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dc.contributor.authorWalmsley, Cliveen
dc.date.accessioned2017-01-10T11:06:53Z
dc.date.available2017-01-10T11:06:53Z
dc.date.issued2016-08-02
dc.identifier.urihttp://hdl.handle.net/1842/19506
dc.description.abstractEnvironmental bodies are undertaking active efforts to improve habitat connectivity by mitigating barriers to fish passage on rivers. As part of efforts to restore rivers, methods are needed to identify which barriers to fish passage should be prioritised for removal. Semi-automated methods which analyse Digital River Networks (DRN) offer the potential to provide this information in a cost-effective and timely manner. This paper proposes a new methodology for deriving habitat size as an area or length from which improves upon existing reviewed approaches. This methodology is verified to check its accuracy and consistency against an alternate approach which uses length as the metric. It is then implemented on a larger data set for the River Ribble to demonstrate its ability to use area and illustrate how that changes prioritisation results. Usability is assessed using a System Usability Scale and the pre-processing is found to be the main limitation for this methodology, however, this is a factor which is likely to affect all network basis analysis. The proposed methodology provides a new proof of concept approach to derive habitat area between barriers to fish passage from a DRN.en
dc.language.isoen
dc.publisherThe University of Edinburghen
dc.rightsAttribution-ShareAlike 4.0 Internationalen
dc.rights.urihttp://creativecommons.org/licenses/by-sa/4.0/
dc.subjectFish barrier prioritisation habitat area length usabilityen
dc.titleUsing Digital River Network Data to Improve Methods for Prioritising the Mitigation of Barriers to Fish Passageen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelMastersen
dc.type.qualificationnameMSc Master of Scienceen
dcterms.accessRightsRestricted Accessen


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Attribution-ShareAlike 4.0 International
Except where otherwise noted, this item's license is described as Attribution-ShareAlike 4.0 International