Temperature effect on the temporal dynamic of terrestrial invertebrates in technosols formed after reclamation at a post-mining site in Ukrainian steppe drylands
Abstract
The research was carried out at the Research Centre of the Dnipro State Agrarian and Economic University in Pokrov city. Sampling was carried out in 2013–2015 on a variant of artificial soil (technosols) formed on loess-like loam, red-brown clay, green-grey clay, technological mixture of rocks, and also formed on loess-like loam with a humus-rich 70 cm top soil layer. To investigate the spatiotemporal variation in the abundance, species richness and species composition of invertebrate assemblages within the experimental polygon, the animals were sampled using pitfall traps. In total, 60 pitfall traps were operated simultaneously during each sampling period. Each year the pitfalls were emptied 26 times every 7–9 days. Invertebrates (Arthropoda and Mollusca) of 6 classes, 13 orders, 50 families and 202 species or parataxonomic units were recorded. Diplopoda was most abundant taxonomic group, though it was represented by only one species Rossiulus kessleri (Lohmander, 1927). Coleoptera and Araneae were the most numerous taxonomic groups. Readily available water for plants, precipitation, wind speed, atmospheric temperature (daily minimum, daily maximum, daily mean), atmospheric humidity and atmospheric pressure were used as environmental predictors. Two dimension geographic coordinates of the sampling locations were used to generate a set of orthogonal eigenvector-based spatial variables. Time series of sampling dates were used to generate a set of orthogonal eigenvector-based temporal variables. The moisture content in the technosols was revealed to be the most important factor determining the temporal dynamics of the terrestrial invertebrate community in conditions of semi-arid climate and the ecosystem which formed as a result of the reclamation process. Following soil moisture, the factor most strongly affecting invertebrates in the technosols was temperature. From the total set of the invertebrates, two relatively homogeneous species groups in terms of thermal preferences were extracted: the microtemperature and mesotemperature groups. The microtemperature species are more tolerant to the thermal factor, and the mesotemperature species are more sensitive. The Huisman-Olff-Fresco approach expanded by Jansen-Oksanen provides a wide set of ecologically relevant models which are able to explain species response. The species response to temperature is affected by a complex of other environmental, temporal and spatial factors. The effect of other factors on the species response must be previously extracted to find real estimations of the species temperature optima and tolerance. The approaches to solving this problem may be the object of future investigation.References
Austin, M. P. (1976). On non-linear species response models in ordination. Vegetatio, 33(1), 33–41.
Borcard, D., & Legendre, P. (2002). All-scale spatial analysis of ecological data by means of principal coordinates of neighbour matrices. Ecological Modelling, 153, 51–68.
Borcard, D., Legendre, P., Avois–Jacquet, C., & Tuosimoto, H. (2004). Dissecting the spatial structure of ecological data at multiple scales. Ecology, 85, 1826–1832.
Brandle, M., Ohlschlager, S., & Brandl, R. (2002). Range size in butterflies: Correlation across scales. Evolutionary Ecology Research, 4, 993–1004.
Brown, J. H. (1999). Macroecology: Progress and prospect. Oikos, 87, 3–14.
Buchholz, S. (2009). Community structure of spiders in coastal habitats of a Mediterranean delta region (Nestos Delta, NE Greece). Animal Biodiversity and Conservation, 32(2), 101–115.
Burnham, K. P., & Anderson, D. R. (2002). Model selection and multi-model inference: A practical information-theoretic approach. Springer, Berlin.
Buzuk, G. N. (2017). Phytoindication with ecological scales and regression analysis: Environmental index. Bulletin of Pharmacy, 76, 31–37.
Desender, K., Ervinck, A., & Tack, G. (1999). Beetle diversity and historical ecology of woodlands in Flanders. Belgian Journal of Zoology, 129(1), 139–155.
Didukh, Y. P. (2011). The ecological scales for the species of Ukrainian flora and their use in synphytoindication. Phytosociocentre, Kyiv.
Dray, S., Legendre, P., & Peres-Neto, P. (2006). Spatial modelling: A comprehensive framework for principal coordinate analysis of neighbours matrices (PCNM). Ecological Modelling, 196, 483–493.
Elton, C. (1927). Animal Ecology. Sidgwick and Jackson, London.
Foster, R. G., & Kreitzman, L. (2009). Seasons of life: The biological rhythms that enable living things to thrive and survive. Yale University Press, New Haven.
Gallé, R., Vesztergom, N., & Somogyi, T. (2011). Environmental conditions affecting spiders in grasslands at the lower reach of the River Tisza in Hungary. Entomologica Fennica, 22, 29–38.
Ge, B., Daizhen, Z., Jun, C., Huabin, Z., Chunlin, Z., & Boping, T. (2014). Biodiversity variations of soil macrofauna communitiesin forestsina reclaimed coastwith different diked history. Pakistan Journal of Zoology, 46(4), 1053–1059.
Grinnell, J. (1917). The niche relationship of the California Thrasher. The Auk, 34(4), 427–433.
Hendrychova, M. (2008). Reclamation success in post-mining landscapes in the Czech Republic: A review of pedological and biological studies. Journal of Landscape Studies, 1, 63–78.
Konstantinov, A. S., Korotyaev, B. A., & Volkovitsh, M. G. (2009). Insect biodiversity in the Palearctic region. In: Foottit, R., & Adler, P. (Eds.). Insect biodiversity: Science and society. Blackwell Publisher, Chinchester. Pp. 107–162.
Kunakh, O. N., Kramarenko, S. S., Zhukov, A. V., Zadorozhnaya, G. A., & Kramarenko, A. S. (2018). Intra-population spatial structure of the land snail Vallonia pulchella (Müller, 1774) (Gastropoda; Pulmonata; Valloniidae). Ruthenica, 28(3), 91–99.
Lavelle, P., Bignell, D., Lepage, M., Wolters, V., Roger, P., Ineson, P., Heal, O. W., & Dhillion, S. (1997). Soil function in a changing world: The role of invertebrate ecosystem engineers. European Journal of Soil Science, 33, 159–193.
Lawton, J. H. (1999). Are there general laws in ecology? Oikos, 84, 177–192.
Levin, S. A. (1992). The problem of pattern and scale in ecology. Ecology, 73, 1943–1967.
Oksanen, J. (2004). Multivariate analysis in ecology. Lecture Notes. Department of Biology, Universityof Oulu.
Oksanen, J., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’Hara, R. B., Simpson, G. L., Solymos, P., Stevens, M. H. H., & Wagner, H. (2018). Community Ecology Package. R package version 2.5-2.
Rao, C. R. (1995). A review of canonical coordinates and an alternative to correspondence analysis using Hellinger distance. Qüestiió, 19, 23–63.
Rehor, M., Lang, T., & Eis, M. (2006). Application of new methods in solving current reclamation issues of Severoceske doly, a.s. localities. World of Surface Mining, 6, 383–386.
Sklenicka, P., Prikryl, I., Svoboda, I., & Lhota, T. (2004). Non-productive principles of landscape rehabilitation after long-term opencast mining in north-west Bohemia. Journal of the South African Institute of Mining and Metallurgy, 104, 83–88.
Tokeshi, M. (1999). Species coexistence: Ecological and evolutionary perspectives. Blackwell Science, London.
Warburg, M. R., Linsenmair, K. E., & Bercovitz, K. (1984). The effect of climate on the distribution and abundance of isopods. Symposia of the Zoological Society of London, 53, 339–367.
Westhoff, V., & van der Maarel, E. (1978). The Braun-Blanquet approach. In: Whittaker, R. H. (Ed.). Classification of plant communities. Pp. 289–399.
Wise, D. H. (1993). Spiders in ecological webs. Cambridge University Press, Cambridge.
Yorkina, N., Maslikova, K., Kunah, O., & Zhukov, O. (2018). Analysis of the spatial organization of Vallonia pulchella (Muller, 1774) ecological niche in technosols (Nikopol Manganese Ore Basin, Ukraine). Ecologica Montenegrina, 17, 29–45.