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Understanding the environmental impact on the assembly of local communities in relation to their spatial and temporal connectivity is still a challenge in metacommunity ecology. This study aims to unravel underlying metacommunity processes and environmental factors that result in observed zooplankton communities. Unlike most metacommunity studies, we jointly examine active and dormant zooplankton communities using a DNA metabarcoding approach to overcome limitations of morphological species identification. We applied two-fragment (COI and 18S) metabarcoding to monitor communities of 24 kettle holes over a two-year period to unravel (i) spatial and temporal connectivity of the communities, (ii) environmental factors influencing local communities, and (iii) dominant underlying metacommunity processes in this system. We found a strong separation of zooplankton communities from kettle holes of different hydroperiods (degree of permanency) throughout the season, while the community composition within single kettle holes did not differ between years. Species richness was primarily dependent on pH and permanency, while species diversity (Shannon Index) was influenced by kettle hole location. Community composition was impacted by kettle hole size and surrounding field crops. Environmental processes dominated temporal and spatial processes. Sediment communities showed a different composition compared to water samples but did not differ between ephemeral and permanent kettle holes. Our results suggest that communities are mainly structured by environmental filtering based on pH, kettle hole size, surrounding field crops, and permanency. Environmental filtering based on specific conditions in individual kettle holes seems to be the dominant process in community assembly in the studied zooplankton metacommunity.
Evidence of female preference for odor of distant over local males in a bat with female dispersal
(2021)
Geographic variation of sexually selected male traits is common in animals. Female choice also varies geographically and several studies found female preference for local males, which is assumed to lead to local adaptation and, therefore, increases fitness. As females are the nondispersing sex in most mammalian taxa, this preference for local males might be explained by the learning of male characteristics. Studies on the preference of females in female-dispersing species are lacking so far. To find out whether such females would also show preferences for local males, we conducted a study on greater sac-winged bats (Saccopteryx bilineata), a species where females disperse and males stay in their natal colony. Male greater sac-winged bats possess a wing pouch that is filled with odoriferous secretion and fanned toward females during courtship display. In a combination of chemical analysis and behavioral preference tests, we analyzed whether the composition of wing sac secretion varies between two geographically distinct populations (300 km), and whether females show a preference for local or distant male scent. Using gas chromatography, we found significant differences in the composition of the wing sac odors between the two geographically distinct populations. In addition, the behavioral preference experiments revealed that females of both populations preferred the scent of geographically distant males over local males. The wing sac odor might thus be used to guarantee optimal outbreeding when dispersing to a new colony. This is-to our knowledge-the first study on odor preference of females of a species with female-biased dispersal.
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.
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.
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'.
Meta‐communities of habitat islands may be essential to maintain biodiversity in anthropogenic landscapes allowing rescue effects in local habitat patches. To understand the species‐assembly mechanisms and dynamics of such ecosystems, it is important to test how local plant‐community diversity and composition is affected by spatial isolation and hence by dispersal limitation and local environmental conditions acting as filters for local species sorting. We used a system of 46 small wetlands (kettle holes)—natural small‐scale freshwater habitats rarely considered in nature conservation policies—embedded in an intensively managed agricultural matrix in northern Germany. We compared two types of kettle holes with distinct topographies (flatsloped, ephemeral, frequently plowed kettle holes vs. steep‐sloped, more permanent ones) and determined 254 vascular plant species within these ecosystems, as well as plant functional traits and nearest neighbor distances to other kettle holes. Differences in alpha and beta diversity between steep permanent compared with ephemeral flat kettle holes were mainly explained by species sorting and niche processes and mass effect processes in ephemeral flat kettle holes. The plant‐community composition as well as the community trait distribution in terms of life span, breeding system, dispersal ability, and longevity of seed banks significantly differed between the two habitat types. Flat ephemeral kettle holes held a higher percentage of non‐perennial plants with a more persistent seed bank, less obligate outbreeders and more species with seed dispersal abilities via animal vectors compared with steep‐sloped, more permanent kettle holes that had a higher percentage of wind‐dispersed species. In the flat kettle holes, plant‐species richness was negatively correlated with the degree of isolation, whereas no such pattern was found for the permanent kettle holes. Synthesis: Environment acts as filter shaping plant diversity (alpha and beta) and plant‐community trait distribution between steep permanent compared with ephemeral flat kettle holes supporting species sorting and niche mechanisms as expected, but we identified a mass effect in ephemeral kettle holes only. Flat ephemeral kettle holes can be regarded as meta‐ecosystems that strongly depend on seed dispersal and recruitment from a seed bank, whereas neighboring permanent kettle holes have a more stable local species diversity.
Meta-communities of habitat islands may be essential to maintain biodiversity in anthropogenic landscapes allowing rescue effects in local habitat patches. To understand the species-assembly mechanisms and dynamics of such ecosystems, it is important to test how local plant-community diversity and composition is affected by spatial isolation and hence by dispersal limitation and local environmental conditions acting as filters for local species sorting.We used a system of 46 small wetlands (kettle holes)natural small-scale freshwater habitats rarely considered in nature conservation policiesembedded in an intensively managed agricultural matrix in northern Germany. We compared two types of kettle holes with distinct topographies (flat-sloped, ephemeral, frequently plowed kettle holes vs. steep-sloped, more permanent ones) and determined 254 vascular plant species within these ecosystems, as well as plant functional traits and nearest neighbor distances to other kettle holes.Differences in alpha and beta diversity between steep permanent compared with ephemeral flat kettle holes were mainly explained by species sorting and niche processes and mass effect processes in ephemeral flat kettle holes. The plant-community composition as well as the community trait distribution in terms of life span, breeding system, dispersal ability, and longevity of seed banks significantly differed between the two habitat types. Flat ephemeral kettle holes held a higher percentage of non-perennial plants with a more persistent seed bank, less obligate outbreeders and more species with seed dispersal abilities via animal vectors compared with steep-sloped, more permanent kettle holes that had a higher percentage of wind-dispersed species. In the flat kettle holes, plant-species richness was negatively correlated with the degree of isolation, whereas no such pattern was found for the permanent kettle holes.Synthesis: Environment acts as filter shaping plant diversity (alpha and beta) and plant-community trait distribution between steep permanent compared with ephemeral flat kettle holes supporting species sorting and niche mechanisms as expected, but we identified a mass effect in ephemeral kettle holes only. Flat ephemeral kettle holes can be regarded as meta-ecosystems that strongly depend on seed dispersal and recruitment from a seed bank, whereas neighboring permanent kettle holes have a more stable local species diversity.
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.