Changes in pore networks and readily dispersible soil following structure liming of clay soils

Structure liming aims to improve soil structure (i.e., the spatial arrangement of particles and pores) and its stability against external and internal forces. Effects of lime application on soil structure have received considerable interest, but only a few studies have investigated effects on macro- and mesopore networks. We used X-ray computed tomography to image macropore networks (phi >= 0.3 mm) in soil columns and mesopores (phi > 0.01 mm) in soil aggregates from three field sites with (silty) clay soils after the application of structure lime (3.1 t ha(-1) or 5 t ha(-1)- of CaO equivalent). Segmented X-ray images were used to quantify soil porosity and pore size distributions as well as to analyse pore architecture and connectivity metrics. In addition, we investigated the amount of readily dispersible soil particles. Our results demonstrate that structure liming affected both, macropore networks and amounts of readily dispersible soil to different degrees, depending on the field site. Significant changes in macropore networks and amounts of readily dispersible soil after lime application were found for one of the three field sites, while only some indications for similar changes were observed at the other two sites. Overall, structure liming tended to decrease soil macroporosity and shift pore size distribution from larger (epsilon( >100 mm) ) and medium sized macropores (epsilon( 0.3-1.0) (mm)) towards smaller macropores (epsilon( 0.1-0.3) (mm)). Furthermore, liming tended to decrease the critical and average pore diameters, while increasing the surface fractal dimension and specific surface area of macropore network. Structure liming also reduced the amounts of readily dispersible soil particles. We did not find any changes in mesopore network properties within soil aggregates or biopore networks in columns and aggregates. The effects of lime on macropore networks remain elusive, but may be caused by the formation of hydrate phases and carbonates which occupy pore space

Differences in substrate use efficiency: impacts of microbial community composition, land use management, and substrate complexity

Microbial substrate use efficiency is an important property in process-based soil organic matter models, but is often assumed to be constant in mechanistic models. However, previous studies question if a constant efficiency is appropriate, in particular when evaluating carbon (C) cycling across temperatures and various substrates. In the present study, we evaluated the relation between substrate use efficiency, microbial community composition and substrate complexity in contrasting long-term management regimes (47-49 years of either arable, ley farming, grassland, or forest systems). Microbial community composition was assessed by phospholipid fatty acid analysis and three indices of substrate use efficiencies were considered: (i) thermodynamic efficiency, (ii) calorespirometric ratio, and (iii) metabolic quotient. Three substrates, d-glucose, l-alanine, or glycogen, varying in complexity, were added separately to soils, and heat production as well as C mineralization was determined over a 32-h incubation period at 12.5 A degrees C. Microbial communities from forest systems were most efficient in utilizing substrates, supporting our hypothesis that maturing ecosystems become more efficient. These changes in efficiency were linked to microbial community composition with fungi and Gram-negative bacteria being important biomarkers. Despite our initial hypothesis, complex substrate such as glycogen was utilized most efficiently. Our findings emphasize that differences in land use management systems as well as the composition of soil organic matter need to be considered when modelling C dynamics in soils. Further research is required to establish and evaluate appropriate proxies for substrate use efficiencies in various ecosystems

Soil organic carbon models need independent time-series validation for reliable prediction

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

Decomposition of soil organic matter under a changing climate

Soil organic matter is the largest carbon (C) pool in the terrestrial C cycle, and soil CO₂ emissions surpass anthropogenic emissions from fossil fuel combustion by a factor of nine. Therefore, mechanisms controlling C stabilisation in soils and its feedback to climate change are widely debated. During decomposition, microbial substrate-use efficiency is an important property because it determines the allocation of substrate C to biosynthesis and respiratory losses. High efficiency values indicate that C primarily remains in soils while low efficiency implies that C is primarily lost into the atmosphere. Despite empirical evidence that efficiency is temperature sensitive, traditional Earth system models treat this property as a constant. The aim of this thesis was to improve our mechanistic understanding of drivers regulating substrate-use efficiency with special consideration to climate change. It investigated the impacts of (i) temperature, (ii) microbial community composition and (iii) substrate quality on substrate-use efficiency. Within the thesis, a microbial energetics approach was applied and further developed using isothermal calorimetry. Further, the thesis compared common approaches for measuring microbial substrate-use efficiency, and the implications of the resultant empirical data for projected C stocks were tested using a modelling approach. Substrate-use efficiency was generally temperature sensitive and decreased with increasing temperature. The observed temperature responses were non-linear and varied across land use management systems. The changes in substrate-use efficiency with temperature were driven rather by changes in microbial physiology than by shifts in active microbial communities. Nevertheless, fungi and Gram-negative bacteria tended towards relatively higher efficiencies. Efficiencies varied among utilised substrates, but substrate quality per se was a poor proxy for efficiency. Projected losses from soil C stocks varied across land use management systems and were up to 39 % and 15 % for grassland and forest systems, respectively. Results from the modelling approach confirmed that substrate-use efficiency is one of the factors to which soil C stocks react most sensitively. Findings from this thesis emphasise the importance of furthering our understanding of substrate-use efficiency for reliable climate projections

Decomposition of Soil Organic Matter under a Changing Climate: A Matter of Efficiency

Soil organic matter is the largest carbon (C) pool in the terrestrial C cycle, and soil CO 2emissions surpass anthropogenic emissions from fossil fuel combustion by a factor ofnine. Therefore, mechanisms controlling C stabilisation in soils and its feedback toclimate change are widely debated. During decomposition, microbial substrate-useefficiency is an important property because it determines the allocation of substrate Cto biosynthesis and respiratory losses. High efficiency values indicate that C primarilyremains in soils while low efficiency implies that C is primarily lost into theatmosphere. Despite empirical evidence that efficiency is temperature sensitive,traditional Earth system models treat this property as a constant.The aim of this thesis was to improve our mechanistic understanding of driversregulating substrate-use efficiency with special consideration to climate change. Itinvestigated the impacts of (i) temperature, (ii) microbial community composition and(iii) substrate quality on substrate-use efficiency. Within the thesis, a microbialenergetics approach was applied and further developed using isothermal calorimetry.Further, the thesis compared common approaches for measuring microbial substrate-use efficiency, and the implications of the resultant empirical data for projected Cstocks were tested using a modelling approach.Substrate-use efficiency was generally temperature sensitive and decreased withincreasing temperature. The observed temperature responses were non-linear and variedacross land use management systems. The changes in substrate-use efficiency withtemperature were driven rather by changes in microbial physiology than by shifts inactive microbial communities. Nevertheless, fungi and Gram-negative bacteria tendedtowards relatively higher efficiencies. Efficiencies varied among utilised substrates, butsubstrate quality per se was a poor proxy for efficiency. Projected losses from soil Cstocks varied across land use management systems and were up to 39 % and 15 % forgrassland and forest systems, respectively. Results from the modelling approachconfirmed that substrate-use efficiency is one of the factors to which soil C stocks reactmost sensitively. Findings from this thesis emphasise the importance of furthering ourunderstanding of substrate-use efficiency for reliable climate projections.La matière organique du sol est le plus grand réservoir de carbone (C) dans le cycle terrestre du C, et les émissions de CO 2 du sol dépassent les émissions anthropiques provenant de la combustion de combustibles fossiles d'un facteur de 1,5.des sols dépassent de neuf fois les émissions anthropiques provenant de la combustion de combustibles fossiles.neuf. Par conséquent, les mécanismes contrôlant la stabilisation du carbone dans les sols et sa rétroaction sur le changement climatique sont largement débattus.changement climatique sont largement débattus. Au cours de la décomposition, l'efficacité microbienne d'utilisation du substrat est une propriété importante car elle détermine l'efficacité de la décomposition.microbienne est une propriété importante car elle détermine l'allocation du substrat Cdu substrat à la biosynthèse et aux pertes respiratoires. Des valeurs d'efficacité élevées indiquent que le Creste principalement dans les sols, tandis qu'une faible efficacité implique que le C est principalement perdu dans l'atmosphère.l'atmosphère. Malgré les preuves empiriques que l'efficacité est sensible à la température,les modèles traditionnels du système terrestre traitent cette propriété comme une constante.L'objectif de cette thèse était d'améliorer notre compréhension mécanique des facteurs qui régulent l'efficacité de l'utilisation du substrat à l'aide de modèles spéciaux.régulant l'efficacité de l'utilisation des substrats, avec une attention particulière pour le changement climatique. Elle aElle a étudié les impacts de (i) la température, (ii) la composition de la communauté microbienne et (iii) la qualité du substrat sur l'efficacité d'utilisation du substrat.(iii) de la qualité du substrat sur l'efficacité d'utilisation du substrat. Dans le cadre de la thèse, une approche de l'énergétique microbienne a été appliquée et approfondie.énergétique microbienne a été appliquée et développée à l'aide de la calorimétrie isotherme.En outre, la thèse a comparé les approches courantes pour mesurer l'efficacité de l'utilisation du substrat microbien, et les implications de la calorimétrie isotherme.et les implications des données empiriques résultantes pour les stocks de Cont été testées à l'aide d'une approche de modélisation.L'efficacité d'utilisation du substrat était généralement sensible à la température et diminuait avec l'augmentation de la température.avec l'augmentation de la température. Les réponses observées à la température n'étaient pas linéaires et variaient en fonction des systèmes de gestion de l'utilisation des sols.et variaient selon les systèmes de gestion de l'utilisation des terres. Les changements dans l'efficacité de l'utilisation du substrat en fonction de la température étaient plutôt dus à des changements dans l'activité microbienne.Les changements dans l'efficacité d'utilisation du substrat en fonction de la température étaient plutôt dus à des changements dans la physiologie microbienne qu'à des changements dans les communautés microbiennes actives.communautés microbiennes actives. Néanmoins, les champignons et les bactéries Gram-négatives ont eu tendance à atteindre des efficacités relativement plus élevées.vers des efficacités relativement plus élevées. Les efficacités varient selon les substrats utilisés, maisLa qualité du substrat en tant que telle n'est pas un bon indicateur de l'efficacité. Les pertes prévues de stocks de Cdu sol varient selon les systèmes de gestion de l'utilisation des terres et atteignent respectivement 39 % et 15 % pour les prairies et les forêts.respectivement pour les prairies et les forêts. Les résultats de l'approche de modélisationont confirmé que l'efficacité de l'utilisation des substrats est l'un des facteurs auxquels les stocks de carbone dans le sol réagissent de la manière la plus sensible.les plus sensibles. Les résultats de cette thèse soulignent l'importance d'approfondir notre compréhension de l'efficacité de l'utilisation des substrats pour des systèmes fiables et durables.compréhension de l'efficacité de l'utilisation des substrats pour des projections climatiques fiables

Turning points in climate change adaptation

Concerned decision makers increasingly pose questions as to whether current management practices are able to cope with climate change and increased climate variability. This signifies a shift in the framing of climate change from asking what its potential impacts are to asking whether it induces policy failure and unacceptable change. In this paper, we explore the background, feasibility, and consequences of this new framing. We focus on the specific situation in which a social-political threshold of concern is likely to be exceeded as a result of climate change, requiring consideration of alternative strategies. Action is imperative when such a situation is conceivable, and at this point climate change becomes particularly relevant to decision makers. We call this situation an “adaptation turning point.” The assessment of adaptation turning points converts uncertainty surrounding the extent of a climate impact into a time range over which it is likely that specific thresholds will be exceeded. This can then be used to take adaptive action. Despite the difficulty in identifying adaptation turning points and the relative newness of the approach, experience so far suggests that the assessment generates a meaningful dialogue between stakeholders and scientists. Discussion revolves around the amount of change that is acceptable; how likely it is that unacceptable, or more favorable, conditions will be reached; and the adaptation pathways that need to be considered under these circumstances. Defining and renegotiating policy objectives under climate change are important topics in the governance of adaptation

Soil organic carbon models need independent time-series validation for reliable prediction

International audienceAbstract 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