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P>Despite ample research, understanding plant spread and predicting their ability to track projected climate changes remain a formidable challenge to be confronted. We modelled the spread of North American wind-dispersed trees in current and future (c. 2060) conditions, accounting for variation in 10 key dispersal, demographic and environmental factors affecting population spread. Predicted spread rates vary substantially among 12 study species, primarily due to inter-specific variation in maturation age, fecundity and seed terminal velocity. Future spread is predicted to be faster if atmospheric CO2 enrichment would increase fecundity and advance maturation, irrespective of the projected changes in mean surface windspeed. Yet, for only a few species, predicted wind-driven spread will match future climate changes, conditioned on seed abscission occurring only in strong winds and environmental conditions favouring high survival of the farthest-dispersed seeds. Because such conditions are unlikely, North American wind-dispersed trees are expected to lag behind the projected climate range shift.
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.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
RangeShiftR
(2021)
Reliably modelling the demographic and distributional responses of a species to environmental changes can be crucial for successful conservation and management planning. Process-based models have the potential to achieve this goal, but so far they remain underused for predictions of species' distributions. Individual-based models offer the additional capability to model inter-individual variation and evolutionary dynamics and thus capture adaptive responses to environmental change. We present RangeShiftR, an R implementation of a flexible individual-based modelling platform which simulates eco-evolutionary dynamics in a spatially explicit way. The package provides flexible and fast simulations by making the software RangeShifter available for the widely used statistical programming platform R. The package features additional auxiliary functions to support model specification and analysis of results. We provide an outline of the package's functionality, describe the underlying model structure with its main components and present a short example. RangeShiftR offers substantial model complexity, especially for the demographic and dispersal processes. It comes with elaborate tutorials and comprehensive documentation to facilitate learning the software and provide help at all levels. As the core code is implemented in C++, the computations are fast. The complete source code is published under a public licence, making adaptations and contributions feasible. The RangeShiftR package facilitates the application of individual-based and mechanistic modelling to eco-evolutionary questions by operating a flexible and powerful simulation model from R. It allows effortless interoperation with existing packages to create streamlined workflows that can include data preparation, integrated model specification and results analysis. Moreover, the implementation in R strengthens the potential for coupling RangeShiftR with other models.
Talitrids are the only family within the order Amphipoda to have colonised supralittoral and terrestrial environments. They live in a variety of settings, from sandy to rocky and pebble beaches, to river and lake banks, and to leaf litter and caves. A common feature is the absence of a planktonic larval stage to facilitate passive dispersal over long-distances. However, some species have broad distributions. Genetic studies over the past 25 years have tried to explain this apparent contradiction by assessing patterns of species genetic structuring on different geographical scales. Here, we review the molecular studies available to date and focus on the population genetics of talitrids. Most of these studies considered populations in the Mediterranean area, but also along the Atlantic coast and in Canary Island caves. From this review, the group emerges as a potential model to understand processes of dispersal and divergence in non-highly-vagile supralittoral organisms. At the same time, studies on these issues are still too restricted geographically: a worldwide scale including different regions would provide us with a better perspective on these problems.
The spatial distribution of a species is determined by dynamic processes such as reproduction, mortality and dispersal. Conventional static species distribution models (SDMs) do not incorporate these processes explicitly. This limits their applicability, particularly for non-equilibrium situations such as invasions or climate change. In this paper we show how dynamic SDMs can be formulated and fitted to data within a Bayesian framework. Our focus is on discrete state-space Markov process models which provide a flexible framework to account for stochasticity in key demographic processes, including dispersal, growth and competition. We show how to construct likelihood functions for such models (both discrete and continuous time versions) and how these can be combined with suitable observation models to conduct Bayesian parameter inference using computational techniques such as Markov chain Monte Carlo. We illustrate the current state-of-the-art with three contrasting examples using both simulated and empirical data. The use of simulated data allows the robustness of the methods to be tested with respect to deficiencies in both data and model. These examples show how mechanistic understanding of the processes that determine distribution and abundance can be combined with different sources of information at a range of spatial and temporal scales. Application of such techniques will enable more reliable inference and projections, e.g. under future climate change scenarios than is possible with purely correlative approaches. Conversely, confronting such process-oriented niche models with abundance and distribution data will test current understanding and may ultimately feedback to improve underlying ecological theory.
The Strange-tailed Tyrant Alectrurus risora (Aves: Tyrannidae) is an endemic species of southern South American grasslands that suffered a 90% reduction of its original distribution due to habitat transformation. This has led the species to be classified as globally Vulnerable. By the beginning of the last century, populations were partially migratory and moved south during the breeding season. Currently, the main breeding population inhabits the Ibera wetlands in the province of Corrientes, north-east Argentina, where it is resident all year round. There are two remaining small populations in the province of Formosa, north-east Argentina, and in southern Paraguay, which are separated from the main population by the Parana-Paraguay River and its continuous riverine forest habitat. The populations of Corrientes and Formosa are separated by 300 km and the grasslands between populations are non-continuous due to habitat transformation. We used mtDNA sequences and eight microsatellite loci to test if there were evidences of genetic isolation between Argentinean populations. We found no evidence of genetic structure between populations (Phi(ST) = 0.004, P = 0.32; Fst = 0.01, P = 0.06), which can be explained by either retained ancestral polymorphism or by dispersal between populations. We found no evidence for a recent demographic bottleneck in nuclear loci. Our results indicate that these populations could be managed as a single conservation unit on a regional scale. Conservation actions should be focused on preserving the remaining network of areas with natural grasslands to guarantee reproduction, dispersal and prevent further decline of populations.
Dispersal and foodweb dynamics have long been studied in separate models. However, over the past decades, it has become abundantly clear that there are intricate interactions between local dynamics and spatial patterns. Trophic meta-communities, i.e. meta-foodwebs, are very complex systems that exhibit complex and often counterintuitive dynamics. Over the past decade, a broad range of modelling approaches have been used to study these systems. In this paper, we review these approaches and the insights that they have revealed. We focus particularly on recent papers that study trophic interactions in spatially extensive settings and highlight the common themes that emerged in different models. There is overwhelming evidence that dispersal (and particularly intermediate levels of dispersal) benefits the maintenance of biodiversity in several different ways. Moreover, some insights have been gained into the effect of different habitat topologies, but these results also show that the exact relationships are much more complex than previously thought, highlighting the need for further research in this area. This article is part of the theme issue 'Integrative research perspectives on marine conservation'.
A seed sowing experiment was conducted in a mixed secondary woodland on acidic soils in NE Germany with Melampyrum pratense, an annual ant-dispersed forest herb which lacks a natural population in the study area, but is abundant in similar habitats. Each set of 300 seeds was sown within one square metre at three sites in 1997, and the development of the populations was recorded from 1998 onward. Additionally, seed fall patterns were studied in a natural population by means of adhesive cardboard. All trials resulted in the recruitment of populations, which survived and increased in both individual number and area, up to the year 2001. Thus, local distribution of Melampyrum pratense is dispersallimited. Total individual number increased from 105 to 3,390, and total population area from 2.07 to 109.04 m². Migration occurred in all directions. Mean migration rate was 0.91 m per year, and the highest migration rate was 6.48 m. No individual was recorded beyond 7.63 m from the centres of the sawn squares after three years, suggesting exclusive short-distance dispersal. As primary dispersal enables only distances of up to 0.25 m, ants are presumed to be the main dispersal vectors. Despite differences in individual number and colonization patterns, migration rates did not differ significantly between the populations, but were significantly higher in 2001 due to an increased population size. Colonization patterns were characterized by a rapid, negative exponential decrease of population density with increasing distance from the sown plot, suggesting a colonization by establishment of more or less isolated outposts of individuals and a subsequent gradual infill of the gaps between. My results resemble myrmecochorous dispersal distances in temperate woodlands, and migration rates and patterns across ecotones from ancient to recent deciduous forests. They may function as a colonization model of Melampyrum pratense after accidental long-distance dispersal.