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.

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 Early warning indicators of grassland degradation in inner Mongolia

2017 ◽  
Author(s):  
Jie Qin ◽  
Guodong Han ◽  
Zhongwu Wang ◽  
Linxi Hu ◽  
Jun Zhang
Keyword(s):  
Early Warning ◽  
Inner Mongolia ◽  
Grassland Degradation ◽  
Desert Steppe ◽  
Meadow Steppe ◽  
Vegetation Composition ◽  
Typical Steppe ◽  
Early Warning Indicators ◽  
Warning Indicators ◽  
Spatial Threshold

Backgroung: With the implementation of the Household Production Responsibility System in China almost 30 years ago, obvious spatial heterogeneity has developed over rangeland. Methods: We examined lifeform functional groups over 5 years on household ranches in different grazing utilization rate (30%-95%) ecosystems in Inner Mongolia to identify the early warning indicators of grassland degradation. Results: The results showed that a similar grassland utilization threshold occurred in different types of steppe, with 78-89% utilization for meadow steppe, 81-89% for typical steppe and 70-85% for desert steppe. The vegetation composition above these utilization thresholds did not show obvious signs of degradation; therefore, the risk of degradation was difficult to determine. The spatial threshold (WD: L) had a value of 31.40:100 for meadow steppe, 8.53:100 for typical steppe and 42.21:100 for desert steppe. Conclusion: Land managers cannot easily determine the risk of degeneration according to the vegetation composition or function group. So the spatial threshold is important for implemented strategies to prevent degradation, and our study provides new insights to improve the management and restoration of degraded grassland in Inner Mongolia.

scholarly journals Early warning indicators of grassland degradation in inner Mongolia

2017 ◽  
Author(s):  
Jie Qin ◽  
Guodong Han ◽  
Zhongwu Wang ◽  
Linxi Hu ◽  
Jun Zhang
Keyword(s):  
Early Warning ◽  
Inner Mongolia ◽  
Grassland Degradation ◽  
Desert Steppe ◽  
Meadow Steppe ◽  
Vegetation Composition ◽  
Typical Steppe ◽  
Early Warning Indicators ◽  
Warning Indicators ◽  
Spatial Threshold

Backgroung: With the implementation of the Household Production Responsibility System in China almost 30 years ago, obvious spatial heterogeneity has developed over rangeland. Methods: We examined lifeform functional groups over 5 years on household ranches in different grazing utilization rate (30%-95%) ecosystems in Inner Mongolia to identify the early warning indicators of grassland degradation. Results: The results showed that a similar grassland utilization threshold occurred in different types of steppe, with 78-89% utilization for meadow steppe, 81-89% for typical steppe and 70-85% for desert steppe. The vegetation composition above these utilization thresholds did not show obvious signs of degradation; therefore, the risk of degradation was difficult to determine. The spatial threshold (WD: L) had a value of 31.40:100 for meadow steppe, 8.53:100 for typical steppe and 42.21:100 for desert steppe. Conclusion: Land managers cannot easily determine the risk of degeneration according to the vegetation composition or function group. So the spatial threshold is important for implemented strategies to prevent degradation, and our study provides new insights to improve the management and restoration of degraded grassland in Inner Mongolia.

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 Herders’ opinions about desirable stocking rates and overstocking in the rangelands of northern China

2014 ◽  
Vol 36 (6) ◽  
pp. 601 ◽  
Author(s):  
Xiangyang Hou ◽  
Yantin Yin ◽  
David Michalk ◽  
Xiangjun Yun ◽  
Yong Ding ◽  
...  
Keyword(s):  
Formal Education ◽  
Northern China ◽  
Rangeland Management ◽  
Chinese Government ◽  
Desert Steppe ◽  
Stocking Rate ◽  
Meadow Steppe ◽  
Typical Steppe ◽  
Breeding Practices ◽  
Stocking Rates

Herders’ desirable stocking rates and their opinions of overstocking were studied using survey and multi-regression methods in the meadow steppe, typical steppe and desert steppe regions of northern China. It was found that individual herders had their own perception of their particular ‘desirable stocking rate’, which referred to the number of livestock that the herders thought they could keep or maintain on an area of rangeland over a specified period of time. These perceptions were not in line with the ‘balancing animals and grass’ policy of the Chinese government, and herders used them as a guide to adjust stock-breeding practices. Most herders admitted that they bred more livestock now than 10 years ago, but insisted that there was no overstocking and many even thought that their rangelands could still carry more livestock. They also held the view that they took into account the carrying capacity of rangelands when making decisions about livestock-breeding practices. Individual herders thought that the reasonable stocking rate range should be 0.75–1.50 sheep units ha–1 (meadow steppe), 0.60–1.50 sheep units ha–1 (typical steppe), and 0.50–0.75 sheep units ha–1 (desert steppe), respectively. The herders from the desert steppe regions were most concerned about the overstocking of rangelands, and the concern of herders was in the order desert steppe > typical steppe > meadow steppe. The herders with more formal education and those who worked in a village council and had smaller areas of rangelands, were more concerned about the overstocking of rangelands. It is argued that such herders should be given more access to policy and market information, including extensive grazing and modern stall-feeding technologies, and encouraged to reduce their desirable stocking rates, leading to more sustainable rangeland management in northern China.

scholarly journals Phenology Response to Climatic Dynamic across China’s Grasslands from 1985 to 2010

2018 ◽  
Vol 7 (8) ◽  
pp. 290 ◽  
Author(s):  
Jun Wang ◽  
Tiancai Zhou ◽  
Peihao Peng
Keyword(s):  
Climate Change ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Climatic Factors ◽  
Growing Season ◽  
Northern China ◽  
Plant Phenology ◽  
Meadow Steppe ◽  
Typical Steppe ◽  
Alpine Steppe

Because the dynamics of phenology in response to climate change may be diverse in different grasslands, quantifying how climate change influences plant growth in different grasslands across northern China should be particularly informative. In this study, we explored the spatiotemporal variation of the phenology (start of the growing season [SOS], peak of the growing season [POS], end of the growing season [EOS], and length of the growing season [LOS]) across China’s grasslands using a dataset of the GIMMS3g normalized difference vegetation index (NDVI, 1985–2010), and determined the effects of the annual mean temperature (AMT) and annual mean precipitation (AMP) on the significantly changed phenology. We found that the SOS, POS, and EOS advanced at the rates of 0.54 days/year, 0.64 days/year, and 0.65 days/year, respectively; the LOS was shortened at a rate of 0.62 days/year across China’s grasslands. Additionally, the AMT combined with the AMP explained the different rates (ER) for the significantly dynamic SOS in the meadow steppe (R2 = 0.26, p = 0.007, ER = 12.65%) and typical steppe (R2 = 0.28, p = 0.005, ER = 32.52%); the EOS in the alpine steppe (R2 = 0.16, p < 0.05, ER = 6.22%); and the LOS in the alpine (R2 = 0.20, p < 0.05, ER = 6.06%), meadow (R2 = 0.18, p < 0.05, ER = 16.69%) and typical (R2 = 0.18, p < 0.05, ER = 19.58%) steppes. Our findings demonstrated that the plant phenology in different grasslands presented discrepant dynamic patterns, highlighting the fact that climate change has played an important role in the variation of the plant phenology across China’s grasslands, and suggested that the variation and relationships between the climatic factors and phenology in different grasslands should be explored further in the future.

scholarly journals Estimating Grassland Carbon Stocks in Hulunber China, Using Landsat8 Oli Imagery and Regression Kriging †

Sensors ◽  
2019 ◽  
Vol 19 (24) ◽  
pp. 5374
Author(s):  
Lei Ding ◽  
Zhenwang Li ◽  
Xu Wang ◽  
Ruirui Yan ◽  
Beibei Shen ◽  
...  
Keyword(s):  
Carbon Stock ◽  
Vegetation Index ◽  
Regional Scale ◽  
Carbon Stocks ◽  
Estimation Accuracy ◽  
Regression Kriging ◽  
Meadow Steppe ◽  
Model Accuracy ◽  
Study Region ◽  
Typical Steppe

Accurately estimating grassland carbon stocks is important in assessing grassland productivity and the global carbon balance. This study used the regression kriging (RK) method to estimate grassland carbon stocks in Northeast China based on Landsat8 operational land imager (OLI) images and five remote sensing variables. The normalized difference vegetation index (NDVI), the wide dynamic range vegetation index (WDRVI), the chlorophyll index (CI), Band6 and Band7 were used to build the RK models separately and to explore their capabilities for modeling spatial distributions of grassland carbon stocks. To explore the different model performances for typical grassland and meadow grassland, the models were validated separately using the typical steppe, meadow steppe or all-steppe ground measurements based on leave-one-out crossvalidation (LOOCV). When the results were validated against typical steppe samples, the Band6 model showed the best performance (coefficient of determination (R2) = 0.46, mean average error (MAE) = 8.47%, and root mean square error (RMSE) = 10.34 gC/m2) via the linear regression (LR) method, while for the RK method, the NDVI model showed the best performance (R2 = 0.63, MAE = 7.04 gC/m2, and RMSE = 8.51 gC/m2), which were much higher than the values of the best LR model. When the results were validated against the meadow steppe samples, the CI model achieved the best estimation accuracy, and the accuracy of the RK method (R2 = 0.72, MAE = 8.09 gC/m2, and RMSE = 9.89 gC/m2) was higher than that of the LR method (R2 = 0.70, MAE = 8.99 gC/m2, and RMSE = 10.69 gC/m2). Upon combining the results of the most accurate models of the typical steppe and meadow steppe, the RK method reaches the highest model accuracy of R2 = 0.69, MAE = 7.40 gC/m2, and RMSE = 9.01 gC/m2, while the LR method reaches the highest model accuracy of R2 = 0.53, MAE = 9.20 gC/m2, and RMSE = 11.10 gC/m2. The results showed an improved performance of the RK method compared to the LR method, and the improvement in the accuracy of the model is mainly attributed to the enhancement of the estimation accuracy of the typical steppe. In the study region, the carbon stocks showed an increasing trend from west to east, the total amount of grassland carbon stock was 79.77 × 104 Mg C, and the mean carbon stock density was 47.44 gC/m2. The density decreased in the order of temperate meadow steppe, lowland meadow steppe, temperate typical steppe, and sandy steppe. The methodology proposed in this study is particularly beneficial for carbon stock estimates at the regional scale, especially for countries such as China with many grassland types.

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