@misc{AtmaniBookhagenSmith2022, author = {Atmani, Farid and Bookhagen, Bodo and Smith, Taylor}, title = {Measuring Vegetation Heights and Their Seasonal Changes in the Western Namibian Savanna Using Spaceborne Lidars}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1275}, issn = {1866-8372}, doi = {10.25932/publishup-56991}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-569915}, pages = {20}, year = {2022}, abstract = {The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.}, language = {en} } @article{AtmaniBookhagenSmith2022, author = {Atmani, Farid and Bookhagen, Bodo and Smith, Taylor}, title = {Measuring vegetation heights and their seasonal changes in the Western Namibian Savanna using spaceborne lidars}, series = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, volume = {14}, journal = {Remote sensing / Molecular Diversity Preservation International (MDPI)}, number = {12}, edition = {12}, publisher = {MDPI}, address = {Basel, Schweiz}, issn = {2072-4292}, doi = {10.3390/rs14122928}, pages = {1 -- 20}, year = {2022}, abstract = {The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.}, language = {en} } @book{FlottererMaximovaSchneideretal.2022, author = {Flotterer, Boris and Maximova, Maria and Schneider, Sven and Dyck, Johannes and Z{\"o}llner, Christian and Giese, Holger and H{\´e}ly, Christelle and Gaucherel, C{\´e}dric}, title = {Modeling and Formal Analysis of Meta-Ecosystems with Dynamic Structure using Graph Transformation}, series = {Technische Berichte des Hasso-Plattner-Instituts f{\"u}r Digital Engineering an der Universit{\"a}t Potsdam}, journal = {Technische Berichte des Hasso-Plattner-Instituts f{\"u}r Digital Engineering an der Universit{\"a}t Potsdam}, number = {147}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, isbn = {978-3-86956-533-0}, issn = {1613-5652}, doi = {10.25932/publishup-54764}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-547643}, publisher = {Universit{\"a}t Potsdam}, pages = {47}, year = {2022}, abstract = {The dynamics of ecosystems is of crucial importance. Various model-based approaches exist to understand and analyze their internal effects. In this paper, we model the space structure dynamics and ecological dynamics of meta-ecosystems using the formal technique of Graph Transformation (short GT). We build GT models to describe how a meta-ecosystem (modeled as a graph) can evolve over time (modeled by GT rules) and to analyze these GT models with respect to qualitative properties such as the existence of structural stabilities. As a case study, we build three GT models describing the space structure dynamics and ecological dynamics of three different savanna meta-ecosystems. The first GT model considers a savanna meta-ecosystem that is limited in space to two ecosystem patches, whereas the other two GT models consider two savanna meta-ecosystems that are unlimited in the number of ecosystem patches and only differ in one GT rule describing how the space structure of the meta-ecosystem grows. In the first two GT models, the space structure dynamics and ecological dynamics of the meta-ecosystem shows two main structural stabilities: the first one based on grassland-savanna-woodland transitions and the second one based on grassland-desert transitions. The transition between these two structural stabilities is driven by high-intensity fires affecting the tree components. In the third GT model, the GT rule for savanna regeneration induces desertification and therefore a collapse of the meta-ecosystem. We believe that GT models provide a complementary avenue to that of existing approaches to rigorously study ecological phenomena.}, language = {en} } @article{IrobBlaumBaldaufetal.2022, author = {Irob, Katja and Blaum, Niels and Baldauf, Selina and Kerger, Leon and Strohbach, Ben and Kanduvarisa, Angelina and Lohmann, Dirk and Tietjen, Britta}, title = {Browsing herbivores improve the state and functioning of savannas}, series = {Ecology and evolution}, volume = {12}, journal = {Ecology and evolution}, number = {3}, publisher = {Wiley}, address = {Hoboken}, issn = {2045-7758}, doi = {10.1002/ece3.8715}, pages = {19}, year = {2022}, abstract = {Changing climatic conditions and unsustainable land use are major threats to savannas worldwide. Historically, many African savannas were used intensively for livestock grazing, which contributed to widespread patterns of bush encroachment across savanna systems. To reverse bush encroachment, it has been proposed to change the cattle-dominated land use to one dominated by comparatively specialized browsers and usually native herbivores. However, the consequences for ecosystem properties and processes remain largely unclear. We used the ecohydrological, spatially explicit model EcoHyD to assess the impacts of two contrasting, herbivore land-use strategies on a Namibian savanna: grazer- versus browser-dominated herbivore communities. We varied the densities of grazers and browsers and determined the resulting composition and diversity of the plant community, total vegetation cover, soil moisture, and water use by plants. Our results showed that plant types that are less palatable to herbivores were best adapted to grazing or browsing animals in all simulated densities. Also, plant types that had a competitive advantage under limited water availability were among the dominant ones irrespective of land-use scenario. Overall, the results were in line with our expectations: under high grazer densities, we found heavy bush encroachment and the loss of the perennial grass matrix. Importantly, regardless of the density of browsers, grass cover and plant functional diversity were significantly higher in browsing scenarios. Browsing herbivores increased grass cover, and the higher total cover in turn improved water uptake by plants overall. We concluded that, in contrast to grazing-dominated land-use strategies, land-use strategies dominated by browsing herbivores, even at high herbivore densities, sustain diverse vegetation communities with high cover of perennial grasses, resulting in lower erosion risk and bolstering ecosystem services.}, language = {en} } @phdthesis{Kindermann2024, author = {Kindermann, Liana}, title = {Trees, shrubs, and land-use change}, doi = {10.25932/publishup-64894}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-648943}, school = {Universit{\"a}t Potsdam}, pages = {X, 186}, year = {2024}, abstract = {The global drylands cover nearly half of the terrestrial surface and are home to more than two billion people. In many drylands, ongoing land-use change transforms near-natural savanna vegetation to agricultural land to increase food production. In Southern Africa, these heterogenous savanna ecosystems are also recognized as habitats of many protected animal species, such as elephant, lion and large herds of diverse herbivores, which are of great value for the tourism industry. Here, subsistence farmers and livestock herder communities often live in close proximity to nature conservation areas. Although these land-use transformations are different regarding the future they aspire to, both processes, nature conservation with large herbivores and agricultural intensification, have in common, that they change the vegetation structure of savanna ecosystems, usually leading to destruction of trees, shrubs and the woody biomass they consist of. Such changes in woody vegetation cover and biomass are often regarded as forms of land degradation and forest loss. Global forest conservation approaches and international programs aim to stop degradation processes, also to conserve the carbon bound within wood from volatilization into earth's atmosphere. In search for mitigation options against global climate change savannas are increasingly discussed as potential carbon sinks. Savannas, however, are not forests, in that they are naturally shaped by and adapted to disturbances, such as wildfires and herbivory. Unlike in forests, disturbances are necessary for stable, functioning savanna ecosystems and prevent these ecosystems from forming closed forest stands. Their consequently lower levels of carbon storage in woody vegetation have long been the reason for savannas to be overlooked as a potential carbon sink but recently the question was raised if carbon sequestration programs (such as REDD+) could also be applied to savanna ecosystems. However, heterogenous vegetation structure and chronic disturbances hamper the quantification of carbon stocks in savannas, and current procedures of carbon storage estimation entail high uncertainties due to methodological obstacles. It is therefore challenging to assess how future land-use changes such as agricultural intensification or increasing wildlife densities will impact the carbon storage balance of African drylands. In this thesis, I address the research gap of accurately quantifying carbon storage in vegetation and soils of disturbance-prone savanna ecosystems. I further analyse relevant drivers for both ecosystem compartments and their implications for future carbon storage under land-use change. Moreover, I show that in savannas different carbon storage pools vary in their persistence to disturbance, causing carbon bound in shrub vegetation to be most likely to experience severe losses under land-use change while soil organic carbon stored in subsoils is least likely to be impacted by land-use change in the future. I start with summarizing conventional approaches to carbon storage assessment and where and for which reasons they fail to accurately estimated savanna ecosystem carbon storage. Furthermore, I outline which future-making processes drive land-use change in Southern Africa along two pathways of land-use transformation and how these are likely to influence carbon storage. In the following chapters, I propose a new method of carbon storage estimation which is adapted to the specific conditions of disturbance-prone ecosystems and demonstrate the advantages of this approach in relation to existing forestry methods. Specifically, I highlight sources for previous over- and underestimation of savanna carbon stocks which the proposed methodology resolves. In the following chapters, I apply the new method to analyse impacts of land-use change on carbon storage in woody vegetation in conjunction with the soil compartment. With this interdisciplinary approach, I can demonstrate that indeed both, agricultural intensification and nature conservation with large herbivores, reduce woody carbon storage above- and belowground, but partly sequesters this carbon into the soil organic carbon stock. I then quantify whole-ecosystem carbon storage in different ecosystem compartments (above- and belowground woody carbon in shrubs and trees, respectively, as well as topsoil and subsoil organic carbon) of two savanna vegetation types (scrub savanna and savanna woodland). Moreover, in a space-for-time substitution I analyse how land-use changes impact carbon storage in each compartment and in the whole ecosystem. Carbon storage compartments are found to differ in their persistence to land-use change with carbon bound in shrub biomass being least persistent to future changes and subsoil organic carbon being most stable under changing land-use. I then explore which individual land-use change effects act as drivers of carbon storage through Generalized Additive Models (GAMs) and uncover non-linear effects, especially of elephant browsing, with implications for future carbon storage. In the last chapter, I discuss my findings in the larger context of this thesis and discuss relevant implications for land-use change and future-making decisions in rural Africa.}, language = {en} } @article{MoustakasGuentherWiegandetal.2006, author = {Moustakas, Aristides and G{\"u}nther, Matthias and Wiegand, Kerstin and M{\"u}ller, Karl-Heinz and Ward, David and Meyer, Katrin M. and Jeltsch, Florian}, title = {Long-term mortality patterns of the deep-rooted Acacia erioloba}, series = {Journal of vegetation science}, volume = {17}, journal = {Journal of vegetation science}, publisher = {Blackwell}, address = {Malden}, issn = {1100-9233}, doi = {10.1111/j.1654-1103.2006.tb02468.x}, pages = {473 -- 480}, year = {2006}, abstract = {Question: Is there a relationship between size and death in the Iona-lived, deep-rooted tree, Acacia erioloba, in a semi-arid savanna? What is the size-class distribution of A. erioloba mortality? Does the mortality distribution differ from total tree size distribution? Does A. erioloba mortality distribution match the mortality distributions recorded thus far in other environments? Location: Dronfield Ranch, near Kimberley, Kalahari, South Africa. Methods: A combination of aerial photographs and a satellite image covering 61 year was used to provide long-term spatial data on mortality. We used aerial photographs of the study area from 1940, 1964, 1984, 1993 and a satellite image from 2001 to follow three plots covering 510 ha. We were able to identify and individually follow ca. 3000 individual trees from 1940 till 2001. Results: The total number of trees increased over time. No relationship between total number of trees and mean tree size was detected. There were no trends over time in total number of deaths per plot or in size distributions of dead trees. Kolmogorov-Smirnov tests showed no differences in size class distributions for living trees through time. The size distribution of dead trees was significantly different from the size distribution of all trees present on the plots. Overall, the number of dead trees was low in small size classes, reached a peak value when canopy area was 20 - 30 m(2), and declined in lamer size-classes. Mortality as a ratio of dead vs. total trees peaked at intermediate canopy sizes too. Conclusion: A. erioloba mortality was size-dependent, peaking at intermediate sizes. The mortality distribution differs from all other tree mortality distributions recorded thus far. We suggest that a possible mechanism for this unusual mortality distribution is intraspecific competition for water in this semi-arid environment.}, language = {en} }