Drought dynamics and impacts on vegetation in China from 1982 to

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Drought dynamics and impacts on vegetation in China from 1982to 2011

Honglin Wang a ,Aifang Chen a ,Qianfeng Wang b ,Bin He a ,*

Academy of College of Global Change and Earth System,Beijing Normal University,Beijing 100875,China

b Academy of Disaster Reduction and Emergency Management,Ministry of Civil Affairs and Ministry of Education,Beijing Normal University,Beijing 100875,China

A R T I C L E I N F O Article history:

Received 3July 2014

Received in revised form 20November 2014Accepted 29November 2014

Available online 15December 2014Keywords:

Climate change Drought SPI

Vegetation NDVI

Growing season China

A B S T R A C T

We investigated the drought dynamics and their impacts on vegetation change in China from 1982to 2011using the standard precipitation index (SPI)and the normalized difference vegetation index (NDVI)anomaly,which were calculated from meteorological and satellite-derived NDVI data,respectively.The trends in the change of SPI and vegetation were explored based on the non-parametric Mann –Kendall (MK)test and Sen ’s slope test,and the relationship between these trends was examined.The results were as follows:(1)For China as a whole,although the long term trend of drought-impacted areas changed little (à0.045%/10a)over the past 30years,Dry trends were identi ?ed in northeastern and southwestern China.(2)The annual vegetation growth at the national scale showed an increasing trend,with a rate of 0.008%/10a from 1982to 2011;cropland vegetation presented the largest increase in NDVI (p <0.05).(3)Droughts that occurred during the growing season and pre-growing season both had large negative impacts on vegetation growth,and signi ?cant in ?uences were found in northern China,especially in the northwestern https://www.360docs.net/doc/ec8621627.html,pared to the northern areas,the NDVI in southern China appeared to bene ?t from warming temperatures.

1.Introduction

Many parts of the world have suffered from serious droughts in recent years,which have greatly impacted socio –economic systems and the environment (IPCC,2001).Major drought events have raised the question of whether droughts are becoming more frequent and more severe,as projected by climate change studies (Zhao and Running,2010).Another concern is whether drought,which is one of the major disturbances to vegetation growth,may weaken the ability of vegetation to function as a carbon sink (Xu et al.,2011).For the improved understanding of the vulnerability of the terrestrial carbon cycle and the sustainable use of natural vegetation resources (Xu et al.,2012),it is of particular importance to understand and assess the consequences of drought on vegetation at different scales.

The impacts of drought on vegetation have been extensively studied on regional and global scales.For instance,a recent study indicated that droughts are counteracting the increase in global net primary productivity (NPP)caused by global warming (Zhao and

Running,2010).On a regional scale,the severe 2003drought in Europe caused great impacts on a variety of land-cover types,and most ecosystems recovered to a normal state by early 2004(Gobron et al.,2005).Rainforests in the Amazon region play an important role in the global carbon cycle,and extreme droughts in this region in 2010seemed to cause a signi ?cant increase in tree mortality and carbon losses (Xu et al.,2011).Thus,serious droughts are causing adverse effects on terrestrial ecosystems.

Vegetation growth has signi ?cantly increased over the last three decades in China (He et al.,2007).This can be mainly attributed to national warming and ecological conservation projects,such as the Three-North Shelter Forest Program (TNSFP)(Duan et al.,2011),the Beijing –Tianjin Sand Source Control Program (Wu et al.,2013),the Grain for Green Project (Zhang et al.,2012a ),and small-scale regional ecological engineering (Huang et al.,2012).During the 20th century,China experienced a series of drought events (Xiao et al.,2009),and the increasing drought stress associated with warming and reduced rainfall was found to contribute to the decrease in the growing season ’s normalized difference vegetation index (NDVI)in northern China after the 1990s (Peng et al.,2011).In 2010,southwest China suffered a severe and sustained spring drought,which reduced the regional annual gross primary productivity (GPP)and NPP by 65and 45Tg

*Corresponding author.Tel.:+86158********.E-mail address:hebin@https://www.360docs.net/doc/ec8621627.html, (B.He).https://www.360docs.net/doc/ec8621627.html,/10.1016/j.ecoleng.2014.11.063

Ecological Engineering 75(2015)303–307

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Ecological Engineering

j o u r n a l h o m e p a g e :w w w.e l s e v i e r.c o m /l o c a t e /e c o l e n

C/a,respectively,and both the annual GPP and NPP in2010were the lowest during the period of2000–2010(Zhang et al.,2012b). Obviously,drought has become one of the most important disturbances to vegetation growth in China.Furthermore,droughts lower the water levels of rivers,reservoirs,and lakes,which limits water availability for ecosystem and agricultural production and leads to ecological degradation and reduced food productivity (Piao et al.,2010;Zhang et al.,2012b;Yu et al.,2013).

Although previous studies have provided much information on the relationship between drought and vegetation growth, many efforts mainly focused on the impacts of single drought events were concentrated on a regional scale.In addition,the responses of vegetation to drought during the growing and non-growing seasons are still not clear.Our main goal is to explore the drought dynamics in China and their impacts on vegetation from1982to2011.Firstly,the spatial-temporal characteristics of drought are analyzed based on drought area and the trend of drought index.Secondly,the relationships between drought variations and vegetation growth are used to explore how a drought will impact vegetation growth.Our results will provide scienti?c information for drought prediction and forest management in China.

2.Datasets and methods

2.1.Datasets

The monthly precipitation(mm)data from1982–2011at 752meteorological stations in China were collected from the China Meteorological Data Sharing Service.To avoid the possible effects of arti?cial shifts in the data caused by the relocations of measurement sites and equipment observation error,the meteorological data were checked for homogeneity with reference to a previously used method(Ren et al.,2008).Stations with less than30years of data were also rejected(Yu et al.,2013).A total of 603stations were selected for this study according to the data availability criteria in China.

The NDVI is usually used for measuring vegetation growth.In this study,we used the National Oceanic and Atmospheric Administration/Advanced Very High Resolution Radiometer (NOAA/AVHRR)NDVI dataset,which was produced by Global Inventory Modeling and Mapping Studies(GIMMS)(Tucker et al., 2005).The dataset spans the period from1982–2011and has a 0.083 spatial resolution and a15-day interval.The GIMMS NDVI has been corrected to remove non-vegetation effects,including sensor degradation,inter-satellite differences,and volcanic aerosol effects(Zhou et al.,2001).The monthly NDVI was derived from two images from each month using the maximum value composite (MVC)method(Holben1986).Our analysis was mainly con?ned to the growing season,which was de?ned as April–October and was constantly applied across the whole country(Zhou et al.,2001). Based on vegetation maps with a scale of1:1,000,000from the Atlas of China's Vegetation,the vegetation was classi?ed into four types:forest,shrub,grassland,and cropland(Zhao et al., 2011).

2.2.Methods

The standardized precipitation index(SPI)(McKee et al.,1993) was selected to assess drought variations in China.The SPI is a widely used drought index,which is derived from precipitation data alone to determine a water de?cit and surplus and can be calculated for short or long time scales(Paulo et al.,2003).The multi-time scale SPI allowed us to analyze the relationship between drought and vegetation at various time scales.The criteria for drought classi?cation was referenced in McKee's study (McKee et al.,1993).

The non-parametric Mann–Kendall(MK)test was applied for the SPI trend tests.The MK test is a rank-based procedure, which is suitable for detecting non-linear trends(Kendall,1975). It is frequently used for detecting trends in hydrological and meteorological time series(Hamed,2008). Con?dence probabilities of95%(p<0.05)was considered to be signi?cant.

The Sen slope estimator was applied to obtain the trend in vegetation growth from1982to2011(Sen,1968).This estimation did not require the data to be distributed normally and has been widely applied in vegetation growth studies(Fernandes and Leblanc,2005).

The bilinear interpolation method was used to extract the NDVI values for the station data based on grid vegetation data with a spatial resolution of0.083 (Vu et al.,2012).The monthly NDVI sequence data were generated at station in China and spans the period from1982to2011.Finally,the Pearson correlation analysis was used to explore the relationship between the NDVI anomaly and drought(SPI less thanà1.0)(Madden and Williams,1978; Trenberth and Shea,2005).The data processing and calculations were conducted with the Interactive Data Language(IDL)program and the ArcGIS9.3software.

3.Results

3.1.Temporal and spatial characteristics of drought

The inter-annual variation in the percentage of drought-impacted areas(SPI of less thanà1.0)in China from1982–2011are shown in Fig.1(a).Relatively large dry areas occurred in the middle of the1980s,the late1990s,the early2000s,and the most recent1–2years.The largest drought-impacted area percentage(27.69%)occurred in1986and represented approxi-mately one-quarter of China's total territory.This value was followed by26.07%in2001,25.1%in1997,and22.51%in2011. Despite the large inter-annual variability,the long-term trends in the drought-impacted areas in China as a whole decreased slightly (by0.045%/10a)over the past30years.

The annual trends of SPI for each station in China were also investigated based on the MK test.The positive and negative results indicated trends towards wetter and drier conditions, respectively(Fig.1(b)).The SPI trends showed great spatial variability.Dry trends were identi?ed in northeastern and southwestern China,but signi?cant wet trends were detected in western China.

3.2.Trends in vegetation growth over the past3decades

Inter-annual variations in the NDVI for different vegetation types are shown in Fig.2(a).The NDVI increased remarkably for all vegetation types(p<0.05).The largest increases appeared in croplands and shrubs,with values of0.015/10a and0.01/10a respectively,followed by0.007/10a for grasslands and0.006/10a for forests.At the national scale,the average NVDI for all annual vegetation in China demonstrated a signi?cant increasing trend, with a rate of0.007/10a.The annual NDVI trend patterns were dramatically spatially heterogeneous(Fig.2(b)).Signi?cant increasing trends in vegetation growth occurred in central,eastern, and southern China,and signi?cant decreasing trends occurred in the northwestern and northeastern areas and some parts of the southwestern area.

304H.Wang et al./Ecological Engineering75(2015)303–307

3.3.Relationship between drought and vegetation

To assess the impact of droughts occurring in the growing season(April–October)and pre-growing season(November of the previous year to March)on vegetation,we calculated the relationships between the growing season SPI and NDVI anomaly, and between the pre-growing season SPI and growing season NDVI anomaly respectively,as shown in Fig.3.For both conditions, signi?cant positive relationships mainly occurred in the north-western and northern areas of China,which are arid and semi-arid regions.This indicated that droughts occurring during the growing season or pre-growing season should have large adverse impacts on vegetation growth.In addition,more stations had signi?cant positive relationships between growing season SPI and NDVI compared with the pre-growing season(60vs.48).This indicated that droughts occurring in the growing season might have more serious in?uences on vegetation growth than those occurring in the pre-growing season.It is worthy to note that the vegetation in northeastern China is very sensitive to pre-growing season drought,but it is less sensitive to growing season drought.

4.Discussion

The trends in the drought-impacted areas showed slight changes and were essentially consistent with the results calculated using Palmer Drought Severity Index(PDSI),which presented an increasing trend of0.50%/10a from1951to2003(Zou,2005). However,a signi?cant upward trend with a rate of3.7%/10a from 1951to2010(Yu et al.,2013)was revealed based on another widely used drought index,the Standardized Precipitation Evapotranspi-ration Index(SPEI).Through investigating the trend in the SPI,we found that dry trends occurred in the northeast and southwest regions of China,which were similar to the areas that experienced precipitation decreases(Yu et al.,2013).The SPI values were calculated solely based on precipitation data;thus,the environ-mental factors that impact the distribution of precipitation, including latitude,longitude,and topography,may also have an in?uence on the spatial patterns of the SPI(Zhai et al.,2005;Zhang and Feng,2010).

A signi?cant increasing trend in the annual vegetation growth in China was found in our study.This result was similar to that of Peng's study,in which the growing season(April–October)NDVI was found to signi?cantly increase by0.0007yearà1from1982to 2010on a national scale(Peng et al.,2011).The spatial patterns of vegetation growth changes were generally consistent with other ?ndings on vegetation changes in China(He et al.,2007;Xu et al., 2012).In northern China,the vegetation growth displayed a decreasing trend,which was attributed to warming temperatures and the related increasing evapotranspiration rates and soil water de?cits(Duan et al.,2011).The relationship between the growing season NDVI and temperature anomalies is shown in Fig.4.The high negative correlations mainly in the north indicated that

Fig.1.Percentage of drought-impacted areas(a)and annual SPI trends from1982to2011(b).

Fig.2.Inter-annual variations of annual NDVI(a)and the spatial distribution of annual NDVI trends(b)for1982–2011.

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increasing temperatures could lead to adverse effects on vegeta-tion growth.However,increasing trends in NDVI were also found in small parts of North China,such as the western part of Inner Mongolia.The possible reasons for this observation are the following:(1)the negative effects of increasing temperature on vegetation growth were offset by increasing precipitation;(2)the encroachment of trees and shrubs into grasslands that are affected by climate,soil formations,and other factors promoted vegetation growth,and thus affected the aboveground net primary produc-tivity(ANPP)and ecosystem carbon(C)and nitrogen(N)pools (Huang et al.,2012);(3)ecological engineering bene?ted vegeta-tion growth in this region(Peng et al.,2011).Increasing trends in vegetation were observed in southern China.A widely accepted viewpoint is that vegetation in this region is mainly controlled by temperature.Warming temperatures have prolonged the growing season,improved photosynthetic ef?ciency,and increased vege-tation productivity(Duan et al.,2011).As shown in Fig.4,higher positive correlations were mainly found in the south.

Signi?cant positive correlations between the SPI and NDVI anomaly were identi?ed for both the growing and pre-growing seasons in north China(Wang et al.,2010),implying that vegetation growth was affected not only by the growing season precipitation de?cit,but also by the pre-growing season drought conditions.These results are not dif?cult to understand,as many previous studies assert that precipitation is the main factor limiting vegetation growth(Zhao et al.,2011).Although the vegetation could be restored to a normal status after the end of a drought(Zhang et al.,2012b),but long duration and frequent droughts will inevitably lead to the vegetation degradation. Signi?cant negative correlations between the SPI and NDVI anomaly occurred in the southern region,indicating that the precipitation de?cits favored vegetation growth.This was mainly due to the resilience and restorability of vegetation to drought stress.Previous studies have con?rmed that resilience of vegeta-tion to drought stress is stronger in humid regions than in other regions(Vicente-Serrano et al.,2013).In addition,the cloud coverage in southern China is markedly larger than that in northern China(less cloud coverage for more solar radiation)(He et al.,2007).During drought periods the increased radiation due to decreasing cloud coverage may promote vegetation growth (Saleska et al.,2007).

Overall,drought is an important disturbance to vegetation growth in China,especially for North China.Other factors, including the in?uence of climate change,ecological engineering, the resilience and restorability of vegetation,the encroachment of other biome types,etc.,contribute to the complex interaction processes of vegetation growth and drought.

5.Conclusion

We conclude that the variation trends in drought-impacted areas were slight(à0.045%/10a)during1982–2011;droughts occurring during the growing season and pre-growing season both had great impacts on the NDVI;and a signi?cant in?uence of drought on vegetation was found in northern China,especially in the northwest.Our study on drought dynamics in China can guide agricultural production for the continued development of adapta-tion strategies to protect vulnerable ecosystems and to ensure agricultural security.The?ndings on the relationship between drought and vegetation growth can also provide a vital scienti?c basis for China's drought predication and forest management.

Acknowledgments

This work was?nancially supported by the National Basic Research Development Program of China(grant no. 2012CB95570001and2011CB952001)and the National Natural Science Foundation of China(grant no.41301076)and the State Key Program of National Natural Science of China (grant no.41330527).

Fig.3.The relationship between growing season(April–October)SPI and NDVI(a)and between the pre-growing season SPI(November of the previous year to March)and growing season NDVI anomaly(b).

Fig.4.Correlation between growing season NDVI and temperature anomalies.

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