Biogeochemistry & Ecophysiology at Duke University

Author: nc56@duke.edu (Page 2 of 4)

High resolution sampling and sensing of N2 fixation in the ocean

New insights into the distributions of nitrogen fixation and diazotrophs revealed by high-resolution sensing and sampling methods

 

N2 fixation rates and molecular sampling sites

Nitrogen availability limits marine productivity across large ocean regions. Diazotrophs can supply new nitrogen to the marine environment via nitrogen (N2) fixation, relieving nitrogen limitation. The distributions of diazotrophs and N2 fixation have been hypothesized to be generally controlled by temperature, phosphorus and iron availability in the global ocean. However, even in the North Atlantic where most research on diazotrophs and N2 fixation has taken place, environmental controls remain contentious. Here we measure diazotroph composition, abundance and activity at high resolution using newly developed underway sampling and sensing techniques. We capture a diazotrophic community shift from Trichodesmium to UCYN-A between the oligotrophic, warm (25-29°C) Sargasso Sea and relatively nutrient-enriched, cold (13-24°C) subpolar and eastern American coastal waters. Meanwhile, N2 fixation rates measured in this study are among the highest ever recorded globally and show significant increase with phosphorus availability across the transition from the Gulf Stream into subpolar and coastal waters despite colder temperatures and higher nitrate concentrations. Transcriptional patterns in both Trichodesmium and UCYN-A indicate phosphorus stress in the subtropical gyre. Over this iron-replete transect spanning the western North Atlantic, our results suggest that temperature is the major factor controlling the diazotrophic community structure while phosphorous drives N2 fixation rates. Overall, the occurrence of record-high UCYN-A abundance and peak N2 fixation rates in the cold coastal region where nitrate concentrations are highest (~200 nM) challenges current paradigms on what drives the distribution of diazotrophs and N2 fixation. See publication.

 

New estimates of Global Marine Gross Primary Production

The global distribution of marine euphotic-depth integrated Gross Primary Production (GPP) by machine-learning (Random Forest) upscaling of field observations of GPP derived from the triple isotopes of dissolved oxygen

See Press Release

Approximately half of global primary production occurs in the ocean. While the large-scale variability in net primary production (NPP) has been extensively studied, ocean gross primary production (GPP) has thus far received less attention. In this study, we derived two satellite-based GPP models by training machine-learning algorithms (Random Forest) withlight-dark bottle incubations (GPPLD) and the triple isotopes of dissolved oxygen (GPP17Δ).The two algorithms predict global GPPs of 9.2 ± 1.3 * 1015 and 15.1 ± 1.05 * 1015 mol O2 yr-1 for GPPLD and GPP17Δ, respectively. The projected GPP distributions agree with our understanding of the mechanisms regulating primary production. Global GPP17Δwas higher than GPPLD by an average factor of 1.6 which varied meridionally. The discrepancy between GPP17Δ and GPPLD simulations can be partly explained by the known biases of each methodology. After accounting for some of these biases, the GPP17Δ and GPPLD converge to 9.5~12.6 *1015 mol O2 yr-1, equivalent to 103~150 Pg C yr-1. Our results suggest that global oceanic GPP is 1.5-2.2 fold larger than oceanic NPP and comparable to GPP on land.

For more information, see publication.

Machine-learning estimates of global marine N2 fixation and diazotrophs

Machine-learning (random forest) estimate of depth-integrated N2 fixation and nifH gene distribution (Tang et al. 2019, Tang & Cassar 2019)

Marine nitrogen (N2) fixation supplies “new” nitrogen to the global ocean, supporting  uptake and sequestration of carbon. Despite its central role, marine N2 fixation and its controlling factors remain elusive. In this study, we compile over 1,100 published observations to identify the dominant predictors of marine N2 fixation and derive global estimates based on the machine learning algorithms of random forest (RF) and support vector regression (SVR). We find that no single environmental property predicts N2 fixation at global scales. Our RF and SVR algorithms, trained with sampling coordinates and month, solar radiation, wind speed, sea surface temperature, sea surface salinity, surface nitrate, surface phosphate, surface excess phosphorus, minimum oxygen in upper 500 m, photosynthetically available radiation (PAR), mixed layer depth, averaged PAR in the mixed layer, and chlorophyll-a concentration, estimate global marine N2 fixation ranging from 68 to 90 Tg N yr-1. Comparison of our machine learning estimates and 11 other model outputs currently available in literature shows substantial discrepancies in the global magnitude and spatial distribution of marine N2 fixation, especially in the tropics and in high latitudes. The large uncertainties in marine N2 fixation highlighted in our study argue for increased and more coordinated efforts using geochemical tracers, modeling, and observations over broad ocean regions.

See Tang et al. (2019) and Tang & Cassar (2019) for more information.

Cassar receives PECASE Award

The Presidential Early Career Award for Scientists and Engineers (PECASE) is the highest honor bestowed by the United States government on outstanding scientists and engineers in the early stages of their independent research careers.

NSF announcement: Cassar receives PECASE award “for developing a revolutionary method to measure marine nitrogen fixation on regional and global scales and robustly quantify nitrogen cycling between the ocean and the atmosphere, and for building partnerships with community science educators to foster climate change literacy”. See Duke announcement.

 

 

 

Tuna carbon isotopes suggest change in plankton communities

Illustrations by Boris Colas, SPC

See Nicholas School Press Release and original manuscript Lorrain et al. (2019): Considerable uncertainty remains over how increasing atmospheric CO2 and anthropogenic climate changes are affecting open‐ocean marine ecosystems from phytoplankton to top predators. Biological time series data are thus urgently needed for the world’s oceans. Here, we use the carbon stable isotope composition of tuna to provide a first insight into the existence of global trends in complex ecosystem dynamics and changes in the oceanic carbon cycle. From 2000 to 2015, considerable declines in δ13C values of 0.8‰–2.5‰ were observed across three tuna species sampled globally, with more substantial changes in the Pacific Ocean compared to the Atlantic and Indian Oceans. Tuna recorded not only the Suess effect, that is, fossil fuel‐derived and isotopically light carbon being incorporated into marine ecosystems, but also recorded profound changes at the base of marine food webs. We suggest a global shift in phytoplankton community structure, for example, a reduction in 13C‐rich phytoplankton such as diatoms, and/or a change in phytoplankton physiology during this period, although this does not rule out other concomitant changes at higher levels in the food webs. Our study establishes tuna δ13C values as a candidate essential ocean variable to assess complex ecosystem responses to climate change at regional to global scales and over decadal timescales. Finally, this time series will be invaluable in calibrating and validating global earth system models to project changes in marine biota.

Revisiting the distribution of marine N2 fixation

Marine N2 fixation supports a significant portion of oceanic primary production by making N2 bioavailable to planktonic communities, in the process influencing atmosphere-ocean carbon fluxes and our global climate. However, the geographical distribution and controlling factors of marine N2 fixation remain elusive largely due to sparse observations. Here we present unprecedented high-resolution underway N2 fixation estimates across over 6,000 kilometers of the western North Atlantic. Unexpectedly, we find increasing N2 fixation rates from the oligotrophic Sargasso Sea to North America coastal waters, driven primarily by cyanobacterial diazotrophs. N2 fixation is best correlated to phosphorus availability and chlorophyll-a concentration. Globally, intense N2 fixation activity in the coastal oceans is validated by a meta-analysis of published observations and we estimate the annual coastal N2 fixation flux to be 16.7 Tg N. This study broadens the biogeography of N2 fixation, highlights the interplay of regulating factors, and reveals thriving diazotrophic communities in coastal waters with potential significance to the global nitrogen cycle.

For more information, see publication.

 

Towards quantitative microbiome community profiling using internal standards.

High-throughput sequencing based marine microbiome profiling is rapidly expanding and changing how we study the oceans. Although powerful, the technique is not fully quantitative – it only provides taxon counts in relative abundances. In order to address this issue, we presented a method to quantitatively estimate microbial abundances per unit volume of seawater filtered by spiking in known amounts of internal DNA standards to each sample. We validated this method by comparing the calculated abundances to other independent estimates including chemical markers (pigments) and total bacterial cell counts by flow cytometry. The internal standard approach allows us to quantitatively estimate and compare marine microbial community profiles, with important implications for linking environmental microbiomes to quantitative processes such as metabolic and biogeochemical rates.

QMP and RMP using internal DNA standard method.

PhD Students Alex and Weiyi Take Part in NASA EXPORTS Research Cruise

PhD students Alex Niebergall and Weiyi Tang participated in a NASA-funded research cruise in the Northern Pacific Ocean as part of the Export Processes in the Ocean from Remote Sensing (EXPORTS) project. EXPORTS is a multi-institutional research initiative that seeks to develop a predictive understanding of the export and fate of global ocean net primary production and its implications for present and future climates. The students’ research project specifically looked at the role marine microbes play in drawing carbon dioxide out of the atmosphere.

Duke Environment corresponded with PhD students Alexandria Niebergall and Weiyi Tang to discuss their experience on the EXPORTS research cruise, what sparked their interest in the field and how it will contribute to their own research moving forward.

Factors confounding the interpretation of the oceanic carbon export ratio

See Li and Cassar 2018.

The fraction of primary production exported out of the surface ocean, known as the export ratio ( ef-ratio), is often used to assess how various factors, including temperature, primary production, phytoplankton size and community structure, affect the export efficiency of an ecosystem. To investigate possible causes for reported discrepancies in the dominant factors influencing the export efficiency, we develop a metabolism-based mechanistic model of the ef-ratio. Consistent with earlier studies, we find based on theoretical considerations that the ef-ratio is a negative function of temperature. We show that the -ratio depends on the optical depth, defined as the physical depth times the light attenuation coefficient. As a result, varying light attenuation may confound the interpretation of ef-ratio when measured at a fixed depth (e.g., 100 m) or at the base of the mixed layer. Finally, we decompose the contribution of individual factors on the seasonality of the ef-ratio. Our results show that at high latitudes, the ef-ratio at the base of mixed layer is strongly influenced by mixed layer depth and surface irradiation on seasonal timescales. Future studies should report the ef-ratio at the base of euphotic layer, or account for the effect of varying light attenuation if measured at a different depth. Overall, our modeling study highlights the large number of factors confounding the interpretation of field observations of the ef-ratio.

 

    

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