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All issues Volume 54 (2018) Ann. Limnol. - Int. J. Lim., 54 (2018) 26 Full HTML
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Ann. Limnol. - Int. J. Lim.
Volume 54, 2018
Article Number 26
Number of page(s) 11
DOI https://doi.org/10.1051/limn/2018017
Published online 16 July 2018

© EDP Sciences, 2018

1 Introduction

Species of Ostracoda, which are small microscopic (0.3–7 mm) invertebrates, are one of the most widely dispersed groups of Crustacea. Living forms are distributed from ca. 5000 m deep in ocean (Benson, 1972; Brandão and Yasuhara, 2013) and up to over 4000 m (Laprida et al., 2006; Mischke et al., 2007) and 6000 m in mountain lakes (Pinto, 2013). They can be found in a variety of aquatic habitats from thermal waters (Külköylüoğlu et al., 2003) to cold springs, rivers, creeks, ponds, lakes, troughs and canals. While several species are known to have high levels of tolerances to different environmental variables, some species are considered to have habitat specific adaptive values and can be used as indicator species for particular habitats and conditions. For example, while Heterocypris incongruens (Ramdohr, 1808) is a cosmoecious species that is widely distributed with wide tolerances to some of those major environmental variables (e.g., pH, water temperature, dissolved oxygen, etc.) (Külköylüoğlu, 2013), Thermopsis thermophila Külköylüoğlu, Meisch, Rust 2003, a thermophilic ostracod with a narrow temperature range of 36–55 °C, has only been found from thermal springs in the Great Basin area (USA) (Külköylüoğlu et al., 2003). Despite their importance, freshwater ostracods are not studied extensively and we have a limited knowledge about their water and/or habitat preferences and requirements. In contrast, habitat preference and requirements of species (i.e., ostracods) constitute an important topic for several reasons; they can (1) provide understanding of habitat (water) qualities and/or conditions influenced by natural or anthropogenic factors, (2) be used to estimate past, present and future habitat conditions and species diversities, (3) help monitoring studies and/or conservation issues by means of calculating species co-occurrence patterns, (4) obtain possibilities for accounting abundance and/or diversity measurements, (5) open ways to recognize species role in the community and ecosystems, (6) increase the possibility of calculating their ecological tolerance and optimum values for different environmental factors, and (7) explain species geographical distributional patterns among the habitats (this study). Additionally, it is useful to understand whether certain species of ostracods may prefer (or require) particular type of habitat(s). The importance of this view implies that when species’ habitat preferences are known (if there is any), this information can also be used in palaeontological and palaeogeographical studies for the purpose of reconstruction of the past history of habitats.

There are a few previous studies (Gülen, 1977; 1985a, b; Gülen and Altınsaçlı, 1999) in the area of Turkey but these studies are based on one-time sampling efforts from a few sites, and there is no extensive studies related to habitat preferences and ecology of freshwater ostracods. Accordingly, the aims of the present study were (i) to understand ostracod species’ habitat preferences, (ii) to describe their ecological (physical and chemical preferences) characterization, (iii) to examine the most effective factors on species occurrences amid habitat types, and (vi) to estimate species ecological tolerance and optimum levels in different habitats along with providing species diversity measurements.

2 Materials and methods

2.1 Sampling and methodology

Our sampling sites were randomly visited within the borders of the province Kütahya (ca. 11889 km2 of surface area, covering about 1.5% of Turkey), located in the Aegean region of Turkey (Fig. 1). All samples were gained from shallow (<100 cm of depth) and littoral zones of the aquatic habitats. Samples were collected from 121 sites with 11 different aquatic habitat types (lake, reservoir, pond, wetland, ditch, trough, river, stream, creek, canal and thermal spring) using a hand net (200 μm mesh size) between 19–22 September 2014, and were immediately fixed within 70% ethanol in 250 ml plastic containers. In the laboratory, the samples were filtered using standard sieves (0.5, 1.0, 1.5 and 2.0 mm mesh size) under tap water and transferred into 70% ethanol for future research. Ostracod specimens were separated from other materials with fine needles under a Meiji-Techno stereomicroscope. Each specimen’ soft body parts and carapaces were separated in lactophenol solution after body length was measured for taxonomic description. Each slide was labeled and kept in the laboratory. Olympus-CX4 1 light microscope was used during species identification which was basically done by following the taxonomic keys of Meisch (2000) and Karanovic (2012). Each sample labeled with a code was deposited at the Limnology Laboratory of Abant İzzet Baysal University, Bolu, Turkey and can be available upon request.

Before sampling, GARMIN etrex Vista H GPS system was used to measure geographical information for elevation (elev.) and coordinates about each of sampling sites. Then after, all water samples were collected to prevent possible disturbance for water measurements. Seven major water variables (pH, oxidation-reduction potential (SHE, mV), water temperature (Tw, °C), dissolved oxygen concentration (DO, mg/L), percent oxygen saturation (%sat.), electrical conductivity (EC, µS/cm), salinity (ppt)) and atmospheric pressure (mmHg) were measured with YSI-Professional Plus. Kestrel-3000 model anemometer was used to record air temperature (Ta, °C), relative humidity (%), heat index (HI, °C), wind chill (w. chill, °C), wind speed (m/s), and dew point (Dp, °C) in situ (Tab. 1). For the major water ion concentrations, 100 ml water samples were collected from each sampling site in clean plastic bottles, preserved in cool containers, and analyzed in the laboratory for cations (sodium (Na+), ammonium (NH4+), potassium (K+), magnesium (Mg2+), lithium (Li+), calcium (Ca2+)) and anions (chloride (CI−), nitrite (NO2−), nitrate (NO32−), fluoride (F−), phosphate (PO43−), bromide (Br−), and sulphate (SO42−)). Note that some of those variables are not listed in Table 1 but will be available upon request. Detailed information about the procedure of major ion analyses can be found in Yavuzatmaca et al. (2017a). From each site, we also collected sediment samples in plastic Eppendorf vials for organic and inorganic phosphate and total phosphate (mg kg−) analyses as described in Ruban et al. (1999). Meisch (2000) performed ecological characterization of ostracod species following Hiller (1972) and Hartmann and Hiller (1977). For the species salinity tolerance/preference, he adapted the Venice-system which is also adapted in the current study. According to this system, species were classified with temperature, calcium contents, and salinity and chloride contents (see details in Meisch, 2000). However, the Venice system does not show the water temperature ranges for freshwater habitats. Therefore, we used the temperature ranges ((very cold < 12.8 °C), (>12.8 °C cold ≤ 18 °C), (>18 cold-cool ≤ 21 °C), or (warm ≤ 21 °C)) (Chu et al., 2009; Olivero-Sheldon et al., 2014).

thumbnail Fig. 1

Sampling sites of 121 different sites in Kütahya, Turkey.
Table 1

Mean, maximum, minimum and standard deviations (SdDev) of the environmental variables reported from sampling sites are shown. Higher values of deviations more than the mean values for those variables are italicized. Abbreviations: TPh (total phosphate), InPh (inorganic phosphate), OrPh (organic phosphate). Other abbreviations are provided in materials and methods section.

2.2 Statistical analyses

Alpha diversity of Shannon-Wiener index values were calculated with the Species Diversity and Richness 4 (SDR) program (Seaby and Henderson, 2006). Species percentage contribution and dis/similarities in habitats were analyzed with the analysis of similarities (ANOSIM) and analysis of similarity percentage (SIMPER) along with the Bray-Curtis test. In each of the branching point, habitat(s) effective on species occurrence are illustrated with their effective value. Both analyses were run in Community Analysis Package (CAP 4.1.3.) statistical program (Seaby and Henderson, 2007).

Estimatimation of the most effective environmental variables and their correlation with ostracod species was made with the program CANOCO for windows 4.5 (ter Braak and Šmilauer, 2002) where quantitative data were used for the species. Results were tested with Monte Carlo Permutation tests (499 run) while multicollinearity test was applied to download rare species to eliminate possible consequences of multicollinearity (Birks et al., 1990; ter Braak, 1995). Accordingly, variables with higher inflation factor (VIF > 10) representing a possibility of multicollinearity were removed from the analyses. As suggested (ter Braak and Barendregt, 1986; ter Braak, 1995), before CCA, we tested suitability of our data for CCA with detrended correspondence analysis whose length of gradient was 6.58 indicating the data was suitable for CCA. Species clustering relationships based on habitat type were analyzed with unweighted pair group mean averages (UPGMA) where Jaccard’s coefficient was preferred to use after data were log(e) transformed in Multi Variate Statistical Package version 3.1. (Kovach, 1998). Pearson correlation analysis (SPSS program version 17) (SPSS, 2008) was applied to evaluate possible associations among 22 environmental variables and major ions along with numbers of species. Species ecological tolerance and optimum estimates were calculated with C2 program (Juggins, 2003), where we used species found from three or more different sites. Ternary and scattered plots used to estimate distributional patterns of species with some of those major ions were obtained from JMP ® Pro13.0 program. We only used adult individuals during the statistical analyses. Juveniles, carapaces and/or damaged individuals were not used.

3 Results

In general, species were found in cool (>18 °C) to warmer (≥21 °C), alkaline (pH 8.22), and fresh to slightly brackish waters. Water quality measurements (Tab. 1) indicated low to high (high Ca2+ > low Mg2+ > very low Na+) cations and relatively low (low SO42− > very low Cl− > not significant F−) anion concentrations where Ca2+ was the dominant ion.

Total of 23 species (Candona candida (O.F. Müller, 1776); C. neglecta Sars, 1887; Cypria ophtalmica (Jurine, 1820); Cypridopsis vidua (O.F. Müller, 1776); Darwinula stevensoni (Brady and Robertson, 1870); H. incongruens (Ramdohr, 1808); Heterocypris salina (Brady, 1868); Herpetocypris reptans (Baird, 1835); H. chevreuxi (Sars, 1896); Ilyocypris bradyi Sars, 1890; I. gibba (Ramdohr, 1808); I. hartmanni Lerner-Seggev, 1968; Limnocythere inopinata (Baird, 1843); Physocypria kraepelini G. W. Müller, 1903; Potamocypris fulva (Brady, 1868); P. pallida Alm, 1914; P. unicaudata Schäfer, 1943; Potamocypris variegata (Brady and Norman, 1889); Potamocypris villosa (Jurine, 1820); Prionocypris zenkeri (Chyzer and Toth, 1858); Psychrodromus fontinalis (Wolf, 1920); Psychrodromus olivaceus (Brady and Norman, 1889); Trajancypris clavata (Baird, 1838)) belonging to 13 genera collected from 11 different aquatic habitat types were found from 91 of 121 sampling sites in Kütahya between 19 and 22 September 2014 (Tab. 2). Sixteen species (shown in bold above) were new reports for the province.

Shannon-Wiener alpha diversity index value (H′) was 3.64 with relatively low error term (Jackknife Std Error 0.283). Four species (H. salina, H. incongruens, P. olivaceus, I. bradyi) creating more than 93% of similarities contributed higher alpha values (2.625, 2.434, 2.301, 2.159, respectively) than other species. ANOSIM results revealed that unassigned group averages of 78.65% of the contribution of similarities were provided by 16 most frequently occurring species. Accordingly, finding a negative R value, (sample statistics = −1, p = 0.001, n = 89 observations) suggested that there were no significant differences between the species of the groups, implying that most similar samples were independently found outside of those groups. All the four species exhibited equal or higher tolerance values for pH, dissolved oxygen and water temperature than the average values of the total of 12 most abundant species (Tab. 3). Of which, H. salina, I. bradyi and L. inopinata also revealed the highest tolerances for electrical conductivity while some other species (e.g., P. variegata for dissolved oxygen, P. villosa and D. stevensoni for water temperature) also showed high tolerance levels to different variables. These results may shed light into the fact that these species play a dominant role in a variety of habitats due to their high levels of ecological tolerances.

Among these species, H. incongruens was mostly found in waters with high Ca2+ concentrations between 60 and 80% but low Na+ + K+ and Mg2+ concentrations (<40%) while H. salina was collected from waters with higher Ca2+ between 65 and 90% of dominancy but medium Na+ + K+ (40–80%) and relatively high (>60%) of Mg2+ (Fig. 2). Individuals of I. bradyi were encountered from the waters with high Ca2+ concentrations between 60 and 85% of dominancy but low Na+ + K+ (<30%) and Mg2+ (<40%). Another species, P. olivaceus was also common in waters with a wide range of low to high Ca2+ concentrations from 30 to 90% of dominancy but very low Na+ + K+ (<20%) and Mg2+ (≥60%) (Fig. 3). These species clearly showed higher tolerance levels for dissolved oxygen and water temperature than the mean of total of all species although a few species displayed different levels of tolerance and optimum estimates (see discussion below) (Tab. 3).

UPGMA diagram illustrated three main clustering groups (Fig. 4). In which, regardless of their taxonomic levels, species with common features tend to be clustered in the same group. Groups I and III mostly consisted of species with rare and/or low occurrences while most frequently occurring common species were generally clustered in group II. Except a few rare species (e.g., L. inopinata, C. neglecta, C. candida), most ostracods showed no specific habitat preferences where habitat type was not effective on species occurrences (p > 0.05).

According to CCA results (Tab. 4, Fig. 5), four variables (Tw, EC SHE, pH) were found to be the most effective factors on species occurrences (p < 0.05) while 57.4% of correlation between species and environmental variables were explained with relatively low cumulative percent variation (6.4%) by the first two axes. Pearson correlation analyses showed strong positive and negative correlation between numbers of species and dissolved oxygen (p = 0.002) and water temperature (p = 0.015), respectively. Most of these common species showed relatively wide tolerance ranges to five major environmental variables (Tab. 3).

Table 2

Distribution of numbers of species (NuSpp) are shown from 11 different habitat types. Numbers of habitat type (NuHabtype) indicate numbers of samplings from that of particular habitats. For example, three samplings were done from three different lakes with two species. Two well samples are not shown in this table due to lack of ostracods from these two sites. New reports are shown in bold. Abbreviations: CC, (Candona candida); CN, (C. neglecta); COP, (Cypria ophtalmica); CV, (Cypridopsis vidua); DS, (Darwinula stevensoni); HI, (Heterocypris incongruens); HAS, (H. salina); HR, (Herpetocypris reptans); HC, (H. chevreuxi); IBR, (Ilyocypris bradyi); IG, (I. gibba); IH, (I. hartmanni); LI, (Limnocythere inopinata); PK, (Physocypria kraepelini); PFU, (Potamocypris fulva); PP, (P. pallida); PU, (P. unicaudata); PV, (P. variegata); PVI, (P. villosa); PZE, (Prionocypris zenkeri); PFO, (Psychrodromus fontinalis); PO, (P. olivaceus); TC, (Trajancypris clavata).

Table 3

Optimum (Opt) and tolerance (Tol) values of 12 most abundant species occurred more than three times from different habitats. Abbreviations: Numb, numbers of occurrences; Max, maximum numbers of individuals; N2, Hill’s coefficient. Other abbreviations are given in Materials and Methods.

thumbnail Fig. 2

Occurrence of H. incongruens (a) and H. salina (b) in waters with major cations (Mg2+, Ca2+ and Na+ + K+). Values are in percentage.
thumbnail Fig. 3

Occurrence of (a) P. olivaceus and I. bradyi (b) in waters with major cations (Mg2+, Ca2+ and Na+ + K+). Values are in percentage.
thumbnail Fig. 4

UPGMA dendrogram shows clustering relationships among 16 species within three main groups (I–III).
Table 4

Summary table of CCA results.

thumbnail Fig. 5

(a) CaCA diagram shows distribution of 16 species and 6 environmental vairables measured in Kütahya. Species abbreviations are given in Table 2, (b) CbCA diagram shows distribution of sampling sites with species occurred three or more times in Kütahya.

4 Discussion and conclusion

Until this study, 15 ostracod species were known from Kütahya. These species were mostly reported from hot springs, ponds, creeks, rivers, and swamps (Gülen, 1977; 1985a, b; Gülen and Altınsaçlı, 1999) of particular areas; therefore, they did not represent whole faunal richness of the area. In contrast, during the present study, sampling from all 13 towns, we reported 23 living ostracods from 11 different habitats, of which, 16 were new reports (Tab. 2). During the present study, we did not find eight species (Cypris pubera, O.F. Müller, 1776; Cyclocypris ovum (Jurine, 1820); Cypretta dubiosa (Daday, 1901); Dolerocypris sinensis (Sars, 1903); Eucypris virens (Jurine, 1820); Ilyocypris decipiens Masi, 1905; Ilyocypris divisa Kliei, 1926; Tonnacypris lutaria (Koch, 1838)) which are previously reported from the area. In summary, the area consists of 31 ostracod species at the moment. Comparing to other studies, this number being relatively higher than many other provinces in Turkey suggests potentially high species diversity of the area. Indeed, finding high alpha diversity index value (3.64) supports this view. However, four most frequently occurring species (H. salina, H. incongruens, P. olivaceus, I. bradyi) seemed to be responsible for the majority of the diversity values (2.625, 2.434, 2.301, 2.159, respectively). It is probable that these so called “cosmoecious species” (Külköylüoğlu, 2013) are found in a variety of habitats with wide ranges of geographical distributions (Mezquita et al., 1999a, b; Meisch, 2000; Külköylüoğlu, 2003; Van der Meeren et al., 2010; Yavuzatmaca et al., 2017a, b). Their wide distribution may probably be related to high tolerance levels (Külköylüoğlu, 2003; Iglikowska and Namiotko, 2012). This was actually the case in the present study that our results confirm those of earlier and contemporary studies in different taxonomic groups. For example, Heino and Grönroos (2017) recently showed that while very rare stream insect species did not have much contribution to the local beta diversity, species occurring most frequently in many sites with high abundance and variation were able to provide the most contribution to the local beta diversity. Also, finding of no significant effect of habitat types and reporting species from a variety of habitats may suggest that these species may not have specific habitat preferences in our study.

UPGMA dendrogram (Fig. 4) clustered species into three main groups based on habitat type where most common species tend to be clustered in the second (II) group. It should be underlined that all groups consist of different species of different genera, suggesting no specific habitat preferences at the generic level. Two other groups (I, III) included more of those species with lower and/or rare occurrences. There are two species in the first group (I) while group III is divided into two subgroups. Of the two species in group I, D. stevensoni has a wide geographical distribution found from lentic to lotic habitats. In contrast, I. hartmanni is one of the rarest species and there is not much information about its ecological characteristics.

We found four variables (Tw, EC, SHE, pH) effective on species occurrence while Tw was negatively but strongly correlated to the numbers of species (Tab. 4, Fig. 5). Implication of this finding suggests increasing water temperature may be responsible for gradual reduction in the numbers of species. This is probably because most species found in here were reported from relatively low to medium temperature ranges.

Three of the four most common species, except P. olivaceus, were generally found in waters with high (60–90%) Ca2+ levels (Fig. 3) when Ca2+ −range of P. olivaceus was relatively wider (30–90%) than others (Fig. 6). Calcium in the host waters is one of the most essential elements for ostracods because it is the main source of Ca2+ in the carapace (Kesling, 1951; Turpen and Angell, 1971; Rosenfeld, 1982; Majoran et al., 1999). Thereby, such a demand on Ca2+ may take attention of the species in the waters with amount of Ca2+ enough to produce CaCO3 in carapace. In contrast, since Mg2+ is relatively low in freshwater ostracod carapaces (Wansard et al., 1999; Palacios-Fest and Dettman, 2001), finding species from the water bodies with low Mg2+ concentrations may not be surprising at all. According to Meisch (2000), H. incongruens was ecologically characterized as titanoeuryplastic (occurring indifferently from 0 to >72 mg Ca2+ L−1 ranges), mesothermophilic (preferring or tending to be found between permanent and temporarily cold waters) (and/or medium temperature ranges), and oligohalophilic (?mesohalophilic) (±0.5 to ±5‰ total salt contents) while H. salina was characterized as thermoeuryplastic (with wide temperature ranges), mesopolytitanophilic (mainly occurring from 18 to >72 mg Ca2+ L−1), and mesohalophilic (± 5 to ±18‰ total salt contents). On the other hand, P. olivaceus was ecologically characterized as oligothermophilic (preferring cold waters, mainly found in cold waters), euryplastic for substrate (Nüchterlein, 1969) when I. bradyi was classified as oligothermophilic and rheoeuryplastic (found in both stagnant and flowing waters) by Nüchterlein (1969) whereas as polythermophilic (preferring “warm” waters, mainly found in “warm” waters), mesorheophilic and meso- to polytitanophilic (mainly occurring at >72 mg Ca2+ L−1) by Vesper (1975).

Some of these ecological characteristics do not match with our findings. For example, we found H. incongruens in a variety of habitats (Tab. 2) where water temperature was cold (12.9 °C) to cool (21 °C). However, the species has already been reported from waters with much higher temperature ranges up to 32 °C (Külköylüoğlu et al., 2012), or even higher than 37 °C (Akdemir, pers. obs.), referring to polythermophilic characteristics of the species that can tolerate wide temperature ranges without showing any specific tendency for cold waters. Additionally, occurrence of H. incongruens in deeper parts of the lakes may not be common (Akdemir and Külköylüoğlu, 2014; Akdemir et al., 2016), pointing that shallow water bodies may be better places for the species. Similarly, Ca2+-range of the species was found up to 119 Ca2+ ppm supporting “titanoeuryplastic” characteristics (this study). In terms of salinity contents, the species was reported from oligohalophilic or slightly higher ranges during the present study but Mezquita et al. (1999a, b) reported the species in the waters of Iberian Peninsula where electrical conductivity (referring to salinity) was reaching about 3320 µS cm−1, indicating eu-polyhaline ranges (see details in Külköylüoğlu, 2013). Another species of the same genus, H. salina showed wider ranges of temperature (up to 22 °C) and salinity (EC = 2281 µS cm−1) than H. incongruens, supporting earlier ecological characterization stated by Meisch (2000). Supporting evidence was also provided by Mischke et al. (2012) who reported that H. salina in hyperarid habitats did not display particular habitat preferences for the waters dominated by anion and/or cations in Israel and Jordan where the species did show tolerances to high salinity ranges.

The next two most common species, P. olivaceus and I. bradyi were actually reported with higher temperature and salinity ranges than suggested before. Of which, P. olivaceus was reported from 17–107 mg Ca2+ ranges (titanoeuryplastic, but mainly polytitanophilic) while I. bradyi was found between 25–103 mg Ca2+ ranges (titanoeuryplastic). These results also correspond with higher tolerance ranges of these species than most other species indicated above. According to Meisch (2000), species with wide ecological tolerance might probably be due to their “general purpose genotype” characteristics. Although this approach deserves considerable credits, it refers species occurrences in different (or similar) habitats and environmental conditions. Besides, due to lack studies (e.g., see Havel et al., 1990; Yin et al., 1999) on the relationship between genotype and environmental factors, we need more solid evidences to support this view. Both laboratory (Yu et al., 2009, Külköylüoğlu pers. obs.) and field studies (Schneider et al., 2016; Külköylüoğlu et al., 2017; Yavuzatmaca et al., 2017b) showed that most (if not all) ostracod species do have higher ecological tolerance ranges than what we know previously. Hence, at the moment, ecological knowledge about individual species tolerance (and optimum estimates) ranges is not promising to come up with a general conclusion. It is however true that a few species may have relatively narrow distributional ranges in particular habitats where ecological conditions are suitable for the species.

Like the common species hitherto discussed, some other species with low frequency of occurrences can also be considered for discussion. For example, L. inopinata has generally been encountered from lakes, ponds, swamps and ditches but also known from flowing waters. Baltanás and Geiger (1998) argued that habitat (referring to environmental conditions) preferences of this species coincided with genetically similar individuals whose body size would be larger in stagnant (lentic) or less fluctuating waters than those found in oligo-mesohaline and fluctuating (lotic) waters. Yin et al. (2001) working on living L. inopinata specimens collected from more than 50 lakes and small water bodies in the Tibetan Plateau reported that Mg2+ was an important role on determining the body length of the species which increased until Mg2+ level reached up to 0.12 g L−1. In contrast, when the level was higher than 0.12 g L−1, body size was not increased. We reported this species from five different sites of lakes, ponds and reservoirs during this study within a wide EC ranging from 367 to 1572 µS cm−1 where percent Ca2+ concentration was relatively lower than Mg2+. In general, our findings agree with the ecological characterization of Meisch (2000) as that species is polythermophilic, titanoeuryplastic (occurs also in waters with poor Ca2+ concentrations) and mesohalophilic. In our case, since the species were collected from shallow littoral zones of those lentic water bodies, we did not observe such size difference among adults. Additionally, it is also important to mention that L. inopinata seems to be found in large bodied natural habitats more than artificial habitats. For example, while 15 species were found from several different habitat types including troughs, L. inopinata was among those eight other species not found from troughs. The species was clustered together with P. kraepelini in group III of UPGMA dendrogram. Like L. inopinata, P. kraepelini is also known as a typical lake form (or lake-like lentic habitats). Therefore, finding these two species in the same clustering group is not surprising, and may suggest their common habitat preferences. Although CCA diagram (Fig. 5) exhibited that L. inopinata was located nearby the arrow of redox potential (SHE) along with P. fontinalis, these two species were never seen together in any of the sampling sites. Indeed, the latter species was only found from troughs during our study. Meisch (2000) stated that P. fontinalis was more strongly related to permanently cold waters than its conspecific P. olivaceus discussed above. Ecologically, P. fontinalis was defined as coldstenothermal, polyrheophilic, polytitanophilic (Nüchterlein, 1969), and stygophilic (Meisch, 2000). Akdemir and Külköylüoğlu (in review) provided supportive evidence about these characteristics, underlining that P. fontinalis had low tolerance values for dissolved oxygen in the stream, pond and spring waters of Hatay region in Turkey.

According to CCA diagram (Fig. 5), the three least common species (P. zenkeri, P. villosa and P. variegata) were located on the opposite sites of the variables (arrows), suggesting that these variables may not be strongly effective on these species or there was a negative correlation. One of the most morphologically shared characteristics of these species is the presence of swimming setae on second antenna (except P. zenkeri whose setae are medium size). Such characters may help species moving among the aquatic plants in slow flowing and/or shallow water bodies. Ecologically, these species also illustrate common characteristics as being oligothermophilic, mesorheophilic and polytitanophilic while P. variegata may have higher tolerance ranges than the other two species. We found the third species of the genus Potamocypris, P. fulva, located far away from the center of CCA in opposite to the arrows. Unlike others, P. fulva showed relatively low occurrence frequencies from trough and streams. The species was previously reported from caves as well (Meisch, 2000). Based on these reports, one may consider that species would probably prefer a few types of habitats with limited distribution. The species did not show high levels of ecological tolerances (Tab. 3) to different environmental variables. Due to lack of ecological knowledge, a general characterization about its habitat preferences may not be outlined at the moment; however, our results are in accordance with those of previous studies (Meisch, 2000; Külköylüoğlu, 2013; Uçak et al., 2014; Yavuzatmaca et al., 2017a, b) about ecological characteristics of this species.

Overall, results of this study clearly illustrate the fact that we still have very limited ecological knowledge about species habitat preferences. Also, we are aware of the fact that our sampling was conducted within a couple of days which may limit to make general conclusions about species’ habitat preferences. However, our results strongly suggest that rare and/or endemic ostracods would probably provide better explanations about habitat requirements of ostracods. Thus, detailed and extensive field and laboratory studies on ecology of these species can answer several different questions about the habitat preferences

thumbnail Fig. 6

Distribution of sampling sites among three major cations (a) (Na+, Mg2+, Ca2+) and (b) anions (F−, SO42−, Cl−). Water quality measurements indicated low (very low Na+, low Mg2+, and high Ca2+) anions and relatively low cation (not significant F−, very low Cl−, and low SO42−) values.

Acknowledgements

We would like to thank Dr. Randy Gibson (Texas Aquatic Resources Center, U. S. Fish and Wildlife Service) for his suggestions and help on the final part of the manuscript. Also, we would like to thank Ozan Yılmaz and Meriç Tanyeri for their help during sampling. Thanks are given to Drs. Nusret KARAKAYA (Abant İzzet Baysal University) for his help on major ion analyses, and Benjamin F. Schwartz (Texas State University) for him to provide us permission to use JMP® Pro 13.0.0 (64-bit) program. This study was supported by TÜBİTAK (Project no. 213O172).

References

  • Akdemir D, Külköylüoğlu O. 2014. Preliminary study on distribution, diversity and ecological characteristics of nonmarine Ostracoda (Crustacea) from Erzincan region (Turkey). Turk J Zool 38: 421–431, https://doi.org/10.3906/zoo-1301-16 [CrossRef] [Google Scholar]
  • Akdemir D, Külköylüoğlu O, Yavuzatmaca M, Sarı N. 2016. Freshwater Ostracods (Crustacea) of Gaziantep (Turkey) and their habitat preferences according to movement ability. Fundam Appl Limnol 187/4: 307–314, https://doi.org/10.1127/fal/2016/0665 [Google Scholar]
  • Baltanás A, Geiger W. 1998. Intraspecific morphological variability: morphometry of valve outlines. In: Martens K, ed. Sex and parthenogenesis. Evolutionary ecology of reproductive modes in non-marine ostracods. Leiden (Netherlands): Backhuys Publishers, pp. 127–142. [Google Scholar]
  • Benson RH. 1972. The Bradleya problem, with descriptions of two new psychrospheric ostracode genera, Agrenocythere and Poseidonamicus (Ostracoda: Crustacea). Smithson Contrib Paleobiol 12: 1–138. [CrossRef] [Google Scholar]
  • Birks HJB, Line JM, Juggins S, Stevenson AC, ter Braak CJF. 1990. Diatoms and pH reconstruction. Philos Trans R Soc 327: 263–278, https://doi.org/10.1098/rstb.1990.0062 [CrossRef] [Google Scholar]
  • Brandão SM, Yasuhara M. 2013. Challenging deep-sea cosmopolitanism: taxonomic re-evaluation and biogeography of “Cythere dasyderma Brady, 1880” (Ostracoda). J Micropalaeontol 32: 109–122, https://doi.org/10.1144/jmpaleo2012-009 [CrossRef] [Google Scholar]
  • Chu C, Jones NE, Piggott AR, Buttle JM. 2009. Evaluation of a simple method to classify the thermal characteristics of streams using a nomogram of daily maximum air and water temperatures. N Am J Fish Manag 29: 1605–1619. DOI:10.1577/M08-251.1 [CrossRef] [Google Scholar]
  • Gülen D. 1977. Contribution to the knowledge of the freshwater Ostracoda fauna of Turkey. Istanbul Univ Fen Fak Mecm Ser B 42: 101–106. [Google Scholar]
  • Gülen D. 1985a. The species and distribution of the group Podocopa (Ostracoda-Crustacea) in the freshwaters of western Anatolia. Istanbul Univ Fen Fak Mecm Ser B 42 50: 81–86. [Google Scholar]
  • Gülen D. 1985b. Bisexual Ostracoda (Crustacea) populations in Anatolia. Istanbul Univ Fen Fak Mecm Ser B 42 50: 65–80. [Google Scholar]
  • Gülen D, Altınsaçlı S. 1999. The Ostracoda (Crustacea) fauna of Sakarya river basin. Geosound 35: 69–84. [Google Scholar]
  • Hartmann G, Hiller D. 1977. Beitrag zur Kenntis der Ostracodenfauna des Harzes und seines nördlichen Vorlandes (unter besonderer Berücksichtigung des Männchens von Candona candida). Nat Wiss Ver Goslar 125: 99–116. [Google Scholar]
  • Havel HE, Hebert PDN, Delorme LD. 1990. Genetics of sexual Ostracoda from a low Arctic site. J Evol Biol 3: 65–84. [CrossRef] [Google Scholar]
  • Heino J, Grönroos M. 2017. Exploring species and site contributions to beta diversity in stream insect assemblages. Oecologia 183: 151–160, DOI:10.1007/s00442-016-3754-7 [CrossRef] [PubMed] [Google Scholar]
  • Hiller D. 1972. Untersuchungen zur Biologie und zur Ökologie limnischer Ostracoden aus der Umgebung von Hamburg. Arch Hydrobiol Suppl 40: 400–497. [Google Scholar]
  • Iglikowska A, Namiotko T. 2012. The impact of environmental factors on diversity of Ostracoda in freshwater habitats of subarctic and temperate Europe. Ann Zool Fenn 49: 193–218. [CrossRef] [Google Scholar]
  • Juggins S. 2003. Software for ecological and palaeoecological data analysis and visualization, C2 user guide. Newcastle-Upon-Tyne: University of Newcastle. [Google Scholar]
  • Karanovic I. 2012. Recent freshwater Ostracods of the world. Heidelberg (Berlin): Springer-Verlag, 608 p. [Google Scholar]
  • Kesling RV. 1951. The morphology of ostracod molt stages. Ill Biol Monogr 21: 1–126. [Google Scholar]
  • Kovach W. 1998. Multi-variate statistical package, ver. 3.1. Pentraeth (UK): Kovach Computer Services. [Google Scholar]
  • Külköylüoğlu O. 2003. A new report on and the loss of Scottia pseudobrowniana Kempf, 1971 (Ostracoda) from a limnocrene spring in Bolu, Turkey. Crustaceana 76: 257–268, https://doi.org/10.1163/156854003765911667 [CrossRef] [Google Scholar]
  • Külköylüoğlu O. 2013. Diversity, distribution and ecology of nonmarine Ostracoda (Crustacea) in Turkey: application of pseudorichness and cosmoecious species concepts. Recent Res Dev Ecol 4: 1–18. [Google Scholar]
  • Külköylüoğlu O, Meisch C, Rust WR. 2003. A new genus (Thermopsis thermophila n. gen.) of Ostracoda (Crustacea) from hot springs of western North America. Hydrobiologia 499: 113–123, https://doi.org/10.1023/A:102630851 [CrossRef] [Google Scholar]
  • Külköylüoğlu O, Sarı N, Akdemir D, Yavuzatmaca M, Altınbağ C. 2012. Distribution of sexual and asexual Ostracoda (Crustacea) from different altitudinal ranges in the Ordu region of Turkey: testing the Rapoport rule. High Alt Med Biol 13/2: 126–136, https://doi.org/10.1089/ham.2011.1111 [Google Scholar]
  • Külköylüoğlu O, Yavuzatmaca M, Tanyeri M, Yılmaz O. 2017. Ostracoda (Crustacea) species composition and environmental correlates in different aquatic habitats of the Zonguldak and Bartın regions (Turkey). Turk J Zool 41: 686–695, https://doi.org/10.3906/zoo-1512-36 [CrossRef] [Google Scholar]
  • Laprida C, Díaz A, Ratto N. 2006. Ostracods (Crustacea) from thermal waters, southern Altiplano, Argentina. Micropaleontology 52: 177–188. [CrossRef] [Google Scholar]
  • Majoran S, Agrenius S, Dwyer GS. 1999. The effect of temperature on the geochemical composition of the valves of the ostracod species Krithe praetexta praetexta. Geosound 35: 93–113. [Google Scholar]
  • Meisch C. 2000. Freshwater Ostracoda of Western and Central Europe (Süswasserfauna von Mitteleuropa), Heidelberg: Spektrum Akademischer Verlag, Vol. 8, I–xii, 522 p. [Google Scholar]
  • Mezquita F, Tapia G, Roca JR. 1999a. Ostracoda from springs on the eastern Iberian Peninsula: ecology, biogeography and palaeolimnological implications. Palaeogeogr Palaeoclim Palaeoecol 148: 65–85. [CrossRef] [Google Scholar]
  • Mezquita F, Hernandez R, Rueda J. 1999b. Ecology and distribution of ostracods in a polluted Mediterranean river. Palaeogeogr Palaeoclim Palaeoecol 148: 87–103. [CrossRef] [Google Scholar]
  • Mischke S, Herzschuh U, Massmann G, Zhang C. 2007. An ostracod-conductivity transfer function for Tibetan lakes. J Paleolimnol 38: 509–524, https://doi.org/10.1007/s10933-006-9087-5 [CrossRef] [Google Scholar]
  • Mischke S, Ginat H, Al-Saqarat B, Almogi-Labin A. 2012. Ostracods from water bodies in hyperarid Israel and Jordan as habitat and water chemistry indicators. Ecol Indic 14: 87–99. [CrossRef] [Google Scholar]
  • Nüchterlein H. 1969. Freshwater Ostracods from Franconia: a contribution to the knowledge of systematic and ecology of ostracoda. Int Rev Ges Hydrobiol 54: 223–287. [Google Scholar]
  • Olivero-Sheldon A, Jospe A. Anderson MG. 2014. Northeast lake and pond classification system. In: The nature conservancy, Eastern Conservation Science, Boston (MA): Eastern Regional Office, 55 p. [Google Scholar]
  • Palacios-Fest MR, Dettman DL. 2001. Temperature controls monthly variation in ostracode valve Mg/Ca: Cypridopsis vidua from a small lake in Sonora, Mexico. Geochim Cosmochim Acta 65: 2499–2508. [CrossRef] [Google Scholar]
  • Pinto RL. 2013. Ostracoda from an extreme high-altitude volcanic lake in South America. Nat sicil 37: 283–285. [Google Scholar]
  • Rosenfeld A. 1982. The secretion process of the ostracod carapace. In: Bate RH, Robinson E, Sheppard LM, eds. Fossil and recent ostracods. Chichester (UK): Ellis Horwood Limited, pp. 12–24. [Google Scholar]
  • Ruban V, Lópes-Sánchez JF, Pardo P, Rauret G, Muntau H, Quevauviller PH. 1999. Selection and evaluation of sequential extraction procedures for the determination of phosphorus forms in lake sediment. J Environ Monit 1: 51–56, http://dx.doi.org/10.1039/A807778I. [CrossRef] [PubMed] [Google Scholar]
  • Schneider A, Wetterich S, Schirrmeister L, Herzschuh U, Meyer H, Pestryakova LA. 2016. Freshwater ostracods (Crustacea) and environmental variability of polygon ponds in the tundra of the Indigirka Lowland, north-east Siberia. Polar Res 35: 1–22, https://doi.org/10.3402/polar.v35.25225 [CrossRef] [Google Scholar]
  • Seaby RM, Henderson PA. 2006. Species Diversity and Richness Version 4. England (Lymington): Pisces Conservation Ltd. [Google Scholar]
  • Seaby RM, Henderson PA. 2007. Community Analyses Package (CAP 4.1.3.). England (Lymington): Pisces Conservation Ltd. [Google Scholar]
  • SPSS. 2008. SPSS Inc. Released 2008. SPSS Statistics for Windows, Version 17.0. Chicago: SPSS Inc. [Google Scholar]
  • ter Braak CJF. 1995. Ordination. In: Jongman RHG, ter Braak CJF, Van Tongeren OFR, eds. Data analysis in community and landscape ecology, Cambridge: Cambridge University Press, pp. 91–173. [Google Scholar]
  • ter Braak CJF, Barendregt JG. 1986. Weighted averaging of species indicator values: its efficiency in environmental calibration. Math Biosci 78: 57–72, https://doi.org/10.1016/0025-5564(86)90031-3 [CrossRef] [Google Scholar]
  • ter Braak CJF, Šmilauer P. 2002. CANOCO Reference Manual and CanoDraw for Windows User’s Guide: Software for Canonical Community Ordination (version 4.5). Ithaca NY (USA): Microcomputer Power, 500 p. [Google Scholar]
  • Turpen JB, Angell RW. 1971. Aspects of molting and calcification in the ostracod Heterocypris. Biol Bull 140: 331–338. [CrossRef] [Google Scholar]
  • Uçak S, Külköylüoğlu O, Akdemir D, Başak E. 2014. Distribution, diversity and ecological characteristics of freshwater Ostracoda (Crustacea) in wetland sites of the Ankara region, Turkey. Wetlands 34: 309–324, https://doi.org/10.1007/s13157-013-0499-5 [CrossRef] [Google Scholar]
  • Van der Meeren T, Almendinger JE, Ito E, Martens K. 2010. The ecology of ostracodes (Ostracoda, Crustacea) in western Mongolia. Hydrobiologia 641: 253–273, http://dx.doi.org/10.1007/s10750-010-0089-y [CrossRef] [Google Scholar]
  • Vesper B. 1975. Ein Beitrag zur Ostracodenfauna Schleswig-Holsteins. Mitt Hamb Zool Mus Inst 2: 97–108. [Google Scholar]
  • Wansard G, Mezquita F, Roca JR. 1999. Experimental determination of strontium and magnesium partitioning in calcite of the freshwater ostracod Herpetocypris intermedia. Arch Hydrobiol 145: 237–253. [CrossRef] [Google Scholar]
  • Yavuzatmaca M, Külköylüoğlu O, Yılmaz O, Akdemir D. 2017a. On the relationship of ostracod species (Crustacea) to shallow water ion and sediment phosphate concentration across different elevational range (Sinop, Turkey). Turk J Fish Aquat Sci 17: 1333–1346, DOI:10.4194/1303-2712-v17-6-40 [Google Scholar]
  • Yavuzatmaca M, Külköylüoğlu O, Yılmaz O. 2017b. Estimating distributional patterns of non-marine Ostracoda (Crustacea) and habitat suitability in the Burdur province (Turkey). Limnologica 62: 19–33, https://doi.org/10.1016/j.limno.2016.09.006 [CrossRef] [Google Scholar]
  • Yin Y, Geiger W, Martens K. 1999. Effects of genotype and environment on phenotypic variability in Limnocythere inopinata (Crustacea: Ostracoda). Hydrobiologia 400: 85–114. [CrossRef] [Google Scholar]
  • Yin Y, Li W, Yang X, Wang S, Li S, Xia W. 2001. Morphological responses of Limnocythere inopinata (Ostracoda) to hydrochemical environment factors. Sci China Ser D 44: 316–323. [CrossRef] [Google Scholar]
  • Yu N, Chen S, Li E, Chen J, Chen L. 2009. Tolerance of Physocypria kraepelini (Crustacea, Ostracoda) to water-borne ammonia, phosphate and pH value. J Environ Sci (China) 21: 1575–1580. [Google Scholar]

Cite this article as: Külköylüoğlu O, Yavuzatmaca M, Akdemir D, Çelen E, Dalkıran N. 2018. Ecological classification of the freshwater Ostracoda (Crustacea) based on physicochemical properties of waters and habitat preferences. Ann. Limnol. - Int. J. Lim. 54: 26

All Tables

Table 1

Mean, maximum, minimum and standard deviations (SdDev) of the environmental variables reported from sampling sites are shown. Higher values of deviations more than the mean values for those variables are italicized. Abbreviations: TPh (total phosphate), InPh (inorganic phosphate), OrPh (organic phosphate). Other abbreviations are provided in materials and methods section.

In the text
Table 2

Distribution of numbers of species (NuSpp) are shown from 11 different habitat types. Numbers of habitat type (NuHabtype) indicate numbers of samplings from that of particular habitats. For example, three samplings were done from three different lakes with two species. Two well samples are not shown in this table due to lack of ostracods from these two sites. New reports are shown in bold. Abbreviations: CC, (Candona candida); CN, (C. neglecta); COP, (Cypria ophtalmica); CV, (Cypridopsis vidua); DS, (Darwinula stevensoni); HI, (Heterocypris incongruens); HAS, (H. salina); HR, (Herpetocypris reptans); HC, (H. chevreuxi); IBR, (Ilyocypris bradyi); IG, (I. gibba); IH, (I. hartmanni); LI, (Limnocythere inopinata); PK, (Physocypria kraepelini); PFU, (Potamocypris fulva); PP, (P. pallida); PU, (P. unicaudata); PV, (P. variegata); PVI, (P. villosa); PZE, (Prionocypris zenkeri); PFO, (Psychrodromus fontinalis); PO, (P. olivaceus); TC, (Trajancypris clavata).

In the text
Table 3

Optimum (Opt) and tolerance (Tol) values of 12 most abundant species occurred more than three times from different habitats. Abbreviations: Numb, numbers of occurrences; Max, maximum numbers of individuals; N2, Hill’s coefficient. Other abbreviations are given in Materials and Methods.

In the text
Table 4

Summary table of CCA results.

In the text

All Figures

thumbnail Fig. 1

Sampling sites of 121 different sites in Kütahya, Turkey.
In the text
thumbnail Fig. 2

Occurrence of H. incongruens (a) and H. salina (b) in waters with major cations (Mg2+, Ca2+ and Na+ + K+). Values are in percentage.
In the text
thumbnail Fig. 3

Occurrence of (a) P. olivaceus and I. bradyi (b) in waters with major cations (Mg2+, Ca2+ and Na+ + K+). Values are in percentage.
In the text
thumbnail Fig. 4

UPGMA dendrogram shows clustering relationships among 16 species within three main groups (I–III).
In the text
thumbnail Fig. 5

(a) CaCA diagram shows distribution of 16 species and 6 environmental vairables measured in Kütahya. Species abbreviations are given in Table 2, (b) CbCA diagram shows distribution of sampling sites with species occurred three or more times in Kütahya.
In the text
thumbnail Fig. 6

Distribution of sampling sites among three major cations (a) (Na+, Mg2+, Ca2+) and (b) anions (F−, SO42−, Cl−). Water quality measurements indicated low (very low Na+, low Mg2+, and high Ca2+) anions and relatively low cation (not significant F−, very low Cl−, and low SO42−) values.
In the text

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