Spatial contrasts of seasonal and intraflock broiler litter trace gas emissions, physical and chemical properties

Comprehensive mitigation strategies for gaseous emissions from broiler operations requires knowledge of the litters' physical and chemical properties, gas evolution, bird effects, as well as broiler house management and structure. This research estimated broiler litter surface fluxes for ammonia (NH3), nitrous oxide (N2O), and carbon dioxide (CO2). Ancillary measurements of litter temperature, litter total N, ammonium (NH4+), total C content, moisture, and pH were also made. Grid sampling was imposed over the floor area of two commercial broiler houses at the beginning (Day 1), middle (Day 23), and end (Day 43) of a winter and subsequent summer flock housed on reused pine shavings litter. The grid was composed of 36 points, three locations across the width, and 12 locations down the length of the houses. To observe feeder and waterer (F/W) influences on the parameters, eight additional sample locations were added in a crisscross pattern among these automated supply lines. Color variograms illustrate the nature of parameter changes within each flock and between seasons. Overall trends for the NH3, N2O, and CO2 gas fluxes indicate an increase in magnitude with bird age during a flock for both summer and winter, but flux estimates were reduced in areas where compacted litter (i.e., caked litter or cake) formed at the end of the flocks (at F/W locations and in the fan area). End of flock gas fluxes were estimated at 1040 mg NH3 m(-2) h(-1), 20 mg N2O m(-2) h(-1), and 24,200 mg CO2 m(-2) h(-1) in winter; and 843 mg NH3 m(-2) h(-1), 18 mg N2O m(-2) h(-1)), and 27,200 mg CO2 m(-2) h(-1) in summer. The results of intensive sample efforts during winter and summer flocks, reported visually using contour plots, offer a resource to the poultry industry and researchers for creating new management strategies for improving production and controlling gas evolution. Particularly, efforts could focus on designing housing systems that minimize extremes in litter compaction. The extremes are undesirable with more friable litter prone to greater gas evolution and more compacted litter providing a slippery, disease-sustaining surface.     

The IPBES Conceptual Framework: An Unhelpful Start

The Intergovernmental Platform on Biodiversity and Ecosystem Services (IPBES) have recently launched themselves as the UN-sanctioned instrument for conserving nature. They seek to establish themselves as the authority in this field alongside the well-known Intergovernmental Panel on Climate Change in climate science. Quickly following or even before recent publication of their conceptual framework in two biology journals, they were already underway building upon it. This headlong push, we believe, is ill advised. We show how the framework is unsound as a foundation for further work—in a number of ways and perhaps even by its authors’ own lights. It is therefore urgent that the IPBES thoroughly and thoughtfully reconsider their framework before too much effort is wasted.     

Stochastic Transfer Function Model and Neural Networks to Estimate Soil Moisture1

Abstract: A practical methodology is proposed to estimate the three‐dimensional variability of soil moisture based on a stochastic transfer function model, which is an approximation of the Richard’s equation. Satellite, radar and in situ observations are the major sources of information to develop a model that represents the dynamic water content in the soil. The soil‐moisture observations were collected from 17 stations located in Puerto Rico (PR), and a sequential quadratic programming algorithm was used to estimate the parameters of the transfer function (TF) at each station. Soil texture information, terrain elevation, vegetation index, surface temperature, and accumulated rainfall for every grid cell were input into a self‐organized artificial neural network to identify similarities on terrain spatial variability and to determine the TF that best resembles the properties of a particular grid point. Soil moisture observed at 20 cm depth, soil texture, and cumulative rainfall were also used to train a feedforward artificial neural network to estimate soil moisture at 5, 10, 50, and 100 cm depth. A validation procedure was implemented to measure the horizontal and vertical estimation accuracy of soil moisture. Validation results from spatial and temporal variation of volumetric water content (vwc) showed that the proposed algorithm estimated soil moisture with a root mean squared error (RMSE) of 2.31% vwc, and the vertical profile shows a RMSE of 2.50% vwc. The algorithm estimates soil moisture in an hourly basis at 1 km spatial resolution, and up to 1 m depth, and was successfully applied under PR climate conditions.     

Design and risk assessment tool for vegetative treatment areas receiving agricultural wastewater: Preliminary results

Vegetative treatment areas (VTAs) are commonly being used as an alternative method of agricultural process wastewater treatment. However, it is also apparent that to completely prevent discharge of pollutants to the surrounding environment, settling of particulates and bound constituents from overland flow through VTAs is not sufficient. For effective remediation of dissolved agricultural pollutants, VTAs must infiltrate incoming wastewater. A simple water balance model for predicting VTA soil saturation and surface discharge in landscapes characterized by sloping terrain and a shallow restrictive layer is presented and discussed. The model accounts for the cumulative effect of successive rainfall events and wastewater input on soil moisture status and depth to water table. Nash–Sutcliffe efficiencies ranged from 0.65 to 0.81 for modeled and observed water table elevations after calibration of saturated hydraulic conductivity. Precipitation data from relatively low, average, and high annual rainfall years were used with soil, site, and contributing area data from an example VTA for simulations and comparisons. Model sensitivity to VTA width and contributing area (i.e. barnyard, feedlot, silage bunker, etc.) curve number was also investigated. Results of this analysis indicate that VTAs should be located on steeper slopes with deeper, more-permeable soils, which effectively lowers the shallow water table. In sloping landscapes (>2%), this model provides practitioners an easy-to-use VTA design and/or risk assessment tool that is more hydrological process-based than current methods.     

Phosphorus saturation in spodosols impacted by manure

Significant amounts of phosphorus (P) accumulate in soils receiving animal manures that could eventually result in unacceptable concentrations of dissolved P loss through surface runoff or subsurface leaching. The degree of phosphorus saturation (DPS) relates a soil's extractable P to its P sorbing capacity, and is reportedly a predictor of the P likely to be mobilized from a system. A DPS value (DPS-1) was derived that expressed the percentage of Mehlich 1-extractable P to the sorbing capacity of a Spodosol (expressed as the sum of oxalate-extractable Fe and Al). Values of DPS-1 were determined in various horizons of soil in current and abandoned dairy systems in South Florida's Lake Okeechobee watershed to assess P release potential. Land use within the dairies was classified as highly impacted by cattle (intensive and holding), and minimally impacted by cattle (pasture, forage, or native) areas. The A and E horizon of soils in heavily manure-impacted intensive and holding areas for both active and abandoned dairies generally had higher DPS-1 values than the pasture, forage, and native area soils, which were minimally impacted by manure. Degree of P saturation was also calculated as a percentage of Mehlich 1-extractable P to the sum of Mehlich 1-extractable Fe and Al (DPS-2). Both DPS-1 and DPS-2 were shown to be significantly (P = 0.0001) related to water-extractable P for all soil horizons, suggesting that either index can be used as an indicator for P loss potential from a soil.