March, 2013 Journal of Resources and Ecology Vol.4 No.1 J. Resour. Ecol. 2013 4 (1) 036-042 DOI:10.5814/j.issn.1674-764x.2013.01.005 www.jorae.cn rticle Spatial-temporal Changes in Ecological Risk of Land Use before and after Grain-for-Green Policy in Zhengning County, Gansu Province SHEN Jianxiu 1,2 and WNG Xiuhong 1 * 1 Institute of Geographic Sciences and Natural Resources Research, CS, Being 100101, China; 2 University of Chinese cademy of Sciences, Being 100049, China bstract: The Grain-for-Green Policy aims to convert cropland to grassland and forest across western China, and evaluating ecological risk is essential to its implementation. Because few recent studies have focused on eco-risk changes of land use in the areas affected by significant policies, this paper took Zhengning County in Gansu Province as our focal area, and studied spatial-temporal changes in ecological risk before and after policy implementation. Based on indices of landscape fragmentation and ecosystem service value, an ecological risk assessment method using rcgis and Fragstats was done. The regional gravity center model and land spatial distribution model were also used to enrich the quantitative description of divisional eco-risk and its spatial-temporal variation in the county. Results showed that the implementation of the policy has contributed to an overall reduction in ecological risk in Zhengning County, with a divisional degree order reduction following the pattern: eastern Zhengning > western Zhengning > central Zhengning. The gravity center for eco-risk shifted 4288 m southwest from 1995 to 2010 due to landscape fragmentation. The study implies that greater attention should be paid to forest and grassland restoration in eastern Zhengning, cropland protection in central Zhengning, and soil and water conservation in western Zhengning. Key words: Grain-for-Green Policy; ecological risk assessment; spatial-temporal changes; Zhengning County, Gansu Province 1 Introduction Regional ecological risk refers to the possibility and extent of damage to the structure and function of ecological systems from human activity and natural disasters (Zhang and Liu 2010; Galic et al. 2012). Eco-risk assessment of land use is an essential part of the regional eco-risk assessment system and reveals the comprehensive ecological impact of human activities on the environment and strategies for eco-security management (Graham et al. 1991). Given the relationship between land use and ecological systems, land use types are the basis for constructing reasonable ecosystem structures and evaluating eco-risk (Shen et al. 2012a, 2012b). China s Grain-for-Green Policy of returning marginal cropland to forest or grassland is one of the most important large-scale initiatives to combat land degradation across the country (Wang et al. 2012). The implementation of this policy has resulted in changes in land use and regional ecological security across the Loess Plateau (Wang 2013). Research on eco-risk assessment has focused on conceptual and mathematical models; however, application of these models always is limited. Qualitative analysis or combinations of qualitative and semi-quantitative analyses (Gu et al. 2012; Bartolo et al. 2012) have focused on human activity gathering areas (Liu et al. 2011), natural reserves (Liu et al. 2012) and watershed eco-compensation standards (Xu et al. 2012). However, few studies have focused on changes in eco-risk and land use in areas affected by significant policy, especially eco-risk changes in western China after implementation of the Grain-for-Green Policy. Landscape scale is midway between the ecosystem scale and regional scale, and is commonly used to study social and natural spatial characteristics; thus, the advantage of researches on land use eco-risk assessment at a landscape Received: 2012-11-27 ccepted: 2013-01-29 Foundation: National Natural Science Foundation of China (No. 40971282). * Corresponding author: WNG Xiuhong. Email: wangxh@igsnrr.ac.cn.
SHEN Jianxiu, et al.: Spatial-temporal Changes in Ecological Risk of Land Use before and after Grain-for-Green Policy in Zhengning County, Gansu Province 37 scale is highlighted (Zurlini et al. 2004; Fu et al. 2011). The software Fragstats is widely used for landscape pattern analysis because it can process landscape classification data and independent indices. However, a single index cannot clearly indicate a wide range of landscape fragmentation processes (Qiu et al. 2012). Here, this paper constructed a divisional eco-risk assessment model of land use by combining multi-landscape indices with eco-service values using GIS and geo-statistical tools to analyze temporal changes and spatial distribution in eco-risk of land use before and after the implementation of the Grain-for-Green Policy in Zhengning County. 2 Study area Located in southeastern Gansu province, Zhengning County is typical of the Loess Plateau and has a total area of 1319.5 km 2. Geographically, it is located at 107 56 20 108 38 08 E, 35 14 40 35 36 18 N, with a shape of triangle. Topographically, it is higher in the northeast and lower in the southwest, with an average altitude of 1460 m. The area is a typical ecological fragile county with a gully area accounting for about 82% of total area. Over 1200 gullies of different sizes are the main cause of soil erosion. It is also a typical agricultural county and in 2010 had 1.55 billion CNY of GDP with primary industry accounting for 37.1%. Its cropland accounts for 41.29% of total area. Obvious changes in land use occurred following the implementation of the Grain-for-Green Policy and ecological conditions have been altered. study of temporal and spatial variation in eco-risk and land use is urgently required for this part of China. In order to further analyze the characteristics for eco-risk spatial differentiation in Zhengning County, this paper divided the study area into three parts (east, central and west) based on administrative township-level boundaries, local topographic features and land-use conditions (Fig. 1). 3 Data and methods 3.1 Data source The land use changes in Zhengning County before and after implementation of Grain-for-Green Policy were analyzed based on the land use vector maps for 1995, 2000 and 2010. Maps in 1995 and 2000 were obtained from the Data Center for Resources and Environment Sciences, Chinese cademy of Sciences. The land use vector database in 2010 was artificially interpreted from corresponding rectified Landsat TM images downloaded from the United States Geological Survey, using Envi 4.7 and rcgis 9.3 and referencing existing land use vector maps in 2000 and 1995. Referring to land use classification systems, 1995 and 2000 vector maps, and the actual situation in 2010, land use types were divided into six categories of cropland, forestland, grassland, water land, construction land and unused land, and 16 subtypes. Data on grain yield, cropland area and net primary productivity (NPP) in 2000 were used to rectify the existing eco-service functional value index in connection with different years, regions and land use ecosystem types, which calculated by Xie et al. (2003) (Table 1). Data on grain yield and area of cropland were collected from the Gansu Rural Yearbook (1996 2011). NPP data in 2000 was provided by the Data Center for Resources and Environment Sciences, Chinese cademy of Sciences. ll spatial data were converted to the same Geographic Coordinate System and Projected Coordinate System. 3.2 Methodology In order to analyze the characteristics of landscape distribution, and spatial-temporal changes in ecological risk of land use before and after the Grain-for-Green Policy, this paper constructed a land use eco-risk assessment index using landscape fragmentation and area-weighted ecoservice values. gravity center model was used to enrich Gansu County seat East Silang River 0 West Central Zhidang River 10 20 40 km N Fig.1 Location and division of Zhengning County, Gansu Province.
38 the quantitative description of spatial-temporal variation in divisional eco-risk. land spatial distribution model was used to verify the effect of policy implementation on land distribution. 3.2.1 Eco-risk assessment index construction Regional ecological risk is the product of the probability of harmful events and damage (Mao and Ni 2005). The probability of harmful events (P) is determined by the intensity of interference. The absolute value of damages is difficult to quantify and a relative evaluation method was used. The accident harmful level is determined by regional resistance and ecological value. The greater the regional disruption to intensity, the weaker the resistance; and the higher the ecological value of the area, the greater the ecological loss (Zeng 2010; Dai et al. 2012). Therefore, according to relationships between the above factors, regional ecological risk value (R) can be expressed as: V Eco value R Damage / time = P Interference C Resistance The comprehensive effect of term P/C (the right side of the equation) can be replaced by landscape fragmentation (Zeng 2010). This infers that ecological risk is the product of landscape fragmentation (S) and ecological service value (V): P Interference R Damage / time = V Eco value C Resistance (2) = S V Landscape fragmentation refers to the process of landscape structural change from simple to complex. Interference factors are the main reasons for landscape change from a single, homogeneous and continuous whole entity to complex, heterogeneous and discontinuous patch mosaics, and human activities play a leading role in the formation of landscape fragmentation (Wang et al. 1996). Interrelated to habitat fragmentation, landscape fragmentation reduces connectivity in patches and shape complexity, and increases the amount of edge habitat, with both biological and abiotic (physical) impacts on the ecological environment (Gao and Cai 2010). Thus, landscape fragmentation is a comprehensive reflection of interactions between resistance and interference. Considering the characteristics of patch size, shape and contagion, this paper selected three different landscape indices to characterize landscape fragmentation. t a landscape scale of 4 units pixel neighbor distance, the selected indices include patch density (PD), contagion (CONTG) and edge density (ED). Patch density (PD) can be calculated as follows: N 6 PD = 10 (3) where, PD is patch density (Number km -2 ); N equals the total number of patches in the landscape; and is the total landscape area (m 2 ). The number of patches increases while (1) Journal of Resources and Ecology Vol.4 No.1, 2013 average patch area size declines. high PD value indicates strong landscape disturbance and a high degree of landscape fragmentation. Contagion (CONTG) can be expressed as: where, CONTG is the contagion index (%); P i refers to the proportion of landscape area occupied by patch type i (%); g ik is the number of adjacencies between pixels of patch types i and k based on the double-count method (Number); and m is the number of patch types presented in the landscape (Number). The contagion index indicates landscape connectivity, which is an agglomeration and extending trend of different patch types. High contagion reflects low landscape fragmentation, indicating the dominant patch has high integrity and connectivity. Edge density (ED) can be expressed as: ED m eik k = 1 = 10 6 where, ED is edge density (m km -2 ); e ik equals the total length (m) of edge involving patch type i and k in landscape; and is total landscape area (m 2 ), the same as PD in equation (2). This paper introduces the edge density index in order to offset the influence of frequent neighboring by different patch types (Riitters et al. 1996; Wu 2001). The source of these equations was Fragstats. In summary, this paper constructed a landscape fragmentation index (S), expressed as follows: P PD S = = (6) C CONTG / ED Ecosystem service refers to natural environmental conditions and effectiveness that support human life; these serviced plays an important role in maintaining regional ecological balance and sustainable development (Bingham et al. 1995). In this study, divisional ecological value is quantified as the ecosystem service value coefficient weighted by proportion of area. First, the divisional ecosystem was divided into nine types, including woodland, shrub land, other forestland, high coverage grassland, medium coverage grassland, low coverage grassland, water area, cropland and construction land. Second, based on Xie et al. (2003), the parameters of existing eco-service functional values were rectified in connection with different years, regions and land use ecosystem types (Shen et al. 2012a) (Table 1). Finally, rectified parameters were normalized using the forward range transform method, and an eco-service value index (V i ) for each land use ecosystem was obtained. The formula for the area-weighted ecological service value index is: n i V = V = ( V) a (7) i i= 1 (4) (5)
SHEN Jianxiu, et al.: Spatial-temporal Changes in Ecological Risk of Land Use before and after Grain-for-Green Policy in Zhengning County, Gansu Province 39 Table 1 Rectifying the existing eco-service functional value index. Rectification type Required data Proof Regions Net primary productivity (NPP) of China There is a favorable linear correlation between ecosystem service value and NPP, therefore, it is a relative reliable and feasible approach to quickly estimate regional ecosystem service values from national NPP (Shi et al. 2010) Different years Land use types Means of per unit area yield of grain during 1995 2000, 1995 2005, and 2000 2010 The eco-service rectify parameters of each land-use type Grain yield per unit area is closely associated with elements in an agricultural ecosystem (Robertson et al. 1997) Obtained from the Delphi method in Tang (2011) where, V a is the ecosystem service value coefficient weighted by area proportion; i is the area (km 2 ) of land use ecosystem i (i=9), is the total landscape area (km 2 ); and V i is generalized eco-service value per m 2 indexes for each land use ecosystem. ccording to formulas (2), (6) and (7), the land use ecorisk value of part j in year i can be expressed as follows: R PD 2 = V 100 (8) CONTG / ED 3.2.2 Eco-risk gravity center calculation Using zonal geometry and the table command in the rcgis spatial analyst module, the authors obtained the landscape geometric center coordinates for eastern, central, western and the whole county. Based on geometric center coordinates, divisional eco-risk gravity center coordinates can be calculated using the formula (Haynes and Fotheringham 1984): n n n n = ; = i ig i ig (9) X P X P Y PY P j= 1 j= 1 j= 1 j= 1 where, X i and Y i represent the county s eco-risk gravity center coordinate in year I; X and Y is the geometric center coordinate of part j in year I; P is land use eco-risk value of part j in year i, the same meaning as R in formula (7); and n is the amount of parts (n=3). significant difference between the spatial mean (gravity center) and the geometric center for a spatial phenomenon indicates an uneven distribution. Direction of the deviation indicates high density, and distance indicates the degree of disproportion (He et al. 2011). Similarly, the gravity center coordinate of landscape fragmentation and the areaweighted ecological service value can also be calculated. 3.3.3 Land use transfer distribution testing The spatial distribution patterns of geographic features can be classified as random, clustered and dispersed. random distribution implies that geographic features are independent from their spatial location. clustered distribution means that the distribution of geographic features is closely related to their spatial location, and attracted by other spatial elements. dispersed distribution implies exclusionary features (Chen and Lu 2012). This paper introduced a land use type transfer spatial distribution model to test cropland transference (2000 2010) distribution patterns, and verify the effect of the Grain-for-Green Policy. The authors used the average nearest neighbor distribution analysis tools in rcgis 9.3 to measure the distance between each feature centroid and its nearest neighbor s centroid location. n d / n i i= 1 F = (10) 0.5 / n/ In the previous equation, expression is based on instruction in rcgis 9.3: d i is the distance between feature i and its nearest feature; n corresponds to the total number of features; and is the total study area. The index F is expressed as the ratio of observed distance to expected distance, and the expected distance is based on a hypothetical random distribution with the same number of features covering the same total area. If F is less than 1, the distribution pattern is clustered; if F is greater than 1, it is a dispersed distribution. 4 Results and discussion 4.1 Divisional changes in land use eco-risk Table 2 indicates the values of landscape fragmentation Table 2 Landscape, ecological service and eco-risk in Zhengning in 1995, 2000 and 2010. PD CONTG CONTG/ED V S R West 2010 3.61 58.38 1.23 15.25 292.92 44.66 2000 3.93 59.25 1.20 14.95 327.40 48.95 1995 3.76 60.90 1.28 14.95 293.85 43.93 Central 2010 2.71 53.36 1.19 18.97 227.77 43.20 2000 3.10 57.51 1.21 16.88 256.50 43.29 1995 3.11 58.42 1.23 16.92 253.80 42.94 East 2010 1.63 49.38 1.18 32.76 138.26 45.29 2000 2.57 40.65 0.92 28.08 278.40 78.17 1995 2.66 40.31 0.91 29.61 293.33 86.86 Notes: PD, CONTG, CONTG/ED, V, S and R are patch density (Number km -2 ), contagion index (%), landscape connectivity and regional resistance; area-weighted ecosystem service value; landscape fragmentation; and land use eco-risk assessment index respectively.
40 (S), area-weighted eco-service value index (V) and eco-risk assessment index (R) in eastern, central and western Zhengning in 1995, 2000 and 2010. Before the implementation of the Grain-for-Green Policy from 1995 to 2000, the divisionally ranking order for ecological risk in Zhengning was east Zhengning > west Zhengning > central Zhengning. The highest value of 86.86 appeared in eastern Zhengning in 1995. The order of landscape fragmentation degree was west Zhengning > east Zhengning > central Zhengning, with a peak value of 327.40 in the west in 2000. The order for area weighted eco-service value was east Zhengning > central Zhengning > west Zhengning, with a peak value of 29.61 in the east in 1995. Eco-risk in eastern Zhengning was mainly determined by ecosystem service value, and this would increase under monetary ecological loss during disasters. Eco-risk in the west was mainly determined by the degree of landscape fragmentation, and this would increase due to decreasing resistance from increasing landscape fragmentation. Following implementation of the Grain-for-Green Policy from 2000 to 2010, the rank in eco-risk was east Zhengning > west Zhengning > central Zhengning and similar to the order observed 1995 to 2000. Without obvious peak values, land use eco-risk was low and uniformly distributed. The reduction of eco-risk in the east was reflected in the significant decline of the degree of landscape fragmentation from 278.40 in 2000 to 138.26 in 2010. This represents an average annual rate of change of 5.95%, reflecting the positive effect of the Grain-for-Green Policy in eastern Zhengning. Eco-services were mainly provided by forest and cropland in the east where gullies are largely distributed. Compared to central and western parts of the county, the east had comparative dominant land use types of woodland and shrub land. In western Zhengning, regional eco-risk declined as the rate of landscape fragmentation declined 10.53% and the rate of eco-service values increased 1.98%. Main land types in this section include cultivated dark loessial (Heilu) soil tableland, cultivated loessial (Huangmian) soil slope land and temperate shrub loessial soil steep slope land. lthough soil types are suitable for cultivation in this region, unreasonable reclamation of land with a fragmented landscape structure can easily result in soil erosion and nonpoint source pollution due to multi-gullies and furrows. In order to reduce eco-risk and protect regional ecological security, it is necessary for western Zhengning to build Journal of Resources and Ecology Vol.4 No.1, 2013 an agro-forestry compound ecosystem, to return marginal cropland to forest or grassland, develop drought shrubbery hedge agriculture, and establish a shrub ecosystem for soil and water conservation across the whole county. Construction land in Zhengning is mainly distributed in the central region, where the Zhidang River and Silang River are located. Highly related to the distribution of the construction lands, cropland was the dominant land use type. s shown in Table 2, patch density in the central region decreased from 3.10 km -2 in 2000 to 2.71 km -2 in 2010 after implementation of the Grain-for-Green Policy. This indicates that the number of scattered cropland patches decreased because of ecological restoration; however the agglomeration of patches decreased because of a reduction in CONTG/ED from 1.21 in 2000 to 1.19 in 2010, reflecting a reduction in the connectivity of cropland. The decline in landscape fragmentation in the central region enhanced regional resistance to unexpected disasters. Therefore, because central Zhengning has suitable natural flat tableland and sufficient irrigation, the construction of irrigation infrastructure and water conservancy should be strengthened to further optimize food security. 4.2 Movement of gravity center for land use eco-risk The geometric center of the county (35.43 N, 108.41 E) was calculated in rcgis (Table 3). The moving scope of each gravity center in the study area was 35.31 35.41 N, 108.26 108.36 E. The gravity centers for eco-risk and landscape fragmentation moved 4287.88 m and 4206.14 m southwest, while the gravity center for eco-service value moved 439.32 m northeast from 1995 to 2010 following policy implementation. Fig. 2 shows the movement tracks of gravity centers for landscape fragmentation degree (S), eco-service value (V) and eco-risk value (R). The track of the landscape fragmentation gravity center was consistent with the ecorisk gravity center, indicating that the change in the degree of landscape fragmentation has played a critical role in the movement of the eco-risk gravity center in Zhengning. There were two reasons for the movement of the ecorisk gravity center southwest from 1995 to 2000. First, the landscape fragmentation degree increased because of complex landform types and low vegetation coverage, and unreasonable land use and land degradation in the western part of the count. Second, the ecological service value decreased in eastern Zhengning. Table 3 Gravity centers of assessment indices and movement distances. Coordinate ( ) Distance (m) S V R Latitude Longitude Latitude Longitude Latitude Longitude 2010 N35.38 E108.26 N35.41 E108.36 N35.39 E108.31 2000 N35.39 E108.30 N35.40 E108.35 N35.40 E108.34 1995 N35.39 E108.31 N35.40 E108.35 N35.40 E108.35 2000 2010 3165.05 780.03 2914.54 1995 2000 1041.12 1041.12 1373.38 1995 2010 4206.14 439.42 4287.88
SHEN Jianxiu, et al.: Spatial-temporal Changes in Ecological Risk of Land Use before and after Grain-for-Green Policy in Zhengning County, Gansu Province 41 Year 2010 2008 2006 2004 2002 2000 1998 1996 1994 108.28 Longitude 108.32 108.36 35.41 35.40 35.39 35.38 Latitude Legend Fig. 2 Gravity centers of assessment indices from 1995 to 2010. Note: S represents landscape fragmentation; V is the area-weighted ecosystem service value; and R is land use eco-risk assessment index. fter the Grain-for-Green Policy, patch density in the eastern part decreased from 2.57 km -2 in 2000 to 1.63 km -2 in 2010. Restoration of forest and grassland resulted in an increase in the contagion index value. The substantial decrease in landscape fragmentation in the east contributed to the movement of the eco-risk center southwest. High unit eco-service values for forest and grassland contributed to an increase in eco-risk value in east, forcing the divisional eco-service gravity center northeast. However, the direction of movement of the divisional eco-risk gravity center was mainly determined by the decrease in landscape fragmentation. 4.3 Spatial distribution for land use type transfer Table 4 shows distribution patterns of transferred cropland and new construction land. The index F is expressed as the ratio of observed distance to expected distance; the Z score is the standard deviation of difference between observed distance and expected distance, which is a measure of statistical significance and indicates whether or not to reject the null hypothesis. If the Z score is less than 1.96, within [ 1.96, 1.96] or greater than 1.96, a random, cluster or dispersed distribution will be found respectively. ccording to the F and Z scores in Table 4, the conversion of cropland to forest and grassland followed a clustered distribution pattern. This implies that the distribution of returned cropland in Zhengning has a certain regularity, meeting the requirements of the Grain-for-Green Policy and benefitting sustainable land use and landscape planning. However, the F and Z values calculated for newly increased construction land were 1.87 and 4.7, respectively. The expansion of newly increased construction land had a dispersed distribution pattern, indicating that planning and control of newly increased construction land in Zhengning have been neglected during the process of returning marginal cropland to forest or grassland. S V R Table 4 Spatial distribution model analysis for land use type transfer. Land use change F Z 5 Conclusions Driven by a reduction in landscape fragmentation, eco-risk values in eastern, central and western Zhengning County have decreased significantly after implementation of the Grain-for-Green Policy. Especially in eastern Zhengning, regional ecological resistance has been improved, and the probability of disaster occurrence has declined. The effects of this policy include declining patch density and an increasing contagion index for dominant land types in eastern Zhengning. Based on the analysis of spatial distribution model for land use type transfer, planning for newly increased construction land needs to be strengthened in Zhengning in order to reach regional ecological security. The gravity center for eco-risk moved 4288 m towards southwest Zhengning from 1995 to 2000, a similar pattern to the landscape fragmentation centroid, which moved 4206 m southwest. Prior to policy implementation, movement of the gravity center for eco-risk was determined by decreases in ecological service values in the east and increased landscape fragmentation in the west. From 2000 to 2010, the substantial decrease in the landscape fragmentation degree in the east accelerated movement of the gravity center for eco-risk. To reinforce eco-security management in Zhengning, main countermeasures are summarized as follows: forest and grassland should be mainly protected to develop an ecological conservation area for the whole county in the east; quality of cropland should be guaranteed by controlling the expansion of construction land onto cropland in central Zhengning; landscape fragmentation degree should be decreased and a shrub ecosystem for soil and water conservation is urgently required in order to reduce eco-risk in the west. References Distribution type Cropland to forest, grass land 0.51 18.80 Cluster to forest land 0.66 10.55 Cluster to grass land 0.49 11.93 Cluster Newly increased construction land 1.87 4.70 Dispersed Bartolo R E, R Van Dam, P Bayliss. 2012. Regional ecological risk assessment for ustralia s tropical rivers: pplication of the relative risk model. Human and Ecological Risk ssessment, 18(1): 16-46. Bingham G, R Bishop, M Brody, et al. 1995. Issues in ecosystem valuation: Improving information for decision-making. Ecological Economics, 14(2): 73-90. Chen L, Lu C. 2012. Scale effect of land use and soil erosion in loess gully area. Being: Science Press. (in Chinese) Dai J, Wang H, Wang H, Chen C. 2012. n introduction to framework of assessment of the value of ecosystem services. Progress in Geography, 31(7): 963-969. (in Chinese)
42 Fu L, Xie B, Zhang Y, et al. 2011. Ecological risk assessment of land use in core area of Changsha-Zhuzhou-Xiangtan urban group. Journal of Natural Disasters, 20(2): 96-101. (in Chinese) Galic N, Schmolke, V Forbes, et al. 2012. The role of ecological models in linking ecological risk assessment to ecosystem services in agroecosystems. Science of the Total Environment, 415:93-100. Gao J, Cai Y. 2010. Spatial heterogeneity of landscape ragmentation at multi-scales: case study in Wujang River Basin, Guizhou Province, China. Scientia Geographica Sinica, 30(5): 742-747. (in Chinese) Graham R L, C T Hunsaker, R V O Neill, B L Jackson. 1991. Ecological risk assessment at the regional scale. Ecological pplications, 1(2): 196-206. Gu L, Song B, Tong Z Q, Ma J H. 2012. Spatial distribution and potential ecological risk assessment of heavy metals in roadside soils on different operated times along the Lianyungang-Horgas Highway. Progress in Environmental Science and Engineering (ICEESD2011), 630-635. Haynes K E, S Fotheringham. 1984. Gravity and spatial interaction models. Sage Publications Beverly Hills, C. He Y B, Chen Y Q, Tang H J, et al. 2011. Exploring spatial change and gravity center movement for ecosystem services value using a spatially explicit ecosystem services value index and gravity model. Environmental Monitoring and ssessment, 175(1-4): 563-571. Liu D D, Qu R J, Zhao C H, et al. 2012. Landscape ecological risk assessment in Yellow River Delta. Journal of Food griculture & Environment, 10(2): 970-972. Liu M, Chen L, Gou Y, Dong R. 2011. ssessment of urban ecological risk from spatial interaction models for Liang City. International Journal of Sustainable Development and World Ecology, 18(6): 537-542. Mao X, Ni J. 2005. Recent progress of ecological risk assessment. cta Scientiarum Naturalium Universitatis Pekinensis, 41(4): 646-654. (in Chinese) Qiu J, Wang X, Lu F, et al. 2012. The spatial pattern of landscape fragmentation and its relations with urbanization and socio-economic developments: case study of Being. cta Ecologica Sinica, 32(9): 2659-2669. (in Chinese) Riitters K H, R V O Neill, J D Wickham, K B Jones. 1996. note on contagion indices for landscape analysis. Landscape Ecology, 11(4): 197-202. Robertson G P, K M Klingensmith, M J Klug, et al. 1997. Soil resources, Journal of Resources and Ecology Vol.4 No.1, 2013 microbial activity, and primary production across an agricultural ecosystem. Ecological pplications, 7(1): 158-170. Shen J, Wang X, Liu Y, et al. 2012a. Spatio-temporal changes of ecosystem service value in Zhengning County, Gansu Province before and after the Grain-for Green Policy. Research of Soil and Water Conservation, 19(4): 59-64. (in Chinese) Shen Y, Wang X, Yue Y. 2012b. nalysis of ecological suitability and rational ecological system structure of land types: case study in Zhengning County, Gansu Province. Progress in Geography, 31(5): 561-569. (in Chinese) Shi Q, Wang Z, Wu Y, et al. 2010. Calculation of ecosystem services value and correlation with net primary production (NPP) in Xinjiang. rid Land Geography, 33(3): 427-433. (in Chinese) Tang X. 2011. The ecological classification and pattern change of land-use in Being. Being: Chinese cademy of Sciences. (in Chinese) Wang X. 2013. Spatio-temporal changes in agrochemical inputs and the risk assessment before and after the Grain-for-Green Policy in China. Environnetal Monitoring ssessment, 185 (2): 1927-1937. Wang X, Bu R, Hu Y, Xiao D. 1996. nalysis on landscape fragment of Liaohe delta wetlands. Chinese Journal of pplied Ecology, 7(3): 299-304. (in Chinese) Wang X, Shen Y, Cong R, Lu Q. 2012. Conflicts affecting sustainable development in west China since the start of China s western development policy. Journal of Resources and Ecology, 3(3): 202-208. Wu J. 2001. Landscape ecology_pattern, process, scale and level (2ed edition). Being: Senior Education Press, 106-115. (in Chinese) Xie G, Lu C, Leng Y, et al. 2003. Ecological assets valuation of the Tibetan Plateau. Journal of Natural Resources, 18(2): 185-196. (in Chinese) Xu Y, Gao J, Zhao J, Chen J. 2012. The research progress and prospect of watershed ecological risk assessment. cta Ecologica Sinica, 32(1): 284-292. (in Chinese) Zeng Y. 2010. The regional ecological risk assessment of Hohhot City. cta Ecologica Sinica, 30(3): 0668-0673. (in Chinese) Zhang S, Liu H. 2010. Review of ecological risk assessment methods. cta Ecologica Sinica, 30(10): 2735-2744. (in Chinese) Zurlini G, O Rossi, Ferrarini, et al. 2004. Ecological risk assessment through landscape science approaches. In: Teaf C M, B K Yessekin, M K Khankhasayev (Ed.). Risk ssessment as a Tool for Water Resources Decision-Making in Central sia, Springer Netherlands, 155-173. 生态退耕政策实施前后甘肃正宁县土地利用生态风险时空变化分析 申建秀 1,2 1, 王秀红 1 中国科学院地理科学与资源研究所, 北京 100101; 2 中国科学院大学, 北京 100049 摘要 : 本文选取甘肃省正宁县 1995,2000 和 2010 年土地利用数据和相关耕地统计数据为分析依据, 以 ENVI, rcgis 和 Fragstats 为主要工作平台, 对研究区的土地利用生态风险时空变化进行了分析 为了避免了评价指标选取的主观性, 在景观水平上针对土地利用斑块数量 形状和蔓延度等特点选取了相应的景观指数, 结合生态系统服务价值, 构建了区域土地利用的生态风险评价指数 为了研究生态风险的空间变化和验证生态退耕政策实施的效果, 本文引入了生态风险质心迁移模型和土地利用的空间分布模型, 定量描述了甘肃正宁县实施生态退耕工程前后生态风险的相对大小和时空变化规律 结果表明 :(1) 生态退耕工程的实施使得正宁县东 中 西部的生态风险均减小, 减小幅度在空间分布上表现为 : 东部 > 西部 > 中部 东部为生态风险防范管理的最重要地区 ;(2) 正宁县生态退耕前后生态风险质心向西南方向迁移了 4288m, 东部和西部景观破碎度的大幅度变化对县域生态风险质心的迁移起到了主要的作用 研究结果提示 : 为了进一步加强正宁县生态安全管理, 东部地区应以林地和草地生态保护为主, 中部地区应保证耕地的质量并强化对新增建设用地的规划和控制, 而西部地区则需构建水土保持型农业生态系统 关键词 : 生态退耕政策 ; 生态风险 ; 时空变化分析 ; 甘肃正宁县