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Precision forestry is becoming a key sector for forest planning because it allows complex analyses of forest data to be carried out simply and economically. It contributes to the integration between technicians and operators in the sector by guaranteeing the transparency of the forest management operations (Corona et al., 2017). In the context of the progressive development of technology, we investigated the feasibility of using the hand-held mobile laser scanner (HMLS) system in different types of forest sites and comparison of the characteristics of individual trees (tree height, diameters at breast height) with traditional surveys, applied with the aim to validate the performance of the system for a future alternative methodology for forest planning thanks to the collaboration with the forestry company “Dimensione Ricerca Ecologia Ambiente Italia” (D.R.E.Am. Italia). GEOSLAM ZEB HORIZON ™ laser scanner is a hand-held mobile laser scanner containing SLAM technology that can be solved the problem of no GNSS signal or poor signal under the forest canopy making it more practical for forest investigations (Gollob et al., 2020). 15 forest sample plots are selected to reflect different stand conditions in Mediterranean forests taking into count the development stage and density of the sub-canopy vegetation, as well as the species composition in the forest stands. The aim of this study is to show the possible extrinsic circumstances that make the method fail by varying the ecological status of forest plots.

Inland waters (rivers, lakes and ponds) are important conduits for the emission of terrestrial carbon in Arctic permafrost landscapes. These emissions are driven by turnover of contemporary terrestrial carbon and additional pre-aged (Holocene and late-Pleistocene) carbon released from thawing permafrost soils, but the magnitude of these source contributions to total inland water carbon fluxes remains unknown. Here we present unique simultaneous radiocarbon age measurements of inland water CO2, CH4 and dissolved and particulate organic carbon in northeast Siberia during summer. We show that >80% of total inland water carbon was contemporary in age, but pre-aged carbon contributed >50% at sites strongly affected by permafrost thaw. CO2 and CH4 were younger than dissolved and particulate organic carbon, suggesting emissions were primarily fuelled by contemporary carbon decomposition. Our findings reveal that inland water carbon emissions from permafrost landscapes may be more sensitive to changes in contemporary carbon turnover than the release of pre-aged carbon from thawing permafrost.

Climate change is increasingly favouring the occurrence of extreme weather events, affecting species distribution and tree growth. It has been proposed that mixed forests are more resistant to drought spells and heat waves than corresponding monocultures. We sampled tree cores in nine plots along a latitudinal gradient of the Italian Peninsula (Trentino, Molise and Calabria). The objective of the study was to identify radial growth responses in mixed-species and pure plots of European beech and silver fir to climate dynamics and extreme events. Pointer years, as well as correlation and response functions, were used to analyse the climate–growth relationships in mixed-species and pure plots. Climate–growth relationships showed differences between mixed-species and pure plots only at the regional level. In particular, Trentino differed from Molise and Calabria, when considering maximum temperatures. In Trentino, winter (for silver fir) and summer (for both species) temperatures had a less negative impact on the radial growth of trees, in comparison with Molise and Calabria. Nevertheless, correlations between the radial growth and drought indices, and the principal component analysis, showed that plots were relatively unresponsive to summer drought. These results can be important for the implementation of operational techniques that increase the adaptation of silver fir and European beech to climate change, as well as for assisted migration.

Natural disturbances and management are key drivers for forest carbon balance. We modelled the impact of Vaia storm on forest sink at national scale in Italy. We demonstrate that after Vaia, carbon fluxes among pools and through harvested wood products from salvage logging limit the carbon losses. Our findings can improve the effectiveness of mitigation actions under disturbance scenarios. Climate change increasingly modifies frequency and magnitude of extreme events, such as windstorms, with subsequent strong impacts not only on forest health and stability but also on the forest carbon balance. We aim to assess the combined impact of natural disturbances and forest management on the overall forest carbon accounting, including the mitigation potential from harvested wood products. We modelled the impact of Vaia storm on the evolution of forest carbon balance at national scale until 2030. We considered the effect of Vaia storm in combination with current management practices and salvage logging. Our results suggest that the overall carbon sink decreased only by 4% due to Vaia, because of internal carbon transfers among forest pools (about 3.1 Mt C from living biomass to dead organic matter), and that the potential negative effects of salvage logging, removing about 1.2 Mt C from dead organic matter, can be counterbalanced by long-term carbon accumulation in harvested wood products. Based on our findings, there is an increasing need to robustly consider, through novel approaches (e.g. comprehensive and integrated modelling framework), the effects of natural disturbances in current accounting frameworks, with the final purpose to improve the effectiveness of mitigation strategies in the forestry sector.

Forest aboveground biomass (AGB) is a prime forest parameter that requires global level estimates to study the global carbon cycle. Light detection and ranging (LiDAR) is the state-of-the-art technology for AGB prediction but it is expensive, and its coverage is restricted to small areas. On the contrary, spaceborne Earth observation data are effective and economical information sources to estimate and monitor AGB at a large scale. In this paper, we present a study on the use of different spaceborne multispectral remote sensing data for the prediction of forest AGB. The objective is to evaluate the effects of temporal, spectral, and spatial capacities of multispectral satellite data for AGB prediction. The study was performed on multispectral data acquired by Sentinel-2, RapidEye, and Dove satellites which are characterized by different spatial resolutions, temporal availability, and number of spectral bands. A systematic process of least absolute shrinkage and selection operator (lasso) variable selection generalized linear modeling, leave-one-out cross-validation, and analysis was accomplished on each satellite dataset for AGB prediction. Results point out that the multitemporal data based AGB models were more effective in prediction than the single-time models. In addition, red-edge and short wave infrared (SWIR) channel dependent variables showed significant improvement in the modeling results and contributed to more than 50% of the selected variables. Results also suggest that high spatial resolution plays a smaller role than spectral and temporal information in the prediction of AGB. The overall analysis emphasizes a good potential of spaceborne multispectral data for developing sophisticated methods for AGB prediction especially with specific spectral channels and temporal information.

Soil quality is fundamental for ecosystem long term functionality, productivity and resilience to current climatic changes. Despite its importance, soil is lost and degraded at dramatic rates worldwide. In Europe, the Mediterranean areas are a hotspot for soil erosion and land degradation due to a combination of climatic conditions, soils, geomorphology and anthropic pressure. Soil organic carbon (SOC) is considered a key indicator of soil quality as it relates to other fundamental soil functions supporting crucial ecosystem services. In the present study, the functional relationships among SOC and other important soil properties were investigated in the topsoil of 38 sites under different land cover and management, distributed over three Mediterranean regions under strong desertification risk, with the final aim to define critical SOC ranges for fast loss of important soil functionalities. The study sites belonged to private and public landowners seeking to adopt sustainable land management practices to support ecosystem sustainability and productivity of their land. Data showed a very clear relationship between SOC concentrations and the other analyzed soil properties: total nitrogen, bulk density, cation exchange capacity, available water capacity, microbial biomass, C fractions associated to particulate organic matter and to the mineral soil component and indirectly with net N mineralization. Below 20 g SOC kg−1, additional changes of SOC concentrations resulted in a steep variation of all the analyzed soil indicators, an order of magnitude higher than the changes occurring between 50 and 100 g SOC kg−1 and 3–4 times the changes observed at 20–50 g SOC kg−1. About half of the study sites showed average SOC concentration of the topsoil centimetres

Inland waters (rivers, lakes and ponds) are important conduits for the emission of terrestrial carbon in Arctic permafrost landscapes. These emissions are driven by turnover of contemporary terrestrial carbon and additional “pre-aged” (Holocene and late-Pleistocene) carbon released from thawing permafrost soils, but the magnitude of these source contributions to total inland water carbon fluxes remains unknown. Here we present unique simultaneous radiocarbon age measurements of inland water CO2, CH4 and dissolved and particulate organic carbon in northeast Siberia during summer. We show that >80% of total inland water carbon emissions were contemporary in age, but that pre-aged carbon contributed >50% at sites strongly affected by permafrost thaw. CO2 and CH4 were younger than dissolved and particulate organic carbon, suggesting emissions were primarily fuelled by contemporary carbon decomposition. The study region was a net carbon sink (-876.9 ± 136.4 Mg C for 25 July to 17 August), but inland waters were a source of contemporary (16.8 Mg C) and pre-aged (3.7 Mg C) emissions that respectively offset 1.9 ± 1.2% and 0.4 ± 0.3% of CO2 uptake by tundra (‑897 ± 115 Mg C). Our findings reveal that inland water carbon emissions from permafrost landscapes may be more sensitive to changes in contemporary carbon turnover than the release of pre-aged carbon from thawing permafrost.

Rising atmospheric CO2 concentration ([CO2]) enhances photosynthesis and reduces transpiration at the leaf, ecosystem, and global scale via the CO2 fertilization effect. The CO2 fertilization effect is among the most important processes for predicting the terrestrial carbon budget and future climate, yet it has been elusive to quantify. For evaluating the CO2 fertilization effect on land photosynthesis and transpiration, we developed a technique that isolated this effect from other confounding effects, such as changes in climate, using a noisy time series of observed land-atmosphere CO2 and water vapor exchange. Here, we evaluate the magnitude of this effect from 2000 to 2014 globally based on constraint optimization of gross primary productivity (GPP) and evapotranspiration in a canopy photosynthesis model over 104 global eddy-covariance stations. We found a consistent increase of GPP (0.138 ± 0.007% ppm−1; percentile per rising ppm of [CO2]) and a concomitant decrease in transpiration (−0.073% ± 0.006% ppm−1) due to rising [CO2]. Enhanced GPP from CO2 fertilization after the baseline year 2000 is, on average, 1.2% of global GPP, 12.4 g C m−2 yr−1 or 1.8 Pg C yr−1 at the years from 2001 to 2014. Our result demonstrates that the current increase in [CO2] could potentially explain the recent land CO2 sink at the global scale.

Made available in DSpace on 2020-12-12T02:34:44Z (GMT). No. of bitstreams: 0 Previous issue date: 2020-03-01 Università degli Studi di Palermo Ministero dell’Istruzione, dell’Università e della Ricerca Vegetation natural regeneration after agricultural abandonment is changing the landscape patterns in many areas worldwide. However, the expansion rate, spatio-temporal dynamics, and the role of past vegetation cover in shaping such patterns are still barely quantified in fine and meso scales. Here, we aim to quantify the expansion rate and assess the spatio-temporal patterns and the effects of past cover on natural woody vegetation cover increase. We sampled woodland and shrubland cover from 1992 to 2016 in 30 ha in a formerly managed pastureland in Sicily, Italy. We combined field sampling, GIS tools, and spatial analysis to assess the spatial structure dynamics and test the effects of past cover amount and type and distance from forest or nearest woody patch on the proportional expansion of natural regeneration. After 24 years, woody cover increased 68%, despite the aggregated spatial structure in 1992 remaining almost unchanged in 2016. The past vegetation cover was the best predictor of woody vegetation expansion in two out of three plots. Distance to continuous forest and to the nearest woody patch, as well as cover type, was not relevant. Our study highlights the importance of fine- and meso-scale studies to reveal both the deterministic and stochastic facet of woody vegetation dynamics. Natural regeneration may strongly change landscape patterns even under constant herbivory pressure and long-term deforestation. The detection of cold and hotspots of regeneration provide an important prompt for the design of restoration programs and landscape management. Dipartimento di Scienze Agrarie Alimentari e Forestali Università degli Studi di Palermo (UNIPA) Departamento de Ecologia Universidade Estadual Paulista (UNESP) Departamento de Biología de Organismos y Sistemas – UMIB University of Oviedo Departamento de Ecologia Universidade Estadual Paulista (UNESP) Ministero dell’Istruzione, dell’Università e della Ricerca: 201049EXTW

Large quantities of carbon are stored in the terrestrial permafrost of the Arctic region where the rate of climate warming is two to three times more than the global mean and the largest temperature anomalies observed in autumn and winter. The quantification of the impact of climate warming on the degradation of permafrost and the associated potential release to the atmosphere of carbon stocked in the soil in the form of greenhouse gases, thus further increasing the radiative forcing of the atmosphere, is a research priority in the field of biogeosciences. Land-atmosphere turbulent fluxes of CO2 and CH4 have been monitored at the tundra site of Kytalyk in north-eastern Siberia (70,82 N; 147.48 E) by means of eddy covariance since 2003 and 2008, respectively; regular measurement campaigns have been carried out since then. Here we present results of the seasonal CO2 budget of the tundra ecosystem for the 2003-2016 period based on observations encompassing the permafrost thawing season and analyze the inter-annual differences in the seasonal patterns of CO2 fluxes considering the separate the contribution of climatic drivers and ecosystem functional parameters relative to the processes of respiration and photosynthesis. The variability of the CO2 budget is also discussed in view of the impact of the timing and length of the snow free period.The Kytalyk tundra acted as an atmospheric carbon dioxide sink with relatively small inter-annual variability (-96.1±11.9 gC m-2) during the snow free season and the seasonal CO2 budget did not show any trend over time. The pronounced meteorological variability characterizing Arctic summers was a key factor in shaping the length of the carbon uptake period, which did not progressively increased despite its tendency to start earlier, and in determining the magnitude of CO2 fluxes. No clear evidence of inter-annual changes in the eco-physiological response parameters of CO2 fluxes to climatic drivers (global radiation and air temperature) was found along the course of the analysed period. Methane fluxes had a minor contribution to the carbon budget of the snow-free season representing on average an emission of 3.2 gC m-2 (2008-2016) with apparently small inter-annual variability. Similarly, the size of the carbon exported laterally from the ecosystem in the form of dissolved organic carbon flux amounted to 3.1 gC m-2 as determined experimentally. After including these last terms in the budget, the magnitude of the carbon sink associated with the net ecosystem productivity is reduced by 6%, while the GHG budget still denotes a sink of -60.4 ± 11.9 gC-CO2eq (methane GWP over 100-year time horizon).The monitored tundra was to date exerting a steady climate warming mitigation effect as far as the snow free season is concerned, however the figure of its carbon sink could be potentially sensibly lower due to overlooked emissions in the autumn freeze-up and early winter periods. Also, nonlinear accelerations in the permafrost degradation could happen once tipping points in the Arctic climate are exceeded. Both aspects underline the relevance of long term and continuous biogeochemical monitoring in permafrost tundra environments.

Urban green infrastructure plays an increasingly significant role in sustainable urban development planning as it provides important regulating and cultural ecosystem services. Monitoring of such dynamic and complex systems requires technological solutions which provide easy data collection, processing, and utilization at affordable costs. To meet these challenges a pilot study was conducted using a network of wireless, low cost, and multiparameter monitoring devices, which operate using Internet of Things (IoT) technology, to provide real-time monitoring of regulatory ecosystem services in the form of meaningful indicators for both human health and environmental policies. The pilot study was set in a green area situated in the center of Moscow, which is exposed to the heat island effect as well as high levels of anthropogenic pressure. Sixteen IoT devices were installed on individual trees to monitor their ecophysiological parameters from 1 July to 31 November 2019 with a time resolution of 1.5 h. These parameters were used as input variables to quantify indicators of ecosystem services related to climate, air quality, and water regulation. Our results showed that the average tree in the study area during the investigated period reduced extreme heat by 2 &deg, C via shading, cooled the surrounding area by transferring 2167 &plusmn, 181 KWh of incoming solar energy into latent heat, transpired 137 &plusmn, 49 mm of water, sequestered 8.61 &plusmn, 1.25 kg of atmospheric carbon, and removed 5.3 &plusmn, 0.8 kg of particulate matter (PM10). The values of the monitored processes varied spatially and temporally when considering different tree species (up to five to ten times), local environmental conditions, and seasonal weather. Thus, it is important to use real-time monitoring data to deepen understandings of the processes of urban forests. There is a new opportunity of applying IoT technology not only to measure trees functionality through fluxes of water and carbon, but also to establish a smart urban green infrastructure operational system for management.

The Italian TREETALKER NETWORK (ITT-Net) aims to respond to one of the grand societal challenges: the impact of climate changes on forests ecosystem services and forest dieback. The comprehension of the link between these phenomena requires to complement the most classical approaches with a new monitoring paradigm based on large scale, single tree, high frequency and long-term monitoring tree physiology, which, at present, is limited by the still elevated costs of multi-sensor devices, their energy demand and maintenance not always suitable for monitoring in remote areas. The ITT-Net network will be a unique and unprecedented worldwide example of real time, large scale, high frequency and long-term monitoring of tree physiological parameters. By spring 2020, as part of a national funded project (PRIN) the network will have set 37 sites from the north-east Alps to Sicily where a new low cost, multisensor technology “the TreeTalker®” equipped to measure tree radial growth, sap flow, transmitted light spectral components related to foliage dieback and physiology and plant stability (developed by Nature 4.0), will monitor over 600 individual trees. A radio LoRa protocol for data transmission and access to cloud services will allow to transmit in real time high frequency data on the WEB cloud with a unique IoT identifier to a common database where big data analysis will be performed to explore the causal dependency of climate events and environmental disturbances with tree functionality and resilience.With this new network, we aim to create a new knowledge, introducing a massive data observation and analysis, about the frequency, intensity and dynamical patterns of climate anomalies perturbation on plant physiological response dynamics in order to: 1) characterize the space of “normal or safe tree operation mode” during average climatic conditions; 2) identify the non-linear tree responses beyond the safe operation mode, induced by extreme events, and the tipping points; 3) test the possibility to use a high frequency continuous monitoring system to identify early warning signals of tree stress which might allow to follow tree dynamics under climate change in real time at a resolution and accuracy that cannot always be provided through forest inventories or remote sensing technologies.To have an overview of the ITT Network you can visit www.globaltreetalker.org

Change detection from multi-temporal remote sensing images is an effective way to identify the burned areas after forest fires. However, the complex image scenario and the similar spectral signatures in multispectral bands may lead to many false positive errors, which make it difficult to exact the burned areas accurately. In this paper, a novel-burned area change detection approach is proposed. It is designed based on a new Normalized Burn Ratio-SWIR (NBRSWIR) index and an automatic thresholding algorithm. The effectiveness of the proposed approach is validated on three Landsat-8 data sets presenting various fire disaster events worldwide. Compared to eight index-based detection methods that developed in the literature, the proposed approach has the best performance in terms of class separability (2.49, 1.74 and 2.06) and accuracy (98.93%, 98.57% and 99.51%) in detecting the burned areas. Simultaneously, it can also better suppress the complex irrelevant changes in the background.

Growing demand for wood products, combined with efforts to conserve natural forests, have supported a steady increase in the global extent of planted forests. Here, a two-phase sampling strategy for large-scale assessment of the total area and the total wood volume of fast-growing forest tree crops within agricultural land is presented. The first phase is performed using tessellation stratified sampling on high-resolution remotely sensed imagery and is sufficient for estimating the total area of plantations by means of a Monte Carlo integration estimator. The second phase is performed using stratified sampling of the plantations selected in the first phase and is aimed at estimating total wood volume by means of an approximation of the first-phase Horvitz-Thompson estimator. Vegetation indices from Sentinel-2 are exploited as freely available auxiliary information in a linear regression estimator to improve the design-based precision of the estimator based on the sole sample data. Estimators of the totals and of the design-based variances of total estimators are presented. A simulation study is developed in order to check the design-based performance of the two alternative estimators under several artificial distributions supposed for poplar plantations (random, clustered, spatially trended). An application in Northern Italy is also reported. The regression estimator turns out to be invariably better than that based on the sole sample information. Possible integrations of the proposed sampling scheme with conventional national forest inventories adopting tessellation stratified sampling in the first phase are discussed.

The FLUXNET2015 dataset provides ecosystem-scale data on CO2, water, and energy exchange between the biosphere and the atmosphere, and other meteorological and biological measurements, from 212 sites around the globe (over 1500 site-years, up to and including year 2014). These sites, independently managed and operated, voluntarily contributed their data to create global datasets. Data were quality controlled and processed using uniform methods, to improve consistency and intercomparability across sites. The dataset is already being used in a number of applications, including ecophysiology studies, remote sensing studies, and development of ecosystem and Earth system models. FLUXNET2015 includes derived-data products, such as gap-flled time series, ecosystem respiration and photosynthetic uptake estimates, estimation of uncertainties, and metadata about the measurements, presented for the frst time in this paper. In addition, 206 of these sites are for the frst time distributed under a Creative Commons (CC-BY 4.0) license. This paper details this enhanced dataset and the processing methods, now made available as open-source codes, making the dataset more accessible, transparent, and reproducible., European Union (EU), United States Department of Energy (DOE)

The estimate and parameterization of mass and energy fluxes exchanged in the atmospheric surface-layer, between the biosphere and the atmosphere, plays a key role in many disciplines, e.g. meteorology and atmospheric sciences, ecology and precision agriculture.In mountain environments, crests lines tend to decouple the atmospheric processes close to the ground from those in the upper layers and deeply affect the penetration of solar radiation on the floors and the sidewalls of valleys. The consequent differential heating of the surface allows the onset of many local phenomena, such as thermally-driven flows and temperature inversions, with impacts on the regime of the exchanges. Indeed, the low-wind conditions, the wind interaction with landforms and the atmospheric stability control the turbulence and the development of sub-meso motions, i.e. those phenomena responsible for the diffusion and transport of substances, respectively.The Wheat Project is a 2-year-long project, started on November 2018 and funded by the CARITRO Foundation (“Cassa di Risparmio di Trento e Rovereto”, Italy), which aims at investigating the basic mechanisms responsible for biosphere-atmosphere exchanges in mountain areas, in order to improve their estimate and scaling.Three datasets collected by long-term research infrastructures and composed of both biochemical and atmospheric quantities measured over different ecosystems were selected in the Trentino Alto Adige/South Tirol region (Italy). Data were measured at the research facility managed by the Free University of Bolzano/Bozen at Caldaro, over an apple orchard (220 m ASL, available period 2010-2018), and at the research facilities managed by the Fondazione Edmund Mach at Monte Lavarone, over a forest (1349 m ASL, available period 2000-2018) and at Viote del Monte Bondone, over an Alpine grassland (1553 m ASL, available period 2002-2018).This contribution focuses on the pre-processing procedure adopted to identify representative periods for the analyses and on the methods implemented to retrieve turbulence parameters. In particular, the identification of the characteristic time-scales of small-scale turbulence is carried out through an application of the anisotropic analysis of turbulence, whereas the separation of the turbulence signal from low-frequency fluctuations is performed by implementing a recursive digital filter. Finally, some preliminary results regarding the estimate and the scaling of the turbulent fluxes of momentum, sensible heat, moisture and carbon dioxide are presented.

In the last decade, there has been increased interest in measuring and modeling storage in the five forest carbon pools: the aboveground and belowground biomass (living biomass), the deadwood and litter (dead biomass), and the soil (soil organic matter). In this paper, we examined carbon storage in a holm oak coppice stand in the Madonie Mountains in Sicily (Italy), which is a typical case of managed coppice stands. Today, traditional coppice practices are only applied to a small number of forested areas in Sicily, such as the selected site, because of the decline in demand for wood and charcoal. The dendrometric parameters of the stands were recorded, and silvicultural indices were calculated immediately after cutting as well as during and at the end of the rotation period; they showed the trends typical of coppices. The carbon stocks in the five carbon pools were quantified to investigate the effects of coppicing on carbon storage in this Mediterranean area. Results showed that the lowest living biomass values were observed in the first years following coppicing, except for litter carbon. Belowground biomass and the soil carbon stock did not vary significantly with coppicing. During the rotation period, the aboveground biomass was completely restored, and the balance of the carbon stocks indicates that coppicing is a sustainable forest management choice from the point of view of the carbon balance, given that the logged trees are generally used for bioenergy production.

In forest management, site index information is essential for planning silvicultural operations and forecasting forest development. Site index is most commonly expressed as the average height of the dominant trees at a certain index age, and can be determined either by photo interpretation, field measurements, or projection of age combined with height estimates from remote sensing. However, recently it has been shown that site index can be accurately predicted from bi-temporal airborne laser scanner (ALS) data. Furthermore, single-time hyperspectral data have also been shown to be correlated to site index. The aim of the current study was to compare the accuracy of modelling site index using (1) data from bi-temporal ALS; (2) single-time hyperspectral data with different types of preprocessing; and (3) combined bi-temporal ALS and single-time hyperspectral data. The period between the ALS acquisitions was 11 years. The preprocessing of the hyperspectral data included an atmospheric correction and/or a normalization of the reflectance. Furthermore, a selection of pixels was carried out based on NDVI and compared to using all pixels. The results showed that bi-temporal ALS data explained about 70% (R2) of the variation in the site index, and the RMSE values from a cross-validation were 3.0 m and 2.2 m for spruce- and pine-dominated plots, respectively. Corresponding values for the different single-time hyperspectral datasets were 54%, 3.9 m, and 2.5 m. With bi-temporal ALS data and hyperspectral data used in combination, the results indicated that the contribution from the hyperspectral data was marginal compared to just using bi-temporal ALS. We also found that models constructed with normalized hyperspectral data produced lower RMSE values compared to those constructed with atmospherically corrected data, and that a selection of pixels based on NDVI did not improve the results compared to using all pixels.

The occurrence of old-growth forests is quite limited in Mediterranean islands, which have been subject to particularly pronounced human impacts. Little is known about the carbon stocks of such peculiar ecosystems compared with different stages of secondary succession. We investigated the carbon variation in aboveground woody biomass, in litter and soil, and the nitrogen variation in litter and soil, in a 100 years long secondary succession in Mediterranean ecosystems. A vineyard, three stages of plant succession (high maquis, maquis-forest, and forest-maquis), and an old growth forest were compared. Soil samples at two soil depths (0-15 and 15-30 cm), and two litter types, relatively undecomposed and partly decomposed, were collected. Carbon stock in aboveground woody biomass increased from 6 Mg ha-1 in the vineyard to 105 Mg ha-1 in old growth forest. Along the secondary succession, soil carbon considerably increased from about 33 Mg ha-1 in the vineyard to about 69 Mg ha-1 in old growth forest. Soil nitrogen has more than doubled, ranging from 4.1 Mg ha-1 in the vineyard to 8.8 Mg ha-1 in old growth forest. Both soil parameters were found to be affected by successional stage and soil depth but not by their interaction. While the C/N ratio in the soil remained relatively constant during the succession, the C/N ratio of the litter strongly decreased, probably following the progressive increase in the holm oak contribution. While carbon content in litter decreased along the succession, nitrogen content slightly increased. Overall, carbon stock in aboveground woody biomass, litter and soil increased from about 48 Mg ha-1 in the vineyard to about 198 Mg ha-1 in old growth forest. The results of this study indicate that, even in Mediterranean environments, considerable amounts of carbon may be stored through secondary succession processes up to old growth forest. The occurrence of old-growth forests is quite limited in Mediterranean islands, which have been subject to particularly pronounced human impacts. Little is known about the carbon stocks of such peculiar ecosystems compared with different stages of secondary succession. We investigated the carbon variation in aboveground woody biomass, in litter and soil, and the nitrogen variation in litter and soil, in a 100 years long secondary succession in Mediterranean ecosystems. A vineyard, three stages of plant succession (high maquis, maquis-forest, and forest-maquis), and an old growth forest were compared. Soil samples at two soil depths (0-15 and 15-30 cm), and two litter types, relatively undecomposed and partly decomposed, were collected. Carbon stock in aboveground woody biomass increased from 6 Mg ha(-1) in the vineyard to 105 Mg ha(-1) in old growth forest. Along the secondary succession, soil carbon considerably increased from about 33 Mg ha(-1) in the vineyard to about 69 Mg ha(-1) in old growth forest. Soil nitrogen has more than doubled, ranging from 4.1 Mg ha(-1) in the vineyard to 8.8 Mg ha(-1) in old growth forest. Both soil parameters were found to be affected by successional stage and soil depth but not by their interaction. While the C/N ratio in the soil remained relatively constant during the succession, the C/N ratio of the litter strongly decreased, probably following the progressive increase in the holm oak contribution. While carbon content in litter decreased along the succession, nitrogen content slightly increased. Overall, carbon stock in aboveground woody biomass, litter and soil increased from about 48 Mg ha(-1) in the vineyard to about 198 Mg ha(-1) in old growth forest. The results of this study indicate that, even in Mediterranean environments, considerable amounts of carbon may be stored through secondary succession processes up to old growth forest.

Forest ecosystems are fundamental for the terrestrial biosphere as they deliver multiple essential ecosystem services (ES). In environmental management, understanding ES distribution and interactions and assessing the economic value of forest ES represent future challenges. In this study, we developed a spatially explicit method based on a multi-scale approach (MiMoSe-Multiscale Mapping of ecosystem services) to assess the current and future potential of a given forest area to provide ES. To do this we modified and improved the InVEST model in order to adapt input data and simulations to the context of Mediterranean forest ecosystems. Specifically, we integrated a GIS-based model, scenario model, and economic valuation to investigate two ES (wood production and carbon sequestration) and their trade-offs in a test area located in Molise region (Central Italy). Spatial information and trade-off analyses were used to assess the influence of alternative forest management scenarios on investigated services. Scenario A was designed to describe the current Business as Usual approach. Two alternative scenarios were designed to describe management approaches oriented towards nature protection (scenario B) or wood production (scenario C) and compared to scenario A. Management scenarios were simulated at the scale of forest management units over a 20-year time period. Our results show that forest management influenced ES provision and associated benefits at the regional scale. In the test area, the Total Ecosystem Services Value of the investigated ES increases 85% in scenario B and decreases 82% in scenario C, when compared to scenario A. Our study contributes to the ongoing debate about trade-offs and synergies between carbon sequestration and wood production benefits associated with socio-ecological systems. The MiMoSe approach can be replicated in other contexts with similar characteristics, thus providing a useful basis for the projection of benefits from forest ecosystems over the future L'articolo è disponibile sul sito dell'editore www.elsevier.com/locate/envres

Competitive interactions are important predictors of tree growth. Spatial and temporal changes in resource availability, and variation in species and spatial patterning of trees alter competitive interactions, thus affecting tree growth and, hence, biomass. Competition indices are used to quantify the level of competition among trees. As these indices are normally computed only over small areas, where field measurements are done, it would be useful to have a tool to predict them over large areas. On this regard, remote sensing, and in particular light detection and ranging (lidar) data, could be the perfect tool. The objective of this study was to use lidar metrics to predict competition (on the basis of distance-dependent competition indices) of individual trees and to relate them with tree aboveground biomass (AGB). The selected study area was a mountain forest area located in the Italian Alps. The analyses focused on the two dominant species of the area: Silver fir (Abies alba Mill.) and Norway spruce (Picea abies (L.) H. Karst). The results showed that lidar metrics could be used to predict competition indices of individual trees (R2 above 0.66). Moreover, AGB decreased as competition increased, suggesting that variations in the availability of resources in the soil, and the ability of plants to withstand competition for light may influence the partitioning of biomass.

Extreme climatic events, such as droughts and heat stress, influence terrestrial ecosystem physiology and phenology. These impacts induce anomalies in ecosystem-atmosphere CO2 fluxes, such as gross primary production (GPP) and ecosystem respiration (Reco), and can change the net ecosystem carbon balance. However, despite our increasing understanding of the underlying mechanisms, the magnitudes of the impacts of different types of extremes on GPP and Reco within and between ecosystems remain poorly predicted. Stand structure, species composition, ecosystem history, and the timing and duration of the extremes may influence the ecosystem's response in different ways. Here we aim to identify the major factors controlling the amplitude of extreme event impacts on GPP, Reco, and the resulting net ecosystem production (NEP) from observational data. We focus on the impacts of heat and drought and their combination. Wealso investigate the effects of event duration and how impacts differ between ecosystem types.We identified hydrometeorological extreme events in consistently downscaled water availability and temperature measurements over a 30 year time period. We then used FLUXNET eddy-covariance CO2 flux measurements to estimate the C flux anomalies during these extreme events across dominant vegetation types and climate zones. Overall, our results indicate that short-term heat extremes increased respiration more strongly than they down-regulated GPP, resulting in a moderate reduction of the ecosystem's carbon sink potential. In the absence of heat stress, droughts tended to have smaller and similarly dampening effects on GPP and Reco, which often resulted in neutral NEP responses. The combination of drought and high temperatures typically led to a strong decrease in GPP, whereas heat and drought impacts on respiration partially offset each other. Taken together, compound heat and drought events led to the strongest C sink reduction compared to any single-factor extreme. A key insight of this paper, however, is that duration matters most: for heat stress during droughts, the magnitude of impacts systematically increased with duration, whereas under heat stress without drought, the response of Reco over time was qualitatively contrasting: an initial increase for about two to three weeks was followed by a down-regulation of Reco for long-term heat events. This confirms earlier theories that not only the magnitude but also the duration of an extreme event determines its impact. Our study corroborates the results of several local site-level case studies on the different responses of primary production and respiration, but as a novelty generalizes these findings at the global scale. Specifically, we find that the different response functions of the two antipodal land-atmosphere fluxes GPP and Reco can also result in increasing NEP during certain extreme conditions. Apparently counterintuitive findings of this kind bear great potential for scrutinizing the mechanisms implemented in state-of-the-art terrestrial biosphere models and provide a benchmark for future model development and testing.

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.

Eucalyptus stands in semi-arid areas may contribute to enhance carbon (C) stocks in both biomass and soil. However, the limited information available is mainly focused on short-rotation plantations. In this study, the above- and below-ground C pools in five 50-year-old Eucalyptus camaldulensis Dehnh. stands planted on Miocenic evaporitic deposits in Sicily, Italy, with a xeric and thermic pedoclimate, were measured. Above-ground biomass was determined by partitioning and weighing branches, stem and leaves. Below-ground C pools included the determination of litter, root biomass, and soil organic and inorganic C. In terms of the above-ground biomass, the E. camaldulensis stand accumulated on average 116 Mg ha-1 corresponding to 55 Mg C ha-1. Below-ground biomass consisted mainly of larger roots, followed by fine and medium roots (33 Mg ha-1 corresponding to 14 Mg C ha-1). Litter accumulation on the soil surface accounted for 13 Mg ha-1 corresponding to 5 Mg C ha-1. The amount of C stored in soil was 554 Mg C ha-1, of which 75% was in organic form. Although E. camaldulensis is planted extensively throughout the Southern Hemisphere and tropics where it is managed over short rotations (c. 2–4 years), the results obtained from this study make this species important in terms of future afforestation planning for longer rotations due to its potential to sequester C, particularly in the below-ground components.

Abandonment of agricultural land leads to several consequences for ecosystem functions. Agricultural abandonment may be a significant and low cost strategy for carbon sequestration and mitigation of anthropogenic CO2 emissions due to the vegetation recovery and increase in soil organic matter. The aim of this study was to: (i) estimate the influence of different Soil Regions (areas characterized by a typical climate and parent material association) and Bioclimates (zones with homogeneous climatic regions and thermotype indices) on soil organic carbon (SOC) dynamics after agricultural land abandonment; and (ii) to analyse the efficiency of the agri-environment policy (agri-environment measures) suggested by the European Commission in relation to potential SOC stock ability in the Sicilian Region (Italy). In order to quantify the effects of agricultural abandonment on SOC, a dataset with original data that was sampled in Sicily and existing data from the literature were analysed according to the IPCC (Intergovernmental Panel on Climate Change) methodology. Results showed that abandonment of cropland soils increased SOC stock by 9.03MgCha−1 on average, ranging from 5.4MgCha−1 to 26.7MgCha−1 in relation to the Soil Region and Bioclimate. The estimation of SOC change after agricultural use permitted calculation of the payments for ecosystem service (PES) of C sequestration after agricultural land abandonment in relation to environmental benefits, increasing in this way the efficiency of PES. Considering the 14,337ha of abandoned lands in Sicily, the CO2 emission as a whole was reduced by 887,745Mg CO2. Therefore, it could be concluded that abandoned agricultural fields represents a valid opportunity to mitigate agriculture sector emissions in Sicily.

Aim: We provide the first European-scale geospatial training set relating the charcoal signal in surface lake sediments to fire parameters (number, intensity and area) recorded by satellite moderate resolution imaging spectroradiometer (MODIS) sensors. Our calibration is intended for quantitative reconstructions of key fire-regime parameters by using sediment sequences of microscopic (MIC from pollen slides, particles 10-500 µm) and macroscopic charcoal (MAC from sieves, particles >100 µm). Location: North-south and east-west transects across Europe, covering the mediterranean, temperate, alpine, boreal and steppe biomes. Time period: Lake sediments and MODIS active fire and burned area products were collected for the years 2012-2015. Methods: Cylinder sediment traps were installed in lakes to annually collect charcoal particles in sediments. We quantitatively assessed the relationships between MIC and MAC influx (particles/cm2/year) and the MODIS-derived products to identify source areas of charcoal and the extent to which lake-sediment charcoal is linked to fire parameters across the continent. Results: Source area of sedimentary charcoal was estimated to a 40-km radius around sites for both MIC and MAC particles. Fires occurred in grasslands and in forests, with grass morphotypes of MAC accurately reflecting the burned fuel-type. Despite the lack of local fires around the sites, MAC influx levels reached those reported for local fires. Both MIC and MAC showed strong and highly significant relationships with the MODIS-derived fire parameters, as well as with climatic variation along a latitudinal temperature gradient. Main conclusions: MIC and MAC are suited to quantitatively reconstructing fire number and fire intensity on a regional scale. However, burned area may only be estimated using MAC. Local fires may be identified by using several lines of evidence, e.g. analysis of large particles (>Â600 µm), magnetic susceptibility and sedimentological data. Our results offer new insights and applications to quantitatively reconstruct fires and to interpret available sedimentary charcoal records.

Mediterranean ecosystems are characterized by nearly complete replacement of natural vegetation by intensive croplands and orchards leading to strong soil degradation. Organic carbon is usually accumulated in soils under maquis leading to partial regeneration of fertility for future agricultural use. The aim of this work was to investigate the effect of land use change from maquis to agriculture on soil organic carbon (SOC) stock and its spatial distribution in a Mediterranean system. Three Mediterranean land use systems (seminatural vegetation, cactus pear crop and olive grove) were selected in Sicily and analysed for soil C stocks and their δ13C. Total SOC and δ13C were measured up to 75 cm soil depth within and between the rows of cactus pear and olive grove and along a similar transect in maquis, in order to evaluate the distribution of new and old C derived from roots. The land use change from Mediterranean maquis (C3 plant) to cactus pear (CAM plant) lead to a SOC decrease of 65% after 28 years of cultivation, and a further decrease for 14% after 7 years after the change from cactus pear to olive grove (C3 plant). Considering these SOC losses as well as the periods after the land use changes we calculated the mean residence time (MRT) of soil organic matter. The MRT of C under Mediterranean maquis was about 142 years, but was just 10 years under cactus pear. Root biomass of cactus pear was used for a new approach to estimate root turnover. The root turnover rate of cactus decreased along the soil profile from 7.1% per year in 0–15 cm to 3.7% in 60–75 cm soil depth. Along the transect, the average of root turnover values was highest in the middle of the intra-row. Root turnover and C input were correlated with SOC stocks to evaluate C sequestration potential of soils depending on land use and managements. We conclude that the SOC under maquis is higher and has longer residence time compared to permanent agricultural crops like cactus pear and olives.

The aim of this work was to investigate the effect of an experimental fire used for grassland management on soil organic carbon (SOC) stocks. The study was carried out on Hyparrhenia hirta (L.) Stapf (Hh) grassland and Ampelodesmos mauritanicus (Desf.) T. Durand & Schinz (Am) grasslands located in the north of Sicily. Soil samples were collected at 0–5 cm before and after the experimental fire, and SOC was measured. During the grassland fire, soil surface temperature was monitored. Biomass of both grasses was analysed in order to determine dry weight and its chemical composition. The results showed that SOC varied significantly with vegetation type, while it is not affected in the short term by grassland fire. Am grassland stored more SOC compared with Hh grassland thanks to lower content in the biomass of the labile carbon pool. No significant difference was observed in SOC before and after fire, which could be caused by several factors: first, in both grassland types the measured soil temperature during fire was low due to thin litter layers; second, in a semiarid environment, a higher mineralization rate results in a lower soil carbon labile pool; and third, the SOC stored in the finest soil fractions, physically protected, is not affected by fire.

Soil physical quality (SPQ) can be assessed by different experimental methodologies and criteria and the optimal/critical values or ranges for SPQ indicators are still approximate. Sampling soils with minimal anthropic pressures should allow improvements in SPQ assessment. Different experimental methodologies and criteria were applied to sample a Mediterranean oak forest (Quercus ilex L.) and pasture land, in Sicily, with a varying degree of anthropic disturbance. Soil water retention was determined in the laboratory and the field, using the BEST (Beerkan Estimation of Soil Transfer parameters) procedure of soil hydraulic characterization. Capacity-based indicators, the S index, and location and shape parameters of the pore volume distribution function were calculated for assessing SPQ. With the laboratory data, only the criterion using the capacity-based indicators suggested that SPQ increased as external pressures decreased. Therefore, this criterion appeared to be more reliable than the other tested criteria in the sampled environment. The field method was more prone to suggest good conditions and less able to signal differences between plots as compared with the laboratory method. A forest soil with a good SPQ has an ability to store and provide water to plant roots similar to, but it is more aerated than, a good agricultural soil. Developing BEST for SPQ assessment is advisable since parameters descriptive of the soil water transport properties can be collected with a single experiment. Simultaneous characterization of dendrometric and soil parameters at other sites is recommended to explore the relationships between SPQ indicators and characteristics of the forest cover.

The identification of tree species is an important issue in forest management. In recent years, many studies have explored this topic using hyperspectral, multispectral, and LiDAR data. In this study we analyzed two multi-sensor set-ups: 1) airborne high spatial resolution hyperspectral images combined with LiDAR data; and 2) high spatial resolution satellite multispectral images combined with LiDAR data. Two LiDAR acquisitions were considered: low point density (approx. 0.48 points per m2) and high point density (approx. 8.6 points per m2). The aims of this work were: i) to understand what level of classification accuracy can be achieved using a high spectral and spatial resolution multi-sensor data set-up (very high spatial and spectral resolution airborne hyperspectral images integrated with high point density LiDAR data), over a mountain area characterized by many species, both broadleaf and coniferous; ii) to understand the implications of a downgrading of the data characteristics (in terms of spectral resolution of spectral data and point density of LiDAR data), on species separability, with respect to the previous set-up; and iii) to understand the differences between high- and low-point density LiDAR acquisitions on tree species classification. The study region was a mountain area in the Southern Alps characterized by many tree species (7 species and a “non-forest” class), either coniferous or broadleaf. For each set-up a specific processing chain was adopted, from the pre-processing of the raw data to the classification (two classifiers were used: support vector machine and random forest). Different class definitions were tested, including general macro-classes, forest types, and finally single tree species. Experimental results showed that the set-up based on hyperspectral data was effective with general macro-classes, forest types, and single species, reaching high kappa accuracies (93.2%, 82.1% and 76.5%, respectively). The use of multispectral data produced a reduction in the classification accuracy, which was sharp for single tree species, and still high for forest types. Considering general macro-classes, the multispectral set-up was still very accurate (85.8%). Regarding LiDAR data, the experimental analysis showed that high density LiDAR data provided more information for tree species classification with respect to low density data, when combined with either hyperspectral or multispectral data.

One of the most outstanding issues of current environmental research is the need of reliable assessments of carbon stock (i.e. above-ground (a.g.) and below-ground biomass, deadwood, litter, and organic soil matter) within forest ecosystems. Although shrub vegetation plays an important role in accumulating carbon in many Mediterranean environments, there is still very little knowledge on the carbon they store. In this article, we analyze the a.g. carbon stock of several Mediterranean shrubby communities in Sicily (Italy), dominated by Pistacia lentiscus, Chamaerops humilis, Euphorbia dendroides and Spartium junceum. Plant samples for each species were selected, and morphometric attributes (height, crown diameter, diameter at breast height, etc.) were measured to establish models for estimating a.g. biomass. Dendrometric data were also used to support the assessment of shrub biomass at community level by coupling them with the coverage of the considered woody species estimated from several hundreds of phytosociological releve´s carried out on pre-forest Sicilian communities. Although the results of such an approach have to be considered as rough assessments, the trial proves interesting, given the lack of information on stand biomass of pre-forest vegetation within the Mediterraean region. L'articolo è disponibile sul sito dell'editore http://www.tandfonline.com

The book addresses in a comprehensive way the full greenhouse gases budget of the Italian landscape, focusing on land use and terrestrial ecosystems. In recent years there has been a growing interest in the role of terrestrial ecosystems with regard to the carbon cycle and only recently a regional approach has been considered for its specificity in terms of new methodologies for observations and models and its relevance for national policies on mitigation and adaptation to climate changes. In terms of methods this book describes the role of flux networks and data-driven models, airborne regional measurements of fluxes and specific sectoral approaches related to important components of the human and natural landscapes. There is also a growing need on the part of institutions, agencies and policy stakeholders for new data and analyses enabling them to improve their national inventories of greenhouse gases and their compliance with the UNFCCC process. In this respect the data presented is a basis for a full carbon accounting and available to relevant stakeholders for improvements and/or verification of national inventories. The wealth of research information is the result of a national project, CARBOITALY, which involved 15 Italian institutions and several researchers to provide new data and analyses in the framework of climate policies

The mechanisms of litter decomposition, translocation and stabilization into soil layers are fundamental processes in the functioning of the ecosystem, as they regulate the cycle of soil organic matter (SOM) and CO2 emission into the atmosphere. In this study the contribution of litters of different stages of Mediterranean secondary succession on carbon sequestration was investigated, analyzing the role of earthworms in the translocation of SOM into the soil profile. For this purpose the δ13C difference between meadow C4-C soil and C3-C litter was used in a field experiment. Four undisturbed litters of different stages of succession (45, 70, 100 and 120 since agriculture abandon) were collected and placed on the top of isolated C4 soil cores. The litter contribution to C stock was affected by plant species and it increased with the age of the stage of secondary succession. One year after the litter position, the soil organic carbon increased up to 40% in comparison to soils not treated with litter after 120 years of abandon. The new carbon derived from C3 litter was decomposed and transferred into soil profile thanks to earthworms and the leaching of dissolved organic carbon. After 1 year the carbon increase attributed to earthworm activity was 6 and 13% in the soils under litter of fields abandoned for 120 and 45 years, respectively.

Synchronous sonic anemometric measurements at five heightswithin a mixed coniferous forest were used to test two different parameterisations ofcanopy architecture in the application of a second-order turbulence closure model. Inthe computation of the leaf drag area, the aerodynamic sheltering was replaced with anarchitectural sheltering, assumed to be analogous to the clumping index defined in radiativetransfer theory. Consequently, the ratio of leaf area density and sheltering factor was approximatedby the effective leaf area or the mean contact number, both obtained from the inversion of non-destructive optical measurements. The first parameter represents the equivalentrandomly dispersed leaf area in terms of shading, the second is the average number of leavesthat a straight line intercepts penetrating the canopy with a certain zenith angle. Theselection of this direction was determined by the analysis of the mean angle of the wind vectorduring sweep events. The drag coefficient values obtained from the inversion of themomentum flux equation, using the two proposed parameterisations, are in good agreement withvalues found in the literature. The predicted profiles of turbulence statistics reasonablymatch actual measurements, especially in the case of the mean contact numberparameterisation. The vertical profile of leaf drag area, obtained by forcing the turbulence modelto match the observed standard deviation of vertical velocity (σw), is intermediatebetween the two empirical ones. Finally, the proposed canopy parameterisations were appliedto a Lagrangian transport model to predict vertical profiles of air temperature, H2O andCO2 concentration.

This study aims to develop models to describe CO2 fluxes in terms of environmental and meteorological variables and their variation over an Atlantic blanket bog in Glencar, southwest Ireland. Ten full years (September 2002–August 2012) of data were included in the assessment of CO2 flux and micro-meteorological data. Models were based on non-gapfilled growing season data, using complete calendar years for annual models, and the entire time-series for weekly models, whilst taking interaction between variables into account for increased model accuracy. This was to determine which environmental variables were most influential in directly controlling CO2 exchange on a long- and short-term basis. A homogeneity of slopes (HOS) model was used to determine if there was any ecosystem response to indirect effects (functional response) of environmental or meteorological interannual variation. This model uses multiple regression analysis to determine if the ecosystem response can be better predicted as a linear function of the variables using a single slope model for all years, or a separate slopes model for each year. The separate slopes model gave a different (and improved) outcome for both daytime and night-time CO2 fluxes, and so functional responses were deemed to have occurred. The contribution to variation of day and night-time net ecosystem exchange (NEEday and NEEnight respectively) was then separated into four components: indirect functional responses, direct interannual meteorological variability, direct week to week meteorological variability, and random error, which identified 13.8%, 36.6%, 28.2% and 21.4% respectively of the variation in NEEday, as well as 23.4%, 24.4%, 22.2% and 30% respectively of the variation in NEEnight. Water table level (WTL) had the greatest influence upon functional variation of NEE at the Glencar blanket peatland, and comparisons of modelled NEEday with leaf area index (LAI) measurements verified the estimate of functional contribution using the separate slopes model. The significance of interannual variation (IAV) and functional responses on NEE at Glencar suggests that it is a resilient ecosystem which might be able to adapt to environmental or climatic changes, although given current climate change predictions, it is likely to have a reduced carbon dioxide sink status in the future.

Gross primary productivity (GPP) is the largest and most variable component of the global terrestrial carbon cycle. Repeatable and accurate monitoring of terrestrial GPP is therefore critical for quantifying dynamics in regional-to-global carbon budgets. Remote sensing provides high frequency observations of terrestrial ecosystems and is widely used to monitor and model spatiotemporal variability in ecosystem properties and processes that affect terrestrial GPP. We used data from the Moderate Resolution Imaging Spectroradiometer (MODIS) and FLUXNET to assess how well four metrics derived from remotely sensed vegetation indices (hereafter referred to as proxies) and six remote sensing-based models capture spatial and temporal variations in annual GPP. Specifically, we used the FLUXNET "La Thuile" data set, which includes several times more sites (144) and site years (422) than previous efforts have used. Our results show that remotely sensed proxies and modeled GPP are able to capture statistically significant amounts of spatial variation in mean annual GPP in every biome except croplands, but that the total variance explained differed substantially across biomes (R2 ≈ 0.1−0.8). The ability of remotely sensed proxies and models to explain interannual variability GPP was even more limited. Remotely sensed proxies explained 40–60% of interannual variance in annual GPP in moisture-limited biomes including grasslands and shrublands. However, none of the models or remotely sensed proxies explained statistically significant amounts of interannual variation in GPP in croplands, evergreen needleleaf forests, and deciduous broadleaf forests. Because important factors that affect year-to-year variation in GPP are not explicitly captured or included in the remote sensing proxies and models we examined (e.g., interactions between biotic and abiotic conditions, and lagged ecosystems responses to environmental process), our results are not surprising. Nevertheless, robust and repeatable characterization of interannual variability in carbon budgets is critically important and the carbon cycle science community is increasingly relying on remotely sensing data. As larger and more comprehensive data sets derived from the FLUXNET community become available, additional systematic assessment and refinement of remote sensing-based methods for monitoring annual GPP is warranted., JRC.H.7-Climate Risk Management

Tree species mapping in forest areas is an important topic in forest inventory. In recent years, several studies have been carried out using different types of hyperspectral sensors under various forest conditions. The aim of this work was to evaluate the potential of two high spectral and spatial resolution hyperspectral sensors (HySpex-VNIR 1600 and HySpex-SWIR 320i), operating at different wavelengths, for tree species classification of boreal forests. To address this objective, many experiments were carried out, taking into consideration: 1) three classifiers (support vector machines (SVM), random forest (RF), and Gaussian maximum likelihood); 2) two spatial resolutions (1.5 m and 0.4 m pixel sizes); 3) two subsets of spectral bands (all and a selection); and 4) two spatial levels (pixel and tree levels). The study area is characterized by the presence of four classes 1) Norway spruce, 2) Scots pine, together with 3) scattered Birch and 4) other broadleaves. Our results showed that: 1) the HySpex VNIR 1600 sensor is effective in boreal tree species classification with kappa accuracies over 0.8 (with Pine and Spruce reaching producer's accuracies higher than 95%); 2) the role of the HySpex-SWIR 320i is limited, and its bands alone are able to properly separate only Pine and Spruce species; 3) the spatial resolution has a strong effect on the classification accuracy (an overall decrease of more than 20% between 0.4 m and 1.5 m spatial resolution); and 4) there is no significant difference between SVM or RF classifiers.

The purpose of the study was to evaluate tree species composition estimated using combinations of different remotely sensed data with different inventory approaches for a forested area in Norway. Basal area species composition was estimated as both species proportions and main species by using data from airborne laser scanning (ALS) and airborne (multispectral and hyperspectral) imagery as auxiliary information in combination with three different inventory approaches: individual tree crown (ITC) approach; semi-individual tree crown (SITC) approach; and area-based approach (ABA). The main tree species classification obtained an overall accuracy higher than 86% for all ABA alternatives and for the two other inventory approaches (ITC and SITC) when combining ALS and hyperspectral imagery. The correlation between estimated species proportions and species proportions measured in the field was higher for coniferous species than for deciduous species and increased with the spectral resolution used. Espec...

Clarifying which factors cause an increase or decrease in soil organic carbon (SOC) after agricultural abandonment requires integration of data on the temporal dynamics of the plant community and SOC. A chronosequence of abandoned vineyards was studied on a volcanic island (Pantelleria, Italy). Vegetation in the abandoned fields was initially dominated by annual and perennial herbs, then by Hyparrhenia hirta (L.) Stapf, and finally by woody communities. As a consequence, the dominant photosynthetic pathway changed from C3 to C4 and then back to C3. Conversion of a plant community dominated by one photosynthetic pathway to another changes the 13C/12C ratio of inputs to SOC. Using the time since abandonment and the shift in belowground δ13C of SOC relative to the aboveground δ13C plant community, we estimated C3-C and C4-C changes during secondary succession. SOC content (g kg− 1) increased linearly (R2 = 0.89 and 0.73 for 0–15 and 15–30 cm soil depth) with the age of abandonment, increasing from 12 g kg− 1 in cultivated vineyards to as high as 26 g kg− 1 in the last stage of the succession. δ13C increased in the bulk soil and its three aggregate fractions (> 250, 250–25, and < 25 μm) during succession, but the effect of soil depth and its interaction with succession age were significant only for soil aggregate fractions. Polynomial curves described the change in δ13C over the chronosequence for both depths. δ13C in the bulk soil had increased from − 28‰ to − 24‰ by 35 years after abandonment for both depths but then decreased to − 26‰ at 60 years after abandonment (corresponding with maturity of the woody plant community). Overall, the results indicate that abandoned vineyards on volcanic soil in a semi-arid environment are C sinks and that C storage in these soils is closely related to plant succession.

Ailanthus altissima is a well-known invasive tree in many parts of the world showing an outstanding ability to establish within woodlands and other less-disturbed habitats. Previous studies have reported that control of this species is very difficult because of its strong resprouting. Indeed, effective control can be achieved only by mechanical treatment followed by the application of a systemic herbicide. Operating drills or saws and other mechanical equipment require electric power supply which is not readily available in many invaded sites, notably shrubslands and woodlands. In two study sites, we evaluated control obtained by glyphosate through a stem-injection technique and compared two sources of power for the electric drill used. More than 90% of the glyphosate-treated trees in this study appeared to be dead just 1 month after treatments, and a car battery plus inverter was the most practical electrical source for drilling stems in the field.

We investigated the effects of woody plant colonization of abandoned pastures on soil and litter organic carbon (C) stocks and nitrogen (N) content along a bioclimatic transect in a semi-arid environment (Sicily, Italy). Soil samples were taken in three successional stages (grazed pasture, shrubland, forest) within each of three bioclimates (supramediterranean - “supra”, mesomediterranean - “meso”, thermomediterranean - “thermo”). Organic C and N in litter and soil (0-10 cm and 10-30 cm depth) were determined, as well as soil bulk density. Especially at 0-10 cm depth, changes in C and N contents along successional stages differed among bioclimates. Soil organic carbon (SOC) stock decreased from pasture to shrubland and increased from shrubland to forest in “supra”, increased from pasture to shrubland and then remained stable in “thermo”, and was stable in “meso”. Soil C/N ratio decreased with succession in “supra”, showed no significant trend in “meso”, and increased with succession in “thermo”. Litter C stock increased with succession in “meso”, increased from pasture to shrubland and decreased from shrubland to forest in “thermo”, and increased from pasture to shrubland and then remained stable in “supra”. Litter C/N ratio increased in “thermo” and “supra” from pasture to shrubland and from shrubland to forest, but did not change significantly with succession in “meso”. The different trends in SOC among bioclimates may be caused by changes in the importance of litter input, litter decay rate and mineralization. Successional changes in “meso” and “supra” appeared to be most affected by litter quality, while those in “thermo” appeared to be strongly influenced by limited litter decay due to low soil moisture and high temperature.

We investigated central Mediterranean Pinus halepensis plantations under semi-arid climate in order to evaluate the combined effect of soil treatment and afforestation practices on spontaneous plant species composition, richness and evenness, and on the trend and speed of vegetation dynamics. Phytosociological releves of three different plot typologies, i.e. (1) soil-treatment and plantation, (2) only soil-treatment, (3) no soil-treatment and no plantation, were compared by (a) multivariate analysis and (b) with reference to species richness and evenness. Moreover, in order to compare vegetation dynamics within the plantations with those ones ongoing in semi-natural garrigue communities, we compared life form and syntaxonomic spectra between phytosociological releves taken at 8 years of distance. DCA showed that floristic species composition and similarity are influenced by the canopy cover of Pine trees as well as by soil-treatment practices. Although species richness and evenness are not clearly related to neither soil treatment nor Pine afforestation, canopy cover clearly plays a major role: in fact, the highest Ph cover rates correspond to the lowest values of understory species richness. This is true also if only species of biogeographical/conservation interest are considered. Regarding vegetation dynamics, sites with dense Pine canopy cover evolve much slower than the adjacent garrigue communities. The same factors invoqued to explain the patterns of floristic composition and similarity (i.e. allelopathy and competition for light, water and nutrients) may also explain the lowering of diversity of therophytes and the strong decline of the cover perfomed by both therophytes and hemicryptophytes underneath the canopy of dense Ph plantations. Thus, in sites where Ph cover exceeds about 80%, thinning is recommended not only in order to accelerate succession, but also to give a natural ‘shape’ to afforestations.

Land use changes represent one of the most important components of global environmental change andhave a strong influence on carbon cycling. As a consequence of changes in economy during the last century, areas of marginal agriculture have been abandoned leading to secondary successions. The encroachment of woody plants into grasslands, pastures and croplands is generally thought to increase the carbon stored in these ecosystems even though there are evidences for a decrease in soil carbon stocks after land use change. In this paper, we investigate the effects of woody plant invasion on soil carbon and nitrogen stocks along a precipitation gradient (200–2,500 mm) using original data from paired experiment in Italian Alps and Sicily and data from literature (Guo and Gifford Glob Change Biol 8(4):345–360, 2002). We found a clear negative relationship (-0.05% C mm-1) between changes in soil organic carbon and precipitation explaining 70% of the variation in soil Cstocks after recolonization: dry sites gain carbon (up to? 67%) while wet sites lose carbon (up to -45%). In our data set, there seem to be two threshold values for soil carbon accumulation: the first one is 900 mm of mean annual rainfall, which separates the negative from the positive ratio values; the second one is 750 mm, which divides the positive values in two groups of sites. Most interestingly, this threshold of 750 mm corresponds exactly to a bioclimatic threshold: sites with\750 mm mean annual rainfall is classified as thermo-mediterranean sites, while the ones [750 mm are classified as mesomediterranean sites. This suggests that apart from rainfall also temperature values have an important influence on soil carbon accumulation after abandonment. Moreover, our results confirmed that the correlation between rainfall and trend in soil organic carbon may be related to nitrogen dynamics: carbon losses may occur only if there is a substantial decrease in soil nitrogen stock which occurs in wetter sites probably because of the higher leaching.

article i nfo Remote sensing can be considered a key instrument for studies related to forests and their dynamics. At present, the increasing availability of multisensor acquisitions over the same areas, offers the possibility to combine data from different sensors (e.g., optical, RADAR, LiDAR). This paper presents an analysis on the fusion of airborne LiDAR and satellite multispectral data (IRS 1C LISS III), for the prediction of forest stem volume at plot level in a complex mountain area (Province of Trento, Southern Italian Alps), characterized by different tree species, complex morphology (i.e. altitude ranges from 65 m to 3700 m above sea level), and a range of different climates (from the sub-Mediterranean to Alpine type). 799 sample plots were randomly distributed over the 3000 km 2 of the forested areas of the Trento Province. From each plot, a set of variables were extracted from both LiDAR and multispectral data. A regression analysis was carried out considering two data sources (LiDAR and multispectral) and their combination, and dividing the plot areas into groups according to their species composition, altitude and slope. Experimental results show that the combination of LiDAR and IRS 1C LISS III data, for the estimation of stem volume, is effective in all the experiments considered. The best developed models comprise variables extracted from both of these data sources. The RMSE% on an independent validation set for the stem volume estimation models ranges between 17.2% and 26.5%, considering macro sets of tree species (deciduous, evergreen and mixed), between 17.5% and 29.0%, considering dominant species plots, and between 15.5% and 21.3% considering altitude and slope sets.