Biology subjects

Fronhofer, E. A.

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

At least 19 recordsLinked to original sources

bioRxiv2026

Warming-induced switches in dominance are built into intraguild predation systems

Warming affects food webs globally. In the iconic intraguild predation food web module consisting of a basal resource, a specialist consumer, and an omnivorous predator, resource enrichment can favor the predator by increasing the relative importance of intraguild predation compared to resource competition. Here, we integrate empirically established thermal scaling relationships into a model of intraguild predation. We show that warming can shift the power balance between consumer and predator and affect invasion and equilibrium outcomes by inducing changes to resource enrichment - without any differences in thermal optima between species. The nature of these shifts depends on the thermal scaling of resource self-regulation and the strength of resource top-down regulation. We also test the capacity of several generic early warning signals to predict these shifts and find variance-based indicators to be more reliable than autocorrelation-based ones. Our results have implications for predictive food web ecology and biocontrol applications under global change.

ecology↗

bioRxiv2026

Nutrient heterogeneity emerges from dynamical abiotic-biotic feedback in a spatially explicit plant-herbivore occupancy model

Spatial heterogeneity of abiotic resources is essential for species coexistence. Ecological theory often assumes predefined heterogeneity of resources that constrains community dynamics, but the recent developments of meta-ecosystem ecology and zoogeochemistry highlight nutrient patterns could result from the interactions between the activities and movements of organisms and their abiotic environment. Here we investigate the mechanisms by which biotic-abiotic feedbacks could generate nutrient spatial heterogeneity in a simple plant-herbivore occupancy model where populations forage, recycle, and disperse in a homogenous landscape. By systematically varying organisms ranges of foraging and dispersal, and recycling levels, we found that limited dispersal of plants plays a key role on the emergence of nutrient patchiness by favoring small clusters of vegetation that shape their environment through consumption and recycling. However, herbivores could also create nutrient spatial heterogeneity when large foraging and dispersal ranges, and high recycling, allow them to efficiently track plant hot spots and to increase population persistence. Unexpectedly, strong aggregation of herbivore populations did not necessarily result in nutrient clustering. Rather than via recycling, herbivores mainly affected nutrient distribution indirectly, through their top-down impact on plant distribution. When evenly spread in the landscape, herbivore populations with large foraging ranges created areas of strong herbivory pressure unfavorable to plant colonization where nutrient can accumulate. These results can help understand the dynamical feedback between biota and abiotic resources. In a context where human activities alter both nutrient distribution and species abundances, a better understanding of this biotic-abiotic feedback will be key to anticipate the response of ecosystems to current perturbations.

ecology↗

bioRxiv2025

Experimental Evolution of the Thermal Performance Curve

The thermal performance curve (TPC) of an organism captures how population growth depends on temperature. When populations experience increased temperatures, such as during global climate change, one prediction is that their TPC can evolve to accommodate the new environmental temperature. Although studies on TPC evolution have mostly focused on modifications in population growth rates, TPC evolution can be strongly trait-dependent and require a multi-trait analysis. Thus, if and how the entire TPC across a multitude of traits evolves to change its shape in response to increased temperatures remains debated. Here, we empirically tested how the TPCs of multiple demographic, life-history and movement traits can evolve by selecting four freshwater protist species at increased temperatures starting from clonal populations. After one year of selection, populations showed a signature of evolutionary responses to the highest selection temperatures in different traits depending on the species. Particularly, we found consistent evolutionary reductions in body size in the three species having the largest cells and evolved changes in movement behaviour in all species. In contrast, we overall observed little modifications in population growth rate and in the corresponding TPC shape. These results suggest that adaptation, via evolution of TPCs, might involve the concurrent evolution of several traits. However, this may be species-specific and difficult from de-novo mutation alone, suggesting that natural populations that do not have sufficient standing genetic variation might have to be reliant on other means of mitigating the effects of climate change, such as dispersal.

evolutionary biology↗

bioRxiv2025

From proteins to species ranges: a framework for understanding thermal adaptation during range expansions

Species distributions are governed by both ecological and evolutionary processes. Traditionally, ecological factors have been the primary focus of species distribution studies, but recent work emphasizes the importance of rapid evolution through local adaptation. Here, we focus on adaptation to changing temperatures, which is one of the central challenges populations face today. Importantly, thermal adaptation may be affected by the underlying thermodynamics. Despite many existing models in the fields of thermal biology and spatial evolutionary ecology, there is little integrative theory. However, understanding and modelling the thermodynamic constraints on thermal adaptation is likely essential for more nuanced predictions of the impacts of climate change. By integrating molecular mechanisms and population dynamics in a unified modelling framework, we here study how temperature-dependent processes at the protein level influence the macroecological patterns of range expansions. Our results highlight the importance of the microscopic processes underlying thermal adaptation for capturing the evolutionary ecology of range expansions. Specifically, the molecular bases of thermal adaptation define how and how fast thermal performance can evolve, which determines range expansion speeds. In general, our framework predicts that adaptation to warmer temperatures will be easier than adaptation to cold. Our study underscores the necessity for more interdisciplinary work, combining molecular mechanisms with population dynamics in space in order to improve climate change modeling, enhance prediction accuracy and provide better information for management and conservation of natural populations. Significance StatementAs global temperatures shift, species must adapt to new climates, but how molecular changes scale up to influence population- and ecosystem-level patterns is poorly understood. Here, we link mutations affecting protein stability and enzyme activity to species abilities to expand along temperature gradients. Our models show that adaptation is faster at warmer temperatures and more constrained in the cold, reflecting how mutations shape protein function. Thermodynamic effects amplify the impact of beneficial mutations at higher temperatures, potentially accelerating evolutionary responses. By connecting molecular biophysics to population dynamics and range expansion, this work provides a cross-scale framework for predicting how organisms respond to warming environments.

evolutionary biology↗

bioRxiv2024

Dispersal evolution can only rescue a limited set of species from climate change

Anthropogenic climate change threatens biodiversity on Earth. In response, species can adapt evolutionarily to changing environments or shift their ranges via dispersal. However, dispersal itself can evolve on ecological timescales. We explore theoretically how dispersal evolution modulates the response of metacommunities to climate change. We find that this response depends on the environmental conditions prior to climate change. Variable environments harbour few, dispersive species that are likely to survive climate change by shifting their ranges with their evolved dispersal abilities. Stable environments house many, less dispersive species. Their survival during climate change is less likely, as they can evolve robust, low dispersal traits that prevent range shifts. We identify a limited set of scenarios in which contemporary dispersal evolution can rescue species from climate change, highlighting the importance of species evolutionary histories and evolutionary rates, as determined by their genotype-phenotype maps, for their responses to rapid environmental change.

ecology↗

bioRxiv2024

Co-evolution of host dispersal and parasite virulence in complex landscapes.

Spatial network structure impacts the ecological and evolutionary dynamics of species interactions. Previous work on host-parasite systems has shown that parasite virulence is driven by dispersal rates and spatial structure, assuming that dispersal is an ecologically fixed parameter. However, dispersal is also a trait under selection and can evolve. In this context, we develop an individual-based eco-evolutionary model, in which both parasite virulence and host dispersal can evolve in representative terrestrial (random-geometric graphs; RGGs) and riverine aquatic (optimal channel networks; OCNs) landscapes. We find that in riverine aquatic landscapes, evolutionarily stable (ES) dispersal rates are lower and ES virulence is greater relative to terrestrial landscapes when dispersal mortality is low. When dispersal mortality is high, both dispersal and virulence evolve to lower values in both landscape types. Diverging co-evolutionary patterns between landscapes are explained by differences in network topology. Specifically, the highly heterogeneous degree distribution in riverine aquatic landscapes 1) leads to low parasite relatedness allowing for the evolution of greater virulence and 2) leads to spatial heterogeneity in host densities that constrains the evolution of dispersal to lower values. Our work highlights the importance of considering the concurrent and co-evolution of dispersal when studying trait evolution in complex landscapes.

evolutionary biology↗

bioRxiv2024

Perceived and observed biases within scientific communities: a case study in movement ecology

Who conducts biological research, where, and how the results are disseminated varies among geographies and identities. Identifying and documenting these forms of bias by research communities is a critical first step towards addressing them. We documented perceived and observed biases in movement ecology. Movement ecology is a rapidly expanding sub-discipline of biology, which is strongly underpinned by fieldwork and technology use. First, we surveyed attendees of an international conference, and discussed the results at the conference (comparing uninformed vs informed perceived bias). Although most researchers identified as bias-aware, only a subset of biases were discussed in conversation. Next, by considering author affiliations from publications in the journal Movement Ecology, we found among-country discrepancies between the country of the authors affiliation and study site location related to national economics. At the within-country scale, we found that race-gender identities of postgraduate biology researchers in the USA differed from national demographics. We discuss the role of potential specific causes for the emergence of bias in the sub-discipline, e.g. parachute-science or accessibility to fieldwork. Undertaking data-driven analysis of bias within research sub-disciplines can help identify specific barriers and first steps towards the inclusion of a greater diversity of participants in the scientific process.

ecology↗

bioRxiv2023

Landscape structure drives eco-evolution in host-parasite systems.

Spatial network structure of biological systems drives ecology and evolution by distributing organisms and their genes. The ubiquitous host-parasite systems are no exception. However, past work has largely ignored relevant spatial complexity, hampering the translation of theoretical predictions to real ecosystems. Thus, we develop an eco-evolutionary metapopulation model of host-parasite dynamics where hosts and parasites disperse through realistically complex spatial networks representing major biomes: riverine aquatic and terrestrial. We generate the testable prediction that parasite virulence, or how parasites harm their hosts, is unimodal with dispersal and can reach greater values in aquatic landscapes but saturates to lower values in terrestrial systems. Moreover, we show that kin selection drives virulence evolution. Spatial networks generate characteristic patterns of parasite relatedness which drive differential virulence evolution. Finally, we show that accounting for virulence evolution allows us to predict the distribution of key epidemiological variables (e.g., parasite extinction risks) within spatial networks.

evolutionary biology↗

bioRxiv2023

A gene-regulatory network model for density-dependent and sex-biased dispersal evolution during range expansions.

Dispersal is key to understanding ecological and evolutionary dynamics. Dispersal may itself evolve and exhibit phenotypic plasticity. Specifically, organisms may modulate their dispersal rates in response to the density of their conspecifics (density-dependent dispersal) and their own sex (sex-biased dispersal). While optimal dispersal plastic responses have been derived from first principles, the genetic and molecular basis of dispersal plasticity has not been modelled. An understanding of the genetic architecture of dispersal plasticity is especially relevant for understanding dispersal evolution during rapidly changing spatial ecological conditions such as range expansions. In this context, we develop an individual-based metapopulation model of the evolution of density-dependent and sex-biased dispersal during range expansions. We represent the dispersal trait as a gene-regulatory network (GRN), which can take population density and an individuals sex as an input and analyse emergent context- and condition-dependent dispersal responses. We compare dispersal evolution and ecological dynamics in this GRN model to a standard reaction norm (RN) approach under equilibrium metapopulation conditions and during range expansions. We find that under equilibrium metapopulation conditions, the GRN model produces emergent densitydependent and sex-biased dispersal plastic response shapes that match the theoretical expectation of the RN model. However, during range expansion, when mutation effects are large enough, the GRN model leads to faster range expansion because GRNs can maintain higher adaptive potential. Our results imply that, in order to understand eco-evolutionary dynamics in contemporary time, the genetic architecture of traits must be taken into account.

evolutionary biology↗

bioRxiv2022

Evolution of thermal performance curves: a meta-analysis of selection experiments

Temperatures are increasing due to global changes, putting biodiversity at risk. Organisms are faced with a limited set of options to cope with this situation: adapt, disperse or die. We here focus on the first possibility, more specifically, on evolutionary adaptations to temperature. Ectotherms are usually characterized by a hump-shaped relationship between fitness and temperature, a non-linear reaction norm that is referred to as thermal performance curve (TPC). To understand and predict impacts of global change, we need to know whether and how such TPCs evolve. Therefore, we performed a systematic literature search and a statistical meta-analysis focusing on experimental evolution and artificial selection studies. This focus allows us to directly quantify relative fitness responses to temperature selection by calculating fitness differences between TPCs from ancestral and derived populations after thermal selection. Out of 7561 publications screened, we found 47 studies corresponding to our search criteria representing taxa across the tree of life, from bacteria, to plants and vertebrates. We show that, independently of species identity, the studies we found report a positive response to temperature selection. Considering entire TPC shapes, adaptation to higher temperatures traded off with fitness at lower temperatures, leading to niche shifts. Effects were generally stronger in unicellular organisms. By contrast, we do not find statistical support for the often discussed "Hotter is better" hypothesis. While our meta-analysis provides evidence for adaptive potential of TPCs across organisms, it also highlights that more experimental work is needed, especially for under-represented taxa, such as plants and non-model systems.

evolutionary biology↗

bioRxiv2022

Predicting evolution in experimental range expansions of an aquatic model system

Predicting range expansion dynamics is a challenge for both fundamental and applied research in conservation and global change biology. However, if ecological and evolutionary processes occur on the same time scale, predictions are challenging to make. Combining experimental evolution and mathematical modelling, we assessed the predictability of independent realisations of range expansions in a laboratory model system, the freshwater protozoan Paramecium caudatum. We followed ecological dynamics and evolutionary change in range core and front populations in the experiment. These settings were recreated in a predictive mathematical model, parametrized with dispersal and growth data of the of the 20 founder strains in the experiment. We find that short-term evolution was driven by selection for increased dispersal at the front and general selection for higher growth rates in all treatments. There was a good quantitative match of predicted and observed trait changes. Phenotypic divergence was mirrored by a complete genotypic divergence, indicating the highly repeatable fixation of strains that also were the most likely winners in our model. Long-term evolution in the experimental range front lines resulted in the emergence of a dispersal syndrome, namely a competition - colonisation trade-off. Altogether, both model and experiment highlight the importance of dispersal evolution as a driver of range expansions. Our study suggests that evolution at range fronts may follow predictable trajectories, at least for simple scenarios, and that predicting these dynamics may be possible from knowledge of few key parameters.

evolutionary biology↗

bioRxiv2021

Genetic architecture of dispersal and local adaptation drives accelerating range expansions

Contemporary evolution has the potential to significantly alter biotic responses to global change, including range expansion dynamics and biological invasions. However, predictive models often make highly simplifying assumptions about the genetic architecture underlying relevant traits. This can be problematic since genetic architecture defines evolvability, that is, evolutionary rates, and higher order evolutionary processes, which determine whether evolution will be able to keep up with environmental change or not. Therefore, we here study the impact of the genetic architecture of dispersal and local adaptation, two central traits of high relevance for range expansion dynamics, on the speed and variability of range expansions into an environmental gradient, such as temperature. In our theoretical model we assume that dispersal and local adaptation traits result from the products of two non-interacting gene-regulatory networks (GRNs). We compare our model to simpler quantitative genetics models and show that in the GRN model, range expansions are accelerated, faster and more variable. Increased variability implies that these evolutionary changes reduce predictability. We further find that acceleration in the GRN model is primarily driven by an increase in the rate of local adaptation to novel habitats which results from greater sensitivity to mutation (decreased robustness) and increased gene expression. Our results highlight how processes at microscopic scales, here, within genomes, can impact the predictions of large scale, macroscopic phenomena, such as range expansions, by modulating the rate of evolution.

evolutionary biology↗

bioRxiv2021

Landscape structure and dispersal rate drive large scale catastrophic shifts in spatially explicit metapopulations

Even when environments deteriorate gradually, ecosystems may shift abruptly from one state to another. Such catastrophic shifts are difficult to predict and reverse (hysteresis). While well studied in simplified contexts, we lack a general understanding of how catastrophic shifts spread in realistic spatial contexts. For different types of landscape structure, including typical terrestrial modular and riverine dendritic networks, we here investigate landscape-scale stability in metapopulations made of bistable patches. We find that such metapopulations usually exhibit large scale catastrophic shifts and hysteresis, and that the properties of these shifts depend strongly on metapopulation spatial structure and dispersal rate: intermediate dispersal rates and a riverine spatial structure can largely reduce hysteresis size. Interestingly, our study suggests that large-scale restoration is easier with spatially clustered restoration efforts and in populations characterized by an intermediate dispersal rate.

ecology↗

bioRxiv2021

Fitting deterministic population models tostochastic data: from trajectory matching tostate-space models

Population and community ecology traditionally has a very strong theoretical foundation with well-known dynamical models, such as the logistic and its variations, and many modification of the classical Lotka-Volterra predator-prey and interspecific competition models. More and more, these classical models are being confronted with data via fitting to empirical time series for purposes of projections or for estimating model parameters of interest. However, using statistical models to fit theoretical models to data is far from trivial, especially for time series data where subsequent measurements are not independent. This raises the question of whether statistical inferences using pure observation error models, such as simple (non-)linear regressions, are biased, and whether more elaborate process error models or state-space models have to be used to address this complexity. In order to help empiricists, especially researchers working with experimental laboratory populations in micro- and mesocosms, make informed decisions about the statistical formalism to use, we here compare different error structures one could use when fitting classical deterministic ODE models to empirical data. We consider a large range of biological scenarios and theoretical models, from single species to community dynamics and trophic interactions. In order to compare the performance of different error structure models, we use both realistically simulated data and empirical data from microcosms in a Bayesian framework. We find that many model parameters can be estimated precisely with an appropriate choice of error structure using pure observation error or state-space models, if observation errors are not too high. However, Allee effect models are typically hard to identify and state-space models should be preferred when model complexity increases. Our work shows that, at least in the context of low environmental stochasticity and high quality observations, deterministic models can be used to describe stochastic population dynamics that include process variability and observation error. We discuss when more complex state-space model formulations may be required for obtaining accurate parameter estimates. Finally, we provide a comprehensive tutorial for fitting these models in R. Open researchCode for stochastic individual-based simulations is available from https://doi.org/10.5281/zenodo.5500442. A tutorial for fitting ODE models to time series data in R is presented in the Supplementary Information and is also available online https://github.com/benjamin-rosenbaum/fitting deterministic population models. Data (Fronhofer et al., 2020) will be provided via GitHub and Zenodo.

ecology↗

bioRxiv2021

Selection on growth rate and local adaptation drive genomic adaptation during experimental range expansions in the protist Tetrahymena thermophila

O_LIPopulations that expand their range can undergo rapid evolutionary adaptation of life-history traits, dispersal behaviour, and adaptation to the local environment. Such adaptation may be aided or hindered by sexual reproduction, depending on the context. C_LIO_LIHowever, few studies have investigated the genomic causes and consequences or genetic architecture of such adaptation during range expansions. C_LIO_LIWe here studied genomic adaptation during experimental range expansions of the protist Tetrahymena thermophila in landscapes with a uniform environment or a pH-gradient. Specifically, we investigated two aspects of genomic adaptation during range expansion. Firstly, we investigated the genetic architecture of adaptation in terms of the underlying numbers of allele frequency changes from standing genetic variation and de novo variants. We focused on how sexual reproduction may alter this genetic architecture. Secondly, identified genes subject to selection caused by the expanding range itself, and directional selection due to the presence or absence of the pH-gradient. We focused this analysis on alleles with large frequency changes that occurred in parallel in more than one population to identify the most likely candidate targets of selection. C_LIO_LIWe found that sexual reproduction altered genetic architecture both in terms of de novo variants and standing genetic variation. However, sexual reproduction affected allele frequency changes in standing genetic variation only in the absence of long-distance gene flow. Adaptation to the range expansion affected genes involved in cell divisions and DNA repair, whereas adaptation to the pH-gradient additionally affected genes involved in ion balance, and oxidoreductase reactions. These genetic changes may result from selection on growth and adaptation to low pH. C_LIO_LIOur results suggest that the evolution of life-history and the adaptation to the local environment has a genetic basis during our range expansion experiment. In the absence of gene flow, sexual reproduction may have aided genetic adaptation. Gene flow may have swamped expanding populations with maladapted alleles, thus reducing the extent of evolutionary adaptation during range expansion. Sexual reproduction also altered the genetic architecture of our evolving populations via de novo variants, possibly by purging deleterious mutations or by revealing fitness benefits of rare genetic variants. C_LI

evolutionary biology↗

bioRxiv2020

Dispersal rate and riverine network connectivity shape the genetic diversity of freshwater amphipod metapopulations

Theory predicts that the distribution of genetic diversity in a landscape is strongly dependent on the connectivity of the metapopulation and the dispersal of individuals between patches. However, the influence of explicit spatial configurations such as dendritic landscapes on the genetic diversity and structure of metapopulations is still understudied, and theoretical corroborations of empirical patterns are largely lacking. Here, we used real-world microsatellite data and stochastic simulations of two metapopulations of freshwater amphipods in a 28,000 km2 riverine network to study the influence of spatial connectivity and dispersal strategies on their spatial genetic diversity and structure. We found a significant imprint of the riverine network connectivity on the genetic diversity of both amphipod species. Data from 95 sites showed that allelic richness and observed heterozygosity significantly increased towards more central nodes of the network. In simulation models, dispersal rate was suggested to be the key factor explaining the empirically observed distribution of genetic diversity. Contrary to often-claimed expectations, however, the relevance of directionality of dispersal was only minor. Surprisingly, also the consideration of site-specific carrying capacities, for example by assuming a direct dependency of population size with local river size, substantially decreased the model fit to empirical data. This highlights that directional dispersal and the spatial arrangement of population sizes may have a smaller relevance in shaping population genetic diversity of riverine organisms than previously thought, and that dispersal along the river network is the single-most important determinant of population genetic diversity.

ecology↗

bioRxiv2020

Spatial distribution of local patch extinctions drives recovery dynamics in metacommunities

Human activities lead more and more to the disturbance of plant and animal communities with local extinctions as a consequence. While these negative effects are clearly visible at a local scale, it is less clear how such local patch extinctions affect regional processes, such as metacommunity dynamics and the distribution of diversity in space. Since local extinctions may not be isolated events in space but rather cluster together, it is crucial to investigate their effects in a spatially explicit framework. Here, we use experimental microcosms and numerical simulations to understand the relationship between local patch extinctions and metacommunity dynamics. More specifically, we investigate the effects of the amount and spatial autocorrelation of extinctions in a full factorial design. Experimentally, we found that local patch extinctions increased inter-patch ({beta}-) diversity by creating differences between perturbed and unperturbed patches and at the same time increased local (-) diversity by delaying the competitive exclusion of inferior competitors. Most importantly, recolonization dynamics depended more strongly on the spatial distribution of patch extinctions than on the amount of extinctions per se. Clustered local patch extinctions reduced mixing between perturbed and unperturbed patches which led to slower recovery, lower -diversity in unperturbed patches and higher {beta}-diversity. Results from a metacommunity model matched the experimental observations qualitatively when the model included ranked competitive interactions, giving a hint at the underlying mechanisms. Our results highlight that local patch extinctions can increase the diversity within and between communities, that the strength of these effects depends on the spatial distribution of extinctions and that the effects of local patch extinctions can spread regionally, throughout a landscape. These findings are highly relevant for conservation and management of spatially structured communities under global change.

ecology↗

bioRxiv2020

Host-parasite dynamics set the ecological theatre for the evolution of state- and context-dependent dispersal in hosts

While host-parasite interactions are ubiquitous, the large scale consequences of parasite infections are mainly driven by the spatial context. One trait of pivotal importance for the eco-evolutionary dynamics of such metapopulations is the spatial behaviour of hosts, that is, their dispersal. It is well established that dispersal is not a random process, rather dispersal is informed and may depend on internal and external factors. In host-parasite metapopulations, dispersal may be a function of a hosts infection state, but also of the local context, such as host density or parasite prevalence. Using a dynamical host-parasite metapopulation model, we explore whether host dispersal evolves to be state- and context-dependent and what shapes the evolutionarily stable dispersal reaction norms have. We show that state-dependent dispersal readily evolves in the sense that hosts disperse more when infected. This dispersal bias evolves due to kin selection which is consistent with previous studies. Most importantly, we show that prevalence-dependent dispersal evolves, especially when virulence is high and epidemiological dynamics have predictable signatures. The observed evolutionary outcome, a negatively prevalence-dependent dispersal reaction norm for susceptible hosts, seems counter-intuitive at first. However, our results can be readily explained by the emergent epidemiological dynamics, especially their spatial and temporal correlation patterns. Finally, we show that context-dependency in dispersal may rely on both, prevalence, but also host density cues. Our work provides new insights into the evolution of complex dispersal phenotypes in host-parasite metapopulations as well as on associated feedbacks between ecological dynamics and evolutionary change.

evolutionary biology↗