Global surface-ocean pCO2 and sea–air CO2 flux variability from an observation-driven ocean mixed-layer scheme

A temporally and spatially resolved estimate of the global surface-ocean CO₂ partial pressure field and the sea–air CO₂ flux is presented, obtained by fitting a simple data-driven diagnostic model of ocean mixed-layer biogeochemistry to surface-ocean CO₂ partial pressure data from the SOCAT v1.5 database. Results include seasonal, interannual, and short-term (daily) variations. In most regions, estimated seasonality is well constrained from the data, and compares well to the widely used monthly climatology by Takahashi et al. (2009). Comparison to independent data tentatively supports the slightly higher seasonal variations in our estimates in some areas. We also fitted the diagnostic model to atmospheric CO₂ data. The results of this are less robust, but in those areas where atmospheric signals are not strongly influenced by land flux variability, their seasonality is nevertheless consistent with the results based on surface-ocean data. From a comparison with an independent seasonal climatology of surface-ocean nutrient concentration, the diagnostic model is shown to capture relevant surface-ocean biogeochemical processes reasonably well. Estimated interannual variations will be presented and discussed in a companion paper

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

On observational and modelling strategies targeted at regional carbon exchange over continents

Estimating carbon exchange at regional scales is paramount to understanding feedbacks between climate and the carbon cycle, but also to verifying climate change mitigation such as emission reductions and strategies compensating for emissions such as carbon sequestration. This paper discusses evidence for a number of important shortcomings of current generation modelling frameworks designed to provide regional scale budgets from atmospheric observations. Current top-down and bottom-up approaches targeted at deriving consistent regional scale carbon exchange estimates for biospheric and anthropogenic sources and sinks are hampered by a number of issues: we show that top-down constraints using point measurements made from tall towers, although sensitive to larger spatial scales, are however influenced by local areas much more strongly than previously thought. On the other hand, classical bottom-up approaches using process information collected at the local scale, such as from eddy covariance data, need up-scaling and validation on larger scales. We therefore argue for a combination of both approaches, implicitly providing the important local scale information for the top-down constraint, and providing the atmospheric constraint for up-scaling of flux measurements. Combining these data streams necessitates quantifying their respective representation errors, which are discussed. The impact of these findings on future network design is highlighted, and some recommendations are given

Can guided introspection help avoid rationalization of meat consumption? Mixed-methods results of a pilot experimental study

The need for reducing meat consumption in affluent countries is increasingly recognized as crucial to minimizing carbon footprint. However, confronting individuals with rational arguments can prompt emotional discomfort, which is often relieved by engaging in rationalization processes stabilizing current consumption patterns. Mindfulness research suggests that making people aware of their emotional reactions through introspection can reduce these rationalization processes. In this mixed-method pilot experimental study, we inquired whether a single guided introspection, inspired by the micro-phenomenological interview technique, can alter individuals' experience of and abilities to deal with cognitive dissonance. Furthermore, we asked if such an intervention can stimulate attitude or intention changes concerning meat consumption. After inducing cognitive dissonance by exposing participants to pictures of the slaughter of a cow, the intervention group (n = 36) participated in the guided introspection, while the control group (n = 39) played solitaire. Self-report questionnaire measures of emotional discomfort, rationalization strategies, and attitudes towards meat consumption were administered before and after the intervention. Also, open-ended responses to participants’ experience of the study were analyzed. Quantitative results show significantly lower negative attitudes toward reducing meat consumption in the intervention group compared to the control group (partial 2 = 0.107). Qualitative results indicate that these participants are more aware of negative emotions while engaging less in rationalization strategies. We conclude that our study indicates some potential for guided introspection to affect dissonance resolution and provide suggestions for future research

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

COCAP : a carbon dioxide analyser for small unmanned aircraft systems

Unmanned aircraft systems (UASs) could provide a cost-effective way to close gaps in the observation of the carbon cycle, provided that small yet accurate analysers are available. We have developed a COmpact Carbon dioxide analyser for Airborne Platforms (COCAP). The accuracy of COCAP's carbon dioxide (CO2) measurements is ensured by calibration in an environmental chamber, regular calibration in the field and by chemical drying of sampled air. In addition, the package contains a lightweight thermal stabilisation system that reduces the influence of ambient temperature changes on the CO2 sensor by 2 orders of magnitude. During validation of COCAP's CO2 measurements in simulated and real flights we found a measurement error of 1.2 mu mol mol(-1) or better with no indication of bias. COCAP is a self-contained package that has proven well suited for the operation on board small UASs. Besides carbon dioxide dry air mole fraction it also measures air temperature, humidity and pressure. We describe the measurement system and our calibration strategy in detail to support others in tapping the potential of UASs for atmospheric trace gas measurements.Peer reviewe

Schwann cells and mesenchymal stem cells in laminin- or fibronectin-aligned matrices and regeneration across a critical size defect of 15 mm in the rat sciatic nerve

OBJECTIVE Artificial nerve guides are being developed to substitute for autograft repair after peripheral nerve injuries. However, the use of conduits is limited by the length of the gap that needs to be bridged, with the success of regeneration highly compromised in long gaps. Addition of aligned proregenerative cells and extracellular matrix (ECM) components inside the conduit can be a good strategy to achieve artificial grafts that recreate the natural environment offered by a nerve graft. The purpose of this study was to functionalize chitosan devices with different cell types to support regeneration in limiting gaps in the rat peripheral nerve. METHODS The authors used chitosan devices combined with proteins of the ECM and cells in a rat model of sciatic nerve injury. Combinations of fibronectin and laminin with mesenchymal stem cells (MSCs) or Schwann cells (SCs) were aligned within tethered collagen-based gels, which were placed inside chitosan tubes that were then used to repair a critical-size gap of 15 mm in the rat sciatic nerve. Electrophysiology and algesimetry tests were performed to analyze functional recovery during the 4 months after injury and repair. Histological analysis was performed at the midlevel and distal level of the tubes to assess the number of regenerated myelinated fibers. RESULTS Functional analysis demonstrated that SC-aligned scaffolds resulted in 100% regeneration success in a 15-mm nerve defect in this rat model. In contrast, animals that underwent repair with MSC-aligned constructs had only 90% regeneration success, and those implanted with acellular bridges had only 75% regeneration success. CONCLUSIONS These results indicate that the combination of chitosan conduits with ECM-enriched cellular gels represents a good alternative to the use of autografts for repairing long nerve gaps