Author
Listed:
- Fan Yang
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Quanqin Shao
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
- Xingjian Guo
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Yuzhi Tang
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
University of Chinese Academy of Sciences, Beijing 100049, China)
- Yuzhe Li
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
- Dongliang Wang
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
- Yangchun Wang
(Institute of Mountain Hazards and Environment, Chinese Academy of Sciences, Chengdu 610041, China)
- Jiangwen Fan
(Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)
Abstract
Unmanned aerial vehicle surveys were conducted in the summer season of 2016 and the winter season of 2017 to investigate the large wild herbivore population, including kiangs, Tibetan gazelles and bharals, in Madoi County; the source region of the Yellow River. The study generated forage grass production data in 30 m spatial resolution in Madoi County in 2016 using a downscaling algorithm; estimated a forage-livestock balance including wild animals and domestic animals; and analyzed the effect of the large wild herbivore population on the balance between forage grass and herbivory in Madoi County. The large wild herbivore population was estimated based on the density of the animals in the survey sample strip and compared and verified with available statistical data and the two survey results from the summer season of 2016 and winter season of 2017. The results showed that: (1) in the winter season of 2017, the populations of kiang, Tibetan gazelle and bharal were 17,100, 16,000 and 9300, respectively, while the populations of domestic yak, Tibetan sheep and horse were 70,800, 102,200 and 1200, respectively. The total population of large wild herbivores and domestic animals was 475,000 (sheep units). The ratio (in sheep units) between large wild herbivores and domestic animals was 1:4.5; (2) When only considering domestic animals, the grazing pressure index was 1.13, indicating slight overloading of the grassland. When considering domestic animals and large wild herbivores (kiang, Tibetan gazelle and bharal), the grazing pressure index was 1.38, suggesting moderate overloading of the grassland; (3) If large wild herbivores are not taken into consideration when the forage-livestock balance is calculated, the grazing pressure will be under-estimated by 22%. Overgrazing is the major cause of grassland degradation in Madoi County. An additional 79,000 tons of hay or a 30% reduction in domestic animals is required to maintain a forage-livestock balance in Madoi County.
Suggested Citation
Fan Yang & Quanqin Shao & Xingjian Guo & Yuzhi Tang & Yuzhe Li & Dongliang Wang & Yangchun Wang & Jiangwen Fan, 2018.
"Effect of Large Wild Herbivore Populations on the Forage-Livestock Balance in the Source Region of the Yellow River,"
Sustainability, MDPI, vol. 10(2), pages 1-18, January.
Handle:
RePEc:gam:jsusta:v:10:y:2018:i:2:p:340-:d:129179
Download full text from publisher
Citations
Citations are extracted by the
CitEc Project, subscribe to its
RSS feed for this item.
Cited by:
- Yaowen Kou & Quanzhi Yuan & Xiangshou Dong & Shujun Li & Wei Deng & Ping Ren, 2023.
"Dynamic Response and Adaptation of Grassland Ecosystems in the Three-River Headwaters Region under Changing Environment: A Review,"
IJERPH, MDPI, vol. 20(5), pages 1-30, February.
- Fan Yang & Quanqin Shao & Zhigang Jiang, 2019.
"A Population Census of Large Herbivores Based on UAV and Its Effects on Grazing Pressure in the Yellow-River-Source National Park, China,"
IJERPH, MDPI, vol. 16(22), pages 1-20, November.
- Yaxian Zhang & Jiangwen Fan & Suizi Wang, 2020.
"Assessment of Ecological Carrying Capacity and Ecological Security in China’s Typical Eco-Engineering Areas,"
Sustainability, MDPI, vol. 12(9), pages 1-17, May.
- Andrew Rule & Sarah-Eve Dill & Gordy Sun & Aidan Chen & Senan Khawaja & Ingrid Li & Vincent Zhang & Scott Rozelle, 2022.
"Challenges and Opportunities in Aligning Conservation with Development in China’s National Parks: A Narrative Literature Review,"
IJERPH, MDPI, vol. 19(19), pages 1-24, October.
- Gao, Hongmei & Jiang, Feng & Chi, Xiangwen & Li, Guangying & Cai, Zhenyuan & Qin, Wen & Zhang, Jingjie & Wu, Tong & Zhang, Tongzuo, 2020.
"The carrying pressure of livestock is higher than that of large wild herbivores in Yellow River source area, China,"
Ecological Modelling, Elsevier, vol. 431(C).
- Hui Liu & Xiaoyu Song & Lin Qin & Wang Wen & Xiaodi Liu & Zhiqiang Hu & Yu Liu, 2020.
"Improvement and Application of Key Pasture Theory for the Evaluation of Forage–Livestock Balance in the Seasonal Grazing Regions of China’s Alpine Desert Grasslands,"
Sustainability, MDPI, vol. 12(17), pages 1-12, August.
Corrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:10:y:2018:i:2:p:340-:d:129179. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
We have no bibliographic references for this item. You can help adding them by using this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .
Please note that corrections may take a couple of weeks to filter through
the various RePEc services.