A statistical analysis of spatiotemporal variations and determinant factors of forest carbon storage under China’s Natural Forest Protection Program

Shengnan Wu•Jiaqi Li•Wangming Zhou•Bernard Joseph Lewis•Dapao Yu•Li Zhou•Linhai Jiang•Limin Dai

Introduction

By virtue of its spatial scale,China’s Natural Forest Protection Program is one of the most signi fi cant actions in protecting and recovering forests globally.It regulates the direction of forest resource management and promotes the preservation,cultivation,and development of natural forest resources through reclassi fi cation and rezoning of natural forests.The program prohibits commercial logging in natural forests along the upper reaches of the Yangtze River and the upper and middle reaches of the Yellow River.It mandates large-scale reductions in the timber yield of state-owned forests in the above-mentioned areas and in Inner Mongolia.It accelerates forestation on treeless hills and lands where forestation is practicable.Based on pilot projects in 12 provinces,autonomous regions,and municipalities since 1998,this program was of fi cially launched in 17 provinces,autonomous regions,and municipalities in 2000.The whole program covers all the key state-owned forests in the upper reaches of the Yangtze River,the upper and middle reaches of the Yellow River,and key state-owned forest regions in northeast China and Inner Mongolia.Natural forests in those protected areas cover 73.3 million ha,representing 69% of the total area of China,which is 106.7 million ha(Zhang et al.2000;Hu and Liu 2006).

Literature on the program has addressed its in fl uence on forest resources(Cao et al.2010;Zhang et al.2011),social economy(Edstrom et al.2012),regional landscape patterns(Luo et al.2010;Yu et al.2011),regional ecological recovery(Horst et al.2005;Wu et al.2011;Ren et al.2015),and ecosystem services(Liu et al.2008).Studies on vegetation carbon storage have concentrated on the decline in commercial timber yield(Hu and Liu 2006),arti fi cial forestation(Zhou et al.2014),natural forest cultivation and management(Zhang et al.2011),and natural regeneration of forest vegetation(Wei et al.2013).The program encompasses different regional engineering measures and forest management activities and these different factors contribute differently to local carbon storage.So it is necessary to analyze the in fl uence of different regional management measures on the carbon storage of vegetation and its contribution(Xu 2011).

The vector autoregressive(VAR)model is a method for the analysis of many interrelated variables.In this method,every endogenous variable is treated as function of lagged values of all endogenous variables in the system,thus the single variable regression model is extended to the VAR model of multivariate time series variables.The method can be used to analyze and forecast the mutual impacts between variables in the system,and enabling the determination of leading and potential factors and quantifying their in fl uence(Gao 2006;Cui and Wang 2010).

Vector autoregression(VAR)is a unique model to analyze the linear interdependencies among multiple variables.In a VAR analysis,VAR model treats each endogenous variable as the function of lagged values of all endogenous variables in the system.Thus,simple linear regression model is extended to VAR model which is composed of multiple time series variables.Such method could forecast inter-association among time series systems,and investigate dynamic impacts of random perturbations on variable systems,consequently quantifying their respective effects.

In this article,forest inventory data were used to calculate the carbon storage of forest vegetation.With natural and non-natural factors that have signi fi cant in fl uence on forest resources as variables,the VAR model was used to explore dynamic relations among temperature,precipitation,timber harvest,pest-infected areas, fi re-damaged areas,areas of cultivated forest,reforested areas,and carbon storage.The purposes of this article are to(1)reveal changing features of the vegetation carbon sink function in the area covered by the program,and(2)determine the identity and contribution of the dominant factors responsible for the regional difference of carbon storage.

Materials and methods

The Natural Forest Protection Program covers parts of the upper reaches of the Yangtze River,the upper and middle reaches of the Yellow River,and key state-owned forest regions in northeast China and Inner Mongolia,involving 17 provinces,autonomous regions,and municipalities(Fig.1).Among the three major regions,the program in the upper reaches of the Yangtze River has its boundary at the Three Gorges reservoir area and covers Hubei,Chongqing,Sichuan,Guizhou,Yunnan,and Tibet.The program in the upper and middle reaches of the Yellow River has its boundary at the Xiaolangdi Reservoir area and covers Henan,Shaanxi,Shanxi,Inner Mongolia(non-state-owned forests),Ningxia,Gansu,and Qinghai.The program in Northeast China and Inner Mongolia covers Heilongjiang,Jilin,Inner Mongolia(state-owned forests),Xinjiang,and Hainan(Zhang et al.2000).

Fig.1 Distribution of the Natural Forest Protection Program in 17 provinces,autonomous regions,and municipalities of China

Seven groups of national forest inventory data(State Forestry Administration of the People’s Republic of China)from 1977 to 2013(1977–1981,1984–1988,1989–1993,1994–1998,1999–2003,2004–2008,and 2009–2013)were used to calculate provincial carbon storage and carbon density.The de fi nition of ‘forest’used by the national forest inventory after 1994 changed such that after 1994,‘forest’was de fi ned as stands of trees with crown density＞20%.Prior to 1994,the threshold was＞30%.To avoid the in fl uence of this change on our analyses,the inventory data of 1999–2003 were used to establish a method at the provincial level to calibrate statistics before 1994.Statistics on timber harvest and areas of pest-infestation, fi re-damage,cultivated forest,and reforestation were taken from theChina Forestry Statistical Yearbookfrom 1977 to 2013(State Forestry Administration).

We used the continuous biomass expansion factor(BEF)method to calculate the biomass density of various forest types in each inventory period.The area and stock data of each forest type at various ages were used to calculate the stock density.Biomass density was then calculated with the continuous BEF method.In this study,biomass density referred to the average biomass density of a forest type in a given age group;the carbon conversion coef fi cient was 0.5(Fang et al.2001).

The econometrical analysis software EVIEWS 6.0 was used to establish the VAR model for vegetation carbon storage and such factors as temperature,precipitation,forest pests,timber harvest,forest fi res,forest cultivation,and reforestation to simulate the in fl uence of these factors on carbon storage.To avoid potential heteroscedasticity among variables,natural logarithms of carbon storage,pest-infected area,timber harvest,reforestation area, fi redamaged area,cultivated area,and mean annual temperature and precipitation were used to establish the model for our study.If the variables are fi rst order integration in the stationary test,the variables were simpli fi ed to carbon stocking,timber harvest,reforestation area,cultivated forest area, fi re area,pest area,temperature,and precipitation.Then the response curve for carbon storage after the impact of each factor was simulated through an impulse response and we determined whether the in fl uence of each factor was positive or negative.Variance decomposition was also performed to quantify the in fl uence of these factors,and to evaluate the dominant factors that affect carbon storage in different areas covered by the program(Xu 2011;Wu et al.2015).

We found a lack of statistics concerning fi re-damaged areas in Ningxia and Qinghai,and the pest-infected and areas of cultivated forest in Tibet from 1980 to 2010.Accordingly,the calculation result for these three provinces excluded these factors.In addition,the time span required by this model is longer than 30 years.Chongqing,however,did not separate from Sichuan Province as a municipality until 1997.So Chongqing’s statistics were merged into those of Sichuan before they were employed in the model.Hainan Province had statistics only from 1988 to 2013,so it did not ful fi ll the requirement of the model and is,therefore,not discussed here.

Results

Changes in the vegetation carbon sink of protected areas

Vegetation carbon storage and carbon density in the three NFPP areas(or protected areas)had obvious spatiotemporal variations(Table 1).The vegetation carbon storage in the upper reaches of the Yangtze River was relatively high,representing 35–47.5% of the total in all protected areas.In contrast,the carbon storage in the upper and middle reaches of the Yellow River was relatively low,representing 22.3–26.3% of the total.The total vegetation carbon storage in all protected areas increased from～3900 Tg C in 1977–1981 to ～6000 Tg C in 2009–2013,increasing by～2100 Tg C with an annual growth rate of 59.86 Tg C a-1.The annual growth rates of the upper and middle reaches of the Yellow River,the upper reaches of the Yangtze River,and key state-owned forest regions were 13.3,39.8,and 6.9 Tg C a-1,respectively(Fig.2).These results indicate that the vegetation in the upper reaches of the Yangtze River had the greatest carbon sink capacity.The vegetation carbon sink capacity changed over the time periods studied.Although the whole area under the NFPP functioned as a carbon source from 1984 to 1988(-5.26 Tg C a-1),it served as a carbon sink during other inventory periods.The minimum carbon sink(4.79 Tg C a-1)occurred in 1989–1993,while the maximum carbon sink(160.23 Tg C a-1)occurred in 1999–2003.

Implementation of the program correlates with large changes in carbon sequestration values,which increased 12.3 times from 1994–1998 to 1989–1993.Before the implementation of the program(1977–1998),the vegetation carbon pool increased at the upper and middle reaches of the Yellow River and the upper reaches of the Yangtze River,while it decreased in the state-owned forest regions of northeast China and Inner Mongolia.After the implementation of the program(1999–2013),increase was seen in every protected area.Compared to the period before the program,the vegetation carbon pool of the upper and middle reaches of the Yellow River,the upper reaches of the Yangtze River,the state-owned forest regions of northeast China and Inner Mongolia,and the entire NFPP area increased by 324.5,745.3,474.3,and 1544.0 Tg C,respectively(Fig.3).

The vegetation carbon density of individual protected areas ranged from 35.31 to 58.93 Mg C/ha.Speci fi cally,the vegetation carbon density of the upper and middle reaches of the Yellow River displayed a tendency to increase,while that of the upper reaches of the Yangtze River and the state-owned forest regions of northeast China and Inner Mongolia decreased initially and then increased.In total,after the implementation of the program,the vegetation carbon density of all protected areas showed an increase(Fig.4).

ectively resp density,ass carbon storage and biom on ass carb D represent biom S and BC The BC areas.C ha-1)in NFPP density(Mg on and carb C)storage(Tg on carb ble 1 Vegetation Ta D 013 BC 2009–2 S BC D 04–2008 BC 20 S BC D 3 BC 99–200 19 S BC D–1998 BC 1994 S BC D 3 89–199 BC 19 S BC D 84–1988 BC 19 S BC D–1981 BC 1977 S BC Area.5 49 43 29 44 35 28 4453.4.5.1.8.8.8.5 54.1 100.0.3 35 57 36 60 71 5638.9.7.8.8.2.3 55 58.9.9 2.5 1216.4 4.7 1.6 28 9.3 1060.5 3.7 78 1378.7 4.9 75 848.9 202.2 884.0 176.5 2804.7 541.3 1037.7 122.4 54.2 1755.7 54.2 51.1 35.6 46.3 33.3 30.9 40.0 41.2 53.0 1.2.7 28 54 32.2.6.1 69 51 59.1.5.3.0 10 65 60.2 57 115.7 18.1 4.0 262.3 94.3 53.2 672.6 20.1 12713.4 851.2 145.7 798.7 129.8 89.6 25502.3 985.2 110.5 50.7 48.7 16 53.2 8 49.3 35.7 44.2 32.1 28.0 39.5 40.2 51.4 1.0 1022.8 50.0 25.3 57.1 66.7 47.5 66.3 57.2 53.8 2.1 6 1016.9 3.3 4.8 2263.5 45.0 634.4 89.9 5.6 2.7 8.6 4.2 47 85 64 8594.8 6787.1 21.3 0.7 3.10 23 1051.0 1479.5 52.5 49.4 37.5 44.6 29.4 28.1 39.8 40.5 49.0 97.0 20.7 49.0 24.2 49.2 64.9 45.4 57.3 56.6 51.5 100.8.1 153.8 219.4.0 44 41.3 553.5 977.9 586.4 395.9.6 82 578.5.1 73.5 1716 454.2 796.2.5 98 46.3.1 1395 48.2 38.0 22.8 42.2 22.1 2356.9.2 36.9 47.0 93.4 16.8 61.9 20.7 38.5 65.7 43.7 53.4 48.4 50.1 5.4 1015.7 5.0 1.7 2236.9 36.8 569.5 1.0 99 58 441.1 9.1 68.4 2.6 5356.2 18.4 7.8 49 838.1 13 85.3 40.6 61.8 14 42.3 37.6 23.6 40.4 27.0 24.5 35.4 36.0 37.7 66.6 16.6 54.7 36.6 43.8 60.1 44.6 45.7 31.2 48.3 102.7.1 8 165.9 212.6.8 42.8 28 547.0 955.7 442.253.3 65.1 562.2 89.0 12.3 14447.0 825.1 83.3 23.9 79.3 13 45.2 30.4 25.1 41.2 24.8 25.3 33.8 35.3 55.0 72.5 15.9 49.4 37.5 48.4 64.6 52.2 66.4 56.3.3 98 10.5 5.6 207.7.4 35 24.3 9.8.6.3.7.1.8 51 901.6 424.6 275.7 61 515.5 96 1373 468.8 948.0 92 1508 ing olia Chongq Gansu hai Qing xia Ning Shaanxi Henan xi Shan ner Mong an InTotal Sichuan+Tibet Hubei Yunnan Guizhou Total Jilin Heilongjiang Xinjiang Hain Total reaches per and middleRiver the ned forest Upofthe Yellow per reaches of UpYangtze River Key state-ow region

Fig.2 Carbon sink values of different protected areas in various periods.The UMYR,UYR,KSFR and NFPP represent the upper reaches of the Yangtze River,key state-owned forest regions,the upper and middle reaches of the Yellow River,and the Natural Forest Protection Program,respectively

Fig.3 Changes in vegetation carbon pool before and after the implementation of the Natural Forest Protection Program.The UMYR,UYR,KSFR and NFPP represent the upper reaches of the Yangtze River,key state-owned forest regions,the upper and middle reaches of the Yellow River,and the Natural Forest Protection Program,respectively

Fig.4 Vegetation carbon density of various protected areas in various periods.The UMYR,UYR and KSFR represent the upper reaches of the Yangtze River,key state-owned forest regions,and the upper and middle reaches of the Yellow River,respectively

Factors that in fl uenced vegetation carbon storageimpulse response

Impulse response is one of the important dynamic features of the VAR model.It depicts the changing in fl uence or impact of each variable on itself and the other variables.It also displays each factor’s process of in fl uence and the positive and negative properties of that in fl uence by means of the impulse-response diagram(Zhu et al.2005;Zhang 2012).The model passed a variable stationary test(augmented Dickey-Fuller or ADF,test),a lag order test,a cointegration test,and an eigenvalue test,displaying a stable state overall.These results indicate that analysis by the VAR model is tenable.

Judging from the impulse response of these three protected areas,some factors exerted a positive impact on the carbon storage of forests,while others exerted a negative impact.The response curve of carbon storage to the impact of each factor fl uctuated within various ranges,but the overall trend remained the same(Fig.5).The track of the carbon storage response to itself,DLNCARBON,displayed a continuous decreasing trend,suggesting that the in fl uence of carbon storage on itself becomes increasingly smaller.The changing response to the impact of forest pests,DLNPEST, fl uctuated mostly below the abscissa,indicating that forest pests hindered the accumulation of carbon.Timber harvest also exerted an apparent negative impact on carbon storage;this is consistent with the conclusion that increasing timber harvests will contribute to the decrease of forest carbon storage.Although forestation had a positive in fl uence on carbon storage,the corresponding response curve,DLNREFOREST, fl uctuated within a small range below the abscissa.This positive in fl uence was much weaker than the negative in fl uence of timber harvest.In addition,forest cultivation in the stateowned forest regions had a strongly positive effect;forest fi re,temperature,and precipitation had little in fl uence on carbon storage.

Fig.5 Impulse-response curve of vegetation carbon storage in the upper reaches of the Yangtze River,key state-owned forest regions,and the upper and middle reaches of the Yellow River.Note(1)The letters a,b,and c represent the upper reaches of the Yangtze River,key state-owned forest regions,and the upper and middle reaches of the Yellow River,respectively;(2)the X-axis represents the lag period of impact and the Y-axis represents change in the value of carbon storage(DLNCARBON).The part above the horizontal axis represents a positive in fl uence,while the part below it represents negative in fl uence

Comparison of factors that in fl uence carbon storage in the various provinces,autonomous regions,and municipalities

Impulse response depicted the positive and negative effects of various factors on carbon storage,while variance decomposition enabled further analysis of the degree to which the factors in fl uenced the process of forest carbon storage.Through variance decomposition of DLNCARBON,we determined the dominant factors of vegetation carbon storage in the various provinces,autonomous regions,and municipalities covered by the program.

The results of variance-decomposition analysis are represented by percentage;the sum of the results of all in fl uencing factors in each province,autonomous region,or municipality is 100%.In Gansu Province,for example,the contribution of the vegetation itself,timber harvest,reforestation,forest cultivation,forest fi re,forest pests,average annualtemperature,and annualprecipitation to the increase of forest carbon storage represented 49,34,5,1,1,6.6,3,and 0.4%,respectively,with the sum of contributing factors being 100%(Table 2).

The dominant factor in fl uencing carbon storage in the upper and middle reaches of the Yellow River was timber harvest.In the upper reaches of the Yangtze River the dominant factor was forest pests.In the key state-owned forest regions the dominant factor was timber harvest.The degrees of in fl uence of these three dominant factors were 11.78,15.99,and 20.23%,respectively,much higher than those of the other factors.In key state-owned regions,however,forestation contributed the same to carbon storage as did timber harvest,with an in fl uence degree of 19.11%,far higher than those of the remaining factors.Forestation is therefore also identi fi ed as a dominant factor in key state-owned forest regions.

Within the upper and middle reaches of the Yellow River,timber harvest was the dominant factor in Gansu,Inner Mongolia,and Shanxi,with in fl uence degrees of 33.78,15.11,and 16.84%respectively.In Ningxia,the in fl uence degrees of forest cultivation and forest pests were 17.48 and 14.78%,respectively,much higher than those of other factors.These two factors were therefore regarded as dominant factors in Ningxia.No individual factor exerted a dominant in fl uence on carbon storage in Henan,Qinghai,or Shaanxi.The principal factors in these three provinces were assumed to be forestation and forest pests,precipitation and forest cultivation,forest pests and forest fi re.

Table 2 Variance decomposition of DLNTAN

In key state-owned forest regions,the dominant factors in fl uencing carbon storage were timber harvestand forestation in Jilin and timber harvest in Heilongjiang.These two provinces had the same dominant factors as the whole forest region.In Xinjiang,however,the dominant factor was forest pests,with an in fl uence degree of 39.61%.

Within the upper reaches of the Yangtze River,the dominant factor was either forest pests or forest cultivation in Guizhou,Hubei,and Sichuan,consistent with results for the whole area.Forest fi re was the dominant factor in fl uencing carbon storage in Tibet,with the in fl uence degree of 66.94%.In Yunnan,forestation had a relatively high in fl uence degree of 5.94%,although other factors contributed similarly to carbon storage.

Discussion

Effect of the Natural Forest Protection Program on the carbon sink function of forest ecosystems in China

Early studies found that the biomass carbon sink of forest stands in China was 75.2 Tg C a-1in 1977–2003(Fang et al.2007)and 70.2 Tg C a-1in 1977–2008(Guo et al.2013);both of these estimates exceed the results of our study.The main reason could be that before the implementation of the program,the stateowned forest regions were important timber production bases in China and these were treated as carbon sources in 1998(Fig.3).But 5–10 years after the program was implemented,the vegetation carbon density there gradually returned to 1977 levels(Fig.4).Among the three areas under the program,the carbon sink function of the key state-owned forest region was the lowest from 1977 to 2013(6.86 Tg C a-1)(Fig.2).After the implementation of the program,the vegetation carbon storage in the whole area covered by the program increased signi fi cantly,and each protected area served as a carbon sink(Table 1;Fig.3).

Data from the 8th forest inventory showed that the area of forests and natural forests protected by this program(87.68 million ha and 59.97 million ha,respectively)represented 45%and 50% of the total forest area in China,respectively.Natural forests are the major areas where vegetation carbon is stored in protected areas,with the carbon storage there representing 96% of the total(Guo et al.2013).Strengthening natural forest management and improving stand quality will play important roles in the increase of forest carbon sequestration in the future(Hu and Liu 2006).

As China’s largest exercise in forestry ecological engineering,NFPP promotes the effective protection and restoration of China’s forest resources and the transfer of timber production from cutting and utilization of natural forests to management and utilization of planted forests.It also promotes the restoration of forest ecological bene fi ts and functions,and the establishment of complete forest ecosystems,along with a reasonable system for forest industry.

Effect of management measures on the vegetation carbon sink in protected areas

Regional differences in the dominant in fl uence factor for carbon storage were closely related to forest resources,ecological environments,forest management policies,and the implementation of forest management activities in the various areas.The Yellow and Yangtze River basins have suffered serious soil erosion,and local forest resources have been severely damaged due to deforestation,steepslope reclamation,and long-term excessive felling(Xie and Zhang 2002).The carbon storage of forest vegetation has therefore been greatly affected.The VAR model outputs con fi rm that timber harvest was the dominant factor in fl uencing carbon storage in these two basins.

As one of China’s six major forest regions,the key stateowned forest region in Jilin Province is an important forestry base for China.The advantages of forest resource endowment provide conditions for the development of forest carbon sequestration in Jilin Province(Chen et al.2011).The average stock per hectare of state-owned forest of the Jilin Forest Industry Group,however,is just 139.5 m3.Although that is much higher than the national average of about 70 m3,it still represents a big gap from the level of 260–300 m3in developed countries(Li 2012).In addition,the area of young and middle-aged forests continuously increases,which will directly in fl uence the total forest stock and the role of carbon sequestration(Wang et al.2011).Strengthening young and middle-aged forest cultivation and improving forest quality have therefore become primary tasks for forest resource recovery and improvement of carbon sequestration capacity in the stateowned forest region in Jilin.

For Heilongjiang,Yunnan,and Inner Mongolia,which are prone to forest fi re,their carbon-containing gas emissions(i.e., fi re-damaged area)represented more than 80% of the national total.The fi re-damaged area of Heilongjiang ranked fi rst of these provinces and its area at highest risk of forest fi res was the Daxing’anling region(Wang et al.2001).The forest region of Heilongjiang is a main carbon sink region for China.Due to the effects of its temperate and cold-temperate monsoon climate,there is a high frequency of forest fi re and almost no forest escaped the effects of fi re.In addition,the rate of disastrous fi res in the forest region is high,especially that of huge forest fi res,which was far higher than the national average(Xu 1998).Forest fi re is the dominant factor in fl uencing carbon storage in Heilongjiang Province.

Xinjiang is the largest province in China,accounting for nearly 17% of China’s land area,but its forest stock and forest coverage rate rank only 10th and 31th,respectively,in China among 34 provinces,autonomous regions,province level municipalities,and special administrative regions.The forest coverage rate is only 2.94%,which is far lower than the national average of 18.92%,indicating a severe shortage of forest resources(Liu et al.2005;Cai 2014).Driven by key forestry projects such as large-scale afforestation,the forest area,stock,and density in Xinjiang have increased signi fi cantly in recent years(Shi 2011),improving the local ecological environment(Chen et al.2011).In their 1975–2005 study of the impact of land use/cover change on the forest carbon cycle in Xinjiang,Chen et al.proposed that afforestation,as the main source of forest carbon storage during this period,contributed to the increase in carbon storage by 54.24 Tg.This indicates that afforestation has become the dominant factor in fl uencing vegetation carbon storage in Xinjiang.

Uncertainty analysis

Because ofthe differencesamong research objects,research methods,in fl uence factors,and data sources,the dominant factors in fl uencing carbon storage may vary with different studies,even for the same area.We found that the dominant factor in fl uencing carbon storage in the stateowned forest region of Heilongjiang was forest fi re,followed by reforestation(Table 2).Xu(2011)employed the same method to study carbon sequestration in the stateowned forest region of Heilongjiang.They found that the dominant factor in fl uencing carbon storage was forest cultivation,followed by forest fi re(ibid.).Earlier,Xu(2011)analyzed the factors in fl uencing forest carbon storage in 20 provinces and autonomous regions,including Liaoning,using grey relational analysis.Among their four in fl uence factors(reforestation area,pest-infected area,timber harvest,and completed investment in capital construction for forest management),the dominant factor in fl uencing carbon storage in Heilongjiang Province was timber harvest,followed by reforestation area(ibid.).

Due to the lack of original data,the in fl uences of forest fi re in Qinghai and Ningxia and forest pests and forest cultivation in Tibet could not be analyzed by the VAR model,so these factors cannot be compared with other provinces.

The VAR model does not consider the signi fi cance of the regression coef fi cient of each equation,and thus fails to verify results.The focus of these tests is the overall stability of the model.As long as the VAR system is stable,we can use the impulse-response function and variance decomposition to study the dynamic impact of random disturbances on the system(Cheng 2009).These tools will be improved further in future research through the optimization of research methods.

Conclusion

The NFPP covers 17 provinces,autonomous regions,and municipalities but its vegetation carbon storage is found mainly in China’s northeast and southwest regions.There was a general increasing trend in vegetation carbon storage in the area of NFPP from 1997 to 2013.The largest contribution of vegetation carbon sequestration among NFPP regions took place in the upper reaches of the Yangtze River.

Using the vector auto regression model to study the in fl uence factors of vegetation carbon storage in the NFPP area proved feasible given the available data.The simulation results show that the dominant in fl uence factors of vegetation carbon storage differed by project area.Timber harvest was the dominant factor in fl uencing carbon storage in the Yellow and Yangtze River basins.Reforestation contributed most to carbon storage in the state-owned forest region of Xinjiang.In state-owned forest regions of Heilongjiang and Jilin Provinces,the dominant factors were forest fi res and forest cultivation,respectively.Accordingly,for the enhancement of carbon sequestration capacity,a longer rotation period and a smaller timber harvest are recommended for the Yellow and Yangtze River basins.Trees should be planted to promote the forest carbon-sink capacity in state-owned forests in Xinjiang.Forest fi res should be prevented in state-owned forests in Heilongjiang,and greater forest cultivation efforts should be made in the state-owned forests in Jilin.

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