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Predicting GPP in Carpathian Beech Forests: Uncovering spatial and temporal patterns using a regression model with climatic, topographic and additional features
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SYSNO ASEP 0601463 Document Type C - Proceedings Paper (int. conf.) R&D Document Type Conference Paper Title Predicting GPP in Carpathian Beech Forests: Uncovering spatial and temporal patterns using a regression model with climatic, topographic and additional features Author(s) Missarov, A. (CZ)
Kašpar, J. (CZ)
Král, K. (CZ)
Brovkina, Olga (UEK-B) RID, SAI, ORCID
Švik, Marian (UEK-B) SAI, RID, ORCIDSource Title Predicting future trends – responses of beech and fir in the Carpathian region. - Lublaň : Slovenian Forestry Institute, The Silva Slovenica Publishing Centre, 2024 / Čater Matjaž ; Dařenová Eva - ISBN 978-961-6993-87-6 Pages s. 67-71 Number of pages 76 s. Publication form Print - P Action Predicting future trends – responses of beech and fir in the Carpathian region Event date 05.09.2024 - 05.09.2024 VEvent location Ljublaň Country SI - Slovenia Event type EUR Language eng - English Country SI - Slovenia Keywords gross primary product ; remote sensing ; regression model ; temperature ; precipitation ; digital elevation model Subject RIV GK - Forestry OECD category Forestry R&D Projects GF21-47163L GA ČR - Czech Science Foundation (CSF) Institutional support UEK-B - RVO:86652079 DOI https://doi.org/10.20315/SilvaSlovenica.0026.12 Annotation Climate change impact ecosystems globally, including the mixed forests of the Carpathian Mountains (Kruhlov et al. 2017). The primary manifestations of climate change are shifts in temperature and precipitation regimes, which undoubtedly affect biomass growth in complex ways. Since direct observations of the future are impossible, we rely on various modeling methods. Machine learning is the most popular contemporary approach for addressing such tasks. The aim of our study is to develop a regression model that predicts the behavior of Gross Primary Product (GPP) based on a range of climatic, topographic, and other variables. We use this model to forecast the growth of beech forests over the next 20 years under different climate scenarios. Workplace Global Change Research Institute Contact Nikola Šviková, svikova.n@czechglobe.cz, Tel.: 511 192 268 Year of Publishing 2025
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