Dynamics of biomass and productivity of three major plantation types in southern China

Hu, 杜虎 Du; Fuping, 曾馥平 Zeng; Kelin, 王克林 Wang; Tongqing, 宋同清 Song; Yuanguang, 温远光 Wen; Chungan, 李春干 Li; Wanxia, 彭晚霞 Peng; Hongwen, 梁宏温 Liang; Hongguang, 朱宏光 Zhu; Zhaoxia, 曾昭霞 Zeng

doi:10.5846/stxb201212121788

Cited by 3 publications

(2 citation statements)

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“…a) The biomass of the herbaceous layer was estimated using dry weight data from herbaceous plants and multiple validated relationships between biomass and relative growth (Du et al, 2014) [20] . These relationships were established through regression analysis using the formula 𝑊𝑊 𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒𝑒 = 0.0755(𝐷𝐷 2 𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑)0.8941…”

Section: Supply Servicesmentioning

confidence: 99%

Quantification of Agroforestry Ecosystem Services in Karst Desertification Control

2024

AJEE

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This study assesses the ecosystem services of agroforestry in karst regions affected by desertification, highlighting its potential for ecological restoration and sustainable management. Agroforestry systems significantly enhance soil stability, water management, and carbon sequestration, thereby contributing to ecological health and helping mitigate the adverse effects of desertification. The research was conducted across various karst areas in southern China, delineated into zones based on degradation severity. The methodology involved quantifying key ecosystem service indicators such as biomass, net primary productivity, carbon storage, and soil quality through innovative models adapted to local environmental conditions. Results indicate that agroforestry systems not only improve provisioning and regulating services inversely related to degradation levels but also offer substantial cultural benefits by enhancing ecological perception and aesthetics through diverse vegetation and topography. Specifically, areas with intense agroforestry interventions showed higher biomass and carbon storage compared to less managed zones. Furthermore, the cultural services provided by these ecosystems, like enhanced ecological perception through improved landscape aesthetics and increased accessibility, underscore their integral role in local ecological and human communities. By integrating ecological and economic strategies, agroforestry in karst regions fosters a sustainable interaction between human activities and natural habitats, supporting both conservation efforts and local livelihoods. The findings advocate for expanded agroforestry practices as a key component of land management policies aimed at ecological restoration and sustainable development in degraded landscapes.

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Section: Supply Servicesmentioning

confidence: 99%

Quantification of Agroforestry Ecosystem Services in Karst Desertification Control

2024

AJEE

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“…Three distinct 2 m Â 2 m zigzag samples of the understory vegetation were constructed in each plot. The biomass density of the understory vegetation in the sample plots was calculated through multiplying the average dry weight of the tiny samples by the expansion factor after drying according to the harvesting technique (Du et al, 2014). Both of trees and understory vegetation contribute to AGB density at the sample size.…”

Section: Field Survey Datamentioning

confidence: 99%

Estimation of forest above‐ground biomass in Guangxi, China, by integrating forest age and stack learning

Liu

Yue

et al. 2023

Land Degrad Dev

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With the implementation of large‐scale ecological restoration projects, Southwest China has become one of the fastest forest growth areas in the world in terms of vegetation cover and above‐ground biomass (AGB). It is expected to be a potential area for achieving the carbon neutrality target in China. Accurate estimation of forest AGB is becoming an increasingly urgent necessity for carbon neutrality and forest management. However, due to the complex geological background, there is significant uncertainty in estimating forest AGB in the southwestern region, which generally results in underestimating carbon sinks from forest restoration. To address the issue, we propose a method by incorporating forest age information and stack learning technique to estimate forest AGB. Based on remote sensing, forest inventory and in situ forest biomass data, three fundamental methods (Multiple regression, Random forest and Support vector machine) are employed and compared to build the AGB estimation model with vegetation indices, texture feature factors and forest age. Optimal basic models are further enhanced by integration learning to improve the estimation performance and then applied to the study area Guangxi to obtain regional AGB information of different forest types. The results show that: (1) forest age plays a vital role in reducing the uncertainty of AGB estimation. By incorporating forest age information, R2 of AGB estimation is improved by 0.07–0.27 and RMSE is decreased by 16.35%–47.47% for different forest types; (2) with R2 value >0.78, random forest model outperforms support vector machine and multiple linear regression models. Compared with the single optimal model, integration model by stack learning further enhances R2 of estimation by 0.02–0.03 and decreases RMSE by 5.20%–14.89%. (3) The total forest AGB in Guangxi is 988.17 Tg and the average forest AGB level is 73.30 t/ha. Natural broadleaf forest has the highest AGB level (86.75 t/ha), followed by natural coniferous forest (81.19 t/ha), planted coniferous forest (63.23 t/ha) and planted eucalyptus forest (49.71 t/ha). AGB level in karst areas is lower than that in non‐karst areas due to soil and water constraints. The majority of plantation forests in Guangxi is in the early and middle stages of forest succession, with the rapid growth of forest AGB, and has hence significant potential as carbon sinks. This study indicates that stack learning and incorporation of forest age could significantly decrease the uncertainty of forest AGB estimation. Our study helps to provide more accurate AGB information for karst ecological project management and regional carbon neutrality assessment.

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The interception effect of heavy metals in different types of Chinese fir plantations

Yang

Chen

Wang

et al. 2020

Environ Geochem Health

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Dynamics of biomass and productivity of three major plantation types in southern China

Cited by 3 publications

References 0 publications

Quantification of Agroforestry Ecosystem Services in Karst Desertification Control

Quantification of Agroforestry Ecosystem Services in Karst Desertification Control

Estimation of forest above‐ground biomass in Guangxi, China, by integrating forest age and stack learning

The interception effect of heavy metals in different types of Chinese fir plantations

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