Co-located ecological data for exploring top- and subsoil carbon dynamics across grassland-woodland contrasts.

Soil organic carbon (SOC) is a soil health indicator and understanding dynamics changing SOC stocks will help achieving net zero goals. Here we present four datasets featuring 11,750 data points covering co-located aboveground and below-ground metrics for exploring ecosystem SOC dynamics. Five sites across England with an established land use contrast, grassland and woodland next to each other, were rigorously sampled for aboveground (n = 109), surface (n = 33 soil water release curves), topsoil, and subsoil metrics.

Topsoil porosity prediction across habitats at large scales using environmental variables.

Soil porosity and its reciprocal bulk density are important environmental state variables that enable modelers to represent hydraulic function and carbon storage. Biotic effects and their 'dynamic' influence on such state variables remain largely unknown for larger scales and may result in important, yet poorly quantified environmental feedbacks. Existing representation of hydraulic function is often invariant to environmental change and may be poor in some systems, particularly non-arable soils.

The potential to increase grassland soil C stocks by extending reseeding intervals is dependent on soil texture and depth.

Grasslands account for ∼30% of global terrestrial carbon (C), of which most is stored in soils and provide important ecosystem services including livestock and forage production. Reseeding of temporary grasslands on a 5-year cycle is a common management practice to rejuvenate sward productivity and reduce soil compaction, but is physically disruptive and may reduce soil organic carbon (SOC) stocks. However, research to date is limited, which impacts on the ability to optimise grassland management for climate change mitigation.

Analytical modelling of soil porosity and bulk density across the soil organic matter and land-use continuum.

The thin layer of soil at the earth's surface supports life, storing water and nutrients for plant uptake. These processes occur in the soil pore space, often half the soil volume, but our understanding of how this volume responds to environmental change is poor. Convention, has been to predict soil porosity, or its reciprocal bulk density (BD), from soil texture using pedotransfer functions (PTFs).

Dielectric Spectroscopy and Application of Mixing Models Describing Dielectric Dispersion in Clay Minerals and Clayey Soils.

The number of sensors, ground-based and remote, exploiting the relationship between soil dielectric response and soil water content continues to grow. Empirical expressions for this relationship generally work well in coarse-textured soils but can break down for high-surface area and intricate materials such as clayey soils. Dielectric mixing models are helpful for exploring mechanisms and developing new understanding of the dielectric response in porous media that do not conform to a simple empirical approach, such as clayey soils.