No Arabic abstract
The famous two-fold cost of sex is really the cost of anisogamy -- why should females mate with males who do not contribute resources to offspring, rather than isogamous partners who contribute equally? In typical anisogamous populations, a single very fit male can have an enormous number of offspring, far larger than is possible for any female or isogamous individual. If the sexual selection on males aligns with the natural selection on females, anisogamy thus allows much more rapid adaptation via super-successful males. We show via simulations that this effect can be sufficient to overcome the two-fold cost and maintain anisogamy against isogamy in populations adapting to environmental change. The key quantity is the variance in male fitness -- if this exceeds what is possible in an isogamous population, anisogamous populations can win out in direct competition by adapting faster.
The CoVid-19 is spreading pandemically all over the world. A rapid defeat of the pandemic requires carrying out on the population a mass screening, able to separate positive from negative cases. Such a cleaning will free a flow of productive population. The current rate and cost of testing, performed with the common PCR (polymerase chain reaction) method and with the available resources, is forcing a selection of the subjects to be tested. Indeed, each one must be examined individually at the cost of precious time. Moreover, the exclusion of potentially positive individuals from screening induces health risks, a broad slowdown in the effort to curb the viral spread, and the consequent mortality rates. We present a new procedure, the Purified by Unified Resampling of Infected Multitudes, in short Purim, able to untangle any massive candidate sample with inexpensive screening, through the cross-correlated analysis of the joint speciments. This procedure can reveal and detect most negative patients and in most cases discover the identity of the few positives already in the first or few secondary tests. We investigate the the two-dimensional correlation case in function of the infection probability. The multi-dimensional topology, the scaled Purim procedure are also considered. Extensive Purim tests may measure and weight the degree of epidemic: their outcome may identify focal regions in the early stages. Assuming hundreds or thousand subjects, the saving both in time and in cost will be remarkable. Purim may be able to filter scheduled flights, scholar acceptance, popular international event participants. The optimal extension of Purim outcome is growing as the inverse of the epidemia expansion. Therefore, the earlier, the better.
We propose a non-steady state model of the global temperature change. The model describes Earths surface temperature dynamics under main climate forcing. The equations were derived from basic physical relationships and detailed assessment of the numeric parameters used in the model. It shows an accurate fit with observed changes in the surface mean annual temperature (MAT) for the past 116 years. Using our model, we analyze the future global temperature change under scenarios of drastic reductions of COtextsubscript{2}. The presence of non-linear feed-backs in the model indicates on the possibility of exceeding two degrees threshold even under the carbon dioxide drastic reduction scenario. We discuss the risks associated with such warming and evaluate possible benefits of developing COtextsubscript{2}-absorbing deciduous tree plantations in the boreal zone of Northern Hemisphere.
Personalized models of the gut microbiome are valuable for disease prevention and treatment. For this, one requires a mathematical model that predicts microbial community composition and the emergent behavior of microbial communities. We seek a modeling strategy that can capture emergent behavior when built from sets of universal individual interactions. Our investigation reveals that species-metabolite interaction modeling is better able to capture emergent behavior in community composition dynamics than direct species-species modeling. Using publicly available data, we examine the ability of species-species models and species-metabolite models to predict trio growth experiments from the outcomes of pair growth experiments. We compare quadratic species-species interaction models and quadratic species-metabolite interaction models, and conclude that only species-metabolite models have the necessary complexity to to explain a wide variety of interdependent growth outcomes. We also show that general species-species interaction models cannot match patterns observed in community growth dynamics, whereas species-metabolite models can. We conclude that species-metabolite modeling will be important in the development of accurate, clinically useful models of microbial communities.
This Letter studies the quasispecies dynamics of a population capable of genetic repair evolving on a time-dependent fitness landscape. We develop a model that considers an asexual population of single-stranded, conservatively replicating genomes, whose only source of genetic variation is due to copying errors during replication. We consider a time-dependent, single-fitness-peak landscape where the master sequence changes by a single point mutation every time $ tau $. We are able to analytically solve for the evolutionary dynamics of the population in the point-mutation limit. In particular, our model provides an analytical expression for the fraction of mutators in the dynamic fitness landscape that agrees well with results from stochastic simulations.
We investigate the competing effects and relative importance of intrinsic demographic and environmental variability on the evolutionary dynamics of a stochastic two-species Lotka-Volterra model by means of Monte Carlo simulations on a two-dimensional lattice. Individuals are assigned inheritable predation efficiencies; quenched randomness in the spatially varying reaction rates serves as environmental noise. We find that environmental variability enhances the population densities of both predators and prey while demographic variability leads to essentially neutral optimization.