Phytoindication approach to assessing factors determining the habitat preferences of red deer (Cervus elaphus)

Abstract

The study examined the possibility of using the phytoindication technique to describe habitat preferences of red deer in a relatively homogeneous area. Two alternative hypotheses were tested. Hypothesis 1 suggests that the relationship between red deer and vegetation is due to a trophic factor, so preferences for individual plant species cause vegetation to influence the distribution of animal numbers. Hypothesis 2 suggests that environmental factors influence vegetation, structuring and determining the productive level of the community as a whole. Therefore, environmental factors, rather than individual plant species, cause vegetation-animal interactions. The research was conducted on Biryuchiy Island Spit, where the Azov-Sivash National Nature Park is located. The geobotanical surveys were performed in three types of ecosystems: sandy steppe (vegetation class Festucetea vaginatae), saline meadows (vegetation class Festuco–Puccinellietea), and artificial forest plantation (vegetation class Robinietea). 250 releves were recorded according to the Brown-Blanquet approach. The number of fecal pellets and the number of groups of pellets of red deer was recorded together with geobotanical surveys in the same sample plots. The pellet groups counted in the field were converted to deer densities in specific vegetation classes taking into account the number of pellet groups on the site and the decay rate of the fecal pellets. The vegetation types were distinguished by the number of deer fecal pellets per unit area. The highest number of fecal pellets was found for the plant class Festucetea vaginatae, somewhat fewer fecal pellets were in the plant class Robinietea, and the lowest number was in the plant class Festuco-Puccinellietea. A geometric distribution model is adequate for explaining the experimental data on the number of fecal pellets. A total of 59 species of flowering plants were found. Based on the species composition and projective cover of species, the ecological regimes of ecotopes were identified by phytoindication. The correspondence analysis of the vegetation revealed two ordination axes. The ordination axis 1 (CA1) was able to explain 11.3% of community inertia, and the ordination axis 2 (CA2) was able to explain 5.2% of community inertia. The maximum excretory activity of animals was recorded for the central part of the ordination space, indicating the presence of an optimum zone in the gradient of environmental factors that structure plant communities. The forward selection procedure allowed the Nutrients Availability variable to be selected as the most important variable to explain variation in the plant community structure. The number of deer fecal pellets exhibited different patterns of response in the Nutrients Availability gradient. The response within the plant class Festucetea vaginatae could best be explained by Model III from the list of HOF-models. The response of the excretory activity of deer within the class Festuco-Puccinellietea could best be fitted by the model IV, which represents a symmetric Gaussian curve. The response of excretory activity in the Robinietea vegetation class was asymmetrical bimodal. The ecological properties of the red deer ecological niche in both the drier and less mineralized part of the range of ecological conditions and the wetter and more mineralized part should be assessed in the context of the prospects for future studies.

Response of earthworms to changes in the aggregate structure of floodplain soils

“…Our results indicate that the abundance of earthworms decreases under conditions of predominance of large aggregates (size greater than 5 mm). The ordinate axis is the number of worm individuals in a 25×25 cm soil sample; the abscissa axis is the proportion of aggregate fractions; 1 -fractions > 10 mm; 2 -fractions 7-10 mm; 3 -fractions 5-7 mm; 4 -fractions 3-5 mm; 5 -fractions 2-3 mm; 6 -fractions 1-2 mm; 7fractions 0.5-1 mm; 8 -fraction of size 0.25-0.5 mm; 9 -fraction of size <0.25 mm; model II -monotonic response; IV -symmetrical bell-shaped response; V -asymmetrical bell-shaped response (response models from the HOF list of functions [97,98]). This result is true for both endogeic A. trapezoides and epigeic D. octaedra.…”

Spatial organization of the soil macrofauna community in a floodplain forest

“…The medium-scale component can be induced by unmeasured vegetation indices. The phytoindicative assessments of environmental factors reflect changes in vegetation structure, but do not fully characterize them [31,73]. The fraction of vegetation variability that also affects soil animals may be independent of environmental gradients or environmental scales may not always be sensitive to such gradients.…”

“…The fraction of vegetation variability that also affects soil animals may be independent of environmental gradients or environmental scales may not always be sensitive to such gradients. The medium-scale component of pure spatial variability may be due to the vegetation variability that cannot be fully characterized by phytoindicator scales [73]. The fine-scale component represents the variability of the soil macrofauna community, which is related to factors of a neutral nature.…”

Spatial variation of soil temperature fields in a urban park

“…Soil temperature is influenced by factors from two groups: these are factors that determine the amount of heat reaching the soil surface and factors that influence the amount of heat transferred along the soil profile [22,23]. The factors that influence the amount of heat that reaches the soil surface are the colour of the soil surface [24], mulching [25], the amount of solar radiation [1,26,27] the slope of the soil surface [28,29], the vegetation cover [30,31], the organic matter content of the soil [32] and the intensity of evaporation from the soil surface [33,34]. The amount of radiation received by the soil affects soil temperature, biological processes such as: seed germination, seedling emergence, plant root growth and nutrient availability.…”