Impact of land use intensity on sandy desertification: An evidence from Horqin Sandy Land, China

Ge, Xiaodong; Dong, Kaikai; Luloff, A. E.; Wang, Luyao; Xiao, Jun

doi:10.1016/j.ecolind.2015.09.035

Cited by 36 publications

(13 citation statements)

References 34 publications

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“…The increase was most significant for grassland, and less for forest. The significant greening trend of grassland in this region was also observed by several previous studies (Ge et al , ; ). The decrease in NDVI in the 1990s was most prominent in grassland, less but observable in cropland, and almost nonexistent for forest.…”

Section: Resultssupporting

confidence: 88%

Normalized Difference Vegetation Index‐based assessment of climate change impact on vegetation growth in the humid‐arid transition zone in northern China during 1982–2013

Yuan

Hou

et al. 2019

Intl Journal of Climatology

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As an ecologically sensitive region, the humid‐to‐arid climate transition zone in the eastern and central north China (ECNC) has experienced varied vegetation change in recent decades, but the exact impacts of climate change and human activities remain uncertain. Based on the Normalized Difference Vegetation Index (NDVI), we established the trend of vegetation change in the past three decades (1982–2013) in the ECNC, and examined the impact of climate and nonclimate factors on vegetation growth within the different eco‐regions. For the study period, the climate in ECNC became significantly warmer and slightly drier, and the overall NDVI increased significantly, but with great spatial variations. Our results suggest that temperature increase has promoted vegetation growth in places that are colder and/or wetter, and with higher vegetation coverage. Precipitation increase has promoted vegetation growth in drier places with sparse vegetation and inhibited growth in wet places with high vegetation coverage. As different eco‐regions typically have different vegetation coverage and occupy different climate zones, their response to climate change also varies. For the study period, increasing temperature and decreasing precipitation promoted vegetation growth in the forest of northern ECNC. Increasing temperature and precipitation led to NDVI increase in the grassland in the south, whereas grassland in the north and west showed no significant change despite temperature increase and precipitation decrease. Cropland responded mostly positively to temperature increase, although correlations between NDVI and climate factors were generally weaker. Using multiple regression models, we found that 60% of the NDVI increase was attributed to climate factors whereas the remaining 40% was likely caused by human activities. Although farming practices and crop rotations might have caused significant decrease in NDVI in small areas, human impact largely led to significant NDVI increase in the grass‐crop transition zones, most likely due to ecological restoration programs.

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Section: Resultssupporting

confidence: 88%

Normalized Difference Vegetation Index‐based assessment of climate change impact on vegetation growth in the humid‐arid transition zone in northern China during 1982–2013

Yuan

Hou

et al. 2019

Intl Journal of Climatology

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“…because ARDL modelling performs better with a smaller sample size than other cointegration techniques (Haug 2002; Abdullah Yusof and Duasa 2010). For instance, the ARDL methodology was shown to achieve good performance in measurement of environmental quality related indicators (such as sandy desertification and deforestation) (Ahmed et al 2015;Ge et al 2016). As a first step (see Fig.…”

Section: (A)mentioning

confidence: 99%

Determining the sensitivity of grassland area burned to climate variation in Xilingol, China, with an autoregressive distributed lag approach

Shabbir

Zhang

Liu

et al. 2019

Int. J. Wildland Fire

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We examined the relationship between climate variables and grassland area burned in Xilingol, China, from 2001 to 2014 using an autoregressive distributed lag (ARDL) model, and describe the application of this econometric method to studies of climate influences on wildland fire. We show that there is a stationary linear combination of non-stationary climate time series (cointegration) that can be used to reliably estimate the influence of different climate signals on area burned. Our model shows a strong relationship between maximum temperature and grassland area burned. Mean monthly wind speed and monthly hours of sunlight were also strongly associated with area burned, whereas minimum temperature and precipitation were not. Some climate variables like wind speed had significant immediate effects on area burned, the strength of which varied over the 2001–14 observation period (in econometrics terms, a ‘short-run’ effect). The relationship between temperature and area burned exhibited a steady-state or ‘long-run’ relationship. We analysed three different periods (2001–05, 2006–10 and 2011–14) to illustrate how the effects of climate on area burned vary over time. These results should be helpful in estimating the potential impact of changing climate on the eastern Eurasian Steppe.

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“…the area of returning farmland to forest and grass, the area of planting trees and grass in unused land and other human factors can change the NPP value and spatial distribution of vegetation by directly changing both the land use type and its intensity. Limited to the spatial scope of human activities, such as urbanisation and grazing, desertification dynamics induced by human factors showed a clustering characteristic(Ge, Dong, Luloff, Wang, & Xiao, 2016;Prince, Becker- Reshef, & Rishmawi, 2009), in being mainly located in the vicinity of towns and villages.The change and adjustment in the range of driving factors or key parameters under the differing scenarios would lead to significant changes in the extent and degree of desertification in North China in 2030. For the baseline scenario, desertification in North China generally presented a reversal trend, with the reversal area more than 5% larger than the area of desertification expansion.…”

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confidence: 99%

Multi‐scenario simulation of desertification in North China for 2030

Zhang

2020

Land Degrad Dev

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Since desertification threatens the global environment and the security of societies, predicting its patterns and trends across space and time would inform policy‐making strategies for desertification control and sustainable development. China is among the countries most severely affected by desertification, representing 17.93% of its total land area. To better understand the future dynamics of desertification in China, a spatial system dynamics model that coupled natural and human factors was developed to simulate the desertification process in North China in 2030 under nine scenarios. The results showed the model had good applicability and satisfactory accuracy for desertification simulation at the national scale, for which temperature and rainfall were the most sensitive factors driving the process. Current ecological projects and policies were found to be effective for desertification control, which would lead to reversal of desertification in 2030 when coupled with average predicted climate conditions; further, this reversal trend would be accelerated under a humid climate scenario. Although positive ecological policies would promote the reversal of desertification, only a 5% increase of rehabilitated area was obtained when it was coupled with an arid climatic conditions. The latter (aridity) and a passive ecological protection policy would together accelerate desertification expansion, especially in the Yili Basin, in the Houshan region of Inner Mongolia and the Yinchuan Plain. Thus, the ecological projects and policies should be carried on in the long‐term to achieve sustainable control and help prevent desertification.

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Impact of land use intensity on sandy desertification: An evidence from Horqin Sandy Land, China

Cited by 36 publications

References 34 publications

Normalized Difference Vegetation Index‐based assessment of climate change impact on vegetation growth in the humid‐arid transition zone in northern China during 1982–2013

Normalized Difference Vegetation Index‐based assessment of climate change impact on vegetation growth in the humid‐arid transition zone in northern China during 1982–2013

Determining the sensitivity of grassland area burned to climate variation in Xilingol, China, with an autoregressive distributed lag approach

Multi‐scenario simulation of desertification in North China for 2030

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