Long-term dynamics of the abundance of earthworms and enchytraeids (Annelida, Clitellata: Lumbricidae, Enchytraeidae) in forests of the Central Urals, Russia

Abstract Background Since the late 1980s, long-term monitoring of terrestrial ecosystems in metal-contaminated areas has been carried out in the Central Urals. As a part of these monitoring programmes, the data on soil macroinvertebrates in undisturbed areas as reference sites continues to be gathered. These data help study the local biodiversity and long-term dynamics of soil macroinvertebrate abundance in non-polluted areas. New information The dataset (available from the GBIF network at https://www.gbif.org/dataset/bf5bc7f6-71a3-4abd-8abc-861ee3cbf84a) includes information from a long-term monitoring programme for two taxa of Annelids, Lumbricidae and Enchytraeidae, which dwell in the topsoil of spruce-fir, birch, pine and floodplain forests in the Central Urals. The dataset includes information on the earthworm community structure (list of species, species abundance, number of egg cocoons, cocoon exuvia, juveniles and adults) and enchytraeid abundance. The dataset consists of 553 sampling events (= samples, corresponding to upper and lower layers of the soil monoliths) and 12739 occurrences (earthworms, mainly identified to species and earthworm cocoons and enchytraeids, identified to family) collected during 1990–1991, 2004, 2014–2016 and 2018–2020. In total, 3305 individuals of earthworms were collected, representing ten (out of twelve) species and all eight genera recorded for the fauna of the Central Urals. In addition, 7292 earthworm egg cocoons and cocoon exuvia and 6926 individuals of enchytraeids were accumulated. The presence-absence data on each of the ten earthworm species, egg cocoons, cocoon exuvia and enchytraeids are provided for each sampling event. All data were collected in undisturbed non-polluted areas and are used as a local reference for ecotoxicological monitoring. The dataset provides valuable information for estimating the composition and abundance of earthworm communities in different habitats over a long time and contributes to the study of soil fauna biodiversity in the Urals.


Introduction
Earthworms (Lumbricidae) are generally recognised as ecosystem engineers in temperate and tropical climates; they affect soil structure, food webs and nutrient cycles (Lavelle et al. 1997, Lavelle et al. 2006. Earthworms, amongst other macrodetritivores, largely determine the rate of organic matter decomposition and plant provision with nutrients, contributing to soil structure formation, thereby influencing soil water regime and fertility and modifying the microflora composition (Brussaard et al. 2007). Given such a significant role, earthworms and other annelids are often used in environmental monitoring (Paoletti et al. 2010) and pollution controls (Cortet et al. 1999).
The presented dataset includes information on annelid abundance and community composition in forests of the Central Urals. Other macroinvertebrates were collected, but not considered in this research. In the study area, two taxa of annelids -earthworms and enchytraeids -are the main soil macrodetritivores. Other groups of macrodetritivores are low-abundant (diplopods) or occasional (woodlice, wood cockroaches Ectobius spp.) compared to western European or more southern regions. Nematoceran larvae (Tipulidae, Limoniidae, Bibionidae, Sciaridae, Chironomidae, Cecidomyiidae and others), Coleopteran larvae (Elateridae) and molluscs are classified as phytosaprophages and their abundance is lower than annelids.
In summary, Tamara Perel (Perel 1979) described the fauna of the Urals as follows: almost exclusively endemic species R. diplotetratheca, E. intermedia and P. tuberosa are widespread in uncultivated soils; E. uralensis is characteristic for floodplain biotopes, while Eisenia nordenskioldi (Eisen, 1873) is very rare. All other species are peregrine, they are occasional or occur near settlements: Aporrectodea caliginosa (Savigny, 1826), In the study area, earthworms can be divided into three ecological categories (according to Bouché 1977): epigeic, epi-endogeic and endogeic. Anecic earthworms, typical for the more western European regions (e.g. Lumbricus terrestris or Aporrectodea longa (Ude, 1885)), are absent. Epigeic species feeding on the plant litter and inhabiting only the O horizon are represented by D. octaedra and B. rubidus. Epi-endogeic species dwelling in the O horizon and the upper (0-10 cm) layer of A horizon are R. diplotetratheca, L. rubellus and E. atlavinyteae. Endogeic species feeding on soil organic matter in the middle (10-20 cm) of mineral horizons are represented by A. rosea, P. tuberosa and O. lacteum. In coniferous forests, epi-endogeic species dominate (70-80% on density, mainly R. diplotetratheca) and endogeic species are of comparable abundance in deciduous forests. In the meadows, these endogeic species are accompanied by A. caliginosa, which dwell in mineral layers deeper than 20 cm. The presented dataset includes ten species belonging to eight genera of the family Lumbricidae. Two species are absent: E. nordenskioldi and E. fetida. The first species is typical for the Cis-Urals and Trans-Urals (Perel 1979) and more northern areas of the Central Urals (Vorobeichik 1998). The second one is mainly inhabiting meadows, pastures and other biotopes with manure-amended soils; this species was also recorded in the study area, but outside the forest biotopes.
Enchytraeids range from 0.1-0.5 mm to 10-20 mm, i.e. they occupy an intermediate position between mesofauna and macrofauna. Gongalsky (Gongalsky 2021) pointed out that often "soil zoologists use the taxonomic, but not the dimensional principle to attribute a group to either the meso-or macrofaunal groups." Therefore, enchytraeids are often referred to as mesofauna. We do not have data on enchytraeid abundance with extraction by the wet-funnel technique. The density of hand-sorted enchytraeids, i.e. individuals over 1-2 mm, wildly underestimates taxon abundance. Nevertheless, the numbers of large individuals can be used as a density index correlating with the taxon abundance. In addition, it would be wrong to deliberately exclude enchytraeids with a maximal possible size of about 10-20 mm from consideration since this can lead to biases in soil macrofauna investigation.
Unfortunately, we do not have data on the species composition of enchytraeids in the Urals. There were no specialists in this taxon for a long time in Russia and the country's territory was almost a blank spot (Nurminen 1980). The situation began to improve only recently (Degtyarev et al. 2020), but so far, the fauna of the Urals has not been studied at all.
Russia is often a blank spot in global biodiversity databases and the global earthworm database is no exception (Phillips et al. 2019). Although Russia comprises 12.7% of the world's land (excluding Antarctica), only 1.7% of research sites (179 out of 10842) are included in this database from its territory; all of them are in the European part, not including the Urals. Such a geographic bias can influence the analysis of global patterns. In the Global Biodiversity Information Facility (GBIF), the number of earthworm occurrences from Russia is comparable to that of other countries. However, specialised datasets ) and occurrences of earthworms in datasets on soil invertebrates (Konakova and Kolesnikova 2021, Konakova et al. 2021, Rybalov and Tikhomirova 2021 are few. Moreover, most of the occurrences are concentrated in one dataset (6926 out of 10563 total occurrences) (Shashkov and Ivanova 2021).
The presented dataset includes information on several years within three decades. Such long-term studies provide the most comprehensive information on the local abundance and community composition of soil animals. This information is essential for several reasons. First, combined with data on the weather conditions, the dataset can be used to analyse potential climate change effects on earthworms (Singh et al. 2019). Second, estimating the spatial and temporal variation in soil animal density is necessary to determine sampling efforts and plan the correct sampling design. Moreover, the before-mentioned variation must be assessed at two spatial scales, within sampling plots and study sites. Third, combined with habitat characteristics, the dataset can be used to analyse factors affecting earthworm abundance and diversity.

Project description
Study area description: The Ural Mountains are a north-south-orientated mountain system, located between the East European plain and West Siberian plain (Fig. 1). The study area is situated in the lowest uplands of the Urals (altitudes are 150-400 m above sea level) and belongs to the southern taiga subzone (Kulikov et al. 2013, Fig. 2). Primary coniferous forests (Picea abies (L.) H.Karst., Abies sibirica Ledeb. and Pinus sylvestris L.) and secondary deciduous forests (Betula pendula Roth, Betula pubescens Ehrh. and Populus tremula L.) prevail. Spruce and fir forests with nemoral flora on loam or heavy loam soils dominate on the western slope of the Urals and pine forests on sandy loam or light loam soils prevail on the eastern side (Kulikov et al. 2013  Soil formation occurs on eluvium and eluvium-diluvium of bedrock metamorphic rocks (shales, sandstones, quartzites and silicified limestones). Soil cover is formed mainly by soddy-podzolic soils (Albic Retisols, Stagnic Retisols and Leptic Retisols), burozems (Haplic Cambisols) and grey forest soils (Retic Phaeozems) (Kaigorodova and Vorobeichik 1996). Zoogenically-active humus form (Dysmull) prevail (Korkina and Vorobeichik 2016, Korkina and Vorobeichik 2018, Korkina and Vorobeichik 2021. The climate is Warm Summer Humid Continental, "Dfb" according to the Köppen-Geiger classification (Peel et al. 2007). The average annual air temperature is +2.0°С; the average annual precipitation is 550 mm; the warmest month is July (+17.7°С) and the coldest month is January (-14.2°С) (mean values for the last 40 years, 1975-2015, according to the data of the nearest meteorological station in Revda). The snowless period is about 215 days (from April to October), the maximum depth of the snow cover is about 40-60 cm.

Sampling methods
Study extent: Study sites were located on gentle slopes of ridges in forests with a different stand composition (spruce-fir, pine and birch forests) and arable lands. Loam and heavy loam soddy-podzolic soils (Albic Retisols and Stagnic Retisols) prevail (Table 1).
A total of seven study sites (= dwc:locationID) were established corresponding to local aggregations of different biotopes (Fig. 2). The number of sampling plots within each study site were unequal: R-E30-Sol (spruce-fir forest) included seven sampling plots, R-E20-Pmay (spruce-fir forest) included six plots, R-B20-Pmay (birch forest) and R-S20-Pmay (pine forest) included one sampling plot each, R-E17-Kryl (spruce and birch forests) included four plots, R-Fp17-Kryl (floodplain forest) and R-A16-Kryl (arable land) included three plots each. Characteristics of the sampling plots. Soil description is given according to WRB 2015. Soil pH is given as mean (standard deviation for n = 5); the asterisk denotes data, based on one sample (taken from soil profile). Soil texture: SL -sandy loam, ML -medium loam, HL -heavy loam, Cclay. Study sites R-E30-Sol and R-E20-Pmay were permanent throughout all years of the study (Table 2)  Total number of the sampling plots (soil monoliths\samples) at the study area.
Long-term dynamics of the abundance of earthworms and enchytraeids (Annelida, ...

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The study of earthworms is part of an ongoing long-term monitoring project, which currently covers the following years: 1990 (12 June Sampling description: Earthworms were collected in June, July and August from 1990-2020. Sampling plots 10 × 10 m in size were established in seven study sites (Table 2).
Annelids (earthworms and enchytraeids) were hand-sorted out of soil monoliths 20 × 20 cm in area and 25-30 cm in depth, depending on the occurrence of macroinvertebrates (Fig. 3). The time interval for extracting one soil monolith from the sampling plot was approximately 5 minutes. In most cases, ten monoliths were collected from each plot, except for one monolith from R-E30-Sol in 2020; two monoliths from R-E17-Kryl, R-Fp17-Kryl and R-A16-Kryl in May 2019 and R-E30-Sol in 2020; three monoliths from R-E17-Kryl, R-Fp17-Kryl and R-A16-Kryl in August 2019; five monoliths from R-E20-Pmay in 2015 and 2016 and R-E30-Sol in August 2016 and 2018; 11 monoliths from R-E30-Sol in August 2015; 40 monoliths from R-E20-Pmay in 1990 ( Table 2). The monoliths were collected randomly, excluding nearby trunk areas with a radius of 0.5-1 m around large trees (more than 30 cm in diameter) and any visible pedoturbations. During sampling, each monolith was divided into two layers, corresponding to the samples: the O horizons (forest litter) and A horizon (organic-mineral). Monoliths were not subdivided into layers and were analysed as a whole sample (the A horizon) in R-A16-Kryl (arable land, see Table 2). Monoliths were placed in plastic bags (separately for the layers), delivered to the laboratory and stored before processing at 12°C for no more than five days (as a rule, 1-2 days). The collected earthworms were carefully washed with water, fixed with 10% formalin and then wetpreserved in 70% ethanol. Enchytraeids and earthworm cocoons were fixed with 70% ethanol.
The sampling and hand sorting procedures were the same in all years. Thus, a total of 284 soil monoliths and 553 samples (organic and organic-mineral horizons) were collected over all these years (Fig. 4).  Unfortunately, the materials collected in 1990 and 1991 were not preserved in full until now. Therefore, in the dataset, unlike all others, these years marked with dwc:basisOfRecord = "HumanObservation." Quality control: A total of more than 3300 individuals of earthworms, 7200 egg cocoons and cocoon exuvia of earthworms and 6900 individuals of enchytraeids were collected. All specimens were wet-preserved in 70% alcohol and stored (with the partial exception of materials from 1990-1991) in the depository of the Laboratory of Population and Community Ecotoxicology of the Institute of Plant and Animal Ecology, Ural Branch, Russian Academy of Sciences (IPAE UB RAS). Adult earthworms were identified to species level using the taxonomic key for the fauna of Russia (Vsevolodova-Perel 1997). Juvenile specimens were identified to species level using external characteristics, such as the colouration, the prostomium shape, the pattern of setae and examination of the internal structure during autopsy (the shape of nephridial bladders, the presence and location of diverticula

Geographic coverage
Description: The study area is located in the southern taiga subzone of the Central Urals, 60-70 km westwards from Yekaterinburg. Study sites are placed in coniferous forests (spruce-fir and pine), secondary birch forests, floodplain forests of small rivers and cultivated arable lands.

Taxonomic coverage
Description: General taxonomic coverage is one phylum, one class, two orders, two families, eight genera and ten species of annelids.  ) presents information from a longterm monitoring programme for two taxa of Annelids, Lumbricidae and Enchytraeidae, which dwell in the topsoil of spruce-fir, birch, pine and floodplain forests in the Central Urals. The dataset describes the earthworm community structure (list of species, species abundance, number of egg cocoons, cocoon exuvia, juveniles and adults) and enchytraeid abundance. The dataset consists of 553 sampling events (= samples), corresponded to 12739 occurrences (earthworms, mainly identified to species and earthworm cocoons and enchytraeids, identified to family), collected during 1990-1991, 2004, 2014-2016 and 2018-2020. In total, 3305 individuals of earthworms were collected, representing ten (out of twelve) species and all eight genera recorded for the fauna of the Central Urals. In addition, 7292 earthworm egg cocoons and cocoon exuvia and 6926 individuals of enchytraeids were accumulated. The presence-absence data on each of the ten earthworm species, egg cocoons, cocoon exuvia and enchytraeids are provided for each sampling event. All data were collected in undisturbed non-polluted areas and are used as a local reference for ecotoxicological monitoring. The dataset provides valuable information for estimating the composition and abundance of earthworm communities in different habitats over a long time and contributes to the study of soil fauna biodiversity in the Urals. Examples: "egg cocoon", "cocoon exuvium". basisOfRecord The specific nature of the data record. A constant "PreservedSpecimen". decimalLatitude The geographic latitude (in decimal degrees, using the spatial reference system given in geodeticDatum) of the geographic centre of the sampling plot. A variable.
Example: "56.7210". decimalLongitude The geographic longitude (in decimal degrees, using the spatial reference system given in geodeticDatum) of the geographic centre of the sampling plot. A variable.
coordinateUncertaintyInMetres The horizontal distance (in metres) from the given decimalLatitude and decimalLongitude describing the smallest circle containing the whole of the Location. A variable. Examples: "10", "100".

geodeticDatum
The ellipsoid, geodetic datum or spatial reference system (SRS) upon which the geographic coordinates given in decimalLatitude and decimalLongitude are based.
A constant "WGS84". kingdom The full scientific name of the kingdom in which the taxon is classified. A constant "Animalia".

phylum
The full scientific name of the phylum or division in which the taxon is classified. A constant "Annelida". class The full scientific name of the class in which the taxon is classified. A constant "Clitellata". order The full scientific name of the order in which the taxon is classified. A variable.
Example: "Crassiclitellata". family The full scientific name of the family in which the taxon is classified. A variable.
Example: "Lumbricidae". genus The full scientific name of the genus in which the taxon is classified. A variable.
Example: "Dendrobaena". specificEpithet The name of the first or species epithet of the scientificName. A variable. Example: "octaedra". taxonRank The taxonomic rank of the most specific name in the scientificName. A variable.
year The four-digit year in which the Event occurred, according to the Common Era