Skip to main content

Thank you for visiting You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

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


Isoprene contributes to the formation of ozone and secondary organic aerosol in the atmosphere, and thus influences cloud albedo and climate. Isoprene is ubiquitous in the surface open ocean where it is produced by phytoplankton, however emissions from the global ocean are poorly constrained, in part due to a lack of knowledge of oceanic sink or degradation terms. Here, we present analyses of ship-based seawater incubation experiments with samples from the Mediterranean, Atlantic, tropical Pacific and circum-Antarctic and Subantarctic oceans to determine chemical and biological isoprene consumption in the surface ocean. We find the total isoprene loss to be comprised of a constant chemical loss rate of 0.05 ± 0.01 d−1 and a biological consumption rate that varied between 0 and 0.59 d−1 (median 0.03 d−1) and was correlated with chlorophyll-a concentration. We suggest that isoprene consumption rates in the surface ocean are of similar magnitude or greater than ventilation rates to the atmosphere, especially in chlorophyll-a rich waters.


Isoprene (2-methyl-1,3-butadiene) emissions by terrestrial and marine life are altogether of a magnitude similar to the sum of natural and anthropogenic emissions of methane1,2, ca. 500 TgC year−1. Owing to its reactivity and short lifetime in the atmosphere3 (minutes to hours), isoprene impacts atmospheric chemistry by forming tropospheric ozone, modifying the oxidation behaviour of other organic compounds, and contributing to secondary organic aerosols4,5. Even though the oceans emit much less isoprene than vegetated land, the potential of biogenic aerosols to influence cloud albedo and lifetimes, hence climate, is large over the vast oceans remote from anthropogenic sources6.

On land, isoprene is produced and released mainly by trees and shrubs7. In the ocean, isoprene is produced primarily by phytoplankton8 and also by seaweeds9. Whilst in vascular plants isoprene production is related to rapid alleviation of thermal and oxidative stress and chemical signalling10,11, the ecophysiological functions of isoprene biosynthesis in phytoplankton are unknown, yet a similar antioxidant role has been speculated12. In any case, isoprene is ubiquitous in the surface ocean, where it occurs at concentrations mostly within the 1–100 nmol m−3 range13,14.

Estimations of the global ocean emission of isoprene have been attempted either by top-down (balancing modelled emissions to atmospheric observations) or bottom-up (modelling oceanic isoprene concentration and air–sea flux) approaches, and they diverge by one or two orders of magnitude14 (maximum range: 0.1–12 TgC year−1). In general, top-down estimates are much higher, which implies that atmospheric measurements, as well as knowledge of the atmospheric processes, are insufficient to properly constrain the top-down models, and/or the bottom-up studies underestimate the net isoprene production. An extra isoprene source through photoproduction by surfactants in the sea surface microlayer was invoked and experimentally demonstrated15 but later esteemed not enough to resolve the large discrepancy16. In any case, the difficulties in constraining the global marine isoprene emission have evidenced that knowledge of the magnitude, drivers, distribution, and dynamics of isoprene cycling processes is still poor due to lack of measurements and depends too much on a number of assumptions and laboratory-based studies11,14,17.

It is thought that not all the isoprene produced by phytoplankton escapes to the atmosphere because part of it is degraded in seawater, but the actual proportion is unknown. Chemical oxidation is taken for granted18 because of isoprene’s high reactivity19, but it has never been measured. Likewise, the occurrence of isoprene-degrading bacteria in seawater has been demonstrated20,21 and a significant microbial sink has been suggested22,23,24, but it has not been experimentally confirmed, let alone measured, in natural conditions including natural concentrations.

We conducted seawater incubations with the aim to determine if isoprene was chemically and biologically consumed in the surface ocean. Detailed time courses with coastal seawater informed on the kinetics of isoprene loss, and these kinetics were used to calculate loss rates from incubations conducted during four oceanographic expeditions across the Mediterranean Sea and the Atlantic Ocean, in the Tropical Pacific, and in Antarctic and Subantarctic waters. The obtained loss rate constants were compared with rate constants of air–sea flux and vertical mixing, and their variability across samples was examined by comparison with biological and environmental variables, with the aim to propose a predictive model that fills a major gap in the assessment of isoprene turnover in the surface ocean.

Results and discussion

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.

Fig. 1: Isoprene loss in dark incubations of coastal seawater.
figure 1

a Time course of isoprene concentration in 2 L dark incubations of non-filtered seawater samples from the back-reef lagoon of Mo’orea in April (blue) and the coastal Mediterranean in March (red) and May (green). Filled and open symbols correspond to duplicate incubations. Exponential fits to the data are shown by lines. See Supplementary Table 1 for fit equations and metrics, water temperatures and chlorophyll a concentrations. b Time course of isoprene concentration in series of 30 mL dark incubations of coastal Mediterranean seawater. Dark blue: non-filtered; red: filtered through 0.2 µm; green: filtered + 10 µmol L−1 H2O2; purple: filtered + 0.0025 units mL−1 bromoperoxidase (BrPO); light blue: filtered + H2O2 + BrPO. Exponential fit results in Supplementary Table 2.

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 oxidants26,31,32 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.

Fig. 2: Geographical distribution of the offshore experiments.
figure 2

Location of the sampling and incubation sites are shown by circles, coloured for isoprene concentration.

Table 1 Measured biological variables and isoprene process rate constants.

Loss rate constants (kloss = kbio + kchem) 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:

$${k}_{{{{{{\rm{loss}}}}}}}=0.10\; (\pm 0.01)\,{{{{{\rm{x}}}}}}\, [{{{{{\rm{chl}}}}}}a]+0.05\; (\pm 0.01)$$
Fig. 3: Isoprene processes and their main drivers.
figure 3

a Rate constant of isoprene loss in dark incubations (kloss, considered to be microbial and chemical consumption) vs. chlorophyll-a concentration. The linear regression equation is kloss = 0.10 × [chla] + 0.05 (R2 = 0.96, p = 10−7, n = 11). The standard error of the slope is 0.01 L mg−1 d−1, and the standard error of the intercept is 0.01 d−1. Error bars represent the experimentally determined standard error of kloss. The colour scale of the circles indicates bacterial abundances. b Specific (chla-normalised) rate of isoprene production vs seawater temperature (SST) across the sample series. The dashed line is the general smoothed trend. The blue line is the exponential adjustment at SST <23 °C: isoprene = 2.04 ×  e(0.13·SST) + 0.71 (R2 = 0.85, p = 10−3, n = 8).

The fact that the variability of kloss is largely driven by [chla] suggests that the variable term (0.10 × [chla]) corresponds to microbiota-dependent consumption (kbio), 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 kbio at 0.06 d−1; more recently23, though, the need for a variable kbio 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 kbio 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 kbio. 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 kbio (or variable kloss) 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 evidence20,21,34 for the presence in marine waters of isoprene-degrading bacteria belonging mainly to the phylum Actinobacteria. Two more recent studies24,35 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 kloss 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 kloss and [chla]. However, the three highest kloss of our experimental series were measured in waters colder than 14 °C where Synechococcus occurred at very low biomass39,40. Therefore, these cyanobacteria cannot be invoked as responsible for the high kloss paralleling high [chla], and a large proportion of the kbio term of kloss 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, kchem. In remarkable support to this, the value of the intercept, 0.05 ± 0.01 d−1, coincides with the kchem commonly prescribed in models hitherto17,18,41, 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 consumption18,41. The kloss vs. [chla] relationship here proposed can also be used to predict kloss from remote sensing chla measurements (chlasat). It must be noted, however, that the algorithms used to obtain [chlasat] 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

$$[{{{{{\rm{chl}}}}}}{a}_{{{{{{\rm{sat}}}}}}}]=0.79\,{{{{{\rm{x}}}}}}\, {[{{{{{\rm{chl}}}}}}a]}^{0.78}\,({R}^{2}=0.66,{n} \, > \, 1000)$$

Substitution in Eq. (1) results in:

$${k}_{{{{{{\rm{loss}}}}}}}=0.14\,{{{{{\rm{x}}}}}}\, {[{{{{{\rm{chl}}}}}}{a}_{{{{{{\rm{sat}}}}}}}]}^{1.28}+0.05$$

which is our recommended equation for kloss prediction from satellite chla. Note that only the variable term (kbio) changes from Eq. (1), while the intercept (kchem) 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:

$$\varDelta [{{{{{\rm{iso}}}}}}]/\varDelta {{{{{\rm{t}}}}}}=[{{{{{\rm{iso}}}}}}]\cdot ({k}_{{{{{{\rm{prod}}}}}}} - {k}_{{{{{{\rm{loss}}}}}}} - {k}_{{{{{{\rm{vent}}}}}}} - {k}_{{{{{{\rm{mix}}}}}}})$$

where kprod, kvent and kmix are the rate constants of isoprene production, ventilation to the atmosphere and vertical downward mixing by turbulent diffusion, respectively.

We calculated kvent 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, kloss was 0.4 to 10 times the kvent (median factor: 1.2). That is, loss through microbial + chemical consumption was of the same order as ventilation, sometimes considerably faster. Vertical mixing, kmix, 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 transport14,17. Altogether, the microbial, chemical, ventilation, and, where relevant, mixing losses resulted in total turnover times (1/(kloss + kvent + kmix)) 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 (kloss + kvent) equals the rate constant of isoprene production (kprod), with kmix adding to either side depending on whether it is an import to or an export from the mixed layer (Table 1). Note that kprod 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 kprod 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 monocultures41,45 (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 plants7,10, 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 temperature45,47,48,49,50. 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 kbio 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, kloss can be anything between 0.03 and 0.09 d−1, and therefore kbio 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 kvent 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].

Fig. 4: Relative magnitude of isoprene cycling processes in the surface ocean, according to oceanic productivity.
figure 4

The width of the arrows is proportional to the magnitude of the process rate constants (d−1), which have been averaged from the seven oligotrophic sites with [chla] <0.4 mg m−3 (blue arrows) and from the four productive sites with [chla] >0.4 mg m−3 (green arrows). Note the change in the relative magnitude of the sinks. The question mark next to the isoprene emission from photochemical reactions onto sea surface surfactants indicates the uncertainty in the magnitude of this source in productive waters.

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 two13,14,51 (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 conditions45,47,50. 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 SST12,13,14,51. 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.


Sampling and physical measurements

Mediterranean coastal water samples were collected in March and May 2021 at the Blanes Bay Microbial Observatory site52, over a 20 m water column, and in August 2021 at a rocky pier of the Barceloneta beach (Barcelona), at 20 cm from patches of the seaweeds Dictyoma dichotoma and Corallina elongata. Surface (0.2 m) seawater was hand-collected from a boat or the rocks, and the temperature was recorded with a calibrated SAIVA/S SD204 CTD sensor. Samples were kept in the dark and taken to the ICM-CSIC lab within 3 h for incubations. The BIOGAPS-Moorea expedition took place in April 2018 at the northern coast of the island of Mo’orea, French Polynesia. Surface (0.2 m) seawater was hand-collected from a boat at two locations: in very shallow waters of the coastal coral reef lagoon, and 3.5 km offshore over a water column depth of 1100 m. Seawater temperature was recorded with an SBE56 sensor (Sea-Bird Sci.) continuously flushed with pumped-in surface seawater. Samples were taken to the Gump Research Station (University California Berkeley) on the island for processing. The HOTMIX cruise53 traversed the Mediterranean Sea from East to West between 27 April and 29 May 2014 on board the R/V Sarmiento de Gamboa. Seawater was collected with a General Oceanics rosette, equipped with 24 L Niskin bottles. Temperature and salinity were recorded with an SBE911 + CTD system (Sea-Bird Sci.). The TransPEGASO cruise40 crossed the Atlantic Ocean from North to South on the R/V Hesperides, between 20 October and 21 November 2014. Surface seawater was sampled using the ship’s underway pumping system, which had the water intake located 4–5 m below sea level. All the parts of the centrifugal pump (BKMKC-10.11, Tecnium) that were in contact with the fluid were made of polypropylene and glass. Seawater temperature and salinity were recorded continuously via the flow-through thermosalinograph SBE21 SeaCAT (Sea-Bird Sci.). The PEGASO cruise39 was conducted on board de R/V Hesperides in the regions of Antarctic Peninsula, South Orkney and South Georgia Islands from 2 January to 11 February 2015. Seawater samples were collected from either the underway pumping system intake (same as above) or the uppermost (4 m) bottle of the rosette on SBE911 + CTD casts, which recorded temperature and salinity. In PEGASO, Lagrangian tracking of the surface (15 m) water patch was conducted using WOCE (World Ocean Circulation Experiment) standard drifters provided with an Iridium communication system. Each drifter consisted of a spherical floatable enclosure that contained a GPS and an emitter, from which 10 m cylindrical drogues hung 5 m below the sphere. The drifters sent their position every 30 min, and all ship operations were conducted next to them54. The same Lagrangian approach was used to check for steady-state behaviour over 24 h in the open NW Mediterranean Sea during the BIOGAPS-MED cruise on board the R/V García del Cid on 20-21/06/2019 (Supplementary Fig. 2).

Incubation experiments

For loss kinetics experiments with coastal water (Fig. 1a and Supplementary Table 1), duplicate all-glass bottles (2 L) were filled, leaving no headspace, and incubated in the dark in a water bath kept at the in situ temperature ±0.5 °C. Aliquots for duplicate isoprene analysis were taken from both bottles at t0 and 2–4 further time points, never removing more than 15% of the bottle volume in total. Since opening the bottles caused the loss of the headspace, at each time point isoprene concentrations were corrected for this loss using the volumetric headspace:water ratio and the dependence of the isoprene Henry’s law constant on temperature55:


where Hcp is the Henry solubility, T is the incubation temperature in Kelvin, Hcc is the dimensionless Henry solubility, [isoa] and [isow] are the isoprene concentrations in air (headspace) and water, respectively, and R is the gas constant.

For the chemical oxidation assay (Fig. 1b and Supplementary Table 1), coastal water was filtered sequentially through polycarbonate 3 and 0.2 µm pore-size filters, and the filtrate was used to fill four series of four gas-tight glass 30 mL vials. A working bromoperoxidase (BrPO) solution was prepared by dissolving 10 units of Corallina officinalis BrPO (Merck) with 100 µl of HEPES (4-(2-hydroxyethyl)−1-piperazineethanesulfonic acid) buffer 0.1 mol L−1 in 900 µl of MilliQ water. One of the series of vials had only filtered water, another was added 10 µmol L−1 of H2O2 (Merck), another was added BrPO to a final concentration of 0.0025 units mL−1, and another was added both H2O2 and BrPO. Together with a series of non-filtered water, they were all incubated in the dark in a water bath kept at the in situ temperature (24 ± 0.5 °C). The initial isoprene concentration was measured from the filtrate before filling the vials, and t1, t2, t3, and t4 concentrations were measured each sacrificing one of the vials.

For the 11 offshore experiments (Fig. 3, Supplementary Fig. 1 and Supplementary Table 2), duplicate all-glass bottles (0.5 L) were filled, leaving no headspace. One of the bottles was analysed in duplicate for isoprene to set the initial concentration. The other bottle was not opened and dark-incubated for 24 h in a tank with constant flushing of pumped-in surface ocean water, to keep incubation temperature the same as in situ. At the conclusion of the incubation time, isoprene concentration was analysed in sequential duplicates, each with its exact incubation time. The sample PEGASO B3 was incubated for only 9 h. The loss rate constant of isoprene kloss (d−1) was calculated as the slope of the natural logarithm of the concentration vs. time, under two assumptions: (a) consumption follows first-order kinetics, as in the case of other trace gases such as dimethyl sulfide56 and methyl halides57; coastal water experiments showed that first-order was a better approximation than zero-order (linear) kinetics (Fig. 1a and Supplementary Table 1); (b) isoprene production by phytoplankton, which is linked to photosynthesis25, is mostly arrested over the 24 h of incubation in the dark; if biosynthesis resumed for a while in the dark33, this would have reduced apparent loss and would have caused underestimation of kloss. The error of kloss was the standard error of the slope of Ln(concentration) vs. time.

Isoprene concentration

Isoprene was measured along with other volatile compounds on a gas chromatography–mass spectrometry system (5975-T LTM GC/MS, Agilent Technologies). Aliquots of 25 mL were drawn from the glass bottle with a glass syringe with a Teflon tube and filtered through a 25 mm glass fibre filter while introduced into a purge and trap system (Stratum, Tekmar Teledyne). The sample was purged by bubbling with 40 mL min−1 of ultrapure He for 12 min while heated to 30 °C. The stripped volatiles were trapped on solid adsorbent (VOCARB 3000) at room temperature and thermally desorbed (250 °C) into the GC. Isoprene monitored as m/z 67 in selected ion monitoring mode, had a retention time of 2.4 min in the LTM DB-VRX chromatographic column held at 35 °C. The detection limit was 1 pmol L−1, and the analytical precision was 5%. In HOTMIX, TransPEGASO and PEGASO, calibration was performed by injections of a gaseous mixture of isoprene in N2. In BIOGAPS-Moorea and coastal water experiments, a liquid standard solution prepared in cold methanol and subsequently diluted in MilliQ water was used instead.

Isoprene ventilation rate constant

The isoprene ventilation or air–sea exchange fluxes (Fvent, in nmol m−2 d−1) were calculated as:

$${F}_{{{{{{\rm{vent}}}}}}}={k}_{{{{{{\rm{AS}}}}}}}\,{{{{{\rm{x}}}}}}\,([{{{{{{\rm{iso}}}}}}}_{{{{{{\rm{w}}}}}}}] - [{{{{{{\rm{iso}}}}}}}_{{{{{{\rm{a}}}}}}}]/{{{{{{\rm{K}}}}}}}_{{{{{{\rm{H}}}}}}})\approx {k}_{{{{{{\rm{AS}}}}}}}\,{{{{{\rm{x}}}}}}\,[{{{{{{\rm{iso}}}}}}}_{{{{{{\rm{w}}}}}}}]$$

where [isow] is the isoprene concentration in surface seawater, [isoa] is the isoprene concentration in the air, KH is Henry’s Law constant for isoprene, and kAS is the gas exchange velocity (cm h−1). Air-side isoprene can be considered near zero and neglected for flux calculations because isoprene is highly reactive in the atmosphere, and it is largely supersaturated in the surface ocean. kAS was estimated using58:

$$k_{{{{{{\rm{AS}}}}}}}=0.251\,{{{{{\rm{x}}}}}}\,{{{{{{\rm{U}}}}}}}_{{{10}}^{2}}\, {{{{{\rm{x}}}}}}\, {({{{{{\rm{Sc}}}}}}/660)}^{-0.5}$$

where U10 is the wind speed at 10 m (m s−1), and Sc is the Schmidt number (non-dimensional). On cruises, the wind speed was measured by the ships’ meteorological stations and averaged over a period of 24 h, which was the duration of the incubations. In offshore Mo’orea, we recorded wind speed on the boat with a portable Skywatch BL500 micrometeorological station. This instantaneous wind speed was converted to the daily average by applying the factor between instantaneous and daily average wind speeds measured at the Gump Station onshore. Sc was computed18 as:


where SST is in degrees Celsius (°C). The error of the computed ventilation fluxes is estimated58 to be 20%. To convert the flux Fvent (nmol m−2 d−1) into the ventilation rate constant kvent (d−1), the flux was divided by the mixed layer depth (ZML, m) and by the isoprene concentration (nmol m−3), assuming that the surface concentration was equal to the average concentration in the mixed layer14. During HOTMIX and PEGASO, ZML was determined from CTD profiles as the depth at which density was 0.125 kg m−3 higher than that at 5 m. In the case of the TransPEGASO cruise and the BIOGAPS-Moorea expedition, where no CTD casts were conducted, we used the geo-localised monthly values from a global climatology59.

Isoprene vertical mixing rate constant

In the case of the three PEGASO samples (sampling sites #9–11), kmix was estimated from measured vertical profiles of isoprene concentration and the turbulent diffusion across the pycnocline (Kz). Thus, the vertical mixing flux at the bottom of the ML (Fmix, nmol m−2 d−1) was calculated as:

$${F}_{{{{{{\rm{mix}}}}}}}={{{K}}}_{{{{{{\rm{z}}}}}}}\,{{{{{\rm{x}}}}}}\,(\varDelta [{{{{{\rm{iso}}}}}}]/\varDelta {{{{{\rm{z}}}}}})$$

where a Kz = 2.6 m2 d−1 (or 0.3 cm2 s−1) was considered appropriate yet conservative for the Southern Ocean60, Δ[iso] (nmol m−3) was the isoprene concentration gradient across the upper pycnocline, and Δz (m) was the distance covered by this gradient. Depending on the location of the concentration maximum, Fmix was positive (loss term, export from the ML) or negative (gain term, import into the ML). kmix (d−1) was calculated by dividing Fmix by the surface isoprene concentration and ZML (determined from the CTD profiles as above). We note that using a wider range of Kz for Southern Ocean locations61,62 (0.1–1.0 cm2 s−1) would give 0.3–3 times the estimates of the kmix at sampling sites #9–11; however, the contribution of kmix to the calculation of kprod is so small (compared to those of the other sinks) that the effect of the Kz range on kprod was only noticeable in #11 (±8% of kprod). For HOTMIX, TransPEGASO and BIOGAPS-Moorea, kmix could not be estimated from in situ data and a fixed value of −0.005 d−1 was taken from the global integral suggested by a model17.

Chlorophyll a concentration

Seawater 250-mL samples were filtered on glass fibre filters, which were extracted with 90% acetone at 4 °C in the dark for 24 h. The fluorescence of extracts was measured with a calibrated Turner Designs fluorometer.

Bacterial abundance

Aliquots of 2 mL of the initial sample were fixed with 1% paraformaldehyde plus 0.05% glutaraldehyde and stored frozen at −80 °C. The numbers of heterotrophic bacteria were determined by flow cytometry (Cube 8, Partec) after staining with SYBR-Green63.

Data availability

All data needed to evaluate the conclusions are available in


  1. Guenther, A. B. et al. The model of emissions of gases and aerosols from nature version 2.1 (MEGAN2.1): an extended and updated framework for modeling biogenic emissions. Geosci. Model Dev. 5, 1471–1492 (2012).

    Google Scholar 

  2. Saunois, M. et al. The global methane budget 2000–2012. Earth Syst. Sci. Data 8, 697–751 (2016).

    Google Scholar 

  3. Medeiros, D., Blitz, M., James, L., Speak, T. & Seakins, P. Kinetics of the reaction of OH with isoprene over a wide range of temperature and pressure including direct observation of equilibrium with the OH adducts. J. Phys. Chem. A 122, 7239–7255 (2018).

    CAS  Google Scholar 

  4. Claeys, M. et al. Formation of secondary organic aerosols through photooxidation of isoprene. Science 303, 1173–1176 (2004).

    CAS  Google Scholar 

  5. Hu, Q.-H. et al. Secondary organic aerosols over oceans via oxidation of isoprene and monoterpenes from Arctic to Antarctic. Sci. Rep. 3, 2280 (2013).

    CAS  Google Scholar 

  6. Carslaw, K. et al. Large contribution of natural aerosols to uncertainty in indirect forcing. Nature 503, 67–71 (2013).

    CAS  Google Scholar 

  7. Pacifico, F., Harrison, S., Jones, C. & Sitch, S. Isoprene emissions and climate. Atmos. Environ. 43, 6121–6135 (2009).

    CAS  Google Scholar 

  8. Bonsang, B., Polle, C. & Lambert, G. Evidence for marine production of isoprene. Geophys. Res. Lett. 19, 1129–1132 (1992).

    CAS  Google Scholar 

  9. Broadgate, W. G., Malin, G., Kupper, F. C., Thompson, A. & Liss, P. S. Isoprene and other non-methane hydrocarbons from seaweeds: a source of reactive hydrocarbons to the atmosphere. Mar. Chem. 88, 61–73 (2004).

    CAS  Google Scholar 

  10. Loreto, F. & Schnitzler, J.–P. Abiotic stresses and induced BVOCs. Trends Plant Sci. 15, 154–166 (2010).

    CAS  Google Scholar 

  11. McGenity, T. J., Crombie, A. T. & Murrell, J. C. Microbial cycling of isoprene, the most abundantly produced biological volatile organic compound on Earth. The ISME J. 12, 931–941 (2018).

    CAS  Google Scholar 

  12. Dani, K. G. S. & Loreto, F. Trade-off between dimethyl sulfide and isoprene emissions from marine phytoplankton. Trends Plant Sci. 22, 361–372 (2017).

    CAS  Google Scholar 

  13. Ooki, A., Nomura, D., Nishino, S., Kikuchi, T. & Yokouchi, Y. A global scale map of isoprene and volatile organic iodine in surface seawater of the Arctic, Northwest Pacific, Indian, and Southern Oceans. J. Geophys. Res. 120, 4108–4128 (2015).

    CAS  Google Scholar 

  14. Hackenberg, S. C. et al. Potential controls of isoprene in the surface ocean. Global Biogeochem. Cycles 31, 644–662 (2017).

    CAS  Google Scholar 

  15. Ciuraru, R. et al. Unravelling new processes at interfaces: photochemical isoprene production at the sea surface. Environ. Sci. Technol. 49, 13199–13205 (2015).

    CAS  Google Scholar 

  16. Brüggemann, M., Hayeck, N. & George, C. Interfacial photochemistry at the ocean surface is a global source of organic vapors and aerosols. Nat. Comm. 9, 2101 (2018).

    Google Scholar 

  17. Conte, L., Szopa, S., Aumont, O., Gros, V. & Bopp, L. Sources and sinks of isoprene in the global open ocean: simulated patterns and emissions to the atmosphere. J. Geophys. Res. 125, e2019JC015946 (2020).

    CAS  Google Scholar 

  18. Palmer, P. I. & Shaw, S. L. Quantifying global marine isoprene fluxes using MODIS chlorophyll observations. Geophys. Res. Lett. 32, L09805 (2005).

    Google Scholar 

  19. Huang, D., Zhang, X., Chen, Z. M., Zhao, Y. & Shen, X. L. The kinetics and mechanism of an aqueous phase isoprene reaction with hydroxyl radical. Atmos. Chem. Phys. 11, 7399–7415 (2011).

    CAS  Google Scholar 

  20. Acuña Alvarez, L., Exton, D. A., Suggett, D. J., Timmis, K. N. & McGenity, T. J. Characterization of marine isoprene-degrading communities. Environ. Microbiol. 11, 3280–3291 (2009).

    Google Scholar 

  21. Johnston, A. et al. Identification and characterisation of isoprene-degrading bacteria in an estuarine environment. Environ. Microbiol. 19, 3526–3537 (2017).

    CAS  Google Scholar 

  22. Moore, R. M. & Wang, L. The influence of iron fertilization on the fluxes of methyl halides and isoprene from ocean to atmosphere in the SERIES experiment. Deep Sea Res. Part II 53, 2398–2409 (2006).

    Google Scholar 

  23. Booge, D. et al. Marine isoprene production and consumption in the mixed layer of the surface ocean – a field study over two oceanic regions. Biogeosciences 15, 649–667 (2018).

    CAS  Google Scholar 

  24. Moore, E. R., Weaver, A. J., Davis, E. W., Giovannoni, S. J. & Halsey, K. H. Metabolism of key atmospheric volatile organic compounds by the marine heterotrophic bacterium Pelagibacter HTCC1062 (SAR11). Environ. Microbiol. (2021).

  25. Bonsang, B. et al. Isoprene emission from phytoplankton monocultures: the relationship with chlorophyll-a, cell volume and carbon content. Environ. Chem. 7, 554–563 (2010).

    CAS  Google Scholar 

  26. Claeys, M. et al. Formation of secondary organic aerosols from isoprene and its gas-phase oxidation products through reaction with hydrogen peroxide. Atmos. Environ. 38, 4093–4098 (2004).

    CAS  Google Scholar 

  27. Lin, C. Y. & Manley, S. L. Bromoform production from seawater treated with bromoperoxidase. Limnol. Oceanogr. 57, 1857–1866 (2012).

    CAS  Google Scholar 

  28. Vitler, H. Peroxidases from phaeophyceae. IV. Fractionation and localization of peroxidase isoenzymes. Botanica Marina 26, 451–455 (1983).

    Google Scholar 

  29. Müller, E., von Gunten, U., Bouchet, S., Droz, B. & Winkel, L. H. E. Reaction of DMS and HOBr as a sink for marine DMS and an inhibitor of bromoform formation. Environ. Sci. Technol. 55, 5547–5558 (2021).

    Google Scholar 

  30. Zinser, E. R. The microbial contribution to reactive oxygen species dynamics in marine ecosystems. Environ. Microbiol. Rep. 10, 412–427 (2018).

    CAS  Google Scholar 

  31. Milne, A., Davey, M. S., Worsfold, P. J., Achterberg, E. P. & Taylor, A. R. Real-time detection of reactive oxygen species generation by marine phytoplankton using flow injection-chemiluminescence. Limnol. Oceanogr. Methods 7, 706–715 (2005).

    Google Scholar 

  32. Rusak, S. A., Peake, B. M., Richard, L. E., Nodder, S. D. & Cooper, W. J. Distributions of hydrogen peroxide and superoxide in seawater east of New Zealand. Mar. Chem. 127, 155–169 (2011).

    CAS  Google Scholar 

  33. Ooki, A. et al. Isoprene production in seawater of Funka Bay, Hokkaido, Japan. J. Oceanogr. (2019).

  34. Dawson, R. A. et al. The microbiology of isoprene cycling in aquatic ecosystems. Aquat. Microb. Ecol. 87, 79–98 (2021).

    Google Scholar 

  35. Moore, E. R., Davie-Martin, C. L., Giovannoni, S. J. & Halsey, K. H. Pelagibacter metabolism of diatom-derived volatile organic compounds imposes an energetic tax on photosynthetic carbon fixation. Environ. Microbiol. 22, 1720–1733 (2020).

    CAS  Google Scholar 

  36. Gasol, J. M. & Duarte, C. M. Comparative analyses in aquatic microbial ecology: how far do they go? FEMS Microbiol. Ecol. 31, 99–106 (2000).

    CAS  Google Scholar 

  37. Sinha, V. et al. Air-sea fluxes of methanol, acetone, acetaldehyde, isoprene and DMS from a Norwegian fjord following a phytoplankton bloom in a mesocosm experiment. Atmos. Chem. Phys. 7, 739–755 (2007).

    CAS  Google Scholar 

  38. Johnson, T. L., Palenik, B. & Brahamsh, B. Characterization of a functional vanadium-dependent bromoperoxidase in the marine cyanobacterium Synechococcus sp. cc93111. J. Phycol. 47, 792–801 (2011).

    CAS  Google Scholar 

  39. Zamanillo, M. et al. Distribution of transparent exopolymer particles (TEP) in distinct regions of the Southern Ocean. Sci. Total Environ. 691, 736–748 (2019).

    CAS  Google Scholar 

  40. Zamanillo, M. et al. Main drivers of transparent exopolymer particle distribution across the surface Atlantic Ocean. Biogeosciences 16, 733–749 (2019).

    CAS  Google Scholar 

  41. Booge, D. et al. Can simple models predict large-scale surface ocean isoprene concentrations? Atmos. Chem. Phys. 16, 11807–11821 (2016).

    CAS  Google Scholar 

  42. Morel, A. et al. Examining the consistency of products derived from various ocean color sensors in open ocean (Case 1) waters in the perspective of a multi-sensor approach. Rem. Sens. Environ. 111, 69–88 (2007).

    Google Scholar 

  43. Galí, M., Devred, E., Levasseur, M., Royer, S. J. & Babin, M. A remote sensing algorithm for planktonic dimethylsulfoniopropionate (DMSP) and an analysis of global patterns. Rem. Sens. Environ. 171, 171–184 (2015).

    Google Scholar 

  44. Davie-Martin, C. L., Giovannoni, S. J., Behrenfeld, M. J., Penta, W. B. & Halsey, K. H. Seasonal and spatial variability in the biogenic production and consumption of volatile organic compounds (VOCs) by marine plankton in the North Atlantic Ocean. Front. Mar. Sci. 7, 611870 (2020).

    Google Scholar 

  45. Meskhidze, N., Sabolis, A., Reed, R. & Kamykowski, D. Quantifying environmental stress-induced emissions of algal isoprene and monoterpenes using laboratory measurements. Biogeosciences 12, 637–651 (2015).

    Google Scholar 

  46. Fall, R. & Copley, S. D. Bacterial sources and sinks of isoprene, a reactive atmospheric hydrocarbon. Environ. Microbiol. 2, 123–130 (2000).

    CAS  Google Scholar 

  47. Shaw, S. L., Chisholm, S. W. & Prinn, R. G. Isoprene production by Prochlorococcus, a marine cyanobacterium, and other phytoplankton. Mar. Chem. 80, 227–245 (2003).

    CAS  Google Scholar 

  48. Gantt, B., Meskhidze, N. & Kamykowski, D. A new physically-based quantification of isoprene and primary organic aerosol emissions from the world’s oceans. Atmos. Chem. Phys. 9, 4915–4927 (2009).

    CAS  Google Scholar 

  49. Exton, D. A., Suggett, D. J., McGenity, T. J. & Steinke, M. Chlorophyll-normalized isoprene production in laboratory cultures of marine microalgae and implications for global models. Limnol. Oceanogr. 58, 1301–1311 (2013).

    Google Scholar 

  50. Shaw, S. L., Gantt, B. & Meskhidze, N. Production and emissions of marine isoprene and monoterpenes: a review. Adv. Meteorol. 2010, 408696 (2010).

    Google Scholar 

  51. Rodríguez-Ros, P. et al. Distribution and drivers of marine isoprene concentration across the Southern Ocean. Atmosphere 11, 556 (2020).

    Google Scholar 

  52. Gasol, J. M. et al. Seasonal patterns in phytoplankton photosynthetic parameters and primary production at a coastal NW Mediterranean site. Sci. Mar. 80S1, 63–77 (2016).

    Google Scholar 

  53. Benavides, M. et al. Basin-wide N2 fixation in the deep waters of the Mediterranean Sea. Global Biogeochem. Cycles 30, 952–961 (2016).

    CAS  Google Scholar 

  54. Royer, S.-J. et al. A high-resolution time-depth view of dimethylsulfide cycling in the surface sea. Sci. Rep. 6, 32325 (2016).

    CAS  Google Scholar 

  55. Sander, R. Compilation of Henry’s law constants (version 4.0) for water as solvent. Atmos. Chem. Phys. 15, 4399–4981 (2015).

    CAS  Google Scholar 

  56. Toole, D. A., Slezak, D., Kiene, R. P., Kieber, D. J. & Siegel, D. A. Effects of solar radiation on dimethylsulfide cycling in the western Atlantic Ocean. Deep Sea Res. Part I 53, 136–153 (2006).

    CAS  Google Scholar 

  57. Tokarczyk, R., Goodwin, K. D. & Saltzman, E. S. Methyl chloride and methyl bromide degradation in the Southern Ocean. Geophys. Res. Lett. 30, 1808 (2003).

    Google Scholar 

  58. Wanninkhof, R. Relationship between wind speed and gas exchange over the ocean revisited. Limnol. Oceanogr. Methods 12, 351–362 (2014).

    Google Scholar 

  59. Holte, J., Talley, L. D., Gilson, J. & Roemmich, D. An Argo mixed layer climatology and database. Geophys. Res. Lett. 44, 5618–5626 (2017).

    Google Scholar 

  60. Yang, M. et al. Lagrangian evolution of DMS during the Southern Ocean gas exchange experiment: the effects of vertical mixing and biological community shift. J. Geophys. Res. 118, 6774–6790 (2013).

    Google Scholar 

  61. Cisewskia, B., Strassa, V. H. & Prandke, H. Upper-ocean vertical mixing in the Antarctic Polar Front Zone. Deep Sea Res. II 52, 1087–1108 (2005).

    Google Scholar 

  62. Law, C. S., Abraham, E. R., Watson, A. J. & Liddicoat, M. I. Vertical eddy diffusion and nutrient supply to the surface mixed layer of the Antarctic circumpolar current. J. Geophys. Res. 108, 3272 (2003).

    Google Scholar 

  63. Gasol, J. M. & del Giorgio, P. A. Using flow cytometry for counting natural planktonic bacteria and understanding the structure of planktonic bacterial communities. Sci. Mar. 64, 197–224 (2000).

    Google Scholar 

Download references


We are thankful to colleagues who provided chlorophyll and bacterial data: J.M. Gasol and J. Arístegui (HOTMIX), S. Nunes, M. Estrada and M.M. Sala (PEGASO and TransPEGASO), and C. Marrasé and M. Cabrera (Mo’orea). We are grateful to the crews and technicians on board the R/Vs Sarmiento de Gamboa and Hesperides, and to the managers and staff of the Gump Station in Mo’orea (administered by UC Berkeley). This research was supported by the Spanish national funding plan for science through projects PEGASO (CTM2012-37615) and BIOGAPS (CTM2016-81008-R) to RS, and through the 'Severo Ochoa Centre of Excellence' accreditation (CEX2019-000928-S) to the ICM-CSIC. PC-G and MM-N were supported by FPI Ph.D. fellowships from the Spanish national funding plan for science, while PR-R was supported by a 'La Caixa' Foundation Ph.D. fellowship. RS is a holder of a European Research Council Advanced Grant (ERC-2018-ADG-834162) under the EU’s Horizon H2020 research and innovation programme.

Author information

Authors and Affiliations



RS designed the work, ran some of the experiments and measurements, processed data, made figures and wrote the paper with contributions from co-authors. PC ran most of the open-ocean experiments and isoprene measurements. PR-R processed data and made some of the figures. MM-N ran the consumption kinetics and oxidation experiments with coastal waters and one of the open-ocean experiments and processed data.

Corresponding author

Correspondence to Rafel Simó.

Ethics declarations

Competing interests

The authors declare no competing interests.

Peer review

Peer review information

Communications Earth & Environment thanks Atsushi Ooki and the other, anonymous, reviewers for their contribution to the peer review of this work. Primary Handling Editors: Clare Davis. Peer reviewer reports are available.

Additional information

Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary information

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Simó, R., Cortés-Greus, P., Rodríguez-Ros, P. et al. Substantial loss of isoprene in the surface ocean due to chemical and biological consumption. Commun Earth Environ 3, 20 (2022).

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI:


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.


Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing