Predictions of biodiversity are improved by integrating trait-based competition with abiotic filtering

All organisms must simultaneously tolerate the environment and access limiting resources if they are to persist. Otherwise they go extinct. Approaches to understanding environmental tolerance and resource competition have generally been developed independently. Consequently, integrating the factors that determine abiotic tolerance with those that affect competitive interactions to model species abundances and community structure remains an unresolved challenge. This is likely the reason why current models of community assembly do not accurately predict species abundances and dynamics. Here, we introduce a new synthetic framework that models both abiotic tolerance and biotic competition by using functional traits, which are phenotypic attributes that influence organism fitness. First, our framework estimates species carrying capacities that vary along abiotic gradients based on whether the phenotype tolerates the local environment. Second, it estimates pairwise competitive interactions as a function of multidimensional trait differences between species and determines which trait combinations produce the most competitive phenotypes. We demonstrate that our combined approach more than doubles the explained variance of species covers in a wetland community compared to the model of abiotic tolerances alone. Trait-based integration of competitive interactions and abiotic filtering improves our ability to predict species abundances across space, bringing us closer to more accurate predictions of biodiversity structure in a changing world.

Evolution of innate behavioral strategies through competitive population dynamics

Many organism behaviors are innate or instinctual and have been "hard-coded" through evolution. Current approaches to understanding these behaviors model evolution as an optimization problem in which the traits of organisms are assumed to optimize an objective function representing evolutionary fitness. Here, we use a mechanistic birth-death dynamics approach to study the evolution of innate behavioral strategies in a population of organisms in silico. In particular, we performed agent-based stochastic simulations and mean-field analyses of organisms exploring random environments and competing with each other to find locations with plentiful resources. We find that when organism density is low, the mean-field model allows us to derive an effective objective function, predicting how the most competitive phenotypes depend on the exploration-exploitation trade-off between the scarcity of high-resource sites and the increase in birth rate those sites offer organisms. However, increasing organism density alters the most competitive behavioral strategies and precludes the existence of a well-defined objective function. Moreover, there exists a range of densities for which the coexistence of many phenotypes persists for evolutionarily long times.

Early alphavirus replication dynamics in single cells reveal a passive basis for superinfection exclusion

SummaryWhile decades of research have elucidated many steps in the alphavirus lifecycle, the earliest replication dynamics have remained unclear. This missing time window has obscured early replicase strand synthesis behavior and prevented elucidation of how the resulting activity gives rise to a superinfection exclusion environment, one of the fastest competitive phenotypes among viruses. Using quantitative live-cell and single-molecule imaging, we characterize the strand preferences of the viral replicase in situ, and measure protein kinetics in single cells over time. In this framework, we evaluate competition between alphaviruses, and uncover that early superinfection exclusion is actually not a binary and unidirectional process, but rather a graded and bidirectional viral interaction. In contrast to competition between other viruses, alphaviruses demonstrate a passive basis for superinfection exclusion, emphasizing the utility of analyzing viral kinetics within single cells.

Neuroendocrinology of Sex-Role Reversal

Synopsis Females of some species are considered sex-role reversed, meaning that they face stronger competition for mates compared to males. While much attention has been paid to behavioral and morphological patterns associated with sex-role reversal, less is known about its physiological regulation. Here, we evaluate hypotheses relating to the neuroendocrine basis of sex-role reversal. We refute the most widely tested activational hypothesis for sex differences in androgen secretion; sex-role reversed females do not have higher levels of androgens in circulation than males. However, we find some evidence that the effects of androgens may be sex-specific; circulating androgen levels correlate with some competitive phenotypes in sex-role reversed females. We also review evidence that sex-role reversed females have higher tissue-specific sensitivity to androgens than males, at least in some species and tissues. Organizational effects may explain these relationships, considering that early exposure to sex steroids can shape later sensitivity to hormones, often in sex-specific ways. Moving forward, experimental and correlative studies on the ontogeny and expression of sex-role reversal will further clarify the mechanisms that generate sex-specific behaviors and sex roles.