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Abstract Numerical models are crucial to understand and/or predict past and future soil organic carbon dynamics. For those models aiming at prediction, validation is a critical step to gain confidence in projections. With a comprehensive review of ~250 models, we assess how models are validated depending on their objectives and features, discuss how validation of predictive models can be improved. We find a critical lack of independent validation using observed time series. Conducting such validations should be a priority to improve the model reliability. Approximately 60% of the models we analysed are not designed for predictions, but rather for conceptual understanding of soil processes. These models provide important insights by identifying key processes and alternative formalisms that can be relevant for predictive models. We argue that combining independent validation based on observed time series and improved information flow between predictive and conceptual models will increase reliability in predictions. 

Abstract Soils store more carbon than other terrestrial ecosystems 1,2 . How soil organic carbon (SOC) forms and persists remains uncertain 1,3 , which makes it challenging to understand how it will respond to climatic change 3,4 . It has been suggested that soil microorganisms play an important role in SOC formation, preservation and loss 5–7 . Although microorganisms affect the accumulation and loss of soil organic matter through many pathways 4,6,8–11 , microbial carbon use efficiency (CUE) is an integrative metric that can capture the balance of these processes 12,13 . Although CUE has the potential to act as a predictor of variation in SOC storage, the role of CUE in SOC persistence remains unresolved 7,14,15 . Here we examine the relationship between CUE and the preservation of SOC, and interactions with climate, vegetation and edaphic properties, using a combination of global-scale datasets, a microbial-process explicit model, data assimilation, deep learning and meta-analysis. We find that CUE is at least four times as important as other evaluated factors, such as carbon input, decomposition or vertical transport, in determining SOC storage and its spatial variation across the globe. In addition, CUE shows a positive correlation with SOC content. Our findings point to microbial CUE as a major determinant of global SOC storage. Understanding the microbial processes underlying CUE and their environmental dependence may help the prediction of SOC feedback to a changing climate. 

Abstract. Elevated atmospheric CO2 concentration is expectedto increase leaf CO2 assimilation rates, thus promoting plant growthand increasing leaf area. It also decreases stomatal conductance, allowingwater savings, which have been hypothesized to drive large-scale greening,in particular in arid and semiarid climates. However, the increase in leafarea could reduce the benefits of elevated CO2 concentration through soilwater depletion. The net effect of elevated CO2 on leaf- andcanopy-level gas exchange remains uncertain. To address this question, wecompare the outcomes of a heuristic model based on the Partitioning ofEquilibrium Transpiration and Assimilation (PETA) hypothesis and three modelvariants based on stomatal optimization theory. Predicted relative changes in leaf-and canopy-level gas exchange rates are used as a metric of plant responsesto changes in atmospheric CO2 concentration. Both model approaches predictreductions in leaf-level transpiration rate due to decreased stomatalconductance under elevated CO2, but negligible (PETA) or no(optimization) changes in canopy-level transpiration due to the compensatoryeffect of increased leaf area. Leaf- and canopy-level CO2 assimilationis predicted to increase, with an amplification of the CO2fertilization effect at the canopy level due to the enhanced leaf area. Theexpected increase in vapour pressure deficit (VPD) under warmer conditions isgenerally predicted to decrease the sensitivity of gas exchange toatmospheric CO2 concentration in both models. The consistentpredictions by different models that canopy-level transpiration varieslittle under elevated CO2 due to combined stomatal conductancereduction and leaf area increase highlight the coordination ofphysiological and morphological characteristics in vegetation to maximizeresource use (here water) under altered climatic conditions.