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Aging in perennial plants is traditionally observed in terms of changes in end-of-season biomass; however, the driving phenological and physiological changes are poorly understood. We found that 3-year-old (mature) stands of the perennial grass Miscanthus×giganteus had 19–30% lower Anet than 1-year-old M.×giganteus (juvenile) stands; 10–34% lower maximum carboxylation rates of Rubisco and 34% lower light-saturated Anet (Asat). These changes could be related to nitrogen (N) limitations, as mature plants were larger and had 14–34% lower leaf N on an area basis (Na) than juveniles. However, N fertilization restored Na to juvenile levels but compensated only 50% of the observed decline in leaf photosynthesis with age. Comparison of leaf photosynthesis per unit of leaf N (PNUE) showed that mature stands had at least 26% lower PNUE than juvenile stands across all N fertilization rates, suggesting that other factors, besides N, may be limiting photosynthesis in mature stands. We hypothesize that sink limitations in mature stands could be causing feedback inhibition of photosynthesis which is associated with the age-related decline in photosynthesis.

A generally accepted understanding of carbon in agricultural fields is that (1) a significant amount of carbon was lost from soils when land was converted from natural vegetation to agricultural ecosystems, (2) over time a steady-state soil carbon concentration is reached with standard agronomic practices, and (3) that improved management practices or optimal crop species selection can result in increased carbon storage over time. The extent of the carbon lost from conversion from native to agricultural ecosystems is variable, but multiple studies show that carbon losses were large and consistent (supporting point 1). While an assumption of steady state is generally accepted (point 2), there are significant challenges in measuring whether mature agroecosystems are gaining or losing carbon. Multiple strategies are continually proposed to increase soil carbon storage (point 3), yet data is sparce given the plentitude of potential opportunities being considered. Furthermore, direct analysis of soil carbon is prone to substantial heterogeneity, leading to challenge in detecting signals relative to noise in heterogeneous soil environments. Eddy covariance measurements, while unable to measure pools of carbon in the soil directly, can infer changes in ecosystem carbon storage when measurements are integrated over time. Here, long-term eddy covariance datasets were used to measure carbon and water fluxes over agricultural ecosystems in the Central Midwestern United States over multiple years for different crop and management practices. The measurements show that conventionally tilled Midwestern row crops, maize and soybean, integrated on a rotational basis typical for this region represents a large carbon source to the atmosphere, counter to point 2 above. However, similar measurements over the same agroecosystem but with conservation tillage practices indicate long-term carbon storage, even after 20+ years of conservation tillage with significant climate variability. These results suggest that large-scale adoption of no-till practices can significantly reduce the large-scale losses of carbon associated with conventional tillage and, potentially, lead to small but meaningful increases in soil carbon storage, supporting point 3. Similar measurements were also collected over perennial grass ecosystems with potential for bioenergy production, including Miscanthus giganteus, Panicum virgatum, and high species diversity prairie. While these agricultural ecosystems show promise for offsetting fossil carbon emissions, they are also predicted to be better at storing carbon than annual row crops. Multiple years of analysis from these ecosystems show that perennial bioenergy crops are much more likely to lead to ecosystem carbon storage than minimally-tilled annual row crops as early as the first year of transition, but the amount of storage varies based on which species is planted. While this research is focused on one location, the results suggest that the assumptions of steady-state and increases in storage over time may not hold for all agricultural ecosystems and in all locations.

Climate change projections indicate that precipitation events in the central United States are expected to become more intense, more frequent in the spring, and less frequent in the summer. Such a precipitation shift could adversely impact crop yields, especially in subfield areas known as farmed potholes, which are highly susceptible to flooding and ponding, and crop death is more likely to occur, particularly early in the growing season. This suggests that planting alternative crops, such as more flood tolerant perennials, in these areas may be a more profitable option. Using observations of crop growth and yield along with ponding depth of a specific field and farmed pothole in the central United States, we developed a spatially explicit version of the agroecosystem model Agro‐IBIS to estimate water depth and crop yield. After evaluating the model, we conducted a case study for a specific farmed pothole with a range of future precipitation scenarios with Agro‐IBIS to simulate the effects of contemporary (2002–2016) and future precipitation on a conventional corn/soybean (Zea mays L. and Glycine max Merr.) rotation and an alternative perennial miscanthus (Miscanthus × giganteus Greef et Deu.) cropping system. The depth and frequency of ponding increased under most future precipitation scenarios. The corn/soybean rotation had greater total loss (i.e., no yield) on average (>30%) for all scenarios in comparison to miscanthus (

The winter fallow period common in annual cropping systems leaves soils vulnerable to erosion and nutrient loss, especially to nitrogen (N) leaching. This vulnerability can be mitigated with perennial crops that have living roots in the ground year‐round. The mechanisms, magnitude, and consistency with which perennial crops retain N are not clear. We used an experiment to test whether a perennial crop, miscanthus (Miscanthus × giganteus Greef et Deu.), would leach less N than continuous maize (Zea mays L.) and how soil net N mineralization (Nmin) may explain observed leaching under varied environment and management conditions. The experiment included three crossed factors: (1) cropping system (maize, juvenile miscanthus = 1–2 years old, mature miscanthus = 3–4 years old); (2) N fertilization (0 and 224 kg N ha−1); and (3) environment (four site‐years at two locations in Iowa, USA, that differed in climate and soil fertility). We measured N cycling dynamics, including: inorganic soil N (ammonium + nitrate), in situ Nmin, N leaching, crop N uptake, and calculated system N use efficiency. There were many complex interactions among factors. On average, cumulative Nmin under juvenile miscanthus was 111% greater than maize, but as miscanthus matured, there was no difference in Nmin between the perennial crop and maize. There was no difference in N leaching between juvenile miscanthus and maize, but mature miscanthus decreased N leaching by 42% and 88% compared to maize (with and without N fertilization, respectively). Across all treatments, there was no relationship between Nmin and N leaching, suggesting other mechanisms are regulating N leaching. Overall, mature miscanthus shows promise as a tool to reduce N losses in areas dominated by annual row‐crops.

Agricultural landscapes are the largest source of anthropogenic nitrous oxide (N(2)O) emissions, but their specific sources and magnitudes remain contested. In the US Corn Belt, a globally important N(2)O source, in-field soil emissions were reportedly too small to account for N(2)O measured in the regional atmosphere, and disproportionately high N(2)O emissions from intermittent streams have been invoked to explain the discrepancy. We collected 3 y of high-frequency (4-h) measurements across a topographic gradient, including a very poorly drained (intermittently flooded) depression and adjacent upland soils. Mean annual N(2)O emissions from this corn–soybean rotation (7.8 kg of N(2)O–N ha(−1)⋅y(−1)) were similar to a previous regional top-down estimate, regardless of landscape position. Synthesizing other Corn Belt studies, we found mean emissions of 5.6 kg of N(2)O–N ha(−1)⋅y(−1) from soils with similar drainage to our transect (moderately well-drained to very poorly drained), which collectively comprise 60% of corn–soybean-cultivated soils. In contrast, strictly well-drained soils averaged only 2.3 kg of N(2)O–N ha(−1)⋅y(−1). Our results imply that in-field N(2)O emissions from soils with moderately to severely impaired drainage are similar to regional mean values and that N(2)O emissions from well-drained soils are not representative of the broader Corn Belt. On the basis of carbon dioxide equivalents, the warming effect of direct N(2)O emissions from our transect was twofold greater than optimistic soil carbon gains achievable from agricultural practice changes. Despite the recent focus on soil carbon sequestration, addressing N(2)O emissions from wet Corn Belt soils may have greater leverage in achieving climate sustainability.

Much field research on perennial bioenergy crops confounds effects of plant age with those of the growing season, which increases uncertainty and the potential for erroneous conclusions, particularly in maturing stands. Most studies rely on stands planted in a single year and measured across multiple subsequent seasons. These “single-start” designs lack statistical power to separate temporal from environment effects. We used a staggered start experimental design to learn if increased statistical power clarified understanding of Miscanthus × giganteus nitrogen (N) needs. We conducted a staggered start experiment with three planting years and five N rates during the M. × giganteus yield-building phase at three sites across IA, USA. Third-year yields were 21.0, 25.0, and 27.1 Mg dry matter (DM) ha−1 at the northwest (NW), central, and southeast (SE) sites, respectively. Nitrogen fertilization effects changed with establishment conditions, but not with plant age. At the most N responsive site, N fertilizer changed yields at all stand ages, but not in every year. Yield increases of 150%, 36%, and 40% were observed in 1-, 2-, and 3-year-old stands, respectively, with N addition. Nitrogen effects on 1-year-old stands were positive in SE IA (2.7 kg DM kg−1 N added), negative (− 2.3 kg DM kg−1 N) in NW IA, and variable in central IA (− 2.2–9.6 kg DM kg−1 N), suggesting a site–year-specific response. Yield increases between the first and second years varied by > 100% depending on establishment conditions, highlighting the need for repeated planting before determining economic and agronomic crop viability.

Satellite L-band vegetation optical depth (L- VOD) is a relatively new but potentially valuable vegetation product. We hypothesize that the relationship between L- VOD and crop plant water, as characterized by the “b-parameter,” should change over the growing season as crops progress through different developmental stages. We find that the b-parameter derived from SMOS and SMAP L- VOD and satellite-scale estimates of crop plant water made by the Agro-IBIS model does in fact exhibit a growing-season pattern. This pattern is consistent among different years during the first half of the growing season.

Demand for biofuel production driven by the Renewable Fuel Standard (RFS2) has coincided with increased land in corn production and increasing nitrogen (N) loss to the Gulf of Mexico. Diversifying cropland with perennial energy crops (miscanthus and switchgrass) may reduce N loss and improve water quality. However, the extent of these benefits depends on the mix of biomass feedstocks (corn stover, perennials) incentivized by the RFS2 and the extent to which energy crops displace N-intensive row crops. We developed an integrated economic-biophysical model to quantify the water quality impacts of three potential policy scenarios that provided corn ethanol at levels before the RFS2 (RFS1 baseline); 15 billion gallons of corn ethanol (corn ethanol only); or 16 billion gallons of cellulosic ethanol in addition to corn ethanol (corn + cellulosic ethanol). Our results showed that economically optimal locations for perennial energy crop production were distributed across idle cropland with lower intrinsic N loss than active cropland. We found stover removal incentivized by the RFS2 offset N loss benefits of perennial energy crops. This finding suggests that targeted incentives for N loss reduction are needed to supplement the RFS2 to induce displacement of N-intensive row crops with energy crops to reduce N losses.

Accurately forecasting crop yield in advance of harvest could greatly benefit decision makers when making management decisions. However, few evaluations have been conducted to determine the impact of including weather forecasts, as opposed to using historical weather data (commonly used) in crop models. We tested a combination of short-term weather forecasts from the Weather Research and Forecasting Model (WRF) to predict in season weather variables, such as, maximum and minimum temperature, precipitation, and radiation at four different forecast lengths (14 days, 7 days, 3 days, and 0 days). This forecasted weather data along with the current and historic (previous 35 years) data were combined to drive Agricultural Production Systems sIMulator (APSIM) in-season corn [Zea mays L] and soybean [Glycine max] grain yield and phenology forecasts for 16 field trials in Iowa, USA. The overall goal was to determine how the inclusion of weather forecasting impacts in-season crop model predictions. We had two objectives 1) determine the impact of weather forecast length on WRF accuracy, and 2) quantify the impact of weather forecasts accuracy on APSIM prediction accuracy. We found that the most accurate weather forecast length varied greatly among the 16 treatments (2 years × 2 sites × 2 crops × 2 management practices), but that the 0 day and 3 day forecasts were, on average, the most accurate when compared to the other forecast lengths. Overall, the accuracy of the in-season crop yield forecast was inversely proportional to forecast length (p = 0.026), but there was variation among treatments. The accuracy of the in-season flowering and maturity forecasts were not significantly affected by inclusion of weather forecast length (p = 0.065). The 14 day forecast provided enough lead time to improve flowering prediction in 8 out of the 16 treatments. The fact that maximum temperature was the most accurate predicted variable by WRF was the reason for improvements in flowering predictions. Our results suggest that a weather forecast from WRF was not better than historical weather for yield prediction.

Biomass sorghum (Sorghum bicolor L. Moench) is a candidate bioenergy feedstock for the U.S. Midwest. Research suggests that biomass sorghum is more drought tolerant and has higher water-use-efficiency (WUE) than maize (Zea mays L.) in water-limiting environments, but most species comparisons of the seasonal evapotranspiration (total ET) and WUE have focused on irrigated systems (WUE defined as the ratio of cumulative dry biomass production (dry matter; DM) to total evapotranspiration (mm); g DM (mm H2O)−1). Since comparative data for the rain-fed Midwest are scarce, we conducted a side-by-side evaluation of the total ET and WUE of maize and biomass sorghum in central Iowa—a site within the U.S. Corn Belt. Total ET was estimated using a micrometeorological method, and aboveground plant biomass was determined using destructive hand harvests. Similar mean WUE was determined for maize (3.51 ± 0.26 g DM (mm H2O)−1) and biomass sorghum (3.47 ± 0.22 g DM (mm H2O)−1) over two non-drought growing seasons with total ET of 567 ± 26 mm and 600 ± 20 mm, respectively. Even though total ET and WUE were not statistically different between species (P > 0.1), maize had significantly greater theoretical ethanol yield (EY; L ethanol m−2) and lower ethanol water requirement (EWR; L water L ethanol−1), relative to biomass sorghum (P

Progress on reducing nutrient loss from annual croplands has been hampered by perceived conflicts between short-term profitability and long-term stewardship, but these may be overcome through strategic integration of perennial crops. Perennial biomass crops like switchgrass can mitigate nitrate-nitrogen (NO3-N) leaching, address bioenergy feedstock targets, and – as a lower-cost management alternative to annual crops (i.e., corn, soybeans) – may also improve farm profitability. We analyzed publicly available environmental, agronomic, and economic data with two integrated models: a subfield agroecosystem management model, Landscape Environmental Assessment Framework (LEAF), and a process-based biogeochemical model, DeNitrification-DeComposition (DNDC). We constructed a factorial combination of profitability and NO3-N leaching thresholds and simulated targeted switchgrass integration into corn/soybean cropland in the agricultural state of Iowa, USA. For each combination, we modeled (i) area converted to switchgrass, (ii) switchgrass biomass production, and (iii) NO3-N leaching reduction. We spatially analyzed two scenarios: converting to switchgrass corn/soybean cropland losing >US$ 100 ha−1 and leaching >50 kg ha−1 (‘conservative’ scenario) or losing >US$ 0 ha−1 and leaching >20 kg ha−1 (‘nutrient reduction’ scenario). Compared to baseline, the ‘conservative’ scenario resulted in 12% of cropland converted to switchgrass, which produced 11 million Mg of biomass and reduced leached NO3-N 18% statewide. The ‘nutrient reduction’ scenario converted 37% of cropland to switchgrass, producing 34 million Mg biomass and reducing leached NO3-N 38% statewide. The opportunity to meet joint goals was greatest within watersheds with undulating topography and lower corn/soybean productivity. Our approach bridges the scales at which NO3-N loss and profitability are usually considered, and is informed by both mechanistic and empirical understanding. Though approximated, our analysis supports development of farm-level tools that can identify locations where both farm profitability and water quality improvement can be achieved through the strategic integration of perennial vegetation.

Large-scale cultivation of perennial bioenergy crops (e.g., miscanthus and switchgrass) offers unique opportunities to mitigate climate change through avoided fossil fuel use and associated greenhouse gas reduction. Although conversion of existing agriculturally intensive lands (e.g., maize and soy) to perennial bioenergy cropping systems has been shown to reduce near-surface temperatures, unintended consequences on natural water resources via depletion of soil moisture may offset these benefits. The hydroclimatic impacts associated with perennial bioenergy crop expansion over the contiguous United States are quantified using the Weather Research and Forecasting Model dynamically coupled to a land surface model (LSM). A suite of continuous (2000–09) medium-range resolution (20-km grid spacing) ensemble-based simulations is conducted using seasonally evolving biophysical representation of perennial bioenergy cropping systems within the LSM based on observational data. Deployment is carried out only over suitable abandoned and degraded farmlands to avoid competition with existing food cropping systems. Results show that near-surface cooling (locally, up to 5°C) is greatest during the growing season over portions of the central United States. For some regions, principal impacts are restricted to a reduction in near-surface temperature (e.g., eastern portions of the United States), whereas for other regions deployment leads to soil moisture reduction in excess of 0.15–0.2 m3 m−3 during the simulated 10-yr period (e.g., western Great Plains). This reduction (~25%–30% of available soil moisture) manifests as a progressively decreasing trend over time. The large-scale focus of this research demonstrates the long-term hydroclimatic sustainability of large-scale deployment of perennial bioenergy crops across the continental United States, revealing potential hot spots of suitable deployment and regions to avoid.

NASA’s Soil Moisture Active Passive (SMAP) is a satellite L–band radiometer whose primary mission is to measure soil moisture. However, it also retrieves vegetation optical depth (VOD), the degree to which vegetation attenuates microwave radiation. We believe that VOD has the potential to monitor crop growth in the US Corn Belt. To show its value, we compare SMAP VOD to satellite–scale estimates of crop productivity created using the Agricultural Integrated BIosphere Simulator (Agro– IBIS) and observed weather at the South Fork SMAP Core Validation Site in the Corn Belt state of Iowa. We find that SMAP VOD is directly proportional to crop water, the mass of liquid water in crop tissue. We discovered this relationship by using new empirical models that relate crop water to crop dry mass, the standard output for Agro–IBIS as well as all other crop models, created with in situ data spanning multiple years and stages of crop development. The value of the proportionality constant (or "b–parameter") relating VOD to crop water at the satellite scale is half as large as the SMAP value. Because L–band VOD is directly proportional to crop water at the satellite scale, SMAP has the potential to evaluate the large–scale performance of crop models in the Corn Belt on a near daily basis.

The goal of this research is to determine the changes in streamflow, dissolved inorganic nitrogen (DIN) leaching and export to the Gulf of Mexico associated with a range of large-scale dedicated perennial cellulosic bioenergy production scenarios within in the Mississippi-Atchafalaya River Basin (MARB). To achieve this goal, we used Agro-IBIS, a vegetation model capable of simulating the biogeochemistry of row crops, miscanthus and switchgrass, coupled with THMB, a hydrology model capable of simulating streamflow and DIN export. Simulations were conducted at varying fertilizer application rates (0 to 200 kg N ha−1) and fractional replacement (5 to 25%) of current row crops with miscanthus or switchgrass across the MARB. The analysis also includes two scenarios where miscanthus and switchgrass (MRX and MRS respectively) each replace the ca. 40% of maize production currently devoted to ethanol. Across the scenarios, there were minor reductions in runoff and streamflow throughout the MARB, with the largest differences (ca. 6%) occurring for miscanthus at the highest fractional replacement scenarios in drier portions of the region. However, differences in total MARB discharge at the basin outlet were less than 1.5% even in the MRX scenario. Reductions in DIN export were much larger on a percentage basis than reductions in runoff, with the highest replacement scenarios decreasing long-term mean DIN export by ca. 15 and 20% for switchgrass and miscanthus, respectively. Fertilization scenarios show that significant reductions in DIN leaching are possible even with application rates of 100 and 150 kg N ha−1 for switchgrass and miscanthus respectively. These results indicate that, given targeted management strategies, there is potential for miscanthus and switchgrass to provide key ecosystem services by reducing the export of DIN, while avoiding hydrologic impacts of reduced streamflow. This article is protected by copyright. All rights reserved.

The Soil Moisture and Ocean Salinity (SMOS) remote sensing satellite was launched by the European Space Agency in 2009. The L-band brightness temperature observed by SMOS has been used to produce estimates of both soil moisture and τ, the optical thickness of the land surface. Although τ should theoretically be proportional to the amount of vegetation present within a SMOS pixel, several initial investigations have not been able to confirm this expected behavior. However, when the noise in the SMOS τ product is removed, τ in the U.S. Corn Belt, a region of extensive row-crop agriculture, has a distinct shape that mirrors the growth and development of crops. We find that the peak value of SMOS τ occurs at approximately 1000 °C day (base 10 °C) growing degree days after the mean planting date of maize (corn). We can explain this finding in the following way: τ is directly proportional to the water column density of vegetation; maize contributes the most to growing season changes in τ in the Corn Belt; and maize reaches its maximum water column density at its third reproductive stage of development, at about 1000 °C day growing degree days. Consequently, SMOS τ could be used to monitor the phenology of crops in the Corn Belt at a spatial resolution similar to a U.S. county and a temporal frequency on the order of days. We also examined the magnitude of the change in SMOS τ over the growing season and hypothesized it would be related to the amount of accumulated solar radiation, but found this not to be the case. On the other hand, the change in magnitude was smallest for the year in which the most precipitation fell. These findings are rational since SMOS τ at the satellite scale is in fact a function of both vegetation and soil surface roughness, and soil surface roughness is reduced by precipitation. To fully explain changes in SMOS τ in the Corn Belt it appears that it will be necessary to use in situ and remotely-sensed observations along with agro-ecosystem models to account for land management decisions made by farmers that affect changes in soil surface roughness and all of the relevant biophysical processes that affect the growth and development of crops.

Historically crop models have been used to evaluate crop yield responses to nitrogen (N) rates after harvest when it is too late for the farmers to make in-season adjustments. We hypothesize that the use of a crop model as an in-season forecast tool will improve current N decision-making. To explore this, we used the Agricultural Production Systems sIMulator (APSIM) calibrated with long-term experimental data for central Iowa, USA (16-years in continuous corn and 15-years in soybean-corn rotation) combined with actual weather data up to a specific crop stage and historical weather data thereafter. The objectives were to: (1) evaluate the accuracy and uncertainty of corn yield and economic optimum N rate (EONR) predictions at four forecast times (planting time, 6th and 12th leaf, and silking phenological stages); (2) determine whether the use of analogous historical weather years based on precipitation and temperature patterns as opposed to using a 35-year dataset could improve the accuracy of the forecast; and (3) quantify the value added by the crop model in predicting annual EONR and yields using the site-mean EONR and the yield at the EONR to benchmark predicted values. Results indicated that the mean corn yield predictions at planting time (R2 = 0.77) using 35-years of historical weather was close to the observed and predicted yield at maturity (R2 = 0.81). Across all forecasting times, the EONR predictions were more accurate in corn-corn than soybean-corn rotation (relative root mean square error, RRMSE, of 25 vs. 45%, respectively). At planting time, the APSIM model predicted the direction of optimum N rates (above, below or at average site-mean EONR) in 62% of the cases examined (n = 31) with an average error range of ±38 kg N ha−1 (22% of the average N rate). Across all forecast times, prediction error of EONR was about three times higher than yield predictions. The use of the 35-year weather record was better than using selected historical weather years to forecast (RRMSE was on average 3% lower). Overall, the proposed approach of using the crop model as a forecasting tool could improve year-to-year predictability of corn yields and optimum N rates. Further improvements in modeling and set-up protocols are needed toward more accurate forecast, especially for extreme weather years with the most significant economic and environmental cost.

The production of perennial cellulosic feedstocks for bioenergy presents the potential to diversify regional economies and the national energy supply, while also serving as climate ‘regulators’ due to a number of biogeochemical and biogeophysical differences relative to row crops. Numerous observational and model based approaches have investigated biogeochemical tradeoffs, such as increased carbon sequestration and increased water use, associated with growing cellulosic feedstocks. A less understood aspect is the biogeophysical changes associated with the difference in albedo (α), which could alter the local energy balance and cause local to regional cooling several times larger than that associated with offsetting carbon. Here, we established paired fields of Miscanthus × giganteus (miscanthus) and Panicum virgatum (switchgrass), two of the leading perennial cellulosic feedstock candidates, and traditional annual row crops in the highly productive “Corn-belt”. Our results show that miscanthus did and switchgrass did not have an overall higher α than current row crops but a strong seasonal pattern existed. Both perennials had consistently higher growing season α than row crops and winter α did not differ. The lack of observed differences in winter α, however, masked an interaction between snow cover and species differences, with the perennial species, compared with the row crops, having a higher α when snow was absent and a much lower α when snow was present. Overall, these changes resulted in an average net reduction in annual absorbed energy of about 5 W/m

Reducing chlorophyll (chl) content may improve the conversion efficiency of absorbed photosynthetically active radiation into biomass and therefore yield in dense monoculture crops by improving light penetration and distribution within the canopy. The effects of reduced chl on leaf and canopy photosynthesis and photosynthetic efficiency were studied in two reportedly robust reduced-chl soybean mutants, Y11y11 and y9y9, in comparison to the wild-type (WT) “Clark” cultivar. Both mutants were characterized during the 2012 growing season whereas only the Y11y11 mutant was characterized during the 2013 growing season. Chl deficiency led to greater rates of leaf-level photosynthesis per absorbed photon early in the growing season when mutant chl content was ~35% of the WT, but there was no effect on photosynthesis later in the season when mutant leaf chl approached 50% of the WT. Transient benefits of reduced chl at the leaf level did not translate to improvements in canopy-level processes. Reduced pigmentation in these mutants was linked to lower water use efficiency, which may have dampened any photosynthetic benefits of reduced chl, especially since both growing seasons experienced significant drought conditions. These results, while not confirming our hypothesis or an earlier published study in which the Y11y11 mutant significantly out yielded the WT, do demonstrate that soybean significantly overinvests in chl. Despite a >50% chl reduction, there was little negative impact on biomass accumulation or yield, and the small negative effects present were likely due to pleiotropic effects of the mutation. This outcome points to an opportunity to reinvest nitrogen and energy resources that would otherwise be used in pigment-proteins into increasing biochemical photosynthetic capacity, thereby improving canopy photosynthesis and biomass production.

Land use change for bioenergy feedstocks is likely to intensify as energy demand rises simultaneously with increased pressure to minimize greenhouse gas emissions. Initial assessments of the impact of adopting bioenergy crops as a significant energy source have largely focused on the potential for bioenergy agroecosystems to provide global-scale climate regulating ecosystem services via biogeochemical processes. Such as those processes associated with carbon uptake, conversion, and storage that have the potential to reduce global greenhouse gas emissions (GHG). However, the expansion of bioenergy crops can also lead to direct biophysical impacts on climate through water regulating services. Perturbations of processes influencing terrestrial energy fluxes can result in impacts on climate and water across a spectrum of spatial and temporal scales. Here, we review the current state of knowledge about biophysical feedbacks between vegetation, water, and climate that would be affected by bioenergy-related land use change. The physical mechanisms involved in biophysical feedbacks are detailed, and interactions at leaf, field, regional, and global spatial scales are described. Locally, impacts on climate of biophysical changes associated with land use change for bioenergy crops can meet or exceed the biogeochemical changes in climate associated with rising GHG's, but these impacts have received far less attention. Realization of the importance of ecosystems in providing services that extend beyond biogeochemical GHG regulation and harvestable yields has led to significant debate regarding the viability of various feedstocks in many locations. The lack of data, and in some cases gaps in knowledge associated with biophysical and biochemical influences on land–atmosphere interactions, can lead to premature policy decisions.

NASA's Soil Moisture Active Passive (SMAP) and ESA's Soil Moisture Ocean Salinity (SMOS) carry satellite L-band radiometers whose primary missions are to measure soil moisture. However, they also allow retrieving of vegetation optical depth (VOD), the degree to which vegetation attenuates microwave radiation. Because attenuation is primarily a function of the total amount of liquid water in a vegetation canopy that is contained within vegetation tissue, VOD could be used to monitor seasonal changes in this quantity, which we call crop water, in major agricultural regions such as the US Corn Belt. There are two main advantages of L-band VOD: it observes the entire canopy volume because soil moisture sensitivity is maintained throughout the growing season; and since it is unaffected by cloud cover there are close to daily measurements. To show its value, we compare SMAP and SMOS VOD to satellite-scale estimates of crop productivity created using the Agricultural Integrated BIosphere Simulator (Agro-IBIS) and observed weather at the South Fork SMAP Core Validation Site in the Corn Belt state of Iowa. We find that SMAP and SMOS VOD are directly proportional to crop water. New empirical models that relate crop water to crop dry mass were required to make this finding. We created these models with in situ data spanning multiple years and stages of crop development. The value of the proportionality constant (or “b-parameter”) relating VOD to crop water at the satellite scale is about half as large as previous estimates. Because L-band VOD is directly proportional to crop water at the satellite scale, and because we understand the relationship between crop water and crop dry mass, SMAP and SMOS have the potential to evaluate the large-scale performance of crop models in the Corn Belt on a near daily basis.

Maize, in rotation with soybean, forms the largest continuous ecosystem in temperate North America, therefore changes to the biosphere-atmosphere exchange of water vapor and energy of these crops are likely to have an impact on the Midwestern US climate and hydrological cycle. As a C4 crop, maize photosynthesis is already CO2 -saturated at current CO2 concentrations ([CO2 ]) and the primary response of maize to elevated [CO2 ] is decreased stomatal conductance (gs ). If maize photosynthesis is not stimulated in elevated [CO2 ], then reduced gs is not offset by greater canopy leaf area, which could potentially result in a greater ET reduction relative to that previously reported in soybean, a C3 species. The objective of this study is to quantify the impact of elevated [CO2 ] on canopy energy and water fluxes of maize (Zea mays). Maize was grown under ambient and elevated [CO2 ] (550 μmol mol(-1) during 2004 and 2006 and 585 μmol mol(-1) during 2010) using Free Air Concentration Enrichment (FACE) technology at the SoyFACE facility in Urbana, Illinois. Maize ET was determined using a residual energy balance approach based on measurements of sensible (H) and soil heat fluxes, and net radiation. Relative to control, elevated [CO2 ] decreased maize ET (7-11%; P 0.01) along with lesser soil moisture depletion, while H increased (25-30 W m(-2) ; P 0.01) along with higher canopy temperature (0.5-0.6 °C). This reduction in maize ET in elevated [CO2 ] is approximately half that previously reported for soybean. A partitioning analysis showed that transpiration contributed less to total ET for maize compared to soybean, indicating a smaller role of stomata in dictating the ET response to elevated [CO2 ]. Nonetheless, both maize and soybean had significantly decreased ET and increased H, highlighting the critical role of elevated [CO2 ] in altering future hydrology and climate of the region that is extensively cropped with these species.

Highlight Expression of cyanobacterial FBP/SBPase in soybean prevents yield depression in a free air CO2 enrichment experiment under simulated future climate conditions with combination of elevated CO2 and elevated temperature., Predictions suggest that current crop production needs to double by 2050 to meet global food and energy demands. Based on theory and experimental studies, overexpression of the photosynthetic enzyme sedoheptulose-1,7-bisphosphatase (SBPase) is expected to enhance C3 crop photosynthesis and yields. Here we test how expression of the cyanobacterial, bifunctional fructose-1,6/sedoheptulose-1,7-bisphosphatase (FBP/SBPase) affects carbon assimilation and seed yield (SY) in a major crop (soybean, Glycine max). For three growing seasons, wild-type (WT) and FBP/SBPase-expressing (FS) plants were grown in the field under ambient (400 μmol mol−1) and elevated (600 μmol mol−1) CO2 concentrations [CO2] and under ambient and elevated temperatures (+2.7 °C during daytime, +3.4 °C at night) at the SoyFACE research site. Across treatments, FS plants had significantly higher carbon assimilation (4–14%), Vc,max (5–8%), and Jmax (4–8%). Under ambient [CO2], elevated temperature led to significant reductions of SY of both genotypes by 19–31%. However, under elevated [CO2] and elevated temperature, FS plants maintained SY levels, while the WT showed significant reductions between 11% and 22% compared with plants under elevated [CO2] alone. These results show that the manipulation of the photosynthetic carbon reduction cycle can mitigate the effects of future high CO2 and high temperature environments on soybean yield.

Utility of perennial bioenergy crops (e.g., switchgrass and miscanthus) offers unique opportunities to transition toward a more sustainable energy pathway due to their reduced carbon footprint, averted competition with food crops, and ability to grow on abandoned and degraded farmlands. Studies that have examined biogeophysical impacts of these crops noted a positive feedback between near-surface cooling and enhanced evapotranspiration (ET), but also potential unintended consequences of soil moisture and groundwater depletion. To better understand hydrometeorological effects of perennial bioenergy crop expansion, this study conducted high-resolution (2-km grid spacing) simulations with a state-of-the-art atmospheric model (Weather Research and Forecasting system) dynamically coupled to a land surface model. We applied the modeling system over the Southern Plains of the United States during a normal precipitation year (2007) and a drought year (2011). By focusing the deployment of bioenergy cropping systems on marginal and abandoned farmland areas (to reduce the potential conflict with food systems), the research presented here is the first realistic examination of hydrometeorological impacts associated with perennial bioenergy crop expansion. Our results illustrate that the deployment of perennial bioenergy crops leads to widespread cooling (1–2 °C) that is largely driven by an enhanced reflection of shortwave radiation and, secondarily, due to an enhanced ET. Bioenergy crop deployment was shown to reduce the impacts of drought through simultaneous moistening and cooling of the near-surface environment. However, simulated impacts on near-surface cooling and ET were reduced during the drought relative to a normal precipitation year, revealing differential effects based on background environmental conditions. This study serves as a key step toward the assessment of hydroclimatic sustainability associated with perennial bioenergy crop expansion under diverse hydrometeorological conditions by highlighting the driving mechanisms and processes associated with this energy pathway. This work was funded by NSF Grant EAR-1204774 SI

a b s t r a c t The production of cellulosic feedstocks for renewable fuels will increase over the coming decades. How- ever, it is uncertain which feedstocks will be best suited for bioenergy production. A key factor dictating feedstock selection for a given region is water use efficiency (WUE), the trade-off between evapotranspira- tion (ET) and carbon uptake or productivity. Using an ecosystem model, two of the top candidate cellulosic feedstocks, Miscanthus × giganteus (miscanthus) and Panicum virgatum (switchgrass) were compared to Zea mays L. (maize), the existing dominant bioenergy feedstock, with 0 and 25% residue removal for the Midwest US. We determined productivity in three ways: harvested yield (HY), net ecosystem productiv- ity (NEP) and net biome productivity (NBP). Evapotranspiration was compared against each of the three productivity metrics, respectively, to yield Harvest Water Use Efficiency (HWUE), Ecosystem Water Use Efficiency (EWUE) and Biome Water Use Efficiency (BWUE). Simulations indicated that, over the study domain, miscanthus had a significantly higher HWUE compared to switchgrass and maize, while maize and switchgrass were similar. When EWUE was compared miscanthus was higher than both maize and switchgrass, which were similar for most of the region. Biome WUE was similar for both of the perenni- als and higher compared to maize for most of the study domain with the exception of the driest regions where maize showed the highest BWUE. Removing 25% of maize residue slightly increased HWUE and greatly decreased BWUE throughout the domain, however only HWUE changes were statistically signif- icant. These results indicate that the feedstock with the highest WUE varied based on the productivity metric, but BWUE for maize was consistently lower than the perennials. Published by Elsevier B.V.

Photorespiration is essential for C3 plants but operates at the massive expense of fixed carbon dioxide and energy. Photorespiration is initiated when the initial enzyme of photosynthesis, ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco), reacts with oxygen instead of carbon dioxide and produces a toxic compound that is then recycled by photorespiration. Photorespiration can be modeled at the canopy and regional scales to determine its cost under current and future atmospheres. A regional-scale model reveals that photorespiration currently decreases US soybean and wheat yields by 36% and 20%, respectively, and a 5% decrease in the losses due to photorespiration would be worth approximately $500 million annually in the United States. Furthermore, photorespiration will continue to impact yield under future climates despite increases in carbon dioxide, with models suggesting a 12–55% improvement in gross photosynthesis in the absence of photorespiration, even under climate change scenarios predicting the largest increases in atmospheric carbon dioxide concentration. Although photorespiration is tied to other important metabolic functions, the benefit of improving its efficiency appears to outweigh any potential secondary disadvantages.

Transpiration—the movement of water from the soil, through plants, and into the atmosphere—is the dominant water flux from the earth's terrestrial surface. The evolution of vascular plants, while increasing terrestrial primary productivity, led to higher transpiration rates and widespread alterations in the global climate system. Similarly, anthropogenic influences on transpiration rates are already influencing terrestrial hydrologic cycles, with an even greater potential for changes lying ahead. Intricate linkages among anthropogenic activities, terrestrial productivity, the hydrologic cycle, and global demand for ecosystem services will lead to increased pressures on ecosystem water demands. Here, we focus on identifying the key drivers of ecosystem water use as they relate to plant physiological function, the role of predicted global changes in ecosystem water uses, trade-offs between ecosystem water use and carbon uptake, and knowledge gaps.

Miscanthus is an intriguing cellulosic bioenergy feedstock because its aboveground productivity is high for low amounts of agrochemical inputs, but soil temperatures below -3.5 °C could threaten successful cultivation in temperate regions. We used a combination of observed soil temperatures and the Agro-IBIS model to investigate how strategic residue management could reduce the risk of rhizome threatening soil temperatures. This objective was addressed using a historical (1978-2007) reconstruction of extreme minimum 10 cm soil temperatures experienced across the Midwest US and model sensitivity studies that quantified the impact of crop residue on soil temperatures. At observation sites and for simulations that had bare soil, two critical soil temperature thresholds (50% rhizome winterkill at -3.5 °C and -6.0 °C for different Miscanthus genotypes) were reached at rhizome planting depth (10 cm) over large geographic areas. The coldest average annual extreme 10 cm soil temperatures were between -8 °C to -11 °C across North Dakota, South Dakota, and Minnesota. Large portions of the region experienced 10 cm soil temperatures below -3.5 °C in 75% or greater for all years, and portions of North and South Dakota, Minnesota, and Wisconsin experienced soil temperatures below -6.0 °C in 50-60% of all years. For simulated management options that established varied thicknesses (1-5 cm) of miscanthus straw following harvest, extreme minimum soil temperatures increased by 2.5 °C to 6 °C compared to bare soil, with the greatest warming associated with thicker residue layers. While the likelihood of 10 cm soil temperatures reaching -3.5 °C was greatly reduced with 2-5 cm of surface residue, portions of the Dakotas, Nebraska, Minnesota, and Wisconsin still experienced temperatures colder than -3.5 °C in 50-80% of all years. Nonetheless, strategic residue management could help increase the likelihood of overwintering of miscanthus rhizomes in the first few years after establishment, although low productivity and biomass availability during these early stages could hamper such efforts.

Globally, photosynthesis accounts for the largest flux of CO₂ from the atmosphere into ecosystems and is the driving process for terrestrial ecosystem function. The importance of accurate predictions of photosynthesis over a range of plant growth conditions led to the development of a C₃ photosynthesis model by Farquhar, von CaemmererBerry that has become increasingly important as society places greater pressures on vegetation. The photosynthesis model has played a major role in defining the path towards scientific understanding of photosynthetic carbon uptake and the role of photosynthesis on regulating the earth's climate and biogeochemical systems. In this review, we summarize the photosynthesis model, including its continued development and applications. We also review the implications these developments have on quantifying photosynthesis at a wide range of spatial and temporal scales, and discuss the model's role in determining photosynthetic responses to changes in environmental conditions. Finally, the review includes a discussion of the larger-scale modelling and remote-sensing applications that rely on the leaf photosynthesis model and are likely to open new scientific avenues to address the increasing challenges to plant productivity over the next century.