Spatial and temporal changes in vegetation and desertification (1982–2018) and their responses to climate change in the Ulan Buh Desert, Northwest China

Li, Jiaqian; Li, Zhuolun; Dong, Shipei; Wei, Minghua; Zhou, Jinyan

doi:10.1007/s00704-021-03522-2

Cited by 13 publications

(10 citation statements)

References 64 publications

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“…Moreover, as an essential component of dryland ecosystems, herbaceous plants account for about 67% of the total dryland flora of Northwest China (Dang and Pan, 2002;Meng and Zhang, 2013). Herbaceous plants are not only essential indicator species of regional resource and environmental status (Luo et al, 2021), but they also have a unique role and special status in supporting material cycling, maintaining ecosystem function, and coping with climate change in ecologically fragile and sensitive environments (Li et al, 2021).…”

Section: Introductionmentioning

confidence: 99%

Precipitation preferences alter the relative importance of herbaceous plant diversity for multifunctionality in the drylands of China

Guo

Zhou²,

Tao³

et al. 2023

Front. Ecol. Evol.

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BackgroundMultiple components of biodiversity are excellent predictors of precipitation-induced changes in ecosystem function. However, the importance of differing scales (alpha versus beta) is usually overlooked in biodiversity–ecosystem multifunctionality studies. Consequently, little is known about how precipitation regulates the relationship between multifunctionality and multiple components of alpha and beta diversity.AimsWe investigated geographic patterns of herbaceous plant diversity and ecosystem multifunctionality along a precipitation gradient spanning more than 2010 km in Northwest China.MethodsWe assessed the effects of herbaceous species, phylogenetic, and functional components at different scales on multifunctionality in drylands.ResultsThe alpha diversity of species and functional beta diversity were key components explaining the variation in multifunctionality. As the main environmental factor, MAP (mean annual precipitation) affected multifunctionality by changing the mediating variables (i.e., species alpha and functional beta diversity). More importantly, a certain precipitation threshold was detected for the relationship of multifunctionality to species alpha and functional beta diversity. MAPs of approximately 158 mm and 140 mm modulated this relationship (shifting it from uncorrelated to significantly correlated).ConclusionsOur findings provide insights into previously neglected mechanisms by which diversity in herbaceous layers at different scales affects ecosystem multifunctionality. It is highlighted that MAP regulates the relationship between diversity and multifunctionality in dryland ecosystems at different scales. Further, diversity may have substantial consequences for multifunctionality where MAP is higher. These empirical results provide a comprehensive understanding of the biodiversity–multifunctionality relationship in the context of precipitation, ultimately contributing to conservation and restoration programs for multifunctionality in drylands.

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Section: Introductionmentioning

confidence: 99%

Precipitation preferences alter the relative importance of herbaceous plant diversity for multifunctionality in the drylands of China

Guo

Zhou²,

Tao³

et al. 2023

Front. Ecol. Evol.

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“…Based on previous studies focusing on the driving mechanism of desertification in northwestern China [9,28,41,42], as well as considering the mining characteristics of this region, 12 indexes were selected as the representative natural and human activity driving factors. These indexes included the average temperature, annual rainfall, total agricultural output value, total animal husbandry output value, and the number of main livestock and coal production activities.…”

Section: Desertification Driving Force Analysis Datamentioning

confidence: 99%

“…The desertification monitoring research using the intelligent algorithm of supervised classification is mainly different in the selection of classification characteristics and machine learning algorithms. In the establishment of multifeature datasets, most studies choose spectral features such as NDVI, Albedo, and TGSI [25][26][27][28]. They consider the vegetation, soil, radiance, and other information comprehensively.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Monitoring of Desertification in Ningdong Based on Landsat Images and Machine Learning

Chen

Shen

et al. 2022

Sustainability

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The ecological stability of mining areas in Northwest China has been threatened by desertification for a long time. Remote sensing information combined with machine learning algorithms can effectively monitor and evaluate desertification. However, due to the fact that the geological environment of a mining area is easily affected by factors such as resource exploitation, it is challenging to accurately grasp the development process of desertification in a mining area. In order to better play the role of remote sensing technology and machine learning algorithms in the monitoring of desertification in mining areas, based on Landsat images, we used a variety of machine learning algorithms and feature combinations to monitor desertification in Ningdong coal base. The performance of each monitoring model was evaluated by various performance indexes. Then, the optimal monitoring model was selected to extract the long-time desertification information of the base, and the spatial-temporal characteristics of desertification were discussed in many aspects. Finally, the factors driving desertification change were quantitatively studied. The results showed that random forest with the best feature combination had better recognition performance than other monitoring models. Its accuracy was 87.2%, kappa was 0.825, Macro-F1 was 0.851, and AUC was 0.961. In 2003–2017, desertification land in Ningdong increased first and then slowly improved. In 2021, the desertification situation deteriorated. The driving force analysis showed that human economic activities such as coal mining have become the dominant factor in controlling the change of desert in Ningdong coal base, and the change of rainfall plays an auxiliary role. The study comprehensively analyzed the spatial-temporal characteristics and driving factors of desertification in Ningdong coal base. It can provide a scientific basis for combating desertification and for the construction of green mines.

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“…Xu, Liu et al found a significant increasing trend of NDVI over the Silk Road Economic Belt (5 • 14 W-133 • 85 E, 25 • 16 N-56 • 16 N) region during the period 1981-2016 [7]. Li et al found a significant increasing trend of NDVI in the Ulanbu Desert region of northwest China during 1982-2018 [8].…”

Section: Introductionmentioning

confidence: 99%

Trend Changes of the Vegetation Activity in Northeastern East Asia and the Connections with Extreme Climate Indices

et al. 2022

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In the context of global warming, vegetation activity in northeastern East Asia (40–45°N, 105–130°E) (NEA) shows a significant growth trend on a multidecadal scale, but how vegetation changes on a decadal scale is unclear. In this study, we find a significant trend of vegetation greening in northeastern East Asia during 1982–1998 and a slowdown in the greening trend during 1998–2014. Trend analysis of the extreme climate indices reveals that the trends of precipitation-related extreme climate indices are similar to those of vegetation change, and further correlation analysis reveals that precipitation-related extreme climate indices have a strong positive correlation with the NDVI. The results indicate that the vegetation in northeastern East Asia is more sensitive to precipitation changes, especially extreme precipitation, compared with the temperature and related extreme indices. Furthermore, the analysis of large-scale atmospheric circulation changes suggests a role of Northwest Pacific subtropical high (NPSH) in the trend changes of precipitation-related extreme indices. The strengthening of NPSH before 1998 enhances the moisture transport to the NEA, providing abundant water vapor favorable for extreme precipitation events, while after 1998, the NPSH trend is much weakened, corresponding to a decrease in the moisture transport trend.

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Spatial and temporal changes in vegetation and desertification (1982–2018) and their responses to climate change in the Ulan Buh Desert, Northwest China

Cited by 13 publications

References 64 publications

Precipitation preferences alter the relative importance of herbaceous plant diversity for multifunctionality in the drylands of China

Precipitation preferences alter the relative importance of herbaceous plant diversity for multifunctionality in the drylands of China

Dynamic Monitoring of Desertification in Ningdong Based on Landsat Images and Machine Learning

Trend Changes of the Vegetation Activity in Northeastern East Asia and the Connections with Extreme Climate Indices

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