The impact of agroforestry networks on scenic beauty estimation: The role of a landscape ecological network on a socio-cultural process

Abstract

The reintroduction of agroforestry networks (via a GIS-supported design procedure) is one of a number of strategies that some authorities of the lagoon of Venice drainage basin (in Italy) are planning to use in order to control lagoon pollution and to achieve landscape amelioration. While attention is paid to the conservation implications and environmental effects of an ecological network, socio-cultural impacts are not generally given the same consideration. The aims of this paper were (1) to assess the impacts of agroforestry network planning outputs on the perception of landscape in terms of scenic beauty (SB) estimation, (2) to analyze the influence of socio-economic variables on the agroforestry role in SB, (3) to analyze the relationships between SB and landscape variables as measured on the local and landscape scales, and (4) to assess the strength of an expert rating SB empirical procedure utilized in the GIS system. The outcomes of the GIS planning procedure application were found to have a positive impact on the perceptive evaluation of landscape, but landscape sites preference did not appear to be significantly different between socio-economic groups: in all cases, sites with an optimized agroforestry network were preferred to the same sites without. A strong explanatory relationship was found to exist between citizens’ scenic beauty estimation (SBE) and the landscape metrics. The representative empirical procedure gave sound qualitative results for this kind of landscape, but can be efficiently substituted by the regression model tested at the “local” scale. At the “landscape” scale it appears that (1) the explanatory power of the landscape pattern metrics selected for the GIS procedure is high, even for the mean “social” SBE, (2) the main explanatory power among network metrics is expressed by connectivity and circuitry, and (3) it is reasonable to expect that the impact of an agroforestry network on citizens’ SBE could be predicted with the empirical models that were tested.