The Ural Mountains are a north-south-orientated mountain system in the Urals, located between the East European and West Siberian plains. The study area is located in the lowest uplands (300–400 m altitude above sea level) in the southern taiga subzone. The prevailing forest types are herb pineries and secondary grass herb birch forests with linden, aspen and larch populations. The main soil types are brown mountain-forest and forest soils, grey soils, mountain-forest and mountain-podzol chernozems. The climate is continental, moderately cold. The annual temperature is 1.8°C and the average precipitation is 450–550 mm. The duration of the vegetation period is 160–170 days and the average height of the snow cover is about 40 cm.

The study was carried out in the Karabash Copper Smelter vicinities (Fig. 1), located within Karabash (90 km northwest of Chelyabinsk, Southern Urals) and it has operated since 1910. KCS is one of the largest point polluters in Russia; the main components of its emissions are heavy metals, dust and sulphur dioxide. The total amount of atmospheric emissions in the 1970s exceeded 370,000 t (of these, 364,500 t of sulphur dioxide and 28,800 t of dust, containing absorbed heavy metals, such as Cu (1530 t), Pb (2570 t) and As (1920 t)). In 2005, the total emissions were no more than 41,000 t, including 38,100 t of sulphur dioxide and 1300 t of dust containing 340 t of Cu, 20 t of Pb and 7 t of As. However, the pool of accumulated pollutants may still strongly impact the biota (Mukhacheva et al. 2010). Two study areas were explored: the first one with intense industrial pollution (0.5–5 km from the smelter, surveyed an area of about 30 km²; dead-cover forests with soil surface mostly covered with non-decomposed litter) and the second one with a regional background level of pollution (20–25 km south of the Smelter, total area of about 50 km², forests with well-developed herbaceous layer (100% coverage in most cases)). Within each area, seven types of habitats were identified, differing in the position in the relief and vegetation structure.

The study was carried out in vicinities of the Karabash Copper Smelter (55.469 N, 60.209 E), located within the City of Karabash (90 km northwest of Chelyabinsk, Southern Urals). A total of 41 sampling plots were established in seven types of habitats: pine, birch and floodplain forests, reed swamp, sparse birch stand, marshy meadow and dump of household waste. All habitats were surveyed using six sampling plots, except for the reed swamp (five plots). The study was completed in July 2012.

The survey of forest woody vegetation at sampling plots

The survey of forest woody vegetation is the leading and only method of accounting for forest resources, making possible the quantitative and qualitative evaluation of the forest health.

During the survey, we identified the following forest elements (according to Harmon et al. 2004):

1. the forest stand – living trees with a diameter at breast height (DBH) of more than 5 cm;
2. the subcanopy – all living trees with DBH of less than 5 cm and height of more than 10 cm; this forest element includes the undergrowth (trees, capable of forming the forest stand) and underwood (bushes, not capable of forming the forest stand);
3. the half-dead tree – the main trunk of which died, but branches with leaves emerge from the dormant buds preserved at the trunk. All detected trees were assigned to the forest stand;
4. the standing dead tree – dead but not fallen trees with a DBH no less than 5 cm and height more than 2 m;
5. the stump – lower part of the dead tree trunk, less than 2 m in height. The diameter was usually measured at the point of breaking of a tree trunk;
6. the downed bole – a fallen/hung tree trunk (or part of it), which is entirely within the sampling plot;
7. the fragment of a downed bole – a fallen tree trunk (or part of it), which is partially within the sampling plot (only the part within the plot was taken into account).

The information about the forest element type is encoded in the eventID and occurrenceID. The authors tried to establish the sampling plots so that the anthropogenic impact (recreation, grazing, felling, haymaking) was minimal. Three sampling plots with a size of 25 × 25 m were established within each type of habitat, except for the reed swamp (two plots at the unpolluted area, see Table 1). When the habitat configuration did not allow arranging a rectangular sampling plot, its size could vary within 471–691 m². Complete estimation of forest woody vegetation was performed at each site in both the subcanopy and forest stand. The trees in the forest stand were estimated throughout the entire sampling plot. An estimation of trees in the subcanopy was carried out at 1–10 subplots of 1–34 m² selected within the sampling plot, depending on the biotope (Table 2).

The distance between the sampling plots in the birch, pine and floodplain forests and the sparse birch stand was 15–40 m. Therefore, subplots in these habitats were arranged randomly: the site was divided into equal squares 5×5 m (1×1 m for the sparse birch stand); each square was assigned a number. Then, three cards (except for some cases, see Table 2) with a number were selected randomly and the corresponding subplots within the sampling plot were approved. The reed swamp and marshy meadow were of limited size: in these habitats, the distance between sampling plots was several metres; in some cases, plots were adjacent to each other. The location of subplots within the sampling plot was uniform. For the waste dump, only one subplot within each sampling plot was established at places where above-ground vegetation was detected.

In the forest stand, a caliper with a scale up to 1 cm was used to measure the trunk diameters. Tree specimens with a diameter at breast height (1.3 m) equal to 5 cm or more were taken into account. Diameter measurements were taken in two mutually perpendicular directions, with the subsequent calculation of the arithmetic mean diameter. The diameters of the standing dead trees and half-dead trees were measured in the same way. The stump diameters were measured at the fracture point using a caliper in two mutually perpendicular directions. Stumps with a base diameter of more than 5 cm were taken into account. Next, the diameter of the subcanopy trees was measured at the level of the root collar using a pole caliper with an accuracy of 0.1 cm. Finally, the downed boles and fragments of downed boles were measured using a caliper: the base and the top diameters of the downed boles (cm) and its length (m) were measured.

The volume of downed bole (V_dbole) was calculated using a modified truncated cone volume equation:

V_dbole=1/3π × H(R²_base + R_base × R_top + R²_top),

where H – length of a downed bole, m; R_base – base radius of a downed bole, m; R_top – top radius of a downed bole, m (these three parameters are not included in the dataset, but are available upon request). The advantage of this formula is its simplicity (only three parameters are involved) and forest ecologists widely use it to assess downed bole biomass rapidly. The volume (m³) of each downed bole that falls within the sampling plot (a whole or a fragment) was calculated.

To calculate the above-ground phytomass of trees of the forest stand, subcanopy and standing dead trees in each habitat type, we used our data obtained and published earlier, which represent a detailed characterisation of the model trees (Usoltsev et al. 2012). A detailed description of the methods for determining the above-ground phytomass of model trees is given below. These data served as the basis for constructing regression equations and subsequent evaluation of the above-ground phytomass of each tree specimen in each habitat type.

For tree species of the forest stand, subcanopy and standing dead trees, the calculation of the parameters of the regression equations were performed by the formula (Kofman 1986):

P_phytomass=a₁ × D^a₂ ,

where P_phytomass – absolute dry above-ground phytomass of the plant, kg; D – diameter of the trunk, cm (for forest stand and standing dead trees measured at the height of 1.3 m, for subcanopy measured at root collar level); a₁ and a₂ – constants of the equation. This type of regression is considered to be the most biologically determined (Kofman 1986). Equation constants are selected by the non-linear estimation method (Levenberg-Macwardt algorithm). The procedure is implemented in STATISTICA v.8.0. Thus, the biomass of each woody plant can be efficiently and reliably estimated by the size of the trunk diameter using the presented dependence equations (Table 3).

Due to restrictions from the Forestry authorities, the following tree species were prohibited for felling: in the forest stand – Acer negundo, Alnus incana, Crataegus sanguinea, Larix sibirica, Malus baccata, Populus tremula, Prunus padus, all species of Salix and Ulmus and all half-dead trees; in the subcanopy – Acer negundo, Larix sibirica, all species of Salix (except for Salix caprea) and Viburnum opulus. Biomass for Alnus incana (including the mortmass of downed boles of this species) and Populus tremula was estimated using literature data (Usoltsev et al. 2018).

The mortmass of the downed bole (P_mort) was calculated, based on the volume estimations:

P_mort=V_mort × p_mort ,

where P_mort – absolute dry mortmass, kg; V_mort – the volume of downed bole, m³; p_mort – average density of moderately decomposed downed bole, kg/m³. The data on downed bole densities were taken as constants from literature sources (Klimchenko et al. 2011) for dead pine (constant for downed bole of coniferous trees, 0.307 kg/m³) and birch (constant for downed bole of deciduous trees, 0.428 kg/m³), as these species predominate in the territory of our study.

A detailed description of methods for determining the above-ground phytomass of model trees

The processing of model trees was carried out in August 2010 outside the sampling plots under consideration according to the following method (Usoltsev and Zalesov 2005).

Model trees of each species were selected in such a way as to cover the entire range of variation in their diameters, from minimum values to maximum values. The model trees were felled in August 2010 when the foliage/needles of the current year were fully formed. After felling, the tree’s length was measured. First, the trunk was divided into ten sections. Then, in the middle of each section, measuring from the butt, discs were cut out making it possible to define the diameter of the trunk in the bark and without bark. These measurements were used to calculate the volumes of the tree’s wood and bark. Next, the bark was removed from the discs taken at relative heights of 20, 50 and 80% of the total trunk height, the wood and bark were weighed separately with an accuracy of 0.1 g, their volume was determined and dried to a constant weight in an oven at 110°C. Then the absolute dry mass of the wood and bark were used to calculate a wood/bark proportion and the absolute dry phytomass of the wood and bark of the entire tree trunk.

The phytomass of tree crowns and their structural parts was determined after dividing the crowns into three sections of the same length, since crowns are heterogeneous in the vertical direction regarding the age and thickness of branches, branch coverage and qualitative composition of needles. After weighing each section of the crown (with an accuracy of 50 g), they were divided into leafy/needled and non-leafy/non-needled branches. Then, a sample (about 0.5 kg) was taken from each section’s leafy/needled part to establish the ratio of needles and skeletal parts. For this purpose, we separated needles from the branches and then separately weighed these components’ mass for each sample (with an accuracy of 1 g). The phytomass of needles and woody parts was determined according to the established ratios for each section and the entire crown. To determine the moisture content and absolute dry weight of needles and branches, samples were taken from each part of the crown and then immediately weighed with an accuracy of 0.01 g. Samples of branches were taken separately from leafy/needled and non-leafy/non-needled branches. The obtained values were used to calculate the absolute dry weight of the needles and tree branches. Weighed portions of needles and branches were dried to constant weight in thermostats at a temperature of 110ºC.

To determine the phytomass of subcanopy trees, they were subdivided into two groups. Firstly, in height, trees less than 0.5 m were fractionated (divided into a trunk, branches and foliage). After that, they were weighed, dried at 110°C to constant weight and the above-ground absolute dry phytomass was determined. From trees more than 0.5 m in height, leafy/needled shoots were cut off with pruning shears and a sample of 100–500 g was taken and weighed; then leaves/needles were removed from the sample and it was re-weighed. Then the leaves/needles and the rest of the sample were dried separately to constant weight, weighed again and the absolute dry matter content in both fractions was calculated. Their values were used to determine the absolute dry weight of the crown of the entire plant. Together with non-leafy/non-needled shoots, the trunk mass was weighed in total, dried at 110°C to constant weight, summed with the crown’s phytomass and then the above-ground absolute dry phytomass was determined.

Plant species identification was carried out mainly in the field; specimens with controversial species affiliation were photographed or placed in a Herbarium and identified later in a laboratory by specialists from the Institute of Plant and Animal Ecology of the Ural Branch of the Russian Academy of Sciences (IPAE UB RAS).

In the following cases, occurrences were identified only to taxonomic ranks of high levels; first, the forest elements related to coarse woody debris (downed boles, fragments of downed boles and stumps). As a rule, these elements are destroyed and reliable determination of their taxonomic affiliation is difficult even down to the family level. Second, forest elements that were absent at the study sites were added to the dataset in order to record the very fact of their absence. In this case, we found it unnecessary to detail more than to the level of the type.

The studied areas are located in the southern taiga subzone of the Southern Urals, in the vicinity of Karabash (polluted sites) and 20 km south of Karabash (sites with a background level of pollution). The same set of habitats represents both polluted and non-polluted areas: pine, birch and floodplain forests, reed swamp, sparse birch stand, marshy meadow and dump of household waste.

55.3222 and 55.4993 Latitude; 60.1092 and 60.2733 Longitude.

General taxonomic coverage is 1 phylum, 2 classes, 7 orders, 8 families, 19 genera and 23 species of woody vegetation (Table 4).

It should be noted that the mature birch trees, presented in the dataset, are identified to genus. The birch is the only species which was not identified by biological species, but by genus (Novikova 2016) since different growing conditions determine a large variability of morphological characters in individual species. Vetchinnikova (Vetchinnikova 2004) noted that, “... the phylogeny and relationships of species in the genus Betula are rather complex; therefore its systematics is extremely difficult and requires new methodological approaches”. Nevertheless, young plants of the genus Betula were quickly identified to species by the presence/absence of pubescence on the leaf blades.

It is also worth adding that only a few members of the genus Salix have been identified as species. The overlap of the ranges of many willow species and their close phylogenetic relationship contributed to the emergence of a significant number of natural hybrids in willows (about 90 hybrid forms have been described) (Antsiferov 1984), which significantly complicates the identification of their species.

Biomass and mortmass of woody vegetation in metal-contaminated areas (Southern Urals, Russia)

https://ipt.ipae.uran.ru/resource?r=frm_bergman_2012&v=1.4

1