Collaborative Research: Modeling Infectious Diseases: How Much Ecological Complexity Must We Address?

传染病生态特别竞赛-2011年春季生态系统不可否认是复杂的。评估充分理解它们的动力学所需的适当复杂程度对于更有效地提高模型的预测精度至关重要。通过这笔赠款的资金，这项理论和实证研究将分析增加宿主-寄生虫模型复杂性的好处，以及包括复杂性在内的动态模型预测准确性的提高程度。来自加州大学圣巴巴拉分校和普林斯顿大学的研究小组将沿着北美太平洋海岸的纬度梯度，研究寄生虫在16个河口系统的食物网中所起的作用。他们将对在这些网络中发现的四种局部寄生虫进行建模，并进行实验室和实地研究，以使模型参数化。这些模型的不同版本将在生态复杂性方面有所不同，包括替代宿主、其他寄生虫、关于生命阶段的不同细节、非宿主的直接和间接影响以及温度。这项研究具有创新性，当然值得投入资金。这项研究将促进对模型性能如何随着复杂性的增加而变化的理解，并调查解决生活期复杂性、替代寄主多样性和食物网复杂性所需的详细程度。研究模型的性能如何随着复杂性的提高而提高，以及包括这种复杂性的成本将提供对传染病模型所需的最适当的复杂性水平的洞察，以使其具有最合适的预测性。这个项目的更广泛影响是非常强大的。这项研究将为如何在复杂系统中最有效地模拟传染病提供一个框架，并将解决寄生虫如何影响生态网络和周围生物多样性的问题。该项目将为培训和支助一名博士后研究员、研究生和本科生，包括来自代表性不足群体的个人提供极好的资金。这项研究还将对K-12的教师和学生进行出色和非常适当的宣传，并将通过与来自墨西哥、捷克共和国、阿根廷和澳大利亚的科学家和学生的互动来加强国际科学合作。

Ecology of Infectious Disease Special Competition - Spring 2011Ecological systems are undeniably complex. Evaluating the appropriate level of complexity needed to fully understand their dynamics is essential to more efficiently increase the predictive accuracy of models. With funding through this Grant, this theoretical and empirical research will analyze the benefits of added complexity in host-parasite models and the extent to which including complexity increases the predictive accuracy of dynamical models. The team from the University of California-Santa Barbara and Princeton University will examine the role played by parasites in food webs for 16 estuarine systems along a latitudinal gradient of the Pacific coast of North America. They will model four focal parasites found in these webs and perform laboratory and field studies to parameterize the model. Versions of these models will vary in aspects of ecological complexity, including alternative hosts, other parasites, varying detail about life stages, direct and indirect effects of non-hosts and temperature.The study is innovative and certainly worth of funding. The research will advance understanding of how model performance changes with added complexity and investigate the level of detail needed to address life-stage complexity, alternative host diversity and food web complexity. Examining how model performance improves with complexity and the cost of including that complexity will provide insight on the most appropriate level of complexity needed for infectious disease models to be most suitably predictive. The broader impacts of this project are very strong. The research from this study will provide a framework for how to most effectively model infectious diseases in complex systems and will address how parasites impact ecological networks and surrounding biodiversity. This project will make excellent provision for the training and support of a post-doctoral researcher, graduate students and undergraduates, including individuals from under-represented groups. This study will also feature excellent and very appropriate outreach to K-12 teachers and students and will enhance international scientific collaboration through interaction with scientists and students from Mexico, Czech Republic, Argentina and Australia.