Population Spread Research Articles

Approach to surveying egg masses of the invasive spotted lanternfly (Hemiptera: Fulgoridae).

For the invasive planthopper Lycorma delicatula, eggs are an attractive target for surveys and management because they can persist from September through May before hatching, and remnants may be retained for years after hatching. Efforts to control this invasive species, though, are hampered by imperfect detection, which impedes early detection and rapid response, obscures management impacts, and reduces the fraction of egg masses that can be managed. To estimate egg mass detectability, we conducted 75 duplicate surveys of 20 × 5 m plots located in forest edges and disturbed areas frequently used by L. delicatula. We fit binomial mixture models and investigated the effects of weather, height (above or below 3 m), season (winter or spring), and basal area of trees within plots, finding no evidence that these factors affected detection rate, which averaged 52.2%. We additionally estimated the fraction of L. delicatula eggs that were laid above 3 m, putting them outside of easy reach for management by scraping or targeted ovicide application. This proportion varied with basal area of trees within plots, and the estimated mean was greater than 50% across the range of basal areas in study plots. Finally, we found that counts of old egg masses correlated with counts of new egg masses laid the year prior, but the ability to infer prior years' egg mass counts was limited. Together, these findings inform managers delimiting L. delicatula populations in mixed habitats and those treating egg masses to slow population growth and spread of this pest.

Estimation of Parameter Distributions for Reaction-Diffusion Equations with Competition using Aggregate Spatiotemporal Data.

Reaction-diffusion equations have been used to model a wide range of biological phenomenon related to population spread and proliferation from ecology to cancer. It is commonly assumed that individuals in a population have homogeneous diffusion and growth rates; however, this assumption can be inaccurate when the population is intrinsically divided into many distinct subpopulations that compete with each other. In previous work, the task of inferring the degree of phenotypic heterogeneity between subpopulations from total population density has been performed within a framework that combines parameter distribution estimation with reaction-diffusion models. Here, we extend this approach so that it is compatible with reaction-diffusion models that include competition between subpopulations. We use a reaction-diffusion model of glioblastoma multiforme, an aggressive type of brain cancer, to test our approach on simulated data that are similar to measurements that could be collected in practice. We use Prokhorov metric framework and convert the reaction-diffusion model to a random differential equation model to estimate joint distributions of diffusion and growth rates among heterogeneous subpopulations. We then compare the new random differential equation model performance against other partial differential equation models' performance. We find that the random differential equation is more capable at predicting the cell density compared to other models while being more time efficient. Finally, we use k-means clustering to predict the number of subpopulations based on the recovered distributions.

Density dependence of seed dispersal and fecundity profoundly alters the spread dynamics of plant populations

Abstract Plant population spread has fundamental ecological and evolutionary importance. Both determinants of plant population spread, fecundity and dispersal, can be density‐dependent, which should cause feedback between population densities and spread dynamics. Yet it is poorly understood how density‐dependence affects key characteristics of spread: spread rate at which the location of the furthest forward individual moves, edge depth (the geographical area over which individuals contribute to spread) and population continuity (occupancy of the spreading population). We present a general modelling framework for analysing the effects of density‐dependent fecundity and dispersal on population spread and parameterize this framework with experimental data from a common‐garden experiment using five wind‐dispersed plant species grown at different densities. Our model shows that density‐dependent fecundity and dispersal strongly affect all three population spread characteristics for both exponential and lognormal dispersal kernels. Spread rate and edge depth are strongly correlated but show weaker correlations with population continuity. Positive density‐dependence of fecundity increases all three spread characteristics. Increasingly positive density‐dependence of dispersal increases spread rate and edge depth but generally decreases population continuity. Density‐dependent fecundity and dispersal are largely additive in their effect on spread characteristics. For population continuity, the joint effects of density‐dependent fecundity and dispersal are somewhat contingent on the dispersal kernel. The common‐garden experiment and the experimentally parameterized mechanistic dispersal model revealed density‐dependent fecundity and dispersal across study species. All study species exhibited negatively density‐dependent fecundity, but they differed qualitatively in the density‐dependence of dispersal distance and probability of long‐distance dispersal. The negative density‐dependence of fecundity and dispersal found for three species reinforced each other in reducing spread rate and edge depth. The positively density‐dependent dispersal found for two species markedly increased spread rate and edge depth. Population continuity was hardly affected by population density in all study species except Crepis sancta in which it was strongly reduced by negatively density‐dependent fecundity. Synthesis. Density‐dependent fecundity and seed dispersal profoundly alter population spread. In particular, positively density‐dependent dispersal should promote the spread and genetic diversity of plant populations migrating under climate change but also complicate the control of invasive species.

A mathematical model based study on the dynamics of corona virus (COVID-19) disease spread in population

A mathematical model based study on the dynamics of corona virus (COVID-19) disease spread in population

New research horizons of epidemiology applied to mental health.

Epidemiological research in psychiatry has always played an important role, having allowed a precise classification of psychiatric disorders and a quantification of their spread in the general population. In the current context of precision psychiatry, the fields of development of epidemiological research include: 1) the relationship between mental health and physical well-being, overcoming the stigma associated with psychiatric disorders; 2) gender differences; 3) the impact of the physical environment on mental health beyond the socio-cultural context. These issues can be explored through a close collaboration between various health professionals, and also by spreading the culture of mental health monitoring in contexts outside psychiatry.

When Everything Becomes Bigger: Big Data for Big Poultry Production.

In future decades, the demand for poultry meat and eggs is predicted to considerably increase in pace with human population growth. Although this expansion clearly represents a remarkable opportunity for the sector, it conceals a multitude of challenges. Pollution and land erosion, competition for limited resources between animal and human nutrition, animal welfare concerns, limitations on the use of growth promoters and antimicrobial agents, and increasing risks and effects of animal infectious diseases and zoonoses are several topics that have received attention from authorities and the public. The increase in poultry production must be achieved mainly through optimization and increased efficiency. The increasing ability to generate large amounts of data ("big data") is pervasive in both modern society and the farming industry. Information accessibility-coupled with the availability of tools and computational power to store, share, integrate, and analyze data with automatic and flexible algorithms-offers an unprecedented opportunity to develop tools to maximize farm profitability, reduce socio-environmental impacts, and increase animal and human health and welfare. A detailed description of all topics and applications of big data analysis in poultry farming would be infeasible. Therefore, the present work briefly reviews the application of sensor technologies, such as optical, acoustic, and wearable sensors, as well as infrared thermal imaging and optical flow, to poultry farming. The principles and benefits of advanced statistical techniques, such as machine learning and deep learning, and their use in developing effective and reliable classification and prediction models to benefit the farming system, are also discussed. Finally, recent progress in pathogen genome sequencing and analysis is discussed, highlighting practical applications in epidemiological tracking, and reconstruction of microorganisms' population dynamics, evolution, and spread. The benefits of the objective evaluation of the effectiveness of applied control strategies are also considered. Although human-artificial intelligence collaborations in the livestock sector can be frightening because they require farmers and employees in the sector to adapt to new roles, challenges, and competencies-and because several unknowns, limitations, and open-ended questions are inevitable-their overall benefits appear to be far greater than their drawbacks. As more farms and companies connect to technology, artificial intelligence (AI) and sensing technologies will begin to play a greater role in identifying patterns and solutions to pressing problems in modern animal farming, thus providing remarkable production-based and commercial advantages. Moreover, the combination of diverse sources and types of data will also become fundamental for the development of predictive models able to anticipate, rather than merely detect, disease occurrence. The increasing availability of sensors, infrastructures, and tools for big data collection, storage, sharing, and analysis-together with the use of open standards and integration with pathogen molecular epidemiology-have the potential to address the major challenge of producing higher-quality, more healthful food on a larger scale in a more sustainable manner, thereby protecting ecosystems, preserving natural resources, and improving animal and human welfare and health.

Recent Developments and Future Perspectives of Vaccines and Therapeutic Agents against SARS-CoV2 Using the BCOV_S1_CTD of the S Protein.

Since the onset of the coronavirus disease 2019 (COVID-19) pandemic, the virus kept developing and mutating into different variants over time, which also gained increased transmissibility and spread in populations at a higher pace, culminating in successive waves of COVID-19 cases. The scientific community has developed vaccines and antiviral agents against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) disease. Realizing that growing SARS-CoV-2 variations significantly impact the efficacy of antiviral therapies and vaccines, we summarize the appearance and attributes of SARS-CoV-2 variants for future perspectives in drug design, providing up-to-date insights for developing therapeutic agents targeting the variants. The Omicron variant is among the most mutated form; its strong transmissibility and immune resistance capacity have prompted international worry. Most mutation sites currently being studied are in the BCOV_S1_CTD of the S protein. Despite this, several hurdles remain, such as developing vaccination and pharmacological treatment efficacies for emerging mutants of SARS-CoV-2 strains. In this review, we present an updated viewpoint on the current issues faced by the emergence of various SARS-CoV-2 variants. Furthermore, we discuss the clinical studies conducted to assist the development and dissemination of vaccines, small molecule therapeutics, and therapeutic antibodies having broad-spectrum action against SARS-CoV-2 strains.

Evolutionary history and intraspecific competition mediate ballistic seed dispersal

Abstract Dispersal plays an important role in the survival and spread of plant populations. However, when grown under stress, a plants' architecture and fecundity may be modified, which can compromise seed dispersal. While populations within a species exhibit trait variation in response to their environment, a mechanistic understanding of how trade‐offs between dispersal ability and competitive ability vary across species' ranges is currently lacking. Using a common garden design, populations of a widespread weedy species (Cardamine hirsuta) were grown to (1) characterize how traits that influence dispersal differ between populations and (2) identify whether a trade‐off between dispersal ability and competitive ability varies among populations in response to intraspecific competition. We measured trait differences between populations and characterized dispersal kernels through exhaustively capturing seeds. In the absence of competition, populations exhibited differences in fecundity and height. Of these traits, fecundity varied more strongly between populations and had a stronger influence on dispersal capacity. The experimental data were then used to parameterize cellular automaton models to explore the consequences of these trait‐mediated dispersal responses for long‐term population dynamics. These simulations identified intraspecific competitive effects on fecundity as the primary driver of variation in spread and patch density among populations. Within‐species variation of dispersal traits occurs among populations across the range of C. hirsuta. In response to conspecific competition, populations also have unequal fecundity and long‐distance dispersal (LDD). Model simulations suggest predictions of species spread are highly modified by characterization of metapopulation life‐history traits such as high fecundity and maintenance of LDD. These mechanisms creating within‐species variation would be important to incorporate in population models of species range expansion and stability. Read the free Plain Language Summary for this article on the Journal blog.

Mapping the Exploration of Identity and Diasporic Belonging: A Literary Study of the Discourse in Jhumpa Lahiri’s Whereabouts

Diaspora is studied in the historical and ethical background of migration of human beings. It is well known for its dislocation, disorientation, uprooted culture, fractured identity, multilingual or multicultural aspects of learning in the history of human migration. It has been studied in the different fields of knowledge and theory, having significant causes and effects of new exploration. In literature, it is studied with the straddle culture of human beings. Most of the diasporas are found unexplainable in the matter of identity formation. The literary and social term ‘diaspora’ is derived from Greek word ‘diaspeiro’ which means ‘to scatter’ or ‘to spread about’. It comprises of the Greek preposition ‘dia’ and verb ‘speiro’. Dia means ‘through’ or ‘between’ and ‘speiro’ means ‘to sow’ or ‘to scatter’. In this way, the word ‘diaspora’ means the scattering of population or the spreading of population across the region they are originated. The conceptual study of diaspora goes back to the human history and was initially used by the ancient Greeks to describe their scattering population all over the world. For the ancient Greeks, it was signified for migration and colonization. In the present context, ‘diaspora’ is read with the taste of modernity in the conceptualization of human migration, having actual feeling or feeling of others in the foreign landscapes. The present paper aims at the diasporic identity as well as the whereabouts of the narrator in the exploration of Jhumpa Lahiri in her latest novel, Whereabouts published in the Italian language in (2018) and translated by herself in (2021). By examining the characters’ quest for a sense of place, negotiation of cultural hybridity, and their grappling with multifaceted identities, this research aims to elucidate the nuanced tapestry of diasporic experiences evident in Lahiri’s literary corpus.

팬데믹 시대의 골프산업 활성화 방안

In order to promote the sustainable development in golf market according to the prolonged spread of COVID-19, this study analyzed the COVID-19 pandemic and the golf activity through a method of literature research and parsed the present status of golf industry at home and abroad. Based on this, a general proposal for revitalizing the golf industry in the pandemic era is as follows. First, as the medium- and long-term development part of the golf industry, ‘A Comprehensive Plan for Sustainable Development of the Golf Industry’ is established. Second, as the section of preparing for the demand for the spread of the golf population, the insufficient golf courses are expanded and newly created. Third, as the part to activate golf products and events, there is expansion in cooperation and exchanges with the interested persons in golf courses and related facilities & businesses. Fourth, as the section to magnify the popularization of golf, the legal and institutional tax reform must be carried out. Fifth, as the part to intensify the golf area software, the cultivation of professional golfers is systematically promoted. Sixth, as the section of global golf, it includes the extension in implementing a digital comprehensive platform for sustainable golf courses and relevant facilities, and the active practice of the leading ESG. Seventh, as the part to globalize golf industry, there is a need to be arranged the establishment of the interagency convergence system such as sports, tourism, education, and health sector in the government.

Modified diffusive epidemic process on Apollonian networks.

We present an analysis of an epidemic spreading process on an Apollonian network that can describe an epidemic spreading in a non-sedentary population. We studied the modified diffusive epidemic process using the Monte Carlo method by computational analysis. Our model may be helpful for modeling systems closer to reality consisting of two classes of individuals: susceptible (A) and infected (B). The individuals can diffuse in a network according to constant diffusion rates [Formula: see text] and [Formula: see text], for the classes A and B, respectively, and obeying three diffusive regimes, i.e., [Formula: see text], [Formula: see text], and [Formula: see text]. Into the same site i, the reaction occurs according to the dynamical rule based on Gillespie's algorithm. Finite-size scaling analysis has shown that our model exhibits continuous phase transition to an absorbing state with a set of critical exponents given by [Formula: see text], [Formula: see text], and [Formula: see text] familiar to every investigated regime. In summary, the continuous phase transition, characterized by this set of critical exponents, does not have the same exponents of the mean-field universality class in both regular lattices and complex networks.

A rapidly spreading deleterious aphid endosymbiont that uses horizontal as well as vertical transmission

Endosymbiotic bacteria that live inside the cells of insects are typically only transmitted maternally and can spread by increasing host fitness and/or modifying reproduction in sexual hosts. Transinfections of Wolbachia endosymbionts are now being used to introduce useful phenotypes into sexual host populations, but there has been limited progress on applications using other endosymbionts and in asexual populations. Here, we develop a unique pathway to application in aphids by transferring the endosymbiont Rickettsiella viridis to the major crop pest Myzus persicae. Rickettsiella infection greatly reduced aphid fecundity, decreased heat tolerance, and modified aphid body color, from light to dark green. Despite inducing host fitness costs, Rickettsiella spread rapidly through caged aphid populations via plant-mediated horizontal transmission. The phenotypic effects of Rickettsiella were sensitive to temperature, with spread only occurring at 19°C and not 25°C. Body color modification was also lost at high temperatures despite Rickettsiella maintaining a high density. Rickettsiella shows the potential to spread through natural M. persicae populations by horizontal transmission and subsequent vertical transmission. Establishment of Rickettsiella in natural populations could reduce crop damage by modifying population age structure, reducing population growth and providing context-dependent effects on host fitness. Our results highlight the importance of plant-mediated horizontal transmission and interactions with temperature as drivers of endosymbiont spread in asexual insect populations.

Modeling the contribution of antibody attack rates to single and dual helminth infections in a natural system

Within-host models of infection can provide important insights into the processes that affect parasite spread and persistence in host populations. However, modeling can be limited by the availability of empirical data, a problem commonly encountered in natural systems. Here, we used six years of immune-infection observations of two gastrointestinal helminths (Trichostrongylus retortaeformis and Graphidium strigosum) from a population of European rabbits (Oryctolagus cuniculus) to develop an age-dependent, mathematical model that explicitly included species-specific and cross-reacting antibody (IgA and IgG) responses to each helminth in hosts with single or dual infections. Different models of single infection were formally compared to test alternative mechanisms of parasite regulation. The two models that best described single infections of each helminth species were then coupled through antibody cross-immunity to examine how the presence of one species could alter the host immune response to, and the within-host dynamics of, the other species. For both single infections, model selection suggested that either IgA or IgG responses could equally explain the observed parasite intensities by host age. However, the antibody attack rate and affinity level changed between the two helminths, it was stronger against T. retortaeformis than against G. strigosum and caused contrasting age-intensity profiles. When the two helminths coinfect the same host, we found variation of the species-specific antibody response to both species together with an asymmetric cross-immune response driven by IgG. Lower attack rate and affinity of antibodies in dual than single infections contributed to the significant increase of both helminth intensities. By combining mathematical modeling with immuno-infection data, our work provides a tractable model framework for disentangling some of the complexities generated by host-parasite and parasite–parasite interactions in natural systems.

Involvement immune response in the pathogenesis of ischemic stroke

Acute disorders of cerebral circulation are one of the leading problems of modern clinical medicine, due to their significant spread in the human population and the extremely negative impact exerted on the patient’s body. Currently available data allow us to talk about the multi-vector nature of the pathogenesis of ischemic brain damage. Within the framework of the cascade of developing pathochemical and pathophysiological processes, an essential role in the formation of ischemic stroke belongs to the inflammatory reaction occurring through the immune system’s response to cerebral tissue ischemia. One of the places of its implementation is the vessel wall located in the ischemic zone, where monocytes and neutrophils are attracted with the help of cell adhesion proteins. Complement activation plays a significant role, carried out mainly due to the C3 component or during the initialization of the mannose pathway. Activation of microglia and astrocytes plays a huge role directly in the focus of ischemia. It should be noted that in the process of activation, both microglia and astrocytes are able to acquire a pro-inflammatory or anti-inflammatory phenotype. The prevalence of the pro-inflammatory variant contributes to prolonged damage to brain tissue, while the predominance of the anti-inflammatory phenotype has a protective effect. An important role is played by a violation of the function of the blood-brain barrier, which provides an additional influx of leukocytes to the site of ischemia. In addition, individual subpopulations of T-lymphocytes penetrating through the damaged barrier also play a significant role in the organization and dynamics of the immuno-inflammatory response. The action of Th1 and Th2 cells, gamma-delta T lymphocytes, natural killer cells, as well as regulatory T lymphocytes has been most studied. The role of B-lymphocytes in the formation of a stroke focus is considered.

Signatures of Adaptation, Constraints, and Potential Redundancy in the Canonical Immune Genes of a Key Pollinator.

All organisms require an immune system to recognize, differentiate, and defend against pathogens. From an evolutionary perspective, immune systems evolve under strong selective pressures exerted by fast-evolving pathogens. However, the functional diversity of the immune system means that different immune components and their associated genes may evolve under varying forms of selection. Insect pollinators, which provide essential ecosystem services, are an important system in which to understand how selection has shaped immune gene evolution as their populations are experiencing declines with pathogens highlighted as a potential contributing factor. To improve our understanding of the genetic variation found in the immune genes of an essential pollinator, we performed whole-genome resequencing of wild-caught Bombus terrestris males. We first assessed nucleotide diversity and extended haplotype homozygosity for canonical immune genes finding the strongest signatures of positive selection acting on genes involved in pathogen recognition and antiviral defense, possibly driven by growing pathogen spread in wild populations. We also identified immune genes evolving under strong purifying selection, highlighting potential constraints on the bumblebee immune system. Lastly, we highlight the potential loss of function alleles present in the immune genes of wild-caught haploid males, suggesting that such genes are potentially less essential for development and survival and represent redundancy in the gene repertoire of the bumblebee immune system. Collectively, our analysis provides novel insights into the recent evolutionary history of the immune system of a key pollinator, highlighting targets of selection, constraints to adaptation, and potential redundancy.

Determinants of FDI inflows: Aggregate versus country-specific evidence from ASEAN-6

This paper seeks to explore the determinants of foreign direct investment (FDI) inflows into six countries of the Association of Southeast Asian Nations (ASEAN), namely Indonesia, Malaysia, the Philippines, Singapore, Thailand and Vietnam, from 1995 to 2019. Estimations for the aggregate model are conducted with the Driscoll–Kraay standard errors panel regression approach, while the country-specific analyses are based on the fully modified ordinary least squares (FMOLS) approach. At the aggregate level, gross domestic product (GDP) growth, trade openness, unemployment, working-age population and interest rate spread are the main drivers of FDI inflows into the ASEAN-6, while per capita GDP, real interest rate and the global financial crisis have no significant impact. The empirical analysis for the specific-country cases yields mixed results, implying that international corporations may have various criteria to evaluate before making investment decisions depending on the development stage of the host country. Our research findings offer several implications for policymakers to attract quality FDI: (i) fostering trade and investment liberalization through taking down trade barriers and tariffs across nations; (ii) enhancing the quality and capacity of the labor force through management policy renovations; (iii) stabilizing interest rates through monetary policy management to ensure macroeconomic stability.

Discovery of an unrecognized nidovirus associated with granulomatous hepatitis in rainbow trout

Rainbow trout (Oncorhynchus mykiss) is the principal species of inland-farmed fish in the Western hemisphere. Recently, we diagnosed in farmed rainbow trout a disease in which the hallmark is granulomatous-like hepatitis. No biotic agents could be isolated from lesions. Still, unbiased high-throughput sequencing and bioinformatics analyses revealed the presence of a novel piscine nidovirus that we named "Trout Granulomatous Virus" (TGV). TGV genome (28,767 nucleotides long) is predicted to encode non-structural (1a and 1ab) and structural (S, M, and N) proteins that resemble proteins of other known piscine nidoviruses. High loads of TGV transcripts were detected by quantitative RT-PCR in diseased fish and visualized in hepatic granulomatous sites by fluorescence in situ hybridization. Transmission electron microscopy (TEM) revealed coronavirus-like particles in these lesions. Together, these analyses corroborated the association of TGV with the lesions. The identification and detection of TGV provide means to control TGV spread in trout populations.

Spread of networked populations is determined by the interplay between dispersal behavior and habitat configuration

Predicting the spread of populations across fragmented habitats is vital if we are to manage their persistence in the long term. We applied network theory with a model and an experiment to show that spread rate is jointly defined by the configuration of habitat networks (i.e., the arrangement and length of connections between habitat fragments) and the movement behavior of individuals. We found that population spread rate in the model was well predicted by algebraic connectivity of the habitat network. A multigeneration experiment with the microarthropod Folsomia candida validated this model prediction. The realized habitat connectivity and spread rate were determined by the interaction between dispersal behavior and habitat configuration, such that the network configurations that facilitated the fastest spread changed depending on the shape of the species' dispersal kernel. Predicting the spread rate of populations in fragmented landscapes requires combining knowledge of species-specific dispersal kernels and the spatial configuration of habitat networks. This information can be used to design landscapes to manage the spread and persistence of species in fragmented habitats.

Qualitative Numerical Analysis of a Free-Boundary Diffusive Logistic Model

A two-dimensional free-boundary diffusive logistic model with radial symmetry is considered. This model is used in various fields to describe the dynamics of spreading in different media: fire propagation, spreading of population or biological invasions. Due to the radial symmetry, the free boundary can be treated by a front-fixing approach resulting in a fixed-domain non-linear problem, which is solved by an explicit finite difference method. Qualitative numerical analysis establishes the stability, positivity and monotonicity conditions. Special attention is paid to the spreading–vanishing dichotomy and a numerical algorithm for the spreading–vanishing boundary is proposed. Theoretical statements are illustrated by numerical tests.

When complex movement yields simple dispersal: behavioural heterogeneity, spatial spread and parasitism in groups of micro-wasps

BackgroundUnderstanding how behavioural dynamics, inter-individual variability and individual interactions scale-up to shape the spatial spread and dispersal of animal populations is a major challenge in ecology. For biocontrol agents, such as the microscopic Trichogramma parasitic wasps, an understanding of movement strategies is also critical to predict pest-suppression performance in the field.MethodsWe experimentally studied the spatial propagation of groups of parasitoids and their patterns of parasitism. We investigated whether population spread is density-dependent, how it is affected by the presence of hosts, and whether the spatial distribution of parasitism (dispersal kernel) can be predicted from the observed spread of individuals. Using a novel experimental device and high-throughput imaging techniques, we continuously tracked the spatial spread of groups of parasitoids over large temporal and spatial scales (8 h; and 6 m, ca. 12,000 body lengths). We could thus study how population density, the presence of hosts and their spatial distribution impacted the rate of population spread, the spatial distribution of individuals during population expansion, the overall rate of parasitism and the dispersal kernel (position of parasitism events).ResultsHigher population density accelerated population spread, but only transiently: the rate of spread reverted to low values after 4 h, in a “tortoise-hare” effect. Interestingly, the presence of hosts suppressed this transiency and permitted a sustained high rate of population spread. Importantly, we found that population spread did not obey classical diffusion, but involved dynamical switches between resident and explorer movement modes. Population distribution was therefore not Gaussian, though surprisingly the distribution of parasitism (dispersal kernel) was.ConclusionsEven homogenous asexual groups of insects develop behavioural heterogeneities over a few hours, and the latter control patterns of population spread. Behavioural switching between resident and explorer states determined population distribution, density-dependence and dispersal. A simple Gaussian dispersal kernel did not reflect classical diffusion, but rather the interplay of several non-linearities at individual level. These results highlight the need to take into account behaviour and inter-individual heterogeneity to understand population spread in animals.