Response of Soil Bacteria of Dicranopteris dichotoma Populations to Vegetation Restoration in Red Soil Region of China

Li, Qi-yan; Zhu, Chen-lu; Yu, Junbao; Wu, Xinyi; Huang, Si-qi; Yang, Fan; Tigabu, Mulualem; Hou, Xiaolong

doi:10.1007/s42729-022-01058-6

Cited by 5 publications

(2 citation statements)

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“…It is a pioneer herbaceous species that can grow in poor site conditions, with a strong survival ability in infertile soils, forming a dominant plant community for the restoration of degraded ecosystems due to severe soil erosion in subtropical regions [4]. The Dicranopteris roots can stabilize the soil structure and provide necessary habitat and nutrient sources for belowground microbes [5]. Thus, Dicranopteris plays an important role in carbon fixation, soil moisture regulation, nutrient cycling [5,6], and in maintaining biodiversity and ecosystem sustainability [7,8].…”

Section: Introductionmentioning

confidence: 99%

“…The Dicranopteris roots can stabilize the soil structure and provide necessary habitat and nutrient sources for belowground microbes [5]. Thus, Dicranopteris plays an important role in carbon fixation, soil moisture regulation, nutrient cycling [5,6], and in maintaining biodiversity and ecosystem sustainability [7,8]. Therefore, mapping the spatial distribution of Dicranopteris biomass is valuable for assessing the effectiveness of implementing conservation measures on the restoration of degraded ecosystems.…”

Section: Introductionmentioning

confidence: 99%

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Integration of Handheld and Airborne Lidar Data for Dicranopteris Dichotoma Biomass Estimation in a Subtropical Region of Fujian Province, China

Li,

Wu,

et al. 2024

Remote Sensing

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Dicranopteris dichotoma is a pioneer herbaceous plant species that is tolerant to barrenness and drought. Mapping its biomass spatial distribution is valuable for understanding its important role in reducing soil erosion and restoring ecosystems. This research selected Luodihe watershed in Changting County, Fujian Province, China, where soil erosion has been a severe problem for a long time, as a case study to explore the method to estimate biomass, including total and aboveground biomass, through the integration of field measurements, handheld laser scanning (HLS), and airborne laser scanning (ALS) data. A stepwise regression model and an allometric equation form model were used to develop biomass estimation models based on Lidar-derived variables at typical areas and at a regional scale. The results indicate that at typical areas, both total and aboveground biomass were best estimated using an allometric equation form model when HLS-derived height and density variables were extracted from a window size of 6 m × 6 m, with the coefficients of determination (R2) of 0.64 and 0.58 and relative root mean square error (rRMSE) of 28.2% and 35.8%, respectively. When connecting HLS-estimated biomass with ALS-derived variables at a regional scale, total and aboveground biomass were effectively predicted with rRMSE values of 17.68% and 17.91%, respectively. The HLS data played an important role in linking field measurements and ALS data. This research provides a valuable method to map Dicranopteris biomass distribution using ALS data when other remotely sensed data cannot effectively estimate the understory vegetation biomass. The estimated biomass spatial pattern will be helpful to understand the role of Dicranopteris in reducing soil erosion and improving the degraded ecosystem.

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