DOI: 10.5061/dryad.vmcvdnd2b
title: Using complementary biomarkers to unravel fish lifetime exposure to hypoxia and mercury

description: Aquatic ecosystems are losing oxygen due to climate change. This
 deoxygenation can favor microbial methylation of mercury (Hg). To
 understand the dynamics of Hg under increasing deoxygenation, we
 simultaneously quantified both Hg and hypoxia (&lt; 2 mg O2/L)
 lifetime chronologies in fishes. We used a novel combination of chemical
 biomarkers in ear stones and eye lenses of benthic Round Goby (Neogobius
 melanostomus) and semi-demersal Yellow Perch (Perca flavescens) from the
 Central Basin of Lake Erie and contrasted it with the less hypoxic but
 more polluted Western Basin. Overall, Central Basin Round Goby were
 exposed to hypoxia throughout their lifetime and exhibited significantly
 elevated eye lens Hg concentrations ([Hg]) compared to their Western Basin
 counterparts. In contrast, the Central Basin Yellow Perch were exposed to
 hypoxia only at their juvenile stage. Central Basin Yellow Perch exhibited
 significantly lower eye lens [Hg] compared to their Western Basin
 counterparts. Patterns revealed by eye lens [Hg] were not detectable in
 muscle tissue [Hg]. Findings show that exposure to hypoxia can alter fish
 lifetime Hg accumulation patterns, with species-specific outcomes.
description: # Using complementary biomarkers to unravel fish lifetime exposure to
 hypoxia and mercury **Authors:** Hadis Miraly1,*, N. Roxanna Razavi1,*,
 Richard T. Kraus2, Ann Marie Gorman3, Elizabeth Duskey4, Matthew
 Altenritter5,†, and Karin E. Limburg1,6,* **Affiliations**: 1State
 University of New York College of Environmental Science and Forestry,
 Syracuse, New York, United States 2U.S. Geological Survey, Great Lakes
 Science Center, Lake Erie Biological Station, Ohio, United States
 3Fairport Fish Research Station, Ohio Department of Natural Resources,
 Fairport Harbor, Ohio, United States 4 Oklahoma State University,
 Department of Natural Resource Ecology and Management, Stillwater,
 Oklahoma, United States 5Department of Environmental Science and Ecology,
 State University of New York at Brockport, Brockport, New York, United
 States, †Deceased 6Department of Aquatic Resources, Swedish University of
 Agricultural Sciences, Uppsala, Sweden *Corresponding authors: Hadis
 Miraly ([hmiraly@esf.edu](mailto:hmiraly@syr.edu)); N. Roxanna Razavi
 ([razavi@esf.edu](mailto:razavi@esf.edu)); Karin Limburg
 ([klimburg@esf.edu](mailto:klimburg@esf.edu)) Access this dataset on
 Dryad: doi:10.5061/dryad.vmcvdnd2b **Description of the data and files
 structure:**  **Eye lens and otolith analyses** The data file named
 **“Compiled lens-otolith data.csv”** contains otolith Mn:Mg and eye lens
 Hg data for both **Round Goby** and **Yellow Perch**. **Compiled
 lens-otolith data.csv:** | Column name | Description | Abbreviation | Unit
 | Missing values | | ----------- |
 ------------------------------------------------------------------ |
 ---------------------------------------------------------------- |
 ------------------------------- |
 ---------------------------------------------------------------------------------------------------------------------------------------------- | | System | Aquatic ecosystem | LE = Lake Erie | - | | | Site | Sampling location | CB = Central Basin of Lake Erie, WE = Western Basin of Lake Erie | - | | | Species | Fish species | - | - | | | Fish ID | Lab fish ID | RG = Round Goby, YP = Yellow Perch | - | | | Age | Fish age | - | - | | | Lens Hg | Concentration of mercury in fish eye lenses | Hg = mercury | nanogram per gram of dry weight | "NA" indicates no eye lens chemistry data were available for that fish in the specified age group because it was not categorized in that group | | Mn/Mg | Otolith chemistry: manganese concentration/magnesium concentration | Mn = manganese, Mg = magnesium | - | "NA" indicates no otolith chemistry data were available for that fish in the specified age group because it was not categorized in that group | **Otolith Mn:Mg Analysis** To examine differences in otolith Mn:Mg across basins and among age groups for each individual fish (for both Round Goby and Yellow Perch), **linear mixed-effects regression models** were applied separately for each species. The R script used for this analysis is: **otolitheyelenses-RGYP.R** Visualization of the results can be found in **Figure 2** in the associated manuscript. The code used to generate Figure 2 is also located in **otolitheyelenses-RGYP.R**. **Eye Lens Hg Analysis** To analyze differences in eye lens Hg levels across basins and among age groups for each individual fish (for both Round Goby and Yellow Perch), **linear mixed-effects regression models** were again applied separately for each species. The R script used for this analysis is: **otolitheyelenses-RGYP.R** Visualization of the results can be found in **Figure 3** in the manuscript. The code used to generate Figure 3 is included in the same script. **Total Length, Age Differences, and Muscle Tissue [Hg] Analyses** **Length and Age Distribution** A **one-way ANOVA** was used to test for differences in total length between basins for each species. A **Chi-Square (χ²)** test was conducted to evaluate whether the distribution of individuals across age groups differed between basins, by species. **Muscle Tissue [Hg] Analysis** **To assess variation in muscle tissue [Hg] concentrations:** A **two-way ANOVA** was performed for each species to test for the effects of age and basin on muscle tissue [Hg]. The data file used: “**MuscleHgTL.csv**” The corresponding R script: **MuscleHg and TL.R** **Conversion of Whole-Body [Hg] to Muscle Tissue [Hg] (Round Goby)** For Round Goby, small individuals (n = 41 of 74 total) were analyzed as whole-body samples for Hg. To ensure consistency with Yellow Perch data (which was based on muscle tissue [Hg]), a linear regression model was used to convert whole-body [Hg] to muscle tissue [Hg]. This model was developed using individuals for which both muscle and whole-body Hg concentrations were available. The data file used: “**MuscleHgTL.csv**” The corresponding R script: **MuscleHg and TL.R** Visualization of the results can be found in **Figure S1** in the supplementary information. **MuscleHgTL.csv:** | Column name | Description | abbreviation | Unit | | :---------- | :--------------------------------------------- | :-------------------------------------------------------------- | :------------------------------- | | Sample ID | Lab fish ID | RG = Round Goby,YP = Yellow Perch | - | | Age | Fish Age | \*\* \*\* | - | | Species | Fish species | \*\* \*\* | - | | Site | Sampling location | CB = Central Basin of Lake Erie,WE = Western Basin of Lake Erie | - | | Muscle Hg | Concentration of mercury in fish muscle tissue | Hg = mercury | nano gram per gram of dry weight | | TL | Total Length of fish | TL = Total length | mm | **RGwhole_tomusclehg.csv** System: Refers to the aquatic ecosystem sampled. In this case, "LE" stands for Lake Erie. Site: Indicates the specific region within the system. "WB" represents the Western Basin of Lake Erie. ID: Unique identifier assigned to each individual fish. For example, "RGWB-01" may stand for Round Goby from the Western Basin. Age: The age of the fish in years. Whole body Hg: The concentration of mercury in the whole body of the fish, typically measured in nanograms per gram (ng/g) dry weight. Muscle Hg: The concentration of mercury in the muscle tissue of the fish, also likely in ng/g dry weight. Some values are missing (cells are blank), which indicate that muscle Hg was not measured Relationship Between Otolith Hypoxia Proxy and Eye Lens Hg Exposure **Exceedance of Hypoxia and Mercury Exposure Thresholds** To estimate the probability that each fish experienced **high hypoxia exposure** during its lifetime, we first established **species-specific thresholds** for both otolith Mn:Mg (as a hypoxia proxy) and eye lens Hg concentrations. **Threshold Calculation** For each species, a **K-median clustering analysis** was applied to partition Mn:Mg values along each fish’s lasered otolith transect into two distinct clusters: One representing **high hypoxia exposure** One representing **low hypoxia exposure** The **K-median method** was chosen for its robustness to outliers, and the threshold was defined as the **mean of the two cluster centroids**. All data were **centered and scaled** prior to clustering. **Bootstrapping with 500 iterations** (Leisch 2006) was used to assess the **stability** of the clustering results. A **similar K-median clustering approach** was used to define species-specific thresholds for **eye lens Hg** concentrations. The stability of both clustering procedures was confirmed using the **mean adjusted Rand index**, yielding values of **0.93 for Hg** and **0.82 for Mn:Mg** (Hubert and Arabie 1985). **Round Goby workflow** **Step 1: Data Preparation** * Reorganized the dataset, added basin information and normalized distances * Generated **.txt files** (**eyelens_goby.txt and otolith_goby.txt** ) for both otolith and eye lens data using **goby_data.R** * Data files used: “**goby_all.xlsx” and** “goby_id.csv” * R script: “**goby_data.R**” **Step 2: Threshold and Probability Calculation** * Calculated hypoxia and Hg thresholds * Computed the conditional probability that each fish experienced high hypoxia exposure * R script: **“goby_Hypoxia-Hg.R"** **Yellow perch workflow** **Step 1: Data Preparation** * Reorganized the dataset, added basin information and normalized distances * Generated .txt files (**eyelens_perch.txt and otolith_perch.txt**) for both otolith and eye lens data using “**perch_data.R**” eyelens_goby, eyelens_perch and otolith_goby, otolith_perch txt files * **Distance**: Distance from a reference point, likely the core of the otolith or lens (in micrometers or arbitrary units). * **MnCa**: Ratio of Manganese to Calcium; a chemical signature used for environmental or physiological analysis (present only in **eyelens** files). * **MnMg**: Ratio of Manganese to Magnesium; another geochemical marker. * **Age**: Estimated age * **ID**: Sample or specimen identifier. * **Basin**: Basin code or name where the specimen was collected (e.g., "WB" for White Basin, "CB" for Clear Basin). * **Dnorm**: Normalized distance; the distance value scaled between 0 and 1. * **MnMg_scale**: Scaled MnMg ratio, likely standardized for analysis (e.g., z-score or centered). - Data files used: “**perch_all.xlsx” and** “perch_id.csv” - R script: “**perch_data.R**” **Step 2: Threshold and Probability Calculation** * Calculated hypoxia and Hg thresholds * Computed the conditional probability that each fish experienced high hypoxia exposure * R script: **“perch_Hypoxia-Hg.R”** **goby_all.xlsx and perch_all.xlsx:** | Column name | Description | abbreviation | Unit | | :------------------------------ | :----------------------------------------------------------------- | :------------------------------------------------------ | :------------------------------- | | Otolith distance from core, um | Otolith laser-transect distance within elemntal profile |   | micrometer | | Mn/Mg | Otolith chemistry: manganese concentration/magnesium concertation  | Mn = manganese,Mg = magnesium | - | | Age | Fish Age\_ on otolith |   | - | | Eye lens distance from core, um | Eye lens laser-transect distance within mercury profile |   | micrometer | | Eye lens Hg ng/g dw | Concentration of mercury in fish eye lenses | Hg = mercury,ng/g dw = nano gram per gram of dry weight | nano gram per gram of dry weight | | Age | Fish Ag\_ on eye lens |   | - | **goby_id.csv and perch_id.csv:** | Column name | Description | abbreviation | Unit | | :---------- | :-------------- | :-------------------------------- | :--- | | Index | numerical order | - | - | | ID | Fish lab ID | RG = Round Goby,YP = Yellow Perch | - |  **R packages** ggplot2 ggpubr tidyr dplyr gridExtra lme4 lmerTest tidyverse emmeans ggplot2 ggpubr ggridges tibble patchwork scales flexclust **References:** Hubert, L. & Arabie, P. (1985). Comparing partitions. *Journal of Classification*, 2, 193-218. 10.1007/BF01908075 Leisch, F. (2006). A toolbox for K-centroids cluster analysis. *Computational Statistics & Data Analysis*, 51, 526-544. [10.1016/j.csda.2005.10.006](http://dx.doi.org/10.1016/j.csda.2005.10.006)