Abstract
BACKGROUND: Since the late 1980s, long-term monitoring of terrestrial ecosystems in metal-contaminated areas near the Middle Ural Copper Smelter has been carried out in the Central Urals. As a part of these monitoring programmes, the data on species diversity, community composition and abundance of soil macroinvertebrates continue to be gathered. NEW INFORMATION: The dataset (available from the GBIF network at https://www.gbif.org/dataset/61e92984-382b-4158-be6b-e391c7ed5a64) includes a 2004 census for soil macroinvertebrates of spruce-fir forests along a pollution gradient in the Central Urals. The dataset describes soil macrofauna's abundance (the number of individuals per sample, i.e. the density) and community structure (list of supraspecific taxa, list of species for most abundant taxa and supraspecific taxa or species abundance). Seventeen sampling plots differed in the levels of toxic metal (Cu, Zn, Pb, Cd and Fe) soil contamination from air emissions of the Middle Ural Copper Smelter (heavily polluted, moderately polluted and unpolluted areas). The dataset consists of 340 sampling events (= samples corresponding to upper and lower layers of the 170 soil monoliths) and 64658 rows (2907 and 61751 for non-zero and zero density of taxa, respectively). Arachnida (Araneae and Opiliones), Carabidae (imagoes), Elateridae (larvae), Chilopoda, Diplopoda, Gastropoda, Staphylinidae (imagoes) and Lumbricidae were identified to species level. In contrast, Mermithida, Enchytraeidae, Lepidoptera larvae, Diptera larvae, Hemiptera, Hymenoptera and some other insects were identified to family or order levels. In total, 8430 individuals of soil macroinvertebrates were collected in two soil layers (organic and organic-mineral horizons), including 1046 Arachnida (spiders and harvestmen), 45 Carabidae, 300 Elateridae, 529 Myriapoda, 741 Gastropoda, 437 Staphylinidae, 623 Lumbricidae and 4709 other invertebrates. The presence-absence data on each taxon are provided for each sampling event. An overwhelming majority of such absences can be interpreted as "pseudo-absences" at the scale of sampling plots or study sites. The dataset contains information helpful for long-term ecotoxicological monitoring of forest ecosystems and contributes to studying soil macrofauna diversity in the Urals.