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Near complete local extinction of iconic anemonefish and their anemone hosts following a heat stress event

Lookup NU author(s): Melissa Versteeg, Dr Theresa RuegerORCiD

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This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License (CC BY-NC-ND).

Abstract

© The Author(s) 2025. A fundamental question in modern-day ecology is: How will populations and their interactions respond to a rapidly changing climate? Documenting local collapses of ecologically and economically important populations can offer insight into broader patterns of decline. Here, we monitored anemonefish (Amphiprion bicinctus) and their host sea anemones (Radianthus magnifica) on three central Saudi Arabian Red Sea reefs from 2022 to 2024, including a 2023 marine heatwave that peaked at a Degree Heating Weeks (DHW) value of ~22 °C-weeks. Across all reefs, we observed a sequence of 100% anemone bleaching, 94.3–100% anemonefish mortality, and 66.4–94.1% anemone mortality. We compare these findings to other recent Indo-Pacific heat stress events of varying intensity, where similar declines were not observed. Our study highlights the vulnerability of mutualistic reef species to extreme heat and suggests that such events may drive local, if not regional, extinctions of ecologically important symbioses.

Publication metadata

Author(s): Bennett-Smith MF, Villela H, Justo MSS, Peinemann VN, Berumen ML, Carvalho S, Garcias-Bonet N, Garcia FC, Versteeg M, Rueger T, Buston PM, Peixoto RS

Publication type: Article

Publication status: Published

Journal: npj Biodiversity

Year: 2025

Volume: 4

Online publication date: 12/09/2025

Acceptance date: 15/08/2025

Date deposited: 01/10/2025

ISSN (electronic): 2731-4243

Publisher: Springer Nature

URL: https://doi.org/10.1038/s44185-025-00107-4

DOI: 10.1038/s44185-025-00107-4

Data Access Statement: The complete dataset used in the analysis is included in the supplementary file with this submission. All statistical analyses and visualizations were conducted in R (v4.3.1) using the following packages: dplyr, tidyr, ggplot2, scales, RColorBrewer, lme4, lmerTest, emmeans, logistf, sjPlot, and performance. The full R code used in this manuscript is available upon request.

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