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Archive for OA

Quantifying uncertainties in future projections of Chesapeake Bay Hypoxia

Posted by mmaheigan 
· Wednesday, December 4th, 2024 

Climate change is expected to especially impact coastal zones, worsening deoxygenation in the Chesapeake Bay by reducing oxygen solubility and increasing remineralization rates of organic matter. However, simulated responses of this often fail to account for uncertainties embedded within the application of future climate scenarios.

Recent research published in Biogeosciences and in Scientific Reports sought to tackle multiple sources of uncertainty in future impacts to dissolved oxygen levels by simulating multiple climate scenarios within the Chesapeake Bay region using a coupled hydrodynamic-biogeochemical model. In Hinson et al. (2023), researchers showed that a multitude of climate scenarios projected a slight increase in hypoxia levels due solely to watershed impacts, although the choice of global earth system model, downscaling methodology, and watershed model equally contributed to the relative uncertainty in future hypoxia estimates. In Hinson et al. (2024), researchers also found that the application of climate change scenario forcings itself can have an outsized impact on Chesapeake Bay hypoxia projections. Despite using the same inputs for a set of three experiments (continuous, time slice, and delta), the more commonly applied delta method projected an increase in levels of hypoxia nearly double that of the other experiments. The findings demonstrate the importance of ecosystem model memory, and fundamental limitations of the delta approach in capturing long-term changes to both the watershed and estuary. Together these multiple sources of uncertainty interact in unanticipated ways to alter estimates of future discharge and nutrient loadings to the coastal environment.

Figure 1: Chesapeake Bay hypoxia is sensitive to multiple sources of uncertainty related to the type of climate projection applied and the effect of management actions. Percent contribution to uncertainty from Earth System Model (ESM), downscaling methodology (DSC), and watershed model (WSM) for estimates of (a) freshwater streamflow, (b) organic nitrogen loading, (c) nitrate loading, and (d) change in annual hypoxic volume (ΔAHV). (e) Summary of all experiment results for ΔAHV, expressed as a cumulative distribution function. The Multi-Factor experiment (blue line) used a combination of multiple ESMs, DSCs, and WSMs, the All ESMs experiment (pink line) simulated 20 ESMs while holding the DSC and WSM constant, and the Management experiment (green line) only simulated 5 ESMs with a single DSC and WSM but incorporated reductions in nutrient inputs to the watershed. The vertical dashed black line marks no change in AHV.

Understanding the relative sources of uncertainty and impacts of environmental management actions can improve our confidence in mitigating negative climate impacts on coastal ecosystems. Better quantifying contributions of model uncertainty, that is often unaccounted for in projections, can constrain the range of outcomes and improve confidence in future simulations for environmental managers.

Figure 2: A schematic of differences between the Continuous and Delta experiments. In the Delta experiment a combination of altered distributions in future precipitation and changes to long-term soil nitrogen stores eventually result in increased levels of hypoxia (right panel).

 

Authors
Kyle E. Hinson (Virginia Institute of Marine Science, William & Mary)
Marjorie A. M. Friedrichs (Virginia Institute of Marine Science, William & Mary)
Raymond G. Najjar (The Pennsylvania State University)
Maria Herrmann (The Pennsylvania State University)
Zihao Bian (Auburn University)
Gopal Bhatt (The Pennsylvania State University, USEPA Chesapeake Bay Program Office)
Pierre St-Laurent (Virginia Institute of Marine Science, William & Mary)
Hanqin Tian (Boston College)
Gary Shenk (USGS Virginia/West Virginia Water Science Center)

A suite of CO2 removal approaches modeled for the 1.5 ˚C future

Posted by mmaheigan 
· Thursday, August 31st, 2023 

Carbon dioxide removal (CDR) is “unavoidable” in efforts to limit end-of-century warming to below 1.5 °C. This is because some greenhouse gas emissions sources—non-CO2 from agriculture, and CO2 from shipping, aviation, and industrial processes—will be difficult to avoid, requiring CDR to offset their climate impacts. Policymakers are interested in a wide variety of ways to draw down CO2 from the atmosphere, but to date, the modeling scenarios that inform international climate policies have mostly used biomass energy with carbon capture and storage (BECCS) as a proxy for all CDR. It is critical to understand the potential of a full suite of CDR technologies, to understand their interactions with energy-water-land systems and to begin preparing for these impacts.

Figure caption: Each of the six carbon dioxide removal approaches identified in recent U.S. legislation and modeled for this study could bring unique benefits and tradeoffs to the energy-water-land system. This image depicts afforestation, direct ocean capture, direct air capture, biochar, enhanced weathering, and bioenergy with carbon capture and storage in clockwise order. Floating carbon dioxide molecules hover above the landscape (image credit: Nathan Johnson, PNNL).

A recent study published in the journal Nature Climate Change was the first to model six major CDR pathways in an integrated assessment model. The modeled pathways range from bioenergy with carbon storage and afforestation (already represented by most models), also direct air capture, biochar and crushed basalt spreading on global croplands, and electrochemical stripping of CO2 from seawater aka direct ocean capture. The removal potential contributed by each of the six pathways varies widely across different regions of the world. Direct ocean capture showed the smallest removal potential but has important potential synergies with water desalination. This method could help arid regions such as the Middle East meet their water needs in a warming world. Enhanced weathering has much larger (GtCO2-yr-1) removal potential and could potentially help ameliorate ocean acidification. Overall, similar total amounts of CO2 are removed compared to other modeling scenarios, but broader set of technologies lessens the risk that any one of them would become politically or environmentally untenable.

Authors:
Jay Fuhrman  (Joint Global Change Research Institute)
Candelaria Bergero (Joint Global Change Research Institute)
Maridee Weber (Joint Global Change Research Institute)
Seth Monteith (ClimateWorks Foundation)
Frances M. Wang (ClimateWorks Foundation)
Andres F. Clarens (University of Virginia)
Scott C. Doney (University of Virginia)
William Shobe (University of Virginia)
Haewon McJeon (Joint Global Change Research Institute )

Twitter: @pnnlab @climateworks @uva

Unveiling the Past and Future of Ocean Acidification: A Novel Data Product covering 10 Global Surface OA Indicators

Posted by mmaheigan 
· Wednesday, August 23rd, 2023 

Accurately predicting future ocean acidification (OA) conditions is crucial for advancing research at regional and global scales, and guiding society’s mitigation and adaptation efforts.

As an update to Jiang et al. 2019, this new model-data fusion product:
1. Utilizes an ensemble of 14 distinct Earth System Models from the Coupled Model Intercomparison Project Phase 6 (CMIP6) along with three recent observational ocean carbon data products –>instead of relying on just one model (i.e., the GFDL-ESM2M) this approach reduces potential projection biases in OA indicators.
2. Eliminates model biases using observational data, and model drift with pre-Industrial controls.
3. Covers 10 OA indicators, an expansion from the usual pH, acidity, and buffer capacity.
4. Incorporates the new Shared Socioeconomic Pathways (SSPs).

The use of the most recent observational datasets and a large Earth System Model ensemble is a major step forward in the projection of future surface ocean OA indicators and provides critical information to guide OA mitigation and adaptation efforts.

Figure X. Temporal changes of global average surface ocean OA indicators as reconstructed and projected from 14 CMIP6 Earth System Models after applying adjustments with observational data: (a) fugacity of carbon dioxide (fCO2), (b) total hydrogen ion content ([H+]total), (c) carbonate ion content ([CO32-]), (d) total dissolved inorganic carbon content (DIC), (e) pH on total scale (pHT), (f) aragonite saturation state (Ωarag), (g) total alkalinity content (TA), (h) Revelle Factor (RF), and (i) calcite saturation state (Ωcalc). The asterisk signs on the left-side y-axes show the values in 1750. The numbers along right-side y-axes, i.e., 1-1.9, 1-2.6, 2-4.5, 3-7.0, and 5-8.5, indicate the shared socioeconomic pathway SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, and SSP5-8.5, respectively. These are missing from panel g because the trajectories were more dependent on the model than the SSP.

Authors
Li-Qing Jiang (University Maryland)
John Dunne (NOAA/Geophysical Fluid Dynamics Laboratory)
Brendan R. Carter (University of Washington)
Jerry F. Tjiputra (NORCE Norwegian Research Centre Bjerknes)
Jens Terhaar (Woods Hole Oceanographic Institution)
Jonathan D. Sharp (University of Washington)
Are Olsen (University of Bergen and Bjerknes Centre for Climate Research)
Simone Alin (NOAA/Pacific Marine Environmental Laboratory)
Dorothee C. E. Bakker (University of East Anglia)
Richard A. Feely (NOAA/Pacific Marine Environmental Laboratory)
Jean-Pierre Gattuso (Sorbonne Université)
Patrick Hogan (NOAA/National Centers for Environmental Information)
Tatiana Ilyina (Max Planck Institute for Meteorology)
Nico Lange (GEOMAR Helmholtz Centre for Ocean Research)
Siv K. Lauvset (NORCE Norwegian Research Centre)
Ernie R. Lewis (Brookhaven National Laboratory)
Tomas Lovato (Fondazione Centro Euro-Mediterraneo sui Cambiamenti Climatici)
Julien Palmieri (National Oceanography Centre)
Yeray Santana-Falcón (Université de Toulouse)
Jörg Schwinger (NORCE Norwegian Research Centre)
Roland Séférian (Université de Toulouse)
Gary Strand (US National Center for Atmospheric Research)
Neil Swart (Canadian Centre for Climate Modelling and Analysis)
Toste Tanhua (GEOMAR Helmholtz Centre for Ocean Research)
Hiroyuki Tsujino (JMA Meteorological Research Institute)
Rik Wanninkhof (NOAA/Atlantic Oceanographic Meteorological Laboratory)
Michio Watanabe (Japan Agency for Marine-Earth Science and Technology)
Akitomo Yamamoto (Japan Agency for Marine-Earth Science and Technology)
Tilo Ziehn (CSIRO Oceans and Atmosphere)

Twitter:
@JiangLiqing, @JensTerhaar, @jpGattuso, @j_d_sharp, @AreOlsen, @SimoneAlin, @Dorothee_Bakker, @RFeely, @ilitat, @sivlauvset, @yeraysf, @TosteTanhua,

Enhanced-warming Kuroshio Current experiences rapid seawater acidification and CO2 increase

Posted by mmaheigan 
· Thursday, March 30th, 2023 

In order to project the future states of the climate and the marine ecosystem it is vital to understand the long-term changes in ocean carbon chemistry driven by anthropogenic influence. A paucity of data make the rates of seawater acidification and partial pressure of CO2 (pCO2) rise on ocean margins highly uncertain.

Figure 1. Graphic summary of 9 years of data from the Kuroshio Current time-series: (a) under the influences of only atmospheric CO2 increase, (b) the combined effect of atmospheric CO2 increase, SST increase, and additional DIC supply, (c) annually averaged air-sea CO2 flux decrease, (d) Projected seawater pCO2 increase under SST rise and sustained DIC increase.

A recent study in Marine Pollution Bulletin documented the rapid increase of seawater pCO2 (3.70±0.57 matm year-1) and acidification (pH at -0.0033±0.0009 unit year-1) along Kuroshio in the East China Sea (Figure 1). These findings were based on nine years of time-series data ( 2010-2018) which are now available on the website of Japan Meteorological Agency (JMA). These trends are significantly greater than the expected rates from CO2 air-sea equilibrium and those reported from other oceanic time-series studies. Interestingly, they showed the contribution of each parameter such as sea surface temperature (SST), sea surface salinity (SSS), and normalized dissolved inorganic carbon (nDIC) and total alkalinity (nTA) to the pCO2 variability. Seawater warming caused rapid rates of pCO2 increase and acidification under sustained DIC increase. The faster pCO2 growth relative to the atmosphere resulted in the CO2 uptake through the air-sea exchange declining by ~50% (~-0.8 to -0.4 mol C m-2 y-1) over the study period.

If this trend continues and the atmospheric CO2 increases at its current rate, the rapid warming Kuroshio regions could change from a sink to a source of CO2 , and cause a loss of oceanic CO2 uptake in the near future (ca. 2030-2040). Further, other “warming hotspots” in the global ocean along western boundary currents with a continuous DIC supply may exhibit similarly accelerated acidification and pCO2 rise. This could lead to a significant reduction in ocean CO2 uptake.

 

Authors:
Shou-En Tsao (Institute of Oceanography, National Taiwan University, Taiwan)
Po-Yen Shen (Institute of Oceanography, National Taiwan University, Taiwan)
Chun-Mao Tseng* (Institute of Oceanography, National Taiwan University, Taiwan)

What can algae tell us about translating laboratory science to nature?

Posted by mmaheigan 
· Thursday, June 9th, 2022 

Ocean acidification research has grown over the past few decades. Much of recent research documents negative impacts of changing carbonate chemistry on calcifying marine organisms in laboratory experiments. At the 2018 Ocean Acidification PI Meeting, a group of us asked “Can these laboratory responses to ocean acidification be scaled up to accurately predict the responses of marine ecosystems?” To answer this research question, we developed a semi-quantitative synthesis of benthic calcifying algae responses to ocean acidification, recently published in the ICES Journal of Marine Science.

Figure 1. Comparing directional responses of individuals and communities to acidification in laboratory and field settings highlights mismatches. Specifically, field studies document higher proportion of negative responses compared to laboratory experiments. We provide a series of recommendations for future research to better bridge this gap of understanding in responses to ocean acidification. Figure modified from Page et al. 2022.

We detail in the paper how the proportion of positive, neutral, and negative responses in laboratory experiments often didn’t match field observations. Additionally, laboratory experiments mainly report short-term responses (days to weeks) across tropical and temperate locations. In contrast, field studies emphasize long-term responses (months to years) from fewer global locations. Using our synthesis, we developed nine recommendations that will enhance our ability to translate laboratory experiment results into actual responses of marine taxa to ongoing and future acidification in the natural environment. These future research directions are applicable not only to ocean acidification studies but can be directly applied to the broader field of climate change. We hope these recommendations will lead to greater confidence in our projections of climate change impacts at different ecological scales, and better inform the conservation and management of our valuable marine ecosystems.

 

Backstory

Initially, we set out to answer this research question through a meta-analysis comparing the effect size of the impacts of ocean acidification on benthic calcifying macroalgae in laboratory and field settings. We quickly realized this approach was not going to work because of the much smaller number of responses recorded in field settings, the different methods used, and response parameters measured between the laboratory and field; these differences made calculating and comparing effect sizes impossible. Therefore, we landed on the approach of conducting a semi-quantitative synthesis to compare directional responses in laboratory and field settings. The results of this synthesis and the process of developing a robust research approach to answer our question inspired us to discuss and develop the recommendations for future research presented in the paper.

 

Authors (affils and Twitter handles)
Heather N. Page (Sea Education Association) @heathernicopage
Keisha D. Bahr (Texas A&M University – Corpus Christi) @thebahrlab
Tyler Cyronak (Nova Southeastern University) @tcyronak
Elizabeth B. Jewett (National Oceanic and Atmospheric Administration) @LibbyJewett
Maggie D. Johnson (King Abdullah University of Science and Technology) @MaggieDJohnson
Sophie J. McCoy (University of North Carolina at Chapel Hill) @MarEcology

Introducing the Coastal Ocean Data Analysis Product in North America (CODAP-NA)

Posted by mmaheigan 
· Friday, October 22nd, 2021 

Coastal ecosystems are hotspots for commercial and recreational fisheries, and aquaculture industries that are susceptible to change or economic loss due to ocean acidification. These coastal ecosystems support about 90% of the global fisheries yield and 80% of the known marine fish species, and sustain ecosystem services worth $27.7 Trillion globally (a number larger than the U.S. economy). Despite the importance of these areas and economies, internally-consistent data products for water column carbonate and nutrient chemistry data in the coastal ocean—vital to understand and predict changes in these systems—currently do not exist. A recent study published in Earth Syst. Sci. Data compiled and quality controlled discrete sampling-based data—inorganic carbon, oxygen, and nutrient chemistry, and hydrographic parameters collected from the entire North American ocean margins—to create a data product called the Coastal Ocean Data Analysis Product for North America (CODAP-NA) to fill the gap. This effort will promote future OA research, modeling, and data synthesis in critically important coastal regions to help advance the OA adaptation, mitigation, and planning efforts by North American coastal communities; and provides a foothold for future synthesis efforts in the coastal environment.

Figure caption. Sampling stations of the CODAP-NA data product.

 

Authors:
Li-Qing Jiang (University of Maryland; NOAA NCEI)
Richard A. Feely (NOAA PMEL)
Rik Wanninkhof (NOAA AOML)
Dana Greeley (NOAA PMEL)
Leticia Barbero (University of Miami; NOAA AOML)
Simone Alin (NOAA PMEL)
Brendan R. Carter (University of Washington; NOAA PMEL)
Denis Pierrot (NOAA AOML)
Charles Featherstone (NOAA AOML)
James Hooper (University of Miami; NOAA AOML)
Chris Melrose (NOAA NEFSC)
Natalie Monacci (University of Alaska Fairbanks)
Jonathan Sharp (University of Washington; NOAA PMEL)
Shawn Shellito (University of New Hampshire)
Yuan-Yuan Xu (University of Miami; NOAA AOML)
Alex Kozyr (University of Maryland; NOAA NCEI)
Robert H. Byrne (University of South Florida)
Wei-Jun Cai (University of Delaware)
Jessica Cross (NOAA PMEL)
Gregory C. Johnson (NOAA PMEL)
Burke Hales (Oregon State University)
Chris Langdon (University of Miami)
Jeremy Mathis (Georgetown University)
Joe Salisbury (University of New Hampshire)
David W. Townsend (University of Maine)

Chesapeake Bay acidification partially offset by submerged aquatic vegetation

Posted by mmaheigan 
· Wednesday, September 30th, 2020 

Ocean acidification is often enhanced by eutrophication and subsequent hypoxia and anoxia in coastal waters, which collectively threaten marine organisms and ecosystems. Acidification is particularly of concern for organisms that form shells and skeletons from calcium carbonate (CaCO3) such as commercially important shellfish species. Given that CaCO3 mineral dissolution can increase the total alkalinity of water and neutralize anthropogenic and metabolic CO2, it is important to include CaCO3 cycle in the coastal water acidification study.  However, very few studies have linked CaCO3 dissolution to the timing and location of its formation in coastal waters. A recent study from the Chesapeake Bay published in Nature Geoscience reveals the occurrence of a bay-wide pH-buffering mechanism resulting from spatially decoupled CaCO3 mineral cycling (Figure 1). Photosynthesis by submerged aquatic vegetation at the head of the Bay and in other shallow, nearshore waters can remove nutrient pollution from the Bay, generate very high pH, and elevate the carbonate mineral saturation state (Figure 1). This facilitates the formation of CaCO3 minerals, which are then transported downstream along with other biologically produced carbonate shells into acidic subsurface waters, where they dissolve. This dissolution of carbonate minerals helps “buffer” the water against pH decreases and even drive pH increases. This finding has great ecological and natural resource management significance, in that coastal nutrient management and reduction via the resurgence of submerged aquatic vegetation can help mitigate low oxygen and acidification stress for these environments and organisms.

Figure 1: Conceptual model of the self-regulated pH-buffering mechanism in the Chesapeake Bay. Calcium carbonate is formed within the high-pH submerged aquatic vegetation beds in shallow waters (top left and upper part of diagram, all Shoals with SAV), where it could be subsequently transported longitudinally and/or laterally into the deep main channel of the mid and lower bay (center) and upon dissolution, increase pH buffering capacity and alleviate coastal acidification (lower section).

 

Authors:
Jianzhong Su (University of Delaware, Xiamen University)
Wei-Jun Cai (University of Delaware)
Jean Brodeur (University of Delaware)
Baoshan Chen (University of Delaware)
Najid Hussain (University of Delaware)
Yichen Yao (University of Delaware)
Chaoying Ni (University of Delaware)
Jeremy Testa (University of Maryland Center for Environmental Science)
Ming Li (University of Maryland Center for Environmental Science)
Xiaohui Xie (University of Maryland Center for Environmental Science, Second Institute of Oceanography)
Wenfei Ni (University of Maryland Center for Environmental Science)
K. Michael Scaboo (University of Delaware)
Yuanyuan Xu (University of Delaware)
Jeffrey Cornwell (University of Maryland Center for Environmental Science)
Cassie Gurbisz (St. Mary’s College of Maryland)
Michael S. Owens (University of Maryland Center for Environmental Science)
George G. Waldbusser (Oregon State University)
Minhan Dai (Xiamen University)
W. Michael Kemp (University of Maryland Center for Environmental Science)

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