The goal of fishcom is to get all the informations concerning the ECOSTAB postdoc project in one place including reproducible code, notes, eventually data and manuscripts.
### Get the repository
You can clone the repository with git by pasting in your terminal:
git clone https://github.com/alaindanet/fishcom.git dir_name_to_be_created
OR
just download the repository: alaindanet/fishcom
If you have Rstudio installed on your
computer, just open fishcom.Rproj with Rstudio.
My notes are available in the introductory vignette
vignettes/intro.html
Raw datas are spreadsheets (xls, csv, etc…) shapefiles and others
cartographic data and reports (of the AFB, ONEMA, etc). The raw datas
come together with R scripts which describe cleaning procedures. The
cleaning procedures end by saving datasets used for data analysis.
It is located in data-raw.
The clean datasets live in data directory and stored in rda
compressed format. Once the package is loaded, they can be call as
easily as load(objet_name).
devtools::load_all()
#> Loading fishcom
data(metaweb_analysis)
names(metaweb_analysis)
#> [1] "metaweb" "species" "resource" "nb_class"
#> [5] "size_class" "piscivory_index" "th_prey_size"The cleaned and filtered objects used for data analysis are named with
the suffix _analysis.
The analysis of data lives in the directory named analysis.
This folder contains scripts in which various metrics are computed for two different aspects that have been more or less arbitrary separated.
The community data lives in the community_metrics and contains the
following metrics:
- species abondances
- species biomass
- species richness
The following metrics are summarised by station:
- mean and cv of species richness
- mean and cv of species biomass
- temporal beta-diversity
The network data lives in the network_analysis and contains the
following metrics:
- connectance
- number of nodes
- modularity and modules
- nestedness
- trophic length
The following metrics are summarised by station:
- mean and cv of all the above indices