Francesco Primo Vaccari

Global patterns of land‐atmosphere fluxes of carbon dioxide, latent heat, and sensible heat derived from eddy covariance, satellite, and meteorological observations

We upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (MTE). We trained MTE to predict site-level gross primary productivity (GPP), terrestrial ecosystem respiration (TER), net ecosystem exchange (NEE), latent energy (LE), and sensible heat (H) based on remote sensing indices, climate and meteorological data, and information on land use. We applied the trained MTEs to generate global flux fields at a 0.5 degrees x 0.5 degrees spatial resolution and a monthly temporal resolution from 1982 to 2008. Cross-validation analyses revealed good performance of MTE in predicting among-site flux variability with modeling efficiencies (MEf) between 0.64 and 0.84, except for NEE (MEf = 0.32). Performance was also good for predicting seasonal patterns (MEf between 0.84 and 0.89, except for NEE (0.64)). By comparison, predictions of monthly anomalies were not as strong (MEf between 0.29 and 0.52). Improved accounting of disturbance and lagged environmental effects, along with improved characterization of errors in the training data set, would contribute most to further reducing uncertainties. Our global estimates of LE (158 +/- 7 J x 10(18) yr(-1)), H (164 +/- 15 J x 10(18) yr(-1)), and GPP (119 +/- 6 Pg C yr(-1)) were similar to independent estimates. Our global TER estimate (96 +/- 6 Pg C yr(-1)) was likely underestimated by 5-10%. Hot spot regions of interannual variability in carbon fluxes occurred in semiarid to semihumid regions and were controlled by moisture supply. Overall, GPP was more important to interannual variability in NEE than TER. Our empirically derived fluxes may be used for calibration and evaluation of land surface process models and for exploratory and diagnostic assessments of the biosphere.

Intercomparison of UAV, aircraft and satellite remote sensing platforms for precision viticulture

Precision Viticulture is experiencing substantial growth thanks to the availability of improved and cost-effective instruments and methodologies for data acquisition and analysis, such as Unmanned Aerial Vehicles (UAV), that demonstrated to compete with traditional acquisition platforms, such as satellite and aircraft, due to low operational costs, high operational flexibility and high spatial resolution of imagery. In order to optimize the use of these technologies for precision viticulture, their technical, scientific and economic performances need to be assessed. The aim of this work is to compare NDVI surveys performed with UAV, aircraft and satellite, to assess the capability of each platform to represent the intra-vineyard vegetation spatial variability. NDVI images of two Italian vineyards were acquired simultaneously from different multi-spectral sensors onboard the three platforms, and a spatial statistical framework was used to assess their degree of similarity. Moreover, the pros and cons of each technique were also assessed performing a cost analysis as a function of the scale of application. Results indicate that the different platforms provide comparable results in vineyards characterized by coarse vegetation gradients and large vegetation clusters. On the contrary, in more heterogeneous vineyards, low-resolution images fail in representing part of the intra-vineyard variability. The cost analysis showed that the adoption of UAV platform is advantageous for small areas and that a break-even point exists above five hectares; above such threshold, airborne and then satellite have lower imagery cost.

Joint control of terrestrial gross primary productivity by plant phenology and physiology

Significance Terrestrial gross primary productivity (GPP), the total photosynthetic CO2 fixation at ecosystem level, fuels all life on land. However, its spatiotemporal variability is poorly understood, because GPP is determined by many processes related to plant phenology and physiological activities. In this study, we find that plant phenological and physiological properties can be integrated in a robust index—the product of the length of CO2 uptake period and the seasonal maximal photosynthesis—to explain the GPP variability over space and time in response to climate extremes and during recovery after disturbance. Terrestrial gross primary productivity (GPP) varies greatly over time and space. A better understanding of this variability is necessary for more accurate predictions of the future climate–carbon cycle feedback. Recent studies have suggested that variability in GPP is driven by a broad range of biotic and abiotic factors operating mainly through changes in vegetation phenology and physiological processes. However, it is still unclear how plant phenology and physiology can be integrated to explain the spatiotemporal variability of terrestrial GPP. Based on analyses of eddy–covariance and satellite-derived data, we decomposed annual terrestrial GPP into the length of the CO2 uptake period (CUP) and the seasonal maximal capacity of CO2 uptake (GPPmax). The product of CUP and GPPmax explained >90% of the temporal GPP variability in most areas of North America during 2000–2010 and the spatial GPP variation among globally distributed eddy flux tower sites. It also explained GPP response to the European heatwave in 2003 (r2 = 0.90) and GPP recovery after a fire disturbance in South Dakota (r2 = 0.88). Additional analysis of the eddy–covariance flux data shows that the interbiome variation in annual GPP is better explained by that in GPPmax than CUP. These findings indicate that terrestrial GPP is jointly controlled by ecosystem-level plant phenology and photosynthetic capacity, and greater understanding of GPPmax and CUP responses to environmental and biological variations will, thus, improve predictions of GPP over time and space.

Carbon Dioxide Emissions of the City Center of Firenze, Italy: Measurement, Evaluation, and Source Partitioning

Abstract An eddy covariance station was installed in the city center of Firenze, Italy, to measure carbon fluxes at half-hourly intervals over a mostly homogeneous urban area. Carbon dioxide (CO2) emission observations made over an initial period of 3.5 months were compared with indirect estimates of CO2 emissions based on inventory data sources of vehicle circulation and natural gas consumption for domestic heating and cooking. Such a comparison provided proper evaluation of the measurements. Using seasonal dynamics of observed fluxes, the overall CO2 source of the city center was partitioned into its major components (i.e., road traffic and domestic heating). Results were directly compared with CO2 source estimates based on inventory sources.

Surface albedo following biochar application in durum wheat

The agronomic use of charcoal from biomass pyrolysis (biochar) represents an interesting option for increasing soil fertility and sequestering atmospheric CO2. However, before moving toward large-scale biochar applications, additional research must evaluate all possible land‐atmosphere feedbacks. Despite the increasing number of studies investigating the effect of biochar on soil physical, chemical and biological properties, only a few have been done on surface albedo variations on agricultural lands. The present work had the aim of characterizing the annual albedo cycle for a durum wheat crop in Central Italy, by means of a spectroradiometer measurement campaign. Plots treated with biochar, at a rate of 30‐60 t ha 1 , showed a surface albedo decrease of up to 80% (after the application) with respect to the control in bare soil conditions, while this difference tended to decrease during the crop growing season, because of the prevailing effect of canopy development on the radiometer response. After the post-harvesting tillage, the soil treated with biochar again showed a lower surface albedo value (<20‐26% than the control), while the measurements taken in the second year after application suggested a clear decrease of biochar influence on soil color. The modeling of the surface energy balance highlighted changes in the partitioning of heat fluxes and in particular a substantial increase of ground heat fluxes on an annual basis.

Physiological and morphological responses of grassland species to elevated atmospheric CO2 concentrations in FACE-systems and natural CO2 springs

Stomatal density, leaf conductance and water relations can be affected by an increase in the concentration of atmospheric CO2, and thus affect plant productivity. However, there is uncertainty about the effects of elevated CO2 on stomatal behaviour, water relations and plant productivity, owing to the lack of long-term experiments in representative natural ecosystems. In this work, variations in stomatal density and index, leaf water relations and plant biomass of semi-natural grassland communities were analysed under field conditions by comparing plants in three different experimental set-ups (natural CO2 springs, plastic tunnels and mini-FACE systems). Natural degassing vents continuously expose the surrounding vegetation to truly long-term elevated CO2 and can complement short-term manipulative experiments. Elevated CO2 concentration effects on stomata persist in the long term, though different species growing in the same environment show species-specific responses. The general decrease in stomatal conductance after exposure to elevated CO2 was not associated with clear changes in stomatal number on leaf surfaces. The hypothesis of long-term adaptive modifications to stomatal number and distribution of plants exposed to elevated CO2 was not supported by these experiments on grassland communities. Elastic cell wall properties were affected to some extent by elevated CO2. Above-ground biomass did not vary between CO2 treatments, leaf area index did not compensate for reduced stomatal conductance, and the root system had potentially greater soil exploration capacity. Considerable between-species variation in response to elevated CO2 may provide a mechanism for changing competitive interactions among plant species.

An energy‐biochar chain involving biomass gasification and rice cultivation in Northern Italy

The competing demand for food and bioenergy requires new solutions for the agricultural sector as, for instance, the coupling of energy production from gasification technology and the application of the resulting biochar as soil amendment. A prerequisite for the implementation of this strategy is the scale‐specific assessment of both the energetic performance and of the impacts in terms of greenhouse gases (GHG) emission and crop responses. This study considered the gasification process developed by Advanced Gasification Technology (AGT, Italy), which is a fixed‐bed, down‐draft, open core, compact gasifier, having 350 kW of nominal electric capacity (microgeneration); this gasifier uses biomass feedstock deriving from agricultural/forest products and byproducts. In this study, the resulting biochar, derived from conifer wood chips of mountain forestry management in North‐western Italy, was applied to a nearby paddy rice field, located in the largest rice agricultural area of Europe. We performed a Life Cycle Analysis (LCA) adapting the BEAT2 model specifically focusing on the GHG balance of the supply chain, from the forestry management to the field distribution of the resulting biochar. The results indicated that the gasification stage had the highest impact in the supply chain in terms of emissions, but net emissions allocated to biochar were always negative (ranging between −0.54 and −2.1 t CO2e t−1 biochar), hypothesizing two scenarios of 32% and 7.3% biochar mineralization rate in soil, over a time period of 100 years. Finally, biochar had a marginal but positive effect on rice yield, thus increasing the sustainability of this energy‐biochar chain.

Fate of Soil Organic Carbon and Polycyclic Aromatic Hydrocarbons in a Vineyard Soil Treated with Biochar

The effect of biochar addition on the levels of black carbon (BC) and polcyclic aromatic hydrocarbons (PAHs) in a vineyard soil in central Italy was investigated within a two year period. Hydropyrolysis (HyPy) was used to determine the contents of BC (BCHyPy) in the amended and control soils, while the hydrocarbon composition of the semi-labile (non-BCHyPy) fraction released by HyPy was determined by gas chromatography-mass spectrometry, together with the solvent-extractable PAHs. The concentrations of these three polycyclic aromatic carbon reservoirs changed and impacted differently the soil organic carbon over the period of the trial. The addition of biochar (33 ton dry biochar ha(-1)) gave rise to a sharp increase in soil organic carbon, which could be accounted for by an increase in BCHyPy. Over time, the concentration of BCHyPy decreased significantly from 36 to 23 mg g(-1) and as a carbon percentage from 79% to 61%. No clear time trends were observed for the non-BCHyPy PAHs varying from 39 to 34 μg g(-1) in treated soils, not significantly different from control soils. However, the concentrations of extractable PAHs increased markedly in the amended soils and decreased with time from 153 to 78 ng g(-1) remaining always higher than those in untreated soil. The extent of the BCHyPy loss was more compatible with physical rather than chemical processes.

Monitoring water stress in Mediterranean semi-natural vegetation with satellite and meteorological data

Abstract In arid and semi-arid environments, the characterization of the inter-annual variations of the light use efficiency ɛ due to water stress still relies mostly on meteorological data. Thus the GPP estimation based on procedures exclusively driven by remote sensing data has not found yet a widespread use. In this work, the potential to characterize the water stress in semi-natural vegetation of three spectral indices (NDWI, SIWSI and NDI7) – from MODIS broad spectral bands – has been analyzed in comparison to a meteorological factor (Cws). The study comprises 70 sites (belonging to 7 different ecosystems) uniformly distributed over Tuscany, and three eddy covariance tower sites. An operational methodology, which combines meteorological and MODIS data, to characterize the inter-annual variations of ɛ due to summer water stress is proposed. Its main advantage is that it relies on existing series of meteorological data characterizing each site and allows calculating a typical Cws profile that can be “updated” ( C w s * ) for the actual conditions using MODIS spectral indices. The results confirm that the modified C w s * can be used as a proxy of water stress that does not require concurrent information on meteorological data.

Comparing integrated stable isotope and eddy covariance estimates of water-use efficiency on a Mediterranean successional sequence

Water-use efficiency (WUE), thought to be a relevant trait for productivity and adaptation to water-limited environments, was estimated for three different ecosystems on the Mediterranean island of Pianosa: Mediterranean macchia (SMM), transition (STR) and abandoned agricultural (SAA) ecosystems, representing a successional series. Three independent approaches were used to study WUE: eddy covariance measurements, C isotope composition of ecosystem respired CO2, and C isotope discrimination (Δ) of leaf material (dry matter and soluble sugars). Seasonal variations in C–water relations and energy fluxes, compared in SMM and in SAA, were primarily dependent on the specific composition of each plant community. WUE of gross primary productivity was higher in SMM than in SAA at the beginning of the dry season. Both structural and fast-turnover leaf material were, on average, more enriched in 13C in SMM than SAA, indicating relatively higher stomatal control and WUE for the long-lived macchia species. This pattern corresponded to 13C-enriched respired CO2 in SMM compared to the other ecosystems. Conversely, most of the annual herbaceous SAA species (terophytes) showed a drought-escaping strategy, with relatively high stomatal conductance and low WUE. An ecosystem-integrated Δ value was weighted for each ecosystem on the abundance of different life forms, classified according to Raunkiar’s system. Agreement was found between ecosystem WUE calculated using eddy covariance and those estimated using integrated Δ approaches. Comparing the isotopic methods, Δ of leaf soluble sugars provided the most reliable proxy for short-term changes in photosynthetic discrimination and associated shifts in integrated canopy-level WUE along the successional series.