18 research outputs found
Anthropogenic Influences in Land Use/Land Cover Changes in Mediterranean Forest Landscapes in Sicily
This paper analyzes and quantifies the land use/land cover changes of the main forest and semi-natural landscape types in Sicily between 1955 and 2012. We analyzed seven representative forest and shrubland landscapes in Sicily. These study areas were chosen for their importance in the Sicilian forest panorama. We carried out a diachronic survey on historical and current aerial photos; all the aerial images used to survey the land use/land cover changes were digitalized and georeferenced in the UTM WGS84 system. In order to classify land use, the Regional Forest Inventory 2010 legend was adopted for the more recent images, and the CORINE Land Cover III level used for the older, lower resolution images. This study quantifies forest landscape dynamics; our results show for almost all study areas an increase of forest cover and expansion, whereas a regressive dynamic is found in rural areas due to intensive agricultural and pasturage uses. Understanding the dynamics of forest landscapes could enhance the role of forestry policy as a tool for landscape management and regional planning
Analisi degli approcci scientifici per la definizione comune di rinnovazione naturale con particolare riferimento all'ambiente mediterraneo
La rinnovazione forestale è il futuro di ogni foresta ed è legata a diversi fenomeni ecologici. Molti studi hanno utilizzato vari metodi per analizzare la rinnovazione forestale; tuttavia, a livello internazionale, non esiste un metodo comune condiviso per classificare il fenomeno della rigenerazione stessa. Con l’obiettivo di trovare una possibile sintesi comune questo lavoro analizza il fenomeno della rinnovazione naturale attraverso sia l’analisi di inventari forestali sia di pubblicazioni scientifiche. La ricerca ha permesso di elaborare un elenco bibliografico multilingue attraverso l’interrogazione di database on-line, la ricerca con parole chiave e l’analisi dei riferimenti bibliografici degli articoli raccolti. L’esame di una vasta gamma di studi sulla rinnovazione forestale naturale ha permesso di selezionare i lavori scientifici che definiscono in maniera inequivocabile la rinnovazione con parametri quantitativi. I parametri presi in considerazione sono stati limitati alle misure dendrometrici più comunemente usati (altezza e diametro). Confrontando i diversi approcci quantitativi adottati nei diversi contesti ecologici è emerso che nei biomi tropicali e temperati le soglie dei parametri quantitativi tendono a valori più elevati rispetto a quelle riscontrate nei biomi Mediterraneo e della Savana. Pertanto, l’approccio comune condiviso è funzionale per standardizzare tali parametri quantitativi e per definire le soglie che caratterizzare i processi di rinnovazione in selvicoltur
Resilience of Mediterranean Forests to Climate Change
In the Mediterranean region, forests play a key role in the welfare of urban and rural peoples, by providing highly appreciated marketed goods as well as high value but nonmarket services. Anthropogenic climate change entails a significant impact on Mediterranean forests, such as the reduced species diversity, high density, pest, and diseases. In this chapter, we present the achievements of the project LIFE ResilForMed (Resilience of Mediterranean Forests to climate change), as Sicilian responds on adaptation and mitigation to climate change: (i) map of Sensitivity Forest Areas to desertification of the Sicilian region; (ii) list of bird indicators showing sensitivity to desertification in Sicily; (iii) set of resilience indicators aimed to assess the resilience of Mediterranean forests to climate changes; (iv) list of sporadic and endemic tree species of Sicilian forests; (v) development of optimal management models suitable to improve or consolidate the resilience of forest and preforest ecosystems. This work is at the forefront of developing knowhow and transferable best management practices that may help Mediterranean forests to adapt to climate change and thereby, safeguard their multifunctional benefits for future generations
Which are Southern Italy’s fastest growing tree species? Lessons from the past for future perspectives, with a special focus on Sicily
Fast growing tree species can generate high wood production in a short time frame. However, maximum productivity is dependent on environmental and management conditions as well as intrinsic plant traits. Within this framework, our research was into tree species with the highest Mean Annual Increments (MAIs) in southern Italy, particularly in Sicily. Eucalyptus spp., Acacia saligna Labill. H. L. Wendl., Ailanthus altissima Mill. (Swingle), Pinus halepensis Mill. (including Pinus brutia Ten.), Pinus canariensis C.Sm. and Pinus radiata D. Don. were identified. In particularly suitable conditions, the MAI of eucalypt coppices ranged from 8 to 12 m3 ha-1, and from 13 to 19 m3 ha-1, in Eucalyptus camaldulensis Dehnh. and Eucalyptus globulus Labill., respectively. The MAI of E. camaldulensis high forests was slightly over 6 m3 ha-1, while that of E. globulus high forests was very similar to its coppice value. Considering the preliminary data, Acacia saligna Labill. H. L. Wendl. can achieve good wood production. Pinus halepensis Mill. and Pinus brutia (Ten.) Holmboe achieved MAIs of 5-7 m3 ha-1. Other species may be promising but either data is very limited or their invasive potential requires careful consideration. This historical review has shown that with optimal tree species-planting site-cultivation technique combinations, tree species can achieve wood yields typical of fast-growing species in Mediterranean Italy, too
The evolution in time of the concept of fast growing tree species: is it possible to use a definition applicable to all environmental conditions?
Although the expression “fast-growing species” (FGS) referred to tree species has been since long time used, a clear definition has not been adopted for decades. Starting from the Italian historical background, we searched for the definitions of FGS formulated over time at a national and international level. The mean annual increment (MAI) of 10 m3 ha-1, identified by the FAO, has been the most commonly considered threshold until recently. Subsequently, experimental activities and research efforts have consistently enhanced the productivity of FGS, and other definitions have been proposed accordingly. Hence, FGS should provide annual wood yields of 15-25 m3 ha-1 with rotations of less than 25-30 years. In Europe, the maximum MAI can reach about 20-25 m3 ha-1, while in fast-growing tropical plantations the MAI frequently exceeds 30-35 m3 ha-1. However, we deem that the threshold of 10 m3 ha-1 year-1 is still reliable for Mediterranean conditions. Since the fast-growing is a relative concept, strongly affected by species’ traits, environmental conditions and cultural practices, a future increase in the productivity levels of wood plantations can be expected
Forest accessibility, Madonie mountains (northern Sicily, Italy): implementing a GIS decision support system
Valorisation and sustainable exploitation of woody biomass from cultivation interventions
might be an important opportunity to track alternative development trails for rural
communities in natural protected areas. The governance of Mediterranean protected areas
is characterized by overlapping, sometimes conflicting institutions, stakeholders and
regulations, causing negative impacts on decision-making processes. We present an open
source GIS-based decision support system tool for mapping forest accessibility and
optimizing woody biomass extraction. Two models were implemented to support forest
managers during the decision-making process in designing and managing wood-energy
supply chains. The optimal grid resolution to run the models was determined via a Least
Cost Path analysis. The models were executed at different scales, performing satisfactorily
when distances between recorded and modelled paths were lower than the grid unit. The
higher the scale, the more the percentile of distances lower than the grid unit. The models
were validated in Madonie mountains, Sicily, Italy
The evolution in time of the concept of fast growing tree species: is it possible to use a definition applicable to all environmental conditions?
Although the expression \u201cfast-growing species\u201d (FGS) referred to tree species has been since long time used, a clear
definition has not been adopted for decades. Starting from the Italian historical background, we searched for the definitions of FGS formulated over time at a national and international level. The mean annual increment (MAI) of 10 m3 ha-1, identified by the FAO, has been the most commonly considered threshold until recently. Subsequently, experimental activities and research efforts have consistently enhanced the productivity of FGS, and other definitions have been proposed accordingly. Hence, FGS should provide annual wood yields of 15-25 m3 ha-1 with rotations of less than 25-30 years. In Europe, the maximum MAI can reach about 20-25 m3 ha-1, while in fast-growing tropical plantations the MAI frequently exceeds 30-35 m3 ha-1. However, we deem that the threshold of 10 m3 ha-1 year-1 is still reliable for Mediterranean conditions. Since the fast-growing is a relative concept, strongly affected by species\u2019 traits, environmental conditions and cultural practices, a future increase in the productivity levels of wood plantations can be expected
Which are Southern Italy’s fastest growing tree species? Lessons from the past for future perspectives, with a special focus on Sicily
Fast growing tree species can generate high wood production in a short time frame. However, maximum productivity is
dependent on environmental and management conditions as well as intrinsic plant traits. Within this framework, our research was into tree species with the highest Mean Annual Increments (MAIs) in southern Italy, particularly in Sicily. Eucalyptus spp., Acacia saligna (Labill.) H. L. Wendl., Ailanthus altissima Mill. (Swingle), Pinus halepensis Mill. (including Pinus brutia Ten.), Pinus canariensis C.Sm. and Pinus radiata D. Don. were identified. In particularly suitable conditions, the MAI of eucalypt coppices ranged from 8 to 12 m3 ha-1, and from 13 to 19 m3 ha-1, in Eucalyptus camaldulensis Dehnh. and Eucalyptus globulus Labill., respectively. The MAI of E. camaldulensis high forests was slightly over 6 m3 ha-1, while that of E. globulus high forests was very similar to its coppice value. Considering the preliminary data, Acacia saligna Labill. H. L. Wendl. can achieve good wood production. Pinus halepensis Mill. and Pinus brutia (Ten.) Holmboe achieved MAIs of 5-7 m3 ha-1. Other species may be promising but either data is very limited or their invasive potential requires careful consideration. This historical review has shown that with optimal tree species-planting site-cultivation technique combinations, tree species can achieve wood yields typical of fast-growing species in Mediterranean Italy, too
Optimizing the Sampling Area across an Old-Growth Forest via UAV-Borne Laser Scanning, GNSS, and Radial Surveying
Aboveground biomass, volume, and basal area are among the most important structural attributes in forestry. Direct measurements are cost-intensive and time-consuming, especially for old-growth forests exhibiting a complex structure over a rugged topography. We defined a methodology to optimize the plot size and the (total) sampling area, allowing for structural attributes with a tolerable error to be estimated. The plot size was assessed by analyzing the semivariogram of a CHM model derived via UAV laser scanning, while the sampling area was based on the calculation of the absolute relative error as a function of allometric relationships. The allometric relationships allowed the structural attributes from trees’ height to be derived. The validation was based on the positioning of a number of trees via total station and GNSS surveys. Since high trees occlude the GNSS signal transmission, a strategy to facilitate the positioning was to fix the solution using the GLONASS constellation alone (showing the highest visibility during the survey), and then using the GPS constellation to increase the position accuracy (up to PDOP~5−10). The tree heights estimated via UAV laser scanning were strongly correlated (r2 = 0.98, RMSE = 2.80 m) with those measured in situ. Assuming a maximum absolute relative error in the estimation of the structural attribute (20% within this work), the proposed methodology allowed the portion of the forest surface (≤60%) to be sampled to be quantified to obtain a low average error in the calculation of the above mentioned structural attributes (≤13%)