Stability and Hopf bifurcation of a delay eco‐epidemiological model with nonlinear incidence rate

In this paper, a three‐dimensional eco‐epidemiological model with delay is considered. The stability of the two equilibria, the existence of Hopf bifurcation and the permanence are investigated. It is found that Hopf bifurcation occurs when the delay τ passes a sequence of critical values. Moreover, by applying Nyquist criterion, the length of delay is estimated for which the stability continues to hold. Numerical simulation with a hypothetical set of data has been done to support the analytical results. This work is supported by the National Natural Science Foundation of China (No. 10771104 and No.10471117), Program for Innovative Research Team (in Science and Technology) in University of Henan Province (No. 2010IRTSTHN006) and Program for Key Laboratory of Simulation and Control for Population Ecology in Xinyang Normal University (No. 201004) and Natural Science Foundation of the Education Department of Henan Province (No. 2009B1100200 and No. 2010A110017) First published online: 10 Feb 201

Modelling dispersal processes in impala-cheetah-lion ecosystems with infection in the lions

The study involved the predator-prey interaction of three species namely the predator (Cheetah Acinonyx jubatus), the super-predator (Lion Panthera leo), and their common prey (Impala Aepyceros melampus). The study area is the Kruger National Park. The predator being an endangered species, faces a survival problem. It is frequently killed by the super-predator to reduce competition for prey. The super-predator also scares away the predator o_ its kills. The prey forms the main diet of the predator. The plight of the predator motivated the author to formulate disease and reaction-diffusion models for the species interactions. The purpose of the models were to predict and explain the effect of large competition from the super-predator on the predator population. Important parameters related to additional predator mortality due to presence of super-predator, the disease incidence rate and induced death rate formed the focal points of the analysis. The dynamics of a predator-prey model with disease in super-predator were investigated. The super-predator species is infected with bovine Tuberculosis. In the study, the disease is considered as biological control to allow the predator population to regain from low numbers. The results highlight that in the absence of additional mortality on the predator by the super-predator, the predator population survives extinction. Furthermore, at current levels of disease incidence, the super-predator population is wiped out by the disease. However, the super-predator population survives extinction if the disease incidence rate is low. Persistence of all populations is possible in the case of low disease incidence rate and no additional mortality imparted on the predator. Furthermore, a two-species subsystem, prey and predator, is considered as a special case to determine the effect of super-predator removal from the system, on the survival of the predator. This is treated as a contrasting case from the smaller parks. The results show that the predator population thrives well in the total absence of its main competitor, with its population rising to at least twice the initial value. A reaction-diffusion three-species predator-prey model was formulated and analysed. Stability of the temporal and the spatio-temporal systems, existence and non-existence of stationary steady state solutions were studied. Conditions for the emergence of stationary patterns were deduced. The results show that by choosing the diffusion coeffcient d2 > _D 2 suffciently large, a non-constant positive solution is generated, that is, stationary patterns emerge, depicting dispersal of species. Predators were observed to occupy habitats surrounding prey. However, super-predators were observed to alternate their habitats, from staying away from prey to invading prey habitat. In the investigation, strategies to determine ways in which the predator species could be saved from extinction and its population improved were devised, and these included isolation of the predator from the super-predator

Dynamical Models of Biology and Medicine

Mathematical and computational modeling approaches in biological and medical research are experiencing rapid growth globally. This Special Issue Book intends to scratch the surface of this exciting phenomenon. The subject areas covered involve general mathematical methods and their applications in biology and medicine, with an emphasis on work related to mathematical and computational modeling of the complex dynamics observed in biological and medical research. Fourteen rigorously reviewed papers were included in this Special Issue. These papers cover several timely topics relating to classical population biology, fundamental biology, and modern medicine. While the authors of these papers dealt with very different modeling questions, they were all motivated by specific applications in biology and medicine and employed innovative mathematical and computational methods to study the complex dynamics of their models. We hope that these papers detail case studies that will inspire many additional mathematical modeling efforts in biology and medicin

On Honey Bee Colony Dynamics and Disease Transmission

The work herein falls under the umbrella of mathematical modeling of disease transmission. The majority of this document focuses on the extent to which infection undermines the strength of a honey bee colony. These studies extend from simple mass-action ordinary differential equations models, to continuous age-structured partial differential equation models and finally a detailed agent-based model which accounts for vector transmission of infection between bees as well as a host of other influences and stressors on honey bee colony dynamics. These models offer a series of predictions relevant to the fate of honey bee colonies in the presence of disease and the nonlinear effects of disease, seasonality and the complicated dynamics of honey bee colonies. We are also able to extract from these models metrics that preempt colony failure. The analysis of disease dynamics in age-structured honey bee colony models required the study of next generation operators (NGO) and the basic reproduction number, $R_0$, for partial differential equations. This led us to the development of a coherent path from the NGO to its discrete compartmental counterpart, the next generation matrix (NGM) as well as the derivation of new closed-form formulae for the NGO for specific classes of disease models

The 9th European Conference on Marine Natural Products

Acknowledgments This work was supported by grants from the European Commission within its FP7 Programme, under the thematic area KBBE.2012.3.2-01 with Grant Number Nos. 311932 “SeaBioTech”, 311848 “BlueGenics”, and 312184 PharmaSea.Peer reviewedPublisher PD