Saxitoxin and tetrodotoxin bioavailability increases in future oceans

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Increasing atmospheric CO2 levels are largely absorbed by the ocean, decreasing surface water pH1. In combination with increasing ocean temperatures, these changes have been identified as a major sustainability threat to future marine life2. Interactions between marine organisms are known to depend on biomolecules, although the influence of oceanic pH on their bioavailability and functionality remains unexplored. Here we show that global change substantially impacts two ecological keystone molecules3 in the ocean, the paralytic neurotoxins saxitoxin and tetrodotoxin. Increasing temperatures and declining pH increase the abundance of their toxic forms in the water. Our geospatial global model predicts where this increased toxicity could intensify the devastating impact of harmful algal blooms, for example through an increased incidence of paralytic shellfish poisoning. Calculations of future saxitoxin toxicity levels in Alaskan clams, Saxidomus gigantea, show critical exceedance of limits safe for consumption. Our findings for saxitoxin and tetrodotoxin exemplify potential consequences of changing pH and temperature on chemicals dissolved in the sea. This reveals major implications not only for ecotoxicology, but also for chemical signals that mediate species interactions such as foraging, reproduction or predation in the ocean, with unexplored consequences for ecosystem stability and ecosystem services.

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Fig. 1: Neurotoxin structures, charge distributions and relative proportions of individual protonation states.
Fig. 2: Global abundance of the toxic saxitoxin protonation state today and in the future.
Fig. 3: Amount of the toxic saxitoxin form present in butter clam Saxidomus gigantea tissue.

Data availability

Source data for curves in Fig. 1 calculated based on the given references and coordinates of the molecular structures are available from the corresponding author upon request. The data used to generate the dataset for Fig. 2 are available from the Harmful Algal Information System metadatabase (HAEDAT,, the NOAA COPEPOD database (, the Global marine environment dataset (GMED, and the IPCC (WCRP CMPI3) multi-model database ( Data used to generate Fig. 3 can be accessed via the website of the Qagan Tayagungin Tribe (>Environment>PSP Program). The extracted, collated data supporting the findings in our study are deposited in the PANGAEA archive and available at

Code availability

The code used to calculate the proportions of different protonation states is available from the corresponding author on request .


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We acknowledge the Viper High Performance Computing facility of the University of Hull and its support team. C.C.R. was funded through D. Parsons’ project grant (no. ERC-2016-COG GEOSTICK). We thank the Quagan Tayagungin Tribe for access to the clam toxicity data at the PSP Program website. We acknowledge the World Climate Research Programme’s Working Group on Coupled Modelling and the climate modelling groups for producing and making available their model output. For CMIP the US Department of Energy’s Program for Climate Model Diagnosis and Inter-comparison provides coordinating support and led the development of software infrastructure in partnership with the Global Organization for Earth System Science Portals. We thank D. Parsons, Energy and Environment Institute, University of Hull, and H. Bartels-Hardege, Biological and Marine Sciences, University of Hull, for valuable suggestions and discussions.

Author information

C.C.R. and J.D.H. designed the study. K.C.W.V. and A.C.A. performed the analysis of the datasets for geospatial models and C.C.R. and D.M.B. calculated the molecular models. Access to toxin mussel data was provided by A.D. and B.W. C.C.R, J.D.H. and K.C.W.V. shared responsibility for, and N.F. contributed to, the writing of the manuscript. All authors contributed to the final version of the manuscript.

Correspondence to C. C. Roggatz.

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Peer review information Nature Climate Change thanks K. Cusick and the other, anonymous, reviewer(s) for their contribution to the peer review of this work.

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Supplementary methods, Figs. 1–3, Table 1 and references.

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