Biró M, Czúcz B, Horváth F et al: Drivers of grassland loss ... (2013)

Biró M, Czúcz B, Horváth F, Révész A, Csatári B, Molnár Zs
Drivers of grassland loss in Hungary during the post-socialist transformation (1987-1999).
Landscape Ecology 28(5): 789-803.

The increase in the speed of land-cover change experienced worldwide is becoming a growing concern. Major socio-economic transitions, such as the breakdown of socialism in Europe, may lead to particularly high rates of landscape transformations. In this paper we examined the loss of semi-natural grasslands in Hungary between 1987 and 1999. We studied the relationship between 9 potential driving forces and the fate of grasslands using logistic GLMs.
Grassland loss was found to be very high (1.31 % per year), which is far higher than either before or after this period. The most influential predictors of grassland loss were environmental and landscape characteristics (soil type, area of remnant grassland patches), and the socio-economic context (distance to paved road, and nearest settlement, human population density). Several processes and relationships can only be understood from a historical perspective (e.g. large extent of afforestation, strong decrease of soil water table). Grassland loss during the study period emerged as a consequence of survival strategies of individual farmers seeking adaptation to the changing environmental and socio-economic conditions, and not urbanization and agricultural intensification which are the main underlying drivers for the ongoing landscape transformations in most parts of the developed world.
Though globalization increasingly influences local land use decisions , reconstructing and modelling recent landscape changes cannot be done without a proper understanding of local history and culture. Our analysis shows the importance of large-area yet high resolution landscape change research, which may reveal unexpected patterns of land cover change, undetected at coarser scales.

Keywords: East-Central Europe, land-cover change, logistic GLMs, proximate and underlying driving forces