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Article

Diatom Diversity and Its Environmental Drivers in Lakes of King George (62° S) and Horseshoe Islands (67° S) in the Maritime Antarctic

by
Hilal Cura
*,† and
Nazlı Olgun
Eurasia Institute of Earth Sciences, Istanbul Technical University, Maslak, 34469 Istanbul, Turkey
*
Author to whom correspondence should be addressed.
†
Present address: Institute of Marine Sciences, Middle East Technical University, Erdemli, 33731 Mersin, Turkey.
Diversity 2026, 18(2), 114; https://doi.org/10.3390/d18020114
Submission received: 1 December 2025 / Revised: 7 February 2026 / Accepted: 9 February 2026 / Published: 10 February 2026
(This article belongs to the Special Issue Diversity and Ecology of Freshwater Plankton)
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Abstract

Diatoms are key primary producers and sensitive indicators in polar freshwater ecosystems, responding to environmental change. This study investigates diatom species richness and the influence of environmental variables in fourteen coastal lakes on King George and Horseshoe Islands in the Maritime Antarctic. Water and surface sediment samples collected in 2017, 2019, and 2020 were analyzed using light and scanning electron microscopy, revealing 83 taxa (species and genera combined) across all lakes except one. King George Island exhibited higher species richness, with frequent occurrences of Planothidium lanceolatum, Fragilaria cf. capucina and Nitzschia cf. homburgiensis. On Horseshoe Island, common taxa included Achnanthes, Achnanthidium, Fragilaria, Nitzschia, Navicula, and Gomphonema. Among the previously measured water chemistry variables, HCO3− (ρ = 0.78, p = 0.005) and K+ (ρ = 0.69, p = 0.019) showed the strongest positive correlations with diatom species richness. Major ions and nutrients, as well as dissolved oxygen, salinity, and pH, exhibited moderate relationships. In contrast, temperature and trace metals displayed weak or negligible correlations, suggesting indirect influences on diatom diversity. These findings demonstrate that diatom communities in the Maritime Antarctic lakes are diverse and are shaped by variations in water chemistry, underscoring the ecological sensitivity of these freshwater ecosystems.

1. Introduction

Diatoms (Bacillariophyta) are a major group of microalgae in aquatic systems, dominating the water columns of rivers and oceans. As primary producers, diatoms are responsible for approximately 25% of global and 50% of marine primary production, which exceeds the amount of oxygen produced by all rainforests [1]. Through this production, diatoms contribute to carbon fixation, accounting for around 45% of marine CO2 fixation [2]. Moreover, diatoms provide a major dietary source for aquatic feeders, thereby representing a key component of aquatic food webs, particularly in Antarctic polar regions. Considering this key role, the identification of diatoms in Antarctic lakes is important for understanding how these communities will respond to extreme conditions and multiple stressors such as warming, climate change and human-caused pressures [3].
In Antarctica, diatoms are a dominant group of primary producers in lakes, ponds, and coastal waters. Freshwater diatom communities are particularly important because lakes respond rapidly to environmental change and catchment processes. Diatom productivity in these systems plays a key role in regulating atmospheric carbon and methane, acting as a net carbon sink on an annual basis [4]. At the same time, strong spatial variability in microbial communities among nearby lakes indicates that local environmental conditions strongly influence community composition [5].
Diatom distribution in Antarctic freshwater systems is controlled mainly by temperature, salinity, pH, and nutrient availability [3,6,7,8]. Temperature is a particularly important factor in cold regions, as it directly affects metabolic rates, growth, and species survival [6,8]. Changes in temperature and salinity have been shown to influence both the distribution and biochemical properties of certain species, including Nitzschia lecointei [6,8]. In addition, atmospheric inputs, sea spray, proximity to glaciers, and ornithogenic activity from penguins and other birds can alter water chemistry and further shape diatom communities [9].
Trace metals also play a critical role in diatom ecology as cofactors in many metabolic reactions, particularly by influencing growth rates [10]. Elements such as manganese (Mn) and iron (Fe) are essential for photosynthesis and detoxification mechanisms, while molybdenum (Mo) is important for nitrogen cycling [11,12,13]. Other metals, including cobalt (Co), copper (Cu), and zinc (Zn2+), act as enzyme cofactors and affect growth and metabolism [14]. In many polar regions, metal bioavailability, especially that of Fe, can be a limiting factor for primary production [15].
In addition to trace metals, macronutrients and major ions are required for many biological functions of diatoms [7,9]. For instance, diatoms require silica (Si) for cell wall formation, nitrogen (N) and phosphorus (P) for biochemical synthesis, and sodium (Na+) for cell division. Other ions, including calcium (Ca2+), magnesium (Mg2+), sulfate (SO42−), nitrate (NO3−, as a major inorganic nitrogen source), potassium (K+), and bicarbonate (HCO3−), are also important for physiological processes [7]. Recent studies have shown that chlorophyll-a (Chl-a) concentrations in the Maritime Antarctic are strongly correlated with ammonium (NH4+) and NO3−, emphasizing the importance of local water chemistry for phytoplankton productivity [9].
Despite rapid climate change, experimental studies have shown that some Antarctic benthic diatoms can tolerate fluctuations in temperature, salinity, and light levels beyond those experienced in their natural environments, suggesting a high degree of flexibility in coping with environmental change [6]. Together, these studies indicate that Antarctic diatoms are strongly influenced by environmental variability [3], yet they also exhibit plasticity that allows them to cope with ongoing and potential future stressors.
According to documented warming trends and reductions in ice-cover duration, climate change is already affecting the Antarctic Peninsula [16,17]. These changes are expected to alter ecosystem processes, nutrient and ion inputs, and, consequently, lake water chemistry and diatom community composition [3]. However, despite numerous studies on Antarctic microbial ecology, our knowledge of freshwater diatom diversity remains incomplete, particularly in less-studied regions. Although several new diatom species have been identified over the past few decades using morphological and molecular approaches [18,19,20,21], available records remain limited. Continuous monitoring is therefore required to better understand the effects of climate change on diatom diversity.
While molecular approaches such as metabarcoding are increasingly applied to improve taxonomic knowledge [19,22,23], challenges remain regarding deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) preservation during remote field expeditions and subsequent laboratory procedures. Consequently, morphological identification by light microscopy (LM) and scanning electron microscopy (SEM) remains a robust and widely applicable approach for the characterization of diatom communities in harsh and remote Antarctic environments.
In this study, we examined diatom species composition in lakes and ponds on King George Island (62° S, South Shetland Islands) and Horseshoe Island (67° S), located further south along the Antarctic Peninsula. Using LM and SEM observations, we described diatom distribution and species richness (the number of taxa identified per site) and discussed how physicochemical parameters, nutrients, major ions, and trace metals influence diatom variability across sampling sites.

2. Materials and Methods

2.1. Study Site

The study was conducted on King George Island (one of the South Shetland Islands) and Horseshoe Island, Antarctica. Samples were collected from nine lakes (L1–L6, HS1, HS2, SK), three ponds (P1–P3), and two organic ponds (OP1, OP2) (Figure 1).
King George Island (62°02′ S, 58°21′ W) lies at the northern end of the South Shetland Islands (Figure 1). The island is ~95 km long and ~25 km wide (1150 km2), and about 92% of its surface is ice-covered (including Collins Glacier in the west) [24]; terrestrial vegetation is limited to lichens and mosses [25]. Fildes Peninsula, in the island’s southwest, is ~7 km long with an average elevation of ~30 m and, together with Ardley Peninsula, forms Antarctica’s second-largest ice-free area (~30 km2) [26]. Four research stations (Great Wall, Escudero, Bellingshausen, Artigas), together with summer airport operations, make it a key logistics hub. The peninsula undergoes ~120–122 annual freeze–thaw cycles, and summer hydrology is controlled by snow and ice melt and glacial runoff [24].
Ardley Peninsula is ~1.9 × 1.5 km and is connected to Fildes Peninsula by a ~30 m-thick sand barrier that can be submerged at high tide; hence, “Ardley Island” also appears in the literature (Figure 1) [9]. Ardley is a major bird breeding site and an Antarctic Specially Protected Area (ASPA); it has no permanent station, but Chile operates two seasonal camps (Ripamonti I–II). Ice-free zones host small summer streams and lakes fed by meltwater.
King George Island is influenced by both subpolar and marine climates; therefore, it is particularly sensitive to climate change, with a warming rate of about 0.19 °C per decade and an estimated reduction of about 7% in glacial cover since 1956 [17,27]. Mean annual air temperatures increased from −3.6 °C in 1948–1950 to −2.0 °C in 1991–2010 [16]. The geology is dominated mainly by volcanic and pyroclastic rocks, such as basalt and basalt-andesitic lavas [9,25,28].
The second study region, Horseshoe Island, is the third-largest island in the Marguerite Bay archipelago, with a total surface area of ~60 km2, of which about 66% is covered by glaciers (glacial and periglacial landforms), semi-permanent ice, and snow (Figure 1) [29]. The island has a dry maritime climate, with mean annual air temperatures ranging from −4.3 °C to −4.6 °C between 1977 and 2015 [29,30]. Its geology is dominated mainly by felsic and mafic igneous rocks, as well as volcanic rocks [31].
In both regions, lake geochemistry is influenced by river inflow, local geology, ornithogenic activity, atmospheric inputs, and sea-salt aerosols, particularly during the ice-free period [9].

2.2. Sampling

Sampling was conducted during three field campaigns: the first in February-March 2017, the second in January 2019 on King George Island, and the third in February 2020 on Horseshoe Island (Table 1).
At several lakes, standardized epilithic sampling by stone brushing was not feasible due to the limited availability of suitable rocky substrates or restricted accessibility along steep lake margins (e.g., Uruguay Lake). Consequently, surface sediments represented the only consistently accessible substrate across all study sites. Sediment samples were therefore collected to characterize sediment-associated (benthic and near-bottom) diatom assemblages.
Sediment samples were collected from a single location at the center of Lake Kitiesh (L2) on King George Island (12 m water depth) using a small boat (Figure 1c). Surface sediments were taken using a sediment grab. Due to harsh weather conditions, sediment sampling from the remaining lakes and ponds was conducted at a single littoral zone in shallow water (approximately 5–10 cm water depth). Only the uppermost sediment layer was retrieved, without brushing of hard substrates; therefore, these samples are enriched in benthic diatom assemblages and reflect local benthic communities rather than epilithic or periphytic biofilms. No sediment sample was collected from Lake Uruguay (L1). All sediment samples (approximately 50–70 g wet weight per site) were stored in sterile plastic bags and kept at 4 °C until analysis.
Water samples for qualitative diatom assessment were collected using a 2.2 L Van Dorn water sampler at Lake Kitiesh (L2), while in the remaining lakes and ponds, water samples were retrieved manually from the surface due to shallow depth and ice conditions. For light microscopy, 100 mL of each water sample was preserved with 1 mL of Merck® Lugol’s iodine solution. The samples were then covered with aluminum foil to protect them from light and stored at 4 °C until analysis.
Water parameters, including pH, dissolved oxygen (DO), temperature, conductivity, salinity, and total dissolved solids (TDS), were measured in six lakes and five ponds on King George Island in 2017 using a multiparameter probe (HI 9828, Hanna Instruments Inc., Woonsocket, RI, USA) (Table 2). Chl-a concentrations were measured using ultraviolet–visible (UV-Vis) spectrophotometry (UV-mini1240, Shimadzu Corporation, Kyoto, Japan) at the Chilean Escudero Station (Table 2) [4]. Oxidation-reduction potentials (ORP) of five of these lakes on King George Island were measured in 2019 (Table 2). The measured parameters were not identical for each lake or each year, as samplings was conducted during different campaigns. The indicated metal, nutrient, and ion concentrations in Table 2 are based on ion chromatography and inductively coupled plasma mass spectrometry (ICP-MS) data obtained in a previous study [9].

2.3. Morphological Analyses with LM and SEM

Diatom identification was conducted on uncleaned material using standard morphological features observed under LM and SEM [32]. All taxonomic assignments were based on standard diatom floras and comparative morphology from freshwater and polar diatom studies [19,32,33,34,35,36,37,38,39], complemented by online taxonomic databases and taxonomic revisions [20,40,41,42,43]. Although chemical cleaning with hydrogen peroxide or hydrochloric acid is commonly applied to improve frustule visibility and taxonomic resolution, this step could not be performed due to limited sample volume and the unavailability of additional material for reprocessing. As repeat sampling from the Antarctic sites was not feasible, further subdivision or re-cleaning of the samples was not possible. To reduce potential taxonomic uncertainty, identifications were carried out conservatively, and specimens lacking clearly visible diagnostic features were identified at the genus level or using open nomenclature (e.g., cf., aff.).
For LM analysis, both water and sediment samples were examined. Sediment samples were prepared by diluting one gram of bulk wet sediment in 50 mL of distilled water, followed by vortexing (Vortex ZX Classic, VELP Scientifica, Usmate Velate, Italy) for 45 s at 1600 rpm to homogenize the suspension after dilution and to disaggregate sediment particles. Prepared slides were covered with Merck® immersion oil and examined under a 100× objective lens using an Ivymen System light microscope (Ivymen System, Madrid, Spain) equipped with a Plan-Apochromat 100× immersion objective (Carl Zeiss Microscopy GmbH, Jena, Germany). Images were captured using a Canon EOS 500D digital camera with Canon EOS Utility software (Canon Inc., Tokyo, Japan).
For SEM analysis, the same dilution and vortexing procedures were applied to sediment samples. The sediment suspension was then filtered through a polycarbonate filter with a 0.22 µm pore size (Whatman®, Cytiva, Marlborough, MA, USA). Filters were placed in Petri dishes and dried for five hours in an incubator at 70 °C before SEM examination. A small portion of each filter (approximately 1 cm2) was cut, mounted on aluminum stubs, and coated with gold. SEM analyses were conducted using a scanning electron microscope (EVO 10, Carl Zeiss Microscopy GmbH, Jena, Germany).
For Lake Uruguay (L1), the filter sample collected in 2019 was used for diatom analysis, as no sediment samples were available from this lake. Surface water was filtered through Whatman® polycarbonate (PC) filters with a 0.22 µm pore size until the filter became clogged (approximately 2370 mL of water), and the filters were stored at 4 °C until analysis.
To compare diatom assemblages among the thirteen coastal lakes (excluding L5) on King George and Horseshoe Islands, the Sørensen similarity index was calculated based on presence–absence data of identified taxa (Table S1). A hierarchical cluster analysis was performed using the Unweighted Pair Group Method with Arithmetic Mean (UPGMA), based on a distance matrix calculated as “1 -Sørensen similarity” (Table S2). All statistical analyses and visualizations were conducted in Python (version 3.13) using the SciPy (version 1.16.3) and Matplotlib (version 3.10.7) libraries.

3. Results

A total of 83 taxa (including both species and genera) were identified on King George and Horseshoe Islands, rather than an equal number of species and genera. The qualitative distribution of diatoms in each lake is summarized in Supplementary Table S1. The most frequently observed taxa across the studied lakes were Planothidium lanceolatum, Fragilaria cf. capucina, Nitzschia cf. homburgiensis, Achnanthidium dolomiticum, Planothidium delicatulum, Pinnularia brebissonii, and Craticula cf. pseudocitrus (Figure 2). Representative LM and SEM images illustrating the morphology of the recorded diatoms and their morphological similarities are presented in Figure 3 and Figure 4.
Sørensen similarity analysis showed generally low to moderate similarity in diatom composition among lakes (Figure 3 and Table S2). According to the dendrogram, Horseshoe Island sites (HS1 and HS2) and OP2 clustered separately from King George Island sites, while SK formed a distinct branch (Figure 3).
Diatom valve sizes varied, ranging from approximately 10–40 μm in length and 2–15 μm in width. Pinnularia divergens and Achnanthes sp. were among the larger taxa encountered, reaching up to ~40 μm in length (Figure 4, pic. 1 and 43). In contrast, Achnanthidium dolomiticum and Diadesmis sp. were among the smallest taxa, with valve lengths of about 10 μm in length (Figure 4, pic. 19 and 39). Most identified taxa were pennate diatoms, with only a few centric diatoms recorded in L1 and L6 on the Fildes Peninsula and in OP2 on Ardley Island (Figure 4, pic. 84).
The most diatom-rich sites were L4 (30 taxa), OP2 (26 taxa), and L6 (26 taxa) on King George Island. Only a few diatoms were recorded in L1 (four taxa) on the Fildes Peninsula, due to the absence of sediment samples from this lake (Table S1). Lakes on Horseshoe Island also showed low diatom species richness, with a maximum of four taxa in HS2 (Table S1). Interestingly, no diatoms were detected in L5 (West Lake) on the Fildes Peninsula, King George Island, in either water or sediment samples.
The correlations between diatom species richness and environmental parameters exhibited weak to strong positive relationships, with sample size varying among parameters (n = 4–14). HCO3− (Spearman ρ = 0.78, p = 0.005) and K+ (Spearman ρ = 0.69, p = 0.019) showed strong and statistically significant positive correlations with diatom species richness, while DO (Spearman ρ = 0.56, p = 0.039) exhibited a moderate but significant positive relationship (Figure 5). Most parameters, including salinity, TDS, Na+, Ca2+, Mg2+, SO42−, NO3−, and Si, showed moderate positive but non-significant correlations (Figure 5). Conversely, temperature, Fe, Co, and Zn2+ exhibited weak or negligible correlations with species richness (Figure 5).

4. Discussion

All of the studied maritime Antarctic lakes contained diatoms, except for Lake L5 on King George Island (Table S1). Most of the identified species matched those previously reported from King George Island, including Pinnularia cf. subantarctica, Pinnularia cf. borealis, Planothidium lanceolatum, Fragilaria cf. capucina, and Nitzschia capitellata [37,38,39]. Microscopic analyses revealed that lakes on King George Island contained higher numbers of diatom species than those on Horseshoe Island, which lies about 600 km farther south (Table S1).
Interestingly, diatom species richness varied significantly among lakes located in close proximity (Figure 1, Table S1). For example, only four diatom species were recorded in Lake Uruguay (L1), whereas Lake Langer (L4), Lake Yanou (L6), and the organic pond OP2 contained 30, 26, and 26 species, respectively (Table S1). Lower species numbers were observed in the ponds P1, P2, P3 and OP1, with 19, 22, 23, and 18 species, respectively (Table S1). Lake Kitiesh (L2) and Lake L3 also had similar diversity, with 19 and 13 species, respectively (Table S1).
In contrast, only a few diatoms were detected in samples from HS1, HS2, and SK on Horseshoe Island (Table S1). The diatom genera identified in Skua Lake were Gomphonema sp., Navicula sp., and Nitzschia sp. (Table S1). These results are consistent with a previous study on sediment cores from Skua Lake, except for the absence of Pleurosigma/Gyrosigma spp. [36]. The lack of Pleurosigma/Gyrosigma spp. in our samples may be related either to the absence of these species or to the limited number of sampling sites, as only one location was considered in each lake. Additionally, Horseshoe Island is characterized by abundant glacial and periglacial landforms, which is consistent with the low temperature measurements observed in this study (Table 2) [29]. Diatom stratigraphy in Skua Lake showed a marine-brackish-freshwater transition over the past 10,000 years [36]. Pigment concentrations, including Chl-a, in Skua Lake were previously associated with the intensity of marine influence and lower latitude location, as well as the potential effect of nutrient transport via faunal activity [36].
The difference in diatom species richness between the two studied islands may be related to the considerably lower temperatures in Horseshoe Island samples (maximum 2.8 °C; Table 2), as King George Island is more strongly influenced by climate change according to regional temperature trends [16,30]. As a consequence of rising temperatures, the annual duration of ice cover is expected to decrease on both islands, leading to increased leaching of elements from soils and enhanced input of nutrients such as N, P, Si, and Fe into the lakes [9].
Similarly, factors such as sea spray inputs and storms impact dissolved solids, conductivity, and pH in lake waters; accordingly, L2, L4 (which has a connection to seawater), and OP2 had higher conductivity values (Table 2) [44]. In addition, lakes near glaciers, such as L1, may be exposed to elevated sediment turbidity, which can have negative effects on planktonic communities and may explain the low primary production observed in L1 [9]. Finally, penguin droppings and seabird guano provide nutrient inputs such as nitrate and nitrite, thereby enhancing phytoplankton growth and, consequently, diatom species richness in these lakes [9].
Sørensen similarity analysis revealed generally low to moderate similarity in diatom composition among lakes, with Sørensen index values ranging from 0.09 to 0.53 (Figure 3 and Table S2). Relatively high similarities were observed between sites OP1 and OP2 (0.53), as well as between L1 and HS2 (0.50), indicating a considerable overlap in species composition. Hierarchical clustering based on Sørensen similarity showed a clear separation between King George Island and Horseshoe Island sites (Figure 3). Despite its high similarity to OP1, OP2 occupied a distinct position in the dendrogram, likely reflecting its location on Ardley Island (Figure 3). Both the dendrogram and Sørensen similarity values indicated that SK exhibited a distinct diatom pattern compared to all other sites (Figure 3 and Table S2).
In the sediment sample from Lake Kitiesh (L2), an unidentified species with globular features, consisting of layers of circles, was recognized (Figure 4, pic. 96). This organism resembled a Coccolithophore sp. but lacked the characteristic diagnostic features, such as the central area and surrounding rim typical of the coccolithophore genus [45]. Similarly, non-phytoplankton forms with an elliptical shape, a mouth-like aperture, and globular features identical to those of the unidentified species were found in samples from Lakes Uruguay (L1) and Yanou (L6) on King George Island (Figure 4, pic. 97). These findings suggest that acid treatments could influence microstructural characteristics; therefore, alternative preparation methods might be beneficial for samples collected from such remote regions.
The relationship between diatom species richness and key physicochemical parameters was explored to identify potential environmental drivers of community structure (Figure 5). Sample size varied among environmental parameters (n = 4–14); therefore, the following correlations are interpreted in an exploratory context, especially for variables with limited data availability, such as Mn (n = 4). Similar exploratory analyses based on limited numbers of Antarctic lakes are common in polar limnological research, where logistical constraints restrict sample size, and are widely used to identify indicative ecological patterns rather than statistically definitive relationships [46,47].
Among the measured variables, HCO3− (Spearman ρ = 0.78, p = 0.005) and K+ (Spearman ρ = 0.69, p = 0.019) exhibited the strongest and statistically significant correlation with species richness, suggesting that carbonate chemistry and ionic balance may be important in shaping diatom communities. HCO3− bioavailability enhances the carbon supply for photosynthetic activity and supports the physiological efficiency of diatoms under low-pH or limited carbon dioxide conditions. This highlights HCO3− as a potentially important environmental driver in Antarctic freshwater systems. Although K+ is not traditionally considered a limiting nutrient for phytoplankton, it can play indirect but ecologically relevant and critical roles through its association with lake ionic composition [48,49]. The positive relationship between K+ concentrations and diatom species richness suggests that K+ tracks higher ionic strength and conductivity, which can influence species sorting via osmotic regulation and physiological tolerance, particularly in oligotrophic and ultra-oligotrophic Antarctic lakes [50]. K+ is a major dissolved cation derived mainly from mineral weathering and glacial or periglacial inputs, and while it does not contribute directly to alkalinity buffering, it often co-varies with alkalinity because both respond to shared geochemical controls [49,50]. K+ may therefore act as an indicator of geochemical environments favorable for diverse diatom communities rather than as a direct driver. Similarly, DO exhibited a positive and statistically significant correlation with diatom species richness (Figure 5). Lakes with higher DO, such as L4, P1, P2, and OP2, included more diatom species. In contrast, lakes L1, L5, and HS2 had lower DO levels and lower species diversity.
Chl-a is commonly used as a proxy for primary productivity; however, its relationship with diatom species richness was moderate in our samples (Figure 5). Similarly, major ions (Na+, Ca+2, Mg2+, and SO42−), nutrients (NO3−, Si, and P), Mn, pH, salinity, and TDS also exhibited moderate but non-significant correlations (Figure 5), implying that these factors may contribute to diatom variability but were not dominant factors in the studied lakes. This outcome may be related to the small sample size, narrow range of variation, multiple interacting factors, or non-linear relationships. For instance, Si is essential for diatom frustules, but its concentrations were likely sufficient across all sites; therefore, it was not a limiting factor. Similarly, pH and Mn may be controlled by oxygen and HCO3− availability; hence, these interactions could obscure direct correlations.
In contrast, most trace metals (Zn2+, Co, and Fe) displayed weak or negligible relationships (Figure 5), even though these parameters are biologically important for several enzymes and photosynthesis. This can be explained by the dual effect of metals as essential micronutrients and potential toxins at higher levels, as well as by their redox properties and indirect or secondary influence. Temperature also showed a weak correlation (Figure 5), suggesting a broader tolerance within the observed temperature range.
In conclusion, diatom species richness exhibited varying degrees of correlation with the measured environmental variables in the studied Antarctic lakes (Figure 5). Among these, the strongest positive relationship was observed with HCO3− concentrations, suggesting a potential link between alkalinity and diatom diversity in these polar freshwater systems. Additionally, lakes with higher alkalinity may provide a buffering effect that stabilizes pH fluctuations. This buffering capacity could enhance the resilience of diatom communities to environmental stress in Antarctic lakes. The influence of moderate and low correlations on diatom diversity in the studied lakes was secondary to the effect of HCO3− and K+.

5. Conclusions

This study documents 83 diatom taxa (species and genera combined) in lakes and ponds on King George and Horseshoe Islands in the Maritime Antarctic, most likely shaped by the distinct limnological characteristics of each lake. The most common species were Planothidium lanceolatum, Fragilaria cf. capucina, and Nitzschia cf. homburgiensis. Species richness showed strong positive links with HCO3−; and K+, suggesting that carbonate availability and ionic composition play important roles in structuring these communities. Other variables exhibited moderate to weaker or non-significant correlations, indicating more indirect influences. Overall, these results provide a valuable baseline and highlight key water-chemistry parameters that could be important for future climate-related assessments in Maritime Antarctic freshwater environments.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/d18020114/s1, Table S1: Qualitative distribution of diatoms in sediments collected from the littoral zone of lakes and ponds on King George and Horseshoe Islands, based on light and SEM microscopy; Table S2: Sørensen similarity index between the thirteen sites on King George and Horseshoe Islands (L5 was excluded).

Author Contributions

Conceptualization, H.C. and N.O.; methodology, H.C. and N.O.; investigation, H.C. and N.O.; laboratory work, H.C.; sampling, N.O.; writing—original draft preparation, H.C. and N.O.; resources, N.O.; writing—review and editing, H.C. and N.O.; visualization, H.C.; supervision, N.O.; project administration, N.O.; funding acquisition, N.O. All authors have read and agreed to the published version of the manuscript.

Funding

This study was funded by the Scientific and Technological Research Council of Türkiye (TÜBİTAK) Project #118Y372, Istanbul Technical University (ITU) Projects #42035 and #40265. The study was conducted under the auspices of the Presidency of the Republic of Türkiye, supported by the Ministry of Industry and Technology and coordinated by the Polar Research Institute of TÜBİTAK.

Data Availability Statement

Data is contained within the article or Supplementary Material.

Acknowledgments

We thank Frederic Thalasso, Maria Soledad Astorga Espana and Lea Cabrol for their support in the field in King George in 2017. We thank Celine Lavergne for sampling on King George Island in 2019 and Atilla Yılmaz for sampling on Horseshoe Island in 2020. We thank Mehmet Baki Yokeş for his guidance and Ümmühan Sancar for her guidance in the identification of diatom species. We also thank Jose Retamales, the Chilean Antarctic Institute (INACH), Burcu Özsoy and the ITU Polar Research Center (POLREC) for the logistical support.

Conflicts of Interest

The authors declare no conflicts of interest. The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript; or in the decision to publish the results.

Abbreviations

The following abbreviations are used in this manuscript:
MnManganese
FeIron
MoMolybdenum
CoCobalt
CuCopper
Zn2+Zinc
NNitrogen
NaSodium
Mg2+Magnesium
SiSilica
PPhosphorus
Ca2+Calcium
K+Potassium
HCO3−Bicarbonate
NO3−Nitrate
NH4+Ammonium
Chl-aChlorophyll-a
HNLCHigh-nutrient low-chlorophyll
OP1, OP2Organic Pond
P1, P2, P3Ponds
HS1, HS2Horseshoe-1, Horseshoe-2
SKSkua Lake
TAETurkish Antarctic Expedition
PCPolycarbonate
DODissolved oxygen
TDSTotal dissolved solids
ORPOxidation-reduction potentials
Tem.Temperature
Salin.Salinity
Con.Conductivity
ICP-MSInductively coupled plasma mass spectrometer
LMLight microscopy
SEMScanning electron microscope
UV-VisUltraviolet–visible
DNADeoxyribonucleic acid
RNARibonucleic acid
NANot available
cf.Compare with
sp.Unspecified species, genus level
UPGMAUnweighted Pair Group Method with Arithmetic Mean

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Figure 1. Representative map showing the locations of the studied lakes and ponds on (a) the Fildes Peninsula and Ardley Islands, King George Island, and (b) Horseshoe Island in the Maritime Antarctic, western coastal region of the Antarctic Peninsula. Field photographs show (c) sampling with a small boat at Kitiesh Lake (L2); (d) general view of Skua Lake; (e) general view of Horseshoe Lake 1 (HS1); (f) Organic Pond OP2 on Ardley Island, King George Island, with thin ice cover and a sampling hole; (g) surface sediment sampling at Kitiesh Lake (L2); (h) surface sediment sampling at Skua Lake (SK) on Horseshoe Island; (i) collected surface sediments from the upper sediment layer in shallow water (5–10 cm depth) (j) collected water samples preserved with Lugol’s iodine solution.
Figure 1. Representative map showing the locations of the studied lakes and ponds on (a) the Fildes Peninsula and Ardley Islands, King George Island, and (b) Horseshoe Island in the Maritime Antarctic, western coastal region of the Antarctic Peninsula. Field photographs show (c) sampling with a small boat at Kitiesh Lake (L2); (d) general view of Skua Lake; (e) general view of Horseshoe Lake 1 (HS1); (f) Organic Pond OP2 on Ardley Island, King George Island, with thin ice cover and a sampling hole; (g) surface sediment sampling at Kitiesh Lake (L2); (h) surface sediment sampling at Skua Lake (SK) on Horseshoe Island; (i) collected surface sediments from the upper sediment layer in shallow water (5–10 cm depth) (j) collected water samples preserved with Lugol’s iodine solution.
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Figure 2. The seven most widespread diatom species identified in lakes and ponds of King George and Horseshoe Islands in the Maritime Antarctic.
Figure 2. The seven most widespread diatom species identified in lakes and ponds of King George and Horseshoe Islands in the Maritime Antarctic.
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Figure 3. Diatom similarity matrix based on the Sørensen similarity index and the corresponding dendrogram for thirteen coastal lakes on King George and Horseshoe Islands (L5 was excluded). Darker colors represent higher similarity among diatom assemblages.
Figure 3. Diatom similarity matrix based on the Sørensen similarity index and the corresponding dendrogram for thirteen coastal lakes on King George and Horseshoe Islands (L5 was excluded). Darker colors represent higher similarity among diatom assemblages.
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Figure 4. Examples of diatom species in King George and Horseshoe Islands. 1. Pinnularia divergens in L4 2. Pinnularia subcapitata var. subrostrata in OP2 3. Pinnularia cf. rhombarea in OP1 4. Pinnularia microstauron var. elongata in P3 5. Pinnularia subsolaris in OP1 6. Pinnularia brebissonii in LM in OP1 and SEM in L6 7. Pinnularia cf. quadratarea in P2 8. Pinnularia sp. in P2 9. and 17. Fragilaria cf. capucina in P1 and OP2 10. Fragilaria sp. in OP2 11. Pinnularia cf. borealis in OP1 12. Pinnularia cf. subantarctica in OP2 13. Fragilaria cf. nanana in P1 14. Fragilaria cf. rumpens in OP1 15. Fragilaria cf. fragilarioides in P2 16. Fragilaria cf. cochabambina in P3 18. Fragilaria sp. in L3 19. Achnanthidium sp. in OP2 20. Achnanthidium cf. minutissimum in P2 21. Achnanthidium nanum in L2 22. Achnanthidium cf. australexiguum in L2 23. Achnanthidium spp. in P1 24. Achnanthidium cf. reimeri in L6 25. Achnanthidium sp. in OP2 26. Humidophila sp. in OP2 27. Humidophila arcuata in P2 and P3 28. Planothidium lanceolatum in P2 29. Planothidium cf. frequentissimum in L4 30. Planothidium delicatulum in L4 31. Planothidium cf. subantarcticum in L3 32. Planothidium biporomum in L3 33. Planothidium cryptolanceolatum in P3 34. Planothidium sp. in L4 35. Planothidium incuriatum in L4 36. Planothidium sp. in L6 37. Humidophila tabellariiformis in P3 38,39. Diadesmis spp. in P3 and P1 40. Craticula spp. in OP2 41. Craticula cf. pseudocitrus in L6 42. Achnanthes cf. sinaensis in P1 43. Achnanthes sp. in L4. 44. Achnanthes cf. taylorensis in OP1 45. Nitzschia spp. in OP1 46. Nitzschia cf. homburgiensis in OP1 47. Nitzschia sp. in L3 48. Gomphonema micropus in OP2 49. Gomphonema cf. sarcophagus in OP2 50. Gomphonema cf. angustatum in OP2 51. Gomphonema sp. in L2 52. Gomphonema cf. gracile in L4 53. Gomphonema cf. duplipunctatum in L4 54. Gomphonema cf. subclavatum in L4 55. Gomphonella sp. in L2 56. Planothidium australe in P2 57. Navicula libonensis in L6 58. Navicula sp. in L6 59. Navicula gregaria in L6 60. Navicula cf. slesvicensis in L6 61. Navicula cf. trilatera in L4 62. Navicula cf. veneta in P1 63. Diatomella balfouriana in L2 64. Eunotia sp. in L4 65. and 80. Placoneis cf. explanata in OP1 and OP2 66. Placoneis paraelginensis in L6 67. Sellaphora sp. in L2 68. Staurosirella sp. in L4 69. Luticola cf. muticopsis in OP2 70. Frustulia sp. in P3 71. Luticola cf. permuticopsis in P3 72. Luticola sp. in L2 73. Eunotia sp. in P3 74. Psammothidium lacustre in P3 75. Psammothidium helveticum in L3 76. Psammothidium cf. acidoclinatum in L6 77. Psammothidium cf. confusoneglectum in L2 78. Psammothidium sp. in P2 79. Stauroneis cf. subgracilis in P1 81. Tabellaria cf. flocculosa in OP2 82. Halamphora sp. in L4 83. Adlafia sp. in P1 84. Unidentified cf. centric diatoms in OP2, L1, P1 respectively 85. Thalassionema spp. in P1 86. Halamphora cf. coraensis in L4 87. Stauroforma cf. inermis in P3 88. Chamaepinnularia sp. in P2 89. Pinnularia sp. in OP2 90. Planothidium sp. and Psammothidium cf. confusoneglectum in L2 91. Planothidium cf. delicatulum, Fragilaria sp. and Gomphonema sp. (From left to right) in OP2 92. Unidentified centric and pennate diatoms in L6 93. Fragilaria sp. and Planothidium sp. in P2. 94. Diatom species, unidentified genus 95. Diatom species, unidentified genus, frustules in girdle view 96. Coccolithophore sp. (non-diatom) in L2 97. Non-phytoplankton species, unidentified genus in L1 and L6 98. Abnormal forms of diatoms in the water and sediment samples respectively: Fragilaria cf. capucina in OP2 (the first three figures), Paraplanothidium cf. victorii in L4, Craticula cf. pseudocitrus in L3.
Figure 4. Examples of diatom species in King George and Horseshoe Islands. 1. Pinnularia divergens in L4 2. Pinnularia subcapitata var. subrostrata in OP2 3. Pinnularia cf. rhombarea in OP1 4. Pinnularia microstauron var. elongata in P3 5. Pinnularia subsolaris in OP1 6. Pinnularia brebissonii in LM in OP1 and SEM in L6 7. Pinnularia cf. quadratarea in P2 8. Pinnularia sp. in P2 9. and 17. Fragilaria cf. capucina in P1 and OP2 10. Fragilaria sp. in OP2 11. Pinnularia cf. borealis in OP1 12. Pinnularia cf. subantarctica in OP2 13. Fragilaria cf. nanana in P1 14. Fragilaria cf. rumpens in OP1 15. Fragilaria cf. fragilarioides in P2 16. Fragilaria cf. cochabambina in P3 18. Fragilaria sp. in L3 19. Achnanthidium sp. in OP2 20. Achnanthidium cf. minutissimum in P2 21. Achnanthidium nanum in L2 22. Achnanthidium cf. australexiguum in L2 23. Achnanthidium spp. in P1 24. Achnanthidium cf. reimeri in L6 25. Achnanthidium sp. in OP2 26. Humidophila sp. in OP2 27. Humidophila arcuata in P2 and P3 28. Planothidium lanceolatum in P2 29. Planothidium cf. frequentissimum in L4 30. Planothidium delicatulum in L4 31. Planothidium cf. subantarcticum in L3 32. Planothidium biporomum in L3 33. Planothidium cryptolanceolatum in P3 34. Planothidium sp. in L4 35. Planothidium incuriatum in L4 36. Planothidium sp. in L6 37. Humidophila tabellariiformis in P3 38,39. Diadesmis spp. in P3 and P1 40. Craticula spp. in OP2 41. Craticula cf. pseudocitrus in L6 42. Achnanthes cf. sinaensis in P1 43. Achnanthes sp. in L4. 44. Achnanthes cf. taylorensis in OP1 45. Nitzschia spp. in OP1 46. Nitzschia cf. homburgiensis in OP1 47. Nitzschia sp. in L3 48. Gomphonema micropus in OP2 49. Gomphonema cf. sarcophagus in OP2 50. Gomphonema cf. angustatum in OP2 51. Gomphonema sp. in L2 52. Gomphonema cf. gracile in L4 53. Gomphonema cf. duplipunctatum in L4 54. Gomphonema cf. subclavatum in L4 55. Gomphonella sp. in L2 56. Planothidium australe in P2 57. Navicula libonensis in L6 58. Navicula sp. in L6 59. Navicula gregaria in L6 60. Navicula cf. slesvicensis in L6 61. Navicula cf. trilatera in L4 62. Navicula cf. veneta in P1 63. Diatomella balfouriana in L2 64. Eunotia sp. in L4 65. and 80. Placoneis cf. explanata in OP1 and OP2 66. Placoneis paraelginensis in L6 67. Sellaphora sp. in L2 68. Staurosirella sp. in L4 69. Luticola cf. muticopsis in OP2 70. Frustulia sp. in P3 71. Luticola cf. permuticopsis in P3 72. Luticola sp. in L2 73. Eunotia sp. in P3 74. Psammothidium lacustre in P3 75. Psammothidium helveticum in L3 76. Psammothidium cf. acidoclinatum in L6 77. Psammothidium cf. confusoneglectum in L2 78. Psammothidium sp. in P2 79. Stauroneis cf. subgracilis in P1 81. Tabellaria cf. flocculosa in OP2 82. Halamphora sp. in L4 83. Adlafia sp. in P1 84. Unidentified cf. centric diatoms in OP2, L1, P1 respectively 85. Thalassionema spp. in P1 86. Halamphora cf. coraensis in L4 87. Stauroforma cf. inermis in P3 88. Chamaepinnularia sp. in P2 89. Pinnularia sp. in OP2 90. Planothidium sp. and Psammothidium cf. confusoneglectum in L2 91. Planothidium cf. delicatulum, Fragilaria sp. and Gomphonema sp. (From left to right) in OP2 92. Unidentified centric and pennate diatoms in L6 93. Fragilaria sp. and Planothidium sp. in P2. 94. Diatom species, unidentified genus 95. Diatom species, unidentified genus, frustules in girdle view 96. Coccolithophore sp. (non-diatom) in L2 97. Non-phytoplankton species, unidentified genus in L1 and L6 98. Abnormal forms of diatoms in the water and sediment samples respectively: Fragilaria cf. capucina in OP2 (the first three figures), Paraplanothidium cf. victorii in L4, Craticula cf. pseudocitrus in L3.
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Figure 5. Exploratory relationships between diatom species richness (number of distinct taxa per lake) and selected environmental variables.
Figure 5. Exploratory relationships between diatom species richness (number of distinct taxa per lake) and selected environmental variables.
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Table 1. The studied lakes and ponds from King George and Horseshoe Islands with geographic information.
Table 1. The studied lakes and ponds from King George and Horseshoe Islands with geographic information.
SitesOther NameShort NameLatitudeLongitudeSampling DateSample Type
King George Island—Fildes Peninsula
Lake 1UruguayL1−62.1853−58.911825 February 2017Water, filter
14 January 2019
Lake 2 KitieshL2 −62.1936−58.966419 February 2017Water, sediment, filter
17 January 2019
Lake 3-L3−62.2010−58.97292 March 2017Water, sediment
Lake 4 LangerL4 −62.2050−58.96652 March 2017Water, sediment
9 January 2019
Lake 5 WestL5 −62.2172−58.96602 March 2017Water, sediment
Lake 6 -L6 −62.2210−58.95902 March 2017Water, sediment
Pond 1-P1−62.1893−58.929525 February 2017Water, sediment
Pond 2-P2−62.1920−58.941725 February 2017Water, sediment
-−62.2210−58.95909 January 2019
Pond 3-P3−62.1944−58.948625 February 2017Water, sediment
Organic Pond 1-OP1−62.1887−58.924225 February 2017Water, sediment
King George Island—Ardley Island
Organic Pond 2-OP2−62.2104−58.94102 March 2017Water, sediment, filter
−62.2104−58.941016 January 2019
Horseshoe Island
Horseshoe 1 -HS1−67.22486−67.8284721 February 2020Water, sediment, filter
Horseshoe 2 -HS2−67.22252−67.8256921 February 2020Water, sediment, filter
Skua Lake -SK−67.18066−67.4844427 February 2020Water, sediment, filter
Table 2. Physicochemical parameters of lakes and ponds on King George and Horseshoe Islands. Water parameters for the 2017 sampling were based on [4], and key nutrient, ion, and metal concentrations were based on ion chromatography and ICP-MS measurements conducted in [9]. DO: dissolved oxygen; Tem.: temperature; Con.: conductivity; Salin.: salinity; TDS: total dissolved solids; Chl-a: chlorophyll-a; ORP: oxidation reduction potential. NA: not available.
Table 2. Physicochemical parameters of lakes and ponds on King George and Horseshoe Islands. Water parameters for the 2017 sampling were based on [4], and key nutrient, ion, and metal concentrations were based on ion chromatography and ICP-MS measurements conducted in [9]. DO: dissolved oxygen; Tem.: temperature; Con.: conductivity; Salin.: salinity; TDS: total dissolved solids; Chl-a: chlorophyll-a; ORP: oxidation reduction potential. NA: not available.
SitespHDO
(%)		Tem. (°C)Con. (μS cm−1)Salin. (g/L)TDS
(mg L−1)		Chl-a
(µg L−1)		ORP (mV)Key Nutrients (µg/L)Key Ions (µg/L)Key Metals (µg/L)Diatom Species Richness
L1
(2017)
(2019)		7.4875.2950.04480.2NANO3−: 0.06
PO43−: <0.001
SO42−: 2.77
Si: 8.57
P: 1.53		HCO3−: 15.50
Mg: 1.00
Na: 12.44
K: 0.27
Ca: 0.90		Fe: 39.54
Mn: <1
Zn: 5.02
Cu: 14.76
Ni: <1		4
9.21004.81220.0661NA121NANANA
L2
(2017)
(2019)		7.2882.52080.101041.3NANO3−: 0.01
PO43−: <0.001
SO42−: 6.61
Si: 6.76
P: <1		HCO3−: 20.50
Mg: 2.17
Na: 16.73
K: 0.60
Ca: 4.88		Fe: 36.20
Mn: <1
Zn: 1.71
Cu: 14.31
Ni: <1		19
11.61015.11760.08NANANANANANA
L38.5970.81150.05580.3NANO3−: 0.03
PO43−: <0.001
SO42−: 5.27
Si: 5.93
P: <1		HCO3−: 19.50
Mg: 2.08
Na: 14.78
K: 0.44
Ca: 5.15		Fe: 52.50
Mn: <1
Zn: 3.24
Cu: 13.98
Ni: <1		13
L4
(2017)
(2019)		8.0891.72060.101030.3NANO3−: 0.11
PO43−: <0.001
SO42−: 45.35
Si: 10.56
P: 2.21		HCO3−: 31.00
Mg: 2.15
Na: 25.12
K: 1.14
Ca: 14.61		Fe: 51.62
Mn: <1
Zn: 6.06
Cu: 13.27
Ni: 1.85		30
9.41128.93130.15156NA141NANANA
L5 7.8842.0750.03380.5NANO3−: 0.08
PO43−: <0.001
SO42−: 2.03
Si: 7.25
P: <1		HCO3−: 18.50
Mg: 1.43
Na: 9.97
K: 0.29
Ca: 3.47		Fe: 39.23
Mn: <1
Zn: 1.02
Cu: 13.72
Ni: <1		0
L6 7.9971.51110.05561.4NANO3−: 0.21
PO43−: <0.001
SO42−: 3.19
Si: 11.21
P: <1		HCO3−: 31.50
Mg: 2.25
Na: 14.55
K: 0.62
Ca: 5.36		Fe: 40.82
Mn: <1
Zn: 0.99
Cu: 13.52
Ni: <1		26
P18.81005.5680.03340.7NANO3−: <0.001
PO43−: <0.001
SO42−: 2.58
Si: 7.00
P: <1		HCO3−: 19.50
Mg: 1.34
Na: 10.33
K: 0.30
Ca: 1.62		Fe: 39.39
Mn: 1.33
Zn: 1.52
Cu: 16.37
Ni: <1		19
P2
(2017)
(2019)		9.11003.2370.02180.5NANO3−: 0.02
PO43−: <0.001
SO42−: 1.16
Si: 5.05
P: 1.38		HCO3−: 16.50
Mg: 0.57
Na: 6.04
K: 0.21
Ca: 0.75		Fe: 40.22
Mn: <1
Zn: 4.02
Cu: 14.86
Ni: <1		22
9.1997.11030.0551NA145NANANA
P38.4935.21000.05500.7NANO3−: 0.47
PO43−: <0.001
SO42−: 3.11
Si: 10.15
P: 6.34		HCO3−: 23.50
Mg: 1.86
Na: 15.11
K: 0.49
Ca: 3.22		Fe: 65.96
Mn: 3.69
Zn: 14.41
Cu: 15.34
Ni: <1		25
OP18.5985.1570.03282.6NANO3−: 0.01
PO43−: <0.001
SO42−: 2.27
Si: 12.76
P: 9.08		HCO3−: 21.50
Mg: 0.97
Na: 9.62
K: 0.25
Ca: 1.36		Fe: 183.60
Mn: 9.88
Zn: 9.70
Cu: 42.74
Ni: <1		18
OP2
(2017)
(2019)		8.41000.92560.121286.9NANO3−: 3.12
PO43−: <0.001
SO42−: 9.86
Si: 17.80
P: 76.15		HCO3−: 34.50
Mg: 5.84
Na: 29.97
K: 1.87
Ca: 9.25		Fe: 100.88
Mn: 22.62
Zn: 1.37
Cu: 13.96
Ni: 1.29		27
9.31089.21120.0556NA103NANANA
HS1 8.0952.8108NANANANANANANA2
HS2 8.1881.1122NANANANANANANA4
SK 7.6872.3158NANANANANANANA3
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Cura, H.; Olgun, N. Diatom Diversity and Its Environmental Drivers in Lakes of King George (62° S) and Horseshoe Islands (67° S) in the Maritime Antarctic. Diversity 2026, 18, 114. https://doi.org/10.3390/d18020114

AMA Style

Cura H, Olgun N. Diatom Diversity and Its Environmental Drivers in Lakes of King George (62° S) and Horseshoe Islands (67° S) in the Maritime Antarctic. Diversity. 2026; 18(2):114. https://doi.org/10.3390/d18020114

Chicago/Turabian Style

Cura, Hilal, and Nazlı Olgun. 2026. "Diatom Diversity and Its Environmental Drivers in Lakes of King George (62° S) and Horseshoe Islands (67° S) in the Maritime Antarctic" Diversity 18, no. 2: 114. https://doi.org/10.3390/d18020114

APA Style

Cura, H., & Olgun, N. (2026). Diatom Diversity and Its Environmental Drivers in Lakes of King George (62° S) and Horseshoe Islands (67° S) in the Maritime Antarctic. Diversity, 18(2), 114. https://doi.org/10.3390/d18020114

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