Supplementary material to “Coastal Acidification by Rivers: A New Threat to Shellfish?”
Joseph Salisbury, Ocean Processes Analysis Laboratory, University of New Hampshire, Durham
Mark Green, Saint Joseph's College, Standish, Maine
Chris Hunt and Janet Campbell, Ocean Processes Analysis Laboratory, University of New Hampshire, Durham
Citation:
Salisbury, J., M. Green, C. Hunt, and J. Campbell (2008), Coastal acidification by rivers: A new threat to shellfish?, Eos Trans. AGU, 89(50), 513. [Full Article (pdf)]

-Figure 1. Seawater for calcification experiments was collected from Casco Bay, Gulf of Maine and passed through a 0.45 µm filter. Solutions of three distinct saturation states (Ω = 0.5, 1.6, 2.0) were made by bubbling seawater with 5% CO2, balance N2 gas to the required pH (seawater alkalinity 2.21 meq. L-1, salinity = 31 ppt, temperature = 21°C). Experimental seawater of each saturation state was then transferred into each of three separate 80mL BOD vials, yielding triplicate samples of each saturation state. Larval Mya were added to each of the 9 vials using a pasture pipette so that final bivalve concentrations were approximately 25 mL-1. At 0, 2, and 4 hour intervals a 1mL sample was removed from each vial and alkalinity measured by titration after Edmond (1970). Carbonate ion (CO32-) concentration and saturation state with respect to aragonite was estimated using the CO2SYS program, the first and second dissociation constants of carbonic acid in seawater (Mehrbach et al., 1973 refit by Dickson and Millero 1987). Increases or decreases in alkalinity measures CO32- consumption or production during CaCO3 precipitation and dissolution, respectively.
Recent research has shown that juveniles of (Mya arenaria), experience significant increases in mortality when Ω values decrease and their aragonite shell dissolves (Green et al, 2004). Because many larval bivalve species initially precipitate their shell as amorphous calcium carbonate (considerably more soluble than aragonite, Brecevic, 1989) we presume here that planktonic bivalves are even more susceptible to dissolution than are the slightly larger, post-set individuals.

- We estimated Ω in the surface waters of Casco Bay (Figure 2) as [CO32- * Ca2+ ]/ Ksp, using the following methods: CO32- was estimated in C-SYS (Zeebe and Wolf-Gladrow, 2001) using measured partial pressure of CO2 and total alkalinity (TA), salinity and SST. Dissociation constants (pK1 and pK2) for carbonate parameter estimates here and below, are from Millero et al. (2006). Ca2+ was measured in the river and allowed to mix conservatively with an estimated oceanic endmember (Reilly, 1967). The aragonite solubility product (Ksp), was estimated as a function of temperature and salinity using the relationship of Mucci (1983). Ω was then mapped to a modeled salinity field (Xue, 2005) based on robust relationships between salinity and Ω that we derive for each cruise date.

- The curves in Figure 3a were produced as follows: We obtained long term mean data for Ca++, TA, pH and temperature for the world's large rivers from the GEMS-Glori database (Meybeck and Ragu, 1997). TA, pH and temperature were used as inputs into C-SYS to estimate carbonate parameters at each river endmember where 0 salinity was assumed. Carbonate parameters at the ocean endmember were also estimated in C-SYS using the following climatological data for the region directly adjacent to the seaward boundary of each plume:
- Surface pCO2 (Takahashi et al., 1997)
- NODC (Levitus) World Ocean Atlas 1994 gridded salinity and surface temperature data (http://www.cdc.noaa.gov/) and
- Modeled TA as a function of Levitus salinity and temperature using the relationship of Lee et al., (2006).
- Ca++ was determined using the salinity relationship in (Reilly, 1967) and allowed to mix conservatively with the river endmember. CO32- was scaled across the salinity gradient in C-SYS using endmember carbonate parameters at the mean annual plume temperature. Ω was then estimated as [CO32- * Ca2+]/ Ksp, using Ksp for aragonite from Mucci (1983).
Ω determined for the region of the Amazon River Plume, was mapped to salinity (Figure 3b). Salinity data shown in this figure are the minimum values from the monthly Levitus (1994) climatology. The plume extent (black contour) was estimated as the region of significant correlation (p < 0.01) between the Levitus monthly salinity climatology and the monthly hydrograph climatology of the Amazon and Orinoco Rivers (Hydrograph climatologies prepared by Dominic Wisser, UNH).
- Trends in the acid concentration of river water delivered to the ocean are spatially variable over continental scales. In recent decades, the significant shift in stream pH towards the acidic range throughout eastern Asia is correlated with an increasing trend in anthropogenic sulphate and nitrate deposition (Kondrat'ev, et al., 2007; Soni and Sarkar, 2006). Since the advent of the Clean Air Act Amendment of 1977 (http://www.epa.gov/air/caa/) acidity levels in precipitation and discharge in North America have decreased due to reduced sulfate emissions (Clow and Mast 1999, Murdoch and Shanley 2006). However, Clow and Mast demonstrated a lack of concurrent riverine alkalinity increase, indicating that the change in acidic deposition (less acidity) has been too low to affect alkalinity. Furthermore, recent work has shown a possible reversal in the declining trend of river acidity (Eschleman et al. 2008).
- Climate change scenarios based upon increasing atmospheric CO2 have predicted an intensification of the hydrologic cycle leading to a global increase in streamflow (Douville et al., 2002; Labat et al. 2004, Huntington 2006). However, forecasts point to variable streamflow conditions at the continental scale with significant regional increases and decreases predicted by mid century (Milly et al. 2005, Aerts et al. 2006). Runoff is the primary driver of both chemical weathering rate (Kump et al. 2000) and riverine chemical flux (Cai et al. 2008). Increased runoff has been shown to increase alkalinity yield from watersheds (Raymond and Oh 2007, Raymond and Cole 2003). Anthropogenic patterns of land use and fertilization will also alter mineral dissolution and fluxes of carbonate species germane to coastal acidification issues (Perrin et al., 2008, Oh and Raymond 2006).
- The area of continental shelf was estimated from the hypsographic curve as 7.1% of the ocean surface (Figure 4.1 in Thurman and Burton, 2001). This estimate does not include the area attributed to the continental slope. Global annual discharge is approximated as 30,000 km3 y-1, from Fekete et al., 2001.
- Concerning the statement about increasing discharge to the Arctic Ocean: The average annual discharge of fresh water from the six largest Eurasian rivers to the Arctic Ocean increased by 7% from 1936 to 1999 (Peterson et al., 2002). During that period discharge was correlated with changes in global mean surface air temperature, suggesting climate change as an important driver. In a sensitivity study, McLellen et al. (2004) considered dam operation, thawing of permafrost and increased fire occurrence, as well as climate change, as drivers of the increased discharge. Although each factor likely contributed to the observed changes, the authors concluded that increasing northward transport of moisture as a result of global warming was the most viable explanation for the observations.
- In reference to issues related to pteropods and ecosystem function, we note that these organisms are particularly threatened by ocean acidification because of the high solubility of aragonite and the fact that W is already low in cool Polar Oceans. Pteropods are unlikely to survive in waters that become undersaturated with aragonite (Orr et al., 2005). They function as an energy source in many ocean ecosystems. For example, in the Ross Sea, the subpolar-polar pteropod, Limacina helicina, can replace krill as the dominant zooplankton species in the ecosystem (Siebel and Dierssen, 2003). In polar and subpolar regions, pteropods are an important food source for a wide range of species, including North Pacific salmon, mackerel, (Armstrong et al., 2005; Willet et al., 2001; Boldt and Haldorson, 2003, Zavolokin et al., 2007), herring, cod, and large whales (Lalli and Gilmer, 1989).
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