Carbono orgânico dissolvido e biodisponibilidade de N e P como indicadores de qualidade do solo

Nas últimas décadas, qualidade do solo tem se tornado um tópico importante na ciência do solo. Embora esforços consideráveis tenham sido dedicados com o intuito de definir "qualidade do solo", ainda não há um conceito amplamente aceito pela comunidade cientifica. A seleção de índices qualitativos para definir qualidade do solo é uma tarefa extremamente difícil, e diversas propriedades químicas, físicas e biológicas tem sido sugeridas como potenciais indicadores. A matéria orgânica do solo está associada com processos químicos, físicos e biológicos no solo, e, portanto, é considerada um dos melhores indicadores de qualidade do solo. O manejo do solo pode influenciar significativamente a dinâmica do carbono orgânico e o ciclo de N, P, e S. Entretanto, mudanças na concentração total da matéria organica em resposta ao manejo pode ser dificil de ser detectada devido à variabilidade natural do solo. Quando comparada com a matéria orgânica total do solo, a fração mais prontamente disponível, como o carbono orgânico dissolvido (COD), é mais sensível às mudanças no manejo do solo a curto e médio prazo e, portanto, pode ser utilizada como indicador fundamental de qualidade do solo ou das alterações das condições naturais. Embora a fração dissolvida represente apenas uma pequena porção da matéria orgânica total do solo, o COD é móvel no solo e constitui uma importante fonte de C para os microorganismos, podendo facilmente refletir os efeitos de diferentes sistemas de manejo. Inúmeros métodos são utilizados para caracterizar o COD, mas os processos que influenciam sua mineralização e a disponibilidade dos elementos associado com a matéria orgânica (N, P, e S) ainda não são completamente entendidos. Pesquisas futuras devem buscar entender os processos que governam a dinâmica de nutrientes e do COD e como os mesmos afetam a qualidade do solo.Soil quality has become an important issue in soil science. Considerable attempts have been made to define soil quality, but a general concept has not yet been accepted by the scientific community. The selection of quantitative indices for soil quality is extremely difficult, and a considerable number of chemical, physical, and biochemical properties have been suggested as potential indicators of soil quality. Because soil organic matter (SOM) can be associated with different soil chemical, physical and biological processes, it has been widely considered as one of the best soil quality indicator. Land use can significantly influence dynamics of organic carbon and N, P, and S cycle. However, changes in total soil organic carbon (SOC) contents in response to land use may be difficult to detect because of the natural soil variability. In the short to medium term, biological properties and readily decomposable fractions of SOC, such as dissolved organic carbon (DOC), are much more sensitive to soil management than is SOM as a whole, and can be used as a key indicator of soil natural functions. Despite the fact that labile C accounts for a small portion of the total organic matter in the soils, DOC is the most mobile and important C-source for microorganisms, and can easily reflect the effects of land use on soil quality. Although several methods are used to characterize DOC, the factors influencing mineralization and bioavailability of elements associated with organic matter (N, P, and S) remains unclear. Future research should focus on the processes that govern DOC and nutrient dynamics and how they affect soil quality

Model-based analyses: Promises, pitfalls, and example applications to the study of cognitive control

We discuss a recent approach to investigating cognitive control, which has the potential to deal with some of the challenges inherent in this endeavour. In a model-based approach, the researcher defines a formal, computational model that performs the task at hand and whose performance matches that of a research participant. The internal variables in such a model might then be taken as proxies for latent variables computed in the brain. We discuss the potential advantages of such an approach for the study of the neural underpinnings of cognitive control and its pitfalls, and we make explicit the assumptions underlying the interpretation of data obtained using this approach

Large-Eddy Simulations of Magnetohydrodynamic Turbulence in Heliophysics and Astrophysics

We live in an age in which high-performance computing is transforming the way we do science. Previously intractable problems are now becoming accessible by means of increasingly realistic numerical simulations. One of the most enduring and most challenging of these problems is turbulence. Yet, despite these advances, the extreme parameter regimes encountered in space physics and astrophysics (as in atmospheric and oceanic physics) still preclude direct numerical simulation. Numerical models must take a Large Eddy Simulation (LES) approach, explicitly computing only a fraction of the active dynamical scales. The success of such an approach hinges on how well the model can represent the subgrid-scales (SGS) that are not explicitly resolved. In addition to the parameter regime, heliophysical and astrophysical applications must also face an equally daunting challenge: magnetism. The presence of magnetic fields in a turbulent, electrically conducting fluid flow can dramatically alter the coupling between large and small scales, with potentially profound implications for LES/SGS modeling. In this review article, we summarize the state of the art in LES modeling of turbulent magnetohydrodynamic (MHD) ows. After discussing the nature of MHD turbulence and the small-scale processes that give rise to energy dissipation, plasma heating, and magnetic reconnection, we consider how these processes may best be captured within an LES/SGS framework. We then consider several special applications in heliophysics and astrophysics, assessing triumphs, challenges,and future directions

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries