Data from: A path towards appropriate degradation experiments for assessing carbon sequestration potential of macroalgae
Data files
Jul 04, 2025 version files 1.89 MB
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degradation_meta-main.zip
24.30 KB
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degredation_database_white_2025.xls
1.87 MB
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README.md
3.63 KB
Abstract
The biodiversity and climate crises have increased the urgency to understand turnover rates and drivers of marine carbon sequestration. Efforts have concentrated on measuring degradation of macroalgae, to quantify how much of their carbon might be sequestered. We systematically reviewed literature on macroalgal degradation, compiling 364 measurements of exponential decay constant k. To date, most degradation experiments (1) are carried out in aquaria or shallow environments, (2) span short timescales, (3) use dried or frozen material, or (4) rarely incorporate environmental gradients driving degradation. Decay constants were higher in intertidal vs. subtidal habitats, for pre-treated algal tissue compared to fresh, and when refractory material was present rather than absent. These patterns have implications for estimates of export efficiency of macroalgal carbon to the deep ocean. Synthesis: We recommend that future studies of macroalgal degradation (1) adopt standardized approaches, such as using fresh material and litter bag mesh size of 10mm, to make studies more comparative, (2) measure degradation with sufficient frequency to robustly estimate decay constants and/or refractory material, and (3) incorporate environmental gradients, including depth, light and oxygen availability, to improve estimates of macroalgal carbon remineralisation rates during transport to deeper water.
Dataset DOI: 10.5061/dryad.44j0zpcsb
Description of the data and file structure
49 variables were extracted from 71 peer reviewed studies, either directly from text and tables or from figures using metadigitise in R. This dataset is used to perform analyses and generate all output such as summaries and visualizations in the accompanying R scripts and manuscript.
The files representing the entry point for the data extraction process (figures and excel files from published papers) are not included here, due to potential copywright infringement.
The scripts used to extract data, however, are included for reference in R scripts 1-3, with a detailed description of the extraction process.
Files and variables
File: degredation_database_white_2025.xls
Description: This file has 5 sheets:
database - All the records found to be relevant for the study following systematic review of the literature, includes 71 peer reviewed studies and 49 variables extracted from each study
database_variables - Description of each of the variable listed within the database
search_terms - Search terms used in Web of Science (WOS)
WOS_savedrecs - List of records exported from WOS following literature search
final_records_following_review - List of relevant records included within the study following evaluation
Variables
- 49 different variables are explained and described in the database_variables sheet
File: degradation_meta-main.zip
Description: Scripts containing details on data extraction, data processing, model fitting, analysis and figures
Code/software
Data extraction, analysis, and figures were made using R (version 4.5.0).
The project contains 7 scripts located in the script directory in degradation_meta-main.zip :
1_dataextract_functions.R includes functions to fit single phase exponential decay curve models to each data set of biomass or carbon loss over time, separate functions fit models with and without a refractory term, and use a range of starting values or self-starting functions.
2_dataextract_k.R collates all published data on macroalgal degradation rates, explains how datasets were extracted from figures downloaded from published articles using metaDigitise and fits single phase exponential decay curve models to each dataset
3_dataextract_temperature.R collates published data on temperature, light and oxygen from degradation experiments when averages were not reported in the study
4_analysis_upsetplot.R synthesises data at the study and experiment level, summarising experiment duration, depth, sampling frequency, habitat etc and creates figure 3
5_analysis_k_exploration.R explores how degradation constant k varies with different biological, environmental and experimental variables
6_analysis_k_exploration_browns.R explores how degradation constant k of brown forest forming macroalgae varies with different biological, environmental and experimental variables, and sensitivity of carbon export models to k and created figure 4
7_supplementary_temperature_k_regressions.R explores how degradation constant k varies with temperature and latitude and creates figure S2 and S3 in supplementary info
Access information
Data was derived from the following sources:
- List of 71 published records included within the study following systematic evaluation are included in the data files, see sheet final_records_following_review
