Unveiling ongoing biogeochemical dynamics of CDOM from surface to deep ocean

Domain: earth_science
Published: 2025-06-04
Editorial outcome: major_revision

Abstract
Understanding the dynamics of marine dissolved organic carbon (DOC) is essential for predicting its role in carbon cycling and its response to climate change. Here, we unveil molecular transformations of marine chromophoric dissolved organic matter (CDOM) across the global ocean using Ultraviolet-visible spectroscopy. Significant variability in CDOM composition within the epi- and mesopelagic layers (<1000 m) correlates with physicochemical parameters, driven by irradiation, primary production, biological activity, transport, and riverine inputs. In the bathypelagic layer (1000–5000 m), up to 18.2% of highly conjugated molecules transform into low-molecular-weight CDOM, despite stable DOC concentrations. This dynamic process sustains biomass production and respiration in deep ocean, contributing a carbon flux of 3–24 Pg C yr−1—up to an order of magnitude more than the fast-sinking particulate organic carbon flux. Our findings offer insights into the molecular transformation of deep-ocean DOM and underscore the need to reassess the bathypelagic DOC pool’s role in the global carbon cycle.

Introduction
The world’s oceans fix ~53 Pg C yr−1 of atmospheric CO2 through photosynthesis in the sunlit layer1. A significant portion of this carbon is rapidly respired by marine microheterotrophs or oxidized via photochemical processes, recycling back to CO2 within the upper ocean. Only a small fraction (~1.5 Pg C yr−1) escapes mineralization and is transported into the bathypelagic layer (>1000 m)2,3. In view of dissolved organic carbon (DOC) account for more than 90% organic carbon4, extensive research has focused on the DOC cycle within the epipelagic and mesopelagic layers to unveil its contributions to the marine carbon cycle. DOC in the bathypelagic layer has often been presumed to be refractory and enough to be transported by ocean currents over thousands of years, inferred from apparent homogeneity and uniform DOC concentrations5. Consequently, the DOC cycle within the bathypelagic layer remains largely unaccounted for in current oceanic carbon cycling models3,6,7.

Despite the significant attenuation of particulate organic carbon (POC), which is produced in the euphotic layer and progressively remineralized as it sinks through the epipelagic and mesopelagic layers, leading to minimal POC availability in the deep ocean, high and relatively uniform bacterial and archaeal abundances have been observed throughout water columns in pelagic ecosystems, including the deep ocean. This raises the mystery of what fuels the abundant biomass production and respiration of bacteria and archaea in the deep ocean3,7–9. Earlier studies hinted at the potential for an overlooked DOC cycle in the deep ocean because the deep-ocean DOC pool contains significant amounts of bomb radiocarbon (14C) produced by nuclear weapons testing, equal to dissolved inorganic carbon levels. These high radiocarbon levels imply a turnover of only a few years or less for much of this surface-accumulated material, indicating that deep ocean DOC is a mixture of chemically distinct forms of carbon with varying radiocarbon ages (semi-labile and refractory fractions)5,10,11. Given that the bathypelagic layer holds around 72% of marine DOC, amounting to as much as 477 Pg C5, any evidence of DOC dynamics in this layer is crucial for reassessing the global carbon cycle and predicting the ocean’s response to increasing atmospheric CO2 and climate change.

Since most fractions of DOC are chromophoric (colored dissolved organic matter, CDOM), ultraviolet-visible (UV-Vis) absorption spectroscopy provides a sensitive and cost-effective method for analyzing the molecular characteristics of CDOM, and can also act as a proxy for certain DOC properties12,13. However, marine CDOM spectra generally feature an early exponential decline in absorbance from ultraviolet to visible wavelengths, reflecting its nature as a complex mixture of organic molecules. Despite extensive use, UV-Vis spectral analyses have not fully elucidated the specific mechanisms of optical signals and intrinsic properties of CDOM due to limitations in defining exact molecular structures, with relationships between spectral parameters and CDOM properties largely empirical and region-specific14–20.

In order to gain insight into and quantify the molecular information conveyed by CDOM spectra, we developed a comprehensive spectral parameter profile across the Pacific, Indian, and Atlantic Oceans. This approach provides a detailed view of the vertical and spatial distribution patterns of marine CDOM from the surface to the deep ocean. Our findings offer perspectives on the gradients in CDOM driven by distinct water mass origins, chemical properties, and variability in organic matter composition. These gradients in CDOM breakdown are not merely chemical phenomena—they would profoundly impact the biological realm and biogeochemical dynamics, including the cycling of carbon, nitrogen, sulfur, and other elements in the dark ocean. Based on these insights, we propose the stepped microbe-DOM loop (SMDL) model to predict CDOM turnover time and flux in the deep ocean. This understanding is crucial for accurately assessing the ocean’s role in the global biogeochemical cycle, particularly regarding carbon storage, cycling, and broader implications for climate change.

Results
Parametrization of CDOM spectra in oceans
Marine CDOM UV-Vis spectra are typically characterized by three Gaussian bands (A, A2, and A3) located approximately at 203, 258, and 327 nm, respectively13,21, along with two additional bands (B1 and B2) at around 305 and 410 nm, which are specific to deep-ocean and terrestrial CDOM, respectively (see Methods). To provide a comprehensive spectral profile for CDOM, six UV-Vis spectral parameters—ag(275), ag(380), B’1, B’2, S275-295, and S380-443—were introduced. The vertical distribution patterns of these parameters in the central Pacific Ocean (150°W) are shown in Fig. 1.

ag(275) reflects the intensity of Band A2, primarily associated with aromatic compounds (AC) such as benzene derivatives and heterocyclic structures (e.g., pyrroles and pyridines), as well as compounds with more extended conjugated structures21. ag(275) values are higher at high latitudes (>40°N) and lower in the Southern Hemisphere mesopelagic zone (20°S–60°S) and subtropical surface waters22.
ag(380) represents the intensity of Band A3, linked to aromatic compounds with a styrene-like core (ACSC) characterized by C=C bonds conjugated to benzene rings, such as caffeic acid, rosmarinic acid, and more extended aromatic structures like naphthalene21. ag(380) values peak in the meso- and bathypelagic layers of the Southern Hemisphere and are lower in the epipelagic and subtropical mesopelagic zones.
S275-295 and S380-443 represent the spectral slopes that capture the root mean square (RMS) width of Bands A2 and A3, respectively, indicating heterogeneity within these bands21. S275-295 is steeper in the sunlit surface waters of subtropical Southern Hemisphere regions22, whereas S380-443 remains relatively uniform, except in the upper Northern Hemisphere layers.
B’1 reflects the intensity of Band B1, associated with CHO compounds rich in C=C, C=O, and COO− functional groups, typically formed through DOM oxidation and ring opening in deep-ocean environments23–26. B’1 values rise sharply near the lower mesopelagic boundary, with high values in the meso- and bathypelagic layers, especially in the Northern Hemisphere. B’2 corresponds to molecules represented by Band B2, which exhibit more extensive conjugated structures than ACSC, resulting in a lower energy gap between the molecular orbitals involved in electron transitions, leading to red-shifted absorption27. B’2 values are higher in the upper Northern Hemisphere layers.

The vertical distribution patterns of these spectral parameters in the eastern Indian Ocean (Fig. S2) and central Atlantic Ocean (Fig. S3) generally resemble those in the Pacific. However, the Atlantic shows greater heterogeneity. These distributions reveal distinct depth-related DOM characteristics across ocean basins, providing insights into the molecular composition, transformation, and age of DOM within the water column.

Global pattern of CDOM dynamics
The distributions of spectral parameters strongly correlate with physicochemical parameters on a global scale (Figs. S1–S3). In the central Pacific and eastern Indian Oceans, eight distinct spectroscopic provinces (SPs) can be identified, while ten SPs are found in the central Atlantic Ocean (see Methods). These SPs align closely with classical biogeochemical provinces (BPs) in the Pacific and Indian Oceans but exhibit more divergence in the Atlantic (Fig. 2).

In the central Pacific Ocean, the epipelagic zone (<200 m) is primarily composed of SP2, SP5, and SP7. These regions generally exhibit low nutrient levels of N, P, and others, which limits biological activity and production, as indicated by low B’1 values (Fig. 1). SP5 and SP7, located in tropical and subtropical areas, experience year-round solar radiation, and photobleaching converts ACSC-like into AC-like compounds characterized by higher S275–295 values and lower ag(380) values22. Both SP7 and BP7 exhibit characteristics of an ocean desert, primarily due to the nutrient-poor conditions of the Pacific Subtropical Gyre. High B’2 values in the Northern Hemisphere are due to terrestrial CDOM input. In the epipelagic layer, substantial variability in molecular composition and DOC (Fig. S4) is primarily driven by light exposure, primary production, lateral transport, and riverine inputs.

The mesopelagic zone (200–1000 m) in the Pacific Ocean mainly comprises three SPs: SP3, SP4, and SP6. These regions receive limited solar radiation, slowing the conversion from ACSC-like to AC-like compounds, and reducing S275-295 values (Fig. 1 and Fig. S1). High concentrations of inorganic nutrients (e.g., N and P) in this zone promote microbial activity and enhance DOC mineralization and CDOM transformation (Fig. S4), increasing in B’1 values (Fig. 1)28,29. SP3, located near Antarctica, is influenced by Subantarctic Mode Water (SAMW) and Antarctic Intermediate Water (AAIW), with low ag(275) and ag(380) values and high S275–295 values (Fig. 1). SP4, spanning latitudes from 0° to 50°N, exhibits a crescent-shaped distribution and aligns geographically with BP4. Here, strong biological activity leads to oxygen depletion and high values of B’1, ag(275), and ag(380), indicating the fragmentation of marine snow and the production of high-aromatic-content CDOM. SP6 acts as a transitional zone between SP2 and SP4, with intermediate values across all spectral parameters.

DOC concentration in the mesopelagic zone follow the Martin Curve with varying attenuation coefficients (k) (Fig. S5a)30. The molecular dynamics of CDOM in this zone are largely influenced by DOC attenuation and associated microbial activity. B’1 correlates positively with k, whereas S275-295 correlates negatively (Fig. S5b). Higher B’1 values indicate regions with more intense microbial activity, as supported by a strong linear relationship between B’1 and apparent oxygen utilization (AOU) across the three oceans (Fig. S6). Lower S275-295 values in these regions suggest a greater in situ production of AC-like compounds by microbial activity.

The bathypelagic zone (>1000 m) comprises two SPs: SP1 and SP8. Both are influenced by the lower circumpolar deep water (LCDW) from Antarctica, resulting in similar physicochemical properties across these regions (Fig. 1 and Fig. S1). The bathypelagic layer holds a high concentration of nutrients, which promotes microbial activity, particularly in the upper layers (1000–3000 m), where B’1 values peak. Influx from SP4, driven by a salinity gradient, contributes to elevated ag(275) and ag(380) values in SP8. Overall, ag(275), ag(380), and B’1 values are slightly higher in the Northern Hemisphere than in the Southern Hemisphere, leading to the division of the deep ocean into two SPs. While physicochemical parameters in the bathypelagic zone show little regional variability, the SPs still reveal important distinctions.

In the Indian Ocean, the CDOM dynamics are similar to those in the Pacific, with the epipelagic layer dominated by SP6, SP7, and SP8. SP6, near the Asian continental shelf, shows high ag(275) and ag(380) values due to terrestrial input (Fig. S2). SP7 and SP8, located at tropical and subtropical regions, received intense sunlight, resulting in higher S275-295 and lower ag(380). SP8, positioned in the subtropical gyre, experienced low nutrient concentrations, which limit biological activity, leading to lower S380–443. In the mesopelagic layer, both SP4 and SP5 were influenced by SAMW and AAIW from the Southern Ocean, resulting in lower ag(275) and ag(380) values. But SP5 exhibits higher nutrient concentrations, leading to higher B’1 values. In the bathypelagic zone, SP1, SP2, and SP3 all showed lower values of S275-295 and higher B’1 values. SP1 is also characterized by high ag(275) and ag(380) values due to the input from SP5.

The dynamics of CDOM in the central Atlantic Ocean share similarities with those in the Pacific and Indian Oceans. In the upper ocean, sunlight irradiation leads to higher values of S275-295 and lower values of ag(275) and ag(380) (Fig. S3). In the deep ocean, higher nutrient concentrations result in higher B’1 values. The presence of the Atlantic Meridional Overturning Circulation (AMOC) promotes efficient vertical mixing, leading to fragmented and overlapping distributions of SPs.

CDOM dynamics in the bathypelagic layer
In the bathypelagic layer, spectral parameters only show subtle variations on a global scale (Figs. 1, S2, and S3), which is consistent with the apparent homogeneity suggested by relatively uniform DOC concentrations. However, closer examination reveals that CDOM in these ancient waters is still subject to ongoing biochemical processes (Fig. S7). In the Pacific and Indian Oceans, there is minimal change in DOC (<1.3%), typically with gradients less than 0.4% per kilometer from 1000 to 5000 m. However, significant and consistent changes in ag(380)/DOC are observed at rates of 18.2 and 13.1%, respectively, with average gradients of ~3.9 and ~2.0% per kilometer from 1000 to 5000 m; except for two key regions: the bottom of the mesopelagic layer in the Southern Hemisphere (20°S–60°S) and near the seafloor (Fig. 3). In the Southern Hemisphere mesopelagic layer, DOC transported by Antarctic currents undergoes microbial degradation resulting in negative gradients of DOC and positive gradients of ag(380)/DOC. At these seafloor level, resuspension and intense biological activity significantly impact both DOC concentration and composition. The uniform gradients of ag(380)/DOC indicate a gradual conversion process from ACSC-like compounds to AC-like and low-molecular-weight (LMW) compounds with depth. This is further supported by the gradients of S380–443 (Fig. S8). The positive values of d(S380–443)/d(depth) below 1000 m reflect a reduction in Band A3 width due to the continuous consumption of ACSC-like compounds. It is noteworthy that the relatively small and inconsistent changes in d(ag(275)/DOC)/d(depth) (Fig. 3) and d(S275–295)/d(depth) (Fig. S8) suggest more complex transformations in A2-related substances, especially in the Indian and Atlantic Oceans. Additionally, the gradient of B’1/DOC shows a clear positive trend in the upper deep ocean (Fig. S8), indicating that nutrient-rich environments support biological activity and the production of B-represented substances. However, these substances degrade rapidly at intermediate depths, with d(B’1/DOC)/d(depth) turning negative at depths greater than 2,000 meters. A rapid decrease in d(B’2/DOC)/d(depth) in upper layers suggest that larger conjugated structures break down quickly in B2-represented substances.

The Atlantic exhibits significantly different trends of DOC and spectral parameter gradients, likely due to the influence of the strong AMOC. The observed gradients in the Pacific and Indian Oceans cannot be explained by density diffusion, which is several orders of magnitude weaker (data not shown).

Deep ocean molecular transformations
We propose that the gradient patterns of spectral parameters and DOC in the deep ocean are primarily governed by the stepped microbe-DOM loop (SMDL), as illustrated in Fig. 4. In the upper deep ocean, bacteria and archaea consume high-molecular-weight (HMW) macromolecules to build biomass and release LMW extracellular substances such as polysaccharides, proteins, lipids, and DNA, resulting in an obvious decrease the intensity of Bands A3 (ag(380)/DOC) and a slight increase/decrease intensity of Bands A2 (ag(275)/DOC), which change consistently with depth (Fig. 3). This transformation extends further, likely leading to even smaller molecules, such as sugars and proteins. Extracellular polymeric substances (EPS) and viral lysis of these microorganisms compensate for some DOC consumption, resulting in little change in overall DOC concentrations, while DOM is in a state of constant molecular flux; meanwhile, suspended and slow-sinking particles (<40 m d−1) form through the aggregation of microbes, detritus, fecal pellets, and other organic particles7,31. As slow-sinking particles transport deeper, they continue to fuel microbial activity7,32,33. During the SMDL, high-energy macromolecules are consumed, producing LMW33,34. This process plays a critical role in shaping deep-ocean DOM distribution and sustaining microbial life across various depths. The balance of nutrient limitation, cell detachment, mortality, and sinking rates maintains the ecological food web in the deep ocean3,7–9.

Historically, deep-ocean DOM was considered recalcitrant, persisting for millennia due to its molecular properties35,36. However, significant amounts of bomb radiocarbon found in the deep-ocean DOC pool suggest that deep-ocean DOC is a mixture of chemically distinct carbon fractions of varying ages5,10,11. Recent studies suggest that DOM recalcitrance is not an intrinsic property of individual molecules, but rather emerges as a bulk property at the ecosystem level35,37,38. The debate surrounding deep-ocean DOM dynamics is complicated by the uniformity of DOC concentrations and the lack of apparent compositional distinction5. This study demonstrates a clear distinction of deep marine DOM at a molecular level. Notably, the vertical gradients of UV-Vis spectral parameters reveal clear trends from HMW to LMW compounds in the deep ocean (Fig. 3).

The breakdown of macromolecules via SMDL is not just a chemical phenomenon—they may profoundly impact the biological realm. One major enigma is the energy source for the huge biomass production and respiration of bacteria and archaea in the deep ocean, where marine snow from the euphotic zone has mostly attenuated in the epi- and mesopelagic layers3,7–9. The stepwise degradation of macromolecules in DOM can provide a steady energy source for microbial communities, supporting a relatively uniform distribution of microbial biomass with depth7,9.

This process aligns with globally consistent relationships observed between biomass across the epi-, meso-, and bathypelagic layers and net primary production (NPP) and consistent vertical gradient of ag(380)/DOC (Fig. 3), underscoring the critical link between surface productivity and deep-ocean energy availability32. For instance, bathypelagic biomass increases significantly, from approximately 200 mg C m−2 d−1 in oligotrophic regions to about 800 mg C m−2 d−1 in mesotrophic regions32.

The structure of DOM molecules—and the associated energy release—affects microbial trophic levels at various depths39,40. Observed shifts in prokaryotic communities and increased archaeal abundance with depth underscore the link between DOM and microbial trophic dynamics7,9,41. Concurrently, rising 15N isotopic signatures in microbes and POC with depth indicate accumulation of nitrogen in DOM cycling41–43.

The mortality and aggregation of microbes in the deep ocean generate significant amounts of slow-sinking and non-sinking particles44,45. Observations indicate that slow-sinking POC concentrations are one or two orders of magnitude higher than those of fast-sinking particles in the mesopelagic layer, with even more non-sinking POC present46,47. This suggests that most slow-sinking particles are produced in situ, rather than from fragmentation of fast-sinking particles7. Data from the Southern Ocean further support this hypothesis, showing that the contribution of slow-sinking POC to total flux increases with depth48. A strong correlation between microbial respiration and suspended POC highlight the essential role of buoyant particles in sustaining metabolic activity in the dark ocean7,49.

According to reported velocities of slow-sinking particles (3–22.2 m d−1)46,47 and spectral parameter gradients (Fig. 3), the turnover time of ag(380)-represented substances ranges from 3 to 30 years (see Methods). Specifically, the turnover times in the Pacific and Indian Oceans are 3–20 and 4–30 years, respectively, and are 14–102 years in the Atlantic Ocean. The turnover time of ag(275)-represented substances spans from 67 to 495 years in the Pacific Ocean. These ages may be overestimated because SMDL can consume and produce simultaneously both HMW and LMW molecules, especially LMW, which complicates accurate turnover calculations for ag(275)-represented substances in the Indian and Atlantic Oceans (Fig. 3).

The SMDL would significantly enhance vertical carbon flux to the deep ocean. According to the downward flux of organic carbon via slow-sinking particles measured in epi- and mesopelagic layers, ranging from 23 to 186 mg C m−2 d-146,47, the SMDL could potentially transport 3–24.5 Pg C yr−1 to the deep ocean, up to an order of magnitude greater than gravitational flux of POC from surface production, estimated at 1.5 Pg C yr−13. This calculation does not account for POC fragmentation or fast-sinking particles generated within the SMDL.

The SMDL’s flux potentially reconciles the gap between the supply of sinking POC and the organic carbon demand in deep-ocean microbial communities3,7,31,50. With microbial respiration in the bathypelagic zone estimated at 1.3–1.6 Pg C yr−1, and upper bounds reaching 18.0–20.4 Pg C yr−1, passive POC sinking alone is insufficient for sustaining bathypelagic microbial populations3,32. Even at its highest flux estimates, POC could only support half of the observed respiration3. Dark ocean chemolithoautotrophy, fueled by reduced compounds like ammonia, sulfide, hydrogen, and iron, supports some biomass8, but its magnitude cannot be of the same order of magnitude as heterotrophic biomass production7,8,51,52. Our findings highlight DOC’s critical role as a substrate source within the SMDL, contributing significantly to the carbon budgets in the deep ocean3,53,54.

Methods
Data sources
Data were collected from the Climate Variability and Predictability (CLIVAR) program along the P16 (2005–2006), I8/I9 (2007), and A16 (2005)–A20/A22 (2003) lines (locations detailed in Fig. S9). DOC records were sourced from the Hansell/Carlson DOC datasets, accessible at [http://yyy.rsmas.miami.edu/groups/biogeochem/Data.html]. UV-Vis spectral data were provided by Norman B. Nelson. Physicochemical parameters, including temperature, salinity, oxygen, nitrate, phosphate, and silicate, were retrieved from the Global Ocean Data Analysis Project (GLODAP) database at [https://glodap.info/]. To align the spectral data with physicochemical parameters, records from CLIVAR lines were matched based on the following criteria: spatial proximity within ±5 km, sampling time within ±1 h, and a relative depth difference not exceeding 5%.

UV-Vis spectra processing methods
The deconvolution of CDOM absorbance spectra (Fig. S10) was performed according to our previous study21 with the Curve Fitting Tool in MATLAB 2016b. Initially, we used only three bands to fit the CDOM spectra. Because the fitting process has multiple solutions, we restricted the maximum amplitude location of Bands A1, A2, and A3 to 6.0-6.3 eV (196.8–206.6 nm), 4.5–4.8 eV (258.3–275.6 nm), and 3.6–3.8 eV (326.3–344.4 nm), respectively. Because the spectral data on CLIVAR lines concern wavelengths >275 nm, in which the relative intensities of Band A1 were typically low (below 20% for most cases), extracting relevant information about Band A1 solely from the spectral data >275 nm was challenging and prone to errors. Therefore, based on statistical analysis, we postulated that the maximum position of Band A1 was at 6.2 eV (200.0 nm), with a root mean square width of 0.75 eV. Additionally, it was assumed that the amplitude of Band A1 was fivefold higher than that of ag(275) due to the well-established observation that ag(200) is typically five times larger than ag(275) in most spectra records. This approximation was then implemented in the further numerical fitting, and in most cases, R2>0.99 is obtained13,21.

For the wavelength ranges 295–330 nm and 400–420 nm, deviations between measured spectra and the three Gaussian-band model (Bands A1–A3) were modeled with two additional Gaussian bands, B1 and B2. The amplitude maxima positions of Band B1 and B2 were set as 4.00–4.10 eV (302.4–310.0 nm) and 2.95–3.10 eV (400.0–420.0 nm), respectively. Absorption coefficients were computed using Eq. (1)

ag(λ) = 2.303 * A(λ) / l (1)

where ag(λ) (m−1) is the Napierian absorption coefficient of CDOM at wavelength λ, A(λ) (dimensionless) is the absorbance at wavelength λ, and l is the path length of the spectrophotometric cell.

The spectral slope Sλ1-λ2 was determined using Eq. (2).

Sλ1-λ2 = (ln ag(λ1) - ln ag(λ2)) / (λ2 - λ1) (2)

UV-Vis absorption spectra of CDOM are fairly well represented by three to five Gaussian distribution bands21 when analyzed against photon energy (eV), computed using by Eq. (3), with resultant spectra modeled by Eq. (4).

E(eV) = 1240 / λ(nm) (3)

A(E) = Σ Aoi * exp [-(E - Eoi)2 / (2 * Wi2)] (4)

where Eoi (eV) is the band center, Aoi is the amplitude, and Wi is the RMS width.

To simplify, the intensity of Band B1 band B2 was computed using Eqs. (5)-(6).

B’1 = ag(305) - ag’(305) (5)

B’2 = ag(410) - ag’(410) (6)

where ag’(305) and ag’(410) represent the absorption coefficients at 305 and 410 nm in the exponentially declining spectra within the ranges 295–330 nm and 380–443 nm, respectively, as determined by Eqs. (7) and (8).

(ln ag’(305) - ln ag(295)) / (305 - 295) = (ln ag(330) - ln ag(295)) / (330 - 295) (7)

(ln ag’(410) - ln ag(380)) / (410 - 380) = (ln ag(443) - ln ag(380)) / (443 - 380) (8)

The DOC–normalized differential spectra (DAS) were computed using Eq. (9).

DAS = (ag(λ)i / DOCi) - (ag(λ)ref / DOCref) (9)

where ag(λ)i represents the absorption of the selected CDOM sample, DOCi denotes the DOC of the selected sample, ag(λ)ref signifies the absorption of the reference sample, and DOCref indicates the DOC of the reference sample.

Identification of spectroscopic and biogeochemical provinces of marine CDOM
Biogeochemical provinces were defined based on physicochemical parameters—temperature, salinity, dissolved oxygen, nitrate, phosphate, and silicate—as described in the literature55. Given the lack of particulate organic carbon flux and spatial variation in the deep sea, this factor was excluded from our analysis.

For classifying UV-Vis-derived spectroscopic provinces of marine CDOM, we organized the spectral parameters (ag(275), ag(380), S275-295, S380-443, B’1, and B’2) as a matrix, with each parameter standardized using Eq. (10).

Xstd = (X - X') / σ (10)

where X' is the average, and σ is the standard deviation.

We divided the normalized data into several clusters using the k-means method56. Relevant calculations were run to retrieve between 2 and 50 clusters using the Euclidean distance approach. The times of repetition were set as 999. The ratio of the intra-class mean distance to inter-class mean distance was computed by Eq. (11).

D = [Σ (k i=1 Σ xij 2Gi d2(xij, ui))] / [Σ (k i=1 Σ j=1 k(k-1) d2(ui, uj))] (11)

where ui represents the central coordinates of class i, and d represents Euclidean distance. The elbow point in the relationship between the D and k functions represent the optimal value of k. All the work was done by MATLAB 2016b using custom scripts.

The computation of the DOC attenuation coefficient
DOC concentrations in the mesopelagic layer decreased vertically following the Martin Curve (Eq. (12)) in each spectroscopic province of the Pacific and Indian Oceans30.

DOCz = DOCz0 * (z / z0)-k (12)

where z is the selected depth, z0 is the referenced depth, DOCz is the DOC at depth z, DOCz0 is the DOC at depth z0, and k is referred as coefficient of attenuation.

The estimation of CDOM turnover time
The distances (h) at which the parameter values (P) of ag(275)/DOC and ag(380)/DOC decrease to zero were estimated using the average P at depth of 1000 m (P1000) and the average gradient of d(P)/d(depth) between 1000 and 5000 m, as described in Eq. (13). The velocity of slow-sinking particles (v) was set to 3–22.2 m d−1, based on values reported in the literature46,47. The turnover time (t) of CDOM was then computed using Eq. (14).

h = P1000 / (d(P) / d(depth)) (13)

t = h / v (14)

Data availability
All data are available within the article, or available from the corresponding authors on request.

Code availability
All code-related methods described in this paper are provided within the article. For access to the code for data processing, please contact the corresponding author.

Peer review rounds
[{"round": 1, "reviewer_comments": {"reviewer_1": "General Review:\nThis research presents several noteworthy findings that contribute to our understanding of the deep ocean carbon cycle.\nSpecifically, the authors demonstrate that approximately 18% of highly conjugated organic matter in the deep ocean is\ntransformed into low-molecular-weight chromophoric dissolved organic matter (CDOM) despite unchanged dissolved\norganic carbon (DOC) concentrations. They proposed the stepped microbe-DOM loop (SMDL) and highlights the active role\nof microbial processes in transforming sinking particulate organic carbon (POC). They calculated DOC turnover time, which\nturned out to be more rapid compared to previous estimation. These contributions could potentially improve the accuracy of\nglobal carbon cycle models.\nThe work is highly relevant to the fields of carbon cycle, oceanography, and\nbiogeochemistry, addressing critical gaps in our understanding of deep ocean carbon\ncycling, particularly the fate of POC and its transformation into DOC. While the study\nintroduces a novel concept - the SMDL, which builds upon existing literature, including\nprevious studies on DOC turnover\ntimes and microbial processes in the deep ocean.\nHowever, the discussion could benefit from a deeper engagement with\nthe results to solidify the conclusions.\nSuggestions for major revision:\n1. Clarify the limitations of using bands <275nm and the potential impact from other chromophores.\nThe methodology is generally appropriate for the study, and the use of absorption spectra to explore DOM transformation is\nwell-founded. However, some clarification is needed. First of all, the fitting method using bands in the absence of measured\nabsorption data (<275nm) is questionable. Moreover, concerning the potential interferences from other chromophores (e.g.,\npigments, iron ions etc.). This detail is crucial for ensuring that the observed effects can be attributed to CDOM without\ninterference from other substances.\n2. Expand the statistical analysis and fitting results in the supplementary material to provide more detailed evidence for the\ndata quality.\nThe study's conclusions are generally well-supported by the data presented. The use of extensive absorption data across\ndifferent oceanic regions provides a comprehensive view of dissolved organic matter (DOM) transformations. However, the\nauthors' reliance on Gaussian decomposition of absorption spectra, which is only partially presented (figure S10) in the\nsupplementary material, raises concerns about the robustness of their conclusions. Providing additional statistical analyses\n(e.g. a summary table of fitting RMSE) to validate the quality of the Gaussian fitting would strengthen the study's claims.\n3. Strengthen the Connection Between the Proposed SMDL Model and Experimental Results.\nThe deep ocean may act as a long-term carbon reservoir, with varying residence times for different types of carbon. The\ndiscussion section \"Deep ocean molecular transformations\" demonstrate that the turnover time of DOC in the deep ocean is\nshorter than previously expected, suggesting that the role of the DOC pool in the deep ocean's carbon cycle requires further\nassessment. However, it relies heavily on literature reviews and lacks a strong connection to the result of this study. The\nauthors should integrate their data more effectively with the SMDL concept and provide clearer links between their findings\nand existing knowledge. Additionally, the use of reported velocities of slow-sinking particles (3–22.2 m d⁻¹) at several\nlocation as a calculation parameter (Line 288) is doubtable, considering the significant variability in particle sinking speeds\ndue to environmental conditions, physical and chemical properties at different location.\n4. Improve Readability with and cross-referencing and consistency in the use of color legends.\nThe figures are generally informative. however, the presentation could be improved by ensuring consistent use of color\nlegends and by providing clearer cross-references to context. For instance, as there are many cross references between\nfigure 3 and figure S8 in the results section of CDOM dynamics, in line 220 d(ag(275)/DOC)/d(depth) is from figure 3, but\nd(S275-295)/d(depth) and from line 222 to 228 describe data from figure S8. Please add more clear referencing and cross-\nreferencing between figures and within the text, particularly between Figure 3 and Figure S8, to improve readability.\nMoreover, please ensure consistency in the use of color legends for the same\nparameters across different sub-figures in figure 3 and figure S8.\nSuggestions for minor revision:\nLine 201: Clarify the basis for \"subtle variations.\" Does this refer to other literature? If so, please add references.\nLine 246-247: Add reference information.\nLine 257: Specify whether \"spatial gradients\" refers to vertical changes. Please be more specific about the term \"spatial.\"\nLines 282-283 and 300-302: These sentences appear to convey the same idea. Please consider revising for clarity and\nconciseness.\nSupplementary Line 55: \"extended fig 5a \" does not exist. Is it fig S5 a?", "reviewer_2": "This manuscript characterizes the spectral properties of CDOM spectra collected across Pacific, Atlantic and Indian Oceans,\nand infers aspects about the molecular composition of the DOM pool across depth in those basins. The transformations that\nDOC undergoes in depth suggest that it is used by microbial communities of the deep ocean to fuel their production, which is\nit a source of additional particulate carbon that can sink and contribute to the immobilization of carbon in the deep ocean.\nMain comment\nThe findings of the manuscript are very valuable and propose a plausible explanation for the secondary production\nhappening in the deep sea without apparently enough organic material coming from the illuminated ocean, which has great\nimplications in the global carbon cycle.\nHowever, I think the authors fail slightly to convey such important message early in the manuscript. In my opinion, the\ndiscussion is much better written than the introduction, and there are few methodological aspects not clearly stated (detailed\nbelow in Specific Comments). I also think, there are few concepts that are not properly used, especially the use of the term\n“primary production” to refer to bacterial production in the deep ocean.\nAnd my main concern is that authors are not making clear how the quantification of CDOM spectral properties, translate\ndirectly into DOM cycling, because the fraction of chromophoric material on the DOM pool is not constant and can be\ntemporally and spatially variable.\nSpecific comments\nABSTRACT. L37 The mention to ¨primary production … in the deep ocean¨ is very confusing and, actually, distracts from the\nkey finding of this work and it is that (previously though) non-biodegradable DOC fuels heterotrophic production in the\ndeep ocean.\nINTRODUCTION\nL58 Again, “primary production … of bacteria and archaea in the deep ocean” sounds contradictory to me. I understand the\nauthors are referring to bacterial production, and therefore mostly heterotrophic, and in any case primary. The same is\nrepeated throughout the manuscript (e.g. L262) mentioning primary production of bacteria which I think it is incorrect\nI don’t know if bomb radiocarbon is a term known by everybody in the field, but it is not by me. The meaning of the sentence\nin L59 is clear, but I think it is necessary a mention to what it is bomb radiocarbon to understand why find it in the deep pool\nindicates shorter than previously though turnover rates.\nL69 Most DOC species have indeed a part that is chromophoric but that does not mean that all DOC is chromophoric. In fact,\nthe authors discuss the implications of their findings for DOC/DOM cycling, but what they are actually measuring is CDOM,\nwhich it is not a constant fraction of the DOM pool.\nL72. It is the wavelength-dependent exponential decay in absorbance a consequence of the variability in molecular\ncomplexity of CDOM molecules? I would say these are two different aspects of the CDOM pool. Even pretty homogeneous\nCDOM pools in terms of molecular composition show the high UV absorption and the exponential decay with wavelength.\nL79 to L88. This is basically the paragraph that states what this paper is going to show, and I don’t think it is clear enough.\nFor instance, the authors mention they are going to decompose the spectra with a three-band method, but later, in methods,\nthey mention two additional bands included in the analysis. There is no information on what is the relationship between the\nbands and the spectroscopic parameters proposed and how these parameters are going to be used to reveal the molecular\ncomposition and the origin of the CDOM is not clear.\nL88. I mentioned this earlier, but here again, how the authors are going to close the gap between measured CDOM spectra\nand interpreted DOM dynamics is not clear.\nRESULTS AND DISCUSSION\nL99. In this paragraph, it seems that the formal analysis/decomposition that the authors do from the CDOM spectra is the\nband analysis, and then what the spectroscopic parameters are or where they came from is unclear. When in fact, to my\nunderstanding, obtaining these six parameters is the proper formal analysis that the authors do to quantify the properties of\nthe CDOM spectra. Additionally, just to be a bit clearer in this section, I would suggest to rename it to “Parametrization of\nCDOM spectra in oceans” (L95).\nL132. In this section, the authors describe the distribution of CDOM types across the ocean, based on their spectral\nproperties, but they jump from CDOM to DOC/DOM indistinctly (e.g. L149, L155, L164).\nL175. It is confusing to me the association the authors make between high concentration of nutrients and microbial activity,\nbecause at the depths the authors are considering this activity should be mostly heterotrophic (apart from some\nchemotrophy). The same idea is used later in L196 to associate higher nutrient concentrations with higher B1‘ values in the\ndeep ocean. And nutrient concentrations mentioned later as a driver for the microbial DOM loop (L246). I would suggest the\nauthors to clarify the connection between nutrient availably and CDOM transformations.\nL200. I like the depth-varying analysis done by the authors to explore the variations in DOC composition with depth even\nwith relatively uniform DOC concentrations. However, and coming back to my main concern regarding measuring\nCDOM/interpreting DOM, these variations of the spectral parameters vs. DOC can be revealing changes in the fraction that\nis chromophoric right? How the authors justify those changes in the molecular composition of the chromophoric fraction are\nextrapolable to the whole DOC pool?\nTypos and format\nL54 The meaning of the sentence is clear, but maybe reformulated will give the reader a better view of the apparent paradox\nthis paper is going to tackle (how can such microbial communities persist in the deep ocean when their primary energy\nsource is largely remineralized before reaching these depths). Suggestion: “Despite the significant attenuation of particulate\norganic carbon (POC), which is produced in the euphotic layer and progressively remineralized as it sinks through the\nepipelagic and mesopelagic layers, leading to minimal POC availability in the deep ocean, high and relatively uniform\nbacterial and archaeal abundances have been observed throughout water columns in pelagic ecosystems, including the\ndeep ocean”.\nL75. “… the specific mechanisms …” of what?\nL79. Maybe “In order to gain insight…”?\nL84. “These parameters are the first time to reveal…” sounds awkward.\nL359. I do not understand this last sentence, maybe an ¨in¨ is missing? (i.e. ¨ This approximation was then implemented in\nthe further numerical fitting¨.)\nFigure 3. Probably a matter of taste, but in my opinion, panel labels that indicate the parameter shown would be useful for\nthe reader, similarly to Fig. 1 and Figures S1, S2 and S3. The same applies to Fig. S8."}, "author_response": "Response: We appreciate your valuable suggestions and have addressed each of them\naccordingly.\n1. Clarify the limitations of using bands <275nm and the potential impact from other\nchromophores.\nResponse: We agree that potential interferences from other chromophores are a key\nconsideration when using UV-Vis absorbance to characterize DOM. It is well\ndocumented that certain ions (e.g., iodide, nitrate, iron) can interfere with UV\nabsorbance at wavelengths <275 nm. Similarly, interference above 450 nm can arise\nfrom particles, algal pigments, and turbidity. To minimize these effects, our analysis\nfocuses on the 275–450 nm range, which has been widely accepted as the most reliable\nregion for CDOM characterization. Although some compounds like mycosporine-like\namino acids (MAAs) may absorb strongly around 320 nm, their contribution is\ngenerally negligible in most cases.\nBecause absorbance <275 nm is strongly affected by ionic interference, most oceanic\nCDOM spectra in dataset (without purification) have no absorbance below 275 nm. In\nour Gaussian band deconvolution, Band A1 was positioned at 6.2 eV (200.0 nm) with\na root mean square width of 0.75 eV, and its amplitude was estimated at five times that\nof a (275), based on established findings that a (200) is typically ~5×a (275).\nThese assumptions are supported by extensive studies of inland waters and purified marine\nDOM, as detailed in our preprint (Research Square, doi:10.21203/rs.3.rs-2357170/v1)\nand our recent publication in Environmental Science & Technology (EST 2025,\ndoi:10.1021/acs.est.5c01019).\nImportantly, we clarify that the Gaussian band deconvolution is used solely for\nillustrative purposes to help explain the spectral parameters. All parameter values used\nin the study were calculated directly from the original spectra—not from the Gaussian\nfits.\n2. Expand the statistical analysis and fitting results in the supplementary material to\nprovide more detailed evidence for the data quality.\nResponse: As noted above, Gaussian band deconvolution is only intended to explain\nspectral parameter meaning. The spectral parameters used in this study were calculated\ndirectly from raw spectra.\nNonetheless, to address concerns about the robustness of the Gaussian fitting, we have\nprovided additional statistical analysis in our EST publication\n(doi:10.1021/acs.est.5c01019). Specifically:\nTo further clarify this point, we have added the following sentence and reference in line\n360:\n\"…and in most cases, R² > 0.99 is obtained 19, 20.\"\n3. Strengthen the Connection Between the Proposed SMDL Model and Experimental\nResults.\nResponse: We appreciate the reviewer’s suggestion. In fact, SMDL model, along with\nturnover time and DOC flux estimations, is grounded in the observed consistency of\nmolecular transformation rates in the deep ocean, which have been discussed in detail\nin lines 256-280. We have added multiple cross-references within the discussion section\nto highlight where and how our experimental data support the mechanisms outlined in\nthe SMDL model (line 230-238; line 266-267; line 288; line 291-295).\nRegarding the use of slow-sinking particle velocities (3–22.2 m d⁻¹), we fully\nacknowledge the reviewer’s concern. These values indeed exhibit considerable\nvariability depending on environmental conditions, particle size and habits, and\nmethodology. However, given the limited availability of such measurements due to the\ntechnical difficulty of collecting them, we carefully selected representative values\nreported in previous studies as reasonable approximations. We greatly appreciate the\nefforts of researchers who have obtained these valuable measurements. Our study\nhighlights the importance of slow-sinking particles in deep ocean carbon cycling. We\nhope our findings encourage further research and more extensive data collection on\nslow-sinking particle velocities in future studies.\n4. Improve Readability with and cross-referencing and consistency in the use of color\nlegends.\nResponse: Thanks for the suggestions. We have added some references to Figure 3 and\nFigure S8 in revised manuscript.\nRegarding the use of consistent color legends, we initially attempted to unify color\nschemes across sub-figures for better visual consistency, but we found that doing so\nsignificantly reduced the ability to distinguish important regional differences among\nthe three ocean basins (Fig. R1). Maintaining distinct color coding for each ocean\nallows for a more accurate interpretation of spatial variability and avoids masking key\npatterns in the data.\nSuggestions for minor revision:\nLine 201: Clarify the basis for \"subtle variations.\" Does this refer to other literature?\nIf so, please add references.\nResponse: The Fig. 1 and Fig. S1 are added here. (line 194)\nLine 246-247: Add reference information.\nResponse: Revised it as suggested. (line 245)\nLine 257: Specify whether \"spatial gradients\" refers to vertical changes. Please be\nmore specific about the term \"spatial.\"\nResponse: It is revised into “vertical”. (line 255)\nLines 282-283 and 300-302: These sentences appear to convey the same idea. Please\nconsider revising for clarity and conciseness.\nResponse: To improve clarity and avoid redundancy, we have revised the sentence in\nlines 300-302 in original manuscript.\n“This calculation does not account for POC fragmentation or fast-sinking particles\ngenerated within the SMDL.” (line 301-302)\nSupplementary Line 55: \"extended fig 5a \" does not exist. Is it fig S5 a?\nResponse: Revised it as suggested.\nReviewer #2 (Remarks to the Author):\nResponse: We appreciate your valuable suggestions and have addressed each of them\naccordingly below.\nSpecific comments\nABSTRACT. L37 The mention to ¨primary production … in the deep ocean¨ is very\nconfusing and, actually, distracts from the key finding of this work and it is that\n(previously though) non-biodegradable DOC fuels heterotrophic production in the\ndeep ocean.\nResponse: As suggested, it is revised into “biomass production”. (line 25)\nINTRODUCTION\nL58 Again, “primary production … of bacteria and archaea in the deep ocean” sounds\ncontradictory to me. I understand the authors are referring to bacterial production,\nand therefore mostly heterotrophic, and in any case primary. The same is repeated\nthroughout the manuscript (e.g. L262) mentioning primary production of bacteria\nwhich I think it is incorrect\nResponse: All revised as above.\nI don’t know if bomb radiocarbon is a term known by everybody in the field, but it is\nnot by me. The meaning of the sentence in L59 is clear, but I think it is necessary a\nmention to what it is bomb radiocarbon to understand why find it in the deep pool\nindicates shorter than previously though turnover rates.\nResponse: As suggested, it is revised into：\n“bomb radiocarbon (¹⁴C) produced by nuclear weapons testing.”(line 52)\nL69 Most DOC species have indeed a part that is chromophoric but that does not mean\nthat all DOC is chromophoric. In fact, the authors discuss the implications of their\nfindings for DOC/DOM cycling, but what they are actually measuring is CDOM, which\nit is not a constant fraction of the DOM pool.\nResponse: We fully agree with the reviewer that CDOM represents only a fraction of\nthe overall DOM pool, and that this fraction is both spatially and temporally variable.\nHowever, despite this variability, CDOM remains a valuable tracer of DOM molecular\ncomposition and transformation history. The DOM pool is a complex and dynamic\nmixture of compounds of varying reactivity and origin. UV-Vis absorption spectra\nprovide not only information on the chromophoric component, but also indirect insights\ninto the relative abundance and processing of non-absorbing DOM, which is closely\nlinked to microbial activity and environmental context.\nTo reflect this nuance more clearly, we revised the sentence in the manuscript (line\n63-64)：\n“Ultraviolet-visible (UV-Vis) absorption spectroscopy provides a sensitive and cost-\neffective method for analyzing the molecular characteristics of CDOM, and can also\nact as a proxy for certain DOC properties.11,12”\nAdditionally, we have cited supporting work (EST 2025, Doi:10.1021/acs.est.5c01019)\nthat demonstrates the use of UV-Vis data to estimate DOC concentrations and evaluate\nDOM transformation states.\nL72. It is the wavelength-dependent exponential decay in absorbance a consequence of\nthe variability in molecular complexity of CDOM molecules? I would say these are two\ndifferent aspects of the CDOM pool. Even pretty homogeneous CDOM pools in terms\nof molecular composition show the high UV absorption and the exponential decay with\nwavelength.\nResponse: We appreciate the reviewer’s insightful observation. Even in relatively\nhomogeneous environmental CDOM pools, the molecular composition remains\nsufficiently complex—comprising a continuum of molecular weights, structures, and\nfunctional groups—to result in broad, featureless absorption spectra.\nThis complexity differs from the behavior of pure organic compounds, which typically\nexhibit distinct absorbance peaks rather than a smooth exponential decay. Therefore,\nwhile exponential decay is a defining characteristic of CDOM in general, it also reflects\nthe underlying ensemble of overlapping absorbance features from many structurally\ndiverse molecules. We have clarified this distinction in the revised manuscript text.\nL79 to L88. This is basically the paragraph that states what this paper is going to show,\nand I don’t think it is clear enough. For instance, the authors mention they are going\nto decompose the spectra with a three-band method, but later, in methods, they mention\ntwo additional bands included in the analysis. There is no information on what is the\nrelationship between the bands and the spectroscopic parameters proposed and how\nthese parameters are going to be used to reveal the molecular composition and the\norigin of the CDOM is not clear.\nResponse: We have rewritten these sentences to highlight the novelty of this study. We\nhave removed methodological details here, as they will be thoroughly introduced in the\nfollowing paragraph.\nL88. I mentioned this earlier, but here again, how the authors are going to close the\ngap between measured CDOM spectra and interpreted DOM dynamics is not clear.\nResponse: Please see our response above.\nRESULTS AND DISCUSSION\nL99. In this paragraph, it seems that the formal analysis/decomposition that the authors\ndo from the CDOM spectra is the band analysis, and then what the spectroscopic\nparameters are or where they came from is unclear. When in fact, to my understanding,\nobtaining these six parameters is the proper formal analysis that the authors do to\nquantify the properties of the CDOM spectra. Additionally, just to be a bit clearer in\nthis section, I would suggest to rename it to “Parametrization of CDOM spectra in\noceans” (L95).\nResponse: It is important to note that Gaussian band deconvolution is introduced in\nFigure S10 solely to illustrate the meaning of spectral parameters. The spectral\nparameter data used in this study are directly calculated from the original spectra,\nindependent of Gaussian band deconvolution.\nIn earlier drafts, we included the Gaussian deconvolution details in the main text.\nHowever, given their complexity and the general readership of Nature Communications,\nwe chose to move this content to the Methods section for clarity. Further\nmethodological detail is available in our preprint (Research Square,\ndoi:10.21203/rs.3.rs-2357170/v1) and recent publication in Environmental Science &\nTechnology (EST 2025, doi:10.1021/acs.est.5c01019).\nAs suggested, we rename this section to “Parametrization of CDOM spectra in\noceans”.(line 86)\nL132. In this section, the authors describe the distribution of CDOM types across the\nocean, based on their spectral properties, but they jump from CDOM to DOC/DOM\nindistinctly (e.g. L149, L155, L164).\nResponse: Please see our response above.\nL175. It is confusing to me the association the authors make between high\nconcentration of nutrients and microbial activity, because at the depths the authors are\nconsidering this activity should be mostly heterotrophic (apart from some\nchemotrophy). The same idea is used later in L196 to associate higher nutrient\nconcentrations with higher B1‘ values in the deep ocean. And nutrient concentrations\nmentioned later as a driver for the microbial DOM loop (L246). I would suggest the\nauthors to clarify the connection between nutrient availably and CDOM\ntransformations.\nResponse: Both carbon (C) and inorganic nutrients—particularly nitrogen (N) and\nphosphorus (P)—are essential for microbial activity. In low-nutrient ocean regions,\nelevated N and P levels can stimulate microbial processes and enhance DOM/CDOM\ntransformations. Conversely, limited availability of these nutrients may reduce\nmicrobial activity, leading to carbon accumulation and increased DOC concentrations,\nas commonly observed in oligotrophic zones or “oceanic deserts.”\nWe have rewritten lines 145-147 to clarify this connection and have added a supporting\nreference (28).\n“High concentrations of inorganic nutrients (e.g., N and P) in this zone promote\nmicrobial activity and enhance DOC mineralization and CDOM transformation (Fig.\nS4), increasing in B1’ values (Fig. 1) 27,28.”\nL200. I like the depth-varying analysis done by the authors to explore the variations in\nDOC composition with depth even with relatively uniform DOC concentrations.\nHowever, and coming back to my main concern regarding measuring\nCDOM/interpreting DOM, these variations of the spectral parameters vs. DOC can be\nrevealing changes in the fraction that is chromophoric right? How the authors justify\nthose changes in the molecular composition of the chromophoric fraction are\nextrapolable to the whole DOC pool?\nResponse: We appreciate the reviewer’s thoughtful question and agree that this is a\ncritical consideration. As response above, although CDOM does not represent the\nentirety of the DOC pool, changes in its spectral parameters can offer meaningful\ninsights into broader DOM transformation dynamics. This is because the production\nand removal of chromophoric and non-chromophoric components are often coupled\nthrough shared microbial pathways. In this context, UV-Vis spectral features—\nincluding intensity, slope, and shape—can act as proxies not only for CDOM\ncomposition, but also for the transformation state of the total DOM pool.\nWe agree this is an area deserving further study. Our analysis is not intended to suggest\na direct one-to-one extrapolation from CDOM to total DOC, but rather to use CDOM\nspectral variability as an accessible and informative lens through which molecular\nchanges in the broader DOM pool may be inferred.\nTypos and format\nL54 The meaning of the sentence is clear, but maybe reformulated will give the reader\na better view of the apparent paradox this paper is going to tackle (how can such\nmicrobial communities persist in the deep ocean when their primary energy source is\nlargely remineralized before reaching these depths). Suggestion: “Despite the\nsignificant attenuation of particulate organic carbon (POC), which is produced in the\neuphotic layer and progressively remineralized as it sinks through the epipelagic and\nmesopelagic layers, leading to minimal POC availability in the deep ocean, high and\nrelatively uniform bacterial and archaeal abundances have been observed throughout\nwater columns in pelagic ecosystems, including the deep ocean”.\nResponse: Revised according to suggestion. (line 44-48)\nL75. “… the specific mechanisms …” of what?\nResponse: … the words “optical signals” was added. (line 68)\nL79. Maybe “In order to gain insight…”?\nResponse: Revised as suggested. (line 71)\nL84. “These parameters are the first time to reveal…” sounds awkward.\nResponse: Revised into:\n“This approach provides, for the first time, a detailed view of the vertical and spatial\ndistribution patterns of marine CDOM from the surface to the deep ocean.…”(line 73-\n75 )\nL359. I do not understand this last sentence, maybe an ¨in¨ is missing? (i.e. ¨ This\napproximation was then implemented in the further numerical fitting¨.)\nResponse: Revised as suggested. (line 359)\nFigure 3. Probably a matter of taste, but in my opinion, panel labels that indicate the\nparameter shown would be useful for the reader, similarly to Fig. 1 and Figures S1, S2\nand S3. The same applies to Fig. S8.\nResponse: We have revised Figures 3 and S8 to include clear panel labels that indicate\nthe parameters shown. Due to space constraints within the figure layout, we placed the\npanel labels above the corresponding sub-figures to maintain readability and visual\nclarity."}, {"round": 2, "reviewer_comments": {"reviewer_1": "Thank you to the authors for your detailed responses and the revisions made to the manuscript. Overall, I find the\nmethodology, data, and conclusions to be sound, and I appreciate the efforts made to address the previous comments.\nHowever, I would like to offer a few minor suggestions for the clarity and completeness of the manuscript. I leave it to the\nauthors’ discretion to address them as they see fit.:\n1. In the revised manuscript, line 37 mentions \"more than 90% organic carbon.\" I recommend that the authors provide a\nreference to support this number.\n2. In Figure 4, please clarify the abbreviations used in the figure caption. For example, \"agg\" and \"disagg\" have not\nappeared previously in the manuscript; term “ESP” have not been previously introduced in the text but may not be\nimmediately clear to all readers.", "reviewer_2": "The authors have addressed my initial concerns and revised the manuscript accordingly. The methodology is now clearer,\nand the implications of the findings are better supported. I would, however, recommend an additional round of proofreading,\nas there are still a few sentences whose meaning is not entirely clear. Other than that, I have no further comments.\nMinor clarification:\nL39-43 After the “while”, it seems a second part of the sentence is missing, am I wrong? Maybe the expected meaning is\nsomething like “DOC in the bathypelagic layer has often been presumed to be refractory and transported by ocean currents\nover thousands of years, inferred from apparent homogeneity and uniform DOC concentrations. Consequently, DOC cycle\nwithin bathypelagic layer remains largely unaccounted for in current oceanic carbon cycling models “."}, "author_response": "Response to Reviewers’ Comments\nThank you for the constructive comments from both you and the reviewers on our ma\nnuscript entitled “Unveiling Ongoing Biogeochemical Dynamics of CDOM from Surf\nace to Deep Ocean” Based on your feedback, we have carefully revised the\nmanuscript to address all concerns.\nREVIEWER COMMENTS:\nReviewer #1 (Remarks to the Author):\nThank you to the authors for your detailed responses and the revisions made to the\nmanuscript. Overall, I find the methodology, data, and conclusions to be sound, and I\nappreciate the efforts made to address the previous comments.\nResponse: Thank you for your valuable suggestion for improving the quality of the\nmanuscript.\nHowever, I would like to offer a few minor suggestions for the clarity and completeness\nof the manuscript. I leave it to the authors’ discretion to address them as they see fit.:\n1. In the revised manuscript, line 37 mentions \"more than 90% organic carbon.\" I\nrecommend that the authors provide a reference to support this number.\nResponse: A literature was added to support this number. Please see Ref. 4 (DeVries,\nT. & Weber, T., Glob. Biogeochem. Cycles, 2017).\n2. In Figure 4, please clarify the abbreviations used in the figure caption. For example,\n\"agg\" and \"disagg\" have not appeared previously in the manuscript; term “ESP” have\nnot been previously introduced in the text but may not be immediately clear to all\nreaders.\nResponse: Revised as suggested, please see Line 622-625:\n“In this figure, POC stands for particulate organic carbon, LMW for low-molecular-\nweight, MMW for medium-molecular-weight, HMW for high-molecular-weight, agg for\naggregation, disagg for disaggregation, and EPS for extracellular polymeric\nsubstances.”\nReviewer #2 (Remarks to the Author):\nThe authors have addressed my initial concerns and revised the manuscript\naccordingly. The methodology is now clearer, and the implications of the findings are\nbetter supported. I would, however, recommend an additional round of proofreading,\nas there are still a few sentences whose meaning is not entirely clear. Other than that,\nI have no further comments.\nResponse: Thank you for your suggestion. We have checked the manuscript again.\nMinor clarification:\nL39-43 After the “while”, it seems a second part of the sentence is missing, am I wrong?\nMaybe the expected meaning is something like “DOC in the bathypelagic layer has\noften been presumed to be refractory and transported by ocean currents over thousands\nof years, inferred from apparent homogeneity and uniform DOC concentrations.\nConsequently, DOC cycle within bathypelagic layer remains largely unaccounted for\nin current oceanic carbon cycling models “.\nResponse: Revised as suggested."}]

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