RUSSIAN JOURNAL OF FOREST SCIENCE, 2018, NO. 3, P. 178-193

СOMPARING ECO-PHYTOCOENOTIC AND ECO-FLORISTIC METHODS OF CLASSIFICATION TO ESTIMATE COENOTIC DIVERSITY AND TO MAP FOREST VEGETATION
N. G. Belyaeva¹, T. V. Chernen’kova¹, O. V. Morozova^1,2, R. B. Sandlerskii³, M. V. Arkhipova^4
1Center for Forest Ecology and Productivity of the Russian Academy of Sciences
Profsoyuznaya st. 84/32 bldg. 14, Moscow, 117997, Russia
Е-mail: n.vin@mail.ru
²Institute of Geography, Russian Academy of Sciences
Staromonetny ln. 29, Moscow, 119017, Russia
³Severtsov institute of ecology and evolution, Russian Academy of Sciences
Leninsky ave. 33, Moscow, 119071, Russia
⁴Sergeev Institute of Environmental Geoscience, Russian Academy of Science
Ulansky ln. 13 bldg. 2, Moscow, 101000, Russia

Received 28 June 2017
Coenotic diversity of forests was assessed using data of field studies, remote sensing (Landsat-5 TM, Landsat-8 OLI and TIRS) and digital elevation models. The study area of 51.5·10³ ha was located in southwestern Moscow Oblast. Forest communities were classified using two different methods: eco-phytocoenotic and eco-floristic. We recognized 15 eco-phytocoenotic syntaxons at groups of associations level, and 9 eco-floristic syntaxons. Accuracy of grouping of field documentation was supported statistically for every approach to classification. Quality of classification was evaluated for representation and abundance of species by step-wise discriminant analysis. It was higher for eco-floristic syntaxons (87.1%) than for eco-phytocoenotic ones (78.9%). Adjustment of composition and names of syntaxons of eco-phytocoenotic classification ensured compliance of typological and mapping units. Quality of prediction of syntaxons recognized from pixel brightness and topographic variables was 78.6%. Quality of discriminant analysis of recognized syntaxons of eco-phytocoenotic model showed lower accuracy of mapping (69.7%). We developed largescale maps of forest vegetation based on both classifications. We showed that representations of eco-phytocoenotic units have higher accuracy. These units correspond to recent state of plant communities at their actual succession stage. On the other hand, eco-floristic units provide insight of a potential vegetation composition of habitat. Large amount of syntaxons of eco-floristic classification (associations and sub-associations) allowed tracing general patterns of vegetation on large-scale maps. This feature could be more informative in medium- to small scale mapping.
Keywords: mixed forests, remote sensing, eco-phytocoenotic and eco-floristic classifications, discriminant analysis, mapping.
Acknowledgements: This study was conducted in the framework of the State Appointment to the Center of forest ecology and productivity of the Russian Academy of sciences ''The concept of remote sensing of health and dynamics of forest ecosystems'' (project 0110-2014-0001). It was partially supported by the Russian Foundation for Basic Research: study of coenotic diversity of forests of East-European Plain (grant 16-05-0014216), study of ecology of forest communities (grant 16-35-00562 mol_a), - and by Russian Scientific Foundation (grant 17-77-10135) for processing of remote sensing data.
DOI: 10.7868/S0024114818030026
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