Parasitic infection: a buffer against ocean acidification?
Recently, there has been a concerted research effort by marine scientists to quantify the sensitivity of marine organisms to ocean acidification (OA). Empirical data generated by this research have been used to predict changes to marine ecosystem health, biodiversity and productivity that will be ca...
Main Authors: | , |
---|---|
Format: | Dataset |
Language: | English |
Published: |
PANGAEA - Data Publisher for Earth & Environmental Science
2016
|
Subjects: | |
Online Access: | https://dx.doi.org/10.1594/pangaea.869417 https://doi.pangaea.de/10.1594/PANGAEA.869417 |
Summary: | Recently, there has been a concerted research effort by marine scientists to quantify the sensitivity of marine organisms to ocean acidification (OA). Empirical data generated by this research have been used to predict changes to marine ecosystem health, biodiversity and productivity that will be caused by continued acidification. These studies have also found that the effects of OA on marine organisms can be significantly modified by additional abiotic stressors (e.g. temperature or oxygen) and biotic interactions (e.g. competition or predation). To date, however, the effects of parasitic infection on the sensitivity of marine organisms to OA have been largely ignored. We show that parasitic infection significantly altered the response of a marine gastropod to simulated OA conditions by reducing the mortality of infected individuals relative to uninfected conspecifics. Without the inclusion of infection data, our analysis would not have detected the significant effect of pH on host mortality. These results strongly suggest that parasitic infection may be an important confounding factor in OA research and must be taken into consideration when assessing the response of marine species to OA. : 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 is 2016-12-13. |
---|