Using a new PDP modelling approach for land-use and land-cover change predictions: A case study in the Stubai Valley (Central Alps)

Due to the progressive forest expansion in European mountain areas triggered by agricultural abandonment, semi-natural meadows and pastures of great ecological and aesthetic value are disappearing. The aim of this study is to predict and analyse the future evolution of land use and land cover (LULC) in the Stubai Valley, Central Alps. We propose a computational Population Dynamics P system (PDP) model that incorporates the main LULC change processes like plant production, grazing, abandonment and reforestation. The advantages of our LULC-PDP model are: (1) the possibility to consider a large number of wild and domestic animals of different species and LULC, (2) the parallel and interdependent evolution of processes, animals and LULC, (3) the easy introduction of new processes and, hence, (4) the straightforward application of the model in other study areas. We simulate LULC changes from 2003 to 2033 in three different scenarios: (1) continuation of current land use, (2) slight reduction in land-use intensity and (3) strong reduction in land-use intensity. Furthermore, we use response-surface models that relate the response variable area and livestock annual variation, allowing better interpretation of LULC changes. The results show the accurate functioning of our model as a prediction tool. We see how agriculturally used grasslands progressively decrease, whereas the forest area increases in all simulated scenarios. The most likely zones to be abandoned are found in the intermediate altitudinal range between 1500 and 2150 m, mostly on steep slopes (>30°). The reduction in the number of cattle is closely linked to the decrease in grazing land. As this tendency questions the conservation of traditional agricultural land, it is important to apply new strategies to preserve these cultural landscapes and the multiple ecosystem services for future generations before they disappear definitively.