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ArticleVulnerability assessment of Ukrainian forests to climate change as the base of nature-based solutions for mitigation and adaptation
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.A wide range of climatic conditions in Ukraine causes significant regional differences in the vulnerability of forests to climate change. The mitigation/adaptation strategy should be based on assessments of their vulnerability at the regional level. Phytoindication model by prof. Y.P. Didukh (1994) was used to assess forest vulnerability. The model gives a quantitative estimation of climate as one of major environmental factors affecting the distribution, condition and productivity of vegetation on the base of climate-related indicators – continentality, humidity and frost. For these indicators climate suitability scales were calculated. Modeling was carried out for main forest species: Pinus sylvestris L., Quercus robur L., Fagus sylvatica L., Picea abies (L.) H.Karst, Betula pendula Roth., Alnus glutinosa (L.) Gaertn. and Robinia pseudoacacia L. Climate projections based on the Euro CORDEX time series (up to 2100) and 2 scenarios of the Representative Concentration Pathways (RCP 4.5, RCP 8.5) were used. By means of Q-GIS the maps containing zones of suitability to climate for each of studied species were created for current climate conditions and future time series. The directions for strengthening the mitigation and adaptive capacity of forests are considered. The mainstream for nature-based solutions is adaptive sustainable forest management, which provides: 1)optimization of land use structure and increasing the forested area; 2) development and implementation of a national forestry program considering the priorities of climate change and low-carbon development; 3) using wood to substitute greenhouse gas intensive-materials and fossil fuels; 4) best forestry practices through the introduction of modern Climate Smart Forestry principles. Keywords: RCP 4.5, RCP 8.5, Euro CORDEX, climate trends, adaptive forest management ID: 3487120 -
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