Higher levels of soil organic matter improve soil water retention, meaning they could mitigate agricultural yield losses from drought. Yet evidence to support such claims is mixed and incomplete. Using data from 12 376 county-years in the United States of America, we show that counties with higher soil organic matter are associated with greater yields, lower yield losses, and lower rates of crop insurance payouts under drought. Under severe drought, an increase of 1% soil organic matter was associated with a yield increase of 2.2 ± 0.33 Mg ha⁻¹(32.7 bu ac⁻¹) and a 36 ± 4.76% reduction in the mean proportion of liabilities paid. Similar, yet smaller, effects were found for less severe levels of drought and this effect was reduced as soil clay content increased. Confirmatory pathway analyses indicate that this positive association of soil organic matter and yields under drought is partially explained by positive effects of soil organic matter on available water capacity and cation exchange capacity, but that soil organic matter may be imparting yield protection via mechanisms not fully captured by those metrics. Overall, our results suggest soil organic matter predicts yield resilience at regional scales in the United States. We argue that data on soil organic matter should be used in agricultural policy and financial planning, with our analyses providing quantitative evidence of the co-benefits of soil organic matter believed fundamental to advancing soil health and carbon sequestration initiatives.

Crop diversity is a key principle of sustainable food production systems. Yet, inter and intra specific diversification is declining in many regions of the world. In Northern Malawi, a participatory action research project (Soils Food and Healthy Communities) has conducted agroecological co-learning with farmers for over a decade, providing an opportunity to explore farmer management, crop choice and variety selection practices. Farmers who participate receive seed for 0.10 ha of on-farm testing for one growing season and then decide whether to continue to grow the crop. Cropping system diversity, management practices and traits associated with crops grown and lost were assessed through interviews with 198 farm households (757 fields). We found an average of 1.3 species per field and 4.0 crops per farm. This is almost twice the level of diversity in other reports from Malawi smallholder farms. Farmers cited a wide range of preferred groundnut variety traits, as well as concerns (namely, high labour requirements). Both modern and local maize varieties are being grown and those retained were often associated with early maturity or preferred grain quality traits such as storability. Overall, farmers at this Northern Malawi agroecology education site are growing diverse crop mixtures that include traditional as well as modern varieties of maize and groundnut.

Soils comprise the largest pool of terrestrial carbon yet have lost significant stocks due to human activity. Changes to land management in cropland and grazing systems present opportunities to sequester carbon in soils at large scales. Uncertainty in the magnitude of this potential impact is largely driven by the difficulties and costs associated with measuring near-surface (0–30 cm) soil carbon concentrations; a key component of soil carbon stock assessments. Many techniques exist to optimize sampling, yet few studies have compared these techniques at varying sample intensities. In this study, we performed ex-ante, high-intensity sampling for soil carbon concentrations at four farms in the eastern United States. We used post hoc Monte-Carlo bootstrapping to investigate the most efficient sampling approaches for soil carbon inventory: K-means stratification, Conditioned Latin Hypercube Sampling (cLHS), simple random, and regular grid. No two study sites displayed similar patterns across all sampling techniques, although cLHS and grid emerged as the most efficient sampling schemes across all sites and strata sizes. The number of strata chosen when using K-means stratification can have a significant impact on sample efficiency, and we caution future inventories from using small strata n, while avoiding even allocation of sample between strata. Our findings reinforce the need for adaptive sampling methodologies where initial site inventory can inform primary, robust inventory with site-specific sampling techniques.