This dataset comprises a code script (script.Rdm) with the associated raw data (data*.csv) from: "Ocean deoxygenation and warming disrupt cooperation in coral reef fish mutualisms."

1. Paper Citation

B. P. Pereira; R. Oliveira; M. D. Martins; R. Rosa; J. R. Paula (2025). Ocean deoxygenation and warming disrupt cooperation in coral reef fish mutualisms. Behavioral Ecology.https://doi.org/10.1093/beheco/araf152

2. Originators

Beatriz Palinhos Pereira

3. Contact information

Name: Beatriz Palinhos Pereira
Institution: MARE ULisboa
email: bppereira@ciencias.ulisboa.pt

4. Date of data collection

September 2022

5. Geographic location(s) of data collection

Cascais, Portugal

6. Information about funding sources that supported the collection and curation of the data

This work was supported by British Ecological Society through a Large Research Grant – LRB21/1004 to JRP.
The study also received support from FCT—Fundação para a Ciência e Tecnologia, I.P.,
within the project grant PTDC/BIA-BMA/0080/2021—ChangingMoods (https://doi.org/10.54499/PTDC/BIA-BMA/0080/2021) to JRP,
the strategic project UIDB/04292/2020 granted to Centro de Ciências do Mar e do Ambiente,
project LA/P/0069/2020 granted to the Associate Laboratory ARNET, and a PhD fellowship 2021.06590.BD to BPP.
JRP was further supported supported by SPECO – Sociedade Portuguesa de Ecologia through the program
“Projetos para Investigadores em Início de Carreira 2020” and by a fellowship from
the ”la Caixa” Foundation (ID 100010434) with a fellowship code LCF/BQ/PR24/12050006.

ACCESS INFORMATION

1. Licenses/restrictions placed on the data

CC0

2. Data derived from other sources

No data derived from other sources

DATA FILES AND VARIABLES

1. Data_FAP.csv

Data from the feeding against preference (FAP) trials with cleaner wrasse (Labroides dimidiatus) across four treatment groups combining temperature (29 °C vs. 32 °C) and oxygen (100% vs. 90% air saturation).

• treatment: Experimental treatment code (C = control, W = warming, D = deoxygenation, WD = warming + deoxygenation).
• ID: Individual cleaner wrasse identification code.
• temperature: Water temperature during the trial (°C).
• O2: Oxygen saturation level (%).
• SCORE: Standardised learning performance score in the FAP test.
• W: Fish body weight (g).
• TL: Fish total length (cm).
• preference: Proportion of choices made towards the preferred food option.

##2. Data_Interactions.csv

Data from natural cleaning interactions between cleaner wrasse (L. dimidiatus) and client fish (Naso elegans) under the same four treatment groups (temperature × oxygen).

• treatment: Experimental treatment code (C = control, W = warming, D = deoxygenation, WD = warming + deoxygenation).
• ID: Cleaner wrasse identification code.
• O2: Oxygen saturation level (%).
• temperature: Water temperature during the trial (°C).
• n_interactions: Total number of cleaning interactions observed.
• cleaner_start: Number of interactions initiated by the cleaner.
• Prop_cleanerstart: Proportion of interactions initiated by the cleaner.
• client_starts: Number of interactions initiated by the client.
• n_posing: Number of posing events by the client.
• n_chase: Number of chases by the client (retaliation).
• n_jolts: Number of client jolts (indicator of cheating detection).
• prop_jolts: Proportion of interactions with jolts.
• n_ts: Number of tactile stimulations performed by the cleaner.
• ts_duration: Total duration of tactile stimulations (s).
• avg_int_duration: Mean duration of cleaning interactions (s).
• total_int_duration: Total time spent in cleaning interactions (s).
• prop_time_int: Proportion of the total observation period spent in cleaning interactions.
• total_vid_time: Total video observation time (s).
• time_not_int: Total time with no interaction (s).

#CODE SCRIPTS AND WORKFLOW

##1. script.Rdm

R Markdown script containing all steps of data analysis, including:

• Importing and inspecting raw data (data_FAP.csv and data_Interactions.csv).
• Statistical analyses of learning performance (FAP test) and cleaning interactions (Video analysis).
• Generation of figures for the manuscript.

#SOFTWARE VERSIONS

All analyses were performed using R, version 4.3.0 (R Core Team, 2013).

##software name and version

loaded packages:

• library(MASS)
• library(performance)
• library(lattice)
• library(ggplot2)
• library(effects)
• library(car)
• library(predictmeans)
• library(multcomp)
• library(glmmTMB)
• library(ggthemes)
• library(ggplot2)
• library(dplyr)
• library(forcats)
• library(hrbrthemes)
• library(viridis)
• library(r2glmm)
• library(ggeffects)
• library(sjmisc)
• library(sjPlot)
• library(emmeans)
• source("HighstatLibV10.R") The HighstatLibV10.R library file from Highland Statistics is not provided due to copyright protection

REFERENCES

R Core Team (2013). R: A Language And Environment For Statistical Computing. Vienna: R Core Team.
Zuur, A. F. & Ieno, E. N. (2016). A protocol for conducting and presenting results of regression-type analyses. Methods Ecol. Evol. 7(6), 636–645. https://doi.org/10.1111/2041-210X.12577
Zuur, A. F., Ieno, E. N., & Elphick, C. S. (2010). A protocol for data exploration to avoid common statistical problems. Methods in ecology and evolution, 1(1), 3-14. https://doi.org/10.1111/j.2041-210X.2009.00001.x
Zuur, A., Ieno, E., Walker, N., Saveliev, A. & Smith, G. (2009). Mixed Effects Models and Extensions in Ecology with R. Journal of Statistical Software, 32, 1-3. https://doi.org/10.18637/jss.v032.b01