The EU-Common Agricultural Policy promotes the introduction of woody and grassy semi-natural habitats (SNH) in agricultural landscapes. While the benefits of these structures in terms of regulating services are already well understood, the understanding of the effects of SNH on visual landscape quality is still relatively unclear. This study investigates the factors determining people’s visual preferences in the context of grassy and woody SNH elements in Swiss and Hungarian landscapes. In each country, a picture-based online choice experiment with 350 participants was conducted, where in a series of choices respondents selected the pictures they liked best. Each choice set contained four pictures with different combinations of the elements crop, grassy and/or woody SNH at different seasons. The resulting data were analysed by means of latent class models including the SNH attributes ‘Woody’ and ‘Grassy’ and additional aesthetic attributes that characterize the vegetation of the pictures used. Results show that the generic SNH attributes alone do not properly explain preferences. Respondents’ choices strongly depend on specific vegetation characteristics that appear and disappear over the year. In particular, flowers as a source of colours and green vegetation as well as ordered structure and the proportion of uncovered soil in the picture play an important role regarding respondents’ aesthetic perceptions of the pictures. We conclude that while people like SNHs as elements of the agricultural landscape in principle, their aesthetic value could be improved by concentrating on more hedges and more flowering species in hedges and meadows.
Schüpbach B., Weiss S. B., Jeanneret P., Zalai M., Szalai M., Frör O.
What determines preferences for semi-natural habitats in agrarian landscapes? A choice-modelling approach across two countries using attributes characterising vegetation.
Landscape and Urban Planning, 206, (February), 2021, 1-12.
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Link: Science Direct
ISSN Print: 0169-2046
ISSN Online: 1872-6062
Digital Object Identifier (DOI): https://doi.org/10.1016/j.landurbplan.2020.103954
Publikations-ID (Webcode): 44925
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