Abstracts:  NVTB - Meeting  2004

How much of its resources should an individual invest in a costly immune system? In this presentation I apply an ESS analysis to an epidemic model to answer this question. On the one hand, an investment in immune function confers protection to infectious agents by reducing host susceptibility, pathogen virulence, or the length of the infectious period. On the other hand, an immune system is costly since it absorbs resources that otherwise might be invested in increasing the host's fertility or longevity. Moreover, an active immune system may be able to clear pathogens efficiently, but at the same time results in immunopathology. By means of a reproductive value approach, I show how to compare the costs and benefits of an immune system systematically, and how to derive the evolutionarily stable level of immune function. The methods are subsequently applied to various plausible scenarios. The analysis reveals that the relationship between the life span of an organism and the optimal level of investment in immune function is less straightforward than one might expect. First, members of a long-lived species do not necessarily have to invest more in immune function than those of a short-lived species. In fact, the opposite may be true. Second, the outcome of evolution can be contingent on the initial conditions. Depending on its initial investment strategy, a population may evolve to a state where very much or almost nothing is invested in a costly immune system.

RNA silencing is widespread among eukaryotes and can protect the eukaryotic cell against viruses and transposons. The introduction of double stranded viral RNA results in sequence specific degradation of the viral mRNAs. RNA silencing can also be triggered by the expression of transgenes: highly expressed transgenes can cause silencing of both the transgene and the homologous endogenous gene. We show with simple differential equation models that the intuitively plausible explanations proposed in the experimental and theoretical literature cannot work. We explore different biologically reasonable extensions of the model and find a mechanism by which all demonstrated silencing phenomena can be explained.

Large mammalian herbivores often face an environment with a heterogeneous distribution of resources. Since these herbivores have to eat, they have to move from one patch of resource to another. My research focuses on the behavioural strategies that herbivores can adopt to find enough of a scarce resource to survive. I will present a first simulation model that includes both naive strategies and strategies that are dependent on past experience.

The Escherichia coli lac operon is one of the most intensively studied genetic regulatory systems. Classically the lac operon is regarded as an AND gate: It's active when there's lactose AND NO glucose. Recent quantitative models of the lac operon adhere closely to this paradigm. However,recent experiments in the group of Alon show that the lac operon differs considerably from an AND gate. A consequence of this is suppression of hysteresis. Using a modified version of the available quantitative models, we study the evolutionary stability of the AND gate and show that the findings of Alon are to be expected.

The house sparrow (Passer domesticus) has shown a rapid decline in The Netherlands over the last decades. To analyse this decline we formulated matrix models based on available data. The dominant eigenvalue of these models is significantly less than one which is in agreement with the mean yearly growth based on the census data. Elasticity analysis indicates that an increase in survival in the first 6~months of life or fledgling production is the best option to mitigate this decline. Assessment of the elasticity of all possible parameter values for survival (i.e.\ values between 0 and 1) indicates a larger region where juvenile survival has a higher elasticity value than adult survival. On the basis of the elasticity analysis and the comparison with data of thriving populations we conclude that to abate the current population decline both juvenile survival in the first 6~months of life and adult survival should be increased.

Chemical risk assessment aims to protect the environment from negative effects, caused by hazardous compounds. In general, protecting the environment is synonymous with protecting populations of organisms. Because experimental testing of population consequences is not feasible, short-term laboratory testing is used as a surrogate. These standard toxicity tests do not allow extrapolations to the population level, mainly because they apply a short, fixed exposure time, and focus on a single endpoint only (e.g.\ survival, growth or reproduction). These limitations can be overcome by (partial) life-cycle toxicity testing, although the test results are harder to analyze. To understand how chemicals affect the life cycle, we first need to understand the organism’s development under non-exposed conditions. The theory of dynamic energy budgets (DEB) aims to describe individual organisms, based on a set of simple rules for metabolic organization. Effects of toxicants can be understood as a change in energetic parameters, like an increase in the maintenance costs or a decrease of the assimilation of energy from food. This insight inspired the development of DEBtox, a suite of models to analyze toxicity tests, implemented into a user-friendly software package. Currently, a project is running at our department, in cooperation with Wageningen University (department of Nematology), to make DEBtox suitable for life-cycle testing, and apply the model to experiments with nematodes. Several adaptations are necessary to apply these models to life-cycle tests: integrating the results for survival, growth and reproduction in a single analysis (because endpoints share common parameters), and describing the effects of ageing of the animals (senescence). The model fit on the life-cycle toxicity data allows for a calculation of the intrinsic rate of population increase, because effects on growth and reproduction of individuals will lead to effects on populations. As the analysis is process based, population responses for untested concentrations can be calculated, and effects under food limitation can be explored. This model-based strategy for chemical risk assessment will be illustrated in this presentation, using preliminary results from the project for nematodes.

The central metabolism of all organisms is rather similar, especially among eukarytes, with a centrol role for carbohydrates as internal energy source. I will discuss arguments for the hypothesis that this ''carbo-hydrate world'' was preceeded by a ''lipid world'', and that by a ''protein/DNA world'', and that by an ''RNA world''. This hypothesis also states that the external energy source was originally chemo-lithotrophy, followed by phototrophy, much later by heterotrophy and eventually by predation. The cellular metabolism evolved from loosely interacting metabolic subunits to more closely interacting ones; the metabolic relationschips among organisms followed a similar pattern. The lecture will discuss the various aspects in the context of the Dynamic Energy Budget theory. A paper on this topic can be download from http://www.bio.vu.nl/thb/research/bib/KooyHeng2004.html .

It has recently been shown that an Allee effect (positive density dependence at low population density) can occur in a population of a predator that is specialized on one stage of the life cycle of its prey, when the prey population is regulated by food- or density-dependent development. Through overcompensation in the prey regulation, feeding by the predator can increase the density of prey in the stage that it feeds on, thereby facilitating its own food source and creating an Allee effect. Alternatively, such a predator may increase the density of prey in other life stages. I study the interaction effect of two predators that each feed exclusively on one specific life stage of a shared prey population. I find that a predator feeding on the regulating (immature) prey stage can strongly increase the prey density for a predator feeding on adult prey, leading to greatly increased persistence of the adult predator. The facilitation is not mutual; the predator that feeds on the regulating stage can persist alone, and is always strongly reduced in density by the presence of the adult-specific predator. Our results add a new perspective to the discussion about coexistence of similar competitors. We show that within-species processes such as density dependent development can lead to unexpected and counterintuitive interactions at the community level.

Several aspects of global change, such as eutrophication with nitrogen, enhanced UV-B irradiation and elevated CO2 levels, have been shown to alter the composition of plant leaf material. As dead plant detritus forms the basal resource of soil decomposer food webs, it is to be expected that the structure and functioning of such systems will change in the time to come. We developed a dynamic model of a Scots pine soil food web near Wekerom (near Wageningen), suitable for studying elemental flows through this system. This ecosystem has been studied well empirically, which facilitated the description of the models trophic structures. We used the model to study the effect of changes in the composition of freshly fallen litter on the dynamics and functioning of the soil ecosystem. We used synthesizing units (SUs) to model multiple resource limitation of the lowest trophic groups. The model predicts that changes in litter composition affect the highest trophic groups (collemboles, enchytraeids, mites, nematodes) more than lower trophic groups (fungi, bactaria). No other dynamics than stable steady states occurred. The absence of oscillations and chaos may be attributed to the ubiquity of weak trophic interactions. We revealed a number of model parameters that need experimental validation. We conclude that collaborations between empiricists and theoreticians are essential for the understanding of ecosystem structure and functioning.

Most theory for character displacement and resource polymorphisms is developed either with models with a one-dimensional resource continuum or with Levins-type models with spatial resource heterogeneity. This is surprising since many systems of empirical research deal with discrete resources which are distributed in a fine grained manner. An exception is a one-locus two-allele model by Wilson and Turelli (1986) for a foraging related trait of a consumer in the presence of two discrete resources. Here we present an adaptive dynamics version of the model of Wilson and Turelli. In both models density and frequency-dependent fitness functions are generated from an explicit treatment of resource consumption and renewal. The presented model extends the model of Wilson and Turelli in several ways: (1) we derive the fitness function from a more detailed foraging model, (2) this gives us the opportunity to investigate the effect of several different trade-offs and (3) we include diet choice as a behavioral trait. The main result of Wilson and Turelli is, that stable polymorphisms can occur even with heterozygote disadvantage. This scenario corresponds to evolutionary branching points in our model. Whether evolutionary branching occurs, depends on the quality of the trade-off curve and the traits which are traded off. The incorporation of diet choice makes polymorphisms more likely. However, this does not happen at classical evolutionary branching points but at singular points where the fitness function is not differentiable.

Eigen has shown that there is a paradox in prebiotic evolution, the so called error threshold. The paradox is as follows: an accurate complex replication mechanism needs a large enough amount of information, and to maintain that much information a replicator needs the very mechanism of accuracy and complexity. Both need each other to emerge, and both are not likely to emerge at the same moment in single species replicators. As a solution to this paradox, Szathmary proposed compartmentalization of a replicator system in the so called Stochastic Corrector Model. In this model, stochasticity in the replicator dynamics and group selection enhance the coexistence of multiple species of replicators, and thus may facilitate the emergence of more complex replicators. However, the compartmentalization imposes limited diffusibility and small population size on the replicator dynamics, and both are known to reduce the information threshold and thus decrease the amount of information which can be maintained. Here, we study the overall effect of the compartmentalization on the error threshold of one single species. We made a comparison between a simple non-interacting self-replicator system with and without compartmentalization. We introduce a two dimensional two layer Cellular Automata model, in which replicators and compartments are explicitly represented and both dynamics are interwoven parallel in time and space. We set our models such that the dynamics of a vesicle depends on its replicator population in several ways. The simulation results showed that, in the case that the growth of a vesicle depends only on the total number of its replicators (not on the composition of its replicators), group selection was not strong enough to compensate the two other effects. Compartmentalization reduced the error threshold, and thus decreased the amount of information which can be kept in one species of self-replicators. The results also showed that the spatial pattern formation on the compartment level also reduced the error threshold, and the difference in the speed of dynamics between replicators and vesicles is a delicate key feature in the determination of error threshold.

In the literature, several methods are described to link data from single-species toxicity data to food-web models. Several approaches can be identified. Simple food chain models can be analyzed for perturbance due to toxicants, either in steady-state or dynamically. Another approach is to incorporate external dose-response functions from laboratory toxicity testing in the model, or alternatively, to model uptake, excretion and metabolism of the toxicant and link the concept of critical body residues to the food web model. A last type of approach is to incorporate species sensitivity distributions for functional groups in the model and use probabilistic modeling techniques to take full advantage of the knowledge on the variability of species sensitivity within functional groups, as known from toxicity data bases. The main difficulty in the evaluation of these models is that they have been built for a specific purpose and validation is performed in different settings. This presentation will illustrate the different types of approaches, identify the merits and limitations and their application in evaluating the effects of chemicals.

Severe Acute Respiratory Syndrome (SARS) has been the first severe contagious disease to emerge in the 21st century. Already early on in the epidemic, various affected regions made their epidemiological data available as epidemic curves: a histogram of the number of patients with onset of symptoms per day. However, inspection of such epidemic curves reveals little about when effective infection control measures were put in place and how effective they have been. We would like to estimate the reproduction number R, which is defined as the number of secondary cases per infective. This reproduction number R measures the transmission potential of an infectious disease, and the effectiveness of infection control measures in reducing transmissibility. We note that for infectious diseases with relatively short time interval between successive infections (like SARS) the shape of the epidemic curve can be directly related to the temporal pattern of reproduction numbers during the epidemic. The estimated time courses of reproduction numbers reveal that SARS epidemics in various affected regions are characterized by a markedly similar transmission potential of the disease, and a similar effectiveness of control measures. In addition, we note that it is possible to estimate the probability that one particular patient has infected another particular patient, using only time of symptom onset for those particular patients. This allows reconstruction of the transmission pattern of infectious diseases. We illustrate the scope of these methods for tracing back the origins of infection in observed outbreaks, using examples of influenza, smallpox, and SARS.

In contrast to classical models of speciation, many recent models come to the conclusion that speciation may be adaptive (i.e., driven by selection), rather than being contingent on external events (e.g., the emergence of barriers preventing gene flow). Two types of speciation models currently get much attention: ''sexual selection'' models explaining the evolution of assortative mating and ''ecological'' models explaining ecological divergence. We discuss the strengths and the weaknesses of both types of models, and we plead for a more integrated approach. By means of specific examples we demonstrate that fully adaptive speciation, driven by disruptive natural and sexual selection, is feasible. However, the conditions under which adaptive speciation may occur are far more restrictive than earlier models appear to suggest.