Quantifying and Understanding Plant Nitrogen Uptake for Systems Modeling PDF

Introduction

Managing nitrogen (N) to increase crop production is one of the success stories of modern agriculture. However, with recent concerns about environmental quality, agricultural managers face new challenges and have had to shift from a single goal of increasing crop production to dual goals of increasing production and reducing environmental impacts. The long-term sustainability of both food security and the environment has set new goals for modern agriculture enterprises. Site-specific optimal management of N under different agroclimatic conditions is an important part of these goals. This optimal management involves synchronizing the timing of soil N availability (mineralization and fertilization) with crop N demand and appropriate water management under uncertain weather conditions. Better understanding and quantification of plant N uptake at different growth stages and under varying conditions is an essential requirement for this purpose.

This new challenge is beyond the many decades of field trials for measuring crop N uptake under specific experimental conditions. It requires a quantitative systems approach to integrate all the factors affecting plant N uptake together to develop integrated management practices (IMP) on a whole system level. Synchronizing plant N demand and soil N supply is the inevitable goal of 21st century agriculture and requires a complete understanding of the dynamics and interactions between N demand and N supply. Since plant N demand is largely unknown and depends on plant growth (e.g., carbon assimilation, phenological stage) and plant stress conditions (e.g., N and water stresses), it is a real-world challenge to decide when and how much fertilizer should be applied to ensure the right amount of available soil N is in the root zone to minimize any potential N loss to the environment. There is also a lag period between the start of plant N stress and the observable stress phenomena in the field.

Agricultural system models are able to take up this challenge because they are developed to integrate all the factors affecting plant N uptake into a virtual management system. As shown in Figure 1.1, N uptake affects and is affected by all the processes in the soil–plant system directly or indirectly. There are many feedback mechanisms that are still unknown to agricultural scientists. Some of the known growth regulators are not considered in models, partially due to lack of quantification of their functionality. Nonetheless, agricultural system models present the potential of integrating all of the processes together based on decades of experimental observations. Although there are numerous system models of different types, N uptake is generally determined by soil N supply and plant N demand (Figure 1.1). The differences lie in how to estimate the supply and demand terms, and how to quantify various factors affecting them.

As shown in Figure 1.1, all the factors are intertwined together. For example, water uptake (transpiration) is one of the main processes affecting N uptake, although some authors have found that N uptake and transpiration can be decoupled (Hansen and Abrahamsen 2008; BassiriRad et al. 2008). Nitrogen cannot be transported in the soil and plant without water. Therefore, water movement in the soil would affect both plant N-uptake estimation and soil N supply. Generally, transpiration is estimated by soil water supply and energy-driven potential transpiration. Plant root growth/distribution and leaf area index are the two main biological parameters determining transpiration in models, and these are in turn affected by plant N uptake. Plant N demand is also determined from biomass production, photosynthate partitioning, and phenology development. Another important issue is that, although qualitative knowledge of the feedback mechanisms exists after decades of field experiments, quantitative representation of these mechanisms is empirical and is not fully understood, especially how the mechanisms dynamically respond to environmental conditions. As a result, plant N-uptake simulations in any given model are generally empirical in nature and are not transferable to other models without taking into account other associated assumptions (e.g., water uptake, carbon allocation). Another aspect that may be important in some situations is that most system models ignore uptake of dissolved organic N (DON) from soils (Wu et al. 2008).