Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/365
Full metadata record
DC FieldValueLanguage
dc.contributor.advisorTyler, Andrew N.-
dc.contributor.advisorWillby, Nigel-
dc.contributor.advisorGilvear, D., (David)-
dc.contributor.authorHunter, Peter D.-
dc.date.accessioned2008-05-28T12:42:01Z-
dc.date.available2008-05-28T12:42:01Z-
dc.date.issued2007-10-01-
dc.identifier.urihttp://hdl.handle.net/1893/365-
dc.description.abstractShallow lakes are an important ecological and socio-economic resource. However, the impact of human pressures, both at the lake and catchment scale, has precipitated a decline in the ecological status of many shallow lakes, both in the UK, and throughout Europe. There is now, as direct consequence, unprecedented interest in the assessment and monitoring of ecological status and trajectory in shallow lakes, not least in response to the European Union Water Framework Directive (2000/60/EC). In this context, the spatially-resolving and panoramic data provided by remote sensing platforms may be of immense value in the construction of effective and efficient strategies for the assessment and monitoring of ecological status in shallow lakes and, moreover, in providing new, spatially-explicit, insights into the function of these ecosystems and how they respond to change. This thesis examined the use of remote sensing data for the assessment of (i) phytoplankton abundance and species composition and (ii) aquatic vegetation distribution and ecophysiological status in shallow lakes with a view to establishing the credence of such an approach and its value in limnological research and monitoring activities. High resolution in-situ and airborne remote sensing data was collected during a 2-year sampling campaign in the shallow lakes of the Norfolk Broads. It was demonstrated that semi-empirical algorithms could be formulated and used to provide accurate and robust estimations of the concentration of chlorophyll-a, even in these optically-complex waters. It was further shown that it was possible to differentiate and quantify the abundance of cyanobacteria using the biomarker pigment C-phycocyanin. The subsequent calibration of the imagery obtained from the airborne reconnaissance missions permitted the construction of diurnal and seasonal regional-scale time-series of phytoplankton dynamics in the Norfolk Broads. This approach was able to deliver unique spatial insights into the migratory behaviour of a potentially-toxic cyanobacterial bloom. It was further shown that remote sensing can be used to map the distribution of aquatic plants in shallow lakes, importantly including the extent of submerged vegetation, which is central to the assessment of ecological status. This research theme was subsequently extended in an exploration of the use of remote sensing for assessing the ecophysiological response of wetland plants to nutrient enrichment. It was shown that remote sensing metrics could be constructed for the quantification of plant vigour. The extrapolation of these techniques enabled spatial heterogeneity in the ecophysiological response of Phragmites australis to lake nutrient enrichment to be characterised and assisted the formulation of a mechanistic explanation for the variation in reedswamp performance in these shallow lakes. It is therefore argued that the spatially synoptic data provided by remote sensing has much to offer the assessment, monitoring and policing of ecological status in shallow lakes and, in particular, for facilitating the development of pan-European scale lake surveillance capabilities for the Water Framework Directive (2000/60/EC). It is also suggested that remote sensing can make a valuable contribution to furthering ecological understanding and, most significantly, in enabling ecosystem processes and functions to be examined at the lake-scale.en
dc.language.isoenen
dc.publisherUniversity of Stirlingen
dc.subjectRemote sensingen
dc.subjectLimnologyen
dc.subjectWater qualityen
dc.subjectWater framework directiveen
dc.subjectAquatic botanyen
dc.subjectPhycologyen
dc.subject.lcshEcophysiologyen
dc.subject.lcshRemote sensingen
dc.subject.lcshLimnologyen
dc.subject.lcshEutrophicationen
dc.subject.lcshLake ecology Great Britainen
dc.subject.lcshLake ecology Europeen
dc.titleRemote sensing in shallow lake ecologyen
dc.typeThesis or Dissertationen
dc.type.qualificationlevelDoctoralen
dc.type.qualificationnameDoctor of Philosophyen
dc.rights.embargodate2010-01-01-
dc.rights.embargoreasonRequire time to publish articles from thesisen
dc.contributor.funderUniversity of Stirling, Northumbria and Essex and Suffolk Wateren
dc.contributor.affiliationSchool of Natural Sciences-
dc.contributor.affiliationBiological and Environmental Sciences-
Appears in Collections:Biological and Environmental Sciences eTheses

Files in This Item:
File Description SizeFormat 
Hunter_PD_PhDThesis_2007.pdf6.37 MBAdobe PDFView/Open


This item is protected by original copyright



Items in the Repository are protected by copyright, with all rights reserved, unless otherwise indicated.

The metadata of the records in the Repository are available under the CC0 public domain dedication: No Rights Reserved https://creativecommons.org/publicdomain/zero/1.0/

If you believe that any material held in STORRE infringes copyright, please contact library@stir.ac.uk providing details and we will remove the Work from public display in STORRE and investigate your claim.