macrofDat

<p>This is a dataset containing a subset from the macrofauna recorded in the
PAPIIT experiment.</p>

datasets

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().

Arturo Sanchez-Porras

ecocbo

Calculating Optimum Sampling Effort in Community Ecology

Edlin Guerra-Castro

macrofDat function

<p>A dataframe with counts of individuals for 43 observations on 34 species.</p>

macrofDat: Dataset on species count of coastal macrofauna.

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