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Register a new userChoosing the fittest as a speciation mechanism
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When a population inhabits an inhomogeneous environment, the fitness value of traits can vary with the position in the environment. Gene flow caused by random mating can nevertheless prevent that a sexually reproducing population splits into different species under such circumstances. This is the problem of sympatric speciation. However, mating need not be entirely random. Here, we present a model where the individually advantageous preference for partners of high fitness can lead to genetic clustering as a precondition for speciation. In simulations, in appropriate parameter regimes, our model leads to the rapid fixation of the corresponding alleles.
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A square lattice is introduced into the Penna model for biological aging in order to study the evolution of diploid sexual populations under certain conditions when one single locus in the individuals genome is considered as identifier of species. The simulation results show, after several generations, the flourishing and coexistence of two separate species in the same environment, i.e., one original species splits up into two on the same territory (sympatric speciation). As well, the mortalities obtained are in a good agreement with the Gompertz law of exponential increase of mortality with age.
How large ecosystems can create and maintain the remarkable biodiversity we see in nature is probably one of the biggest open question in science, attracting attention from different fields, from Theoretical Ecology to Mathematics and Physics. In this context, modeling the stable coexistence of different species competing for limited resources is a particularly demanding task. From the mathematical point of view, coexistence in competitive dynamics can be achieved when dominance among species forms intransitive loops. However, these relationships usually lead to species densities neutrally cycling without converging to a stable equilibrium and, although in recent years several mechanisms have been proposed, models able to explain the robust persistence of competitive ecosystems are lacking. Here we show that stable coexistence in large communities can be achieved when the locality of interactions is taken into account. We consider a simplified ecosystem where individuals of each species lay on a spatial network and interactions are possible only between nodes at a certain distance. Varying such distance allows to interpolate between local and global competition. Our results demonstrate that when two conditions are met: individuals are embedded in space and can only interact with other individuals within a short distance, species coexist reaching a stable equilibrium. On the contrary, when one of these ingredients is missing large fluctuations and neutral cycles emerge.
The fitness of a biological strategy is typically measured by its expected reproductive rate, the first moment of its offspring distribution. However, strategies with high expected rates can also have high probabilities of extinction. A similar situation is found in gambling and investment, where strategies with a high expected payoff can also have a high risk of ruin. We take inspiration from the gamblers ruin problem to examine how extinction is related to population growth. Using moment theory we demonstrate how higher moments can impact the probability of extinction. We discuss how moments can be used to find bounds on the extinction probability, focusing on s-convex ordering of random variables, a method developed in actuarial science. This approach generates best case and worst case scenarios to provide upper and lower bounds on the probability of extinction. Our results demonstrate that even the most fit strategies can have high probabilities of extinction.
Microorganisms live in environments that inevitably fluctuate between mild and harsh conditions. As harsh conditions may cause extinctions, the rate at which fluctuations occur can shape microbial communities and their diversity, but we still lack an intuition on how. Here, we build a mathematical model describing two microbial species living in an environment where substrate supplies randomly switch between abundant and scarce. We then vary the rate of switching as well as different properties of the interacting species, and measure the probability of the weaker species driving the stronger one extinct. We find that this probability increases with the strength of demographic noise under harsh conditions and peaks at either low, high, or intermediate switching rates depending on both species ability to withstand the harsh environment. This complex relationship shows why finding patterns between environmental fluctuations and diversity has historically been difficult. In parameter ranges where the fittest species was most likely to be excluded, however, the beta diversity in larger communities also peaked. In sum, how environmental fluctuations affect interactions between a few species pairs predicts their effect on the beta diversity of the whole community.
Species richness varies widely across the tree of life, and there is great interest in identifying ecological, geographic, and other factors that affect rates of species proliferation. Recent methods for explicitly modeling the relationships among character states, speciation rates, and extinction rates on phylogenetic trees- BiSSE, QuaSSE, GeoSSE, and related models - have been widely used to test hypotheses about character state-dependent diversification rates. Here, we document the disconcerting ease with which neutral traits are inferred to have statistically significant associations with speciation rate. We first demonstrate this unfortunate effect for a known model assumption violation: shifts in speciation rate associated with a character not included in the model. We further show that for many empirical phylogenies, characters simulated in the absence of state-dependent diversification exhibit an even higher Type I error rate, indicating that the method is susceptible to additional, unknown model inadequacies. For traits that evolve slowly, the root cause appears to be a statistical framework that does not require replicated shifts in character state and diversification. However, spurious associations between character state and speciation rate arise even for traits that lack phylogenetic signal, suggesting that phylogenetic pseudoreplication alone cannot fully explain the problem. The surprising severity of this phenomenon suggests that many trait-diversification relationships reported in the literature may not be real. More generally, we highlight the need for diagnosing and understanding the consequences of model inadequacy in phylogenetic comparative methods.
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