Estimating Biomass Carbon Stocks of Inner Mongolia Grasslands Using Multi-Source Data
Accurate estimates of biomass C stocks of grasslands are crucial for grassland management and climate change mitigation efforts. Here, we estimated the mean C stocks of grasslands in the Inner Mongolia Autonomous Region (IMAR), China, in 2020 at a 10 m spatial resolution by combining multi-source da...
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| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2024-12-01
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| Series: | Remote Sensing |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2072-4292/17/1/29 |
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| Summary: | Accurate estimates of biomass C stocks of grasslands are crucial for grassland management and climate change mitigation efforts. Here, we estimated the mean C stocks of grasslands in the Inner Mongolia Autonomous Region (IMAR), China, in 2020 at a 10 m spatial resolution by combining multi-source data, including remote sensing, climate, topography, soil properties, and field surveys. We used the random forest model to estimate the aboveground biomass (AGB) of grasslands, achieving an R<sup>2</sup> value of 0.83. We established a relationship between belowground biomass (BGB) and AGB using a power function based on field data, which allows us to estimate the BGB of grasslands from our AGB estimate. We estimated the mean AGB across IMAR to be 100.7 g m<sup>−2</sup>, with a total value of 1.4 × 10<sup>8</sup> t. The BGB of grasslands is much higher than AGB, with mean and total values of 526.0 g m<sup>−2</sup> and 7.4 × 10<sup>8</sup> t, respectively. Consequently, our C stock estimates show that IMAR grasslands store significantly more C in their BGB (332.6 Tg C) compared to AGB (63.7 Tg C). Random forest model analyses suggested that remotely sensed vegetation indices and soil moisture are the most important predictors for estimating the AGB of grasslands in the IMAR. We highlight the important role of BGB for the C store in the Inner Mongolia grasslands. |
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| ISSN: | 2072-4292 |