Soil organic carbon loss decreases biodiversity but stimulates multitrophic interactions that promote belowground metabolism.

Soil organic carbon (SOC) plays an essential role in mediating community structure and metabolic activities of belowground biota. Unraveling the evolution of belowground communities and their feedback mechanisms on SOC dynamics helps embed the ecology of soil microbiome into carbon cycling, which serves to improve biodiversity conservation and carbon management strategy under global change. Here, croplands with a SOC gradient were used to understand how belowground metabolisms and SOC decomposition were linked to the diversity, composition, and co-occurrence networks of belowground communities encompassing archaea, bacteria, fungi, protists, and invertebrates. As SOC decreased, the diversity of prokaryotes and eukaryotes also decreased, but their network complexity showed contrasting patterns: prokaryotes increased due to intensified niche overlap, while that of eukaryotes decreased possibly because of greater dispersal limitation owing to the breakdown of macroaggregates. Despite the decrease in biodiversity and SOC stocks, the belowground metabolic capacity was enhanced as indicated by increased enzyme activity and decreased enzymatic stoichiometric imbalance. This could, in turn, expedite carbon loss through respiration, particularly in the slow-cycling pool. The enhanced belowground metabolic capacity was dominantly driven by greater multitrophic network complexity and particularly negative (competitive and predator-prey) associations, which fostered the stability of the belowground metacommunity. Interestingly, soil abiotic conditions including pH, aeration, and nutrient stocks, exhibited a less significant role. Overall, this study reveals a greater need for soil C resources across multitrophic levels to maintain metabolic functionality as declining SOC results in biodiversity loss. Our researchers highlight the importance of integrating belowground biological processes into models of SOC turnover, to improve agroecosystem functioning and carbon management in face of intensifying anthropogenic land-use and climate change.

Soil depth and geographic distance modulate bacterial ß-diversity in deep soil profiles throughout the U.S. Corn Belt.

Understanding how microbial communities are shaped across spatial dimensions is of fundamental importance in microbial ecology. However, most studies on soil biogeography have focused on the topsoil microbiome, while the factors driving the subsoil microbiome distribution are largely unknown. Here we used 16S rRNA amplicon sequencing to analyse the factors underlying the bacterial ß-diversity along vertical (0-240 cm of soil depth) and horizontal spatial dimensions (~500,000 km2 ) in the U.S. Corn Belt. With these data we tested whether the horizontal or vertical spatial variation had stronger impacts on the taxonomic (Bray-Curtis) and phylogenetic (weighted Unifrac) ß-diversity. Additionally, we assessed whether the distance-decay (horizontal dimension) was greater in the topsoil (0-30 cm) or subsoil (in each 30 cm layer from 30-240 cm) using Mantel tests. The influence of geographic distance versus edaphic variables on the bacterial communities from the different soil layers was also compared. Results indicated that the phylogenetic ß-diversity was impacted more by soil depth, while the taxonomic ß-diversity changed more between geographic locations. The distance-decay was lower in the topsoil than in all subsoil layers analysed. Moreover, some subsoil layers were influenced more by geographic distance than any edaphic variable, including pH. Although different factors affected the topsoil and subsoil biogeography, niche-based models explained the community assembly of all soil layers. This comprehensive study contributed to elucidating important aspects of soil bacterial biogeography including the major impact of soil depth on the phylogenetic ß-diversity, and the greater influence of geographic distance on subsoil than on topsoil bacterial communities in agroecosystems.

Oxygen availability regulates the quality of soil dissolved organic matter by mediating microbial metabolism and iron oxidation.

Dissolved organic matter (DOM) plays a vital role in biogeochemical processes and in determining the responses of soil organic matter (SOM) to global change. Although the quantity of soil DOM has been inventoried across diverse spatio-temporal scales, the underlying mechanisms accounting for variability in DOM dynamics remain unclear especially in upland ecosystems. Here, a gradient of SOM storage across 12 croplands in northeast China was used to understand links between DOM dynamics, microbial metabolism, and abiotic conditions. We assessed the composition, biodegradability, and key biodegradable components of DOM. In addition, SOM and mineral-associated organic matter (MAOM) composition, soil enzyme activities, oxygen availability, soil texture, and iron (Fe), Fe-bound organic matter, and nutrient concentrations were quantified to clarify the drivers of DOM quality (composition and biodegradability). The proportion of biodegradable DOM increased exponentially with decreasing initial DOM concentration due to larger fractions of depolymerized DOM that was rich in small-molecular phenols and proteinaceous components. Unexpectedly, the composition of DOM was decoupled from that of SOM or MAOM, but significantly related to enzymatic properties. These results indicate that microbial metabolism exhibited a dominant role in DOM generation. As DOM concentration declined, increased soil oxygen availability regulated DOM composition and enhanced its biodegradability mainly through mediating microbial metabolism and Fe oxidation. The oxygen-induced oxidation of Fe(II) to Fe(III) removed complex DOM compounds with large molecular weight. Moreover, increased oxygen availability stimulated oxidase-catalyzed depolymerization of aromatic substances, and promoted production of protein-like DOM components due to lower enzymatic C/N acquisition ratio. As global changes in temperature and moisture will have large impacts on soil oxygen availability, the role of oxygen in regulating DOM dynamics highlights the importance of integrating soil oxygen supply with microbial metabolism and Fe redox status to improve model predictions of soil carbon under climate change.

Lengthening of maize maturity time is not a widespread climate change adaptation strategy in the US Midwest.

Increasing temperatures in the US Midwest are projected to reduce maize yields because warmer temperatures hasten reproductive development and, as a result, shorten the grain fill period. However, there is widespread expectation that farmers will mitigate projected yield losses by planting longer season hybrids that lengthen the grain fill period. Here, we ask: (a) how current hybrid maturity length relates to thermal availability of the local climate, and (b) if farmers are shifting to longer season hybrids in response to a warming climate. To address these questions, we used county-level Pioneer brand hybrid sales (Corteva Agriscience) across 17 years and 650 counties in 10 Midwest states (IA, IL, IN, MI, MN, MO, ND, OH, SD, and WI). Northern counties were shown to select hybrid maturities with growing degree day (GDD°C) requirements more closely related to the environmentally available GDD compared to central and southern counties. This measure, termed "thermal overlap," ranged from complete 106% in northern counties to a mere 63% in southern counties. The relationship between thermal overlap and latitude was fit using split-line regression and a breakpoint of 42.8°N was identified. Over the 17-years, hybrid maturities shortened across the majority of the Midwest with only a minority of counties lengthening in select northern and southern areas. The annual change in maturity ranged from -5.4 to 4.1 GDD year-1 with a median of -0.9 GDD year-1 . The shortening of hybrid maturity contrasts with widespread expectations of hybrid maturity aligning with magnitude of warming. Factors other than thermal availability appear to more strongly impact farmer decision-making such as the benefit of shorter maturity hybrids on grain drying costs, direct delivery to ethanol biorefineries, field operability, labor constraints, and crop genetics availability. Prediction of hybrid choice under future climate scenarios must include climatic factors, physiological-genetic attributes, socio-economic, and operational constraints.

Extreme weather-year sequences have nonadditive effects on environmental nitrogen losses.

The frequency and intensity of extreme weather years, characterized by abnormal precipitation and temperature, are increasing. In isolation, these years have disproportionately large effects on environmental N losses. However, the sequence of extreme weather years (e.g., wet-dry vs. dry-wet) may affect cumulative N losses. We calibrated and validated the DAYCENT ecosystem process model with a comprehensive set of biogeophysical measurements from a corn-soybean rotation managed at three N fertilizer inputs with and without a winter cover crop in Iowa, USA. Our objectives were to determine: (i) how 2-year sequences of extreme weather affect 2-year cumulative N losses across the crop rotation, and (ii) if N fertilizer management and the inclusion of a winter cover crop between corn and soybean mitigate the effect of extreme weather on N losses. Using historical weather (1951-2013), we created nine 2-year scenarios with all possible combinations of the driest ("dry"), wettest ("wet"), and average ("normal") weather years. We analyzed the effects of these scenarios following several consecutive years of relatively normal weather. Compared with the normal-normal 2-year weather scenario, 2-year extreme weather scenarios affected 2-year cumulative NO3- leaching (range: -93 to +290%) more than N2 O emissions (range: -49 to +18%). The 2-year weather scenarios had nonadditive effects on N losses: compared with the normal-normal scenario, the dry-wet sequence decreased 2-year cumulative N2 O emissions while the wet-dry sequence increased 2-year cumulative N2 O emissions. Although dry weather decreased NO3- leaching and N2 O emissions in isolation, 2-year cumulative N losses from the wet-dry scenario were greater than the dry-wet scenario. Cover crops reduced the effects of extreme weather on NO3- leaching but had a lesser effect on N2 O emissions. As the frequency of extreme weather is expected to increase, these data suggest that the sequence of interannual weather patterns can be used to develop short-term mitigation strategies that manipulate N fertilizer and crop rotation to maximize crop N uptake while reducing environmental N losses.

Integrating plant litter quality, soil organic matter stabilization, and the carbon saturation concept.

Labile, 'high-quality', plant litters are hypothesized to promote soil organic matter (SOM) stabilization in mineral soil fractions that are physicochemically protected from rapid mineralization. However, the effect of litter quality on SOM stabilization is inconsistent. High-quality litters, characterized by high N concentrations, low C/N ratios, and low phenol/lignin concentrations, are not consistently stabilized in SOM with greater efficiency than 'low-quality' litters characterized by low N concentrations, high C/N ratios, and high phenol/lignin concentrations. Here, we attempt to resolve these inconsistent results by developing a new conceptual model that links litter quality to the soil C saturation concept. Our model builds on the Microbial Efficiency-Matrix Stabilization framework (Cotrufo et al., 2013) by suggesting the effect of litter quality on SOM stabilization is modulated by the extent of soil C saturation such that high-quality litters are not always stabilized in SOM with greater efficiency than low-quality litters.

Does nitrogen fertilizer application rate to corn affect nitrous oxide emissions from the rotated soybean crop?

Little information exists on the potential for N fertilizer application to corn ( L.) to affect NO emissions during subsequent unfertilized crops in a rotation. To determine if N fertilizer application to corn affects NO emissions during subsequent crops in rotation, we measured NO emissions for 3 yr (2011-2013) in an Iowa, corn-soybean [ (L.) Merr.] rotation with three N fertilizer rates applied to corn (0 kg N ha, the recommended rate of 135 kg N ha, and a high rate of 225 kg N ha); soybean received no N fertilizer. We further investigated the potential for a winter cereal rye ( L.) cover crop to interact with N fertilizer rate to affect NO emissions from both crops. The cover crop did not consistently affect NO emissions. Across all years and irrespective of cover crop, N fertilizer application above the recommended rate resulted in a 16% increase in mean NO flux rate during the corn phase of the rotation. In 2 of the 3 yr, N fertilizer application to corn (0-225 kg N ha) did not affect mean NO flux rates from the subsequent unfertilized soybean crop. However, in 1 yr after a drought, mean NO flux rates from the soybean crops that received 135 and 225 kg N ha N application in the corn year were 35 and 70% higher than those from the soybean crop that received no N application in the corn year. Our results are consistent with previous studies demonstrating that cover crop effects on NO emissions are not easily generalizable. When N fertilizer affects NO emissions during a subsequent unfertilized crop, it will be important to determine if total fertilizer-induced NO emissions are altered or only spread across a greater period of time.

Comparing nitrate sink strength in perennial filter strips at toeslopes of cropland watersheds.

Integration of perennial filter strips (PFS) into the toeslopes of agricultural watersheds may decrease downstream nitrate (NO) losses. However, long-term NO removal depends on the relative importance of several NO sinks in the PFS. Plant biomass and labile soil organic matter (SOM) are temporary NO sinks, while stable SOM is a long-term, but potentially finite, NO sink. In contrast, denitrification is a permanent NO sink. We investigated the relative importance of these NO sinks in PFS at the toeslope of row crop watersheds in Iowa. Using 25- × 30-cm in situ mesocosms, we added NO to PFS soils and quantified NO-N recovery in plant biomass and SOM after one growing season. Further, we compared NO-N recovery in particulate (relatively labile) and mineral-associated (relatively stable) SOM in mesocosms with and without growing perennial vegetation. To determine the potential importance of denitrification, we compared denitrification enzyme activity in soils from paired watersheds with and without PFS. Transfer of NO-N into labile and stable SOM pools was rapid and initially independent of growing vegetation. However, SOM and plant biomass were both relatively minor NO sinks, accounting for <30% of NO-N inputs. Denitrification enzyme activity data indicated that dissolved organic carbon derived from perennial vegetation increased potential denitrifier activity in PFS soils compared with row crop soils. Together, these results constrain SOM and plant biomass as NO sinks and indicate that denitrification was the most important NO sink in perennial filter strips over one growing season.

A long-term nitrogen fertilizer gradient has little effect on soil organic matter in a high-intensity maize production system.

Global maize production alters an enormous soil organic C (SOC) stock, ultimately affecting greenhouse gas concentrations and the capacity of agroecosystems to buffer climate variability. Inorganic N fertilizer is perhaps the most important factor affecting SOC within maize-based systems due to its effects on crop residue production and SOC mineralization. Using a continuous maize cropping system with a 13 year N fertilizer gradient (0-269 kg N ha(-1) yr(-1)) that created a large range in crop residue inputs (3.60-9.94 Mg dry matter ha(-1) yr(-1)), we provide the first agronomic assessment of long-term N fertilizer effects on SOC with direct reference to N rates that are empirically determined to be insufficient, optimum, and excessive. Across the N fertilizer gradient, SOC in physico-chemically protected pools was not affected by N fertilizer rate or residue inputs. However, unprotected particulate organic matter (POM) fractions increased with residue inputs. Although N fertilizer was negatively linearly correlated with POM C/N ratios, the slope of this relationship decreased from the least decomposed POM pools (coarse POM) to the most decomposed POM pools (fine intra-aggregate POM). Moreover, C/N ratios of protected pools did not vary across N rates, suggesting little effect of N fertilizer on soil organic matter (SOM) after decomposition of POM. Comparing a N rate within 4% of agronomic optimum (208 kg N ha(-1) yr(-1)) and an excessive N rate (269 kg N ha(-1) yr(-1)), there were no differences between SOC amount, SOM C/N ratios, or microbial biomass and composition. These data suggest that excessive N fertilizer had little effect on SOM and they complement agronomic assessments of environmental N losses, that demonstrate N2 O and NO3 emissions exponentially increase when agronomic optimum N is surpassed.

Benefitting productivity and the environment: Current and future maize cropping systems improve yield while reducing nitrate load.

Increases in cereal crop yield per area have increased global food security. "Era" studies compare historical and modern crop varieties in controlled experimental settings and are routinely used to understand how advances in crop genetics and management affect crop yield. However, to date, no era study has explored how advances in maize (Zea mays L.) genetics and management (i.e., cropping systems) have affected environmental outcomes. Here, we developed a cropping systems era study in Iowa, USA, to examine how yield and nitrate losses have changed from "Old" systems common in the 1990s to "Current" systems common in the 2010s, and to "Future" systems projected to be common in the 2030s. We tested the following hypothesis: If maize yield and nitrogen use efficiency have improved over previous decades, Current and Future maize systems will have benefits to water quality compared to Old systems. We show that not only have maize yield and nitrogen use efficiency (kg grain kg-1 N), on average, improved over time but also yield-scaled nitrate load + soil nitrate was reduced by 74% and 91% from Old to Current and Future systems, respectively. Continuing these trajectories of improvement will be critical to meet the needs of a growing and more affluent population while reducing deleterious effects of agricultural systems on ecosystem services.

Unlocking complex soil systems as carbon sinks: multi-pool management as the key.

Much research focuses on increasing carbon storage in mineral-associated organic matter (MAOM), in which carbon may persist for centuries to millennia. However, MAOM-targeted management is insufficient because the formation pathways of persistent soil organic matter are diverse and vary with environmental conditions. Effective management must also consider particulate organic matter (POM). In many soils, there is potential for enlarging POM pools, POM can persist over long time scales, and POM can be a direct precursor of MAOM. We present a framework for context-dependent management strategies that recognizes soils as complex systems in which environmental conditions constrain POM and MAOM formation.

Phenotypic and genome-wide association analyses for nitrogen use efficiency related traits in maize (Zea mays L.) exotic introgression lines.

Nitrogen (N) limits crop production, yet more than half of N fertilizer inputs are lost to the environment. Developing maize hybrids with improved N use efficiency can help minimize N losses and in turn reduce adverse ecological, economical, and health consequences. This study aimed to identify single nucleotide polymorphisms (SNPs) associated with agronomic traits (plant height, grain yield, and anthesis to silking interval) under high and low N conditions. A genome-wide association study (GWAS) was conducted using 181 doubled haploid (DH) lines derived from crosses between landraces from the Germplasm Enhancement of Maize (BGEM lines) project and two inbreds, PHB47 and PHZ51. These DH lines were genotyped using 62,077 SNP markers. The same lines from the per se trials were used as parental lines for the testcross field trials. Plant height, anthesis to silking interval, and grain yield were collected from high and low N conditions in three environments for both per se and testcross trials. We used three GWAS models, namely, general linear model (GLM), mixed linear model (MLM), and Fixed and Random model Circulating Probability Unification (FarmCPU) model. We observed significant genetic variation among the DH lines and their derived testcrosses. Interestingly, some testcrosses of exotic introgression lines were superior under high and low N conditions compared to the check hybrid, PHB47/PHZ51. We detected multiple SNPs associated with agronomic traits under high and low N, some of which co-localized with gene models associated with stress response and N metabolism. The BGEM panel is, thus, a promising source of allelic diversity for genes controlling agronomic traits under different N conditions.

In Planta Nitrate Sensor Using a Photosensitive Epoxy Bioresin.

Nitrogen management through monitoring of crop nitrate status can improve agricultural productivity, profitability, and environmental performance. Current plant nitrate test methods require expensive instruments, time-intensive labor, and trained personnel. Frequent monitoring of in planta nitrate levels of the stalks in living plants can help to better understand the nitrogen cycle and the physiological responses to environmental variations. Although existing enzymatic electrochemical sensors provide high selectivity, they suffer from short shelf life, high cost, low-temperature storage requirement, and potential degradation over time. To overcome these issues, an artificial enzyme (vitamin B12 or VB12) and a two-dimensional material (graphene oxide or GO) are introduced into a conventional photoresist (SU8) to form a bioresin SU8-GO-VB12 that can be patterned with photolithography and laser-pyrolyzed into a carbon-based nanocomposite C-GO-VB12. The electrocatalytic activity of the cobalt factor in VB12, the surface enhancement properties of GO, and the porous feature of pyrolytic carbon are synergized through design to provide C-GO-VB12 with a superior ability to detect nitrate ions through redox reactions. In addition, laser writing-based selective pyrolysis allows applying thermal energy to target only SU8-GO-VB12 for selective pyrolysis of the bioresin into C-GO-VB12, thus reducing the total energy input and avoiding the thermal influence on the materials and structures in other areas of the substrate. The C-GO-VB12 nitrate sensor demonstrates a year-long shelf lifetime, high selectivity, and a wide dynamic range that enables a direct nitrate test for the extracted sap of maize stalk. For in situ monitoring of the nitrate level and dynamic changes in living maize plants, a microelectromechanical system-based needle sensor is formed with C-GO-VB12. The needle sensor allows direct insertion into the plant for in situ measurement of nitrate ions under different growth environments over time. The needle sensor represents a new method for monitoring in planta nitrate dynamics with no need for sample preparation, thus making a significant impact in plant sciences.

Nitrate losses across 29 Iowa watersheds: Measuring long-term trends in the context of interannual variability.

In the U.S. Corn Belt, annual croplands are the primary source of nitrate loading to waterways. Long periods of fallow cause most nitrate loss, but there is extreme interannual variability in the magnitude of nitrate loss due to weather. Using mean annual (2001-2018) flow-weighted nitrate-N concentration (FWNC; mg NO3 - -N L-1 ), load (kg NO3 - -N), and yield (kg NO3 - -N ha-1 cropland) for 29 watersheds, our objectives were (a) to quantify the magnitude and interannual variability of 5-yr moving average FWNC, load, and yield; (2) to estimate the probability of measuring 41% reductions in nitrate loss after isolating the effect of weather on nitrate loss by quantifying the interannual variability of nitrate loss in watersheds where there was no trend in 5-yr moving average nitrate loss (Iowa targets a 41% nitrate loss reduction from croplands); and (c) to identify factors that, in the absence of long-term trends in nitrate loss, best explain the interannual variability in nitrate loss. Averaged across all watersheds, the mean probability of measuring a statistically significant 41% reduction in FWNC across 15 yr, should it occur, was 96%. However, the probabilities of measuring 41% reductions in nitrate load and yield were only 44 and 32%. Across watersheds, soil organic matter, tile drainage, interannual variability of precipitation, and watershed area accounted for interannual variability in these nitrate loss indices. Our results have important implications for setting realistic timelines to measure nitrate loss reductions against the background of interannual weather variation and can help to target monitoring intensity across diverse watersheds.

Climate Change and Management Impacts on Soybean N Fixation, Soil N Mineralization, N2O Emissions, and Seed Yield.

Limited knowledge about how nitrogen (N) dynamics are affected by climate change, weather variability, and crop management is a major barrier to improving the productivity and environmental performance of soybean-based cropping systems. To fill this knowledge gap, we created a systems understanding of agroecosystem N dynamics and quantified the impact of controllable (management) and uncontrollable (weather, climate) factors on N fluxes and soybean yields. We performed a simulation experiment across 10 soybean production environments in the United States using the Agricultural Production Systems sIMulator (APSIM) model and future climate projections from five global circulation models. Climate change (2020-2080) increased N mineralization (24%) and N2O emissions (19%) but decreased N fixation (32%), seed N (20%), and yields (19%). Soil and crop management practices altered N fluxes at a similar magnitude as climate change but in many different directions, revealing opportunities to improve soybean systems' performance. Among many practices explored, we identified two solutions with great potential: improved residue management (short-term) and water management (long-term). Inter-annual weather variability and management practices affected soybean yield less than N fluxes, which creates opportunities to manage N fluxes without compromising yields, especially in regions with adequate to excess soil moisture. This work provides actionable results (tradeoffs, synergies, directions) to inform decision-making for adapting crop management in a changing climate to improve soybean production systems.

Agricultural Management Affects the Active Rhizosphere Bacterial Community Composition and Nitrification.

Cropping system diversity provides yield benefits that may result from shifts in the composition of root-associated bacterial and fungal communities, which either enhance nutrient availability or limit nutrient loss. We investigated whether temporal diversity of annual cropping systems (four versus two crops in rotation) influences the composition and metabolic activities of root-associated microbial communities in maize at a developmental stage when the peak rate of nitrogen uptake occurs. We monitored total (DNA-based) and potentially active (RNA-based) bacterial communities and total (DNA-based) fungal communities in the soil, rhizosphere, and endosphere. Cropping system diversity strongly influenced the composition of the soil microbial communities, which influenced the recruitment of the resident microbial communities and, in particular, the potentially active rhizosphere and endosphere bacterial communities. The diversified cropping system rhizosphere recruited a more diverse bacterial community (species richness), even though there was little difference in soil species richness between the two cropping systems. In contrast, fungal species richness was greater in the conventional rhizosphere, which was enriched in fungal pathogens; the diversified rhizosphere, however, was enriched in Glomeromycetes. While cropping system influenced endosphere community composition, greater correspondence between DNA- and RNA-based profiles suggests a higher representation of active bacterial populations. Cropping system diversity influenced the composition of ammonia oxidizers, which coincided with diminished potential nitrification activity and gross nitrate production rates, particularly in the rhizosphere. The results of our study suggest that diversified cropping systems shift the composition of the rhizosphere's active bacterial and total fungal communities, resulting in tighter coupling between plants and microbial processes that influence nitrogen acquisition and retention. IMPORTANCE Crops in simplified, low-diversity agroecosystems assimilate only a fraction of the inorganic nitrogen (N) fertilizer inputs. Much of this N fertilizer is lost to the environment as N oxides, which degrade water quality and contribute to climate change and loss of biodiversity. Ecologically inspired management may facilitate mutualistic interactions between plant roots and microbes to liberate nutrients when plants need them, while also decreasing nutrient loss and pathogen pressure. In this study, we investigate the effects of a conventional (2-year rotation, inorganic fertilization) and a diversified (4-year rotation, manure amendments) cropping system on the assembly of bacterial and fungal root-associated communities, at a maize developmental stage when nitrogen demand is beginning to increase. Our results indicate that agricultural management influences the recruitment of root-associated microbial communities and that diversified cropping systems have lower rates of nitrification (particularly in the rhizosphere), thereby reducing the potential for loss of nitrate from these systems.

Revisiting Biological Nitrogen Fixation Dynamics in Soybeans.

Biological nitrogen (N) fixation is the most relevant process in soybeans (Glycine max L.) to satisfy plant N demand and sustain seed protein formation. Past studies describing N fixation for field-grown soybeans mainly focused on a single point time measurement (mainly toward the end of the season) and on the partial N budget (fixed-N minus seed N removal), overlooking the seasonal pattern of this process. Therefore, this study synthesized field datasets involving multiple temporal measurements during the crop growing season to characterize N fixation dynamics using both fixed-N (kg ha-1) and N derived from the atmosphere [Ndfa (%)] to define: (i) time to the maximum rate of N fixation (ß2), (ii) time to the maximum Ndfa (α2), and (iii) the cumulative fixed-N. The main outcomes of this study are that (1) the maximum rate of N fixation was around the beginning of pod formation (R3 stage), (2) time to the maximum Ndfa (%) was after full pod formation (R4), and (3) cumulative fixation was positively associated with the seasonal vapor-pressure deficit (VPD) and growth cycle length but negatively associated with soil clay content, and (4) time to the maximum N fixation rate (ß2) was positively impacted by season length and negatively impacted by high temperatures during vegetative growth (but positively for VPD, during the same period). Overall, variation in the timing of the maximum rate of N fixation occurred within a much narrower range of growth stages (R3) than the timing of the maximum Ndfa (%), which varied broadly from flowering (R1) to seed filing (R5-R6) depending on the evaluated studies. From a phenotyping standpoint, N fixation determinations after the R4 growth stage would most likely permit capturing both maximum fixed-N rate and maximum Ndfa (%). Further investigations that more closely screen the interplay between N fixation with soil-plant-environment factors should be pursued.

Modeling Flood-Induced Stress in Soybeans.

Despite the detrimental impact that excess moisture can have on soybean (Glycine max [L.] Merr) yields, most of today's crop models do not capture soybean's dynamic responses to waterlogged conditions. In light of this, we synthesized literature data and used the APSIM software to enhance the modeling capacity to simulate plant growth, development, and N fixation response to flooding. Literature data included greenhouse and field experiments from across the U.S. that investigated the impact of flood timing and duration on soybean. Five datasets were used for model parameterization of new functions and three datasets were used for testing. Improvements in prediction accuracy were quantified by comparing model performance before and after the implementation of new stage-dependent excess water functions for phenology, photosynthesis and N-fixation. The relative root mean square error (RRMSE) for yield predictions improved by 26% and the RRMSE predictions of biomass improved by 40%. Extensive model testing found that the improved model accurately simulates plant responses to flooding including how these responses change with flood timing and duration. When used to project soybean response to future climate scenarios, the model showed that intense rain events had a greater negative effect on yield than a 25% increase in rainfall distributed over 1 or 3 month(s). These developments advance our ability to understand, predict and, thereby, mitigate yield loss as increases in climatic volatility lead to more frequent and intense flooding events in the future.