Editorial: Advances in 3D Habitat Mapping of Marine Ecosystem Ecology and Conservation

Full text

EDITORIAL
published: 21 January 2022
doi: 10.3389/fmars.2021.827430
Frontiers in Marine Science | www.frontiersin.org 1January 2022 | Volume 8 | Article 827430
Edited by:
Wei-Bo Chen,
National Science and Technology
Center for Disaster Reduction
(NCDR), Taiwan
Reviewed by:
Lida Teneva,
Independent Researcher,
Sacramento, United States
*Correspondence:
Renata Ferrari
R.FerrariLegorreta@aims.gov.au
Specialty section:
This article was submitted to
Ocean Solutions,
a section of the journal
Frontiers in Marine Science
Received: 02 December 2021
Accepted: 21 December 2021
Published: 21 January 2022
Citation:
Ferrari R, Leon JX, Davies AJ,
Burns JHR, Sandin SA, Figueira WF
and Gonzalez-Rivero M (2022)
Editorial: Advances in 3D Habitat
Mapping of Marine Ecosystem
Ecology and Conservation.
Front. Mar. Sci. 8:827430.
doi: 10.3389/fmars.2021.827430
Editorial: Advances in 3D Habitat
Mapping of Marine Ecosystem
Ecology and Conservation
Renata Ferrari 1
*, Javier X. Leon 2, Andrew J. Davies 3, John H. R. Burns 4,
Stuart A. Sandin 5, Will F. Figueira 6and Manuel Gonzalez-Rivero 1
1Australian Institute of Marine Science, Townsville, QLD, Australia, 2School of Science, Technology and Engineering,
University of the Sunshine Coast, Maroochydore, QLD, Australia, 3University of Rhode Island, Kingston, RI, United States,
4MEGA Lab, University of Hawaii at Hilo, Hilo, HI, United States, 5Scripps Institution of Oceanography, University of
California, San Diego, San Diego, CA, United States, 6Faculty of Science, School of Life and Environmental Sciences, The
University of Sydney, Sydney, NSW, Australia
Keywords: 3D structural complexity, photogrammetry, rugosity, standardization, error reporting, cross-platform,
marine ecology, structure-from-motion
Editorial on the Research Topic
Advances in 3D Habitat Mapping of Marine Ecosystem Ecology and Conservation
Advances in 3D technology have enabled low-cost and accurate measurements of habitat structure
and organism size in both terrestrial and marine environments. However, there is still a need for
guidance on how to apply novel 3D technologies for marine ecology and conservation. Multiple
teams from around the world are leading the application of 3D photogrammetry in marine
ecosystems. The widespread adoption of 3D methodologies produces a growing need for agreed
standards to assess the quality of 3D data (e.g., error metrics). Similarly, standardized techniques
where possible, will ensure collaboration and compatibility of 3D data across space and time.
This Research Topic is a first step toward the standardization of methods and communication of
the state of the field to the wider audience in marine science and conservation using or considering
the use of 3D technologies. The Topic provides relevant information that: (1) defines standard
methods for the application of 3D technologies to marine ecosystem ecology and conservation,
(2) advances fundamental marine ecological and conservation knowledge relevant to the habitat
structure of marine ecosystems; and (3) highlights knowledge gaps and directions to move toward
a high-resolution 3D map of the world’s oceans.
The Research Topic focuses on the use of high-resolution 3D reconstructions of underwater
ecosystems. It includes 13 articles, of which six are original research articles, one is a perspective,
and six are methodological advances. Most of the original research articles also included a
methodological validation or comparison. The geographic scope of this Research Topic ranges from
the Caribbean to Greenland to the Pacific Islands and Australasia. Nine articles were conducted
in coral reefs, three in temperate rocky reefs, and one on a deep-sea cliff, which highlights the
versatility of 3D technologies. The diverse group of articles explored the relationship between
habitat features, benthic and fish abundance, health, diversity, the potential of reef scape genomics,
and the effectiveness of marine protection. A range of equipment from action cameras and DSLRs,
to machine vision cameras, underwater robots, and echo-sounders were used to generate 3D

Ferrari et al. Editorial: Advances in 3D Habitat Mapping
reconstructions, emphasizing how a broad range of 3D
technologies can benefit a wide variety of end users and
applications. Similarly, the breath of the research published
in this Research Topic captured 3D reconstructions of sub-
millimeter resolutions, as well as 3D maps across large
spatial extents.
KEY FINDINGS IN ORIGINAL RESEARCH
ARTICLES
Advancing Fundamental Marine Ecological
and Conservation Knowledge
Across large spatial extents, 3D technologies were used to
characterize structural complexity and investigate its drivers and
representation within marine parks. Asner et al. mapped reef
rugosity (2 and 6 m resolution) to 22 m depth throughout the
eight main Hawaiian Islands, and found rugosity was mainly
driven by water depth and reef slope. Mayorga-Martínez et
al. mapped slope, aspect, curvature, rugosity, and ruggedness
(2.5 m resolution) for three submerged banks and two emerging
reefs in the Southwestern Gulf of Mexico and found structural
complexity increased with depth and was underrepresented
within marine parks.
Three-dimensional technologies were used to investigate the
relationship of surface rugosity and more traditional metrics of
ecosystem health and state at the scale surveys are routinely
conducted (hundreds of squared meters). Urbina-Berreto et al.
explored the relationship between structural complexity and
coral cover on reef slopes and lava-flows and found sites
with the highest coral cover also had the highest structural
complexity. Monfort et al. investigated the relationship between
fish assemblages and surface rugosity in Mediterranean shallow
rocky reefs and found total fish abundance and species richness
FIGURE 1 | Example of two datasets collected with different platforms over the same area of a coral reef. The larger dataset was collected using action cameras and
has a ground sampling distance of approximately 1 cm, the smaller excerpts were collected with a digital single-lens reflex camera and has a ground sampling
distance of approximately 1 mm.
increased with surface rugosity. Kanki et al. investigated
the relationships between the prevalence of four benthic
sessile organisms (ascidian, barnacle, polychaete, and articulated
coralline algae) and terrain variables derived from 3D maps of the
seafloor (cm resolution, 4 m2extent). Filter-feeders were more
abundant on vertical and/or high faces above the seafloor, likely
due to higher current velocities. In contrast, algae occurred at
various heights and on gentle slopes suitable for photosynthesis.
At colony scales, Richaume et al. investigated the effect of
longevity of no-take zones on populations of red coral (Corallium
rubrum) in France, by using photogrammetry to measure
morphometrics. They found after 5-years under protection red
coral colonies were taller and had more branches inside no-
take zones, the difference persisted after 40 years. Million et
al. explored relationships between linear extension and growth
metrics in the staghorn coral (Acropora cervicornis) using
photogrammetry. They found growth in higher order metrics was
not a linear function of growth in branch length and concluded
the use of early growth to predict future performance of corals
is limited.
Methodological Enhancements Over
Traditional Metrics
Several studies independently compared traditional methods
with photogrammetry, unanimously concluding that
metrics derived using 3D technologies are comparable
to traditional metrics. Specifically, several studies agreed
that photogrammetric methods can provide data with
higher precision, lower error, extraction of additional
and useful metrics, and improved representativeness.
Limitations of 3D technologies included its effectiveness
for species-level taxonomic identification, a requirement
for initial investment and a steep learning curve. However,
Frontiers in Marine Science | www.frontiersin.org 2January 2022 | Volume 8 | Article 827430

Ferrari et al. Editorial: Advances in 3D Habitat Mapping
photogrammetric methods were also regarded as more efficient
once established.
Million et al. developed a photogrammetry processing
pipeline for fragments of staghorn coral. 3D models were built
with Agisoft Metashape, which was automated to run on a high-
performance computing system to serially process models. They
showed photogrammetry is an information rich method for
quantifying colony-level morphometrics and is compatible with
field measurements. Couch et al. compared data from in-water
surveys to photogrammetry-derived metrics for assessing coral
demography, bleaching, and diversity. They concluded most
metrics did not vary significantly between methods regardless
of the habitat type or depth, and that photogrammetry offers
a unique opportunity to quantify and mitigate inter-observer
error rigorously. Urbina-Berreto et al. compared field and digital
estimates of coral cover using the Line Intercept Transect
(LIT) method and found in situ estimates were higher than
digitized estimates. They also performed surface analyses on
the orthomosaics to quantify coral cover and found these
yielded the most precise estimates. They concluded surface
analysis was the most efficient method and outperformed other
methods in terms of data outputs and representativeness of the
ecosystem. Conley and Hollander found no significant difference
in surface area measurements derived using traditional methods
(wax dipping, geometrical calculation, and buoyant weight) and
photogrammetry. They used this to characterize the relationship
between buoyant weight and surface area over time for the coral
species Stylophora pistillata.
Several studies published in this Research Topic presented 3D
approaches to derive novel metrics, maximize limited bottom-
time, and explore difficult-to-access environments. Kanki et
al. proposed a new photogrammetric method to 3D map the
seafloor (cm resolution, 4 m2extent) and quantify terrain
variables and the prevalence of sessile organisms. Macedo
Cruz de Oliveira et al. compared methods for classification
of marine organisms from photogrammetric reconstructions of
cold-water coral habitats, and found 3D support vector machine
outperformed other methods, but each method explored has
advantages for specific applications. Van Audenhaege et al.
demonstrated a novel approach for mapping and classifying
vertical habitats (e.g., cliffs, drop-offs) that are difficult to access
and challenging to study. Hatcher et al. developed and tested
a new mapping platform (SQUID-5), capable of 2.5D mapping
complex coral reef habitats (between 3 and 9 m of depth) and is
capable of measuring changes in the morphology and location
of seafloor features over time (∼3 cm resolution) without pre-
existing ground controls. Finally, Bongaerts et al. discussed the
potential of “reef-scape genomics” that uses recent advances in
underwater 3D technology to enable spatially explicit molecular
ecology studies on coral reefs.
Challenges as We Move Toward a 3D Map
of the World’s Oceans
Future applications of 3D mapping, based on photogrammetry
or other technologies, should meet standard requirements that
allow comparisons across environments, sensors, and processing
approaches and ensure a robust assessment of the product’s
quality and uncertainties. Following the recommendations by
James et al., we suggest that: (1) the selection of sensors
and methods is clearly described and justified as fit for
purpose, (2) error reporting includes both the performance
of the model fitting and, importantly, the quality of the 3D
product is assessed using independent measurements, and
(3) uncertainties (e.g., in bias or precision) are explicitly
acknowledged and managed, especially when performing change
detection analyses.
Despite the important contribution of this Research Topic
toward a future 3D map of the world’s oceans, several important
questions remain unanswered. Especially in regard to good
practices when scaling across datasets of different spatial
resolutions (e.g., grain size) and extents (e.g., window
size), defining the key parameters to compare datasets
from different sources (e.g., echosounder vs. cameras),
and the potential and limitations of machine learning
for automatic segmentation and classification of 3D data
(Figure 1).
AUTHOR CONTRIBUTIONS
RF conceived the Research Topic, invited guest editors,
read all articles, summarized, analyzed the research findings
across the Research Topic, and wrote this editorial. All other
authors reviewed manuscript and contributed equally to editing
and reviewing several articles submitted for publication in
Research Topic.
ACKNOWLEDGMENTS
We appreciate the help of Tiny Remmers Barry to source the
panels for the figure used in this editorial and to the authors
of all articles published in this Research Topic. RF and MG-R
were funded through the Reef Restoration and Adaptation
Program and other internal projects within the Australian
Institute of Marine Science. AD was supported by the USDA
National Institute of Food and Agriculture, Hatch Formula
project accession no. 1017848.
Conflict of Interest: The authors declare that the research was conducted in the
absence of any commercial or financial relationships that could be construed as a
potential conflict of interest.
Publisher’s Note: All claims expressed in this article are solely those of the authors
and do not necessarily represent those of their affiliated organizations, or those of
the publisher, the editors and the reviewers. Any product that may be evaluated in
this article, or claim that may be made by its manufacturer, is not guaranteed or
endorsed by the publisher.
Copyright © 2022 Ferrari, Leon, Davies, Burns, Sandin, Figueira and Gonzalez-
Rivero. This is an open-access article distributed under the terms of the Creative
Commons Attribution License (CC BY). The use, distribution or reproduction in
other forums is permitted, provided the original author(s) and the copyright owner(s)
are credited and that the original publication in this journal is cited, in accordance
with accepted academic practice. No use, distribution or reproduction is permitted
which does not comply with these terms.
Frontiers in Marine Science | www.frontiersin.org 3January 2022 | Volume 8 | Article 827430