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Archive for New OCB Research – Page 5

Identifying the water mass composition of a sample has never been so easy!

Posted by mmaheigan

· Thursday, August 31st, 2023

When we collect seawater in any point of the ocean, we are collecting a mix of water masses from different origin that traveled until there keeping their salinity and temperature properties. The Atlantic Ocean is likely the most complex basin in term of water masses containing more than 15 in its depths. Some of them were “born” in the North Atlantic Ocean, others in the Southern Ocean, even in the Mediterranean Sea! And when we collect a seawater sample we can know which water masses are there, where they come from, what happened to each of them during their journey to us, what story can they tell us.

The variation of any non-conservative property (such as dissolved organic carbon or nutrients) in the deep open ocean depends on the mixing of those water masses and on the biogeochemical processes affecting it (such as heterotrophic respiration). But the effect of the water mass mixing is usually very high, so in order to study the biogeochemical processes, it is necessary to remove that effect.

On the other hand, estimating the contribution of the water masses composing a sample is useful to trace the distribution of each water mass identifying the depth of maximum water mass contribution or the depth-range where the water mass is dominant contributing > 50%. Ocean biogeochemists and microbiologists can get more out of their data estimating the impact of water mass mixing on the variability of any chemical (e.g. inorganic nutrients and dissolved organic carbon) or biological (e.g. prokaryotic heterotrophic abundance and production) property.

Knowing the contribution of each water mass to each sample was not an easy task and required expertise on the origin, circulation and mixing patterns of the water masses present in the study area. This could be even harder in very complex oceanic basin such as the deep Atlantic Ocean. The most commonly used methodology is the Optimum Multi-Parameter (OMP) analysis that was first applied by Tomczak in 1981. However, this methodology is time consuming and requires availability of a large set of quality-controlled chemical variables (e.g. nutrients, oxygen,..) together with a deep knowledge of the oceanography of the studied area. Those chemical variables are not always available or do not have the required quality by contrast to potential temperature and salinity that are high standard core variables in any cruise or database. In a recent research article, we applied multi-regression machine learning models to solve ocean water mass mixing. The models tested were trained using the solutions from OMP analyses previously applied to samples from cruises in the Atlantic Ocean. Extremely Randomized Trees algorithm yielded the highest score (R² = 0.9931; mse = 0.000227). The model allows solving the mixing of water masses in the Atlantic Ocean using potential temperature, salinity, latitude, longitude and depth. Potential temperature and salinity are the most commonly collected and curated variables in oceanography both from oceanographic cruises and autonomous vehicles (e.g. ARGO) avoiding the use of less commonly measured chemical variables which also require longer and time-consuming analyses of both the water samples and the data.

Figure 1. A16 section for the contribution of the water masses (A) AAIW5, (B) ENACW12, (C) AAIW3, (D) MW, (E) LSW, (F) ISOW, (G) CDW and (H) WSDW obtained with the Extremely Randomized Trees algorithm. Ocean Data View software (Schlitzer, 2015).

We also provide the code with instructions where any user can easily introduce the required variables (latitude, longitude, depth, temperature and salinity) of the chosen Atlantic samples and obtain the water mass proportion of each one in a fast and easy way. Actually, it would allow the user to obtain this information in real time during a cruise.

New research using other methods like OMP and its variants can be incorporated to the existing model increasing its accuracy and prediction capacity. Help us to improve the model and increase its spatial resolution!

Ocean biogeochemists and microbiologists can benefit from this tool even if they do not have a deep knowledge of the oceanography of the studied area. Identifying the water masses composition of a sample has never been so easy!

Author
Cristina Romera-Castillo (Instituto de Ciencias del Mar-CSIC, Barcelona, Spain)

Twitter: @crisrcas

RPiAlk: Balancing Measurement Uncertainty and Accessibility

Posted by mmaheigan

· Thursday, August 31st, 2023

High-accuracy measurement of total alkalinity (TA) is crucial for our understanding of ocean acidification and the inorganic carbon complex. It is also particularly expensive in terms of labor and resources. These barriers limit its application in understudied settings such as inland waters and developing coastal regions.

To address this problem, the authors constructed an instrument using open-source and low-cost principles and wrote about it in an article published in Limnology & Oceanography: Methods. The instrument implements a standard oceanographic open-cell acidimetric titration method within Python software written to coordinate titration, data acquisition, and calculation on a Raspberry Pi platform called RPiAlk. Repeated analysis of reference materials demonstrated TA measurement precision of 3.0 μmol/kg and measurement uncertainty of 5.3 μmol/kg. This uncertainty qualifies as “weather” level uncertainty (GOA-ON 2015) and approaches “climate” level uncertainty.

We hope the accessibility of this design will aid its replication and improvement by other alkalinity-measuring laboratories, including researchers, regulators, and educators previously without access to such TA instrumentation. An expanded production of high-quality TA measurements may aid scientific understanding of understudied waters around the world.

Authors
Daniel Sandborn (University of Minnesota, Saint Paul)
Elizabeth Minor (University of Minnesota Duluth)
Craig Hill (University of Minnesota Duluth)

Mastodon: @DanielSandborn@sciencemastodon.com

Twitter: @DanielSandborn | @CraigHill_UMD

Backstory
RPiAlk came about as an artifact of instrument development in the Minor Lab at the Large Lakes Observatory. The author had been growing weary of the poor measurement repeatability of manual Gran titration (common in inland waters) and the many problems with comparison to non-linear titration curve fitting demonstrated in Dickson’s SOPs, so he decided to write a program to automate it. To the author’s delight, Dr. M. Humphreys had already written a fantastic TA calculation program, Calkulate. All that was needed was a simple wrapper and I/O function, right? Not quite. If only software and instrument development was that easy. Debugging became as tiresome as it was rewarding and educational.

Unveiling the Hidden Secrets of Ancient Carbon Burial

Posted by mmaheigan

· Thursday, August 31st, 2023

How much carbon has been buried in the depths of our ancient oceans, and how did it shape our planet’s climate? Unraveling this enigma has long eluded researchers, but a recent groundbreaking “bottom-up” study unveils the surprising history of organic carbon burial in marine sediments during the Neogene period.

Departing from conventional methods, this study presents an innovative approach to calculating organic carbon burial rates independently. Drawing from data collected from 81 globally distributed sites, the research covers the Neogene era (approximately 23 to 3 million years ago). The results reveal unprecedented spatiotemporal variability in organic carbon burial, challenging previous estimates. Notably, high burial rates were found during the early Miocene and Pliocene, contrasting with a significant decline during the mid-Miocene, marked by the lowest ratio of organic-to-carbonate burial rates. This finding disputes earlier interpretations of enriched carbonate ¹³C values during the mid-Miocene (so called “Monterey Period” or “Monterey Excursion”) as indicative of massive organic carbon burial.

Figure Caption: Neogene organic carbon (OC) burial in the global ocean. Burial rates calculated using different definitions of provinces, including three approaches: Longhurst (black curve with uncertainty envelope，± 1σ in purple and ± 2σ in pale lilac), Oceans (blue curve), and FAO Fishing (orange curve).

Understanding the complex carbon burial dynamics of ancient oceans holds profound implications for comprehending our planet’s climate evolution. The suppressed organic carbon burial during the warm mid-Miocene, likely driven by temperature-dependent bacterial degradation, suggests the organic carbon cycle acted as a positive feedback mechanism during past global warming events. These findings emphasize the vital role of ocean carbon sequestration, providing stark evidence for policymakers, funding agencies, citizens, and educators to acknowledge its significance in combating modern climate challenges.

Authors
Ziye Li (University of Bremen)
Yi Ge Zhang (Texas A&M University)
Mark Torres (Rice University)
Ben Mills (University of Leeds)

Twitter: @chemclimatology

Backstory
Dr. Zhang, a shipboard organic geochemist during International Ocean Discovery Program Expedition 363, embarked on the legendary drilling ship JOIDES Resolution. While on the journey, Yige spent hours and hours daily crushing samples to measure organic carbon until his palm grew calluses, but the TOC% numbers did not really change. Fueled by sheer determination, Yige’s former student Ziye Li and himself delved into 50 years of IODP data archives to uncover global trends, and with the help of carbon cycle modelers Mark Torres and Ben Mills, leading to the discovery of the history of organic carbon burial.

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 ([CO₃^2-]), (d) total dissolved inorganic carbon content (DIC), (e) pH on total scale (pH_T), (f) aragonite saturation state (Ω_arag), (g) total alkalinity content (TA), (h) Revelle Factor (RF), and (i) calcite saturation state (Ω_calc). 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,

Are you interested in a primer on ocean biogeochemical modeling with hands-on examples?

Posted by mmaheigan

· Thursday, May 11th, 2023

Look no further. This primer article explains what an ocean biogeochemical model is, how such a model is designed and applied, and includes easily accessible code examples. Refresh your memory on commonly used metrics for model evaluation through model-data comparison. Get introduced to the underlying rationale, mechanics, applications, and pitfalls of data assimilation for parameter optimization, state estimation, and observing system design. Peruse overviews of available community code repositories and observational databases. And tour some of the important applications of ocean biogeochemical models for carbon accounting, ocean deoxygenation and acidification studies, and fisheries yield projections. The primer also includes recommendations for best practices in ocean biogeochemical modeling and discusses current limitations and anticipated future developments and challenges. First and foremost, the article is an invitation to get involved.

Figure caption: Schematic representation of the varying level of complexity in biogeochemical models. State variables are indicated by the boxes where different colors correspond to different elemental currencies. The black arrows indicate selected biogeochemical transformations. The simplest, the nutrient–phytoplankton– zooplankton–detritus (NPZD) model, includes four state variables and one nutrient currency, often nitrogen. A typical low-complexity model includes several nutrients and nutrient currencies. Chlorophyll is omitted in the schematic, although many models have a chlorophyll state variable for each phytoplankton group to account for photoacclimation.

Authors
Katja Fennel (Dalhousie University)
Jann Paul Mattern (University of California, Santa Cruz)
Scott C. Doney (University of Virginia)
Laurent Bopp (Institute Pierre Simon Laplace)
Andrew M. Moore (University of California, Santa Cruz)
Bin Wang (Dalhousie University)
Liuqian Yu (Hong Kong University of Science and Technology)

Twitter @katjafennel @ScottDoney1 @laurent_bopp @DalhousieU @uvaevsc

Adaptive emission pathways to stabilize global temperatures

Posted by mmaheigan

· Thursday, May 11th, 2023

Around the world, countries have agreed in the Paris Agreement to limit global warming well below 2°C and to pursue efforts to reduce global warming to 1.5°C. However, large uncertainties remain about which emission pathways will allow us to reach this goal. A recent paper presents a new adaptive approach to create emission pathways and estimate the necessary emission reductions every five years, following the stocktake process of the Paris Agreement. This Adaptive Emissions Reduction Approach (AERA) is solely based on past warming rates, and emissions of CO₂ and non-CO₂ radiative agents, and explicitly does not rely on projections by Earth System Models. Updating the emission pathways every five years, circumvents uncertainties in the climate system and its transient response to cumulative emissions (TCRE). Testing with the Bern3D-LPX Earth System Model of Intermediate Complexity shows that the approach works robustly across a wide range of TCREs, avoids large overshoots, and only small changes to the emission pathways are necessary every five years. This approach will allow policymakers to estimate emission pathways and create a base for international negotiations. Furthermore, it allows simulations with Earth System Models that all converge to the same temperature target to compare the climate at stabilized warming levels.

Figure caption: The three steps of the Adaptive Emission Reduction Approach: 1) Estimating the past anthropogenic warming, 2) estimating the remaining emission budget, and 3) redistributing it over the future years.

Authors
Jens Terhaar (University of Bern, now Woods Hole Oceanographic Institution)
Thomas L Frölicher (University of Bern)
Mathias T Aschwanden (University of Bern)
Pierre Friedlingstein (University of Exeter, Ecole Normale Superieure)
Fortunat Joos (University of Bern)

Twitter @JensTerhaar @froeltho @PFriedling @unibern @snsf_ch @4C_H2020 @ExeterUniMaths @Geosciences_ENS @IPSL_outreach

Hydrostatic pressure substantially reduces deep-sea microbial activity

Posted by mmaheigan

· Thursday, May 11th, 2023

Deep sea microbial communities are experiencing increasing hydrostatic pressure with depth. It is known that some deep sea microbes require high hydrostatic pressure for growth, but most measurements of deep-sea microbial activity have been performed under atmospheric pressure conditions.

In a recent paper published in Nature Geoscience, the authors used a new device coined ‘In Situ Microbial Incubator’ (ISMI) to determine prokaryotic heterotrophic activity under in situ conditions. They compared microbial activity in situ with activity under atmospheric pressure at 27 stations from 175 to 4000 m depths in the Atlantic, Pacific, and the Southern Ocean. The bulk of heterotrophic activity under in situ pressure is always lower than under atmospheric pressure conditions and is increasingly inhibited with increasing hydrostatic pressure. Single-cell analysis revealed that deep sea prokaryotic communities consist of a small fraction of pressure-loving (piezophilic) microbes while the vast majority is pressure-insensitive (piezotolerant). Surprisingly, the piezosensitive fraction (~10% of the total community) responds with a more than 100-fold increase of activity upon depressurization. In the microbe proteomes, the authors uncovered taxonomically characteristic survival strategies in meso- and bathypelagic waters. These findings indicate that the overall heterotrophic microbial activity in the deep sea is substantially lower than previously assumed, which implies major impacts on the carbon budget of the ocean’s interior.

Figure caption: Deep sea microbial activity under varying pressure. (a) In situ bulk leucine incorporation rates normalized to rates obtained at atmospheric pressure conditions. (b) A microscopic view of a 2000 m sample collected in the Atlantic and incubated under atmospheric pressure conditions. The black halos around the cells are silver grains corresponding to their activities. The highly active cells (indicated by arrows) were rarely found in in situ pressure incubations. (c) Depth-related changes in the metaproteome of three abundant deep sea bacterial taxa (Alteromonas, Bacteroidetes, and SAR202). The number indicates shared and unique up- and down-regulated proteins in different depth zones.

Authors
Chie Amano (University of Vienna, Austria)
Zihao Zhao (University of Vienna, Austria)
Eva Sintes (University of Vienna, IEO-CSIC, Spain)
Thomas Reinthaler (University of Vienna, Austria)
Julia Stefanschitz (University of Vienna, Austria)
Murat Kisadur (University of Vienna, Austria)
Motoo Utsumi (University of Tsukuba, Japan)
Gerhard J. Herndl (University of Vienna, Netherlands Institute for Sea Research)

Twitter @microbialoceanW

Does dark carbon fixation supply labile DOC to the deep ocean?

Posted by mmaheigan

· Thursday, March 30th, 2023

Nitrifying microbes are the most abundant chemoautotrophs in the dark ocean. Though better known for their role in the nitrogen cycle, they also fix dissolved inorganic carbon (DIC) into biomass and thus play an important role in the global carbon cycle. The release of organic compounds by these microbes may represent an as-yet unaccounted for source of dissolved organic carbon (DOC) available to heterotrophic marine food webs. Quantifying how much DIC these microbes fix and release again into the ambient seawater is critical to a complete understanding of the carbon cycle in the deep ocean.

To address this knowledge gap, a recent study grew ten diverse nitrifier cultures and measured their cellular carbon (C) content, DIC fixation yields and DOC release rates. The results indicate that nitrifiers release between 5 and 15% of their recently fixed DIC as DOC (Figure 1). This would equate to global ocean fluxes of 0.006–0.02 Pg C yr⁻.

Figure 1. DOC release by ten different chemoautotrophic nitrifying (ammonia- and nitrite-oxidizing) microbes. The diversity of marine nitrifiers used in this study comprises all genera currently available as axenic cultures. Species and strain names are given for completeness.

Our results provide values for biogeochemical models of the global carbon cycle, and help to further constrain the relationship between C and N fluxes in the nitrification process. Elucidating the lability and fate of carbon released by nitrifiers will be the crucial next step to understand its implications for marine food-web functioning and the biological sequestration of carbon in the ocean.

Authors:
Barbara Bayer (University of California, Santa Barbara and University of Vienna)
Kelsey McBeain (University of California, Santa Barbara)
Craig A. Carlson (University of California, Santa Barbara)
Alyson E. Santoro (University of California, Santa Barbara)

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 CO₂air-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 pCO₂increase and acidification under sustained DIC increase. The faster pCO₂growth relative to the atmosphere resulted in the CO₂uptake 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 CO₂increases 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)

Severe warming = 15% increase in bacterial respiration: Southern Ocean most impacted

Posted by mmaheigan

· Thursday, March 30th, 2023

The utilization, respiration, and remineralization of organic matter exported from the ocean surface to its depths are key processes in the ocean carbon cycle. Marine heterotrophic Bacteria play a critical role in these activities. However, most three-dimensional (3-D) coupled physical-biogeochemical models do not explicitly include Bacteria as a state variable. Instead, they rely on parameterization to account for the bacteria’s impact on particle flux attenuation.

A recent study examined how bacteria respond to climate change by employing a 3-D coupled ocean biogeochemical model that incorporates explicit bacterial dynamics. The model (CMCC-ESM2) is a part of the Coupled Model Intercomparison Project Phase 6. The authors first evaluated the reliability of century-scale forecasts (2015-2099) for bacterial stocks and rates in the upper 100 m layer against the compiled measurements from the contemporary period (1988-2011). Next the authors analyzed the predicted trends in bacterial stocks and rates under diverse climate scenarios and explored their association with regional differences in temperature and organic carbon stocks. Three crucial findings were revealed. There is a global-scale decrease in bacterial biomass of 5-10%, with a 3-5% increase in the Southern Ocean (Figure 1). In the Southern Ocean, the rise in semi-labile dissolved organic carbon (DOC) leads to an increase in DOC uptake rates of free-living bacteria; in the northern high and low latitudes, the increase in temperature drives the increase in their DOC uptake rates. Importantly, extreme warming could result in a global increase (up to 15%) and even higher in the Southern Ocean (21% increase) in bacterial respiration (Figure 1), potentially leading to a decline in the biological carbon pump.

This analysis is an unprecedented and early effort to understand the climate-induced changes in bacterial dynamics on a global scale in a systematic manner. This study takes us one step closer to comprehending how bacteria influence the functioning of the biological carbon pump and the distribution of organic carbon pools between surface and deep layers, especially their response to climate change.

Figure 1. Global projections of bacterial carbon stocks and rates during the baseline period (1990-2013) and their changes as anomalies under the most-severe climate change scenario (i.e., SSP5-8.5) relative to the baseline period (2076-2099). The stocks and rates during the baseline period (a, b, c, g, h, i) and their changes as anomalies under the most-severe climate change scenario (d, e, f, j, k, l). All variables are depth-integrated in the upper 100 m. Solid-line contours as standard deviation from averaging over 1990-2013. Anomalies are 2076-2099 average values relative to 1990-2013 average values. Global bacterial biomass has decreased by 5-10%, with a 3-5% increase in the Southern Ocean. However, extreme warming may increase bacterial respiration worldwide, thereby reducing the efficiency of the biological carbon pump. This study provides an early attempt to understand the response of bacteria to climate change and their impact on the distribution of organic carbon in the ocean.

Author
Heather Kim, Woods Hole Oceanographic Institution

Funding for the Ocean Carbon & Biogeochemistry Project Office is provided by the National Science Foundation (NSF) and the National Aeronautics and Space Administration (NASA). The OCB Project Office is housed at the Woods Hole Oceanographic Institution.

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