Dataset Information

Grassland ecosystem responses to climate change and human activities within the Three-River Headwaters region of China.

ABSTRACT: The Three-River Headwaters region (TRHR) of China is an important part of the Qinghai-Tibetan Plateau. Although the TRHR is rich in grassland resources, the ecosystem of this area is extremely fragile. Natural and artificial interference have been key to the development of grassland ecosystem spatiotemporal heterogeneity, although the intensity and mode of their influence on ecological processes varies depending on scale; analyses in this area are therefore also scale-dependent. We use multi-scale nested data to analyze the mechanisms underlying the influence of climate change and human activities on grassland net primary productivity (NPP) by applying a multi-level modeling approach. The results of this study show that: (1) The annual grassland NPP of the TRHR has risen in a wavelike pattern over time, increasing by 39.88% overall; (2) Differences of 54.9% and 41.1% in temporal grassland NPP can be attributed to variations between these watersheds as well as county characteristics, and; (3) Although the 'warm and moist' climate trend seen over the course of this study has proved beneficial in enhancing grassland NPP, the rate of increase has tended to be faster in relatively dry and warm regions. Economic development and population growth have both exerted negative impacts on grassland NPP.

SUBMITTER: Han Z

PROVIDER: S-EPMC5998084 | biostudies-literature | 2018 Jun

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Grassland ecosystem responses to climate change and human activities within the Three-River Headwaters region of China.

Han Ze Z Song Wei W Deng Xiangzheng X Xu Xinliang X

Scientific reports 20180613 1

The Three-River Headwaters region (TRHR) of China is an important part of the Qinghai-Tibetan Plateau. Although the TRHR is rich in grassland resources, the ecosystem of this area is extremely fragile. Natural and artificial interference have been key to the development of grassland ecosystem spatiotemporal heterogeneity, although the intensity and mode of their influence on ecological processes varies depending on scale; analyses in this area are therefore also scale-dependent. We use multi-sca ...[more]

PMID: 29899341

Similar Datasets

Project description:Grassland degradation has emerged as a serious socio-economic and ecological problem, endangering both long-term usage and the regional biogeochemical cycle. Climate change and human activities are the two leading factors leading to grassland degradation. However, it is unclear what the degradation level caused by these two factors is. Using the normalized difference vegetation index (NDVI) and coefficient of variation of NDVI (CVNDVI), the spatial distribution features of grassland degradation or restoration were analyzed in Qilian County in the northeast of the Qinghai-Tibet Plateau. The dominant climate variables affecting NDVI variation were selected through the combination of random forest model and stepwise regression method to improve the residual trend analysis, and on this basis, twelve possible scenarios were established to evaluate the driving factors of different degraded grasslands. Finally, used the Hurst index to forecast the trend of grassland degradation or restoration. The results showed that approximately 55.0% of the grassland had been degraded between 2000 and 2019, and the area of slight degradation (NDVIslope > 0; CVNDVI (slope) > 0; NDVIvalue > 0.2) accounted for 48.6%. These regions were centered in the northwest of Qilian County. Climate and human activities had a joint impact on grassland restoration or degradation. Human activities played a leading role in grassland restoration, while climate change was primarily a driver of grassland degradation. The regions with slight degradation or re-growing (NDVIslope > 0; CVNDVI (slope) > 0), moderate degradation (NDVIslope < 0; CVNDVI (slope) > 0), and severe degradation or desertification (NDVIslope < 0; CVNDVI (slope) < 0) were dominated by the joint effects of climate and anthropogenic activity accounted for 34.3%, 3.3%, and 1.3%, respectively, of the total grassland area. Grasslands in most areas of Qilian County are forecasted to continue to degrade, including the previously degraded areas, with continuous degradation areas accounting for 54.78%. Accurately identifying the driving factors of different degraded grassland and predicting the dynamic change trend of grassland in the future is the key to understand the mechanism of grassland degradation and prevent grassland degradation. The findings offer a reference for accurately identifying the driving forces in grassland degradation, as well as providing a scientific basis for the policy-making of grassland ecological management.

Project description:BackgroundQuantitative evaluations of the relative impacts of climate change and anthropogenic activity on grasslands are significant for understanding grassland degradation mechanisms and controlling degraded grasslands. However, our knowledge about the effects of anthropogenic activities and climate change on the grassland in a mountain basin system in arid regions of Central Asia is still subject to great uncertainties.MethodsIn this research, we have chosen the net primary productivity (NPP) as an index for revealing grassland dynamics processes. Moreover, the human appropriation of net primary production (NPPH), which was calculated as the potential NPP (NPPP) minus the actual NPP (NPPA), was applied to distinguish the relative influences of climate change and human activities on the grassland NPP variations in a mountain basin system of Central Asia from 2001-2015.ResultsThe results indicated that the grassland NPPA showed an increasing trend (35.88%) that was smaller than the decreasing trend (64.12%). The respective contributions of human activity, climate change and the two together to the increase in the NPPA were 6.19%, 81.30% and 12.51%, respectively. Human activity was largely responsible for the decrease in the grassland NPPA, with the area experiencing human-induced decreases accounting for 98.21% of the total decreased area, which mainly occurred during spring/autumn pasture and winter pasture. Furthermore, the average grazing pressure index (GPI) values of summer pastures, spring/autumn pasture and winter pastures were 1.04, 3.03 and 1.83, respectively, from 2001-2015. In addition, negative correlations between the NPP and GPI occupied most of the research area (92.41%).DiscussionOur results indicate that: (i) anthropogenic activities were the primary cause of the reduction in the grassland NPP, especially grazing activities. (ii) For areas where the grassland NPP has increased, precipitation was the dominant climatic factor over temperature in controlling the grassland NPP changes in the study area. (iii) The findings of the current research indicate that some measures should be taken to reduce livestock pressure, and artificial grasslands can be built along the Irtysh River and the Ulungur River to relieve grazing pressure on spring/autumn pastures and winter pastures. Our results could provide reliable information for grassland management and the prevention of grassland degradation in arid regions of Central Asia.

Dataset Information

Grassland ecosystem responses to climate change and human activities within the Three-River Headwaters region of China.

Publications

Grassland ecosystem responses to climate change and human activities within the Three-River Headwaters region of China.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets