January 20, 2008

A Sustainability Assessment of a High-Yield Agroecosystem in Huantai County, China

By Liu, Wenna Wu, Wenliang; Wang, Xiubin; Wang, Mingxin; Bao, Yonghong

Keywords: Sustainability assessment, high-yield, agroecosystem, regional-scale SUMMARY

Sustainable agricultural development is a perennial issue for agricultural researchers, government managers, and policy makers worldwide, but especially in developing countries. In China, farms in Shandong Province epitomize modern agriculture and play a vital role in providing food for the burgeoning population. However, Chinese agriculture is being challenged by declining resources and environmental deterioration resulting from modern farming practices. China must establish an efficient agricultural sustainability index (ASI) to evaluate agricultural conditions and offer recommendations for sustainable development. Here, we use Huantai County, Shandong Province to test a regional-scale ASI from social, economic and ecological factors that includes 11 sustainability indicators. To further evaluate the complex agroecosystem, we employed the analytic hierarchy process (AHP) and AMOEBA methods to assess agricultural sustainability from 1982 to 2003. The results show that environmental problems, especially groundwater depletion, are limiting regional sustainable development.


Food security is an enormous challenge for scientists, government managers, and policy makers throughout the world, as both population and food demand increase. Scientists from many fields strive to understand agricultural sustainability to ensure food supplies, social consolidation, and national prosperity (Lagerberg and Brown 1999; Pannell and Glenn 2000; Shi 2002). Intensive agriculture, which is characteristic of high-yield farming, has contributed greatly to the crop production increases in recent decades by using irrigation and massive chemical fertilizer and pesticide inputs. However, this has led, at local, regional, national, and global scales, to negative environmental consequences, such as degraded land, biodiversity loss, and polluted crops and groundwater (Matson et al. 1997; Fedoroff et al. 2005). Hence, the development of more sustainable long-term agricultural alternatives has received much attention. The difficulties in understanding the relationship between sustainability and agriculture have led analysts to conceptualize and evaluate agricultural sustainability from diverse research perspectives (Smit and Smithers 1993; Hansen 1996; Gowda and Jayaramaiah 1998; Smith and Mcdonald 1998; Rigby and Caceres 2001; Roefie and Lucas 2004). Despite the diversity of thought, definitions of agricultural sustainability display a notable consistency and generally include three important features: social acceptability, environmental soundness, and economic viability (Zhen and Routray 2003; Rasul and Thapa 2004; Zhen et al. 2005). Agricultural sustainability requires achieving all three standards. A sustainable agroecosystem must be economically profitable and productive as well as environmentally beneficial. Studies on establishing and maintaining agricultural sustainability at die farming level have found that the pattern of inorganic fertilizer and chemical pesticide use, groundwater availability, land cultivation mode, and the farmer's environmental consciousness have a large influence on the sound development of agriculture (Rosenberg et al. 1998; Ali 2003; Deng et al. 2005).

We investigated different criteria and approaches to agricultural sustainability. However, putting theories of sustainability into agricultural practice is impeded by the temporal and spatial singularities of agricultural production, and the complexity of agroecosystems. In sustainability assessments, the selection of a single indicator or indicator set to transform defined principles into measurable parameters is difficult. Moreover, the chosen indicators should reduce the systemic complexity and integrate systematic information (Giampietro 1997; von Wiren-Lehr 2001; Cui et al. 2004).

Here, we evaluate sustainable agricultural development in Huantai County, Shandong Province, the first dunliang xian on the northern plain of China, using an agricultural sustainability index (ASI). The diree-dimensional and multi-attribute ASI indicators encompass environmental (soil and groundwater), economic (productivity and counteractive or elastic capacity), and social (human health and lifestyle) factors. We employed AHP (analytic hierarchy process) and AMOEBA methods to conduct this evaluation of agricultural sustainability for the years 1982-2003. We also discuss agricultural management strategies for environmentally beneficial and economically viable crop production.


Huantai County, population 484,000, is located in die centre of Shandong Province, China, (36[degrees]51'-37[degrees]06'N and 117[degrees]50'0 -118[degrees]10'E). The total area of die county is 509.53 km2, of which arable land totals 333 km2, under a dominant wheatmaize rotation. The county measures 24.4 km north to south and 27.3 km west to east. The per capita land area is about 0.06 ha. Huantai County has abundant water resources, covering 1,652 hm^sup 2^ and including five rivers and a lake. It became the first dunliang county to achieve a crop yield of 1,000 kg in 1990. The county has 11 towns and 343 villages. The per capita income is about 4,000 yuan annually. The region has a typical continental monsoon climate, characterized by an average annual temperature of 12.5[degrees]C and unevenly distributed precipitation of 586.4 mm. Summer (JulyAugust) rainfall usually accounts for just over 50% of total annual precipitation. The 1982 national soil survey lists three main soil types in the area: cinnamon, alluvial, and Shajiang black. Because of its favourable climate and high-soil fertility, the region is the dominant food-producing area for China (Figure 1).

We selected tins region for our study for die following reasons: Huantai County has a long history of agricultural production and has played a key role in ensuring food security for the entire country; the county exemplifies a model high-yield cropping system reflecting the intensified agricultural production practices on the northern plain of China; long-term field experiments and sitespecific observations have been conducted since the 1970s, generating accessible soil fertility and water quality data; and litde research has been performed at the regional level on agricultural sustainability assessment or on the biological, human health, or environmental consequences of modern cultivation methods.


Data collection

Data were collected from both primary and secondary sources. Primary data included household and institutional surveys and lab analyses. secondary data were taken from statistical yearbooks and documents from the local statistical department and relevant government agencies.

Establishment of the ASI hierarchy

The main challenge in measuring agricultural sustainability is to define the scope and context at different scales. Definitions of sustainable agriculture agree on three fundamental criteria: ecological soundness, economic viability, and social acceptability. However, the importance of each of the primary criteria and of sustainable agriculture indicators is rated differendy. We used the AHP to compare multiple criteria and indicators. AHP is a systematic, compensatory, multi-attributes approach that can involve both quantitative and qualitative elements. In conventional AHP, reciprocal conditions, homogeneity, dependence and expectations should be observed (Armacost et al. 1999; Mau-Crimmins et al. 2005). Using the specific characteristics of a high-yield cropping system and the place-specific attributes, we constructed a hierarchical framework to assess sustainable development in a regional agroecosystem from social, economic and ecological perspectives. The hierarchy of our regional agricultural development assessment was constructed with the goal of 'sustainability' at the top, followed by the three fundamental criteria (social acceptability, economic viability and ecological integrity) and 11 indicators at the lowest level (Figure 2). The assessment was developed from field surveys, discussions with experts, and a literature review. As shown in Figure 2, the objective at layer 1 is sustainable development. The three main criteria of social, economic and ecological factors comprise layer 2. Finally, the 11 indicators that were used to assess sustainability are listed in the third layer.

Weights determination and data standardization

After developing the ASI hierarchy, we set the relative weights of the different levels. In light of the subordinate relationship of the lower layers to those above and the relationship of factors at the same level, the importance of the various ASI factors was compared to determine the weighting. The relative importance of the indicators was expressed on a scale from 1 to 9 (Krajnc and Glavic 2005). A value of 1 indicates that two factors are equally preferred, while a value of 9 indicates that one is nine times more important than the other (Table 1).

To calculate the weighting of the three criteria and 11 indicators, we constructed a judgment matrix. As shown in Table 2, the social acceptability, economic viability and ecological integrity elements were given values of 0.279, 0.349, and 0.372, respectively, according to their roles in local agricultural development. The weighting of the 11 indicators was 0.444 (Cll), 0.556 (C12), 0.334 (C21), 0.257 (C22), 0.223 (C23), 0.186 (C24), 0.170 (C31), 0.183 (C32), 0.212 (C33), 0.242 (C34), and 0.193 (C35). In order to control the results of the AHP method, a pairwise comparison was made to examine the consistency ratio (CR) among the indicators at the given level. Comparisons were acceptable for a CR

Arable land fertility contained four soil factors: alkali- dissolved nitrogen, readily available phosphorus, readily available potassium and organic matter. The calculation was as follows: arable land fertility = (0.375 x alkali-dissolved nitrogen) + (0.125 x readily available phosphorus) + (0.125 x readily available potassium) + (0.375 x organic matter). The data for the four indicators were standardized before calculating the soil fertility index.

The main constraint in developing an agricultural sustainability assessment is determining how to aggregate indicators with different attributes into an holistic evaluation. A common way to solve this problem is to normalize the indicators. We standardized our data using the following formula (Krajnc and Glavic 2005): Sij = (Aij- a- f / (b^sub j^-a^sub j^), where Sij is the standardized value, Aij is the actual value, a is the minimum of the j range, and b^sub j^ is the maximum of the j range.

Construction of the evaluation model

Comprehensive information on sustainable development in agriculture is essential to constructing a regional-scale assessment model. An excessive number of indicators creates difficulties in judging the current status of the agricultural system. Thus, a quantitative model may be used to obtain a composite assessment of agricultural sustainability. We grouped the standardized indicators into three sustainability sub-criteria, and tiien used AHP to syndiesize them into an overall index of die agricultural system. A simple madiematical model was set up to integrate social, economic and ecological information: I^sub AS^ = (W^sub society^ x I^sub society^) + (W^sub economy^ x I^sub economy^) + (W^sub ecology^, x I^sub ecology^), where IAS is the agricultural sustainability exponent; W^sub society^, W^sub ecmomy^, and W^sub ecologyy^, are the weighted social, economic and ecological factors; and I^sub society^, I^sub economy^, and I^sub ecology^ are the separate evaluation exponents of each of the three subunits.


Five ecological, four economic and two social indicators were integrated into sustainability sub-indices at a regional scale and then aggregated into an agricultural sustainability exponent. We calculated the individual development index of die three subunits and the integrated agricultural sustainability exponent to analyze the 1982-2003 trend presented in Figure 3. The three subunits reflected different changes: the social and economic curves trended upward, with the economic curve fluctuating strongly over time, while the ecological index digressed. The I^sub AS^ and the subunit indices revealed the development trend of the agroecosystem for any given year relative to other years.

Change in agricultural sustainability on a temporal scale

The change in the I^sub AS^ value from 1982 to 2003 demonstrates thiat the agricultural system maintained progress toward sustainability over that period (Figure 3a). A higher I^sub AS^ value indicates the development of greater agricultural sustainability and is synchronous to a higher score of the three sub- indices, I^sub society^, I^sub economy^ and I^sub ecology^. The development curve can be pictured as a parabola. The value fell in 1997, relative to the two preceding years. It peaked in 1999, and then declined in the following two years. In 2002, the I^sub AS^ value began to rise again, with the 2003 value higher than that of the base year 1982, thus demonstrating an overall improvement in agricultural sustainability. The relatively high I^sub AS^ value can be understood as a measure of the probability of maintaining progress in sustainability in subsequent years in Huantai County.

However, it is difficult to achieve a true conclusion through some exterior phenomena. In fact, the current production pattern did not allow the county to maintain its progress in agricultural sustainability. Officials at different governmental levels must acknowledge the serious problems impeding agricultural sustainability. Social conditions, agricultural production and the environmental quality of the county were appraised by calculating the sub-indices. Wide variations existed within the three subunits during 1982-2003 (Figure 3b). Three distinct development periods could be distinguished within the whole timeframe. The first was the period from 1982 to 1993; the second, from 1993 to 1999; and the third, from 1999 to 2003. In the first stage, the social (I^sub society^) and economic (I^sub economy^) sub-indices climbed steadily. Then they began to develop opposing trends. Simultaneously, the ecological subindex (I^sub ecology^) fluctuated weakly, which indicated that the rapid economic and social development did not have large negative impacts on environmental quality. The modernization of farm cultivation technology and the broad introduction of better seed stocks stimulated the social and economic improvement in agriculture. At the initial stages of the improvement in productivity, the ecological system could retain its resilience and stability in die face of rapid social and economic change. From 1993 to 1999, the huge changes that had occurred in the ecological, social and economic systems were reflected in the fluctuations of I^sub socieyy^, I^sub economy^, and I^sub ecology^. The social subindex continued to trend upward, while the ecological and economic indices were altered. l^sub ecology^ decreased sharply and reached its lowest value in 1996. From there, it increased rapidly and peaked in 1999. The ups and downs in leamm, over the seven years were mainly due to fluctuations in food prices in the domestic market, which led to a reduction from 2.956 to 2.354 in the agricultural cost-benefit ratio. During the same period, land productivity showed little increase, and suffered a large drop in 1997. The sudden drop in food prices beginning in 1993 hindered progress in crop cultivation and reduced food production. After 1997, the rise in food prices induced an economic recovery.

Similar to the economic sub-index, the ecological sub-index also displayed complex changes, tracking the social and economic changes. The alterations in the ecological sub-index in die three time periods were substantial. A calamitous storm in 1997 dropped I^sub ecology^ to its lowest value. It began to rise as I^sub economy^ recovered. During the course of 1999-2003, Ieamom. decreased in the first two years and then stabilized. However, the social subindex I^sub society^ continued an upward trend, while I^sub ecology^ plummeted. The main cause of the ecological degradation was a decline in landscape diversity, arable land area, and especially groundwater resources, due to wholesale land conversion and farm cultivation. This result underscored the fact that a single index cannot determine the I^sub AS^ value. The economy can critically influence regional development, but it does not determine systematic sustainability. This is an important point because the current emphasis on economic development tends to overshadow environmental protection and sustainability.

AMOEBA reading of agricultural sustainability

An AMOEBA reading provides a graphic representation of system performance as assessed through various factors that cannot be expressed by other tools. Thus, an overall assessment by a visual recognition of the difference among various profiles is possible.

As shown in Figure 3, the I^sub AS^, and the I^sub society^, I^sub economy^ and I^sub ecology^ can also illuminate positive or negative tendencies in the agricultural system during 1982-2003. However, the key factors inducing changes in the I^sub AS^ and sub- indices could not be identified by analyzing the fluctuant curves. Hence, we investigated changes in the critical indicators through the AMOEBA approach. The AMOEBA reading shown in Figure 4 characterizes the various agricultural system indicators in the different development stages. Figure 4 shows four composite evaluations of agricultural sustainability in Huantai County for the years 1987, 1993, 1999 and 2002. Each circle was divided into 11 equal parts for each of the ASI indicators. The indicator data were normalized and assigned a fixed value in a coordinate system. The indicator values were then linked, forming an irregular polygon. We could then determine the limiting factors of a sustainable agroecosystem by the proportion of the circle each indicator occupied. A comparison of the four profiles in Figure 4 (the distribution of actual results over the feasibility domains, i.e. the filled areas) shows die influence of various factors on the agricultural system as it operated in different socioeconomic and ecological contexts.

In the 1980s, a socioeconomic depression and lagging development were the main drawbacks to systematic sustainability, while the ecosystem benefited from less human influences. In the early 1990s, improvements in agro-technology led to greater development and land productivity. Holistic development of the agroecosystem peaked in 1999, but became unbalanced in 2002. The AMOEBA reading shows that social and economic indicator values in Huantai County continued to progress, but ecological indicator values declined. The rapid development of the socioeconomic system came at a cost to the environment. Most important was the large decrease in groundwater, which is the main resource for farm irrigation. Excessive groundwater use caused a water scarcity, further affecting agricultural production and living conditions. In addition, the same rate of fertilizer use could not elevate soil fertility to the extent of the early years, leading to a drop in agricultural productivity. Thus, social and economic factors were the limiting elements in the early development period, and the scarcity of resources and environmental degradation were the dominant elements in die later stage. In order to ensure agricultural sustainability, social, economic and ecological subsystems must be developed in an integrated fashion. In addition, the assessment of the sustainability of the agricultural system should be made from a holistic perspective. DISCUSSION AND CONCLUSIONS

Diverse concepts of agricultural sustainability, differing descriptions of agroecosystem performance, and spatiotemporal complexities increase the difficulty of constructing an evaluation index and suggesting solutions to current problems (Andreoli et al. 1999; Bell and Morse 2005). Furthermore, ecological factors tend to be ignored in intensive agriculture as demographic and socioeconomic pressures rise (Giampietro 1997). From our analysis, the ASI constructed for Huantai County accurately reflected the state of agricultural development. Therefore, this ASI can be applied to other high-yield areas at regional or local scales. Our investigation of the social, economic and ecological dimensions of agricultural sustainability on a county scale showed that environmental factors were the main constraint to the agricultural progress of Huantai County. Current flood irrigation practices depleted groundwater resources. Excessive use of chemical fertilizers (300-500 kg N/hm^sup 2^ a) further degraded the quality of the groundwater, which in turn depressed agricultural production and human health. The sharp decline in the arable land area led to a reduction in total food output, which gready threatened the food security of China. Although economic progress contributed gready to sustainable development in the agricultural system, it was not the only determining factor. Environmental and social factors should be included in an integrated assessment of agricultural sustainability. Environmental and socioeconomic factors affect agricultural production heavily and, in turn, agricultural development leads to environmental and socioeconomic alterations (D'haeze etal. 2005). Our evaluation of agricultural performance (I^sub AS^) using AHP and AMOEBA suggested that the situation in Huantai County has been relatively stable in recent years. However, more attention needs to be directed toward agriculturally derived water depletion and nitrate pollution of groundwater reserves (Liu et al. 2005). Protecting the existing soil and water resources and exploiting renewable energy sources are the pressing issues for local sustainable development. Reducing the use of chemical fertilizers and pesticides, enhancing the application of organic fertilizers, and applying scientific farm management principles will dramatically improve the agroecosystem environment (Matson et al. 1997; Messing et al. 2003). Finally, the environmental consciousness of policy makers, government managers, agricultural researchers and the farmers must be heightened.


This research was sponsored by the National Natural Science Foundation of China (Project 30270220) and the National Key Technologies R&D Program for the 10th Five-Year Plan. We would like to sincerely thank Prof. Zhang Fengrong and Prof. Liu Guangdong for their valuable suggestions and comments. We also tiiank Han Qifeng and Zhao Yueye of the Huantai County Government for providing necessary help on agricultural investigation. Thank to everyone who assisted in the work.


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Wenna Liu1, Wenliang Wu1*, Xiubin Wang2, Mingxin Wang1 and Yonghong Bao1

1 College of Resources and Environmental Science, China Agricultural University, Beijing, China

2 Plant Nutrition and Fertilizer Research Center, Chinese Academy of Agricultural Science, Beijing, China

Correspondence: Wenliang Wu, College of Resources and Environmental Science, China Agricultural University, 2 YuanMingYuan West Road, Haidian District, Beijing, 100094, China. Email: [email protected]

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