权益分类	功能权益	普通用户	{{item.name}}会员
{{category.name}}	{{benefitItem.name}}

Host dispersal, individual variation and spatial heterogeneity in avian malaria

禽疟疾的宿主扩散、个体变异和空间异质性

基本信息

批准号：
NE/F005725/1
负责人：
Ben Sheldon
金额：
$ 65.84万
依托单位：
University of Oxford
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2008
资助国家：
英国
起止时间：
2008 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=NE%2FF005725%2F1
关键词：
Host dispersal individual variation spatial

项目摘要

Understanding how individuals vary is particularly important in evolutionary ecology, as this allows us to understand how individuals might respond to their environment. Parasites make up the majority of species, so investigating the interactions between hosts and parasites is an important part of understanding wild populations. Despite this, few such studies have been undertaken at a large enough scale to improve our knowledge of host-parasite interactions in the wild. Host infection with parasites varies markedly in space, even at a local scale in the case of avian malaria in our tit population. Hosts take their parasites with them wherever they go, so the dispersal of hosts is an important factor in understanding the spatial heterogeneity of disease. The risk of parasite infection in wild populations varies in space, often due to variation in the abundance of infectious stages of the parasite. This can be due to variation in environmental conditions such as temperature and humidity, or inherent spatial processes such as disease clustering. Does a site have a high level of disease infection due to the local environment, or because infected individuals have moved there? The proposed project will study a long term population of great tits and blue tits at Wytham Woods, near Oxford. Avian malaria is transmitted by mosquitoes, and infects 30% of breeding blue tits at Wytham. Our large nestbox population means that most breeding birds are individually ringed as chicks so we can track their movements; we can sample around 500 adults of both blue tits and great tits over a useful geographical scale to examine the influence of local environment and host dispersal on the distribution of avian malaria infection. Recent statistical models to predict the distribution and spread of disease that take account of this spatial dimension provide an increasingly good fit to the patterns seen in real life epidemics, such as the 2001 foot and mouth epidemic. Interestingly, the avian malaria parasites in our study population fall into two species groups that each has a different spatial distribution. Developments in the use of DNA-based malaria diagnosis, the use of Geographical Information Sytems to accurately map spatial locations and environmental measurements of habitat variation using satellite imagery and microclimate using miniature data loggers mean that we can confidently approach what were, until recently, logistically daunting questions in ecology. We have three objectives: 1. To understand the causes of individual variation in infection with avian malaria. To what extent is infection determined by natal conditions, maternal status, age or inherited factors? We will use a combination of existing long-term data on avian malaria in tits complemented by data collected during this project, and a large scale field experiment to switch clutches of eggs between nests. 2. To determine the extent to which the observed spatial distribution of the two malaria species results from host-driven processes, particularly host dispersal. We will examine the spatial characteristics of avian malaria infection between classes of birds with different dispersal, both residents and immigrants to the population, and conduct an experiment to manipulate dispersal by moving birds between woodlands. 3. Finally, we will employ a mathematical modelling approach to examine the relative roles if host dispersal, maternal immunity and the risk of malaria infection in generating the spatial patterns of disease we see in our study population. These models will concentrate on the important effects identified by our preceding work, generating new testable hypotheses and leading to further empirical and modelling work. These three approaches are made possible by the large and well studied population of tits, and will address the fundamental ecology of avian malaria in a wild bird population, while increasing our wider understanding of disease.

了解个体如何变化在进化生态学中特别重要，因为这使我们能够了解个体如何对环境做出反应。寄生虫占物种的大多数，因此调查宿主和寄生虫之间的相互作用是了解野生种群的重要组成部分。尽管如此，很少有这样的研究已经进行了足够大的规模，以提高我们的知识，宿主-寄生虫在野外的相互作用。寄生虫的宿主感染在空间上有明显的差异，即使在我们山雀种群中的禽疟病例中也是如此。宿主无论走到哪里，都会携带寄生虫，因此宿主的传播是了解疾病空间异质性的一个重要因素。野生种群中寄生虫感染的风险在空间上各不相同，这通常是由于寄生虫感染阶段丰度的变化。这可能是由于温度和湿度等环境条件的变化，或疾病聚集等固有的空间过程。一个地点的疾病感染率高是因为当地环境，还是因为感染者搬到那里？拟议中的项目将在牛津附近的Wytham Woods研究大山雀和蓝山雀的长期种群。禽疟疾是由蚊子传播的，在怀瑟姆，30%的繁殖蓝山雀会感染。我们庞大的巢箱种群意味着大多数繁殖鸟类都是单独的雏鸟，因此我们可以跟踪它们的运动;我们可以在一个有用的地理范围内对大约500只成年蓝山雀和大山雀进行采样，以研究当地环境和宿主扩散对禽疟疾感染分布的影响。最近预测疾病分布和传播的统计模型考虑到了这一空间维度，与真实的流行病（如2001年的口蹄疫）的模式越来越吻合。有趣的是，我们研究人群中的禽疟疾寄生虫分为两个物种组，每个物种组具有不同的空间分布。在使用基于DNA的疟疾诊断、使用地理信息系统准确绘制空间位置图、使用卫星图像对生境变化进行环境测量以及使用微型数据记录仪对小气候进行测量方面的发展，意味着我们可以自信地处理直到最近还在逻辑上令人生畏的生态学问题。我们有三个目标：1。了解禽疟感染个体差异的原因。感染在多大程度上是由纳塔尔条件、母亲状况、年龄或遗传因素决定的？我们将使用现有的长期数据的组合，在山雀禽疟疾补充数据收集在这个项目中，和一个大规模的现场实验，以切换窝之间的鸡蛋离合器。2.确定在何种程度上观察到的空间分布的两种疟疾的结果主机驱动的过程，特别是主机的传播。我们将研究不同传播的鸟类（居民和移民）之间的禽疟感染的空间特征，并进行一项实验，通过在林地之间移动鸟类来操纵传播。3.最后，我们将采用数学建模的方法来研究的相对作用，如果主机扩散，孕产妇免疫力和疟疾感染的风险，在产生的疾病的空间模式，我们看到在我们的研究人群。这些模型将集中在我们以前的工作所确定的重要影响，产生新的可检验的假设，并导致进一步的实证和建模工作。这三种方法是由大量的和充分研究的山雀种群，并将解决野生鸟类种群中的禽疟疾的基本生态学，同时增加我们对疾病的更广泛的了解。