DOI: 10.5061/dryad.905qfttsz
title: Seagrass ecosystems reduce disease risk and economic loss in marine farming production

description: 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. 
description: 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
 <em>SI Appendix</em>.
description: # Seagrass ecosystems reduce disease risk and economic loss in marine
 farming production
 [https://doi.org/10.5061/dryad.905qfttsz](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](https://www.iucnredlist.org/resources/spatial-data-download) -EEZ boundaries: File obtainable from [https://www.marineregions.org/downloads.php](https://www.marineregions.org/downloads.php) -Phosphorus concentration in the ocean: File obtainable from [https://www.nodc.noaa.gov/OC5/woa13/woa13data.html](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](https://www.nodc.noaa.gov/OC5/woa13/woa13data.html) -Red Algae production: File obtainable from [www.fao.org/fishery/statistics/software/fishstatj/en](http://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.