Journal of Theoretical Biology最新文献

Food webs are a central subject in community ecology, because consumption supports the flow of matter through the system, which is at the base of many of its functions. Identifying the mechanisms that are at the origin of food web structure is useful, e.g., for restoration purposes. We investigated the extent to which trait-matching, which contributes to defining the strength of trophic interactions, can cause the emergence of food webs with a non-trivial, multi-trophic, hierarchical structure. We compared for that purpose the structural properties of food webs simulated by four food web model variants, depending whether trait-matching was linear or nonlinear and whether population dynamics and evolution were accounted for (dynamical model) or not (static model). Nonlinear trait-matching can restrict interactions in phenotypic space so as to obtain localized interactions (i.e., each species interact with a small subset of species), which is a key element for food web formation. In the static case, nonlinear trait-matching allowed for the emergence of food webs, at a relatively low connectance as with random graphs. In the dynamical case, nonlinear trait-matching combined with population dynamics and evolution allowed for the formation of groups of phenotypically close species, resulting in food webs with a multi-trophic, hierarchical structure.

Plants are essential for life on Earth, serving as a major source of food supply and contributing to the planet's carbon balance. Mathematical modelling is an important mechanism for predicting and optimising plant growth in agriculture, and Thornley's mathematical model (Thornley, 1997) is one of the most widely used models describing carbon and nitrogen allocation in plants. However, a formal mathematical analysis of the model's behaviour has not been performed. Our analysis of the model provides new insights into how and why the model can be inappropriate. By varying the values of some model parameters, we identify non-physical and even quite chaotic behaviour. In response, we modify Thornley's model by including additional litter terms, resulting in the elimination of these non-physical behaviours.

Organisms invariably experience trade-offs in their capacities for interacting with their environments. In resource competition, this often means that an organism's ability to acquire one resource can only come at the cost of less ability with others. If the traits governing resource acquisition are under selection and heritable, this will induce eco-evolutionary dynamics along the trade-off. For Lotka-Volterra models derived from MacArthur resource competition models and for explicit resource models with two resources, the shape and dimensionality of trade-offs has seen substantial study. However, how the joint effects of trade-off shapes and the number of resources under competition affect eco-evolutionary outcomes has seen relatively little. For example, is diversification through evolutionary branching more or less likely when the number of resources increases? Here, we will present techniques complementary to existing ones for recasting trade-offs in an implicit form. Combining adaptive dynamics and resource-competition theory, we derive expressions for directional and stabilizing/disruptive selection. We apply our techniques to two models of resource competition and investigate how the number of resources and trade-off shapes affect the stability characteristics of the generalist strategy, and how diverse a community of consumers can be assembled through successive evolutionary branching. We find that even for these simple and highly symmetric models, outcomes are surprisingly complex and idiosyncratic. Taken together, our results deepen our understanding of the eco-evolutionary dynamics of resource competition for multiple resources.

Mosquito-borne diseases (MBDs) pose increasing threats under future climate change scenarios and an understanding of mosquito population dynamics is pivotal to predicting future risk of MBDs. Most models that describe mosquito population dynamics often assume that adult life-history is independent of adult age and yet mosquito senescence is known to affect mosquito mortality, fecundity and other key biological traits. Despite this, little is known about the effects of adult age at the level of the mosquito population, especially under varying temperature scenarios. We develop a stage-structured delayed differential equations (DDEs) model incorporating the effects of the abiotic environment and adult age to shed light on the complex interactions between age, temperature, and mosquito population dynamics. Taking Culex pipiens, a major vector of West Nile Virus, as our study species our results show that failing to consider mosquito senescence can lead to underestimates of future mosquito abundances predicted under climate change scenarios. We also find that the age-dependent mechanisms combined with the effects of density-dependent mortality on the immature stages can result in mosquito abundances decreasing at extreme temperatures. With our work, we underscore the need for more studies to consider the effects of mosquito age. Not accounting for senescence can compromise the accuracy of abundance estimates and has implications for predicting the risk of future MBD outbreaks.