Substantial loss of isoprene in the surface ocean due to chemical and biological consumption

Evidence for biological and chemical isoprene consumption in coastal seawater

The time course of isoprene concentration in coastal seawater samples incubated in closed glass bottles at the in situ temperature and in the dark demonstrated sustained loss for at least 45 h (Fig. 1a). Enclosure without headspace prevented isoprene loss by ventilation, and darkness was assumed to arrest all or most of the biological production²⁵ and any photochemical production¹⁵ or degradation. Thus, the measured loss was considered the result of microbial degradation and chemical oxidation. In most cases an exponential function fitted better the decay than a linear function (Supplementary Table 1), indicating first-order (concentration-dependent) kinetics for isoprene loss.

Incubation of microorganism-devoid (filtered through 0.2 µm) coastal seawater sampled next to seaweeds showed an isoprene loss (0.12 d⁻¹) that was half the loss in non-filtered water (0.20 d⁻¹; Fig. 1b and Supplementary Table 2), implying that chemical oxidation accounted for half the total loss. Oxidation by OH·, the fastest amongst isoprene reactions with oxidative transients for which reaction rate data exist¹⁹, could account for the observed chemical loss. However, the possibility of oxidation by hitherto overlooked, pervasive oxidants like H₂O₂ deserved consideration. The addition of unrealistically high concentrations of either H₂O₂ or the enzyme bromoperoxidase (BrPO), substantially speeded up the chemical loss (0.91 d⁻¹ with 10 µmol H₂O₂ L⁻¹, 0.31 d⁻¹ with 0.0025 units BrPO mL⁻¹; Fig. 1b and Supplementary Table 2). Isoprene could have reacted with H₂O₂ in seawater as it does in acidic aerosols²⁶. Besides, should dissolved²⁷ BrPOs from seaweeds or outer-membrane-bound²⁸ BrPOs from phytoplankton occur, they would have reacted with added H₂O₂ to produce hypobromous acid (HOBr), a strong oxidant²⁹ that would further remove isoprene. Indeed, the addition of BrPO consumed isoprene because it produced HOBr by reaction with the naturally occurring H₂O₂. Confirming this interpretation, large HOBr production by simultaneous addition of BrPO and H₂O₂ caused complete isoprene removal in less than 4 h (Fig. 1b). Therefore, the results shown in Fig. 1b indicate that isoprene is reactive to pervasive H₂O₂ either directly or through the formation of enzymatically derived HOBr. All in all, first-order total isoprene loss (Fig. 1a) is expected to depend on photochemically-produced oxidants³⁰ like H₂O₂, OH· and ¹O₂ as well as on microbiota through (a) microbial uptake and catabolism¹¹ and (b) reaction with biologically produced oxidants^26,31,32 like HOBr, H₂O₂ or superoxide.

Variability of isoprene loss rate constants in the open ocean

Ten of the eleven offshore experimental sites were located in the open ocean, and one was located on the Southwestern Atlantic Shelf. Altogether they covered wide ranges of latitude (40°N–61°S), sea surface temperature (−0.8–28.6 °C), daily-averaged wind speed (3–12 m s⁻¹), fluorometric chlorophyll-a (chla) concentration (0.1–5.8 mg m⁻³), and isoprene concentration (4–104 nmol m⁻³) (Fig. 2, Table 1 and Supplementary Table 3). Unfiltered seawater samples from the surface ocean were incubated in glass bottles for 24 h, at the in situ temperature and in the dark, and first-order loss rate constants were determined from initial and final isoprene concentrations (see Methods). Note that loss was determined under the assumption that isoprene production was arrested in the dark²⁵. There is published evidence that residual isoprene production may occur in the dark³³, but in our incubations, it was insufficient to counteract loss. Thus, isoprene losses caused by processes other than ventilation may have been underestimated.

Loss rate constants (k_loss = k_bio + k_chem) varied over an order of magnitude, ranging 0.03–0.64 d⁻¹ with a median of 0.08 d⁻¹ (Table 1). They did not show any significant relationship to sea surface temperature (SST) (Supplementary Fig. 1) but showed proportionality to the chla concentration (Fig. 3a) that was best described by the following linear regression equation:

The fact that the variability of k_loss is largely driven by [chla] suggests that the variable term (0.10 × [chla]) corresponds to microbiota-dependent consumption (k_bio), which in our experiments gave values between 0 and 0.59 d⁻¹, with a median of 0.03 d⁻¹. These are the first experimental estimates of their kind and, hence, there are no other data to compare to. With a lack of experimental data, a pioneering modelling study¹⁸ proposed the use of a fixed k_bio at 0.06 d⁻¹; more recently²³, though, the need for a variable k_bio spanning at least between 0.01 and 0.1 d⁻¹ was invoked to balance observed concentrations in situ with predictions of the production term from phytoplankton culture data once the ventilation and chemical losses were accounted for. Our experimental results indicate that such variable k_bio indeed exists and spans even a broader range. The most complete model of the global oceanic isoprene cycle to date¹⁷ also performed the best simulations with a variable k_bio. This was computed proportional to the simulated [chla], with a proportionality coefficient of 0.054, i.e. roughly half the coefficient we obtained by linear regression of observations (0.10).

Part of the k_bio (or variable k_loss) is to be attributed to degradation or utilisation by heterotrophic bacteria. A pioneering study²⁰ demonstrated the potential for bacterial consumption after isoprene additions at concentrations at least four orders of magnitude higher than natural concentrations. This has been accompanied by sparse but solid evidence^20,21,34 for the presence in marine waters of isoprene-degrading bacteria belonging mainly to the phylum Actinobacteria. Two more recent studies^24,35 suggested that members of the ubiquitous SAR11, the most abundant bacterial clade in the ocean, can also consume isoprene, but this was mainly based on indirect evidence and requires confirmation. Our k_loss did not show any significant correlation with the total bacterial abundance (Table 1). It must be noted, though, that bacterial abundance does not necessarily parallel heterotrophic bacterial activity, less so the activity of specific phyla, whereas a general trend of higher bacterial activity with higher [chla] is commonly observed³⁶. Besides, phytoplankton-derived oxidants like the aforementioned H₂O₂ and HOBr may have also contributed to the dependence of isoprene loss on [chla]. Circumstantial evidence in one study³⁷ suggested that the cosmopolitan cyanobacterium Synechococcus might consume isoprene; it is worth noting that Synechococcus harbours membrane-bound BrPO³⁸ and may, thus, consume isoprene as a side-process of combatting oxidative stress caused by H₂O₂. If confirmed, this could have contributed to the correlation between k_loss and [chla]. However, the three highest k_loss of our experimental series were measured in waters colder than 14 °C where Synechococcus occurred at very low biomass^39,40. Therefore, these cyanobacteria cannot be invoked as responsible for the high k_loss paralleling high [chla], and a large proportion of the k_bio term of k_loss must correspond to degradation by heterotrophic bacteria³⁴ as well as to reaction with biogenic oxidants from phytoplankton.

We attribute the intercept of Eq. (1) to a less variable loss by microbiota-independent chemical oxidation¹⁸, k_chem. In remarkable support to this, the value of the intercept, 0.05 ± 0.01 d⁻¹, coincides with the k_chem commonly prescribed in models hitherto^17,18,41, which was calculated from reaction rate constants and estimated steady-state concentrations of photochemically-produced OH· and ¹O₂ in the surface ocean.

Despite the limited number of experiments, the fact that they cover a wide range of contrasting oceanic regions and conditions confers to Eq. (1) the potential to be used in numerical models of marine isoprene cycling, replacing the fixed term for microbial consumption^18,41. The k_loss vs. [chla] relationship here proposed can also be used to predict k_loss from remote sensing chla measurements (chla_sat). It must be noted, however, that the algorithms used to obtain [chla_sat] from satellite spectral data and to compare among sensors, are validated against HPLC-measured chla⁴², not against the fluorometric chla that was used in Eq. (1). To convert fluorometric to satellite chla concentrations we used a relationship obtained with a global compilation of in situ fluorometric measurements and their match-ups from SeaWiFS and MODIS Aqua sensors:⁴³

Substitution in Eq. (1) results in:

which is our recommended equation for k_loss prediction from satellite chla. Note that only the variable term (k_bio) changes from Eq. (1), while the intercept (k_chem) is maintained at 0.05 d⁻¹.

Comparison of isoprene sinks and total turnover time

The change of isoprene concentration ([iso]) in the surface mixed layer over time can be described as the budget of sources and sinks:

where k_prod, k_vent and k_mix are the rate constants of isoprene production, ventilation to the atmosphere and vertical downward mixing by turbulent diffusion, respectively.

We calculated k_vent from our sampling sites over a period of 24 h (Table 1). Ventilation has been considered the main isoprene sink from the upper mixed layer of the ocean¹⁸. In our sampling sites, k_loss was 0.4 to 10 times the k_vent (median factor: 1.2). That is, loss through microbial + chemical consumption was of the same order as ventilation, sometimes considerably faster. Vertical mixing, k_mix, was estimated to be one order of magnitude lower than the other process rates (Table 1), and in all cases but one it was calculated or assumed not to be a loss term but an import term into the mixed layer, because vertical profiles generally show maximum isoprene concentrations below the mixed layer and turbulent diffusion causes upward transport^14,17. Altogether, the microbial, chemical, ventilation, and, where relevant, mixing losses resulted in total turnover times (1/(k_loss + k_vent + k_mix)) of isoprene between 1.4 and 16 days, median 5 days (Table 1).

Isoprene production

Assuming steady-state for isoprene concentrations over 24 h (Supplementary Fig. 2), i.e. Δ[iso]/Δt = 0 in Eq. (4), the sum of the daily rate constants of all sinks (k_loss + k_vent) equals the rate constant of isoprene production (k_prod), with k_mix adding to either side depending on whether it is an import to or an export from the mixed layer (Table 1). Note that k_prod was the highest coinciding with higher [chla]. This is consistent with a recent study⁴⁴ where measurement of the net biological isoprene production (i.e. production — consumption rates) across seasons in the open ocean was attempted; net production rates increased in May, coinciding with a large increase in [chla] and phytoplankton cell abundance.

The product of k_prod by the isoprene concentration gives the daily isoprene production rate, which can be normalised by dividing it by the chla concentration. In our study, this specific isoprene production rate varied between 1 and 38 nmol (mg chla)⁻¹ d⁻¹ (Table 1), median 8 nmol (mg chla)⁻¹ d⁻¹. These values are within the broad range reported across phytoplankton taxa from laboratory studies with monocultures^41,45 (0.3–32, median 3 nmol (mg chla)⁻¹ d⁻¹, n = 124). Five of the eleven sites gave values >13 nmol (mg chla)⁻¹ d⁻¹, i.e. in the higher end of the laboratory data range. This is not unexpected, since measurements in monoculture experiments are typically conducted before reaching nutrient limitation, below light saturation and in the absence of UV radiation, to mention three stressors commonly occurring in the surface open ocean. If isoprene biosynthesis and release is enhanced by any of these stressors, as is the case in vascular plants^7,10, then monoculture-derived results will easily render underestimates of isoprene production in the open ocean. Production by heterotrophic bacteria⁴⁶ could have also contributed to increase apparent specific isoprene production rates, but the occurrence and importance of this process in the marine environment is unknown.

When plotted against the SST, which was also the temperature of the incubations, specific isoprene production rates increased exponentially between −0.8 and 23 °C and dropped drastically at higher SST (Fig. 3b). Several studies with phytoplankton monocultures have reported positive dependence of specific isoprene production rates on temperature^{45,47,48,49,50}. One of these studies⁴⁵ described that the increase with temperature reaches an optimum for production that varies among phytoplankton strains and with light intensity, but falls around 23–26 °C. The most detailed study⁴⁷ was conducted with a Prochlorococcus strain; remarkably, the shape of the specific production rate vs. temperature curve for this cyanobacterium strain was almost identical to that of Fig. 3b, with an exponential increase until 23 °C and a drop thereafter. This is the canonical curve type of enzymatic activities, but the thermal behaviour of the enzymes for isoprene synthesis in marine unicellular algae has not yet been characterised¹².

Revising the magnitude and players of the marine isoprene cycle

Our results allow redrawing the isoprene cycle in the surface mixed layer of the ocean. Figure 4 sketches the magnitude of the rate constants for production and sinks presented in Table 1, averaged according to a chla concentration threshold: the blue and green arrows correspond to the experiments in waters with [chla] lower and higher than 0.4 mg m⁻³, respectively. Isoprene production in productive (chla-richer) waters is faster than in oligotrophic (chla-poorer) waters. Vertical mixing is assumed to majorly constitute an input into the mixed layer, yet very small. Photochemical production and emission from surfactants¹⁵ in the surface microlayer of productive waters is depicted as uncertain. Among sinks, the microbiota-dependent consumption is much faster in productive waters; actually, the statistical uncertainty of Eq. (1) and the uneven distribution of incubation results along the [chla] axis hamper resolving k_bio in phytoplankton-poor waters (<0.4 mg m⁻³), which represent nearly 80% of the area of the global surface ocean as a monthly average. Here, k_loss can be anything between 0.03 and 0.09 d⁻¹, and therefore k_bio will be <0.04 d⁻¹. Putative purely chemical oxidation is considered invariant irrespective of the chla content; consequently, the combined microbial + chemical loss is much faster in productive waters. The k_vent for ventilation to the atmosphere is not significantly different between the two groups because it depends on wind speed and SST, which are both independent of [chla].

Note that this comparison applies to process rate constants k (d⁻¹), which represent the velocities at which processes occur and are attributable to biological and environmental agents. The actual process rates (nmol m⁻³ d⁻¹) will result from multiplying each of these k by the isoprene concentration, [iso]. Even though [iso] tends to increase with [chla], there is no such a thing as a globally valid proportionality between the two^13,14,51 (Table 1). All in all, more isoprene is produced in productive waters but more is consumed as well; therefore, predicting the resulting effect on isoprene concentrations and air–sea fluxes is not straightforward.

Concluding remarks

Until now, most of the focus of isoprene cycling studies had been on the production term, considering specific production rates by phytoplankton as though they were constitutive and shaped by phylogeny⁴¹, with an occasional emphasis on how they are tuned by acclimation to environmental conditions^45,47,50. Even though teasing apart phylogeny and acclimation at the cross-basin and seasonal scales is not an easy task because species and community succession are interlinked with environmental stressors, our results call for a deeper exploration of the ecophysiological drivers of isoprene biosynthesis by phytoplankton. As a matter of fact, whilst isoprene production is grosso modo related to phytoplankton biomass and primary production (Fig. 4), the resulting isoprene concentration does not necessarily follow indicators of phytoplankton biomass such as chla but it is further influenced by environmental factors such as SST^12,13,14,51. In spite of the lack of a mechanistic explanation, we conclude that temperature plays an important role in governing chla-normalised isoprene production across regions of the open ocean. While expanding the lab-derived database of specific isoprene production rates across phytoplankton taxa is always desirable, we argue there is a need for in situ measurements under variable natural conditions if we are to reliably predict isoprene production in the ocean.

We also show that the loss terms in the cycle are more complex and variable than believed, with a microbiota-dependent sink that is tightly coupled to production and can dominate over ventilation in chla-rich waters (Fig. 4). Considering all sinks together (ventilation, biological and chemical loss and, on one occasion, vertical mixing), the resulting total turnover times of isoprene in the surface mixed layer of the open ocean are in the order of one or two weeks in oligotrophic waters but can be as short as 1 to 4 days in productive waters. The microorganisms and metabolic mechanisms involved in isoprene biological consumption³⁴ warrant further investigation because this important sink will be regulated by triggers of microbial speciation and activity, potential co-metabolisms, and microbial mortality by predators and viruses. Our results also indicate that chemical onsumption is more variable than estimated hitherto and has abiotic and biotic terms involving photochemically as well as biologically derived oxidants. All in all, isoprene concentration and emission to the atmosphere can no longer be regarded as controlled only by phytoplankton biomass and functional types, with fixed loss rates dominated by the physicochemical processes (air–sea exchange and oxidation), but rather intimately connected to the variable structure and dynamics of the pelagic microbial food web.

Source: Ecology - nature.com