TY - JOUR A1 - Fer, Istem A1 - Tietjen, Britta A1 - Jeltsch, Florian T1 - High-resolution modelling closes the gap between data and model simulations for Mid-Holocene and present-day biomes of East Africa JF - Palaeogeography, palaeoclimatology, palaeoecology : an international journal for the geo-sciences N2 - East Africa hosts a striking diversity of terrestrial ecosystems, which vary both in space and time due to complex regional topography and a dynamic climate. The structure and functioning of these ecosystems under this environmental setting can be studied with dynamic vegetation models (DVMs) in a spatially explicit way. Yet, regional applications of DVMs to East Africa are rare and a comprehensive validation of such applications is missing. Here, we simulated the present-day and mid-Holocene vegetation of East Africa with the DVM, LPJ-GUESS and we conducted an exhaustive comparison of model outputs with maps of potential modern vegetation distribution, and with pollen records of local change through time. Overall, the model was able to reproduce the observed spatial patterns of East African vegetation. To see whether running the model at higher spatial resolutions (10′ × 10′) contribute to resolve the vegetation distribution better and have a better comparison scale with the observational data (i.e. pollen data), we run the model with coarser spatial resolution (0.5° × 0.5°) for the present-day as well. Both the area- and point-wise comparison showed that a higher spatial resolution allows to better describe spatial vegetation changes induced by the complex topography of East Africa. Our analysis of the difference between modelled mid-Holocene and modern-day vegetation showed that whether a biome shifts to another is best explained by both the amount of change in precipitation it experiences and the amount of precipitation it received originally. We also confirmed that tropical forest biomes were more sensitive to a decrease in precipitation compared to woodland and savanna biomes and that Holocene vegetation changes in East Africa were driven not only by changes in annual precipitation but also by changes in its seasonality. KW - Dynamic vegetation models KW - Biome KW - Mid-Holocene KW - Leaf area index KW - Climate change KW - East Africa Y1 - 2016 U6 - https://doi.org/10.1016/j.palaeo.2015.12.001 SN - 0031-0182 SN - 1872-616X VL - 444 SP - 144 EP - 151 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Fer, Istem A1 - Tietjen, Britta A1 - Jeltsch, Florian A1 - Wolff, Christian Michael T1 - The influence of El Nino-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario JF - Biogeosciences N2 - The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security. Y1 - 2017 U6 - https://doi.org/10.5194/bg-14-4355-2017 SN - 1726-4170 SN - 1726-4189 VL - 14 SP - 4355 EP - 4374 PB - Copernicus CY - Göttingen ER - TY - JOUR A1 - Fer, Istem A1 - Tietjen, Britta A1 - Jeltsch, Florian A1 - Wolff, Christian Michael T1 - The influence of El Nino-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario JF - Biogeosciences N2 - The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security. Y1 - 2017 U6 - https://doi.org/10.5194/bg-14-4355-2017 SN - 1726-4170 SN - 1726-4189 VL - 14 IS - 18 SP - 4355 EP - 4374 PB - Copernicus CY - Katlenburg-Lindau ER - TY - GEN A1 - Fer, Istem A1 - Tietjen, Britta A1 - Jeltsch, Florian A1 - Wolff, Christian Michael T1 - The influence of El Nino-Southern Oscillation regimes on eastern African vegetation and its future implications under the RCP8.5 warming scenario N2 - The El Nino-Southern Oscillation (ENSO) is the main driver of the interannual variability in eastern African rainfall, with a significant impact on vegetation and agriculture and dire consequences for food and social security. In this study, we identify and quantify the ENSO contribution to the eastern African rainfall variability to forecast future eastern African vegetation response to rainfall variability related to a predicted intensified ENSO. To differentiate the vegetation variability due to ENSO, we removed the ENSO signal from the climate data using empirical orthogonal teleconnection (EOT) analysis. Then, we simulated the ecosystem carbon and water fluxes under the historical climate without components related to ENSO teleconnections. We found ENSO-driven patterns in vegetation response and confirmed that EOT analysis can successfully produce coupled tropical Pacific sea surface temperature-eastern African rainfall teleconnection from observed datasets. We further simulated eastern African vegetation response under future climate change as it is projected by climate models and under future climate change combined with a predicted increased ENSO intensity. Our EOT analysis highlights that climate simulations are still not good at capturing rainfall variability due to ENSO, and as we show here the future vegetation would be different from what is simulated under these climate model outputs lacking accurate ENSO contribution. We simulated considerable differences in eastern African vegetation growth under the influence of an intensified ENSO regime which will bring further environmental stress to a region with a reduced capacity to adapt effects of global climate change and food security. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 394 Y1 - 2017 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-403853 ER - TY - THES A1 - Fer, Istem T1 - Modeling past, present and future climate induced vegetation changes in East Africa T1 - Modellierung vergangener, gegenwärtiger und zukünftiger klimainduzierter Vegetationsveränderungen in Ostafrika N2 - Ostafrika ist ein natürliches Labor: Durch ein Studium seiner einzigartigen geologischen und biologischen Geschichte lassen sich unsere Theorien und Modelle überprüfen und verbessern. Ein Studium seiner Gegenwart und seiner Zukunft wiederum hilft uns dabei, die global bedeutende Artenvielfalt und die ökosystemaren Dienstleistungen Ostafrikas zu schützen. Eine zentrale Rolle spielt dabei spielt die ostafrikanische Vegetation, deren Dynamiken in dieser Dissertation durch Computersimulationen quantifiziert werden sollen. Über Computersimulationen lassen sich frühere Rahmenbedingungen reproduzieren, Voraussagen treffen oder Simulationsexperimente durchführen, die durch Feldforschung nicht möglich wären. Zuallererst muss jedoch ihre Leistungsfähigkeit überprüft werden. Die von dem Modell anhand der heutigen Inputs gelieferten Ergebnisse stimmten weitgehend mit heutigen Beobachtungen ostafrikanischer Vegetation überein. Als nächstes wurde die frühere Vegetation simuliert, für die fossile Pollen-Daten zum Abgleich vorliegen. Über Computermodelle lassen sich Wissenslücken zwischen Standorten überbrücken, bei denen wir über fossile Pollen-Daten verfügen, sodass ein vollständigeres Bild der Vergangenheit entsteht. Zusätzlich validiert wurde die Leistungsfähigkeit des Modells durch die hohe Übereinstimmung zwischen Modell und Pollen-Daten, wo sie im Raum überlappen. Nachdem das Modell getestet und für die Region validiert war, konnte eine der seit langem offenen Fragen über die ostafrikanische Vegetation angegangen werden, nämlich wie Ostafrika seines Tropenwaldes verlustig gehen konnte. In den Tropen wird die heutige Vegetation weltweit hauptsächlich von Wäldern dominiert, mit Ausnahme der Tropengebiete Ostafrikas, wo Wälder nur noch stellenweise an der Küste und im Hochland vorkommen. Durch eine Reihe von Simulationsexperimenten konnte aufgezeigt werden, unter welchen Bedingungen jene Waldgebiete früher zusammenhingen und schließlich fragmentiert wurden. Die Studie hat erwiesen, wie empfindlich die ostafrikanische Vegetation für die Klimaschwankungen ist, die durch den künftigen Klimawandel zu erwarten sind. Weitere Auswirkungen auf das ostafrikanische Klima ergeben sich aus dem El Niño/Southern Oscillation-Phänomen (ENSO), das aus Temperaturfluktuationen zwischen dem Ozean und der Atmosphäre herrührt und künftig an Intensität zunehmen dürfte. Die derzeitigen Klimamodelle sind allerdings noch nicht gut genug beim Erfassen solcher Ereignismuster. In einer Studie wurde der Einfluss des ENSO-Phänomens auf die ostafrikanische Vegetation quantifiziert und dabei aufgezeigt, wie sehr sich die künftige Vegetation von den heute simulierten Ergebnissen unterscheiden könnte, bei denen der genaue ENSO-Beitrag nicht berücksichtigt werden kann. Bei der Berechnung der künftigen weltweiten CO2-Bilanz und den zu treffenden Entscheidungen stellt dies einen zusätzlichen Unsicherheitsfaktor dar. N2 - 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. KW - East Africa KW - vegetation modeling KW - paleovegetation KW - El Nino Southern Oscillation KW - Ostafrika KW - Vegetationsmodellierung KW - Paläovegetation KW - El Niño/Southern Oscillation-Phänomen Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-427777 ER -