Soil amendment with artificial black carbon (BC; biomass transformed by incomplete combustion) has the potential to mitigate climate change. Nevertheless, the accurate quantification of BC in soil remains a critical issue. Here, we successfully used dynamic thermal analysis (DTA) to quantify centennial BC in soil. We demonstrate that DTA is largely under-exploited despite providing rapid and low-cost quantitative information over the range of soil organic matter.

We compared miniaturised visible and near-infrared spectrometers to a portable visible–near-infrared instrument, which is more expensive. Statistical and machine learning algorithms were used to model 29 key soil health indicators. Accuracy of the miniaturised spectrometers was comparable to the portable system. Soil spectroscopy with these tiny sensors is cost-effective and could diagnose soil health, help monitor soil rehabilitation, and deliver positive environmental and economic outcomes.

Soil ecological stoichiometry offers a tool to explore the distribution, cycling, limitation, and balance of chemical elements. This study improved the understanding of soil organic carbon and nutrient dynamics in tea plantation ecosystems and also provided supplementary information for soil ecological stoichiometry in global terrestrial ecosystems.

Soil structure is of central importance for soil functions. It is, however, ill defined. With the increasing availability of X-ray CT scanners, more and more soils are scanned and an undisturbed image of the soil's structure is produced. Often, a qualitative description is all that is derived from these images. We provide now a web-based Soil Structure Library where these images can be evaluated in a standardized quantitative way and can be compared to a world-wide data set.

Although present in food security key areas, Arenosols carbon stocks are barely studied. A 150-year-old land use change in a Mediterranean Arenosol showed a loss from 50 Gt C ha^-1 to 3 Gt C ha^-1 after grape cultivation. ¹⁴C showed that deep ploughing in a vineyard plot redistributed the remaining microbial carbon both vertically and horizontally. Despite the drastic degradation of the organic matter pool, Arenosols would have a high carbon storage potential, targeting the 4 per 1000 initiative.

Digital soil mapping (DSM) allows us to regionalize soil properties by relating them to environmental covariates with the help of an empirical model. Legacy soil data provide a valuable basis to generate high-resolution soil maps with DSM. We studied the usefulness of data-clustering methods to tackle potential sampling bias in legacy soil data while applying DSM for soil texture regionalization. Clustering has proved to be useful in various steps of the DSM process.

Maps of soil properties made by machine learning techniques are increasingly applied in Earth surface process modelling and agronomy. Maps of the same area made by different methods appear quite different and also differ from field-based polygon soil survey maps. We explore these differences both visually and numerically, using methods that quantify the spatial patterns. Readers can apply the methods to their areas of interest in the USA with the supplied R Markdown scripts.

As soil carbon has become a key component of climate-smart agriculture, the demand for high-resolution maps has increased drastically. Meanwhile, machine learning algorithms are becoming more widely used and are opening up new solutions in soil mapping. This paper shows which algorithms perform best, how soil inventory data can be most efficiently used for digital soil mapping, and the different available options and methods to derive high-resolution soil carbon data at the large regional scale.

How to effectively convert corn straw into humic substances and return them to the soil in a relatively stable form is a concerning topic. Through a 360 d field experiment under equal carbon (C) mass, we found that return of the fermented corn straw treated with Trichoderma reesei to the field is more valuable and conducive to increasing easily oxidizable organic C, humus C content, and carbon pool management index than the direct application of corn straw.

The potential to reverse the negative effects caused in topsoil by inversion tillage, using alternative agricultural practices, was evaluated. Reduced and no tillage, and additions of manure/compost, improved topsoil structure and OC content. Residue retention had a positive impact on structure. We concluded that the negative effects of inversion tillage can be mitigated by reducing tillage intensity or adding organic materials, optimally combined with non-inversion tillage.

We explored the effects of mild alternate wetting and drying (AWD) irrigation combined with rice straw return on N₂O emissions and rice yield through rice pot experiments. Mild AWD irrigation significantly increased both N₂O and yield-scaled N₂O emissions. The addition of rice straw under mild AWD irrigation could promote N₂O emissions. Mild AWD irrigation could reduce soil-nitrogen uptake by rice when urea was applied. Mild AWD irrigation reduced rice aboveground biomass but not rice yield.

This study shows how an innovative soil and crop management including no-tillage, cover crops and organic amendments is able to improve the topsoil physical quality compared to conventional management for rainfed cereal cropping in a semi-arid Mediterranean area in Navarre (Spain).

Major soil carbon pools and fluxes were assessed along a climatic gradient expanding 4 °C in mean annual temperature for two important boreal conifer forest stand types. Species and a warmer climate affected soil organic matter (SOM) cycling but not stocks. Contrarily to common hypotheses, SOM lability was not reduced by warmer climatic conditions and perhaps increased. Results apply to cold and wet conditions and a stable vegetation composition along the climate gradient.

We found that climatic, edaphic, plant and microbial variables jointly affect soil inorganic carbon (SIC) stock in Tibetan grasslands, and biotic factors have a larger contribution than abiotic factors to the variation in SIC stock. The effects of microbial and plant variables on SIC stock weakened with soil depth, while the effects of edaphic variables strengthened. The contrasting responses and drivers of SIC stock highlight differential mechanisms underlying SIC preservation with soil depth.

The chemical quality of biomass can be described with holocellulose (relatively easily decomposable by microorganisms) and Klason lignin (relatively recalcitrant) contents. Measuring both is laborious. In a recent study, models have been proposed which can predict both quicker from mid-infrared spectra. However, it has not been analyzed if these models make correct predictions for biomass in soils and how to improve them. We provide such a validation and a strategy for their improvement.

Biological soil crusts (biocrusts) stabilize the soil surface mainly in arid regions but are also present in Mediterranean and humid climates. We studied this stabilizing effect through wet and dry sieving along a large climatic gradient in Chile and found that the stabilization of soil aggregates persists in all climates, but their role is masked and reserved for a limited number of size fractions under humid conditions by higher vegetation and organic matter contents in the topsoil.

Historically, many peatlands in the boreal region have been drained for timber production. Given the prospects of a drier future due to climate change, wetland restorations are now increasing. Better maps hold the key to insights into restoration targets and land-use management policies, and maps are often the number one decision-support tool. We use an AI-developed soil moisture map based on laser scanning data to illustrate how the mapping of peatlands can be improved across an entire nation.