Latest Publications

Urban-Rural Co-Visioning is a highly relevant planning and research tool that addresses key challenges in urban-rural development. It helps policymakers and other stakeholders in dynamic urban-rural regions navigate transformation processes to achieve sustainability. It brings together different perspectives from planning, science and civil society, leading to a shared understanding of regional development goals, local actions and cooperation.

The findings of the URA research project clearly demonstrate how deeply embedded urban-rural relationships are in daily life and how vital they are for guiding spatial transformation toward sustainability. Drawing from the successful implementation of co-visioning processes in both research regions, the authors of this policy paper explain the preconditions and provide a step-by-step guide to co-visioning, and they offer recommendations for decisionmakers engaged at the urban-rural interface.

Abstract

Linear agricultural nutrient regimes are the principal cause for perturbation of the geochemical cycles for nitrogen (N) and phosphorus (P) and other planetary boundaries. Nutrient cycles are characterized by high spatial disparity and China is a hotspot due to high fertilizer application rates. Using substance flow analysis, this study identified and quantified nutrient flows from agricultural production to residue management of Huangyan tangerines (Citrus reticulata) and water bamboo (Zizania latifolia) in a case study of Huangyan district (Taizhou City, Zhejiang province). About 754 Mg/a of N and 105 Mg/a of P can theoretically be recovered in the tangerines and water bamboo systems from currently untapped material flows. This could replace 59% of the N and 15% of the P currently applied as chemical fertilizer, reducing environmental impacts. Combining the nutrient recovery of both systems and upscaling the results to Taizhou City, the goal from the 14th Five-Year Plan for Agricultural and Rural Modernization to save 1182 Mg of nutrients per year could be exceeded by almost 12 times. This study’s data have varying degrees of uncertainty. The analysis of data representativeness shows potential for improvements, especially in the agricultural production of water bamboo and the nutrient contents of material flows.