Regional adaptation defines sensitivity to future ocean acidification

Physiological responses to temperature are known to be a major determinant of species distributions and can dictate the sensitivity of populations to global warming. In contrast, little is known about how other major global change drivers, such as ocean acidification (OA), will shape species distrib...

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Bibliographic Details
Main Authors: Calosi, Piero, Melatunan, Sedercor, Turner, Lucy M, Artioli, Yuri, Davidson, Robert L, Byrne, Jonathan J, Viant, Mark R, Widdicombe, Stephen, Rundle, Simon
Format: Dataset
Language:English
Published: PANGAEA - Data Publisher for Earth & Environmental Science 2017
Subjects:
pH
Online Access:https://dx.doi.org/10.1594/pangaea.874858
https://doi.pangaea.de/10.1594/PANGAEA.874858
Description
Summary:Physiological responses to temperature are known to be a major determinant of species distributions and can dictate the sensitivity of populations to global warming. In contrast, little is known about how other major global change drivers, such as ocean acidification (OA), will shape species distributions in the future. Here, by integrating population genetics with experimental data for growth and mineralization, physiology and metabolomics, we demonstrate that the sensitivity of populations of the gastropod Littorina littorea to future OA is shaped by regional adaptation. Individuals from populations towards the edges of the natural latitudinal range in the Northeast Atlantic exhibit greater shell dissolution and the inability to upregulate their metabolism when exposed to low pH, thus appearing most sensitive to low seawater pH. Our results suggest that future levels of OA could mediate temperature-driven shifts in species distributions, thereby influencing future biogeography and the functioning of marine ecosystems. : In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2016) was used to compute a complete and consistent set of carbonate system variables, as described by Nisumaa et al. (2010). In this dataset the original values were archived in addition with the recalculated parameters (see related PI). The date of carbonate chemistry calculation by seacarb is 2017-04-26.