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Background Anthropogenic CO2 emissions are increasing the partial pressure of CO2 (pCO2) in the atmosphere and as pCO2 increases, the air-sea equilibrium of pCO2 favors its diffusion into the sea. The diffusion of CO2 into the sea consequently modifies the carbonate chemistry in seawater. Ocean acidification (OA) refers to changes in the carbonate chemistry of seawater that result in decreased pH and is driven by the oceanic uptake of atmospheric CO2 (Guinotte and Fabry 2008). As pH is decreases, carbonate ions are less available, making it more difficult for calcifying marine organisms to thrive. The Salish Sea is already experiencing pH levels not generally predicted for the open ocean until 2100. The shellfish industry has experienced the direct impacts of OA suffering major oyster larvae mortality (Mabardy et al. 2015). Eelgrass meadows have been identified as potential habitat to mitigate OA because eelgrass takes up dissolved CO2 and bicarbonate through photosynthesis (Beer and Rehnberg 1997). Previous research has established that eelgrass are carbon limited and are expected to increase photosynthesis under OA conditions (Zimmerman et al. 1995). Therefore, eelgrass could potentially mitigate OA by drawing down carbon. At the meadow scale, seagrass presence relative to substrate cover is correlated with higher seawater pH compared to nearby seawater that does not have seagrass. In this study, I propose to test how the density of eelgrass, light and pCO2 changes the potential for eelgrass to drawdown a meaningful amount of carbon in a controlled setting. Our research could identify characteristics of eelgrass habitats that have the potential to draw down a meaningful amount of carbon to mitigate OA. Resource managers interested in shellfish restoration could potentially utilize eelgrass habitat as refugia from OA. Dr. Brooke Love and I have constructed a flow-through CO2 delivery mesocosm modeled after Jokiel et al. (2014) to experimentally test our research questions (Figure 3, see methods). Additional graduate students are also interested in using our mesocosm set-up for OA experiments. Cristina Villalobos’ is currently conducting experiments alongside spring courses at Shannon Point Marine Center (SPMC). Over the summer, Natalie Coleman’s experiment will be conducted alongside the Research Experience for Undergraduate (REU) program. If we move the mesocosm set-up outdoors using portable shelving, we could generate more lab space at SPMC. Therefore, researchers that share SPMC facilities will no longer conflict with our mesocosm set-up. Preliminary studies that we conducted using our mesocosm set-up have also reinforced the benefits of moving the mesocosm set-up outside (Figures 1 and 2). Data collected from preliminary studies conducted in fall 2017 showed that eelgrass increased pH and decreased pCO2 when exposed to light (Figure 2). Eelgrass at higher densities mitigated OA at a greater rate but only up to a certain density (Figure 2). The two densest eelgrass treatments showed no difference in OA mitigation possibly due to self-shading (Figure 2). Additionally, we found that eelgrass exposed to the dark, exacerbated OA (decreased pH) also up to a threshold density (Figure 3). In our pilot study, eelgrass mitigated OA for both pCO2 treatments but not differently (Figure 3). The similar mitigation of OA in both pCO2 treatments contradicts previous research which has established that eelgrass drawdown more carbon when exposed to higher pCO2 concentrations since eelgrass are carbon limited (Zimmerman et al. 1997). Our research shows that our pCO2 treatments resulted in an affect above intended values (Figure 2). Additionally, the light conditions we exposed our eelgrass were limiting (1.7 mol m-2 s-1) since light values were below saturating light conditions (7 mol m-2 s-1) for eelgrass (Thom et al. 2008). Therefore, the absent effect of pCO2 treatment could be because both of our pCO2 treatments relieved carbon limitations or that both pCO2 treatments were light limited. For spring 2017, we propose refining our methods to incorporate ecologically relevant pCO2 and light treatments. To improve our methods for our next experiment, we will decrease pCO2 concentrations to obtain ambient (400 ppm) and enriched (1400 ppm) pCO2 treatments. We will implement a system for reducing pCO2 concentrations which has been developed by the Puget Sound Restoration Fund (PSRF) for aquaculture research. The PSRF use Bio-Balls to filter organic matter from inflowing seawater and to increase the surface area of seawater to promote the outgassing of CO2. For our experiment, our seawater supply will permeate through Bio-Balls before flowing into our header tank to decrease the concentrations of our low pCO2 treatment (Figure 3).

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We will also increase the light conditions we expose our eelgrass to by moving our mesocosm set-up outdoors. Since light will vary diurnally, we will need to account for that by collecting continuous light measurements using a PAR sensor. Finally, we will measure the leaf area index (LAI) and the chlorophyll content of our eelgrass to compare changes in carbonate chemistry due to eelgrass to field populations of eelgrass because eelgrass populations vary greatly throughout the Salish Sea (Christiaen et al. 2016).

Figure 1. In our pilot study, eelgrass was exposed to light. Here we represent the effect of eelgrass density (0, 194.4, 583.1 and 971.8 shoots m-2) and pCO2 (moderate and high 944 ± 15 µatm and 3201 ± 79 µatm respectively (± SE)) on ∆pH Hr-1 and ∆pCO2 Hr-1. Letters represent post-hoc tests for differences between eelgrass density treatments. These data were measured using CO2 SYS data.

Figure 2. In our pilot study, eelgrass was exposed to the dark. Here we represent the effects of eelgrass densities (0, 194.4, 388.7, 583.1, and 777.5 shoot m-2) on the change in pH per hour for eelgrass exposed to moderate pCO2 (944 ± 15 µatm). Letters represent post-hoc tests for differences between eelgrass density treatments. These data were measured using a pH glass electrode. Purpose To experimentally test how eelgrass density, light and pCO2 interact to modify carbon uptake of eelgrass, we will use a mesocosm system to inform a mathematical model that includes these factors to predict areas of eelgrass that mitigate ocean acidification.

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Methods Mesocosm Set-Up

Ø CO2 enrichment system: We have constructed a CO2 delivery mesocosm set-up outlined by Jokiel et al. (2014) to obtain the separate pCO2 treatments (Figure 3). We will add an additional Bio-Ball filtration system to our seawater supply to run in concert with the current CO2 delivery mesocosm set-up. Our ambient seawater supply is currently being pumped in from Guemes Channel into an overflowing header tank that diverts the flow into gravity-fed mesocosms. Half of our mesocosms will be enriched with CO2 using a continuous supply of CO2 gas that is regulated by a peristaltic pump (EW-07522-20 Masterflex L/S Digital Drive). The desired level for the elevated pCO2 treatment is achieved by adjusting the speed of the peristaltic pump relative to the flow rate of water into the mesocosms. Once regulated, the CO2 gas bleeds into the intake of a Marineland Maxi-jet 900 powerhead pump where the gas undergoes complete dissolution. A magnetically driven impeller breaks up the CO2 gas into miniscule bubbles driving its diffusion into the water column due to the greater surface area of CO2. The other 8 mesocosms will be set up in an identical way, except without the CO2 gas input. The Bio-Ball system will help to alleviate abnormally high concentrations of pCO2 in mesocosms without CO2 gas input. Once pCO2 treatments have reached an equilibrium, the flow-through seawater will be halted so that changes in carbonate chemistry are due to eelgrass photosynthesis. We will also avoid water temperature increases by placing mesocosms inside a coozy tank with constant flow-through seawater.

Figure 3. CO2 delivery system outlined by Jokiel et al. (2014) for obtaining different pCO2 treatments.

Ø Leaf Area Index (LAI) manipulations: I will excavate adult eelgrass shoots with intact rhizomes by hand from Padilla Bay, WA in spring 2017. The collected eelgrass shoots will be immediately transported to SPMC in Anacortes, WA and rinsed in 15 ppt seawater for one hour to eliminate clinging epifauna and reduce any presence of wasting disease (Carr et al. 2011). Shoots will be placed in an outdoor holding tank for a one-week acclimation period in ambient flowing seawater. Experimental shoots will have rhizomes which are 5 cm long.

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We will manipulate different leaf area index (LAI) treatments based on data collected in the field data and place them in separate mesocosms for the duration of the experiment (Figure 4). At the end of the experiment, we will measure eelgrass shoot morphology. To calculate total leaf area, 20 eelgrass shoots will be haphazardly sampled from each experimental chamber to record sheath widths and individual leaf. The LAI is calculated by dividing the total leaf area by the total ground area. The 20 subsamples of eelgrass will be resampled to estimate total LAI for experimental chambers containing more than 20 eelgrass shoots (Figure 4).

Ø Light manipulations and diurnal variation: We will create two separate light treatments by reducing light conditions (by approximately 50%) using mesh screens in half of our mesocosms and exposing the other half to saturating light (0% shading) (Figure 4). Eelgrass will be exposed to our light treatments for 5 hours (Figure 4). The experiment will continue after sunset for an additional 3 hours in a period of darkness. Since light varies diurnally, continuous light measurements will be collected using an Odyssey PAR logger where measurements will be taken every 10 seconds. Light within the eelgrass canopy can also vary depending on the LAI of eelgrass. Therefore, hourly photosynthetic active (PAR) measurements will be taken using a QSL-100 irradiance sensor placed within the eelgrass canopy (Figure 4). Measurements

Ø Water chemistry: Hourly in situ pH and water temperature will be taken for each experimental chamber. We will measure pH and temperature using a Thermo Scientific A221 pH probe inserted through a small opening in the experimental chambers. pH probe data will be used to describe trends in data and not to quantify changes in carbonate chemistry due to eelgrass. To supplement hourly measurements, water samples for dissolved inorganic carbon (DIC) and pH will be taken 4 times over the duration of the experiment. We will take water samples at the start of the experiment, at the end of exposing eelgrass to light and again at the beginning and end of exposing eelgrass to the dark to quantify changes in carbonate chemistry. We will collect DIC samples using a 10-ml syringe and fill 6 ml scintillation vial bottom-up and overflowing the vial to prevent head space. 10 µl additions of HgCl2 will be added to capped DIC samples and then refrigerated at 2 C. Dissolved inorganic carbon samples will be analyzed the following two days of their collection using an Apollo SciTech AS-C3 DIC analyzer. pH samples will be collected using a 30-ml syringe and filling 20-ml scintillation vial using similar methods as described for DIC. We will immediately place pH samples in a water bath for 40 minutes at 25 oC. pH samples will be analyzed using a spectrophotometer (Agilent 8453A UV-VIS) and we will record water temperature using a Fluke 1523 reference thermometer and probe. Three pH measurements will be taken per sample and 30 µl m-cresol dye is added to the sample between each measurement as an indicator of pH (Clayton and Byrne, 1993). DIC and pH measurements will be used to calculate associated carbonate system parameters, change in aragonite saturation state (DWAr), change in the partial pressure of CO2 (DpCO2) and change in total alkalinity (DTA), using CO2 SYS (Pierrot et al. 2006) with K1 and K2 equilibrium constants from Mehrbach et al. (1973) and refit by Dickson and Millero (1987). CO2 SYS data will be used as our most accurate method in quantifying changes in carbonate chemistry due to eelgrass.

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Ø Chlorophyllandbiomassmeasurements: I will normalize my results by chlorophyll content and above ground biomass to relate these measurements to LAI values. We will conduct a chlorophyll analysis outlined by Lorenzen (1966) to evaluate photosynthetic responses at different light and pCO2 levels directly after the experiment. We will measure chlorophyll content by extracting 20% of shoots from each experimental chamber and rinsing them in 5% phosphoric acid to remove epiphytes. Whole shoots will be blended and placed in light proof containers of 90% acetone (v/v) for approximately 24 hours. We will vortex 2 duplicate samples taken from whole shoots for 5 minutes at 3000 rpm (Fisher Scientific Vortex Mixer) and decant the liquid into a fluorometer cuvette. We will measure absorbance using a chlorophyll fluorometer (Turner 10_AU). Two chlorophyll measurements will be taken before and after the addition of at least two drops of 1 N HCL to the chlorophyll sample. Chlorophyll content will be calculated using equations from Dennison (1990). Aboveground biomass will be collected at the end of experimentation following the methods outlined by Short and Duarte (2001). Once the LAI’s are measured, we will separate aboveground biomass from belowground biomass at the first rhizome internode and we will remove epiphytes from leaf surfaces. Whole plants will be placed in paper bags and dried in an oven (Fisher Scientific Isotemp 500 series) at 60 oC for at least 24 hours. Dry weights for each plant will be measured using a Mettler Toledo XS205 scale. Statistical Analysis We are expecting nonlinear trends in our data and plan to address this by using a Generalized Linear Mixed Model (GLMM) to depict the shape of the functional response. We will test the effect of leaf area index (LAI), pCO2 and light (PAR) on the changes in pH and DIC. Time and tank will be included as random factors in the model and we will evaluate which of our explanatory variables (LAI, pCO2, and PAR) are significant predictors for quantifying changes in pH and DIC in the experiment. Our model will be parsed based on Akaike’s Information Criterion (AIC) to determine the most parsimonious model. We will also evaluate the relative influence of individual contributing factors on changes in pH and DIC by extracting average rates for each explanatory variable from our model. Repeated experimental trials will be conducted to further validate our model. Research Design To assess the effect of pCO2 on eelgrass’ ability to alter carbonate chemistry, 2 pCO2 treatments, ambient pCO2 and enriched pCO2 (400 ppm and 1700 ppm respectively) will be applied to an array of 16 randomized acrylic tanks containing 40L of seawater (Figure 3). Within each pCO2 treatment, half of the tanks will be maintained under a saturating irradiance treatment and the remaining tanks will be maintained under a half-saturating light treatment (Figure 4). After 5 hours of light exposure, all tanks will be maintained in the dark for 3 hours after sunset (Figure 4). Four assemblages of eelgrass of varying LAI will be placed in individual mesocosms. We will manipulate LAI by creating four eelgrass density treatments (0, 20, 60, & 100 shoots per mesocosm) which corresponded to LAI values of (0, 2, 7, 11). LAI treatments will be assigned haphazardly to mesocosms for each pCO2 treatment and each light treatment. Seawater and CO2 delivery will be halted so we can measure the direct change in carbonate chemistry due to eelgrass. Recirculating pumps will continue to allow the seawater to encounter leaf surfaces. Seawater will be circulated at 870 L hr-1 to homogenize the carbonate chemistry within each experimental chamber.

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Figure 4. Experimental design for our mesocosm study manipulating treatments (see legend) for leaf area index (LAI), pCO2 and irradiance. Of the 16 total mesocosms, 8 will receive enriched pCO2 and 8 will receive ambient pCO2. Within each pCO2 treatment, 4 different LAI treatments will be assigned to individual mesocosms. After 5 hours of exposure to light, the mesocosms will be monitored for 3 hours after sunset. Anticipated Results If we move our experiment outside to solve the issue of limiting light and account for the diurnal variation of light, I expect to observe bigger and more accurate changes in the carbon drawdown of eelgrass due to light. The change of carbon drawdown due to pCO2 will most likely generate a smaller change in carbon drawdown. The refined experiment could perhaps, lead to similar results found in our past pilot studies (Figure 1 and 2) except, saturating light conditions and lower pCO2 conditions could also elucidate the lack of pCO2 effect in our preliminary studies. The effect of eelgrass LAI is expected to be like our preliminary studies as well (Figure 1 and 2). Eelgrass will most likely reach a threshold for their rate of carbon drawdown where self-shading at higher LAI treatments will inhibit further mitigation of OA. Eelgrass placed in the dark are expected to decrease pH linearly with increasing LAI. Overall, I expect refining my methods to incorporate ecologically relevant light and pCO2 treatments will help us apply our model to assess areas of eelgrass that are capable of mitigating ocean acidification throughout the Salish Sea. Schedule Our experiment will be conducted over a weekend near the end of May. Eelgrass shoots will be collected prior to the experiment and allowed to acclimate at SPMC for one week. The experiment itself will take roughly 8 hours but data processing will continue throughout the following week. Carbonate chemistry samples (pH and DIC) will be analyzed the following 2 days of the experiment since pH measurements are time sensitive. Chlorophyll extractions will be collected and stored immediately after the experiment and analyzed within the following week. Aboveground biomass will be dried after the quantification of LAI and weighed within the following week.

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Project Budget

Supplies and Equipment Requested: 20 lbs food grade CO2 tank 15.23 Shelving unit 169.00 Odyssey PAR logger 217.00 PVC/gutters 30.00 100' Tygon Tubing 25.00 90% Acetone (v/v) 29.58 (2) Marineland Maxi-Jet 900 PRO Water Pumps 70.58 Total $556.39

Funded Items (DNR IAA grant): Supplies and Equipment Required:

CRM standards for DIC analyzer $200 20 lbs food grade CO2 tank 15.23

m-Cresol Dye for spectrophotometric pH $81.80 Shelving unit 169.00 Marineland Maxi-Jet 900 PRO Water Pumps $35.29 Odyssey PAR logger 217.00

200' Vinyl Tubing $50.00 PVC/gutters 30.00

(20) Nylon Hose Barbs (5/16' ID) $25.24 100' Tygon Tubing 25.00

(40) Nylon Hose Barbs (1/4' ID) $50.24 90% Acetone (v/v) 29.58

200' CO2 feed tubing $512.11 (2) Marineland Maxi-Jet 900 PRO Water Pumps 70.58

(2) Power strips $16.83 CRM standards for DIC analyzer 200.00

Shed $341.91 m-Cresol Dye for spectrophotometric pH 81.80

(16) Power Head Pumps $564.64 Total $838.19

Cole-Parmer Persistaltic Pump $1,418.11 20 lbs CO2 Tank $15.23 Total $3,311

*If the full amount of the proposed budget is not funded, we plan to salvage old tubing, PVC, gutters and power head pumps.

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Francisco Bay: role of light availability on metabolism, growth and survival. Aquatic Botany 51:67-86. Zimmerman RC, Kohrs DG, Steller DL, and Alberte RS. 1997. Impacts of CO2 enrichment on

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