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The proportion of major elements in marine organic matter links cellular processes to global nutrient, oxygen and carbon cycles. Differences in the C:N:P ratios of organic matter have been observed between ocean biomes, but these patterns have yet to be quantified from the underlying small-scale physiological and ecological processes. Here we use an ecosystem model that includes adaptive resource allocation within and between ecologically distinct plankton size classes to attribute the causes of global patterns in the C:N:P ratios. We find that patterns of N:C variation are largely driven by common physiological adjustment strategies across all phytoplankton, while patterns of N:P are driven by ecological selection for taxonomic groups with different phosphorus storage capacities. Although N:C varies widely due to cellular adjustment to light and nutrients, its latitudinal gradient is modest because of depth-dependent trade-offs between nutrient and light availability. Strong latitudinal variation in N:P reflects an ecological balance favouring small plankton with lower P storage capacity in the subtropics, and larger eukaryotes with a higher cellular P storage capacity in nutrient-rich high latitudes. A weaker N:P difference between southern and northern hemispheres, and between the Atlantic and Pacific oceans, reflects differences in phosphate available for cellular storage. Despite simulating only two phytoplankton size classes, the emergent global variability of elemental ratios resembles that of all measured species, suggesting that the range of growth conditions and ecological selection sustain the observed diversity of stoichiometry among phytoplankton.

Limnology and Oceanography, 68 (6), ISSN:0024-3590, ISSN:1939-5590

Climate change-driven trends in phytoplankton populations, as viewed by Earth-observing satellites, were thought to be masked by strong natural variability, so that >30 years of continuous data was needed to detect a climate trend. Here we show that climate change trends emerge more rapidly in ocean color (remote sensing reflectance, Rrs), as Rrs is multivariate and some wavebands have low interannual variability. We find significant trends in a twenty-year time-series of Rrs from the MODIS-Aqua satellite over 52% of the global surface ocean, primarily equatorward of 40º. The climate change signal in Rrs emerges after twenty years in similar regions covering a similar fraction of the ocean in a state-of-the-art ecosystem model, implying that the observed trends may indeed be driven by climate change. Ocean color may thus be a sentinel of climate change in surface ocean ecology and biogeochemistry.

Global biogeochemical ocean models are invaluable tools to examine how physical, chemical, and biological processes interact in the ocean. Satellite-derived ocean-color properties, on the other hand, provide observations of the surface ocean with unprecedented coverage and resolution. Advances in our understanding of marine ecosystems and biogeochemistry are strengthened by the combined use of these resources, together with sparse in situ data. Recent modeling advances allow simulation of the spectral properties of phytoplankton and remote-sensing reflectances, bringing model outputs closer to the kind of data that ocean-color satellites can provide. However, comparisons between model outputs and analogous satellite products (e.g. chlorophyll-a) remain problematic: Most evaluations are based on point-by-point comparisons in space and time where spuriously large errors can occur from small spatial and temporal mismatches, whereas global statistics provide no information on how well a model resolves processes at regional scales. Here, we employ a unique suite of methodologies, Probability Density Functions to Evaluate Models (PDFEM), which generate a robust comparison of these resources. The probability density functions of physical and biological properties of Longhurst's provinces are compared, to evaluate how well a model resolves related processes. Differences in the distributions of chlorophyll-a concentration [mg m-3] provide information on matches and mismatches between models and observations. In particular, mismatches help isolate regional sources of discrepancy, which can lead to improving both simulations and satellite algorithms. Furthermore, the use of radiative transfer in the model to mimic remotely-sensed products facilitate model-observation comparisons of optical properties of the ocean.

Climate change is altering marine biogeochemistry, thereby modifying factors affecting the formation and trophic transfer of the bioaccumulative neurotoxicant methylmercury (MeHg) in the global ocean. However, both the directionality and magnitude of future changes are unclear. Here we use a coupled 3-D atmosphere-ocean-ecology model to forecast how MeHg concentrations in the surface ocean will respond to changes in primary production and associated carbon export in 2100. Model results suggest a 68-93% increase in MeHg in the polar oceans and a 23% decrease in the high-latitude North Atlantic Ocean. Phytoplankton MeHg reservoirs will increase at high-latitudes and decrease in the mid- and low-latitude oceans due to a poleward shift in habitat. Ocean acidification is projected to increase phytoplankton MeHg reservoirs globally by promoting the growth of Synechococcus, a small phytoplankton species that efficiently accumulates MeHg. Changes in MeHg reservoirs in herbivorous zooplankton mimic their prey but with larger magnitudes due to non-linearity embedded in the food web structure. The effect of climate-driven shifts in marine biogeochemistry thus needs to be considered in evaluating future trajectories in biological MeHg concentrations.

Significance Marine microbe growth is limited by iron over about half of the global ocean surface. Dissolved iron is quickly lost from the ocean, but its availability to marine microbes may be enhanced by binding with organic molecules which, in turn, are produced by microbes. We hypothesize this forms a reinforcing cycle between biological activity and iron cycling that locally matches the availability of iron and other nutrients, leading to global-scale resource colimitation between macronutrients and micronutrients, and maximizing biological productivity. Idealized models support this hypothesis, depending on the specific relationships between microbial sources and sinks of organic molecules. An evolutionary selection may have occurred which optimizes these characteristics, resulting in “just enough” iron in the ocean., Iron is the limiting factor for biological production over a large fraction of the surface ocean because free iron is rapidly scavenged or precipitated under aerobic conditions. Standing stocks of dissolved iron are maintained by association with organic molecules (ligands) produced by biological processes. We hypothesize a positive feedback between iron cycling, microbial activity, and ligand abundance: External iron input fuels microbial production, creating organic ligands that support more iron in seawater, leading to further macronutrient consumption until other microbial requirements such as macronutrients or light become limiting, and additional iron no longer increases productivity. This feedback emerges in numerical simulations of the coupled marine cycles of macronutrients and iron that resolve the dynamic microbial production and loss of iron-chelating ligands. The model solutions resemble modern nutrient distributions only over a finite range of prescribed ligand source/sink ratios where the model ocean is driven to global-scale colimitation by micronutrients and macronutrients and global production is maximized. We hypothesize that a global-scale selection for microbial ligand cycling may have occurred to maintain “just enough” iron in the ocean.

Marine diazotrophs fix dinitrogen gas into bioavailable nitrogen that drives the ocean nitrogen cycle; yet, efforts to infer global diazotroph distributions have been limited by a sparsity of observations. In situ measurements of nifH gene abundance (essential for nitrogen fixation) are increasingly being used to inform the biogeography of diazotrophs. However, comparing such gene abundances spatially, temporally and between diazotroph species remains difficult. We synthesize existing data on gene-to-cell and cell-to-biomass conversions for four major diazotroph groups to convert nifH gene counts to abundance- and biomass-based biogeographic "currencies." Results suggest up to two orders of magnitude uncertainty converting from nifH gene abundance to cell abundance, and up to four orders of magnitude uncertainty from nifH gene abundance to biomass. Uncertainty arises due to large taxonomic variation in cell size and presumed polyploidy, that is, variability in the number of genomes per cell. Such uncertainties hinder comparing biogeographies of different species. Additionally, numerical models need biogeographies for validation, typically in the currency of carbon biomass. Here, we show that conversion uncertainty from nifH gene abundance to biomass overwhelms biomass variability simulated in such models. These results demonstrate a basic currency problem in converting gene abundance observations to biogeographically meaningful quantities for synthesizing studies and modeling approaches. Such issues may also have relevance to other genes and organisms beyond diazotrophs. To avoid biases in interpreting gene counts as a measure of abundance, we suggest converting gene counts to a binary presence/non-detect metric to map broad biogeographical distributions more robustly., Limnology and Oceanography, 67 (4), ISSN:0024-3590, ISSN:1939-5590

Remote sensing observations from satellites and global biogeochemical models have combined to revolutionize the study of ocean biogeochemical cycling, but comparing the two data streams to each other and across time remains challenging due to the strong spatial-temporal structuring of the ocean. Here, we show that the Wasserstein distance provides a powerful metric for harnessing these structured datasets for better marine ecosystem and climate predictions. Wasserstein distance complements commonly used point-wise difference methods such as the root mean squared error, by quantifying differences in terms of spatial displacement in addition to magnitude. As a test case we consider Chlorophyll (a key indicator of phytoplankton biomass) in the North-East Pacific Ocean, obtained from model simulations, in situ measurements, and satellite observations. We focus on two main applications: 1) Comparing model predictions with satellite observations, and 2) temporal evolution of Chlorophyll both seasonally and over longer time frames. Wasserstein distance successfully isolates temporal and depth variability and quantifies shifts in biogeochemical province boundaries. It also exposes relevant temporal trends in satellite Chlorophyll consistent with climate change predictions. Our study shows that optimal transport vectors underlying Wasserstein distance provide a novel visualization tool for testing models and better understanding temporal dynamics in the ocean., Comment: 6 figures

Significance Prochlorococcus is the smallest and most abundant photosynthetic organism on Earth and is thought to be confined to low-latitude regions by its requirement for warm waters. Latitudinal transects in the North Pacific, however, demonstrate that the poleward decrease of this species occurs across a wide range of temperatures. An additional mechanism is likely required. We use theory, computational models, and additional observational data to suggest that the poleward decrease is caused by an ecological interaction: a shared predator which consumes both Prochlorococcus and similar-sized heterotrophic bacteria. Understanding the fate of this organism requires a knowledge of the interconnected ecosystem of other organisms, where both direct and indirect interactions control community structure., Prochlorococcus is both the smallest and numerically most abundant photosynthesizing organism on the planet. While thriving in the warm oligotrophic gyres, Prochlorococcus concentrations drop rapidly in higher-latitude regions. Transect data from the North Pacific show the collapse occurring at a wide range of temperatures and latitudes (temperature is often hypothesized to cause this shift), suggesting an ecological mechanism may be at play. An often used size-based theory of phytoplankton community structure that has been incorporated into computational models correctly predicts the dominance of Prochlorococcus in the gyres, and the relative dominance of larger cells at high latitudes. However, both theory and computational models fail to explain the poleward collapse. When heterotrophic bacteria and predators that prey nonspecifically on both Prochlorococcus and bacteria are included in the theoretical framework, the collapse of Prochlorococcus occurs with increasing nutrient supplies. The poleward collapse of Prochlorococcus populations then naturally emerges when this mechanism of “shared predation” is implemented in a complex global ecosystem model. Additionally, the theory correctly predicts trends in both the abundance and mean size of the heterotrophic bacteria. These results suggest that ecological controls need to be considered to understand the biogeography of Prochlorococcus and predict its changes under future ocean conditions. Indirect interactions within a microbial network can be essential in setting community structure.

Methylmercury (CH3Hg+, MMHg) in the phytoplankton and zooplankton, which form the bottom of marine food webs, is a good predictor of MMHg in top predators, including humans. Therefore, evaluating the potential exposure of MMHg to higher trophic levels (TLs) requires a better understanding of relationships between MMHg biomagnification and plankton dynamics. In this study, a coupled ecological/physical model with 366 plankton types of different sizes, biogeochemical functions, and temperature tolerance is used to simulate the relationships between MMHg biomagnification and the ecosystem structure. The study shows that the MMHg biomagnification becomes more significant with increasing TLs. Trophic magnification factors (TMFs) in the lowest two TLs show the opposite spatial pattern to TMFs in higher TLs. The low TMFs are usually associated with a short food-chain length. The less bottom-heavy trophic pyramids in the oligotrophic oceans enhance the MMHg trophic transfer. The global average TMF is increased from 2.3 to 2.8 in the warmer future with a medium climate sensitivity of 2.5 °C. Our study suggests that if there are no mitigation measures for Hg emission, MMHg in the high-trophic-level plankton is increased more dramatically in the warming future, indicating greater MMHg exposure for top predators such as humans.

Marine phytoplankton generate half of global primary production, making them essential to ecosystem functioning and biogeochemical cycling. Though phytoplankton are phylogenetically diverse, studies rarely designate unique thermal traits to different taxa, resulting in coarse representations of phytoplankton thermal responses. Here we assessed phytoplankton functional responses to temperature using empirically derived thermal growth rates from four principal contributors to marine productivity: diatoms, dinoflagellates, cyanobacteria, and coccolithophores. Using modeled sea surface temperatures for 1950–1970 and 2080–2100, we explored potential alterations to each group’s growth rates and geographical distribution under a future climate change scenario. Contrary to the commonly applied Eppley formulation, our data suggest phytoplankton functional types may be characterized by different temperature coefficients (Q10), growth maxima thermal dependencies, and thermal ranges which would drive dissimilar responses to each degree of temperature change. These differences, when applied in response to global simulations of future temperature, result in taxon-specific projections of growth and geographic distribution, with low-latitude coccolithophores facing considerable decreases and cyanobacteria substantial increases in growth rates. These results suggest that the singular effect of changing temperature may alter phytoplankton global community structure, owing to the significant variability in thermal response between phytoplankton functional types., Phytoplankton communities are important players in biogeochemical processes, but are sensitive to global warming. Here, a meta-analysis shows how the varied responses of phytoplankton to rising temperatures could potentially alter growth dynamics and community structure in a future ocean.

Plankton play an important role in marine food webs, in biogeochemical cycling, and in moderating Earth's climate. Their possible responses to climate change are of broad scientific and social inte...

The inventory and variability of oceanic dissolved inorganic carbon (DIC) is driven by the interplay of physical, chemical, and biological processes. Quantifying the spatiotemporal variability of these drivers is crucial for a mechanistic understanding of the ocean carbon sink and its future trajectory. Here, we use the Estimating the Circulation and Climate of the Ocean-Darwin ocean biogeochemistry state estimate to generate a global-ocean, data-constrained DIC budget and investigate how spatial and seasonal-to-interannual variability in three-dimensional circulation, air-sea CO2 flux, and biological processes have modulated the ocean sink for 1995–2018. Our results demonstrate substantial compensation between budget terms, resulting in distinct upper-ocean carbon regimes. For example, boundary current regions have strong contributions from vertical diffusion while equatorial regions exhibit compensation between upwelling and biological processes. When integrated across the full ocean depth, the 24-year DIC mass increase of 64 Pg C (2.7 Pg C year−1) primarily tracks the anthropogenic CO2 growth rate, with biological processes providing a small contribution of 2 (1.4 Pg C). In the upper 100 m, which stores roughly 13 (8.1 Pg C) of the global increase, we find that circulation provides the largest DIC gain (6.3 Pg C year−1) and biological processes are the largest loss (8.6 Pg C year−1). Interannual variability is dominated by vertical advection in equatorial regions, with the 1997–1998 El Niño-Southern Oscillation causing the largest year-to-year change in upper-ocean DIC (2.1 Pg C). Our results provide a novel, data-constrained framework for an improved mechanistic understanding of natural and anthropogenic perturbations to the ocean sink. © 2022. The Authors.

Light, essential for photosynthesis, is present in two periodic cycles in nature: seasonal and diel. Although seasonality of light is typically resolved in ocean ecosystem and biogeochemistry models because of its significance for seasonal succession and biogeography of phytoplankton, the diel light cycle is generally not resolved. Here we use a three-dimensional global ocean model and compare high temporal resolution simulations with and without diel light cycles. The model simulates 15 phytoplankton types of different cell size, encompassing two broad ecological strategies: small cells with high nutrient affinity (gleaners) and larger cells with high maximal growth rate (opportunists). Both are grazed by zooplankton and limited by nitrogen, phosphorus and iron. Simulations show that diel cycles of light induce diel cycles in phytoplankton populations and limiting nutrients in the global ocean. Diel nutrient cycles are associated with higher concentration of limiting nutrients by up to 200% at low latitudes (-40° to 40°), a process that increases opportunists’ biomass by up to 50%. Size classes with the highest maximal growth rates from both gleaner and opportunist groups are favored the most by diel light cycles. This mechanism weakens as latitude increases because the effects of the seasonal cycle dominate over those of the diel cycle. The present work shows that resource competition under diel light cycles has a significant impact on phytoplankton biogeography, indicating the necessity of resolving diel processes in global ocean models.

Climate‐change‐induced alterations of oceanic conditions will lead to the ecological niches of some marine phytoplankton species disappearing, at least regionally. How will such losses affect the ecosystem and the coupled biogeochemical cycles? Here, we couch this question in terms of ecological redundancy (will other species be able to fill the ecological roles of the extinct species) and biogeochemical redundancy (can other species replace their biogeochemical roles). Prior laboratory and field studies point to a spectrum in the degree of redundancy. We use a global three‐dimensional computer model with diverse planktonic communities to explore these questions further. The model includes 35 phytoplankton types that differ in size, biogeochemical function and trophic strategy. We run two series of experiments in which single phytoplankton types are either partially or fully eliminated. The niches of the targeted types were not completely reoccupied, often with a reduction in the transfer of matter from autotrophs to heterotrophs. Primary production was often decreased, but sometimes increased due to reduction in grazing pressure. Complex trophic interactions (such as a decrease in the stocks of a predator's grazer) led to unexpected reshuffling of the community structure. Alterations in resource utilization may cause impacts beyond the regions where the type went extinct. Our results suggest a lack of redundancy, especially in the ‘knock on’ effects on higher trophic levels. Redundancy appeared lowest for types on the edges of trait space (e.g. smallest) or with unique competitive strategies. Though highly idealized, our modelling findings suggest that the results from laboratory or field studies often do not adequately capture the ramifications of functional redundancy. The modelled, often counterintuitive, responses—via complex food web interactions and bottom‐up versus top‐down controls—indicate that changes in planktonic community will be key determinants of future ocean global change ecology and biogeochemistry., Climate change induced alterations of oceanic conditions will lead to the ecological niches of some marine phytoplankton species disappearing, at least regionally. We use a computer model to explore phytoplankton ecological redundancy (i.e., will other species be able to fill the ecological roles of the extinct species) and biogeochemical redundancy (i.e., can other species replace their biogeochemical roles). The results are often counterintuitive due to complex foodweb interactions, interplay of bottom‐up versus top‐down controls, and non‐local effects; responses that laboratory or field studies may not adequately capture.

Mercury is a potent neurotoxin that poses health risks to the global population. Anthropogenic mercury emissions to the atmosphere are projected to decrease in the future due to enhanced policy efforts such as the Minamata Convention, a legally-binding international treaty entered into force in 2017. Here, we report the development of a comprehensive climate-atmosphere-land-ocean-ecosystem and exposure-risk model framework for mercury and its application to project the health effects of future atmospheric emissions. Our results show that the accumulated health effects associated with mercury exposure during 2010–2050 are $19 (95% confidence interval: 4.7–54) trillion (2020 USD) realized to 2050 (3% discount rate) for the current policy scenario. Our results suggest a substantial increase in global human health cost if emission reduction actions are delayed. This comprehensive modeling approach provides a much-needed tool to help parties to evaluate the effectiveness of Hg emission controls as required by the Minamata Convention., Mercury is a neurotoxin and pollutant with enhanced emissions from anthropogenic activities. Here, the authors develop a global emissions, transport, and human risk model and find substantial future losses in revenue and public health if emission reductions proposed by the Minamata Convention are delayed.

Quantifying variability in the ocean carbon sink remains problematic due to sparse observations and spatiotemporal variability in surface ocean pCO2. To address this challenge, we have updated and improved ECCO‐Darwin, a global ocean biogeochemistry model that assimilates both physical and biogeochemical observations. The model consists of an adjoint‐based ocean circulation estimate from the Estimating the Circulation and Climate of the Ocean (ECCO) consortium and an ecosystem model developed by the Massachusetts Institute of Technology Darwin Project. In addition to the data‐constrained ECCO physics, a Green's function approach is used to optimize the biogeochemistry by adjusting initial conditions and six biogeochemical parameters. Over seasonal to multidecadal timescales (1995–2017), ECCO‐Darwin exhibits broad‐scale consistency with observed surface ocean pCO2 and air‐sea CO2 flux reconstructions in most biomes, particularly in the subtropical and equatorial regions. The largest differences between CO2 uptake occur in subpolar seasonally stratified biomes, where ECCO‐Darwin results in stronger winter uptake. Compared to the Global Carbon Project OBMs, ECCO‐Darwin has a time‐mean global ocean CO2 sink (2.47 ± 0.50 Pg C year−1) and interannual variability that are more consistent with interpolation‐based products. Compared to interpolation‐based methods, ECCO‐Darwin is less sensitive to sparse and irregularly sampled observations. Thus, ECCO‐Darwin provides a basis for identifying and predicting the consequences of natural and anthropogenic perturbations to the ocean carbon cycle, as well as the climate‐related sensitivity of marine ecosystems. Our study further highlights the importance of physically consistent, property‐conserving reconstructions, as are provided by ECCO, for ocean biogeochemistry studies.

Global marine eco-provinces are determined toward tackling complexity and to explore community structure using unsupervised ML., An unsupervised learning method is presented for determining global marine ecological provinces (eco-provinces) from plankton community structure and nutrient flux data. The systematic aggregated eco-province (SAGE) method identifies eco-provinces within a highly nonlinear ecosystem model. To accommodate the non-Gaussian covariance of the data, SAGE uses t-stochastic neighbor embedding (t-SNE) to reduce dimensionality. Over a hundred eco-provinces are identified with the density-based spatial clustering of applications with noise (DBSCAN) algorithm. Using a connectivity graph with ecological dissimilarity as the distance metric, robust aggregated eco-provinces (AEPs) are objectively defined by nesting the eco-provinces. Using the AEPs, the control of nutrient supply rates on community structure is explored. Eco-provinces and AEPs are unique and aid model interpretation. They could facilitate model intercomparison and potentially improve understanding and monitoring of marine ecosystems.