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 -