Park managers in alpine areas must deal with the increase in forest coverage that has been observed in most European mountain areas, where traditional farming and agricultural practices have been abandoned. The aim of this study is to develop a fine-scale model of a broad area to support the managers of Paneveggio Nature Park (Italy) in conservation planning by focusing on the fate of priority areas for conservation in the next 50-100 years. GIS analyses were performed to assess the afforestation dynamic over time using two historical maps (from 1859 and 1936) and a series of aerial photographs and ortho-photos (taken from 1954 to 2006) covering a time span of 150 years. The results show an increase in the forest surface area of about 35%. Additionally, the forest became progressively more compact and less fragmented, with a consequent loss of ecotones and open habitats that are important for biodiversity. Markov chain-cellular automata models were used to project future changes, evaluating the effects on a habitat scale. Simulations show that some habitats defined as priority by the EU Habitat Directive will be compromised by the forest expansion by 2050 and suffer a consistent loss by 2100. This protocol, applied to other areas, can be used for designing long-term management measures with a focus on habitats where conservation status is at risk.

© iForest -Biogeosciences and Forestry IntroductionForest cover in the Alps in the past centuries was shaped by human activities: agriculture and timber harvesting affected the lower and intermediate elevations while farming the higher (MacDonald et al. 2000). In fact, the traditional form of farming in the Alps involved moving livestock (mainly cows and sheep) from the valleys to the higher pastures according to the season. In winter the animals were sheltered in the valleys while during the summer they were carried to higher pastures where they could exploit the seasonal abundance of food. The herdsman used to stay in the typical mountain dairy called "Malga" surrounded by natural pastures or grassland derived from forest clearance (Piussi 2000). Farming in these areas was traditionally extensive and carried out by means of local and frugal breeds.During World War I the forests of the eastern Italian Alps were extensively exploited by the soldiers because the fighting took place on the national border which ran along the tops of the mountains in the area being investigated. Since the end of World War II land use in mountain areas has changed dramatically: as many people moved to the cities, the traditional activities were almost abandoned, and consequently the pressure that shaped the vegetation for centuries was no longer there (De Natale et al. 2005, Sitzia et al. 2007, Sitzia 2009). While these social issues affect the Alps as well as in the study area, their impact on vegetation distribution and composition are harder to estimate (Swetnam et al. 1999, Scarascia-Mugnozza et al. 2000, Ciolli et al. 2002, Dullinger et al. 2003, Garbarino et al. 2009).There are interesting studies showing that agriculture related biodiversity is highly threatened both through abandonment and intensification but, unfortunately, much of the available data concerns arable and lowland farmland, although there is a lack of knowledge in mountain areas (Marriott et al. 2004).The The problem has been fully recognised also at EU level: a recent EEA report (European Environment Agency 2004) stresses the fact that the prevalence of high nature value farmland is in less productive areas, such as those located in southern Europe and in mountainous regions. Many relevant conservation efforts have been undertaken at a European level, such as the Pan-European biological and landscape diversity strategy, the Bern Convention, the European Landscape Convention, the Birds and Habitats Directives.In order to understand the ecological dynamics in the Alps under changing social and climatic conditions, it is crucial to develop a knowledge of what the forest landscape was like in the past and to get a precise idea of the rapidity of the natural succession set up in the open semi-natural grassland habitats.Multi-temporal analysis of historical maps, aerial photographs and satellite images with the aid of GIS is the best tools to reconstruct the past distribution of forest cover. The recent availability of aerial and satellite imagery and of the instru...

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A recently discovered population of the North American grey squirrel (Sciurus carolinensis), introduced to Ticino Park, Lombardy (N Italy)

Historical maps constitute an essential information for investigating the ecological and landscape features of a region over time. The integration of heritage maps in GIS models requires their digitalization and classification. This paper presents a semi-automatic procedure for the digitalization of heritage maps and the successive filtering of undesirable features such as text, symbols and boundary lines. The digitalization step is carried out using Object-based Image Analysis (OBIA) in GRASS GIS and R, combining image segmentation and machine-learning classification. The filtering step is performed by two GRASS GIS modules developed during this study and made available as GRASS GIS add-ons. The first module evaluates the size of the filter window needed for the removal of text, symbols and lines; the second module replaces the values of pixels of the category to be removed with values of the surrounding pixels. The procedure has been tested on three maps with different characteristics, the “Historical Cadaster Map for the Province of Trento” (1859), the “Italian Kingdom Forest Map” (1926) and the “Map of the potential limit of the forest in Trentino” (1992), with an average classification accuracy of 97%. These results improve the performance of classification of heritage maps compared to more classical methods, making the proposed procedure that can be applied to heterogeneous sets of maps, a viable approach.

Abstract:The brown marmorated stink bug, Halyomorpha halys Stål (Hemiptera: Pentatomidae), is an invasive pest that has expanded its range outside of its original confinements in Eastern Asia, spreading through the United States, Canada and most of the European and Eurasian countries. The invasiveness of this agricultural and public nuisance pest is facilitated by the availability of an array of suitable hosts, an r-selected life history and the release from natural enemies in the invaded zones. Traditional monitoring methods are usually impeded by the lack of time and resources to sufficiently cover large geographical ranges. Therefore, the citizen science initiative "BugMap" was conceived to complement and assist researchers in breaking down the behavior of this invasive pest via a user-friendly, freely available mobile application. The collected data were employed to forecast its predicted distribution and to identify the areas at risk in Trentino, Northern Italy. Moreover, they permitted the uncovering of the seasonal invasion dynamics of this insect, besides providing insight into its phenological patterns, life cycle and potential management methods. Hence, the outcomes of this work emphasize the need to further integrate citizens in scientific endeavors to resolve ecological complications and reduce the gap between the public and science.