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      Fine-Scale Variation in Vector Host Use and Force of Infection Drive Localized Patterns of West Nile Virus Transmission

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          Abstract

          The influence of host diversity on multi-host pathogen transmission and persistence can be confounded by the large number of species and biological interactions that can characterize many transmission systems. For vector-borne pathogens, the composition of host communities has been hypothesized to affect transmission; however, the specific characteristics of host communities that affect transmission remain largely unknown. We tested the hypothesis that vector host use and force of infection (i.e., the summed number of infectious mosquitoes resulting from feeding upon each vertebrate host within a community of hosts), and not simply host diversity or richness, determine local infection rates of West Nile virus (WNV) in mosquito vectors. In suburban Chicago, Illinois, USA, we estimated community force of infection for West Nile virus using data on Culex pipiens mosquito host selection and WNV vertebrate reservoir competence for each host species in multiple residential and semi-natural study sites. We found host community force of infection interacted with avian diversity to influence WNV infection in Culex mosquitoes across the study area. Two avian species, the American robin ( Turdus migratorius) and the house sparrow ( Passer domesticus), produced 95.8% of the infectious Cx. pipiens mosquitoes and showed a significant positive association with WNV infection in Culex spp. mosquitoes. Therefore, indices of community structure, such as species diversity or richness, may not be reliable indicators of transmission risk at fine spatial scales in vector-borne disease systems. Rather, robust assessment of local transmission risk should incorporate heterogeneity in vector host feeding and variation in vertebrate reservoir competence at the spatial scale of vector-host interaction.

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          Functional diversity: back to basics and looking forward.

          Functional diversity is a component of biodiversity that generally concerns the range of things that organisms do in communities and ecosystems. Here, we review how functional diversity can explain and predict the impact of organisms on ecosystems and thereby provide a mechanistic link between the two. Critical points in developing predictive measures of functional diversity are the choice of functional traits with which organisms are distinguished, how the diversity of that trait information is summarized into a measure of functional diversity, and that the measures of functional diversity are validated through quantitative analyses and experimental tests. There is a vast amount of trait information available for plant species and a substantial amount for animals. Choosing which traits to include in a particular measure of functional diversity will depend on the specific aims of a particular study. Quantitative methods for choosing traits and for assigning weighting to traits are being developed, but need much more work before we can be confident about trait choice. The number of ways of measuring functional diversity is growing rapidly. We divide them into four main groups. The first, the number of functional groups or types, has significant problems and researchers are more frequently using measures that do not require species to be grouped. Of these, some measure diversity by summarizing distances between species in trait space, some by estimating the size of the dendrogram required to describe the difference, and some include information about species' abundances. We show some new and important differences between these, as well as what they indicate about the responses of assemblages to loss of individuals. There is good experimental and analytical evidence that functional diversity can provide a link between organisms and ecosystems but greater validation of measures is required. We suggest that non-significant results have a range of alternate explanations that do not necessarily contradict positive effects of functional diversity. Finally, we suggest areas for development of techniques used to measure functional diversity, highlight some exciting questions that are being addressed using ideas about functional diversity, and suggest some directions for novel research.
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            R: a language and environment for statistic computing

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              Measuring Biological Diversity

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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2011
                19 August 2011
                : 6
                : 8
                : e23767
                Affiliations
                [1 ]Department of Pathobiological Sciences, University of Wisconsin, Madison, Wisconsin, United States of America
                [2 ]Department of Environmental Studies, Emory University, Atlanta, Georgia, United States of America
                [3 ]Programa de Investigación en Enfermedades Tropicales, Escuela de Medicina Veterinaria, Universidad Nacional, Heredia, Costa Rica
                [4 ]Graduate School of Environmental Science & Global Center of Excellence Program on Integrated Field and Environmental Studies, Hokkaido University, Sapporo, Hokkaido, Japan
                [5 ]Department of Natural Resources and Environmental Sciences, University of Illinois, Urbana, Illinois, United States of America
                [6 ]Department of Pathobiology, University of Illinois, Urbana, Illinois, United States of America
                [7 ]Conservation Biology, University of Minnesota, St. Paul, Minnesota, United States of America
                [8 ]Department of Microbiology and Molecular Genetics, Michigan State University, Lansing, Michigan, United States of America
                Institut Pasteur, France
                Author notes

                Conceived and designed the experiments: GLH UDK JDB MOR EDW TLG. Performed the experiments: GLH SRL. Analyzed the data: GLH LFC. Contributed reagents/materials/analysis tools: EDW. Wrote the paper: GLH LFC TKA.

                Article
                PONE-D-11-07553
                10.1371/journal.pone.0023767
                3158794
                21886821
                0a897b07-d4ab-4a39-b401-9f995901d634
                Hamer et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 21 April 2011
                : 25 July 2011
                Page count
                Pages: 8
                Categories
                Research Article
                Biology
                Ecology
                Community Ecology
                Community Structure
                Medicine
                Epidemiology
                Infectious Disease Epidemiology
                Public Health
                Disease Ecology
                Veterinary Science
                Veterinary Diseases
                Zoonotic Diseases
                Veterinary Epidemiology

                Uncategorized
                Uncategorized

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