Enhancing scientific publishing in the field of silviculture

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Assessing the mechanical stability of trees in artificial plantations of Pinus nigra J. F. Arnold using the LWN tool under different site indexes

In young black pine plantations, the most valuable and interesting thinning scheme is mainly based on the positive selection of dominant and well-shaped trees to be candidates for carbon sequestration, timber production and natural regeneration. The mechanical stability of candidate trees is here a fundamental skill that must be taken into account and the slenderness ratio (HD) is one of the main indicators. HD has been recently proved to be correlated to the living whorl number (LWN) by Cantiani & Chiavetta (2015). In this study, the statistical model was re-calibrated in order to study the influence of soil fertility on the HD - Living whorls number (LWN) relationship.The fertility-balanced models estimated a different LWN threshold. The model for the highest fertility class (Site index 24) estimated 12 LWN (RMSE of 20%). Similarly, a lower value were detected for the other two fertility classes, SI20 and SI16, where 10 LWN were considered enough with an associated RMSE of 16% and 17% respectively. Compared to the general model provided by Cantiani & Chiavetta (11 LWN with 18% of RMSE) the site index approach improved the accuracy and reliability

Forest-food nexus: a topical opportunity for human well-being and silviculture

As population will reach over 9 billion by 2050, interest in the forest-food nexus is rising. Forests play an important role in food production and nutrition. Forests can provide nutritionally-balanced diets, woodfuel for cooking and a broad set of ecosystem services. A large body of evidence recommends multi-functional and integrated landscape approaches to reimagine forestry and agriculture systems. Here, after a commented discussion of the literature produced in the last decade about the role for forests with respect to the food security global emergency, we summarize the state of the art in Italy as a representative country-case-study. The aim is to increase awareness about the potential of silviculture in Italy for combining ecological resilience with economic resilience, and reducing the pressure over tropical and sub-tropical forests by means of a sustainable intensification of forest management at national level. Although a quantification of the Italian non-wood forest products is difficult, the potential of this sector for the Italian bioeconomy is relatively high. Italy is among the four top European exporters of cork stoppers, is one of the three top countries for chestnut seed processing, and is among the leading exporters of wild mushroom, while it is the only European country among the top five global importers of tannins. In order to develop this sector for the food industry, more research is needed on non-wood forest products, the scale of production, emerging markets, marketing and production innovation. On the other hand, chain-supply fragmentation, landowner inertia, and lack of governance and cooperation may hamper an effective exploitation of non-wood products. A renewed joint impulse for exploitation of wood and non-wood products may come from a sustainable intensification of forest management. The strategies to guarantee an effective supply of non-wood products require appropriate business skills and the presence of a structured business services. A transparent market is also essential. Therefore, the introduction of standards (like those by forest certification schemes) is very important. They can add value to products and emphasize the importance and complexity of the forest sector. However, the implementation of sustainable forest management for an effective supply of non-wood products is affected by the availability of appropriate planning tools, and the public officers need a new mindset to stimulate and support business capacity of forest owners

Assestamento forestale e processi partecipativi: il caso del Parco naturale regionale dei Monti Lucretili

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Early impact of alternative thinning approaches on structure diversity and complexity at stand level in two beech forests in Italy

Stand structure, tree density as well as tree spatial pattern define natural dynamics and competition process. They are therefore parameters used to define any silvicultural management type. This work aims to report first data resulting from a silvicultural experiment in beech forests. The objective of the trial is testing the structure manipulation in terms of diversity and the reduction of inter-tree competition of different thinning approaches. Alternative thinning methods have been applied in two independent experimental sites located in the pre-Alps and Southern Apennines, in Italy. Specific goals were to: (i) verify the impact early after thinning implementation on forest structure through a set of diversity and competition metrics resulting from a literature review; (ii) the sensitivity of tested indexes to effectively detect thinning manipulation. Main result show the low sensitivity of stand structure indexes and the ability of competition metrics to detect thinning outcome

Early impact of alternative thinning approaches on structure diversity and complexity at stand level in two beech forests in Italy

Stand structure, tree density as well as tree spatial pattern define natural dynamics and competition process. They are therefore parameters used to define any silvicultural management type. This work aims to report first data resulting from a silvicultural experiment in beech forests. The objective of the trial is testing the structure manipulation in terms of diversity and the reduction of inter-tree competition of different thinning approaches. Alternative thinning methods have been applied in two independent experimental sites located in the pre-Alps and Southern Apennines, in Italy. Specific goals were to: (i) verify the impact early after thinning implementation on forest structure through a set of diversity and competition metrics resulting from a literature review; (ii) the sensitivity of tested indexes to effectively detect thinning manipulation. Main result show the low sensitivity of stand structure indexes and the ability of competition metrics to detect thinning outcome

Harmonized forest categories in central Italy

To support sustainable forest management, planning policies and environmental actions, it is essential to have available common and standardized geospatial information on forest structure, composition and distribution. In this paper we present a harmonized forest categories (HFCs) map of four administrative Regions located in central Italy (i.e. Marche, Abruzzo, Lazio and Molise) at a scale of 1:400,000. The study area extends over 42,246 km2, 14,878 km2 of which are covered by forests. Four regional forest maps were harmonized in order to produce common standardized information on composition, structure and the distribution of forests in central Italy. A forest category is a forest vegetation unit defined by the main tree species composition. In this study we adopted a nomenclature scheme composed of 16 forest and shrubland categories. This work represents the first HFCs map in Italy over a large area. The legend is also harmonized with the European Environment Agency forest types nomenclature

Indicators for the assessment and certification of cork oak management sustainability in Italy

Sustainable forest management (SFM) is crucial for forest ecosystem productivity and conservation, especially in systems such as cork oak (Quercus suber L.) threatened by human activities and biotic and abiotic factors. In this study SFM indicators with particular reference to cork oak forests in the region of Sardinia (Italy) are proposed and tested. Sustainable and responsible management options specifically aimed at cork oak forest management and chain of custody certification are also provided. A set of ten indicators was proposed and assessed by an expert panel in cork oak management. Five indicators were also tested against data on structure, origin, health condition and management in 285 forest compartments managed by FoReSTAS (Regional Forest Agency for Land and Environment of Sardinia, Italy), including 361 sampling plots and 5345 trees. In order to investigate the priorities and perceptions of SFM experts and stakeholders, a survey was also carried out by completion of a questionnaire on the technical issues of cork oak woodland management. The survey results highlighted a need to improve environmental and economic performance by means of SFM and certification. The indicators tested in Sardinian cork oak woodlands showed that about 80% of the stands fulfilled management sustainability requirements. The suggested SFM indicators can effectively support proactive management and conservation measures, representing a valuable tool in the current context of growing environmental and socioeconomic awareness

Cork oak management sustainability: indicators for a certification prototype

In this study we tested a set of indicators of sustainable cork oak forest management in Sardinia (Italy). First, we defined a list of specific indicators derived from attributes collected during the conventional management planning process. Secondly, we selected threshold values consulting a panel of experts on cork forest management. Thirdly, we applied the set of proposed indicators and related thresholds to a database of 361 sample plots and 285 forest compartments, representing 2% of the Sardinian cork oak forests, to test its potential suitability

Application of k-nearest neighbor on multispectral images to estimate forest parameters

Natural resources management requires several parameters estimate in order to support the identification of the best alternatives to  forest areas management. In particular, forest ecosystems require a complex and increasing set of descriptive information, where forest inventories put up important information, however not in a continuous spatial way. Lately, several scientific researches have been focusing on establishing methodologies to relate data from field to those obtained from multispectral images. Modeling these relations can extend the estimates of forest inventory data to not sampled areas. This research evaluated performance of non-parametric analysis using the K-Nearest Neighbor (k-NN) on SPOT 5 images. It evaluated the results obtained from the spatialization of some forest attributes in a forest area located at Molise, Italy. Among several methodologies for spatial distance calculations, the use of multiregressive non-parametric distances revealed the best results. Density and number of species on the ground revealed a Pearson correlation coefficient of r = 0.58 as compared to data obtained from multispectral images, lightly lower than the obtained for basal area and volume, which were r = 0.62 and 0.71, respectively.A gestão dos recursos naturais requer a estimativa de uma série de parâmetros para o apoio da identificação de alternativas mais adequadas para a gestão e manejo das áreas florestais. Em particular, os ecossistemas florestais exigem um complexo e crescente conjunto de informações, e os inventários florestais fornecem informações preciosas, entretanto, espacialmente, de forma não contínua. Muitos trabalhos científicos vêm direcionando esforços para o desenvolvimento de metodologias que relacionam os dados da terra com informações de imagens multiespectrais. A modelagem dessas relações pode estender as estimativas dos dados de inventário florestal em áreas não amostradas. Neste trabalho, foi avaliado o desempenho de uma análise não paramétrica, com a utilização do algoritmo K-Nearest Neighbor em imagens SPOT5. Foram avaliados os resultados obtidos na espacialização de atributos florestais em uma área em Molise, na Itália. Entre as diversas metodologias para os cálculos das distâncias espaciais, o uso do método baseado nas distâncias multirregressivas não paramétricas apresentaram os melhores resultados. A densidade e número de espécies levantados em campo apresentaram um coeficiente de correlação de Pearson ρ = 0,58, comparativamente às informações obtidas nas imagens multispectrais, ligeiramente inferior aos obtidos para a área basal e volume, que obtiveram, respectivamente, ρ = 0,62 e 0,71.AbstractApplication of k-nearest neighbor on multispectral images to estimate forest parameters. Natural resources management requires several parameters estimate in order to support the identification of the best alternatives to  forest areas management. In particular, forest ecosystems require a complex and increasing set of descriptive information, where forest inventories put up important information, however not in a continuous spatial way. Lately, several scientific researches have been focusing on establishing methodologies to relate data from field to those obtained from multispectral images. Modeling these relations can extend the estimates of forest inventory data to not sampled areas. This research evaluated performance of non-parametric analysis using the K-Nearest Neighbor (k-NN) on SPOT 5 images. It evaluated the results obtained from the spatialization of some forest attributes in a forest area located at Molise, Italy. Among several methodologies for spatial distance calculations, the use of multiregressive non-parametric distances revealed the best results. Density and number of species on the ground revealed a Pearson correlation coefficient of r = 0.58 as compared to data obtained from multispectral images, lightly lower than the obtained for basal area and volume, which were r = 0.62 and 0.71, respectively.Keywords: Forest inventory; remote sensing; basal area; volume