Resource Allocation Dynamics Research Articles

Prezygotic resource-allocation dynamics and reproductive trade-offs in Calymperaceae (Bryophyta).

Resource allocation is difficult to characterize in plants because of the challenges of quantifying gametes and propagules. We surveyed six sympatric, unisexual species in the family Calymperaceae (Bryophyta) to test for trade-offs in prezygotic sexual and asexual expression and density-dependent survivorship of female gametangia. We tallied gametangial and asexual propagule output for 1820 shoots from 17 populations of six species at monthly intervals during one year (2010-2011) in a central Amazonian forest. Generalized linear mixed models were used to test for trade-offs in sexual and asexual expression and density-dependent senescence probability of gametangia. Precipitation and microsite variables were also included in the model. For all species, sexual and asexual expression were positively correlated with mean monthly precipitation. Asexually expressing shoots produced significantly fewer gametangia than nonexpressing ones, and the probability of senescence increased with shoot density. Archegonium density per shoot was also consistently lower than the modeled optimum to maximize the number of receptive archegonia. Trade-offs among reproductive strategies and positive density-dependent senescence of female gametangia suggest that prezygotic sexual and asexual expression come at a tangible investment. However, the apparently inefficient resource-allocation dynamics in the production of female gametangia makes the possible advantages of squandering such investments unclear. One possibility is that the study populations, like those of many dioicous mosses, are skewed toward expressing females with low sporophyte production, which would suggest that asexual reproduction predominates and upstages efficient resource allocation in prezygotic investment.

Node influence identification via resource allocation dynamics

Identifying the node influence in complex networks is an important task to optimally use the network structure and ensure the more efficient spreading in information. In this paper, by taking into account the resource allocation dynamics (RAD) and the k-shell decomposition method, we present an improved method namely RAD to generate the ranking list to evaluate the node influence. First, comparing with the epidemic process results for four real networks, the RAD method could identify the node influence more accurate than the ones generated by the topology-based measures including the degree, k-shell, closeness and the betweenness. Then, a growing scale-free network model with tunable assortative coefficient is introduced to analyze the effect of the assortative coefficient on the accuracy of the RAD method. Finally, the positive correlation is found between the RAD method and the k-shell values which display an exponential form. This work would be helpful for deeply understanding the node influence of a network.

Controlling collective dynamics in complex minority-game resource-allocation systems

Resource allocation takes place in various kinds of real-world complex systems, such as traffic systems, social services institutions or organizations, or even ecosystems. The fundamental principle underlying complex resource-allocation dynamics is Boolean interactions associated with minority games, as resources are generally limited and agents tend to choose the least used resource based on available information. A common but harmful dynamical behavior in resource-allocation systems is herding, where there are time intervals during which a large majority of the agents compete for a few resources, leaving many other resources unused. Accompanying the herd behavior is thus strong fluctuations with time in the number of resources being used. In this paper, we articulate and establish that an intuitive control strategy, namely pinning control, is effective at harnessing the herding dynamics. In particular, by fixing the choices of resources for a few agents while leaving the majority of the agents free, herding can be eliminated completely. Our investigation is systematic in that we consider random and targeted pinning and a variety of network topologies, and we carry out a comprehensive analysis in the framework of mean-field theory to understand the working of control. The basic philosophy is then that, when a few agents waive their freedom to choose resources by receiving sufficient incentives, the majority of the agents benefit in that they will make fair, efficient, and effective use of the available resources. Our work represents a basic and general framework to address the fundamental issue of fluctuations in complex dynamical systems with significant applications to social, economical, and political systems.

Biomass partitioning and water content relationships at the branch and whole-plant levels and as a function of plant size in Elaeagnus mollis populations in Shanxi, North China

Understanding of the biomass (dry weight) allocation and water relations in populations will provide useful information on the growth patterns and resource-allocation dynamics. By destructive sampling, foliage, branch and root biomass were measured in the endangered shrub Elaeagnus mollis populations growing in Shanxi province, North China. Biomass partitioning and water content relationships were compared at the branch and whole-plant levels, and as a function of basal diameter (plant size). The biomass was mainly distributed in the bigger branches at the branch level, and in the branch wood at the whole-plant level, and branch biomass (but not foliage or root biomass) increases significantly with increasing basal diameter. As a result, branch wood became the major biomass pool, even though considerable biomass was also allocated to the roots. However, the relative water content decreased from the periphery of the crown to the interior of the shrub at the branch level, and from the aboveground to the belowground at the whole-plant level though no significant variation among foliage, branches, and roots. Yet it increased significantly for the whole-plant with increasing basal diameter. The ratio of belowground to aboveground biomass was smaller than 1.0, even as a function of basal diameter. These growth responses indicated a strong adaptation to the shrub’s growing conditions. Biomass was primarily allocated above the ground and the aboveground components grew faster than the belowground one.

Bipartite network projection and personal recommendation

One-mode projecting is extensively used to compress bipartite networks. Since one-mode projection is always less informative than the bipartite representation, a proper weighting method is required to better retain the original information. In this article, inspired by the network-based resource-allocation dynamics, we raise a weighting method which can be directly applied in extracting the hidden information of networks, with remarkably better performance than the widely used global ranking method as well as collaborative filtering. This work not only provides a creditable method for compressing bipartite networks, but also highlights a possible way for the better solution of a long-standing challenge in modern information science: How to do a personal recommendation.

Power-law strength-degree correlation from resource-allocation dynamics on weighted networks

Many weighted scale-free networks are known to have a power-law correlation between strength and degree of nodes, which, however, has not been well explained. We investigate the dynamic behavior of resource-traffic flow on scale-free networks. The dynamical system will evolve into a kinetic equilibrium state, where the strength, defined by the amount of resource or traffic load, is correlated with the degree in a power-law form with tunable exponent. The analytical results agree well with simulations.