TY - GEN A1 - Epp, Laura Saskia A1 - Kruse, Stefan A1 - Kath, Nadja J. A1 - Stoof-Leichsenring, Kathleen Rosemarie A1 - Tiedemann, Ralph A1 - Pestryakova, Luidmila Agafyevna A1 - Herzschuh, Ulrike T1 - Temporal and spatial patterns of mitochondrial haplotype and species distributions in Siberian larches inferred from ancient environmental DNA and modeling T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Changes in species' distributions are classically projected based on their climate envelopes. For Siberian forests, which have a tremendous significance for vegetation-climate feedbacks, this implies future shifts of each of the forest-forming larch (Larix) species to the north-east. However, in addition to abiotic factors, reliable projections must assess the role of historical biogeography and biotic interactions. Here, we use sedimentary ancient DNA and individual-based modelling to investigate the distribution of larch species and mitochondrial haplotypes through space and time across the treeline ecotone on the southern Taymyr peninsula, which at the same time presents a boundary area of two larch species. We find spatial and temporal patterns, which suggest that forest density is the most influential driver determining the precise distribution of species and mitochondrial haplotypes. This suggests a strong influence of competition on the species' range shifts. These findings imply possible climate change outcomes that are directly opposed to projections based purely on climate envelopes. Investigations of such fine-scale processes of biodiversity change through time are possible using paleoenvironmental DNA, which is available much more readily than visible fossils and can provide information at a level of resolution that is not reached in classical palaeoecology. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 1052 KW - ecological genetics KW - ecological modelling KW - palaeoecology KW - plant ecology KW - climate change KW - introgression KW - temperature KW - treeline KW - vegetation KW - mitochondrial haplotypes KW - Siberian larch KW - larch species KW - range shifts KW - vegetation-climate feedbacks KW - ecosystems KW - impacts KW - dynamics Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-468352 SN - 1866-8372 IS - 1052 ER - TY - GEN A1 - Goodwin, Guillaume C. H. A1 - Mudd, Simon M. A1 - Clubb, Fiona J. T1 - Unsupervised detection of salt marsh platforms BT - a topographic method T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - Salt marshes filter pollutants, protect coastlines against storm surges, and sequester carbon, yet are under threat from sea level rise and anthropogenic modification. The sustained existence of the salt marsh ecosystem depends on the topographic evolution of marsh platforms. Quantifying marsh platform topography is vital for improving the management of these valuable landscapes. The determination of platform boundaries currently relies on supervised classification methods requiring near-infrared data to detect vegetation, or demands labour-intensive field surveys and digitisation. We propose a novel, unsupervised method to reproducibly isolate salt marsh scarps and platforms from a digital elevation model (DEM), referred to as Topographic Identification of Platforms (TIP). Field observations and numerical models show that salt marshes mature into subhorizontal platforms delineated by subvertical scarps. Based on this premise, we identify scarps as lines of local maxima on a slope raster, then fill landmasses from the scarps upward, thus isolating mature marsh platforms. We test the TIP method using lidar-derived DEMs from six salt marshes in England with varying tidal ranges and geometries, for which topographic platforms were manually isolated from tidal flats. Agreement between manual and unsupervised classification exceeds 94% for DEM resolutions of 1 m, with all but one site maintaining an accuracy superior to 90% for resolutions up to 3 m. For resolutions of 1 m, platforms detected with the TIP method are comparable in surface area to digitised platforms and have similar elevation distributions. We also find that our method allows for the accurate detection of local block failures as small as 3 times the DEM resolution. Detailed inspection reveals that although tidal creeks were digitised as part of the marsh platform, unsupervised classification categorises them as part of the tidal flat, causing an increase in false negatives and overall platform perimeter. This suggests our method may benefit from combination with existing creek detection algorithms. Fallen blocks and high tidal flat portions, associated with potential pioneer zones, can also lead to differences between our method and supervised mapping. Although pioneer zones prove difficult to classify using a topographic method, we suggest that these transition areas should be considered when analysing erosion and accretion processes, particularly in the case of incipient marsh platforms. Ultimately, we have shown that unsupervised classification of marsh platforms from high-resolution topography is possible and sufficient to monitor and analyse topographic evolution. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 936 KW - accuracy assessment KW - tidal flats KW - vegetation KW - extraction KW - elevation KW - sedimentation KW - opportunity KW - ecosystems KW - morphology KW - salinity Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-459329 SN - 1866-8372 IS - 936 SP - 239 EP - 255 ER - TY - GEN A1 - Kruse, Stefan A1 - Gerdes, Alexander A1 - Kath, Nadja J. A1 - Herzschuh, Ulrike T1 - Implementing spatially explicit wind-driven seed and pollen dispersal in the individual-based larch simulation model BT - LAVESI-WIND 1.0 T2 - Postprints der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe N2 - It is of major interest to estimate the feedback of arctic ecosystems to the global warming we expect in upcoming decades. The speed of this response is driven by the potential of species to migrate, tracking their climate optimum. For this, sessile plants have to produce and disperse seeds to newly available habitats, and pollination of ovules is needed for the seeds to be viable. These two processes are also the vectors that pass genetic information through a population. A restricted exchange among subpopulations might lead to a maladapted population due to diversity losses. Hence, a realistic implementation of these dispersal processes into a simulation model would allow an assessment of the importance of diversity for the migration of plant species in various environments worldwide. To date, dynamic global vegetation models have been optimized for a global application and overestimate the migration of biome shifts in currently warming temperatures. We hypothesize that this is caused by neglecting important fine-scale processes, which are necessary to estimate realistic vegetation trajectories. Recently, we built and parameterized a simulation model LAVESI for larches that dominate the latitudinal treelines in the northernmost areas of Siberia. In this study, we updated the vegetation model by including seed and pollen dispersal driven by wind speed and direction. The seed dispersal is modelled as a ballistic flight, and for the pollination of ovules of seeds produced, we implemented a wind-determined and distance-dependent probability distribution function using a von Mises distribution to select the pollen donor. A local sensitivity analysis of both processes supported the robustness of the model's results to the parameterization, although it highlighted the importance of recruitment and seed dispersal traits for migration rates. This individual-based and spatially explicit implementation of both dispersal processes makes it easily feasible to inherit plant traits and genetic information to assess the impact of migration processes on the genetics. Finally, we suggest how the final model can be applied to substantially help in unveiling the important drivers of migration dynamics and, with this, guide the improvement of recent global vegetation models. T3 - Zweitveröffentlichungen der Universität Potsdam : Mathematisch-Naturwissenschaftliche Reihe - 929 KW - long-distance dispersal KW - climate-change KW - genetic-structure KW - plant migration KW - larix-sibirica KW - DNA variation KW - large-scale KW - vegetation KW - landscape KW - future Y1 - 2020 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-445978 SN - 1866-8372 IS - 929 SP - 4451 EP - 4467 ER - TY - THES A1 - Siegmund, Jonatan Frederik T1 - Quantifying impacts of climate extreme events on vegetation T1 - Über die Quantifizierung des Einflusses extremer Klimaereignisse auf Vegetation BT - event coincidence analysis and its applications across scales BT - die Event Koinzidenz Analyse und deren Anwendung auf verschiedenen Skalen N2 - Together with the gradual change of mean values, ongoing climate change is projected to increase frequency and amplitude of temperature and precipitation extremes in many regions of Europe. The impacts of such in most cases short term extraordinary climate situations on terrestrial ecosystems are a matter of central interest of recent climate change research, because it can not per se be assumed that known dependencies between climate variables and ecosystems are linearly scalable. So far, yet, there is a high demand for a method to quantify such impacts in terms of simultaneities of event time series. In the course of this manuscript the new statistical approach of Event Coincidence Analysis (ECA) as well as it's R implementation is introduced, a methodology that allows assessing whether or not two types of event time series exhibit similar sequences of occurrences. Applications of the method are presented, analyzing climate impacts on different temporal and spacial scales: the impact of extraordinary expressions of various climatic variables on tree stem variations (subdaily and local scale), the impact of extreme temperature and precipitation events on the owering time of European shrub species (weekly and country scale), the impact of extreme temperature events on ecosystem health in terms of NDVI (weekly and continental scale) and the impact of El Niño and La Niña events on precipitation anomalies (seasonal and global scale). The applications presented in this thesis refine already known relationships based on classical methods and also deliver substantial new findings to the scientific community: the widely known positive correlation between flowering time and temperature for example is confirmed to be valid for the tails of the distributions while the widely assumed positive dependency between stem diameter variation and temperature is shown to be not valid for very warm and very cold days. The larger scale investigations underline the sensitivity of anthrogenically shaped landscapes towards temperature extremes in Europe and provide a comprehensive global ENSO impact map for strong precipitation events. Finally, by publishing the R implementation of the method, this thesis shall enable other researcher to further investigate on similar research questions by using Event Coincidence Analysis. N2 - Neben der graduellen Änderung der mittleren klimatischen Bedingungen wird für viele Regionen Europas ein Anstieg in Häufigkeit und Intensität der Temperatur- und Niederschlagsextreme projiziert. Die Auswirkungen solcher meist nur kurz anhaltenden Klimaextreme auf terrestrische Ökosysteme sind zentraler Bestandteile aktueller Klimaforschung, weil nicht per se davon ausgegangen werden kann, dass Abhängihkeitsverhältnisse zwischen Klima- und Umweltvariblen linear skalierbar sind. Weil klimatische Extremereignisse selten und in der Regel nur von kurzer Dauer sind, wird für Untersuchungen über deren Auswirkungen eine analytische Methode benötigt, welche es erlaubt die Gleichzeitigkeit von Events in zwei Zeitreihen zu quantifizieren. In diesem Manuskript wird der neue statistische Ansatz der Event Coincidence Analysis sowie deren R-Implementierung vorgestellt. Zusätzlich werden verschiedene Anwendungen der Methode im Bereich der Klimafolgenforschung auf unterschiedlichen Skalen vorgelegt: Die Auswirkungen außergewöhnlicher Ausprägungen verschiedener meteorologischer Parameter auf den Stammumfang heimischer Bäume auf der täglichen lokalen Skala, die Auswirkungen von extremen Temperatur- und Niederschlagsereignissen auf die Blühzeitpunkte heimischer Sträucher auf der wöchentlichen regionalen Skala, die Auswirkung von Temperaturextremen auf den Allgemeinzustand eines Ökosystems (NDVI) auf der wöchentlichen kontinentalen Skala und der Einfluss von El Nino und La Nina Events auf Niedeschlagsanomalien auf der saisonalen globalen Skala. Schließlich soll die Veröffentlichung einer R-Implementierung der Methodik andere Wissenschaftler zur Nutzung letzterer befähigen und diese bei der Beantwortung weiterer Forschungsfragen unterstützen. KW - vegetation KW - event coincidence analysis KW - climate extreme events KW - climate impacts KW - Vegetation KW - Event Koinzidenz Analyse KW - extreme Klimaereignisse Y1 - 2018 U6 - http://nbn-resolving.de/urn/resolver.pl?urn:nbn:de:kobv:517-opus4-407095 ER -