Britten Gregory L.

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Britten
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Gregory L.
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  • Article
    Seasonal succession and spatial patterns of Synechococcus microdiversity in a salt marsh estuary revealed through 16S rRNA gene oligotyping
    (Frontiers Media, 2017-08-09) Mackey, Katherine R. M. ; Hunter-Cevera, Kristen R. ; Britten, Gregory L. ; Murphy, Leslie G. ; Sogin, Mitchell L. ; Huber, Julie A.
    Synechococcus are ubiquitous and cosmopolitan cyanobacteria that play important roles in global productivity and biogeochemical cycles. This study investigated the fine scale microdiversity, seasonal patterns, and spatial distributions of Synechococcus in estuarine waters of Little Sippewissett salt marsh (LSM) on Cape Cod, MA. The proportion of Synechococcus reads was higher in the summer than winter, and higher in coastal waters than within the estuary. Variations in the V4–V6 region of the bacterial 16S rRNA gene revealed 12 unique Synechococcus oligotypes. Two distinct communities emerged in early and late summer, each comprising a different set of statistically co-occurring Synechococcus oligotypes from different clades. The early summer community included clades I and IV, which correlated with lower temperature and higher dissolved oxygen levels. The late summer community included clades CB5, I, IV, and VI, which correlated with higher temperatures and higher salinity levels. Four rare oligotypes occurred in the late summer community, and their relative abundances more strongly correlated with high salinity than did other co-occurring oligotypes. The analysis revealed that multiple, closely related oligotypes comprised certain abundant clades (e.g., clade 1 in the early summer and clade CB5 in the late summer), but the correlations between these oligotypes varied from pair to pair, suggesting they had slightly different niches despite being closely related at the clade level. Lack of tidal water exchange between sampling stations gave rise to a unique oligotype not abundant at other locations in the estuary, suggesting physical isolation plays a role in generating additional microdiversity within the community. Together, these results contribute to our understanding of the environmental and ecological factors that influence patterns of Synechococcus microbial community composition over space and time in salt marsh estuarine waters.
  • Article
    Assessing the potential of backscattering as a proxy for phytoplankton carbon biomass
    (American Geophysical Union, 2023-04-28) Serra‐Pompei, Camila ; Hickman, Anna ; Britten, Gregory L. ; Dutkiewicz, Stephanie
    Despite phytoplankton contributing roughly half of the photosynthesis on earth and fueling marine food‐webs, field measurements of phytoplankton biomass remain scarce. The particulate backscattering coefficient (bbp) has often been used as an optical proxy to estimate phytoplankton carbon biomass (Cphyto). However, total observed bbp is impacted by phytoplankton size, cell composition, and non‐algal particles. The lack of phytoplankton field data has prevented the quantification of uncertainties driven by these factors. Here, we first review and discuss existing bbp algorithms by applying them to bbp data from the BGC‐Argo array in surface waters (<10 m). We find a bbp threshold where estimated Cphyto differs by more than an order of magnitude. Next, we use a global ocean circulation model (the MITgcm Biogeochemical and Optical model) that simulates plankton dynamics and associated inherent optical properties to quantify and understand uncertainties from bbp‐based algorithms in surface waters. We do so by developing and calibrating an algorithm to the model. Simulated error‐estimations show that bbp‐based algorithms overestimate/underestimate Cphyto between 5% and 100% in surface waters, depending on the location and time. This is achieved in the ideal scenario where Cphyto and bbp are known precisely. This is not the case for algorithms derived from observations, where the largest source of uncertainty is the scarcity of phytoplankton biomass data and related methodological inconsistencies. If these other uncertainties are reduced, the model shows that bbp could be a relatively good proxy for phytoplankton carbon biomass, with errors close to 20% in most regions.Key PointsPhytoplankton carbon bbp‐based algorithms can differ up to an order of magnitude at low bbp valuesAn algorithm fitted to a global model output shows biases ranging between 15% and 40% in most regionsMost uncertainties are due to the relative contribution of phytoplankton to total bbp
  • Article
    Challenges and opportunities in connecting gene count observations with ocean biogeochemical models: Reply to Zehr and Riemann (2023)
    (Association for the Sciences of Limnology and Oceanography, 2023-05-08) Meiler, Simona ; Britten, Gregory L. ; Dutkiewicz, Stephanie ; Moisander, Pia H. ; Follows, Michael J.
    As authors of Meiler et al. (2022), we welcome Zehr and Riemann's (2023) comment and discussion. We agree, of course, with the general statement that “quantification of gene copy numbers is valuable in marine microbial ecology” and wish to clarify that one of the purposes of Meiler et al. (2022) was to address the specific challenge of using a compilation of quantitative polymerase chain reaction (qPCR) nifH data to evaluate the skill of biogeochemical models. In that particular case, the data were most helpful in constraining the range of diazotrophs, but several sources of uncertainty limited more detailed quantitative evaluations. This was not intended to imply a lack of value or promise for such applications of qPCR data: we believe that testing and constraining biogeochemical and ecological models will be an important application of qPCR data, yet the quantitative interface between molecular data and biogeochemical models remains at its infancy. In the following, we first provide a background perspective for the Meiler et al. (2022) study, pointing out why observations and simulations are rooted in different currencies. We then discuss in more detail some of the specific points raised by Zehr and Riemann (2023) and highlight why further efforts toward intercalibration of currencies used to measure and simulate marine microbial populations is particularly significant if we are to fully exploit the data in biogeochemical and climate modeling applications. We end by summarizing some potentially fruitful avenues for future effort stimulated by this dialog.
  • Article
    Historical and future maximum sea surface temperatures
    (American Association for the Advancement of Science, 2024-01-26) Cael, B. Barry ; Burger, Friedrich A. ; Henson, Stephanie A. ; Britten, Gregory L. ; Frolicher, Thomas L.
    Marine heat waves affect ocean ecosystems and are expected to become more frequent and intense. Earth system models’ ability to reproduce extreme ocean temperature statistics has not been tested quantitatively, making the reliability of their future projections of marine heat waves uncertain. We demonstrate that annual maxima of detrended anomalies in daily mean sea surface temperatures (SSTs) over 39 years of global satellite observations are described excellently by the generalized extreme value distribution. If models can reproduce the observed distribution of SST extremes, this increases confidence in their marine heat wave projections. 14 CMIP6 models' historical realizations reproduce the satellite-based distribution and its parameters’ spatial patterns. We find that maximum ocean temperatures will become warmer (by 1.07° ± 0.17°C under 2°C warming and 2.04° ± 0.18°C under 3.2°C warming). These changes are mainly due to mean SST increases, slightly reinforced by SST seasonality increases. Our study quantifies ocean temperature extremes and gives confidence to model projections of marine heat waves.
  • Article
    Learning from positive deviants in fisheries
    (Wiley, 2024-02-05) Schiller, Laurenne ; Britten, Gregory L. ; Auld, Graeme ; Worm, Boris
    Despite progress in the management of assessed fish populations, many countries lag behind international commitments to restore overexploited stocks to healthy abundances. Here we use a mixed-methods positive deviance approach, also known as ‘bright spot’ analysis, to understand what drives the successful governance of exploited species by learning from positive outliers, or ‘deviants’. We use Canada as a case study, identifying factors driving the abundance of 230 commercially exploited fish and invertebrate populations, of which only 28% were classified at healthy abundance in 2022. We first applied a generalized linear model to test how diverse socio-ecological fishery attributes relate to stock health. We found healthier stocks are positively and significantly correlated with certain management regions, more selective gears, eco-certification, and high fishery value. Counterintuitively, healthier stocks were also associated with high inherent fishing vulnerability and the absence of reference points. We then used fishery expert surveys and interviews to investigate the social and institutional characteristics of stocks healthier than expected, given their circumstances. We found that fisheries targeting these positive outliers have lower conflict among users, balanced stakeholder involvement in data collection and decision-making, and improved accounting of mortality sources. Lessons from these positive deviants can be applied to improve underperforming management systems that are struggling to reverse overexploitation in Canada and elsewhere. More generally, we suggest that a positive deviance approach, already used in public health, could be a promising tool to learn about successful fisheries management interventions, and the diverse actors responsible for ensuring these interventions are successful.