This repository hosts the main BenthFun project documents. The fieldwork will be split into two campaigns 🤿 (i.e., spring 🍃 2023 and fall 🍂 2023) and the repository is organized into 3 folders as follows:
📁 Data is the folder where you might find the data needed to run the analysis 💻.
This folder is organized itself as follows:
- 0️⃣ Fieldwork documents to print – This sub-folder is used to store the lab and underwater documents to print 🖨.
- 1️⃣ Diving log – This sub-folder hosts the dates and hours of each dive 🤿. It is the cornerstone for each script written.
- 2️⃣ Incubations – This sub-folder contains the 3 main experiments folders 🧪. Each of them contains O2 and light ☀️ data organized by incubation day. The three main experiments are: a) Transplants, b) Historic and c) PI Curves. More information will be added on this later.
- 3️⃣ Alkalinity – This sub-folder has been used to determine the total alkalinity of each sample 👩🔬.
- 4️⃣ Visual census – this last sub-folder contains information about tile biodiversity and cover 🌱, an xlsx file to convert cover to biomass regarding the species observed and a masterclass led by Nuria Teixido and Antonia Chiarore in order to ID benthic species.
📁 Outputs hosts the main outputs for further analyses.
You might find the main figures 📊, summary and intermediate tables 📋 defined from analyses to generate summaries and figures.
📁 R_Script hosts the scripts used for the current analyses 💻.
Several scripts have been written so far:
Respiration & Photosynthesis
Quality_Check_O2_Sensorsis the first script to use. It allows us to check the O2 data quality from each incubation and to extract intermediate tables in the Outputs folder 📋.MiniDotswill be used then to summarize O2 data for each experiment 🧪 (e.g., Transplants at T0, Transplants at T1).
Calcification
Titration_alkalinityis used to define the total alkalinity (TA) from the lab titrations 👩🔬.Alkalinityis used to convert TA to calcification or dissolution rates 🐚.
Light influence
PI_Photois used to look at the PAR profile during the PI curve experiment ☀️.PAR_Profilesis used to define the PI curves and to visualise them 📈.
Viz
Vizwill be used to load each script and to provide the figures 📊
⚠️ You can also find important documents in Google Drive OR pCloud
System informations
R version 4.2.1 (2022-06-23)
Platform: x86_64-apple-darwin17.0 (64-bit)
Running under: macOS Monterey 12.2.1
Matrix products: default
LAPACK: /Library/Frameworks/R.framework/Versions/4.2/Resources/lib/libRlapack.dylib
locale:
[1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
attached base packages:
[1] stats graphics grDevices utils datasets methods base
other attached packages:
[1] readxl_1.4.2 patchwork_1.1.2 lubridate_1.9.2 forcats_1.0.0 stringr_1.5.0
[6] dplyr_1.1.0 purrr_1.0.1 readr_2.1.4 tidyr_1.3.0 tibble_3.2.0
[11] ggplot2_3.4.1 tidyverse_2.0.0
Main collaborators: Samir Alliouane, Jordi Boada, Jérémy Carlot, Antonia Chiarore, Steeve Comeau, Jean-Pierre Gattuso, Alice Mirasole, Melissa Palmisciano, Nuria Teixido