Shape of cumulative land use systems' area distribution as a parameter of anthropogenic impact on landscapes
Abstract
Statement of the problem and paper objective. Current challenges address global and regional threats to biotic and landscape diversity and the urgent need for its conservation, restoration and reproduction. They make it necessary to improve the tools for conceptual, information and calculating assessment of human activities impact on the environment. That is why the study of the landscapes anthropization, i.e. the process of their transformation through human activity, and the identification of the effects of this anthropization on the environment remains the most pressing problem of geography and geoecology. Given this, the paper objective was to substantiate, develop and verify new and sufficiently informative analytical tools for modeling anthropogenic impact of the land use and/or land cover (LULC) system on landscapes and/or physic-geographic taxons.
Methods and results. The experience shows that the resumptive graphic solutions for the analysis of anthropogenic impact on landscapes can be correctly represented in the form of certain modified graphs of statistics. So, the classified scheme of the LULC system areas' cumulative distribution in landscapes and/or physic-geographic taxons was substantiated and constructed as analytical tool for modeling anthropogenic impact on landscapes / taxons. The scheme is based on the concept that the types of the mentioned distribution in its shape are adequate a certain category and the intensity of anthropogenic impact on landscapes or taxons. Properly the distribution of LULC system areas was typified by the ranges for the parameter of polynomial trends in the cumulative graphs of these areas in landscapes or their aggregations. Under these conditions, the scheme of areas' cumulative distribution operates with ten types of distribution – from excessively convex to excessively concave. These types also reflect different anthropogenic impacts on taxons – from weak to excessively strong.
Verification of the scheme calculating LULC system areas' cumulative distribution was realized for the test megaregion, including 30 physic-geographic areas and 130 physic-geographic districts of the five regions in the zones of mixed (coniferous / broad-leaved) and broad-leaved forests and forest-steppe of Ukraine. Relevant digital choropleths concerning anthropogenic impact on these taxons were simulated and analyzed.
Scientific novelty and practical significance. Scientific novelty is determined by the reason that the developed scheme and obtained model results are more parametrically diverse than in the existing procedures. This is caused by the fact that the proposed tools are more informative and statistically effective for identification of anthropogenic impact on landscapes and physic-geographic taxons than the average-weighted and other calculating anthropization indexes or schemes for consideration the impact of only dominant LULC systems. The verification of the developed tools for the test megaregion affirmed the general validity of the proposed new methodical approaches. The paper results are applicable for the improvement of procedures, schemes and projects of environmental management for plain terrestrial landscapes and their aggregations in midlatitudes.
Downloads
References
Samoilenko V., Plaskalnyi V. (2017). Modern procedure of landscape anthropization analysis. Problems of Geogra-phy, 1-2: 31-42. Sofia: Bulgarian Academy of Science, National Institute of Geophysics, Geodesy and Geography. Available at: http://geoproblems.eu/wp-content/uploads/2017/10/2017_12/2_samoilenko.pdf
Samoilenko V.M, Dibrova I.O., Plaskalnyi V.V. (2018). Anthropization of Landscapes. Monograph [in Ukrainian]. Kyiv: Nika-Center, 232. Available at: http://geo.univ.kiev.ua/images/doc_file/navch_lit/Antropizazia%20landchaftiv_ Samoylenko.pdf
Walz U., Stein C. (2014). Indicators of hemeroby for the monitoring of landscapes in Germany. Journal for Nature Conservation, 22: 279-289. Available at: http://dx.doi.org/10.1016/j.jnc.2014.01.007
IOER Monitor (2018). Monitor of Settlement and Open Space Development. Leibniz Institute of Ecological Urban and Regional Development.Web source: http://www.ioer-monitor.de
Winter S. (2012). Forest naturalness assessment as a component of biodiversity monitoring and conservation man-agement. Forestry, 85, 2: 293-304. Available at: https://doi.org/10.1093/forestry/cps004
Paracchini M.L., Capitani C. (2011). Implementation of a EU wide indicator for the rural-agrarian landscape. JRC scientific and technical reports (EUR 25114 EN-2011). Luxembourg: Publications Office of the European Union, 89. Available at: http://dx.doi.org/10.2788/25137
Eurostat Statistics (2012). Eurostat Statistics Explain: Agri-environmental indicator – landscape state and diversi-ty. Web source: http://ec.europa.eu/eurostat/statistics-explained
Csorba P., Szabó S. (2009). Degree of human transformation of landscapes: a case study from Hungary // Hungari-an Geographical Bulletin, 58. 2: 91-99. Available at: http://www.mtafki.hu/konyvtar/kiadv/HunGeoBull2009/ HunGeoBull_2009_2_91-99.pdf
Kiedrzynski M. et al. (2014). Historical Land Use, Actual Vegetation and the Hemeroby levels in ecological evalua-tion of an urban river valley in perspective of its rehabilitation plan. Pol. J. Environ. Stud., 23, 1: 109-117. Avail-able at: http://www.pjoes.com/Historical-Land-Use-Actual-Vegetation-r-nand-the-Hemeroby-Levels-in-Ecological-Evaluation,89173,0,2.html
Frank S. (2014). Development and Validation of a Landscape Metrics Based Approach for Standardized Land-scape Assessment Considering Spatial Patterns. Statement of the PhD Candidate. Technische Universität Dresden, 97. Available at: https://tud.qucosa.de/api/qucosa%3A28247/attachment/ATT-1/
Wrbka T. et al. (2004). Linking pattern and process in cultural landscapes. An empirical study based on spatially explicit indicators. Land Use Policy, 21(3): 289-306. Available at: https://doi.org/10.1016/j.landusepol.2003.10.012
Rüdisser J. et al. (2012). Distance to nature – A new biodiversity relevant environmental indicator set at the land-scape level. Ecological Indicators, 15: 208-216. Available at: https://doi.org/10.1016/j.ecolind.2011.09.027
Mercuri A.M., Florenzano A. (2019). The Long-Term Perspective of Human Impact on Landscape for Environmen-tal Change (LoTEC) and Sustainability: From Botany to the Interdisciplinary Approach. Sustainability, 11(2): 413-419. Available at: https://doi.org/10.3390/su11020413
Ellis E.C. et al. (2013). Used planet: a global history. Proceedings of the National Academy of Sciences of the USA, 110, 20: 7978-7985. Available at: https://dx.doi.org/10.1073%2Fpnas.1217241110
Guidelines for land use mapping in Australia: principles, procedures and definitions (2011). Australian Bureau of Agricultural and Resource Economics and Sciences. Fourth edition. Canberra: Commonwealth of Australia, 132. Available at: https://catalogue.nla.gov.au/Record/5739000
Shyshchenko P.G., Gavrylenko O.P. (2014). Geoecological rationale of environmental management projects. Text-book (el. version) [in Ukrainian]. Kyiv: Alterpress, 414.
Shyshchenko P.G., Gavrylenko O.P. (2015). Constructive-geographic bases of rational environmental management. Textbook (el. version) [in Ukrainian]. Kyiv: SE "Print Service", 395.
Grodzynskyi M.D. (2014). Landscape ecology. Textbook [in Ukrainian]. Kyiv: Znannia, 550.
Samoilenko V.M., Ivanok D.V. (2015). Modeling of basin geosystems. Monograph [in Ukrainian]. Kyiv: SE "Print Service", 208. Available at: http://geo.univ.kiev.ua/images/doc_file/navch_lit/Samojlenko_mod_bas.pdf
Kovalchuk, I., Mykytchyn, O., & Kovalchuk, A. (2019). Geoinformation modeling of anthropogenic transformation of the basin geosystems (case study of Dnister right tributaries). Visnyk of V. N. Karazin Kharkiv National Universi-ty, Series "Geology. Geography. Ecology", 51: 124-139. Available at: https://doi.org/10.26565/2410-7360-2019-51-09
Samoilenko V., Dibrova I. et al. (2018). Procedure of Landscape Anthropization Extent Modeling: Implementation for Ukrainian Physic-Geographic Taxons. Environmental Research, Engineering and Management, 74, 2: 67-81. Available at: http://dx.doi.org/10.5755/j01.erem.74.2.20646
Samoilenko V., Dibrova I. (2019). Geoecological Situation in Land Use. Environmental Research, Engineering and Management, 75, 2: 36-46. Available at: http://dx.doi.org/10.5755/j01.erem.75.2.22253
Samoilenko V.M, Dibrova I.O. (2019). Natural-geographic Modeling. Textbook [in Ukrainian]. Kyiv: Nika-Center, 320. Available at: http://geo.univ.kiev.ua/images/doc_file/navch_lit/Sam_Dibrova_PG_model_2019.pdf
Bossard M. et al. (2000). CORINE land cover technical guide – Addendum 2000. Technical report No 40. Copen-hagen: EEA, 105. Available at: https://www.eea.europa.eu/publications/tech40add
Samoilenko V. (2002). Probabilistic mathematical methods in geoecology. Manual [in Ukrainian]. Kyiv: Nika-Center, 404.
Topuzov O., Vishnikina L., Samoilenko V. et al. (2019). Modernization of Geographic Education at High School: Geoinformation Training Models. Information Technologies and Learning Tools, 73, 5: 174-184. Available at: https://doi.org/10.33407/itlt.v73i5.3190
National Atlas (2007). National Atlas of Ukraine (electronic version) [in Ukrainian]. Institute of Geography NASU, SRPE "Cartography" et al.
European Space Agency (ESA) (2015). Climate Change Initiative Land Cover (CCI-LC) Map. Web source: http://maps.elie.ucl.ac.be/CCI/viewer
Globeland30 Land Cover Map (2011). National Geomatics Center of China (NGCC). Web source: http://www.globallandcover.com/GLC30Download