Vertical distribution changes in land cover between 1990 and 2015 within the Koshi River Basin, Central Himalayas

doi:10.1007/s11442-021-1904-2

Abstract

Abstract:

The study of mountain vertical natural belts is an important component in the study of regional differentiation. These areas are especially sensitive to climate change and have indicative function, which is the core of three-dimensional zonality research. Thus, based on high precision land cover and digital elevation model (DEM) data, and supported by MATLAB and ArcGIS analyses, this paper aimed to study the present situation and changes of the land cover vertical belts between 1990 and 2015 on the northern and southern slopes of the Koshi River Basin (KRB). Results showed that the vertical belts on both slopes were markedly different from one another. The vertical belts on the southern slope were mainly dominated by cropland, forest, bare land, and glacier and snow cover. In contrast, grassland, bare land, sparse vegetation, glacier and snow cover dominated the northern slope. Study found that the main vertical belts across the KRB within this region have not changed substantially over the past 25 years. In contrast, on the southern slope, the upper limits of cropland and bare land have moved to higher elevation, while the lower limits of forest and glacier and snow cover have moved to higher elevation. The upper limit of alpine grassland on the northern slope retreated and moved to higher elevation, while the lower limits of glacier and snow cover and vegetation moved northward to higher elevations. Changes in the vertical belt were influenced by climate change and human activities over time. Cropland was mainly controlled by human activities and climate warming, and the reduced precipitation also led to the abandonment of cropland, at least to a certain extent. Changes in grassland and forest ecosystems were predominantly influenced by both human activities and climate change. At the same time, glacier and snow cover far away from human activities was also mainly influenced by climate warming.

Key words: vertical belt, land cover, Central Himalayas, Koshi River Basin, climate change

WU Xue, PAUDEL Basanta, ZHANG Yili, LIU Linshan, WANG Zhaofeng, XIE Fangdi, GAO Jungang, SUN Xiaomin. Vertical distribution changes in land cover between 1990 and 2015 within the Koshi River Basin, Central Himalayas[J].Journal of Geographical Sciences, 2021, 31(10): 1419-1436.

Figures/Tables 7

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Table 1

Table 2

References 45

[1]	Brunschon C, Behling H, 2010. Reconstruction and visualization of upper forest line and vegetation changes in the Andean depression region of southeastern Ecuador since the last glacial maximum: A multi-site synthesis. Review of Palaeobotany and Palynology, 163: 139-152. doi: 10.1016/j.revpalbo.2010.10.005
[2]	Bryn A, Potthoff K, 2018, Elevational treeline and forest line dynamics in Norwegian mountain areas: A review. Landscape Ecology, 33: 1225-1245. doi: 10.1007/s10980-018-0670-8
[3]	Bu Z K, Wang S Z, Lang H Q et al., 2003. Vegetation vertical zone spectrum and its features on southern slope of Laobai Mountain in Huangnihe Nature Reserve. Journal of Mountain Science, 21(1): 80-84. (in Chinese)
[4]	Cavieres L A, Penaloza A, Arroyo M K, 2000. Altitudinal vegetation belts in the high-Andes of central Chile (33 degrees S). Revista Chilena De Historia Natural, 73: 331-344.
[5]	Cidan L Z, 1997. General situation of Mount Qomolangma Nature Reserve. China Tibetology, (1): 3-20. (in Chinese)
[6]	Fang C S, Meng Y, Liu X X et al., 2015. Driving force factors of LUCC of the Jilin section of Liaohe River based on principle analysis. Journal of Jilin University, 53(3): 577-581. (in Chinese)
[7]	Fang J Y, Yoda K, 1989. Climate and vegetation in China II: Distribution of main vegetation types and thermal climate. Ecological Research, 4(1): 71-83. doi: 10.1007/BF02346944
[8]	Gao J G, Zhang Y L, Liu L S et al., 2014. Climate change as the major driver of alpine grasslands expansion and contraction: A case study in the Mt. Qomolangma (Everest) National Nature Preserve, southern Tibetan Plateau. Quaternary International, 336: 108-116. doi: 10.1016/j.quaint.2013.09.035
[9]	Gay A, Cerdan O, Mardhel V et al., 2016. Application of an index of sediment connectivity in a lowland area. Journal of Soils & Sediments, 16(1): 280-293.
[10]	Guo S Z, Bai H Y, Huang X Y et al., 2019. Remote sensing phenology of Larix chinensis forest in response to climate change in Qinling Mountains. Chinese Journal of Ecology, 38(4): 1123-1132. (in Chinese)
[11]	He W H, Zhang B P, Pang Y et al., 2015. Effect of slope aspect on the distribution of mountain forest in the northern flank of the central Tianshan Mountains. Mountain Research, 33(5): 546-552. (in Chinese)
[12]	Hu Z Y, Dietz A J, Kuenzer C, 2019. Deriving regional snow line dynamics during the ablation seasons 1984-2018 in European mountains. Remote Sensing, 11(8): 933. doi: 10.3390/rs11080933
[13]	Ji X Y, Luo L, Wang X Y et al., 2018. Identification and change analysis of mountain altitudinal zone in Tianshan Bogda Natural Heritage Site based on “DEM-NDVI-Land Cover Classification”. Journal of Geo-Information Science, 20(9): 1350-1360. (in Chinese)
[14]	Li L H, Zhang Y L, Liu L S et al., 2018. Current challenges in distinguishing climatic and anthropogenic contributions to alpine grassland variation on the Tibetan Plateau. Ecology and Evolution, 8: 5949-5963. doi: 10.1002/ece3.4099
[15]	Li L H, Zhang Y L, Liu L S et al., 2018. Spatiotemporal patterns of vegetation greenness change and associated climatic and anthropogenic drivers on the Tibetan Plateau during 2000-2015. Remote Sensing, 10(10), 1525. doi: 10.3390/rs10101525
[16]	Li L H, Zhang Y L, Wu J S et al., 2019. Increasing sensitivity of alpine grasslands to climate variability along an elevational gradient on the Qinghai-Tibet Plateau. Science of The Total Environment, 678: 21-29. doi: 10.1016/j.scitotenv.2019.04.399
[17]	Liu J Y, Shao Q Q, Yan X D et al., 2016. The climatic impacts of land use and land cover change compared among countries. Journal of Geographical Sciences, 26(7): 889-903. doi: 10.1007/s11442-016-1305-0
[18]	Mansur S, Yusup M, Nasima N, 2016. Landscape characteristics of the vertical natural zones of Tianshan Tomur Nature Reserve. Journal of Glaciology and Geocryology, 38(5): 1425-1431. (in Chinese)
[19]	Mohapatra J, Singh C P, Tripathi O P et al., 2019. Remote sensing of alpine treeline ecotone dynamics and phenology in Arunachal Pradesh Himalaya. International Journal of Remote Sensing, 40: 7986-8009. doi: 10.1080/01431161.2019.1608383
[20]	Nie Y, Zhang Y L, Ding M J et al., 2013. Lake change and its implication in the vicinity of Mt. Qomolangma (Everest), Central High Himalayas, 1970-2009. Environmental Earth Sciences, 68(1): 251-265. doi: 10.1007/s12665-012-1736-6
[21]	Nie Y, Zhang Y L, Liu L S et al., 2010. Monitoring glacier change based on remote sensing in the Mt. Qomolangma National Nature Preserve. Acta Geographica Sinica, 65(1): 13-28. (in Chinese)
[22]	Paudel B, Gao J G, Zhang Y L et al., 2016. Changes in cropland status and their driving factors in the Koshi River Basin of the Central Himalayas, Nepal. Sustainability, 8(9): 1-17. doi: 10.3390/su8010001
[23]	Paudel B, Wu X, Zhang Y L et al., 2020. Farmland abandonment and its determinants in the different ecological villages of the Koshi River Basin, Central Himalayas: Synergy of high-resolution remote sensing and social surveys. Environmental Research, 188: 109711. doi: 10.1016/j.envres.2020.109711
[24]	Peters M K, Hemp A, Appelhans T et al., 2019. Climate land use interactions shape tropical mountain biodiversity and ecosystem functions. Nature, 568(7750): 1-5.
[25]	Qi W, Zhang Y L, Gao J G et al., 2013. Climate change on the southern slope of Mt. Qomolangma (Everest) Region in Nepal since 1971. Journal of Geographical Sciences, 23(4): 595-611. doi: 10.1007/s11442-013-1031-9
[26]	Rastner P, Prinz R, Notarnicola C et al., 2019. On the automated mapping of snow cover on glaciers and calculation of snow line altitudes from multi-temporal Landsat data. Remote Sensing, 11: 1410. doi: 10.3390/rs11121410
[27]	Ren P, Neron V, Rossi S et al., 2020. Warming counteracts defoliation-induced mismatch by increasing herbivore-plant phenological synchrony. Global Change Biology, 26: 2072-2080. doi: 10.1111/gcb.v26.4
[28]	Sieg B, Danie J, Fred J A, 2005. Altitudinal zonation of vegetation in continental West Greenland with special reference to snowbeds. Phytocoenologia, 35(4): 887-908. doi: 10.1127/0340-269X/2005/0035-0887
[29]	Sigdel S R, Wang Y, Camarero J J et al., 2018. Moisture-mediated responsiveness of treeline shifts to global warming in the Himalayas. Global Change Biology, 24.
[30]	Sun J, Cheng G W, 2014. Mountain altitudinal belt: A review. Ecology and Environmental Sciences, 23(9): 1544-1550. (in Chinese)
[31]	Sun R H, 2008. Digital identification and analysis of mountain altitudinal belts[D]. Beijing: Institute of Geographic Sciences and Resources, CAS. (in Chinese)
[32]	Wu X, Gao J G, Zhang Y L et al., 2017. Land cover status in the Koshi River Basin, Central Himalayas. Journal of Resources and Ecology, 8(1): 10-19. doi: 10.5814/j.issn.1674-764x.2017.01.003
[33]	Wu X, Sun X M, Wang Z F et al., 2020. Vegetation changes and their response to climate change in the Koshi River Basin of Central Himalayas since 2000. Sustainability, 12(16): 1-15. doi: 10.3390/su12010001
[34]	Xiao F, Ling F, Du Y et al., 2010. Digital extraction of altitudinal belt spectra in the West Kunlun Mountains using SPOT-VGT NDVI and SRTM DEM. Journal of Mountain Science, 7(2): 133-145. doi: 10.1007/s11629-010-1068-5
[35]	Xie F D, Wu X, Liu L S et al., 2021. Land use and land cover change within the Koshi River Basin of the Central Himalayas since 1990. Journal of Mountain Science, 18(1): 159-177. doi: 10.1007/s11629-019-5944-3
[36]	Xu J, Zhang B P, Tan J et al., 2009. Spatial relationship between altitudinal vegetation belts and climatic factors in the Qinghai-Tibetan Plateau. Journal of Mountain Science, 27(6): 663-670. (in Chinese)
[37]	Xu J, Zhang B P, Zhu Y H et al., 2006. Distribution and geographical analysis of altitudinal belts in the Altun-Qilian Mountains. Geographical Research, 25(6): 977-984. (in Chinese)
[38]	Yu P, Yao Y H, Zhao F et al., 2012. A method for identifying slope aspect information of mountain altitudinal belts. Journal of Mountain Science, 30(3): 290-298. (in Chinese)
[39]	Zhang B P, Mo S G, Wu H Z et al., 2004. Digital spectra and analysis of altitudinal belts in Tianshan Mountains, China. Journal of Mountain Science, 1: 18-28. doi: 10.1007/BF02919356
[40]	Zhang J W, Jiang S, 1973. A primary study on the vertical vegetation belt of Mt. Jolmo-Lungma (Everest) Region and its relationship with horizontal zone. Acta Botanica Sinica, 15(2): 221-236. (in Chinese)
[41]	Zhang W, Zhang Y L, Wang Z F et al., 2006. Analysis of vegetation change in Mt. Qomolangma Natural Reserve. Progress in Geography, 25(3): 12-21. (in Chinese)
[42]	Zhang Y L, Gao J G, Liu L S et al., 2013. NDVI-based vegetation changes and their responses to climate change from 1982 to 2011: A case study in the Koshi River Basin in the middle Himalayas. Global and Planetary Change, 108: 139-148. doi: 10.1016/j.gloplacha.2013.06.012
[43]	Zhang Y L, Liu L S, Li B Y et al., 2021. Boundary data of the Tibetan Plateau (2021 version). Digital Journal of of Global Change Data Repository, https://doi.org/10.3974/geodb.2021.07.10.V1.
[44]	Zhang Y L, Wu X, Zheng D, 2020. Vertical differentiation of land cover in the Central Himalayas. Journal of Geographical Sciences, 30(6): 969-987. doi: 10.1007/s11442-020-1765-0
[45]	Zhao F, Liu J J, Zhu W B et al., 2020. Spatial variation of altitudinal belts as dividing index between warm temperate and subtropical zones in the Qinling-Daba Mountains. Journal of Geographical Sciences, 30(4): 642-656. doi: 10.1007/s11442-020-1747-2

Land cover	Southern slope						Northern slope
	1990			2015			1990			2015
	Altitude range	Core distribution zone	Dominant belt	Altitude range	Core distribution zone	Dominant belt	Altitude range	Core distribution zone	Dominant belt	Altitude range	Core distribution zone	Dominant belt
Cropland	96-4300	800-1800	100-700	96-4300	600-1800	100-1000	2300-4600	4100-4400	-	2200-4600	4100-4400	-
Forest	96-4200	800-3000	700-2000	96-4200	900-2700	1000-3900	2100-4200	3200-4100	2100-4000	2100-4200	3200-4100	2100-3900
Shrub land	100-5100	600-2200 3400-4500	2000-3700	100-5100	2100-4500	-	2300-5000	4200-4900	4000-4100	2400-4800	4200-4900	3900-4100
Grassland	200-5300	3700-5300	3700-4000	1400-5300	4300-5100	-	2500-5300	4400-5000	4100-5300	2600-5300	4400-5000	4100-5100
Sparse vegetation	2100-5500	4800-5500	-	2100-5500	4700-5500	-	2500-5500	5000-5500	-	2500-5500	5000-5300	5100-5300
Waterbody	100-5600	200-800 5000-5300	-	100-5600	200-1000 4800-5600	-	2200-5600	4100-4500	-	2200-5600	4100-4600	-
Built-up area	400-700 1400-2400	1400-1600 2200-2400	-	400-4400	1000-2000	-	4200-4400	4200-4400	-	3500-4400	4200-4400	-
Bare land	Over 200	4300-5600	4000-5400	Over 200	4400-5700	3900-5700	Over 2200	5000-5900	-	Over 2200	4900-5900	-
Wetland	Less than 5400	200-1700	-	Less than 5500	200-1800	-	3500-5700	4100-4400	5300-5900	3500-5700	4200-4500	5500-6000
Glacier and snow cover	Over 3700	5000-5900	Over 5400	Over 4000	5000-6000	Over 5700	Over 3600	5500-6500	Over 5900	Over 3600	5600-6500	Over 6000

Land cover on southern slope	Variable	β	S.E.	Wald	Sig (p)	Odds ratio
Glacier and snow cover	TMP	70.084	28.101	6.220	0.013	2.735
	TMX	458.526	152.815	9.003	0.003	1.366
	TMN	-705.254	216.345	10.627	0.001	0.000
Forest	PRE	-0.008	0.012	0.508	0.047	0.992
Forest	TMN	93.948	72.954	1.658	0.019	6.326
Cropland	PRE	0.138	0.034	16.884	0.000	1.148
	TMP	305.274	93.714	10.611	0.001	3.790
	TMN	-219.798	100.111	4.820	0.028	0.000
	TMX	-877.120	240.970	13.249	0.000	0.000
Bare land	TMN	-120.064	61.371	3.827	0.050	0.000
Bare land	TMX	187.431	93.069	4.056	0.044	2.513
Land cover on northern slope	Variable	β	S.E.	Wald	Sig (p)	Odds ratio
Glacier and snow cover	TMN	454.324	139.590	10.593	0.001	2.043
Glacier and snow cover	TMX	-759.591	180.584	17.693	0.000	0.000
Grassland	TMP	-76.096	14.043	29.365	0.000	0.000
Grassland	TMN	-271.772	155.047	3.072	0.080	0.000