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Article

Ecological Indicative Stressors of Native vs. Non-Native Fish in an Ultra-Oligotrophic Region of the Mediterranean Sea

1
Department of Basic Sciences, Fisheries Faculty, Akdeniz University, Main Campus, 07058 Antalya, Turkey
2
Independent Researcher, 50060 Londa, FI, Italy
3
Independent Researcher, 72020 Cellino San Marco, BR, Italy
*
Author to whom correspondence should be addressed.
Sustainability 2023, 15(3), 2726; https://doi.org/10.3390/su15032726
Submission received: 15 December 2022 / Revised: 23 January 2023 / Accepted: 25 January 2023 / Published: 2 February 2023
(This article belongs to the Section Sustainable Oceans)

Abstract

:
In the present study, we investigated the different ecological characteristics of native and non-native demersal fish collected in 2014–2015 on the shelf of the Antalya Gulf in the Eastern Mediterranean Sea. Lessepsian migrants originating from the Indo-Pacific Ocean were classified as non-indigenous species (NIS) and the other species, which were mostly Atlanto-Mediterranean, were classified as indigenous species (IS). The results showed that the faunistic characteristics of IS and NIS differed significantly in space but only partly over time. The density and species diversity of the IS increased with the seafloor depth, while the opposite pattern was observed for the NIS, which were found mostly in shallow waters. Proximity to rivers and Posidonia oceanica meadows and the presence of a marine protected area (MPA) were also important factors determining the differences in the ecological characteristics of IS and NIS. The ecological ordination of the fish assemblages in the canonical correspondence analysis (CCA) space was V-shaped for the IS and =-shaped for the NIS, and it was mainly determined by bottom depth. Altogether, the ordination took the shape of a double strikethrough (V) due to the NIS filling an available niche. Hierarchically, the NIS (“occupiers”) and IS (“resisters”) shared the shallowest waters, while the middle-shelf waters were occupied by NIS (“gapers”) and IS (“escapers”) separately. The upper shelf was occupied only by IS (“homekeepers”) and “minorities” of NIS. Finally, we identified eight factors as ecological indicators of NIS and IS: bottom depth, bottom vegetation status, fish hierarchy, key species, water productivity, fish trophic level, life strategy and morphometry.

1. Introduction

Investigating the ecological characteristics of NIS in new areas can contribute to knowledge on the dynamics of these species that may be relevant for the entire Mediterranean. Research interest in non-indigenous species—also known as alien species—has increased significantly in recent decades, especially in the Mediterranean Sea, which can be considered one of the main invasion hotspots worldwide. Many newcomers to the Mediterranean are of Indo-Pacific origin, but they can also come from the Atlantic as a result of natural invasion through the Strait of Gibraltar or introduction by humans. The introduction of alien species can have negative effects on native biodiversity and local food webs, as well as social and economic impacts. In particular, monitoring of the populations of different fish taxa is of paramount importance due to their commercial value and relevance as a food source. In the present study, we defined non-indigenous species (NIS) as those fish species originating in the Indo-Pacific and Red Sea, and most of the other fish were of Atlanto-Mediterranean origin [1].
The Mediterranean Sea is inhabited by more than 700 fish species [2,3]. Among these species, at least 80 are non-indigenous migrants from the Red Sea and Indo-Pacific [4,5]. The migration of tropical species from the Red Sea to the Mediterranean started following the building up of the Suez Canal in 1869. Reverse migration is considered negligible, and the migration direction is mainly influenced by long-term differences in hydrological conditions, such as temperature, salinity and water level, between the Mediterranean and Red Sea [6]. Shipping activities seem to be the most significant pathway for the introduction of NIS, and their migration rate has recently increased since the enlargement of the Suez Canal was completed in 2015 [7].
The Eastern Mediterranean basin is generally more exposed to the introduction of NIS compared to the western basin because of its peculiar physical and biological conditions. A total of 106 alien fish species have been reported in the Eastern Mediterranean [8]. These species correspond to nearly 70% of the alien fish known in the Mediterranean and are mostly of Indo-Pacific origin [8]. In Turkish Mediterranean waters, a total of 74 alien fish species (66 Indo-Pacific and 8 Atlantic) have been recorded [9].
In general, in the Levantine Sea, which is located in the Eastern Mediterranean, the maximum numbers of fish species have been recorded off Israel and in İskenderun Bay, Turkey (253–272 species). The other parts of the Turkish coast have fish species numbers varying between 168 and 252, depending on the productivity of the different regions [10,11].
Furthermore, the ecosystems of the Eastern Mediterranean show a degradation pattern over time caused mainly by alterations resulting from trophic interactions, climate change and fishing activities [10,11,12,13,14,15,16,17,18,19,20,21]. In particular, fishing activities can have a noticeable impact on ecosystems, and it has been suggested that 7.1% of the total primary production is required to sustain fisheries in this area [22].
Conditions facilitating the introduction, establishment and colonizing activities of NIS are usually related to the physical and biological characteristics of the new colonized habitats, including mechanisms of interaction with indigenous species. Continuous propagule pressure is also considered a major driver for the establishment of NIS in a new environment [13,23].
Climate matching is an important factor determining the dispersal success of NIS [14], and global change is favoring the geographical expansion of some ‘‘winner’’ species [24]. Increasing water temperature in the Eastern Mediterranean Sea is favoring the establishment of alien tropical species in a process of so-called “tropicalization” [25,26]. Environmental suitability also depends on other abiotic factors, such as habitat structure, seafloor depth and primary productivity levels [27]. The Levantine Sea, in particular, is a warm and highly oligotrophic area. These features may be associated with higher trophic levels and “Levantine nanism”, a phenomenon characterized by smaller body sizes among species in the Levant compared to conspecifics from other parts of the Mediterranean [28,29]. The invasion success of NIS is also determined by their size composition, life history strategies, length at first maturity, spawning type [22,27,30], ability to be active during the day and schooling level [4,15,23,31]. Moreover, NIS may have specific feeding preferences, and their establishment depends on resource partitioning with native species [16,27,32,33]. NIS may fill all niches available in a community and replace native fish with similar trophic levels [17]. NIS may also interact with each other in the new environment. For example, according to the invasional meltdown hypothesis, non-native species can facilitate invasion by and survival of other alien species over time [34]. New vacant niches may also be created by human activities, such as fishing [35,36,37], depending on species resilience [27], fishing season [18], catch compositions and discard percentages [38] and the suitability of marine protected areas [39].
From an alternative perspective, we can take note of the Bimodal Oscillating System (BiOS), a process that leads to switching of the circulation pattern of the North Ionian Gyre (NIG) between cyclonic and anticyclonic in decadal intervals in the Ionian Sea and can affect the thermohaline properties in the Southern Adriatic [40]. Therefore, the BiOS influences the Levantine surface water (LSW) and Levantine intermediate water (LIW) via the Ionian jet [41]. The Ionian jet carries the waters linked with the Southern Adriatic current toward the East Mediterranean, influencing the water salinity and nutrient levels of the study area via the Rhodes Gyre [41] when the NIG turns to cyclonic circulation.
Global warming and uncontrolled introduction of NIS are leading the Mediterranean Sea to a new state, with differences at the regional scale [42]. However, knowledge about the ecological impact of Lessepsian species on native ones is still limited [43]. In the present study, we explored the spatiotemporal distribution and compared different quantitative and qualitative parameters of NIS and IS fish from the shelf of the Antalya Gulf, one of the few ultra-oligotrophic coastal areas of the Mediterranean Sea.

2. Materials and Methods

The study area was selected since it has been classified as an oligotrophic area [10,11] that provides a natural in situ mesocosm without extra nutrients and as an area with a wider shelf extension that exhibits a gradual change in the fish assemblage with increasing bottom depth. Another reason was that the NIS species were established later in the present study area than along other Turkish coasts (İskenderun and Mersin Bay) impacted by anthropogenic effects [1]. Sampling was carried out on board the R/V Akdeniz Su at an average speed of 2.5 knots for approximately 30 min using a conventional commercial otter trawl (35 m headline and 88 mm diamond mesh size for the wings, 44 mm for the codend and 22 mm for the codend cover) on the shelf and shelf break of the Antalya Gulf —one of the most oligotrophic regions of the Mediterranean Sea—in May, August and October 2014 and February 2015 [11]. The study area was divided into three sub-regions: R1, a fishing zone with a non-vegetated, soft bottom; R2, a fishing zone characterized by meadows of Posidonia oceanica (Linnaeus) Delile, 1813; and R3, a marine protected area with negligible fishing pressure (mainly longline nets and setlines) and a poorly vegetated bottom [1,44,45]. Each region was assigned five fixed stations located at 10 m, 25 m, 75 m, 125 m and 200 m bottom depths. These depths were chosen since the ground between 10 and 25 m represented a euphotic zone based on water optical measurements and a lower shelf with sediment composed mainly of coarse and slime sand, the ground between 75 and 125 m represented a disphotic zone and a middle shelf with sediment composed of coarse mud and, finally, the ground at the greater depth represented an aphotic zone and an upper shelf with sediment composed of slime mud [1]. Furthermore, extra stations were positioned in the in-between regions at 300 m bottom depths to examine the fish ontogenetic succession from the continental shelf to the shelf break (Figure 1). Location data were recorded using D-GPS every second during trawling. After each haul, fishes were identified to the species level and the total weight (kg) of each of the sorted species was measured to within 0.01 kg. A subsample was taken when necessary and then preserved in 4%–5% borax-buffered formaldehyde. At the laboratory, all specimens were individually assessed for the total length (TL, 0.1 mm) and weight (W, 0.0001 g), respectively [1,44,46,47].
Collection of samples and in situ measurements of the biotic and abiotic environmental parameters were performed simultaneously. Geographical coordinates were recorded using a GPS unit to estimate the distance trawled along the seabed. In order to determine fish ecological preferences, environmental parameters (temperature, salinity, density, pH, oxygen, chl-a, total suspended matter, Secchi disk, photosynthetically active radiation (PAR), zooplankton, size fragmented across three groups) were collected simultaneously, as previously detailed by de Meo et al. [1] and Mutlu et al. [44]. Species abundance and biomass were standardized using the swept area. In order to calculate the swept area, trawling distance was estimated from the geographical coordinates recorded with the D-GPS and multiplied by wing spread, which as calculated as half of the head rope [48].
The Lessepsian migrants originating from the Indo-Pacific Ocean were classified as non-indigenous species (NIS) and the other species, which were mostly Atlanto-Mediterranean, as indigenous species (IS; see Appendix A). Soyer’s dominance index (D%), frequency of occurrence (FO%) and numerical occurrence (NO%) were calculated to determine the consistency of species’ presence in the study area [49]. The faunistic characteristics (number of species (S), abundance (N), Margalef’s richness index (d), Pielou’s evenness index (J’) and Shannon–Weiner diversity index (H’)) of NIS and IS fishes were calculated using PRIMER version 6+ software [50,51]. Generalized linear models (GLMs) with a Poisson distribution were used to examine the spatiotemporal patterns of the faunistic characteristics of osseous IS and NIS fish using MatLab (version 2021a, Matworks Inc., Beltsville, MD, USA).
In order to describe the spatiotemporal distribution of the fish assemblages, non-parametric multidimensional scaling (nMDS) was applied to the Bray–Curtis similarity matrix of the log10-transformed abundances of the two fish groups (NIS and IS). Then, differences in fish abundances for different sampling regions, months and bottom depths (factors) were tested using three-way PERMANOVA. Accordingly, a similarity of percentage (SIMPER) analysis was applied to the abundance in order to determine the contributor species within the factors and discriminator species between the factors for the NIS and IS species. The Spearman rank correlation between the similarity matrices of the abundance and biomass of IS and NIS fish was determined using the RELATE test. Both the PERMANOVA and RELATE tests were conducted to observe whether a significant correlative interaction existed in space and time. Cumulative dominance curves for abundance and biomass (the abundance–biomass comparison (ABC) method) were constructed, and the W-statistic was used to compare IS and NIS fish life history strategies (r-selected or K-selected strategy) for the different sampling regions, months and bottom depths. The abovementioned analyses were carried out in PRIMER [51].
The log10-transformed abundance of the fish species was subjected to canonical correspondence analyses (CCAs) to cluster the stations and determine the IS and NIS assemblages and the species–environment relation using CANOCO (version 4.5) [52]. This helped with the linear ordination of the NIS and IS groups in relation to the environmental parameters in space (region and depth) and time (season).
After the analyses, the NIS and IS fish assemblages were hierarchically classified according to the spatiotemporal distribution and annual depth ranges for the occurrence of the NIS vs. IS fish determined with the nMDS and CCA, since most of NIS fish inhabited the shallower waters. NIS fish that inhabited and expanded in the shallower waters were named “occupiers” and IS fish that presumably struggled with the shallower water NIS were named “resisters”. Moreover, some of the NIS assemblages that inhabited the middle-shelf waters were called “gapers”, while some of the IS that inhabited the space just shallower or deeper (close to edges of the middle shelf) than the middle shelf were called “escapers”. In the upper shelf, the few NIS that were found were called “minorities”, whereas the IS were called “homekeepers”.
Log10 length- and weight-frequency histograms were normalized with probability density functions and the differences for the different regions, depths and seasons were tested separately for NIS and IS using a one-sample Kolmogorov–Smirnov test in MatLab [53] to determine one stressor: the fish morphometrical characteristics of the NIS and IS.

3. Results

A total of 147 fish species were identified in the present study. Thirty-five species were of Indo-Pacific origin and were assigned to the NIS group. All the other species—which consisted of 100 Atlanto-Mediterranean species, 8 cosmopolitan species, 3 species endemic to the Mediterranean and 1 species endemic to the Atlantic (Appendix A)—were assigned to the IS group.

3.1. Faunistic Indicators

According to Soyer’s index, there were 5 constant (DO% ≥ 50) and 20 common (25 < DO% < 50) IS fish and 2 constant and 6 common NIS fish in the study area (Appendix A). In general, the two fish groups differed clearly in their spatial distribution. IS fish occurred with lower numbers, abundances and biomass compared to NIS (Figure 2). The species number differed greatly along the depth gradient between the IS and NIS (Spearman rank correlation r = −0.333; p < 0.05). The highest number of NIS fish was found at the shallowest depths, and the number generally decreased abruptly after a depth of 25 m (see Table S1a in the Supplementary Materials and Figure 2a and Figure 3a). The highest number of IS fish was recorded at intermediate depths (75–125 m; Table S1a). This trend was observed for all regions, but differences in the numbers of fishes along the depth gradient between the two groups were more pronounced in regions R2 and R3, where P. oceanica meadows covered the rocky substrata (Figure 2a). The largest seasonal variation occurred at the depths where we observed the highest number of species for both IS and NIS (Figure 3a). While the average number of IS fish peaked in August, the numbers of NIS fish were highest in February and October at depths greater than 25 m (Figure 3a). No temporal variation was observed at the shelf break zone (200–300 m).
Fish abundance and biomass showed similar patterns as species number (Figure 2b,c). The abundances of IS and NIS fish were negatively correlated (r= −0.371; p < 0.05) but not their biomass (r = −0.028; p > 0.05; Figure 3b,c). The biomass of IS remained relatively constant across sample depths at around 500 kg/km2, while the biomass of NIS decreased logarithmically from 145 kg/km2 at 25 m to 0.90 kg/km2 at 300 m (Figure 3c). The abundance of IS increased from 9.594 ind/km2 at 10 m to 42.573 ind/km2 at 300 m, and this trend was reversed for the NIS (Table S1a). The maximum NIS abundance recorded at each station was around 70,000 ind/km2, while it reached around 164,000 ind/km2 for the IS (Figure 2b). The maximum biomass was around 1.5 tons/km2 for the NIS and around 5 tons/km2 for the IS (Figure 2c). IS had the highest density in R3, a marine protected area, while NIS were more abundant in R1 (Table S1b, Figure 2b,c). The IS exhibited the highest density in August, while the NIS reached a minimum at this time. The density of the NIS peaked in February, with the second-highest density recorded in October (Table S1c, Figure 3b,c).
Margalef’s index values for the IS and NIS were negatively correlated (r = −0.315; p < 0.05). As expected, the NIS had lower species richness than the IS fish (Table S1, Figure 3d). The richness index ranged between 4.1 at 300 m and 6.4 at 75 m for the IS, while it decreased from 2.8 at 10 m to around 1.1 at 200–300 m for the NIS. Regional richness was higher in R1 for both fish groups. The seasonal richness was at the maximum in May and October for both IS and NIS (Table S1, Figure 3d). Seasonal variation in richness was high at 10–125 m for the IS and at 10–25 m for the NIS (Figure 3d). There was no significant correlation (r = 0.220; p > 0.05) between the Pielou’s evenness index values for the IS and NIS fish, and the values showed minimal variations along the depth gradient and between regions and seasons (Table S1, Figure 3e). The seasonal variation in the evenness index for the NIS increased along the depth gradient (Figure 3e). There was a significant negative correlation (r = −0.355; p < 0.05) between the Shannon–Weiner diversity index values for IS and NIS fish. The spatiotemporal variation in the diversity index values was similar to that in the numbers of species for both the IS and NIS (Table S1, Figure 3).
Furthermore, the results of the generalized linear model (GLM) showed a significant positive effect of bottom depth on the absolute faunistic characteristics (i.e., number of species, abundance and biomass) but not on the indices (Table S1 and Figure 4). However, bottom depth negatively affected all the faunistic characteristics of the NIS fish. There were also positive effects of region and season on the absolute faunistic characteristics of the IS fish. Region had a significant negative effect on the absolute faunistic characteristics of the NIS fish, while season did not affect any of the faunistic traits.

3.2. Fish Assemblages

The results of the three-way PERMANOVA showed that the abundances of the IS and NIS were significantly different for different regions, seasons, bottom depths and interactions of region and season with depth (Table S2). The RELATE analysis showed a positive correlation between the similarity matrices for the abundance (Spearman correlation, r = 0.588; p < 0.05) and biomass (r = 0.586; p < 0.05) of the IS and NIS.
The spatiotemporal ordination of the IS assemblages based on their abundances in the n-MDS was primarily controlled by the seafloor depth and presented a V-shaped pattern (Figure 5a). Fish assemblages in the ordination plot were scattered at shallow waters and gradually clustered along the depth gradient up to 125 m. Assemblages from greater depths grouped separately. The NIS assemblages had a completely different configuration in the ordination space (Figure 5). The deep-water assemblages (200–300 m) were scattered around the shallow waters located in the center of the ordination plot (Figure 5b). At depths shallower than 200 m, NIS assemblages assumed a straight-line pattern (=). In contrast to the IS, the scattering of the NIS assemblages increased with bottom depth, and the highest dispersion occurred at 75 m, followed by 125 m. Season and region did not have clear effects on the ordinations of IS and NIS assemblages.
The SIMPER analysis showed that the increasing number and diversity of contributor species along the bottom depth gradient were stronger for the IS compared to the NIS (Table S3). In general, average similarity increased with depth. For the IS, various contributors were present at each depth up to the shelf-break zone (200–300 m), where Argentina sphyraena was the dominant species (Table S3). In contrast, there were few contributors for the NIS (Upeneus spp, Saurida lessepsianus and Nemipterus randalli), and at 300 m, no contributor species were present. Furthermore, Equulites klunzingeri, Callionymus filamentosus, Lagocephalus suezensis and Champsodon nudivittis followed the main contributor NIS that were introduced previously in the Mediterranean.
The average similarity was almost the same among regions for pooled IS and NIS. However, region R1, characterized by a non-vegetated soft bottom, had different contributor species in comparison to R2 and R3 (Table S4). Specifically, the NIS Upeneus mollucensis was the main species in R1, followed by its native competitor species Mullus barbatus. In contrast, in the other regions, M. barbatus was the main contributor species. In general, three NIS and four IS contributed 50% of the average similarity in R1. In contrast, there was only one NIS in region R2, which was fully vegetated by P. oceanica meadows. In region R3, which was less vegetated than region R2, four IS were the most important contributors, followed by two NIS. For the IS fish only, the average similarity was the highest in R2, while it was the same in R1 and R3 (Table S5). NIS fish had different average regional similarity and main contributor species, which likely depended on the coverage area of the Posidonia meadows (Table S5).

3.3. Fish Assemblage–Environment Relation

The canonical correspondence analysis (CCA) confirmed the results of the three-way PERMANOVA (Figure 6). IS assemblages presented a V-shaped spatiotemporal distribution (Figure 6a), while the NIS had an =-shaped distribution (Figure 7a). Thus, altogether, the pooled fish groups had a V-shaped distribution.
Considering the CCA results for the IS, the first axis explained 21.1% of the variance, while the second axis explained 37.4% of the cumulative variance. This variation was proved by the Monte Carlo test and was statistically significant for the first canonical axis (F = 6.972, p = 0.0020) and for all axes combined (F = 1.754, p = 0.0020). The first canonical axis was positively correlated with the bottom depth (0.905) and negatively with the finest fraction of bioseston (−0.564) and chl-a close to the bottom (−0.510). The second canonical axis had the strongest correlation with the bottom type (−0.839), followed by the finest fraction of bioseston (0.448), the sea surface (−0.398) and subsurface salinity (−0.440) and the largest fraction of seston (0.370). The configuration was explained by a variance of 13.4% for the species data and of 23.8% for the species–environment relation in CCA1.
The NIS fish were ordered in the CCA configuration according to the bottom depth gradient (Figure 6 and Figure 7). Fish assemblages from shallow water (10–25 m) were closer together in comparison to fish from greater depths, which were scattered along the CCA1 and CCA2 axes (Figure 7). The spatial distribution of NIS fish species in CCA1 was correlated positively with the bottom type (0.664) and depth (0.875) and negatively with the finest fraction of bioseston (−0.537) and near-bottom chl-a (−0.352) (Figure 7a). This correlation was explained by a variance of 20.6% and was statistically significant (Monte Carlo test; F = 4.447, p = 0.002). An explained variance of 10.5% of the total variance was estimated for the species data. In CCA2, none of the environmental parameters were correlated with fish assemblages, and the explained variance (10.3%) was not significant (F = 1.195, p = 0.088) at p < 0.05.
The IS and NIS fish showed similar ordinations as the configuration of the sampling stations in CCA (Figure 6 and Figure 7). Fish seemed to be ordered by bottom depth. The IS fish from the shallow water (10–25 m) were aggregated on the left end of the V, followed by the fish located at greater depths of the shelf (75–200 m), which were grouped at the junction of the V (Figure 6a). The IS fish from the greatest depth (300 m) were located at the right end of the V. In contrast, the NIS fish gathered mainly in shallow waters (10–25 m; Figure 7b). Thus, the shallow and productive area was shared by both the IS and NIS fish. Considering their ecological niche and the position of NIS fish in the CCA, we classified the IS fish in three groups: “resisters”, “escapers” and “home-keepers”. The NIS fish were named “occupiers” or “gapers”. The few NIS species observed at greater depths were called “minorities”.

3.4. Abundance/Biomass Relation

The abundance–biomass comparison (ABC) curves and the W-statistic, which represented the area between the two curves, differed between the IS and NIS (Figure S1). The abundance curve lay above the biomass curve and had a positive W-statistic at all the depths for the IS (Figure S1A). In contrast, for the NIS, there was a gradual change in the patterns of biomass and abundance (Figure S1B). At depths of 10–25 m, where most of the NIS were caught, the abundance curve lay above the biomass curve. Thereafter, the curves crossed each other once or twice at intermediate depths (75–125 m), while the biomass curve lay above the abundance curve at the greatest depths (200–300 m). The W-statistic increased with the bottom depth.
The IS and NIS also had different ABC curves in different regions (Figure S2). For the IS, the W-statistic values decreased from west to east in the study area and were all negative, indicating that the abundance curves lay above the biomass curves. For the NIS, the abundance curve was above the biomass curves in R1, while it crossed the biomass curve in R2 and then fell below the biomass curve in R3 (Figure S2B).
An evident temporal difference was observed between the ABC curves of the IS and NIS. The biomass curves were below the abundance curves in all seasons, except for that for the NIS in August. The W-statistic of the NIS was double that of the IS in October, but they were similar in February and May.

3.5. Biometric Indicators

Biometric indicators differed greatly between IS and NIS osseous fish. The maximum length, length–weight relationships, individual length and weight and their frequency distributions suggested an equilibrium between the IS and NIS fish at (in order of importance) bottom depths and in regions and seasons.

3.5.1. Length–Weight Relationship

Overall, the qualitative length–weight relationships (LWRs) of the IS and NIS did not differ, as the two fish groups had similar intercepts (a) and slopes (b) with only a few exceptions (Table 1). Furthermore, both showed isometric growth, regardless of the sample size of each fish species. The mean individual lengths were similar between the IS and NIS, while the mean individual weight of the IS was 1.5-fold higher than that of the NIS (Table 1). The average maximum length and average maximum weight of the IS were similar to those of the NIS. In the LWR, a group of NIS and IS had b values ≤ 3) (c.a. 10 cm and 10 g on average; ~16 g at maxima), indicating similar growth in the LWR for small specimens of IS and NIS, and another group was characterized by specimens growing with b > 3.
Utilizing the measurements of each specimen, one-way ANOCOVA showed that there was a significant difference in the quantitative LWRs between the IS and NIS fish (p = 2.96 × 10−207) at p < 0.05. Nevertheless, IS and NIS presented similar mean lengths and weights, and both showed negative allometric growth, especially the NIS (Table S6). However, considering the measurements of each fish species, the LWRs presented isometric growth, and this was attributed to the existence of a possible equilibrium between the IS and NIS osseous fish (Table 1).

3.5.2. Length and Weight Histograms

There was clear differences in the spatiotemporal distributions shown in the length (LH) and weight histograms (WH) between the IS and NIS osseous fish, and they became more pronounced along the depth gradient (Figure 8, Table S7). The length frequency was significantly different at different depths, regions and seasons between the IS and NIS (Figures S3 and S4), while the weight frequency was significantly different only at different depths (Figure 8, Table S7).
The mode of the log10 length was around 0.5 cm for the IS and 1.2 cm for the NIS at different regions and that of the log10 weight was around 1.2 g for both fish groups (Table S7, Figure S3), indicating that smaller specimens of IS had higher weight, while the opposite was true for the NIS. The peak frequencies were higher in R1 and R2 than in R3 for the LH and WH for both IS and NIS. Specimens smaller and lighter than the peak values were dominant in R1 and R2, while larger and heavier specimens were observed in R3 (Figure S3). However, the mid-size classes around the mode were highly variable in the different regions (Figure S3).
Bottom depth was the most important factor determining the frequency distributions of length and weight for both IS and NIS (Figure 8). The IS exhibited unimodal LH and WH along the depth gradient, while the NIS had multi-modal distributions. In general, the LH of the IS seemed to be normally distributed, whilst the LH of the NIS fish increased with the bottom depth: smaller specimens occurred in shallow waters and larger ones at greater depths (Figure 8). However, the smallest and largest specimens of the NIS fish occurred at the shallowest depths. The trend in the WH of the IS along the bottom gradient was completely different from that of NIS (Figure 8). Lighter specimens of IS occurred at greater depths, while the weight of the NIS increased with the depth gradient. Similarly to the LH, the lightest and heaviest specimens of the NIS fish were found in the shallowest waters (Figure 8).
The LH of IS fish changed slightly with the seasons, as the dominance of the modal value decreased gradually from October and May through August to February (Figure S4). The LH of the NIS reached peaks in February and August with relatively larger specimens, with lower peaks in May and October. The WH was distributed similarly across the seasons for both IS and NIS.

4. Discussion

The proportion of the NIS fish at the different stations reached a maximum of 59% of the total number of fish species, accounting for 75% of the abundance and 65% of the biomass (Figure S5).
The average inclusion of the NIS comprised 24% of the total number of species, close to the value recorded for Israeli waters (33% [54]). In this study, NIS made up 59% of the total fish biomass at the maximum, lower than the biomass reached by NIS in İskenderun Bay (70%), a eutrophic region along the Eastern Turkish coast [18].
The proportion of NIS fish has been estimated to be only 15% for the Eastern and 9% for the entire Mediterranean Sea [55], lower than in our study. In Turkish Mediterranean waters, the average biomass of NIS fish decreased westwards. In İskenderun Bay, a eutrophic area and the easternmost point of the Mediterranean Sea, non-indigenous fish make up 62% of the biomass. In Mersin Bay, a region under the influence of great freshwater supplies, NIS biomass has been found to be 34%, while in Anamur Bay, an oligotrophic region neighboring the present study area to the east, NIS biomass was 27% (25% at waters shallower than 30 m and 12% on average on the shelf) [56]. However, in the Adriatic Sea, another oligotrophic region of the Mediterranean, only 11 Lessepsian fish species were recorded, probably because of the limited food availability [57]; in addition, most of Lessepsian fish have not reached the Adriatic Sea because of the thermohaline barrier between the Eastern and Western Mediterranean [44,47]. Fishing also has a great impact on the proportion of NIS, and Gucu and Bingel [18] estimated a biomass of 45% before the fishing season and 35% after the fishing season.
Another pathway for the introduction of the Indo-Pacific fish species is related to sea level changes [6] owing to the chronological evolution of the Suez Canal’s morphometry [4,6,10,17,58]. As the sea level has increased, the introduction of fish species in the Eastern Mediterranean Sea has accelerated, and this also depends on the differences in the sea temperature between the Indian Ocean and Mediterranean Sea. Temperature and salinity play an important role in influencing the colonization success of NIS at shallow depths [18]. Arndt and Schembri [19] attributed the occurrence of NIS fish at greater depths to the widening and deepening of the Suez Canal in 1980. The establishment of NIS has also been linked to different ecological traits, such as the tendency to form schools and spawning types, with benthic spawners and species with adhesive eggs being more successful colonizers [4,19,58].
In the Eastern Mediterranean, the catch per unit effort (CPUE) for NIS increased between 1996 and 2013, while it remained stable over this period for IS, suggesting that competitive exclusion may be limited [16].
In accordance with the previously published literature [12,26], we identified eight factors that could function as discernible ecological indicators of IS and NIS.

4.1. Bottom Depth

In comparison with the IS, the seafloor depth has restricted the extensive dispersion of the NIS in the Eastern Mediterranean Sea, as the numbers of fish decrease from the shallow waters through the intermediate depths to the upper shelf/shelf break. We also observed the opposite patterns for the faunistic characteristics of the IS and NIS fish along the depth gradient. Similarly, the relative abundance of NIS fish decreased from 51% in shallow waters through to 24% in the intermediate waters and 8% in the deep waters off Israel [38]. Most of the NIS were concentrated at bottom depths shallower than 30 m. Their depth preferences could be linked to different factors, including sea level changes due to the deepening and widening of the Suez Canal over time [6]. Indeed, the minimum depth at which a species is observed is an important factor determining dispersal success, and it was here probably related to the depth of the Suez Canal at the time of invasion. Species with high dispersal success were associated with a minimum depth of 8.0 m, while those with medium and high dispersal rates had minimum depths of 14.2 m and 22.2 m, respectively [19]. CPUE values for indigenous and alien species along the depth gradient off the Israeli coast showed very different trends. The CPUE of IS fish gradually increased with depth, while the CPUE of alien fish species peaked at around 40 m. Similarly, the CPUE of IS cephalopods and crustaceans peaked at around 100 and 175 m, while NIS invertebrates peaked at around 25 m and decreased sharply at greater depths [16]. Patania and Mutlu [59] observed a similar distribution for NIS crustaceans in the present study area, which were largely represented by six species: Penaeus pulchricaudatus, Penaeus hathor, Thalamita poissonii, Portunus segnis, Charybdis (G.) longicollis and Erugosquilla massavensis. They were all dominant in waters shallower than 30 m, while IS crustaceans were found at the greater depths. Similarly, Garuti and Mutlu [45] estimated an increase in the average abundance of IS cephalopods with the seafloor depth in the present study area. Abundance was low at depths ≤ 25 m (≤ 5 ind/km2), moderate at the middle shelf (29–83 ind/km2) and high at the shelf edge and break (144 and 132 ind/km2).

4.2. Bottom Vegetation Status

In the present study, P. oceanica formed meadows at bottom depths shallower than 30 m in the fishing region R2 and in the non-fishing zone R3. In these regions, the number and the diversity of contributor species were lower for the NIS compared to the IS. These regional differences for the NIS fish could be attributed to the presence of seagrass habitats, which may favor the establishment of immigrant species [60].
Kalogirou et al. [61] contrasted feeding guilds of fish from P. oceanica meadows and sandy habitats in an area of the Eastern Mediterranean, revealing that the proportional contribution of NIS individuals from the meadows was lower than those from sandy bottoms (12.7 vs. 20.4%, respectively), although they had similar values for biomass (13.6 vs. 23.4%).
This indicates that highly diverse systems, such as seagrass meadows, may be more resistant to introductions than less diverse systems. In habitats with increasing species richness, fishes’ competitive abilities may intensify, while in less diverse systems, potential niches remain available for new colonizers [61,62].
Along the coast of Israel, Lessepsian migrants were found to have higher abundance in the south due to the wider shelf area along the migration vector, as well as in grounds strongly disturbed by trawling [38].
Along the rocky coast of Lebanon, NIS were more abundant in water shallower than 12 m. However, Lessepsian species, such as S. lessepsianus, can colonize deeper zones compared to their IS counterpart Synodus saurus [63].

4.3. Hierarchy

In the present study, we classified IS and NIS fish according to a hierarchy referring to their interactions in the ecological space. We named the IS sharing a habitat with the NIS (“occupiers”) at shallow depths “resisters”, the IS established in the middle shelf that left the productive shallow waters “escapers” and the IS living predominantly at greater depths together with a few NIS (“minorities”) “home keepers”. This ecological classification took into account the role of interspecific interaction between the alien species [34] and was supported by the escape-from-enemy hypothesis: “if a host does manage to leave a specialist enemy behind, it is unlikely to encounter another following introduction” [64]. Prey fishes are often juveniles, the size of which shows a positive correlation with predator size [65].
Increasing proportions of NIS biomass have been found to have important effects on the food web hierarchy, as there was a decrease in native top predators and fish at a medium trophic level together with a rapid increase in alien fish, mainly from medium trophic levels [12].
Givan et al. [26] identified three main stressors explaining changes in IS abundance at shallow depths in the Eastern Mediterranean. Firstly, shallow waters are more commonly invaded by NIS due to the low depth of the Suez Canal, their main invasion vector. Moreover, fishing efforts are often confined to the shallow waters (15–150 m). Climate change is also less pronounced at greater depths, where NIS generally occur at low densities.
In the Eastern Mediterranean, a low direct impact on IS fish has been determined due to the fact that NIS fish tend to occupy available ecological niches [66,67].

4.4. Key Fish Species

In ultra-oligotrophic marine environments such as the present study area, few effective and dominant species, such as opportunistic ones, are able to colonize and take advantage of the limited available niches. Edelist et al. [17] identified a limited number of contributor IS and NIS fish along the depth gradient in the southeastern Mediterranean. Shallow waters were found to be inhabited by less abundant IS (Pagellus erythrinus) and more abundant high-level-feeder NIS (N. randalli, Jaydia smithi, Ostorhinchus fasciatus and Plotosus lineatus), while greater depths exhibited decreasing abundances of Merluccius merluccius. These differences were attributed to the dominance of NIS with small body sizes in the warm upper layer of the water column, as specimen size decreases with temperature [29]. The fast-growing populations of NIS fish are typically composed of small-sized specimens (e.g., P. lineatus, C. filamentosus and E. klunzingeri, Lagocephalus spp. and small species from the family Apogonidae) [68].
Competitive displacement of native Mediterranean species has been suggested for different species, such as M. merluccius by S. lessepsianus [69], Mullus spp. by Upeneus spp. [70] and Sarpa salpa by Siganus spp. [27,71,72]. Furthermore, the NIS Upeneus moluccensis and S. lessepsianus were found to be highly abundant, whilst the IS M. barbatus and Mullus surmuletus showed notably reduced populations over two decades in the Eastern Mediterranean Sea [17]. S. lessepsianus and U. moluccensis were found to be the dominant NIS in the deeper waters off the Israeli cost together with Mullus spp., as also found in our study [38]. It should be noted that the catch composition for NIS varies between day and night, as some species are diurnal (U. moluccensis, S. lessepsianus and E. klunzingeri) and others nocturnal (C. filamentosus) [38]. Nocturnal NIS fish were found to be more successful in colonization because of low competition from native species [4,31].
With regard to the season, NIS fish, such as S. lessepsianus and U. moluccensis, were found to have the highest density in winter and autumn, followed by spring and summer. In contrast, IS fish had the highest density in summer when their recruitment occurs following spawning [29,38,73].

4.5. Water Productivity (Food Web)

In this study, the highly productive zone was restricted to the shallow area (≤ 25 m), while the greater depths were virtually devoid of water nutrients. The finest fraction of bioseston and near-bottom chl-a, indicative of water productivity along the depth gradient, determined the distribution of NIS assemblages, which were mostly located in shallow waters.
In the Antalya Gulf, one of the ultra-oligotrophic regions of the Eastern Mediterranean Sea, we identified 147 fish species: 35 fish were NIS of Indo-Pacific origin, 100 species were Atlanto-Mediterranean, 8 were cosmopolitan, 3 were endemic and 1 was an Atlantic fish species. In general, the maximum fish species numbers were recorded in Israeli waters and at İskenderun Bay in the Levantine Sea (253–272 species). The rest of the Turkish coast had fish species numbers varying between 168 and 252 [10]. With regard to the NIS, Massuti et al. [74] reported 38 alien fish in the Western Mediterranean Sea, a number then updated to 45 species, including 20 casual occurrences and 25 established ones. Guidetti et al. [75] reported 50 alien fish species in the central Mediterranean Sea, of which 19 were casually observed, 25 were established and 6 were uncertain. In the Eastern Mediterranean Sea, the number of alien fish increases notably with a total of 106 species reported, most of them of Indo-Pacific or Red Sea origin [8]. At some locations, the ratio between the number of alien fish species and the number of native species was found to be 11-fold higher in 2015 compared to 1945 [20]. The Turkish Mediterranean coast harbors a total of 74 NIS fish, of which 66 are of Indo-Pacific origin [76]. Along the coast of Muğla, neighboring the present study area to the west, 45 Lessepsian fish species have been recorded [77]. Therefore, the number of IS and NIS has changed locally in the Mediterranean Sea. The number of IS reaches a maximum (28 spp) in the Levantine Sea (20–28 spp along the northern coast and 12–19 spp along the southern coast), higher than the number of NIS (24 spp along the Egyptian coast and 28–64 spp along the Israeli coast in the south and 25–38 spp in İskenderun Bay and 24–28 spp in Mersin Bay in the north; all coasts have high productivity). Then, the number of NIS decreases to 19–23 spp for the rest of the southern Turkish coast and to 11–23 spp on the shelf and 2–4 spp on the slope of the ultra-oligotrophic Antalya Gulf [10,11].
The present area could favor the establishment of NIS because there are few dominant IS competing for the niches available in the ecosystem. According to the biotic resistance hypothesis presented by Levine and Adler [78], diverse ecological interactions between resident species can constrain the establishment success of new colonizers. Higher species richness causes an increase in competition between species and, therefore, fewer food resources are available for the NIS [5,79,80]. Thus, in areas with low species richness where few species are dominant, NIS might be able to establish themselves more successfully compared to areas with high diversity indices [5].
According to a study by D’Amen and Azzurro [39], almost all MPAs are at high risk of invasion in the Levantine Sea, including the present study area, while other regions present low suitability for most invasive species. The Antalya Gulf is considered an ultra-oligotrophic area of the Eastern Mediterranean Sea where species diversity is low compared to other regions in the Eastern and Western Mediterranean. While this could favor the establishment of NIS, the area also has very low ship traffic at the national and international scales, which is one of the main pathways for the introduction of NIS [7,81].

4.6. Fish Trophic Level

As previously mentioned, the introduction of alien species results in changes in the biomasses of various functional groups and species; specifically, in a decrease in native top predators and medium-trophic-level fish and, at the same time, an explosion of alien species, mainly from medium trophic levels [20]. Significant declines in the biomass of native demersal predators (e.g., hake) and native medium-trophic-level fishes (e.g., mullets) over time has favored an increase in alien species from their respective families [17,21]. In our study, the IS mullets were still resilient to the NIS mullets with regard to abundance and biomass. However, the hake and the Atlantic lizardfish seemed to occur in limited quantities compared to the NIS lizardfish (Appendix A). P. erythrinus seemed to be able to withstand the presence of its corresponding NIS in shallow waters, but Pagellus acarne probably could not, as the LWR suggested a decline in the number of the largest individuals.

4.7. Fish Life Strategy

Fish life strategy was most easily observed using the ABC curves for the seafloor depth and the different regions. NIS fish decreased along the depth gradient. The r-selected NIS fish were dominant in shallow waters and at equilibrium with k-selected NIS in the middle shelf, while k-selected fish were predominant at greater depths. One factor highlighting the succession of the NIS was the maximum fish length, an indicator of the features of the r- or k-selected organisms [14]. Fish with an r-selected life strategy are much more effective in dispersing in comparison to larger k-selected organisms [14]. The successful establishment of an alien species depends on its ability to use resources, occupy vacant niches, compete successfully and achieve a stable and/or large population, all typical characteristics of an r-selected life history strategy [19,82,83]. Moreover, r-selected fish seem to have a higher resilience to fishing compared to k-selected ones [36,84,85]. For instance, fishing pressure off the Israeli coast may have contributed to a decrease in slow-growing species (k-strategists) and indirectly benefitted fast-growing ones (r-selected), most of which are NIS. Length at first maturity was found to be lower in the most strongly increasing species, all of which were invasive, compared to the most strongly decreasing ones, which were mostly native [27].

4.8. Fish Morphometrical Characteristics

Body length is strongly associated with fish range size and dispersal ability [86]. However, the size spectrum of IS fish has remained remarkably constant, despite a large and size-specific increase in NIS biomass in the Mediterranean [87]. The size spectra of NIS seems to converge with the IS, suggesting similar energetic constraints and sensitivities to fishing, with a minor impact on the structure of the native community [87].
Arndt et al. [19,27] estimated mean lengths indicating the establishment success of NIS fish: 44.2 cm for low success, 29.4 cm for medium success and 29.8 cm for high success. NIS fish between 10 and 20 cm long were highly populous in the present study area, while the typical range has been found to be 20–30 cm along other Mediterranean coasts, and the size increment among the individuals is probably a result of the change in habitat [88]. This could be due to differences in productivity among the areas, which may lead to faster growth, or in trawl selectivity.
Due to a rise in the sea surface temperature, the succession speed of NIS exhibited a fivefold increase during the 1980s. Climate matching and year of introduction were determinant factors for dispersal. In particular, subtropical NIS fish tended to disperse more widely than NIS of tropical origin [14]. However, sea surface temperature does not significantly affect the dispersion and establishment of Mediterranean NIS in their native depth range [15,19]. Furthermore, the NIS fish that occupy larger ranges of habitats in their native environment and are able to form schools have higher probabilities of introduction [15].

5. Conclusions

The factors affecting the biometrical distribution of IS and NIS fish were estimated in the Antalya Gulf, which is a semi-closed gulf mostly uninfluenced by the Atlantic rim current employed as a mesocosm area. Compared to the previous qualitative and quantitative data, the ratio of NIS to IS has not changed significantly over time, as the NIS have continued to be introduced into the Levantine Sea. The present study preliminarily assessed eight descriptive factors (stressors) for the interactive distribution between IS and NIS fish along the northern Levant coast. These factors were bottom depth, bottom vegetation status, fish hierarchy, key species, water productivity, fish trophic level, life strategy and morphometry. The NIS introduced earlier adapted to the Levantine Sea, whereas the NIS introduced later generated a hierarchy above the IS in the space of the shelf. The NIS have filled the gap formed by the V-shaped ecological distribution of IS fish along the bottom depth gradient. Hierarchically, NIS (occupiers) and IS (resisters) share the shallowest waters, while the middle-shelf waters are occupied by NIS (gapers) and IS (escapers) separately. The upper shelf is only occupied by IS (homekeepers) and NIS minorities. Every newly introduced and established species first populated a colony and then exhibited evolved adaptation and population of the ground, since the subsequently introduced NIS were welcomed to the ground of the marine environment [89]. Therefore, the interaction of IS and NIS has been maintained over time and space.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su15032726/s1, Figure S1: ABC cumulative dominance curves across the bottom depth gradient for the IS (column A) and the NIS fish (column B) with the W-statistic value (W); Figure S2: ABC cumulative dominance curves across regions (R1, R2 and R3) for the IS (column A) and the NIS fish (column B) with the W-statistic value (W); Figure S3: Length (LH) and weight (WH) frequency distributions, normalized with probability density functions, of a total of 28987 individuals of IS and 7642 individuals of the NIS osseous fish among the regions; Figure S4: Length (LH) and weight (WH) frequency distributions, normalized with probability density functions, of a total of 28987 individuals of IS and 7642 individuals of the NIS osseous fish among the seasons; Figure S5: Percent proportions of the NIS fish in the total number of species, abundance and biomass (Circle color; Blue: May 2014. Green: August 2014. Red: October 2014. Magenta: February 2015); Table S1: Estimates of the GLM (model is Poisson distribution estimated by the variogram) and spatio-temporal (a: bottom depth; b: regions; c: seasons) distribution of average faunistic characters (S; number of species, N; abundance, ind/km2, B; biomass, kg/km2, d; Margalef’s species richness, J’; Pielou’s evenness index, and H’; Shannon-Weiner diversity index) between IS and NIS fish. Proportions of NIS with respect to the total S, N, and B. Average proportions are shown in bold. (Bold estimates were significantly effective at p < 0.05. Sign of the estimates denotes the positive or negative effect); Table S2: Significance level (p) of the 3-way PERMANOVA results among factors (source) of the regions, of seasons, and of bottom depths and their interactions. Bold p value was significantly different at p < 0.05; Table S3: SIMPER analyses for the IS and NIS along the bottom depth gradient. Contributor species* at each depth (Avg. Sim.; percent average similarity for each depth, Avg. Abn; log10-transformed average abundances ind/km2, Av. Sim: average similarity of each species**, Sim/SD: A ratio of similarity to standard deviation of each species**, and Cum%: percent cumulative similarity by each species); Table S4: SIMPER analyses for pooled data of the IS and NIS among the regions. Contributor species* at each depth (Avg. Sim.; percent average similarity for each depth, Avg. Abn; log10-transformed average abundances ind/km2, Av. Sim: average similarity of each species**, Sim/SD: A ratio of similarity to standard deviation of each species**, and Cum%: percent cumulative similarity by each species); Table S5: SIMPER analyses for the IS and NIS among the regions. Contributor species* at each depth (Avg. Sim.; percent average similarity for each depth, Avg. Abn; log10-transformed average abundances ind/km2, Av. Sim: average similarity of each species**, Sim/SD: A ratio of similarity to standard deviation of each species**, and Cum%: percent cumulative similarity by each species); Table S6: A whole estimate of ANOCOVA analysis for the LWR between IS and NIS osseous fish regarding number of specimens (N) for the analyses, regardless of the species; Table S7: Significance level, p values of Kolmogorov–Smirnov test for length and weight frequency distribution among the regions, depths, and seasons within each of IS and NIS fish, and IS vs NIS fish. Bolds denote unequal distribution at p < 0.05.

Author Contributions

Conceptualization, E.M.; methodology, E.M.; software, E.M.; validation, E.M.; formal analysis, E.M., I.d.M., C.M. and M.C.D.; investigation, E.M., I.d.M., C.M. and M.C.D.; resources, E.M., I.d.M., C.M. and M.C.D.; data curation, I.d.M. and C.M.; writing—original draft preparation, E.M.; writing—review and editing, E.M., I.d.M. and M.C.D.; visualization, E.M.; supervision, E.M.; project administration, E.M.; funding acquisition, E.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Scientific Research Coordination Unit of Akdeniz University, grant number, 2014.01.0111.001.

Institutional Review Board Statement

The animal study protocol was approved by the “Akdeniz Üniversitesi Hayvan Deneyleri Yerel Etik Kurulu” Animal Experiments Local Ethics Committee of Akdeniz University (protocol no: 2013.12.03).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data are not shared but the data will be available if requested by the journal.

Acknowledgments

The present study was funded by the Scientific Research Coordination Unit of Akdeniz University within the framework of three projects (project no: 2014.01.0111.001) mainly coordinated by Erhan Mutlu. This study was part of Ilaria de Meo’s MSc thesis co-supervised by Erhan Mutlu and Claudia Miglietta’s MSc thesis co-supervised by M. Cengiz Deval. We thank Ahmet Şahin, M. Tunca Olguner and Cansu Olguner, as well as the crew of the R/V Akdeniz Su for their help on board.

Conflicts of Interest

The authors declare no conflict of interest.

Appendix A

Table A1. The IS and NIS fish with their annual and seasonal dominance (constant and common species, D (%)), frequency of occurrence (most frequently occurring species in italic font, FO (%)) and numerical occurrence (most abundantly occurring species in bold font, NO (%)) in the sampling months and year, as well as the ranges of abundance (Mn, minimum— mean ± standard deviation, X ± SD, Mx, maximum, ind.km−2), biomass (Mn, minimum, mean ± standard deviation, X ± SD, Mx, maximum, kg.km−2) and bottom depth range (minimum, maximum, MxD, the depth where the maximum abundance occurred) of the species and their origin (Sts, native species of the Mediterranean Sea (IS)—A-M: Atlanto-Mediterranean, A: Atlantic, M: Mediterranean, C: cosmopolitant—and Indo-Pacific alien species (NIS)). Abb, abbreviation of fish species used in the statistical analyses.
Table A1. The IS and NIS fish with their annual and seasonal dominance (constant and common species, D (%)), frequency of occurrence (most frequently occurring species in italic font, FO (%)) and numerical occurrence (most abundantly occurring species in bold font, NO (%)) in the sampling months and year, as well as the ranges of abundance (Mn, minimum— mean ± standard deviation, X ± SD, Mx, maximum, ind.km−2), biomass (Mn, minimum, mean ± standard deviation, X ± SD, Mx, maximum, kg.km−2) and bottom depth range (minimum, maximum, MxD, the depth where the maximum abundance occurred) of the species and their origin (Sts, native species of the Mediterranean Sea (IS)—A-M: Atlanto-Mediterranean, A: Atlantic, M: Mediterranean, C: cosmopolitant—and Indo-Pacific alien species (NIS)). Abb, abbreviation of fish species used in the statistical analyses.
SpeciesAbbOriginWithin All SpeciesWithin IS and
NIS
Abundance (ind/km2)Biomass (kg/km2)
D%FO%NO%FO%NO%MnX ± SDMxDepth Range, MxDMnX ± SDMxMxD
Aetomylaeus bovinusAbovA-M5.060.230.0110.300.013192.6 ± 1.61148.5–13.5, 8.556.7610.13 ± 6.44472.208.5
Alosa fallaxAfalA-M1.270.060.0010.070.002260.3 ± 0.32611–11, 110.450.01 ± 0.010.45
Anthias anthiasAantA-M6.330.280.0700.370.084716.7 ± 9.759477.7–128.8, 128.80.070.18 ± 0.105.71128.8
Argentina sphyraenaAsphA-M31.651.415.4221.876.4892991288.2 ± 329.216348115–299, 193.12.1711.08 ± 2.66111.34186.3
Arnoglossus imperialisAimpA-M5.060.230.0040.300.005130.9 ± 0.52476.5–287.3, 77.70.090.01 ± 0.000.1677.7
Arnoglossus laternaAlatA-M29.111.300.1261.720.1511730.0 ± 7.331711.5–193.1, 350.150.23 ± 0.073.0284.2
Arnoglossus rueppeliiArueA-M20.250.900.1091.190.1302225.8 ± 7.945884.6–299, 2990.020.10 ± 0.031.72286.4
Arnoglossus thoriAthoA-M18.990.850.3411.120.4092681.1 ± 26.7122235–130, 740.230.56 ± 0.199.7874
Balistes capriscusBcapC11.390.510.0150.670.018133.5 ± 1.3778.5–25.7, 12.10.272.46 ± 2.10166.0111.2
Blennius ocellarisBoceA-M24.051.070.1311.420.1572231.1 ± 13.792267–137, 111.90.150.48 ± 0.2213.02111.9
Boops boopsBbooA-M63.292.823.3293.733.98416791.0 ± 165.968368.5–286.4, 111.90.2119.68 ± 4.16200.75111.9
Bothus podasBpodA-M43.041.924.0352.544.82926958.7 ± 230.3109108.5–289.5, 8.50.3411.41 ± 3.10194.598.5
Callionymus maculatusCmacA-M3.800.170.0050.220.006201.2 ± 0.738115–194, 1150.06<0.01 ± 0.000.16115
Capros aperAapeA-M22.781.011.0651.341.27520253.0 ± 137.510589127–299, 265.10.011.82 ± 1.2093.73265.1
Caranx crysosCcryA-M2.530.110.0110.150.014652.7 ± 2.014811–11.2, 11.23.100.11 ± 0.085.3811.2
Carapus acusCacuM2.530.110.0020.150.003190.5 ± 0.423125–133.9, 1250.02<0.01 ± 0.000.02133.9
Carcharhinus plumbeusCpluM1.270.060.0010.070.002240.3 ± 0.32474–74, 7436.670.46 ± 0.4636.6774
Centracanthus cirrusCcirA-M11.390.510.8780.671.05024208.5 ± 86.74101117.7–193.1, 141.10.161.57 ± 0.6941.39141.1
Cepola macrophtalmaCmacA-M3.800.170.0070.220.008191.6 ± 1.06584.6–133.9, 870.090.01 ± 0.000.2187
Chelidonichthys cuculusCcucA-M7.590.340.1120.450.1341626.5 ± 22.71792125–299, 2990.260.55 ± 0.4434.17299
Chelidonichthys lucernaClucA-M17.720.790.0481.040.0571311.4 ± 3.92118.5–193.1, 12.10.360.39 ± 0.159.9612.1
Chlorophthalmus agassiziCagaC17.720.799.0111.0410.783252140.8 ± 1216.085848141.1–299, 2900.0220.45 ± 12.04870.97290
Citharus linguatulaClinA-M64.562.873.0493.813.64817724.3 ± 288.62186610.5–289.5, 111.90.1815.58 ± 6.09455.76111.9
Coelorinchus caelorhincusCcaeA-M6.330.282.2840.372.734865542.7 ± 319.218189258.3–299, 2995.094.48 ± 2.81196.69299
Conger congerCconA-M12.660.560.0120.750.015163.0 ± 0.94623.1–298.6, 298.60.020.34 ± 0.1712.00298.6
Dactylopterus volitansDvolC7.590.340.0090.450.010162.0 ± 0.83911–117.7, 110.320.07 ± 0.042.7394
Dasyatis centrouraDcenA-M1.270.060.0030.070.003490.6 ± 0.649186.3–186.3, 186.3200.052.53 ± 2.53200.05186.3
Dasyatis pastinacaDpasA-M32.911.460.1151.940.1371327.3 ± 7.34788.5–141.1, 1118.1140.88 ± 9.63450.0611
Deltentosteus quadrimaculatusDquaA-M18.990.850.1051.120.1261325.0 ± 10.572612–286.4, 130.60.010.04 ± 0.021.01130.6
Dentex dentexDdenA-M2.530.110.0020.150.003130.5 ± 0.42635–76.5, 3525.380.92 ± 0.6847.5535
Dentex macrophthalmusDmacA-M7.590.340.1840.450.2203543.7 ± 25.2165674–163.3, 117.71.070.64 ± 0.3419.5674
Dentex maroccanusDmarA-M27.851.246.2321.647.457201480.5 ± 756.35626478.3–287.3, 111.90.5845.63 ± 20.761351.00111.9
Dicologlossa cuneataDcunA-M3.800.170.0090.220.011432.2 ± 1.38711.5–29.4, 11.70.250.02 ± 0.010.9511.5
Diplodus annularisDannA-M26.581.181.7901.572.14213425.3 ± 209.9152678.5–121.8, 11.20.3110.28 ± 4.51308.3011.2
Diplodus vulgarisDvulA-M1.270.060.0080.070.0091481.9 ± 1.914813.5–13.5, 13.57.400.09 ± 0.097.4013.5
Dipturus oxyrinchusDoxyA-M6.330.280.0200.370.024234.8 ± 2.7193193.1–287.3, 286.42.285.17 ± 3.82290.00286.4
Echeneis naucratesEnauC1.270.060.0010.070.001220.3 ± 0.32211.7–11.7, 11.721.830.28 ± 0.2821.8311.7
Engraulis encrasicolusEencA-M7.590.340.0660.450.0782615.6 ± 9.263135–193.1, 73.70.130.24 ± 0.159.2173.7
Epinephelus aeneusEaenA-M27.851.240.2171.640.2601551.6 ± 15.793411.2–84.2, 25.73.895.85 ± 1.5580.6525
Epinephelus haifensisEhaiA-M1.270.060.0040.070.005771.0 ± 1.07777–77, 770.930.01 ± 0.010.9377
Etrumeus teresEterA-M3.800.170.0060.220.007191.4 ± 0.8468.5–125, 1250.380.02 ± 0.010.56121.8
Gadiculus argenteusGargA-M1.270.060.0020.070.003430.5 ± 0.543258.3–258.3, 258.30.22<0.01 ± 0.000.22258.3
Glossanodon leioglossusGleiA-M22.781.016.1991.347.418171472.8 ± 626.533887127–299, 1300.0410.12 ± 4.19213.07194
Gnathophis mystaxGmysA-M8.860.390.0170.520.020224.0 ± 1.66425.7–299, 1370.270.40 ± 0.189.67121.8
Gobius geniporusGgenM1.270.060.0010.070.001150.2 ± 0.21557–57, 570.11<0.01 ± 0.000.1157
Gobius nigerGnigA-M2.530.110.0030.150.004190.8 ± 0.64113.5–25, 250.170.01 ± 0.010.4625
Gymnura altavelaGaltA-M13.920.620.0380.820.045198.9 ± 3.72488.5–121.8, 8.553.6735.42 ± 14.75835.508.5
Helicolenus dactylopterusHdacA-M13.920.620.3710.820.4442188.2 ± 45.5308474–299, 2990.120.89 ± 0.4226.04299
Hoplostethus mediterraneusHmedC2.530.110.0070.150.008221.6 ± 1.4108258.3–290, 2900.220.01 ± 0.010.63290
Hymenocephalus italicusHitaA-M5.060.230.4020.300.4814295.4 ± 69.34945258.3–299, 258.30.250.28 ± 0.2115.05258.3
Lepidopus caudatusLcauA-M1.270.060.0010.070.001220.3 ± 0.322258.3–258.3, 258.30.750.01 ± 0.010.75258.3
Lepidorhombus whiffiagonisLwhiA-M12.660.560.0890.750.1062121.1 ± 8.1485186.3–299, 298.60.253.41 ± 1.79131.73298.6
Lepidotrigla cavilloneLcavA-M44.301.972.8952.613.46418687.8 ± 281.81606012.2–289.5, 111.90.028.45 ± 3.65217.03111.9
Lepidotrigla dieuzeideiLdieA-M16.460.730.7270.970.87041172.6 ± 73.94737141.1–298.6, 265.10.163.12 ± 1.57108.93265.1
Lithognathus mormyrusLmorA-M25.321.131.0631.491.27219252.6 ± 86.344338.5–84.6, 111.009.68 ± 3.16156.1425.7
Liza saliensLsalA-M2.530.110.0110.150.013392.6 ± 2.216711–13.5, 13.52.320.28 ± 0.2519.9913.5
Lophius budegassaLbudA-M13.920.620.0220.820.027215.3 ± 1.8108111.9–299, 258.30.203.89 ± 1.5566.69195
Macroramphosus scolopaxMscoA-M41.771.863.0822.463.68820732.2 ± 183.9944110.7–286.4, 111.90.073.00 ± 0.7643.41111.9
Merluccius merlucciusMmerA-M35.441.580.3082.090.3681373.1 ± 15.662478.3–299, 258.30.736.61 ± 1.5286.00258.3
Microchirus ocellatusMoceA-M16.460.730.0770.970.0922118.3 ± 8.253910.7–137, 121.80.460.49 ± 0.2619.60121.8
Microchirus variegatusMvarA-M1.270.060.0010.070.002250.3 ± 0.32584.2–84.2, 84.20.17<0.01 ± 0.000.1784.2
Mullus barbatusMbarA-M82.283.6611.3924.8513.632182706.4 ± 540.1286738.5–197.1, 740.2873.34 ± 14.29598.2084.6
Mullus surmuletusMsurA-M17.720.790.0761.040.0911618.2 ± 7.544123.1–286.4, 121.80.451.01 ± 0.4024.01121.8
Nettastoma melanurumNmelA-M8.860.390.0330.520.040167.9 ± 5.744181–299, 82.30.030.03 ± 0.021.8982.3
Pagellus acarnePacaA-M43.041.923.1042.543.71513737.5 ± 262.6146278.5–289.5, 84.60.2419.44 ± 8.29535.4384.2
Pagellus erythrinusPeryA-M67.092.993.7813.964.52513898.3 ± 216.6125338.5–298.6, 111.90.6040.37 ± 11.05737.89111.9
Pagrus aurigaPaurA-M2.530.110.0020.150.002190.5 ± 0.3198.5–13.5, 8.50.210.01 ± 0.000.328.5
Pagrus bogaraveoPbogA-M1.270.060.0090.070.0111682.1 ± 2.116877.7–77.7, 77.71.420.02 ± 0.021.4277.7
Pagrus caeruleostictusPcaeA-M22.781.010.2271.340.2721854.0 ± 20.714078.5–31.6, 13.50.163.19 ± 1.0552.5225.7
Pagrus pagrusPpagA-M18.990.850.3491.120.4181882.9 ± 58.2457911–289.5, 128.80.046.10 ± 4.78376.47128.8
Peristedion cataphractumPcatA-M8.860.390.3310.520.3962278.6 ± 58.04529258.3–299, 287.30.220.72 ± 0.5442.07287.3
Phycis blennoidesPbleA-M2.530.110.0030.150.004220.8 ± 0.642258.3–299, 2991.290.07 ± 0.064.17299
Pomadasys incisusPincA-M3.800.170.0070.220.009301.7 ± 1.05611.2–21.9, 13.52.480.30 ± 0.2317.7911.2
Raja asteriasRastA-M1.270.060.0030.070.004570.7 ± 0.757115–115, 11564.680.82 ± 0.8264.68115
Raja clavataRclaA-M25.321.130.1911.490.2281945.4 ± 22.6173611–299, 111.90.0714.53 ± 5.19366.78111.9
Raja miraletusRmirA-M25.321.130.0981.490.1171623.3 ± 6.425473.7–298.6, 128.81.0111.00 ± 3.77260.60195
Rhinobatos rhinobatosRrhiA-M1.270.060.0010.070.001160.2 ± 0.21623.1–23.1, 23.1132.431.68 ± 1.68132.4323.1
Sardina pilchardusSpilA-M10.130.450.1500.600.1792135.6 ± 21.6164125.7–163.3, 73.70.550.39 ± 0.1913.5473.7
Sardinella auritaSaurA-M6.330.280.0110.370.014212.7 ± 1.37811–25.7, 25.70.150.11 ± 0.085.8425.7
Sardinella maderensisSmadA-M1.270.060.0010.070.002260.3 ± 0.32611–11, 110.26<0.01 ± 0.000.26
Scorpaena elongataSeloA-M11.390.510.0700.670.0842216.6 ± 7.955035–298.6, 350.421.48 ± 0.9673.9635
Scorpaena porcusSporA-M5.060.230.0190.300.023224.5 ± 2.816082.3–141.1, 82.30.360.04 ± 0.021.3982.3
Scorpaena scrofaSscrA-M8.860.390.0280.520.033136.6 ± 3.216335–299, 111.90.060.41 ± 0.2010.00111.9
Scorpana notataSnotA-M6.330.280.0500.370.0607411.9 ± 5.525235–195, 82.31.460.31 ± 0.2318.03111.9
Scyliorhinus caniculaScanA-M11.390.510.0840.670.1012020.0 ± 9.0485165.8–299, 298.60.381.69 ± 0.8548.46298.6
Serranus cabrillaScabA-M31.651.410.6611.870.79119157.1 ± 50.2293210.7–133.9, 350.194.69 ± 1.5374.8777
Serranus hepatusShepA-M46.842.080.9682.761.15913230.0 ± 44.2157622.7–194, 250.091.93 ± 0.3716.3825
Serranus scribaSscrA-M1.270.060.0010.070.001190.2 ± 0.21913.5–13.5, 13.51.140.01 ± 0.011.1413.5
Solea senegalensisSsenA1.270.060.0020.070.002390.5 ± 0.53910.5–10.5, 10.50.19<0.01 ± 0.000.1910.5
Solea vulgarisSvulA-M18.990.850.0411.120.049139.7 ± 2.812511–130.6, 23.10.261.71 ± 0.5825.4825.7
Sparisoma cretenseScreA-M1.270.060.0030.070.004570.7 ± 0.7578.5–8.5, 8.51.330.02 ± 0.021.338.5
Sparus aurataSauraA-M2.530.110.0030.150.003130.6 ± 0.5388.5–11, 8.51.090.07 ± 0.054.198.5
Sphoeroides pachygasterSpacC2.530.110.0070.150.009201.8 ± 1.5120165.8–189, 18915.940.57 ± 0.4128.69189
Sphyraena sphyraenaSsphA-M3.800.170.0050.220.006191.2 ± 0.85911.2–25, 11.21.240.09 ± 0.053.5611.2
Sphyraena viridensisSvirA-M5.060.230.0050.300.006131.2 ± 0.64125.7–78.3, 25.71.190.10 ± 0.053.3925.7
Spicara maenaSmaeA-M39.241.750.6382.310.76315151.5 ± 38.2194811.2–298.6, 133.90.366.10 ± 2.37171.56111.9
Spicara smarisSsmaA-M60.762.705.5063.586.588211308.0 ± 287.21200010.7–298.6, 111.90.0924.39 ± 6.98479.52111.9
Squatina oculataSocuA-M3.800.170.0090.220.011252.1 ± 1.410212.1–189.4, 189.412.262.64 ± 1.76107.23189.4
Squatina squatinaSsquA-M3.800.170.0090.220.011222.2 ± 1.49282.3–141.1, 141.115.645.20 ± 3.65252.1782.3
Synchiropus phaetonSphaA-M12.660.560.3310.750.3962078.6 ± 36.32125141.1–299, 2990.020.45 ± 0.2314.58299
Synodus saurusSsauA-M21.520.960.0911.270.1081321.5 ± 7.539111.5–130, 740.321.23 ± 0.4318.23128.8
Torpedo marmorataTmarA-M1.270.060.0010.070.001190.2 ± 0.21925.7–25.7, 25.70.580.01 ± 0.010.5825.7
Trachinus dracoTdraA-M3.800.170.0040.220.005241.0 ± 0.632121.8–137, 1370.850.03 ± 0.020.91130
Trachurus mediterraneusTmedA-M34.181.520.2602.010.3111361.8 ± 27.419538.5–287.3, 111.90.091.82 ± 0.6843.41111.9
Trachurus trachurusTtraA-M20.250.900.1511.190.1811635.8 ± 13.692281–286.4, 133.90.080.65 ± 0.2616.61189
Trichiurus lepturusTlepC8.860.390.0580.520.0701913.9 ± 8.057411–163.3, 13.50.090.58 ± 0.3929.6113.5
Trigla lyraTlyrA-M5.060.230.1460.300.1751934.7 ± 26.8206467–128.8, 770.880.44 ± 0.3325.8077
Trigloporus lastovizaTlasA-M30.381.350.3861.790.4621691.7 ± 28.2139311.5–141.1, 740.142.91 ± 0.9343.41111.9
Umbrina cirrosaUcirA-M1.270.060.0010.070.001130.2 ± 0.21311–11, 110.750.01 ± 0.010.75
Uranoscopus scaberUscaA-M15.190.680.0260.900.031136.2 ± 2.617711–197.1, 11.50.140.50 ± 0.198.14141.1
Xyrichthys novaculaXnovA-M7.590.340.0140.450.017193.4 ± 1.57410.5–111.9, 120.170.04 ± 0.021.3611
Zeus faberZfabC21.520.960.0491.270.0591611.7 ± 3.111323–287.3, 670.080.76 ± 0.4232.53163.3
Alepes djedabaAdjeI-P3.800.170.0040.690.025191.0 ± 0.6388.5–31.6, 8.50.570.04 ± 0.021.5731.6
Apogonichthyoides pharaonisAphaI-P6.330.280.0051.150.033181.3 ± 0.62610.7–23, 110.040.01 ± 0.000.2723
Callionymus filamentosusCfilI-P41.771.860.2717.591.6461864.3 ± 16.38248.5–186.3, 12.10.070.63 ± 0.167.4712.1
Champsodon capensisCcapI-P1.270.060.0070.230.0431331.7 ± 1.7133115–115, 1150.950.01 ± 0.010.95115
Champsodon nudivittisCnudI-P16.460.730.0682.990.4112116.0 ± 5.227457–195, 73.70.060.14 ± 0.042.0773.7
Champsodon voraxCvorI-P13.920.620.0282.530.170136.6 ± 2.311373.7–265.1, 1270.150.06 ± 0.021.02127
Cynoglossus sinusarabiciCsinI-P21.520.960.0383.910.230179.0 ± 2.410910.5–197.1, 111.90.050.06 ± 0.020.6223.1
Decapterus russelliDrusI-P1.270.060.0020.230.011330.4 ± 0.433117.7–117.7, 117.73.830.05 ± 0.053.83117.7
Equulites klunzingeriEkluI-P34.181.525.1656.2131.427221227.0 ± 364.2153568.5–192, 11.20.078.80 ± 2.84115.6111.2
Fistularia commersoniiFcomI-P29.111.300.2965.291.8031870.4 ± 25.113818.5–77.7, 25.70.081.29 ± 0.5938.9025.7
Herklotsichthys punctatusHpunI-P1.270.060.0010.230.008240.3 ± 0.32474–74, 740.16<0.01 ± 0.000.1674
Jaydia quekettiAqueI-P2.530.110.0020.460.011130.4 ± 0.32078.3–189, 1890.08<0.01 ± 0.000.09189
Jaydia smithiiAsmiI-P3.800.170.0060.690.035201.4 ± 0.85021.9–25.7, 21.90.210.03 ± 0.021.2421.9
Lagocephalus guentheriLgueI-P13.920.620.1042.530.6331324.7 ± 11.368510.5–78.3, 110.301.27 ± 0.4924.1711
Lagocephalus sceleratusLsceI-P17.720.790.0453.220.2751310.8 ± 3.414611–78.3, 78.30.112.52 ± 1.76135.2778.3
Lagocephalus suezensisLsueI-P41.771.861.1677.597.10013277.2 ± 98.255128.5–128, 21.90.105.86 ± 2.10148.9821.9
Muraenesox cinereusMcinI-P1.270.060.0010.230.006190.2 ± 0.2198.5–8.5, 8.52.420.03 ± 0.032.428.5
Nemipterus randalliNranI-P31.651.410.2845.751.7262367.4 ± 15.559621.5–298.6, 78.30.312.89 ± 0.7030.8687
Ostorhinchus fasciatusOfasI-P17.720.790.0863.220.5261620.5 ± 7.137011.5–94, 25.70.130.14 ± 0.053.1425.7
Pelates quadrilineatusPquaI-P6.330.280.0401.150.244199.5 ± 6.95298.5–77.2, 29.40.240.24 ± 0.1813.2329.4
Petroscirtes ancylodonPancI-P1.270.060.0010.230.007220.3 ± 0.32211.7–11.7, 11.70.22<0.01 ± 0.000.2211.7
Pomadasys stridensPstrI-P6.330.280.0231.150.139135.4 ± 4.232911–26, 25.70.060.14 ± 0.118.2225.7
Pteragogus trispilusPpel, PtriI-P5.060.230.0160.920.099203.9 ± 2.822011.5–29.4, 29.40.080.02 ± 0.011.1329.4
Sargocentron rubrum SrubI-P1.270.060.0030.230.016490.6 ± 0.64922.7–22.7, 22.75.400.07 ± 0.075.4022.7
Saurida lessepsianusSlesI-P53.162.370.5519.663.35313130.9 ± 25.1138110.5–298.6, 25.70.1013.37 ± 3.18186.7225.7
Scomber japonicusSjapI-P2.530.110.0040.460.023130.9 ± 0.758130.6–133.9, 133.90.530.04 ± 0.032.31133.9
Siganus rivulatusSrivI-P6.330.280.0321.150.198227.7 ± 4.729811–26, 21.90.350.16 ± 0.106.9521.9
Sillago suezensisSsueI-P11.390.510.7212.074.38940171.3 ± 101.076778.5–27.7, 111.044.26 ± 1.92125.3611
Solea elongataSeloI-P3.800.170.0060.690.035201.4 ± 0.84611.5–299, 141.10.040.08 ± 0.075.21299
Sphyraena chrysotaeniaSchrI-P3.800.170.0090.690.056192.2 ± 1.71298.5–21.9, 111.450.12 ± 0.096.5911
Stephanolepis diasprosSdiaI-P22.781.010.0724.140.4381317.1 ± 5.02768.5–84.2, 11.50.030.24 ± 0.084.4211.5
Torquigener flavimaculosusTflaI-P21.520.960.0463.910.2801811.0 ± 3.21558.5–84.2, 770.020.11 ± 0.041.8177
Tylerius spinosissimusTspiI-P2.530.110.0020.460.014130.6 ± 0.43157–78.3, 570.03<0.01 ± 0.000.0557
Upeneus moluccensisUmolI-P67.092.993.87812.1823.60018921.4 ± 179.372688.5–197.1, 1270.1816.40 ± 2.77124.26127
Upeneus poriUporI-P34.181.523.4506.2120.99042819.5 ± 197.7103478.5–87, 21.50.5613.65 ± 3.75213.3021.5

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Figure 1. Seasonal trawl-sampling track lines during 2014–2015 (blue: May 2014, green: August 2014, red: October 2014, magenta: February 2015), as well as the 2 mile border indicating the prohibition of fisheries (red line) and the 12 mile border (blue line). Fixed depths are in the order of the shallowest to the deepest bottom depths seaward from the coast to open water in each of the regions (R1–R3) (a). The study area showing the different bottom types from the acoustical track lines determined by the echosounder during 2014–2015 (b) (from Garuti and Mutlu [45]).
Figure 1. Seasonal trawl-sampling track lines during 2014–2015 (blue: May 2014, green: August 2014, red: October 2014, magenta: February 2015), as well as the 2 mile border indicating the prohibition of fisheries (red line) and the 12 mile border (blue line). Fixed depths are in the order of the shallowest to the deepest bottom depths seaward from the coast to open water in each of the regions (R1–R3) (a). The study area showing the different bottom types from the acoustical track lines determined by the echosounder during 2014–2015 (b) (from Garuti and Mutlu [45]).
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Figure 2. Spatiotemporal distribution of number of species (a), abundance (b) and biomass (c) of native fish species (IS, A) and non-native species (NIS, B). Blue: May 2014. Green: August 2014. Red: October 2014. Magenta: February 2015.
Figure 2. Spatiotemporal distribution of number of species (a), abundance (b) and biomass (c) of native fish species (IS, A) and non-native species (NIS, B). Blue: May 2014. Green: August 2014. Red: October 2014. Magenta: February 2015.
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Figure 3. Faunistic traits ((a); S: number of species, (b); N: abundance (ind/km2), (c); B: biomass (kg/km2), (d); d: Margalef’s richness index, (e); J′: Pielou’s evenness index, (f); H′: Shannon–Weiner diversity index) of the native fish (A) and non-native fish (B) for different seasons (M: May, A: August, O; October, F: February) and depths for the entire study area.
Figure 3. Faunistic traits ((a); S: number of species, (b); N: abundance (ind/km2), (c); B: biomass (kg/km2), (d); d: Margalef’s richness index, (e); J′: Pielou’s evenness index, (f); H′: Shannon–Weiner diversity index) of the native fish (A) and non-native fish (B) for different seasons (M: May, A: August, O; October, F: February) and depths for the entire study area.
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Figure 4. Estimates of the GLM (the model was a Poisson distribution estimated by the variogram) for the response variables Re (depth, region and season) and predicted variables Pr (S: number of species, N: abundance (ind/km2), B: biomass (kg/km2)) of the IS and NIS fish.
Figure 4. Estimates of the GLM (the model was a Poisson distribution estimated by the variogram) for the response variables Re (depth, region and season) and predicted variables Pr (S: number of species, N: abundance (ind/km2), B: biomass (kg/km2)) of the IS and NIS fish.
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Figure 5. Non-parametric multidimensional scaling (n-MDS) of Bray–Curtis similarity matrix of log10-transformed abundances of the IS (a) and NIS (b). Symbols represent the different bottom depths. Labels indicate the sampling months (F, February; M, May; A, August; O, October).
Figure 5. Non-parametric multidimensional scaling (n-MDS) of Bray–Curtis similarity matrix of log10-transformed abundances of the IS (a) and NIS (b). Symbols represent the different bottom depths. Labels indicate the sampling months (F, February; M, May; A, August; O, October).
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Figure 6. Biplot of CCA using log-transformed [log10(X + 1)] abundance values for environmental variables (arrows) (a) and fish species (b) at five depth ranges (indicated by numbers) in four sampling months (May, August, October and February). Arrows refer to the direction and relative importance of the environmental variables (see Table 1 for abbreviations of the parameters).
Figure 6. Biplot of CCA using log-transformed [log10(X + 1)] abundance values for environmental variables (arrows) (a) and fish species (b) at five depth ranges (indicated by numbers) in four sampling months (May, August, October and February). Arrows refer to the direction and relative importance of the environmental variables (see Table 1 for abbreviations of the parameters).
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Figure 7. Biplot of canonical correspondence analysis (CCA) for sample (symbols classified according to bottom depths in meters)–species–environmental variables (arrows) relation (a) and scatter plot of the NIS fish (b) (see Appendix A for the abbreviations of the fish species).
Figure 7. Biplot of canonical correspondence analysis (CCA) for sample (symbols classified according to bottom depths in meters)–species–environmental variables (arrows) relation (a) and scatter plot of the NIS fish (b) (see Appendix A for the abbreviations of the fish species).
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Figure 8. Length (LH) and weight (WH) frequency distributions normalized with probability density functions for a total of 28,987 IS osseous fish individuals and 7642 NIS osseous fish individuals along the bottom depth gradient.
Figure 8. Length (LH) and weight (WH) frequency distributions normalized with probability density functions for a total of 28,987 IS osseous fish individuals and 7642 NIS osseous fish individuals along the bottom depth gradient.
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Table 1. Average individual total length in cm (minimum, maximum and mean); average individual total weight in g (minimum, maximum and mean); regression constants (a and b) of LWRs; and growth type (GT) (I: isometric growth) for IS and NIS osseous fish, regardless of number of specimens (N) used in the analyses, all averaged from estimates of the LWR for each species unweighted by the number of individuals.
Table 1. Average individual total length in cm (minimum, maximum and mean); average individual total weight in g (minimum, maximum and mean); regression constants (a and b) of LWRs; and growth type (GT) (I: isometric growth) for IS and NIS osseous fish, regardless of number of specimens (N) used in the analyses, all averaged from estimates of the LWR for each species unweighted by the number of individuals.
TLTW
MinMaxMeanMinMaxMeanabGTN
ISMean9.921.314.928.6187.163.70.0152.988I28,987
SD6.812.17.9195.2578.4218.90.0150.442
NISMean8.619.013.210.6170.241.30.0152.951I7642
SD6.113.07.121.4562.5123.50.0120.360
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Mutlu, E.; Meo, I.d.; Miglietta, C.; Deval, M.C. Ecological Indicative Stressors of Native vs. Non-Native Fish in an Ultra-Oligotrophic Region of the Mediterranean Sea. Sustainability 2023, 15, 2726. https://doi.org/10.3390/su15032726

AMA Style

Mutlu E, Meo Id, Miglietta C, Deval MC. Ecological Indicative Stressors of Native vs. Non-Native Fish in an Ultra-Oligotrophic Region of the Mediterranean Sea. Sustainability. 2023; 15(3):2726. https://doi.org/10.3390/su15032726

Chicago/Turabian Style

Mutlu, Erhan, Ilaria de Meo, Claudia Miglietta, and Mehmet Cengiz Deval. 2023. "Ecological Indicative Stressors of Native vs. Non-Native Fish in an Ultra-Oligotrophic Region of the Mediterranean Sea" Sustainability 15, no. 3: 2726. https://doi.org/10.3390/su15032726

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