Understanding and reconciling different approaches for quantifying nitrogen use efficiency in cropping systems

doi:10.21203/rs.3.rs-60369/v1

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Understanding and reconciling different approaches for quantifying nitrogen use efficiency in cropping systems

https://doi.org/10.21203/rs.3.rs-60369/v1

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Nitrogen use efficiency (NUE) has been widely used in cropping systems to study nitrogen (N) cycles and inform N management on various spatial scales, from a single plant to the globe. Although the number of NUE studies is growing, interpretation of results is unfortunately hindered by widely differing definitions and quantification methods among studies, suggesting a pressing need for harmonization of approaches. Here, we proposed a conceptual framework to understanding the differences and connections among three major approaches for determining NUE, namely, the difference approach, 15N tracer approach, and N balance approach. Using the Chinese cereal cropping system as an example, we demonstrated that the results of those NUE assessments could be very different even for the same cropping system (0.32, 0.24, and 0.52, respectively). Such a difference is attributable largely to the soil legacy effect and could be reduced by extending the observations for a longer term. This study provides the necessary understanding to reconcile NUE values from different approaches and consequently to better inform N management in cropping systems.

Agroecology

Applied Biochemistry

Geochemistry

Agricultural Engineering

nitrogen use efficiency (NUE)

difference method

15N tracer method

N balance method

soil legacy effect

replenishment effect

Nitrogen (N) is a critical element for boosting crop yield and is consequently important for global food security¹. However, large N inputs to croplands as fertilizer and manure lead to N losses to the environment via leaching or gaseous emissions, leading to increased adverse environmental impacts from local to global scales (e.g., eutrophication and climate change) and threatening human health². To address these challenges, the efficient management of N in crop production is essential³.

To measure the efficiency of N use in crop production and determine the impacts of N inputs on the environment, an indicator of nitrogen use efficiency (NUE) is widely and increasingly used by agronomists, biogeochemists, policymakers, and other stakeholders at various temporal and spatial scales⁴. Unfortunately, while the use of NUE is growing, interpretation and synthesis of results is impeded by widely differing definitions and calculation methods, hindering comparisons among studies and experience-sharing among researchers and regions⁵. Understanding the differences and connections among existing approaches for quantifying NUE is particularly important and timely due to the growing policy interest in evaluating the agricultural sustainability⁶. Many international organizations (e.g., Sustainable Development Solution Network, United Nations Environmental Program, Global Partnership on Nutrient Management, European Union N Expert Panel) and countries (e.g., Germany) have attempted to use NUE or develop indicators based on NUE to assess the sustainability of nutrient management. However, debates about the methodologies remain, urging for a better understanding of the NUE concepts and the approaches for quantifying it.

There have been three main approaches widely used for defining and quantifying NUE (Table 1 and Fig. 1):

The difference approach (NUE_diff), defined as the harvested N in fertilized plots minus the harvested N in nonfertilized control plots, then divided by N fertilizer inputs;
The ¹⁵N tracer approach (NUE_15N), which applies fertilizer with ¹⁵N tracer and tracks the proportion of ¹⁵N harvested in the crop product;
The N balance approach (NUE_bala), defined as the harvested N divided by all N inputs.

A review of the existing literature suggests that the NUE of cereal cropping systems was in the range of 0.27–0.37 (China) and 0.42–0.48 (the globe) based on the NUE_diff and NUE_15N approaches, while they were approximately 0.68 (China) and 0.62–0.99 (the globe) based on the NUE_bala approach (Table 1). These contrasting results depict a very different picture of crop N management in China and around the world, leading to confusion or even misinformed decisions in N management practices and policies. Such confusion may also exist on a plot scale. For example, in some well-managed field trials, the observed NUE_diff or NUE_15N are usually around 0.2–0.5, appearing to indicate high N-loss risk and significant room for NUE improvement^{8, 10, 16}; however in those trials, large N harvests were usually observed (close to or even higher than N input), and NUE based on N balance approach could be close to or even higher than one, indicating very low N-loss risk or even depletion of soil N stock.

Here, we proposed a conceptual framework, with supporting case studies, to identify the differences and connections among these three commonly used approaches for defining and quantifying NUE and to discuss major considerations for choosing proper approaches as the use of NUE assessments grows.

The same principle but different approaches

In principle, NUEs are defined and quantified to assess how much of the N input to a system is used effectively by the product and harvested from the system⁵. In practice, three major approaches developed under different experimental and operational settings can lead to divergent results and possibly differing interpretations, even for the same experimental site and for the same growing season (Fig. 1a, b, c). A conceptual framework that depicts the linkages and differences among the three approaches is visualized in Fig 1d. While all three approaches share harvested N (HN_T) and N fertilizer inputs (F_N) as part of their calculation formulas, the relationship among NUEs obtained with these approaches can be determined by harvested N in the control plots (HN_C), fraction of harvested N derived from in-season-applied N fertilizer (%Ndff), and nonfertilizer N inputs (NF_N) measured in NUE_diff, NUE_15N, and NUE_bala approaches respectively. Mainly due to legacy effects of previous years’ fertilizer additions, points B and C in Fig. 1d (determined by HN_C and %Ndff respectively) are usually above reference point A (determined by NF_N), suggesting a higher NUE_bala than that obtained with the other two approaches. Such differences are prevalent, especially in short-term experiments (e.g., experiments for one or several growing seasons).

To showcase the differences among approaches, we constructed an example for China’s cereal cropping system based on the synthesis of values from the literature (numbers in the brackets of Fig. 1d). We developed this example based on mean values from the literature (mainly obtained by national on-farm surveys and field trials) instead of a single experiment because few studies have tested all three approaches simultaneously, and experiments for a single site may lack representativeness. The results suggest that even for the same cropping system (i.e., Chinese cereal cropping system in this case) with consistently defined N inputs and harvest rates, different NUE approaches will result in different values with the following trend: NUE_15N (0.24) < NUE_diff (0.32) < NUE_bala (0.52). Consequently, it is critical to understand the causes for the differences among those approaches to better achieve efficient N management.

Mind the gap: differences and connections among the three approaches

The most obvious difference among the three approaches is that NUE_diff and NUE_15N assess the efficiency of fertilizer use, while NUE_bala assesses the efficiency of N inputs beyond fertilizer (F_N + NF_N). However, when the bioavailability of NF_N (BA_NF, long-term uptake% of NF_N) is the same as that of F_N (BA_F), then the NUE for F_N use based on the balance approach (NUE_{bala_F}, = (HN_T– NF_N× BA_NF)/F_N) is the same as NUE_bala (Supplementary Fig. 1). It is possible that BA_NF is higher than BA_F, but even if all of NF_N can be converted to crop product during the same growing season (i.e., BA_NF = 1.0), the adjusted NUE for fertilizer use based on the N balance approach could still be lower than NUE_diff and NUE_15N¹⁴. Taking our Chinese cereal cropping system case as an example, NUE_{bala_F} ranges from 0.38 to 0.66, depending on the bioavailability of NF_N(Supplementary Fig. 1). However, even the lower boundary of NUE_{bala_F} is still higher than NUE_15N (0.24) and NUE_diff (0.32), indicating other important drivers for the differences between NUE_bala and the other two approaches.

The major driver for the remaining differences between NUE_bala and the other two approaches is the legacy effect of fertilization during previous seasons (Table 1). Fertilizer N inputs not only supply the plant N needs for the season of application but also replenish soil N and support the maintenance of the long-term N supply in the soil¹⁰. For example, the meta-analysis of Yan et al.¹⁴ shows that only 42% of N fertilizer is recovered by crop products during the same growing season, while 34% is retained in the soil, which could be utilized in future growing seasons or lost to the environment.

With the exception of newly formed croplands, most farms have a history of fertilizer or manure amendments. This commonplace legacy or replenishment effect of fertilizer application indicates that a long-term view of fertilizer efficiency is necessary in most cases for understanding the NUE_diff and NUE_15N approaches (Supplementary Fig. 2). However, often due to logistical constraints (e.g., funding and site maintenance), the experiments for determining NUE are usually conducted for one to several growing seasons with different considerations of legacy effects, leading to divergence in the results. With single-season observations, the NUE_diff and NUE_15N approaches reflect the fertilizer recovery rate during the current growing season, with no or largely discounted consideration of legacy effects. In contrast, the NUE_bala is based on the assumption of mass balance in soil N stocks, and does not exclude the long-term legacy effects of N inputs but may over- or underestimate the actual NUE if significant mining or accumulation of soil N occurs during the year of observation (Table 1). Therefore, the difference between single-season NUE_15N and NUE_bala (e.g., the difference between 0.52 and 0.24 in the Chinese cereal cropping system case) can be used to estimate the size of the legacy effect of applying ¹⁵N fertilizer (Fig. 1d).

If the observation period could be extended from a single season to multiple years or even decades, the assessment outcomes from the three approaches will change due to the diminishing legacy effect: the HN_C will likely decrease as soil N stock is continuously depleted without replenishment from additional N inputs, while the cumulative %Ndff will likely increase as more ¹⁵N will be recovered since the pulse addition of ¹⁵N tracer (i.e., points B and C will likely to move towards point A in Fig. 1d). Consequently, the observed NUE_diff and the cumulative NUE_15N will likely increase as observation is conducted for a longer period of time (Fig. 1e). Moreover, the NUE_bala may fluctuate due to the year-to-year yield variation, but the moving averages of the NUE_bala over several years under consistent management practices tend to be stable, as the average annual soil N stock change tends to be negligible compared to the annual N fertilizer inputs over a long period of time¹⁷. Consequently, the assessments from the NUE_15N and NUE_diff approaches tend to converge with that from the NUE_bala approach for long-term observations (Fig. 1e).

The difference between the NUE_diff and NUE_15N assessments could be attributed to the following reasons: 1) In addition to directly providing N for plant uptake, fertilizer inputs may change the in-season soil N supply by promoting root-mediated or soil microbe-mediated soil N turnover or abiotic adsorption-desorption exchange, leading to the differences between NUE_diff and NUE_15N^{13, 14, 18}. This effect tends to increase the harvested N in the fertilized plots of the NUE_diff approach but does not increase the recovered fertilizer N in the NUE_15N approach. Consequently, it may lead to a higher NUE value for the NUE_diff approach. 2) Given the “law of diminishing returns” between N inputs and N yields, the NUE for F_N is inherently lower than the NUE for NF_N (slope of line DB < slope of line BO in Fig. 1d). Consequently, NUE_diff, which is based on the different yield responses to two N input levels, could show a lower NUE result than the approaches dealing with only one N input (i.e., NUE_bala or NUE_15N). Overall, NUE_diff can be higher or lower than NUE_15N, depending on which reason dominates, but the difference is generally low in most reports (e.g., < 0.1 in Table 1).

Choosing a proper approach

Overall, when the observation is conducted over a long term and the NF_N is negligible, the three approaches for NUE assessment (NUE_diff, NUE_15N, and NUE_bala) tend to converge and the assessments from these approaches could be compared for informing management practices. However, in practice, these approaches are often implemented for only one or a few growing seasons due to many logistical constraints, and the NF_N sources are usually diverse and their quantities are uncertain. Therefore, the comparison of NUE assessments from different approaches may be biased by the inherent differences associated with these approaches, and it is essential that the assessment approach is carefully chosen and consistently implemented among practices or regions to avoid such bias.

Fortunately, a proper approach can be chosen by identifying the goal of the assessment and comparison, as well as the associated logistical requirements, including cost. For example, NUE_diff is a straightforward and cost-effective approach to assess the short-term response of harvested N to N fertilization under different environments or management conditions. The NUE_diff approach is suitable for experimental situations, such as research stations, but it is often difficult to perform in an actual farming operation because it is hard to convince farmers to devote some portion of their land to low yields due to lack of N fertilization. NUE_15N is most accurate in tracing the fate and distribution of N fertilizer in the soil-crop system, but it is usually applicable at relatively small space-time scales due to the high cost of ¹⁵N-materials and ¹⁵N-measurements.

In comparison, NUE_bala has great advantages in evaluating the resource and environmental performances of N inputs in crop production, especially when the averaged change in soil N stock is small or even negligible compared to the annual N inputs during the observation period. 1) Given the definition of NUE_bala and soil N balance, “1–NUE_bala” can be considered the fraction of N lost or subject to lose to the environment¹¹. Applying a similar formula to NUE_diff and NUE_15N, N losses to the environment are potentially overestimated due to the legacy effect (description of such overestimation existed widely in published papers^{12, 13, 19}). 2) NUE_bala is based on data more readily available from farm to national scales. For example, grain yield and N fertilizer rates are typical values used in farmers’ bookkeeping, and they are commonly collected in national or regional surveys or statistics. Admittedly, the data for some NF_N sources (e.g., biological N fixation) are still not widely available, and using default values may introduce uncertainties. Such uncertainties could be important to consider when the NF_N is not negligible (e.g., > 5%) compared to the fertilizer N rate.

It should be noted that, despite the approach, short-term observations are limited in reflecting the long-term effect of changing management practices¹⁵. First, crop yield and N uptake vary from year to year due to changing weather conditions and consequently affect the NUE assessment. Second, the impact of the new management practices on yield and NUE may be buffered by a soil legacy effect. Agronomic measures combined with fertilizer rate reduction are often reported in the literature as being effective for improving in-season NUE_diff or NUE_15N while maintaining crop yields²⁰. However, it must be recognized that some of these measures may only improve the soil environment and promote the release of previously accumulated nutrients in the short term and may eventually deplete soil N supply capacity, as well as yield and NUE, in the long term. Accounting for N balance and NUE_bala may help to relieve part of the concerns about soil depletion, but NUE_bala assessment tends to be biased when the soil N stocks are not in a steady state (Table 1). Consequently, to assess the impacts of different management practices on NUE, we recommend long-term observations (e.g., over a decade, but at least beyond three growing seasons) when possible.

The three commonly used NUE assessment approaches, NUE_diff, NUE_15N, and NUE_bala, are all designed to assess the effectiveness of N inputs to a crop production system. However, the different experimental designs, along with nonfertilizer N inputs and soil legacy effects, lead to differences in the assessment results even for the same crop production system. Improved understanding of the advantages and disadvantages of each approach is needed as studies of NUE increase, because it is critical to choose a proper approach based on the major goal of assessment and implement it consistently to enable fair comparisons. Given the limitations of the short-term observations and soil legacy effect, it is important to implement long-term trials for assessing the impacts of management practices on yield and the efficiency of N use.

Average N inputs and N harvests in the Chinese cereal cropping system. The average synthetic fertilizer N input was 208 kg N ha^-1 season^-1 based on the on-farm investigation at the national scale during 2005–2014^21-23 (Supplementary Table 2). The nonfertilizer N input was 59 kg N ha^-1 season^-1 based on the on-farm survey for manure application²³ (16 kg N ha^-1 season^-1, Supplementary Table 2) and the model simulation for deposition (17 kg N ha^-1 season^-1), biological fixation (20 kg N ha^-1 season^-1), irrigation (4 kg N ha^-1 season^-1), and seeds (2 kg N ha^-1 season^-1)²⁴.

The average harvest N (HN_T, aboveground N uptake = grain + straw) was 138 kg N ha^-1 season^-1, which was calculated according to the grain yield (on-farm investigation at the national scale during 2005–2014), the average weighted ratio of “grain: straw” (or harvest index), and average N concentrations in grain and straw in Chinese cereal crops^21-23 (Supplementary Table 2). In the simulation, all straw was assumed to be harvested and regarded as a product, regardless of how it was used after removal from field boundaries.

NUE calculations for the Chinese cereal cropping system. We estimated the HN_C according to the average reductions in grain yield and N concentration according to published results for Chinese cereal cropping systems. In this simulation, the control was estimated to have only 72.5% of the yield (Supplementary Fig. 3) and 71.0% of the N concentration (Supplementary Table 2) of the treatment with conventional N fertilization, so the aboveground N uptake in the control was only 51.4% (= 72.5% × 71.0%) of that in the treatment. This proportion (HN_C%, = HN_C/HN_T) was in line with that for cereal cropping systems at the global scale¹⁴. Consequently, the HN_C was calculated as 138 × 0.514 = 71 kg N ha^-1 season^-1.

In previous in situ ¹⁵N tracer studies, the Ndff% was generally determined. Under the condition of conventional N fertilization (fertilizer N rate in the range of 100–300 kg N ha^-1 season^-1), the Ndff% in the application year was in the range of 0.115–0.696 (n=216) with an average of 0.358 (Supplementary Table 1). As a result, the ¹⁵N recovered by harvest during the application season was calculated as 138 × 0.358 = 50 kg N ha^-1 season^-1.

The average NUE_bala in the Chinese cereal cropping system was calculated directly according to the fluxes of N inputs and HN_T. In China, the agricultural sector of the government conducted several national soil censuses in different years. The results showed that the N reserves in Chinese cropland have only changed slightly (averagely increasing approximately 3 kg N ha^-1 yr^-1, or 0.18% yr^-1) since 1980, which indirectly indicates that soil N is almost in a steady state¹⁷.

Simulating NUE_diff, NUE_15N, and NUE_bala changes in long-term experiments. The data sources for NUE, such as N fertilizer inputs and N harvests, were from the Rothamsted Broadbalk Wheat Experiment from 1969, when high yielding short straw wheat varieties and 3- and 5-course rotations were introduced and modern insect, weed and disease control began (www.era.rothamsted.ac.uk/). The harvested N values for the 1^st wheat in treatments receiving normal rates of phosphorus, potassium, and magnesium fertilizer but receiving 0 and 144 kg ha^-1 N fertilizer (treatment code: N0PKMg and N3PKMg) were selected as HN_C and HN_T in this simulation. To calculate NUE_bala, the nonfertilizer N input was estimated as the sum of the annual wet deposition record²⁵ and a uniform estimate was used for other N inputs (15 kg N ha^-1 yr^-1 including biotic N fixation, seed, etc.). The experiment started in 1843 and has lasted for > 170 years, which means that the soil in the control plots (receiving 0 kg fertilizer-N ha^-1) had a lower total N content than that in the treatment plots in 1969 due to the lower N fertilizer and residual N inputs. Therefore, we expect the differences between NUE_bala and NUE_diff to be underestimated at the beginning of the study period (1969–2015).

Since there was no long-term ¹⁵N experiment at the same site for direct comparison with the NUE_diff and NUE_bala approaches, we constructed a possible NUE_15N observation record using the following assumptions: 1) ¹⁵N labeled fertilizer was applied in 1969 at the rate of 144 kg N ha^-1, and the same rate of nonlabeled fertilizer was applied in the subsequent years; 2) the proportions of ¹⁵N harvested (%Ndff) in the first season and in subsequent seasons were the same as those in a 28-year-long ¹⁵N tracer experiment in France²⁶. Microplot-based ¹⁵N tracer trials were only conducted for four consecutive years (1980-1983) in the “N3PKMg” plots receiving 144 kg ha^-1 N fertilizer. The %Ndff of winter wheat in the first season was in the range of 0.518–0.648 with an average of 0.584²⁷. This percentage was very close to that in Sebilo et al.²⁶ where the %Ndff in the first season equaled 0.581. We predicted the potential %Ndff after 28 years using a two-pool decay model (Supplementary Fig. 4). The original data for making Fig. 1e can be found in Supplementary Table 4.

Acknowledgments

We thank Dr. Margaret Glendining from the Rothamsted Research for providing us with the data to indicate the changes of NUE in the long-term Broadbalk Wheat Experiment.

Competing interests

The authors declare no competing interests.

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Table 1. Definition, calculation, and mean values of nitrogen use efficiency (NUE) in cereal cropping systems based on three major approaches.

Approaches	Difference approach (NUE_diff)	¹⁵N tracer approach (NUE_15N)	N balance approach (NUE_bala)
Major focus of the assessment	The use efficiency of N fertilizer	The use efficiency of N fertilizer	The use efficiency of all N inputs, and the fraction of N inputs subject to surplus or loss
Application on spatial scales	Plot, field	Confined microplate, plot, field	Field, watershed, region, nation, or globe
Application on temporal scales	Single to multiple growing seasons	Often conducted for a single growing season	From a single growing season to multiple decades
Requirement for soil N status	No requirement	No requirement	Change in soil N stock is low or negligible compared to total N input and total N output
Soil legacy effect	Largely excluded for short-term experiments	Not considered for single-season experiments	Partly or all included based on soil N status^*
Formulas^#	= (HN_T – HN_C)/F_N	= (HN_T – Ndfs)/F_N = (HN_T × %Ndff)/F_N	= HN_T/(F_N+ NF_N)
Assumption about the contribution of N inputs to harvested N	The contribution of other N inputs (e.g. NF_N) to harvested N during the studied period is the same (= HN_C) in the control and treatment plots	The contribution of other N inputs (e.g. NF_N) to harvested N during the studied period can be traced as Ndfs (HN_T - Ndff)	The contribution of all N inputs to harvested N during the studied period is HN_T
Data source	Mostly field trials	Mostly field trials	Mostly statistical data or survey data
Mean values in China	0.30⁷; 0.27 (n=667)⁸; 0.35 (n=461)⁹	0.37 (n=92)¹⁰; 0.36 (n=216) (Supplementary Table 1)	0.68^†‡,³; 0.68^†,¹¹
Mean values at global scale	0.48^†,¹²; 0.47 (n=748)¹³; 0.48 (n=452)¹⁴	0.44 (n=804)¹³; 0.42 (n=622)¹⁴; 0.42 (n=88)¹⁵	0.99^†‡,³; 0.62^{†, 4}

^* Only when the soil N status is in a steady state can the soil legacy effect of N input in the current season (to subsequent seasons) be offset by the soil legacy effect of N input in the previous seasons (to the current season).

^# Abbreviations: fertilizer N inputs (F_N), nonfertilizer N inputs (NF_N; including deposition, manure, biological fixation, irrigation, seeds, etc.), harvested N in the control plots (HN_C, without N fertilization), harvested N in the treatment plots (HN_T, with N fertilization), fraction of harvested N derived from in-season-applied N fertilizer (%Ndff), harvest N derived from soil (Ndfs, = HN_T – Ndff).

^† To facilitate the comparison between different approaches, all aboveground N was uniformly calculated as the harvested N. For cereal crops, the NUE for aboveground N (grain + aboveground straw) is approximately 1.45 times the NUE for grain N according to their empirical ratio.

^‡ Neither biological N fixation nor manure applications were considered.

There is NO Competing Interest.

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Understanding and reconciling different approaches for quantifying nitrogen use efficiency in cropping systems

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The same principle but different approaches

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