Reducing livestock quantities to avoid manure nitrogen surplus: would meat self-sufficiency be met in eastern regions of China?

Abstract

In building a sustainable food system, the management of livestock production should avoid nitrogen (N) surplus and ensure animal-sourced food self-sufficiency. Reducing livestock quantities in regions producing excess of animal-sourced food and livestock manure is an effective approach for mitigating manure N surplus. In this study, we considered the eastern regions of China as a case study to quantitatively analyze whether meat self-sufficiency could be met when reducing the livestock quantity to avoid manure N surplus. In addition to considering the baseline scenario, considering the current livestock quantity (scenario C), we defined three strategies corresponding to livestock reduction scenarios: taking meat self-sufficiency as a priority regardless of the manure balance (scenario TB); taking manure N surplus avoidance as a priority regardless of the meat balance (scenario MNB); and considering the most limiting conditions between satisfying meat self-sufficiency and avoiding manure N surplus (scenario LF). A balance index was used to describe the excess (i.e., positive value) or deficiency (i.e., negative value) of meat and manure N. Concerning the whole of eastern China, in scenario LF, the meat balance index (TBI) and manure N balance index (MNBI) were 0.25 and −0.39, respectively, which could satisfy meat demand while avoid manure N surplus (for scenarios C, TB, and MNB, the TBIs were 1.95, 0, and 1.09, and the MNBIs were 0.56, −0.48, and 0, respectively). At the regional level, the regions with meat self-sufficiency accounted for more than 70% in the LF scenario, and manure N surplus could be avoided in all regions. However, southwestern China should adopt further measures, such as trading among adjacent regions and increasing manure fertilizer application, to satisfy the meat demand while avoiding surplus manure N.

Keywords

• Reduce livestock quantity
• Manure nitrogen management
• Food security
• Spatial cluster analysis
• Integrated crop-livestock