Data and code from: Active restoration of a long-lived octocoral drives rapid functional recovery in a temperate reef
Data files
Feb 14, 2025 version files 500.78 KB
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README.md
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RedCoral.zip
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Abstract
Whether restoration actions achieve full ecological recovery is still debated. This is particularly controversial in the marine realm, where the success of restoration is mostly evaluated in terms of the short-term survival of transplanted organisms. In view of this, we combined population and trait-based approaches to explore the long-term effectiveness of active restoration of a key Mediterranean octocoral. For this purpose, an assemblage with restored Corallium rubrum colonies was monitored over ten years and compared with a nearby reference site. Our results revealed growth of the transplanted colonies followed by a change in the functional structure (i.e., dominance and diversity of traits) of the restored assemblage. Interestingly, this change was related not only to the development of the coral but also to the arrival and/or increase of species with different traits. Overall, our findings provide an example of how active restoration of long-lived octocorals can be an effective tool for recovering highly high-diverse coralligenous assemblages at decadal timescales.
https://doi.org/10.5061/dryad.j3tx95xrn
Description of the data and file structure
The dataset contains the data and code necessary to replicate the results of: Active restoration of a long-lived octocoral drives rapid functional recovery in a temperate reef.
The archived files include a RedCoral.ZIP that includes the R scripts and data to generate: Figures 1 to 5 from the main text, along with the supplementary materials (supplementary Figure S1 to S7, supplementary Table S1 to S3).
The archive is organised in 4 sub-directories: Data (contains the raw data files), Scripts (contains R Scripts to generate all results), PlottingAccesories (fonts and images necessary to plot the figures) and Output (empty placeholder for the results generated by the script). Each raw dataset with their variables and scripts is further detailed below.
Files and variables
./Data (contains raw data files needed to produce all statistics and figures that appear in the paper):
- “Community.csv” contains the coverage of the macrobenthic sessile species of the studied sites.
- Station: Local name of the sites
- Year: Monitored Year
- Photo_ID: File name of the analysed photos.
- Path: Location of the photos.
- SpeciesID: Species identification down to the lowest taxonomic level possible.
- Points: amount of points identified for each Species in each photo.
- Coverage: coverage of each Species at each photo.
- Total_Points: Total amount of Points identified per photo.
- Total_Coverage: Total amount of Coverage identified per photo.
- “Height.csv” contains the heights of the Corallium rubrum colonies. Note that Height can contain NAs, when the red coral colonies where positioned in an angle that it did no permit extract colony height through the photogrametric techniques.
- Species: Name of the measured species
- Site: Local name of the Sites
- Year: Monitored Year
- Photo_ID: File name of the analysed photos.
- Colony: ID per Photo of measured red coral colony
- Height: colony height in mm
- Epibiosi: % of surface with epibiosis
- Necrosi: % of surface with necrosis
- “Traits.csv” contains the coded values for the twelve traits of the detected species as detailed in supplementary Table S4
- “Library.csv” contains the categories for each species to group them in major taxonomic groups
Code/software
./Scripts (Contains the R code scripts used to produce the analyses and the figures):
- “Demographics.R” is used to analyze and plot the Corallium rubrum demographic traits (Figure 1 to 2 and Table S1)
- “Taxonomic.R” is used to explore the taxonomic coverage of the communities (Figure 3, STable S2 and SFigure S1)
- “FSpaceAndFRichness.R” is used to create the functional space and compute and plot the functional range, functional divergence and functional beta-diversity of the two communities. (Figure 4 and 5C:G, SFigure S2, S3 and S7,
- “FIdentity.R” should be used after “FSpaceAndFRichness.R” and is used to analyze and plot the functional identity of the two communities (Figure 5, SFigure S4, S5, S6, STable S3)
- “pairwise.adonis.R” auxiliary script to perform pairwise permanova on the position of the centroid within the functional space throughout time. Is called by FIdentity.R, does not need to be run.