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Old-growth forests have an important role in maintaining animal and plant diversity, are important carbon (C) reservoirs and are privileged sites to study long-term plant physiological responses, long-term forest dynamics and climate change impact on forest ecosystems. Several studies have highlighted how old-living trees undergo age-related declines with hydraulic limitations and reduction in photosynthesis, though some recent works have suggested that such a decline is not always observed. Our study aims at understanding the role of atmospheric CO2 increase on tree C uptake and stomatal conductance (gs) in old-living trees by analysing the long-term patterns of tree growth and intrinsic water use efficiency (iWUE) in three old-growth forests in the Balkans (Bosnia-Herzegovina and Montenegro), using dendrochronology and isotopic analysis. We hypothesised a long-term increase in iWUE in the studied old-growth forests, mostly related to enhanced photosynthesis rather than reduced stomatal conductance. Tree cores were sampled from dominant silver fir (Abies alba Mill.) trees in each forest. Tree-ring widths were measured and basal area increments (BAI) were assessed for each sampled tree and, from the six longest chronologies, five decades were chosen for cellulose extraction, its isotopic analysis (δ13C, δ18O), iWUE and leaf water 18O evaporative enrichment above the source water (Δ18OL) determination. We observed a continuous and significant increase in iWUE from 1800 to 2010 in the sampled dominant trees at all the three old-growth forests. Our BAI data and our estimates of Δ18OL across the study period support the idea that enhanced photosynthesis rather than reduced stomatal conductance is the major driver of the measured iWUE increase. Thus, our results support some recent findings challenging the hypothesis that iWUE in forests is primarily the result of a CO2-induced reduction in stomatal conductance as well as the so called hydraulic limitation hypothesis. [ABSTRACT FROM AUTHOR]

Forest biomass is a renewable energy source, more climate-friendly than fossil fuels and widely available in Europe. The wood energy chain has been suggested as a means to re-activate forest management and improve the value of forest stands in marginalized rural areas. However, wall-to-wall estimates of forest biomass, needed to design the location and size of power and heat biomass plants in any given territory, are notoriously difficult to obtain. This paper tests an algorithm to predict forest biomass using publicly available Landsat satellite imagery in the Liguria region, northern Italy. We used regional forest inventory data to train and validate an artificial neural network (ANN) classifier that uses remotely-sensed information such as three principal components of Landsat-5 TM spectral bands, the Enhanced Vegetation Index (EVI), and topography, to retrieve aboveground live tree volume. Percent root mean square error was -9% and -23% for conifers and broadleaves respectively in the calibration dataset, and -27% and -24% in the validation dataset. The reconstructed volume map was updated to present day using current volume increment rates reported by the Italian National Forest Inventory. A wall-to-wall map of forest biomass from harvest residues was finally produced based on species-specific wood density, biomass expansion factors, volume logged for timber assortments, forest accessibility, and topography. Predicted aboveground forest volume ranged from 81 to 391 m³ ha-1. In forests available for wood supply (70% of the total), planned volume removals averaged 25.4 m³ ha-1, or 18.7% of the average standing stock across. Biomass available for bioenergy supply was 1.295.921 million Mg dry matter or 8.95 Mg ha-1. This analysis workflow can be replicated in all mountain regions with a predominant broadleaved coppice component. [ABSTRACT FROM AUTHOR]

In a context of progressive expansion of the Italian forest area, we present the results of a national survey exploring public perception of forests across different geographical scales in Italy. Perceptions of forests are assessed in relation to popular beliefs on relevant environmental issues such as countering climate change, protecting biodiversity, and promoting social cohesion and environmental education. Participants (N = 1059) living in five different regions of Northern (Trentino-Alto Adige/Südtirol, Piemonte), Central (Lazio, Molise) and Southern Italy (Puglia), were recruited in the survey and completed a paper-and-pencil questionnaire. Survey questions regarded the estimated percentage of forest cover, the perceived importance of different environmental issues and of different material and non-material forest products, as well as participants' perceptions regarding connectedness to nature. Results revealed a generalized tendency to overestimate the extension of forest surface area in the participants' region, in Italy, and in the European Union. Results also showed high scores for participants' perceived importance of environmental issues, such as climate change and biodiversity protection, and in their belief that forests could play a positive role in addressing these issues and providing important outcomes and benefits for the quality of human life, such as health and well-being or social cohesion. [ABSTRACT FROM AUTHOR]

Human activities have the potential to enhance carbon sequestration by the world's forests and contribute to climate change mitigation. Voluntary carbon trading is currently the only option to pursue and reward carbon sequestration by forestry activities. Carbon credits for enhanced sequestration can be sold to partners wishing to offset their own emissions. Here we illustrate the steps taken to design guidelines for the generation of voluntary carbon credits by improved forest management in Piemonte, Italy. The guidelines have been developed in a joint effort by academia, regional administrations, forest owners and professional consultants. In particular, we show how to compute the baseline and the additionality of credit-generating forest management activities, and how to reconcile the generation of forest carbon credits with law requirements, technical limitations, and the provision of other ecosystem services. To illustrate the profitability of carbon credit generation, we simulated the application of carbon credit guidelines to two forest-rich mountain watersheds in the southern part of the Piemonte region. The two dominating tree species are beech (Fagus sylvatica L.) and chestnut (Castanea sativa Mill.). We computed current forest carbon stock and carbon credits generated in 20 years under business as usual and an alternative biomass retention scenario. The IFM resulted in an avoided harvest of 39,362 m³ for a net total of 64,014 MgCO2e after subtracting harvest emissions, or 38 Mg ha-1 throughout the permanence period of 20 years. These steps can be replicated in other mountain regions where there is interest in promoting this ecosystem service as an alternative or an addition to production-oriented forest management. [ABSTRACT FROM AUTHOR]

Human activities have the potential to enhance carbon sequestration by the world's forests and contribute to climate change mitigation. Voluntary carbon trading is currently the only option to pursue and reward carbon sequestration by forestry activities. Carbon credits for enhanced sequestration can be sold to partners wishing to offset their own emissions. Here we illustrate the steps taken to design guidelines for the generation of voluntary carbon credits by improved forest management in Piemonte, Italy. The guidelines have been developed in a joint effort by academia, regional administrations, forest owners and professional consultants. In particular, we show how to compute the baseline and the additionality of credit-generating forest management activities, and how to reconcile the generation of forest carbon credits with law requirements, technical limitations, and the provision of other ecosystem services. To illustrate the profitability of carbon credit generation, we simulated the application of carbon credit guidelines to two forest-rich mountain watersheds in the southern part of the Piemonte region. The two dominating tree species are beech (Fagus sylvatica L.) and chestnut (Castanea sativa Mill.). We computed current forest carbon stock and carbon credits generated in 20 years under business as usual and an alternative biomass retention scenario. The IFM resulted in an avoided harvest of 39,362 m3 for a net total of 64,014 MgCO2e after subtracting harvest emissions, or 38 Mg ha-1 throughout the permanence period of 20 years. These steps can be replicated in other mountain regions where there is interest in promoting this ecosystem service as an alternative or an addition to production-oriented forest management. [ABSTRACT FROM AUTHOR]

Aerial LiDAR (Light Detection and Ranging) derived data are widely adopted for the study and characterization of forests. In particular, LiDAR derived-CHM (Canopy Height Model) has proved essential in identifying tree height variability and estimating many forest features such as biomass and wood volume. However, CHM quality may be affected by internal limits and anomalies caused by raw data (point cloud) processing (i.e., vertical errors), which are quite often disregarded by users, thus generating potentially erroneous results in their applications. In this work, an auto-consistent procedure for the fast evaluation of CHM accuracy has been developed based on the assessment of internal anomalies affecting CHM data obtained by differencing gridded DSM (Digital Surface Model) and DTM (Digital Terrain Model). To this purpose, a CHM was generated using the gridded DTMs and DSMs provided by the Cartographic Office of the Piemonte Region (north-western Italy). We estimated the local potential CHM error over the whole region, and demonstrated its strictly dependence on the terrain morphometry, particularly slope. The relationship between potential CHM error and slope was modeled separately for mountain, hill and flat terrain contexts, and used to produce a potential error map over the whole region. Our results showed that approximately 20% of the regional territory suffers from CHM uncertainty (in particular high elevation areas, including the treeline), though the majority of regional forest categories was affected by negligible CHM error. The potential consequences of CHM error in forest applications were evaluated, concluding that the tested LiDAR dataset provide a reliable basis for forest applications in most of the regional territory. [ABSTRACT FROM AUTHOR]