The spatial distribution of forests in Europe represents the legacy of centuries of human land use decisions. Due to the limited availability of historical data, most studies on forest cover change focus only on analyzing recent decades, thereby overlooking the important long-term context. However, the latter is essential to improve our understanding of present landscape patterns. This study quantifies the spatiotemporal dynamics in drivers of forest gain in Switzerland. Specifically, we model forest gain in a long-term study covering 150 years (1850–2000) split into periods of similar length (∼30 years). This makes it possible to identify non-linear dynamics and whether drivers have changed over time. The rates of forest change are quantified based on analyzing historical maps and contemporary forest inventory data. Generalized additive models (GAMs) are fitted to examine the variation in the relative importance of socioeconomic and biophysical explanatory variables. Our results suggest that both biophysical and socioeconomic variables co-drive forest gain. Biophysical variables (such as temperature and slope) were identified as the major drivers explaining variations in forest gain. The most important socioeconomic driver was the change in the percentage of people employed per economic sector, although its effect came with a substantial time lag. Changes in employment per sector for the periods 1920–1941 and 1941–1980 were relevant for forest gain between 1980 and 2000. The identified time lag effect emphasizes the added value of long-term studies, since legacies may persist for decades, adding further complexity to contemporary land change processes. These findings are relevant to many temperate ecosystems that are experiencing increases in forest cover. Such insights can improve both future forest change predictions as well as the development of policies for sustainable landscape management.
- Historical maps
- Long-term forest cover expansion
- Socioeconomic and biophysical drivers
- Time lag effect