Sex ratio and dynamic behavior in populations of the exotic blowfly Chrysomya albiceps (Diptera, Calliphoridae)

Sex ratio is an essential component of life history to be considered in population growth. Chrysomya albiceps is a blowfly species with a naturally biased sex ratio. In this study, we evaluated the impact of changes in sex ratio on the dynamic behavior of C. albiceps using a density-dependent mathematical model that incorporated demographic parameters such as survival and fecundity. These parameters were obtained by exponential regression, with survival and fecundity being estimated experimentally as a function of larval density. Bifurcation diagram of the results indicated the evolution of stable equilibrium points as a function of sex ratio. A continually increasing sex ratio yielded a hierarchy of bifurcating stable equilibrium points that evolved into a chaotic regime. The demographic parameters obtained by exponential regression were also changed to maximum and minimum values in order to analyze their influence on dynamic behavior with sex ratio being considered as an independent variable. Bifurcations with periodicity windows between chaos regimes were also found.

A razão sexual é um componente essencial da biologia de organismos a ser considerado em crescimento populacional. Chrysomya albiceps é uma espécie de mosca varejeira que exibe um desvio na razão sexual em relação à proporção 1:1. Neste estudo avaliamos o impacto de alterações na razão sexual sobre o comportamento dinâmico de C. albiceps utilizando um modelo matemático dependente da densidade que incorpora parâmetros demográficos como sobrevivência e fecundidade. Os parâmetros foram obtidos por regressão exponencial, com sobrevivência e fecundidade sendo estimadas experimentalmente em função da densidade larval. O diagrama de bifurcação gerado pelos resultados indicou a evolução de pontos de equilíbrio estável em função da razão sexual. A sucessão contínua dos valores da razão sexual resultou em uma hierarquia de pontos de equilíbrio estável produzida por bifurcações, resultando em regime caótico. Os parâmetros demográficos obtidos por regressão exponencial foram também mudados para valores máximos e mínimos, a fim de analisar a influência deles sobre o comportamento dinâmico da espécie, tendo a razão sexual como variável independente. Bifurcações com janelas de periodicidade intercaladas com o regime caótico também foram encontradas.

A multi-neighbor-joining approach for phylogenetic tree reconstruction and visualization

The computationally challenging problem of reconstructing the phylogeny of a set of contemporary data, such as DNA sequences or morphological attributes, was treated by an extended version of the neighbor-joining (NJ) algorithm. The original NJ algorithm provides a single-tree topology, after a cascade of greedy pairing decisions that tries to simultaneously optimize the minimum evolution and the least squares criteria. Given that some sub-trees are more stable than others, and that the minimum evolution tree may not be achieved by the original NJ algorithm, we propose a multi-neighbor-joining (MNJ) algorithm capable of performing multiple pairing decisions at each level of the tree reconstruction, keeping various partial solutions along the recursive execution of the NJ algorithm. The main advantages of the new reconstruction procedure are: 1) as is the case for the original NJ algorithm, the MNJ algorithm is still a low-cost reconstruction method; 2) a further investigation of the alternative topologies may reveal stable and unstable sub-trees; 3) the chance of achieving the minimum evolution tree is greater; 4) tree topologies with very similar performances will be simultaneously presented at the output. When there are multiple unrooted tree topologies to be compared, a visualization tool is also proposed, using a radial layout to uniformly distribute the branches with the help of well-known metaheuristics used in computer science.

Recent advances in gene expression data clustering: a case study with comparative results

Several advanced techniques have been proposed for data clustering and many of them have been applied to gene expression data, with partial success. The high dimensionality and the multitude of admissible perspectives for data analysis of gene expression require additional computational resources, such as hierarchical structures and dynamic allocation of resources. We present an immune-inspired hierarchical clustering device, called hierarchical artificial immune network (HaiNet), especially devoted to the analysis of gene expression data. This technique was applied to a newly generated data set, involving maize plants exposed to different aluminum concentrations. The performance of the algorithm was compared with that of a self-organizing map, which is commonly adopted to deal with gene expression data sets. More consistent and informative results were obtained with HaiNet.

Diffusion model applied to postfeeding larval dispersal blowflies (Diptera: Calliphoridae)

This paper presents a diffusion model of larval dispersal especifically designed to account for particular aspects of postfeeding larval dispersal from the food source in organisms such as blowflies. In these organisms the dispersal of immatures includes two groups of individuals, those that are actively migrating and those that initiated the pupation process. The classical diffusion equation in one dimension was modified to incorporate a function which describes the burying of larvae to become pupae. The analytical solution of this equation predicts oscillatory and monotonic dispersal behaviors, which are observed in experimental populations of blowfly species.

Theoretical estimates of consumable food and probability of acquiring food in larvae of Chrysomya putoria (Diptera: Calliphoridae)

An indirect estimate of consumable food and probability of acquiring food in a blowfly species, Chrysomya putoria, is presented. This alternative procedure combines three distinct models to estimate consumable food in the context of the exploitative competition experienced by immature individuals in blowfly populations. The relevant parameters are derived from data for pupal weight and survival and estimates of density-independent larval mortality in twenty different larval densities. As part of this procedure, the probability of acquiring food per unit of time and the time taken to exhaust the food supply are also calculated. The procedure employed here may be valuable for estimations in insects whose immature stages develop inside the food substrate, where it is difficult to partial out confounding effects such as separation of faeces. This procedure also has the advantage of taking into account the population dynamics of immatures living under crowded conditions, which are particularly characteristic of blowflies and other insects as well.