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Chesapeake Bay acidification buffered by spatially decoupled carbonate mineral cycling

Nature Geoscience volume 13, pages 441–447 (2020)Cite this article

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Abstract

Uptake of anthropogenic carbon dioxide (CO2) from the atmosphere has acidified the ocean and threatened the health of marine organisms and their ecosystems. In coastal waters, acidification is often enhanced by CO2 and acids produced under high rates of biological respiration. However, less is known about buffering processes that counter coastal acidification in eutrophic and seasonally hypoxic water bodies, such as the Chesapeake Bay. Here, we use carbonate chemistry, mineralogical analyses and geochemical modelling to demonstrate the occurrence of a bay-wide pH-buffering mechanism resulting from spatially decoupled calcium carbonate mineral cycling. In summer, high rates of photosynthesis by dense submerged aquatic vegetation at the head of the bay and in shallow, nearshore areas generate high pH, an elevated carbonate mineral saturation state and net alkalinity uptake. Calcium carbonate particles produced under these conditions are subsequently transported downstream into corrosive subsurface waters, where their dissolution buffers pH decreases caused by aerobic respiration and anthropogenic CO2. Because this pH-buffering mechanism would be strengthened by further nutrient load reductions and associated submerged aquatic vegetation recovery, our findings suggest that the reduction of nutrient inputs into coastal waters will not only reduce eutrophication and hypoxia, but also alleviate the severity of coastal ocean acidification.

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Fig. 1: Distributions of water properties in the Chesapeake Bay in August 2016.
Fig. 2: Non-conservative carbonate system behaviour.
Fig. 3: Water chemistry and calcium carbonate precipitation in Susquehanna Flats SAV beds.
Fig. 4: Differential effects on pH from biogeochemical processes in the Chesapeake Bay.
Fig. 5: Conceptual model of the self-regulated pH-buffering mechanism in the Chesapeake Bay.

Data availability

The data presented in this study can be found in the NCEI Ocean Archive with accession number 0209358. Source data are provided with this paper.

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Acknowledgements

This work was supported by grants from the US National Oceanic and Atmospheric Administration (NA15NOS4780184, NA15NOS4780190 and NA18NOS4780179). We acknowledge the USGS, Maryland Department of Natural Resources and Virginia Institute of Marine Science (VIMS) for the monitoring data. We thank C. Hodgkins for assistance with the field work. This is University of Maryland Center for Environmental Science publication number 5821 and reference number UMCES CBL 2020-101.

Author information

Author notes

  1. Xiaohui Xie

    Present address: State Key Laboratory of Satellite Ocean Environment Dynamics, Second Institute of Oceanography, Hangzhou, China

Authors and Affiliations

  1. School of Marine Science and Policy, University of Delaware, Newark, DE, USA

    Jianzhong Su, Wei-Jun Cai, Jean Brodeur, Baoshan Chen, Najid Hussain, K. Michael Scaboo & Yuan-yuan Xu

  2. State Key Laboratory of Marine Environmental Science, Xiamen University, Xiamen, China

    Jianzhong Su & Minhan Dai

  3. Materials Science and Engineering, University of Delaware, Newark, DE, USA

    Yichen Yao & Chaoying Ni

  4. Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, MD, USA

    Jeremy M. Testa

  5. Horn Point Laboratory, University of Maryland Center for Environmental Science, Cambridge, MD, USA

    Ming Li, Xiaohui Xie, Wenfei Ni, Jeffrey Cornwell, Michael S. Owens & W. Michael Kemp

  6. St. Mary’s College of Maryland, St. Mary’s City, MD, USA

    Cassie Gurbisz

  7. College of Earth, Ocean, and Atmospheric Sciences, Oregon State University, Corvallis, OR, USA

    George G. Waldbusser

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Contributions

W.-J.C. was responsible for the design of the work. J.S. analysed the data. B.C. and J.M.T. co-led the cruises. B.C., J.S., J.B., N.H., K.M.S. and Y.-Y.X. were responsible for sample collection and analysis. Y.Y. and C.N. contributed to the mineralogical analysis. M.L., X.X. and W.N. contributed to physical mixing and particle transport. J.C. and M.S.O. contributed to the weight percentage of CaCO3. J.M.T., C.G. and G.G.W. contributed supplementary materials and data. J.S. and W.-J.C. drafted the manuscript. All authors contributed to discussion and revision of the manuscript.

Corresponding author

Correspondence to Wei-Jun Cai.

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The authors declare no competing interests.

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Peer review information Primary Handling Editors: James Super; Xujia Jiang.

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Extended data

Extended Data Fig. 1 Sampling sites during August 2016 cruise in the Chesapeake Bay.

Green areas show the coverage of Submersed Aquatic Vegetation (SAV) beds in the Chesapeake Bay in 2016 (http://www.vims.edu/bio/sav/maps.html). The upper, mid and lower bay (separated by the black lines) accounted for 16.4%, 64.0% and 19.6% of the total SAV coverage in 2016 (39,524 hectares). The arrow shows the outlet of the Susquehanna River. Red circles show the related locations of the four endmembers. Note that stations 82, 83, 85 and 87 are located further offshore in the Mid-Atlantic Bight and were visited during July 2015.

Source data

Extended Data Fig. 2 Carbonate system variations and bottom depths in the vicinity of the Susquehanna Flats in 2018.

The dashed line separates the western deep channel and eastern shallow flats, where SAV beds were present. The arrows show the cruise path. Sampling sites are labelled in the inserted maps. The SAV biomass was low in early June (a, c), but was high in early September (b, d) 2018. The Δ values in each station are relative to CB1.1, which was our uppermost station near the Susquehanna River mouth.

Source data

Extended Data Fig. 3 SEM images of CaCO3 precipitates on the leaf surface of Vallisneria americana collected from Susquehanna Flats in 2018.

a, semi-spherical crystallites; b, ellipsoidal crystallites; c, polycrystalline maze-like aggregates; d, aggregates with other materials; e, arborisation-like aggregates; f, rice-like aggregates. The atomic composition in Spectrum 32: 41.8% C, 18.4% Ca, 17.2% O, 10.5% K, 6.5% C, 1.9% Na, 1.6% S, 1.3% Mg, 0.8% P; Spectrum 27: 40.8% C, 25.2% O, 14.4% Ca, 9.2% N, 5.3% K, 2.4% Mg, 1.6% P, 1.0% Na; Spectrum 1: 42.9% O, 27.7% Ca, 25.4% C, 1.4% K, 1.2% Si, 0.9% Al, 0.2% Na, 0.2% Mg; sum spectrum in (e): 31.1% C, 29.9% O, 22.3% Ca, 4.6% Fe, 4.4% Si, 3.8% Al, 2.0% K, 1.9% Mg; Spectrum 13: 41.6% O, 38.1% Ca, 12.5% C, 3.7% K, 1.5% Cl, 1.1% Mg, 0.9% Si, 0.5% Na, 0.2% Al.

Source data

Extended Data Fig. 4 Effective concentration (C*) and removal (percentage) of TA and Ca2+ in the Chesapeake Bay in August 2016.

The fitting equation for TA (a) at salinity < =22 is C = 0.00002708×S6-0.00336738×S5+0.17376067×S4-4.6574875×S3+64.65219917×S2-344.24526458×S+1342.095396, whereas at salinity >22 the equation is C = 31.791176×S +1172.4787872. The fitting equation for Ca2+ (b) at salinity < =22 is C = -0.00001835×S6+0.00171504×S5-0.05591518×S4+0.67310609×S3-0.73633157×S2+265.9022229×S+368.4115086, while at salinity >22 the equation is C = 270.483366×S +740.833973. C* can be acquired by extending the derivative at any salinity to zero salinity in a concentration-salinity plot. The removal percentage at any salinity relative to freshwater input can be calculated via removal (%) = (C0-C*)/C0×100, where C0 means the concentration at freshwater end.

Source data

Extended Data Fig. 5 Numerical model simulation of the transport of fine particles from the Susquehanna Flats in the Chesapeake Bay.

The model simulates suspended sediment concentration (SSC) at surface, mid-depth and bottom water in the bay after the initial release of sediment particles (diameter = 2 μm) from all water depths on the Susquehanna Flats. SSC is shown on a logarithmic scale. The initial concentration is set as 0.5 kg m-3 over the Susquehanna Flats and the release time is on 00:00:00 May 31th, 2016. The output snapshots are the concentrations 1 hour, 1 day, 10 days, 30 days, 60 days and 90 days after the initial release of particles.

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Supplementary information

Supplementary Information

Supplementary Figs. 1–4 and Tables 1 and 2.

Source data

Source Data Fig. 1

Water property data for section plot.

Source Data Fig. 2

Cruise data, endmember values and deviation values.

Source Data Fig. 3

Sensor data, SEM images and CaCO3 content data.

Source Data Fig. 4

ΔpH for different biogeochemical processes.

Source Data Extended Data Fig. 1

Latitude and longitude of sampling sites.

Source Data Extended Data Fig. 2

Carbonate chemistry on the Susquehanna Flats.

Source Data Extended Data Fig. 3

SEM images and atomic composition of CaCO3 precipitates on the leaf surface.

Source Data Extended Data Fig. 4

TA and Ca2+ data in August 2016.

Source Data Extended Data Fig. 5

The full path of data repository for model simulation.

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Su, J., Cai, WJ., Brodeur, J. et al. Chesapeake Bay acidification buffered by spatially decoupled carbonate mineral cycling. Nat. Geosci. 13, 441–447 (2020). https://doi.org/10.1038/s41561-020-0584-3

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