Vulnerability of Agricultural Production under a Rapid Urbanization Process in China Xiangzheng Deng, Qunou Jiang, Wei Huang Institute of Geographical Sciences and Natural Resource Research, Chinese Academy of Sciences International Conference on Sustainability Science in Asia (ICSS-Asia)

Factors leading to vulnerability for agricultural production Climate changes Natural disaster Losses of agricultural lands Increased activity of insects Spreading of plant diseases Agricultural waste disposal Urbanization

Rapid urbanization leading to vulnerability for agricultural production Rapid urbanization is identified by the conversion of agricultural lands to housing and other nonfarm uses By perception, this conversion will challenges our long-term capacity to provide food, fiber and ecosystem services to a growing world population.

China’s cereal yield(10kg/ha), and production (million tons) After 1998 Prod: -18% Yield: stagnant

China’s cereal sown area (million ha) The fall of sown area after 1998, As generated the concern of China’s government

Issues related with the vulnerability of agricultural production associated with the rapid urbanization process Has cultivated land declined due to the urban land expansion sharply? How has this affected grain production in the past? Is the urban land expansion contributing to the loss of cultivated area? What is the potential impacts of urban land expansion on agricultural production ？ How does the urban land expansion lead to vulnerability of agricultural production?

Goals of Presentation Measure the impacts on agricultural production from urban land expansion Identify the spatial heterogeneity of urban land expansion process as well as the vulnerability of agricultural production Explore the relationship between vulnerability of agricultural production and factors related with the urban land expansion

Data and methods Remote sensing data (RSD) identifying land uses Derived from Landsat TM/ETM, 1988, 1995, 2000 and 2005 Organized as one area percentage dataset Meteorological data Raw record derived from the China Meteorological Administration Surface data Soil attribute data Derived from the second round of nationwide soil survey Terrain condition data Slope, elevation, landform Social and economic data Population density,GDP, Agricultural Investment, fertilizer uses

Data and methods Use an estimation system for agricultural productivity (ESAP) to measure the impacts on agricultural production from urban land expansion Use an analytical hierarchical process (AHP) approach to explore the spatial heterogeneity of the vulnerability of agricultural production Use an econometric method to explore the relationship between the vulnerability of agricultural production and factors related with the urban land expansion

Measure the impacts on agricultural production from the urban land expansion

Estimation System for Agricultural Production (ESAP)

Rationale of ESAP

Urban Growth of Chengdu, the capital of Sichuan province, China Urban Core – 1990 Orange area: Newly expanded built up area (most of it on cultivated land) between 1990 and 2000

Urban core Urban sprawl Rural patches = In this study, we only examine “urban core”

Using 1-km APDM to describe China’s land conversions 1-km APDM: a new technique to convert vector data into a series of grid data with 1 km resolution without losing detailed acreage information Three steps –build up a standard grid frame with vector format and make each grid cell with 1 by 1 km scales and identified with a unique ID. –use the frame to intersect with the vector data of land uses to allocate all layers of land uses/land use changes into each cell. –provide a summary of area, length, etc. for each cell group by class or level. Each cell with 1 km 2 area contains the land conversion information, e.g., cultivated area in 1988/2000/2005 and the conversion between cultivated land and other land cover types.

Spatial variation of land uses and temporal changes represented by 1-APDM data 1988/138.5Mha2000/141.1Mha Cultivated land Forestry area Grassland Built-up area +2.6 Mha-1.1 Mha-3.5 Mha+1.8 Mha Net changes of area (ha) in each 10 by 10 kilometers,

Spatial variation of land uses and temporal changes represented by 1-APDM data 2000/141.1Mha Cultivated land Forestry area Grassland Built-up area Mha+0.21 Mha-1.42 Mha+1.70 Mha 2005/140.5Mha Net changes of area (ha) in each 10 by 10 kilometers,

China’s land conversions under the rapid urbanization process, Total reduction: 2.6 million ha, or 1.9% New uses: - Built-up Area (47%); Forestry area (17%); - Grassland (22%); Water area (11%); Unused land (5%) Total addition: 5.2 million ha, or 3.8% Sources: - Built-up Area (0%); Forestry area (29%) - Grassland (55%); Water area (4%); Unused land (11%)

China’s land conversions under the rapid urbanization process, Total reduction: 2.7 million ha, or 1.5% New uses: - Built-up Area (49%); Forestry area (17%); - Grassland (20%); Water area (12%); Unused land (2%) Total addition: 2.1million ha, or 1.2% Sources: - Built-up Area (0%); Forestry area (18%) - Grassland (57%); Water area (7%); Unused land (18%)

Urban land expansion identified at the 1km*1km GRID scale,

Urban land expansion identified by the 1km*1km GRID scale,

Growth rate of Built-up area (BuA) Growth rate = Newly expanded area (88-00)/BuA (1988)

Growth rate of Built-up area (BuA) Growth rate = Newly expanded area (00-05)/BuA (2000)

Urban land expansion by provinces (10^3 ha) 1988 to 2000

Urban land expansion by provinces (10 ^3 ha) 2000 to 2005

Spatial heterogeneity of the growth rate of the BuA ( ) Urban land expanded by 1.7 million ha, or 3.84% With a share of 0.18% of total land area The following regions featured by dramatic urban land expansion North China Plain (Beijing and Tianjin) East and Southeast areas - Lower Yangtze River Delta (Shanghai, Jiangsu) - Pearl River Delta (Guangdong) Inland areas -Sichuan Basin -Xinjiang and other NW provincial capitals

Urban land expanded by 1.68 million ha, or 3.66% With a share of 0.18% of total land area The following regions featured by dramatic urban land expansion North China plain (Beijing, Tianjin, Shandong) East and Southeast areas - Lower Yangtze River Delta (Zhejiang, Shanghai) - Pearl River Delta (Guangdong) Inland areas -Sichuan Basin (Sichuan, Chongqing) -Ningxia, Shaanxi, Xinjiang Spatial heterogeneity of the growth rate of the BuA ( )

Spatial heterogeneity of the agricultural productivity of China, estimated based on ESAP Unit: ton/ha

Increase of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Increase of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Decrease of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Decrease of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Net change of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Net change of agricultural production associated with changes in cultivated land by provinces, Unit:10^3 ton

Percentage change of agricultural production due to land conversions in the period between 1988 and 2000

Percentage change of agricultural production due to land conversions in the period between 2000 and 2005

Impacts on the agricultural production from the urban land expansion in the period between 1988 and 2000 Land Conversions in China, Changes of Ag productivity by Provinces, Changes of ag production: –decreased by 2.2% ( ); –0.14% per year on average Regional differences: –North China Plain (Beijing, Hebei); Eastern coastal areas (Shanghai, Jiangsu, Zhejiang, Shandong) –South China (Guangdong); Sichuan Basin (Sichuan, Chongqing) –Inner Mongolia, Ningxia

Land Conversions in China, Changes of Ag productivity by Provinces, Changes of ag production: –decreased by 1.58% ( ); –0.10% per year on average Regional differences: –North China Plain (Beijing, Tianjin); Eastern coastal areas (Shanghai, Jiangsu, Zhejiang, Shandong) –South China (Guangdong); Sichuan Basin (Sichuan, Chongqing) –Xinjiang, Inner Mongolia, Ningxia –Northeast plain (Heilongjiang, Jilin) Impacts on the agricultural production from the urban land expansion in the period between 2000 to 2005

Explore the spatial heterogeneity of vulnerability of agricultural production

Analyzing vulnerability for agricultural sector

Factors selected for vulnerability assessment for agricultural production Sensitivity factor Climate-sensitive factors (environment changes) Weight Other sensitive factor (environment changes) Weight Precipitation variability for critical month Forest coverage Climatic disaster rate Aridity Days with rainstorm Variability of accumulated temperature for critical growing periods Adaptation factor Social and economic factors (socioeconomic conditions) WeightAgricultural production FactorWeight Rural per capita net income0.1129Share of irrigated land GDP share of non- agricultural sector Share of cultivated area Share of agricultural population Cultivated land per capita Investment in agricultural science and technology Grain yield0.1805

Spatial heterogeneity of vulnerability gradients Low High

Explore the “causality” between vulnerability of agricultural production with the relevant factors associated with rapid urbanization process

Spatial heterogeneity of the Cultivated Land Quality (CLQ)

Gain and loss of cultivated land area along with the cultivated land quality (CLQ) gradients, New cultivated area Lost cultivated area Comparing the change of “quality” of cultivated land that was converted to other uses with the “quality” of newly expanded cultivated area in China,

New cultivated area Lost cultivated area Comparing the change of “quality” of cultivated land that was converted to other uses with the “quality” of newly expanded cultivated area in China, Gain and loss of cultivated land area along with the cultivated land quality (CLQ) gradients,

Causality function to be estimated Vulnerability = f( urban land expansion, agricultural productivity, economic growth, population, Z) Z include a couple of influencing factors, e.g., rainfall, temperature, elevation, terrain slope, soil pH, soil organic matter, loam, distance to expressway, distance to mega cities, …

Results by using the Logit estimator Ordinal Logit Model:

Estimates of the marginal effects from the relevant factors, VariableLow vulnerable Moderate vulnerable High vulnerable Urban land expansion0.050 (1.59) (1.59) (1.59) Ag production (15.17)*** (27.11)*** (29.88)*** Population0.001 (1.17) (1.17) (1.17) GDP0.001 (1.66)* (1.67)* (1.67)* Rainfall (4.64)*** (4.78)*** (4.79)*** Temperature0.004 (16.51)*** (46.06)*** (63.39)*** Cultivated area in (2.82)*** (2.86)*** (2.86)***

VariableLow vulnerableModerate vulnerableHigh vulnerable Urban land expansion0.031 (1.40) (1.91) ( 1.98 ) Ag. production (15.12)*** (27.22)*** ( ) *** Population0.001 (1.34) (1.35) ( 1.35 ) GDP0.001 (2.90)*** (2.94)*** ( 2.94 ) *** Rainfall (4.52)*** (4.66)*** ( 4.66 ) *** Temperature0.004 (16.42)*** (46.10)*** ( ) *** Cultivated area in (2.81)*** (2.84)*** ( 2.85 ) *** Estimates of the marginal effects from the relevant factors,

Impacts of the vulnerability of agricultural production due to urban land expansion Impacts for the entire China: Increase by 0.3 of log odds for the high vulnerability level ( ) Increase by 0.2 of log odds for the high vulnerability level ( ) Regional differences: NW China (e.g., China, Xinjiang) Central China (e.g, the agricultural and pasturing transitional zones)

Concluding remarks By using an Ordinary Logistic Regression approach, we explored the relationship between the vulnerability of agricultural production and urban land expansion. There are “somewhat” relation between urban land expansion and the vulnerability of agricultural production. Although our results support the conclusion that urban land expansion has not compromised China’s ability to largely feed itself, this is no guarantee that this will continue into the future. In fact, according to the successful experiences of development in other countries, it is almost certain that there will be continuing pressure on the nation’s cultivated land. Notably, the employment and creation of wealth associated with the new uses of land will be many times greater than if the land was left in agriculture.

Summary Good policy management, however, requires that the process of conversion is done rationally and that the productivity of the remaining resources in the agricultural sector is improved. There is also scope for the expansion of the role of land markets in identifying the areas that should be developed and those that should be protected. The ultimate goal of China’s government must be to tacking the critical issues leading to vulnerability for agricultural production and find the harmonious balance urbanization, which is inevitable process and is going to consuming more land, and the conservation of cultivated land which sustain the sustainable development of agriculture in China.

Thank you!