the vegetation cover dynamics (1982–2006) in different erosion regions of the yellow river basin,...

land degradation & development

Land Degrad. Develop. 23: 62–71 (2012)

Published online 27 October 2010 in Wiley Online Library (wileyonlinelibrary.com) DOI: 10.1002/ldr.1050

THE VEGETATION COVER DYNAMICS (1982–2006) IN DIFFERENT EROSIONREGIONS OF THE YELLOW RIVER BASIN, CHINA

C. Y. MIAO1*, L. YANG2, X. H. CHEN3 AND Y. GAO4

1State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Global Change and Earth System Science, Beijing Normal University,Beijing 100875, PR China

2State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, ChineseAcademy of Sciences, Beijing 100101, PR China

3School of Natural Resources, University of Nebraska-Lincoln, Lincoln, NE 68583, USA4School of Soil and Water Conservation, Beijing Forestry University, Beijing 100083, PR China

Received 4 May 2009; Revised 23 July 2010; Accepted 27 August 2010

ABSTRACT

Vegetation significantly influences human health in the Yellow River basin and the plant cover is vulnerable to people. Typical types of erosionin the Yellow River basin include that caused by water, wind and freeze–thaw. In this paper, vegetation cover change from 1982 to 2006 wasstudied for a number of different erosion regions. The Global Inventory Monitoring and Modeling Studies Normalized Difference VegetationIndex (GIMMS NDVI) data were employed, while climatic data were also used for analysis of other influencing factors. It was shown that:(1) generally the vegetation cover in different erosion regions displayed similar increasing trends; (2) spatially the vegetation cover washighest in the water erosion region, the second highest was in the freeze–thaw region and the lowest in the wind erosion region; and(3) vegetation cover in the Yellow River basin is influenced by climate factors, especially by temperature. In water erosion regions, thetemporal change of vegetation cover seemed complicated by comprehensive climatic and human influences. In wind erosion regions,the vegetation cover had close relations to precipitation. In freeze–thaw erosion regions, the vegetation cover was primarily altered bytemperature. In all the three erosion regions, significant change of the vegetation cover occurred from 2000 just after the ‘Grain for Green’(GFG) programme was implemented throughout China. Copyright # 2010 John Wiley & Sons, Ltd.

key words: Yellow River basin; PR China; remote sensing; erosion; vegetation cover dynamics

INTRODUCTION

Eco-environmental systems are dynamic due to climatic

disturbances, such as drought, wind, flood and solar

radiation, or human interferences (Lozano et al., 2007).

Nowadays, various sorts of problems in the global eco-

environment are threatening the sustainable development of

societies, even though these challenges have received great

attention from governments and scientists (Chen et al.,

2008). In order to assess eco-environmental change, it is

possible to use vegetation cover dynamics as an indicator.

Long time-series data on vegetation cover are usually used to

detect discrete change and gradual change.

Nowadays, remote sensing (RS) technology is widely

used for monitoring the state of vegetation cover, due to its

high efficiency for acquiring updated information (Bannari

et al., 1995). The Normalized Difference Vegetation Index

* Correspondence to: C. Y. Miao, State Key Laboratory of Earth SurfaceProcesses and Resource Ecology, College of Global Change and EarthSystem Science, Beijing Normal University, 19 Xinjiekou Wai Street,Beijing 100875, PR China.E-mail: [email protected]

Copyright # 2010 John Wiley & Sons, Ltd.

(NDVI), can be defined as the difference between near

infrared and red waveband radiance or reflectance divided

by the sum of radiance or reflectance for these two

wavebands (Stow et al., 1998), and it remains the basic

vegetation index widely employed for vegetation cover

monitoring (Trishchenko et al., 2002). It was found that

change in NDVI time-series can indicate the variation in

vegetation conditions proportional to the absorption of

radiation used for photosynthesis (Sellers, 1985), and there

is a good correlation between the NDVI value and the

vegetation cover density, biomass and leaf area index (LAI)

(Xin et al., 2008). In addition, the NDVI also correlates with

climate variables such as precipitation, temperature,

evaporation, etc. (Chen et al., 2008). Therefore, the NDVI

index can be used not only to describe spatiotemporal

variation of vegetation, but also to reflect the vegetation

feedback and response to climate.

In China, the vegetation cover shows an increasing trend in

recent years according to the NDVI (Chen et al., 2002; Fang et

al., 2004); however, interannual variation rates of vegetation

indexes have apparent spatial differentiations (Piao and Fang,

2001, 2003). Moreover, Li et al. (2002), using Advanced Very

Figure 1. Distribution of erosion types in the Yellow River basin. Thisfigure is available in colour online at wileyonlinelibrary.com

VEGETATION COVER DYNAMICS (1982–2006) 63

High Resolution Radiometer (AVHRR) NDVI data for 1983–

1992 and climatic data from 160 monitoring stations, detected

a significant correlation between NDVI value and rainfall in

China; the results show that the correlation coefficient

increases in order from evergreen forest to deciduous forest,

to shrubs and desert vegetation, to steppe and savanna. Most

research has been focused on the regions with fragile and

sensitive ecology such as Qinghai–Tibet Plateau (Ding et al.,

2005; Liang et al., 2007; Li et al., 2008), northwestern China

(Ma et al., 2003; Li et al., 2005; Deng et al., 2006; Ma and

Veroustraete, 2006; Xu et al., 2007), agro-pastoral transition

regions (Xia et al., 2006; Fan et al., 2007), karst regions (Wang

and Yang, 2006; Meng and Wang, 2007; Xiao and Weng,

2007), etc.

Among these fragile and sensitive regions, the Yellow

River basin has received the most attention in China (Sun et

al., 2001; Yang et al., 2002; Li and Yang, 2004; Xin et al.,

2008), due to its vital domestic status and problematic eco-

environment. In the whole Yellow River basin, it was found

that the vegetation cover showed an increasing trend during

1982–1999 (Sun et al., 2001), with the increasing rate

reaching at 0�58 per cent in this period (Yang et al., 2002).

Although the monthly NDVI sometimes lags behind the

corresponding precipitation within a year, it still shows

positive correlations between annual NDVI series and

annual precipitation in the Yellow River basin (Li and Yang,

2004), and no significant correlation between NDVI value

and temperature (Liu and Xiao, 2006). The results from the

Yellow River basin indicate that vegetation showed an

increasing trend during the past 20 years, the interannual

variability of NDVI in the Yellow River basin has a close

relationship with climate and this relationship is enhanced in

the grassland, but weakened in the forest and irrigated

agricultural areas. Using the NDVI temporal series from

National Oceanic and Atmospheric Administration (NOAA)

AVHRR image, Yang et al. (2006) found that there is no

significant trend in alpine vegetation cover in the source

regions of the Yellow River during 1982–2001, and the

vegetation cover is sensitive to the temperature change.

However, the vegetation cover in the source regions presents

a common degradation tendency if the analysis focuses only

on the period of 1980–2000, and the decreasing precipitation

affects the plant cover greatly (Guo et al., 2008). Given the

time limitation of NOAA AVHRR, Xin et al. (2008)

extended the NDVI series by regressing with the SPOT VGT

(1999–2006) dataset. They discovered that the NDVI of

sandy land vegetation, grassland and cultivated areas show a

significant increasing trend in the Loess Plateau, but that the

NDVI for the forest shows a decreasing trend, and a

significant correlation exists between vegetation cover and

precipitation.

However, more efforts are still needed due to insuffi-

ciencies in the previous studies: (1) Lack of updated NDVI


time-series for the whole basin: most of the pre-existing

research concentrated on the period between 1980 and 2000.

(2) Lack of spatial analysis for the climatic influences has

been a problem, most of the past studies mainly applied

to temporal correlation when analysing the climatic effects.

(3) Lack of systematic studies in terms of different erosion

regions; actually, the Yellow River basin can be divided into:

water erosion, wind erosion and freeze–thaw erosion

regions. This study investigates the dynamic change of

vegetation cover in water, wind and freeze–thaw erosion

regions in the Yellow River basin. A longer time-series

(1982–2006) was considered for interpretations of both

temporal and spatial variations of vegetation cover. This

study is of primary importance for understanding runoff

production, soil erosion and integrated river basin manage-

ment.

STUDY AREA

The Yellow River (Huanghe) is the second largest river in

China, with a total length of 5464 km. It originates in the

northeast of the Tibetan Plateau, runs across the Loess

Plateau of North China and the Ordos Plateau and flows

eastwards to the Bohai Sea, via semi-arid and semi-humid

regions (Figure 1). The Yellow River basin (7�52� 105 km2)

is one of the most important basins in China, directly

supporting a population of 130 million, mostly farmers and

rural people. The Yellow River basin covers nine provinces,

i.e. Qinghai, Sichuang, Gansu, Ningxia, Inner Mongolia,

Shaanxi, Shanxi, Henan and Shandong. Due to the

overexploitation of natural resources and expanding human

economic production, the Yellow River basin has changed

markedly with serious soil and water loss and degradation of

the total eco-environment. Nowadays, the Yellow River is

LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)

64 C. Y. MIAO ET AL.

well known for its tremendous sediment load and is

frequently referred to as a mud river. The Yellow River

annually carries 1�6 billion metric tons of sediment to the

sea, and the average annual erosion rate of the entire Yellow

River Basin reaches 2480 t km�2, which is the highest of any

major river system worldwide (Shi and Shao, 2000), and

accounts for 1/15 of the sediment discharge of the world’s

rivers (Zhang et al., 2009).

According to the Second Soil Erosion Survey with Remote

Sensing Technology (1990s), the erosion types in the Yellow

River basin include: water erosion, wind erosion and freeze–

thaw erosion, and each erosion type accounts for 73�87,

16�57 and 9�56 per cent area of the whole Yellow River

basin, respectively (Figure 1).

MATERIALS AND METHODS

Data Source and Pre-treatment

The Global Inventory Monitoring and Modeling Studies

(GIMMS) NDVI dataset was derived from the NOAA/

AVHRR, and provides information about the monthly

changes in terrestrial vegetation during the period from

August 1981 to December 2006. The GIMMS data are based

on 15-day interval with 8 km spatial resolution (Tucker

et al., 2005). Due to incomplete data in 1981, the dataset

used for this research is from 1982 to 2006 and consists of

600 half-monthly GIMMS NDVI images. The GIMMS

NDVI dataset largely reduced the variation of NDVI caused

by solar zenith angle change through drift correction (Piao

et al., 2003). It has also been corrected for these aspects:

distortions caused by cloud cover (Vermote et al., 1997),

sensor inter-calibration differences (Vermote and Kaufman,

1995), solar zenith angle and viewing angle effects, volcanic

aerosols and interpolation of missing data in the Northern

Hemisphere during the winter (Jin et al., 2008).

The time-series of daily precipitation and temperature

records from 1982 to 2006 at 175 climatological stations

were collected for this study. The stations in and around the

Yellow River basin were shown in Figure 1. According to the

Chinese Bureau of Meteorology Standards, annual climatic

datasets were derived from daily data. The climatic data

were provided by the National Meteorological Information

Center, China Meteorological Administration.

Data Processing

To further eliminate the influence of clouds, atmosphere and

solar altitude angle, the international universal Maximum

Value Composites (MVCs) technique was used to get

monthly maximum NDVI (Stow et al., 2007), which selects

the highest NDVI at each pixel from GIMMS NDVI (15-day

interval) (Zhou et al., 2003). The annual average NDVI and

seasonally integrated NDVI (SINDVI) were calculated


according to the monthly maximum NDVI. Annual average

NDVI is the mean value of 12 monthly maximum NDVI, and

SINDVI is the sum of NDVI values for each pixel and all

time intervals of MVCs for which the NDVI exceeds a

critical value (commonly NDVI> 0�1)(Stow et al., 2003).

The NDVI values in the three erosion regions were obtained

using the GIS software of ArcInfo 9�01.

Research Methods

The statistical indexes variation coefficient (Cv) and trend

coefficient (r) were adopted to analysed the characteristics of

NDVI series. The variation coefficient (Cv) is a normalized

measure of dispersion of a probability distribution calcu-

lated by eliminating the effects of unit and mean difference.

It is defined as the ratio of the standard deviation to the mean

(Bruland and Richardson, 2004) (Equation 1):

Cv ¼

ffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi1

n�1

Pni¼1

xi�xð Þ2

s

x(1)

where, n is the number of years for NDVI, xi is the NDVI in

the ith year and xis the multi-year average NDVI value.

Generally, Cv< 0�1 was regarded as weak variability,

0�1�Cv�1 as moderate variability and Cv> 1 as strong

variability (Hu et al., 2005). Trend coefficient (r) was used to

illuminate the long-term change direction and extent of

variant. In this study, it can be calculated by the process of

linear regression between the NDVI series and the time

series (Shin and Deng, 2000; Miehle et al., 2006)

(Equation 2):

r ¼

Pni¼1

xi�xð Þ i�tð ÞffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiPni¼1

xi�xð Þ2 Pni¼1

i�tð Þ2

s (2)

where t is the half of the time-series’ length. A positive value

of r indicated a linear increasing trend of the vegetation

cover during the interested period. On the contrary, a

negative value of r denoted a decreasing trend. The absolute

value of r reflected the increase or decrease speed (Gao et al.,

2009).

RESULTS

Spatial Distribution of Vegetation Cover

Based on the interannual average GIMMS NDVI (1982–

2006), the lowest vegetation cover appeared in the wind

erosion region (annual average NDVI range between 0 and

0�2), and followed by the freeze–thaw erosion (annual

average NDVI range between 0�1 and 0�4) (Figure 2). The

highest vegetation cover was primarily distributed in the


Figure 2. Spatial distribution of the annual average NDVI in the YellowRiver basin (1982–2006). This figure is available in colour online at

wileyonlinelibrary.com


water erosion region (annual average NDVI range between

0�2 and 0�8). Nevertheless, exceptions did exist for lower

vegetation cover in the water erosion regions nearby the

wind erosion region. Overall, higher vegetation cover often

appeared in the southern (especially in Xi’an and its

surrounding areas) and eastern areas than in the northern and

western areas in the whole Yellow River basin.

Interannual Vegetation Cover Variation

It was found that the annual NDVI in the three erosion

regions showed an increasing trend with a 95 per cent

confidence level during 1982–2006 (Figure 3). The Spear-

man correlation R are 0�67 (whole basin), 0�58 (water

erosion region), 0�55 (wind erosion region) and 0�70

(freeze–thaw erosion region). The increasing NDVI demon-

strated the improving ecosystems in the basin, and the

Figure 3. Temporal variation of average annual vegetation in the YellowRiver (1982–2006). This figure is available in colour online at



distinct fluctuation reflected different functions from

external factors in the three regions. In the Yellow River

basin, the vegetation cover improved rapidly after the low

value in 2000 (Figure 3). Annual NDVI value in the water,

wind and freeze–thaw erosion regions were: 0�28–0�32,

0�15–0�20 and 0�23–0�29, respectively; the order agreed well

with the spatial distribution of NDVI as shown in Figure 2.

Because of the large percentage, the interannual fluctuated

characteristic of NDVI in the water erosion region was

synchronous with the whole basin. The slope of regression

line, as shown in Figure 3, exhibits the increasing rate of

NDVI. It was found that the vegetation cover in the Yellow

River increased by the rate of 0�075 per cent per year.

Among these three major erosion regions, the highest

increasing rate appeared in the freeze–thaw erosion region,

followed by the water erosion region and then by the wind

erosion region. The mean increasing rates of NDVI were

0�124, 0�071 and 0�057 per cent per year, respectively. In

addition, a statistically significant trend of SINDVI was also

detected in the Yellow River (Figure 4). Compared with the

NDVI, the vibration of SINDVI series in the Yellow River

were more obvious. Interannual variation in SINDVI was

caused by variations in the magnitude of NDVI values in

some years and by different season lengths in other years (or

a combination of both factors).

Spatiotemporal Variation of Vegetation Cover

In the Yellow River basin, almost all the variation coefficient

Cv of vegetation cover concentrated in the range of 0–0�2during the period of 1982–2006, and exiguous pixels with

variation coefficient over 0�2 cannot be presented clearly in

the figure (Figure 5a). The weak variability (Cv< 0�1)

occupied the overwhelming majority of the area of the

Yellow River basin, and the moderate variability

(0�1�Cv�1) mostly distributed along the mainstream of

the Yellow River.

Figure 4. Temporal variation of SINDVI in the Yellow River basin (1982–2006).


Figure 5. The variation coefficient (a) and trend coefficient (b) in theYellow River basin during 1982–2006. This figure is available in colour

online at wileyonlinelibrary.com


The vegetation cover change in the Yellow River basin

showed a significant spatial difference (Figure 5b). In the

freeze–thaw erosion region, nearly all areas presented an

increasing trend with a high trend coefficient. The eco-

environment in the water and wind erosion regions was

ameliorated in general; however, the area with decreasing

vegetation cover was still enlarged when compared with the

freeze–thaw erosion region. In the wind erosion regions, the

vegetation cover around Yinchuan City (ellipse-shaped zone

in Figure 5b) showed a degrading trend. In the water erosion

region, the degrading trend occurred in the area between

Taiyuan and Xi’an (ellipse zone in Figure 5b), which

belongs to the Fen River basin. In these two kinds of erosion

regions, both of areas with a degrading trend were close to

the mainstream.

Figure 6. The climatic condition in the Yellow River basin (1982–2000).(a) precipitation; (b) temperature. This figure is available in colour online at


DISCUSSIONS

Spatiotemporal Characteristics of Vegetation Cover

The spatial distribution of vegetation cover (Figure 2) is

accorded with the natural condition in the Yellow River

basin. In the wind erosion region, the annual average

precipitation and temperature is 276�71 mm and 7�328C,


respectively (Figure 6). Most of this region is classified into

arid and semiarid areas in China. All of the Tenggeli Desert,

the Kubuqi Desert and the Wulanbuhe Desert are located in

this region. The low-precipitation and serious desertification

conditions make it difficult for plants to grow, and results in

the poorest vegetation cover.

In the freeze–thaw erosion region, the location on the

Southern Qinghai Plateau and the high altitude leads to low

air temperature. The annual average temperature is �0�878C(Figure 6). It greatly shortens plant’s growing season and

counteracts the vegetation’s photosynthesis. At the same

time, due to the atrocious weather and sparse population,

there has been little need for ecological reclamation in the

freeze–thaw erosion region in past decades.

In the water erosion region, the annual average

precipitation and temperature were 487�10 mm and

17�778C (Figure 6). The moderate climate and the

reasonable soil favour plant growth. As a result, the annual

vegetation cover in the water erosion region is the best.

Zones in the water erosion region, which border the wind

erosion region, have less vegetation cover with low NDVI.

The reason is mainly that the natural conditions in this area,

are similar to the wind erosion region (Maowusu Desert lies

in this area).


Figure 7. The annual precipitation and temperature variation in the YellowRiver basin.


The primary vegetation cover in the wind and freeze–thaw

erosion regions is really poor, so it is easy to register a higher

trend coefficient, as long as the growing conditions are

improved (Figure 5b). The synchronous trend coefficient in

this region leads to a NDVI with the highest increasing rate

(Figure 3d). In the water erosion region, the relative high

vegetation cover depresses the increasing trend. Moreover,

the vegetation cover in the hilly and gully region of the Loess

Plateau showed a descending trend during 1982–2006, and

the result is consistent with the Xin et al. (2008). In this area,

there is a large population and extensive croplands; in order

to meet the need for food, cultivation of steep areas and

intensive landuse cause serious soil erosion, destroy the eco-

environment further and consequently the vegetation cover

is decreasing.

Influencing Factor of Vegetation Variation

The vegetation cover dynamic is influenced by the climatic

conditions and anthropogenic factors.

Climatic factors

According to variation coefficient Cv and trend coefficient r,

the annual precipitation during 1982–2006 in the Yellow

River basin followed a decreasing trend (r¼�0�14) with a

moderate variability (Cv¼ 0�12), but a significant increasing

trend (r¼ 0�82) and weak variability (Cv¼ 0�04) were

detected for the annual average temperature (Figure 7).

Analysing the correlation between interannual NDVI and

the climatic factor indicated that the vegetation cover is

more sensitive to the temperature than precipitation, and the

correlation between annual NDVI and annual average

temperature in the whole Yellow River basin is significant at

the 95 per cent confidence level, using the Spearman

correlation R¼ 0�65. If the examination is focused-down to

the level of spatial pixel, it is found that the precipitation and

temperature influence the vegetation cover in a more

complicated manner (Figures 8,9 and 10). Generally, the

vegetation cover in the wind erosion region shows a positive

correlation with annual precipitation and negative corre-

lation with temperature (Figure 8). During the plant growth,

dryness is the great disadvantage in wind erosion region.

Warmer conditions might accelerated evapotranspiration,

especially in Spring and Summer, the higher temperature

aggravates the water deficiency, and as a result, suppresses

the growth of vegetation (Figure 9). Plentiful precipitation

will alleviate desertification, and afford water for growth. It

is found that the precipitation in Summer supports

vegetation and helps reduce wind erosion (Figure 10).

Compared with the wind erosion region, the reverse

phenomenon occurred in most of the freeze–thaw erosion

region. Along with the increasing temperature, the time

needed for thawing the frozen soil layer is shortened, and the

growing season is prolonged, which is beneficial to plant


growth, so the vegetation cover gave a positive correlation

with the annual temperature (Figures 8b and 9). However, a

negative correlation between the vegetation cover and

annual precipitation is abnormal (Figures 8a and 10). The

anomaly can be explained by the facts that (1) water

availability is not a critical limiting factor for vegetation

growth in the freeze–thaw erosion region. Water is relatively

plentiful in this region and the area of freeze–thaw is less

than 15 per cent of the whole Yellow River basin, but

contributes about 35 per cent of total water resources in the

basin (Zheng et al., 2009). (2)The types of land use in this

region are more sensitive to temperature and solar radiation

than precipitation. Alpine and subalpine grasslands occupy

the overwhelming majority of the land in the freeze–thaw

erosion region according to the IGBP DISCover dataset with

1 km resolution (Loveland et al., 2000). When compared

with the precipitation, it is reported that the temperature

and solar radiation play more significant effects during the

grassland growth (Yang et al., 2003). Consequently,

the increasing temperature and solar radiation facilitate

the vegetation cover in this region although the precipitation

is decreasing. (3) Part of precipitation in the freeze–thaw


Figure 8. Correlation between annual average NDVI and climate factors (1982–2000); (a) with annual precipitation, (b) with annual temperature. This figure isavailable in colour online at wileyonlinelibrary.com

Figure 9. The correlation between monthly NDVI and monthly average temperature. This figure is available in colour online at wileyonlinelibrary.com

Copyright # 2010 John Wiley & Sons, Ltd. LAND DEGRADATION & DEVELOPMENT, 23: 62–71 (2012)


Figure 10. The correlation between monthly NDVI and monthly precipitation. This figure is available in colour online at wileyonlinelibrary.com


erosion region falls in the form of snow. Generally, the

NDVI is expressed on a scale between �1 and + 1. GIMMS

NDVI ranges between �0�2 and 0�1 for snow, inland water

bodies, deserts and exposed soils, and increases from about

0�1 to 0�7 for increasing amounts of vegetation (Zhou et al.,

2001). In the freeze–thaw erosion region, part of precipi-

tation falls in the form of snow (Figure 6b), which influences

the calculation of NDVI to a certain extent. In particular the

affects the water erosion region. The four ellipse zones in

Figure 8 shows a reversed trend with the rest of water erosion

region. The ellipse zone belongs to the Fen-Wei basin, where

the relatively flat terrain was developed into irrigated

farming land. The irrigation area is more than 231�6 ha

(Yang et al., 2004), and according to the land use map of the

Yellow River basin, the crops planted there mainly include

paddy rice and winter wheat. Increasing temperature is

beneficial to crop growth (especially for winter wheat), so

there is positive correlation between yearly vegetation cover

and annual temperature (Figures 8b and 9). A leading

irrigation area in the Yellow River basin, the Fen-Wei River

basin is seldom dependant on precipitation, it is mainly

supplied from the upper reaches by watercourse. It was

estimated more than 50 per cent water of irrigation in the

Fen-Wei River basin comes from a diversion project

(YRCC, 2000), which channels the streamflow into crop-

lands. At the same time, the precipitation in the Fen-wei

River basin shows a declining trend over the past 20 years


(Zuo, 2006; Su et al., 2007). As a result, the seemingly

abnormal positive correlation appeared in the ellipse zone.

The rest of the region is mainly hilly and gully Loess

Plateau. It is influenced by desert wind erosion.

Anthropogenic factors

Cimate change is one of the most important factors

influencing Yellow River basin spatiotemporal variation

of vegetation. However, the impacts from human activities

should not be neglected. Social and economic factors, such

as national policy, people’s consciousness, agricultural

modernization, economic level and life style change, might

profoundly affect the vegetation (Vicente-Serrano et al.,

2004). According to the data from the State Forestry Bureau,

since the 1980s, the new area of forest planting has been

500� 104 hm2 per year in China. In the Yellow River basin,

new afforestation is estimated to have been 52�59� 104 hm2

during 1991–1999 (Yang et al., 2002).

It was found that the vegetation cover has increased

quickly since 2000; the rate far exceeds that in the period

1982–2000 (Figure 3). The temperature after 2000 in the

Yellow River basin has shown a decreasing trend (Figure 7).

So, the vegetation cover increased sharply since 2000 mainly

due to human factors. Indeed, the most effective impacts

from human activities has been the ‘Grain for Green’ (GFG)

programme, which was launched by the Chinese Govern-



ment at the end of 1999. The objective of this programme is

to increase the vegetation coverage on steep slopes by

planting trees or sowing grass on former cropland. Farmers

are encouraged to take land units on steep slopes out of

production and to plant trees. At the same time, farmers

participating in the GFG programme will be compensated

with free grain and cash payments. The tree seedlings are

provided for free by the Government. The GFG was

practiced experimentally in three provinces (Sichuan,

Shannxi, Gansu) in 1999, and has then popularized

Countrywide until 2002, which explains why the vegetation

cover increased quickly after it the minimum in 2000. The

total area of the GFG programme in the Yellow River basin

reached 8�27 million hectares during 1999–2006 (YRCC,

2008), which resulted in a significant increase of the

vegetation cover on farmland (Zhou et al., 2009).

CONCLUSIONS

The results of this study suggest that, under the dual effects

of natural conditions and human activities, the vegetation

cover in the wind erosion region is lowest, followed by the

freeze–thaw region and then by the water erosion region. So

the wind erosion region is the critical area for eco-

environment reconstruction. The interannual vegetation

cover dynamic shows a continued increase from 1982 to

2006 in the whole Yellow River basin, but it has a significant

spatial variation. The vegetation cover in the Fen River basin

shows a descending trend during 1982–2006, which reflects

the negative effects of human action. This area should be

singled-out for further eco-environment reconstruction

because the vegetation cover variation in the Yellow River

basin is greatly influenced by the water erosion region. In the

Yellow River basin, all the variation is weak or moderate,

and shows little variability (Cv< 0�1) can be recognized for

most of the area of the Yellow River basin.

Vegetation cover in the Yellow River basin is influenced

by climate factors, especially by temperature. In the wind

erosion region, warmer conditions might accelerate the

evapotranspiration and suppress growth, but plentiful

precipitation should alleviate any desertification. If there

is thawing in the frozen erosion region, increasing

temperature will prolong the plant growing season. In the

water erosion region, the vegetation cover in the Fen-wei

basin showed a negative correlation with annual precipi-

tation. The latter needs further study in the future. In the rest

of the area of the water erosion region high precipitation and

low temperatures will be helpful to plant growth. Besides the

effects of climatic factors, human activities contribute to the

vegetation cover variation. Especially after the implementa-

tion of the GFG, the role of human management in

increasing the vegetation cover is obvious.


ACKNOWLEDGEMENTS

Funding for this research was provided by the National

Natural Science Foundation of China (grant no. 41001153)

and State Key Laboratory of Earth Surface Processes and

Resource Ecology (grant no. 2009-KF-03). We are grateful

to the Yellow River Water Conservancy Commission

(YRCC) (China), the National Meteorological Information

Center (China), and the Flemish Institution (Belgium), for

permitting us access to data on soil erosion division map,

meteorological information, and vegetation cover related to

the Yellow River basin.

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the vegetation cover dynamics (1982–2006) in different erosion regions of the yellow river basin,...

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