This paper analyses the effects of land abandonment on runoff and sediment yield in a central inland area of Portugal. Rainfall simulation experiments were performed in areas of traditional land use (land cultivated with cereals) with various types of soil plant cover associated with the period of abandonment (4-5 years, 15-20 years and 30-40 years) in two different seasons, namely under very dry conditions and after a long wet period.Statistical analysis showed a notable difference between the cultivated soils and those abandoned for a long period of time, which included appreciable vegetation recovery, higher organic matter content and negligible overland flow and soil loss. Cereal cultivation, in particular ploughing, is a very negative land management practice, due to the high runoff and soil loss. Within 4-5 years a crust develops over abandoned soils with sparse herbaceous plant cover, particularly after a dry season, which enhances runoff and sediment yield. In scrubland and oak plots, although marked water repellency was registered at the end of a dry, warm season, its influence seems to be irrelevant in terms of overland flow and erosion yield. The major factor in controlling overland flow and reducing soil erosion rates appears to be the role played by vegetation in protecting the soil surface and supplying organic carbon to the top layer.
Coastal dune fields and dune-body associated lakes were studied through sedimentological, malacological and palynological analyses. Lake deposits and palaeosoil horizons gave new information about phases of aeolian activity and dune building, coastline and sea level, vegetation history and cultural impact. After a period of intense aeolian activity (Late Pleistocene) that limited soil-forming processes, a wet aeolian field, recorded by podzolized sands and interdune wetland deposits, was present in the region. Around 5000 to 4000 yr BP sea level reached the current level and the coastline was situated c. 1 km further inland compared with the present situation. Subsequently lagoon-barrier island systems developed c. 4000 yr BP. Vegetation in the region during this time was a pine/oak forest. Between 4000 and 1600 yr BP the forest was replaced by a semi-natural heathland. Later the heathland was degraded, allowing dune migration and finally formation of a desert-like landscape. This process was probably a consequence of a combination of deteriorating climate during the ‘Little Ice Age’ (LIA) and overgrazing. To counteract sand invasion, reforestation efforts were initiated in the region c. 300 years ago and locally along the coastal margin between 1924 and 1940. Formation of the row of freshwater lakes bordering the dune field at present was contemporaneous with the initial reforestation phase. A close relation between lake formation and accumulation of sand dunes was found. Various types of dunes were identified, truncated dunes, parabolic dunes and transverse/oblique dunes. Dune migration caused an eastward displacement of lakes.
Geographic information system analysis and artificial neural network modelling were combined to evaluate forest-fire susceptibility in the Central Portugal administrative area. Data on forest fire events, indicated by burnt areas during the years from 1990 to 2007, were identified from official records. Topographic, supporting infrastructures, vegetation cover, climatic, demographic and satellite-image data were collected, processed and integrated into a spatial database using geographic information system techniques. Eight fire-related factors were extracted from the collected data, including topographic slope and aspect, road density, viewsheds from fire watchtowers, land cover, Landsat Normalised Difference Vegetation Index, precipitation and population density. Ratings were calculated for the classes or categories of each factor using a frequency-probabilistic procedure. The thematic layers (burnt areas and fire-related factors) were analysed using an advanced artificial neural network model to calculate the relative weight of each factor in explaining the distribution of burnt areas. A forest-fire susceptibility index was calculated using the trained back-propagation artificial neural network weights and the frequency-probabilistic ratings, and then a general forest-fire susceptibility index map was constructed in geographic information system. Burnt areas were used to evaluate the forest-fire susceptibility index map, and the results showed an agreement of 78%. This forest-fire susceptibility map can be used in strategic and operational forest-fire management planning at the regional scale.
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