1
|
Anderson SI, Fronda C, Barton AD, Clayton S, Rynearson TA, Dutkiewicz S. Phytoplankton thermal trait parameterization alters community structure and biogeochemical processes in a modeled ocean. GLOBAL CHANGE BIOLOGY 2024; 30:e17093. [PMID: 38273480 DOI: 10.1111/gcb.17093] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/12/2023] [Revised: 10/19/2023] [Accepted: 11/20/2023] [Indexed: 01/27/2024]
Abstract
Phytoplankton exhibit diverse physiological responses to temperature which influence their fitness in the environment and consequently alter their community structure. Here, we explored the sensitivity of phytoplankton community structure to thermal response parameterization in a modelled marine phytoplankton community. Using published empirical data, we evaluated the maximum thermal growth rates (μmax ) and temperature coefficients (Q10 ; the rate at which growth scales with temperature) of six key Phytoplankton Functional Types (PFTs): coccolithophores, cyanobacteria, diatoms, diazotrophs, dinoflagellates, and green algae. Following three well-documented methods, PFTs were either assumed to have (1) the same μmax and the same Q10 (as in to Eppley, 1972), (2) a unique μmax but the same Q10 (similar to Kremer et al., 2017), or (3) a unique μmax and a unique Q10 (following Anderson et al., 2021). These trait values were then implemented within the Massachusetts Institute of Technology biogeochemistry and ecosystem model (called Darwin) for each PFT under a control and climate change scenario. Our results suggest that applying a μmax and Q10 universally across PFTs (as in Eppley, 1972) leads to unrealistic phytoplankton communities, which lack diatoms globally. Additionally, we find that accounting for differences in the Q10 between PFTs can significantly impact each PFT's competitive ability, especially at high latitudes, leading to altered modeled phytoplankton community structures in our control and climate change simulations. This then impacts estimates of biogeochemical processes, with, for example, estimates of export production varying by ~10% in the Southern Ocean depending on the parameterization. Our results indicate that the diversity of thermal response traits in phytoplankton not only shape community composition in the historical and future, warmer ocean, but that these traits have significant feedbacks on global biogeochemical cycles.
Collapse
Affiliation(s)
- Stephanie I Anderson
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Clara Fronda
- Laboratoire de Physique, Ecole Normale Supérieure, Paris, France
| | - Andrew D Barton
- Scripps Institution of Oceanography and Department of Ecology, Behavior and Evolution, San Diego, California, USA
| | - Sophie Clayton
- Department of Ocean and Earth Sciences, Old Dominion University, Norfolk, Virginia, USA
| | - Tatiana A Rynearson
- Graduate School of Oceanography, University of Rhode Island, Narragansett, Rhode Island, USA
| | - Stephanie Dutkiewicz
- Department of Earth, Atmospheric and Planetary Sciences, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| |
Collapse
|
2
|
Chase AP, Boss ES, Haëntjens N, Culhane E, Roesler C, Karp‐Boss L. Plankton Imagery Data Inform Satellite-Based Estimates of Diatom Carbon. GEOPHYSICAL RESEARCH LETTERS 2022; 49:e2022GL098076. [PMID: 36245955 PMCID: PMC9541314 DOI: 10.1029/2022gl098076] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/31/2022] [Revised: 06/01/2022] [Accepted: 06/03/2022] [Indexed: 06/16/2023]
Abstract
Estimating the biomass of phytoplankton communities via remote sensing is a key requirement for understanding global ocean ecosystems. Of particular interest is the carbon associated with diatoms given their unequivocal ecological and biogeochemical roles. Satellite-based algorithms often rely on accessory pigment proxies to define diatom biomass, despite a lack of validation against independent diatom biomass measurements. We used imaging-in-flow cytometry to quantify diatom carbon in the western North Atlantic, and compared results to those obtained from accessory pigment-based approximations. Based on this analysis, we offer a new empirical formula to estimate diatom carbon concentrations from chlorophyll a. Additionally, we developed a neural network model in which we integrated chlorophyll a and environmental information to estimate diatom carbon distributions in the western North Atlantic. The potential for improving satellite-based diatom carbon estimates by integrating environmental information into a model, compared to models that are based solely on chlorophyll a, is discussed.
Collapse
Affiliation(s)
- A. P. Chase
- Applied Physics LaboratoryUniversity of WashingtonSeattleWAUSA
| | - E. S. Boss
- School of Marine SciencesUniversity of MaineOronoMEUSA
| | - N. Haëntjens
- School of Marine SciencesUniversity of MaineOronoMEUSA
| | - E. Culhane
- Woods Hole Oceanographic InstitutionWoods HoleMAUSA
| | - C. Roesler
- Department of Earth and Oceanographic ScienceBowdoin CollegeBrunswickMEUSA
| | - L. Karp‐Boss
- School of Marine SciencesUniversity of MaineOronoMEUSA
| |
Collapse
|
3
|
Mishra RK, Jena B, Venkataramana V, Sreerag A, Soares MA, AnilKumar N. Decadal changes in global phytoplankton compositions influenced by biogeochemical variables. ENVIRONMENTAL RESEARCH 2022; 206:112546. [PMID: 34902377 DOI: 10.1016/j.envres.2021.112546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/06/2021] [Revised: 11/28/2021] [Accepted: 12/06/2021] [Indexed: 06/14/2023]
Abstract
The global environmental changes owing to natural and anthropogenic influences are challenging the structure and functioning of the ocean ecosystem. The complex processes interacting within the physical, chemical, and biological environment at different spatio-temporal scales and their impact on the ocean ecosystem processes are yet to be investigated. A long term trend on phytoplankton biomass in terms of Chlorophyll-a concentration (Chl-a), phytoplankton compositions and the processes that control the variability is required for understanding the ocean ecosystem. This study investigated decadal trends (2002-2015) of phytoplankton composition and biogeochemical parameters over the Global Ocean (GO), Southern Ocean (SO), and the Arctic Ocean (AO) using ocean color remote sensing and assimilated data from the National Aeronautics and Space Administration (NASA) Ocean biogeochemical model. The results revealed the dominance of larger cell phytoplankton mainly diatoms throughout the SO and AO; however, the coccolithophores dominate in the remaining part of the GO. Analysis of nutrients showed that nitrate is not a limiting factor for the variability of phytoplankton biomass in the SO and AO. The low nitrate concentration influenced in the rest of the GO. The photosynthetically available radiation (PAR) limiting the phytoplankton biomass and composition in the SO and AO. Although the SO is known as the high nutrient low chlorophyll (HNLC) region of the GO, the low iron concentration along with the PAR co-limits the growth of phytoplankton biomass. Trend analysis showed that an increase in Chl-a and diatoms in the SO and AO. In contrast, it declined significantly in the other regions of the GO, in response to the consistent increase in sea surface temperature. The results indicated that, shifting of phytoplankton community from regional to global scale have a greater implication for climate change and marine ecosystem.
Collapse
Affiliation(s)
- R K Mishra
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India.
| | - B Jena
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India
| | - V Venkataramana
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India
| | - A Sreerag
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India
| | - Melena A Soares
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India
| | - N AnilKumar
- National Centre for Polar and Ocean Research, Ministry of Earth Science, Government of India, Vasco-da-Gama, India
| |
Collapse
|
4
|
Bisson KM, Boss E, Werdell PJ, Ibrahim A, Frouin R, Behrenfeld MJ. Seasonal bias in global ocean color observations. APPLIED OPTICS 2021; 60:6978-6988. [PMID: 34613181 PMCID: PMC8500483 DOI: 10.1364/ao.426137] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/01/2021] [Accepted: 07/01/2021] [Indexed: 06/13/2023]
Abstract
In this study, we identify a seasonal bias in the ocean color satellite-derived remote sensing reflectances (Rrs(λ);sr-1) at the ocean color validation site, Marine Optical BuoY. The seasonal bias in Rrs(λ) is present to varying degrees in all ocean color satellites examined, including the Visible Infrared Imaging Radiometer Suite, Sea-Viewing Wide Field-of-View Sensor, and Moderate Resolution Imaging Spectrometer. The relative bias in Rrs has spectral dependence. Products derived from Rrs(λ) are affected by the bias to varying degrees, with particulate backscattering varying up to 50% over a year, chlorophyll varying up to 25% over a year, and absorption from phytoplankton or dissolved material varying by up to 15%. The propagation of Rrs(λ) bias into derived products is broadly confirmed on regional and global scales using Argo floats and data from the cloud-aerosol lidar with orthogonal polarization instrument aboard the cloud-aerosol lidar and infrared pathfinder satellite. The artifactual seasonality in ocean color is prominent in areas of low biomass (i.e., subtropical gyres) and is not easily discerned in areas of high biomass. While we have eliminated several candidates that could cause the biases in Rrs(λ), there are still outstanding questions regarding potential contributions from atmospheric corrections. Specifically, we provide evidence that the aquatic bidirectional reflectance distribution function may in part cause the observed seasonal bias, but this does not preclude an additional effect of the aerosol estimation. Our investigation highlights the contributions that atmospheric correction schemes can make in introducing biases in Rrs(λ), and we recommend more simulations to discern these influence Rrs(λ) biases. Community efforts are needed to find the root cause of the seasonal bias because all past, present, and future data are, or will be, affected until a solution is implemented.
Collapse
Affiliation(s)
- K. M. Bisson
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331, USA
| | - E. Boss
- School of Marine Sciences, University of Maine, Orono, Maine 04469, USA
| | - P. J. Werdell
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
| | - A. Ibrahim
- Ocean Ecology Laboratory, NASA Goddard Space Flight Center, Greenbelt, Maryland 20771, USA
| | - R. Frouin
- Scripps Institution of Oceanography, La Jolla, California 92093, USA
| | - M. J. Behrenfeld
- Department of Botany and Plant Pathology, Oregon State University, Corvallis, Oregon 97331, USA
| |
Collapse
|
5
|
Chase AP, Kramer SJ, Haëntjens N, Boss ES, Karp‐Boss L, Edmondson M, Graff JR. Evaluation of diagnostic pigments to estimate phytoplankton size classes. LIMNOLOGY AND OCEANOGRAPHY, METHODS 2020; 18:570-584. [PMID: 33132771 PMCID: PMC7589370 DOI: 10.1002/lom3.10385] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/16/2020] [Revised: 06/01/2020] [Accepted: 07/11/2020] [Indexed: 05/19/2023]
Abstract
Phytoplankton accessory pigments are commonly used to estimate phytoplankton size classes, particularly during development and validation of biogeochemical models and satellite ocean color-based algorithms. The diagnostic pigment analysis (DPA) is based on bulk measurements of pigment concentrations and relies on assumptions regarding the presence of specific pigments in different phytoplankton taxonomic groups. Three size classes are defined by the DPA: picoplankton, nanoplankton, and microplankton. Until now, the DPA has not been evaluated against an independent approach that provides phytoplankton size calculated on a per-cell basis. Automated quantitative cell imagery of microplankton and some nanoplankton, used in combination with conventional flow cytometry for enumeration of picoplankton and nanoplankton, provide a novel opportunity to perform an independent evaluation of the DPA. Here, we use a data set from the North Atlantic Ocean that encompasses all seasons and a wide range of chlorophyll concentrations (0.18-5.14 mg m-3). Results show that the DPA overestimates microplankton and picoplankton when compared to cytometry data, and subsequently underestimates the contribution of nanoplankton to total biomass. In contrast to the assumption made by the DPA that the microplankton size class is largely made up of diatoms and dinoflagellates, imaging-in-flow cytometry shows significant presence of diatoms and dinoflagellates in the nanoplankton size class. Additionally, chlorophyll b is commonly attributed solely to picoplankton by the DPA, but Chl b-containing phytoplankton are observed with imaging in both nanoplankton and microplankton size classes. We suggest revisions to the DPA equations and application of uncertainties when calculating size classes from diagnostic pigments.
Collapse
Affiliation(s)
| | - Sasha J. Kramer
- Interdepartmental Graduate Program in Marine ScienceUniversity of California Santa BarbaraSanta BarbaraCaliforniaUSA
| | - Nils Haëntjens
- School of Marine SciencesUniversity of MaineOronoMaineUSA
| | | | - Lee Karp‐Boss
- School of Marine SciencesUniversity of MaineOronoMaineUSA
| | - Mimi Edmondson
- School of Marine SciencesUniversity of MaineOronoMaineUSA
| | - Jason R. Graff
- Department of Botany and Plant PathologyOregon State UniversityCorvallisOregonUSA
| |
Collapse
|
6
|
Schoefs B, Van de Vijver B, Wetzel CE, Ector L. Introduction : From diatom species identification to ecological and biotechnological applications. BOTANY LETTERS 2020. [PMID: 0 DOI: 10.1080/23818107.2020.1719883] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/08/2023]
Affiliation(s)
- Benoît Schoefs
- Metabolism, bIoengineering of Molecules from Microalgae and Applications, Mer Molécules Santé, Le Mans University, Le Mans, France
| | - Bart Van de Vijver
- Research Department, Meise Botanic Garden, Meise, Belgium
- Department of Biology - ECOBE, University of Antwerp, Antwerp, Belgium
| | - Carlos E. Wetzel
- Department Environmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
| | - Luc Ector
- Department Environmental Research and Innovation (ERIN), Luxembourg Institute of Science and Technology (LIST), Belvaux, Luxembourg
| |
Collapse
|
7
|
Tsakalakis I, Pahlow M, Oschlies A, Blasius B, Ryabov AB. Diel light cycle as a key factor for modelling phytoplankton biogeography and diversity. Ecol Modell 2018. [DOI: 10.1016/j.ecolmodel.2018.06.022] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/28/2022]
|
8
|
Reverse weathering as a long-term stabilizer of marine pH and planetary climate. Nature 2018; 560:471-475. [DOI: 10.1038/s41586-018-0408-4] [Citation(s) in RCA: 94] [Impact Index Per Article: 15.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 06/07/2018] [Indexed: 11/08/2022]
|
9
|
Diatom Phenology in the Southern Ocean: Mean Patterns, Trends and the Role of Climate Oscillations. REMOTE SENSING 2016. [DOI: 10.3390/rs8050420] [Citation(s) in RCA: 28] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
|
10
|
Environmental information for a marine ecosystem research approach for the northern Antarctic Peninsula (RV Polarstern expedition PS81, ANT-XXIX/3). Polar Biol 2015. [DOI: 10.1007/s00300-015-1861-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
|