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This is a protocol for generating images to be used in 3D model building via Agisoft Metashape for coral photogrametry. This will cover underwater, field-based methods and tips to collect photographs and preprocessing of photos to improve model building. Image capture is the most important part of 3D photogrammetry because the photos taken at this point will be all that you'll have to build models and collect data. As such, you want to ensure you have enough photos to work with in the future so, in general, more is better. That being said, too many blurry or out of focus pictures will hamper model building. You can optimize your time in the field by taking enough photos from the appropriate angles, however efficiency will come with practice. This is the protocol developed and used by the Kenkel lab to phenotype Acropora cervicornis colonies as part of field operations in the Florida Keys. We incorporate Agisoft Metashape markers in this workflow to scale models and improved model building. The scaling objects used by the Kenkel lab are custom-made, adjustable PVC arrays that include unique markers and bleaching color cards, affectionately called the "Tomahawk". Specs for building a Tomahawk are included in this protocol. Filtering and pre-processing of photos is not always necessary but can be used to salvage 3D models that would be otherwise blurry or incomplete. Here, we describe photo editing in Adobe Lightroom to adjust several characteristics of hundreds of images simultaneously. For a walkthrough and scripts to run Agisoft Metashape on the command line, see https://github.com/wyattmillion/Coral3DPhotogram. For directions to phenotype coral from 3D models see our Phenotyping in MeshLab protocol. These protocols, while created for branching coral, can be applied to 3D models of any coral morphology or any object really. Our goal is to make easy-to-use protocols using accessible softwares in the hopes of creating a standardized method for 3D photogrammetry in coral biology. DOI dx.doi.org/10.17504/protocols.io.bgdcjs2w 

This protocol describes the process of phenotyping branching coral using the 3D model editing software, MeshLab. MeshLab is a free, straightforward software to analyze 3D models of corals that is especially useful in its ability to import color from Agisoft Metashape models. This protocol outlines the steps used by the Kenkel lab to noninvasively phenotype Acropora cervicornis colonies for total linear extension (TLE), surface area, volume, and volume of interstitial space. We incorporate Agisoft Metashape markers with our Tomahawk scaling system (see Image Capture Protocol) in our workflow which is useful for scaling and to improve model building. Other scaling objects can be used, however these markers provide a consistent scale that do not obstruct the coral during image capture. MeshLab measurements of TLE have been groundtruthed to field measures of TLE. 3D surface area and volume have not yet been compared to traditional methods of wax dipping, for surface area, and water displacement, for volume. However, in tests with shapes of known dimensions, i.e. cubes, MeshLab produced accurate measures of 3D surface area and volume when compared to calculated surface area and volume. For directions to photograph coral for 3D photogrammetry see our Image Capture Protocol. For a walkthrough and scripts to run Agisoft Metashape on the command line, see https://github.com/wyattmillion/Coral3DPhotogram. These protocols, while created for branching coral, can be applied to 3D models of any coral morphology or any object really. Our goal is to make easy-to-use protocols using accessible softwares in the hopes of creating a standardized method for 3D photogrammetry in coral biology. Go to http://www.meshlab.net/#download to download the appropriate software for your operating system. P. Cignoni, M. Callieri, M. Corsini, M. Dellepiane, F. Ganovelli, G. Ranzuglia MeshLab: an Open-Source Mesh Processing Tool Sixth Eurographics Italian Chapter Conference, page 129-136, 2008 DOI dx.doi.org/10.17504/protocols.io.bgbpjsmn 

A formidable challenge for global change biologists is to predict how natural populations will respond to the emergence of conditions not observed at present, termed novel climates. Popular approaches to predict population vulnerability are based on the expected degree of novelty relative to the amplitude of historical climate fluctuations experienced by a population. Here, we argue that predictions focused on amplitude may be inaccurate because they ignore the predictability of environmental fluctuations in driving patterns of evolution and responses to climate change. To address this disconnect, we review major findings of evolutionary theory demonstrating the conditions under which phenotypic plasticity is likely to evolve in natural populations, and how plasticity decreases population vulnerability to novel environments. We outline key criteria that experimental studies should aim for to effectively test theoretical predictions, while controlling for the degree of climate novelty. We show that such targeted tests of evolutionary theory are rare, with marine systems being overall underrepresented in this venture despite exhibiting unique opportunities to test theory. We conclude that with more robust experimental designs that manipulate both the amplitude and predictability of fluctuations, while controlling for the degree of novelty, we may better predict population vulnerability to climate change. 

Abstract Coral bleaching is the single largest global threat to coral reefs worldwide. Integrating the diverse body of work on coral bleaching is critical to understanding and combating this global problem. Yet investigating the drivers, patterns, and processes of coral bleaching poses a major challenge. A recent review of published experiments revealed a wide range of experimental variables used across studies. Such a wide range of approaches enhances discovery, but without full transparency in the experimental and analytical methods used, can also make comparisons among studies challenging. To increase comparability but not stifle innovation, we propose a common framework for coral bleaching experiments that includes consideration of coral provenance, experimental conditions, and husbandry. For example, reporting the number of genets used, collection site conditions, the experimental temperature offset(s) from the maximum monthly mean (MMM) of the collection site, experimental light conditions, flow, and the feeding regime will greatly facilitate comparability across studies. Similarly, quantifying common response variables of endosymbiont (Symbiodiniaceae) and holobiont phenotypes (i.e., color, chlorophyll, endosymbiont cell density, mortality, and skeletal growth) could further facilitate cross‐study comparisons. While no single bleaching experiment can provide the data necessary to determine global coral responses of all corals to current and future ocean warming, linking studies through a common framework as outlined here, would help increase comparability among experiments, facilitate synthetic insights into the causes and underlying mechanisms of coral bleaching, and reveal unique bleaching responses among genets, species, and regions. Such a collaborative framework that fosters transparency in methods used would strengthen comparisons among studies that can help inform coral reef management and facilitate conservation strategies to mitigate coral bleaching worldwide.