Ecological networks experiencing persistent biological invasions may exhibit distinct topological properties, complicating the understanding of how network topology affects disease transmission during invasion-driven community assembly. We developed a trait-based network model to assess the impact of network topology on disease transmission, measured as community- and species-level disease prevalence. We found that trait-based feeding interactions between host species determine the frequency distribution of the niche of co-occurring species in steady-state communities, being either bimodal or multimodal. The width of the growth kernel influences the degree-biomass relationship of species, being either weakly positive or strongly negative. When this relationship is weakly positive, species-level disease prevalence is primarily correlated with biomass. However, when the degree-biomass relationship is strongly negative, species-level disease prevalence is determined by the difference between a host species’ in-degree and out-degree closeness centrality. At the community level, disease prevalence is generally amplified by increasing host richness, community biomass, and the standard deviation of interaction generality, while it is diluted by higher network connectance. Our framework verifies the amplification effects of host richness during invasion-driven community assembly and offers valuable insights for estimating disease prevalence based on host network topology.
Of Chargaff’s four rules on DNA base quantity, his second parity rule (PR-2) is the most contentious. Various biometricians (e.g., Sueoka, Lobry) regarded PR-2 compliance as a non-adaptive feature of modern genomes that could be modeled through interrelations among mutation rates. However, PR-2 compliance with stem-loop potential was considered adaptively relevant by biochemists familiar with analyses of nucleic acid structure (e.g., of Crick) and of meiotic recombination (e.g., of Kleckner). Meanwhile, other biometricians had shown that PR-2 complementarity extended beyond individual bases (1-mers) to oligonucleotides (k-mers), possibly reflecting “advantageous DNA structure” (Nussinov). An “introns early” hypothesis (Reanney, Forsdyke) had suggested a primordial nucleic acid world with recombination-mediated error-correction requiring genome-wide stem-loop potential to have evolved prior to localized intrusions of protein-encoding potential (exons). Thus, a primordial genome was equivalent to one long intron. Indeed, when assessed as the base order-dependent component (correcting for local influences of GC%), modern genes, especially when evolving rapidly under positive Darwinian selection, display high intronic stem-loop potential. This suggests forced migration from neighboring exons by competing protein-encoding potential. PR-2 compliance may have first arisen non-adaptively. Primary prototypic structures were later strengthened by their adaptive contribution to recombination. Thus, contentious views may actually be in harmony.
Explaining the evolution of cooperation in the strong altruism scenario, where a cooperator does not benefit from her contribution to the public goods, is a challenging problem that requires positive assortment among cooperators (i.e., cooperators must tend to associate with other cooperators) or punishment of defectors. The need for these drastic measures stems from the analysis of a group selection model of temporarily formed random groups introduced by Hamilton nearly fifty years ago to describe the fate of altruistic behavior in a population. Challenging conventional wisdom, we show analytically here that strong altruism evolves in Hamilton’s original model in the case of biparental sexual reproduction. Moreover, when the cost of cooperation is small and the amplified contribution shared by group members is large, cooperation is the only stable strategy in equilibrium. Thus, our results provide a solution to the ‘problem of origination’ of strong altruism, i.e. how cooperation can take off from an initial low frequency of cooperators. We discuss a possible reassessment of cooperation in cases of viral co-infection, as cooperation may even be favored in situations where the prisoner’s dilemma applies.
Two simple algorithms based on combining odor concentration differences across time and space along with information on the flow direction are tested for their ability to locate an odor source in four different odor landscapes. Image data taken from air plumes in three different regimes and a water plume are used as test environments for a bilateral (“stereo sampling”) algorithm using concentration differences across two sensors and a “casting” algorithm that uses successive samples to decide orientation. Agents are started at random locations and orientations in the landscape and allowed to move until they reach the source of the odor (success) or leave the imaged area (failure). Parameters for the algorithm are chosen to optimize success and to minimize path length to the source. Success rates over 90% are consistently obtained with path lengths that can be as low as twice the starting distance from the source in air and four times the distance in the highly turbulent water plumes. We find that parameters that optimize success often lead to more exploratory pathways to the source. Information about the direction from which the odor is coming is necessary for successful navigation in the water plume and reduces the path length in the three tested air plumes.
We report the effects of varying physiological and other properties on the heat and water exchange in the maxilloturbinate structure (MT) of the bearded seal (Erignathus barbatus or Eb) in realistic environments, using a computational fluid dynamics (CFD) model. We find that the water retention in percent is very high (about 90 %) and relatively unaffected by either cold (−30 °C) or warm (10 °C) conditions. The retention of heat is also high, around 80 % . Based on a consideration of entropy production by the maxilloturbinate system, we show that anatomical and physiological properties of the seal provide good conditions for heat and water exchange at the mucus lining in the seal’s nasal cavity. At normal values of tidal volume and maxilloturbinate (MT) length, the air temperature in the MT reaches the body temperature before the air has left the MT channels. This confers a safety factor which is expected to be helpful in exercise, when ventilation increases.
In this study, we examine the effects of connectivity on the total catch of a fishery consisting of two fishing sites when the fish population is a predator of a larger prey–predator system. To this end, we analyze a prey–predator fish community model in a two-site environment and compute catch at Maximum Sustainable Yield (MSY). We exhibit some emergence phenomenon: the total catch can be greater than the sum of the catch at two isolated sites due to connectivity. This result is obtained when the two sites are heterogeneous. We show that the increase in capture at MSY is maximal for a certain value of the carrying capacity of the second site, all other parameters remaining constant, including the carrying capacity of the first site. A stronger phenomenon can also be observed: even if none of the sites is viable for fishing, the entire system can be viable. We then study the effects of the heterogeneity of the sites and illustrate our results through simulations. It is shown that the excess yield at MSY can become very significant when the characteristics of the prey and predator in terms of potential growth are opposite at each site.
How does the spatial heterogeneity of landscapes interact with the adaptive evolution of populations to influence their spreading speed? This question arises in agricultural contexts where a pathogen population spreads in a landscape composed of several types of crops, as well as in epidemiological settings where a virus spreads among individuals with distinct immune profiles. To address it, we introduce an analytical method based on reaction–diffusion models. We focus on spatially periodic environments with two distinct patches, where the dispersing population consists of two specialized morphs, each potentially mutating to the other. We present new formulas for the speed together with criteria for persistence, accounting for both rapidly and slowly varying environments, as well as small and large mutation rates. Altogether, our analytical and numerical results yield a comprehensive understanding of persistence and spreading dynamics. In particular, compared to a situation without mutations or to a single morph spreading in a heterogeneous landscape, the introduction of mutations to a second morph with reverse specialization, while consistently impeding persistence, can significantly increase speed, even if the mutation rate between the two morphs is very small. Additionally, we find that the amplitude of the spatial fragmentation effect is significantly increased in this case. This has implications for agroecology, emphasizing the higher importance of landscape structure in influencing adaptation-driven population dynamics.