Classification and mapping of habitats in the northwestern part of the Bolshezemelskaya tundra

Abstract

The integrity and preservation of natural habitats is the basis for the existence of flora and fauna, as well as many aspects of the life of the indigenous population. The high sensitivity of Arctic landscapes and natural ecosystems to anthropogenic and climatic factors predetermines the need for monitoring of habitats. Classification and inventory of Arctic habitats is made on the example of a key site in the Bolshezemelskaya tundra — adjacent tundra to the Bolvansky Nos Cape (23.7 km2) (Fig. 1). The diagnostics of biotopes was carried out on the basis of a previously developed typological scheme of territorial units of vegetation (TUV), which, along with the syntaxonomic composition, takes into account the features of ecology and spatial organization (Lavrinenko, 2020b; Lavrinenko, Lavrinenko, 2021). The diagnostics of higher units of habitats is based on their position on the generalized geomorphological profile and relief elements, which predetermine the peculiarities of the impact of the entire variety of en vironmental and climatic factors on biotopes. The types of spatial structures (temporal and ecological series, complexes, and combinations) of heterogeneous TUVs, reflecting the location features, intensity, direction, and the result of the environmental factors interaction, are the main diagnostic characteristics of habitats. The classification of vegetation and position of syntaxa, taking into account their confinement to TUVs, underlie the accurate diagnosis of biotopes. The phytosociological (= Braun-Blanquet) classification is the basis of the TUVs nomenclature. The list of syntaxa of different ranks (Matveyeva, Lavrinenko, 2021) is the basis for the formation of the TUVs categories names that diagnose biotopes. A digital elevation model (DEM) of the key area was made using ArcticDEM data (https://www.pgc.umn.edu/data/arcticdem/) to estimate the location of TUVs as habitat indicators (Fig. 2a). NDWI (Normalized Difference Water Index) (McFeeters, 1996) and NDVI (Normalized Difference Vegetation Index), which reflects the reserves of green phytomass (Walker et al., 2003) (Fig. 2b) were calculated from Sentinel-2A satellite images. Spatial combination of several layers – high-resolution satellite images, DEM, spectral indices (Fig. 3), in GIS made it possible to characterize the important indicators of biotopes. Habitats of two categories of the highest, first level — AB and CB, confined to large elements of the landscape, are found in a key area in the tundra zone. The categories of the second level (AB1, …, CB3) differ in their position on the generalized geomorphological profile, from the highest positions (AB1 — eluvial locations) to the lowest ones (CB3 — accumulative marine terraces). The features of the substrate, along with the position on the profile, were taken into account when identifying categories of biotopes of the third categories. Thus, in the AB1 category, habitats of a lower level differ significantly in terms of soil characteristics: AB1.1, sandy; AB1.2 — loamy-gravelly carbonate, AB1.3 — gleyzems and peat-gleyzems. The well-pronounced physiognomic (color, texture) and spectral (indices, signatures) characteristics of the TUVs levels, along with the position in the relief and features of the substrate, were used to distinguish the fourth and lower habitat categories. Diagnostics of plant communities forming TUVs was carried out on the basis of reference signatures (using Sentinel-2 images) of those phytocoenoses in which geobotanical relevés were made with coordinate reference and syntaxonomic affiliation was established. Terrestrial plots are assigned to 2 categories of habitats of the first level, 7 — of the second, 13 — of the third and 18 — of the fourth, which include all the diversity of biotopes of the key site and unite those that are close in their position on the geomorphological profile and ecological indicators. All categories of habitats of the third level, and in some cases the fourth one, are diagnosed with TUVs classes (Lavrinenko, 2020b), represented by simple and complex combinations of plant communities of different syntaxa. The characteristics of vegetation and soils, the composition of syntaxa (those that are described) are given for categories of the second – third levels. More than 1100 contours, including 140 represented by water bodies, have been identified in the key area. The habitats map of the northwestern part of the Bolshezemelskaya tundra was prepared on a scale of 1 : 25 000. It demonstrates the diversity of biotopes in the study site; terrestrial plots classified as habitat categories of the first —fourth levels are presented on it (Fig. 29, 30). The main emphasis in the identification and characterization of habitats is made on their resource potential for species and communities of plants and animals, as well as for humans. This immediately transfers the question of the significance and relevance of such works from the field of fundamental academic research on the study and mapping of biotopes, to the field of direct practical application of the results obtained. Different categories of habitats have different resource values for certain biological objects, which makes it possible to characterize them from the standpoint of ecological, economic and environmental significance.

Russian Arctic Vegetation Archive—A new database of plant community composition and environmental conditions

“…A significant part of the Western Siberian dataset (1003 plots) was compiled by team members during the 2017 expedition to the Yamalo-Nenets Autonomous district (Sofronova et al, 2019;Telyatnikov et al, 2019aTelyatnikov et al, , 2019bTelyatnikov, Khitun, Chernyadyeva, & Kuzmina, 2021;Telyatnikov, Khitun, Chernyadyeva, Kuzmina, & Ermokhina, 2021;Potemkin et al, 2021), while other datasets were independently contributed by researchers or based on previously published data (Dedov, 1940;Kholod, 2007;Koroleva & Kopeina, 2018, Koroleva et al, 2019Lavrinenko et al, 2016;Lavrinenko & Lavrinenko, 2018a, 2018bMatveyeva, 2006;Matveyeva & Lavrinenko, 2011;Pospelova & Pospelov, 2010;Telyatnikov et al, 2015Telyatnikov et al, , 2022Walker et al, 2019).…”

“…Openaccess data can be freely and directly downloaded from the AVA-RU website as Creative commons 4.0 (https://opend efini tion.org/licen ses/cc-by/), but citation of the data source is required (see above). The AVA-RU data have already been used for a broad range of research including vegetation classification and mapping (Koroleva & Kulyugina, 2015;Lavrinenko & Lavrinenko, 2018a, 2018bLavrinenko, Matveyeva & Lavrinenko, 2016;Matveyeva, 2006;Telyatnikov, Khitun, Chernyadyeva, & Kuzmina, 2021;Telyatnikov, Khitun, Chernyadyeva, Kuzmina, & Ermokhina, 2021;Telyatnikov et al, 2022), species distribution modelling (Ermokhina et al, 2023) and species richness prediction . We also plan the import of the AVA-RU datasets into sPlot (s-Plot, 2023; https://www.idiv.de/en/splot.html).…”