Revisit | R Documentation |
The data is from the revisit to the low-elevation, non-serpentine sites of
Robert Whittaker’s historic plant community study sites in the Siskiyou Mountains of Southwest Oregon
(Damschen, Harrison & Grace 2010).
Briefly, the data consists of the abundance of 75 species in 52 sites,
calculated from the number of 100 quadrat corners per site that each species intersected
(Miller et al. 2018, 2019).
The environmental variable and functional trait are standardized versions of
the original topographic moisture gradient (TMG) and the leaf carbon-to-nitrogen ratio (C:N),
respectively (Miller et al. 2019). The dataframe Revisit
has been derived from the
whittaker_revisit_data.csv file from Miller et al. (2018), who describe the variables as follows
site
study site ID (integer, one study plot per site)
species
name of species
trait
functional trait: leaf tissue carbon to nitrogen ratio
env
environmental variable: site position on the topographic moisture gradient (higher numbers are topographically drier sites)
value
plant abundance (see Description for details)
y
matrix with two columns with, as successes and failures, value and 100 - value, respectively.
Damschen, E.I., Harrison, S. & Grace, J.B. (2010) Climate change effects on an endemic-rich edaphic flora: resurveying Robert H. Whittaker's Siskiyou sites (Oregon, USA). Ecology, 91, 3609-3619. https://doi.org/10.1890/09-1057.1
Miller JED, Damschen EI, Ives AR (2018) Data from: Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models. Dryad Digital Repository. https://doi.org/10.5061/dryad.7gj0s3b
Miller JED, Damschen EI, Ives AR (2019) Functional traits and community composition: a comparison among community-weighted means, weighted correlations, and multilevel models. Methods in Ecology and Evolution. https://doi.org/10.1111/2041-210x.13119
ter Braak (2019) New robust weighted averaging- and model-based methods for assessing trait-environment relationships. Methods in Ecology and Evolution (https://doi.org/10.1111/2041-210X.13278)
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