Phylogeny and biogeography of Primula sect. Armerina: implications for plant evolution under climate change and the uplift of the Qinghai-Tibet Plateau

Alpine meadow and alpine steppe are the two most widely distributed nonzonal vegetation types in the Qinghai-Tibet Plateau. In the context of global climate change, the differences in spatial-temporal variation trends and their responses to climate change are discussed. It is of great significance to reveal the response of the Qinghai-Tibet Plateau to global climate change and the construction of ecological security barriers. This study takes alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau as the research objects. The normalized difference vegetation index (NDVI) data and meteorological data were used as the data sources between 2000 and 2018. By using the mean value method, threshold method, trend analysis method and correlation analysis method, the spatial and temporal variation trends in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau were compared and analyzed, and their differences in the responses to climate change were discussed. The results showed the following: (1) The growing season length of alpine meadow was 145~289 d, while that of alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau was 161~273 d, and their growing season lengths were significantly shorter than that of alpine meadow. (2) The annual variation trends of the growing season NDVI for the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau increased obviously, but their fluctuation range and change rate were significantly different. (3) The overall vegetation improvement in the Qinghai-Tibet Plateau was primarily dominated by alpine steppe and alpine meadow, while the degradation was primarily dominated by alpine meadow. (4) The responses between the growing season NDVI and climatic factors in the alpine meadow, alpine steppe and the overall vegetation of the Qinghai-Tibet Plateau had great spatial heterogeneity in the Qinghai-Tibet Plateau. These findings provide evidence towards understanding the characteristics of the different vegetation types in the Qinghai-Tibet Plateau and their spatial differences in response to climate change.

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Spatial variability of topsoil δ13C across Qinghai-Tibet Plateau

10.5194/egusphere-egu21-5768 ◽

2021 ◽

Author(s):

Yunsen Lai ◽

Shaoda Li ◽

Xiaolu Tang ◽

Xinrui Luo ◽

Liang Liu ◽

...

Keyword(s):

Climate Change ◽

Machine Learning ◽

Spatial Variability ◽

Soil Carbon ◽

Tibet Plateau ◽

Learning Approach ◽

Carbon Turnover ◽

Machine Learning Approach ◽

Qinghai Tibet Plateau ◽

Soil Carbon Turnover

Soil carbon isotopes (&#948;13C) provide reliable insights at the long-term scale for the study of soil carbon turnover and topsoil &#948;13C could well reflect organic matter input from the current vegetation. Qinghai-Tibet Plateau (QTP) is called &#8220;the third pole of the earth&#8221; because of its high elevation, and it is one of the most sensitive and critical regions to global climate change worldwide. Previous studies focused on variability of soil &#948;13C at in-site scale. However, a knowledge gap still exists in the spatial pattern of topsoil &#948;13C in QTP. In this study, we first established a database of topsoil &#948;13C with 396 observations from published literature and applied a Random Forest (RF) algorithm (a machine learning approach) to predict the spatial pattern of topsoil &#948;13C using environmental variables. Results showed that topsoil &#948;13C significantly varied across different ecosystem types (p < 0.05).&#160; Topsoil &#948;13C was -26.3 &#177; 1.60 &#8240; for forest, 24.3 &#177; 2.00 &#8240; for shrubland, -23.9 &#177; 1.84 &#8240; for grassland, -18.9 &#177; 2.37 &#8240; for desert, respectively. RF could well predict the spatial variability of topsoil &#948;13C with a model efficiency (pseudo R2) of 0.65 and root mean square error of 1.42. The gridded product of topsoil &#948;13C and topsoil &#946; (indicating the decomposition rate of soil organic carbon, calculated by &#948;13C divided by logarithmically converted SOC) with a spatial resolution of 1000 m were developed. Strong spatial variability of topsoil &#948;13C was observed, which increased gradually from the southeast to the northwest in QTP. Furthermore, a large variation was found in &#946;, ranging from -7.87 to -81.8, with a decreasing trend from southeast to northwest, indicating that carbon turnover rate was faster in northwest QTP compared to that of southeast. This study was the first attempt to develop a fine resolution product of topsoil &#948;13C for QTP using a machine learning approach, which could provide an independent benchmark for biogeochemical models to study soil carbon turnover and terrestrial carbon-climate feedbacks under ongoing climate change.

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Projected Changes in Permafrost Active Layer Thickness Over the Qinghai‐Tibet Plateau Under Climate Change

Water Resources Research ◽

10.1029/2019wr024969 ◽

2019 ◽

Vol 55 (9) ◽

pp. 7860-7875 ◽

Cited By ~ 3

Author(s):

Dongsheng Zhao ◽

Shaohong Wu

Keyword(s):

Climate Change ◽

Layer Thickness ◽

Active Layer ◽

Tibet Plateau ◽

Active Layer Thickness ◽

Projected Changes ◽

Qinghai Tibet Plateau

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The Impacts of Human Activities on Ecosystems within China’s Nature Reserves

Sustainability ◽

10.3390/su11236629 ◽

2019 ◽

Vol 11 (23) ◽

pp. 6629

Author(s):

Ping Zhu ◽

Wei Cao ◽

Lin Huang ◽

Tong Xiao ◽

Jun Zhai

Keyword(s):

Climate Change ◽

Human Activities ◽

Arid Zone ◽

Ecosystem Dynamics ◽

Tibet Plateau ◽

Warm Temperate Zone ◽

Nighttime Light ◽

Qinghai Tibet Plateau ◽

Warm Temperate ◽

Semi Arid

Protected areas (PAs) provide refuges for threatened species and are considered to be the most important approach to biodiversity conservation. Besides climate change, increasing human population is the biggest threat to biodiversity and habitats in PAs. In this paper, the temporal and spatial variations of land cover changes (LCC), vegetation fraction (VFC), and net primary productivity (NPP) were studied to present the ecosystem dynamics of habitats in 6 different types of national nature reserves (NNRs) in 8 climate zones in China. Furthermore, we used Defense Meteorological Satellite Program/Operational Linescan System (DMSP/OLS) nighttime light datasets and the human disturbance (HD) index estimated from LCC to quantify the living and developing human pressures within the NNRs in the period 2000–2013. The results showed that (1) the living human activities of NNRs increased apparently in the humid warm-temperate zone, Qinghai-Tibet Plateau, mid-temperate semi-arid zone, and mid-temperate humid zone, with the highest increase of nighttime light observed in inland wetlands; (2) the developing human activities in NNRs indicated by the HD index were higher in the humid warm-temperate zone and mid-temperate semi-arid zone as a result of increasing areas of agricultural and built activities, and lower in the sub-tropics due to improved conservation of forest ecosystems; (3) the relationship between HD and VFC suggests that ecosystems in most NNRs of south-subtropics, mid-temperate arid zone and Qinghai-Tibet Plateau were predominantly impacted by climate change. However, HDs were the prevalent factor of ecosystem dynamics in most NNRs of north-subtropics, mid-temperate semi-arid and humid zones.

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