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How good are we at assessing the impact of ocean acidification in coastal systems? Limitations, omissions and strengths of commonly used experimental approaches with special emphasis on the neglected role of fluctuations

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How good are we at assessing the impact of ocean acidification in coastal systems? Limitations, omissions and strengths of commonly used experimental approaches with special emphasis on the neglected role of fluctuations Abstract. Much of our past research on ocean acidification has focussed on direct responses to pCO 2 increase at the (sub-) organism level, but does not produce findings that can be projected into the natural context. On the basis of a review of ,350 recent articles mainly on ocean acidification effects, we highlight major limitations of commonly used experimental approaches. Thus, the most common type of investigation, simplified and tightly controlled laboratory experiments, has yielded a wealth of findings on short-term physiological responses to acidification, but any extrapolation to the natural ecosystem level is still problematic. For this purpose, an upscaling is required regarding the number of stressors, of ontogenetic stages, of species, of populations, of generations as well as the incorporation of fluctuating intensities of stress. Because the last aspect seems to be the least recognised, we treat in more detail the natural fluctuations of the carbonate system at different temporal and spatial scales. We report on the very rare investigations that have assessed the biological relevance of natural pH or pCO 2 fluctuations. We conclude by pleading the case for more natural research approaches that integrate several organisational levels on the response side, several drivers, biological interactions and environmental fluctuations at various scales.
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How good are we at assessing the impact of ocean
acidification in coastal systems? Limitations, omissions
and strengths of commonly used experimental approaches
with special emphasis on the neglected role of fluctuations
M. Wahl
A
,
B
,V. Saderne
A
and Y. Sawall
A
A
Geomar Helmholtz Centre for Ocean Research, Duesternbrookerweg 20, D-24105 Kiel, Germany.
B
Corresponding author. Email: mwahl@geomar.de
Abstract. Much of our past research on ocean acidification has focussed on direct responses to pCO
2
increase at the (sub-)
organism level, but does not produce findings that can be projected into the natural context. On the basis of a review of
,350 recent articles mainly on ocean acidification effects, we highlight major limitations of commonly used experimental
approaches. Thus, the most common type of investigation, simplified and tightly controlled laboratory experiments, has
yielded a wealth of findings on short-term physiological responses to acidification, but any extrapolation to the natural
ecosystem level is still problematic. For this purpose, an upscaling is required regarding the number of stressors, of
ontogenetic stages, of species, of populations, of generations as well as the incorporation of fluctuating intensities of stress.
Because the last aspect seems to be the least recognised, we treat in more detail the natural fluctuations of the carbonate
system at different temporal and spatial scales. We report on the very rare investigations that have assessed the biological
relevance of natural pH or pCO
2
fluctuations. We conclude by pleading the case for more natural research approaches that
integrate several organisational levels on the response side, several drivers, biological interactions and environmental
fluctuations at various scales.
Additional keywords: amplitudes at different scales, boundary layers, coastal habitats, fluctuations v. constant regimes,
global change.
Received 13 June 2014, accepted 19 November 2014, published online 17 June 2015
Introduction
Biological systems are embedded in a physical environment that
fluctuates at various scales (Hofmann et al. 2011;Frieder et al.
2012). Seasons impose regular fluctuations at the temporal scale
of months (Frankignoulle and Bouquegneau 1990;Thomsen
et al. 2010). Climate dynamics (e.g. anthropogenic shifts, North
Atlantic Oscillation) drive environmental change at the scale of
decades (Soares et al. 2014). Weather and discrete upwelling or
downwelling events are responsible for abiotic variability at the
scale of hours to weeks (Feely et al. 2008;Saderne et al. 2013).
Biological activities such as respiration and photosynthesis lead
to fluctuations at frequencies of seconds to weeks (Hofmann et al.
2011;Buapet et al. 2013). The various drivers of fluctuations in
pH or pCO
2
have been excellently reviewed by Waldbusser and
Salisbury (2014). The various physicochemical environmental
variables relevant to the performance of aquatic organisms
(e.g. light, temperature, salinity, nutrients, pH) are differentially
affected by the above drivers which, at a given geographical
position, fluctuate at different amplitude and frequency. Conse-
quently, at any point in time, these variables could be at different
distances from the physiological optimum of a given organism.
To complicate things, the value of this optimum differs among
physiological phases of an organism, among the various onto-
genetic stages of a species and among the various species in a
community interacting with each other (e.g. Hadfield and
Strathmann 1996;Wahl et al. 2011;Byrne and Przeslawski
2013). Although most of the foregoing is well known to most
scientists and has beenaccounted for in more ‘mature’ fields such
as intertidal ecology, we have the impression that in the study of
ocean acidification it is time to move onward from rather sim-
plistic laboratory experiments to more complex approaches
allowing inference beyond the laboratory bench.
One paradigm that has ruled ecological research over the past
decades is to study the influence of single factors on a given
response variable by using treatments with different levels of
that factor and keeping all other factors constant. This approach
is undoubtedly of immense analytical value because it allows us
to identify the effects of the factor considered clearly and with
high statistical power. It is, at the same time, limited to identify
the (immediate) effect of this one factor at this one intensity on a
usually well defined single response variable. Most of us would
agree that in order to determine the impact of a given factor such
as ocean acidification in a natural context on a given species we
need to know: (1) its interactions with other abiotic factors in the
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system, (2) its impact on important life-history traits of a
species, (3) the sensitivity of all developmental stages of
the species to this factor, (4) the carry-over effects between
successive developmental stages, (5) the impact of this factor on
species interacting with the focal species (parasites, pathogens,
consumers, facilitators, competitors), (6) the variability of factor
strength and of organism sensitivity in time, (7) the differences
in sensitivity to this factor among populations of the focal
species, and (8) the importance of whether the putative stress
is constant (pressure) or fluctuating (pulse). If we accept this
view, we must conclude that many of the results produced in the
past – although clear and significant – cannot be used to predict
the in situ response to the factor considered at the species or
ecosystem level. We explicitly include much of our own
research in this category (e.g. Appelhans et al. 2012,2014;
Pansch et al. 2012;Saderne et al. 2013).
In the following we try to highlight our methodologically
caused research limitations using the example of ocean acidifi-
cation which has been one of the most active fields of marine
ecological research during the last decade. To this purpose we
have identified several methodological traits (see Methods) from
a total of 324 articles, which, during the past decade, reported on
the biological effect of reducing pH. Besides other limitations,
one of the most widespread and least acknowledged simplifica-
tions of the published research was to ignore the importance of
temporal fluctuations in the pH regime. One reason certainly is
that often the in situ fluctuations are unknown. To illustrate the
range of such fluctuations, we extracted the information on
frequency, amplitude and rate-of-change regarding in situ fluc-
tuations of pH or pCO
2
from 54 papers reporting on natural
fluctuations of pH in marine habitats until August 2014. In
addition, we present data from our own, as yet unpublished,
work to illustrate hitherto largely ignored fluctuations at the
small scale (submillimetres) of a diffusive boundary layer that
constitutes the ‘nano’-habitat of microorganisms, larvae and
spores. Furthermore, we provide an example of an experimental
set-up allowing for combining natural fluctuations with con-
trolled treatments (‘Kiel Benthocosms’).
Our review will be structured by two main questions,
namely: ‘Which are the most common methodological traits
in ocean acidification (OA) research of the past decade?’ and, as
an example of one of these traits, ‘How do frequency and
amplitude of fluctuations in pH (or other variables of the
carbonate system) differ between the typical OA experiment
and natural systems?’ The results of these analyses will allow us
to conclude how well most of our findings on OA effects are
appropriate for evaluating OA impacts in coastal systems.
Recognising that since 2013 there has been a shift towards more
complex and more realistic experiments, we will end with a plea
to pursue and intensify this movement towards experimental
designs that produce more relevant insights (e.g. Byrne and
Przeslawski 2013;Stewart et al. 2013).
Materials and methods
Dominant traits of experimental marine OA studies
We searched for studies that investigated the effects of ocean
acidification, pH changes, or pCO
2
changes on marine organ-
isms in the Web of Science core collection, Science Citation
Index Expanded (SCI-EXPANDED). The following search
conditions were used: TI ¼(‘carbon dioxide’ OR CO
2
OR CO2
OR pCO
2
OR pCO
2
OR hypercapnia OR ‘ocean acidification’)
AND TS ¼(effect* OR affect* OR impact* OR stress*) AND
TS ¼(marine OR seawater) AND TS ¼(organism* OR
communit* OR species) NOT TS ¼(lake OR freshwater). The
following Web of Science categories were applied: Ecology
or marine, freshwater biology, oceanography, environmental
science, physiology, biology, plant science, biochemistry,
molecular biology, environmental studies, microbiology. All
papers published between 1945 and March 2014 were searched.
This search profile yielded 527 hits, of which 324 contained
experimental work in the field, mesocosms or laboratory, which
were consequently used for our meta-analysis (all 324 refer-
ences are provided as Table S1 of the Supplementary material).
The other studies were either purely oceanographic, pure water
chemistry, observational or descriptive in situ studies and
therefore not suitable for this analysis. The information
extracted from the studies were the following experimental
design characteristics: (1) whether the study was conducted
in the laboratory, in mesocosms or in the field, (2) which
ontogenetic stage was considered, (3) how many successive
ontogenetic stages were considered, (4) how many successive
generations were considered, (5) how many (interactive) factors
were applied, (6) whether the treatment levels were constant
or fluctuating, and in how many (7) geographical regions,
(8) seasons of the year or (9) different years the experiment was
run. The categorisation of every study is presented in Table S1 of
the Supplementary material.
In situ fluctuations of pH
We considered only those studies where at least one of the
descriptors of the carbonate chemistry (i.e. pCO
2
, pH, CO
2 (aq)
,
HCO
3
,CO
3
2
) has been measured in a natural benthic habitat.
Studies documenting only air–sea exchanges of CO
2
(through,
for example, floating bells) or variations within artificial
enclosures were excluded. We restricted our search to marine
systems and excluded estuaries, but included brackish marginal
seas such as the Baltic Sea or the Black Sea. In total, 54
publications from the last four decades met the above criteria
(see Table S2 in the Supplementary material).
We considered as ‘continuous’ any series in which at least
one parameter of the carbonate chemistry was measured with a
sampling frequency of less than 30 min. ‘Transects’ corresponds
to studies in which measurements were conducted simulta-
neously on at least two locations along an environmental
abiotic (e.g. depth, tidal zonation) or biotic (ecotones) gradient.
‘Replicated’ corresponds to studies in which measurements
were conducted simultaneously at at least two locations of
similar abiotic and biotic characteristics.
Characterisation of algal diffusive boundary layer
The diffusive boundary layer on the alga surface was investi-
gated on freshly collected Fucus vesiculosus blades (n¼3) in
September 2013 with a pH-microsensor. In a flow-through
system a Fucus blade was fixed horizontally on a ruler, which
allowed a directional flow over the alga surface. Water
temperature was kept constant at 208C and the velocity was
BMarine and Freshwater Research M. Wahl et al.
regulated by a valve. A pH-microsensor with a tip diameter
of 10 mm, a multimeter and a motor-run micromanipulator
(all from Unisense, Denmark) were used to measure the pH
in 40–100-mm steps approaching the alga surface. Velocity
(stagnant, slow (0.5 cm s
1
) and high (1.5 cm s
1
)) and light
conditions (light or dark) were manipulated, resulting in six
different treatments, each applied on all blades. Between each
treatment, the persisting diffusive boundary layer was first
destroyed (water burst with a syringe) and then left for 5 min to
build up under the new condition. Pilot assays had shown that
this time lag is sufficient for the build-up of a stable boundary
layer under non-stagnant conditions. Under stagnant conditions,
the stabilisation of the boundary layer takes somewhat longer
(depending on temperature), but our first priority was to permit
the same time for the algal physiology to acclimate to the new
conditions. The profiles measured under stagnant conditions
may thus be on the conservative side.
Results and discussion
Dominant traits of experimental OA studies
Most of the investigations were restricted to one ontogenetic
stage (75%), to one generation (96%), to one factor (72%), to
one season (96%), to a single year (99%), were laboratory based
(73%) and applied the treatment at a constant intensity (89%)
(Fig. 1). Studies upscaling in two (or more) of these traits
simultaneously by, for instance, examining multifactor effects
on several ontogenetic stages are very rare (see Table S1),
namely 13 out of 327 (or 4%).
The results produced by the numerous single-factor and
single-target experiments were, undoubtedly, important in the
‘juvenile’ phase of OA research shaping our feeling for potential
impacts of given pH shifts on given organisms or on given
suborganismal processes. In situ, however, the net impact may
differ. For example, the impact of a stressor may be additive,
synergistic or antagonistic (selective mortality leading to
reduced sensitivity of older stages) across ontogenetic stages
and knowing the impact of pH on only one stage gives an
incomplete picture. Also, in the course of a year, a perennial
species usually passes through different physiological phases
and a given level of pH may be expected to have very different
impacts in different seasons. Additionally, the in situ pH level,
as well as many other environmental variables (Miller-Neilan
and Rose 2014), is variable (see below) in time and space.
Planktonic organisms, which can be considered more or less
‘resident’ in a particular water body, unless they migrate
100
90
80
70
60
50
Proportion of studies (%)
40
30
20
10
0
Kind of study Ontogenetic stage Number of
ontogenetic
stages
Number
of generations
Number
of factors
Fluctuat. Number
of regions
Number
of seasons
Number
of years
Lab
Mesoc.
Field
Adult
Gametes
Larvae
Juveniles
1
2
3
4
1
2
>2
1
2
>2
1
2
>2
1
2
>2
1
2
3
>3
N
Y
Fig. 1. Trait distribution of OA research effort as extracted from .300 recent investigations regarding OA effects on marine organisms (see Table S1).
The dark bars indicate the traits of experimental approach apparently preferred for their simplicity or potential to deliver clear and significant results.
Publications sum up to 100% within each aspect of experimental design given on the x-axis.
Fluctuations matter Marine and Freshwater Research C
vertically, will mainly experience pH fluctuations in time.
Sedentary benthic organisms, in contrast, experience temporal
fluctuations plus spatial heterogeneity in pH distribution when
water movement (currents, up- or downwelling) transport this
heterogeneity through space.
Many of these short-comings have been recognised in recent
years. Thus, OA is increasingly combined with other environ-
mental factors (e.g. Connell and Russell 2010;Connell et al.
2013;Hiebenthal et al. 2013;Duarte et al. 2014), OA effects are
followed over several ontogenetic stages (e.g. Forsgren et al.
2013;Kurihara et al. 2013), differentiated among seasons
(e.g. Miller et al. 2012;McCoy 2013) or followed over several
generations (e.g. Low-De´carie et al. 2011;Lohbeck et al. 2013).
How pH or pCO
2
fluctuations at frequencies and amplitudes
similar to those in the natural habitat may modulate OA impact
relative to constant conditions, however, is still virtually unex-
plored. One plausible reason is, that long-term, high-resolution
monitoring of these in situ fluctuations do not exist for most
habitats.
In situ fluctuations in carbonate chemistry
In the following we will present recently published evidence for
spatial and temporal pH fluctuations at different scales. We will
only briefly mention the drivers for these fluctuations because
these have recently been reviewed excellently by Waldbusser
and Salisbury (2014).
Overall, we found 54 publications in which at least one of the
descriptors of the carbonate chemistry (pCO
2
, pH, total alkalin-
ity, dissolved inorganic carbon (DIC), [CO
2
]
(aq)
, [HCO
3
],
[CO
3
2
]) had been monitored in situ. We noted a large disparity
in the research effort among benthic habitats. Tropical coral
reefs, with 24 studies (49% of the total of studies), have received
most of the research attention so far (Table 1). Studies on the
fluctuations in intertidal rock pools were represented by nine
studies (16.5% of the total). Rock pools have been recognised
since the 1950s as extremely fluctuating environments with
respect to pCO
2
and O
2
(Daniel and Boyden 1975;Truchot
and Duhamel-Jouve 1980) and have attracted the attention of
physiologists in particular. Sea grass meadows were represented
by only nine studies (16.5%) as well, which is a small number
considering their ecological importance. Most of these studies
have been conducted in Posidonia oceanica meadows of
the Mediterranean Sea (Frankignoulle and Diste`che 1984;
Frankignoulle 1988;Frankignoulle and Bouquegneau 1990;
Hendriks et al. 2014). Only one study on Zosteraceae was found
despite their worldwide distribution in temperate areas (Buapet
et al. 2013) and only two studies focussed on tropical sea grass
meadows of Thalassia spp. (Yates et al. 2007;Semesi et al.
2009). Seaweed habitats (excluding kelp, 11% of the total) as
well as kelp forests (7% of total) are severely understudied
relative to their ecological relevance. In addition, all kelp studies
in this context were performed in Macrocystis pyrifera habitats
(Delille et al. 2000,2009;Hofmann et al. 2011;Frieder et al.
2012). We did not find any studies on temperate or tropical
gastropod or bivalve reefs (or any reef formed by organisms
other than tropical reef-building corals), such as those formed by
oysters or mussels. Confirming a general trend in benthic
ecology, we found that the research effort is strongly skewed
towards tropical coral reefs.
Sea water pH may be biologically altered at the local scale
(kilometres to submillimetres) especially in coastal systems that
are dominated by sea grasses, macroalgae, mussel beds, corals
or other engineering benthic organisms (reviewed by Duarte
et al. 2013). The main mechanisms are uptake of CO
2
(or HCO
3
)
during photosynthesis by micro- and macroalgae, the release of
CO
2
during respiration by all organisms, and the reduction of
total alkalinity and release of CO
2
during shell formation by
calcifiers (e.g. Hurd et al. 2009). The mechanism of release of
CO
2
during calcification is as follows: HCO
3
dissociates to H
þ
and CO
3
2
, whereas the latter is constantly precipitated as
skeletal CaCO
3
,H
þ
associates again with HCO
3
and forms
H
2
CO
3
, which subsequently dissociates into H
2
O and CO
2
(Hurd et al. 2009). Therefore, a subtle equilibrium of feedback
loops is established between photosynthesis, respiration and
calcification activities of autotrophs, heterotrophs and calci-
fiers. These processes are influenced by the physiological status
of the organism and the energy availability, as well as by various
abiotic factors such as temperature, availability of light and
nutrients and water movement. Water movement, furthermore,
transports differently preconditioned water bodies into a partic-
ular habitat, for example by vertical convection, tides, currents
and up- or down-welling. All these factors in turn fluctuate with
time of day, weather conditions, season and even interannually,
leading eventually to temporal or spatial inversion of net carbon
flow into or out of organisms and, in consequence, to biogenic
fluctuations in seawater pH. The amplitude of these fluctuations
can be expected to relate positively with biomass to water
volume ratio and negatively to the water exchange rate, whereas
both frequency and amplitude can vary substantially over spatial
and temporal scales. The biogenic modulation of pH may be
strong enough to entirely mask global trends in ocean acidifica-
tion in coastal habitats (Anthony et al. 2013;Duarte et al. 2013).
Table 1. Number of in situ studies on natural fluctuations of the carbonate system
Data are based on 54 publications (see Table S2). Numbers in parentheses are percentages
Habitat Corals Seagrass Seaweeds and mixed macrophytes Kelps Tidepools
27 (49) 9 (16.5) 6 (11) 4 (7) 9 (16.5)
Sampling type Continuous Discrete
16 (30) 38 (70)
Duration Hour to day Day to week Week to season Season to year Multiple years
13 (24) 11 (20) 7 (13) 17 (32) 5 (9)
Spatial design Single site Multiple sites Transect
27 (51) 15 (28) 11 (20)
DMarine and Freshwater Research M. Wahl et al.
Large-scale spatio-temporal fluctuations: interannual
variation, decadal cycles, climate change
Multiannual variations of carbonate chemistry are the least
monitored. Very few long-term mooring recordings, such as
those for coral reefs (Drupp et al. 2011,2013), have been con-
ducted in benthic habitats. These slow fluctuations can be
influenced by periodic climatic events such as variations of the
North Atlantic Oscillation or the El Nin
˜o–La Nin
˜asuccession.
Multiannual directional shifts in pCO
2
, as occurs in the course of
climate change (Stocker et al. 2013), are not fluctuations in the
strict sense and not subject of this investigation. It should just be
mentioned that such long-term shifts may happen at much faster
rates at small spatial scales (e.g. 0.039 to 0.054 pH unit year
1
in a rock pool) than for the open ocean (0.0019 pH unit year
1
)
(Wootton et al. 2008).
Intermediate-scale spatio-temporal fluctuations: seasons
Seasonality, in particular due to changes in light and tempera-
tures, has a strong impact on seawater chemistry (Frankignoulle
and Diste`che 1984;Delille et al. 2009;Shaw et al. 2012).
The variation of the photoperiod and irradiance influence the
autotrophy v. heterotrophy balance of ecosystems, and tem-
perature influences metabolic activity, both factors with an
increasing effect with higher latitude. Seasonal variation of
pCO
2
with an amplitude of ,500 matm has been reported for
kelp forests (Macrosystis pyrifera) of a subantarctic region
(Kerguelen Islands, French Southern and Antarctic Lands) with
diurnal variations being approximately half as large in winter as
in summer (Delille et al. 2000,2009). In a temperate area,
Frankignoulle and Diste`che (1984) reported seasonal variations
in pCO
2
of ,500 matm in sea grass meadows (Posidonia
oceanica) in the Mediterranean Sea (Corsica, France). In a
Hawaiian coral reef (Oahu), Drupp et al. (2011) found seasonal
variation in pCO
2
with an amplitude of 61 matm with no
noticeable change in the diurnal amplitude among seasons. In a
coral reef off Bermuda, Bates and Leone (2001) found a sea-
sonal variation of ,100 matm.
Seasonality is also often characterised by changes in the
intensity of meteorological events, such as rain and wind
regimes (Manzello 2010;Saderne et al. 2013). Increased rainfall
and river runoff in the wet season dilutes seawater, which
reduces salinity and consequently the total alkalinity and the
buffering capacity of seawater. Under such conditions, we
expect the amplitude of biogenic pH variations to be most
pronounced – if the activity of the organisms is not reduced by
this potential osmotic stress (e.g. Saderne et al. 2013). This
effect has been observed in Panamanian coral reefs during
the wet tropical season (Manzello 2010). Reduced buffering
capacity might also explain the particularly important diurnal
pH variations recorded in brackish environments such as the
Elkhorn estuary (Hofmann et al. 2011) or in the western Baltic
Sea (Saderne et al. 2013). However, in the other direction,
dissolved organic matter load imported by riverine runoff can
increase the buffering capacity by increasing alkalinity
(see Kulin´ski et al. 2014 for explanation). Aside from these
effects on buffering capacity, riverine runoff influences sea-
water temperature, injects nutrients (phosphate, nitrates, and
silicates) and increases turbidity. Altogether, the combination of
these can affect the biology of organisms and the chemical
properties of seawater seasonally or after storm events. This
was, for example, found in some coral reefs, where the carbonate
chemistry changed after heavy storms (Massaro et al. 2012;
Drupp et al. 2013).
Transient upwelling driven by meteorology is another impor-
tant phenomenon affecting carbonate chemistry and its dynam-
ics in costal habitats. During upwelling, the shoaling of the
thermocline brings colder and, often, more saline water masses
of lower pH and pO
2
and higher pCO
2
to shallow coastal
habitats. The interaction of these water masses with the photo-
synthesis of macrophytes can produce extreme changes in the
biogenic variations of the carbonate chemistry. This was dem-
onstrated by Saderne et al. (2013) during seasonal upwelling
into a macroalgal habitat of the western Baltic Sea. During this
event, the bulk seawater pCO
2
increased from atmospheric
equilibrated (426 matm) to 1600 matm, along with an increase
in salinity of ,2 units and a decrease in temperature of ,38C.
The conjunction of the changes in the bulk water abiotic
parameters (pCO
2
, salinity and temperature) resulted in an
increase of the circadian pCO
2
amplitude to 600 matm, and in
a counter-intuitive decrease of the pH variations of 0.35 units.
These effects were not due to enhanced photosynthesis (which
was reduced by 20%), but to a shift in the equilibrium between
CO
2
, HCO
3
2
, and CO
3
2
.
Small-scale spatio-temporal fluctuation: day–night cycles
and day-to-day variation
The most conspicuous pH or pCO
2
fluctuation pattern is
observed during day–night cycles in small coastal habitats or in
plankton patches. At this small spatio-temporal scale, the
amplitudes are large. This is mainly driven by the oscillation of
irradiation over 24 h leading to high net CO
2
uptake through
phototrophic organisms during the day, which increases pH, and
CO
2
release by all organisms at night, which decreases pH
(Koch et al. 2013). The amplitude of these day–night fluctua-
tions may differ among seasons. For example, in a kelp forest,
pCO
2
was reported to vary during a day–night cycle by 160 matm
in winter and 340 matm in summer (Delille et al. 2009).
Similarly, the day–night fluctuation of pCO
2
in a temperate
Fucus spp. stand showed amplitudes between 240 and 400 matm
in late summer, which may reach 2000 matm in autumn (Saderne
et al. 2013). More short-term and sporadic fluctuations in UW
irradiation attributable to weather conditions and plankton
shading can be expected to result in correspondingly changing
frequencies and amplitudes of pH fluctuations in macrophyte
stands. In addition to light, speed and direction of currents can
vary over a day as a consequence of tidal cycles or wind events.
Low current speed reduces the exchange rate and dilution of a
water body, which should permit higher amplitudes of pH var-
iation, whereas high current speeds result in lower amplitudes.
Diurnal fluctuations are strongest in stagnant water, as it occurs,
for example, in tide pools. Here, diurnal variations of pCO
2
exceeding 1000 matm day
1
are commonly found (Truchot and
Duhamel-Jouve 1980;Morris and Taylor 1983;Nguyen and
Byrne 2014). Current velocities decrease with decreasing dis-
tance to the substrate. Zooming in from the scale of the metre to
the micrometre above the substratum, Shashar and colleagues
Fluctuations matter Marine and Freshwater Research E
(1996) differentiate three strata of boundary layers: the benthic,
the momentum and the diffusion boundary layer. The benthic
boundary layer is, at the scale of metres down to centimetres,
created by the friction of water with the substratum relief, algae
and seaweed canopy or reef (Hurd 2000). It causes an
enhancement of the residence time of water in benthic habitats
with, as a consequence, an increase of amplitude of the varia-
tions of carbonate chemistry. A momentum boundary layer is
generated, at the scale of centimetres to millimetres, by the
topography of the substratum, plants or sessile benthic animals,
but also by their pumping, ciliary or tentacle activity, generating
very localised small-scale currents (Shashar et al. 1996). As an
example, Cornwall et al. (2013) describe an increasingly wide
day–night amplitude in pH from ,10 cm above a cobble
assemblage covered with articulate coralline algae to within
several millimetres from the algal surface. At moderate bulk
water velocity of 1.5 cm s
1
the pH difference between day and
night conditions was ,0.05 at 68 mm from the algal surface and
almost 0.3 at 6 mm from the algal surface. The diffusive
boundary layer is a microscale concentration gradient of
molecules forming at the surface of metabolically active tissues
due to water viscosity. In an unpublished study, we investigated
the gradient of pH in the diffusive boundary layer above the
thallus of the brown alga Fucus vesiculosus. We found dark–
light pH fluctuations of more than 1.0 unit within minutes under
stagnant water conditions on the surface of a Fucus blade. Under
increasing bulk water velocities (0, 0.5 and 1.5 cm s
1
) the
boundary layer thickness on a Fucus vesiculosus thallus
decreased from ,700 to 200 mm (no difference between the
velocities 0.5 and 1.5 cm s
1
) and the amplitude of the dark–
light fluctuations of pH decreased within the boundary layer
(Fig. 2). Closest to the substratum, pH fluctuated by 1.5 units
under stagnant conditions and by 0.5 units under moderate water
movement (Fig. 2). Organisms living in such micro- or nano-
habitats dominated by primary producers will thus experience
strong and fast changes of pH, which can be as dramatic as a
30-fold increase or decrease in H
þ
ion concentration within
minutes (Fig. 2). As an example, depending on their body size,
epibionts on the Fucus thallus will experience different fluctu-
ation regimes in different strata of the boundary layer.
Bryozoans or juvenile barnacles (,500 mm high) will be
subjected to weak pH fluctuations (,0.2 units) and that only
under stagnant conditions. Freshly settling larvae of many
invertebrates (typically 200–250 mm high) will experience
strong fluctuations (,1 unit) under stagnant conditions and no
fluctuations under flow conditions. Diatoms (1–50 mm) have
to tolerate strong fluctuations (1.3 units under stagnant and
0.3 units under flowing conditions). Finally, bacteria (0.5–5 mm
high) are subject to extreme fluctuations (1.5 units) under
stagnant and moderate (0.4 units) fluctuations under flowing
conditions. It should be noted that these values were measured
5 min after a switch between dark and light. This means that
under stagnant conditions, but not under flowing conditions, the
thickness of the boundary layer is likely to increase over time.
Temperature, furthermore, affects the viscosity of water and the
solubility of gases, which thereby influences the seawater
chemistry. In the context of the diffusive boundary layer, for
example, this would mean that higher temperature leads to lower
viscosity, which leads to decrease in the thickness of the
boundary in all flow regimes other than stagnant. Furthermore,
diffusion rates increase, as well as metabolic rates, leading
overall to a steeper pH gradient within a narrower boundary
layer. This, however, still needs to be tested.
The strong fluctuations in pH described may represent an
alternation of phases of stress and phases of release from stress.
This biogenic instability of the immediate environment may be
beneficial or detrimental to physiological performance. Whether
it has the potential to locally modulate the presumed stress
exerted by the steady global rise in pCO
2
(OA) is largely
unknown.
Relationship between spatial scales and effect size
(amplitude)
Given the increasing inertia of larger water bodies, we would
expect the amplitude of biogenic fluctuations to inversely relate
to spatial scale. The amplitude of biogenic carbonate chemistry
fluctuations in coastal habitats such as coral reefs is, indeed,
inversely related to the water column size and water exchange
rate (Bates and Leone 2001). For example, Ohde and van
Woesik (1999), in a transect study across an atoll near Okinawa
Island (Japan) found a maximum diurnal amplitude of 927 mtm
in the most shallow area (reef flat) in the centre of the atoll. Tide
pools, with their reduced water column height and exchange
rate, are the habitats where biological activity creates particu-
larly strong variations of carbonate chemistry with amplitude of
fluctuations increasing with height on the shore (Daniel and
Boyden 1975). The largest amplitudes by far in biogenic pH
fluctuations are recorded at very small scales (i.e. in benthic
boundary layers at the submillimetre scale) (Spilling et al. 2010;
Hurd and Pilditch 2011; and example given above). The inverse
relationship between spatial scale, frequency and amplitude of
9.2
Spirorbis, bryozoans, juvenile barnacles
Diverse larve
Diatoms
Bacterial biofilm
0, Light
0, Dark
0.5, Light
0.5, Dark
1.5, Dark
1.5, Light
Velocity (cm s1), light/dark
9.0
8.8
8.6
8.4
8.2
pH
8.0
7.8
Distance to Fucus surface (μm)
7.6
1200
1000
800
600
400
200
0
Fig. 2. Gradients of pH with a diffusive boundary layer on a thallus of the
brown macroalga Fucus vesiculosus. The diffusive boundary layer was
allowed to build up under light and dark conditions at various bulk velocities
within 5 min before measuring. The thallus surface is located at distance ¼0,
i.e. at the right border of the graph. The vertical lines depict the outer limit of
the strata above the macroalgal thallus surface (‘0 cm’) in which different
epibionts typically live.
FMarine and Freshwater Research M. Wahl et al.
pH fluctuation is presented in Fig. 3. Because smaller water
bodies have less inertia, scales and rates of change are not
independent. Indeed, the rate of pH change relates negatively to
the spatial scale considered (Fig. 4). Slowest changes happen in
the open ocean, fast change is observed in coastal habitats, and
the most dramatic fluctuations in pH were described from the
subcentimetre or even submillimetre ‘nanohabitats’ in the
boundary layers on algal surfaces (Spilling et al. 2010;Cornwall
et al. 2013). In the open ocean, diurnal and seasonal fluctuations
at much smaller amplitude occur in plankton patches (Schulz
and Riebesell 2013), which, in this context, could be considered
floating microhabitats.
Biological effects of fluctuations
Our widespread ignorance regarding the biological relevance
of pH or pCO
2
fluctuations stems from the methodological
research limitations mentioned earlier. The bulk of our inves-
tigations in the laboratory use constant treatment levels. In field
experiments fluctuations are tolerated but their importance
relative to non-fluctuating conditions is rarely assessed. At this
point it is important to note that constant and fluctuating
conditions are not two discrete conditions. Rather, ‘constancy’
represents a point on a continuum where frequency of a vari-
able’s fluctuations is long relative to an organism’s biological
rhythms or amplitude is close to zero.
Possible effects of fluctuations are numerous. Obviously, in a
fluctuating regime the distance to the optimal value of an
environmental variable (relative to the requirements of a target
species) continuously changes. As a consequence, the relative
performance of a species will increase and decrease during such
fluctuations. The physiological response may show some lag
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
6
4
2
0
Space (log(m))
Time (log(d))
2
4
6
80
1
2
3
4
5
1
ΔpH
Fig. 3. Relationship between the typical amplitude (‘delta pH’) and
frequency (‘Time’) of pH fluctuations and the estimated size of the system
considered (‘Space’). The data were extracted from selected papers report-
ing in situ fluctuations (Morris and Taylor 1983;Middelboe and Hansen
2007;Semesi et al. 2009;Spilling et al. 2010;Thomsen et al. 2010;Hofmann
et al. 2011;Hurd and Pilditch 2011;Frieder et al. 2012;Gray et al. 2012;
Price et al. 2012;Cornwall et al. 2013;Johnson et al. 2013;Melzner et al.
2013;Saderne et al. 2013;Saderne and Wahl 2013;Stocker et al. 2013;
Comeau et al. 2014;Hendriks et al. 2014) and from the authors’ own
measurements presented in this paper. It should be noted that amplitudes,
temporal and spatial scales were estimated from graphic and text informa-
tion in these articles and only represent orders of magnitudes.
0.3
0.25
0.2
0.15
y 0.0167x 0.0616
R2 0.5895
P 0.017
0.1
0.05
0
0.05
6420
Space (m, lo
g
)
Delta pH (h)
2468
0.1
Fig. 4. Rate of change in pH at different spatial scales. The smaller the scale considered, the steeper is the slope of
pH change per unit time, i.e. the more rapid and stronger is the pH change. Linear regression results are shown in
upper right corner. Data sources as in Fig. 2.
Fluctuations matter Marine and Freshwater Research G
that reflects the physiological buffer (e.g. internal pH control) of
an organism. When a fluctuating variable periodically trans-
gresses physiological thresholds, phases of stress may alternate
with phases of relaxation from stress. Fluctuating regimes may
select for ‘physiological generalists’ that can cope with a wide
range of environmental variables. Although many organisms
show a remarkable amount of phenotypic plasticity in their
response to fluctuating environmental variables (Hadfield and
Strathmann 1996), this plasticity may come at some cost
(Waldbusser and Salisbury 2014). Plasticity may be too slow
when environmental parameters change fast, which may occur
when fluctuations are characterised by high amplitude and high
frequency. When organisms cannot acclimatise to fast transient
change their tolerance range should be wide, or they could
switch off sensitive processes. The responses to warming are
stronger and more negative when the expected fluctuations are
incorporated in the warming treatment (e.g. Vasseur et al. 2014).
Some of this increased impact may be attributable to Jensen’s
inequality (Fig. 5) predicting that symmetrical fluctuations of a
variable often produce asymmetrical responses of an organism
when the response curve is curvilinear. Another stressful aspect
of fluctuating regimes is that extreme events are more likely.
The transient transgressions of tolerance thresholds followed by
relaxation periods may not only selectively favour high pheno-
typic plasticity (see above) but may also select for more robust
genotypes (Pansch et al. 2014).
Only a handful of studies have investigated whether pH
(actual or future) impacts organisms differently in constant v.
fluctuating pH regimes of the same average pH (or pCO
2
).
Calcifying macroalgae seem to suffer from pH fluctuations both
under low and under elevated pCO
2
levels (Cornwall et al.
2013). However, thick boundary layers may allow photosyn-
thetic calcifiers to create a beneficial nanohabitat at their thallus
surface, which permits calcification even when the bulk water is
acidified to critical levels (Cornwall et al. 2014). These authors
showed that strong water turbulence leading to thinner boundary
layers may weaken this protective function. Pulses of low pH
(simulating upwelling) reduce the performance of snails (Kim
et al. 2013), but this effect was not compared with a constant
regime of the same mean pH. A fluctuating pCO
2
regime
benefits the growth of coral recruits, possibly because they more
easily sequester DIC when pCO
2
is high (Dufault et al. 2012).
pH fluctuations may buffer the negative effect of ocean acidifi-
cation with regard to the calcification in corals (Comeau et al.
2014). Larvae of two mussel species suffered less from ocean
acidification when the regime was fluctuating (Frieder et al.
2014). Similarly, Schneider, Sawall, Saderne, Hiebenthal,
Mu
¨ller and Wahl (unpubl. data) found that biogenic fluctuations
of pH mitigated ocean acidification effects on mussel calcifica-
tion because the mussels shifted their calcification activities to
phases of relaxation from acidification stress (i.e. daytime).
Some fluctuation effects of other environmental factors have
been described. Relative to constant conditions of the same
mean, pulsed hyposalinity is more stressful to the plant Halo-
phila (Griffin and Durako 2012), light pulses mitigate low light
stress for phytoplankton (Helbling et al. 2013), and fluctuating
temperature around a warm mean stress corals more heavily
than a constant temperature regime (Putnam and Edmunds
2011) but the constant regime was slightly cooler!). In a
theoretical study, Vasseur and coworkers (2014) propose that
fluctuating, relative to constant, temperature regimes favour
species living at their colder distributional edge but not species
at their warmer distributional edge, and that global warming
effects may be more drastic than thought if one incorporates
fluctuations into the picture. Empirical evidence for these
hypotheses is still wanting.
Conclusions
In coastal habitats environmental conditions fluctuate and in all
of the few extant investigations the target species were affected
differently in the presence of fluctuations as compared with
constant conditions. Disregarding natural fluctuations in our
research will, together with the other limitations of our usual
experimental approaches (Fig. 1), substantially weaken the
relevance of our insights. We undoubtedly have assembled an
impressive amount of information about acute ocean acidifica-
tion impacts. In order to collate these into a coherent and real-
istic picture we need to: (1) feed these pieces of knowledge into
descriptive models and (2) run more holistic multifactorial or
multivariate investigations, including driver fluctuations at
natural scales of frequency and amplitude. Wherever possible,
such investigations should be long enough to allow for accli-
mation or adaptation of the target species, their associated
microbiomes and their interactions with other species in the
community. One promising approach is to run investigations
on ocean acidification (or many other ecological issues) in
mesocosm systems, as pleaded for by Stewart et al. (2013) and
Gattuso et al. (2014). For example, for over a year we have run
an experiment on global change effects under near-natural
conditions in a series of large mesocosms (‘Kiel Benthocosms’:
Fig. 6). The community is a bladder wrack assemblage,
including macroalgae, their micro- and macroepibionts, meso-
grazers, starfish, mussels, fish, at their natural proportions
7.5
Relative performance
7.6 7.7
fmin fmax
7.8
C
7.9
mc < mf
8.0 8.1 8.2 8.3 8.4 8.5 8.6 pH
mf
mc
Fig. 5. Jensen’s inequality illustrating the expectation that constant (c) and
fluctuating (f) regimes of the same mean may produce different responses
when the relation between an environmental variable and an organism’s
performance is non-linear. Thus, symmetrical fluctuations (between f
min
and
f
max
) around the mean (c) of a driver (pH in this example) may lead to an
asymmetrial response distribution (m
f
) around the mean response (m
c
)toa
constant pH and, thus, to a reduced performance (m
f
,m
c
) of the target
species.
HMarine and Freshwater Research M. Wahl et al.
transplanted into the benthocosms. Drivers (temperature, acid-
ification, nutrients, hypoxia) are applied as delta treatments,
i.e. as add-ons onto ambient conditions. The values of the delta
treatments correspond to the prediction for the shift of means
until 2100 – as far as such predictions exist at the regional scale.
Fluctuations, as driven by the metabolism of the community in
the benthocosms and by the biology and hydrography of the Kiel
Fjord (Germany) water, which feeds the benthocosms in a run-
through mode, are freely admitted. The experimental durations
cover all seasons. The response is registered at the species- and
the community-level, thus integrating the responses at the level
of different ontogenetic stages, different species and their
shifting interactions. By this approach we expect to improve our
capacity to understand how global change affects species in their
natural environments, the communities composed of these
species, and the ecosystem services they provide. Although
these benthocosms are conceptually quite advanced, they still
have their limitations. Thus, certain organisms, e.g. pteropods,
fishes and kelp, can be maintained in a good physiological status
for only 3–6 months, for as yet unknown reasons; and the ‘wall
effects’, i.e. enhanced growth of microbiota and filamentous
algae, must be controlled or accounted for. Laboratory experi-
ments in microcosms will always remain important for eluci-
dating single and isolated effects, and field experiments could
serve to verify the benthocosm results. A complementary use of
all three approaches, with an emphasis on innovative mesocosm
systems allowing for multiple-factor treatments, multiple-
species responses and the incorporation of natural fluctuations,
will be necessary to achieve a realistic appreciation of future
OA impacts in coastal habitats.
10.00
high pCO2
low pCO2
low pCO2
high pCO2
9.75
9.50
9.25
9.00
8.75
8.50
8.25
8.00
7.75
pH
7.50
7.25
7.00
10.00
9.75
9.50
9.25
9.00
8.75
8.50
8.25
8.00
7.75
7.50
7.25
7.00
Experimental da
y
s between Jul
y
2013 and September 2013
Δ5C
Δ0C
Fig. 6. Kiel Benthocosms: Fluctuating Delta pH treatment at two temperature regimes (ambient is
D08, warm or ‘future’ is Dþ58C) and two acidification regimes (low pCO
2
or ‘ambient’ at ,400 matm
(light grey lower curve); high pCO
2
or ‘future’ at 1100 matm (dark grey upper curve) in the hooded
headspaces of the benthocosms). The fast oscillations (amplitude in the hi pCO
2
regime indicated by
the vertical black line) are the biogenic signal attributable to the circadian shifts in community
photosynthesis and respiration of the benthocosm communities. The black dotted lines indicate the
seasonal decrease in the Kiel Fjord pH. The double-headed arrows indicate the effect of the head-space
pCO
2
treatment on the pH in the benthocosms. Although the same treatment strength in pCO
2
enhancement of the headspace air is applied, this translates to a smaller difference in pH at the
lower temperature. The biogenic day–night fluctuations in pH also feature a smaller amplitude in the
cooler regime.
Fluctuations matter Marine and Freshwater Research I
Without such upscaling of our experimental approach to a
more complex and more ‘real’ level we are in the situation
described in a German joke:
A man searches for his lost keys under a street light at night.
He is soon joined in his efforts by a helpful passer-by. After
30 min of unsuccessful search the helper asks whether the
unfortunate man was really sure that he lost his keys at this
very place. The man answered: ‘No, no, I lost them around
the street corner, but there is no street light there and it is so
much more convenient to search here where we can see’.
Acknowledgements
We greatly appreciate the valuable comments of Christopher Cornwall
(University of Perth, WA, Australia) on an earlier version of this article. The
comments and advice of two anonymous reviewers and the editor Steve
Hawkins have very substantially improved the substance and style of this
article. We gratefully acknowledge their efforts.
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www.publish.csiro.au/journals/mfr
LMarine and Freshwater Research M. Wahl et al.
... The intensity of biological activity and the temporal and spatial scale of effects are mainly dependent on the size, biomass, morphology and metabolic rate of organisms and communities in relation to the water volume surrounding them ( Figure 2; Lesser et al., 1994;Lowe & Falter, 2015;Stewart & Carpenter, 2003). Biologically driven fluctuations ( Figure 2) occur on spatial scales ranging from small (µm to cm) to large (m to hundreds of m), and temporal scales of variation are generally faster at small (seconds) compared with large (hours to days) spatial scales (Boyd et al., 2016;Kapsenberg & Cyronak, 2019;Wahl et al., 2016). ...
... An increasing number of publications emphasizes the importance of incorporating fluctuating regimes into experiments testing the responses of organisms and communities to ocean global change, in particular to ocean warming, acidification and deoxygenation (Boyd et al., 2016;Britton et al., 2019;Rivest et al., 2017;Wahl et al., 2016). Furthermore, at this stage, we do not understand how alterations in the metabolism of engineer species due to ocean global change will feedback to shape their surrounding water chemistry, in relation to hydrodynamics (e.g. ...
... Temperature also changes the transport of dissolved materials across the DBL as it affects fluid viscosity, gas solubility and the diffusion coefficient (Denny, 2015;Vogel, 1999). Increasing temperature usually decreases the DBL thickness and increases diffusion rates, leading to a steeper concentration gradient in the DBL (Wahl et al., 2016). The effects of temperature on the physical properties of the DBL are superimposed to direct effects on organism's metabolism (Brown et al., 2004) and result in specific chemical conditions surrounding the organism. ...
Article
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Marine coastal zones are highly productive, and dominated by engineer species (e.g. macrophytes, molluscs, corals) that modify the chemistry of their surrounding seawater via their metabolism, causing substantial fluctuations in oxygen, dissolved inorganic carbon, pH, and nutrients. The magnitude of these biologically‐driven chemical fluctuations is regulated by hydrodynamics, can exceed values predicted for the future open ocean, and creates chemical patchiness in subtidal areas at various spatial (µm to meters) and temporal (minutes to months) scales. While the role of hydrodynamics is well explored for planktonic communities, its influence as a crucial driver of benthic organism‐ and community functioning is poorly addressed, particularly in the context of ocean global change. Hydrodynamics can directly modulate organismal physiological activity or indirectly influence an organism’s performance by modifying its habitat. This review addresses recent developments in (i) the influence of hydrodynamics on the biological activity of engineer species, (ii) the description of chemical habitats resulting from the interaction between hydrodynamics and biological activity, (iii) the role of these chemical habitat as refugia against ocean acidification and deoxygenation, and (iv) how species living in such chemical habitats may respond to ocean global change. Recommendations are provided to integrate the effect of hydrodynamics and environmental fluctuations in future research, to better predict the responses of coastal benthic ecosystems to ongoing ocean global change.
... Average sea surface pH conditions may not always be representative, especially when looking at highly fluctuating environments such as coastal, estuarine, and tidal realms (Wahl et al. 2016). The correct identification of the naturally occurring pH range is therefore crucial when studying the impact of pH on chemical communication at the molecular chemical level. ...
... A comparable effect was also found for boundary layers around complex macroalgae assemblages (Cornwall et al. 2013). In stagnant water conditions, the pH in the vicinity of Fucus vesiculosus was measured to range from pH 7.6 in the dark to pH 9.2 in the light (Wahl et al. 2016). Wahl and co-workers further established that while for bacterial biofilms and diatoms on the immediate surface of F. vesiculosus pH fluctuations can be large (exceeding ±1.0 pH units) and happen at a very short time scale of minutes, other organisms living in the vicinity of the macroalgae experience less strong fluctuations at longer time scales and the scale of fluctuation depends on the flow velocity of the surrounding water (Wahl et al. 2016). ...
... In stagnant water conditions, the pH in the vicinity of Fucus vesiculosus was measured to range from pH 7.6 in the dark to pH 9.2 in the light (Wahl et al. 2016). Wahl and co-workers further established that while for bacterial biofilms and diatoms on the immediate surface of F. vesiculosus pH fluctuations can be large (exceeding ±1.0 pH units) and happen at a very short time scale of minutes, other organisms living in the vicinity of the macroalgae experience less strong fluctuations at longer time scales and the scale of fluctuation depends on the flow velocity of the surrounding water (Wahl et al. 2016). ...
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Marine macroalgae are important ecosystem engineers in marine coastal habitats. Macroalgae can be negatively impacted through excessive colonization by harmful bacteria, fungi, microalgae, and macro-colonisers and thus employ a range of chemical compounds to minimize such colonization. Recent research suggests that environmental pH conditions potentially impact the functionality of such chemical compounds. Here we predict if and how naturally fluctuating pH conditions and future conditions caused by ocean acidification will affect macroalgal (antifouling) compounds and thereby potentially alter the chemical defence mediated by these compounds. We defined the relevant ecological pH range, analysed and scored the pH-sensitivity of compounds with antifouling functions based on their modelled chemical properties before assessing their distribution across the phylogenetic macroalgal groups, and the proportion of sensitive compounds for each investigated function. For some key compounds, we also predicted in detail how the associated ecological function may develop across the pH range. The majority of compounds were unaffected by pH, but compounds containing phenolic and amine groups were found to be particularly sensitive to pH. Future pH changes due to predicted average open ocean acidification pH were found to have little effect. Compounds from Rhodophyta were mainly pH-stable. However, key algal species amongst Phaeophyceae and Chlorophyta were found to rely on highly pH-sensitive compounds for their chemical defence against harmful bacteria, microalgae, fungi, and biofouling by macro-organisms. All quorum sensing disruptive compounds were found the be unaffected by pH, but the other ecological functions were all conveyed in part by pH-sensitive compounds. For some ecological keystone species, all of their compounds mediating defence functions were found to be pH-sensitive based on our calculations, which may not only affect the health and fitness of the host alga resulting in host breakdown but also alter the associated ecological interactions of the macroalgal holobiont with micro and macrocolonisers, eventually causing ecosystem restructuring and the functions (e.g. habitat provision) provided by macroalgal hosts. Our study investigates a question of fundamental importance because environments with fluctuating or changing pH are common and apply not only to coastal marine habitats and estuaries but also to freshwater environments or terrestrial systems that are subject to acid rain. Hence, whilst warranting experimental validation, this investigation with macroalgae as model organisms can serve as a basis for future investigations in other aquatic or even terrestrial systems.
... The biological consequences of the patterns of environmental variation just described remain understudied (Dowd et al. 2015, Wahl et al. 2015, Boyd et al. 2016, Morash et al. 2018. Ideally, experimental designs targeting the physiological consequences of variation should be informed by detailed knowledge of those patterns. ...
... In the absence of suitable shortcuts, we advocate for a concerted empirical effort to quantify the physiological consequences of environmental variation, particularly in scenarios where organisms experience simultaneous fluctuations of several variables during their lifetime (Wahl et al. 2015). In the interest of space, we do not review the effects of univariate environmental shifts on specific physiological traits . ...
... Rather, in many instances it may be sufficient, at least at the outset, to treat physiological mechanisms as a black box, measuring simple, integrative, and ecologically relevant response variables such as growth rate or reproductive output. Even so, the complexity of individual environmental experiences and the nuances of multifactorial environments will demand far more complex experimental designs than are currently the norm (Dowd et al. 2015, Wahl et al. 2015, Koussoroplis et al. 2017. Once patterns are described at this integrative level, it is incumbent upon physiologists to fill in the mechanistic details that produce outputs from the black box, and specifically to better characterize response times for physiological processes such as photoacclimation, the turnover of transient carbon (Halsey & Jones 2015) in phytoplankton, membrane restructuring, and TMAO accumulation. ...
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To better understand life in the sea, marine scientists must first quantify how individual organisms experience their environment, and then describe how organismal performance depends on that experience. In this review, we first explore marine environmental variation from the perspective of pelagic organisms, the most abundant life forms in the ocean. Generation time, the ability to move relative to the surrounding water (even slowly), and the presence of environmental gradients at all spatial scales play dominant roles in determining the variation experienced by individuals, but this variation remains difficult to quantify. We then use this insight to critically examine current understanding of the environmental physiology of pelagic marine organisms. Physiologists have begun to grapple with the complexity presented by environmental variation, and promising frameworks exist for predicting and/or interpreting the consequences for physiological performance. However, new technology needs to be developed and much difficult empirical work remains, especially in quantifying response times to environmental variation and the interactions among multiple covarying factors. We call on the field of global-change biology to undertake these important challenges. Expected final online publication date for the Annual Review of Marine Science, Volume 14 is January 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.
... Lowder et al. 10.3389/fmars.2022.909017 that live in dynamic pH environments (Wahl et al., 2015). Here, we tested the hypotheses that reduced stable pH conditions would affect the mineralization and mechanical properties of exoskeletal defense structures, that the effects would differ in magnitude across structures, and that fluctuating reduced pH conditions would mitigate these effects. ...
Article
Full-text available
Spiny lobsters rely on multiple biomineralized exoskeletal predator defenses that may be sensitive to ocean acidification (OA). Compromised mechanical integrity of these defensive structures may tilt predator-prey outcomes, leading to increased mortality in the lobsters’ environment. Here, we tested the effects of OA-like conditions on the mechanical integrity of selected exoskeletal defenses of juvenile California spiny lobster, Panulirus interruptus . Young spiny lobsters reside in kelp forests with dynamic carbonate chemistry due to local metabolism and photosynthesis as well as seasonal upwelling, yielding daily and seasonal fluctuations in pH. Lobsters were exposed to a series of stable and diurnally fluctuating reduced pH conditions for three months (ambient pH/stable, 7.97; reduced pH/stable 7.67; reduced pH with low fluctuations, 7.67 ± 0.05; reduced pH with high fluctuations, 7.67 ± 0.10), after which we examined the intermolt composition (Ca and Mg content), ultrastructure (cuticle and layer thickness), and mechanical properties (hardness and stiffness) of selected exoskeletal predator defenses. Cuticle ultrastructure was consistently robust to pH conditions, while mineralization and mechanical properties were variable. Notably, the carapace was less mineralized under both reduced pH treatments with fluctuations, but with no effect on material properties, and the rostral horn had lower hardness in reduced/high fluctuating conditions without a corresponding difference in mineralization. Antennal flexural stiffness was lower in reduced, stable pH conditions compared to the reduced pH treatment with high fluctuations and not correlated with changes in cuticle structure or mineralization. These results demonstrate a complex relationship between mineralization and mechanical properties of the exoskeleton under changing ocean chemistry, and that fluctuating reduced pH conditions can induce responses not observed under the stable reduced pH conditions often used in OA research. Furthermore, this study shows that some juvenile California spiny lobster exoskeletal defenses are responsive to changes in ocean carbonate chemistry, even during the intermolt period, in ways that can potentially increase susceptibility to predation among this critical life stage.
... However, studies investigating the effect of environmental factors other than temperature and pH as well as experiments with multifactorial design with CWC are still scarce (except for 15,17,18 ). Similarly, most studies used constant conditions and neglected naturally occurring strong and short-term fluctuations relevant to individual organisms 67,68 . However, this may hamper our understanding of the performance of organisms, contribute to observed response heterogeneity and limit our predictions for the future of the ocean 69,70 . ...
Article
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The stratified Chilean Comau Fjord sustains a dense population of the cold-water coral (CWC) Desmophyllum dianthus in aragonite supersaturated shallow and aragonite undersaturated deep water. This provides a rare opportunity to evaluate CWC fitness trade-offs in response to physico-chemical drivers and their variability. Here, we combined year-long reciprocal transplantation experiments along natural oceanographic gradients with an in situ assessment of CWC fitness. Following transplantation, corals acclimated fast to the novel environment with no discernible difference between native and novel (i.e. cross-transplanted) corals, demonstrating high phenotypic plasticity. Surprisingly, corals exposed to lowest aragonite saturation (Ωarag < 1) and temperature (T < 12.0 °C), but stable environmental conditions, at the deep station grew fastest and expressed the fittest phenotype. We found an inverse relationship between CWC fitness and environmental variability and propose to consider the high frequency fluctuations of abiotic and biotic factors to better predict the future of CWCs in a changing ocean. The cold-water coral Desmophyllum dianthus benefits from stable environmental conditions in deep waters of Comau Fjord (Chile) and is able to acclimatise quickly to new environmental conditions after transplantation.
... The experiment lasted for 12 months Hexaplex trunculus was selected as the model species for this experiment since it is a common and widely distributed sublittoral gastropod, which is well-adjusted to varying physical environmental conditions characterising transitional coastal systems (e.g. rock pools, lagoons) where temperature and pH fluctuations occur naturally (Wahl et al. 2016). Hexaplex trunculus has been widely used as a Tributyltin (TBT) pollution bioindicator and is also an edible species with important economic value in several countries (Abidli et al. 2009). ...
Article
Full-text available
Digitisation of specimens (e.g. zoological, botanical) can provide access to advanced morphological and anatomical information and promote new research opportunities. The micro-CT technology may support the development of "virtual museums" or "virtual laboratories" where digital 3D imaging data are shared widely and freely. There is currently a lack of universal standards concerning the publication and curation of micro-CT datasets. The aim of the current project was to create a virtual gallery with micro-CT scans of individuals of the marine gastropod Hexaplex trunculus , which were maintained under a combination of increased temperature and low pH conditions, thus simulating future climate change scenarios. The 3D volume-rendering models created were used to visualise the structure properties of the gastropods shells. Finally, the 3D analysis performed on the micro-CT scans was used to investigate potential changes in the shell properties of the gastropods. The derived micro-CT 3D images were annotated with detailed metadata and can be interactively displayed and manipulated using online tools through the micro-CT virtual laboratory, which was developed under the LifeWatchGreece Research Infrastructure for the dissemination of virtual image galleries collection supporting the principles of FAIR data.
... Furthermore, tolerances to multiple stressors within individual species might differ among populations, further challenging predictive efforts. That is, individual species can display high levels of plasticity in response to exposure to stressful conditions (Hufbauer et al., 2012;Wahl et al., 2016), with long-term sub-lethal exposures potentially building resilience (Vasseur et al., 2014). Accordingly, multiple stressors may manifest differently among populations, depending on the prevailing conditions of the environment. ...
Article
Full-text available
Aquatic ecosystems are threatened by multiple stressors which might interact in non-additive ways. Two key stressors in marine systems that are likely to be mediated by ongoing climate change are temperature and salinity. Here, we experimentally examine the influence of warming and desalination on mortality rates of a key herbivorous sea urchin, Paracentrotus lividus, between two populations over time. Mortality rates were significantly increased by warming and desalination as individual stressors, with up to total mortality exhibited at the highest water temperature (27 °C) and lowest salinity (25). However, these stressors interacted, with desalination significantly exacerbating mortality rates at the highest temperature, but not under lower thermal regimes (21 °C and 25 °C). Mortality rates were relatively consistent between two sea urchin populations. Overall, temperature and salinity stressors can significantly interact to mediate mortality rates of key aquatic species, in ways that cannot be predicted by considering individual stressors in isolation. Future research should incorporate multiple environmental contexts to better understand and predict species responses to changing climate.
... This phenomenon is likely to be exacerbated by OA particularly under slow flows, such as those presented here. Moreover, fluctuations in pH are likely to be higher, which has varied effects on calcifying species (e.g., Eriander et al., 2016;Wahl et al., 2016). ...
Article
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Macroalgae, with their various morphologies, are ubiquitous throughout the world’s oceans and provide ecosystem services to a multitude of organisms. Water motion is a fundamental physical parameter controlling the mass transfer of dissolved carbon and nutrients to and from the macroalgal surface, but measurements of flow speed and turbulence within and above macroalgal canopies are lacking. This information is becoming increasingly important as macroalgal canopies may act as refugia for calcifying organisms from ocean acidification (OA); and the extent to which they act as refugia is driven by water motion. Here we report on a field campaign to assess the flow speed and turbulence within and above natural macroalgal canopies at two depths (3 and 6 m) and two sites (Ninepin Point and Tinderbox) in Tasmania, Australia in relation to the canopy height and % cover of functional forms. Filamentous groups made up the greatest proportion (75%) at both sites and depth while foliose groups were more prevalent at 3 than at 6 m. Irrespective of background flows, depth or site, flow speeds within the canopies were <0.03 m s–1 – a ∼90% reduction in flow speeds compared to above the canopy. Turbulent kinetic energy (TKE) within the canopies was up to two orders of magnitude lower (<0.008 m2 s–2) than above the canopies, with higher levels of TKE within the canopy at 3 compared to 6 m. The significant damping effect of flow and turbulence by macroalgae highlights the potential of these ecosystems to provide a refugia for vulnerable calcifying species to OA.
... However, most laboratory experiments on shallow water marine organisms have been conducted using stable levels of elevated pCO 2 consistent with open ocean projections, instead of those ecological relevant to the study organism (Gunderson, Armstrong, & Stillman, 2016;McElhany & Shallin Busch, 2013;Wahl, Saderne, & Sawall, 2016). Empirical studies testing populations across their geographic range, have shown that sensitivity to future stable ocean acidification conditions is linked to the local pCO 2 conditions experienced (Hoshijima & Hofmann, 2019;Kelly & Hofmann, 2013;Pespeni et al., 2013;Thomsen et al., 2017;Vargas et al., 2017). ...
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Environmental pCO2 variation can modify the responses of marine organisms to ocean acidification, yet the underlying mechanisms for this effect remain unclear. On coral reefs, environmental pCO2 fluctuates on a regular day-night cycle. Effects of future ocean acidification on coral reef fishes might therefore depend on their response to this diel cycle of pCO2. To evaluate the effects on the brain molecular response, we exposed two common reef fishes (Acanthochromis polyacanthus and Amphiprion percula) to two projected future pCO2 levels (750 and 1,000 µatm) under both stable and diel fluctuating conditions. We found a common signature to stable elevated pCO2 for both species, which included the downregulation of immediate early genes, indicating lower brain activity. The transcriptional program was more strongly affected by higher average pCO2 in a stable treatment than for fluctuating treatments, however, the largest difference in molecular response was between stable and fluctuating pCO2 treatments. This indicates that a response to a change in environmental pCO2 conditions is different for organisms living in a fluctuating than in stable environments. This differential regulation was related to steroid hormones and circadian rhythm (CR). Both species exhibited a marked difference in the expression of CR genes among pCO2 treatments, possibly accommodating a more flexible adaptive approach in the response to environmental changes. Our results suggest that environmental pCO2 fluctuations might enable reef fishes to phase shift their clocks and anticipate pCO2 changes, thereby avoiding impairments and more successfully adjust to ocean acidification conditions.
... However, testing at the community level often lacks replication and control and is likely to be environmentally unacceptable due to the large quantities of toxic substances used (Moermond et al. 2015). However, isolating part of a natural community, using controlled ecosystem enclosures and other such systems, allows replication of treatment levels and, adds statistical control, and limits the amount of toxicant needed (Wahl et al. 2015). ...
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