Aquatic insects represent a large and diverse group derived from various terrestrial ancestors that re-inhabited aquatic environments, comprising about 76,000 species adapted to all types of freshwater habitats (Samways & Deacon 2021). Although most insects are characterized by a subaquatic life cycle, few species spend their entire life submerged in waters. Most aquatic insects undergo an aquatic immature stage followed by a terrestrial adult (e.g. Odonata, Ephemeroptera, Trichoptera, Megaloptera), being considered semiaquatic, associated only with aquatic and semiaquatic vegetation (Bouchard 2004). These organisms are an important component of aquatic (and sometimes terrestrial) food webs, playing an essential role in nutrient cycling processes (Balian et al. 2008). Most of the larval stages are active and passive filter or deposit feeders, representing an intermediate step between microorganisms and fish in the food chain and constituting an important food source for the latter (Rosenberg & Resh 1993). Due to their large biomass, high reproduction rates with short-lived generations and rapid colonization, insect larvae are successfully used in assessing the structure and function of aquatic ecosystems as important tools in ecology (Hershey & Lamberti 2001), genetics (Sivaramakrishnan et al. 2014) and evolutionary studies (Kristensen 1981; Mazzuccoa et al. 2015). Aquatic ecosystems are exposed to multiple anthropogenic pressures that significantly affect their health condition (Buczyńska and & Buczyński 2019; Gómez-Baggethun et al. 2019; Mureșan et al. 2019; Teacă et al. 2019; Begun et al. 2020) due to habitat change, pollution (Davidson et al. 2013) and soil erosion (Broadman 2013). Being highly sensitive to pollution, aquatic insects are frequently used as bioindicators to assess the impact of environmental stressors on lentic and lotic water systems and the water quality (Nasirian & Irvine 2017), as any change in their composition or density indicates a change in the water quality (Varma & Pratap 2006). Compared to fish and plankton, they have a higher ability to tolerate pollution-induced environmental stress (da Rocha et al. 2010; Andem et al. 2012).
Taxonomic assignment of macroinvertebrates at the species level has proven challenging when using a morphology-based identification technique (Barrett & Hebert 2005). Moreover, identification of early life stages of aquatic insects (larvae and nymphs) based on morphological characters is particularly difficult since most of the identification keys are available only for adults. During the last decades, complementary molecular techniques were used based on DNA analysis for accurate identification and uncertainties linked to the morphological approach (Navajas & Fenton 2000). To date, DNA barcoding based on amplification of the mitochondrial cytochrome C oxidase subunit I gene region has been the most frequently used technique for discriminating invertebrate species (Hebert et al. 2003). In addition to morphological identification, which in most cases could only be performed at the family or genus level, DNA barcoding has allowed identification of specimens up to the species level (Baird et al. 2012).
The distribution and abundance of most aquatic insect communities are considered to be affected by several factors such as current velocity, temperature, altitude, season, total suspended solids, availability of food, and the like (Crisci-Bispo et al. 2007). In general, these organisms require sufficient amounts of dissolved oxygen to survive, and this parameter has the potential to limit aquatic insect diversity (Kamsia et al. 2007). Studies have reported that their dispersal is strongly related to water depth (Hasmi et al. 2021), and the occurrence of certain species is correlated with the presence of vegetation (Crisci-Bispo et al. 2007). Furthermore, the nature of the substrate plays an important role in determining the species distribution and the structure of their communities (Ciutti et al. 2004).
Over the last decades, the distribution, ecology and diversity of aquatic insect species populating the Danube River have been the subject of several studies (Graf et al. 2006; Tubić et al. 2013; Farkas et al. 2014; Krno et al. 2018; Navara et al. 2020), including the Danube sector that crosses the Romanian territory (Chiriac 2004; Pavel et al. 2018). Meanwhile, a very limited number of studies have used molecular identification by DNA barcoding based on COI gene fragments of insects collected from terrestrial environments in Romania, not counting a survey of 180 butterflies (Dincă et. al. 2011), and no identification of aquatic insects using genetic methods has been carried out so far.
In this context, the current study aimed to identify insect larvae belonging to seven different species of the following orders: Odonata –
The Lower Sector of the Danube River, between Baziaş (44°48’57”N; 21°23’28”E) and the estuary where the river meets the Black Sea, has a length of 1075 km, including the Danube Delta (Sulina 45°15’74”N; 29°65’92”E). In this section, 10 main tributaries from the territory of Bulgaria and Romania flow into the Danube. The section of the river traversing a plane area (altitude 38–102 m) becomes shallower and broader, with several major islands. In this region, the currents slow down considerably and the water quality is significantly affected by anthropogenic pollution consisting of excessive loads of nutrients, organic material, and hazardous substances (ICPDR 2009). The Sulina channel, a distributary of the Danube with a total length of 71.7 km, begins at a bifurcation of the Tulcea distributary and carries about 20% of the water and suspended sediment discharge of the river (Bondar & Panin 2000). The water along this branch is particularly affected by human activities (agriculture, fish farming, tourism), with frequent discharges of detergents, domestic waste, and oil products, leading to enrichment with dissolved nutrients (Cretescu et al. 2021).
Sampling was carried out in late spring (May 2019, 2020) when the average temperature ranged from 17.2°C to 19.1°C.
Sediment samples were collected along the lower section of the Danube River from km 626 to km 811, including the Sulina branch, during 2019 and 2020 trips (Fig. 1; Table 1). Of the total 41 samples, 27 were collected in the lower Danube section (Fig. 1A), including seven samples from the Corabia area (between km 626 and km 631), eight samples from the Bechet area (from km 674 and km 676.5.5), nine samples from the Pişculeț area (km 760 – km 765), and three samples from the Cetate area (from km 806 and km 811), and 14 samples were obtained from the Sulina branch (Fig. 1B). Samples were collected at different depths, ranging from 2.5 to 17.5 m (Table 2).
Sampling locations in the Lower Danube and density of larvae
Crt. No. | Sites | Coordinates | Number of individuals/m2 | |||||||
---|---|---|---|---|---|---|---|---|---|---|
Lat. (α) | Long. (λ) | |||||||||
1. | * km 811 | 44°4’53.2” | 23°1’48.8” | 0 | 0 | 7.4 | 0 | 0 | ||
2. | ** km 808 | 44°3’49.7” | 23°3’7.4” | 0 | 0 | 0 | 0 | 50.4 | 0 | 0 |
3. | ** km 806 | 44°2’55.3” | 23°2’14.5” | 0 | 0 | 0 | 0 | 226.8 | 0 | 0 |
4. | ** km 765 | 43°48’18.2” | 22°57’34.3” | 0 | 0 | 0 | 0 | 403.2 | 0 | 0 |
5. | 0 | 0 | 0 | 0 | 0 | 25.2 | 0 | |||
6. | ** km 764.5 | 43°48’36.8” | 22°58’12.0” | 0 | 0 | 0 | 0 | 0 | 1008 | 0 |
7. | ** km 764 | 43°48’5.7” | 22°58’35.5” | 0 | 0 | 0 | 0 | 25.2 | 25.2 | 0 |
8. | * km 762.5 | 43°48’37.7” | 22°59’52.7” | 7.4 | 0 | 0 | 0 | 162.8 | 0 | |
9. | * km 762 | 43°47’54.0” | 23°0’2.4” | 0 | 29.6 | 0 | 0 | 0 | 0 | 0 |
10. | 0 | 0 | 0 | 0 | 4388.2 | 7.4 | 0 | |||
11. | * km 761 | 43°48’14.3” | 23°0’54.4” | 0 | 0 | 0 | 0 | 0 | 7.4 | 0 |
12. | ** km 760 | 43°48’9.8” | 23°1’51.1” | 0 | 0 | 0 | 0 | 201.6 | 0 | 0 |
13. | * km 678 | 43°44’40,6” | 23°57’52.9” | 0 | 0 | 7.4 | 0 | 7.4 | 0 | 0 |
14. | * km 676.5 | 43°44’18.0” | 23°58’42.9” | 0 | 0 | 0 | 0 | 96.2 | 0 | 0 |
15. | * km 676 | 43°44’13.0” | 23°59’4.3” | 0 | 0 | 0 | 1813 | 0 | 0 | |
16. | 0 | 0 | 0 | 29.6 | 0 | 0 | 0 | |||
17. | * km 675.5 | 43°44’38,7” | 23°59’42,9” | 0 | 7.4 | 0 | 0 | 7.4 | 7.4 | 0 |
18. | * km 675 | 43°44’5.5” | 23°59’45.1” | 0 | 0 | 7.4 | 0 | 0 | 0 | 0 |
19. | * km 674.5 | 43°44’3.0” | 24°0’8.1” | 0 | 66.6 | 0 | 7.4 | 488.4 | 0 | 0 |
20. | ** km 674 | 43°43’52.9” | 24°0’27.3” | 0 | 0 | 0 | 0 | 25.2 | 0 | 0 |
21. | * km 631 | 43°46’8.3” | 24°29’58.8” | 0 | 96.2 | 0 | 0 | 0 | 0 | 0 |
22. | * km 630 | 43°45’32.0” | 24°30’49.5” | 0 | 429.2 | 14.8 | 0 | 0 | 0 | 0 |
23. | 0 | 0 | 0 | 0 | 1894.4 | 0 | 0 | |||
24. | * km 629 | 43°45’25.4” | 24°31’18.5” | 0 | 0 | 0 | 0 | 7.4 | 0 | 0 |
25. | ** km 627.5 | 43°45’17.2” | 24°32’34.2” | 0 | 25.2 | 0 | 0 | 252 | 0 | 0 |
26. | ** km 626.5 | 43°45’46.6” | 24°33’30.4” | 0 | 0 | 0 | 0 | 100.8 | 0 | 0 |
27. | * km 626 | 43°45’37.5” | 24°33’48.9” | 29.6 | 7.4 | 0 | 0 | 310.8 | 0 | 0 |
28. | * km 108(a) Ceatal Sf. Gheorghe | 45°11’04.9” | 28°53’26.7” | 0 | 0 | 0 | 0 | 214.6 | 0 | 0 |
29. | * km 108(b) Ceatal Sf. Ghoerghe | 45°11’04.39” | 28°53’26.7” | 0 | 0 | 0 | 0 | 7.4 | 0 | 0 |
30. | * NM 33 Sulina branch | 45°11’22.8” | 28°55’22.3” | 0 | 0 | 0 | 0 | 74 | 0 | 0 |
31. | * NM 24 (a) Sulina branch | 45°10’28.5” | 29°03’19.4” | 0 | 0 | 0 | 0 | 384.8 | 0 | 0 |
32. | * NM 24 (b) Sulina branch | 45°10’29.9” | 29°03’19.3” | 0 | 0 | 0 | 0 | 629 | 0 | 0 |
33. | * NM 21 Sulina channel | 45010’54.2” | 29°10’19.1” | 0 | 0 | 0 | 0 | 1420.8 | 0 | 0 |
34. | * NM 16 Sulina branch | 45°10’33.3” | 29°19’05.5” | 0 | 0 | 0 | 0 | 651.2 | 0 | 0 |
35. | * NM 14 (a) Sulina branch | 45°10’33.9” | 29°21’34.8” | 0 | 0 | 0 | 0 | 370 | 0 | 0 |
36. | * NM14 (b) Sulina branch | 45°10’32.4” | 29°21’17.0” | 0 | 0 | 0 | 0 | 1206.2 | 0 | 0 |
37. | * NM 14 (c) Sulina branch (Crisan) | 45°10’30.9” | 29°21’39.6” | 0 | 0 | 0 | 0 | 518 | 0 | 0 |
38. | * Old Danube (Meander) | 45°10’41.4” | 29°21’05.1” | 0 | 0 | 0 | 0 | 0 | 7.4 | 0 |
39. | * NM 8 (a) Sulina branch | 45°10’20.3” | 29°28’47.6” | 0 | 0 | 0 | 0 | 148 | 0 | 0 |
40. | * NM 8 (b) Sulina branch | 45°10’39.4” | 29°28’33.2” | 0 | 0 | 0 | 0 | 0 | 0 | 14.8 |
41. | * NM 2 Sulina branch | 45°09’39.6” | 29°36’31.6” | 0 | 0 | 0 | 0 | 296 | 0 | 0 |
Year of sampling, depth, substrate type, dissolved oxygen and presence of macrophytes
Crt. No. | Sites | Year of sampling | Depth (m) | Type of substrate | Dissolved oxygen mg/L | Macrophytes presence (+/-) | |
---|---|---|---|---|---|---|---|
Mean values/area | Value/site | ||||||
Corabia area | 8.58 | ||||||
1. | km 626 | 2019 | 3.0 | sand | 8.90 | - | |
2. | km 626.5 | 2020 | 7.3 | gravelly sand | 8.10 | - | |
3. | km 627.5 | 2020 | 5.0 | sand | 8.81 | - | |
4. | km 629 | 2019 | 9.2 | gravelly sand | 8.82 | - | |
5. | km 630 | 2019 | 8.2 | gravelly sand | 8.04 | + | |
2020 | 8.67 | ||||||
6. | km 631 | 2019 | 5.3 | sand | 8.77 | - | |
Bechet area | 8.77 | ||||||
7. | km 674 | 2019 | 3.3 | sand | 8.75 | - | |
8. | km 674.5 | 2019 | 3.2 | sand | 8.75 | + | |
9. | km 675 | 2019 | 4.0 | sand | 8.67 | - | |
10. | km 675.5 | 2019 | 6.3 | sand | 8.67 | + | |
11. | km 676 | 2019 | 3.7 | gravelly sand | 9.31 | + | |
2020 | 8.10 | ||||||
12. | km 676.5 | 2020 | 3.0 | sand | 8.15 | - | |
13. | km 678 | 2019 | 5.9 | sand | 9.78 | + | |
Pisculeţ area | 8.85 | ||||||
14. | km 760 | 2019 | 3.9 | sand | 9.36 | - | |
15. | km 761 | 2019 | 4.2 | sand | 9.61 | + | |
16. | km 762 | 2019 | 5.0 | sand | 8.95 | + | |
2020 | 8.99 | ||||||
17. | km 762.5 | 2019 | 4.8 | gravelly sand | 8.96 | - | |
18. | km 764 | 2019 | 3.5 | sand | 8.55 | + | |
19. | km 764.5 | 2019 | 4.9 | sand | 8.55 | + | |
20. | km 765 | 2019 | 2.8 | gravelly sand | 8.38 | + | |
2020 | 8.31 | ||||||
Cetate area | 7.80 | ||||||
21. | km 806 | 2019 | 3.8 | gravelly sand | 8.13 | - | |
22. | km 808 | 2019 | 5.0 | sand | 7.25 | - | |
23. | km 811 | 2019 | 7.8 | gravelly sand | 8.02 | - | |
Sulina area | 8.25 | ||||||
24. | Old Danube meander | 2019 | 5.0 | sandy mud | 7.04 | - | |
25. | NM 24(a) Sulina branch | 2019 | 16.5 | sand | 7.93 | - | |
26. | NM 16 Sulina branch | 2019 | 5.2 | muddy sandy gravel | 7.90 | - | |
27. | NM 8(a) Sulina branch | 2019 | 14.4 | sandy mud | 7.95 | - | |
28. | NM 2 Sulina branch | 2019 | 17.5 | gravelly mud | 7.96 | - | |
29. | NM 33 Sulina branch | 2019 | 12.5 | gravelly mud | 9.38 | - | |
30. | NM 24(b) Sulina branch | 2019 | 12.5 | sand | 9.01 | - | |
31. | NM 14(b) Sulina branch | 2019 | 13.5 | sandy mud | 9.55 | - | |
32. | NM 8(b) Sulina branch (Meander) | 2019 | 4.3 | sandy mud | 9.07 | - | |
33. | NM 14(c) Sulina branch (Crisan) | 2019 | 11.5 | sand | 7.95 | - | |
34. | NM 14(a) Sulina branch (Crisan) | 2019 | 10.7 | gravelly mud | 7.95 | - | |
35. | NM 21 Sulina channel | 2019 | 6.5 | sandy mud | 7.97 | - | |
36. | Km 108(a) Ceatal Sf. Gheorghe | 2019 | 6.4 | sandy mud | 7.97 | - | |
37. | Km 108(b) Ceatal Sf. Gheorghe | 2019 | 6.4 | gravelly mud | 7.97 | - |
NM – nautical miles
The sediments were sampled using two different Van Veen seabed sediment grabs with a surface of 0.039 m2 (small) and 0.135 m2 (large), respectively. The number of individuals collected per unit surface (1 m2) was calculated based on their number contained in each sample, using a multiplication factor of 25.2 for the small Van Veen grab, and 7.4 for the large Van Veen grab (SR EN ISO 10870:2012).
Insect larvae samples were washed immediately after collection using 250 and 125 μm mesh sieves to remove excess sediment particles and preserve macrofauna. Each specimen was washed with sterile water and preserved in 200 μl Tris-EDTA pH 8 buffer at −20°C for genetic identification (Ross et al. 1990). For morphological identification, a mixed solution of Rose Bengal and 4% buffered formaldehyde was used for sample preservation (SR EN ISO 5661-1:2008).
Statistical analysis of insect larvae populations was performed by calculating the univariate index (density as ind. m−2).
Granulometric analysis of sediment samples was performed using a Mastersizer 2000E Ver 5.20 Malvern diffractometer (Malvern Instrument Ltd). Grain size classes (sand, silt, clay) and fractions within each class were determined according to the Udden–Wentworth logarithmic scale. Sediment classification was carried out based on the Folk diagram (Folk 1954).
The dissolved oxygen content in each water sample was measured in situ using an oximeter Oxi 320/Set (WTW Germany).
Taxonomic identification was performed by examining the morphological characters of different body parts (antennae, head, thorax, abdomen, annal region, caudal cerci, external gills, legs) according to the identification keys provided by Heidemann & Seidenbusch (2002) for Odonata, Hickin (1967), Lecureuil et al. (1983), Wallace et al. (2003) for Trichoptera, Baurenfeind & Soldán (2012) for Ephemeroptera, Vallenduuk & Cuppen (2004) for Lepidoptera and Kaiser (1977) for Megaloptera, using a SteREO Discovery V8 (Carl Zeiss) microscope and an Axiostar (Carl Zeiss) microscope.
Total genomic DNA was extracted using the DNeasy Blood & Tissue Kit (Qiagen), following an optimized protocol that includes an initial stage of cell disruption (Iancu et al. 2015). Organisms introduced into Tris-EDTA pH 8 buffer were homogenized for 12 min at 20°C, 50 Hz, in a SpeedMill PLUS Cell Homogenizer (Analitik Jena, Germany) in the presence of 5 ZR BashingBead lysis matrix 0.2 mm (Zymo Research), and then processed following the manufacturer’s instructions.
Genetic identification of insect larvae was performed by DNA barcoding. Fragments of the mitochondrial COI gene were PCR amplified using the Mastercycler ProS System (Eppendorf, Austria). The PCR mixture contained 50 ng/μ genomic DNA, 1 x Taq buffer of 2.5 mM MgCl2 (ThermoFisher Scientific), 0.1 mM dNTP (ThermoFisher Scientific), 1 x BSA (New England Biolab), 1 unit of Taq DNA polymerase (ThermoFisher Scientific) and 10 pmol/μl of COI invertebrate universal forward (LCO1490: 5’-GGTCAACAAATCAAA-GATATTGG-3’) and reverse (HCO2198: 5’-TAAACTTCAGGGTGAC-CAAAAAATCA-3’) primers (Folmer et al. 1994) in a 50 μl final volume. The reaction was conducted for an initial denaturation step for 2 min at 95°C, followed by 5 cycles of 30 s at 94°C, 1.5 min at 45°C and 1 min at 72°C, 35 cycles of 30 s at 94°C, 1.5 min at 50°C, 1 min at 72°C, with a final extension step of 5 min at 72°C. Each PCR reaction contained a negative control without insect DNA. The PCR products were analyzed on 1% agarose gel (Cleaver Scientific, Ltd, England) by electrophoresis and amplicons were visualized via a UV transilluminator (Syngene International Ltd.). Further, the PCR products were purified with the QIAquick PCR Purification Kit (Qiagen) and sequenced on both strands (Macrogen, the Netherlands).
Nucleotide sequences were analyzed using Sequence Assembly and Alignment – CodonCode Aligner Software (CodonCode Corporation 2003). Sequence identification was performed using the BLAST-NCBI platform (
The identified insect larvae COI sequences were deposited in GenBank under accession numbers [MW139674] for
Considering the varying grain size of the studied sediments along the Danube River sections (Opreanu et al. 2007; Tiron & Provansal 2010; Dutu et al. 2018; Tiron Dutu et al. 2019), the presence of identified insect larvae was correlated with the substrate type, including sand, gravelly sand, muddy sandy gravel, gravelly mud, and sandy mud sediments (Table 1). All analyzed species were found in sandy and gravelly sandy substrates, except for
Association of insect larvae with different types of substrate
Insect species | Order | Type of substrate | ||||
---|---|---|---|---|---|---|
Sand | Gravelly sand | Muddy sandy gravel | Gravelly mud | Sandy mud | ||
Odonata | + | + | - | - | - | |
+ | + | - | - | - | ||
+ | + | - | - | + | ||
Trichoptera | + | + | + | + | + | |
Ephemeroptera | + | + | - | - | - | |
Lepidoptera | + | + | - | - | - | |
Megaloptera | - | - | - | - | + |
(+) presence; (−) absence of insect larvae
The water depth in the study area ranged from 2.8 m to 17.5 m (Table 2), depending on the sampling location. Thus, all the investigated species were present in the bathymetric range of 2.8–5 m. However, only
No major differences in dissolved oxygen concentrations were observed between the surveyed areas, with mean values ranging from 7.80 mg l−1 (Cetate) to 8.85 mg l−1 (Bechet; Table 2). In general, the obtained values indicate relatively unpolluted waters conducive to the development of larvae belonging to these taxonomic orders of insects (Jacob et al. 1984).
Macrophytes, represented by submerged plants (
Genetic identification of isolated insect larvae from all locations along the lower Danube section (Table 4) was based on sequence identity of the COI amplicon using a 97% threshold for BLAST sequence screening of the NCBI GenBank database (Hebert et al. 2003). All specimens belonging to
Best match COI gene sequence of insect larvae species from the Danube River
Insect species | Identity (%) | Cover (%) | GenBank reference |
---|---|---|---|
99.84 | 100.00 | MT298455.1 | |
99.36 | 98.00 | MT298633.1 | |
99.83 | 99.00 | KX143573.1 | |
100.00 | 98.00 | KX104210.1 | |
99.84 | 98.00 | KY262534.1 | |
98.66 | 97.00 | LR135742.1 | |
98.41 | 97.00 | JX438311.1 |
In addition to molecular identification, all collected larvae species were morphologically confirmed (data not shown).
The presence and density of the seven insect species along the Danube sections showed a varying profile in relation to the type of sediment in the two consecutive years (Figs 2 & 3; Tables 1 & 2).
In 2019,
Larvae of
In 2019, larvae of
Larvae of
Due to their sensitivity to several abiotic and biotic factors, immature stages of aquatic insects are particularly useful for monitoring the water quality in freshwater ecosystems (Arimoro & Ikomi 2008; Barman & Gupta 2015). As such, our study addressed the identification and distribution of several biological indicators in the Danube section that crosses the Romanian territory to highlight their presence at different depths and in different substrates.
In Romania, the first detailed taxonomic, biological, and ecological studies of Odonata were performed by Cîrdei & Bulimar (1969), and by Bulimar (1973, 1976, 1993). Odonata larvae were used as bioindicators of anthropogenic disturbances, as shown for
Another cosmopolitan species recorded during our survey was
Larvae of the caddisfly
Furthermore, the reported eurybathic character of this species (Savić et al. 2013) appeared to be consistent with our findings that identified an abundant population in both shallow (< 5 m) and deep (> 10 m) Danube locations, suggesting that depth variation is not a limiting factor for its distribution.
So far, the eurybiontic mayfly
The herbivorous caterpillar
The alderfly
The dissolved oxygen content in water appeared to be one of the most important environmental factors for the survival, development, and reproduction of aquatic insects, which generally require high concentrations of dissolved oxygen to complete their life cycle (Hossain et al. 2015; Prommi & Payakka 2015). In our study, relatively high concentrations of dissolved oxygen were recorded in all analyzed Danube areas. Despite this, only
Given the importance of these organisms as biological indicators, their accurate taxonomic identification is essential. Thereby, DNA barcoding was used during our survey as the main method for taxonomic identification of species, being a successfully applied technique in biodiversity assessment studies (Cordero et al. 2017). The morphological investigation of larvae failed to identify the taxonomic characters of
The current data, advancing the knowledge about the spatial distribution and abundance of Odonata, Trichoptera, Ephemeroptera, Lepidoptera and Megaloptera larvae in the lower Danube River, provide a novel insight into their role as freshwater biological indicators. Aquatic insects are among the most sensitive organisms to changes in environmental conditions, therefore further research should be undertaken to assess their ecological role in relation to various environmental parameters that may affect their distribution.