Early ecological responses of bentho-demersal communities to new Fishery No-Take Zones in the NW Mediterranean: evidence of passive restoration
Authors:
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MarinaBiel-Cabanelas1,2✉Emailmarinabiel@icm.csic.es
AndreuSantín3
GabrielRivas-Mena4
SofiaFaramelli1,2
CristinaMartín1
FabiolaMariaCecchini1,5
AntoniSánchez1,2
MiguelLópez1,2
JoséAntonioGarcía1
NixonBahamon1
JacopoAguzzi1
JoanB.Company1
JordiGrinyó1
1Institut de Ciències del Mar (ICM-CSIC)BarcelonaSpain
2Program in BiodiversityUniversitat Autonoma de Barcelona08193Bellaterra, BarcelonaSpain
3CIIMAR–Interdisciplinary Centre of Marine and Environmental ResearchPortoPortugal
4Institute of Marine BiologyUniversity of Montenegro85330KotorMontenegro
5Departament de Biologia Evolutiva, Facultat de Ciencies de la TerraEcologia i Ciencies Ambientals, Universitat de BarcelonaBarcelonaSpain
Marina Biel-Cabanelas1,2; Andreu Santín3; Gabriel Rivas-Mena4; Sofia Faramelli1,2; Cristina Martín1; Fabiola Maria Cecchini1,5; Antoni Sánchez1,2; Miguel López1,2; José Antonio García1; Nixon Bahamon1; Jacopo Aguzzi1; Joan B. Company1; Jordi Grinyó1
1. Institut de Ciències del Mar (ICM-CSIC), Barcelona, Spain
2. Program in Biodiversity, Universitat Autonoma de Barcelona, Bellaterra 08193, Barcelona, Spain
3. CIIMAR–Interdisciplinary Centre of Marine and Environmental Research, Porto, Portugal
4. Institute of Marine Biology, University of Montenegro, Kotor, 85330, Montenegro
5. Departament de Biologia Evolutiva, Ecologia i Ciencies Ambientals, Facultat de Ciencies de la Terra, Universitat de Barcelona, Barcelona, Spain
Corresponding author: marinabiel@icm.csic.es / ORCID: 0000-0002-7770-8256
Abstract
Fishery no-take Zones (FNTZs) are increasingly being used as a spatial management tool to promote marine habitat recovery and enhance the sustainable use of fishery resources. To evaluate their effectiveness in shelf edge and upper continental slope habitats, a characterization of sessile and motile fauna within eleven FNTZs implemented along the Catalan margin was conducted. Surveys were conducted between 2023 and 2024 using Remote Operated Vehicle (ROV) video-transects across two depth ranges (100–300 m and > 300 m), covering both protected and adjacent Control areas. Sessile and motile fauna were analyzed separately, to assess the different response in organisms with different life strategies. Results revealed that the effects of protection varied across depths and locations. Sessile fauna exhibited significantly higher densities, richness, and diversity in several FNTZs, especially at the shelf edge, while motile fauna displayed less consistent trends. Community analyses showed differences between protected and control sites, with FNTZs hosting more habitat-forming species opposed to motile species which were more represented in Control areas. Despite initial signs of structural differentiation, results indicate that ecological recovery in soft-sediment at this depth remains slow and spatially variable, likely restricted by the habitat physical degradation consequence of decades of trawling. This research provides the first regional-scale, non-destructive assessment of FNTZs effectiveness on Mediterranean soft sediments and establishes critical reference data for future monitoring.
Keywords:
ecological restoration
baseline
monitoring
spatial management
bentho-demersal communities
soft sediments habitats
no-take MPAs
Declarations
The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
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Data Availability
All data supporting the findings of this study are available within the paper and its Supplementary Material. Further information is available from the authors upon reasonable request, subject to permission from the Institut de Ciències del Mar.
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1. Introduction
Marine soft sediments make up approximately 70% of the planet's seafloor (Snelgrove, 1999; Thrush et al. 2001), forming the most extensive continuous ecosystem on Earth and its largest carbon reservoir (Dutkiewicz et al. 2015). These habitats have long been considered to have little topographic structure (Thrush et al. 2001), but sedimentary environments are much more heterogeneous and spatially complex than previously recognized (Zajac, 2008; Sigwart et al. 2023). These systems lack abiotic three-dimensional structures, but host biogenic structures or structures made by organisms that play a critical role in controlling abiotic conditions and resources (Bruschetti, 2019). These organisms are known as 'ecosystem engineers' (sensu Jones et al. 1994). By modifying the three-dimensional structure above and below the sediment surface, they influence sediment dynamics (Sardà & Aguzzi, 2012; Aguzzi et al. 2023), thereby increasing patchiness and habitat diversity (Bouma et al. 2009). This facilitates the settling of diverse communities otherwise incapable of survival in the same region, thus supporting a high diversity of fauna (Snelgrove, 1999; Thrush et al. 2001; Pusceddu et al. 2014; Santín et al. 2021). Notwithstanding, soft bottom communities are some of the most productive fishing grounds across the globe (Snelgrove, 1999; Eigaard et al. 2017). Due to their important secondary production, soft-bottom communities are targeted and severely disturbed by fishing activities on continental shelves, specifically, accounting for 61% of global bottom trawling fisheries (Oberle et al. 2016), which has resulted in decades of anthropogenic impact caused by human exploitation (Dayton et al. 1995; Jennings & Kaiser, 1998; Puig et al. 2012; Durán et al. 2023).
Bottom trawling is generally recognized as one of the most environmentally disturbing activities carried out at sea (Jennings & Kaiser, 1998; Thrush et al. 1998). This fishing method is characterized by being a non-selective fishing practice that requires the towing of large and wide nets and heavy metal bottom-contact structures (up to several tonnes in air (Jones, 1992), also known as otter doors, to keep the net open as it is dragged along the seabed to catch demersal species. Even since its initial implementation, bottom trawling already raised concerns among marine biologists and environmentalists (Steadman et al. 2021; Jarvis & Brennan, 2024). In this regard, it is noteworthy to mention that even the earliest known reference to trawling (the Commons' petition to King Edward III in 1376, cited in Bolster, 2012) calls for its abolition due to its detrimental effects on fish populations and habitats. In the Mediterranean, a similar fishing technique was used in the lagoons of Albufera (Valencia, Spain) during the 13th century and later transferred to sea in the 17th century (Martínez Shaw & Díaz, 1988; Sacchi, 2008). Petitions to decision-makers to restrict the use of these bottom “proto” trawl fisheries were also mentioned in the 16th century in the Netherlands, the 17th century in Japan, the 18th century in France and the 19th in Spain (de Groot, 1984; Sacchi, 2008; Steadman et al. 2021). Nevertheless, the practice has persisted over time (Jarvis & Brennan, 2024).
Historically, from the 1850s onwards, industrialization in Europe and North America drove fishing vessels toward more intensive operations. Steam-powered hauling in the 1870s and engines in the 1880s increased fishing capacity (Palanques et al. 2006; Payne et al. 2009; Steadman et al. 2021), and from the 1930s, trawling reached the northwestern Mediterranean continental slope (Bas 1985; Palanques et al. 2006; Puig et al. 2012). Larger industrial trawlers and post-World War II technologies, including extended-range fishing and echosounders (Thermes et al. 2023; Jarvis & Brennan, 2024), amplified fishing intensity and seafloor impacts (Palanques et al. 2006; Bolster, 2012; Puig et al. 2012; Steadman et al. 2021). Nowadays, on a global scale, approximately 22 million km2 of seabed is affected by commercial trawling annually (Halpern et al. 2008).
The chronic trawling activity has been proven to directly impact the ecosystem by removing large amounts of biomass, reducing the abundance of target fish populations (Clark et al. 2016), and producing discards composed of non-commercial species or undersized individuals (Hall et al. 2000). In this sense, ecosystem functioning is influenced by the damage to the seabed and its associated communities with checked effects such as a decline in the abundance of bioengineering species, which reduces habitat complexity (Watling & Norse, 1998; Roberts, 2002; Colloca et al. 2004; Gray et al. 2006; Grinyó et al. 2020). Furthermore, bottom trawling structurally modifies the seafloor by removing topographical features such as ripples, mesophotic reefs and even boulders over 30 tonnes weight (Atkinson, 2012; Brennan et al. 2016), and resuspends sediments which in turn negatively affect benthic communities (Palanques et al. 2006; Pusceddu et al. 2014; Wilson et al. 2015; Arjona-Camas et al. 2021; Bilan et al. 2023). These effects are significant and have the potential to induce irreversible changes in community structure and composition (Pusceddu et al. 2014; Clark et al. 2016). Still, despite its aforementioned consequences, bottom-trawling fishing has become an enforced component of the global food supply (Hiddink et al. 2020; Steadman et al. 2021) to meet the current and growing demand for sea-sourced food, which globally increased by 127% from 1962 to 2022 (FAO, 2024), landing around 19 million tons of fish and invertebrates annually (Amoroso et al. 2018).
In the Mediterranean Sea, trawling vessels operate between 50 and 800 m (Gorelli et al. 2016) and its footprint in shallow areas (< 200 m) ranges between 57 and 86% (Eigaard et al. 2017) and from 37–64% in deeper areas (> 200m) (Amoroso et al. 2018). Currently, in the Mediterranean this fishing practice generates the highest revenues of any fishing gear used (United Nations Environment Programme, 2024), being responsible for 41% of the annual turnover in the region (FAO, 2023). In this context, the Mediterranean and the Black Sea ranked second among the FAO's 16 Major Fishing Areas in terms of the highest rate of stocks fished at unsustainable levels in 2021 (58%), surpassed only by the Southeast Pacific (66.7%) (FAO, 2023). Consequently, overfishing has been identified as one of the main causes of biodiversity loss in this region (European Environment Agency, 2019).
Since 1992, with the publication of the EU Habitats Directive, the conservation of certain European marine regions has improved through management incentives of certain marine species and habitats (Publications Office of the European Union, 2021). However, a significant portion of these areas remain in unfavorable conditions due to anthropogenic pressures surpassing conservation efforts (European Environment Agency, 2019). Effective management of the major stresses, such as fishing activity, is a crucial element for conservation. In this regard, the European Union’s Common Fishery Policy (CFP) aims to reduce fishing effort in the European Seas through permanent and temporary closures, as part of its key management objectives (Pranovi et al. 2015; ICATMAR, 2023;). Spatiotemporal closures, also known as Marine Protected Areas (MPAs) can be subject to varying degrees of protection, ranging from areas designated as partially protected, where specific uses and extractive activities are still permitted, to fully protected areas or Fishery No-Take Zones (FNTZs), which are areas where all extractive fishing activities are strictly prohibited (Day et al. 2012; Giakoumi et al. 2017; Vigo et al. 2024). This spatial management strategy is implemented in diverse ways across many countries (Fraschetti et al. 2002), and has been identified as a valuable tool for the conservation and recovery of marine ecosystems and their associated ecosystem services (Leenhardt et al. 2015; Giakoumi et al. 2017).
The prohibition of fishing within MPAs has been documented to provide numerous benefits. These include increase on the abundance, richness, and biomass of target fish species, with a shift towards bigger and older individuals than in previously exploited populations (Bell, 1983; García-Rubies & Zabala, 1990; Francour, 1991, 1994; Dufour et al. 1995té et al. 2001; Harmelin, 1995; Halpern, 2003). Marine Protected Areas also contribute to the conservation of biodiversity, the protection of sources of larvae and biomass, and the provision of a hedge against fisheries management failures (Sanchirico et al. 2006), as well as numerous socio-economic benefits (Badalamenti et al. 2000). Such benefits can extend beyond reserve boundaries and are observed in adjacent areas as a result of the spillover (sensu Rowley, 1994) of adults and juveniles from the FNTZ to neighboring fishing grounds (McClanahan & Mangi, 2000; Stobart et al. 2009; Lenihan et al. 2021; Sala-Coromina et al. 2021; Vigo et al. 2023), thereby providing additional socio-economic benefits such as an increased fishery yield (Badalamenti et al. 2000). Studies focused on the impact of protection on benthic species suggest positive effects on benthic and sessile fauna, with more prevalent, abundant, and diverse habitat-forming species in the FNTZ (Bevilacqua et al. 2006; Ferrari et al. 2018; Pikesley et al. 2021). It is hypothesized that protection within MPAs influences benthic fauna indirectly, as the recovery of carnivorous fish alters trophic interactions and affects benthic community structure (Sala, 1997; Pinnegar et al. 2000; Fraschetti et al. 2002; Howarth et al. 2015).
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Spain approved the “Management Plan for the Conservation of Demersal Marine Resources in the Mediterranean Sea” in 2020 (Order APA/753/2020, BOE, 31st July 2020) with the objective of achieving maximum sustainable yield by 2025. This national plan aligns with the European Western Mediterranean Multiannual Plan (WMMAP; Regulation (EU) 2019/2022), which aims to manage bottom trawl fisheries, rebuild commercial fish stocks, reduce discards and bycatch, and reverse unsustainable fishing practices. This Spanish regulation included measures to establish permanent and temporal areas in all Geographical Subareas (GSAs) within the Spanish economic exclusive zone (EEZ). In several cases, the final defined areas were the result of an intense negotiation process between all stakeholders involved: the fishing sector, the administration offices and scientific organizations (ICATMAR, 2023). The measures implemented in this plan were the creation of 3 spatio-temporal closures for vessels engaged in bottom trawling, longlines, or gill-nets targeting: the European hake, Merluccius merluccius (Linnaeus, 1758); the deep-water rose shrimp, Parapenaeus longirostris (Lucas, 1846); the Norwegian lobster, Nephrops norvegicus (Linnaeus, 1758); the red mullet, Mullus barbatus (Linnaeus, 1758); the red shrimp, Aristeus antennatus (Risso, 1816); and the giant red shrimp, Aristaeomorpha foliacea (Risso, 1827). Two following amendments (Order APA/1397/2021, BOE, 10th December, 2021; Order APA/825/2022, BOE, 24th August, 2022) increased the number of permanent closed areas to 20 in the GSA6 in Catalonia, covering over 46 thousand hectares and representing 3.85% of the trawling fishing ground in the Catalan margin. These closures were implemented in areas where commercial demersal species spawned and with high concentrations of individuals below minimum landing size (Order APA/753/2020, BOE, 31st July, 2020). Their aims are to recover fishing stocks within the protected zone and to contribute to the restoration of bentho-demersal communities in the area and improve seabed quality. For some species, the cease of fishing activities, has been observed to have a spillover effect of adults and juveniles from the protected area to adjacent zones, indicating early passive restoration or natural regeneration (Sala-Coromina et al. 2021; ICATMAR, 2023). This phenomenon, defined as unassisted natural recovery following the cessation of perturbation is a key aspect of ecological restoration. In such instances, the presence of sufficient nearby populations is observed to enable recolonization without the necessity for active interventions to trigger abiotic and biotic recovery (Gann et al. 2019).This research aimed to establish a baseline and characterize the status of sessile and motile fauna in 11 Fishery No-Take Zones (FNTZs) established by the Spanish "Management Plan for the Conservation of Demersal Marine Resources in the Mediterranean Sea" in August 2020 (Order APA/825/2022, 24th of August, 2022). These zones, located along the Catalan margin and implemented in August 2020, represent a recent policy intervention aimed at recovering overexploited marine resources.
The central research question of this study is whether these FNTZs are already promoting measurable ecological responses in bentho-demersal communities, consistent with early stages of passive restoration. The specific objectives of this study are: a) to characterize the current composition and structure of sessile and motile communities within the FNTZs; b) to compare these communities with those in ecologically similar areas still subject to active fishing; c) to provide baseline data for long-term monitoring of ecological dynamics within the protected areas.
A novel aspect of this research is the prospecting of several areas across a large region, with different bathymetries, exclusively using non-destructive and non-extractive methods, such as remote imaging systems, to survey bentho-demersal communities. This approach avoids ecosystem disturbance from traditional monitoring techniques and minimizes additional pressure on these recently established FNTZs (Murphy & Jenkins, 2010; Chimienti, 2020; Nalmpanti et al. 2023).
In the broader context, this work aims to contribute to the growing body of science-based monitoring strategies that align with marine conservation goals under the EU Marine Strategy Framework Directive, thereby supporting the adaptive management of MPAs in the Mediterranean Sea.
2. Material y methods
2.1 Study area
A total of 24 video transects were recorded between April 18 and May 20, 2023, and on November 30, 2024, during surveys conducted aboard the R/V Ramón Margalef (see Supplementary Material, Table 1). All video transects were carried out during daylight hours in the spring season, except for one transect (Mer_Ros Control), which was conducted during a separate oceanographic campaign in the fall, also during daylight hours. Eleven FNTZs were subject to study and were categorized in two bathymetric ranges, shelf edge (100–300 m) and upper slope (> 300 m). Video transects were conducted in both the FNTZ and an adjacent Control Area (Fig. 1; See Supplementary Material Table 1). All video transects were recorded using the ROV 'Liropus 2000', equipped with a forward-facing video camera (HD Kongberg OE14-502A), depth and altimeter sensors, a compass, two parallel laser beams (LASER 532 nm), and four halogen lights (250 W Deep Sea Power & Light) (IEO, 2010). During navigation, the ROV was maintained at 1 to 1.5 meters above the seafloor and travelled at a constant speed of 0.3 knots. The underwater positioning of the ROV was tracked every 1.14 seconds using the High Precision Acoustic Positioning System (HiPAP 350 P Simrad), an USBL acoustic system, and recorded with the HYPACK software, achieving a spatial accuracy of 0.3% and a range error of less than 20 cm (Vigo et al. 2023).
Fig. 1
Fishery No-Take Zones (FNTZs) surveyed. Black triangles represent ROV transects in FNTZs, black dots represent ROV transects conducted as a control in adjacent fishing grounds (Control Areas). Projected view UTM zone 31N (WGS84) with geographic coordinates indicated for reference.
2.2 Video analysis
Quantitative video analysis was conducted following the methodologies established by Gori et al. (2011) and Grinyó et al. (2016), utilizing BIIGLE 2.0 software (Bio-Image Indexing and Graphical Labelling Environment). This online tool is specifically designed for annotating benthic fauna and marine imagery (Langenkämper et al. 2017). Video files were uploaded in MP4 format using the H.264 codec.
Laser beams from the ROV were used during video analysis as a fixed scale of 10cm width. The unit of measurement extended between the two lasers and included an additional 20 cm on either side, resulting in a field of view of 50 cm. Each observed organism was annotated according to this field of view, considering the distance of the laser beam. The dives were designed to cover as much area as possible while surveying all seabed substrates and assessing the effects of the fishing ban on bentho-demersal communities. We divided the transect into 5 m² segments, defined as Sampling Units (SUs) based on this measurement, an approach previously validated in other image-based studies on the continental shelf and slope environments (Grinyó et al. 2018; Enrichetti et al. 2019). Although transect length and number varied slightly among sites, sampling effort was standardized by analyzing data per equal-area (SUs), and by normalizing metrics to sampled area to ensure comparability across FNTZs and Control areas. To define the SUs along the video transect, distances between consecutive latitude and longitude positions were first calculated using the spherical cosine formula. These distances were then accumulated from the starting point of the transect. According to this formula:
d = R⋅arccos(sinφ1⋅sinφ2+cosφ1⋅cosφ2⋅cos(λ2−λ1))
Finally, the cumulative distance was divided by the length equivalent to 5 m² (area / transect width), thereby assigning each point to its corresponding sampling unit. To accurately estimate the length of each transect, we removed all sequences that included motion pauses and loops from the ROV footage. Also, where the ROV was too detached from the seafloor or when suspended sediments prevented a clear view of the seafloor, video sequences were discarded.
2.3 Fauna identification
All organisms of size above 2 cm in length, visible in current HD systems (i.e., referred thereafter as “megafauna” (Mecho et al. 2018; Danovaro et al. 2020)) were identified to the lowest possible taxonomic level. Since not all the organisms could be identified to the species level, Operational Taxonomic Units (OTUs) were used to classify organisms morphologically distinct. Different taxonomic literature was used for the identification of fauna (Zariquiey, 1968; Riedl, 1986; Lloris, 2015; Fourt et al. 2017; WoRMS Editorial Board, 2025) which was then validated by specialists from the Institut de Ciències del Mar (ICM-CSIC). The article follows the current taxonomy proposed in World Register of Marine Species (WoRMS Editorial Board, 2025) for all identified taxa. Seabed substrate type was classified using the categories by Dominguez-Carrió et al. (2022) and found that were all muddy fine to medium sand, herein referred to as soft substrates.
2.4 Statistical analysis
The analysis of taxonomic composition and diversity was conducted using the software R (R Core Team 2024), with data manipulation conducted with the dplyr package (Wickham et al. 2023) and visualization through the ggplot2 package (Wickham, 2016). To test the minimum effort necessary (hours of video analyzed) to characterize the bentho-demersal community, species accumulation curves were generated using the R package vegan package (Oksanen et al. 2025). These curves plot the cumulative number of species detected against a measure of sampling effort (i.e., SU in this case), providing a measure of sampling efficacy in biodiversity sampling, based on species detection saturation (Colwell et al. 1994).
Analyses for motile and sessile benthic megafauna were conducted separately due to distinctive ecological strategies in relation to motility and consequent bioturbation activity as well as habitat forming capabilities (Smith et al. 2000; Grinyó et al. 2022). Motile fauna group included all video-detected Vertebrata, Crustacea (i.e., Decapoda), Mollusca and Echinodermata (minus Crinoidea), the sessile group included all Cnidaria, Bryozoa, Hydrozoa, Annelida, Porifera, Tunicata, and Crinoidea (i.e., Echinodermata). The total number of individuals, the number of each SU, and its average density were computed. Density was only accounted for the occupied SU with each registered species. Normality assessment was evaluated using the Shapiro-Wilk test, using the function shapiro.test(). In case of a non-normal distribution, the Kruskal-Wallis test for comparing densities among groups was used with the function kruskal.test().
Richness, defined as the number of species, was computed for each SU within each combination of study area and protection regime (FNTZ vs Control), as well as in relation to organism motility (Motile vs Sessile), using the dplyr package (Wickham et al. 2023). To account for variation in sampling effort across SUs, species richness was normalized by total sampled area, computing effort from transect length multiplied by a fixed width of 5 meters to estimate area in square meters. Since the data were non-parametric, the Kruskal–Wallis rank sum test was used to assess whether normalized species richness differed significantly among protection categories within each area. The test was applied iteratively across all areas using a functional programming approach from the purrr package (Wickham & Henry, 2025). The Shannon Index was also computed for each SU with the diversity () function from the vegan package (Oksanen et al. 2025) and tested for differences with kruskal.test().
For the analysis of the different communities as function of the different protection regimes, a non-metric Multidimensional Scaling (NMDS) analysis was performed. First, a community matrix suitable for ordination was formed, and in order to avoid distortions in the results caused by rare or sporadic species entries (Marchant, 2002; Poos & Jackson, 2012), those with fewer than 5 observations across all the samplings as well as SUs with no fauna recorded were removed. Then, a Bray-Curtis distance matrix was computed, and NMDS was run in parallel (10 replicates) using the metaMDS function from the vegan package (Oksanen et al. 2025). The solution with the lowest stress was selected. To test for statistically significant differences in species composition, PERMANOVA was conducted (marginal model) using adonis2 with 999 permutations.
To identify species significantly associated with specific combinations of protection regime per area the Indicator Value (IndVal) was computed (Dufrêne & Legendre, 1997) using the indval() function from the labdsv package, and tested species associations with combined groups. The procedure involved 999 permutations to assess statistical significance. Only species with significant associations (p ≤ 0.05) were preserved as representative of each combination of area and protection regime. For each study area, the three most representative species were identified based on IndVal analysis.
3. Results
The video sequences retained accounted for 87.4% of the total recorded material, corresponding to a total duration of 67 hours and 45 minutes across all 11 FNTZs (see Supplementary Material Table 1). A total of 7860 SUs was obtained and examined, of which, 4277 (54.41%) showed presence of fauna. Species Accumulation curves were performed to test for sampling accuracy and sufficiency (See Supplementary Material Fig. 1). The minimum SU to cover 95% of the presumed species present per transect was calculated and reached per each study area and protection regime. The combined transects covered a total swept area of 0.393 km2. Overall, 30827 organisms were spotted, with 2022 (6.56%) remaining unidentified and categorized as “Unknown”, resulting in 93.44% of successful identifications, 159 OTUs belonging to 99 genus, 64 families, 23 classes and 8 phyla (Supplementary Material Table 2).
3.1 Density over different areas
To assess the effect of protection regime (i.e., Control vs. FNTZ), the focus was placed on species density (individuals·m-2) across the video-inspected areas and separated it among different motility strategies. Normality assessment with the Shapiro-Wilk test (W = 0.12905 and p-value = 2.2e-16), determine the density variable does not follow a normal distribution, and non-parametric methods were used further upon.
3.1.1. Sessile fauna
The results across the surveyed regions indicate varying responses of sessile species’ density to protection regime (Control vs. FNTZ). Among sessile species, several statistically significant differences in density between FNTZ and Control were observed (Fig. 2; Table 1). Sessile fauna density varied among study areas according to both protection regime and bathymetric range. At the shelf edge sites, densities were significantly higher within FNTZs than in Control Areas at Mer_Vil, Mer_Bar, Bol_Terr, and Rep_BLP. Conversely, higher densities were observed in Control Areas at Bol_Bru and Mer_Are, while no significant differences were detected at Mer_Ros. At the upper slope sites, density was higher in FNTZ only at Cig_Vil, with no significant differences between protection regimes at Cig_Pal, Cig_RP, and Cig_Bar. Comprehensive species-specific data are presented in Table 3 of the Supplementary Material.
Fig. 2
Distributions of sessile species density (individuals·m-2) in FNTZ (light blue) and control area (red). The plot illustrates the median and the interquartile range (IQR), while data points located beyond the whiskers are identified as statistical outliers.
Bathymetric Range | Area | Motility | Protection | Mean | SD | n | p-value | H statistic | df |
|---|---|---|---|---|---|---|---|---|---|
Shelf edge | Bol_Bru | Motile | Control | 0.518 | 0.293 | 117 | 0.001 | 10.785 | 1 |
FNTZ | 0.408 | 0.237 | 191 | ||||||
Sessile | Control | 1.911 | 0.799 | 126 | 1.49 × 10⁻⁴ | 14.381 | 1 | ||
FNTZ | 1.645 | 1.074 | 260 | ||||||
Bol_Terr | Motile | Control | 0.553 | 0.651 | 137 | 0.938 | 0.006 | 1 | |
FNTZ | 0.438 | 0.324 | 277 | ||||||
Sessile | Control | 0.229 | 0.076 | 7 | 0.030 | 4.717 | 1 | ||
FNTZ | 0.438 | 0.342 | 217 | ||||||
Mer_Are | Motile | Control | 0.597 | 0.376 | 72 | 1.91 × 10⁻⁶ | 22.685 | 1 | |
FNTZ | 0.378 | 0.240 | 143 | ||||||
Sessile | Control | 5.873 | 2.580 | 79 | 8.84 × 10⁻⁶ | 19.746 | 1 | ||
FNTZ | 4.640 | 2.789 | 262 | ||||||
Mer_Bar | Motile | Control | 0.287 | 0.132 | 87 | 0.090 | 2.874 | 1 | |
FNTZ | 0.378 | 0.295 | 81 | ||||||
Sessile | Control | 0.614 | 0.353 | 139 | 1.16 × 10⁻⁵ | 19.234 | 1 | ||
FNTZ | 1.133 | 0.987 | 132 | ||||||
Mer_Ros | Motile | Control | 0.340 | 0.183 | 94 | 0.213 | 1.548 | 1 | |
FNTZ | 0.380 | 0.223 | 347 | ||||||
Sessile | Control | 0.912 | 0.486 | 136 | 0.099 | 2.729 | 1 | ||
FNTZ | 1.229 | 1.110 | 540 | ||||||
Mer_Vil | Motile | Control | 0.360 | 0.222 | 89 | 0.020 | 5.374 | 1 | |
FNTZ | 0.279 | 0.138 | 53 | ||||||
Sessile | Control | 2.697 | 3.088 | 148 | 3.94 × 10⁻⁹ | 34.654 | 1 | ||
FNTZ | 8.241 | 6.154 | 68 | ||||||
Rep_BLP | Motile | Control | 0.553 | 0.651 | 137 | 0.698 | 0.150 | 1 | |
FNTZ | 0.389 | 0.208 | 71 | ||||||
Sessile | Control | 0.229 | 0.076 | 7 | 0.022 | 5.246 | 1 | ||
FNTZ | 0.469 | 0.314 | 78 | ||||||
Upper slope | Cig_Bar | Motile | Control | 0.586 | 0.763 | 99 | 0.006 | 7.585 | 1 |
FNTZ | 0.269 | 0.097 | 32 | ||||||
Sessile | Control | 0.217 | 0.058 | 12 | 0.338 | 0.917 | 1 | ||
FNTZ | 0.200 | 0.000 | 11 | ||||||
Cig_Pal | Motile | Control | 0.728 | 0.989 | 134 | 5.22 × 10⁻⁸ | 29.633 | 1 | |
FNTZ | 0.349 | 0.184 | 78 | ||||||
Sessile | Control | 0.503 | 0.556 | 78 | 0.112 | 2.533 | 1 | ||
FNTZ | 0.349 | 0.224 | 63 | ||||||
Cig_RP | Motile | Control | 0.339 | 0.206 | 72 | 0.188 | 1.737 | 1 | |
FNTZ | 0.286 | 0.141 | 49 | ||||||
Sessile | Control | 0.276 | 0.130 | 34 | 0.065 | 3.401 | 1 | ||
FNTZ | 0.368 | 0.241 | 62 | ||||||
Cig_Vil | Motile | Control | 0.830 | 2.276 | 54 | 0.201 | 1.632 | 1 | |
FNTZ | 0.384 | 0.288 | 64 | ||||||
Sessile | Control | 0.267 | 0.147 | 27 | 0.001 | 12.089 | 1 | ||
FNTZ | 0.436 | 0.255 | 89 |
3.1.2 Motile fauna
Motile fauna densities exhibited a heterogeneous response to protection regime across the study areas (Fig. 3). In the shelf edge, higher densities were recorded in Control Areas compared to FNTZs (Table 1) at Bol_Bru, Mer_Are, and Mer_Vil. No significant differences between protection regimes were detected at Rep_BLP and Bol_Terr, while mean densities were higher within FNTZ at Mer_Bar and Mer_Ros, although these differences were not statistically significant. In the upper slope areas, higher densities were also observed in Control Areas at Cig_Pal and Cig_Bar, whereas Cig_RP and Cig_Vil showed no significant differences between protection regimes. Comprehensive species-specific data are displayed in Table 3 of the Supplementary Material.
Fig. 3
Motile species density (individuals·m-2) distribution for the FNTZ (light blue) and Control area (red). This plot displays the median and interquartile range. Data points, plotted outside the box and whiskers, are considered statistical outliers.
3.2 Richness and Shannon Diversity Index
A
Species richness was summarized using boxplots in order to compare richness (i.e., the number of different species across every SU) between FNTZ and Control of each surveyed area (Fig. 4). Significant differences in FNTZs were observed in several areas (Table 2). In the shelf edge areas, higher richness was observed within FNTZ at Bol_Terr, Mer_Bar, and Rep_BLP, whereas Mer_Are and Mer_Vil exhibited greater richness in Control Areas. No significant differences were detected at Bol_Bru and Mer_Ros. In the upper slope areas, species richness was higher in FNTZ at Cig_Vil, while Cig_Bar and Cig_Pal displayed higher richness in Control Areas. No significant differences were found at Cig_RP. Overall, species richness varied spatially across sites and bathymetric ranges, with higher values in FNTZ at numerous locations, particularly along the shelf edge.
Bathymetric Range | Area | Protection | Mean | SD | n | χ² | p-value |
|---|---|---|---|---|---|---|---|
Shelf edge | Bol_Bru | Control | 0.930 | 0.318 | 126 | 2.026 | 0.155 |
FNTZ | 0.905 | 0.405 | 260 | ||||
Bol_Terr | Control | 0.279 | 0.127 | 139 | 64.385 | 1.02 × 10⁻¹⁵ | |
FNTZ | 0.455 | 0.246 | 330 | ||||
Mer_Are | Control | 0.965 | 0.366 | 79 | 16.452 | 4.99 × 10⁻⁵ | |
FNTZ | 0.774 | 0.348 | 262 | ||||
Mer_Bar | Control | 0.514 | 0.235 | 144 | 15.043 | 1.05 × 10⁻⁴ | |
FNTZ | 0.675 | 0.339 | 136 | ||||
Mer_Ros | Control | 0.743 | 0.293 | 138 | 0.088 | 0.767 | |
FNTZ | 0.749 | 0.392 | 558 | ||||
Mer_Vil | Control | 0.601 | 0.223 | 148 | 61.232 | 5.07 × 10⁻¹⁵ | |
FNTZ | 0.355 | 0.196 | 88 | ||||
Rep_BLP | Control | 0.279 | 0.127 | 139 | 56.273 | 6.31 × 10⁻¹⁴ | |
FNTZ | 0.541 | 0.290 | 95 | ||||
Upper slope | Cig_Bar | Control | 0.279 | 0.120 | 101 | 4.023 | 0.045 |
FNTZ | 0.235 | 0.077 | 40 | ||||
Cig_Pal | Control | 0.584 | 0.361 | 135 | 25.332 | 4.83 × 10⁻⁷ | |
FNTZ | 0.386 | 0.190 | 97 | ||||
Cig_RP | Control | 0.286 | 0.133 | 93 | 1.937 | 0.164 | |
FNTZ | 0.261 | 0.114 | 92 | ||||
Cig_Vil | Control | 0.329 | 0.202 | 62 | 4.275 | 0.039 | |
FNTZ | 0.366 | 0.167 | 106 |
The Shannon Diversity Index varied among study areas according to protection regime (Fig. 5; Table 3). Diversity was higher in FNTZ than in Control in Bol_Bru, Bol_Terr, Mer_Bar, Cig_Vil, and Rep_BLP. Diversity was higher in Control than in FNTZ in Cig_Pal, Cig_RP, and Mer_Vil. No significant differences were observed in Mer_Are and Mer_Ros, where the Shannon index did not differ statistically between protection regimes.
Fig. 5
Shannon Index representing H' values for FNTZs (blue) and Control areas (red) for the two bathymetric ranges. The plot shows the median and interquartile range, with any data points beyond the box and whiskers marked as statistical outliers.
α | |||||||
|---|---|---|---|---|---|---|---|
Bathymetric Range | Area | Protection | Mean | SD | n | χ² | p-value |
Shelf edge | Bol_Bru | Control | 1.172 | 0.340 | 1507 | 59.877 | 1.01 × 10⁻¹⁴ |
FNTZ | 1.275 | 0.434 | 2528 | ||||
Bol_Terr | Control | 0.267 | 0.356 | 387 | 356.061 | 2.03 × 10⁻⁷⁹ | |
FNTZ | 0.875 | 0.482 | 1082 | ||||
Mer_Are | Control | 0.613 | 0.298 | 2535 | 38.930 | 4.39 × 10⁻¹⁰ | |
FNTZ | 0.589 | 0.384 | 6348 | ||||
Mer_Bar | Control | 0.915 | 0.452 | 552 | 105.460 | 9.68 × 10⁻²⁵ | |
FNTZ | 1.168 | 0.439 | 901 | ||||
Mer_Ros | Control | 1.265 | 0.370 | 780 | 0.844 | 0.358 | |
FNTZ | 1.243 | 0.451 | 3977 | ||||
Mer_Vil | Control | 0.627 | 0.341 | 2156 | 3000.688 | < 1 × 10⁻¹⁶ | |
FNTZ | 0.107 | 0.139 | 2876 | ||||
Rep_BLP | Control | 0.267 | 0.356 | 387 | 328.837 | 1.72 × 10⁻⁷³ | |
FNTZ | 1.097 | 0.487 | 321 | ||||
Upper slope | Cig_Bar | Control | 0.276 | 0.306 | 303 | 4.579 | 0.032 |
FNTZ | 0.180 | 0.307 | 54 | ||||
Cig_Pal | Control | 1.239 | 0.535 | 684 | 164.460 | 1.20 × 10⁻³⁷ | |
FNTZ | 0.692 | 0.448 | 246 | ||||
Cig_RP | Control | 0.411 | 0.436 | 169 | 8.882 | 0.003 | |
FNTZ | 0.301 | 0.377 | 184 | ||||
Cig_Vil | Control | 0.499 | 0.333 | 260 | 8.331 | 0.004 | |
FNTZ | 0.585 | 0.415 | 317 | ||||
3.3 Community structure
The Non-metric Multi-Dimensional Scaling (NMDS) was conducted on two reduced datasets of sessile fauna with 2511 SUs containing 35 OTUs; and for motile taxa, with 2614 SU containing 56 OTUs.
3.3.1 Sessile fauna
A
Regarding community structure, NMDs (Fig. 6) indicate a clear segregation between communities from FNTZs and adjacent areas. This visual pattern is supported by PERMANOVA results (See Table 4 Supplementary material), which indicate significant differences between protection regimes (p = 0.001) and high R² values (0.857–0.999), suggesting that protection status explains most of the observed variation in community structure.Fig. 6
Non-metric Multi-Dimensional Scaling (NMDS) output plots for sessile fauna in all study areas. Sampling units containing sessile fauna organisms ordered considering protection regimes.
3.3.2 Motile fauna
A
The nMDS plots for motile fauna across all surveyed areas (Fig. 7), suggests consistent differences (i.e., under the form of separation in clustering) in SUs from FNTZ and Control per each area, reflecting differences in those assemblages. This pattern is quantitatively supported by the PERMANOVA (See Table 5 Supplementary Material), which showed significant differences (p = 0.001) between all sites and protection regimes. The R² values, ranging from 0.744 (Cig_RP) to 0.998 (Cig_Vil), indicate that a substantial proportion of the variation in community composition is explained by the fact that the area is protected. The highest explanatory power is observed in sites such as Mer_Bar, Bol_Terr and Cig_Vil.Fig. 7
Non-metric Multi-Dimensional Scaling (nMDS) output plots for motile fauna in all study areas. Sampling units containing sessile fauna organisms ordered considering protection regimes. Each subplot corresponds to a different site, comparing Control and FNTZ.
Taking a closer look to the group of taxa predominant in each area (Fig. 8) and how they differ among FTNZs and Control Areas, shelf edge areas present a greater diversity of present groups than the upper slope ones, which are mostly dominated by Cnidaria (uniquely represented by Ceriantharia individuals), Teleostei, Arthropoda and Elasmobranchii. There is no incidence of other groups such as Annelida, Ascidia, Bryozoa, Chordata (Tunicata non-Teleostei), Echinodermata and Mollusca, which have a positive presence in the shallower areas. The response and difference between FNTZs and their Control Areas is widely heterogenic, without clear discernable patterns. In terms of group representation and focusing on shelf edge areas, cnidarians were the most abundant and widespread taxon under both protection regimes, particularly in Bol_Bru and Mer_Are. Chordates and Annelida were also well represented across most shelf-edge sites. Some variation was evident in Mer_Bar and Rep_BLP, where FNTZ sites exhibited increased representation of Echinodermata and Bryozoa. Control sites tended to have a slightly higher presence of Chordata, Teleostei and Arthropoda. Mer_Vil presents an over representation of Echinodermata, due to the presence of a Crinoidea field on it. These shifts, however, were subtle and not uniform across all areas, yet, a higher group diversity in FNTZ than in Control Areas can be observed for most cases.
For upper slope areas, differences between Control and FNTZ regimes were slightly more pronounced, though modest overall. The proportional contribution of Arthropoda, Cnidaria, and Chordata varied between regimes, but these differences were inconsistent among sites. Cnidaria appears to be more present on FNTZs than in Control Areas, but Arthropoda and Teleostei follow an uneven pattern across sites. For instance, Cig_RP and Cig_Pal exhibited a modest increase in Chordata and Cnidaria in FNTZ compared to Control, while Cig_Bar remained dominated by Arthropoda under both regimes. Cig_Vil showed only minor shifts, with Chordata and Cnidaria alternating as dominant groups.
Fig. 8
Percentage of taxa from total faunistic observations observed in the 11 FNTZs and their respective Control Areas for both bathymetrical ranges.
3.4 IndVal
The associated IndVal scores and corresponding p-values for species across protection statuses are detailed in the Supplementary Material Table 6, and demonstrate statistically significant spatial patterns in species associations across both FNTZs and Control Areas.
3.4.1 Sessile fauna
Sessile taxa were generally more strongly associated with FNTZs, although patterns varied across bathymetric ranges. In the shelf edge areas, FNTZs were predominantly characterized by Alcyonium palmatum (Pallas, 1766), Lytocarpia myriophyllum (Linnaeus, 1758), Diazona violacea (Savigny, 1816), Funiculina quadrangularis (Pallas, 1766), Bryozoa, Crinoidea, Filograninae, Hydrozoa, Myxicola infundibulum (Montagu, 1808), and Suberites syringella (Schmidt, 1868). Control Areas were indicated by sessile taxa such as F. quadrangularis, L. myriophyllum, Sabellida, Pennatulidae, Cavernularia pusilla (Philippi, 1835), A. palmatum, and Pteroeides griseum (Bohadsch, 1761). Some species, including F. quadrangularis and L. myriophyllum, were present in both regimes but showed higher IndVal scores in FNTZs or Control depending on the site. In the upper slope areas, FNTZs were primarily indicated by Ceriantharia and Crinoidea, whereas Control Areas had fewer distinctive sessile indicators, with Ceriantharia occurring in both FNTZ and Control but generally at lower IndVal scores in Control Areas.
3.4.2 Motile fauna
Motile species had a stronger association with Control zones across the study areas, but without common species among them. In the shelf edge areas, Argentina sphyraena (Linnaeus, 1758) was identified as a significant indicator in both FNTZ and Control Areas at Bol_Bru, although its association was more pronounced with the Control area. In Bol_Terr, Trachurus trachurus (Linnaeus, 1758) and Scyliorhinus canicula (Linnaeus, 1758) were primarily associated with Control Areas, while A. sphyraena and Gadiculus argenteus (Guichenot, 1850) appeared as more indicative of FNTZs. At Rep_BLP, T. trachurus was again strongly associated with Control sites.
In the upper slope areas, motile species dominated the indicator assemblages, particularly members of Myctophidae and Brachyura, which were primarily associated with Control Areas at Cig_Bar and Cig_Pal. At Cig_RP, Stomias boa (Risso, 1810) emerged as a key indicator for FNTZs, whereas Myctophidae were detected in both zones. Cig_Vil exhibited the highest IndVal scores for motile species, with Lepidopus caudatus (Euphrasen, 1788) being a strong indicator for FNTZs, while Myctophidae were primarily associated with Control Areas.
4. Discussion
This study presents the first large-scale, non-destructive baseline assessment of newly established Fishery No-Take Zones (FNTZs) in soft-sediment habitats of the Northwestern Mediterranean. It represents an essential first step toward the long-term monitoring of these communities and the evaluation of FNTZs effectiveness in facilitating passive ecological restoration. In contrast to previous research primarily focused on rocky or coral reef ecosystems, this work integrates quantitative ROV-based data collected from eleven sites spanning two bathymetric strata. This approach provides an unprecedented regional perspective on early-stage passive restoration processes in previously trawled benthic environments. The findings emphasize the importance of accounting for species mobility when evaluating the effectiveness of marine reserves, as this factor plays a critical role in shaping ecological responses and recovery trajectories.
4.1 Effectiveness of Spatial Management
Although various ecosystem conservation and restoration strategies exist, spatial management is currently considered the most effective, and perhaps the only, approach capable of successfully protecting and restoring the environment (Clark & Dunn, 2012). Fishery No-Take Zones (FNTZs) offer protection to all species and habitats within a designated area from extractive activities and provides an opportunity to mitigate several threats impacting marine ecosystems and vulnerable habitats (Moilanen, 2008; Lester et al. 2009).
However, the timescales expected to provide results are widely heterogeneous (Clark et al. 2016) and may vary depending on the taxa in focus and the ecosystemic services at stake. As some authors suggested, the idiosyncratic nature of the FNTZ creation may affect their impacts and outcomes, varying with the goal it was set by the institution establishing it. It would depend on whether the FNTZ is part of a network of reserves, location, size, protection duration, and the characteristics of the species under consideration (Jennings & Kaiser, 1998té et al. 2001; Lester et al. 2009; Claudet et al. 2010; Clavel-Henry et al. 2024).
Nowadays, most of the conducted studies are in MPAs set to protect nearshore rocky or coral reef habitat, indicating a lack of studies (and potentially marine reserves) in certain habitat types such as soft sediment (Lester et al. 2009). This is the first comprehensive study in multiple FNTZs and different bathymetric ranges placed on soft sediment bottoms in the Mediterranean. These zoning strategies are especially relevant in the context of deep-sea environments, where slow-growing and poorly dispersed species are particularly susceptible to disturbance. Recovery in such systems is often limited by the availability and fitness of colonizers, especially when impacted areas are isolated from larval sources (Lacharité & Metaxas, 2013; Clark et al. 2016).
4.2 Ecological indicators and Taxa-Specific Responses
When assessing the effects of marine protection across different regions, several considerations can be drawn. Regarding individual density, FNTZs exhibit higher mean densities of sessile taxa, although this trend is not consistent in all areas (see Fig. 2, Fig. 3). Regarding the general pattern per depth, sessile fauna density varied across study areas according to bathymetric range and also in response to protection regime. At the shelf edge, densities were generally higher within FNTZs, specifically at Mer_Vil, Mer_Bar, Bol_Terr, and Rep_BLP, indicating potential benefits of protection. However, opposite trends at Bol_Bru and Mer_Are and the absence of differences at Mer_Ros suggest that responses are site-specific or influenced by local conditions. On the upper slope, only Cig_Vil showed higher densities in FNTZs, with no significant differences elsewhere, reflecting greater environmental variability at depth or slower recovery. Overall, these patterns indicate that protection enhances sessile fauna in some areas, but effects are modulated by local habitat and depth-related factors.
Regarding motile fauna, in the shelf edge higher densities in some Control Areas at Bol_Bru, Mer_Are, and Mer_Vil suggest that motile taxa may persist or even benefit under moderate disturbance or habitat turnover. In contrast, densities were slightly higher between regimes at both Rep_BLP and Bol_Terr, although these differences were not significant. Values in FNTZs at Mer_Bar and Mer_Ros indicate localized variability. On the upper slope, greater densities in Control Areas at Cig_Pal and Cig_Bar, and the absence of differences in the Cig_Vil and Cig_RP, further highlight the site-specific and inconsistent response of motile fauna. Overall, these results suggest that protection effects on motile fauna are faint or context-dependent, likely influenced by the mobility or life strategy of species and site-specific conditions rather than management status alone.
In this regard, significant increases in population density and species diversity in FNTZs have also been commonly reported in the literature (Palumbi, 2004; Lester et al. 2009; Giakoumi et al. 2017). However, this trend is not consistent in all cases (Halpern, 2003; Sala et al. 2012). When focusing on motile fauna, it displayed a heterogeneous response to protection, with patterns varying among areas and bathymetric ranges (see Fig. 2, Fig. 3 & Table 1).
Sessile taxa exhibited early and localized positive responses to protection, confirming that reduced disturbance benefits habitat-forming organisms. In contrast, motile taxa showed no consistent differences between regimes, suggesting that mobility, trophic flexibility, and limited time since closure have delayed observable effects. The results advocate for an efficacy of reserves depends upon the life habits of targeted species modulated combined. Species with limited adult mobility tend to respond more strongly to reserve protection, provided their recruitment is not severely compromised (Palumbi, 2004; Lester et al. 2009). In contrast, highly mobile species often show muted responses unless exploitation levels are extremely high and recruitment is sufficient to offset losses outside reserve boundaries (Palumbi, 2004; Lester et al. 2009). Species that benefit from protection have in common being particularly large-bodied, slow-growing, and late-reproducing predators, and are expected to be more abundant and larger in older and larger FNTZs (Giakoumi et al. 2017). For instance, Lophius sp. (Linnaeus, 1758), S. canicula, Helicolenus dactylopterus (Delaroche, 1809), and M. merluccius are present in both protection regimes for several areas. For H. dactylopterus and Lophius sp., there are no differences between treatments, and for S. canicula (0.23 ± 0.04 individuals·m-2 FNTZs vs 0.21 ± 0.02 individuals·m-2 Control) and M. merluccius (0.23 ± 0.04 individuals·m-2 FNTZs vs 0.21 ± 0.02 individuals·m-2 Control). There is a slight tendency towards a higher density in FNTZs, but it is not significant (see Supplementary Material Table 3).
Concerning other indicators such as species richness and Shannon Index, those indices varied spatially across the surveyed areas and bathymetric ranges. Along the shelf edge, several FNTZs, including Bol_Terr, Mer_Bar, and Rep_BLP, showed higher richness compared to Control sites. In contrast, Mer_Are and Mer_Vil exhibited greater richness in Control Areas, while Bol_Bru and Mer_Ros showed no significant differences. On the Upper slope, richness was higher in FNTZ at Cig_Vil, whereas Cig_Bar and Cig_Pal were richer in Control Areas, with Cig_RP showing no difference. These patterns suggest that the effect of protection on species richness is subject to context and influenced by local environmental conditions; no common trend can be extracted.
Shannon Diversity Index trends reflect the same aforementioned patterns. Diversity was higher in FNTZ at Bol_Bru, Bol_Terr, Mer_Bar, Cig_Vil, and Rep_BLP, indicating more even assemblages in some protected areas. Conversely, Control sites showed higher diversity at Cig_Pal, Cig_RP, and Mer_Vil. No significant differences in diversity were detected at Mer_Are and Mer_Ros, consistent with richness data. Overall, FNTZs support higher richness and diversity in certain locations, but spatial variability and site-specific factors strongly influence these outcomes.
These findings highlight the importance of considering spatial heterogeneity, habitat quality, and ecological connectivity when assessing the effectiveness of FNTZs, and they underscore that adaptive management and site-specific monitoring, as well as a broader scale, are essential to optimize and further understand these outcomes.
Overall, the quantitative indicators (density, richness, and diversity) revealed heterogeneous yet coherent trends across the region, reflecting spatially variable but ecologically consistent responses to protection. Sessile taxa generally exhibited higher values within FNTZs, particularly along the shelf edge, suggesting an early positive effect of reduced trawling pressure on these organisms. In contrast, motile taxa displayed less consistent spatial patterns, likely influenced by their capacity to move across reserve boundaries and feeding behavior. These contrasting responses indicate that the ecological benefits of protection are beginning to emerge for sessile species, while the motile components of the community may require longer timeframes or broader management measures to display detectable changes.
4.3 Community Composition and IndVal Findings
Despite the aforementioned results in density and biodiversity among areas, when performing an NMDS analysis, a clear segregation pattern appears among communities in both protection regimes (Fig. 6, Fig. 7); they are represented as separate communities with significant differences. There is almost no overlap in this aspect, clearly indicating a community differentiation inside and outside the FNTZs.
Regarding the composition of each community (Fig. 8), when focusing on specific regions (e.g., Mer_Bar and Rep_BLP), FNTZs exhibited higher representation of echinoderms and bryozoans, taxa generally sensitive to bottom disturbance, whereas Control sites showed greater prevalence of Teleostei and arthropods, suggesting that mobile or opportunistic species persist under continued anthropogenic pressure.
On the whole, FNTZs generally supported more taxonomically diverse yet less individually dominant assemblages, suggesting a tendency to enhance ecological specialization. Although differences in group representation between Control and FNTZ sites were modest, a consistent tendency emerged for sessile or fragile taxa (e.g., bryozoans, echinoderms, poriferans) to be more abundant in protected areas.
A
Taking a closer look at the species composition of the communities through IndVal Scores (See supplementary material, Table 6), there is a higher representation of sessile and habitat-forming species in FNTZ communities. Findings demonstrate that FNTZs at the shelf edge support a broader and more diverse assemblage of indicator species, including several habitat-forming and structure-building taxa, reflecting a more specialized community structure under protection. In these areas, a stronger association with OTUs like Crinoidea, Bryozoa, F. quadrangularis, A. palmatum, and sponges such as Suberites spp. (Nardo, 1833) is often displayed with high IndVal scores. These sessile organisms are species with structural and ecological importance since they contribute to habitat complexity and biodiversity enhancement (Buhl-Mortensen et al. 2010) Also noteworthy is that many FNTZ indicator species, especially the sessile taxa, are exclusively found or better associated in protected areas and not present on active fishing grounds. These species are typically vulnerable to physical disturbance and exhibit low motility, making them highly dependent on undisturbed habitats for persistence (Sciberras et al. 2018). Their strong association with FNTZs suggests that protection from fishing activities facilitates the recovery and maintenance of structurally complex benthic communities.In contrast, indicative species of Control areas were largely motile and opportunistic, including Trachurus trachurus (Linnaeus, 1758), S. canicula, Brachyura, and Argentina sphyraena (Linnaeus, 1758). The prevalence of these taxa in unprotected zones is consistent with their broader ecological tolerances and ability to exploit disturbed environments. This pattern aligns with previous findings that motile or generalist species are less sensitive to fishing impacts and can persist under moderate levels of exploitation (Palumbi, 2004; Lester et al. 2009).
As a general trend, Ceriantharia individuals appear across most sites, especially in the upper slope areas, and in both protection regimes. This suggests it may be broadly resilient due to its retractile capacities to avoid or minimize fishing stress (Ambroso et al. 2021), and is considered a taxon living mainly subsurface with high burrowing capacity as fishing pressure tolerant (Clark et al. 2016), being almost the only sessile species present in upper slope depths. Also, mobile scavengers with the potential to benefit from moving into a disturbed area with increased food availability were considered “favored” (Clark et al. 2016). In the data analyzed, this can be reflected in OTUs like Brachyura, Goneplax rhomboids (Linnaeus, 1758), Monodaeus couchii (Couch, 1852), and other Decapoda being more abundant in Control Areas rather than in FTNZs for upper slope areas (See Supplementary material Table 2).
From these results, it can be concluded that species in various trophic groups react differently to protection (Palumbi, 2004). In a meta-analysis of reserve effects, Micheli et al. (2004) reveal that omnivores and detritivores respond little, if at all, to reserve protection. Species that ingest algae, invertebrates, or plankton exhibit a mild response. Predatory fish have the largest reaction, with their abundance virtually doubling across all experiments (Palumbi, 2004). Predatory fish are highly valued fishing targets, and as a result, they respond to reserves when they are no longer overfished (Lester et al. 2009). Detritivores and herbivores may be less often fished and so less likely to benefit from protection (Palumbi, 2004; Lester et al. 2009). Also, for less motile species, population growth inside reserves depends on recruitment rates exceeding the emigration of adults beyond reserve boundaries (Palumbi, 2004).
A second reason for the disparities in response to reserves is that a greater number of predators may consume more prey, and if these preys are smaller species, the middle trophic levels occupied by these smaller species may drop rather than grow (Palumbi, 2004). So, indirect effects, such as predator-prey dynamics and species interactions, further complicate reserve outcomes (Gaines et al. 2003; Micheli et al. 2004). Despite general positive trends, not all species experience reserve effects (Lester et al. 2009). Approximately 25% of species may not respond to protection, and only a subset of those that do may contribute to spillover (Palumbi, 2004). This variety emphasizes the significance of developing reserve networks that take into consideration species-specific ecological features, fishing pressures, and local community usage patterns (Palumbi, 2004; Lester et al. 2009).
4.4 Restoration dynamics and ecological limitations
Quick-response and reproductively successful organisms tend to dominate newly protected areas, whereas long-lived and slow-growing species are disadvantaged, unable to survive under the newly established environmental conditions or taking much longer to recover (Kaiser et al. 2006). The latter will be strongly affected, vastly reducing the potential for such species to re-establish themselves or colonize new areas (Thrush et al. 2001).
Empirical evidence supports this trend: in Norwegian seamounts, megabenthic assemblages dominated by slow-growing corals showed no detectable recovery from trawling impact even after 5–10 years (Williams et al. 2010; Clark et al. 2016). Despite the permanent cessation of fishing activities, the whole community has been driven to a shift. Similar community restructuring was observed in South Kattegat, where the cessation of bottom trawling in a FNTZ led to a shift in the community composition (Sköld et al. 2025).
This constraint is especially relevant at greater depths, where, despite equivalent levels of sensitivity to disturbance, recovery times are substantially longer. Evidence from the present study reinforces this pattern: within upper slope areas, sessile fauna was largely absent, except for isolated Ceriantharia individuals at this depth, while differences between protected and unprotected shelf-edge areas remained less evident than anticipated. These results reflect the high sensitivity and low recoverability of deep-sea benthic assemblages and their limited capacity to recover within the short temporal scales typically considered in management planning frameworks (Clark et al. 2016; Lambert et al. 2017).
The aftermath of bottom trawling highlights the vulnerability of benthic communities to long-term physical disturbance. In the 11 FNTZs analyzed, as shown in Table 1, differences in time since closure among sites did not translate into clear gradients in ecological indicators. Although some areas have been closed for a longer period, there are still no notable differences in ecological indicators in relation to their oldness. A key limitation of this study is the absence of prior data to the establishment of closures, preventing robust temporal comparisons. Hence, time since closure was not incorporated as a variable, but will be considered on future monitoring efforts aimed to address this gap.
Previous research indicates that recovery trajectories in these systems can take over three years and are heavily dependent on habitat type, taxonomic composition, and the degree of physical alteration to the substrate (Sciberras et al. 2018). In these study areas, hard substrates have been iteratively removed for decades when they were active fishing grounds, trawlers tore rocks and boulders out of their way (de Groot, 1984; Freese et al. 1999), relocating them to places where they no longer disturb their activity. This phenomenon leads to substrate loss and, consequently, homogenization of habitats and the loss of small-scale patchiness, thereby increasing the risk of losing ecological function (Thrush et al. 2001). This is especially true for sessile organisms, as recovery largely depends on recruitment, settlement, and growth in impacted areas, as well as the extent of substrate modification following the fishing event (Sciberras et al. 2018). Many organisms depend on those hard substrates for larval attachment. For example, many sessile invertebrates, such as anemones, tunicates, and soft corals, depend on finding empty shells for attachment, and trawling can bury or completely remove these shells (McConnaughey & Syrjala, 2014). Other species of sessile macrofauna, including sponges, bryozoans, and ascidians, require hard substrates such as rocks for settlement and larval survival (Sarà, 1986; Cima, 2023;), and their presence is essential for larval connectivity and population resilience (Sciascia et al. 2022). Protection of the area alone cannot simply recover all the substrates, and habitat rehabilitation could be helpful, even necessary to achieve the restoration goals.
A
The variability observed among FNTZs also suggests that ecological recovery is governed by local substrate history and physical disturbance intensity. Areas subjected to decades of chronic trawling likely require longer protection periods, to exhibit measurable changes in community structure. Hence, early-stage monitoring like the present one is critical to document initial trajectories and establish realistic baselines for long-term restoration assessment. The results of this study conclude that we cannot extract a continuous pattern of the FNTZ areas benefiting from the fishing ban in the short term yet, as not enough time has passed to show a clear passive structure recovery. Recovery of both sessile and motile fauna takes time, and it is uneven and heterogeneous among areas with similar depth and substrate conditions (Sciberras et al. 2018). Recovery rates depend not only on the magnitude of the impact but also on the habitat type and taxon affected (Sciberras et al. 2018). The oldest areas do not exhibit the highest densities or richness, contrary to the investigators' premises in this paper. Heterogeneity is key, and even though some tendency is clear among areas favoring the FNTZ conditions, it can be established that longer periods are expected to yield real and significant changes in these bentho-demersal communities, which have been long-term impacted and severely disrupted chronically. Although restoration concepts are improving and scaling up in recent years (Life ECOREST, 2021; Santin et al. 2022), they are incapable of fully reverse the damage done for decades and are unachievable in the short term (Van Dover et al. 2014; Clark et al. 2016). Effective restoration will therefore require sustained management commitment, enhanced monitoring programs, and substantial investment in both scientific and financial resources.5. Conclusions
This study represents a foundational step in establishing a long-term ecological baseline for assessing the effectiveness of FNTZs in promoting passive restoration on Mediterranean soft-sediment habitats. By combining quantitative ROV surveys across 11 closures, it demonstrates that protection can already foster early structural differentiation, particularly in sessile taxa and in shallower depths, while highlighting that motile components require longer timeframes to respond.
Historical bottom trawling has compromised seabed structure, removing hard substrates and destroying natural orography, leading to habitat homogenization, hindering recovery potential in deep-sea habitats. The lack of consistent improvements across closures highlights that recovery of deep-sea and soft-sediment communities likely occurs over longer timescales than predicted, beyond those typically considered in management planning.
For these reasons, active restoration and long-term monitoring are essential. Passive protection alone cannot rebuild lost substrate complexity or recover chronically disturbed systems. Future steps should prioritize the establishment of long-term, standardized monitoring programs, pre- and post-closure baselines, and experimental restoration efforts including substrate recovery and recruitment facilitation. Advancing such integrative strategies will be crucial to translating spatial protection into measurable ecosystem restoration and resilience in deep-sea and soft-sediment environments.
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Acknowledgement
The success of this work was made possible thanks to the dedicated support of the crews of the R/V Ramon Margalef, whose professionalism and support are gratefully acknowledged. Appreciation is also extended to the ROV Liropus 2000 operators from ACSM for their skilled and reliable execution of underwater surveys. The contribution of Daniela Scutaru; Sara Biancardi; Simone Gaetano Amato; Chiara Fini; Mathias Foirest; involved in the annotation of imagery is sincerely appreciated, as their careful work greatly facilitated data processing. Special thanks are extended to Ricardo Santos and Marc Balcells, who assisted in the identification and confirmation of species, whose taxonomic expertise was essential to ensuring the accuracy and reliability of the biodiversity assessments.
Electronic Supplementary Material
Below is the link to the electronic supplementary material
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Author Contribution
Marina Biel-Cabanelas (M.B.C.) – Conceptualization; Data curation; Formal analysis; Investigation; Methodology; Software; Visualization; Writing – original draft; Writing – review & editing.Andreu Santín (A.S.) – Conceptualization; Funding acquisition; Supervision; Validation; Writing – review & editing.Gabriel Rivas-Mena (G.R.) – Investigation; Writing – review & editing.Sofia Faramelli (S.F.) – Data curation; Investigation; Writing – review & editing.Cristina Martín (C.M.) – Investigation.Fabiola Maria Cecchini (F.M.C.) – Investigation; Writing – review & editing.Antoni Sánchez (A.S.) – Investigation.Miguel López (M.L.) – Investigation; Writing – review & editing.José Antonio García (J.A.G.) – Investigation; Methodology; Software.Nixon Bahamon (N.B.) – Funding acquisition; Supervision; Validation; Writing – review & editing.Jacopo Aguzzi (J.A.) – Conceptualization; Funding acquisition; Supervision; Validation; Writing – review & editing.Joan B. Company (J.B.C.) – Conceptualization; Funding acquisition; Project administration; Supervision; Validation; Writing – review & editing.Jordi Grinyó (J.G.) – Conceptualization; Funding acquisition; Project administration; Supervision; Validation; Writing – review & editing.All authors have read and approved the final manuscript.
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