Woody vegetation under industrial pollution (Southern Urals, Russia): modifying influence of habitat conditions

Description

Data Records

The data in this sampling event resource has been published as a Darwin Core Archive (DwC-A), which is a standardized format for sharing biodiversity data as a set of one or more data tables. The core data table contains 411 records.

2 extension data tables also exist. An extension record supplies extra information about a core record. The number of records in each extension data table is illustrated below.

This IPT archives the data and thus serves as the data repository. The data and resource metadata are available for download in the downloads section. The versions table lists other versions of the resource that have been made publicly available and allows tracking changes made to the resource over time.

Versions

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How to cite

Please be aware, this is an old version of the dataset.  Researchers should cite this work as follows:

Bergman I, Nesterkov A (2021): Woody vegetation under industrial pollution (Southern Urals, Russia): modifying influence of habitat conditions. v1.1. Institute of Plant and Animal Ecology (IPAE). Dataset/Samplingevent. https://ipt.ipae.uran.ru/resource?r=frm_bergman_2012&v=1.1

Rights

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

GBIF Registration

This resource has been registered with GBIF, and assigned the following GBIF UUID: 61384edd-2d0a-437b-8cf0-ff4d2dfcc0da.  Institute of Plant and Animal Ecology (IPAE) publishes this resource, and is itself registered in GBIF as a data publisher endorsed by Participant Node Managers Committee.

Keywords

Samplingevent; aerial pollution; biodiversity; biomass; biotope; coarse woody debris (CWD); copper smelter; dead-standing tree; deadwood; diameter at breast height (DBH); forest stand; mortmass; phytomass; stump; subcanopy

Contacts

Igor Bergman

• Metadata Provider ●
• Author ●
• Originator ●
• Point Of Contact

senior researcher

Institute of plant and animal ecology, UB RAS

Yekaterinburg

RU

http://orcid.org/0000-0002-5587-3840

Alexey Nesterkov

• Metadata Provider ●
• Curator ●
• Originator ●
• Point Of Contact

researcher

Institute of plant and animal ecology, UB RAS

Yekaterinburg

RU

http://orcid.org/0000-0001-8382-8468

Geographic Coverage

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.

Taxonomic Coverage

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

Temporal Coverage

Project Data

No Description available

The personnel involved in the project:

Sampling Methods

The sampling process included the assessment of all woody vegetation specimens at sampling plots. During the assessment, we identified the following forest elements: 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 a forest stand) and underwood (small trees and bushes not included in the forest stand); 3. the half-dead tree – the main trunk of which died, but branches with leaves emerge from the preserved dormant buds. All detected trees were assigned to the forest stand; 4. the dead-standing tree – dead but not fallen trees with a DBH no less than 5 cm and height more than 2 m; 5. the stump – dead but not fallen trees, less than 2 m in height; 6. the deadwood – a fallen/hung tree trunk (or part of it), which is entirely within the sampling plot; 7. the fragment of deadwood – 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). For representatives of these forest elements, the diameters (at breast height or root collar level) were measured, and phytomass (for living trees) or mortmass (for coarse woody debris) were calculated. Diameter measurements were taken in two mutually perpendicular directions using a caliper (or a pole caliper for subcanopy), with the subsequent calculation of the arithmetic mean diameter. Phytomass and mortmass were calculated using our detailed characterization of the model trees, obtained in August 2010 outside the sampling plots under consideration and published earlier (Usoltsev et al., 2012). A detailed description of the methods for determining the aboveground phytomass of model trees is given below. The sample of model trees of each species was formed following the series of tree diameter distributions. The model trees were fallen in August 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 made it possible to define the diameters 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 disks 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 constant weight in an oven at 110°C. Then the oven-dry mass of the wood and bark were used to calculate a wood/bark proportion and the oven-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 separate needles from the branches and then separately weigh 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 oven-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 oven-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 100–105 ºC. To determine the phytomass of subcanopy trees, they were subdivided into two groups. First, 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 aboveground oven-dry phytomass was determined. From trees more than 0.5 m in height, leafy/needled shoots were cut off with pruning shears, 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 oven-dry matter content in both fractions was calculated. Their values were used to determine the oven-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, summarized with the crown’s phytomass, and then determined the aboveground oven-dry phytomass.

Method step description:

1. Fieldwork. The sampling plots were tried to be founded so that the anthropogenic impact (recreation, grazing, felling, haymaking) was minimal. Three sampling plots with a size of 25×25 m were founded within each type of habitat, except for the reed swamp (two plots at the non-polluted area). When the habitat configuration did not allow to arrange 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. 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. 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 sparse birch stand (10 cards) and marshy meadow (5 cards)) with a number were pulled out of the pocket, 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 meters; 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 founded at places where aboveground 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 dead-standing trees and half-dead trees were measured in the same way. The stump diameters were measured using a caliper at the base of the stumps 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 deadwood and fragment of deadwood were measured using a caliper: the base and the top diameters of the deadwood (cm) and its length (m) were measured.
2. Biomass calculation. Based on the data of measurements of the forest elements, we calculate the volume of deadwood (V_deadwood): V_deadwood = 1/3 × π × H(R^2_base + R_base × R_top + R^2_top), where H – length of deadwood, m; R_base – base radius of deadwood, m; R_top – top radius of deadwood, m. The volume (m3) of each deadwood that falls within the sampling plot (a whole or a fragment) was calculated. To calculate the aboveground phytomass of trees of the forest stand, subcanopy, and dead-standing trees in each habitat type, we used our data obtained and published earlier, which represent a detailed characterization of the model trees (Usoltsev et al., 2012). A detailed description of the methods for determining the aboveground phytomass of model trees is given in the Sampling section. These data served as the basis for constructing regression equations and subsequent evaluation of the aboveground phytomass of each tree specimen in each habitat type. For tree species of the forest stand, subcanopy, and dead-standing trees, the calculation of the parameters of the regression equations were performed by the formula: P_phytomass = a1 × D^a2, where P_phytomass – oven-dry aboveground phytomass of the plant, kg; D – diameter of the trunk, cm (for forest stand and dead-standing 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 nonlinear estimation method (Levenberg-Macwardt algorithm, calculated in STATISTICA v.8.0); the formulas for different tree species are presented below. Tree species as part of the forest stand: P=0.098613*D^2.53413 (Betula sp.); P=0.12004*D^2.38449 (Pinus sylvestris); P=0.321051*D^2.04809 (Picea obovata); P=0.14492*D^2.30065 (Populus tremula); P=0.065389*D^2.4907 (Alnus incana); P=0.050513*D^2.69275 (Sorbus aucuparia). Tree species as part of the subcanopy: P=0.040593*D^2.17829 (Chamaecytisus ruthenicus); P=0.025749*D^3.28474 (Sorbus aucuparia); P=0.01467*D^2.00523 (Rubus idaeus); P=0.060674*D^2.78288 (Rosa majalis); P=0.017878*D^2.92874 (Pinus sylvestris); P=0.023576*D^3.15147 (Betula sp.); P=0.03445*D^3.08644 (Populus tremula); P=0.017657*D^3.27133 (Alnus incana); P=0.052977*D^2.40134 (Abies sibirica); P=0.065709*D^1.90958 (Prunus padus); P=0.041403*D^2.73328 (Cotoneaster lucidus); P=0.033553*D^2.67063 (Salix caprea). Tree species as dead-standing trees of the forest stand: P=0.12954*D^2.39547 (Betula sp.); P=0.130432*D^2.31176 (Pinus sylvestris); P=0.068865*D^2.47813 (Alnus incana). The coefficients of determination (R^2) for all equations vary within 0.71–0.99. All constants are statistically significant (p<0.05), except for Rubus idaeus (p<0.08). Due to restrictions from the forestry, 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 deadwood of this species) and Populus tremula was estimated using literature data (Usoltsev et al., 2018). The mortmass of the deadwood (P_mort) was calculated based on the volume estimations: P_mort = V_mort × p_mort, where P_mort – oven-dry mortmass, kg; V_mort – the volume of deadwood, m3; p_mort – average density of moderately decomposed deadwood, kg/m3. The data on deadwood densities were taken as constants from literature source (Klimchenko et al., 2011) for dead pine (constant for deadwood of coniferous trees, 0.307 kg/m3) and birch (constant for deadwood of deciduous trees, 0.428 kg/m3), as these species predominate in the territory of our study.

Collection Data

Bibliographic Citations

1. Klimchenko A.V., Verkhovets S.V., Slinkina O.A., Koshurnikova N.N. 2011. Zapasy krupnykh drevesnykh ostatkov v srednetayezhnykh ekosistemakh Priyeniseyskoy Sibiri [Stocks of coarse woody debris in the middle taiga ecosystems of the Yenisei Siberia] // Geografiya i prirodnyye resursy. № 2. P. 91-97 (in Russian).
2. Kofman G.B. 1986. Rost i forma derev’yev [Growth and shape of trees]. Novosibirsk: Nauka. 211 p. (in Russian).
3. Usoltsev V.A., Chasovskikh V.P., Tsepordei I.S. 2018. Fitomassa lesnykh derev'yev i biogeografiya: issledovaniye sistemnykh svyazey sredstvami informatsionnykh tekhnologiy: monografiya. [Phytomass of forest trees and biogeography: a study of systemic relationships through information technology: a monograph.] Yekaterinburg: Izdatel'stvo Ural'skogo gosudarstvennogo lesotekhnicheskogo universiteta. 456 p. + CD-ROM. (in Russian).
4. Usoltsev V.A., Vorobeychik E.L., Bergman I.E. 2012. Biologicheskaya produktivnost’ lesov Urala v usloviyakh tekhnogennogo zagryazneniya: issledovaniye sistemy svyazey i zakonomernostey [Biological productivity of the forests of the Urals in the conditions of technogenic pollution: a study of the system of connections and patterns]. Yekaterinburg: Izdatel'stvo Ural'skogo gosudarstvennogo lesotekhnicheskogo universiteta. 365 p. (in Russian).

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