scholarly journals Estimation and Climate Factor Contribution of Aboveground Biomass in Inner Mongolia’s Typical/Desert Steppes

2019 ◽  
Vol 11 (23) ◽  
pp. 6559
Author(s):  
Wang ◽  
Dong ◽  
Baoyin ◽  
Bao
Keyword(s):  
Spatial Resolution ◽  
Aboveground Biomass ◽  
Inner Mongolia ◽  
Vegetation Index ◽  
Desert Steppe ◽  
Individual Effect ◽  
Function Model ◽  
Typical Steppe ◽  
Independent Variable ◽  
The Individual

Grassland biomass is an essential part of the regional carbon cycle. Rapid and accurate estimation of grassland biomass is a hot topic in research on grassland ecosystems. This study was based on field-measured biomass data and satellite remote sensing data from the Moderate resolution imaging spectroradiometer (MODIS). A generalized linear model (GLM) was used to analyze the aboveground biomass (AGB), dynamic changes, and relevance of climatic factors of the typical/desert steppe in Inner Mongolia during the growing seasons from May 2009 to October 2015. The results showed that: (1) The logarithmic function model with the ratio vegetation index (RVI) as the independent variable worked best for the typical steppe area in Inner Mongolia, while the power function model with the normalized differential vegetation index (NDVI) as the independent variable worked best for the desert steppe area. The R2 values at a spatial resolution of 250 m were higher than those at a spatial resolution 500 m. (2) From 2009 to 2015, the highest values of AGB in the typical steppe and desert steppe of Inner Mongolia both appeared in 2012, and were 41.9 Tg and 7.0 Tg, respectively. The lowest values were 30.7 Tg and 5.8 Tg, respectively, in 2009. (3) The overall spatial distribution of AGB decreased from northeast to southwest. It also changed considerably over time. From May to August, AGB at the same longitude increased from south to north with seasonal variations; from August to October, it increased from north to south. (4) A variation partitioning analysis showed that in both the typical steppe and desert steppe, the combined effect of precipitation and temperature contributed the most to the aboveground biomass. The individual effect of temperature contributed more than precipitation in the typical steppe, while the individual effect of precipitation contributed more in the desert steppe. Thus, the hydrothermal dynamic hypothesis was used to explain this pattern. This study provides support for grassland husbandry management and carbon storage assessment in Inner Mongolia.

scholarly journals Changing Trends of NDVI and Their Responses to Climatic Variation in Different Types of Grassland in Inner Mongolia from 1982 to 2011

2019 ◽  
Vol 11 (12) ◽  
pp. 3256 ◽  
Author(s):  
Jie Yang ◽  
Zhiqiang Wan ◽  
Suld Borjigin ◽  
Dong Zhang ◽  
Yulong Yan ◽  
...  
Keyword(s):  
Inner Mongolia ◽  
Vegetation Index ◽  
Climatic Variation ◽  
Future Research ◽  
Desert Steppe ◽  
Vegetation Density ◽  
Meadow Steppe ◽  
Typical Steppe ◽  
Changing Trends ◽  
Different Types

Normalized difference vegetation index (NDVI) is commonly used to indicate vegetation density and condition. NDVI was mostly correlated with climate factors. We analyzed changing trends of NDVI in different types of grassland in Inner Mongolia and the response of NDVI to climatic variation from 1982 to 2011. NDVI of meadow steppe increased significantly in spring while it decreased in other seasons. The annual mean NDVI in typical steppe and desert steppe increased significantly in the last 30a. However, in the greatest area of steppe desert, the NDVI had no significant change in summer, autumn, and the growing season. In meadow steppe, typical steppe, and desert steppe, the area showed a positive correlation of NDVI to temperature as highest in spring compared to other seasons, because warming in spring is beneficial to the plant growth. However, in the greatest area of steppe desert, the correlation of NDVI to temperature was not significant. The NDVI was positively correlated to precipitation in four types of grassland. In the steppe desert, the precipitation had no significant effect on the NDVI due to the poor vegetation cover in this region. The NDVI was not significantly correlated to the precipitation in autumn because of vegetation withering in the season and not need precipitation. Precipitation was a more important factor rather than temperature to NDVI in the region. The response of NDVI to temperature and precipitation in different seasons should be studied in more detail and the effect of other factors on NDVI should be considered in future research.

The aboveground biomass of desert steppe and its spatiotemporal variation in western Inner Mongolia

2013 ◽  
Vol 5 (3) ◽  
pp. 339
Author(s):  
Gao Tian ◽  
Xu Bin ◽  
Yang Xiu-Chun ◽  
Jin Yun-Xiang ◽  
Ma Hai-Long ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Inner Mongolia ◽  
Spatiotemporal Variation ◽  
Desert Steppe

Temporal and spatial heterogeneity of drought impact on vegetation growth on the Inner Mongolian Plateau

2018 ◽  
Vol 40 (2) ◽  
pp. 113 ◽  
Author(s):  
Miao Bailing ◽  
Li Zhiyong ◽  
Liang Cunzhu ◽  
Wang Lixin ◽  
Jia Chengzhen ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Severity Index ◽  
Drought Severity ◽  
Summer Drought ◽  
Desert Steppe ◽  
Vegetation Types ◽  
Mongolian Plateau ◽  
Typical Steppe ◽  
Recent Climate ◽  
Normalised Difference Vegetation Index

Drought frequency and intensity have increased in recent decades, with consequences for the structure and function of ecosystems of the Inner Mongolian Plateau. In this study, the Palmer drought severity index (PDSI) was chosen to assess the extent and severity of drought between 1982 and 2011. The normalised difference vegetation index (NDVI) was used to analyse the responses of five different vegetation types (forest, meadow steppe, typical steppe, desert steppe and desert) to drought. Our results show that during the last 30 years, the frequency and intensity of droughts have increased significantly, especially in summer and autumn. The greatest decline in NDVI in response to drought was observed in typical steppe and desert steppe vegetation types. Compared with other seasons, maximum decline in NDVI was observed in summer. In addition, we found that NDVI in the five vegetation types showed a lag time of 1–2 months from drought in the spring and summer. Ancillary soil moisture conditions influenced the drought response, with desert steppe showing a stronger lag effect to spring and summer drought than the other vegetation types. Our results show that drought explains a high proportion of changes in NDVI, and suggest that recent climate change has been an important factor affecting vegetation productivity in the area.

scholarly journals NDVI-Based Vegetation Change in Inner Mongolia from 1982 to 2006 and Its Relationship to Climate at the Biome Scale

2014 ◽  
Vol 2014 ◽  
pp. 1-12 ◽  
Author(s):  
Linghui Guo ◽  
Shaohong Wu ◽  
Dongsheng Zhao ◽  
Yunhe Yin ◽  
Guoyong Leng ◽  
...  
Keyword(s):  
Climate Change ◽  
Land Use ◽  
Land Use Change ◽  
Inner Mongolia ◽  
Vegetation Change ◽  
Vegetation Index ◽  
Potential Evapotranspiration ◽  
Vegetation Type ◽  
Growing Season ◽  
Desert Steppe

Based on the normalized difference vegetation index (NDVI), we analyzed vegetation change of the six major biomes across Inner Mongolia at the growing season and the monthly timescales and estimated their responses to climate change between 1982 and 2006. To reduce disturbance associated with land use change, those pixels affected by land use change from the 1980s to 2000s were excluded. At the growing season scale, the NDVI increased weakly in the natural ecosystems, but strongly in cropland. Interannual variations in the growing season NDVI for forest was positively linked with potential evapotranspiration and temperature, but negatively correlated with precipitation. In contrast, it was positively correlated with precipitation, but negatively related to potential evapotranspiration for other natural biomes, particularly for desert steppe. Although monthly NDVI trends were characterized as heterogeneous, corresponding to monthly variations in climate change among biome types, warming-related NDVI at the beginning of the growing season was the main contributor to the NDVI increase during the growing season for forest, meadow steppe, and typical steppe, but it constrained the NDVI increase for desert steppe, desert, and crop. Significant one-month lagged correlations between monthly NDVI and climate variables were found, but the correlation characteristics varied greatly depending on vegetation type.

scholarly journals Impact of Grazing on Soil Carbon and Microbial Biomass in Typical Steppe and Desert Steppe of Inner Mongolia

PLoS ONE ◽  
2012 ◽  
Vol 7 (5) ◽  
pp. e36434 ◽  
Author(s):  
Nan Liu ◽  
Yingjun Zhang ◽  
Shujuan Chang ◽  
Haiming Kan ◽  
Lijun Lin
Keyword(s):  
Microbial Biomass ◽  
Soil Carbon ◽  
Inner Mongolia ◽  
Desert Steppe ◽  
Typical Steppe

scholarly journals Satellite-Derived Estimation of Grassland Aboveground Biomass in the Three-River Headwaters Region of China during 1982–2018

2021 ◽  
Vol 13 (15) ◽  
pp. 2993
Author(s):  
Ruiyang Yu ◽  
Yunjun Yao ◽  
Qiao Wang ◽  
Huawei Wan ◽  
Zijing Xie ◽  
...  
Keyword(s):  
Spatial Resolution ◽  
Aboveground Biomass ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Growth Period ◽  
Spatiotemporal Variation ◽  
Coefficient Of Determination ◽  
Gradient Boosting ◽  
Ancillary Data

The long-term estimation of grassland aboveground biomass (AGB) is important for grassland resource management in the Three-River Headwaters Region (TRHR) of China. Due to the lack of reliable grassland AGB datasets since the 1980s, the long-term spatiotemporal variation in grassland AGB in the TRHR remains unclear. In this study, we estimated AGB in the grassland of 209,897 km2 using advanced very high resolution radiometer (AVHRR), MODerate-resolution Imaging Spectroradiometer (MODIS), meteorological, ancillary data during 1982–2018, and 75 AGB ground observations in the growth period of 2009 in the TRHR. To enhance the spatial representativeness of ground observations, we firstly upscaled the grassland AGB using a gradient boosting regression tree (GBRT) model from ground observations to a 1 km spatial resolution via MODIS normalized difference vegetation index (NDVI), meteorological and ancillary data, and the model produced validation results with a coefficient of determination (R2) equal to 0.76, a relative mean square error (RMSE) equal to 88.8 g C m−2, and a bias equal to −1.6 g C m−2 between the ground-observed and MODIS-derived upscaled AGB. Then, we upscaled grassland AGB using the same model from a 1 km to 5 km spatial resolution via AVHRR NDVI and the same data as previously mentioned with the validation accuracy (R2 = 0.74, RMSE = 57.8 g C m−2, and bias = −0.1 g C m−2) between the MODIS-derived reference and AVHRR-derived upscaled AGB. The annual trend of grassland AGB in the TRHR increased by 0.37 g C m−2 (p < 0.05) on average per year during 1982–2018, which was mainly caused by vegetation greening and increased precipitation. This study provided reliable long-term (1982–2018) grassland AGB datasets to monitor the spatiotemporal variation in grassland AGB in the TRHR.

scholarly journals Remote-sensing inversion method for aboveground biomass of typical steppe in Inner Mongolia, China

2021 ◽  
Vol 120 ◽  
pp. 106883
Author(s):  
Xin Lyu ◽  
Xiaobing Li ◽  
Jirui Gong ◽  
Shengkun Li ◽  
Huashun Dou ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Aboveground Biomass ◽  
Inner Mongolia ◽  
Inversion Method ◽  
Typical Steppe

scholarly journals Precipitation Variability Affects Aboveground Biomass Directly and Indirectly via Plant Functional Traits in the Desert Steppe of Inner Mongolia, Northern China

2021 ◽  
Vol 12 ◽  
Author(s):  
Huan Cheng ◽  
Yuanbo Gong ◽  
Xiaoan Zuo
Keyword(s):  
Leaf Area ◽  
Functional Traits ◽  
Aboveground Biomass ◽  
Inner Mongolia ◽  
Structural Equation Models ◽  
Plant Functional Traits ◽  
Leaf Nitrogen Content ◽  
Dry Matter Content ◽  
Desert Steppe ◽  
Precipitation Changes

Clarifying the response of community and dominance species to climate change is crucial for disentangling the mechanism of the ecosystem evolution and predicting the prospective dynamics of communities under the global climate scenario. We examined how precipitation changes affect community structure and aboveground biomass (AGB) according to manipulated precipitation experiments in the desert steppe of Inner Mongolia, China. Bayesian model and structural equation models (SEM) were used to test variation and causal relationship among precipitation, plant diversity, functional attributes, and AGB. The results showed that the responses of species richness, evenness, and plant community weighted means traits to precipitation changes in amount and year were significant. The SEM demonstrated that precipitation change in amount and year has a direct effect on richness, evenness, and community-weighted mean (CWM) for height, leaf area (LA), specific leaf area (SLA), leaf dry matter content (LDMC), leaf nitrogen content (LNC), and leaf carbon content (LCC) and AGB; there into CWM for height and LDMC had a direct positive effect on AGB; LA had a direct negative effect on AGB. Three dominant species showed diverse adaptation and resource utilization strategies in response to precipitation changes. A. polyrhizum showed an increase in height under the precipitation treatments that promoted AGB, whereas the AGB of P. harmala and S. glareosa was boosted through alterations in height and LA. Our results highlight the asynchronism of variation in community composition and structure, leaf functional traits in precipitation-AGB relationship. We proposed that altered AGB resulted from the direct and indirect effects of plant functional traits (plant height, LA, LDMC) rather than species diversity, plant functional traits are likely candidate traits, given that they are mechanistically linked to precipitation changes and affected aboveground biomass in a desert steppe.

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