Data from: Turning the tide: A 2°C increase in heat tolerance can halve climate change induced losses in four cold-adapted kelp species
Data files
Apr 23, 2025 version files 3.26 GB
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README.md
4.49 KB
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Turning_the_tide.zip
3.26 GB
Abstract
Kelp forests are susceptible to climate change as their sessile nature and low dispersal capacity hinders tracking of suitable conditions. The emergence of a wide array of approaches to increasing thermal tolerance seeks to change the outlook of biodiversity in a changing climate but lacks clear targets of impactful thermal resilience. Here, we utilize species distribution models (SDMs) to evaluate the potential of enhanced thermal tolerance to buffer the effects of climate change on cold-adapted kelp species: Saccharina latissima, Alaria esculenta, Laminaria hyperborea, and Laminaria digitata. For each species, we compared a baseline model - where the thermal niche remained unchanged - to models where the simulated maximum sea surface temperature tolerance was increased by 1-5°C. These models were projected into three climate change scenarios: sustainability (Shared Socioeconomic Pathway (SSP) 1-1.9, Paris Agreement), regional rivalry (SSP3-7.0) and fossil-fuel development (SSP 5-8.5). Our SDMs demonstrate that an increase of 1-2°C in thermal tolerance could recover over 50% of predicted losses of suitable habitat for cold-adapted kelps. However, A. esculenta, a species of growing commercial interest, still faced persistent habitat contraction across all climate change scenarios and simulated tolerance increases including up to 15% unrecovered losses under SSP5-8.5, even with a simulated 5°C increase in thermal tolerance. Our findings highlight the need for a two-pronged approach to conserve cold-adapted kelp forests: stringent reductions in greenhouse gas emission reductions in line with the SSP1-1.9 scenario, and strategies to boost kelp’s thermal tolerance by at least 1-2°C. This dual approach is crucial to maintain 90% of the current suitable habitat of S. latissima and L. digitata, and 70% for A esculenta and L. hyperborea. Relying on mitigation or adaptation alone will likely be insufficient to maintain their historic range under projected climate change.
Access this repo on Dryad: https://doi.org/10.5061/dryad.f4qrfj751
Description of the data and file structure
Primary script Kelpmodel_submit.R collects occurrence data and environmental layers, produces a baseline SDM in the present, projects it in the future, and implements simulated tolerance increases from 1-5 degrees C. Each species results are a separate run of the script. The "outputs" folder is provided populated with the results associated with the manuscript as an example (results_species_2024-09-25_). Our results are provided and described in the published article and its supplements. Extension to species not included in our analysis is possible by updating the "my_species" variable and calculating an appropriate transition function via iterative review of the thermal response curves produced by the base and modified models. Extension to other environmental variables and/or climate change scenarios can be done within the script through the modification of the included queries to the Bio-ORACLE ERDAP database (details below).
Turning_the_tide.zip contents:
inputs - raster layers comprising EEZs (eez_all_sf.shp), coastlines (coastLineRes005.tif), and marine ecoregions (WCMC-036-MEOW-PPOW-2007-2012.shp). A pruned brown algae dataset in R environment (dataBrownAlgaePruned.RData) format is also provided, as documented in Assis et al., 2020.
outputs - per species and climate change scenario results, including associated processed layers and raw/filtered occurrences. Created and organized programmatically within script. Variables, including downloaded environmental layers and intermediate data structures, are preserved at the end of each run in a .RData file. Overviews of model performance and variable contribution as the model is modified for each tolerance increase are provided in .csv files within each transition folder. Any variable available through Bio-ORACLE in the present and future can be used and retrieved for modeling with the current framework of the script by updating variable names in the script. Layers retrieved from the Bio-ORACLE ERDDAP server in this way are stored as .nc files, but named randomly and are therefore deleted and retrieved with each run. Keys of variable names and units are available through Bio-ORACLE both via the biooracler R package and the main website. Primary results (figures of the modeling region, modeled suitability, binarized model suitability, area lost and recovered as .png files) are available within the scenario folder. Outputs are organized as:
├───scripts
├───inputs
├───outputs
│ ├───<species>
│ │ ├───layers
│ │ ├───occurrences
│ │ ├───results_<species>_<date>
│ │ │ ├───<scenario>
│ │ │ │ ├───transition_1
│ │ │ │ ├───transition_2
│ │ │ │ ├───transition_3
│ │ │ │ ├───transition_4
│ │ │ │ └───transition_5
scripts - Kelpmodel_submit.R reads in data, creates models (species and layers to be user specified), writes results to outputs folder. This is the only script required for analysis. If applying to new species, transition function values (manuscript section 2.4) must be determined via iterative review of the thermal response curves of the base and modified models. Some of the most computationally intensive portions of the script are associated with cross-validation and variable selection which need only be completed once per species. Commenting out these sections (labeled in R script) can substantially reduce run time for subsequent modeling efforts on the same species.
Code compatibility information:
The majority of analysis was performed in R version 4.4.0 (2024-04-24) with RStudio version 2023.9.0.463 Platform: x86_64-pc-linux-gnu Running under: Ubuntu 22.04.5 LTS in a cluster computing Linux environment, but collaborators successfully repeated the analysis on local machines running both Mac and Windows using R version 4.3.3 (2024-02-29 ucrt).
