杨波, 何露, 闵庆文. 城市边缘区农业劳动生产率综合评价——以四川郫都林盘农耕文化系统为例[J]. 中国生态农业学报(中英文), 2020, 28(9): 1397-1404. DOI: 10.13930/j.cnki.cjea.190897
引用本文: 杨波, 何露, 闵庆文. 城市边缘区农业劳动生产率综合评价——以四川郫都林盘农耕文化系统为例[J]. 中国生态农业学报(中英文), 2020, 28(9): 1397-1404. DOI: 10.13930/j.cnki.cjea.190897
YANG Bo, HE Lu, MIN Qingwen. Comprehensive evaluation of agriculture labor productivity in Pidu Linpan Farming System in Chengdu urban fringe[J]. Chinese Journal of Eco-Agriculture, 2020, 28(9): 1397-1404. DOI: 10.13930/j.cnki.cjea.190897
Citation: YANG Bo, HE Lu, MIN Qingwen. Comprehensive evaluation of agriculture labor productivity in Pidu Linpan Farming System in Chengdu urban fringe[J]. Chinese Journal of Eco-Agriculture, 2020, 28(9): 1397-1404. DOI: 10.13930/j.cnki.cjea.190897

城市边缘区农业劳动生产率综合评价——以四川郫都林盘农耕文化系统为例

Comprehensive evaluation of agriculture labor productivity in Pidu Linpan Farming System in Chengdu urban fringe

  • 摘要: 提高农业劳动生产率是促进农业农村发展的重要路径,是乡村振兴战略的基本要求,对农业劳动生产率的综合评价是因地制宜地提出乡村发展路径的基础。位于城市边缘的传统农耕地区面临路径选择的困境,对这类地区农业劳动生产率等指标的测算和评价,可为地区经济发展、劳动力转移等研究奠定基础。本研究以地处成都市郊的中国重要农业文化遗产四川郫都林盘农耕文化系统为例,对遗产地各镇(街道)的农业劳动生产率、劳动参与率、劳动强度指数等进行了定量测算和空间格局评价,并运用多元回归分析方法对影响农业劳动生产率的生产条件因素进行了分析研究。结果显示:1)遗产地农业劳动生产率和劳动强度指数总体水平分别为4.03万元·人-1和54.69%;12个农业镇(街道)之间的农业劳动生产率和劳动强度指数差异较大。2)各镇(街道)农业劳动生产率和劳动强度指数空间格局上均呈现出北高南低的特征;其中,唐元镇农业劳动生产率最高(6.35万元·人-1),郫筒街道最低(1.72万元·人-1)。3)各镇(街道)农业劳动参与率与城镇化程度呈空间异质性,农业参与率总体上呈西北高东南低的趋势;其中,新民场镇劳动参与率最高(45.57%),红光镇最低(8.46%)。4)各农业生产条件因素中,单位农业产值能耗、单位农用地面积化肥施用量、人均农用地面积和农业劳动参与率的提高均对农业劳动生产率具有促进作用,前两个因素对农业劳动生产率的影响大于后两个因素。基于此,郫都林盘农耕文化系统农业发展应从空间差异化、生产现代化和产业多样化等方面着手,发挥城市边缘区在资本、技术等方面的优势,维持农地轮作模式,保障西北部各镇农业持续生产,加强东南部各镇基础设施和加工业建设。同时鼓励农民开展多种经营拓宽增收渠道,促进该地区的乡村振兴。

     

    Abstract: Improving agricultural labor productivity is essential for promoting agricultural and rural development and is the basic requirement of rural revitalization strategies. The comprehensive evaluation of agricultural labor productivity is the basis of rural development strategy suitable for the local conditions. With Pidu Linpan Farming System in the suburban area of Chengdu, designated as one of the China Nationally Important Agricultural Heritage Systems (China-NIAHS) sites in 2020, as a case, this study quantitatively evaluated agricultural labor productivity, labor participation rate, and labor intensity index of 12 agricultural towns (subdistricts). Multiple regression analysis was used to research the main influencing factors of labor productivity. The results showed that the agricultural labor productivity of the overall Pidu Linpan Farming System was 4.03×104 ¥·capita-1, and the labor intensity was 54.69% in 2017. There were large differences in agricultural labor productivity and labor intensity among 12 agricultural towns. The agricultural labor productivity and labor intensity index of the heritage were higher in northern towns and lower in southern ones. The highest agricultural labor productivity (6.35×104 ¥·capita-1) was in Tangyuan Town, and the lowest (1.72×104 ¥·capita-1) was in Pitong Town. The labor intensity index of northern towns, such as Hongguang, Tangyuan, and Tangchang, was higher than 65%, while that of southern towns was lower than the overall level of the heritage. The agricultural labor participation and urbanization rates showed spatial heterogeneity, and the labor participation rate of the northwest region was higher than the southeast region. Among them, the highest agricultural labor participation rate (45.57%) was in Xinminchang Town, and the lowest (8.46%) was in Hongguang. Among the factors of agricultural production conditions, the increase of energy consumption per unit output value, fertilizer application amount per unit area farmland, agricultural area per capita, and agricultural labor participation rate promoted agricultural labor productivity. The first two factors had a greater impact on agricultural labor productivity than the latter two in the heritage. The standardization regression coefficient of energy consumption per unit output value and fertilizer application amount per unit area farmland were more than 0.93, while those of agricultural area per capita and agricultural labor participation rate were 0.637 and 0.282, respectively. Further analysis revealed that, as an important part of the Pidu Linpan Farming System, the pattern of crop rotation in flooded land and dry land was helpful to improve the utilization efficiency of land and labor resources, which promoted the farmers' concurrent business. Therefore, the agricultural development of the agricultural heritage should start from spatial differentiation, production modernization, and industrial diversification to promote rural revitalization in the adjacent areas of the city. While making full use of the advantages of urban fringe in capital and technology, the farmland rotation pattern should be maintained, and the sustainable development of agriculture in the northwestern towns and the construction of infrastructure and the processing industry in the southeastern towns should be strengthened. Based on the unsaturated state of labor intensity, farmers should be encouraged to make better use of their leisure time, develop diversified businesses and expand channels for increasing their income, and promote rural revitalization in areas as an urban fringe.

     

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