Seagrass ecosystems reduce disease risk and economic loss in marine farming production
Data files
Nov 26, 2024 version files 15.36 KB
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Combined_Disease_and_Environment_Dataset.csv
8.29 KB
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README.md
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Abstract
Seaweed farming comprises over half of global coastal and marine aquaculture production by mass, however the future of the industry is increasingly threatened by disease outbreaks. Nature-based solutions provided by enhancing functions of coinciding species or ecosystems offer an opportunity to increase yields by reducing disease outbreaks while conserving biodiversity. Seagrass ecosystems can reduce the abundance of marine bacterial pathogens, although it remains unknown whether this service can extend to reducing disease risk in a marine resource. Using a meta-analysis of articles published over the past 40 years, we find that 17 known diseases of seaweeds are associated with bacteria that have been previously shown to be lower when associated with seagrass ecosystems. Next, we surveyed over 8,000 individual seaweeds among farms in Indonesia and found disease risk is reduced by 75% when seaweeds are co-cultivated directly within seagrass ecosystems, compared to when seagrass ecosystems were removed. Finally, we estimate that farming seaweed with seagrass ecosystems could increase annual revenue by $292,470 – $1,015,990 USD per km2 from yield loss due to disease reduction, and that ~20.7 million km2 in 107 countries and 34 territories have suitable environmental conditions for farming seaweeds with seagrass ecosystems. These results highlight the global utility for nature-based solutions as an ecologically and economically sustainable management strategy.
https://doi.org/10.5061/dryad.905qfttsz
This dataset contains the required information to determine the influence of seagrasses on diseases of the seaweed, Kappaphycus sp., associated environmental drivers, global cultivation area, and potential economic benefit of seagrass-seaweed co-culture. The main data file, Combined Disease and Environment Dataset.csv, is a result of seaweed disease surveys conducted on farms in Indonesia that did and didn't remove seagrass from cultivation areas. Other files are based on existing literature and methodology to determine potentail co-cultivation area and economic consequences.
Description of the data and file structure
Files:
Combined Disease and Environment Dataset.csv - contains disease and environmental parameters from surveys conducted on seaweeds growing in Indonesian farms. All environmental parameters were collected through an EXO Multiparameter Sonde Data included:
Site: Numeric Representation of site ID
Regency: Broad Area of Farm
Date: Date survey was conducted
Desa: Name of site
Dusun: Sub area of farm
Treatment: Whether the farm did or did not cultivate the seaweed with seagrass
Replicate: The line the seaweeds were grown on
Temp: Temperature, degrees celsius
TDS: Total Dissolved Solids, mg/L
Sal: Salinity, ppt
ODO: Dissolved Oxygen
pH: pH of seawater at the seaweed farming line
Turb: Tubidity, Formazin Nephelometric Units
Chlor: Chlorophyll concentration
BGA: Blue-green algae concentration
Enterococcus: Number of colony forming units of Entercoccus bacteria
Transect: The number of the transect
Transect.length.m: length of the transect in meters
Healthy: Count of seaweeds with no visible signs of disease
Disease: Count of seaweeds with signs of disease
Severe Disease: Count of seaweeds with substantial signs of disease
Total: total count of seaweeds
Prevalence: Percent of seaweeds with disease
Density: Number of seaweeds per meter on the line
Percent.cover: Percent cover of seaweeds; Empty cells represent locations where seagrass was absent
Species.1-5: Species of seagrasses present on each transect; Empty cells represent where species of seagrass was not found
ten_yr_mean.tif: Image file of global averaged Sea Surface Temperature used in calculating suitable seaweed cultivation area.
ten_yr_sd.tif: Image file of global standard deviation of Sea Surface Temperature used in calculating suitable seaweed cultivation area.
Sharing and access information
Data is derived from:
Froehlich, H. E., Afflerbach, J. C., Frazier, M., & Halpern, B. S. (2019). Blue growth potential to mitigate climate change through seaweed offsetting. Current Biology, 29(18), 3087-3093.
Links to other publicly accessible locations of the data:
- Seagrass locations - ICUN: File obtainable from https://www.iucnredlist.org/resources/spatial-data-download
-EEZ boundaries: File obtainable from https://www.marineregions.org/downloads.php
-Phosphorus concentration in the ocean: File obtainable from https://www.nodc.noaa.gov/OC5/woa13/woa13data.html
-Nitrogen concentration in the ocean: File obtainable from https://www.nodc.noaa.gov/OC5/woa13/woa13data.html
-Red Algae production: File obtainable from www.fao.org/fishery/statistics/software/fishstatj/en and filtered for red algal production
Code and Software
Below are a description the scripts used for analysis and figure generation. All scripts were created in R version 4.4.0:
S1_Seaweed_Mariculture_Disease.r: Script to import and analyze disease prevalence of Kappaphycus seaweeds in Indonesia. Analyses include examining differences in disease prevalence between farms with and without seagrass and how disease prevalence is related to environmental parameters.
S2_Seaweed_Aquaculture_Map.r: Using methodology based on Froehlich et al 2019 Blue Growth Potential to Mitigate Climate Change through Seaweed Offsetting, determine suitable cultivation area of Kappaphycus and find the intersect with Seagrass ranges.
S3_Seaweed_Coculture_Economics.r: Using estimates of density, loss, and farm gate prices of seaweeds, estimate the difference in revenue when accounting for the reduction in disease when seaweed is grown with seagrass.
S4_Seaweed Disease Metaanalysis.r: Calculate reporting statistics for meta-analyses based on PRISMA reporting.
Fieldwork was conducted at 16 seaweed farms along the southwest coast of Sulawesi in Indonesia, where seaweed is currently co-cultivated in coastal areas directly within intact seagrass ecosystems and where seagrass ecosystems naturally occur, but have been removed. The estimated economic value of disease risk reduction associated with the co-cultivation of seaweed with seagrass ecosystems and global geographic suitability is briefly described in each figure legend. Full materials and methods, including mechanisms of seagrass filtration can be found in the SI Appendix.
- Fiornza, Evan A.; Abu, Nur; Feeney, William E. et al. (2024). Seagrass ecosystems reduce disease risk and economic loss in marine farming production. Zenodo. https://doi.org/10.5281/zenodo.14183508
- Fiornza, Evan A.; Abu, Nur; Feeney, William E. et al. (2024). Seagrass ecosystems reduce disease risk and economic loss in marine farming production. Zenodo. https://doi.org/10.5281/zenodo.14183507
- Fiorenza, Evan A.; Abu, Nur; Feeney, William E. et al. (2024). Seagrass ecosystems reduce disease risk and economic loss in marine farming production. Proceedings of the National Academy of Sciences. https://doi.org/10.1073/pnas.2416012121