title: A comprehensive assessment of agricultural intensification scenarios for the Dongting Lake basin in south-central China in 2030.
abstract: To explore the future of the material demand, pollutant emission, production, and arable land area surrounding the Dongting Lake basin, and to find a potential solution for agricultural development, this study assumes the following four agriculture intensification scenarios: the natural development scenario (ND), the production development scenario (PD), the moderate intensification scenario (MI), and the local resilience scenario (LR). The scenarios focus on different developmental patterns (natural development, short-term production growth, long-term sustainability, or self-sufficiency).The result shows to satisfy the food demand in 2030, and the production of crop and meat will be 26.96, 30.25, 28.05, and 16.27 × 10(6) t in ND, PD, MI, and LR, respectively; more than 1.78 × 10(6) ha of arable land is needed. Compared with the year 2012, the material input and pollutant output will increase by a maximum of 18.32 and 122.31 %, respectively. By classifying the environmental risk into four categories-greenhouse gas emission, air pollution, eutrophication, and ecotoxicity-the composite environmental risk index (CER) is calculated. The CER in PD was the highest, followed by that in ND, LR, and MI. Due to the production allocation within the 35 cities and counties, the spatial distribution of CER is more homogenous in PD and MI than in ND. The analysis of the scenarios reveals that through technological improvement and spatial allocation of agricultural production, scenario MI could be a potential direction for the government to design a sustainable agricultural-environmental system.
authors.affiliation: Department of Land Resources Management, College of Resources and Environmental Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.
authors.forename: Guanyi
authors.initials: G
authors.lastname: Yin
authors.affiliation: Department of Land Resources Management, College of Resources and Environmental Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China. liulm@cau.edu.cn.
authors.forename: Liming
authors.initials: L
authors.lastname: Liu
authors.affiliation: Department of Land Resources Management, College of Resources and Environmental Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.
authors.forename: Xiao
authors.initials: X
authors.lastname: Chang
authors.affiliation: Department of Land Resources Management, College of Resources and Environmental Sciences, China Agricultural University, No. 2 Yuanmingyuan West Road, Haidian District, Beijing, 100193, China.
authors.forename: Jin
authors.initials: J
authors.lastname: Sun
mesh_terms: D000383:Agriculture / Q000379:methods* / Q000639:trends; D002681:China; D003247:Conservation of Natural Resources / Q000379:methods* / Q000639:trends; D018556:Crops, Agricultural / Q000254:growth & development*; D005544:Forecasting; D060106:Lakes / Q000737:chemistry*; D008962:Models, Theoretical
keywords: Agricultural intensification; Agricultural land use; Environmental risk; Material input; Pollutant output; Scenario analysis