Swimming through the carbonscape: A zooplankton-centric view of Puget Sound pH

Understand the carbon chemistry environment experienced by zooplankton in Puget Sound is essential to predicting how ocean acidification will affect these species. Puget sound has a spatially variable and temporally dynamic carbon chemistry environment as a consequence of interacting physical and bi...

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Bibliographic Details
Main Authors: McElhany, Paul, Ladd, Tanika, Khangaonkar, Tarang
Format: Text
Language:English
Published: Western CEDAR 2014
Subjects:
Online Access:https://cedar.wwu.edu/ssec/2014ssec/Day2/112
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Summary:Understand the carbon chemistry environment experienced by zooplankton in Puget Sound is essential to predicting how ocean acidification will affect these species. Puget sound has a spatially variable and temporally dynamic carbon chemistry environment as a consequence of interacting physical and biological processes. Zooplankton have complex movement patterns as a consequence of passive drifting, active swimming toward or way from stimuli, daily vertical migrations (DVM), and density dependent interactions. We used an individual-based approach to simulate movement of several zooplankton species in a 3-d model of carbon chemistry dynamics in Puget Sound. The unstructured-grid model includes hydrodynamics and water quality variables such as nutrients and oxygen at spatial scales as small as ten meters (horizontal) and temporal scales as small as minutes. We added carbon chemistry to the model using empirically derived local relationships with oxygen, temperature and salinity. Zooplankton movement was modeled for species that exhibit a variety of behaviors exhibited by Puget Sound species. Model output consists of time series of carbon parameter exposure (e.g. pH) that can be used to create realistic conditions for laboratory experiments and to assess vulnerability of zooplankton species to current and future acidification. Vulnerability is a function of exposure (addressed in this study) and sensitivity (addressed in lab experiments). The exposure time series approach moves beyond simple assessment of average conditions to consider species where peak exposures or rates of change in carbon parameters may drive sensitivity.