Terrestrial Ecosystems in a Changing Environment: A Dominant Role for Water

Transpiration—the movement of water from the soil, through plants, and into the atmosphere—is the dominant water flux from the earth\u27s 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

Candidate Perennial Bioenergy Grasses have a Higher Albedo than Annual Row Crops

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 trade-offs, 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 (a), 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 9 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 a than current row crops, but a strong seasonal pattern existed. Both perennials had consistently higher growing season a than row crops and winter a did not differ. The lack of observed differences in winter a, however, masked an interaction between snow cover and species differences, with the perennial species, compared with the row crops, having a higher a when snow was absent and a much lower a when snow was present. Overall, these changes resulted in an average net reduction in annual absorbed energy of about 5 W m -2 for switchgrass and about 8 W m -2 for miscanthus relative to annual crops. Therefore, the conversion from annual row to perennial crops alters the radiative balance of the surface via changes in a and could lead to regional cooling

Chlorophyll can be reduced in crop canopies with little penalty to photosynthesis

The hypothesis that reducing chlorophyll content (Chl) can increase canopy photosynthesis in soybeans was tested using an advanced model of canopy photosynthesis. The relationship between leaf Chl, leaf optical properties, and photosynthetic biochemical capacity were measured in 67 soybean accessions showing large variation in leaf Chl. These relationships were integrated into a biophysical model of canopy-scale photosynthesis to simulate the intercanopy light environment and carbon assimilation capacity of canopies with WT, a Chl-deficient mutant (Y11y11), and 67 other mutants spanning the extremes of Chl to quantify the impact of variation in leaf-level Chl on canopy-scale photosynthetic assimilation and identify possible opportunities for improving canopy photosynthesis through Chl reduction. These simulations demonstrate that canopy photosynthesis should not increase with Chl reduction due to increases in leaf reflectance and non-optimal distribution of canopy nitrogen. However, similar rates of canopy photosynthesis can be maintained with a 9% savings in leaf nitrogen resulting from decreased Chl. Additionally, analysis of these simulations indicate that the inability of Chl reductions to increase photosynthesis arises primarily from the connection between Chl and leaf reflectance and secondarily from the mismatch between the vertical distribution of leaf nitrogen and the light absorption profile. These simulations suggest that future work should explore the possibility of using reduced Chl to improve canopy performance by adapting the distribution of the saved nitrogen within the canopy to take greater advantage of the more deeply penetrating light

Using a Crop Modeling Framework for Precision Cost-Benefit Analysis of Variable Seeding and Nitrogen Application Rates

A key goal of precision agriculture is to achieve the maximum crop yield while minimizing inputs and loses from cropping systems. The challenge for precision agriculture is that these factors interact with one another on a subfield scale. Seeding density and nitrogen (N) fertilizer application rates are two of the most important inputs influencing agronomic, economic and environmental outcomes in cropping systems including yield, return on investment (ROI), and nitrate (NO3−) leaching. Here a cropping system model framework is used to predict site-specific subfield optimum seeding density and (N) fertilizer application rates based on publicly available data sources. The framework is used estimate differences in yield, ROI, NO3− leaching, and N2O emissions corresponding with economic optimum (maximum ROI) and agronomic optimum (maximum yield) inputs. The framework couples the process-based APSIM cropping system model with the SSURGO soils database, Daymet weather data service, land grant university estimates of crop production costs and commodity price estimates, and the R statistics software. Framework performance was evaluated using multiple years of precision yield monitor data obtained from a conventionally managed continuous maize (Zea mays L.) cropping system field located in north central Iowa on which varying N-fertilizer rates were applied. Subfield model estimates of crop yield were sensitive to initial conditions related to historical management of the field and had an r2 = 0.65 and a root mean square error of 1645.0 kg ha−1. A site-specific application of the framework comparing economic optimum seeding density and N-fertilizer rates with agronomic optimum values estimated an average ROI benefit of 7.2% as well as an average NO3− leaching and N2O emissions reductions of 2.5 and 7.6 kg ha−1, respectively. However, in a minority of cases NO3− leaching was greater at the economic optimum, indicating that managing to maximize ROI rather than yield may not always reduce environmental impacts. Our results suggest that managing cropping systems for the economic optimum is plausible using publicly available data with our framework and will likely lead to improved environmental outcomes

A realistic meteorological assessment of perennial biofuel crop deployment: a Southern Great Plains perspective

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-1204774S

SMOS Optical Thickness Changes in Response to the Growth and Development of Crops, Crop Management, and Weather

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

The economic and environmental costs and benefits of the renewable fuel standard

Mandates, like the renewable fuel standard (RFS), for biofuels from corn and cellulosic feedstocks, impact the environment in multiple ways by affecting land use, nitrogen (N)-leakage, and greenhouse gas (GHG) emissions. We analyze the differing trade-offs these different types of biofuels offer among these multi-dimensional environmental effects and convert them to a monetized value of environmental damages (or benefits) that can be compared with the economic costs of extending these mandates over the 2016–2030 period. The discounted values of cumulative net benefits (or costs) are then compared to those with a counterfactual level of biofuels that would have been produced in the absence of the RFS over this period. We find that maintaining the corn ethanol mandate at 56 billion l till 2030 will lead to a discounted cumulative value of an economic cost of $199 billion over the 2016–2030 period compared to the counterfactual scenario; this includes$109 billion of economic costs and $85 billion of net monetized environmental damages. The additional implementation of a cellulosic biofuel mandate for 60 billion l by 2030 will increase this economic cost by$69 billion which will be partly offset by the net discounted monetized value of environmental benefits of $20 billion, resulting in a net cost of$49 billion over the 2016–2030 period. We explore the sensitivity of these net (economic and environmental) costs to alternative values of the social costs of carbon and nitrogen and other technological and market parameters. We find that, unlike corn ethanol, cellulosic biofuels can result in positive net benefits if the monetary benefits of GHG mitigation are valued high and those of N-damages are not very high

Quantitative Assessment of Satellite L-Band Vegetation Optical Depth in the U.S. Corn Belt

Satellite L-band vegetation optical depth (L-VOD) contains new information about terrestrial ecosystems. However, it has not been evaluated against the geophysical variable that it represents, plant water, the mass of liquid water contained within vegetation tissue per ground area. We quantitatively assess the seasonal variation of three L-VOD products at the South Fork Core Validation Site in the Corn Belt state of Iowa where L-VOD is directly proportional to crop plant water. We use three satellite-scale crop plant water estimates: in situ measurements; a normalized difference water index (NDWI) calibrated with in situ measurements; and a crop model. We find that overall the L-VOD satellite products are 0.02-0.09 Np (0.4-1.7 kg · m⁻²) lower than the three estimates. We show that overestimation of L-VOD can be attributed to dynamic soil surface roughness, and hypothesize that crop plant water observations will require the incorporation of this effect into retrieval algorithms

Assessing the Potential to Decrease the Gulf of Mexico Hypoxic Zone with Midwest US Perennial Cellulosic Feedstock Production

The goal of this research was 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 (0–200 kg N ha -1) and fractional replacement (5–25%) 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

Forecasting yields and in-season crop-water nitrogen needs using simulation models

Forecasting crop yields and water-nitrogen dynamics during the growing cycle of the crops can greatly advance in-season decision making processes. To date, forecasting approaches include the use of statistical or mechanistic simulation models, aerial images, or combinations of these to make the predictions. Different approaches and models have different capabilities, strengths, and limitations. System-level mechanistic simulation models (crop and soil models together) usually offer more prediction and explanatory power at the cost of extensive input data. In contrast, statistical approaches or aerial images can be more robust than mechanistic models but their applicability and prediction/explanatory power is limited. The combination of these technologies is viewed as a very promising tool to assist Midwestern agriculture, but in general, all of these technologies are in their initial stages of implementation and more time is needed to prove their potential. Here we present results from a pilot project that aimed to forecast weather, soil water-nitrogen status, crop water-nitrogen demand, and end-of-season crop yields in Iowa using two process-based mechanistic simulation models