Temperature extremes of 2022 reduced carbon uptake by forests in Europe.

The year 2022 saw record breaking temperatures in Europe during both summer and fall. Similar to the recent 2018 drought, close to 30% (3.0 million km2) of the European continent was under severe summer drought. In 2022, the drought was located in central and southeastern Europe, contrasting the Northern-centered 2018 drought. We show, using multiple sets of observations, a reduction of net biospheric carbon uptake in summer (56-62 TgC) over the drought area. Specific sites in France even showed a widespread summertime carbon release by forests, additional to wildfires. Partial compensation (32%) for the decreased carbon uptake due to drought was offered by a warm autumn with prolonged biospheric carbon uptake. The severity of this second drought event in 5 years suggests drought-induced reduced carbon uptake to no longer be exceptional, and important to factor into Europe's developing plans for net-zero greenhouse gas emissions that rely on carbon uptake by forests.

In-situ start and end of growing season dates of major European crop types from France and Bulgaria at a field level.

Crop phenology data offer crucial information for crop yield estimation, agricultural management, and assessment of agroecosystems. Such information becomes more important in the context of increasing year-to-year climatic variability. The dataset provides in-situ crop phenology data (first leaves emergence and harvest date) of major European crops (wheat, corn, sunflower, rapeseed) from seventeen field study sites in Bulgaria and two in France. Additional information such as the sowing date, area of each site, coordinates, method and equipment used for phenophase data estimation, and photos of the France sites are also provided. The georeferenced ground-truth dataset provides a solid base for a better understanding of crop growth and can be used to validate the retrieval of phenological stages from remote sensing data.

Exploring the potential of Δ17O in CO2 for determining mesophyll conductance.

Mesophyll conductance to CO2 from the intercellular air space to the CO2-H2O exchange site has been estimated using δ18O measurements (gm18). However, the gm18 estimates are affected by the uncertainties in the δ18O of leaf water where the CO2-H2O exchange takes place and the degree of equilibration between CO2 and H2O. We show that measurements of Δ17O (i.e.Δ17O=δ17O-0.528×δ18O) can provide independent constraints on gm (gmΔ17) and that these gm estimates are less affected by fractionation processes during gas exchange. The gm calculations are applied to combined measurements of δ18O and Δ17O, and gas exchange in two C3 species, sunflower (Helianthus annuus L. cv. 'sunny') and ivy (Hedera hibernica L.), and the C4 species maize (Zea mays). The gm18 and gmΔ17 estimates agree within the combined errors (P-value, 0.876). Both approaches are associated with large errors when the isotopic composition in the intercellular air space becomes close to the CO2-H2O exchange site. Although variations in Δ17O are low, it can be measured with much higher precision compared with δ18O. Measuring gmΔ17 has a few advantages compared with gm18: (i) it is less sensitive to uncertainty in the isotopic composition of leaf water at the isotope exchange site and (ii) the relative change in the gm due to an assumed error in the equilibration fraction θeq is lower for gmΔ17 compared with gm18. Thus, using Δ17O can complement and improve the gm estimates in settings where the δ18O of leaf water varies strongly, affecting the δ18O (CO2) difference between the intercellular air space and the CO2-H2O exchange site.

Multi-sensor spectral synergies for crop stress detection and monitoring in the optical domain: A review.

Remote detection and monitoring of the vegetation responses to stress became relevant for sustainable agriculture. Ongoing developments in optical remote sensing technologies have provided tools to increase our understanding of stress-related physiological processes. Therefore, this study aimed to provide an overview of the main spectral technologies and retrieval approaches for detecting crop stress in agriculture. Firstly, we present integrated views on: i) biotic and abiotic stress factors, the phases of stress, and respective plant responses, and ii) the affected traits, appropriate spectral domains and corresponding methods for measuring traits remotely. Secondly, representative results of a systematic literature analysis are highlighted, identifying the current status and possible future trends in stress detection and monitoring. Distinct plant responses occurring under shortterm, medium-term or severe chronic stress exposure can be captured with remote sensing due to specific light interaction processes, such as absorption and scattering manifested in the reflected radiance, i.e. visible (VIS), near infrared (NIR), shortwave infrared, and emitted radiance, i.e. solar-induced fluorescence and thermal infrared (TIR). From the analysis of 96 research papers, the following trends can be observed: increasing usage of satellite and unmanned aerial vehicle data in parallel with a shift in methods from simpler parametric approaches towards more advanced physically-based and hybrid models. Most study designs were largely driven by sensor availability and practical economic reasons, leading to the common usage of VIS-NIR-TIR sensor combinations. The majority of reviewed studies compared stress proxies calculated from single-source sensor domains rather than using data in a synergistic way. We identified new ways forward as guidance for improved synergistic usage of spectral domains for stress detection: (1) combined acquisition of data from multiple sensors for analysing multiple stress responses simultaneously (holistic view); (2) simultaneous retrieval of plant traits combining multi-domain radiative transfer models and machine learning methods; (3) assimilation of estimated plant traits from distinct spectral domains into integrated crop growth models. As a future outlook, we recommend combining multiple remote sensing data streams into crop model assimilation schemes to build up Digital Twins of agroecosystems, which may provide the most efficient way to detect the diversity of environmental and biotic stresses and thus enable respective management decisions.

The CO2 record at the Amazon Tall Tower Observatory: A new opportunity to study processes on seasonal and inter-annual scales.

High-quality atmospheric CO2  measurements are sparse in Amazonia, but can provide critical insights into the spatial and temporal variability of sources and sinks of CO2 . In this study, we present the first 6 years (2014-2019) of continuous, high-precision measurements of atmospheric CO2 at the Amazon Tall Tower Observatory (ATTO, 2.1°S, 58.9°W). After subtracting the simulated background concentrations from our observational record, we define a CO2 regional signal ( ΔCO2obs ) that has a marked seasonal cycle with an amplitude of about 4 ppm. At both seasonal and inter-annual scales, we find differences in phase between ΔCO2obs and the local eddy covariance net ecosystem exchange (EC-NEE), which is interpreted as an indicator of a decoupling between local and non-local drivers of ΔCO2obs . In addition, we present how the 2015-2016 El Niño-induced drought was captured by our atmospheric record as a positive 2σ anomaly in both the wet and dry season of 2016. Furthermore, we analyzed the observed seasonal cycle and inter-annual variability of ΔCO2obs together with net ecosystem exchange (NEE) using a suite of modeled flux products representing biospheric and aquatic CO2 exchange. We use both non-optimized and optimized (i.e., resulting from atmospheric inverse modeling) NEE fluxes as input in an atmospheric transport model (STILT). The observed shape and amplitude of the seasonal cycle was captured neither by the simulations using the optimized fluxes nor by those using the diagnostic Vegetation and Photosynthesis Respiration Model (VPRM). We show that including the contribution of CO2 from river evasion improves the simulated shape (not the magnitude) of the seasonal cycle when using a data-driven non-optimized NEE product (FLUXCOM). The simulated contribution from river evasion was found to be 25% of the seasonal cycle amplitude. Our study demonstrates the importance of the ATTO record to better understand the Amazon carbon cycle at various spatial and temporal scales.

Leaf scale quantification of the effect of photosynthetic gas exchange on Δ47 of CO2.

The clumped isotope composition (Δ47, the anomaly of the mass 47 isotopologue relative to the abundance expected from a random isotope distribution) of CO2 has been suggested as an additional tracer for gross CO2 fluxes. However, the effect of photosynthetic gas exchange on Δ47 has not been directly determined and two indirect/conceptual studies reported contradicting results. In this study, we quantify the effect of photosynthetic gas exchange on Δ47 of CO2 using leaf cuvette experiments with one C4 and two C3 plants. The experimental results are supported by calculations with a leaf cuvette model. Our results demonstrate the important roles of the Δ47 value of CO2 entering the leaf, kinetic fractionation as CO2 diffuses into, and out of the leaf and CO2-H2O isotope exchange with leaf water. We experimentally confirm the previously suggested dependence of Δ47 of CO2 in the air surrounding a leaf on the stomatal conductance and back-diffusion flux. Gas exchange can enrich or deplete the Δ47 of CO2 depending on the Δ47 of CO2 entering the leaf and the fraction of CO2 exchanged with leaf water and diffused back to the atmosphere, but under typical ambient conditions, it will lead to a decrease in Δ47.

Spring enhancement and summer reduction in carbon uptake during the 2018 drought in northwestern Europe.

We analysed gross primary productivity (GPP), total ecosystem respiration (TER) and the resulting net ecosystem exchange (NEE) of carbon dioxide (CO2) by the terrestrial biosphere during the summer of 2018 through observed changes across the Integrated Carbon Observation System (ICOS) network, through biosphere and inverse modelling, and through remote sensing. Highly correlated yet independently-derived reductions in productivity from sun-induced fluorescence, vegetative near-infrared reflectance, and GPP simulated by the Simple Biosphere model version 4 (SiB4) suggest a 130-340 TgC GPP reduction in July-August-September (JAS) of 2018. This occurs over an area of 1.6 × 106 km2 with anomalously low precipitation in northwestern and central Europe. In this drought-affected area, reduced GPP, TER, NEE and soil moisture at ICOS ecosystem sites are reproduced satisfactorily by the SiB4 model. We found that, in contrast to the preceding 5 years, low soil moisture is the main stress factor across the affected area. SiB4's NEE reduction by 57 TgC for JAS coincides with anomalously high atmospheric CO2 observations in 2018, and this is closely matched by the NEE anomaly derived by CarbonTracker Europe (52 to 83 TgC). Increased NEE during the spring (May-June) of 2018 (SiB4 -52 TgC; CTE -46 to -55 TgC) largely offset this loss, as ecosystems took advantage of favourable growth conditions. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.

Global 3-D Simulations of the Triple Oxygen Isotope Signature Δ17O in Atmospheric CO2.

The triple oxygen isotope signature Δ17O in atmospheric CO2, also known as its "17O excess," has been proposed as a tracer for gross primary production (the gross uptake of CO2 by vegetation through photosynthesis). We present the first global 3-D model simulations for Δ17O in atmospheric CO2 together with a detailed model description and sensitivity analyses. In our 3-D model framework we include the stratospheric source of Δ17O in CO2 and the surface sinks from vegetation, soils, ocean, biomass burning, and fossil fuel combustion. The effect of oxidation of atmospheric CO on Δ17O in CO2 is also included in our model. We estimate that the global mean Δ17O (defined as Δ 17 O = ln ( δ 17 O + 1 ) - λ RL · ln ( δ 18 O + 1 ) with λ RL = 0.5229) of CO2 in the lowest 500 m of the atmosphere is 39.6 per meg, which is ∼20 per meg lower than estimates from existing box models. We compare our model results with a measured stratospheric Δ17O in CO2 profile from Sodankylä (Finland), which shows good agreement. In addition, we compare our model results with tropospheric measurements of Δ17O in CO2 from Göttingen (Germany) and Taipei (Taiwan), which shows some agreement but we also find substantial discrepancies that are subsequently discussed. Finally, we show model results for Zotino (Russia), Mauna Loa (United States), Manaus (Brazil), and South Pole, which we propose as possible locations for future measurements of Δ17O in tropospheric CO2 that can help to further increase our understanding of the global budget of Δ17O in atmospheric CO2.

Determination of the triple oxygen and carbon isotopic composition of CO2 from atomic ion fragments formed in the ion source of the 253 Ultra high-resolution isotope ratio mass spectrometer.

RATIONALE: Determination of δ17 O values directly from CO2 with traditional gas source isotope ratio mass spectrometry is not possible due to isobaric interference of 13 C16 O16 O on 12 C17 O16 O. The methods developed so far use either chemical conversion or isotope equilibration to determine the δ17 O value of CO2 . In addition, δ13 C measurements require correction for the interference from 12 C17 O16 O on 13 C16 O16 O since it is not possible to resolve the two isotopologues. METHODS: We present a technique to determine the δ17 O, δ18 O and δ13 C values of CO2 from the fragment ions that are formed upon electron ionization in the ion source of the Thermo Scientific 253 Ultra high-resolution isotope ratio mass spectrometer (hereafter 253 Ultra). The new technique is compared with the CO2 -O2 exchange method and the 17 O-correction algorithm for δ17 O and δ13 C values, respectively. RESULTS: The scale contractions for δ13 C and δ18 O values are slightly larger for fragment ion measurements than for molecular ion measurements. The δ17 O and Δ17 O values of CO2 can be measured on the 17 O+ fragment with an internal error that is a factor 1-2 above the counting statistics limit. The ultimate precision depends on the signal intensity and on the total time that the 17 O+ beam is monitored; a precision of 14 ppm (parts per million) (standard error of the mean) was achieved in 20 hours at the University of Göttingen. The Δ17 O measurements with the O-fragment method agree with the CO2 -O2 exchange method over a range of Δ17 O values of -0.3 to +0.7‰. CONCLUSIONS: Isotope measurements on atom fragment ions of CO2 can be used as an alternative method to determine the carbon and oxygen isotopic composition of CO2 without chemical processing or corrections for mass interferences.

Widespread reduction in sun-induced fluorescence from the Amazon during the 2015/2016 El Niño.

The tropical carbon balance dominates year-to-year variations in the CO2 exchange with the atmosphere through photosynthesis, respiration and fires. Because of its high correlation with gross primary productivity (GPP), observations of sun-induced fluorescence (SIF) are of great interest. We developed a new remotely sensed SIF product with improved signal-to-noise in the tropics, and use it here to quantify the impact of the 2015/2016 El Niño Amazon drought. We find that SIF was strongly suppressed over areas with anomalously high temperatures and decreased levels of water in the soil. SIF went below its climatological range starting from the end of the 2015 dry season (October) and returned to normal levels by February 2016 when atmospheric conditions returned to normal, but well before the end of anomalously low precipitation that persisted through June 2016. Impacts were not uniform across the Amazon basin, with the eastern part experiencing much larger (10-15%) SIF reductions than the western part of the basin (2-5%). We estimate the integrated loss of GPP relative to eight previous years to be 0.34-0.48 PgC in the three-month period October-November-December 2015.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.

Changes in surface hydrology, soil moisture and gross primary production in the Amazon during the 2015/2016 El Niño.

The 2015/2016 El Niño event caused severe changes in precipitation across the tropics. This impacted surface hydrology, such as river run-off and soil moisture availability, thereby triggering reductions in gross primary production (GPP). Many biosphere models lack the detailed hydrological component required to accurately quantify anomalies in surface hydrology and GPP during droughts in tropical regions. Here, we take the novel approach of coupling the biosphere model SiBCASA with the advanced hydrological model PCR-GLOBWB to attempt such a quantification across the Amazon basin during the drought in 2015/2016. We calculate 30-40% reduced river discharge in the Amazon starting in October 2015, lagging behind the precipitation anomaly by approximately one month and in good agreement with river gauge observations. Soil moisture shows distinctly asymmetrical spatial anomalies with large reductions across the north-eastern part of the basin, which persisted into the following dry season. This added to drought stress in vegetation, already present owing to vapour pressure deficits at the leaf, resulting in a loss of GPP of 0.95 (0.69 to 1.20) PgC between October 2015 and March 2016 compared with the 2007-2014 average. Only 11% (10-12%) of the reduction in GPP was found in the (wetter) north-western part of the basin, whereas the north-eastern and southern regions were affected more strongly, with 56% (54-56%) and 33% (31-33%) of the total, respectively. Uncertainty on this anomaly mostly reflects the unknown rooting depths of vegetation.This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Niño on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.