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

The cell envelope structure of cable bacteria

Cable bacteria are long, multicellular micro-organisms that are capable of transporting electrons from cell to cell along the longitudinal axis of their centimeter-long filaments. The conductive structures that mediate this long-distance electron transport are thought to be located in the cell envelope. Therefore, this study examines in detail the architecture of the cell envelope of cable bacterium filaments by combining different sample preparation methods (chemical fixation, resin-embedding, and cryo-fixation) with a portfolio of imaging techniques (scanning electron microscopy, transmission electron microscopy and tomography, focused ion beam scanning electron microscopy, and atomic force microscopy). We systematically imaged intact filaments with varying diameters. In addition, we investigated the periplasmic fiber sheath that remains after the cytoplasm and membranes were removed by chemical extraction. Based on these investigations, we present a quantitative structural model of a cable bacterium. Cable bacteria build their cell envelope by a parallel concatenation of ridge compartments that have a standard size. Larger diameter filaments simply incorporate more parallel ridge compartments. Each ridge compartment contains a similar to 50 nm diameter fiber in the periplasmic space. These fibers are continuous across cell-to-cell junctions, which display a conspicuous cartwheel structure that is likely made by invaginations of the outer cell membrane around the periplasmic fibers. The continuity of the periplasmic fibers across cells makes them a prime candidate for the sought-after electron conducting structure in cable bacteria

The Cell Envelope Structure of Cable Bacteria

Cable bacteria are long, multicellular micro-organisms that are capable of transporting electrons from cell to cell along the longitudinal axis of their centimeter-long filaments. The conductive structures that mediate this long-distance electron transport are thought to be located in the cell envelope. Therefore, this study examines in detail the architecture of the cell envelope of cable bacterium filaments by combining different sample preparation methods (chemical fixation, resin-embedding, and cryo-fixation) with a portfolio of imaging techniques (scanning electron microscopy, transmission electron microscopy and tomography, focused ion beam scanning electron microscopy, and atomic force microscopy). We systematically imaged intact filaments with varying diameters. In addition, we investigated the periplasmic fiber sheath that remains after the cytoplasm and membranes were removed by chemical extraction. Based on these investigations, we present a quantitative structural model of a cable bacterium. Cable bacteria build their cell envelope by a parallel concatenation of ridge compartments that have a standard size. Larger diameter filaments simply incorporate more parallel ridge compartments. Each ridge compartment contains a ~50 nm diameter fiber in the periplasmic space. These fibers are continuous across cell-to-cell junctions, which display a conspicuous cartwheel structure that is likely made by invaginations of the outer cell membrane around the periplasmic fibers. The continuity of the periplasmic fibers across cells makes them a prime candidate for the sought-after electron conducting structure in cable bacteria

The challenges and opportunities of addressing particle size effects in sediment source fingerprinting: A review

publisher: Elsevier articletitle: The challenges and opportunities of addressing particle size effects in sediment source fingerprinting: A review journaltitle: Earth-Science Reviews articlelink: http://dx.doi.org/10.1016/j.earscirev.2017.04.009 content_type: article copyright: © 2017 Elsevier B.V. All rights reserved