Why can China maintain a high crop diversity? A spatial-temporal dynamic analysis

Crop diversity is crucial for producing more food and nutrition in the crowded planet and achieving agricultural sustainable development, and thus it is a hot topic in shaping policies aimed at ensuring food security. Many studies have revealed that enhanced crop diversity can benefit crop productivity. However, research on how to maintain a relatively high crop diversity at regional and national scales remains limited. This study attempts to examine the underlying mechanisms of crop diversity changes in China and eventually answer why China can maintain a high crop diversity from the spatial-temporal perspective. To achieve this end, the county level crop area dataset for the period of 1980–2014 was compiled and used to quantify the spatiotemporal dynamics of crop diversity in China. The result reveals that the China’s crop diversity trended upward over past 35 years, evidenced by more than 7 major crops at national level and 4 major crops at county level having undergone massive planting process to maintain a high crop diversity. Spatially, the crop diversity increased in more than two-thirds of the counties, and its hotspots moved gradually to the south-west mountainous area. The natural factor of slope and the social factor of population density contributed to shape the crop diversity pattern in global effects. In contrast, the irrigation degree, elevation of cropland, mean annual temperature and precipitation affected the spatially non-stationary distribution of crop diversity at the local level. On the whole, the maintenance of a higher crop diversity in China not only was limited by natural conditions, but also subject to adopt the multi-cropping systems strategic choice for the country to agricultural conditions. We argued that crop diversity can be an indicator to draw agricultural zoning, and increasing crop diversity should be recognized as a policy tool to implement agricultural sustainable development strategy.

Data-Driven Evaluation and Optimization of Agricultural Sustainable Development Capability: A Case Study of Northern Anhui

Human survival depends on the sustainable development of agriculture. This study constructs a data-driven evaluation and optimization method of agricultural sustainable development capacity, aiming to better cope with challenges such as environmental pollution and excessive consumption of resources and energy, as well as improve agricultural economic level. Further, an evaluation index system was constructed based on comprehensive consideration of energy and resources utilization, environmental pollution, and agricultural economy. After simplifying and integrating the data, a data envelopment analysis model was constructed to quantitatively evaluate the capability for agricultural sustainable development and its changing trend. Moreover, its influencing factors were analyzed from the perspective of input, which provides accurate countermeasures for improving agricultural sustainable development ability, resource utilization efficiency, and process optimization. This study shows the realization process of the aforementioned method for the agricultural development of six cities in northern Anhui from 2010 to 2019. Our results suggest that the sustainable development ability of northern Anhui is weak, but overall, has a good development trend. Based on our results, some countermeasures were proposed to control production scale reasonably, reduce environmental load, and improve resource efficiency, which provides a reference for policymakers to guide and standardize the development of regional agriculture.

Consumption and Production Patterns for Agricultural Sustainable Development

Agriculture has always played a key role in feeding the world population and ensuring the development of sustainable food production systems [...]

The critical review of agriculture technological transfer in the era of decentralization

The progress of agricultural technological transfer in accordance with socio-economic conditions has long been recognized as an obstacle in accelerating agricultural development. After two decades of implementing decentralization, Indonesian agricultural technological transfer has become more complex. The purpose of this study is to identify the performance of the agricultural technological transfer after two decades of implementation of the decentralization in Indonesia. The lack of collaboration between the various agriculture institutions, as well as a centralistic approach in agricultural development for more than three decades considered to be the main inhibiting factor of the effectiveness of technological transfer. The implementation of the decentralization policy in early 2001 has affected in changes fundamental of the organizational structure and management of government institutions that carry out extension functions in agriculture. This fundamental change has implications in the performance of most agricultural sector’s organizations and personnel. Developing agricultural sustainable development requires collaboration between local, regional and central levels. In creating decentralized agricultural policy, including the technology transfer and innovation, it will be effective when they have commitment to a mutually support between related institutions. Pentahelix sinergy among stakeholders in local level will be substantial for maintaining long term agricultural sustainable development goals.

Application and Comparison of Multiple Models on Agricultural Sustainability Assessments: A Case Study of the Yangtze River Delta Urban Agglomeration, China

Operationalization of sustainability assessments is necessary to promote the sustainable development of agroecosystems. However, primarily, focus has been on the development of sustainability assessment tools with less attention on whether these are suitable for adoption and implementation in specific areas. This drawback could lead to inappropriate management guidance for agricultural practices. Hence, three extensively used models, i.e., the Driver–Pressure–State–Impact–Response (DPSIR) framework, ecological footprint (EF), and emergy analysis (EMA), were applied to quantify the sustainability performance of the agroecosystems in 27 cities in the Yangtze River Delta Urban Agglomeration (YRDUA), China, in 2016. The models were compared using the Pearson correlation analysis and natural break method, to determine a more adaptive method for agricultural sustainability assessments. The level of agricultural sustainable development of each city varied according to the methodology considered for its calculation. Compared with the EMA model, the DPSIR and EF models showed a better relationship (Pearson correlation coefficient of 0.71). The DPSIR model more accurately represented regional rankings of the agricultural sustainability at the municipality level due to its comprehensive consideration of multiple dimension factors and significance for policy making. However, each methodology has its own contribution depending on the study objectives. Hence, different models should be used for adequate determination of agricultural sustainable development at different regional scales; this would also enable better implementation of agricultural practices as well as policies in any given agricultural area for promoting the sustainable development of agroecosystems.