Soil health assessment frameworks translate soil measurements into scores that inform management decisions, yet different frameworks can yield different conclusions about the same soils. Few studies evaluate how framework design shapes these interpretations. Using a management-explicit dataset (n = 262) from Ontario’s Greater Golden Horseshoe, we compared distribution-based scoring with reference-based benchmarking. We sampled Luvisols, Gleysols, and Cambisols planted in grains and oilseeds with contrasting tillage and cover cropping, alongside perennial references, and evaluated indicator redundancy, management sensitivity, and the influence of sampling design and statistical inference. Carbon and nitrogen indicators were strongly correlated. Aggregate stability by image analysis was less correlated with carbon indicators and robust to organic amendment effects. All indicators except aggregate stability by wet sieving showed management sensitivity. Both frameworks yielded similar score rank ordering, though distribution-based scores were lower because row-cropped and perennial soils were pooled. Interpretations were sensitive to database composition under the distribution approach and to reference management types under the reference approach. Assessment outcomes therefore depend on framework design, experimental design, and assumptions, not measurements alone. For soil health frameworks to be effective decision-support tools, they must be transparent about assumptions, responsive to and inclusive of management differences, and based on balanced representation of the soils and management systems they aim to inform.
Plants are important drivers of C cycling in vegetated terrestrial ecosystems and are commonly assumed to acquire C solely from the atmosphere. However, plant-physiological studies indicate that plants can also take up C from the soil via their roots. We used two complementary 13C-tracer experiments to determine under which conditions root-mediated C uptake occurs and how net tracer incorporation varies with C substrate, growth medium, soil texture, and plant functional type. First, seedlings of Plantago lanceolata and Picea abies were grown in nutrient solutions containing 13C-labelled glucose or L-lysine. After four weeks, 2.0–5.5
Understanding how soil organic carbon (SOC) changes over time and depth in agricultural systems is critical for informing soil health stewardship and carbon monitoring in SOC-focused programs. Yet, knowledge is limited on how SOC trajectories vary across depth and among different fractions and soil health metrics—particulate organic carbon (POC), mineral-associated organic carbon (MAOC), permanganate oxidizable carbon (POXC), and mineralizable carbon (MINC). We analyzed archived soils from three long-term Midwest trials: two in Nebraska comparing residue removal and retention in continuous corn over 10 and 19 years, and one at the Great Lakes Bioenergy Research Center (GLBRC) comparing continuous corn and perennial switchgrass after 9 years. At the 19-year Nebraska experiment, increasing plant inputs through residue retention enhanced SOC, particularly in surface soils. At both Nebraska experiments, POXC more closely tracked total SOC than MAOC, POC, or MINC. At GLBRC, surface-level SOC losses occurred under corn, whereas switchgrass exhibited whole-profile SOC losses. Across sites, MAOC showed minimal change, MINC often declined, and POC responses were variable, while POXC was the most reliable indicator of SOC gains and losses. Extending sampling beyond surface soils revealed larger changes, highlighting that surface-focused measurements alone can misrepresent SOC dynamics. Overall, long-term monitoring across multiple SOC fractions and depths is essential for accurately assessing SOC change under different management practices. Our findings provide actionable insights for regenerative agroecosystems and highlight the potential use of POXC as a soil health metric for informing management decisions and SOC-focused programs.
Fabaceae is a large, diverse, and abundant plant family with origins in the tropics. Many species in this plant family can fix nitrogen through symbiotic relationships with bacteria living in root nodules. This has been a common lens through which biogeochemists seek to understand the distribution and role of this important plant family in tropical ecosystems. However, species in this family have many additional functional traits that distinguish them from co-occurring taxa. Here we discuss how considering a wider range of traits including wood, leaf, seed, and phenological traits can help us better understand the distributions of legumes over biogeographic and ecological gradients (latitudinal, continental, climatic and succession) and their ecosystem-level consequences.
As tropical peatlands in Southeast Asia are increasingly drained for agriculture, the net effect of this conversion on nitrous oxide (N2O) emissions remains unclear. We examined how this land-use change affects nitrogen (N) cycling by comparing two contrasting tropical peat ecosystems in Sarawak, Malaysia: a managed oil palm plantation and a pristine peat swamp forest. We measured soil N2O and dinitrogen (N2) emissions, and for microbial functional and structural community and diversity, we quantified the abundances of N cycle functional genes and conducted metagenomic sequencing of microbial communities from below-ground (peat soil and litter) and above-ground (canopy soil and tree leaves) ecosystem compartments. The oil palm plantation soil was a significant N2O emitter (65.48 ± 43.18 μg N m−2 h−1), whereas the peat swamp soil acted as a near-complete N2O sink (0.89 ± 1.18 μg N m−2 h−1). Soil microbial communities played a central role in N transformations, with the genus Roseiarcus being the strongest predictor of soil N2O emissions, and Paludisphaera most strongly linked to soil N2O sink capacity. Oil palm leaves harboured approximately 89
