Next Article in Journal
Dietary Inclusion of Micro-Algal Astaxanthin on Gut Health of Rainbow Trout Oncorhynchus mykiss: Insights from Gut Morphology, Physiological Indices and Microbiota Diversity
Previous Article in Journal
Full Scale Testing of a Concept for Salinity Regulation to Mitigate Sea Lice Infestation in Salmon Farming
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Occurrence and Community Structure of Wild Fish Within Adriatic Sea Fish Farms

1
Department of Ecology, Agronomy, and Aquaculture, University of Zadar, Trg kneza Višeslava 9, 23000 Zadar, Croatia
2
Center for Geospatial Technologies, University of Zadar, Trg kneza Višeslava 9, 23000 Zadar, Croatia
3
Cromaris d.d., Gaženička ulica 4b, 23000 Zadar, Croatia
*
Author to whom correspondence should be addressed.
Fishes 2025, 10(10), 504; https://doi.org/10.3390/fishes10100504
Submission received: 30 August 2025 / Revised: 27 September 2025 / Accepted: 6 October 2025 / Published: 8 October 2025

Abstract

This study presents, for the first time, the occurrence and community structure of wild fish inside marine aquaculture cages of gilthead seabream (Sparus aurata), European sea bass (Dicentrarchus labrax), greater amberjack (Seriola dumerili), meagre (Argyrosomus regius), and common dentex (Dentex dentex). Coexistence of farmed and wild fish was observed only in cages of gilthead seabream and European sea bass, with wild fish constituting 0.08% of the total sampled fish biomass. Twelve wild fish species from five families were recorded: Carangidae, Clupeidae, Mugilidae, Moronidae, and Sparidae. Bogue (Boops boops) and jack mackerel (Trachurus sp.) were the most abundant. Multivariate analysis indicated that location significantly influenced the wild fish community composition, while reared species and farming duration, along with their interaction, had no significant effect. Descriptive comparisons suggested potential differences in biometric traits of bogue and jack mackerel between reared species and farming duration. The findings highlight the need for further research on wild fish in cages to better understand the potential health and biosecurity risks they may pose.
Key Contribution: This is the first study to quantify wild fish assemblages co-occurring with reared species inside marine aquaculture cages in the Adriatic Sea. It reveals location as a key driver of community composition.

1. Introduction

Aquaculture is increasingly seen as a viable solution to meet the food requirements of a growing population [1]. Croatia possesses considerable potential for advancing this sector, thanks to its advantageous natural conditions and geographic location, which are similar to those of other Mediterranean nations. In Croatia, floating net cages are used to cultivate various species, such as gilthead seabream (Sparus aurata), European sea bass (Dicentrarchus labrax), meagre (Argyrosomus regius), greater amberjack (Seriola dumerili), common dentex (Dentex dentex), and tuna (Thunnus thynnus) [2].
In the Mediterranean, floating sea cages attract a variety of wild fish. These structures protect the fish from predators and provide them with a food source [3,4,5,6,7,8].
The regular food supply from the farm results in greater abundance, biomass, and longer presence of fish around cage structures compared to areas without farming [9,10]. Wild fish aggregating around cages feed on food pellets, and it is estimated that wild fish may consume 10% of the feed administered on the farm [5]. Wild predatory fish often congregate around these cages in search of prey rather than eating the offered food, with bluefish (Pomatomus saltatrix) identified as a primary predator at fish farms [9]. Additionally, nearby habitats influence the structure of the wild fish community around sea cage fish farms [11]. Furthermore, using nighttime lighting on the farm can attract more fish by illuminating various organisms, thereby increasing the capture rates of commercially important species for fisheries [12]. Fish farms located closer to the coast tend to attract more wild fish, with over 80% being adults [3], in contrast to fish aggregation devices (FADs), which primarily attract juveniles [13]. Several environmental factors, including terrain, proximity to the coastline, ocean currents, and depth, significantly impact the presence of wild fish near cages [5].
The wild fish species found near European sea bass and gilthead seabream farms mainly belong to the Clupeidae, Sparidae, and Mugilidae families [5,7]. Seasonal changes influence the abundance of wild fish around farms with peaks in summer and autumn, and a decline in winter [4,5]. A study of wild fish communities around tuna, European sea bass, and gilthead seabream farms found significantly higher abundance of garfish (Belone belone) in the wild fish communities around tuna farms compared to the abundance of garfish in wild fish communities around European sea bass and gilthead seabream farms [6].
There is concern that the presence of wild fish in the vicinity of farmed populations increases the risk of pathogen transmission and the emergence of new diseases affecting both wild and farmed fish [14,15]. Viral nervous necrosis (VNN) and lactococci are emerging diseases affecting farmed fish, and there is a suspicion that the infection can be transmitted from wild fish in the Mediterranean [16,17,18].
In marine fish cage farming, wild fish can enter the cage and, depending on their adaptive abilities and biological characteristics, may remain in that environment, as evidenced by the presence of wild fish caught from the cage. In salmon farming cages, eight different wild fish species have been found inside net cages, demonstrating that small fish can enter [19]. Access occurs through openings smaller than the mesh size, typically in search of food, attracted by light, or due to the accumulation of dead fish and uneaten feed at the cage bottom. Once inside, individuals may grow beyond the mesh size and become unable to escape. Wild fish may also be caught in a new net cage during the transition from one cage to another; furthermore, the cage itself could be damaged, allowing wild fish to enter [9]. During farming, there is a need to remove fouling from aquaculture cages and replace the net with one that matches the mesh size to the size of the fish [20]. In salmon farms with technology similar to Adriatic farms, it was found that fish smaller than the net’s mesh can enter the cage [19], and net damage could also facilitate entry [9,21]. This suggests that aquaculture cages, designed for monoculture, unintentionally trap wild fish. In 2017, Fisheries and Oceans Canada (DFO) investigated the predation of wild fish by farmed salmon in British Columbia, with a focus on the negative effects on wild fish caught inadvertently in fish farms [22]. The study discovered that 0.1% of farmed salmon stomachs contained wild fish, mainly herring (Clupea pallasii), pollack (Pollachius virens), hake (Merluccius merluccius), and cod (Gadus morhua). The author highlights several negative effects on wild fish in farm cages, including becoming prey for farmed salmon, accidental catch during farming operations, injuries or stress caused by capture, and the risk of transmitting pathogens to farmed fish.
The population and occurrence of wild fish in cages within the Mediterranean, especially in the Adriatic Sea, have received limited research [9,23]. Notably, wild bogues kept in captivity show improved body condition and gonadal indices [23].
The aim of the research was to identify which species of wild fish can coexist with farmed European sea bass, gilthead seabream, meagre, common dentex, and greater amberjack. Specifically, the aim was to examine the influence of farm location, reared species, and farming duration on wild fish assemblages and biometric traits of the most common wild species. Determining the possibility of cohabitation of wild and farmed fish is important considering the potential health and biosecurity risks that this cohabitation can pose. Additionally, the results could raise awareness of the need to develop technologies to prevent wild fish from entering fish farming cages.

2. Materials and Methods

2.1. Study Site

The study of wild fish within marine aquaculture cages involved analysing samples from seven farm locations (L1–L7) across two regions: Zadar County and Istria County, as illustrated in Figure 1. A more detailed map of Zadar County study sites is available in supplementary Figure S1. To better describe the environmental characteristics of each location, spatial analyses were performed in QGIS 3.44.2 (Solothurn). Allocated Zones for Aquaculture (AZA) were obtained from the spatial plans of Zadar and Istria counties, and farms within each AZA were manually vectorized at a scale of 1:2000. Habitat data were retrieved as Web Feature Service (WFS) layers from Bioportal, their geometries were validated for topological consistency, and subsequently overlaid with AZA polygons. Habitat information is available in the supplementary Table S1 due to its extensive size. Bathymetric data were obtained from Navionics (https://maps.garmin.com/en-US/marine/?maps=another-brand&overlay=false, accessed on 15 September 2025) sonar records. Table 1 shows, for each AZA, the depth range defined by its shallowest and deepest farm. Data on maximum permitted production, authorized species, the number of approved farms, and their respective areas were sourced from the Aquaculture Permits Register. A summary of this information is provided in Table 1.
In addition to environmental and production characteristics, farming practices were also considered, as they influence both cage conditions and potential interactions with wild fish. The farms employ identical feeding and farming methods. Fry weighing 3–5 g were initially kept in cages with a 25 m diameter before being moved to larger cages of 50 m diameter. The net mesh size, starting at 10 mm, is designed to match the size of the fish and later expands to 24 mm. Net replacements involve wrapping a new net around the existing cage, then removing and replacing the old one. During the first year, replacements are more frequent, occurring monthly in summer. In the second year, the replacement rate drops, and fouling is controlled without changing the cages; instead, fouling is removed using net-cleaning robots.

2.2. Sampling Protocol

The study used samples from cages rearing gilthead seabream, European sea bass, greater amberjack, meagre, and common dentex, collected between March and June 2023 (species codes defined in Table 1), ensuring consistency in seasonal conditions. The fish caught for commercial purposes was used as a sample. During catching, the volume of the net cage was reduced before trawl fishing. The captured fish were transferred to the ship and then cooled in ice containers. The total sample consisted of 49 fish cages used for aquaculture, of which 20 cages contained wild fish. Each site included 2 to 5 active rearing cages, and a total of 18 cages were sampled across all sites. Depending on site logistics, some cages were sampled once, while others were sampled multiple times during the same rearing cycle. The exact sampling dates and frequencies are listed in Supplementary Table S2. In cases where repeated sampling occurred within the same farming cycle (i.e., the same fish cohort and cage structure), the data were pooled to represent a single cage-level dataset, as no substantial changes in fish assemblage were expected within the short timeframe. Sampling at different farms was not always synchronous due to differences in harvest schedules; however, all sampling occurred within the same seasonal window. All wild fish caught during each harvest event were included in the analysis.
During processing, all fish were sorted, and each wild fish was separated. Each fish underwent biometric measurements. In this context, wild fish are those not farmed in the examined cage. Additionally, 30 farmed fish were sampled for biometric analysis. Measurements included total body length (TL), measured from the front of the head to the tail tip, to the nearest 1 mm, and body weight (W), recorded in grams using a Sartorius digital scale, to the nearest 0.01 g. The condition factor index (K) was calculated using Fulton’s formula [24]:
K = W T L 3 × 100
where
  • W—body weight of the fish (g)
  • TL—total body length of the fish (cm)

2.3. Statistical Analyses

All statistical analyses were conducted in R 4.5.0 [25], primarily using the vegan package for multivariate community analysis [26]. To analyze wild fish communities inside aquaculture cages, all wild individuals recorded on harvest days were aggregated at the cage level. In cases of repeated sampling within the same cage, data were combined. Each sampling unit thus represented the full wild fish assemblage associated with a single cage. Samples were collected from aquaculture cages stocked between 2017 and 2021. For statistical analyses, only stocking generations from 2019 to 2021 were included, as data from earlier years were limited and inconsistent. Nevertheless, data from 2017 and 2018 were retained for descriptive purposes.
The abundance of farmed fish per cage was estimated by dividing the total harvested biomass by the average individual weight. Wild fish were counted separately. In all cages, the number of total harvested fish exceeded the minimum statistical sample size required for detecting wild species within a 5% margin of error.
To standardize the data, relative species abundances were calculated for each cage using the decostand() function.
Community composition was analyzed using non-metric multidimensional scaling (NMDS) based on Bray–Curtis dissimilarities, calculated from square-root-transformed relative abundances (metaMDS, k = 2). Stress values were reported to assess ordination reliability. Species vectors were fitted using envfit() for species with more than one individual, with significance assessed via permutation tests (p < 0.05).
PERMANOVA (adonis2, 999 permutations) was used to test the effects of location (7 levels), reared species (gilthead seabream, European sea bass), and stocking year (2019–2021) on wild fish community composition. Homogeneity of multivariate dispersion was tested using PERMDISP (betadisper()), followed by ANOVA.
Differences in total length, weight, and condition factor index (K) were explored descriptively using plots of arithmetic means with standard deviation bars for bogue (Boops boops) (2019–2021) and jack mackerel (Trachurus sp.) (2019) at L1, grouped by reared species (gilthead seabream SA, European sea bass DL).
The initial dataset included 2800 wild fish from 20 aquaculture cages. After excluding two cages with incomplete metadata (98 individuals), the final dataset used for statistical analyses comprised 2702 fish from 18 aquaculture cages.

3. Results

Over three months, a total of 1285.93 tons of farmed fish were examined, along with 1.04 tons of wild fish, accounting for 0.08%. Table 2 displays the presence of wild fish in samples of gilthead seabream, European sea bass, greater amberjack, meagre, and common dentex. Twelve wild fish species were recorded in association with either gilthead seabream or European sea bass as reared species across all seven locations. Individuals belonging to the family Mugilidae (M) were recorded at the family level. Trachurus (T) was identified at the genus level. All other taxa were identified at the species level: bogue (Boops boops, BB), axillary seabream (Pagellus acarne, PA), blackspot seabream (Pagellus bogaraveo, PB), chub mackerel (Scomber japonicus, SJ), salema porgy (Sarpa salpa, SS), European sea bass (Dicentrarchus labrax, DL), saddled seabream (Oblada melanura, OM), sardine (Sardina pilchardus, SP), round sardinella (Sardinella aurita, S), and common two-banded seabream (Diplodus vulgaris, DV). Recorded fish are categorized into five families, with the Sparidae family being the most diverse, featuring six species. The other families consist of Carangidae, Clupeidae, Mugilidae, and Moronidae.
A total of 2800 wild fish were recorded, with the bogue being the most prevalent at 1749 individuals, followed by jack mackerel at 686, the Mugilidae family at 167, axillary seabream at 107, chub mackerel at 59, salema porgy at 27, sardine at 10, saddled seabream at 8, round sardinella at 6, sea bass at 2, and a single two-banded seabream individual. The largest number of individuals was collected at location L1 (n = 1062), followed by L7 (n = 549) and L4 (n = 425) (Table 3).
The number of sampled cages per stocking year varied from 1 (2017, 2018) to 8 (2021). The highest number of wild fish individuals was found in cages stocked in 2021 (n = 1562), and the lowest in cages from 2018 (n = 35). Abundance per cage ranged from 4 to 713 individuals (M = 135, SD = 175).
The dataset used for community composition analyses included 2702 individuals from 18 aquaculture cages, representing 12 wild fish species. After square-root transformation and Bray–Curtis dissimilarity calculation, NMDS produced a stable two-dimensional solution (stress = 0.061), confirmed by consistent results across 20 random starts. NMDS ordination plot revealed clear spatial patterns in wild fish assemblages when grouped by location (Figure 2). Species vectors fitted with envfit() revealed that six taxa were significantly associated with the NMDS ordination (p < 0.05, n > 1). The strongest correlations were observed for bogue (BB) (r2 = 0.91), jack mackerel (T) (r2 = 0.86), and salema porgy (SS) (r2 = 0.59). These vectors indicate species that contributed most to the variation in community structure across aquaculture farm locations (Figure 2), highlighting spatial gradients in species dominance.
PERMANOVA indicated that location had a significant effect on wild fish community composition (R2 = 0.746, F = 5.39, p = 0.001). Effects of reared species (R2 = 0.117, F = 2.12, p = 0.114) and stocking year (R2 = 0.023, F = 0.37, p = 0.824) on wild fish community composition were not significant. Models with interaction terms confirmed the dominant role of location (p = 0.002); other factors and interactions were not significant. Marginal PERMANOVA tests yielded similar results: location (p = 0.001), reared species (p = 0.582), and year (p = 0.990). PERMDISP analyses showed no significant dispersion differences between groups defined by location (F = 1.51, p = 0.260), reared species (F = 0.12, p = 0.735), or year (F = 0.07, p = 0.932).
Biometric data were obtained for all twelve wild fish species and are available in Supplementary Table S3. Only bogue (Boops boops) and jack mackerel (Trachurus sp.) were present across different combinations of farm location, reared species, and stocking year, enabling a descriptive visual comparison of their biometric traits. Mean total length, weight, and condition factor index (K) for bogue (2019–2021) and jack mackerel (2019) at the L1 location are presented in Table 4 and visualized in Figure 3 and Figure 4. While visual inspection suggests potential differences in biometric values between reared species (gilthead seabream vs. European sea bass), no formal statistical testing was performed due to limited replication and unbalanced sampling. These observations should therefore be interpreted cautiously.
Biometric measures of all recorded wild taxa are presented in Supplementary Table S3.

4. Discussion

The interaction between wild and farmed fish has been a focus of research for many years. Previous studies have confirmed the presence of wild fish around Mediterranean farms [3,4,5,8]; however, their presence within farm cages remains underexplored [9,23].
This three-month study examined for the first time the presence and community structure of wild fish species in aquaculture cages in the Adriatic Sea. Our findings support earlier research showing that wild fish can survive in cage environments, a phenomenon also documented in salmon farming [19,20]. The wild fish in our study accounted for 0.08% of the total sampled fish biomass, which is likely due to their ability to adapt and coexist with farmed species. Wild fish were only present in gilthead seabream and European sea bass aquaculture cages, with no wild fish seen in meagre, greater amberjack, or common dentex cages. The farming technology was the same and does not seem to explain the absence of wild fish in some reared species. The common dentex, greater amberjack, and meagre are predators [27], which may be a reason why wild fish have not been able to coexist there. Predators usually prefer live prey over pelleted food, even when pellets are available [9]. Predators have been observed in salmon farms, where wild fish serve as prey for farmed fish, accounting for approximately 0.1% of the diet of farmed salmon [22].
The wild fish community structure in our study aligns with earlier research on wild fish near cages of European sea bass and gilthead seabream [4,7,8]. Since wild fish populations in cages have not been extensively studied, it is not possible to compare our study with others. This study did not include control sites outside of cages; however, earlier studies have reported up to 38 wild fish species around fish farms in the Mediterranean [3,5,8]. In our samples from inside the cages, we recorded twelve wild species.
Overall, we recorded 12 fish taxa across five families. The most prevalent family was Sparidae, with five species, among which the bogue was the most common, representing 62% of the total sampled wild fish, followed by jack mackerel at 24%. The importance of both Sparidae and Carangidae members was reported in previous studies near European sea bass and gilthead seabream farms [4,7].
Earlier studies identified bogue as the dominant wild fish species around Mediterranean fish farms, as was the case in our study. In the wild fish population, the proportion of bogue ranged from 40.97% [7] to as much as 80.5% [8].
Our results suggest that wild fish richness and abundance appeared higher in gilthead seabream cages compared to European sea bass cages, with 11 taxa recorded in gilthead seabream cages and 6 in European sea bass cages. However, this trend was not statistically significant, and the only significant factor shaping wild fish communities was location. Notably, species from the Clupeidae and Moronidae families were absent in the sea bass cages. This may indicate that Clupeidae species were preyed upon by European sea bass. The only Moronidae species observed in the gilthead seabream cages was the European sea bass, which could not be distinguished from those in the European sea bass farm cages. Multivariate analysis showed that location had a significant influence on the composition of wild fish assemblages. Spatial patterns in wild fish community composition, visualized using NMDS ordination (Figure 2), revealed distinct clustering of certain locations, suggesting that site-specific environmental and biological factors influenced assemblage structure inside aquaculture cages. Although environmental factors such as depth, coastal proximity, and surrounding habitat types likely influenced the observed differences in wild fish communities across locations, these variables could not be statistically tested due to the lack of replication across sites. Each location had a unique combination of environmental conditions, and sampling units (cages) were nested within those locations, preventing formal isolation of individual environmental drivers. Previous studies indicate that location significantly impacts the composition of the wild fish community around the cage [3,5,8]. In our research, for example, location L7 was characterized by high species richness (n = 8) and wild fish abundance (n = 549). The high within-site variability in mean abundance (SD = 351.4) suggests a more heterogeneous assemblage, which likely contributed to the spatial separation of L7 in the NMDS ordination space. Ecological characteristics of L7 may further explain this pattern (Table 1). The site is located in a shallow and enclosed coastal area, with a maximum depth of only –40 m and a minimum distance from the coastline of 50 m. Additionally, the location is far away from all other locations. These factors could potentially lead to a distinct community structure. Location L2 also appeared as an outlier in the NMDS ordination, likely driven by a combination of environmental and biological factors. Located more than one kilometer from the coast, the farthest offshore among all locations, this location may have higher water exchange and reduced retention of organic matter around the cages. Although species richness was high (n = 8), total wild fish abundance was relatively low (n = 163), and the dominant species, bogue (BB), was virtually absent, with only 14 individuals recorded in total. The combination of low overall abundance and limited presence of key structuring species may have contributed to the distinct community composition observed at this site. Finally, locations L6 and L3 were both characterized by low species richness (n = 2 and n = 4, respectively). In both cases, bogue (BB) dominated the wild fish assemblages. This dominance, in combination with the lack of community complexity, might explain the clustering of L6 and L3 in the NMDS ordination space, in the direction of the bogue vector. The effects of reared species and farming duration in our study did not significantly affect the wild fish community structure in the cages.
The five species were present in both farmed species: bogue, jack mackerel, Mugilidae, salema porgy, and round sardinella. Only one species, the bogue, was present in both farmed species and at all locations, which may indicate the species’ ability to adapt to different locations and challenges arising from coexistence with various types of fish.
The attractiveness of commercial food to bogue may explain their abundance both inside and outside the cages. Previous studies of the stomach contents of wild fish around cages have found that bogue had 90% of their stomachs filled with pellets fed to reared species [5]. At the location L1, we had data on the bogue from two rearing species and three stocking years, which provided us with the opportunity to analyze the differences in the biometric characteristics of the bogue under different conditions. The mean weight and total length of the bogue in gilthead seabream cages tended to increase with a longer rearing period. In contrast, in European sea bass cages, both the mean weight and total length of bogue tend to decrease with a longer rearing period.
In this study, the average condition factor index for caged bogue was high; in gilthead seabream cages at location L1, it was 1.33 in cages stocked in 2020 and 2021, and slightly higher at 1.36 in cages from 2019. This aligns with a previous study that bogue near cages showed a higher condition factor index than those farther from the farm [28,29]. Furthermore, study [23] found that bogue close to the cage had indices between 1.01 and 1.02, whereas those inside the cage ranged from 1.17 to 1.19.
However, it is crucial to note that all bogue individuals were adults, and our research took place during the bogue spawning season, which may have influenced the findings. The largest bogue recorded in our study measured 39.8 cm and weighed 949 g (Supplementary Table S3), both exceeding previously documented sizes of wild bogue for the Adriatic Sea and the Mediterranean and wild bogue near cages [5,6,27,30].
The total length of jack mackerel at L1 was similar in both reared species and lower than previously reported by [5] for this species. The differences in mean weight reflect a lower condition factor index in the European sea bass cages. The largest jack mackerel in our study measured 39 cm in length and weighed 662 g (Supplementary Table S3). Biometric data from wild fish in cages with farmed fish suggest that their coexistence is successful and that they obtain sufficient food to achieve a higher condition factor index. Analysis of previous data suggests that these wild fish likely receive more food than they would in their natural habitat, and the length of their coexistence was enough to influence their condition [5]. Moreover, other species not observed in our study might have entered the cages but either failed to adapt to long-term rearing conditions or fell prey to predators. While this study does not offer conclusive answers, it highlights areas for future research.
Wild fish populations are often mentioned in biosecurity discussions related to farmed fish. Contact between wild and farmed fish facilitates disease transmission, posing a significant challenge in managing the health of farmed fish, especially during times of rising sea temperatures [31]. The bogue is a species often overlooked but plays a role in disease transmission. It is frequently cited for its potential to spread diseases to farms and to be affected by them [32,33,34]. As a member of the same family as the gilthead seabream, it presents a risk for transmitting host-specific parasites between the two species. Given that it is the most numerous fish around and inside cages, supported by our findings and previous reports, it should be included in biosecurity plans alongside other common wild fish near cages.
Our research offers valuable insights for evaluating the ecological impacts of mariculture and enhancing biosecurity prevention and management strategies. We also emphasize the need to understand how and which wild fish can coexist with farmed fish and to support measures that prevent their entry.

5. Conclusions

Farming cages attract a variety of wild fish species, which are drawn in by the food source and shelter from predators. This research confirmed that some species of wild fish can enter these cages and coexist alongside farmed gilthead seabream and European sea bass; however, no wild fish were observed in the cages of farmed meagre, greater amberjack, and common dentex. The bogue emerged as the most prevalent wild fish species, aligning with previous studies conducted in the Mediterranean Sea. This research confirms the importance of monitoring interactions between farmed and wild fish to better understand the environmental impacts of aquaculture. Future research should focus on precisely identifying the methods by which wild fish enter cages and aim to clarify ways to reduce their presence within farming installations.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/fishes10100504/s1, Figure S1: Detailed map of Zadar County study sites; Table S1: Overview of benthic habitat types within aquaculture zones (AZAs) across the seven farm locations surveyed in this study (L1–L7); Table S2: Sampling effort and net management per cage; Table S3: Summary of biometric characteristics of wild fish species recorded inside Adriatic marine aquaculture cages.

Author Contributions

Conceptualization, S.Č., I.Z.Č., R.M., B.B., F.T., T.G., T.Š., R.B., B.M., I.Ž., and L.B.; Data curation, S.Č., I.Z.Č., and L.B.; Formal analysis, S.Č., I.Z.Č., R.M., B.B., F.T., T.G., and L.B.; Funding acquisition, S.Č.; Investigation, S.Č., B.B., F.T., T.G., R.B., and L.B.; Methodology, S.Č. and L.B.; Project administration, S.Č.; Resources, S.Č.; Supervision, S.Č. and L.B.; Validation, S.Č.; Visualization, I.Z.Č. and R.M.; Writing—original draft, S.Č. and L.B.; Writing—review & editing, S.Č., I.Z.Č., R.M., T.Š., R.B., B.M., I.Ž., and L.B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Regarding the Ethical statement, it is not applicable to this study. The EU legislation regarding fish farming operations does not require an ethical review beyond those already included in the EU Directive 98/58 and the recommendation of the Standing Committee of the European Convention on the Protection of Animals kept for Farming Purposes (https://www.coe.int/t/e/legal_affairs/legal_co-operation/biological_safety_and_use_of_animals/Farming/Rec%20fish%20E.asp, accessed on 15 September 2025). This research was conducted under standard production conditions and in full compliance with the animal welfare regulations applicable to aquaculture in the Republic of Croatia and the European Union. Data were collected during routine farming practices at an aquaculture site, with all handling and harvesting of fish carried out by the farm operators under national legal frameworks. The production company is certified according to GlobalG.A.P. and Aquaculture Stewardship Council (ASC) standards, which ensure high levels of animal welfare. The researchers only recorded biometric data on wild fish that had already been captured during regular farm operations. Relevant certification documents are provided as an attachment.

Data Availability Statement

The data presented in this study are available on request from the corresponding author upon reasonable request.

Acknowledgments

The research was carried out in the framework of the TIDE project supported by the University of Zadar. The authors would like to thank the Cromaris R&D team for technical support and assistance during this research.

Conflicts of Interest

Author Renata Barić was employed by the company Cromaris d.d. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as potential conflicts of interest.

References

  1. Troell, M.; Costa-Pierce, B.; Stead, S.; Cottrell, R.S.; Brugere, S.; Farmery, A.K.; Little, D.L.; Strand, A.; Pullin, R.; Soto, D.; et al. Perspectives on aquaculture’s contribution to the Sustainable Development Goals for improved human and planetary health. J. World Aquac. Soc. 2023, 54, 251–342. [Google Scholar] [CrossRef]
  2. Milošević, R.; Šarić, T.; Bavčević, L.; Datković, A.; Čolak, S.; Župan, I. Mariculture in Croatia: A Spatial Perspective. Naše More Znan. Časopis More Pomor. 2024, 71, 98–108. [Google Scholar] [CrossRef]
  3. Dempster, T.; Sanchez-Jerez, P.; Bayle-Sempere, J.T.; Giménez-Casalduero, F.; Valle, C. Attraction of wild fish to sea-cage fish farms in the south-western Mediterranean Sea: Spatial and short-term temporal variability. Mar. Ecol. Prog. Ser. 2002, 242, 237–252. [Google Scholar] [CrossRef]
  4. Valle, C.; Bayle-Sempere, J.T.; Dempster, T.; Sanchez-Jerez, P.; Giménez-Casalduero, F. Temporal variability of wild fish assemblages associated with a sea-cage fish farm in the south-western Mediterranean Sea. Estuar. Coast. Shelf Sci. 2007, 72, 299–307. [Google Scholar] [CrossRef]
  5. Fernandez-Jover, D.; Sanchez-Jerez, P.; Bayle-Sempere, J.T.; Valle, C.; Dempster, T. Seasonal patterns and diets of wild fish assemblages associated with Mediterranean coastal fish farms. The International Credential Evaluation Service. J. Mar. Sci. 2008, 65, 1153–1160. [Google Scholar]
  6. Šegvić Bubić, T.; Grubišić, L.; Tičina, V.; Katavić, I. Temporal and spatial variability of pelagic wild fish assemblages around Atlantic bluefin tuna Thunnus thynnus farms in the eastern Adriatica Sea. J. Fish Biol. 2011, 78, 78–97. [Google Scholar] [CrossRef]
  7. Ballester-Moltó, M.; Sanchez-Jerez, P.; García-García, B.; Aguado-Giménez, F. Husbandry and environmental conditions explain temporal variability of wild fish assemblages aggregated around a Mediterranean fish farm. Aquac. Environ. Interact. 2015, 7, 193–203. [Google Scholar] [CrossRef]
  8. Akyol, O.; Özgül, A.; Düzbastılar, F.O.; Şen, H.; de Urbina, J.M.O.; Ceyhan, T. Seasonal variations in wild fish aggregation near sea-cage fish farms in the Turkish Aegean Sea. Aquac. Rep. 2020, 18, 100478. [Google Scholar] [CrossRef]
  9. Sanchez-Jerez, P.; Fernandez-Jover, D.; Bayle-Sempere, J.; Valle, C.; Dempster, T.; Tuya, F.; Juanes, F. Interactions between bluefish Pomatomus saltatrix (L.) and coastal sea-cage farms in the Mediterranean Sea. Aquaculture 2008, 282, 61–67. [Google Scholar] [CrossRef]
  10. Şensurat-Genç, T.; Akyol, O.; Özgül, A.; Özden, U. Food composition of whiting Merlangius merlangus, captured around the sea-cage fish farms in Ordu, South-Eastern Black Sea. J. Mar. Biol. Assoc. United Kingd. 2019, 99, 1651–1659. [Google Scholar] [CrossRef]
  11. Tuya, F.; Sanchez-Jerez, P.; Dempster, T.; Boyra, A.; Haroun, R.J. Changes in demersal wild fish aggregations beneath a sea-cage fish farm after the cessation of farming. J. Fish Biol. 2006, 69, 682–697. [Google Scholar] [CrossRef]
  12. McConnell, A.; Routledge, R.; Connors, B.M. Effect of artificial light on marine invertebrate and fish abundance in an area of salmon farming. Mar. Ecol. Prog. Ser. 2010, 419, 147–156. [Google Scholar] [CrossRef]
  13. Castro, J.; Santiago, J.S.; Santana-Ortega, A.T. A general theory on fish aggregation to floating objects: An alternative to the meeting point hypothesis. Rev. Fish Biol. Fish. 2002, 11, 255–277. [Google Scholar] [CrossRef]
  14. Daszak, P.; Cunningham, A.A.; Hyatt, A.D. Emerging infectious diseases of wildlife--threats to biodiversity and human health. Science 2000, 21, 443–449. [Google Scholar] [CrossRef]
  15. Arechavala-Lopez, P.; Sanchez-Jerez, P.; Bayle-Sempere, J.T.; Uglem, I.; Mladineo, I. Reared fish, farmed escapees and wild fish stocks-a triange of pathogen transmission of concern to Mediterranean aquaculture management. Aquac. Environ. Interact. 2013, 3, 153–161. [Google Scholar] [CrossRef]
  16. Bandín, I.; Souto, S. Betanodavirus and VER Disease: A 30-year Research Review. Pathogens 2020, 9, 106. [Google Scholar] [CrossRef] [PubMed]
  17. Padrós, F.; Caggiano, M.; Toffan, A.; Constenla, M.; Zarza, C.; Ciulli, S. Integrated Management Strategies for Viral Nervous Necrosis (VNN) Disease Control in Marine Fish Farming in the Mediterranean. Pathogens 2022, 11, 330. [Google Scholar] [CrossRef]
  18. Salogni, C.; Bertasio, C.; Accini, A.; Gibelli, L.R.; Pigoli, C.; Susini, F.; Podavini, E.; Scali, F.; Varisco, G.; Alborali, G.L. The Characterisation of Lactococcus garvieae Isolated in an Outbreak of Septicaemic Disease in Farmed Sea Bass (Dicentrarchus labrax, Linnaues 1758) in Italy. Pathogens 2024, 13, 49. [Google Scholar] [CrossRef] [PubMed]
  19. Fjelldal, P.G.; Solberg, M.F.; Glover, K.A.; Folkedal, O.; Nilsson, J.; Finn, R.N.; Hansen, T.J. Documentation of multiple species of marine fish trapped in Atlantic salmon sea-cages in Norway. Aquat. Living Resour. 2018, 31, 31. [Google Scholar] [CrossRef]
  20. Fitridgea, I.; Dempstera, T.; Guentherb, J.; de Nysc, R. The impact and control of biofouling in marine aquaculture: A review. Biofouling 2012, 28, 649–669. [Google Scholar] [CrossRef]
  21. Araujo, G.S.; Silva, J.W.A.D.; Cotas, J.; Pereira, L. Fish farming techniques: Current situation and trends. J. Mar. Sci. Eng. 2022, 10, 1598. [Google Scholar] [CrossRef]
  22. Proboszcz, S. Wild Fish Trapped: Incidental Catch in the Salmon Farming Industry; Watershed Watch Salmon Society: Vancouver, BC, Canada, 2019; pp. 1–16. [Google Scholar]
  23. Mustać, B.; Bavčević, L.; Petani, B.; Grgić, T.; Franov, Š.; Ušalj, Š.; Marketin, M.; Babin, B.; Čolak, S. Relationship between Body Condition and Gonadosomatic Index of the Bogue (Boops Boops) from the Middle Part of the Eastern Adriatic Sea. Naše More Znan. Časopis More Pomor. 2024, 71, 91–97. [Google Scholar] [CrossRef]
  24. Bagenal, T.B.; Tesch, F.W. Age and Growth. In Methods for Assessment of Fish Production in Fresh Waters; Bagenal, T.B., Ed.; Blackwell Scientific Publications: Oxford, UK, 1978; pp. 101–136. [Google Scholar]
  25. R Core Team. R: A Language and Environment for Statistical Computing, (Version 4.5.0); R Foundation for Statistical Computing: Vienna, Austria, 2025. Available online: https://www.R-project.org/.
  26. Oksanen, J.; Simpson, G.; Blanchet, F.; Kindt, R.; Legendre, P.; Minchin, P.; O’Hara, R.; Solymos, P.; Stevens, M.; Szoecs, E.; et al. Vegan: Community Ecology Package, (R package Version 2.7-1), Cran: Vienna, Austria, 2025. [CrossRef]
  27. Jardas, I. Jadranska Ihtiofauna; Školska knjiga: Zagreb, Croatia, 1996; pp. 268–269. [Google Scholar]
  28. Arechavala-Lopez, P.; Sanchez-Jerez, P.; Bayle-Sempere, J.; Fernandez-Jover, D.; Martinez-Rubio, L.; Lopez-Jimenez, J.A.; Martinez-Lopez, F.J. Direct interaction between wild fish aggregations at fish farms and fisheries activity at fishing grounds: A case study with Boops boops. Aquac. Res. 2011, 42, 996–1010. [Google Scholar] [CrossRef]
  29. Fernandez-Jover, D.; Faliex, E.; Sanchez-Jerz, P.; Sasal, P.; Bayle-SWempere, J.T. Coastal fish farming does not affect the total parasite communities of wild fish in SW Mediterranean. Aquaculture 2010, 300, 10–16. [Google Scholar] [CrossRef]
  30. Crec’hriou, R.; Neveu, R.; Lenfant, P. Length–weight relationship of main commercial fishes from the French Catalan coast. J. Appl. Ichthyol. 2012, 28, 861–862. [Google Scholar] [CrossRef]
  31. Garrabou, J.; Gómez-Gras, D.; Medrano, A.; Cerrano, C.; Ponti, M.; Schlegel, R.; Harmelin, J.G. Marine heatwaves drive recurrent mass mortalities in the Mediterranean Sea. Glob. Change Biol. 2022, 28, 5708–5725. [Google Scholar] [CrossRef] [PubMed]
  32. Šarušić, G. Preliminary report of infestation by isopod Cerathotoa oestroides (Risso 1826), in marine cultured fish. Bull. Eur. Ass. Fish Pathol. 1998, 19, 110–113. [Google Scholar]
  33. Mladineo, I.; Maršić-Lučić, J. Host Switch of Lamellodiscus elegans (Monogenea: Monopisthocotylea) and Sparicotyle chrysophrii (Monogenea: Polyopisthocotylea) between Cage-reared Sparids. Vet. Res. Commun. 2007, 31, 153–160. [Google Scholar] [CrossRef] [PubMed]
  34. Mladineo, I.; Šegvić, T.; Grubišić, L. Molecular evidence for the lack of transmission of the monogenean Sparicotyle chrysophrii (Monogenea, Polyopisthocotylea) and isopod Ceratothoa oestroides (Crustacea, Cymothoidae) between wild bogue (Boops boops) and cage-reared sea bream (Sparus aurata) and sea bass (Dicentrarchus labrax). Aquaculture 2009, 295, 160–167. [Google Scholar] [CrossRef]
Figure 1. Farm locations in Zadar County (L1—Kosara, L2—Lavdara, L3—Lamjana, L4—Zman, L5—Velo Zalo, L6—Kudica) and Istria County (L7—Budava).
Figure 1. Farm locations in Zadar County (L1—Kosara, L2—Lavdara, L3—Lamjana, L4—Zman, L5—Velo Zalo, L6—Kudica) and Istria County (L7—Budava).
Fishes 10 00504 g001
Figure 2. NMDS ordination of wild fish assemblages inside aquaculture cages, based on Bray–Curtis dissimilarities. Each point represents one cage (code = reared species and stocking year; SA = Sparus aurata, DL = Dicentrarchus labrax), colored and shaped by location. The left panel shows site-level NMDS positions; the right panel includes significant species vectors fitted with the envfit() function (p < 0.05). Arrow direction indicates increasing abundance, and length is scaled by r2. Species codes: BB = Boops boops, T = Trachurus sp., M = Mugilidae, PA = Pagellus acarne, SJ = Scomber japonicus, SS = Salpa sarpa.
Figure 2. NMDS ordination of wild fish assemblages inside aquaculture cages, based on Bray–Curtis dissimilarities. Each point represents one cage (code = reared species and stocking year; SA = Sparus aurata, DL = Dicentrarchus labrax), colored and shaped by location. The left panel shows site-level NMDS positions; the right panel includes significant species vectors fitted with the envfit() function (p < 0.05). Arrow direction indicates increasing abundance, and length is scaled by r2. Species codes: BB = Boops boops, T = Trachurus sp., M = Mugilidae, PA = Pagellus acarne, SJ = Scomber japonicus, SS = Salpa sarpa.
Fishes 10 00504 g002
Figure 3. Mean weight, total length, and condition factor index (K) of bogue (Boops boops) recorded inside aquaculture cages stocked with reared European sea bass (DL) or gilthead seabream (SA) during the 2019–2021 stocking years. Error bars indicate ±1 standard deviation. The sample size (n) is labeled next to each data point.
Figure 3. Mean weight, total length, and condition factor index (K) of bogue (Boops boops) recorded inside aquaculture cages stocked with reared European sea bass (DL) or gilthead seabream (SA) during the 2019–2021 stocking years. Error bars indicate ±1 standard deviation. The sample size (n) is labeled next to each data point.
Fishes 10 00504 g003
Figure 4. Mean weight, total length, and condition factor index (K) of jack mackerel (Trachurus sp.) recorded inside aquaculture cages stocked with reared European sea bass (DL) or gilthead seabream (SA) in 2019 stocking year. Error bars indicate ±1 standard deviation. Sample size (n) is displayed next to each point.
Figure 4. Mean weight, total length, and condition factor index (K) of jack mackerel (Trachurus sp.) recorded inside aquaculture cages stocked with reared European sea bass (DL) or gilthead seabream (SA) in 2019 stocking year. Error bars indicate ±1 standard deviation. Sample size (n) is displayed next to each point.
Fishes 10 00504 g004
Table 1. Environmental and production characteristics of the farm locations.
Table 1. Environmental and production characteristics of the farm locations.
Farm LocationAZA Area (ha)Farms Area (ha)Cultivated Species in AZAMax. Yield (t)Total Farms (n)Total Cages (n)Min. Depth (m)Max. Depth (m)Min. Coastal Distance (m)
L1. Kosara 40829.37DL, SA, DD, AR, SD4310587−10−5244
L2. Lavdara 75726.34DL, SA, AR 2000440−20−641082
L3. Lamjana 87152.68DL, SA, DD, AR, SD2520560−12−5556
L4. Zman 15855.32DL, SA, AR3000139−42−64277
L5. Velo Zalo 10811.06DL, SA, AR1101246−17−4436
L6. Kudica 16423.22DL, SA, AR700128−30−44375
L7. Budava 11111.48DL, SA1100326−10−4050
Reared species codes: DL = European sea bass (Dicentrarchus labrax), SA = Gilthead seabream (Sparus aurata), DD = Common dentex (Dentex dentex), AR = Meagre (Argyrosomus regius), SD = Greater amberjack (Seriola dumerili). AZA = Allocated Zones for Aquaculture.
Table 2. Presence of wild fish taxa in sea cages of five farmed fish species. Columns represent farmed fish species, while rows represent wild fish taxa. The occurrence of a wild taxon in a cage is indicated by a plus sign (+), whereas a minus sign (−) denotes its absence.
Table 2. Presence of wild fish taxa in sea cages of five farmed fish species. Columns represent farmed fish species, while rows represent wild fish taxa. The occurrence of a wild taxon in a cage is indicated by a plus sign (+), whereas a minus sign (−) denotes its absence.
TaxonSparus aurataDicentrarchus labraxSeriola dumeriliArgyrosomus regiusDentex dentex
Carangidae
Scomber japonicus+
Trachurus sp.++
Clupeidae
Sardina pilchardus+
Sardinella aurita++
Moronidae
Dicentrarchus labrax+n/a
Mugilidae++
Sparidae
Boops boops++
Pagellus acarne+
Pagellus bogaraveo+
Sarpa salpa++
Oblada melanura+
Diplodus vulgaris+
Table 3. Summary of sampling effort across aquaculture locations (L1–L7). For each location and reared species, the table shows the number of sampled cages (n cages), number of wild fish species (n species), and total number of wild fish individuals (Abundance). The mean (M), standard deviation (SD), minimum (Min), and maximum (Max) values refer to the abundance of wild fish per cage, calculated for all sampled cages with the same reared species at a given location. Stocking years refer to the year in which farmed fish were introduced into each sampled cage.
Table 3. Summary of sampling effort across aquaculture locations (L1–L7). For each location and reared species, the table shows the number of sampled cages (n cages), number of wild fish species (n species), and total number of wild fish individuals (Abundance). The mean (M), standard deviation (SD), minimum (Min), and maximum (Max) values refer to the abundance of wild fish per cage, calculated for all sampled cages with the same reared species at a given location. Stocking years refer to the year in which farmed fish were introduced into each sampled cage.
LocationReared Speciesn cagesn species AbundanceM SD Min Max Stocking Years
L1Sparus aurata4 5 968 242 317.2 35 713 2019, 2021
Dicentrarchus labrax2 3 94 47 17 35 59 2018, 2019
L2Sparus aurata2 8 163 81.5 21.9 66 97 2021
L3Sparus aurata1 2 69 69 NA 69 69 2019
Dicentrarchus labrax2 4 324 162 140 63 261 2017, 2020
L4Sparus aurata2 7 425 212.5 268 23 402 2019
L5Dicentrarchus labrax3 4 92 30.7 26.1 10 60 2019, 2020, 2021
L6Sparus aurata2 2 116 58 76.4 4 112 2020, 2021
L7Sparus aurata2 8 549 274.5 351.4 26 523 2020, 2021
Table 4. Summary statistics for biometric data (mean ± SD) of bogue (Boops boops) and jack mackerel (Trachurus sp.) sampled inside aquaculture cages at location L1. Data are shown by reared species (DL = Dicentrarchus labrax, SA = Sparus aurata) and stocking year.
Table 4. Summary statistics for biometric data (mean ± SD) of bogue (Boops boops) and jack mackerel (Trachurus sp.) sampled inside aquaculture cages at location L1. Data are shown by reared species (DL = Dicentrarchus labrax, SA = Sparus aurata) and stocking year.
SpeciesVariableReared SpeciesStocking YearMean ± SD
Jack mackerel (T)weight (g)Dicentrarchus labrax (DL)2019147.39 ± 46.40
length (cm)201924.04 ± 2.35
K20191.04 ± 0.06
weight (g)Sparus aurata (SA)2019183.36 ± 138.31
length (cm)201924.16 ± 5.41
K20191.07 ± 0.17
Bogue (BB)weight (g)Dicentrarchus labrax (DL)2019316.36 ± 105.97
2020494.87 ± 92.91
2021491.41 ± 52.11
Sparus aurata (SA)2019501.40 ± 145.19
2020349.08 ± 171.51
2021356.99 ± 122.16
length (cm)Dicentrarchus labrax (DL)201928.17 ± 3.22
202033.43 ± 2.12
202133.76 ± 1.00
Sparus aurata (SA)201932.94 ± 3.39
202028.81 ± 4.60
202129.59 ± 3.27
KDicentrarchus labrax (DL)20191.39 ± 0.21
20201.32 ± 0.21
20211.28 ± 0.12
Sparus aurata (SA)20191.36 ± 0.16
20201.33 ± 0.16
20211.33 ± 0.18
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

Čolak, S.; Zubak Čižmek, I.; Milošević, R.; Babin, B.; Tafra, F.; Grgić, T.; Šarić, T.; Barić, R.; Mustać, B.; Župan, I.; et al. Occurrence and Community Structure of Wild Fish Within Adriatic Sea Fish Farms. Fishes 2025, 10, 504. https://doi.org/10.3390/fishes10100504

AMA Style

Čolak S, Zubak Čižmek I, Milošević R, Babin B, Tafra F, Grgić T, Šarić T, Barić R, Mustać B, Župan I, et al. Occurrence and Community Structure of Wild Fish Within Adriatic Sea Fish Farms. Fishes. 2025; 10(10):504. https://doi.org/10.3390/fishes10100504

Chicago/Turabian Style

Čolak, Slavica, Ivana Zubak Čižmek, Rina Milošević, Bruna Babin, Filip Tafra, Tomislav Grgić, Tomislav Šarić, Renata Barić, Bosiljka Mustać, Ivan Župan, and et al. 2025. "Occurrence and Community Structure of Wild Fish Within Adriatic Sea Fish Farms" Fishes 10, no. 10: 504. https://doi.org/10.3390/fishes10100504

APA Style

Čolak, S., Zubak Čižmek, I., Milošević, R., Babin, B., Tafra, F., Grgić, T., Šarić, T., Barić, R., Mustać, B., Župan, I., & Bavčević, L. (2025). Occurrence and Community Structure of Wild Fish Within Adriatic Sea Fish Farms. Fishes, 10(10), 504. https://doi.org/10.3390/fishes10100504

Article Metrics

Back to TopTop