A - Papers appearing in refereed journals
Collins, A. L., Zhang, Y., McMillan, S., Dixon, E. R., Cancer-Berroya, E., Poiret, C. and Stringellow, A. 2017. Fingerprinting source contributions to bed sediment‐associated organic matter in the headwater subcatchments of the River Itchen SAC, Hampshire, UK. River Research and Applications. 33 (10), pp. 1515-1526.
|Authors||Collins, A. L., Zhang, Y., McMillan, S., Dixon, E. R., Cancer-Berroya, E., Poiret, C. and Stringellow, A.|
Excessive accumulation of sediment‐associated organic matter in river beds has detrimental impacts on aquatic ecology, including fish. Sediment and source samples were collected from 3 headwater tributaries of the River Itchen, in southern England. Near infrared spectra and bulk stable carbon and nitrogen isotopes were employed as fingerprint properties to quantify the relative contributions from catchment‐based (farmyard manures/slurries, damaged road verges, and septic tanks) and channel‐based (decaying instream vegetation, watercress farms, and fish farms) sources. The findings suggested that over the duration of the sampling period, the final estimated median relative contributions in the Candover Stream subcatchment were in the order: farmyard measures/slurries 74% > decaying instream vegetation 15% > watercress farms 6% > septic tanks 3% > damaged road verges 2%. For the River Arle subcatchment, corresponding estimated median relative contributions were in the order: watercress farms 40% > farmyard manures/slurries 28% > decaying instream vegetation 21% > fish farms 7% > damaged road verges and septic tanks 2% each. Similar contributions were estimated for the Tichborne Stream subcatchment: watercress farms 36% > farmyard manures/slurries 26% > decaying instream vegetation 26% and damaged road verges and septic tanks at 6% each. These source apportionment estimates will contribute to stakeholder engagement and targeted management interventions.
|Keywords||bulk stable isotopes|
|NIR reflectance spectroscopy|
|sediment‐associated organic matter|
|Year of Publication||2017|
|Journal||River Research and Applications|
|Journal citation||33 (10), pp. 1515-1526|
|Digital Object Identifier (DOI)||doi:10.1002/rra.3172|
|Online||09 Aug 2017|
|Copyright license||CC BY|
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