Publications by authors named "Nicolas Vuichard"

Effective nitrogen fertilizer management is crucial for reducing nitrous oxide (NO) emissions while ensuring food security within planetary boundaries. However, climate change might also interact with management practices to alter NO emission and emission factors (EFs), adding further uncertainties to estimating mitigation potentials. Here, we developed a new hybrid modeling framework that integrates a machine learning model with an ensemble of eight process-based models to project EFs under different climate and nitrogen policy scenarios.

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Article Synopsis
  • * The study reveals that in 2019, Nr had a net cooling effect on the climate due to factors like increased aerosol loading, which outweighs the warming effects from greenhouse gases like nitrous oxide and ozone.
  • * Future scenarios suggest that while Nr's cooling effect may weaken, warming will likely persist, emphasizing the need to reduce both Nr and greenhouse gas emissions to meet climate goals set by the Paris Agreement.
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Future socioeconomic climate pathways have regional water-quality consequences whose severity and equity have not yet been fully understood across geographic and economic spectra. We use a process-based, terrestrial-freshwater ecosystem model to project 21st-century river nitrogen loads under these pathways. We find that fertilizer usage is the primary determinant of future river nitrogen loads, changing precipitation and warming have limited impacts, and CO fertilization-induced vegetation growth enhancement leads to modest load reductions.

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The observed global net land carbon sink is captured by current land models. All models agree that atmospheric CO and nitrogen deposition driven gains in carbon stocks are partially offset by climate and land-use and land-cover change (LULCC) losses. However, there is a lack of consensus in the partitioning of the sink between vegetation and soil, where models do not even agree on the direction of change in carbon stocks over the past 60 years.

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Our study suggests that the global CO fertilization effect (CFE) on vegetation photosynthesis has declined during the past four decades. The Comments suggest that the temporal inconsistency in AVHRR data and the attribution method undermine the results’ robustness. Here, we provide additional evidence that these arguments did not affect our finding and that the global decline in CFE is robust.

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Variability in climate exerts a strong influence on vegetation productivity (gross primary productivity; GPP), and therefore has a large impact on the land carbon sink. However, no direct observations of global GPP exist, and estimates rely on models that are constrained by observations at various spatial and temporal scales. Here, we assess the consistency in GPP from global products which extend for more than three decades; two observation-based approaches, the upscaling of FLUXNET site observations (FLUXCOM) and a remote sensing derived light use efficiency model (RS-LUE), and from a suite of terrestrial biosphere models (TRENDYv6).

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The enhanced vegetation productivity driven by increased concentrations of carbon dioxide (CO) [i.e., the CO fertilization effect (CFE)] sustains an important negative feedback on climate warming, but the temporal dynamics of CFE remain unclear.

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Nitrous oxide (NO), like carbon dioxide, is a long-lived greenhouse gas that accumulates in the atmosphere. Over the past 150 years, increasing atmospheric NO concentrations have contributed to stratospheric ozone depletion and climate change, with the current rate of increase estimated at 2 per cent per decade. Existing national inventories do not provide a full picture of NO emissions, owing to their omission of natural sources and limitations in methodology for attributing anthropogenic sources.

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Article Synopsis
  • - The FLUXNET2015 dataset encompasses ecosystem-scale data on carbon dioxide, water, and energy exchange, collected from 212 global sites contributing over 1500 site-years of data until 2014.
  • - The dataset was systematically quality controlled and processed, facilitating consistency for various applications in ecophysiology, remote sensing, and ecosystem modeling.
  • - For the first time, derived data products such as time series, ecosystem respiration, and photosynthesis estimates are included, and 206 sites are made accessible under a Creative Commons license, with the processing methods available as open-source codes.
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Gaps in our current understanding and quantification of biomass carbon stocks, particularly in tropics, lead to large uncertainty in future projections of the terrestrial carbon balance. We use the recently published GlobBiomass data set of forest above-ground biomass (AGB) density for the year 2010, obtained from multiple remote sensing and in situ observations at 100 m spatial resolution to evaluate AGB estimated by nine dynamic global vegetation models (DGVMs). The global total forest AGB of the nine DGVMs is 365 ± 66 Pg C, the spread corresponding to the standard deviation between models, compared to 275 Pg C with an uncertainty of ~13.

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Article Synopsis
  • The seasonal changes in carbon dioxide levels in the northern hemisphere are changing, with Mauna Loa being a key location for measuring these levels.
  • Before the 1980s, the amount of carbon dioxide in the air increased during different seasons, but this change has slowed down since then.
  • This slowdown is mainly due to the effects of climate change, like droughts, which counteract the growth of plants that usually absorb more carbon dioxide.
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Understanding changes in terrestrial carbon balance is important to improve our knowledge of the regional carbon cycle and climate change. However, evaluating regional changes in the terrestrial carbon balance is challenging due to the lack of surface flux measurements. This study reveals that the terrestrial carbon uptake over the Republic of Korea has been enhanced from 1999 to 2017 by analyzing long-term atmospheric CO concentration measurements at the Anmyeondo Station (36.

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Our understanding and quantification of global soil nitrous oxide (N O) emissions and the underlying processes remain largely uncertain. Here, we assessed the effects of multiple anthropogenic and natural factors, including nitrogen fertilizer (N) application, atmospheric N deposition, manure N application, land cover change, climate change, and rising atmospheric CO concentration, on global soil N O emissions for the period 1861-2016 using a standard simulation protocol with seven process-based terrestrial biosphere models. Results suggest global soil N O emissions have increased from 6.

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Evaluating the response of the land carbon sink to the anomalies in temperature and drought imposed by El Niño events provides insights into the present-day carbon cycle and its climate-driven variability. It is also a necessary step to build confidence in terrestrial ecosystems models' response to the warming and drying stresses expected in the future over many continents, and particularly in the tropics. Here we present an in-depth analysis of the response of the terrestrial carbon cycle to the 2015/2016 El Niño that imposed extreme warming and dry conditions in the tropics and other sensitive regions.

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Spatial patterns and temporal trends of nitrogen (N) and phosphorus (P) deposition are important for quantifying their impact on forest carbon (C) uptake. In a first step, we modeled historical and future change in the global distributions of the atmospheric deposition of N and P from the dry and wet deposition of aerosols and gases containing N and P. Future projections were compared between two scenarios with contrasting aerosol emissions.

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The PALS Land sUrface Model Benchmarking Evaluation pRoject (PLUMBER) illustrated the value of prescribing performance targets in model intercomparisons. It showed that the performance of turbulent energy flux predictions from different land surface models, at a broad range of flux tower sites using common evaluation metrics, was on average worse than relatively simple empirical models. For sensible heat fluxes, all land surface models were outperformed by a linear regression against downward shortwave radiation.

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Several lines of evidence point to European managed grassland ecosystems being a sink of carbon. In this study, we apply ORCHIDEE-GM a process-based carbon cycle model that describes specific management practices of pastures and the dynamics of carbon cycling in response to changes in climatic and biogeochemical drivers. The model is used to simulate changes in the carbon balance [i.

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The greenhouse gas (GHG) balance of European grasslands (EU-28 plus Norway and Switzerland), including CO2 , CH4 and N2 O, is estimated using the new process-based biogeochemical model ORCHIDEE-GM over the period 1961-2010. The model includes the following: (1) a mechanistic representation of the spatial distribution of management practice; (2) management intensity, going from intensively to extensively managed; (3) gridded simulation of the carbon balance at ecosystem and farm scale; and (4) gridded simulation of N2 O and CH4 emissions by fertilized grassland soils and livestock. The external drivers of the model are changing animal numbers, nitrogen fertilization and deposition, land-use change, and variable CO2 and climate.

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About 25% of European livestock intake is based on permanent and sown grasslands. To fulfill rising demand for animal products, an intensification of livestock production may lead to an increased consumption of crop and compound feeds. In order to preserve an economically and environmentally sustainable agriculture, a more forage based livestock alimentation may be an advantage.

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Future climate change and increasing atmospheric CO2 are expected to cause major changes in vegetation structure and function over large fractions of the global land surface. Seven global vegetation models are used to analyze possible responses to future climate simulated by a range of general circulation models run under all four representative concentration pathway scenarios of changing concentrations of greenhouse gases. All 110 simulations predict an increase in global vegetation carbon to 2100, but with substantial variation between vegetation models.

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Although the CO(2) mitigation potential of biofuels has been studied by extrapolation of small-scale studies, few estimates exist of the net regional-scale carbon balance implications of biofuel cultivations programs, either growing conventional biofuel crops or applying new advanced technologies. Here we used a spatially distributed process-driven model over the 20 Mha of recently abandoned agricultural lands of the Former Soviet Union to quantify the GHG mitigation by biofuel production from Low Input/High Diversity (LIHD) grass-legume prairies and to compare this GHG mitigation with the one of soil C sequestration as it currently occurs. LIHD has recently received a lot of attention as an emerging opportunity to produce biofuels over marginal lands leading to a good energy efficiency with minimal adverse consequences on food security and ecosystem services.

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