Journal of Geographical Sciences © 2007

Science in China Press

Springer-Verlag

DOI: 10.1007/s11442-007-0152-4

Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001 ZHANG Wei1,2, *ZHANG Yili1,3, WANG Zhaofeng1,2, DING Mingjun1,2, YANG Xuchao1,2, LIN Xuedong2,3, LIU Linshan1 1. Institute of Geographic Sciences and Natural Resources Research, CAS, Beijing 100101, China; 2. Graduate School of the Chinese Academy of Sciences, Beijing 100039, China; 3. Institute of Tibetan Plateau Research, CAS, Beijing 100085, China

Abstract: Based on the NOAA AVHRR-NDVI data from 1981 to 2001, the digitalized China Vegetation Map (1:1,000,000), DEM, temperature and precipitation data, and field investigation, the spatial patterns and vertical characteristics of natural vegetation changes and their influencing factors in the Mt. Qomolangma Nature Reserve have been studied. The results show that: (1) There is remarkable spatial difference of natural vegetation changes in the Mt. Qomolangma Nature Reserve and stability is the most common status. There are 5.04% of the whole area being seriously degraded, 13.19% slightly degraded, 26.39% slightly improved, 0.97% significantly improved and 54.41% keeping stable. The seriously and slightly degraded areas, which mostly lie in the south of the reserve, are along the national boundaries. The areas of improved vegetation lie in the north of the reserve and the south side of the Yarlung Zangbo River. The stable areas lie between the improved and degraded areas. Degradation decreases with elevation. (2) Degeneration in the Mt. Qomolangma Nature Reserve mostly affects shrubs, needle-leaved forests and mixed forests. (3) The temperature change affects the natural vegetation changes spatially while the integration of temperature changes, slopes and aspects affects the natural vegetation change along the altitude gradients. (4) It is the overuse of resources that leads to the vegetation degeneration in some parts of the Mt. Qomolangma Nature Reserve. Keywords: Mt. Qomolangma (Everest); nature reserve; AVHRR; vegetation degradation; Himalayas

1

Introduction

On 18 May 1989, the Mt. Qomolangma Nature Reserve (MQNR) in Tibet Autonomous Region formally came into existence and it was listed as World Network of Biosphere Reserves (WNBR) in May 2005 (Li, 2001; Lin, 2005). The MQNR is a comprehensive reserve, which mainly protects alpine ecosystems, plateau natural landscapes, geological remains and TiReceived: 2006-11-22 Accepted: 2007-01-19 Foundation: Supported by the National Basic Research Program of China, No.2005CB422006; Social Commonweal Research Project of Ministry of Science and Technology of China, No.2005DIA3J106; National Natural Science Foundation of China, No.40331006 Author: Zhang Wei (1979–), Ph.D. Candidate, specialized in land-use/land-cover change and physical geography. *Corresponding author: Zhang Yili, e-mail: [email protected]

www.scichina.com

www.springerlink.com

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

153

betan historical and cultural heritages (Cidanlunzhu, 1997). Along with the increase of human activities in the Mt. Qomolangma region, human requirements for biologic resources have threatened local sustainable development (Gupta, 1978). However, there have been few studies on the spatial and temporal changes of surface vegetation. International studies on resource use and sustainable development in the Himalayas region had already evolved (Shrestha, 1981; Chalise, 1983; Sharma et al., 1994). The results indicated that large-scale land use changes caused great increase of agricultural land and decrease of forests were the result of the rapid increase of population and economic development (Brown et al., 2000; Tiwari, 2000). Moreover, energy requirements (Negi, 1993), improper and frequent variety of government management (Negi et al., 1999; Ali et al., 2005) and the development of the tourism industry (Awashi et al., 2003) were also important reasons for forest resources’ decrease in this region. At present, there is a lack of systematic reports about vegetation changes in the Mt. Qomolangma region. By means of AVHRR-NDVI data and linear regression method, the basic patterns of natural vegetation changes in the MQNR were preliminarily analyzed and the influencing factors were discussed in this paper. We hope the results of this study would give references to environment change researches, ecological constructions and sustainable development in this region. 2

Study area

The study area is the Mt. Qomolangma Nature Reserve, which is located close to the frontier with Nepal, including Tingri, Gyirong, Nyalam and Dinggye Counties in Tibet Autonomous Region in China (Figure 1). The reserve is from national boundaries to the south, the Yarlung Zangbo River and south Tibet watershed to the north, the watershed between the Mingjiu River and Yala River to the east and watershed of Baruo Zangbo, Amuga River and Sangzhuo River to the west. The area of the reserve is about 3.4×104 km2, lying in a range from 27°48´N to 29°19´N and from 84°28′ E to 88°23′ E. According to the analysis of meteorological data of Tingri and Nyalam, the 30-yearaveraged annual air temperature is 2.87℃ in Tingri and 3.61℃ in Nyalam from 1971 to 2000 (Yang et al., 2006). The 30-year-averaged annual precipitation is 259.81 mm in Tingri and 665.57 mm in Nyalam. MQNR is very abundant in the ecosystems and its vertical zones are remarkable. The vertical range of vegetation distribution is from 1600 m a.s.l. (on the southeastern slope and the southwestern slope) to 6000m/6200m a.s.l. (Jiang, 1974; Team of Scientific Expedition to Tibet of CAS, 1975; Fei, 1981; The Comprehensive Scientific Expedition to the Qinghai-Xizang Plateau, 1988). From the foot to the peak, the vertical vegetation zones on the south scope of the Himalayas are composed of the mountain subtropical evergreen broad-leaved forests, mountain warm-temperate needle-leaved and broad-leaved mixed forests, mountain cold-temperate needle-leaved forests, subalpine cold-temperate needle-leaved forests, subalpine frigid shrubs and meadows, alpine frigid meadows and cushion vegetation and alpine frigid moraine lichens. Above 5500 m a.s.l. is a snow and ice belt. From the foot to the peak, the vertical vegetation zones on the north scope of the Himalayas consist of plateau frigid semi-arid steppes, alpine frigid meadows and cushion vegetation and alpine frigid moraine lichens. Above 6000 m a.s.l. is snow and ice belt.

154

Journal of Geographical Sciences

Figure 1

Location of the Mt. Qomolangma Nature Reserve

The four counties in the MQNR are all agricultural counties with a population of about 8.86×104 in 2000. According to the economic statistic and calculating at the price in 2000, the total output value of agriculture was 2.00×108 yuan, which included 1.20×108 yuan of output value of agriculture, 3.06×106 yuan of forestry, and 7.65×107 yuan of stock raising. At the end of 2000, the amount of livestock on hand was 9.04×104, which included 1.32×104 of big livestock and 7.72 ×104 of sheep (Tibet Statistical Bureau, 2001). 3 3.1

Data and methods Data

The data used is the NOAA/AVHRR-NDVI data of every ten days from 1981 to 2001 from NASA of America. The spatial resolution is 1 km after being resampled. The interpolated temperature and precipitation data from 1981 to 1999 come from the postdoctoral report of Dr. Tao Bo (Tao, 2005). The DEM data is delivered from ‘Global Land Cover Network’ (GLCN), which is resampled to 100 m. The vegetation type data is obtained through digitalized China Vegetation Map (scale 1:1,000,000; The Editorial Board of Vegetation Map of China, CAS, 2001). Other data such as range of research area, boundaries, administration centers and rivers are from data volume of ‘Data Center for Resources and Environmental Sciences, CAS’. Although different vegetation types are limited in elevation, and can not fully fall into the elevation ranges because of the precision limitation of China Vegetation Map (scale 1:1,000,000), the authors corrected the attributes of some wrong polygons and listed most of

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

155

the vegetation in their elevation range (Table 1). Four changes have been made: (1) broad-leaved forests to mixed forests; (2) mixed forests, needle-leaved forests and shrubs out of the upper elevation limit to needle-leaved forests, shrubs and meadows respectively; (3) steppes and meadows out of the upper elevation limit to alpine sparse vegetation; and (4) alpine sparse vegetation out of the lower elevation limit to steppes. Table 1

Percentages of different vegetation types in its elevation ranges Needle-leaved Mixed forests Shrubs Steppes forests

Meadows

Alpine sparse vegetation

Elevation ranges (m)

2500-3100

3100-3900

3900-4700

4000-5000

3900-5600

4700-6000

In the range (%)

72.97

76.69

79.16

88.74

97.89

93.89

Out of the range (%)

27.03

23.31

20.84

11.26

2.11

6.11

3.2 3.2.1

Methods Computing and classifying NDVI linear regression coefficients

In order to eliminate the effect of clouds, the Maximum Value Composite (MVC) was used in the data processing and average values of July, August and September were selected as the peak value of a year to calculate the linear regression coefficients by means of Least Square Method (Micael, 2000). n

∑ ( x − x )( y − y ) i

b=

i

i =1

n

∑ ( x − x )2 i

i =1

where b is the trend coefficient, xi and yi are the year and the NDVI of the year respectively and x and y are the average of all the years and the average of all the annual NDVI. To find the natural fluctuation range of NDVI, this study chose 13 areas–with acreage of 200 km2 each–including lakes, frozen grounds, deserts, and salinas in Tibetan Plateau (Ding et al., 2006). There was no vegetation in these areas (Hou et al., 1979). Through analysis and statistics, 97% of coefficients in these areas were fell into the category between -0.2 and 0.2, so this range was taken as a range of no vegetation change. Meanwhile it was found the standard deviation was 0.21 about all coefficients of the Tibetan Plateau, and extended double standard deviation at the both ends of the range of no change, resulting in ±0.62. This value was thus taken as the boundary of slight and obvious change. Based on the above analysis, all the coefficients were divided into 5 grades: less than -0.62, -0.62 to -0.2, -0.2 to 0.2, 0.2 to 0.62 and more than 0.62. 3.2.2

Spatial analysis

Spatial correlation analysis was done in the Grid extension model in ArcInfo 9.0 by command Correlation. In order to finish analysis along the altitude gradients, DEM data was divided into 23 zones with an elevation interval of 200 m from 2000 m to 6600 m. Then the average values of NDVI trend coefficients, precipitation and temperature change trend coefficients (Least Square Method), slopes and aspects at a certain altitude zone were calculated in the Grid extension model in ArcInfo 9.0 by command Zonalstats. The following statistical analysis was achieved in SPSS, and the partial correlation with two-tail examination was

156

Journal of Geographical Sciences

finished. 3.3

Explanation of some phrases

3.3.1

Vegetation change

The linear regression coefficients of NDVI value on a pixel were classified. There were five classes: less than -0.62, -0.62 to -0.2, -0.2 to 0.2, 0.2 to 0.62 and more than 0.62, which respectively corresponded to serious degradation, slight degradation, stability, slight improvement and significant improvement to indicate vegetation change status. The areas and ratios of natural vegetation changes were statistically computed excluding water, glacier and other non-vegetation types as well as cultivated areas. 3.3.2

NDVI, precipitation and temperature change

We used the average values of linear regression coefficients of NDVI, precipitation and temperature change on a pixel at a certain altitude zone.

4 4.1

Results The spatial characteristics of natural vegetation changes

The main characteristic of natural vegetation changes in the Mt. Qomolangma Nature Reserve was stability and the areas of vegetation improved were more than that degraded. There were 5.04% of the natural vegetation changes becoming seriously degraded, 13.19% slightly degraded, 26.39% slightly improved, 0.97% significantly improved and 54.41% stable. A belt-shaped spatial distribution was distinguished (Figure 2). The seriously de-

Figure 2

Natural vegetation changes in the Mt. Qomolangma Nature Reserve from 1981 to 2001

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

157

graded places were mainly found near Gyirong town in Gyirong County, around Nyalam town in Nyalam County, and near Qudang village and around the Rongxia village in Tingri County. The areas of improved vegetation lied in the north of the reserve and the south side of the Yarlung Zangbo River, especially in the north of the Tingri and Gyirong counties. The stable areas lied between the improved and degraded areas. 4.2

The vertical characteristics of natural vegetation changes

The upper limit of vegetation distribution in the MQNR is about 6000 m a.s.l. (lichens can be found in few regions at about 7400 m) and the forests line is about 3900 m a.s.l. (Team of Scientific Expedition to Tibet of CAS, 1975; Miehe, 1988). The natural vegetation changes at different altitude zones were obvious and discussed in their elevation range (Figure 3). The slight degradation and stability of natural vegetation changes could be found in every zone. The serious degradation of natural vegetation changes took place in a range from 2600 m to 6200 m. The natural vegetation changes of slight and significant improvement were respectively in a range from 3800 m to 6000 m and from 4400 m to 5600 m. The vertical characteristics of natural vegetation changes could be divided into two parts: (1) Degraded zone. At the altitude from 2400 m to 4000 m natural vegetations were in degraded change status. (2) Stable zone. At the altitude from 4000 m to 6000 m natural vegetations are stable. Along with the increase of elevation, natural vegetation changes transited from degraded to stable. The limit was just corresponded with the forest line.

Figure 3 serve

4.3

Percentages of natural vegetation changes at different altitudes in the Mt. Qomolangma Nature Re-

The changes of vegetation types

Degradation showed an absolute predominance over the mixed forests (Table 2). Slight degradation was the main changing characteristic for needle-leaved forests, which occupied

158

Journal of Geographical Sciences

over 60% of the whole area. Any improvement could not be found in needle-leaved and mixed forests. Slight degradation was the main changing characteristic for shrubs. Most of the area of shrubs was in degraded state and 24.72% seriously degraded, which was one of the largest in all of the vegetation types. Stability and slight improvement were the main characteristics for steppe and meadow changes, of which the stable area was the biggest among all kinds of changing states. Stability and slight degradation were the main changing characteristics for alpine sparse vegetation. Vegetation changes could be divided into three types: (1) Stability to improvement. They were steppes and meadows. (2) Stability to degradation. It was alpine sparse vegetation. (3) Degradation. They were shrubs, needle-leaved forests and mixed forests. Table 2

Change percentages of different vegetation types in the Mt. Qomolangma Nature Reserve (unit: %) Serious Slight degStability degradation radation

Mixed forests Needle-leaved forests Shrubs Steppes Meadows Alpine sparse vegetation

4.73 24.72 24.72 0.04 3.49 8.26

78.38 60.11 39.22 2.16 9.06 25.10

16.89 15.17 29.48 64.09 53.13 52.46

Slight improvement 0.00 0.00 6.58 32.61 33.11 13.46

Significant Main change condition improvement 0.00 0.00 0.00 1.10 1.22 0.70

Degradation Degradation Degradation Stability-improvement Stability-improvement Stability-degradation

The mixed forests were distributed in the area from 2000 m to 4000 m a.s.l., mainly from 2500 m to 3100 m a.s.l. (Tables 1 and 3). Slight degradation occurred in every elevation zone. The needle-leaved forests were distributed in the area from 2400 m to 4600 m, mainly from 3100 m to 3900 m. Effect of slight degradation also occurred in each elevation zone and much more serious degradation took place in contrast to the mixed forests. Shrubs were distributed in the area from 2600 m to 5600 m, mainly from 3900 m to 4700 m. Over 4000 m, slight improvement appeared and the percents of stability started to increase. Steppes were distributed in the area from 3400 m to 5800 m, mainly from 4000 m to 5000 m. Stability occurred almost in every zone and its ratio was higher than mixed forests, needle-leaved forests and shrubs. The meadows were distributed in the area from 3600 m to 6000 m, mainly from 3900 m to 5600 m, with most keeping stable too. The alpine sparse vegetation was distributed in the area from 3400 m to 6600 m, mainly from 4700 m to 6000 m. The ratio of slight and serious degradation increased in most of the elevation zones compared to steppes and meadows. In the degraded zone, mixed forests, needle-leaved forests and shrubs were mainly distributed and were affected. In the stable zone, shrubs, steppes, meadows and alpine sparse vegetation were distributed in most areas and most of them kept stable. Shrubs could be found in two different zones and appeared more degraded in the degenerative zone than in the stable zone. In conclusion, the degenerated objects in the MQNR were mostly the shrubs, needle-leaved forests and mixed forests. 4.4

The relationship between physical conditions and natural vegetation changes

Related researches confirmed that southern Tibet was one of the most significant warming areas in China (Feng et al., 1998). Along with the increase of the elevation, temperature

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

159

Figure 4 Temperature change (a) and average slopes (b) along the altitude gradients with NDVI change in the Mt. Qomolangma Nature Reserve

160

Journal of Geographical Sciences

Table 3 Vertical change of percentages of different vegetation types in the Mt. Qomolangma Nature Reserve * A.S.L. (m) I II III IV V VI 2000-2200 2200-2400 2400-2600 2600-2800 2800-3000 3000-3200 3200-3400 3400-3600 3600-3800 3800-4000 4000-4200 4200-4400 4400-4600 4600-4800 4800-5000 5000-5200 5200-5400 5400-5600 5600-5800 5800-6000 6000-6200 6200-6400 6400-6600 * I, II, III, IV, V and VI represent mixed forests, needle-leaved forests, shrubs, steppes, meadows and alpine sparse vegetation. Legend is equal to that in Figure 2.

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

161

changes showed similar curves with NDVI change (Figure 4a). The spatial correlation analysis showed the correlation coefficients of temperature change and NDVI change was 0.53 and the result of the partial correlation analysis was 0.93 along the altitude gradients (Table 4). Hence the temperature change affected the regional vegetation change not only spatially but also vertically. Global warming has made notable temperature increase in the high altitude region, which has good impacts on growth of natural vegetation (Watson et al., 2001). Natural vegetation improvements in the north of the reserve may be related with the warming. Average slopes showed a negative relationship with NDVI change (Figure 4b). The coefficient of the partial correlation analysis between average slopes and NDVI change was -0.93 along the altitude gradients. The slope mainly affected the regional vegetation change vertically. Natural vegetation trended to degenerate on steep slope areas. The degraded zone, which had an average slope of over 10 degrees, was disadvantageous for vegetation growth. The average aspects in the MQNR are in a range of 149.33 to 201.39 degrees (0 degree started from north and rotated clockwise). The coefficient of the partial correlation analysis between average aspects and NDVI change was 0.62 along the altitude gradients, which indicated that the natural vegetation on the eastern and southern slopes could get more heat to grow better and might be over utilized or grazed (Liu et al., 2006). Thus they were fragile and easy to be degraded. Table 4

Correlation analysis of NDVI change and its influencing factors Vertical partial correlation coefficients * Spatial correlation coefficients

Temperature change - NDVI change Average slope - NDVI change Precipitation change - NDVI change Average aspect - NDVI change

0.93 -0.93 (Significance less than 95% level) 0.41

0.53 -0.34 0.07

0.62

0.00

* Partial correlation coefficients, 99% level of significance, two-tail examination and 23 samples.

4.5 Impacts of human activities on vegetation changes in the Mt. Qomolangma Nature Reserve In the regions of humans’ distribution, human activities and climatic factors influence vegetation together and the land use and land cover change produced by human activities are prominent (Gao et al., 2004). According to the current price, in 1995, the output value of forestry occupied 0.88% of the gross agriculture production and rose to 1.54% in 2000 (Table 5), which increased by 74.51%. This change meant that the forests resources in the MQNR were greatly exploited and utilized after the mid 1990s. This might be an important Table 5 Economic conditions in 1995 & 2000 in the Mt. Qomolangma Nature Reserve*# (unit: %) Ratio of GOVFa to GOVA Ratio of GOVFo to GOVA Ratio of GOVAH to GOVA Year 1995 2000 1995-2000

58.28 60.04

0.88 1.54

40.84 38.42

3.01

74.51

-5.90

* Data came from (Tibet Bureau of Statistics, 1996 and 2001). The output values in the MQNR were the summation of its four counties. # GOVA, GOVFa, GOVFo and GOVAH represent Gross Output Value of Agriculture, Gross Output Value of Farming, Gross Output Value of Forestry and Gross Output Value of Animal Husbandry.

162

Journal of Geographical Sciences

factor that caused severe forest degeneration in the Mt. Qomolangma region. Farmers and herdsmen obtained income, built houses and gained warmth by deforestation. How to halt deforestation became a chief environmental protection problem for local governments (Peng, 1999; Li, 2001; Zhu et al., 2002; He, 2005). Field survey found that in some areas about 4700 m a.s.l., herdsmen reclaimed meadows into farmlands (Zhang et al., 2005) and dig meadows to build vallums and houses, which destroyed the surface vegetations and ultimately induced desertification (Dong, 2005; You, 2005). People made their living by exploiting biologic resources (such as medicinal herbs), which were difficult to regenerate in such harsh natural condition. It was the overuse of resources that led to degeneration in parts of the region.

5 5.1

Conclusions and discussion Conclusions of vegetation changes in the Mt. Qomolangma Nature Reserve

Through the analysis of natural vegetation changes in the MQNR and their influencing factors, the results show that: (1) A belt-shaped spatial distribution of natural vegetation changes is distinguished and stability is the most common status. Along with the increase of elevation, the state of natural vegetation changes transits from degradation to stability. (2) The worst affected natural vegetation zones in the MQNR are mostly composed of shrubs, needle-leaved forests and mixed forests. (3) The temperature change affects natural vegetation changes spatially while the integration of temperature changes, slopes and aspects affects natural vegetation changes along the altitude gradients. (4) Overuse of resources by human beings has led to natural vegetation degeneration in some parts of the MQNR. 5.2

Recommendations for ecological protection and regional development

The ecological protection methods for the MQNR should not be emphasized on forcing management but to be related with local sustainable development (Peng, 1999). The sustainable development must be tied with local economic development to eliminate poverty and solve the living problems for local inhabitants. It was a successful example that the China International Center for Economic and Technical Exchanges and the United Nations Development Programme (UNDP) authorized a community-based, economic and social development project in the MQNR. On one hand it modeled community-based development. On the other hand it helped the local government make a development project that provided more working and incoming opportunities. What’s more, a series of illustrations about the project was taken in the four counties (China International Center for Economic and Technical Exchanges, 2000). 5.3

Discussion

NOAA remote sensing images are the only continuous satellite data that can be got since the 1980s. They are fit for large-scale vegetation change research, but there are some limitations

ZHANG Wei et al.: Vegetation change in the Mt. Qomolangma Nature Reserve from 1981 to 2001

163

such as coarse resolution. A further study on seriously degraded areas by means of high resolution remote sensing images is good complementarities for the research. The physical and social conditions in the MQNR are restrictive and lots of basic data can be difficult to obtain. This study offers primary research and further researches can combine with the field working materials from the Fourth Mt. Qomolangma Comprehensive Scientific Expedition. Acknowledgements: The authors would like to thank Mr. Wang Zhizhong, Mr. Pubuzhaxi of Tingri County and other administrators in Tingri County, Prof. Huang Rongfu of Northwest Institute of Plateau Biology, CAS, and Prof. Kang Shichang of ITP, CAS for their supports and guidance during the field survey; Prof. Zheng Du, Associate Prof. Feng Xuehua and Dr. Tao Bo of IGSNRR, CAS for their supports to the research, Global Land Cover Network Programme by FAO, Italian Cooperation and Data Center for Resources and Environmental Sciences of CAS for their data support.

References Ali J, Benjaminsen T A, Hammad A A et al., 2005. The road to deforestation: An assessment of forest loss and its causes in Basho Valley, Northern Pakistan. Global Environmental Change Part A, 15(4): 370-380. Awashi A, Uniyal S K et al., 2003. Forest resource availability and its use by the migratory villages of Uttarkashi, Garhwal Himalaya (India). Forest Ecology and Management, 174(1-3): 13-24. Brown S, Shrestha B, 2000. Market-driven land-use dynamics in the middle mountains of Nepal. Journal of Environmental Management, 59(3): 217-225. Chalise S R, 1983. Energy efficiency and conservation in Nepal. Energy, 8(1-2): 133-136. China International Center for Economic and Technical Exchanges, 2000. Sustainable development in the Mt. Qomolangma Natural Reserve. http://www.cicete.org/poverty/tibet.htm. (in Chinese) Cidanlunzhu, 1997. General Situation of Mt. Qomolangma Natural Reservoir. China Tibetology, 1: 3-22. (in Chinese) Ding Mingjun, Zhang Yili, Shen Zhenxi et al., 2006. Land cover change along the Qinghai-Tibet Highway and Railway from 1981 to 2001. Journal of Geographical Sciences, 16(4): 387-395. Dong Xiaorui, 2005-08-01. Degradation of Vegetations in the Mt. Qomolangma area. http://www.cas.cn/html/Dir/ 2005/08/02/2235.htm. (in Chinese) Fei Jinshen, 1981. Random notes of scientific survey in Mt. Qomolangma. Tianjin: Tianjin Science & Technology Press. (in Chinese) Feng Song, Tang Maocang, Wang Dongmei, 1998. The new evidences of climate change startup of Tibetan Plateau. Chinese Science Bulletin, 43(6): 633-636. (in Chinese) Gao Zhiqiang, Liu Jiyuan, Cao Mingkui et al., 2004. Impacts of land use and climate change on regional net primary productivity. Journal of Geographical Sciences, 14(3): 349-358. Gupta R K, 1978. Impact of human influences on the vegetation of the Western Himalaya. Plant Ecology (Historical Archive), 37(2): 111-118. He Manhong, 2005. Environmental protection in the Mt. Qomolangma. 2005-08-17. http://info.tibet.cn/news/ tpxw/whhb/t20050817_48140.htm. (in Chinese) Hou Xueyu, Sun Shizhou, He Miaoguang et al., 1982. Vegetation Map of the People’s Republic of China. Beijing: Map Press of China. (in Chinese) Jiang Di, 1974. Mt. Qomolangma. Beijing: The Commercial Press. (in Chinese) Li Bosheng, 2001. Special and beautiful fields: Mt. Qomolangma Natural Reservoir. Human and Biosphere, 2: 4-11. (in Chinese) Lin Bin, 2005-03-25. Tibet Autonomous Region was listed as World Network of Biosphere Reserves. http://news.xinhuanet.com/newscenter/2005-03/25/content_2742799.htm. (in Chinese) Liu Linshan, Zhang Yili, Bai Wanqi et al., 2006. Characteristics of grassland degradation and driving forces in the source region of the Yellow River from 1985 to 2000. Journal of Geographical Sciences, 16 (2): 131-142.

164

Journal of Geographical Sciences

Micael C R, 2000. Is northern China winning the battle against desertification? Satellite remote sensing as a tool to study biomass trends on the Ordos Plateau in semiarid China. AMBIO, 29(8): 468-476. Miehe G, 1988. Vegetation patterns on Mount Everest as influenced by monsoon and fonn. Plant Ecology (Historical Archive), 79(1-2): 21-32. NEGI A K, Bhatt B P, Todaria N P, 1999. Local population impacts on the forests of Garhwal Himalaya, India. The Environmentalist, 19(4): 293-303. Negi A K, Todaria N P, 1993. Studies on the impact of local folk on forests of Garhwal Himalaya. 1: Energy from biomass. Biomass and Bioenergy, 4(6): 447-454. Peng Yueming, 1999. About the tactics of forest resource protection in the central regions of Tuolong valley in Zhumulangma peak nature reserve. Sichuan Forestry Exploration and Design, 1: 4-8. (in Chinese) Sharma S, Singh S P, 1994. Energy use pattern and sustainable development: A case study in rural landscape of the Central Himalaya. Landscape and Urban Planning, 29(1): 19-24. Shrestha K L, 1981. Nepal’s energy situation. Energy, 6(8): 817-821. Tao Bo, 2005. Preliminary study on spatio-temporal patterns of terrestrial carbon budgets driven by climatic change in China. Postdoctoral Research Report. (in Chinese) Team of Scientific Expedition to Tibet of CAS, 1975. Dissertation of Scientific Expedition to Mt. Qomolangma Region: Physical Geography. Beijing: Science Press. (in Chinese) The Comprehensive Scientific Expedition to the Qinghai-Xizang Plateau, 1988. Series of Integrated Scientific Expedition to the Qinghai-Tibet Plateau: Vegetation of Tibet. Beijing: Science Press. (in Chinese) The Editorial Board of Vegetation Map of China, CAS, 2001. Vegetation Atlas of China (1:1,000,000). Beijing: Science Press. (in Chinese) Tibet Bureau of Statistics (comp.), 1996. Tibet Statistical Yearbook 1995. Beijing: China Statistics Press. (in Chinese) Tibet Bureau of Statistics (comp.), 2001. Tibet Statistical Yearbook 2000. Beijing: China Statistics Press. (in Chinese) Tiwari P C, 2000. Land-use changes in Himalaya and their impact on the plains ecosystem: need for sustainable land use. Land Use Policy, 17(2): 101-111. Watson R T, and the core writing team (eds.), 2001. Climate Change 2001: Synthesis Report. IPCC, Geneva, Switzerland, pp184. Yang Xuchao, Zhang Yili, Zhang Wei et al., 2006. Climate change in Mt. Qomolangma region from 1971. Journal of Geographical Sciences, 16 (3): 326-336. You Xueqing, Luo Hui, 2005. Serious degraded in the Mt. Qomolagma area. Science and Technology Daily. 2005-05-08. http://tech.tom.com/1121/1122/200559-193930.html (in Chinese) Zhang Yili, Huang Rongfu, Wang Zhaofeng et al., 2005. Field survey records of biodiversity and environment group: The Fourth Integrated Scientific Survey in Mt. Qomolangma Region. Research Group of Land Change in Qinghai-Tibet Plateau, IGSNRR, CAS. (in Chinese) Zhu Yukun, Nimucairang, 2002. Discussion on strategies about orientation and development of forest resources in Tibet. Tibetan Research, 1: 97-103. (in Chinese)