Relative effects of climate change and human activities on net primary productivity in Shule River Basin

Yanyan, 周妍妍 Zhou; Minxiang, 朱敏翔 Zhu; Xiaojuan, 郭晓娟 Guo; Kai, 李凯 Li; Junxia, 苗俊霞 Miao; Jianjun, 郭建军 Guo; Xiaofeng, 徐晓锋 Xu; Dongxia, 岳东霞 Yue

doi:10.5846/stxb201809141984

Cited by 3 publications

(3 citation statements)

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“…FVC res = FVC obs − FVC pre (4) where FVC res is the residual, which represents the FVC of vegetation under the influence of human activities; FVC obs is the original FVC; and FVC pre is the FVC of vegetation under the influence of climate change.…”

Section: (4) Residual Analysismentioning

confidence: 99%

“…The United Nations Convention to Combat Desertification defines desertification as the degradation of land in arid, semi-arid and dry sub-humid areas, indicating that desertification is essentially a manifestation of land degradation under certain conditions [1,2]. Climate change has a very complex impact on desertification, as it alters vegetation cover and vegetation indices in desertified areas [3][4][5]. At present, the influences of various climate factors on desertification remain unclear.…”

Section: Introductionmentioning

confidence: 99%

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Influence of Key Climate Factors on Desertification in Inner Mongolia

Liu,

Ma,

Liu

et al. 2023

Atmosphere

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Desertification is a major environmental problem facing the world today, and climate change is an important factor influencing desertification. This study investigates the impact of changes in key climate factors on desertification based on normalized difference vegetation index data, precipitation data and evaporation data from Inner Mongolia between 1982 and 2020 using correlation analysis, regression modelling, and residual analysis. The results show that precipitation and evaporation are significantly correlated with mild desertification and severe desertification, respectively, with correlation coefficients reaching 0.98 and −0.96, respectively. In severely desertified areas in central-eastern Inner Mongolia, there is a high correlation between desertification and temperature, the characteristics of the correlation of average maximum and minimum temperatures with desertification are similar to those of the correlation of average temperature with desertification, and the average maximum and minimum temperatures are well correlated with mild desertification, with correlation coefficients as high as 0.98 and 0.978, respectively. Climate contribution accounts for 97% of desertification in severely desertified areas, indicating that climate change has increased desertification in these areas. In regions with improved desertification, approximately 75% are primarily influenced by climate change (with a relative contribution greater than 50%), with climate factors exhibiting a relative contribution greater than 75% to desertification in 30% of these regions.

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Section: (4) Residual Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Influence of Key Climate Factors on Desertification in Inner Mongolia

Liu,

Ma,

Liu

et al. 2023

Atmosphere

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“…Gang, Zhou [21] and Zhou, Gang [8] have extended the study area of this method to global and regional scales. Therefore, the NPP coupled with scenario simulation method has been proven to be reliable in monitoring land degradation [23,[29][30][31].…”

Section: Introductionmentioning

confidence: 99%

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Yang,

Xu,

Sun

et al. 2023

Agronomy

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Central Asia is one of the most sensitive regions to climate changes in the world and the grassland degradation of this region has attracted considerable concern. Quantifying the driving force of grassland degradation is important for understanding the effects of climate variation and human activities on grassland. In this study, net primary productivity (NPP) was selected as an indicator to quantitatively evaluate the relative role of climate variation and human activities in Central Asia from 2000 to 2020. This study used the global NPP product MOD17A3 as actual NPP and estimated the potential NPP using the Thornthwaite memorial model. The potential NPP and the difference between the potential NPP and actual NPP were used to represent the influence of climate variation and human activities. The grassland degradation or restoration can be demonstrated by the slope of actual NPP (SA). A positive slope value (SA) suggested that restoration occurs, whereas a negative slope value suggested that degradation occurred. The results showed that 23.08% of the total grassland area experienced grassland degradation, whereas 2.51% of the whole grassland underwent grassland restoration. Furthermore, 53.8% of the degraded grassland areas were influenced by climate variation, and 14.5% were caused by human activities. By contrast, the relative roles of climate variation and human activities in grassland restoration were 25% and 47.9%, respectively. The NPP variation also could be calculated by assessing the effects of these factors and the results showed that 55.7% of the NPP decrease was caused by climate variation, whereas 9.6% was a result of human activities. On the contrary, climate variation and human activities resulted in 19.8% and 37.3% of grassland restoration, respectively. Therefore, climate variation was the dominant factor of grassland degradation, and human activities were the main driver of grassland restoration in Central Asia.

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Study on Spatial-Temporal Pattern and Driving Forces of Net Primary Production of Vegetation in Guangdong from the Perspective of “Production-Living-Ecological Space”

吕

2023

GSER

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Relative effects of climate change and human activities on net primary productivity in Shule River Basin

Cited by 3 publications

References 0 publications

Influence of Key Climate Factors on Desertification in Inner Mongolia

Influence of Key Climate Factors on Desertification in Inner Mongolia

Dynamic of Grassland Degradation and Its Driving Forces from Climate Variation and Human Activities in Central Asia

Study on Spatial-Temporal Pattern and Driving Forces of Net Primary Production of Vegetation in Guangdong from the Perspective of “Production-Living-Ecological Space”

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