Jena Soil Model (JSM v1.0; revision 1934): a microbial soil organic carbon model integrated with nitrogen and phosphorus processes

Plant–soil interactions, such as the coupling of plants' below-ground biomass allocation with soil organic matter (SOM) decomposition, nutrient release and plant uptake, are essential to understand the response of carbon (C) cycling to global changes. However, these processes are poorly represented in the current terrestrial biosphere models owing to the simple first-order approach of SOM cycling and the ignorance of variations within a soil profile. While the emerging microbially explicit soil organic C models can better describe C formation and turnover, at present, they lack a full coupling to the nitrogen (N) and phosphorus (P) cycles with the soil profile. Here we present a new SOM model – the Jena Soil Model (JSM) – which is microbially explicit, vertically resolved and integrated with the N and P cycles. To account for the effects of nutrient availability and litter quality on decomposition, JSM includes the representation of enzyme allocation to different depolymerisation sources based on the microbial adaptation approach as well as of nutrient acquisition competition based on the equilibrium chemistry approximation approach. Herein, we present the model structure and basic features of model performance in a beech forest in Germany. The model reproduced the main SOM stocks and microbial biomass as well as their vertical patterns in the soil profile. We further tested the sensitivity of the model to parameterisation and showed that JSM is generally sensitive to changes in microbial stoichiometry and processes

Nitrification amplifies the decreasing trends of atmospheric oxygen and implies a larger land carbon uptake

[1] Atmospheric O-2 trend measurements are used to partition global oceanic and land biotic carbon sinks on a multiannual basis. The underlying principle is that a terrestrial uptake or release of CO₂ is accompanied by an opposite flux of O-2. The molar ratio of the CO₂ and O-2 terrestrial fluxes should be 1, if no other elements are considered. However, reactive nitrogen produced by human activities (e.g., fertilizers, N deposition) is also being incorporated into plant tissues. The various reaction pathways of the terrestrial nitrogen cycle cause fluxes of atmospheric O-2. Thus the cycles of nitrogen, carbon, and oxygen must be linked together. We report here on previously unconsidered anthropogenic nitrogen-related mechanisms which impact atmospheric O-2 trends and thus the derived global carbon sinks. In particular, we speculate that anthropogenic-driven changes are driving the global nitrogen cycle to a more oxidized state, primarily through nitrification, nitrate fertilizer industrial production, and combustion of fossil fuels and anthropogenic biomass burning. The sum of these nitrogen-related processes acts to additionally decrease atmospheric O-2 and slightly increase atmospheric CO₂. We have calculated that the effective land biotic O-2: CO₂ molar ratio ranges between 0.76 and 1.04 rather than 1.10 ( moles of O-2 produced per mole of CO₂ consumed) over the period 1993 - 2003, depending on which of four contrasting nitrogen oxidation and reduction pathway scenarios is used. Using the scenario in which we have most confidence, this implies a 0.23 PgC yr(-1) correction to the global land biotic and oceanic carbon sinks of most recently reported estimates over 1993 - 2003, with the land biotic sink becoming larger and the oceanic sink smaller. We have attributed large uncertainties of 100% to all nitrogen-related O-2 and CO₂ fluxes and this corresponds up to +/- 0.09 PgC yr(-1) increase in global carbon sink uncertainties. Thus accounting for anthropogenic nitrogen-related terrestrial fluxes of O-2 results in a 45% larger land biotic sink of 0.74 +/- 0.78 PgC yr(-1) and a slightly smaller oceanic sink of 2.01 +/- 0.66 PgC yr(-1) for the decade 1993 - 2003. [References: 38

Controls of terrestrial ecosystem nitrogen loss on simulated productivity responses to elevated CO₂

The availability of nitrogen is one of the primary controls on plant growth. Terrestrial ecosystem nitrogen availability is not only determined by inputs from fixation, deposition, or weathering, but is also regulated by the rates with which nitrogen is lost through various pathways. Estimates of large-scale nitrogen loss rates have been associated with considerable uncertainty, as process rates and controlling factors of the different loss pathways have been difficult to characterize in the field. Therefore, the nitrogen loss representations in terrestrial biosphere models vary substantially, adding to nitrogen cycle-related uncertainty and resulting in varying predictions of how the biospheric carbon sink will evolve under future scenarios of elevated atmospheric CO2. Here, we test three commonly applied approaches to represent ecosystem-level nitrogen loss in a common carbon–nitrogen terrestrial biosphere model with respect to their impact on projections of the effect of elevated CO2. We find that despite differences in predicted responses of nitrogen loss rates to elevated CO2 and climate forcing, the variety of nitrogen loss representation between models only leads to small variety in carbon sink predictions. The nitrogen loss responses are particularly uncertain in the boreal and tropical regions, where plant growth is strongly nitrogen-limited or nitrogen turnover rates are usually high, respectively. This highlights the need for better representation of nitrogen loss fluxes through global measurements to inform models.</p

The European carbon cycle response to heat and drought as seen from atmospheric CO(2)data for 1999-2018

In 2018, central and northern parts of Europe experienced heat and drought conditions over many months from spring to autumn, strongly affecting both natural ecosystems and crops. Besides their impact on nature and society, events like this can be used to study the impact of climate variations on the terrestrial carbon cycle, which is an important determinant of the future climate trajectory. Here, variations in the regional net ecosystem exchange (NEE) of CO(2)between terrestrial ecosystems and the atmosphere were quantified from measurements of atmospheric CO(2)mole fractions. Over Europe, several observational records have been maintained since at least 1999, giving us the opportunity to assess the 2018 anomaly in the context of at least two decades of variations, including the strong climate anomaly in 2003. In addition to an atmospheric inversion with temporally explicitly estimated anomalies, we use an inversion based on empirical statistical relations between anomalies in the local NEE and anomalies in local climate conditions. For our analysis period 1999-2018, we find that higher-than-usual NEE in hot and dry summers may tend to arise in Central Europe from enhanced ecosystem respiration due to the elevated temperatures, and in Southern Europe from reduced photosynthesis due to the reduced water availability. Despite concerns in the literature, the level of agreement between regression-based NEE anomalies and temporally explicitly estimated anomalies indicates that the atmospheric CO(2)measurements from the relatively dense European station network do provide information about the year-to-year variations of Europe's carbon sources and sinks, at least in summer. This article is part of the theme issue 'Impacts of the 2018 severe drought and heatwave in Europe: from site to continental scale'.Peer reviewe

History of El Nino impacts on the global carbon cycle 1957-2017 : a quantification from atmospheric CO2 data

Interannual variations in the large-scale net ecosystem exchange (NEE) of CO2 between the terrestrial biosphere and the atmosphere were estimated for 1957-2017 from sustained measurements of atmospheric CO2 mixing ratios. As the observations are sparse in the early decades, available records were combined into a 'quasi-homogeneous' dataset based on similarity in their signals, to minimize spurious variations from beginning or ending data records. During El Nino events, CO2 is anomalously released from the tropical band, and a few months later also in the northern extratropical band. This behaviour can approximately be represented by a linear relationship of the NEE anomalies and local air temperature anomalies, with sensitivity coefficients depending on geographical location and season. The apparent climate sensitivity of global total NEE against variations in pan-tropically averaged annual air temperature slowly changed over time during the 1957-2017 period, first increasing (though less strongly than in previous studies) but then decreasing again. However, only part of this change can be attributed to actual changes in local physiological or ecosystem processes, the rest probably arising from shifts in the geographical area of dominating temperature variations. This article is part of a discussion meeting issue 'The impact of the 2015/2016 El Nino on the terrestrial tropical carbon cycle: patterns, mechanisms and implications'.Peer reviewe

Development and evaluation of an ozone deposition scheme for coupling to a terrestrial biosphere model

Ozone (O3) is a toxic air pollutant that can damage plant leaves and substantially affect the plant's gross primary production (GPP) and health. Realistic estimates of the effects of tropospheric anthropogenic O3 on GPP are thus potentially important to assess the strength of the terrestrial biosphere as a carbon sink. To better understand the impact of ozone damage on the terrestrial carbon cycle, we developed a module to estimate O3 uptake and damage of plants for a state-of-the-art global terrestrial biosphere model called OCN. Our approach accounts for ozone damage by calculating (a) O3 transport from 45 m height to leaf level, (b) O3 flux into the leaf, and (c) ozone damage of photosynthesis as a function of the accumulated O3 uptake over the lifetime of a leaf. A comparison of modelled canopy conductance, GPP, and latent heat to FLUXNET data across European forest and grassland sites shows a general good performance of OCN including ozone damage. This comparison provides a good baseline on top of which ozone damage can be evaluated. In comparison to literature values, we demonstrate that the new model version produces realistic O3 surface resistances, O3 deposition velocities, and stomatal to total O3 flux ratios. A sensitivity study reveals that key metrics of the air-to-leaf O3 transport and O3 deposition, in particular the stomatal O3 uptake, are reasonably robust against uncertainty in the underlying parameterisation of the deposition scheme. Nevertheless, correctly estimating canopy conductance plays a pivotal role in the estimate of cumulative O3 uptake. We further find that accounting for stomatal and non-stomatal uptake processes substantially affects simulated plant O3 uptake and accumulation, because aerodynamic resistance and non-stomatal O3 destruction reduce the predicted leaf-level O3 concentrations. Ozone impacts on GPP and transpiration in a Europe-wide simulation indicate that tropospheric O3 impacts the regional carbon and water cycling less than expected from previous studies. This study presents a first step towards the integration of atmospheric chemistry and ecosystem dynamics modelling, which would allow for assessing the wider feedbacks between vegetation ozone uptake and tropospheric ozone burden

Phasic, Event-Related Transcutaneous Auricular Vagus Nerve Stimulation Modifies Behavioral, Pupillary, and Low-Frequency Oscillatory Power Responses

Transcutaneous auricular vagus nerve stimulation (taVNS) has been proposed to activate the locus ceruleus-noradrenaline (LC-NA) system. However, previous studies failed to find consistent modulatory effects of taVNS on LC-NA biomarkers. Previous studies suggest that phasic taVNS may be capable of modulating LC-NA biomarkers such as pupil dilation and alpha oscillations. However, it is unclear whether these effects extend beyond pure sensory vagal nerve responses. Critically, the potential of the pupillary light reflex as an additional taVNS biomarker has not been explored so far. Here, we applied phasic active and sham taVNS in 29 subjects (16 female, 13 male) while they performed an emotional Stroop task (EST) and a passive pupil light reflex task (PLRT). We recorded pupil size and brain activity dynamics using a combined Magnetoencephalography (MEG) and pupillometry design. Our results show that phasic taVNS significantly increased pupil dilation and performance during the EST. During the PLRT, active taVNS reduced and delayed pupil constriction. In the MEG, taVNS increased frontal-midline theta and alpha power during the EST, whereas occipital alpha power was reduced during both the EST and PLRT. Our findings provide evidence that phasic taVNS systematically modulates behavioral, pupillary, and electrophysiological parameters of LC-NA activity during cognitive processing. Moreover, we demonstrate for the first time that the pupillary light reflex can be used as a simple and effective proxy of taVNS efficacy. These findings have important implications for the development of noninvasive neuromodulation interventions for various cognitive and clinical applications.SIGNIFICANCE STATEMENTtaVNS has gained increasing attention as a noninvasive neuromodulation technique and is widely used in clinical and nonclinical research. Nevertheless, the exact mechanism of action of taVNS is not yet fully understood. By assessing physiology and behavior in a response conflict task in healthy humans, we demonstrate the first successful application of a phasic, noninvasive vagus nerve stimulation to improve cognitive control and to systematically modulate pupillary and electrophysiological markers of the noradrenergic system. Understanding the mechanisms of action of taVNS could optimize future clinical applications and lead to better treatments for mental disorders associated with noradrenergic dysfunction. In addition, we present a new taVNS-sensitive pupillary measure representing an easy-to-use biomarker for future taVNS studies

Evaluating two soil carbon models within the global land surface model JSBACH using surface and spaceborne observations of atmospheric CO₂

The trajectories of soil carbon (C) in the changing climate are of utmost importance, as soil carbon is a substantial carbon storage with a large potential to impact the atmospheric carbon dioxide (CO2) burden. Atmospheric CO2 observations integrate all processes affecting C exchange between the surface and the atmosphere. Therefore they provide a benchmark for carbon cycle models. We evaluated two distinct soil carbon models (CBALANCE and YASSO) that were implemented to a global land surface model (JSBACH) against atmospheric CO2 observations. We transported the biospheric carbon fluxes obtained by JSBACH using the atmospheric transport model TM5 to obtain atmospheric CO2. We then compared these results with surface observations from Global Atmosphere Watch (GAW) stations as well as with column XCO2 retrievals from the GOSAT satellite. The seasonal cycles of atmospheric CO2 estimated by the two different soil models differed. The estimates from the CBALANCE soil model were more in line with the surface observations at low latitudes (0 N–45 N) with only 1 % bias in the seasonal cycle amplitude (SCA), whereas YASSO was underestimating the SCA in this region by 32 %. YASSO gave more realistic seasonal cycle amplitudes of CO2 at northern boreal sites (north of 45 N) with underestimation of 15 % compared to 30 % overestimation by CBALANCE. Generally, the estimates from CBALANCE were more successful in capturing the seasonal patterns and seasonal cycle amplitudes of atmospheric CO2 even though it overestimated soil carbon stocks by 225 % (compared to underestimation of 36 % by YASSO) and its predictions of the global distribution of soil carbon stocks was unrealistic. The reasons for these differences in the results are related to the different environmental drivers and their functional dependencies of these two soil carbon models. In the tropical region the YASSO model showed earlier increase in season of the heterotophic respiration since it is driven by precipitation instead of soil moisture as CBALANCE. In the temperate and boreal region the role of temperature is more dominant. There the heterotophic respiration from the YASSO model had larger annual variability, driven by air temperature, compared to the CBALANCE which is driven by soil temperature. The results underline the importance of using sub-yearly data in the development of soil carbon models when they are used in shorter than annual time scales

How does the terrestrial carbon exchange respond to inter-annual climatic variations? : A quantification based on atmospheric CO2 data

The response of the terrestrial net ecosystem exchange (NEE) of CO2 to climate variations and trends may crucially determine the future climate trajectory. Here we directly quantify this response on inter-annual timescales by building a linear regression of inter-annual NEE anomalies against observed air temperature anomalies into an atmospheric inverse calculation based on long-term atmospheric CO2 observations. This allows us to estimate the sensitivity of NEE to inter-annual variations in temperature (seen as a climate proxy) resolved in space and with season. As this sensitivity comprises both direct temperature effects and the effects of other climate variables co-varying with temperature, we interpret it as "inter-annual climate sensitivity". We find distinct seasonal patterns of this sensitivity in the northern extratropics that are consistent with the expected seasonal responses of photosynthesis, respiration, and fire. Within uncertainties, these sensitivity patterns are consistent with independent inferences from eddy covariance data. On large spatial scales, northern extratropical and tropical interannual NEE variations inferred from the NEE-T regression are very similar to the estimates of an atmospheric inversion with explicit inter-annual degrees of freedom. The results of this study offer a way to benchmark ecosystem process models in more detail than existing effective global climate sensitivities. The results can also be used to gap-fill or extrapolate observational records or to separate inter-annual variations from longer-term trends.Peer reviewe