Overview

This repository contains all datasets and code used in the analyses for the manuscript *"*Differing temperature regimes have no impact on the heat stress response of shallow and upper mesophotic populations of a temperate calcareous sponge" (DOI: 10.1098/rspb.2025.1103). The study examines how shallow (10 m) and upper–mesophotic (30–50 m) populations of a temperate calcareous sponge respond to marine heatwaves (MHWs) - extreme thermal events that are becoming more frequent and intense due to anthropogenic climate change. Temperate mesophotic ecosystems (TMEs), typically experiencing cooler and more stable thermal regimes, may host populations with different thermal tolerances than their shallow-water counterparts. This repository provides full transparency and reproducibility for all analyses, figures, and microbial community assessments presented in the manuscript.

Below is a detailed description of the dataset structure, contents, and associated analytical scripts.

Repository Contents

1. Raw and Processed Data

01_RawData.zip: raw FASTQ sequencing reads

• Contains all raw 16S rRNA amplicon sequencing reads used for microbial community analyses.
• These reads were processed into an OTU table using the pipeline described in MHW_microbial_sequences.R.

all.data.xlsx

A multi-sheet Excel file containing all environmental, physiological, and microbial datasets. Sheets include:

• fiord.temp.10 – Temperature (degree C) logger data collected at 10 m depth.
• fiord.temp.30 – Temperature logger data collected at 30 m depth.
• fiord.temp.50 – Temperature logger data collected at 50 m depth.
• regression – Buoyant weight and ash-free dry weight (AFDW) measurements used to calculate respiration rates (per gram AFDW) and construct regression models.
• schedule – Temperature data from experimental heatwave simulations, used to generate temperature schedule plots.
• resp_bw – Buoyant weight measurements and respiration rates for each sponge under each thermal treatment across experimental time points.
• survival – Survival data used for Kaplan–Meier survival analyses.
• OTU – Operational Taxonomic Unit (OTU) table generated from 16S sequences and used for microbial community composition analyses.

Each sheet includes raw data in the format used directly for statistical and graphical workflows.

2. Code and Scripts

MHW_final_complete_stats_and_plots_ProcB.R

• Main script used for all statistical analyses and figure generation.
• Includes:
  • Data wrangling and transformation
  • Temperature time-series analyses
  • Survival modelling (Kaplan–Meier)
  • Linear mixed-effects models
  • Respiration analyses
  • Community composition analyses (ordination, PERMANOVA, etc.)
  • All plotting code used in the manuscript (ggplot2)
• Packages and functions referenced throughout correspond to those described in the Methods section of the manuscript.

MHW_microbial_sequences.R

• Full pipeline for processing raw 16S amplicon data.
• Steps include:
  • Quality filtering and trimming
  • Error modelling
  • Generation of OTU table
  • Taxonomic assignment
  • Export of processed community data for downstream analyses.
• Ensures reproducibility from raw sequences through to the final OTU table.

3. Study Context

Marine heatwaves (MHWs) are increasing globally due to climate change and pose a particular threat to TMEs - light-dependent ecosystems found between ~30–150 m depth. These habitats typically experience stable, cooler temperatures that may influence the thermal tolerance of resident species, including sponges, which are often dominant benthic organisms. This study compares physiological and microbial responses to heat stress between shallow and upper–mesophotic sponge populations to test the hypothesis that shallow-water individuals possess greater thermal resilience. All data and code used to evaluate this hypothesis are provided here.

4. How to Use These Files

Reproducibility

1. Begin by downloading all data files, including 01_RawData.zip if microbial analyses are desired.
2. Use MHW_microbial_sequences.R to reproduce the OTU table from raw reads.
3. Load all.data.xlsx into R using readxl, openxlsx, or similar packages.
4. Run MHW_final_complete_stats_and_plots_ProcB.R to reproduce all figures and statistical outputs from the manuscript.

Dependencies

All required R packages are listed and loaded in the scripts themselves

5. Contact

For further clarification, please refer to the Methods section of the manuscript or contact the corresponding author.

6. Data Availability

This README accompanies the Dryad submission and provides all relevant details required for reuse, interpretation, and replication.