Science of the Total Environment 725 (2020) 138501

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Science of the Total Environment
journal homepage: www.elsevier.com/locate/scitotenv

Changes in ﬁsh communities due to benthic habitat shifts under ocean
acidiﬁcation conditions
Carlo Cattano a,b,⁎, Sylvain Agostini c, Ben P. Harvey c, Shigeki Wada c, Federico Quattrocchi d, Gabriele Turco a,b,
Kazuo Inaba c, Jason M. Hall-Spencer c,e, Marco Milazzo a,ba

Department of Earth and Marine Sciences (DiSTeM), University of Palermo, via Archiraﬁ 20-22, 90123 Palermo, Italy
CoNISMa (Interuniversity Consortium of Marine Sciences), Piazzale Flaminio 9, 00196 Rome, Italy
Shimoda Marine Research Center, University of Tsukuba, 5-10-1 Shimoda, 415-0025 Shizuoka, Japand
IRBIM - Istituto per le Risorse Biologiche e le Biotecnologie Marine, CNR - National Research Council, Via Luigi Vaccara 61, 91026 Mazara del Vallo, TP, ItalyeMarine Biology and Ecology Research Centre, University of Plymouth, Plymouth, PL4 8AA, UKbc

H I G H L I G H T S

G R A P H I C A L

A B S T R A C T• Ocean acidiﬁcation-mediated habitat
shifts and decreased complexity affectassociated ﬁsh communities.
• Altered ﬁsh traits and reduced diversity
occurred under near-future ocean acidiﬁcation levels.
• Ocean acidiﬁcation may oppose thepoleward-shift of tropical ﬁsh species
under warming.

a r t i c l e

i n f oArticle history:
Received 22 January 2020
Received in revised form 27 March 2020
Accepted 4 April 2020
Available online 5 April 2020
Editor: Henner Hollert
Keywords:
Carbon dioxide
Biogenic habitat complexity
Scleractinian coral coverReef-associated ﬁsha b s t r a c t
Ocean acidiﬁcation will likely change the structure and function of coastal marine ecosystems over coming decades. Volcanic carbon dioxide seeps generate dissolved CO2 and pH gradients that provide realistic insights
into the direction and magnitude of these changes. Here, we used ﬁsh and benthic community surveys to assess
the spatio-temporal dynamics of ﬁsh community properties off CO2 seeps in Japan. Adding to previous evidence
from ocean acidiﬁcation ecosystem studies conducted elsewhere, our ﬁndings documented shifts from calciﬁed
to non-calciﬁed habitats with reduced benthic complexity. In addition, we found that such habitat transition led
to decreased diversity of associated ﬁsh and to selection of those ﬁsh species better adapted to simpliﬁed ecosystems dominated by algae. Our data suggest that near-future projected ocean acidiﬁcation levels will oppose theongoing range expansion of coral reef-associated ﬁsh due to global warming.
© 2020 Elsevier B.V. All rights reserved.

⁎ Corresponding author at: Department of Earth and Marine Sciences (DiSTeM), University of Palermo, via Archiraﬁ 20-22, 90123 Palermo, Italy.
E-mail address: cattancarlo@gmail.com (C. Cattano).

https://doi.org/10.1016/j.scitotenv.2020.138501
0048-9697/© 2020 Elsevier B.V. All rights reserved.

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C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

Editor: Henner Hollert
1. Introduction
Shifts in marine biogenic habitats in response to anthropogenic activities and a range of stressors have been documented since the1960s (Hughes, 1994). In tropical coral reef ecosystems examples include studies of the impacts of overﬁshing (Jackson et al., 2001), outbreaks of coral-eating predators (De'ath et al., 2012), diseases(Hughes, 1994), pollution (McCulloch et al., 2003), hurricanes(Hughes, 1994), and extreme temperatures (Hoegh-Guldberg, 1999).
Ocean warming is changing coastal marine communities, for example
due to (1) warm-water species (e.g. corals and tropical ﬁsh) moving
poleward following their thermal physiological niche, (2) changes inthe strength of interspeciﬁc interactions (e.g. increase of herbivory
from warm-water ﬁsh leading to the loss of kelp forests at their low latitude limits), and (3) a decrease in biogenic habitat complexity (e.g.
Vergés et al., 2014, 2016; Hall-Spencer and Harvey, 2019).
Ocean Acidiﬁcation (OA), the alteration of seawater carbonate
chemistry due to rising atmospheric CO2 concentrations, adds an extra
set of stressors to those caused by warming. Meta-analyses show that
decreased seawater pH due to OA may impair calciﬁcation and accelerate dissolution for many calcifying habitat-formers, while rising pCO2
levels may enhance the primary production and carbon ﬁxation rates
of non-calcifying autotrophs (Falkenberg et al., 2013; Harvey et al.,2013; Kroeker et al., 2013; Wittmann and Pörtner, 2013). As a result,
there will be losers and winners under OA conditions, with effects on
ecosystems documented along gradients in seawater pH at CO2 seeps
around the world (e.g., Hall-Spencer et al., 2008; Fabricius et al., 2011)
including reductions in habitat complexity, shifts in competitive interactions and changes in species dominance.
While CO2 seeps are not perfect analogues for ocean acidiﬁcation(e.g., Fabricius et al., 2017), they nevertheless comprise one of thevery few ﬁeld-based tools available to assess OA effects on ecosystems
and communities (Hall-Spencer and Harvey, 2019). To date, our knowledge about the ecosystem effects of OA is advancing rapidly with increasing evidence from temperate (Hall-Spencer et al., 2008;
Nagelkerken et al., 2015; Milazzo et al., 2019), subtropical (Agostini
et al., 2018) and tropical (Fabricius et al., 2011, 2014; Inoue et al.,2013; Enochs et al., 2015) CO2 seeps. The responses of biogenic habitats
to OA differ regionally. Shifts from diverse to depauperate scleractinian
species assemblages and from hard to soft coral communities have been
observed in Papua New Guinea (Fabricius et al., 2011), Palau (Barkley
et al., 2015) and in Southern Japan (Inoue et al., 2013). As carbon dioxide levels increase, there is a shift in community dominance from corals
to seaweeds in the Northern Mariana Islands (Enochs et al., 2015) and at
a subtropical-temperate transition zone in Japan (Agostini et al., 2018).
How such OA-induced habitat shifts affect ﬁsh requires further study as
most work at CO2 seeps to date at has focused on bacteria, algae and invertebrates (Hall-Spencer et al., 2008; Fabricius et al., 2014; Sunday
et al., 2017; Milazzo et al., 2019).
Very few attempts have been made to estimate the effects of OAinduced habitat simpliﬁcation on ﬁsh communities (Munday et al.,2014; Nagelkerken et al., 2015, 2017). A study at three CO2 seeps in
Papua New Guinea reported reduced coral reef complexity at elevated
CO2 respect to control sites. However, there was no difference in ﬁsh
species richness between seep and control sites, and no difference inﬁsh community structure at two out of the three seep-control groups
examined (Munday et al., 2014). The only slight differences detected
in ﬁsh community structure were mostly driven by small-bodied ﬁsh
species showing strong habitat preferences (Munday et al., 2014). In another paper, Nagelkerken et al. (2015) documented shifts from kelp/
macroalgae and seagrass to low-relief turf-algae at temperate CO2
seeps that seemed to cause a loss of ﬁsh predators and predatory releaseof prey ﬁsh species, even though their antipredator responses werecompromised.

At present, how ocean warming and acidiﬁcation will affect ecosystem properties and functioning is still under debate. Some modelling attempts suggest that declines in aragonite saturation state (Ωarag) will
limit the poleward expansion of tropical coral reefs that is underway
due to ongoing warming (Yara et al., 2012; van Hooidonk et al., 2014),
as will insufﬁcient light in winter for coral algal symbiont photosynthesis (Muir et al., 2015).
Here, we evaluate the temporal consistency of changes in ﬁsh communities in response to biogenic habitat shifts off CO2 seeps located in
the NW Paciﬁc (Japan), in a region that has naturally low levels of
pCO2, high carbonate saturation levels and elevated local seawater temperatures (Midorikawa et al., 2005). These conditions allow the coexistence of both canopy-forming macroalgae and scleractinian coral
communities at ambient CO2 conditions, while a transition to lowrelief algal turf habitats occurs at elevated CO2 levels (Agostini et al.,2018; Harvey et al., 2019). To assess how ﬁsh community properties
changed spatially along the pCO2 gradient, we coupled ﬁsh and benthic
community assessments (habitat complexity, canopy height, and %cover), along a CO2 gradient and at control sites off Shikine Island (Eastern Japan). The study was carried out over two time periods (June and
September) to investigate whether the effects of OA-mediated habitat
shifts on ﬁsh community composition and structure are temporally consistent, speciﬁcally when acute seasonal typhoons (usually from July to
September), may affect benthic community structure and habitat complexity. In addition, we carried out ﬁsh trait comparisons between the
different CO2 sites, to assess changes in taxonomic richness and abundance of ﬁsh subdivided by geographic distribution (Tropical, Subtropical and Temperate), trophic guilds (Carnivore, Omnivore, Herbivore
and Planktivore) and afﬁnity to coral reef habitats.
We expected that ﬁsh communities would change in compositionand structure as a result of decreasing habitat complexity along a spatial
CO2 gradient and that these changes would be consistent over time.
Since it has been suggested that OA may decrease overall habitat complexity (e.g. from complex corals and canopy-forming algae to lowproﬁle algae and turfs; Sunday et al., 2017), we expected that ﬁsh community species richness would decrease with increasing levels of CO2.
As CO2 enrichment acts both as a stressor for scleractinian corals andas a substrate for primary producers, we also expected that the numberof species of ﬁsh from tropical and subtropical origins would decrease,
while the diversity of herbivorous ﬁsh would increase in elevated CO2
conditions.
2. Materials and methods
2.1. Study sites and carbonate chemistry
Shikine is a volcanic island east of the Izu peninsula in Japan (34° 19′
9“ N, 139° 12’ 18” E) with many CO2 seeps in shallow waters. Based on
previous geochemical investigations (Agostini et al., 2015), our survey
locations were selected to avoid potentially confounding geochemicalfactors (e.g. high sulﬁdes, negative redox potential, altered total alkalinity and elevated temperature). One location (Elevated-CO2) was within
Mikawa Bay and a second location (Control) characterised by ambient
CO2 conditions was positioned in an adjacent bay with similar depths(3–12 m), and exposure to wind and currents (Fig. 1).
To document spatial variation in the carbonate chemistry, a WQC24
multi-parameter logger (DKK-TOA Corporation, Tokyo, Japan) and a
HydroC® CO2 II sensor (Contros System & Solutions GmbH, Germany)
were deployed between 9:00 am and 3:00 pm by scuba divers alongfour and ﬁve 100-m transects in the Elevated- and Control CO2 locations, respectively (Fig. 1). Every 10 m the seawater pH (NBS scale),temperature (T, °C), salinity, and depth (m) were recorded for 5 minwith the DKK-TOA, whilst the HydroC® CO2 II sensor recorded measures of pCO2 (μatm) every 5 s. The CO2 sensor detects dissolved CO2
molecules that diffuse through a thin ﬁlm composite membrane into
an internal gas circuit containing a detector chamber where the pCO2

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Fig. 1. Map of the study showing Shikine Island, the two CO2 locations (Elevated and Control) and the ﬁve CO2 sites (High, Mid, Low, Ref1 and Ref2) where the benthic and ﬁsh 25 mtransects were positioned.

is determined by means of an IR absorption spectrometer. Both loggers
were positioned at 1 m from the sea-bottom at an average depth range
of 3–12 m, and were attached to a ﬂoating buoy equipped with a GPS(eTrex30x, Garmin) to record the exact position of each measurement.
Total alkalinity (TA) was measured from seawater samples collectedunderwater at each location (N = 24 in June; N = 25 in September).
Water samples were immediately ﬁltered at 0.45 μm using disposable
cellulose acetate ﬁlters (Dismic, Advantech, Japan) and stored at room
temperature in the dark (for no more than one week) until measurement. TA was measured by titration (TiTouch i915, Metrohm) with
HCl at 0.1 mol l−1, and calculated from the Gran function between
pH 4.2 and 3.0. The titrations were cross-validated using a working

standard (SD: ± 9 μmol kg−1) and against certiﬁed reference materialpurchased from the A.G. Dickson laboratory (Batch 152). The CO2SYS
software (Pierrot et al., 2006) was used to calculate pCO2 (Table 1)
from T, pH, salinity and TA values, and to control in situ continuous measurements of pCO2 recorded by the HydroC® CO2 II sensor. The disassociation constants from Mehrbach et al. (1973), as adjusted by Dickson
and Millero (1987), HSO4 using Dickson (1990), and total borate concentrations from Uppström (1974) were used for carbonate chemistrycalculations (Table 1). The HydroC® CO2 II sensor was not employedin the September survey due to logistic constrains.
The carbonate chemistry measurements along the nine 100-m transects were used to identify ﬁve sampling CO2 sites in the rocky subtidal

Table 1
Seawater chemistry of the subtidal sampling sites off Shikine Island. Values from June and September surveys are reported as mean (±SD). Minimum (Min) and maximum (Max) pCO2
values are also reported. pCO2 calc. = pCO2 levels calculated with CO2SYS. pCO2 meas. = pCO2 levels measured with the HydroC® CO2 II logger.
a) June 2016
CO2
location

CO2
site

Salinity

T °C

pH nbsn(pH)TA(μmol kg−1)

pCO2 calc. (μatm)

pCO2 meas. (μatm)

n (pCO2
meas.)

Elevated
Elevated
ElevatedControl
Control

High
Mid
Low
Ref 1
Ref 2

34.5 (0.05)
34.6 (0.07)
34.7 (0.05)
34.7 (0.05)
34.8 (0.05)

19.9 (0.5)
19.4 (0.5)
19.5 (0.7)
18.9 (0.3)
19.5 (0.2)

7.87 (0.15)
8.09 (0.05)
8.16 (0.05)
8.21 (0.01)
8.25 (0.03)

11
17
16
28
27

2249.92253.42270.52253.12250.8971.7 (434.0) Min:591.8 Max:2062.1
497.2 (72.6) Min:373.8 Max:645.8
404.9 (54.8) Min:361.2 Max:523.2
348.2 (10.6) Min:322.0 Max:367.6
311.5 (29.3) Min:255.4 Max:356.7

952.8 (450.8) Min:567.7 Max:2360.4
552.1 (188.2) Min:368.2 Max:1552.1
402.1 (53.4) Min:358.0 Max:591.1
347.9 (13.9) Min:307.2 Max:373.8
311.8 (29.1) Min:251.9 Max:357.8

417
843
555
994
913

b) September 2016
CO2 location

CO2 site

Salinity

T °C

pH nbsn (pH)TA (μmol kg−1)

pCO2 calc. (μatm)

Elevated
Elevated
ElevatedControl
Control

High
Mid
Low
Ref 1
Ref 2

33.9 (0.1)
33.9 (0.2)
33.9 (0.0)
33.9 (0.2)
33.9 (0.2)

26.0 (0.1)
25.1 (1.0)
25.6 (0.1)
26.3 (1.4)
26.2 (1.7)

7.65 (0.09)
7.91 (0.12)
8.13 (0.01)
8.18 (0.01)
8.16 (0.01)

4
6
4
4
4

2267.82257.32269.32249.92249.51646.4 (397.3) Min:1220.9 Max:2026.5
849.7 (291.0) Min:524.4 Max:1372.0
459.3 (12.7) Min:442.7 Max:473.1
395.4 (11.9) Min:379.3 Max:407.8
420.8 (13.6) Min:409.2 Max:439.8

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C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

zone between 3 and 12 m depth in Mikawa bay and the Control bay: one‘High-CO2’ (High), one ‘Mid-CO2’ (Mid) and one ‘Low-CO2’ (Low), andtwo ‘Ambient-CO2’ (Ref 1 and Ref 2; Fig. 1; Table 1). In each CO2 site,both the benthic habitats and the ﬁsh communities were characterised
as detailed below.
2.2. Benthic habitat characterisation
Average canopy height and percentage cover (% cover) of benthic
taxa were recorded in the June and September surveys along 25 m
strip transects positioned in the ﬁve CO2 sites (High, Mid, Low, Ref1
and Ref2). Speciﬁcally, four transects were deployed in the ‘HighCO2’site (High), six transects within the ‘Mid-CO2’ (Mid) site, six transects within the ‘Low-CO2’ (Low) site, and nine transects each in thetwo ‘Ambient CO2’ sites (Ref1 and Ref2; Fig. 1). Within each 25 m benthic transect, the canopy height was measured every meter using thepoint-intercept method, and a Biotic Habitat Proﬁle (BHP) ratio was estimated as a proxy of biotic complexity. BHP, conceptually similar to thewell-established chain method, was calculated a posteriori by dividing
the contoured distance following the measured canopy proﬁle by thelinear distance (i.e. 25 m).
The % cover of benthic taxa was assessed in ten photoquadrats, positioned at ca. 5 m apart along each 25 m transect. An Olympus Stylus
Tough TG3 with a PT056 camera housing was mounted on a 1 × 1 m
frame. The % cover was estimated using the open-access software
Image-J (http://rsb.info.nih.gov/ij/; Schneider et al., 2012) by tracing
the 2-dimensional outline of each benthic morphological taxon. For
each photoquadrat the % cover of the following benthic groups was recorded: Turf algae, crustose coralline algae (CCA), Non-Canopy-forming
ﬂeshy algae (b5 cm canopy height), Canopy-forming algae (≥ 5 cm canopy height), Caulerpa chemnitzia var. peltata, Table corals, Soft Corals,
Encrusting Corals, Massive Corals (i.e. boulder corals with massive
growth forms), Anemones and Sponges.
2.3. Fish surveys
Species composition and relative abundance of ﬁsh were visually
censused within standard linear 25 × 5 m transects (Harmelin-Vivien
et al., 1985). A total of 73 and 37 transects were carried out on Juneand September 2016, respectively. Fish transects were located haphazardly within each sampling CO2 site at 4–10 m depth, and were conducted between 09.00 am and 03.00 pm by a scuba diver leaving
behind a 25 m measure tape, while counting and identifying all theﬁsh encountered 2.5 m either side of the tape (125 m2; HarmelinVivien et al., 1985). Water visibility exceeded 15 m for all counts. Eachsampling day, only two spatially separated transects (at N20 m distanceeach other) were gathered at each CO2 site to avoid temporal dependence of data (Stewart-Oaten et al., 1986).
To make trait-mediated comparisons among different CO2 conditions, the different ﬁsh species were also subdivided by geographical origin (Tropical, Subtropical and Temperate), by trophic guild (Carnivore,
Omnivore, Herbivore and Planktivore), and by their association withcoral reefs (i.e. coral reef associated and non-associated species) following Nakamura et al. (2013) and FishBase (http://www.ﬁshbase.org/).
2.4. Data analyses
Changes in benthic habitat composition among CO2 sites wereanalysed using non-metric multidimensional scaling technique(nMDS) and tested with Permutational Multivariate Analysis of Variance (PERMANOVA; Anderson and Braak, 2003) using the software
PRIMER 6 and PERMANOVA+ β3 package (Clarke and Gorley, 2006).
The analysis was performed on Bray-Curtis measures in a multivariate
context of untransformed % cover data, using 9999 permutations of
the appropriate units. Two ﬁxed factors were considered: “CO2 site”

with 5 levels (High, Mid, Low, Ref 1 and Ref 2) and “Season” with two
2 levels (June and September).
To identify the relevant variables characterising the benthic habitat
which were responsible for the variation in ﬁsh community structure
and composition, we used a Multivariate Distance Based Linear Model[DISTLM, Anderson et al., 2008]. Both the ﬁsh community and the benthic datasets were square root transformed and the step-wise model selection method based on the AIC criterion was performed to assess thebenthic variables related with Bray-Curtis resemblance matrix of theﬁsh dataset. To visualise the ﬁsh community data as a biplot, theDistance-based redundancy analysis (dbRDA; Legendre and Anderson,
1999; McArdle and Anderson, 2001) using the benthic variables identiﬁed by the DISTLM routine was used.
To investigate the potential relationship between pCO2 and habitat
complexity (as BHP index, log transformed) we used an Additive
Mixed Model (AMM) with a Gaussian distribution and the identity
link. AMM was used because it allows for the modelling of the nonlinear effects of continuous explanatory variables by incorporatingsmooth functions (Wood, 2011). Speciﬁcally, the cubic regression spline
was used as a one-dimensional non-parametric smoothing function andthe number of knots k was set to 6, to prevent the models from producing complex non-linear relationships of little biological signiﬁcance(Wood, 2006). To account for the lack of independence of the BHP
data of the same Site per Season we used Site x Season as random intercept, which is assumed to be normally distributed with mean 0 and variance σ2. Data for both sampling campaigns (June and September) werecombined into a single data set and Season was modelled as a factor. The
model was ﬁtted using maximum likelihood (ML) parameter estimation. The analysis was performed using the R (R Core Team, 2018) package ‘mgcv’ (Wood, 2011).
We also used a method derived from meta-analysis to assess the effects of the different CO2 conditions on the number (S) and abundance(N) of ﬁsh species, also considering their classiﬁcation by geographicaldistribution (Sorigin), trophic guild (Ntrophic) and coral reef association(Scoral). To this aim, we calculated the effect size (a metric that quantiﬁes
the difference between the control and experimental groups) as the response ratio, i.e. the natural logarithm of the ratio between the averaged
response variable values (S, N, Sorigin, Ntrophic, Scoral) recorded at the Elevated CO2 (High, Mid and Low CO2 sites) and Control (Ref1 and Ref2
sites) locations. These analyses were performed using the R (R Core
Team, 2018) package ‘metafor’ (Viechtbauer, 2010).
3. Results and discussion
Benthic communities changed from rocky habitats dominated byscleractinian corals and canopy-forming macroalgae to rocky reefs covered in low-proﬁle and turf algae from Control (Ref1 and Ref2) to Elevated CO2 sites (Low, Mid and High) and this observation wasconsistent in both of the considered time periods (Fig. 2; PERMANOVA:
CO2 site x Season, Pseudo-F = 7781.2; P(perm) = 0.0001). Compositionand structure of benthic communities did not differ between sites
within ambient CO2 condition both in June (i.e., Ref1 = Ref 2; Pairwise t-test, t = 1.52; P(perm) = 0.08) and September (Pair-wise ttest, t = 1.20; P(perm) = 0.28) surveys, whilst they did signiﬁcantly differ in most of the pair-wise comparisons of sites within the elevated CO2
sites (Table S1).
Table, massive and encrusting corals were common at control sites
in both sampling periods. They are able to survive at this high latitude(34° N) in the NW Paciﬁc due to the warm northward ﬂow of theKuroshio Current (Veron and Minchin, 1992). Hard corals were absent
along transects taken at elevated CO2 conditions. In contrast to someother CO2 seep systems (Suggett et al., 2012; Inoue et al., 2013), softcorals were rare and were absent in our elevated CO2 transects. Instead,dense mats of Caulerpa chemnitzia var. peltata and the diatom Biddulphia
biddulphiana covered most of the rocky substrata at the elevated CO2
sites in June. These species were not seen in our transects in September,

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Fig. 2. Non-metric multidimensional scaling (nMDS) on benthic habitats at the ﬁve CO2 sampling sites (High, Mid, Low, Ref1 and Ref2) in June (ﬁlled symbols) and September (empty
symbols). Photomosaics of benthic community shifts observed in June and September along the CO2 gradient are also reported. The ﬁgure shows a clear community shifts in bothseasons from zooxanthellate scleractinian corals and canopy-forming macroalgae at Control CO2 location (Ref1 and Ref2) to macroalgae at the Low and Mid CO2 sites and turf algae atthe High CO2 site.

often revealing a covering of crustose coralline algae or low proﬁle turf
algae on the rocks (Fig. 2). As recently suggested, this was likely due tostrong wave energy during typhoon activity that occurs in summer andearly autumn (from late July to early October each year) on Shikine Island (Harvey et al., 2019). This major seasonal habitat shift resulted inan overall loss of canopy height due to the increase in the abundanceof a few low proﬁle algal and turf species which may outcompete
large and slow-growing species under ocean acidiﬁcation conditions(Harley et al., 2012; O'Brien and Scheibling, 2018; Harvey et al., 2019).
The ability of a few opportunistic species to withstand OA effects, beneﬁt from CO2 enrichment and displace dominant habitat-forming species(such as canopy-forming algae or coral early stages), has been previously documented (e.g. Connell et al., 2018; Agostini et al., 2018) andcan be attributed to stunted successional development (Gaylord et al.,2015).
Previous CO2 seeps studies revealed both detrimental and no effects
of elevated CO2 levels on the eco-physiological and behavioral performances of ﬁsh (e.g. Munday et al., 2014; Nagelkerken et al., 2015;
Milazzo et al., 2016; Cattano et al., 2017; Di Franco et al., 2019). Here
we focus on ﬁsh responses at the community level.
Fish assemblages changed signiﬁcantly between sites along the CO2
gradient, and between elevated CO2 and reference sites. The DISTLM
procedure revealed differences in ﬁsh assemblage composition andstructure, and identiﬁed ﬁve variables that best explained such patterns: the table and massive corals, the turf, the non-canopy forming
algae and the CCA. The dbRDA ordination of the dataset constrainedby these variables showed that the difference in the ﬁsh communities
along the CO2 gradient was best explained by turf, massive and noncanopy algae, while the differences between June and September
were best explained by table corals and CCA (Fig. 3). Thus, the clear
change of ﬁsh communities from ambient to elevated CO2 conditions
was associated with a biogenic habitat shift under OA conditions.
To date, few studies have documented the effects of OA-induced
habitat changes on the structure and composition of ﬁsh communities.
Munday et al. (2014) found that ﬁsh communities differed little between CO2 seeps and nearby control reefs in Papua New Guinea, suggesting that such similarities were due to the contribution of highly
mobile ﬁsh species, which are able to move in and out of small CO2
seep areas. The few observed differences in the abundance of certainﬁsh species were related to coral community changes (from branched
to massive corals) between CO2 exposed and un-exposed reefs (seeFabricius et al., 2014) rather than by the direct effects of high CO2 on
ﬁsh. Nagelkerken et al. (2015) described habitat characteristics andﬁsh species composition at two different CO2 seeps, documenting predator reductions and habitat shifts at elevated CO2 conditions, which together led to an increase of a few territorial ﬁsh species. A more recent

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C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

Fig. 3. dbRDA ordination of ﬁsh community data from ﬁve sampling CO2 sites (High, Mid, Low, Ref1 and Ref2) constrained by ﬁve environmental variables (CCA, Massive corals, tablecorals, Turf and non canopy algae) identiﬁed by DISTLM as signiﬁcant in explaining 84,3% of ﬁtted and 22% of total variation. Vectors represent strength of variables in the model. Their
length in relation to the circle radius (radius = 1.0) and their direction indicate the strength and the sign, respectively, of the relationship between the variable and the axes. Filled
and empty symbols represent data from June and September, respectively.

Fig. 4. AMM (Additive Mixed Model) showing the relationship between pCO2 values and habitat complexity (BHP). a) Fitted values (±95% conﬁdence intervals) of pCO2 values and habitat
complexity (log-transformed BHP index) for June (black dots) and September (green dots); b) model residuals (black dots) and estimated smoothing curve (solid line with ±95%
conﬁdence interval) showing the pCO2 effects on BHP. The effect is signiﬁcant (i.e. positive or negative) when the CI (grey area) does not overlap the zero (dashed line); c) partial
effect (solid lines) of the factor Season on the BHP index (dashed lines indicate the ±95% conﬁdence interval for September). The vertical lines reported on the x-axis of panels b and c
represent the observations from the different pCO2 values and from the two seasons, respectively.

C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

study carried out off the White Island CO2 seeps in New Zealand documented loss of ﬁsh diversity and homogenisation of ﬁsh communities
under OA conditions, suggesting that elevated CO2 indirectly boosted
the abundance of a single species thus altering the competitive relationships among species and suppressing the abundance of the competitive
subordinates (Nagelkerken et al., 2017). Contrary to these previous
studies, where ﬁsh community differences between CO2 exposed andunexposed reefs were evaluated focusing on a few species with narrow
home ranges, here we compared the structure and the composition ofentire ﬁsh communities ﬁnding signiﬁcant differences among the four
CO2 conditions considered.
The effects of OA on ﬁsh communities may depend on how elevated
CO2 affects the different species directly and indirectly. By altering acidbase balance and the processing of sensory information, elevated CO2
concentrations affect physiological and behavioral performance in ﬁsh,although such effects are species- and trait-speciﬁc (reviewed in
Cattano et al., 2018). In addition, by promoting shifts in biogenic habitat(Milazzo et al., 2019), habitat simpliﬁcation (Sunday et al., 2017) andfood web simpliﬁcation (Fabricius et al., 2014; Vizzini et al., 2017),
high CO2 conditions may indirectly affect some ﬁsh species, especiallythose with highly specialised habitat and resource use. Conversely, generalist species could cope better with the predicted effects of OA on habitat and resources (e.g. Wilson et al., 2008a). This inter-speciﬁc

7

variability in the extent to which ﬁsh may respond to OA-driven habitat
modiﬁcations could play a role in shaping the direction of community
shift and the composition of novel ﬁsh communities under elevated
CO2 conditions (Nagelkerken et al., 2017).
Our ﬁndings support the prediction that OA simpliﬁes habitat composition and reduces habitat complexity (Sunday et al., 2017). Biogenic
habitat complexity (BHP) decreased with increasing pCO2 levels, in a
non-linear relationship (Fig. 4a). When looking at model residuals including both seasons, habitat complexity was high at pCO2 values
below ~500 μatm, whilst this relationship was signiﬁcantly negativefor values up to ~ 1000 μatm (i.e. decreased complexity with increasing
pCO2), after which no signiﬁcant effects were detected probably due tothe low sample size (Fig. 4b). Overall, this trend was consistent in thetwo sampling campaigns (Fig. 4c). The minimum index values werereached between ~500 and ~1000 μatm, where table corals disappeared
being replaced mainly by turf, non-canopy algae and Caulerpa
chemnitzia var. peltata, and where the only calcifying groups were represented by CCA or a few encrusting corals. The consistent complexity
reduction in the elevated CO2 sites compared to control conditions
matches the habitat shift from corals and canopy-forming macroalgae
to turf dominated reefs, which indeed provides fewer structure andhabitat functions than corals (Filbee-Dexter and Wernberg, 2018).
Such transition to less complex habitats may lead to the loss of a suite

Fig. 5. Meta-analysis-derived approach to assess overall and trait-based changes of ﬁsh community at the different elevated CO2 sites, both in June and September. Each point represents
the log response ratio (LnRR) of the average value for the different ﬁsh community variables recorded at Low, Mid and High CO2 sites relative to the ambient CO2 condition (i.e. Control
location: Ref1 and Ref2 together), indicating the sign and the strength of change. a) Number and abundance of ﬁsh species (all the censused species); b) Sorigin: number of species by theirgeographic distribution (Tropical, Sub-tropical or Temperate); c) Ntrophic: abundance of species by their trophic guild (Omnivore, Planktivore, Carnivore or Herbivore); d) Scoral: number ofcoral-reef associated ﬁsh species. Squares indicate signiﬁcant effects per p b0.05. Small circles indicate no signiﬁcant differences.

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C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

of resources for ﬁsh (e.g. food and space availability) and to the alteration of important ecological processes, such as foraging, settlement
and predation avoidance. OA research in CO2 seeps has documented altered properties and non-linear responses for invertebrate communities
along CO2 gradients (e.g. Fabricius et al., 2014; Milazzo et al., 2019),
whilst no effects were detected in ﬁsh communities despite lower habitat complexity under elevated CO2 conditions (Munday et al., 2014).
Here for the ﬁrst time, a consistent temporal response of the ﬁshfauna to the OA-mediated habitat shift was documented. Overall, thenumber of species declined by 35% and 57% when comparing ﬁsh species richness at Control vs High CO2 sites in June and September, respectively (see Table S3). In addition, average species richness andabundance signiﬁcantly decreased from Control to elevated CO2 conditions, with the lowest values recorded at the High and Mid CO2 sites(Fig. 5a; Table S3). Such a pattern was consistent in both June and September (Fig. 5a; Table S3) and conﬁrms previous evidence that shifts toward less complex habitat causes decreased ﬁsh diversity andabundance (e.g. Wilson et al., 2008b), as well as simpliﬁed andhomogenised ﬁsh communities under OA conditions (Nagelkerken
et al., 2017).
Trait-based approaches are increasingly being used to characterise
ecological changes in disturbed ecosystems (Mouillot et al., 2013). Environmental alterations may not only lead to biodiversity loss, but also tochanges in community function, through the selection of species withtraits well-adapted to the new environmental conditions. Since functional groups may show speciﬁc habitat requirements and preferences,
the occurrence and abundance of certain species can be strongly inﬂuenced by habitat composition and characteristics. As expected, traitbased comparisons of ﬁsh communities along the CO2 gradient reveal
a change in composition toward ﬁsh species of less tropical and subtropical origin (Fig. 5b), which is very likely related to the observed
loss of scleractinian corals at N400 ppm CO2 and to the disappearanceof the more specialised associated ﬁsh fauna they support. Therefore,
the observed transitions from corals/high-proﬁle algae to low-proﬁle/turf algae support the available models suggesting that OA will holdtemperature-induced poleward expansion of coral habitats (Yaraet al., 2012), and this will cascade on the composition of the associatedﬁsh fauna with a decreasing pool of tropical, sub-tropical and coral reef
associated species under elevated CO2 conditions. In this regard,
Nakamura et al. (2013) documented an increase of warm-water tropicalﬁsh along the Japan high-latitude waters. Our ﬁndings rather suggestthat if ongoing OA will act as a supplementary game-changer in thenear future, this could not be the case.
When looking at ﬁsh trophic guilds we found that, relative to ambient CO2 conditions, the abundance of herbivorous ﬁsh was signiﬁcantly
higher at the High CO2 site in June, but not in September when seasonal
typhoons caused the removal of macroalgal and turf cover particularly
from the high CO2 area (Fig. 5c). Conversely, omnivorous species
showed the opposite pattern being more abundant after the typhoonseason. These results support previous evidence showing that an increased abundance of herbivore species at elevated CO2 conditions canbe driven by the greater biomass of primary producers associated withenhanced nutritional quality (Vizzini et al., 2017). When turf andalgae are removed by wave action, the availability and type of foodchanges, with repercussions on trophic guild composition (i.e., less herbivorous and more omnivorous species). In addition to this, results fromrecent experiments suggest that by increasing their macrophyte consumption and defecation rates, herbivore population growth could further modify trophic processes in benthic systems under OA conditions,hence amplifying detritus biomass production and potentially altering
energy pathways and ecosystem functioning (Zarco-Perello et al.,2019).
By contrast, a consistent decrease in the abundance of carnivore species was observed along the CO2 gradient in both the sampling seasons(Fig. 5c). Such switches in the composition of functional groups(i.e., increase of herbivore and reduction in carnivores) appears to be acommon community property in elevated CO2 systems and has been
described by other ecosystem studies carried out in temperate natural
CO2 vent systems (Vizzini et al., 2017; Nagelkerken et al., 2015;
Milazzo et al., 2019). In this regard, we speculate that piscivorous species may be attracted to more complex habitat characterised by higher
prey abundance, while herbivores may prefer less complex areas
where primary production is higher and this resource can be accessedmore easily. We also found a consistent decline in the abundance ofplanktivorous ﬁsh and in the number of coral reef associated species
from ambient to elevated CO2 conditions (Fig. 5c and d). Again, thisseems to be related to the loss of coral species at the more elevated
CO2 sites, which provide structural complexity and represent the preferred habitat for many coral ﬁsh species and their prey (Coker et al.,2014; Smith et al., 2016). Our ﬁndings add to previous evidence fromocean warming studies showing ﬁsh diversity declines following extensive coral loss due to bleaching events (e.g. Pratchett et al., 2011). In thisregard, we suggest that OA may act as an additional bottleneck for ﬁsh
community resilience under predicted ocean change scenarios.
Natural analogues have many beneﬁts for furthering knowledge
about the responses of ﬁsh to OA conditions, but they are not perfect analogues for acidifying oceans. The seep areas are localised and so ﬁsh canmove in and out, complicating dose-response assessments (Hurlbert,
1984; Munday et al., 2014; Cornwall and Hurd, 2015). Moreover, carbonate chemistry can be highly variable at CO2 seeps (Cattano et al.,2016; Cattano et al., 2017; Agostini et al., 2018) and toxic areas aroundvolcanic vents need to be avoided in studies of the effects of ocean acidiﬁcation (Vizzini et al., 2013). Nonetheless, the seeps allow studies ofthe ecosystem effects of OA and over time, using multiple CO2 seep locations, a pattern is beginning to emerge about the effects of OA on ﬁshcommunities. An additional caveat with volcanic CO2 seeps is that
ocean acidiﬁcation is occurring concurrently with warming, thus
preventing their use as analogues for future oceans (Rastrick et al.,2018). This issue can be addressed by assessing ecosystem responses
at CO2 seep in different biogeographic regions, or by manipulating temperature along CO2 gradients (Alessi et al., 2019), or by exploiting marine heat waves to assess the combined stress of rising temperatureand elevated CO2 (Rodolfo-Metalpa et al., 2011). In this context, recent
evidence combining laboratory, mesocosm and meta-analyses of CO2
seep research suggests that OA affects the outcome of ocean warming(Goldenberg et al., 2018).
In summary, our data provide direct evidence that shifts in biogenic
habitat and complexity reduction underpin a major loss (35–57%) ofmarine ﬁsh diversity as levels of carbon dioxide in seawater increasein coastal waters off Japan. Ocean acidiﬁcation is expected to limit thepoleward range expansion of coral reef-associated ﬁsh that is now occurring due to warming in Japan (Yamano et al., 2011; Agostini et al.,2018; Kumagai et al., 2018) and elsewhere (Baird et al., 2012; Serrano
et al., 2013; Denis et al., 2015; Tuckett et al., 2017). By enhancing thecompetitive strength of algae at the expense of structurally complex calcifying organisms, such as corals, our surveys indicate that ocean acidiﬁcation will change ﬁsh community function with a greater abundanceof herbivorous ﬁsh species but fewer carnivores and planktivores. Suchchanges in ﬁsh communities would cause major changes in trophic processes and energy pathways, as well as affecting ﬁsheries. We conclude
that the indirect effects of rising CO2 levels on coastal ecosystems will
have a profound impact on reef ﬁsh communities.

CRediT authorship contribution statement
Carlo Cattano: Conceptualization, Writing - original draft, Investigation. Sylvain Agostini: Investigation. Ben P. Harvey: Investigation.
Shigeki Wada: Investigation. Federico Quattrocchi: Formal analysis.
Gabriele Turco: Formal analysis. Kazuo Inaba: Investigation. Jason M.
Hall-Spencer: Investigation. Marco Milazzo: Conceptualization, Writing - original draft, Investigation.

C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

Acknowledgements
We would like to thank the technical staff of Shimoda Marine Research Center (University of Tsukuba) for ﬁeld assistance and the useof RV Tsukuba, and Prof. Alessandro Aiuppa and Dr. Rossella Di Napoli(University of Palermo, Italy) for providing the HydroC Carbon Dioxide
Sensor. We are grateful to Prof. Nakamura for help with ﬁsh identiﬁcation. This study was supported by the ‘International Education and Research Laboratory Program’, University of Tsukuba (Japan). Travel
costs were funded by the University of Palermo (Italy) for C.C. and by
a Japan Society for the Promotion of Science Short Term Invitation Fellowship (Grant Number: S16073) and by JAMBIO (Japan) for M.M.
Images used within the graphical abstract are courtesy of the Integration and Application Network, University of Maryland Center for Environmental Science (ian.umces.edu/symbols/).
Declaration of competing interest
The authors declare that they have no known competing ﬁnancial
interests or personal relationships that could have appeared to inﬂuence the work reported in this paper.
Appendix A. Supplementary data
Supplementary data to this article can be found online at https://doi.
org/10.1016/j.scitotenv.2020.138501.

References
Agostini, S., Wada, S., Kon, K., Omori, A., Kohtsuka, H., Fujimura, H., et al., 2015. Geochemistry of two shallow CO2 seeps in Shikine Island (Japan) and their potential for ocean
acidiﬁcation research. Reg. Stud. Mar. Sci. 2, 45–53.
Agostini, S., Harvey, B.P., Wada, S., Kon, K., Milazzo, M., Inaba, K., Hall-Spencer, J.M., 2018.
Ocean acidiﬁcation drives community shifts towards simpliﬁed non-calciﬁed habitats
in a subtropical−temperate transition zone. Sci. Rep. 8, 11354.
Alessi, C., Giomi, F., Furnari, F., Sarà, G., Chemello, R., Milazzo, M., 2019. Ocean acidiﬁcationand elevated temperature negatively affect recruitment, oxygen consumption andcalciﬁcation of the reef-building Dendropoma cristatum early life stages: evidence
from a manipulative ﬁeld study. Sci. Total Environ. 693, 133476.
Anderson, M., Braak, C.T., 2003. Permutation tests for multi-factorial analysis of variance.
J. Stat. Comput. Simul. 73 (2), 85–113.
Anderson, M., Gorley, R.N.R.N., Clarke, K., Anderson, M.J., Gorley, R.N., Clarke, K.R.,
Anderson, M., Gorley, R., Andersom, M.J., 2008. PERMANOVA+ for PRIMER. Guide
to Software and Statistical Methods.
Baird, A.H., Sommer, B., Madin, J.S., 2012. Pole-ward range expansion of Acropora spp.
along the east coast of Australia. Coral Reefs 31, 1063. https://doi.org/10.1007/
s00338-012-0928-6.
Barkley, H.C., Cohen, A.L., Golbuu, Y., Starczak, V.R., De Carlo, T.M., Shamberger, K.E.F.,
2015. Changes in coral reef communities across a natural gradient in seawater pH.
Sci. Adv. 1, e1500328.
Cattano, C., Giomi, F., Milazzo, M., 2016. Effects of ocean acidiﬁcation on embryonic respiration and development of a temperate wrasse living along a natural CO2 gradient.
Conservation physiology 4 (1), cov073.
Cattano, C., Calò, A., Di Franco, A., Firmamento, R., Quattrocchi, F., Sdiri, K., et al., 2017.
Ocean acidiﬁcation does not impair predator recognition but increases juvenile
growth in a temperate wrasse off CO2 seeps. Mar. Environ. Res. 132, 33–40.
Cattano, C., Claudet, J., Domenici, P., Milazzo, M., 2018. Living in a high CO2 world: a global
meta-analysis shows multiple trait-mediated ﬁsh responses to ocean acidiﬁcation.
Ecol. Monogr. 88 (3), 320–335.
Clarke, K.R., Gorley, R.N., 2006. User manual/tutorial. Primer-E Ltd, Plymouth, p. 93.
Coker, D.J., Wilson, S.K., Pratchett, M.S., 2014. Importance of live coral habitat for reefﬁshes. Rev. Fish Biol. Fish. 24 (1), 89–126.
Connell, S.D., Doubleday, Z.A., Foster, N.R., Hamlyn, S.B., Harley, C.D., Helmuth, B., et al.,2018. The duality of ocean acidiﬁcation as a resource and a stressor. Ecology 99 (5),1005–1010.
Cornwall, C.E., Hurd, C.L., 2015. Experimental design in ocean acidiﬁcation research: problems and solutions. ICES J. Mar. Sci. 73 (3), 572–581.
De’ath, G., Fabricius, K.E., Sweatman, H., Puotinen, M., 2012. The 27-year decline of coral
cover on the Great Barrier Reef and its causes. Proceedings of the National Academyof Sciences U.S.A. 109, 17995–17999.
Denis, V., De Palmas, S., Benzoni, F., Chen, C.A., 2015. Extension of the known distribution
and depth range of the scleractinian coral Psammocora stellata: ﬁrst record from a
Taiwanese mesophotic reef. Mar. Biodivers. 45 (4), 619–620.
Di Franco, A., Calò, A., Sdiri, K., Cattano, C., Milazzo, M., Guidetti, P., 2019. Ocean acidiﬁcation affects somatic and otolith growth relationship in ﬁsh: evidence from an in situ
study. Biol. Lett. 15 (2), 20180662.

9

Dickson, A.G., 1990. Thermodynamics of the dissociation of boric acid in synthetic seawater from 273.15 to 318.15 K. Deep Sea Research Part A. Oceanographic Research Papers 37 (5), 755–766.
Dickson, A.G., Millero, F.J., 1987. A comparison of the equilibrium constants for the dissociation of carbonic acid in seawater media. Deep Sea Research Part A. Oceanographic
Research Papers 34 (10), 1733–1743.
Enochs, I.C., Manzello, D.P., Donham, E.M., Kolodziej, G., Okano, R., Johnston, L., et al., 2015.
Shift from coral to macroalgae dominance on a volcanically acidiﬁed reef. Nat. Clim.
Chang. 5, 1083–1088.
Fabricius, K.E., Langdon, C., Uthicke, S., Humphrey, C., Noonan, S., De’ath, G., et al., 2011.
Losers and winners in coral reefs acclimatized to elevated carbon dioxide concentrations. Nat. Clim. Chang. 1, 165–169.
Fabricius, K.E., De’ath, G., Noonan, S., Uthicke, S., 2014. Ecological effects of ocean acidiﬁcation and habitat complexity on reef-associated macroinvertebrate communities.
Proc. R. Soc. B Biol. Sci. 281, 20132479.
Fabricius, K.E., Noonan, S.H., Abrego, D., Harrington, L., 2017. Low recruitment due to altered settlement substrata as primary constraint for coral communities under
ocean acidiﬁcation. Proc. R. Soc. B Biol. Sci. 284 (1862), 20171536.
Falkenberg, L.J., Russell, B.D., Connell, S.D., 2013. Contrasting resource limitations of marine primary producers: implications for competitive interactions under enriched
CO2 and nutrient regimes. Oecologia 172, 575–583 (2013).
Filbee-Dexter, K., Wernberg, T., 2018. Rise of turfs: a new battlefront for globally declining
kelp forests. BioScience 68 (2), 64–76.
Gaylord, B., Kroeker, K.J., Sunday, J.M., Anderson, K.M., Barry, J.P., Brown, N.E., et al., 2015.
Ocean acidiﬁcation through the lens of ecological theory. Ecology 96 (1), 3–15.
Goldenberg, S.U., Nagelkerken, I., Marangon, E., Bonnet, A., Ferreira, C.M., Connell, S.D.,
2018. Ecological complexity buffers the impacts of future climate on marine consumers. Nat. Clim. Chang. 8, 229–233.
Hall-Spencer, J.M., Harvey, B.P., 2019. Ocean acidiﬁcation impacts on coastal ecosystemservices due to habitat degradation. Emerg. Top. Life Sci. 3 (2), 197–206.
Hall-Spencer, J.M., Rodolfo-Metalpa, R., Martin, S., Ransome, E., Fine, M., Turner, S.M., etal., 2008. Volcanic carbon dioxide vents show ecosystem effects of ocean acidiﬁcation.
Nature 454, 96–99.
Harley, C.D., Anderson, K.M., Demes, K.W., Jorve, J.P., Kordas, R.L., Coyle, T.A., Graham,
M.H., 2012. Effects of climate change on global seaweed communities. J. Phycol. 48(5), 1064–1078.
Harmelin-Vivien, M.L., Harmelin, J.G., Chauvet, C., Duval, C., Galzin, R., Lejeune, P., et al.,1985. Evaluation visuelle des peuplements et populations de poissons méthodes etproblèmes. Revue d’Écologie 40, 467–539.
Harvey, B.P., Gwynn-Jones, D., Moore, P.J., 2013. Meta-analysis reveals complex marine biological responses to the interactive effects of ocean acidiﬁcation and warming. Ecol.
Evol. 3 (4), 1016–1030.
Harvey, B.P., Agostini, S., Kon, K., Wada, S., Hall-Spencer, J.M., 2019. Diatoms dominate andalter marine food-webs when CO2 rises. Diversity 11 (12), 242.
Hoegh-Guldberg, O., 1999. Climate change, coral bleaching and the future of the world’s
coral reefs. Mar. Freshw. Res. 50 (8), 839–866.
van Hooidonk, R., Maynard, J.A., Manzello, D., Planes, S., 2014. Opposite latitudinal gradients in projected ocean acidiﬁcation and bleaching impacts on coral reefs. Glob.
Chang. Biol. 20, 103–112.
Hughes, T.P., 1994. Catastrophes, phase-shifts, and large scale degradation of a Caribbean
coral reef. Science 265, 1547–1551.
Hurlbert, S.H., 1984. Pseudoreplication and the design of ecological ﬁeld experiments.
Ecol. Monogr. 54 (2), 187–211.
Inoue, S., Kayanne, H., Yamamoto, S., Kurihara, H., 2013. Spatial community shift fromhard to soft corals in acidiﬁed water. Nat. Clim. Chang. 3, 683–687.
Jackson, J.B.C., Kirby, M.X., Berger, W.H., et al., 2001. Historical overﬁshing and the recent
collapse of coastal ecosystems. Science 293, 629–637.
Kroeker, K.J., Kordas, R.L., Crim, R., Hendriks, I.E., Ramajo, L., Singh, G.S., Duarte, C.M.,
Gattuso, J.P., 2013. Impacts of ocean acidiﬁcation on marine organisms: quantifying sensitivities and interaction with warming. Glob. Chang. Biol. 19 (6),1884–1896.
Kumagai, N.H., Molinos, J.G., Yamano, H., Takao, S., Fujii, M., Yamanaka, Y., 2018. Ocean
currents and herbivory drive macroalgae-to-coral community shift under climate
warming. Proc. Natl. Acad. Sci. 115 (36), 8990–8995.
Legendre, P., Anderson, M.J., 1999. Distance-based redundancy analysis: testing multispecies responses in multifactorial ecological experiments. Ecol. Monogr. 69 (1), 1–24.
McArdle, B.H., Anderson, M.J., 2001. Fitting multivariate models to community data: acomment on distance-based redundancy analysis. Ecology 82 (1), 290–297.
McCulloch, M., Fallon, S., Wyndham, T., Hendy, E., Lough, J., Barnes, D., 2003. Coral recordof increased sediment ﬂux to the inner Great Barrier Reef since European settlement.
Nature 421 (6924), 727–730.
Mehrbach, C., Culberson, C.H., Hawley, J.E., Pytkowicx, R.M., 1973. Measurement of the apparent dissociation constants of carbonic acid in seawater at atmospheric pressure 1.
Limnol. Oceanogr. 18 (6), 897–907.
Midorikawa, T., Nemoto, K., Kamiya, H., Ishii, M., Inoue, H.Y., 2005. Persistently strong oceanic CO2 sink in the western subtropical North Paciﬁc. Geophys. Res. Lett. 32, L05612.
Milazzo, M., Cattano, C., Alonzo, S.H., Foggo, A., Gristina, M., Rodolfo-Metalpa, R., et al.,2016. Ocean acidiﬁcation affects ﬁsh spawning but not paternity at CO2 seeps. Proc.
R. Soc. B Biol. Sci. 283 (1835), 20161021.
Milazzo, M., Alessi, C., Quattrocchi, F., Chemello, R., D’Agostaro, R., Gil, J., et al., 2019. Biogenic habitat shifts under long-term ocean acidiﬁcation show nonlinear community
responses and unbalanced functions of associated invertebrates. Sci. Total Environ.
667, 41–48.
Mouillot, D., Graham, N.A., Villéger, S., Mason, N.W., Bellwood, D.R., 2013. A functional approach reveals community responses to disturbances. Trends Ecol. Evol. 28 (3),167–177.

10

C. Cattano et al. / Science of the Total Environment 725 (2020) 138501

Muir, P.R., Wallace, C.C., Done, T., Aguirre, J.D., 2015. Limited scope for latitudinal extension of reef corals. Science 348, 1135–1138.
Munday, P.L., Cheal, A.J., Dixson, D.L., Rummer, J.L., Fabricius, K.E., 2014. Behavioural impairment in reef ﬁshes caused by ocean acidiﬁcation at CO2 seeps. Nat. Clim. Chang.
4, 1–6.
Nagelkerken, I., Russell, B.D., Gillanders, B.M., Connell, S.D., 2015. Ocean acidiﬁcation alters ﬁsh populations indirectly through habitat modiﬁcation. Nat. Clim. Chang. 6,
89–95.
Nagelkerken, I., Goldenberg, S.U., Ferreira, C.M., Russell, B.D., Connell, S.D., 2017. Species
interactions drive ﬁsh biodiversity loss in a high-CO2 world. Curr. Biol. 27 (14),2177–2184.
Nakamura, Y., Feary, D.A., Kanda, M., Yamaoka, K., 2013. Tropical ﬁshes dominate temperate reef ﬁsh communities within western Japan. PLoS One 8, e81107.
O’Brien, J.M., Scheibling, R.E., 2018. Turf wars: competition between foundation and turfforming species on temperate and tropical reefs and its role in regime shifts. Mar.
Ecol. Prog. Ser. 590, 1–17.
Pierrot, D., Lewis, E., Wallace, D.W.R., 2006. MS Excel Program Developed for CO2 System
Calculations. ORNL/CDIAC-105a. Carbon Dioxide Information Analysis Center, Oak
Ridge National Laboratory, U.S. Department of Energy, Oak Ridge, Tennessee
https://doi.org/10.3334/CDIAC/otg.CO2SYS_XLS_CDIAC105a.
Pratchett, M.S., Hoey, A.S., Wilson, S.K., Messmer, V., Graham, N.A., 2011. Changes in biodiversity and functioning of reef ﬁsh assemblages following coral bleaching and coralloss. Diversity 3 (3), 424–452.
R Core Team, 2018. R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria.
Rastrick, S.S., Graham, H., Azetsu-Scott, K., Calosi, P., Chierici, M., Fransson, A., et al., 2018.
Using natural analogues to investigate the effects of climate change and ocean acidiﬁcation on northern ecosystems. ICES J. Mar. Sci. 75 (7), 2299–2311.
Rodolfo-Metalpa, R., Houlbrèque, F., Tambutté, E., Boisson, F., Baggini, C., Patti, F.P., Jeffree,R., et al., 2011. Coral and mollusc resistance to ocean acidiﬁcation adversely affectedby warming. Nat. Clim. Chang. 1, 308–312.
Schneider, C.A., Rasband, W.S., Eliceiri, K.W., 2012. NIH image to ImageJ: 25 years of image
analysis. Nat. Methods 9 (7), 671.
Serrano, E., Coma, R., Ribes, M., Weitzmann, B., García, M., Ballesteros, E., 2013. Rapid
northward spread of a zooxanthellate coral enhanced by artiﬁcial structures andsea warming in the western Mediterranean. PLoS One 8 (1), e52739.
Smith, J.N., De’ath, G., Richter, C., Cornils, A., Hall-Spencer, J.M., Fabricius, K.E., 2016. Ocean
acidiﬁcation reduces demersal zooplankton that reside in tropical coral reefs. Nat.
Clim. Chang. 6, 1124–1129.
Stewart-Oaten, A., Murdoch, W.W., Parker, K.R., 1986. Environmental impact assessment:“pseudoreplication” in time? Ecology 67, 929–940.
Suggett, D.J., Hall-Spencer, J.M., Rodolfo-Metalpa, R., Boatman, T.G., Payton, R., Tye Pettay,D., et al., 2012. Sea anemones may thrive in a high CO2 world. Glob. Chang. Biol. 18,
3015–3025.
Sunday, J.M., Fabricius, K.E., Kroeker, K.J., Anderson, K.M., Brown, N.E., Barry, J.P., et al.,2017. Ocean acidiﬁcation can mediate biodiversity shifts by changing biogenic habitat. Nat. Clim. Chang. 7 (1), 81.

Tuckett, C.A., de Bettignies, T., Fromont, J., Wernberg, T., 2017. Expansion of corals on temperate reefs: direct and indirect effects of marine heatwaves. Coral Reefs 36 (3),947–956.
Uppström, L.R., 1974. The boron/chlorinity ratio of deep-sea water from the Paciﬁc Ocean.
Deep-Sea Res. Oceanogr. Abstr. 21, 161–162.
Vergés, A., Steinberg, P.D., Hay, M.E., Poore, A.G.B., Campbell, A.H., Ballesteros, E., et al.,2014. The tropicalization of temperate marine ecosystems: climate-mediatedchanges in herbivory and community phase shifts. Proc. R. Soc. B Biol. Sci. 281,
20140846.
Vergés, A., Doropoulos, C., Malcolm, H.A., Skye, M., Garcia-Pizá, M., Marzinelli, E.M., et al.,2016. Long-term empirical evidence of ocean warming leading to tropicalization ofﬁsh communities, increased herbivory, and loss of kelp. Proc. Natl. Acad. Sci. U.S.A.
113 (48), 13791–13796.
Veron, J.E.N., Minchin, P.R., 1992. Correlations between sea surface temperature, circulation patterns and the distribution of hermatypic corals of Japan. Cont. Shelf Res. 12(7–8), 835–857.
Viechtbauer, W., 2010. Conducting meta-analyses in R with the metafor package. J. Stat.
Softw. 36 (3), 1–48.
Vizzini, S., Di Leonardo, R., Costa, V., Tramati, C.D., Luzzu, F., Mazzola, A., 2013. Trace element bias in the use of CO2 vents as analogues for low pH environments: implications
for contamination levels in acidiﬁed oceans. Estuar. Coast. Shelf Sci. 134, 19–30.
Vizzini, S., Martínez-Crego, B., Andolina, C., Massa-Gallucci, A., Connell, S.D., Gambi, M.C.,
2017. Ocean acidiﬁcation as a driver of community simpliﬁcation via the collapse ofhigher-order and rise of lower-order consumers. Sci. Rep. 7 (1), 4018.
Wilson, S.K., Burgess, S.C., Cheal, A.J., Emslie, M., Fisher, R., Miller, I., et al., 2008a. Habitat
utilization by coral reef ﬁsh: implications for specialists vs. generalists in a changing
environment. J. Anim. Ecol. 77 (2), 220–228.
Wilson, S.K., Fisher, R., Pratchett, M.S., Graham, N.A.J., Dulvy, N.K., Turner, R.A., et al.,2008b. Exploitation and habitat degradation as agents of change within coral reefﬁsh communities. Glob. Chang. Biol. 14, 2796–2809.
Wittmann, A.C., Pörtner, H.O., 2013. Sensitivities of extant animal taxa to ocean acidiﬁcation. Nat. Clim. Chang. 3 (11), 995.
Wood, S.N., 2006. Low-rank scale-invariant tensor product smooths for generalized additive mixed models. Biometrics 62 (4), 1025–1036.
Wood, S.N., 2011. Fast stable restricted maximum likelihood and marginal likelihood estimation of semiparametric generalized linear models. J. R. Stat. Soc. Ser. B (Stat
Methodol.) 73 (1), 3–36.
Yamano, H., Sugihara, K., Nomura, K., 2011. Rapid poleward range expansion of tropicalreef corals in response to rising sea surface temperatures. Geophys. Res. Lett. 38 (4).
Yara, Y., Vogt, M., Fujii, M., Yamano, H., Hauri, C., Steinacher, M., et al., 2012. Ocean acidiﬁcation limits temperature-induced poleward expansion of coral habitats around
Japan. Biogeosciences 9, 4955–4968.
Zarco-Perello, S., Langlois, T.J., Holmes, T., Vanderklift, M.A., Wernberg, T., 2019.
Overwintering tropical herbivores accelerate detritus production on temperate
reefs. Proc. R. Soc. B 286 (1915), 20192046.