Sources of sediment-bound organic matter infiltrating spawning gravels during the incubation and emergence life stages of salmonids

Collins, Adrian L.; Williams, L.J.; Zhang, Yusheng; Marius, M.; Dungait, Jennifer A. J.; Smallman, D.J.; Dixon, E. R.; Stringfellow, Anne; Sear, David; Jones, J. Iwan; Naden, Pamela S.

doi:10.1016/j.agee.2014.06.018

Cited by 41 publications

(44 citation statements)

References 76 publications

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“…The Modified MixSIR model uses Bayesian as opposed to frequentist distribution‐based principles, and predicted source proportions can be biased by the choice of sediment unmixing model structure (Laceby & Olley, ; Smith & Blake, ). Previous work has explored a range of weightings including those for tracer analytical precision (Collins et al, ) or discriminatory power (e.g., Collins et al, ) and spatial variations in tracers by source category (e.g., Gellis & Noe, ; Wilkinson et al, ) as well as corrections for particle size (Collins et al, ) or organic matter (e.g., Gellis & Noe, ) selectivity. Here, given the inherent uncertainties associated with these numerical model parameters (Koiter, Owens, Petticrew, & Lobb, ; Laceby et al, ), such additions to unmixing model structure were avoided.…”

Section: Resultsmentioning

confidence: 99%

Fingerprinting the contribution of quarrying to fine‐grained bed sediment in a mountainous catchment, Iran

Nosrati

Collins

2019

River Research & Apps

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The contribution of quarrying in the context of multiple catchment sources of fine‐grained sediment has rarely been investigated. This study assessed the relative importance of quarrying as a sediment source alongside rangeland surface soils and channel banks in a mountainous catchment in northern Tehran, Iran, using fingerprinting. Eight geochemical tracers were measured on 24 potential sediment source samples and four fine‐grained sediment samples. Statistical analysis to select three different composite fingerprints for discriminating the potential sediment sources comprised: (a) the Kruskal–Wallis H test (KW‐H), (b) a combination of KW‐H and discriminant function analysis (DFA), and (c) a combination of KW‐H and principal components and classification analysis (PCCA). A Bayesian unmixing model was used to apportion sediment source contributions using the three composite fingerprints. Using the KW‐H composite signature, the respective relative contributions (with uncertainty ranges) from channel banks, rangeland surface soils, and quarrying were estimated as 28.4% (10.9–46.8), 15.1% (6.6–22.7), and 56.6% (38.3–74.2), compared with 35.4% (11.9–60.1), 13.4% (4.1–22.2), and 51.3% (26.5–74.3) using a composite signature selected using a combination of KW‐H and DFA, or 20.7% (3.9–41.7), 17.2% (4.4–29.9), and 61.4% (44–78.8) using a fingerprint selected using KW‐H and PCCA. The different composite signatures therefore all consistently suggested that quarrying is the dominant source of the fine‐grained sediment samples. Potential mitigation measures targeting this land use include closure to permit revegetation to reduce exposure of bare surfaces to sediment mobilization. Limitations and uncertainties associated with this preliminary investigation are briefly discussed.

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Section: Resultsmentioning

confidence: 99%

Fingerprinting the contribution of quarrying to fine‐grained bed sediment in a mountainous catchment, Iran

Nosrati

Collins

2019

River Research & Apps

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“…The inclusion of both sub‐indices lends support to the arguments to take account of both the mineral and organic components of sediment stress on the aquatic environment (Collins et al ., , ) and properly addresses the definition of sediment stress in the EU WFD. Organic material can be introduced into the fine‐grained sediment load of river systems from a variety of sources, and recent studies have demonstrated fingerprinting procedures for apportioning such inputs (Collins et al ., ).…”

Section: Discussionmentioning

confidence: 99%

Development of a biotic index using stream macroinvertebrates to assess stress from deposited fine sediment

et al. 2015

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1. Detrimental impacts of excessive fine-grained sediment inputs to streams and rivers are well established. What is less well understood is the susceptibility of different elements of the freshwater biota to such perturbations and how such knowledge of their susceptibility could aid in identifying where excessive fine-grained sediment is impairing ecological condition. 2. Following the collection of biological and sediment data from 179 streams across England and Wales, representative of a range of river types over a gradient of fine sediment loading, objective statistical approaches were applied to establish relationships between the macroinvertebrate assemblage and fine-grained sediment inputs to river channels. 3. Having factored out that portion of the biological variation associated with natural environmental gradients, a model comprising mass of organic sediment in erosional areas of the stream bed [predominantly associated with the first axis of the partial canonical correspondence analysis (pCCA)], and mass of fine-grained sediment in the surface drape of depositional areas and % organic content in erosional areas (associated with the second axis of the pCCA) as explanatory variables best accounted for the residual variation in the macroinvertebrate assemblage. 4. The relative position of taxa along both axes of the pCCA, provided a ranking of taxa in relation to the two gradients of fine-grained sediment and provided the basis for a new empirically derived diagnostic index for fine-grained sediment stress in rivers. Two sub-indices were derived to capture the assemblage responses to both the gradient of organic sediment in erosional areas and the gradient of total fines in depositional areas. The two sub-indices were then combined to derive the new combined fine sediment index (CoFSI sp ). 5. The index was tested on an independent test data set (comprising 127 samples from 83 sites) and was found to provide a robust indication of benthic fine-grained sediment conditions (Spearman's rank correlations q = À0.519 to À0.703). The strength of correlation with the total fine-grained sediment gradient was always greater than that for other routinely used indices, confirming that CoFSI sp offered additional explanatory power when assessing this stressor of aquatic environments.

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“…Fine sediment can reduce light penetration and suppress primary production in algae and macrophytes (Izagirre, Serra, Guasch, & Elosegi, ; Jones, Collins, et al, ; Jones, Murphy, et al, ; Yamada & Nakamura, ). Deposited fine sediment can alter bed morphology and degrade habitat for macroinvertebrates (Jones, Collins, et al, ; Jones, Murphy, et al, ) and fish (Collins et al, ; Sear et al, ). In addition, fine sediment provides a transport vector for bound nutrients, heavy metals, and other contaminants (Owens et al, ), particularly from urban run‐off (Jartun, Ottesen, Steinnes, & Volden, ; Witter, Nguyen, Baidar, & Sak, ).…”

Section: Introductionmentioning

confidence: 99%

Bank‐derived material dominates fluvial sediment in a suburban Chesapeake Bay watershed

Cashman

Gellis

Sanisaca

et al. 2018

River Research & Apps

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Excess fine sediment is a leading cause of ecological degradation within the Chesapeake Bay watershed. To effectively target sediment mitigation measures, it is necessary to identify and quantify the delivery of sediment sources to local waterbodies. This study examines the contributions of sediment sources within Upper Difficult Run, a suburbanized watershed in Fairfax County, Virginia. A source sediment library was constructed from stream banks, forest soils, and road dust. Target sediments were collected from fine channel deposits and suspended sediment during 16 storm events from 2008 to 2012. Apportionment of targets to sources was performed using Sed_SAT, a publicly available toolkit for sediment fingerprinting. Bed sediment was dominated by stream bank material (mean: 98%), with minor contributions from forests (2%). Suspended fine sediments were also dominated by stream banks (suspended sediment concentration‐weighted mean: 91%), with minor contributions from roads (8%) and forests (<1%). Stream banks dominated at all discharges, and on the rising limb and at peak flow, sediment concentrations increased due to bank material rather than surface erosion. Sediment budget data indicated that direct bank erosion was insufficient to account for the suspended load derived from stream banks. However, bank‐derived sediment re‐mobilized from in‐channel storage could account for this difference and, combined, resulted in a sediment delivery ratio of 0.847 for all bank‐derived sediments. Results demonstrate that stream bank erosion is responsible for the majority of fine sediment in this suburban watershed of the Chesapeake Bay drainage area. Thus, management actions to control upland sources of sediment may have limited effect on the sediment conditions of Upper Difficult Run, whereas efforts focusing on bank stabilization, channel restoration, and/or stormwater management to reduce bank erosion may improve the ecological condition of these waterbodies.

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Sources of sediment-bound organic matter infiltrating spawning gravels during the incubation and emergence life stages of salmonids

Cited by 41 publications

References 76 publications

Fingerprinting the contribution of quarrying to fine‐grained bed sediment in a mountainous catchment, Iran

Fingerprinting the contribution of quarrying to fine‐grained bed sediment in a mountainous catchment, Iran

Development of a biotic index using stream macroinvertebrates to assess stress from deposited fine sediment

Bank‐derived material dominates fluvial sediment in a suburban Chesapeake Bay watershed

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