Peer Review #3 of "the Use of Pseudo-Multivariate Standard Error to Improve the Sampling Design of Coral Monitoring Programs (V0.1)"

The characteristics of coral reef sampling and monitoring are highly variable, with numbers of units and sampling effort varying from one study to another.Numerous works have been carried out to determine an appropriate effect size through statistical power, however, always from a univariate perspective.In this work, we aimed to assess the multivariate standard error of a series of reefs in Venezuela, sampled between 2017 and 2018, and also, to evaluate the consequences of using different combinations of points, quadrats, and transects over this error.For this, the multivariate standard error of 36 sites previously sampled was estimated, using four 30m-transects with 15 photo-quadrats each and 25 random points per quadrat.We obtained that the multivariate standard error was highly variable between sites and is not correlated with the univariate standard error nor with the richness of species.Then, a subset of sites were re-annotated using 100 uniformly distributed points, which allowed the simulation of different numbers of transects per site, quadrats per transect and points per quadrat using resampling techniques.The magnitude of the multivariate standard error stabilized by adding more transects, however, adding more quadrats or points does not improve the estimate.For this case study, when comparing between sampling with 10 transects, 10 quadrats per transect and 25 points per quadrat; and the original data for Venezuela, we find that the error is reduced by half.We recommend the use of multivariate standard error in reef monitoring programs, in particular when conducting pilot surveys to optimize the estimation of the community structure.