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      Appraisal of unimodal cues during agonistic interactions in Maylandia zebra

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          Abstract

          Communication is essential during social interactions including animal conflicts and it is often a complex process involving multiple sensory channels or modalities. To better understand how different modalities interact during communication, it is fundamental to study the behavioural responses to both the composite multimodal signal and each unimodal component with adequate experimental protocols. Here we test how an African cichlid, which communicates with multiple senses, responds to different sensory stimuli in a social relevant scenario. We tested Maylandia zebra males with isolated chemical (urine or holding water coming both from dominant males), visual (real opponent or video playback) and acoustic (agonistic sounds) cues during agonistic interactions. We showed that (1) these fish relied mostly on the visual modality, showing increased aggressiveness in response to the sight of a real contestant but no responses to urine or agonistic sounds presented separately, (2) video playback in our study did not appear appropriate to test the visual modality and needs more technical prospecting, (3) holding water provoked territorial behaviours and seems to be promising for the investigation into the role of the chemical channel in this species. Our findings suggest that unimodal signals are non-redundant but how different sensory modalities interplay during communication remains largely unknown in fish.

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          GLUMIP 2.0: SAS/IML Software for Planning Internal Pilots.

          Internal pilot designs involve conducting interim power analysis (without interim data analysis) to modify the final sample size. Recently developed techniques have been described to avoid the type I error rate inflation inherent to unadjusted hypothesis tests, while still providing the advantages of an internal pilot design. We present GLUMIP 2.0, the latest version of our free SAS/IML software for planning internal pilot studies in the general linear univariate model (GLUM) framework. The new analytic forms incorporated into the updated software solve many problems inherent to current internal pilot techniques for linear models with Gaussian errors. Hence, the GLUMIP 2.0 software makes it easy to perform exact power analysis for internal pilots under the GLUM framework with independent Gaussian errors and fixed predictors.
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            Fitting Linear Mixed-Effects Models using lme4

            Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.
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              An introduction to multimodal communication

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                peerj
                peerj
                PeerJ
                PeerJ Inc. (San Francisco, USA )
                2167-8359
                1 August 2017
                2017
                : 5
                : e3643
                Affiliations
                [1 ]Equipe Neuro-Ethologie Sensorielle, ENES/Neuro-PSI CNRS UMR 9197, Université de Lyon/Saint-Etienne , Saint-Etienne, France
                [2 ]INRIA, Beagle, Université de Lyon , Villeurbanne, France
                [3 ]Departamento de Biologia Animal and cE3c—Centre for Ecology, Evolution and Environmental Changes, Faculdade de Ciências, Universidade de Lisboa , Lisbon, Portugal
                [4 ]MARE—Marine and Environmental Sciences Centre, ISPA, Instituto Universitário , Lisbon, Portugal
                Article
                3643
                10.7717/peerj.3643
                5543927
                28785523
                30662e06-d477-4c3b-8212-d7e9230398b0
                ©2017 Chabrolles 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
                : 15 May 2017
                : 12 July 2017
                Funding
                Funded by: Université de Lyon/Saint-Etienne
                Funded by: Centre National de la Recherche Scientifique (CNRS)
                Funded by: French ‘Ministère de la Recherche
                This study has been funded by the Université de Lyon/Saint-Etienne and the Centre National de la Recherche Scientifique (CNRS). LC was supported by a PhD fellowship from the French ‘Ministère de la Recherche’. Travel between France and Portugal was funded by the Université de Lyon/Saint-Etienne. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Animal Behavior
                Zoology

                playback experiments,visual,acoustic,agonistic interactions,unimodal signals,olfaction

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