Archive for respiration

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

Towards using historical oxygen observations to reconstruct the air-sea flux of biological oxygen

Posted by mmaheigan 
· Tuesday, December 13th, 2022 

Dissolved oxygen (O2) is a central observation in oceanography with a long history of relatively high precision measurements and increasing coverage over the 21st century. O2 is a powerful tracer of physical, chemical and biological processes (e.g., photosynthesis and respiration, wave-induced bubbles, mixing, and air-sea diffusion). A commonly used approach to partition the processes controlling the O2 signal relies on concurrent measurements of argon (an inert gas), which has solubility properties similar to O2. However, only a limited fraction of O2 measurements have paired argon measurements.

Figure 1. (a) The newly developed empirical model to parameterize the physical oxygen saturation anomaly (ΔO2[phy]) in order to separate the biological contribution from total oxygen, and (b-c) regional, inter-annual, and decadal variability of air-sea gas flux of biological oxygen (F[O2]bio as) reconstructed from the historical dissolved oxygen record.

A recent study published in the Journal of Global Biogeochemical Cycles presents semi-analytical algorithms to separate the biological and physical O2 oxygen signals from O2 observations. Among the approaches, a machine-learning algorithm using ship-based measurements and historical records of physical parameters from reanalysis products as predictors shows encouraging performance. The researchers leveraged this new algorithm to reconstruct regional, inter-annual, and decadal variability of the air-sea flux of biological oxygen (from historical O2 records.

The long-term objective of this proof-of-concept effort is to estimate from historical oxygen records and a rapidly growing number of O2 measurements on autonomous platforms. In regions where vertical and horizontal mixing is weak, the projected  approximates net community production, providing an independent constraint on the strength of the biological carbon pump.

 

Authors:
Yibin Huang (Duke University)
Rachel Eveleth (Oberlin College)
David (Roo) Nicholson (Woods Hole Oceanographic Institution)
Nicolas Cassar (Duke University)

How do coccolithophores survive the darkness?

Posted by mmaheigan 
· Friday, April 1st, 2022 

Coccolithophores have survived several major extinction events over geologic time. The most significant was the asteroid impact at the K/T boundary, followed by months of darkness. Additionally, coccolithophores regularly reside in the twilight zone, just beyond the reach of sunlight. A paper recently published in the New Phytologist addresses how these photosynthetic algae can persist and grow, albeit slowly, in darkness using osmotrophy.

The authors discovered that the osmotrophic uptake of certain types of dissolved organic carbon (DOC) can support survival in low light. They completed a 30-day darkness experiment to determine how the concentration of several DOC compounds affects growth. The coccolithophore species Cruciplacolithus neohelis growth rate increased with the increasing concentration of dissolved organic compounds. They also examined the kinetics of short-term uptake of radiolabeled DOC compounds and found that the uptake rate generally showed Michaelis-Menten-like saturation kinetics. All radiolabeled DOC compounds were incorporated into the POC fraction, but surprisingly also into the particulate inorganic carbon (PIC) fraction (i.e., calcite coccoliths).

These results suggest that osmotrophic uptake in coccolithophores may be significant enough to be included in carbon cycle models, especially if they can simultaneously take up a wide range of organic compounds. Surprisingly, we detected 14C-DOC in the PIC fraction after only 24 hours. This remarkably rapid incorporation is most likely due to the respiration of radiolabeled DOC into dissolved inorganic carbon (DIC), subsequently used by coccolithophores for calcification. These results have implications for the biological carbon pump and alkalinity pump paradigms, as we confirmed that both POC and PIC originate from DOC on short time scales.

 

The arsenic respiratory cycle in pelagic waters of Oxygen Deficient Zones

Posted by mmaheigan 
· Wednesday, October 30th, 2019 

Oxygen Deficient Zones (ODZs) are naturally occurring functionally anoxic regions of the open ocean which can act as proxies for early Earth’s anoxic ocean. Without free oxygen, microorganisms in these regions use alternative electron acceptors to oxidize organic material. These functionally anoxic regions are also hotspots for chemoautotrophic pathways. Some microorganisms can use arsenic based compounds to oxidize organic material, and others can couple nitrate reduction with arsenic oxidation supporting autotrophic carbon fixation thus linking arsenic respiration with carbon and nitrogen cycling. While arsenic concentrations in modern oceans are relatively low, the Precambrian ocean likely had periods of high arsenic concentrations. Integrating over time and space of anoxic waters, arsenic-based metabolisms may have had significant implications for the biogeochemical cycling of not only arsenic, but also carbon and nitrogen.

Figure 1: Arsenotrophic genes identified in the Eastern Tropical North Pacific Oxygen Deficient Zone. (A) Genomic complement for dissimilatory arsenate reduction assembled from metagenomes which likely supports respiration of organic matter. (B) Genomic complement for putative chemoautotrophic arsenite oxidation pathway assembled from metagenomes which may couple with nitrate reduction to support organic matter production. (C) Relative abundance of genes associated with arsenite oxidase (aioA), dissimilatory arsenate reduction (arrA), and forward dissimilatory sulfite reductase (dsrA) associated with sulfur reduction; abundance shown as a relative contribution to the total microbial community as estimated by abundance of RNA polymerase genes (rpoB). The genes arrA and forward-dsrA are more abundant in the particulate fraction, whereas aioA is more abundant in the free-living fraction. (D) Relative abundance of genes in the microbial community for the more abundant genes aioA-like and reverse form of dsrA associated with sulfur oxidation. aioA-like genes are relatively more abundant within the particulate fraction, with no strong partitioning between fractions identified for the reverse-dsrA genes. Arsenical reduction and chemoautotrophic arsenical oxidation are likely performed by different microbial groups within the ODZ communities.

Recent work in PNAS identified gene sequences for a complete arsenic respiratory cycle from Eastern Tropical North Pacific (ETNP) ODZ metagenomes. The authors identified arsenotrophic genes for dissimilatory arsenate reduction from one group of microorganisms and genes for a putative chemoautotrophic arsenite oxidation pathway from another group within the ETNP ODZ microbial community. Analysis of genomic sequences from a free-living sample and from particulate-associated sample indicate niche differentiation of these pathways—arsenate reduction genes enriched within the particulate fraction and arenite oxidation enriched in the free-living water column. In addition to the presence of these genes in metagenomes, the authors identified the active expression of these arsenotrophic genes in publicly available metatranscriptomes from the ETNP and Eastern Tropical South Pacific ODZs. Theyalso found an abundance of sequences in the ETNP ODZ for the gene aioA-like, which is a closely related enzyme to arsenite oxidase (aioA), but with an unconfirmed function. The identification of these actively expressed genes in modern ODZs enables further investigation of these cycles that were likely important in early oceans. These findings also highlight that there are still yet to be discovered respiratory pathways in ODZs. Arsenotrophy, in conjunction with other niche respiratory pathways – both known and as yet undiscovered – likely sum to a considerable contribution of energy flow and elemental cycling through these anoxic systems.

Authors:
Jaclyn Saunders (University of Washington; present affiliation Woods Hole Oceanographic Institution)
Clara Fuchsman (University of Washington; present affiliation Horn Point Laboratory)
Cedar McKay & Gabrielle Rocap (University of Washington)

 

See related University of Washington press-release

Hotspots of biological production: Submesoscale changes in respiration and production

Posted by mmaheigan 
· Thursday, April 26th, 2018 

The biological pump is complex and variable. To better understand it, scientists have often focused on variations in biological parameters such as fluorescence and community structure, and have less often observed variations in rates of production. Production rates can be estimated using oxygen as a tracer, since photosynthesis produces oxygen and respiration consumes it. In a recent article in Deep Sea Research Part I, the authors presented high-resolution maps of oxygen in the upper 140 m of the ocean in the subtropical and tropical Atlantic, produced from a towed undulating instrument. This provides a synoptic, high-resolution view of oxygen anomalies in the surface ocean. These data reveal remarkable hotspots of biological production and respiration co-located with areas of elevated fluorescence. These hotspots are often several kilometers wide (horizontal) and ~10 m long (vertical). They are preferentially associated with edges of eddies, but not all edges sampled contained hotspots. Although this study captures only two-dimensional glimpses of these hotspots, precluding formal calculations of production rates, likely estimates of source water suggest that many of these hotspots may actually be areas of enhanced respiration rather than enhanced photosynthesis. The paper describes a conceptual model of nutrients, new production, respiration, fluorescence, and oxygen during the formation and decline of these hotspots. These data raise intriguing questions–if the hotspots do indeed have substantially different rates of production and respiration than surrounding waters, then they could lead to significant changes in estimates of production in the upper ocean. Additionally, understanding the mechanisms that produce these hotspots could be critical for predicting the effects of climate change on the magnitude of the biological pump.

(a) Oxygen concentrations and (b) fluorescence at ~1 km resolution over 300 km from 15.13°N, 57.47°W to 12.30°N, 56.42° W, as measured by sensors attached to the (c) Video Plankton Recorder II. Note that no contouring was used for this plot – every pixel represents an actual data point. Figure modified from Stanley et al., 2017. VPR image photograph by Phil Alatalo.

Authors:
Rachel H. R. Stanley (Wellesley College)
Dennis J. McGillicuddy Jr. (WHOI)
Zoe O. Sandwith (WHOI)
Haley Pleskow (Wellesley College)

Increased temperatures suggest reduced capacity for carbon

Posted by mmaheigan 
· Thursday, January 18th, 2018 

The ocean’s biological pump works to draw down atmospheric carbon dioxide (CO2) by exporting carbon from the surface ocean. This process is less efficient at higher temperatures, implying a possible climate feedback. Recent work by Cael et al. provides an explanation of why this feedback occurs and an estimate of its severity.

In a highly simplified view, carbon export depends on the balance between two temperature-dependent processes: 1) The autotrophic production and 2) the heterotrophic respiration of organic carbon. Cael and Follows (Geophysical Research Letters 2016) recently developed a mechanistic model based on established temperature dependencies for photosynthesis and respiration to explore feedbacks between export efficiency and climate. Heterotrophic growth rates increase more so than phototrophic rates with increasing temperature, which suggests that at higher temperatures, community respiration will increase relative to production, thereby decreasing export efficiency. Although simplistic, the model captures the temperature dependence of export efficiency observations.

Figure: Schematic of the mechanism on which the Cael and Follows (2016) model is based. (a) Photosynthesis (dark grey) and respiration (light grey) respond to temperature differently, yielding (b) a decline in export efficiency at higher temperatures.

More recently, Cael, Bisson, and Follows (Limnology and Oceanography 2017) applied this model to sea surface temperature records and estimated a ~1.5% decline in globally-averaged export efficiency over the past three decades of increasing ocean temperatures as a result of this metabolic mechanism. This ~1.5% decline is equivalent to a reduced ocean sequestration of approximately 100 million fewer tons of carbon annually, comparable to the annual carbon emissions of the United Kingdom. The model provides a framework in which to consider the relationship between climate and ocean carbon export that might also elucidate large-scale (e.g., glacial-interglacial) atmospheric CO2 changes of the past.

Authors:
B. B. Cael (MIT/WHOI)
Kelsey Bisson (UCSB)
Mick Follows (MIT)

Filter by Keyword

abundance acidification additionality advection africa air-sea air-sea interactions algae alkalinity allometry ammonium AMO AMOC anoxic Antarctic Antarctica anthro impacts anthropogenic carbon anthropogenic impacts appendicularia aquaculture aquatic continuum aragonite saturation arctic Argo argon arsenic artificial seawater Atlantic atmospheric CO2 atmospheric nitrogen deposition authigenic carbonates autonomous platforms bacteria bathypelagic BATS BCG Argo benthic bgc argo bio-go-ship bio-optical bioavailability biogeochemical cycles biogeochemical models biogeochemistry Biological Essential Ocean Variables biological pump biophysics bloom blue carbon bottom water boundary layer buffer capacity C14 CaCO3 calcification calcite carbon carbon-climate feedback carbon-sulfur coupling carbonate carbonate system carbon budget carbon cycle carbon dioxide carbon export carbon fluxes carbon sequestration carbon storage Caribbean CCA CCS changing marine chemistry changing marine ecosystems changing marine environments changing ocean chemistry chemical oceanographic data chemical speciation chemoautotroph chesapeake bay chl a chlorophyll circulation climate change climate changes climate variability CO2 coastal and estuarine coastal darkening coastal ocean cobalt Coccolithophores commercial community composition conservation cooling effect copepod copepods coral reefs CTD currents cyclone daily cycles data data access data assimilation database data management data product Data standards DCM dead zone decadal trends decomposers decomposition deep convection deep ocean deep sea coral deoxygenation depth diatoms DIC diel migration diffusion dimethylsulfide dinoflagellate dinoflagellates discrete measurements distribution DOC DOM domoic acid DOP dust DVM ecology economics ecosystem management ecosystems eddy Education EEZ Ekman transport emissions ENSO enzyme equatorial current equatorial regions ESM estuarine and coastal carbon fluxes estuary euphotic zone eutrophication evolution export export fluxes export production EXPORTS extreme events faecal pellets fecal pellets filter feeders filtration rates fire fish Fish carbon fisheries fishing floats fluid dynamics fluorescence food webs forage fish forams freshening freshwater frontal zone functional role future oceans gelatinous zooplankton geochemistry geoengineering geologic time GEOTRACES glaciers gliders global carbon budget global ocean global warming go-ship grazing greenhouse gas Greenland ground truthing groundwater Gulf of Maine Gulf of Mexico Gulf Stream gyre harmful algal bloom high latitude human food human impact human well-being hurricane hydrogen hydrothermal hypoxia ice age ice cores ice cover industrial onset inland waters in situ inverse circulation ions iron iron fertilization isotopes jellies katabatic winds kelvin waves krill kuroshio lab vs field land-ocean continuum larvaceans lateral transport LGM lidar ligands light light attenuation lipids machine learning mangroves marine carbon cycle marine heatwave marine particles marine snowfall marshes mCDR Mediterranean meltwater mesopelagic mesoscale mesoscale processes metagenome metals methane methods microbes microlayer microorganisms microplankton microscale microzooplankton midwater mitigation mixed layer mixed layers mixing mixotrophs mixotrophy model modeling model validation mode water molecular diffusion MPT MRV multi-decade n2o NAAMES NASA NCP nearshore net community production net primary productivity new ocean state new technology Niskin bottle nitrate nitrogen nitrogen cycle nitrogen fixation nitrous oxide north atlantic north pacific nuclear war nutricline nutrient budget nutrient cycles nutrient cycling nutrient limitation nutrients OA ocean-atmosphere ocean acidification ocean acidification data ocean alkalinity enhancement ocean carbon storage and uptake ocean carbon uptake and storage ocean color ocean modeling ocean observatories ocean warming ODZ oligotrophic omics OMZ open ocean optics organic particles oscillation outwelling overturning circulation oxygen pacific paleoceanography PAR parameter optimization parasite particle flux particles partnerships pCO2 PDO peat pelagic PETM pH phenology phosphate phosphorus photosynthesis physical processes physiology phytoplankton PIC piezophilic piezotolerant plankton POC polar polar regions policy pollutants precipitation predation predator-prey prediction pressure primary productivity Prochlorococcus prokaryotes proteins pteropods pycnocline radioisotopes remineralization remote sensing repeat hydrography residence time resource management respiration resuspension rivers rocky shore Rossby waves Ross Sea ROV salinity salt marsh satellite scale seafloor seagrass sea ice sea level rise seasonal seasonality seasonal patterns seasonal trends sea spray seawater collection seaweed secchi sediments sensors sequestration shelf ocean shelf system shells ship-based observations shorelines silica silicate silicon cycle sinking sinking particles size SOCCOM soil carbon southern ocean south pacific spatial covariations speciation SST state estimation stoichiometry subduction submesoscale subpolar subtropical sulfate surf surface surface ocean Synechococcus technology teleconnections temperate temperature temporal covariations thermocline thermodynamics thermohaline thorium tidal time-series time of emergence titration top predators total alkalinity trace elements trace metals trait-based transfer efficiency transient features Tris trophic transfer tropical turbulence twilight zone upper ocean upper water column upwelling US CLIVAR validation velocity gradient ventilation vertical flux vertical migration vertical transport volcano warming water clarity water mass water quality waves weathering western boundary currents wetlands winter mixing zooplankton

Copyright © 2024 - OCB Project Office, Woods Hole Oceanographic Institution, 266 Woods Hole Rd, MS #25, Woods Hole, MA 02543 USA Phone: 508-289-2838  •  Fax: 508-457-2193  •  Email: ocb_news@us-ocb.org

link to nsflink to noaalink to WHOI

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.