A landscape project for the coexistence of agriculture and nature: a proposal for the coastal area of a Natura 2000 site in Sicily (Italy)
AbstractMany rural coastal Mediterranean areas suffer from great anthropomorphic pressure. This is due to intensive agriculture, and construction for residential, tourism and industrial uses. The present work investigates the idea of using a landscape project in the Gulf of Gela in South Sicily to recover the dunes and the area behind them. The method used is based on the literature and will evaluate and interpret the dynamics of the landscape, so as to draw up a landscape plan, which can be used to help sustain the assets of the area, in a way, which is compatible with conserving nature. This method was tested in the LIFE11-Leopoldia project, funded by the European Union. The results of the study form part of the landscape project. This project is aimed at connecting the different productive zones in the area, protecting the natural environments and the rural historical patrimony, through combining the modern road networks with the older slower, historic infrastructure. Three different levels of landscape management are proposed: total protection (the dunes), high-level protection (the area behind the dunes where traditional agriculture is practised, buffer areas and ecological connecting areas), medium levels of protection (sustainable agriculture, green connections and ecological corridors). The key aims of the project are as follows: transversality - repairing the agricultural fabric and the relationship between the land and the sea; sustainability - recovering the environmental system and traditional activities; flexibility - agriculture with only minor environmental impact.
PlumX Metrics provide insights into the ways people interact with individual pieces of research output (articles, conference proceedings, book chapters, and many more) in the online environment. Examples include, when research is mentioned in the news or is tweeted about. Collectively known as PlumX Metrics, these metrics are divided into five categories to help make sense of the huge amounts of data involved and to enable analysis by comparing like with like.
Copyright (c) 2016 Lara Riguccio, Laura Carullo, Patrizia Russo, Giovanna Tomaselli
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.