Showing papers in "Biogeosciences in 2022"

A seamless ensemble-based reconstruction of surface ocean <i>p</i>CO<sub>2</sub> and air–sea CO<sub>2</sub> fluxes over the global coastal and open oceans

Abstract: Abstract. We have estimated global air–sea CO2 fluxes (fgCO2) from the open ocean to coastal seas. Fluxes and associated uncertainty are computed from an ensemble-based reconstruction of CO2 sea surface partial pressure (pCO2) maps trained with gridded data from the Surface Ocean CO2 Atlas v2020 database. The ensemble mean (which is the best estimate provided by the approach) fits independent data well, and a broad agreement between the spatial distribution of model–data differences and the ensemble standard deviation (which is our model uncertainty estimate) is seen. Ensemble-based uncertainty estimates are denoted by ±1σ. The space–time-varying uncertainty fields identify oceanic regions where improvements in data reconstruction and extensions of the observational network are needed. Poor reconstructions of pCO2 are primarily found over the coasts and/or in regions with sparse observations, while fgCO2 estimates with the largest uncertainty are observed over the open Southern Ocean (44∘ S southward), the subpolar regions, the Indian Ocean gyre, and upwelling systems. Our estimate of the global net sink for the period 1985–2019 is 1.643±0.125 PgC yr−1 including 0.150±0.010 PgC yr−1 for the coastal net sink. Among the ocean basins, the Subtropical Pacific (18–49∘ N) and the Subpolar Atlantic (49–76∘ N) appear to be the strongest CO2 sinks for the open ocean and the coastal ocean, respectively. Based on mean flux density per unit area, the most intense CO2 drawdown is, however, observed over the Arctic (76∘ N poleward) followed by the Subpolar Atlantic and Subtropical Pacific for both open-ocean and coastal sectors. Reconstruction results also show significant changes in the global annual integral of all open- and coastal-ocean CO2 fluxes with a growth rate of +0.062±0.006 PgC yr−2 and a temporal standard deviation of 0.526±0.022 PgC yr−1 over the 35-year period. The link between the large interannual to multi-year variations of the global net sink and the El Niño–Southern Oscillation climate variability is reconfirmed.

Representativeness assessment of the pan-Arctic eddy covariance site network and optimized future enhancements

Abstract: Abstract. Large changes in the Arctic carbon balance are expected as warming linked to climate change threatens to destabilize ancient permafrost carbon stocks. The eddy covariance (EC) method is an established technique to quantify net losses and gains of carbon between the biosphere and atmosphere at high spatiotemporal resolution. Over the past decades, a growing network of terrestrial EC tower sites has been established across the Arctic, but a comprehensive assessment of the network's representativeness within the heterogeneous Arctic region is still lacking. This creates additional uncertainties when integrating flux data across sites, for example when upscaling fluxes to constrain pan-Arctic carbon budgets and changes therein. This study provides an inventory of Arctic (here > = 60∘ N) EC sites, which has also been made available online (https://cosima.nceas.ucsb.edu/carbon-flux-sites/, last access: 25 January 2022). Our database currently comprises 120 EC sites, but only 83 are listed as active, and just 25 of these active sites remain operational throughout the winter. To map the representativeness of this EC network, we evaluated the similarity between environmental conditions observed at the tower locations and those within the larger Arctic study domain based on 18 bioclimatic and edaphic variables. This allows us to assess a general level of similarity between ecosystem conditions within the domain, while not necessarily reflecting changes in greenhouse gas flux rates directly. We define two metrics based on this representativeness score: one that measures whether a location is represented by an EC tower with similar characteristics (ER1) and a second for which we assess if a minimum level of representation for statistically rigorous extrapolation is met (ER4). We find that while half of the domain is represented by at least one tower, only a third has enough towers in similar locations to allow reliable extrapolation. When we consider methane measurements or year-round (including wintertime) measurements, the values drop to about 1/5 and 1/10 of the domain, respectively. With the majority of sites located in Fennoscandia and Alaska, these regions were assigned the highest level of network representativeness, while large parts of Siberia and patches of Canada were classified as underrepresented. Across the Arctic, mountainous regions were particularly poorly represented by the current EC observation network. We tested three different strategies to identify new site locations or upgrades of existing sites that optimally enhance the representativeness of the current EC network. While 15 new sites can improve the representativeness of the pan-Arctic network by 20 %, upgrading as few as 10 existing sites to capture methane fluxes or remain active during wintertime can improve their respective ER1 network coverage by 28 % to 33 %. This targeted network improvement could be shown to be clearly superior to an unguided selection of new sites, therefore leading to substantial improvements in network coverage based on relatively small investments.

Modelling submerged biofouled microplastics and their vertical trajectories

Abstract: Abstract. The fate of (micro)plastic particles in the open ocean is controlled by biological and physical processes. Here, we model the effects of biofouling on the subsurface vertical distribution of spherical, virtual plastic particles with radii of 0.01–1 mm. The biological specifications include the attachment, growth and loss of algae on particles. The physical specifications include four vertical velocity terms: advection, wind-driven mixing, tidally induced mixing and the sinking velocity of the biofouled particle. We track 10 000 particles for 1 year in three different regions with distinct biological and physical properties: the low-productivity region of the North Pacific Subtropical Gyre, the high-productivity region of the equatorial Pacific and the high mixing region of the Southern Ocean. The growth of biofilm mass in the euphotic zone and loss of mass below the euphotic zone result in the oscillatory behaviour of particles, where the larger (0.1–1.0 mm) particles have much shorter average oscillation lengths (<10 d; 90th percentile) than the smaller (0.01–0.1 mm) particles (up to 130 d; 90th percentile). A subsurface maximum particle concentration occurs just below the mixed-layer depth (around 30 m) in the equatorial Pacific, which is most pronounced for larger particles (0.1–1.0 mm). This occurs because particles become neutrally buoyant when the processes affecting the settling velocity of a particle and the seawater's vertical movement are in equilibrium. Seasonal effects in the subtropical gyre result in particles sinking below the mixed-layer depth only during spring blooms but otherwise remaining within the mixed layer. The strong winds and deepest average mixed-layer depth in the Southern Ocean (400 m) result in the deepest redistribution of particles (>5000 m). Our results show that the vertical movement of particles is mainly affected by physical (wind-induced mixing) processes within the mixed-layer and biological (biofilm) dynamics below the mixed layer. Furthermore, positively buoyant particles with radii of 0.01–1.0 mm can sink far below the euphotic zone and mixed layer in regions with high near-surface mixing or high biological activity. This work can easily be coupled to other models to simulate open-ocean biofouling dynamics, in order to reach a better understanding of where ocean (micro)plastic ends up.

Global modelling of soil carbonyl sulfide exchanges

Abstract: Abstract. Carbonyl sulfide (COS) is an atmospheric trace gas of interest for C cycle research because COS uptake by continental vegetation is strongly related to terrestrial gross primary productivity (GPP), the largest and most uncertain flux in atmospheric CO2 budgets. However, to use atmospheric COS as an additional tracer of GPP, an accurate quantification of COS exchange by soils is also needed. At present, the atmospheric COS budget is unbalanced globally, with total COS flux estimates from oxic and anoxic soils that vary between −409 and −89 GgS yr−1. This uncertainty hampers the use of atmospheric COS concentrations to constrain GPP estimates through atmospheric transport inversions. In this study we implemented a mechanistic soil COS model in the ORCHIDEE (Organising Carbon and Hydrology In Dynamic Ecosystems) land surface model to simulate COS fluxes in oxic and anoxic soils. Evaluation of the model against flux measurements at seven sites yields a mean root mean square deviation of 1.6 pmol m−2 s−1, instead of 2 pmol m−2 s−1 when using a previous empirical approach that links soil COS uptake to soil heterotrophic respiration. However, soil COS model evaluation is still limited by the scarcity of observation sites and long-term measurement periods, with all sites located in a latitudinal band between 39 and 62∘ N and no observations during wintertime in this study. The new model predicts that, globally and over the 2009–2016 period, oxic soils act as a net uptake of −126 GgS yr−1 and anoxic soils are a source of +96 GgS yr−1, leading to a global net soil sink of only −30 GgS yr−1, i.e. much smaller than previous estimates. The small magnitude of the soil fluxes suggests that the error in the COS budget is dominated by the much larger fluxes from plants, oceans, and industrial activities. The predicted spatial distribution of soil COS fluxes, with large emissions from oxic (up to 68.2 pmol COS m−2 s−1) and anoxic (up to 36.8 pmol COS m−2 s−1) soils in the tropics, especially in India and in the Sahel region, marginally improves the latitudinal gradient of atmospheric COS concentrations, after transport by the LMDZ (Laboratoire de Météorologie Dynamique) atmospheric transport model. The impact of different soil COS flux representations on the latitudinal gradient of the atmospheric COS concentrations is strongest in the Northern Hemisphere. We also implemented spatiotemporal variations in near-ground atmospheric COS concentrations in the modelling of biospheric COS fluxes, which helped reduce the imbalance of the atmospheric COS budget by lowering soil COS uptake by 10 % and plant COS uptake by 8 % globally (with a revised mean vegetation budget of −576 GgS yr−1 over 2009–2016). Sensitivity analyses highlighted the different parameters to which each soil COS flux model is the most responsive, selected in a parameter optimization framework. Having both vegetation and soil COS fluxes modelled within ORCHIDEE opens the way for using observed ecosystem COS fluxes and larger-scale atmospheric COS mixing ratios to improve the simulated GPP, through data assimilation techniques.

Physiological and climate controls on foliar mercury uptake by European tree species

Abstract: Abstract. Despite the importance of vegetation uptake of atmospheric gaseous elemental mercury (Hg(0)) within the global Hg cycle, little knowledge exists on the physiological, climatic, and geographic factors controlling stomatal uptake of atmospheric Hg(0) by tree foliage. We investigate controls on foliar stomatal Hg(0) uptake by combining Hg measurements of 3569 foliage samples across Europe with data on tree species' traits and environmental conditions. To account for foliar Hg accumulation over time, we normalized foliar Hg concentration over the foliar life period from the simulated start of the growing season to sample harvest. The most relevant parameter impacting daily foliar stomatal Hg uptake was tree functional group (deciduous versus coniferous trees). On average, we measured 3.2 times higher daily foliar stomatal Hg uptake rates in deciduous leaves than in coniferous needles of the same age. Across tree species, for foliage of beech and fir, and at two out of three forest plots with more than 20 samples, we found a significant (p<0.001) increase in foliar Hg values with respective leaf nitrogen concentrations. We therefore suggest that foliar stomatal Hg uptake is controlled by tree functional traits with uptake rates increasing from low to high nutrient content representing low to high physiological activity. For pine and spruce needles, we detected a significant linear decrease in daily foliar stomatal Hg uptake with the proportion of time during which water vapor pressure deficit (VPD) exceeded the species-specific threshold values of 1.2 and 3 kPa, respectively. The proportion of time within the growing season during which surface soil water content (ERA5-Land) in the region of forest plots was low correlated negatively with foliar Hg uptake rates of beech and pine. These findings suggest that stomatal uptake of atmospheric Hg(0) is inhibited under high VPD conditions and/or low soil water content due to the regulation of stomatal conductance to reduce water loss under dry conditions. Other parameters associated with forest sampling sites (latitude and altitude), sampled trees (average age and diameter at breast height), or regional satellite-observation-based transpiration product (Global Land Evaporation Amsterdam Model: GLEAM) did not significantly correlate with daily foliar Hg uptake rates. We conclude that tree physiological activity and stomatal response to VPD and soil water content should be implemented in a stomatal Hg model to assess future Hg cycling under different anthropogenic emission scenarios and global warming.

Observation-constrained estimates of the global ocean carbon sink from Earth system models

Abstract: Abstract. The ocean slows global warming by currently taking up around one-quarter of all human-made CO2 emissions. However, estimates of the ocean anthropogenic carbon uptake vary across various observation-based and model-based approaches. Here, we show that the global ocean anthropogenic carbon sink simulated by Earth system models can be constrained by two physical parameters, the present-day sea surface salinity in the subtropical–polar frontal zone in the Southern Ocean and the strength of the Atlantic Meridional Overturning Circulation, and one biogeochemical parameter, the Revelle factor of the global surface ocean. The Revelle factor quantifies the chemical capacity of seawater to take up carbon for a given increase in atmospheric CO2. By exploiting this three-dimensional emergent constraint with observations, we provide a new model- and observation-based estimate of the past, present, and future global ocean anthropogenic carbon sink and show that the ocean carbon sink is 9 %–11 % larger than previously estimated. Furthermore, the constraint reduces uncertainties of the past and present global ocean anthropogenic carbon sink by 42 %–59 % and the future sink by 32 %–62 % depending on the scenario, allowing for a better understanding of the global carbon cycle and better-targeted climate and ocean policies. Our constrained results are in good agreement with the anthropogenic carbon air–sea flux estimates over the last three decades based on observations of the CO2 partial pressure at the ocean surface in the Global Carbon Budget 2021, and they suggest that existing hindcast ocean-only model simulations underestimate the global ocean anthropogenic carbon sink. The key parameters identified here for the ocean anthropogenic carbon sink should be quantified when presenting simulated ocean anthropogenic carbon uptake as in the Global Carbon Budget and be used to adjust these simulated estimates if necessary. The larger ocean carbon sink results in enhanced ocean acidification over the 21st century, which further threatens marine ecosystems by reducing the water volume that is projected to be undersaturated towards aragonite by around 3.7×106–7.4×106 km3 more than originally projected.

Acidification of the Nordic Seas

Abstract: Abstract. Due to low calcium carbonate saturation states, and winter mixing that brings anthropogenic carbon to the deep ocean, the Nordic Seas and their cold-water corals are vulnerable to ocean acidification. Here, we present a detailed investigation of the changes in pH and aragonite saturation in the Nordic Seas from preindustrial times to 2100, by using in situ observations, gridded climatological data, and projections for three different future scenarios with the Norwegian Earth System Model (NorESM1-ME). During the period of regular ocean biogeochemistry observations from 1981–2019, the pH decreased with rates of 2–3 × 10−3 yr−1 in the upper 200 m of the Nordic Seas. In some regions, the pH decrease can be detected down to 2000 m depth. This resulted in a decrease in the aragonite saturation state, which is now close to undersaturation in the depth layer of 1000–2000 m. The model simulations suggest that the pH of the Nordic Seas will decrease at an overall faster rate than the global ocean from the preindustrial era to 2100, bringing the Nordic Seas' pH closer to the global average. In the esmRCP8.5 scenario, the whole water column is projected to be undersaturated with respect to aragonite at the end of the 21st century, thereby endangering all cold-water corals of the Nordic Seas. In the esmRCP4.5 scenario, the deepest cold-water coral reefs are projected to be exposed to undersaturation. Exposure of all cold-water corals to corrosive waters can only be avoided with marginal under the esmRCP2.6 scenario. Over all timescales, the main driver of the pH drop is the increase in dissolved inorganic carbon (CT) caused by the raising anthropogenic CO2, followed by the temperature increase. Thermodynamic salinity effects are of secondary importance. We find substantial changes in total alkalinity (AT) and CT as a result of the salinification, or decreased freshwater content, of the Atlantic water during all time periods, and as a result of an increased freshwater export in polar waters in past and future scenarios. However, the net impact of this decrease (increase) in freshwater content on pH is negligible, as the effects of a concentration (dilution) of CT and AT are canceling.

Evaluation of soil carbon simulation in CMIP6 Earth System Models

Abstract: Abstract. The response of soil carbon represents one of the key uncertainties in future climate change. The ability of Earth System Models (ESMs) to simulate present day soil carbon is therefore vital for reliable projections. In this study the most up-to-date CMIP6 ESMs are evaluated against empirical datasets to assess the ability of each model to simulate soil carbon and related controls: Net Primary Productivity (NPP) and soil carbon turnover time (τs). Comparing CMIP6 with CMIP5, uncertainties in modelled soil carbon remain, particularly the underestimation of northern high latitude soil carbon stocks. There is a robust improvement in the simulation of NPP in CMIP6 compared with CMIP5, however the same improvements are not seen in the simulation of τs. These results suggest a greater emphasis is required on improving the representation of below-ground soil processes in future developments of models. These improvements would help reduce the uncertainty of projected carbon release from global soils under climate change and to increase confidence in the carbon budgets associated with different levels of global warming.

Bridging the gaps between particulate backscattering measurements and modeled particulate organic carbon in the ocean

Abstract: Abstract. Oceanic particulate organic carbon (POC) is a small but dynamic component of the global carbon cycle. Biogeochemical models historically focused on reproducing the sinking flux of POC driven by large fast-sinking particles (LPOC). However, suspended and slow-sinking particles (SPOC, here < 100 µm) dominate the total POC (TPOC) stock, support a large fraction of microbial respiration, and can make sizable contributions to vertical fluxes. Recent developments in the parameterization of POC reactivity in PISCES (Pelagic Interactions Scheme for Carbon and Ecosystem Studies model; PISCESv2_RC) have improved its ability to capture POC dynamics. Here we evaluated this model by matching a global 3D simulation and 1D simulations at 50 different locations with observations made from biogeochemical (BGC-) Argo floats and satellites. Our evaluation covers globally representative biomes between 0 and 1000 m depth and relies on (1) a refined scheme for converting particulate backscattering at 700 nm (bbp700) to POC, based on biome-dependent POC / bbp700 ratios in the surface layer that decrease to an asymptotic value at depth; (2) a novel approach for matching annual time series of BGC-Argo vertical profiles to PISCES 1D simulations forced by pre-computed vertical mixing fields; and (3) a critical evaluation of the correspondence between in situ measurements of POC fractions, PISCES model tracers, and SPOC and LPOC estimated from high vertical resolution bbp700 profiles through a separation of the baseline and spike signals. We show that PISCES captures the major features of SPOC and LPOC across a range of spatiotemporal scales, from highly resolved profile time series to biome-aggregated climatological profiles. Model–observation agreement is usually better in the epipelagic (0–200 m) than in the mesopelagic (200–1000 m), with SPOC showing overall higher spatiotemporal correlation and smaller deviation (typically within a factor of 1.5). Still, annual mean LPOC stocks estimated from PISCES and BGC-Argo are highly correlated across biomes, especially in the epipelagic (r=0.78; n=50). Estimates of the SPOC / TPOC fraction converge around a median of 85 % (range 66 %–92 %) globally. Distinct patterns of model–observations misfits are found in subpolar and subtropical gyres, pointing to the need to better resolve the interplay between sinking, remineralization, and SPOC–LPOC interconversion in PISCES. Our analysis also indicates that a widely used satellite algorithm overestimates POC severalfold at high latitudes during the winter. The approaches proposed here can help constrain the stocks, and ultimately budgets, of oceanic POC.

Late Neogene evolution of modern deep-dwelling plankton

Abstract: Abstract. The fossil record of marine microplankton provides insights into the evolutionary drivers which led to the origin of modern deep-water plankton, one of the largest components of ocean biomass. We use global abundance and biogeographic data, combined with depth habitat reconstructions, to determine the environmental mechanisms behind speciation in two groups of pelagic microfossils over the past 15 Myr. We compare our microfossil datasets with water column profiles simulated in an Earth system model. We show that deep-living planktonic foraminiferal (zooplankton) and calcareous nannofossil (mixotroph phytoplankton) species were virtually absent globally during the peak of the middle Miocene warmth. The evolution of deep-dwelling planktonic foraminifera started from subpolar–mid-latitude species, during late Miocene cooling, via allopatry. Deep-dwelling species subsequently spread towards lower latitudes and further diversified via depth sympatry, establishing modern communities stratified hundreds of metres down the water column. Similarly, sub-euphotic zone specialist calcareous nannofossils become a major component of tropical and sub-tropical assemblages during the latest Miocene to early Pliocene. Our model simulations suggest that increased organic matter and oxygen availability for planktonic foraminifera, and increased nutrients and light penetration for nannoplankton, favoured the evolution of new deep-water niches. These conditions resulted from global cooling and the associated increase in the efficiency of the biological pump over the last 15 Myr.

Reviews and syntheses: The promise of big diverse soil data, moving current practices towards future potential

Abstract: Abstract. In the age of big data, soil data are more available and richer than ever, but – outside of a few large soil survey resources – they remain largely unusable for informing soil management and understanding Earth system processes beyond the original study. Data science has promised a fully reusable research pipeline where data from past studies are used to contextualize new findings and reanalyzed for new insight. Yet synthesis projects encounter challenges at all steps of the data reuse pipeline, including unavailable data, labor-intensive transcription of datasets, incomplete metadata, and a lack of communication between collaborators. Here, using insights from a diversity of soil, data, and climate scientists, we summarize current practices in soil data synthesis across all stages of database creation: availability, input, harmonization, curation, and publication. We then suggest new soil-focused semantic tools to improve existing data pipelines, such as ontologies, vocabulary lists, and community practices. Our goal is to provide the soil data community with an overview of current practices in soil data and where we need to go to fully leverage big data to solve soil problems in the next century.

The role of cover crops for cropland soil carbon, nitrogen leaching, and agricultural yields – a global simulation study with LPJmL (V. 5.0-tillage-cc)

Abstract: Abstract. Land management practices can reduce the environmental impact of agricultural land use and production, improve productivity, and transform cropland into carbon sinks. In our study we assessed the biophysical and biogeochemical impacts and the potential contribution of cover crop practices to sustainable land use. We applied the process-based, global dynamic vegetation model LPJmL (Lund–Potsdam–Jena managed Land) V. 5.0-tillage-cc with a modified representation of cover crops to simulate the growth of grasses on cropland in periods between two consecutive main crops' growing seasons for near-past climate and land use conditions. We quantified simulated responses of agroecosystem components to cover crop cultivation in comparison to bare-soil fallowing practices on global cropland for a period of 50 years. For cover crops with tillage, we obtained annual global median soil carbon sequestration rates of 0.52 and 0.48 t C ha−1 yr−1 for the first and last decades of the entire simulation period, respectively. We found that cover crops with tillage reduced annual nitrogen leaching rates from cropland soils by medians of 39 % and 54 % but also the productivity of the following main crop by an average of 1.6 % and 2 % for the 2 analyzed decades. The largest reductions in productivity were found for rice and modestly lowered ones for maize and wheat, whereas the soybean yield revealed an almost homogenously positive response to cover crop practices replacing bare-soil fallow periods. The obtained simulation results of cover crop with tillage practices exhibit a good ability of the model version to reproduce observed effects reported in other studies. Further, the results suggest that having no tillage is a suitable complementary practice to cover crops, enhancing soil carbon sequestration and the reduction in nitrogen leaching, while reducing potential trade-offs with the main-crop productivity due to their impacts on soil nitrogen and water dynamics. The spatial heterogeneity of simulated impacts of cover crops on the variables assessed here was related to the time period since the introduction of the management practice as well as to environmental and agronomic conditions of the cropland. This study supports findings of other studies, highlighting the substantial potential contribution of cover crop practices to the sustainable development of arable production.

Changing sub-Arctic tundra vegetation upon permafrost degradation: impact on foliar mineral element cycling

Abstract: Abstract. Arctic warming and permafrost degradation are modifying northern ecosystems through changes in microtopography, soil water dynamics, nutrient availability, and vegetation succession. Upon permafrost degradation, the release of deep stores of nutrients, such as nitrogen and phosphorus, from newly thawed permafrost stimulates Arctic vegetation production. More specifically, wetter lowlands show an increase in sedges (as part of graminoids), whereas drier uplands favor shrub expansion. These shifts in the composition of vegetation may influence local mineral element cycling through litter production. In this study, we evaluate the influence of permafrost degradation on mineral element foliar stocks and potential annual fluxes upon litterfall. We measured the foliar elemental composition (Al, Ca, Fe, K, Mn, P, S, Si, and Zn) of ∼ 500 samples of typical tundra plant species from two contrasting Alaskan tundra sites, i.e., an experimental sedge-dominated site (Carbon in Permafrost Experimental Heating Research, CiPEHR) and natural shrub-dominated site (Gradient). The foliar concentration of these mineral elements was species specific, with sedge leaves having relatively high Si concentration and shrub leaves having relatively high Ca and Mn concentrations. Therefore, changes in the species biomass composition of the Arctic tundra in response to permafrost thaw are expected to be the main factors that dictate changes in elemental composition of foliar stocks and maximum potential foliar fluxes upon litterfall. We observed an increase in the mineral element foliar stocks and potential annual litterfall fluxes, with Si increasing with sedge expansion in wetter sites (CiPEHR), and Ca and Mn increasing with shrub expansion in drier sites (Gradient). Consequently, we expect that sedge and shrub expansion upon permafrost thaw will lead to changes in litter elemental composition and therefore affect nutrient cycling across the sub-Arctic tundra with potential implications for further vegetation succession.

Thirty-eight years of CO2 fertilization has outpaced growing aridity to drive greening of Australian woody ecosystems

Abstract: Abstract. Climate change is projected to increase the imbalance between the supply (precipitation) and atmospheric demand for water (i.e., increased potential evapotranspiration), stressing plants in water-limited environments. Plants may be able to offset increasing aridity because rising CO2 increases water use efficiency. CO2 fertilization has also been cited as one of the drivers of the widespread “greening” phenomenon. However, attributing the size of this CO2 fertilization effect is complicated, due in part to a lack of long-term vegetation monitoring and interannual- to decadal-scale climate variability. In this study we asked the question of how much CO2 has contributed towards greening. We focused our analysis on a broad aridity gradient spanning eastern Australia's woody ecosystems. Next we analyzed 38 years of satellite remote sensing estimates of vegetation greenness (normalized difference vegetation index, NDVI) to examine the role of CO2 in ameliorating climate change impacts. Multiple statistical techniques were applied to separate the CO2-attributable effects on greening from the changes in water supply and atmospheric aridity. Widespread vegetation greening occurred despite a warming climate, increases in vapor pressure deficit, and repeated record-breaking droughts and heat waves. Between 1982–2019 we found that NDVI increased (median 11.3 %) across 90.5 % of the woody regions. After masking disturbance effects (e.g., fire), we statistically estimated an 11.7 % increase in NDVI attributable to CO2, broadly consistent with a hypothesized theoretical expectation of an 8.6 % increase in water use efficiency due to rising CO2. In contrast to reports of a weakening CO2 fertilization effect, we found no consistent temporal change in the CO2 effect. We conclude rising CO2 has mitigated the effects of increasing aridity, repeated record-breaking droughts, and record-breaking heat waves in eastern Australia. However, we were unable to determine whether trees or grasses were the primary beneficiary of the CO2-induced change in water use efficiency, which has implications for projecting future ecosystem resilience. A more complete understanding of how CO2-induced changes in water use efficiency affect trees and non-tree vegetation is needed.

Technical note: A view from space on global flux towers by MODIS and Landsat: the FluxnetEO data set

Abstract: Abstract. The eddy-covariance technique measures carbon, water, and energy fluxes between the land surface and the atmosphere at hundreds of sites globally. Collections of standardised and homogenised flux estimates such as the LaThuile, Fluxnet2015, National Ecological Observatory Network (NEON), Integrated Carbon Observation System (ICOS), AsiaFlux, AmeriFlux, and Terrestrial Ecosystem Research Network (TERN)/OzFlux data sets are invaluable to study land surface processes and vegetation functioning at the ecosystem scale. Space-borne measurements give complementary information on the state of the land surface in the surroundings of the towers. They aid the interpretation of the fluxes and support the benchmarking of terrestrial biosphere models. However, insufficient quality and frequent and/or long gaps are recurrent problems in applying the remotely sensed data and may considerably affect the scientific conclusions. Here, we describe a standardised procedure to extract, quality filter, and gap-fill Earth observation data from the MODIS instruments and the Landsat satellites. The methods consistently process surface reflectance in individual spectral bands, derived vegetation indices, and land surface temperature. A geometrical correction estimates the magnitude of land surface temperature as if seen from nadir or 40∘ off-nadir. Finally, we offer the community living data sets of pre-processed Earth observation data, where version 1.0 features the MCD43A4/A2 and MxD11A1 MODIS products and Landsat Collection 1 Tier 1 and Tier 2 products in a radius of 2 km around 338 flux sites. The data sets we provide can widely facilitate the integration of activities in the eddy-covariance, remote sensing, and modelling fields.

Estimating dry biomass and plant nitrogen concentration in pre-Alpine grasslands with low-cost UAS-borne multispectral data – a comparison of sensors, algorithms, and predictor sets

Abstract: Abstract. Grasslands are an important part of pre-Alpine and Alpine landscapes. Despite the economic value and the significant role of grasslands in carbon and nitrogen (N) cycling, spatially explicit information on grassland biomass and quality is rarely available. Remotely sensed data from unmanned aircraft systems (UASs) and satellites might be an option to overcome this gap. Our study aims to investigate the potential of low-cost UAS-based multispectral sensors for estimating above-ground biomass (dry matter, DM) and plant N concentration. In our analysis, we compared two different sensors (Parrot Sequoia, SEQ; MicaSense RedEdge-M, REM), three statistical models (linear model; random forests, RFs; gradient-boosting machines, GBMs), and six predictor sets (i.e. different combinations of raw reflectance, vegetation indices, and canopy height). Canopy height information can be derived from UAS sensors but was not available in our study. Therefore, we tested the added value of this structural information with in situ measured bulk canopy height data. A combined field sampling and flight campaign was conducted in April 2018 at different grassland sites in southern Germany to obtain in situ and the corresponding spectral data. The hyper-parameters of the two machine learning (ML) approaches (RF, GBM) were optimized, and all model setups were run with a 6-fold cross-validation. Linear models were characterized by very low statistical performance measures, thus were not suitable to estimate DM and plant N concentration using UAS data. The non-linear ML algorithms showed an acceptable regression performance for all sensor–predictor set combinations with average (avg; cross-validated, cv) Rcv2 of 0.48, RMSEcv,avg of 53.0 g m2, and rRMSEcv,avg (relative) of 15.9 % for DM and with Rcv,avg2 of 0.40, RMSEcv,avg of 0.48 wt %, and rRMSEcv, avg of 15.2 % for plant N concentration estimation. The optimal combination of sensors, ML algorithms, and predictor sets notably improved the model performance. The best model performance for the estimation of DM (Rcv2=0.67, RMSEcv=41.9 g m2, rRMSEcv=12.6 %) was achieved with an RF model that utilizes all possible predictors and REM sensor data. The best model for plant N concentration was a combination of an RF model with all predictors and SEQ sensor data (Rcv2=0.47, RMSEcv=0.45 wt %, rRMSEcv=14.2 %). DM models with the spectral input of REM performed significantly better than those with SEQ data, while for N concentration models, it was the other way round. The choice of predictors was most influential on model performance, while the effect of the chosen ML algorithm was generally lower. The addition of canopy height to the spectral data in the predictor set significantly improved the DM models. In our study, calibrating the ML algorithm improved the model performance substantially, which shows the importance of this step.

Predicting the impact of spatial heterogeneity on microbially mediated nutrient cycling in the subsurface

Abstract: Abstract. The subsurface is a temporally dynamic and spatially heterogeneous compartment of the Earth's critical zone, and biogeochemical transformations taking place in this compartment are crucial for the cycling of nutrients. The impact of spatial heterogeneity on such microbially mediated nutrient cycling is not well known, which imposes a severe challenge in the prediction of in situ biogeochemical transformation rates and further of nutrient loading contributed by the groundwater to the surface water bodies. Therefore, we used a numerical modelling approach to evaluate the sensitivity of groundwater microbial biomass distribution and nutrient cycling to spatial heterogeneity in different scenarios accounting for various residence times. The model results gave us an insight into domain characteristics with respect to the presence of oxic niches in predominantly anoxic zones and vice versa depending on the extent of spatial heterogeneity and the flow regime. The obtained results show that microbial abundance, distribution, and activity are sensitive to the applied flow regime and that the mobile (i.e. observable by groundwater sampling) fraction of microbial biomass is a varying, yet only a small, fraction of the total biomass in a domain. Furthermore, spatial heterogeneity resulted in anaerobic niches in the domain and shifts in microbial biomass between active and inactive states. The lack of consideration of spatial heterogeneity, thus, can result in inaccurate estimation of microbial activity. In most cases this leads to an overestimation of nutrient removal (up to twice the actual amount) along a flow path. We conclude that the governing factors for evaluating this are the residence time of solutes and the Damköhler number (Da) of the biogeochemical reactions in the domain. We propose a relationship to scale the impact of spatial heterogeneity on nutrient removal governed by the log10Da. This relationship may be applied in upscaled descriptions of microbially mediated nutrient cycling dynamics in the subsurface thereby resulting in more accurate predictions of, for example, carbon and nitrogen cycling in groundwater over long periods at the catchment scale.

Spatially varying relevance of hydrometeorological hazards for vegetation productivity extremes

Abstract: Abstract. Vegetation plays a vital role in the Earth system by sequestering carbon, producing food and oxygen, and providing evaporative cooling. Vegetation productivity extremes have multi-faceted implications, for example on crop yields or the atmospheric CO2 concentration. Here, we focus on productivity extremes as possible impacts of coinciding, potentially extreme hydrometeorological anomalies. Using monthly global satellite-based Sun-induced chlorophyll fluorescence data as a proxy for vegetation productivity from 2007–2015, we show that vegetation productivity extremes are related to hydrometeorological hazards as characterized through ERA5-Land reanalysis data in approximately 50 % of our global study area. For the latter, we are considering sufficiently vegetated and cloud-free regions, and we refer to hydrometeorological hazards as water- or energy-related extremes inducing productivity extremes. The relevance of the different hazard types varies in space; temperature-related hazards dominate at higher latitudes with cold spells contributing to productivity minima and heat waves supporting productivity maxima, while water-related hazards are relevant in the (sub-)tropics with droughts being associated with productivity minima and wet spells with the maxima. Alongside single hazards compound events such as joint droughts and heat waves or joint wet and cold spells also play a role, particularly in dry and hot regions. Further, we detect regions where energy control transitions to water control between maxima and minima of vegetation productivity. Therefore, these areas represent hotspots of land–atmosphere coupling where vegetation efficiently translates soil moisture dynamics into surface fluxes such that the land affects near-surface weather. Overall, our results contribute to pinpointing how potential future changes in temperature and precipitation could propagate to shifting vegetation productivity extremes and related ecosystem services.

Oxygen export to the deep ocean following Labrador Sea Water formation

Abstract: Abstract. The Labrador Sea in the North Atlantic Ocean is one of the few regions globally where oxygen from the atmosphere can reach the deep ocean directly. This is the result of wintertime deep convection, which homogenizes the water column to a depth of up to 2000 m and brings deep water undersaturated in oxygen into contact with the atmosphere. In this study, we analyze how the intense oxygen uptake during Labrador Sea Water (LSW) formation affects the properties of the outflowing deep western boundary current, which ultimately feeds the upper part of the North Atlantic Deep Water layer in much of the Atlantic Ocean. Seasonal cycles of oxygen concentration, temperature, and salinity from a 2-year time series collected by sensors moored at 600 m nominal depth in the outflowing boundary current at 53∘ N show a cooling, freshening, and increase in oxygen content of the water flowing out of the basin between March and August. Analysis of Argo float data suggests that this is preceded by an increased input of LSW into the boundary current about 1 month earlier. This input is the result of newly ventilated LSW entering from the interior, as well as LSW formed directly within the boundary current. Together, these results imply that the southward export of newly formed LSW primarily occurs in the months following the onset of deep convection, from March to August, and that this direct LSW export route controls the seasonal oxygen increase in the outflow at 600 m depth. During the rest of the year, properties of the boundary current measured at 53∘ N resemble those of Irminger Water, which enters the basin with the boundary current from the Irminger Sea. The input of newly ventilated LSW increases the oxygen concentration from 298 µmol L−1 in January to a maximum of 306 µmol L−1 in April. As a result of this LSW input, an estimated (1.60 ± 0.42) × 1012 mol yr−1 of oxygen are added to the outflowing boundary current, mostly during spring and summer, equivalent to 50 % of the wintertime uptake from the atmosphere in the interior of the basin. The export of oxygen from the subpolar gyre associated with this direct southward pathway of LSW is estimated to supply 42 %–71 % of the oxygen consumed annually in the upper North Atlantic Deep Water layer in the Atlantic Ocean between the Equator and 50∘ N. Our results show that the formation of LSW is important for replenishing oxygen to the deep oceans, meaning that possible changes in its formation rate and ventilation due to climate change could have wide-reaching impacts on marine life.

Microbial labilization and diversification of pyrogenic dissolved organic matter

Abstract: Abstract. With the increased occurrence of wildfires around the world, interest in the chemistry of pyrogenic organic matter (pyOM) and its fate in the environment has increased. Upon leaching from soils by rain events, significant amounts of dissolved pyOM (pyDOM) enter the aquatic environment and interact with microbial communities that are essential for cycling organic matter within the different biogeochemical cycles. To evaluate the biodegradability of pyDOM, aqueous extracts of laboratory-produced biochars were incubated with soil microbes, and the molecular changes to the composition of pyDOM were probed using ultrahigh-resolution mass spectrometry (Fourier transform–ion cyclotron resonance–mass spectrometry). Given that solar irradiation significantly affects the composition of pyDOM during terrestrial-to-marine export, the effects of photochemistry were also evaluated in the context of pyDOM biodegradability. Ultrahigh-resolution mass spectrometry revealed that many different (both aromatic and aliphatic) compounds were biodegraded. New labile compounds were produced, 22 %–40 % of which were peptide-like. These results indicated that a portion of pyDOM has been labilized into microbial biomass during the incubations. Fluorescence excitation–emission matrix spectra revealed that some fraction of these new bio-produced molecules is associated with proteinaceous fluorophores. Two-dimensional 1H–1H total correlation nuclear magnetic resonance (NMR) spectroscopy identified a peptidoglycan-like backbone within the microbially produced compounds. These results are consistent with previous observations of peptidoglycans within the soil and ocean nitrogen cycles where remnants of biodegraded pyDOM are expected to be observed. Interestingly, the exact nature of the bio-produced organic matter was found to vary drastically among samples indicating that the microbial consortium used may produce different exudates based on the composition of the initial pyDOM. Another potential explanation for the vast diversity of molecules is that microbes only consume low molecular-weight compounds, but they also produce reactive oxygen species (ROS), which initiate oxidative and recombination reactions that degrade high molecular-weight compounds and produce new molecules. Some of the bio-produced molecules (212–308 molecular formulas) were identified in estuarine and marine (surface and abyssal oceanic), and 81–192 of these formulas were of molecular composition attributed to carboxyl-rich alicyclic molecules (CRAM). These results indicate that some of the pyDOM biodegradation products have an oceanic fate and can be sequestered into the deep ocean. The observed microbially mediated diversification of pyDOM suggests that pyDOM contributes to the observed large complexity of natural organic matter observed in riverine and oceanic systems. More broadly, our research shows that pyDOM can be substrate for microbial growth and be incorporated into environmental food webs within the global carbon and nitrogen cycles.

Nutrient transport and transformation in macrotidal estuaries of the French Atlantic coast: a modeling approach using the Carbon-Generic Estuarine Model

Abstract: Abstract. Estuaries are key reactive ecosystems along the land–ocean aquatic continuum, with significant ecological and economic value. However, they have been facing strong morphological management changes and increased nutrient and contaminant inputs, possibly leading to ecological problems such as coastal eutrophication. Therefore, it is necessary to quantify the import and export fluxes of the estuaries, their retention capacity, and estuarine eutrophication potential. The 1-D Carbon-Generic Estuary Model (C-GEM) was used to simulate the transient hydrodynamics, transport, and biogeochemistry for estuaries with different sizes and morphologies along the French Atlantic coast during the period 2014–2016 using readily available geometric, hydraulic, and biogeochemical data. These simulations allowed us to evaluate the budgets of the main nutrients (phosphorus – P; nitrogen – N; silica – Si) and total organic carbon (TOC), and their imbalance, providing insights into their eutrophication potential. Cumulated average annual fluxes to the Atlantic coast from the seven estuaries studied were 9.6 kt P yr−1, 259 kt N yr−1, 304 kt Si yr−1, and 145 kt C yr−1. Retention rates varied depending on the estuarine residence times, ranging from 0 %–27 % and 0 %–34 % to 2 %–39 % and 8 %–96 % for total phosphorus (TP), total nitrogen (TN), dissolved silica (DSi), and TOC, respectively. Large-scale estuaries had higher retention rates than medium and small estuaries, which we interpreted in terms of estuarine residence times. As shown by the indicator of eutrophication potential (ICEP), there might be a risk of coastal eutrophication, i.e., the development of non-siliceous algae that is potentially harmful to the systems studied due to the excess TN over DSi. This study also demonstrates the ability of our model to be applied with a similar setup to several estuarine systems characterized by different sizes, geometries, and riverine loads.

Predicting mangrove forest dynamics across a soil salinity gradient using an individual-based vegetation model linked with plant hydraulics

Abstract: Abstract. In mangrove forests, soil salinity is one of the most significant environmental factors determining forest distribution and productivity as it limits plant water uptake and carbon gain. However, salinity control on mangrove productivity through plant hydraulics has not been investigated by existing mangrove models. Here we present a new individual-based model linked with plant hydraulics to incorporate physiological characterization of mangrove growth under salt stress. Plant hydraulics was associated with mangroves' nutrient uptake and biomass allocation apart from water flux and carbon gain. The developed model was performed for two coexisting species – Rhizophora stylosa and Bruguiera gymnorrhiza – in a subtropical mangrove forest in Japan. The model predicted that the productivity of both species was affected by soil salinity through downregulation of stomatal conductance. Under low-soil-salinity conditions (< 28 ‰), B. gymnorrhiza trees grew faster and suppressed the growth of R. stylosa trees by shading that resulted in a B. gymnorrhiza-dominated forest. As soil salinity increased, the productivity of B. gymnorrhiza was significantly reduced compared to R. stylosa, which led to an increase in biomass of R. stylosa despite the enhanced salt stress (> 30 ‰). These predicted patterns in forest structures across the soil salinity gradient remarkably agreed with field data, highlighting the control of salinity on productivity and tree competition as factors that shape the mangrove forest structures. The model reproducibility of forest structures was also supported by the predicted self-thinning processes, which likewise agreed with field data. Aside from soil salinity, seasonal dynamics in atmospheric variables (solar radiation and temperature) were highlighted as factors that influence mangrove productivity in a subtropical region. This physiological principle-based improved model has the potential to be extended to other mangrove forests in various environmental settings, thus contributing to a better understanding of mangrove dynamics under future global climate change.

Ignoring carbon emissions from thermokarst ponds results in overestimation of tundra net carbon uptake

Abstract: Abstract. Arctic permafrost landscapes have functioned as a global carbon sink for millennia. These landscapes are very heterogeneous, and the omnipresent water bodies within them act as a carbon source. Yet, few studies have focused on the impact of these water bodies on the landscape carbon budget. We deepen our understanding of carbon emissions from thermokarst ponds and constrain their impact by comparing carbon dioxide and methane fluxes from these ponds to fluxes from the surrounding tundra. We use eddy covariance measurements from a tower located at the border between a large pond and semi-terrestrial tundra. When we take the open-water areas of thermokarst ponds into account, our results show that the estimated summer carbon uptake of the polygonal tundra is 11 % lower. Further, the data show that open-water methane emissions are of a similar magnitude to polygonal tundra emissions. However, some parts of the pond's shoreline exhibit much higher emissions. This finding underlines the high spatial variability in methane emissions. We conclude that gas fluxes from thermokarst ponds can contribute significantly to the carbon budget of Arctic tundra landscapes. Consequently, changes in the water body distribution of tundra landscapes due to permafrost degradation may substantially impact the overall carbon budget of the Arctic.

Trace gas fluxes from tidal salt marsh soils: implications for carbon–sulfur biogeochemistry

Abstract: Abstract. Tidal salt marsh soils can be a dynamic source of greenhouse gases such as carbon dioxide (CO2), methane (CH4), and nitrous oxide (N2O), as well as sulfur-based trace gases such as carbon disulfide (CS2) and dimethylsulfide (DMS) which play roles in global climate and carbon–sulfur biogeochemistry. Due to the difficulty in measuring trace gases in coastal ecosystems (e.g., flooding, salinity), our current understanding is based on snapshot instantaneous measurements (e.g., performed during daytime low tide) which complicates our ability to assess the role of these ecosystems for natural climate solutions. We performed continuous, automated measurements of soil trace gas fluxes throughout the growing season to obtain high-temporal frequency data and to provide insights into magnitudes and temporal variability across rapidly changing conditions such as tidal cycles. We found that soil CO2 fluxes did not show a consistent diel pattern, CH4, N2O, and CS2 fluxes were highly variable with frequent pulse emissions (> 2500 %, > 10 000 %, and > 4500 % change, respectively), and DMS fluxes only occurred midday with changes > 185 000 %. When we compared continuous measurements with discrete temporal measurements (during daytime, at low tide), discrete measurements of soil CO2 fluxes were comparable with those from continuous measurements but misrepresent the temporal variability and magnitudes of CH4, N2O, DMS, and CS2. Discrepancies between the continuous and discrete measurement data result in differences for calculating the sustained global warming potential (SGWP), mainly by an overestimation of CH4 fluxes when using discrete measurements. The high temporal variability of trace gas fluxes complicates the accurate calculation of budgets for use in blue carbon accounting and earth system models.

A convolutional neural network for spatial downscaling of satellite-based solar-induced chlorophyll fluorescence (SIFnet)

Abstract: Abstract. Gross primary productivity (GPP) is the sum of leaf photosynthesis and represents a crucial component of the global carbon cycle. Space-borne estimates of GPP typically rely on observable quantities that co-vary with GPP such as vegetation indices using reflectance measurements (e.g., normalized difference vegetation index, NDVI, near-infrared reflectance of terrestrial vegetation, NIRv, and kernel normalized difference vegetation index, kNDVI). Recent work has also utilized measurements of solar-induced chlorophyll fluorescence (SIF) as a proxy for GPP. However, these SIF measurements are typically coarse resolution, while many processes influencing GPP occur at fine spatial scales. Here, we develop a convolutional neural network (CNN), named SIFnet, that increases the resolution of SIF from the TROPOspheric Monitoring Instrument (TROPOMI) on board of the satellite Sentinel-5P by a factor of 10 to a spatial resolution of 500 m. SIFnet utilizes coarse SIF observations together with high-resolution auxiliary data. The auxiliary data used here may carry information related to GPP and SIF. We use training data from non-US regions between April 2018 until March 2021 and evaluate our CNN over the conterminous United States (CONUS). We show that SIFnet is able to increase the resolution of TROPOMI SIF by a factor of 10 with a r2 and RMSE metrics of 0.92 and 0.17 mW m−2 sr−1 nm−1, respectively. We further compare SIFnet against a recently developed downscaling approach and evaluate both methods against independent SIF measurements from Orbiting Carbon Observatory 2 and 3 (together OCO-2/3). SIFnet performs systematically better than the downscaling approach (r=0.78 for SIFnet, r=0.72 for downscaling), indicating that it is picking up on key features related to SIF and GPP. Examination of the feature importance in the neural network indicates a few key parameters and the spatial regions in which these parameters matter. Namely, the CNN finds low-resolution SIF data to be the most significant parameter with the NIRv vegetation index as the second most important parameter. NIRv consistently outperforms the recently proposed kNDVI vegetation index. Advantages and limitations of SIFnet are investigated and presented through a series of case studies across the United States. SIFnet represents a robust method to infer continuous, high-spatial-resolution SIF data.

Modelling temporal variability of in situ soil water and vegetation isotopes reveals ecohydrological couplings in a riparian willow plot

Abstract: Abstract. The partitioning of water fluxes in the critical zone is of great interest due to the implications for understanding water cycling and quantifying water availability for various ecosystem services. We used the tracer-aided ecohydrological model EcH2O-iso to use stable water isotopes to help evaluate water, energy, and biomass dynamics at an intensively monitored study plot under two willow trees, a riparian species, in Berlin, Germany. Importantly, we assessed the value of in situ soil and plant water isotope data in helping to quantify xylem water sources and transit times, with coupled estimates of the temporal dynamics and ages of soil and root uptake water. The willows showed high water use through evapotranspiration, with limited percolation of summer precipitation to deeper soil layers due to the dominance of shallow root uptake (>80 % in the upper 10 cm, 70 %–78 % transpiration/evapotranspiration). Lower evapotranspiration under grass (52 %–55 % transpiration/evapotranspiration) resulted in higher soil moisture storage, greater soil evaporation, and more percolation of soil water. Biomass allocation was predominantly foliage growth (57 % in grass and 78 % in willow). Shallow soil water age under grass was estimated to be similar to under willows (15–17 d). Considering potential xylem transit times showed a substantial improvement in the model's capability to simulate xylem isotopic composition and water ages and demonstrates the potential value of using in situ data to aid ecohydrological modelling. Root water uptake was predominately derived from summer precipitation events (56 %) and had an average age of 35 d, with xylem transport times taking at least 6.2–8.1 d. By evaluating isotope mass balances along with water partitioning, energy budgets, and biomass allocation, the EcH2O-iso model proved a useful tool for assessing water cycling within the critical zone at high temporal resolution, particularly xylem water sources and transport, which are all necessary for short- and long-term assessment of water availability for plant growth.

Wintertime process study of the North Brazil Current rings reveals the region as a larger sink for CO₂ than expected

Abstract: Abstract. The key processes driving the air–sea CO2 fluxes in the western tropical Atlantic (WTA) in winter are poorly known. WTA is a highly dynamic oceanic region, expected to have a dominant role in the variability in CO2 air–sea fluxes. In early 2020 (February), this region was the site of a large in situ survey and studied in wider context through satellite measurements. The North Brazil Current (NBC) flows northward along the coast of South America, retroflects close to 8∘ N and pinches off the world's largest eddies, the NBC rings. The rings are formed to the north of the Amazon River mouth when freshwater discharge is still significant in winter (a time period of relatively low run-off). We show that in February 2020, the region (5–16∘ N, 50–59∘ W) is a CO2 sink from the atmosphere to the ocean (−1.7 Tg C per month), a factor of 10 greater than previously estimated. The spatial distribution of CO2 fugacity is strongly influenced by eddies south of 12∘ N. During the campaign, a nutrient-rich freshwater plume from the Amazon River is entrained by a ring from the shelf up to 12∘ N leading to high phytoplankton concentration and significant carbon drawdown (∼20 % of the total sink). In trapping equatorial waters, NBC rings are a small source of CO2. The less variable North Atlantic subtropical water extends from 12∘ N northward and represents ∼60 % of the total sink due to the lower temperature associated with winter cooling and strong winds. Our results, in identifying the key processes influencing the air–sea CO2 flux in the WTA, highlight the role of eddy interactions with the Amazon River plume. It sheds light on how a lack of data impeded a correct assessment of the flux in the past, as well as on the necessity of taking into account features at meso- and small scales.

Carbon, nitrogen, and phosphorus stoichiometry of organic matter in Swedish forest soils and its relationship with climate, tree species, and soil texture

Abstract: Abstract. While the carbon (C) content of temperate and boreal forest soils is relatively well studied, much less is known about the ratios of C, nitrogen (N), and phosphorus (P) of the soil organic matter, as well as the abiotic and biotic factors that shape them. Therefore, the aim of this study was to explore carbon, nitrogen, and organic phosphorus (OP) contents and element ratios in temperate and boreal forest soils and their relationships with climate, dominant tree species, and soil texture. For this purpose, we studied 309 forest soils located all over Sweden between 56 and 68∘ N. The soils are a representative subsample of Swedish forest soils with a stand age >60 years that were sampled for the Swedish Forest Soil Inventory. We found that the N stock of the organic layer increased by a factor of 7.5 from −2.0 to 7.5 ∘C mean annual temperature (MAT), which is almost twice as much as the increase in the organic layer stock along the MAT gradient. The increase in the N stock went along with an increase in the N:P ratio of the organic layer by a factor of 2.1 from −2.0 to 7.5 ∘C MAT (R2=0.36, p<0.001). Forests dominated by pine had higher C:N ratios in the organic layer and mineral soil down to a depth of 65 cm than forests dominated by spruce. Further, also the C:P ratio was increased in the pine-dominated forests compared to forests dominated by other tree species in the organic layer, while the C:OP ratio in the mineral soil was not elevated in pine forests. C, N, and OP contents in the mineral soil were higher in fine-textured soils than in coarse-textured soils by a factor of 2.3, 3.5, and 4.6, respectively. Thus, the effect of texture was stronger on OP than on N and C likely because OP adsorbs very rigidly to mineral surfaces. Further, we found that the P and K concentrations of the organic layer were inversely related to the organic layer stock, while the N:P ratio was positively related to the organic layer stock. Taken together, the results show that the N:P ratio of the organic layer was most strongly related to MAT. Further, the C:N ratio was most strongly related to dominant tree species even in the mineral subsoil. In contrast, the C:P ratio was only affected by dominant tree species in the organic layer, but the C:OP ratio in the mineral soil was hardly affected by tree species due to the strong effect of soil texture on the OP concentration.

Acidification, deoxygenation, and nutrient and biomass declines in a warming Mediterranean Sea

Abstract: Abstract. The projected warming, nutrient decline, changes in net primary production, deoxygenation and acidification of the global ocean will affect marine ecosystems during the 21st century. Here, the climate change-related impacts on the marine ecosystems of the Mediterranean Sea in the middle and at the end of the 21st century are assessed using high-resolution projections of the physical and biogeochemical state of the basin under Representative Concentration Pathways (RCPs) 4.5 and 8.5. In both scenarios, the analysis shows changes in the dissolved nutrient contents of the euphotic and intermediate layers of the basin, net primary production, phytoplankton respiration and carbon stock (including phytoplankton, zooplankton, bacterial biomass and particulate organic matter). The projections also show uniform surface and subsurface reductions in the oxygen concentration driven by the warming of the water column and by the increase in ecosystem respiration as well as an acidification signal in the upper water column linked to the increase in the dissolved inorganic carbon content of the water column due to CO2 absorption from the atmosphere and the increase in respiration. The projected changes are stronger in the RCP8.5 (worst-case) scenario and, in particular, in the eastern Mediterranean due to the limited influence of the exchanges in the Strait of Gibraltar in that part of the basin. On the other hand, analysis of the projections under the RCP4.5 emission scenario shows a tendency to recover the values observed at the beginning of the 21st century for several biogeochemical variables in the second half of the period. This result supports the idea – possibly based on the existence in a system such as the Mediterranean Sea of a certain buffer capacity and renewal rate – that the implementation of policies for reducing CO2 emission could indeed be effective and could contribute to the foundation of ocean sustainability science and policies.

Physiological control on carbon isotope fractionation in marine phytoplankton

Abstract: Abstract. One of the great challenges in biogeochemical research over the past half a century has been to quantify and understand the mechanisms underlying stable carbon isotope fractionation (εp) in phytoplankton in response to changing CO2 concentrations. This interest is partly grounded in the use of fossil photosynthetic organism remains as a proxy for past atmospheric CO2 levels. Phytoplankton organic carbon is depleted in 13C compared to its source because of kinetic fractionation by the enzyme RubisCO during photosynthetic carbon fixation, as well as through physiological pathways upstream of RubisCO. Moreover, other factors such as nutrient limitation, variations in light regime as well as phytoplankton culturing systems and inorganic carbon manipulation approaches may confound the influence of aquatic CO2 concentrations [CO2] on εp. Here, based on experimental data compiled from the literature, we assess which underlying physiological processes cause the observed differences in εp for various phytoplankton groups in response to C-demand/C-supply, i.e., particulate organic carbon (POC) production / [CO2]) and test potential confounding factors. Culturing approaches and methods of carbonate chemistry manipulation were found to best explain the differences in εp between studies, although day length was an important predictor for εp in haptophytes. Extrapolating results from culturing experiments to natural environments and for proxy applications therefore require caution, and it should be carefully considered whether culture methods and experimental conditions are representative of natural environments.