The study evaluates the effect of trachyte and basalt powders on soil and maize yield in the Sudano-Sahelian zone of Cameroon. Texture, base saturation, and organic carbon indicate moderate limitations. The climate is favourable for maize cultivation. Rock powder application significantly improves yield, with basalt being more effective than trachyte. The advantage of using rock powders lies in their environmental benefits, long-term effectiveness, and more affordable cost.

Soil acidity below the plow layer harms crops and is difficult to correct with surface lime applications. Adding organic matter may help lime move deeper, but its effectiveness remains uncertain. We set up column leaching experiments to identify the mechanisms of subsurface liming. We found that combining lime with organic amendments can improve deeper soil conditions, but only in soils that do not strongly retain organic carbon. These insights can help develop better soil management strategies.

Fungal necromass carbon (FNC) contribution to mineral-associated organic carbon (MAOC) and particulate organic carbon (POC) was higher than bacterial necromass carbon (BNC). In 0–20 cm, FNC and BNC contributed more to MAOC, their contributions shifted toward POC in 20–100 cm. Microbial necromass carbon was affected by total nitrogen, mean annual rainfall, and electrical conductance in 0–20, while affected by available potassium, SOC, and mean annual temperature in 20–100.

Uneven data collection can make it hard to predict soil properties accurately in new areas. We developed a method to show where predictions are reliable and where more data is needed. By training a model in one region and applying it to another, we found that our approach effectively recognized river patterns but was biased toward overrepresented soil types. This tool can guide smarter data collection, helping improve predictions and make better use of resources for soil management.

Permafrost soils store vast amounts of organic carbon, key to understanding climate change. This study uses machine learning and combines existing data with new field data to create detailed regional maps of soil carbon and nitrogen stocks for the Yukon coastal plain. The results show how soil properties vary across the landscape highlighting the importance of data selection for accurate predictions. These findings improve carbon storage estimates and may aid regional carbon budget assessments.

Cover crops (CC) help capture nitrates, but their role in mitigating pesticide impacts has been less studied. We evaluated how two CC densities (vs. bare soil) affected pesticide residues in soil and solution over 3 months in a greenhouse pot experiment. Our results show that well-developed CCs, by sustaining active edaphic microbiota, enhance pesticide biodegradation across a wide range of active substances. This further confirms the role of CCs in groundwater protection.

We developed a multiscale simulation model that combines 3D plant architecture with carbon cycling in the rhizosphere and soil to understand how dry spells impact carbon and water flows, focusing on the activity of the soil microbes. We found that the microbial communities’ characteristics and dry spells’ start dates significantly affect rhizosphere CO₂ emissions and carbon cycling. This model can help understand the effects of climate change on plant growth and soil organic matter dynamics.

Farmers need precise information about their fields to use water, fertilizers, and other resources efficiently. This study combines underground soil data and satellite images to create detailed field maps using advanced machine learning. By testing different ways of processing data, we ensured a balanced and accurate approach. The results help farmers manage their land more effectively, leading to better harvests and more sustainable farming practices.

Studies on how microbes use C in soils typically assume oxic conditions, but often overlook anaerobic processes and extracellular metabolite release. We examined how O₂ and Fe content affect C mineralisation in forest soils by tracking 13C flow into biomass, CO₂, metabolites and the active microbes under oxic and anoxic conditions. Results showed that anoxic conditions preserved C longer, especially in the high-Fe soils. We conclude that microbial exudates play a role in anoxic C stabilisation.

Water-soluble organic carbon (WSOC) is crucial in boreal forests, but its behavior across soil depths is poorly understood. Our study found that shallow soils contain complex WSOC molecules with high biodegradability, while deeper soils have simpler molecules that are also highly biodegradable. These results reveal the significant role of WSOC in carbon cycling across soil layers, improving our understanding of carbon dynamics in boreal ecosystems impacted by climate change.

To understand how warming will change the dynamics of roots across soil profile, we took usage of a long-term field warming experiment and incubated ¹³C-labelled roots at three different depths. After 3 years of incubation, warming only accelerate the decomposition of root in topsoil (< 20 cm) but not in subsoil (> 20 cm). Hydrolysable lipids derived from root, which are considered as recalcitrant compounds and could be preserved for long time in the soil, are also decomposed faster in topsoil.

Long-term cropping reduced total stocks of soil organic carbon (SOC). This study examined the microscale processes which regulates the preservation of SOC under long-term cropping, with an understanding of this being essential for predicting SOC persistence and to identify approaches to re-building SOC stocks in agroecosystems.

Controlled experiments show that adding phosphorus (P) to soils relieves microbial P limitation to degrade soil organic carbon (SOC). No alternative explanation currently exists. We show increased desorption of OC with P supply in subtropical forests, which was used to satisfy microbial C-limitation induced while incorporating P into microbial biomass, and driving CO₂ emission, without further SOC degradation. We provide newer an alternative mechanism vital for constraining land C models.