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Article

Troubles Never Come Alone: Outcome of Multiple Pressures on a Temperate Rocky Reef

1
Seascape Ecology Laboratory, DiSTAV (Department of Earth, Environment and Life Sciences), University of Genoa, Corso Europa, 26, 16132 Genova, Italy
2
Benthic Ecology Laboratory, DiSTAV (Department of Earth, Environment and Life Sciences), University of Genoa, Viale Benedetto XV, 16132 Genova, Italy
3
Department of Integrative Marine Ecology (EMI), Stazione Zoologica Anton Dohrn–National Institute of Marine Biology, Ecology and Biotechnology, Genoa Marine Centre (GMC), Villa del Principe, Piazza del Principe 4, 16126 Genoa, Italy
4
NBFC, National Biodiversity Future Center, 90133 Palermo, Italy
*
Author to whom correspondence should be addressed.
Water 2023, 15(4), 825; https://doi.org/10.3390/w15040825
Submission received: 27 January 2023 / Revised: 14 February 2023 / Accepted: 16 February 2023 / Published: 20 February 2023
(This article belongs to the Special Issue Anthropogenic Impacts on Benthic Marine Ecosystems)

Abstract

:
Climate change is affecting rocky reef ecosystems in a multitude of ways at global scale. During summer 2018, the rocky reef communities of Portofino Marine Protected Area (MPA) (NW Mediterranean) were affected by thermal anomalies, a mucilaginous event, and the seasonal expansion of Caulerpa cylindracea. Moreover, a severe storm occurred on 29 October. The effects of these pressures on the rocky reef communities were analysed at different depths (10 m, 20 m, 30 m, and 40 m) and at three times (June, October, December) to evaluate change at short temporal scale. Portofino MPA’s communities have significantly changed: thermal anomalies mostly affected the biota living above the summer thermocline (ca 20 m depth); mucilaginoius aggregates first impacted the communities in shallow waters and only later those in deep waters, where they typically fall in late summer; the greatest impact by Caulerpa cylindracea was detected at 20 m depth; the storm directly impacted communities in shallow and intermediate waters by uprooting algal species, while it had indirect effects at greater depths through sediment redistribution. Disentangling the effects of multiple pressures on coastal ecosystems is one of the most pressing goals in marine ecology and biodiversity conservation. This study represents an attempt in this direction as applied to the short-term dynamics of rocky reef communities under a climate change scenario.

1. Introduction

Rocky reef ecosystems are exposed to several co-occurring impacts [1] due to many different global and local pressures (e.g., pollution, overfishing, coastal works, spread of alien species, ocean acidification, and climate change), which threaten their state of health [2]. Any abiotic or biotic agent exceeding its range of normal variation and capable of altering the ecosystem’s state is frequently defined as a stressor [3]. However, a distinction between stress and disturbance is necessary, as they have different ecological meanings: the former refers to a condition that restricts production, while the lattercauses partial or total destruction of biomass [4]. In the context of ecological dynamics, they are also distinguished based on their frequency [5], intensity, duration, and effects ([6], and references therein). For this reason, the new term ‘affectors’ has been proposed [6,7] to embrace both stressors (i.e., environmental factors that reduce the productivity within the ecosystem because of the energetic cost of adaptation) and disturbances (i.e., unpredictable, episodic events that disrupt the state of the ecosystem, causing abrupt mortality and a decrease in biomass).
When subjected to a single affector, ecosystems are generally able to recover, but under the pressure of multiple affectors they may undergo irreversible change [8]. The sequential and interactive consequences of multiple affectors alter the mechanisms that regulate community composition, leading to phase shifts [9]. To date, most ecological studies have investigated the responses of ecosystems to one single affector; however, the dynamics and structure of an ecosystem are rarely influenced by a single environmental factor [10]. The need to better understand the cumulative effects of multiple affectors is one of the most pressing goals in marine ecology and conservation [11].
Climate change is perhaps the most serious threat to marine ecosystems, triggering unpredictable consequences on their structure and functioning [12]. Both on land and in the ocean, the first direct effects of climate change are due to positive thermal anomalies such as the so-called heat waves—abnormally high temperatures for a short period in a particular region [13,14]. In recent decades, abrupt increases in sea water temperature have caused mass mortality of marine species [15,16,17] and changes in community composition and structure [18]. In addition, high temperatures have promoted the development of mucilaginous aggregates, with negative effects on benthic ecosystems [19,20].
Another worrisome effect of the increasing temperature is the range expansion of invasive alien species [21], which represents a worldwide threat to the integrity of ecosystems, to economy, and even to human health ([22], and references therein]. The impact of these species can be context-dependent, varying at different spatial and temporal scales [23]. In the Mediterranean Sea, one of the worst invasive species is the green alga Caulerpa cylindracea [24,25,26]. Its success has been facilitated by habitat loss due to human-related activities. As a consequence of this further pressure, the composition of native benthic assemblages changes [27] toward homogenisation [28]. As another consequence of climate change, the intensity and frequency of extreme events are increasing [29]. Hurricanes and storms have caused important impacts on marine ecosystems [30,31] by damaging coastal communities with the mechanical removal of benthic species [32,33].
Like many other coastal habitats, rocky reefs are subjected to both local and global pressures. While many studies have considered intertidal communities [34,35,36], the effects of multiple affectors on subtidal communities have rarely been investigated [37,38]. Rocky reefs represent environments of great scientific and economic value [39], due to the high biodiversity they host [40] and the ecosystem services they offer [41]. Understanding the effects of multiple affectors on rocky reefs is of fundamental importance for conservation policies [42].
This paper aims at evaluating the short-term changes (June to December) undergone by the rocky reef communities of the Portofino MPA during 2018, when different stressors (i.e., thermal anomalies, a mucilaginous event, and the seasonal expansion of C. cylindracea) came into action contemporaneously (mostly in full summer), while a disturbance, i.e. a severe storm, occurred on 29 October. The study was carried out at four different depths (10 m, 20 m, 30 m, and 40 m), under the hypothesis that the expected consequences are different along a vertical gradient.
The starting assumptions on which this study was based were: (i) the main driver of change in a temperate rocky reef should be seasonality [43], which mainly affects shallow water communities (at 10 m and 20 m depths); (ii) mucilage should affect first the communities at the thermocline (where mucilagethe aggregates form) and later the deep water ones (at 30 m and 40 m depths), where the mucilaginous aggregates typically fall in late summer, covering erect organisms, such as gorgonian corals [44]; (iii) the greatest impacts due to the expansion of C. cylindracea were expected at the 20 m depth, as already reported by previous studies [20]; (iv) the severe storm was expected to have mainly caused impacts on shallow water communities, most subjected to wave action.

2. Materials and Methods

2.1. Study Area

The Portofino Marine Protected Area (MPA), established in 1999, covers an area of 346 ha in the Ligurian Sea (NW Mediterranean) and encircles a rocky promontory, which spans out towards the sea for about 5 km. The southern front of the promontory is characterised by high vertical or sub-vertical cliffs, which continue underwater to a depth of about 50 m, while the eastern and western sides are comparatively shallower [44].
Increasing urbanisation of the Ligurian coast has amplified large-scale and chronic impacts, affecting marine ecosystems. Before the protection regime came into effect, climate change and local human pressures have led to a phase shift in the rocky reef communities of Portofino MPA in the 1990s [20,45].

2.2. Sea Surface Temperatures Data Management

Trends of the yearly mean sea surface temperatures (SST) from 1948 till 2019 were examined to evaluate the potential role of temperature as a driver of change in the rocky reef communities. As 2018 had been one of the warmest years on record [46], we compared the monthly SST values for 2018 with the climatological mean (monthly mean values) of the previous 70 years (1948 to 2017). For each month of 2018, thermal anomalies (aSST) were detected by applying the follow formula:
a S S T = SST 2018 SST mean σ
where SST2018 is the monthly mean (±SD) for 2018, SSTmean is the monthly climatological mean, and σ is the standard deviation of the climatological mean. The differences between 2018 and the climatological mean were evaluated through a Mann–Kendall test [47].
The SST data were derived from NOAA (US National Oceanic and Atmospheric Administration; https://psl.noaa.gov/cgi-bin/data/timeseries/timeseries1.pl, accessed on 1 September 2022) satellite records.

2.3. Field Activities and Data Collection

Data on the rocky reef communities of the Portofino MPA were collected by scuba diving using photoquadrats in three sites (Figure 1): Altare (44°18’20’’ N, 9°11’48’’ E), Colombara (44°18’35’’ N, 9°10’38’’ E), and Torretta (44°18’45’’ N, 9°10’03’’ E). The three sites have similar environmental and morphological characteristics and are equally exposed to the considered affectors. To assess the differences in community composition and structure before and after the onset of seasonal and recurrent stressors (i.e., thermal anomalies, mucilaginous events, expansion of Caulerpa cylindracea), data were collected from 19 to 21 June and from 18 to 23 October 2018. Following the unpredictable storm that hit the Ligurian coast on 29 October, further data were collected between 12 and 13 December 2018 to quantify the impact of this disturbance. To analyse the effects of all affectors in relation to the depth, data were collected at 10 m, 20 m, 30 m, and 40 m depths. In each combination of sites and depths, 32 random photoquadrats (each covering an area of 50 × 50 cm2) were taken (Figure 2).

2.4. Photographic Analysis

Each photoquadrat was analysed using the software Image J [48] to calculate the percent cover of any organism present at the lowest possible taxonomic level (usually species). When species identification was not possible, lumped categories based on similar morphological and structural characteristics (i.e., OTUs, operational taxonomic units) were adopted [49,50]. The abiotic component (sediment and bare rock) was also recorded.

2.5. Community Data Management

Cover data of species and OTUs were organised in a matrix ((time × site × depth) × species/OTUs) and transformed by applying arcsine√(x⁄100). A non-metric multidimensional scaling (nMDS) based on the Bray–Curtis index was applied to highlight potential changes over time and depth in rocky reef communities.
To test the differences in percent cover over time, a two-way permutational multivariate analysis of variance (PERMANOVA), followed by a PAIRWISE test for significant terms, was performed on orthogonal factors; ‘time’ (3 levels: June, October, and December) and ‘depth’ (4 levels: 10 m, 20 m, 30 m, 40 m) were fixed, while ‘site’ (3 levels: Altare, Colombara, and Torretta) was random.
Two time intervals were considered to highlight when the major changes occurred in the Portofino MPA rocky reef communities: June to October and October to December. The Pythagoras theorem was applied to the first two nMDS axis scores to measure the time trajectories between the two time intervals at the four depths [51]. For example, the time trajectory between June and October at 10 m depth was calculated as the geometric distance between the 10 m centroids of June and October as follows:
T t 10 = ( x O x J ) 2 + ( y O y J ) 2
where Tt10 is the length of the time trajectory at 10 m, xJ and yJ are the axis scores of the 10 m centroid of June, and xO and yO are the axis scores of the 10 m centroid of October. Analogous formulas were applied to measure the time trajectories between June and October and between October and December at all the depths surveyed. Differences between time trajectories at each depth were evaluated by Student’s t-test.
A SIMPER analysis based on the Bray–Curtis index was applied to identify the descriptors (species or OTUs) that mostly contributed to differences in community composition among the three times at each depth.
To assess the relative importance of the dominant species (cover > 5%) in determining overall changes in community composition and structure, a graphical display was produced, where each time (June, October, December) was represented by the species/OTUs mean value. In addition, the Shannon–Wiener diversity index (computed with the natural logarithm ln) was applied to evaluate whether changes in the community composition were reflected in the community structure (diversity).
Analyses were performed using the software PaSt [52], Primer 6 + PERMANOVA [53], and RStudio [54] packages.

2.6. Role of Seasonality in Community Change

Change in cover data of seasonal species (i.e., the sum of all the seasonal species, the alien C. cylindracea excluded) were considered as the community response to variation in the thermal regime; these data were analysed to highlight their trend in the investigated period. Differences among the three times at each depth were evaluated by Kruskall–Wallis test.
A new simulated data matrix ((time × depth) × species/OTUs), excluding seasonal species, was generated to distinguish the community changes due to seasonality from those referable to the other affectors. We used the term ‘simulated’ to make clear that we did not perform a real, physical removal experiment in the field. This procedure has already been applied for studies involving a so-called ‘inclusion versus exclusion’ approach, in which the descriptor of interest is an integral part of the response ([28], and reference therein). An nMDS analysis based on the Bray–Curtis index was applied to the simulated data matrix, and the time trajectories between June and October and between October and December were measured using the axis scores, as done for the original data matrix. Differences between the time trajectories of the original data matrix and the simulated one were evaluated by Student’s t-test.

2.7. Data Management for Mucilage, Caulerpa cylindracea, and the Severe Storm

The cover data for mucilage and C. cylindracea were analysed to highlight their trends in the investigated period. Differences among the three times at each depth were evaluated by Kruskall–Wallis test.
As done for seasonal species, two new simulated data matrices ((time × depth) × species/OTUs), each excluding one stressor (mucilage or C. cylindracea), were generated to test the effect of such stressor on the rocky reef community composition. An nMDS analysis based on the Bray–Curtis index was applied to each simulated data matrix, and the time trajectories between June and October and between October and December were measured using the axis scores, as done for the original data matrix. Differences between the time trajectories of the original data matrix and the simulated ones were evaluated by Student’s t-test.
Differences in the cover of abiotic components and perennial species, which are not expected to show seasonal variation, between October and December at each depth were analysed by Student’s t-test to evaluate the effect of the storm. The species or OTUs that most contributed to differences were identified through a SIMPER analysis.

3. Results

3.1. Sea Surface Temperature and Thermal Anomalies

An analysis of the climatological mean SST showed a positive trend for the last 70 years (Figure 3A). In 2018, the SST yearly mean value was 17.4 ± 1.42 °C, 1.2 °C higher than the yearly mean for 1948–2017. The yearly mean SST for 2018 was slightly higher than that of the year 2003 (17.2 ± 1.4 °C), when a severe mass mortality event occurred in the northwestern Mediterranean rocky reef communities [15]. Comparing the monthly SST values for 2018 with the monthly SST mean values of the previous 70 years unveiled uninterrupted thermal anomalies from August to November (Figure 3B, Table 1).

3.2. Changes in Community Composition and Structure

A total of 91 species and 7 OTUs were recorded (Supplementary Materials, Tables S1 and S2). The nMDS applied to the cover data ordered the photoquadrat points according to two gradients: a spatial one along the 1st (horizontal) axis, and a temporal one along the 2nd (vertical) axis (Figure 4A). The spatial gradient was an expression of increasing depths from the left (10 m) to the right (40 m) of the 1st axis.
The temporal gradient was expressed from bottom to top by seasonality, with the points of June, October, and December well separated from each other (Figure 4A,B). The nMDS did not show any ordination of photoquadrat points according to the factor site (Figure 4A).
The PERMANOVA results evidenced significant differences for the interactions between the time, site, and depth factors (Table 2). The PAIRWISE results showed significant differences for each combination of the three factors, indicating a pervasive change with time along the whole depth gradient in all the sites considered (Table 2).
Comparing the time trajectories between June and October and between October and December at each depth by Student’s t-test, significant differences were observed at 10 m (p = 0.004), 20 m (p = 0.009), and 40 m (p = 0.200). The magnitude of change between October and December was always greater than that between June and October, highlighting that the major changes in rocky reef communities occurred from October to December (Figure 4C).
The SIMPER analysis identified the descriptors that mostly contributed to community change at each depth in the two time intervals considered (Table 3): (i) Dictyota dichotoma at 10 m and 20 m depth between June and October; (ii) Jania spp. at 10 m depth in both time intervals and at 20 m depth between June and October; (iii) Padina pavonica at 20 m depth between October and December; (iv) mucilage at 40 m in both time intervals; (v) Caulerpa cylindracea especially at 20 m, and secondarily at 10 m and 30 m, in both time intervals; (vi) Ellisolandia elongata at 10 m in both time intervals; (vii) encrusting corallines at 10 m and secondarily at 20 m between October and December; (viii) Halopteris scoparia at 10 m and 20 m in both time intervals; (ix) sediment at all depths investigated in both time intervals.
The species composition of the Portofino MPA community changed over time, mainly due to both the descriptors that represent the effect of change (i.e., seasonal species and perennial species after the storm) and the descriptors that are at the same time the cause and the effect of change (i.e., mucilage and Caulerpa cylindracea) (Figure 5).
The Shannon–Wiener diversity index did not show relevant differences between the communities at the three time points investigated, with the partial exception of 20 m depth, where a slight decrease was observed in October (Figure 6).

3.3. Seasonal Variations

The Kruskall–Wallis test applied to cover data for seasonal species at the three times evidenced significant differences at 10 m, 20 m, and 30 m depth (Figure 7A). The greatest changes were observed at 10 m, where the cover of seasonal species decreased significantly (p = 3.36 · 10−14) from June (67.7 ± 1.9) to October (37.1 ± 2.1) and again in December (5.3 ± 0.5). Significant changes also occurred at 20 m, where cover increased significantly (p = 2.42 · 10−11) from June (33.1 ± 4.2) to October (41.5 ± 3.5) and decreased from October to December (1.4 ± 0.2). The algal species that exhibited the greatest variations were Dictyota dichotoma, Jania spp., and Padina pavonica, which were abundant in June and October and then disappeared in December at both 10 m and 20 m depth (Figure 5).
Student’s t-test applied to the time trajectories of the original data matrix and the simulated data matrix confirmed significant change in rocky reef communities between October and December at 10 m (p = 0.02) and 20 m (p = 0.02) depth (Table 4).

3.4. Proliferation of Mucilaginous Aggregates

The Kruskal–Wallis test applied to mucilage cover data at the three times evidenced major differences at 20 m and 40 m (Figure 7B). The mucilage decreased significantly (p = 1.10 · 10−6) from June (10.2 ± 4.1) to October (0.2 ± 0.1) at 20 m; on the contrary, it increased significantly (p = 9.82 · 10−14) from June (0.1 ± 0.1) to October (17.7 ± 2.2) at 40 m. At both depths, the mucilage disappeared completely in December.
Student’s t-test applied to the time trajectories of the original data matrix and the simulated data matrix showed significant differences at 40 m depth (Table 4), both between June and October (p = 0.005) and between October and December (p = 7.89 · 10−5).

3.5. Caulerpa cylindracea Expansion

The Kruskall–Wallis test applied to the cover of C. cylindracea at the three times evidenced major changes at 20 m depth, where C. cylindracea increased significantly (p = 5.24 · 10−13) from June (1.8 ± 0.3) to October (35.8 ± 3.4), disappearing in December (Figure 7C).
The Student’s t-test applied to the time trajectories of the original data matrix and the simulated data matrix confirmed significant differences between October and December at the 20 m (p = 0.002) depth (Table 4).

3.6. Effects of the Storm

The SIMPER analysis highlighted the following perennial species and abiotic components as responsible for the main significant differences betweencommunities between October and December: Ellisolandia elongata, encrusting corallines, Halopteris scoparia, and sediment (Table 3). All exhibited significant variations in cover between the two times (Figure 8). E. elongata increased significantly from 7.7 ± 1.2 to 23.6 ± 1.9 (p = 1.69 · 10−6) at 10 m depth. The encrusting corallines increased significantly from 5.3 ± 0.6 to 22.7 ± 1.4 (p = 2.71 · 10−10) at 10 m depth and from 5.1 ± 0.4 to 15.8 ± 1.3 (p = 3.18 · 10−7) at 20 m. H. scoparia decreased significantly from 32.5 ± 2.5 to 8.8 ± 0.5 (p = 7.19 · 10−9) at 10 m and from 4.3 ± 1.8 to zero (p = 2.11 · 10−2) at 20 m. The sediment increased significantly from 5.4 ± 0.7 to 8.8 ± 0.6 (p = 1.18 · 10−3) at 10 m depth and from 7.6 ± 1.4 to 11.5 ± 1.4 (p = 5.42 · 10−2) at 20 m depth, while it decreased significantly from 20.8 ± 1.3 to 16.2 ± 0.7 (p = 9.93 · 10−3) at 30 m depth and from 25.9 ± 2.1 to 19.1 ± 3.3 (p = 9.36 · 10−2) at 40 m depth.

3.7. Magnitude of Pressures According to the Depth

Each single affector exhibited different impacts along the vertical gradient (Figure 9). The seasonality contributed mainly to the changes in shallow water communities (10 m and 20 m). The mucilage affected benthic communities at different times and depths: in June at 20 m and in October at 40 m. The highest cover of C. cylindracea was recorded at 20 m. The severe storm had impacts along all the water column, but especially at 10 m and 20 m depth.

4. Discussion

In 2018, the rocky reef communities of Portofino MPA suffered three major stressors (high temperature, mucilage, and the invasive alien alga Caulerpa cylindracea) and were subjected to a severe disturbance (the storm of 29 October). Sea surface temperature (SST) was the highest over the last 70 years, slightly surpassing the hot season of 2003 [15]; similarly, the mucilaginous event equalled the one in 2003 [19,20], and a peak in the cover of C. cylindracea occurred [55]. The October storm was the most severe that ever hit the Ligurian coast [33]. The cumulative action of all these affectors triggered significant changes in the rocky reef communities in all sites considered from June to December. However, although changes in community composition were evident, this was not reflected in a change in community structure (diversity). Species diversity is an emergent property of ecosystems that is often maintained within narrow limits, notwithstanding change in species composition [56].
When multiple affectors act simultaneously, as happened at Portofino MPA, each one may produce similar or distinct effects [57,58]. Distinguishing the outcome of every single affector, even excluding natural variability, is difficult [39,59]. Taking into account four depths, under the hypothesis that every single affector impacted differently along the vertical gradient, this study explored the possibility to face this difficulty.
Mediterranean coastal benthic ecosystems are strongly subjected to the seasonal variation of environmental factors [60], but the effects of seasonality are damped with depth [43]. As expected, at Portofino MPA, the major variation in the cover of seasonal species was recorded at the 10 m depth. However, the observed decrease in perennial species, such as Halopteris scoparia, and the increase in Ellisolandia elongata and encrusting corallines cannot be explained by the effects of seasonality alone. A possible explanation is that the October storm cleaned off the soft-bodied species H. scoparia from of the upper layer, making more visible the hard, calcified, and more resistant species (E. elongata and the encrusting corallines) of the basal layer.
Overall, the time trajectories illustrated that the greatest change in the rocky reef community between June and December occurred at 20 m depth, in response not only to seasonality but also to other affectors. The mucilaginous aggregates formed mostly at this depth, just below the summer thermocline [20]. The invasive alga C. cylindracea showed the highest cover there, conforming to previous years [28]. As observed at 10 m depth, the decrease in H. scoparia and the increase in calcified corallines in December point to the cleaning effect of the storm.
At 30 m depth, only small differences in community composition were observed from June to December; this result was consistent with the trend for all affectors that did not show noteworthy changes at this depth. A slight quantity of mucilage was observed only in October, and a negligible cover of C. cylindracea was recorded in June. Although significant, the variation in the cover of seasonal species was modest overall.
The significant change at 40 m depth was attributable to the fall of mucilage in late summer; while not being present in June, the mucilaginous aggregates covered a wide extent of the seafloor in October [20], only to completely disappear in December. The seasonal species and C. cylindracea were slight or not represented at this depth.
The only affector that impacted all four depths investigated was the severe storm that occurred at the end of October. Besides the cleaning effect on the species of the upper layer, the storm redistributed sediment along the depth gradient. In this case, the removal of the upper layer, which occurred mostly in the algal-dominated shallow-water communities, may also have made the sediment more visible on the rocky substrate.
Notwithstanding the significant interactions between the various sources of variability, the initial hypothesis that exploring different depths could have disentangled the effects of the four affectors was corroborated by the results of the present study, which adopted three different methodological approaches: (i) a multivariate analysis that allowed the time trajectories of change to be measured; (ii) the variation in cover of selected descriptors (species/OTUs) used as proxies for natural variability and the three affectors considered; (iii) the exploration of simulated matrices, where three of the proxies (i.e., seasonality, mucilage, and C. cylindracea) were excluded in turn.
No evident effect was observed due to the thermal anomalies recorded in the period investigated. The species more vulnerable to the increase in water temperature (e.g., Paramuricea clavata and sponges) did not show any decrease in cover following the thermal anomalies. The short period of the present study obviously did not allow an assessment of the long-term effects of such affector on vulnerable species. Unequivocal evidence of the effects of increasing temperature on rocky reefs has been reported elsewhere [15,16,17], and according to the predictions, thermal anomalies will lead to reductions in the number of taxa composing the benthic communities [61].
The effect of the storm was more evident at 10 m depth but involved all communities at the four depths investigated. Extreme storms are certainly disruptive events, and the increase in their frequency in recent decades raises concern for the future of biological communities [62]. In the marine realm, several studies about the effects of tropical hurricanes have been conducted on coral reefs (but less so in temperate reefs), highlighting species removal and sediment reshuffling [31,63], as observed at the Portofino MPA. This study analysed the effects of the severe storm shortly after (about one month later) its occurrence, and only through future monitoring will it be possible to assess the recovery capacity of benthic communities after this disturbance.
The mucilage, following a first bloom at 20 m, mostly impacted the community at 40 m depth covering erect species. Massive developments of mucilage are considered a worrisome ecological threat to marine ecosystems [64]. Covering wide areas of the substrate, mucilage limits light penetration and alters chemical and physical environments, causing anoxic conditions beneath [65]. Signs of necrosis due to mucilaginous events have been described for several benthic taxa in many different Mediterranean areas ([66], and references therein). However, no reduction in species cover was observed in December that was attributable to the mucilage, but once again sustained monitoring would be necessary to assess the long-term effects of this single affector.
C. cylindracea peaked at 20 m, where negative effects on diversity and spatial heterogeneity have already been demonstrated [28]. C. cylindracea was shown to easily colonise areas subject to loss of native species cover, and to prevent their recovery by facilitating the settlement and persistence of alternative assemblages dominated by stress-tolerant species [67,68]. Transient ecological effects, generated by a temporary deviation from the original disturbance regime, are, thus, transformed into permanent changes [25].
The cumulative effect of the considered pressures peaked at the 20 m depth, where the greatest changes in the rocky reef community were documented. Overall, these results suggest that the cumulative effect of multiple affectors is stronger than that of any individual affector, no matter how intense it is.
Notwithstanding the consistent results, our approach undoubtedly has several inherent limits: (i) despite the analyses conducted on the seasonal species, it is difficult to completely exclude natural variability when assessing changes over time due to the other affectors considered, two of which (mucilage and C. cylindracea) also exhibit seasonal trends; (ii) the lack of comparable information in the years before and after 2018 limits the possibility to infer cause–effect relationships between affectors and community change; (iii) considering only one sampling time before and after each affector may not be enough to thoroughly explore the sources of variation.
Interactions among multiple affectors, which can trigger abrupt changes in marine communities, are still poorly understood, and their consequences pose important challenges to researchers and conservationists alike [60,69]. Historical data series and the revisitation of sites already surveyed in the past are essential to illustrate ecological change [59,70], but short-term studies considering the multiple affectors acting almost simultaneously may help disentangle their effects. The importance of analysing ecological changes at different scales has been underlined on several occasions ([71], and reference therein). As a short-term scale example, this study may represent an attempt to describe the dynamics of temperate rocky reef communities following the impacts of co-occurring punctual events.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/w15040825/s1. Table S1: List of the 91 species and 7 OTUs recorded in the Portofino MPA. For each species the presence (1) and absence (0) in the three months surveyed at the four different depths are reported. Table S2: List of the conspicuous species and OTUs (cover > 1%) recorded in the Portofino MPA, ordered alphabetically. For each species the mean cover (±SE) values for the three months surveyed at the four different depths are reported.

Author Contributions

A.A.: Investigation, conceptualisation, data curation, formal analysis, writing—original draft. V.P.: Investigation, data curation, formal analysis. V.A.: Data curation, methodology, formal analysis. C.N.B.: Conceptualisation, methodology, writing—review and editing. C.M.: Conceptualisation, methodology, writing—review and editing. A.O.: Investigation, writing—review and editing. M.M.: Conceptualisation, supervision, project administration. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Data Availability Statement

The data presented in this study are available in the Supplementary Materials.

Acknowledgments

Thanks are due to Lorenzo Meroni (University of Genoa) for his scientific advice. Alix Varenne, Chiara Redoano, and Silvia Mangraviti contributed to the photographic analyses. The logistical support during field activities provided by Andrea Galliadi (Diving Evolution, Santa Margherita Ligure) is gratefully acknowledged.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map of the Portofino Marine Protected Area (Ligurian Sea, NW Mediterranean) with the three sites surveyed (Altare, Colombara, and Torretta) represented by hot pink circles. Geographic coordinates in WGS84.
Figure 1. Map of the Portofino Marine Protected Area (Ligurian Sea, NW Mediterranean) with the three sites surveyed (Altare, Colombara, and Torretta) represented by hot pink circles. Geographic coordinates in WGS84.
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Figure 2. Examples of photoquadrats (each covering an area of 50 × 50 cm2) carried out at three times (June, October, and December) and at four depths (10 m, 20 m, 30 m, and 40 m).
Figure 2. Examples of photoquadrats (each covering an area of 50 × 50 cm2) carried out at three times (June, October, and December) and at four depths (10 m, 20 m, 30 m, and 40 m).
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Figure 3. (A) Fourth-degree polynomial trend (r = 0.75) of the yearly mean sea surface temperature (SST) values in the Portofino MPA from 1948 to 2019. (B) The 2018 SST monthly values compared to the SST overall monthly mean values of the previous 70 years. The SST values were derived from NOAA satellite data (www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl, accessed on 1 September 2022).
Figure 3. (A) Fourth-degree polynomial trend (r = 0.75) of the yearly mean sea surface temperature (SST) values in the Portofino MPA from 1948 to 2019. (B) The 2018 SST monthly values compared to the SST overall monthly mean values of the previous 70 years. The SST values were derived from NOAA satellite data (www.esrl.noaa.gov/psd/cgi-bin/data/timeseries/timeseries1.pl, accessed on 1 September 2022).
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Figure 4. (A) Multivariate analysis (nMDS) plot of Portofino MPA species/OTU ratios. Individual observation points are represented by different colours and shapes according to time (J = June, shown in orange; O = October, shown in green; D = December, shown in blue) and depth. The colour gradations represent different sites at the three times (A = Altare; C = Colombara; T = Torretta). (B) The nMDS plot showing only the centroids and with time trajectories represented by arrows (light grey for trajectories between June and October; dark grey for trajectories between October and December). (C) Differences (* = significance p < 0.001) between time trajectory values (derived from axis scores and analysed with Student’s t-test) for June to October and October to December at each depth (10 m, 20 m, 30 m, and 40 m).
Figure 4. (A) Multivariate analysis (nMDS) plot of Portofino MPA species/OTU ratios. Individual observation points are represented by different colours and shapes according to time (J = June, shown in orange; O = October, shown in green; D = December, shown in blue) and depth. The colour gradations represent different sites at the three times (A = Altare; C = Colombara; T = Torretta). (B) The nMDS plot showing only the centroids and with time trajectories represented by arrows (light grey for trajectories between June and October; dark grey for trajectories between October and December). (C) Differences (* = significance p < 0.001) between time trajectory values (derived from axis scores and analysed with Student’s t-test) for June to October and October to December at each depth (10 m, 20 m, 30 m, and 40 m).
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Figure 5. Compositional change in the rocky reef communities of Portofino MPA at the three times investigated (J = June; O = October; D = December). The descriptor ‘others’ includes species whose cover was always <5%.
Figure 5. Compositional change in the rocky reef communities of Portofino MPA at the three times investigated (J = June; O = October; D = December). The descriptor ‘others’ includes species whose cover was always <5%.
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Figure 6. The community structure, expressed by mean (±se) diversity (Shannon–Wiener index), of the Portofino MPA at the three time periods investigated (J = June; O = October; D = December).
Figure 6. The community structure, expressed by mean (±se) diversity (Shannon–Wiener index), of the Portofino MPA at the three time periods investigated (J = June; O = October; D = December).
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Figure 7. Percent cover (+ se) of (A) seasonal species, (B) mucilage, and (C) Caulerpa cylindracea at the three times (June in orange, October in green, December in blue) at the four depths surveyed (10 m, 20 m, 30 m, and 40 m).
Figure 7. Percent cover (+ se) of (A) seasonal species, (B) mucilage, and (C) Caulerpa cylindracea at the three times (June in orange, October in green, December in blue) at the four depths surveyed (10 m, 20 m, 30 m, and 40 m).
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Figure 8. Percent cover (+se) of the species or abiotic components, indicating the effects of the storm and identified by the SIMPER analysis (see Table 3), before (Oct = October) and after (Dec = December) the storm occurrence at four different depths (10 m, 20 m, 30 m, and 40 m).
Figure 8. Percent cover (+se) of the species or abiotic components, indicating the effects of the storm and identified by the SIMPER analysis (see Table 3), before (Oct = October) and after (Dec = December) the storm occurrence at four different depths (10 m, 20 m, 30 m, and 40 m).
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Figure 9. A schematic illustration of the level of pressure exerted by affectors considered (seasonality, mucilage, Caulerpa cylindracea, and the storm of 29 October) on the rocky reefs of Portofino MPA at the four depths investigated (circle sizes are roughly proportional to their intensity).
Figure 9. A schematic illustration of the level of pressure exerted by affectors considered (seasonality, mucilage, Caulerpa cylindracea, and the storm of 29 October) on the rocky reefs of Portofino MPA at the four depths investigated (circle sizes are roughly proportional to their intensity).
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Table 1. The 2018 thermal anomalies (in bold) detected by applying the method proposed by Jiménez-Muñoz et al. [47].
Table 1. The 2018 thermal anomalies (in bold) detected by applying the method proposed by Jiménez-Muñoz et al. [47].
JanFebMarAprMayJunJulAugSepOctNovDec
Thermal anomalies (°C)−0.70.1−0.40.61.41.41.83.02.61.92.02.0
Mann-Kendall test (p)0.4700.0610.2030.2160.7430.1160.0600.0010.0090.0010.0030.237
Table 2. Results of the PERMANOVA and PAIRWISE tests applied on rocky reef communities of Portofino MPA. Times = June (J), October (O), and December (D); sites = Altare, Colombara, and Torretta; depth = 10, 20, 30, and 40 m.
Table 2. Results of the PERMANOVA and PAIRWISE tests applied on rocky reef communities of Portofino MPA. Times = June (J), October (O), and December (D); sites = Altare, Colombara, and Torretta; depth = 10, 20, 30, and 40 m.
PERMANOVA
SourceSSDfR2FP
Time 6.03220.13565.1850.001
Site 1.01820.02311.0020.001
Depth 17.85430.399128.6260.001
Time × Site 0.43340.0092.3420.002
Time × Depth 4.07260.09114.6700.001
Site × Depth 2.09060.0477.5270.001
Time × Site × Depth 1.532120.0342.75920.001
Residual 11.6602520.260
Total 44.492287
PAIRWISE test
AltareColombaraTorretta
J ≠ OJ ≠ DO ≠ DJ ≠ OJ ≠ DO ≠ DJ ≠ OJ ≠ DO ≠ D
10 m 0.0010.0010.0010.0010.0030.0010.0010.0010.001
20 m 0.0010.0010.0010.0010.0020.0010.0010.0010.001
30 m 0.0010.0010.0010.0010.0010.0020.0020.0010.001
40 m 0.0220.0010.0020.0010.0010.0010.0010.0010.001
Table 3. Descriptors that mostly contributed (>5%) to the similarity between June–October and between October–December identified by SIMPER analysis (based on the Bray–Curtis index). J-O: June to October; O-D: October to December.
Table 3. Descriptors that mostly contributed (>5%) to the similarity between June–October and between October–December identified by SIMPER analysis (based on the Bray–Curtis index). J-O: June to October; O-D: October to December.
SIMPER Analysis
10 m20 m30 m40 m
J-OO-DJ-OO-DJ-OO-DJ-OO-D
Seasonality
Dictyota dichotoma30.6 18.0
Jania spp.10.716.55.1
Padina pavonica 6.3
Stressors
Mucilage 7.9 7.7 19.415.6
Caulerpa cylindracea 5.019.424.67.08.4
Others
Ellisolandia elongata6.012.2
Encrusting corallines 11.8 9.0 6.2
Halopteris scoparia15.214.65.3
Sediment5.85.35.76.610.37.513.314.9
Table 4. The p values of Student’s t-test, applied to analyse the differences between time trajectories (J-O: June to October; O-D: October to December) of the original data matrix and the simulated ones at the four depths investigated. Significant differences are in bold.
Table 4. The p values of Student’s t-test, applied to analyse the differences between time trajectories (J-O: June to October; O-D: October to December) of the original data matrix and the simulated ones at the four depths investigated. Significant differences are in bold.
p Values ANOVA
Seasonal SpeciesMucilageCaulerpa cylindracea
J-OO-DJ-OO-DJ-OO-D
10 m0.2650.0210.1020.9560.3750.181
20 m0.5470.0220.6650.7100.3910.002
30 m0.5310.5470.0370.1830.1090.342
40 m0.2560.0940.0050.0000.1150.003
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Azzola, A.; Picchio, V.; Asnaghi, V.; Bianchi, C.N.; Morri, C.; Oprandi, A.; Montefalcone, M. Troubles Never Come Alone: Outcome of Multiple Pressures on a Temperate Rocky Reef. Water 2023, 15, 825. https://doi.org/10.3390/w15040825

AMA Style

Azzola A, Picchio V, Asnaghi V, Bianchi CN, Morri C, Oprandi A, Montefalcone M. Troubles Never Come Alone: Outcome of Multiple Pressures on a Temperate Rocky Reef. Water. 2023; 15(4):825. https://doi.org/10.3390/w15040825

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Azzola, Annalisa, Virginia Picchio, Valentina Asnaghi, Carlo Nike Bianchi, Carla Morri, Alice Oprandi, and Monica Montefalcone. 2023. "Troubles Never Come Alone: Outcome of Multiple Pressures on a Temperate Rocky Reef" Water 15, no. 4: 825. https://doi.org/10.3390/w15040825

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