Data and Model from the Novel Forests of Singapore
================

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# About

Welcome to the `R` package `novelforestSG`! It contains the raw forest
community data used in Lai et al. (2021) and Neo et al. (2017).

In addition, it provides a `download_model()` function to download the
`brms` model fitted in Lai et al. (2021). This model object also
contains input data that include the environmental/landscape variables
of the 97 forest plots analysed by Lai et al. (2021). However, this does
not include three plots in Neo et al. (2017) that had no woody stems.
Environmental/landscape variables for all 100 plots, and more variables
such as canopy cover and litter depth are now available.

# Installation

From CRAN:

    install.packages("novelforestSG")

Or install the development version (especially if the devel version \>
CRAN version as stated above):

    install.packages("remotes")  # prerequisite
    remotes::install_github("hrlai/novelforestSG")

# Using the data

To access the raw data:

    library(novelforestSG)
    lapply(novelforest_data, head)

For more information, see `?novelforest_data`.

To access the summarised data and environmental variables used in the
Lai et al. (2021) analysis, first download the model object. The model
object is too large (16.5 MB) to come with the package, but the
`download_model` function will download the model from our [GitHub
development website](https://github.com/hrlai/novelforestSG):

    mod <- download_model()

Then, extract the input data from the model object:

    in_dat <- mod$data

In the input/summarised data, you will find the environmental variables
as certain columns. These plot-level measurements can be matched to the
stem-level raw data via plot names. See `?download_model` for more
details. Note that the predictor variables were log-transformed and then
scale to zero mean and unit SD prior to modelling.

# Dependencies

Because we analysed the data using the `brms` v2.10.0 package in `R`, it
is highly recommended that you [install
`brms`](https://github.com/paul-buerkner/brms) to squeeze the most out
of the model output:

    install.packages("brms")

You may also need `RTools` or `Xcode`, depending on your operating
system; see [the `brms`
homepage](https://github.com/paul-buerkner/brms#user-content-how-do-i-install-brms).
This will take a few minutes so have a cup of hot beverage handy.

# Issues

Please feel free to report any issues to [our GitHub Issue
page](https://github.com/hrlai/novelforestSG/issues).

# Erratum

While releasing additional data between v1.2.1 to v2.0.0, we realised
that some observations were removed by mistake in the original dataset
used in Lai et al. (2021). These omitted data are now included in
\>v2.0.0. We repeated the analysis using the corrected data in v2.0.0
and obtained extremely similar findings as reported Lai et al. (2021),
which is reassuring! Please feel free to contact us if you have any
concern.

# Citation

We believe that the sharing of datasets is important for advancing
ecology. When you use the data or model output in your original research
or meta-analysis, we appreciate if the following papers are cited.

If you use the trees data:

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

If you use the presence–absence data of all vascular plants, or the
environmental/landscape variables:

> Neo, L., Yee, A. T. K., Chong, K. Y., Kee, C. Y., & Tan, H. T. W.
> (2017). Vascular plant species richness and composition in two types
> of post-cultivation tropical secondary forest. *Applied Vegetation
> Science*, 20(4), 692–701. doi: 10.1111/avsc.12322

See the
[LICENSE](https://github.com/hrlai/novelforestSG/blob/master/LICENSE.md)
file for license rights.

# Contacts

Hao Ran Lai <hrlai.ecology@gmail.com>  
Kwek Yan Chong <kwek@nus.edu.sg>  
Alex Thiam Koon Yee <alex_yee@nparks.gov.sg>
