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Chapter Twenty - Mycoplasmal conjunctivitis in house finches: the study of an emerging disease
- from Part III - Understanding wildlife disease ecology at the community and landscape level
- Edited by Kenneth Wilson, Lancaster University, Andy Fenton, University of Liverpool, Dan Tompkins
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- Book:
- Wildlife Disease Ecology
- Published online:
- 28 October 2019
- Print publication:
- 14 November 2019, pp 574-597
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Summary
Mycoplasma gallisepticum causes disease in poultry and emerged as a novel pathogen in house finches resulting in a mycoplasmal conjunctivitis epidemic across North America after a single successful host jump from poultry to house finches. The rapid spread of the epidemic across eastern North America, causing a decline in host abundance, has been documented. Once established, disease prevalence showed regular seasonal variation: a late summer/early autumn peak, a mid-December minimum, followed by a late winter peak and a breeding season minimum, which requires seasonal reproduction (providing an autumn pulse of naïve hosts) and winter social aggregation as well as partial immunity of recovered birds. Virulence evolved rapidly: in eastern populations it increased once the disease had become endemic. In western North America the established strain was of much lower virulence, but once established also increased in virulence. We show that virulence may evolve in opposite directions depending on selection pressures. A detailed study showed that disease decreased survival and mobility and a high proportion of birds recovered; also that re-observation rates of clinically diseased birds are often different from those of asymptomatic birds; only calculations which include this effect allow an accurate estimate of disease prevalence.
21 - Use of citizen-science monitoring for pattern discovery and biological inference
- Edited by Robert A. Gitzen , University of Missouri, Columbia, Joshua J. Millspaugh, University of Missouri, Columbia, Andrew B. Cooper, Simon Fraser University, British Columbia, Daniel S. Licht
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- Book:
- Design and Analysis of Long-term Ecological Monitoring Studies
- Published online:
- 05 July 2012
- Print publication:
- 07 June 2012, pp 460-478
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Summary
Introduction
Citizen science, broadly speaking, is the involvement of amateur (i.e. unpaid, but not necessarily unskilled) participants in the process of scientific studies, typically with data collection or data processing (Cooper et al. 2007, Silvertown 2009). The benefits of citizen-science monitoring programs for public engagement and education are often emphasized (Chapter 23), but here we focus on programs sharing the same primary motivation as those discussed in the rest of this volume: obtaining data and information needed for managing and understanding ecological systems. Often, “amateur” monitoring may be the only or the most cost-effective approach for obtaining such information. For example, an important role for citizen science in monitoring of animals or plants follows from the fact that identification of species is currently difficult or impossible to automate, although technological inroads are being made (e.g. Brower 2006, Sarpola et al. 2008). Thus, if the goal is to monitor over large geographical areas such as most or all of a species’ range, data will often need to be collected by a large number of people, and volunteer-dependent monitoring will be the only logistically feasible approach (with very few exceptions, e.g. Smith 1995).
While creating opportunities for monitoring, volunteer-based approaches also can introduce challenges for the design of studies and analyses of the resultant data (Box 21.1). Challenges are created by three common characteristics of data that come from citizen-science projects. First, the wide geographic and temporal scope of studies mean that attention must be paid to maintaining consistency in data-collection protocols and checking for potential spatial and temporal sources of bias. Second, data often must be collected using protocols that are potentially not as demanding of the data collectors as are protocols for professionally collected data. Third, data are often collected for surveillance monitoring and the general nature of such data may allow their re-use for multiple purposes, necessitating additional steps in analyses to investigate the possibility that biases exist for which the study design does not adequately control. Although we do not wish to imply that volunteer-collected data will always have these characteristics, we believe that these traits are present frequently enough in citizen-science monitoring to warrant their place in motivating the topics discussed in this chapter. In contrast, if data from a citizen-science project can be collected with a tightly controlled survey design and are well-suited to answering a focused question using a well thought out parametric statistical model or with a design-based analysis, then there is nothing to distinguish such a project from any other monitoring initiative discussed in this volume. Aside from issues discussed under Data Collection and Management, below, we will not discuss these “targeted” projects.