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Fronhofer, E. A.

Publications and source records attributed to Fronhofer, E. A..

35 records · Page 2Linked to original sources
bioRxiv2020

Generation and application of river network analogues for use in ecology and evolution

O_LISeveral key processes in freshwater ecology and evolution are governed by the connectivity inherent to dendritic river networks. These networks have extensively been analyzed from a geomorphological and hydrological viewpoint, yet network structures classically used in modelling have only been partially representative of the structure of real river basins, and have often failed to capture well known scaling features of real river networks. Pioneering work has identified optimal channel networks (OCNs) as spanning trees that reproduce all scaling features characteristic of real, natural stream networks worldwide. While these networks have been used to generate landscapes for studies on metapopulations, biodiversity and epidemiology, their generation has not been generally accessible. C_LIO_LIGiven the increasing interest in dendritic riverine networks by ecologists and evolutionary biologists, we here present a method to generate OCNs and, to facilitate its application, we also provide the R-package OCNet. Owing to the random search process that generates OCNs, multiple network replicas spanning the same surface can be built, allowing one to perform computational experiments whose results do not depend on the particular shape of a single river network. The OCN construct also enables the generation of elevational gradients derived from the optimal network configuration, which can constitute three-dimensional landscapes for spatial studies in both terrestrial and freshwater realms. Moreover, the OCNet package provides functions that aggregate the OCN into an arbitrary number of nodes, calculate several metrics and descriptors of river networks, and draw relevant features of the network. C_LIO_LIWe describe the main functionalities of the package and present how it can be integrated into other R-packages commonly used in spatial ecology. Moreover, we exemplify the generation of OCNs and discuss an application to a metapopulation model for an invasive riverine species. C_LIO_LIIn conclusion, OCNet provides a powerful tool to generate and use realistic river network analogues for various applications. It thereby allows the design of spatially realistic studies in increasingly impacted ecosystems, and enhances our knowledge on spatial processes in freshwater ecology in general. C_LI

ecology↗
bioRxiv2020

Trade-off between virulence and dispersal drives parasite evolution at experimental invasion front

Eco-evolutionary processes may play an important role in the spatial spread of infectious disease. Current theory predicts more exploitative parasites to evolve in highly connected populations or at the front of spreading epidemics. However, many parasites rely on host dispersal to reach new populations. This may lead to conflict between local transmission and global spread, possibly counteracting selection for higher virulence. Here, we used the freshwater host Paramecium caudatum and its bacterial parasite Holospora undulata to investigate parasite evolution under an experimental range expansion scenario with natural host dispersal. We find that parasites evolving at experimental range fronts favoured higher dispersal rates of infected hosts than did parasites evolving in core populations. Front parasites further showed lower levels of virulence (host division and survival) and delayed development of infection, consistent with parameter estimates from an epidemiological model that we fitted on experimental time-series data. This combined evidence suggests an evolutionary trade-off between virulence and host-mediated dispersal, with a concomitant reduction in the investment into horizontal transmission. Our experiment illustrates how parasite evolution can be shaped by divergent selection encountered in different segments of an epidemic wave. Such an interplay between demography and spatial selection has important implications for the understanding and management of emerging diseases, and, more generally, for biological invasions and other non-equilibrium scenarios of spreading populations. SIGNIFICANCE STATEMENTWhat drives parasite evolution in spatially expanding epidemics? Many parasites require dispersal of infected hosts to reach new patches, and this may produce specific adaptations enhancing spatial spread. We performed experimental range expansions in an aquatic model system, with natural dispersal of infected hosts. Parasites from experimental range fronts were less virulent and interfered less with host dispersal, but also invested less in horizontal transmission than parasites from the range core. Thus, dispersal adaptation at the front may come at a cost of reduced horizontal transmission, a trade-off rarely considered in theoretical models on parasite virulence evolution. These results have important implications in the context of emerging diseases, and for parasite evolution during biological invasions or other spatial non-equilibrium scenarios.

evolutionary biology↗
bioRxiv2020

Travelling with a parasite: the evolution of resistance and dispersal syndrome during experimental range expansion

Rapid evolutionary change during range expansions can lead to diverging range core and front populations, with the emergence of dispersal syndromes (coupled responses in dispersal and life-history traits). Besides intraspecific effects, range expansions may be impacted by interspecific interactions such as parasitism. Yet, despite the potentially large impact of parasites imposing additional selective pressures on the host, their role on range expansions remains largely unexplored. Using microcosm populations of the ciliate Paramecium caudatum and its bacterial parasite Holospora undulata, we studied experimental range expansions under parasite presence or absence. We found that the interaction of range expansion and parasite treatments affected the evolution of host dispersal syndromes. Namely, front populations showed different associations of population growth parameters and swimming behaviours than core populations, indicating divergent evolution. Parasitism reshaped trait associations, with hosts evolved in the presence of the parasite exhibiting overall increased resistance and reduced dispersal. Nonetheless, when comparing infected range core and front populations, we found a positive association, suggesting joint evolution of resistance and dispersal at the front. We conclude that host-parasite interactions during range expansions can change evolutionary trajectories; this in turn may feed back on the ecological dynamics of the range expansion and parasite epidemics.

evolutionary biology↗
bioRxiv2019

Sex and gene flow modulate evolution during rangeexpansions in the protist Tetrahymena thermophila

At species range edges, individuals often face novel environmental conditions that may limit range expansion until populations adapt. The potential to adapt depends on genetic variation upon which selection can act. However, populations at species range edges are often genetically depauperated. One mechanism to increase genetic variation is to reshuffle existing variation through sex. During range expansions, sex can, however, act as a double-edged sword. The gene swamping hypothesis predicts that for populations expanding along an abiotic gradient, sex can hinder adaptation if asymmetric dispersal leads to numerous maladapted dispersers from the range core swamping the range edge. In this study, we experimentally tested the gene swamping hypothesis by performing replicated range expansions in landscapes with or without an abiotic pH-gradient, using the ciliate Tetrahymena thermophila, while simultaneously manipulating the occurrence of gene flow and sex. We show that sex accelerated evolution of local adaptation in the absence of gene flow, but hindered it in the presence of gene flow. The effect of sex, however, was independent of the pH-gradient, indicating that not only abiotic gradients but also the biotic gradient in population density leads to gene swamping. Overall, our results show that gene swamping can affect adaptation in life-history strategies.

evolutionary biology↗
bioRxiv2019

Interaction of pH stress and demography leads to convergent evolution in the protist Tetrahymena thermophila

Abiotic stress is a major force of selection that organisms are constantly facing. While the evolutionary effects of various stressors have been broadly studied, it is only more recently that the relevance of interactions between evolution and underlying ecological conditions, that is, eco-evolutionary feedbacks, have been highlighted. Here, we experimentally investigated how populations adapt to pH-stress under high population densities. Using the protist species Tetrahymena thermophila, we studied how four different genotypes evolved in response to stressfully low pH conditions and high population densities. We found that genotypes underwent evolutionary changes, some shifting up and others shifting down their intrinsic rates of increase (r0). Overall, evolution at low pH led to the convergence of r0 and intraspecific competitive ability () across the four genotypes. Given the strong correlation between r0 and , we argue that this convergence was a consequence of selection for increased density-dependent fitness at low pH under the experienced high density conditions. Increased density-dependent fitness was either attained through increase in r0, or decrease of , depending on the genetic background. In conclusion, we show that demography can influence the direction of evolution under abiotic stress.

evolutionary biology↗
bioRxiv2019

Coevolution alters predator life history traits, behavior and morphology in experimental microbial communities

Predator-prey interactions are key for the dynamics of many ecosystems. An increasing body of evidence suggests that rapid evolution and co-evolution can alter these interactions, with important ecological implications, by acting on traits determining fitness, including reproduction, anti-predatory defense and foraging efficiency. However, most studies to date have focused only on evolution in the prey species, and the predator traits in (co-)evolving systems remain poorly understood. Here we investigated changes in predator traits after ~600 generations in a predator-prey (ciliate-bacteria) evolutionary experiment. Predators independently evolved on seven different prey species, allowing generalization of the predators evolutionary response. We used highly resolved automated image analysis to quantify changes in predator life history, morphology and behavior. Consistent with previous studies, we found that prey evolution impaired growth of the predator. In contrast, predator evolution did not cause a clear increase in fitness when feeding on ancestral prey. However, predator evolution affected morphology and behavior, increasing size, speed and directionality of movement, which have all been linked to higher prey search efficiency. These results show that in (co-)evolving systems, predator adaptation can occur in traits relevant to offense level without translating into an increased ability of the predator to grow on the ancestral prey type.

evolutionary biology↗
bioRxiv2019

Metaecosystem dynamics drive community composition in experimental multi-layered spatial networks

Cross-ecosystem subsidies are studied with a focus on resource exchange at local ecosystem boundaries. This perspective ignores regional dynamics that can emerge via constraints imposed by the landscape, potentially leading to spatially-dependent effects of subsidies and spatial feedbacks. Using miniaturized landscape analogues of river dendritic and terrestrial lattice spatial networks, we manipulated and studied resource exchange between the two whole networks. We found that community composition in dendritic networks depended on the resource pulse from the lattice network, with the strength of this effect declining in larger downstream patches. In turn, this spatially-dependent effect imposed constraints on the lattice network with populations in that network reaching higher densities when connected to more central patches in the dendritic network. Consequently, localized cross-ecosystem fluxes, and their respective effects on recipient ecosystems, must be studied in a perspective taking into account the explicit spatial configuration of the landscape.\n\nStatement of authorshipEH, IG, EAF and FA designed the research; EH conducted the lab experiment with support from IG, EAF and FA, processed the experimental data with methodological developments from IG, and carried out the analysis of experimental data; all authors participated in results interpretation; EH wrote the first draft of the manuscript; All authors significantly contributed to further manuscript revisions.

ecology↗
bioRxiv2019

Assessing different components of biodiversity across a river network using eDNA

O_LIAssessing individual components of biodiversity, such as local or regional taxon richness, and differences in community composition is a long-standing challenge in ecology. It is especially relevant in spatially structured and diverse ecosystems. Environmental DNA (eDNA) has been suggested as a novel technique to accurately measure biodiversity. However, we do not yet fully understand the comparability of eDNA-based assessments to previously used approaches. C_LIO_LIWe sampled may-, stone-, and caddisfly genera with contemporary eDNA and kicknet methods at 61 sites distributed over a large river network, allowing a comparison of various diversity measures from the catchment to site levels and providing insights into how these measures relate to network properties. We extended our survey data with historical records of total diversity at the catchment level. C_LIO_LIAt the catchment scale, eDNA and kicknet detected similar proportions of the overall and cumulative historically documented species richness (gamma diversity), namely 42% and 46%, respectively. We further found a good overlap (62%) between the two contemporary methods at the regional scale. C_LIO_LIAt the local scale, we found highly congruent values of local taxon richness (alpha diversity) between eDNA and kicknet. Richness of eDNA was positively related with discharge, a descriptor of network position, while kicknet was not. C_LIO_LIBeta diversity between sites was similar for the two contemporary methods. Contrary to our expectation, however, beta diversity was driven by species replacement and not by nestedness. C_LIO_LIAlthough optimization of eDNA approaches is still needed, our results indicate that this novel technique can capture extensive aspects of gamma diversity, proving its potential utility as a new tool for large sampling campaigns across hitherto understudied complete river catchments, requiring less time and becoming more cost-efficient than classical approaches. Overall, the richness estimated with the two contemporary methods is similar at both local and regional scale but community composition is differently assessed with the two methods at individual sites and becomes more similar with higher discharge. C_LI

ecology↗
bioRxiv2018

The conflict between adaptation and dispersal for maintaining biodiversity in changing environments

Dispersal and adaptation both allow species to persist in changing environments. Yet, we have limited understanding of how these processes interact to affect species persistence, especially in diverse communities where biotic interactions greatly complicate responses to environmental change. Here we use a stochastic metacommunity model to demonstrate how dispersal and adaptation to environmental change independently and interactively contribute to biodiversity maintenance. Dispersal provides spatial insurance, whereby species persist on the landscape by shifting their distributions to track favourable conditions. In contrast, adaptation allows species to persist by allowing for evolutionary rescue. But, when species both adapt and disperse, dispersal and adaptation do not combine positively to affect biodiversity maintenance, even if they do increase the persistence of individual species. This occurs because faster adapting species evolve to hold onto their initial ranges (i.e. monopolization effects), thus impeding slower adapting species from shifting their ranges and thereby causing extinctions. Importantly, these differences in adaptation speed emerge as the result of competition, which alters population sizes and colonization success. By demonstrating how dispersal and adaptation each independently and interactively contribute to the maintenance of biodiversity, we provide a framework that links the theories of spatial insurance, evolutionary rescue, and monopolization. This highlights the expectation that the maintenance of biodiversity in changing environments depends jointly on rates of dispersal and adaptation, and, critically, the interaction between these processes.\n\nSignificance StatementSpecies can persist when the environment changes by shifting their ranges through dispersal or by adapting to the new conditions that they experience. Thus, we might expect that dispersal and adaptation in combination would increase persistence. Using a simulation model, we show that this may not be the case. Instead, species competition causes dispersal and adaptation to have conflicting contributions to biodiversity maintenance. Dispersal and adaptation each independently increase biodiversity maintenance. But when species both disperse and evolve, faster adapting species persist in their current ranges, preventing others from shifting their ranges to track environmental change. These findings highlight the need to consider ecological and evolutionary processes together, or we risk underestimating how global change will impact biodiversity.

ecology↗
bioRxiv2018

Dispersal syndromes can impact ecosystem functioning in spatially structured freshwater populations

Dispersal can strongly influence ecological and evolutionary dynamics. Besides the direct contribution of dispersal to population dynamics, dispersers often differ in their phenotypic attributes from non-dispersers, which leads to dispersal syndromes. The consequences of such dispersal syndromes have been widely explored at the population and community level, however, to date, ecosystem-level effects remain unclear. Here, we examine whether dispersing and resident individuals of two different aquatic keystone invertebrate species have different contributions to detrital processing, a key function in freshwater ecosystems. Using experimental two-patch systems, we found no difference in leaf consumption rates with dispersal status of the common native species Gammarus fossarum. In Dikerogammarus villosus, however, a Ponto-Caspian species now expanding throughout Europe, dispersers consumed leaf litter at roughly three times the rate of non-dispersers. Furthermore, this put the contribution of dispersing D. villosus to leaf litter processing on par with native G. fossarum, after adjusting for differences in organismal size. Given that leaf litter decomposition is a key function in aquatic ecosystems, and the rapid species turnover in freshwater habitats with range expansions of non-native species, this finding suggests that dispersal syndromes may have important consequences for ecosystem functioning.

ecology↗
bioRxiv2018

The shape of density dependence and the relationship between population growth, intraspecific competition and equilibrium population density

The logistic growth model is one of the most frequently used formalizations of density dependence affecting population growth, persistence and evolution. Ecological and evolutionary theory and applications to understand population change over time often include this model. However, the assumptions and limitations of this popular model are often not well appreciated. Here, we briefly review past use of the logistic growth model and highlight limitations by deriving population growth models from underlying consumer-resource dynamics. We show that the logistic equation likely is not applicable to many biological systems. Rather, density-regulation functions are usually non-linear and may exhibit convex or both concave and convex curvatures depending on the biology of resources and consumers. In simple cases, the dynamics can be fully described by the continuous-time Beverton-Holt model. More complex consumer dynamics show similarities to a Maynard Smith-Slatkin model. Importantly, we show how population-level parameters, such as intrinsic rates of increase and equilibrium population densities are not independent, as often assumed. Rather, they are functions of the same underlying parameters. The commonly assumed positive relationship between equilibrium population density and competitive ability is typically invalid. As a solution, we propose simple and general relationships between intrinsic rates of increase and equilibrium population densities that capture the essence of different consumer-resource systems. Relating population level models to underlying mechanisms allows us to discuss applications to evolutionary outcomes and how these models depend on environmental conditions, like temperature via metabolic scaling. Finally, we use time-series from microbial food chains to fit population growth models and validate theoretical predictions. Our results show that density-regulation functions need to be chosen carefully as their shapes will depend on the study systems biology. Importantly, we provide a mechanistic understanding of relationships between model parameters, which has implications for theory and for formulating biologically sound and empirically testable predictions.

ecology↗
bioRxiv2018

Nonlinear Effects of Intraspecific Competition Alter Landscape-Wide Upscaling of Ecosystem Function

A major focus of ecology is to understand and predict ecosystem function across scales. Many ecosystem functions are only measured at local scales, while their effects occur at a landscape level. Here, we investigate how landscape-scale predictions of ecosystem function depend on intraspecific competition, a fine-scale process. Specifically, we experimentally investigated the effect of intraspecific density of shredding macroinvertebrates on associated leaf litter decomposition, a key function in freshwater ecosystems. Across two species, we found that leaf processing rates declined with increasing density following a power law, likely due to interference competition. To demonstrate consequences of this nonlinearity, we upscaled estimates of leaf litter processing from shredder abundance surveys in 10 replicated headwater streams. In accordance with Jensens inequality, applying density-dependent consumption rates reduced estimates of catchment-scale leaf consumption up to 60-fold versus using density-independent rates. Our work highlights the need for spatially-explicit upscaling which accounts for intraspecific interactions.

ecology↗
bioRxiv2017

Bottom-up and top-down control of dispersal across major organismal groups: a coordinated distributed experiment

Organisms rarely experience a homogeneous environment. Rather, ecological and evolutionary dynamics unfold in spatially structured and fragmented landscapes, with dispersal as the central process linking these dynamics across spatial scales. Because dispersal is a multi-causal and highly plastic life-history trait, finding general drivers that are of importance across species is challenging but highly relevant for ecological forecasting.\n\nWe here tested whether two fundamental ecological forces and main determinants of local population dynamics, top-down and bottom-up control, generally explain dispersal in spatially structured communities. In a coordinated distributed experiment spanning a wide range of actively dispersing organisms, from protozoa to vertebrates, we show that bottom-up control, that is resource limitation, consistently increased dispersal. While top-down control, that is predation risk, was an equally important dispersal driver as bottom-up control, its effect depended on prey and predator space use and whether dispersal occurred on land, in water or in the air: species that routinely use more space than their predators showed increased dispersal in response to predation, specifically in aquatic environments. After establishing these general causes of dispersal, we used a metacommunity model to show that bottom-up and top-down control of dispersal has important consequences for local population fluctuations as well as cascading effects on regional metacommunity dynamics. Context-dependent dispersal reduced local population fluctuations and desynchronized dynamics between communities, two effects that increase population and community stability.\n\nOur study provides unprecedented insights into the generality of the positive resource dependency of dispersal as well as a robust experimental test of current theory predicting that predator-induced dispersal is modulated by prey and predator space use. Our experimental and theoretical work highlights the critical importance of the multi-causal nature of dispersal as well as its cascading effects on regional community dynamics, which are specifically relevant to ecological forecasting.

ecology↗
bioRxiv2017

Population turnover reverses classic island biogeography predictions in river-like landscapes

Statement of authorshipEH, IG, EAF and FA designed the research; IG and EAF designed the model; IG programmed and ran the model, analyzed the simulation data with support from EAF and produced the figures; EH conducted the lab experiment with support from IG, EAF and FA, processed the experimental data with support from IG, and carried out the analysis of experimental data; all authors participated in results interpretation; EH wrote the first draft of the manuscript; All authors significantly contributed to further manuscript revisions. EH and IG contributed equally to this work.

ecology↗
bioRxiv2017

Kin competition as driver of range expansions

With ongoing global change, life is continuously forced to move to novel areas, which leads to dynamically changing species ranges. As dispersal is central to range dynamics, factors promoting fast and distant dispersal are key to understanding and predicting species ranges. During range expansions, genetic variation is depleted at the expanding front. Such conditions should reduce evolutionary potential, while increasing kin competition. Organisms able to recognise relatives may be able to assess increased levels of relatedness at expanding range margins and to increase their dispersal in a plastic manner. Using individual-based simulations and experimental range expansions of a spider mite, we demonstrate that plastic responses to kin structure can be at least as important as evolution in driving range expansion speed. Because recognition of kin or kind is increasingly documented across the tree of life, we anticipate it to be a highly important but neglected driver of range expansions.

ecology↗
bioRxiv2017

Dynamic species classification of microorganisms across time, abiotic and biotic environments - a sliding window approach

1. Technological advances have greatly simplified to take and analyze digital images and videos, and ecologists increasingly use these techniques for trait, behavioral and taxonomic analyses. The development of techniques to automate biological measurements from the environment opens up new possibilities to infer species numbers, observe presence/absence patterns and recognize individuals based on audio-visual information.\n\n2. Streams of quantitative data, such as temporal species abundances, are processed by machine learning (ML) algorithms into meaningful information. Machine learning approaches learn to distinguish classes (e.g., species) from observed quantitative features (phenotypes), and in-turn predict the distinguished classes in subsequent observations. However, in biological systems, the environment changes, often driving phenotypic changes in behaviour and morphology.\n\n3. Here we describe a framework for classifying species under dynamic biotic and abiotic conditions using a novel sliding window approach. We train a random forest classifier on subsets of the data, covering restricted temporal, biotic and abiotic ranges (i.e. windows). We test our approach by applying the classification framework to experimental microbial communities where results were validated against manual classification. Individuals from one to six ciliate species were monitored over hundreds of generations in dozens of different species combinations and over a temperature gradient. We describe the steps of our classification pipeline and systematically explore the effects of the abiotic and biotic environments as well as temporal effects on classification success.\n\n4. Differences in biotic and abiotic conditions caused simplistic classification approaches to be unsuccessful. In contrast, the sliding window approach allowed classification to be highly successful, because phenotypic differences driven by environmental change could be captured in the learning algorithm. Importantly, automatic classification showed comparable success compared to manual identifications.\n\n5. Our framework allows for reliable classification even in dynamic environmental contexts, and may help to improve long-term monitoring of species from environmental samples. It therefore has application in disciplines with automatic enumeration and phenotyping of organisms such as eco-toxicology, ecology and evolutionary ecology, and broad-scale environmental monitoring.

ecology↗
bioRxiv2016

Upstream trophic structure modulates downstream community dynamics via resource subsidies.

In many natural systems, the physical structure of the landscape dictates the flow of resources. Despite mounting evidence that communities dynamics can be indirectly coupled by reciprocal among-ecosystem resource flows, our understanding of how directional resource flows might indirectly link biological communities is limited. We here propose that differences in community structure upstream should lead to different downstream dynamics, even in the absence of dispersal. We report an experimental test of the effect of upstream community structure on downstream community dynamics in a simplified but highly controlled setting, using protist microcosms. We implemented directional flows of resources, without dispersal, from a standard resource pool into upstream communities of contrasting interaction structure and then to further downstream communities of either one or two trophic levels. Our results demonstrate that different types of species interactions in upstream habitats may lead to different population sizes and levels of biomass in these upstream habitats. This, in turn, leads to varying levels of detritus transfer (dead biomass) to the downstream communities, thus influencing their population densities and trophic interactions in predictable ways. Our results suggest that the structure of species interactions in directionally structured ecosystems can be a key mediator of alterations to downstream habitats. Alterations to upstream habitats can thus cascade down to downstream communities, even without dispersal.

ecology↗