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Alley-cropping systems that pair economically important tree species with crop production in alleyways have the potential to diversify outputs and improve resource use efficiency. However, management practices are more complex because trees and crops have different nutrient requirements and access different depths in the soil profile. Foliar nutrient concentrations are often used to determine fertility plans for fruit and nut production orchards, but these recommendations may not be appropriate in integrated tree and crop production systems. This research describes foliar nutrient concentrations in three different tree species, red oak (Quercus rubra L.), pecan [Carya illinoinensis (Wangenh.) K. Koch], and black walnut (Juglans nigra L.), at an alley-cropping site in northwest Arkansas, USA from 2004 to 2012. Foliar nutrient concentrations did not differ in trees fertilized by poultry litter when compared to those receiving synthetic N fertilizer. Concentrations of nutrients changed over time in all three species, with Mg and Ca increasing and N, K, S, Fe, and Na decreasing as trees aged. A principal components analysis indicated that leaf nutrient levels in oak and pecan were much more similar to each other than to black walnut. Some of the foliar nutrient concentrations identified in this study were inconsistent with sufficiency ranges reported in fruit and nut production orchards. However, given the multiple aims of an alley-cropping system, these inconsistencies may not represent deficiencies in available nutrients for these tree species. [ABSTRACT FROM AUTHOR]

Fast-response infrared gas analyzers (IRGAs) have been widely used over three decades in many ecosystems for long-term monitoring of water vapor fluxes in the surface layer of the atmosphere. While some of the early IRGA sensors are still used in these national and/or regional eco-flux networks, optically-improved IRGA sensors are newly employed in the same networks. The purpose of this study was to evaluate the performance of water vapor density and flux data from three generations of IRGAs - LI-7500, LI-7500A, and LI-7500RS (LI-COR Bioscience, Inc., Nebraska, USA) - over the course of a growing season in Bushland, Texas, USA in an irrigated maize canopy for 90 days. The energy balance ratio, which is the sum of turbulent fluxes divided by the sum of surface available energy, was used to assess systematic biases of the IRGA sensors for evapotranspiration (ET). Water vapor density measurements were in generally good agreement, but temporal drift occurred in different directions and magnitudes. Means exhibited mostly shift changes that did not impact the flux magnitudes, while variances of water vapor density fluctuations were occasionally in poor agreement, especially following rainfall events. LI-7500 variances were largest compared to recent LI-7500RS and LI-7500A results manifesting in widened cospectra, especially under unstable and neutral static stability. Agreement among the sensors was best under the typical irrigation-cooled boundary layer, with a 14% interinstrument coefficient of variability under advective conditions. Generally, the smallest variances occurred with the LI-7500RS, and high-frequency spectral corrections were larger for these measurements resulting in similar fluxes between the LI-7500A and LI-7500RS. Fluxes from the LI-7500 were best representative of growing season ET based on a world-class lysimeter reference measurement but using the energy balance ratio as an estimate of systematic bias corrected most of the differences among measured fluxes. [ABSTRACT FROM AUTHOR]

Decreased groundwater levels of the Ogallala Aquifer have increased interest in simulating crop responses to deficit irrigation strategies to evaluate the sustainable irrigation management for profitable crop production. However, the ability of widely used simulation models to accurately represent crop responses to deficit irrigation is not thoroughly evaluated. Therefore, the objective of this research was to evaluate the efficacy of the plant stress algorithms in Soil and Water Assessment Tool (SWAT) to simulate corn (Zea mays L.) responses to deficit irrigation treatments. Results showed simulated corn leaf area index (LAI), biomass, and yield under full irrigation scenarios matched measured data reasonably well at two study sites. However, clear reductions in model performance statistics for corn LAI simulations were found under the deficit irrigation scenarios for both sites (Nash- Sutcliffe efficiency [NSE] <0.49; percent bias [PBIAS] >14%). Additionally, considerable overestimation of yield occurred in the deficit irrigation scenarios for both sites (PBIAS >30% in most years). The unsatisfactory results from simulations of both LAI and yield under the deficit irrigation scenarios suggested potential deficiencies of the plant stress algorithms in SWAT. Two apparent limitations of the plant stress algorithms were (i) the equation for computing actual plant growth factor using a singular stress factor, determined by the maximum value of four plant stress factors of water, temperature, nitrogen, and phosphorus, and (ii) the computed actual plant growth factor only adjusting potential daily accumulations of LAI rather than modifying the shape of the LAI development by adjusting related parameters. [ABSTRACT FROM AUTHOR]

The survival of America's small farms depends on some pretty basic factors. And sometimes they are right at our feet. In the Southeast's tall fescue belt--stretching from Arkansas and Missouri [...]