China’s meadow grasslands: challenges and opportunities

Li, Linghao; Xin, Xiaoping; Tang, Huajun; Hou, Lianping

doi:10.1007/s11104-022-05403-7

Cited by 5 publications

(2 citation statements)

References 24 publications

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“…The livestock numbers surged under the loose restrictions on livestock inventories. As a result, there was an alarming degradation of grassland nationwide until the national campaign of livestock exclusion from grasslands commenced in the early 2000s [47]. A large number of herder families have been moving from the Three Rivers Source Region to centralized resettlement areas and urbanization was continuously promoted (see IS area time series in Figure 10).…”

Section: Grassland Transitions In Qinghaimentioning

confidence: 99%

Classification and Transition of Grassland in Qinghai, China, from 1986 to 2020 with Landsat Archives on Google Earth Engine

He,

Shi,

Ding

et al. 2023

Land

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The lack of long-duration, high-frequency grassland classification products limits further understanding of the grasslands’ long-term succession. This study first explored the annual mapping of grassland with fourteen categories at 30 m in Qinghai, China, from 1986 to 2020 based on Google Earth Engine (GEE) and the Integrated Orderly Classification System (IOCSG). Specifically, we proposed an image composite strategy to obtain annual source images for classification, by quarterly compositing multi-sensor and multi-temporal Landsat surface reflectance images. Subsequently, the 35-year area time series of each category was analyzed in terms of trend, degree of change, and succession of each category. The results indicate that the different grasslands of the IOCSG can be effectively differentiated by utilizing the designed feature bands of remote sensing data. Additionally, the proposed annual image composition strategy can not only decrease the invalid pixels but also promote classification accuracy. The grasslands transition analysis from 1986 to 2020 implies the progressive urbanization, warming, and wetting trend in Qinghai. The generated 35-year annual grassland thematic data in Qinghai can serve as an elementary dataset for further regional ecological and climate change studies. The proposed methodology of large-scale grassland classification can also be referenced to other applications like land use/cover mapping and ecological resource monitoring.

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Section: Grassland Transitions In Qinghaimentioning

confidence: 99%

Classification and Transition of Grassland in Qinghai, China, from 1986 to 2020 with Landsat Archives on Google Earth Engine

He,

Shi,

Ding

et al. 2023

Land

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“…Provisioning services are closely related to the Land 2023, 12, 1079 2 of 21 subsistence of pastoral people, among which forage production is one of the most important because grazing activities largely rely on the forage provided by grasslands [5][6][7]. However, it has been reported that China's grasslands have undergone marked degradation in recent years [8], threatening the sustainable supply of forage and challenging the sustainability of pastoral regions [9]. One of the most intuitive manifestations is the imbalance between forage supply and demand.…”

Section: Introductionmentioning

confidence: 99%

Forage Supply–Demand Assessment and Influencing Factor Analysis from the Perspective of Socio-Ecological System: A Case Study of Altay Prefecture, China

Yang

Nan

et al. 2023

Land

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The provision and utilization of grassland resources connect grassland ecosystems and pastoral society. Revealing the mechanism behind the forage supply–demand relationship and balancing forage supply and demand is essential in pastoral socio-ecological systems. Taking Altay Prefecture as the case study, this study quantified the dynamics of natural forage supply, artificial supplemental forage, and forage demand. The ratio of forage supply to demand was calculated in the traditional grazing scenario and the grazing prohibition and supplemental feeding scenario. The results showed that during 2001–2018, the forage supplied by natural grasslands fluctuated, with the highest and lowest values in 2013 and 2008, respectively. The artificial supplemental forage increased at a higher rate in 2011–2018 than in 2001–2010. The overall trend of forage demand was upward, at approximately 2.98 × 104 t/a. The ratio of forage supply to demand decreased in the traditional scenario with an average value of 0.4717 and increased in the grazing prohibition and supplemental feeding scenario with an average value of 0.8289. The influencing factors were analyzed from the perspective of the interactions between the socio-ecological system elements, and the forage supply–demand relationships were conceptualized based on the social–ecological system framework. This study concludes that natural grasslands cannot entirely meet the increasing forage demand without artificial supplemental forage. The increasing artificial supplemental forage has promoted a balance between forage supply and demand, indicating an optimized grassland utilization pattern. The factors that affect forage supply–demand relationships are interrelated, and a holistic perspective should be adopted when implementing management measures.

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Transformation of regional vegetation driven by climate change during the last deglacial–early Holocene at Chaohu Lake, eastern China: New pollen insights

Han,

Shu,

et al. 2024

Review of Palaeobotany and Palynology

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China’s meadow grasslands: challenges and opportunities

Cited by 5 publications

References 24 publications

Classification and Transition of Grassland in Qinghai, China, from 1986 to 2020 with Landsat Archives on Google Earth Engine

Classification and Transition of Grassland in Qinghai, China, from 1986 to 2020 with Landsat Archives on Google Earth Engine

Forage Supply–Demand Assessment and Influencing Factor Analysis from the Perspective of Socio-Ecological System: A Case Study of Altay Prefecture, China

Transformation of regional vegetation driven by climate change during the last deglacial–early Holocene at Chaohu Lake, eastern China: New pollen insights

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