measurement of ∆47 and ∆48 in CO2 with external reproducibilities close to the respective shot-noise limits. The analyte gases originate from pure carbonates that were digested in hypersaturated orthophosphoric acid and purified using a fully automated device. Δ47 data sets with 117 replicate analyses in total on 22 pedogenic carbonate nodules from two Spanish Middle Miocene sections reveal the continental Southern European thermal structure during the end of the Middle Miocene Climatic Optimum (MCO) and the complete Middle Miocene Climatic Transition (MMCT; from 15.33 to 12.98 Ma).
The analysis of the global stratospheric meridional circulation, known as the Brewer-Dobson circulation, is an essential part of both experimental and theoretical atmospheric sciences. This large-scale circulation has a crucial influence on the global burden of greenhouse gases and ozone depleting substances throughout the complete atmosphere. This makes it an important factor for the Earth’s radiative budget, which is perceptible at the Earth’s surface despite the remote location of the stratosphere. In the course of climate change it is generally expected that also the Brewer-Dobson circulation undergoes significant changes in structure and strength, although the exact repercussions are still uncertain and thus remain an open scientific question. A general problem for the observational investigation of the dynamical processes in the stratosphere is that residual mean transport cannot be measured directly and hence requires the use of sophisticated proxies. Many studies in the past consider the so-called mean age of air, which is a measure of the average time an air parcel has spent in the stratosphere since passing a certain reference point. While changes in the strength and structure can be detected and visualized using mean age of air, a more thorough distinction between the different involved transport mechanisms of the circulation (residual circulation, mixing) cannot be made. For that, consideration of a full distribution of all relevant transit times through the stratosphere, an age spectrum, is favorable and a powerful tool to analyze the spatial structure as well as possible future changes in detail. Mean age of air and age spectra can be readily derived in atmospheric modeling studies, but an observationally based retrieval is challenging. Mean age of air is usually approximated from measurements of very long-lived trace gas species that act as a dynamical tracer for the stratosphere. The retrieval of age spectra from observations, however, remains an open task for which different methods have been proposed in the past, that often require a combination of strong assumptions and model data explicitly. This is a major issue for a precise and independent investigation of stratospheric dynamics based on measurements. The focus of this cumulative dissertation is on the development process and application of an inversion method to derive stratospheric age spectra from mixing ratios of chemically active substances that combines an applicable and precise ansatz with a minimized amount of necessary model data. Chemically active species have the important benefit that chemistry and transport in the stratosphere are strongly correlated so that the state of depletion of a trace gas can give some information on certain parts of the age spectrum. Considering a sufficient number of distinct trace gases simultaneously, a full approximation of the age spectrum should be possible. The main section of this thesis is split into three parts, which follow the main aspects and key results of the three publications involved (Hauck et al., 2019, 2020; Keber et al., 2020). The newly developed inverse method is based upon the previously established ansatz by Schoeberl et al. (2005), but constrains the shape of the age spectrum by a single parameter inverse Gaussian function. This keeps the balance between applicability and accuracy with a limited amount of measurement data. Additionally, the method introduces a seasonal scaling factor that imposes higher order maxima and minima onto the intrinsically monomodal spectrum based on the seasonal cycle of the tropical upward mass flux to incorporate phases of weaker and stronger transport. A proof of concept of the inverse method is provided using an idealized simulation of the ECHAM/MESSy Atmospheric Chemistry (EMAC) model, where the method is applied to a set of artificial radioactive trace gases with known chemical lifetime. The results imply that the method works properly and retrieves age spectra that match the EMAC reference spectra significantly well on the global and seasonal scale. Only in the lower stratosphere, the performance of the inverse method on the seasonal scale decreases as entrainment into the stratosphere is considered only across the tropical tropopause. Transport across the local extratropical tropopause, however, is a key feature for trace gases in the extratropical lowermost stratosphere so that this entrainment must be included explicitly.
In the second part, the discovered problems are approached to make the inverse method applicable to observations. The formulation of the method is extended to incorporate transport explicitly across the tropical (30° S – 30° N), northern extratropical (30° N – 90° N), and southern extratropical tropopause (30° S – 90° S) each with a single age spectrum that can be inverted independently.
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Historic amphibian settlements in the northwestern Nile delta - a geoarchaeological perspective
(2020)
No concise picture of the archaeological and palaeoecological evolution can be drawn for the northwestern Nile delta, and archaeological records show significant population dynamics that still need explanation and spur the need for further palaeoenvironmental research. This study delivers a set of new methods especially in the fields of remote sensing and data analytics that can be regarded as important milestones and foundations for further palaeoenvironmental research in the area. Additionally, it shows new insights for individual time slices.
This geoarchaeological project is a cooperation with the archaeological excavations of the German Archaeological Institute (DAI) in Buto and Kom el’Gir. It expands the work of Wunderlich (1989) which laid important foundations in understanding the origin of the initial landscape that was later colonized in different cultural stages showing different dynamics, settlement intensities and even long phases of abandonment or breaks in between. This forms the starting point for relating the population dynamics of the different cultural phases reaching from Predynastic (prior to 3150 before Christ) up to the Greco-Roman era (~anno Domini 650) to the environmental history and events that occurred in the area. It is very likely that environmental changes such as the shifting of major water routes, inundation or paludification of larger areas or other environmental events affected settlements and human life in the area.
In the fields of remote sensing new methods are presented to complete information on the location of ancient settlements, and complex workflows are developed that allow the tracing of subsurface structures via indirect analysis of vegetation growth in larger time series data. It was verified that a relationship exists between vegetation performance, the appearance of archaeologic material in the topsoil, and the location of former Nile river branches.
Together with a new high resolution digital elevation model (DEM) based on TanDEM-X data, new interpretations with a high spatial significance are possible. For individual time slices, namely the Late Dynastic and Greco-Roman era, this work delivers a detailed landscape description suggesting a finely ramified subdelta, with all settlements placed on alluvial levees. This explains the massive increase in settlements in the Ptolemaic, Roman and in particular late Roman periods (4th century before Christ – anno Domini 7th century).
We sampled the Nile delta clays together with the channels and the material of the archaeologic excavations in vibracores and profile walls. This geologic inspection of the subsurface together with geochemical results from a handheld portable X-ray fluorescence device (pXRF) allowed new interpretations of the landscape and environmental history. For example, we used geochemical data to distinguish between artificial and natural channels as a measure for the anthropogenic influence, a proxy for past environmental characteristics and lastly as a basis for a new dating method. Many of the channels, for instance, were dated by our own 14C datings, comparisons with the previous work ofWunderlich (1989) and application of new dating approach based on machine learning with artificial neural networks. Additionally, we run a full methodological approach, and examine the applicability of pXRF methods in general, and test the quality of the data to detect distinct geochemical differences between the main settlement phases with advanced methods in data analytics. The dating is based, for example, on the training of artificial neural networks with pXRF data from archaeological material of well-dated context to date test data of cultural layers within the vibracores. With this method the homogeneous Nile alluvium, cultural layers and channels can be dated roughly and, as a result, fundamental changes in the landscape can be linked with the settlement history of Buto and neighboring tells.