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Data Descriptor

Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands

1
Faculty of Biology, Shenzhen MSU-BIT University, 1 International University Park Road, Shenzhen 518172, China
2
Faculty of Biology, Lomonosov Moscow State University, Leninskiye Gory 1, 119991 Moscow, Russia
3
Faculty of Sciences, Penza State University, Krasnaya Street 40, 440026 Penza, Russia
4
Department of Ecology, Institute of Biology and Biomedicine, Lobachevsky State University of Nizhny Novgorod, 23 Prospekt Gagarina, 603022 Nizhny Novgorod, Russia
*
Author to whom correspondence should be addressed.
Data 2023, 8(11), 173; https://doi.org/10.3390/data8110173
Submission received: 21 September 2023 / Revised: 30 October 2023 / Accepted: 3 November 2023 / Published: 17 November 2023
(This article belongs to the Special Issue Data Science in Invertebrate)

Abstract

:
Testate amoebae are unicellular eukaryotic organisms covered with an external skeleton called a shell. They are an important component of many terrestrial ecosystems, especially peatlands, where they can be preserved in peat deposits and used as a proxy of surface wetness in paleoecological reconstructions. Here, we represent a database from a vast but poorly studied region of the Western Siberia Lowland containing information on TA occurrences in relation to substrate moisture and WTD. The dataset includes 88 species from 32 genera, with 2181 incidences and 21,562 counted individuals. All samples were collected in oligotrophic peatlands and prepared using the method of wet sieving with a subsequent sedimentation of aqueous suspensions. This database contributes to the understanding of the distribution of testate amoebae and can be further used in large-scale investigations.
Dataset License: CC-BY 4.0

1. Summary

Testate amoebae (TA) are a large polyphyletic group of microorganisms with a complicated systematic position that regularly renews [1,2,3]. They are characterized by the presence of a rigid external cell cover called a shell. Over the past 200 years of investigations, about 2000 species have been described. Most of them are freshwater, but they are widely observed in almost all types of terrestrial ecosystems [4].
TA are the most abundant and diverse component of microbial communities in peatlands [5] and can constitute up to 50% of the total microbial biomass [6]. They include bacterivorous, mixotrophic and even predatory organisms and might form complex multilevel trophic chains [7]. TA are characterized by a unique set of features such as a worldwide distribution, diverse and decay-resistant shells, high sensitivity and quick responses to environmental changes that make them useful bioindicators of past and present conditions [8,9]. The most important environmental factor affects the species structure of TA assemblages is substrate moisture, as has been demonstrated in numerous studies [10,11,12,13]. In particular, the surface moisture in mire ecosystems greatly depends on the water table depth (WTD), which varies along the microtopography determining TA distribution [14,15]. Therefore, the provided dataset contains information on TA occurrences in relation to substrate moisture and WTD.
Boreal peatlands are widely distributed in Northern America, Northern Europe and Western Siberia. However, the study of the distribution of testate amoebae in these regions is extremely uneven. For example, the vast Siberian regions remain a blank spot on the map [16,17,18,19,20,21,22]. This dataset description is based on testate amoebae data published in Mazei et al., 2017 [23]. Thus, the main aim of this contribution is to provide a dataset on the distribution of testate amoebae in relation to surface wetness and related characteristics in peatlands in the Western Siberia Lowland (WSL).

2. Data Description

2.1. Dataset Description

The dataset is organized according to GBIF requirements for “Occurrence Data” type [24], and it follows Darwin Core standard of Biodiversity Information Standards (historical “TDWG”—Taxonomic Databases Working Group) and uses terms of “Occurrence” [25]. In the dataset, each observation includes basic information on the location (latitude/longitude), date of observation, name of the observer, substrate moisture and a comment on the sampling point location (microtopography of the sampling point). The coordinates were determined in situ using a GPS device (Table 1).

2.2. Species Diversity and Community Structure in the Dataset

The dataset presents information on 88 species of testate amoebae belonging to 14 families except for incertae sedis and 32 genera found in the WSL (Tyumen region and Yamalo-Nenets Autonomous okrug) (Table 2). The total number of occurrences was 2181 (localization of an individual of the same species, as well as the total number of samples reviewed), and the number of counted individuals was 21,562. The most diverse families in terms of genus number were Hyalospheniidae (6), Centropyxidae (4) and incertae sedis (5—genera Ellipsopyxis, Paraquadrula, Physochila, Tracheleuglypha and Trigonopyxis). The greatest number of species were observed in the families Euglyphidae (16), Centropyxidae (15) and Hyalospheniidae (11).
The most abundant species in the Western Siberia peatlands is Trinema lineare (25.4% of the total individual counts). The following species are also abundant and constitute more than 1%: Corythion dubium (7.26%), Assulina muscorum (6.46%), Euglypha laevis (5.59%), Centropyxis aerophila (5.29%), Trinema enchelys (3.89%), Phryganella hemisphaerica (3.41%), Trinema complanatum (2.98%), Euglypha rotunda (2.53%), Nebela tincta (2.32%), Lesquereusia epistomium (1.93%), Centropyxis aerophila sphangicola (1.84%), Corythion orbicularis (1.70%), Cryptodifflugia oviformis (1.70%), Cyclopyxis arcelloides (1.54%), Assulina seminulum (1.47%), Bullinularia indica (1.37%), Euglypha tuberculata (1.32%), Euglypha strigosa glabra (1.3%), Arcella rotundata (1.28%), Trigonopyxis arcula (1.16%), Archerella flavum (1.09%) and Centropyxis orbicularis (1.02%). The other 66 species (Table 3) were less abundant than 1% of the total counts. T. lineare is the most common species (found in 94% of all sampling points). The following species have been encountered in more than 20% of samples: A. muscorum (83%), E. laevis (74%), C. dubium (66%), C. aerophila (52%), T. complanatum (52%), E. tuberculata (51%), P. hemisphaerica (50%), T. enchelys (50%), E. strigosa glabra (48%), C. orbicularis (46%), B. indica (46%), N. tincta (36%), C. oviformis (32%), Euglypha strigosa (32%), A. flavum (31%), T. arcula (29%), Galeripora catinus (29%), Euglypha compressa (29%), A. seminulum (28%), E. rotunda (26%), C. aerophila sphangicola (26%), Galeripora arenaria (22%), Euglypha ciliata (22%), Alabasta militaris (20%), Nebela collaris (20%). Centropyxis sylvatica minor, Paraquadrula irregularis, Arcella megastoma, Centropyxis constricta, Euglypha compressa glabra, Padaungiella lageniformis, Padaungiella wailesi, Plagiopyxis minuta, Planocarina marginata, Sphenoderia lenta and Trinema grandis were found in a single sample and are therefore considered rare. The other 52 species were found in less than 20% but more than 1% of samples.

3. Methods

3.1. Study Area

The materials for the study were collected in six study areas along the latitudinal gradient at the WSL (Figure 1) in July 2008 and June 2009. All sampling sites were represented by various types of mire ecosystems located in the geographical range of 58° to 66° N and 68° to 79° E.
Study area 1 (N 58.79°, E 68.79°) is located on the east bank of the Irtysh River and was represented by two mires. Both of them are forested peatlands (‘ryam’) with Pinus sibirica or Betula sp. in the tree stand. The shrub cover is dominated by Rhododendron tomentosum and Rubus chamaemorus; the moss layer is formed by Sphagnum species, Pleurozium schreberi, Dicranum spp., Cladonia lichens, Hylocomnium splendens and Polytrichum commune.
Study area 2 (N 58.23°, E 68.22°) is located further south on the east bank of the Irtysh River and is represented by two mires. The vegetation cover is similar to the previous study site, with a denser Betula sp. canopy, the presence of Rhododendron tomentosum with Andromeda polifolia and sedges and a moss cover primarily formed by Sphagnum mosses.
Study area 3 (N 66.4°, E 79.02°) is located in the far north of the WSL, near the eastern bank of the Pur River. This site is an open tundra peatland with low vegetation of Betula nana, Rhododendron tomentosum and Oxycoccus palustris underlined by Sphagnum, Cladonia and Pleurozium schreberi.
Study area 4 (N 65.58°, E 77.58°) is located to the west of the Pur River in the vicinity of the town of Urengoi. It includes three sites: (1) an open permafrost peatland with Betula nana, Salix, Rhododendron tomentosum, Rubus chamaemorus and Sphagnum species and brown mosses including Polytrichum strictum and Polytrichum commune; (2) a lake-margin mat with dominated Eriophorum spp. with Andromeda polifolia and Rhododendron tomentosum and Sphagnum in the moss cover; (3) a shrub-dominated peatland with Betula, Salix, sedges, Polytrichum commune and Sphagnum.
Study area 5 (N 60.12°, E 71.50°) is in the middle taiga zone in the center of the WSL, south of the River Ob. The petaland is covered by Pinus sylvestris, Rhododendron tomentosum, Chamaedaphne calyculata, Rubus chamaemorus and Sphagnum.
Four sites were chosen in Study area 6 (N 58.23°, E 68.22°) on the east bank of the Irtysh River in the vicinity of the town of Tobolsk. Two of the peatlands are ‘ryams’ with Pinus, abundant Rhododendron tomentosum and Andromeda polifolia among shrubs and Pleurozium schreberi and sparse Sphagnum mosses. Two other peatlands are sedge-dominated, with an extensive cover of Carex species, Oxycoccus palustris, Sphagnum mosses and rare Betula trees.

3.2. Sample Collection and Treatment

Samples for the study were collected in an attempt to cover the diversity of habitat types in each study site, taking into account the microtopography of peatland, i.e., hummocks, lawns and hollows. The sampled substrates represented either mosses (if present) or plant litter (if mosses are not dominant or absent) of approximately 5 cm depth and 25 cm3 volume. Each sample was carefully removed and immediately placed in sealed plastic bags to avoid contamination and moisture loss. Further, it was refrigerated as soon as possible at 5 °C until laboratory processing and analyses to avoid major post-sampling changes in the community structure [26]. WTD was measured in situ during fieldwork. Holes for WTD were made at the sampling point and settled for 30 minutes before the measurement using a ruler.
Samples were divided into two parts in the laboratory. One of them was used for testate amoebae extraction following the method based on suspension in water, physical agitation and subsequent sedimentation described by Mazei et al. (2011) [17]. Samples (1 cm3) were soaked in water for 24 hours, stirred for 30 minutes and filtered through a 500 μm mesh. The suspension was left to settle for the other 24 hours and the supernatant was decanted off. No back-filtering step was used as this leads to the loss of small taxa and a relatively large mesh size (500 μm) was used to retain the largest tests [20,27]. Samples were examined using a light microscope and shells were identified to the highest possible taxonomic resolution at 400× and 200× magnification using Mazei and Tsyganov (2006) until a minimum count of 150 shells in each sample [28]. The taxonomic classification at the genus level is based on the revisions of Kosakyan et al. (2016a, b) [2] as summarized in Tsyganov et al. (2016) [29], González-Miguéns et al. (2021) [3] and González-Miguéns et al. (2022) [30].
Moisture content was determined from the other part of the sample. Wet subsamples were weighed and placed in an oven at 105 °C for eight hours. Further, samples were cooled in the desiccator to room temperature and then weighed again. Percentage moisture was calculated based on the difference between the wet and dry sample weights.

Author Contributions

Conceptualization and methodology—Y.M.; Fieldwork—Y.M., N.M., A.T., V.C. and K.B.; Microscopy—V.C., S.Y. and K.B.; database construction—X.G., J.S., B.Y., D.S., N.S. and A.E.; writing—original draft preparation, D.S. and K.B.; writing—review and editing, A.E., A.T., N.K. and Y.M. All authors have read and agreed to the published version of the manuscript.

Funding

The work was supported by the Shenzhen Natural Science Foundation: 20200828181231001 and Russian Science Foundation (19-14-00102).

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are openly available in GBIF at https://doi.org/10.15468/avvq78. accessed on 15 July 2020.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. Map of the study areas. Numbers are study areas described in Methods.
Figure 1. Map of the study areas. Numbers are study areas described in Methods.
Data 08 00173 g001
Table 1. Description of the dataset.
Table 1. Description of the dataset.
Column LabelColumn Description
eventIDAn identifier for the set of information associated with an Event
occurrenceIDAn identifier for the occurrence (as opposed to a particular digital record of the occurrence)
basisOfRecordThe specific nature of the data record
eventDateThe date when material was collected or the sampling period
KingdomThe full scientific name of the Kingdom in which the taxon is classified
scientificNameThe full scientific name, including the genus name and the lowest level of taxonomic rank with the authority
FamilyThe full scientific name of the Family in which the taxon is classified
ClassThe full scientific name of the Class in which the taxon is classified
taxonRankThe taxonomic rank of the most specific name in the scientificName
decimalLatitudeThe geographic latitude of a location in decimal degrees
decimalLongitudeThe geographic longitude of a location in decimal degrees
countryCodeThe standard code for the country in which the location is found
individualCountThe number of individuals present at the time of the occurrence
organismQuantityA number or enumeration value for the quantity of organisms (counted shells)
organismQuantityTypeThe type of quantification system used for the quantity of organisms
measurementTypeThe nature of the measurement, fact, characteristic, or assertion (substrate moisture)
measurementUnitThe units associated with the dwc:measurementValue (%)
measurementValueThe value of the measurement, fact, characteristic, or assertion
locationRemarksComments or notes about the dcterms:Location (microtopography)
Table 2. Species diversity of testate amoeba families in the dataset.
Table 2. Species diversity of testate amoeba families in the dataset.
FamiliesNumber of GeneraNumber of SpeciesNumber of Occurrences
Amphitremidae Poche, 19131144
Arcellidae Ehrenberg, 184329131
Assulinidae Lara et al., 200723180
Centropyxidae Jung, 1942415284
Cryptodifflugiidae Jung, 19421146
Difflugiidae Wallich, 18641350
Euglyphidae Wallich, 1864, emend. Lara et al., 2007216489
Heleoperidae Jung, 19421220
Hyalospheniidae Schultze, 1877 emend. Kosakyan and Lara, 2012611177
Incertae sedis (Class: Tubulinea)57109
Lesquereusiidae Jung, 19422348
Netzeliidae Kosakyan et al., 2016, emend. Gonzales-Miguens et al., 20212549
Phryganellidae Jung, 19421284
Sphenoderiidae Chatelain et al., 2013129
Trinematidae Hoogenraad & De Groot, 1940, emend Adl et al., 201228461
Total32882181
Table 3. Abundance (in %) and occurrences (samples) per study area of testate amoeba species from the dataset. Species names are listed in alphabetical order; study area codes are described in the Methods section. ab.—abundance; occ.—number of occurrences.
Table 3. Abundance (in %) and occurrences (samples) per study area of testate amoeba species from the dataset. Species names are listed in alphabetical order; study area codes are described in the Methods section. ab.—abundance; occ.—number of occurrences.
TaxaStudy Area
123456
ab.occ.ab.occ.ab.occ.ab.occ.ab.occ.ab.occ.
Alabasta longicollis (Penard 1890) Duckert, Blandenier, Kosakyan & Singer 20180.0000.0000.0000.0410.4520.000
Alabasta militaris (Penard 1890) Duckert, Blandenier, Kosakyan & Singer 20182.46100.6711.1880.1480.2210.000
Arcella gibbosa Penard, 18900.0000.0000.0000.0210.0000.305
Arcella hemisphaerica Perty, 18520.0000.9210.0000.1140.0000.757
Arcella rotundata Playfair, 19180.7613.9120.0000.1148.9161.147
Archerella flavum (Archer, 1877) Loeblich and Tappan, 19610.0001.5830.5920.61172.4552.1617
Assulina muscorum Greeff, 18887.191611.4105.84105.71455.0176.2530
Assulina seminulum Ehrenberg, 18480.1220.0817.74101.58260.1110.000
Awerintzewia cyclostoma Schouteden, 19060.0000.0000.0000.0210.0000.337
Bullinularia indica (Penard, 1907) Deflandre, 19530.7650.5832.95110.91280.3322.3117
Centropyxis aculeata (Ehrenberg, 1838) Stein, 18590.0610.0000.0000.0420.0000.000
Centropyxis aculeata oblonga Deflandre, 19290.0000.0000.0000.0000.0000.996
Centropyxis aerophila Deflandre, 19290.7640.0003.281011.38500.7811.239
Centropyxis aerophila sphangicola Deflandre, 19293.0482.4120.0713.08210.3320.123
Centropyxis cassis (Wallich, 1864) Deflandre, 19290.1210.0003.4160.2160.0000.000
Centropyxis constricta (Ehrenberg, 1841) Penard, 18900.0000.0000.0000.0000.0000.031
Centropyxis ecornis (Ehrenberg, 1841) Leidy, 18790.0000.0000.2610.0000.0000.185
Centropyxis gibba Deflandre, 19290.0000.0000.0000.0000.0000.907
Centropyxis orbicularis Deflandre, 19290.3535.1630.0000.0533.5651.299
Centropyxis platystoma (Penard, 1890) Deflandre, 19290.1210.0000.0000.2380.0000.154
Centropyxis sylvatica (Deflandre, 1929) Bonnet and Thomas, 19555.09112.5840.0000.0000.0000.091
Corythion dubium Taranek, 18716.90134.25516.08129.10471.8962.7912
Corythion orbicularis (Penard, 1910) Iudina, 19962.98120.5822.1082.00300.5641.0810
Cryptodifflugia oviformis Penard, 19022.5170.5820.2030.58111.4544.3919
Cyclopyxis arcelloides (Penard, 1902) Deflandre, 19291.2923.8340.0000.00011.5831.4710
Cyclopyxis eurystoma Deflandre, 19290.5840.9220.0000.0000.0000.000
Cyclopyxis kahli (Deflandre, 1929)1.2310.1710.0000.0420.0000.000
Cylindrifflugia bacillariarum (Perty, 1849) González-Miguéns et al., 20220.0000.0000.2610.0211.0030.429
Cylindrifflugia elegans (Penard, 1890) González-Miguéns et al., 20220.0002.0840.0000.0001.1130.182
Difflugia bacillifera Penard, 18900.0000.0000.7220.1660.0000.244
Difflugia globulosa Dujardin, 18370.0000.0000.0000.3580.0000.368
Difflugia penardi Cash and Hopkinson, 19090.0000.0001.0550.2891.5640.184
Ellipsopyxis pauliani Bonnet, 19650.1810.0000.2610.1980.0001.1713
Euglypha acanthophora Ehrenberg, 18410.0000.0000.0000.0210.6730.000
Euglypha capsiosa Coûteaux, 19780.0000.1710.9270.0950.1110.000
Euglypha ciliata Ehrenberg, 18480.7660.0000.2640.1980.0000.8114
Euglypha ciliata glabra Wailes, 19150.2930.3310.2010.37100.0000.183
Euglypha compressa Carter, 18641.4060.8330.1310.47180.1110.4212
Euglypha compressa glabra Wailes, 19150.0610.0000.0000.0000.0000.000
Euglypha cristata decora Jung, 19420.0000.0000.2010.0520.0000.091
Euglypha cristata Leidy, 18740.0000.0000.5220.23100.0002.589
Euglypha denticulata Brown, 19120.2930.0000.0000.0420.0000.000
Euglypha laevis (Ehrenberg, 1845) Perty, 18491.1791.7526.76126.25488.3586.8227
Euglypha rotunda Ehrenberg, 184511.93125.4971.5760.0420.0002.0110
Euglypha simplex Decloitre, 19650.0610.3310.6650.0420.0000.124
Euglypha strigosa (Ehrenberg, 1848) Leidy, 18781.0590.0001.77111.02250.0000.031
Euglypha strigosa glabra Wailes, 18980.7670.2521.90121.87330.4520.9313
Euglypha tuberculata Dujardin, 18411.2370.5021.2591.98411.8950.429
Galeripora arenaria (Greeff, 1866) González-Miguéns et al., 20210.4720.0000.0000.46110.5621.9217
Galeripora arenaria compressa (Chardez, 1957) González-Miguéns et al., 20210.5330.0000.0000.1680.0000.213
Galeripora arenaria sphagnicola (Deflandre, 1928) González-Miguéns et al., 20210.0000.0000.0710.0510.0000.000
Galeripora catinus (Penard, 1890) González-Miguéns et al., 20210.9930.5821.5770.1871.6771.6515
Galeripora discoides (Ehrenberg, 1871) González-Miguéns et al., 20210.0000.0000.0710.0000.2210.031
Galeripora megastoma (Penard, 1902) González-Miguéns et al., 20210.0000.0000.0000.0000.0000.031
Gibbocarina galeata (Penard, 1890) Kosakyan et al., 20160.0000.0000.0000.0213.5652.2520
Heleopera sphagni Leidy, 18740.0000.2510.0710.5460.0000.000
Heleopera sylvatica Penard, 18900.0000.0000.0000.0000.1111.5011
Hyalosphenia elegans Leidy, 18740.1211.0830.5910.1250.0000.000
Hyalosphenia papilio Leidy, 18740.7021.3321.0560.0421.7830.4210
Lesquereusia epistomium Penard, 19020.0610.0000.0000.0006.9056.4319
Nebela collaris (Ehrenberg, 1848) sensu Kosakyan et Gomaa, 20130.0000.0001.3180.75180.0000.062
Nebela tincta (Leidy, 1879) Awerintzew, 190610.12120.0816.30100.68150.6740.579
Netzelia oviformis (Cash, 1909) Ogden, 19790.0000.0000.0000.0000.8932.109
Netzelia wailesi (Ogden, 1980) Meisterfeld, 19840.0000.0000.0000.0000.0000.818
Padaungiella lageniformis Penard, 18900.0000.0000.0000.0000.0000.031
Padaungiella wailesi Deflandre, 19360.0000.0000.0000.0210.0000.000
Paraquadrula irregularis Wallich, 18630.0000.0000.0000.0410.0000.000
Phryganella acropodia (Hertwig & Lesser, 1874) Hopkinson, 19090.0000.3310.0000.68100.4510.000
Phryganella hemisphaerica Penard, 19025.73102.3342.89105.08432.4530.242
Physochila griseola (Penard, 1911) Jung, 19550.0001.4210.0000.0000.0001.5913
Placocista spinosa Penard, 18990.1820.0000.1310.51150.0000.214
Plagiopyxis callida Penard, 19100.0000.0000.0000.0000.0000.609
Plagiopyxis minuta Penard, 19100.0000.0000.0000.0000.0000.031
Planocarina carinata (Archer 1867) Kosakyan et al., 20160.0000.0000.0000.0530.0000.000
Planocarina marginata (Archer 1867) Kosakyan et al., 20160.0000.0000.0000.0210.0000.000
Scutiglypha scutigera (Penard, 1911) Foissner & Schiller, 20010.2320.3310.0000.0720.0000.000
Sphenoderia fissirostris Penard, 18900.0000.0000.0710.0520.0000.515
Sphenoderia lenta Schlumberger, 18450.0000.0000.0000.0210.0000.000
Tracheleuglypha dentata (Vejdovsky, 1882) Deflandre, 19280.2310.1710.4620.2130.0000.514
Trigonopyxis arcula major Chardez, 19600.3520.0000.0000.0000.0000.000
Trigonopyxis arcula Penard, 19122.6980.5022.4391.02100.8950.367
Trigonopyxis minuta Schönborn and Peschke, 19881.3540.0001.9060.8230.3310.153
Trinema complanatum Penard, 18900.6450.6741.1844.99404.1232.1018
Trinema enchelys Ehrenberg, 18380.7050.0004.72115.27380.0005.2317
Trinema grandis (Chardez, 1960) Golemansky, 19630.0000.0000.0000.0210.0000.000
Trinema lineare Penard, 189019.181539.541213.061328.065722.27825.4229
Trinema lineare truncatum Chardez, 19640.0000.0000.0000.35110.2210.062
Trinema penardi Thomas & Chardez, 19580.1210.0000.0000.1950.0000.000
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Saldaev, D.; Babeshko, K.; Chernyshov, V.; Esaulov, A.; Gu, X.; Kriuchkov, N.; Mazei, N.; Saldaeva, N.; Su, J.; Tsyganov, A.; et al. Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands. Data 2023, 8, 173. https://doi.org/10.3390/data8110173

AMA Style

Saldaev D, Babeshko K, Chernyshov V, Esaulov A, Gu X, Kriuchkov N, Mazei N, Saldaeva N, Su J, Tsyganov A, et al. Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands. Data. 2023; 8(11):173. https://doi.org/10.3390/data8110173

Chicago/Turabian Style

Saldaev, Damir, Kirill Babeshko, Viktor Chernyshov, Anton Esaulov, Xiuyuan Gu, Nikita Kriuchkov, Natalia Mazei, Nailia Saldaeva, Jiahui Su, Andrey Tsyganov, and et al. 2023. "Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands" Data 8, no. 11: 173. https://doi.org/10.3390/data8110173

APA Style

Saldaev, D., Babeshko, K., Chernyshov, V., Esaulov, A., Gu, X., Kriuchkov, N., Mazei, N., Saldaeva, N., Su, J., Tsyganov, A., Yakimov, B., Yushkovets, S., & Mazei, Y. (2023). Biodiversity of Terrestrial Testate Amoebae in Western Siberia Lowland Peatlands. Data, 8(11), 173. https://doi.org/10.3390/data8110173

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