Category: Lab News (Page 2 of 4)

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 (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.

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.

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.