Nutrient supply controls particulate elemental concentrations and ratios in the low latitude eastern Indian Ocean

Learning stochastic dynamics and predicting emergent behavior using transformers

We show that a neural network originally designed for language processing can learn the dynamical rules of a stochastic system by observation of a single dynamical trajectory of the system, and can accurately predict its emergent behavior under conditions not observed during training. We consider a lattice model of active matter undergoing continuous-time Monte Carlo dynamics, simulated at a density at which its steady state comprises small, dispersed clusters. We train a neural network called a transformer on a single trajectory of the model. The transformer, which we show has the capacity to represent dynamical rules that are numerous and nonlocal, learns that the dynamics of this model consists of a small number of processes. Forward-propagated trajectories of the trained transformer, at densities not encountered during training, exhibit motility-induced phase separation and so predict the existence of a nonequilibrium phase transition. Transformers have the flexibility to learn dynamical rules from observation without explicit enumeration of rates or coarse-graining of configuration space, and so the procedure used here can be applied to a wide range of physical systems, including those with large and complex dynamical generators.

Metals profile in deep-sea sediment from an active tectonic region around Simeulue Island, Aceh, Indonesia

Simeulue waters are adjacent to the northern part of Sumatra Island, which is undergoing massive land-use transformations; moreover, the waters are located in an active tectonic region. Land changes and tectonic activity might affect the metal pollution profile in this deep sea area. Thus, this study aimed to investigate the vertical profile and assess the sediment quality from the deep-sea marine sediment around Simeulue Island based on metal concentration. Seventy-six bottom sediment samples were collected from eight cores at a water depth of up to 2800 m in the Simeulue waters, Indonesia, in November 2017. Metals Cd, Cu, Fe, Ni, Pb, and Zn were quantified from the cores and multivariate analyses were carried out to understand the process. Metals distributions are analogous to the grain size parameters and LOI₅₅₀ distribution pattern, while Sumatra and Simeulue islands influenced grain size and LOI₅₅₀ spatial distribution. The vertical grain size profile exhibited no extreme oscillation in the investigated cores. Thus, sediment transport from the Island was the main suspect for these metals' profiles in the deep water, and the tectonic activity had a minor impact. Cu, Ni, Pb, and Zn tend to rise in the collected cores, suggesting that the accumulation of the metals is growing. While Fe tended to be stable and Cd oscillated in the cores. Indices were computed to assess the metal contamination profile. The cores were dominated by EF class 1 (none to slight enrichment) status and I_geo class 1 (unpolluted). Cd was the metal of concern in the study since a high Cd was observed in some layers (maximum EF = 26.45 and maximum I_geo = 3.81). Thus, this study can be used as a database to improve the regulation formulation for improved environmental managerial efforts in the region.

Bacteria and Archaea Regulate Particulate Organic Matter Export in Suspended and Sinking Marine Particle Fractions

The biological carbon pump (BCP) in the Southern Ocean is driven by phytoplankton productivity and is a significant organic matter sink. However, the role of particle-attached (PA) and free-living (FL) prokaryotes (bacteria and archaea) and their diversity in influencing the efficiency of the BCP is still unclear. To investigate this, we analyzed the metagenomes linked to suspended and sinking marine particles from the Sub-Antarctic Southern Ocean Time Series (SOTS) by deploying a Marine Snow Catcher (MSC), obtaining suspended and sinking particulate material, determining organic carbon and nitrogen flux, and constructing metagenome-assembled genomes (MAGs). The suspended and sinking particle-pools were dominated by bacteria with the potential to degrade organic carbon. Bacterial communities associated with the sinking fraction had more genes related to the degradation of complex organic carbon than those in the suspended fraction. Archaea had the potential to drive nitrogen metabolism via nitrite and ammonia oxidation, altering organic nitrogen concentration. The data revealed several pathways for chemoautotrophy and the secretion of recalcitrant dissolved organic carbon (RDOC) from CO₂, with bacteria and archaea potentially sequestering particulate organic matter (POM) via the production of RDOC. These findings provide insights into the diversity and function of prokaryotes in suspended and sinking particles and their role in organic carbon/nitrogen export in the Southern Ocean. IMPORTANCE The biological carbon pump is crucial for the export of particulate organic matter in the ocean. Recent studies on marine microbes have shown the profound influence of bacteria and archaea as regulators of particulate organic matter export. Yet, despite the importance of the Southern Ocean as a carbon sink, we lack comparable insights regarding microbial contributions. This study provides the first insights regarding prokaryotic contributions to particulate organic matter export in the Southern Ocean. We reveal evidence that prokaryotic communities in suspended and sinking particle fractions harbor widespread genomic potential for mediating particulate organic matter export. The results substantially enhance our understanding of the role played by microorganisms in regulating particulate organic matter export in suspended and sinking marine fractions in the Southern Ocean.

Nutrient uptake plasticity in phytoplankton sustains future ocean net primary production

Annually, marine phytoplankton convert approximately 50 billion tons of dissolved inorganic carbon to particulate and dissolved organic carbon, a portion of which is exported to depth via the biological carbon pump. Despite its important roles in regulating atmospheric carbon dioxide via carbon sequestration and in sustaining marine ecosystems, model-projected future changes in marine net primary production are highly uncertain even in the sign of the change. Here, using an Earth system model, we show that frugal utilization of phosphorus by phytoplankton under phosphate-stressed conditions can overcompensate the previously projected 21st century declines due to ocean warming and enhanced stratification. Our results, which are supported by observations from the Hawaii Ocean Time-series program, suggest that nutrient uptake plasticity in the subtropical ocean plays a key role in sustaining phytoplankton productivity and carbon export production in a warmer world.

Global Ocean Particulate Organic Phosphorus, Carbon, Oxygen for Respiration, and Nitrogen (GO-POPCORN)

Concentrations and elemental stoichiometry of suspended particulate organic carbon, nitrogen, phosphorus, and oxygen demand for respiration (C:N:P:−O2) play a vital role in characterizing and quantifying marine elemental cycles. Here, we present Version 2 of the Global Ocean Particulate Organic Phosphorus, Carbon, Oxygen for Respiration, and Nitrogen (GO-POPCORN) dataset. Version 1 is a previously published dataset of particulate organic matter from 70 different studies between 1971 and 2010, while Version 2 is comprised of data collected from recent cruises between 2011 and 2020. The combined GO-POPCORN dataset contains 2673 paired surface POC/N/P measurements from 70°S to 73°N across all major ocean basins at high spatial resolution. Version 2 also includes 965 measurements of oxygen demand for organic carbon respiration. This new dataset can help validate and calibrate the next generation of global ocean biogeochemical models with flexible elemental stoichiometry. We expect that incorporating variable C:N:P:-O2 into models will help improve our estimates of key ocean biogeochemical fluxes such as carbon export, nitrogen fixation, and organic matter remineralization.

Global patterns and predictors of C:N:P in marine ecosystems

Oceanic nutrient cycles are coupled, yet carbon-nitrogen-phosphorus (C:N:P) stoichiometry in marine ecosystems is variable through space and time, with no clear consensus on the controls on variability. Here, we analyze hydrographic, plankton genomic diversity, and particulate organic matter data from 1970 stations sampled during a global ocean observation program (Bio-GO-SHIP) to investigate the biogeography of surface ocean particulate organic matter stoichiometry. We find latitudinal variability in C:N:P stoichiometry, with surface temperature and macronutrient availability as strong predictors of stoichiometry at high latitudes. Genomic observations indicated community nutrient stress and suggested that nutrient supply rate and nitrogen-versus-phosphorus stress are predictive of hemispheric and regional variations in stoichiometry. Our data-derived statistical model suggests that C:P and N:P ratios will increase at high latitudes in the future, however, changes at low latitudes are uncertain. Our findings suggest systematic regulation of elemental stoichiometry among ocean ecosystems, but that future changes remain highly uncertain.

Upwelling and nutrient dynamics in the Arabian Gulf and sea of Oman

This study demonstrates the vertical and horizontal distribution of nutrients and the seasonal response of nutrients to upwelling in the Arabian Gulf and the Sea of Oman. Thus, monthly data on nitrate, phosphate, and silicate are obtained from the World Ocean Atlas 2018 (WOA), as well as estimates of coastal and curl driven upwelling in both regions. The results of the study indicate that the Sea of Oman's surface and deep waters contained higher concentrations of nutrients than the Arabian Gulf by 80%. In addition, both regions have exhibited a general increase in the vertical distribution of nutrients as the depth increases. Among the aforementioned nutrients, nitrate is found to be a more limiting nutrient for phytoplankton growth than phosphate as the nitrate-to-phosphate ratios (N:P) in surface waters are lower (≤ 4.6:1) than the Redfield ratio (16:1). As for the upwelling, curl-driven upwelling accounts for more than half of the total upwelling in both regions, and both play an important role in nutrient transport. Thus, nutrients are upwelled from the subsurface to the mixed layer at a rate of 50% in the Oman Sea from 140 m to 20 m during the summer and to 40 m during the winter. Similarly, the Arabian Gulf shows 50% transport for nitrates, but 32% for phosphates, from 20 m to 5-10 m. However, due to the abundance of diatoms at the surface of the Arabian Gulf, the surface silicate content is 30% higher than that of the deeper waters.

Environmental control of marine phytoplankton stoichiometry in the North Atlantic Ocean

The stoichiometric coupling of carbon to limiting nutrients in marine phytoplankton regulates the magnitude of biological carbon sequestration in the ocean. While clear links between plankton C:N ratios and environmental drivers have been identified, the nature and direction of these links, as well as their underlying physiological and ecological controls, remain uncertain. We show, with a well-constrained mechanistic model of plankton ecophysiology, that while nitrogen availability and temperature emerge as the main drivers of phytoplankton C:N stoichiometry in the North Atlantic, the biological mechanisms involved vary depending on the spatiotemporal scale and region considered. We find that phytoplankton C:N stoichiometry is overall controlled by nitrogen availability below 40° N, predominantly driven by ecoevolutionary shifts in the functional composition of the phytoplankton communities, while phytoplankton stoichiometric plasticity in response to dropping temperatures and increased grazing pressure dominates at higher latitudes. Our findings highlight the potential of "organisms-to-ecosystems" modeling approaches based on mechanistic models of plankton biology accounting for physiology, ecology, and trait evolution to explore and explain complex observational data and ultimately improve the predictions of global ocean models.

Learning non-stationary Langevin dynamics from stochastic observations of latent trajectories

Many complex systems operating far from the equilibrium exhibit stochastic dynamics that can be described by a Langevin equation. Inferring Langevin equations from data can reveal how transient dynamics of such systems give rise to their function. However, dynamics are often inaccessible directly and can be only gleaned through a stochastic observation process, which makes the inference challenging. Here we present a non-parametric framework for inferring the Langevin equation, which explicitly models the stochastic observation process and non-stationary latent dynamics. The framework accounts for the non-equilibrium initial and final states of the observed system and for the possibility that the system's dynamics define the duration of observations. Omitting any of these non-stationary components results in incorrect inference, in which erroneous features arise in the dynamics due to non-stationary data distribution. We illustrate the framework using models of neural dynamics underlying decision making in the brain.

Responses of Marine Diatom-Dinoflagellate Competition to Multiple Environmental Drivers: Abundance, Elemental, and Biochemical Aspects

Ocean-related global change has strongly affected the competition between key marine phytoplankton groups, such as diatoms and dinoflagellates, especially with the deleterious consequency of the increasing occurrence of harmful algal blooms. The dominance of diatoms generally shifts toward that of dinoflagellates in response to increasing temperature and reduced nutrient availability; however, contradictory findings have also been observed in certain sea areas. A key challenge in ecology and biogeochemistry is to quantitatively determine the effects of multiple environmental factors on the diatom-dinoflagellate community and the related changes in elemental and biochemical composition. Here, we test the interplay between temperature, nutrient concentrations and their ratios on marine diatom-dinoflagellate competition and chemical composition using bi-algal competition experiments. The ubiquitous diatom Phaeodactylum tricornutum and dinoflagellate Prorocentrum minimum were cultivated semi-continuously, provided with different N and P concentrations (three different levels) and ratios (10:1, 24:1, and 63:1 molar ratios) under three temperatures (12, 18, and 24°C). The responses of diatom-dinoflagellate competition were analyzed by a Lotka-Volterra model and quantified by generalized linear mixed models (GLMMs) and generalized additive models (GAMs). The changes in nutrient concentrations significantly affected diatom-dinoflagellate competition, causing a competitive superiority of the diatoms at high nutrient concentrations, independent of temperature and N:P supply ratios. Interestingly, the effect amplitude of nutrient concentrations varied with different temperatures, showing a switch back toward a competitive superiority of the dinoflagellates at the highest temperature and at very high nutrient concentrations. The ratios of particulate organic nitrogen to phosphorus showed significant negative correlations with increasing diatoms/dinoflagellates ratios, while lipid biomarkers (fatty acids and sterols) correlated positively with increasing diatoms/dinoflagellates ratios over the entire ranges of temperature, N and P concentrations and N:P ratios. Our results indicate that the integration of phytoplankton community structure and chemical composition provides an important step forward to quantitatively understand and predict how phytoplankton community changes affect ecosystem functions and biogeochemical cycles in the ocean.

Quantitative study of conservative gradient force and non-conservative scattering force exerted on a spherical particle in optical tweezers

We rigorously calculate the conservative gradient force (GF) and the non-conservative scattering force (SF) associated with the optical tweezers (the single beam optical trap). A wide range of parameters are considered, with particle size ranging from the Rayleigh to Mie regime (radius ∼3 µm), dielectric constant ranging from metallic (large and negative) to high dielectrics (large and positive), numerical aperture (NA) ranging from 0.5 to 1.33, and different polarizations. The trap depth associated with GF can reach 123 and 168 k_BT per mW for a 0.5 µm-radius polystyrene particle illuminated by a 1064 nm Gaussian beam with NA = 0.9 and 1.3, respectively. This indicates that unless at a low beam power or with a small NA, the Brownian fluctuations do not play a role in the stability. The transverse GF orthogonal to beam propagation always dominates over the transverse SF. While the longitudinal SF can be larger than the longitudinal GF when the scattering is strong, the NA is small, or when absorption is present, optical trapping under these conditions is difficult. Generally speaking, absorption reduces GF and enhances SF, while increasing a dielectric constant enhances GF slightly but boosts SF significantly owing to stronger scattering. These results verify previous experimental observations and explain why optical tweezers are so robust across such a wide range of conditions. Our quantitative calculations will also provide a guide to future studies.

Nutrient ratios in marine particulate organic matter are predicted by the population structure of well-adapted phytoplankton

A common assumption of a constant nitrogen-to-phosphorus ratio (N:P) of 16:1 in marine particulate organic matter (POM) appears to be invalidated by observations of major spatial variations in N:P. Two main explanations have been proposed. The first attributes the N:P variability to changes in the community composition of well-adapted phytoplankton. The second proposes that variability arises from physiological acclimation involving intracellular adjustments of nutrient allocation under nutrient deficiency. Using a model of phytoplankton physiology, observational datasets, and a review of laboratory culture results, we assess the mechanistic basis of N:P variability. We find that the taxonomic composition of well-adapted phytoplankton best explains observed variations in POM N:P. Furthermore, we show that acclimation to nutrient deficiency may be safely neglected when considering the effects of ecology on POM N:P. These findings provide insight into the controls on global variability in POM composition and average phytoplankton physiological performance in the oceans.

Linking regional shifts in microbial genome adaptation with surface ocean biogeochemistry

Linking 'omics measurements with biogeochemical cycles is a widespread challenge in microbial community ecology. Here, we propose applying genomic adaptation as 'biosensors' for microbial investments to overcome nutrient stress. We then integrate this genomic information with a trait-based model to predict regional shifts in the elemental composition of marine plankton communities. We evaluated this approach using metagenomic and particulate organic matter samples from the Atlantic, Indian and Pacific Oceans. We find that our genome-based trait model significantly improves our prediction of particulate C : P (carbon : phosphorus) across ocean regions. Furthermore, we detect previously unrecognized ocean areas of iron, nitrogen and phosphorus stress. In many ecosystems, it can be very challenging to quantify microbial stress. Thus, a carefully calibrated genomic approach could become a widespread tool for understanding microbial responses to environmental changes and the biogeochemical outcomes. This article is part of the theme issue 'Conceptual challenges in microbial community ecology'.

Marine nitrogen fixers mediate a low latitude pathway for atmospheric CO2 drawdown

Roughly a third (~30 ppm) of the carbon dioxide (CO₂) that entered the ocean during ice ages is attributed to biological mechanisms. A leading hypothesis for the biological drawdown of CO₂ is iron (Fe) fertilisation of the high latitudes, but modelling efforts attribute at most 10 ppm to this mechanism, leaving ~20 ppm unexplained. We show that an Fe-induced stimulation of dinitrogen (N₂) fixation can induce a low latitude drawdown of 7–16 ppm CO₂. This mechanism involves a closer coupling between N₂ fixers and denitrifiers that alleviates widespread nitrate limitation. Consequently, phosphate utilisation and carbon export increase near upwelling zones, causing deoxygenation and deeper carbon injection. Furthermore, this low latitude mechanism reproduces the regional patterns of organic δ¹⁵N deposited in glacial sediments. The positive response of marine N₂ fixation to dusty ice age conditions, first proposed twenty years ago, therefore compliments high latitude changes to amplify CO₂ drawdown.

Iron fertilisation of the high latitude oceans is a well-established biological mechanism to explain the ice age drawdown of atmospheric CO₂, yet modelling has so far struggled to account for a sufficient drawdown via this mechanism. Here, the authors propose that N₂ fixers, which inhabit the lower latitude ocean, made a significant contribution to CO₂ drawdown and so amplified the global response to iron fertilisation during ice ages.