Systematic review of the uncertainty of coral reef futures under climate change, datasets
Data files
Feb 27, 2024 version files 121.05 KB
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README.md
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Supplementary_Data_1.xlsx
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Supplementary_Data_2.xlsx
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Supplementary_Data_3.xlsx
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Supplementary_Data_File.xlsx
Abstract
Climate change impact syntheses, such as those by the Intergovernmental Panel on Climate Change (IPCC), consistently assert that limiting global warming to 1.5°C is unlikely to safeguard most of the world’s coral reefs. This prognosis primarily stems from 'excess heat’ threshold models, which assume that widespread coral bleaching predictably occurs when temperatures accumulate beyond a specific threshold. Our systematic review of research projecting coral reef futures to climate change (n=79) revealed that 'excess heat' models constituted only one third (32%) of all studies but attracted a high proportion (68%) of citations in the field. We observed that most methods employed deterministic cause-and-effect rules rather than probabilistic relationships, impeding the field's ability to estimate uncertainties of coral reef futures. In attempting to assess the consistency of projected impacts, we aimed to identify common coral reef metrics under the same emissions scenarios. However, disparate choices in metrics and emissions scenarios hindered a cohesive synthesis and limited the exploratory analysis to a small fraction of available studies. We found substantial discrepancies in expected impacts to coral reefs, suggesting that some 'excess heat' models may project more extreme impacts than other methods. Drawing on lessons from the field of climate change science, we propose that an IPCC ensemble-like approach to generating probabilistic projections for coral reef futures is feasible. Successful implementation will require improved coordination among modeling efforts to select common output metrics and emission scenarios, addressing existing geographical biases, among other gaps in current modeling efforts.
README: Systematic review of the uncertainty of coral reef futures under climate change, datasets
Published paper resulting from this data can be found at: https://doi.org/10.1038/s41467-024-46255-2
Summary
This study conducted a systematic review of 79 published articles projecting coral reef responses to future climate change. This dataset contains qualitative and quantitative data extracted from the published studies, including model types, geographic focus, and projected impacts on coral reefs.
Description of the data and file structure
Supplementary Data File
Extracted Data: Source data for effect size calculations (n=8 published studies).
- Short.reference used to identify the published study from which the data were extracted. See Full Reference List within this Read.Me file
- Scenario.ID identifies the individual scenario within each published study, numbered sequentially as scenario 1 (S1), scenario 2 (S2)
- N.c is n/number of model runs for control scenario
- N.e is n/number of model runs for future end-of-century (experimental) scenario
- M.c is the Model estimate for baseline scenario
- M.e is the model estimate of end of century projections
- Sd.c is the standard deviation of end of century projection estimates
- Sd.e is the standard deviation of the baseline scenario estimates
Supplementary_Data1
Summary Database: Overview of the dataset including study details, geographic focus, spatial scale, modeling approach, and examined stressors.
- Author(s) describes the authors of the published studies from which the data were extracted. See Full Reference List within this Read.Me file
- Year refers to the year of publication of the published studies
- Ref number identifies the full reference in the Full Reference List within this Read.Me file
- Approach type classified the models into five broad categories of methodologies: (a) ‘excess heat’/threshold models, (b) population dynamic models, (c) species distribution models, (d) ecological-evolutionary models, and (e) projective meta-analyses of published data (see published study for formal definitions). In a few cases where studies could not be categorized, the model type was recorded as ‘other’
- Focal projection(s) units is the unit in which the published studies delivered their projections
- Spatial scale refers to the spatial scale of the projections published, classified as either regional or global
- Geographic focus refers to the region the projections were formulated for (e.g. Great Barrier Reef, Australia)
- Major stressor(s) examined refer to the main drivers that were used to parameterize the models (e.g. warming, ocean acidification)
Supplementary_Data2
Complete Database: Detailed information from all 79 reviewed studies (qualitative characteristics)
- Unique_ID is a random unique ID assigned to each of the published papers within the dataset
- Author_list is a comprehensive list of all authors of the published studies within the dataset
- Article_ttle is the title of the published article
- Source_journal is the scientific journal in which the article was published
- Publication_year refers to the year of publication of the published studies
- Times_cited is the number of citations received by the published studies according to the Thomson Reuters Web of Science database on March 6, 2023.
- Model_category classified the models into five broad categories of methodologies: (a) ‘excess heat’/threshold models, (b) population dynamic models, (c) species distribution models, (d) ecological-evolutionary models, and (e) meta-analyses of published data (see published study for formal definitions). In a few cases where studies could not be categorized, the model type was recorded as ‘other’
- Model_technique refers to the method used to model heat stress (thermal threshold technique versus continuous variable technique). For studies to be classified as threshold techniques, the use of these metrics had to form the primary framework of the models that delivered projections. The second technique represents approaches that abandon the central threshold concept to focus on empirical relationships between continuous variables.
- if_TM_Threshold type records the type of thermal threshold used. N/a is used when the study did not use a thermal threshold, or it was not clearly reported.
- Focal_projection_unit records the units in which the published studies delivered their projections.
- Spatial_scale refers to the spatial scale of the projections published, classified as either regional or global.
- Reported_geographic_focus refers to the region the projections were formulated for (e.g. Great Barrier Reef, Australia)
- Drivers_used_summary records a summary of drivers used to parameterise the models.
- Underlying model structure/ description is a summary of the model structure and its purpose
- Key_assumptions is a description of the main assumptions made by the model
- Future_scenarios_examined refers to the exact future emissions pathways used
- Model_geographic_resolution records the spatial resolution of the model output
- Downscaled_yes_no records yes for when downscaling techniques were used to improve spatial resolution and no when downscaling techniques were not used
- Downscaled_method records which type of downscaling technique was used (either statistical or dynamic). N/A is used when the study did not use a downscaling technique
- Study_purpose is a summary of the published study's aims and its findings
- Study advantages is a synthesis of the published study's key advantages
- Study_gaps is a synthesis of the published study's key limitations
Supplementary_Data 3
Exploratory Meta-analysis Database: Scenario descriptions for data included in the effect size analysis.
- Author(s) describes the authors of the published studies from which the data were extracted. See Full Reference List within this Read.Me file
- Year refers to the year of publication of the published studies
- Ref is a number that identifies the full reference in the Full Reference List within this Read.Me file
- Scenario identifies the individual scenario within each published study, numbered sequentially as scenario 1 (S1), scenario 2 (S2)
- Scenario description is a summary of the future scneario modelled
- Reported warming refers to the future emissions pathway used to model future warming
- Classified warming categorizes these warming levels into different scenarios of 1.5 - 2ºC, 2 - 4ºC, and >4ºC represent projections at the end-of-century (years 2090-2100)
- Reported projection unit is the unit in which the published studies delivered their projections
- Classified projection unit represents the categories in which the projection units were analysed (e.g. % reef cells at risk)
Klein_et_al.,_2024
- R script: Script used for exploratory meta-analysis
Reference List
We use numbers that reference the sources we used to collect our data. Below is a list of the sources and their corresponding numbers.
Supplementary References
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Methods
We conducted a comprehensive literature search using the Thomson Reuters Web of Science database to identify studies that projecting the impacts of climate change on shallow tropical and sub-tropical coral reefs. This search, adhering to PRISMA guidelines, yielded 2705 peer-reviewed articles, which we refined to 79 relevant articles published between 1999 and 2023 based on a specific selection criteria (Dataset 1). These studies were categorized into five major methodology types and further classified based on their approaches to simulating heat stress. Key characteristics such as the model output variables, spatial scale, and geographic area of each study were extracted, along with their methodological approaches, assumptions, and the techniques used.
Our study aimed to assess and compare the projected impacts and uncertainties of various model types using a meta-analysis approach. The database of 79 studies was considered for inclusion in the exploratory meta-analysis based on specific criteria (view published article and supplementary methods for detailed list and Supplementary Figure 1). Briefly, to enable a meaningful analysis, we identified the three most frequently used model outputs in our database. Among those, only studies that provided: 1) sufficient data for projection estimates and uncertainty measures to be reliably extracted or calculated, 2) reported end-of-century projections, and 3) used a baseline period between 2000 and 2015, were selected for the exploratory meta-analysis. In cases where projection and uncertainty estimates were presented in figures, values were extracted using PlotDigitizer, where possible.