Biology subjects

Weissing, F. J.

Publications and source records attributed to Weissing, F. J..

At least 19 recordsLinked to original sources

bioRxiv2026

The evolution of a condition-dependent mutation rate enhances evolvability

Empirical studies have demonstrated that mutation rates may change with individual condition, such as in the case of stress-induced mutagenesis. This has led to the hypothesis that condition-dependent (or "plastic") mutation rates could be selectively favoured, as the increased production of new mutants in times of maladaptation enhances evolvability, the ability to undergo adaptive evolution. However, while empirical evidence for condition-dependent mutation rates is accumulating, theoretical models studying their evolution are lacking. Here, we employ an individual-based simulation approach to examine the evolution of condition-dependent mutation rates in a changing environment. We find that condition-dependent mutation rates consistently evolve when the environment changes at an intermediate pace. Furthermore, populations with condition-dependent mutation rates are substantially better adapted to their (changing) environment. Finally, the evolutionary dynamics of condition-dependent mutation rates are both accelerated and destabilised when the mutation rate is self-referential (i.e., when mutator loci affect their own mutation rate). We conclude that condition-dependent mutation rates (and thus evolvability) can readily evolve in changing environments. Significance statementMutation provides the raw material for evolution. Mutation rates thus tune evolvability, the ability to undergo adaptive evolution: if mutation rates are too low, evolution is impeded; if mutation rates are too high, adaptive traits cannot be maintained. Using a theoretical model, we explore the evolution of plastic mutation rates that systematically depend on the condition of the organism and its environment. An example is stress-induced mutagenesis in bacteria, which is implicated in the evolution of antibiotic resistance. We show that plastic mutation rates readily evolve, providing "well-timed" variation specifically when organisms are poorly adapted. Such plastic mutation rates thus facilitate better adaptation to changing environments, and their evolution provides an example of evolvability itself evolving.

evolutionary biology↗

bioRxiv2025

Sexual selection driven by direct benefits leads to the erosion of direct benefits

Most sexual selection models assume that the evolution of female choosiness is driven by indirect (genetic) benefits, such as the production of more viable offspring or more attractive sons. There is ample empirical evidence that female choosiness can also provide direct (non-genetic) benefits, including access to good territories or paternal care. Yet, theoretical models of direct-benefits sexual selection are scarce. Here, we use individual-based evolutionary simulations to explore the joint evolution of female mating preferences and male ornamentation under sexual selection driven by direct benefits. We find that, within each generation, male ornamentation reliably indicates paternal quality (the direct benefit); females thus benefit from being choosy and readily evolve preferences for male ornamentation. Yet this in turn selects for males to invest resources in ornamentation at the expense of paternal care. Across generations, female selection for ornamented males (driven by the pursuit of direct benefits) thus erodes the very benefit it seeks, leading to population decline and potentially extinction. Our results highlight the complexity and non-intuitive nature of direct-benefits sexual selection.

evolutionary biology↗

bioRxiv2025

Programming alphavirus with IFN-γ overrides the adverse effects of macrophages on oncolytic virotherapy

Interference by tumor-associated macrophages may significantly reduce the efficacy of therapeutic viruses designed to infect cancer cells and activate antitumor T-cells. Using a computational model, we hypothesized that viruses encoding a T cell-stimulating signal, like IFN-{gamma}, could overcome this barrier. We engineered an alphavirus-based replicon expressing IFN-{gamma} and evaluated its effect in various human-derived tumor-immune coculture systems and an in vivo murine model. While alphavirus replicons do not replicate in macrophages, macrophages acted as a barrier, limiting tumor infection in a frequency-dependent but phenotype-independent manner. Nonetheless, T-cell activation occurred even when only a fraction of infected tumor cells expressed IFN-{gamma}, regardless of macrophage presence, frequency, or phenotype. Additionally, viral stimulation drove macrophage-repolarization towards a pro-inflammatory phenotype favoring T-cell activation. These findings highlight a strategy for optimizing virotherapy in macrophage-rich tumors by designing viruses that stimulate T-cell activation, ensuring therapeutic efficacy.

immunology↗

bioRxiv2024

Personality predicts dispersal and settlement in a novel habitat - a mesocosm experiment

Studying the relationship between dispersal tendencies and personality, or dispersal syndromes, under ecologically relevant conditions is challenging, especially in fish. Laboratory studies lack environmental complexity and scale, while field-based approaches are often unfeasible. We here mimicked dispersal events; encompassing all three phases of dispersal (departure, transience, settlement) in a large experimental mesocosm containing a gradient of low- and high-quality breeding sites. Using Passive Integrated Transponder (PIT)-tagged three-spined sticklebacks (Gasterosteus aculeatus), we remotely monitored the movements and behaviours of two groups, each consisting of 40 individuals of known personality, continuously over two weeks. We tested whether personality variation explained differences in departure timing, transience movements, settlement success and spatial distribution along the environmental gradient. We found evidence for a dispersal syndrome. Specifically, more active/aggressive individuals dispersed quicker in the mesocosm, spent more time on territories and collected more eggs. However, we did not detect phenotype-environment correlations. Our findings highlight the importance of personality-dependent dispersal, with specific behavioural types driving dispersal and settlement success. Furthermore, our mesocosm setup provides unique insights into dispersal dynamics in a system where detailed observations in all dispersal stages are rare. Despite limitations, behavioural experiments in mesocosms serve as a valuable bridge between laboratory and natural systems.

animal behavior and cognition↗

bioRxiv2024

Emergence of alternative offspring care patterns from the evolution of parental negotiation strategies

The evolution of parental cooperation is challenging to explain because caring for offspring is costly, and parents face an evolutionary conflict of interests over how much care each should contribute. Evolutionary game theory suggests that this conflict may be resolved through parental negotiation, where the parents make their care level dependent on the care provided by their partner. However, mathematical negotiation models typically predict a low level of parental cooperation. As these models are not dynamically explicit and tend to neglect stochasticity, we here investigate the evolution of parental negotiation strategies by means of individual-based simulations. Our results differ markedly from earlier analytical predictions. Parental negotiation strategies readily evolve, but replicate simulations result in four alternative care patterns: uniparental care, sex-biased care and egalitarian biparental care with constant or oscillatory care levels. Hence, pronounced sex differences in parental care can evolve even in the absence of sexual selection and uncertainty of paternity. Effective parental cooperation is the most frequent outcome, but in contrast to the earlier models, it is not based on parental compensation but on a tit-for-tat negotiation strategy. Actually, compensation destabilises cooperation and leads to less effective outcomes where one parental sex exploits the other one.

evolutionary biology↗

bioRxiv2024

A neural network model for the evolution of reconstructive social learning

Learning from others is an important adaptation. However, the evolution of social learning and its role in the spread of socially transmitted information are not well understood. Few models of social learning account for the fact that socially transmitted information must be reconstructed by the learner, based on the learners previous knowledge and cognition. To represent the reconstructive nature of social learning, we present a modelling framework that incorporates the evolution of a neural network and a simple yet biologically realistic learning mechanism. The framework encompasses various forms of individual and social learning and allows the investigation of their interplay. Individual-based simulations reveal that an effective neural network structure rapidly evolves, leading to adaptive inborn behaviour in static environments, pure individual learning in highly variable environments, and a combination of individual and social learning in environments of intermediate stability. However, the evolutionary outcome depends strongly on the type of social learning (social guidance versus social instruction) and the order of individual and social learning. Moreover, the evolutionary dynamics of social learning can be surprisingly complex, with replicate simulations converging to alternative outcomes. We discuss the relevance of our modelling framework for cultural evolution and suggest future avenues of research.

evolutionary biology↗

bioRxiv2024

A path analysis disentangling determinants of natal dispersal in a cooperatively breeding bird

Delayed offspring dispersal is an important aspect of the evolution of cooperative breeding. By applying a path-analysis approach to the long-term Seychelles warbler (Acrocephalus sechellensis) dataset, we studied whether and how delayed dispersal is affected by territory quality, the presence of helpers and non-helping subordinates, maternal breeding status, age and fecundity, and offspring sex ratio. We found that offspring are more likely to disperse when their genetic mothers are co-breeders, helpers are absent and territory quality is high. In contrast to earlier findings, our analysis does not support the idea that offspring sex ratio is affected by territory quality and helper presence. Our findings suggest that a complex interplay of ecological and social factors shapes dispersal decisions. Our study underscores the importance of considering proximate factors in understanding cooperative breeding dynamics, and it shows that path analyses offer valuable insights into dissecting the intricate relationships influencing dispersal in wild populations.

ecology↗

bioRxiv2023

A neural network model for the evolution of learning in changing environments

The ability to learn from past experience is an important adaptation, but how natural selection shapes learning is not well understood. Here, we present a novel way of modelling learning using small neural networks and a simple, biology-inspired learning algorithm. Learning affects only part of the network, and it is governed by the difference between expectations and reality. We used this model to study the evolution of learning under various environmental conditions and different scenarios for the trade-off between exploration (learning) and exploitation (foraging). Efficient learning regularly evolved in our individual-based simulations. However, in line with previous studies, the evolution of learning was less likely in relatively constant environments (where genetic adaptation alone can lead to efficient foraging) or in the case of short-lived organisms (that cannot afford to spend much of their lifetime on exploration). Once learning did evolve, the characteristics of the learning strategy (the duration of the learning period and the learning rate) and the average performance after learning were surprisingly little affected by the frequency and/or magnitude of environmental change. In contrast, an organisms lifespan and the distribution of resources in the environment had a strong effect on the evolved learning strategy. Interestingly, a longer learning period did not always lead to better performance, indicating that the evolved neural networks differ in the effectiveness of learning. Overall, however, we showed that a biologically inspired, yet relatively simple, learning mechanism can evolve to lead to an efficient adaptation in a changing environment. Author SummaryThe ability to learn from experience is an important adaptation. However, it is still unclear how learning is shaped by natural selection. Here, we present a novel way of modelling the evolution of learning using small neural networks and a simple, biology-inspired learning mechanism. Computer simulations reveal that efficient learning readily evolves in this model. However, the evolution of learning is less likely in relatively constant environments (where evolved inborn preferences can guide animal behaviour) and in short-lived organisms (that cannot afford to spend much of their lifetime on learning). If learning does evolve, the evolved learning strategy is strongly affected by the lifespan and environmental richness but surprisingly little by the rate and degree of environmental change. In summary, we show that a simple and biologically plausible mechanism can help understand the evolution of learning and the structure of the evolved learning strategies.

evolutionary biology↗

bioRxiv2023

Neural network models for the evolution of associative learning

The ability to learn from past experience is an important adaptation, but how natural selection shapes learning is not well understood. Here, we investigate the evolution of associative learning (the association of stimuli with rewards) by a modelling approach that is based on the evolution of neural networks (NNs) underlying learning. Individuals employ their genetically encoded NN to solve a learning task with fitness consequences. NNs inducing more efficient learning have a selective advantage and spread in the population. We show that in a simple learning task, the evolved NNs, even those with very simple architecture, outperform well-studied associative learning rules, such as the Rescorla-Wagner rule. During their evolutionary trajectory, NNs often pass a transitional stage where they functionally resemble Rescorla-Wagner learning, but further evolution shapes them to approximate the theoretically optimal learning rule. Networks with a simple architecture evolve much faster and tend to outperform their more complex counterparts on a shorter-term perspective. Also, on a longer-term perspective network complexity is not a reliable indicator of evolved network performance. These conclusions change somewhat when the learning task is more challenging. Then the performance of many evolved networks is not better than that of the Rescorla-Wagner rule; only some of the more complex networks reach a performance level close to the optimal Bayesian learning rule. In conclusion, we show that the mechanisms underlying learning influence the outcome of evolution. A neural-network approach allows for more flexibility and a wider set of evolutionary outcomes than most analytical studies, while at the same time, it provides a relatively straightforward and intuitive framework to study the learning process.

evolutionary biology↗

bioRxiv2022

A life-history perspective on the evolutionary interplay of sex ratios and parental sex roles

Parental care is one of the most diverse social behaviours, and caring by the male, female or both parents is essential for successful reproduction of many organisms. Theoretical and empirical studies suggest that parental sex roles are associated with biased sex ratios. However, there is considerable debate on the causal relationship between parental sex roles and sex ratio biases and on the relative importance of the operational sex ratio (OSR), the adult sex ratio (ASR), and the maturation sex ratio (MSR). Here we use individual-based evolutionary simulations to investigate the joint evolution of sex-specific parental behaviour and the various sex ratios in several life history scenarios. We show that sex differences in maturation time or mortality rates at various life-history stages predict the evolution of parental sex roles relatively well: typically, but not always, parental care is biased toward the sex with the lower mortality or the faster maturation. The association of parental sex roles with the various sex ratios is more intricate. In our simulations, the operational sex ratio at evolutionary equilibrium was typically biased toward the less-caring sex. However, the direction and strength of OSR biases often changed drastically in the course of evolution, implying that, rather than being a driver of parental sex roles, OSR biases emerge as a consequence of sex-biases in parental care. When the MSR or the ASR is biased, this bias is generally associated with a bias in parental care: the overrepresented sex does most of the caring. However, the opposite pattern (that the underrepresented sex did most of the caring) also occurs in some scenarios. Moreover, pronounced parental sex roles may also evolve in the absence of an MSR or ASR bias. Taken together, we conclude that none of the sex ratios can be viewed as drivers of a parental care bias; they rather co-evolve with parental care bias in a subtle manner.

evolutionary biology↗

bioRxiv2022

Ideal free distribution of unequal competitors: spatial assortment and evolutionary diversification of competitive ability

Ideal free distribution theory attempts to predict the distribution of well-informed ( ideal) and unconstrained ( free) foragers in space based on adaptive individual decisions. When individuals differ in competitive ability, a whole array of equilibrium distributions is possible, and it is unclear which of these distributions are most likely. In the first part of our study, we show that strong competitors have an intrinsically stronger preference for highly productive habitat patches than poor competitors. This leads to an equilibrium distribution where the average competitive ability on a patch is strongly correlated with the productivity of the patch. In the second part of our study, we consider what happens if differences in competitive ability are heritable and, hence, subject to natural selection. Under constant environmental conditions, selection eliminates such differences: a single strategy prevails that optimally balances the costs and benefits associated with competitive ability. If the productivity of patches changes during the lifetime of individuals, the spatial assortment of competitors of equal competitive ability gives poor competitors a systematic advantage in times of environmental change, while good competitors benefit from equilibrium conditions. Using evolutionary individual-based simulations, we demonstrate that environmental change may then lead to the diversification of competitive ability.

ecology↗

bioRxiv2022

Mesocosm experiments reveal the loss of migratory tendencies in a recently isolated population of three-spined sticklebacks

In the 1970s, water management in the Netherlands resulted in numerous isolated populations of three-spined sticklebacks, which can no longer migrate from freshwater to the sea. We tested whether [~]50 years of isolation resulted in reduced migratory tendencies in these resident sticklebacks. Lab-based individual testing showed behavioural divergence between residents and migrants, but also produced counter-intuitive results, especially with regards to movement tendencies. To detect differences in migration tendencies, we set up a semi-natural mesocosm, consisting of connected ponds, where movements of numerous individuals could continually be tracked at larger spatial scales. We found that wild-caught residents and migrants exhibited no differences in movement tendencies within ponds, but residents moved significantly less between ponds than migrants. Between-pond movements were consistent and the observed differences were robust across contexts (changes in water flow and group size). Our study reveals that larger-scale movement tendencies can diverge over short time scales in response to human-induced isolation, and highlights the importance of observing behaviour in ecologically relevant setups that bridge the gap between lab and field studies.

animal behavior and cognition↗

bioRxiv2022

Resource sharing leads to the emergence of division of labour

Division of labour occurs in a broad range of organisms. Yet, how division of labour can emerge in the absence of pre-existing interindividual differences is poorly understood. Using a simple but realistic model, we show that in a group of initially identical individuals, division of labour emerges spontaneously if returning foragers share part of their resources with other group members. In the absence of resource sharing, individuals follow an activity schedule of alternating between foraging and other tasks. If non-foraging individuals are fed by other individuals, their alternating activity schedule becomes interrupted, leading to task specialisation and the emergence of division of labour. Furthermore, nutritional differences between individuals reinforce division of labour. Such differences can be caused by increased metabolic rates during foraging or by dominance interactions during resource sharing. Our model proposes a plausible mechanism for the self-organised emergence of division of labour in animal groups of initially identical individuals. This mechanism could also play a role for the emergence of division of labour during the major evolutionary transitions to eusociality and multicellularity.

evolutionary biology↗

bioRxiv2022

Modelling the spatial dynamics of oncolytic virotherapy in the presence of virus-resistant tumor cells

Oncolytic virotherapy is a promising form of cancer treatment that uses native or genetically engineered viruses to target, infect and kill cancer cells. Unfortunately, this form of therapy is not effective in a substantial proportion of cancer patients, partly due to the occurrence of infection-resistant tumor cells. To shed new light on the mechanisms underlying therapeutic failure and to discover strategies that improve therapeutic efficacy we designed a cell-based model of viral infection. The model allows to investigate the dynamics of infection-sensitive and infection-resistant cells in tumor tissue in presence of the virus. To reflect the importance of the spatial configuration of the tumor on the efficacy of virotherapy, we compare three variants of the model: two 2D models of a monolayer of tumor cells and a 3D model. In all model variants, we systematically investigate how the therapeutic outcome is affected by properties of the virus (e.g. the rate of viral spread), the tumor (e.g. production rate of resistant cells, cost of resistance), the healthy stromal cells (e.g. degree of resistance to virus) and the timing of treatment. We find that various therapeutic outcomes are possible when resistant cancer cells arise at low frequency in the tumor. These outcomes depend in an intricate but predictable way on the death rate of infected cells, where faster death leads to rapid virus clearance and cancer persistence. Our simulations reveal three different causes of therapy failure: rapid clearance of the virus, rapid selection of resistant cancer cells, and a low rate of viral spread due to the presence of infection-resistant healthy cells. Our models suggest that improved therapeutic efficacy can be achieved by sensitizing healthy stromal cells to infection, although this remedy has to be weighed against the toxicity induced in the healthy tissue.

cancer biology↗

bioRxiv2022

Novel pathogen introduction rapidly alters evolved movement strategies, restructuring animal societies

Animal sociality emerges from individual decisions on how to balance the costs and benefits of being sociable. Movement strategies incorporating social information -- the presence and status of neighbours -- can modulate spatial associations, helping animals avoid infection while benefiting from indirect information about their environment. When a novel pathogen is introduced into a population, it should increase the costs of sociality, selecting against gregariousness. Yet current thinking about novel pathogen introductions into wildlife neglects hosts potential evolutionary responses. We built an individual-based model that captures essential features of the repeated introduction, and subsequent transmission of an infectious pathogen among social hosts. Examining movements in a foraging context, widely shared by many species, we show how introducing a novel pathogen to a population provokes a rapid evolutionary transition to a dynamic social distancing movement strategy. This evolutionary shift triggers a disease-dominated ecological cascade of increased individual movement, decreased resource harvesting, and fewer social encounters. Pathogen-risk adapted individuals form less clustered social networks than their pathogen-risk naive ancestors, which reduces the spread of disease. The mix of post-introduction social movement strategies is influenced by the usefulness of social information and disease cost. Our work demonstrates that evolutionary adaptation to pathogen introductions and re-introductions can be very rapid, comparable to ecological timescales. Our general modelling framework shows why evolutionary dynamics should be considered in movement-disease models, and offers initial predictions for the eco-evolutionary consequences of wildlife pathogen spillover scenarios.

ecology↗

bioRxiv2022

Putting life history theory to the test - the estimation of reproductive values from field data

Quantifying fitness is important to understand adaptive evolution. Reproductive values are useful for making fitness comparisons involving different categories of individuals, like males and females. By definition, the reproductive value of a category is the expected per capita contribution of the members of that category to the gene pool of future generations. Life history theory reveals how reproductive values can be determined via the estimation of life-history parameters, but this requires intricate algebraic calculations. Recently, a more intuitive, pedigree-based method has become popular, which estimates the genetic contributions of individuals to future generations by tracking their descendants down the pedigree. Here we compare both methods. We implement various life-history scenarios (for which the "true" reproductive values can be calculated) in individual-based simulations, use the simulation data to estimate reproductive values with both methods, and compare the results with the true target values. We show that the pedigree-based estimation of reproductive values is either systematically biased (and hence inaccurate), or very imprecise. This holds even for simple life histories and under idealized conditions. In contrast, the traditional algebraic method estimates reproductive values with high accuracy and precision. Lay SummaryTo study evolution in empirical systems it is important to accurately and precisely measure fitness. Here, using simulations, we compare two methods for estimating fitness and test their accuracy and precision. One estimates life-history parameters and calculates a fitness proxy using complex algebra. The other method estimates genetic contribution to future generations by tracking descendants down the pedigree. We conclude that the pedigree method is unreliable, while the algebraic method is accurate and precise.

evolutionary biology↗

bioRxiv2021

Does genetic differentiation underlie behavioral divergence in response tomigration barriers in sticklebacks? A common garden experiment

Water management measures in the 1970s in the Netherlands have produced a large number of resident populations of three-spined sticklebacks that are no longer able to migrate to the sea. This may be viewed as a replicated field experiment, allowing us to study how the resident populations are coping with human-induced barriers to migration. We have previously shown that residents are smaller, bolder, more exploratory, more active, more aggressive, exhibited lower shoaling and lower migratory tendencies compared to their ancestral migrant counterparts. However, it is not clear if these differences in wild-caught residents and migrants reflect genetic differentiation, rather than different developmental conditions. To investigate this, we raised offspring of four crosses (migrant [male] x migrant [female], resident [male] x resident [female], migrant [male] x resident [female], resident [male] x migrant [female]) under similar controlled conditions and tested for differences in morphology and behavior as adults. We found that lab-raised resident sticklebacks exhibited lower shoaling and migratory tendencies as compared to lab-raised migrants, retaining the differences in their wild-caught parents. This indicates genetic differentiation of these traits. For all other traits, the lab-raised sticklebacks of the various crosses did not differ significantly, suggesting that the earlier-found contrast between wild-caught fish reflect differences in their environment. Our study shows that barriers to migration can lead to rapid differentiation in behavioral tendencies over contemporary timescales ([~]50 generations), and that part of these differences reflects genetic differentiation. Significance statementMany organisms face changes to their habitats due to human activities. Much research is therefore dedicated to the question whether and how organisms are able to adapt to novel conditions. We address this question in three-spined sticklebacks, where water management measures cut off some populations, prohibiting their seasonal migration to the North Sea. In a previous study, we showed that wild-caught resident fish exhibited markedly different behavior than migrants. To disentangle whether these differences reflect genetic differentiation or differences in the conditions under which the wild-caught fish grew up, we conducted crosses, raising the F1 offspring under identical conditions. As their wild-caught parents, the F1 of resident x resident crosses exhibited lower migratory and shoaling tendencies than the F1 of migrant x migrant crosses, while the F1 of hybrid crosses were intermediate. This suggests that [~]50 years of isolation are sufficient to induce behaviorally relevant genetic differentiation.

evolutionary biology↗

bioRxiv2021

Habitat fragmentation induces rapid divergence of migratory and isolated sticklebacks

The adaptive capacity of many organisms is seriously challenged by human-imposed environmental change, which currently happens at unprecedented rates and magnitudes. For migratory fish, habitat fragmentation is a major challenge that can compromise their survival and reproduction. Therefore, it is important to study if fish populations can adapt to such modifications of their habitat. Here, we study whether originally anadromous three-spined stickleback populations (Gasterosteus aculeatus; migrants) changed in behavior and morphology in response to human-induced isolation. We made use of a natural field-experiment, where the construction of pumping stations and sluices in the 1970s unintendedly created replicates of land-locked stickleback populations ( resident) in the Netherlands. For two years, we systematically tested populations of residents and migrants for differences in morphology and behavioral traits (activity, aggressiveness, exploration, boldness and shoaling) in lab-based assays. We detected differences between migrant and resident populations in virtually all phenotypic traits studied: compared to the ancestral migrants, residents were smaller in size, had fewer and smaller plates and were significantly more active, aggressive, exploratory and bolder and shoaled less. Despite large ecological differences between 2018 and 2019, results were largely consistent across the two years. Our study shows that human-induced environmental change has led to the rapid and consistent morphological and behavioral divergence of stickleback populations in about 50 generations. Such changes may be adaptive but this remains to be tested. Lay summaryThe adaptive capacity of many organisms is seriously challenged by human-imposed environmental changes. For example, migratory fish encounter man-made barriers that impede their movements and force them to adopt a resident lifecycle. Here we study whether and how populations of three-spined sticklebacks diverged in response to human-induced isolation. We show that about 50 generations of isolation were sufficient to induce substantial morphological and behavioral differentiation between land-locked populations ( residents) and their migratory ancestors ( migrants).

ecology↗