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dc.contributor.authorBoehme, Lars
dc.contributor.authorLonergan, Mike
dc.contributor.authorTodd, Christopher David
dc.date.accessioned2014-12-05T12:01:03Z
dc.date.available2014-12-05T12:01:03Z
dc.date.issued2014-12-03
dc.identifier.citationBoehme , L , Lonergan , M & Todd , C D 2014 , ' A comparison of gridded sea surface temperature datasets for marine ecosystem studies ' Marine Ecology Progress Series , vol. 516 , pp. 7-22 . https://doi.org/10.3354/meps11023en
dc.identifier.issn0171-8630
dc.identifier.otherPURE: 80983409
dc.identifier.otherPURE UUID: dc7759f9-27bd-4332-8aba-dd205657cc67
dc.identifier.otherWOS: 000346418900002
dc.identifier.otherScopus: 84916601054
dc.identifier.otherORCID: /0000-0002-9690-2839/work/60427255
dc.identifier.urihttp://hdl.handle.net/10023/5878
dc.descriptionThe authors acknowledge the support of the MASTS pooling initiative (The Marine Alliance for Science and Technology for Scotland) in the completion of this study (grant reference HR09011).en
dc.description.abstractIn assessing impacts of a changing environment on the structure and functioning of marine ecosystems, the challenge remains to distinguish the effects of noise and of temporal and spatial autocorrelation from environmental drivers of biotic change. One analytical approach is to de-trend the data and use the resulting residuals; an alternative method involves use of the raw anomalies and a reduction of the degrees of freedom (df) to make the hypothesis testing more conservative. Here, we assess the comparability of 3 gridded sea surface temperature (SST) datasets—ERSST V3b, HadISST, and OISST V2—to in situ measurements. The 1° gridded HadISST and OISST V2 showed the highest similarity, while the weaker correlations with ERSST V3b probably are attributable to its coarser 2° grid. We investigated the performance of 2 commonly applied statistical methods to resolving autocorrelation, and proceeded to correlation analyses between the SST datasets and 2 contemporaneous 15 yr time-series of the somatic growth condition of annual cohorts of Atlantic salmon Salmo salar, which migrate to the Norwegian Sea. For these latter analyses, reducing df could not fully resolve the problem of high positive autocorrelation. The 3 oceanographic datasets do not provide the same correlative outcomes and levels of significance with the salmon time-series. When analysing time-series that pre-date the availability of satellite data, the choice of dataset is restricted to either ERSST V3b or HadISST; but for recent studies (1982 onwards) OISST V2 also is available, and it will be important to assess the relative merits of the 3 SST data sources when interpreting contrasting correlative outcomes.
dc.format.extent16
dc.language.isoeng
dc.relation.ispartofMarine Ecology Progress Seriesen
dc.rights© The authors 2014. Open Access under Creative Commons by Attribution Licence. Use, distribution and reproduction are unrestricted. Authors and original publication must be credited.en
dc.subjectOceanographyen
dc.subjectSalmonen
dc.subjectSea surface temperatureen
dc.subjectAutocorrelationen
dc.subjectTime-seriesen
dc.subjectQH301 Biologyen
dc.subject.lccQH301en
dc.titleA comparison of gridded sea surface temperature datasets for marine ecosystem studiesen
dc.typeJournal articleen
dc.description.versionPublisher PDFen
dc.contributor.institutionUniversity of St Andrews.School of Biologyen
dc.contributor.institutionUniversity of St Andrews.Sea Mammal Research Uniten
dc.contributor.institutionUniversity of St Andrews.Marine Alliance for Science & Technology Scotlanden
dc.contributor.institutionUniversity of St Andrews.Scottish Oceans Instituteen
dc.identifier.doihttps://doi.org/10.3354/meps11023
dc.description.statusPeer revieweden
dc.identifier.urlhttp://www.int-res.com/abstracts/meps/v516/p7-22/en


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