Nothing Special   »   [go: up one dir, main page]
Next Article in Journal
Blockchain Technology and Corporate Performance: Empirical Evidence from Listed Companies in China
Previous Article in Journal
Sustaining Economic Growth: E-Service Quality’s Role in Fostering Customer Loyalty in Nigeria SMEs
You seem to have javascript disabled. Please note that many of the page functionalities won't work as expected without javascript enabled.
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Sustainability
Volume 16
Issue 21
10.3390/su16219176
sustainability-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Assessing Atlantic Kelp Forest Restoration Efforts in Southern Europe

by
Alexandre F. S. Marques
1,
Álvaro Sanchéz-Gallego
1,
Rodrigo R. Correia
1,
Isabel Sousa-Pinto
2,3,
Silvia Chemello
2,
Inês Louro
4,
Marco F. L. Lemos
1 and
João N. Franco
1,*
1
MARE—Marine and Environmental Sciences Centre & ARNET—Aquatic Research Network Associated Laboratory, ESTM, Polytechnic of Leiria, 2520-630 Peniche, Portugal
2
CIIMAR—Interdisciplinary Centre of Marine and Environmental Research, University of Porto, 4450-208 Matosinhos, Portugal
3
Departamento de Biologia, Faculdade de Ciências da Universidade do Porto, 4169-007 Porto, Portugal
4
SeaForester Lda, 2765-253 Estoril, Portugal
*
Author to whom correspondence should be addressed.
Sustainability 2024, 16(21), 9176; https://doi.org/10.3390/su16219176
Submission received: 7 August 2024 / Revised: 30 September 2024 / Accepted: 10 October 2024 / Published: 23 October 2024
Browse Figures
Figure 1
<p>(<b>A</b>) Section of the western continental Portuguese coast where the deployments took place. Three distinct zones were selected: (<b>B</b>) The coast of Peniche, with Marques-Neves as the reference Kelp forest (I) and Consolação (II); (<b>C</b>) In the Berlengas Islands at the sites Elefante (III) and Galos (IV); (<b>D</b>) and in the Cascais area at Boca do Inferno (V).</p> "> Figure 2
<p>(<b>A</b>) Technique used to deploy the gravel from the surface; (<b>B</b>) Scientific divers deployed buoys marking the area for deployment (100 m<sup>2</sup>) in Berlengas at the Galos site; (<b>C</b>) close-up of the deployed green gravel.</p> "> Figure 3
<p>Percentage of each bottom substratum category (reef plateau, boulders, and sand) measured in 25 m transects at the different studied sites (<span class="html-italic">n</span> = 5). Numbers within each bar indicate the site’s Rugosity Index (RI) achieved (<span class="html-italic">n</span> = 5).</p> "> Figure 4
<p>(<b>A</b>) Average seawater temperature (measured in situ); (<b>B</b>) sea surface temperature—SST; (<b>C</b>) near surface chlorophyll <span class="html-italic">a</span> level—Chla <span class="html-italic">a</span>, and (<b>D</b>) absolute average water movement in all monitored sites. Statistically significant different groups (a, b, and c) are shown (Tukey’s HSD; <span class="html-italic">p</span> ≤ 0.05). Error bars are ±2 sd of means (n.a. = not assessed).</p> "> Figure 5
<p>(<b>A</b>) Concentration of phosphates, (<b>B</b>) nitrates, and (<b>C</b>) nitrites at depth at all monitored sites. Statistically significant different groups (a and b) are shown (Tukey’s HSD; <span class="html-italic">p</span> ≤ 0.05). Error bars are ±2 sd of means. (<span class="html-italic">n</span> = 9 per site).</p> "> Figure 6
<p>(<b>A</b>) Gravel retention and (<b>B</b>) deployment success at the four deployment sites in the three monitoring moments after 3, 6, and 8 months of deployment.</p> "> Figure 7
<p>Coefficient plot of the first component of the PLS regression model. The model included data from all the deployment sites to explain the green gravel success index. Importance was deemed as high if the coefficient was higher than 0.15 (<span class="html-italic">n</span> = 80).</p> ">
Versions Notes

Abstract

:
Kelp forests are essential marine ecosystems increasingly compromised by human activities. Effective reforestation strategies are urgently needed, and the “green gravel” method is a viable tool already used in some European regions. This study aimed to assess the success of this method using the native Kelp species Laminaria ochroleuca on the Portuguese coastline. Cultures of green gravel were reared until the specimens reached a size of approximately 3 cm. The gravel was then deployed at selected sites in Peniche, Berlengas, and Cascais. Over an eight-month period, scientific scuba divers monitored the integration of Kelp, along with associated fish, invertebrate, and algae communities. Nutrient availability, temperature, water movement, substrate type, and Rugosity Index (RI) were also measured. The highest success rate was 12% in Consolação, with Elefante and Galos (Berlengas) reaching 7% and 4%, respectively. By the end of the monitoring period, Cascais had no remaining Kelp on green gravel. Present data suggest that higher success is dependent on less rugged and higher RI topography. Higher grazing pressure, rougher terrain, and unexpected sedimentation appear to be the main obstacles to deployment success. Solid knowledge (biologic and topographic) on the restoration site, starting restoration actions near already established Kelp forests, and significantly scaling up restoration efforts could substantially improve the success of the green gravel method in future reforestation campaigns.

1. Introduction

Kelp forests are an integral and expansive component of marine habitats, especially in the “cold to temperate” regions of our oceans [1,2]. These marine forests are one of the most diverse and productive ecosystems, supporting primary and secondary production [3,4]. This is of utmost importance to the fauna which inhabits these forests, as food source, or as protection for rearing their young [1,5,6]. Marine forests also offer goods and services to humanity [7], supporting fisheries [8,9], serving as both carbon and nitrogen storage, and protecting our shorelines from erosion [10,11].
Nonetheless, anthropogenic and climate-driven factors are contributing to the decline in marine forests, and Kelp forests are no exception [12,13]. Stressors such as ocean warming, overfishing, eutrophication events, and recurrence of extreme events (such as storms) have profound consequences on marine resources, with Kelp forests already dwindling, and with projections of greater decline sooner than later [14,15,16].
Reversing the decline of various ecosystems, including those in the marine realm, is a topic currently receiving significant attention. For example, Sustainable Development Goal 14 of the United Nations (UN) aims to “conserve and sustainably use the oceans, seas and marine resources for sustainable development”. Additionally, the UN Decade of Restoration and the UN Decade of Ocean Science for Sustainable Development (2021–2030) along with the recent EU parliament-adopted Nature Restoration Law (2022/0195/COD) to restore 20% of EU’s land and sea, highlight the recognition that EU habitats are in poor condition and urgent actions are needed, including ecological restoration [17,18].
Therefore, the need for effective restoration tools capable of promoting the large-scale recovery of coastal ecosystems in the face of intensifying climatic and anthropogenic stress has never been greater. Efforts to restore Kelp forests have had, historically, mixed results when it comes to recovering local communities [19]. These mixed results also tend to be achieved with either a top-down approach (where the Kelp’s grazers are removed) or be of a smaller spatial scale [12,20]. Transplanting whole adult Kelps as also been attempted, as well as different seeding/transplanting techniques [21]. However, these methods can pose challenges and may be particularly susceptible to large scale failure, whilst also being economically challenging to implement and scale up [22,23].
More recently, a new approach to reforesting Kelp forests has been gaining traction, the “green gravel” method [24]. With this technique, small rocks are sown with macroalgae propagules and reared in laboratory conditions, later being deployed or out planted in designated areas [24]. Green gravel has been applied effectively in different regions, providing an efficient, cost-effective, and easily up-scalable methodology. It requires relatively little economic investment and can be applicable to a variety of species, with each workgroup adapting it to a species of ecological reference within their geographical area [25,26]. Moreover, it does not rely on transplanting other adult specimens from neighbouring communities or rearing specimens to adulthood in the laboratory, representing an ethically and economically sustainable alternative [24]. However, this technique is certainly not flawless. Some of the main concerns are the introduction of foreign substances into the ocean [19], the susceptibility of the small Kelps attached to the rocks to high wave exposure [27,28], or herbivory [17,29]. Even so, the promised efficiency and cost–benefit [24] seem to possibly outweigh some of these concerns, and consequently, restoration trials using green gravel as the restoration method were conducted on the continental Portuguese Western Coast.
Along the Portuguese coast, Kelps forests have been declining, especially in central and southern Portugal, where Kelp coverage is very sparse or absent, compared to the northern regions of the country where Kelp forests persist [30,31]. One of the three main Kelp species found across the Portuguese coast is Laminaria ochroleuca, commonly known as golden Kelp. Together with Saccorhiza polyschides, these two species dominate the Kelp landscape of central to southern Portugal. For our reforestation efforts, L. ochroleuca, a more resilient perennial species [32,33], contrary to the annual S. polyschides [34,35], was the selected species for assessing the effectiveness of the green gravel method in our reforestation efforts, all the way from laboratory rearing to out planting of the seeded gravel.
This study aimed to conduct the first trials of Kelp habitat restoration using the green gravel method in southern Europe. This involved cultivating native juvenile Kelp of L. ochroleuca on stones under controlled conditions, followed by their deployment in various costal habitats. The deployed green gravel was monitored and various physical and biological variables that could influence the success of this method were assessed. The results are discussed with the aim of providing improvements to optimize and further develop the method, ensuring higher scalability and success rates.

2. Materials and Methods

2.1. Green Gravel Cultures

Green gravel cultures (n = 4, Table S1) were produced using the same source of zoospores of Laminaria ochroleuca specimens collected by scientific scuba divers in the regions of Peniche (N 39°22.501′; W 009°23.571′) and in Viana do Castelo (N 41°41.932′; W 008°51.218′) during the summer months of 2021 and 2022. Established methods were followed [19,24], adapting them for the present Kelp species and facilities. Briefly, after exposing the reproductive tissue to thermal and osmotic stress, the released zoospore solution (15000 spores mL−1) was seeded directly onto the green gravel. The gravel, composed of a mix of limestone and granite stones (3–5 cm, Table S1), was previously washed and kept in tanks connected to a main reservoir within a closed seawater system. Water temperature was controlled using AquaMedic Titan 1600 chillers (Bissendorf, Germany). Light was provided by TMC 12 W LED lamps (Chorleywood, UK) in a 12:12 h cycle with a 5 min sunrise/sunset. Light levels were initially set at 30 µmol m−2 s−1 photons and gradually ramped up to 100 µmol m−2 s−1 over a 14-week period. The water was treated with AquaMedic Helix Max 2.0 UV sterilizers (Bissendord, Germany). Salinity and pH were followed every 2–3 days using a YSI Professional Plus multiparameter probe (Yellow Springs, OH, USA). Nutrients were provided to the cultures every second week with Provasoli’s Enrichment Solution [36]. All cultures were maintained until L. ochroleuca juveniles reached a size of 30 ± 12 mm (mean ± sd, n = 40).

2.2. Green Gravel Deployment

To assess the success of the green gravel technique, cultivated batches were deployed at four different localities along the Portuguese coast (Figure 1). All sites were previously surveyed to ensure that the topography was primarily composed of rocky bottom with minimal to no sand coverage (≤5%). The depths of all deployment areas (17 m, Table S2) were identical to our reference Kelp forest in Marques-Neves (18 m), as previous trials in shallow water (between 5 and 10 m of depth) were unable to be quantified due to the complete disappearance of the gravel. Light availability at the depth of these deployment areas is not physiologically limiting as Kelp forests in the continental Portuguese coast are present at least down to 25 m depth [37].
Gravel deployment occurred during different months of the year (Table S2). The seeded gravel was deployed directly from the surface (Figure 2A) within a pre-marked area using a small vessel adapted for deployment and scientific diving. Scientific divers marked the corners of the deployment polygon (quadrangular shape) with anchors attached to ropes connected to surface buoys (Figure 2B). This method provided a surface reference to assist the boat in deploying the seeded stones (Figure 2C) within the study area.

2.3. Deployment Areas Monitoring

In all deployment locations, biodiversity (i.e., ichthyofauna, invertebrates, and existing Kelp forest) was assessed using randomly oriented replicated belt transects at different monitoring intervals: three, six, and eight months after deployment.
Ichthyofauna (adult and subadult individuals) were counted and identified within each location using randomly oriented replicated belt transects (n = 5) of 100 m2 (25 × 4 m), deployed by the same scientific diver [37]. Briefly, the diver swam at a constant speed along each transect, recording the abundance of each fish species (Table S3). On the return swim, invertebrates were counted within a reduced transect area (n = 5) of 50 m2 (25 × 2 m) (Table S4). For further analysis, potentially grazing species included both herbivorous fish and sea urchins. Herbivorous fishes were categorized according to their trophic affinities [38,39] and defined as those species able to consume algae, thus including omnivorous species [40,41]. The density of Kelp species was also recorded at all deployment areas along each transect (25 × 2 m) [37] (Table S5).
Reef bottom topography was recorded along each transect (n = 5), noting the extent of three bottom (substratum) dominant categories: reef plateau, boulders, and sand as percentages relative to the total 25 m length of each transect. Additionally, the rugosity of the substrate was assessed by carefully setting a 10 m long chain conforming to the seafloor features and then measuring the linear distance covered by the chain (n = 5). The ratio of these measurements represents the rugosity of the two-dimensional profile and is presented as the Rugosity Index (RI) [42].
At each of the selected deployment sites, water movement (m s−2) and temperature (°C) logger sensors (HOBO® Pendant, Onset Computer Corporation, Bourne, MA, USA) were deployed on a marker buoy 1 m above the bottom, taking measurements every 15 min. Due to a loss of logger equipment, satellite data regarding sea surface temperate (SST) were also analyzed. These data were available on NASA’s Giovanni Web, with nighttime SST detected via Moderate Resolution Imaging Spectroradiometer (MODIS)-Aqua sensor (NASA, Washington, DC, USA) [43].
In addition, during the monitoring campaigns, saltwater samples (n = 3) were collected at depth at each diving site for nutrient availability analysis. These samples were stored in a cooled container until processing in the laboratory, where they were filtered and stored frozen (−20 °C) until analysis. Chemical analyses were conducted to quantify (in µM) phosphates (PO43−), nitrates (NO3−), and nitrites (NO2−) using Spectroquant® photometric kits (Merck KGaA, Darmstadt, Germany) and analyzed with a Spectroquant® Move 100 colorimeter (Merck KGaA, Darmstadt, Germany). Due to unforeseen circumstances, some samples were inadvertently compromised, so chlorophyll a (Chl a) data from a MODIS-Aqua sensor, available on NASA’s Giovanni Web, were used as a proxy and further analyzed [43].
Every monitoring interval (i.e., 3, 6, and 8 months after deployment), the retention rate and success of the green gravel method were assessed. Monitoring efforts after this period were not accurate due to the biofouling or sediment coverage affecting the seeded stones, especially in sites where naturally occurring L. ochroleuca is present. Through scientific diving, all visible green gravel were counted within sampling quadrats (50 × 50 cm, n = 40) along four equally distant deployed linear transects, at equal distances within the deployment area. The retention rate was calculated as the number of stones deployed divided by the number of stones counted, normalized by square metre. The success index was calculated as follows: (number of gravels counted—gravels without Kelp) divided by the total number of gravels counted. Both the gravel retention and the success index were expressed as percentages.

2.4. Statistical Analysis

Throughout the analysis of all measured variables, one-way analysis of variance (ANOVA) was used to determine the presence of statistically significant differences between group means. Differences were considered significant at p < 0.05. When such differences were found, a post hoc analysis was conducted using Tukey’s Honestly Significant Difference (HSD) with a 95% confidence interval. The analyses were performed in IBM SPSS Statistics for Windows, Version 29.0.2.0. To identify the key predictors influencing the success of green gravel, a Partial Least Squares (PLS) regression model was employed. The dataset comprised the success index from the four deployment sites and seven predictor variables (reef plateau coverage, boulder coverage, RI, grazers, SST, Chl a, and water movement). The performance of the PLS model was evaluated based on the explained variance in both the predictor variables and the response variable, in addition to the Root Mean Squared Error of Prediction (RMSEP). The percentage of variance explained by the model components was extracted from the model summary, and the predictive ability was assessed using the R2 and Q2 metrics. The Q2 value was calculated using cross-validated predictions. The analysis was conducted using the pls package in R.

3. Results

3.1. Biological Community

The fish visual census across all sites recorded 31 fish species, as shown in Table S3. In the deployment areas within the Berlengas MPA, Elefante and Galos, 12.0 ± 1.0 and 12.0 ± 2.0 (mean ± sd) different species were recorded. In coastal Peniche, Consolação and Marques-Neves had the lowest species richness values, with 8.7 ± 1.6 and 8.2 ± 2.3, respectively.
Among all reported fish species, five were considered as grazing species. The presence of grazing fish was highest in Cascais (60.3 ± 18.6 ind 100 m2), followed by the Berlengas sites Elefante (44.8 ± 19.5 ind 100 m2) and Galos (15.0 ± 5.9 ind 100 m2). Peniche’s coastline had the lowest presence of grazing fish, with Consolação at 2.1 ± 0.4 ind 100 m2 and Marques-Neves with 1.5 ± 0.4 ind per 100 m2.
Amongst the eight recorded species of invertebrates, three species were considered to be potential Kelp grazers (sea-urchins), as in Table S4. Elefante was the most heavily populated by urchins, with 5.8 ± 0.5 ind 50 m2, and Sphaerechinus granularis was the most representative species. Galos had the second highest urchin abundance, with 1.6 ± 0.24 ind per 50 m2, and with S. granularis again being the most common species. Cascais had the highest diversity of invertebrate species (4.3 ± 1.2) while ranking third in sea urchin abundance at 2.4 ± 0.4 ind per 50 m2. Marques-Neves and Consolação had the lowest urchin abundances, with 1.3 ± 0.6 and 0.6 ± 0.4 ind per 50 m2, respectively.
Our reference Kelp forest Marques-Neves had the highest Kelp abundance (221.1 ± 40.5 ind 50 m2) and presence of the three Kelp species, L. ochroleuca, Phyllariopsis spp., and S. polyschides, as shown in Table S5. Here, L. ochroleuca was the most common Kelp species, with 207.3 ± 66.5 ind 50 m2. The presence of the three Kelp species was also recorded in Consolação. This site had the second highest Kelp abundance (55.5 ± 21.5 ind 50 m2) with an average of 35.2 ± 21.9 L. ochroleuca ind 50 m2. In the other three deployment sites, only Phylariopsis spp. was present. Cascais had the lowest Phylariopsis spp. density (1.3 ± 1.2 ind 50 m2), followed by Elefante and Galos with 29.5 ± 12.1 and 45.9 ± 19.2 ind 50 m2, respectively.

3.2. Bottom Type and Rugosity Index (RI)

The reference site (Marques-Neves) has a 100.0% coverage of the rocky reef plateau substratum (Figure 3). Consolação has a similar topography (99.0% reef plateau), with minimal sand coverage (1.0%). All the deployment sites were below the 5.0% sand coverage threshold, except for Galos with 5.6%. In Elefante, a 44.0% boulder coverage was recorded, while Galos had 36.8%. Cascais registered 17.2% reef plateau coverage and the highest boulder coverage at 78.0%. In terms of Rugosity Index, Marques-Neves was the least rugged with and index of 0.98 (Figure 3). Elefante and Galos RI were 0.91 and 0.90, respectively. Cascais and Consolação were also very similar in rugosity, with an index of 0.84.

3.3. Environmental Data

In situ temperature data are presented in Figure 4A. Significant differences in mean temperatures across sites were detected (F (3, 890) = [80.66]; p = 0.00). Both Berlengas’ sites, Elefante with 17.1 ± 1.4 °C and Galos at 16.7 ± 1.5 °C, were significantly different (p = 0.02). These sites were warmer than those of Peniche (p ≤ 0.05): Marques-Neves at 15.7 ± 1.3 °C and Consolação with 15.4 ± 1.4 °C. Minimum temperature was recorded in Consolação at 13.0 °C, while the highest temperature was recorded in Galos at 20.4 °C. Equipment loss in Cascais prevented in situ seawater temperature assessment.
Satellite SST is presented in Figure 4B. Cascais averaged a higher SST than all other sites at 16.8 ± 1.9 °C, with Elefante having the lowest SST at 16.0 ± 1.7 °C. The maximum recorded SST occurred in Cascais (19.9 °C), while the minimum was recorded in Marques-Neves (13.5 °C). No statistically significant differences were found between all deployment areas (F (4, 115) = [0.85]; p = 0.50).
The chlorophyll a levels are shown in Figure 4C. There were significant differences found between the different areas (F (4, 100) = [8.56]; p = 0.00), with Elefante and Galos having significantly lower concentrations of Chl a (with 1.5 ± 1.4 mg m−3 and 1.0 ± 0.5 mg m−3, respectively), but similar levels to Marques-Neves (2.3 ± 1.2 mg m−3; p > 0.05). Consolação (3.6 ± 3.3 mg−3) and Cascais (4.01 ± 2.4 mg−3) exhibited higher and statistically similar (p = 0.95) concentrations of Chl a.
Measured water movement was revealed to be significantly different between areas (F (4, 350) = [44.01]; p = 0.00). Absolute water movement was significantly higher (p = 0.00) in our reference forest with 0.09 ± 0.08 m s−2 (Figure 4D), while Consolação exhibited the lowest movement at 0.01 ± 0.01 m s−2. Galos (0.03 ± 0.00 m s−2) and Cascais (0.04 ± 0.00 m s−2) had statistically similar averages (p = 1.00), with Elefante (0.03 ± 0.01 m s−2) being statistically placed between those sites and Consolação’s average (p > 0.05).
The nutrient content of our saltwater samples is shown in Figure 5. Phosphate concentrations (PO43−) were statistically different between all sites (F (3, 43) = [4.30]; p = 0.01) (Figure 5A). The reference site had the lowest PO43− concentration with 1.1 ± 0.5 µM, being significantly lower (p = 0.01) than Elefante, where the highest phosphate concentration was recorded, averaging 2.0 ± 0.3 µM. Consolação and Galos were statistically similar (p = 0.96), falling between the other two sites with 1.5 ± 0.8 µM and 1.4 ± 0.3 µM, respectively.
Nitrate concentrations (NO3−) (Figure 5B) also varied significantly (F (3, 43) = [3.91]; p = 0.02), with Marques-Neves having the highest mean concentration at 48.5 ± 2.5 µM. The remaining areas exhibited statistically similar concentrations among themselves (p > 0.05). Within this group, Cascais had the higher nitrate concentration at 46.9 ± 1.6 µM, while both Berlengas sites had significantly lower nitrate levels (p ≤ 0,05) than our reference site, with Elefante at 45.8 ± 0.3 µM and Galos at 46.1 ± 2.2 µM.
Statistically significant differences also occurred with nitrite concentration (NO2−) (Figure 5C) between all areas (F (3, 43) = [5.49]; p = 0.00). Elefante had the lowest concentration of nitrite at 0.7 ± 0.0 µM, being statistically lower than both Consolação and Galos (p ≤ 0,05) with 1.0 ± 0.1 µM and 1.0 ± 0.2 µM, respectively. Marques-Neves was statistically between both groups, averaging 0.9 ± 0.1 µM.

3.4. Retention and Success

The green gravel retention index and success index (both expressed in percentages) are depicted in Figure 6. Regarding retention (Figure 6A), final levels after an 8-month period were consistently lower than those observed at the initial 3-month monitoring period. Consolação began with 85.3% retention, gradually decreasing to our peak final retention rate of 70.5%. Cascais initially exhibited the highest retention rate at 87.8% but concluded the monitoring period with 59.4% retention. Both Berlengas sites experienced sharp declines in retention around the 6-month period, with Elefante dropping from an initial 78.1% to 31.4%, and Galos decreasing from 34.1% to 16.7%.
Variation in success (Figure 6B) displayed similar trends, with all sites ending the monitoring period with lower success indices compared to their initial values. Cascais started with the highest success index of all sites at 41.5%, declining to 35.7% at 6 months and then abruptly dropping to 0.0% by the end of the experiment. Both Berlengas sites saw a spike in success at 6 months, with Galos even reaching the highest success rate across all moments at 48.2%, despite finishing at 4.4% after the 8 months. Elefante started at 8.6%, peaked at 18.2% during the second monitoring campaign, and concluded down at 6.7%. Consolação started monitoring at 16.0%, dropping to 13.5% and ending with the highest final success index among all deployment sites at 11.8%.

3.5. Partial Least Squares Regression Model

The coefficient plot of the first component of a PLS regression model (Figure 7) including the data from the four deployment sites, (R2y = 59.51; Q2 = 54.81; n = 80) show that both Rugosity Index and Reef Plateau coverage had a significant positive influence on success, with variable of importance (VIP) values over 1. Grazer abundance (herbivore fish and urchins) alongside boulder coverage have a high negative importance in explaining success. SST, Chl a, and water movement levels were of less importance for the model (Figure 7).

4. Discussion

In this study, a Kelp reforestation trial was conducted using the green gravel method for the first time in southern Europe. The findings show the potential of using this methodology along Portugal’s coastline, with Laminaria ochroleuca as the selected Kelp species. Environmental factors like nutrient availability, water movement, and temperature did not seem to hinder deployment success. While less rugged and rockier reef plateau-like substratum seemed to improve success, grazing pressure and post-deployment sedimentation (not measured in this study) were likely the main obstacles to green gravel survival. Despite these challenges, we achieved a maximum success rate of ~12% over an 8-month period. Deployment success was higher in Consolação (11.8%), followed by Elefante (6.7%) and Galos (4.4%), while Cascais had no green gravel with attached Kelp.
In terms of green gravel production, all deployed batches attained very similar yields. Although all batches were seeded at the same initial spore density, future deployments could explore different seeding densities or culture improvements such as light intensity [19,24,44]. The method of surface deployment of the gravel was successful, with the Kelps demonstrating high tolerance to the descent turbulence. However, some expected losses occurred, either due to blades detaching from the gravel or the gravel landing Kelp-side down. The spread of the gravel could be improved, especially in rugged locations where it tended to aggregate in nooks and crevices (Figure S1A). Nevertheless, with scaling up in mind, the surface deployment of gravel is undoubtedly an efficient approach.
Grazer abundance revealed marked patterns. There was a clear disparity in sea urchin populations, with S. granularis dominating in the Berlengas MPA (Figure S1B), while Paracentrotus lividus was predominant in coastal Peniche (with a more balanced presence observed in Cascais). Both species are considered voracious herbivores [45,46,47,48]. Regarding grazing fish, the unexpectedly high abundance of Spondyliossoma cantharus in Cascais suggests a potentially significant herbivore pressure on the deployed green gravel (Figure S1C). The relatively low numbers of Sarpa salpa in Berlengas (even completely absent in Galos) are also noteworthy. This gregarious herbivore species is known to form large schools, particularly in the Berlengas MPA [49], but it was quite elusive during our monitoring campaigns. This observation could potentially skew our grazer data, underestimating herbivore pressure in both Elefante and Galos, and it is known that unbalanced fish herbivory can lead to the total collapse of Kelp populations [50,51].
Environmental factors had a seemingly limited impact on the deployed gravel (PLS regression: water movement, temperature, and nutrient availability). Despite some significant differences detected between sites, the assessed values are within the observed range of L. ochroleuca along the Portuguese coast [37,52]. Nevertheless, monitoring these parameters remains crucial for future efforts, particularly using in situ measurements [23].
Regarding bottom topography, coastal Peniche is mainly composed of reef plateau, with it being the sole substratum category in Marques-Neves, achieving an RI of nearly 1 (at 0.98). The lower RI values of Elefante and Galos (in Berlengas) show that these sites are a bit more rugged due to the increase in boulder coverage. Despite Consolação’s RI being lower than that of the Berlengas sites, it showed higher reef plateau coverage, suggesting a rougher plateau structure with shallower crevices and deformations. Cascais had both the lowest RI and the highest boulder coverage, with deeper features where gravel could settle. Initially, these features may seem beneficial for gravel retention and preventing dispersion beyond the monitored area. However, the pooling of gravel in those crevices can later expose them to different challenges (Figure S2) that may hinder deployment success and complicate monitoring efforts. Covering gravel with turf algae (e.g., Asparagopsis armata) that can out-compete and outgrow our Kelp, or even sedimentation after particularly stormy periods, can compromise Kelp development [53]. Indeed, sedimentation, despite not being measured in this study, was likely the main contributor to the unsuccessful results in Cascais. After deployment and between the different monitoring moments, large amounts of sediments (sand) covered the study area, preventing the growth of Kelp and/or promoting the scouring of the deployed green gravel. In addition, the sedimentation also reduced our ability to properly assess the restoration trials’ evolution. These challenges were also evident in Berlengas, where a spike in success and a decline in retention at the 6-month mark could be mainly attributed to a sedimentation episode and a bloom in A. armata coverage during that time of year (Figure S2B), with this invasive seaweed being highly aggressive on the habitat both through rapid growth and the production of a myriad of chemical toxic compounds [54,55]. Consequently, only gravel with visibly healthy and developed L. ochroleuca blades could be found and assessed (Figure S2C).
Nonetheless, these deployments achieved reasonable retention rates, even at the final monitoring moment at 8 months when compared with other restoration efforts. As noted by other authors, the absence/dispersal of gravel from the designated study area does not necessarily signify a loss of restoration efforts [24,27]. It is possible that the seeded gravel was swept away by currents before the Kelp’s holdfast could anchor over the gravel and onto the seafloor (Figure S3A). Even if swept away, if it lands in a suitable place, the Kelp can continue to grow and mature, with Kelp found outside the marked area even developing sori (Figure S3B). This is probably the hallmark of true success and, incidentally, was observed in Consolação.
Several factors may contribute to Consolação’s relative success while other areas failed. As evidenced by the PLS model, both RI and reef plateau coverage seem highly important and conducive to deployment success. This aligns perfectly with Consolação’s topography and contrasts with the characteristics of Cascais, where success was absent. Additionally, our PLS model indicates that higher boulder coverage likely limits success, with Consolação and Cascais positioned at opposite ends of this spectrum in terms of this substratum’s coverage. This may be related to the presence of boulders, which can affect the final position of the stones during deployment, making the conditions less favourable for growth.
A similar scenario applies to grazer pressure. This study’s data confirms herbivory as a hindering factor of Kelp survivability and restoration success [56,57,58,59]. Like the reference forest, Consolação has significantly lower grazer abundance, contrasting with Cascais and Berlengas. In fact, it was hypothesized that in both Berlengas’ sites, the observed success might be reduced over time due to continuous herbivory pressure. Additionally, Consolação likely benefits from nearby Kelp-covered areas. The presence of these nearby alternative feeding grounds may enhance the success of green gravel by reducing the potential impact of herbivory, thereby mitigating this pressure to a greater extent [60]. Further enhancement of this potentially protective factor could be achieved by starting restoration efforts closer to established Kelp forests [12,53], by scaling up beyond experimental settings, increasing the size and number of areas to improve success rates [61], or by doing this next to Kelp cultivation sites. By expanding and improving deployment efforts while extending monitoring periods, we aim to foster the development of fully mature specimens that enhance the survival prospects of newly deployed gravel and/or existing recruits [62,63]. As suggested by Earp et al. [23], further research into timing deployments to maximize retention, promote growth, and mitigate herbivory is essential. However, balancing the choice of deploying in less herbivore-dense areas [56] or areas influenced by unfavourable environmental conditions [57], and the timing of deployment can be challenging depending on the location. For instance, in the present case, deploying immediately after winter storms to optimize initial survival could increase vulnerability to herbivorous species like S. salpa schools during summer in sites such as Berlengas. However, it can be argued that substantially increasing the restoration efforts in terms of the number of deployed stones and deployment area may significantly increase the success rates and, therefore, achieve a successful restoration action.

5. Conclusions

Given that these are the first attempts at reforesting with green gravel in southern Europe, an exposed coastline, achieving an initial deployment success rate of up to 12% should be considered a significant achievement, especially given the experimental scale of this study. These promising outcomes support both the green gravel methodology and the use of L. ochroleuca for reforestation of the Portuguese coastline. These findings provide insights and new guidelines for future deployments, where scaling up efforts and better site selection will help overcome the initial challenges posed by grazing pressure and sedimentation. Overcoming these obstacles, while employing new techniques (e.g., genetically profiling and mixing already established populations) combined with prolonged and persistent deployment efforts, could lead to the establishment of considerable large, mature, and self-sustaining L. ochroleuca forests using the green gravel method on Portugal’s, and similar, coastlines.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/su16219176/s1, Table S1: Details of green gravel cultivations; Table S2: Summary of our seaforestation actions; Table S3: Fish species and abundance at the reference site and deployment areas during 2023; Table S4: Invertebrate species and abundance at the reference site and the deployment areas during 2023; Table S5: Kelp species and abundance recorded at the reference site and the deployment areas during 2023; Figure S1: Gravel spread and herbivory challenges; Figure S2: Kelp monitoring challenges; Figure S3: Signs of success, holdfast development and sori tissue.

Author Contributions

Conceptualization, J.N.F.; methodology, J.N.F., A.F.S.M. and Á.S.-G.; validation, all authors; formal analysis, A.F.S.M. and J.N.F.; investigation, all authors; resources, J.N.F.; writing—original draft preparation, A.F.S.M. with contribution of J.N.F.; writing—review and editing, all authors; project administration and funding acquisition, J.N.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by EEA grants through the project BLUEFORESTS—“Seaforests for blue carbon—natural capital from nature-based solutions” (PT-INNOVATION-0081). This study was also supported by Fundação para a Ciência e a Tecnologia FCT/MCTES (PIDDAC) to MARE (https://doi.org/10.54499/UIDB/04292/2020; https://doi.org/10.54499/UIDP/04292/2020), and to the Associate Laboratory ARNET (https://doi.org/10.54499/LA/P/0069/2020). I. Louro was employed by the company Seaforester. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Informed Consent Statement

Not applicable.

Data Availability Statement

The original contributions presented in the study are included in the article/Supplementary Materials; further inquiries can be directed to the corresponding author.

Acknowledgments

The authors want to acknowledge MARE-IPLEIRIA, SeaForester, and CIIMAR colleagues that supported this work at different stages with their own time.

Conflicts of Interest

Author Inês Louro was employed by the company SeaForester Lda. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  1. Wernberg, T.; Krumhansl, K.; Filbee-Dexter, K.; Pedersen, M.F. Status and Trends for the World’s Kelp Forests. In World Seas: An Environmental Evaluation: Ecological Issues and Environmental Impacts; Academic Press: Cambridge, MA, USA, 2019; Volume III, pp. 57–78. [Google Scholar]
  2. Bennett, S.; Wernberg, T.; Connell, S.D.; Hobday, A.J.; Johnson, C.R.; Poloczanska, E.S. The ‘Great Southern Reef’: Social, Ecological and Economic Value of Australia’s Neglected Kelp Forests. Mar. Freshw. Res. 2015, 67, 47–56. [Google Scholar] [CrossRef]
  3. Peters, J.R.; Reed, D.C.; Burkepile, D.E. Climate and Fishing Drive Regime Shifts in Consumer-Mediated Nutrient Cycling in Kelp Forests. Glob. Chang. Biol. 2019, 25, 3179–3192. [Google Scholar] [CrossRef] [PubMed]
  4. Teagle, H.; Hawkins, S.J.; Moore, P.J.; Smale, D.A. The Role of Kelp Species as Biogenic Habitat Formers in Coastal Marine Ecosystems. J. Exp. Mar. Biol. Ecol. 2017, 492, 81–98. [Google Scholar] [CrossRef]
  5. Graham, M.H. Effects of Local Deforestation on the Diversity and Structure of Southern California Giant Kelp Forest Food Webs. Ecosystems 2004, 7, 341–357. [Google Scholar] [CrossRef]
  6. Steneck, R.S.; Graham, M.H.; Bourque, B.J.; Corbett, D.; Erlandson, J.M.; Estes, J.A.; Tegner, M.J. Kelp Forest Ecosystems: Biodiversity, Stability, Resilience and Future. Environ. Conserv. 2002, 29, 436–459. [Google Scholar] [CrossRef]
  7. Salomidi, M.; Katsanevakis, S.; Borja, Á.; Braeckman, U.; Damalas, D.; Galparsoro, I.; Mifsud, R.; Mirto, S.; Pascual, M.; Pipitone, C.; et al. Assessment of Goods and Services, Vulnerability, and Conservation Status of European Seabed Biotopes: A Stepping Stone towards Ecosystem-Based Marine Spatial Management. Mediterr. Mar. Sci. 2012, 13, 49–88. [Google Scholar] [CrossRef]
  8. Bertocci, I.; Araújo, R.; Oliveira, P.; Sousa-Pinto, I. REVIEW: Potential Effects of Kelp Species on Local Fisheries. J. Appl. Ecol. 2015, 52, 1216–1226. [Google Scholar] [CrossRef]
  9. Wing, S.R.; Durante, L.M.; Connolly, A.J.; Sabadel, A.J.M.; Wing, L.C. Overexploitation and Decline in Kelp Forests Inflate the Bioenergetic Costs of Fisheries. Glob. Ecol. Biogeogr. 2022, 31, 621–635. [Google Scholar] [CrossRef]
  10. Smale, D.A.; Burrows, M.T.; Moore, P.; O’Connor, N.; Hawkins, S.J. Threats and Knowledge Gaps for Ecosystem Services Provided by Kelp Forests: A Northeast Atlantic Perspective. Ecol. Evol. 2013, 3, 4016–4038. [Google Scholar] [CrossRef]
  11. Eger, A.M.; Marzinelli, E.M.; Beas-Luna, R.; Blain, C.O.; Blamey, L.K.; Byrnes, J.E.K.; Carnell, P.E.; Choi, C.G.; Hessing-Lewis, M.; Kim, K.Y.; et al. The Value of Ecosystem Services in Global Marine Kelp Forests. Nat. Commun. 2023, 14, 1894. [Google Scholar] [CrossRef]
  12. Campbell, A.H.; Marzinelli, E.M.; Vergés, A.; Coleman, M.A.; Steinberg, P.D. Towards Restoration of Missing Underwater Forests. PLoS ONE 2014, 9, e84106. [Google Scholar] [CrossRef] [PubMed]
  13. Araújo, R.M.; Assis, J.; Aguillar, R.; Airoldi, L.; Bárbara, I.; Bartsch, I.; Bekkby, T.; Christie, H.; Davoult, D.; Derrien-Courtel, S.; et al. Status, Trends and Drivers of Kelp Forests in Europe: An Expert Assessment. Biodivers. Conserv. 2016, 25, 1319–1348. [Google Scholar] [CrossRef]
  14. Krumhansl, K.A.; Okamoto, D.K.; Rassweiler, A.; Novak, M.; Bolton, J.J.; Cavanaugh, K.C.; Connell, S.D.; Johnson, C.R.; Konar, B.; Ling, S.D.; et al. Global Patterns of Kelp Forest Change over the Past Half-Century. Proc. Natl. Acad. Sci. USA 2016, 113, 13785–13790. [Google Scholar] [CrossRef] [PubMed]
  15. Filbee-Dexter, K.; Wernberg, T. Rise of Turfs: A New Battlefront for Globally Declining Kelp Forests. Bioscience 2018, 68, 64–76. [Google Scholar] [CrossRef]
  16. Martínez, B.; Radford, B.; Thomsen, M.S.; Connell, S.D.; Carreño, F.; Bradshaw, C.J.A.; Fordham, D.A.; Russell, B.D.; Gurgel, C.F.D.; Wernberg, T. Distribution Models Predict Large Contractions of Habitat-Forming Seaweeds in Response to Ocean Warming. Divers. Distrib. 2018, 24, 1350–1366. [Google Scholar] [CrossRef]
  17. Duarte, C.M.; Agusti, S.; Barbier, E.; Britten, G.L.; Castilla, J.C.; Gattuso, J.-P.; Fulweiler, R.W.; Hughes, T.P.; Knowlton, N.; Lovelock, C.E.; et al. Rebuilding Marine Life. Nature 2020, 580, 39–51. [Google Scholar] [CrossRef]
  18. European Parliament and the Council. European Commission Regulation of the European Parliament and of the Council on Nature Restoration and Amending Regulation (EU) 2022/869; PE-CONS 74/23; European Parliament and the Council: Brussels, Belgium, 2024. [Google Scholar]
  19. Alsuwaiyan, N.A.; Filbee-Dexter, K.; Vranken, S.; Burkholz, C.; Cambridge, M.; Coleman, M.A.; Wernberg, T. Green Gravel as a Vector of Dispersal for Kelp Restoration. Front. Mar. Sci. 2022, 9, 910417. [Google Scholar] [CrossRef]
  20. Eger, A.M.; Vergés, A.; Choi, C.G.; Christie, H.; Coleman, M.A.; Fagerli, C.W.; Fujita, D.; Hasegawa, M.; Kim, J.H.; Mayer-Pinto, M.; et al. Financial and Institutional Support Are Important for Large-Scale Kelp Forest Restoration. Front. Mar. Sci. 2020, 7, 535277. [Google Scholar] [CrossRef]
  21. Verdura, J.; Sales, M.; Ballesteros, E.; Cefalì, M.E.; Cebrian, E. Restoration of a Canopy-Forming Alga Based on Recruitment Enhancement: Methods and Long-Term Success Assessment. Front. Plant Sci. 2018, 9, 416710. [Google Scholar] [CrossRef]
  22. Wood, G.V.; Filbee-Dexter, K.; Coleman, M.A.; Valckenaere, J.; Aguirre, J.D.; Bentley, P.M.; Carnell, P.; Dawkins, P.D.; Dykman, L.N.; Earp, H.S.; et al. Upscaling Marine Forest Restoration: Challenges, Solutions and Recommendations from the Green Gravel Action Group. Front. Mar. Sci. 2024, 11, 1364263. [Google Scholar] [CrossRef]
  23. Earp, H.S.; Smale, D.A.; Pérez-Matus, A.; Gouraguine, A.; Shaw, P.W.; Moore, P.J. A Quantitative Synthesis of Approaches, Biases, Successes, and Failures in Marine Forest Restoration, with Considerations for Future Work. Aquat. Conserv. Mar. Freshw. Ecosyst. 2022, 32, 1717–1731. [Google Scholar] [CrossRef]
  24. Fredriksen, S.; Filbee-Dexter, K.; Norderhaug, K.M.; Steen, H.; Bodvin, T.; Coleman, M.A.; Moy, F.; Wernberg, T. Green Gravel: A Novel Restoration Tool to Combat Kelp Forest Decline. Sci. Rep. 2020, 10, 3983. [Google Scholar] [CrossRef] [PubMed]
  25. Falace, A.; Kaleb, S.; De La Fuente, G.; Asnaghi, V.; Chiantore, M. Ex Situ Cultivation Protocol for Cystoseira amentacea var. stricta (Fucales, Phaeophyceae) from a Restoration Perspective. PLoS ONE 2018, 13, e0193011. [Google Scholar] [CrossRef] [PubMed]
  26. Vanderklift, M.A.; Doropoulos, C.; Gorman, D.; Leal, I.; Minne, A.J.P.; Statton, J.; Steven, A.D.L.; Wernberg, T. Using Propagules to Restore Coastal Marine Ecosystems. Front. Mar. Sci. 2020, 7, 565403. [Google Scholar] [CrossRef]
  27. Earp, H.S.; Smale, D.A.; Catherall, H.J.N.; Moore, P.J. An Assessment of the Utility of Green Gravel as a Kelp Restoration Tool in Wave-Exposed Intertidal Habitats. J. Mar. Biol. Assoc. UK 2024, 104, e28. [Google Scholar] [CrossRef]
  28. Wernberg, T.; Thomsen, M.S.; Baum, J.K.; Bishop, M.J.; Bruno, J.F.; Coleman, M.A.; Filbee-Dexter, K.; Gagnon, K.; He, Q.; Murdiyarso, D.; et al. Impacts of Climate Change on Marine Foundation Species. Ann. Rev. Mar. Sci. 2024, 16, 247–282. [Google Scholar] [CrossRef]
  29. Shears, N.T.; Babcock, R.C. Marine Reserves Demonstrate Top-down Control of Community Structure on Temperate Reefs. Oecologia 2002, 132, 131–142. [Google Scholar] [CrossRef]
  30. Azevedo, J.; Franco, J.N.; Vale, C.G.; Lemos, M.F.L.; Arenas, F. Rapid Tropicalization Evidence of Subtidal Seaweed Assemblages along a Coastal Transitional Zone. Sci. Rep. 2023, 13, 11720. [Google Scholar] [CrossRef]
  31. Pereira, T.R.; Engelen, A.H.; Pearson, G.A.; Valero, M.; Serrão, E.A. Population Dynamics of Temperate Kelp Forests near Their Low-Latitude Limit. Aquat. Bot. 2017, 139, 8–18. [Google Scholar] [CrossRef]
  32. Pereira, T.R.; Azevedo, I.C.; Oliveira, P.; Silva, D.M.; Sousa-Pinto, I. Life History Traits of Laminaria ochroleuca in Portugal: The Range-Center of Its Geographical Distribution. Aquat. Bot. 2019, 152, 1–9. [Google Scholar] [CrossRef]
  33. Biskup, S.; Bertocci, I.; Arenas, F.; Tuya, F. Functional Responses of Juvenile Kelps, Laminaria ochroleuca and Saccorhiza polyschides, to Increasing Temperatures. Aquat. Bot. 2014, 113, 117–122. [Google Scholar] [CrossRef]
  34. Fernández, C. The Retreat of Large Brown Seaweeds on the North Coast of Spain: The Case of Saccorhiza polyschides. Eur. J. Phycol. 2011, 46, 352–360. [Google Scholar] [CrossRef]
  35. Soares, C.; Švarc-Gajić, J.; Oliva-Teles, M.T.; Pinto, E.; Nastić, N.; Savić, S.; Almeida, A.; Delerue-Matos, C. Mineral Composition of Subcritical Water Extracts of Saccorhiza polyschides, a Brown Seaweed Used as Fertilizer in the North of Portugal. J. Mar. Sci. Eng. 2020, 8, 244. [Google Scholar] [CrossRef]
  36. Provasoli, L. Media and Prospects for the Cultivation of Marine Algae. In Cultures and Collections of Algae, Proceedings of the US-Japan Conference, Hakone, Japan, 12–15 September 1966; Japanese Society of Plant Physiology: Kyoto, Japan, 1968; pp. 63–75. [Google Scholar]
  37. Franco, J.N.; Arenas, F.; Sousa-Pinto, I.; de los Santos, C.B. Snapshot of Macroalgae and Fish Assemblages in Temperate Reefs in the Southern European Atlantic Ecoregion. Diversity 2020, 12, 26. [Google Scholar] [CrossRef]
  38. Henriques, S.; Pais, M.P.; Costa, M.J.; Cabral, H. Development of a Fish-Based Multimetric Index to Assess the Ecological Quality of Marine Habitats: The Marine Fish Community Index. Mar. Pollut. Bull. 2008, 56, 1913–1934. [Google Scholar] [CrossRef]
  39. Henriques, S.; Pais, M.P.; Costa, M.J.; Cabral, H.N. Seasonal Variability of Rocky Reef Fish Assemblages: Detecting Functional and Structural Changes Due to Fishing Effects. J. Sea Res. 2013, 79, 50–59. [Google Scholar] [CrossRef]
  40. Sala, E.; Zabala, M. Fish Predation and the Structure of the Sea Urchin Paracentrotus lividus Populations in the NW Mediterranean. Mar. Ecol. Prog. Ser. 1996, 140, 71–81. [Google Scholar] [CrossRef]
  41. Horta, M.; Costa, M.J.; Cabral, H. Spatial and Trophic Niche Overlap between Diplodus bellottii and Diplodus vulgaris in the Tagus Estuary, Portugal. J. Mar. Biol. Assoc. UK 2004, 84, 837–842. [Google Scholar] [CrossRef]
  42. Walbridge, S.; Slocum, N.; Pobuda, M.; Wright, D.J. Unified Geomorphological Analysis Workflows with Benthic Terrain Modeler. Geosciences 2018, 8, 94. [Google Scholar] [CrossRef]
  43. Acker, J.G.; Leptoukh, G. Online Analysis Enhances Use of NASA Earth Science Data. EOS Trans. Am. Geophys. Union 2007, 88, 14–17. [Google Scholar] [CrossRef]
  44. Chemello, S.; Pinto, I.S.; Pereira, T.R. Optimising Kelp Cultivation to Scale up Habitat Restoration Efforts: Effect of Light Intensity on “Green Gravel” Production. Hydrobiology 2023, 2, 347–353. [Google Scholar] [CrossRef]
  45. Boudouresque, C.F.; Verlaque, M. Ecology of Paracentrotus lividus. In Developments in Aquaculture and Fisheries Science; Elsevier: Amsterdam, The Netherlands, 2001; Volume 32, pp. 177–216. [Google Scholar] [CrossRef]
  46. Boudouresque, C.F.; Verlaque, M. Paracentrotus lividus. In Developments in Aquaculture and Fisheries Science; Elsevier: Amsterdam, The Netherlands, 2020; Volume 43, pp. 447–485. [Google Scholar]
  47. Guillou, M.; Grall, J.; Connan, S. Can Low Sea Urchin Densities Control Macro-Epiphytic Biomass in a North-East Atlantic Maerl Bed Ecosystem (Bay of Brest, Brittany, France)? J. Mar. Biol. Assoc. UK 2002, 82, 867–876. [Google Scholar] [CrossRef]
  48. Tsirintanis, K.; Sini, M.; Doumas, O.; Trygonis, V.; Katsanevakis, S. Assessment of Grazing Effects on Phytobenthic Community Structure at Shallow Rocky Reefs: An Experimental Field Study in the North Aegean Sea. J. Exp. Mar. Biol. Ecol. 2018, 503, 31–40. [Google Scholar] [CrossRef]
  49. Vasco-Rodrigues, N.; Mendes, S.; Franco, J.; Castanheira, M.F.; Castro, N.; Maranhão, P. Fish Diversity in the Berlengas Natural Reserve (Portugal), a Marine Protected Area. Ecologia 2011, 3, 35–43. [Google Scholar]
  50. Barrientos, S.; Piñeiro-Corbeira, C.; Barreiro, R. Temperate Kelp Forest Collapse by Fish Herbivory: A Detailed Demographic Study. Front. Mar. Sci. 2022, 9, 817021. [Google Scholar] [CrossRef]
  51. Vergés, A.; Doropoulos, C.; Malcolm, H.A.; Skye, M.; Garcia-Pizá, M.; Marzinelli, E.M.; Campbell, A.H.; Ballesteros, E.; Hoey, A.S.; Vila-Concejo, A.; et al. Long-Term Empirical Evidence of Ocean Warming Leading to Tropicalization of Fish Communities, Increased Herbivory, and Loss of Kelp. Proc. Natl. Acad. Sci. USA 2016, 113, 13791–13796. [Google Scholar] [CrossRef]
  52. Franco, J.N.; Tuya, F.; Bertocci, I.; Rodríguez, L.; Martínez, B.; Sousa-Pinto, I.; Arenas, F. The ‘Golden Kelp’ Laminaria ochroleuca under Global Change: Integrating Multiple Eco-physiological Responses with Species Distribution Models. J. Ecol. 2018, 106, 47–58. [Google Scholar] [CrossRef]
  53. Eger, A.M.; Marzinelli, E.M.; Christie, H.; Fagerli, C.W.; Fujita, D.; Gonzalez, A.P.; Hong, S.W.; Kim, J.H.; Lee, L.C.; McHugh, T.A.; et al. Global Kelp Forest Restoration: Past Lessons, Present Status, and Future Directions. Biol. Rev. 2022, 97, 1449–1475. [Google Scholar] [CrossRef]
  54. Silva, C.O.; Lemos, M.F.L.; Gaspar, R.; Gonçalves, C.; Neto, J.M. The Effects of the Invasive Seaweed Asparagopsis armata on Native Rock Pool Communities: Evidences from Experimental Exclusion. Ecol. Indic. 2021, 125, 107463. [Google Scholar] [CrossRef]
  55. Ponte, J.M.S.; Seca, A.M.L.; Barreto, M.C. Asparagopsis Genus: What We Really Know About Its Biological Activities and Chemical Composition. Molecules 2022, 27, 1787. [Google Scholar] [CrossRef] [PubMed]
  56. Carney, L.; Waaland, J.; Klinger, T.; Ewing, K. Restoration of the Bull Kelp Nereocystis luetkeana in Nearshore Rocky Habitats. Mar. Ecol. Prog. Ser. 2005, 302, 49–61. [Google Scholar] [CrossRef]
  57. Duggins, D.; Eckman, J.; Siddon, C.; Klinger, T. Interactive Roles of Mesograzers and Current Flow in Survival of Kelps. Mar. Ecol. Prog. Ser. 2001, 223, 143–155. [Google Scholar] [CrossRef]
  58. Taylor, D.I.; Schiel, D.R. Algal Populations Controlled by Fish Herbivory across a Wave Exposure Gradient on Southern Temperate Shores. Ecology 2010, 91, 201–211. [Google Scholar] [CrossRef]
  59. Franco, J.; Wernberg, T.; Bertocci, I.; Duarte, P.; Jacinto, D.; Vasco-Rodrigues, N.; Tuya, F. Herbivory Drives Kelp Recruits into ‘Hiding’ in a Warm Ocean Climate. Mar. Ecol. Prog. Ser. 2015, 536, 1–9. [Google Scholar] [CrossRef]
  60. Morris, R.L.; Hale, R.; Strain, E.M.A.; Reeves, S.E.; Vergés, A.; Marzinelli, E.M.; Layton, C.; Shelamoff, V.; Graham, T.D.J.; Chevalier, M.; et al. Key Principles for Managing Recovery of Kelp Forests through Restoration. Bioscience 2020, 70, 688–698. [Google Scholar] [CrossRef]
  61. Hambäck, P.A.; Englund, G. Patch Area, Population Density and the Scaling of Migration Rates: The Resource Concentration Hypothesis Revisited. Ecol. Lett. 2005, 8, 1057–1065. [Google Scholar] [CrossRef]
  62. Eger, A.M.; Aguirre, J.D.; Altamirano, M.; Arafeh-Dalmau, N.; Arroyo, N.L.; Bauer-Civiello, A.M.; Beas-Luna, R.; Bekkby, T.; Bennett, S.; Bernal, B.; et al. The Kelp Forest Challenge: A Collaborative Global Movement to Protect and Restore 4 Million Hectares of Kelp Forests. J. Appl. Phycol. 2024, 36, 951–964. [Google Scholar] [CrossRef]
  63. Layton, C.; Shelamoff, V.; Cameron, M.J.; Tatsumi, M.; Wright, J.T.; Johnson, C.R. Resilience and Stability of Kelp Forests: The Importance of Patch Dynamics and Environment-Engineer Feedbacks. PLoS ONE 2019, 14, e0210220. [Google Scholar] [CrossRef]
Sustainability 16 09176 g001
Figure 1. (A) Section of the western continental Portuguese coast where the deployments took place. Three distinct zones were selected: (B) The coast of Peniche, with Marques-Neves as the reference Kelp forest (I) and Consolação (II); (C) In the Berlengas Islands at the sites Elefante (III) and Galos (IV); (D) and in the Cascais area at Boca do Inferno (V).
Figure 1. (A) Section of the western continental Portuguese coast where the deployments took place. Three distinct zones were selected: (B) The coast of Peniche, with Marques-Neves as the reference Kelp forest (I) and Consolação (II); (C) In the Berlengas Islands at the sites Elefante (III) and Galos (IV); (D) and in the Cascais area at Boca do Inferno (V).
Sustainability 16 09176 g001
Sustainability 16 09176 g002
Figure 2. (A) Technique used to deploy the gravel from the surface; (B) Scientific divers deployed buoys marking the area for deployment (100 m2) in Berlengas at the Galos site; (C) close-up of the deployed green gravel.
Figure 2. (A) Technique used to deploy the gravel from the surface; (B) Scientific divers deployed buoys marking the area for deployment (100 m2) in Berlengas at the Galos site; (C) close-up of the deployed green gravel.
Sustainability 16 09176 g002
Sustainability 16 09176 g003
Figure 3. Percentage of each bottom substratum category (reef plateau, boulders, and sand) measured in 25 m transects at the different studied sites (n = 5). Numbers within each bar indicate the site’s Rugosity Index (RI) achieved (n = 5).
Figure 3. Percentage of each bottom substratum category (reef plateau, boulders, and sand) measured in 25 m transects at the different studied sites (n = 5). Numbers within each bar indicate the site’s Rugosity Index (RI) achieved (n = 5).
Sustainability 16 09176 g003
Sustainability 16 09176 g004
Figure 4. (A) Average seawater temperature (measured in situ); (B) sea surface temperature—SST; (C) near surface chlorophyll a level—Chla a, and (D) absolute average water movement in all monitored sites. Statistically significant different groups (a, b, and c) are shown (Tukey’s HSD; p ≤ 0.05). Error bars are ±2 sd of means (n.a. = not assessed).
Figure 4. (A) Average seawater temperature (measured in situ); (B) sea surface temperature—SST; (C) near surface chlorophyll a level—Chla a, and (D) absolute average water movement in all monitored sites. Statistically significant different groups (a, b, and c) are shown (Tukey’s HSD; p ≤ 0.05). Error bars are ±2 sd of means (n.a. = not assessed).
Sustainability 16 09176 g004
Sustainability 16 09176 g005
Figure 5. (A) Concentration of phosphates, (B) nitrates, and (C) nitrites at depth at all monitored sites. Statistically significant different groups (a and b) are shown (Tukey’s HSD; p ≤ 0.05). Error bars are ±2 sd of means. (n = 9 per site).
Figure 5. (A) Concentration of phosphates, (B) nitrates, and (C) nitrites at depth at all monitored sites. Statistically significant different groups (a and b) are shown (Tukey’s HSD; p ≤ 0.05). Error bars are ±2 sd of means. (n = 9 per site).
Sustainability 16 09176 g005
Sustainability 16 09176 g006
Figure 6. (A) Gravel retention and (B) deployment success at the four deployment sites in the three monitoring moments after 3, 6, and 8 months of deployment.
Figure 6. (A) Gravel retention and (B) deployment success at the four deployment sites in the three monitoring moments after 3, 6, and 8 months of deployment.
Sustainability 16 09176 g006
Sustainability 16 09176 g007
Figure 7. Coefficient plot of the first component of the PLS regression model. The model included data from all the deployment sites to explain the green gravel success index. Importance was deemed as high if the coefficient was higher than 0.15 (n = 80).
Figure 7. Coefficient plot of the first component of the PLS regression model. The model included data from all the deployment sites to explain the green gravel success index. Importance was deemed as high if the coefficient was higher than 0.15 (n = 80).
Sustainability 16 09176 g007
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Marques, A.F.S.; Sanchéz-Gallego, Á.; Correia, R.R.; Sousa-Pinto, I.; Chemello, S.; Louro, I.; Lemos, M.F.L.; Franco, J.N. Assessing Atlantic Kelp Forest Restoration Efforts in Southern Europe. Sustainability 2024, 16, 9176. https://doi.org/10.3390/su16219176

AMA Style

Marques AFS, Sanchéz-Gallego Á, Correia RR, Sousa-Pinto I, Chemello S, Louro I, Lemos MFL, Franco JN. Assessing Atlantic Kelp Forest Restoration Efforts in Southern Europe. Sustainability. 2024; 16(21):9176. https://doi.org/10.3390/su16219176

Chicago/Turabian Style

Marques, Alexandre F. S., Álvaro Sanchéz-Gallego, Rodrigo R. Correia, Isabel Sousa-Pinto, Silvia Chemello, Inês Louro, Marco F. L. Lemos, and João N. Franco. 2024. "Assessing Atlantic Kelp Forest Restoration Efforts in Southern Europe" Sustainability 16, no. 21: 9176. https://doi.org/10.3390/su16219176

APA Style

Marques, A. F. S., Sanchéz-Gallego, Á., Correia, R. R., Sousa-Pinto, I., Chemello, S., Louro, I., Lemos, M. F. L., & Franco, J. N. (2024). Assessing Atlantic Kelp Forest Restoration Efforts in Southern Europe. Sustainability, 16(21), 9176. https://doi.org/10.3390/su16219176

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop