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dc.contributor.advisorSmout, Sophie Caroline
dc.contributor.advisorIllian, Janine
dc.contributor.authorJones, Esther Lane
dc.coverage.spatialxii, 178 p.en_US
dc.date.accessioned2017-12-07T10:06:41Z
dc.date.available2017-12-07T10:06:41Z
dc.date.issued2017-06-21
dc.identifier.urihttps://hdl.handle.net/10023/12278
dc.descriptionElectronic version excludes material for which permission has not been granted by the rights holderen
dc.description.abstractSpecies distribution maps can provide important information to focus conservation efforts and enable spatial management of human activities. Two sympatric marine predators, grey seals (Halichoerus grypus) and harbour seals (Phoca vitulina), have overlapping ranges but contrasting population dynamics around the UK; whilst grey seals have generally increased, harbour seals have shown significant regional declines. A robust analytical methodology was developed to produce maps of grey and harbour seal usage estimates with corresponding uncertainty, and scales of spatial partitioning between the species were found. Throughout their range, both grey and harbour seals spend the majority of their time within 50 km of the coast. The scalability of the analytical approach was enhanced and environmental information to enable spatial predictions was included. The resultant maps have been applied to inform consent and licensing of marine renewable developments of wind farms and tidal turbines. For harbour seals around Orkney, northern Scotland, distance from haul out, proportion of sand in seabed sediment, and annual mean power were important predictors of space-use. Utilising seal usage maps, a framework was produced to allow shipping noise, an important marine anthropogenic stressor, to be explicitly incorporated into spatial planning. Potentially sensitive areas were identified through quantifying risk of exposure of shipping traffic to marine species. Individual noise exposure was predicted with associated uncertainty in an area with varying rates of co-occurrence. Across the UK, spatial overlap was highest within 50 km of the coast, close to seal haul outs. Areas identified with high risk of exposure included 11 Special Areas of Conservation (from a possible 25). Risk to harbour seal populations was highest, affecting half of all SACs associated with the species. For 20 of 28 animals in the acoustic exposure study, 95% CI for M-weighted cumulative Sound Exposure Levels had upper bounds above levels known to induce Temporary Threshold Shift. Predictions of broadband received sound pressure levels were underestimated on average by 0.7 dB re 1μPa (± 3.3). An analytical methodology was derived to allow ecological maps to be quantitatively compared. The Structural Similarity (SSIM) index was enhanced to incorporate uncertainty from underlying spatial models, and a software algorithm was developed to correct for internal edge effects so that loss of spatial information from the map comparison was limited. The application of the approach was demonstrated using a case study of sperm whales (Physeter macrocephalus, Linneaus 1758) in the Mediterranean Sea to identify areas where local-scale differences in space-use between groups and singleton whales occurred. SSIM is applicable to a broad range of spatial ecological data, providing a novel tool for map comparison.en_US
dc.language.isoenen_US
dc.publisherUniversity of St Andrews
dc.relationJones , E L , McConnell , B J , Smout , S C , Hammond , P S , Duck , C D , Morris , C , Thompson , D , Russell , D J F , Vincent , C , Cronin , M , Sharples , R J & Matthiopoulos , J 2015 , ' Patterns of space use in sympatric marine colonial predators reveals scales of spatial partitioning ' (Postprint version of Chapter 2) http://hdl.handle.net/10023/9386en
dc.relation.urihttp://hdl.handle.net/10023/9386
dc.rightsAttribution-NoDerivatives 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nd/4.0/*
dc.subjectSpatial ecologyen_US
dc.subjectTelemetryen_US
dc.subjectMarine spatial planningen_US
dc.subjectDensity estimationen_US
dc.subjectHabitat selection modellingen_US
dc.subjectMarine renewablesen_US
dc.subjectEnvironmental dataen_US
dc.subjectMarine protected areasen_US
dc.subjectGrey sealsen_US
dc.subjectHarbour sealsen_US
dc.subjectSperm whalesen_US
dc.subjectHalichoerus grypusen_US
dc.subjectPhoca vitulinaen_US
dc.subjectPhyseter macrocephalusen_US
dc.subjectSound exposureen_US
dc.subjectShipping noiseen_US
dc.subjectMarine pollutantsen_US
dc.subjectAnthropogenic stressorsen_US
dc.subjectGEEen_US
dc.subjectGAMen_US
dc.subjectMap comparisonen_US
dc.subjectStructural Similarity indexen_US
dc.subjectSpace useen_US
dc.subjectSpatial distributionen_US
dc.subjectWind farmen_US
dc.subjectTidal turbineen_US
dc.subject.lccQH541.15S62J7
dc.subject.lcshSpatial ecologyen
dc.subject.lcshPredatory marine animals--Ecology--Great Britainen
dc.subject.lcshGray seals--Effect of noise on--Great Britainen
dc.subject.lcshHarbor seals--Effect of noise on--Great Britainen
dc.titleSpatial ecology of marine top predatorsen_US
dc.typeThesisen_US
dc.contributor.sponsorUniversity of St Andrews. Centre for Research into Ecological and Environmental Modelling (CREEM)en_US
dc.type.qualificationlevelDoctoralen_US
dc.type.qualificationnamePhD Doctor of Philosophyen_US
dc.publisher.institutionThe University of St Andrewsen_US
dc.publisher.departmentNERC Sea Mammal Research Unit (SMRU)en_US
dc.identifier.doihttps://doi.org/10.17630/10023-12278


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