A Comparison of the Diagnostic Accuracy of in-situ and Digital Image-Based Assessments of Coral Health and Disease

Burns, John H. R.; Weyenberg, Grady; Mandel, Travis; Ferreira, Sofia B.; Drew, G. M.; Kinoshita, Chad K.; Marshall, Micah; Moral, Nicholas A. V. Del; Murphy, Shane; Pascoe, Kailey H.; Runyan, Alexandra; Spengler, Alexander; Wells, B.; Wilde, Danielle K.; Pelayo, Roberto

doi:10.3389/fmars.2020.00304

Cited by 15 publications

(19 citation statements)

References 34 publications

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“…However, we expect the effects of overexposure to be minimal because cameras were white balanced at depth, imagery was rigorous quality controlled, and all SfM annotators used the same monitors and settings. Our results differ slightly from previous studies that found bleaching estimates did not differ between in-water and photoquad (Page et al, 2016) or SfM surveys (Burns et al, 2020). Previous studies were conducted on a very limited number of shallow homogenous sites; therefore, it is unsurprising that our results differ given that we surveyed 104 sites distributed across a large range of depths, turbidity, lighting, and habitats.…”

Section: Most Metrics Show Low Methodological Biascontrasting

confidence: 99%

“…Both in-water and SfM survey methods have a variety of strengths and weaknesses for coral demographic and community surveys (Table 1), and which method to choose depends on the research question, the timeline for data dissemination, and logistical constraints of the survey. Similar to Burns et al (2020), our study highlights that there may not be a "gold standard" for colony-level surveys, and observed methodological differences can highlight deficiencies in either method. In-water surveys allow divers to look at corals at the polyp-level from all possible angles, which is important for observing taxa located in crevices, under overhangs, or covered by sand or algae.…”

Section: Strengths and Weaknesses Of Sfm And In-water Surveyssupporting

confidence: 56%

“…To date, a majority of studies on coral reefs utilizing SfM methodology have focused on quantifying structural complexity (Burns et al, 2015a;Figueira et al, 2015;Storlazzi et al, 2016;Bryson et al, 2017;Fukunaga et al, 2020;Torres-Pulliza et al, 2020). Others have used SfM in smallscale studies to quantify disease and bleaching (Fox et al, 2019;Voss et al, 2019;Burns et al, 2020), spatial clustering of corals (Edwards et al, 2017;Pedersen et al, 2019), coral growth (Kodera et al, 2020;Lange and Perry, 2020), and size frequency distributions (Hernández-Landa et al, 2020). SfM can generate high resolution mosaics that facilitate colony-level assessments, but SfM may limit our ability to capture every surface and colony-angle that can be achieved with in-water assessments and significant post processing may impede timely data generation.…”

Section: Introductionmentioning

confidence: 99%

“…Thus a comprehensive methodological comparison is needed to assess data comparability and methodological trade-offs. While Burns et al (2020) conducted a small scale study comparing in-water assessments of coral health to data generated from SfM, no study has tested whether the standard suite of coral metrics (e.g., density, colony size, diversity, partial mortality, prevalence of altered health states, and diversity) extracted from SfM imagery are consistent with in-water observations across gradients of community structure, depth and reef complexity.…”

Section: Introductionmentioning

confidence: 99%

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Comparing Coral Colony Surveys From In-Water Observations and Structure-From-Motion Imagery Shows Low Methodological Bias

et al. 2021

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As the threats to coral reefs mount, scientists and managers are looking for innovative ways to increase the scope, scale, and efficiency of coral reef monitoring. Monitoring changes in coral communities and demographic features provides key information about ecosystem function and resilience of reefs. While most monitoring programs continue to rely on in-water visual survey methods, scientists are exploring 3D imaging technologies such as photogrammetry, also known as Structure-from-Motion (SfM), to enhance precision of monitoring, increase logistical efficiency in the field, and generate a permanent record of the reef. Here, we quantitatively compare data generated from in-water surveys to SfM-derived metrics for assessing coral demography, bleaching, and diversity in the main Hawaiian Islands as part of NOAA’s National Coral Reef Monitoring Program. Our objectives were to compare between-method error to within-method error, test for bias between methods, and identify strengths and weaknesses of both methods. Colony density, average colony diameter, average partial mortality, prevalence of bleaching, species richness, and species diversity were recorded using both methods within the same survey areas. For all metrics, the magnitude of between-method error was comparable to the within-method error for the in-water method and between method error was significantly higher than within-method error for SfM for one of the seven metrics. Our results also reveal that a majority of the metrics do not vary significantly between methods, nor did we observe a significant interaction between method and habitat type or method and depth. Exceptions include estimates of partial mortality, bleaching prevalence, and Porites juvenile density–though differences between methods are generally small. Our study also highlights that SfM offers a unique opportunity to more rigorously quantify and mitigate inter-observer error by providing observers unlimited “bottom time” and the opportunity to work together to resolve difficult annotations. However, the necessary investment in equipment and expertise does present substantial up-front costs, and the time associated with curating imagery, photogrammetric modeling, and manual image annotation can reduce the timeliness of data reporting. SfM provides a powerful tool to reimagine how we study and manage coral reefs, and this study provides the first quantified methodological comparison to validate the transition from standard in-water methods to SfM survey methods for estimates of coral colony-level surveys.

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Section: Most Metrics Show Low Methodological Biascontrasting

confidence: 99%

Section: Strengths and Weaknesses Of Sfm And In-water Surveyssupporting

confidence: 56%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Comparing Coral Colony Surveys From In-Water Observations and Structure-From-Motion Imagery Shows Low Methodological Bias

et al. 2021

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“…Within the sphere of marine ecological research, this technology is being applied to analyse reef benthic community composition and habitat condition (Bayley, Mogg, Purvis, & Koldewey, 2019; Burns et al., 2020; Carlot et al., 2020; Edwards et al., 2017; Fukunaga, Burns, Craig, & Kosaki, 2019; Fukunaga, Burns, Pascoe, & Kosaki, 2020), to inform associated community dynamics, and species behavioural interactions (Bayley & Rose, 2020; González‐Rivero et al., 2017; Palma et al., 2019; Tebbett, Streit, & Bellwood, 2020), and to assess changes in morphological complexity or growth through time (Bayley, 2019; Ferrari, Bryson, et al, 2016; Ferrari et al., 2017; Lange & Perry, 2020; Lavy et al., 2015; Magel, Burns, Gates, & Baum, 2019; Rossi, Castagnetti, Capra, Brooks, & Mancini, 2020). The technique is also being usefully applied to inform analysis of other marine and coastal systems, using drones and remotely operated vehicles (Casella et al., 2017; Castellanos‐Galindo, Casella, Mejía‐Rentería, & Rovere, 2019; Chirayath & Instrella, 2019; Palma et al., 2018; Price et al., 2019; Teague & Scott, 2017; Varela et al., 2019), making this a rapidly evolving and adaptable tool.…”

Section: Ecological Applicationsmentioning

confidence: 99%

A protocol for the large‐scale analysis of reefs using Structure from Motion photogrammetry

Bayley

Mogg

2020

Methods Ecol Evol

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Remote sensing of Antarctic polychaete reefs (Serpula narconensis): reproducible workflows for quantifying benthic structural complexity with action cameras, remotely operated vehicles and structure‐from‐motion photogrammetry

Montes-Herrera

Hill

Cummings

et al. 2023

Remote Sens Ecol Conserv

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Quantifying the structural complexity provided by biogenic habitat structures is important in ecology, conservation and management, and yet remains a challenging task, particularly in deep sea and polar environments, that current photogrammetry tools can alleviate. In this study, we demonstrate how small remotely operated vehicles and compact underwater GoPro® action cameras can be easily integrated into coastal Antarctic surveys to quantify structural complexity of under‐ice benthos via underwater photogrammetry. Forty‐four pairs of 1 m2 quadrats at 1 cm resolution, each comprising an orthomosaic and three‐dimensional reconstructions, were analyzed to describe relationships between benthic cover and structural complexity metrics. The study case provided insights into a unique biogenic habitat, highlighting the role of integrating structural complexity metrics in Antarctic benthic surveys. Although no clear relationships between structural complexity and biodiversity were found, high cover of live reef‐building polychaetes was associated with higher levels of structural complexity, particularly fractal dimension (D). Further, broken biogenic structures, product of disturbance events retain habitat structural complexity known to be associated with larvae settlement and biogenic reef growth. This suggests that D can be used as a metric for detecting subtle changes in biogenic structural complexity. We build from available open‐source code, a reproducible scientific workflow that is expected to facilitate the acquisition and analysis of structural complexity metrics. The workflow presented aims to encourage and accelerate the use of photogrammetry tools for benthic studies aiming to quantify biogenic structural complexity across depths and latitudes.

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A Comparison of the Diagnostic Accuracy of in-situ and Digital Image-Based Assessments of Coral Health and Disease

Cited by 15 publications

References 34 publications

Comparing Coral Colony Surveys From In-Water Observations and Structure-From-Motion Imagery Shows Low Methodological Bias

Comparing Coral Colony Surveys From In-Water Observations and Structure-From-Motion Imagery Shows Low Methodological Bias

A protocol for the large‐scale analysis of reefs using Structure from Motion photogrammetry

Remote sensing of Antarctic polychaete reefs (Serpula narconensis): reproducible workflows for quantifying benthic structural complexity with action cameras, remotely operated vehicles and structure‐from‐motion photogrammetry

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