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The Relative Pollen Productivities (RPPs) of common steppe species are estimated using Extended R-value (ERV) model based on pollen analysis and vegetation survey of 30 surface soil samples from typical steppe area of northern China. Artemisia, Chenopodiaceae, Poaceae, Cyperaceae, and Asteraceae are the dominant pollen types in pollen assemblages, reflecting the typical steppe communities well. The five dominant pollen types and six common types (Thalictrum, Iridaceae, Potentilla, Ephedra, Brassicaceae, and Ulmus) have strong wind transport abilities; the estimated Relevant Source Area of Pollen (RSAP) is ca. 1000 m when the sediment basin radius is set at 0.5 m. Ulmus, Artemisia, Brassicaceae, Chenopodiaceae, and Thalictrum have relative high RPPs; Poaceae, Cyperaceae, Potentilla, and Ephedra pollen have moderate RPPs; Asteraceae and Iridaceae have low RPPs. The reliability test of RPPs revealed that most of the RPPs are reliable in past vegetation reconstruction. However, the RPPs of Asteraceae and Iridaceae are obviously underestimated, and those of Poaceae, Chenopodiaceae, and Ephedra are either slightly underestimated or slightly overestimated, suggesting that those RPPs should be considered with caution. These RPPs were applied to estimating plant abundances for two fossil pollen spectra (from the Lake Bayanchagan and Lake Haoluku) covering the Holocene in typical steppe area, using the "Regional Estimates of Vegetation Abundance from Large Sites" (REVEALS) model. The RPPs-based vegetation reconstruction revealed that meadow-steppe dominated by Poaceae, Cyperaceae, and Artemisia plants flourished in this area before 6500-5600 cal yr BP, and then was replaced by present typical steppe.
The Himalaya has a major influence on global and regional climate, in particular on the Asian monsoon system. The foreland basin of the Himalaya contains a record of tectonics and paleoclimate since the Miocene. Previous work on the evolution of vegetation and climate has focused on the central and western Himalaya, where a shift from C3 to C4 vegetation has been observed at similar to 7 Ma and linked to increased seasonality, but the climatic evolution of the eastern part of the orogen is less well understood. In order to track vegetation as a marker of monsoon intensity and seasonality, we analyzed delta C-13 and 8180 values of soil carbonate and associated delta C-13 values of bulk organic carbon from previously dated sedimentary sections exposing the syn-orogenic detrital Dharamsala and Siwalik Groups in the west, and, for the first time, the Siwalik Group in the east of the Himalayan foreland basin. Sedimentary records span from 20 to 1 Myr in the west (Joginder Nagar, Jawalamukhi, and Haripur Kolar sections) and from 13 to 1 Myr in the east (Kameng section), respectively. The presence of soil carbonate in the west and its absence in the east is a first indication of long-term lateral climatic variation, as soil carbonate requires seasonally arid conditions to develop. delta C-13 values in soil carbonate show a shift from around -10 parts per thousand to -2 parts per thousand at similar to 7 Ma in the west, which is confirmed by delta C-13 analyses on bulk organic carbon that show a shift from around -23 parts per thousand to -19 parts per thousand at the same time. Such a shift in isotopic values is likely to be associated with a change from C3 to C4 vegetation. In contrast, delta C-13 values of bulk organic carbon remain at 23 parts per thousand o in the east. Thus, our data show that the current east -west variation in climate was established at similar to 7 Ma. We propose that the regional change towards a more seasonal climate in the west is linked to a decrease of the influence of the Westerlies, delivering less winter precipitation to the western Himalaya, while the east remained annually humid due to its proximity to the monsoonal moisture source. (C) 2017 Elsevier B.V. All rights reserved.
East Africa is a natural laboratory: Studying its unique geological and biological history can help us better inform our theories and models. Studying its present and future can help us protect its globally important biodiversity and ecosystem services. East African vegetation plays a central role in all these aspects, and this dissertation aims to quantify its dynamics through computer simulations.
Computer models help us recreate past settings, forecast into the future or conduct simulation experiments that we cannot otherwise perform in the field. But before all that, one needs to test their performance. The outputs that the model produced using the present day-inputs, agreed well with present-day observations of East African vegetation. Next, I simulated past vegetation for which we have fossil pollen data to compare. With computer models, we can fill the gaps of knowledge between sites where we have fossil pollen data from, and create a more complete picture of the past. Good level of agreement between model and pollen data where they overlapped in space further validated our model performance.
Once the model was tested and validated for the region, it became possible to probe one of the long standing questions regarding East African vegetation: How did East Africa lose its tropical forests? The present-day vegetation in the tropics is mainly characterized by continuous forests worldwide except in tropical East Africa, where forests only occur as patches. In a series of simulation experiments, I was able to show under which conditions these forest patches could have been connected and fragmented in the past. This study showed the sensitivity of East African vegetation to climate change and variability such as those expected under future climate change.
El Niño Southern Oscillation (ENSO) events that result from the fluctuations in temperature between the ocean and atmosphere, bring further variability to East African climate and are predicted to increase in intensity in the future. But climate models are still not good at capturing the pattens of these events. In a study where I quantified the influence of ENSO events on East African vegetation, I showed how different the future vegetation could be from what we currently predict with these climate models that lack accurate ENSO contribution. Consideration of these discrepancies is important for our future global carbon budget calculations and management decisions.