Chivers, Douglas P; McCormick, Mark I; Nilsson, Göran E; Munday, Philip L; Watson, Sue-Ann; Meekan, Mark; Mitchell, Matthew D; Corkill, Katherine C; Ferrari, Maud C O (2014): Impaired learning of predators and lower prey survival under elevated CO2: a consequence of neurotransmitter interference [dataset]. PANGAEA, https://doi.org/10.1594/PANGAEA.848083, Supplement to: Chivers, DP et al. (2014): Impaired learning of predators and lower prey survival under elevated CO2: a consequence of neurotransmitter interference. Global Change Biology, 20(2), 515-522, https://doi.org/10.1111/gcb.12291
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Abstract:
Ocean acidification is one of the most pressing environmental concerns of our time, and not surprisingly, we have seen a recent explosion of research into the physiological impacts and ecological consequences of changes in ocean chemistry. We are gaining considerable insights from this work, but further advances require greater integration across disciplines. Here, we showed that projected near-future CO2 levels impaired the ability of damselfish to learn the identity of predators. These effects stem from impaired neurotransmitter function; impaired learning under elevated CO2 was reversed when fish were treated with gabazine, an antagonist of the GABA-A receptor - a major inhibitory neurotransmitter receptor in the brain of vertebrates. The effects of CO2 on learning and the link to neurotransmitter interference were manifested as major differences in survival for fish released into the wild. Lower survival under elevated CO2 , as a result of impaired learning, could have a major influence on population recruitment.
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Further details:
Gattuso, Jean-Pierre; Epitalon, Jean-Marie; Lavigne, Héloïse (2015): seacarb: seawater carbonate chemistry with R. R package version 3.0.6. https://cran.r-project.org/package=seacarb
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Latitude: -14.666670 * Longitude: 145.466670
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Comment:
In order to allow full comparability with other ocean acidification data sets, the R package seacarb (Gattuso et al, 2015) 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 is 2015-07-09.
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License:
Creative Commons Attribution 3.0 Unported (CC-BY-3.0)
Status:
Curation Level: Enhanced curation (CurationLevelC)
Size:
416 data points