A comparison of conventional and 137 Cs-based estimates of soil erosion rates on arable and grassland across lowland England and Wales

Soils deliver a range of ecosystem services and underpin conventional global food production which must increase to feed the projected growth in human population. Although soil erosion by water and subsequent sediment delivery to rivers are natural processes, anthropogenic pressures, including modern farming practices and management, have accelerated soil erosion rates on both arable and grassland. A range of approaches can be used to assess and document soil erosion rates and, in the case of the UK, these mainly comprise the 137Cs-based approach, conventional surveys using volumetric measurements, integration of information on suspended sediment flux, fine sediment source apportionment and landscape sediment retention and traditional bounded hydrological monitoring at edge-of-field using experimental platforms. We compare the erosion rates for arable and grassland in lowland England assessed by these different techniques. Rates assessed by volumetric measurements are similar to those generated by integrating information on suspended sediment flux, sources and landscape retention, but are much less than those estimated by the 137Cs-based approach; of the order of one magnitude less for arable land. The 137Cs approach assumes an initial distribution of 137Cs uniformly spread across the landscape and relates the sampled distribution to erosion, but other (transport) processes are also involved and their representation in the calibration procedures remains problematic. We suggest that the 137Cs technique needs to be validated more rigorously and conversion models re-calibrated. As things stand, rates of erosion based on the distribution of 137Cs may well overstate the severity of the problem in lowland Britain and, therefore, are not a reliable indicator of water erosion rates

High-temporal resolution fluvial sediment source fingerprinting with uncertainty: a Bayesian approach

This contribution addresses two developing areas of sediment fingerprinting research. Specifically, how to improve the temporal resolution of source apportionment estimates whilst minimizing analytical costs and, secondly, how to consistently quantify all perceived uncertainties associated with the sediment mixing model procedure. This first matter is tackled by using direct X-ray fluorescence spectroscopy (XRFS) and diffuse reflectance infrared Fourier transform spectroscopy (DRIFTS) analyses of suspended particulate matter (SPM) covered filter papers in conjunction with automatic water samplers. This method enables SPM geochemistry to be quickly, accurately, inexpensively and non-destructively monitored at high-temporal resolution throughout the progression of numerous precipitation events. We then employed a Bayesian mixing model procedure to provide full characterization of spatial geochemical variability, instrument precision and residual error to yield a realistic and coherent assessment of the uncertainties associated with source apportionment estimates. Applying these methods to SPM data from the River Wensum catchment, UK, we have been able to apportion, with uncertainty, sediment contributions from eroding arable topsoils, damaged road verges and combined subsurface channel bank and agricultural field drain sources at 60- and 120-minute resolution for the duration of five precipitation events. The results presented here demonstrate how combining Bayesian mixing models with the direct spectroscopic analysis of SPM-covered filter papers can produce high-temporal resolution source apportionment estimates that can assist with the appropriate targeting of sediment pollution mitigation measures at a catchment level

Sensitivity of fluvial sediment source apportionment to mixing model assumptions: A Bayesian model comparison

Mixing models have become increasingly common tools for apportioning fluvial sediment load to various sediment sources across catchments using a wide variety of Bayesian and frequentist modeling approaches. In this study, we demonstrate how different model setups can impact upon resulting source apportionment estimates in a Bayesian framework via a one-factor-at-a-time (OFAT) sensitivity analysis. We formulate 13 versions of a mixing model, each with different error assumptions and model structural choices, and apply them to sediment geochemistry data from the River Blackwater, Norfolk, UK, to apportion suspended particulate matter (SPM) contributions from three sources (arable topsoils, road verges, and subsurface material) under base flow conditions between August 2012 and August 2013. Whilst all 13 models estimate subsurface sources to be the largest contributor of SPM (median ∼76%), comparison of apportionment estimates reveal varying degrees of sensitivity to changing priors, inclusion of covariance terms, incorporation of time-variant distributions, and methods of proportion characterization. We also demonstrate differences in apportionment results between a full and an empirical Bayesian setup, and between a Bayesian and a frequentist optimization approach. This OFAT sensitivity analysis reveals that mixing model structural choices and error assumptions can significantly impact upon sediment source apportionment results, with estimated median contributions in this study varying by up to 21% between model versions. Users of mixing models are therefore strongly advised to carefully consider and justify their choice of model structure prior to conducting sediment source apportionment investigations

Apportioning sources of organic matter in streambed sediments: An integrated molecular and compound-specific stable isotope approach

We present a novel application for quantitatively apportioning sources of organic matter in streambed sediments via a coupled molecular and compound-specific isotope analysis (CSIA) of long-chain leaf wax n-alkane biomarkers using a Bayesian mixing model. Leaf wax extracts of 13 plant species were collected from across two environments (aquatic and terrestrial) and four plant functional types (trees, herbaceous perennials, and C3 and C4 graminoids) from the agricultural River Wensum catchment, UK. Seven isotopic (δ13C27, δ13C29, δ13C31, δ13C27–31, δ2H27, δ2H29, and δ2H27–29) and two n-alkane ratio (average chain length (ACL), carbon preference index (CPI)) fingerprints were derived, which successfully differentiated 93% of individual plant specimens by plant functional type. The δ2H values were the strongest discriminators of plants originating from different functional groups, with trees (δ2H27–29 = − 208‰ to − 164‰) and C3 graminoids (δ2H27–29 = − 259‰ to − 221‰) providing the largest contrasts. The δ13C values provided strong discrimination between C3 (δ13C27–31 = − 37.5‰ to − 33.8‰) and C4 (δ13C27–31 = − 23.5‰ to − 23.1‰) plants, but neither δ13C nor δ2H values could uniquely differentiate aquatic and terrestrial species, emphasizing a stronger plant physiological/biochemical rather than environmental control over isotopic differences. ACL and CPI complemented isotopic discrimination, with significantly longer chain lengths recorded for trees and terrestrial plants compared with herbaceous perennials and aquatic species, respectively. Application of a comprehensive Bayesian mixing model for 18 streambed sediments collected between September 2013 and March 2014 revealed considerable temporal variability in the apportionment of organic matter sources. Median organic matter contributions ranged from 22% to 52% for trees, 29% to 50% for herbaceous perennials, 17% to 34% for C3 graminoids and 3% to 7% for C4 graminoids. The results presented here clearly demonstrate the effectiveness of an integrated molecular and stable isotope analysis for quantitatively apportioning, with uncertainty, plant-specific organic matter contributions to streambed sediments via a Bayesian mixing model approach

Measurement component technology. Volume 3: Cryogenic temperature measurement and high temperature strain gage technology

For abstract, see N74-27185

Posttraumatic Stress among Young Urban Children Exposed to Family Violence and Other Potentially Traumatic Events

This study examines the relationship between the number of types of traumatic events experienced by children 3 to 6 years old, parenting stress, and children\u27s posttraumatic stress (PTS). Parents and caregivers provided data for 154 urban children admitted into community-based mental health or developmental services. By parent and caregiver report, children experienced an average of 4.9 different types of potentially traumatic events. Nearly one quarter of the children evidenced clinically significant PTS. Posttraumatic stress was positively and significantly related to family violence and other family-related trauma exposure, nonfamily violence and trauma exposure, and parenting stress. Additionally, parenting stress partially mediated the relationship between family violence and trauma exposure and PTS. This study highlights the need for early violence and trauma exposure screening in help-seeking populations so that appropriate interventions are initiated

Focus, Vol. 1 No. 1

A literary magazine of student writing published by the Department of English of Stephen F. Austin State College.https://scholarworks.sfasu.edu/focus/1000/thumbnail.jp