Data for: Integrating biotic interactions in niche analyses unravels patterns underlying community composition in clownfishes

---

1. General Information

Dataset Title

Data for the article:
Integrating biotic interactions in niche analyses unravels patterns underlying community composition in clownfishes

Dataset DOI

https://doi.org/10.5061/dryad.2bvq83bv8

Authors

Alberto Garcia Jimenez
Olivier Broennimann
Antoine Guisan
Théo Gaboriau
Nicolas Salamin

Author ORCID IDs

Alberto Garcia Jimenez – https://orcid.org/0000-0002-1532-8784
Olivier Broennimann – https://orcid.org/0000-0001-9913-3695
Antoine Guisan – https://orcid.org/0000-0002-3998-4815
Théo Gaboriau – https://orcid.org/0000-0001-7530-2204
Nicolas Salamin – https://orcid.org/0000-0002-3963-4954

Contact

Alberto Garcia Jimenez
Department of Computational Biology
University of Lausanne

Email:
agarcia26286@gmail.com
alberto.garciajimenez@unil.ch

---

2. Dataset Description

This dataset contains the data, scripts, model outputs, and figures used in the study:

Garcia Jimenez et al. – Integrating biotic interactions in niche analyses unravels patterns underlying community composition in clownfishes.

The study investigates how biotic interactions between clownfish species (Amphiprion spp.) and their host sea anemones influence ecological niche structure and spatial community composition across the Indo-Pacific.

The dataset includes:

• species occurrence datasets
• environmental predictors used in ecological niche modelling
• interaction matrices between clownfish and sea anemones
• niche overlap and spatial analysis results
• environmental niche models (ENMs)
• mutualism-refined niche models
• statistical model outputs
• reproducible analysis scripts
• figures and supplementary tables used in the manuscript

---

3. Repository Structure

The dataset is organized into compressed archives.

Dataset
├── data.zip
├── results.zip
├── Rdata.zip
├── figures.zip
├── tables.zip
└── scripts.zip

---

4. Recommended Software

The following free or open-source software can be used to view the files:

.csv — R, Python, LibreOffice Calc
.R — RStudio or R
.RDS — R
.pdf — any PDF reader
.tex — LaTeX editors such as TeX Live or Overleaf
.tif — QGIS, ArcGIS, or R packages such as terra
.shp/.dbf/.shx/.prj — QGIS, ArcGIS, or R package sf |Note: Shapefiles can be opened and used in any GIS software and in R or Python. A shapefile consists of multiple file types beyond the .shp (specifically, .cpg, .dbf, .prj, .sbn, and .sbx). The user only interacts directly with the .shp file but the other files need to be in the same directory.
.zip — any archive utility

Analyses were developed using:

R ≥ 3.6.3
RStudio 2021.09.2

---

5. Data Sources

Occurrence records were compiled from:

• GBIF (Global Biodiversity Information Facility)
• Reef Life Survey (RLS)
• OBIS (Ocean Biogeographic Information System)
• Hexacoral database

Environmental predictors were obtained from:

• GMED (Global Marine Environment Datasets)
• Bio-Oracle

Marine regions follow the Marine Ecoregions of the World (MEOW) classification.

---

6. Folder Descriptions

6.1 data.zip

This folder contains all primary input datasets used in the analyses.

data/

• amph_occ_env_final_dataset.csv
• anem_occ_env_final_dataset.csv
• interaction_matrix.csv
• old_interaction_matrix.csv
• selected_environmental_variables.csv
• marine_regions.csv
• marine_regions.shp
• marine_regions.dbf
• marine_regions.shx
• marine_regions.prj
• meow_ecos_df.csv
• qc/

Occurrence datasets

amph_occ_env_final_dataset.csv — Geo‑referenced occurrence records for clownfish species including environmental predictors.

anem_occ_env_final_dataset.csv — Geo‑referenced occurrence records for sea anemone host species including environmental predictors.

Dataset format:

species: clownfish species name (character)

x: longitude (decimal degrees)

y: latitude (decimal degrees)

Interaction matrices

interaction_matrix.csv — Species-named binary matrix describing documented clownfish–anemone mutualistic interactions.

old_interaction_matrix.csv — Previous version of the interaction matrix retained for reproducibility of earlier analyses.

Environmental predictors

selected_environmental_variables.csv — Environmental predictor variables extracted for all grid cells in the study region (~0.083° resolution).

Environmental predictor variables extracted for all grid cells in the study region
at approximately 0.083° spatial resolution. These variables were used in the
environmental niche modelling analyses.

Each row corresponds to a geographic grid cell.

Variables:
x: Longitude of the grid cell centre. Units: decimal degrees.
y: Latitude of the grid cell centre. Units: decimal degrees.
bo2dissolve: Mean dissolved oxygen concentration at the bottom of the water column. Units: mmol m^-3.
bphosphate: Mean phosphate concentration in seawater. Units: µmol L^-1.
chlarange: Range (max–min) of chlorophyll-a concentration across the year. Units: mg m^-3.
parmean: Mean photosynthetically active radiation. Units: Einstein m^-2 day-1.
dissolved.oxygen.mean: Mean dissolved oxygen concentration along the water column. Units: mmol m^-3.
nitrate.mean: Mean nitrate concentration. Units: µmol L^-1.
temperature.range: Annual range of sea surface temperature. Units: °C.
sstmean: Mean sea surface temperature. Units: °C.
sstrange: Range of sea surface temperature across the year. Units: °C.

Marine regions

marine_regions.shp/.dbf/.shx/.prj — GIS shapefile representing marine provinces used in spatial analyses.

marine_regions.csv — Tabular version of marine region classifications.

Variables:
x: Longitude of the grid cell centre. Units: decimal degrees.
y: Latitude of the grid cell centre. Units: decimal degrees.
province: Marine province assigned to the grid cell based on the MEOW biogeographic classification.
realm: Marine realm assigned to the grid cell based on the MEOW biogeographic classification.

QC datasets

qc/ contains summary datasets used during data preparation to assess overlap among occurrence data sources.

---

6.2 results.zip

Contains datasets produced as outputs of the analyses.

These include:

• ROU (Relative Occupancy of the environmental niche) metrics
• niche overlap datasets
• spatial analysis datasets
• statistical model outputs
• environmental niche models
• mutualism‑refined niche models
• raster predictions
• shapefiles of predicted distributions

Key datasets include:

ROU_data.csv
ROU_data_envhost_predictors.csv
ROU_data_host_predictors.csv
ROU_data_oldA.csv

niche_overlaps.csv
niche_overlaps_corrected.csv

spatial_results.csv
spatial_results_corrected.csv
summary_spatial.csv

with additional folders:

├── amph_EBMs_newA
├── amph_EBMs_oldA
├── amph_ENMs
├── anem_ENMs
├── raster_maps
└── shapefiles

containing environmental niche models to be loaded using NINA function load_model(folder) and predicted species distributions provided as raster GeoTIFF files (.tif) and shapefiles.

---

6.3 Rdata.zip

Contains serialized R objects used in the analyses.

Rdata/

• GG_spatialGLMM.RDS
• GS_spatialGLMM.RDS
• SS_spatialGLMM.RDS
• all_spatialGLMM.RDS
• amphEBMs.RDS
• amphEBMs_oldA.RDS
• amphENMs.RDS
• amphENMs_envhostpredictors.RDS
• amphENMs_glob.RDS
• anemENMs.RDS
• anemENMs_glob.RDS

These files contain fitted model objects and can be loaded in R using:

readRDS("filename.RDS")

---

6.4 scripts.zip

Contains all R scripts required to reproduce the analyses.

Scripts include:

0a_occ_datapreparation.R
0b_env_datapreparation.R
0c_marine_regions.R
0d.env_var_selection.R
1_reg_models.R
2_ROU_analysis.R
3_nicheOverlaps.R
4_spatialCompetition.R
4_spatialCompetition_corrected.R
GLM_and_moranItests.R
Models_evaluation.R
spatialGLMM.R
functions.R

Additional scripts generate figures and tables used in the manuscript.

---

6.5 figures.zip

Contains all main and supplementary figures used in the manuscript.

figures/

• Fig1–Fig5 (main manuscript figures)
• FigS1–FigS10 (supplementary figures)
• maps/ (species distribution maps derived from niche modelling analyses)

---

6.6 tables.zip

Contains supplementary tables in LaTeX format.

tables/

• TableS1_Cramers_test.tex
• TableS2_ROU_GvsS_summary.tex
• TableS3.Spatial GLMMs.tex

---

7. Missing Data Codes

NA — missing value

---

8. License

All files in this dataset are distributed under the CC0 1.0 Universal Public Domain Dedication, as required by Dryad.

---

9. Confirmation Regarding Licensing and Third‑Party Data

The authors confirm that all materials included in this Dryad submission are compatible with the CC0 license waiver required by Dryad.

Occurrence data used in the analyses were obtained from publicly accessible biodiversity databases (GBIF, OBIS, Reef Life Survey) and were processed and aggregated by the authors for analytical purposes.

Environmental predictors were derived from publicly available environmental datasets (GMED and Bio‑Oracle).

The versions included in this repository consist of derived analytical datasets, model outputs, and figures generated by the authors.

All figures included in figures.zip were produced by the authors using the scripts included in this dataset. The authors confirm that these figures may be distributed under the CC0 waiver applied by Dryad.

The authors confirm that the dataset does not contain copyrighted material redistributed in its original form and that all files included here are compatible with the CC0 public domain dedication required for Dryad deposits.