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dc.contributor.authorHill, Timothy
dc.contributor.authorChocholek, Melanie
dc.contributor.authorClement, Robert
dc.date.accessioned2019-03-19T13:30:14Z
dc.date.available2019-03-19T13:30:14Z
dc.date.issued2017-06
dc.identifier258117246
dc.identifiere8924e23-3561-4e5d-8a96-08c06aa3ffac
dc.identifier000400445900003
dc.identifier85018434862
dc.identifier000400445900003
dc.identifier.citationHill , T , Chocholek , M & Clement , R 2017 , ' The case for increasing the statistical power of eddy covariance ecosystem studies : why, where and how? ' , Global Change Biology , vol. 23 , no. 6 , pp. 2154-2165 . https://doi.org/10.1111/gcb.13547en
dc.identifier.issn1354-1013
dc.identifier.urihttps://hdl.handle.net/10023/17313
dc.descriptionWe acknowledge the support of the Natural Environment Research Council funded projects: CBESS (Coastal Biodiversity and Ecosystem Service Sustainability: NE/J015644/1) and GREENHOUSE (Generating Regional Emissions Estimates with a Novel Hierarchy of Observations and Upscaled Simulation Experiments: NE/K002619/1).en
dc.description.abstractEddy covariance (EC) continues to provide invaluable insights into the dynamics of Earth's surface processes. However, despite its many strengths, spatial replication of EC at the ecosystem scale is rare. High equipment costs are likely to be partially responsible. This contributes to the low sampling, and even lower replication, of ecoregions in Africa, Oceania (excluding Australia) and South America. The level of replication matters as it directly affects statistical power. While the ergodicity of turbulence and temporal replication allow an EC tower to provide statistically robust flux estimates for its footprint, these principles do not extend to larger ecosystem scales. Despite the challenge of spatially replicating EC, it is clearly of interest to be able to use EC to provide statistically robust flux estimates for larger areas. We ask: How much spatial replication of EC is required for statistical confidence in our flux estimates of an ecosystem? We provide the reader with tools to estimate the number of EC towers needed to achieve a given statistical power. We show that for a typical ecosystem, around four EC towers are needed to have 95% statistical confidence that the annual flux of an ecosystem is nonzero. Furthermore, if the true flux is small relative to instrument noise and spatial variability, the number of towers needed can rise dramatically. We discuss approaches for improving statistical power and describe one solution: an inexpensive EC system that could help by making spatial replication more affordable. However, we note that diverting limited resources from other key measurements in order to allow spatial replication may not be optimal, and a balance needs to be struck. While individual EC towers are well suited to providing fluxes from the flux footprint, we emphasize that spatial replication is essential for statistically robust fluxes if a wider ecosystem is being studied.
dc.format.extent12
dc.format.extent844131
dc.language.isoeng
dc.relation.ispartofGlobal Change Biologyen
dc.subjectCarbonen
dc.subjectCarbon dioxideen
dc.subjectCO2en
dc.subjectEddy covarianceen
dc.subjectEffect sizeen
dc.subjectFluxen
dc.subjectLatenten
dc.subjectReplicationen
dc.subjectSensibleen
dc.subjectSignificanten
dc.subjectQH301 Biologyen
dc.subjectNDASen
dc.subject.lccQH301en
dc.titleThe case for increasing the statistical power of eddy covariance ecosystem studies : why, where and how?en
dc.typeJournal articleen
dc.contributor.sponsorNERCen
dc.contributor.sponsorNERCen
dc.contributor.institutionUniversity of St Andrews. School of Earth & Environmental Sciencesen
dc.identifier.doi10.1111/gcb.13547
dc.description.statusPeer revieweden
dc.identifier.grantnumberNE/J015644/1en
dc.identifier.grantnumberNE/J015644/1en


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