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In this work, we developed a RS-based methodology aimed at improving the assessment of inter-annual land cover dynamics in heterogeneous and resilient landscapes. This is the case of the Spanish Natural Park of Sierra de Ancares, where human interference during the last century has resulted in the destruction and fragmentation of the original land cover. A supervised classification with a maximum likelihood algorithm was followed by an uncertainty assessment by using fuzzy classifications and confusion indices (CI). This allowed us to show how much of the study area contains a substantial amount of error, distinguishing data that might be useful to measure land change from data that are not particularly useful, and therefore to detect true changes not skewed by the effects of uncertainty. Even if patterns of change were always coherent among images, they were more realistic after reducing uncertainty, although the number of available pixels (i.e. unmasked by the method) decreased substantially. Using these data, we modelled land cover dynamics by using a program specifically created to determine the frequency of disturbances (mainly fire events), or recurrence, and the vegetation recovery time during the study period. The model outputs showed correlated landscape patterns at a broad scale and provide useful results to explore land cover change from pattern to process.

Summary In Mediterranean mountainous areas, forests have expanded in recent decades because traditional management practices have been abandoned or reduced. However, understanding the ecological mechanisms behind landscape change is a complex undertaking because the influence of land use may be reinforced or constrained by abiotic factors such as climate. In this work, we evaluated their combined effects on recent forest expansion across climatic, topographic and management gradients. We used orthorectified aerial photographs from the second half of the twentieth century (1956, 1974, 1983, 1990 and 2004) to monitor changes in forest distribution in a set of 20 head‐water basins in the Cantabrian Mountains of north‐west Spain, at the Eurosiberian–Mediterranean limit. In particular, we evaluated the role of land‐use history (comparing natural vs. anthropic basins) and microclimate (comparing shaded vs. sunny aspects) of forest gain/loss rates and spatial distribution shifts. Finally, we applied Species Distribution Modelling techniques (MaxEnt and BIOMOD) in the stated scenarios of land‐use history and microclimate, to assess habitat suitability for forest expansion on the basis of topography, soil properties and mesoclimatic variables. Forest cover increased from 10.72% in 1956 to 27.67% in 2004 in the area. The rate of expansion was significantly higher in natural basins and, particularly, on shaded slopes. In all cases, the mean elevation of new forest patches increased during the study period, which was particularly evident on natural sunny slopes. The performance of the models and the magnitude of the effects varied across land‐use histories and microclimatic conditions. Soil properties and temperature and precipitation in late spring and early summer were the main drivers of forest expansion in modelling exercises, although expansion rates and upward altitudinal shifts were primarily controlled by land‐use history and the biogeographic origin of the forests. Synthesis. The combination of monitoring and modelling techniques used in this work contributed to the understanding of forest expansion in cultural systems, indicating that ecological succession is not a homogeneous process, but varies spatially due to human and abiotic constraints since historical times.

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