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

2020 
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.
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    42
    References
    3
    Citations
    NaN
    KQI
    []