Root Cortical Aerenchyma Enhances the Growth of Maize on Soils with Suboptimal Availability of Nitrogen, Phosphorus, and Potassium    

Abstract

Root cortical aerenchyma (RCA) is induced by hypoxia, drought, and several nutrient deficiencies. Previous research showed that RCA formation reduces the respiration and nutrient content of root tissue. We used SimRoot, a functional-structural model, to provide quantitative support for the hypothesis that RCA formation is a useful adaptation to suboptimal availability of phosphorus, nitrogen, and potassium by reducing the metabolic costs of soil exploration in maize (Zea mays). RCA increased the growth of simulated 40-d-old maize plants up to 55%, 54%, or 72% on low nitrogen, phosphorus, or potassium soil, respectively, and reduced critical fertility levels by 13%, 12%, or 7%, respectively. The greater utility of RCA on low-potassium soils is associated with the fact that root growth in potassium-deficient plants was more carbon limited than in phosphorusand nitrogen-deficient plants. In contrast to potassium-deficient plants, phosphorus-and nitrogen-deficient plants allocate more carbon to the root system as the deficiency develops. The utility of RCA also depended on other root phenes and environmental factors. On low-phosphorus soils (7.5 mM), the utility of RCA was 2.9 times greater in plants with increased lateral branching density than in plants with normal branching. On low-nitrate soils, the utility of RCA formation was 56% greater in coarser soils with high nitrate leaching. Large genetic variation in RCA formation and the utility of RCA for a range of stresses position RCA as an interesting crop-breeding target for enhanced soil resource acquisition.

Functional implications of root cortical senescence for soil resource capture

“…Both RCS and RCA are accelerated by nutrient deficiencies (Gillespie and Deacon 1988;Drew et al 1989;Elliott et al 1993), reduce radial nutrient transport (Hu et al 2014;Schneider et al 2017a), reduce radial hydraulic conductivity (Fan et al 2007;Schneider et al 2017a), reduce metabolic costs (Zhu et al 2010;Postma and Lynch 2011b;Jaramillo et al 2013;Saengwilai et al 2014;Chimungu et al 2015), are influenced by exposure to ethylene (Lascaris and Deacon 1991b;Lenochová et al 2009;Schneider et al 2017c), and are types of PCD Jiang et al 2010;Schneider et al 2017c). Two ethylene-related genes were upregulated during both RCS and RCA formation (Rajhi et al 2011;Schneider et al 2017c).…”

OpenSimRoot: widening the scope and application of root architectural models

“…O pen S im R oot has a nutrient module to simulate the simultaneous uptake of solutes, originally implemented to simulate the impact of RSA on nutrient uptake, and to test tradeoffs for the acquisition of nutrients (Postma & Lynch, 2011a; Dathe et al ., 2013). Postma et al .…”

“…Stress impact functions can be defined for components such as leaf expansion rate, photosynthesis rates, respiration rates and root elongation rates or secondary growth. By making the initial response of the shoot stronger than that of the roots, the plant decreases the shoot to root ratios when nutrient deficient (Postma & Lynch, 2011a). O pen S im R oot will move towards a functional equilibrium, although, as a result of the inherent slow nature of growth, and the relatively fast dynamics of other processes, this functional equilibrium might not be reached (Postma & Lynch, 2011b; Postma et al ., 2014b).…”

“…simroot is one of the most feature‐rich and highly cited functional–structural root architectural models. However, the last full description dates back 20 yr (Lynch et al ., 1997), and subsequent papers have reported applications of the model, with successive changes embedded in methods sections (Postma & Lynch, 2011a,b; Dathe et al ., 2013). Here, we describe fully a new, open‐source version, branded O pen S im R oot , which is freely available for download (http://rootmodels.gitlab.io/OpenSimRoot).…”

“…Later versions coupled physiological mechanisms, such as root respiration, nutrient uptake, canopy photosynthesis and RSA, to simulate how the root phenotype dynamically interacts with the soil environment, and how this interaction influences the acquisition of soil resources and, consequently, plant growth (Postma & Lynch, 2011a,b, 2012; Dathe et al ., 2013, 2016; Postma et al ., 2014a; York et al ., 2016). The initial focus was on P capture (Lynch & Beebe, 1995; Ge et al ., 2000; Ma et al ., 2001; Postma & Lynch, 2011b), which was later expanded to include C (photosynthesis), nitrogen (N), potassium (K) and water (Postma et al ., 2008; Postma & Lynch, 2011a; Dathe et al ., 2013). Microeconomic theory, in which resource acquisition is compared with resource investment costs, has guided the interpretation of results (Lynch, 2007; Postma et al ., 2014b).…”