昆虫杆状病毒流行病模拟模型及Java模拟软件

研究昆虫杆状病毒流行病模拟模型,对确定基因工程改造杆状病毒的主攻方向,明确病毒病田间流行的机制与关键因素,以及制定生物防治策略,均具有重要的理论与实践意义.本研究研制了用于昆虫杆状病毒流行病模拟的数学模型和Java模拟软件,该模型包括描述种群动态的一个微分方程组,描述气温变化、作物生长及病毒动态的若干模型等.模拟软件用...     

昆虫种群动态模拟模型

昆虫是动物界中最大的类群,与人类有着密切的利害关系。对昆虫的数量预测与符合经济和生态规律的管理,一直都被国内外列入重点研究课题。种群动态模拟是害虫管理中重要的基础工作。近十年来,关于昆虫种群动态模型的理论和实验研究进展迅速。现分别从单种种群和多种种群两个方面对国内外近些年来昆虫种群动态模拟模型的研究进展进行了概括和总结。单种种群从两个方面阐述:一是最基本的种群动态模拟模型Log istic方程的研究成果,包括方程的修正、参数的拟合与最优捕获策略等;另一个方面是对种群动态模拟常用的矩阵模型的概述,主要介绍不等期年龄组、矩阵维数的变化、矩阵维数与历期的关系、个体之间的发育差异以及发育速率差异等等对昆虫种群动态模型的影响。多种群主要从建模和模型应用两个部分对国内外研究成果进行综述。最后,对种群动态模拟模型研究的发展方向做了深入地讨论,即在原有的数据采集工作的基础上,使用面向对象程序设计语言,把各种要素包括各种物种及各种环境条件抽象成类,用消息传递来表示昆虫种群内个体与个体、昆虫种群与环境之间的相互作用,再结合先进的数学算法,建立一个直观的、操作简单的昆虫种群动态模型库,使模型结构与现实世界有最大的相似性。这样就可以实现昆虫种群动态的可视化、立体化、实时化和精确化的监测及预测。     

Interannual population dynamics of the green spruce aphid Elatobium abietinum (Walker) in France

The hypothesis that similar processes govern interannual dynamics of green spruce aphid in the UK and France, is generally supported by the application of a general discrete model. A simple model based on relatively few parameters was able to closely characterise interannual population dynamics from completely independent aerial and arboreal samples of aphids. Long-term field population estimates of the green spruce aphid Elatobium abietinum (Walker) in France have provided the opportunity to select and evaluate the generality of a model, which was developed in the UK to explain the year-to-year variations in peak abundance of the aphid. The objective was to observe the influence of the local climates and disturbing climate factors on the population densities of the insect in two regions of France. The model uses climate variables and aphid population data from regular samples in the two regions that were investigated. A general discrete model was used to predict aphid population densities. The model performed well in tracking the interannual patterns of population but was less likely to predict absolute population density. To improve predictions, further account would need to be taken of additional site-specific climate variables and the strength of overcompensating density dependence. Nevertheless, it is clear that broadly similar processes are at work in the population dynamics of this insect across its biogeographical range.     

Modeling population dynamics of a tea pest with temperature-dependent development: predicting emergence timing and potential damage

The tea leaf roller, Caloptilia theivora Walsingham (Lepidoptera: Gracillariinae), is one of the serious pests of tea plants in Japan. To understand the mechanism of seasonal occurrence of this insect pest, we developed a population dynamics model that explicitly incorporates the temperature-dependent development of the pest. The model predictions were compared with observed captures in pheromone traps at the experimental site of the Kagoshima Tea Experiment Research Station in Japan. The results showed that the emergence timing of the insect pest observed in the field was determined primarily by temperature. The relationship between the timing of adult emergence and the leaf damage level was also studied using a logistic regression model. The infestation level decreased as the interval between the adult peak emergence date and the date of tea plucking increased, implying that asynchrony between plant phenology and emergence of the insect pest is a critical factor reducing damage level. We examined how the damage level changes according to global warming. Increased temperature made the timing of insect appearance forward and enhance asynchrony of plant–pest phenology. Therefore, reduction of damage level by the insect pest is expected under global warming.     

Invasion models of vegetation dynamics

Since communities change as a result of their successful invasion by new species it seems logical to attempt to predict future vegetation change by focussing on the invasion process. Several such invasion models are reviewed, and one particular model, based on dynamic game theory is developed further. This model can be used as an alternative to linear (e.g. Markov chain) models for the prediction of vegetation dynamics, and also to compare invasive abilities of species and resistance to invasion of communities. The main advantage of the model lies in the fact that it operates at a sufficiently high level of integration to allow for model calibration (in spite of the large number of underlying processes), and yet has an obvious population biological interpretation (in terms of the success of invading populations). The model can be calibrated using either time course data or experimental data, and it may be helpful in understanding what determines the fate of an invading population. It is used here to analyze two published vegetation dynamics data sets.This work was financially supported by operating grant A8115 from the Natural Sciences and Engineering Research Council of Canada.     

A mathematical model of baculovirus infection on insect cells at low multiplicity of infection

The expression efficiency of the insect cells-baculovirus system used for insecticidal virus production and the expression of medically useful foreign genes is closely related with the dynamics of infection. The present studies develop a model of the dynamic process of insect cell infection with baculovirus at low multiplicity of     

Modelling density-dependent resistance in insect-pathogen interactions.

We consider a mathematical model for a host-pathogen interaction where the host population is split into two categories: those susceptible to disease and those resistant to disease. Since the model was motivated by studies on insect populations, we consider a discrete-time model to reflect the discrete generations which are common among insect species. Whether an individual is born susceptible or resistant to disease depends on the local population levels at the start of each generation. In particular, we are interested in the case where the fraction of resistant individuals in the population increases as the total population increases. This may be seen as a positive feedback mechanism since disease is the only population control imposed upon the system. Moreover, it reflects recent experimental observations from noctuid moth-baculovirus interactions that pathogen resistance may increase with larval density. We find that the inclusion of a resistant class can stabilise unstable host-pathogen interactions but there is greatest regulation when the fraction born resistant is density independent. Nonetheless, inclusion of density dependence can still allow intrinsically unstable host-pathogen dynamics to be stabilised provided that this effect is sufficiently small. Moreover, inclusion of density-dependent resistance to disease allows the system to give rise to bistable dynamics in which the final outcome is dictated by the initial conditions for the model system. This has implications for the management of agricultural pests using biocontrol agents-in particular, it is suggested that the propensity for density-dependent resistance be determined prior to such a biocontrol attempt in order to be sure that this will result in the prevention of pest outbreaks, rather than their facilitation. Finally we consider how the cost of resistance to disease affects model outcomes and discover that when there is no cost to resistance, the model predicts stable periodic outbreaks of the insect population. The results are interpreted ecologically and future avenues for research to address the shortfalls in the present model system are discussed.     

Mechanical-Statistical Modeling in Ecology: From Outbreak Detections to Pest Dynamics

Knowledge about large-scale and long-term dynamics of (natural) populations is required to assess the efficiency of control strategies, the potential for long-term persistence, and the adaptability to global changes such as habitat fragmentation and global warming. For most natural populations, such as pest populations, large-scale and long-term surveys cannot be carried out at a high resolution. For instance, for population dynamics characterized by irregular abundance explosions, i.e., outbreaks, it is common to report detected outbreaks rather than measuring the population density at every location and time event. Here, we propose a mechanical-statistical model for analyzing such outbreak occurrence data and making inference about population dynamics. This spatio-temporal model contains the main mechanisms of the dynamics and describes the observation process. This construction enables us to account for the discrepancy between the phenomenon scale and the sampling scale. We propose the Bayesian method to estimate model parameters, pest densities and hidden factors, i.e., variables involved in the dynamics but not observed. The model was specified and used to learn about the dynamics of the European pine sawfly (Neodiprion sertifer Geoffr., an insect causing major defoliation of pines in northern Europe) based on Finnish sawfly data covering the years 1961–1990. In this application, a dynamical Beverton–Holt model including a hidden regime variable was incorporated into the model to deal with large variations in the population densities. Our results gave support to the idea that pine sawfly dynamics should be studied as metapopulations with alternative equilibria. The results confirmed the importance of extreme minimum winter temperatures for the occurrence of European pine sawfly outbreaks. The strong positive connection between the ratio of lake area over total area and outbreaks was quantified for the first time.     

变维矩阵模型在温室白粉虱种群动态模拟中的应用

自七十年代以来,温室白粉虱(Trialeurodes vaporariorum Westw.)已成为我国北部温室中的主要害虫。为了最经济地将害虫控制在经济允许水平以下,必须进行数量预报和最优管理。为此,建立种群动态的模拟模型是必不可少的一步。 当然,影响昆虫种群动态的因子是很多的。但作为变温动物,温度因子是最基本的因子之一。尤其对那些象温室白粉虱的昆虫,温室系统相对地简单,天敌从种类到数量上都很     

Scale-dependent mechanisms in the population dynamics of an insect herbivore

A multiscale approach has lead to significant advances in the understanding of species population dynamics. The scale-dependent nature of population processes has been particularly clearly illustrated for insect herbivores. However, one of the most well-studied insect herbivores, the galling sawfly Euura lasiolepis, has to date been examined almost exclusively at fine spatial scales. The preference-performance, plant vigour and larval survival hypotheses are well supported by this species. Here, we test these hypotheses at a spatial scale larger than that previously considered, i.e. across a landscape in northern Arizona represented by an altitudinal gradient encompassing a series of drainages. We also develop a qualitative model for understanding the population dynamics of E. lasiolepis based on patterns of survival and mortality found in this study and previous ones. Gall density was highly variable across the altitudinal gradient, not explained by host plant variables, and thus a poor surrogate fot population abundance. These findings for the first time fail to support the plant vigour and preference hierarchy hypotheses for E. lasiolepis. Dispersal limitation most likely explains the lack of support for these hypotheses at this scale. By contrast, sawfly survival, gall abortion, parasitism and larval mortality were well explained by host plant quality variables and altitude. The larval survival hypothesis was well supported and is thus comparatively scale-invariant. A qualitative model developed here highlighted the importance of both willow water status and disturbance in determining host plant quality, as well as an apparent trade off between shoot length and plant moisture status in determining vital rates across the altitudinal gradient. This study thus demonstrated for the first time the scale-dependent nature of mechanisms underlying the population dynamics E. lasiolepis, and identified the interaction between parasitism and altitude as a novel mechanism underlying spatial patterns in the survival and mortality patterns of this species.     

Modeling and optimal control of insect pest populations

A distributed-parameter population dynamics model is developed specifically for use with variational optimization techniques. The objective is to develop a modeling/ optimization technique that will permit the development of optimal control policies which minimize combined costs of pest control and economic-yield loss. The model results and optimal control policies are continuous and distributed in time and in insect age. The technique is applied to a study of control by pesticide of the southern green stink bug, Nezara viridula (Linnaeus), a major pest of soybeans in the South. In this case study, the model results agree well with field-survey results, while the optimal control trajectories are reasonable and suggest several avenues for further study.     

Fine-scale genetic population structure of southern pine beetle (Coleoptera: Curculionidae) in Mississippi forests

The southern pine beetle, Dendroctonus frontalis Zimmerman, is the most destructive insect pest of pine forests in the southeastern United States, Mexico, and Central America. Southern pine beetle aggressively attacks pine trees, and when in epidemic stages, they are capable of killing even the most healthy pine trees in a short period of time. Despite the amount of destruction caused by the southern pine beetle and the amount of monetary loss faced by the timber industry and recreation, the population genetics of this species has been limited to comparisons among distant geographic locations. This study investigates the fine-scale genetic population structure of the southern pine beetle in Mississippi. Very little genetic differentiation was observed among samples. Bayesian assignment testing failed to detect multiple groups within all samples; estimates of genetic differentiation and genetic distance were very low in magnitude; and a Mantel test did not reveal a significant relationship between genetic distance and geographic distance. These results suggest that management of the southern pine beetle needs to consider the potential movements of individuals within and among national forests and should be focused on a large scale, at least as big as continuously forested areas and possibly even multiple forests. These results further suggest that removal of beetle-infested trees is important.     

Extending and expanding the Darwinian synthesis: the role of complex systems dynamics

Darwinism is defined here as an evolving research tradition based upon the concepts of natural selection acting upon heritable variation articulated via background assumptions about systems dynamics. Darwin's theory of evolution was developed within a context of the background assumptions of Newtonian systems dynamics. The Modern Evolutionary Synthesis, or neo-Darwinism, successfully joined Darwinian selection and Mendelian genetics by developing population genetics informed by background assumptions of Boltzmannian systems dynamics. Currently the Darwinian Research Tradition is changing as it incorporates new information and ideas from molecular biology, paleontology, developmental biology, and systems ecology. This putative expanded and extended synthesis is most perspicuously deployed using background assumptions from complex systems dynamics. Such attempts seek to not only broaden the range of phenomena encompassed by the Darwinian Research Tradition, such as neutral molecular evolution, punctuated equilibrium, as well as developmental biology, and systems ecology more generally, but to also address issues of the emergence of evolutionary novelties as well as of life itself.     

Olive Fruit Fly (Bactrocera oleae) Population Dynamics in the Eastern Mediterranean: Influence of Exogenous Uncertainty on a Monophagous Frugivorous Insect

Despite of the economic importance of the olive fly (Bactrocera oleae) and the large amount of biological and ecological studies on the insect, the factors driving its population dynamics (i.e., population persistence and regulation) had not been analytically investigated until the present study. Specifically, our study investigated the autoregressive process of the olive fly populations, and the joint role of intrinsic and extrinsic factors molding the population dynamics of the insect. Accounting for endogenous dynamics and the influences of exogenous factors such as olive grove temperature, the North Atlantic Oscillation and the presence of potential host fruit, we modeled olive fly populations in five locations in the Eastern Mediterranean region. Our models indicate that the rate of population change is mainly shaped by first and higher order non-monotonic, endogenous dynamics (i.e., density-dependent population feedback). The olive grove temperature was the main exogenous driver, while the North Atlantic Oscillation and fruit availability acted as significant exogenous factors in one of the five populations. Seasonal influences were also relevant for three of the populations. In spite of exogenous effects, the rate of population change was fairly stable along time. We propose that a special reproductive mechanism, such as reproductive quiescence, allows populations of monophagous fruit flies such as the olive fly to remain stable. Further, we discuss how weather factors could impinge constraints on the population dynamics at the local level. Particularly, local temperature dynamics could provide forecasting cues for management guidelines. Jointly, our results advocate for establishing monitoring programs and for a major focus of research on the relationship between life history traits and populations dynamics.     

New field of insect science: Research on the use of insect properties

In recent years, research on “insect properties” has been attracting much attention for industrial applications of insect technology. This is a new field of research that attempts to analyze specific physiological properties of insects to develop technology for helping humankind. The term “insect properties” has been used to refer to “specific biological functions of insects” since around 1986, and it is now widely accepted in Japan. From 1996, the National Institute of Sericultural and Entomological Science (NISES) promoted “Research for utilization of insect properties” as a “Center of Excellence (COE)” project funded by the Science and Technology Agency. At this point, a new research field called “Research for utilization of insect properties” was initiated, and this led to the recognition of this field by the academic community. In the 21st century, remarkable results, including the development of transgenic silkworms and the full decoding of the silkworm genome, have been achieved. It is expected that this advanced technology will be a powerful tool for progress of research on the use of insect properties. This review presents an overview of the current state of research on use of insect properties as a new technology.     

稻纵卷叶螟(Cnaphalocrocis medinalis Guene''e)种群生命系统模型的研究

经过五年来对稻纵卷叶螟自然种群生命表的研究,组建了预测种群动态的生命系统模拟模型。本模型为一变维矩阵组合模型。除能随环境温度而改变矩阵维数外,采用生理年龄为矩阵步长。每一虫期内各个体的发育不一致,矩阵中各元素均为某些环境因素的函数,共组建有18个子模式。在输入起始日期,预测期限,水稻生育期,环境温、湿度和初始种群各年龄向量后,即可自动打印出逐日种群年龄向量及总虫量。计算机模拟曲线与实测曲线基本吻合。本模型可用来预测南京地区稻纵卷叶螟二代迁入峰后种群的发展以至第三代种群各虫态的起始虫量和发生期。     

温度对昆虫繁殖力的影响及其生理生化机制

生殖是昆虫维持种群繁衍的基本生命活动,温度是重要的影响因素之一。温度偏离正常生长温度会影响昆虫性腺发育和能量代谢,从而导致昆虫生殖生理异常,具体表现为产卵数降低、性比偏移、产卵前期变化、孵化率降低等。温度影响昆虫繁殖可能的生化与分子机制主要有性外激素、蜕皮激素、保幼激素及其他内分泌神经肽和热激蛋白等的参与,但该方面的研究尚处在初步探索阶段,多不成系统,需要进一步深入。研究温度对于昆虫繁殖力的影响对害虫爆发预测具有重要作用,可为害虫防治提供新思路;而且研究温度对繁殖力的影响可以预测在全球变暖的背景下昆虫种群密度的新变化和新分布情况,为全球生态系统的动态变化提供参考。     

Modeling of the forest insect population size: a game theory approach

A game theory model of insect population dynamics is proposed. For the case when the population may be in one of two states: when physiological processes are directed to growth and reproduction, and when physiological processes are directed to the development of defense reactions, outbreaks of mass reproduction of insect populations may occur in conditions when population and environment have the "memory", and the state of population and environment depends on their state at the previous time moment. In the framework of the model, the well known effect of insect phase variation during the outbreak of reproduction is explained.     

Diet,Food Intake of Phrynocephalus frontalis （Agamidae） and Its Potential Role in Desert Habitat

We examined the dietary diversity and food intake of Phrynocephalus frontalis, compared the difference of insect diversity in the natural habitats with different lizard densities, and discussed the potential role of this lizard in the desert ecosystem. The results show that： （1） arthropodans of the orders Coleoptera, Hymenoptera and Hemiptera were major dietary components of P. frontalis; （2） coleoptera larvae always formed the predominant component of lizard diets; （3） dietary diversities of P. frontalis were not significantly different between summer and autumn or between the two sexes; （4） the similarity in trophic niches between seasons was 0.756, whereas the similarity in trophic niches between sexes was 0.994; （5） stomach content weight of lizards varied significantly among different seasons, but there was no significant difference in stomach content weight between sexes; （6） insect diversity differed significantly among the groups of the habitat with different degrees of lizard density, and the habitat with moderate lizards density had the highest insect diversity. We infer that P. frontalis prey mainly on insects and change their diet and food intake with season; males and females consumed similar preys in types and weights. As an important predator, P. frontalis could affect the insect community in the arid ecosystem of Hunshandak Desert on the Mongolian Plateau.     

Development of a satellite-based hazard rating system for Dendroctonus frontallis (Coleoptera: Scolytidae) in the Ouachita Mountains of Arkansas

The southern pine beetle, Dendroctonus frontalis Zimmermann (Coleoptera: Scolytidae), is the most damaging forest insect pest of pines (Pinus spp.) throughout the southeastern United States. Hazard rating schemes have been developed for D. frontalis, but for these schemes to be accurate and effective, they require extensive on-site measurements of stand attributes such as host density, age, and basal area. We developed a stand hazard-rating scheme for several watersheds in the Ouachita Highlands of Arkansas based upon remotely sensed data and a geographic information system. A hazard model was developed using stand attributes (tree species, stand age and density, pine basal area, and landform information) and was used to establish baseline hazard maps for the watersheds. Landsat 7 ETM+ data were used for developing new hazard maps. Two dates of Landsat imagery were used in the analyses (August 1999 and October 1999). The highest correlations between hazard rating scores and remotely sensed variables from either of the dates included individual Landsat 7 ETM+ bands in the near- and mid-infrared regions as well as variables derived from various bands (i.e., Tasseled cap parameters, principal component parameters, and vegetation indices such as the calculated simple ratio and normalized difference vegetation index). Best subset regression analyses produced models to predict stand hazard to southern pine beetle that consisted of similar variables that resembled but were more detailed than maps produced using inverse distance weighted techniques. Although the models are specific for the study area, with modifications, they should be transferable to geographically similar areas.