ecocbo: Calculating Optimum Sampling Effort in Community Ecology (original) (raw)

A system for calculating the optimal sampling effort, based on the ideas of "Ecological cost-benefit optimization" as developed by A. Underwood (1997, ISBN 0 521 55696 1). Data is obtained from simulated ecological communities with prep_data() which formats and arranges the initial data, and then the optimization follows the following procedure of four functions: (1) prep_data() takes the original dataset and creates simulated sets that can be used as a basis for estimating statistical power and type II error. (2) sim_beta() is used to estimate the statistical power for the different sampling efforts specified by the user. (3) sim_cbo() calculates then the optimal sampling effort, based on the statistical power and the sampling costs. Additionally, (4) scompvar() calculates the variation components necessary for (5) Underwood_cbo() to calculate the optimal combination of number of sites and samples depending on either an economic budget or on a desired statistical accuracy. Lastly, (6) plot_power() helps the user visualize the results of sim_beta().

Version: 0.13.0
Depends: R (≥ 4.1.0)
Imports: ggplot2, ggpubr, sampling, stats, rlang, dplyr, tidyr, tidyselect, parabar, parallelly, vegan, SSP, plotly
Suggests: knitr, rmarkdown, testthat (≥ 3.0.0)
Published: 2025-08-23
DOI: 10.32614/CRAN.package.ecocbo
Author: Edlin Guerra-CastroORCID iD [aut, cph], Arturo Sanchez-PorrasORCID iD [aut, cre]
Maintainer: Arturo Sanchez-Porras <sp.arturo at gmail.com>
BugReports: https://github.com/arturoSP/ecocbo/issues
License: GPL (≥ 3)
URL: https://github.com/arturoSP/ecocbo
NeedsCompilation: no
Materials: README, NEWS
CRAN checks: ecocbo results

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