Biology subjects

Gokhale, C. S.

Publications and source records attributed to Gokhale, C. S..

At least 19 recordsLinked to original sources

bioRxiv2026

On the evolution of emergence patterns driven by environmental cycles

Regular environmental cycles such as day and night or the lunar cycle are ubiquitous and drive many biological processes. Many organisms have evolved endogenous time-keeping mechanisms to anticipate these cycles to accurately time their behavior or synchronize physiological processes. The evolution of such synchronization to environmental cycles and their variability is not very well understood. As an example, we use the marine insect Clunio (Diptera, Chironomidae), which synchronize adult emergence and reproduction with the lunar cycle, and show different emergence patterns across populations. We use a model constructed with replicator-mutator dynamics to provide a novel outlook at the evolution of these emergence patterns. In particular, we investigate the effect of two traits of individual phenotypic variability of emergence, the spread and shape, on population-wide emergence patterns. We find that the semilunar and lunar emergence patterns are alternatively stable and occur when the phenotypic distribution has a narrow and is roughly flat. Arrhythmic emergence occurs when the phenotypic distribution is wide and nearly flat. The semi-lunar pattern can only be observed when the parameter of rhythmicity is changed. With our model, we introduce the concepts of frequency-dependent selection and individual phenotypic variability into the theory of chronobiology, which gives us insights into the evolution of rhythmicity in these organisms.

evolutionary biology↗

bioRxiv2025

Evolution of first aid and social wound care in an army ant society

Injuries and infections pose a significant threat to fitness. Animals cope with this problem by performing self-medication or receiving social care from members of the group. While the benefits of wound care in increasing survival are clear, the forces driving the evolution of these behaviours are not fully understood. Contrary to the current hypothesis that social wound care is more likely to evolve in small groups due to the high relative value of an individual, we demonstrate that group size is not necessary for its evolution or retention. Instead, our theoretical model formalises how injury rate and lethality are fundamental drivers of care rather than group size. This is further evidenced by the presence of wound care in the army ant Eciton burchellii, a species with colonies of [~]1 million ants that hunts pugnacious prey. Here, wound care significantly increased survival in ants with infected wounds, occurring in two phases: direct care at the raiding site, and treatment with antimicrobial secretions in the bivouac. This species is the first to provide on-site care, thereby minimising the latency to receive care and thus potentially the likelihood of lethal wound infection. Our findings reject the notion that small group size is necessary for the evolution or retention of social wound care, revealing instead that injury-driven care can be a widespread and adaptive feature of even the largest insect societies. Significance StatementInjuries and infections threaten survival, but animals can counter these dangers through self-medication or social care. It has been suggested that helping behaviours directed towards vulnerable or injured individuals, such as social wound care, are more likely to evolve in small groups. This study in an army ant with [~]1 million workers shows otherwise, with injury frequency likely being the key component for the evolution or retention of wound-care behaviours. The unique strategy of on-site care at the raiding site, followed by antimicrobial care inside the bivouac, significantly improved survival outcomes. Our theoretical model further shows that even at low rates of care, fitness benefits are high, suggesting that social wound care may be far more widespread than previously thought.

evolutionary biology↗

bioRxiv2025

How competition can drive allochronic divergence: a case study in the marine midge, Clunio marinus

Synchronizing mating to extrinsic environmental cycles can increase the chance of successful reproduction. However, the resulting temporally-assorted mating may precipitate speciation if coupled with divergent selection. This process might be particularly relevant to the marine midge Clunio marinus, which synchronizes its reproduction to different lunar phases. In Ro-scoff (France) two sympatric populations differ in reproductive timing but are still connected by gene flow. A previous study found a relationship between the timing of reproduction and larval depth in the intertidal zone. Building on this observation, we ask if the link between reproductive timing and depth could be a mechanism for divergence when coupled with competition-induced density-dependent fitness. We devise an individual-based model replicating the reproductive behavior of C. marinus and find that sympatric divergence can occur, even when we model sexual reproduction with recombination and an explicit genetic basis. Our results suggest this mechanism is a likely hypothesis for the allochronic divergence observed in the Roscoff populations. Additionally, our study provides insights into how density-dependent fitness and competition may play a role in allochronic divergence in general.

evolutionary biology↗

bioRxiv2025

Optimising play for learning risky behaviour

Animals adapt their behaviour to current environmental conditions to enhance survival and reproductive success. While longterm adaptation occurs through evolutionary processes acting on heritable variation, individuals can also adapt within their lifetime via learning. Learning is particularly advantageous in environments that are uncertain or fluctuate across a lifespan or a few generations. However, reliance on individual learning entails a critical risk. Juveniles may begin life poorly adapted to their surroundings, requiring exploration to learn. Such an approach can be costly and dangerous, especially for species engaging in risky activities such as hunting dangerous prey. We explore how early-life learning in a protected environment, such as one buffered by parental care, can facilitate effective behavioural adaptation in later, riskier contexts. As a representative case, we model the decision-making process of a predator hunting both safe and dangerous prey. We analyse decisionmaking dynamics through reinforcement learning, extending beyond classical dynamic programming approaches. Our results show that experiences in a juveniles early environment can generalise to a distinct adult environment, provided there is sufficient structural similarity between them. Our findings demonstrate that incorporating structured play or safe exploration in early life can significantly enhance the performance of learningbased adaptation in dangerous environments.

animal behavior and cognition↗

bioRxiv2025

Higher-order equivalence of Lotka-Volterra and replicator dynamics

The Lotka-Volterra equations are foundational in ecology, modelling logistic growth in isolated populations and complex dynamics in interacting species. Hofbauer and Sigmund established that these equations are equivalent to the replicator dynamics of evolutionary games, so dynamic patterns in ecology are mirrored in evolutionary games and vice versa. Both fields have since turned to non-linearities and higher-order interactions, where it is unclear whether this equivalence still holds. Here, we demonstrate the general equivalence and illustrate it in classical non-linear models from theoretical ecology. Non-linearities in either field leave this foundational connection intact. Yet directly modelling ecological dynamics with evolutionary games, or the reverse, risks misinterpretation, since species in Lotka-Volterra dynamics cannot be equated with strategies in evolutionary games. Our study reveals the tight interplay between ecology and evolutionary game theory, and the robustness of their mathematical connection even in complex scenarios, alongside its caveats.

evolutionary biology↗

bioRxiv2024

Early eukaryogenesis by host-initiated obligate ectosymbiosis and metabolic inhibition

Microbial symbiosis is extremely common among metabolically coupled cells, and, presumably, gave rise to mitochondria. How such symbioses emerge, evolve and stabilize are unknown, especially in the prokaryotic domain, where endosymbioses are virtually nonexistent. Yet there is growing evidence suggesting that the eukaryotic cell emerged from such a prokaryotic partnership, where integration was not the result of phagocytotic inclusion (as in case of plastids) but of metabolic cooperation. While prokaryotes almost ubiquitously engage in metabolic syntrophy, it is unknown if such cooperation alone can enable stable, dependent ectosymbioses that could pave the road toward physical integration of parties. Here, we tested the hypothesis that free-living syntrophy can lead to stable ectosymbiosis between microbial partners, using an ecological mathematical model. Assuming an already syntrophic and asymmetric partnership of free-living hosts and symbionts, we investigated under what conditions obligate ectosymbiosis evolve. Our results show that reduced inhibition (of self-inhibiting metabolic products) over the contact surface of partners can stabilize the ectosymbiotic consortia against free-living forms. Furthermore, strong metabolic activity between the host and their ectosymbionts could facilitate obligacy in their physical association. The model points to the significance of the contact surface in the evolution of crucial endosymbiotic features. Our results support the hypothesis that cooperative, syntrophic microbes (especially prokaryotes) are capable of coevolving to form species-specific ectosymbiosis by means of reducing the inhibition of accumulating products, a necessary first step towards endosymbiotic integration. The model provides a plausible explanation on how common metabolic syntrophy can lead to physical integration of parties through gradual ectosymbiosis. Moreover, our work fills a gap between microbial cooperation models (assuming free-living species) and those that are concerned only with already concluded physical integration under a multilevel selection paradigm.

evolutionary biology↗

bioRxiv2024

Assessing the probability and time of weed control failure due to herbicide resistance evolution

The recurrent exposure to herbicides in agricultural landscapes forces weeds to adapt in a race against extinction. What role newly arising mutations and pre-existing variation play in this evolution of herbicide resistance is critical for developing management strategies. Here, we present a model of rapid adaptation in response to strong selection, capturing complex life cycles of sexual and asexual reproduction and dormancy in a perennial weed. Using a multitype Galton-Watson process, we derive the probability of herbicide resistance evolution and the waiting time distribution until resistant plants appear in the field. We analyse the effect of seed bank dynamics and details of the reproductive system in defining the probability and timing of resistance adaptation in Sorghum halepense. Further, we investigate key factors determining the primary source of adaptive variation. We find that even small fitness costs associated with resistance reduce adaptation from standing genetic variation. For herbicide resistance inherited in a (incompletely) dominant fashion, self-pollination also diminishes standing variation for herbicide resistance by increasing the homozygosity. Our study highlights the importance of seed banks for weeds adaptive potential, preserving genetic information of forgone selection and prolonging the period in which the population can adapt.

evolutionary biology↗

bioRxiv2023

On multiple infections by parasites with complex life cycles

Host manipulation is a common strategy of parasites with complex life cycles. It directly affects predator-prey dynamics in trophically transmitted parasites. Theoretical studies suggest that predation-enhancing manipulation of-ten decimates the prey population, making parasites prone to extinction. Host manipulation, however, can also reduce predation due to conflicting interests when multiple parasites infect a host, which is often neglected in theoretical studies. Misaligned interests of coinfecting parasites can occur due to limited carrying capacity or parasitoid developmental stage. Including this realistic complexity in a mathematical model, the results depart from previous studies substantially. We show that coinfecting multi-trophic parasites can preserve the predator-prey system and themselves through manipulation and reproduction parameters. Our study highlights the necessity of and provides the means for incorporating the reality of multiple parasites and their multi-trophic life cycles into the theory of parasite ecology.

ecology↗

bioRxiv2023

Economic analysis of disease and control of multi-field epidemics in agriculture

Epidemics of plant diseases are estimated to cause significant economic losses in crop production. Fungicide applications are widely used to control crop diseases but incur substantial indirect costs. One essential class of indirect costs arises due to the evolution of fungicide resistance. This indirect cost must be estimated reliably to design economic policy for more sustainable use of fungicides. Such estimation is difficult because the cost depends on economic parameters and the evo-epidemiological properties of crop pathogens. Even a conceptual framework for such estimation is missing. To address this problem, we combined a spatially implicit mathematical model of crop epidemics with an economic analysis at the landscape scale. We investigated how the net economic return from a landscape depends on the proportion of fungicide-treated fields. We discovered a pattern of accelerating (or decelerating) returns, contrary to expected diminishing returns. Next, we calculated the economic cost of the evolution of fungicide resistance as the difference between the optimal net return of the landscape in the absence and presence of resistance. We found that this cost depends strongly on the fungicide price, the degree of resistance, the pathogens basic reproduction number and the yield loss due to disease. Surprisingly, the cost declines with the fungicide price and exhibits a non-monotonic pattern as a function of the basic reproduction number. Hence, to calculate the cost, we must estimate these parameters robustly, incorporating variations in environmental conditions, crop varieties and the genetic composition of pathogen populations. Appropriate estimation of the cost of resistance evolution can inform economic policy and encourage more sustainable use of fungicides. Author SummaryFungicides protect crops from diseases and are essential for securing the global food supply, but they incur serious indirect costs to society and the environment. One such cost arises because of the evolution of fungicide resistance. Part of the pathogen population (fungicide-resistant) can gain protection from a fungicide via a genetic change. If fungicide applications continue, the fungicide-resistant subpopulation increases and dominates the population, leading to low efficacy. Resistance can lead to severe economic losses, but no conceptual framework exists for estimating them. We present a novel mathematical framework to estimate the economic costs of fungicide resistance at the landscape scale. We combined an epidemiological model describing disease spread with an economic cost-benefit analysis. Surprisingly, we found that the economic cost of resistance declines for more expensive fungicides. This cost also depends on the pathogens capacity to spread (invasiveness): the cost is highest for pathogens with intermediate invasiveness. Thus, the cost of resistance depends on economic parameters and the biological characteristics of plant diseases. Our findings can inform economic policies for sustainable fungicide use, such as taxes or subsidies. Our paper also contributes to the broader discourse on agricultural sustainability while ensuring global food security.

evolutionary biology↗

bioRxiv2023

On the structure of an evolutionary transition: dependence and cohesion in incipient endosymbioses

Eukaryogenesis is the prototypical example of an egalitarian evolutionary transition in individuality, and endosymbiosis, more generally, is central to the origins of many complex biological systems. Why do only some symbioses undergo such a transition, and how does the host-symbiont relationship change during this process? Here, we characterise endosymbiosis by two emergent collective-level properties: host and symbiont survival as a collective ("mutual dependence") and the level of synchronised reproduction ("reproductive cohesion"). Using adaptive dynamics, we study the evolution of the traits underlying these properties. First, by adding a carrying capacity for the collective population - a realism omitted in previous models - we find novel reasons why complete dependence or cohesion might not evolve, thus providing further theoretical support for the rarity of transitions in individuality. Second, our model suggests that asymmetries in evolutionary outcomes of hosts and symbionts can be explained by a difference in their population growth parameters, coupled with their shared fate when in a collective. Lastly, we show that during the early stages of an endosymbiosis, even if investments in dependence and cohesion are uncorrelated, mutual dependence arises faster than reproductive cohesion. Our results hence shed light on three aspects of endosymbiosis: coevolution between the host and symbiont, coevolution between dependence and cohesion, and ultimately on the opportunity of undergoing an evolutionary transition. Connecting to ecological factors, this work uncovers fundamental properties of endosymbioses, providing a clear way forward for theoretical and empirical investigations.

evolutionary biology↗

bioRxiv2023

Antibiotic-mediated interactions underlying microbial diversity

The immense diversity observed in natural microbial communities is surprising in light of the numerous weapons microbes have evolved to inhibit each others growth. It is thus imperative to understand which interaction patterns can sustain a biodiverse community when individual species antagonistically affect one another. In this study, we leverage potent methods from theoretical ecology to show how antibiotic-mediated interactions between microbes drive biological diversity. Building on previous experimental and theoretical results, we analyse the dynamics induced by various interaction graphs involving antibiotic production, resistance, and degradation. Previous work has recognised the importance of a particular producer-sensitive-degrader (PSD) motif in the interaction graph. We study this motif in detail and elucidate the mechanistic reason for this importance. Concretely, we give exact rules for coexistence in some simple cases where exhaustive enumeration of the interaction graphs is feasible. More generally, our results suggest that the PSD motif, in combination with a cyclic interaction structure, is sufficient for stable coexistence in well-mixed populations. Using individual-based simulations, we then study the importance of the PSD motif in spatially structured populations. We show that community coexistence is robust for an extensive range of antibiotic and degrader diffusivities. Together, these findings illuminate the interaction patterns that give rise to diversity in complex microbial communities, stressing that antagonism does not imply a lack of diversity and suggesting clear approaches for culturing synthetic microbial consortia.

microbiology↗

bioRxiv2022

Impact of female mate copying on male morph dynamics

Mate copying (MC), a type of non-independent mate choice, is a behaviour observed in many vertebrate and few invertebrate species. It occurs when an individuals sexual preference gets socially inclined toward those of its conspecifics. Theoretical models and experimental studies of MC have been limited to choice between two options (or morphs). In this study we model the evolution of morphology in a population under varying extents of mate copying. Multiple morphs and multiple observations are considered and a generalisable model is presented. We quantify the level of copying needed to achieve pseudo-stable equilibria in the presence of multiple morphs. Moving closer to realistic scenarios we support our theoretical development with simulations and discuss relevance for empirical model systems.

animal behavior and cognition↗

bioRxiv2022

Parasitoid pressures and silence evolution

Acoustic signals used by organisms to attract mates are known to attract parasitoid flies. The parasitoid flies lay their eggs inside the host signaler, eventually killing the host. We build a host-parasitoid acoustic model to investigate the effect of parasitoid flies on the signalling hosts eco-evolutionary dynamics. We used field crickets as a system to build the framework of the model. We explore how the sex ratio and the female parasitoid fecundity impact the evolution of the acoustic signal and population density of the signalling hosts. We also explore the stability of the host populations with an increase in parasitoid load. We find that up to a threshold value, an increase in parasitoid load leads to a thriving yet silent host population. Consistent with field observations, we show how this emergence of silence as an evolutionary strategy is immediate. Our results show that a drastic increase in the parasitoid load can rapidly push the signalling host population towards instability and extinction.

evolutionary biology↗

bioRxiv2022

Ecological Drivers of Community Cohesion

From protocellular to societal, networks of living systems are complex and multi-scale. The assembly of these intricate interdependencies, under ecological pressures, can be nearly impossible to understand using pairwise methods. We develop a mathematical and computational model based on a four-strain Saccharomyces cerevisiae synthetic inter-dependent system. Our system leverages transiently structured ecologies for achieving community cohesion. We show how ecological interventions could reverse or slow the extinction rate of a cohesive community. An interconnected system first needs to persist long enough to be a subject of natural selection. Our emulation of Darwins warm little ponds with an ecology governed by transient compartmentalisation provides the necessary persistence. Our results find utility across scales of organisation, stressing the importance of cyclic processes in major evolutionary transitions engineering of synthetic microbial consortia and conservation biology.

ecology↗

bioRxiv2021

The effect of mating complexity on gene drive dynamics

Gene drive technology promises to deliver on some of the global challenges humanity faces to-day in healthcare, agriculture and conservation. However, there is a limited understanding of the consequences of releasing self-perpetuating transgenic organisms into the wild populations under complex ecological conditions. In this study, we analyze the impact of three such complexities, mate-choice, mating systems and spatial mating network, on the population dynamics for two distinct classes of modification gene drive systems. All three factors had a high impact on the modelling outcome. First, we demonstrate that distortion based gene drives appear to be more robust against the mate-choice than viability-based gene drives. Second, we find that gene drive spread is much faster for higher degrees of polygamy. Including a fitness cost, the drive is fastest for intermediate levels of polygamy. Finally, the spread of gene drive is faster and more effective when the individuals have fewer connections in a spatial mating network. Our results highlight the need to include mating complexities while modelling the properties of gene drives such as release thresholds, timescales and population-level consequences. This inclusion will enable a more confident prediction of the dynamics of engineered gene drives and possibly even inform on the origin and evolution of natural gene drives.

evolutionary biology↗

bioRxiv2021

Evolution of reproductive strategies in incipient multicellularity

Multicellular organisms can potentially show a large degree of diversity in reproductive strategies, as they could reproduce offspring with varying sizes and compositions compared to their unicellular ancestors. In reality, only a few of these reproductive strategies are prevalent. To understand why this could be the case, we develop a stage-structured population model to probe the evolutionary growth advantages of reproductive strategies in incipient multicellular organisms. The performance of reproductive strategies is evaluated by the growth rates of corresponding populations. We identify the optimal reproductive strategy, which leads to the largest growth rate for a population. Considering the effects of organism size and cellular interaction, we found that distinct reproductive strategies could perform uniquely or equally well under different conditions. Only binary-splitting reproductive strategies can be uniquely optimal. Our results show that organism size and cellular interaction can play crucial roles in shaping reproductive strategies in nascent multicellularity. Our model sheds light on understanding the mechanism driving the evolution of reproductive strategies in incipient multicellularity. Meanwhile, beyond multicellularity, our results imply a crucial factor in the evolution of reproductive strategies of unicellular species - organism size.

evolutionary biology↗

bioRxiv2020

Memory shapes microbial populations

Correct decision making is fundamental for all living organisms to thrive under environmental changes. The patterns of environmental variation and the quality of available information define the most favourable strategy among multiple options, from randomly adopting a phenotypic state to sensing and reacting to environmental cues. Memory - a phenomenon often associated with, but not restricted to, higher multicellular organisms - can help when temporal correlations exist. How does memory manifest itself in unicellular organisms? Through a combination of deterministic modelling and stochastic simulations, we describe the population-wide fitness consequences of phenotypic memory in microbial populations. Moving beyond binary switching models, our work highlights the need to consider a broader range of switching behaviours when describing microbial adaptive strategies. We show that multiple cellular states capture the empirical observations of lag time distributions, overshoots, and ultimately the phenomenon of phenotypic heterogeneity. We emphasise the implications of our work in understanding antibiotic tolerance, and, in general, survival under fluctuating environments.

microbiology↗

bioRxiv2020

How sequence populations persist inside a genome

Compared to their eukaryotic counterparts, bacterial genomes are small and contain extremely tightly packed genes. Therefore, discovering a large number of short repetitive sequences in the genomes of Pseudomonads and Enterobacteria is unexpected. These sequences can independently replicate in the host genome and form populations that persist for millions of years. Here we model the interactions of intragenomic sequence populations with the bacterial host. In a simple model, sequence populations either expand until they drive the host to extinction or the sequence population gets purged from the genome. Including horizontal gene transfer does not change the qualitative outcome of the model and leads to the extinction of the sequence population. However, a sequence population can be stably maintained, if each sequence provides a benefit that decreases with increasing sequence population size. But concurrently, the replication of the sequence population needs to be costly to the host. Surprisingly, in regimes where horizontal gene transfer plays a role, the benefit conferred by the sequence population does not have to exceed the damage it causes. Together, our analyses provide a plausible scenario for the persistence of sequence populations in bacterial genomes. More importantly, we hypothesize a limited biologically relevant parameter range, which can be tested in future experiments.

evolutionary biology↗