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      Capturing complexity: field-testing the use of ‘structure from motion’ derived virtual models to replicate standard measures of reef physical structure

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          Abstract

          Reef structural complexity provides important refuge habitat for a range of marine organisms, and is a useful indicator of the health and resilience of reefs as a whole. Marine scientists have recently begun to use ‘Structure from Motion’ (SfM) photogrammetry in order to accurately and repeatably capture the 3D structure of physical objects underwater, including reefs. There has however been limited research on the comparability of this new method with existing analogue methods already used widely for measuring and monitoring 3D structure, such as ‘tape and chain rugosity index (RI)’ and graded visual assessments. Our findings show that analogue and SfM RI can be reliably converted over a standard 10-m reef section (SfM RI = 1.348 × chain RI—0.359, r 2 = 0.82; and Chain RI = 0.606 × SfM RI + 0.465) for RI values up to 2.0; however, SfM RI values above this number become increasingly divergent from traditional tape and chain measurements. Additionally, we found SfM RI correlates well with visual assessment grades of coral reefs over a 10 × 10 m area (SfM RI = 0.1461 × visual grade + 1.117; r 2 = 0.83). The SfM method is shown to be affordable and non-destructive whilst also allowing the data collected to be archival, less biased by the observer, and broader in its scope of applications than standard methods. This work allows researchers to easily transition from analogue to digital structural assessment techniques, facilitating continued long-term monitoring, whilst also improving the quality and additional research value of the data collected.

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          A manifesto for reproducible science

          Improving the reliability and efficiency of scientific research will increase the credibility of the published scientific literature and accelerate discovery. Here we argue for the adoption of measures to optimize key elements of the scientific process: methods, reporting and dissemination, reproducibility, evaluation and incentives. There is some evidence from both simulations and empirical studies supporting the likely effectiveness of these measures, but their broad adoption by researchers, institutions, funders and journals will require iterative evaluation and improvement. We discuss the goals of these measures, and how they can be implemented, in the hope that this will facilitate action toward improving the transparency, reproducibility and efficiency of scientific research.
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            Gwyddion: an open-source software for SPM data analysis

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              ‘Structure-from-Motion’ photogrammetry: A low-cost, effective tool for geoscience applications

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                Author and article information

                Contributors
                Journal
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ
                PeerJ Inc. (San Diego, USA )
                2167-8359
                4 March 2019
                2019
                : 7
                : e6540
                Affiliations
                [1 ]Department of Life Sciences, Natural History Museum of London , London, UK
                [2 ]Centre for Biodiversity and Environment Research, University College London, University of London , London, UK
                [3 ]Conservation Programmes, Zoological Society of London , London, UK
                [4 ]Tritonia Scientific , Oban, UK
                [5 ]NERC National Facility for Scientific Diving, Scottish Association for Marine Science , Oban, UK
                [6 ]Centre for Ecology and Conservation (CEC), University of Exeter, Penryn Campus , Cornwall, UK
                [7 ]Department of Life Sciences, Imperial College London , London, UK
                Author information
                http://orcid.org/0000-0002-8609-6204
                Article
                6540
                10.7717/peerj.6540
                6404651
                30863678
                13ff697a-e4f5-47ac-9268-15a66790240b
                © 2019 Bayley 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
                : 18 October 2018
                : 30 January 2019
                Funding
                Funded by: Natural Environment Research Council (NERC)
                Funded by: Zoological Society of London CASE award: NERC grant reference
                Award ID: NE/L002485/1
                Funded by: NERC Services and Facilities capital equipment scheme
                Funded by: The Bertarelli Foundation
                This work was supported by a Natural Environment Research Council (NERC) studentship and Zoological Society of London CASE award (NERC grant reference: NE/L002485/1). Additional funding for software and hardware used in analysis was provided through the NERC Services and Facilities capital equipment scheme. Equipment support was provided by the Bertarelli Foundation. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
                Categories
                Conservation Biology
                Marine Biology
                Computational Science
                Climate Change Biology
                Spatial and Geographic Information Science

                structure,monitoring,complexity,reef,photogrammetry,imaging
                structure, monitoring, complexity, reef, photogrammetry, imaging

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