@phdthesis{May2013, author = {May, Felix}, title = {Spatial models of plant diversity and plant functional traits : towards a better understanding of plant community dynamics in fragmented landscapes}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus-68444}, school = {Universit{\"a}t Potsdam}, year = {2013}, abstract = {The fragmentation of natural habitat caused by anthropogenic land use changes is one of the main drivers of the current rapid loss of biodiversity. In face of this threat, ecological research needs to provide predictions of communities' responses to fragmentation as a prerequisite for the effective mitigation of further biodiversity loss. However, predictions of communities' responses to fragmentation require a thorough understanding of ecological processes, such as species dispersal and persistence. Therefore, this thesis seeks an improved understanding of community dynamics in fragmented landscapes. In order to approach this overall aim, I identified key questions on the response of plant diversity and plant functional traits to variations in species' dispersal capability, habitat fragmentation and local environmental conditions. All questions were addressed using spatially explicit simulations or statistical models. In chapter 2, I addressed scale-dependent relationships between dispersal capability and species diversity using a grid-based neutral model. I found that the ratio of survey area to landscape size is an important determinant of scale-dependent dispersal-diversity relationships. With small ratios, the model predicted increasing dispersal-diversity relationships, while decreasing dispersal-diversity relationships emerged, when the ratio approached one, i.e. when the survey area approached the landscape size. For intermediate ratios, I found a U-shaped pattern that has not been reported before. With this study, I unified and extended previous work on dispersal-diversity relationships. In chapter 3, I assessed the type of regional plant community dynamics for the study area in the Southern Judean Lowlands (SJL). For this purpose, I parameterised a multi-species incidence-function model (IFM) with vegetation data using approximate Bayesian computation (ABC). I found that the type of regional plant community dynamics in the SJL is best characterized as a set of isolated "island communities" with very low connectivity between local communities. Model predictions indicated a significant extinction debt with 33\% - 60\% of all species going extinct within 1000 years. In general, this study introduces a novel approach for combining a spatially explicit simulation model with field data from species-rich communities. In chapter 4, I first analysed, if plant functional traits in the SJL indicate trait convergence by habitat filtering and trait divergence by interspecific competition, as predicted by community assembly theory. Second, I assessed the interactive effects of fragmentation and the south-north precipitation gradient in the SJL on community-mean plant traits. I found clear evidence for trait convergence, but the evidence for trait divergence fundamentally depended on the chosen null-model. All community-mean traits were significantly associated with the precipitation gradient in the SJL. The trait associations with fragmentation indices (patch size and connectivity) were generally weaker, but statistically significant for all traits. Specific leaf area (SLA) and plant height were consistently associated with fragmentation indices along the precipitation gradient. In contrast, seed mass and seed number were interactively influenced by fragmentation and precipitation. In general, this study provides the first analysis of the interactive effects of climate and fragmentation on plant functional traits. Overall, I conclude that the spatially explicit perspective adopted in this thesis is crucial for a thorough understanding of plant community dynamics in fragmented landscapes. The finding of contrasting responses of local diversity to variations in dispersal capability stresses the importance of considering the diversity and composition of the metacommunity, prior to implementing conservation measures that aim at increased habitat connectivity. The model predictions derived with the IFM highlight the importance of additional natural habitat for the mitigation of future species extinctions. In general, the approach of combining a spatially explicit IFM with extensive species occupancy data provides a novel and promising tool to assess the consequences of different management scenarios. The analysis of plant functional traits in the SJL points to important knowledge gaps in community assembly theory with respect to the simultaneous consequences of habitat filtering and competition. In particular, it demonstrates the importance of investigating the synergistic consequences of fragmentation, climate change and land use change on plant communities. I suggest that the integration of plant functional traits and of species interactions into spatially explicit, dynamic simulation models offers a promising approach, which will further improve our understanding of plant communities and our ability to predict their dynamics in fragmented and changing landscapes.}, language = {en} } @phdthesis{Carus2017, author = {Carus, Jana}, title = {Plant-habitat interactions in brackish marshes}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-404966}, school = {Universit{\"a}t Potsdam}, pages = {VII, 103}, year = {2017}, abstract = {Estuarine marshes are ecosystems that are situated at the transition zone between land and water and are thus controlled by physical and biological interactions. Marsh vegetation offers important ecosystem services by filtrating solid and dissolved substances from the water and providing habitat. By buffering a large part of the arriving flow velocity, attenuating wave energy and serving as erosion control for riverbanks, tidal marshes furthermore reduce the destructive effects of storm surges and storm waves and thus contribute to ecosystem-based shore protection. However, in many estuaries, extensive embankments, artificial bank protection, river dredging and agriculture threaten tidal marshes. Global warming might entail additional risks, such as changes in water levels, an increase of the tidal amplitude and a resulting shift of the salinity zones. This can affect the dynamics of the shore and foreland vegetation, and vegetation belts can be narrowed or fragmented. Against this background, it is crucial to gain a better understanding of the processes underlying the spatio temporal vegetation dynamics in brackish marshes. Furthermore, a better understanding of how plant-habitat relationships generate patterns in tidal marsh vegetation is vital to maintain ecosystem functions and assess the response of marshes to environmental change as well as the success of engineering and restoration projects. For this purpose, three research objectives were addressed within this thesis: (1) to explore the possibility of vegetation serving as self-adaptive shore protection by quantifying the reduction of current velocity in the vegetation belt and the morphologic plasticity of a brackish marsh pioneer, (2) to disentangle the roles of abiotic factors and interspecific competition on species distribution and stand characteristics in brackish marshes, and (3) to develop a mechanistic vegetation model that helps analysing the influence of habitat conditions on the spatio-temporal dynamic of tidal marsh vegetation. These aspects were investigated using a combination of field studies and statistical as well as process-based modelling. To explore the possibility of vegetation serving as self-adaptive coastal protection, in the first study, we measured current velocity with and without living vegetation, recorded ramet density and plant thickness during two growing periods at two locations in the Elbe estuary and assessed the adaptive value of a larger stem diameter of plants at locations with higher mechanical stress by biomechanical measurements. The results of this study show that under non-storm conditions, the vegetation belt of the marsh pioneer Bolboschoenus maritimus is able to buffer a large proportion of the flow velocity. We were furthermore able to show that morphological traits of plant species are adapted to hydrodynamic forces by demonstrating a positive correlation between ramet thickness and cross-shore current. In addition, our measurements revealed that thicker ramets growing at the front of the vegetation belt have a significantly higher stability than ramets inside the vegetation belt. This self-adaptive effect improves the ability of B. maritimus to grow and persist in the pioneer zone and could provide an adaptive value in habitats with high mechanical stress. In the second study, we assessed the distribution of the two marsh species and a set of stand characteristics, namely aboveground and belowground biomass, ramet density, ramet height and the percentage of flowering ramets. Furthermore, we collected information on several abiotic habitat factors to test their effect on plant growth and zonation with generalised linear models (GLMs). Our results demonstrate that flow velocity is the main factor controlling the distribution of Bolboschoenus maritimus and Phragmites australis. Additionally, inundation height and duration, as well as intraspecific competition affect distribution patterns. This study furthermore shows that cross-shore flow velocity does not only directly influence the distribution of the two marsh species, but also alters the plants' occurrence relative to inun-dation height and duration. This suggests an effect of cross-shore flow velocity on their tolerance to inundation. The analysis of the measured stand characteristics revealed a negative effect of total flow velocity on all measured parameters of B. maritimus and thus confirmed our expectation that flow velocity is a decisive stressor which influences the growth of this species. To gain a better understanding of the processes and habitat factors influencing the spatio-temporal vegetation dynamics in brackish marshes, I built a spatially explicit, mechanistic model applying a pattern-oriented modelling approach. A sensitivity analysis of the para-meters of this dynamic habitat-macrophyte model HaMac suggests that rhizome growth is the key process for the lateral dynamics of brackish marshes. From the analysed habitat factors, P. australis patterns were mainly influenced by flow velocity. The competition with P. australis was of key importance for the belowground biomass of B. maritimus. Concerning vegetation dynamics, the model results emphasise that without the effect of flow velocity the B. maritimus vegetation belt would expand into the tidal flat at locations with present vegetation recession, suggesting that flow velocity is the main reason for vegetation recession at exposed locations. Overall, the results of this thesis demonstrate that brackish marsh vegetation considerably contributes to flow reduction under average flow conditions and can hence be a valuable component of shore-protection schemes. At the same time, the distribution, growth and expansion of tidal marsh vegetation is substantially influenced by flow. Altogether, this thesis provides a clear step forward in understanding plant-habitat interactions in tidal marshes. Future research should integrate studies of vertical marsh accretion with research on the factors that control the lateral position of marshes.}, language = {en} } @phdthesis{Reeg2019, author = {Reeg, Jette}, title = {Simulating the impact of herbicide drift exposure on non-target terrestrial plant communities}, doi = {10.25932/publishup-42907}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-429073}, school = {Universit{\"a}t Potsdam}, pages = {178}, year = {2019}, abstract = {In Europe, almost half of the terrestrial landscape is used for agriculture. Thus, semi-natural habitats such as field margins are substantial for maintaining diversity in intensively managed farmlands. However, plants located at field margins are threatened by agricultural practices such as the application of pesticides within the fields. Pesticides are chemicals developed to control for undesired species within agricultural fields to enhance yields. The use of pesticides implies, however, effects on non-target organisms within and outside of the agricultural fields. Non-target organisms are organisms not intended to be sprayed or controlled for. For example, plants occurring in field margins are not intended to be sprayed, however, can be impaired due to herbicide drift exposure. The authorization of plant protection products such as herbicides requires risk assessments to ensure that the application of the product has no unacceptable effects on the environment. For non-target terrestrial plants (NTTPs), the risk assessment is based on standardized greenhouse studies on plant individual level. To account for the protection of plant populations and communities under realistic field conditions, i.e. extrapolating from greenhouse studies to field conditions and from individual-level to community-level, assessment factors are applied. However, recent studies question the current risk assessment scheme to meet the specific protection goals for non-target terrestrial plants as suggested by the European Food Safety Authority (EFSA). There is a need to clarify the gaps of the current risk assessment and to include suitable higher tier options in the upcoming guidance document for non-target terrestrial plants. In my thesis, I studied the impact of herbicide drift exposure on NTTP communities using a mechanistic modelling approach. I addressed main gaps and uncertainties of the current risk assessment and finally suggested this modelling approach as a novel higher tier option in future risk assessments. Specifically, I extended the plant community model IBC-grass (Individual-based community model for grasslands) to reflect herbicide impacts on plant individuals. In the first study, I compared model predictions of short-term herbicide impacts on artificial plant communities with empirical data. I demonstrated the capability of the model to realistically reflect herbicide impacts. In the second study, I addressed the research question whether or not reproductive endpoints need to be included in future risk assessments to protect plant populations and communities. I compared the consequences of theoretical herbicide impacts on different plant attributes for long-term plant population dynamics in the community context. I concluded that reproductive endpoints only need to be considered if the herbicide effect is assumed to be very high. The endpoints measured in the current vegetative vigour and seedling emergence studies had high impacts for the dynamic of plant populations and communities already at lower effect intensities. Finally, the third study analysed long-term impacts of herbicide application for three different plant communities. This study highlighted the suitability of the modelling approach to simulate different communities and thus detecting sensitive environmental conditions. Overall, my thesis demonstrates the suitability of mechanistic modelling approaches to be used as higher tier options for risk assessments. Specifically, IBC-grass can incorporate available individual-level effect data of standardized greenhouse experiments to extrapolate to community-level under various environmental conditions. Thus, future risk assessments can be improved by detecting sensitive scenarios and including worst-case impacts on non-target plant communities.}, language = {en} } @phdthesis{Crawford2020, author = {Crawford, Michael Scott}, title = {Using individual-based modeling to understand grassland diversity and resilience in the Anthropocene}, doi = {10.25932/publishup-47941}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-479414}, school = {Universit{\"a}t Potsdam}, pages = {174}, year = {2020}, abstract = {The world's grassland systems are increasingly threatened by anthropogenic change. Susceptible to a variety of different stressors, from land-use intensification to climate change, understanding the mechanisms driving the maintenance of these systems' biodiversity and stability, and how these mechanisms may shift under human-mediated disturbance, is thus critical for successfully navigating the next century. Within this dissertation, I use an individual-based and spatially-explicit model of grassland community assembly (IBC-grass) to examine several processes, thought key to understanding their biodiversity and stability and how it changes under stress. In the first chapter of my thesis, I examine the conditions under which intraspecific trait variation influences the diversity of simulated grassland communities. In the second and third chapters of my thesis, I shift focus towards understanding how belowground herbivores influence the stability of these grassland systems to either a disturbance that results in increased, stochastic, plant mortality, or eutrophication. Intraspecific trait variation (ITV), or variation in trait values between individuals of the same species, is fundamental to the structure of ecological communities. However, because it has historically been difficult to incorporate into theoretical and statistical models, it has remained largely overlooked in community-level analyses. This reality is quickly shifting, however, as a consensus of research suggests that it may compose a sizeable proportion of the total variation within an ecological community and that it may play a critical role in determining if species coexist. Despite this increasing awareness that ITV matters, there is little consensus of the magnitude and direction of its influence. Therefore, to better understand how ITV changes the assembly of grassland communities, in the first chapter of my thesis, I incorporate it into an established, individual-based grassland community model, simulating both pairwise invasion experiments as well as the assembly of communities with varying initial diversities. By varying the amount of ITV in these species' functional traits, I examine the magnitude and direction of ITV's influence on pairwise invasibility and community coexistence. During pairwise invasion, ITV enables the weakest species to more frequently invade the competitively superior species, however, this influence does not generally scale to the community level. Indeed, unless the community has low alpha- and beta- diversity, there will be little effect of ITV in bolstering diversity. In these situations, since the trait axis is sparsely filled, the competitively inferior may suffer less competition and therefore ITV may buffer the persistence and abundance of these species for some time. In the second and third chapters of my thesis, I model how one of the most ubiquitous trophic interactions within grasslands, herbivory belowground, influences their diversity and stability. Until recently, the fundamental difficulty in studying a process within the soil has left belowground herbivory "out of sight, out of mind." This dilemma presents an opportunity for simulation models to explore how this understudied process may alter community dynamics. In the second chapter of my thesis, I implement belowground herbivory - represented by the weekly removal of plant biomass - into IBC-grass. Then, by introducing a pulse disturbance, modelled as the stochastic mortality of some percentage of the plant community, I observe how the presence of belowground herbivores influences the resistance and recovery of Shannon diversity in these communities. I find that high resource, low diversity, communities are significantly more destabilized by the presence of belowground herbivores after disturbance. Depending on the timing of the disturbance and whether the grassland's seed bank persists for more than one season, the impact of the disturbance - and subsequently the influence of the herbivores - can be greatly reduced. However, because human-mediated eutrophication increases the amount of resources in the soil, thus pressuring grassland systems, our results suggest that the influence of these herbivores may become more important over time. In the third chapter of my thesis, I delve further into understanding the mechanistic underpinnings of belowground herbivores on the diversity of grasslands by replicating an empirical mesocosm experiment that crosses the presence of herbivores above- and below-ground with eutrophication. I show that while aboveground herbivory, as predicted by theory and frequently observed in experiments, mitigates the impact of eutrophication on species diversity, belowground herbivores counterintuitively reduce biodiversity. Indeed, this influence positively interacts with the eutrophication process, amplifying its negative impact on diversity. I discovered the mechanism underlying this surprising pattern to be that, as the herbivores consume roots, they increase the proportion of root resources to root biomass. Because root competition is often symmetric, herbivory fails to mitigate any asymmetries in the plants' competitive dynamics. However, since the remaining roots have more abundant access to resources, the plants' competition shifts aboveground, towards asymmetric competition for light. This leads the community towards a low-diversity state, composed of mostly high-performance, large plant species. We further argue that this pattern will emerge unless the plants' root competition is asymmetric, in which case, like its counterpart aboveground, belowground herbivory may buffer diversity by reducing this asymmetry between the competitively superior and inferior plants. I conclude my dissertation by discussing the implications of my research on the state of the art in intraspecific trait variation and belowground herbivory, with emphasis on the necessity of more diverse theory development in the study of these fundamental interactions. My results suggest that the influence of these processes on the biodiversity and stability of grassland systems is underappreciated and multidimensional, and must be thoroughly explored if researchers wish to predict how the world's grasslands will respond to anthropogenic change. Further, should researchers myopically focus on understanding central ecological interactions through only mathematically tractable analyses, they may miss entire suites of potential coexistence mechanisms that can increase the coviability of species, potentially leading to coexistence over ecologically-significant timespans. Individual-based modelling, therefore, with its focus on individual interactions, will prove a critical tool in the coming decades for understanding how local interactions scale to larger contexts, and how these interactions shape ecological communities and further predicting how these systems will change under human-mediated stress.}, language = {en} } @phdthesis{Malchow2023, author = {Malchow, Anne-Kathleen}, title = {Developing an integrated platform for predicting niche and range dynamics}, doi = {10.25932/publishup-60273}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-602737}, school = {Universit{\"a}t Potsdam}, pages = {xiv, 169}, year = {2023}, abstract = {Species are adapted to the environment they live in. Today, most environments are subjected to rapid global changes induced by human activity, most prominently land cover and climate changes. Such transformations can cause adjustments or disruptions in various eco-evolutionary processes. The repercussions of this can appear at the population level as shifted ranges and altered abundance patterns. This is where global change effects on species are usually detected first. To understand how eco-evolutionary processes act and interact to generate patterns of range and abundance and how these processes themselves are influenced by environmental conditions, spatially-explicit models provide effective tools. They estimate a species' niche as the set of environmental conditions in which it can persist. However, the currently most commonly used models rely on static correlative associations that are established between a set of spatial predictors and observed species distributions. For this, they assume stationary conditions and are therefore unsuitable in contexts of global change. Better equipped are process-based models that explicitly implement algorithmic representations of eco-evolutionary mechanisms and evaluate their joint dynamics. These models have long been regarded as difficult to parameterise, but an increased data availability and improved methods for data integration lessen this challenge. Hence, the goal of this thesis is to further develop process-based models, integrate them into a complete modelling workflow, and provide the tools and guidance for their successful application. With my thesis, I presented an integrated platform for spatially-explicit eco-evolutionary modelling and provided a workflow for their inverse calibration to observational data. In the first chapter, I introduced RangeShiftR, a software tool that implements an individual-based modelling platform for the statistical programming language R. Its open-source licensing, extensive help pages and available tutorials make it accessible to a wide audience. In the second chapter, I demonstrated a comprehensive workflow for the specification, calibration and validation of RangeShiftR by the example of the red kite in Switzerland. The integration of heterogeneous data sources, such as literature and monitoring data, allowed to successfully calibrate the model. It was then used to make validated, spatio-temporal predictions of future red kite abundance. The presented workflow can be adopted to any study species if data is available. In the third chapter, I extended RangeShiftR to directly link demographic processes to climatic predictors. This allowed me to explore the climate-change responses of eight Swiss breeding birds in more detail. Specifically, the model could identify the most influential climatic predictors, delineate areas of projected demographic suitability, and attribute current population trends to contemporary climate change. My work shows that the application of complex, process-based models in conservation-relevant contexts is feasible, utilising available tools and data. Such models can be successfully calibrated and outperform other currently used modelling approaches in terms of predictive accuracy. Their projections can be used to predict future abundances or to assess alternative conservation scenarios. They further improve our mechanistic understanding of niche and range dynamics under climate change. However, only fully mechanistic models, that include all relevant processes, allow to precisely disentangle the effects of single processes on observed abundances. In this respect, the RangeShiftR model still has potential for further extensions that implement missing influential processes, such as species interactions. Dynamic, process-based models are needed to adequately model a dynamic reality. My work contributes towards the advancement, integration and dissemination of such models. This will facilitate numeric, model-based approaches for species assessments, generate ecological insights and strengthen the reliability of predictions on large spatial scales under changing conditions.}, language = {en} }