Understanding the ocean carbon and sulfur cycles in the context of a variable ocean : a study of anthropogenic carbon storage and dimethylsulfide production in the Atlantic Ocean

Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at the Massachusetts Institute of Technology and the Woods Hole Oceanographic Institution February 2010Anthropogenic activity is rapidly changing the global climate through the emission of carbon dioxide. Ocean carbon and sulfur cycles have the potential to impact global climate directly and through feedback loops. Numerical modeling, field and laboratory studies are used to improve our mechanistic understanding of the impact of natural variability on carbon and sulfur cycling. Variability in ocean physics, specifically changes in vertical mixing, is shown to significantly impact both cycles. The impact of interannual variability on the detection and attribution of anthropogenic carbon (Canthro) and the storage of Canthro in the Atlantic Ocean is analyzed using a three-dimensional global ocean model. Several regions are identified where empirical methods used to estimating Canthro are not able to correct for natural variability in the ocean carbon system. This variability is also shown to bias estimates of long term trends made from hydrographic observations. In addition, the storage of Canthro in North Atlantic mode waters is shown to be strongly influenced by water mass transformation during wintertime mixing events. The primary mechanisms responsible for seasonal variability in dimethylsulfoniopropionate (DMSP) degradation and dimethylsulfide (DMS) production in the oligotrophic North Atlantic are investigated using potential enzyme activity and gene expression and abundance data. Vertical mixing and UV radiative stress appear to be the dominant mechanisms behind seasonal variability in DMS production in the Sargasso Sea. This thesis demonstrates the importance of and dynamics of bacterial communities responsible for DMSP degradation and DMS production in oligotrophic surface waters. These findings suggest that modifications to current numerical models of the upper ocean sulfur cycle may be needed. Specifically, current static parameterizations of bacterial DMSP cycling should be replaced with a dynamic bacterial component including DMSP degradation and DMS production.My graduate research was supported by a Linden Earth Systems Graduate Fellowship (MIT), a Department of Defense NDSEG fellowship, an EPA STAR fellowship, the Scurlock Fund, and the Ocean Venture Fund. Additional funding for this work was provided by the National Science Foundation (OCE02-23869, OCE-0623034, OCE-072417, OCE-0525928, OCE-0425166), the Gordon and Betty Moore Foundation, and the Center for Microbial Oceanography Research and Education (CMORE) an NSF Science and Technology Center (EF-0424599)

Model output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014

Dataset: Modeled phytoplankton dynamicsModel output of phytoplankton community composition variability as a function of intensity and duration of environmental disturbance at the Hawaii Ocean Time-series (HOT) location and nearby regions between 2003 and 2014. Model output was generated from numerical model simulations. For a complete list of measurements, refer to the full dataset description in the supplemental file 'Dataset_description.pdf'. The most current version of this dataset is available at: https://www.bco-dmo.org/dataset/854787NSF Division of Ocean Sciences (NSF OCE) OCE-1538525, NSF Ocean Sciences Research Initiation Grants (NSF OCE-RIG) OCE-RIG-132331

US National BioGeoSCAPES Workshop Report

Virtual Meeting held November 10-12, 2021BioGeoSCAPES (BGS) is an international program being developed to understand controls on ocean productivity and metabolism by integrating systems biology (‘omics) and biogeochemistry (Figure 1). To ensure global input into the design of the BGS Program, countries interested in participating were tasked with holding an organizing meeting to discuss the country-specific research priorities. A United States BGS planning meeting, sponsored by the Ocean Carbon & Biogeochemistry (OCB) Project Office, was convened virtually November 10-12, 2021. The objectives of the meeting were to communicate the planning underway by international partners, engage the US community to explore possible national contributions to such a program, and build understanding, support, and momentum for US efforts towards BGS. The meeting was well-attended, with 154 participants and many fruitful discussions that are summarized in this document. Key outcomes from the meeting were the identification of additional programs and partners for BGS, a prioritization of measurements requiring intercalibration, and the development of a consensus around key considerations to be addressed in a science plan. Looking forward, the hope is that this workshop will serve as the foundation for future US and international discussions and planning for a BGS program, enabled by NSF funding for an AccelNet project (AccelNet - Implementation: Development of an International Network for the Study of Ocean Metabolism and Nutrient Cycles on a Changing Planet (BioGeoSCAPES)), beginning in 2022.This workshop was held thanks to funding to US OCB by the National Science Foundation (NSF) (OCE-1850983) and National Aeronautic and Space Administration (NASA) (NNX17AB17G). The organizers give thanks to all workshop participants for their thoughtful discussions and input during the workshop

A high-throughput assay for quantifying phenotypic traits of microalgae

High-throughput methods for phenotyping microalgae are in demand across a variety of research and commercial purposes. Many microalgae can be readily cultivated in multi-well plates for experimental studies which can reduce overall costs, while measuring traits from low volume samples can reduce handling. Here we develop a high-throughput quantitative phenotypic assay (QPA) that can be used to phenotype microalgae grown in multi-well plates. The QPA integrates 10 low-volume, relatively high-throughput trait measurements (growth rate, cell size, granularity, chlorophyll a, neutral lipid content, silicification, reactive oxygen species accumulation, and photophysiology parameters: ETRmax, Ik, and alpha) into one workflow. We demonstrate the utility of the QPA on Thalassiosira spp., a cosmopolitan marine diatom, phenotyping six strains in a standard nutrient rich environment (f/2 media) using the full 10-trait assay. The multivariate phenotypes of strains can be simplified into two dimensions using principal component analysis, generating a trait-scape. We determine that traits show a consistent pattern when grown in small volume compared to more typical large volumes. The QPA can thus be used for quantifying traits across different growth environments without requiring exhaustive large-scale culturing experiments, which facilitates experiments on trait plasticity. We confirm that this assay can be used to phenotype newly isolated diatom strains within 4 weeks of isolation. The QPA described here is highly amenable to customisation for other traits or unicellular taxa and provides a framework for designing high-throughput experiments. This method will have applications in experimental evolution, modelling, and for commercial applications where screening of phytoplankton traits is of high importance

A unified theory for organic matter accumulation

Organic matter constitutes a key reservoir in global elemental cycles. However, our understanding of the dynamics of organic matter and its accumulation remains incomplete. Seemingly disparate hypotheses have been proposed to explain organic matter accumulation: the slow degradation of intrinsically recalcitrant substrates, the depletion to concentrations that inhibit microbial consumption, and a dependency on the consumption capabilities of nearby microbial populations. Here, using a mechanistic model, we develop a theoretical framework that explains how organic matter predictably accumulates in natural environments due to biochemical, ecological, and environmental factors. Our framework subsumes the previous hypotheses. Changes in the microbial community or the environment can move a class of organic matter from a state of functional recalcitrance to a state of depletion by microbial consumers. The model explains the vertical profile of dissolved organic carbon in the ocean and connects microbial activity at subannual timescales to organic matter turnover at millennial timescales. The threshold behavior of the model implies that organic matter accumulation may respond nonlinearly to changes in temperature and other factors, providing hypotheses for the observed correlations between organic carbon reservoirs and temperature in past earth climates

Revising upper-ocean sulfur dynamics near Bermuda : new lessons from 3 years of concentration and rate measurements

© The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Environmental Chemistry 13 (2016): 302-313, doi:10.1071/EN15045.Oceanic biogeochemical cycling of dimethylsulfide (DMS), and its precursor dimethylsulfoniopropionate (DMSP), has gained considerable attention over the past three decades because of the potential role of DMS in climate mediation. Here we report 3 years of monthly vertical profiles of organic sulfur cycle concentrations (DMS, particulate DMSP (DMSPp) and dissolved DMSP (DMSPd)) and rates (DMSPd consumption, biological DMS consumption and DMS photolysis) from the Bermuda Atlantic Time-series Study (BATS) site taken between 2005 and 2008. Concentrations confirm the summer paradox with mixed layer DMS peaking ~90 days after peak DMSPp and ~50 days after peak DMSPp : Chl. A small decline in mixed layer DMS was observed relative to those measured during a previous study at BATS (1992–1994), potentially driven by long-term climate shifts at the site. On average, DMS cycling occurred on longer timescales than DMSPd (0.43 ± 0.35 v. 1.39 ± 0.76 day–1) with DMSPd consumption rates remaining elevated throughout the year despite significant seasonal variability in the bacterial DMSP degrader community. DMSPp was estimated to account for 4–5 % of mixed layer primary production and turned over at a significantly slower rate (~0.2 day–1). Photolysis drove DMS loss in the mixed layer during the summer, whereas biological consumption of DMS was the dominant loss process in the winter and at depth. These findings offer new insight into the underlying mechanisms driving DMS(P) cycling in the oligotrophic ocean, provide an extended dataset for future model evaluation and hypothesis testing and highlight the need for a reexamination of past modelling results and conclusions drawn from data collected with old methodologies.The authors acknowledge funding from the National Science Foundation (NSF) (OCE-0425166) and the Center for Microbial Oceanography Research and Education (CMORE) a NSF Science and Technology Center (EF-0424599)

Neural mechanisms of self-affirmation's stress buffering effects

Self-affirmation can buffer stress responses across different contexts, yet the neural mechanisms for these effects are unknown. Self-affirmation has been shown to increase activity in reward-related neural regions, including the ventral striatum and ventromedial prefrontal cortex (VMPFC). Given that reward-related prefrontal cortical regions such as the VMPFC are involved in reducing neurobiological and behavioral responses to stress, we hypothesized that self-affirmation would activate VMPFC and also reduce neural responses to stress in key neural threat system regions such as the dorsal anterior cingulate cortex (dACC) and anterior insula (AI). We explored this hypothesis using self-affirmation and evaluative stress tasks following a within-subjects design in the fMRI scanner. Consistent with prior work, self-affirmation blocks led to lower self-reported stress and improved performance. With respect to neural activity, compared to control blocks, self-affirmation blocks led to greater VMPFC activity, and subsequently less left AI (but not dACC) activity during stress task blocks. Functional connectivity analyses revealed greater connectivity between the VMPFC and left and right AI during self-affirmation compared to control. These findings begin to articulate the neural circuits involved in self-affirmation's effects during exposure to stressors, and more broadly specify neural reward-based responses to stressful situations

Environmental, biochemical and genetic drivers of DMSP degradation and DMS production in the Sargasso Sea

Author Posting. © The Author(s), 2011. This is the author's version of the work. It is posted here by permission of John Wiley & Sons for personal use, not for redistribution. The definitive version was published in Environmental Microbiology 14 (2012): 1210-1223, doi:10.1111/j.1462-2920.2012.02700.x.Dimethylsulfide (DMS) is a climatically relevant trace gas produced and cycled by the surface ocean food web. Mechanisms driving intraannual variability in DMS production and dimethylsulfoniopropionate (DMSP) degradation in open-ocean, oligotrophic regions were investigated during a 10 month time-series at the Bermuda Atlantic Time-series Study site in the Sargasso Sea. Abundance and transcription of bacterial DMSP degradation genes, DMSP lyase enzyme activity, and DMS and DMSP concentrations, consumption rates, and production rates were quantified over time and depth. This interdisciplinary dataset was used to test current hypotheses of the role of light and carbon supply in regulating upper-ocean sulfur cycling. Findings supported UV-A dependent phytoplankton DMS production. Bacterial DMSP degraders may also contribute significantly to DMS production when temperatures are elevated and UV-A dose is moderate, but may favor DMSP demethylation under low UV-A doses. Three groups of bacterial DMSP degraders with distinct intraannual variability were identified and niche differentiation was indicated. The combination of genetic and biochemical data suggest a modified ‘bacterial switch’ hypothesis where the prevalence of different bacterial DMSP degradation pathways is regulated by a complex set of factors including carbon supply, temperature, and UV-A dose.This research was funded by National Science Foundation (NSF) grants OCE- 0525928, OCE-072417, and OCE-042516. Additional funding was provided by the NSF Center for Microbial Oceanography Research and Education (CMORE), the Gordon and Betty Moore Foundation, the Scurlock Fund, the Ocean Ventures Fund, a National Defense Science and Engineering Graduate Fellowship, and an Environmental Protection Agency STAR Graduate Fellowship

The evolution of trait correlations constrains phenotypic adaptation to high CO 2 in a eukaryotic alga

Microbes form the base of food webs and drive biogeochemical cycling. Predicting the effects of microbial evolution on global elemental cycles remains a significant challenge due to the sheer number of interacting environmental and trait combinations. Here, we present an approach for integrating multivariate trait data into a predictive model of trait evolution. We investigated the outcome of thousands of possible adaptive walks parameterized using empirical evolution data from the alga Chlamydomonas exposed to high CO(2). We found that the direction of historical bias (existing trait correlations) influenced both the rate of adaptation and the evolved phenotypes (trait combinations). Critically, we use fitness landscapes derived directly from empirical trait values to capture known evolutionary phenomena. This work demonstrates that ecological models need to represent both changes in traits and changes in the correlation between traits in order to accurately capture phytoplankton evolution and predict future shifts in elemental cycling