Data quality in applied geochemistry: the requirements, and how to achieve them

To obtain a reliable interpretation of geochemical data, we need to ensure that the measurements are of sufficiently high quality. To do this we need to be able to specify quantitatively the data quality that we need, and then to be certain that we are getting it. The latter can be achieved only if properly validated analytical methods are employed, and well-designed quality control schemes are used as a matter of routine.     

Additive versus multiplicative models in ecologic regression

Much research in environmental epidemiology relies on aggregate-level information on exposure to potentially toxic substances and on relevant covariates. We compare the use of additive (linear) and multiplicative (log-linear) regression models for the analysis of such data. We illustrate how both additive and multiplicative models can be fit to aggregate-level data sets in which disease incidence is the dependent variable, and contrast these results with similar models fitted to individual-level data. We find (1) that for aggregate-level data, multiplicative models are more likely than additive models to introduce bias into the estimation of rates, an effect not found with individual-level data; and (2) that under many circumstances multiplicative models reduce the precision of the estimates, an effect also not found in individual-level models. For both additive and multiplicative models of aggregate-level data, we find that, in the presence of covariates, narrow confidence interval are obtained only when two or more antecedent factors are strongly related to the measured covariate and/or the exposure of primary substantive interest. We conclude that the equivalency of fitting additive versus multiplicative models in studies with individual-level binary data does not carry over to studies that analyze aggregate-level information. For aggregate data, we strongly recommend use of additive models. Supported by Grant #1 U19 EH000102 from the National Center for Environmental Health, Centers for Disease Control and Prevention, Atlanta, GA.     

Soil moisture and rainfall intensity thresholds for runoff generation in southwestern Wisconsin agricultural watersheds

The goal of this study was to improve understanding of the factors that influence runoff generation during non‐frozen ground periods in small agricultural watersheds in southwestern Wisconsin where the landscapes are controlled by dolostone bedrock in order to provide agricultural producers with a manure management tool. Six small watersheds (ranging from 6 to 17 ha) within two southwestern Wisconsin farm sites (Discovery Farms Program (DFP) and Pioneer Farm (PF)) were instrumented, and surface runoff was continuously monitored from 2004 to 2007. The soils in all watersheds were formed in deep (~1 m) loessial sites. A direct‐plant management strategy and corn‐soybean crop rotation were utilized within watersheds at DFP. A conventional tillage system (chisel plow in the fall followed by soil finisher in the spring) and a corn‐oat‐alfalfa crop rotation were utilized within watersheds at PF. At PF, the amount of precipitation leaving the landscape as surface runoff (1.8%) was two times greater compared to DFP (0.9%), indicating that the direct‐plant management system was better at retaining precipitation than the chisel plow/soil finisher system. Using breakpoint regression analysis, a non‐linear response in runoff generation with antecedent soil moisture (ASM) was observed with a threshold ASM of 0.39 cm³cm^?3 (approximately 80% of total porosity) for all six watersheds. Below this threshold, runoff coefficients were near zero. Above this threshold, runoff coefficients increased with ASM. A non‐linear response in runoff generation with maximum 30 min rainfall intensity (I30) was also observed, and threshold I30 values increased as ASM decreased and as crop cover increased. Copyright © 2012 John Wiley & Sons, Ltd.     

Turbulence Measurements above a Pine Forest

Eddy fluxes of momentum, sensible and latent heat, and turbulence spectra measured over the Thetford Forest during 10 days in the Spring of 1973 are described. The measured total heat flux (H + λE) for 122 20-min periods agreed closely on average with independent estimates from an energy balance method. There was evidence that the energy balance data gave small systematic overestimates of available energy during the hours before noon, compensated by slight underestimates for the remainder of the day. A comparison of measured wind speeds and friction velocities in neutral stability confirmed the validity of the aerodynamic method for estimating momentum fluxes at heights of a few roughness lengths above the canopy. In stable conditions the log-linear wind profile $U=(u_{?t}/k)({? ln}((z-d)/z_{0})+←pha(z-d-z_{0})/L)$ with α = 3.4 ± 0.4 provided a good fit to the data. Spectra in unstable conditions were generally more sharply peaked than those measured by other workers over smoother terrain: differences were less marked in the case of vertical velocity in stable conditions. Temperature spectra in these stable conditions showed high energy at relatively low wavenumbers, and wT cospectra showed a cospectral gap; both of these results were associated with an intermittent sawtooth structure in the temperature fluctuations.     

Comparison of methods used in the measurement of precipitation and evaporation

Summary The measurement of evaporation and precipitation continues to be most problematic, particularly in terms of the accuracy of the instruments used and their standardization world-wide. This paper analyzes daily data from three rain gauges and two evaporimeters over a five-year period and correlates observed differences with the prevailing meteorological conditions. It was determined that ground-level gauges and large evaporation tanks provide the most acceptable and representative measurements from instruments currently in use. However, new developments are necessary for improved accuracy and world-wide adoption.With 2 Figures     

Pollen-based continental climate reconstructions at 6 and 21 ka: a global synthesis

Subfossil pollen and plant macrofossil data derived from ¹⁴C-dated sediment profiles can provide quantitative information on glacial and interglacial climates. The data allow climate variables related to growing-season warmth, winter cold, and plant-available moisture to be reconstructed. Continental-scale reconstructions have been made for the mid-Holocene (MH, around 6 ka) and Last Glacial Maximum (LGM, around 21 ka), allowing comparison with palaeoclimate simulations currently being carried out as part of the fifth Assessment Report (AR5) of the Intergovernmental Panel on Climate Change. The synthesis of the available MH and LGM climate reconstructions and their uncertainties, obtained using modern-analogue, regression and model-inversion techniques, is presented for four temperature variables and two moisture variables. Reconstructions of the same variables based on surface-pollen assemblages are shown to be accurate and unbiased. Reconstructed LGM and MH climate anomaly patterns are coherent, consistent between variables, and robust with respect to the choice of technique. They support a conceptual model of the controls of Late Quaternary climate change whereby the first-order effects of orbital variations and greenhouse forcing on the seasonal cycle of temperature are predictably modified by responses of the atmospheric circulation and surface energy balance.