Contribution and stability of forest-derived soil organic carbon during woody encroachment in a tropical savanna. A case study in Gabon

In this study, we quantified the contribution of forest-derived carbon (FDC) to the soil organic C (SOC) pool along a natural succession from savanna (S) to mixed Marantaceae forest (MMF) in the Lopè National Park, Gabon. Four 1-ha plots, corresponding to different stages along the natural succession, were used to determine the SOC stock and soil C isotope composition (δ13C) to derive the FDC contribution in different soil layers down to 1 m depth. Besides, to investigate changes in SOC stability, we determined the 14C concentration of SOC to 30 cm depth and derived turnover time (TT). Results indicated that SOC increased only at the end of the succession in the MMF stage, which stored 46% more SOC (41 Mg C ha−1) in the 0–30 cm depth than the S stage (28.8 Mg C ha−1). The FDC contribution increased along forest succession affecting mainly the top layers of the initial successional stages to 15 cm depth and reaching 70 cm depth in the MMF stage. The TT suggests a small increase in stability in the 0–5 cm layer from S (146 years) to MMF (157 years) stages. Below 5 cm, the increase in stability was high, suggesting that FDC can remain in soils for a much longer time than savanna-derived C. In conclusion, the natural succession toward Marantaceae forests can positively impact climate change resulting in large SOC stocks, which can be removed from the atmosphere and stored for a much longer time in forest soils compared to savanna soils

Selective Methods to Investigate Authenticity and Geographical Origin of Mediterranean Food Products

The Mediterranean diet is promoted as one of the healthiest and closely linked to socioecological practices, knowledge and traditions, promoting sustainable food production, and linking geographical origin with food quality and ecosystem services. Consumer adherence to this dietary pattern drives increased consumption of authentic “premium” foods, such as Iberian pig meat and dry-cured ham from Portugal and Spain, argan oil from Morocco, “Djebel” lamb from Tunisia and truffles from Italy and Slovenia, i.e., food products that respond to current ethical, environmental and socially sustainable demands. Geographical indication and appellation of origin can increase traditional food products competitiveness, but the high-value recognition of these products can also lead to economically motivated product adulteration. It is therefore imperative to protect the high added value of these unique food products by ensuring their quality, authenticity, provenance and sustainable production systems. In this review, we provide a critical evaluation of the analytical methods that are currently used for the determination of provenance and authenticity of these Mediterranean products as well as possible strategies for improving the throughput and affordability of the methods discussed.info:eu-repo/semantics/publishedVersio

What is the future for agroforestry in Italy?

The successful promotion of agroforestry in Italy depends on both a recognition of tradition and the opportunities for innovation. In Italy, agroforestry has traditionally been a key component of landscape management. Complex systems, based on the integration among crops–livestock–fruit/forest trees, provided a wide variety of products (e.g. food, feed, fibers, fuelwood and timber) and other ecosystem services (e.g. soil erosion control and biodiversity preservation). Silvopastoral systems have been used for centuries and are still managed in marginal areas. The integration of fruits trees (in primis olive trees) with crops and grazing was widely practiced and is still profitable. Coltura promiscua was historically developed integrating fruit and forest trees and particularly multifunctional trees (e.g. Juglans regia L. and Prunus avium L.) to support vines and intercrops. Building on recent research, projects have also focused on innovation in agroforestry. The adoption of shade tolerant forage species and crops has been studied in silvopastoral and olive systems. Silvopastoral systems can significantly offset the greenhouse gas emissions produced by livestock and shield grazing animals from “heat waves”. Integration of fast growing timber trees (like Populus) in arable systems can help reverse the decline in plantation forestry in Italy. Finally, the constraints imposed by the EU agricultural policy, especially the prevalent provisions for monocrops severely limiting the introduction of innovative agroforestry approaches, are discussed. New political measures and certification actions are strongly required

STRUCTURAL PATTERNS, GROWTH PROCESSES, CARBON STOCKS IN AN ITALIAN NETWORK OF OLD-GROWTH BEECH FORESTS

In the framework of the Project of National Interest (PRIN) “Climate change and forests - Dendroecological and ecophysiological responses, productivity and carbon balance on the Italian network of old-growth beech forests”, 9 old beech (Fagus sylvatica L.) forests were sampled in the eastern Alps and in the central Apennines to assess: i) the degree of ‘old-growthness’ on a structural and dendroecological basis; ii) the carbon (C) stocks in the different ecosystem compartments; iii) some ecophysiological traits using stable isotopes. Live and dead tree structure, soil features and C stocks were examined in some among the oldest and less disturbed beech forests in Italy. Furthermore, leaves, litter and wood cores were sampled for concurrent dendroecological, nutrient and stable isotope analysis, to study age structure, disturbance history and medium- and long-term response to climate and ecophysiological traits. In all sampled stands, values of basal area, volume and large trees density reached or exceeded control values reported for European and North American old-growth forests, while total amount of deadwood was generally low, except in two sites. Diameter distribution showed a remarkable differentiation from bimodal to ‘rotated-sigmoid’ curve. In accordance with structural analyses, disturbance chronologies revealed the importance of frequent low-to-moderate events in generating a fine-scale structure, confirming previous results on beech forests. Different degrees of ‘old-growthness’ were identified for Alpine and Apennine beech stands through the ‘structural-based approach’, which proved to be a valid tool for old-growth forests detection. Preliminary results on carbon stocks on a subset of sites indicate that these old-growth forests are relevant carbon reservoirs, with 192-268 MgC ha-1 of total biomass (67-73% aboveground; 27-33% belowground, 4 stands) and 7-21 MgC ha-1 of deadwood. In these stands, also forest floor (excluding deadwood) and soils are stores of relevant amount of carbon (5-9 MgC ha-1 litter layer, 4 stands; 168-420 MgC ha-1 mineral soil, 3 stands). Finally, carbon isotope discrimination (Δ) analysis, a proxy of wateruse efficiency, was applied on tree-ring cores from a subset of sites. The perspectives of this technique for a retrospective ecophysiological interpretation of climate-change impact on old-growth forests were described. Preliminary results obtained within this PRIN project indicate that the reported ecological indicators can be used to produce a description of forest structures and processes driving stand dynamics (‘structural-based approach’). Furthermore, the use of multiple sampling and research techniques and the integration of research groups with complementary expertise can foster deeper understanding of the ecology and dynamics of old-growth forests.L'articolo è disponibile sul sito dell'editore http://www.aisf.it

Self-Organizing Deep Learning (SO-UNet)—A Novel Framework to Classify Urban and Peri-Urban Forests

Forest-type classification is a very complex and difficult subject. The complexity increases with urban and peri-urban forests because of the variety of features that exist in remote sensing images. The success of forest management that includes forest preservation depends strongly on the accuracy of forest-type classification. Several classification methods are used to map urban and peri-urban forests and to identify healthy and non-healthy ones. Some of these methods have shown success in the classification of forests where others failed. The successful methods used specific remote sensing data technology, such as hyper-spectral and very high spatial resolution (VHR) images. However, both VHR and hyper-spectral sensors are very expensive, and hyper-spectral sensors are not widely available on satellite platforms, unlike multi-spectral sensors. Moreover, aerial images are limited in use, very expensive, and hard to arrange and manage. To solve the aforementioned problems, an advanced method, self-organizing–deep learning (SO-UNet), was created to classify forests in the urban and peri-urban environment using multi-spectral, multi-temporal, and medium spatial resolution Sentinel-2 images. SO-UNet is a combination of two different machine learning technologies: artificial neural network unsupervised self-organizing maps and deep learning UNet. Many experiments have been conducted, and the results showed that SO-UNet overwhelms UNet significantly. The experiments encompassed different settings for the parameters that control the algorithms

Timescape: A Novel Spatiotemporal Modeling Tool

We developed a novel approach in the field of spatiotemporal modeling, based on the spatialisation of time, the Timescape algorithm. It is especially aimed at sparsely distributed datasets in ecological research, whose spatial and temporal variability is strongly entangled. The algorithm is based on the definition of a spatiotemporal distance that incorporates a causality constraint and that is capable of accommodating the seasonal behavior of the modeled variable as well. The actual modeling is conducted exploiting any established spatial interpolation technique, substituting the ordinary spatial distance with our Timescape distance, thus sorting, from the same input set of observations, those causally related to each estimated value at a given site and time. The notion of causality is expressed topologically and it has to be tuned for each particular case. The Timescape algorithm originates from the field of stable isotopes spatial modeling (isoscapes), but in principle it can be used to model any real scalar random field distribution

Photosynthesis-nitrogen relationships: interpretation of different patterns between Pseudotsuga menziesii and Populus x euroamericana in a mini-stand experiment

We compared photosynthesis–nitrogen relationships of one broad-leaved (poplar; Populus × euroamericana (Dole) Guinier) and one conifer (Douglas-fir; Pseudotsuga menziesii (Mirb.) Franco) species. Plants were grown in large pots to allow free root development and were kept well watered. We determined effects of low, intermediate and high nitrogen supply rates on area-based leaf nitrogen (Na) and chlorophyll concentrations, leaf mass per area (LMA), light-saturated photosynthesis (Amax), maximum carboxylation (Vcmax) and electron transport rate (Jmax), photosynthetic nitrogen-use efficiency (PNUE), and proportions of leaf N in active Rubisco (PR), bioenergetic pools (PB) and the light-harvesting complex (PLH). Nitrogen supply significantly affected leaf Na. Leaf mass per area did not differ between species and was unaffected by the N treatments. In both species, there was a positive correlation between leaf Na and chlorophyll concentration, and between leaf Na and the photosynthetic parameters Amax, Jmax and Vcmax. At comparable leaf Na, however, poplar showed twofold higher PNUE and a threefold steeper slope of the Amax– nitrogen relationship than Douglas-fir. Leaf Na was negatively correlated with PNUE in Douglas-fir but not in poplar. Leaf Na was also negatively correlated with PR, PB and PLH in Douglas-fir, whereas in poplar, a negative correlation was found only for PLH. Parameter PR was significantly higher in poplar than in Douglas-fir. The ratio of CO2 concentration in the intercellular space to that in ambient air was higher in poplar than in Douglas-fir. Overall, our data suggest that differences in the photosynthesis–nitrogen relationship and PNUE between Douglas-fir and poplar primarily reflect a different investment of N to active Rubisco, and possibly a different constraint to CO2 diffusion

Variation in nitrogen supply changes the water use efficiency of Pseudotsuga menziesii and Populus x euroamericana; a comparison of three different approaches to determine water-use efficiency

We studied the effects of three nitrogen (N) supply rates (low, intermediate and high) on Douglas-fir (Pseudotsuga menziesii (Mirb.) Franco) seedlings and poplar clone “I-214” (Populus × euroamericana (Dole) Guinier) cuttings growing in mini-stands. Our specific objectives were to: (1) evaluate the effects ofNsupply onwater-use efficiency (WUE) and biomass production; (2) determine if N affects WUE through control of carbon assimilation rates or through stomatal control of water loss; and (3) compare three methods of estimating WUE: one short-term method (WUEi, based on gas exchange measurements) and two long-term methods (WUET, based on the ratio between biomass production and transpired water, and Δ, based on leaf carbon isotope discrimination tested as a proxy of WUE). In both species, biomass production, WUEi andWUET increased with increasing Nsupply, but there was no effect of N supply on either transpiration or stomatal conductance and Δ was negatively related to leaf N concentration. Plots of Δ versus both WUEi and WUET revealed negative trends, but the regression betweenWUEi and Δ was significant only for Douglas-fir, and the regression between WUET and Δ was significant only for poplar. Thus, the mechanisms underlying the response of WUE to N supply were mainly related to a positive effect of N supply on photosynthetic rates. The data confirm that carbon isotope discrimination may be a useful proxy of WUE. The finding that N availability enhances both biomass production and WUE may have practical implications in regions where these factors impose constraints on forest productivity