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

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See also original publication in Nature Communications

Since the middle of the past century, the Western Antarctic Peninsula has warmed rapidly with a significant loss of sea ice but the impacts on plankton biodiversity and carbon cycling remain an open question. Here, using a 5-year dataset of eukaryotic plankton DNA metabarcoding, we assess changes in biodiversity and net community production in this region. Our results show that sea-ice extent is a dominant factor influencing eukaryotic plankton community composition, biodiversity, and net community production. Species richness and evenness decline with an increase in sea surface temperature (SST). In regions with low SST and shallow mixed layers, the community was dominated by a diverse assemblage of diatoms and dinoflagellates. Conversely, less diverse plankton assemblages were observed in waters with higher SST and/or deep mixed layers when sea ice extent was lower. A genetic programming machine-learning model explained up to 80% of the net community production variability at the Western Antarctic Peninsula. Among the biological explanatory variables, the sea-ice environment associated plankton assemblage is the best predictor of net community production. We conclude that eukaryotic plankton diversity and carbon cycling at the Western Antarctic Peninsula are strongly linked to sea-ice conditions.

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The significance of the water-side gas transfer velocity for air–sea CO₂ gas exchange (k) and its non-linear dependence on wind speed (U) is well accepted. What remains a subject of inquiry are biases associated with the form of the non-linear relation linking k to U (hereafter labeled as f(U), where f(.) stands for an arbitrary function of U), the distributional properties of U (treated as a random variable) along with other external factors influencing k, and the time-averaging period used to determine k from U. To address the latter issue, a Taylor series expansion is applied to separate f(U) into a term derived from time-averaging wind speed (labeled as ⟨U⟩, where ⟨.⟩ indicates averaging over a monthly time scale) as currently employed in climate models and additive bias corrections that vary with the statistics of U. The method was explored for nine widely used f(U) parameterizations based on remotely-sensed 6-hourly global wind products at 10 m above the sea-surface. The bias in k of monthly estimates compared to the reference 6-hourly product was shown to be mainly associated with wind variability captured by the standard deviation σσU around ⟨U⟩ or, more preferably, a dimensionless coefficient of variation Iu= σσU/⟨U⟩. The proposed correction outperforms previous methodologies that adjusted k when using ⟨U⟩ only. An unexpected outcome was that upon setting I2u = 0.15 to correct biases when using monthly wind speed averages, the new model produced superior results at the global and regional scale compared to prior correction methodologies. Finally, an equation relating I2u to the time-averaging interval (spanning from 6 h to a month) is presented to enable other sub-monthly averaging periods to be used. While the focus here is on CO₂, the theoretical tactic employed can be applied to other slightly soluble gases. As monthly and climatological wind data are often used in climate models for gas transfer estimates, the proposed approach provides a robust scheme that can be readily implemented in current climate models

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.

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

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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 (GPP_LD) and the triple isotopes of dissolved oxygen (GPP_17Δ)_.The two algorithms predict global GPPs of 9.2 ± 1.3 * 10¹⁵ and 15.1 ± 1.05 * 10¹⁵ mol O₂ yr^-1 for GPP_LD and GPP_17Δ, respectively. The projected GPP distributions agree with our understanding of the mechanisms regulating primary production. Global GPP_17Δwas higher than GPP_LD by an average factor of 1.6 which varied meridionally. The discrepancy between GPP_17Δ and GPP_LD simulations can be partly explained by the known biases of each methodology. After accounting for some of these biases, the GPP_17Δ and GPP_LD 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 (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.

See a news article describing Yajuan’s experience on the ACE expedition.

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.

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.

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.

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.