Biodiversity Data Journal : Data Paper (Biosciences)
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Data Paper (Biosciences)
Taxonomic diversity and abundance of enchytraeids (Annelida, Clitellata, Enchytraeida) in the Northern Palaearctic. 1. Asian part
expand article infoMaxim I. Degtyarev‡, Ruslan A. Saifutdinov‡, Daniil I. Korobushkin‡, Alexander I. Bastrakov‡, Margarita A. Danilova‡, Ivan D. Davydov‡, Anastasia Yu. Gorbunova‡, Polina A. Guseva‡, Evgeniy I. Karlik‡, Roza E. Koshchanova§, Ksenia G. Kuznetsova|, Iurii M. Lebedev‡, Dmitriy A. Medvedev‡, Roman R. Obolenskiy‡, Anna V. Popova‡, Nina A. Pronina‡, Leonid B. Rybalov‡, Alexei V. Surov‡, Akmal B. Tadzhimov§, Alexander I. Tarasov, Vladislav A. Vasiliev, Andrey S. Zaitsev‡, Elena Yu. Zvychaynaya‡, Konstantin B. Gongalsky‡
‡ A.N. Severtsov Institute of Ecology and Evolution RAS, Moscow, Russia
§ Karakalpak State University named after Berdakh, Nukus, Uzbekistan
| University of Bergen, Bergen, Norway
¶ Lomonosov Moscow State University, Moscow, Russia
Corresponding author: Ruslan A. Saifutdinov (sairusair@gmail.com)
Academic editor: Emilia Rota
Received: 24 Oct 2023 | Accepted: 26 Dec 2023 | Published: 03 Jan 2024
© 2024 Maxim Degtyarev, Ruslan Saifutdinov, Daniil Korobushkin, Alexander Bastrakov, Margarita Danilova, Ivan Davydov, Anastasia Gorbunova, Polina Guseva, Evgeniy Karlik, Roza Koshchanova, Ksenia Kuznetsova, Iurii Lebedev, Dmitriy Medvedev, Roman Obolenskiy, Anna Popova, Nina Pronina, Leonid Rybalov, Alexei Surov, Akmal Tadzhimov, Alexander Tarasov, Vladislav Vasiliev, Andrey Zaitsev, Elena Zvychaynaya, Konstantin Gongalsky
This is an open access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Citation: Degtyarev MI, Saifutdinov RA, Korobushkin DI, Bastrakov AI, Danilova MA, Davydov ID, Gorbunova AYu, Guseva PA, Karlik EI, Koshchanova RE, Kuznetsova KG, Lebedev IM, Medvedev DA, Obolenskiy RR, Popova AV, Pronina NA, Rybalov LB, Surov AV, Tadzhimov AB, Tarasov AI, Vasiliev VA, Zaitsev AS, Zvychaynaya EYu, Gongalsky KB (2024) Taxonomic diversity and abundance of enchytraeids (Annelida, Clitellata, Enchytraeida) in the Northern Palaearctic. 1. Asian part. Biodiversity Data Journal 12: e114682. https://doi.org/10.3897/BDJ.12.e114682
 Open Access

Abstract

Background

Enchytraeids, or potworms, are tiny oligochaetes that are distributed worldwide in many terrestrial, freshwater and marine ecosystems. Despite their key role in the functioning of ecosystems, the diversity and abundance of Enchytraeidae are rarely studied due to the laborious process of species identification. The present study addresses this gap and sheds some light on the distribution and abundance of enchytraeids in the lands of the Northern Palearctic. The provided dataset constitutes the latest and comprehensive field sampling of enchytraeid assemblages across the Asiatic part of the Northern Palearctic, encompassing an original set of soil samples systematically collected throughout the region from 2019 to 2022.

New information

The dataset includes occurrences from 131 georeferenced sites, encompassing 39 species and 7,074 records. This represents the first dataset providing species-specific information about the distribution and abundance of terrestrial enchytraeids across an extensive geographic area covering the Asian sector of the Northern Palaearctic. The compiled dataset is the key for exploring and understanding local and regional enchytraeid diversity. It may also serve as a valuable resource for monitoring and conserving the entire soil biodiversity.

Keywords

sampling event, soil fauna, potworm, tundra, boreal, nemoral, steppe, desert, Siberia, Russian Far East, Uzbekistan, Kazakhstan, Mongolia, mesofauna, Enchytraeidae, soil fauna, terrestrial oligochaetes

Introduction

Enchytraeids, also known as potworms, are tiny, yet ecologically impactful components of biota living in soils and freshwater and marine sediments worldwide (Erséus et al. 2010, Rota and de Jong 2015). Despite their small size and especially where earthworms are scarce or absent, they play a vital role in terrestrial ecosystems by regulating many key processes like nutrient cycling and maintaining soil structure (Potapov et al. 2022). However, due to the highly laborious taxonomic identification that involves in vivo morphological evaluation, as well as the considerable lack of experienced staff worldwide, there is a dramatic shortage of studies devoted to understanding their temporal and spatial distribution at the species level (Römbke et al. 2017). This is especially true for the eastern part of the Northern Palearctic, which remains as one of the least studied areas in terms of enchytraeids (Nurminen 1982, Rota and de Jong 2015). Nevertheless, the situation is changing and there is a growing interest in the ecology and taxonomy of Enchytraeidae in this part of the world (Rota et al. 2018, John et al. 2019, Degtyarev et al. 2020). The objective of this data paper is to address this knowledge gap. To achieve this, we conducted a field survey of enchytraeid fauna and population across various biomes within the Northern Palearctic between 2019 and 2022. Due to the extensive geographical extent and the significant amount of material that still requires identification, we have chosen to split the resulting dataset into two main parts: Asian and European. The dataset dedicated to the European part will be submitted to the same journal in the near future (Saifutdinov et al., in prep.).

General description

Purpose: 

The purpose of the data paper is to depict the distribution and abundance of enchytraeids in the Northern Palearctic Region, particularly in its Asiatic part.

Project description

Study area description: 

The area under investigation is the Asian part of the Northern Palearctic, encompassing a diverse range of biome types, starting from Siberian tundra in the far north to temperate forests and deserts in the south (Binney et al. 2017). We limit the research area to the Ural Mountains in the west, Uzbekistan and Mongolia in the south. The territory of China was excluded due to organisational reasons. In total, we examined 131 sites located within various biomes as classified by the WWF (Olson et al. 2001), including: (1) tundra, (2) boreal forests, (3) temperate coniferous forests, (4) temperate broadleaf and mixed forests, (5) temperate grasslands, savannahs and shrublands, (6) flooded grasslands and savannahs and (7) deserts and xeric shrublands. In each of the biomes, we collected from a different number of sites due to logistical constraints and various extraction capacities. Comprehensive information about each site is given in Table 1.

Table 1.
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Locations, habitat information and number of recorded enchytraeid species for sampling sites in the Asian Northern Palaearctic Region.

Biome

Site ID

Vegetation

Species Recorded

Tundra

12-07-2020-RU-CK-23

Flood plain meadow

4

Tundra

12-07-2020-RU-CK-24

Alnus krummholz

3

Tundra

15-07-2020-RU-KK-27

Tundra

3

Tundra

16-07-2020-RU-KK-28

Tundra

2

Tundra

13-07-2020-RU-KK-29

Tundra

1

Tundra

08-07-2021-RU-CK-31

Alnus krummholz

0

Tundra

08-07-2021-RU-CK-32

Alnus krummholz

1

Tundra

10-07-2021-RU-CK-33

Alnus krummholz

4

Tundra

08-07-2021-RU-CK-35

Alnus krummholz

4

Tundra

12-07-2021-RU-CK-61

Sphagnum - Rubus chamaemorus tundra

1

Tundra

09-07-2021-RU-CK-62

Salix thicket

4

Tundra

08-07-2021-RU-CK-63

Salix thicket

3

Tundra

10-05-2022-RU-KK-88

Low-growing Pinus shrubland

7

Boreal forest

11-07-2019-RU-SL-1

Larix forest with Pinus pumilia

2

Boreal forest

11-07-2019-RU-SL-2

Coniferous forest with Pinus pumilia

1

Boreal forest

12-07-2019-RU-SL-5

Taiga forest with Larix gmelinii

2

Boreal forest

28-07-2019-RU-MG-12

Larix forest

3

Boreal forest

09-08-2019-RU-SL-13

Coniferous shrubland with Sasa kurilensis

9

Boreal forest

28-07-2019-RU-MG-14

Alnus forest with high grass

4

Boreal forest

26-07-2019-RU-MG-19

Larix forest

0

Boreal forest

27-07-2019-RU-MG-22

Larix forest

2

Boreal forest

27-07-2020-RU-MG-25

Larix forest

1

Boreal forest

23-08-2021-RU-YA-39

Pinus pumilia woodland

8

Boreal forest

23-08-2021-RU-YA-40

Pinus pumilia woodland

2

Boreal forest

23-08-2021-RU-YA-41

Pinus pumilia woodland

1

Boreal forest

21-08-2021-RU-YA-42

Larix - dwarf Betula woodland

2

Boreal forest

26-08-2021-RU-YA-43

Pinus pumilia woodland

3

Boreal forest

25-08-2021-RU-YA-44

Larix - Pinus pumilia woodland

2

Boreal forest

26-08-2021-RU-YA-45

Pinus pumilia woodland

3

Boreal forest

21-08-2021-RU-YA-46

Larix - dwarf Betula woodland

2

Boreal forest

26-08-2021-RU-YA-47

Pinus pumilia woodland

1

Boreal forest

23-08-2021-RU-YA-48

Larix - dwarf Betula woodland

1

Boreal forest

26-08-2021-RU-YA-49

Pinus pumilia woodland

1

Boreal forest

21-08-2021-RU-YA-50

Larix - dwarf Betula woodland

1

Boreal forest

23-08-2021-RU-YA-51

Larix - dwarf Betula woodland

1

Boreal forest

25-08-2021-RU-YA-52

Larix - Pinus pumilia woodland

0

Boreal forest

25-08-2021-RU-YA-53

Larix - Pinus pumilia woodland

2

Boreal forest

21-08-2021-RU-YA-54

Larix - dwarf Betula woodland

2

Boreal forest

21-08-2021-RU-YA-55

Larix - dwarf Betula woodland

2

Boreal forest

24-08-2021-RU-YA-56

Larix - Pinus pumilia woodland

2

Boreal forest

23-08-2021-RU-YA-57

Larix - dwarf Betula woodland

2

Boreal forest

24-08-2021-RU-YA-58

Larix - Pinus pumilia woodland

2

Boreal forest

21-08-2021-RU-YA-59

Larix - dwarf Betula woodland

1

Boreal forest

24-08-2021-RU-YA-60

Larix - Pinus pumilia woodland

0

Boreal forest

16-06-2021-RU-IR-64

Pinus forest

4

Boreal forest

16-06-2021-RU-IR-65

Pinus forest

4

Boreal forest

16-09-2021-RU-SV-66

Urtica thickets

1

Boreal forest

06-06-2022-RU-HM-79

Pinus forest with Betula

2

Boreal forest

06-06-2022-RU-HM-80

Pinus forest with Betula

2

Boreal forest

06-06-2022-RU-HM-81

Pinus forest

3

Boreal forest

21-06-2022-RU-SV-83

Betula - Pinus forest

4

Boreal forest

21-06-2022-RU-SV-85

Betula - Pinus - Picea forest

6

Boreal forest

09-05-2022-RU-KT-91

Coniferous forest

4

Boreal forest

27-09-2022-RU-SV-104

Betula - Populus forest belt with Salix and Mixed Grasses

4

Boreal forest

27-09-2022-RU-SV-105

Populus forest with Mixed Grasses

4

Boreal forest

27-09-2022-RU-SV-106

Scattered forest on Anthropogenic Soils

2

Boreal forest

27-09-2022-RU-SV-107

Tilia - Betula - Abies forest

3

Boreal forest

27-09-2022-RU-SV-108

Betula forest

4

Boreal forest

28-09-2022-RU-SV-109

Betula - Pinus forest

3

Boreal forest

28-09-2022-RU-SV-110

Mixed fen forest

5

Boreal forest

28-09-2022-RU-SV-111

Lowland Sedge Bog with Salix

1

Boreal forest

28-09-2022-RU-SV-112

Mixed Coniferous and Deciduous fen forest

2

Boreal forest

29-09-2022-RU-SV-113

Populus - Betula forest

0

Boreal forest

30-09-2022-RU-SV-114

Picea - Pinus - Abies forest

3

Boreal forest

30-09-2022-RU-SV-115

Picea forest

3

Boreal forest

30-09-2022-RU-SV-116

Betula - Abies - Spruce forest

4

Boreal forest

30-09-2022-RU-SV-117

Betula - Abies forest

2

Boreal forest

30-09-2022-RU-SV-118

Betula - Abies forest

2

Boreal forest

20-08-2022-RU-ZK-125

Pinus forest with Populus

3

Boreal forest

20-08-2022-RU-ZK-126

Meadow with Salix

10

Boreal forest

18-08-2022-RU-BU-130

Pinus forest

0

Boreal forest

18-08-2022-RU-BU-131

Steppe

0

Temp. conifer. forest

03-08-2021-RU-AL-36

Betula forest

3

Temp. conifer. forest

02-08-2021-RU-AL-37

Pinus forest

5

Temp. conifer. forest

01-08-2021-RU-AL-38

Siberian Pinus - Picea forest

1

Temp. conifer. forest

10-07-2022-RU-NS-89

Deciduous forest

4

Temp. conifer. forest

13-07-2022-RU-AL-90

Deciduous forest

8

Temp. broadleaf & mixed forest

19-08-2019-RU-PK-8

Sparse Quercus forest

7

Temp. broadleaf & mixed forest

13-08-2019-RU-PK-9

Quercus - Betula forest

8

Temp. broadleaf & mixed forest

14-08-2019-RU-PK-11

Sparse Betula forest

7

Temp. broadleaf & mixed forest

14-08-2019-RU-PK-18

Quercus - Betula forest

5

Temp. broadleaf & mixed forest

20-08-2019-RU-SL-20

Abies and Picea forest

7

Temp. broadleaf & mixed forest

21-08-2019-RU-SL-21

Sasa kurilensis thicket

1

Temp. broadleaf & mixed forest

12-06-2020-RU-SL-26

Broadleaf forest

4

Temp. broadleaf & mixed forest

12-06-2020-RU-SL-30

Picea - Abies forest

2

Temp. broadleaf & mixed forest

18-06-2022-RU-KN-82

Pinus forest with Betula and Vaccinium vitis-idaea

0

Temp. broadleaf & mixed forest

19-06-2022-RU-TN-84

Pinus forest

1

Temp. broadleaf & mixed forest

18-06-2022-RU-KN-87

Betula - Pinus forest

2

Temp. grasslands & savannas

27-07-2019-RU-ZK-3

Dry steppe with Stipa and Leymus

0

Temp. grasslands & savannahs

28-07-2019-RU-ZK-4

Dry steppe with Stipa and Leymus

0

Temp. grasslands & savannahs

25-07-2019-RU-ZK-6

Periodically flooded meadow with Carex

4

Temp. grasslands & savannahs

29-07-2019-RU-ZK-15

Mountain steppe with Leymus and Carex

2

Temp. grasslands & savannahs

15-05-2022-RU-CB-75

Forb - feather meadow

2

Temp. grasslands & savannahs

15-05-2022-RU-CB-76

Feather grass steppe

0

Temp. grasslands & savannahs

15-05-2022-RU-CB-77

Feather grass steppe

0

Temp. grasslands & savannahs

15-05-2022-RU-CB-78

Cereal forb meadow with feather

3

Temp. grasslands & savannahs

18-06-2022-RU-KN-86

Betula - Pinus forest

4

Temp. grasslands & savannahs

20-06-2022-MN-Ulaanbaatar-92

Ruderal vegetation

2

Temp. grasslands & savannahs

21-06-2022-MN-Töv-93

Larix forest

6

Temp. grasslands & savannahs

22-06-2022-MN-Ulaanbaatar-94

Picea forest

2

Temp. grasslands & savannahs

22-06-2022-MN-Töv-95

Cedrus - Picea forest

0

Temp. grasslands & savannahs

21-06-2022-MN-Töv-96

Betula fusca forest

5

Temp. grasslands & savannahs

22-06-2022-MN-Ulaanbaatar-97

Flood plain

1

Temp. grasslands & savannahs

23-06-2022-MN-Ulaanbaatar-98

Under Salix near the river

2

Temp. grasslands & savannahs

23-06-2022-MN-Töv-99

Salix thicket

2

Temp. grasslands & savannahs

23-06-2022-MN-Töv-100

Meadow steppe

0

Temp. grasslands & savannahs

21-06-2022-MN-Ulaanbaatar-101

Steppe under grazing

0

Temp. grasslands & savannahs

23-06-2022-MN-Ulaanbaatar-102

Ulmus on the slope

0

Temp. grasslands & savannahs

15-07-2022-KZ-Shyngyrlau-103

Feather grass steppe

1

Temp. grasslands & savannahs

28-10-2022-UZ-Tashkent-119

Old agricultural field

1

Temp. grasslands & savannahs

01-11-2022-UZ-Samarqand-120

Ulmus forest

5

Temp. grasslands & savannahs

31-10-2022-UZ-Samarqand-121

Forest strip near vineyard

4

Temp. grasslands & savannahs

31-10-2022-UZ-Samarqand-122

Populus, Acer pseudoplatanus, Quercus, Juglans forest

0

Temp. grasslands & savannahs

23-10-2022-UZ-Tashkent-123

Juglans regia forest

0

Temp. grasslands & savannahs

28-10-2022-UZ-Sirdaryo-124

Cotton field canal

0

Temp. grasslands & savannahs

28-10-2022-UZ-Jizzax-127

Dry mountain steppe

0

Temp. grasslands & savannahs

25-10-2022-UZ-Fergana-128

Cane with Populus in canal near cotton field

0

Temp. grasslands & savannahs

26-10-2022-UZ-Namangan-129

Shrubland

1

Flooded grasslands

07-08-2019-RU-PK-7

Meadow / shrubland with Carex

2

Flooded grasslands

08-08-2019-RU-PK-10

Periodically flooded meadow with Carex

5

Flooded grasslands

05-08-2019-RU-AM-16

Meadow / deciduous forest with Prunus padus

9

Flooded grasslands

05-08-2019-RU-AM-17

Mixed forest and shrubland

0

Flooded grasslands

20-07-2021-RU-HK-34

Pinus koraiensis forest

5

Deserts & xeric shrublands

04-05-2022-UZ-Xorazm-67

Larix forest

1

Deserts & xeric shrublands

30-04-2022-UZ-Xorazm-68

Meadow near orchard

1

Deserts & xeric shrublands

30-04-2022-UZ-Xorazm-69

Cotton field canal

0

Deserts & xeric shrublands

03-05-2022-UZ-Karakalpakstan-70

Deciduous forest

0

Deserts & xeric shrublands

03-05-2022-UZ-Karakalpakstan-71

Ruderal vegetation

0

Deserts & xeric shrublands

02-05-2022-UZ-Karakalpakstan-72

Deciduous forest

0

Deserts & xeric shrublands

05-05-2022-UZ-Karakalpakstan-73

Elaeagnus argentea - Turanga thicket

0

Deserts & xeric shrublands

05-05-2022-UZ-Karakalpakstan-74

Dry canal bottom

0

Sampling methods

Sampling description: 

The material for the dataset was collected between 2019 and 2022. We selected sampling sites in areas that were not heavily disturbed by human activity. In arid regions, we chose the most humid (but not flooded) spots. The sampling protocol was developed in compliance with widely recognised methods (Ghilarov 1975, Coleman et al. 2004). At each site, we collected a random selection of 1 to 7 soil monoliths. Detailed information on number of soil monoliths collected from each site can be found in the "samplingEffort" column within the GBIF dataset (Degtyarev et al. 2023). These soil monoliths were taken using a 5-cm-diameter steel corer down to a depth of 10 cm. After collection, the soil was carefully placed into plastic bags and transported to the laboratory at the A. N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow. Subsequently, the soil samples were stored in a refrigerator at +4°C until extraction. Enchytraeids were extracted from the soil using the wet funnel technique as described by Didden et al. (1995). It is commonly known as Graefe's method and is a somewhat simplified modification of O'Connor's method (O'Connor 1962). Graefe's innovation is the rejection of artificial heating of the surface of the soil sample. Otherwise, it is not significantly different in efficiency from the O'Connor method (Kobetičová and Schlaghamerský 2003). We placed a sieve in each funnel and a soil monolith in each sieve. Then tap water was poured into the funnel so that the soil monolith was completely covered. A test tube was attached to each funnel and placed in a container with room temperature water. This precaution aimed to prevent potential overheating of the extracted enchytraeids, considering the possibility of random and sudden temperature fluctuations in the extraction room. Extraction was carried out for 16 to 24 hours, after which the tubes were detached from the funnels and the contents of the tubes were poured into Petri dishes.

Quality control: 

The samples were collected by a number of soil zoologists and ecologists from the A.N. Severtsov Institute of Ecology and Evolution, Russian Academy of Sciences, Moscow and trained volunteers. In total, 39 different enchytraeid species were collected. Given the variance in the number of soil monoliths across sites, the dataset includes abundance expressed as individuals per square metre. Enchytraeid species were identified in vivo immediately after the extraction procedure, according to Schmelz and Collado (2010). For species not included in this guide or described later, comparisons with original descriptions were used. We also employed molecular analysis to verify the species Fridericia bulboides and Mesenchytraeus gigachaetus. Detailed information on the methods used for molecular analysis is available in Degtyarev et al. (2020).

Some of the species we have found exhibit distinct morphological differences from all known enchytraeid species. We are confident that these species have not yet been described in literature. A comprehensive description of these species will be possible once more data have been collected. Therefore, we have decided to refer to them as Fridericia sp. 1, Enchytraeus sp. 1, Henlea sp. 1 and Henlea sp. 2 for now. Henlea sp. 1 and Henlea sp. 2 are large Henlea worms, both with unusually robust spermathecae. Fridericia sp. 1 is a medium-sized Fridericia species from mountainous Uzbekistan. Enchytraeus sp. 1 is possibly an obligate parthenogenetic species from the E. buchholzi group, characterised by underdeveloped male copulatory organs.

The taxonomy follows the WoRMS database (Timm and Erséus 2023). Scientific names were checked using the GBIF species matching tool. Subsequently, the identified enchytraeids were used for further molecular analyses (COI and/or H3 genes). As such, all instances of enchytraeid occurrences within the studied sites were recorded as dwc:basisOfRecord = "HumanObservation". Juvenile specimens were identified at the genus level. The identification of all enchytraeids was conducted by Maxim Degtyarev.

Step description: 

1) The selection of study sites was driven by the intention to locate undisturbed areas displaying minimal or no signs of human activity.

2) Site sampling was carried out at a distance of no less than 100 m from the borders of selected zonal sites within one of the seven biome types according to WWF (Olson et al. 2001): tundra, boreal forests, temperate coniferous forests, temperate broadleaf and mixed forests, temperate grasslands, savannahs and shrublands, flooded grasslands and savannahs, as well as desert and xeric shrublands.

3) At each site, soil monoliths were collected using a steel corer with a diameter of 5 cm, reaching a depth of 10 cm.

4) The transportation of soil monoliths was conducted in isothermic containers to prevent soil overheating, which could lead to the mortality of organisms present.

5) Enchytraeids were extracted from the soil using the wet funnel method as described by Didden et al. (1995).

6) Following the extraction process, enchytraeids were identified in vivo to the species level using an Olympus BX-43 microscope. Subsequently, they were preserved in 96% alcohol for further molecular and isotopic analyses.

Geographic coverage

Description: 

The research region was located in the Asian part of the Northern Palearctic, from the Ural Mountains in the west to the Pacific coast in the Russian Far East (Fig. 1). It included biomes in West and East Siberian Russia, Kazakhstan, Mongolia, Uzbekistan and the Russian Far East. This extensive geographic area consists of diverse habitat types, including tundra, taiga, steppe, boreal forest and mountain ranges. Spanning a large latitudinal gradient, the region contains hot desert (BWh), cold desert (BWk), hot semi-arid (BSh) and cold semi-arid (BSk) climates in the south, transitioning to humid continental (Dfa) and warm summer continental (Dfb) climates in the mid-latitudes and subarctic (Dfc) and tundra (ET) climates in the far north near the Arctic, according to the Köppen-Geiger climate classification (Beck et al. 2018).

Figure 1.  

Enchytraeidae sampling locations in the Asian part of the Northern Palaearctic. The map was created using QGIS 3.32.2 - Lima software (QGIS.org 2023).

The geographical references were obtained by recording the coordinates of the sampling sites using a mobile phone and the Organic Maps app (Organic Maps OÜ 2023). The measurement error of the coordinates was approximately 25 m. The WGS84 coordinate system was used for all records.

Coordinates: 

39.3147 and 72.4874 Latitude; 53.5298 and 177.8474 Longitude.

Taxonomic coverage

Description: 

Across the 131 sites studied within seven biomes in the Asiatic part of the Northern Palaearctic, we identified a total of 39 species belonging to 16 genera. The highest species richness was recorded in boreal forests (34 species in total, see Table 2). Temperate broadleaf and mixed forests, as well as grasslands and shrublands, hosted approximately 20 species each. In the tundra biome, we found 16 species. The number of species in temperate coniferous forests, flooded grasslands and savannahs ranged from 10 to 11. The lowest species richness was observed in xeric shrublands and deserts (Table 2).

Table 2.
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Average species richness per sampling site within a biome (m ± SE), total species richness and average abundance (indiv. per square metre ± SE) of enchytraeids in the studied biomes of the Asiatic part of the Northern Palaearctic. The numbers in brackets adjacent to specific biomes indicate the number of true replicates. Unidentified enchytraeids were excluded when counting the number of species. Specimens identified only at the genus level (Genus sp.) were included in the analysis as unique species, while juvenile specimens were only included in the counts if species from the same genus were absent at the site. The classification of biomes is given according to Olson et al. (2001).

Biome

Average No of Species

Total No of Species

Average abundance

Tundra (n = 13)

2.77 ± 0.47

16

7207 ± 3126

Boreal forests (n = 59)

2.31 ± 0.24

34

4296 ± 831

Temperate coniferous forests (n = 5)

3.4 ± 0.87

10

3789 ± 1044

Temperate broadleaf and mixed forests (n = 11)

3.64 ± 0.79

20

5725 ± 1767

Temperate grasslands, savannahs and shrublands (n = 30)

1.40 ± 0.29

19

2287 ± 516

Flooded grasslands and savannahs (n = 5)

4.00 ± 1.38

11

12288 ± 7644

Deserts and xeric shrublands (n = 8)

0.25 ± 0.16

2

384 ± 269

The average species richness of enchytraeids varied between four species per site in flooded grasslands and savannahs and 0.25 species per site in deserts and xeric shrublands. The same trends were also observed in the case of the average abundance of enchytraeids (see Table 2).

Taxa included:
Rank Scientific Name Common Name
family Enchytraeidae pot worm

Temporal coverage

Data range: 
2019-7-11 - 2022-11-01.

Usage licence

Usage licence: 
Other
IP rights notes: 

This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).

Data resources

Data package title: 
Taxonomic diversity and abundance of enchytraeids (Annelida: Clitellata: Enchytraeida) in the Northern Palaearctic. 1. Asian part
Resource link: 
https://doi.org/10.15468/appcnv
Alternative identifiers: 
https://www.gbif.org/dataset/918d7d69-1626-4980-9f6a-74d04da30fde; http://gbif.ru:8080/ipt/resource?r=enchytraeids_2
Number of data sets: 
1
Data set name: 
Taxonomic diversity and abundance of enchytraeids (Annelida: Clitellata: Enchytraeida) in the Northern Palaearctic. 1. Asian part
Download URL: 
http://gbif.ru:8080/ipt/archive.do?r=enchytraeids_2&v=1.7
Data format: 
Darwin Core Archive format (https://ipt.gbif.org/manual/en/ipt/latest/dwca-guide)
Description: 

The dataset includes two related tables linked by the eventID column - Sampling Events and Associated Occurrences. The Sampling Events table consists of 131 events. The Associated Occurrences table consists of 7,074 occurrences (Degtyarev et al. 2023).

Column label Column description
eventID (Event core, Occurrence extension) Each event is assigned a unique identifier constructed from the sampling date, country code, region abbreviation for Russia or full name for other countries and sampling site number. For example, the identifier "03-05-2022-UZ-Karakalpakstan-70" corresponds to the event recorded on 3 May 2022, at sampling site #70 in Karakalpakstan, Uzbekistan.
eventDate (Event core) Date on which soil samples were collected, formatted as YYYY-MM-DD (year-month-day) according to ISO 8601.
day (Event core) The integer day of the month on which the dwc:Event occurred.
month (Event core) The integer month in which the dwc:Event occurred.
year (Event core) The four-digit year in which the dwc:Event occurred, according to the Common Era Calendar.
samplingProtocol (Event core) A constant value describing the extraction method used for all sampling events. The protocol was wet extraction of animals from 19.6 cm2 soil cores using funnels.
samplingEffort (Event core) The number of soil samples collected and processed using the extraction procedure.
sampleSizeValue (Event core) A numeric value for a measurement of the size (volume) of a sample in a sampling dwc:Event.
sampleSizeUnit (Event core) The unit of measurement of the size (volume) of a sample in a sampling dwc:Event.
locality (Event core) The name of the closest town, village or other significant human settlement near the sampling site.
decimalLatitude (Event core) The geographic latitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic centre of a dcterms:Location.
decimalLongitude (Event core) The geographic longitude (in decimal degrees, using the spatial reference system given in dwc:geodeticDatum) of the geographic centre of a dcterms:Location.
coordinatePrecision (Event core) A decimal representation of the precision of the coordinates given in the dwc:decimalLatitude and dwc:decimalLongitude.
coordinateUncertaintyInMeters (Event core) The horizontal distance (in metres) from the given dwc:decimalLatitude and dwc:decimalLongitude describing the smallest circle containing the whole of the dcterms:Location.
geodeticDatum (Event core) The ellipsoid, geodetic datum or spatial reference system (SRS), upon which the geographic coordinates given in dwc:decimalLatitude and dwc:decimalLongitude are based. Constant value - "WGS84".
country (Event core) The name of the country or major administrative unit in which the dcterms:Location occurs.
countryCode (Event core) The standard code for the country in which the dcterms:Location occurs.
stateProvince (Event core) The name of the next smaller administrative region than country (state, province, canton, department, region etc.), in which the dcterms:Location occurs. For sampling events in Russia, this records the federal subject (republic, krai, oblast etc.) where the sample was collected. For sampling events in other countries, this records administrative regions according to Database of Global Administrative Areas.
habitat (Event core) This variable provides the biome classification assigned to the sampling location, based on the habitat typing system defined by the World Wildlife Fund (WWF). For additional information about the WWF biome classification system, please refer to Olson et al. (2001).
type (Event core) The nature or genre of the resource. Constant value - event.
occurenceID (Occurrence extension) Each occurrence is assigned a unique identifier constructed from the sampling date, country code, region abbreviation for Russia or full name for other countries, sampling site number and occurrence number at that site. For example, the identifier "12-07-2019-RU-SL-5-14" corresponds to the 14th occurrence recorded on 12 July 2019 at sampling site #5 in Sakhalin Oblast, Russia.
basisOfRecord (Occurrence extension) This field contains a constant value indicating the record type. All occurrences have the value "Human observation" because organisms were identified in vivo and then used for further molecular and isotopic analyses after collection.
recordedBy (Occurrence extension) The person, group or organisation responsible for originally recording the occurrence data. For example: "Korobushkin D | Saifutdinov R".
identifiedBy (Occurrence extension) The person, group or organisation responsible for identification. For all records in this dataset, organisms were identified by Maxim Degtyarev.
organismQuantity (Occurrence extension) A number or enumeration value for the quantity of dwc:Organisms.
organismQuantityType (Occurrence extension) The type of quantification system used for the quantity of dwc:Organisms.
occurenceStatus (Occurrence extension) A statement about the presence or absence of a dwc:Taxon at a dcterms:Location.
taxonRemarks (Occurrence extension) Freeform remarks entered relevant to the taxonomy and characterisation of the documented species or taxon. Example: "Henlea cf. nasuta".
scientificName (Occurrence extension) The full scientific name, with authorship and date information, if known. Example: "Henlea nasuta (Eisen, 1878)".
kingdom (Occurrence extension) The full scientific name of the kingdom in which the dwc:Taxon is classified.
phylum (Occurrence extension) The full scientific name of the phylum or division in which the dwc:Taxon is classified.
class (Occurrence extension) The full scientific name of the class in which the dwc:Taxon is classified.
order (Occurrence extension) The full scientific name of the order in which the dwc:Taxon is classified.
family (Occurrence extension) The full scientific name of the family in which the dwc:Taxon is classified.
genus (Occurrence extension) The full scientific name of the genus in which the dwc:Taxon is classified.
scientificNameAuthorship (Occurrence extension) The authorship information for the dwc:scientificName formatted according to the conventions of the applicable dwc:nomenclaturalCode.
taxonRank (Occurrence extension) The taxonomic rank of the most specific name in the dwc:scientificName.

Acknowledgements

The sampling, identification and preparation of the manuscript were funded by the Russian Science Foundation, grant No. 21-14-00227 "Soil-living Enchytraeids of the Northern Palearctic".

Author contributions

Maxim I. Degtyarev - collected soil material, extracted enchytraeids from soil, identified enchytraeids to the species level, revised manuscript;

Ruslan A. Saifutdinov - collected soil material, prepared dataset, wrote the metadata description and manuscript;

Daniil I. Korobushkin - collected soil material, prepared dataset, created the map;

Margarita A. Danilova, Iurii M. Lebedev - collected soil material, taxonomic verification of the specimens using molecular analysis;

Polina A. Guseva, Ksenia G. Kuznetsova, Dmitriy A. Medvedev, Elena Yu. Zvychaynaya - taxonomic verification of the specimens using molecular analysis;

Evgeniy I. Karlik - collected soil material, logistical support during investigation;

Alexander I. Bastrakov, Ivan D. Davydov, Roza E. Koshchanova, Anna V. Popova, Leonid B. Rybalov, Alexei V. Surov, Akmal B. Tadzhimov, Alexander I. Tarasov, Vladislav A. Vasiliev - collected soil material;

Anastasia Yu. Gorbunova, Roman R. Obolenskiy, Nina A. Pronina - extracted enchytraeids from soil;

Andrey S. Zaitsev - project supervision, collected soil material, revised manuscript;

Konstantin B. Gongalsky - project supervision, funding aquisition, collected soil material, revised manuscript.

References

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