Preprint
Climate analogues as a tool for marine aquaculture planning and adaptation
Research Square, Vol.23 June 2026
Research Square Company
2026
Abstract
Sea surface temperature (SST) has increased by approximately 1 °C since 1901 and is projected to continue rising throughout the 21st century. Unlike wild species that can migrate, farmed aquaculture species are confined to fixed locations and require proactive planning to remain viable under changing climate conditions. We developed a spatially explicit framework that identifies climate analogues (places where future temperatures resemble those at current production sites) by integrating CMIP6 SST projections, species-specific thermal thresholds, and spatial constraints for the period 2021–2100. Atlantic salmon (Salmo salar) aquaculture in Tasmania was used as a case study. Analogues were classified as suitable or optimal based on the frequency of days exceeding species’ temperature thresholds relative to current farming conditions. By the 2050s, suitable analogue areas are projected to decline by 6.8% (SSP1-2.6) to 25.5% (SSP5-8.5), with losses by 2100 ranging from 9.3% (SSP1-2.6) to 77.1% (SSP5-8.5). Under the most stringent mitigation pathway (SSP1-1.9), suitable analogues remain stable or expand throughout the century. Optimal analogues decline more sharply, from 0.5% (SSP1-1.9) to 82% (SSP5-8.5). Spatial constraints created a jurisdictional gradient: State waters lost 45–55% of suitable analogue area, Commonwealth waters 3–7%, and high seas <1%. Under SSP5-8.5, State waters lose all optimal analogues by 2021–2030 and suitable analogues by 2031–2040, while Commonwealth waters retain 326,040–462,082 km² of viable area by mid-century. Climate analogues provide a powerful tool for climate-smart aquaculture planning, informing decisions on site viability, offshore expansion, species selection, and long-term technological adaptation.
Details
- Title
- Climate analogues as a tool for marine aquaculture planning and adaptation
- Authors
- Marina Christofidis (Corresponding Author) - Griffith UniversityDavid Schoeman - University of the Sunshine CoastJeremy Harte (Author) - Griffith UniversityVanessa Adams (Author) - University of TasmaniaJackson Stockbridge (Author) - Griffith UniversityCaitlin Kuempel (Author) - Griffith University
- Publication details
- Research Square, Vol.23 June 2026
- Publisher
- Research Square Company
- Date published
- 2026
- DOI
- 10.21203/rs.3.rs-9882223/v1
- Copyright note
- © This work is licensed under a Creative Commons Attribution 4.0 International License
- Data Availability
- Data analysis and visualization were conducted in RStudio 2025.05.0+496. All required information to replicate this analysis is available at: Marina6578/Climate_analogues_marine_aquaculture. We used daily SST projections (2015–2100) and corresponding historical runs (2003–2014) downloaded from the Earth System Grid Federation (ESGF — https://esgf.nci.org.au/search) and historical Multiscale Ultrahigh Resolution (MUR) Level-4 daily product developed by NASA's Jet Propulsion Laboratory (JPL) (https://podaac.jpl.nasa.gov/dataset/MUR-JPL-L4-GLOB-v4.1). The datasets of uses and habitats that we considered as constraints to aquaculture are detailed in Table 1. The packages used for Spatial data processing was performed using sf (Pebesma, 2018) and terra (Hijmans, 2020), while oceanographic data were accessed through rerddap (Chamberlain, 2015). The tidyverse collection of packages (Wickham et al., 2019), including dplyr (Wickham et al., 2019, 2014),ggplot2 (Wickham, 2016), purrr (Wickham and Henry, 2015), stringr (Wickham, 2009), and readr (Wickham et al., 2015), provided the foundation for data manipulation and visualization. Interactive maps were created using tmap (Tennekes, 2018) and leaflet (Cheng et al., 2015), while reactable (Lin, 2019) was used for interactive tables. Color palettes were implemented through viridis(Garnier, 2015), and project organization was managed with here (Müller, 2017). Additional visualization tools included rasterVis (Perpinan Lamigueiro and Hijmans, 2011) and table formatting with kableExtra (Zhu, 2017).
- Organisation Unit
- School of Science, Technology and Engineering
- Language
- English
- Record Identifier
- 991252398802621
- Output Type
- Preprint
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