DOI: 10.5061/dryad.s4mw6m9j8
title: Data from: Body condition reveals hidden correlations between co-infection and behavior in sunfish

description: The role of parasites in maintaining consistent inter-individual
 differences in behavior (i.e., personality) is the subject of increasing
 study and debate. While behavioral differences may expose individuals
 differently to parasites, parasite infection can itself change host
 behavior, sometimes favoring the parasite’s own transmission. Furthermore,
 parasites can alter the functioning of energetically costly organs like
 the brain, thus affecting cognitive performance. However, relationships
 among infection, cognition, and behavior can be complex and difficult to
 interpret, especially in wild populations where individual health status
 is unknown. The inclusion of body condition as a fitness proxy may help
 reveal relationships between parasites and host traits that are otherwise
 masked. We examined relationships among host body condition, personality
 (i.e., exploration, boldness), cognition (i.e., aversive learning), and
 parasite density in wild-caught pumpkinseed sunfish (Lepomis gibbosus)
 naturally infected with endoparasites. We measured exploration (i.e,.
 surface explored in cm), boldness (i.e,. latency to emerge from shelter in
 seconds) and cognition (i.e. aversive learning; difference between trial 1
 and 2 in latency time to enter the black side). Exploration and boldness
 were measured twice (trial 1 and 2). Cognitive performance had one
 learning trial, and two test trials (24-hour delay between trials).
 Exploration in an open field test was repeatable in sunfish. Boldness,
 assessed using a shelter test, was not repeatable, but was correlated with
 exploration. Host exploration decreased with both increasing parasite
 density and decreasing body condition. Only individuals in relatively
 lower body condition displayed a negative relationship between parasite
 density and exploration, suggesting a pathologic effect of the parasites
 on the sunfish. Aversive learning was not influenced by co-infection. Our
 results show that body condition is important to consider when studying
 wild populations as some patterns observed between parasite density and
 host behavior were only revealed when body condition was taken into
 consideration.
description: # Data from: Body condition reveals hidden correlations between
 co-infection and behavior in sunfish Dataset DOI:
 [10.5061/dryad.s4mw6m9j8](10.5061/dryad.s4mw6m9j8) ## Description of the
 data and file structure We measured exploration (i.e. surface explored in
 cm for 10 minutes using an open-field test), boldness (i.e. latency to
 emergence from the shelter in seconds for a maximum of 300 seconds) and
 cognitive performance (i.e. difference between trial 1 and 2 in the
 latency to enter the black side) in wild pumpkinseed sunfish (*Lepomis
 gibbosus,* n = 65). We selected individuals from Lake Cromwell
 (Saint-Hippolyte, Canada) with a range of infection (i.e. blackspots,
 cestodes, yellow grub). We tested exploration and boldness for two trials
 and measured repeatability of these traits. We tested cognition using one
 learning trial, then two test trials. We measured body condition using
 the Fulton index (K) using the adjusted fish mass (i.e. fish mass -
 parasite mass) (mass/standard length3 in cm).  We had n = 21 fish that
 were accidentally defrosted, and thus, we only considered n = 65 to
 measure repeatability and correlations between traits, but n = 44 for
 models looking at the impact of parasites since we could not quantify
 parasite loads in defrosted fish.  We looked at the impact of co-infection
 (i.e. blackspots and internal parasite density) on these behavioral and
 cognitive traits). We included trial, body condition, an interaction
 between blackspot density and body condition, an interaction between
 internal parasite density and body condition and an interaction between
 both parasite densities in our models for exploration, boldness and
 cognition.  ### Files and variables **Data file
 "complete_final.csv"**: this datafile was used for our models
 looking at the impact of parasite infection on exploration and boldness.
 Each fish ID appears twice (trial 1 and trial 2). We also used this
 datafile to measure repeatability and correlation between traits, while
 accounting for trials as a random factor. | **VARIABLE** | **DESCRIPTION**
 | | :----------- |
 :--------------------------------------------------------------------------------------------------------- | | ID | Fish number | | ES | Test trial number (1 or 2) | | EX | Exploration trials, proportion of surface explored in 10 minutes | | BO | Boldness trials, latency to emerge from a shelter after being chased with a net. (max 300s) | | SUR | Boldness trials, binary variable. Whether the fish emerged (1) or not (0) from the shelter after 5 minutes | | L.B | Logarithm of BO | | BS | Density of blackspots (n/standard length in cm), scaled and centered | | FUL | Fulton index, scaled and entered | | OT | Density of internal parasites (n/standard length), scaled and centered | | log.d.INT | Logarithm of OT | | TOT | Total density of parasites (BS+OT), scaled and centered | | GR | Fish group (4 groups), 1 and 2 from July, 3 and 4 from September. | | MO | Month of testing (2 months, (1): July, (2): September) | | defrost  | Fish that were defrosted accidentally (1) (not used in analysis for internal parasite density) (n = 21) | | adj.M | Adjusted mass (g), total mass minus parasite mass | | INT\_num | Number of internal parasites | | BS\_num | Number of blackspots on the right side of the fish | | cog | Inhibitory avoidance learning, latency to go to the dark compartment on trial 2 | | anxi | Anxiety, proportion of time spend in the dark side for 5 minutes | 
 
 **Data file "complete2.csv"**: this datafile was used for our
 models looking at the impact of parasite infection on cognition. Each fish
 ID appears only once.  | **VARIABLE** | **DESCRIPTION** | |
 :--------------- |
 :--------------------------------------------------------------------------------------------------------------------------------------------------------------- | | ID | Fish number | | GR | Fish group (4 groups), 1 and 2 from July, 3 and 4 from September. | | ex.1 and ex.2 | Exploration trials (2 trials), percentage of surface explored in 10 minutes | | es1, es2, es3  | Inhibitory avoidance learning trials (3 trials), latency to go to the dark compartment | | lat.1, lat.2 | Boldness trials (2 trials), latency to emerge from a shelter after being chased with a net. (max 300s) | | cog\_performance | Difference between es2 and es3 (trial 1 and 2) in the inhibitory avoidance learning in the latency to enter the black side as a measure of cognitive performance | | anxi | Anxiety, proportion of time spend in the dark side for 5 minutes. | | M | Fish mass in grams  | | SL  | Standard length in mm | | SL.cm | Standard length in cm | | adj.M | Adjusted mass (i.e. total fish mass minus parasite mass) | | FUL | Fulton index: masse(g)/taille(cm)\^3 | | adj.FUL | Fulton index calculated with the adjusted mass | | BS | Number of blackspots on the right side of the fish | | d.BS | Blackspot density: BS/SL.cm | | log.d.BS | Logarithm of d.BS | | INT | Number of internal parasites | | d.INT | Internal parasites density: INT/SL.cm | | d.TOTAL | Total density of parasite: (INT+BS)/SL.cm | | defrost | Fish that were accidentally defrosted (1) and not used in models looking at internal parasite density (n=21) | ## Code/software We used R statistical software to analyse the data version 4.0.5 as shown below: ``` R version 4.0.5 (2021-03-31) -- "Shake and Throw" Copyright (C) 2021 The R Foundation for Statistical Computing Platform: x86_64-w64-mingw32/x64 (64-bit) ``` The packages needed are tidyverse, MASS, glmmTMB, gt, latex2exp, posterior, gt, glue, dplyr,magrittr, ggplot2, cowplot, jpeg, magick, rptR, webshot2, car, stats, gridExtra, AICcmodavg, lmer4, vegan, lmerTest, rsq, ggpubr, MuMIn, jtools. No other software is needed to access/visualize the data. The file "**script_final.R**" is the script used in R to analyse the data.