The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau

Chen, Baoxiong; Zhang, Xianzhou; Tao, Jian; Wu, Jianshuang; Wang, Jingsheng; Shi, Peili; Zhang, Yangjian; Yu, Chengqun

doi:10.1016/j.agrformet.2014.01.002

Cited by 560 publications

(353 citation statements)

References 56 publications

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“…might explain variability in grassland biomass production (Kawamura et al, 2005;Mokany et al, 2006;Blanco et al, 2014;Carilla et al, 2011;Valone and Kelt, 1999). Chen et al (2014) referred that human activities on Chinese alpine grassland significantly intensified in [2001][2002][2003][2004][2005].…”

Section: Spatial Distribution Of Grassland Biomass and Relative Uncermentioning

confidence: 99%

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Jia

Liu

Yang

et al. 2016

Ecological Indicators

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a b s t r a c tAccurate estimation of grassland biomass and its dynamics are crucial not only for the biogeochemical dynamics of terrestrial ecosystems, but also for the sustainable use of grassland resources. However, estimations of grassland biomass on large spatial scale usually suffer from large variability and mostly lack quantitative uncertainty analyses. In this study, the spatial grassland biomass estimation and its uncertainty were assessed based on 265 field measurements and remote sensing data across Northern China during [2001][2002][2003][2004][2005]. Potential sources of uncertainty, including remote sensing data sources (DATsrc), model forms (MODfrm) and model parameters (biomass allocation, BMallo, e.g. root:shoot ratio), were determined and their relative contribution was quantified. The results showed that the annual grassland biomass in Northern China was 1268.37 ± 180.84 Tg (i.e., 532.02 ± 99.71 g/m 2 ) during 2001-2005, increasing from western to eastern area, with a mean relative uncertainty of 19.8%. There were distinguishable differences among the uncertainty contributions of three sources (BMallo > DATsrc > MODfrm), which contributed 52%, 27% and 13%, respectively. This study highlighted the need to concern the uncertainty in grassland biomass estimation, especially for the uncertainty related to BMallo.

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Section: Spatial Distribution Of Grassland Biomass and Relative Uncermentioning

confidence: 99%

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Jia

Liu

Yang

et al. 2016

Ecological Indicators

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“…The Tibetan-inhabited regions are usually located in the areas adjacent to nature reserves; some important economic development regions, such as county towns, are also distributed within nature reserves. This also means that grazing activity has affected the nature reserves in different ways and has affected their function (Glindermann et al, 2009;Chen et al, 2014).…”

Section: Discussionmentioning

confidence: 99%

Assessment of effectiveness of nature reserves on the Tibetan Plateau based on net primary production and the large sample comparison method

Zhang

et al. 2016

J. Geogr. Sci.

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Twenty-one typical coupled large samples were chosen from areas within and surrounding nature reserves on the Tibetan Plateau using the large sample comparison method (LSCM). To evaluate the effectiveness of the nature reserves in protecting the ecological environment, the alpine grassland net primary production (NPP) of these coupled samples were compared and the differences between them before and after their establishment as protected areas were analyzed. The results showed that: (1) With respect to the alpine grassland NPP, the ecological and environmental conditions of most nature reserves were more fragile than those of the surrounding areas and also lower than the average values for the Tibetan Plateau. (2) Of the 11 typical nature reserves selected, the positive trend in the NPP for Manzetang was the most significant, whereas there was no obvious trend in Taxkorgan. With the exception of Selincuo, the annual NPP growth rate in the nature reserves covered by alpine meadow and wetland was higher than that in nature reserves consisting of alpine steppe and alpine desert. (3) There were notable findings in 21 typical coupled samples: (a) After the establishment of the nature reserves, the annual rate of increase in the NPP in 76% of samples inside nature reserves and 82% of samples inside national nature reserves was higher than that of the corresponding samples outside nature reserves. (b) The effectiveness of ecological protection of the Mid-Kunlun, Changshagongma, Zoige and Selincuo (Selin Co) nature reserves was significant; the effectiveness of protection was relatively sig-28 Journal of Geographical Sciences nificant in most parts of the Sanjiangyuan and Qiangtang nature reserves, whereas in south-east Manzetang and north Taxkorgan the protection effectiveness was not obvious. (c) The ecological protection effectiveness was significant in nature reserves consisting of alpine meadow, but was weak in nature reserves covered by alpine steppe. This study also shows that the advantage of large sample comparison method in evaluating regional ecology change. Careful design of the samples used, to ensure comparability between the samples, is crucial to the success of this LSCM.

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“…Additionally, different vegetation types may require different temperature thresholds to trigger the start of the growing season. Vegetation in cold environments require lower threshold temperature than that in warm conditions [53,54].…”

Section: Discussionmentioning

confidence: 99%

Evaluating Vegetation Growing Season Changes in Northeastern China by Using GIMMS LAI3g Data

Xie

Zhou

et al. 2017

Climate

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Accurate understanding and detecting of vegetation growth change is essential for providing suitable management strategies for ecosystems. Several studies using satellite based vegetation indices have demonstrated changes of vegetation growth and phenology. Temperature is considered a major determinant of vegetation phenology. To accurately detect the response of vegetation to climate variations, this study investigated the vegetation phenology in the northeast (NE) region of China by using in-situ temperature observations and satellite-based leaf area index estimates (LAI3g) for the period 1982-2011. Firstly, a spatial distribution of the averaged phenology over the 30 years was obtained. This distribution showed that a tendency for an early start of the growing season (SoS) and late end of the growing season (EoS) was observed towards of the southeastern part of NE China, with the late SoS and early EoS occurring at higher latitudes. Secondly, the temperature-based and satellite-based phenological trends were analyzed. Then the significant advanced trend (SAT), significant delayed trend (SDT), and nonsignificant trend (NT) of SOS and EOS in NE region of China were detected by using the Mann-Kendall trend test approach. Finally, changes in phenological trends were investigated by using the temperature-based and satellite-based phenology method. A comparison of the phenological trend shows that there are some significant advanced trends of SOS and significant delayed trends of EOS in the NE region of China over 30 years. The results of this study can provide important support of the view that a lengthening of growing season duration occurred at the northern high latitudes in recent decades.

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The impact of climate change and anthropogenic activities on alpine grassland over the Qinghai-Tibet Plateau

Cited by 560 publications

References 56 publications

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Estimation and uncertainty analyses of grassland biomass in Northern China: Comparison of multiple remote sensing data sources and modeling approaches

Assessment of effectiveness of nature reserves on the Tibetan Plateau based on net primary production and the large sample comparison method

Evaluating Vegetation Growing Season Changes in Northeastern China by Using GIMMS LAI3g Data

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