Lessons learned from collaborations between the shellfish industry and academia in the Pacific Northwest.

Transcription

1 (and many others) Lessons learned from collaborations between the shellfish industry and academia in the Pacific Northwest. Burke Hales, George Waldbusser, Iria Gimenez, Elizabeth Brunner, Stephanie Smith College of Earth, Ocean and Atmospheric Sciences Oregon State University Andy Suhrbier PCSGA Dick Feely, NOAA- PMEL Jan Newton, UW- APL, WOAC

2 Background: Ocean acidification and bivalves. 1. Atmospheric CO 2 is higher now, and is rising faster, than at any time in the last ~million years 2. This rise is the result of human emissions of fossil CO 2 3. ~25% of the human emissions are now in the ocean 4. CO 2 added to water causes a series of rapid reactions that increase pco 2, decrease ph, and decrease carbonate mineral stability (Ω). 5. Calcifying organisms, particularly bivalves, have negative response to the effects of rising CO 2, particularly Ω and at modern levels. 6. Natural and anthropogenic depletion of Ω are additive, and coastal settings are subject to a variety of natural exacerbations.

3 Interruption: WTF is Ω? Ω is a property of seawater that tells whether or not conditions are favorable for making shells out of calcium carbonate. When Ω > 1, the water favors shell formation. When Ω < 1, it favors shell dissolution. Shell- formers do better when Ω >> 1. Shell- formers do worse when Ω approaches 1, and worse still when Ω < 1. Acidification makes Ω lower, reducing favorable conditions for shell formers.

4 Background: Ocean acidification is not ph alone, and ph alone is insufficient for assessing OA The ph problem. ph is: 1. Easy to observe but difficult to interpret; 2. Prone to noise that is larger than the meaningful signal; 3. Subject to environmental biases; 4. Rarely a driver of responses; 5. Only an indicator, and an imperfect one, of actual conditions.

5 Carbonate chemistry responds in multiple ways to perturbation. Carbonate chemistry covariance: Single- factor manipulation (e.g. CO 2 bubbling or mineral acid/base addition) drives multiple factors to co- vary. What really matters? Ω, pco 2, ph co- variance for fixed T, S, Alk.

6 The Pacific Bivalve Story Coastal bays recently began experiencing natural and hatchery larval production failure in 2007, dubbed the Pacific Seed Stock Crisis. Support for collaboration between academia, industry, and professional organizations led to the identification of OA as a contributor, and subsequent mitigation strategies. See Barton et al for story. WCSH- OSU collaboration found larval success was determined by Ω in spawn water, with less sensitivity to ph. See Barton et al for story. But Is it really Ω, considering other covarying factors? Are there effects that can be seen in the wild?

7 Is it Ω? Is it really Ω? Lots of other stuff going on Need an experimental method to de- couple the carbonate chemistry

8 Is it Ω? Experimental results for growth of normally- developed larvae No effect of pco2 over µatm! No effect of ph over ! (apparent trend is all Ω) Clear, strong Ω effect. Two cohorts of each of two species! Waldbusser et al., 2015a

9 Is it Ω? Do native species respond differently than introduced/naturalized species? Waldbusser et al. 2015b Nope. Appears to be a ubiquitous response of planktonic- larval bivalves

10 Is it Ω? PCO2 = 412 Omega = 0.77 ph = 7.77 PCO2 = 368 Omega = 3.02 ph = 8.09 PCO2 = 2876 Omega = 0.94 ph = 7.39 PCO2 = 2758 Omega = 3.81 ph = 7.70 Oh yeah, it s Ω Imaging by Brunner

11 Are there quantifiable impacts in the wild? Natural- Setting Willapa Bay and OA 2 nd - largest estuary on US Pacific coast (670 km 2 ) 50% of area is intertidal Fed by >8 small mountainous rivers driven mostly by rainfall. Immediately N of Columbia River, which mostly flows to the N during winter. One of the few bays to maintain a naturally reproducing population of non- native C. gigas. Home to protected broodstock reserves, the parent Nahcotta Columbia River stock for hatchery and experimental subjects. Has been without good natural oyster set in last ~7 years. Estuarine circulation and productivity lead to a fattening line near Nahcotta Good CO 2 monitoring began in 2011.

12 Are there OA impacts in Willapa Bay? The few relevant ecological time- series show lots of variability before OA could have been a perturbation Dumbauld et al. JSR 2011 Limitations in measurement ability mean no valid carbonate chemistry measurements for this entire record Good monitoring started in 2011! Observational data limitations; historical variability that is hard to ascribe to OA.

13 Willapa Bay: Four years of PCSGA sample- collection, OSU analysis a) Temperature C spawning/ survival threshold Fundamental measurements: Temperature. Experiences thermal optimum centered on mid July b) Salinity c) TCO2 (µmol kg -1 ) d) PCO 2 (µatm) /1 3/1 5/1 7/1 9/1 11/1 Day of year Salinity. Asymmetric maximum, centered on early September TCO 2. Looks kind of like Salinity PCO 2. Looks noisy Hales et al. 2016, Estuaries and Coasts

14 Willapa Bay: Four years of CO 2 chemistry at the Fattening Line a) Alk (µmol kg -1 ) b) ph t c) Ω ar Acute Ω- effect threshold /1 3/1 5/1 7/1 9/1 11/1 Day of Year Chemical coupling breaks down in this environment! ph doesn t matter, and is a poor indicator of what does! Calculated parameters: Alkalinity. Looks even more like S ph. Noisy early in the year, seeming downward trend through summer. Ω ar. Noisy, esp early in the year, but seems to have rising trend through summer with early September maximum. ar Hales et al. 2016, Estuaries and Coasts ph t PCO 2 (µatm)

15 Willapa Bay: Pacific Oysters and Carbonate Chemistry Thermal optimum Modern Ωoptimum /1 7/1 9/1 11/1 Date 1. Oysters require favorable conditions in both Ω and T, but, 2. Ω and T optima are not synchronous. a. Ω windows are shorter and b. Shifted later in the year Hales et al. 2016, Estuaries and Coasts

16 Ω ar Willapa Bay: What is the role of rising CO 2? 1/1 3/1 5/1 7/1 9/1 11/1 Day of Year Thermal optimum Modern Ωoptimum Pre-industrial Ωoptimum The Result: pre- industrial Ω is overall higher, as expected. Greatest pre- industrial enhancement is in the early season would have been good years;?? would still have been lousy. 5/1 7/1 9/1 11/1 Date Hales et al. 2016, Estuaries and Coasts

17 Willapa Bay: Can we estimate frequency of favorable conditions? a) TCO 2 (µmol kg -1 ) b) Alk (µmol kg -1 ) d) Alk/TCO 2 c) Ω ar Property- Salinity coherence suggests a mixing- controlled system modified by warming and productivity. Can we model this in a simple way? Hales et al. in prep Salinity

18 Bay mouth box heating Willapa Bay: A simple box model. Mid- bay Fattening Line box Upper bay box Assumed to track the inner- shelf ocean; dynamics are prescribed to match seasonal upwelling Fast exchange NCP The one we care about. Dynamics set by exchange between upper and mouth boxes, heating, and productivity Slow exchange River input. Fast in spring, tapers off in summer, jumps again in fall Hales et al. in prep

19 Willapa Bay: A simple model. d) PCO c) TCO2 (µmol kg -1 2 (µatm) ) b) Salinity a) Temperature observations Model How did we do? Mostly not bad. What can we do with this? Perform Monte- Carlo analysis assuming independent random variability of upwelled endmember, initial ocean conditions, maximum heating and NCP terms, assuming Gaussian distributions in each. Repeat analysis for system corrected for C anth - absent conditions. 1/1/12 4/1/12 7/1/12 10/1/12 Date 2012 Hales et al. in prep

20 Frequency of occurrence Willapa Bay: A simple statistical model. 86% of modern simulations show 0 days of optima overlap 59% of pre- industrial simulations show 0 days of optima overlap Good days, modern Good-days, Atmospheric CO 2 = 300 ppm Frequency of occurrence % of pre- industrial simulations show >20 days of optima overlap Days with thermal- optima overlap Hales et al. in prep Days with thermal- optima overlap 13% of pre- industrial simulations show >20 days of optima overlap

21 Conclusions 1. Shell- mineral stability (Ω) is the leading factor determining larval bivalve sensitivity to OA, and is proximal today. This is a NOW problem that was only uncovered through industry- academia collaboration. 2. Full constraint of carbonate chemistry is essential for interpretation of the ecological record, and has only recently become feasible because of initial PCSGA- OSU collaboration. 3. Thermal optima in Willapa Bay are not synchronous with Ω optima, leaving a small and shrinking window of opportunity for settlement. 4. The impact of anthropogenic CO 2 is disproportionately greater in the early stages of the thermal optima, and is the cause of the asynchrony. 5. There appear to have always been bad years in Ω- T space, but good years had a ~40% pre- industrial probability; ~13% modern.