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Pan-regional marine benthic cryptobiome biodiversity
patterns revealed by metabarcoding Autonomous Reef
Monitoring Structures
J.K. Pearman, G. Chust, E. Aylagas, E. Villarino, J.R. Watson, A. Chenuil,
A. Borja, A.E. Cahill, L. Carugati, R. Danovaro, et al.
To cite this version:
J.K. Pearman, G. Chust, E. Aylagas, E. Villarino, J.R. Watson, et al.. Pan-regional marine benthic
cryptobiome biodiversity patterns revealed by metabarcoding Autonomous Reef Monitoring Struc-
tures. Molecular Ecology, Wiley, 2020, 29, pp.4882-4897. �10.1111/mec.15692�. �hal-02973058�
This article has been accepted for publication and undergone full peer review but has not been
through the copyediting, typesetting, pagination and proofreading process, which may lead to
differences between this version and the Version of Record. Please cite this article as doi:
10.1111/MEC.15692
This article is protected by copyright. All rights reserved
DR. JOHN KENNETH PEARMAN (Orcid ID : 0000-0002-2237-9723)
DR. EVA AYLAGAS (Orcid ID : 0000-0001-9792-8451)
DR. NAIARA RODRIGUEZ-EZPELETA (Orcid ID : 0000-0001-6735-6755)
Article type : Original Article
Pan-regional marine benthic cryptobiome biodiversity patterns revealed by metabarcoding
Autonomous Reef Monitoring Structures
Running Title: Pan-regional ARMS biodiversity
Pearman, J.K.
1,2
, Chust, G.
3
, Aylagas, E.
1
, Villarino, E.
3,9,10
, Watson, J.R.
9
, Chenuil, A.
4
, Borja,
A.
5
, Cahill, A.E.
6
, Carugati, L.
7
, Danovaro, R.
7
, David, R.
4
, Irigoien, X.
3,5
, Mendibil, I.
3
,
Moncheva, S.
8
, Rodríguez-Ezpeleta, N.
3
, Uyarra, M.C.
5
, Carvalho, S.
1
1 King Abdullah University of Science and Technology (KAUST), Red Sea Research Center,
Thuwal, 23955-6900 Saudi Arabia
2 Coastal and Freshwater Group, Cawthron Institute, Private Bag 2, Nelson 7042, New Zealand
3 AZTI, Basque Research and Technology Alliance (BRTA) - Marine Research, Herrera Kaia,
Portualdea z/g – 20110 Pasaia (Gipuzkoa), Spain
4 Institut Méditerranéen de Biodiversité et d’Ecologie marine et continentale (IMBE), Aix
Marseille Univ, Avignon Université, CNRS, IRD, IMBE, Marseille,
France
5 IKERBASQUE, Basque Foundation for Science, Bilbao, Spain
6 Biology Department, Albion College, Albion, Michigan, USA
7 Dipartimento di Scienze della Vita e dell’Ambiente, Università Politecnica delle Marche,
Ancona, Italy
Accepted Article
This article is protected by copyright. All rights reserved
8 Institute of Oceanology, (IO-BAS), First May Street 40, P.O.Box 152, Varna 9000,
Bulgaria
9 College of Earth, Ocean and Atmospheric Sciences, Oregon State University, Corvallis, OR,
USA, 97330
10 Scripps Institution of Oceanography & Section of Ecology, Behavior and Evolution
University of California San Diego, 9500 Gilman Drive #0218 | La Jolla, CA 92093
Corresponding Author: Susana Carvalho, King Abdullah University of Science and
Technology, Red Sea Research Center, Thuwal 23955-6900, Kingdom of Saudi Arabia
Telephone +966-(12) 8082908
Email: susana.carvalho@kaust.edu.sa
Keywords: biodiversity; ecosystem connectivity; climate change; metapopulation; dispersal
limitation; ecological niche; ecological monitoring; mitochondrial cytochrome oxidase I (COI)
Abstract:
Autonomous Reef Monitoring Structures (ARMS) have been applied worldwide to characterize
the critical yet frequently overlooked biodiversity patterns of marine benthic organisms. In order
to disentangle the relevance of environmental factors in benthic patterns, here, through
standardized metabarcoding protocols, we analyze sessile and mobile (<2 mm) organisms
collected using ARMS deployed across six regions with different environmental conditions (3
sites x 3 replicates per region): Baltic, Western Mediterranean, Adriatic, Black and Red Seas, and
the Bay of Biscay. A total of 27473 Amplicon Sequence Variants (ASVs) were observed ranging
from 1404 in the Black Sea to 9958 in the Red Sea. No ASVs were shared amongst all regions.
The highest number of shared ASVs was between the Western Mediterranean and the Adriatic Sea
(116) and Bay of Biscay (115). Relatively high numbers of ASVs (103), mostly associated with
the genus Amphibalanus, were also shared between the lower salinity seas (Baltic and Black
Seas). We found that compositional differences in spatial patterns of rocky-shore benthos are
Accepted Article
This article is protected by copyright. All rights reserved
determined slightly more by dispersal limitation than environmental filtering. Dispersal limitation
was similar between sessile and mobile groups, while the sessile group had a larger environmental
niche breadth than the mobile group. Further, our study can provide a foundation for future
evaluations of biodiversity patterns in the cryptobiome, which can contribute up to 70% of the
local biodiversity.
Introduction
Oceanic and coastal areas are essential sources of goods and services for human well-being
(Barbier, Hacker, Koch, Stier, & Silliman, 2011; Costanza et al., 1997), but are also affected by
human pressures (Halpern et al., 2008; Korpinen & Andersen, 2016; Lotze, Guest, O’Leary, Tuda,
& Wallace, 2018). These pressures highlight the need for scientifically informed conservation and
management efforts (Costello & Wilson, 2011). Understanding what shapes biodiversity is vital so
that changes in the status of biological communities can be anticipated and managed (Andersen,
Halpern, Korpinen, Murray, & Reker, 2015; Costello & Wilson, 2011; Elliott, 2014; Micheli et al.,
2013), for example through the protection of species on the brink of extinction (Costello &
Wilson, 2011). Contrary to terrestrial domains, biogeographic barriers are relatively limited in the
oceans making marine ecosystems particularly vulnerable to the effects of local disasters, for
example oil spills and fisheries overharvesting, expanding over large distances (Cordes et al.,
2016; Sammarco et al., 2013). Thus, the development of data-driven and standardized
environmental monitoring tools, to maintain natural levels of biodiversity within nearshore
ecosystems, is of paramount importance (Danovaro et al., 2016).
Traditional monitoring techniques in hard-bottom marine environments have mainly been based
on visual census and morphological identification of the most conspicuous organisms present (e.g.
macroalgae, corals, sponges, fish) along transects (that vary in length, width and also on the
method - e.g. photo-transects versus line intercept method) (Danovaro et al., 2016). However, a
high proportion of the benthic biodiversity in these systems comprises small sessile, encrusting or
mobile organisms (Enochs, Toth, Brandtneris, Afflerbach, & Manzello, 2011). These organisms
are considered to be part of the cryptobiome (Carvalho et al., 2019) as they inhabit cavities
Accepted Article
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(cryptic habitats) within the rocky architecture for temporary shelter (e.g. nocturnal species) or as
a source of food, and are often neglected during traditional surveys (Pearman, Anlauf, Irigoien, &
Carvalho, 2016; Reaka-Kudla, 1997). The cryptobiome encompasses a diverse selection of
ecologically important groups such as suspension feeders (Richter, Wunsch, Rasheed, Kötter, &
Badran, 2001; Scheffers, de Goeij, van Duyl, & Bak, 2003), predators (Reaka, 1987), herbivores
(Coen, 1988) and detritivores (Rothans & Miller, 1991). Because of their diverse ecological roles,
small size and fast generation times (Finlay, 2002), the responses of the cryptobiome to
environmental stressors may differ from those of the larger macro-organisms usually studied.
Despite their importance in benthic ecosystems, the cryptic nature of being small and difficult to
spot, as well as the diversity of the phyla represented, requires specialized taxonomists for
identification, creating a bottleneck which can limit both the temporal and spatial scales at which
studies can be undertaken.
Recognizing the urgency for standardized methods to comprehensively assess hard bottom benthic
biodiversity across different habitats and regions, the Coral Reef Ecosystem Division (CRED) of
the United States National Oceanic and Atmospheric Administration (NOAA) developed the
Autonomous Reef Monitoring Structures (ARMS;
https://www.pifsc.noaa.gov/cred/survey_methods/arms/overview.php). The alternating open and
obstructed format in the gaps between plates comprising the ARMS was designed to mimic the
structural complexity of hard-bottom substrata allowing the colonization of a variety of organisms
with different niche preferences (Zimmerman & Martin, 2004). ARMS-associated communities
can be analyzed either morphologically (David et al., 2019) or through DNA metabarcoding (e.g.
targeting a short DNA fragment of the mitochondrial cytochrome oxidase I (COI) gene) to identify
the whole spectrum of their biodiversity and community composition of sessile and mobile
organisms (Leray & Knowlton, 2015). In addition, with the deployment of ARMS across large
spatial scales and the use of standardized sampling protocols, large scale biodiversity patterns can
be obtained. So far this has been undertaken using molecular approaches along the length of the
Red Sea (Carvalho et al., 2019; Pearman et al., 2019) with morphological assessments of benthic
substrates being undertaken in European waters and the Red Sea (David et al., 2019). ARMS have
been deployed globally (https://www.oceanarms.org/deployments/search, accessed 07/07/2020)
opening the possibility for global studies. Comparisons between ARMS and coral dead head
communities show the same average similarity as comparisons between dead head communities
Accepted Article