Big Decisions and Sparse Data: Adapting Scientific Publishing to the Needs of Practical Conservation

The biggest challenge in conservation biology is breaking down the gap between research and practical management. A major obstacle is the fact that many researchers are unwilling to tackle projects likely to produce sparse or messy data because the results would be difficult to publish in refereed journals. The obvious solution to sparse data is to build up results from multiple studies. Consequently, we suggest that there needs to be greater emphasis in conservation biology on publishing papers that can be built on by subsequent research rather than on papers that produce clear results individually. This building approach requires: (1) a stronger theoretical framework, in which researchers attempt to anticipate models that will be relevant in future studies and incorporate expected differences among studies into those models; (2) use of modern methods for model selection and multi-model inference, and publication of parameter estimates under a range of plausible models; (3) explicit incorporation of prior information into each case study; and (4) planning management treatments in an adaptive framework that considers treatments applied in other studies. We encourage journals to publish papers that promote this building approach rather than expecting papers to conform to traditional standards of rigor as stand-alone papers, and believe that this shift in publishing philosophy would better encourage researchers to tackle the most urgent conservation problems.

Reflections on practical approaches to involving children and young people in the data analysis process

This article reflects on key methodological issues emerging from children and young people's involvement in data analysis processes. We outline a pragmatic framework illustrating different approaches to engaging children, using two case studies of children's experiences of participating in data analysis. The article highlights methods of engagement and important issues such as the balance of power between adults and children, training, support, ethical considerations, time and resources. We argue that involving children in data analysis processes can have several benefits, including enabling a greater understanding of children's perspectives and helping to prioritise children's agendas in policy and practice. (C) 2007 The Author(s). Journal compilation (C) 2007 National Children's Bureau.