Model-guided fieldwork: Practical guidelines for multidisciplinary research on wildlife ecological and epidemiological dynamics

Olivier Restif, David T.S. Hayman, Juliet R.C. Pulliam, Raina K. Plowright, Dylan B. George, Angela D. Luis, Andrew A. Cunningham, Richard A. Bowen, Anthony R. Fooks, Thomas J. O'Shea, James L.N. Wood, Colleen T. Webb

Research output: Contribution to journalComment/debate

117 Scopus citations

Abstract

Infectious disease ecology has recently raised its public profile beyond the scientific community due to the major threats that wildlife infections pose to biological conservation, animal welfare, human health and food security. As we start unravelling the full extent of emerging infectious diseases, there is an urgent need to facilitate multidisciplinary research in this area. Even though research in ecology has always had a strong theoretical component, cultural and technical hurdles often hamper direct collaboration between theoreticians and empiricists. Building upon our collective experience of multidisciplinary research and teaching in this area, we propose practical guidelines to help with effective integration among mathematical modelling, fieldwork and laboratory work. Modelling tools can be used at all steps of a field-based research programme, from the formulation of working hypotheses to field study design and data analysis. We illustrate our model-guided fieldwork framework with two case studies we have been conducting on wildlife infectious diseases: plague transmission in prairie dogs and lyssavirus dynamics in American and African bats. These demonstrate that mechanistic models, if properly integrated in research programmes, can provide a framework for holistic approaches to complex biological systems. 2012 Crown.

Original languageEnglish
Pages (from-to)1083-1094
Number of pages12
JournalEcology Letters
Volume15
Issue number10
DOIs
StatePublished - Oct 2012

Keywords

  • Field ecology
  • Infectious diseases
  • Mathematical models
  • Statistical models
  • Study design
  • Wildlife epidemiology

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