DOI: 10.5061/dryad.08kprr5bp
title: Biomonitoring planktonic threats to salmon aquaculture: morphological and eDNA metabarcoding data

description: Salmonid aquaculture, a major component of the Northern European, North
 American, and Chilean coastal economies, is under threat from challenges
 to gill health, many of which originate from plankton communities. A first
 step towards mitigating losses is to characterize the biological drivers
 of poor gill health. Numerous planktonic taxa have been implicated,
 including toxic and siliceous microalgae, hydrozoans, and scyphozoans;
 however, rigorous longitudinal surveys of plankton diversity and gill
 health have been lacking. In the current study, we present and assess an
 exhaustive identification approach combining both morphological and
 molecular methods together with robust statistical models to identify the
 planktonic drivers of proliferative gill disease (PGD) and fish mortality.
 We undertook longitudinal evaluation at two marine aquaculture facilities
 on the west coast of Scotland using daily data collected during the 2021
 growing season (March-October). Examining these two different sites, ­one
 sheltered and one exposed­ to the open sea, we identified potentially new,
 important, and unexpected planktonic drivers of PGD and mortality (e.g.,
 doliolids and appendicularians) and confirmed the significance of some
 established threats (e.g., hydrozoans and diatoms). We also explored
 delayed or ‘lagged’ effects of plankton abundances on gill health and
 undertook a comparison of environmental DNA (eDNA) metabarcoding and
 microscopy in their ability to identify and quantify planktonic species.
 Our data highlight the diversity of planktonic threats to salmonid
 aquaculture as well as the importance of using both molecular and
 morphological approaches to detect those. There is now an urgent need to
 expand systematic longitudinal molecular and morphological approaches
 across multiple sites and over multiple years. The resultant catalogue of
 main biological drivers will enable early warning systems, new treatments,
 and, ultimately, a sustainable platform for future salmonid aquaculture in
 the marine environment.
description: # Biomonitoring planktonic threats to salmon aquaculture: morphological
 and eDNA metabarcoding data
 [https://doi.org/10.5061/dryad.08kprr5bp](https://doi.org/10.5061/dryad.08kprr5bp) ## Description of the data and file structure Between March and October 2021, we monitored two sites on the NW coast of Scotland, UK: a sheltered site with a large freshwater input was monitored for 223 sampling days, whilst an exposed open water site provided us with 191 sampling days. This daily monitoring included phytoplankton and zooplankton surveys, as well as eDNA sampling. Moreover, matching our sampling period, our collaborators in the farms provided mortality data (interpolated z-score data), PGD and AGD scores (scaled from one to five for increasing severance, see Noguera & Marcos Lopez, 2019 for details), environmental data related to temperature, oxygen levels, salinity, and visibility in the water adjacent to the cages, and treatments applied to fish during our study. ### Files and variables #### File: Salmon\_Code\_For\_Submission\_Anonymised.Rmd **Description:** Best plankton predictors for diminished salmon health: data analysis, models, and figures. #### File: all\_non\_interpolated\_data\_January\_2024.csv **Description:** Daily monitoring in two salmon aquaculture sites, including phytoplankton and zooplankton surveys, as well as eDNA sampling. Other salmon health (mortality data, PGD, and AGD scores) and environmental data (temperature, oxygen levels, salinity, and visibility in the water adjacent to the cages), and treatments applied to fish during our study were provided by our collaborators in the farms and also added to this dataset. ##### Variables * Date: March to October 2021 * Exposure: sheltered/exposed site * Temperature: °C * Oxygen: mg/L * Salinity: ppm * Clarity: m * AGD.Score: Amoebic Gill Disease, scaled from one to five for increasing severance * PGD.Score: Proliferative Gill Disease, scaled from one to five for increasing severance * Mortality: interpolated z-score data * Phytoplankton abundance: cells per liter * Zooplankton abundance: individuals per m^3 * OTUs: The eDNA metabarcoding approach assigned 9577 OTUs. Upon aggregation of OTUs at the genus level and exclusion of non-relevant taxa (e.g. mammal, fish, amphibian, and avian DNA), the total number of plankton genera was 447. ##### Missing values: N/A ## Code/software For the purposes of statistical modelling, we transformed our eDNA metabarcoding data to compositional data using the R package “compositions” v.2.0-8 and the function “acomp” (van den Boogaart & Tolosana-Delgado, 2008). For multivariate analysis of microscopy and eDNA metabarcoding species data, we determined between-sample similarities using Jaccard’s distance and visualized these with multidimensional scaling ordination using the “vegan” R package v.2.6-4 (Oksanen et al., 2022). For modelling purposes, data gaps along the timeline were filled, separately within each site, using linear interpolation with the function na.approx and the R package zoo v1.8-12 (Zeileis & Grothendieck, 2005).  To test the individual effect of each species on PGD or mortality, after accounting for temperature, oxygen, and the other species present, we used the *glmm.hp *R package v.0.1.2 (Lai et al., 2022). The lagging of data was performed on the fish condition data using the package lubridate v.1.9.3 (Grolemund & Wickham, 2011) and subsequently, this lagged dataset was merged with the non-lagged species-abundance dataset. All analysis was carried out in R v.4.3.1. (R Core Team, 2022).