DOI: 10.5061/dryad.83bk3jb68
title: Diverging carbonate budgets following tropicalisation of temperate reefs

description: Climate-driven shifts in habitat-forming species abundance and
 distributions are transforming how ecosystems produce and cycle carbon,
 nutrients, and energy. Temperate kelp forests are increasingly being
 replaced by tropical or warm-affinity habitat-forming species like turf
 seaweeds and corals, i.e., “tropicalised”. These changes can have
 cascading effects on associated species such as calcifying organisms,
 which contribute to sediment generation and carbon cycling via the
 production of calcium carbonate. This study quantified carbonate
 production and erosion across a temperate kelp forest and three
 tropicalised reef states following the 2011 marine heat wave: kelp-turf
 mix, warmer-affinity seaweeds, and coral-turf dominance. Results show
 gross carbonate production was highest in coral-turf reefs (1.85 ± 0.65 kg
 m⁻² yr⁻¹), lowest in warmer-affinity seaweed reefs (0.04 ± 0.02 kg m⁻²
 yr⁻¹), and intermediate in temperate kelp forests (0.60 ± 0.19 kg m⁻²
 yr⁻¹). These differences were linked to the abundance of corals in the
 coral-turf state and scarce calcifying algae in the warmer-affinity
 seaweed state. Bioerosion played a moderate role in the overall budget,
 but the dominant bioeroders differed between habitats: urchins in
 temperate reefs contributed 80% less than parrotfishes in tropicalised
 reefs. Overall, tropicalisation can either increase or decrease carbonate
 availability, depending on the dominant habitat-formers. These shifts may
 significantly impact inorganic carbon cycling and the structural and
 functional integrity of coastal reef ecosystems.
description: # Diverging carbonate budgets following tropicalisation of temperate reefs
 Dataset DOI:
 [10.5061/dryad.83bk3jb68](https://doi.org/10.5061/dryad.83bk3jb68) ##
 Description of the data and file structure * This script analyses data
 from the study: * "Diverging carbonate budgets following
 tropicalisation of temperate reefs" * The analysis quantifies changes
 in benthic community structure, calcification, and bioerosion across a
 temperate-to-tropical transition. Analyses and figures correspond to: *
 Tropicalisation states (Figure 2) * Community % cover by organism (Figure
 3) * Carbonate production and bioerosion (Figure 4) ### Files and
 variables #### File: Photo_quadrat_data_RSPB-2025-2578.csv
 **Description**: Photo-habitat quadrat analyses across sites * *Site*:
 Study site * *Transect*: Replicate transect * *Functional_Group*: Benthic
 functional group * *Count:* Each row = one random point on image ####
 File: Calcifier_data_RSPB-2025-2578.csv **Description**: Percent cover and
 carbonate production of calcifiers * *Scenario*: Tropicalisation states
 (turf/coral, temperate seaweeds, transition stage, warmer-affinity
 seaweeds) * *Site*: Study site * *Transect*: Replicate * *Morph*:
 Calcifiers category (CCA, articulated macroalgae, *Acropora* branching,
 *Acropora* plating, massive corals, encrusting corals, *Turbinaria*, other
 branching) * *Organism*: Calcifier class (Corals, CCA, or articulated
 macroalgae)  * *Production_kg.m.2.yr.1*: Carbonate production (kg.m
 ^-2^.year ^-1^) * *Perc_cover*: Calcifier percent cover (%) #### File:
 Bioeroder_data_RSPB-2025-2578.csv **Description**: Parrotfish and urchin
 bioerosion  * *Scenario*: Tropicalisation scenarios (turf/coral, temperate
 seaweeds, transition stage, warmer-affinity seaweeds) * *Site*: Study site
 * *Organism*: Bioeroders (Urchins or parrotfish) * *Prod_orga_site*: Mean
 bioerosion (kg.m ^-2^.year ^-1^) * *sd_site*: Standard deviation of the
 mean bioerosion at the site level * *n*: Number of transects * *se*:
 Standard error of the mean bioerosion at the site level #### File:
 RSPB-2025-2578_Script.R **Description:** R script used to perform all
 analyses and generate figures. ###### ***Software / Session Information***
 R version: 4.4.1 (2024-06-14) Required R packages: patchwork (1.2.0),
 emmeans (1.10.3), mvabund (4.2.1), vegan (2.6-6.1), tidyverse (2.0.0),
 dplyr (1.1.4), glmmTMB (1.1.9), DHARMa (0.4.6), ggplot2 (3.5.1) ######
 **How to reproduce the analysis** 1. Download all data files and the R
 script. 2. Place `.csv` files in the same folder as the script. 3. Open
 **R** or **RStudio**. 4. Install required packages if not already
 installed. 5. Run `RSPB-2025-2578_Script.R` top-to-bottom. All figures and
 statistical outputs in the manuscript will be reproduced.