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ArticleCoupling machine learning and forest simulations to promote the applicability of long-term forest projections under climate change perspectives
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Projecting forest dynamics is the foundation for sound decision support in adaptive forest management. However, due to their complexity, many forest modeling techniques addressing global changes in terrestrial ecosystems are limited to scientific applications. Integrating conventional research and artificial intelligence technologies has the potential to bridge research and practical use. In this study, we propose a Machine Learning (ML) framework that facilitates the implementation of long-term forest projections under climate change scenarios. Our approach combines ML and forest simulations based on process-based models to project forest dynamics. The goal is to leverage the complementary strength of process-based and state-of-the-art ML models to improve predictions at a reduced computational cost. We use environmental data and periodic field measurements at a national scale to train ML models to predict forest growth. By integrating process-based simulations we investigate how the additional variables can improve the prediction accuracy. The proposed hybrid ML framework identifies forest dynamics processes and drivers across spatial and temporal scales, contributing at many levels to the climate change adaptation: from increasing awareness of the climate-induced hazards to enhancing education and assisting in sustainable natural resource management and planning. Keywords: adaptive forest management, climate change, forest growth modelling, machine learning ID: 3623078 -
ArticleForest succession by space and time based on climate and landuse changes
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.This research predicted the transition of forest structure by analyzing changes in the dominant vegetation and spatial distribution based on climate and land use changes. The research region involves the mountainous and city vicinity located in Okcheon-gun, Korea. Climate change detailing was carried out until 2100 by employing the SSP2-4.5 scenario and the MaxEnt model was used to predict the land cover change. The data stemming from the above were applied to the Landis-II model. The analysis of forest changes was performed based on the years 2050 and 2100 that showed the most dramatic prediction results of climate changes. Comparing to 2020, the mean minimum temperature fell down by 0.45°C in 2050 and increased by about 0.96°C in 2100. The mean maximum temperature increased by about 0.31°C in 2050 and about 1.96°C in 2100. In the prediction of land cover change, mountainous region exhibited a decreased tendency of agricultural lands in 2050 and 2100, and region city vicinity showed a decrease in residential lands, demonstrating very small land cover changes of the forest in both regions. As for the predicted vegetation change, both regions showed a decrease in the dominant area of Pinus densiflora, Pinus Koraiensis, and Pinus rigida, on the other hand, showing an increase in the dominant area of Quercus serrate, Quercus variabilis, and Quercus aliena. In conclusion, the future forest vegetation of two regions showed a decreased tendency in the alien species that could not reproduce under natural conditions, tree species that grow in cold climate regions, and the reforestaion species that were planted due to a necessity of human beings, whereas the area of Quercus species, which are mainly distributed to a relatively warm climate, increased. Therefore, in order to determine tree species for restoration where interfered nature and area that need logging, it should be decided based on the predicted vegetation change in a given area to maximize the forest function. Keywords: Forest transition; Climate change; Landuse change; LANDIS-II; Sustainable forest management ID: 3621835 -
ArticleForest bioeconomy as an engine for sustainable development, water resources management and mitigation of the effects of climate change
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Brazil presents a great opportunity for the development of the bioeconomy, based on the management of natural forests, especially public forests, as well as the integration of the forestry component into agricultural systems, especially in private areas. Related to the management of natural forests, the importance of expanding the use of biodiversity products, especially non-timber, in a sustainable manner and with technological innovation, is highlighted. Currently, just 10 products accounts for more than 90% of non-timber forest production from native forests. A potential that is still underutilized, especially if we consider the Amazon biome. With regards to the integration of the forestry component into agricultural systems, the various forms of production developed around the world stand out, which are important alternatives for water conservation, sustainable development and mitigation of the effects of climate change. In Brazil, the Forest Law differentiates areas occupied by family farmers or traditional peoples and communities, encouraging the practice of agroforestry systems in Legal Reserve areas, as longer as they do not deviate from the existing vegetation cover and do not harm the environment. Therefore, agroforestry systems are presented as an alternative for their potential for income generation, water conservation, among other environmental services. In this sense, several practices are discussed around the world, such as: “domestic forest”, “forest gardens”, “climate smart agriculture” and “integrated landscape management. In general, it is observed that Brazil presents a great opportunity for the development of the bioeconomy, from the management of natural forests and the integration of the forest component to agricultural systems. Finally, these development opportunities for the Forest Bioeconomy stand out as paths for Sustainable Development, Water Resources Management and the Mitigation of the Effects of Climate Change. Keywords: Adaptive and integrated management, Sustainable forest management, Economic Development, Climate change, Agriculture. ID: 3623981
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