Literature DB >> 29055595

First use of a compound-specific stable isotope (CSSI) technique to trace sediment transport in upland forest catchments of Chile.

Claudio Bravo-Linares1, Paulina Schuller2, Alejandra Castillo2, Luis Ovando-Fuentealba2, Enrique Muñoz-Arcos2, Oscar Alarcón2, Sergio de Los Santos-Villalobos3, Renan Cardoso4, Marcelo Muniz4, Roberto Meigikos Dos Anjos4, Ramón Bustamante-Ortega5, Gerd Dercon6.   

Abstract

Land degradation is a problem affecting the sustainability of commercial forest plantations. The identification of critical areas prone to erosion can assist this activity to better target soil conservation efforts. Here we present the first use of the carbon-13 signatures of fatty acids (C14 to C24) in soil samples for spatial and temporal tracing of sediment transport in river bodies of upland commercial forest catchments in Chile. This compound-specific stable isotope (CSSI) technique was tested as a fingerprinting approach to determine the degree of soil erosion in pre-harvested forest catchments with surface areas ranging from 12 to 40ha. For soil apportionment a mixing model based on a Bayesian inference framework was used (CSSIAR v.2.0). Approximately four potential sediment sources were used for the calculations of all of the selected catchments. Unpaved forestry roads were shown to be the main source of sediment deposited at the outlet of the catchments (30-75%). Furthermore, sampling along the stream channel demonstrated that sediments were mainly comprised of sediment coming from the unpaved roads in the upper part of the catchments (74-98%). From this it was possible to identify the location and type of primary land use contributing to the sediment delivered at the outlet of the catchments. The derived information will allow management to focus efforts to control or mitigate soil erosion by improving the runoff features of the forest roads. The use of this CSSI technique has a high potential to help forestry managers and decision makers to evaluate and mitigate sources of soil erosion in upland forest catchments. It is important to highlight that this technique can also be a good complement to other soil erosion assessment and geological fingerprinting techniques, especially when attempting to quantify (sediment loads) and differentiate which type of land use most contributes to sediment accumulation.
Copyright © 2017 Elsevier B.V. All rights reserved.

Entities:  

Keywords:  CSSI; CSSIAR; Fatty acids; Fingerprinting; Soil forest management

Year:  2017        PMID: 29055595     DOI: 10.1016/j.scitotenv.2017.09.163

Source DB:  PubMed          Journal:  Sci Total Environ        ISSN: 0048-9697            Impact factor:   7.963


  3 in total

1.  Exploring innovative techniques for identifying geochemical elements as fingerprints of sediment sources in an agricultural catchment of Argentina affected by soil erosion.

Authors:  Romina Torres Astorga; Sergio de Los Santos Villalobos; Hugo Velasco; Olgioly Domínguez-Quintero; Renan Pereira Cardoso; Roberto Meigikos Dos Anjos; Yacouba Diawara; Gerd Dercon; Lionel Mabit
Journal:  Environ Sci Pollut Res Int       Date:  2018-05-15       Impact factor: 4.223

2.  Investigating the importance of recreational roads as a sediment source in a mountainous catchment using a fingerprinting procedure with different multivariate statistical techniques and a Bayesian un-mixing model.

Authors:  Kazem Nosrati; Adrian L Collins
Journal:  J Hydrol (Amst)       Date:  2019-02       Impact factor: 5.722

3.  Sediment source fingerprinting: benchmarking recent outputs, remaining challenges and emerging themes.

Authors:  Adrian L Collins; Martin Blackwell; Pascal Boeckx; Charlotte-Anne Chivers; Monica Emelko; Olivier Evrard; Ian Foster; Allen Gellis; Hamid Gholami; Steve Granger; Paul Harris; Arthur J Horowitz; J Patrick Laceby; Nuria Martinez-Carreras; Jean Minella; Lisa Mol; Kazem Nosrati; Simon Pulley; Uldis Silins; Yuri Jacques da Silva; Micheal Stone; Tales Tiecher; Hari Ram Upadhayay; Yusheng Zhang
Journal:  J Soils Sediments       Date:  2020-09-16       Impact factor: 3.308

  3 in total

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