Source of the soybean N credit in maize production

Nitrogen response trials throughout the United States Corn Belt show that economic optimum rates of N fertilization are usually less for maize (Zea mays L.) following soybean (Glycine max L.) than for maize following maize; however, the cause of this rotation effect is not fully understood. The objective of this study was to investigate the source of the apparent N contribution from soybean to maize (soybean N credit) by comparing soil N mineralization rates in field plots of unfertilized maize that had either nodulated soybean, non-nodulated soybean, or maize as the previous crop. Crop yields, plant N accumulation, soil inorganic N, and net soil mineralization were measured. Both grain yield (6.3 vs. 2.8 Mg ha^–1) and above-ground N accumulation (97 vs. 71 kg ha^–1) were greatly increased when maize followed nodulated soybean compared with maize following maize. A partial benefit to yield and N accumulation was also observed for maize following non-nodulated soybean. Cumulative net soil N mineralization following nodulated soybean, non-nodulated soybean, and maize was 112, 92 and 79 kg N ha^–1, respectively. Net mineralization of soil N appeared to be influenced by both quality (C:N ratio) and quantity of residue from the previous crop. In addition to an increase in plant available N from mineralization, the amount of soil inorganic N (especially in soil 5 cm from the row) was greater following nodulated soybean than non-nodulated soybean or maize. Based on these data, the soybean N credit appears to result from a combination of a decrease in net soil mineralization in continuous maize production and an increase in residual soil N from symbiotic fixation.     

Effects of Crop Diversity on Agroecosystem Function: Crop Yield Response

Understanding the role of diversity in the functioning of ecosystems has important implications for agriculture. Previous agricultural research has shown that crop rotation and the use of cover crops can lead to increases in yield relative to monoculture; however, few studies have been performed within the broader context of diversity–ecosystem function theory and in the absence of chemical inputs. We performed a field experiment in SW Michigan, USA, in which we manipulated the number of crop species grown in rotation and as winter cover crops over a 3-year period to test if varying the number of species in a rotation affected grain yield, a critical metric of ecosystem function in row-crops. The experimental design was unique in that no fertilizer or pesticides were used, and the only management variable manipulated was number of species in the rotation, thus providing a strong comparison to grassland diversity–ecosystem function experiments. Treatments included continuous monocultures of three row-crops, corn Zea mays L., soybean Glycine max (L.) Merr., and winter wheat Triticum aestivum L., and 2- and 3-year annual rotations with and without cover crops (zero, one, or two legume/small grain species), encompassing a range of crop diversity from one to six species. Crop yields and weed biomass were measured annually for 3 years and plant available soil nitrogen was measured over the course of the growing season in the final year of the study. In all 3 years, corn grain yield increased linearly in response to the number of crops in the rotation. Corn yields in the highest diversity treatment (three crops, plus three cover crops) were over 100% higher than in continuous monoculture and were not significantly different from the county average for each of the 3 years despite the absence of chemical inputs. Corn yields in the diversity treatments were strongly correlated with the availability of inorganic soil nitrogen, which was likely influenced by the number of different legume species (crops and cover crops) present in the rotation. In soybean and winter wheat, yield differences among crop diversity treatments were also significant, but of lower magnitude (32 and 53%, respectively), and showed little direct relationship to the number of crop species grown in a rotation. Results demonstrate that agricultural research motivated by ecological theory can provide important insights into the functioning of agroecosystems and enhance our understating of the linkages between diversity and ecosystem function. Importantly, these results suggest that reduced chemical inputs do not necessarily result in yield penalties and provide support for incorporation of crop or species diversity when determining how ecosystem services can be included in food, fiber, and biofuel production.     

Will photosynthesis of maize (Zea mays) in the US Corn Belt increase in future [CO2] rich atmospheres? An analysis of diurnal courses of CO2 uptake under free‐air concentration enrichment (FACE)

The C₄ grass Zea mays (maize or corn) is the third most important food crop globally in terms of production and demand is predicted to increase 45% from 1997 to 2020. However, the effects of rising [CO₂] upon C₄ plants, and Z. mays specifically, are not sufficiently understood to allow accurate predictions of future crop production. A rainfed, field experiment utilizing free‐air concentration enrichment (FACE) technology in the primary area of global corn production (US Corn Belt) was undertaken to determine the effects of elevated [CO₂] on corn. FACE technology allows experimental treatments to be imposed upon a complete soil–plant–atmosphere continuum with none of the effects of experimental enclosures on plant microclimate. Crop performance was compared at ambient [CO₂] (354 μ mol mol^?1) and the elevated [CO₂] (549 μmol mol^?1) predicted for 2050. Previous laboratory studies suggest that under favorable growing conditions C₄ photosynthesis is not typically enhanced by elevated [CO₂]. However, stomatal conductance and transpiration are decreased, which can indirectly increase photosynthesis in dry climates. Given the deep soils and relatively high rainfall of the US Corn Belt, it was predicted that photosynthesis would not be enhanced by elevated [CO₂]. The diurnal course of gas exchange of upper canopy leaves was measured in situ across the growing season of 2002. Contrary to the prediction, growth at elevated [CO₂] significantly increased leaf photosynthetic CO₂ uptake rate (A) by up to 41%, and 10% on average. Greater A was associated with greater intercellular [CO₂], lower stomatal conductance and lower transpiration. Summer rainfall during 2002 was very close to the 50‐year average for this site, indicating that the year was not atypical or a drought year. The results call for a reassessment of the established view that C₄ photosynthesis is insensitive to elevated [CO₂] under favorable growing conditions and that the production potential of corn in the US Corn Belt will not be affected by the global rise in [CO₂].     

The Impact of White-Tailed Deer on Agricultural Landscapes in 3 National Historical Parks in Maryland

Abstract: The legislative authorization of some United States national historical parks (NHP) includes maintaining an agricultural landscape as a management objective. This management objective can prove difficult to accomplish in some NHP given increasing white-tailed deer (Odocoileus virginianus) densities. Our goal was to quantify the impact of white-tailed deer foraging on agricultural landscapes in forested NHPs in Maryland, USA. We monitored 12 and 13 corn (Zea mays) fields at 3 NHP during the 2003 and 2004, respectively. Each field had ***3 5 × 5-m fenced and unfenced plots along the edge and a similar set within the interior of the field. Within each plot we examined the number of stalks with corn, corn ear quality, and field weight prior to harvest. Fenced plots had higher weights of corn, more stalks with corn ears, and higher quality corn than unfenced plots. Estimates of silage yield based on crop weights indicate deer reduced silage yield in individual fields by 5-43% during the study period. Crop loss differed between years and fields, with plots in the Chesapeake and Ohio Canal NHP sustaining the highest crop weight loss (28%). Eventual crop loss was correlated with proportion of corn plants browsed within 2 weeks of emergence. Some variability in loss between fields was due to landscape metrics, as fields surrounded by more forest experienced the highest loss. Our results indicate the NHP agriculture fields we studied receive significant deer damage to corn crops and may not be able to maintain mandated management without regulating deer numbers.     

Developing a photosynthetic sterility model to estimate CO2 fixation through the crop yield in Asia with the aid of MODIS data

Remote sensing technologies have been advanced continuously to a certain level for multi-scale applications to ease social and political concerns resulting from food security. In this study, an integrated monitoring, sensing and modeling system for estimating CO₂ fixation and grain yields using a photosynthetic sterility model was developed. Input data for model computation include observed meteorological data, numerical prediction reanalysis data, and satellite data such as solar radiation, land-cover and Normalized Difference Vegetation Index (NDVI) on a continental scale. Model validation requires crop yields and the Crop Situation Index (CSI) was provided by the Japanese government. It also demonstrates the application potential of this system to grain fields of paddy rice, winter wheat, and maize in Southeast Asia. The carbon hydrate in grains has the same chemical formula as that of cellulose in grain vegetation. The partition of sequestered CO₂ into grain, straw, and root portions of plant biomass weight was computed. The present photosynthesis model was evaluated using the mass of carbon included in the harvested grains of provincial crop production. Results indicate that the proposed system successfully estimates the photosynthesis fixation of rice reasonably well in Japan and China through the analysis of carbon in grains. However, the model tends to underestimate the photosynthesis rates for winter wheat and maize. The parameterization of radiation response function and the temperature response functions for low-temperature sterility need to be improved in the future.     

The influence of feedstock supply risk on location of stover‐based bio‐gasoline plants

This study models and quantifies spatially referenced probability distributions of corn residue cost and assesses their influence on comparative advantages of different areas of the Corn Belt to attract biofuel plants. Results suggest that irrigated areas of the Corn Belt, despite their relatively low planting density, may result more attractive than some of their rainfed counterparts in the eastern Corn Belt due to low risk in feedstock cost resulting from stability of yields. Therefore, agricultural districts in the Great Plains of the US may not need to pay high subsidies to compete with those in the eastern Corn Belt to attract biofuel firms. Policy restrictions on irrigation due to concerns over groundwater depletion may, however, diminish the relative comparative advantage of the irrigated Corn Belt for biofuel production.     

Refuge or Reservoir? The Potential Impacts of the Biofuel Crop Miscanthus x giganteus on a Major Pest of Maize

Background

Interest in the cultivation of biomass crops like the C4 grass Miscanthus x giganteus (Miscanthus) is increasing as global demand for biofuel grows. In the US, Miscanthus is promoted as a crop well-suited to the Corn Belt where it could be cultivated on marginal land interposed with maize and soybean. Interactions (direct and indirect) of Miscanthus, maize, and the major Corn Belt pest of maize, the western corn rootworm, (Diabrotica virgifera virgifera LeConte, WCR) are unknown. Adding a perennial grass/biomass crop to this system is concerning since WCR is adapted to the continuous availability of its grass host, maize (Zea mays).

Methodology/Principal Findings

In a greenhouse and field study, we investigated WCR development and oviposition on Miscanthus. The suitability of Miscanthus for WCR development varied across different WCR populations. Data trends indicate that WCR populations that express behavioural resistance to crop rotation performed as well on Miscanthus as on maize. Over the entire study, total adult WCR emergence from Miscanthus (212 WCR) was 29.6% of that from maize (717 WCR). Adult dry weight was 75–80% that of WCR from maize; female emergence patterns on Miscanthus were similar to females developing on maize. There was no difference in the mean no. of WCR eggs laid at the base of Miscanthus and maize in the field.

Conclusions/Significance

Field oviposition and significant WCR emergence from Miscanthus raises many questions about the nature of likely interactions between Miscanthus, maize and WCR and the potential for Miscanthus to act as a refuge or reservoir for Corn Belt WCR. Responsible consideration of the benefits and risks associated with Corn Belt Miscanthus are critical to protecting an agroecosystem that we depend on for food, feed, and increasingly, fuel. Implications for European agroecosystems in which Miscanthus is being proposed are also discussed in light of the WCR''s recent invasion into Europe.     

Semiarid Crop Production from a Hydrological Perspective: Gap between Potential and Actual Yields

Rapid population growth in the dry climate regions, arable land scarcity, and irrigation expansion limitations direct our interest to possibilities of yield increase in rainfed agriculture. Literature, however, indicates large differences between actual and potential yields, and between yields on farmers’ fields and research stations. This article focuses on the determinants of these yield gaps and the windows of opportunity for yield increase on the farmer's field together with the agricultural challenges involved. The study links the conventional approach to estimate crop water requirements and dry spell effects on biomass production to a conceptual Green Water Crop Model. This model addresses the effects on crop yields of the sequential diversions of infiltrating rainfall (rainwater partitioning into runoff, plant available soil water, and deep percolation) and of different relations between nonproductive evaporation flow and productive transpiration flow, defined together as green water flow. Also, the effects of droughts and dry spells are analyzed. The model is used to demonstrate typical situations for semiarid and dry subhumid conditions (lengths of growing period (LGP) of 90 and 179 days, respectively) for maize (Zea mays (L.)) under on-station agricultural conditions. Based on detailed water flow analysis in a 3-year on-farm case study in the Sahel on pearl millet (Pennisetum glaucum (L.) Br.), the model is used to clarify the large scope for improved yield levels, achievable through land and water management securing that runoff losses and deep percolation are reduced and nonproductive evaporation losses minimized. The analysis indicates that poor rainwater partitioning and low plant water uptake capacity alone reduces estimated on-farm grain yields to 1/10th of the potential yields. This suggests that lack of water per se not necessarily is the primary constraint to crop growth even in drought prone areas of sub-Saharan Africa. The conclusion is that even a doubling of crop yields would be agro-hydrologically possible with relatively small manipulations of rainwater partitioning in the water balance.     

A deep learning approach to conflating heterogeneous geospatial data for corn yield estimation: A case study of the US Corn Belt at the county level

Understanding large‐scale crop growth and its responses to climate change are critical for yield estimation and prediction, especially under the increased frequency of extreme climate and weather events. County‐level corn phenology varies spatially and interannually across the Corn Belt in the United States, where precipitation and heat stress presents a temporal pattern among growth phases (GPs) and vary interannually. In this study, we developed a long short‐term memory (LSTM) model that integrates heterogeneous crop phenology, meteorology, and remote sensing data to estimate county‐level corn yields. By conflating heterogeneous phenology‐based remote sensing and meteorological indices, the LSTM model accounted for 76% of yield variations across the Corn Belt, improved from 39% of yield variations explained by phenology‐based meteorological indices alone. The LSTM model outperformed least absolute shrinkage and selection operator (LASSO) regression and random forest (RF) approaches for end‐of‐the‐season yield estimation, as a result of its recurrent neural network structure that can incorporate cumulative and nonlinear relationships between corn yield and environmental factors. The results showed that the period from silking to dough was most critical for crop yield estimation. The LSTM model presented a robust yield estimation under extreme weather events in 2012, which reduced the root‐mean‐square error to 1.47 Mg/ha from 1.93 Mg/ha for LASSO and 2.43 Mg/ha for RF. The LSTM model has the capability to learn general patterns from high‐dimensional (spectral, spatial, and temporal) input features to achieve a robust county‐level crop yield estimation. This deep learning approach holds great promise for better understanding the global condition of crop growth based on publicly available remote sensing and meteorological data.     

Winter oilseed production for biofuel in the US Corn Belt: opportunities and limitations

Interest from the US commercial aviation industry and commitments established by the US Navy and Air Force to use renewable fuels has spurred interest in identifying and developing crops for renewable aviation fuel. Concern regarding greenhouse gas emissions associated with land‐use change and shifting land grown for food to feedstock production for fuel has encouraged the concept of intensifying current prominent cropping systems through various double cropping strategies. Camelina (Camelina sativa L.) and field pennycress (Thlaspi arvense L.) are two winter oilseed crops that could potentially be integrated into the corn (Zea mays L.)–soybean [(Glycine max (L.) Merr.] cropping system, which is the prominent cropping system in the US Corn Belt. In addition to providing a feedstock for renewable aviation fuel production, integrating these crops into corn–soybean cropping systems could also potentially provide a range of ecosystem services. Some of these include soil protection from wind and water erosion, soil organic C (SOC) sequestration, water quality improvement through nitrate reduction, and a food source for pollinators. However, integration of these crops into corn–soybean cropping systems also carries possible limitations, such as potential yield reductions of the subsequent soybean crop. This review identifies and discusses some of the key benefits and constraints of integrating camelina or field pennycress into corn–soybean cropping systems and identifies generalized areas for potential adoption in the US Corn Belt.     

A county‐level estimation of renewable surface water and groundwater availability associated with potential large‐scale bioenergy feedstock production scenarios in the United States

This study examines fresh renewable water resources available for bioenergy feedstock production in the United States. The impacts of feedstock irrigation on surface and groundwater resources available to nonbioenergy sectors were quantified using a pair of water availability indexes: streamflow availability index and percolation flow availability index. The two metrics were applied to both historical (2008) and three possible future biomass production scenarios from the 2016 U.S. Billion‐Ton Report at the county level. For both historical and future scenarios, we found that the consumptive irrigation requirements for bioenergy feedstock account for <0.01% of annual streamflow in all but three counties in Nebraska. Results suggest that the irrigation demand of future biomass production could be supplied by annual renewable groundwater flow in about 94% of feedstock‐growing counties that use groundwater for irrigation, representing about 92% of production tonnage. Counties that require irrigation from nonrenewable groundwater resources are mostly located in the Northern Plains and Pacific regions. We also evaluated the sensitivity of crop water footprint estimation to soil moisture carryover by comparing blue water estimates from six different empirical and process‐based methods. Our findings suggest that accounting for preseason soil moisture is critical for representative blue water estimation, so that the irrigation water consumption is not overestimated. This is especially true in the Corn Belt region, where blue water estimates with and without preseason soil moisture would be about 1.9 versus 45.5 billion m³/year under the historical scenario. This difference is smaller in semiarid regions like the High Plains, but the blue water estimate can still triple if soil moisture is not considered. From the perspective of renewable surface water and groundwater resources, scaling feedstock production up in the High Plains and California will require careful planning integrated with water management strategies to improve water resource conservation.     

Economic Considerations for the Adoption of Transgenic Crops: The Case of Bt Corn

Biotechnology is offering farmers new crop production opportunities and challenges. Prior to selecting a transgenic variety, farmers must consider the cost of the technology fee, possible yield drag, potential pest infestations, possible reductions in pesticide costs, refuge requirements to minimize the development of insect resistance, and adjustments in cultural practices. Moreover, crop segregation in the field, storage, and shipment may be necessary to capture potential price premiums for nontransgenic varieties. As farmers consider these various production and marketing factors, they find that Bt corn is a more profitable control method for European corn borer in the Western Corn Belt relative to the Eastern Corn Belt. This is primarily due to higher infestation probabilities in the Western Corn Belt, coupled with greater demand for manufacturing and export uses in the Eastern Corn Belt where several buyers do not accept transgenic corn.     

Using a Crop Growth Model to Quantify Regional Biogas Potentials: an Example of the Model Region Biberach (South-West Germany)

Over the last decade, political framework conditions in the energy sector provoked a strong focus on biogas production in Germany. In this context, a sufficient and secure regional biomass supply is needed in order to run biogas plants economically. It is important to estimate which biomass amounts can be produced and are available for bioenergy production in a defined region. The present study focused on a model-based approach quantifying the biomass and, from this, the resulting biogas potential of the model region of Biberach (south-west Germany) using the process-oriented crop growth model DSSAT 4.0. Considering the regional soil and climate conditions of the model region, dry matter yields of maize, triticale, and a crop rotation system (CRS) of maize and triticale including different management systems (change in sowing and harvest date) were simulated. The results indicated an adequate model fit between simulated and measured yields. Dry matter yields of maize (14.7 t ha^?1), triticale (12.7 t ha^?1), and the CRS (18.1–19.2 t ha^?1) differed significantly, indicating that the chosen CRS provided the highest dry matter yields. The biomass potential of all crops was simulated considering different bioenergy scenarios depending on the available agricultural land used for bioenergy. The highest biomass potential was provided by the management system consisting of maize and triticale sown on 1 May and 15 October, respectively. Finally, an additional energy potential of 45,000 kW_el (bioenergy scenario 50/50 % of the agricultural land used for biogas production) and of 5,700 kW_el (bioenergy scenario 25/25 % of the agricultural land used for biogas production) was determined for the county of Biberach by implementing a CRS, which consisted of maize and triticale. It could be concluded that an additional biomass potential for biogas production exists in the county. Suitable areas for the location of biogas plants could be identified based on the available biomass potential.     

Did maize domestication and early spread mediate the population genetics of corn leafhopper?

Investigating how crop domestication and early farming mediated crop attributes, distributions, and interactions with antagonists may shed light on today's agricultural pest problems. Crop domestication generally involved artificial selection for traits desirable to early farmers, for example, in creased productivity or yield, and enhanced qualities, though invariably it altered the interactions between crops and insects, and expanded the geographical ranges of crops. Thus, some studies suggest that with crop domestication and spread, insect populations on wild crop ancestors gave rise to pestiferous insect populations on crops. Here, we addressed whether the emergence of corn leafhopper (Dalbulus ma id is) as an agricultural pest may be associated with domestication and early spread of maize (Zea mays mays). We used AFLP markers and mitochondrial COI sequences to assess population genetic structuring and haplotype relationships among corn leafhopper samples from maize and its wild relative Zea diploperennis from multiple locations in Mexico and Argentina. We uncovered seven corn leafhopper haplotypes contained within two haplogroups, one haplogroup containing haplotypes associated with maize and the other containing haplotypes associated with Z. diploperennis in a mountainous habitat. Within the first haplogroup, one haplotype was predominant across Mexican locations, and another across Argentinean locations;both were considered pestiferous. We suggested that the divergence times of the maize-associated haplogroup and of the "pestiferous" haplotypes are correlated with the chronology of maize spread following its domestication. Overall, our results support a hypothesis positing that maize domestication favored corn leafhopper genotypes preadapted for exploiting maize so that they became pestiferous, and that with the geographical expansi on of maize farming, corn leafhopper colonized Z. diploperennis, a host exclusive to secluded habitats that serves as a refuge for archaic corn leafhopper genotypic diversity. Broadly, our results help explain the extents to which crop domestication and early spread may have mediated the emergence of today's agricultural pests.     

The potential impact of second‐generation biofuel landscapes on at‐risk species in the US

The recent increase in corn ethanol production has drawn attention to the environmental sustainability of biofuel production. Environmental assessments of second‐generation biofuel crops (SGBC) have focused primarily on greenhouse gas emissions and water quality. However, expanding the production of cellulosic biomass resources, especially those that require dedicated agricultural land, is also likely to have impacts on biodiversity. We developed an optimization framework for projecting the spatial pattern of SGBC expansion in the United States and intersected these predictions with occurrence data for at‐risk species. In particular, we focused on two candidate perennial grass feedstocks, Panicum virgatum (switchgrass), and Miscanthus × giganteus (Miscanthus). Tradeoffs between biodiversity and economic profitability are assessed using county level data sets of SGBC yield, agricultural land availability, land rents, and at‐risk species occurrences. Results show that future SGBC expansion is likely to occur outside of the Corn Belt, where conventional biofuel feedstocks are currently grown. The set of at‐risk species that could potentially be impacted is therefore likely to be different from the at‐risk species prevalent in the agroecological landscapes of the Upper Midwest that are dominated by corn and soy production. The total number and type of potentially impacted taxa is influenced by several factors, including the total demand for cellulosic biomass, the type of agricultural land used for production, and the method for defining at‐risk species. SGBC production is also concentrated in fewer counties when a national species conservation constraint is combined with a biofuel production mandate. This analysis provides a foundation for future research on species conservation in bioenergy production landscapes and highlights the importance of incorporating biodiversity into broader environmental assessments of biofuel sustainability.     

Analysis of climate signals in the crop yield record of sub‐Saharan Africa

Food security and agriculture productivity assessments in sub‐Saharan Africa (SSA) require a better understanding of how climate and other drivers influence regional crop yields. In this paper, our objective was to identify the climate signal in the realized yields of maize, sorghum, and groundnut in SSA. We explored the relation between crop yields and scale‐compatible climate data for the 1962–2014 period using Random Forest, a diagnostic machine learning technique. We found that improved agricultural technology and country fixed effects are three times more important than climate variables for explaining changes in crop yields in SSA. We also found that increasing temperatures reduced yields for all three crops in the temperature range observed in SSA, while precipitation increased yields up to a level roughly matching crop evapotranspiration. Crop yields exhibited both linear and nonlinear responses to temperature and precipitation, respectively. For maize, technology steadily increased yields by about 1% (13 kg/ha) per year while increasing temperatures decreased yields by 0.8% (10 kg/ha) per °C. This study demonstrates that although we should expect increases in future crop yields due to improving technology, the potential yields could be progressively reduced due to warmer and drier climates.     

The impact of cropland cover on river nutrient levels in the Mississippi River Basin

Aim This study developed high‐resolution datasets of the area of maize, soybean and wheat cultivation in the United States for 1950, 1970 and 1992. The datasets were used to examine the relationship between individual crop cover and nutrient levels in rivers across the Mississippi River Basin. Location This study was conducted in the United States, with focus on the Mississippi River Basin. Methods County and state‐level estimates of the planted area of maize, soybean and wheat were integrated with a satellite‐derived pattern in total cropland to develop 5′ × 5′ resolution datasets of the fractional area of maize, soybean and wheat in the United States for 1950, 1970 and 1992. Regression analysis was used to determine the relationships between mean levels of nitrogen, phosphorous and silica in 25 rivers across the Mississippi Basin, and the extent of maize, soybean and wheat cultivation in the watersheds. Results The crop datasets provide a spatially explicit representation of the area of the three primary crops in 1950, 1970 and 1992. The datasets clearly depict the rapid expansion of soybean cultivation, the increased specialization of individual agricultural regions, and the accompanying reduction in agricultural biodiversity since 1950. The statistical analysis identified strong correlations between the extent of maize and soybean cover in a watershed and the level of nitrogen (N) and phosphorous (P) at the watershed outlet. In particular, the area of maize appears to be strongly related to the concentration of total‐N and the ratio of dissolved inorganic‐N and organic‐N at the watershed outlet. Conclusions The intensification of cultivation of the three primary crops — maize, soybean and wheat — has altered land cover and water quality across the U.S. since 1950. The high present‐day rate of fertilizer use on maize and the expansion of soybean cultivation could be largely responsible for the change in nutrient ratios in the Mississippi River since 1950.     

UPA2 and ZmRAVL1: Promising targets of genetic improvement of maize plant architecture

正Maize (Zea mays ssp. mays) is a major staple crop, with the highest tonnage among cereal crops worldwide(FAO 2014). Over the past century, maize yields have increased about 8-fold in the US central Corn Belt (from1,287 kg/ha in the 1930s to 11,084 kg/ha in 2017, http://m entary     

Cover crop root contributions to soil carbon in a no‐till corn bioenergy cropping system

Crop residues are potential biofuel feedstocks, but residue removal may reduce soil carbon (C). The inclusion of a cover crop in a corn bioenergy system could provide additional biomass, mitigating the negative effects of residue removal by adding to stable soil C pools. In a no‐till continuous corn bioenergy system in the northern US Corn Belt, we used ¹³CO₂ pulse labeling to trace plant C from a winter rye (Secale cereale) cover crop into different soil C pools for 2 years following rye cover crop termination. Corn stover left as residue (30% of total stover) contributed 66, corn roots 57, rye shoots 61, rye roots 50, and rye rhizodeposits 25 g C m^?2 to soil. Five months following cover crop termination, belowground cover crop inputs were three times more likely to remain in soil C pools than were aboveground inputs, and much of the root‐derived C was in mineral‐associated soil fractions. After 2 years, both above‐ and belowground inputs had declined substantially, indicating that the majority of both root and shoot inputs are eventually mineralized. Our results underscore the importance of cover crop roots vs. shoots and the importance of cover crop rhizodeposition (33% of total belowground cover crop C inputs) as a source of soil C. However, the eventual loss of most cover crop C from these soils indicates that cover crops will likely need to be included every year in rotations to accumulate soil C.     

Alternative biomass strategies for bioenergy: implications for bird communities across the southeastern United States

Concerns over energy demands and climate change have led the United States to set ambitious targets for bioenergy production in the coming decades. The southeastern United States has had a recent increase in biomass woody pellet production and is projected to produce a large portion of the nation's cellulosic biofuels. We conducted a large‐scale, systematic comparison of potential impacts of two types of bioenergy feedstocks – corn (Zea mays) and pine (Pinus spp.) – on bird communities across the southeastern United States. In addition, we evaluated three biomass alternatives for woody biomass from pine plantations: thinning, residue harvest, and short‐rotation energy plantations (SREPs). We conducted transect counts for birds in eight different land uses across the region (85 sites), including corn fields, reference forest, and plantation forests, 2013–2015. We then used hierarchical occupancy models to test the effect of these biomass alternatives on 31 species. Across all species, birds had lower rates of occupancy in corn fields compared to pine stands. Thinning had positive effects on the average occupancy across species, while residue harvest and the potential conversion of conventional plantations to SREPs had negative effects. Cavity nesters and species with bark‐gleaning foraging strategies tended to show the strongest responses. These results highlight the potential negative effects of corn as an energy crop relative to the use of pine biomass. In addition, harvesting biomass via thinning was a bird‐friendly harvest method in comparison with other alternatives. While SREPs may negatively impact some bird species, previously reported yields emphasize that they may provide an order of magnitude greater yield per unit area than other alternatives considered, such that this land‐use practice may be an important alternative to minimize the bioenergy impacts across the landscape.