Abstract
Land use change significantly affects ecosystem services provision. This impact, however, is difficult to assess and thus often neglected in policy making. It is therefore the task of territorial planning discipline to explore methodological approaches capable of making explicit complex relationships in order to use them as tools for effectively designing the sustainable development.
In this paper, we report changes in land use over a 28-year period considering the territory of the Basilicata region. Our aim is to translate these changes in ecosystem services values, highlighting potentials of a framework able to integrate monetary figures into a larger approach based on the interactions between biomes and the meaning of human well-being more closely linked to the economics sector.
The results show that the greatest loss occurred at the detriment of wooded areas and agricultural mosaic while bare land and arable land increased. Several municipalities experienced significant changes involving above all the classes in the agricultural compartment. The growth of urban settlements took place everywhere affecting to a much greater extent the most important centers, the only ones not subject to depopulation.
Our estimate quantifies these changes in a total annual loss of ecosystem service delivery higher than €39 million with some municipalities where this loss corresponds to a significant part of GDP. Reversing the perspective, moreover, the internal areas emerge where, also due to depopulation, the monetization of ecosystem services leads to pro capita amounts equivalent to multiples of GDP per capita.
The study sets the basis for an approach oriented towards defining tangible criteria for assessing the sustainability of territorial transformations and land use change.
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Pilogallo, A., Saganeiti, L., Scorza, F., Murgante, B. (2020). Assessing the Impact of Land Use Changes on Ecosystem Services Value. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2020. ICCSA 2020. Lecture Notes in Computer Science(), vol 12253. Springer, Cham. https://doi.org/10.1007/978-3-030-58814-4_47
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