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Recent improvements of remote sensing based forest aboveground biomass estimation in China







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    Developing simultaneously modeling systems for improving the reliability of tree aboveground biomass- carbon and its components estimates for Machilus odoratissimus nees in the central highlands, Viet Nam
    XV World Forestry Congress, 2-6 May 2022
    2022
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    Machilus odoratissimus Nees is a multi-purpose species with, high economic value and environmental protection, so this tree species is commonly used in agroforestry models. In plantation management, it demands modeling systems that predict accurately aboveground biomass- carbon and its components. At the same time, the developed models support computing carbon accumulation of forest trees in agroforestry models for the program of reducing emissions from deforestation and forest degradation (REDD). Twenty-two 300 m2 plots were measured within the full range of 1 to 7 ages in the Central Highlands of VietNam. A total of 22 quadratic mean diameter trees were destructively sampled to obtain a dataset of the dry iomass/carbon of the stem (Bst/Cst), bark (Bba/Cba), branches (Bbr/Cbr), leaves (Ble/Cle), and total tree aboveground biomass/carbon (AGB/AGC). We examined the performance of weighted nonlinear models fit by maximum likelihood and weighted nonlinear seemingly unrelated regression (SUR) fit by generalized least squares for predicting tree aboveground biomass- carbon and its components. The simultaneous estimation of AGB/AGC and its components produced a higher reliability than that of the models of tree components and the total developed separately. The selected forms of modeling systems were AGB = Bst + Bba + Bbr + Ble = a1×(D2H)b1 + a2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 and AGC = Cst + Cba+ Cbr + Cle = a1×(D2H)b1 ++2×(D2H)b2 + a3×Db3 + a4×(D2H)b4 (where D is the diameter at breast height and H is the height of the tree). Keywords: Agroforestry, Machilus odoratissimus, seemingly unrelated regression (SUR), tree biomass- carbon ID: 3472953
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    Managing taxonomic and functional diversity is the key to sustain aboveground biomass and soil microbial diversity: A synthesis from long-term forest restoration of southern China
    XV World Forestry Congress, 2-6 May 2022
    2022
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    Exploring the biodiversity-ecosystem functioning relationship is one of the central goals of ecological research. Restoration is essential for supporting key ecosystem functions such as aboveground biomass production and managing soil microbial diversity. However, the relative importance of functional versus taxonomic diversity in explaining aboveground biomass and soil microbial diversity during restoration is poorly understood. Here, we used a trait-based approach to test for the importance of multiple plant diversity attributes in regulating aboveground biomass and soil microbial diversity in four 30- years-old restored subtropical forests in southern China. High-throughput Illumina sequencing was applied for detecting fungal and bacterial diversity. We show that both taxonomic and functional diversities are significant and positive regulators of aboveground biomass; however, functional diversity (FD) was more important than taxonomic diversity (TD) in controlling aboveground biomass. FD had the strongest direct effect on aboveground biomass compared with TD, soil properties, and community weighted mean (CWM) traits. Our results further indicate that leaf and root morphological traits and traits related to the nutrient content in plant tissues showed acquisitive resource use strategy which influenced aboveground biomass. In contrast to aboveground biomass, taxonomic diversity explained more of the soil microbial diversity than the FD and soil properties. Prediction of fungal richness was better than that of bacterial richness. In addition, root traits explained more variation of soil microbes than the leaf traits. Our results suggest that both TD and FD play a role in shaping aboveground biomass and soil microbial diversity; but FD is more important in supporting aboveground biomass while TD for belowground microbial diversity. These results imply that enhancing TD and FD is important to restoring and managing degraded forest landscapes. Key words: Biodiversity-Ecosystem functions; soil microbial diversity, taxonomic diversity, functional diversity, forest restoration ID: 3486373
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    Agricultural Information System- Building Provincial Capacity for Crop Estimation, Forecasting and Reporting based on the Integral Use of Remotely Sensed Data
    GCP/PAK/125/USA
    2014
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    The overall objective of the project is to help the Government of Pakistan in improving current systems for the integral use of remotely sensed data into existing data collection, analysis, and dissemination systems and the development of complementary systems to enable integration of satellite remotely-sensed data and improved field estimates for area and yield forecasting; and estimation and crop condition monitoring.

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