methods and challenges in ocean acidification monitoring
TRANSCRIPT
Methods and Challenges in Ocean Acidification Monitoring in Puget Sound
KING COUNTY MARINE MONITORING
METHODS
WHAT ARE SOME CHALLENGES? WHY MONITOR OCEAN ACIDIFICATION? Ocean acidification (OA) refers to the process of oceans absorbing increasing CO2 from
the atmosphere, resulting in decreased pH and potentially corrosive conditions to
organisms like shellfish. In late 2015, the marine monitoring program at King County added
OA indicators in order to begin to understand baseline conditions and trends in in Central
Puget Sound (King County, 2015), and contribute to sound-wide efforts. This region can be
particularly vulnerable due to processes such as upwelling of high CO2 Pacific waters that
enter Puget Sound, as well as inputs of local nutrients and organic matter that can
potentially exacerbate the problem (Feely, et al., 2010). Also, pH is a key property due to
impact on rates of chemical reactions and thresholds of biological toxicity, such as
changing toxicity of ammonia to fish and crustaceans with changing pH, with higher
vulnerability at larval and juvenile stages (Eddy, 2005).
R/V Sound Guardian
King County Marine Monitoring Webpage and data access:
http://green2.kingcounty.gov/marine
Stephanie Jaeger King County Dept. of Natural Resources and Parks, Seattle, Washington
Offshore Waters
Sampled bi-weekly at
14 sites (monthly Jan &
Dec)
Full CTD profiles
(temperature, salinity,
density, DO,
fluorescence, PAR,
transmissivity, nitrate)
Discrete samples for
dissolved nutrients
(ammonia,
nitrate+nitrite, silica,
orthophosphate),TSS,
fecal indicator bacteria,
chlorophyll-a
Beach Waters
Sampled monthly
Analyzed for dissolved
nutrients, fecal
indicator bacteria,
temperature, and
salinity
Moorings
Near-surface depths
(1 to 10m) at 4 sites
Temperature, salinity,
dissolved oxygen,
fluorescence, turbidity,
and pH
SeaFET pH at 2 sites,
SUNA nitrate at one
site, Met station at two
sites
Discrete samples for
total alkalinity and
dissolved inorganic
carbon (DIC) at 2 sites
Phytoplankton
Sampled bi-weekly at
10 sites (monthly Jan
& Dec)
FlowCAM analysis of
10-300 µm size range
Species list for each
sample compiled by
microscopy Zooplankton
Sampled bi-weekly at
3 sites (monthly Jan &
Dec)
Full water column
vertical tows and
Bongo net tows
SUMMARY
In partnership with the UW Northwest Environmental Moorings and PMEL Carbon Groups, total alkalinity
and DIC collection and preservation methods were compared in August 2016 at the Point Wells ORCA
mooring, in order to ground truth an alternative method. Three treatments completed at three depths:
RESULTS
Mean and one std. deviation of total alkalinity and DIC results by
treatment method and depth (n = 3). No significant difference between
each method (p = 0.5 and 0.4; respectively); however, in general, more
variability is observed in the filtered and delayed poisoning method.
Salinity vs. measured total alkalinity for all samples (n=76). Red dots are from a nearshore site in inner
Quartermaster Harbor, near creek drainages. Blue triangles are from Pt. Williams and Pt. Wells in the
Central Basin. The black line represents the equation derived in the Fassbender study.
Components
currently used for
OA indicators
• In-situ moorings measure pH and
other variables at 15-minute
intervals.
• Total alkalinity and DIC collected
monthly supplement and quality
control pH data, analyzed by the
PMEL Carbon Group at NOAA
following the methods of Dickson et.
al (2007).
• King County Environmental Lab
prohibits use of mercury, so
alternative preservation is used.
• Samples filtered (0.45 µm) using a
peristaltic pump from a Niskin bottle,
following Bockmon and Dickson
(2014) methods, and later poisoned
with mercuric chloride at PMEL to
extend holding times.
• External pH data from the SeaFET
corrected with salinity, as internal pH
has been more susceptible to
biofouling
• Mooring pH is corrected by
calculated total pH (derived from
TA/DIC samples) if needed,
preferably during well-mixed
conditions (Bresnahan et. al, 2014).
Inner Quartermaster Harbor
on Vashon Island, one of the
OA monitoring sites.
Location of offshore marine program stations in the
Central Basin. OA monitoring sites are starred.
Retrieval of the
Quartermaster Harbor
SeaFET instrument.
Preparing the zooplankton
bongo net tow, pictured with
the CTD rosette.
I. Prior to characterizing long-term trends in pH such as due to processes like ocean acidification, it is
important to understand the uncertainty of pH measurements and the variability on short time scales, such
due to interplay of photosynthesis and respiration.
Accurately measuring pH is limited by (Bresnahan, et al., 2014).:
• Initial calibration approach and quality of validation samples
• Sensor performance, conditioning and drift
• Quality of auxiliary measurements (e.g. temperature and salinity)
II. In order to better understand OA dynamics and ecosystem impacts, it is important to measure other
carbonate parameters besides pH alone (Newton, et al., 2015). The biological process of shell formation of
organisms like shellfish is related to the aragonite saturation state (ΩAragonite). Values less than one indicate
this mineral has a higher potential to dissolve, with some variability based on species and habitat distribution.
E.g., the concentration of human-caused CO2 has been linked to the dissolution of one species zooplankton
(pteropods) off the Pacific coast (Feely et al., 2016). In order to derive ΩAragonite, at least two properties of the
carbonate system must be characterized.
OBJECTIVE 1: HOW DO ALTERNATIVE SAMPLE PRESERVATION
METHODS COMPARE?
OBJECTIVE 2: CAN SALINITY BE USED TO EMPIRICALLY DERIVE TOTAL
ALKALINITY IN CENTRAL PUGET SOUND?
OBJECTIVE 3: CAN THIS LEAD TO IMPROVEMENTS IN PH TIME
SERIES AND UNDERSTANDING CARBONATE DYNAMICS?
ORCA water column profiles at Pt. Well on 8/8/2016.
Solid lines show profiles after TA/DIC water sampling;
dotted lines show earlier profiles. Green diamonds
show discrete salinity results and sample depths.
1) No filter and samples immediately poisoned
with HgCl2 after collection (most common
method)
2) Filtered (0.45 µm) and 24-hour delay in
poisoning with HgCl2 upon arrival at PMEL lab
(King County method)
3) Filtered and immediately poisoned with HgCl2
Results: All methods fall within ± 2 µmol/kg specification for both DIC and total alkalinity, with the exception
of the 90-m total alkalinity samples with the filtered and delayed treatment (± 4 µmol/kg). The relative std.
deviation for all samples is < 0.2%. Organic matter can contribute to alkalinity, and may lead to some
differences between the filtered and unfiltered samples, though not significantly shown here. • If possible, best to directly measure at least two properties of the carbonate system to
understand ocean acidification (OA)
• In lieu of a 2nd carbonate property, it is possible to empirically derive other OA indicators, as
long as measurement errors are minimal and data are carefully quality controlled and
validated with water samples
• The alternative filtration method may be used, as long as samples are preserved with HgCl2 in
a reasonable timeframe. Replicate samples are recommended for better accuracy.
• Further work is needed prior to using a different preservative such as ZnCl2
• Empirically-derived total alkalinity results support the Fassbender study (2016) but further
stresses the need for a different calculation at low salinities (<26 PSU)
• More work is needed in order to successfully predict aragonite saturation state in Central
Puget Sound, with the goal of using as a gauge of ocean acidification impacts to local species
and ecosystems
REFERENCES
Only one in-situ carbonate variable (pH) is currently measured, so exploring whether a 2nd variable can be
derived is central to understanding OA dynamics like aragonite saturation state. All of King County’s discrete
salinity results are compared to total alkalinity (TA) samples analyzed by PMEL, and compared to the empirical
salinity/TA relationship shown by Fassbender et. al (2016).
Results: This comparison follows a similar pattern to the Fassbender study, where the tightest relationship
between salinity and TA occurs at salinities > 26 PSU. This suggests the need for development of a stepwise
relationship for lower salinities commonly found in Puget Sound. Also, the median residual between measured TA
and empirical TA for the higher salinity samples is -14 µmol/kg, which may be attributed to different collection
methods, where filtration can remove some of the organic alkalinity component to TA.
Residuals are
calculated from
measured TA minus
empirically-derived
TA, where negative
values indicate that
the measurements
are lower than
predication by the
TA/S relationship.
Dotted lines show
± 2σ for all data.
Beach site on Vashon Island, looking over Puget Sound (S. Jaeger) King County’s Point Williams monitoring buoy in Central Puget Sound near Lincoln Park
Example of time series at Point Williams mooring (1m) from Sept. – Nov.
2016. Temperature, salinity, and DO are from a YSI 6600 V2 sonde co-
located with a SeaFET instrument. In the bottom panel, Ωaragonite (blue) Is
empirically derived from external pH and salinity. Error bounds (pink) are
calculating assuming a combined error up to ±0.02 pH and ±30 µmol/kg
total alkalinity uncertainties.
Zooming in to one-week of the time series at Point Williams in
mid-October, when multiple methods were used for pH water
sample analysis on Oct. 18. External pH (salinity corrected) falls
within 0.02 pH of all the water samples, while internal pH has
drifted out of spec, likely due to biofouling. Note also the large
error bounds in derived Ωaragonite.
.
Data collected at 15-minute intervals at moorings is helpful for
understanding temporal dynamics in the carbonate system,
where daily and seasonal swings in pH can far exceed
changes in long-term trends. One goal is to use existing data
to empirically calculate Ωaragonite, an ecologically-relevant OA
indicator.
Results: Initial results capture fluctuations and patterns in pH
and Ωaragonite over time; however, more work is needed to
understand uncertainties in these relationships. For example,
a measurement error of -0.02 pH and -30 µmol/kg TA leads
to close to 0.1 Ωaragonite error, which could push the
calculation below the threshold of 1, and may not represent
natural conditions.
• Bockmon & Dickson (2014). Limnol. and Oceanogr: Methods, 12, 191-195.
• Bresnahan, Martz, Takeshita, Johnson, & LaShomb. (2014). Methods in Oceanography, 9, 44
- 60.
• Dickson, Sabine, & Christian (Eds.). (2007). PICES Special Publication 3:191.
• Eddy. (2005). Review, J. of Fish Biology, 67(6), 1495-1513.
• Fassbender, Alin, Feely, Sutton, Newton, & Byrne (2016). Estuaries and Coasts, 1-15.
• Feely, Alin, Newton, Sabine, Warner, Devol, et al. (2010). Estuarine, Coastal and Shelf
Science, 88, 442-449.
• Feely, Alin, Carter, Bednarsek, Hales, Chan, Hill, et. al (2016). Estuarine, Coastal and Shelf
Science,183, 260-270.
• Newton, Feely, Jewett, Williamson, & Mathis. (2015). Global Ocean Acidification Network:
Requirements and governance plan. 2nd ed., GOA-ON.
Acknowledgments: Data from the Point Wells ORCA mooring provided by W. Ruef and the UW Northwest Environmental Moorings
Group. Thanks for B. Krueger, D. Hutchens, and D. Robinson from KCEL for all the field sampling. Thanks to the PMEL Carbon Group for
lab sample analysis. Thanks to A. Fassbender for helpful discussion about impacts on total alkalinity and salinity relationship.