Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years
In the past 10 years, extreme weather phenomena have increased, and global warming has markedly advanced; moreover, the intensity of human activity has gradually increased. These have an impact on the growth of global vegetation. Related studies have focused on the Tibetan Plateau and some northern...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-04-01
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| Series: | Ecological Indicators |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S1470160X24004679 |
| _version_ | 1827279084458082304 |
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| author | Chang Chang Yu Chang Zaiping Xiong Hongshun Liu Rencang Bu |
| author_facet | Chang Chang Yu Chang Zaiping Xiong Hongshun Liu Rencang Bu |
| author_sort | Chang Chang |
| collection | DOAJ |
| description | In the past 10 years, extreme weather phenomena have increased, and global warming has markedly advanced; moreover, the intensity of human activity has gradually increased. These have an impact on the growth of global vegetation. Related studies have focused on the Tibetan Plateau and some northern provinces of China to estimate grassland AGB at a large scale but a low resolution. Hulunbuir Grassland is an important supplier of livestock products, and therefore, it is important to precisely map AGB and explore the response of Hulunbuir Grassland AGB to climate change and human activities at a high resolution to identify complex spatial details. In this study, we selected vegetation indices from Landsat 8 OLI and topographic indices and used multiple linear regression and machine learning algorithms to estimate the spatial distribution of AGB from 2013 to 2022. Then, we analyzed the correlations between AGB and cumulative precipitation and daily average temperature in summer and between population density and livestock density at the pixel level. Our results demonstrated that the RF model performed well, with an RMSE of 28.23 and R2 value of 0.74; the AGB was positively correlated with the cumulative precipitation in summer in 94.45 % of the area and negatively correlated with the daily average temperature in summer in 96.32 % of the area. We suggest that it is necessary to reduce grazing activities in future warm and drought years and to adjust sources of income to adapt to the decrease in AGB under global warming conditions. This study will provide reference for the countries or regions that depend on temperate grasslands for husbandry. |
| first_indexed | 2024-04-24T08:13:14Z |
| format | Article |
| id | doaj.art-cef2714b15bb4d86a99d4a5f615b71d1 |
| institution | Directory Open Access Journal |
| issn | 1470-160X |
| language | English |
| last_indexed | 2024-04-24T08:13:14Z |
| publishDate | 2024-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Ecological Indicators |
| spelling | doaj.art-cef2714b15bb4d86a99d4a5f615b71d12024-04-17T04:48:55ZengElsevierEcological Indicators1470-160X2024-04-01161112010Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten yearsChang Chang0Yu Chang1Zaiping Xiong2Hongshun Liu3Rencang Bu4CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; Corresponding author.CAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; University of Chinese Academy of Sciences, Beijing 100049, ChinaCAS Key Laboratory of Forest Ecology and Silviculture, Institute of Applied Ecology, Chinese Academy of Sciences, Shenyang 110016, China; E’erguna Wetland Ecosystem National Research Station, Hulunbuir 022250, ChinaIn the past 10 years, extreme weather phenomena have increased, and global warming has markedly advanced; moreover, the intensity of human activity has gradually increased. These have an impact on the growth of global vegetation. Related studies have focused on the Tibetan Plateau and some northern provinces of China to estimate grassland AGB at a large scale but a low resolution. Hulunbuir Grassland is an important supplier of livestock products, and therefore, it is important to precisely map AGB and explore the response of Hulunbuir Grassland AGB to climate change and human activities at a high resolution to identify complex spatial details. In this study, we selected vegetation indices from Landsat 8 OLI and topographic indices and used multiple linear regression and machine learning algorithms to estimate the spatial distribution of AGB from 2013 to 2022. Then, we analyzed the correlations between AGB and cumulative precipitation and daily average temperature in summer and between population density and livestock density at the pixel level. Our results demonstrated that the RF model performed well, with an RMSE of 28.23 and R2 value of 0.74; the AGB was positively correlated with the cumulative precipitation in summer in 94.45 % of the area and negatively correlated with the daily average temperature in summer in 96.32 % of the area. We suggest that it is necessary to reduce grazing activities in future warm and drought years and to adjust sources of income to adapt to the decrease in AGB under global warming conditions. This study will provide reference for the countries or regions that depend on temperate grasslands for husbandry.http://www.sciencedirect.com/science/article/pii/S1470160X24004679Aboveground biomassGrasslandRandom forestVegetation indicesSpatiotemporal variation |
| spellingShingle | Chang Chang Yu Chang Zaiping Xiong Hongshun Liu Rencang Bu Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years Ecological Indicators Aboveground biomass Grassland Random forest Vegetation indices Spatiotemporal variation |
| title | Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years |
| title_full | Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years |
| title_fullStr | Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years |
| title_full_unstemmed | Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years |
| title_short | Estimating the aboveground biomass of the Hulunbuir Grassland and exploring its spatial and temporal variations over the past ten years |
| title_sort | estimating the aboveground biomass of the hulunbuir grassland and exploring its spatial and temporal variations over the past ten years |
| topic | Aboveground biomass Grassland Random forest Vegetation indices Spatiotemporal variation |
| url | http://www.sciencedirect.com/science/article/pii/S1470160X24004679 |
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