The response of forest ecosystems to increased atmospheric CO₂is constrained by nutrient availability. It is thus crucial to account for nutrient limitation when studying the forest response to ...climate change. The objectives of this study were to describe the nutritional status of the main European tree species, to identify growth‐limiting nutrients and to assess changes in tree nutrition during the past two decades. We analysed the foliar nutrition data collected during 1992–2009 on the intensive forest monitoring plots of the ICP Forests programme. Of the 22 significant temporal trends that were observed in foliar nutrient concentrations, 20 were decreasing and two were increasing. Some of these trends were alarming, among which the foliar P concentration in F. sylvatica, Q. Petraea and P. sylvestris that significantly deteriorated during 1992–2009. In Q. Petraea and P. sylvestris, the decrease in foliar P concentration was more pronounced on plots with low foliar P status, meaning that trees with latent P deficiency could become deficient in the near future. Increased tree productivity, possibly resulting from high N deposition and from the global increase in atmospheric CO₂, has led to higher nutrient demand by trees. As the soil nutrient supply was not always sufficient to meet the demands of faster growing trees, this could partly explain the deterioration of tree mineral nutrition. The results suggest that when evaluating forest carbon storage capacity and when planning to reduce CO₂emissions by increasing use of wood biomass for bioenergy, it is crucial that nutrient limitations for forest growth are considered.
As an interdisciplinary field of research, phenology is developing rapidly, and the contents of phenological research have become increasingly abundant. In addition, the potentiality of remote ...sensing technologies has largely contributed to the growth and complexity of this discipline, in terms of the scale of analysis, techniques of data processing, and a variety of topics. As a consequence, it is increasingly difficult for scientists to get a clear picture of remotely sensed phenology (rs+pheno) research. Bibliometric analysis is increasingly used for the study of a discipline and its conceptual dynamics. This review analyzed the last 40 years (1979–2018) of publications in the rs+pheno field retrieved from the Scopus database; such publications were investigated by means of a text mining approach, both in terms of bibliographic and text data. Results demonstrated that rs+pheno research is exponentially growing through time; however, it is primarily considered a subset of remote sensing science rather than a branch of phenology. In this framework, in the last decade, agriculture is becoming more and more a standalone science in rs+pheno research, independently from other related topics, e.g., classification. On the contrary, forestry struggles to gain its thematic role in rs+pheno studies and remains strictly connected with climate change issues. Classification and mapping represent the major rs+pheno topic, together with the extraction and the analysis of phenological metrics, like the start of the growing season. To the contrary, forest ecophysiology, in terms of ecosystem respiration and net ecosystem exchange, results as the most relevant new topic, together with the use of the red edge band and SAR (Synthetic Aperture Radar) data in rs+pheno agricultural studies. Some niche emerging rs+pheno topics may be recognized in the ocean and arctic investigations linked to phytoplankton blooming and ice cover dynamics. The findings of this study might be applicable for planning and managing remotely sensed phenology research; scientists involved in such discipline might use this study as a reference to consider their research domain in a broader dynamical network.
Knowing the extent and frequency of forest cuttings over large areas is crucial for forest inventories and monitoring. Remote sensing has amply proved its ability to detect land cover changes, ...particularly in forested areas. Among various strategies, those focusing on mapping using classification approaches of remotely sensed time series are the most frequently used. The main limit of such approaches stems from the difficulty in perfectly and unambiguously classifying each pixel, especially over wide areas. The same procedure is of course simpler if performed over a single pixel. An automated method for identifying forest cuttings over a predefined network of sampling points (IUTI) using multitemporal Sentinel 2 imagery is described. The method employs normalized difference vegetation index (NDVI) growth trajectories to identify the presence of disturbances caused by forest cuttings using a large set of points (i.e., 1580 “forest” points). We applied the method using a total of 51 S2 images extracted from the Google Earth Engine over two years (2016 and 2017) in an area of about 70 km2 in Tuscany, central Italy.
The delivery of biomass products from the production place to the point of final transformation is of fundamental importance within the constitution of energy chains based on biomass use as a ...renewable energy source. Transport can be one of the most economically expensive operations of the entire biomass energy production process, which limits choices in this sector, often inhibiting any expansive trends. A geographic identification, through remote sensing and photo-interpretation, of the different biomass sources was used to estimate the potential available biomass for energy in a small-scale supply chain. This study reports on the sustainability of transport costs calculated for different types of biomass sources available close a biomass power plant of a small-scale energy supply chain, located in central Italy. To calculate the transport cost referred to the identified areas we used the maximum travel time parameter. The proposed analysis allows us to highlight and visualize on the map the areas of the territory characterized by greater economic sustainability in terms of lower transport costs of residual agroforestry biomass from the collection point to the final point identified with the biomass power plant. The higher transport cost was around €40 Mg−1, compared to the lowest of €12 Mg−1.
Cost-effective sampling methods for the estimation of variables of interest that are time-consuming are a major concern. Ranked set sampling (RSS) is a sampling method that assumes that a set of ...sampling units drawn from the population can be ranked by other means without the actual measurement of the variable of interest. We used data on vegetation dynamics from satellite remote sensing as a means in which to rapidly rank sampling units across various land covers and to estimate their residual agroforestry biomass contribution for a small cogeneration facility located in the center of a study area in central Italy. A remote sensing map used as an auxiliary variable in RSS enabled us to cut down the photo-interpretation of the residual biomass present in sampling units from 745 to 139, increase the relative precision of the estimate over common simple random sampling, and avoid individual subjective bias being introduced. The photo-interpretation of the sampling units resulted in a 1.12 Mg ha−1 year−1 mean annual density of residual biomass supply, although unevenly distributed among land cover classes; this led to an estimate of a yearly supply of 132 Gg over the whole 2276 km2 wide study area. Further applications of this study might include the spatial quantification of biomass supply-related ecosystem services.
This study aimed at testing whether the integration of precision farming (PF) and agroecological practices could influence wheat yield in the short term on soils exposed to varying degrees of risk ...from flooding. The study embraced two years (2018–2019 and 2020–2021) of wheat cultivation in Central Italy. A two-way factorial grid with agronomic practice (two levels: agroecology vs. conventional on-farm management) and soil vulnerability to flooding (three levels: extreme, mild, non-vulnerable) as factors was set up. The agroecology level included a number of agroecology practices (rotation, use of nitrogen-fixing crops, mulching, and reduction in chemical fertilization). Crop phenology and photosynthetic activity of wheat was monitored by remotely-sensed Normalized Difference Vegetation Index (NDVI). Grain yield was estimated at twenty sampling points at the end of year 2. A flooding event occurred during year 2, which led to significantly lower photosynthetic activity compared to year 1 in extremely vulnerable plots regardless of agronomic practices. Grain yield measurements confirmed that vulnerability was the sole factor significantly affecting yield. The study concludes that food security on vulnerable land can be guaranteed only when precision farming and agroecological practices are coupled with water management techniques that strengthen the resilience of vulnerable soils to floods.
Recent decades have seen a progressive degradation of soils owing to an intensification of farming practices (weeding and high trafficking), increasing use of pesticides and fertilizers, mainly ...nitrogen, resulting in a steady decline in soil organic matter, a key component to maintain soil fertility. The work has coupled the normalized difference vegetation index (NDVI) of wheat cultivation in Central Italy to soil properties where the wheat was grown to identify the properties linked to within-field variability in productivity. NDVI was assessed through Copernicus Sentinel-2 (S-2) data during the wheat anthesis phase. The main outcome showed a significant correlation of NDVI variability to soil colloidal status and to the relative quantity in the exchange complex of the Ca2+ ions. No relationship emerged between NDVI and soil macronutrients (nitrogen, phosphorus, and potassium) concentration. The work suggested that such elements (nitrogen, especially) should not be provided solely considering the vegetation index spatial variations. Rational and sustainable management of soil fertility requires the integration of the NDVI data with the whole complex of soil physical/chemical status. In this way, the identification of the real key factors of fertility will avoid the negative impact of overfertilization. As an example, a fertilization plan was simulated for the sunflower–wheat sequence. The results showed that in the study area additional supplies of N and K would be unnecessary.
The exploration of crop seasonality across a region offers a way to help understand the phenological spatial patterns of complex landscapes, like agricultural ones. Knowing the role of environmental ...factors in influencing crop phenology patterns and processes is a key aspect for understanding the impact of climate and land use changes on agricultural landscape dynamics. We identified pixels with similar phenological behavior (i.e., pheno-clusters) and compared them to the land cover map of the study area to assess the role of the land management component in controlling the phenological patterns identified. Results demonstrated that soil texture is the most important factor for permanent crops, while large amount of rainfall and high values of available water content are the main drivers in spring cultivations (i.e., irrigated crops). Scarce water availability (in terms of soil texture, low annual precipitation and high minimum temperature) represented the main driving factor for non-irrigated crops, whose phenology is characterized by summer drought and fall-winter productivity. Compared to vegetation maps that use only land cover from a single season or period, using seasonality of the NDVI time series to classify the agricultural landscape provides different and more ecologically relevant information about croplands.
The autonecrotic tomato line V20368 (working code IGSV) spontaneously develops necrotic lesions with acropetal progression in response to an increase in temperature and light irradiation. The process ...is associated with the interaction between tomato and Cladosporium fulvum, the fungal agent of leaf mold. The contemporary presence of an in-house allele encoding the Rcr3lyc protein and the resistance gene Cf-2pim (from Solanum pimpinellifolium) causes auto-necrosis on the leaves even in the absence of the pathogen (hybrid necrosis). The aim of the work was (i) to examine the potential value of the necrotic genotype as a model system for setting up theoretical guidance for monitoring the phytosanitary status of tomato plants and (ii) to develop a predictive model for the early detection of pathogens (or other stresses) in the tomato or other species. Eighteen IGSV tomato individuals at the 4–5th true-leaf stage were grown in three rows (six plants per row) considered to be replicates. The healthy control was the F1 hybrid Elisir (Olter). A second mutant line (SA410) deriving from a cross between the necrotic mutant and a mutant line of the lutescent (l) gene was used during foliar analysis via microspectrometry. The leaves of the mutants and normal plants were monitored through a portable VIS/NIR spectrometer SCIOTM (Consumer Physics, Tel Aviv, Israel) covering a spectral range between 740 and 1070 nm. Two months after the transplant, the acropetal progression of the autonecrosis showed three symptomatic areas (basal, median, apical) on each IGSV plant: necrotic, partially damaged, and green, respectively. Significantly lower chlorophyll content was found in the basal and median areas of IGSV compared with the control (Elisir). A supervised classification/modelling method (SIMCA) was used. Applying the SIMCA model to the dataset of 162 tomato samples led to the identification of the boundary between the healthy and damaged samples (translational critical distance). Two 10 nm wavelength ranges centred at 865 nm and 1055 nm exhibited a stronger link between symptomatology and spectral reflectance. Studies on specific highly informative mutants of the type described may allow for the development of predictive models for the early detection of pathogens (or other stresses) via proximal sensing.
•We applied machine learning to EVI profiles to iden6fy SFD pixels.•We analyzed the influence of topographic factors on SFD pixels distribu6on.•We analyzed the produc6vity loss of SFD pixels compared ...to the previous 15 years.•Eleva6on proved to be the main topographic driver for SFD pixels distribu6on.•A produc6vity loss of 14% occurred compared to the previous 15 years.
In common beech forests the most damaging frosts are those that occur at the end of spring. At that time the fresh new leaves are at a vulnerable stage and risk to be readily killed by the freezing temperatures. The ability to identify late spring frost spatial dynamics is a key issue for understanding forest patterns and processes linked to such extreme event. The aim of this study is to detect, map and quantify the vegetation anomalies that occurred in the mono-specific beech forest of the Lazio, Abruzzo and Molise National Park (Italy) after an exceptional spring frost recorded on the 25th of April 2016. Results showed that, beech forests at lower elevations that had an early greening process were subject to spring frost damage (SFD pixels) and their productivity performance strongly decreased with respect to the previous 15 years; to the contrary the beech forests located at higher elevations did not suffer the spring frost effects (NSFD pixels) thanks to their delayed leaf unfolding phase. The duration of the effects of freezing stress for the SFD pixels was about two months, until the end of June, confirmed by Net Ecosystem Exchange measurements. This greening hiatus led to an average 14% loss of productivity compared to the previous 15 years. Elevation had a significant role on the probability of occurrence of SFD pixels. Productivity loss in SFD pixels was more severe at elevations in the range 1500–1700 m, on steeply terrains and North aspects. This study represents a step forward the systematic use of automated techniques to study areas subject to stress or anomalies from multitemporal satellite imagery and to identify break points and recovery of the greening process.
PDF
