Author
Francesco Primo Vaccari
Other affiliations: Max Planck Society
Bio: Francesco Primo Vaccari is an academic researcher from National Research Council. The author has contributed to research in topics: Biochar & Eddy covariance. The author has an hindex of 32, co-authored 82 publications receiving 7826 citations. Previous affiliations of Francesco Primo Vaccari include Max Planck Society.
Topics: Biochar, Eddy covariance, Soil water, Soil fertility, Soil carbon
Papers published on a yearly basis
Papers
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Potsdam Institute for Climate Impact Research1, University of Bayreuth2, University of California, Berkeley3, Institut national de la recherche agronomique4, Dresden University of Technology5, ETH Zurich6, Max Planck Society7, South Dakota State University8, Academy of Sciences of the Czech Republic9, Finnish Forest Research Institute10, Finnish Meteorological Institute11, Oak Ridge National Laboratory12, Centre national de la recherche scientifique13, University of Helsinki14, Weizmann Institute of Science15
TL;DR: In this paper, the authors analyse the effect of extrapolation of night-time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long-term data sets.
Abstract: This paper discusses the advantages and disadvantages of the different methods that separate net ecosystem exchange (NEE) into its major components, gross ecosystem carbon uptake (GEP) and ecosystem respiration (Reco). In particular, we analyse the effect of the extrapolation of night-time values of ecosystem respiration into the daytime; this is usually done with a temperature response function that is derived from long-term data sets. For this analysis, we used 16 one-year-long data sets of carbon dioxide exchange measurements from European and US-American eddy covariance networks. These sites span from the boreal to Mediterranean climates, and include deciduous and evergreen forest, scrubland and crop ecosystems. We show that the temperature sensitivity of Reco, derived from long-term (annual) data sets, does not reflect the short-term temperature sensitivity that is effective when extrapolating from night- to daytime. Specifically, in summer active ecosystems the long
2,881 citations
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Max Planck Society1, Laval University2, Harvard University3, McMaster University4, Lund University5, Karlsruhe Institute of Technology6, Dresden University of Technology7, Institut national de la recherche agronomique8, University of Toledo9, University College Cork10, Oregon State University11, ETH Zurich12, Free University of Bozen-Bolzano13, United States Forest Service14, Wageningen University and Research Centre15, National Research Council16, Clark University17
TL;DR: In this paper, the authors upscaled FLUXNET observations of carbon dioxide, water, and energy fluxes to the global scale using the machine learning technique, model tree ensembles (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.
Abstract: 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.
927 citations
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TL;DR: This work compares NDVI surveys performed with UAV, aircraft and satellite, to assess the capability of each platform to represent the intra-vineyard vegetation spatial variability and results indicate that the different platforms provide comparable results in vineyards characterized by coarse vegetation gradients and large vegetation clusters.
Abstract: 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.
464 citations
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Montana State University1, Karlsruhe Institute of Technology2, University of Bayreuth3, Roskilde University4, Technical University of Denmark5, McMaster University6, Lund University7, Finnish Meteorological Institute8, Dresden University of Technology9, National Research Council10, CSIRO Marine and Atmospheric Research11, University College Cork12, University of Göttingen13, Laval University14, Queen's University15, ETH Zurich16, Free University of Bozen-Bolzano17, Tuscia University18, Max Planck Society19, University College Dublin20, Spanish National Research Council21, University of Sassari22, Russian Academy of Sciences23
TL;DR: In this article, the authors explored the relationship between energy balance closure and landscape heterogeneity using MODIS products and GLOBEstat elevation data and found that landscape-level heterogeneity in vegetation and topography cannot be ignored as a contributor to incomplete energy balance closures at the surface-atmosphere exchange measurements.
416 citations
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TL;DR: In this paper, a large volume application of Biochar (30 and 60 t −1 ) on durum wheat in the Mediterranean climate condition, showing the viability of BC application for carbon sequestration on this crop.
386 citations
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TL;DR: An increase in future drought events could turn temperate ecosystems into carbon sources, contributing to positive carbon-climate feedbacks already anticipated in the tropics and at high latitudes.
Abstract: Future climate warming is expected to enhance plant growth in temperate ecosystems and to increase carbon sequestration. But although severe regional heatwaves may become more frequent in a changing climate their impact on terrestrial carbon cycling is unclear. Here we report measurements of ecosystem carbon dioxide fluxes, remotely sensed radiation absorbed by plants, and country-level crop yields taken during the European heatwave in 2003.We use a terrestrial biosphere simulation model to assess continental-scale changes in primary productivity during 2003, and their consequences for the net carbon balance. We estimate a 30 per cent reduction in gross primary productivity over Europe, which resulted in a strong anomalous net source of carbon dioxide (0.5 Pg Cyr21) to the atmosphere and reversed the effect of four years of net ecosystem carbon sequestration. Our results suggest that productivity reduction in eastern and western Europe can be explained by rainfall deficit and extreme summer heat, respectively. We also find that ecosystem respiration decreased together with gross primary productivity, rather than accelerating with the temperature rise. Model results, corroborated by historical records of crop yields, suggest that such a reduction in Europe's primary productivity is unprecedented during the last century. An increase in future drought events could turn temperate ecosystems into carbon sources, contributing to positive carbon-climate feedbacks already anticipated in the tropics and at high latitudes.
3,408 citations
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TL;DR: The results from this review may provide the most plausible estimates of how plants in their native environments and field-grown crops will respond to rising atmospheric [CO(2)]; but even with FACE there are limitations, which are discussed.
Abstract: Contents
Summary 1
I. What is FACE? 2
II. Materials and methods 2
III. Photosynthetic carbon uptake 3
IV. Acclimation of photosynthesis 6
V. Growth, above-ground production and yield 8
VI. So, what have we learned? 10
Acknowledgements 11
References 11
Appendix 1. References included in the database for meta-analyses 14
Appendix 2. Results of the meta-analysis of FACE effects 18
Summary
Free-air CO2 enrichment (FACE) experiments allow study of the effects of elevated [CO2] on plants and ecosystems grown under natural conditions without enclosure. Data from 120 primary, peer-reviewed articles describing physiology and production in the 12 large-scale FACE experiments (475–600 ppm) were collected and summarized using meta-analytic techniques. The results confirm some results from previous chamber experiments: light-saturated carbon uptake, diurnal C assimilation, growth and above-ground production increased, while specific leaf area and stomatal conductance decreased in elevated [CO2]. There were differences in FACE. Trees were more responsive than herbaceous species to elevated [CO2]. Grain crop yields increased far less than anticipated from prior enclosure studies. The broad direction of change in photosynthesis and production in elevated [CO2] may be similar in FACE and enclosure studies, but there are major quantitative differences: trees were more responsive than other functional types; C4 species showed little response; and the reduction in plant nitrogen was small and largely accounted for by decreased Rubisco. The results from this review may provide the most plausible estimates of how plants in their native environments and field-grown crops will respond to rising atmospheric [CO2]; but even with FACE there are limitations, which are also discussed.
3,140 citations
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TL;DR: It is argued that contextual cues should be used as part of deep learning to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales.
Abstract: Machine learning approaches are increasingly used to extract patterns and insights from the ever-increasing stream of geospatial data, but current approaches may not be optimal when system behaviour is dominated by spatial or temporal context. Here, rather than amending classical machine learning, we argue that these contextual cues should be used as part of deep learning (an approach that is able to extract spatio-temporal features automatically) to gain further process understanding of Earth system science problems, improving the predictive ability of seasonal forecasting and modelling of long-range spatial connections across multiple timescales, for example. The next step will be a hybrid modelling approach, coupling physical process models with the versatility of data-driven machine learning.
2,014 citations
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TL;DR: Improved understanding of the molecular and biochemical mechanisms by which plants respond to elevated [CO2], and the feedback of environmental factors upon them, will improve the ability to predict ecosystem responses to rising [ CO2] and increase the potential to adapt crops and managed ecosystems to future atmospheric [CO 2].
Abstract: This review summarizes current understanding of the mechanisms that underlie the response of photosynthesis and stomatal conductance to elevated carbon dioxide concentration ([CO2]), and examines how downstream processes and environmental constraints modulate these two fundamental responses. The results from free-air CO2 enrichment (FACE) experiments were summarized via meta-analysis to quantify the mean responses of stomatal and photosynthetic parameters to elevated [CO2]. Elevation of [CO2] in FACE experiments reduced stomatal conductance by 22%, yet, this reduction was not associated with a similar change in stomatal density. Elevated [CO2] stimulated light-saturated photosynthesis (Asat) in C3 plants grown in FACE by an average of 31%. However, the magnitude of the increase in Asat varied with functional group and environment. Functional groups with ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco)-limited photosynthesis at elevated [CO2] had greater potential for increases in Asat than those where photosynthesis became ribulose-1,5-bisphosphate (RubP)-limited at elevated [CO2]. Both nitrogen supply and sink capacity modulated the response of photosynthesis to elevated [CO2] through their impact on the acclimation of carboxylation capacity. Increased understanding of the molecular and biochemical mechanisms by which plants respond to elevated [CO2], and the feedback of environmental factors upon them, will improve our ability to predict ecosystem responses to rising [CO2] and increase our potential to adapt crops and managed ecosystems to future atmospheric [CO2].
1,836 citations
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TL;DR: In this article, the authors identify ten contrasting perspectives that shape the vulnerability debate but have not been discussed collectively and present a set of global vulnerability drivers that are known with high confidence: (1) droughts eventually occur everywhere; (2) warming produces hotter Droughts; (3) atmospheric moisture demand increases nonlinearly with temperature during drought; (4) mortality can occur faster in hotter Drought, consistent with fundamental physiology; (5) shorter Drought can become lethal under warming, increasing the frequency of lethal Drought; and (6) mortality happens rapidly
Abstract: Patterns, mechanisms, projections, and consequences of tree mortality and associated broad-scale forest die-off due to drought accompanied by warmer temperatures—“hotter drought”, an emerging characteristic of the Anthropocene—are the focus of rapidly expanding literature. Despite recent observational, experimental, and modeling studies suggesting increased vulnerability of trees to hotter drought and associated pests and pathogens, substantial debate remains among research, management and policy-making communities regarding future tree mortality risks. We summarize key mortality-relevant findings, differentiating between those implying lesser versus greater levels of vulnerability. Evidence suggesting lesser vulnerability includes forest benefits of elevated [CO2] and increased water-use efficiency; observed and modeled increases in forest growth and canopy greening; widespread increases in woody-plant biomass, density, and extent; compensatory physiological, morphological, and genetic mechanisms; dampening ecological feedbacks; and potential mitigation by forest management. In contrast, recent studies document more rapid mortality under hotter drought due to negative tree physiological responses and accelerated biotic attacks. Additional evidence suggesting greater vulnerability includes rising background mortality rates; projected increases in drought frequency, intensity, and duration; limitations of vegetation models such as inadequately represented mortality processes; warming feedbacks from die-off; and wildfire synergies. Grouping these findings we identify ten contrasting perspectives that shape the vulnerability debate but have not been discussed collectively. We also present a set of global vulnerability drivers that are known with high confidence: (1) droughts eventually occur everywhere; (2) warming produces hotter droughts; (3) atmospheric moisture demand increases nonlinearly with temperature during drought; (4) mortality can occur faster in hotter drought, consistent with fundamental physiology; (5) shorter droughts occur more frequently than longer droughts and can become lethal under warming, increasing the frequency of lethal drought nonlinearly; and (6) mortality happens rapidly relative to growth intervals needed for forest recovery. These high-confidence drivers, in concert with research supporting greater vulnerability perspectives, support an overall viewpoint of greater forest vulnerability globally. We surmise that mortality vulnerability is being discounted in part due to difficulties in predicting threshold responses to extreme climate events. Given the profound ecological and societal implications of underestimating global vulnerability to hotter drought, we highlight urgent challenges for research, management, and policy-making communities.
1,786 citations