title: The case for increasing the statistical power of eddy covariance ecosystem studies: why, where and how?
abstract: Eddy 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.
authors: Department of Geography, Exeter University, Rennes Drive, Exeter, EX4 4RJ, UK.
authors: Timothy
authors: T
authors: Hill
authors: Department of Earth and Environmental Science, University of St Andrews, Irvine Building, North Street, St Andrews, KY16 9AL, UK.
authors: Melanie
authors: M
authors: Chocholek
authors: School of GeoSciences, The University of Edinburgh, Crew Building, Alexander Crum Brown Road, Edinburgh, EH9 3FF, UK.
authors: Robert
authors: R
authors: Clement
mesh_terms: D000349:Africa; D001315:Australia; D002245:Carbon Dioxide; D003627:Data Interpretation, Statistical; D017753:Ecosystem; D013020:South America
chemical_list: D002245:Carbon Dioxide
keywords: CO2; carbon; carbon dioxide; eddy covariance; effect size; flux; latent; replication; sensible; significant