Dugenne, Mathilde, Marco Corrales-Ugalde, Jessica Y Luo, Rainer Kiko, Todd D O'Brien, Jean-Olivier Irisson, Fabien Lombard, Lars Stemmann, and Charles A Stock, et al., June 2024: First release of the Pelagic Size Structure database: global datasets of marine size spectra obtained from plankton imaging devices. Earth System Science Data, 16(6), DOI:10.5194/essd-16-2971-20242971-2999. Abstract
In marine ecosystems, most physiological, ecological, or physical processes are size dependent. These include metabolic rates, the uptake of carbon and other nutrients, swimming and sinking velocities, and trophic interactions, which eventually determine the stocks of commercial species, as well as biogeochemical cycles and carbon sequestration. As such, broad-scale observations of plankton size distribution are important indicators of the general functioning and state of pelagic ecosystems under anthropogenic pressures. Here, we present the first global datasets of the Pelagic Size Structure database (PSSdb), generated from plankton imaging devices. This release includes the bulk particle normalized biovolume size spectrum (NBSS) and the bulk particle size distribution (PSD), along with their related parameters (slope, intercept, and R2) measured within the epipelagic layer (0–200 m) by three imaging sensors: the Imaging FlowCytobot (IFCB), the Underwater Vision Profiler (UVP), and benchtop scanners. Collectively, these instruments effectively image organisms and detrital material in the 7–10 000 µm size range. A total of 92 472 IFCB samples, 3068 UVP profiles, and 2411 scans passed our quality control and were standardized to produce consistent instrument-specific size spectra averaged to 1° × 1° latitude and longitude and by year and month. Our instrument-specific datasets span most major ocean basins, except for the IFCB datasets we have ingested, which were exclusively collected in northern latitudes, and cover decadal time periods (2013–2022 for IFCB, 2008–2021 for UVP, and 1996–2022 for scanners), allowing for a further assessment of the pelagic size spectrum in space and time. The datasets that constitute PSSdb's first release are available at https://doi.org/10.5281/zenodo.11050013 (Dugenne et al., 2024b). In addition, future updates to these data products can be accessed at https://doi.org/10.5281/zenodo.7998799.
Phytoplankton stoichiometry modulates the interaction between carbon, nitrogen and phosphorus cycles. Environmentally driven variations in phytoplankton C:N:P can alter biogeochemical cycling compared to expectations under fixed ratios. In fact, the assumption of fixed C:N:P has been linked to Earth System Model (ESM) biases and potential misrepresentation of responses to future change. Here we integrate key elements of the Adaptive Trait Optimization Model (ATOM) for phytoplankton stoichiometry with the Carbon, Ocean Biogeochemistry and Lower Trophics (COBALT) ocean biogeochemical model. Within a series of global ocean-ice-ecosystem retrospective simulations, ATOM-COBALT reproduced observations of phytoplankton N:P, and compared to static ratios, exhibited reduced phytoplankton P-limitation, enhanced N-fixation, and increased low-latitude export, improving consistency with observations and highlighting the biogeochemical implications of dynamic N:P. We applied ATOM-COBALT to explore the impacts of different physiological mechanisms hypothesized to underlie N:P variation, finding that two mechanisms together drove the observed patterns: proportionality of P-rich ribosomes in phytoplankton cells to growth rates and reductions in P-storage during scarcity. A third mechanism which linked temperature with phytoplankton biomass allocations to non-ribosomal proteins, led only to relatively modest impacts because this mechanism decreased the temperature dependence of phytoplankton growth rates, compensating for changes in N:P. We find that there are quantitative response differences that associate distinctive biogeochemical footprints with each mechanism, which are most apparent in highly productive low-latitude regions. These results suggest that variable phytoplankton N:P makes phytoplankton productivity and export resilient to environmental changes, and support further research on the physiological and environmental drivers of phytoplankton stoichiometry and biogeochemical role.
Pelagic tunicates (salps, pyrosomes) and fishes generate jelly falls and/or fecal pellets that sink roughly 10 times faster than bulk oceanic detritus, but their impacts on biogeochemical cycles in the ocean interior are poorly understood. Using a coupled physical-biogeochemical model, we find that fast-sinking detritus decreased global net primary production and surface export, but increased deep sequestration and transfer efficiency in much of the extratropics and upwelling zones. Fast-sinking detritus generally decreased total suboxic and hypoxic volumes, reducing a “large oxygen minimum zone (OMZ)” bias common in global biogeochemical models. Newly aerobic regions at OMZ edges exhibited reduced transfer efficiencies in contrast with global tendencies. Reductions in water column denitrification resulting from improved OMZs improved simulated nitrate deficits relative to phosphate. The carbon flux to the benthos increased by 11% with fast-sinking detritus from fishes and pelagic tunicates, yet simulated benthic fluxes remained on the lower end of observation-based estimates.
Martin, Adrian P., Angela Bahamondes Dominguez, Chelsey A Baker, Chloé M J Baumas, Kelsey M Bisson, Emma Cavan, Mara Freilich, Eric D Galbraith, Martí Galí, Stephanie A Henson, Karin F Kvale, Carsten Lemmen, and Jessica Y Luo, et al., December 2024: When to add a new process to a model – and when not: A marine biogeochemical perspective. Ecological Modelling, 498, DOI:10.1016/j.ecolmodel.2024.110870. Abstract
Models are critical tools for environmental science. They allow us to examine the limits of what we think we know and to project that knowledge into situations for which we have little or no data. They are by definition simplifications of reality. There are therefore inevitably times when it is necessary to consider adding a new process to a model that was previously omitted. Doing so may have consequences. It can increase model complexity, affect the time a model takes to run, impact the match between the model output and observations, and complicate comparison to previous studies using the model. How a decision is made on whether to add a process is no more objective than how a scientist might design a laboratory experiment. To illustrate this, we report on an event where a broad and diverse group of marine biogeochemists were invited to construct flowcharts to support making the decision of when to include a new process in a model. The flowcharts are used to illustrate both the complexity of factors that modellers must consider prior to making a decision on model development and the diversity of perspectives on how that decision should be reached. The purpose of this paper is not to provide a definitive protocol for making that decision. Instead, we argue that it is important to acknowledge that there is no objectively “best” approach and instead we discuss the flowcharts created as a means of encouraging modellers to think through why and how they are doing something. This may also hopefully guide observational scientists to understand why it may not always be appropriate to include a process they are studying in a model.
Negrete-García, Gabriela, Jessica Y Luo, Colleen M Petrik, Manfredi Manizza, and Andrew D Barton, November 2024: Changes in Arctic Ocean plankton community structure and trophic dynamics on seasonal to interannual timescales. Biogeosciences, 21(22), DOI:10.5194/bg-21-4951-20244951-4973. Abstract
The Arctic Ocean experiences significant seasonal to interannual environmental changes, including in temperature, light, sea ice, and surface nutrient concentrations, that influence the dynamics of marine plankton populations. Here, we use a hindcast simulation (1948–2009) of size-structured Arctic Ocean plankton communities, ocean circulation, and biogeochemical cycles in order to better understand how seasonal to interannual changes in the environment influence phytoplankton physiology, plankton community structure, trophic dynamics, and fish production in the Arctic Ocean. The growth of model phytoplankton was primarily limited in winter, spring, and fall by light, but in summer, the growth of smaller and larger phytoplankton was mostly limited by temperature and nutrient availability, respectively. The dominant trophic pathway in summer was from phytoplankton to herbivorous zooplankton such that the average trophic position of model zooplankton was lower in the summer growing season compared to the rest of the year. On interannual timescales, changes in plankton community composition were strongly tied to interannual changes in bottom-up forcing by the environment. In the summer, in years with less ice and warmer temperatures, the biomass of phytoplankton and zooplankton was higher, the size–abundance relationship slopes were more negative (indicative of a phytoplankton community enriched in smaller phytoplankton), zooplankton had higher mean trophic position (indicative of greater carnivory), and potential fishery production was greater, fueled by increased mesozooplankton biomass and flux of organic matter to the benthos. The summertime shift toward greater carnivory in warmer and low-ice years was due primarily to changes in phenology, with phytoplankton and microzooplankton blooms occurring approximately 1 month earlier in these conditions and carnivorous zooplankton increasing in abundance during summer. The model provides a spatially and temporally complete overview of simulated changes in plankton communities in the Arctic Ocean occurring on seasonal to interannual timescales, and it provides insights into the mechanisms underlying these changes as well as their broader biogeochemical and ecosystem significance.
Stamieszkin, Karen, Nicole C Millette, Jessica Y Luo, Elizabeth M Follett, Nicholas R Record, and David G Johns, March 2024: Large protistan mixotrophs in the North Atlantic Continuous Plankton Recorder time series: associated environmental conditions and trends. Frontiers in Marine Science, 11, DOI:10.3389/fmars.2024.1320046. Abstract
Aquatic ecologists are integrating mixotrophic plankton – here defined as microorganisms with photosynthetic and phagotrophic capacity – into their understanding of marine food webs and biogeochemical cycles. Understanding mixotroph temporal and spatial distributions, as well as the environmental conditions under which they flourish, is imperative to understanding their impact on trophic transfer and biogeochemical cycling. Mixotrophs are hypothesized to outcompete strict photoautotrophs and heterotrophs when either light or nutrients are limiting, but testing this hypothesis has been hindered by the challenge of identifying and quantifying mixotrophs in the field. Using field observations from a multi-decadal northern North Atlantic dataset, we calculated the proportion of organisms that are considered mixotrophs within individual microplankton samples. We also calculated a “trophic index” that represents the relative proportions of photoautotrophs (phytoplankton), mixotrophs, and heterotrophs (microzooplankton) in each sample. We found that the proportion of mixotrophs was positively correlated with temperature, and negatively with either light or inorganic nutrient concentration. This proportion was highest during summertime thermal stratification and nutrient limitation, and lowest during the North Atlantic spring bloom period. Between 1958 and 2015, changes in the proportion of mixotrophs coincided with changes in the Atlantic Multi-decadal Oscillation (AMO), was highest when the AMO was positive, and showed a significant uninterrupted increase in offshore regions from 1992-2015. This study provides an empirical foundation for future experimental, time series, and modeling studies of aquatic mixotrophs.
Deposition of mineral dust plays an important role in upper-ocean biogeochemical processes, particularly by delivering iron to iron-limited regions. Here we examine the impact of dynamically changing iron deposition on tropical Pacific Ocean biogeochemistry in fully coupled earth system model projections under several emissions scenarios. Projected end-of-21st-century increases in central tropical Pacific dust and iron deposition strengthen with increasing emissions/radiative forcing, and are aligned with projected soil moisture decreases in adjacent land areas and precipitation increases over the equatorial Pacific. Increased delivery of soluble iron results in a reduction in, and eastward contraction of, equatorial Pacific phytoplankton iron limitation and shifts primary production and particulate organic carbon flux projections relative to a high emissions projection (SSP5-8.5) wherein soluble iron deposition is prescribed as a static climatology. These results highlight modeling advances in representing coupled land-air-sea interactions to project basin-scale patterns of ocean biogeochemical change.
Greer, Adam T., Moritz Schmid, Patrick I Duffy, Kelly L Robinson, Mark A Genung, Jessica Y Luo, Thelma Panaïotis, Christian Briseño-Avena, Marc E Frischer, Su Sponaugle, and Robert Cowen, January 2023: In situ imaging across ecosystems to resolve the fine-scale oceanographic drivers of a globally significant planktonic grazer. Limnology and Oceanography, 68(1), DOI:10.1002/lno.12259192-207. Abstract
Doliolids are common gelatinous grazers in marine ecosystems around the world and likely influence carbon cycling due to their large population sizes with high growth and excretion rates. Aggregations or blooms of these organisms occur frequently, but they are difficult to measure or predict because doliolids are fragile, under sampled with conventional plankton nets, and can aggregate on fine spatial scales (1–10 m). Moreover, ecological studies typically target a single region or site that does not encompass the range of possible habitats favoring doliolid proliferation. To address these limitations, we combined in situ imaging data from six coastal ecosystems, including the Oregon shelf, northern California, southern California Bight, northern Gulf of Mexico, Straits of Florida, and Mediterranean Sea, to resolve and compare doliolid habitat associations during warm months when environmental gradients are strong and doliolid blooms are frequently documented. Higher ocean temperature was the strongest predictor of elevated doliolid abundances across ecosystems, with additional variance explained by chlorophyll a fluorescence and dissolved oxygen. For marginal seas with a wide range of productivity regimes, the nurse stage tended to comprise a higher proportion of the doliolids when total abundance was low. However, this pattern did not hold in ecosystems with persistent coastal upwelling. The doliolids tended to be most aggregated in oligotrophic systems (Mediterranea and southern California), suggesting that microhabitats within the water column favor proliferation on fine spatial scales. Similar comparative approaches can resolve the realized niche of fast-reproducing marine animals, thus improving predictions for population-level responses to changing oceanographic conditions.
Millette, Nicole C., Rebecca J Gast, and Jessica Y Luo, et al., June 2023: Mixoplankton and mixotrophy: future research priorities. Journal of Plankton Research, fbad020, DOI:10.1093/plankt/fbad020. Abstract
Phago-mixotrophy, the combination of photoautotrophy and phagotrophy in mixoplankton, organisms that can combine both trophic strategies, have gained increasing attention over the past decade. It is now recognized that a substantial number of protistan plankton species engage in phago-mixotrophy to obtain nutrients for growth and reproduction under a range of environmental conditions. Unfortunately, our current understanding of mixoplankton in aquatic systems significantly lags behind our understanding of zooplankton and phytoplankton, limiting our ability to fully comprehend the role of mixoplankton (and phago-mixotrophy) in the plankton food web and biogeochemical cycling. Here, we put forward five research directions that we believe will lead to major advancement in the field: (i) evolution: understanding mixotrophy in the context of the evolutionary transition from phagotrophy to photoautotrophy; (ii) traits and trade-offs: identifying the key traits and trade-offs constraining mixotrophic metabolisms; (iii) biogeography: large-scale patterns of mixoplankton distribution; (iv) biogeochemistry and trophic transfer: understanding mixoplankton as conduits of nutrients and energy; and (v) in situ methods: improving the identification of in situ mixoplankton and their phago-mixotrophic activity.
The pelagic tunicates, gelatinous zooplankton that include salps, doliolids, and appendicularians, are filter feeding grazers thought to produce a significant amount of particulate organic carbon (POC) detritus. However, traditional sampling methods (i.e., nets), have historically underestimated their abundance, yielding an overall underappreciation of their global biomass and contribution to ocean biogeochemical cycles relative to crustacean zooplankton. As climate change is projected to decrease the average plankton size and POC export from traditional plankton food webs, the ecological and biogeochemical role of pelagic tunicates may increase; yet, pelagic tunicates were not resolved in the previous generation of global earth system climate projections. Here we present a global ocean study using a coupled physical-biogeochemical model to assess the impact of pelagic tunicates in the pelagic food web and biogeochemical cycling. We added two tunicate groups, a large salp/doliolid and a small appendicularian to the NOAA-GFDL Carbon, Ocean Biogeochemistry, and Lower Trophics version 2 (COBALTv2) model, which was originally formulated to represent carbon flows to crustacean zooplankton. The new GZ-COBALT simulation was able to simultaneously satisfy new pelagic tunicate biomass constraints and existing ecosystem constraints, including crustacean zooplankton observations. The model simulated a global tunicate biomass of 0.10 Pg C, annual tunicate production of 0.49 Pg C y-1 in the top 100 m, and annual tunicate detritus production of 0.98 Pg C y-1 in the top 100 m. Tunicate-mediated export flux was 0.71 Pg C y-1, representing 11% of the total export flux past 100 m. Overall export from the euphotic zone remained largely constant, with the GZ-COBALT pe-ratio only increasing 5.3% (from 0.112 to 0.118) compared to the COBALTv2 control. While the bulk of the tunicate-mediated export production resulted from the rerouting of phytoplankton- and mesozooplankton-mediated export, tunicates also shifted the overall balance of the upper oceans away from recycling and towards export. Our results suggest that pelagic tunicates play important trophic roles in both directly competing with microzooplankton and indirectly shunting carbon export away from the microbial loop.
Plankton community models are critical tools for understanding the processes that shape marine plankton communities, how plankton communities impact biogeochemical cycles, and the feedbacks between community structure and function. Here, using the flexible Marine Biogeochemistry Library (MARBL), we present the Size-based Plankton ECological TRAits (MARBL-SPECTRA) model, which is designed to represent a diverse plankton community while remaining computationally tractable. MARBL-SPECTRA is composed of nine phytoplankton and six zooplankton size classes represented using allometric scaling relationships for physiological traits and interactions within multiple functional types. MARBL-SPECTRA is embedded within the global ocean component of the Community Earth System Model (CESM) and simulates large-scale, emergent patterns in phytoplankton growth limitation, plankton phenology, plankton generation time, and trophic transfer efficiency. The model qualitatively reproduces observed global patterns of surface nutrients, chlorophyll biomass, net primary production, and the biogeographies of a range of plankton size classes. In addition, the model simulates how predator:prey dynamics and trophic efficiency vary across gradients in total ecosystem productivity. Shorter food chains that export proportionally more carbon from the surface to the ocean interior occur in productive, eutrophic regions, whereas in oligotrophic regions, the food chains are relatively long and export less organic matter from the surface. The union of functional type modeling with size-resolved, trait-based modeling approaches allows MARBL-SPECTRA to capture both large-scale elemental cycles and the structure of planktonic food webs affecting trophic transfer efficiency.
Petrik, Colleen M., Jessica Y Luo, Ryan F Heneghan, Jason D Everett, Cheryl S Harrison, and Anthony J Richardson, November 2022: Assessment and constraint of mesozooplankton in CMIP6 Earth system models. Global Biogeochemical Cycles, 36(11), DOI:10.1029/2022GB007367. Abstract
Although zooplankton play a substantial role in the biological carbon pump and serve as a crucial link between primary producers and higher trophic level consumers, the skillful representation of zooplankton is not often a focus of ocean biogeochemical models. Systematic evaluations of zooplankton in models could improve their representation, but so far, ocean biogeochemical skill assessment of Earth system model (ESM) ensembles have not included zooplankton. Here we use a recently developed global, observationally based map of mesozooplankton biomass to assess the skill of mesozooplankton in six CMIP6 ESMs. We also employ a biome-based assessment of the ability of these models to reproduce the observed relationship between mesozooplankton biomass and surface chlorophyll. The combined analysis found that most models were able to reasonably simulate the large regional variations in mesozooplankton biomass at the global scale. Additionally, three of the ESMs simulated a mesozooplankton-chlorophyll relationship within the observational bounds, which we used as an emergent constraint on future mesozooplankton projections. We highlight where differences in model structure and parameters may give rise to varied mesozooplankton distributions under historic and future conditions, and the resultant wide ensemble spread in projected changes in mesozooplankton biomass. Despite differences, the strength of the mesozooplankton-chlorophyll relationships across all models was related to the projected changes in mesozooplankton biomass globally and in regional biomes. These results suggest that improved observations of mesozooplankton and their relationship to chlorophyll will better constrain projections of climate change impacts on these important animals.
Harrison, Cheryl S., and Jessica Y Luo, et al., February 2021: Identifying global favourable habitat for early juvenile loggerhead sea turtles. Journal of the Royal Society Interface, 18(175), DOI:10.1098/rsif.2020.0799. Abstract
Loggerhead sea turtles (Caretta caretta) nest globally on sandy beaches, with hatchlings dispersing into the open ocean. Where these juveniles go and what habitat they rely on remains a critical research question for informing conservation priorities. Here a high-resolution Earth system model is used to determine the biophysical geography of favourable ocean habitat for loggerhead sea turtles globally during their first year of life on the basis of ocean current transport, thermal constraints and food availability (defined here as the summed lower trophic level carbon biomass). Dispersal is simulated from eight major nesting sites distributed across the globe in four representative years using particle tracking. Dispersal densities are identified for all turtles, and for the top 15% ‘best-fed’ turtles that have not encountered metabolically unfavourable temperatures. We find that, globally, rookeries are positioned to disperse to regions where the lower trophic biomass is greatest within loggerheads' thermal range. Six out of the eight nesting sites are associated with strong coastal boundary currents that rapidly transport hatchlings to subtropical–subpolar gyre boundaries; narrow spatial migratory corridors exist for ‘best-fed’ turtles associated with these sites. Two other rookeries are located in exceptionally high-biomass tropical regions fuelled by natural iron fertilization. ‘Best-fed’ turtles tend to be associated with lower temperatures, highlighting the inverse relationship between temperature and lower trophic biomass. The annual mean isotherms between 20°C and the thermal tolerance of juvenile loggerheads are a rough proxy for favourable habitat for loggerheads from rookeries associated with boundary currents. Our results can be used to constrain regions for conservation efforts for each subpopulation, and better identify foraging habitat for this critical early life stage.
Kearney, Kelly A., Steven J Bograd, Elizabeth J Drenkard, Fabien A Gomez, Melissa A Haltuch, Albert Hermann, Michael G Jacox, Isaac C Kaplan, Stefan Koenigstein, and Jessica Y Luo, et al., August 2021: Using global-scale Earth system models for regional fisheries applications. Frontiers in Marine Science, DOI:10.3389/fmars.2021.622206. Abstract
Climate change may impact ocean ecosystems through a number of mechanisms, including shifts in primary productivity or plankton community structure, ocean acidification, and deoxygenation. These processes can be simulated with global Earth system models (ESMs), which are increasingly being used in the context of fisheries management and other living marine resource (LMR) applications. However, projections of LMR-relevant metrics such as net primary production can vary widely between ESMs, even under identical climate scenarios. Therefore, the use of ESM should be accompanied by an understanding of the structural differences in the biogeochemical sub-models within ESMs that may give rise to these differences. This review article provides a brief overview of some of the most prominent differences among the most recent generation of ESM and how they are relevant to LMR application.
Long, Matthew C., J Keith Moore, Keith Lindsay, Michael Levy, Scott C Doney, Jessica Y Luo, Kristen M Krumhardt, Robert T Letscher, Maxwell Grover, and Zephyr T Sylvester, December 2021: Simulations with the Marine Biogeochemistry Library (MARBL). Journal of Advances in Modeling Earth Systems, 13(12), DOI:10.1029/2021MS002647. Abstract
The Marine Biogeochemistry Library (MARBL) is a prognostic ocean biogeochemistry model that simulates marine ecosystem dynamics and the coupled cycles of carbon, nitrogen, phosphorus, iron, silicon, and oxygen. MARBL is a component of the Community Earth System Model (CESM); it supports flexible ecosystem configuration of multiple phytoplankton and zooplankton functional types; it is also portable, designed to interface with multiple ocean circulation models. Here, we present scientific documentation of MARBL, describe its configuration in CESM2 experiments included in the Coupled Model Intercomparison Project version 6 (CMIP6), and evaluate its performance against a number of observational data sets. The model simulates present-day air-sea CO2 flux and many aspects of the carbon cycle in good agreement with observations. However, the simulated integrated uptake of anthropogenic CO2 is weak, which we link to poor thermocline ventilation, a feature evident in simulated chlorofluorocarbon distributions. This also contributes to larger-than-observed oxygen minimum zones. Moreover, radiocarbon distributions show that the simulated circulation in the deep North Pacific is extremely sluggish, yielding extensive oxygen depletion and nutrient trapping at depth. Surface macronutrient biases are generally positive at low latitudes and negative at high latitudes. CESM2 simulates globally integrated net primary production (NPP) of 48 Pg C yr−1 and particulate export flux at 100 m of 7.1 Pg C yr−1. The impacts of climate change include an increase in globally integrated NPP, but substantial declines in the North Atlantic. Particulate export is projected to decline globally, attributable to decreasing export efficiency associated with changes in phytoplankton community composition.
Robinson, Kelly L., Su Sponaugle, Jessica Y Luo, Miram R Gleiber, and Robert Cowen, November 2021: Big or small, patchy all: Resolution of marine plankton patch structure at micro- to submesoscales for 36 taxa. Science Advances, 7(47), DOI:10.1126/sciadv.abk2904. Abstract
Despite the ecological importance of microscale (0.01–1 meter) and fine-scale (1 to hundreds of meters) plankton patchiness, the dimensions and taxonomic identity of patches in the ocean are nearly unknown. We used underwater imaging to identify the position, horizontal length scale, and density of taxa-specific patches of 32 million organisms representing 36 taxa (200 micrometers to 20 centimeters) in the continental and oceanic environments of a subtropical, western boundary current. Patches were the most frequent in shallow, continental waters. For multiple taxa, patch count varied parabolically with background density. Taxa-specific patch length and organism size exhibited negative size scaling relationships. Organism size explained 21 to 30% of the variance in patch length. The dominant length scale was phylogenetically random and <100 meters for 64% of taxa. The predominance of micro- and fine-scale patches among a diverse suite of plankton suggests social and coactive processes may contribute to patch formation.
Krumhardt, Kristen M., Nicole S Lovenduski, Matthew C Long, and Jessica Y Luo, et al., June 2020: Potential Predictability of Net Primary Production in the Ocean. Global Biogeochemical Cycles, 34(6), DOI:10.1029/2020GB006531. Abstract
Interannual variations in marine net primary production (NPP) contribute to the variability of available living marine resources, as well as influence critical carbon cycle processes. Here we provide a global overview of near‐term (1 to 10 years) potential predictability of marine NPP using a novel set of initialized retrospective decadal forecasts from an Earth System Model. Interannual variations in marine NPP are potentially predictable in many areas of the ocean 1 to 3 years in advance, from temperate waters to the tropics, showing a substantial improvement over a simple persistence forecast. However, some regions, such as the subpolar Southern Ocean, show low potential predictability. We analyze how bottom‐up drivers of marine NPP (nutrients, light, and temperature) contribute to its predictability. Regions where NPP is primarily driven by the physical supply of nutrients (e.g., subtropics) retain higher potential predictability than high‐latitude regions where NPP is controlled by light and/or temperature (e.g., the Southern Ocean). We further examine NPP predictability in the world's Large Marine Ecosystems. With a few exceptions, we show that initialized forecasts improve potential predictability of NPP in Large Marine Ecosystems over a persistence forecast and may aid to manage living marine resources.
Luo, Jessica Y., Robert H Condon, and Charles A Stock, et al., September 2020: Gelatinous zooplankton-mediated carbon flows in the global oceans: A data-driven modeling study. Global Biogeochemical Cycles, 34(9), DOI:10.1029/2020GB006704. Abstract
Among marine organisms, gelatinous zooplankton (GZ; cnidarians, ctenophores, and pelagic tunicates) are unique in their energetic efficiency, as the gelatinous body plan allows them to process and assimilate high proportions of oceanic carbon. Upon death, their body shape facilitates rapid sinking through the water column, resulting in carcass depositions on the seafloor (“jelly‐falls”). GZ are thought to be important components of the biological pump, but their overall contribution to global carbon fluxes remains unknown. Using a data‐driven, three‐dimensional, carbon cycle model resolved to a 1° global grid, with a Monte Carlo uncertainty analysis, we estimate that GZ consumed 7.9–13 Pg C y−1 in phytoplankton and zooplankton, resulting in a net production of 3.9–5.8 Pg C y−1 in the upper ocean (top 200 m), with the largest fluxes from pelagic tunicates. Non‐predation mortality (carcasses) comprised 25% of GZ production, and combined with the much greater fecal matter flux, total GZ particulate organic carbon (POC) export at 100 m was 1.6–5.2 Pg C y−1, equivalent to 32–40% of the global POC export. The fast sinking GZ export resulted in a high transfer efficiency (Teff) of 38–62% to 1,000 m and 25–40% to the seafloor. Finally, jelly‐falls at depths >50 m are likely unaccounted for in current POC flux estimates and could increase benthic POC flux by 8–35%. The significant magnitude of and distinct sinking properties of GZ fluxes support a critical yet underrecognized role of GZ carcasses and fecal matter to the biological pump and air‐sea carbon balance.
Schmid, Moritz, Robert Cowen, Kelly L Robinson, Jessica Y Luo, Christian Briseño-Avena, and Su Sponaugle, January 2020: Prey and predator overlap at the edge of a mesoscale eddy: fine-scale, in-situ distributions to inform our understanding of oceanographic processes. Scientific Reports, 10, DOI:10.1038/s41598-020-57879-x. Abstract
Eddies can enhance primary as well as secondary production, creating a diverse meso- and sub-mesoscale seascape at the eddy front which can affect the aggregation of plankton and particles. Due to the coarse resolution provided by sampling with plankton nets, our knowledge of plankton distributions at these edges is limited. We used a towed, undulating underwater imaging system to investigate the physical and biological drivers of zoo- and ichthyoplankton aggregations at the edge of a decaying mesoscale eddy (ME) in the Straits of Florida. Using a sparse Convolutional Neural Network we identified 132 million images of plankton. Larval fish and Oithona spp. copepod concentrations were significantly higher in the eddy water mass, compared to the Florida Current water mass, only four days before the ME's dissipation. Larval fish and Oithona distributions were tightly coupled, indicating potential predator-prey interactions. Larval fishes are known predators of Oithona, however, Random Forests models showed that Oithona spp. and larval fish concentrations were primarily driven by variables signifying the physical footprint of the ME, such as current speed and direction. These results suggest that eddy-related advection leads to largely passive overlap between predator and prey, a positive, energy-efficient outcome for predators at the expense of prey.
Séférian, Roland, Sarah Berthet, Andrew Yool, Julien Palmieri, Laurent Bopp, Alessandro Tagliabue, Lester Kwiatkowski, Olivier Aumont, James R Christian, John P Dunne, Marion Gehlen, Tatiana Ilyina, Jasmin G John, Hongmei Li, Matthew C Long, Jessica Y Luo, Hideyuki Nakano, Anastasia Romanou, Jörg Schwinger, and Charles A Stock, et al., August 2020: Tracking Improvement in Simulated Marine Biogeochemistry Between CMIP5 and CMIP6. Current Climate Change Reports, 6, DOI:10.1007/s40641-020-00160-095-119. Abstract
Purpose of Review:
The changes or updates in ocean biogeochemistry component have been mapped between CMIP5 and CMIP6 model versions, and an assessment made of how far these have led to improvements in the simulated mean state of marine biogeochemical models within the current generation of Earth system models (ESMs).
Recent Findings:
The representation of marine biogeochemistry has progressed within the current generation of Earth system models. However, it remains difficult to identify which model updates are responsible for a given improvement. In addition, the full potential of marine biogeochemistry in terms of Earth system interactions and climate feedback remains poorly examined in the current generation of Earth system models.
Summary:
Increasing availability of ocean biogeochemical data, as well as an improved understanding of the underlying processes, allows advances in the marine biogeochemical components of the current generation of ESMs. The present study scrutinizes the extent to which marine biogeochemistry components of ESMs have progressed between the 5th and the 6th phases of the Coupled Model Intercomparison Project (CMIP).
Cordero-Quirós, Nathalí, Arthur J Miller, A Subramanian, Jessica Y Luo, and Antonietta Capotondi, October 2019: Composite physical-biological El Niño and La Niña conditions in the California Current System in CESM1-POP2-BEC. Ocean Modelling, 142, DOI:10.1016/j.ocemod.2019.101439. Abstract
El Niño-Southern Oscillation (ENSO) is recognized as one of the potentially predictable drivers of California Current System (CCS) variability. In this study, we analyze a 67-year coarse-resolution (1°) simulation using the ocean model CESM-POP2-BEC forced by NCEP/NCAR reanalysis winds to develop a model composite of the physical-biological response of the CCS during ENSO events. The model results are also compared with available observations. The composite anomalies for sea surface temperature (SST), pycnocline depth, 0m-100m vertically averaged chlorophyll, 0m-100m vertically averaged zooplankton, 25m-100m vertically averaged nitrate, and oxygen at 200m depth exhibit large-scale coherent relationships between physics and the ecosystem, including reduced nutrient and plankton concentrations during El Niño, and increased nutrient and plankton concentrations during La Niña. However, the anomalous model response in temperature, chlorophyll, and zooplankton is generally much weaker than observed and includes a 1-2 month delay compared to observations. We also highlight the asymmetry in the model CCS response, where composite model La Niña events are stronger and more significant than model El Niño events, which is a feature previously identified in observations of CCS SST as well as in tropical Pacific Niño-4 SST where atmospheric teleconnections associated with ENSO are forced. These physical-biological composites provide a view of some of the limitations to the potentially predictable impacts of ENSO teleconnections on the CCS within the modeling framework of CESM-POP2-BEC.
Greer, Adam T., L M Chiaverano, and Jessica Y Luo, et al., March 2018: Ecology and behaviour of holoplanktonic scyphomedusae and their interactions with larval and juvenile fishes in the northern Gulf of Mexico. ICES Journal of Marine Science, 75(2), DOI:10.1093/icesjms/fsx168. Abstract
Pelagia noctiluca is a venomous, globally distributed holoplanktonic scyphomedusa that periodically forms aggregations in coastal environments, yet little is known about its ecology and behaviour in the northern Gulf of Mexico (nGOM). Using a high resolution plankton imaging system, we describe the patch characteristics of Pelagia medusae in relation to fine-scale biological and physical variables during two summers at shallow (∼25 m, 2016) and deeper (∼45 m, 2011) sampling areas on the nGOM shelf. At the deeper site during the day, average Pelagia medusae concentrations just underneath a surface plume of fresher water (10–25 m) ranged from 0.18 to 0.91 ind. m−3, with a Lloyd’s patchiness index of 13.87, indicating strong aggregation tendencies (peak fine-scale concentration reached 27 ind. m−3). These patches were often associated with horizontal gradients in salinity, and concentrations of several zooplankton taxa (e.g. chaetognaths, hydromedusae, siphonophores, and ctenophores) were significantly negatively correlated with Pelagia medusae abundance (p < 0.0001, Spearman correlations). Although larval fish abundance was not correlated with Pelagia medusae on the 1 m3 scale (19.25 m horizontal distance), larval and juvenile fishes between 0.6 and 2.0 cm aggregated underneath the bell of some Pelagia medusae during the daytime only, even within hypoxic waters. Vertical distributions collected on a diel cycle demonstrated that Pelagia medusae perform a reverse diel vertical migration constrained by low salinity near the surface. These data suggest that salinity changes drive the distribution of Pelagia medusae vertically and horizontally, and when sufficient concentrations are present, medusae are capable of exerting a top-down effect on the abundances of their zooplankton prey. For zooplankton with high visual acuity, such as larval and juvenile fishes, the relationship with Pelagia medusae may change on a diel cycle and depend on the sensory ability of potential prey.
Luo, Jessica Y., et al., December 2018: Automated plankton image analysis using convolutional neural networks. Limnology and Oceanography: Methods, 16(12), DOI:10.1002/lom3.10285. Abstract
The rise of in situ plankton imaging systems, particularly high‐volume imagers such as the In Situ Ichthyoplankton Imaging System, has increased the need for fast processing and accurate classification tools that can identify a high diversity of organisms and nonliving particles of biological origin. Previous methods for automated classification have yielded moderate results that either can resolve few groups at high accuracy or many groups at relatively low accuracy. However, with the advent of new deep learning tools such as convolutional neural networks (CNNs), the automated identification of plankton images can be vastly improved. Here, we describe an image processing procedure that includes preprocessing, segmentation, classification, and postprocessing for the accurate identification of 108 classes of plankton using spatially sparse CNNs. Following a filtering process to remove images with low classification scores, a fully random evaluation of the classification showed that average precision was 84% and recall was 40% for all groups. Reliably classifying rare biological classes was difficult, so after excluding the 12 rarest taxa, classification accuracy for the remaining biological groups became > 90%. This method provides proof of concept for the effectiveness of an automated classification scheme using deep‐learning methods, which can be applied to a range of plankton or biological imaging systems, with the eventual application in a variety of ecological monitoring and fisheries management contexts.
Durden, J, and Jessica Y Luo, et al., November 2017: Integrating “Big Data” into Aquatic Ecology: Challenges and Opportunities. Limnology and Oceanography Bulletin, 26(4), DOI:10.1002/lob.10213. Abstract
Got “Big Data”? Not sure how best to use it? Big Data is becoming an important facet of aquatic ecology, and researchers must learn to harness it to reap the rewards of using it. The benefits of using Big Data are many, and include advancements in scientific understanding at larger scales and higher resolution, applications to improving environmental management and policy, and public engagement. We aim to demystify the use of Big Data for individual scientists, and provide some food for thought for the aquatic ecology community on how to develop this sphere. To achieve this, we highlight six key challenges: (1) how to recognize if you have Big Data, (2) handling Big Data, (3) issues with classical analytical techniques, (4) verification of Big Data, (5) considerations for data sharing, and (6) community development of knowledge infrastructures. We then present approaches and tools which have been successfully applied to these challenges in aquatic ecology and other scientific fields.
Kelly, P T., Tom Bell, A J Reisinger, T L Spanbauer, L E Bortolotti, J A Brentrup, Christian Briseño-Avena, Xiaoli Dong, A M Flanagan, Elizabeth M Follett, J Grosse, T Guy-Haim, M A Holgerson, R A Hovel, and Jessica Y Luo, et al., May 2017: Ecological Dissertations in the Aquatic Sciences: An Effective Networking and Professional Development Opportunity for Early Career Aquatic Scientists. Limnology and Oceanography Bulletin, 26(2), DOI:10.1002/lob.10180.
Robinson, Kelly L., and Jessica Y Luo, et al., April 2017: A Tale of Two Crowds: Public Engagement in Plankton Classification. Frontiers in Marine Science, 4, 82, DOI:10.3389/fmars.2017.00082. Abstract
“Big data” are becoming common in biological oceanography with the advent of sampling technologies that can generate multiple, high-frequency data streams. Given the need for “big” data in ocean health assessments and ecosystem management, identifying and implementing robust, and efficient processing approaches is a challenge for marine scientists. Using a large plankton imagery data set, we present two crowd-sourcing approaches applied to the problem of classifying millions of organisms. The first used traditional crowd-sourcing by asking the public to identify plankton through a web-interface. The second challenged the data science community to develop algorithms via an industry partnership. We found traditional crowd-sourcing was an excellent way to engage and educate the public while crowd-sourcing data scientists rapidly generated multiple, effective solutions. As the need to process and visualize large and complex marine data sets is expected to grow over time, effective collaborations between oceanographers and computer and data scientists will become increasingly important.
Faillettaz, R, M Picheral, and Jessica Y Luo, et al., April 2016: Imperfect automatic image classification successfully describes plankton distribution patterns. Methods in Oceanography, 15-16, DOI:10.1016/j.mio.2016.04.003. Abstract
Imaging systems were developed to explore the fine scale distributions of plankton (<10 m), but they generate huge datasets that are still a challenge to handle rapidly and accurately. So far, imaged organisms have been either classified manually or pre-classified by a computer program and later verified by human operators. In this paper, we post-process a computer-generated classification, obtained with the common ZooProcess and PlanktonIdentifier toolchain developed for the ZooScan, and test whether the same ecological conclusions can be reached with this fully automatic dataset and with a reference, manually sorted, dataset. The Random Forest classifier outputs the probabilities that each object belongs in each class and we discard the objects with uncertain predictions, i.e. under a probability threshold defined based on a 1% error rate in a self-prediction of the learning set. Keeping only well-predicted objects enabled considerable improvements in average precision, 84% for biological groups, at the cost of diminishing recall (by 39% on average). Overall, it increased accuracy by 16%. For most groups, the automatically-predicted distributions were comparable to the reference distributions and resulted in the same size-spectra. Automatically-predicted distributions also resolved ecologically-relevant patterns, such as differences in abundance across a mesoscale front or fine-scale vertical shifts between day and night. This post-processing method is tested on the classification of plankton images through Random Forest here, but is based on basic features shared by all machine learning methods and could thus be used in a broad range of applications.
Luo, Jessica Y., et al., September 2014: Environmental drivers of the fine-scale distribution of a gelatinous zooplankton community across a mesoscale front. Marine Ecology Progress Series, 510, DOI:10.3354/meps10908. Abstract
Mesoscale fronts occur frequently in many coastal areas and often are sites of elevated productivity; however, knowledge of the fine-scale distribution of zooplankton at these fronts is lacking, particularly within the mid-trophic levels. Furthermore, small (<13 cm) gelatinous zooplankton are ubiquitous, but are under-studied, and their abundances underestimated due to inadequate sampling technology. Using the In Situ Ichthyoplankton Imaging System (ISIIS), we describe the fine-scale distribution of small gelatinous zooplankton at a sharp salinity-driven front in the Southern California Bight. Between 15 and 17 October 2010, over 129000 hydromedusae, ctenophores, and siphonophores within 44 taxa, and nearly 650000 pelagic tunicates were imaged in 5450 m3 of water. Organisms were separated into 4 major assemblages which were largely associated with depth-related factors. Species distribution modeling using boosted regression trees revealed that hydromedusae and tunicates were primarily associated with temperature and depth, siphonophores with dissolved oxygen (DO) and chlorophyll a fluorescence, and ctenophores with DO. The front was the least influential out of all environmental variables modeled. Additionally, except for 6 taxa, all other taxa were not aggregated at the front. Results provide new insights into the biophysical drivers of gelatinous zooplankton distributions and the varying influence of mesoscale fronts in structuring zooplankton communities.
McClatchie, S, Robert Cowen, K Nieto, Adam T Greer, and Jessica Y Luo, et al., April 2012: Resolution of fine biological structure including small narcomedusae across a front in the Southern California Bight. Journal of Geophysical Research: Oceans, 117(C4), DOI:10.1029/2011JC007565. Abstract
We sampled a front detected by SST gradient, ocean color imagery, and a Spray glider south of San Nicolas Island in the Southern California Bight between 14 and 18 October 2010. We sampled the front with an unusually extensive array of instrumentation, including the Continuous Underway Fish Egg Sampler (CUFES), the undulating In Situ Ichthyoplankton Imaging System (ISIIS) (fitted with temperature, salinity, oxygen, and fluorescence sensors), multifrequency acoustics, a surface pelagic trawl, a bongo net, and a neuston net. We found higher fluorescence and greater cladoceran, decapod, and euphausiid densities in the front, indicating increased primary and secondary production. Mesopelagic fish were most abundant in oceanic waters to the west of the front, market squid were abundant in the front associated with higher krill and decapod densities, and jack mackerel were most common in the front and on the shoreward side of the front. Egg densities peaked to either side of the front, consistent with both offshore (for oceanic squid and mesopelagic fish) and shelf origins (for white croaker and California halibut). We discovered unusually high concentrations of predatory narcomedusae in the surface layer of the frontal zone. Potential ichthyoplankton predators were more abundant either in the front (decapods, euphausiids, and squid) or shoreward of the front (medusae, chaetognaths, and jack mackerel). For pelagic fish like sardine, which can thrive in less productive waters, the safest place to spawn would be offshore because there are fewer potential predators.