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mvabund (version 4.2.1)

solberg: Solberg Data

Description

This dataset contains a list with abundance data of species and a factor variable.

Usage

data(solberg)

Arguments

Format

A list containing the elements

abund

a data frame containing 12 rows and has 53 variables, corresponding to the species. It has the following variables: Paramesacanthion_sp., Halalaimus_sp., Viscosia_sp., Symplocostoma_sp., Bathylaimus_inermis, Bathylaimus_sp., Rhabdodemania_sp., Pandolaimus_latilaimus, Halanonchus_sp. , Trefusia_sp., Chromadora_sp., Dichromadora_sp., Neochromadora_sp., Prochromadorella_sp., Neotonchus_sp., Marylynnia_complexa, Paracanthonchus_sp., Cyatholaimidae_un ., Choniolaimus_papillatus, Halichoanolaimus_dolichurus, Richtersia_inaequalis, Dorylaimopsis_punctatus, Sabatieria_longicaudata, Sabatieria_punctata, Sabatieria_sp., Setosabieria_hilarula, Chromaspirina_sp., Molgolaimus_sp., Spirinia_parasitifera, Aponema_torosa, Microlaimus_sp.1, Microlaimus_sp.2, Camacolaimus_sp., Leptolaimus_elegans, Monhystera_sp., Amphimonhystera_sp., Daptonema_sp.1, Daptonema_sp.2, Daptonema_sp.3, Theristus_aff_acer, Xyalidae_un., Sphaerolaimus_macrocirculus, Sphaerolaimus_paradoxus, Desmolaimus_sp., Eleutherolaimus_sp., Eumorpholaimus_sp., Terschellingia_longicaudata, Paralinhomoeus_conicaudatus, Linhomieidae_un.A, Linhomieidae_un.B, Axonolaimus_sp., Odontophora_sp., Unidentified

x

a factor with the levels control, high, low

Details

The abundance of each species was measured as the count of the number of organisms in the sample.

References

Gee J. M., Warwick R. M., Schaanning M., Berge J. A. and Ambrose W. G. Jr (1985) Effects of organic enrichment on meiofaunal abundance and community structure in sublittoral soft sediments. Journal of Experimental Marine Biology and Ecology. 91(3), 247-262.

Examples

Run this code
# NOT RUN {
data(solberg)
solbergdat <- mvabund( solberg$abund )
treatment <- solberg$x

## Create a formula for multivariate abundance data:
foo.sol <- mvformula( solbergdat ~ treatment )

## Fit a multivariate linear model:
lm.solberg <- manylm(foo.sol)
lm.solberg
# }

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