Elsevier

Marine Chemistry

Volume 227, 20 December 2020, 103896
Marine Chemistry

Using empirical dynamic modeling to assess relationships between atmospheric trace gases and eukaryotic phytoplankton populations in coastal Southern California

https://doi.org/10.1016/j.marchem.2020.103896Get rights and content

Highlights

  • Causality testing shows that phytoplankton affect atmospheric trace gases.

  • Phytoplankton and gas relationships are observed during specific ecosystem states.

  • Small peaks, not seasonal cycle, in many trace gases were linked to various phytoplankton.

  • Some major peaks in CH3Br and CHCl3 correlated with phytoplankton taxa.

Abstract

Many different atmospheric trace gases have been directly and indirectly linked to biological sources and sinks. Here we assess how atmospheric mixing ratios of a range of halocarbons (CH3Br, CH2Br2, CHBr3, CH3Cl, CHCl3, and CH3I) and COS are causally connected to naturally occurring marine eukaryotic phytoplankton in coastal Southern California. We use a self-organizing map to characterize the abiotic environment and empirical dynamic modeling with convergent cross mapping to identify causal interactions between multiple in situ 8-year time-series, sampled at the Ellen Browning Scripps Pier at Scripps Institution of Oceanography. Our work supports previous findings that halocarbon production is found in a variety of marine phytoplankton taxa and suggests that local phytoplankton may have the ability to affect changes in the mixing ratios of halocarbons in nearshore environments. There were notable links between changes in CH3I and several different diatom taxa and between changes in CHCl3 and a group of phytoplankton during specific ecosystem states. Our results suggest that both seasonal and non-seasonal shifts in eukaryotic phytoplankton structure contribute to small fluctuations in atmospheric halocarbon mixing ratios that exhibit strong seasonality and may occasionally play a larger role in atmospheric mixing ratios of halocarbons that display reduced seasonality.

Introduction

Phytoplankton can affect the atmospheric mixing ratios of a range of trace gases directly through production and indirectly by contributing biomass that is broken down during senescence and death. It is known that phytoplankton can produce halogenated volatile organic compounds (VOCs), a class of trace gases that are of interest due to their effects on tropospheric chemistry and their ability to destroy ozone when transported to the stratosphere (WMO, 2018). Specifically, a variety of marine phytoplankton and macrophytes have been shown to emit methyl bromide (CH3Br), dibromomethane (CH2Br2), bromoform (CHBr3), methyl chloride (CH3Cl), chloroform (CHCl3), and methyl iodide (CH3I) in the lab (Manley and Dastoor, 1988; Scarratt and Moore, 1996, Scarratt and Moore, 1998; Moore, 2003; Colomb et al., 2008; Brownell et al., 2010; Paul and Pohnert, 2011; Johnson et al., 2015; Lim et al., 2018) and at offshore sites (Baker et al., 2000; Moore and Tokarczyk, 1993; Moore, 2003). While in situ studies relating specific nearshore coastal marine phytoplankton to atmospheric mixing ratios of these trace gases are notably lacking, previous work in the open ocean has linked CH3Br, CH2Br2, CHBr3, CH3Cl, CHCl3, and CH3I to chlorophyll a concentration and phytoplankton type (Arnold et al., 2010).

The inorganic compound carbonyl sulfide (COS) is another trace gas that is linked to phytoplankton. COS is the most abundant sulfur-containing gas in the atmosphere and can indirectly affect climate by contributing to the stratospheric sulfate pool through interactions with UV light and free radicals (Carpenter et al., 2014; Whelan et al., 2018). COS from the marine environment is produced by a combination of sources, including salt marsh vegetation (Commane et al., 2013; Whelan et al., 2013) and the photochemical oxidation of dissolved organic sulfur compounds (Andreae and Ferek, 1992), mainly dimethylsulfide and the organic building block carbon disulfide (Andreae and Crutzen, 1997; Kettle et al., 2002). Thus, COS production is indirectly related to phytoplankton activities and it has also been observed to be consumed at low levels by marine algae (Blezinger et al., 2000).

The aforementioned studies either took place in laboratory settings or are based on relatively few data points during fairly short periods of fieldwork, limiting the projection of these data to other settings or the wider ecosystem. The lack of long-term monitoring has made it difficult to establish clear links between natural populations of phytoplankton and atmospheric trace gases. Long-standing time-series provide a unique framework in which to analyze and statistically relate many different variables in an open system and simultaneously allow for baseline observations, an understanding of natural cycles (e.g., seasonality, upwelling, etc.), and an understanding of anthropogenic change. By studying variables that are not removed from natural ecological interactions or environmental perturbations, conclusions regarding connections between different variables are more accurate.

We took advantage of several long-standing time-series collected from the Ellen Browning Scripps Pier (Scripps Pier), located within the Southern California Bight ecosystem, to establish causal links between naturally occurring and ecologically active (changing due to natural abiotic and biotic pressures) eukaryotic phytoplankton populations and atmospheric trace gases over 8 years. Our overarching goal was to assess how atmospheric mixing ratios of halocarbons and COS may be affected by natural populations of ecologically active marine eukaryotic phytoplankton through time. We did not seek to explain all of the variation observed in any of the trace gas mixing ratios, nor in the phytoplankton populations. Rather, we sought to assess whether changes in groups of specific phytoplankton led to time-lagged changes in trace gases at certain times. Many of the time-series displayed strong nonlinear dynamics (meaning that the time-series could be correlated at some points in time and not others) and so we utilized 1) a self-organizing map (SOM, Kohonen, 2001) to segment and characterize the abiotic portion of the ecosystem state (e.g. water temperature), and 2) empirical dynamic modeling (EDM) with convergent cross mapping (CCM) to assess causal links between individual phytoplankton and trace gases. This latter method has been used for a wide range of applications including identifying drivers of global influenza cases (Deyle et al., 2016) and controls on fish recruitment (Deyle et al., 2018). EDM with CCM has also been used to predict coastal algal blooms in Southern California (McGowan et al., 2017). EDM with CCM is particularly useful to our purposes because it can show causality between nonlinear time-series that may correlate during certain system states (all the ecological and abiotic factors that describe a regime or ecosystem state) but not in others, and can recreate system states without input for all the variables naturally acting on a time-series (Sugihara et al., 2012). Put another way, ecological and environmental interactions may only be present during some time-periods and CCM allowed us to assess causal links between individual phytoplankton taxa and trace gases without data describing every variable present in our system (e.g., terrestrial biomass production of a trace gas, atmospheric transport, etc.). However, the link between phytoplankton and trace gases may not be direct (e.g., trace gases could be indirectly linked to phytoplankton community structure through the microbial degradation of senescent or dead phytoplankton). Therefore, we used CCM to show which populations may have a direct or indirect link to atmospheric trace gas mixing ratios. Finally, while a SOM does not show causality, it can characterize different ecosystem states for the variables that were used and thus allowed us to assess if there were certain abiotic ecosystem states during which phytoplankton and traces gases were causally linked.

We had two broad expectations going into this study. First, because many eukaryotic phytoplankton and trace gases follow seasonal cycles, we expected that annually seasonal phytoplankton would causally link to trace gases that followed corresponding seasonal cycles. Second, we anticipated causal links between stochastic phytoplankton and trace gases with reduced seasonality. Regardless of our expectations, establishing connections between phytoplankton and trace gases (and the ecosystem states that those links exist within) is the first step in assessing how direct and/or indirect phytoplankton production of these trace gases are affected by long-term sustained ecosystem shifts or changes in specific seasonal factors.

Section snippets

Methods

All data were collected off the Scripps Pier at Scripps Institution of Oceanography (SIO; 32.8663° N, 117.2546° W). SIO is located in La Jolla, CA within the often-studied Southern California Bight ecosystem (Di Lorenzo, 2003; Tai and Palenik, 2009; McGowan et al., 2017). Local conditions are influenced by the adjacent California Current ecosystem, with offshore upwelling typically occurring in summer months (Bakun, 1973).

The Advanced Global Atmospheric Gases Experiment (AGAGE) measures a range

Variation in trace gases, environmental variables, and eukaryotic phytoplankton

All of the observed trace gases displayed significant variation over the time-series and were sorted into three groups based on seasonality: 1) visible annual seasonality, 2) visible annual seasonality with an aseasonal feature, and 3) multiple-seasonality (with reliable peaks in multiple seasons) to no seasonality. CH3Cl, CH3I, and COS each displayed strong seasonality with maxima in one season: winter/spring for CH3Cl and summer for CH3I and COS (Fig. 1D, F, G). CH2Br2 and CHBr3 also

Discussion

Through the use of EDM with CCM we were able to show that changes in several species, genera, and types of eukaryotic phytoplankton led to changes in select trace gases in a nearshore Southern California coastal environment. Though ρ values for various phytoplankton affecting trace gases were low, our findings demonstrate that phytoplankton community composition has an impact on atmospheric chemistry in the marine boundary layer. Phytoplankton influence trace gas mixing ratios through direct

Conclusion

This work demonstrated that naturally occurring, ecologically active eukaryotic phytoplankton affect a range of trace gases in coastal Southern California on scales of 0 to 3 weeks during different times of the year. We utilized long-standing in situ observations to capture the effects of naturally occurring environmental or ecological interactions and applied causality testing to assess directionality of relationships. The method successfully identified some causal interactions between coastal

Declaration of Competing Interest

None.

Acknowledgements

The authors wish to specifically acknowledge Kristi Seech and Mary Hilbern for their efforts on phytoplankton cell identification and enumeration, James Fumo for data integration, John A. McGowan for support and leadership over the decades with the McGowan Plankton and Chlorophyll Program (Funding provided by private donors and the MacArthur Foundation) and Southern California Coastal Ocean Observing Harmful Algal Bloom Monitoring Program (NOAA NA16NOS0120022, NA11NOS120029, and NA17RJ1231).

References (81)

  • M.G. Scarratt et al.

    Production of methyl bromide and methyl chloride in laboratory cultures of marine phytoplankton II

    Mar. Chem.

    (1998)
  • M.E. Whelan et al.

    Salt marsh vegetation as a carbonyl sulfide (COS) source to the atmosphere

    Atmos. Environ.

    (2013)
  • M.O. Andreae et al.

    Atmospheric aerosols: biogeochemical sources and role in atmospheric chemistry

    Science

    (1997)
  • M.O. Andreae et al.

    Photochemical production of carbonyl sulfide in seawater and its emission to the atmosphere

    Glob. Biogeochem. Cycles

    (1992)
  • S.R. Arnold et al.

    Relationships between atmospheric organic compounds and air-mass exposure to marine biology

    Environ. Chem.

    (2010)
  • A.R. Baker et al.

    Distribution and sea-air fluxes of biogenic trace gases in the eastern Atlantic Ocean

    Glob. Biogeochem. Cycles

    (2000)
  • A. Bakun

    Coastal upwelling indices, west coast of North America, 1946-71. U.S. Dep. Commer. NOAA Tech. Rep. NMFS SSRF-671, 103 p

    (1973)
  • E.A. Betterton et al.

    Reductive dehalogenation of bromoform in aqueous solution

    Environ. Health Perspect.

    (1995)
  • S. Blezinger et al.

    Enzymatic consumption of carbonyl sulfide (COS) by marine algae

    Biogeochemistry

    (2000)
  • S. Bondu et al.

    Effects of salt and light stress on the release of volatile halogenated organic compounds by Solieria chordalis: a laboratory incubation study

    Bot. Mar.

    (2008)
  • J.S. Bowman et al.

    Recurrent seascape units identify key ecological processes along the western Antarctic peninsula

    Glob. Chang. Biol.

    (2018)
  • D.K. Brownell et al.

    Production of methyl halides by Prochlorococcus and Synechococcus

    Glob. Biogeochem. Cycles

    (2010)
  • L.J. Carpenter et al.

    Novel biogenic iodine-containing trihalomethanes and other short-lived halocarbons in the coastal East Atlantic

    Glob. Biogeochem. Cycles

    (2000)
  • L.J. Carpenter et al.

    Atmospheric chemistry and physics air-sea fluxes of biogenic bromine from the tropical and North Atlantic Ocean, Atmos

    Chem. Phys.

    (2009)
  • L.J. Carpenter et al.

    CHAPTER 1 Update on Ozone-Depleting Substances (ODSs) and Other Gases of Interest to the Montreal Protocol UPDATE ON OZONE-DEPLETING SUBSTANCES (ODSs) AND OTHER GASES OF INTEREST TO THE MONTREAL PROTOCOL Contents, Global Ozone Research and Monitoring

    (2014)
  • A. Colomb et al.

    Screening volatile organic compounds (VOCs) emissions from five marine phytoplankton species by head space gas chromatography/mass spectrometry (HS-GC/MS)

    J. Environ. Monit.

    (2008)
  • R. Commane et al.

    Carbonyl sulfide in the planetary boundary layer: coastal and continental influences

    J. Geophys. Res. Atmos.

    (2013)
  • R. Core Team

    R: A Language and Environment for Statistical Computing

    (2018)
  • E.R. Deyle et al.

    Global environmental drivers of influenza

    Proc. Natl. Acad. Sci. U. S. A.

    (2016)
  • E. Deyle et al.

    Ecosystem-based forecasts of recruitment in two menhaden species

    Fish Fish.

    (2018)
  • R.J. Ferek et al.

    Photochemical production of carbonyl sulphide in marine surface waters

    Nature

    (1984)
  • K.D. Goodwin et al.

    Production of bromoform and dibromomethane by Giant Kelp: factors affecting release and comparison to anthropogenic bromine sources

    Limnol. Oceanogr.

    (1997)
  • P.M. Gschwend et al.

    Volatile halogenated organic compounds released to seawater from temperate marine macroalgae

    Science

    (1985)
  • J.D. Happell et al.

    Methyl iodide in the Greenland/Norwegian seas and the tropical Atlantic Ocean: evidence for photochemical production

    Geophys. Res. Lett.

    (1996)
  • T.L. Johnson et al.

    Halomethane production by vanadium-dependent bromoperoxidase in marine Synechococcus

    Limnol. Oceanogr.

    (2015)
  • T. Kataoka et al.

    Production of Dibromomethane and changes in the bacterial Community in Bromoform-Enriched Seawater

    Microbes Environ.

    (2019)
  • W.C. Keene et al.

    Composite global emissions of reactive chlorine from anthropogenic and natural sources: reactive chlorine emissions inventory

    J. Geophys. Res. Atmos.

    (1999)
  • A.J. Kettle et al.

    Global budget of atmospheric carbonyl sulfide: temporal and spatial variations of the dominant sources and sinks

    J. Geophys. Res.

    (2002)
  • M.A.K. Khalil et al.

    Natural emissions of chlorine-containing gases: reactive chlorine emissions inventory

    J. Geophys. Res. Atmos.

    (1999)
  • D.B. King et al.

    Implications of methyl bromide supersaturations in the temperate North Atlantic Ocean

    J. Geophys. Res. Atmos.

    (2000)
  • View full text