Best Paper in Pedometrics 2016
D G Rossiter, Chairman Pedometrics Awards Committee
e-mail: dgr2@cornell.edu
Thirty votes were received. Unlike the 2015 award, this time there were no clear favourites, and in fact two papers received the most the first place votes. Seven of the eight papers received at least one first-place vote, and the voters had quite a range of rankings, with quite some controversy (expressed to me in e-mails with the votes) about what is pedometrics and what are research vs. review. In any case the papers were all excellent and of high importance, either in terms of their methods, their concepts, or their results. After re-assigning votes through seven rounds, they both ended up with 14 votes. For the first time we have a split victory; in DOI order:
- Viscarra Rossel, R.A., T. Behrens et al. (2016). A global spectral library to characterize the world’s soil. Earth-Science Reviews 155, 198–230. https://doi.org/10.1016/j.earscirev.2016.01.012
- Poggio, L., Gimona, A., Spezia, L., & Brewer, M. J. (2016). Bayesian spatial modelling of soil properties and their uncertainty: The example of soil organic matter in Scotland using R-INLA. Geoderma, 277, 69–82. https://doi.org/10.1016/j.geoderma.2016.04.026
The Viscarra Rossel et al. paper was appreciated for the global coverage and integration of diverse sources of information into a consistent product that can be used for pedometric research. As these authors say, “We hope that this work will reinvigorate our community’s discussion towards larger, more coordinated collaborations. We also hope that use of the database will deepen our understanding of soil so that we might sustainably manage it and extend the research outcomes of the soil, earth and environmental sciences towards applications that we have not yet dreamed of.”
The Poggio et al. paper was appreciated for the introduction of a cutting-edge geostatistical technique to the digital soil mapping toolbox. As the authors say “The Bayesian framework using INLA offers a viable alternative to existing methods for digital soil mapping, with comparable validation results, important computational gains, good assessment of uncertainty and potential for integrated modelling uncertainty propagation.”
Who says your vote doesn’t count? If one more person had voted for either of these papers higher than the other, that paper would have won. Thanks to all who nominated papers and who voted after having read these excellent papers. For those who have not read all the papers, I encourage you to find time to do so; you will be informed of the state-of-the-art in pedometrics and stimulated in your own work. This award, along with the 2015 award, was presented at Pedometrics 2017 in Wageningen.