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      Nests of red wood ants ( Formica rufa-group) are positively associated with tectonic faults: a double-blind test

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          Abstract

          Ecological studies often are subjected to unintentional biases, suggesting that improved research designs for hypothesis testing should be used. Double-blind ecological studies are rare but necessary to minimize sampling biases and omission errors, and improve the reliability of research. We used a double-blind design to evaluate associations between nests of red wood ants ( Formica rufa, RWA) and the distribution of tectonic faults. We randomly sampled two regions in western Denmark to map the spatial distribution of RWA nests. We then calculated nest proximity to the nearest active tectonic faults. Red wood ant nests were eight times more likely to be found within 60 m of known tectonic faults than were random points in the same region but without nests. This pattern paralleled the directionality of the fault system, with NNE–SSW faults having the strongest associations with RWA nests. The nest locations were collected without knowledge of the spatial distribution of active faults thus we are confident that the results are neither biased nor artefactual. This example highlights the benefits of double-blind designs in reducing sampling biases, testing controversial hypotheses, and increasing the reliability of the conclusions of research.

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          R: language and environment for statistical computing

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            Evidence of Experimental Bias in the Life Sciences: Why We Need Blind Data Recording

            Observer bias and other “experimenter effects” occur when researchers’ expectations influence study outcome. These biases are strongest when researchers expect a particular result, are measuring subjective variables, and have an incentive to produce data that confirm predictions. To minimize bias, it is good practice to work “blind,” meaning that experimenters are unaware of the identity or treatment group of their subjects while conducting research. Here, using text mining and a literature review, we find evidence that blind protocols are uncommon in the life sciences and that nonblind studies tend to report higher effect sizes and more significant p-values. We discuss methods to minimize bias and urge researchers, editors, and peer reviewers to keep blind protocols in mind.
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              Blind trust in unblinded observation in Ecology, Evolution, and Behavior

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                12 October 2017
                2017
                : 5
                : e3903
                Affiliations
                [1 ]Department of Biology, Lawrence University , Appleton, WI, USA
                [2 ]Faculty of Electrical Engineering and Information Technology, Technical University of Dortmund , Dortmund, Germany
                [3 ]IT-Consulting Berberich , Erftstadt, Germany
                [4 ]Rubenstein School of Environment and Natural Resources, University of Vermont , Burlington, VT, USA
                [5 ]Harvard Forest, Harvard University , Petersham, MA, USA
                Author information
                http://orcid.org/0000-0002-3901-8713
                http://orcid.org/0000-0002-9566-3813
                http://orcid.org/0000-0003-4151-6081
                Article
                3903
                10.7717/peerj.3903
                5641425
                73c19a2b-8857-41d1-988f-a4d6841f458f
                © 2017 Del Toro et al.

                This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ) and either DOI or URL of the article must be cited.

                History
                : 6 July 2017
                : 18 September 2017
                Funding
                Funded by: National Science Foundation Postdoctoral Research Fellowship
                Funded by: NSF grant
                Award ID: DEB-1136646
                Funded by: National Science Foundation Dimensions of Biodiversity grant
                Award ID: NSF-1136703
                Israel Del Toro was supported by a National Science Foundation Postdoctoral Research Fellowship; Aaron M. Ellison was supported by NSF grant (DEB-1136646); Nathan J. Sanders was supported by a National Science Foundation Dimensions of Biodiversity grant (NSF-1136703). The funders had no role in study design, data collection, and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Biogeography
                Ecology
                Entomology
                Statistics

                double-blind,tectonic faults,formicidae,species distributions,clustering

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