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Corn Yield Increase Under Constant Fertilizer Did Not Reduce Nitrate Export
Chelsea C. Clifford1, Emily R. Waring2, Carl H. Pederson1, Matthew J. Helmers1,*
Published in Journal of the ASABE 66(5): 1153-1161 (doi: 10.13031/ja.15538). Copyright 2023 American Society of Agricultural and Biological Engineers.
1Agricultural and Biosystems Engineering, Iowa State University, Ames, Iowa, USA.
2Center for Information Technology Research in Interest of Society, University of California, Merced, California, USA.
*Correspondence: mhelmers@iastate.edu
The authors have paid for open access for this article. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License https://creative commons.org/licenses/by-nc-nd/4.0/
Submitted for review on 16 January 2023 as manuscript number NRES 15538; approved for publication as a Research Article and as part of the “Advances in Drainage: Selected Works from the 11th International Drainage Symposium” Collection by Community Editor Dr. Zhiming Qi of the Natural Resources & Environmental Systems Community of ASABE on 21 July 2023.
Highlights
Abstract. Aquatic problems from the export of nutrients, especially nitrate, from row crops are recalcitrant in the Mississippi-Atchafalaya River Basin and globally severe. Previous studies have proposed to reduce these problems in part by improving crop yields, particularly corn, leaving less nitrate surplus to export. Simultaneous increases in fertilizer application rates and grain yields in recent decades have made testing this notion with large-scale agricultural statistics difficult. This experiment in Iowa featured a corn-soybean rotation with corn fertilized with nitrogen at a nearly consistent rate from 1989 to 2021. Corn yields increased at a rate not statistically distinguishable from the surrounding county’s (144 vs. 148 kg ha-1 yr-1), but drainage nitrate concentration and loading remained flat overall, oscillating with precipitation. Results suggest that increasing corn yield, and thereby partial factor productivity, with standard shifts in cultivars over time, cannot alone solve the U.S. Corn Belt’s nitrate surplus problem, supporting previous recommendations for active and multi-layered conservation efforts. Five- to ten-year positive and negative sub-trends in nitrate export within the longer dataset reaffirm the importance of truly long-term experiments and monitoring to accurately assess the impacts of management.
Water health worldwide suffers from agricultural nutrient pollution (Mateo-Sagasta et al., 2018). Nowhere better exemplifies this problem than Iowa, the leading contributor of nitrate in the Mississippi-Atchafalaya watershed, and thus to hypoxia in the Gulf of Mexico (Jones et al., 2018). Annual row crops, primarily corn (Zea mays L.; maize) and soybeans (Glycine max L.; soy), dominate a landscape blanketed pre-colonization by tallgrass prairie (Gallant et al., 2011). Corn plants in annual row-cropping systems generally require the regular addition of nitrogen-based fertilizer to grow healthily and to yield enough grain to make planting economically worthwhile (Morris et al., 2018). While crops uptake the greatest fraction of applied nitrogen, soil holds some, and denitrification and other processes also bleed off much of the excess, the small fraction of nitrogen that eventually escapes from fertilizer into water creates serious problems (Donner et al., 2004). Nitrate levels even below the US Environmental Protection Agency’s accepted level of 10 mg L-1 in drinking water can contribute to negative public health outcomes (Ward et al., 2018). Most Iowans get their water from private wells, which not uncommonly exceed this threshold (Manley et al., 2022). Even Des Moines Water Works, which supplies Iowa’s capital, has struggled to keep nitrate levels low for decades (Lucey and Goolsby, 1993; Eller, 2022). Aquatic nitrogen adversely affects aquatic communities both within the U.S. Midwest (Schmidt et al., 2019) and down the Mississippi River, infamously contributing to the Gulf of Mexico “dead zone” of annual harmful algal blooms and hypoxia (Rabalais et al., 1996). Agricultural fertilizer and aquatic nitrate remain a dominant water quality concern for water flowing from the Mississippi and Atchafalaya Rivers (Aggarwal et al., 2022) and beyond (Schürings et al., 2022), even after more than a quarter century (Rabalais et al., 1996) of widespread recognition, research, and conservation work to combat hypoxia in the Gulf of Mexico. Surplus nitrogen in the US Midwest and the “dead zone” have proven resistant to reduction (Boesch, 2019), though their worsening has slowed (Byrnes et al., 2020).
One relatively simple and economically attractive proposed partial solution to the problem of nitrogen surplus in and around Iowa is to increase grain yields relative to fertilizer inputs. Logically, more nitrogen exported as grain will leave less behind in fields for export into vulnerable aquatic ecosystems and groundwater resources (Gentry et al., 2009). Thus, increasing yields without equivalently increasing inputs is one way proposed to increase crop N-use efficiency (NUECrop) (Sinclair and Vadez, 2002, as cited in Asibi et al., 2019; Lu et al., 2019; Dattamudi et al., 2020) and the related measure of partial factor productivity (PFP). These indices characterize how much grain is generated per unit of fertilizer applied, i.e., the return on fertilizer. Multiple studies have characterized optimizing N-use efficiency as critical to maintaining economically viable crop yields while minimizing environmental damage (Martinez-Feria et al., 2018; McLellan et al., 2018).
Conveniently for testing this hypothesis, corn yields have consistently grown for decades. Less conveniently, the concomitant increase in fertilizer (Cao et al., 2018) is nearly inextricably entwined with these yield gains, and high rates of nutrient surplus remain a problem (Byrnes et al., 2020). With multiple components of the nitrogen budget in flux, it is difficult to parse from large-scale trends if increases in yields can reduce drainage nitrogen export.
Where real-world data confounds, controlled experiments can clarify. The Agricultural Drainage Water Research and Demonstration Site (ADW) in north-central Iowa has featured experimental corn-soybean rotation plots with consistent rates of fertilizer application to corn since 1989. These plots remove the influence of changing fertilizer application rates, allowing an unobstructed assessment of the effect of changes in corn yield on drainage nitrate export. If increasing yield can decrease nitrate loading, then we should see nitrate loading decrease as yields increase in our experiment. However, if increasing yield cannot decrease nitrate loading, then nitrate loading should remain constant as yields increase. Identifying which of these outcomes occurred allows us to empirically assess if increasing corn yields and N-use efficiency is actually a viable strategy for reducing nitrate loading and its cascading aquatic harms.
Materials and Methods
Experiment Description
The Iowa State University and the Iowa Department of Agriculture and Land Stewardship established the Agricultural Drainage Water Research and Demonstration Site (ADW) outside Gilmore City in Pocahontas County, Iowa (42.748°N, 94.496°W), in 1989 through the Iowa Groundwater Protection Act. This experiment features 78 experimental plots, each measuring 0.5 hectares (15.2 meters by 38 meters), with 72 of them being active. The plots are located on nearly flat terrain with an average slope of 1% and consist of poorly drained clay loams, including Nicollet, Webster, and Canisteo soils. The center half of each plot drains through tile buried 1.06 m deep into aluminum sumps, where that drainage flow is monitored (fig. 1). A 16 mm, Trident T-10 water meter (Neptune Technology Group, Inc., Tallassee, Alabama) records flow coming from each monitored tile line, while a plated sprayer orifice nozzle diverts a continuous subsample of approximately 0.25% of flow into formerly glass and later high-density polyethylene jugs. ADW also features a weather station (fig. 1) that records precipitation through a tipping bucket (Campbell Scientific, Inc., Logan, Utah), backed up by a manual rain gauge generally consulted at the same time as water sampling. Lawlor et al. (2008) provided a detailed description of ADW, which other publications from the experiment (Helmers et al., 2005; Singh et al., 2006; Qi et al., 2011; Helmers et al., 2012; Lagzdinš and Helmers, 2015; Waring et al., 2020; Waring et al., 2022) augmented.
Plots at this study site have featured a variety of conservation and control cropping treatments over the years, including corn and soybeans in various rotations with various tillage, fertilizer, and cover cropping treatments, plus unfertilized pasture. While the exact plots have varied over time, this site has always included “untreated” or “farmer normal” plots consistently fertilized around the land grant university recommended rate of 165 kg ha-1 (Kaiser et al., 2022; table 1). These plots constitute the experiment described in this article. This fertilizer consisted formerly of urea-ammonium nitrate and later aqueous ammonia and anhydrous ammonia (table 1), formerly applied at planting and later as an early season side-dress, midrow with a conventional knife applicator. These plots are all chisel-plowed immediately post-harvest in the fall, spring disked, fertilized, and planted in an annual corn-soybean rotation with herbicide applied. Half were planted in corn and half in soybeans at any given time, with any given area alternating from one to the other annually. Whole plots alternated for most of the experiment, but plots were split into halves that rotated crops from 1994 to 2004 (table 1). We lack records of the cultivars planted, but we consulted annually with our local seed salesperson for recommendations. So, our corn cultivars can also be considered “farmer normal” for the area over time.
Data Collection
From 1989 to 2022, we recorded weekly or sub-weekly flow meter readings and collected a cumulative subsample from each water sample jug while the ground remained unfrozen and tiles drained, approximately April through October. We treated collected 125 mL water subsamples with 1 mL sulfuric acid to reduce sample pH below two, or formerly chilled them, to avoid microbial activity in transport. Laboratories at Iowa State University, formerly known as the Agricultural and Biosystems Engineering Water Quality, and now part of the Department of Ecology, Evolution, and Organismal Biology Wetland Research Laboratory, analyzed the samples for NO3-N. They initially used the cadmium reduction method in a Quickchem 2000 Automated Ion Analyzer flow injection system (Lachet Instruments, Milwaukee, Wisc.) and later employed a second-derivative spectroscopy technique (Crumpton et al., 1992). We controlled the quality of the data by removing data associated with system malfunctions, such as pump failure and resultant sump flooding and contamination. Annual yield measurements came with harvest by three-row combine, for 12 central rows out of 20 total in each plot. In some years (1990-2001, 2009-2014, and 2016-2020), the National Soil Tilth Analytical Chemistry Laboratory in Ames, Iowa, and later Ward Laboratories, Inc., in Kearney, Nebraska, also analyzed the nitrogen content of ground samples of this harvested grain.
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In addition to the data we collected at ADW, this analysis includes US federal data. Gaps in our own precipitation monitoring data we filled from the U.S. National Oceanic and Atmospheric Association weather station GHCND: USC00136719 in Pocahontas, Iowa (NOAA, 2022), approximately 13.5 km west of ADW. Comparative data on average corn yields for the whole of Pocahontas County came from the U.S. Department of Agriculture National Agricultural Statistics Service (USDA, 2022), as did average nitrogen fertilizer application for the state of Iowa (USDA, 2022).
Data Analysis
We report yields for corn only. To calculate PFP, we divided annual corn yields (kg ha-1) by annual fertilizer application (kg ha-1). However, water measurements for split plot treatments from 1994 to 2004 (table 1) came from whole plots (fig. 1), each water measurement reflecting half corn and half soybeans. So, to disentangle corn and soybean influences on water measurements from split plots, we include water quality results from both corn and soybean years of rotating full plots. We aggregated approximately weekly individual water measurements for each experimental plot into annual values. Flows and precipitation were simply summed. We calculated nitrate loads by multiplying individual flow measurements by corresponding individual nitrate concentrations, then summed these to calculate annual loads. Reported concentrations are flow-weighted averages, i.e., annual loads divided by annual flow.
Per statistics, we calculated slopes and adjusted r2 values in R for simple linear models (“summary” command applied to command “lm” in “stats” package, (R Core Team, 2022) of the ADW period of record, 1989 to 2021, for correlations between year and both yield and PFP for the ADW experiment. We made the same calculations for 1990-2021 for correlations at ADW between year and precipitation, drainage, nitrate concentration, and nitrate load, respectively, and also for 1990-2020 between year and grain N content. For models of drainage, nitrate concentration, and nitrate load, we report two versions of each analysis, one of only plot/year combinations including corn, i.e., split plots and corn years of rotating full plots, and another version also including soy only plot/year combinations, i.e., split plots and both corn and soy years of rotating full plots. In these water models, to compensate for varying numbers of plots in the experiment over time, we also weighted each value by the inverse of the number of plots with data that year, so that each year had the same total weight worth of plots. For relationships between year and average yield in Pocahontas County and between year and average nitrogen fertilizer application in Iowa, we calculated slopes but avoided further statistics, as we only had averages for response variables. For the aforementioned slopes of ADW data, we also calculated 95% confidence intervals (command “confint” in R package “stats,” R Core Team, 2022) based on a t-distribution.
Results and Discussion
While maintaining a basically consistent fertilizer application rate just above the recommended maximum return to nitrogen (Kaiser et al., 2022) from 1989 to 2021, yields in our experiment increased on average by 144 kg ha-1 yr-1, with a 95% confidence interval of 116-170 kg ha-1 yr-1. Our yield increase over time is thus not statistically differentiable from the county-wide average increase of 148 kg ha-1 yr-1 in the same period (fig. 2a), even as fertilizer rates in Iowa increased on average by 0.339 kg ha-1 yr-1 from 1990 to 2021. Thus, experimental yields increased at a similar rate to ambient Pocahontas County yields without needing an increase in fertilizer to do so in our experiment. Given the only slight variation in fertilizer application rate over the course of this experiment, the increase in yield also corresponds to an increase in partial factor productivity (PFP) over the decades (fig. 2b). Thus, this experiment indeed increased crop N-use efficiency over time without raising fertilizer input.
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| Figure 2. (a) Experimental and broader Pocahontas County increases in corn yields, and (b) experimental increase in partial factor productivity (PFP), 1989-2021. Pocahontas County average yields increased by an average of 148 kg ha-1 yr-1. Meanwhile, yields for our consistently fertilized plots increased on average by 144 kg ha-1 yr-1, with a 95% confidence interval of 116 to 170 kg ha-1 yr-1 (r2 = 0.47). Experiment PFP increased by 0.90 per year, with a 95% confidence interval of 0.738 to 1.07 (r2 = 0.49). |
We suspect our experimental increase in yields results from widespread improvements in the genetics of corn cultivars. As we lack information about cultivars planted and did not experiment directly with the productivity of different varieties, we cannot empirically confirm the role of seed genetics in the observed corn yield increase. However, corn hybrids have shown greater yields (Assefa et al., 2017; Johnson et al., 2019), PFP (Ciampitti and Vyn, 2012; DeBruin et al., 2017), and NUE (Haegele et al., 2013; Woli et al., 2016; Mueller et al., 2019) over the decades in other studies in the Midwest. Meanwhile, no other inputs changed notably in this period. Our agronomic practices remained essentially constant other than cultivars, and annual precipitation changed in no consistent direction over the decades (fig. 3). It is possible that other climate factors, such as solar radiation, contributed somewhat to yield improvements (Tollenar et al., 2017; Butler et al., 2018), but even the ability to capitalize on these factors links back to genetic improvements in corn over time (Kovaleski and Baseggio, 2019; Messina et al., 2022).
Whatever the causes of the yield and PFP increase in our experiment, they did not lead to a decrease in nitrate exports. Drainage nitrate concentration and load neither increased nor decreased consistently during this time (r2 = 0.00 for both). Slopes were indistinguishable from zero, -0.06 mg L-1 yr-1 (95% confidence interval of -0.017 to 0.05 mg L-1 yr-1) for concentration, and -0.02 kg ha-1 yr-1 (95% confidence interval -0.72 to 0.68 kg ha-1 yr-1) for load, in plot-years containing corn (figs. 3c and e). Water results collated for corn and soybean years of the rotation plus split plots (figs. 3b, d, and f) differed little from the same results for the corn years and split plots only (figs. 3a, c, and e); annual averages of drainage, nitrate concentration, and nitrate load were nearly identical regardless of soybean inclusion. So, we can safely assume that the split plot years of the corn analysis, when water results reflected half corn and soybeans in phases II and III (figs. 3a, c, and e), still reflect the effect of corn yields on water quality approximately as well as in fully corn plot years. Thus, instead of increased corn yield decreasing drainage nitrate exports over time, drainage nitrate concentration and load varied year to year with precipitation and drainage volumes across crop rotations in no consistent direction (fig. 3).
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| Figure 3. Nitrate exports in experimental plots neither increased nor decreased, but instead followed water variation. Points show plot-level values; dashed lines show site (precipitation) or experimental (drainage and nitrate values) annual averages, and solid lines show slope over the period of record. Plots on the left (a, c, and e) reflect corn years (black) and split plots (dark green). Plots on the right (b, d, and f) reflect both corn and soy years, as well as split plots. (a) Site precipitation and drainage from experimental plots containing corn covaried over time, but neither increased nor decreased consistently (precipitation slope = 0.23 cm yr-1, 95% CI -0.44 to 0.91, and r2 = 0.00; drainage slope = -0.13 cm yr-1, 95% CI -0.60 to 0.33, and r2 = 0.00). (b) Adding years of rotating plots planted only in soybeans changed (a) little (drainage slope = -0.11 cm yr-1, 95% CI -0.47 to 0.26, and r2 = 0.00). (c) Corn-containing years of experimental plot drainage nitrate concentration also varied over time without consistent direction of change (slope = -0.06 mg L-1 yr-1, 95% CI -0.17 to 0.05, and r2 = 0.00), as did their (e) drainage nitrate load (slope = -0.02 kg ha-1 yr-1, 95% CI -0.72 to 0.68, and r2 = 0.00). Inclusion of soybean years of rotating plots changed (c) little to (d; concentration slope = -0.02 mg L-1 yr-1, 95% CI -0.11 to 0.07, and r2 = 0.00), and (e) little to (f; load slope = 0.08 mg L-1 yr-1, 95% CI -0.46 to 0.61, and r2 = 0.00). |
Failure of increased corn yields to decrease nitrate exports could result from decreased corn grain N content. In general, corn grain and stover N percent have decreased over time with newer and higher yielding cultivars, such that grain exports of N have not increased as quickly as yield and biomass (Ciampitti and Vyn, 2012, 2013). We did see a decline in average corn grain N percentage over time in this experiment, but the relationship was not robust (fig. 4). We cannot further parse the details of physiological changes in corn plants in this experiment. Given Iowa’s highly organic soils, the decomposition of corn residue between harvest and planting could also mask small effects on drainage nitrate exports by any changes in corn yield over time. At this site, from 1991 to 1993, even unfertilized corn plots continued to export an average of 9.9 mg L-1 yr-1 of nitrate, nearly the EPA drinking water standard. However, grain N would not have remained as residue, and since corn grain and stover N content correlate (Ciampitti and Vyn, 2012, 2013), these plots’ corn residue likely did not increase in N over time either. In all, these results fit with previous findings that increases in yield and growth may occur through N dilution rather than equivalent increases in N uptake (Ciampitti and Vyn, 2012, 2013), and thus have little to no effect on N surplus loading to drainage.
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| Figure 4. Corn grain percent nitrogen over time in consistently fertilized plots (slope = -0.007, 95% CI -0.011 to -0.004, and r2 = 0.15). Each point represents one plot, sampled at harvest, and the line represents the slope of the overall linear model. |
Whatever the reason, increasing yield alone did not reduce nitrate leaching from maize row-cropping. We further confirm that PFP has no apparent relationship with nitrate load from plots containing corn across these decades of sustained high fertilizer application at ADW (fig. 5). So, it is likely that any efforts at increasing crop N-use efficiency simply through yield increase and normal cultivar shifts, including as part of the broader goal to improve the N balance (sensu McLellan et al. (2018)), do not alone reduce N-loading. Yield and PFP increases do have other benefits, and increases in NUE achieved through means that actually reduce nitrate inputs or surpluses, such as reducing fertilizer, remain important conservation tools (Eagle et al., 2017; Sharpley et al., 2019; Tamagno et al., 2022). However, Iowa’s increase in corn yields in recent decades presumably does not balance out its concomitant increase in fertilizer application rates, in terms of aquatic nutrient loading. Our results affirm the need for a multi-pronged and layered agricultural conservation approach, from a spatially and temporally tailored and targeted menu of in-field, edge-of-field, downstream, and landscape-scale conservation options, from cover crops to constructed wetlands, from re-closing nutrient and water cycles to shifts from monocultures of commodities (Robertson and Vitousek, 2009; Liebman et al., 2013; Porter et al., 2015; Basche and Edelson, 2017; Eagle et al., 2017; Christianson et al., 2018; Mateo-Sagasta et al., 2018; Boesch, 2019; Sharpley et al., 2019; Cheng et al., 2020; Prokopy et al., 2020; Suttles et al., 2021; Aggarwal et al., 2022; Feyereisen et al., 2022). Scientific assessment and prioritization of which approaches have the largest effects under what circumstances (e.g., Tamagno et al., 2022) yield much more effective conservation strategies than do economically appealing hopes alone. This article recommends the downfall of one such hope: extant corn yield improvements are not solving the “dead zone.”
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| Figure 5. Nitrate load as a function of (a) corn yield and (b) partial factor productivity (PFP). Each point represents one plot in one year, and the line represents the slope of the overall linear model. Neither corn yield (slope = -0.0003, 95% CI -0.004 to 0.003, and r2 = 0.00) nor PFP (slope = 0.044 kg ha-1, 95% CI -0.49 to 0.58, and r2 = 0.00) had a significant relationship with nitrate load. Loads in this figure come from plots either wholly or half planted in corn that year; rotation years of plots planted fully in soybeans are not included. |
While the full span of our experimental dataset reveals a lack of change in water quality, the data displays spans of roughly 5-10 years in which increasing or decreasing trends in nitrate drainage exports do appear, typically matching short-term trends in weather. For example, concentration increased from 1994 to 1999 and load from 1997 to 2007. Admittedly, water measurements in these years mostly represented mixed corn and soy, from the experiment’s split plot era (1994-2004). More notably, concentration decreased from 1990 to 1993 and 2013 to 2020, and load decreased from 1990 to 1994 and 2007 to 2011. Thus, if we had only conducted this experiment in the early nineties or in the 2010’s, for the 5-10-year span common in experimental monitoring, we might have incorrectly concluded that corn yield and PFP increases succeeded in lowering drainage nitrate exports. This experiment thereby affirms the necessity of long-term monitoring for arriving at accurate conclusions from environmental datasets, especially given climate and other global change (Cowles et al., 2021). In resolving the role, or rather lack thereof, of corn yield increase in reducing nitrate surplus, by eliminating the confounding variable of fertilizer increase present in the broader landscape, this study also demonstrates the value of long-term experiments specifically. While these results come from only one site in north-central Iowa, it is likely that corn yields have increased at least partially independently of fertilizer rates, while similarly not solving the nitrate export problem, throughout the U.S. Corn Belt and beyond.
Conclusions
This experiment documents a lack of reduction in drainage nitrate export by increase in corn yields at a consistent fertilizer rate over more than thirty years. The economic incentive to increase grain yields will not get the US Midwest or other areas predominated by industrial corn agriculture out of their nitrate problems. Instead, the Mississippi-Atchafalaya River Basin, Gulf of Mexico, and other affected waters require active conservation efforts, as wide, deep, and inclusive as the problems that created the need, for their water quality to improve.
Acknowledgments
Dozens of Iowa State University students and staff collected experimental data and maintained the experiment over the years. This experimental data is part of the Iowa Agricultural Drainage and Nutrient Studies, which is a cooperative project between the Iowa Department of Agriculture and Land Stewardship and Iowa State University and has been supported, in part, through funds authorized by the Iowa Groundwater Protection Act. In addition, research from 2011 to 2015 was part of a regional collaborative project supported by the USDA-National Institute of Food and Agriculture, award number 2011-68002-30190, "Cropping Systems Coordinated Agricultural Project: Climate Change, Mitigation, and Adaptation in Corn-based Cropping Systems."
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