Abstract

Plantation, forestry, and livestock are inseparably intertwined and constitute the main sectors of the agricultural system. An integrated analysis of energy flow and material conversion processes of the agro-forestry-livestock system is beneficial for achieving sustainable and coordinated agricultural development. The availability of water resources is sensitive to climatic conditions and human activities, and uncoordinated water allocation affects the combined efficiency of various agricultural sectors. Therefore, an integrated modeling framework, based on the water-energy-food nexus under water supply uncertainty, is developed to maximize the performance of agro-forestry-livestock system. The advantages of the model include (1) systematic analysis of energy flow and material conversion processes in farmland, forest land and livestock; (2) consideration of trade-offs between economic benefits, multiple energy use efficiency (biomass, light energy), environmental impacts, and ecological benefits in the system; and (3) rational allocation of farmland, forest land, and livestock resources under the uncertainty of water supply. Empirical frequency analysis was used to obtain different frequencies of water supply. The model framework is based on a multi-objective programming model, which is solved by an affiliation function approach. The model constructs several objective functions, such as economic benefits, bioenergy productivity, light energy use efficiency, ecological economic benefits, and greenhouse gas emissions of the agro-forestry-livestock system. The concordance index was applied to evaluate the integrated performance of the model. The method was applied to Heilongjiang Province in northeastern China, where plantation, forestry, and livestock are predominant. Results show that livestock manure and urine have the highest energy potential, followed by wood, and straw has the lowest energy production. The main contribution to greenhouse gas emissions from the plantation is N2O, and the main contribution from livestock is CH4. The model had a higher concordance index for the larger water supply, but lower crop yield and photosynthetically active radiation. The proposed modeling framework contributes to the generation of stable and coordinated optimization solutions and provides decision makers methods and perspectives for sustainable agriculture.

Full Text
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