POPD Posters

eSMB2020 eSMB2020 Follow 2:30 - 3:30pm, Monday - Wednesday
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  1. Abdel H. Halloway (POPD)

    Purdue University
    "Non-Equilibrial Dynamics in Under-Saturated Communities"
    The concept of the evolutionarily stable strategy (ESS) has been fundamental to the development of evolutionary game theory. It represents an equilibrial evolutionary state in which no rare invader can grow in population size. With additional work, the ESS concept has been formalized and united with other stability concepts such as convergent stabil- ity, neighborhood invasion stability, and mutual invisibility. Other work on evolutionary models, however, shows the possibility of unstable and/or non-equilibrial dynamics such as limit cycles and evolutionary suicide. Such “pathologies” remain outside of a well-defined context, especially the currently defined stability concepts of evolutionary games. Ripa et al. (2009) offer a possible reconciliation between work on non-equilibrial dynamics and the ESS concept. They noticed that the systems they analyzed show non-equilibrial dynam- ics when under-saturated and “far” from the ESS and that getting “closer” to the ESS through the addition of more species stabilized their systems. To that end, we analyzed three models of evolution, two predator-prey models and one competition model of evolu- tionary suicide, to see how the degree of saturation affects the stability of the system. In the predator-prey models, stability is linked to degree of saturation. Specifically, a fully saturated community will only show stable dynamics, and unstable dynamics occur only when the community is under-saturated. With the competition model, we demonstrate it to be permanently under-saturated, likely showing such extreme dynamics for this rea- son. Though not a general proof, our analysis of the models provide evidence of the link between community saturation and evolutionary dynamics. Our results offer a possible placement of these unstable and non-equilibrial dynamics into a wider framework. In addi- tion, the results concur with previous results showing greater evolutionary response to less biodiversity and clarifies the effect of extrinsic vs. intrinsic non-equilibrial evolutionary dynamics on a community.

  2. Angela Lynn Peace (POPD)

    Texas Tech University
    "A Simple model of pathogen-mediated nutrient dynamics"
    How do nitrogen and phosphorus availability impact infectious disease, and what are the reciprocal effects of pathogens on ecosystem nutrient dynamics? These questions are fundamental to understanding the coupling between disease dynamics and nutrient cycles, yet disease-ecosystem relationships are often overlooked. Relationships linking infectious disease with ecosystem nutrient dynamics are multidirectional and can form feedback loops, though the dynamic interdependence of these processes is little understood. We illustrate the impact of disease-ecosystem feedback loops for the dynamics of both infection outcomes and ecosystem nutrients using a simple mathematical model. The model is a nonsmooth system of ordinary differential equations combining approaches from classical ecological models (logistic and droop growth) and epidemiological models (disease transmission). Our model incorporates the effects of nutrient availability on growth rates of susceptible and infected hosts, as well as the return of nutrients to the environment following host death. Despite the simplicity of this model, our results illustrate complex dynamics in host populations, infection patterns, and ecosystem nutrients that can arise from even a simple disease-nutrient feedback.

  3. Anna H Sisk (POPD)

    "Linking Immuno-Epidemiology Principles to Violence"
    Societies have always struggled with the causes and effects of violence, but only recently has there been a drive to better understand violence as a disease and to consider it from a public health perspective. Through the work of many physicians and psychologists we have realized violence is less like a moral failing and more like a disease. This realization unified professionals from the medical/epidemiological fields and those in psychology in a common goal to end violence and help heal those exposed to it. Recently, interesting analogies have been made between community-level infectious disease epidemiology and how violence spreads within a community. Experts in public health and medicine have suggested that an epidemiological framework could be used to study violence. Infectious disease studies are often approached from two different scales: outbreak/community and immune system/individual. At both the epidemiological/community and immune system/individual scales, mathematical modeling of infectious disease dynamics plays an important role. Each scale has been modeled in isolation from the other; however, there is a natural connection between the epidemiological and immune system dynamics, since a person’s immune response determines the likelihood of transmission to others. Thus, there has been a push to consider both scales in the multi-scale integrated approach of Immuno-Epidemiological (IE) modeling. We plan to apply the approaches used for IE modeling to violence by employing the epidemiological part of the model to explore violence spread on the community level and the immune system model to look at the impact that violence exposure has on an individual with respect to increasing their propensity to commit violence. In this talk I will expand on and formalize the analogy of violence as an infectious disease and show how the well-developed principles of mathematical epidemiology and immunology is a useful framework for understanding the dynamics of violence. Next, we will look at a preliminary susceptible-exposed-infected (SEI) mathematical model for violence spread on the community level and compare this model with traditional disease modeling. Then we will explore some basic equilibrium and stability analysis of the SEI model and look at the real-world interpretations of this analysis.

  4. Antonela Marozzi (POPD)

    "An alternative method for calf density and recruitment estimation using pregnancy on wild guanacos (Lama guanicoe)."
    Per capita recruitment is a parameter that determines most of the variation in population growth rate in wild temperate ungulates and it is generally estimated by young:female ratio. It has been proposed that this approach should be improved since only count data is used in most cases and the probability of observing calves at heel declines with the age of the calf because it is more independent of the mother. In this study, we propose an alternative method to estimate calf density (ACD) using pregnancy rate obtained from hormonal fecal metabolites and total density estimates. Then we use ACD to calculate recruitment by young:female ratio and compare the results with recruitment estimates using traditional count data (TCD). To set the parameters of ACD we used information of a partially-migratory guanaco (Lama guanicoe) population of La Payunia Provincial Reserve (Mendoza-Argentina). We calculated ACD by the following equation:A=p×h×s×D (eq. 1), where p is the pregnancy rate (0.32), s is the probability of survival (0.61), h is female's proportion (0.60), D is total density and A is calf density. First, we ran a data simulation to calculate A, using p, h, and s as deterministic parameters and D as a random parameter with a Log-Normal distribution. With the simulated data, we calculated per capita recruitment (R) and we adjusted a density-dependent model, as is expected for large ungulates: LogR=-0,179*D*[exp⁡(-0,013*D)] (eq. 2). Second, we used real data of four population surveys to estimate density by ACD. To do this we replaced the D term of the eq. 1 with field data and then, we calculated recruitment using those results. All the other terms of eq. 1 were kept the same because they belong to the population under study. Third, we estimated recruitment by young:female ratio using count data of the same surveys and compared real data recruitment estimations by ACD and TCD. Both estimations seem to follow the same pattern of the simulated data. However, recruitment obtained using ACD (0.09; 0.06; 0.07; 0.05) were lower than those calculated by TCD (0.36; 0.10; 0.31; 0.18). We hypothesized two main reasons: 1) our estimation is assuming a constant pregnancy rate; therefore, if new pregnant females entered the area under study from nearby regions from one year to the other, that information was not considered and could have led to an underestimation of recruitment by ACD. 2) In general, only a small number of calves is counted in population surveys, which may increase data dispersion, and as a consequence an overestimation of recruitment by TCD. Our innovative approach using total density estimations and pregnancy data might be useful to estimate young densities avoiding the problems of counting calves. As recruitment is one of the most important parameters to make management decisions like population control, our approach might be an alternative to reduce count data biases and should be tested in other ungulates populations.

  5. Bhawna Malik (POPD)

    Shiv Nadar University
    "Stochastic extinction of drug-resistant strains: Modelling the role of socio-economic factors in the pattern of extinction"
    Stochastic fluctuations in transmission may increase the probability of extinction of pathogens. While overuse of antibiotics leads to the emergence of new resistant strains in population by lowering its fitness cost, other socioeconomic factors may change the selection pressure and increase the probability of extinc- tion of the resistant strain. We develop a stochastic model of drug-resistance integrating socioeconomic growth in population to study the dynamics of extinction of resistant strain in the community, where it competes with the existing sensitive strain. We analytically derive the extinction threshold from the stochastic model using the multi-type branching process theory and obtain conditions for pathogen ex- tinction or persistence in population. Using numerical simulations, we compute the extinction probability, which shows a good estimate of values obtained from the branching process. Sensitivity analysis of the model also identifies parameters that have the most impact on the extinction of the strains. Although the transmission potential of respective strains plays a major role in extinction, our results illustrate that higher income, awareness, lower antibiotic use may increase the chance of extinction significantly by lowering antibiotic misuse. These analyses are beneficial to health policy makers and may quantify some parameters which are important to control the situation.

  6. Björn Vessman (POPD)

    University of Lausanne
    "A theoretical investigation of artificial community selection methods"
    Our lab studies small bacterial communities that degrade polluting industrial waste fluids. While our standard species combination can degrade some 40% of the pollutants, we hypothesize that a) the community could improve over time and b) that combinations with other species may be even more efficient. We now ask whether we can assemble and breed new communities with improved degradation efficiency. Previous attempts to experimentally select for community functions, such as host phenotypes and degradation or production of certain chemicals, have shown mixed results. Fundamentally, the experimental design needs to maintain a variance in the community function and ensure that the trait that forms the basis of the function is inherited between transfers. Further, the selection method should reduce conflicts between different species and the conflict of interest between population growth and community functions, while avoiding cheater phenotypes and inadvertent selection for biomass yield. Two main experimental designs have so far been used for experimental community selection. We evaluate and compare these, and a new method that we propose, by developing theoretical models and computational simulations of the selection methods. Our first results have given us a basal understanding of how the different selection methods work on a community level. Further, the simulations show that our proposed design can explore different species combinations to select for pollutant degradation among small communities. In addition, mutations and possible mixing between communities introduce the variance between communities that allows for evolution in the long term. We now explore how robust the results are to model assumptions. Our study can aid the design of future artificial community selection experiments, and contribute to our fundamental understanding of multi-level selection.

  7. Bryce Morsky (POPD)

    University of Pennsylvania
    "Evolution of contribution timing in public goods games"
    Life-history strategies are a crucial aspect of life, which are complicated in group-living species, where pay-offs additionally depend on others’ behaviours. Previous theoretical models of public goods games have generally focused on the amounts individuals contribute to the public good. Yet a much less-studied strategic aspect of public goods games, the timing of contri- butions, can also have dramatic consequences for individual and collective performance. Here, we develop two stage game theoretical models to explore how the timing of contributions evolves. In the first stage, individuals contrib- ute to a threshold public good based on a performance schedule. The second stage begins once the threshold is met, and the individuals then compete as a function of their performance. We show how contributing rapidly is not necessarily optimal, because delayers can act as ‘cheats,’ avoiding contributing while reaping the benefits of the public good. However, delaying too long can put the delayers at a disadvantage as they may be ill-equipped to compete. These effects lead to bistability in a single group, and spatial diversity among multiple interacting groups.

  8. Caren Barceló (POPD)

    "Projecting the time scale of initial increase in fishery yield after implementation of marine protected areas"
    Marine protected areas (MPAs) are being implemented globally to achieve conservation goals and benefit fisheries. However, MPAs require adaptive management to determine whether they are meeting their stated goals. This requires projection of the timing of increased performance after MPA establishment. Analyses of the projection of abundance and biomass have identified the information required and the expected timelines for meeting conservation goals. Projection of fishery yield, is more complex because it involves uncertain larval connectivity and the way in which the fishery is managed. Here, we develop a two-patch model with age structure represented by a renewal equation model to understand and to project the initial timing of the increase in fishery yield from larvae exported outside the MPA. By convolving a species-specific recruitment index with a yield-per-recruit equation, we are able to derive a yield function and yield timescale for each species. A key result is that the projection of yield is a weighted moving average of the larval production due to the projected MPA biomass, with the weightings being the age reversed age distribution of yield. Notably, this links MPA management to fishery management. Yield projection differs from the projection of MPA biomass in the sense that it depends on an uncertain factor due to uncertain connectivity. We demonstrate this mechanism with life histories of 16 harvested species found along the Pacific coast of the United States. The lag between the time of peak biomass within the MPA and the time that the increased fishery yield reaches its maximum depends on the pattern of the contribution to yield at each age. This age distribution of yield in turn depends on the age-dependent patterns of growth, natural mortality, and harvest. For the 16 species we considered, that lag ranged from 7 to 16 years. This general model and the range of exemplary species provide broadly applicable general guidance for this important emerging aspect of fisheries management.

  9. Christopher Carlson (POPD)

    University of Pennsylvania
    "Partner Specificity in Mutualisms"
    Mutualistic species vary in their level of partner specificity; yet, the evolutionary mechanisms which underpin partner specificity and generalism are not yet fully understood. One factor which may underpin variation in specificity is the degree of antagonism/cooperation in the relationship between hosts and symbionts. It is possible that mutualist hosts cooperatively specialize, maximizing mutual symbiotic benefit with a preferred symbiont, or antagonistically specialize, maximizing resource extraction from a preferred symbiont. Specialization in a preferred symbiont reduces the benefit of association with non-preferred symbionts, while generalists receive similar benefit from all symbionts. Here, we employ evolutionary game dynamics and adaptive dynamics in order to assess the evolutionary stability of cooperative specialization, antagonistic specialization, and generalism. When hosts specialize cooperatively, our system is bistable, favoring one of the specialist hosts and its preferred symbiont. When hosts specialized antagonistically, host and symbiont frequencies cycle continuously when average specialist payoff is greater than average symbiont payoffs. Higher average generalist payoff causes generalism to be an evolutionary stable strategy. Cooperative specialization unilaterally favors greater cooperation between specialist hosts and preferred symbionts, while antagonistic specialization leads to an evolutionary arms race in which symbionts attempt to escape host exploitation. We conclude that the cooperation-antagonism continuum which exists in mutualisms may play a key role in determining the pattern of partner specificity which develops within mutualistic relationships.

  10. Connah Griffith Michael Johnson (POPD)

    University of Warwick
    "Developing a computational tool for multiscale simulations of chemically coupled cell populations"
    Many biological systems are spatially organised, from animals and plants to microbial communities. Mathematical modelling can help us improve our understanding of, and design better-informed experiments to probe, the dynamics of such systems. The development of computational tools for modelling spatially organised biological systems has largely focused on either so-called agent-based models or on physico-chemical models based on partial differential equations (PDEs) Agent-based models can readily incorporate cell-specific properties such as speciation, cell cycle dynamics, and replication. However, these models typically allow limited spatial resolution for chemical dynamics, have a high computational cost, and can be affected from user-implementation choices, such as the chosen sequence of simulation updating rules. In contrast, PDE-based models allow a much finer grained simulation based on densities of state variables and are well suited to simulations based on physical properties, geometry, mechanical motion, and chemical reactions; however, cell-specific attributes cannot be readily incorporated in these models. Here, we combine the benefits of agent-based and PDE models, by extending an existing software library, Chaste, to allow coupling between agent-based and PDE models. Chaste is a modular, open-source PDE solver platform that is widely used by the systems biology community already. It utilises finite element solvers to simulate individual reaction-diffusion equations, coupled to a mesh-based layer that defines structures acting as chemical sources or sinks. These PDE solvers may be solved across a mutable mesh embedded with a wide range of cell-based modelling paradigms with easily customisable modular cell behaviours, aspects enhanced when compared to similar softwares. Here, we expand this CHASTE functionality to allow the simulation of complex reaction-diffusion dynamics with multiple PDE variables and multiple cell structures. The resulting system will allows us to model and simulate multicellular systems coupled through any number of shared or communicated chemicals. As such, the new system will be suitable to study the dynamics of biological systems such as bacterial biofilms. In our own work, we aim to use this extended CHASTE platform to simulate early evolution of protocellular metabolic systems, in particular, reaction systems that are separated across cell-like phase separations in an otherwise homogenous primordial soup. Spatial dynamics in such early metabolic systems have not been considered to date and it will be interesting to characterise what kind of system dynamics can emerge under different parameter regimes of metabolite diffusion, phase dynamics, and reaction kinetics.

  11. Dominic Brass (POPD)

    UK Centre for Ecology and Hydrology
    "Phenotypic plasticity as a cause and consequence of population dynamics"
    Predicting how species respond to dynamically changing and novel environments is crucial for guiding conservation and mitigation strategies. Phenotypic plasticity is a mechanism of trait variation demonstrably important in determining how individuals and populations adapt to environmental change. The effects of phenotypic plasticity can be quantified in individuals by measuring environment-trait relationships, but it is often difficult to predict how phenotypic plasticity affects populations from environment-trait relationships alone. Variation in the life-history traits expressed by individuals may alter population processes, and this in turn can feedback to induce further variation in the traits expressed by individuals. This means the assumption that environment-trait relationships validated for individuals are representative of how populations respond to environmental change risks mischaracterising the effect of environmental change on populations. Predicting the effect of phenotypic plasticity on populations necessitates the development and utilisation of specialised predictive tools able to integrate empirically verified mechanisms of trait variation into a population's dynamical processes. We have derived a novel general mathematical framework linking trait variation due to phenotypic plasticity to population dynamics which we apply to the classical example of Nicholson's blowflies. This application reveals a rich set of counter-intuitive population-dynamical behaviours and highlights how seemingly sensible predictions about how environment-trait relationships generalise to population responses break down in the context of a populations dynamical processes. Our results demonstrate the importance of the interplay between phenotypic plasticity and population dynamics and the need to account for the effects of trait variation when making predictions about population responses to environmental change.

  12. Easton R. White (POPD)

    University of Vermont
    "Catastrophes and socio-ecological systems"
    Amid global pandemics and climate change, it is clear that coupled models of human and environmental systems are needed. These socio-ecological models have been used to understand fisheries, disease spread, and deforestation. These models have only recently been used to understand how human actions and behavior affect coral reef fisheries, with a focus on shifts to alternative stable states. We extend this work to study the effect of catastrophes, e.g. hurricanes, on these systems. We show the conditions necessary for long-term coral reef health with fishing. We also examine the effect of the disturbance regime (timing, magnitude, type) on the overall system dynamics. These results both advance our understanding of catastrophes and socio-ecological systems as well as point to ways to build fisheries that are robust to rare events.

  13. Enrico Sandro Colizzi (POPD)

    Origins Center; Leiden University
    "Evolution of multicellularity driven by emergent collective migration"
    The evolution of multicellularity is a major evolutionary transition: individual cells give up their reproductive autonomy to form aggregates. Aggregation evolves because it can confer a fitness advantage over unicellularity, e.g. because of protection from predators, functional specialisation or because aggregates can respond to environmental cues unavailable to single cells. These aggregate-level properties arise from cell-cell interactions, and determine the evolutionary course of the cells by imposing novel selection pressures. Thus, the evolutionary feedback between cell interactions and group-level properties is at the root of the evolution of multicellularity. We explore the emergence of multicellular aggregates in a computational model where a population of cells searches for resources by chemotaxis in a spatially and temporally noisy gradient. Cells can evolve their adhesion to one another, and are selected on a cell's distance from the source of the gradient as a proxy for the availability of resources. We show that undifferentiated multicellularity evolves because cell aggregates perform collective chemotaxis more efficiently than single cells. A unicellular strategy based on efficient dispersal (rather than collective movement) can also evolve when environmental changes occur frequently. We find that both strategies prevent the invasion of the other through interference competition. We conclude that collective behaviour can be an emergent driver of the evolution of adhesion - and therewith undifferentiated multicellularity.

  14. Felipe E M Campos (POPD)

    University of São Paulo
    "A modelling approach to study landscape effects on abundance from patch demographic processes"
    Biodiversity loss is one of the great challenges to be faced by the current and the future generations. Habitat loss and fragmentation are important sources of concern. A recent debate over the effects of habitat fragmentation on biodiversity led to contradictory results. Some argue that habitat fragmentation has profound negative effects on biodiversity, while others challenge this view and advocate that those effects are usually negligible and mostly positive when significant. One source of disagreement comes from the scale of investigations made so far. Initial studies investigated the patch-scale mechanisms by which habitat fragmentation affects biodiversity and generally supported negative effects, for example by means of edge effects, vulnerability of small populations to stochasticity, etc. Recently, however, studies seeking a landscape-scale pattern of how habitat fragmentation impacts biodiversity failed to reach consistent results. This apparent contradiction between mechanisms and observed pattern highlighted the need for mechanistic understanding on how patch-scale mechanisms lead to landscape-scale patterns. In this study we link patch-scale mechanisms to landscape-scale abundance patterns by means of a patch model consisting of a system of ordinary differential equations. The equations describe the populations of the patches, which are interdependent and affected by four basic demographic processes: births, deaths, immigration and emigration. We promote the link between scales by deriving an insightful expression for the landscape equilibrium abundance and a necessary and a sufficient condition for landscape extinction, all of them integrating the demographic processes of all patches. As a second step, we sought to describe birth, death, immigration and emigration rates in terms of characteristics of the patches, like patch areas and inter-patch distances. This translates our landscape equilibrium abundance expression and extinction conditions in terms of landscape traits commonly used in Landscape Ecology, like habitat amount (sum of the areas of all patches) and landscape configuration metrics (functions of the traits of all patches). We use data collected from an Individual Based Model (IBM) to illustrate each of the steps of this study.

  15. Femke Thon (POPD)

    Bielefeld University
    "Modeling intraspecific chemodiversity - theory and first results"
    Explaining the causes and effects of different types of diversity is one of the key research missions in ecology and evolutionary biology. Plants produce numerous metabolites. There is a great diversity of metabolites between species, populations, and members of the same population. This chemodiversity has numerous ecological and economic implications. However, the mechanisms which maintain chemodiversity are still largely unknown. A theoretical framework is needed as a first step to bridge this gap in evolutionary knowledge. The goal of this project is therefore to develop mathematical and computational models linking genes, enzymes, metabolites, and ecological interactions to start building a theoretical framework for the evolutionary emergence and maintenance of plant chemodiversity. The screening hypothesis postulates that plants developed a set of biosynthetic pathways in which a great number of metabolites can quickly evolve. The more metabolites there are, the more likely it is that some have a defensive role against herbivores. Additionally, in existing models for the maintenance of other types of diversity, different types of negative frequency-dependent-selection (NFDS) frequently play an important role. In this project, we develop models based on the screening hypothesis and NFDS to investigate whether these hypotheses can explain how observed chemodiversity may have evolved and may be maintained. We will work together closely with empiricists to produce models which can be used to predict possible and empirically testable evolutionary pathways for model species based on realistic assumptions about these species. In the first phase of the project, we develop an individual-based model of a plant population and implement it in C++. This model includes a submodel of the biosynthetic pathways which determine the metabolites each individual produces. In the pathway, a primary metabolite is modified by various enzymes. The coding and regulatory genes for these enzymes evolve through mutation, gene duplication, and gene loss. The resulting metabolite(s) determine the fitness effects of each individual genotype. On my poster, I will present the evolutionary thought behind the model and the results from the first phases of the implementation.

  16. Fernando Luiz Pio dos Santos (POPD)

    "Investigation of the Aedes spread using a reaction-diffusion mathematical model"
    In this work, we developed a reaction-diffusion mathematical model to describe the spread of dengue infection in a two-dimensional computational domain. We aimed to understand how the disease spreads from a specific location to another, considering the diffusion coefficients of both infected populations, mosquitoes, and humans. Our contribution provides an in-depth analysis of the optimal control problem and it outlines a more explicit modeling framework based on real spatial-temporal data. São Paulo Research Foundation (FAPESP), grant 2018/03116-3.

  17. Jack M Hughes (POPD)

    "Thermodynamic Inhibition in a Biofilm Reactor with Suspended Bacteria"
    We formulate a biofilm reactor model with suspended bacteria that accounts for thermodynamic growth inhibition. The reactor model is a chemostat style model consisting of a single replenished growth promoting substrate, a single reaction product, suspended bacteria, and wall attached bacteria in the form of a bacterial biofilm. We present stability results for the washout equilibrium and conduct a computational study. While stability conditions are similar to a chemostat model, we find that the steady-state concentration of the replenished substrate depends on its inflow concentration. In the computational study, we find that thermodynamic inhibition limits substrate utilization/ production both inside the biofilm and inside the aqueous phase, resulting in less suspended bacteria and a thinner biofilm.

  18. Jorge Arroyo-Esquivel (POPD)

    Department of Mathematics, University of California Davis
    "Spatial dynamics and spread of ecosystem engineers"
    Ecosystem engineers are organisms characterized by interacting with other organisms thorough physical modifications of modifying their habitat. Examples of ecosystem engineers include Spartina alterniflora cordgrass or the zebra mussel Dreissena polymorpha. For both of these, the effect of modifying the environment can be non-local, affecting other regions farther away from the region populated by the ecosystem engineer. This shows the importance of understanding the population dynamics of ecosystem engineers in a spatial context. To do this we have developed the simplest spatially explicit model possible of ecosystem engineers, incorporating two local populations. We use this model to understand the relationship between dispersal and engineering effects, both at local and regional scales. Our main result is that the delayed Allee effect induced in the nonspatial model is extended to the spatial model, so the spread dynamics of an ecosystem engineer can be similar to the Allee case. However, there are more complex possibilities due to the effect of the environment modification.

  19. Kathyrn R Fair (POPD)

    University of Guelph
    "Spatial Structure in Protected Forest-Grassland Mosaics: Exploring Futures Under Climate Change"
    In mosaic ecosystems, multiple land types coexist as alternative stable states exhibiting distinct spatial patterns. Forest-grassland mosaics are ecologically valuable, due to their high species richness. However, anthropogenic disturbances threaten these ecosystems. Designating protected areas is one approach to preserving natural mosaics. Such work must account for climate change, yet there are few spatially-explicit models of mosaics under climate change that can predict its effects. We construct a spatially-explicit simulation model for a natural forest-grassland mosaic, parameterized for Southern Brazil. Using this model, we investigate how the spatial structure of these systems is altered under climate change and other disturbance regimes. By including local spatial interactions and fire-mediated forest recruitment, our model reproduces important spatial features of protected real-world mosaics, including the number of forest patches and overall forest cover. Multiple concurrent changes in environmental conditions have greater impacts on tree cover and spatial structure in simulated mosaics than single changes. This sensitivity reflects the narrow range of conditions under which simulated mosaics persist and emphasizes their vulnerability. Our model predicts that, in protected mosaics, climate change impacts on the fire-mediated threshold to recruitment will likely result in substantial increases in forest cover under Representative Concentration Pathway (RCP) 8.5, with potential for mosaic loss over a broad range of initial forest cover levels. Forest cover trajectories are similar until 2150, when cover increases under RCP 8.5 outpace those under RCP 2.6. Mosaics that persist under RCP 8.5 may experience structural alterations at the patch and landscape level. Our simple model predicts several realistic aspects of spatial structure as well as plausible responses to likely regional climate shifts. Hence, further model development could provide a useful tool when building strategies for protecting these ecosystems, by informing site selection for conservation areas that will be favourable to forest-grassland mosaic under future climates.

  20. Lauren Mossman, Kylie Landa (POPD)

    St.Olaf College
    "Phage-antibiotic synergy inhibited by temperate and chronic virus competition"
    As antibiotic resistance grows more frequent for common bacterial infections, alternative treatment strategies such as phage therapy have become more widely studied in the medical field. While many studies have explored the efficacy of antibiotics, phage therapy, or synergistic combinations of antibiotics and phage, the impact of virus competition on the efficacy of antibiotic treatment has not yet been considered. Here, we model the synergy between antibiotics and two viral types, temperate and chronic, in controlling bacterial infections. We demonstrate that while combinations of antibiotic and temperate viruses exhibit synergy, competition between temperate and chronic viruses inhibits bacterial control with antibiotics. In fact, our model reveals that antibiotic treatment counterintuitively increases the bacterial load when a large fraction of the bacteria develop antibiotic-resistance.

  21. Laurie Balstad (POPD)

    St. Olaf College
    "Parasite intensity influences evolution of migratory behavior via migratory escape"
    Migration can allow individuals to escape parasite infection, which can lead to a lower infection probability (prevalence) in a population and/or fewer parasites per individual (intensity). Since individuals with more parasites often have lower survival and/or fecundity, infection intensity shapes the life-history tradeoffs determining when migration is favored as a strategy to escape infection. Yet, most theory relies on susceptible-infected (SI) modeling frameworks, defining individuals as either healthy or infected, ignoring details of infection intensity. Here we develop a novel modeling approach that captures infection intensity as a spectrum, and ask under what conditions migration evolves as function of how infection intensity changes over time. We show that the relative timescales of migration and infection accumulation determine when migration is favored. We also find that population-level heterogeneity in infection intensity can lead to partial migration, where less-infected individuals migrate while more infected individuals remain resident. Our model is one of the first to consider how infection intensity can lead to migration. Our results frame migratory escape in light of infection intensity, rather than prevalence, thus demonstrating that decreased infection intensity should be considered a benefit of migration, alongside other typical drivers of migration.

  22. Lee Altenberg (POPD)

    University of Hawaii at Manoa
    "Spectral Graph Theory in the Analysis of Biological Evolution"
    Weighted graphs can be used to model biological evolution under natural selection and mutation: vertices correspond to genotypes, edges correspond to mutation from one genotype to another, vertex weights correspond to fitnesses, and edge weights correspond to mutation rates. Weinberger, Stadler, Grover and others have used Fourier decompositions of the vertex weights in terms of the eigenvectors of the edge weights, in order to characterize the 'ruggedness' of these 'adaptive landscapes'. This Fourier analysis has been used to characterize random walks on the graphs. But it has not been used in the actual evolutionary population dynamics under selection and mutation. Here we find that the original spectral graph results of Collatz and Sinogowitz (1957) appear as a lower bound on the asymptotic mean fitness of the population, and the spectral gap of the mutation matrix appears in an upper bound. This reveals an intimate connection between robustness of a population to mutation and the relaxation times of population perturbations due to mutation.

  23. Luana Tais Bassani (POPD)

    Universidade de São Paulo
    "Basic sanitation's role over breeding sites maintenance for Aedes aegypti development during rain absence according to a fuzzy rule-based system"
    Basic sanitation refers to the set of services, infrastructures, and operational installations for the supply of drinking water, sanitary sewerage, and management of solid waste. A precarious basic sanitation service contributes to the spreading of water-diseases. The delimitation of the urban and rural areas supports the public policies of sanitation investment and vector-borne control. In continental land sized countries like Brazil, this categorization has the influence of subjective aspects from peri-urban areas. When we evaluate sanitation system efficiency, we take into account that the total population services matter, which helps to understand and avoid frontier region border diseases that can potentially spread to urban regions and cause outbreaks. Recent episodes of Aedes aegypti related diseases in Brazilian regions that used to be immune, due to the geographic location and severe winters, shows that Brazilian public health is not prepared to deal with Aedes aegypti development. We propose a fuzzy rule-based system to measure the influence of sanitation and rain lack over the Aedes aegypti population dynamics. The system entries are fuzzy sets that involve four linguistic variables, which are the percentage of the urban population, as well as the percentage of served population by water supply, frequents solid waste collection, and sanitary sewerage. We use real data disclosed by the Brazilian institutions IBGE and SNIS (Instituto Brasileiro de Geografia e Estatística - Brazilian Institute of Geography and Statistics; Sistema Nacional de Informações sobre Saneamento - Brazilian sanitation information system). The system output feeds a characteristic parameter, which aims to quantify the contribution attributed to the basic sanitation of the city on the maintenance of breeding sites of Aedes aegypti during periods without rain. The fuzzy system provides a value that represents a parameter, which we couple to the age and stage-structured population projection matrix model for Aedes aegypti. A value closer to 0 means that the sanitation panorama of the city is ideal, and the Aedes aegypti population development is limited, according to lower precipitation periods. Spite of the slow development due to the water sources' lack, it is sensitive to temperature and individuals' age. Through the model, basic sanitation plays a role over stimuli for the quiescent egg, and mortality of larva and pupa during periods with a few precipitation millimeters episodes. Through this analysis, we are forecasting population dynamics fluctuations in drier periods, which is highly influenced by basic sanitation in municipalities that offer precarious sanitation services.

  24. Lucy Lansch-Justen (POPD)

    Instituto Gulbenkian de Ciência
    "Evolutionary rescue from mutational meltdown"
    Mutagenic drugs are promising candidates for the treatment of various RNA virus infections. By increasing the mutation rate of the virus they lead to rapid accumulation of deleterious mutation load, which is proposed to ultimately result in extinction as described by the theoretical concepts of mutational meltdown and lethal mutagenesis. However, the conditions and potential mechanisms of viral escape from the effects of mutagenic drugs have not been systematically explored. Here we investigate the population dynamics and genetics of a population under high mutation rates and discuss the probabilities of evolutionary rescue by means of three mechanisms: (1) “traditional” beneficial mutations increasing growth/fitness, (2) a mutation rate modifier (i.e., evolution of resistance), and (3) a modifier of the distribution of fitness effects, which either dampens or increases deleterious effects (i.e., evolution of tolerance). We investigate extinction times and we find that successful rescue mutations have to appear early to compensate the increasing mutational load. However, the observed stochasticity of rescue, especially by means of tolerance, highlights potential dangers of the use of mutagenic treatments that are almost impossible to capture in experimental trials. Supervisor: Claudia Bank Co-author: Mark Schmitz

  25. Mauro Mobilia (POPD)

    "Population Dynamics in a Changing Environment: Random versus Periodic Switching"
    Environmental changes greatly influence the evolution of populations. In this talk, we discuss the dynamics of a population of two strains, one growing slightly faster than the other, competing for resources in a time-varying binary environment modelled by a carrying capacity that switches either randomly or periodically between states of resources abundance and scarcity. The population dynamics is characterised by demographic noise (birth and death events) coupled to the fluctuating population size. By combining analytical and simulation methods, we elucidate the similarities and differences of evolving subject to stochastic and periodic switching. We show that the population size distribution is generally broader under intermediate and fast random switching than under periodic variations, with periodic changes leading to an abrupt transition from slow to fast switching regimes. The fixation probability under intermediate/fast random and periodic switching can hence vary significantly, with markedly different asymptotic behaviours. We also determine the conditions under which the fixation probability of the slow strain is maximum when the dynamics is driven by asymmetric switching. If time permits, I will outline how our methodology also allows us to analyse the complex eco-evolutionary dynamics arising when the slow strain produces public goods benefiting the entire population.

  26. Nicole Althermeler (POPD)

    Bielefeld University
    "Ancestral lines under selection for multiple sites: Pruning the Ancestral Selection Graph"
    Understanding ancestral processes under selection and mutation is among the fundamental challenges in population genetics. An important concept here is the ancestral selection graph (ASG) extracted from the Moran Model. This is, however, difficult to handle, both analytically and computationally, if two or more sites (that is, gene loci or sequence sites) are considered. Here a computational approach to pruning the ASG in the case of M sites is presented. The basic idea explores any incoming selective arrow, putting a hold onto the previously-active line. Should the incoming line be determined to be the ancestral line, it becomes the new active line and the previously-active line is dismissed. The set of types (that is, haplotypes or alleles) can be modelled in terms of sequences s ∈ {0, 1}M or fitness classes w ∈ {0,..,M}. The pruning procedure so far takes advantage of using sequences, but may be adjusted to fitness. Some preliminary results for different mutation and selection parameters and the resulting mutation process on the ancestral line are presented. This is joint work with Ellen Baake.

  27. Paweł Klimasara (POPD)

    University of Information Technology and Management in Rzeszów, University of Silesia in Katowice
    "A Savanna Dynamics Model"
    Savannas are mixed woodland-grassland ecosystems that cover fifth of Earth’s land surface. They are characterised by a continuous grass layer and a discontinuous layer of woody plants. In understanding complex savanna dynamics of main interest is the question how do trees and grasses co-exist without one dominating the other? Amongst possible explanations there has been recognized that disturbances like fires or browsing and grazing may play fundamental role. There is quite rich literature on models of tree-grass coexistence in savannas with such non-equilibrium approach. From the mathematical point of view models containing many different factors often lack formal stochasticity and their analysis is usually based on numerical simulations. Moreover, another important determinant of savanna structure - water availability - is of less unpredictable nature following seasonality. Most of the plants growth happens during wet seasons while large amounts of dry grasses additionally support fires during dry seasons. These effects usually are not directly included in existing models of savanna dynamics. We introduced two minimalistic models of tree-grass coexistence driven by fire disturbances. We provided careful mathematical analysis of appropriate piecewise deterministic Markov process and showed the existence of a unique stationary distribution of tree and grass biomasses using the tools of stochastic semigroup theory. Continuing this approach we work on analytic results for more realistic setting including the seasonality via its effects on plants growth rate as well as a probability of occurrence and intensity of fires. Moreover, we want to include in the final model also grazing and browsing effects (similarly to the one provided in (6) but along with seasonality).

  28. Pijush Panday (POPD)

    Indian Statistical Institute
    "Dynamical behaviour of a stage-structured predator-prey model by incorporating cost and benefits of group defense"
    In predator-prey theory, the predator can affect on prey population by the killing of the prey and by causing predation fear on the prey population. The prey population also adjusts some behavioral approaches to reduce their predation risk which may influence their long term survival. In the present study, we formulate a predator-prey model dividing the prey population into two stages: juvenile and adult. We assume that when adult preys are sensitive to predation, they adapt group defense as an anti-predator strategy to lower their predation risk. To include group defense in the adult prey population, we consider Holling type IV functional responses for adult prey and predator interaction. But group defense has a negative effect by decreasing their reproduction potential. A parameter predator-taxis sensitivity introduces to interlink benefits of group defense and its costs. Increasing predator-taxis sensitivity also increases the group defense level of adult preys and benefits them by lowering predation risk. But also causes a detrimental effect by decreasing their reproduction rate simultaneously. We study some mathematical properties such as positivity, boundedness, local stability of equilibrium points, and bifurcation behaviors of the model. Our result suggests that the maturation rate can destabilize the system by producing oscillatory coexistence. For higher maturation rate the predator population suddenly extinct from the system, where oscillatory coexistence may disappear and the system becomes stable around the predator-free state. We also observe that predator-taxis sensitivity enhances the destabilizing nature of the system. However, for increasing the level of fear, the destabilization vanishes and the system shows stable behavior. It is also observed that predator- taxis sensitivity can be beneficial for adult prey as their density may increase with increasing the values of predator-taxis sensitivity. We also notice that above a threshold value of predator- taxis sensitivity the system shows bistable behavior. Our fear-induced stage-structured model exhibits interesting and rich dynamical behaviors.

  29. Renato Antunes Costa de Andrade (POPD)

    University of Glasgow
    "Persistence of intraguild predation in a 1D finite domain using variational approximations"
    Fragmentation of the natural landscapes due to human activity has an undeniable undeniable eundeniable effect over the wildlife. The most known example being deforestation and the subsequent extinction of forest inhabiting species. In this context, a natural question to ask is: what is the minimum habitat size that allows for (co)existence of the species living in a given environment? The work described here then sought to address this inquiry for the particular case of 3 ecologically interacting species: a prey, its predator and a common resource. A system known as an intraguild predation module. We proposed and studied a model consisting of 3 coupled reaction-di_x000B_usion partial differential equations. In addition to numerical simulations, we used a method of approximation based on variational principles capable of providing analytical estimates for critical habitat sizes for the coexistence of the species involved in the proposed model. life. The most known example being deforestation and the subsequent extinction of forest inhabiting species. In this context, a natural question to ask is: what is the minimum habitat size that allows for (co)existence of the species living in a given environment? The work described here then sought to address this inquiry for the particular case of 3 ecologically interacting species: a prey, its predator and a common resource. A system known as an intraguild predation module. We proposed and studied a model consisting of 3 coupled reaction-diffusion partial differential equations. In addition to numerical simulations, we used a method of approximation based on variational principles capable of providing analytical estimates for critical habitat sizes for the coexistence of the species involved in the proposed model.

  30. Renier G Mendoza (POPD)

    "Explicit solution of an age-structured model using a generalized Lambert W function"
    Structured population models, which account for the state of individuals given features such as age, gender, and size, are widely used in the fields of ecology and biology. In this paper, we consider an age-structured population model describing the population of adults and juveniles. The model consists of a system of ordinary and neutral delay differential equations. We present an explicit solution to the model using a generalization of the Lambert W function called the r-Lambert W function. The r-Lambert W function, denoted Wr(a), is a function satisfying Wr(a)e^(W_r(a))+rWr(a)-a=0, where a is a nonzero complex number and r is a real number. Numerical simulations with varying parameters and initial conditions are done to illustrate the obtained solution.

  31. Román Zapién-Campos (POPD)

    Max Planck Institute for Evolutionary Biology
    "When timescales meet: Microbiome dynamics is influenced by hosts’ life-history."
    Microbial life is highly abundant in the biosphere. Macroscopic lifeforms are no exception. We harbor a large number of microorganisms in different parts of our bodies, often referred to as the microbiome. What separates us from abiotic habitats is that we undergo life-cycles. We have developed stochastic models to understand the consequences of host life-history on the ecology of the microbiome. Particularly, we focus on the effect of the host lifespan and initial microbiome. Our results point at the limits imposed by life-history, but also at the diverse dynamics, even in contexts free of selection at the level of microbes and hosts. Multiple reported experimental observations in organisms like nematodes, fruit flies, and zebrafish can be unified around colonization. These include the emergence and coexistence of alternative microbiome states, the persistence of microbe-free hosts, and the inconsistent occurrence of microbial types.

  32. Russell Milne (POPD)

    "Effects of Variation in Fishing Rate and Nutrient Loading on Coral Reef Health with Implications for Marine Protected Area Design"
    Coral reefs rank among the highest-biodiversity habitats in the world, hosting many fish and invertebrate species found nowhere else. Additionally, reef ecosystems generate billions of dollars in revenue annually for coastal communities via fishing and tourism. However, from the Caribbean to Australia, coral reefs are in decline worldwide. Causes of this include anthropogenic stressors such as overfishing and excess input of nitrogen and other nutrients. To evaluate the threats posed to reefs by these processes, I simulate reef dynamics using a mechanistic, spatially explicit model fit using field data. I find three major regimes: one where coral dominates with periodic algal blooms, one where coral and algae coexist, and one where coral is driven to extinction by algae, in order from lowest to highest fishing rates. For moderate fishing rates, both a healthy coral population and a profitable local fishing industry can exist. Also, establishing a marine protected area (MPA) with no fishing in 20 percent of the simulated area is enough to maintain the coral-dominant equilibrium in the rest of the system, even when fishing rates outside the MPA are very high. Decreasing nutrient input into the system can also shift it towards the coral-dominant equilibrium. The rates of nutrient loading at which regime shifts are predicted to occur vary nonlinearly with fishing rate.

  33. Sarah MacQueen (POPD)

    "Modelling the effects of site constancy in bumble bees"
    Foraging site constancy, or repeated return to the same location forage, is an important aspect of bumble bee behaviour, and should therefore be an important consideration when using modelling to predict the pollination services provided by bumble bees. However, it is unknown exactly how bumble bees select their foraging site, and most modelling studies do not account for this uncertainty. We used an individual based model to explore how predictions of pollination services and bee fitness change under different foraging site selection methods. Pollination services are measured as the percent of fields and number of flowers visited, and bee fitness is measured as the amount of different resource types collected and using behavioural budgets. We tested two different site-reconnaissance or searching methods (random and realistic exploration behaviour) and four different site- selection methods (random and optimizing based on distance from the nest, local wildflower density, or net rate of energy return), as well as comparing results on landscapes with different total amounts of resource and proportional amounts of crop. We found that site- selection methods have a greater impact on crop pollination services and bee fitness than do site-reconnaissance or landscape characteristics, indicating that the site-selection method is an important consideration when modelling bumble bee pollination services. In general, site-selection based on optimizing for the net rate of energy return leads to both the highest crop pollination services and the longest foraging trips. The percent of crop fields visited, amount of time spent foraging, number of foraging sites located in crops, and the number of flowers visited may be used to make hypotheses about how real bees select their foraging sites.

  34. Shota Shibasaki (POPD)

    University of Lausanne
    "Fluctuating environments affect the strength of species interactions and diversity in microbial communities similarly"
    Microorganisms live in environments that often fluctuate between mild and harsh conditions. Although such fluctuations are bound to cause local extinctions and thereby affect species diversity in microbial communities, it is still unknown (i) how species diversity changes over the rate of environmental fluctuations and (ii) how this relates to changes in species interactions. Here, we use a mathematical model to describe the dynamics of resources, toxins and species abundances in a chemostat where resource supplies switch between scarce and abundant. Over the majority of the explored parameter space, species compete with one another, but the strength of competition between species pairs changed over the switching rate in a pattern that depended on their sensitivity to toxins. When their toxin sensitivities were low, an effect of competition was highest at a low switching rate. At other toxin sensitivity values, competition was instead highest at intermediate or high switching rates. In communities of up to ten species, the strength of competition in species pairs was a good predictor for how community beta diversity changed over the environmental switching rate: diversity was lowest when competition was highest. This shows that an analysis of pairwise species interactions can be used to estimate how beta diversity changes over environmental switching rates. Our results also indicate that predicting how environmental switching affects communities is very difficult a priori, as it depends on the properties of its members, such as their tolerance to environmental toxicity. This may explain the contradicting results of some earlier studies on the intermediate disturbance hypothesis.

  35. Silas Poloni (POPD)

    Institute for Theoretical Physics- São Paulo State University
    "Intraguild Predation in Periodic Habitats"
    Fragmentation of natural landscapes is an ongoing process, mainly led by human activities, such as urban growth, roadway construction and farming. This phenomena may lead to many changes in the dynamics of populations that live in such landscapes, posing new challenges to our understanding of population persistence and diversity therein. One of the first approaches on how we may treat such problems mathematically was given by Shigesada in 1986, where a single population invading an infinite unidimensional habitat, composed of two types of patches layed on the real line alternately, is considered. Along that, theoretical aspects of how populations behave on the borders between different types of patches were developed, unraveling new classes of realistic boundary conditions for spatial ecology models, giving us new results and insights in this field. In this work we consider an Intraguild Predation (IGP) model, a community module composed of two consumers of a shared resource, with a predation relation between such consumers, usually referred as IG-Prey and IG-Predator. First we deal with invasions of both IG-Prey and IG-Predator in an homogeneous landscape, with either the resource established alone or together with the other consumer. Then, using Cobbold and Yurk's homogenization technique, we formulate and investigate the problem in a periodic habitat, composed of two types of patches where IGP relations are present, but allowed to have different parameters, such as less resource consumption, enhanced mortality or reduced resource productivity in one of the patches. Our results show that coexistence between IG-Prey and IG-Predator is possible within a range of resource productivity in homogeneous landscapes, being such range determined via analysis of the minimal speeds of invasion. In heterogeneous landscapes, with IGP being viable on both patches, we find that the necessary conditions for coexistence may be relaxed given certain movement behavior of both consumers and resource alike, whilst some configurations restrict such condition. We also explore how the ranges of coexistence in terms of resource productivity change with the sizes of the two habitat types considered, finding that such regions are also diminished or enlarged, depending on the movement behavior of the IGP populations.

  36. So Nakashima (POPD)

    "Lineage EM Algorithm for Inferring Latent States from Cellular Lineage Trees"
    A population of genetically identical cells is phenotypically heterogeneous. The heterogeneity is partially inherited over generations and can work as a bet-hedging strategy of the survival of the population under fluctuating environments. A typical instance of the bet-hedging strategy is the bacterial persistence. To understand such strategies, we need to identify the phenotypes of each cell and its inheritance. For this purpose, recent advancements in single-cell analysis and microfluidic devices offer us useful lineage data, though such data accommodate but do not explicitly show the phenotypic information of each cell. Several studies have attempted to overcome the difficulty by inferring the phenotypes from lineage data via latent-variable estimation. However, we must correct the bias caused by the growth of the population, which we call the survivorship bias, in the estimation. In this work, we characterize the survivorship bias and establish a correction method of the bias. Then, we propose an expectation-maximization (EM) type latent variable estimation, which we call Lineage EM algorithm (LEM). LEM is bias-free and applicable to various kinds of lineage data to characterize the phenotype of the cells. Finally, we apply LEM to a synthetic and a real lineage tree of E. coli and validate the performance.

  37. Tatiana Yakushkina (POPD)

    NRU Higher School of Economics
    "Modified Replicator Systems with Ecological DIversification"
    In this study, we construct new variations of replicator systems, which include experimentally observed properties of living systems. First, we analyze a quasispecies system with niche diversification and mutator effect. We examine the case with different fitness landscapes in the first and second habitats and migration flow between them. It is shown that such systems have rich phase structure, governed by the transition and mutation rates. Second, we focus on such modifications of classical models of microbiological evolution that include explicit specification on nutrition type. For the cases with one and multiple common nutrients, the evolutionary dynamics of the population is discussed.

  38. Vahini Reddy Nareddy (POPD)

    University of Massachusetts Amherst
    "Representing spatial ecological oscillators by dynamical Ising model with memory"
    Spatial synchronization in many biological systems are known to develop from short-range interactions of local oscillators. Locally-coupled ecological oscillators with noise and two-cycle behavior undergo a phase transition from incoherence to synchrony. These phase transitions exist in the Ising universality class, ensuring that the stationary properties of the ecological systems can be replicated by the simple Ising model. The universal properties shared by all the models in the universality class match that of the Ising model. Here we are interested in studying the dynamical properties shared between the ecological oscillators and the Ising model as synchronization is a dynamic phenomenon. We show that we need to go beyond the simple Ising model with nearest neighbor coupling and add a memory term to explain the tendency of local oscillators to maintain their phase of oscillations. We infer the Ising parameters using maximum likelihood methods by representing the ecological oscillators with the dynamical Ising model with memory. This correspondence to the dynamical Ising model is useful as it reveals that the spatial properties arise independent of local dynamics and the Ising parameters play a clear role in both understanding and predicting the dynamics of the ecological system. We study the location of phase transition in Ising parameter space and the ability of the dynamical Ising model to predict the future dynamics. We find that the simple dynamical Ising model is reasonable good at representing the ecological oscillators. This agreement between the dynamics of spatially-coupled ecological oscillators and the dynamical Ising model suggests the potential for simplification of many complex biological systems.

  39. Vandana Revathi Venkateswaran (POPD)

    "The effect of parental investment on immunocompetence and sexual immune dimorphism"
    Sexes of a species show different characteristics beyond the differences in their sex- ual organs; this is known as sexual dimorphism and applies to immunocompetence as well. Immunocompetence is the ability of an individual to mount an immune response when exposed to pathogens. Females are shown to have increased longevity that comes with higher immunocompetence as compared to males and this may also lead to an increased probability of autoimmune disease in females. However, for some species such as pipefishes and seahorses belonging to the Syngnathid family, studies show that the males have a higher immunocompetence. Experimental evidences suggest that this could be due to the fact that these males undergo pregnancy i.e. the males have brood pouches where the eggs are fertilized; the fathers provide oxygen and nutrition to their offspring until they give birth to the juveniles. Therefore, an increase in immunocompetence may also be related to the amount of parental investment. In this study, using state dependent life-history theory, we show that for most species systems it is optimal to invest more in immunocompetence when the time spent in parental investment is longer. Our findings also show that an increase in parental investment brings about an earlier immunosenescence i.e. the gradual deterioration of the immune system that occurs with aging. We observe that an increase in investment towards immunocompetence is more pronounced in short-lived species with long brooding periods whereas species with a longer lifespan allocate more reserves towards offspring production. Our model also accounts for intraspecies scenarios: if a sex spends a longer fraction of its reproductive season in pregnancy or brooding (as compared to the other sex), then we find that this sex would invest more towards immunocompetence.

  40. Vitor de Oliveira Sudbrack (POPD)

    "Population dynamics in highly fragmented landscapes"
    Human action fragments the natural habitat of several species all around the world. Understanding the effects of fragmentation to ecosystems is key to elaborate the best policies to avoid species extinctions. Therefore, it is important to study how the populations and ecosystems respond to these kinds of changes in landscapes. In this work, we use numerical methods to simulate reaction-diffusion equations in artificial landscapes generated with different structural distributions while keeping the total amount of habitat constant. This guarantees we are observing phenomena caused by fragmentation per se. We discuss the net effects of fragmentation into the steady total population. In order to do that correctly, we established the correlation between fragmentation metrics with fixed amount of habitat, to ensure that conclusions are not biased by interdependencies of metrics. We have also analytically calculated the critical size to allow population growth for bidimensional landscapes within our model, with given symmetries. These results prove that habitat area is not the only factor when it comes to population settling, and hence patch shape matters. Recent explorations on our model revel the presence of different movement scales, intra-patch and inter-patches. Future prospects of this project are studying how fragmentation affects features of population spatial distribution and investigations about regimes of fragmentation that allow non-interactive (or weakly interacting) subpopulations to form. We will also explore consequences of fragmentation to communities.

  41. Vivian Dornelas (POPD)

    "Impact of the landscape heterogeneity on the spatial organization of a single-species population"
    It is common to observe in nature the emergence of collective behavior in biological populations, such as pattern formation. In this work, we are interested in characterizing the distribution of a single-species population (such as some bacteria or vegetation), based on mathematical models that describe the spatio-temporal evolution of the density, governed by elementary processes, such as dispersion, growth, and nonlocal competition by resources. Using a generalization of the FKPP equation, we study the role that a heterogeneous environment has in the spatial organization of a population. We investigate the structures that emerge near the border from one environment to the other. We found that, depending on the shape of nonlocal interaction and other model parameters, three different profiles can emerge from the interface: sustained oscillations (or spatial patterns, without amplitude decay); attenuated oscillations (with amplitude decreasing from the interface); exponential decay (without oscillations) to a flat profile. We related the wavelength and the rate of decay of oscillations with the parameters of the interaction (characteristic length and form of decay with distance). We discussed how the heterogeneities of the environment allow access to information about the biological phenomena of the system, hidden in the homogeneous case, such as those that mediate competitive interactions.

  42. William (Bill) Sherwin (POPD)

    UNSW Sydney
    "Monitoring and Forecasting Diversity: Entropy Unifies Molecules and Ecosystems"
    At all scales from molecules to ecosystems, we measure biodiversity to indicate outcomes of natural changes or threatening processes, so that we can compare these with forecasts under various management schemes. Every biodiversity level has four basic processes – dispersal, adaptation, random change, and generation of novel ecosystems, species, or genetic variants. How can we exploit this similarity? Entropy is an obvious choice, being a general forecasting and measurement tool throughout science. It is also a simple transform of the biodiversity-measure ‘profile’: Richness; Gini-Simpson; and Shannon. Conservation managers mostly use Richness and Shannon for biodiversity measurement, and have some forecasts for MaxEnt (Shannon) and Simpson - so there is a mismatch between what is forecast and measured. In contrast, measures and forecasts in molecular ecology are now well developed for the entire profile of biodiversity-measures, within and between areas (Trends Ecol.Evol. 32:948). Shannon approaches outperform others in some important tasks, such as tracing rangeshift or invasion, and genetic estimates of dispersal for input to metapopulation models. Thus the stage is set to unify our monitoring and forecasting of these four processes that are common across all biodiversity levels, using a complete diversity profile that encompasses Richness, Shannon and Simpson. This will integrate well with the many entropic methods in studies of the physical environment.

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