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Biology subjects

Archontoulis, S.

Publications and source records attributed to Archontoulis, S..

3 recordsLinked to original sources

Four Decades of Breeding and Increasing Plant Density Management Reshaped Maize Root System Architecture

Understanding how crop root system architecture (RSA) is influenced by genetics and management is vital for root-based improvement. We examined the impact of four decades of maize breeding on RSA using a panel of maize hybrids planted at different densities across six site-years in the Midwest. Root crowns were shovel-excavated and imaged via X-ray tomography, generating dozens of fine-grained 3D traits. Modern root systems were significantly smaller with fewer, thinner roots at higher density compared to older hybrids. However, the total amount of roots in the topsoil extrapolated across an acre was indistinguishable, revealing an equilibrium between crown size and density. Surprisingly, there was a 20% increase in the soil volume explored by individual modern hybrids, indicating increased overlap of root systems. We estimated modern hybrids share 43-46% of the topsoil with neighbors, compared to 14% in the oldest. Furthermore, when the oldest hybrids were grown at modern densities, their root crowns became more elliptical than modern hybrids, highlighting potential differences in avoidance response. Root systems of modern hybrids may be more intertwined and less competitive, revealing an adaptation to increased density stress in maize agriculture with implications for trait-based approaches to engineer more productive, efficient systems. HIGHLIGHTThis study uses a new panel of maize hybrids to explore how decades of yield-focused breeding and advancements in planting density have indirectly impacted maize root systems.

plant biology↗

A Multi-Model Ensemble Reveals Soil Carbon Gains from Regenerative Practices in the U.S. Midwest Cropland

Process-based cropping systems models (CSMs) are key components of measurement, monitoring, reporting, and verification (MMRV) frameworks of carbon markets, but their application suffers from model-specific differences that keep any one model from working well across all combinations of soils, climates, crops, and agronomic practices at varying scales. Multi-model ensemble (MME), successfully used to quantify soil, management and climate impact on crop productivity, provide an opportunity to better estimate changes in soil organic carbon (SOC) outcomes for agronomic practices that have the potential to mitigate SOC loss at scale. We used an MME across 46 million hectares of US Midwest cropland at a resolution of 4- km2 to assess the aggregate ability of different regenerative practices to sequester SOC at this scale compared to their dynamic baselines. MME was validated with long-term experimental data and compared to its constituent CSMs, showing greater accuracy and lower uncertainty. The results show that adopting no-till combined with cover crops increased SOC stocks by 0.36 {+/-} 0.12 Mg ha-1 yr-1 aggregated across the entire U.S. Midwest cropland. At the regional scale, this corresponds to a net SOC gain of 16.4 Tg C yr-1 compared to business-as-usual baselines. These benefits are approximately halved when each management change is practiced individually, and the modest gains are only fully realized when continued over the long-term in soils with low initial carbon stock. Results demonstrate the power of MMEs run at high resolution for providing robust estimates of environmental outcomes following agricultural practice change, and for pinpointing locations for most effective intervention. This approach can alleviate many producer carbon market participation barriers and help address market issues while ultimately supporting large-scale regenerative agriculture initiatives.

ecology↗

The effects of soil depth on the structure of microbial communities in agricultural soils in Iowa, USA

The determination of how microbial community structure changes within the soil profile, will be beneficial to understanding the long-term health of agricultural soil ecosystems and will provide a first step towards elucidating how deep soil microbial communities contribute to carbon sequestration. This study aimed to investigate the differences in the microbial community abundance, composition and diversity throughout from the surface layers down to deep soils in corn and soybean fields in Iowa, USA. We used 16S rRNA amplicon sequencing of soil samples to characterize the change in microbial community structure. Our results revealed decreased richness and diversity in bacterial community structure with increasing soil depth. We also observed distinct distribution patterns of bacterial community composition along soil profiles. Soil and root data at different depths enabled us to demonstrate that the soil organic matter, soil bulk density and plant water availability were all significant factors in explaining the variation in soil microbial community composition. Our findings provide valuable insights in the changes in microbial community structure to depths of 180 cm in one of the most productive agricultural regions in the world. This knowledge will be important for future management and productivity of agroecosystems in the face of increasing demand for food and climate change.

microbiology↗