download_model {novelforestSG}

Download Model Fitted to novelforest_data

Description

Download the brms model fitted to novelforest_data (Lai et al. 2021). The model object is too large (16.5 MB) to be included with the package, so this function downloads the model from the developmental GitHub website. The generalised linear mixed-effect model was fitted via brms::brm so this package is recommended to make full use of the model object.

Usage

download_model(save_to = NULL)

Arguments

save_to

Path and name of the file where the R object is saved to. Defaults to NULL, which does not save the model object locally.

Value

A brms model output of class brmsfit, which is a list containing the input data and other slots that store the model components.

Notably, the data slot contains a data.frame with the following response variables:

SD_N_0

first-order native taxonomic diversity, i.e., species richness

SD_N_2

second-order native taxonomic diversity, i.e., inverse Simpson index

SD_E_0

first-order exotic taxonomic diversity

SD_E_2

second-order exotic taxonomic diversity

FD_N_0

first-order native functional diversity

FD_N_2

second-order native functional diversity

FD_E_0

first-order exotic functional diversity

FD_E_2

second-order exotic functional diversity,

and the following explanatory variables (and measurement units if you backtransform them using backtransform):

dist

Distance to old-growth forests (m)

size

Patch area (km^2)

nitrogen

Total soil nitrogen (mg/kg)

phosphorous

Total extractable soil phosphorous (mg/kg)

potassium

Total extractable soil potassium (mg/kg)

patch

Forest patch ID

#' Note that all explanatory variables were log-transformed and standardised to zero mean and unit standard deviations. Use backtransform to obtain the variables in their original scales. See Lai et al. (2021) for more details on model building and data collection.

References

Lai, H.R., Tan, G.S.Y., Neo, L., Kee, C.Y., Yee, A.T.K., Tan, H.T.W. and Chong, K.Y. (2021) Decoupled responses of native and exotic tree diversities to distance from old-growth forest and soil phosphorous in novel secondary forests. Applied Vegetation Science, 24, e12548. doi:10.1111/avsc.12548

See Also

backtransform, brms::brmsfit, brms::brm

Examples

## Not run: 
novelforest_model <- download_model()

# library(brms)  # recommended
summary(novelforest_model)

# to obtain input data
novelforest_model$data

## End(Not run)