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DocumentBiomass estimation in mangrove forests: a comparison of allometric models incorporating species and structural information
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.Improved estimates of aboveground biomass are required to improve our understanding of the productivity of mangrove forests to support the long-term conservation of these fragile ecosystems which are under threat from many natural and anthropogenic pressures. To understand how individual species affects biomass estimates in mangrove forests, five species-specific and four genus-specific allometric models were developed. Independent tree inventory data were collected from 140 sample plots to compare the aboveground biomass (AGB) among the species-specific models and seven existing frequently used pan-tropical and Sundarbans-specific generic models. The effect of individual tree species was also evaluated using model parameters for wood densities (from individual trees to the whole Sundarbans) and tree heights (individual, plot average and plot top height). All nine species-specific models explained a high percentage of the variance in tree AGB (R2 = 0.97 to 0.99) with the diameter at breast height (DBH) and total height (H). At the individual tree level, the generic allometric models overestimated AGB from 22% to 167% compared to the species-specific models. At the plot level, mean AGB varied from 111.36 Mg ha-1 to 299.48 Mg ha-1, where AGB significantly differed in all generic models compared to the species-specific models (p < 0.05). Using measured species wood density (WD) in the allometric model showed 4.5% to 9.7% less biomass than WD from a published database and other sources. When using plot top height and plot average height rather than measured individual tree height, the AGB was overestimated by 19.5 % and underestimated by 8.3% (p < 0.05). The study demonstrates that species-specific allometric models and individual tree measurements benefit biomass estimation in mangrove forests. Tree level measurement from the inventory plots, if available, should be included in allometric models to improve the accuracy of forest biomass estimates, particularly when upscaling individual trees up to the ecosystem level. Keywords: Climate change, Monitoring and data collection, Sustainable forest management ID: 3621710 -
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 -
ArticleInfluence of snow cover change and temperature anomalies on the transformation of boreal forests and fires in north Asia
XV World Forestry Congress, 2-6 May 2022
2022Also available in:
No results found.In the last three decades, the number and area of fires in the North Asian taiga, forest-tundra and tundra is increasing. Analysis of spatial data on fires against the information on local climate anomalies indicates significant correlation. The estimates are generally based on average seasonal temperatures and the duration of the vegetation period; however, while these parameters are useful for global bioclimatic regularities, they are not sufficient for local forest change influenced by small-scale climate effects. Comparison of satellite images at the beginning and the end of the snow period with patterns of fire activities shows that the frequency and scale of temperature and snow anomalies are also key factors. Field studies that aimed to verify the snow properties as identified through satellite imagery were carried out on more than 200 plots in the Urals and the Russian Far East. It was found out that tree crowns of dark-coniferous and mixed forests intercept up to a quarter of total snow reducing accumulation and decreasing snowmelt logging. This leads to the desiccation of the soil layer in spring and increases the risk of fires in forests, where this risk used to be low. Another important effect is the increased frequency of dry and hot autumns in taiga and forest-tundra, which dramatically aggravate the risk of litter ignition. Field observations and analysis of satellite images for 30 years give information on the spatial differentiation of the effects. The higher risk of fires associated with the redistribution of snow by tree crowns is typical of the south and central taiga. Soil desiccation in autumn is the important factor for fires in the north taiga and forest-tundra. These effects are additional to the seasonal temperature anomalies, which are the key risk factor. Taking account of these effects in context of the global warming provides better estimation of fires, including the risk of fires in unique forests on protected areas in North Asia. Keywords: Climate change, Adaptive and integrated management, Biodiversity conservation, Sustainable forest management, Research ID: 3485018
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