Cynthia J. Hays

Potential production and environmental effects of switchgrass and traditional crops under current and greenhouse-altered climate in the central United States : a simulation study

If, as many climate change analysts speculate, industrial and other emissions of CO2 can be offset by substitution of biofuels, large areas of land, including agricultural land, may be converted to the production of biomass feedstocks. This paper explores the feasibility for the Missouri‐Iowa‐Nebraska‐Kansas (MINK) region of the US of converting some agricultural land to the production of switchgrass (Panicum virgatum L.), a perennial warm season grass, as a biomass energy crop. The erosion productivity impact calculator (EPIC) crop growth model simulated production of corn (Zea mays L.), sorghum (Sorghum bicolor(L.) Moench), soybean (Glycine maxL.), winter wheat (Triticum aestivumL.) and switchgrass at 302 sites within the MINK region. The analysis is done for both current climatic conditions and a regional climate model-based scenario of possible climate change. Daily climate records from 1983 to 1993 served as baseline and the NCAR-RegCM2 model (RegCM hereafter) nested within the CSIRO general circulation model (GCM) provided the climate change scenario. Crop production was simulated at two atmospheric CO2 concentrations ([CO2]) at 365 and 560 ppm to consider the CO2-fertilization effect. Simulated yields of the perennial switchgrass increased at all sites with a mean yield increase of 5.0 Mg ha 1 under the RegCM climate change scenario. Switchgrass yields benefited from temperature increases of 3.0‐8.0 C, which extended the growing season and reduced the incidence of cold stress. Conversely, the higher temperatures under the RegCM scenario decreased yields of corn, soybean, sorghum and winter wheat due to increased heat stress and a speeding of crop maturity. With no CO2-fertilization effect, EPIC simulated maximum decreases from baseline of 1.5 Mg ha 1 for corn, 1.0 Mg ha 1 for sorghum, 0.8 Mg ha 1 for soybean and 0.5 Mg ha 1 for winter wheat. Simulated yields increased for all crops under the RegCM scenario with CO2 set to 560 ppm. Yields increased above baseline for 34% of the soybean and 37% of the winter wheat farms under RegCM/[CO2] D 560 ppm scenario. Water use increased for all crops under the higher temperatures of the CSIRO scenario. Precipitation increases resulted in greater runoff from the traditional crops but not from switchgrass due to the crop’s increased growth and longer growing season. Simulated soil erosion rates under switchgrass and wheat cultivation

Comparative responses of EPIC and CERES crop models to high and low spatial resolution climate change scenarios

We compared the responses of the CERES and EPIC crop models, for wheat and corn, to two different climate change scenarios of different spatial scales applied to the central Great Plains. The scenarios were formed from a high-resolution regional climate model (RegCM) and a coarse resolution general circulation model, which provided the initial and boundary conditions for the regional model. Important differences in yield were predicted by the two models for the two different scenarios. For corn, CERES simulated moderate yield decreases for both scenarios, while EPIC simulated a decrease for the coarse scenario but no change for the fine scale scenario. Differences in the simulation of wheat yields were also found. These differences were traced to the contrasting ways in which the models form final yield, even though their strategies for simulating potential total biomass are similar. We identify the crop model type as an important uncertainty in impacts assessment in addition to the spatial resolution of climate change scenarios.

Relations between Directional Spectral Vegetation Indices and Leaf Area and Absorbed Radiation in Alfalfa

Abstract Sensors on satellite platforms with extreme view angles have been increasingly used to analyze regional and global vegetation cover and productivity because of frequent observations. This study, using experimental and theoretical methods, analyzed variations in vegetation indices with sun-view geometry as a means of understanding the sensitivity of relations beween vegetation indices and the biophysical properties, the leaf area index (LAI), and the instantaneous fraction of absorbed photosynthetically active radiation (fAPAR). Canopy bidirectional reflectance factors (BRFs) of an alfalfa crop were measured and simulated at a variety of solar and view zenith angles. Also, fAPAR, LAI, and leaf optical properties were measured. Measured and simulated canopy reflectances agreed generally within 1% (absolute). Normalized difference and simple ratio vegetation indices (NDVI and SRVI, respectively), derived from BRFs, varied with view and solar zenith angles. The minimum for near-infrared (NIR) BRFs and relatively high red BRFs generally occurred near nadir, resulting in some of the lowest vegetation index values. Highest VI values were generally obtained at forward view angles. Variation of NDVI with sun-view-geometry was greatest at LAs 2. Measured reflectances indicate that relations between NDVI and LAI and between SRVI and fAPAR were curvilinear across all solar and view zenith angle combinations in the solar principal plane, whereas relations between SRVI and LAI and between NDVI and fAPAR varied from linear to curvilinear. Analyses revealed that vegetation indices at large view zenith angles were poorly correlated with fAPAR, whereas those at small zenith angles were strongly correlated. In general, vegetation indices were more sensitive to fAPAR than to LAI, which is attributed to the fact that fAPAR is a radiation quantity, whereas LAI is nonlinearly related to radiation. Regression of fAPAR with VI values derived from combinations of red and NIR BRFs from similar and nonsimilar directions indicates that the highest correlation is in near-nadir and backscatter directions. However, further investigation into variations of relations between remotely sensed observations and canopy attributes and into the usefulness of off-nadir in extracting information is recommended.

Biophysical properties affecting vegetative canopy reflectance and absorbed photosynthetically active radiation at the FIFE site

Leaves of the dominant grass species of the First International Satellite Land Surface Climatology Project (ISLSCP) Field Experiment (FIFE) site reflect and transmit radiation in a similar manner to other healthy green leaves. Visible reflectance factors (RFs) and transmittance factors (TFs) were lower for older leaves than younger leaves except during senescence, when RF and TF values were higher. Near-infrared (NIR) RF values increased and TF values decreased with leaf age, with the reverse occurring as the leaf underwent senescence. Leaf optical properties were not found to be dependent on leaf water potential in the range from −0.5 to −3.0 MPa. Canopy bidirectional reflectance factor (BRF) values generally increased with increasing view zenith angle (θυ). Maximum values were in the backscatter direction, whereas BRF values in the visible region were lowest at oblique off-nadir θυ in the forward scatter direction and at or near nadir in the NIR region. Solar principal plane BRF values varied most at large solar zenith angles (θs). Visible and mid-infrared canopy BRF values decreased and NIR BRF values increased with leaf area index (LAI). Soil BRF distributions in the solar principal plane varied slightly with θs and θυ and varied considerably for wet and dry surfaces. Spectral vegetation indices (SVIs) varied with θs and θυ; values were lowest in the backscatter direction and highest in the forward scatter direction. The fraction of absorbed photosynthetically active radiation (APAR) increased with increasing θs. APAR had a strong linear relationship to nadir-derived SVI values but not to oblique off-nadir-derived SVI values. The relatively small dependence of off-nadir SVI values on θs should allow daily APAR values to be estimated from measurements made at any time of the day.

Spatial scales of climate information for simulating wheat and maize productivity: the case of the US Great Plains

Abstract The spatial aggregation of climate and soils data for use in site-specific crop models to estimate regional yields is examined. The purpose of this exercise is to determine the optimum spatial resolution of observed climate and soils data for simulating major crops grown in the central Great Plains (maize, wheat), beginning at a scale of 2.8°×2.8° (T42), which is close to that of the European Centre for Medium-Range Forecasting (ECMWF) general circulation model (GCM) grid cell and progressively disaggregating climate and soils data to finer spatial scales. Using the Erosion Productivity Impact Calculator (EPIC) crop model, observed crop yields for the period 1984–1992 are compared with yields simulated with observed 1984–1992 climate. The goal is to identify the spatial resolution of climate and soils data which minimizes statistical error between observed and modeled yields. Agreement between simulated and observed maize and wheat was greatly improved when climate data was disaggregated to approximately 1°×1° resolution. No disaggregation results for hay were statistically significant. Disaggregation of climate data finer than the 1°×1° resolution gave no further improvement in agreement. Disaggregation of soils data gave no additional improvement beyond that of the disaggregation of climate data.

Assessing Winter Wheat Responses to Climate Change Scenarios: A Simulation Study in the U.S. Great Plains

Hard red winter wheat (Triticum aestivum L.) is a major crop in the Great Plains region of the U.S. The goal of this assessment effort was to investigate the influence of two contrasting global climate change projections (U.K. Hadley Center for Climate Prediction and Research and Canadian Centre for Climate Modelling and Analysis) on the yield and percent kernel nitrogen content of winter wheat at three locations in Nebraska. These three locations represent sub-humid and semi arid areas and the transition between these areas and are also representative of major portions of the winter wheat growing areas of the central Great Plains. Climate scenarios based on each of the projections for each location were developed using the LARS-WG weather generator along with data from automated weather stations. CERES-Wheat was used to simulate the responses for two contrasting cultivars of wheat using two sowing dates. The first sowing date represented current sowing dates appropriate for each location. The second sowing date was later and represents the approximate date when the mean air temperature from the climate scenarios is the same as the mean air temperature from the actual climate data at the current sowing dates. The yield and percent kernel nitrogen content using the two climate scenarios generally decrease going from the sub-humid eastern to the semi arid western parts of Nebraska. Results from these simulations indicate that yield and percent kernel nitrogen content using the two climate scenarios could not both be maintained at levels currently simulated. Protein content (directly related to kernel nitrogen content) and end-use quality are the primary determinants for the use of hard red winter wheat in baked goods. Nitrogen management and new cultivars, which can enhance the uptake and translocation of nitrogen, will be proactive steps to meet the challenges of global climate change as represented by these climate scenarios.

Modelling the effect of shelterbelts on maize productivity under climate change: An application of the EPIC model

Abstract The potential of shelterbelts to ameliorate climate change induced crop stress, particularly in semi-arid regions such as the North American Great Plains, is examined. Specifically, the microlimate effects of shelterbelts, synthesized from empirical studies in the literature, are inserted into the Erosion-Productivity Impact Calculator (EPIC) crop model to simulate the response of dryland maize to shelter at The University of Nebraska Agricultural Research and Development Center (ARDC) near Mead, Nebraska. Though lack of extensive observed maize yield data precluded rigorous validation, the shelterbelt version of EPIC and a version simulating an unsheltered control were tested with 2 years of observed maize yield data from ARDC. EPIC underpredicted the observed ratio of shelter to open field maize yields as expected because not all benefits of shelter to crops can be incorporated into EPIC. However, the two versions correctly simulated the magnitude of difference in the shelterbelt to open field ratios between the 2 years. The two EPIC versions were then subjected to prescribed increments to temperature, and increments/decrements to precipitation and windspeed to examine differences in crop productivity between the two EPIC versions. The results show that simulated shelter increases dryland maize yields above corresponding unsheltered yields for almost all levels of climate change. The model results suggest that shelterbelts provide a night-time cooling that partially compensates the tendency of warming to shorten the growing season. They also suggest that evapotranspiration is reduced in shelter, thus reducing crop moisture stress. The positive effect of shelter on dryland maize at all levels of temperature increase is greatest for the most severe changes: maximum precipitation deficiency and greatest increase in windspeed. Despite methodological limitations, the findings suggest that shelterbelts may afford important protection from climate warming.

Simulating the impact of human land use change on forest composition in the Great Plains agroecosystems with the Seedscape model

The expansion and contraction of marginal cropland in the Great Plains often involves small forested strips of land that provide important ecological benefits. The effect of human disturbance on these forests is not well known. Because of their unique structure such forests are not well-represented by forest gap models. In this paper, the development, testing and application of a new model known as Seedscape are described. Seedscape is a modification of the JABOWA-II model, and it uses a spatially-explicit landscape to resolve small-scale features of highly fragmented forests in the eastern Great Plains. It was tested and evaluated with observations from two sites, one in Nebraska and a second in eastern Iowa. Seedscape realistically simulates succession at the Nebraska site, but is less successful at the Iowa site. Seedscape was also applied to the Nebraska site to simulate the effect that varying forest corridor widths, in response to the presumed expansion/contraction of adjacent agricultural land, has on succession properties. Results suggest that small differences in widths have negligible effects on forest composition, but large differences in widths may cause statistically-significant changes in the relative importance of some species. We assert that long-term ecological change in human dominated landscapes is not well understood, in part, because of inadequate modeling techniques. Seedscape provides a much-needed tool for assessing the ecological implications of land use change in forests of predominately agricultural landscapes.

An improved goniometer system for calibrating field reference-reflectance panels

Abstract Field reference-reflectance panels need an initial calibration and periodic recalibration to ensure valid field reflectance data. The field calibration method proposed by Jackson et al. (1987) is an affordable means to accomplish this provided that a field goniometer system is available. Design and construction details for such a system are described.

Estimating net radiation with remotely sensed data: Results from KUREX‐91 and FIFE studies∗

Net radiation (Rn) is the major source of energy for evaporating water, heating the soil and air, and photosynthesis. The objective of this study is to estimate this important parameter with various models that have been developed to estimate the radiation balance components with remotely sensed data, and readily available meteorological data. Data used in this paper were collected over grassland vegetation during the FIFE‐87, ‐88, ‐89 studies and the KUREX‐91 study. For all studies estimated values of Rn were within about 10% of measured Rn. For the KUREX‐91 study, measured and estimated Rn agreed to within about 1%. Improvement in a model(s) to estimate the reflected shortwave flux would provide an even better estimate of Rn since in all studies the reflected radiation stream was overestimated compared to the measured values. There was no clear trend for under or over‐estimation of incoming short‐wave radiation from study to study. Components of the long‐wave balance were estimated with low mean relativ...