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International journal of environmental research and public health2019; 16(22); 4402; doi: 10.3390/ijerph16224402

A Population Census of Large Herbivores Based on UAV and Its Effects on Grazing Pressure in the Yellow-River-Source National Park, China.

Abstract: Using the Yellow-River-Source National Park (YRSNP) as a study site, an unmanned aerial vehicle (UAV) remote sensing and line transect method was used to investigate the number of wild herbivorous animals and livestock, including the kiang () and Tibetan gazelle (). A downscaling algorithm was used to generate the forage yield data in YRSNP based on a 30-m spatial resolution. On this basis, we estimated the forage-livestock balance, which included both wild animals and livestock, and analyzed the effects of functional zone planning in national parks on the forage-livestock balance in YRSNP. The results showed that the estimates of large herbivore population numbers in YRSNP based on population density in the aerial sample strips, which were compared and validated with official statistics and warm season survey results, indicated that the numbers of kiangs and Tibetan gazelles in the 2017 cold season were 12,900 and 12,100, respectively. The numbers of domestic yaks, Tibetan sheep, and horses were 53,400, 76,800, and 800, respectively, and the total number of sheep units was 353,200. The ratio of large wild herbivores and livestock sheep units was 1:5. Large wild herbivores have different preferences for functional zones, preferring ecological restoration areas consisting mainly of sparse grassland. The grazing pressure indices of the core reserve areas and ecological restoration areas were 0.168 and 0.276, respectively, indicating that these two regions still have high grazing potential. However, the grazing pressure index of the traditional utilization areas was 1.754, indicating that these grasslands are severely overloaded. After the planning and implementation of functional zones, the grazing pressure index of YRSNP was 1.967. Under this measure, the number of livestock was not reduced and the grazing pressure nearly doubled, indicating that forage-livestock conflict has become more severe in YRSNP.
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Publication Date: 2019-11-11 PubMed ID: 31717940PubMed Central: PMC6888295DOI: 10.3390/ijerph16224402Google Scholar: Lookup
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Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research study utilized unmanned aerial vehicles (UAV) to conduct a census of large herbivores in Yellow-River-Source National Park (YRSNP), China. The study explored the effects of this population on grazing pressure and determined the grazing capacity of different zones within the park.

Methodology

The research involved several significant methods and procedures:

  • An unmanned aerial vehicle (UAV) equipped for remote sensing was used for surveying animal populations. A line transect method was also employed for counting the number of wild herbivorous animals and livestock in YRSNP.
  • A downscaling algorithm was used to produce forage yield data based on a 30-m spatial resolution. This data was essential in estimating the forage-livestock balance.
  • Population density estimates were derived from aerial surveys. These estimates were validated using official statistics and warm season survey results.
  • Finally, a grazing pressure index was calculated for different functional zones within the park. The team evaluated these zones’ grazing potential and the effect of zone planning on forage-livestock balance.

Findings

The research yielded several significant findings:

  • In the cold season of 2017, the population count showed 12,900 kiangs and 12,100 Tibetan gazelles. There were 53,400 yaks, 76,800 Tibetan sheep, and 800 horses, yielding a total of 353,200 sheep units.
  • The ratio of large wild herbivores to livestock sheep units was found to be 1:5, confirming that livestock numbers exceed that of wild herbivorous animals significantly.
  • The study found that large wild herbivores preferred ecological restoration areas, containing primarily sparse grassland.
  • Grazing pressure indices were calculated for different zones. The core reserve areas and ecological restoration areas had pressure indices of 0.168 and 0.276 respectively, indicating high grazing potential. However, traditional utilization areas had a pressure index of 1.754, signaling severe overgrazing.
  • Another important outcome of the study was that even with the implementation of functional zones, the grazing pressure index rose to 1.967 due to a lack of reduction in livestock numbers. This increase suggests a worsening forage-livestock conflict in YRSNP.

Implications

From a conservation perspective, these findings point towards the urgent need to regulate livestock numbers within the park to ensure a balanced forage-livestock relationship. Greater emphasis should also be placed on restoring and preserving areas with high grazing potential. The use of UAV technology in wildlife census and observing grazing patterns also offers a promising approach for sustainable wildlife management.

Cite This Article

APA
Yang F, Shao Q, Jiang Z. (2019). A Population Census of Large Herbivores Based on UAV and Its Effects on Grazing Pressure in the Yellow-River-Source National Park, China. Int J Environ Res Public Health, 16(22), 4402. https://doi.org/10.3390/ijerph16224402

Publication

International journal of environmental research and public health
ISSN: 1660-4601
NlmUniqueID: 101238455
Country: Switzerland
Language: English
Volume: 16
Issue: 22
PII: 4402

Researcher Affiliations

Yang, Fan
  • School of Economics and Management, Zhejiang Ocean University, Zhoushan, 316022, China.
  • Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Shao, Quanqin
  • Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing, 100101, China.
Jiang, Zhigang
  • Institute of Zoology, Chinese Academy of Sciences, Beijing, 100101, China.

MeSH Terms

  • Animals
  • Cattle
  • Censuses
  • China
  • Grassland
  • Herbivory
  • Horses
  • Livestock
  • Parks, Recreational
  • Population Density
  • Remote Sensing Technology
  • Rivers
  • Seasons
  • Sheep

Conflict of Interest Statement

The authors declare no conflict of interest.

References

This article includes 56 references
  1. Liu J, Xu X, Shao Q. Grassland degradation in the “Three-River Headwaters” region, Qinghai Province.. Acta Geogr. Sin. 2008;18:259–273.
    doi: 10.1007/s11442-008-0259-2google scholar: lookup
  2. Jiang Z. On classification of protected areas and the construction of China’s Protected Area System with national parks as a leading part.. Biodivers. Sci. 2018;26:775–779.
    doi: 10.17520/biods.2018168google scholar: lookup
  3. Qiao H, Wang X, Wang W, Luo Z, Tang K, Huang Y, Yang S, Cao W, Zhao X, Jiang J. From nature reserve to national park system pilot: Changes of environmental coverage in the Three-River-Source National Park and implications for amphibian and reptile conservation.. Biodivers. Sci. 2018;26:202–209.
    doi: 10.17520/biods.2017305google scholar: lookup
  4. Bruner AG, Gullison RE, Rice RE, da Fonseca GA. Effectiveness of parks in protecting tropical biodiversity.. Science 2001 Jan 5;291(5501):125-8.
    doi: 10.1126/science.291.5501.125pubmed: 11141563google scholar: lookup
  5. Xu W, Xiao Y, Zhang J, Yang W, Zhang L, Hull V, Wang Z, Zheng H, Liu J, Polasky S, Jiang L, Xiao Y, Shi X, Rao E, Lu F, Wang X, Daily GC, Ouyang Z. Strengthening protected areas for biodiversity and ecosystem services in China.. Proc Natl Acad Sci U S A 2017 Feb 14;114(7):1601-1606.
    doi: 10.1073/pnas.1620503114pmc: PMC5321011pubmed: 28137858google scholar: lookup
  6. Chen H, Zhu Q, Peng C, Wu N, Wang Y, Fang X, Gao Y, Zhu D, Yang G, Tian J, Kang X, Piao S, Ouyang H, Xiang W, Luo Z, Jiang H, Song X, Zhang Y, Yu G, Zhao X, Gong P, Yao T, Wu J. The impacts of climate change and human activities on biogeochemical cycles on the Qinghai-Tibetan Plateau.. Glob Chang Biol 2013 Oct;19(10):2940-55.
    doi: 10.1111/gcb.12277pubmed: 23744573google scholar: lookup
  7. Li X, Gao J, Brierley G, Qiao Y, Zhang J, Yang Y. Rangeland degradation on the Qinghai-Tibet plateau: Implications for rehabilitation.. Land Degrad. Dev. 2013;24:72–80.
    doi: 10.1002/ldr.1108google scholar: lookup
  8. Shao Q, Cao W, Fan J, Huang L, Xu X. Effects of an ecological conservation and restoration project in the Three-River Source Region, China.. Acta Geogr. Sin. 2017;27:183–204.
    doi: 10.1007/s11442-017-1371-ygoogle scholar: lookup
  9. Zhang L, Fan J, Zhou D, Zhang H. Ecological protection and restoration program reduced grazing pressure in the Three-River Headwaters Region, China.. Rangel. Ecol. Manag. 2017;70:540–548.
    doi: 10.1016/j.rama.2017.05.001google scholar: lookup
  10. Betts M, Mitchell D, Dlamond A, Bety J. Uneven rates of landscape change as a source of bias in roadside wildlife surveys.. J. Wildl. Manag. 2007;71:2266–2273.
    doi: 10.2193/2006-004google scholar: lookup
  11. Sibanda M, Murwira A. Cotton fields drive elephant habitat fragmentation in the Mid Zambezi Valley, Zimbabwe.. Int. J. Appl. Earth Obs. 2012;19:286–297.
    doi: 10.1016/j.jag.2012.05.014google scholar: lookup
  12. Guo Q, Wu F, Hu T, Chen L, Liu J, Zhao X, Gao S, Pang S. Perspectives and prospects of unmanned aerial vehicles in remote sensing monitoring of biodiversity.. Biodivers. Sci. 2016;24:1267–1278.
    doi: 10.17520/biods.2016105google scholar: lookup
  13. Carr NL, Rodgers AR, Kingston SR, Hettinga PN, Thompson LM, Renton JL, Wilson PJ. Comparative woodland caribou population surveys in Slate Islands Provincial Park, Ontario.. Rangifer. 2012;23:321–329.
    doi: 10.7557/2.32.2.2270google scholar: lookup
  14. Vermeulen C, Lejeune P, Lisein J, Sawadogo P, Bouché P. Unmanned aerial survey of elephants.. PLoS One 2013;8(2):e54700.
    doi: 10.1371/journal.pone.0054700pmc: PMC3566131pubmed: 23405088google scholar: lookup
  15. Mulero-Pázmány M, Stolper R, van Essen LD, Negro JJ, Sassen T. Remotely piloted aircraft systems as a rhinoceros anti-poaching tool in Africa.. PLoS One 2014;9(1):e83873.
    doi: 10.1371/journal.pone.0083873pmc: PMC3885534pubmed: 24416177google scholar: lookup
  16. Ditmer MA, Vincent JB, Werden LK, Tanner JC, Laske TG, Iaizzo PA, Garshelis DL, Fieberg JR. Bears Show a Physiological but Limited Behavioral Response to Unmanned Aerial Vehicles.. Curr Biol 2015 Aug 31;25(17):2278-83.
    doi: 10.1016/j.cub.2015.07.024pubmed: 26279232google scholar: lookup
  17. Gonzalez LF, Montes GA, Puig E, Johnson S, Mengersen K, Gaston KJ. Unmanned Aerial Vehicles (UAVs) and Artificial Intelligence Revolutionizing Wildlife Monitoring and Conservation.. Sensors (Basel) 2016 Jan 14;16(1).
    doi: 10.3390/s16010097pmc: PMC4732130pubmed: 26784196google scholar: lookup
  18. Szantoi Z, Smith S, Strona G, Koh L, Wich S. Mapping orangutan habitat and agricultural areas using Landsat OLI imagery augmented with unmanned aircraft system aerial photography.. Int. J. Remote Sens. 2017;38:2231–2245.
    doi: 10.1080/01431161.2017.1280638google scholar: lookup
  19. Brisson-Curadeau É, Bird D, Burke C, Fifield DA, Pace P, Sherley RB, Elliott KH. Seabird species vary in behavioural response to drone census.. Sci Rep 2017 Dec 20;7(1):17884.
    doi: 10.1038/s41598-017-18202-3pmc: PMC5738335pubmed: 29263372google scholar: lookup
  20. Mulero-Pázmány M, Jenni-Eiermann S, Strebel N, Sattler T, Negro JJ, Tablado Z. Unmanned aircraft systems as a new source of disturbance for wildlife: A systematic review.. PLoS One 2017;12(6):e0178448.
    doi: 10.1371/journal.pone.0178448pmc: PMC5479521pubmed: 28636611google scholar: lookup
  21. Behnke RH. Equilibrium and non-equilibrium models of livestock population dynamics in pastoral Africa: Their relevance to Arctic grazing systems.. Rangifer. 1999;20:141–152.
    doi: 10.7557/2.20.2-3.1509google scholar: lookup
  22. Sullivan S, Rohde R. On non-equilibrium in arid and semi-arid grazing systems.. J. Biogeogr. 2002;29:1595–1618.
    doi: 10.1046/j.1365-2699.2002.00799.xgoogle scholar: lookup
  23. Gillson L, Hoffman MT. Ecology. Rangeland ecology in a changing world.. Science 2007 Jan 5;315(5808):53-4.
    doi: 10.1126/science.1136577pubmed: 17204634google scholar: lookup
  24. Xu B, Yang X, Jin Y, Wang D, Yang Z, Li J, Liu H, Yu H, Ma H. Monitoring and evaluation of grassland-livestock balance in pastoral and semi-pastoral counties of China.. Geogr.Res. 2012;31:1998–2006.
  25. Xu M. A review of grassland carrying capacity: Perspective and dilemma for research in China on “forage-livestock balance”.. Acta Pratacult. Sin. 2014;23:321–329.
  26. Qi J, Xin X, John R, Groisman P, Chen J. Understanding livestock production and sustainability of grassland ecosystems in the Asian Dryland Belt.. Ecol. Proc. 2017;6:22.
    doi: 10.1186/s13717-017-0087-3google scholar: lookup
  27. Thapa GB, Paudel GS. Evaluation of the livestock carrying capacity of land resources in the Hills of Nepal based on total digestive nutrient analysis.. Agric. Ecosyst. Environ. 2000;78:223–235.
    doi: 10.1016/S0167-8809(99)00128-0google scholar: lookup
  28. Silori CS, Mishra BK. Assessment of livestock grazing pressure in and around the elephant corridors in Mudumalai Wildlife Sanctuary, South India.. Biodivers. Conserv. 2001;10:2181–2195.
    doi: 10.1023/A:1013285910650google scholar: lookup
  29. Zhang J, Zhang L, Liu W, Qi Y, Wo X. Livestock-carrying capacity and overgrazing status of alpine grassland in the Three-River Headwaters region, China.. Acta Geogr. Sin. 2014;24:303–312.
    doi: 10.1007/s11442-014-1089-zgoogle scholar: lookup
  30. Fan JW, Shao QQ, Liu JY, Wang JB, Harris W, Chen ZQ, Zhong HP, Xu XL, Liu RG. Assessment of effects of climate change and grazing activity on grassland yield in the Three Rivers Headwaters Region of Qinghai-Tibet Plateau, China.. Environ Monit Assess 2010 Nov;170(1-4):571-84.
    doi: 10.1007/s10661-009-1258-1pubmed: 20041346google scholar: lookup
  31. Cai H, Yang X, Xu X. Human-induced grassland degradation/restoration in the central Tibetan Plateau: The effects of ecological protection and restoration projects.. Ecol. Eng. 2015;83:112–119.
    doi: 10.1016/j.ecoleng.2015.06.031google scholar: lookup
  32. Fu M, Tian J, Zhu Y, Tian Y, Zhao Z, Li J. Indentification of functional zones and methods of target management in Sanjiangyuan National Park.. Biodivers. Sci. 2017;25:71–79.
    doi: 10.17520/biods.2016098google scholar: lookup
  33. . Code of Parctice for Terrestrial Wildlife and Its Habitat Survey.. .
  34. Harris R, Burnham K. On estimating wildlife densities from line transect data.. Acta Zool. Sin. 2002;48:812–818.
  35. Joseph L, Bard-Jorgen B. Density of Tibetan antelope, Tibetan wild ass and Tibetan gazelle in relation to human presence across the Chang Tang Nature Reserve of Tibet, China.. Acta Zool. Sin. 2005;51:586–597.
  36. Guo X, Shao Q, Li Y, Wang Y, Wang D, Liu J, Fan J, Yang F. Application of UAV Remote Sensing for a Population Census of Large Wild Herbivores—Taking the Headwater Region of the Yellow River as an Example.. Remote Sens. 2018;10:1041.
    doi: 10.3390/rs10071041google scholar: lookup
  37. Xu B, Yang X, Tao W, Qin Z, Liu H, Miao J, Bi Y. MODIS-based remote sensing monitoring of grass production in China.. Int. J. Remote Sens. 2008;29:5313–5327.
    doi: 10.1080/01431160802036276google scholar: lookup
  38. Zhang Y, Fan J, Cao W, Zhang H. Spatial and temporal dynamics of grassland yield and its response to precipitation in the Three River Headwater Region from 2006 to 2013.. Acta Pratacult. Sin. 2017;26:10–19.
  39. Lechowicz MJ. The sampling characteristics of electivity indices.. Oecologia 1982 Jan;52(1):22-30.
    doi: 10.1007/BF00349007pubmed: 28310104google scholar: lookup
  40. Xin Y, Du T, Xin Y, Wu A, Lu G. The evaluation of carrying capacity of grassland in Qinghai.. Qinghai Pratacult. 2011;20:13–22.
  41. Fan J, Shao Q, Wang J, Chen Z, Zhong H. An analysis of temporal-spatial dynamics of grazing pressure on grassland in Three Rivers Headwater Region.. Chin. J. Grassl. 2011;33:64–72.
  42. . Calculation of Rangeland Carrying Capacity.. .
  43. . A Survey of Terrestrial Wildlife Resources in China.. .
  44. Chen Z, Shao Q, Liu J, Wang J. Analysis of net primary productivity of terrestrial vegetation on the Qinghai-Tibetan Plateau, based on MODIS remote sensing data.. Sci. China Earth Sci. 2012;42:402–410.
  45. Dong S, Wu X, Liu S, Su X, Wu Y, Shi J, Li X, Zhang X, Xu D, Weng J. Estimation of ecological carrying capacity for wild yak, kiang, and Tibetan antelope based on habitat suitability in the Aerjin Mountain Nature Reserve, China.. Acta Ecol. Sin. 2015;35:7598–7607.
  46. Wu Y, Dong S, Zhang X, Liu Y, Shi J, Zhang X, Su X, Wang X, Li Y. Summer habitat selection of the ungulates equus kiang and bos grunniens in Altun Mountain Reserve.. Chin. J. Zool. 2014;49:317–327.
  47. Retzer V, Reudenbach C. Modelling the carrying capacity and coexistence of pika and livestock in the mountain steppe of the South Gobi, Mongolia.. Ecol. Model. 2005;189:89–104.
    doi: 10.1016/j.ecolmodel.2005.03.003google scholar: lookup
  48. Zhang L, Luo Z, Mallon D, Li C, Jiang Z. Biodiversity conservation status in China’s growing protected areas.. Biol. Conserv. 2017;210:89–100.
    doi: 10.1016/j.biocon.2016.05.005google scholar: lookup
  49. Han Z, Song W, Deng X, Xu X. Grassland ecosystem responses to climate change and human activities within the Three-River Headwaters region of China.. Sci Rep 2018 Jun 13;8(1):9079.
    doi: 10.1038/s41598-018-27150-5pmc: PMC5998084pubmed: 29899341google scholar: lookup
  50. Yang F, Shao Q, Guo X, Tang Y, Li Y, Wang D, Wang Y, Fan J. Effect of Large Wild Herbivore Populations on the Forage-Livestock Balance in the Source Region of the Yellow River.. Sustainability. 2018;10:340.
    doi: 10.3390/sဂ0340google scholar: lookup
  51. Hodgson JC, Baylis SM, Mott R, Herrod A, Clarke RH. Precision wildlife monitoring using unmanned aerial vehicles.. Sci Rep 2016 Mar 17;6:22574.
    doi: 10.1038/srep22574pmc: PMC4795075pubmed: 26986721google scholar: lookup
  52. Zhao X, Zhao L, Li Q, Chen H, Zhou H, Xu S, Dong Q, Wu G, He Y. Using balance of seasonal herbage supply and demand to inform sustainable grassland management on the Qinghai–Tibetan Plateau.. Front. Agric. Sci. Eng. 2018;5:1–8.
  53. Wang Y, Wesche K. Vegetation and soil responses to livestock grazing in Central Asian grasslands: A review of Chinese literature.. Biodivers. Conserv. 2016;25:2401–2420.
    doi: 10.1007/s10531-015-1034-1google scholar: lookup
  54. Sloat L, Gerber J, Samberg L, Smith W, Herrero M, Ferreira L, Godde C, West P. Increasing importance of precipitation variability on global livestock grazing lands.. Nat. Clim. Chang. 2018;8:214–218.
    doi: 10.1038/s41558-018-0081-5google scholar: lookup
  55. Antoine S, Steeve D. Resource selection in a high-altitude rangeland equid, the kiang (Equus kiang): Influence of forage abundance and quality at multiple spatial scales.. Can. J. Zool. 2014;92:239–249.
  56. Chetri M, Odden M, Wegge P. Snow Leopard and Himalayan Wolf: Food Habits and Prey Selection in the Central Himalayas, Nepal.. PLoS One 2017;12(2):e0170549.
    pmc: PMC5298268pubmed: 28178279doi: 10.1371/journal.pone.0170549google scholar: lookup

Citations

This article has been cited 2 times.
  1. Kou Y, Yuan Q, Dong X, Li S, Deng W, Ren P. Dynamic Response and Adaptation of Grassland Ecosystems in the Three-River Headwaters Region under Changing Environment: A Review. Int J Environ Res Public Health 2023 Feb 27;20(5).
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  2. Mohammadi A, Almasieh K, Wan HY, Nayeri D, Alambeigi A, Ransom JI, Cushman SA. Integrating spatial analysis and questionnaire survey to better understand human-onager conflict in Southern Iran. Sci Rep 2021 Jun 14;11(1):12423.
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