Seasonal Shifts: Tracking Fish Larval Diversity in a Coastal Marine Protected Area

Abstract

This research explored the influence of seasonal and environmental variables on the variation and density of ichthyoplankton in the Thermaikos Gulf and the adjacent marine protected area of the Litochoro artificial reef in Pieria, northern Greece. The objective was to assess the condition of existing ichthyoplankton communities, understand their relationship with seasonal environmental parameters, and ascertain whether the area plays the role of a fish nursery site. Observations were carried out on the boundary of the marine protected area near Litochoro, with collection sessions occurring during the spring, summer, and fall seasons from 2018 to 2021. Ichthyoplankton was collected using a bongo net sampler across 16 stations, identifying seventy larval fish species. Measurements of physico-chemical parameters were taken as well as community and population metrics such as species abundances. In the Litochoro area, the interplay between environmental conditions and the dynamics of ichthyoplankton species highlights significant ecological trends. Notably, commercially important species such as Engraulis encrasicholus (anchovy) and Sardina pilchardus (sardine) exhibited peaks in abundances, with anchovies reaching up to 544/10 m² in May 2021 and sardines peaking at 383/10 m² in April 2020. These species are crucial both ecologically, as integral components of the marine food web, and economically, serving as primary targets in local fisheries. Spearman analysis showed some species like anchovy having a negative trend with chl-a values. Also, diversity indices had strong negative correlations with chl-a values, suggesting that higher chl-a concentrations might be associated with lower biodiversity whereas most diversity indices, apart from Pielou’s normality index (J) and Simpson’s diversity index (1–lambda), showed a significant positive correlation with surface salinity. This suggests that increased salinity levels might boost certain facets of biodiversity during the summer and early autumn months.

1. Introduction

Recent studies have shown increasing interest in the construction of artificial reefs, which are recognized for their role in enhancing marine ecosystems and providing structured habitats for various aquatic species. They provide protection for marine organisms against trawling practices and bolster artisanal fishing efforts. Moreover, these structures contribute to the improvement of fish habitats, aid in coastal erosion control, and facilitate marine research. They also function as sanctuaries for adult marine species [1]. Research has shown that these reefs boost primary productivity and benefit recreational fishing [1,2]. As is the case in Litochoro, when an AR is installed, the adjacent area—which may extend for several kilometers around the AR—is typically designated as a Marine Protected Area (MPA) with specific fishing regulations. These coastal MPAs serve as safeguarded breeding grounds for numerous marine species [3]. The term “marine protected area” can vary widely in interpretation across different global contexts, often reflecting diverse ecological, political, and social priorities. However, in the context of this study, the term specifically refers to an area surrounding an artificial reef. Here, the designation of an MPA comes with imposed fishing regulations aimed at conservation and management of marine resources. This localized definition aligns with the specific regulatory framework in Greece, where the establishment of an artificial reef automatically triggers the classification of the surrounding waters as a protected area, primarily to safeguard and enhance marine ecosystems that are critical as nursery grounds and biodiversity hotspots. This study examines ichthyoplankton communities in the marine protected area surrounding the artificial reef of Litochoro, exploring whether this zone exhibits the qualities of a nursery ground. It also correlates the abundances of ichthyoplankton with various environmental parameters.

The Thermaikos Gulf, situated in the Aegean Sea, supports a rich and varied marine ecosystem that is shaped by the inflow from important rivers like the Axios and Aliakmon, as well as smaller streams including the Loudias and Gallikos [4]. Within this gulf, there are two artificial reef systems encircled by a coastal marine protected area. The first system is located near Kitros, where detailed seasonal studies on ichthyoplankton communities [3], adult fish population changes [2], and comparative analyses of adult fish populations before and after the marine protected area was established [5] have been conducted. The second system is found in the Litochoro area, south of Kitros. Positioned about 45 km from the Aliakmon River delta, the Litochoro artificial reef and its adjacent marine protected zone are influenced by fresh water from the Aliakmon as well as from the Axios and Loudias Rivers to the north [4]. Additionally, local streams like the Aesonas and the Chelopotamos may also affect the area.

Despite its ecological significance, comprehensive studies on the temporal and environmental factors affecting ichthyoplankton in this area are rare [3]. This research examines the relationships between environmental variables and ichthyoplankton around the Litochoro artificial reef in Pieria.

2. Materials and Methods

For the collection of ichthyoplankton as well as environmental parameters throughout the water column of the artificial reef in Litochoro, Pieria, nine sampling sessions were conducted over the period from 2018 to 2021 (approximately three samplings per year), across a network of 16 stations (

Table 1. Station coordinates and depths of sampling locations (N = 16) for gathering environmental and ichthyoplankton data in the outer Thermaikos Gulf, located in the Aegean Sea off the coast of Litochoro, within the Pieria region of Greece.

Station	Longitude	Latitude	Depth (Fathoms)	Depth (Meters)
1	40087143	22381630	27.7	50.6
2	40074866	22385237	29	53
3	40060149	22389422	30.1	55
4	4005144	2239284	31	56.6
5	4004826	2238238	29.5	53.9
6	4006321	22376859	28.1	51.3
7	40071701	22371921	26.2	47.9
8	40082193	22368646	25.2	46
9	40082651	22385320	22.4	40.9
10	40073841	22358094	22.8	41.6
11	40061361	22361924	24.6	44.9
12	40050807	22364170	25.3	46.2
13	4005313	22355688	22	40.2
14	40059390	22350378	19	34.754
15	4007067	2234512	15.5	28.368
16	4008288	2234254	14.8	27.067

, Figure 1).

Ichthyoplankton were gathered using a paired bongo net sampler, with each net featuring a 60 cm diameter frame (0.28 m² per mouth) and outfitted with 250 µm mesh conical nets. The bongo net was towed horizontally, and sampling was carried out only during the day with no replicate hauls. After collection, the plankton was transferred to individual glass sample jars and preserved in a mixture of 70% pure alcohol, 29% deionized water, and 1% glycerin, which helps to reduce the evaporation rate of the alcohol. The samples underwent analysis at the Fisheries Research Institute of Kavala where the ichthyoplankton were classified to the most specific taxonomic level feasible using contemporary taxonomic guides and the literature [6,7].

The abundance of fish larvae captured at each site was standardized to a per unit area of sea surface (10 m²) to establish annual abundance metrics. Additionally, the monthly average abundances of larvae for each species were determined by averaging the normalized counts from all stations per species. Using these data, several diversity indices were computed, including the Margalef index, Shannon–Wiener diversity index, and Simpson’s diversity index. These indices were utilized to analyze species assemblages in line with the current literature [8].

During the sampling sessions, key environmental factors such as temperature, salinity, and density were measured at 16 strategically placed stations across the reef area (see Figure 1), utilizing a Seabird Electronics SBE 19plus CTD (Sea-Bird Scientific, Bellevue, WA, USA), (conductivity, temperature, depth). These parameters were recorded both at the surface (0–5 m depth) and throughout the water column (from just below 5 m to the seabed). The mean values for both surface and deeper water levels were computed for further analysis. The CTD provided precise measurements of temperature (to the nearest 0.001 °C) and salinity (in practical salinity units, PSU, to the nearest 0.001). Temperature and salinity gradients were calculated by subtracting the values at the bottom from those at the surface. Additionally, a Niskin Bottle sampler (General Oceanics Inc., Miami, FL, USA), (5 L capacity) was employed to collect water samples from various depths (surface, 5, 10, 20, and bottom) for chl-a analysis (mg/m³ chl-a), determined using trichromatic spectroscopy as per protocols in [9], with measurements made on a HITACHI U2001 spectrophotometer (Hitachi High-Tech Corporation, Tokyo, Japan). Similarity matrices using the Bray–Curtis measure were produced, and NMDS was employed to visually represent the relationships between sampled months, focusing on the relative abundance of each taxonomic group (Figure 2). Analysis of Similarities (ANOSIM) assessed whether the differences in assemblage groupings during the sampling periods in the NMDS ordinations were significant. Similarity Percentage Analysis (SIMPER) was utilized to identify the dominant taxa within each seasonal grouping.

3. Results

3.1. Environmental Parameters

The environmental parameters tracked during the ichthyoplankton sampling sessions displayed temporal fluctuations, which are believed to play a critical role in the ecological dynamics observed. The chl-a concentrations, indicative of primary productivity, showed some fluctuations across the sampling periods. Peak concentrations were observed in April 2019 with a surface chl-a value of 3.136 mg/m³, suggesting a robust spring phytoplankton bloom. In stark contrast, markedly lower concentrations were recorded in September 2019 (surface chl-a: 0.062 mg/m³), aligning with seasonal declines in primary productivity as the region transitioned from summer to autumn.

Salinity measurements, which can influence water column stratification and habitat suitability for various marine species, also displayed variability. Notably, the salinity gradient was most pronounced in October 2018, in April 2019, and in May 2019, with a differential of −1.95, −1.64, and −1.445, respectively, between surface and deeper waters, demonstrating increased freshwater presence in the surface layer and reflecting significant vertical stratification that may limit nutrient interchange across the water column.

Temperature profiles further corroborated the presence of distinct seasonal patterns. The highest temperature gradient was observed in September 2019 (8.163 °C between surface and deeper waters), indicative of strong thermal stratification during the late summer months. Such conditions are known to affect larval dispersion and survival rates by altering the vertical distribution of their planktonic food sources.

Together, these environmental parameters—chl-a, salinity, and temperature—provide a comprehensive picture of the biophysical conditions during each sampling event. The observed variations are crucial for understanding the seasonal and interannual dynamics of ichthyoplankton populations in the study area, as they directly influence the growth, survival, and distribution patterns of marine larvae [10].

Table 2. Average values for environmental parameters measured during each sampling season at field sites located in the outer Thermaikos Gulf, off the coastal zone of Litochoro in the Pieria region of Greece. During the surveys (N = 140), environmental parameters were recorded at both the surface (from 0–5 m depth) and within the water column (>5 m depth to the bottom). These values were then averaged across all sample sites for each category. The table displays the summarized averages with units provided as follows: temperature in degrees Celsius (°C), chl-a in micrograms per liter (µg·L⁻¹), and salinity in Practical Salinity Units (PSU).

Year	Month	Statistic	Surface chl-a	chl-a	Surface Salinity	Salinity	Salinity Gradient	Surface Temperature	Temp.	Temperature Gradient
2018	October	Mean	0.967	0.916	36.548	37.495	−1.956	20.155	19.720	1.509
2019	April	Mean	3.136	1.416	37.068	38.494	−1.640	15.951	14.452	1.941
	May	Mean	2.316	1.168	37.168	38.158	−1.445	20.018	16.710	5.505
	September	Mean	0.062	0.423	37.221	37.838	−0.064	24.267	21.722	8.163
2020	April	Mean	0.528	0.364	37.205	38.185	−0.901	21.446	15.866	7.657
	May	Mean	0.566	0.323	37.633	38.112	−0.982	19.226	17.087	4.572
	September	Mean	0.241	0.271	37.626	37.876	−0.898	24.512	23.431	5.815
2021	April	Mean	0.613	0.465	38.518	38.731	−0.393	14.910	14.782	0.231
	May	Mean	0.351	0.024	38.096	38.332	−1.061	21.715	18.961	5.481

provides a summarized presentation of the average values for environmental parameters recorded during each sampling season.

3.2. Ichthyoplankton Sampling

The species abundances recorded across the nine sampling events demonstrated a dynamic and varied ichthyoplankton community.

In October 2018, a moderate diversity of species was observed, with abundances of Engraulis encrasicholus (37/10 m²) and Liza ramada (26/10 m²). The spring of 2019, specifically April, showed a dramatic increase in the abundance of Engraulis encrasicholus (206/10 m²), which dominated the samples. Further, the data from May 2019 revealed an even higher spike in Engraulis encrasicholus abundance (283/10 m²), paired with numbers of Ceratoscopelus maderensis (74/10 m²). By September 2019, the individual species abundances were more balanced, with Engraulis encrasicholus at a lower yet significant 99/10 m². The trend in 2020 continued with Engraulis encrasicholus displaying high abundances in April (383/10 m²) and May (294/10 m²). This peak diversity correlates with the highest recorded abundances of Engraulis encrasicholus (544/10 m²) and an increase in Sardina pilchardus (220/10 m²) and Spicara smaris (173/10 m²), emphasizing a significant late spring biomass accumulation.

Overall, the study identified fish larvae from 85 taxa, including 78 species across 34 families (

Table 3. List of taxa collected at field sites in the outer region of the Thermaikos Gulf, in the Aegean Sea offshore of the coastal zone of Kitros, in the Pieria region of Greece. The table shows the average abundance of each taxon, measured as the number of larvae per 10 square meters (N, larvae/10 m²).

Family	Species	18-Oct	19-Apr	19-May	19-Sep	20-Apr	20-May	20-Sep	21-Apr	21-May
Blenniidae	Blennius gatorugine	0	0	7	0	0	0	0	0	4
	Parablennius gattorugine	0	0	0	0	7	20	0	39	1
Bothidae	Arnoglossus laterna	5	0	0	17	23	9	9	24	57
	Arnoglossus thori	11	15	7	24	22	11	13	10	16
Callanthiidae	Callanthias ruber	0	0	0	0	0	0	0	0	1
Callionymidae	Callionymus maculatus	0	11	38	10	7	0	7	10	7
	Callionymus lyra	4	11	10	7	0	0	9	3	8
Carangidae	Seriola dumerili	0	0	0	0	0	0	17	0	5
	Trachurus mediterraneus	0	0	0	0	17	33	17	0	36
	Trachurus trachurus	0	0	0	0	7	0	11	1	13
Centracanthidae	Centracanthus cirrus	0	0	0	0	14	0	0	0	0
Centrolophidae	Centrolophus niger	0	0	0	0	0	0	7	0	0
Cepolidae	Cepola macrophthalma	12	0	0	21	23	7	0	7	10
	Cepola rubescens	0	0	0	0	0	28	7	3	4
Clupeidae	Sardina pilchardus	0	69	0	0	0	0	0	146	220
Dorosomatidae	Sardinela aurita	0	0	34	0	47	32	0	42	99
Engraulidae	Engraulis encrasicholus	37	206	283	99	383	294	299	320	544
Gadidae	Micromesistius poutassou	0	0	0	0	17	0	0	0	18
Gobiesocidae	Lepadogaster lepadogaster	0	7	7	0	0	0	0	0	1
Gobiidae	Aphia minuta	0	0	0	0	0	0	9	7	14
	Crystalogobius linearis	0	7	7	0	0	0	0	0	0
	Gobius II	12	17	17	0	35	0	0	0	0
	Gobius niger	0	0	0	0	35	41	37	14	21
	Gobius spp.	0	0	0	116	0	32	0	118	53
	Pomatoschistus minutus	0	0	0	28	0	0	0	0	0
Gonostomatidae	Cyclothone braueri	0	0	7	0	9	0	0	0	1
Labridae	Coris julis	0	0	0	0	0	7	0	0	4
	Labridae	0	0	0	0	7	0	0	0	2
	Labrus mixtus	0	0	0	0	7	7	0	0	0
	Symphodus melops	0	0	5	0	11	0	0	0	2
	Symphodus nigrescens	13	0	0	8	0	0	13	0	0
	Symphodus ocellatus	0	0	0	0	0	0	0	3	6
Merlucciidae	Merluccius merluccius	0	14	0	0	0	0	0	0	1
Mugilidae	Chelon labrosus	0	0	0	0	0	0	0	0	4
	Chelon ramada	0	0	0	20	0	0	0	0	0
	Liza aurata	13	0	0	0	0	0	11	0	2
	Liza ramada	26	0	37	0	0	0	0	0	9
	Liza saliens	0	0	0	0	0	0	0	0	4
	Mugil cephalus	0	0	0	8	0	0	0	0	0
	Mugilidae	7	10	0	7	0	24	13	0	14
Mullidae	Mullus barbatus	0	0	0	0	31	0	0	0	0
	Mullus surmuletus	0	0	7	0	23	0	0	1	4
Myctophidae	Ceratoscopelus maderensis	6	0	74	14	9	44	0	0	1
	Diaphus holti	0	0	0	0	7	7	0	1	0
	Hygophum benoiti	0	0	0	0	23	0	7	7	1
	Lobianchia dofleini	0	0	0	0	0	0	8	0	0
	Myctophum punctatum	0	0	0	0	0	0	0	1	0
Ophidiidae	Parophidion vassali	0	0	0	0	0	0	9	0	1
Pomacentridae	Chromis chromis	0	0	0	7	0	0	0	0	0
Pomatomidae	Pomatomus saltatrix	0	0	0	8	0	0	9	1	8
Scombridae	Euthynnus alletteratus	0	0	0	0	0	0	0	1	0
	Scomber colias	5	0	25	8	29	7	9	0	4
Scophthalmidae	Lepidorhombus whiffiagonis	0	0	0	6	0	0	0	0	0
Scorpaenidae	Scorpaena porcus	7	0	0	10	0	0	16	0	0
	Scorpaena scrofa	0	0	0	23	0	0	0	1	0
	Scorpaena sp.	0	0	0	10	0	0	0	0	0
Serranidae	Anthias anthias	7	0	0	15	0	0	13	0	0
	Serranus cabrilla	0	8	0	0	15	15	0	0	10
	Serranus hepatus	0	0	15	13	22	17	14	5	56
Soleidae	Buglossidium luteum	0	8	0	14	7	0	15	1	0
	Solea lascaris	16	0	0	0	0	0	0	0	0
Sparidae	Boops boops	0	17	0	0	11	0	0	10	3
	Dentex dentex	0	0	0	0	0	0	0	0	3
	Dilpodus annularis	4	24	0	0	21	0	9	11	5
	Diplodus sargus	0	24	0	0	7	0	0	4	0
	Lithognathus mormyrus	0	0	20	0	23	0	0	0	2
	Oblada melanura	0	0	0	0	21	0	0	0	0
	Pagellus acarne	15	0	37	17	0	0	11	0	0
	Pagellus bogaraveo	8	0	0	0	11	0	0	0	0
	Pagrus pagrus	0	0	0	12	11	17	0	0	7
	Sparidae	0	9	0	0	98	0	0	24	61
	Sparus aurata	0	0	0	0	0	0	0	0	7
	Spicara maena	0	0	24	0	0	0	0	0	0
	Spicara smaris	0	43	52	0	42	7	0	173	41
	Spicara sp.	0	0	0	0	0	0	0	0	13
	Spondilosoma cantharus	0	0	0	0	0	0	0	0	1
Sphyraenidae	Sphyraena sphyraena	0	0	0	0	0	0	9	0	0
Trachinidae	Trachinus draco	0	0	0	10	0	0	9	0	0
	Trachinus vipera	0	0	0	0	0	0	9	0	0
Triglidae	Chelidonicthys lucerna	0	0	0	0	0	0	11	1	1
	Eutrigla gurnardus	0	0	0	9	0	0	0	0	0
	Lepidotrigla cavillone	0	0	0	0	0	0	0	1	0
Unknown	Unknown	0	0	0	10	21	14	14	12	64
Uranoscopidae	Uranoscopus scaber	0	0	0	6	29	0	0	0	8

).

The gathered environmental data were used to assess their potential impact on ichthyoplankton distributions and abundances, employing Spearman’s rank correlation statistical method (

Table 4. Spearman analysis correlating the most important species (19 species) of fish larvae to environmental factors.

	Ee	Sp	Pp	Mc	Mb	Ms	Sa	Sc	Ps	Mm	Lm	Ss	Al	Pa	At	Cr	Cl	Gs	Sporcus
AvTemp	−0.200	−0.436	0.183	0.411	−0.274	−0.402	0.137	0.343	0.60 *	−0.365	−0.238	−0.881 **	0.092	0.529	0.234	0.411	0.017	0.018	0.842 **
AvSal	0.605 *	0.782 *	−0.201	−0.411	0.137	0.475	0.274	−0.460	−0.083	0.525	0.248	0.865 **	0.303	−0.676 *	−0.109	−0.411	0.100	0.256	−0.762 *
SurfTemp	0.083	−0.347	0.237	0.411	0.137	−0.055	0.274	0.544	0.633 *	−0.160	0.158	−0.729 *	0.235	0.383	0.586	0.411	0.109	−0.128	0.703 *
SurfSal	0.711 *	0.477	0.257	0.000	−0.138	0.147	0.413	−0.210	0.636	−0.069	−0.080	0.153	0.776 *	−0.431	−0.004	0.000	−0.298	0.743 *	−0.114
TempGrad	0.100	−0.495	0.475	0.548	0.411	0.201	0.000	0.787 *	0.330	−0.228	0.416	−0.373	0.118	0.365	0.619 *	0.548	0.050	−0.128	0.366
SalGrad	0.335	−0.050	0.422	0.550	0.206	0.073	−0.138	0.218	0.580	−0.435	−0.085	−0.051	0.620	−0.064	0.345	0.550	−0.391	0.623 *	0.244
AvChla	−0.650	−0.069	−0.511	0.000	−0.137	−0.073	−0.548	−0.209	−0.605 *	0.091	−0.119	0.424	−0.689 *	0.310	−0.368	0.000	0.360	−0.292	−0.188
SurfChla	−0.317	0.149	−0.548	−0.548	−0.137	0.073	−0.274	−0.343	−0.771 *	0.274	0.020	0.593	−0.638 *	−0.055	−0.619 *	−0.548	0.276	−0.402	−0.545

Species shown as Engraulis encrasicholus = Ee, Sardina pilchardus = Sp, Pagrus pagrus = Pp, Mugil cephalus = Mc, Mullus barbatus = Mb, Mullus surmuletus = Ms, Sparus aurata = Sa, Scomber colias = Sc, Pomatomus saltatrix = Ps, Merluccius merluccius = Mm, Lithognathus mormyrus = Lm, Spicara smaris = Ss, Arnoglossus laterna = Al, Pagellus acarne = Pa, Arnoglossus thori = At, Chelon ramada = Cr, Callionymous lyra = Cl, Gobius spp. = Gs. A single asterisk (*) indicates that the correlation is significant at the 0.05 level (2-tailed), meaning there is a 5% chance that the observed correlation could occur by chance if there was truly no association. A double asterisk (**) signifies that the correlation is significant at the 0.01 level (2-tailed), which shows a stronger confidence in the results, as there is less than a 1% probability that such a correlation would appear by chance under the null hypothesis of no association. These markers help in assessing the reliability of the correlation coefficients reported in the table.

).

3.3. Ichthyoplankton Diversity Indices

The analysis of diversity indices (

Table 5. Results of diversity index assessments for ichthyoplankton collected from the outer Thermaikos Gulf, off the coast of Litochoro in the Pieria region of Greece. It includes the number of species identified (S) and presents findings across several indices: Margalef’s abundance index (d), the Brillouin index, Fisher’s alpha (α), Pielou’s evenness index (J), Shannon–Wiener’s diversity index (H’), and Simpson’s diversity index (1–lambda).

Sample	S	N	d	J’	Brillouin	Fisher	H’(loge)	1-Lambda’
18-Oct	18	32	4.906	0.9959	2.245	17.03	2.879	0.9735
19-Apr	18	37	4.705	0.9899	2.221	13.79	2.861	0.9668
19-May	20	43	5.047	0.988	2.411	14.48	2.96	0.9685
20-Sep	29	56	6.943	0.9944	2.68	23.96	3.348	0.9815
20-Apr	38	80	8.452	0.9928	3.019	28.48	3.611	0.9845
20-May	21	44	5.276	0.99	2.411	15.62	3.014	0.971
20-Sep	32	61	7.545	0.994	2.755	27.28	3.445	0.9832
21-Apr	32	57	7.675	0.9706	2.743	30.32	3.364	0.9788
21-May	53	93	11.48	0.9791	3.212	51.4	3.887	0.9882

) across the sampling events provides crucial insights into the ecological complexity and stability of the ichthyoplankton communities over the study period. These indices include Margalef, Pielou, Brillouin, Fisher, Shannon, and Simpson, each offering a different perspective on species richness and evenness.

Starting in October 2018, a moderate diversity is indicated by a Shannon index of 2.879 and a Simpson index of 0.9735, suggesting a relatively balanced ecosystem with a fair distribution of species abundances. However, it is in September 2020 that we observe a significant increase in diversity metrics, with the Shannon index reaching its highest value of 3.348 and the Simpson index at 0.9815, indicating a highly diverse and evenly distributed ichthyoplankton community. The trend of increasing diversity continues into 2020, peaking in April where the Shannon index climbs to 3.611, and the Fisher’s alpha reaches its highest at 28.48, reflecting an increase in species richness. This peak is associated with high recruitment and possibly favorable environmental conditions that support a wider range of species. By May 2021, the community structure appears even more robust, as evidenced by the highest recorded Margalef richness index for the entire study period at 11.48, alongside the highest Shannon index value of 3.887. This points to a complex ecosystem with numerous species coexisting. In contrast, Pielou’s evenness index shows less variation over time, consistently indicating a relatively even distribution of individuals among species, with values typically close to 1.0. This suggests that no single species dominates the community entirely at any sampling point, supporting the conclusion of a balanced ecosystem.

Overall, these diversity indices highlight significant temporal variability in ichthyoplankton community composition, likely influenced by seasonal cycles, environmental conditions, and interspecific interactions. This variability is crucial for understanding ecosystem health and resilience in response to natural and anthropogenic changes.

3.4. Season-Based Non-Metric Multidimensional Scaling

In this analysis, the spring cluster is formed by the sampling months of April 2020, April 2021, May 2021, and May 2020. The autumn cluster includes September 2019 and September 2020. Additionally, the months of April 2019, May 2019, and October 2018 are shown as distinct and separate from these clusters.

4. Discussion

Aquatic organisms have developed adaptive mechanisms to respond to shifts in environmental conditions, helping them maintain their normal physiological state amid real or perceived environmental changes [11]. Factors such as deviations from natural ranges in temperature, salinity, and hydrodynamic conditions, along with food scarcity, act as stressors. These stressors challenge or disrupt the organisms’ dynamic equilibrium and significantly impact their metabolic and biochemical functions, triggering responses related to stress [12].

Water temperature is crucial in affecting both the biochemical and physiological processes that are vital for the survival of organisms living in aquatic settings [13]. Additionally, it determines the spawning periods of thermophilic fish species. Data from the Black Sea show a lengthening of the spawning season; anchovy ichthyoplankton, typically seen from June to September, extended their presence from May to October between 2011 and 2016 [14]. Other significant parameters influencing the selection of spawning grounds for small pelagic fish include temperature, salinity, depth, and chl-a levels [15].

The study’s findings indicate interactions between environmental conditions and ichthyoplankton species dynamics across the sampling events. These interactions are evidently influenced by variations such as chl-a, salinity, and temperature. The conditions of strong thermal stratification, particularly noted during the late summer months when the highest temperature gradient reached 8.163 °C between surface and deeper waters, are known to affect larval dispersion and survival rates [16].

Vertical stratification, as observed in the study where freshwater layers predominantly accumulated at the surface, plays a crucial role in controlling the availability of nutrients to surface-dwelling phytoplankton. This, in turn, can significantly influence the composition and distribution of the ichthyoplankton community. The stratification patterns, characterized by limited nutrient interchange across the water column, underscore the importance of understanding these dynamics for predicting ecological responses in marine environments.

In the Litochoro area, species presence indicates fish larvae occurrences of several commercially important species. Among these, Engraulis encrasicholus (anchovy) is particularly prominent, with abundances peaking dramatically in May 2021 at 544/10 m², underscoring its critical role both as a staple in marine food webs and in local fisheries. The spring 2019 increased abundance of Engraulis encrasicholus is indicative of a seasonal spawning event or migration pattern into the sampling area. The further rise of anchovy abundance in May 2019 points to an ongoing high productivity phase possibly linked to the warmer temperatures and increased chl-a levels observed during this period. By September 2019, the overall species diversity appeared to increase, shown by the highest recorded Shannon index value of the study period (3.348). This shift might reflect a transition in community structure after the peak reproductive season. The 2020 trend for Engraulis encrasicholus continued displaying high abundances, underscoring its critical role within the local marine ecosystem. The diversity indices and species count reached their peaks in May 2021, with the Shannon index peaking at 3.887, reflecting an exceptionally diverse community. These patterns suggest that temporal variations in species abundances are likely influenced by both abiotic factors such as temperature and chl-a concentrations and biotic factors including reproductive cycles and interspecies interactions within the ichthyoplankton community.

Other commercially valuable species include Sardina pilchardus (sardine), which also showed significant numbers, especially in April 2020 with an abundance of 383/10 m². These species are key targets in local commercial fishing due to their demand in the market and culinary uses. Additionally, Pagrus pagrus (red porgy) and Mugil cephalus (grey mullet) consistently appeared throughout the sampling, indicating their stable presence in the ecosystem. Other species such as Mullus barbatus, Mullus surmuletus, Sparus aurata, Scomber colias, Pomatomus saltatrix, Spondilosoma cantharus, Merluccius merluccius, and Lithognathus mormyrus (

Table 6. The table summarizes the Spearman analysis of diversity indices for ichthyoplankton sampled at field sites in the outer Thermaikos Gulf, off the coast of Litochoro in the Pieria region of Greece. It reports the number of species (S) detected and provides the results for several diversity indices: Margalef’s abundance index (d), the Brillouin index, Fisher’s alpha (α), Pielou’s evenness index (J), Shannon–Wiener’s diversity index (H’), and Simpson’s diversity index (1–lambda). A single asterisk (*) indicates that the correlation is significant at the 0.05 level (2-tailed), meaning there is a 5% chance that the observed correlation could occur by chance if there was truly no association. A double asterisk (**) signifies that the correlation is significant at the 0.01 level (2-tailed).

	S	N	d	J	Brillouin	Fisher	H	Lamda
AvTemp	0.143	0.150	0.133	0.633	0.243	0.200	0.250	0.433
AvSal	0.311	0.317	0.300	−0.883 **	0.209	0.233	0.200	−0.033
AvDens	−0.059	−0.083	−0.033	−0.683 *	−0.159	−0.083	−0.167	−0.367
SurfTemp	0.429	0.467	0.383	0.550	0.527	0.350	0.517	0.683 *
SurfSal	0.747 *	0.728 *	0.753 *	−0.536	0.685 *	0.711 *	0.711 *	0.519
SurfDens	−0.050	−0.067	−0.033	−0.817 **	−0.167	−0.050	−0.150	−0.383
TempGrad	0.378	0.433	0.317	0.383	0.435	0.100	0.417	0.450
SalGrad	0.603	0.594	0.603	−0.025	0.563	0.527	0.577	0.494
DensGrad	−0.319	−0.350	−0.283	−0.333	−0.427	−0.100	−0.383	−0.417
AvChla	−0.790 *	−0.800 **	−0.767 *	−0.017	−0.795 *	−0.683 *	−0.833 **	−0.800 **
SurfChla	−0.689 *	−0.700 *	−0.667 *	−0.317	−0.711 *	−0.617	−0.733 *	−0.800 **

) appeared in relatively low numbers, despite their significant economic importance in local fisheries [2]. These species showed sporadic appearances across different sampling periods, often coinciding with specific environmental conditions such as variations in surface chl-a, salinity, and temperature gradients. For instance, in April 2021, Mullus barbatus and Pomatomus saltatrix were noted in minimal amounts during a period characterized by intermediate chl-a concentrations and slight variations in temperature and salinity gradients, which indicate the water column stability. This pattern suggests that larger environmental shifts, particularly in primary productivity (as indicated by chl-a) and water column stability (as suggested by salinity and temperature gradients), could influence the distribution and spawning activities of these species. Moreover, larval distribution is heavily influenced by sea currents that play a crucial role in the distribution of marine larvae, influencing their dispersal across various habitats and impacting the broader marine ecosystem dynamics, facts that could also explain their lower-than-expected appearance in this study’s samples [17].

Τhe Spearman analysis showed that high anchovy abundances coincide with low average chlorophyll values (R = −0.65, p < 0.05) (Table 6). In May 2021, chl-a levels reached 0.351 mg/m³ at the surface, coinciding with peak abundances of Sardina pilchardus and Spicara smaris (220/10 m² and 173/10 m², respectively). This period also reflects some level of primary productivity; however, the correlation is not statistically significant (R = −0.069–0.42, p > 0.05). It appears that other oceanographic parameters are more crucial for the above species abundances (Table 6).

The relatively higher chl-a levels observed in October 2018, recorded at 0.967 mg/m³, indicate enhanced primary productivity, which could support a diverse array of marine species. Similar to anchovy, the Spearman analysis demonstrated a significant but negative trend for A. laterna regarding chl-a values (R = −0.69, p < 0.05), and for the majority of species the correlations were negative or insignificant (R = −0.61–0.36, p > 0.05). However, the lowest recorded salinity gradient of −1.956 during the same period could influence the vertical distribution of nutrients and organisms, potentially enriching surface waters where most photosynthesis occurs.

The salinity gradient noted in May 2020 shows a minor connection with the variety of species present. As salinity can significantly influence the distribution of marine larvae [18], changes in this parameter likely impact the habitat suitability for species such as Chelon ramada and Mugilidae, which were abundant during this period. The abundances of these species showed a good interrelationship with the salinity gradient, yet insignificant as demonstrated by Spearman analysis (R = 0.5, p = 0.12 for both). The factor that seems to play a crucial role in predicting the abundances of species is either surface salinity (E. encrashicolus: R = 0.71, A. laterna: R = 0.87, Gobius spp.: R = 0.74, p < 0.05) or average salinity (S. pislchardus: R = 0.78, S. smaris: R = 0.86) (Table 6), indicating that their presence is more enhanced with minimum freshwater outputs, pointing at the summer/autumn period. Conversely, high river runoffs increased the abundances of P. acarne (R = −0.68, p < 0.05) and S. porcus (R = −0.76, p < 0.05).

Additionally, in the Litochoro area, temperature is a significant factor for the presence of S. porcus (average T: R = 0.48, surface T: 0.70, p < 0.05), indicating high abundances during the summer and early autumn period and suggesting the opposite trend for S. smaris (average T: R = −0.88, surface T: −0.73, p < 0.05). For S. colias, the most significant parameter for its presence is the temperature gradient (R = 0.79, p < 0.05), being more favored under strong thermal stratification.

High diversity values, such as those seen in May 2021 (Shannon index 3.887), indicate a stable and resilient community. This diversity supports a variety of trophic interactions and ecological roles, essential for maintaining ecosystem health. The presence of both high and low abundance species like Engraulis encrasicholus and Callionymus lyra across different sampling points suggests a dynamic balance influenced by ongoing environmental changes. Interestingly, most diversity indices, apart from Pielou’s normality index (J) and Simpson’s diversity index (1–lambda), show a significant positive correlation with surface salinity. This suggests that increased salinity levels might boost certain facets of biodiversity during the summer and early autumn months. Stable environmental conditions, such as consistent higher salinity and warmer temperatures, indeed contribute to the establishment of stable breeding and nursery grounds for fish. These conditions can enhance the recruitment success of fish species by modulating their growth, condition, and survival. Coastal areas, which include these nursery grounds, are essential for the development of juvenile fish and are highly dependent on the environmental quality of these areas. The quality and stability of these habitats are crucial for supporting diverse and healthy populations of juvenile fish, which are key to sustaining fish populations overall [19].

A related study on ichthyoplankton assemblages was conducted in the marine protected area of the artificial reef of Kitros, located north of Litochoro [3]. By comparing the two, key differences emerge primarily due to Kitros’s greater river influence. Kitros exhibits significant fluctuations in salinity and temperature, indicating freshwater inflow, which impacts its marine conditions. This is in contrast to Litochoro, where more stable marine conditions prevail, showing moderate seasonal temperature variations and relatively stable salinity levels. Chl-a levels are consistently higher in Kitros [3], likely due to nutrient-rich river runoff, enhancing primary productivity. This contributes to a higher variability and abundance of species in Kitros, including riverine species and those tolerant to lower salinity. In contrast, Litochoro’s species composition is more consistent, dominated by species like Engraulis encrasicholus, suggesting favorable marine conditions for spawning. Diversity indices in Kitros show more fluctuation [3], reflecting the dynamic interaction between freshwater and seawater, whereas Litochoro’s indices suggest a stable and diverse ecosystem. The differences highlight the need for tailored conservation strategies that consider the distinct ecological characteristics of each area.

As far as the season-based MDS analysis (Figure 2) is concerned, the clustering of April and May in 2020 and 2021 can be attributed to similar species abundances influenced by recurring spring ecological conditions. During these months, favorable environmental factors such as increasing temperatures and a rich supply of planktonic food promote high reproductive activities among key species. Specifically, in April 2020, the surface temperature reached 21.446 °C with a temperature gradient of 7.657 °C, indicative of warmer surface waters that can enhance plankton growth. October 2018, the only sampling to take place so late in autumn, is distinct for having a relatively low abundance of Engraulis encrasicholus at 37/10 m², which is notably lower compared to that in other months. This contrasts with April 2019 and May 2019 where the abundance of anchovies was considerably higher at 206/10 m² and 283/10 m², respectively. However, what further differentiates April and May from other periods are the additional species with significant abundances. April 2019 featured counts of Diplodus sargus and Dilpodus annularis, each at 24/10 m², and Spicara smaris at 69/10 m². May 2019 continued this trend with Ceratoscopelus maderensis at 74/10 m² and Spicara smaris at 52/10 m². These specific peaks in species other than anchovies contribute to their ecological distinctiveness, influencing the patterns. This result is strengthened by the fact that these months are characterized by higher river presence (as indicated by higher surface salinity and a lower salinity gradient) and, as a result, by higher primary production (as indicated by higher surface and average chl-a values). Engraulis encrasicholus, a pivotal species for indicating spring productivity, showed increases in numbers with abundances reaching 383/10 m² in April 2020 and an even higher 544/10 m² in May 2021, with both months being characterized by high temperature gradients (Table 2). This pattern is indicative of its spawning period, which typically peaks during spring [20]. Similarly, Chelon ramada exhibited high abundances during these months. Other species such as Sardina pilchardus and Spicara smaris displayed increased numbers in the April and May 2021 samplings. This consistency led to the grouping of these specific months in the multivariate statistical analysis, highlighting a stable seasonal pattern in the community structure of ichthyoplankton in the region. The clustering of September 2019 and September 2020 suggests that these months shared similar dynamics, as during September, the marine environment begins to shift from summer to autumn, affecting water temperatures, nutrient dynamics, and species’ behaviors [21]. In September 2019 and September 2020, specific species such as Engraulis encrasicholus showed significant abundances, with counts of 99/10 m² and 299/10 m², respectively. Other species like Gobius spp. [22] and Scorpaena porcus [23] also displayed consistent patterns between these months, with Gobius spp. at 116/10 m² in September 2019 and similar levels in 2020.

These similarities in species abundances are influenced by several factors typical of September in the region [3]. The water temperatures are generally beginning to cool but remain warm enough to support active feeding and growth for many species. Additionally, the post-summer period might still benefit from residual summer productivity, providing sufficient food resources for a diverse range of species. The regular occurrence of similar species abundances during these months of consecutive years likely results in their grouping in the multivariate analysis, demonstrating a consistent ecological pattern driven by the seasonal transition from summer to autumn in the Litochoro marine environment.

These observations underline the critical need for continuous monitoring to adaptively manage ichthyoplankton populations and the broader marine ecosystem. The association between environmental variables and species abundances illustrates how climate change might influence marine biodiversity [24]. Extended monitoring and more detailed spatial analysis are recommended to refine the understanding of the observed patterns. Investigating the genetic diversity within populations, especially for highly abundant and ecologically significant species like Engraulis encrasicholus and Sardina pilchardus, could reveal insights into their resilience and adaptability to environmental variability.

5. Conclusions

This study has described the dynamics between environmental factors and the community structure of ichthyoplankton in the Litochoro area, underscoring the influence of abiotic factors such as chl-a, salinity, and temperature on marine species’ distribution and abundance.

In the coastal region of Litochoro, surface salinity significantly influences the distribution of ichthyoplankton species such as Engraulis encrasicholus, Arnoglossus laterna, and Gobius spp., while average salinity is more critical for Sardina pilchardus and Spicara smaris. These findings suggest that lower freshwater outputs, typically occurring in the summer and autumn, enhance the presence of these species. Conversely, species like Pagellus acarne and Scorpaena porcus thrive with higher river runoffs. Additionally, temperature plays a significant role in the abundance of Scorpaena porcus, showing peak numbers in summer and early autumn, while Spicara smaris exhibits a reverse trend. For Scomber colias, the most significant factor affecting its distribution is the temperature gradient, with greater abundance under conditions of strong thermal stratification. Anchovy, key for indicating spring productivity, significantly increases in abundance during the spring, aligning with its peak spawning period. This pattern underscores the critical influence of temperature gradients during its reproductive timing.

Anchovy, the most abundant species in this study, exhibits a negative correlation with high average chl-a values, indicating that high abundances of anchovy coincide with low average chlorophyll values. Furthermore, most diversity indices display a strong negative correlation with high chl-a values, suggesting that higher concentrations of chl-a may be linked to lower biodiversity. However, it is well documented that fish larvae can only consume phytoplankton indirectly; the phytoplankton must first be eaten by zooplankton, which in turn affects fish populations. In contrast, most diversity indices show a significant positive correlation with surface salinity. This indicates that increased salinity levels may enhance certain aspects of biodiversity during the summer and early autumn months. This pattern has been consistent over multiple years, demonstrating the species’ dependence on stable environmental conditions to sustain its population dynamics.

More stable marine conditions prevail compared to other previously studied regions in the gulf of Thermaikos. The area shows moderate seasonal temperature variations and relatively stable salinity levels. Litochoro’s species composition is consistent, dominated by species like Engraulis encrasicholus, suggesting favorable marine conditions for spawning. Litochoro’s diversity indices suggest a stable and diverse ecosystem. More stable marine conditions in Litochoro support a unique community structure, less influenced by riverine inputs and more by marine stability. This contrast underscores the necessity for region-specific conservation and management strategies that cater to the unique environmental and ecological conditions of each area.

In conclusion, the findings from this study advocate for continued and detailed monitoring of the marine ecosystem in the Litochoro area. Such efforts are vital for understanding the ongoing changes and potential future shifts in ichthyoplankton communities due to environmental pressures, including climate change. Furthermore, understanding the genetic diversity within key species could provide deeper insights into their resilience and adaptive capacities, essential for developing effective management and conservation strategies. This comprehensive approach will help safeguard the ecological and economic viability of these important marine resources.