A call for statistical editors in ecology Henrik von Wehrden 1, 2, 3 , Jannik Schultner 1 , and David J. Abson 3 1 Leuphana University Lu ¨ neburg, Institute of Ecology, Faculty of Sustainability, Scharnhorststr. 1, 21335 Lu ¨ neburg, Germany 2 Leuphana University Lu ¨ neburg, Centre of Methods, Scharnhorststr. 1, 21335 Lu ¨ neburg, Germany 3 FuturES Leuphana University, Scharnhorststr. 1, 21335 Lu ¨ neburg, Germany Maintaining the quality of peer-review in the face of an ever-increasing quantity of article submissions [1] repre- sents a major challenge for authors, reviewers, and editors. It is increasingly difficult for time-constrained editors and reviewers to maintain the consistent quality of published papers without increasing turnover periods in the review process. At the same time, the limited publication capacity of journals necessitates increased rejection rates, which in turn leads to reviewers and editors being increasingly criticized, despite their best efforts and intentions, for being subjective, nontransparent, or even biased in their evaluation of manuscripts [2]. Here, we argue that the use of statistical editors within the peer-review process could benefit the field of ecology not only by decreasing manuscript review periods and reducing reviewers’ workloads, but also by improving the quality and reproducibility of statistics of published research. Statistical analyses are an increasingly pivotal part of the scientific process [3]. Concurrent with the increasing use of statistics, there has been an upsurge in the diversity and sophistication of statistical methods used in ecology [4,5]. Many new approaches have been implemented in the past few decades and are now an important part of ecol- ogists’ statistical toolbox. The increased breadth and depth of statistical approaches applied in ecology makes the identification of reviewers with both suitable statisti- cal expertise and knowledge of the specific research field for a given paper an increasingly difficult task for editors. This potentially slows the review process or leads to experts in the research field needlessly reviewing manu- scripts that lack the statistical rigor necessary for peer- review publication. Editors acknowledge this problem by relying on reviewers who provide sufficient statistical expertise [6]. Dedicated statistical editors, as a formal part of the peer-review process, would initially screen the statistical analyses of empirical papers, verifying that the statistics are appropriate, correctly applied and reproducible. Sta- tistical editors would return papers not matching the standards of the given journal to the authors, proposing reanalysis and resubmission (Figure 1). The benefits of using statistical editors are at potentially fourfold: (i) turnover periods for peer-review are decreased. The review process of a manuscript with imperfect statistics typically takes several months, while a statistical editor could return the manuscript to authors within days or weeks, asking for a reanalysis (Figure 1); (ii) reviewers invest less time in imperfect manuscripts. While an em- pirical paper might stand or fall with its statistical design and analysis, reviewers need to consider all of the compo- nents of a manuscript. A statistical editor would check only this one core criterion as a precondition for the subsequent peer-review; (iii) statistical analyses are potentially ap- plied more consistently. By encouraging authors to use more standardized and reproducible approaches, the ap- plication of statistics should become more coherent, mak- ing analyses more accessible to the reader and increasing the opportunity for comparisons between studies and meta-analysis; and (v) using statistical editors may in turn encourage journals to outline and clearly communicate to its contributors the standards of statistics deemed neces- sary for publication and thereby decrease the number of unsuitable initial submissions. Despite the potential advantages of including statistical editors in the review procedure, we acknowledge doing so is not without risk. Adding another layer to the review process potentially creates a new set of ‘knowledge gate- keepers’. Recognizing that ecology is a diverse, often con- text-dependent field, we suggest that statistical editors’ role should be to guide authors in improving their manu- scripts [7], but that the right to reject submissions remains with managing editors and reviewers. An initial check of submissions by a statistical editor could reduce the bur- densomeness of the peer-review process and increase the empirical rigor of ecological research. Letter Time scale Author Editor Reviewer Author Editor Reviewer Stascal editor Sound stascs Inial check Demand revision Current scheme Proposed scheme Days–weeks Weeks–months TRENDS in Ecology & Evolution Figure 1. Illustration of the current scheme of peer-review in ecology and the procedure proposed here. 0169-5347/ ß 2015 Published by Elsevier Ltd. http://dx.doi.org/10.1016/j.tree.2015.03.013 Corresponding author: von Wehrden, H. (Henrik.von_wehrden@leuphana.de). Keywords: peer-review; quantitative ecology; statistical analysis. TREE-1930; No. of Pages 2 Trends in Ecology & Evolution xx (2015) 1–2 1